| Date post: | 17-Jan-2016 |
| Category: |
Documents |
| Upload: | emery-wilcox |
| View: | 218 times |
| Download: | 1 times |
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)
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
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
2050 BAU Scenario:Deforested 2,698,735 km2
Forest 3,320,409 km2
Non-forest 1,497,685 km2
500 km Soares-Filho et al. 2004
2050 Governance Scenario:Deforested 1,655,734 km2
Forest 4,363,410 km2
Non-forest 1,497,685 km2
500 km Soares-Filho et al. 2004
% Amazon Range Deforested#
sp
eci
es
(164
sp
p. e
xa
min
ed
)
Critical Habitats for Imperiled Species – Full Species Ranges(Imperiled: n=48; >40% Amazonian Range Deforested Under BAU 2050)
Critical Habitats for Imperiled Species – Forest in BAU 2050(Imperiled: n=48; >40% Amazonian Range Deforested Under BAU 2050)
Critical Habitats for Imperiled Species – Forest in GOV 2050(Imperiled: n=48; >40% Amazonian Range Deforested Under BAU 2050)
Critical Habitats for Imperiled Species – Full Species Ranges(Imperiled: n=12; >40% Amazonian Range Deforested Under GOV 2050)
Critical Habitats for Imperiled Species – Forest in GOV 2050(Imperiled: n=12; >40% Amazonian Range Deforested Under GOV 2050)
CallitrichidaeMico argentatusSilvery Marmoset
BAU 2050
89% Range Loss
GOV 2050
CallitrichidaeMico argentatusSilvery Marmoset
Gov Saves 45%80.4% Outside PAs, ARPA& Ind. Res.
AtelidaeAteles marginatusWhite-whiskered Spider Monkey
BAU 2050
69% Range Loss
GOV 2050
AtelidaeAteles marginatusWhite-whiskered Spider Monkey
Gov Saves 35%54% Outside PAS, ARPA &Indig Res.
BAU 2050
TayassuidaeTayassu pecariWhite-lipped Peccary
High Hunting PressureNomadic/Seasonal Habitat UseLarge Ranges Epidemics from Livestock DiseasesMajor Prey Large Cats
37% Range Loss
GOV 2050
TayassuidaeTayassu pecariWhite-lipped Peccary
66% Outside PAs, ARPA Indig.Gov Saves 15% Range
BAU 2050
FelidaePanthera oncaJaguar
Heavy Hunting PressurePrey Base Eroded Will Prey on Livestock Largest Contiguous RangesRemaining within Amazon Basin;36% Range Loss
GOV 2050
FelidaePanthera oncaJaguar
65% Outside PAs, ARPA Indig R.Gov Saves 14% but also Prey base
BAU 2050
CervidaeBlastocerus dichotomusMarsh Deer
High Hunting PressureCritical Habitats w/in RangeEpidemics from Livestock DiseasesMajor Prey of Large Cats
41% Historical Range Loss
GOV 2050
CervidaeBlastocerus dichotomusMarsh Deer
66% Outside PAs, ARPA, Ind. Reserves; Gov Saves 16% Range
Current Marsh Deer (Blastocerus dichotomus) Range
1,084,523 km2
50,920 km2
Critical Marsh Deer Range with Suitable Habitat
Amazon Region Protected Areas Program (ARPA) Areas in BAU 2050:Deforested 381,775 km2
Forest 176,122 km2
Non-forest 50,391 km2
ARPA Areas in GOV 2050:Deforested 71,902 km2
Forest 485,995 km2
Non-forest 50,391 km2
BAU 2010Deforested 84,712 km2
Forest 473,185 km2
Non-forest 50,391 km2
BAU 2020Deforested 149,947 km2 Forest 407,950 km2
Non-forest 50,391 km2
BAU 2030Deforested 235,982 km2
Forest 321,915 km2
Non-forest 50,391 km2
BAU 2040Deforested 321,941 km2
Forest 235,956 km2
Non-forest 50,391 km2
BAU 2050Deforested 381,775 km2
Forest 176,122 km2
Non-forest 50,391 km2
Governance Critical to Maintain Forest Cover in ARPA Sites
0
100,000
200,000
300,000
400,000
500,000
600,000
2010 2020 2030 2040 2050Year
Are
a (k
m2 )
Forest- BAU
Forest- GOV
46% differential area loss
SWA Global 200
11
22
3344
SWA (Global 200)
1. SWA Moist Forest2. Jurua-Purus Moist Forest3. Madeira-Purus Moist Forest4. Madeira-Tapajos Moist Forest
PeruPeru
BoliviaBolivia
WWF’s Priority Conservation Areas
% Ecoregion Deforested
BAU 2050 GOV 2050
Forest Loss Within Ecoregions
% Deforested
Deforestation Within Ecoregions
75%
75%
83%
100 km
86% of Remaining Ombrofila Estacional Forests in BAU 2050 in Protected Areas/Indigenous Reserves
XINGU
BAU 2050 – 15% Forest184,076 km2
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
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
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;
