Suchergebnisse

Context
The primary selective forces responsible for shaping life-history traits come from the physical and biological environment in which a species resides. Consequently, the limits of a species range may provide a useful measure of adaptive potential to environmental change. The proximity of foraging grounds to terrestrial nursing habitat constrains central-place foragers such as otariid seals in selecting breeding locations. The Australian sea lion (Neophoca cinerea) is an endangered otariid endemic to Australia, whose northern-range extent occurs at a temperate–tropical transition zone on the western coast of Western Australia (WA).

Aims
Currently, there is a complete absence of data on the foraging ecology of Australian sea lions in WA. We sought to address this critical knowledge gap and provide data on the foraging ecology of adult female Australian sea lions at three isolated breeding colonies in western WA.

Methods
We used stable-isotope ratios of carbon (δ13C) and nitrogen (δ15N) in the whiskers of pups as proxies to characterise feeding behaviour of 10–28% of all adult female Australian sea lions at each colony. We then compared these geographic data to (1) conspecifics at similar latitude in South Australia (SA) and (2) isotopic data collated from other studies on seabirds that inhabit the region, to place foraging behaviour of adult female Australian sea lions into context.

Key results
At the southernmost colonies in WA, individual animals were members of one of two distinct isotopic clusters that could be described by differences in δ15N and δ13C values. Individuals at the northernmost colony displayed δ15N values similar to those of seabirds in the same region. Across the study, isotope ratios of adult female Australian sea lions in western WA were between 3‰ and 5‰ lower than those observed at a colony at similar latitude in SA.

Conclusions
Gross differences in the physical oceanography between WA and SA may in part explain the differences in isotope ratios of individuals between the regions, with lower δ15N and δ13C values in WA probably reflecting the relatively depauperate conditions of the Leeuwin Current.

Implications
Potential regional differences in trophic structure should be considered when developing appropriate management plans for Australian sea lions and regional variation in the diet of Australian sea lion warrants further investigation.

Abstract
ContextData obtained from camera traps are increasingly used to inform various population-level models. Although acknowledged, imperfect detection probabilities within camera-trap detection zones are rarely taken into account when modelling animal densities.

AimsWe aimed to identify parameters influencing camera-trap detection probabilities, and quantify their relative impacts, as well as explore the downstream implications of imperfect detection probabilities on population-density modelling.

MethodsWe modelled the relationships between the detection probabilities of a standard camera-trap model (n=35) on a remotely operated animal-shaped soft toy and a series of parameters likely to influence it. These included the distance of animals from camera traps, animal speed, camera-trap deployment height, ambient temperature (as a proxy for background surface temperatures) and animal surface temperature. We then used this detection-probability model to quantify the likely influence of imperfect detection rates on subsequent population-level models, being, in this case, estimates from random encounter density models on a known density simulation.

Key resultsDetection probabilities mostly varied predictably in relation to measured parameters, and decreased with an increasing distance from the camera traps and speeds of movement, as well as heights of camera-trap deployments. Increased differences between ambient temperature and animal surface temperature were associated with increased detection probabilities. Importantly, our results showed substantial inter-camera (of the same model) variability in detection probabilities. Resulting model outputs suggested consistent and systematic underestimation of true population densities when not taking imperfect detection probabilities into account.

ConclusionsImperfect, and individually variable, detection probabilities inside the detection zones of camera traps can compromise resulting population-density estimates.

ImplicationsWe propose a simple calibration approach for individual camera traps before field deployment and encourage researchers to actively estimate individual camera-trap detection performance for inclusion in subsequent modelling approaches.