The isotopic niche of consumers represents biologically relevant information on resource and habitat use. Several tools have been developed to quantify niche size and overlap. Nonetheless, methods adapted by spatial ecologists to quantify animal home ranges can be modified for use in stable isotope ecology when data are not normally distributed in bivariate space. We offer a tool that draws on existing spatial metrics, such as minimum convex polygon (MCP) and standard ellipse area (SEA), and add novel metrics using kernel utilization density (KUD) estimators to measure isotopic niche size and overlap. We present examples using empirical and simulated data to demonstrate the performance of the package kernel isotopic niches in r (rKIN) under various scenarios. Results of niche size from MCP, SEA and KUD were highly correlated but divergent among datasets. Overall, the KUD method produced the largest niche sizes and was more sensitive to the distribution of the isotopic data. Pairwise estimates of overlap were highly variable, likely because MCP and SEA inherently include or exclude unused areas in the resulting niche estimate. Four bandwidth methods (reference, normal scale, plug‐in and biased cross‐validation) produced comparable estimates of niche size and overlap at various sample sizes (10–40). Niche size and overlap were consistent across sample sizes >15. Use of rKIN will allow isotope ecologists to quantify niche shifts, expansions or contractions, as well as assess the performance of several estimation methods. The package also can be applied to other data types (e.g. principal component analysis, multi‐dimensional scaling) so long as axes and measurement units are identical and can be converted to Cartesian coordinates.

For decades, ecologists have debated the importance of biotic interactions (e.g., competition) and abiotic factors in regulating populations. Competition can influence patterns of distribution, abundance, and resource use in many systems but remains difficult to measure. We quantified competition between two sympatric small mammals, Keen's mice (Peromyscus keeni) and dusky shrews (Sorex monticolus), in four habitat types on Prince of Wales Island in Southeast Alaska. We related shrew density to that of mice using standardized regression models while accounting for habitat variables in each year from 2010-2012, during which mice populations peaked (2011) and then crashed (2012). Additionally, we measured dietary overlap and segregation using stable isotope analysis and kernel utilization densities and estimated the change in whole community energy consumption among years. We observed an increase in densities of dusky shrews after mice populations crashed in 2012 as expected under competitive release. In addition, competition coefficients revealed that the influence of Keen's mice was dependent on their density. Also in 2012, shrew diets shifted, indicating that they were able to exploit resources previously used by mice. Nonetheless, increases in shrew numbers only partially compensated for the community energy consumption because, as insectivores, they are unlikely to utilize all food types consumed by their competitors. In pre-commercially thinned stands, which exhibit higher diversity of resources compared to other habitat types, shrew populations were less affected by changes in mice densities. These spatially and temporally variable interactions between unlikely competitors, observed in a relatively simple, high-latitude island ecosystem, highlight the difficulty in assessing the role of biotic factors in structuring communities.

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Mule deer (Odocoileus hemionus hemionus) populations have been declining throughout their range and deteriorating habitat conditions are likely one cause of these declines. Reductions in food and cover availability along traditional routes may especially influence habitat use during migration by mule deer. Forest management practices such as underburning, the practice of using low-severity fires to reduce fuel loads, are often assumed to be beneficial to deer through enhancement of forage quality and quantity. However, these practices may be detrimental to mule deer through decreases in food and cover availability. Currently, little is known about the effects of underburning on habitat use by mule deer during migration. We analyzed Global Positioning System tracking data from 187 adult female mule deer in central Oregon, USA, from 2005 to 2012 in relation to 243 areas that were underburned between 1977 and 2009 to assess effects of underburning on habitat use during seasonal migrations. During spring migration, mule deer decreased use of recently underburned (i.e., 7 yearssince-burned) areas compared with pretreatment use. There was not a difference in use of recently underburned areas before and after treatment during autumn migration. In spring, the proportion of used underburned areas declined postburn without recovering to preburn levels up to 20 years after treatment. The proportion of underburned areas used in autumn was much more variable, with use of postburn areas fluctuating above the preburn mean but never reaching the preburn maximum. We contend that reductions in forage and cover availability from underburning may negatively affect migrating mule deer, especially during spring. Thus, efforts should be taken to minimize burning large, continuous areas along migration routes and avoid burning adjacent areas during the same year to maintain a diverse mosaic of understory age classes, which will allow deer to make habitat use choices during migration. Ó

Mule deer (Odocoileus hemionus hemionus) populations have been declining throughout their range and loss or deterioration of habitat has been associated with observed trends. An understanding of the relative importance of landscape characteristics in affecting mule deer distribution will allow wildlife managers that alter habitat to make predictions regarding future use by mule deer, which is likely to influence mule deer population size and recruitment. We radio‐marked 376 adult female mule deer with global positioning system‐collars from 2006–2012 in south‐central Oregon, USA, to evaluate summer habitat use. We used multiple linear regression to develop a resource utilization function (RUF) model for mule deer to relate landscape characteristics to the height of a utilization distribution estimated with a Brownian bridge movement model. We validated the predictive capacity of the RUF model with locations from an independent dataset of 95 deer that summered within our study area. Our best model describing mule deer habitat use included 5 covariates: overstory canopy cover, slope, distance to forest edge, distance to intermittent or perennial streams, and distance to dirt roads. Predicted intensity of use peaked at roughly 40% canopy cover and decreased with increasing slope and distance from forest edge. Predicted use was greater closer to streams and decreased, albeit slightly, with increasing distance from dirt roads. Model validation revealed our model predicted summer habitat use by mule deer very well. Our results provide a basis for predicting effects of future land management actions on mule deer habitat use on summer range. Forest management prescriptions that maintain canopy cover around 40% and create forest edge may benefit mule deer in south‐central Oregon and other forested ecosystems, particularly if these prescriptions are implemented on areas with gentle slopes and access to streams. © 2019 The Wildlife Society.