An integrated high-resolution mapping shows congruent biodiversity patterns of Fagales and Pinales.

The documentation of biodiversity distribution through species range identification is crucial for macroecology, biogeography, conservation, and restoration. However, for plants, species range maps remain scarce and often inaccurate. We present a novel approach to map species ranges at a global scale, integrating polygon mapping and species distribution modelling (SDM). We develop a polygon mapping algorithm by considering distances and nestedness of occurrences. We further apply an SDM approach considering multiple modelling algorithms, complexity levels, and pseudo-absence selections to map the species at a high spatial resolution and intersect it with the generated polygons. We use this approach to construct range maps for all 1957 species of Fagales and Pinales with data compilated from multiple sources. We construct high-resolution global species richness maps of these important plant clades, and document diversity hotspots for both clades in southern and south-western China, Central America, and Borneo. We validate the approach with two representative genera, Quercus and Pinus, using previously published coarser range maps, and find good agreement. By efficiently producing high-resolution range maps, our mapping approach offers a new tool in the field of macroecology for studying global species distribution patterns and supporting ongoing conservation efforts.

Scanning amplicons with CRISPR-Dx detects endangered amphibians in environmental DNA.

More efficient methods for extensive biodiversity monitoring are required to support rapid measures to address the biodiversity crisis. While environmental DNA (eDNA) metabarcoding and quantitative PCR (qPCR) methods offer advantages over traditional monitoring approaches, their large-scale application is limited by the time and labour required for developing assays and/or for analysis. CRISPR (clustered regularly interspaced short palindromic repeats) diagnostic technologies (Dx) may overcome some of these limitations, but they have been used solely with species-specific primers, restricting their versatility for biodiversity monitoring. Here, we demonstrate the feasibility of designing species-specific CRISPR-Dx assays in silico within a short metabarcoding fragment using a general primer set, a methodology we term 'ampliscanning', for 18 of the 22 amphibian species in Switzerland. We sub-selected nine species, including three classified as regionally endangered, to test the methodology using eDNA sampled from ponds at nine sites. We compared the ampliscanning detections to data from traditional monitoring at these sites. Ampliscanning was successful at detecting target species with different prevalences across the landscape. With only one visit, we detected more species per site than three traditional monitoring visits (visual and acoustic detections by trained experts), in particular more elusive species and previously undocumented but expected populations. Ampliscanning detected 25 species/site combinations compared to 12 with traditional monitoring. Sensitivity analyses showed that larger numbers of field visits and PCR replicates are more important for reliable detection than many technical replicates at the CRISPR-Dx assay level. Given the reduced sampling and analysis effort, our results highlight the benefits of eDNA and CRISPR-Dx combined with universal primers for large-scale monitoring of multiple endangered species across landscapes to inform conservation measures.

Harnessing paleo-environmental modeling and genetic data to predict intraspecific genetic structure.

Spatially explicit simulations of gene flow within complex landscapes could help forecast the responses of populations to global and anthropological changes. Simulating how past climate change shaped intraspecific genetic variation can provide a validation of models in anticipation of their use to predict future changes. We review simulation models that provide inferences on population genetic structure. Existing simulation models generally integrate complex demographic and genetic processes but are less focused on the landscape dynamics. In contrast to previous approaches integrating detailed demographic and genetic processes and only secondarily landscape dynamics, we present a model based on parsimonious biological mechanisms combining habitat suitability and cellular processes, applicable to complex landscapes. The simulation model takes as input (a) the species dispersal capacities as the main biological parameter, (b) the species habitat suitability, and (c) the landscape structure, modulating dispersal. Our model emphasizes the role of landscape features and their temporal dynamics in generating genetic differentiation among populations within species. We illustrate our model on caribou/reindeer populations sampled across the entire species distribution range in the Northern Hemisphere. We show that simulations over the past 21 kyr predict a population genetic structure that matches empirical data. This approach looking at the impact of historical landscape dynamics on intraspecific structure can be used to forecast population structure under climate change scenarios and evaluate how species range shifts might induce erosion of genetic variation within species.