Reintroducing a large herbivore: a remote sensing and modeling approach to determine the mountain bongo’s (Tragelaphus euryceros isaaci) past and present critical habitat
Lyndon
Despard
Estes, University of Virginia; Rare Species Conservatory Foundation, lde2c@virginia.edu
(Presenting)
Adam
Gachuhi
Mwangi, Moi University, adamgm2003@yahoo.com
Gregory
S.
Okin, University of Virginia; University of California Los Angeles, okin@virginia.edu
Herman
Henry
Shugart, University of Virginia, hhs@virginia.edu
The mountain bongo (Tragelaphus euryceros isaaci) is a rare, shy antelope confined to several isolated Kenyan montane forests. The bongo is the “flagship” species of these ecosystems, but has declined drastically in the last 40 years. An ambitious multi-lateral reintroduction effort aims to reverse this decline by re-establishing a viable wild population on the Mount Kenya World Heritage Site using captive bongo from North America. Success depends on learning the poorly-understood bongo’s ecological requirements. Studying the elusive bongo in difficult mountain terrain presents two challenges: 1) collecting large and spatially comprehensive field datasets is difficult; 2) critical habitat variables may operate at different scales. To overcome these difficulties, a field dataset collected from the nearby Aberdares mountains’ bongo population will be combined with ASTER, Spot, Landsat, and MODIS data to identify and map the past and present distribution of habitat variables. Spectral mixture and texture analyses will delineate forest structure. Vegetation types will be classified using an enhanced technique that incorporates prior probabilities derived from DEM-based models of vegetation distribution. The resulting maps will be used to generate statistical models that will identify: 1) ecological features important to the bongo and the scales at which they operate; 2) the current and historical distribution of the bongo’s core habitat. Data collected from a remnant herd on Mount Kenya will enable independent model validation. A collaborative population genetics study using fecal DNA is expected to provide population and range size estimates that will greatly enhance this ecological assessment.