Moving beyond presence and absence when examining changes in species distributions

Abstract

Species distributions are often simplified to binary representations of the ranges where they are present and absent. It is then common to look for changes in these ranges as indicators of the effects of climate change, the expansion or control of invasive species or the impact of human land-use changes. We argue that there are inherent problems with this approach, and more emphasis should be placed on species relative abundance rather than just presence. The sampling effort required to be confident of absence is often impractical to achieve, and estimates of species range changes based on survey data are therefore inherently sensitive to sampling intensity. Species niches estimated using presence-absence or presence-only models are broader than those for abundance and may exaggerate the viability of small marginal sink populations. We demonstrate that it is possible to transform models of predicted probability of presence to expected abundance if the sampling intensity is known. Using case studies of Antarctic mosses and temperate rain forest trees, we demonstrate additional insights into biotic change that can be gained using this method. While species becoming locally extinct or colonising new areas are extreme and obviously important impacts of global environmental change, changes in abundance could still signal important changes in biological systems and be an early warning indicator of larger future changes.

Rapid shifts in distribution and high‐latitude persistence of oceanographic habitat revealed using citizen science data from a climate change hotspot

“…Quantifying shifts in species range boundaries is an important priority for species redistribution science (Bonebrake et al., ), yet difficulty identifying ranges edges from observational data make distinguishing shifts problematic (Ashcroft et al., ). For example, range boundaries determined directly from occurrence data are sensitive to sampling intensity (Brown et al., ), and variation in sampling effort through time can lead to incorrectly inferring range edge shifts (Bates et al., ; Hassall & Thompson, ).…”

“…Mapped indices of habitat suitability have previously been used to identify species core habitats (Hill, Tobin, Reside, Pepperell, & Bridge, ), but are rarely used to identify shifts in the range boundaries of marine species (but see Robinson, Gledhill, et al., ). Combining spatial predictions of species’ probability of occurrence from SDMs with sampling effort information has recently proved useful for identifying range boundaries for terrestrial species based on minimum relative abundance values (Ashcroft et al., ). When sampling effort is unknown, independent species occurrence data may be compared with spatial predictions from SDMs to define range boundaries or habitat edges in terms of a threshold probability of occurrence or a minimum habitat suitability value (Champion, Hobday, Zhang, Pecl, & Tracey, ).…”

Habitat suitability estimated by niche models is largely unrelated to species abundance

“…This measure provides an estimate of variation explained between abundance and suitability. Lastly, previous studies have suggested that abundance–suitability relationships may be difficult to detect if variance in abundance estimates is too low (Ashcroft et al, ). That is, low variance and background noise in population abundance estimation could lead to type II errors.…”

Global drivers of population density in terrestrial vertebrates

“…This would be an important step forward to investigate macroecological patterns (McGill & Collins, ), such as species abundance distributions (McGill et al, ; Xiao, O'Dwyer, & White, ), biomass distribution (Hatton et al, ) or range size–abundance relationships (Gaston et al, ). Understanding the spatial patterns of abundance would allow conservation biologists to identify regions within species distributions where viability is low (Di Marco et al, ; Hilbers et al, ) and contribute to forecasting the responses of species to climate change, assuming space for time substitution as done in species distribution modelling (Ashcroft et al, ). Finally, estimates of species abundance over large geographical scales and for multiple species would permit description of the change in a number of biodiversity measures (e.g., heterogeneity indices, functional or phylogenetic diversity metrics weighted by species relative abundance) over time and space (Schipper et al, ).…”