Measuring and monitor changes in regional ecosystem services using Auckland Council s Terrestrial Biodiversity Monitoring Programme (TBMP) Craig Bishop, Stacey Lockie, Todd Landers and Jade Khin (RIMU) Other funding and support from operations biosecurity and biodiversity teams
Basic outline of program Forest and scrub data in c.400 plots with tier 1/2/3/4 split Methods very similar to standard 20m x 20m forest plots + birds + pests + condition data All plots measured on a five year cycle with first remeasure due in 2014/15 Wetland monitoring in (at least) 220 plots, plus more intensive in c.5 key wetlands. Other types to add (coastal, hist. rare ecosystems etc.)
Why do we collect this data? To comply with various Acts and international commitments [Rio Treaty and NZ Biodiversity Strategy (2000), Resource Management Act (?), Local Government Act (?), NPS on biodiversity (?), and national SOE standards issued by MfE, DoC etc. (?)] Auckland Plan (& Unitary Plan?) directives [Ensure that the resources and production systems that underpin working rural land are protected, maintained and improved; Integrate consideration of ecosystem services into decision making] Public mandate for a variety of practical (weeds and pests, seas slugs, stream and beach water quality) and more biophilia type reasons
What use is the data? Characterize forest composition and structure, and bird abundance and distribution Weed and pest infestations and distribution Regional State of the Environment (SOE) monitoring, including changes in provision of ecosystems services Quantify biodiversity gains from intensive management Baseline data for other uses (e.g. biodiversity offsets) Provide information/ inspiration for politicians and local interest groups National reporting of biodiversity Getting out an about in the landscape, including many little visited or unknown nooks and crannies Building links between council staff managing biodiversity in different areas (RIMU, Biodiversity, Biosecurity, Regional Parks, Local Parks, Zoo) (Better) Scientific enquiry and interest Other. Serendipity and the value of good baseline data
Major strength of Auckland program is the wide landscape/ ecosystem coverage Not just extensive forest tracts sampled, different landscapes including rural, urban, peri-urban (also by political unit, geographical, land tenure, land type, ecological district, management, LENZ class etc.) Wide spatial coverage with replication to boost sample size in some groups Landscape scale more suitable for measuring ecosystem services in different types of habitat Leverage from other programs using data + adding points or types of analysis
Changes in seedling density and native dominance in forest plots by LENZ level IV threat class (n = 218) LENZ level IV threat class Native seedling density Exotic/ native seedling Weedy exotic/ native seedling Acutely threat 15,300 0.26 0.06 Chronic threat 13,700 0.34 0.10 At risk 30,100 0.07 0.04 Better protect 27,200 0.05 0.02 Well protect 28,600 0.02 0.01
Changes in seedling density and native dominance in forest plots by Ecological District Ecological District Native seed/ density Exotic/ native Awhitu 14,800 0.12 GBI (Aotea) 41,800 0.02 Hunua Kaipara Manukau Otamatea Rodney Tamaki Waitakere 19,200 0.03 21,800 0.18 7,700 0.28 29,200 0.11 27,500 0.03 25,500 0.19 38,600 0
Many other types of indicators can also be derived from the data usefulness? Total Basal area (m2/ ha) Native basal area (m2/ ha) Native BA/ exotic BA Rural 99.3 91.8 0.06 Urban 104.5 73.4 0.39 Wild main Tenure 161.4 116.4 0.0 exotic: native bird species Island 0.23 Wild main 0.76 Rural main 0.89 Urban 1.17 TOTAL 0.53 0.2 0.15 0.1 0.05 0-0.05 45 40 35 30 25 20 15 10 5 0 Average density of native birds in 5 minute bird counts Hunua - KMA Hunua - rest Waitakere - ARK Mean exotic: native BA ratio by LENZ threat class Acutely threat Chronic threat At risk Crit. under protected Waitakere - rest Protected
Approach to deriving numerical indicators Decide on a meaningful indicator (e.g. % BA of indigenous trees) and assess for a wide range of values in natural systems (from plot data); including successional gradients Convert to a 0 1 (or other standard) scale. Easy for % data, needs a good regional dataset for others (e.g. total BA, # species, diversity of growth forms etc.) Repeat X times Sum of individual indicators is biodiversity score for a specific type of ecosystem or location, this can then be entered into a (larger) ecosystem services assessment framework
Plugging into a ecosystem services calculation Category Ecosystem service Usefulness of forest plot data for valuing this service Supporting services nutrient and seed dispersal and cycling? Investigate links between biodiversity and ecosystem processes Supporting services Primary production Forest plots, direct from BA values and changes Provisioning Wild food Forest plots, species presence and abundance information Provisioning Water? Regulating carbon sequestration and climate regulation Forest plot data, direct measures with reference to other NZ studies Regulating Cultural services Cultural services waste decomp. and detoxification cultural, intellectual and spiritual inspiration recreational experiences (including ecotourism)? Investigate links between biodiversity and ecosystem processes Forest plots (with ref to standards), LENZ data? (minor)
Areas of further interest & study I Key to usefulness for ecosystem services is analysis/ case studies that correlate measured biodiversity parameters and measure of the value of ecosystem services Links between native/ exotic species composition and structure & physical processes (soil nutrient status, litter decay, processing aerial and waterborne pollutants) (also to inverts, soil MO s etc.) Using plot data to create larger scale maps of forest condition around a sample point, rather than just point source plot information
Areas of further interest & study II More efficient use of field time: $ to collect data vs. value from the data Links between land management and biodiversity (cumulative change; measure and monitor # and impact of permitted vs. consented vs. unconsented biodiversity negatives ) Derivation of useful indicators of ecosystem quality (including ecosystem services) from the large datasets generated by plot based sampling. Which indicator? How to calculate? What to use as a benchmark? How to present in a way that is correct? Captures the public imagination?
The end Thanks to the ex ARC staff who got this program up and running, and all the field staff 2009-2013