Predicting Species and Community Responses to Global Change Using Structured Expert Judgement: an Australian Mountain Ecosystems Case Study
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Received: 14 March 2021 | Accepted: 24 May 2021 DOI: 10.1111/gcb.15750 PRIMARY RESEARCH ARTICLE Predicting species and community responses to global change using structured expert judgement: An Australian mountain ecosystems case study James S. Camac1,2 | Kate D. L. Umbers3,4 | John W. Morgan2,5 | Sonya R. Geange6 | Anca Hanea1 | Rachel A. Slatyer6 | Keith L. McDougall7 | Susanna E. Venn8 | Peter A. Vesk9 | Ary A. Hoffmann10 | Adrienne B. Nicotra6 1Centre of Excellence for Biosecurity Risk Analysis, School of BioSciences, The University of Melbourne, Parkville, Vic., Australia 2Research Centre for Applied Alpine Ecology, La Trobe University, Bundoora, Vic., Australia 3School of Science, Western Sydney University, Penrith, NSW, Australia 4Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia 5Department of Ecology, Environment and Evolution, La Trobe University, Bundoora, Vic., Australia 6Research School of Biology, Australian National University, Acton, ACT, Australia 7NSW Department of Planning, Industry and Environment, Queanbeyan, NSW, Australia 8Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood, Vic., Australia 9School of BioSciences, The University of Melbourne, Parkville, Vic., Australia 10Bio21 Institute, School of BioSciences, The University of Melbourne, Parkville, Vic., Australia Correspondence James S. Camac, Centre of Excellence Abstract for Biosecurity Risk Analysis, School of Conservation managers are under increasing pressure to make decisions about the al- BioSciences, The University of Melbourne, Parkville 3010, Vic., Australia. location of finite resources to protect biodiversity under a changing climate. However, Email: [email protected] the impacts of climate and global change drivers on species are outpacing our capac- Funding information ity to collect the empirical data necessary to inform these decisions. This is particu- Centre of Excellence for Biosecurity larly the case in the Australian Alps which have already undergone recent changes in Risk Analysis National Climate Change Adaptation Research Facility; Centre for climate and experienced more frequent large- scale bushfires. In lieu of empirical data, Biodiversity Analysis, ANU; Department we use a structured expert elicitation method (the IDEA protocol) to estimate the of Industry Conference Support Program change in abundance and distribution of nine vegetation groups and 89 Australian al- pine and subalpine species by the year 2050. Experts predicted that most alpine veg- etation communities would decline in extent by 2050; only woodlands and heathlands are predicted to increase in extent. Predicted species- level responses for alpine plants and animals were highly variable and uncertain. In general, alpine plants spanned the range of possible responses, with some expected to increase, decrease or not change in cover. By contrast, almost all animal species are predicted to decline or not change in abundance or elevation range; more species with water- centric life- cycles are ex- pected to decline in abundance than other species. While long- term ecological data will always be the gold standard for informing the future of biodiversity, the method This is an open access article under the terms of the Creat ive Commo ns Attri bution-NonCo mmercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. © 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd. 4420 | wileyonlinelibrary.com/journal/gcb Glob Change Biol. 2021;27:4420–4434. CAMAC ET AL. | 4421 and outcomes outlined here provide a pragmatic and coherent basis upon which to start informing conservation policy and management in the face of rapid change and a paucity of data. KEYWORDS adaptive capacity, alpine, biodiversity conservation, climate change, expert elicitation, exposure risk 1 | INTRODUCTION taxonomic groups have been based primarily on species correlative distribution models (e.g. La Sorte & Jetz, 2010; Lawler et al., 2009; Alpine, subalpine and montane species are predicted to be neg- Thomas et al., 2004). More sophisticated models incorporating spe- atively impacted by climate change. For the most part, this is be- cies' physiological, ecological and evolutionary characteristics will cause the climate envelope of many mountain species is expected to likely facilitate better identification of the species most at risk from shrink and, in some regions, disappear entirely as a consequence of climate change (Briscoe et al., 2019). However, multiple challenges increased global temperatures (Freeman et al., 2018; Halloy & Mark, exist when attempting to build and use such process- based models 2003; La Sorte & Jetz, 2010). While range contractions have already (Briscoe et al., 2019). First, the data necessary to parameterize these been observed in some mountain plants (Grabherr et al., 1994; models are rarely available for most species. Second, such models Lenoir et al., 2008; Steinbauer et al., 2020) and animals (Freeman rarely incorporate indirect climate change impacts on other abiotic et al., 2018; Wilson et al., 2005), not all species are responding to (e.g. disturbance regimes) and biotic (e.g. interspecific competition, climate change in the same way (Gibson- Reinemer & Rahel, 2015; predation) stresses known to affect population ecology, physiology Lenoir et al., 2010; Tingley et al., 2012). What remains unclear is and ultimately species' persistence (Fordham et al., 2012; Geyer the capacity of mountain species to adapt (Hargreaves et al., 2014; et al., 2011; Guisan & Thuiller, 2005). Lastly, the technical skill and Louthan et al., 2015; Michalet et al., 2014; Normand et al., 2014), time required to build and interpret these models restrict their use and the characteristics that allow species to persist in the face of a to specialists (Briscoe et al., 2019). Given that the rate of climate changing climate (Foden et al., 2018; Fordham et al., 2012). change impacts has already outpaced our capacity to collect the To understand the complexities and uncertainties of species required data and build necessary models to assess species empir- responses to climate change, there have been several attempts to ically, it is important to utilize alternative methods that make use quantify adaptive capacity (Foden et al., 2013; Gallagher et al., 2019; of existing expertise across taxa to estimate adaptive capacity and Ofori et al., 2017). Adaptive capacity describes the ability of systems identify conservation priorities (Granger Morgan et al., 2001). and organisms to persist and adjust to threats, to take advantage of The need to predict how species will respond to climate change is opportunities, and/or to respond to change (IPCC, 2014; Millenium particularly pertinent to the Australian alpine ecosystem which has a Ecosystem Assessment, 2005). Adaptive capacity confers resilience high level of endemism and a restricted geographical range (Venn et al., to perturbation, allowing ecological systems to reconfigure them- 2017). Since 1979, mean spring temperatures in the Australian Alps selves with change (Holling, 1973). In the context of alpine biota in have risen by approximately 0.4°C and annual precipitation has fallen Australia, adaptive capacity is the ability of species to maintain their by 6% (Wahren et al., 2013), with a consequent decline in snow pack often limited geographical distributions and population abundance depth (Sanchez- Bayo & Green, 2013). Snow cover in Australia is now at when the climate and other factors are altered. While the under- its lowest in the past 2000 years (McGowan et al., 2018). These climatic lying factors determining adaptive capacity encompass genetic and changes correlate with changes in floristic structure, abundance and epigenetic variation, life- history traits and phenotypic plasticity diversity (Camac et al., 2015; Wahren et al., 2013) and increases in fire (Dawson et al., 2011; Ofori et al., 2017), little is known about which frequency and severity (Camac et al., 2017; Zylstra, 2018). Changes are taxa have high adaptive capacity, how to quantify it, how it varies expected to threaten the many locally adapted and endemic species, within and across related species, or how to manage populations in with cascading effects on biodiversity and ecosystem services such as order to maximize it. As a consequence, data required to advise on carbon storage and water yield (Williams et al., 2014). the adaptive capacity of species are often lacking. Here, we quantify the future abundance of Australian alpine species Nonetheless, conservation practitioners and land managers are using the IDEA protocol (Investigate, Discuss, Estimate and Aggregate; under increasing pressure to make decisions about the allocation of Hemming et al., 2018). This structured elicitation protocol provides a finite resources used to conserve biodiversity under climate change. robust framework to estimate risk when data are either inadequate Decisions are typically based on vulnerability assessments that in- or lacking entirely (Hemming et al., 2018). Many of the elements es- corporate exposure risk, species sensitivity and adaptive capacity sential to mitigating against common cognitive group and individual (Foden et al., 2013, 2018; Ofori et al., 2017). Until now, assessments biases are prescribed in the IDEA protocol (Hemming et al., 2018). For of potential climate