1. Synergies and tradeoffs between conservation of tiger habitat and ecosystem service provision in Sumatra, Indonesia Nirmal Bhagabati World Wildlife Fund

2. Background Incorporating ecosystem services into conservation planning still a new field Quantitative / spatial analyses of ES distribution are necessary first steps But data, time window and capacity to do such analyses often limited Thus, often need to analyses simply, with limited data.

3. Sumatra as a case study Rich biodiversity Ecosystem services of global (carbon sequestration) and local (hydrological, NTFPs etc) significance High deforestation rates But also policy and advocacy windows of opportunity at regional, national and international levels And potential for PES schemes

4. Questions 1) Where, and how much, did ES provision align with tiger habitat conservation in 2008? 2) How will ES service provision and the quality of tiger habitat change from 2008 to two alternative scenarios of future development (green vs BAU)? 3) How does targeting single vs multiple services change the potential for attaining conservation goals?

5. Q1. Where, and how much, did ES provision align with tiger habitat conservation in 2008?

6. Based on visual inspection, InVEST model score of > 0.9 corresponds reasonably well with observed tiger occurrence (from Wibisono and Pusparini 2010). We could use 0.9 as a rule- of-thumb cutoff score, or else find a statistically supported cutoff score? First, find threshold habitat quality score (from InVEST) such that scores higher than this are likely to have tigers

7. This is based on tiger conservation landscape (TCL ) polygons, but these are quite similar to our InVEST score > 0.9 or the observed areas Overlays of ES with tiger habitat in 2008

8. Relative importance of Tiger Conservation Landscapes for Ecosystem Services in Central Sumatra 5000 % !! % difference in services between TCLs and rest of landscape in 2008 How do high habitat quality areas compare to the rest of the landscape with regard to ES supply?

9. Q2. How will ES service provision and the quality of tiger habitat change from 2008 to two alternative scenarios of future development (green vs BAU)?

10. Region-wide change in services and habitat under alternative scenarios Can make similar bar graph just for the areas that go above or below the 0.9 quality threshold under either scenario

11. Assuming a habitat quality score of >= 0.9 represents good tiger habitat… Calculate how much area of 0.9 and greater quality score is gained or lost under either scenario Calculate % gain or loss of service stocks in these areas of high-quality habitat loss

12. Q3. How does targeting single vs multiple services change the potential for attaining conservation goals?

13. High total carbon gain High gains in at least one service Sub-watersheds with high service gains in the Vision relative to the plan: What are the potential gains in habitat? High biomass carbon gain

14. Could also do the following Target the sub-watersheds with the top x% of gains (vision relative to plan) in – Only one service - At least one service For these sub-watersheds, ask: – How much additional area do we get of 0.9 quality or better, if we select for only one service vs at least one?

15. What is new / significant about this study? Many previous studies of ES/biodiv tradeoffs primarily done as research studies – This one done at the request of WWF Indonesia and govt stakeholders to provide input to spatial planning – Being disseminated to stakeholders

16. What is new / significant about this study? Synergies between conservation priorities and ES provision still a matter of debate – This paper adds new information to this issue Directly relevant to WWF conservation goals (tiger conservation) Spatially explicit at a fairly detailed scale (districts), unlike some previous studies

17. Limitations and future considerations Simple scenarios Only mapped service stocks, not realized supply to beneficiaries Ground-truthing and validation needed 0.9 quality threshold is based on eyeballing, more sophisticated threshold needed? 0.9 (or any quality threshold) does not necessarily indicate tigers presence

18. Limitations and future considerations Need to consider opportunity costs, other socioeconomic aspects for policy design Ultimate impact on the ground? – Yet to see – perhaps more immediately, focus on extent to which discourse surrounding LU and conservation is being influenced by these analyses

19. Thanks…. Team Sumatra (Thomas Barano, Marc Conte, Driss Ennaanay, Oki Hadian, Emily McKenzie, Nasser Olwero, Amy Rosenthal, Aurelie Shapiro, Heather Tallis, and Stacie Wolny) Taylor for helping to structure and think this through – and for constructive “prodding”

21. Q1. Where does ES provision align with tiger habitat conservation? Find threshold habitat score such that scores higher than this are likely to have tigers – Statistically or by eyeballing? Overlays of ES with tiger habitat What proportion of total ES supply within landscape is contained within high quality habitat? – And how does this proportion change with scenarios?

22. Based on visual inspection, InVEST model score of > 0.9 corresponds reasonably well with observed tiger occurrence

23. 904 randomly distributed sampling points at least 5 km from one another (to reduce spatial autocorrelation) Observed Sumatran tiger distribution is from Wibisono and Pusparini (2010)

24. Tigers present according to W&P (2010) N = 343 points Mean habitat quality score = 0.8 Sd = 0.3 Rest of study area N = 561 points Mean habitat quality score = 0.3 Sd = 0.2 Distribution of habitat quality scores from InVEST