Using multiple scales of movement to highlight risk–reward strategies of coyotes (Canis latrans) in mixed‐use landscapes DOI Creative Commons
Amy Van Scoyoc, Kendall L. Calhoun, Justin S. Brashares

и другие.

Ecosphere, Год журнала: 2024, Номер 15(8)

Опубликована: Авг. 1, 2024

Abstract Many wildlife species vary habitat selection across space, time, and behavior to maximize rewards minimize risk. Multi‐scale research approaches that identify variation in can highlight not only preferences risk tolerance but also movement strategies afford coexistence or cause conflict with humans. Here, we examined how anthropogenic natural features influenced coyote ( Canis latrans ) a mixed‐use, agricultural landscape Mendocino County, California, USA. We used resource functions hidden Markov models test whether for varied by time of day behavioral state (resting, foraging, traveling). found coyotes avoided development, but, contrary our expectations, selected roads, agriculture, areas human encounter rifle use regardless diel period state. While traveling, increased roads ruggedness, indicating unpaved may enhance connectivity mixed‐use landscapes. Finally, mountain lion when resting at night, signifying from predators was factor coarse scales. Coyote places times associated activity, without scales, signals potential if are perceived people as nuisance.

Язык: Английский

Using multiple scales of movement to highlight risk–reward strategies of coyotes (Canis latrans) in mixed‐use landscapes DOI Creative Commons
Amy Van Scoyoc, Kendall L. Calhoun, Justin S. Brashares

и другие.

Ecosphere, Год журнала: 2024, Номер 15(8)

Опубликована: Авг. 1, 2024

Abstract Many wildlife species vary habitat selection across space, time, and behavior to maximize rewards minimize risk. Multi‐scale research approaches that identify variation in can highlight not only preferences risk tolerance but also movement strategies afford coexistence or cause conflict with humans. Here, we examined how anthropogenic natural features influenced coyote ( Canis latrans ) a mixed‐use, agricultural landscape Mendocino County, California, USA. We used resource functions hidden Markov models test whether for varied by time of day behavioral state (resting, foraging, traveling). found coyotes avoided development, but, contrary our expectations, selected roads, agriculture, areas human encounter rifle use regardless diel period state. While traveling, increased roads ruggedness, indicating unpaved may enhance connectivity mixed‐use landscapes. Finally, mountain lion when resting at night, signifying from predators was factor coarse scales. Coyote places times associated activity, without scales, signals potential if are perceived people as nuisance.

Язык: Английский

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