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Ecologists frequently ask questions that are best addressed with a model comparison approach. Under this system, the merit of several models is considered without necessarily requiring that (1) models are nested, (2) one of the models is true, and (3) only current data be used. This is in marked contrast to the pragmatic blend of Neyman-Pearson and Fisherian significance testing conventionally emphasized in biometric texts (Christensen 2005), in which (1) just two hypotheses are under consideration, representing a pairwise comparison of models, (2) one of the models, H sub(0), is assumed to be true, and (3) a single data set is used to quantify evidence concerning H sub(0).

The steady upward trend in the use of model selection and Bayesian methods in ecological research has made it clear that both approaches to inference are important for modern analysis of models and data. However, in teaching Bayesian methods and in working with our research colleagues, we have noticed a general dissatisfaction with the available literature on Bayesian model selection and multimodel inference. Students and researchers new to Bayesian methods quickly find that the published advice on model selection is often preferential in its treatment of options for analysis, frequently advocating one particular method above others. The recent appearance of many articles and textbooks on Bayesian modeling has provided welcome background on relevant approaches to model selection in the Bayesian framework, but most of these are either very narrowly focused in scope or inaccessible to ecologists. Moreover, the methodological details of Bayesian model selection approaches are spread thinly throughout the literature, appearing in journals from many different fields. Our aim with this guide is to condense the large body of literature on Bayesian approaches to model selection and multimodel inference and present it specifically for quantitative ecologists as neutrally as possible. We also bring to light a few important and fundamental concepts relating directly to model selection that seem to have gone unnoticed in the ecological literature. Throughout, we provide only a minimal discussion of philosophy, preferring instead to examine the breadth of approaches as well as their practical advantages and disadvantages. This guide serves as a reference for ecologists using Bayesian methods, so that they can better understand their options and can make an informed choice that is best aligned with their goals for inference.

Since Darwin published the \"Origin,\" great progress has been made in our understanding of speciation mechanisms. The early investigations by Mayr and Dobzhansky linked Darwin's view of speciation by adaptive divergence to the evolution of reproductive isolation, and thus provided a framework for studying the origin of species. However, major controversies and questions remain, including: When is speciation nonecological? Under what conditions does geographic isolation constitute a reproductive isolating barrier? and How do we estimate the \"importance\" of different isolating barriers? Here, we address these questions, providing historical background and offering some new perspectives. A topic of great recent interest is the role of ecology in speciation. \"Ecological speciation\" is defined as the case in which divergent selection leads to reproductive isolation, with speciation under uniform selection, polyploid speciation, and speciation by genetic drift defined as \"nonecological.\" We review these proposed cases of nonecological speciation and conclude that speciation by uniform selection and polyploidy normally involve ecological processes. Furthermore, because selection can impart reproductive isolation both directly through traits under selection and indirectly through pleiotropy and linkage, it is much more effective in producing isolation than genetic drift. We thus argue that natural selection is a ubiquitous part of speciation, and given the many ways in which stochastic and deterministic factors may interact during divergence, we question whether the ecological speciation concept is useful. We also suggest that geographic isolation caused by adaptation to different habitats plays a major, and largely neglected, role in speciation. We thus provide a framework for incorporating geographic isolation into the biological species concept (BSC) by separating ecological from historical processes that govern species distributions, allowing for an estimate of geographic isolation based upon genetic differences between taxa. Finally, we suggest that the individual and relative contributions of all potential barriers be estimated for species pairs that have recently achieved species status under the criteria of the BSC. Only in this way will it be possible to distinguish those barriers that have actually contributed to speciation from those that have accumulated after speciation is complete. We conclude that ecological adaptation is the major driver of reproductive isolation, and that the term \"biology of speciation,\" as proposed by Mayr, remains an accurate and useful characterization of the diversity of speciation mechanisms.

The effect of ecological change on evolution has long been a focus of scientific research. The reverse--how evolutionary dynamics affect ecological traits--has only recently captured our attention, however, with the realization that evolution can occur over ecological time scales. This newly highlighted causal direction and the implied feedback loop--eco-evolutionary dynamics--is invigorating both ecologists and evolutionists and blurring the distinction between them. Despite some recent relevant studies, the importance of the evolution-to-ecology pathway across systems is still unknown. Only an extensive research effort involving multiple experimental approaches--particularly long-term field experiments--over a variety of ecological communities will provide the answer.

Akaike's information criterion (AIC) is increasingly being used in analyses in the field of ecology. This measure allows one to compare and rank multiple competing models and to estimate which of them best approximates the “true” process underlying the biological phenomenon under study. Behavioural ecologists have been slow to adopt this statistical tool, perhaps because of unfounded fears regarding the complexity of the technique. Here, we provide, using recent examples from the behavioural ecology literature, a simple introductory guide to AIC: what it is, how and when to apply it and what it achieves. We discuss multimodel inference using AIC--a procedure which should be used where no one model is strongly supported. Finally, we highlight a few of the pitfalls and problems that can be encountered by novice practitioners.

Niche construction theory (NCT) explicitly recognizes environmental modification by organisms (“niche construction”) and their legacy over time (“ecological inheritance”) to be evolutionary processes in their own right. Here we illustrate how niche construction theory provides useful conceptual tools and theoretical insights for integrating ecosystem ecology and evolutionary theory. We begin by briefly describing NCT, and illustrating how it differs from conventional evolutionary approaches. We then distinguish between two aspects of niche construction—environment alteration and subsequent evolution in response to constructed environments—equating the first of these with “ecosystem engineering.” We describe some of the ecological and evolutionary impacts on ecosystems of niche construction, ecosystem engineering, and ecological inheritance, and illustrate how these processes trigger ecological and evolutionary feedbacks and leave detectable ecological signatures that are open to investigation. Finally, we provide a practical guide to how NCT could be deployed by ecologists and evolutionary biologists to explore eco-evolutionary dynamics. We suggest that, by highlighting the ecological and evolutionary ramifications of changes that organisms bring about in ecosystems, NCT helps link ecosystem ecology to evolutionary biology, potentially leading to a deeper understanding of how ecosystems change over time.

Natural selection commonly drives the origin of species, as Darwin initially claimed. Mechanisms of speciation by selection fall into two broad categories: ecological and mutation-order. Under ecological speciation, divergence is driven by divergent natural selection between environments, whereas under mutation-order speciation, divergence occurs when different mutations arise and are fixed in separate populations adapting to similar selection pressures. Tests of parallel evolution of reproductive isolation, trait-based assortative mating, and reproductive isolation by active selection have demonstrated that ecological speciation is a common means by which new species arise. Evidence for mutation-order speciation by natural selection is more limited and has been best documented by instances of reproductive isolation resulting from intragenomic conflict. However, we still have not identified all aspects of selection, and identifying the underlying genes for reproductive isolation remains challenging.

Ecological speciation is considered an adaptive response to selection for local adaptation. However, besides suitable ecological conditions, the process requires assortative mating to protect the nascent species from homogenization by gene flow. By means of a simple model, we demonstrate that disruptive ecological selection favors the evolution of sexual preferences for ornaments that signal local adaptation. Such preferences induce assortative mating with respect to ecological characters and enhance the strength of disruptive selection. Natural and sexual selection thus work in concert to achieve local adaptation and reproductive isolation, even in the presence of substantial gene flow. The resulting speciation process ensues without the divergence of mating preferences, avoiding problems that have plagued previous models of speciation by sexual selection.

Significance In recent years, there has been a vigorous debate among ecologists over the merits of two contrasting models of biodiversity: the niche and neutral theories of ecology. Using two different theoretical models of ecological dynamics, we show that there is a transition between a selection-dominated regime (the niche phase) and a drift-dominated regime (the neutral phase). This is analogous to the phase diagram of water, which can be in the solid, liquid, or gas phase, depending on the temperature and pressure. Our results demonstrate how the niche and neutral theories both emerge from the same underlying ecological principles.

This paper proposes a new way of using forward selection of explanatory variables in regression or canonical redundancy analysis. The classical forward selection method presents two problems: a highly inflated Type I error and an overestimation of the amount of explained variance. Correcting these problems will greatly improve the performance of this very useful method in ecological modeling. To prevent the first problem, we propose a two-step procedure. First, a global test using all explanatory variables is carried out. If, and only if, the global test is significant, one can proceed with forward selection. To prevent overestimation of the explained variance, the forward selection has to be carried out with two stopping criteria: (1) the usual alpha significance level and (2) the adjusted coefficient of multiple determination ($R_{a}^{2}$) calculated using all explanatory variables. When forward selection identifies a variable that brings one or the other criterion over the fixed threshold, that variable is rejected, and the procedure is stopped. This improved method is validated by simulations involving univariate and multivariate response data. An ecological example is presented using data from the Bryce Canyon National Park, Utah, USA.