Abstract
When species distribution models (SDMs) are used to predict how a species will respond to environmental change, an important assumption is that the environmental niche of the species is conserved over evolutionary time-scales. Empirical studies conducted at ecological time-scales, however, demonstrate that the niche of some species can vary in response to environmental change. We use habitat and locality data of five species of stream fishes collected across seasons to examine the effects of niche variability on the accuracy of projections from Maxent, a popular SDM. We then compare these predictions to those from an alternate method of creating SDM projections in which a transformation of the environmental data to similar scales is applied. The niche of each species varied to some degree in response to seasonal variation in environmental variables, with most species shifting habitat use in response to changes in canopy cover or flow rate. SDMs constructed from the original environmental data accurately predicted the occurrences of one species across all seasons and a subset of seasons for two other species. A similar result was found for SDMs constructed from the transformed environmental data. However, the transformed SDMs produced better models in ten of the 14 total SDMs, as judged by ratios of mean probability values at known presences to mean probability values at all other locations. Niche variability should be an important consideration when using SDMs to predict future distributions of species because of its prevalence among natural populations. The framework we present here may potentially improve these predictions by accounting for such variability.
Highlights
Recent advances in the application of geographic information systems (GIS) analytical techniques have offered a powerful opportunity to predict species distributions in the context of spatially and temporally variable habitats [1,2]
C. anomalum significantly altered its niche in response to changes in low canopy cover, and L. megalotis significantly altered its niche in response to changes in total canopy cover (Fig. 2)
Niche conservatism as applied in GIS-based studies is commonly viewed as an evolutionary phenomenon [9]
Summary
Recent advances in the application of geographic information systems (GIS) analytical techniques have offered a powerful opportunity to predict species distributions in the context of spatially and temporally variable habitats [1,2]. Suitable areas can be extrapolated onto other geographic regions or into the future using forecasted environmental conditions to predict a species’ distribution [3,4] This method has proven useful for conservation planning by predicting the occurrence of rare species [5], responses of species to global climate change [6], and the impacts of invasive species [7]. On ecological timescales the niche of some species has been shown to be quite flexible, such as for species colonizing new geographic areas [10], experiencing annual variation in climatic variables [11], or responding to seasonal variation [12] Such niche variability has presented a challenge to the ability of correlative SDMs to predict changes in species’ distributions in response to environmental change, to the extent that the failure of predictions from SDMs has been used as evidence for niche shifts [10]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
