Are we overestimating the niche? Removing marginal localities helps ecological niche models detect environmental barriers

Sufficient versus optimal climatic stability during the Late Quaternary: using environmental quality to guide phylogeographic inferences in a Neotropical montane system

Quaternary climatic oscillations affected species distributions worldwide, creating cycles of connectivity and isolation that impacted population demography and promoted lineage divergence. These effects have been well studied in temperate regions. Taxa inhabiting mesic montane habitats in tropical ecosystems show high levels of endemism and diversification in the distinct mountain ranges they inhabit; such a pattern has commonly been ascribed to past climatic oscillations, but few phylogeographic studies have tested this hypothesis. Here, we combine ecological niche models of species distributions with molecular data to study phylogeographic patterns in two rodents endemic to the highlands of Costa Rica and western Panama (Reithrodontomys creper and Nephelomys devius). In so doing, we apply a novel approach that incorporates a basic ecological principle: the expected positive relationship between environmental suitability and population abundance. Specifically, we use niche models to predict potential patterns of population connectivity and stability of different suitability levels during climatic extremes of the last glacial–interglacial cycle; we then test these predictions with population genetic analyses of a mitochondrial and a nuclear marker. The detailed predictions arising from the different levels of suitability were moderately to highly congruent with the molecular data depending on the species. Overall, results suggest that in these tropical montane ecosystems, cycles of population connectivity and isolation followed a pattern opposite to that typically described for temperate or lowland tropical ecosystems: namely, higher connectivity during the colder glacials, with isolation in montane refugia during the interglacials, including today. Nevertheless, the individualistic patterns for each species indicate a potentially wide gamut of phylogeographic histories reflecting particularities of their niches. Taken together, this study illustrates how phylogeographic inferences may benefit from niche model outputs that provide more detailed predictions of connectivity and finer characterizations of potential refugia through time.

Collinearity in ecological niche modeling: Confusions and challenges

Ecological niche models are widely used in ecology and biogeography. Maxent is one of the most frequently used niche modeling tools, and many studies have aimed to optimize its performance. However, scholars have conflicting views on the treatment of predictor collinearity in Maxent modeling. Despite this lack of consensus, quantitative examinations of the effects of collinearity on Maxent modeling, especially in model transfer scenarios, are lacking. To address this knowledge gap, here we quantify the effects of collinearity under different scenarios of Maxent model training and projection. We separately examine the effects of predictor collinearity, collinearity shifts between training and testing data, and environmental novelty on model performance. We demonstrate that excluding highly correlated predictor variables does not significantly influence model performance. However, we find that collinearity shift and environmental novelty have significant negative effects on the performance of model transfer. We thus conclude that (a) Maxent is robust to predictor collinearity in model training; (b) the strategy of excluding highly correlated variables has little impact because Maxent accounts for redundant variables; and (c) collinearity shift and environmental novelty can negatively affect Maxent model transferability. We therefore recommend to quantify and report collinearity shift and environmental novelty to better infer model accuracy when models are spatially and/or temporally transferred.

Can Niche Modeling and Geometric Morphometrics Document Competitive Exclusion in a Pair of Subterranean Rodents (Genus Ctenomys) with Tiny Parapatric Distributions?

Species with similar ecological requirements coexisting in the same geographic region are prone to competitively exclude each other. Alternatively, they may coexist if character displacement acts to change the niche requirements of one or both species. We used two methodological approaches (ecological niche modeling [ENM] and geometric morphometrics) to test two hypotheses: given their behavioral, morphological, and ecological similarities, one species competitively excludes the other; and, character displacement enables their coexistence at two sites in which the species are known to occur in sympatry. The results from the ENM-based approach did not provide evidence for competitive exclusion; however, the morphometric analyses documented displacement in size of C. minutus. This result, suggests that C. minutus might exclude C. flamarioni from areas with softer soils and higher food availability. We stress the importance of using multiple methodological approaches when testing prediction of competitive exclusion. However, both methods had limited explanatory power given that the focal species possess truly peculiar distributions, being largely parapatric and restricted to narrow, small geographic areas with a strange distribution and there is a need to search for additional methods. We discuss the idiosyncrasy of the ENM-based approach when applied to organisms with subterranean habits.

Introducing BioSARN - an ecological niche model refinement tool

Environmental niche modeling outputs a biological species' potential distribution. Further work is needed to arrive at a species' realized distribution. The Biological Species Approximate Realized Niche (BioSARN) application provides the ecological modeler with a toolset to refine Environmental niche models (ENMs). These tools include soil and land class filtering, niche area quantification and novelties like enhanced temporal corridor definition, and output to a high spatial resolution land class model. BioSARN is exemplified with a study on Fraser fir, a tree species with strong land class and edaphic correlations. Soil and land class filtering caused the potential distribution area to decline 17%. Enhanced temporal corridor definition permitted distinction of current, continuing, and future niches, and thus niche change and movement. Tile quantification analysis provided further corroboration of these trends. BioSARN does not substitute other established ENM methods. Rather, it allows the experimenter to work with their preferred ENM, refining it using their knowledge and experience. Output from lower spatial resolution ENMs to a high spatial resolution land class model is a pseudo high‐resolution result. Still, it maybe the best that can be achieved until wide range high spatial resolution environmental data and accurate high precision species occurrence data become generally available.