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Based on an extensive model intercomparison, we assessed trends in biodiversity and ecosystem services from historical reconstructions and future scenarios of land-use and climate change. During the 20th century, biodiversity declined globally by 2 to 11%, as estimated by a range of indicators. Provisioning ecosystem services increased several fold, and regulating services decreased moderately. Going forward, policies toward sustainability have the potential to slow biodiversity loss resulting from land-use change and the demand for provisioning services while reducing or reversing declines in regulating services. However, negative impacts on biodiversity due to climate change appear poised to increase, particularly in the higher-emissions scenarios. Our assessment identifies remaining modeling uncertainties but also robustly shows that renewed policy efforts are needed to meet the goals of the Convention on Biological Diversity.

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., (© 2022 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.)

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., Competing Interests: The authors declare no competing interest.

Competing Interests: The authors declare no competing interest.

Reducing the rate of global biodiversity loss is a major challenge facing humanity 1 , as the consequences of biological annihilation would be irreversible for humankind 2-4 . Although the ongoing degradation of ecosystems 5,6 and the extinction of species that comprise them 7,8 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 value 9,10 , 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 loss 10 , these areas urgently require targeted protection to ensure the long-term persistence of biodiversity, alongside efforts to protect and restore more-degraded environments.

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., (© 2019 John Wiley & Sons Ltd.)

To date Paralytic shellfish toxin (PST) variants in cyanobacteria have primarily been characterized using high performance liquid chromatography coupled with fluorescence detection. In this study we re-evaluated the PST profiles of five cyanobacterial cultures (Dolichospermum circinale AWQC131C, Aphanizomenon sp. NH-5, Raphidiopsis raciborskii T3, Scytonema cf. crispum CAWBG524 and CAWBG72) and one environmental sample (Microseria wollei) using hydrophilic interaction liquid chromatography coupled with electrospray ionization tandem mass spectrometry. A total of 35 different PST variants were detected. D. circinale contained the highest number of variants (23), followed by S. cf. crispum CAWBG72 (21). Many of the variants detected in the cultures/environmental sample had not been reported from these strains previously: D. circinale (14 variants), S. cf. crispum CAWBG72 (16), S. cf. crispum CAWBG524 (9), Aphanizomenon sp. (9), R. raciborskii (7), and M. wollei (7). Of particular interest was the detection of M-toxins (Aphanizomenon sp., R. raciborskii, D. circinale). These have previously only been identified from shellfish where they were thought to be metabolites. Well-characterized PST variant profiles are essential for research investigating the genetic basis of PST production, and given that the toxicity of each variants differs, it will assist in refining risk assessments., (Copyright © 2018. Published by Elsevier Ltd.)

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., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

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 (β- 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.

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., (© 2012 Blackwell Publishing Ltd.)

In response to climate change and other threatening processes there is renewed interest in the role of refugia and refuges. In bioregions that experience drought and fire, micro-refuges can play a vital role in ensuring the persistence of species. We develop and apply an approach to identifying potential micro-refuges based on a time series of remotely sensed vegetation greenness (fraction of photosynthetically active radiation intercepted by the sunlit canopy; fPAR). The primary data for this analysis were NASA MODIS 16-day L3 Global 250 m (MOD13Q1) satellite imagery. This method draws upon relevant ecological theory (source sink habitats, habitat templet) to calculate a micro-refuge index, which is analyzed for each of the major vegetation ecosystems in the case-study region (the Great Eastern Ranges of New South Wales, Australia). Potential ecosystem greenspots were identified, at a range of thresholds, based on an index derived from: the mean and coefficient of variance (COV) of fPAR over the 10-year time series; the minimum mean annual fPAR; and the COV of the 12 values of mean monthly fPAR. These greenspots were mapped and compared with (1) an index of vascular plant species composition, (2) environmental variables, and (3) protected areas. Potential micro-refuges were found within all vegetation ecosystem types. The total area of ecosystem greenspots within the upper 25% threshold was 48 406 ha; around 0.2% of the total area of native vegetation (23.9 x 10(6) ha) in the study region. The total area affected by fire was 3.4 x 10(6) ha. The results of the environmental diagnostic analysis suggest deterministic controls on the geographical distribution of potential micro-refuges that may continue to function under climate change. The approach is relevant to other regions of the world where the role of micro-refuges in the persistence of species is recognized, including across the world's arid zones and, in particular, for the Australian, southern African, and South American continents. Micro-refuge networks may play an important role in maintaining beta-diversity at the bio-region scale and contribute to the stability, resilience, and adaptive capacity of ecosystems in the face of ever-growing pressures from human-forced climate change, land use, and other threatening processes.

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 β-diversity) over space can help overcome this shortfall in our knowledge, yet individually, predictions of α- or β-diversity have their limitations. In this study, we present a novel approach to combining models of α- and β-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., (© 2011 Blackwell Publishing Ltd/CNRS.)

Models of windblown pollen or spore movement are required to predict gene flow from genetically modified (GM) crops and the spread of fungal diseases. We suggest a simple form for a function describing the distance moved by a pollen grain or fungal spore, for use in generic models of dispersal. The function has power-law behaviour over sub-continental distances. We show that air-borne dispersal of rapeseed pollen in two experiments was inconsistent with an exponential model, but was fitted by power-law models, implying a large contribution from distant fields to the catches observed. After allowance for this 'background' by applying Fourier transforms to deconvolve the mixture of distant and local sources, the data were best fit by power-laws with exponents between 1.5 and 2. We also demonstrate that for a simple model of area sources, the median dispersal distance is a function of field radius and that measurement from the source edge can be misleading. Using an inverse-square dispersal distribution deduced from the experimental data and the distribution of rapeseed fields deduced by remote sensing, we successfully predict observed rapeseed pollen density in the city centres of Derby and Leicester (UK).