•Many commonly used methods infer ecological processes from species distributions.•Historical biogeographic processes can cause spurious ecological inferences.•Many empirical results in ecological ...biogeography may be driven by these biases.•New methods may better handle these biases, but are comparatively rarely used.•Future development in ecological biogeography requires better handling of spatial patterns.
Over the past few decades, there has been a rapid proliferation of statistical methods that infer evolutionary and ecological processes from data on species distributions. These methods have led to considerable new insights, but they often fail to account for the effects of historical biogeography on present-day species distributions. Because the geography of speciation can lead to patterns of spatial and temporal autocorrelation in the distributions of species within a clade, this can result in misleading inferences about the importance of deterministic processes in generating spatial patterns of biodiversity. In this opinion article, we discuss ways in which patterns of species distributions driven by historical biogeography are often interpreted as evidence of particular evolutionary or ecological processes. We focus on three areas that are especially prone to such misinterpretations: community phylogenetics, environmental niche modelling, and analyses of beta diversity (compositional turnover of biodiversity).
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Maxent, one of the most commonly used methods for inferring species distributions and environmental tolerances from occurrence data, allows users to fit models of arbitrary complexity. Model ...complexity is typically constrained via a process known as
L
1
regularization, but at present little guidance is available for setting the appropriate level of regularization, and the effects of inappropriately complex or simple models are largely unknown. In this study, we demonstrate the use of information criterion approaches to setting regularization in Maxent, and we compare models selected using information criteria to models selected using other criteria that are common in the literature. We evaluate model performance using occurrence data generated from a known "“true"” initial Maxent model, using several different metrics for model quality and transferability. We demonstrate that models that are inappropriately complex or inappropriately simple show reduced ability to infer habitat quality, reduced ability to infer the relative importance of variables in constraining species' distributions, and reduced transferability to other time periods. We also demonstrate that information criteria may offer significant advantages over the methods commonly used in the literature.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, INZLJ, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZRSKP
In defense of ‘niche modeling’ Warren, Dan L.
Trends in ecology & evolution (Amsterdam),
09/2012, Volume:
27, Issue:
9
Journal Article
Peer reviewed
There is a growing awareness of problems with the estimation of the ecological tolerances of species through correlative modeling approaches. These problems have led some investigators to argue for ...abandoning terms such as ‘ecological niche model’ and ‘environmental niche model’ in favor of the ostensibly more value-neutral ‘species distribution model’, as the models are thought to frequently be poor estimators of the niche. Here, I argue that most applications to which these models are put require the assumption that they do estimate the niche, however imperfectly, and that obscuring this inescapable and potentially flawed assumption in the terminology may only serve to hinder the development of the field.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
We present software that facilitates quantitative comparisons of environmental niche models (ENMs). Our software quantifies similarity of ENMs generated using the program Maxent and uses ...randomization tests to compare observed similarity to that expected under different null hypotheses. ENMTools is available online free of charge from <http://purl.oclc.org/enmtools>.
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Bayesian inference using Markov chain Monte Carlo (MCMC) has become one of the primary methods used to infer phylogenies from sequence data. Assessing convergence is a crucial component of these ...analyses, as it establishes the reliability of the posterior distribution estimates of the tree topology and model parameters sampled from the MCMC. Numerous tests and visualizations have been developed for this purpose, but many of the most popular methods are implemented in ways that make them inconvenient to use for large data sets. RWTY is an R package that implements established and new methods for diagnosing phylogenetic MCMC convergence in a single convenient interface.
The ENMTools software package was introduced in 2008 as a platform for making measurements on environmental niche models (ENMs, frequently referred to as species distribution models or SDMs), and for ...using those measurements in the context of newly developed Monte Carlo tests to evaluate hypotheses regarding niche evolution. Additional functionality was later added for model selection and simulation from ENMs, and the software package has been quite widely used. ENMTools was initially implemented as a Perl script, which was also compiled into an executable file for various platforms. However, the package had a number of significant limitations; it was only designed to fit models using Maxent, it relied on a specific Perl distribution to function, and its internal structure made it difficult to maintain and expand. Subsequently, the R programming language became the platform of choice for most ENM studies, making ENMTools less usable for many practitioners. Here we introduce a new R version of ENMTools that implements much of the functionality of its predecessor as well as numerous additions that simplify the construction, comparison and evaluation of niche models. These additions include new metrics for model fit, methods of measuring ENM overlap, and methods for testing evolutionary hypotheses. The new version of ENMTools is also designed to work within the expanding universe of R tools for ecological biogeography, and as such includes greatly simplified interfaces for analyses from several other R packages.
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Aim
Species distribution models are used across evolution, ecology, conservation and epidemiology to make critical decisions and study biological phenomena, often in cases where experimental ...approaches are intractable. Choices regarding optimal models, methods and data are typically made based on discrimination accuracy: a model's ability to predict subsets of species occurrence data that were withheld during model construction. However, empirical applications of these models often involve making biological inferences based on continuous estimates of relative habitat suitability as a function of environmental predictor variables. We term the reliability of these biological inferences ‘functional accuracy.’ We explore the link between discrimination accuracy and functional accuracy.
Methods
Using a simulation approach we investigate whether models that make good predictions of species distributions correctly infer the underlying relationship between environmental predictors and the suitability of habitat.
Results
We demonstrate that discrimination accuracy is only informative when models are simple and similar in structure to the true niche, or when data partitioning is geographically structured. However, the utility of discrimination accuracy for selecting models with high functional accuracy was low in all cases.
Main conclusions
These results suggest that many empirical studies and decisions are based on criteria that are unrelated to models’ usefulness for their intended purpose. We argue that empirical modelling studies need to place significantly more emphasis on biological insight into the plausibility of models, and that the current approach of maximizing discrimination accuracy at the expense of other considerations is detrimental to both the empirical and methodological literature in this active field. Finally, we argue that future development of the field must include an increased emphasis on simulation; methodological studies based on ability to predict withheld occurrence data may be largely uninformative about best practices for applications where interpretation of models relies on estimating ecological processes, and will unduly penalize more biologically informative modelling approaches.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Environmental niche models, which are generated by combining species occurrence data with environmental GIS data layers, are increasingly used to answer fundamental questions about niche evolution, ...speciation, and the accumulation of ecological diversity within clades. The question of whether environmental niches are conserved over evolutionary time scales has attracted considerable attention, but often produced conflicting conclusions. This conflict, however, may result from differences in how niche similarity is measured and the specific null hypothesis being tested. We develop new methods for quantifying niche overlap that rely on a traditional ecological measure and a metric from mathematical statistics. We reexamine a classic study of niche conservatism between sister species in several groups of Mexican animals, and, for the first time, address alternative definitions of “niche conservatism” within a single framework using consistent methods. As expected, we find that environmental niches of sister species are more similar than expected under three distinct null hypotheses, but that they are rarely identical. We demonstrate how our measures can be used in phylogenetic comparative analyses by reexamining niche divergence in an adaptive radiation of Cuban anoles. Our results show that environmental niche overlap is closely tied to geographic overlap, but not to phylogenetic distances, suggesting that niche conservatism has not constrained local communities in this group to consist of closely related species. We suggest various randomization tests that may prove useful in other areas of ecology and evolutionary biology.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
A key element to a successful Markov chain Monte Carlo (MCMC) inference is the programming and run performance of the Markov chain. However, the explicit use of quality assessments of the MCMC ...simulations—convergence diagnostics—in phylogenetics is still uncommon. Here, we present a simple tool that uses the output from MCMC simulations and visualizes a number of properties of primary interest in a Bayesian phylogenetic analysis, such as convergence rates of posterior split probabilities and branch lengths. Graphical exploration of the output from phylogenetic MCMC simulations gives intuitive and often crucial information on the success and reliability of the analysis. The tool presented here complements convergence diagnostics already available in other software packages primarily designed for other applications of MCMC. Importantly, the common practice of using trace-plots of a single parameter or summary statistic, such as the likelihood score of sampled trees, can be misleading for assessing the success of a phylogenetic MCMC simulation. Availability: The program is available as source under the GNU General Public License and as a web application at http://ceb.scs.fsu.edu/awty Contact: jwilgenb@scs.fsu.edu
Understanding the role of geography and ecology in species divergence is central to the study of evolutionary diversification. We used climatic, geographic, and biological data from nine wild Andean ...tomato species to describe each species' ecological niche and to evaluate the likely ecological and geographical modes of speciation in this clade. Using data from >1000 wild accessions and publicly available data derived from geographic information systems for various environmental variables, we found most species pairs were significantly differentiated for one or more environmental variables. By comparing species' predicted niches generated by species distribution modeling (SDM), we found significant niche differentiation among three of four sister-species pairs, suggesting ecological divergence is consistently associated with recent divergence. In comparison, based on age-range correlation (ARC) analysis, there was no evidence for a predominant geographical (allopatric vs. sympatric) context for speciation in this group. Overall, our results suggest an important role for environmentally mediated differentiation, rather than simply geographical isolation, in species divergence.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
PDF
