Biological significance of scat marking by otters has been a controversial subject among scientists. Using multiyear (2014–2017) data of otter spraint counts in South Korea, this study aimed to test whether the observed pattern of spraint presence/absence is driven by detection error and if/how scat counts can be a proxy for otter abundance at the landscape scale. To test the first hypothesis, spraint presence/absence was analyzed through occupancy models, which relied on environmental variables related to otter detectability and presence. Spraint count models were used to test the second hypothesis against resource-related covariates in combination with landscape, anthropogenic, and climate variables through machine learning algorithms (MLAs). The detection probability has specifically decreased in areas characterized by high rainfall and human population densities, whereas the probability has increased near food-rich sites, characterized by high marking frequencies. The temporal trends of spraint count predictions were in line with changes in the diversity of fish communities in 2014–2017 instead of fish biomass, suggesting that the availability of feeding resources is higher where fish communities are more diverse. Because diverse fish communities can attract otters, fish diversity conservation is critical for preserving this mammal's populations. This fine scale four-year monitoring has contributed to the disentanglement of the role of spraint presence/absence and spraint counts in detectability and population trends. This will assist in identifying key resource areas and planning strategies to promote otter conservation and dispersal dynamics.

Is scat marking a reliable tool for otter census and surveys at the landscape scale?

Di Febbraro M.
Co-primo
;
Loy A.
Ultimo
2022-01-01

Abstract

Biological significance of scat marking by otters has been a controversial subject among scientists. Using multiyear (2014–2017) data of otter spraint counts in South Korea, this study aimed to test whether the observed pattern of spraint presence/absence is driven by detection error and if/how scat counts can be a proxy for otter abundance at the landscape scale. To test the first hypothesis, spraint presence/absence was analyzed through occupancy models, which relied on environmental variables related to otter detectability and presence. Spraint count models were used to test the second hypothesis against resource-related covariates in combination with landscape, anthropogenic, and climate variables through machine learning algorithms (MLAs). The detection probability has specifically decreased in areas characterized by high rainfall and human population densities, whereas the probability has increased near food-rich sites, characterized by high marking frequencies. The temporal trends of spraint count predictions were in line with changes in the diversity of fish communities in 2014–2017 instead of fish biomass, suggesting that the availability of feeding resources is higher where fish communities are more diverse. Because diverse fish communities can attract otters, fish diversity conservation is critical for preserving this mammal's populations. This fine scale four-year monitoring has contributed to the disentanglement of the role of spraint presence/absence and spraint counts in detectability and population trends. This will assist in identifying key resource areas and planning strategies to promote otter conservation and dispersal dynamics.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/112827
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