Scaling range sizes to threats for robust predictions of risks to biodiversity

Abstract

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range-size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red-list assessments for decades, appropriate spatial scales of AOO for predicting risks of species' extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale-sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1-1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer-scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid-measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape-scale threats to species and ecosystems.

Range area matters, and so does spatial configuration: predicting conservation status in vertebrates

“…However, it has been largely overlooked in comparative studies of species' extinction risk (Cardillo et al 2008, Arbetman et al 2017. As previously reported, the best descriptor of conservation status is the area of the range, likely due to its direct association with total population size: all else been equal, larger ranges should have lower risks (Bielby et al 2008, Harris and Pimm 2008, Davidson et al 2009, Giam et al 2011, Joppa et al 2016, Keith et al 2018). In addition, the better conservation status of large range areas could be associated to a buffer effect against stochastic impacts.…”

“…To overcome this limitation, many studies have searched for correlates of conservation status, including morphological, ecological, life history and behavioral species' traits (Purvis et al 2000, Cardillo et al 2008, Davidson et al 2009, Fritz et al 2009, González-Suárez and Revilla 2013). Among these correlates, the best/more common statistical predictor of status for different taxa, is range area which is a measure of the spatial extent of the geographical space a species occupies (Keith et al 2018). Everything else being equal, larger range areas can host more individuals, and thus, are associated with lower risk of extinction (Gaston 1994, Cardillo et al 2005, Gaston and Fuller 2009, Orzechowski et al 2015, Runge et al 2015.…”

“…There are several aspects that determine the risk of extinction of a species. The IUCN (IUCN 2012) considers the following criteria to assess the risk of extinction of a given species: the number of individuals, the generation length, the population trend and the range size and its spatial aggregation (IUCN 2012, Joppa et al 2016, Murray et al 2017, Keith et al 2018. While a useful measure of conservation status, a species range size can be difficult to measure (Gaston 1991, 2003, Gaston and Fuller 2009).…”

“…Arguably, ignoring variation in the spatial configuration of species' ranges could lead to overor under-estimation of conservation status and thus, less effective use of conservation resources. Previous studies have assessed the effects of different spatial metrics on conservation status (Cardillo et al 2008, Joppa et al 2016, Murray et al 2017, Keith et al 2018), but we lack a comprehensive evaluation covering different taxa and testing multiple descriptors.…”

Least concern to endangered: Applying climate change projections profoundly influences the extinction risk assessment for wild Arabica coffee

“…There was considerable variability for the two emission scenarios A2 and A1B, with a −30% to + 30% difference in reduction/increase in the niche, between the two. Much of this variation was in EOO, which is not surprising as the EOO metric can be highly variable and sensitive to outlying occurrences (Hartley & Kunin, ; Keith, Akçakaya, & Murray, ; Keith, Auld, Ooi, & Mackenzie, ). The future projections (IUCN sub criterion A3), with emission scenario A2, consistently reports higher loses in AOO and the two population metrics, as expected.…”