Non‐equilibrium in plant distribution models – only an issue for introduced or dispersal limited species?

Abstract

Species distribution models rely on the assumption that species' distributions are at equilibrium with environmental conditions within a region – i.e. they occur in all suitable habitats. If this assumption holds, species occurrence should be predictable from measures of the environment. Introduced species may be poor candidates for distribution models due to their presumed lack of equilibrium within the landscapes they occupy, although predicting their potential distributions is often of critical importance to natural resource managers. We determined if the accuracy of species distribution models differed between 17 native and 17 introduced riparian plant species in the western United States. We also assessed if model accuracy was associated with both environmental and biological factors that can influence dispersal. We used Random Forests to model species distributions and linear regression to determine if model accuracy was associated with dispersal‐related traits. Model accuracy for introduced species was higher than that for native species. Dispersal‐related traits did not affect model accuracy or improvement, though two other traits, family affiliation and rarity on the landscape, did have an effect. Distance‐based measures of dispersal potential improved model fit equally for both native and introduced species and for species with a variety of dispersal traits, suggesting that the importance of regional propagule pressure is relatively constant across species with different dispersal opportunities. Several lines of future questioning are suggested by our results, including why introduced species may in some cases produce more accurate distribution models than native species and how species dispersal traits relate to distribution model accuracy at different spatial scales.

Data‐centric species distribution modeling: Impacts of modeler decisions in a case study of invasive European frog‐bit

“…Critical evaluations of invasive species distribution modeling have noted limitations that arise from non‐equilibrium and range shifts when species move into an area they are not native to, which leads to a smaller realized distribution compared to the species' potential distribution (Václavík and Meentemeyer, 2012 ; Pili et al, 2020 ; Cho et al, 2022 ). These limitations may be more relevant for but are not exclusive to invasive species, nor do they necessarily reduce the performance capacity of invasive species models compared to native species models (Menuz et al, 2015 ). Given the potential for invasive species to significantly harm ecosystems, SDMs are still a useful, widely accepted tool for assessing current distributions (Dutra Silva et al, 2021 ; Cho et al, 2022 ).…”

“…We addressed this by avoiding extrapolation and focused on training, testing, and predicting onto the same study region. The predictive capacity of invasive SDMs can be improved by using anthropogenic explanatory variables in addition to climate variables (Beans et al, 2012 ; Rodríguez‐Rey et al, 2019 ) and incorporating measures of dispersal pressure (Menuz et al, 2015 ). Population density and distance from the nearest boat launch fulfilled these roles in our models.…”

A unified framework to model the potential and realized distributions of invasive species within the invaded range

“…We assume that using dispersal‐related covariates in models of the realized distribution but not in models of the potential distribution may explain this pattern and thus suggests source–sink dynamics (Pulliam, ). Noteworthy, our unified framework can also be applied to native species, especially endemics and specialist species, and could yield more efficient results given that the disequilibrium between the realized and the potential distributions is not an issue of specific concern for introduced species but is of far more general concern for all species (Menuz et al., ).…”

“…To produce models reflecting the realized distribution of the invasion, we propose to use all available absences, both DLAs and EAs, as input data (Figure b) and to also incorporate into the models additional predictor variables describing dispersal‐related measures (Meentemeyer, Anacker, Mark, & Rizzo, ; Menuz, Kettenring, Hawkins, & Cutler, ). Meentemeyer et al.…”

Improving Species Distribution Modelling of freshwater invasive species for management applications

“…Human-related factors play indeed a fundamental role in the introduction and dispersal of invasive species [12, 13], and accordingly, consideration of human mediated dispersion appears essential for improving the explanatory and predictive accuracy of models [14]. Existing SDMs studies have incorporated variables such as human population density or presence of roads [15] to account for the effect of human-mediated dispersal, but more detailed human-related variables are required to account for propagule pressure (e.g.…”