Trophic interactions within food webs affect species distributions, coexistence, and provision of ecosystem services but can be strongly impacted by climatic changes. Understanding these impacts is therefore essential for managing ecosystems and sustaining human well\uffe2\uff80\uff90being. Here, we conducted a global synthesis of terrestrial, marine, and freshwater studies to identify key gaps in our knowledge of climate change impacts on food webs and determine whether the areas currently studied are those most likely to be impacted by climate change. We found research suffers from a strong geographic bias, with only 3.5% of studies occurring in the tropics. Importantly, the distribution of sites sampled under projected climate changes was biased\uffe2\uff80\uff94areas with decreases or large increases in precipitation and areas with low magnitudes of temperature change were under\uffe2\uff80\uff90represented. Our results suggest that understanding of climate change impacts on food webs could be broadened by considering more than two trophic levels, responses in addition to species abundance and biomass, impacts of a wider suite of climatic variables, and tropical ecosystems. Most importantly, to enable better forecasts of biodiversity responses to climate change, we identify critically under\uffe2\uff80\uff90represented geographic regions and climatic conditions which should be prioritized in future research.Extreme weather events can have strong negative impacts on species survival and community structure when surpassing lethal thresholds. Extreme, short\uffe2\uff80\uff90lived, winter warming events in the Arctic rapidly melt snow and expose ecosystems to unseasonably warm air (for instance, 2\uffe2\uff80\uff9310\uffe2\uff80\uff83\uffc2\uffb0C for 2\uffe2\uff80\uff9314 days) but upon return to normal winter climate exposes the ecosystem to much colder temperatures due to the loss of insulating snow. Single events have been shown to reduce plant reproduction and increase shoot mortality, but impacts of multiple events are little understood as are the broader impacts on community structure, growth, carbon balance, and nutrient cycling. To address these issues, we simulated week\uffe2\uff80\uff90long extreme winter warming events \uffe2\uff80\uff93 using infrared heating lamps and soil warming cables \uffe2\uff80\uff93 for 3 consecutive years in a sub\uffe2\uff80\uff90Arctic heathland dominated by the dwarf shrubsEmpetrum hermaphroditum, Vaccinium vitis\uffe2\uff80\uff90idaea(both evergreen) andVaccinium myrtillus(deciduous). During the growing seasons after the second and third winter event, spring bud burst was delayed by up to a week forE. hermaphroditumandV. myrtillus, and berry production reduced by 11\uffe2\uff80\uff9375% and 52\uffe2\uff80\uff9395% forE. hermaphroditumandV. myrtillus, respectively. Greater shoot mortality occurred inE. hermaphroditum(up to 52%),V. vitis\uffe2\uff80\uff90idaea(51%), andV. myrtillus(80%). Root growth was reduced by more than 25% but soil nutrient availability remained unaffected. Gross primary productivity was reduced by more than 50% in the summer following the third simulation. Overall, the extent of damage was considerable, and critically plant responses were opposite in direction to the increased growth seen in long\uffe2\uff80\uff90term summer warming simulations and the \uffe2\uff80\uff98greening\uffe2\uff80\uff99 seen for some arctic regions. Given the Arctic is warming more in winter than summer, and extreme events are predicted to become more frequent, this generates large uncertainty in our current understanding of arctic ecosystem responses to climate change.
", "keywords": ["flowering phenology", "0106 biological sciences", "extreme events", "climate change", "13. Climate action", "arctic", "winter warming", "nutrient cycling", "GPP", "15. Life on land", "dwarf shrub", "01 natural sciences", "SDG 15 - Life on Land"]}, "links": [{"href": "https://doi.org/10.1111/j.1365-2486.2011.02424.x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/j.1365-2486.2011.02424.x", "name": "item", "description": "10.1111/j.1365-2486.2011.02424.x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/j.1365-2486.2011.02424.x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-04-13T00:00:00Z"}}, {"id": "10.3389/fsufs.2020.00115", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:29Z", "type": "Journal Article", "created": "2020-08-21", "title": "A Decision Support Model for Assessing the Water Regulation and Purification Potential of Agricultural Soils Across Europe", "description": "Water regulation and purification (WR) function is defined as \u201cthe capacity of the soil to remove harmful compounds and the capacity of the soil to receive, store and conduct water for subsequent use and to prevent droughts, flooding and erosion.\u201d It is a crucial function that society expects agricultural soils to deliver, contributing to quality water supply for human needs and in particular for ensuring food security. The complexity of processes involved and the intricate tradeoff with other necessary soil functions requires decision support tools for best management of WR function. However, the effects of farm and soil management practices on the delivery of the WR function has not been fully addressed by decision support tools for farmers. This work aimed to develop a decision support model for the management of the WR function performed by agricultural soils. The specific objectives of this paper were (i) to construct a qualitative decision support model to assess the water regulation and purification capacity of agricultural soils at field level, to (ii) conduct sensitivity analysis of the model; and (iii) to validate the model with independent empirical data. The developed decision support model for WR is a hierarchical qualitative model with 5 levels and has 27 basic attributes describing the soil (S), environment (E), and management (M) attributes of the field site to be assessed. The WR model is composed of 3 sub-models concerning (1) soil water storage, (2) P and sediment loss in runoff, and (3) N leaching in percolating water. The WR decision support model was validated using a representative dataset of 94 field sites from across Europe and had an overall accuracy of 75% when compared to the empirically derived values across these sites. This highly accurate, reliable, and useful decision support model for assessing the capacity of agricultural soils to perform the WR function can be used by farmers and advisors help manage and protect their soil resources for the future. This model has also been incorporated into the Soil Navigator decision support tool which provides simultaneous assessment of the WR function and other important soil functions for agriculture.", "keywords": ["2. Zero hunger", "decision support tool", "Nutrition. Foods and food supply", "food security", "04 agricultural and veterinary sciences", "soil functions", "TP368-456", "15. Life on land", "water quality", "01 natural sciences", "INCREASE", "Food processing and manufacture", "6. Clean water", "climate change", "13. Climate action", "EXTREME EVENTS", "water regulation", "11. Sustainability", "MANAGEMENT", "0401 agriculture", " forestry", " and fisheries", "TX341-641", "water purification", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.3389/fsufs.2020.00115"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Sustainable%20Food%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fsufs.2020.00115", "name": "item", "description": "10.3389/fsufs.2020.00115", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fsufs.2020.00115"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-08-21T00:00:00Z"}}, {"id": "10138/303695", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:26Z", "type": "Journal Article", "created": "2019-03-19", "title": "Uneven global distribution of food web studies under climate change", "description": "AbstractTrophic interactions within food webs affect species distributions, coexistence, and provision of ecosystem services but can be strongly impacted by climatic changes. Understanding these impacts is therefore essential for managing ecosystems and sustaining human well\uffe2\uff80\uff90being. Here, we conducted a global synthesis of terrestrial, marine, and freshwater studies to identify key gaps in our knowledge of climate change impacts on food webs and determine whether the areas currently studied are those most likely to be impacted by climate change. We found research suffers from a strong geographic bias, with only 3.5% of studies occurring in the tropics. Importantly, the distribution of sites sampled under projected climate changes was biased\uffe2\uff80\uff94areas with decreases or large increases in precipitation and areas with low magnitudes of temperature change were under\uffe2\uff80\uff90represented. Our results suggest that understanding of climate change impacts on food webs could be broadened by considering more than two trophic levels, responses in addition to species abundance and biomass, impacts of a wider suite of climatic variables, and tropical ecosystems. Most importantly, to enable better forecasts of biodiversity responses to climate change, we identify critically under\uffe2\uff80\uff90represented geographic regions and climatic conditions which should be prioritized in future research.