Species Distribution and Climate Change

Maximum entropy modeling of species geographic distributions

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

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.

Model selection in ecology and evolution

Niche Conservatism: Integrating Evolution, Ecology, and Conservation Biology

▪ Abstract Niche conservatism is the tendency of species to retain ancestral ecological characteristics. In the recent literature, a debate has emerged as to whether niches are conserved. We suggest that simply testing whether niches are conserved is not by itself particularly helpful or interesting and that a more useful focus is on the patterns that niche conservatism may (or may not) create. We focus specifically on how niche conservatism in climatic tolerances may limit geographic range expansion and how this one type of niche conservatism may be important in (a) allopatric speciation, (b) historical biogeography, (c) patterns of species richness, (d) community structure, (e) the spread of invasive, human-introduced species, (f) responses of species to global climate change, and (g) human history, from 13,000 years ago to the present. We describe how these effects of niche conservatism can be examined with new tools for ecological niche modeling.

The merging of community ecology and phylogenetic biology

The increasing availability of phylogenetic data, computing power and informatics tools has facilitated a rapid expansion of studies that apply phylogenetic data and methods to community ecology. Several key areas are reviewed in which phylogenetic information helps to resolve long-standing controversies in community ecology, challenges previous assumptions, and opens new areas of investigation. In particular, studies in phylogenetic community ecology have helped to reveal the multitude of processes driving community assembly and have demonstrated the importance of evolution in the assembly process. Phylogenetic approaches have also increased understanding of the consequences of community interactions for speciation, adaptation and extinction. Finally, phylogenetic community structure and composition holds promise for predicting ecosystem processes and impacts of global change. Major challenges to advancing these areas remain. In particular, determining the extent to which ecologically relevant traits are phylogenetically conserved or convergent, and over what temporal scale, is critical to understanding the causes of community phylogenetic structure and its evolutionary and ecosystem consequences. Harnessing phylogenetic information to understand and forecast changes in diversity and dynamics of communities is a critical step in managing and restoring the Earth's biota in a time of rapid global change.

Fusion or Failure? The Future of Conservation Biology

How wide is the “knowing-doing” gap in invasion biology?

Invasion biology and conservation biology: time to join forces to explore the links between species traits and extinction risk and invasiveness

Expansion and decline of species are natural phenomena (Levin, 2000). However, owing to the increasing infl uence of humans worldwide, the processes driving expansion and decline have speeded up dramatically. Hence, we have the current biodiversity crisis. Humanmediated forces are making some species rarer (ie, driving them towards extinction) while at the same time making some species expand their ranges (‘invasive’ sensu Richardson et al., 2000). Undisputedly, the immediate causes for extinction of native species and invasiveness of aliens are extrinsic factors, such as habitat destruction and climate change. However, the ultimate causes have to be ecological and life-history characteristics of species (Kotiaho et al., 2005). Therefore, important research directions in conservation biology and invasion biology are the analyses of species traits associated with rarity (Murray et al., 2002) and invasiveness (Pyšek and Richardson, 2007), respectively. The first are important for prioritizing conservation efforts, and the second are important for prioritizing eradication efforts and the development of screening protocols of potential invasiveness of species considered for introduction to other regions. Unravelling the links between species traits and extrinsic factors is highly complex, particularly because assessment of the causes of rarity and invasiveness relies mainly on retrospective analyses since large-scale controlled experiments are often not feasible (Richardson et al., 2004). However, with the increasing availability of large, widely accessible databases and analytical approaches (eg, Wilson et al., 2007), it is becoming easier to test which traits are associated with rarity and invasiveness, and under which conditions.