Bending the curve of terrestrial biodiversity needs an integrated strategy Summary paragraph Increased efforts are required to prevent further losses of terrestrial biodiversity and the ecosystem services it provides 1,2. Ambitious targets have been proposed, such as reversing the declining trends in biodiversity 3-yet, just feeding the growing human population will make this a challenge 4. We use an ensemble of land-use and biodiversity models to assess whether (and if so, how) humanity can reverse terrestrial biodiversity declines due to habitat conversion, a major threat to biodiversity 5. We show that immediate efforts, consistent with the broader sustainability agenda but of unprecedented ambition and coordination, may allow to feed the growing human population while reversing global terrestrial biodiversity trends from habitat conversion. If we decide to increase the extent of land under conservation management, restore degraded land, and generalize landscapelevel conservation planning, biodiversity trends from habitat conversion could become positive by mid-century on average across models (confidence interval: 2042-2061), but not for all models. Food prices could increase and, on average across models, almost half (confidence interval: 34-50%) of future biodiversity losses could not be avoided. However, additionally tackling the drivers of landuse change may avoid conflict with affordable food provision and reduces the food system's environmental impacts. Through further sustainable intensification and trade, reduced food waste, and healthier human diets, more than two thirds of future biodiversity losses are avoided and the biodiversity trends from habitat conversion are reversed by 2050 for almost all models. Although limiting further loss will remain challenging in several biodiversity-rich regions, and other threats, such as climate change, must be addressed to truly reverse biodiversity declines, our results show that bold conservation efforts and food system transformation are central to an effective post-2020 biodiversity strategy. Reversing biodiversity trends by 2050 Without further efforts to counteract habitat loss and degradation, we projected that global biodiversity will continue to decline (BASE scenario; Fig. 1). Rates of loss over time for all nine BDIs in 2010-2050 were close to or greater than those estimated for 1970-2010 (Extended data Extended Data Table 1). For various biodiversity aspects, on average across IAM and BDI combinations, peak losses over the 2010-2100 period were: 13% (range: 1-26%) for the extent of suitable habitat, 54% (range: 45-63%) for wildlife population density, 5% (range: 2-9%) for local compositional intactness , 4% (range: 1-12%) for global extinctions, and 4% (range: 2-8%) for regional extinctions (Extended Data Table 1). Percentage losses were greatest in biodiversity-rich regions (Sub-Saharan Africa, South Asia, South East Asia, the Caribbean and Latin America; Extended Data Fig. 2). The projected future trends for habitat loss and degradation and its driv...

Integrated high-resolution maps of carbon stocks and biodiversity that identify areas of potential co-benefits for climate change mitigation and biodiversity conservation can help facilitate the implementation of global climate and biodiversity commitments at local levels. However, the multi-dimensional nature of biodiversity presents a major challenge for understanding, mapping and communicating where and how biodiversity benefits coincide with climate benefits. A new integrated approach to biodiversity is therefore needed. Here, we (a) present a new high-resolution map of global above- and below-ground carbon stored in biomass and soil, (b) quantify biodiversity values using two complementary indices (BIp and BIr) representing proactive and reactive approaches to conservation, and (c) examine patterns of carbon–biodiversity overlap by identifying 'hotspots' (20% highest values for both aspects). Our indices integrate local diversity and ecosystem intactness, as well as regional ecosystem intactness across the broader area supporting a similar natural assemblage of species to the location of interest. The western Amazon Basin, Central Africa and Southeast Asia capture the last strongholds of highest local biodiversity and ecosystem intactness worldwide, while the last refuges for unique biological communities whose habitats have been greatly reduced are mostly found in the tropical Andes and central Sundaland. There is 38 and 5% overlap in carbon and biodiversity hotspots, for proactive and reactive conservation, respectively. Alarmingly, only around 12 and 21% of these proactive and reactive hotspot areas, respectively, are formally protected. This highlights that a coupled approach is urgently needed to help achieve both climate and biodiversity global targets. This would involve (1) restoring and conserving unprotected, degraded ecosystems, particularly in the Neotropics and Indomalaya, and (2) retaining the remaining strongholds of intactness. This article is part of the theme issue ‘Climate change and ecosystems: threats, opportunities and solutions’.

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 )), 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.

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.

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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).

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.