Past, present and future refugia for Tasmania's palaeoendemic flora

Abstract

Aim Refugia under past climates have been important in structuring current patterns in diversity, while refugia under anthropogenic climate change will likely be important in retaining this diversity and shaping new patterns. However, few studies have examined the congruence of past, present and future refugia, or the spatiotemporal connectivity of these refugia. Our aim was to test the extent of overlap of refugia under Last Glacial Maximum (LGM), present (2015) and likely future climates (2100), for Tasmania's palaeoendemic flora. We then aimed to identify areas of high spatiotemporal refugia connectivity, as priority areas for conservation and management. Location Tasmania, Australia. Methods We developed and applied a new community‐level approach to identifying refugia, based on generalized dissimilarity modelling of compositional turnover and a set of reference sites with known biodiversity value. Using these projections of palaeoendemic plant refugia for past, present and future climates, we developed and applied a second approach to quantify the level of connectivity of these refugia over space and time. Results Although there was large overlap (85%) between current and future climates in the distribution of the highest value palaeoendemic refugia, the small congruence of these areas with refugia at the LGM resulted in only a small area (c. 9 km2) of persistent high value refugia over all three time periods. Despite this, our spatiotemporal analysis identified several areas of high connectivity in refugial environments for Tasmania's palaeoendemic flora over time. Main conclusions The community‐level approaches we demonstrate here to quantify refugia and their spatiotemporal connectivity have the potential to advance our understanding of biodiversity dynamics, particularly for taxonomic groups that are species‐rich, poorly studied or comprised of many rare species, where species‐level approaches are less suitable.

Validating climate‐change refugia: empirical bottom‐up approaches to support management actions

“…, ; Mokany et al . ). Nevertheless, elevated rates of extinction may be the exception more than the rule (Harrison and Noss ), which underscores the value of relying on biodiversity and endemism (as opposed to extinction) to validate refugia function, as well as using metrics such as response variables to monitor future conditions under an adaptive management approach.…”

Identifying in situ climate refugia for plant species

“…The potential for refugia to mitigate the effects of climate change and safeguard the persistence of biodiversity is an important consideration for climate change adaptation planning (Noss 2001, Taberlet and Cheddadi 2002, Ashcroft 2010, Game et al 2011, Groves et al 2012, Keppel et al 2015, Maher et al 2017, Mokany et al 2017. By conserving climate refugia, ecological and evolutionary factors are captured, facilitating population persistence and thereby promoting conservation of biodiversity (Groves et al 2012).…”

“…Further, sites that were also refugia during historical climate change are likely to contain endemic and threatened species (Reside et al 2013, Harrison andNoss 2017), implying some level of irreplaceability and thus further enhancing their conservation value. Where possible, including climate refugia in reserves and connecting them to surrounding habitats is a sensible conservation strategy (Maher et al 2017, Mokany et al 2017. Formal decision analysis can be valuable here, allowing land managers to prioritize conservation action (e.g.…”

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability

“…Methods such as species distribution models (SDMs) are used to forecast range shifts and changes in species composition (Elith & Leathwick, 2009;Fitzpatrick, Gove, Sanders, & Dunn, 2008;Lawler et al, 2009), identify climate refugia and priorities for protection (Graham, VanDerWal, Phillips, Moritz, & Williams, 2010;Loarie et al, 2008;Mokany et al, 2017), and estimate extinction risk (Thomas et al, 2004;Urban, 2015). Forecasts from these correlative models may be particularly sensitive to climate novelty given their reliance on extrapolation of parameter values beyond those for which the model was developed and validated (Fitzpatrick & Hargrove, 2009;Hutson, 1977;Mainali et al, 2015;Owens et al, 2013;Randin et al, 2006;Zurell, Elith, & Schr€ oder, 2012).…”