Examining current or future trade-offs for biodiversity conservation in north-eastern Australia

With the high rate of ecosystem change already occurring and predicted to occur in the coming decades, long-term conservation has to account not only for current biodiversity but also for the biodiversity patterns anticipated for the future. The trade-offs between prioritising future biodiversity at the expense of current priorities must be understood to guide current conservation planning, but have been largely unexplored. To fill this gap, we compared the performance of four conservation planning solutions involving 662 vertebrate species in the Wet Tropics Natural Resource Management Cluster Region in north-eastern Australia. Input species data for the four planning solutions were: 1) current distributions; 2) projected distributions for 2055; 3) projected distributions for 2085; and 4) current, 2055 and 2085 projected distributions, and the connectivity between each of the three time periods for each species. The four planning solutions were remarkably similar (up to 85% overlap), suggesting that modelling for either current or future scenarios is sufficient for conversation planning for this region, with little obvious trade-off. Our analyses also revealed that overall, species with small ranges occurring across steep elevation gradients and at higher elevations were more likely to be better represented in all solutions. Given that species with these characteristics are of high conservation significance, our results provide confidence that conservation planning focused on either current, near-or distant-future biodiversity will account for these species.Peer reviewe

Incorporating altered fire frequency scenarios in species distribution models improves climate change predictions for tropical savanna birds

Biodiversity conservation in the face of changing climate requires reliable predictions of species distributions. Distribution models need to include variables that strongly influence species persistence. Species will be affected by climate change directly by altering the amount and location of suitable climatic space, and indirectly by climate driven modification of habitat. While climate is a good predictor of species distributions, biotic and abiotic landscape factors also influence distribution. Very few studies of climate change effects on biodiversity have included key landscape factors in distribution modelling, despite recognition that landscape alteration through processes such as fire and land clearing changes fauna patterning. For birds in Australian tropical savannas, change in fire regimes is a critical conservation issue, linked to species decline. While species may show gradual shifts in distribution due to changes in temperature and rainfall, species are likely to show a more immediate response to changes in fire as a result of climatic changes. This study examines species' responses to changes in fire by projecting species distribution modelling algorithms built using Maxent onto scenarios with increased fire frequency. We accounted for important static landscape elements by including remnant vegetation and soil spatial layers. This study identified that increased fire frequency alters the predictions for birds by changing the amount of suitable habitat. Climate change combined with increased fire frequency will reduce available habitat; more than simply using climate predictions alone. Our results demonstrate the importance of including landscape factors into distribution modelling when generating species predictions. Understanding the impacts of landscape factors on bird distributions, in particular fire, is a critical step in conservation planning and adaptation of land management for combating biodiversity loss due to climate change

Addressing potential cumulative impacts of development on threatened species: the case of the endangered black-throated finch

Where threatened biodiversity is adversely affected by development, policies often state that "no net loss" should be the goal and biodiversity offsetting is one mechanism available to achieve this. However, developments are often approved on an ad hoc basis and cumulative impacts are not sufficiently examined. We demonstrate the potential for serious threat to an endangered subspecies when multiple developments are planned. We modelled the distribution of the black-throated finch (Poephila cincta cincta) using bioclimatic data and Queensland's Regional Ecosystem classification. We overlaid granted, extant extractive and exploratory mining tenures within the known and modelled ranges of black-throated finches to examine the level of incipient threat to this subspecies in central Queensland, Australia. Our models indicate that more than half of the remaining P. cincta cincta habitat is currently under extractive or exploratory tenure. Therefore, insufficient habitat exists to offset all potential development so "no net loss" is not possible. This has implications for future conservation of this and similarly distributed species and for resource development planning, especially the use of legislated offsets for biodiversity protection

Weather, Not Climate, Defines Distributions of Vagile Bird Species

Background\ud \ud Accurate predictions of species distributions are essential for climate change impact assessments. However the standard practice of using long-term climate averages to train species distribution models might mute important temporal patterns of species distribution. The benefit of using temporally explicit weather and distribution data has not been assessed. 1We hypothesized that short-term weather associated with the time a species was recorded should be superior to long-term climate measures for predicting distributions of mobile species.\ud \ud Methodology\ud \ud We tested our hypothesis by generating distribution models for 157 bird species found in Australian tropical savannas (ATS) using modelling algorithm Maxent. The variable weather of the ATS supports a bird assemblage with variable movement patterns and a high incidence of nomadism. We developed “weather” models by relating climatic variables (mean temperature, rainfall, rainfall seasonality and temperature seasonality) from the three month, six month and one year period preceding each bird record over a 58 year period (1950–2008). These weather models were compared against models built using long-term (30 year) averages of the same climatic variables.\ud \ud Conclusions\ud \ud Weather models consistently achieved higher model scores than climate models, particularly for wide-ranging, nomadic and desert species. Climate models predicted larger range areas for species, whereas weather models quantified fluctuations in habitat suitability across months, seasons and years. Models based on long-term climate averages over-estimate availability of suitable habitat and species' climatic tolerances, masking species potential vulnerability to climate change. Our results demonstrate that dynamic approaches to distribution modelling, such as incorporating organism-appropriate temporal scales, improves understanding of species distributions

The capacity of refugia for conservation planning under climate change

Refugia – areas that may facilitate the persistence of species during large-scale, long-term climatic change – are increasingly important for conservation planning. There are many methods for identifying refugia, but the ability to quantify their potential for facilitating species persistence (ie their “capacity”) remains elusive. We propose a flexible framework for prioritizing future refugia, based on their capacity. This framework can be applied through various modeling approaches and consists of three steps: (1) definition of scope, scale, and resolution; (2) identification and quantification; and (3) prioritization for conservation. Capacity is quantified by multiple indicators, including environmental stability, microclimatic heterogeneity, size, and accessibility of the refugium. Using an integrated, semi-mechanistic modeling technique, we illustrate how this approach can be implemented to identify refugia for the plant diversity of Tasmania, Australia. The highest- capacity climate-change refugia were found primarily in cool, wet, and topographically complex environments, several of which we identify as high priorities for biodiversity conservation and management

Projecting Global Biodiversity Indicators under Future Development Scenarios

To address the ongoing global biodiversity crisis, governments have set strategic objectives and have adopted indicators to monitor progress toward their achievement. Projecting the likely impacts on biodiversity of different policy decisions allows decision makers to understand if and how these targets can be met. We projected trends in two widely used indicators of population abundance Geometric Mean Abundance, equivalent to the Living Planet Index and extinction risk (the Red List Index) under different climate and land-use change scenarios. Testing these on terrestrial carnivore and ungulate species, we found that both indicators decline steadily, and by 2050, under a Business-as-usual (BAU) scenario, geometric mean population abundance declines by 18-35% while extinction risk increases for 8-23% of the species, depending on assumptions about species responses to climate change. BAU will therefore fail Convention on Biological Diversity target 12 of improving the conservation status of known threatened species. An alternative sustainable development scenario reduces both extinction risk and population losses compared with BAU and could lead to population increases. Our approach to model species responses to global changes brings the focus of scenarios directly to the species level, thus taking into account an additional dimension of biodiversity and paving the way for including stronger ecological foundations into future biodiversity scenario assessments.Peer reviewe

Quantifying the “avoided” biodiversity impacts associated with economic development

Achieving global sustainability objectives such as the UN Sustainable Development Goals or Aichi Targets, including remaining within planetary boundaries, necessitates proactively avoiding a proportion of the environmental impacts otherwise expected to result from economic development. Quantifying these “avoided” impacts is important for monitoring progress toward meeting sustainability objectives, but doing so in a consistent way is fraught with difficulty. Using the mitigation of biodiversity impacts by development projects as an example, we explored the challenges of defining and measuring impact avoidance. Avoidance can be defined as either action-based or outcome-based, and classified by whether it is achieved through project cancellation, spatial avoidance, design-based avoidance, or temporal avoidance. We also examined what drives different types of project proponents to implement avoidance measures. To support empirical quantification of the contribution that avoidance makes toward conservation goals, we present a framework for structuring assessments of biodiversity impact avoidance. Our framework has widespread applicability in conservation science, policy, and practice, as well as relevance for broader policies that seek to avoid environmental and social impacts

Restoring habitat for fire-impacted species' across degraded Australian landscapes

In the summer of 2019-2020, southern Australia experienced the largest fires on record, detrimentally impacting the habitat of native species, many of which were already threatened by past and current anthropogenic land use. A large-scale restoration effort to improve degraded species habitat would provide fire-affected species with the chance to recover and persist in burnt and unburnt habitat. To facilitate this, decision-makers require information on priority species needs for restoration intervention, the suite of potential restoration interventions, and the priority locations for applying these interventions. We prioritize actions in areas where restoration would most likely provide cost-effective benefits to priority species (defined by each species proportion of habitat burned, threat status, and vulnerability to fires), by integrating current and future species habitat suitability maps with spatially modelled costs of restoration interventions such as replanting, removing invasive species, and implementing ecologically appropriate fire management. We show that restoring the top similar to 69% (112 million hectares) of the study region (current and future distributions of priority species) accounts for, on average, 95% of current and future habitat for every priority species and costs similar to AUD$73 billion yr(-1) (AUD$650 hectare(-1) yr(-1)) annualized over 30 years. This effort would include restoration actions over 6 million hectares of fire-impacted habitat, costing similar to AUD$8.8 billion/year. Large scale restoration efforts are often costly but can have significant societal co-benefits beyond biodiversity conservation. We also show that up to 291 MtCO2 (similar to 150 Mt DM) of carbon could be sequestered by restoration efforts, resulting in approximately AUD$253 million yr(-1) in carbon market revenue if all carbon was remunerated. Our approach highlights the scale, costs, and benefits of targeted restoration activities both inside and outside of the immediate bushfire footprint over vast areas of different land tenures

A national-scale dataset for threats impacting Australia's imperiled flora and fauna

Australia is in the midst of an extinction crisis, having already lost 10% of terrestrial mammal fauna since European settlement and with hundreds of other species at high risk of extinction. The decline of the nation's biota is a result of an array of threatening processes; however, a comprehensive taxon-specific understanding of threats and their relative impacts remains undocumented nationally. Using expert consultation, we compile the first complete, validated, and consistent taxon-specific threat and impact dataset for all nationally listed threatened taxa in Australia. We confined our analysis to 1,795 terrestrial and aquatic taxa listed as threatened (Vulnerable, Endangered, or Critically Endangered) under Australian Commonwealth law. We engaged taxonomic experts to generate taxon-specific threat and threat impact information to consistently apply the IUCN Threat Classification Scheme and Threat Impact Scoring System, as well as eight broad-level threats and 51 subcategory threats, for all 1,795 threatened terrestrial and aquatic threatened taxa. This compilation produced 4,877 unique taxon–threat–impact combinations with the most frequently listed threats being Habitat loss, fragmentation, and degradation (n = 1,210 taxa), and Invasive species and disease (n = 966 taxa). Yet when only high-impact threats or medium-impact threats are considered, Invasive species and disease become the most prevalent threats. This dataset provides critical information for conservation action planning, national legislation and policy, and prioritizing investments in threatened species management and recovery

Quantifying extinction risk and forecasting the number of impending Australian bird and mammal extinctions

A critical step towards reducing the incidence of extinction is to identify and rank the species at highest risk, while implementing protective measures to reduce the risk of extinction to such species. Existing global processes provide a graded categorisation of extinction risk. Here we seek to extend and complement those processes to focus more narrowly on the likelihood of extinction of the most imperilled Australian birds and mammals. We considered an extension of existing IUCN and NatureServe criteria, and used expert elicitation to rank the extinction risk to the most imperilled species, assuming current management. On the basis of these assessments, and using two additional approaches, we estimated the number of extinctions likely to occur in the next 20 years. The estimates of extinction risk derived from our tighter IUCN categorisations, NatureServe assessments and expert elicitation were poorly correlated, with little agreement among methods for which species were most in danger – highlighting the importance of integrating multiple approaches when considering extinction risk. Mapped distributions of the 20 most imperilled birds reveal that most are endemic to islands or occur in southern Australia. The 20 most imperilled mammals occur mostly in northern and central Australia. While there were some differences in the forecasted number of extinctions in the next 20 years among methods, all three approaches predict further species loss. Overall, we estimate that another seven Australian mammals and 10 Australian birds will be extinct by 2038 unless management improves