Human pressures on the ocean are thought to be increasing globally, yet we know little about their patterns of cumulative change, which pressures are most responsible for change, and which places are experiencing the greatest increases. Managers and policymakers require such information to make strategic decisions and monitor progress towards management objectives. Here we calculate and map recent change over 5 years in cumulative impacts to marine ecosystems globally from fishing, climate change, and ocean- and land-based stressors. Nearly 66% of the ocean and 77% of national jurisdictions show increased human impact, driven mostly by climate change pressures. Five percent of the ocean is heavily impacted with increasing pressures, requiring management attention. Ten percent has very low impact with decreasing pressures. Our results provide large-scale guidance about where to prioritize management efforts and affirm the importance of addressing climate change to maintain and improve the condition of marine ecosystems.
Abstract:The Caribbean Islands Biodiversity Hotspot is exceptionally important for global biodiversity conservation due to high levels of species endemism and threat. A total of 755 Caribbean plant and vertebrate species are considered globally threatened, making it one of the top Biodiversity Hotspots in terms of threat levels. In 2009, Key Biodiversity Areas (KBAs) were identified for the Caribbean Islands through a regionallevel analysis of accessible data and literature, followed by extensive national-level stakeholder consultation. By applying the Vulnerability criterion, a total of 284 Key Biodiversity Areas were defined and mapped as holding 409 (54%) of the region's threatened species. Of these, 144 (or 51%) overlapped partially or completely with protected areas. Cockpit Country, followed by Litchfield Mountain -Matheson's Run, Blue Mountains (all Jamaica) and Massif de la Hotte (Haiti) were found to support exceptionally high numbers of globally threatened taxa, with more than 40 such species at each site. Key Biodiversity Areas, building from Important Bird Areas, provide a valuable framework against which to review the adequacy of existing national protectedarea systems and also to prioritize which species and sites require the most urgent conservation attention.
The importance of ecosystems for supporting human well-being is increasingly recognized by both the conservation and development sectors. Our ability to conserve ecosystems that people rely on is often limited by a lack of spatially explicit data on the location and distribution of ecosystem services (ES), the benefits provided by nature to people. Thus there is a need to map ES to guide conservation investments, to ensure these co-benefits are maintained. To target conservation investments most effectively, ES assessments must be rigorous enough to support conservation planning, rapid enough to respond to decision-making timelines, and often must rely on existing data. We developed a framework for rapid spatial assessment of ES that relies on expert and stakeholder consultation, available data, and spatial analyses in order to rapidly identify sites providing multiple benefits. We applied the framework in Madagascar, a country with globally significant biodiversity and a high level of human dependence on ecosystems. Our objective was to identify the ES co-benefits of biodiversity priority areas in order to guide the investment strategy of a global conservation fund. We assessed key provisioning (fisheries, hunting and non-timber forest products, and water for domestic use, agriculture, and hydropower), regulating (climate mitigation, flood risk reduction and coastal protection), and cultural (nature tourism) ES. We also conducted multi-criteria analyses to identify sites providing multiple benefits. While our approach has limitations, including the reliance on proximity-based indicators for several ES, the results were useful for targeting conservation investments by the Critical Ecosystem Partnership Fund (CEPF). Because our approach relies on available data, standardized methods for linking ES provision to ES use, and expert validation, it has the potential to quickly guide conservation planning and investment decisions in other data-poor regions.
The coffee sector is working towards sector-wide commitments for sustainable production. Yet, knowledge of where coffee is cultivated and its environmental impact remains limited, in part due to the challenges of mapping coffee using satellite remote sensing. We recognize the urgency to capitalize on recent technological advances to improve remote sensing methods and generate more accurate, reliable, and scalable approaches to coffee mapping. In this study, we provide a systematic review of satellite-based approaches to mapping coffee extent, which produced 43 articles in the peer-reviewed and gray literature. We outline key considerations for employing effective approaches, focused on the need to balance data affordability and quality, classification complexity and accuracy, and generalizability and site-specificity. We discuss research opportunities for improved approaches by leveraging the recent expansion of diverse satellite sensors and constellations, optical/Synthetic Aperture Radar data fusion approaches, and advances in cloud computing and deep learning algorithms. We highlight the need for differentiating between production systems and the need for research in important coffee-growing geographies. By reviewing the range of techniques successfully used to map coffee extent, we provide technical recommendations and future directions to enable accurate and scalable coffee maps.
Demand-side restrictions on high-deforestation commodities are expanding as a climate policy, but their impact on reducing tropical deforestation and emissions has yet to be quantified. Here we model the effects of demand-side restrictions on high-deforestation palm oil in Europe on deforestation and emissions in Indonesia. We do so by integrating a model of global trade with a spatially explicit model of land-use change in Indonesia. We estimate a European ban on high-deforestation palm oil from 2000–2015 would have led to a 8.9% global price premium on low-deforestation palm oil, resulting in 21,374 ha/yr (1.60%) less deforestation and 21.1 million tCO2/yr (1.91%) less emissions from deforestation in Indonesia relative to what occurred. A hypothetical Indonesia-wide carbon price would have achieved equivalent emission reductions at $0.81/tCO2. Impacts of a ban are small because: 52% of Europe’s imports of high-deforestation palm oil would have shifted to non-participating countries; the price elasticity of supply of high-deforestation oil palm cropland is small (0.13); and conversion to oil palm was responsible for only 32% of deforestation in Indonesia. If demand-side restrictions succeed in substantially reducing deforestation, it is likely to be through non-price pathways.
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