Conservationists are far from able to assist all species under threat, if only for lack of funding. This places a premium on priorities: how can we support the most species at the least cost? One way is to identify 'biodiversity hotspots' where exceptional concentrations of endemic species are undergoing exceptional loss of habitat. As many as 44% of all species of vascular plants and 35% of all species in four vertebrate groups are confined to 25 hotspots comprising only 1.4% of the land surface of the Earth. This opens the way for a 'silver bullet' strategy on the part of conservation planners, focusing on these hotspots in proportion to their share of the world's species at risk.

Biodiversity hotspots for conservation priorities

https://www.cs.princeton.edu/~schapire/papers/ecolmod.pdf

Maximum entropy modeling of species geographic distributions

Accurate modeling of geographic distributions of species is crucial to various applications in ecology and conservation. The best performing techniques often require some parameter tuning, which may be prohibitively time-consuming to do separately for each species, or unreliable for small or biased datasets. Additionally, even with the abundance of good quality data, users interested in the application of species models need not have the statistical knowledge required for detailed tuning. In such cases, it is desirable to use "default settings", tuned and validated on diverse datasets. Maxent is a recently introduced modeling technique, achieving high predictive accuracy and enjoying several additional attractive properties. The performance of Maxent is influenced by a moderate number of parameters. The first contribution of this paper is the empirical tuning of these parameters. Since many datasets lack information about species absence, we present a tuning method that uses presence-only data. We evaluate our method on independently collected high-quality presence-absence data. In addition to tuning, we introduce several concepts that improve the predictive accuracy and running time of Maxent. We introduce "hinge features" that model more complex relationships in the training data; we describe a new logistic output format that gives an estimate of probability of presence; finally we explore "background sampling" strategies that cope with sample selection bias and decrease model-building time. Our evaluation, based on a diverse dataset of 226 species from 6 regions, shows: 1) default settings tuned on presence-only data achieve performance which is almost as good as if they had been tuned on the evaluation data itself; 2) hinge features substantially improve model performance; 3) logistic output improves model calibration, so that large differences in output values correspond better to large differences in suitability; 4) "target-group" background sampling can give much better predictive performance than random background sampling; 5) random background sampling results in a dramatic decrease in running time, with no decrease in model performance.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.0906-7590.2008.5203.x

Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation

Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale-dependent

/pdf/predicting-the-impacts-of-climate-change-on-the-distribution-f5pj1nly81.pdf

Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?

▪ Abstract As better phylogenetic hypotheses become available for many groups of organisms, studies in community ecology can be informed by knowledge of the evolutionary relationships among coexisting species. We note three primary approaches to integrating phylogenetic information into studies of community organization: 1. examining the phylogenetic structure of community assemblages, 2. exploring the phylogenetic basis of community niche structure, and 3. adding a community context to studies of trait evolution and biogeography. We recognize a common pattern of phylogenetic conservatism in ecological character and highlight the challenges of using phylogenies of partial lineages. We also review phylogenetic approaches to three emergent properties of communities: species diversity, relative abundance distributions, and range sizes. Methodological advances in phylogenetic supertree construction, character reconstruction, null models for community assembly and character evolution, and metrics of community ...

/pdf/phylogenies-and-community-ecology-52euwskuu7.pdf

Phylogenies and Community Ecology

This book provides a first synthetic view of an emerging area of ecology and biogeography, linking individual- and population-level processes to geographic distributions and biodiversity patterns. Problems in evolutionary ecology, macroecology, and biogeography are illuminated by this integrative view. The book focuses on correlative approaches known as ecological niche modeling, species distribution modeling, or habitat suitability modeling, which use associations between known occurrences of species and environmental variables to identify environmental conditions under which populations can be maintained. The spatial distribution of environments suitable for the species can then be estimated: a potential distribution for the species. This approach has broad applicability to ecology, evolution, biogeography, and conservation biology, as well as to understanding the geographic potential of invasive species and infectious diseases, and the biological implications of climate change. The authors lay out conceptual foundations and general principles for understanding and interpreting species distributions with respect to geography and environment. Focus is on development of niche models. While serving as a guide for students and researchers, the book also provides a theoretical framework to support future progress in the field.

Ecological Niches and Geographic Distributions

Theory predicts low niche differentiation between species over evolutionary time scales, but little empirical evidence is available. Reciprocal geographic predictions based on ecological niche models of sister taxon pairs of birds, mammals, and butterflies in southern Mexico indicate niche conservatism over several million years of independent evolution (between putative sister taxon pairs) but little conservatism at the level of families. Niche conservatism over such time scales indicates that speciation takes place in geographic, not ecological, dimensions and that ecological differences evolve later.

https://science.sciencemag.org/content/sci/285/5431/1265.full.pdf

Conservatism of Ecological Niches in Evolutionary Time

Risk maps summarizing landscape suitability of novel areas for invading species can be valuable tools for preventing species’ invasions or controlling their spread, but methods employed for development of such maps remain variable and unstandardized. We discuss several considerations in development of such models, including types of distributional information that should be used, the nature of explanatory variables that should be incorporated, and caveats regarding model testing and evaluation. We highlight that, in the case of invasive species, such distributional predictions should aim to derive the best hypothesis of the potential distribution of the species by using (1) all distributional information available, including information from both the native range and other invaded regions; (2) predictors linked as directly as is feasible to the physiological requirements of the species; and (3) modelling procedures that carefully avoid overfitting to the training data. Finally, model testing and evaluation should focus on well-predicted presences, and less on efficient prediction of absences; a k-fold regional cross-validation test is discussed.

Use of niche models in invasive species risk assessments.

Summary
The field of ecological niche modelling or species distribution modelling has seen enormous activity and attention in recent years, in the light of exciting biological inferences that can be drawn from correlational models of species' environmental requirements (i.e. ecological niches) and inferences of potential geographic distributions. Among the many methods used in the field, one or two are in practice assumed to be ‘best’ and are used commonly, often without explicit testing.
We explore herein implications of the ‘no free lunch’ theorem, which suggests that no single optimization approach will prove to be best under all circumstances: we developed diverse virtual species with known niche and dispersal properties to test a suite of niche modelling algorithms designed to estimate potential areas of distribution.
The result was that (i) indeed, no single ‘best’ algorithm was found and (ii) different algorithms performing very different manners depending on the particularities of the virtual species.
The conclusion is that niche or distribution modelling studies should begin by testing a suite of algorithms for predictive ability under the particular circumstances of the study and choose an algorithm for a particular challenge based on the results of those tests. Studies that do not take this step may use algorithms that are not optimal for that particular challenge.

https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/2041-210X.12397

No silver bullets in correlative ecological niche modelling: insights from testing among many potential algorithms for niche estimation

Aim To provide a test of the conservatism of a species’ niche over the last 20,000 years by tracking the distribution of eight pollen taxa relative to climate type as they migrated across eastern North America following the Last Glacial Maximum (LGM).



Location  North America.



Methods  We drew taxon occurrence data from the North American pollen records in the Global Pollen Database, representing eight pollen types – all taxa for which ≥5 distinct geographic occurrences were available in both the present day and at the LGM (21,000 years ago ± 3000 years). These data were incorporated into ecological niche models based on present-day and LGM climatological summaries available from the Palaeoclimate Modelling Intercomparison Project to produce predicted potential geographic distributions for each species at present and at the LGM. The output for each time period was projected onto the ‘other’ time period, and tested using independent known occurrence information from that period.



Results  The result of our analyses was that all species tested showed general conservatism in ecological characteristics over the climate changes associated with the Pleistocene-to-Recent transition.



Main conclusions  This analysis constitutes a further demonstration of general and pervasive conservatism in ecological niche characteristics over moderate periods of time despite profound changes in climate and environmental conditions. As such, our results reinforce the application of ecological niche modelling techniques to the reconstruction of Pleistocene biodiversity distribution patterns, and to project the future potential distribution range of species in the face of global-scale climatic changes.

Andrew Townsend Peterson

Papers

Ecological Niches and Geographic Distributions

Conservatism of Ecological Niches in Evolutionary Time

Use of niche models in invasive species risk assessments.

No silver bullets in correlative ecological niche modelling: insights from testing among many potential algorithms for niche estimation

Conservatism of ecological niche characteristics in North American plant species over the Pleistocene-to-Recent transition