Predicting potential distributions of large carnivores in Kenya: An occupancy study to guide conservation
Data files
Jul 08, 2022 version files 544.48 KB
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Cheetah_detection_history_mdmm.csv
26.73 KB
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Cheetah_observer_covariate_mdmm.csv
26.73 KB
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Cheetah_site_covariates.csv
9.46 KB
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Covariates_all_grids.csv
45.47 KB
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Kenya_boundary_UTM.cpg
5 B
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Kenya_boundary_UTM.dbf
99 B
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Kenya_boundary_UTM.prj
408 B
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Kenya_boundary_UTM.sbn
132 B
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Kenya_boundary_UTM.sbx
116 B
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Kenya_boundary_UTM.shp
2.68 KB
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Kenya_boundary_UTM.shx
108 B
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Leopard_detection_history_mdmm.csv
21.84 KB
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Leopard_observer_covariate_mdmm.csv
21.84 KB
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Leopard_site_covariates.csv
9.09 KB
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Lion_detection_history_mdmm.csv
28.49 KB
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Lion_observer_covariate_mdmm.csv
28.49 KB
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Lion_site_covariates.csv
12.41 KB
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README.txt
8.68 KB
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Spotted_hyaena_detection_history_mdmm.csv
32.02 KB
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Spotted_hyaena_observer_covariate_mdmm.csv
32.02 KB
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Spotted_hyaena_site_covariates.csv
9.66 KB
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Striped_hyaena_detection_history_mdmm.csv
21.65 KB
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Striped_hyaena_observer_covariate_mdmm.csv
21.65 KB
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Striped_hyaena_site_covariates.csv
9.30 KB
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Survey_grid_clean.cpg
5 B
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Survey_grid_clean.dbf
6.10 KB
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Survey_grid_clean.prj
408 B
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Survey_grid_clean.sbn
6.71 KB
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Survey_grid_clean.sbx
900 B
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Survey_grid_clean.shp
107.10 KB
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Wild_dog_detection_history_mdmm.csv
22.46 KB
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Wild_dog_observer_covariate_mdmm.csv
22.46 KB
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Wild_dog_site_covariates.csv
9.27 KB
Abstract
Aim: Species distribution maps are frequently the foundation upon which species-specific conservation strategies are developed, however, mapping species distribution is challenging, especially across large spatial extents. Our aim was to use a novel empirical approach to predict the national distribution for all six large carnivore species found in Kenya to guide conservation and management decisions by identifying knowledge and conservation gaps.
Location: Kenya
Methods: Data on carnivore presence and absence were collected through questionnaires and sightings-based surveys. These data were combined and analysed using single-season false-positive occupancy models, which account for imperfect detections and false positives. To inform conservation strategies, we used the occupancy outputs to make predictions for unsampled areas and create occupancy-based distribution maps, where ψ>0.50, to (1) quantify differences with IUCN Red List range maps, (2) quantify overlap with wildlife areas and (3) identify areas of high carnivore richness.
Results: Large carnivore occupancy was associated with land conversion, habitat, and prey availability. Our results suggest that all six species are widely distributed across Kenya and reveal substantial differences in distribution maps compiled by the IUCN Red List. More specifically, our occupancy-based distribution maps predict a much larger distribution for African wild dog (5.09X), lion (4.77X), and leopard (1.46X), similar distribution for cheetah, and smaller distribution for spotted hyaena (0.84X) and striped hyaena (0.65X). For all large carnivores, the vast majority (~80%) of their predicted distribution falls outside wildlife areas and northern Kenya is predicted to have the highest large carnivore richness.
Main conclusions: Our results are encouraging as large carnivores may be widely distributed across Kenya, in some cases potentially more so than previously acknowledged. However, much of this range lies outside wildlife areas and represents areas of concern both for conservation and human livelihoods illustrating the challenges of conserving large carnivores across their range.
Usage notes
Usage notes can be found in the README.txt file