Sex‐specific population dynamics of ocelots in Belize using open population spatial capture–recapture

Abstract

We used open population, spatial capture–recapture (SCR) models to estimate sex‐specific density, survival, per capita recruitment, and population growth rate of ocelots (Leopardus pardalis) at five sites in Belize with up to 12 yr of data per site. Open population SCR models enabled us to separate survival and recruitment from migration using an ecologically realistic, spatially explicit movement model. Yearly survival probability across 4 broadleaf forest sites was estimated at 0.73–0.84 for males and 0.81–0.87 for females, with no clear indication of sex differences. Yearly per capita recruitment was estimated across four broadleaf forest sites at 0.06–0.08 recruits/N for males and 0.09–0.12 recruits/N for females, again with no clear indication of sex differences. At a pine forest site with a population comprised largely of males, survival and recruitment estimates were similar to the broadleaf sites. Population densities in the broadleaf forest sites ranged from 6.5 to 14.7 ocelots/100 km2, and 0.9–2.5 ocelots/100 km2 in the pine forest site, with strong evidence of a female‐biased sex ratio in the broadleaf sites and a male‐biased sex ratio in the pine forest site. We also found strong evidence that female within‐year space use at the broadleaf sites was smaller than that of males, and that within‐year space use at the pine forest site was larger than that at broadleaf sites. Between‐year home‐range relocation at broadleaf sites was of a similar spatial scale as within‐year space use, consistent with philopatry. We found evidence of a small population decline (posterior probability > 0.9) at two of four broadleaf sites; however, given the level of uncertainty about decline magnitudes, we suggest continued monitoring of these sites to increase site‐years and gain further precision on population growth rate estimates. Estimating demographic parameters at large spatial and temporal scales is important for establishing reliable baseline estimates for future comparison and for understanding changes in population dynamics. Long‐term data sets like those we collected are of particular importance for long‐lived species living at low densities and large spatial scales, where not many individuals are exposed to capture in any one year.

A decade of systematic camera trapping in two strictly protected areas reveals the demography of a Eurasian lynx (Lynx lynx) population in Central Europe

“…, similar again toSatter et al (2019). Our results of generation time (2.64 years) and the average litter size of 1.97 (range 1-3) were close to those of other studies in Europe.…”

“…However, we did not nd any strong difference in survival rates between sexes. A similar open population SCR study, conducted on a low-density ocelot population in Belize, also showed no signi cant differences in sex-speci c survival, despite a survival rate of 0.86 for females and 0.78 for males (Satter et al 2019). The authors suggested the statistical power was not enough to detect signi cant differences between sexes in these parameters, although they were able to determine sex for a large number of adult ocelots (n = 322).…”

Long‐term monitoring of ocelot densities in Belize

“…Thus, this camera spacing appears appropriate for ocelots. However, other studies attempting similar estimates for cats with differing body sizes, should pay careful attention to camera spacing relative to movement parameters of the target species (Satter et al , Satter ). Our cameras were spaced closer together than twice the estimated value of σ and produced sufficient numbers of spatial recaptures.…”

Jaguar (Panthera onca) density and tenure in a critical biological corridor

“…Differences between the sexes in home range size and ranging behavior (such as the avoidance of trail systems; e.g., Sollmann et al 2011 ) may result in sex-specific detectability by trail-based camera traps. Under these conditions, allowing g0 and σ to vary by sex in SCR models can improve the accuracy of density estimates ( Sollmann et al 2011 ; Tobler and Powell 2013 ; Satter et al 2019 ).…”