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11. Predictive mapping of tree species assemblages in an African montane rainforest

Author

Babaasa, Dennis, Finn, John T., Schweik, Charles M., Fuller, Todd K., Sheil, Douglas, Babaasa, Dennis, Finn, John T., Schweik, Charles M., Fuller, Todd K., and Sheil, Douglas

Abstract

Conservation of mountain ecosystems can benefit from knowledge of habitats and their distribution patterns. This benefit is particularly true for diverse ecosystems with high conservation values such as the “Afromontane” rainforests. We mapped the vegetation of one such forest: the rugged Bwindi Impenetrable Forest, Uganda—a World Heritage Site known for its many restricted-range plants and animal taxa including several iconic species. Given variation in elevation, terrain and human impacts across Bwindi, we hypothesised that these factors influence the composition and distribution of tree species. To test this, detailed surveys were carried out using stratified random sampling. We established 289 georeferenced sample sites (each with 15 trees ≥20 cm dbh) ranging from 1,320 to 2,467 m a.s.l. and measured 4,335 trees comprising 89 species that occurred in four or more sample sites. These data were analysed against twenty-one digitally mapped biophysical variables using various analytical techniques including non-metric multidimensional scaling (NMDS) and random forests. We identified six tree species assemblages with distinct compositions. Among the biophysical variables, elevation had the strongest correlation with the ordination (r2=0.5; p<0.001). The “out-of-bag” (OOB) estimate of the error rate for the best final model was 50.7% meaning that nearly half of the variation was accounted for using a limited set of variables. We demonstrate that it is possible to predict the spatial pattern of such a forest based on sampling across a highly complex landscape. Such methods offer accurate mapping of composition that can guide conservation.

Published
2024

12. Jaguar predation on domestic horses in the dry forest of northwestern Costa Rica.

Author

Morera, Brayan, Montalvo, Víctor, Moya, Jairo, Obando, Javier, Sáenz‐Bolaños, Carolina, Fuller, Todd K., and Carrillo, Eduardo

Subjects
GLOBAL Positioning System, PROBABILITY density function, HORSES, TROPICAL dry forests, VEGETATION management, JAGUAR
Abstract

Depredation of domestic horses (Equus caballus) by jaguars (Panthera onca) is an example of human–wildlife conflict that has not received much attention. We monitored spatio‐temporal activity and distribution of horses in a 2.64‐km2 fenced area in the dry forest of northwestern Costa Rica in response to 16 jaguar killings of horses during January‐November 2017. We monitored 4 horses (2 males, 2 females) equipped with global positioning system transmitters from February‐September 2018 to identify daily and seasonal patterns of use of cover types and a water source by horses. We then compared these results to the previous locations where jaguars killed horses to identify the circumstances under which horses seemed more vulnerable to jaguar predation. Based on 1,693 locations, horses spent most time in grassland (92%) rather than forest and edge vegetation (8%) and used a core area of 0.74 km2 (kernel density estimation) to 0.86 km2 (minimum convex polygon). Of 16 horse predation events by jaguars, 9 events (56%) occurred in grasslands, 4 in forested areas (25%), and 3 in the forest edge (19%), indicating predation events occurred disproportionately from expected counts based on horse use of vegetation. The predation sites were characterized by a higher proportion of edge and a lower proportion of forest compared to a random points. We suggest that when horses explored areas near the edge of forested areas, the chances of being preyed on by jaguars increased. [ABSTRACT FROM AUTHOR]

Published
2024
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