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Online digital data from media platforms have the potential to complement biodiversity monitoring efforts. We propose a strategy for integrating these data into current biodiversity datasets in light of the Kunming-Montreal Global Biodiversity Framework., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Soriano-Redondo 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.)

As the number of observations submitted to the citizen science platform iNaturalist continues to grow, it is increasingly important that these observations can be identified to the finest taxonomic level, maximizing their value for biodiversity research. Here, we explore the benefits of acting as an identifier on iNaturalist., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Accurate maps of species ranges are essential to inform conservation, but time-consuming to produce and update. Given the pace of change of knowledge about species distributions and shifts in ranges under climate change and land use, a need exists for timely mapping approaches that enable batch processing employing widely available data. We develop a systematic approach of batch-processing range maps and derived Area of Habitat maps for terrestrial bird species with published ranges below 125,000 km2 in Central and South America. (Area of Habitat is the habitat available to a species within its range.) We combine existing range maps with the rapidly expanding crowd-sourced eBird data of presences and absences from frequently surveyed locations, plus readily accessible, high resolution satellite data on forest cover and elevation to map the Area of Habitat available to each species. Users can interrogate the maps produced to see details of the observations that contributed to the ranges. Previous estimates of Areas of Habitat were constrained within the published ranges and thus were, by definition, smaller-typically about 30%. This reflects how little habitat within suitable elevation ranges exists within the published ranges. Our results show that on average, Areas of Habitat are 12% larger than published ranges, reflecting the often-considerable extent that eBird records expand the known distributions of species. Interestingly, there are substantial differences between threatened and non-threatened species. Some 40% of Critically Endangered, 43% of Endangered, and 55% of Vulnerable species have Areas of Habitat larger than their published ranges, compared with 31% for Near Threatened and Least Concern species. The important finding for conservation is that threatened species are generally more widespread than previously estimated., Competing Interests: The authors have declared that no competing interests exist. The views expressed in this publication do not necessarily reflect those of IUCN.

Knowledge products comprise assessments of authoritative information supported by standards, governance, quality control, data, tools, and capacity building mechanisms. Considerable resources are dedicated to developing and maintaining knowledge products for biodiversity conservation, and they are widely used to inform policy and advise decision makers and practitioners. However, the financial cost of delivering this information is largely undocumented. We evaluated the costs and funding sources for developing and maintaining four global biodiversity and conservation knowledge products: The IUCN Red List of Threatened Species, the IUCN Red List of Ecosystems, Protected Planet, and the World Database of Key Biodiversity Areas. These are secondary data sets, built on primary data collected by extensive networks of expert contributors worldwide. We estimate that US$160 million (range: US$116-204 million), plus 293 person-years of volunteer time (range: 278-308 person-years) valued at US$ 14 million (range US$12-16 million), were invested in these four knowledge products between 1979 and 2013. More than half of this financing was provided through philanthropy, and nearly three-quarters was spent on personnel costs. The estimated annual cost of maintaining data and platforms for three of these knowledge products (excluding the IUCN Red List of Ecosystems for which annual costs were not possible to estimate for 2013) is US$6.5 million in total (range: US$6.2-6.7 million). We estimated that an additional US$114 million will be needed to reach pre-defined baselines of data coverage for all the four knowledge products, and that once achieved, annual maintenance costs will be approximately US$12 million. These costs are much lower than those to maintain many other, similarly important, global knowledge products. Ensuring that biodiversity and conservation knowledge products are sufficiently up to date, comprehensive and accurate is fundamental to inform decision-making for biodiversity conservation and sustainable development. Thus, the development and implementation of plans for sustainable long-term financing for them is critical.

The world's governments have committed to preventing the extinction of threatened species and improving their conservation status by 2020. However, biodiversity is not evenly distributed across space, and neither are the drivers of its decline, and so different regions face very different challenges. Here, we quantify the contribution of regions and countries towards recent global trends in vertebrate conservation status (as measured by the Red List Index), to guide action towards the 2020 target. We found that>50% of the global deterioration in the conservation status of birds, mammals and amphibians is concentrated in <1% of the surface area, 39/1098 ecoregions (4%) and eight/195 countries (4%) - Australia, China, Colombia, Ecuador, Indonesia, Malaysia, Mexico, and the United States. These countries hold a third of global diversity in these vertebrate groups, partially explaining why they concentrate most of the losses. Yet, other megadiverse countries - most notably Brazil (responsible for 10% of species but just 1% of deterioration), plus India and Madagascar - performed better in conserving their share of global vertebrate diversity. Very few countries, mostly island nations (e.g. Cook Islands, Fiji, Mauritius, Seychelles, and Tonga), have achieved net improvements. Per capita wealth does not explain these patterns, with two of the richest countries - United States and Australia - fairing conspicuously poorly. Different countries were affected by different combinations of threats. Reducing global rates of biodiversity loss will require investment in the regions and countries with the highest responsibility for the world's biodiversity, focusing on conserving those species and areas most in peril and on reducing the drivers with the highest impacts.