French Institute of Pondicherry

About: French Institute of Pondicherry is a facility organization based out in Puducherry, India. It is known for research contribution in the topics: Holocene & Vegetation. The organization has 168 authors who have published 238 publications receiving 5663 citations.

TRY plant trait database : Enhanced coverage and open access

Abstract: 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.

Functional Rarity: The Ecology of Outliers

Abstract: Rarity has been a central topic for conservation and evolutionary biologists aiming to determine the species characteristics that cause extinction risk. More recently, beyond the rarity of species, the rarity of functions or functional traits, called functional rarity, has gained momentum in helping to understand the impact of biodiversity decline on ecosystem functioning. However, a conceptual framework for defining and quantifying functional rarity is still lacking. We introduce 12 different forms of functional rarity along gradients of species scarcity and trait distinctiveness. We then highlight the potential key role of functional rarity in the long-term and large-scale maintenance of ecosystem processes, as well as the necessary linkage between functional and evolutionary rarity.

Biomass : an r package for estimating above-ground biomass and its uncertainty in tropical forests

Abstract: 1. Estimating forest above-ground biomass (AGB), or carbon (AGC), in tropical forests has become a major concern for scientists and stakeholders. However, AGB assessment procedures are not fully standardized and even more importantly the uncertainty associated with AGB estimates is seldom assessed. 2. Here, we present an R package designed to compute both AGB/AGC estimate and its associated uncertainty from forest plot datasets, using a Bayesian inference procedure. The package builds upon previous work on pantropical and regional biomass allometric equations and published datasets by default but it can also integrate unpublished or complementary datasets in many steps. 3. BIOMASS performs a number of standard tasks on input forest tree inventories: i) tree species identification, if available, is automatically corrected; ii) wood density is estimated from tree species identity; iii) if height data are available, a local height-diameter allometry may be built; else height is inferred from pantropical or regional models; iv) finally, AGB/AGC are estimated by propagating the errors associated with all the calculation steps up to the final estimate. R code is given in the paper and in the appendix for illustration purpose. 4. The BIOMASS package should contribute to improved standards for AGB calculation for tropical forest stands, and will encourage users to report the uncertainties associated with stand-level AGB/AGC estimates in future studies.

BioTIME: A database of biodiversity time series for the Anthropocene

Abstract: Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)).Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.