The Forest Productivity Optimisation System A decision support tool

Transcription

1 You can change this image to be appropriate for your topic by inserting an image in this space or use the alternate title slide with lines. Note: only one image should be used and do not overlap the title text. Enter your Business Unit or Flagship name in the ribbon above the url. [delete instructions before use] The Forest Productivity Optimisation System A decision support tool Daniel Mendham, Jody Bruce, Kimberley Opie July 2013 CSIRO ECOSYSTEM SCIENCES/CSIRO SUSTAINABLE AGRICULTURE FLAGSHIP 1 Introducing the FPOS DSS Daniel Mendham

2 Introduction We recognize that there is often a disconnect between research and management Plantation managers are often making decisions based on minimal biophysical information and without integrative decision making tools. Our project aim: to develop a decision support system that provides a mechanism to deliver research outputs into the hands of managers also allows managers to feed back into research 2 Introducing the FPOS DSS Daniel Mendham

3 Background In the beginning there was BPOS BPOS V2 was produced through our work in Project (Managing and sustaining site resources) of the Forestry CRC The structural concepts of BPOS were retained for FPOS, but FPOS has a greatly expanded the scope New versions of CABALA Tree size distribution modelling New photosynthesis model for dealing with climate change Coppice (weeds + advanced health modules not active in FPOS) New empirical overlays 3 Introducing the FPOS DSS Daniel Mendham

4 Key differences between BPOS and FPOS New species 3 core species: (E. globulus), E. nitens, P. radiata 2 prospective species : E. smithii, P. pinaster New products Solid wood regimes can be accounted for New climates Down scaled predictions on future climates from 3 climate model predictions New regions/soil types Coverage of most of the key growing areas in southern Australia Updated interface 4 Introducing the FPOS DSS Daniel Mendham

5 Structure of the FPOS system FPOS is a web based system that consists of the following elements: A live version of tree size distribution CABALA A database of pre run CABALA outputs Empirical processing modules to add value to CABALA outputs An interface to allow the user to easily extract information from the database and empirical overlays 5 Introducing the FPOS DSS Daniel Mendham

6 Pre configured CABALA runs Input #of options Climatic zone 115 Species 5 Stocking rates 15 Soil fertility ratings 5 Soil depths 5 Thinning regimes 30 Climate model 4 Rainfall variation 5 Total combinations* 129,375,000 Database of outputs starts empty, is populated upon request 6 Introducing the FPOS DSS Daniel Mendham

7 Climatic zones and climate models 7 Introducing the FPOS DSS Daniel Mendham

8 FPOS climatic zones and climatic variation FPOS site classification is based on climatic zones Can be based on rainfall, temperature or evaporation Historical climate is derived from SILO ( ). Future climate models from downscaled GCM s (to be described later). Exposed site option Rainfall variation is derived from the 30 year sequence 20 x 10 year running means Below average and Above average are the mean +/ 1 SD Well below average and Well above average are the mean +/ 2 SD Only rainfall changes other variables stay the same 8 Introducing the FPOS DSS Daniel Mendham

9 Climatic zones WA Perth Bunbury Manjimup Albany Esperance Legend Major towns 550 mm rainfall, 1500 mm evaporation 550 mm rainfall, 1300 mm evaporation 650 mm rainfall, 1500 mm evaporation 650 mm rainfall, 1300 mm evaporation 650 mm rainfall, 1100 mm evaporation 750 mm rainfall, 1500 mm evaporation 750 mm rainfall, 1300 mm evaporation 750 mm rainfall, 1100 mm evaporation 850 mm rainfall, 1500 mm evaporation 850 mm rainfall, 1300 mm evaporation 850 mm rainfall, 1100 mm evaporation 950 mm rainfall, 1500 mm evaporation 950 mm rainfall, 1300 mm evaporation 950 mm rainfall, 1100 mm evaporation 1050 mm rainfall, 1500 mm evaporation 1050 mm rainfall, 1300 mm evaporation 1050 mm rainfall, 1100 mm evaporation 1150 mm rainfall, 1500 mm evaporation 1150 mm rainfall, 1300 mm evaporation 1150 mm rainfall, 1100 mm evaporation 1250 mm rainfall, 1100 mm evaporation 9 Introducing the FPOS DSS Daniel Mendham

10 Climatic zones GT Bendigo Mount Gambier Hamilton Ballarat Legend Major towns 550 mm rainfall, 1300 mm evaporation 550 mm rainfall, 1100 mm evaporation 650 mm rainfall, 1300 mm evaporation Warrnambool Colac 650 mm rainfall, 1100 mm evaporation 650 mm rainfall, 900 mm evaporation 750 mm rainfall, 1100 mm evaporation 750 mm rainfall, 900 mm evaporation 850 mm rainfall, 1100 mm evaporation 850 mm rainfall, 900 mm evaporation 950 mm rainfall, 1100 mm evaporation 950 mm rainfall, 900 mm evaporation 10 Introducing the FPOS DSS Daniel Mendham

11 Climatic zones Eastern Victoria Legend Major towns 550 mm rainfall, 1300 mm evaporation 550 mm rainfall, 1100 mm evaporation 650 mm rainfall, 1300 mm evaporation 650 mm rainfall, 1100 mm evaporation 650 mm rainfall, 900 mm evaporation 750 mm rainfall, 1300 mm evaporation 750 mm rainfall, 1100 mm evaporation 750 mm rainfall, 900 mm evaporation 850 mm rainfall, 1300 mm evaporation 850 mm rainfall, 1100 mm evaporation 850 mm rainfall, 900 mm evaporation 950 mm rainfall, 1300 mm evaporation 950 mm rainfall, 1100 mm evaporation 950 mm rainfall, 900 mm evaporation 1050 mm rainfall, 1300 mm evaporation 1050 mm rainfall, 1100 mm evaporation Melbourne Morwell Sale 1150 mm rainfall, 1300 mm evaporation 1150 mm rainfall, 1100 mm evaporation 1250 mm rainfall, 1300 mm evaporation 1250 mm rainfall, 1100 mm evaporation 1250 mm rainfall, 900 mm evaporation 1350 mm rainfall, 1300 mm evaporation 1350 mm rainfall, 1100 mm evaporation 1350 mm rainfall, 900 mm evaporation 1450 mm rainfall, 1100 mm evaporation 1450 mm rainfall, 900 mm evaporation 11 Introducing the FPOS DSS Daniel Mendham

12 Climatic zones Tasmania Legend Burnie Devonport Launceston Major towns 50 m, 550 mm 50 m, 650 mm 50 m, 750 mm 250 m, 950 mm 250 m, 1050 mm 250 m, 1150 mm 250 m, 1250 mm 450 m, 750 mm 450 m, 850 mm 450 m, 950 mm 450 m, mm 50 m, 850 mm 250 m, 1350 mm 550 m, 550 mm 50 m, 950 mm 250 m, 1450 mm 550 m, 650 mm 50 m, 1050 mm 250 m, 1550 mm 550 m, 750 mm 50 m, 1150 mm 350 m, 550 mm 550 m, 850 mm 50 m, mm 350 m, 650 mm 550 m, 950 mm 150 m, 550 mm 350 m, 750 mm 550 m, mm Hobart 150 m, 650 mm 150 m, 750 mm 350 m, 850 mm 350 m, 950 mm 650 m, 750 mm 650 m, 850 mm 150 m, 850 mm 350 m, 1050 mm 650 m, 900+ mm 150 m, 950 mm 350 m, 1150 mm 750 m, 550 mm 150 m, mm 350 m, 1250 mm 750 m, 650 mm 250 m, 550 mm 250 m, 650 mm 350 m, 1350 mm 350 m, mm 750 m, 750 mm 750 m, 850 mm 250 m, 750 mm 450 m, 550 mm 750 m, 950 mm 250 m, 850 mm 450 m, 650 mm 750 m, mm 12 Introducing the FPOS DSS Daniel Mendham

13 Selection of future climate models 24 GCM s and 6 emission scenarios currently available We reduced this to a choice of 3 in FPOS Best case Worst case Most likely (Historical) 13 Introducing the FPOS DSS Daniel Mendham

14 Clarke JM, Whetton PH, Hennessy KJ (2011) Climate model selection 14 Introducing the FPOS DSS Daniel Mendham

15 15 Introducing the FPOS DSS Daniel Mendham

16 Downscaling of the selected climate models A statistical stationary approach to modify the base climate (current climate) Current climate is defined by the IPCC as Applied to 2030 time climate model predictions Some limitations to this approach Not capturing extremes in daily weather Doesn t capture changes in rainfall pattern 16 Introducing the FPOS DSS Daniel Mendham

17 CABALA Testing and Validation 17 Introducing the FPOS DSS Daniel Mendham

18 Species Parameters for CABALA CABALA has been recently rewritten in many areas, so old parameters no longer work even for existing species Development of new parameters is a complicated and fraught Validation data comes from a range of sources, experiments, papers, industry. And there is always the unknown what has happened at the site are the soils too complicated for CABALA? nutritional problems? is the weather sequence suitable? Are we getting the right answer for the right reason? 18 Introducing the FPOS DSS Daniel Mendham

19 Eucalyptus globulus y = x R² = Introducing the FPOS DSS Daniel Mendham Presentation title Presenter name Page 19

20 Eucalyptus globulus ET AvAnnCabET 1: y = x R² = Introducing the FPOS DSS Daniel Mendham Presentation title Presenter name Page 20

21 Pinus radiata Predicted volume y = 0.84x + 93 R² = Observed Volume 21 Introducing the FPOS DSS Daniel Mendham

22 The FPOS interface 22 Introducing the FPOS DSS Daniel Mendham

23 Login page Access to the system is restricted Logins usually at organisational level Any information you enter into the system is only available to your login 23 Introducing the FPOS DSS Daniel Mendham

24 Site Inputs 24 Introducing the FPOS DSS Daniel Mendham

25 Site inputs page This is where you can See the sites you have entered Edit, create or delete specific information 25 Introducing the FPOS DSS Daniel Mendham

26 Site details Sites are characterised by a matrix of fixed factors to describe Climatic zone Soil type Soil depth Rainfall variation Climate model Management factors 26 Introducing the FPOS DSS Daniel Mendham

27 How is the soil information used? Soil types and soil depths are used by the model to represent the water holding capacity of the soil Soil fertility is not accounted for by soil type this is a separate input Soil fertility can be estimated by the system based on total C and C:N ratios, but this isn t always accurate: the algorithm gives the following result: Soil Carbon (%) CN ratio = high fertility 5 = low fertility Use your own intuition to check and/or enter fertility 27 Introducing the FPOS DSS Daniel Mendham

28 How are the products and thinning regimes used? Users can choose between pulpwood or sawlog regimes (peeler logs can be assessed as a sawlog regime) Rotation length is up to 20 years for pulpwood, or up to 40 years for sawlog regime Yield of pulpwood rotations are based only on standing volume Yield of sawlog rotations is based on log size class distribution CABALA outputs include stand size class distribution This is split into log sizes during the CABALA run, in 5 cm min diameter increments from <10 cm to >55 cm. Assumptions include: minimum billet length of 2 m for any given size Conical stem volume shape Log sizes are saved as part of the CABALA output 28 Introducing the FPOS DSS Daniel Mendham

29 Observed productivity data You can also enter productivity data for a site 29 Introducing the FPOS DSS Daniel Mendham

30 Economic parameters Scenario outputs can be based on biophysical or economic basis Categories of economic inputs include: Establishment costs Management costs Harvest and transportation Returns Inflation rates 30 Introducing the FPOS DSS Daniel Mendham

31 Site Outputs 31 Introducing the FPOS DSS Daniel Mendham

32 Site Outputs A range of outputs can be requested for a scenario: Productivity Nutrient export Economics Water use efficiency Nitrogen fertilization Species Climate model 32 Introducing the FPOS DSS Daniel Mendham

33 Nutrient Export Explore the impact of residue retention or removal on site nutrient pools 33 Introducing the FPOS DSS Daniel Mendham

34 Economics What happens to the predicted economic outputs With different economic models? With different rotation lengths? 34 Introducing the FPOS DSS Daniel Mendham

35 Species CABALA will run each of the 5 species for any given scenario Not all outputs are likely to make sense as some species will be outside of their core model validation zone. CABALA will fail when trying to model some species off site for example, E. nitens in the northern areas of SW WA 35 Introducing the FPOS DSS Daniel Mendham

36 Climate model How is climate change likely to affect my predicted productivity? 36 Introducing the FPOS DSS Daniel Mendham

37 Outputs WUE Water use efficiency is volume of wood produced per unit of water, or GPP/unit of water transpired. This interface allows you to explore the effects of different site or different management on water use efficiency 37 Introducing the FPOS DSS Daniel Mendham

38 Outputs N nutrition N nutrition is a simple cost/benefit analysis for N fertilizer addition. Response curve based on C:N ratio is ok for globulus in most situations but not for other species Users need to enter their own coefficients The output is the rate of N required in any given year to maximise the NPV of the fertilizer addition 38 Introducing the FPOS DSS Daniel Mendham

39 Multi site outputs Sensitivity Analysis Mapping tool 39 Introducing the FPOS DSS Daniel Mendham

40 Model accuracy Explore how well the model is predicting across your sites 40 Introducing the FPOS DSS Daniel Mendham

41 Wood flow predictions Explore how rainfall variation and/or climate change may impact on standing volume and harvest volumes 41 Introducing the FPOS DSS Daniel Mendham

42 Sensitivity analysis Allows for comparison of outputs with different Soil types Soil depths Soil fertilities Economic scenario Rainfall regime Harvest age Rotation Species Climate model Thinning regime Can be evaluated as biophysical or economic outputs 42 Introducing the FPOS DSS Daniel Mendham

43 Mapping tool View site locations In relation to climatic zones Quick summary available Based on google maps can zoom in to block level if desired 43 Introducing the FPOS DSS Daniel Mendham

44 Next steps Model improvement and independent validation Support for adoption Feedback from users Filling of gaps in knowledge/understanding Iterative enhancement 44 Introducing the FPOS DSS Daniel Mendham

45 Acknowledgements FWPA CRC Forestry CSIRO FPOS project partners WA Plantation Resources Green Triangle Forest Products Forestry SA APFL ABP HVP FPOS steering committee chair FPOS steering committee members 45 Introducing the FPOS DSS Daniel Mendham

46 Thank you CSIRO Ecosystem Sciences Daniel Mendham t e Daniel.Mendham@csiro.au w CSIRO ECOSYSTEM SCIENCES/CSIRO SUSTAINABLE AGRICULTURE FLAGSHIP 46 Introducing the FPOS DSS Daniel Mendham