50 research outputs found

    Deciphering the adjustment between environment and life history in annuals: lessons from a geographically-explicit approach in Arabidopsis thaliana

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    The role that different life-history traits may have in the process of adaptation caused by divergent selection can be assessed by using extensive collections of geographically-explicit populations. This is because adaptive phenotypic variation shifts gradually across space as a result of the geographic patterns of variation in environmental selective pressures. Hence, large-scale experiments are needed to identify relevant adaptive life-history traits as well as their relationships with putative selective agents. We conducted a field experiment with 279 geo-referenced accessions of the annual plant Arabidopsis thaliana collected across a native region of its distribution range, the Iberian Peninsula. We quantified variation in life-history traits throughout the entire life cycle. We built a geographic information system to generate an environmental data set encompassing climate, vegetation and soil data. We analysed the spatial autocorrelation patterns of environmental variables and life-history traits, as well as the relationship between environmental and phenotypic data. Almost all environmental variables were significantly spatially autocorrelated. By contrast, only two life-history traits, seed weight and flowering time, exhibited significant spatial autocorrelation. Flowering time, and to a lower extent seed weight, were the life-history traits with the highest significant correlation coefficients with environmental factors, in particular with annual mean temperature. In general, individual fitness was higher for accessions with more vigorous seed germination, higher recruitment and later flowering times. Variation in flowering time mediated by temperature appears to be the main life-history trait by which A. thaliana adjusts its life history to the varying Iberian environmental conditions. The use of extensive geographically-explicit data sets obtained from field experiments represents a powerful approach to unravel adaptive patterns of variation. In a context of current global warming, geographically-explicit approaches, evaluating the match between organisms and the environments where they live, may contribute to better assess and predict the consequences of global warming

    Ús, modelització i organització de dades de biodiversitat

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    Una tesi doctoral llegida al CREAF, a la UAB, proposa un sistema d'informació mitjançant l'ús dels models de distribució d'espècies d'interès per a la conservació i d'espècies exòtiques invasores per tal de generar mapes útils en la conservació de la biodiversitat. Aquest sistema d'informació està orientat al seguiment temporal d'àrees protegides, dels canvis en els seus límits al llarg del temps i dels que es produeixen durant el procés de tramitació legal

    Tackling intraspecific genetic structure in distribution models better reflects species geographical range

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    Genetic diversity provides insight into heterogeneous demographic and adaptive history across organisms' distribution ranges. For this reason, decomposing single species into genetic units may represent a powerful tool to better understand biogeographical patterns as well as improve predictions of the effects of GCC (global climate change) on biodiversity loss. Using 279 georeferenced Iberian accessions, we used classes of three intraspecific genetic units of the annual plant Arabidopsis thaliana obtained from the genetic analyses of nuclear SNPs (single nucleotide polymorphisms), chloroplast SNPs, and the vernalization requirement for flowering. We used SDM (species distribution models), including climate, vegetation, and soil data, at the whole-species and genetic-unit levels. We compared model outputs for present environmental conditions and with a particularly severe GCC scenario. SDM accuracy was high for genetic units with smaller distribution ranges. Kernel density plots identified the environmental variables underpinning potential distribution ranges of genetic units. Combinations of environmental variables accounted for potential distribution ranges of genetic units, which shrank dramatically with GCC at almost all levels. Only two genetic clusters increased their potential distribution ranges with GCC. The application of SDM to intraspecific genetic units provides a detailed picture on the biogeographical patterns of distinct genetic groups based on different genetic criteria. Our approach also allowed us to pinpoint the genetic changes, in terms of genetic background and physiological requirements for flowering, that Iberian A. thaliana may experience with a GCC scenario applying SDM to intraspecific genetic units

    Quantifying temporal change in plant population attributes : insights from a resurrection approach

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    Rapid evolution in annual plants can be quantified by comparing phenotypic and genetic changes between past and contemporary individuals from the same populations over several generations. Such knowledge will help understand the response of plants to rapid environmental shifts, such as the ones imposed by global climate change. To that end, we undertook a resurrection approach in Spanish populations of the annual plant Arabidopsis thaliana that were sampled twice over a decade. Annual weather records were compared to their historical records to extract patterns of climatic shifts over time. We evaluated the differences between samplings in flowering time, a key life-history trait with adaptive significance, with a field experiment. We also estimated genetic diversity and differentiation based on neutral nuclear markers and nucleotide diversity in candidate flowering time (FRI and FLC) and seed dormancy (DOG1) genes. The role of genetic drift was estimated by computing effective population sizes with the temporal method. Overall, two climatic scenarios were detected: intense warming with increased precipitation and moderate warming with decreased precipitation. The average flowering time varied little between samplings. Instead, within-population variation in flowering time exhibited a decreasing trend over time. Substantial temporal changes in genetic diversity and differentiation were observed with both nuclear microsatellites and candidate genes in all populations, which were interpreted as the result of natural demographic fluctuations. We conclude that drought stress caused by moderate warming with decreased precipitation may have the potential to reduce within-population variation in key life-cycle traits, perhaps as a result of stabilizing selection on them, and to constrain the genetic differentiation over time. Besides, the demographic behaviour of populations probably accounts for the substantial temporal patterns of genetic variation, while keeping rather constant those of phenotypic variation

    A hierarchical Bayesian Beta regression approach to study the effects of geographical genetic structure and spatial autocorrelation on species distribution range shifts

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    Global climate change (GCC) may be causing distribution range shifts in many organisms worldwide. Multiple efforts are currently focused on the development of models to better predict distribution range shifts due to GCC. We addressed this issue by including intraspecific genetic structure and spatial autocorrelation (SAC) of data in distribution range models. Both factors reflect the joint effect of ecoevolutionary processes on the geographical heterogeneity of populations. We used a collection of 301 georeferenced accessions of the annual plant Arabidopsis thaliana in its Iberian Peninsula range, where the species shows strong geographical genetic structure. We developed spatial and nonspatial hierarchical Bayesian models (HBMs) to depict current and future distribution ranges for the four genetic clusters detected. We also compared the performance of HBMs with Maxent (a presence-only model). Maxent and nonspatial HBMs presented some shortcomings, such as the loss of accessions with high genetic admixture in the case of Maxent and the presence of residual SAC for both. As spatial HBMs removed residual SAC, these models showed higher accuracy than nonspatial HBMs and handled the spatial effect on model outcomes. The ease of modelling and the consistency among model outputs for each genetic cluster was conditioned by the sparseness of the populations across the distribution range. Our HBMs enrich the toolbox of software available to evaluate GCC-induced distribution range shifts by considering both genetic heterogeneity and SAC, two inherent properties of any organism that should not be overlooked

    A hierarchical Bayesian Beta regression approach to study the effects of geographical genetic structure and spatial autocorrelation on species distribution range shifts

    Get PDF
    Global climate change (GCC) may be causing distribution range shifts in many organisms worldwide. Multiple efforts are currently focused on the development of models to better predict distribution range shifts due to GCC. We addressed this issue by including intraspecific genetic structure and spatial autocorrelation (SAC) of data in distribution range models. Both factors reflect the joint effect of ecoevolutionary processes on the geographical heterogeneity of populations. We used a collection of 301 georeferenced accessions of the annual plant Arabidopsis thaliana in its Iberian Peninsula range, where the species shows strong geographical genetic structure. We developed spatial and nonspatial hierarchical Bayesian models (HBMs) to depict current and future distribution ranges for the four genetic clusters detected. We also compared the performance of HBMs with Maxent (a presence-only model). Maxent and nonspatial HBMs presented some shortcomings, such as the loss of accessions with high genetic admixture in the case of Maxent and the presence of residual SAC for both. As spatial HBMs removed residual SAC, these models showed higher accuracy than nonspatial HBMs and handled the spatial effect on model outcomes. The ease of modelling and the consistency among model outputs for each genetic cluster was conditioned by the sparseness of the populations across the distribution range. Our HBMs enrich the toolbox of software available to evaluate GCC-induced distribution range shifts by considering both genetic heterogeneity and SAC, two inherent properties of any organism that should not be overlooked

    Unravelling plant diversification: Intraspecific genetic differentiation in hybridizing Anacyclus species in the western Mediterranean Basin

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    Premise: The interfertile species Anacyclus clavatus, A. homogamos, and A. valentinus represent a plant complex coexisting in large anthropic areas of the western Mediterranean Basin with phenotypically mixed populations exhibiting a great floral variation. The goal of this study was to estimate the genetic identity of each species, to infer the role of hybridization in the observed phenotypic diversity, and to explore the effect of climate on the geographic distribution of species and genetic clusters. Methods: We used eight nuclear microsatellites to genotype 585 individuals from 31 populations of three Anacyclus species for population genetic analyses by using clustering algorithms based on Bayesian models and ordination methods. In addition, we used ecological niche models and niche overlap analyses for both the species and genetic clusters. We used an expanded data set, including 721 individuals from 129 populations for ecological niche models of the genetic clusters. Results: We found a clear correspondence between species and genetic clusters, except for A. clavatus that included up to three genetic clusters. We detected individuals with admixed genetic ancestry in A. clavatus and in mixed populations. Ecological niche models predicted similar distributions for species and genetic clusters. For the two specific genetic clusters of A. clavatus, ecological niche models predicted remarkably different areas. Conclusions: Gene flow between Anacyclus species likely explains phenotypic diversity in contact areas. In addition, we suggest that introgression could be involved in the origin of one of the two A. clavatus genetic clusters, which also showed ecological differentiationPID2019‐104135GB‐I00, PID2021‐124187NB‐I0

    Uncertainty matters: ascertaining where specimens in natural history collections come from and its implications for predicting species distributions

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    Natural history collections (NHCs) represent an enormous and largely untapped wealth of information on the Earth's biota, made available through GBIF as digital preserved specimen records. Precise knowledge of where the specimens were collected is paramount to rigorous ecological studies, especially in the field of species distribution modelling. Here, we present a first comprehensive analysis of georeferencing quality for all preserved specimen records served by GBIF, and illustrate the impact that coordinate uncertainty may have on predicted potential distributions. We used all GBIF preserved specimen records to analyse the availability of coordinates and associated spatial uncertainty across geography, spatial resolution, taxonomy, publishing institutions and collection time. We used three plant species across their native ranges in different parts of the world to show the impact of uncertainty on predicted potential distributions. We found that 38% of the 180+ million records provide coordinates only and 18% coordinates and uncertainty. Georeferencing quality is determined more by country of collection and publishing than by taxonomic group. Distinct georeferencing practices are more determinant than implicit characteristics and georeferencing difficulty of specimens. Availability and quality of records contrasts across world regions. Uncertainty values are not normally distributed but peak at very distinct values, which can be traced back to specific regions of the world. Uncertainty leads to a wide spectrum of range sizes when modelling species distributions, potentially affecting conclusions in biogeographical and climate change studies. In summary, the digitised fraction of the world's NHCs are far from optimal in terms of georeferencing and quality mainly depends on where the collections are hosted. A collective effort between communities around NHC institutions, ecological research and data infrastructure is needed to bring the data on a par with its importance and relevance for ecological research

    Community engagement: The ‘last mile’ challenge for European research e-infrastructures

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    Europe is building its Open Science Cloud; a set of robust and interoperable e-infrastructures with the capacity to provide data and computational solutions through cloud-based services. The development and sustainable operation of such e-infrastructures are at the forefront of European funding priorities. The research community, however, is still reluctant to engage at the scale required to signal a Europe-wide change in the mode of operation of scientific practices. The striking differences in uptake rates between researchers from different scientific domains indicate that communities do not equally share the benefits of the above European investments. We highlight the need to support research communities in organically engaging with the European Open Science Cloud through the development of trustworthy and interoperable Virtual Research Environments. These domain-specific solutions can support communities in gradually bridging technical and socio-cultural gaps between traditional and open digital science practice, better diffusing the benefits of European e-infrastructures

    Progress in authority management of people names for collections

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    The concept of building a network of relationships between entities, a knowledge graph, is one of the most effective methods to understand the relations between data. By organizing data, we facilitate the discovery of complex patterns not otherwise evident in the raw data. Each datum at the nodes of a knowledge graph needs a persistent identifier (PID) to reference it unambiguously. In the biodiversity knowledge graph, people are key elements (Page 2016). They collect and identify specimens, they publish, observe, work with each other and they name organisms. Yet biodiversity informatics has been slow to adopt PIDs for people and people are currently represented in collection management systems as text strings in various formats. These text strings often do not separate individuals within a collecting team and little biographical information is collected to disambiguate collectors. In March 2019 we organised an international workshop to find solutions to the problem of PIDs for people in collections with the aim of identifying people unambiguously across the world's natural history collections in all of their various roles. Stakeholders were represented from 11 countries, representing libraries, collections, publishers, developers and name registers. We want to identify people for many reasons. Cross-validation of information about a specimen with biographical information on the specimen can be used to clean data. Mapping specimens from individual collectors across multiple herbaria can geolocate specimens accurately. By linking literature to specimens through their authors and collectors we can create collaboration networks leading to a much better understanding of the scientific contribution of collectors and their institutions. For taxonomists, it will be easier to identify nomenclatural type and syntype material, essential for reliable typification. Overall, it will mean that geographically dispersed specimens can be treated much more like a single distributed infrastructure of specimens as is envisaged in the European Distributed Systems of Scientific Collections Infrastructure (DiSSCo). There are several person identifier systems in use. For example, the Virtual International Authority File (VIAF) is a widely used system for published authors. The International Standard Name Identifier (ISNI), has broader scope and incorporates VIAF. The ORCID identifier system provides self-registration of living researchers. Also, Wikidata has identifiers of people, which have the advantage of being easy to add to and correct. There are also national systems, such as the French and German authority files, and considerable sharing of identifiers, particularly on Wikidata. This creates an integrated network of identifiers that could act as a brokerage system. Attendees agreed that no one identifier system should be recommended, however, some are more appropriate for particular circumstances. Some difficulties have still to be resolved to use those identifier schemes for biodiversity : 1) duplicate entries in the same identifier system; 2) handling collector teams and preserving the order of collectors; 3) how we integrate identifiers with standards such as Darwin Core, ABCD and in the Global Biodiversity Information Facility; and 4) many living and dead collectors are only known from their specimens and so they may not pass notability standards required by many authority systems. The participants of the workshop are now working on a number of fronts to make progress on the adoption of PIDs for people in collections. This includes extending pilots that have already been trialed, working with identifier systems to make them more suitable for specimen collectors and talking to service providers to encourage them to use ORCID iDs to identify their users. It was concluded that resolving the problem of person identifiers for collections is largely not a lack of a solution, but a need to implement solutions that already exist
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