Flurin Leugger

With accelerating biodiversity erosion, it is critical for species conservation to use rapid and scalable monitoring methods. One powerful biodiversity monitoring method that has emerged recently is environmental DNA (eDNA). eDNA analyses currently require lengthy protocols in well-equipped laboratories, slowing down the analyses and limiting applications across broad scales. Here, we developed a protocol for eDNA analyses, leveraging CRISPR-based diagnostic systems (Dx) with lateral flow tests to rapidly process and analyze eDNA samples on site. To test the versatility of the field-based protocol, we designed a CRISPR-Dx assay specific to the threatened and elusive African manatee (Trichechus senegalensis). We sampled water across ten locations in a national park in the Republic of Congo and detected manatee DNA directly on site in almost half of the sites. We later confirmed these detections with a high-sensitivity protocol in a well-equipped laboratory. The CRISPR-Dx detections were mainly confirmed with a previously reported quantitative PCR (qPCR) assay. Despite the lower sensitivity of the field-based protocol, our analysis shows that its speed and ease of application provide advantages over slower and more expensive methods to detect threatened and elusive species, in particular if the protocol is improved in the future. Our methodology will increase the accessibility to and speed of eDNA analyses, enhancing biodiversity monitoring efforts and species conservation initiatives.

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.

Aim: Understanding the drivers of species distribution ranges and population genetic structure can help predict species' responses to global change, while mitigating threats to biodiversity through effective conservation measures. Here, we combined species habitat suitability through time with process-based models and genomic data to investigate the role of landscape features and functional connectivity in shaping the population genetic structure of Northern chamois.
Location: European Alps.
Taxon: Northern chamois (Rupicapra rupicapra).
Methods: Using a model that simulates dispersal and tracks the functional connectivity of populations over dynamic landscapes, we modelled the response of the chamois to climate change from the last glaciation (20,000 years ago) to the present. We reconstructed species habitat suitability and landscape connectivity over time and simulated cumulative divergence of populations as a proxy for genetic differentiation. We then compared simulated divergence with the actual population structure of 449 chamois (with >20 k SNPs) sampled across the Alps.
Results: We found that Alpine populations of chamois are structured into two main clades, located in the south-western and the eastern Alps. The contact zone between the two lineages is located near the Rhone valley in Switzerland. Simulations reproduced the geographic differentiation of populations observed in the genomic data, and limited dispersal ability and landscape connectivity co-determined the fit of the simulations to data.
Main conclusions: The contemporary genetic structure of the chamois across the Alps is explained by limited functional connectivity in combination with large rivers or valleys acting as dispersal barriers. The results of our analysis combining simulations with population genomics highlight how biological characteristics, habitat preference and landscapes shape population genetic structure over time and in responses to climate change. We conclude that spatial simulations could be used to improve our understanding of how landscape dynamics, shaped by geological or climatic forces, impact intra- and interspecific diversity.

• 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.

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.

Aim: The summits of mountain ranges at mid‐latitude in the Northern Hemisphere share many ecological properties with the Arctic, including comparable climates and similar flora. We hypothesize that the orogeny during the Oligocene‐Miocene combined with global cooling led to the origin and early diversification of cold‐adapted plant lineages in these regions. Before the establishment of the Arctic cryosphere, adaptation and speciation in high elevation areas of these mountain ranges may have led to higher species richness compared to the Arctic. Subsequent colonization from mid‐latitude mountain ranges to the Arctic may explain similar but poorer flora.
Location: Arctic‐Alpine regions of the Northern Hemisphere.
Methods: We mapped the cold climate in the Northern Hemisphere for most of the Cenozoic (60 Ma until present) based on paleoclimate proxies coupled with paleoelevations. We generated species distribution maps from occurrences and regional atlases for 5,464 plant species from 756 genera occupying cold climates. We fitted a generalized linear model to evaluate the association between cold‐adapted plant species richness and environmental, as well as geographic variables. Finally, we performed a meta‐analysis of studies which inferred and dated the ancestral geographic origin of cold‐adapted lineages using phylogenies.
Results: We found that the subalpine‐alpine areas of the mid‐latitude mountain ranges comprise higher cold‐adapted plant species richness than the Palearctic and Nearctic polar regions. The topo‐climatic reconstructions indicate that the cold climatic niche appeared in mid‐latitude mountain ranges (42-38 Ma), specifically in the Himalayan region, and only later in the Arctic (22-18 Ma). The meta‐analysis of the dating of the origin of cold‐adapted lineages indicates that most clades originated in central Asia between 39-7 Ma.
Main conclusions: Our results support the hypothesis that the orogeny and progressive cooling in the Oligocene‐Miocene generated cold climates in mid‐latitude mountain ranges before the appearance of cold climates in most of the Arctic. Early cold mountainous regions likely allowed for the evolution and diversification of cold‐adapted plant lineages followed by the subsequent colonization of the Arctic. Our results follow Humboldt's vision of integrating biological and geological context in order to better understand the processes underlying the origin of arctic‐alpine plant assemblages.