Effects of Land Use Change on Mammals Across Dynamic Frontiers in the Amazon Basin

1. Effects of Land Use Change on Mammals Across Dynamic Frontiers in the Amazon Basin Claudia Azevedo-Ramos, Oswaldo de Carvalho, Jr., Ana Cristina M. Oliveria (IPAM); Lisa M. Curran & Alice McDonald (Yale University); Britaldo Silveira Soares-Filho (UFMG), Ane A.C. Alencar (IPAM) & Daniel C. Nepstad (WHRC/IPAM)

2. Major Questions & Objectives • Determine how land use change scenarios (BAU & GOV 2010-2050) affect biodiversity across the Amazon Basin; • Identify the specific species and ecoregions under threat; • Conduct nested-scale simulation and empirical analyses within dynamic frontiers of BR163 & Mato Grosso; • Determine species-specific and spatially-explicit effects of forest cover loss, fire and land use type on vertebrate populations; scale-up to basin-wide analyses; • Influence biodiversity conservation and management priorities/approaches toward regions undergoing dynamic land use change and outside of protected areas incl. private landholders

3. Conservative Methods for Initial Assessment of Effects of Land Use Change on Mammals • 164 mammal species (non-volant; non-aquatic); 23 Families, 74 Genera; • 97%-15% (median = 89%) of geo-range in Amazon basin; Assumptions: habitat widespread & evenly distributed throughout range; most optimistic range projected by experts – often limited sampling points; mammals most resilient w large ranges; Prelim. Analyses: No key habitats or corridors removed; No spatially-explicit dynamics of forest/non-forest; Initial Analyses did NOT include: logged/hunted/burned/climate change or fine scale 9 habitat type associations with probability of movement/use; but underway in next iteration with refined models

4. 500 km 2050 BAU Scenario: Deforested 2,698,735 km2 Forest 3,320,409 km2 Non-forest 1,497,685 km2 Soares-Filho et al. 2004

5. 500 km 2050 Governance Scenario: Deforested 1,655,734 km2 Forest 4,363,410 km2 Non-forest 1,497,685 km2 Soares-Filho et al. 2004

6. % Amazon Range Deforested # species (164 spp. examined)

7. Critical Habitats for Imperiled Species – Full Species Ranges (Imperiled: n=48; >40% Amazonian Range Deforested Under BAU 2050)

8. Critical Habitats for Imperiled Species – Forest in BAU 2050 (Imperiled: n=48; >40% Amazonian Range Deforested Under BAU 2050)

9. Critical Habitats for Imperiled Species – Forest in GOV 2050 (Imperiled: n=48; >40% Amazonian Range Deforested Under BAU 2050)

10. Critical Habitats for Imperiled Species – Full Species Ranges (Imperiled: n=12; >40% Amazonian Range Deforested Under GOV 2050)

11. Critical Habitats for Imperiled Species – Forest in GOV 2050 (Imperiled: n=12; >40% Amazonian Range Deforested Under GOV 2050)

12. Callitrichidae Mico argentatus Silvery Marmoset 89% Range Loss BAU 2050

13. Callitrichidae Mico argentatus Silvery Marmoset Gov Saves 45% 80.4% Outside PAs, ARPA & Ind. Res. GOV 2050

14. Atelidae Ateles marginatus White-whiskered Spider Monkey 69% Range Loss BAU 2050

15. Atelidae Ateles marginatus White-whiskered Spider Monkey Gov Saves 35% 54% Outside PAS, ARPA & Indig Res. GOV 2050

16. High Hunting Pressure Nomadic/Seasonal Habitat Use Large Ranges Epidemics from Livestock Diseases Major Prey Large Cats Tayassuidae Tayassu pecari White-lipped Peccary BAU 2050 37% Range Loss

17. Tayassuidae Tayassu pecari White-lipped Peccary 66% Outside PAs, ARPA Indig. Gov Saves 15% Range GOV 2050

18. Heavy Hunting Pressure Prey Base Eroded Will Prey on Livestock Largest Contiguous Ranges Remaining within Amazon Basin; 36% Range Loss Felidae Panthera onca Jaguar BAU 2050

19. Felidae Panthera onca Jaguar 65% Outside PAs, ARPA Indig R. Gov Saves 14% but also Prey base GOV 2050

20. High Hunting Pressure Critical Habitats w/in Range Epidemics from Livestock Diseases Major Prey of Large Cats Cervidae Blastocerus dichotomus Marsh Deer BAU 2050 41% Historical Range Loss

21. Cervidae Blastocerus dichotomus Marsh Deer 66% Outside PAs, ARPA, Ind. Reserves; Gov Saves 16% Range GOV 2050

22. Current Marsh Deer (Blastocerus dichotomus)Range 1,084,523 km2

23. Critical Marsh Deer Range with Suitable Habitat 50,920 km2

24. Amazon Region Protected Areas Program (ARPA) Areas in BAU 2050: Deforested 381,775km2 Forest 176,122 km2 Non-forest 50,391 km2

25. ARPA Areas in GOV 2050: Deforested 71,902 km2 Forest 485,995 km2 Non-forest 50,391 km2

26. BAU 2010 Deforested 84,712 km2 Forest 473,185 km2 Non-forest 50,391 km2

27. BAU 2020 Deforested 149,947 km2Forest 407,950 km2 Non-forest 50,391 km2

28. BAU 2030 Deforested 235,982 km2 Forest 321,915 km2 Non-forest50,391 km2

29. BAU 2040 Deforested 321,941 km2 Forest235,956 km2 Non-forest 50,391 km2

30. BAU 2050 Deforested 381,775 km2 Forest176,122 km2 Non-forest50,391 km2

31. Governance Critical to Maintain Forest Cover in ARPA Sites 46% differential area loss

32. WWF’s Priority Conservation Areas SWA (Global 200) 1. SWA Moist Forest 2. Jurua-Purus Moist Forest 3. Madeira-Purus Moist Forest 4. Madeira-Tapajos Moist Forest 2 1 3 4 Peru Bolivia SWA Global 200

33. Forest Loss Within Ecoregions BAU 2050 GOV 2050 % Ecoregion Deforested

34. Deforestation Within Ecoregions 75% 83% 75% % Deforested

35. 86% of Remaining Ombrofila EstacionalForests in BAU 2050 in Protected Areas/Indigenous Reserves 100 km BAU 2050 – 15% Forest 184,076 km2 XINGU

36. Critical Importance of Privately-Owned Land Management (APP & Reserva Legal) within Mato Grosso Dry Forests • Distinctive forest communities • Region harbors 46 mammalian species; • 57% spp. on CITES; inc. flagship species, heavily hunted and vulnerable species; • Potentially >85% habitat loss; • Critical source/sink habitats esp. for Xingu/Indigenous lands; • Private holdings critical for biodiversity: 82,000 ha; 52% forested; APP riparian zones maintained 6,000 ha; • Document before-after recovery from fire

37. Current Analyses with Future Activities • 88 mammal species examined within BR 163; • Conducting spatially-explicit analyses w simulations (99-02) within 4 subregions along frontier incl BAU/GOV 2010-2050; • Will incorporate species-specific habitat use, hunting pressure with 1) logged, 2) pasture, 3) mechanized agri; 4) smallholders; and 5) burned area or fire vulnerability models; • Address lack of ecological data OUTSIDE PAs & within specific habitats/uses/vulnerability within the matrix; • Simulate a suite of decision rules re spatial extent of crossings, hunting annuli and recovery

38. Summary Results to Date • Effective “governance” critical for mammalian conservation in the Amazon basin; • ARPA essential (esp. for > 21 highly vulnerable primate species), but establishment/demarcation alone insufficient; • Focal ecoregions identified for concerted management efforts with high mammalian diversity/vulnerability: Tapajos-Xingu, Purus-Madeira & Madeira-Tapajos; Mato Grosso • Highly vulnerable taxa (BAU 2050) have 54-87% of range outside PAs, ARPA & Indigenous Reserves- • Even if lose 30-40% of habitat, predict synergistic effects of logging/hunting, fragmentation, burned areas with ecological interactions esp. in key ecoregions with high land cover change;

39. Thank you