Jaguars as Landscape Detectives: Ecology and Conservation...
Transcript of Jaguars as Landscape Detectives: Ecology and Conservation...
Instituto de Pesquisas EcológicasInstituto de Pesquisas EcológicasInstituto de Pesquisas EcológicasInstituto de Pesquisas Ecológicas
Jaguars as Landscape Detectives: Ecology and Conservation in the Upper Paraná River, Brazil
Laury Cullen, Ph. D.
Fernando Lima, M. Sc.
Dênis Sana
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São Paulo
Pontal do Paranapanema
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Atlantic Forest
1500
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Atlantic Forest
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Atlantic Forest
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Atlantic Forest
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Atlantic Forest
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Atlantic Forest (11% left)
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The Pontal region today
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Morro do Diabo (Devil’s Hill) State Park (37000 ha – 370 Km2)
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The upper Paraná-Paranapanema Region
200 Km
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Black lion tamarin
Tapir
The landless people
Rare and common species
Jaguar
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Jaguars as Landscape Detectives
A landscape detective is defined as a species that helps determine how to manage landscapes and to design and manage protected area networks.
Life history and behavioural features of jaguar make them potentially suitable as landscape species.
The main aim of this study is to use the jaguar as a landscape detective to develop a network of core protected areas for the Upper Paraná Region, which lies in the highly threatened Atlantic Forest of Brazil.
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Main hypothesis
By using jaguars as a landscape detectives we can identify and assess three important features that characterize large carnivores and large scale conservation planning:
(1) Prey diversity and density;(2) Large core areas, important habitat
patches for biodiversity conservation;(3) Landscape connectivity.
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Objectives / questions
Questions are linked to the three broad scientific arguments that constitute the landscape detective approach:
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1. What is the absolute density of jaguars in high priority protected areas?
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2. How do jaguars select habitats? What are their home ranges and movement patterns?
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3. How is the spatial structure of the jaguar metapopulation in the region; their location, sizes, initial abundances and carrying capacities?
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Methods and resultsQuestion 1. Estimating jaguars density in the Morro do Diabo
State Park
Camera-Trapping
Capture and recapture analysis (Otis et al. 1978)
Program CAPTURE (Rexstand
and Burnham 1991)
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Sample design
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Grid sampling sizeA = L x L logo L2
= AL = √3.5 = 1.870m
Sampling Design
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Sampling area–
A = PIxR2
logo R2
= A/PI–
R = 3.5/3.1415 = 1.055m
Sampling Design
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Sampling area–
1.000m between stations–
+/-
10% (Max: 1.050m; Min: 950m)
Sampling Design
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Equipment
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Protocols adapted from Karanth & Nichols (2002);•
Camera Base (©
2007 Mathias Tobler);•
GIS
Protocols
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Density and MMDM estimates of jaguars in the Morro do Diabo State Park using two different methods.
Method MMDM (km)
Males Females
Density
(jaguars/100 km2) (CI)
Camera Trapping 23.18 6.67 2.47 ± 0.33
Radio Tracking 25.56 15.65 2.20 (N/A)
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Methods and results
Question 2. Home range and movement patterns of jaguars in the Upper Paraná region
Home range and movements
Jaguar captures (Box traps and trained dogs)
VHF radio tracking
GPS Radio tracking
Satellite images
Habitat map
Arcview
3.3 with animal movement analysis extension
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www.televilt.se
GPS Tracking
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Location StatsMinimum X 367864,00
Minimum Y 7492064,00
Maximum X 380929,00
Maximum Y 7497519,00
Sample Size 761,00
Mean of X 370415,34
Mean of Y 7495642,86
The minimum distance 0,00
The maximum distance 4981,97
The total distance 101619,20
The mean distance 1116,69
Mean Bearing 83,95
Minimum Date 20030211
Maximum Date 20030703
Duration of Study 142,00
Minimum Speed(units/day) 0,00
Maximum Speed(units/day) 4981,97
Mean Daily Speed 715,63
MCP Area 143,79 Km2
95% Ellipse Area 143 96 Km2
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Home range areas (km2) for 3 adult male and 7 adult female jaguars in Morro do Diabo State Park and Ivinhema State Park (1998-2006), using a fixed-kernel estimator.
Animal ID
Years tracked
Annual home range Dry-season home range Wet-season home range
No. loc.
50% 85% 95% No. loc.
50% 85% 95% No. loc.
50% 85% 95%
Morro do Diabo State Park M1 1 162 14 50 89 88 6 44 85 74 15 52 86M2 1 156 55 275 471 138 42 272 478 18 30 127 255F1 1 92 2 9 18 58 1 5 12 34 7 20 37F2 2 17 35 98 129 - - - - 17 35 98 129F3 5 35 47 131 192 24 40 105 143 11 38 203 305F4 2 214 12 41 65 131 15 49 77 83 5 21 34F5 1 18 18 80 121 18 18 80 121 - - - -Male mean
159 34 162 280 113 24 158 281 46 15 52 86
Female mean
75 20 60 92 58 8 27 44 36 6 20 36
Ivinhema State Park
M3 2 799 20 147 299 399 31 157 295 400 21 139 290F6 4 326 7 87 135 148 31 89 152 179 6 68 119F7 1 183 26 173 289 154 24 125 241 30 18 45 63Male mean
404 20 147 299 299 31 157 295 300 21 139 290
Female mean
254 16 130 212 151 27 107 196 104 12 56 91
* For calculation of averages I included only those jaguars with ? 30 locations.
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Table 5.3. Home range size for jaguars obtained using the 100% Minimum Convex Polygon in different studies in the Neotropics.
Home Range Size (km2 ) Habitat Source Country Male (n) Female (n) 33.4 (4) 10.3 (3) Forest Rabinowitz and Nottingham (1986) Belize 36.9 (2) 45.5 (2) Forest Ceballos et al. (2002) México 88.7 (4) 70 (1) Forest Crawshaw (1995) Brazil 90 (2) 32.3 (3) Pantanal Schaller and Crawshaw (1980) Brazil 152.4 (1) 139.6 (4) Pantanal Crawshaw and Quigley (1991) Brazil 130 (1) 49 (2) Llanos Scognamillo et al. (2002) Venezuela 56 (7) 39 (2) Forest Crawshaw et al. (2004) Brazil/Argentina 265 (2) 228 (1) Cerrado Silveira (2004) Brazil 162 (2) 60 (5) Forest This Study * Brazil 147 (1) 130 (2) Marsh This Study * Brazil * Home range estimates based on 85% Fixed Kernel
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Figure 5.12. Movements of M1 adult male in the Morro do Diabo State Park,showing the use of a nearby fragment in the north and across the ParanapanemaRiver to the south.
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Figure 5.13. Adult male M3 moved outside the Ivinhema State Park to a 2000 haisolated forest fragment 30 Km to west, using some gallery forests as travelroutes. The dates associated with each location show that this movement required the adult male to traverse open pastures.
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Methods and resultsQuestion 3. Habitat selection of jaguars in the Upper Parana
region
Habitat Selection
Jaguar locations
Habitat Map
Habitat Use (U)
Habitat Availability (A)
Habitat selectivity was then defined by comparing availability (A) and utilization (U), using Ivlev’s (1961) index of selectivity = (U –
A)/(U + A).
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Table 7.1.Habitat availability, use and selection by jaguars in the Upper Paraná.
Habitat type
Symbol
(A) Availability Proportion in the study site
(%)
(U) Use: Proportion of
jaguar locations (%)
Ivlev’s Index of
selectivity
Water water 6.997 4.104 -0.26057 Primary forest primfor 5.239 13.841 0.45087
Secondary forest secfor 2.605 5.153 0.32848 Alluvial forest aluv 0.970 1.025 0.02754
Dense marshland densemarsh 4.977 10.045 0.33734 Open marshland openmarsh 11.013 25.695 0.39995
Agriculture agric 17.208 17.921 0.02030 Pasture pasture 50.991 22.216 -0.39307
Based on these results, I defined (HS) as:
0.00203*[agric]+0.00275*[aluv]+0.03373*[densemarsh]+0.04000*[openmarsh]-
0.03931*[pasture]+0.04509*[primfor]+0.03285*[secfor]-0.02606*[water]
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Methods and resultsQuestion 4. Metapopulation structure of jaguars in the Upper
Rio Paraná region
Landscape Data
Habitat selection information from studied jaguars
Habitat Suitability Map (HSM)
Patch Recognition
Patch Structure
Spatial Metapopulation Model
Population Viability (PVA) and Risk Analysis
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Methods and resultsQuestion 3. Metapopulation structure of jaguars in the Pontal
do Paranapanema Region and the upper Rio Paraná
ecosystem
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Methods and resultsMetapopulation structure of jaguars in the Pontal do
Paranapanema Region and the upper Rio Paraná
ecosystem
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Habitat suitability function determines the suitability of a location given various input maps describing environmental variables.
0.022343*[agric]+0.030943*[aluv]+0.038971*[densemarsh]+0.034810*[openmarsh]-0.074584*[pasture]+0.066265*[primfor]+0.045048*[secfor]-
0.0097*[water]
It attempts to identify habitat patchiness from the jaguars point of view and how the species perceives the patchiness of the landscape
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Patch structure of jaguar
populations in the upper Paraná-
Paranapanema
region
Habitat Suitability Map
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Patch structure of jaguar
populations in the upper Paraná-
Paranapanema
region
HST= Habitat suitability threshold for patches. The value of HS below which it is assumed that the species cannot reproduce (2.0 was used here)
ND= Neighborhood distance is used to find patches. The average foraging distance of the species (3200 mts used)
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Using the Model to Increase Protected
Areas Size
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Patch #
Location K* Init.* abund.
Total HS
Avg. HS
Area (km2)
Area as % of
patches1 Morro do Diabo 9 14 20678 5,30 351 19,61 2 Ivinhema 14 21 32256 2,97 976 54,47 3 Ilha Grande 7 10 15273 2,96 465 25,92
Total 30 45 68207 3,74 1792 100,00
K = only adults and sub adults, Init. Abundance = all individuals
HS = Habitat Suitability
Table 12. Carrying capacities, initial abundances and areas of patches identified by the model.
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Methods and results
Question 5. Population Viability
Initial abundances data
Carrying capacity data
Vital rates data (fecundity and survival data)
Density dependency (ceiling model)
Monte Carlo simulations
RAMAS Metapopulation (Akçakaya, R. 2002)
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This can be explained by the type of source and sink dynamics The smaller populations are more prone to extinction as a result of demographic stochastic. Increasing dispersal means jaguars going from more stable larger populations to smaller and more extinction-prone populations.
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Parameter/Scenario Effect Terminal a extinction
risk
Metapop b occup.
MD O
I V O
I G O
Base model - 68% 12 2 8 2 Base model + 10% dispersal rate - 100% 3 1 1 1 Base model + 10 disp.rate + 15% vital rates + 1% 42 12 20 10Base model + 10% nat. dispersal + Iguaçu Park + 0% 65 3 3 6 Base model + 10% nat.disp + transloc + Iguaçu + 0% 74 10 11 6
a. Shows the probability that the metapopulation abundance will end up below a threshold number of 10 individuals 50 years from now;
b. Metapopulation occupancy: shows the total number of individuals the metapopulation is likely to have 50 years from now;
MDO= Morro do Diabo Area occupancy in 50 years;IVO= Ivinhema Area occupancy in 50 years;IGO= Ilha Grande Area occupancy in 50 years. Transloc= translocations or managed dispesal at 10 % rate among all populations.
Table 13. Sensitivity of results to different parameters and scenarios used when modelling the viability of the upper Paraná-
Paranapanema jaguar metapopulation.
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Metapopulation
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Summary of preliminary results
Camera trapping estimated jaguar population for the Morro Park to be around 2.22
individuals/100 Km2. This estimate is lower when compared to other southern and
Pantanal jaguar populations in Brazil, but similar from estimates obtained from other
Neotropical areas.
These differences could be attributed to the lower productivity of semideciduous Atlantic Forests on the interior, bordering the cerrado vegetation, thus affecting the distribution and
density of prey species.
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Summary of preliminary results
Patch analysis identified 3 major habitat areas for jaguars and biodiversity conservation. Only
2,6 % of the total landscape analysed is covered by the three suitable patches found.
Total jaguar population estimated for the eco- region is around 45 individuals.
Gaps found between patches might affect landscape connectivity and dispersal between patches. However the habitat map identified important stepping-stone areas that could be
managed and restored to approximate and link jaguar populations in the long term
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Summary of preliminary results
Sensitivity analysis showed significant results when dispersal is combined with a 15% increase in population vital rates (increasing survivorships and decreasing mortality rates) and/or considering the
Iguaçu Falls population in the plan.
The metapopulation and all identified populations are likely to persist and
stabilize when this scenario is considered.
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Next Steps (2009-2011)
1. Dispersal Studies
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Next Steps (2009-2011)
2. Revisiting the Iguacú Falls Jaguar Population
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Next Steps (2009-2011)
3. Management Plan
Our main goal is to update the current jaguar conservation model by developing a management plan for maintaining viable populations of the jaguar in the Upper
Paraná River Corridor, Brazil. Step 1: Updating land- cover/land-use maps
and demographic data
The aim of this task is to use the most recent information that is
available for supporting the model development. The maps for land-cover and land-use form the
basis of the habitat model, and the demographic data
form the basis of the metapopulation model.
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Next Steps (2009-2011)
3. Management Plan
Step 2: Updating and validating the habitat model
. We will use the same type of data (land-use maps and
jaguar GPS locations) that were used in the previous
model (and updated in Step 1) to develop habitat models using two other methods:
logistic regression and maximum entropy methods.
We will then validate the models by estimating the
habitat function for part of the landscape and using it to predict habitat suitability
values for the remainder of the landscape and comparing the
predicted values to jaguar GPS locations.
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Next Steps (2009-2011)
3. Management Plan
Step 3: Producing land ownership maps and database
In order to use results of such a model in making
actual management decisions, the results must
be spatially explicit, i.e., they must allow comparing multiple scenarios that may
involve different combinations of available
and suitable land, in relation to currently existing
protected areas. The result will be a detailed map of
land ownership, with each parcel (e.g., each farm) identified in terms of its availability for a set of conservation options.
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Next Steps (2009-2011)
3. Management Plan
Step 4: The Workshop
.
To review the model and its assumptions, and determine plausible ranges for uncertain parameters;
To identify potential management options (e.g., protection of subsets of available land units, translocation, protection of prey base, reducing road mortality, increasing
connectivity, etc.);
To characterize each management action in terms of its effects on model parameters;
To make preliminary runs of the model with selected management options to support more precise identification of management options;
To get feedback from the agencies in terms of the best format for presenting the results of the model.
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Next Steps (2009-2011)
3. Management Plan
Step 5: Making management recommendations
We will run a comprehensive sensitivity analysis, with two objectives:
to determine the sensitivity of management recommendations (e.g., the optimal set of management actions)
to data and model uncertainties, and to identify future research activities that can reduce any uncertainties that are reflected in
management recommendations.
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The Wildlife Trust The Liz Claiborne Art Orternberg
Foundation
The Whitley Awards The Rolex Awards
BBC Wildlife Fund DICE and Dept. Anthropology UKC
The Conservation Food and Health Foundation The Lincoln Park Zoo
The Woodland Park Zoo The Boticario
Foundation
CAPES-Brazil Pró
Carnívoros
CESP