Refining model estimates of potential species’ distributions to relevant accessible areas

Abstract

Dispersal is an important, yet overlooked phenomenon when studying species’ distributions using ecological niche models (ENMs). Here, we use species’ dispersal limits to evaluate and refine ENM estimates only to the areas accessible to the species within the study region and, thereby, enhance the model interpretations. First, we ran multiple ENMs to estimate the distribution of sea krait species in both marine and terrestrial environments. Second, we estimated dispersal of the sea kraits using a cost analysis approach. Finally, we outline a new approach that combines dispersal models and ENMs with the purpose of estimating the accessible range when projecting species’ distribution estimates outside the known species range. We found that only a small proportion of the area the ENMs were projected over was accessible to sea kraits. The majority of the suitable areas for sea kraits are within the accessible area. Outside the accessible area, there is only a very limited suitable area for sea kraits. Our results suggest that when dispersal is taken into account, sea kraits seem to occupy most of their suitable available niche and that they may be unable to colonize much of the area outside of their dispersal ranges. Using dispersal estimates to refine species’ distribution predictions is a useful tool for refining the area of focus when ENM results are interpreted. Estimating species’ dispersal also helps evaluate the ability of the models to predict the species’ distributions in areas that are not accessible to the species and, hence, the potential commission error represented by overprediction.

A dynamic theory of the area of distribution

“…We contend that to fully incorporate all factors, simulations must be performed. Many process‐oriented models exist in this field (Briscoe et al, 2019; Gherghel et al, 2020), and one could ask why yet another algorithm should be introduced. Whether our approach is preferable, on empirical grounds, to any of the many methods (Gherghel et al, 2020) that add movements to niche modelling requires a comparison well beyond the mainly theoretical aims of this work.…”

“…Many process‐oriented models exist in this field (Briscoe et al, 2019; Gherghel et al, 2020), and one could ask why yet another algorithm should be introduced. Whether our approach is preferable, on empirical grounds, to any of the many methods (Gherghel et al, 2020) that add movements to niche modelling requires a comparison well beyond the mainly theoretical aims of this work. One of our major theoretical results is that the informative matrix product cannot be ‘disentangled’.…”

“…We focus on only two parts of the BAM: niche and dispersal, both of crucial importance to determine areas of distribution (Gherghel et al, 2020). Including biotic interactions is a substantial challenge due to complex theory and a lack of data, and it may be the case that interactions are less important at coarse geographical scales (Peterson et al, 2011).…”

Biotic interactions vary across species' ranges and are likely conserved through geological time

“…For spadefoot toads, we used their specific distribution ranges (IUCN, 2016, accessed on April 20th, 2016) (Figure 1). Background ensures the relatively accessible area of the studied species is taken into account when species distribution models are built, as recommended by previous literature (Barve et al., 2011; Cooper & Soberon, 2018; Gherghel et al., 2019). These settings were also used in a previous paper on spadefoot toads' biogeography (Gherghel & Martin, 2020).…”

Eco-Cultural Niche Breadth and Overlap Within the Cucuteni–Trypillia Culture Groups During the Eneolithic

“…Broadly, ECNM has been adopted by archeologists (Banks, 2017) to explore the interactions between cultural and natural systems and to understand how ecological dynamics influenced the adaptations and movements of prehistoric populations (Banks et al, 2008;Banks et al, 2009). Therefore, even if the concept of ecological niche modeling (ENM) is derived from and commonly used in biodiversity (Soberón and Peterson, 2005;Bobrowski et al, 2018;Gherghel et al, 2019) and geographic ecology (Peterson et al, 2011), ECNM applies the same methodology to analyses of the archaeological record and prehistoric human culture using GIS. The usefulness of ECNM for archeology is that it offers the opportunity to quantitatively evaluate the hypothesis that a given adaptive system was influenced by ecological constraints or alternatively that the characteristics and geographic distribution may have been influenced more by non-ecological processes (e.g., cultural factors) (Banks et al, 2011).…”