New plant trait records of the Hungarian flora

Canopy height, leaf area (LA), specific leaf area (SLA) and leaf dry matter content (LDMC) data of 210 species of the Hungarian flora resulting from our field sampling are presented in this data paper

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

Plant Trait Records of the Hungarian and Serbian Flora and Methodological Description of Some Hard to Measure Plant Species

New plant trait measurements collected during the field sampling in Pannonian sandy grasslands in Hungary and Serbia are presented. Selected traits include canopy height, leaf area (LA), specific leaf area (SLA) and leaf dry matter content (LDMC). The leaf area measurement procedures of overlapping, 3-dimensional or otherwise difficult-to-measure leaves and shoots are described in details.</jats:p

Pollination and dispersal trait spectra recover faster than the growth form spectrum during spontaneous succession in sandy old‐fields

Question: Spontaneous succession is the most natural and cost‐effective solution for grassland restoration. However, little is known about the time required for the recovery of grassland functionality, i.e., for the recovery of reproductive and vegetative processes typical of pristine grasslands. Since these processes operate at different scales, we addressed the question: do reproductive and vegetative processes require different recovery times during spontaneous succession? Location: Kiskunság sand region (Central Hungary). Methods: As combinations of plant traits can be used to highlight general patterns in ecological processes, we compared reproductive (pollination‐ and dispersal‐related) and vegetative (growth form) traits between recovered grasslands of different age (&lt;10 years old; 10–20 years old; 20–40 years old) and pristine grasslands. Results: During spontaneous succession, the reproductive trait spectra became similar to those of pristine grasslands earlier than the vegetative ones. In arable land abandoned for 10 years, pollination‐ and dispersal‐related trait spectra did not show significant difference to those of pristine grasslands; anemophily and anemochory were the prevailing strategies. Contrarily, significant differences in the growth form spectrum could be observed even after 40 years of abandonment; in recovered grasslands erect leafy species prevailed, while the fraction of dwarf shrubs and tussock‐forming species was significantly lower than in pristine grasslands. Conclusions: The recovery of the ecological processes of pristine grasslands might require different amounts of time, depending on the spatial scale at which they operate. The reproductive trait spectra recovered earlier than the vegetative one, since reproductive attributes first determine plant species sorting at the regional level towards their respective habitats. The recovery of the vegetative trait spectrum needs more time as vegetative‐based interactions operate on a smaller spatial scale. Thus, vegetative traits might be more effective in the long‐term assessment of restoration success than the reproductive ones

ReSurveyEurope: A database of resurveyed vegetation plots in Europe

Aims: We introduce ReSurveyEurope - a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions. Results: ReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover-abundance classes such as variants of the Braun-Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020. Conclusions: ReSurveyEurope is a new resource to address a wide range of research questions on fine-scale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well-established European Vegetation Archive (EVA). ReSurvey:Europe data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

ReSurveyEurope: A database of resurveyed vegetation plots in Europe

Aims: We introduce ReSurveyEurope - a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions. Results: ReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover-abundance classes such as variants of the Braun-Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020. Conclusions: ReSurveyEurope is a new resource to address a wide range of research questions on fine-scale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well-established European Vegetation Archive (EVA). ReSurvey:Europe data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome

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