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GEOG 596A Identifying Potential Dispersal Corridors for the Common Chimpanzee (Pan troglodytes) in Hoima District, Uganda Marta Jarzyna.

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Presentation on theme: "GEOG 596A Identifying Potential Dispersal Corridors for the Common Chimpanzee (Pan troglodytes) in Hoima District, Uganda Marta Jarzyna."— Presentation transcript:

1 GEOG 596A Identifying Potential Dispersal Corridors for the Common Chimpanzee (Pan troglodytes) in Hoima District, Uganda Marta Jarzyna

2 Presentation Overview Common Chimpanzee Study Area Objectives Data and Methods - Field Data Collection - Modeling and Analysis Anticipated Results Timeline

3 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

4 Study Area - Uganda Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline

5 Study Area - Hoima

6 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

7 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

8 Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline Field Data Collection – Monitoring Locations Itohya Forest Kyampuro Forest Birungu Forest

9 Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline Field Data Collection – Monitoring Locations ItohyaKyampuro Birungu Photo: M. Jarzyna

10 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

11 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

12 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

13 Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline Field Data Collection – Nest Census

14 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

15 Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline Field Data Collection – DISTANCE IDAnalysis Condition Density [individual/ km 2 ] 1Observation = ‘All Mammals’170.4 2Observation = ‘Black-and-White Colobus’ 110.0 3Observation = ‘Mangabey’22.9 4Observation = ‘Red-tailed Monkey’95.9 5Observation = ‘Baboon’22.9

16 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

17 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

18 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 [-] Sum112,151.45,442,720N/A100,762.4N/A Average843.240,923291.2757.615,990.1 Median8.731920237.54.572 Maximum49,541.61,829,1001333.346,904.4137,616.5 Minimum0.0912025.300

19 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

20 Common Chimpanzee Study Area Objectives Data&Methods Anticipated Results Timeline Anticipated Results

21 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

22 Dr. Doug Miller Dr. Joe Bishop Dr. Bettina Grieser Johns Chimpanzee Sanctuary and Wildlife Conservation Trust Wildlife Conservation Society Uganda WWF Uganda Acknowledgements

23 Questions? Photo: M. Jarzyna


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