TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Estimating pairwise relatedness in a small sample of individuals

The genetic relatedness between individuals because of their recent common ancestry is now routinely estimated from marker genotype data in molecular ecology, evolutionary biology and conservation studies. The estimators developed for this purpose assume that marker allele freque218 in a population are known without errors. Unfortunately, however, these frequencies, upon which both the definition and the estimation of relatedness are based, are rarely known in reality. Frequently, the only data available in a relatedness analysis are a sample of multilocus genotypes from which both allele frequencies and relatedness must be deduced. Furthermore, because of various constraints, sample sizes of individuals can be quite small (say <50 individuals) in practice. This study shows, for the first time, that the widely used relatedness estimators become severely biased when they use allele frequencies calculated from an extremely small sample (say <10 individuals). The extent of bias depends on the sample size, the (unknown) population allele frequencies, the actual relatedness and the estimators. It also shows that relatedness estimators become even more biased when they use allele frequencies calculated from a sample by omitting a focal pair of individuals whose relatedness is being estimated. This study modifies two estimators to suit small samples and shows, both analytically and by analysing simulated and empirical data, that the two modified estimators are much less biased, more precise and more accurate than the original estimators. These performance advantages of the modified estimators are shown to increase with a decreasing sample size of individuals and with an increasing value of actual relatedness

Topography shapes the local coexistence of tree species within species complexes of Neotropical forests

Forest inventories in Amazonia include around 5000 described tree species belonging to more than 800 genera. Numerous species-rich genera share genetic variation among species because of recent speciation and/or recurrent hybridisation, forming species complexes. Despite the key role that tree species complexes play in understanding Neotropical diversification, and their need to exploit a diversity of niches, little is known about the mechanisms that allow local coexistence of tree species complexes and their species in sympatry. In this study, we explored the fine-scale distribution of five tree species complexes and 22 species within these complexes. Combining forest inventories, botanical determination, and LiDAR-derived topographic data over 120 ha of permanent plots in French Guiana, we used a Bayesian modelling framework to test the role of fine-scale topographic wetness and tree neighbourhood on the occurrence of species complexes and the relative distribution of species within complexes. Species complexes of Neotropical trees were widely spread across the topographic wetness gradient at the local scale. Species within complexes showed pervasive niche differentiation along with topographic wetness and competition gradients. Similar patterns of species-specific habitat preferences were observed within several species complexes: species more tolerant to competition for resources grow in drier and less fertile plateaus and slopes. If supported by partial reproductive isolation of species and adaptive introgression at the species complex level, our results suggest that both species-specific habitat specialisation within species complexes and the broad ecological distribution of species complexes might explain the success of these species complexes at the regional scale.CEnter of the study of Biodiversity in Amazoni