Expression-environment associations in transcriptomic heat stress responses for a global plant lineage.

The increasing frequency and severity of heatwaves will intensify stress on plants. Given regional variation in heatwave exposure and expected differences in thermal tolerance between species it is unlikely that all plant species will be affected equally by climate change. However, little is currently known about variation in the responses of plants to heat stress, or how those responses differ among closely related species adapted to different environments. Here we quantify the response of 17 Acacia species (175 RNA-seq libraries), from across Australia's diverse biomes, to a multi-day experimental heatwave treatment to identify variation in transcriptomic and physiological responses to heat stress. Genes with known heat response functions showed consistent responses across Acacia species. Up to 10% of all genes and over 100 gene families showed significant clinal variation in the magnitude of their expression plasticity across species. Specifically, gene families linked to the temperature stress response were overrepresented among significant relationships with home range temperature conditions. Gene expression responses seen on the first day of the heatwave were more frequently associated with home range climates, while expression responses by day four were more commonly related to photosystem II acclimation. Comparative transcriptomics on non-model species has the potential to provide key information on stress response plasticity, especially when linked with our understanding of model species. Our study indicates that the pressing challenge to identifying potentially vulnerable species to climate change could be benefited by the further exploration of clinal variation in transcriptome plasticity.

Reporting the biodiversity impacts of greenhouse gas emissions.

There are increasing demands for organisations and governments to report their biodiversity impacts, yet there are limited methods to account for the consequences of emitting greenhouse gases on global biodiversity. We use published evidence to derive a conversion factor of approximately 2.3 × 10-7 species expected to be committed to extinction per tCO2 e emitted. We demonstrate how this conversion factor can be used to account for emissions-related biodiversity impacts of organisations and nations.

Environmental DNA reveals a mismatch between diversity facets of Amazonian fishes in response to contrasting geographical, environmental and anthropogenic effects.

Freshwater ecosystems are among the most endangered ecosystem in the world. Understanding how human activities affect these ecosystems requires disentangling and quantifying the contribution of the factors driving community assembly. While it has been largely studied in temperate freshwaters, tropical ecosystems remain challenging to study due to the high species richness and the lack of knowledge on species distribution. Here, the use of eDNA-based fish inventories combined to a community-level modelling approach allowed depicting of assembly rules and quantifying the relative contribution of geographic, environmental and anthropic factors to fish assembly. We then used the model predictions to map spatial biodiversity and assess the representativity of sites surveyed in French Guiana within the EU Water Framework Directive (WFD) and highlighted areas that should host unique freshwater fish assemblages. We demonstrated a mismatch between the taxonomic and functional diversity. Taxonomic assemblages between but also within basins were mainly the results of dispersal limitation resulting from basin isolation and natural river barriers. Contrastingly, functional assemblages were ruled by environmental and anthropic factors. The regional mapping of fish diversity indicated that the sites surveyed within the EU WFD had a better representativity of the regional functional diversity than taxonomic diversity. Importantly, we also showed that the assemblages expected to be the most altered by anthropic factors were the most poorly represented in terms of functional diversity in the surveyed sites. The predictions of unique functional and taxonomic assemblages could, therefore, guide the establishment of new survey sites to increase fish diversity representativity and improve this monitoring program.

Towards a continent-wide ecological site condition database using calibrated expert evaluations.

A cost-effective way of undertaking comprehensive, continental-scale, assessments of ecological condition is needed to support large-scale conservation planning, monitoring, reporting, and decision-making. Currently, cross-jurisdictional inconsistency in assessment methods limits the capacity to scale-up monitoring. Here we present a novel way to build a coherent continent-wide site-level ecological condition dataset, using cross-calibration methods to integrate assessments from many observers. We focus on the use of condition assessments from individual expert observers, a currently untapped resource. Our approach has two components: (1) a simple online tool that captures expert assessments at specific locations; (2) a process of calibrating and rescaling disparate expert evaluations that can be applied to the data to provide a consistent dataset for use in conservation assessments. We describe a pilot study, involving 28 experts, who contributed 314 individual site condition assessments across a wide range of ecosystems and regions throughout continental Australia. A correction factor for each expert was used to rescale the contributed site condition assessment scores, based on a set of 77 photographic images, each scored for their condition by multiple experts, using a linear mixed model. Our approach shows strong promise for delivering the volumes of data required to develop continental-scale reference libraries of site condition assessments. Although developed from expert elicitation, the approach could also be used to harmonize the collation of existing condition datasets. The process we demonstrate can also facilitate online citizen scientists to make site condition assessments that can be cross-calibrated using contributed images.

Linking life history to landscape for threatened species conservation in a multiuse region.

Landscape-scale conservation that considers metapopulation dynamics will be essential for preventing declines of species facing multiple threats to their survival. Toward this end, we developed a novel approach that combines occurrence records, spatial-environmental data, and genetic information to model habitat, connectivity, and patterns of genetic structure and link spatial attributes to underlying ecological mechanisms. Using the threatened northern quoll (Dasyurus hallucatus) as a case study, we applied this approach to address the need for conservation decision-making tools that promote resilient metapopulations of this threatened species in the Pilbara, Western Australia, a multiuse landscape that is a hotspot for biodiversity and mining. Habitat and connectivity were predicted by different landscape characteristics. Whereas habitat suitability was overwhelmingly driven by terrain ruggedness, dispersal was facilitated by proximity to watercourses. Although there is limited evidence for major physical barriers in the Pilbara, areas with high silt and clay content (i.e., alluvial and hardpan plains) showed high resistance to dispersal. Climate subtlety shaped distributions and patterns of genetic turnover, suggesting the potential for local adaptation. By understanding these spatial-environmental associations and linking them to life-history and metapopulation dynamics, we highlight opportunities to provide targeted species management. To support this, we have created habitat, connectivity, and genetic uniqueness maps for conservation decision-making in the region. These tools have the potential to provide a more holistic approach to conservation in multiuse landscapes globally.

La conservación a nivel del paisaje que incluye las dinámicas metapoblacionales será esencial para prevenir la declinación de especies con múltiples amenazas a su supervivencia. Enfocados en este fin, desarrollamos una estrategia novedosa que combina los registros presenciales, datos espacio-ambientales e información genética para modelar la conectividad de hábitat y los patrones de estructura genética y conectar los atributos espaciales con los mecanismos ecológicos subyacentes. Usamos al cuol del norte (Dasyurus hallucatus) como estudio de caso para aplicar esta estrategia y abordar la necesidad de herramientas de decisión en la conservación que promuevan metapoblaciones resilientes de esta especie en la Pilbara de Australia Occidental, un paisaje multiusos que es un punto caliente para la biodiversidad y la minería. Diferentes características del paisaje pronosticaron la conectividad y el hábitat. Mientras que la escabrosidad del terreno causó enormemente la idoneidad del hábitat, la dispersión estuvo propiciada por la proximidad a los cauces. Aunque hay evidencias limitadas de barreras físicas importantes en la Pilbara, las áreas con un contenido elevado de limo y arcilla (es decir, planicies aluviales y de alio) mostraron una gran resistencia a la dispersión. La matización climática determinó la distribución y los patrones del recambio genético, lo que sugiere un potencial para la adaptación local. Si entendemos estas asociaciones espacio-ambientales y las conectamos con las dinámicas metapoblacionales y de historia de vida, podemos resaltar las oportunidades para proporcionar un manejo focalizado de la especie. Para respaldar esto hemos creado mapas de hábitat, conectividad y singularidad genética para las decisiones de conservación en la región. Estas herramientas tienen el potencial de proporcionar una estrategia más holística para la conservación en los paisajes multiusos de todo el mundo.

Reconciling global priorities for conserving biodiversity habitat.

Degradation and loss of natural habitat is the major driver of the current global biodiversity crisis. Most habitat conservation efforts to date have targeted small areas of highly threatened habitat, but emerging debate suggests that retaining large intact natural systems may be just as important. We reconcile these perspectives by integrating fine-resolution global data on habitat condition and species assemblage turnover to identify Earth's high-value biodiversity habitat. These are areas in better condition than most other locations predicted to have once supported a similar assemblage of species and are found within both intact regions and human-dominated landscapes. However, only 18.6% of this high-value habitat is currently protected globally. Averting permanent biodiversity loss requires clear, spatially explicit targets for retaining these unprotected high-value habitats.

Habitat-based biodiversity assessment for ecosystem accounting in the Murray-Darling Basin.

Understanding how biodiversity is changing over space and time is crucial for well-informed decisions that help retain Earth's biological heritage over the long term. Tracking changes in biodiversity through ecosystem accounting provides this important information in a systematic way and readily enables linking to other relevant environmental and economic data to provide an integrated perspective. We derived biodiversity accounts for the Murray-Darling Basin, Australia's largest catchment. We assessed biodiversity change from 2010 to 2015 for all vascular plants, all waterbirds, and 10 focal species. We applied a scalable habitat-based assessment approach that combined expected patterns in the distribution of biodiversity from spatial biodiversity models with a time series of spatially complete data on habitat condition derived from remote sensing. Changes in biodiversity from 2010 to 2015 varied across regions and biodiversity features. For the entire Murray-Darling Basin, the expected persistence of vascular plants increased slightly from 2010 to 2015 (from 86.8% to 87.1%), mean species richness of waterbirds decreased slightly (from 12.5 to 12.3 species), whereas for the focal species the estimated area of habitat increased for 8 species and decreased for 1 species. Regions in the north of the Murray-Darling Basin generally had decreases in biodiversity from 2010 to 2015, whereas in the south biodiversity was stable or increased. Our results demonstrate the benefits of habitat-based biodiversity assessments in providing fully scalable biodiversity accounts across different biodiversity features, consistent with the United Nations System of Environmental Economic Accounting - Ecosystem Accounting (SEEA EA) framework.

Evaluación de la Biodiversidad con base en el Hábitat para la Contabilización de Ecosistemas en la Cuenca Murray-Darling Resumen El conocimiento sobre cómo está cambiando la biodiversidad en el tiempo y en el espacio es crucial para las decisiones bien informadas que ayudan a retener la herencia biológica de la Tierra a largo plazo. El seguimiento de cambios en la biodiversidad mediante la contabilidad de los ecosistemas proporciona esta información importante de manera sistémica y permite fácilmente la conexión con otros datos ambientales y económicos relevantes para proporcionar una perspectiva integrada. Derivamos la contabilidad de la biodiversidad para la Cuenca Murray-Darling, la mayor cuenca de Australia. Analizamos los cambios en la biodiversidad entre 2010 y 2015 de todas las plantas vasculares, todas las aves acuáticas y diez especies focales. Aplicamos una estrategia de evaluación basada en el hábitat que combinó los patrones esperados en la distribución de la biodiversidad a partir de modelos espaciales de la biodiversidad con una serie temporal de datos espacialmente completos derivados de la teledetección de la condición del hábitat. Los cambios en la biodiversidad entre 2010 y 2015 variaron entre las regiones y las características de la biodiversidad. Para toda la Cuenca Murray-Darling, la persistencia esperada de las plantas vasculares incrementó ligeramente durante los años de estudio (de 86.8% a 87.1%), la riqueza promedio de especies de aves acuáticas disminuyó un poco (de 12.5 a 12.3 especies), mientras que el área estimada del hábitat de las especies focales incrementó para ocho especies y disminuyó para una. Las regiones al norte de la cuenca tuvieron disminuciones generalizadas de la biodiversidad entre 2010 y 2015, mientras al sur, la biodiversidad se mantuvo estable o incrementó. Nuestros resultados demuestran los beneficios que tienen las evaluaciones de la biodiversidad basadas en el hábitat para proporcionar una contabilidad de la biodiversidad completamente escalable entre las diferentes características de la biodiversidad, acorde con la estructura del Sistema de Contabilidad Económico-Ambiental - Contabilidad de los Ecosistemas (SEEA EA) de las Naciones Unidas.

A regional-scale assessment of using metabolic scaling theory to predict ecosystem properties.

Metabolic scaling theory (MST) is one of ecology's most high-profile general models and can be used to link size distributions and productivity in forest systems. Much of MST's foundation is based on size distributions following a power law function with a scaling exponent of -2, a property assumed to be consistent in steady-state ecosystems. We tested the theory's generality by comparing actual size distributions with those predicted using MST parameters assumed to be general. We then used environmental variables and functional traits to explain deviation from theoretical expectations. Finally, we compared values of relative productivity predicted using MST with a remote-sensed measure of productivity. We found that fire-prone heath communities deviated from MST-predicted size distributions, whereas fire-sensitive rainforests largely agreed with the theory. Scaling exponents ranged from -1.4 to -5.3. Deviation from the power law assumption was best explained by specific leaf area, which varies along fire frequency and moisture gradients. While MST may hold in low-disturbance systems, we show that it cannot be applied under many environmental contexts. The theory should remain general, but understanding the factors driving deviation from MST and subsequent refinements is required if it is to be applied robustly across larger scales.

Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change.

Based on the sensitivity of species to ongoing climate change, and numerous challenges they face tracking suitable conditions, there is growing interest in species' capacity to adapt to climatic stress. Here, we develop and apply a new generic modelling approach (AdaptR) that incorporates adaptive capacity through physiological limits, phenotypic plasticity, evolutionary adaptation and dispersal into a species distribution modelling framework. Using AdaptR to predict change in the distribution of 17 species of Australian fruit flies (Drosophilidae), we show that accounting for adaptive capacity reduces projected range losses by up to 33% by 2105. We identify where local adaptation is likely to occur and apply sensitivity analyses to identify the critical factors of interest when parameters are uncertain. Our study suggests some species could be less vulnerable than previously thought, and indicates that spatiotemporal adaptive models could help improve management interventions that support increased species' resilience to climate change.

Birds of a feather: using species assemblages to assess vulnerability to extinction.

Estimating extinction vulnerability for a large number of species presents significant challenges for researchers, but is of high importance considering the large number of species that are currently unassessed. We present a method using a type of artificial neural network (self organizing map; SOM), which utilizes the co-occurrence patterns of species to estimate each species' vulnerability to extinction. We use this method on Australian bird assemblages and compare the SOM-generated rankings for vulnerability with assessments from the IUCN Red List for those species in which populations have actually been estimated. For species that have had their populations estimated, the SOM performed well in distinguishing those species ranked of least concern by IUCN from those species in one of the other IUCN categories. Further, 19 species that were identified as highly vulnerable by the SOM analysis have never had their populations estimated and have been ranked by the IUCN of least concern. We show how the SOM can identify spatial variation in vulnerability for a species, and identify those regions in Australia in which the resident species have the greatest levels of vulnerability (central Australia). We conclude that the SOM provides a useful tool for researchers and agencies dealing with conservation strategies focused on large numbers of species and we urge a more detailed assessment of the 19 bird species identified by this analysis as vulnerable to extinction.

Linking changes in community composition and function under climate change.

Climate change is expected to directly alter the composition of communities and the functioning of ecosystems across the globe. Improving our understanding of links between biodiversity and ecosystem functioning across large spatial scales and rapid global change is a major priority to help identify management responses that will retain diverse, functioning systems. Here we address this challenge by linking projected changes in plant community composition and functional attributes (height, leaf area, seed mass) under climate change across Tasmania, Australia. Using correlative community-level modeling, we found that projected changes in plant community composition were not consistently related to projected changes in community mean trait values. In contrast, we identified specific mechanisms through which alternative combinations of projected functional and compositional change across Tasmania could be realized, including loss/replacement of functionally similar species (lowland grasslands/grassy woodlands) and loss of a small number of functionally unique species (lowland forests). Importantly, we demonstrate how these linked projections of change in community composition and functional attributes can be utilized to inform specific management actions that may assist in maintaining diverse, functioning ecosystems under climate change.

Dynamic macroecology and the future for biodiversity.

Reliable projections of climate-change impacts on biodiversity are vital in formulating conservation and management strategies that best retain biodiversity into the future. While recent modelling has focussed largely on individual species, macroecology has the potential to add significant value to these efforts, by incorporating important community-level constraints and processes. Here we show how a new dynamic macroecological approach can project climate-change impacts collectively across all species in a diverse taxonomic group, overcoming shortfalls in our knowledge of biodiversity, while incorporating the key processes of dispersal and community assembly. Our approach applies a recently published technique (DynamicFOAM) to predict the present composition of every community, which form the initial conditions for a new metacommunity model (M-SET) that projects changes in composition over time, under specified climate and habitat scenarios. Applying this approach at fine resolution to plant biodiversity in Tasmania (2,051 species; 1,157,587 communities), we project high average turnover in community composition from 2010 to 2100 (mean Sorensen's dissimilarity = 0.71 (±7.0 × 10-5 )), with major reductions in species richness (32.9 (±0.02) species lost per community) and no plant species benefitting from climate change in the long term. We also demonstrate how our modelling approach can identify habitat likely to be of high value for retaining rare and poorly reserved species under climate change. Our analyses highlight the potential value of this dynamic macroecological approach, that incorporates key ecological processes in projecting climate change impacts for all species simultaneously and uses simple macroecological inputs that can be derived even for highly diverse and poorly studied taxa.

Combining α - and ß -diversity models to fill gaps in our knowledge of biodiversity.

For many taxonomic groups, sparse information on the spatial distribution of biodiversity limits our capacity to answer a variety of theoretical and applied ecological questions. Modelling community-level attributes (α- and ß-diversity) over space can help overcome this shortfall in our knowledge, yet individually, predictions of α- or ß-diversity have their limitations. In this study, we present a novel approach to combining models of α- and ß-diversity, with sparse survey data, to predict the community composition for all sites in a region. We applied our new approach to predict land snail community composition across New Zealand. As we demonstrate, these predictions of metacommunity composition have diverse potential applications, including predicting γ-diversity for any set of sites, identifying target areas for conservation reserves, locating priority areas for future ecological surveys, generating realistic compositional data for metacommunity models and simultaneously predicting the distribution of all species in a taxon consistent with known community diversity patterns.

Bayesian spatio-temporal modelling to assess the role of extreme weather, land use change and socio-economic trends on cryptosporidiosis in Australia, 2001-2018.

BACKGROUND: Intensification of land use threatens to increase the emergence and prevalence of zoonotic diseases, with an adverse impact on human wellbeing. Understanding how the interaction between agriculture, natural systems, climate and socioeconomic drivers influence zoonotic disease distribution is crucial to inform policy planning and management to limit the emergence of new infections. OBJECTIVES: Here we assess the relative contribution of environmental, climatic and socioeconomic factors influencing reported cryptosporidiosis across Australia from 2001 to 2018. METHODS: We apply a Bayesian spatio-temporal analysis using Integrated Nested Laplace Approximation (INLA). RESULTS: We find that area-level risk of reported disease are associated with the proportions of the population under 5 and over 65 years of age, socioeconomic disadvantage, annual rainfall anomaly, and the proportion of natural habitat remaining. This combination of multiple factors influencing cryptosporidiosis highlights the benefits of a sophisticated spatio-temporal statistical approach. Two key findings from our model include: an estimated 4.6% increase in the risk of reported cryptosporidiosis associated with 22.8% higher percentage of postal area covered with original habitat; and an estimated 1.8% increase in disease risk associated with a 77.99 mm increase in annual rainfall anomaly at the postal area level. DISCUSSION: These results provide novel insights regarding the predictive effects of extreme rainfall and the proportion of remaining natural habitat, which add unique explanatory power to the model alongside the variance associated with other predictive variables and spatiotemporal variation in reported disease. This demonstrates the importance of including perspectives from land and water management experts for policy making and public health responses to manage environmentally mediated diseases, including cryptosporidiosis.

Protecting Biodiversity (in All Its Complexity): New Models and Methods.

We are facing a biodiversity crisis at the same time as we are acquiring an unprecedented view of the world's biodiversity. Vast new datasets (e.g., species distributions, traits, phylogenies, and interaction networks) hold knowledge to better comprehend the depths of biodiversity change, reliably anticipate these changes, and inform conservation actions. To harness this information for conservation, we need to integrate the largely independent fields of biodiversity modeling and conservation. We highlight new developments in each respective field, early examples of how they are being brought together, and ideas for a future synthesis such that conservation decisions can be made with fuller awareness of the biodiversity at stake.

Scenarios and Models to Support Global Conservation Targets.

Global biodiversity targets have far-reaching implications for nature conservation worldwide. Scenarios and models hold unfulfilled promise for ensuring such targets are well founded and implemented; here, we review how they can and should inform the Aichi Targets of the Strategic Plan for Biodiversity and their reformulation. They offer two clear benefits: providing a scientific basis for the wording and quantitative elements of targets; and identifying synergies and trade-offs by accounting for interactions between targets and the actions needed to achieve them. The capacity of scenarios and models to address complexity makes them invaluable for developing meaningful targets and policy, and improving conservation outcomes.

Biodiversity Models: What If Unsaturation Is the Rule?

Improving biodiversity predictions is essential if we are to meet the challenges posed by global change. As knowledge is key to feed models, we need to evaluate how debated theory can affect models. An important ongoing debate is whether environmental constraints limit the number of species that can coexist in a community (saturation), with recent findings suggesting that species richness in many communities might be unsaturated. Here, we propose that biodiversity models could address this issue by accounting for a duality: considering communities as unsaturated but where species composition is constrained by different scale-dependent biodiversity drivers. We identify a variety of promising advances for incorporating this duality into commonly applied biodiversity modelling approaches and improving their spatial predictions.

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.