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.

The transition of natural landscapes to agricultural uses has resulted in severe loss of soil organic carbon, significantly contributing to CO₂ emissions and rising global temperatures. However, soil has the largest store of terrestrial carbon (C), a considerable sink and effective strategy for climate change mitigation if managed properly. Cover crops (CC) and no-till (NT) management are two management strategies that are known to increase percent organic carbon (%OC); however, adoption of these practices has been low in the mid-South due to lack of region-specific research and resistance to unproven practices. Therefore, the purpose of this study was to evaluate the impacts of CC-NT treatments in soybean cropping systems on soil percent organic carbon (%OC) and CO₂ flux following long-term implementation. Results showed significantly greater %OC in NT (1.27% ± 0.03) than reduced till (RT; 1.10% ± 0.03; p < 0.001) and greater in both CC (rye: 1.23% ± 0.03, rye + clover: 1.22% ± 0.03) than no cover (1.11% ± 0.03; p < 0.001). Bacterial abundance (p = 0.005) and pH (p = 0.006) were significant predictors of %OC. There was no overall significant difference in CO₂ flux between tillage or CC treatments; however, there were significant differences between NT and RT in July of 2020 when %RH increased (p < 0.001). Bacterial abundance negatively impacted CO₂ flux (p < 0.05), which contradicts most studies. The rate of proportional change and pattern of variability in C pools suggested loss of %OC in RT treatments that were not apparent when considering %OC alone. The results of this study provide valuable insight into C turnover and the effectiveness of CC use in the Mid-South to increase soil C stocks.

Species coexistence is governed by availability of resources and intraguild interactions including strategies to reduce ecological overlap. Gray foxes are dietary generalist mesopredators expected to benefit from anthropogenic disturbance, but populations have declined across the midwestern USA, including severe local extirpation rates coinciding with high coyote and domestic dog occurrence and low red fox occurrence. We used data from a large‐scale camera trap survey in southern Illinois, USA to quantify intraguild spatial and temporal interactions among the canid guild including domestic dogs. We used a two‐species co‐occurrence model to make pairwise assessments of conditional occupancy and detection rates. We also estimated temporal activity overlap among species and fit a fixed‐effects hierarchical community occupancy model with the four canid species. We partitioned the posterior distributions to compare gray fox occupancy probabilities conditional on estimated state of combinations of other species to assess support for hypothesized interactions. We found no evidence of broadscale avoidance among native canids and conclude that spatial and temporal segregation were limited by ubiquitous human disturbance. Mean guild richness was two canid species at a site and gray fox occupancy was greater when any combination of sympatric canids was also present, setting the stage for competitive exclusion over time. Domestic dogs may amplify competitive interactions by increasing canid guild size to the detriment of gray foxes. Our results suggest that while human activities can benefit some mesopredators, other species such as gray foxes may serve as bellwethers for habitat degradation with trophic downgrading and continued anthropogenic homogenization.

Context: Anthropogenic landscape modification and fragmentation result in loss of species and can alter ecosystem function. Assessment of the ecological value of urban reserve networks requires baseline and continued monitoring. However, depending on the desired indicators and parameters, effective monitoring can involve extensive sampling that is often financially or logistically infeasible. Aims: We employed a low-intensity, mixed-detector survey design to monitor the small-mammal community across a network of 53 fragmented forest preserves (225 sites) in a highly urbanised landscape in the Chicago metropolitan area from August to October, 2009–2012. Methods: We used a sequential process to fit single-season occupancy and pairwise co-occurrence models for six common small mammal species to evaluate habitat associations and interspecific interactions. Key results: Shrew species and meadow voles occurred more often in open canopy-associated habitats, whereas occupancy was greater for eastern chipmunks, grey squirrels and white-footed mice in closed-canopy habitats. Habitat associations were complicated by negative pairwise interactions, resulting in reduced occurrence of meadow voles when predatory short-tailed shrews were present and lower occupancy rates of white-footed mouse when chipmunk competitors where present. White-footed mice co-occurred with short-tailed shrews, but detection of white-footed mice was lower when either eastern chipmunks or short-tailed shrews were present, suggesting that densities of these species could be inversely related. Conclusions: We found evidence for both habitat segregation and interspecific interactions among small mammal species, by using low-intensity sampling across the reserve network. Thus, our sampling and analysis approach allowed for adequate assessment of the habitat associations and species interactions within a small-mammal community. Implications: Our findings demonstrated the utility of this monitoring strategy and community as bioindicators for urban-reserve networks. The approach described holds promise for efficient monitoring of reserve networks in fragmented landscapes, critical as human population densities and urbanisation increase, and we discuss how adaptive sampling methods could be incorporated to further benefit conservation efforts.