Incorporating time into the traditional correlational distributional modelling framework: A proof‐of‐concept using the Wood Thrush Hylocichla mustelina

Rethinking ecological niches and geographic distributions in face of pervasive human influence in the Anthropocene

Species are distributed in predictable ways in geographic spaces. The three principal factors that determine geographic distributions of species are biotic interactions (B), abiotic conditions (A), and dispersal ability or mobility (M). A species is expected to be present in areas that are accessible to it and that contain suitable sets of abiotic and biotic conditions for it to persist. A species' probability of presence can be quantified as a combination of responses to B, A, and M via ecological niche modeling (ENM; also frequently referred to as species distribution modeling or SDM). This analytical approach has been used broadly in ecology and biogeography, as well as in conservation planning and decision-making, but commonly in the context of 'natural' settings. However, it is increasingly recognized that human impacts, including changes in climate, land cover, and ecosystem function, greatly influence species' geographic ranges. In this light, historical distinctions between natural and anthropogenic factors have become blurred, and a coupled human-natural landscape is recognized as the new norm. Therefore, B, A, and M (BAM) factors need to be reconsidered to understand and quantify species' distributions in a world with a pervasive signature of human impacts. Here, we present a framework, termed human-influenced BAM (Hi-BAM, for distributional ecology that (i) conceptualizes human impacts in the form of six drivers, and (ii) synthesizes previous studies to show how each driver modifies the natural BAM and species' distributions. Given the importance and prevalence of human impacts on species distributions globally, we also discuss implications of this framework for ENM/SDM methods, and explore strategies by which to incorporate increasing human impacts in the methodology. Human impacts are redefining biogeographic patterns; as such, future studies should incorporate signals of human impacts integrally in modeling and forecasting species' distributions.

Evaluating niche changes during invasion with seasonal models in Capsella bursa-pastoris

PREMISE

Researchers often use ecological niche models to predict where species might establish and persist under future or novel climate conditions. However, these predictive methods assume species have stable niches across time and space. Furthermore, ignoring the time of occurrence data can obscure important information about species reproduction and ultimately fitness. Here, we assess compare ecological niche models generated from full-year averages to seasonal models.

METHODS

In this study, we generate full-year and monthly ecological niche models for Capsella bursa-pastoris in Europe and North America to see if we can detect changes in the seasonal niche of the species after long-distance dispersal.

RESULTS

We find full-year ecological niche models have low transferability across continents and there are continental differences in the climate conditions that influence the distribution of C. bursa-pastoris. Monthly models have greater predictive accuracy than full-year models in cooler seasons, but no monthly models can predict North American summer occurrences very well.

CONCLUSIONS

The relative predictive ability of European monthly models compared to North American monthly models suggests a change in the seasonal timing between the native range to the non-native range. These results highlight the utility of ecological niche models at finer temporal scales in predicting species distributions and unmasking subtle patterns of evolution.

Phenology dictates the impact of climate change on geographic distributions of six co-occurring North American grasshoppers

Throughout the last century, climate change has altered the geographic distributions of many species. Insects, in particular, vary in their ability to track changing climates, and it is likely that phenology is an important determinant of how well insects can either expand or shift their geographic distributions in response to climate change. Grasshoppers are an ideal group to test the hypothesis that phenology correlates with range expansion, given that co-occurring confamilial, and even congeneric, species can differ in phenology. Here, I tested the hypothesis that early- and late-season species should possess different range expansion potentials, as estimated by habitat suitability from ecological niche models. I used nine different modeling techniques to estimate habitat suitability of six grasshopper species of varying phenology under two climate scenarios for the year 2050. My results suggest that, of the six species examined here, early-season species were more sensitive to climate change than late-season species. The three early-season species examined here might shift northward during the spring, while the modeled geographic distributions of the three late-season species were generally constant under climate change, likely because they were pre-adapted to hot and dry conditions. Phenology might therefore be a good predictor of how insect distributions might change in the future, but this hypothesis remains to be tested at a broader scale.