Summary: Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. Most frequently, individual animals are monitored and pooled to estimate population‐level effects without regard to group or individual‐level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. Here we review random‐effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

Detailed empirical models predicting both species occurrence and fitness across a landscape are necessary to understand processes related to population persistence. Failure to consider both occurrence and fitness may result in incorrect assessments of habitat importance leading to inappropriate management strategies. We took a two‐stage approach to identifying critical nesting and brood‐rearing habitat for the endangered Greater Sage‐Grouse (Centrocercus urophasianus) in Alberta at a landscape scale. First, we used logistic regression to develop spatial models predicting the relative probability of use (occurrence) for Sage‐Grouse nests and broods. Secondly, we used Cox proportional hazards survival models to identify the most risky habitats across the landscape. We combined these two approaches to identify Sage‐Grouse habitats that pose minimal risk of failure (source habitats) and attractive sink habitats that pose increased risk (ecological traps). Our models showed that Sage‐Grouse select for heterogeneous patches of moderate sagebrush cover (quadratic relationship) and avoid anthropogenic edge habitat for nesting. Nests were more successful in heterogeneous habitats, but nest success was independent of anthropogenic features. Similarly, broods selected heterogeneous high‐productivity habitats with sagebrush while avoiding human developments, cultivated cropland, and high densities of oil wells. Chick mortalities tended to occur in proximity to oil and gas developments and along riparian habitats. For nests and broods, respectively, approximately 10% and 5% of the study area was considered source habitat, whereas 19% and 15% of habitat was attractive sink habitat. Limited source habitats appear to be the main reason for poor nest success (39%) and low chick survival (12%). Our habitat models identify areas of protection priority and areas that require immediate management attention to enhance recruitment to secure the viability of this population. This novel approach to habitat‐based population viability modeling has merit for many species of concern.

We revised distribution maps of potential presettlement habitat and current populations for Greater Sage-Grouse (Centrocercus urophasianus) and Gunnison Sage- Grouse (C. minimus) in North America. The revised map of potential presettlement habitat included some areas omitted from previously published maps such as the San Luis Valley of Colorado and Jackson area of Wyoming. Areas excluded from the revised maps were those dominated by barren, alpine, and forest habitats. The resulting presettlement distribution of potential habitat for Greater Sage-Grouse encompassed 1 200 483 km², with the species' current range 668 412 km². The distribution of potential Gunnison Sage-Grouse habitat encompassed 46 521 km², with the current range 4787 km². The dramatic differences between the potential presettlement and current distributions appear related to habitat alteration and degradation, including the adverse effects of cultivation, fragmentation, reduction of sagebrush and native herbaceous cover, development, introduction and expansion of invasive plant species, encroachment by trees, and issues related to livestock grazing. Distribución de Centrocercus spp. en América del Norte Resumen. Revisamos los mapas de distribución potencial precolombino y de poblaciones actuales de Centrocerus urophasianus y C. minimus en América del Norte. El mapa modificado de hábitat potencial precolombino incluyó algunas áreas omitidas de mapas anteriormente publicados, como el Valle San Luis de Colorado y el área de Jackson, Wyoming. Las áreas excluídas de los mapas modificados fueron las dominadas por hábitats forestales, alpinos y estériles. La distribución precolombina resultante para C. urophasianus abarcó 1 200 483 km², con un territorio actual de 668 412 km². La distribución de habitat potencial para C. minimus abarcó 46 521 km², con un territorio actual de 4787 km². Estos contrastes tan marcados parecen estar relacionados con la modificación y degradación del hábitat, incluyendo los efectos nocivos de la agricultura, la fragmentación de hábitat, la disminución de Artemisia spp. y otras coberturas herbáceas nativas, el desarollo, la introducción y la expansión de especies de plantas invasoras, la invasión de árboles y cuestiones relacionadas con pastoreo de ganado.