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Aim Many vertebrate species globally are dependent on forests, most of which require active protection to safeguard global biodiversity. Forests, however, are increasingly either being disturbed, planted or managed in the form of timber or food plantations. Because of a lack of spatial data, forest management has commonly been ignored in previous conservation assessments. Location Global. Methods We combine a new global map of forest management types created solely from remote sensing imagery with spatially explicit information on the distribution of forest-associated vertebrate species and protected areas globally. Using Bayesian logistic regressions, we explore whether the amount of forested habitat available to a species as well as information on species-specific threats can explain differences in IUCN extinction risk categories. Results We show that disturbed and human-managed forests dominate the distributional ranges of most forest-associated species. Species considered as non-threatened had on average larger amounts of non-managed forests within their range. A greater amount of planted forests did not decrease the probability of species being threatened by extinction. Even more worrying, protected areas are increasingly being established in areas dominated by disturbed forests. Conclusion Our results imply that species extinction risk and habitat assessments might have been overly optimistic with forest management practices being largely ignored so far. With forest restoration being at the centre of climate and conservation policies in this decade, we caution that policy makers should explicitly consider forest management in global and regional assessments.

Meeting Brazil’s ambitious national commitments on both climate change mitigation and biodiversity conservation depends on securing its reserves of forest carbon and biodiversity. Brazil’s ‘Forest Code’ is a key tool to reconcile environmental preservation and agricultural production; it limits deforestation and requires forest restoration in illegally deforested areas. However, not all provisions of the law’s 2012 revision have yet been implemented and some are facing new challenges. Using modelled land use change projections for the whole of the country, we show that full implementation and enforcement of the law has the potential to contribute to conserving biodiversity. Biodiversity outcomes will be especially positive if (i) deforested areas are restored in ways that support recolonization by native species and (ii) additional measures are implemented to protect native vegetation in areas like Caatinga dry forests and Cerrado savannas, which may experience added pressure displaced from other regions by Forest Code implementation.

To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature’s contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions.

This short communication presents an ecosystem assessment framework developed within ESMERALDA; a Horizon2020-funded EU project aimed at delivering a ‘flexible methodology’ to assist towards pan-European and regional Mapping and Assessment of Ecosystem Services (MAES). The framework we present is closely aligned with assessment frameworks developed within the MAES (2014) and Millennium Ecosystem Assessment (2010) initiatives. Mapping, fundamental to the work of MAES as well as ESMERALDA, is placed at the heart of a wider suite of activities carried out within ecosystem assessment. This enables flexibility in where and how integration takes place. Beyond the biophysical parameters at the core of the framework, emphasis is given to the inclusion of social and economic factors to ensure policy relevance. Consultation, both internal to the ESMERALDA Consortium and external - amongst those already conducting ecosystem assessments across Europe - helped guide the development of the framework. Online consultation will provide information about the development of guidance around the framework and initiate the collation of good practice examples. The framework and accompanying guidance will contribute towards a final guidance tool due at the end of the ESMERALDA project lifetime.

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’.

The World Economic Forum now ranks biodiversity loss as a top-five risk to the global economy, and the draft post-2020 Global Biodiversity Framework proposes an expansion of conservation areas to 30% of the earth’s surface by 2030 (hereafter the “30% target”), using protected areas (PAs) and other effective area-based conservation measures (OECMs). Two immediate concerns are how much a 30% target might cost and whether it will cause economic losses to the agriculture, forestry and fisheries sectors. Conservation areas also generate economic benefits (e.g. revenue from nature tourism and ecosystem services), making PAs/Nature an economic sector in their own right. If some economic sectors benefit but others experience a loss, high-level policy makers need to know the net impact on the wider economy, as well as on individual sectors. The current report, based on the work of over 100 economists/scientists, analyses the global economic implications of a 30% PA target for agriculture, forestry, fisheries, and the PA/nature sector itself. (OECMs were only defined by the CBD in 2018, too recently to economically model, but we include a qualitative treatment of them.) We carried out two analyses: a global financial one (concrete revenues and costs only); and a tropics- focused economic one (including non-monetary ecosystem service values), for multiple scenarios of how a 30% PA target might be implemented. Our financial analysis showed that expanding PAs to 30% would generate higher overall output (revenues) than non-expansion (an extra $64 billion-$454 billion per year by 2050). (Figure 1-2). In the economic analysis, only a partial assessment was possible, focusing on forests and mangroves. For those biomes alone, the 30% target had an avoided-loss value of $170-$534 billion per year by 2050, largely reflecting the benefit of avoiding the flooding, climate change, soil loss and coastal storm- surge damage that occur when natural vegetation is removed. The value for all biomes would be higher. Implementing the proposal would therefore make little initial difference to total (multi-sector) economic output, although a modest rise in gross output value is projected. The main immediate difference between expansion and non-expansion is therefore in broader economic/social values. Expansion outperforms non-expansion in mitigating the very large economic risks of climate change and biodiversity loss (Figure 5). The 30% target would also increase by 63%- 98% the area recognised as Indigenous Peoples’ and local communities’ land-based nature stewardship contribution (within appropriate rights and governance frameworks). Economic growth in the PA/nature sector (at 4-6%) was also many times faster than the 1% growth expected in competing sectors (Figure 3). Marine expansion restores growth to fisheries (after a shock) but non-expansion leads to a mid-term contraction (Figure 4). The annual investment needed for an expanded (30%) PA system is $103 – $178 billion1. This figure includes $68 billion for the existing system, of which only $24.3 is currently spent. (Underfunded systems lose revenue, assets, carbon and biodiversity). Most of the investment need is in low- and middle-income countries (LMICs). These often have a competitive asset advantage in terms of natural areas, but they may need international support to capitalise on that opportunity. Otherwise, growing the PA sector could also entrench global economic inequalities. Benefits and costs also accrue to different stakeholders at smaller (e.g. local) scales, making welfare distribution a challenge that needs addressing.

Summary paragraphTo meet the ambitious objectives of biodiversity and climate conventions, countries and the international community require clarity on how these objectives can be operationalized spatially, and multiple targets be pursued concurrently1. To support governments and political conventions, spatial guidance is needed to identify which areas should be managed for conservation to generate the greatest synergies between biodiversity and nature’s contribution to people (NCP). Here we present results from a joint optimization that maximizes improvements in species conservation status, carbon retention and water provisioning and rank terrestrial conservation priorities globally. We found that, selecting the top-ranked 30% (respectively 50%) of areas would conserve 62.4% (86.8%) of the estimated total carbon stock and 67.8% (90.7%) of all clean water provisioning, in addition to improving the conservation status for 69.7% (83.8%) of all species considered. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to improve the conservation status of 86.3% of plant and vertebrate species on Earth. Our results provide a global baseline on where land could be managed for conservation. We discuss how such a spatial prioritisation framework can support the implementation of the biodiversity and climate conventions.

The use of environmental DNA (eDNA) is rapidly emerging as a potentially valuable survey technique for rare or hard to survey freshwater organisms. For the great crested newt (Triturus cristatus) in the UK, the substantial cost and manpower requirements of traditional survey methods have hampered attempts to assess the status of the species. We tested whether eDNA could provide the basis for a national citizen science-based monitoring programme for great crested newts by (i) comparing the effectiveness of eDNA monitoring with torch counts, bottle trapping and egg searches and (ii) assessing the ability of volunteers to collect eDNA samples throughout the newt’s UK range. In 35 ponds visited four times through the breeding season, eDNA detected newts on 139 out of 140 visits, a 99.3% detection rate. Bottle traps, torch counts and egg searches were significantly less effective, detecting newts 76%, 75% and 44% of the time. eDNA was less successful at predicting newt abundance being positively, but weakly, correlated with counts of the number of newts. Volunteers successfully collected eDNA samples across the UK with 219 of 239 sites (91.3%) correctly identified as supporting newts. 8.7% of sites generated false negatives, either because of very small newt populations or practical difficulties in sample collection. There were no false positives. Overall, we conclude that eDNA is a highly effective survey method and could be used as the basis for a national great crested newt monitoring programme.