Multinational evaluation of genetic diversity indicators for the Kunming-Montreal Global Biodiversity Framework.

Under the recently adopted Kunming-Montreal Global Biodiversity Framework, 196 Parties committed to reporting the status of genetic diversity for all species. To facilitate reporting, three genetic diversity indicators were developed, two of which focus on processes contributing to genetic diversity conservation: maintaining genetically distinct populations and ensuring populations are large enough to maintain genetic diversity. The major advantage of these indicators is that they can be estimated with or without DNA-based data. However, demonstrating their feasibility requires addressing the methodological challenges of using data gathered from diverse sources, across diverse taxonomic groups, and for countries of varying socio-economic status and biodiversity levels. Here, we assess the genetic indicators for 919 taxa, representing 5271 populations across nine countries, including megadiverse countries and developing economies. Eighty-three percent of the taxa assessed had data available to calculate at least one indicator. Our results show that although the majority of species maintain most populations, 58% of species have populations too small to maintain genetic diversity. Moreover, genetic indicator values suggest that IUCN Red List status and other initiatives fail to assess genetic status, highlighting the critical importance of genetic indicators.

SoilTemp: A global database of near-surface temperature.

Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

Ex situ conservation of two rare oak species using microsatellite and SNP markers.

Plant collections held by botanic gardens and arboreta are key components of ex situ conservation. Maintaining genetic diversity in such collections allows them to be used as resources for supplementing wild populations. However, most recommended minimum sample sizes for sufficient ex situ genetic diversity are based on microsatellite markers, and it remains unknown whether these sample sizes remain valid in light of more recently developed next-generation sequencing (NGS) approaches. To address this knowledge gap, we examine how ex situ conservation status and sampling recommendations differ when derived from microsatellites and single nucleotide polymorphisms (SNPs) in garden and wild samples of two threatened oak species. For Quercus acerifolia, SNPs show lower ex situ representation of wild allelic diversity and slightly lower minimum sample size estimates than microsatellites, while results for each marker are largely similar for Q. boyntonii. The application of missing data filters tends to lead to higher ex situ representation, while the impact of different SNP calling approaches is dependent on the species being analyzed. Measures of population differentiation within species are broadly similar between markers, but larger numbers of SNP loci allow for greater resolution of population structure and clearer assignment of ex situ individuals to wild source populations. Our results offer guidance for future ex situ conservation assessments utilizing SNP data, such as the application of missing data filters and the usage of a reference genome, and illustrate that both microsatellites and SNPs remain viable options for botanic gardens and arboreta seeking to ensure the genetic diversity of their collections.

AREAdata: A worldwide climate dataset averaged across spatial units at different scales through time.

In an era of increasingly cross-discipline collaborative science, it is imperative to produce data resources which can be quickly and easily utilised by non-specialists. In particular, climate data often require heavy processing before they can be used for analyses. Here we describe AREAdata, a continually updated, free-to-use online global climate dataset, pre-processed to provide the averages of various climate variables across different administrative units (e.g., countries, states). These are daily estimates, based on the Copernicus Climate Data Store's ERA-5 data, regularly updated to the near-present and provided as direct downloads from our website (https://pearselab.github.io/areadata/). The daily climate estimates from AREAdata are consistent with other openly available data, but at much finer-grained spatial and temporal scales than available elsewhere. AREAdata complements the existing suite of climate resources by providing these data in a form more readily usable by researchers unfamiliar with GIS data-processing methods, and we anticipate these resources being of particular use to environmental and epidemiological researchers.