Angiosperms are the cornerstone of most terrestrial ecosystems and human livelihoods^1,2. A robust understanding of angiosperm evolution is required to explain their rise to ecological dominance. So far, the angiosperm tree of life has been determined primarily by means of analyses of the plastid genome^3,4. Many studies have drawn on this foundational work, such as classification and first insights into angiosperm diversification since their Mesozoic origins^5–7. However, the limited and biased sampling of both taxa and genomes undermines confidence in the tree and its implications. Here, we build the tree of life for almost 8,000 (about 60%) angiosperm genera using a standardized set of 353 nuclear genes⁸. This 15-fold increase in genus-level sampling relative to comparable nuclear studies⁹ provides a critical test of earlier results and brings notable change to key groups, especially in rosids, while substantiating many previously predicted relationships. Scaling this tree to time using 200 fossils, we discovered that early angiosperm evolution was characterized by high gene tree conflict and explosive diversification, giving rise to more than 80% of extant angiosperm orders. Steady diversification ensued through the remaining Mesozoic Era until rates resurged in the Cenozoic Era, concurrent with decreasing global temperatures and tightly linked with gene tree conflict. Taken together, our extensive sampling combined with advanced phylogenomic methods shows the deep history and full complexity in the evolution of a megadiverse clade.

Before environmental DNA (eDNA) can establish itself as a robust tool for biodiversity monitoring, comparison with existing approaches is necessary, yet is lacking for terrestrial mammals. Moreover, much is unknown regarding the nature, spread and persistence of DNA shed by animals into terrestrial environments, or the optimal experimental design for understanding these potential biases. To address some of these challenges, we compared the detection of terrestrial mammals using eDNA analysis of soil samples against confirmed species observations from a long-term (approx. 9-year) camera-trapping study. At the same time, we considered multiple experimental parameters, including two sampling designs, two DNA extraction kits and two metabarcodes of different sizes. All mammals regularly recorded with cameras were detected in eDNA. In addition, eDNA reported many unrecorded small mammals whose presence in the study area is otherwise documented. A long metabarcode (≈220 bp) offering a high taxonomic resolution, achieved a similar efficiency as a shorter one (≈70 bp) and a phosphate buffer-based extraction gave similar results as a total DNA extraction method, for a fraction of the price. Our results support that eDNA-based monitoring should become a valuable part of ecosystem surveys, yet mitochondrial reference databases need to be enriched first.

Livestock conservation practice is changing rapidly in light of policy, climate change and market demands. The last decade saw a step change in technological and analytical approaches to define, manage and conserve Farm Animal Genomic Resources (FAnGR). These changes pose challenges for FAnGR conservation in terms of technological continuity, analytical capacity and the methodologies needed to exploit new, multidimensional data. The ESF Genomic Resources program final conference addressed these problems attempting to contribute to the development of the research and policy agenda for the next decade. We broadly identified four areas related to methodological and analytical challenges, data management and conservation. The overall conclusion is that there is a need for the use of current state-of-the-art tools to characterise the state of genomic resources in non-commercial and local breeds. The livestock genomic sector, which has been relatively well-organised in applying such methodologies so far, needs to make a concerted effort in the coming decade to enable to the democratisation 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.

Summary: Digital elevation models (DEMs) are often used in landscape ecology to retrieve elevation or first derivative terrain attributes such as slope or aspect in the context of species distribution modelling. However, DEM‐derived variables are scale‐dependent and, given the increasing availability of very high‐resolution (VHR) DEMs, their ecological relevance must be assessed for different spatial resolutions. In a study area located in the Swiss Western Alps, we computed VHR DEMs‐derived variables related to morphometry, hydrology and solar radiation. Based on an original spatial resolution of 0·5 m, we generated DEM‐derived variables at 1, 2 and 4 m spatial resolutions, applying a Gaussian Pyramid. Their associations with local climatic factors, measured by sensors (direct and ambient air temperature, air humidity and soil moisture) as well as ecological indicators derived from species composition, were assessed with multivariate generalized linear models (GLM) and mixed models (GLMM). Specific VHR DEM‐derived variables showed significant associations with climatic factors. In addition to slope, aspect and curvature, the underused wetness and ruggedness indices modelled measured ambient humidity and soil moisture, respectively. Remarkably, spatial resolution of VHR DEM‐derived variables had a significant influence on models’ strength, with coefficients of determination decreasing with coarser resolutions or showing a local optimum with a 2 m resolution, depending on the variable considered. These results support the relevance of using multi‐scale DEM variables to provide surrogates for important climatic variables such as humidity, moisture and temperature, offering suitable alternatives to direct measurements for evolutionary ecology studies at a local scale.

A workshop recently held at the École Polytechnique Fédérale de Lausanne (EPFL, Switzerland) was dedicated to understanding the genetic basis of adaptive change, taking stock of the different approaches developed in theoretical population genetics and landscape genomics and bringing together knowledge accumulated in both research fields. Indeed, an important challenge in theoretical population genetics is to incorporate effects of demographic history and population structure. But important design problems (e.g. focus on populations as units, focus on hard selective sweeps, no hypothesis‐based framework in the design of the statistical tests) reduce their capability of detecting adaptive genetic variation. In parallel, landscape genomics offers a solution to several of these problems and provides a number of advantages (e.g. fast computation, landscape heterogeneity integration). But the approach makes several implicit assumptions that should be carefully considered (e.g. selection has had enough time to create a functional relationship between the allele distribution and the environmental variable, or this functional relationship is assumed to be constant). To address the respective strengths and weaknesses mentioned above, the workshop brought together a panel of experts from both disciplines to present their work and discuss the relevance of combining these approaches, possibly resulting in a joint software solution in the future.

Premise: Recent phylogenetic studies of the Araceae have confirmed the position of the duckweeds nested within the aroids, and the monophyly of a clade containing all the unisexual flowered aroids plus the bisexual‐flowered Calla palustris. The main objective of the present study was to better resolve the deep phylogenetic relationships among the main lineages within the family, particularly the relationships between the eight currently recognized subfamilies. We also aimed to confirm the phylogenetic position of the enigmatic genus Calla in relation to the long‐debated evolutionary transition between bisexual and unisexual flowers in the family.Methods: Nuclear DNA sequence data were generated for 128 species across 111 genera (78%) of Araceae using target sequence capture and the Angiosperms 353 universal probe set.Results: The phylogenomic data confirmed the monophyly of the eight Araceae subfamilies, but the phylogenetic position of subfamily Lasioideae remains uncertain. The genus Calla is included in subfamily Aroideae, which has also been expanded to include Zamioculcadoideae. The tribe Aglaonemateae is newly defined to include the genera Aglaonema and Boycea.Conclusions: Our results strongly suggest that new research on African genera (Callopsis, Nephthytis, and Anubias) and Calla will be important for understanding the early evolution of the Aroideae. Also of particular interest are the phylogenetic positions of the isolated genera Montrichardia, Zantedeschia, and Anchomanes, which remain only moderately supported here.