No abstract

Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation (normalNfalse^area) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing normalNfalse^area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small normalNfalse^area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an normalNfalse^area >1,000, where 30% had an normalNfalse^area <30. In this frequently encountered scenario of small normalNfalse^area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.

Habitat fragmentation may disrupt original patterns of gene flow and lead to drift-induced differentiation among local population units. Top predators such as the jaguar may be particularly susceptible to this effect, given their low population densities, leading to small effective sizes in local fragments. On the other hand, the jaguar's high dispersal capabilities and relatively long generation time might counteract this process, slowing the effect of drift on local populations over the time frame of decades or centuries. In this study, we have addressed this issue by investigating the genetic structure of jaguars in a recently fragmented Atlantic Forest region, aiming to test whether loss of diversity and differentiation among local populations are detectable, and whether they can be attributed to the recent effect of drift. We used 13 microsatellite loci to characterize the genetic diversity present in four remnant populations, and observed marked differentiation among them, with evidence of recent allelic loss in local areas. Although some migrant and admixed individuals were identified, our results indicate that recent large-scale habitat removal and fragmentation among these areas has been sufficiently strong to promote differentiation induced by drift and loss of alleles at each site. Low estimated effective sizes supported the inference that genetic drift could have caused this effect within a short time frame. These results indicate that jaguars' ability to effectively disperse across the human-dominated landscapes that separate the fragments is currently very limited, and that each fragment contains a small, isolated population that is already suffering from the effects of genetic drift.

The jaguar is the top predator of the Atlantic Forest (AF), which is a highly threatened biodiversity hotspot that occurs in Brazil, Paraguay and Argentina. By combining data sets from 14 research groups across the region, we determine the population status of the jaguar and propose a spatial prioritization for conservation actions. About 85% of the jaguar’s habitat in the AF has been lost and only 7% remains in good condition. Jaguars persist in around 2.8% of the region, and live in very low densities in most of the areas. The population of jaguars in the AF is probably lower than 300 individuals scattered in small sub-populations. We identified seven Jaguar Conservation Units (JCUs) and seven potential JCUs, and only three of these areas may have ≥50 individuals. A connectivity analysis shows that most of the JCUs are isolated. Habitat loss and fragmentation were the major causes for jaguar decline, but human induced mortality is the main threat for the remaining population. We classified areas according to their contribution to jaguar conservation and we recommend management actions for each of them. The methodology in this study could be used for conservation planning of other carnivore species.

Accurately estimating home range and understanding movement behavior can provide important information on ecological processes. Advances in data collection and analysis have improved our ability to estimate home range and movement parameters, both of which have the potential to impact species conservation. Fitting continuous-time movement model to data and incorporating the autocorrelated kernel density estimator (AKDE), we investigated range residency of forty-four jaguars fit with GPS collars across five biomes in Brazil and Argentina. We assessed home range and movement parameters of range resident animals and compared AKDE estimates with kernel density estimates (KDE). We accounted for differential space use and movement among individuals, sex, region, and habitat quality. Thirty-three (80%) of collared jaguars were range resident. Home range estimates using AKDE were 1.02 to 4.80 times larger than KDE estimates that did not consider autocorrelation. Males exhibited larger home ranges, more directional movement paths, and a trend towards larger distances traveled per day. Jaguars with the largest home ranges occupied the Atlantic Forest, a biome with high levels of deforestation and high human population density. Our results fill a gap in the knowledge of the species’ ecology with an aim towards better conservation of this endangered/critically endangered carnivore—the top predator in the Neotropics.