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A Conservation-Based Approach to Compensation for Livestock Depredation: The Florida Panther Case Study.

Jacobs CE, Main MB - PLoS ONE (2015)

Bottom Line: Depredation sites of tagged calves had a significantly greater probability of panther presence than depredation sites of untagged calves that were found by ranchers in open pastures.This suggests that there may be more calves killed in high risk environments than are being found and reported by ranchers and that panthers can hunt effectively in open environments.We suggest that our approach could be applied to prioritize and categorize private lands for participation in a Payment for Ecosystem Services program that compensates landowners for livestock loss and incentivizes conserving high quality habitat for large carnivores where livestock depredation is a concern.

View Article: PubMed Central - PubMed

Affiliation: Department of Wildlife Ecology and Conservation, University of Florida Institute of Food and Agricultural Sciences, Gainesville, Florida, United States of America.

ABSTRACT
Calf (Bos taurus) depredation by the federally endangered Florida panther (Puma concolor coryi) on ranches in southwest Florida is an important issue because ranches represent mixed landscapes that provide habitat critical to panther recovery. The objectives of this study were to (1) quantify calf depredation by panthers on two ranches in southwest Florida, and (2) develop a habitat suitability model to evaluate the quality of panther hunting habitat on ranchlands, assess whether the model could predict predation risk to calves, and discuss its potential to be incorporated into an incentive-based compensation program. We ear-tagged 409 calves with VHF transmitters on two ranches during 2011-2013 to document calf mortality. We developed a model to evaluate the quality of panther hunting habitat on private lands in southwest Florida using environmental variables obtained from the Florida Natural Areas Inventory (FNAI) Cooperative Landcover Database and nocturnal GPS locations of panthers provided by the Florida Fish and Wildlife Conservation Commission (FWC). We then tested whether the model could predict the location of calf depredation sites. Tagged calf loss to panthers varied between the two ranches (0.5%/yr to 5.3%/yr) and may have been influenced by the amount of panther hunting habitat on each ranch as the ranch that experienced higher depredation rates contained a significantly higher probability of panther presence. Depredation sites of tagged calves had a significantly greater probability of panther presence than depredation sites of untagged calves that were found by ranchers in open pastures. This suggests that there may be more calves killed in high risk environments than are being found and reported by ranchers and that panthers can hunt effectively in open environments. It also suggests that the model may provide a means for evaluating the quality of panther hunting habitat and the corresponding risk of depredation to livestock across the landscape. We suggest that our approach could be applied to prioritize and categorize private lands for participation in a Payment for Ecosystem Services program that compensates landowners for livestock loss and incentivizes conserving high quality habitat for large carnivores where livestock depredation is a concern.

No MeSH data available.


Probability of panther presence (y-axis) associated with changes in environmental variables (x-axis) as predicted by the panther hunting habitat model.UF = Upland Forest, WF = Wetland Forest, SBP = Shrub-Brush-Prairie, NFW = Non-Forested Wetland, UP = Unimproved pasture, IP = Improved Pasture, RC = Row Crops, CG = Citrus Groves.
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pone.0139203.g002: Probability of panther presence (y-axis) associated with changes in environmental variables (x-axis) as predicted by the panther hunting habitat model.UF = Upland Forest, WF = Wetland Forest, SBP = Shrub-Brush-Prairie, NFW = Non-Forested Wetland, UP = Unimproved pasture, IP = Improved Pasture, RC = Row Crops, CG = Citrus Groves.

Mentions: The panther hunting habitat model produced an AUC value of 0.778, which is considered moderate performance [37]. The model was highly significant in that it predicted documented panther locations statistically better (p < 0.001) than 1,000 random models, which means that its accuracy was significantly higher than what would be expected by chance alone. Environmental variables contributed to the model in different ways (Table 4) and positive influences included the size of forest patches and percentage of forest cover (Fig 2). Forest edge density also had a positive influence until edge densities approached 3,000 m/km2 (13 km/4.5 km2), after which the probability of panther presence began to decline (Fig 2). Cover types that had the highest probability of panther presence included upland forest, wetland forest, and unimproved pasture (Fig 2).


A Conservation-Based Approach to Compensation for Livestock Depredation: The Florida Panther Case Study.

Jacobs CE, Main MB - PLoS ONE (2015)

Probability of panther presence (y-axis) associated with changes in environmental variables (x-axis) as predicted by the panther hunting habitat model.UF = Upland Forest, WF = Wetland Forest, SBP = Shrub-Brush-Prairie, NFW = Non-Forested Wetland, UP = Unimproved pasture, IP = Improved Pasture, RC = Row Crops, CG = Citrus Groves.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4589380&req=5

pone.0139203.g002: Probability of panther presence (y-axis) associated with changes in environmental variables (x-axis) as predicted by the panther hunting habitat model.UF = Upland Forest, WF = Wetland Forest, SBP = Shrub-Brush-Prairie, NFW = Non-Forested Wetland, UP = Unimproved pasture, IP = Improved Pasture, RC = Row Crops, CG = Citrus Groves.
Mentions: The panther hunting habitat model produced an AUC value of 0.778, which is considered moderate performance [37]. The model was highly significant in that it predicted documented panther locations statistically better (p < 0.001) than 1,000 random models, which means that its accuracy was significantly higher than what would be expected by chance alone. Environmental variables contributed to the model in different ways (Table 4) and positive influences included the size of forest patches and percentage of forest cover (Fig 2). Forest edge density also had a positive influence until edge densities approached 3,000 m/km2 (13 km/4.5 km2), after which the probability of panther presence began to decline (Fig 2). Cover types that had the highest probability of panther presence included upland forest, wetland forest, and unimproved pasture (Fig 2).

Bottom Line: Depredation sites of tagged calves had a significantly greater probability of panther presence than depredation sites of untagged calves that were found by ranchers in open pastures.This suggests that there may be more calves killed in high risk environments than are being found and reported by ranchers and that panthers can hunt effectively in open environments.We suggest that our approach could be applied to prioritize and categorize private lands for participation in a Payment for Ecosystem Services program that compensates landowners for livestock loss and incentivizes conserving high quality habitat for large carnivores where livestock depredation is a concern.

View Article: PubMed Central - PubMed

Affiliation: Department of Wildlife Ecology and Conservation, University of Florida Institute of Food and Agricultural Sciences, Gainesville, Florida, United States of America.

ABSTRACT
Calf (Bos taurus) depredation by the federally endangered Florida panther (Puma concolor coryi) on ranches in southwest Florida is an important issue because ranches represent mixed landscapes that provide habitat critical to panther recovery. The objectives of this study were to (1) quantify calf depredation by panthers on two ranches in southwest Florida, and (2) develop a habitat suitability model to evaluate the quality of panther hunting habitat on ranchlands, assess whether the model could predict predation risk to calves, and discuss its potential to be incorporated into an incentive-based compensation program. We ear-tagged 409 calves with VHF transmitters on two ranches during 2011-2013 to document calf mortality. We developed a model to evaluate the quality of panther hunting habitat on private lands in southwest Florida using environmental variables obtained from the Florida Natural Areas Inventory (FNAI) Cooperative Landcover Database and nocturnal GPS locations of panthers provided by the Florida Fish and Wildlife Conservation Commission (FWC). We then tested whether the model could predict the location of calf depredation sites. Tagged calf loss to panthers varied between the two ranches (0.5%/yr to 5.3%/yr) and may have been influenced by the amount of panther hunting habitat on each ranch as the ranch that experienced higher depredation rates contained a significantly higher probability of panther presence. Depredation sites of tagged calves had a significantly greater probability of panther presence than depredation sites of untagged calves that were found by ranchers in open pastures. This suggests that there may be more calves killed in high risk environments than are being found and reported by ranchers and that panthers can hunt effectively in open environments. It also suggests that the model may provide a means for evaluating the quality of panther hunting habitat and the corresponding risk of depredation to livestock across the landscape. We suggest that our approach could be applied to prioritize and categorize private lands for participation in a Payment for Ecosystem Services program that compensates landowners for livestock loss and incentivizes conserving high quality habitat for large carnivores where livestock depredation is a concern.

No MeSH data available.