Ecological Modelling 360 (2017) 343–362 Contents lists available at ScienceDirect Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel Bridging the gap between climate science and regional-scale biodiversity conservation in south-eastern Australia Michael J. Drielsma a,b,∗ , Jamie Love a,b , Kristen J. Williams c , Glenn Manion d , Hanieh Saremi b , Tom Harwood c , Janeen Robb d a Office of Environment and Heritage, NSW, Australia b University of New England, Armidale, NSW, Australia c CSIRO Land and Water, Canberra ACT, 2601, Australia d Independent environmental consultant, Armidale, NSW, Australia a r t i c l e i n f o Article history: Received 30 December 2016 Received in revised form 18 May 2017 Accepted 22 June 2017 Keywords: Terrestrial biodiversity assessment Climate change impacts and adaptation Biological communities Australia a b s t r a c t Recognition of a trajectory of climate change has raised concerns over implications for the conservation of biodiversity. Quantifying the severity of the issue and informing adaptation measures presents a challenge to ecological modelling. We undertook a study of biodiversity impacts and adaptation using spatial modelling across south- eastern Australia. The study aimed to (1) forecast future impacts on biodiversity arising from 18 plausible climate futures, and (2) identify places where land management actions including revegetation will max- imise expected improvements to projected biodiversity persistence. This work augments well-tested regional-scale biodiversity assessment by considering an uncertain future climate. Generalised Dissimilarity Models (GDMs) were developed at two baselines (1990 and 2000) to char- acterise the continuous nature of compositional turnover of vascular plants varying with climate, soils and landform across the region. The classified outputs of the GDM, representing a vegetation-based bio- diversity surrogate, were projected using kernel regression to simulate changing distributions for the future epochs 2020, 2030, 2050 and 2070, referred to as Bio-climatic Classes (BCC). BCC distributions were combined with a model of current ecosystem condition and applied to a range of biodiversity assessment methodologies, including the Biodiversity Forecasting Tool, the Spatial Links Tool and a new coupled time-series metapopulation occupancy model. The BFT evaluation of the BCC distributions and their respective ecosystem conditions, forecasts a reduction in biodiversity persistence across the region of between 3 and 20 percent by 2070 (due to climate change only) adding to a past loss of 20 percent since European settlement (due to land use change only, not other factors such as weeds and pests). Maps of compositional dissimilarity change in vascular plants point to varying degrees of expected change in biodiversity across south-eastern Australia. Conservation benefit analysis indicates a general increase and re-distribution of the relative benefits of undertaking conservation to sustain or enhance biodiversity across the region. Results have been incorporated into novel visualisations, to assist environmental managers and others to interpret the complex concepts and issues associated with the work, and support regional adaptation planning. Crown Copyright © 2017 Published by Elsevier B.V. All rights reserved. ∗ Corresponding author at: Office of Environment and Heritage (NSW), University of New England, Armidale, NSW, 2351, Australia. E-mail addresses: Michael.Drielsma@environment.nsw.gov.au, mdriels2@une.edu.au (M.J. Drielsma). 1. Introduction 1.1. Modelling biodiversity for a changing climate To be effective, biodiversity conservation should respond to identified risks, even when complexity and uncertainty places limitations on the ability to predict the outcome (Haag and Kaupenjohann, 2001; Freedman, 1998). A trajectory of significant climate change is now upon us (Heller and Zavaleta, 2009), although the precise nature and consequences http://dx.doi.org/10.1016/j.ecolmodel.2017.06.022 0304-3800/Crown Copyright © 2017 Published by Elsevier B.V. All rights reserved.