On the use of climate covariates in aquatic species distribution models: are we at risk of throwing out the baby with the bath water?

Abstract

Species distribution models (SDMs) in river ecosystems can incorporate climate information by using air temperature and precipitation as surrogate measures of instream conditions or by using independent models of water temperature and hydrology to link climate to instream habitat. The latter approach is preferable but constrained by the logistical burden of developing water temperature and hydrology models. We therefore assessed whether regional scale, freshwater SDM predictions are fundamentally different when climate data versus instream temperature and hydrology are used as covariates. Maximum entropy (MaxEnt) SDMs were built for 15 freshwater fishes using one of two covariate sets: 1) air temperature and precipitation (climate variables) in combination with physical habitat variables; or 2) water temperature, hydrology (instream variables) and physical habitat. Three procedures were then used to compare results from climate vs instream models. First, equivalence tests assessed average pairwise differences (site‐specific comparisons throughout each species’ range) among climate and instream models. Second, ‘congruence’ tests determined how often the same stream segments were assigned high habitat suitability by climate and instream models. Third, Schoener's D and Warren's I niche overlap statistics quantified range‐wide similarity in predicted habitat suitability from climate vs instream models. Equivalence tests revealed small, pairwise differences in habitat suitability between climate and instream models (mean pairwise differences in MaxEnt raw scores for all species < 3 × 10–4). Congruence tests showed a strong tendency for climate and instream models to predict high habitat suitability at the same stream segments (median congruence = 68%). D and I statistics reflected a high margin of overlap among climate and instream models (median D = 0.78, median I = 0.96). Overall, we found little support for the hypothesis that SDM predictions are fundamentally different when climate versus instream covariates are used to model fish species’ distributions at the scale of the Columbia Basin.

Current and projected future risks of freshwater fish invasions in China

“…However, the incorporation of fine-scale biological data into national assessments is not possible due to insufficient data. In addition, incorporating variables that represent instream conditions is recommended to calibrate SDMs for freshwater species, but recent research showed that predictions do not fundamentally differ for climate versus instream-based models (McGarvey et al 2018). Second, despite our efforts to remove any potential sampling biases through careful geographical and environmental filtering of the occurrence records, uneven spatial distribution of collection efforts may have truncated the full range of suitable areas, especially for species for which available data are few and opportunistic (Beck et al 2014).…”

“…The accelerating establishment and spread of nonnative species will undoubtedly continue to homogenize China's freshwater fish fauna and further accentuate the loss of distinctiveness across communities in the future (Liu et al 2017a). In addition, incorporating variables that represent instream conditions is recommended to calibrate SDMs for freshwater species, but recent research showed that predictions do not fundamentally differ for climate versus instream-based models (McGarvey et al 2018). This, in turn, could facilitate the establishment of other invaders and exacerbate the magnitude of invasion-related impacts ('invasional meltdown'; sensu Simberloff 2006).…”

Predictor complexity and feature selection affect Maxent model transferability: Evidence from global freshwater invasive species

“…The use of such variables for modelling freshwater species may, however, be counterintuitive, given that their distributions are typically limited by instream conditions (e.g., hydrology, water temperature). While high‐resolution instream data are currently unavailable on a global scale, there has been evidence (e.g., McGarvey et al., 2018) demonstrating that climatic variables, in conjunction with physical habitat data, can serve as reasonable surrogates for instream variables, given that these distal variables are often causally linked to proximal drivers of freshwater species distributions (e.g., air temperature directly affecting water temperature; altitude and slope directly influencing channel morphology) (Zeng et al., 2016).…”

Inter-basin water transfers and the expansion of aquatic invasive species

“…In brief, SDMs correlate the occurrence of a given species with the environmental conditions, usually climatic, of the sites it inhabits in order to locate areas that are most susceptible to invasion (Guisan and Thuiller 2005). While direct indicators of water conditions (water temperature and river flow) are preferable over indirect climate surrogates (air temperature and precipitation), multiple studies have demonstrated the prominent role of climate over geological (Quinn et al 2014), hydrological (McGarvey et al 2017) or socio-economic aspects (Gallardo and Aldridge 2013a) on the distribution of aquatic organisms at the global scale. Climate surrogates are especially useful when modelling invasive species because they allow using information from the entire global range of distribution of invasive species (native and invasive).…”