TRY plant trait database – enhanced coverage and open access

Global Change Biology, Journal Year: 2019, Volume and Issue: 26(1), P. 119 - 188

Published: Dec. 31, 2019

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

Language: Английский

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Open Science principles for accelerating trait-based science across the Tree of Life

Nature Ecology & Evolution, Journal Year: 2020, Volume and Issue: 4(3), P. 294 - 303

Published: Feb. 17, 2020

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological evolutionary science, new data methods have proliferated rapidly. Yet accessing integrating disparate sources considerable challenge, slowing progress toward global synthesis to integrate organisms. Trait science needs vision achieving integration all Here, we outline how adoption key Open Science principles—open data, open source methods—is transforming increasing transparency, democratizing access accelerating synthesis. To enhance widespread these principles, introduce Traits Network (OTN), global, decentralized community welcoming researchers institutions pursuing collaborative goal standardizing We demonstrate adherence principles is OTN five activities that can accelerate Life, thereby facilitating rapid advances address scientific inquiries environmental issues. Lessons learned along path will provide framework addressing similarly complex informatics challenges. A introduced aims standardize species organismal groups, based on Science.

Language: Английский

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Global root traits (GRooT) database

Global Ecology and Biogeography, Journal Year: 2020, Volume and Issue: 30(1), P. 25 - 37

Published: Sept. 9, 2020

Abstract Motivation Trait data are fundamental to the quantitative description of plant form and function. Although root traits capture key dimensions related responses changing environmental conditions effects on ecosystem processes, they have rarely been included in large‐scale comparative studies global models. For instance, remain absent from nearly all that define spectrum Thus, overcome conceptual methodological roadblocks preventing a widespread integration trait into analyses we created Global Root (GRooT) Database. GRooT provides ready‐to‐use by combining expertise ecologists with mobilization curation. Specifically, (a) determined set core relevant function based an assessment experts, (b) maximized species coverage through standardization within among traits, (c) implemented quality checks. Main types variables contained contains 114,222 records 38 continuous traits. Spatial location grain arid, continental, polar, temperate tropical biomes. Data were derived experimental field studies. Time period recorded between 1911 2019. Major taxa level measurement includes for which taxonomic information is available. vary their resolution, subspecies or varieties being highest genera lowest resolution It 184 varieties, 6,214 species, 1,967 254 families. Owing variation sources, database include both individual observations mean values. Software format two csv files. A GitHub repository files script R query database.

Language: Английский

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Pladias Database of the Czech flora and vegetation

Preslia, Journal Year: 2021, Volume and Issue: 93(1), P. 1 - 87

Published: Jan. 1, 2021

The Pladias (Plant Diversity Analysis and Synthesis) Database of the Czech Flora Vegetation was developed by project team in 2014-2018 has been continuously updated since then.The flora section database contains critically revised information on vascular flora, including 13.6 million plant occurrence records, which are dynamically displayed maps, data 120 characteristics (traits, environmental associations other information), divided into sections (1) Habitus growth type, (2) Leaf, (3) Flower, (4) Fruit, seed dispersal, (5) Belowground organs clonality, (6) Trophic mode, (7) Karyology, (8) Taxon origin, (9) Ecological indicator values, (10) Habitat sociology, (11) Distribution frequency, (12) Threats protection.The vegetation types extracted from monograph Republic.The supplemented national botanical bibliographies, electronic versions standard monographs, a more than 17,000 pictures taxa types, digital maps (shapefiles) with information.The available online public portal www.pladias.cz,which also provides download options for various datasets identification keys to species Republic.In this paper, we describe general scope, structure content database, details characteristics.To illustrate main geographical patterns selected characteristics, provide mean values numerical or proportions categories categorical map country grid 5 longitudinal × 3 latitudinal minutes (approximately 6 km 5.5 km).We summarize variation functional traits using principal component analysis.

Language: Английский

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Global models and predictions of plant diversity based on advanced machine learning techniques

New Phytologist, Journal Year: 2022, Volume and Issue: 237(4), P. 1432 - 1445

Published: Nov. 14, 2022

Summary Despite the paramount role of plant diversity for ecosystem functioning, biogeochemical cycles, and human welfare, knowledge its global distribution is still incomplete, hampering basic research biodiversity conservation. Here, we used machine learning (random forests, extreme gradient boosting, neural networks) conventional statistical methods (generalized linear models generalized additive models) to test environment‐related hypotheses broad‐scale vascular gradients model predict species richness phylogenetic worldwide. To this end, 830 regional inventories including c . 300 000 predictors past present environmental conditions. Machine showed a superior performance, explaining up 80.9% 83.3% richness, illustrating great potential such techniques disentangling complex interacting associations between environment diversity. Current climate heterogeneity emerged as primary drivers, while conditions left only small but detectable imprints on Finally, combined predictions from multiple modeling (ensemble predictions) reveal patterns centers at resolutions down 7774 km 2 Our predictive maps provide accurate estimates available grain sizes relevant conservation macroecology.

Language: Английский

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Reassessment of the risks of climate change for terrestrial ecosystems

Nature Ecology & Evolution, Journal Year: 2024, Volume and Issue: 8(5), P. 888 - 900

Published: Feb. 26, 2024

Abstract Forecasting the risks of climate change for species and ecosystems is necessary developing targeted conservation strategies. Previous risk assessments mapped exposure global land surface to changes in climate. However, this procedure unlikely robustly identify priority areas actions because nonlinear physiological responses colimitation processes ensure that ecological will not map perfectly forecast climatic changes. Here, we combine ecophysiological growth models 135,153 vascular plant growth-form information transform ambient future climatologies into phytoclimates, which describe ability climates support forms characterize terrestrial ecosystems. We 33% 68% experience a significant phytoclimate by 2070 under representative concentration pathways RCP 2.6 8.5, respectively. Phytoclimates without present-day analogue are emerge on 0.3–2.2% 0.1–1.3% currently realized phytoclimates disappear. Notably, geographic pattern change, disappearance novelty differs markedly from analogous trends detected previous studies, thereby defining new priorities highlighting limits using untransformed indices assessments. Our findings suggest profound transformation biosphere underway emphasize need timely adaptation biodiversity management practices.

Language: Английский

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Half a Century of Temperate Non‐Forest Vegetation Changes: No Net Loss in Species Richness, but Considerable Shifts in Taxonomic and Functional Composition

Global Change Biology, Journal Year: 2025, Volume and Issue: 31(1)

Published: Jan. 1, 2025

ABSTRACT In recent decades, global change and local anthropogenic pressures have severely affected natural ecosystems their biodiversity. Although disentangling the effects of these factors is difficult, they are reflected in changes functional composition plant communities. We present a comprehensive, large‐scale analysis long‐term communities various non‐forest habitat types Czech Republic based on 1154 vegetation‐plot time series from 53 resurvey studies comprising 3909 records. focused not only taxonomic diversity but also characteristics Species richness most increased over time, community shifted significantly. Habitat specialists threatened species became less represented communities, indicating decline quality. The spread trees, shrubs, tall herbaceous plants, strong competitors, nutrient‐demanding all habitats, coupled with light‐demanding species, suggests an effect eutrophication succession following abandonment traditional management. Moreover, we identified specific trends certain habitats. wetlands, springs, mires, moisture‐demanding decreased, probably due to drainage, river regulations, increasing drought resulting climate change. Dry grasslands, ruderal, weed, sand, shallow‐soil vegetation more mesic, successional processes were pronounced suggesting stronger management eutrophication. alpine subalpine vegetation, meadows mesic pastures, heathlands, insect‐pollinated declined, proportion grasses increased. Overall, provide deep insights into underlying drivers help conservationists take appropriate countermeasures.

Language: Английский

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Macroecology in the age of Big Data – Where to go from here?

Journal of Biogeography, Journal Year: 2019, Volume and Issue: 47(1), P. 1 - 12

Published: July 17, 2019

Abstract Recent years have seen an exponential increase in the amount of data available all sciences and application domains. Macroecology is part this “Big Data” trend, with a strong rise volume that we are using for our research. Here, summarize most recent developments macroecology age Big Data were presented at 2018 annual meeting Specialist Group Ecological Society Germany, Austria Switzerland (GfÖ). Supported by computational advances, has been rapidly developing field over years. Our highlighted important avenues further progress terms standardized collection, integration, method development process integration. In particular, focus on (a) gaps new initiatives to close them, example through space‐ airborne sensors, (b) how various sources types can be integrated, (c) uncertainty assessed data‐driven analyses (d) machine learning approaches opened ways investigating processes rather than simply describing patterns. We discuss opens up opportunities, but also poses challenges macroecological future, it will essential carefully assess quality, reproducibility compilation analytical methods, communication uncertainties. Major depend definition standards workflows macroecology, such scientific quality integrity guaranteed, collaboration research projects made easier.

Language: Английский

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Linking Plant Functional Ecology to Island Biogeography

Trends in Plant Science, Journal Year: 2020, Volume and Issue: 25(4), P. 329 - 339

Published: Jan. 14, 2020

Language: Английский

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sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

Global Ecology and Biogeography, Journal Year: 2021, Volume and Issue: 30(9), P. 1740 - 1764

Published: June 21, 2021

Abstract Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying predicting the effects of global change on ecosystems. Vegetation plots record occurrence or abundance all species co‐occurring within delimited local areas. This allows absences to be inferred, information seldom provided by existing datasets. Although many vegetation have been recorded, most are not available research community. A recent initiative, called ‘sPlot’, compiled first plot database, continues grow curate it. The sPlot however, extremely unbalanced spatially environmentally, open‐access. Here, we address both these issues (a) resampling using several environmental variables as sampling strata (b) securing permission from data holders 105 local‐to‐regional datasets openly release data. We thus present sPlotOpen, largest open‐access dataset ever released. sPlotOpen can used explore diversity at community level, ground truth remote sensing applications, a baseline monitoring. Main types variable contained ( n = 95,104) recording cover naturally vascular contains three partially overlapping resampled c . 50,000 each), replicates analyses. Besides geographical location, date, size, biome, elevation, slope, aspect, type, naturalness, coverage various layers, source dataset, plot‐level also include community‐weighted means variances 18 functional traits TRY Plant Trait Database. Spatial location grain Global, 0.01–40,000 m². Time period 1888–2015, dates. Major taxa level measurement 42,677 taxa, records. Software format Three main matrices (.csv), relationally linked.

Language: Английский

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