Risks in extrapolating habitat preferences over the geographical range of threatened taxa: a case study of the quokka (Setonix brachyurus) in the southern forests of Western Australia

Abstract

Context Extrapolation of knowledge for threatened taxa between parts of their range that are disconnected and/or ecologically diverse can result in significant sources of error that undermine the effectiveness of conservation efforts. Aims We investigated the risks associated with extrapolation of ecological information across environmental gradients, using the quokka (Setonix brachyurus) as a case study. Information documented in the northern part of its range is currently used to manage this species across its range in south-western Australia. We examined the suitability of this approach by developing a habitat suitability model (HSM) for the quokka in the southernmost areas of its range and comparing this with existing knowledge for the species. Methods We surveyed 327 sites, representative of a range of ecotypes, for presence/absence of quokkas. Occupancy models were applied to select a subset of habitat variables that best predicted occupancy patterns. Key results Occupancy patterns were influenced by complex vegetation structure, low levels of woody debris and habitat patchiness. HSMs developed for quokkas in the north could not predict occupancy patterns in the south. Significant fragmentation of subpopulations was observed due to patchiness in the availability of suitable habitat. Conclusions The choice of predictor variables in HSMs that are not transferrable between regions could contribute to inappropriate management of habitat for quokkas and an increased risk of local extinctions. In addition, failure to consider processes that affect preferred habitat variables could contribute to the segregation of habitat patches and intervening distances that are too great for successful dispersal, immigration and recolonisation processes. Implications The extrapolation of HSMs between geographical areas can increase the risk of outcomes that are detrimental to the conservation of threatened species. Where such extrapolation is necessary, actions guided by the HSMs should be implemented in a management framework that can detect adverse effects, allow for inclusion of new ecological information and explicitly consider the limitations and assumptions of this approach. In addition, perceptions of habitat fragmentation need to include processes such as fire regimes and feral animals that affect the availability and connectivity of habitat and have the potential to adversely affect population viability.

The relevance of genetic structure in ecotype designation and conservation management

“…In various species, some populations show adaptations to their local environment, as illustrated by plants adapted to conditions of drought (Exposito‐Alonso et al, 2018 ), and fish (Kang et al, 2017 ) and mammals (Werhahn et al, 2018 ) adapted to life at high altitudes. For some species, habitat suitability models from parts of their range are thus not reliably transferrable to other regions, with important consequences for management (Bain et al, 2015 ; Denryter et al, 2017 ). Ecological knowledge of the species under study can provide perspectives on whether observed animal movements are common or atypical; for example, regarding sex‐biased dispersal (Støen et al, 2006 ), and the occurrence of seasonal movements in species that are usually nonmigratory (Musiani et al, 2007 ) or exhibit vagrant behaviour (Kutschera et al, 2016 ).…”

The effectiveness of opportunistic public reports versus professional data to estimate large carnivore distribution

“…However, despite its limitations, public‐gathered data have the potential to provide meaningful contributions in biodiversity science and policy‐making (Isaac et al, 2014; Tulloch et al, 2013), particularly when the questions are suitable for the data available (Guillera‐Arroita et al, 2015). Large public‐gathered data sets collected at broad spatiotemporal extents can lower the risk of false inferences (Bain et al, 2015) and could be integrated with other data sources to improve statistical inferences (e.g., Koshkina et al, 2017; Sun et al, 2019). Yet, it is important to note that citizen science and opportunistic reports can have low performance when estimating temporal patterns in abundance, due to observation, reporting, or geographical bias (Kamp et al, 2016; van Strien et al, 2013).…”

Responses of sympatric canids to human development revealed through citizen science

“…Despite its shortcomings, opportunistically gathered data have the potential to make meaningful contributions in biodiversity science and policy‐making (Isaac et al., 2014; Tulloch, Possingham, Joseph, Szabo, & Martin, 2013). Particularly, large citizen science data sets collected at broad spatiotemporal extents can reduce the amount of unsampled variation and lower the risk of false inferences (Bain, Wayne, & Bencini, 2015), and have potential to be integrated with other data sources to model population level dynamics and improve statistical inferences (Sun, Fuller, & Hurst, 2018). Data collected by citizen scientists can be equivalent in reliability and precision to that produced by traditional monitoring approaches (Rafiq et al., 2019).…”