![]() We characterize this uncertainty in the strength of evidence with two different types of confidence intervals, which we term "global" and "local." We discuss how evidence uncertainty can be used to improve scientific inference and illustrate this with a reanalysis of the model identification problem in a prominent landscape ecology study using structural equations.Ĭontext. This sampling distribution allows us to determine how secure we are in our evidential statement. We develop non-parametric bootstrap methodologies for estimating the sampling distribution of the evidence estimator under model misspecification. ![]() Unfortunately, the standard theory breaks down if the models are misspecified, as is commonly the case in scientific studies. This uncertainty is well characterized by the standard statistical theory of estimation. To use evidence, either for decision making or as a guide to the accumulation of knowledge, an understanding of the uncertainty in the evidence is needed. This is done via an evidence function, such as SIC, an estimator of the sample size scaled difference of divergences between the generating mechanism and the competing models. The main goal of the evidential paradigm is to quantify the strength of evidence in the data for a reference model relative to an alternative model. ![]() Scientists need to compare the support for models based on observed phenomena. Given the widespread accessibility of LMMs in ecology and evolution, future simulation studies and further assessments of these statistical methods are necessary to understand the consequences both of violating and of routinely following simple guidelines. when they are 'nuisance' parameters used to group non-independent data), but further work is needed to explore alternative scenarios. Thus, it may be acceptable to use fewer than five levels of random effects if one is not interested in making inferences about the random effects terms (i.e. LMMs including low-level random effects terms may come at the expense of increased singular fits, but this did not appear to influence coverage probability or RMSE, except in low sample size (N = 30) scenarios. Instead, the coverage probability of fixed effects estimates is sample size dependent. Here, I simulate datasets and fit simple models to show that having few random effects levels does not strongly influence the parameter estimates or uncertainty around those estimates for fixed effects terms-at least in the case presented here. Having so few levels makes the estimation of the variance of random effects terms (such as ecological sites, individuals, or populations) difficult, but it need not muddy one's ability to estimate fixed effects terms-which are often of primary interest in ecology. One common guideline is that one needs at least five levels of the grouping variable associated with a random effect. Behavioral flexibility may promote species persistence as climate changes, and should be considered in conservation strategies of vulnerable species, such as eastern spotted skunks.Īs linear mixed-effects models (LMMs) have become a widespread tool in ecology, the need to guide the use of such tools is increasingly important. Our findings indicate that small endotherms, like the eastern spotted skunk, rely extensively on behavioral thermoregulation, instead of physiological adaptation, to buffer themselves against changing environmental conditions. Increased activity of skunks during or shortly after precipitation may be driven by increased prey availability. Lower activity and movement at cooler temperatures significantly reduces thermoregulatory costs for small endotherms. Eastern spotted skunks likely reduce predation risk by being active between sunset and sunrise when they are less visible to predators. ![]() Variation in moon illumination, which may affect predation risk, did not impact skunk nightly activity or movement. Total time active and total distance moved each night increased with ambient temperature and rainfall. Eastern spotted skunks were strictly nocturnal, exhibiting almost no daytime activity. Nightly movements and activity of skunks were monitored in association with ambient temperature, precipitation, and moon illumination during late winter through summer in Alabama. We used accelerometer-informed GPS telemetry to assess nightly activity and movement patterns in response to environmental conditions in a small endotherm, the eastern spotted skunk (Spilogale putorius). Behaviorally, animals often respond to changes in their environment through regulation of activity and associated movement patterns. Daily and seasonal fluctuations in environmental conditions can significantly impact the survivorship and reproductive success of animals by altering energetic costs and predation risks.
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