Mapping the planet’s critical natural assets

Sustaining the organisms, ecosystems and processes that underpin human wellbeing is necessary to achieve sustainable development. Here we define critical natural assets as the natural and semi-natural ecosystems that provide 90% of the total current magnitude of 14 types of nature’s contributions to people (NCP), and we map the global locations of these critical natural assets at 2 km resolution. Critical natural assets for maintaining local-scale NCP (12 of the 14 NCP) account for 30% of total global land area and 24% of national territorial waters, while 44% of land area is required to also maintain two global-scale NCP (carbon storage and moisture recycling). These areas overlap substantially with cultural diversity (areas containing 96% of global languages) and biodiversity (covering area requirements for 73% of birds and 66% of mammals). At least 87% of the world’s population live in the areas benefitting from critical natural assets for local-scale NCP, while only 16% live on the lands containing these assets. Many of the NCP mapped here are left out of international agreements focused on conserving species or mitigating climate change, yet this analysis shows that explicitly prioritizing critical natural assets and the NCP they provide could simultaneously advance development, climate and conservation goals.We thank all the participants of two working groups hosted by Conservation International and the Natural Capital Project for their insights and intellectual contributions. For further advice or assistance, we thank A. Adams, K. Brandon, K. Brauman, A. Cramer, G. Daily, J. Fisher, R. Gould, L. Mandle, J. Montgomery, A. Rodewald, D. Rossiter, E. Selig, A. Vogl and T. M. Wright. The two working groups that provided the foundation for this analysis were funded by support from the Marcus and Marianne Wallenberg Foundation to the Natural Capital Project (R.C.-K. and R.P.S.) and the Betty and Gordon Moore to Conservation International (R.A.N. and P.M.C.)

GCM compareR: A web application to assess differences and assist in the selection of general circulation models for climate change research

Climate change research often relies on downscaled general circulation models (GCM), projections of future scenarios that are used to build ecological and evolutionary models. With more than 35 different GCMs widely available at a resolution of 10 km and finer, standardized methods to understand the differences among GCM projections in a region of interest and to choose which GCM to use for analysis are essential to maximize relevance to policy and to assure a proper treatment of uncertainty. To help researchers and policymakers understand and select form the range of available GCM scenarios, we have developed GCM compareR, an open-source web application written in r using shiny. GCM compareR is freely accessible with an easy interactive user interface, has preloaded climate scenario data to increase the speed of analysis and is fully documented to ensure reproducibility. Users of the application need no prior experience in coding. GCM compareR is designed to compare GCMs and different climate change scenarios to provide full, documented exploration of the possible alternative futures from within the range of projections in CMIP5 climate models. Designed with a wide group of users in mind, including ecologists, conservationists and policymakers, the application is designed to adapt analyses to any geographic area of interest. Results are provided as figures, tables and maps that clearly communicate the differences among model projections for the region. Additionally, the tool allows for the export of a report that records the parameter choices and results of a session, along with contextual information, to make the analysis fully transparent and replicable

Geographic name resolution service: A tool for the standardization and indexing of world political division names, with applications to species distribution modeling

Massive biological databases of species occurrences, or georeferenced locations where a species has been observed, are essential inputs for modeling present and future species distributions. Location accuracy is often assessed by determining whether the observation geocoordinates fall within the boundaries of the declared political divisions. This otherwise simple validation is complicated by the difficulty of matching political division names to the correct geospatial object. Spelling errors, abbreviations, alternative codes, and synonyms in multiple languages present daunting name disambiguation challenges. The inability to resolve political division names reduces usable data, and analysis of erroneous observations can lead to flawed results. Here, we present the Geographic Name Resolution Service (GNRS), an application for correcting, standardizing, and indexing world political division names. The GNRS resolves political division names against a reference database that combines names and codes from GeoNames with geospatial object identifiers from the Global Administrative Areas Database (GADM). In a trial resolution of political division names extracted from >270 million species occurrences, only 1.9%, representing just 6% of occurrences, matched exactly to GADM political divisions in their original form. The GNRS was able to resolve, completely or in part, 92% of the remaining 378,568 political division names, or 86% of the full biodiversity occurrence dataset. In assessing geocoordinate accuracy for >239 million species occurrences, resolution of political divisions by the GNRS enabled the detection of an order of magnitude more errors and an order of magnitude more error-free occurrences. By providing a novel solution to a significant data quality impediment, the GNRS liberates a tremendous amount of biodiversity data for quantitative biodiversity research. The GNRS runs as a web service and is accessible via an API, an R package, and a web-based graphical user interface. Its modular architecture is easily integrated into existing data validation workflows. Copyright: © 2022 Boyle et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

How deregulation, drought and increasing fire impact Amazonian biodiversity

Biodiversity contributes to the ecological and climatic stability of the Amazon Basin, but is increasingly threatened by deforestation and fire. Here we quantify these impacts over the past two decades using remote-sensing estimates of fire and deforestation and comprehensive range estimates of 11,514 plant species and 3,079 vertebrate species in the Amazon. Deforestation has led to large amounts of habitat loss, and fires further exacerbate this already substantial impact on Amazonian biodiversity. Since 2001, 103,079–189,755 km2 of Amazon rainforest has been impacted by fires, potentially impacting the ranges of 77.3–85.2% of species that are listed as threatened in this region. The impacts of fire on the ranges of species in Amazonia could be as high as 64%, and greater impacts are typically associated with species that have restricted ranges. We find close associations between forest policy, fire-impacted forest area and their potential impacts on biodiversity. In Brazil, forest policies that were initiated in the mid-2000s corresponded to reduced rates of burning. However, relaxed enforcement of these policies in 2019 has seemingly begun to reverse this trend: approximately 4,253–10,343 km2 of forest has been impacted by fire, leading to some of the most severe potential impacts on biodiversity since 2009. These results highlight the critical role of policy enforcement in the preservation of biodiversity in the Amazon

Conservation needs to integrate knowledge across scales

International audienc

Areas of global importance for conserving terrestrial biodiversity, carbon and water

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