Rigorous science that produces reliable knowledge is critical to wildlife management because it increases accurate understanding of the natural world and informs management decisions effectively. Application of a rigorous scientific method based on hypothesis testing minimizes unreliable knowledge produced by research. To evaluate the prevalence of scientific rigor in wildlife research, we examined 24 issues of the Journal of Wildlife Management from August 2013 through July 2016. We found 43.9% of studies did not state or imply a priori hypotheses, which are necessary to produce reliable knowledge. We posit that this is due, at least in part, to a lack of common understanding of what rigorous science entails, how it produces more reliable knowledge than other forms of interpreting observations, and how research should be designed to maximize inferential strength and usefulness of application. Current primary literature does not provide succinct explanations of the logic behind a rigorous scientific method or readily applicable guidance for employing it, particularly in wildlife biology; we therefore synthesized an overview of the history, philosophy, and logic that define scientific rigor for biological studies. A rigorous scientific method includes 1) generating a research question from theory and prior observations, 2) developing hypotheses (i.e., plausible biological answers to the question), 3) formulating predictions (i.e., facts that must be true if the hypothesis is true), 4) designing and implementing research to collect data potentially consistent with predictions, 5) evaluating whether predictions are consistent with collected data, and 6) drawing inferences based on the evaluation. Explicitly testing a priori hypotheses reduces overall uncertainty by reducing the number of plausible biological explanations to only those that are logically well supported. Such research also draws inferences that are robust to idiosyncratic observations and unavoidable human biases. Offering only post hoc interpretations of statistical patterns (i.e., a posteriori hypotheses) adds to uncertainty because it increases the number of plausible biological explanations without determining which have the greatest support. Further, post hoc interpretations are strongly subject to human biases. Testing hypotheses maximizes the credibility of research findings, makes the strongest contributions to theory and management, and improves reproducibility of research. Management decisions based on rigorous research are most likely to result in effective conservation of wildlife resources. © 2018 The Wildlife Society.

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Resource heterogeneity across the landscape prompts animals to make behavioral tradeoffs to survive and reproduce. Behavioral thermoregulation can buffer organisms from thermal extremes but may conflict with other essential activities such as predator avoidance or foraging, and necessitate tradeoffs among resource requirements. We evaluated patterns of habitat selection relative to thermal conditions, forage availability, and concealment cover for female eastern wild turkeys (Meleagris gallopavo silvestris) with broods to assess potential tradeoffs among resource requirements. We quantified air temperature (°C), vegetation characteristics (e.g., visual obstruction), and arthropod biomass (g/m 2 ) at locations used by broods across 5 study sites in the southeastern United States during May-July 2019-2020. We used conditional logistic regression to estimate brooding female resource selection at the second (home range) and third (within home range) orders. Specifically, we identified differences in selection between brooding and non-brooding females (second order), and factors influencing selection of sites used by brooding females during the day (when loafing and foraging) and night (roosting; third order). Brooding females selected sites with cooler temperatures (β = −0.22; 95% CI = −0.338-−0.102) and greater ground cover vegetation (β = 0.02; 95% CI = 0.013-0.033) than non-brooding females.Additionally, biomass of large prey (Orthoptera) was positively

Global climate change is increasing the frequency and severity of extreme climatic events (ECEs) which may be especially detrimental during late‐winter when many species are surviving on scarce resources. However, monitoring animal populations relative to ECEs is logistically challenging. Crowd‐sourced datasets may provide opportunity to monitor species' responses to short‐term chance phenomena such as ECEs. We used 14 years of eBird—a global citizen science initiative—to examine distribution changes for seven wintering waterfowl species across North America in response to recent extreme winter polar vortex disruptions. To validate inferences from eBird, we compared eBird distribution changes against locational data from 362 GPS‐tagged Mallards (Anas platyrhynchos) in the Mississippi Flyway. Distributional shifts between eBird and GPS‐tagged Mallards were similar following an ECE in February 2021. In general, the ECE affected continental waterfowl population distributions; however, responses were variable across species and flyways. Waterfowl distributions tended to stay near wintering latitudes or moved north at lesser distances compared with non‐ECE years, suggesting preparedness for spring migration was a stronger “pull” than extreme weather was a “push” pressure. Surprisingly, larger‐bodied waterfowl with grubbing foraging strategies (i.e., geese) delayed their northward range shift during ECE years, whereas smaller‐bodied ducks were less affected. Lastly, wetland obligate species shifted southward during ECE years. Collectively, these results suggest specialized foraging strategies likely related to resource limitations, but not body size, necessitate movement from extreme late‐winter weather in waterfowl. Our results demonstrate eBird's potential to monitor population‐level effects of weather events, especially severe ECEs. eBird and other crowd‐sourced datasets can be valuable to identify species which are adaptable or vulnerable to ECEs and thus, begin to inform conservation policy and management to combat negative effects of global climate change.

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