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 1.Determine how land use change scenarios (BAU & GOV 2010- 2050) affect biodiversity across the Amazon Basin; 2.Identify the specific species and ecoregions under threat; 3.Conduct nested-scale simulation and empirical analyses within dynamic frontiers of BR163 & Mato Grosso; 4.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; 5.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. 2050 BAU Scenario: Deforested2,698,735 km 2 Forest3,320,409 km 2 Non-forest1,497,685 km 2 500 km Soares-Filho et al. 2004

5. 2050 Governance Scenario: Deforested 1,655,734 km 2 Forest 4,363,410 km 2 Non-forest1,497,685 km 2 500 km 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 BAU 2050 89% Range Loss

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

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

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

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

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

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

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

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

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

22. Current Marsh Deer (Blastocerus dichotomus) Range 1,084,523 km 2

23. 50,920 km 2 Critical Marsh Deer Range with Suitable Habitat

24. Amazon Region Protected Areas Program (ARPA) Areas in BAU 2050: Deforested 381,775 km 2 Forest 176,122 km 2 Non-forest 50,391 km 2

25. ARPA Areas in GOV 2050: Deforested 71,902 km 2 Forest485,995 km 2 Non-forest 50,391 km 2

26. BAU 2010 Deforested 84,712 km 2 Forest473,185 km 2 Non-forest 50,391 km 2

27. BAU 2020 Deforested 149,947 km 2 Forest 407,950 km 2 Non-forest 50,391 km 2

28. BAU 2030 Deforested 235,982 km 2 Forest 321,915 km 2 Non-forest 50,391 km 2

29. BAU 2040 Deforested 321,941 km 2 Forest 235,956 km 2 Non-forest 50,391 km 2

30. BAU 2050 Deforested 381,775 km 2 Forest 176,122 km 2 Non-forest 50,391 km 2

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

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

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

34. % Deforested Deforestation Within Ecoregions 75% 83%

35. 100 km 86% of Remaining Ombrofila Estacional Forests in BAU 2050 in Protected Areas/Indigenous Reserves XINGU BAU 2050 – 15% Forest 184,076 km 2

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;