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Trade represents a significant threat to many wild species and is often clandestine and poorly monitored. Information on which species are most prevalent in trade and potentially threatened by it therefore remains fragmentary. We used 7 global data sets on birds in trade to identify species or groups of species at particular risk and assessed the extent to which they were congruent in terms of the species recorded in trade. We used the frequency with which species were recorded in the data sets as the basis for a trade prevalence score that was applied to all bird species globally. Literature searches and questionnaire surveys were used to develop a list of species known to be heavily traded to validate the trade prevalence score. The score was modeled to identify significant predictors of trade. Although the data sets sampled different parts of the broad trade spectrum, congruence among them was statistically strong in all comparisons. Furthermore, the frequency with which species were recorded within data sets was positively correlated with their occurrence across data sets, indicating that the trade prevalence score captured information on trade volume. The trade prevalence score discriminated well between species identified from semi-independent assessments as heavily or unsustainably traded and all other species. Globally, 45.1% of all bird species and 36.7% of globally threatened bird species had trade prevalence scores ≥1. Species listed in Appendices I or II of CITES, species with large geographical distributions, and nonpasserines tended to have high trade prevalence scores. Speciose orders with high mean trade prevalence scores included Falconiformes, Psittaciformes, Accipitriformes, Anseriformes, Bucerotiformes, and Strigiformes. Despite their low mean prevalence score, Passeriformes accounted for the highest overall number of traded species of any order but had low representation in CITES appendices. Geographical hotspots where large numbers of traded species co-occur differed among passerines (Southeast Asia and Eurasia) and nonpasserines (central South America, sub-Saharan Africa, and India). This first attempt to quantify and map the relative prevalence in trade of all bird species globally can be used to identify species and groups of species that may be at particular risk of harm from trade and can inform conservation and policy interventions to reduce its adverse impacts., (© 2024 The Author(s). Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.)

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., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)