The influence of movement on the occupancy–density relationship at small spatial scales

Abstract

The global decline of large carnivores demands effective and efficient methods to monitor population status, particularly using non-invasive methods. Density is among the most useful metrics of population status because it is directly comparable across space and time. Unfortunately, density is difficult to measure reliably, especially for mobile, cryptic species. Recently, efforts have turned to approximating density based on its relationship to more readily estimable indices of occurrence. However, the relationship between density and such indices is contingent on several key assumptions that field studies often violate. Recent research has shown that these relationships are unreliable where sampling units are not independent, as is often the case when estimating density or occurrence of large carnivores. Here, we use the largest data set thus far collected for leopards (Panthera pardus)-88 camera-trap surveys undertaken in 24 protected areas between 2013 and 2018-to explore how density and other population characteristics relate to parameter estimates in occupancy and Royle-Nichols abundance models. We show how home-range size confounds underlying relationships, with larger home ranges inflating the proportion of area used (PAU) and resulting in double counting in abundance models. Relativizing estimates of occupancy and abundance by home-range size improved their relationship with density, but the relationship remained weak and largely uninformative for management. Our findings illustrate the pitfalls of using the PAU or abundance as implicit proxies for density and highlight the challenges of assessing population status for wide-ranging, cryptic species across fragmented landscapes.

Unsustainable anthropogenic mortality disrupts natal dispersal and promotes inbreeding in leopards

“…Similar findings of reduced dispersal and outbreeding benefits linked to sustained harvest have been documented in pumas (Logan & Sweanor, ; Sweanor, Logan, & Hornocker, ), bobcats ( Lynx rufus ; Johnson, Walker, & Hudson, ), and black bears ( Ursus americanus ; Moore, Draheim, Etter, Winterstein, & Scribner, ). While the PMC leopard population is currently recovering from high levels of anthropogenically‐linked mortality (Rogan et al, ), demographic‐based metrics alone do not reveal the loss of genetic diversity and the consequences this may have for the future health and viability of the population (Kendall et al, ). Our results thus further highlight the importance of population connectivity to ensure gene flow and genetic diversity through immigration (Fattebert, Robinson, et al, ; Frankham, ; Hauenstein et al, ).…”

“…Historically, the SSGR and PMC populations were possibly linked via dispersal (Fattebert, Hunter, Balme, Dickerson, & Slotow, ). The two study sites also have similar habitats (open to semi‐wooded savannah), climates (mean monthly temperatures ranging from 19 to 33°C and average annual rainfall of ~600 mm), levels of prey abundance, and similar leopard densities (SSGR: 11.81 ± 2.56 leopards 100/km 2 , Balme et al, ; PMC: 9.51 ± 1.22 leopards 100/km 2 following recovery, Rogan et al, ), forming contiguous leopard habitat with no physical barriers to dispersal (Figure ). Accordingly, the observed differences in spatial behavior and genetic structure are assumed to be the result of human interference rather than due to other environmental or ecological factors, such as competitor presence or density which does not differ between these reserves (Balme, Pitman, et al, ; Balme et al, ; Fattebert et al, ; Rogan et al, ).…”

Spatial partial identity model reveals low densities of leopard and spotted hyaena in a miombo woodland

“…Obtaining robust density estimates for carnivores, which are cryptic, wide‐ranging and often solitary, is challenging (Balme et al ., 2009a; Sollmann et al ., 2011). Various techniques have been employed to estimate carnivore abundance and density, each with their own limitations (Balme et al ., 2014; Midlane et al ., 2015; Rogan et al ., 2019). In recent years, density estimates derived from camera trapping, for example using capture–recapture modelling, have become increasingly important in wildlife ecology and species management (Royle et al ., 2014; Rover and Zimmermann, 2016).…”

Estimating the density of small population of leopardPanthera pardususing multi-session photographic□sampling data

“…Alternatively, the different density point estimates could be "sampling variation", i.e. variation in a statistic from sample to sample, which is commonly seen in multi-session SECR studies of leopards (Rogan et al, 2019;Rosenblatt et al, 2016). There are two possible reasons supporting that the density has not changed between the two sessions.…”

“…This results in smaller σ and larger g 0 in warm season. In addition to season, leopard populations may exhibit marked inter-annual variation in σ (Rogan et al, 2019;Rosenblatt et al, 2016), possibly due to their dynamic spatial patterns and home range sizes.…”