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Additional file 7. Additional Figures showing the spatial and temporal extent of studies across ecological context variables.

Climate change and human pressures are changing the global distribution and the extent of intermittent rivers and ephemeral streams (IRES), which comprise half of the global river network area. IRES are characterized by periods of flow cessation, during which channel substrates accumulate and undergo physico‐chemical changes (preconditioning), and periods of flow resumption, when these substrates are rewetted and release pulses of dissolved nutrients and organic matter (OM). However, there are no estimates of the amounts and quality of leached substances, nor is there information on the underlying environmental constraints operating at the global scale. We experimentally simulated, under standard laboratory conditions, rewetting of leaves, riverbed sediments, and epilithic biofilms collected during the dry phase across 205 IRES from five major climate zones. We determined the amounts and qualitative characteristics of the leached nutrients and OM, and estimated their areal fluxes from riverbeds. In addition, we evaluated the variance in leachate characteristics in relation to selected environmental variables and substrate characteristics. We found that sediments, due to their large quantities within riverbeds, contribute most to the overall flux of dissolved substances during rewetting events (56%–98%), and that flux rates distinctly differ among climate zones. Dissolved organic carbon, phenolics, and nitrate contributed most to the areal fluxes. The largest amounts of leached substances were found in the continental climate zone, coinciding with the lowest potential bioavailability of the leached OM. The opposite pattern was found in the arid zone. Environmental variables expected to be modified under climate change (i.e. potential evapotranspiration, aridity, dry period duration, land use) were correlated with the amount of leached substances, with the strongest relationship found for sediments. These results show that the role of IRES should be accounted for in global biogeochemical cycles, especially because prevalence of IRES will increase due to increasing severity of drying events.

Motivation: The Tundra Trait Team (TTT) database includes field-based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade-offs, trait environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained: The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (>1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain: Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub-Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain: All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement: Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release. 2Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Aarhus, Denmark 3Senckenberg Gesellschaft fD?r Naturforschung, Biodiversity and Climate Research Centre (BiK?F), Frankfurt, Germany 4Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado 5National Ecological Observatory Network, Boulder, Colorado 6Institute of Arctic and Alpine Research, University of Colorado, Boulder, Colorado 7Arctic Research Center, Department of Bioscience, Aarhus University, Aarhus, Denmark 8Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Bioscience, Aarhus University, Aarhus, Denmark 9Department of Biological and Environmental Sciences, Qatar University, Doha, Qatar 10Department of Forestry, Forest and Wildlife Research Center, Mississippi State University, Mississippi 11Department of Evolutionary Biology, Ecology and Environmental Sciences, University of Barcelona, Barcelona, Spain 12Biodiversity Research Institute, University of Barcelona, Barcelona, Spain 13Institute of Botany and Landscape Ecology, Greifswald University, Greifswald, Germany 14Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Xishuangbanna, China 15Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland 16Department of Ecology and Environmental Science, Ume� University, Ume�, Sweden 17Environmental Sciences, Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands 18School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona 19Department of Earth Sciences, University of Gothenburg, Gothenburg, Sweden 20Gothenburg Global Biodiversity Centre, GD?teborg, Sweden 21Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden 22Martin Luther University Halle?Wittenberg, Institute of Biology / Geobotany and Botanical Garden, Halle (Saale), Germany 23German Centre for Integrative Biodiversity Research (iDiv) Halle?Jena?Leipzig, Leipzig, Germany 24Adam Mickiewicz University, Institute of Geoecology and Geoinformation, Poznan, Poland 25University of Alaska Anchorage, Department of Biological Sciences, Anchorage, Alaska 26Technische Universit�t MD?nchen, Freising, Germany 27Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy 28The Alaska Department of Fish and Game, Anchorage, Alaska 29Department of Biology, Memorial University, St. John�s, Newfoundland and Labrador, Canada 30Department of Arctic and Marine Biology, Faculty of Biosciences, Fisheries and Economics, UiT? The Arctic University of Norway, Troms�, Norway 31Systems Ecology, Department of Ecological Science, Vrije Universiteit, Amsterdam, The Netherlands 32Department of Botany, University of Otago, Dunedin, New Zealand 33Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria 34Center for Permafrost (CENPERM), Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark 35Department of Physiological Diversity, Helmholtz Centre for Environmental Research ? UFZ, Leipzig, Germany 36Department of Ecology and Genetics, University of Oulu, Oulu, Finland 37Arctic Centre, University of Lapland, Rovaniemi, Finland 38Swiss Federal Research Institute WSL, Birmensdorf, Switzerland 39Department of Geography, University of British Columbia, Vancouver, British Columbia, Canada 40Faculty of Science and Technology, Federation University, Ballarat, Victoria, Australia 41Global Ecology Unit, CREAF?CSIC?UAB, Bellaterra, Catalonia, Spain 42CREAF, Bellaterra, Cerdanyola del Vall�s, Catalonia, Spain 43Department of Ecology, Environment and Evolution, La Trobe University, Bundoora, Australia 44Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa 45Department of Biology, Queen�s University, Kingston, Ontario, Canada Scopus

Motivation The Tundra Trait Team (TTT) database includes field-based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade-offs, trait?environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub-Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.