Seagrass Monitoring Postdredging

Transcription

1 Seagrass Monitoring Postdredging Report Ichthys Nearshore Environmental Monitoring Program L384-AW-REP L384-AW-REP Prepared for INPEX April 2015

2 Document Information Prepared for INPEX Project Name File Reference L384-AW-REP-10081_0_.docm Job Reference L384-AW-REP Date April 2015 Contact Information Cardno (NSW/ACT) Pty Ltd Cardno (WA) Pty Ltd Cardno (NT) Pty Ltd Level 9, The Forum 11 Harvest Terrace Level 6, 93 Mitchell Street 203 Pacific Highway West Perth WA 6005 Darwin NT 0800 St Leonards NSW 2065 Telephone: Telephone: Telephone: Facsimile: Facsimile: Facsimile: International: International: International: Document Control Version Date Author Author Initials Reviewer Reviewer Initials A 27/01/2015 Isabel Jimenez IJ Lachlan Barnes LB B 17/03/2015 Isabel Jimenez IJ Craig Blount CB 0 28/04/2015 Isabel Jimenez IJ Christopher Holloway CGH This document is produced by Cardno solely for the benefit and use by the client in accordance with the terms of the engagement for the performance of the Services. Cardno does not and shall not assume any responsibility or liability whatsoever to any third party arising out of any use or reliance by any third party on the content of this document. Prepared for INPEX Cardno ii

3 Executive Summary A Seagrass Monitoring Program has been developed for the Ichthys Project Nearshore Environmental Monitoring Plan (NEMP) to monitor minimal predicted seagrass impacts in the Darwin Outer region from dredging and spoil disposal activities associated with the Ichthys LNG Project (the Project). Season One East Arm (EA) dredging within Darwin Harbour operated from 27 August 2012 to 30 April Season Two dredging commenced on 23 October 2013 along the Gas Export Pipeline (GEP) route and on 1 November 2013 in EA. Activities for EA and the GEP dredging were completed on 11 June 2014 and 12 July 2014 respectively. Two main impact pathways identified by which the Project s dredging and spoil disposal activities may potentially affect key seagrass habitats in Darwin Outer were through the: suspension of sediments in the water column reducing light availability and causing a reduction in photosynthesis; and smothering and burial of seagrass by sedimentation. The Seagrass Monitoring Program used towed-video mapping techniques to measure changes in distribution and cover of the two dominant genera of seagrass (Halodule and Halophila) within Darwin Outer. In order to improve the understanding of the physical drivers of change in seagrass habitat, the program also involved interpretation of seagrass data in relation to turbidity and benthic light availability that was measured as part of the Water Quality and Subtidal Sedimentation Monitoring Program (WQSSMP). These data were used to develop seagrass growth response models to predict the likelihood of change in seagrass cover at Darwin Outer Survey Areas. These models were in turn used to discriminate natural changes from those that could potentially be a result of Project dredging activities. Towed-video surveys were undertaken at six key seagrass habitats (Survey Areas) in the Darwin Outer region (Fannie Bay, Woods Inlet, Lee Point, Casuarina Beach, East Point and Charles Point West) during the Baseline Phase (B1) in the 2012 dry season, prior to the commencement of dredging and quarterly throughout the Dredging and Post Dredging Phases of the Project. Dredging Phase monitoring comprised a total of seven towed-video seagrass mapping surveys, with two surveys during Season One dredging (D1: October 2012; D2: February 2013), two surveys during the 2013 dry season dredging hiatus (D3: May 2013; D4: August/September 2013) and three surveys during Season Two dredging (D5: November 2013; D6: February 2014; D7: May 2014). Post-dredging Phase monitoring comprised of two towed-video surveys undertaken between 3 July 2014 and 9 July 2014 (P1) and between 15 October 2014 and 21 October 2014 (P2). This report provides a description of the results from P1 and P2, and interprets changes in seagrass habitat distribution in relation to findings from all previous surveys. The towed-video mapping surveys have shown an overall natural seasonal cycle of decline and recovery of Halodule and Halophila in Darwin Outer that is consistent with what is anticipated for these genera in the wet tropics. The mapping surveys have also shown that there are distinct genus-specific spatial and temporal patterns for Halodule and Halophila in addition to the overarching seasonal cycle. Of the two genera, Halophila has shown the most seasonality, with a general expansion of distribution spatial extent during the dry season and reduction during the wet season. The extent of Halophila in Darwin Outer has ranged from approximately 2,700 ha in D1 (October 2012) during the dry season to complete absence from all Survey Areas during the wet season in D2 (February 2013) and completed Survey Areas in D6 (February 2014). The largest patches of Halophila mapped were on the east side of Darwin Outer off Casuarina Beach and to the east of Lee Point. Although the measured spatial extent of Halodule has varied naturally since the commencement of monitoring, changes in distribution have not been to the same extent as Halophila and have occurred mainly as changes to the size of existing patches rather than a redistribution of new patches (as occurred for Halophila). Patches of Halophila were generally located in slightly deeper water (between -9.5 m and +2 m Lowest Astronomical Tide; LAT) than Halodule (between -1 m and +2 m LAT) and there was generally very little overlap between patches of the two genera. The spatial distribution of Halophila habitat observed during P1 (July 2014) and P2 (October 2014) were consistent with previous observations during the 2012 dry season (surveys B1 in June 2012 and D1 in October 2012) and the 2013 dry season (surveys D3 May 2013 and D4 in August/September 2013). Halophila habitat expanded at most Survey Areas between D7 (May 2014) and P1 (July 2014) and between Prepared for INPEX Cardno iii

4 P1 and P2 (October 2014). Mapping results were generally consistent with outcomes of the seagrass growth response models predicting that increases in cover of Halophila were likely given the dry season conditions of low turbidity (generally below 7 Nephelometric Turbidity Units(NTU)) and high benthic light (ranging between 4 and 11 mol photons/m 2 /day). A decrease in cover was recorded in the Lee Point Survey Area from approximately 1,103 ha during D7 (May 2014) to 277 ha during P1 (July 2014). Risk assessment analyses based on the seagrass response models provided no indication that this reduction in Halophila habitat was due to dredging activities. Other natural contributing factors to this change may include smallscale spatial variability in turbidity, temporal variability in nutrient availability, and natural shifts in sediments. During P1 and P2, Halodule habitat was mapped in the same general areas as in all previous surveys and this was consistent with 2012 and 2013 dry season survey findings. Following a wet season decline in cover between D5 (November 2013) and D7 (May 2014), there was a considerable expansion of Halodule habitat at Casuarina Beach between D7 (May 2014) and P1 (July 2014). The decline was most likely caused by wind and wave action from episodic weather events in late January 2014 to early February During P1 (July 2014) and P2 (October 2014) the distribution and cover of Halodule at Casuarina Beach was similar to that prior to D7 and for similar times of year in 2012 and 2013, indicating a recovery from the natural disturbance over the wet season. This recovery is consistent with the known resilience of Halodule as this genera is commonly found to survive well in unstable environments and to recover rapidly after disturbances. There was no evidence to suggest a delayed impact of dredging activities on the distribution or cover of Halodule habitat during the monitoring period. Final updates to the seagrass response models indicated that seasonal changes to the extent and cover of Halophila between June 2012 (B1) and October 2014 (P2) were explained relatively well by the two selected light-related variables (mean daily turbidity and percentage of low light days over the 28-period). These two variables have consistently been the best descriptors of change in Halophila cover and were included in all seagrass response models since D3 (May 2013). Similarly the seagrass response model indicates that Halodule extent was best explained by the 14-day and 28-day average turbidity values, while depthdependent variables (i.e. benthic light availability) only had a very low explanatory power. However, to date most of the variability in Halodule seagrass response model is not explained by the light and depth related variables currently tested. In summary, during the Post-dredging Phase, results from broad-scale towed-video mapping of seagrass habitats, together with predictions from seagrass response models, indicated no delayed influence of dredging-related excess turbidity at seagrass monitoring sites in Darwin Outer. These Post-dredging Phase results coupled with those from the Dredging Phase meet the objectives of the Seagrass Monitoring Program and indicate that there has been no influence of dredging-related excess turbidity on seagrass growth at monitoring sites to date. Although the extent of seagrass habitat in Darwin Outer has varied extensively over the monitoring program, the changes observed are likely to be a result of natural dynamic seasonal cycles. Prepared for INPEX Cardno iv

5 Glossary Term or Acronym Definition B1 Baseline survey 1 completed 22 May 2012 to 2 July 2012 BACI BHD BOM CSD Before-After-Control-Impact Backhoe Dredging Bureau of Meteorology Cutter Suction Dredging D1 Dredging survey 1 completed 8 October 2012 to 26 October 2012 D2 Dredging survey 2 completed 17 February 2013 to 24 February 2013 D3 Dredging survey 3 completed 15 May 2013 to 21 May 2013 D4 Dredging survey 4 completed 29 August 2013 to 4 September 2013 D5 Dredging survey 5 completed 11 November 2013 to 15 November 2013 D6 Dredging survey 6 completed 22 February 2014 to 26 February 2014 D7 Dredging survey 7 completed 21 May 2014 to 26 May 2014 DSDMP EA EIS GEP GLM IMOS LAT NEMP NRS NTC NTU Dredging and Spoil Disposal Management Plan East Arm Environmental Impact Statement Gas Export Pipeline Generalized Linear Model Integrated Marine Observing System Lowest Astronomical Tide Nearshore Environmental Monitoring Plan National Reference Station BOM National Tidal Centre Nephelometric Turbidity Units P1 Post-dredging survey 1 completed 3 July 2014 to 9 July 2014 P2 Post-dredging survey 2 completed 15 October 2014 to 21 October 2014 PAR Photosynthetically Active Radiation Prepared for INPEX Cardno v

6 Term or Acronym SEIS SP TC TS TSHD WQSSMP Definition Supplement to the draft Environmental Impact Statement Separable Portion Tropical Cyclone large-scale, atmospheric wind-and-pressure system that originates over tropical ocean areas characterized by low pressure at its center and by circular wind motion. Characterized by sustained winds of 63 km/hr or greater. Tropical System - large-scale, atmospheric wind-and-pressure system originates over tropical ocean areas Trailing Suction Hopper Dredger Water Quality and Subtidal Sedimentation Monitoring Program Prepared for INPEX Cardno vi

7 Table of Contents Executive Summary Glossary iii v 1 Introduction Background Requirement to Monitor Seagrass Summary of the Baseline Surveys Drop Camera Surveys Broad-scale Towed-video Mapping Surveys Development of Seagrass Response Models and the Seagrass Decision Support Framework2 1.5 Summary of the Dredging Phase Surveys Objectives 4 2 Methodology Overview Vessels, Safety and Environmental Management Sites, Timing and Frequency of Surveys Towed-video Surveys Physical Environment Metocean Conditions Near-bed Water Temperature, Turbidity and Light Data Analysis Seagrass Spatial Data Underwater Light Climate Seagrass Growth Predictions Potential Dredging-related Influence Final Updates to the Seagrass Response Model Data Management and Quality Control 13 3 Dredging Operations 14 4 Results Seagrass Distribution Changes Spatial Distribution Depth Distribution Percentage Cover Metocean Conditions and Light History Wind and Waves Water Temperature Rainfall and Surface PAR Near-bed Turbidity Underwater Light Climate Seagrass Growth Predictions Survey P1 (July 2014) Survey P2 (October 2014) Potential Dredging-related Influence Underwater Light prior to P1 (July 2014) Potential Influence on Seagrass Growth prior to P1 (July 2014) Seagrass Growth Response 41 Prepared for INPEX Cardno vii

8 4.5.1 Halophila Halodule Updated Growth Response Models 43 5 Discussion Seasonal Patterns and Inter-specific Differences in Growth of Halophila and Halodule Post-dredging Distribution and Cover of Halophila Post-dredging Distribution and Cover of Halodule Development of Predictive Seagrass Growth Models 46 6 Conclusion 48 7 Acknowledgments 49 8 References 50 Tables Table 1-1 Table 2-1 Table 3-1 Table 4-1 Table 4-2 Table 4-3 Table 4-4 Table 4-5 Previous and revised reactive seagrass management triggers (INPEX 2012, 2013, 2014) 5 Summary of towed-video surveys to date and corresponding dredging activities 8 East Arm dredge footprint summary 14 Near-bed daily-average turbidity statistics between 27 May 2014 and 21 October 2014 for Woods Inlet (WOD_1), Charles Point (CHP_02), Fannie Bay (FAN_01), East Point (EAS_01), Casuarina Beach (CAS_01) and Lee Point (LEE_01) 26 Statistics of the daily dose of PAR (mol photons/m 2 /day) at -1 m LAT between 27 May 2014 and 21 October Results of logistic regressions between WQSSMP historical turbidity and light variables and changes (increase or decrease between consecutive surveys) in percentage cover of Halophila between all surveys (May 2012 to October 2014) 41 Results of the logistic regression between WQSSMP historical turbidity and light variables and changes (increase or decrease) in percentage cover of Halodule between all surveys (May 2012 to October 2014) 42 Predictive logistic models for Halodule and Halophila based on all data collected between Baseline (June 2012) and P2 (October 2014) 43 Figures Figure 2-1 Figure 3-2 Figure 4-1 Figure 4-2 Figure 4-3 Figure 4-4 Figure 4-5 Locations of seagrass Sample and Survey Areas 7 EA dredging footprint and GEP route 15 Halodule and Halophila distribution from the Baseline and Dredging Phase towed-video surveys: B1 (June 2012) to D4 (August/September 2013) 18 Halodule and Halophila distribution from Dredging and Post-dredging Phase towed-video surveys: D5 (November 2013) to P2 (October 2014). It should be noted that not all Survey Areas were completed during the D6 (February 2014) survey 19 Depth distributions and percentage cover of Halophila and Halodule at Fannie Bay and Lee Point Survey Areas from survey B1 (June 2012) to P2 (October 2014). The larger x-axis scale should be noted for Lee Point in survey D1 (October 2012) and D3 (May 2013) 21 Depth distributions and percentage cover of Halophila and Halodule at Woods Inlet and Casuarina Beach from survey B1 (June 2012) to P2 (October 2014) 22 Depth distributions and percentage cover of Halophila and Halodule at East Point and Charles Point West Survey Areas from survey B1 (June 2012) to P2 (October 2014). The larger x-axis scale should be noted for East Point in survey D1 (October 2012) 23 Prepared for INPEX Cardno viii

9 Figure 4-6 Figure 4-7 Figure 4-8 Figure 4-9 BOM Darwin Airport wind speed and wind direction between 27 May 2014 and 21 October BOM Darwin Airport wind rose between 27 May 2014 and 21 October IMOS Darwin significant wave height and peak wave period; BOM Fort Hill Wharf recorded tide and residual tide between 27 May 2014 and 21 October Near-bed daily-average water temperature at seagrass monitoring sites between 27 May 2014 and 21 October Shaded grey areas indicate seagrass towed-video surveys P1 (July 2014) and P2 (October 2014), and vertical dotted lines indicate the end of EA dredging (pink) and GEP dredging (green) 25 Figure 4-10 BOM Darwin Airport Daily rainfall; and ARM Darwin Airport PAR between 27 May 2014 and 21 October Figure 4-11 Box and whisker plot of daily-averaged near-bed turbidity at seagrass sites between 27 May 2014 and 21 October Figure 4-12 PAR daily dose between 09:45 and 15:45 at -1 m LAT at Fannie Bay, Lee Point and Woods Inlet from 10 August 2012 to 21 October Figure 4-13 PAR daily dose between 09:45 and 15:45 at -1 m LAT at Charles Point, East Point and Casuarina Beach from 10 August 2012 to 21 October Figure 4-14 Probability of increase in percentage cover of Halodule (based on the 14-day and 28-day mean turbidity, Equation 2 Section 2.6.3) and Halophila (based on the 28-day and 84-day mean turbidity, Equation 4 Section 2.6.3) for each Survey Area preceding the P1 (July 2014) survey 31 Figure 4-15 Probability (±SE) of an increase in the percentage cover predicted for Halophila and Halodule for each Survey Area based on light data over the 28 days preceding the P1 (July 2014) survey32 Figure 4-16 Probability of increase in percentage cover of Halodule (based on the 14-day and 28-day mean turbidity, Equation 2) and Halophila (based on the 28-day and 84-day mean turbidity, Equation 4) for each Survey Area preceding the P2 (October2014) survey. Predictions were not generated for Woods Inlet due to insufficient turbidity data (Appendix D) 33 Figure 4-17 Probability (±SE) of an increase in the percentage cover predicted for Halophila and Halodule for each Survey Area based on light data over the 28 days preceding the P2 (October 2014) survey. Predictions were not generated for Woods Inlet due to insufficient turbidity data (Appendix D) 34 Figure day moving average of Measured and modelled (Estimated Background and Empirical Model) daily PAR dose at Woods Inlet, Fannie Bay, Lee Point, Casuarina Beach, Charles Point and East Point from 27 May 2014 to 8 July 2014 prior to P1 survey 36 Figure 4-19 Probability of increase in percentage cover of Halophila and Halodule predicted based on the 14-day, 28-day and 84-day mean turbidity for the three turbidity scenarios prior to survey P1 (July 2014) 38 Figure 4-20 Probability of increase in percentage cover of Halophila predicted based on the percentage of days receiving less than 1 mol photons/m 2 /day estimated over 28 days from three turbidity scenarios prior to P1 (July 2014) 39 Figure 4-21 Probability of increase in percentage cover of Halodule predicted based on the percentage of days receiving less than 5 mol photons/m 2 /day estimated over 28 days from three turbidity scenarios prior to P1 (July 2014) 40 Appendices Appendix A July 2014 Towed-video Habitat Mapping Technical Report Appendix B October 2014 Towed-video Habitat Mapping Technical Report Appendix C Depth of Towed-video Sample Areas Appendix D Turbidity Time Series Appendix E Historical Conditions of Turbidity prior to P1 (July 2014) Appendix F Historical Conditions of Turbidity prior to P2 (October 2014) Prepared for INPEX Cardno ix

10 1 Introduction 1.1 Background INPEX is the operator of the Ichthys LNG Project (the Project). The Project comprises the development of offshore production facilities at the Ichthys Field in the Browse Basin, some 820 km west-south-west of Darwin, an 889 km long subsea gas export pipeline (GEP) and an onshore processing facility and product loading jetty at Bladin Point on Middle Arm Peninsula in Darwin Harbour. To support the nearshore infrastructure at Bladin Point, dredging works were carried out to extend safe shipping access from near East Arm Wharf to the new product loading facilities at Bladin Point, which is supported by piles driven into the sediment. A trench was also dredged to seat and protect the GEP for the Darwin Harbour portion of its total length. Dredged material was disposed at the spoil ground located approximately 12 km north-west of Lee Point. A detailed description of the dredging and spoil disposal methodology is provided in Section 2 of the East Arm (EA) Dredging and Spoil Disposal Management Plan (DSDMP) (INPEX 2013) and GEP DSDMP (INPEX 2014a). 1.2 Requirement to Monitor Seagrass Following a draft Environmental Impact Statement (EIS) (INPEX 2011a) and Supplement to the draft EIS (SEIS) (INPEX 2011b), the Project was approved subject to conditions that included monitoring for potential effects of dredging or spoil disposal on local ecosystems (including seagrasses) and potentially vulnerable populations. The EIS describes two main impact pathways by which the Project s dredging and spoil disposal activities may affect seagrass: suspended sediment in the water column reducing light availability and causing a reduction in photosynthesis; and smothering and burial of seagrass by sedimentation. A Seagrass Monitoring Program was established for the Ichthys Project Nearshore Environmental Monitoring Plan (NEMP) to monitor minimal seagrass impacts predicted to result from dredging and spoil disposal activities (Cardno 2014a). 1.3 Summary of the Baseline Surveys Drop Camera Surveys High-definition underwater drop camera surveys were initially conducted to detect changes in leaf/shoot density and percentage cover at seagrass monitoring sites. A Before-After-Control-Impact (BACI) experimental design was used to compare changes in percentage cover and density within potential Impact locations (Fannie Bay, Woods Inlet, and Lee Point) with Control locations (East Point, Casuarina Beach and Charles Point) (Figure 2-1) during the monitoring program. The program was designed to detect statistically significant changes that would be compared to management trigger values of 20% and 30% change above natural variability. Baseline surveys conducted between June 2012 and August 2012 revealed that these trigger values were far too conservative when compared to the large natural spatial and temporal variability in distribution and abundance of the two dominant seagrass genera (Halodule and Halophila). During June 2012, mean seagrass percentage cover was low, ranging between 1.9 ± 0.3% and 4.5 ± 0.5% at all locations, and by August 2012 had increased by a factor of two to three at Fannie Bay, Woods Inlet and Charles Point (ranging between 4.8 ± 0.8% and 11.7 ± 1.0%). A tenfold increase was recorded at Lee Point during the same period, reaching 18.6 ± 1.0% in August 2012 (Cardno 2013a). As a consequence of the high natural variability, trigger levels set in the EA DSDMP (Rev. 1; INPEX 2012) did not represent ecologically significant change in such a dynamic system and could not be used to assess the small and localised potential impacts from dredging activities. As a result of these early findings, a new monitoring approach was adopted to track changes in seagrass distribution and health over large spatial scales. The drop camera method was replaced with the more suitable broad-scale towed-video mapping surveys to better assess changes in seagrass distribution over large spatial scales (Section 1.3.2). The BACI design framework was replaced by a predictive model, which has been used to relate changes in seagrass distribution and cover to environmental conditions. Prepared for INPEX Cardno 1

11 1.3.2 Broad-scale Towed-video Mapping Surveys Baseline towed-video surveys were conducted between May 2012 and July 2012 to map the distribution and extent of seagrass habitat over large spatial scales in the Darwin Outer region. Data from towed-video surveys were used to produce seagrass habitat maps along the Cox Peninsula (including Charles Point and Woods Inlet) and the north-eastern foreshore to the east of Lee Point (also including Fannie Bay, East Point and Casuarina Beach). Baseline Phase survey maps (May 2012 to July 2012) showed that seagrass habitats in the Darwin Outer region were dominated by Halophila spp. (including mostly Halophila decipiens) and Halodule spp. (including Halodule uninervis), hereafter collectively referred to as the genera Halophila and Halodule respectively. These habitats occurred on soft sandy sediments at depths between +2.2 m and -0.5 m Lowest Astronomical Tide (LAT) along the Cox Peninsula and between +2.2 m and -3.3 m LAT along the north-eastern foreshore (Cardno 2013a). A second mapping survey carried out at the end of the dry season in October 2012 (Dredging survey 1; D1) revealed a large expansion of seagrass habitats (approximately 250% relative increase in the total areal extent of seagrass habitats). This consisted mostly of an offshore expansion of the distribution of Halophila (at depths up to -10 m LAT) (Cardno 2013b). The expansion was most pronounced at locations northeast of East Point with estimated increases in seagrass habitat extents of approximately 521 ha, 1,022 ha and 2,117 ha at East Point, Casuarina Beach and Lee Point respectively. Although the survey occurred after the start of dredging operations on 27 August 2012, dredging and spoil disposal volumes remained relatively minor (Backhoe Dredging (BHD) only) until commencement of primary Cutter Suction Dredging (CSD) operations on 4 November Results of survey D1 (October 2012) were therefore considered representative of the large natural variability of seagrass habitats in the Darwin region. 1.4 Development of Seagrass Response Models and the Seagrass Decision Support Framework To improve the understanding of seagrass dynamics in the Darwin region, and to investigate the potential drivers of change in Halophila and Halodule habitats, an analysis was conducted in August 2013 on metocean, water quality and seagrass distribution data collected between May 2012 and May Changes in the distribution and abundance of each genus between surveys were compared with corresponding historical conditions of light and turbidity using a Generalized Linear Model (GLM) (Quinn and Keough 2002). A GLM procedure was used to identify light and turbidity variables that were correlated with either increases or decreases in the cover of each genus, and to identify relevant timeframes of exposure to conditions (14 days, 28 days or 84 days). First, the relationships between changes in seagrass distribution (decrease or increase in cover) and individual light-related variables were derived using seagrass, light and turbidity data collected from May 2012 to August 2013). Changes in percentage cover of Halophila and Halodule between surveys were compared with the following light-related variables: > Mean daily photosynthetically active radiation (PAR) dose (measured as mol photons/m 2 /day); > Mean daily turbidity (measured in Nephelometric Turbidity Units; NTU); and > Proportion of days PAR below 1, 3 and 5 mol photons/m 2 /day. Turbidity and daily PAR dose were identified (Cardno 2013c) as the most common metrics of seagrass light requirements used to understand changes in seagrass distribution and abundance (Lee et al. 2007; Chartrand et al. 2012; Collier et al. 2012). Light requirements are also often described in terms of the number of days above or below species-specific thresholds (Collier et al. 2012). Analyses included days below species specific PAR thresholds in order to improve the understanding of conditions likely to result in seagrass loss. It was found that decreases in the percentage cover of Halophila generally occurred within a mean turbidity range of 8 NTU to 13 NTU over a month (28 days) prior to the surveys, while increases generally occurred below a mean turbidity level of approximately 5 NTU. Patterns for Halodule cover were mostly similar to those for Halophila, although the range of mean turbidity values associated with a decrease in cover was slightly more variable (i.e. 5 NTU to 15 NTU). Prepared for INPEX Cardno 2

12 Levels of light that were associated with changes in seagrass cover were also examined. Changes in Halodule and Halophila cover were significantly correlated with a number of light variables, including mean daily PAR dose and the fraction of low light days (below 1, 3 or 5 mol photons/m 2 /day), although changes associated with light were not as clear as they were for turbidity. Changes in the cover of Halophila were correlated with light variables over short (14 days), medium (28 days) and longer (84 days) temporal scales. In contrast, changes in the cover of Halodule were correlated with changes in light variables over the medium temporal scale (i.e. 28 days) only. Decreases in percentage cover for Halophila were mostly associated with a range of 4 to 9 mol photons/m 2 /day over a 28-day period, whilst decreases in Halodule cover were mostly associated with a range of 7 to 17 mol photons/m 2 /day. This range of higher PAR values suggests that the light requirement for Halodule is greater than that for Halophila in the Darwin region. This is consistent with observations of Halodule distribution, which generally dominate intertidal habitats that generally receive higher levels of light compared with the shallow subtidal habitats in the Darwin region where Halophila prevails (Cardno 2013c, 2014b). The relationships between changes to seagrass distribution and levels of turbidity and light were incorporated into the seagrass Trigger Action Response Plan (TARP) in the EA and GEP DSDMPs (INPEX 2013, 2014a). This improved the ability to assess risk of a change in seagrass (Halophila and Halodule) that may be associated with dredging-related increases in turbidity and consequently a reduction of benthic light. The Seagrass Decision Support Framework (DSF) (Cardno 2013c) was developed to modify the Level 2 and Level 3 trigger assessments for seagrass. Under the DSF, the Level 2 trigger involved evaluation of the probabilities of Halophila and Halodule growth (in distribution) as a function of the historical light conditions prior to a Level 1 trigger exceedance attributable to the Project s dredging and spoil disposal activities, and the probabilities for the forecasted conditions following the exceedance. If the outcome indicated a likely risk to either Halophila or Halodule at a reactive site due to a reduction in light from dredge-excess turbidity, then a reactive seagrass monitoring (towed-video) survey was to be undertaken. Results from the reactive seagrass monitoring survey would then be incorporated into the Level 3 trigger assessment, which follows a similar process to the Level 2 trigger assessment. This Level 3 assessment would be used to confirm whether the dredge-excess turbidity that caused the Level 1 exceedance actually resulted in a measured impact to seagrass as predicted by the Level 2 Risk to Receptor Assessment. 1.5 Summary of the Dredging Phase Surveys Dredging Phase monitoring has comprised a total of seven towed-video seagrass mapping surveys, with two surveys during Season One dredging (D1: October 2012; D2: February 2013), two surveys during the 2013 dry season dredging hiatus (D3: May 2013; D4: August/September 2013), and three surveys during Season Two of EA dredging and GEP dredging operations (D5: November 2013; D6: February 2014; D7: May 2014). Survey D7 (21 May to 26 May 2014) was undertaken approximately three weeks before the end of Season Two EA dredging operations (11 June 2014). During Dredging Phase towed-video mapping surveys have shown an overall seasonal cycle of decline and recovery of Halodule and Halophila in Darwin Outer that is consistent with what is anticipated for these genera in the wet tropics. The mapping surveys have also shown that there are distinct genus-specific spatial and temporal patterns for Halodule and Halophila in addition to the overarching seasonal cycle. Of the two genera, Halophila has shown the most seasonality, with a general expansion of distribution spatial extent during the dry season and reduction during the wet season. The extent of Halophila in Darwin Outer has ranged from approximately 2,700 ha in D1 (October 2012) during the dry season to complete absence from all Survey Areas in D2 (February 2013) and Survey Areas mapped in D6 (February 2014) during the wet season. The largest patches of Halophila mapped were on the east side of Darwin Outer off Casuarina Beach and to the east of Lee Point. Patches of Halophila were generally located in slightly deeper water (between -9.5 m and +2 m Lowest Astronomical Tide; LAT) than Halodule (between -1.5 m and +2 m LAT) and there was generally very little overlap between patches of the two genera. Although the measured spatial extent of Halodule also varied naturally during the Dredging Phase surveys, changes in distribution were not to the same extent as those observed for Halophila and have occurred mainly as changes to the size of patches rather than a redistribution of patches (as occurred for Halophila). The largest patch of Halodule has consistently been mapped in the intertidal area (to +2 m LAT) off Casuarina Beach. Prepared for INPEX Cardno 3

13 Extreme seasonal fluctuations in turbidity and light in Darwin Outer were recorded throughout the Dredging Phase as part of the Water Quality and Subtidal Sedimentation Monitoring Program (WQSSMP). Turbidity was generally higher during wet seasons when several tropical systems and cyclones generated heavy rainfall, strong winds and large swell and waves. During these high turbidity events, there were periods where no light was available for photosynthesis at the seabed. Dry season conditions were relatively benign in comparison to the wet season, although elevated turbidity was often observed during spring tides. Overall, as a result of these natural drivers, 173 wet season and 20 dry season Level 1 turbidity trigger exceedances were recorded at reactive monitoring sites Fannie Bay, Lee Point and Woods Inlet during the Dredging Phase. All of these exceedances were attributed to natural causes. Seagrasses in Darwin Outer were observed to respond to natural seasonal environmental changes through fluctuations in cover and distribution. Generalised linear models revealed that selected light-related variables (turbidity and light at the seabed) explained some of the temporal patterns in seagrass extent. Given that turbidity measured at seagrass monitoring sites was generally in the long-term range of natural variability (Cardno 2014b), fluctuations in seagrass cover and distribution were considered to be natural. In general, GLM analyses revealed that the seasonal changes to the extent of Halophila extent were explained relatively well by the selected light-related variables (mean daily turbidity and percentage of low light days over the preceding 28-day and 84-day periods). Most of the variability in Halodule extent was best explained by the preceding 14-day and 28-day average turbidity values, while depth-dependent variables (i.e. benthic light availability) only had a very low explanatory power. Although Halodule generally persisted to a greater extent than Halophila in the wet season there are indications that Halodule was vulnerable to weather events with increased wave energy. At Casuarina Beach, for example, the extent of Halodule in D7 (May 2014) decreased by two thirds relative to D5 (November 2013). High energy metocean conditions persisted for an extended period during the passage of Tropical System (TS) 05U and Tropical Cyclone (TC) Fletcher in January 2014 to early February Such conditions may have led to direct damage from strong waves in the shallow seagrass habitats where Halodule has generally been mapped, as well as potentially smothering from increased sediment resuspension/movement. Predictions from seagrass response models during all Dredging Phase surveys based on dredging and background conditions of turbidity indicated no influence of dredging-related excess turbidity on Halodule and Halophila growth in the Survey Areas at potential Impact sites. 1.6 Objectives The main objectives of the Seagrass Monitoring Program are to: > Monitor and report potential impacts to seagrass communities as a result of dredging and spoil disposal activities; > Measure seasonal changes in Halophila and Halodule distribution at key seagrass habitat areas in Fannie Bay, East Point, Casuarina Beach, Lee Point, Woods Inlet and Charles Point West; and > Increase the understanding of seagrass dynamics in Darwin Harbour and surrounds. The Seagrass Monitoring Program involved regular sampling of seagrass using towed-video mapping to determine trends in its distribution. These data were collected in parallel with informative water quality parameters as part of the WQSSMP. The suite of seagrass distribution and supporting water quality data were examined to help determine the risk of impact on seagrass habitat from dredging and spoil disposal. This report outlines the findings of the Post-dredging Phase seagrass towed-video surveys P1 (3 July 2014 to 9 July 2014) and P2 (15 October 2014 to 21 October 2014) that measured changes in the distribution of Halophila and Halodule since the completion of the previous survey (D7) on 26 May 2014, and examines the relationship between these changes and historical light and turbidity conditions to assess potential delayed impacts from dredging and spoil disposal activities. Prepared for INPEX Cardno 4

14 Table 1-1 Previous and revised reactive seagrass management triggers (INPEX 2012, 2013, 2014) Components Level 1Trigger Daily Average Turbidity Level 2 Trigger Level 3 Trigger Previous (EA DSDMP Rev. 1) Trigger value (Wet Season) (1 Nov to 30 Apr) Trigger value (Dry Season) (1 May to 31 Oct) Intensity (95%ile) Duration (90%ile) >63 NTU >52 NTU over 5 consecutive days Intensity (99%ile) Duration (95%ile) >17 NTU >13 NTU over 4 consecutive days Frequency (90%ile) >52 NTU > 5 days per 7-day rolling period Frequency (95%ile) >13 NTU > 3 days per 7-day rolling period Loss in seagrass distribution (percentage cover): > level of detection AND Loss in leaf/shoot density (leaves/m 2 ): >20% net detectable loss Loss in seagrass distribution (percentage cover): > level of detection + 10% AND Loss in in leaf/shoot density (leaves/m 2 ): >30% net detectable loss Revised (EA DSDMP Rev. 4 and GEP DSDMP Rev. 7) Trigger value (Wet Season) (1 Nov to 30 Apr) Trigger value (Dry Season) (1 May 31 Oct) Intensity (95%ile) Duration (90%ile) >63 NTU >52 NTU over 5 consecutive days Intensity (99%ile) Duration (95%ile) >17 NTU >13 NTU over 4 consecutive days Frequency (90%ile) >52 NTU > 5 days per 7-day rolling period Frequency (95%ile) >13 NTU > 3 days per 7-day rolling period Risk to Receptor Assessment Outcome of risk assessment to inform the potential risk of impact to Halophila and Halodule resulting from the Project s dredging and / or spoil disposal activities. moderate or high risk rating = exceedance Observed impact assessment Outcome of reactive seagrass monitoring and impact assessment to assess the impact to Halophila and Halodule resulting from the Project s dredging and / or spoil disposal activities. moderate or high observed impact rating = exceedance Prepared for INPEX Cardno 5

15 2 Methodology 2.1 Overview To meet the objectives of the Seagrass Monitoring Program, towed-video surveys were routinely undertaken to assess broad-scale changes in the extent and percentage cover of the dominant genera of seagrass in the Darwin region. These are comprised of habitats supporting Halophila (including mostly H. decipiens) and Halodule (including H. uninervis). To investigate the physical drivers of change in seagrass habitats in the Darwin region, changes in the abundance and depth distribution of each genus are compared to the turbidity and light climate during the intervening period between surveys. To examine the potential impacts on seagrass communities from dredging and spoil disposal activities, the measured historical conditions of turbidity and light are compared with modelled estimates of background conditions. Seagrass response models are then applied to each scenario to predict changes in seagrass growth that may be due to dredging-related increases in turbidity. 2.2 Vessels, Safety and Environmental Management Field work conducted during Post-dredging survey 1 (P1; July 2014) and 2 (P2, October 2014) was carried out from the MV Weapon. All work was completed in accordance with the Project Health Safety and Environment (HSE) Plan. 2.3 Sites, Timing and Frequency of Surveys Towed-video seagrass Survey Areas (Figure 2-1) include seagrass habitats at Fannie Bay, Woods Inlet and Lee Point identified as potential Impact sites in the EA DSDMP (Rev. 4) (INPEX 2013), and other key seagrass habitats at Casuarina Beach, East Point and Charles Point West for information. A summary of towed-video surveys conducted in the Baseline, Dredging and Post-dredging Phases is given in Table 2-1, and quarterly seagrass distribution maps are provided in individual technical reports (Geo Oceans 2012a,b, 2013a-c, 2014a,b; Appendix A and Appendix B). Seagrass was also mapped at a second site along the Cox Peninsula (Charles Point East) in D1 (October 2012), D2 (February 2013) and D3 (May 2013). Mapping at this site was not carried out thereafter due to visibility being frequently too poor for reliable data collection and time constraints of completing the survey within one neap tide. Prepared for INPEX Cardno 6

16 Figure 2-1 Locations of seagrass Sample and Survey Areas Prepared for INPEX Cardno 7

17 Table 2-1 Summary of towed-video surveys to date and corresponding dredging activities Project Dredging Activities Baseline (Pre-dredging) Towedvideo Baseline survey (B1) Sampling Dates Technical Report Interpretive Report 22 May 2012 to 2 June to 18 June June 2012 to 2 July 2012 Geo Oceans 2012a Baseline Report (Cardno 2013a) BHD commenced 27 August 2012 Dredging survey 1 (D1) 8 to 12 October to 26 October 2012 Geo Oceans 2012b Dredging Report 1 (Cardno 2013b) CSD commenced 4 November 2012 Dredging survey 2 (D2) 18 to 22 February 2013 Geo Oceans 2013b Season One dredging ceased 30 April 2013 (Dry season hiatus) Dredging survey 3 (D3) 16 to 20 May 2013 Geo Oceans 2013c Data Synthesis (Appendix A, Cardno 2013c) Dredging survey 4 (D4) 29 August 2013 to 4 September 2013 Appendix B, Cardno 2013a Cardno 2014c GEP dredging commenced on 23 October 2013 Dredging survey 5 (D5) 11 November 2013 to 15 November 2013 Appendix A, Cardno 2014c Cardno 2014d East Arm dredging recommenced for Season Two on 1 November 2013 Dredging survey 6 (D6) 22 February 2014 to 26 February 2014 Appendix A, Cardno 2014d Cardno 2014e Dredging survey 7 (D7) 21 May 2014 to 26 May 2014 Appendix A, Cardno 2014f Cardno 2014f Season Two East Arm dredging was completed on 11 June 2014 GEP dredging was completed on 12 July 2014 Postdredging survey 1 (P1) Postdredging survey 1 (P2) 3 July 2014 to 9 July October 2014 to 21 October 2014 Appendix A, this report Appendix B, this report This report This report 1 The first of the three B1 field trips was focused on locating seagrass habitats and identifying suitable sites for drop camera monitoring surveys (Cardno 2013a). Many transects were exploratory and conducted in other benthic habitats rather than directed at seagrass mapping. The majority of seagrass habitat mapping data was collected in the second and third B1 field trips. Prepared for INPEX Cardno 8

18 2.4 Towed-video Surveys The spatial scale of Darwin seagrass habitats and the constraints of surveying during neap tides only allows for the use of techniques that facilitate the rapid examination of large areas of the seabed along the Darwin Outer foreshore. This was achieved by using a towed camera system (Geo Oceans (GO) Visions) to collect high-resolution still images and video footage of the seafloor along a set of transects distributed throughout the key seagrass habitats (Figure 2-1 and Appendix A). One hundred and fifty-three predetermined Sample Areas (each approximately 50 m in radius) were distributed across the spatial extent of the Survey Areas at Fannie Bay, Woods Inlet, Lee Point, Casuarina Beach, East Point and Charles Point West (Figure 2-1). The number of and distance between Sample Areas within each Survey Area was selected based on the extent and spatial heterogeneity of each seagrass habitat and time constraints of surveying during a single neap tide period (Appendix A). The distance between Sample Areas ranged between approximately 120 m and 170 m at smaller more complex seagrass habitats such as at Woods Inlet, Fannie Bay and Charles Point West, and between approximately 340 m and 480 m at larger relatively homogeneous habitats at Lee Point, Casuarina Beach and East Point (Geo Oceans 2012b). These are within the recommended range (100 m to 500 m) for mapping seagrass distribution across spatial scales between 1 km and 10 km (McKenzie 2003). Within each Sample Area at Fannie Bay and Woods Inlet, the video camera was towed along the seafloor at a speed of 1 to 2 km/hr and approximately 1 m above the substratum in a transect ~50 m long (Appendix A). One transect was conducted inside each Sample Area. Point data were recorded along each transect at approximately one second intervals and included: > Transect depth (m LAT); > Occurrence (presence/absence); and > Genus-specific percentage cover (Halophila and Halodule). Data for genus-specific occurrence and percentage cover were primarily intended to derive maps of seagrass distribution for the visual assessment of broad-scale changes in seagrass habitat. This is described in detail in individual technical reports (Geo Oceans 2012a,b, 2013a-c, 2014a,b) and in Appendix A and Appendix B of this report. To investigate the relationship between physical parameters and observed change in seagrass distribution, additional analyses were conducted on these spatial data (Section 2.6) together with WQSSMP data: 1) measurements of turbidity at each location in the period between surveys (referred to as historical turbidity conditions); and 2) light conditions at the depth of each transect (historical light conditions). The Sample Areas (transect locations) were initially selected for mapping purposes to enable spatial interpolation across the Survey Areas. The spatial spread of transects therefore included depths ranging between approximately -5 m and +2 m LAT (Appendix C). Throughout the Seagrass Monitoring Program (inclusive of P1 and P2), transects were located within the same Survey Areas visited in previous surveys. 2.5 Physical Environment Water quality and weather data collected or sourced as part of the WQSSMP were used to contextualise and to support interpretation of changes in seagrass distribution observed during the reporting period. Data collection methods are described in detail in Cardno (2014g) and summarised below Metocean Conditions Wind, wave and water level data were used to contextualise changes in turbidity and underwater light climate. Wind speed and direction (recorded at 30-minute intervals) were obtained from the Bureau of Meteorology (BOM) weather station at Darwin Airport (BOM Reference ). Water level data (recorded every five minutes) were obtained from the Fort Hill Wharf tide gauge maintained by the BOM National Tidal Centre (NTC). Wave characteristics (significant wave height and peak wave period) were obtained from the Integrated Marine Observing System (IMOS) National Reference Station (NRS) Darwin mooring (IMOS platform code: NRSDAR). Solar (surface) irradiance (recorded every minute) was obtained from the USA Atmospheric Radiation Measurement Climate Research Facility situated adjacent to the BOM meteorological office near Darwin Prepared for INPEX Cardno 9

19 International Airport. This dataset was used to calculate time-series of the light extinction coefficient of the water column and underwater light climate at the depth of the seagrass Sample Areas (transect centroids) Near-bed Water Temperature, Turbidity and Light Near-bed water temperature, turbidity and light (PAR) were recorded together with depth at 15-minute intervals at water quality monitoring stations deployed as part of the WQSSMP (Cardno 2015) in proximity of seagrass habitat at Charles Point West, Woods Inlet, Fannie Bay, East Point, Casuarina Beach and Lee Point. Temperature, turbidity and PAR sensors were each fixed to seabed frames at heights of approximately 0.4 m, 1.0 m and 1.15 m above the seabed respectively. It should be noted that the frames were deployed at varying depths among the monitoring stations (ranging from approximately -4 m LAT at Casuarina Beach to -2.5 m LAT at Woods Inlet) and that PAR data therefore required normalisation to a constant depth (as described in Section 2.6.2). 2.6 Data Analysis Seagrass Spatial Data Seagrass point data (occurrence and percentage cover) along each transect were averaged and georeferenced to the centre point (transect centroid) of each Sample Area. Spatial interpolation models were then applied to these centroid data points to predict the distribution of seagrass between known points and to produce maps of seagrass distribution. Interpolation tools and mapping products are described in Appendix A and are primarily intended for the visualisation of seagrass habitat and qualitative assessments of change over large spatial scales (km). Spatially interpolated maps were used to evaluate the areal extent of seagrass habitats. This was calculated together with an estimate of uncertainty which accounts for the varying distance between Sample Areas (referred to as the reliability estimate as described in Appendix A and Appendix B). Geo-referenced towed-video centroid point data include the following: > Genus-specific percentage cover (Halophila and Halodule); > Occurrence (presence or absence); and > Transect depth (m LAT), rounded to the nearest 0.5 m for comparison with calculated benthic PAR. In order to test the relationships between the light climate and seagrass condition, genus-specific changes in percentage cover were calculated at each Sample Area (transect centroid) between the May 2014 survey (D7) survey and the July 2014 survey (P1), and between the July 2014 survey (P1) and the October 2014 survey (P2). Towed-video percentage cover data were initially intended for mapping purposes and visualization of broadscale spatial and temporal patterns in seagrass distribution and are therefore treated as semi-quantitative measures of seagrass abundance in each Sample Area. Therefore, some level of uncertainty is associated with the calculations of change in cover between surveys. Prior to comparison with historical WQSSMP light variables, these data were first categorised as either a decrease or an increase in percentage cover for use in the analyses (Section 2.6.3) Underwater Light Climate Time-series measurements of near-bed PAR (WQSSMP) were used to characterise the underwater light climate of seagrass habitats. Measurements provided PAR data at the deployment depths of the water quality monitoring stations (ranging between -4 m LAT and -2.5 m LAT), and the following protocol was applied to derive PAR across the depth range of surveyed seagrass. This involved firstly estimating the light extinction coefficient of the water column and secondly applying it to the measurements of solar surface irradiance (herein referred to as surface irradiance) and depth, as summarised below and in Cardno (2014g). The near-bed time-series measurements of PAR were used together with time-series measurements of depth (subject to tidal changes) and surface irradiance to estimate the extinction coefficient of the water column using Beer s law: Prepared for INPEX Cardno 10

20 ( ( )) ( ) ( ) ( ) (1) where I(z(t)) is the PAR intensity (µmol photons/m 2 /s) at depth z(t) (m) at time t, I 0 (t) the surface irradiance (z=0) at time t and k(t) (m -1 ) the light extinction coefficient at time t. Due to possible bias from reflection losses of light at the surface of the water when the sun angle is low, the extinction coefficients were calculated only between 09:45 and 15:45 local time (09:00 to 15:00 solar time). As extinction coefficients are dependent on multiple time-series measurements (e.g. PAR, depth and surface irradiance), extinction coefficient time-series were fragmented into periods during which all measurements were recorded and light penetration to the sensors was sufficient. This dataset was augmented using the time-series measurements of near-bed turbidity, which can be related to light extinction. Comparison of near-bed turbidity and the extinction coefficient datasets was used to derive an empirical relationship between the light extinction coefficient and turbidity (Cardno 2015). This empirical relationship was in turn applied to the complete turbidity time-series in order to generate continuous time-series of the extinction coefficient (including times when no light reached the near-bed PAR sensors but would reach shallower depths in seagrass habitat). The complete time-series of extinction coefficient estimates were then used to calculate light penetration (from surface irradiance data) at various depths within seagrass habitat (Cardno 2015). In order to describe historical light conditions at the seafloor prior to each survey, and provide contextual information to interpret changes in seagrass distribution between surveys, the time-series of light and turbidity data were examined for the period prior to P1 (i.e. from the end of Survey D7 on 27 May 2014 to the end of P1 on 8 July 2014) and the period prior to P2 (from the end of Survey P1 on 9 July 2014 to the end of P2 on 21 October 2014). In these two reporting periods prior to P1 and P2, summary statistics (mean, median, maximum, 25 th, 75 th and 90 th percentiles) were used to describe light and turbidity time-series, and cumulative distribution functions (CDF) were used to compare with conditions prior to other surveys Seagrass Growth Predictions In order to evaluate and describe the response of Darwin seagrass to historical turbidity and light conditions, genus-specific seagrass response models were established based on seagrass, turbidity and light data collected from May 2012 to August 2013 as part of the seagrass monitoring program and the WQSSMP (Cardno 2014c). Models were subsequently updated with the inclusion of data collected in November 2013 (D5) (Cardno 2014d), February 2014 (D6) (Cardno 2014e) and May 2014 (D7) (Cardno 2014f). Model inputs were selected based on the correlation between changes in seagrass percentage cover and individual lightrelated variables, and involve the mean daily turbidity over short, medium and long time-periods (14, 28 and 84 days respectively), and the percentage of days receiving less than 1 and 5 mol photons/m 2 /day calculated over a time period of 28 days (Cardno 2014f). In order to assess the current understanding of the physical drivers of change in seagrass distribution, model predictions based on WQSSMP historical conditions of light and turbidity prior to P1 (July 2014) and P2 (October 2014) were compared with changes in percentage cover (decrease or increase) of Halophila and Halodule observed since D7 (May 2014). Two separate models for Halodule were used to calculate the probability (p) of an increase in Halodule cover. The model that best explained the variability in Halodule cover over time was based solely on turbidity (Cardno 2014f): ln = ( 14 ) ( 28 ) (2) However, this turbidity model does not allow predictions of depth-dependent responses, because all depths from individual sites are assigned identical turbidity values from the corresponding water quality station. By contrast, light data were estimated for a range of depths and were therefore used in a second model to resolve possible depth-related differences in the growth of Halodule: ln = (% <5 28 ) (3) For Halophila, two separate models were also used to calculate the probability (p) of an increase in cover. Because of the total absence of Halophila during the February 2013 (D2) and February 2014 (D6) surveys Prepared for INPEX Cardno 11

21 (wet season), it was found that most of the variability in Halophila could be explained by a model based solely on turbidity (Cardno 2014f): ln = ( 28 ) ( 84 ) (4) This turbidity model does not allow predictions of depth-dependent responses of Halophila, and therefore light data that were estimated for a range of depths were used in a second model to resolve possible depthrelated differences in the growth of Halophila (Cardno 2014f): ln = (% <1 28 ) (5) The genus-specific growth response models were used to predict the likely effects of WQSSMP historical turbidity and light conditions prior to each of the P1 (July 2014) and P2 (October 2014) surveys on changes in seagrass distribution. The models were applied to turbidity and light conditions in the three months prior to P1 and P2 to estimate the likelihood of change since the D7 (May 2014) and P1 surveys respectively. Timeseries of daily turbidity measured at the corresponding water quality stations were assumed to be representative for all transects within a Survey Area adjacent to the station, while time-series measurements of daily PAR dose were calculated at the specific depth of individual transects Potential Dredging-related Influence The growth response models were used together with WQSSMP turbidity data at each monitoring site to evaluate the possibility that dredge-related excess turbidity potentially generated prior to the end of dredging activities on 11 June 2014 may have had a delayed influence on seagrass cover and distribution during survey P1 (July 2014). The analysis was not applied to survey P2 (October 2014), which occurred more than 84 days after the end of EA dredging and hence outside the relevant time-frames identified in the seagrass response models (Equations 2 to 5, Section 2.6.3). Three modelled response scenarios were compared to evaluate the risk of dredge-derived turbidity potentially affecting the depth distribution of seagrass. These scenarios are defined by the following turbidity datasets: > Scenario 1 Measured turbidity (historical data collected prior to P1 (July 2014), as described in Section 2.6.3, which combines natural and possible dredging influences; > Scenario 2 Estimated background turbidity (non-dredge related): measured turbidity minus Season Two (2013/2014 East Arm dredging) Forecast model excess turbidity (EA DSDMP Rev. 4); and > Scenario 3 Empirical model turbidity (estimated from the tide/wave Empirical model outlined in Appendix E of the Seagrass DSF, Cardno 2013c). An estimate of potential dredge-derived turbidity effects is assumed to relate to the difference between Scenario 1 (Measured) and Scenario 2 (Estimated background), while Scenario 3 (Empirical model) provides an estimate of the uncertainty in the approach. It should be noted that the Season Two (2013/2014 EA dredging) Forecast model excess turbidity provides a conservative estimate of potential dredging-related excess turbidity and not an actual measure of this contribution (it may be considered to represent the worst case). Each scenario was used to derive time-series measurements of benthic light at a range of depths, to use as inputs to the genus-specific seagrass growth response models (Section 2.6.3). Seagrass growth predictions were generated using each of the three scenarios to examine the likely growth response (i.e. increase or decrease in cover) at a range of depths (0.5 m increments) at each site. Differences in the predicted probabilities of seagrass growth between the three scenarios were examined to assess the risk of changes in distribution as a result of potential dredging-related excess turbidity Final Updates to the Seagrass Response Model The GLM procedure used to derive the predictive models (Equations 2 to 5, Section 2.6.3) following D7 (May 2014) (Cardno 2014f) was repeated with the dataset including all data collected from B1 (June 2012) to P2 (October 2014) in order to update the model coefficients with the complete dataset. The GLM procedure involved examining the correlation between change in seagrass cover and individual light-related variables, assessing different timeframes of response, and finally selecting a reduced set of variables for inclusion in Prepared for INPEX Cardno 12

22 composite models such as Equation 2, as described in the Seagrass DSF (Cardno 2013c) and summarised in Section Time-series of daily turbidity measured at the corresponding water quality stations were assumed to be representative for all transects within a Survey Area adjacent to the station, while time-series measurements of daily PAR dose were calculated at the specific depth of individual transects, as described in Section In order to identify relevant timeframes of exposure, all variables were calculated over timeframes of 14 days, a month (28 days) and three months (84 days) prior to each towed-video survey (Table 2-1). Light variables that were significantly correlated with a change in seagrass cover were used to create a predictive model with multiple predictors and update Equations 2 to 5. Variables were tested for correlation with one another prior to inclusion in the final predictive model. The model was produced by sequentially adding the variables that yielded the highest Nagelkerke pseudo-r 2 (measure of the goodness of fit for the GLM model) and checking for their significance in the model at every addition. The model with the highest number of significant variables was chosen. 2.7 Data Management and Quality Control The Quality Assurance and Quality Control (QA/QC) processes applied to the WQSSMP data are described in the WQSSMP Baseline Report (Cardno 2013d). The QA/QC processes applied to the spatial data are described in the Seagrass Monitoring Program Baseline Report (Cardno 2013a). Prepared for INPEX Cardno 13

23 3 Dredging Operations The dredging program involved a number of dredge vessels including Backhoe Dredgers (BHDs), a Cutter Suction Dredger (CSD) and Trailing Suction Hopper Dredgers (TSHDs), operating in different areas depending on water depths, bed material characteristics and the amount of material to be removed. The EA dredging campaign was divided into five Separable Portions (SP1 to SP5) that refer to the location within the dredge footprint and duration of specific dredging activities. The SPs are summarised in Table 3-1 and presented in Figure 3-2. The Project s dredging operations were undertaken over two seasons. Season One commenced on 27 August 2012 with BHDs. Primary dredging operations commenced approximately two months after BHD operations on 4 November 2012 with the arrival of the biggest CSD ever to work in Australian waters, the Athena. Direct TSHD operations were also undertaken during Season One of dredging, with Season One dredging ceasing on 30 April At the cessation of Season One dredging operations, overall EA dredge progress was approximately 43% complete. Season Two of dredging for EA commenced on 1 November 2013 after being temporarily suspended for six months during the 2013 dry season. Season Two dredging in EA extended into part of the 2014 dry season and was completed on 11 June Overall, 16.1 Mm 3 of material was approved to be removed from EA. Dredging for the GEP was undertaken in Season Two of dredging, commencing on 23 October 2013, with the direct TSHD operating intermittently up until 28 November The GEP BHD operations commenced on 7 March 2014 and were completed on 12 July Overall, Mm 3 of material was approved to be removed along the GEP. Table 3-1 ID SP1 SP2 SP3 SP4 SP5 East Arm dredge footprint summary Separable Portion Separable Portion 1 Module Offloading Facility (MOF) Separable Portion 2 Jetty Pocket Separable Portion 3 Berth Area Separable Portion 4 Approach Channel, Berth Approach and Turning Area Separable Portion 5 Walker Shoal Prepared for INPEX Cardno 14

24 Figure 3-2 EA dredging footprint and GEP route Prepared for INPEX Cardno 15

25 4 Results 4.1 Seagrass Distribution Changes This section presents the results of the Post-dredging seagrass monitoring surveys P1 (July 2014) and P2 (October 2014) and provides an overview of results collected throughout the Seagrass Monitoring Program. Throughout this report references are made to data from the Baseline Phase and the Dredging Phase surveys, details of which are presented in previous reports Spatial Distribution Habitat distribution maps of Halophila and Halodule for P1 (July 2014) and P2 (October 2013) are provided in Appendix A and Appendix B. Figure 4-1 and Figure 4-2 provide visual overviews of broad-scale changes in seagrass distribution in Darwin Outer since the commencement of monitoring in June 2012 (B1) Halophila During P1 (July 214), Halophila habitat was recorded in all Survey Areas (Figure 4-2) and covered an estimated area of 853 ha (± 370 ha reliability estimate) (Appendix A). This was in contrast to D7 (May 2014) completed just six weeks prior to P1, whereby Halophila habitat was recorded only at Fannie Bay and Lee Point as well as one transect at Charles Point West (with an area of 881 ± 280 ha; Cardno 2014f). Similar dry season habitat expansion occurred in previous years at Woods Inlet during D1 (October 2012), Casuarina Beach during D3 (May 2013) and East Point during D4 (August/September 2013) (Figure 4-1 and Figure 4-2). At Fannie Bay the distribution of Halophila habitat during P1 (July 2014) was similar to D7 (May 2014). In contrast at Lee Point the distribution of Halophila had changed from a continuous habitat covering approximately 1,103 ha ± 267 ha during D7 (Cardno 2014f) to three distinct patches covering approximately 277 ha ± 240 ha during P1. This included an area towards the south of the Survey Area where Halophila had not been recorded during D7. A similar dry season decline in Halophila habitat was also observed during D5 (November 2013) following a large expansion between D2 (February 2013) and D3 (May 2013). At Charles Point Halophila was again recorded in only one transect but further inshore compared to D7. During P2 (October 2014), further expansion of Halophila habitat was observed compared to during D7 and P1 at East Point, Casuarina Beach and Charles Point West, while there were changes in the distribution of patches at Woods Inlet and Lee Point, and a decline in the northern area of Fannie Bay (Figure 4-2). It should be noted that a similar decline at this site was observed between D4 (August/September 2013) and D5 (November 2013). The total areal extent of Halophila habitat estimated during P2 was 2,029 ha (±605 ha reliability estimate) (Appendix B). Changes recorded during P1 and P2 were consistent with the high level of variability of Halophila habitat observed throughout Dredging Phase surveys (Cardno 2014f) and seasonal patterns of change observed in the 2012 and 2013 dry seasons (Figure 4-1, Figure 4-2, Appendix A and Appendix B) Halodule During P1 (July 2014) Halodule habitat was recorded at all Survey Areas and covered an estimated area of 1,731 ha (± 458 ha reliability estimate) (Figure 4-2, Appendix A). At Lee Point, new patches of Halodule were recorded, resulting in an expansion of habitat from 34 ha (± 2 ha reliability estimate) during D7 (May 2014) to 140 ha (± 20 ha reliability estimate) during P1. There was also a considerable expansion of Halodule habitat at Casuarina Beach since D7 (May 2014), reaching an area of 1,438 ha (± 396 ha reliability estimate) which was comparable to all other surveys prior to November 2013 (D5) (Figure 4-1, Figure 4-2, Appendix A). The total areal extent of Halodule habitat estimated during P2 was 1,791 ha (±498 ha) and comparable to that of P1. Compared to P1, during P2 the distribution of Halodule at Lee Point and Casuarina Beach was, however, different around the edges of the distribution and completely absent from the East Point Survey Area (Figure 4-2, Appendix B). The habitat distribution of Halodule during P1 and P2 was largely consistent with findings at a similar time in previous years (B1 in June 2012, D1 in October 2012, D4 in August/September 2013 and D5 in November Prepared for INPEX Cardno 16

26 2013). Results were also generally similar to all other surveys since B1 (June 2012) (except D7 at Casuarina Beach) with no indication of seasonal change in spatial distribution and extent of Halodule habitat. Prepared for INPEX Cardno 17

27 Figure 4-1 Halodule and Halophila distribution from the Baseline and Dredging Phase towed-video surveys: B1 (June 2012) to D4 (August/September 2013) N.B. Mapping at Charles Point East was only carried out from survey D1 (October 2012) to D3 (May 2013) Prepared for INPEX Cardno 18

28 Figure 4-2 Halodule and Halophila distribution from Dredging and Post-dredging Phase towed-video surveys: D5 (November 2013) to P2 (October 2014). It should be noted that not all Survey Areas were completed during the D6 (February 2014) survey Prepared for INPEX Cardno 19

29 4.1.2 Depth Distribution Consistent with all previous surveys, Halodule was again recorded mostly in the intertidal and shallow subtidal zones (between -1 m and +2 m LAT) during P1 (July 2014) and P2 (October 2014) with little difference among Survey areas in the recorded lower depth limit (Figure 4-3, Figure 4-4 and Figure 4-5). During both P1 and P2 there were only minimal changes (i.e. ± 0.5 m) in the recorded lower limit of the depth distribution of Halodule compared to Baseline Phase and Dredging Phase surveys. An exception to this was at East Point where Halodule was not recorded during P2 (Figure 4-5). In contrast Halophila was more widespread across a range of depths (between -5.5 m and +2 m LAT) during P1, reaching higher densities in the subtidal zone (i.e. below 0 m LAT) (Figure 4-3, Figure 4-4 and Figure 4-5). The depth distribution of Halophila varied substantially among Survey Areas, with lower depth limits during P1 of -5.5 m LAT, -4.5 m LAT, -2 m LAT and 0 m LAT at Casuarina Beach, Lee Point, East Point and Fannie Bay respectively. The depth distribution of Halophila was also more variable than Halodule between P1 and P2 as well as among previous sampling surveys. This was consistent with changes observed since B1 (June 2012) and indicating a general pattern of wet season decline followed by dry season recovery and increasing depth distribution. Changes since D7 were most pronounced at Casuarina Beach, where Halophila was absent during D7 and was recorded to a maximum depth of -5.5 m LAT during both P1 (albeit at low density) and P2 (Figure 4-4, Appendix A). A similar pattern was found at East Point whereby no Halophila was recorded during D7 although it was subsequently found mainly at a depth of -0.5 m LAT during P1 and to a maximum depth of -2.5 m LAT during P2 (Figure 4-5). A seasonal pattern was less clear at Charles Point West where the lower depth limit of Halophila changed from -1 m LAT during D7 to 0 m LAT during P1 and -1.5 m LAT during P2. Changes in the depth distribution of Halophila since D7 were minimal at Woods Inlet and Fannie Bay, while the redistribution of patches at Lee Point during P2 resulted in the maximum depth limit changing from -4.5 m LAT during D7 and P1 to -1 m LAT during P2 (Figure 4-3). The relative stability in depth distribution of Halodule since D7, and the large changes in depth distribution of Halophila were consistent with changes observed since the commencement of monitoring in June In particular at Casuarina Beach, East Point, Charles Point West and Woods Inlet the lower depth limit of Halophila habitat was also greater during D1 (October 2012) in the late dry season compared to other surveys, consistent with seasonal growth patterns of Halophila. Given the dynamic nature of results between survey periods and seasons, no indication of a delayed impact from dredging activities on the depth distribution of Halophila and Halodule is evident Percentage Cover The percentage cover of Halophila generally increased in all Survey Areas from D7 (May 2014) to P1 (July 2014) and P2 (October 2014), with the exception of Fannie Bay where a decline in the northern section of the Survey Area was recorded during P2 (Figure 4-3 to Figure 4-5 and Appendices A and B). Halophila habitat was recorded with percentage cover from 10% to 20% at Casuarina Beach, East Point and Lee Point during P1 (July 2014) (Appendix A), while during P2 (October 2014) the percentage cover ranged from 20% to 50% at Charles Point West, East Point and Casuarina Beach. The percentage cover of Halodule typically ranged between 10% and 20% across most transects (Sample Areas) at Casuarina Beach, Charles Point West, Fannie Bay and Woods Inlet during both P1 and P2. It remained comparatively low (between 5% and 10% cover) at East Point during P1 and at Lee Point during P1 and P2 (Appendix A and Appendix B). Results from P1 and P2 are consistent with previous observations whereby Halophila percentage cover generally reached greater values though more ephemeral compared to Halodule cover.(figure 4-3, Figure 4-4 and Figure 4-5). Prepared for INPEX Cardno 20

30 Fannie Bay 2 B1 - June D1 - October D2 - February D3 - May Halodule Halophila D4 - August D5 - November D6 - February D7 - May 2014 Depth (m LAT) P1 - July P2 - October Percent Cover (%) Percent Cover (%) Lee Point 2 B1 - June D1 - October D2 - February D3 - May Halodule Halophila D4 - August D5 - November D6 - February D7 - May 2014 Depth (m LAT) P1 - July P2 - October 2014 Percent Cover (%) Percent Cover (%) Figure 4-3 Depth distributions and percentage cover of Halophila and Halodule at Fannie Bay and Lee Point Survey Areas from survey B1 (June 2012) to P2 (October 2014). The larger x- axis scale should be noted for Lee Point in survey D1 (October 2012) and D3 (May 2013) Prepared for INPEX Cardno 21

31 Woods Inlet 2 B1 - June D1 - October D2 - February D3 - May Halodule Halophila D4 - August D5 - November D6 - February D7 - May 2014 Depth (m LAT) P1 - July P2 - October Percent Cover (%) Percent Cover (%) Casuarina Beach 2 B1 - June D1 - October D2 - February D3 - May Halodule Halophila D4 - August D5 - November D6 - February D7 - May 2014 Depth (m LAT) P1 - July P2 - October Percent Cover (%) Percent Cover (%) Figure 4-4 Depth distributions and percentage cover of Halophila and Halodule at Woods Inlet and Casuarina Beach from survey B1 (June 2012) to P2 (October 2014) Prepared for INPEX Cardno 22

32 East Point 2 B1 - June D1 - October D2 - February D3 - May Halodule Halophila D4 - August D5 - November D6 - February D7 - May 2014 Depth (m LAT) P1 - July P2 - October Percent Cover (%) Percent Cover (%) Charles Point West 2 B1 - June D1 - October D2 - February D3 - May Halodule Halophila D4 - August D5 - November D6 - February D7 - May 2014 Depth (m LAT) P1 - July P2 - October Percent Cover (%) Percent Cover (%) Figure 4-5 Depth distributions and percentage cover of Halophila and Halodule at East Point and Charles Point West Survey Areas from survey B1 (June 2012) to P2 (October 2014). The larger x-axis scale should be noted for East Point in survey D1 (October 2012) Prepared for INPEX Cardno 23

33 4.2 Metocean Conditions and Light History Wind and Waves Winds observed during the five-month period between the D7 (May 2014) and P2 (October 2014) surveys were characteristic of dry season wind patterns with prevailing south-east trade winds (Figure 4-6 and Figure 4-7), and some northerly winds towards the end of the reporting period from 5 September 2014 to 21 October 2014 (Figure 4-6). Daily average wind speeds were generally in the 10 to 20 km/hr range throughout the reporting period, apart from a slightly elevated wind event on 8 June 2014 (24.6 km/hr). Figure 4-6 BOM Darwin Airport wind speed and wind direction between 27 May 2014 and 21 October 2014 Figure 4-7 BOM Darwin Airport wind rose between 27 May 2014 and 21 October 2014 Prepared for INPEX Cardno 24

34 Significant wave height (Figure 4-8) was generally less than 0.5 m for the entire reporting period, and was slightly elevated on 8 June 2014 peaking at 0.6 m. The residual water levels (i.e. difference between recorded and predicted tide) are also shown in Figure 4-8 to identify surge events (which would cause the measured tidal level to differ from the predicted values). This plot indicates that no significant surge events occurred during the five month period between the D7 (May 2014), and P2 (October 2014) surveys. Tidal residuals were generally less than 0.2 m. The largest tidal ranges during the monitoring period were observed during spring tides on 14 June 2014, 14 July 2014, 12 August 2014, 10 September 2014 and 10 October 2014, with peak ranges of 6.9 m, 7.1 m, 7.1 m, 7.0 m and 7.2 m respectively. Figure 4-8 IMOS Darwin significant wave height and peak wave period; BOM Fort Hill Wharf recorded tide and residual tide between 27 May 2014 and 21 October Water Temperature Near-bed daily-average water temperature decreased from 29ºC to 24ºC in the period preceding P1 (July 2014), before increasing to 26ºC by 5 August Following a slight decrease to 24ºC in mid-august 2014, near-bed water temperature increased to 30ºC by P2 (October 2014) (Figure 4-9). Figure 4-9 Near-bed daily-average water temperature at seagrass monitoring sites between 27 May 2014 and 21 October Shaded grey areas indicate seagrass towed-video surveys P1 (July 2014) and P2 (October 2014), and vertical dotted lines indicate the end of EA dredging (pink) and GEP dredging (green) Prepared for INPEX Cardno 25

35 4.2.3 Rainfall and Surface PAR The reporting period saw minimal rainfall in Darwin (Figure 4-10). The most significant rainfall event was 9.8 mm on 15 October 2014, with an additional five minor rainfall events including 4.2 mm on 20 October 2014, 2 mm on 30 May 2014 and 0.2 mm on 28 August 2014, 22 September 2014 and 16 October There was a general increase in surface PAR recorded at the Darwin Airport, from approximately 30 mol/m 2 /day on 27 May 2014 to 40 mol/m 2 /day by mid-september 2014 (Figure 4-10). Surface PAR then fluctuated between 30 and 40 mol/m 2 /day until the end of the reporting period on 21 October There was one instance when surface PAR decreased to 20 mol/m 2 /day on 19 June 2014 (Figure 4-10). Figure 4-10 BOM Darwin Airport Daily rainfall; and ARM Darwin Airport PAR between 27 May 2014 and 21 October Near-bed Turbidity Time-series measurements of near-bed turbidity for the reporting period are presented in Appendix D and summarised in Table 4-1. Turbidity levels were low to moderate for the Darwin region during this reporting period, with median daily-averaged turbidity levels less than 6.4 NTU for all sites. Overall, turbidity levels were representative of the dry season conditions. Table 4-1 ID Near-bed daily-average turbidity statistics between 27 May 2014 and 21 October 2014 for Woods Inlet (WOD_1), Charles Point (CHP_02), Fannie Bay (FAN_01), East Point (EAS_01), Casuarina Beach (CAS_01) and Lee Point (LEE_01) Mean NTU Median NTU Max NTU SD NTU 25th %ile NTU 75th %ile NTU 90th %ile NTU WOD_01* CHP_ FAN_ EAS_ CAS_ LEE_ * Statistics for Woods Inlet are based on a limited dataset with turbidity data not available from 6 September 2014 to 5 October 2014 (Appendix D). Statistics of daily-averaged turbidity are also visualised through box and whisker plots (Figure 4-11). The lower and upper limits of the box represent the 25 th and 75 th percentiles respectively; the horizontal line represents the median and the box notches the upper and lower 95% confidence levels about the median value. The whiskers extend to the minimum and maximum values defined for a normal distribution (set at three times the interquartile range about the median); and the black crosses are measured outliers beyond these limits. Mean daily-averaged turbidity is indicated by a black dot. Prepared for INPEX Cardno 26

36 The plots illustrate that median daily-averaged turbidity was comparable between East Point, Fannie Bay and Woods Inlet, although the latter was characterised by some excursions above 20 NTU which occurred between 9 October 2014 and 12 October 2014 (Appendix D). Turbidity was lowest and least variable at Lee Point (generally below 1.1 NTU) and Casuarina Beach (generally below 2.8 NTU). Figure 4-11 Box and whisker plot of daily-averaged near-bed turbidity at seagrass sites between 27 May 2014 and 21 October 2014 During the reporting periods prior to P1 and P2 (defined in Section 2.6.2), the daily averaged turbidity was similar or generally lower compared to the corresponding periods in the previous year (as shown in Appendix E and Appendix F by the cumulative distribution functions for each of these time periods). Turbidity during the reporting period prior to P1 (between the end of D7 on 27 May 2014 and the end of P1 on 8 July 2014) had also significantly decreased since the previous reporting period (from D6 on 27 February 2014 to the end of D7 on 27 May 2014) at Charles Point, Lee Point and Woods Inlet, and had remained generally similar at Casuarina Beach, East Point and Fannie Bay (Appendix E). Turbidity had significantly decreased in the reporting period prior to P2 (from the end of P1 on 9 July 2014 to the end of P2 on 21 October 2014) at East Point and Lee Point, and had remained generally similar at all other sites (Appendix F) Underwater Light Climate Temporal dynamics of the underwater light climate at seagrass sites since the commencement of data collection, inclusive of the reporting period, are shown in Figure 4-12 and Figure 4-13 as the daily dose of PAR accumulated between 9:45 and 15:45 for a representative depth of -1 m LAT. The amount of light available for photosynthesis at -1 m LAT during the reporting period ranged from 2.9 mol photons/m 2 /day (25 th percentile at Woods Inlet) to 17.9 mol photons/m 2 /day (75 th percentile at Lee Point) (Table 4-2) and was higher than of the previous reporting period (between survey D6 on 27 February 2014 and D7 on 27 May 2014) which ranged between 1.2 and 10.2 mol photons/m 2 /day (Cardno 2014f). Results indicate that seagrass habitat at Lee Point received the most light, with a mean dose at -1 m LAT of 14.7 mol photons/m 2 /day between 27 May 2014 and 21 October 2014, while Woods Inlet received the least amount of light, with a mean dose of 4.0 mol photons/m 2 /day (Table 4-2). No Survey Area underwent periods of darkness at a depth of -1 m LAT and there was an increase in the amount of light available for photosynthesis between May 2014 and October 2014 (Figure 4-12, Figure 4-13). In particular at Lee Point the daily dose of PAR was consistently greater than 10 mol photons/m 2 /day from mid-july onwards and greater than 5 mol photons/m 2 /day at Casuarina Beach and East Point. Prepared for INPEX Cardno 27

37 Table 4-2 Statistics of the daily dose of PAR (mol photons/m 2 /day) at -1 m LAT between 27 May 2014 and 21 October 2014 Site ID Mean Median Max SD 25th %tile 75th %ile 90th %ile WOD_01* CHP_ FAN_ EAS_ CAS_ LEE_ * Statistics for Woods Inlet are based on a limited dataset with turbidity data not available from 6 September 2014 to 5 October 2014 (Appendix D) Prepared for INPEX Cardno 28

38 Figure 4-12 PAR daily dose between 09:45 and 15:45 at -1 m LAT at Fannie Bay, Lee Point and Woods Inlet from 10 August 2012 to 21 October 2014 Prepared for INPEX Cardno 29

39 Figure 4-13 PAR daily dose between 09:45 and 15:45 at -1 m LAT at Charles Point, East Point and Casuarina Beach from 10 August 2012 to 21 October 2014 Prepared for INPEX Cardno 30

40 4.3 Seagrass Growth Predictions Survey P1 (July 2014) The outcomes of the turbidity-only growth response models for Halophila and Halodule (Equations 2 and 4 Section 2.6.3) for P1 (July 2014) are shown in Figure The models predicted that an increase in the percentage cover of Halodule and Halophila was more likely than a decrease (probability of growth > 0.5) at all Survey Areas, with the exception of Charles Point West for Halophila where the predicted probability of an increase or decrease were similar with a large standard error. Predictions for Halodule were in general agreement with P1 towed-video survey results showing no decrease in Halodule habitat since D7 (May 2014) and an increase at Casuarina Beach (Section ). Predictions for Halophila were also in general agreement with P1 towed-video survey results which showed an increase in Halophila habitat since D7 (May 2014) at Woods Inlet, East Point and Casuarina, and a redistribution of habitat with no change in extent at Charles Point West. An exception to this was the decrease in Halophila habitat observed at Lee Point, which was not predicted by the models. Therefore, this change could not be explained by WQSSMP historical conditions of measured turbidity, which remained generally below 1.1 NTU at this site with no indication of potential delayed influence from dredging activities (Section 4.2.4). Probability of Increase in Cover Halodule - P1 (July 2014) 0.0 Woods Inlet Charles Point West Fannie Bay East Point Casuarina Beach Lee Point Probability of Increase in Cover Halophila - P1 (July 2014) 0.0 Woods Inlet Charles Point West Fannie Bay East Point Casuarina Beach Lee Point Figure 4-14 Probability of increase in percentage cover of Halodule (based on the 14-day and 28-day mean turbidity, Equation 2 Section 2.6.3) and Halophila (based on the 28-day and 84-day mean turbidity, Equation 4 Section 2.6.3) for each Survey Area preceding the P1 (July 2014) survey Prepared for INPEX Cardno 31

41 Outcomes of the second predictive models (Equations 3 and 5, Section 2.6.3) based on the depthdependent light variables preceding P1 (July 2014) are shown in Figure A decline in percentage cover of Halodule since D7 (May 2014) was predicted to occur (probability of growth < 0.5) at depths below +0.5 m LAT at Woods Inlet, 0 m LAT at Fannie Bay, East Point and Charles Point, -2 m LAT at Casuarina and -3 m LAT at Lee Point. Model predictions for Halodule therefore were again consistent with P1 survey results, whereby no loss in habitat was predicted to occur within the depth range previously recorded during D7 (May 2014) (between -1 m LAT at Casuarina Beach and + 2 m LAT at Fannie Bay, Charles Point West and Woods Inlet). Similarly for Halophila the depth-dependent model predicted that an increase in percentage cover was more likely than a decrease within the depth range previously recorded during D7 (between -4.5 m LAT at Lee Point and +1 m LAT at Fannie Bay) Halodule Halodule Halophila Halophila Woods Inlet East Point Probability of Increase in Percentage Cover Fannie Bay Lee Point Charles Point Casuarina Beach Depth (m LAT) Figure 4-15 Probability (±SE) of an increase in the percentage cover predicted for Halophila and Halodule for each Survey Area based on light data over the 28 days preceding the P1 (July 2014) survey Prepared for INPEX Cardno 32

42 4.3.2 Survey P2 (October 2014) The outcomes of the turbidity-only growth response models for Halophila and Halodule (Equations 2 and 4, Section 2.6.3) for P2 (October 2014) are shown in Figure The model for Halodule predicted that an increase in percentage cover was more likely than a decrease (probability of growth > 0.5) at all Survey Areas during P2, and this was in general agreement with P2 towed-video survey results whereby Halodule distribution remained similar between P1 and P2 at Charles Point West, Woods Inlet and Fannie Bay, with some habitat expansion at Casuarina Beach. The models however failed to predict the decline in Halodule habitat observed at East Point. Model predictions for Halophila indicated that an increase in percentage cover was more likely than a decrease at Casuarina and East Point during P2 were consistent with towed-video survey results at these locations (Figure 4-16). Similarly the model predicted that based on turbidity conditions prior to P2, some decline in Halophila habitat was likely at Fannie Bay, also consistent with towed-video survey results (Section 4.1). However, at Charles Point West and Lee Point the model predicted a high likelihood of decrease and increase in percentage cover respectively, and this was in contrast with survey results at these locations (Figure 4-16). Probability of Increase in Cover Halodule - P2 (October 2014) Charles Point West Fannie Bay East Point Casuarina Beach Lee Point Halophila -P2 (October 2014) Probability of Increase in Cover Charles Point West Fannie Bay East Point Casuarina Beach Lee Point Figure 4-16 Probability of increase in percentage cover of Halodule (based on the 14-day and 28-day mean turbidity, Equation 2) and Halophila (based on the 28-day and 84-day mean turbidity, Equation 4) for each Survey Area preceding the P2 (October2014) survey. Predictions were not generated for Woods Inlet due to insufficient turbidity data (Appendix D) Prepared for INPEX Cardno 33

43 Results for the second predictive models (Equations 3 and 5, Section 2.6.3) based on the depth-dependent light variables preceding P2 (October 2014) (Figure 4-17) were again generally consistent with survey results. A decline in percentage cover of Halodule since D7 (May 2014) was predicted to occur (probability of growth < 0.5) at depths below 1 m LAT at Fannie Bay and Charles Point, below -2.5 m LAT at Casuarina Beach and East Point, and 1 m LAT at Lee Point. These depths were outside the depth range of Halodule previously recorded at these Survey Areas, therefore no change in depth distribution was expected (Figure 4-3, Figure 4-4and Figure 4-5). This was consistent with survey results in all Survey Areas except East Point. Similarly changes in the depth distribution of Halophila were neither expected nor observed at Casuarina Beach and East Point. At Lee Point no decrease in Halophila cover was expected at any depth sampled, and this was in contrast with survey results showing a change in the maximum depth limit from -4.5 m LAT during P1 to -1 m LAT during P Halodule Halophila Fannie Bay Casuarina Beach Probability of Increase in Percentage Cover Lee Point Charles Point East Point Depth (m LAT) Figure 4-17 Probability (±SE) of an increase in the percentage cover predicted for Halophila and Halodule for each Survey Area based on light data over the 28 days preceding the P2 (October 2014) survey. Predictions were not generated for Woods Inlet due to insufficient turbidity data (Appendix D) Prepared for INPEX Cardno 34

44 4.4 Potential Dredging-related Influence Underwater Light prior to P1 (July 2014) During two spring tides and the intervening neap tide between 15 May 2014 and 5 June 2014, dailyaveraged near-bed turbidity measured at East Point and Charles Point exceeded the 95 th percentile confidence limit for the empirical turbidity model (based on wave and tide data) for 14 days and 4 days (Cardno 2015). This indicated that dry season dredging activities during Dredging Season Two potentially had a minor short-term influence on water quality at these sites. During the following neap tides centred on the 22 June 2014 turbidity levels at both sites were inside the 95 th percentile confidence limit for the model (Cardno 2015). Although there was no discernible contribution from dredging during periods of elevated turbidity at potential Impact sites, Fannie Bay, Lee Point and Woods Inlet, a conservative approach was adopted in line with the Seagrass DSF (Cardno 2013b) to examine the potential delayed influence from dredging activities on benthic light and seagrass growth at all sites. This was assessed by comparing benthic light and seagrass growth predictions based on the Estimated background and Measured turbidity scenarios prior to P1 (July 2014) as described in Section The former scenario is generated using the Season Two dredging Forecast model excess turbidity, which is a conservative estimate of potential dredging-related excess turbidity, not an actual measure of this contribution. The difference in benthic PAR (28-day moving average at a depth of -1m LAT) between Estimated background and Measured turbidity scenarios is shown in Figure 4-18 for the period preceding P1 (July At Casuarina Beach and Lee Point differences between the two scenarios were minimal (<1 mol photons/m 2 /day) throughout the monitoring period. At Woods Inlet, Fannie Bay and Charles Point the two scenarios differed by approximately 1 to 2 mol photons/m 2 /day prior to the end of EA dredging on 11 June 2014 and typically by less than 1 mol photons/m 2 /day thereafter. At East Point, a difference of approximately 3 mol photons/m 2 /day persisted between the two scenarios until the end of dredging activities, and decreased to less than 1 mol photons/m 2 /day by 24 June 2014 (Figure 4-18). Therefore by P1 (July2014) the 28-day averaged PAR was comparable between the two scenarios, providing no indication of a potential delayed influence of dredging activities on the light history preceding P1 at all seagrass sites (including the potential Impact sites Lee Point, Fannie Bay and Woods Inlet). The Empirical Model scenario differed from both the Measured and Estimated Background scenarios at all sites, providing an estimate of the expected uncertainty in the approach. Prepared for INPEX Cardno 35

45 Figure day moving average of Measured and modelled (Estimated Background and Empirical Model) daily PAR dose at Woods Inlet, Fannie Bay, Lee Point, Casuarina Beach, Charles Point and East Point from 27 May 2014 to 8 July 2014 prior to P1 survey Prepared for INPEX Cardno 36

46 4.4.2 Potential Influence on Seagrass Growth prior to P1 (July 2014) Halophila Model predictions calculated under the Measured (historical turbidity data collected prior to P1 (July 2014)), Empirical (estimated from the tide/wave Empirical model) and the Estimated Background (modelled natural turbidity without dredge contribution) scenarios (Section 2.6.4) are shown in Figure 4-19 and Figure At all Survey Areas the predicted probability of observing an increase in P1 was comparable under the Measured and Estimated Background turbidity scenarios. Both scenarios predicted that an increase in the percentage cover of Halophila was more likely than a decrease (probability of growth > 0.5) at all Survey Areas, with the exception of Charles Point West where an increase and decrease were predicted with similar probability (Figure 4-19). The depth limit (at which the predicted probability of a decline was more likely than growth) was also similar between the two scenarios at all Survey Areas (Figure 4-20). Predicted probabilities of growth for the Empirical scenario were lower than the other two scenarios for all Survey Areas (Figure 4-19). The predicted depth limits for the Empirical scenario were also considerably shallower than the other two scenarios (by approximately 2 m at Woods Inlet and East Point, and up to 8 m at Lee Point) (Figure 4-20). These model outcomes were due to the measured turbidity being often lower (and thus more favourable for growth of Halophila) than predictions from the empirical turbidity model (Cardno 2015). Results indicated no potential influence of dredging-related excess turbidity on the growth of Halophila at any Survey Area Halodule At all Survey Areas, differences in the predicted probability of growth of Halodule were generally minimal between the Empirical, Estimated Background and Measured turbidity scenarios (i.e. error bars overlapping in most cases). There was one exception at Lee Point, where the probability of an increase in Halodule habitat for the Empirical scenario was lower than the other two scenarios (Figure 4-19) with a large difference in the predicted depth distribution (Figure 4-21). This resulted from the measured turbidity often being lower than empirical model predictions (Cardno 2015) which highlights the uncertainty in the modelling approach. The similarity between outcomes form the Estimated Background and Measured scenarios indicate no potential influence of dredging-related excess turbidity on the growth of Halodule at any of the Survey Areas. Prepared for INPEX Cardno 37

47 Probability of Increase in Cover Measured Halophila (P1- July 2014) Estimated Background Empirical Measured Estimated Background Empirical Measured Estimated Background Empirical Measured Estimated Background Empirical Measured Estimated Background Empirical Measured Estimated Background Fannie Bay Woods Inlet Lee Point Casuarina Beach East Point Charles Point West Location / Scenario Empirical Probability of Increase in Cover Halodule (P1- July 2014) Measured Estimated Background Empirical Measured Estimated Background Empirical Measured Estimated Background Empirical Measured Estimated Background Empirical Measured Estimated Background Empirical Measured Estimated Background Fannie Bay Woods Inlet Lee Point Casuarina Beach East Point Charles Point West Location / Scenario Empirical Figure 4-19 Probability of increase in percentage cover of Halophila and Halodule predicted based on the 14-day, 28-day and 84-day mean turbidity for the three turbidity scenarios prior to survey P1 (July 2014) Prepared for INPEX Cardno 38

48 Figure 4-20 Probability of increase in percentage cover of Halophila predicted based on the percentage of days receiving less than 1 mol photons/m 2 /day estimated over 28 days from three turbidity scenarios prior to P1 (July 2014) Prepared for INPEX Cardno 39

49 Figure 4-21 Probability of increase in percentage cover of Halodule predicted based on the percentage of days receiving less than 5 mol photons/m 2 /day estimated over 28 days from three turbidity scenarios prior to P1 (July 2014) Prepared for INPEX Cardno 40

50 4.5 Seagrass Growth Response Data from P1 (July 2014) and P2 (October 2014) were used, together with previous survey data, to update the relationships between changes in seagrass distribution and historical conditions of light and turbidity. Results of logistic regression analyses testing for relationships between change (increases or decreases between consecutive surveys) in cover of Halophila and Halodule and individual light variables are shown in Table 4-3 and Table 4-4 respectively Halophila Changes in the cover of Halophila were significantly correlated with light variables over the short (14 days), medium (28 days) and longer (84 days) time frames (Table 4-3), which was consistent with findings from the preceding four analyses of seagrass and light data, from May 2012 to May 2014 (Cardno 2014c-f). Mean daily turbidity calculated over the 28-day period preceding surveys was again the variable that best accounted for changes in Halophila cover (Nagelkerke pseudo-r 2 value of 0.48), followed by the percentage of days with PAR dose below 1 mol photons/m 2 /day over the same 28-day period (pseudo-r 2 value of 0.22). Table 4-3 Results of logistic regressions between WQSSMP historical turbidity and light variables and changes (increase or decrease between consecutive surveys) in percentage cover of Halophila between all surveys (May 2012 to October 2014) Bold p-values indicate statistically significant correlations Halophila Mean daily turbidity (NTU) % day PAR < 1 mol photons/m 2 /day % day PAR < 3 mol photons/m 2 /day % day PAR < 5 mol photons/m 2 /day PAR Daily Dose (mol photons/m 2 /day) Days p-value Intercept Slope pseudo-r 2 14 < < < < < < < Prepared for INPEX Cardno 41

51 4.5.2 Halodule Consistent with previous data analyses (Cardno 2014c-f), changes in the cover of Halodule were more strongly correlated with light variables calculated over the medium temporal scale (28 days) (Table 4-4), and very weakly with only some light variables calculated over the shorter or longer temporal scales (i.e.14 and 84 days respectively). In addition, the low pseudo-r 2 values indicate that the variability in Halodule cover was poorly explained by the light variables tested. The variables accounting for most of the variability were the daily-averaged turbidity calculated over a 28-day period, which was consistent with D7 (May 2014) results (Cardno 2014f) and the proportion of days receiving less than 5 mol photons/m 2 /day over a 28-day period. The proportion of variability explained by the proportion of days receiving less than 1, 3 and 5 mol photons/m 2 /day were all low (pseudo-r 2 values ranging between 0.05 and 0.07) and had decreased from the D7 (May 2014) results (Cardno 2014f). Table 4-4 Results of the logistic regression between WQSSMP historical turbidity and light variables and changes (increase or decrease) in percentage cover of Halodule between all surveys (May 2012 to October 2014) Bold p-values indicate statistically significant correlations Halodule Daily average turbidity (NTU) % day PAR < 1 mol/m 2 /day % day PAR < 3 mol/m 2 /day % day PAR < 5 mol/m 2 /day PAR Daily Dose (mol/m 2 /day) Days p-value Intercept Slope pseudo-r < < < < < Prepared for INPEX Cardno 42

52 4.6 Updated Growth Response Models The GLM procedure used to derive the predictive models (Equations 2 to 5, Section 2.6.3) following surveys D4 (August/September 2013), D5 (November 2013), D6 (February 2014) and D7 (May 2014) was repeated with the inclusion of P1 (July 2014) and P2 (October 2014) seagrass and water quality data. The updated model coefficients are shown in Table 4-5. The parameters of the models derived from the augmented datasets including P1 and P2 were very similar compared with those following D7 (Cardno 2014f; and provided in Section 2.6.3). The updated model for Halophila comprised the 28-day average turbidity and the proportion of days receiving less than 1 mol photons/m 2 /day calculated over the same time period. In contrast to the D7 update, the 84 day average turbidity was not retained in the current model. In addition, it should also be noted that the pseudo-r 2 of 0.50 (measure of the goodness of fit) for the updated model was lower than that of D7 (0.63), D6 (0.67) and D5 (0.67) and lower than the value of 0.73 for the model based on data to D4, indicating that the inclusion of new data since November 2013 has progressively contributed additional unexplained variability. Similarly to the previous Halodule model, the highest Nagelkerke pseudo-r 2 for the updated model resulted from the 14-day and 28-day average turbidity (R 2 = 0.14). A second, depth-dependent model (based on light variables) was again added to resolve possible depth-related differences in the growth of Halodule (Table 4-5). The predictive variables included in both models for Halodule were the same as for the D7 and D6 updates, with minimal change to the parameter values (< 10% variation) since D7 (Equations 2 and 3 in Section 2.6.3). It should be noted that most of the variability in Halodule cover remains unexplained by the light-related variables tested. Table 4-5 Predictive logistic models for Halodule and Halophila based on all data collected between Baseline (June 2012) and P2 (October 2014) p = probability of increase in seagrass cover Model Pseudo-R 2 Halophila Ln(p / 1-p) = (average turbidity over 28 days) (% of days with PAR dose < 1 mol photons/m 2 /day over 28 days) Halodule Ln(p / 1-p) = (average turbidity over 14 days) (average turbidity over 28 days) 0.14 Ln(p/1-p) = (% of days with PAR dose < 5 mol photons/m 2 /day over 28 days) Prepared for INPEX Cardno 43

53 5 Discussion Seagrass monitoring has been undertaken to investigate mimimal predicted impacts from the Project s dredging activities on seagrass communities. Ten towed-video mapping surveys have been undertaken during monitoring, including a Baseline survey (B1, June 2012) prior to the commencement of dredging activities, and seven surveys undertaken periodically throughout the Dredging Phase of the Project (D1: October 2012, D2: February 2013, D3: May 2013, D4: August/September 2013, D5: November 2013, D6: February 2014, D7: May 2014). Two towed-video mapping surveys were conducted during the Postdredging Phase of the Seagrass Monitoring Program following the end of EA and GEP dredging activities on 11 June 2014 and 12 July 2014 respectively (P1: 3 July 2014 to 9 July 2014 and P2: 15 October 2014 to 21 October 2014). This report outlines the findings of P1 (July 2014) and P2 (October 2014) and examines changes in the distribution of the dominant genera of seagrass in the Darwin Outer region (Halodule and Halophila) since completion of survey D7 on 26 May Changes are compared to natural seasonal changes observed throughout monitoring and are evaluated together with historical conditions of light and turbidity to assess the risk of a potential delayed impact on seagrass habitats from dredging activities prior to the end of EA and GEP dredging. Throughout the Dredging and Post-dredging Phase monitoring there has been no evidence of potential influence from Project dredging activities on seagrass distribution. Changes in the distribution and percentage cover of Halodule and Halophila have been primarily driven by the influence of climatic seasons (dry and wet season). 5.1 Seasonal Patterns and Inter-specific Differences in Growth of Halophila and Halodule Throughout monitoring the towed-video mapping surveys have shown an overall seasonal cycle of decline and recovery of Halodule and Halophila in Darwin Outer that is consistent with what is anticipated for these genera in the wet tropics (Short et al. 2010a, b). The mapping surveys have also shown that there are distinct genus-specific spatial and temporal patterns for Halodule and Halophila in addition to the overarching seasonal cycles of distribution. Halodule habitat has generally been found in the intertidal and shallow subtidal zone in Darwin Outer Survey Areas (between -1 m and +2 m LAT) with percentage cover ranging between approximately 5% and 10% to 20% cover with the lowest values recorded during wet season surveys D2 (February 2013) and D6 (February 2014, although data was collected only at Fannie Bay and Woods Inlet in this survey) (Cardno 2014f). Despite seasonal changes in percentage cover, the spatial distribution of Halodule habitat has been relatively stable with the genus found in similar locations in each of the Survey Areas across all surveys. By contrast, Halophila habitat has generally been located in deeper subtidal waters and at times in the intertidal zone (between -9.5 m and +2 m LAT) and there was generally very little overlap between patches of the two genera (Figure 4-1, Figure 4-2, Cardno 2014f). Halophila has also shown considerably more seasonality, with a general expansion of distribution spatial extent during the dry season and extreme reduction during the wet season. In particular it was absent from all Survey Areas completed during D2 (February 2013) and D6 (February 2014). 5.2 Post-dredging Distribution and Cover of Halophila Changes in the spatial distribution of Halophila habitat observed during P1 (July 2014) and P2 (October 2014) were consistent with changes previously observed during the 2012 dry season (surveys B1 in June 2012 and D1 in October 2012) and the 2013 dry season (surveys D3 in May 2013 and D4 in August/September 2013) (Figure 4-1 and Figure 4-2). Halophila habitat expanded at most Survey Areas between D7 (May 2014) and P1 (July 2014). This was most notable at Casuarina Beach, East Point and Woods Inlet where Halophila had not been recorded during D7 and was found six weeks later to cover areas of approximately 337 ha, 181 ha and 11 ha, respectively, during P1. The absence of Halophila from these areas during D7 (following the 2013/2014 wet season) was consistent with findings from the 2012/2013 wet season whereby Halophila was absent from all Prepared for INPEX Cardno 44

54 Survey Areas during D2 (February 2013). The subsequent habitat expansion during P1 were similar to previous dry season results during D1 (October 2012) at Woods Inlet, D3 (May 2013) at Casuarina Beach and D4 (August/September 2013) at East Point (Figure 4-1 and Figure 4-2) and were consistent with dry season growth patterns of Halophila in the wet tropics (Short et al. 2010b). Conditions of turbidity and benthic light prior to P1 were generally representative of the dry season, with daily-averaged turbidity remaining below 7.0 NTU and mean PAR at -1m LAT ranging between 4.0 and 10.9 mol photons/m 2 /day at these sites. Consistent with mapping survey results, outcomes of the seagrass growth response models predicted these conditions to be largely favourable for growth of Halophila (Figure 4-14). By contrast at Fannie Bay and Charles Point West the extent and distribution of Halophila habitat remained relatively unchanged during P1 (approximately 43 ha and 4 ha respectively), and a decrease was recorded in the Lee Point Survey Area from approximately 1,103 ha to 277 ha. These results could not be attributed to an unfavourable light climate, as these sites were also characterised by dry season conditions of turbidity and light, resulting in predictions of likely growth of Halophila by the seagrass growth response models (Figure 4-14). Note that a similar result was found during D5 (November 2013) whereby Halophila habitat had also declined during the dry season at Lee Point, following a large expansion between D2 (February 2013) and D3 (May 2013). Such results highlight the dynamic nature of Halophila distribution, which may also be influenced by additional factors not considered in the light-based models, such as changes in nutrient availability and temperature, natural shifts in sediments, and possibly small-scale spatial variability in turbidity not accounted for by turbidity measured at individual water quality stations located near or within the Survey Area. Models can also inform on the potential impact of dredging-related excess turbidity on the light history. However, modelling for P1 (July 2014) indicated that estimates of dredging-related excess turbidity were unlikely to influence light conditions and growth of Halophila at these Survey Areas (Section 4.4.2). Risk assessment analyses based on records of turbidity, seagrass distribution maps and outcomes of the seagrass response models therefore provided no indication of a potential delayed influence of dredging activities on Halophila habitat distribution during P1 in any Survey Area. During P2 (October 2014) there was a further expansion of Halophila habitat at most Survey Areas and most notably at Casuarina Beach and East Point where the estimated habitat extent increased approximately three-fold to 1,103 ha and 527 ha, respectively. There was also a notable increase in the percentage cover of Halophila at all Survey Areas, from values up to 10% to 20% cover during P1 (Appendix A) to 40% cover during P2, with small patches at Lee Point, Charles Point West and East Point recording up to 60% cover (Appendix B). Dry season conditions of low turbidity and increased light persisted between P1 and P2 and again resulted in the seagrass response models predicting that continued growth of Halophila was likely (Figure 4-16). A decline in Halophila habitat was however recorded in the northern portion of the Fannie Bay Survey Area during P2. A similar change in distribution of Halophila during the dry season had previously been observed at Fannie Bay for comparable periods between D3 (May 2013) and D4 (August/September 2013) (Figure 4-1), even though light and turbidity conditions had been considered generally favourable for growth during this period (Cardno 2014c). Similarly to the decline observed at Lee Point during P1, the change at Fannie Bay could not be attributed to unfavourable light conditions and instead further highlight the dynamic nature of Halophila growth patterns. In summary, patterns of decline and recovery observed since monitoring began in June 2012 were consistent with seasonal growth patterns of Halophila in the wet tropics and were similar to large temporal changes observed in the Kimberley region between November 2007 and December 2008 (Masini et al. 2009). Results from P1 (July 2014) conducted shortly (one month) after the end of EA dredging operations on 11 June 2014 and P2 (October 2014) conducted four and three months after the end of EA and GEP (12 July 2014) dredging operations respectively, showed a general dry season expansion of Halophila habitat and provided no indication of potential delayed influence of dredging-related excess turbidity on the growth of Halophila. 5.3 Post-dredging Distribution and Cover of Halodule During P1 (July 2014) Halodule habitat was mapped in the same general areas compared to D7 (May 2014), except at Lee Point where two additional patches were recorded and at Casuarina Beach where Prepared for INPEX Cardno 45

55 considerable habitat expansion was recorded (Figure 4-2). Halodule habitat reached an estimated area of approximately 1,438 ha which was comparable to surveys prior to D5 (November 2013) (Figure 4-1, Figure 4-2, Appendix A). Mapping survey results from D7 (May 2014) revealed that the extent of Halodule habitat at Casuarina Beach had decreased by a third since D5 (November 2013). As discussed previously (Cardno 2014f), this was most likely due to wind and wave action from episodic weather events in late January 2014 to early February 2014 caused by TS05U (from 13 January 2014 to 22 January 2014) and TC Fletcher (from 30 January 2014 to 11 February 2014), resulting in strong waves and littoral mixing in shallow seagrass habitats for an extended period of time, potentially limiting light at the seafloor through sediment resuspension, smothering or directly damaging/removing seagrass in the area. The considerable expansion of Halodule habitat at Casuarina Beach in the six weeks between D7 (May 2014) and P1 (July 2014) were consistent with dry season conditions of low turbidity and high benthic light and with predictions from the seagrass response models (Figure 4-14). This habitat expansion potentially occurred through growth from seeds stored in the sediment, fragments transported by currents, or vegetative growth from neighbouring habitats (outside of the Survey Area) (Birch and Birch 1984; Larkum et al. 2006). During P2 (October 2014) Halodule habitat was again mapped in the same general areas as in previous surveys and this was consistent with 2012 (D1) and 2013 (D3 and D4) dry season survey findings (Figure 4-1 and Figure 4-2). The distribution of Halodule habitat has generally remained consistent throughout monitoring and has shown considerably less seasonal variability compared to Halophila habitat (Cardno 2014f). Halodule habitat was however not found in the East Point Survey Area during P2, and this decline since P1 (July 2014) was not predicted by the seagrass response model for Halodule based on continued dry season turbidity and light conditions that were considered favourable for growth. Halodule habitat had been previously absent from the East Point Survey Area during B1 (June 2012) before being mapped in the south-eastern portion of the Survey Area during D1 (October 2012). This may indicate movement of habitat edges outside of the Survey Area boundaries. In any case these changes occurred during the dry season and indicate a level of natural variability in Halodule that remains unexplained by historical conditions of light and turbidity. In addition to potential contributing factors noted above for Halophila (nutrients and temperature), Halodule has a primarily intertidal distribution and may be more affected by wave action, increased mixing in shallow areas and episodic exposure to air at low spring tides. It may also respond to changes in light over longer timeframes than considered here. As for Halophila, P1 and P2 results provided no indication of potential delayed influence of dredging-related excess turbidity on the growth of Halodule following the end of EA and GEP dredging operations. Throughout the monitoring program, despite some natural seasonal and spatial variability in the distribution and coverage of Halodule there was no evidence to suggest Project dredging influenced seagrass within Darwin Outer Survey Areas. 5.4 Development of Predictive Seagrass Growth Models To improve the understanding of seagrass dynamics in the Darwin region and to investigate the potential drivers of change in Halophila and Halodule habitats, an analysis was conducted following D3 (May 2013) on metocean, water quality and seagrass distribution data collected between May 2012 and May A GLM (Quinn and Keough 2002) procedure was used to identify light and turbidity variables that may correlate with either increases or decreases in the cover of each genus between surveys and to identify relevant timeframes of exposure (14 days, 28 days or 84 days). The procedure was repeated following each subsequent survey (D4 to P2) resulting in successive updates to the seagrass response models. Changes in Halophila cover between June 2012 (B1) and October 2014 (P2) were best accounted for by the mean daily turbidity calculated over the 28-day period preceding surveys (Nagelkerke pseudo-r 2 value of 0.48), followed by the percentage of days with PAR dose below 1 mol photons/m 2 /day over the same 28-day period (pseudo-r 2 value of 0.22) (Table 4-3). These two variables have consistently been the best descriptors of change for Halophila and were included in all seagrass response models since D3 (Cardno 2014c-f). The D3 version of the model also included the 14-day average turbidity (Appendix A, Cardno 2014c), while the D5, D6 and D7 updates included the 84-day average turbidity (Cardno 2014d-f). Successive updates to the models indicate that changes in Halophila cover over time were explained relatively well by the mean daily turbidity and percentage of low light days over the medium term temporal scale (28-days). However, the inclusion of new data during each survey since D4 has progressively Prepared for INPEX Cardno 46

56 decreased the goodness of fit of each model (with the pseudo-r 2 value decreasing from 0.73 for the D4 model to 0.50 for the final P2 model update. Therefore the inclusion of new data since November 2013 (D5) has progressively contributed variability that is not explained by the variables incorporated in the model. Changes in Halodule cover between June 2012 (B1) and October 2014 (P2) were more strongly correlated with the daily-averaged turbidity calculated over a 28-day and a 14-day period and the proportion of days receiving less than 5 mol photons/m 2 /day calculated over a 28-day period. The pseudo-r 2 value of the final Halodule response model (0.14) and all previous models (range 0.11 to 0.22) was low (Table 4-4). Such results indicate that throughout the monitoring program the majority of the variability in Halodule cover remains unexplained by the light and turbidity variables included in the model. The high level of spatial and temporal variability in the percentage cover and distribution of both Halophila and Halodule throughout the monitoring program has posed challenges to the detection and assessment of potential dredging-related impacts on seagrasses in the Darwin Outer region. In particular, seasonal cycles of decline and recovery of seagrasses in the wet tropics preclude the traditional monitoring approaches based on the detection of change assessed against conservative management triggers. The Seagrass Monitoring Program was adapted to suit the naturally dynamic nature of the system within the Darwin region. Broad-scale mapping of seagrass habitat and semi-quantitative towed-video techniques were found to be more suitable than localised quantitative techniques (such as the drop camera method, Cardno 2013a) to assess environmentally significant change in such a dynamic system. The adoption of light based modelling techniques has provided a risk assessment methodology that takes into account the natural cycles of decline and recovery of highly variable tropical species such as Halophila and Halodule. Prepared for INPEX Cardno 47

57 6 Conclusion Consistent with what is anticipated for seagrasses in the wet tropics, the Seagrass Monitoring Program detected large natural changes in the percentage cover, distribution and extent of the dominant seagrass genera, Halodule and Halophila, in Darwin Outer from June 2012 (B1) to October 2014 (P2). There was no evidence to suggest Project dredging and construction activities contributed to these changes to seagrass habitat distribution rather they generally conform to a natural seasonal cycles of decline (wet season) and recovery (dry season). The distribution of Halophila in Darwin Outer has been highly variable throughout the monitoring program and has shown considerable natural seasonality, with a general expansion of extent during the dry season and reduction during the wet season. Overall, the cycle of decline and recovery of Halophila extent over the 2012/2013 and 2013/2014 wet seasons were consistent with expectations from the highly dynamic nature of similar seagrass habitats in the wet tropics (Short et al. 2010a,b) and can be considered part of a natural seasonal cycle. The largest patches of Halophila mapped were on the east side of Darwin Outer off Casuarina Beach and to the east of Lee Point in Darwin Outer. Patches of Halophila were located in slightly deeper water (between +2.0 m and -9.5 m LAT) than Halodule (between -1.0 m and +2.0 m LAT) with very little overlap between patches of the two genera. Although the extent of Halodule has changed naturally since the commencement of monitoring, changes have not been to the extent observed for Halophila and have occurred mainly as changes to the size of the same patches rather than a redistribution of patches (as occurred for Halophila). The largest patch of Halodule mapped was located off Casuarina Beach, mainly in the intertidal area. In contrast to Halophila, survey results since the start of the monitoring program have highlighted that changes to percentage cover and spatial distribution of Halodule are less sensitive than Halophila to the large fluctuations in turbidity and light conditions measured in the Darwin Outer region. In fact, areas of Halodule have persisted throughout the wet and dry seasons without evidence of a strong decline and recovery, despite extreme changes in turbidity and benthic light. An exception to this persistence was Casuarina Beach where the extent of Halodule habitat decreased by a third in May 2014 (most likely due to wind and wave action from episodic weather events) and recovered by P1 (July 2014). Such a recovery is consistent with known characteristics of Halodule, as a fast-growing early coloniser known to survive well in unstable environments and to recover rapidly after disturbances (Short et al 2010a). Analyses of towed-video transect data from all seagrass surveys, together with light and turbidity monitoring data, has contributed to the explanation of patterns of seagrass decline and growth observed between May/June 2012 (B1) and October 2014 (P2). In general, changes in Halophila cover over time were explained relatively well by the selected light-related variables (mean daily turbidity and percentage of low light days over a 28-day period). The variables that were found to best explain changes in Halodule cover were the 14-day and 28-day average turbidity values. Most of the variability in Halodule cover remains unexplained by the light-related variables tested during the monitoring program. The extent reduction between D5 (November 2013) and D7 (May 2014) suggests that other factors related to adverse metocean conditions, such as smothering or direct damage/removal, are likely to affect the growth and persistence of Halodule in Survey Areas in Darwin Outer. Model predictions contributed to the understanding of the broad-scale response of seagrass habitat in Darwin Outer to seasonal changes in light climate and to identify light and turbidity conditions that could result in changes to seagrass spatial extent and distribution (particularly for Halophila). Predictions from seagrass response models based on dredging and background conditions of turbidity indicated no delayed influence of dredging-related excess turbidity on Halodule or Halophila growth in the Survey Areas Postdredging. Prepared for INPEX Cardno 48

58 7 Acknowledgments This report was written by Dr Isabel Jimenez, and reviewed by Dr Lachlan Barnes. Data analysis and production of figures was undertaken by Dr Andrea Nicastro, Dr Isabel Jimenez, Phebe Bicknell, Christopher Beadle, Ben Brayford and Shani Archer. Field work for the Post-dredging survey P1 (July 2014) and P2 (October 2014) was undertaken by Ben Piek, Ade Lambo and Nick Veitch. Prepared for INPEX Cardno 49

59 8 References Birch,W.R. and Birch, M. (1984). Succession and pattern of tropical intertidal seagrasses in Cockle Bay, Queensland, Australia: a decade of observations. Aquatic Botany, 19, pp Cardno (2013a). Seagrass Monitoring Program Baseline Report. Report for INPEX. Cardno (NSW/ACT) Pty Ltd, Sydney. Cardno (2013b). Bimonthly Seagrass Monitoring Report- Dredging Report 1. Prepared for INPEX. Cardno (NSW/ACT) Pty Ltd, Sydney. Cardno (2013c). Seagrass Decision Support Framework Ichthys Project Nearshore Environmental Monitoring Program. Prepared for INPEX, November Cardno (2013d). Water Quality and Subtidal Sedimentation Monitoring Program Baseline Report. Prepared for INPEX. Cardno (NSW/ACT) Pty Ltd, Sydney. Cardno (2014a). Ichthys Nearshore Environmental Monitoring Plan, Rev 5. Prepared for INPEX. Cardno (NSW/ACT) Pty Ltd, Sydney. Cardno (2014b) Darwin Harbour A summary of the Ichthys LNG Project Nearshore Environmental Monitoring Program. Prepared for INPEX, Cardno (NSW/ACT) Pty Ltd, Sydney. Cardno (2014c). Quarterly Seagrass Monitoring Report Dredging Report 4 Ichthys Project Nearshore Environmental Monitoring Program. Prepared for INPEX. Cardno (NSW/ACT) Pty Ltd, Sydney. Cardno (2014d). Quarterly Seagrass Monitoring Report Dredging Report 5 Ichthys Project Nearshore Environmental Monitoring Program. Prepared for INPEX. Cardno (NSW/ACT) Pty Ltd, Sydney. Cardno (2014e). Quarterly Seagrass Monitoring Report Dredging Report 6 Ichthys Project Nearshore Environmental Monitoring Program. Prepared for INPEX. Cardno (NSW/ACT) Pty Ltd, Sydney. Cardno (2014f). Quarterly Seagrass Monitoring Report End of Dredging Report Ichthys Project Nearshore Environmental Monitoring Program. Prepared for INPEX. Cardno (NSW/ACT) Pty Ltd, Sydney. Cardno (2015). Water Quality and Subtidal Sedimentation End of Dredging Report Ichthys Project Nearshore Environmental Monitoring Program. Prepared for INPEX. Cardno (NSW/ACT) Pty Ltd, Sydney. Chartrand, K. M., Rasheed, M., Petrou, K. and Ralph, P. (2012). Establishing tropical seagrass light requirements in a dynamic port environment. 12 th International Coral Reef Symposium, Cairns, Australia. 15B Seagrasses and seagrass ecosystems. Collier, C. J., Waycott, M. and McKenzie, L. J. (2012). Light thresholds derived from seagrass loss in the coastal zone of the northern Great Barrier Reef, Australia. Ecological Indicators. pp Geo Oceans (2012a). : Seagrass Baseline and Marine Habitat Mapping. Survey June 2012: Technical Report. Prepared for Cardno, on behalf of INPEX. Geo Oceans (2012b). : Seagrass Habitat Monitoring Survey October 2012: Technical Report. Prepared for Cardno, on behalf of INPEX. Geo Oceans (2013a). Towed Camera Seagrass Monitoring Method Statement February Ichthys Nearshore Environmental Monitoring Program. Prepared for Cardno, on behalf of INPEX. Geo Oceans (2013b). : Seagrass Habitat Monitoring Survey May Ichthys Nearshore Environmental Monitoring Program. Prepared for Cardno, on behalf of INPEX. Geo Oceans (2013c). : Seagrass Habitat Monitoring Survey September Prepared for Cardno, on behalf of INPEX. Geo Oceans (2014a) : Seagrass Habitat Monitoring Survey February Prepared for Cardno, on behalf of INPEX. Geo Oceans (2014b) : Seagrass Habitat Monitoring Survey May Ichthys Nearshore Environmental Monitoring Program. Prepared for Cardno, on behalf of INPEX. INPEX (2011a). Ichthys Gas Field Development Project, Draft Environmental Impact Statement. INPEX Operations Australia Pty Ltd. INPEX (2011b). Ichthys Gas Field Development Project, Supplement to the Draft Environmental Impact Statement. INPEX Operations Australia Pty Ltd. INPEX (2012). Dredging and Spoil Disposal Management Plan East Arm (Rev 1). INPEX (2013). Dredging and Spoil Disposal Management Plan East Arm (Rev 4). Prepared for INPEX Cardno 50

60 INPEX (2014). Dredging and Spoil Disposal Management Plan Gas Export Pipeline (Rev 7). Larkum, A.W.D., Orth, R.J. and Duarte, C.M. (2006). Seagrasses: Biology, Ecology and Conservation. Springer, Dordrecht Lee, K. S., Park, S. R. and Kim, Y. K. (2007). Effects of irradiance, temperature, and nutrients on growth dynamics of seagrass: A review. Experimental Marine Biology and Ecology. pp Masini, R. J., Sim, C. B. and Simpson, C. J. (2009). Protecting the Kimberley: A synthesis of scientific knowledge to support conservation management in the Kimberley region of Western Australia. Department of Environment and Conservation, Western Australia. McKenzie, L. J. (2003). Draft guidelines for the rapid assessment of seagrass habitats in the western Pacific (QFS, NFC, Cairns), pp. 43. Quinn, G. P. and Keough, M. J. (2002). Experimental design and data analysis for biologists. Cambridge University Press, Cambridge, UK. Short, F. T., Carruthers, T. J. R., Waycott, M., Kendrick, G. A., Fourqurean, J. W., Callabine, A., Kenworthy, W. J. and Dennison, W. C. (2010a). Halodule uninervis. In: IUCN IUCN Red List of Threatened Species. Version Available from: Downloaded on 18 September Short, F. T., Carruthers, T. J. R., Waycott, M., Kendrick, G. A., Fourqurean, J. W., Callabine, A., Kenworthy, W. J. and Dennison, W. C. (2010b). Halophila decipiens. In: IUCN IUCN Red List of Threatened Species. Version Available from: Downloaded on 18 September Prepared for INPEX Cardno 51

61 Ichthys Nearshore Environmental Monitoring Program APPENDIX A JULY 2014 TOWED-VIDEO HABITAT MAPPING TECHNICAL REPORT Prepared for INPEX Cardno 52

62 Ichthys Nearshore Environmental Monitoring Program Seagrass Habitat Monitoring July 2014 Technical Report Prepared for Cardno on behalf of INPEX Rev 0 September 2014 Document code: INPICHSGR.904

63 Prepared for Cardno Prepared by Geo Oceans Pty Ltd Seagrass Habitat Monitoring July 2014 Technical Report Document code: INPICHSGR.904 Revision History Rev Authors Distribution Recipients No. Copies & Format Review Date Reviewer Review type Date A1 Ben Piek I. Jimenez (Cardno) 1 x e-copy 22/07/2014 A. Lambo N. Veitch Technical /Editorial 22/07/2014 A2 Ben Piek I. Jimenez (Cardno) 1 x e-copy 04/08/2014 I. Jimenez (Cardno) Technical /Editorial 04/08/2014 A3 Ben Piek I. Jimenez (Cardno) 1 x e-copy 15/08/2014 J. Lamb Editorial 19/08/2014 B Ben Piek 0 Ben Piek J. Lamb (Cardno) J. Lamb (Cardno) 1 x e-copy 03/09/2014 A. Nicastro Technical 02/09/ x e-copy 10/09/2014 J. Lamb Editorial 10/09/2014 Disclaimer Geo Oceans Pty Ltd (Geo Oceans) has prepared this report at the request of Cardno on behalf of INPEX. This document is subject to and issued in accordance with the agreed terms and scope between the above listed companies. Copyright Geo Oceans Pty Ltd 2014.

64 EXECUTIVE SUMMARY A Seagrass Monitoring Program has been developed to detect potential changes in seagrass and to infer whether any changes are a result of dredging and/or spoil disposal activities associated with the Ichthys LNG Project (the Project) in Darwin Harbour. The Nearshore Environmental Monitoring Plan (NEMP, Cardno 2014) sets out a framework for the Seagrass Monitoring Program, including towed camera surveys, to assess the distribution of seagrasses in Darwin Harbour. This report describes the results of the July 2014 field survey, which was completed from 3 July 2014 to 9 July The survey involved the use of a towed camera system and customised data analysis software to record geo-referenced habitat point data, and video and still images within 153 Sample Areas at all Survey Areas in and around the Darwin region. The total spatial extent of seagrass (Halodule and Halophila combined) mapped during the July 2014 survey was 2,500 hectares (± 518 ha reliability estimate). Seagrass was present at all Survey Areas and was observed at depths between +2.2 m and -5.5 m Lowest Astronomical Tide (LAT). The spatial extent of Halodule mapped during the July 2014 survey was 1,731 ha (± 458 ha reliability estimate), with Halodule recorded in all Survey Areas. Halodule cover was generally sparse ( 10%), with cover up to 20% at Casuarina Beach, Charles Point, Fannie Bay and Woods Inlet. Halophila was also recorded in all Survey Areas and covered a total area of 853 ha (± 370 ha reliability estimate). Halophila was generally sparse, with cover typically less than 10%, but reached up to 60% cover in patches towards the northern end of Fannie Bay.

65 Table of Contents 1.! Introduction... 1! 1.1.! Existing Data... 1! 1.2.! Objectives... 2! 2.! Methods... 3! 2.1.! Field Data Collection... 3! 2.2.! Equipment... 3! 2.3.! Survey Design... 3! ! Survey Areas... 3! ! Sample Areas... 4! 2.4.! Image Classification... 7! 2.5.! Data Processing... 7! ! Point Data Processing... 7! ! Interpolation... 8! 2.6.! Spatial Accuracy Assessment... 9! ! Reliability Estimate... 9! 2.7.! QA/QC... 10! 3.! Results... 11! 3.1.! Seagrass Distribution and Habitat Extent... 11! 4.! Discussion... 20! 5.! References... 21! List of Figures Figure 1 Geo Oceans topside control unit being operated during survey operations... 3! Figure 2 Seagrass Survey 9 - July 2014 survey design... 6! Figure 3. Percentage cover modelled values... 9! Figure 4. Presence and absence interpolation modelled values... 9! Figure 5 Example images of: (a) Halodule at Charles Point; and (b) Halophila at Fannie Bay from July ! Figure 6 Example of dead epiphyte-covered Halophila at East Point over consecutive surveys during: a) May 2014; and b) July ! Figure 7 Seagrass Survey 9 July 2014 Total Seagrass Distribution... 15!

66 Figure 8 Seagrass Survey 9 July 2014 Halophila Distribution... 16! Figure 9 Seagrass Survey 9 July 2014 Halodule Distribution... 17! Figure 10 Seagrass Survey 9 July 2014 Halophila Cover... 18! Figure 11 Seagrass Survey 9 July 2014 Halodule Cover... 19! List of Tables Table 1 Number of Sample Areas surveyed in each Survey Area in July ! Table 2 Depth range (LAT) of seagrass... 13! List of Appendices Appendix 1 Spline Interpolation Settings and Parameters Appendix 2 Maps of seagrass distribution in June 2012, October 2012, February 2013 and May

67 1. INTRODUCTION INPEX is the operator of the Ichthys LNG Project (the Project). The Project comprises the development of offshore production facilities at the Ichthys Field in the Browse Basin, some 820 km west-south-west of Darwin, an 889 km long subsea gas export pipeline (GEP) and an onshore processing facility and product loading jetty at Bladin Point on Middle Arm Peninsula in Darwin Harbour. To support the nearshore infrastructure at Bladin Point, dredging works were carried out to extend safe shipping access from near East Arm Wharf to the new product loading facilities at Bladin Point, supported by piles driven into the sediment. A trench was dredged to seat and protect the GEP for the Darwin Harbour portion of its total length. Dredged material was disposed at the spoil ground located approximately 12 km north-west of Lee Point. A detailed description of the dredging and spoil disposal methodology is provided in Section 2 of the East Arm (EA) Dredging and Spoil Disposal Management Plan (DSDMP) (INPEX 2013) and GEP DSDMP (INPEX 2014). Following the Draft Environmental Impact Statement (EIS) (INPEX 2010) and Supplementary EIS (SEIS) (INPEX 2011), the Project was approved subject to conditions that included monitoring for potential effects of dredging or spoil disposal on local ecosystems (including seagrasses) and potentially vulnerable populations. Sedimentation and increased turbidity have the potential to impact seagrasses by limiting the light available for photosynthesis, thus affecting their growth rate and, ultimately, seagrass survival. A monitoring program was therefore set up to examine the potential impact on seagrasses in and around the Darwin Harbour region from dredging and spoil disposal activities associated with the Project. The aim of the Seagrass Monitoring Program is to detect changes in seagrass distribution and habitat extent from potential dredge impacts. The Seagrass Monitoring Program (Appendix B of the Nearshore Environmental Monitoring Plan (NEMP) (Cardno 2014)) included mapping surveys of the areal extent of seagrass habitat and distribution of seagrass habitat twice a year in the wet and dry season (i.e. quarterly). However, the scope of the mapping surveys has since been increased to undertake broad-scale semiquantitative seagrass mapping surveys using the methods described in the INPEX Seagrass Habitat Monitoring October 2012 Survey technical report (Geo Oceans 2012a). A towed video seagrass habitat mapping survey was undertaken in July 2014 as part of Seagrass Monitoring Program to assess the distribution and habitat extent of seagrass in the Darwin Harbour region following completion of Project dredging activities. This report describes the survey design, seagrass distribution and habitat extent Existing Data INPEX submitted a Draft EIS (INPEX 2010) and SEIS (INPEX 2011) as part of the approval processes for the Project. To support the EIS, Geo Oceans (2011a) collated and classified available marine habitat information to produce maps showing the distribution of benthic habitats in the waters surrounding Darwin Harbour. This included a towed camera survey to collect marine habitat data from Darwin Harbour to Adam Bay in December 2010 (Geo Oceans 2011a) using similar methods to those employed for the current survey. The soft sediments in the sheltered bays between Shoal Bay and Fannie Bay supported communities that were dominated by Halodule spp. (e.g. Halodule uninervis), with Halophila sp. (e.g. Halophila decipiens) and Syringodium sp. also present. The majority of the seagrass habitat was found on the soft sediments in the lower littoral intertidal zone between 0 m and +1 m (Lowest Astronomical Tide (LAT)), but sparse communities extended into the shallow subtidal coastline from Shoal Bay to Fannie Bay in water depth less than -3 m LAT. There Page 1 of 24

68 was no seagrass recorded in Darwin Harbour Inner (i.e. demarcation boundary extends approximately northeast across the harbour mouth from Talc Head to Emery Point, Darwin). Habitat surveys conducted in Darwin Outer by Geo Oceans prior to the start of the Project (2011a, 2011b), and nearshore environmental monitoring undertaken since June 2012 (Geo Oceans 2012a, 2012b, 2012c, 2012d, 2012e, 2012f, 2013a, 2013b, 2013d, 2013e, 2014a and 2014b), have found Halophila spp. in particular to be ephemeral and to exhibit large changes in spatial distribution and percentage cover over relatively short time periods (i.e. weeks). Although large changes in percentage cover have also been recorded in Halodule spp. habitat, its spatial distribution has been more consistent and, in contrast to Halophila spp., has persisted through the wet season Objectives The objectives of this survey were to: Map the distribution of seagrass at the defined Survey Areas using methods that can be repeated and compared over time; and Assess changes in seagrass distribution and extent between the June 2012, October 2012, February 2013, May 2013, August 2013, November 2013, February 2014, May 2014 and July 2014 surveys. Page 2 of 24

69 2. METHODS 2.1. Field Data Collection The July 2014 survey was undertaken over one neap tide period by one field team from 3 July 2014 to 9 July 2014 as part of the quarterly seagrass monitoring program. The survey was performed during a neap tide to maximise water visibility for image capture. Data were collected in all Sample Areas in each Survey Area shown in Figure Equipment Geo Oceans customised Visual Basic software program (GO Visions) and towed camera system (Figure 1) recorded geo-referenced habitat point data, video and still images within each Transect Area using the same equipment and software employed in the previous towed camera surveys (Geo Oceans 2011a, 2012a, 2012b, 2012c, 2012e, 2013a, 2013b, 2013d, 2013e, 2014a and 2014b). The location coordinates of the data were captured and recorded using a differential global positioning system (DGPS) mounted to the vessel and encoded to all of the data using a topside control unit. Figure 1 Geo Oceans topside control unit being operated during survey operations 2.3. Survey Design Survey Areas The Survey Area boundaries were defined using a combination of existing data (including bathymetric contours, habitat maps and seagrass distribution data) and logistical constraints. Consequently, the following six Survey Areas were defined (Figure 2): Page 3 of 24

70 Charles Point West, located 3 km east of Charles Point; Woods Inlet, located 2.5 km south of Mandorah; Fannie Bay, located in Fannie Bay; East Point, located immediately north of East Point; Casuarina Beach, located near Casuarina Beach; and Lee Point, located 1.5 km east of Lee Point. The first surveys recorded seagrass present in waters deeper than +2.2 m LAT (Geo Oceans 2012e). Existing elevation data were used to create a +2.2 m LAT bathymetric contour line. This line was used to define the inshore distribution of the Survey Areas. The outer depth limit of the seagrass in each Survey Area was determined using the habitat point data collected during this survey (Geo Oceans 2012a). Reef habitat areas that were mapped in the first survey (Geo Oceans 2012e) and the Project Restricted Work Areas provided to Geo Oceans by Cardno were excluded from the Survey Areas. Transects within each of the Survey Areas were located within pre-defined Sample Areas (Table 1) Sample Areas One hundred and fifty-nine towed camera transects of a minimum 50 m in length were surveyed inside the pre-defined Sample Areas (Table 1). For consistency among surveys, July 2014 data were collected within the same Sample Areas previously surveyed at all Survey Areas. Each Sample Area was a circular area with a 50 m radius. One transect was completed inside each Sample Area. This survey design allowed enough area and flexibility for safe and efficient vessel navigation and positioning when capturing the data. The differences in transect density within the Survey Areas is a result of the differences in habitat type and complexity between these areas. The larger Survey Areas, such as Casuarina Beach and Lee Point, generally consist of large areas of sand substrates with low topography resulting in large homogeneous seagrass patches; therefore, these homogeneous habitats allow for a lower transect density to map the seagrass habitat boundaries. On the other hand, the smaller Survey Areas (i.e. Woods Inlet and Fannie Bay) generally have a greater topographical complexity, resulting in patchy habitat distribution, and therefore require a greater transect density to map the areas with similar accuracy. Page 4 of 24

71 Table 1 Number of Sample Areas surveyed in each Survey Area in July 2014 Survey Area No. of Sample Areas Casuarina Beach 33 Charles Point West 12 East Point 19 Fannie Bay 38 Lee Point 20 Woods Inlet 31 Total 153 Page 5 of 24

72 Darwin Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Reef Sample Areas Survey Areas Casuarina Beach Charles Point West East Point Fannie Bay Lee Point Woods Inlet Charles Point Mandorah East Point Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 9 - July 2014 Survey Design km GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 INPICHSGR_606 10/07/2014 AL A3 Copyright Geo Oceans Pty Ltd 2014 Figure 2

73 2.4. Image Classification GO Visions software allows image analysis and habitat classification-trained marine scientists to assign and record habitat data in real-time (i.e. as the images are recorded). The habitat point data recorded using the software are defined using the same hierarchical habitat classification scheme that was used for the previous surveys. The software recorded percentage cover for five different subtidal Community Classes : Halodule; Halophila; Coral; Macroalgae; and Filter feeders. Other information collected included: Substrate categorisation; Biota counts; Other taxonomic information and modifiers; Water depth; Camera height off seafloor; Image frame size; and Image quality. Positioning data (via DGPS) were received at one-second intervals, encoded to the video and recorded in a database table along with the biota and substrate attributes assigned using the GO Visions software. It should be noted that while the additional habitat and environmental data were collected and stored by GO Visions, only the seagrass and depth data were used for the purposes of this monitoring report Data Processing Interpolation models were applied to the measured data to predict the distribution and percentage cover of seagrass in each of the Survey Areas. Interpolation models use mathematical functions to create a surface of cell values between the known point data locations. The known point data used in the interpolation were the habitat point data seagrass cover and seagrass presence values as described below Point Data Processing Seagrass percentage cover point data from each Sample Area were averaged and georeferenced to the transect centre point (centroid) of the Sample Areas. The steps used to process the transect centroid point data were as follows: 1. The habitat point data inside each Sample Area were extracted for analysis (i.e. points outside the transect areas were excluded from the analysis); Page 7 of 24

74 2. Seagrass cover the seagrass percentage cover from the habitat point data within each Sample Area (step 1) was averaged and attached to the Sample Area centroid; and 3. Seagrass presence and absence an additional field was added to the centroid point data to reclassify the average cover values to present or absent values (seagrass presence values). The thresholds and classification values to define the points as present or absent were as follows: a. Seagrass cover > 0.5% seagrass was considered present and the transect centroid was assigned a value of 1; and b. Seagrass cover < 0.5% seagrass was considered absent and the transect centroid was assigned a value of Interpolation Two different approaches were used to produce maps of seagrass percentage cover distribution and habitat extent Percentage Cover Data The distribution of seagrass was predicted using the Spline With Barriers Spatial Analyst interpolation tool in ArcGIS (version 10.1) Geographical Information Software (GIS) program. A spline interpolation method was chosen largely due to its computational stability and efficiency (Li and Heap 2008). In particular, a spline technique allows for the predicted surface values (i.e. percentage seagrass cover) to be more robustly determined when sample data are irregularly spread out within a survey area (Hutchinson 1998). The settings and parameters set for the interpolation model are defined in Appendix 1. The interpolation model produced a raster surface of cell values (i.e. percentage cover) by fitting a minimum-curvature surface to the habitat point data. Therefore, the method estimates unknown values by bending a surface through known values. The resulting percentage cover rasters show the predicted percentage cover (from 0% to 100%; Figure 3). The raster surface was then converted into polygon features to display the percentage cover of seagrass. Seagrass was defined as present where cell values were greater than 0.5% (Figure 3). The resultant seagrass percentage cover maps (Figure 10 and Figure 11) are displayed to illustrate the differences in seagrass density within and between Survey Areas and are not intended to determine the boundaries of seagrass habitat. While a spline interpolation is a suitable tool for this mapping exercise, it should be noted that there are inherent limitations to interpolating spatially continuous percentage cover values from discrete field measurements, particularly when the difference between sampled values is large (Azpurua and Ramos 2010). Therefore, resultant polygon outlines are associated with a level of uncertainty, in particular at low percentage cover values near the outer boundaries. These boundaries are more accurately modelled through interpolation of the presence and absence data (Section ), together with estimates of mapping accuracy (Section 2.6). Page 8 of 24

75 Figure 3. Percentage cover modelled values Presence and Absence Data Seagrass habitat distribution was modelled using the centroid point data present (1) and absent (0) values. The values were interpolated (spline interpolation with barriers) to create a surface of values between 0 and 1. The half-interval (0.5) was used to classify the surface as present (values >0.5) or absent (values <0.5) (Figure 4). Seagrass presence/absence distribution maps were used to estimate the areal extent (in ha) of seagrass habitat. It should be noted that separate interpolations were undertaken for the distribution of total seagrass, and of the separate seagrass genera. Therefore, the mapped extent of the total seagrass distributions will differ somewhat from the mapped extent of the separate seagrass genera distributions if combined. Figure 4. Presence and absence interpolation modelled values 2.6. Spatial Accuracy Assessment Reliability Estimate Estimates of the areal extent of seagrass habitat are presented together with an estimate of error based on the uncertainty around the location of habitat boundaries. This uncertainty is estimated from the distance between the calculated habitat boundary (estimated at the halfinterval between present and absent seagrass, Section ) and an outer boundary near the absent seagrass points. The outer boundary was calculated from the percentage cover raster surface (Section ), whereby raster values greater than 0.5% were converted to a polygon defining the seagrass as present and values less than 0.5% as seagrass absent (Figure 3). Page 9 of 24

76 The reliability estimate of seagrass extent was calculated from the difference between the seagrass habitat areas (based on presence/absence habitat boundary), and the percentage cover distribution areas (based on outer boundary) QA/QC As part of every seagrass habitat mapping survey, data Quality Assurance (QA) procedures are undertaken before, during and after the survey. These include the following steps. Pre-field: In-field: Only experienced analysts are used for the real-time habitat classification. The analysts have undergone training to calibrate their percent cover estimates against reference video footage from previous surveys when seagrass precent cover was fully quantified using a Coral Point Count with Excel extensions (CPCe) software image analysis method. Two experienced analysts are present during all field trips, with verification of the habitat classification being made in real-time; and Whenever practical, the same analyst will undertake the habitat classifications during a survey in order to maintain consistency and reduce the likelihood of user bias. Post-field: The habitat point database is checked for blank fields, erroneous GPS coordinates, missing time stamps and habitat classifications; The data are then converted into a GIS shapefile (as point data) and displayed in ArcGIS where the point data, across the whole percent cover range, are reviewed spatially for any classification anomalies that are not consistent with the surrounding point data and historical habitat data; If the point data at a particular transect are considered erroneous, the still images and video footage are reviewed by a different analyst to check the accuracy of the classifications; If the classifications are deemed incorrect the transect is re-analysed; and In addition to these initial steps, all transects in which the transect average (i.e. transect centroid value) is above zero percent but below five percent are systemically reviewed in line with the two preceding steps outline above. Page 10 of 24

77 3. RESULTS 3.1. Seagrass Distribution and Habitat Extent The July 2014 towed camera survey captured 24,125 points of benthic habitat data. All 153 Sample Area transects were completed. Weather conditions during the survey were dry, with light winds. No rainfall was observed during the survey. Water visibility was generally good. The total spatial extent of seagrass (Halophila and Halodule combined) mapped during the July 2014 survey was 2,500 ha (± 518 ha reliability estimate) (Table 3, Figure 7). Seagrass was present at all Survey Areas and was observed at depths between +2.2 m and -5.5 m LAT (Table 2). Halophila was recorded at all Survey Areas (Figure 8), covering an area of 853 ha (± 370 ha reliability estimate). Halophila was generally sparse, with cover typically less than 10% (Figure 10). Small patches of Halophila at Lee Point and East Point were found to have 20% to 40% coverage (Figure 10) and a small patch of Halophila at the northern end of Fannie Bay reached 40% to 60% cover. At most sites Halophila appeared to be in good health with little epiphytic growth, with the exception of Fannie Bay and Lee Point where some epiphytic growth was observed (Figure 5). At Casuarina Beach, East Point and Lee Point a number of Sample Areas contained Halophila seagrass with heavy epiphytic growth in areas where seagrass had not been recorded during the previous survey in May 2014 (Figure 6). Halodule was recorded at all Survey Areas and covered an area of 1,731 ha (± 458 ha reliability estimate) (Figure 9). Casuarina Beach, Charles Point, Fannie Bay and Woods Inlet all had areas with at least 10% to 20% coverage (Figure 11). East Point and Lee Point had sparse coverage (5% to 10% and 1% to 5%, respectively). At most sites Halodule appeared to be generally in good health, with little epiphytic growth (Figure 5), with the exception of Fannie Bay where moderate epiphytic growth was seen. Page 11 of 24

78 4. DISCUSSION The total spatial extent of seagrass (Halophila and Halodule combined) mapped during the July 2014 survey was 2,500 ha (± 518 ha reliability estimate). Halophila was recorded in all Survey Areas, including at Casuarina Beach and East Point, where it had not been recorded in the previous (May 2014) survey (Figure 8). At Casuarina Beach and East Point, over 10% cover was observed in some transects (Figure 10). At Lee Point, the distribution of Halophila decreased since the May 2014 survey (Figure 8), with cover of up to 20% in the remaining patches (Figure 10). Within the remaining Survey Areas there was little change since the May 2014 survey. At Lee Point, Casuarina Beach and East Point a significant proportion of the Sample Areas (50%, 15% and 42% respectively) contained Halophila seagrass with heavy epiphytic growth (see example from Lee Point in Figure 6). During the May 2014 survey at Lee Point, such heavy epiphytic growth on Halophila was not apparent. However, such epiphytic growth on Halophila was observed at Casuarina Beach and East Point during the May 2014 survey. The percentage cover and distribution of Halodule has remained generally consistent across surveys (Figure 9 and Figure 11) and has been observed in similar areas in all previous seagrass mapping surveys (Geo Oceans 2011a, 2012a, 2012e, 2013a, 2013b, 2013d, 2013e, 2014a and 2014b). This was most noticeable at Woods Inlet, where the extent of Halodule has changed little since surveys commenced in An exception was at Casuarina Beach where the spatial extent of Halodule habitat had decreased in May 2014 compared to all previous surveys (Figure 9). July 2014 results indicate an increase to a spatial extent comparable to the August 2013 survey (Geo Oceans 2013d). Within Survey Areas, Halodule has remained the dominant genera within the lower-littoral intertidal waters between 0 m and +2.2 m LAT. To assist temporal comparison of habitat areas, a spatial area measure of mapping accuracy (the reliability estimate ) was introduced based on estimated error of habitat outlines between interpolations, presence/absence data and interpolations based on percent cover data. The high reliability estimate values encountered at Lee Point during this survey are likely a result of the patchy nature of Halodule distribution, as well as the wide spacing of sample areas at this Survey Area. A mapping accuracy assessment was not undertaken for this survey; however, the results from the previous accuracy assessments undertaken during the February 2013 and May 2013 surveys (93% and 90%, respectively) indicate that the survey design and methodology are effective in accurately mapping the distribution of seagrass within the defined Survey Areas. Page 20 of 24

79 (a) (b) Figure 5 Example images of: (a) Halodule at Charles Point; and (b) Halophila at Fannie Bay from July 2014 Page 12 of 24

80 Table 2 Depth range (LAT) of seagrass June 2012 Oct 2012 Feb 2013 May 2013 Aug 2013 Nov 2013 Feb 2014* May 2014 July 2014 Min m m m +2.4 m +2.4 m +2.0 m +1.9 m +2.2 m +2.2 m Max m m m -7.4 m -3.4 m -2.9 m -0.9 m -5.7 m -5.5 m * The February 2014 depth range applies to Fannie Bay and Woods Inlet only. Table 3 Total seagrass extent calculations (ha) (± reliability estimate) Survey Area Jun 2012 Oct 2012 Feb 2013 May 2013 Aug 2013 Nov 2013 Feb 2014 May 2014 July 2014 Casuarina Beach*** 1,712 2,734 (±263) 1,232 (±239) 1,268 (±422) 1,570 (±400) 1,565 (±343) -** 365 (±259) 1,821 (±182) East Point (±61) 40 (±20) 42 (±47) 308 (±150) 243 (±32) -* 44 (±19) 212 (±54) Fannie Bay (±90) 50 (±54) 70 (±51) 99 (±55) 46 (±31) 58 (±30) 78 (±19) 78 (±17) Lee Point *** 602 2,719 (±131) 33 (±81) 1,817 (±491) 914 (±388) 183 (±337) -** 866 (±249) 316 (±251) Woods Inlet (±14) 50 (±18) 41 (±12) 57 (±22) 52 (±14) 63 (±10) 46 (±7) 52 (±12) Charles Point West (±7) 19 (±4) 29 (±2) 36 (±4) 18 (±11) -** 19 (±5) 22 (±2) Total 2,526 6,306 (±566) 1,424 (±416) 3,268 (±1,021) 2,984 (±1,011) 2,107 (±768) 121 (±40) 1,418 (±557) 2,500 (±518) * Insufficient data were collected at East Point for spatial interpolations and habitat extent calculations. ** Poor visibility and unfavourable sea state prevented sampling at these Survey Areas in February *** The revised boundaries for Casuarina Beach and Lee Point Survey Areas prevent a direct comparison with surveys prior to August Page 13 of 24

81 (a) (b) Figure 6 Example of dead epiphyte-covered Halophila at East Point over consecutive surveys during: a) May 2014; and b) July 2014 Page 14 of 24

82 ± Darwin Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas February 2014* May 2014 July 2014 Charles Point East Point Map Notes: Seagrass distribution was predicted by interpolation of the towed camera survey data. Present: seagrass cover >0.5 Absent: seagrass cover <0.5 *Only Woods Inlet and Fannie Bay were sampled during the February 2014 survey. Mandorah Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 9 - July 2014 Total Seagrass Distribution km Copyright Geo Oceans Pty Ltd 2014 GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_6 17/07/2014 JN A3 Figure 7

83 ± Darwin Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas February 2014* May 2014 July 2014 Charles Point East Point Map Notes: Seagrass distribution was predicted by interpolation of the towed camera survey data. Present: seagrass cover >0.5 Absent: seagrass cover <0.5 *Only Woods Inlet and Fannie Bay were sampled during the February 2014 survey. Mandorah Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 9 - July 2014 Halophila Distribution km Copyright Geo Oceans Pty Ltd 2014 GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_6 17/07/2014 JN A3 Figure 8

84 ± Darwin Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas February 2014* May 2014 July 2014 Charles Point Map Notes: Seagrass distribution was predicted by interpolation of the towed camera survey data Present: seagrass cover >0.5 Absent: seagrass cover <0.5 East Point *Only Woods Inlet and Fannie Bay were sampled during the February 2014 survey. Mandorah Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 9 - July 2014 Halodule Distribution km Copyright Geo Oceans Pty Ltd 2014 GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_6 17/07/2014 JN A3 Figure 9

85 ± Darwin Charles Point East Point Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas Halophila Cover 0% <1% 1-5% 5-10% 10-20% 20-40% 40-60% 60-80% >80% Mandorah Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 9 - July 2014 Halophila Cover km GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_5 17/07/2014 JN A3 Copyright Geo Oceans Pty Ltd 2014 Figure 10

86 ± Darwin Charles Point East Point Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas Halodule Cover 0% <1% 1-5% 5-10% 10-20% 20-40% 40-60% 60-80% >80% Mandorah Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 9 - July 2014 Halodule Cover km GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_6 17/07/2014 JN A3 Copyright Geo Oceans Pty Ltd 2014 Figure 11

87 5. REFERENCES Azpurua, M. and Ramos, K.R (2010). A Comparison of Spatial Interpolation Methods for Estimation of Average Electromagnetic Field Magnitude. Progress in Electromagnetics Research. Vol 14, pp Cardno (2014). Ichthys Project Nearshore Environmental Monitoring Plan. INPEX Gas Field Development. June Geo Oceans (2011a). Ichthys Gas Field Development Project: Benthic Habitat Mapping of the Darwin region Methods of Data Collection, Collation, and Map Production. Ichthys Technical Appendix S6. Geo Oceans (2011b). Marine Habitat Assessment East Arm Wharf Expansion Project: Draft Technical Memo. Prepared for NT Department for Lands and Planning. Geo Oceans (2012a). : Seagrass Habitat Monitoring Survey October 2012: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2012b). Marine Habitat Assessment East Arm Wharf Expansion Project: Technical Report. Prepared for NT Department for Lands and Planning. Unpublished report. Geo Oceans (2012c). Marine Habitat Assessment East Point Aquatic Life Reserve: Technical Report. Prepared for NT Power and Water Corporation. Unpublished report. Geo Oceans (2012d). Baseline Marine Habitat Monitoring Survey for NT Department of Land and Planning East Arm Wharf Expansion Project: Technical Report. Prepared for URS Australia Pty Ltd on behalf of NT Department of Land and Planning. Geo Oceans (2012e). : Seagrass Baseline and Marine Habitat Mapping. Survey June 2012: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2012f). Marine Habitat Monitoring Survey for NT Department of Land and Planning East Arm Wharf Expansion Project: Technical Report. Prepared for Macmahon Contractors Pty Ltd. Geo Oceans (2013a). : Seagrass Habitat Monitoring Survey February 2013: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2013b). : Seagrass Habitat Monitoring Survey May 2013: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2013c). Revised Towed Camera Seagrass Monitoring Method Statement. Prepared for Cardno on behalf of INPEX. Geo Oceans (2013d). : Seagrass Habitat Monitoring Survey August 2013: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2013e). : Seagrass Habitat Monitoring Survey November 2013: Technical Report. Prepared for Cardno on behalf of INPEX. Page 21 of 24

88 Geo Oceans (2014a). : Seagrass Habitat Monitoring Survey February 2014: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2014b). : Seagrass Habitat Monitoring Survey May 2014: Technical Report. Prepared for Cardno on behalf of INPEX. Hutchinson, M.F (1998). Interpolation of Rainfall Data with Thin Plate Smoothing Splines - Part I: Two Dimensional Smoothing of Data with Short Range Correlation. Journal of Geographic Information and Decision Analysis. Vol 2, pp INPEX (2010). Ichthys Gas Field Development Project, Draft Environmental Impact Statement. INPEX (2011). Ichthys Gas Field Development Project, Supplement to the Draft Environmental Impact Statement. INPEX (2013). Dredging and Spoil Disposal Management Plan East Arm (Rev 4). INPEX Operations Australia Pty Ltd. INPEX (2014). Dredging and Spoil Disposal Management Plan Gas Export Pipeline (Rev 7). INPEX Operations Australia Pty Ltd. Li, J. and Heap, A.D (2008). A Review of Spatial Interpolation Methods for Environmental Scientists. Geoscience Australia, Record 2008/23, 137pp. Page 22 of 24

89 Appendix 1 Spline Interpolation Settings and Parameters. ArcGIS Resource Centre Parameter Explanation Data type Input point features (Required) The input point features containing the z- values to be interpolated into a surface raster. Composite Geodataset Z value field (Required) Field that holds a height or magnitude value for each point. This can be a numeric field or the shape field if the in_point_features contain Field z-values. Input barrier features (Optional) Output cell size (Required) Smoothing factor (Optional) The optional input barrier features to constrain the interpolation. The cell size at which the output raster will be created. If a value of zero is entered the shorter of the width or the height of the extent of the input point features in the input spatial reference, divided by 250, will be used as the cell size. The parameter that influences the smoothing of the output surface. The default is 0.0. No smoothing is applied when the value is zero and the maximum amount of smoothing is applied when the factor equals 1. Composite Geodataset Analysis cell size Project Data SeagrassCover_TransectArea scentroids_july2014 Seagrass_Cover; Halophila_Cover; Halodule_Cover; Seagrass_Presence Survey_Areas polygon 10 m Double 0 Page 23 of 24

90 Appendix 2 Maps of seagrass distribution in June 2012, October 2012, February 2013 and May 2013 Page 24 of 24

91 ± Darwin 100 Kilometers Map Legend Gas Export Pipeline Dredging Footprint Lee Point Spoil Disposal Site Survey Boundary (June 2012) Survey Boundary (Oct 2012 to May 2013) Seagrass Distribution June 2012 Casuarina Beach Oct 2012 Feb 2013 May 2013 Charles Point East Point Map Notes: Seagrass distribution was predicted by interpolation of the towed camera survey data. Present: seagrass cover > 0.5% = 1 Absent: seagrass cover <0.5% = 0 Cell values greater than 0.5 were classified as seagrass present. No data was captured in the February 2013 survey at Charles Point East Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Fannie Bay Ichthys Development Project Seagrass Survey 4 - May 2013 Seagrass Distribution Woods Inlet Kilometers GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_400 13/08/2013 BB A3 Copyright Geo Oceans Pty Ltd 2012 Appendix 3-1

92

93 ± Darwin 100 Kilometers Map Legend Gas Export Pipeline Dredging Footprint Spoil Disposal Site Lee Point Survey Boundary (June 2012) Survey Boundary (Oct 2012 to May 2013) Halophila Distribution June 2012 Casuarina Beach Oct 2012 Feb 2013 May 2013 Charles Point East Point Note: June 2012 Survey - The Survey Area at Casuarina Beach and Lee Point was smaller than the subsequent surveys; there was inadequate data to model Halodule and Halophila distribution at the survey sites on the Cox Peninsula. The Charles Point East site was not surveyed in February There was no Halophila recorded in Feb Seagrass distribution was predicted by interpolation of the towed camera survey data. Present: seagrass cover > 0.5% = 1 Absent: seagrass cover <0.5% = 0 Cell values greater than 0.5 were classified as seagrass present. Fannie Bay Ichthys Development Project Seagrass Survey 4 - May 2013 Halophila Distribution Woods Inlet Kilometers Copyright Geo Oceans Pty Ltd 2012 GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_400 13/08/2013 BB A3 Appendix 3-3

94 Ichthys Nearshore Environmental Monitoring Program APPENDIX B OCTOBER 2014 TOWED-VIDEO HABITAT MAPPING TECHNICAL REPORT Prepared for INPEX Cardno 54

95 Ichthys Project Nearshore Environmental Monitoring Program Seagrass Habitat Monitoring October 2014 Technical Report Prepared for Cardno on behalf of INPEX Rev 0 November 2014 Document code: INPICHSGR.1004

96 Prepared for Cardno Prepared by Geo Oceans Pty Ltd Ichthys Project Nearshore Environmental Monitoring Program Seagrass Habitat Monitoring October 2014 Technical Report Document code: INPICHSGR.1004 Revision History Rev Authors Distribution Recipients No. Copies & Format Date Review Reviewer Review type Date A1 Ade Lambo A. Nicastro (Cardno) 1 x e-copy 4/11/2014 N. Veitch Editorial 31/10/2014 A2 Ade Lambo A. Nicastro (Cardno) 1 x e-copy 6/11/2014 A. Nicastro (Cardno) Technical 6/11/2014 B1 Ade Lambo A. Nicastro (Cardno) 1 x e-copy 14/11/2014 S. Harrison (INPEX) Technical 13/11/2014 B2 Ade Lambo A. Nicastro (Cardno) 1 x e-copy 18/11/ Ade Lambo A. Nicastro (Cardno) 1 x e-copy 18/11/2014 Disclaimer Geo Oceans Pty Ltd (Geo Oceans) has prepared this report at the request of Cardno on behalf of INPEX. This document is subject to and issued in accordance with the agreed terms and scope between the above listed companies. Copyright Geo Oceans Pty Ltd 2014.

97 EXECUTIVE SUMMARY A Seagrass Monitoring Program has been developed to detect potential changes in seagrass and to infer whether any changes are a result of dredging and/or spoil disposal activities associated with the Ichthys LNG Project (the Project) in Darwin Harbour. The Nearshore Environmental Monitoring Plan (NEMP, Cardno 2014) sets out a framework for the Seagrass Monitoring Program, including towed camera surveys, to assess the distribution of seagrasses in Darwin Harbour. This report describes the results of the October 2014 field survey, which was completed from 15 October 2014 to 21 October The survey involved the use of a towed camera system and customised data analysis software to record geo-referenced habitat point data, and video and still images within 153 Sample Areas at all Survey Areas in Darwin Outer. The total spatial extent of seagrass (Halodule and Halophila combined) mapped during the October 2014 survey was 3,635 ± 591 ha reliability estimate. Seagrass was present at all Survey Areas and was observed at depths between +2.2 m and -5.6 m lowest astronomical tide (LAT). The spatial extent of Halodule mapped during the October 2014 survey was 1,791 ± 498 ha reliability estimate, with Halodule recorded in all Survey Areas except East Point. Halophila was recorded in all Survey Areas and covered a total area of 2,029 ± 605 ha reliability estimate.

98 Table of Contents 1.! Introduction... 1! 1.1.! Existing Data... 1! 1.2.! Objectives... 2! 2.! Methods... 3! 2.1.! Field Data Collection... 3! 2.2.! Equipment... 3! 2.3.! Survey Design... 3! ! Survey Areas... 3! ! Sample Areas... 4! 2.4.! Image Classification... 7! 2.5.! Data Processing... 7! ! Point Data Processing... 7! ! Interpolation... 8! 2.6.! Spatial Accuracy Assessment... 9! ! Reliability Estimate... 9! 2.7.! Quality Assurance/Quality Control (QA/QC)... 10! 3.! Results... 11! 3.1.! Seagrass Distribution and Habitat Extent... 11! 4.! Discussion... 19! 5.! References... 20! List of Figures Figure 1 Geo Oceans topside control unit being operated during survey operations... 3! Figure 2 Seagrass Survey 10 October 2014 survey design... 6! Figure 3 Percentage cover modelled values... 9! Figure 4 Presence and absence interpolation modelled values... 9! Figure 5 Example images of (a) Halodule at Woods Inlet and (b) Halophila at East Point from October ! Figure 6 Seagrass Survey 10 October 2014 Total Seagrass Distribution... 14! Figure 7 Seagrass Survey 10 October 2014 Halophila Distribution... 15! Figure 8 Seagrass Survey 10 October 2014 Halodule Distribution... 16!

99 Figure 9 Seagrass Survey 10 October 2014 Halophila Cover... 17! Figure 10 Seagrass Survey 10 October 2014 Halodule Cover... 18! List of Tables Table 1 Number of Sample Areas surveyed in each Survey Area in October ! Table 2. Total seagrass extent calculations (ha) (± reliability estimate)... 13! Table 3. Depth range (m LAT) of seagrass (Halophila and Halodule combined)... 13! List of Appendices Appendix 1 Spline Interpolation Settings and Parameters Appendix 2 Maps of seagrass distribution in June 2012, October 2012, February 2013 and May

100 1. INTRODUCTION INPEX is the operator of the Ichthys LNG Project (the Project). The Project comprises the development of offshore production facilities at the Ichthys Field in the Browse Basin, some 820 km west-south-west of Darwin, an 889 km long subsea gas export pipeline (GEP) and an onshore processing facility and product loading jetty at Bladin Point on Middle Arm Peninsula in Darwin Harbour. To support the nearshore infrastructure at Bladin Point, dredging works were carried out to extend safe shipping access from near East Arm Wharf to the new product loading facilities at Bladin Point, supported by piles driven into the sediment. A trench was dredged to seat and protect the GEP for the Darwin Harbour portion of its total length. Dredged material was disposed at the spoil ground located approximately 12 km north-west of Lee Point. A detailed description of the dredging and spoil disposal methodology is provided in Section 2 of the East Arm (EA) Dredging and Spoil Disposal Management Plan (DSDMP) (INPEX 2013) and GEP DSDMP (INPEX 2014). Following the Draft Environmental Impact Statement (EIS) (INPEX 2010) and Supplementary EIS (SEIS) (INPEX 2011), the Project was approved subject to conditions that included monitoring for potential effects of dredging or spoil disposal on local ecosystems (including seagrasses) and potentially vulnerable populations. Sedimentation and increased turbidity have the potential to impact seagrasses by limiting the light available for photosynthesis, thus affecting their growth rate and, ultimately, survival. A monitoring program was therefore set up to examine the potential impact on seagrasses in and around the Darwin Harbour region from dredging and spoil disposal activities associated with the Project. The aim of the Seagrass Monitoring Program is to detect changes in seagrass distribution and habitat extent from potential dredge impacts. The Seagrass Monitoring Program (Appendix B of the Nearshore Environmental Monitoring Plan (NEMP) (Cardno 2014)) included twice-yearly mapping surveys of the areal extent of seagrass habitat and distribution of seagrass habitat. However, the scope of the mapping surveys has since been increased to undertake broad-scale semi-quantitative seagrass mapping surveys using the methods described in the INPEX Seagrass Habitat Monitoring October 2012 Survey technical report (Geo Oceans 2012a). A towed video seagrass habitat mapping survey was undertaken in October 2014 as part of Seagrass Monitoring Program, to assess the distribution and habitat extent of seagrass in the Darwin Harbour region following completion of Project dredging activities. This report describes the survey design, seagrass distribution and habitat extent Existing Data INPEX submitted a Draft EIS (INPEX 2010) and SEIS (INPEX 2011) as part of the approval processes for the Project. To support the EIS, Geo Oceans (2011a) collated and classified available marine habitat information to produce maps showing the distribution of benthic habitats in the waters surrounding Darwin Harbour. This included a towed camera survey to collect marine habitat data from Darwin Harbour to Adam Bay in December 2010 (Geo Oceans 2011a) using similar methods to those employed for the current survey. The soft sediments in the sheltered bays between Shoal Bay and Fannie Bay supported communities that were dominated by Halodule spp. (e.g. Halodule uninervis), with Halophila sp. (e.g. Halophila decipiens) and Syringodium sp. also present. The majority of the seagrass habitat was found on the soft sediments in the lower littoral intertidal zone between 0 m and +1 m (Lowest Astronomical Tide (LAT)), but sparse communities extended into the shallow Page 1 of 23

101 subtidal coastline from Shoal Bay to Fannie Bay in water depth less than -3 m LAT. There was no seagrass recorded in Darwin Harbour Inner (i.e. demarcation boundary extends approximately northeast across the harbour mouth from Talc Head to Emery Point, Darwin). Habitat surveys conducted in Darwin Outer by Geo Oceans prior to the start of the Project (2011a, 2011b), and nearshore environmental monitoring undertaken since June 2012 (Geo Oceans 2012a, 2012b, 2012c, 2012d, 2012e, 2012f, 2013a, 2013b, 2013d, 2013e, 2014a, 2014b, 2014c), have found Halophila spp. in particular to be ephemeral and to exhibit large changes in spatial distribution and percentage cover over relatively short time periods (i.e. weeks). Although large changes in percentage cover have also been recorded in Halodule spp. habitat, its spatial distribution has been more consistent and, in contrast to Halophila spp., has persisted through the wet season Objectives The objectives of this survey were to: Map the distribution of seagrass at the defined Survey Areas using methods that can be repeated and compared over time; and Assess changes in seagrass distribution and extent between the June 2012, October 2012, February 2013, May 2013, August 2013, November 2013, February 2014, May 2014, July 2014 and October 2014 surveys. Page 2 of 23

102 2. METHODS 2.1. Field Data Collection The October 2014 survey was undertaken over one neap tide period by one field team from 15 October 2014 to 21 t October The survey was performed during a neap tide to maximise water visibility for image capture. Data were collected in all Sample Areas in each Survey Area shown in Figure Equipment Geo Oceans customised Visual Basic software program (GO Visions) and towed camera system (Figure 1) recorded geo-referenced habitat point data, video and still images within each Transect Area using the same equipment and software employed in the previous towed camera surveys (Geo Oceans 2011a, 2012a, 2012b, 2012c, 2012e, 2013a, 2013b, 2013d, 2013e, 2014a, 2014b, 2014c). The location coordinates of the data were captured and recorded using a differential global positioning system (DGPS) mounted to the vessel and encoded to all of the data using a topside control unit. Figure 1 Geo Oceans topside control unit being operated during survey operations 2.3. Survey Design Survey Areas The Survey Area boundaries were defined using a combination of existing data (including bathymetric contours, habitat maps and seagrass distribution data) and logistical constraints. Consequently, the following six Survey Areas were defined (Figure 2): Page 3 of 23

103 Charles Point West, located 3 km east of Charles Point; Woods Inlet, located 2.5 km south of Mandorah; Fannie Bay, located in Fannie Bay; East Point, located immediately north of East Point; Casuarina Beach, located near Casuarina Beach; and Lee Point, located 1.5 km east of Lee Point. The first surveys recorded seagrass present in waters deeper than +2.2 m LAT (Geo Oceans 2012e). Existing elevation data were used to create a +2.2 m LAT bathymetric contour line. This line was used to define the inshore distribution of the Survey Areas. The outer depth limit of the seagrass in each Survey Area was determined using the habitat point data collected during this survey (Geo Oceans 2012a). Reef habitat areas that were mapped in the first survey (Geo Oceans 2012e) and the Project Restricted Work Areas provided to Geo Oceans by Cardno were excluded from the Survey Areas. Transects within each of the Survey Areas were located within pre-defined Sample Areas (Table 1) Sample Areas One hundred and fifty-three towed camera transects of a minimum 50 m in length were surveyed inside the pre-defined Sample Areas (Table 1). For consistency among surveys, October 2014 data were collected within the same Sample Areas previously surveyed at all Survey Areas. Each Sample Area was a circular area with a 50 m radius. One transect was completed inside each Sample Area. This survey design allowed enough area and flexibility for safe and efficient vessel navigation and positioning when capturing the data. The differences in transect density within the Survey Areas area result of the differences in habitat type and complexity between these areas. The larger Survey Areas, such as Casuarina Beach and Lee Point, generally consist of large areas of sand substrates with low topography resulting in large homogeneous seagrass patches; therefore, these homogeneous habitats allow for a lower transect density to map the seagrass habitat boundaries. On the other hand, the smaller Survey Areas (i.e. Woods Inlet and Fannie Bay) generally have a greater topographical complexity, resulting in patchy habitat distribution, and therefore require a greater transect density to map the areas with similar accuracy. Page 4 of 23

104 Table 1 Number of Sample Areas surveyed in each Survey Area in October 2014 Survey Area No. of Sample Areas Casuarina Beach 33 Charles Point West 12 East Point 19 Fannie Bay 38 Lee Point 20 Woods Inlet 31 Total 153 Page 5 of 23

105 Darwin Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Reef Sample Areas Survey Areas Casuarina Beach Charles Point West East Point Fannie Bay Lee Point Woods Inlet Charles Point Mandorah East Point Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 10 - October 2014 Survey Design km GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 INPICHSGR_10 28/10/2014 AL A3 Copyright Geo Oceans Pty Ltd 2014 Figure 2

106 2.4. Image Classification GO Visions software allows image analysis and habitat classification-trained marine scientists to assign and record habitat data in real-time (i.e. as the images are recorded). The habitat point data recorded using the software are defined using the same hierarchical habitat classification scheme that was used for the previous surveys. The software recorded percentage cover for five different subtidal Community Classes : Halodule; Halophila; Coral; Macroalgae; and Filter feeders. Other information collected included: Substrate categorisation; Biota counts; Other taxonomic information and modifiers; Water depth; Camera height off seafloor; Image frame size; and Image quality. Positioning data (via DGPS) were received at one-second intervals, encoded to the video and recorded in a database table along with the biota and substrate attributes assigned using the GO Visions software. It should be noted that while the additional habitat and environmental data were collected and stored by GO Visions, only the seagrass and depth data were used for the purposes of this monitoring report Data Processing Interpolation models were applied to the measured data to predict the distribution and percentage cover of seagrass in each of the Survey Areas. Interpolation models use mathematical functions to create a surface of cell values between the known point data locations. The known point data used in the interpolation were the habitat point data seagrass cover and seagrass presence values as described below Point Data Processing Seagrass percentage cover point data from each Sample Area were averaged and georeferenced to the centre point (transect centroid) of the Sample Areas. The steps used to process the transect centroid point data were as follows: 1. The habitat point data inside each Sample Area were extracted for analysis (i.e. points outside the transect areas were excluded from the analysis); Page 7 of 23

107 2. Seagrass cover the seagrass percentage cover from the habitat point data within each Sample Area (step 1) was averaged and attached to the Sample Area centroid (centre point); and 3. Seagrass presence and absence an additional field was added to the centroid point data to reclassify the average cover values to present or absent values (seagrass presence values). The thresholds and classification values to define the points as present or absent were as follows: a. Seagrass cover > 0.5% seagrass was considered present and the transect centroid was assigned a value of 1; and b. Seagrass cover < 0.5% seagrass was considered absent and the transect centroid was assigned a value of Interpolation Two different approaches were used to produce maps of seagrass percentage cover distribution and habitat extent Percentage Cover Data The distribution of seagrass was predicted using the Spline With Barriers Spatial Analyst interpolation tool in ArcGIS (version 10.1) Geographical Information Software (GIS) program. A spline interpolation method was chosen largely due to its computational stability and efficiency (Li and Heap 2008). In particular, a spline technique allows for the predicted surface values (i.e. percentage seagrass cover) to be more robustly determined when sample data are irregularly spread out within a survey area (Hutchinson 1998). The settings and parameters set for the interpolation model are defined in Appendix 1. The interpolation model produced a raster surface of cell values (i.e. percentage cover) by fitting a minimum-curvature surface to the habitat point data. Therefore, the method estimates unknown values by bending a surface through known values. The resulting percentage cover rasters show the predicted percentage cover (from 0% to 100%; Figure 3). The raster surface was then converted into polygon features to display the percentage cover of seagrass. Seagrass was defined as present where cell values were greater than 0.5% (Figure 3). The resultant seagrass percentage cover maps (Figure 9 and Figure 10) are displayed to illustrate the differences in seagrass density within and between Survey Areas and are not intended to determine the boundaries of seagrass habitat. While a spline interpolation is a suitable tool for this mapping exercise, it should be noted that there are inherent limitations to interpolating spatially continuous percentage cover values from discrete field measurements, particularly when the difference between sampled values is large (Azpurua and Ramos 2010). Therefore, resultant polygon outlines are associated with a level of uncertainty, in particular at low percentage cover values near the outer boundaries. These boundaries are more accurately modelled through interpolation of the presence and absence data (Section ), together with estimates of mapping accuracy (Section 2.6). Page 8 of 23

108 Figure 3 Percentage cover modelled values Presence and Absence Data Seagrass habitat distribution was modelled using the centroid point data present (1) and absent (0) values. The values were interpolated (spline interpolation with barriers) to create a surface of values between 0 and 1. The half-interval (0.5) was used to classify the surface as present (values >0.5) or absent (values <0.5) (Figure 4). Seagrass presence/absence distribution maps were used to estimate the areal extent (in ha) of seagrass habitat. It should be noted that separate interpolations were undertaken for the distribution of total seagrass, and of the separate seagrass genera. Therefore, the mapped extent of the total seagrass distributions will differ somewhat from the mapped extent of the separate seagrass genera distributions if combined. Figure 4 Presence and absence interpolation modelled values 2.6. Spatial Accuracy Assessment Reliability Estimate Estimates of the areal extent of seagrass habitat are presented together with an estimate of error based on the uncertainty around the location of habitat boundaries. This uncertainty is estimated from the distance between the calculated habitat boundary (estimated at the halfinterval between present and absent seagrass, Section ) and an outer boundary near the absent seagrass points. The outer boundary was calculated from the percentage cover raster surface (Section ), whereby raster values greater than 0.5% were converted to Page 9 of 23

109 a polygon defining the seagrass as present and values less than 0.5% as seagrass absent (Figure 3). The reliability estimate of seagrass extent was calculated from the difference between the seagrass habitat areas (based on presence/absence habitat boundary), and the percentage cover distribution areas (based on outer boundary) Quality Assurance/Quality Control (QA/QC) As part of every seagrass habitat mapping survey, data QA procedures are undertaken before, during and after the survey. These include the following steps. Pre-field: Only experienced analysts are used for the real-time habitat classification. The analysts have undergone training to calibrate their percent cover estimates against reference video footage from previous surveys when seagrass precent cover was fully quantified using a Coral Point Count with Excel extensions (CPCe) software image analysis method. In-field: Two experienced analysts are present during all field trips, with verification of the habitat classification being made in real-time; and Whenever practical, the same analyst will undertake the habitat classifications during a survey in order to maintain consistency and reduce the likelihood of user bias. Post-field: The habitat point database is checked for blank fields, erroneous GPS coordinates, missing time stamps and habitat classifications; The data are then converted into a GIS shapefile (as point data) and displayed in ArcGIS where the point data, across the whole percent cover range, are reviewed spatially for any classification anomalies that are not consistent with the surrounding point data and historical habitat data; If the point data at a particular transect are considered erroneous, the still images and video footage are reviewed by a different analyst to check the accuracy of the classifications; If the classifications are deemed incorrect the transect is re-analysed; and In addition to these initial steps, all transects in which the transect average (i.e. transect centroid value) is above zero percent but below five percent are systemically reviewed in line with the two preceding steps outline above. Page 10 of 23

110 3. RESULTS 3.1. Seagrass Distribution and Habitat Extent The October 2014 towed camera survey captured 19,653 points of benthic habitat data. All 153 Sample Area transects were completed. Weather conditions during the survey were dry, with light to moderate winds. No rainfall was observed during the survey. Water visibility was generally good with some poorer visibility experienced at Charles Point West. The total spatial extent of seagrass mapped during the October 2014 survey was 3,635 ± 591 ha reliability estimate (Table 2, Figure 6). Seagrass was present at all Survey Areas and was observed at depths between +2.2 m and -5.6 m LAT (Table 3). Halophila and Halodule generally appeared to be in good health with little epiphytic growth (see examples in Figure 5). There were no patches of Halophila with heavy epiphytic growth, as observed at Casuarina Beach and Lee Point during the previous survey (July 2014) (Geo Oceans 2014c). Halophila was recorded at all Survey Areas (Figure 7), covering a total area of 2,029 ± 605 ha reliability estimate. Halodule was recorded at all Survey Areas, except East Point (Figure 8), covering a total area of 1,791 ± 498 ha reliability estimate. The observed Halophila beds were generally quite dense, with cover typically of 40% (Figure 9). Small patches of Halophila at Charles Point West, Lee Point and East Point were found to have up to 60% cover (Figure 9), with Fannie Bay demonstrating the lowest cover (1% to 5%). The largest spatial extent of Halophila was mapped at Casuarina Beach (Figure 7). Charles Point West, Fannie Bay and Woods Inlet all had patches of Halodule of at least 20% to 40% cover (Figure 10). Halodule cover at Lee Point was the lowest recorded among all the Survey Areas, with 5% to 10% cover recorded in patches within the southwest corner of the Survey Area. Similarly, the density of Halodule at Casuarina Beach was relatively low; up to 20% cover in some areas, though typically between 1% and 10% through most of the Survey Area (Figure 10). Page 11 of 23

111 (a) (b) Figure 5 Example images of (a) Halodule at Woods Inlet and (b) Halophila at East Point from October 2014 Page 12 of 23

112 Table 2. Total seagrass extent calculations (ha) (± reliability estimate) Survey Area Casuarina Beach*** Jun ,712 Oct ,734 (±263) Feb ,232 (±239) May ,268 (±422) Aug ,570 (±400) Nov ,565 (±343) Feb ** May (±259) July (±182) Oct (±144) East Point (±61) 40 (±20) 42 (±47) 308 (±150) 243 (±32) -* 44 (±19) 212 (±54) 514 (±144) Fannie Bay (±90) 50 (±54) 70 (±51) 99 (±55) 46 (±31) 58 (±30) 78 (±19) 78 (±17) 51 (±39) Lee Point*** 602 2,719 (±131) 33 (±81) 1,817 (±491) 914 (±388) 183 (±337) -** 866 (±249) 316 (±251) 377 (±242) Woods Inlet (±14) 50 (±18) 41 (±12) 57 (±22) 52 (±14) 63 (±10) 46 (±7) 52 (±12) 67 (±12) Charles Point West (±7) 19 (±4) 29 (±2) 36 (±4) 18 (±11) -** 19 (±5) 22 (±2) 34 (±10) Total 2,526 6,306 (±566) 1,424 (±416) 3,268 (±1,021) 2,984 (±1,011) 2,107 (±768) 121 (±40) 1,418 (±557) 2,500 (±518) 3,635 (±591) * Insufficient data were collected at East Point for spatial interpolations and habitat extent calculations. ** Poor visibility and unfavourable sea state prevented sampling at these Survey Areas in February *** The revised boundaries for Casuarina Beach and Lee Point Survey Areas prevent a direct comparison with surveys prior to August Table 3. Depth range (m LAT) of seagrass (Halophila and Halodule combined) Jun Oct Feb May Aug Nov Feb May July Oct * Min Max * The February 2014 depth range applies to Fannie Bay and Woods Inlet only. Page 13 of 23

113 Darwin Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas May 2014 July 2014 October 2014 Charles Point Map Notes: Seagrass distribution was predicted by interpolation of the towed camera survey data. Present: seagrass cover >0.5 Absent: seagrass cover <0.5 Mandorah East Point Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 10 - October 2014 Total Seagrass Distribution km GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 INPICHSGR_10 14/11/2014 AL A3 Copyright Geo Oceans Pty Ltd 2014 Figure 6

114 Darwin Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas May 2014 July 2014 October 2014 Charles Point Map Notes: Seagrass distribution was predicted by interpolation of the towed camera survey data. Present: seagrass cover >0.5 Absent: seagrass cover <0.5 Mandorah East Point Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 10 - October 2014 Halophila Distribution km GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 INPICHSGR_10 14/11/2014 AL A3 Copyright Geo Oceans Pty Ltd 2014 Figure 7

115 Darwin Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas May 2014 July 2014 October 2014 Charles Point Map Notes: Seagrass distribution was predicted by interpolation of the towed camera survey data Present: seagrass cover >0.5 Absent: seagrass cover <0.5 Mandorah East Point Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 10 - October 2014 Halodule Distribution km GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 INPICHSGR_10 14/11/2014 AL A3 Copyright Geo Oceans Pty Ltd 2014 Figure 8

116 Darwin Charles Point Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas Halophila Cover 0% <1% 1-5% 5-10% 10-20% 20-40% 40-60% 60-80% >80% Mandorah East Point Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 10 - October 2014 Halophila Cover km GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 INPICHSGR_10 31/10/2014 AL A3 Copyright Geo Oceans Pty Ltd 2014 Figure 9

117 Darwin Charles Point Lee Point Casuarina Beach Map Legend Dredging Footprint Gas Export Pipeline Spoil Disposal Site Survey Areas Halodule Cover 0% <1% 1-5% 5-10% 10-20% 20-40% 40-60% 60-80% >80% Mandorah East Point Fannie Bay Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Darwin Woods Inlet INPEX Ichthys Development Project Seagrass Survey 10 - October 2014 Halodule Cover km GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 INPICHSGR_10 31/10/2014 AL A3 Copyright Geo Oceans Pty Ltd 2014 Figure 10

118 4. DISCUSSION The total spatial extent of seagrass (Halophila and Halodule combined) mapped during the October 2014 survey was 3,635 ha (± 591 ha reliability estimate). Halophila was recorded at all Survey Areas in varying densities. The observed Halophila beds were generally quite dense, with cover typically of 40%. Small patches of Halophila at Charles Point West, Lee Point and East Point were found to have up to 60% cover. The distribution of Halophila at Casuarina Beach and East Point had increased substantially from the previous survey in July 2014, with large patches of relatively dense seagrass (up to 40% cover) (Figure 9). Comparison with the previous two surveys (May 2014 and July 2014) also showed substantial shifting of patches at Lee Point (Figure 7), which reflects its ephemeral nature observed since the commencement of the Seagrass Monitoring Program (Appendix 2-2). It should be noted that the patches of Halophila with heavy epiphytic growth observed at Casuarina Beach and Lee Point in July 2014 (Geo Oceans 2014c) were not observed during this survey, with the Halophila appearing to be in good health with little epiphytic growth. As with previous surveys, this survey reinforced the observation that the distribution of Halodule seagrass remains relatively consistent across surveys (Figure 8), except at Casuarina Beach, where its distribution was lower in May 2014 than on more recent surveys (July 2014 and October 2014). During this survey, Halodule was observed in similar areas to previous surveys (Appendix 2-3; Geo Oceans 2011a, 2012a, 2012e, 2013a, 2013b, 2013d, 2013e, 2014a, 2014b, 2014c), most noticeably at Fannie Bay, Woods Inlet and Charles Point West, where its extent has changed little since surveys commenced in 2012 (Figure 10, Appendix 2-3). No Halodule was observed at East Point during this survey, as was the case during the June 2012 survey. At Casuarina Beach, the spatial extent of Halodule has increased in the current survey relative to the May 2014 and July 2014 surveys (Figure 8), and was comparable to the distribution observed in the June 2012 survey (Geo Oceans 2012e). Within the Survey Areas, Halodule seagrass remains the dominant genera within the lower intertidal and upper subtidal habitat areas, while Halophila dominates the lower subtidal areas. To assist temporal comparison of habitat areas, a spatial area measure of mapping accuracy (the reliability estimate ) was introduced based on estimated error of habitat outlines between interpolations, presence/absence data and interpolations based on percent cover data. As with previous surveys, the high reliability estimate values encountered at Lee Point during this survey are likely a result of the patchy nature of Halodule distribution, as well as the wide spacing of sample areas at this Survey Area. A mapping accuracy assessment was not undertaken for this survey; however, the results from the previous accuracy assessments undertaken during the February 2013 and May 2013 surveys (93% and 90%, respectively) indicate that the survey design and methodology are effective in accurately mapping the distribution of seagrass within the defined Survey Areas. Page 19 of 23

119 5. REFERENCES Azpurua, M. and Ramos, K.R (2010). A Comparison of Spatial Interpolation Methods for Estimation of Average Electromagnetic Field Magnitude. Progress in Electromagnetics Research. Vol 14, pp Cardno (2014). Ichthys Project Nearshore Environmental Monitoring Plan. INPEX Gas Field Development. June Geo Oceans (2011a). Ichthys Gas Field Development Project: Benthic Habitat Mapping of the Darwin region Methods of Data Collection, Collation, and Map Production. Ichthys Technical Appendix S6. Geo Oceans (2011b). Marine Habitat Assessment East Arm Wharf Expansion Project: Draft Technical Memo. Prepared for NT Department for Lands and Planning. Geo Oceans (2012a). : Seagrass Habitat Monitoring Survey October 2012: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2012b). Marine Habitat Assessment East Arm Wharf Expansion Project: Technical Report. Prepared for NT Department for Lands and Planning. Unpublished report. Geo Oceans (2012c). Marine Habitat Assessment East Point Aquatic Life Reserve: Technical Report. Prepared for NT Power and Water Corporation. Unpublished report. Geo Oceans (2012d). Baseline Marine Habitat Monitoring Survey for NT Department of Land and Planning East Arm Wharf Expansion Project: Technical Report. Prepared for URS Australia Pty Ltd on behalf of NT Department of Land and Planning. Geo Oceans (2012e). : Seagrass Baseline and Marine Habitat Mapping. Survey June 2012: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2012f). Marine Habitat Monitoring Survey for NT Department of Land and Planning East Arm Wharf Expansion Project: Technical Report. Prepared for Macmahon Contractors Pty Ltd. Geo Oceans (2013a). : Seagrass Habitat Monitoring Survey February 2013: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2013b). : Seagrass Habitat Monitoring Survey May 2013: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2013c). Revised Towed Camera Seagrass Monitoring Method Statement. Prepared for Cardno on behalf of INPEX. Geo Oceans (2013d). : Seagrass Habitat Monitoring Survey August 2013: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2013e). : Seagrass Habitat Monitoring Survey November 2013: Technical Report. Prepared for Cardno on behalf of INPEX. Page 20 of 23

120 Geo Oceans (2014a). : Seagrass Habitat Monitoring Survey February 2014: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2014b). : Seagrass Habitat Monitoring Survey May 2014: Technical Report. Prepared for Cardno on behalf of INPEX. Geo Oceans (2014c). : Seagrass Habitat Monitoring Survey July 2014: Technical Report. Prepared for Cardno on behalf of INPEX. Hutchinson, M.F (1998). Interpolation of Rainfall Data with Thin Plate Smoothing Splines - Part I: Two Dimensional Smoothing of Data with Short Range Correlation. Journal of Geographic Information and Decision Analysis. Vol 2, pp INPEX (2010). Ichthys Gas Field Development Project, Draft Environmental Impact Statement. INPEX (2011). Ichthys Gas Field Development Project, Supplement to the Draft Environmental Impact Statement. INPEX (2013). Dredging and Spoil Disposal Management Plan East Arm (Rev 4). INPEX Operations Australia Pty Ltd. INPEX (2014). Dredging and Spoil Disposal Management Plan Gas Export Pipeline (Rev 6). INPEX Operations Australia Pty Ltd. Li, J. and Heap, A.D (2008). A Review of Spatial Interpolation Methods for Environmental Scientists. Geoscience Australia, Record 2008/23, 137pp. Page 21 of 23

121 Appendix 1 Spline Interpolation Settings and Parameters ArcGIS Resource Centre Parameter Explanation Data type Input point features (Required) The input point features containing the z- values to be interpolated into a surface raster. Composite Geodataset Z value field (Required) Field that holds a height or magnitude value for each point. This can be a numeric field or the shape field if the in_point_features contain Field z-values. Input barrier features (Optional) Output cell size (Required) Smoothing factor (Optional) The optional input barrier features to constrain the interpolation. The cell size at which the output raster will be created. If a value of zero is entered the shorter of the width or the height of the extent of the input point features in the input spatial reference, divided by 250, will be used as the cell size. The parameter that influences the smoothing of the output surface. The default is 0.0. No smoothing is applied when the value is zero and the maximum amount of smoothing is applied when the factor equals 1. Composite Geodataset Analysis cell size Project Data SeagrassCover_TransectArea scentroids_october2014 Seagrass_Cover; Halophila_Cover; Halodule_Cover; Seagrass_Presence Survey_Areas polygon 10 m Double 0 Page 22 of 23

122 Appendix 2 Maps of seagrass distribution in June 2012, October 2012, February 2013 and May 2013 Page 23 of 23

123 ± Darwin 100 Kilometers Map Legend Gas Export Pipeline Dredging Footprint Lee Point Spoil Disposal Site Survey Boundary (June 2012) Survey Boundary (Oct 2012 to May 2013) Seagrass Distribution June 2012 Casuarina Beach Oct 2012 Feb 2013 May 2013 Charles Point East Point Map Notes: Seagrass distribution was predicted by interpolation of the towed camera survey data. Present: seagrass cover > 0.5% = 1 Absent: seagrass cover <0.5% = 0 Cell values greater than 0.5 were classified as seagrass present. No data was captured in the February 2013 survey at Charles Point East Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Fannie Bay Ichthys Development Project Seagrass Survey 4 - May 2013 Seagrass Distribution Woods Inlet Kilometers GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_400 13/08/2013 BB A3 Copyright Geo Oceans Pty Ltd 2012 Appendix 2-1

124 ± Darwin 100 Kilometers Map Legend Gas Export Pipeline Dredging Footprint Spoil Disposal Site Lee Point Survey Boundary (Oct 2012 to May 2013) Survey Boundary (June 2012) Halodule Distribution June 2012 Casuarina Beach Oct 2012 Feb 2013 May 2013 Charles Point East Point Note: June 2012 Survey - The Survey Area at Casuarina Beach and Lee Point was smaller than the subsequent surveys; there was inadequate data to model Halodule and Halophila distribution at the survey sites on the Cox Peninsula. The Charles Point East site was not surveyed in February Disclaimer: While all attempts have been made to ensure the accuracy of the information presented, GeoOceans does not guarantee the correctness or suitability of the information for any particular purpose. Fannie Bay Ichthys Development Project Seagrass Survey 4 - May 2013 Halodule Distribution Copyright Geo Oceans Pty Ltd 2012 Woods Inlet Kilometers GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_400 2/08/2013 BB A3 Appendix 2-2

125 ± Darwin 100 Kilometers Map Legend Gas Export Pipeline Dredging Footprint Spoil Disposal Site Lee Point Survey Boundary (June 2012) Survey Boundary (Oct 2012 to May 2013) Halophila Distribution June 2012 Casuarina Beach Oct 2012 Feb 2013 May 2013 Charles Point East Point Note: June 2012 Survey - The Survey Area at Casuarina Beach and Lee Point was smaller than the subsequent surveys; there was inadequate data to model Halodule and Halophila distribution at the survey sites on the Cox Peninsula. The Charles Point East site was not surveyed in February There was no Halophila recorded in Feb Seagrass distribution was predicted by interpolation of the towed camera survey data. Present: seagrass cover > 0.5% = 1 Absent: seagrass cover <0.5% = 0 Cell values greater than 0.5 were classified as seagrass present. Fannie Bay Ichthys Development Project Seagrass Survey 4 - May 2013 Halophila Distribution Woods Inlet Kilometers Copyright Geo Oceans Pty Ltd 2012 GDA 1994 MGA Zone 52 Projection: Transverse Mercator Datum: GDA 1994 ± INPICHSGR_400 13/08/2013 BB A3 Appendix 2-3

126 Ichthys Nearshore Environmental Monitoring Program APPENDIX C DEPTH OF TOWED-VIDEO SAMPLE AREAS Prepared for INPEX Cardno

127 Appendix C-1 Number of towed-video transects at 0.5 m depth increments for all Survey Areas combined Depth (m LAT) June 2012 October 2012 February 2013 May August November February 2014 May 2014 July October Survey Areas were revised prior to survey D4 (August/September 2013) and no longer extend beyond the -6.5 m LAT depth contour. Results are therefore not directly comparable with previous surveys. Prepared for INPEX Cardno

128 Appendix C-2 Number of towed-video transects at 0.5 m depth increments for each Survey Area Survey Area Depth (m LAT) June 2012 October 2012 February 2013 May 2013 August November Casuarina Beach February May 2014 July Charles Point West October 2014 Prepared for INPEX Cardno

129 Survey Area Depth (m LAT) June 2012 October 2012 February 2013 May 2013 August November February 2014 May 2014 July 2014 East Point Fannie Bay Lee Point October 2014 Prepared for INPEX Cardno

130 Survey Area Depth (m LAT) June 2012 October 2012 February 2013 May 2013 August November February 2014 May 2014 July Woods Inlet October Survey Areas were revised prior to survey D4 (August/September 2013) and no longer extend beyond the -6.5 m LAT depth contour. Results are therefore not directly comparable with previous surveys Prepared for INPEX Cardno

131 Ichthys Nearshore Environmental Monitoring Program APPENDIX D TURBIDITY TIME SERIES Prepared for INPEX Cardno

132 Appendix D-1 Near-bed turbidity at Casuarina Beach during the reporting period (27 May 2014 to 21 October 2014) Prepared for INPEX Cardno

133 Appendix D-2 Near-bed turbidity at Charles Point (Site 02) during the reporting period (27 May 2014 to 21 October 2014) Prepared for INPEX Cardno

134 Appendix D-3 Near-bed turbidity at East Point during the reporting period (27 May 2014 to 21 October 2014) Prepared for INPEX Cardno

135 Appendix D-4 Near-bed turbidity at Lee Point during the reporting period (27 May 2014 to 21 October 2014) Prepared for INPEX Cardno

136 Appendix D-5 Near-bed turbidity at Fannie Bay during the reporting period (27 May 2014 to 21 October 2014) Prepared for INPEX Cardno

137 Appendix D-6 Near-bed turbidity at Woods Inlet during the reporting period (27 May 2014 to 21 October 2014) Prepared for INPEX Cardno

138 Ichthys Nearshore Environmental Monitoring Program APPENDIX E HISTORICAL CONDITIONS OF TURBIDITY PRIOR TO P1 (JULY 2014) Prepared for INPEX Cardno

139 Appendix E-1 Comparison of the Cumulative Distribution Functions (CDFs) for daily average turbidity between the period preceding P1 (27 May 2014 to 8 July 2014), the corresponding period from the previous year (27 May 2013 to 8 July 2013) and the previous reporting period (27 February 2014 to 26 May 2014) at Casuarina Beach and Charles Point (Site 02) Prepared for INPEX Cardno

140 Appendix E-2 Comparison of the Cumulative Distribution Functions (CDFs) for daily average turbidity between the period preceding P1 (27 May 2014 to 8 July 2014), the corresponding period from the previous year (27 May 2013 to 8 July 2013) and the previous reporting period (27 February 2014 to 26 May 2014) at East Point and Lee Point Prepared for INPEX Cardno

141 Appendix E-3 Comparison of the Cumulative Distribution Functions (CDFs) for daily average turbidity between the period preceding P1 (27 May 2014 to 8 July 2014), the corresponding period from the previous year (27 May 2013 to 8 July 2013) and the previous reporting period (27 February 2014 to 26 May 2014) at Fannie Bay and Woods Inlet Prepared for INPEX Cardno

142 Ichthys Nearshore Environmental Monitoring Program APPENDIX F HISTORICAL CONDITIONS OF TURBIDITY PRIOR TO P2 (OCTOBER 2014) Prepared for INPEX Cardno