Carnivore guilds play a vital role in ecological communities by cascading trophic effects, energy and nutrient transfer, and stabilizing or destabilizing food webs. Consequently, the structure of carnivore guilds can be critical to ecosystem patterns. Body size is a crucial influence on intraguild interactions, because it affects access to prey resources, effectiveness in scramble competition, and vulnerability to intraguild predation. Coyotes (Canis latrans), bobcats (Lynx rufus), gray foxes (Urocyon cinereoargenteus), raccoons (Procyon lotor), red foxes (Vulpes vulpes), and striped skunks (Mephitis mephitis) occur sympatrically throughout much of North America and overlap in resource use, indicating potential for interspecific interactions. Although much is known about the autecology of the individual species separately, little is known about factors that facilitate coexistence and how interactions within this guild influence distribution, habitat use, and temporal activity of the smaller carnivores. To assess how habitat autecology and interspecific interactions affect the structure of this widespread carnivore guild, we conducted a large‐scale, non‐invasive carnivore survey using an occupancy modeling framework. We deployed remote cameras during 3‐week surveys to detect carnivores at 1,118 camera locations in 357 2.6‐km2 sections (3–4 cameras/section composing a cluster) in the 16 southernmost counties of Illinois (16,058 km2) during January–April, 2008–2010. We characterized microhabitat at each camera location and landscape‐level habitat features for each camera cluster. In a multistage approach, we used information‐theoretic methods to evaluate competing models for detection, species‐specific habitat occupancy, multispecies co‐occupancy, and multiseason (colonization and extinction) occupancy dynamics. We developed occupancy models for each species to represent hypothesized effects of anthropogenic features, prey availability, landscape complexity, and vegetative land cover. We quantified temporal activity patterns of each carnivore species based on their frequency of appearance in photographs. Further, we assessed whether smaller carnivores shifted their diel activity patterns in response to the presence of potential competitors. Of the 102,711 photographs of endothermic animals, we recorded photographs of bobcats (n = 412 photographs), coyotes (n = 1,397), gray foxes (n = 546), raccoons (n = 40,029), red foxes (n = 149), and striped skunks (n = 2,467). Bobcats were active primarily during crepuscular periods, and their activity was reduced with precipitation and higher temperatures. The probability of detecting bobcats decreased after a bobcat photograph was recorded, suggesting avoidance of remote cameras after the first encounter. Across southern Illinois, bobcat occupancy at the camera‐location and camera‐cluster scale (ψtrueˆlocal = 0.24 ± 0.04, camera cluster ψtrueˆcluster = 0.75 ± 0.06) was negatively influenced by anthropogenic features and infrastructure. Bobcats had high rates of coloni...

: Survival of white‐tailed deer (Odocoileus virginianus) fawns has been quantified throughout much of North America. However, few studies have assessed the influence of intrinsic factors (e.g., fawn age and birth mass) and habitat on fawn survival. During 2002‐2004, we captured and radiocollared 166 fawns in southern Illinois, USA, to estimate survival rates, determine causes of mortality, and identify factors influencing fawn survival. We used a known fates model in program MARK to estimate survival rates and compare explanatory models based on Akaike's Information Criterion corrected for small sample sizes (AICc). We developed 2 candidate sets of a priori models to quantify factors influencing fawn survival: model set 1 included intrinsic factors and model set 2 focused on habitat variables. We recorded 64 mortalities and the overall survival rate was 0.59 (95% CI = 0.51‐0.68). Predation was the leading source of mortality (64%) and coyotes (Canis latrans) were the most prominent predator. For model set 1, model {Sage X year} had the lowest AICc value suggesting that the age at mortality varied among capture years. For model set 2, model {Slandscape+forest} had the lowest AICc value and indicated that areas inhabited by surviving fawns were characterized by a few large (i.e., > 5 ha) irregular forest patches adjacent to several small nonforest patches, and survival areas also contained more edge habitat than mortality areas. Due to the magnitude of coyote predation, survival areas could have represented landscapes where coyotes were less effective at locating and capturing fawns when compared to mortality areas. This study was the first account of macrohabitat characteristics directly influencing fawn survival. Wildlife managers can use this information to determine how habitat management activities may affect deer populations.

Ecologists routinely fit complex models with multiple parameters of interest, where hundreds or more competing models are plausible. To limit the number of fitted models, ecologists often define a model selection strategy composed of a series of stages in which certain features of a model are compared while other features are held constant. Defining these multi-stage strategies requires making a series of decisions, which may potentially impact inferences, but have not been critically evaluated. We begin by identifying key features of strategies, introducing descriptive terms when they did not already exist in the literature. Strategies differ in how they define and order model building stages. Sequential-by-sub-model strategies focus on one sub-model (parameter) at a time with modeling of subsequent sub-models dependent on the selected sub-model structures from the previous stages. Secondary candidate set strategies model sub-models independently and combine the top set of models from each sub-model for selection in a final stage. Build-up approaches define stages across sub-models and increase in complexity at each stage. Strategies also differ in how the top set of models is selected in each stage and whether they use null or more complex sub-model structures for non-target sub-models. We tested the performance of different model selection strategies using four data sets and three model types. For each data set, we determined the "true" distribution of AIC weights by fitting all plausible models. Then, we calculated the number of models that would have been fitted and the portion of "true" AIC weight we recovered under different model selection strategies. Sequential-by-sub-model strategies often performed poorly. Based on our results, we recommend using a build-up or secondary candidate sets, which were more reliable and carrying all models within 5-10 AIC of the top model forward to subsequent stages. The structure of non-target sub-models was less important. Multi-stage approaches cannot compensate for a lack of critical thought in selecting covariates and building models to represent competing a priori hypotheses. However, even when competing hypotheses for different sub-models are limited, thousands or more models may be possible so strategies to explore candidate model space reliably and efficiently will be necessary.

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: Establishment and spread of infectious diseases are controlled by the frequency of contacts among hosts. Although managers can estimate transmission coefficients from the relationship between disease prevalence and age or time, they may wish to quantify or compare contact rates before a disease is established or while it is at very low prevalence. Our objectives were to quantify direct and indirect contacts rates among white‐tailed deer (Odocoileus virginianus) and to compare these measures of contact rate with simpler measures of joint space use. We deployed Global Positioning System (GPS) collars on 23 deer near Carbondale, Illinois, USA, from 2002 to 2005. We used location data from the GPS collars to measure pairwise rates of direct and indirect contact, based on a range of proximity criteria and time lags, as well as volume of intersection (VI) of kernel utilization distributions. We analyzed contact rates at a given distance criterion and time lag using mixed‐model logistic regression. Direct contact rates increased with increasing VI and were higher in autumn—spring than in summer. After accounting for VI, the estimated odds of direct contact during autumn—spring periods were 5.0–22.1‐fold greater (depending on the proximity criterion) for pairs of deer in the same social group than for between‐group pairs, but for direct contacts during summer the within:between‐group odds ratio did not differ significantly from 1. Indirect contact rates also increased with VI, but the effects of both season and pair‐type were much smaller than for direct contacts and differed little as the time lag increased from 1–30 days. These results indicate that simple measures of joint space use are insufficient indices of direct contact because group membership can substantially increase contacts at a given level of joint space use. With indirect transmission, however, group membership had a much smaller influence after accounting for VI. Relationships between contact rates and season, VI, and pair‐type were generally robust to changes in the proximity criterion defining a contact, and patterns of indirect contacts were affected little by the choice of time lag from 1–30 days. The use of GPS collars provides a framework for testing hypotheses about the form of contact networks among large mammals and comparing potential direct and indirect contact rates across gradients of ecological factors, such as population density or landscape configuration.