Upload
alfred-flowers
View
219
Download
0
Tags:
Embed Size (px)
Citation preview
GEOG 596A
Identifying Potential Dispersal Corridors for the Common Chimpanzee (Pan
troglodytes)in
Hoima District, Uganda
Marta Jarzyna
Presentation Overview
• Common Chimpanzee• Study Area• Objectives• Data and Methods
- Field Data Collection- Modeling and Analysis
• Anticipated Results• Timeline
Common chimpanzee – Pan troglodytes
• Closest living relatives to modern human being
• Found in tropical forests of Western and Central Africa (21 countries)
• IUCN Conservation Status: Endangered
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Photo: M. Jarzyna
Study Area - Uganda
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Study Area - Hoima
Main objective: Establish a potential dispersal corridor for the common chimpanzee (P. troglodytes) between Bugoma and Budongo
In detail:• Evaluate chimp density and distribution in Hoima• Conduct landscape analysis• Propose dispersal corridor route
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Objectives
• Field Data Collection (Completed for GEOG 596C)- Mammal Surveys- Nest Census
• Modeling and Analysis- Species Distribution Model- Landscape Analysis- Least-Cost Path Analysis
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Data and Methods
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Field Data Collection – Monitoring Locations
• Itohya Forest
• Kyampuro Forest
• Birungu Forest
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Field Data Collection – Monitoring LocationsItohya Kyampuro
Birungu
Photo: M. Jarzyna
Photo: M. Jarzyna
Photo: M. Jarzyna
• Distance Sampling • Line transects• Perpendicular distance to observed objects of interests
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Field Data Collection – Survey Method
Photo: M. Jarzyna
• Conducted in October 2009 through January 2010• Distance sampling• Conducted in the morning• Approximately 3 km of transects
should be sampled• Data collected:
- Mammal species- Distance of the animal/group to the observer- Height of the animal/group- Number of animals in group
• Statistical analysis using DISTANCE
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Field Data Collection – Mammal Survey
Photo: M. Jarzyna
• Conducted in October 2009 through January 2010• One chimpanzee >4 years old builds one nest a night• Distance sampling• Three main methods:
- Standing Crop Count- Marked Nest Count- Encounter Rate
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Field Data Collection – Nest Census
Photo: M. Jarzyna
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Field Data Collection – Nest Census
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Field Data Collection – DISTANCE
• Allows for design and analysis of distance sampling surveys of wildlife populations
• Calculates the density and abundance of detected objects • Probability of detecting an object decreases with increasing
distance from the observer• Statistical tools to estimate the drop-off in detection
probability
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Field Data Collection – DISTANCE
ID Analysis ConditionDensity
[individual/km2]
1 Observation = ‘All Mammals’ 170.4
2 Observation = ‘Black-and-White Colobus’
110.0
3 Observation = ‘Mangabey’ 22.9
4 Observation = ‘Red-tailed Monkey’ 95.9
5 Observation = ‘Baboon’ 22.9
B
P19% P2
13%
P319%
P46%
T12%
T24%
T31%
T44%
T517%
T61%
T72%
T81%
T921%
• Species Distribution Model – ZONATION- To establish distribution of the chimpanzee in Hoima District
• Landscape Analysis – FRAGSTATS- To establish extent and fragmentation of the focal habitat
• Least-Cost Path Analysis – ArcGIS- To establish potential dispersal corridors
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Modeling and Analysis
• Conservation planning software• When field monitoring not feasible
- time - labor
• Approximate distribution of the chimpanzee• Landscapes categorization - accordingly to the value for the chimpanzee
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Species Distribution Model - ZONATION
Zonation 2002
• Spatial pattern analysis program• Patch level• Spatial configuration - patch size distribution and density,
patch shape complexity, edge metrics, core area, isolation/proximity, connectivity, etc.
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Landscape Analysis - FRAGSTATS
Area [ha] Perimeter [m]
Perimeter-Area Ratio [-]
Core Area [ha] Proximity Index [-]
Sum 112,151.4 5,442,720 N/A 100,762.4 N/A
Average 843.2 40,923 291.2 757.6 15,990.1
Median 8.73 1920 237.5 4.5 72
Maximum 49,541.6 1,829,100 1333.3 46,904.4 137,616.5
Minimum 0.09 120 25.3 0 0
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Least Cost-Path Analysis - ArcGIS
• Dispersal suitability layer created based on the landscape metrics values
• Cost associated with crossing the patches
ArcGIS 2010
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Anticipated Results
• Data modeling and analysis (by July 15)
- DISTANCE – density of the chimpanzee population- ZONATION – species distribution- FRAGSTATS – landscape analysis - ArcGIS – least-cost path analysis
• Compiling results (by July 31)
• Discussion of the results (by August 15)
• Final edits to the report/paper (by September 15)
Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline
Next Steps/Timeline
• Dr. Doug Miller• Dr. Joe Bishop• Dr. Bettina Grieser Johns• Chimpanzee Sanctuary and Wildlife Conservation Trust• Wildlife Conservation Society Uganda• WWF Uganda
Acknowledgements
Questions?
Photo: M. Jarzyna
Photo: M. Jarzyna