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

Abstract

Aim: To propose a species distribution modelling framework and its companion "iSDM" R package for predicting the potential and realized distributions of invasive species within the invaded range.Location: Northern France. Methods:The non-equilibrium distribution of invasive species with the environment within the invaded range affects the environmental representativeness of species presenceabsence data collected from the field and introduces uncertainty in observed absences as these may either reflect unsuitable sites or be incidental. To address these issues, we here propose an environmental systematic sampling design to collect presence-absence data from the field and a probability index to sort and subsequently separate environmental absences (EAs: reflecting environmentally unsuitable sites) from dispersal-limited absences (DLAs: reflecting sites out of dispersal reach). We first conducted a comprehensive test based on a virtual species to evaluate the performance of our framework. Then, we applied it on different life stages of a non-native tree species (Prunus serotina Ehrh.) invasive in Europe. Results:Regarding the potential distribution, we found higher model performances for both the virtual species (true skill statistics (TSS) > 0.75) and P. serotina (TSS ≥ 0.68) after carefully selecting absences with a low probability to be DLAs compared with classical models that incorporate both EAs and DLAs (e.g. TSS = 0.11 for P. serotina with 80% of DLAs). On the contrary, both EAs and DLAs as well as dispersal-related covariates were needed to capture the realized distribution of both the virtual species and P. serotina. Main Conclusions:Our framework helps overcoming the conceptual and methodological limitations of the disequilibrium in species' distribution models inherent to invasive species and enables managers to robustly estimate both the realized and potential distributions of invasive species. Although more relevant for modelling the distribution of non-native species, this framework can also be applied to native species. K E Y W O R D Salien species, biological invasions, dispersal limitations, potential niche, realized niche, species distribution modelling, virtual species

Modeling current and potential distributions of mammal species using presence‐only data: A case study on British deer

“…We would consider few British mammals to be more mobile than deer and so as an upper limit, the choice of 20 km as a distance for defining neighboring sightings is only likely to be too small for rare or poorly recorded species where the granularity of observations is low. This effect is seen in our results with the rarer invasive non-native deer species showing highest predictive accuracy at greater distances despite evidence to suggest at least some range over smaller areas than the better recorded native species (Chapman, Claydon, Claydon, Forde, & Harris, 1993) (Hattab et al, 2017). However, since Chinese water deer and muntjac both have warm temperate/subtropical origins, it is unlikely that environmental data from their native ranges will translate to the British landscape and it is perhaps most prudent to wait until such time as there are sufficient data for their invaded range.…”

“…For some species (Chinese water deer and muntjac), predictions are restricted, we assume, by a lack of exposure to certain environments as a result of their relatively recent introduction and their current limited distributions rather than deficient sampling. Where this is the case for species naturally occupying the same bioclimatic zone, it may be possible to consider supplementing data, and corresponding inference of environmental dependence, from other locations where the species is present (Hattab et al, ). However, since Chinese water deer and muntjac both have warm temperate/subtropical origins, it is unlikely that environmental data from their native ranges will translate to the British landscape and it is perhaps most prudent to wait until such time as there are sufficient data for their invaded range.…”

“…In this paper, we outline a general methodology based on a hierarchical Bayesian modelling framework (Latimer, Wu, Gelfand, & Silander, 2006) to estimate both the realized (current) and potential (future) distribution of terrestrial mammal species using opportunistic occurrence data accounting for both reporting bias (detectability) (van Strien, Swaay, & Termaat, 2013) and critically dispersal limited/ anthropogenic influences (Hattab et al, 2017). We assess the validity of this method considering an example case study focusing on British deer; for which good data are available both to fit models and to perform independent validation.…”

Testing methods in species distribution modelling using virtual species: what have we learnt and what are we missing?

“…Effects of dispersal patterns/constraints De Marco et al 2008, Saupe et al 2012, Thibaud et al 2014, Hattab et al 2017, De Marco and Nobrega 2018 • Predicting distributions from early stages of invasion is difficult because the species has not occupied all of its potential environmental space. At late stages of dispersal, considering dispersal constraints may become less important.…”

A landscape genetic analysis of important agricultural pest species in Tunisia: The whitefly Bemisia tabaci

“…tabaci are both relevant tasks for managing this plant pests. For instance, control and eradication efforts should focus on the current distribution while containment efforts should focus on the interface between the current and potential distributions [ 62 ]. Mapping the current distribution will require a better knowledge of host species and B .…”