Multiple introductions boosted genetic diversity in the invasive range of black cherry (Prunus serotina; Rosaceae)

Background and Aims Black cherry (Prunus serotina) is a North American tree that is rapidly invading European forests. This species was introduced first as an ornamental plant then it was massively planted by foresters in many countries but its origins and the process of invasion remain poorly documented. Based on a genetic survey of both native and invasive ranges, the invasion history of black cherry was investigated by identifying putative source populations and then assessing the importance of multiple introductions on the maintenance of gene diversity. Methods Genetic variability and structure of 23 populations from the invasive range and 22 populations from the native range were analysed using eight nuclear microsatellite loci and five chloroplast DNA regions. Key Results Chloroplast DNA diversity suggests there were multiple introductions from a single geographic region (the north-eastern United States). A low reduction of genetic diversity was observed in the invasive range for both nuclear and plastid genomes. High propagule pressure including both the size and number of introductions shaped the genetic structure in Europe and boosted genetic diversity. Populations from Denmark, The Netherlands, Belgium and Germany showed high genetic diversity and low differentiation among populations, supporting the hypothesis that numerous introduction events, including multiple individuals and exchanges between sites, have taken place during two centuries of plantation. Conclusions This study postulates that the invasive black cherry has originated from east of the Appalachian Mountains (mainly the Allegheny plateau) and its invasiveness in north-western Europe is mainly due to multiple introductions containing high numbers of individual

Predicting climate change impacts on the threatened Quercus arbutifolia in montane cloud forests in southern China and Vietnam: Conservation implications

Trees of montane cloud forests (MCFs) often have small and isolated populations and face numerous threats. Due to limited conservation resources, management decisions are often based on scarce biological information. This study investigated the current status of populations of the critically endangered oak species Quercus arbutifolia in southern China, including its distribution, threats, population structure, and area of occupancy (AOO). Additionally, by using ensembles of small models (ESMs), the present and future (2050) distributions of climatically suitable habitats were predicted throughout south China and Vietnam. The present distribution of Q. arbutifolia is extremely fragmented, with only eight confirmed populations and a very small number of individuals (ca. 1200 in total). The results presented here show that Q. arbutifolia populations suffer from habitat destruction and fragmentation, small population size, unbalanced population structure, and pressure from strong competitor species, even though all known occurrences of Q. arbutifolia are in already established nature reserves. Based on the utilized models, the current potential distribution is limited to MCFs, and 17 new areas were predicted to have complete habitats suitability for Q. arbutifolia. However, only a small area in Fujian province will remain suitable for Q. arbutifolia in the future. The current AOO of Q. arbutifolia is very small (8.49 km2), with one-third of all populations predicted to be extinct by 2050, even under the minimum emission assumption. Finally, various actions and conservation measures, such as search for new unknown populations as well as ex situ and in situ conservation, are introduced and discussed in this paper

Too many candidates: Embedded covariate selection procedure for species distribution modelling with the covsel R package

1. Selecting the best subset of covariates out of a panel of many candidates is a key and highly influential stage of the species distribution modelling process. Yet, there is currently no commonly accepted and widely adopted standard approach by which to perform this selection. 2. We introduce a two-step “embedded” covariate selection procedure aimed at optimizing the predictive ability and parsimony of species distribution models fitted in a context of high-dimensional candidate covariate space. The procedure combines a collinearity-filtering algorithm (Step A) with three model-specific embedded regularization techniques (Step B), including generalized linear model with elastic net regularization, generalized additive model with null-space penalization, and guided regularized random forest. 3. We evaluated the embedded covariate selection procedure through an example application aimed at modelling the habitat suitability of 50 species in Switzerland from a suite of 123 candidate covariates. We demonstrated the ability of the embedded covariate selection procedure to provide significantly more accurate species distribution models as compared to models obtained with alternative procedures. Model performance was independent of the characteristics of the species data, such as the number of occurrence records or their spatial distribution across the study area. 4. We implemented and streamlined our embedded covariate selection procedure in the covsel R package, paving the way for a ready-to-use, automated, covariate selection tool that was missing in the field of species distribution modelling. All the information required for installing and running the covsel R package is openly available on the GitHub repository https://github.com/N-SDM/covsel

N‐SDM: a high‐performance computing pipeline for Nested Species Distribution Modelling

Predicting contemporary and future species distributions is relevant for science and decision making, yet the development of high‐resolution spatial predictions for numerous taxonomic groups and regions is limited by the scalability of available modelling tools. Uniting species distribution modelling (SDM) techniques into one high‐performance computing (HPC) pipeline, we developedN‐SDM, an SDM platform aimed at delivering reproducible outputs for standard biodiversity assessments.N‐SDMwas built around a spatially‐nested framework, intended at facilitating the combined use of species occurrence data retrieved from multiple sources and at various spatial scales.N‐SDMallows combining two models fitted with species and covariate data retrieved from global to regional scales, which is useful for addressing the issue of spatial niche truncation. The set of state‐of‐the‐art SDM features embodied inN‐SDMincludes a newly devised covariate selection procedure, five modelling algorithms, an algorithm‐specific hyperparameter grid search, and the ensemble of small‐models approach.N‐SDMis designed to be run on HPC environments, allowing the parallel processing of thousands of species at the same time. All the information required for installing and runningN‐SDMis openly available on the GitHub repositoryhttps://github.com/N‐SDM/N‐SDM

N‐SDM: a high‐performance computing pipeline for Nested Species Distribution Modelling

Predicting contemporary and future species distributions is relevant for science and decision making, yet the development of high-resolution spatial predictions for numerous taxonomic groups and regions is limited by the scalability of available modelling tools. Uniting species distribution modelling (SDM) techniques into one high-performance computing (HPC) pipeline, we developed N-SDM, an SDM platform aimed at delivering reproducible outputs for standard biodiversity assessments. N-SDM was built around a spatially-nested framework, intended at facilitating the combined use of species occurrence data retrieved from multiple sources and at various spatial scales. N-SDM allows combining two models fitted with species and covariate data retrieved from global to regional scales, which is useful for addressing the issue of spatial niche truncation. The set of state-of-the-art SDM features embodied in N-SDM includes a newly devised covariate selection procedure, five modelling algorithms, an algorithm-specific hyperparameter grid search, and the ensemble of small-models approach. N-SDM is designed to be run on HPC environments, allowing the parallel processing of thousands of species at the same time. All the information required for installing and running N-SDM is openly available on the GitHub repository https://github.com/N-SDM/N-SDM

The mossy north : an inverse latitudinal diversity gradient in European bryophytes

It remains hotly debated whether latitudinal diversity gradients are common across taxonomic groups and whether a single mechanism can explain such gradients. Investigating species richness (SR) patterns of European land plants, we determine whether SR increases with decreasing latitude, as predicted by theory, and whether the assembly mechanisms differ among taxonomic groups. SR increases towards the south in spermatophytes, but towards the north in ferns and bryophytes. SR patterns in spermatophytes are consistent with their patterns of beta diversity, with high levels of nestedness and turnover in the north and in the south, respectively, indicating species exclusion towards the north and increased opportunities for speciation in the south. Liverworts exhibit the highest levels of nestedness, suggesting that they represent the most sensitive group to the impact of past climate change. Nevertheless, although the extent of liverwort species turnover in the south is substantially and significantly lower than in spermatophytes, liverworts share with the latter a higher nestedness in the north and a higher turn-over in the south, in contrast to mosses and ferns. The extent to which the similarity in the patterns displayed by spermatophytes and liverworts reflects a similar assembly mechanism remains, however, to be demonstrated.Peer reviewe

Evolutionary Insights on C4 Photosynthetic Subtypes in Grasses from Genomics and Phylogenetics

In plants, an oligogene family encodes NADP-malic enzymes (NADP-me), which are responsible for various functions and exhibit different kinetics and expression patterns. In particular, a chloroplast isoform of NADP-me plays a key role in one of the three biochemical subtypes of C4 photosynthesis, an adaptation to warm environments that evolved several times independently during angiosperm diversification. By combining genomic and phylogenetic approaches, this study aimed at identifying the molecular mechanisms linked to the recurrent evolutions of C4-specific NADP-me in grasses (Poaceae). Genes encoding NADP-me (nadpme) were retrieved from genomes of model grasses and isolated from a large sample of C3 and C4 grasses. Genomic and phylogenetic analyses showed that 1) the grass nadpme gene family is composed of four main lineages, one of which is expressed in plastids (nadpme-IV), 2) C4-specific NADP-me evolved at least five times independently from nadpme-IV, and 3) some codons driven by positive selection underwent parallel changes during the multiple C4 origins. The C4 NADP-me being expressed in chloroplasts probably constrained its recurrent evolutions from the only plastid nadpme lineage and this common starting point limited the number of evolutionary paths toward a C4 optimized enzyme, resulting in genetic convergence. In light of the history of nadpme genes, an evolutionary scenario of the C4 phenotype using NADP-me is discussed

Crop Wild Relatives conservation in Switzerland. Distribution of priority CWR

Species distribution (observed and modelled) of 265 priority crop wild relatives in Switerland. Appendix S5 from Petitpierre et al. "Importance of agriculture for Crop Wild Relatives conservation in Switzerland"</p

Importance of agriculture for crop wild relatives conservation in Switzerland

While considered an essential part of the genetic diversity of plants, Crop Wild Relatives (CWR), are rarely the primary focus of conservation strategies. Despite this, a large portion of wild flora shares genetic relationships with cultivated species. The conservation of CWR presents not only a challenge to conservationists but also an opportunity to engage other sectors, such as agriculture, in a collaborative effort towards biodiversity preservation. Here, we quantified the association between agricultural areas and the distribution of CWR in Switzerland. To achieve this, we compiled a comprehensive checklist of Swiss CWR representing 2′227 taxa, identifying 285 taxa as priority CWR for Switzerland. Following a taxa-specific ecogeographic analysis, we analysed the extent to which priority CWR are already contained in existing protected areas as well as their distribution in the agricultural area. The observed species richness of priority CWR was compared to the modelled priority CWR richness to identify potential conservation gaps. Among the 285 priority CWR, 64 taxa (22.5%) are not significantly better covered by existing protected areas than a random species. However, 28.8% and 15.5% of these priority taxa are more frequently distributed in agricultural and summer grazing areas respectively than random expectations. A clear deficit of species richness of these priority CWR was inferred on lowlands, possibly related to a lower sampling effort. We further identified a minimal network of 39 complementary sites that contains all Swiss priority CWR and that could be used as a primary conservation infrastructure. Our results support better consideration of CWR in agricultural areas, an important “reservoir” for expanding specific measures of conservation

Contrasting spatio-temporal climatic niche dynamics during the eastern and western invasions of spotted knapweed in North America

Aim: The spotted knapweed (Centaurea stoebe), a plant native to south-east and central Europe, is highly invasive in North America. We investigated the spatio-temporal climatic niche dynamics of the spotted knapweed in North America along two putative eastern and western invasion routes. We then considered the patterns observed in the light of historical, ecological and evolutionary factors.Location: Europe and North America.Methods: The niche characteristics of the east and west invasive populations of spotted knapweed in North America were determined from documented occurrences over 120 consecutive years (1890–2010). For this investigation, the 2.5 and 97.5 percentiles of values along temperature and precipitation gradients, as given by the two first axes of a principal components analysis (PCA), were calculated. We additionally measured the climatic dissimilarity between invaded sites and the native niche using a multivariate environmental similarity surface (MESS) analysis.Results: Along both invasion routes, the species established in regions with climatic conditions that were similar to those in the native niche. An initial spread in ruderal habitats always preceded spread in (semi-)natural habitats. In the east, the niche gradually increased over time until it reached limits similar to the native niche. Conversely, in the west the niche abruptly expanded after an extended time lag into climates not occupied in the native range; only the native cold niche limit was conserved.Main conclusions: Our study reveals that different niche dynamics have taken place during the eastern and western invasions. This pattern indicates different combinations of historical, ecological and evolutionary factors in the two ranges. We hypothesize that the lack of a well-developed transportation network in the west at the time of the introduction of spotted knapweed confined the species to a geographically and climatically isolated region. The invasion of dry rangelands may have been favoured during the agricultural transition in the 1930s by release from natural enemies, local adaptation and less competitive vegetation, but further experimental and molecular studies are needed to explain these contrasting niche patterns fully. Our study illustrates the need and benefit of applying large-scale, temporally explicit approaches to understanding biological invasions