Implications of the 2019-2020 megafires for the biogeography and conservation of Australian vegetation.

Australia's 2019-2020 'Black Summer' bushfires burnt more than 8 million hectares of vegetation across the south-east of the continent, an event unprecedented in the last 200 years. Here we report the impacts of these fires on vascular plant species and communities. Using a map of the fires generated from remotely sensed hotspot data we show that, across 11 Australian bioregions, 17 major native vegetation groups were severely burnt, and up to 67-83% of globally significant rainforests and eucalypt forests and woodlands. Based on geocoded species occurrence data we estimate that >50% of known populations or ranges of 816 native vascular plant species were burnt during the fires, including more than 100 species with geographic ranges more than 500 km across. Habitat and fire response data show that most affected species are resilient to fire. However, the massive biogeographic, demographic and taxonomic breadth of impacts of the 2019-2020 fires may leave some ecosystems, particularly relictual Gondwanan rainforests, susceptible to regeneration failure and landscape-scale decline.

Wilderness areas halve the extinction risk of terrestrial biodiversity.

Reducing the rate of global biodiversity loss is a major challenge facing humanity1, as the consequences of biological annihilation would be irreversible for humankind2-4. Although the ongoing degradation of ecosystems5,6 and the extinction of species that comprise them7,8 are now well-documented, little is known about the role that remaining wilderness areas have in mitigating the global biodiversity crisis. Here we model the persistence probability of biodiversity, combining habitat condition with spatial variation in species composition, to show that retaining these remaining wilderness areas is essential for the international conservation agenda. Wilderness areas act as a buffer against species loss, as the extinction risk for species within wilderness communities is-on average-less than half that of species in non-wilderness communities. Although all wilderness areas have an intrinsic conservation value9,10, we identify the areas on every continent that make the highest relative contribution to the persistence of biodiversity. Alarmingly, these areas-in which habitat loss would have a more-marked effect on biodiversity-are poorly protected. Given globally high rates of wilderness loss10, these areas urgently require targeted protection to ensure the long-term persistence of biodiversity, alongside efforts to protect and restore more-degraded environments.

Projecting impacts of global climate and land-use scenarios on plant biodiversity using compositional-turnover modelling.

Nations have committed to ambitious conservation targets in response to accelerating rates of global biodiversity loss. Anticipating future impacts is essential to inform policy decisions for achieving these targets, but predictions need to be of sufficiently high spatial resolution to forecast the local effects of global change. As part of the intercomparison of biodiversity and ecosystem services models of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, we present a fine-resolution assessment of trends in the persistence of global plant biodiversity. We coupled generalized dissimilarity models, fitted to >52 million records of >254 thousand plant species, with the species-area relationship, to estimate the effect of land-use and climate change on global biodiversity persistence. We estimated that the number of plant species committed to extinction over the long term has increased by 60% globally between 1900 and 2015 (from ~10,000 to ~16,000). This number is projected to decrease slightly by 2050 under the most optimistic scenario of land-use change and to substantially increase (to ~18,000) under the most pessimistic scenario. This means that, in the absence of climate change, scenarios of sustainable socio-economic development can potentially bring extinction risk back to pre-2000 levels. Alarmingly, under all scenarios, the additional impact from climate change might largely surpass that of land-use change. In this case, the estimated number of species committed to extinction increases by 3.7-4.5 times compared to land-use-only projections. African regions (especially central and southern) are expected to suffer some of the highest impacts into the future, while biodiversity decline in Southeast Asia (which has previously been among the highest globally) is projected to slow down. Our results suggest that environmentally sustainable land-use planning alone might not be sufficient to prevent potentially dramatic biodiversity loss, unless a stabilization of climate to pre-industrial times is observed.

Climate Velocity Can Inform Conservation in a Warming World.

Climate change is shifting the ranges of species. Simple predictive metrics of range shifts such as climate velocity, that do not require extensive knowledge or data on individual species, could help to guide conservation. We review research on climate velocity, describing the theory underpinning the concept and its assumptions. We highlight how climate velocity has already been applied in conservation-related research, including climate residence time, climate refugia, endemism, historic and projected range shifts, exposure to climate change, and climate connectivity. Finally, we discuss ways to enhance the use of climate velocity in conservation through tailoring it to be more biologically meaningful, informing design of protected areas, conserving ocean biodiversity in 3D, and informing conservation actions.

Downscaling land-use data to provide global 30″ estimates of five land-use classes.

Land-use change is one of the biggest threats to biodiversity globally. The effects of land use on biodiversity manifest primarily at local scales which are not captured by the coarse spatial grain of current global land-use mapping. Assessments of land-use impacts on biodiversity across large spatial extents require data at a similar spatial grain to the ecological processes they are assessing. Here, we develop a method for statistically downscaling mapped land-use data that combines generalized additive modeling and constrained optimization. This method was applied to the 0.5° Land-use Harmonization data for the year 2005 to produce global 30″ (approx. 1 km(2)) estimates of five land-use classes: primary habitat, secondary habitat, cropland, pasture, and urban. The original dataset was partitioned into 61 bio-realms (unique combinations of biome and biogeographical realm) and downscaled using relationships with fine-grained climate, land cover, landform, and anthropogenic influence layers. The downscaled land-use data were validated using the PREDICTS database and the geoWiki global cropland dataset. Application of the new method to all 61 bio-realms produced global fine-grained layers from the 2005 time step of the Land-use Harmonization dataset. Coarse-scaled proportions of land use estimated from these data compared well with those estimated in the original datasets (mean R (2): 0.68 ± 0.19). Validation with the PREDICTS database showed the new downscaled land-use layers improved discrimination of all five classes at PREDICTS sites (P < 0.0001 in all cases). Additional validation of the downscaled cropping layer with the geoWiki layer showed an R (2) improvement of 0.12 compared with the Land-use Harmonization data. The downscaling method presented here produced the first global land-use dataset at a spatial grain relevant to ecological processes that drive changes in biodiversity over space and time. Integrating these data with biodiversity measures will enable the reporting of land-use impacts on biodiversity at a finer resolution than previously possible. Furthermore, the general method presented here could be useful to others wishing to downscale similarly constrained coarse-resolution data for other environmental variables.

Macroecological scale effects of biodiversity on ecosystem functions under environmental change.

Conserving different spatial and temporal dimensions of biological diversity is considered necessary for maintaining ecosystem functions under predicted global change scenarios. Recent work has shifted the focus from spatially local (α-diversity) to macroecological scales (ß- and γ-diversity), emphasizing links between macroecological biodiversity and ecosystem functions (MB-EF relationships). However, before the outcomes of MB-EF analyses can be useful to real-world decisions, empirical modeling needs to be developed for natural ecosystems, incorporating a broader range of data inputs, environmental change scenarios, underlying mechanisms, and predictions. We outline the key conceptual and technical challenges currently faced in developing such models and in testing and calibrating the relationships assumed in these models using data from real ecosystems. These challenges are explored in relation to two potential MB-EF mechanisms: "macroecological complementarity" and "spatiotemporal compensation." Several regions have been sufficiently well studied over space and time to robustly test these mechanisms by combining cutting-edge spatiotemporal methods with remotely sensed data, including plant community data sets in Australia, Europe, and North America. Assessing empirical MB-EF relationships at broad spatiotemporal scales will be crucial in ensuring these macroecological processes can be adequately considered in the management of biodiversity and ecosystem functions under global change.

Hypothermia and near-drowning associated with life-threatening injuries: A remarkable recovery: A case report.

A young male suffered multiple severe injuries after a fall and near-drowning. On presentation to the emergency department (ED), he was in a critical and unstable condition and his chances of survival were deemed very low. This case illustrates the management of the hypothermic multi-trauma patient and the remarkable recovery made possible by a high standard of care.

Australia is 'free to choose' economic growth and falling environmental pressures.

Over two centuries of economic growth have put undeniable pressure on the ecological systems that underpin human well-being. While it is agreed that these pressures are increasing, views divide on how they may be alleviated. Some suggest technological advances will automatically keep us from transgressing key environmental thresholds; others that policy reform can reconcile economic and ecological goals; while a third school argues that only a fundamental shift in societal values can keep human demands within the Earth's ecological limits. Here we use novel integrated analysis of the energy-water-food nexus, rural land use (including biodiversity), material flows and climate change to explore whether mounting ecological pressures in Australia can be reversed, while the population grows and living standards improve. We show that, in the right circumstances, economic and environmental outcomes can be decoupled. Although economic growth is strong across all scenarios, environmental performance varies widely: pressures are projected to more than double, stabilize or fall markedly by 2050. However, we find no evidence that decoupling will occur automatically. Nor do we find that a shift in societal values is required. Rather, extensions of current policies that mobilize technology and incentivize reduced pressure account for the majority of differences in environmental performance. Our results show that Australia can make great progress towards sustainable prosperity, if it chooses to do so.

SIS along a continuum (SIS(c)) epidemiological modelling and control of diseases on directed trade networks.

Network theory has been applied to many aspects of biosciences, including epidemiology. Most epidemiological models in networks, however, have used the standard assumption of either susceptible or infected individuals. In some cases (e.g. the spread of Phytophthora ramorum in plant trade networks), a continuum in the infection status of nodes can better capture the reality of epidemics in networks. In this paper, a Susceptible-Infected-Susceptible model along a continuum in the infection status (SIS(c)) is presented, using as a case study directed networks and two parameters governing the epidemic process (probability of infection persistence (p(p)) and of infection transmission (p(t)). The previously empirically reported linear epidemic threshold in a plot of p(p) as a function of p(t) (Pautasso and Jeger, 2008) is derived analytically. Also the previously observed negative correlation between the epidemic threshold and the correlation between links in and out of nodes (Moslonka-Lefebvre et al., 2009) is justified analytically. A simple algorithm to calculate the threshold conditions is introduced. Additionally, a control strategy based on targeting market hierarchical categories such as producers, wholesalers and retailers is presented and applied to a realistic reconstruction of the UK horticultural trade network. Finally, various applications (e.g., seed exchange networks, food trade, spread of ideas) and potential refinements of the SIS(c) model are discussed.

Learning from history, predicting the future: the UK Dutch elm disease outbreak in relation to contemporary tree disease threats.

Expanding international trade and increased transportation are heavily implicated in the growing threat posed by invasive pathogens to biodiversity and landscapes. With trees and woodland in the UK now facing threats from a number of disease systems, this paper looks to historical experience with the Dutch elm disease (DED) epidemic of the 1970s to see what can be learned about an outbreak and attempts to prevent, manage and control it. The paper draws on an interdisciplinary investigation into the history, biology and policy of the epidemic. It presents a reconstruction based on a spatial modelling exercise underpinned by archival research and interviews with individuals involved in the attempted management of the epidemic at the time. The paper explores what, if anything, might have been done to contain the outbreak and discusses the wider lessons for plant protection. Reading across to present-day biosecurity concerns, the paper looks at the current outbreak of ramorum blight in the UK and presents an analysis of the unfolding epidemiology and policy of this more recent, and potentially very serious, disease outbreak. The paper concludes by reflecting on the continuing contemporary relevance of the DED experience at an important juncture in the evolution of plant protection policy.

Networks in plant epidemiology: from genes to landscapes, countries, and continents.

There is increasing use of networks in ecology and epidemiology, but still relatively little application in phytopathology. Networks are sets of elements (nodes) connected in various ways by links (edges). Network analysis aims to understand system dynamics and outcomes in relation to network characteristics. Many existing natural, social, and technological networks have been shown to have small-world (local connectivity with short-cuts) and scale-free (presence of super-connected nodes) properties. In this review, we discuss how network concepts can be applied in plant pathology from the molecular to the landscape and global level. Wherever disease spread occurs not just because of passive/natural dispersion but also due to artificial movements, it makes sense to superimpose realistic models of the trade in plants on spatially explicit models of epidemic development. We provide an example of an emerging pathosystem (Phytophthora ramorum) where a theoretical network approach has proven particularly fruitful in analyzing the spread of disease in the UK plant trade. These studies can help in assessing the future threat posed by similar emerging pathogens. Networks have much potential in plant epidemiology and should become part of the standard curriculum.