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The 196 parties to the Convention on Biological Diversity (CBD) will soon agree to a post-2020 global framework for conserving the three elements of biodiversity (genetic, species, and ecosystem diversity) while ensuring sustainable development and benefit sharing. As the most significant global conservation policy mechanism, the new CBD framework has far-reaching consequences- it will guide conservation actions and reporting for each member country until 2050. In previous CBD strategies, as well as other major conservation policy mechanisms, targets and indicators for genetic diversity (variation at the DNA level within species, which facilitates species adaptation and ecosystem function) were undeveloped and focused on species of agricultural relevance. We assert that, to meet global conservation goals, genetic diversity within all species, not just domesticated species and their wild relatives, must be conserved and monitored using appropriate metrics. Building on suggestions in a recent Letter in Science (Laikre et al., 2020) we expand argumentation for three new, pragmatic genetic indicators and modifications to two current indicators for maintaining genetic diversity and adaptive capacity of all species, and provide guidance on their practical use. The indicators are: 1) the number of populations with effective population size above versus below 500, 2) the proportion of populations maintained within species, 3) the number of species and populations in which genetic diversity is monitored using DNA-based methods. We also present and discuss Goals and Action Targets for post-2020 biodiversity conservation which are connected to these indicators and underlying data. These pragmatic indicators and goals have utility beyond the CBD; they should benefit conservation and monitoring of genetic diversity via national and global policy for decades to come. ; Supplementary material: Tables S1 and S2 and Fig. S1 compile estimates of Ne/Nc from several reviews and new data. ; The EU Framework Horizon 2020 through the ...

International audience ; Livestock conservation practice is changing rapidly in light of policy developments, climate change and diversifying market demands. The last decade has seen a step change in technology and analytical approaches available to define, manage and conserve Farm Animal Genomic Resources (FAnGR). However, these rapid changes pose challenges for FAnGR conservation in terms of technological continuity, analytical capacity and integrative methodologies needed to fully exploit new, multidimensional data. The final conference of the ESF Genomic Resources program aimed to address these interdisciplinary problems in an attempt to contribute to the agenda for research and policy development directions during the coming decade. By 2020, according to the Convention on Biodiversity's Aichi Target 13, signatories should ensure that the genetic diversity of .farmed and domesticated animals and of wild relatives .is maintained, and strategies have been developed and implemented for minimizing genetic erosion and safeguarding their genetic diversity." However, the real extent of genetic erosion is very difficult to measure using current data Therefore, this challenging target demands better coverage, understanding and utilization of genomic and environmental data, the development of optimized ways to integrate these data with social and other sciences and policy analysis to enable more flexible, evidence based models to underpin FAnGR conservation. At the conference, we attempted to identify the most important problems for effective livestock genomic resource conservation during the next decade. Twenty priority questions were identified that could be broadly categorized into challenges related to methodology, analytical approaches, data management and conservation. It should be acknowledged here that while the focus of our meeting was predominantly around genetics, genomics and animal science, many of the practical challenges facing conservation of genomic resources are societal in origin and are predicated on the value (e.g., socio-economic and cultural) of these resources to farmers, rural communities and society as a whole. The overall conclusion is that despite the fact that the livestock sector has been relatively well-organized in the application of genetic methodologies to date, there is still a large gap between the current state-of-the-art in the use of tools to characterize genomic resources and its application to many non-commercial and local breeds, hampering the consistent utilization of genetic and genomic data as indicators of genetic erosion and diversity. The livestock genomic sector therefore needs to make a concerted effort in the coming decade to enable to the democratization of the powerful tools that are now at its disposal, and to ensure that they are applied in the context of breed conservation as well as development.

Only five species of the once-diverse Rhinocerotidae remain, making the reconstruction of their evolutionary history a challenge to biologists since Darwin. We sequenced genomes from five rhinoceros species (three extinct and two living), which we compared to existing data from the remaining three living species and a range of outgroups. We identify an early divergence between extant African and Eurasian lineages, resolving a key debate regarding the phylogeny of extant rhinoceroses. This early Miocene (∼16 million years ago [mya]) split post-dates the land bridge formation between the Afro-Arabian and Eurasian landmasses. Our analyses also show that while rhinoceros genomes in general exhibit low levels of genome-wide diversity, heterozygosity is lowest and inbreeding is highest in the modern species. These results suggest that while low genetic diversity is a long-term feature of the family, it has been particularly exacerbated recently, likely reflecting recent anthropogenic-driven population declines. ; The authors acknowledge support from the Science for Life Laboratory, the Garvan Institute of Medical Research, the Knut and Alice Wallenberg Foundation, and the National Genomics Infrastructure funded by the Swedish Research Council and Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We thank the Natural History Museum at the University of Oslo for providing the Javan rhinoceros sample. We thank the Museum of the Institute of Plant and Animal Ecology (UB RAS, Ekaterinburg) for providing the sample of Siberian unicorn. M.T.P.G. was supported by European Research Council (ERC) Consolidator grant 681396 (Extinction Genomics). E.D.L. was supported by Independent Research Fund Denmark grant 8021-00218B. A.C. was supported by an Australian Research Council Laureate Fellowship (FL140100260). T.M.B. is supported by funding from the ERC under the European Union's Horizon 2020 research and innovation program (grant agreement 864203), grant BFU2017-86471-P (MINECO/FEDER, UE), "Unidad de Excelencia María de Maeztu" funded by the AEI (CEX2018-000792-M), Howard Hughes International Early Career, and Secretaria d'Universitats i Recerca and CERCA Programme del Departament d'Economia i Coneixement de la Generalitat de Catalunya (GRC 2017 SGR 880). L.D. was supported by the Swedish Research Council (2017-04647) and Formas (2018-01640). ; With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2018-000792-M). ; Peer reviewed