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Nitrogen (N) deposition poses a severe risk to global terrestrial ecosystems, and managing this threat is an important focus for air pollution science and policy. To understand and manage the impacts of N deposition, we need metrics which accurately reflect N deposition pressure on the environment, and are responsive to changes in both N deposition and its impacts over time. In the UK, the metric typically used is a measure of total N deposition over 1–3 years, despite evidence that N accumulates in many ecosystems and impacts from low-level exposure can take considerable time to develop. Improvements in N deposition modelling now allow the development of metrics which incorporate the long-term history of pollution, as well as current exposure. Here we test the potential of alternative N deposition metrics to explain vegetation compositional variability in British semi-natural habitats. We assembled 36 individual datasets representing 48,332 occurrence records in 5479 quadrats from 1683 sites, and used redundancy analyses to test the explanatory power of 33 alternative N metrics based on national pollutant deposition models. We find convincing evidence for N deposition impacts across datasets and habitats, even when accounting for other large-scale drivers of vegetation change. Metrics that incorporate long-term N deposition trajectories consistently explain greater compositional variance than 1–3 year N deposition. There is considerable variability in results across habitats and between similar metrics, but overall we propose that a thirty-year moving window of cumulative deposition is optimal to represent impacts on plant communities for application in science, policy and management.

Plant growth in nitrogen (N)-limited, unfertilised terrestrial ecosystems should respond to additional N inputs from atmospheric deposition (Ndep). We investigated this for sites in Great Britain (GB) by compiling 796 estimates of net primary productivity (NPP) from measured biomass production over the period 1932–2014, although the great majority were for 1990 onwards. The sites were largely vegetated with shrubs, grass and bracken, and had a wide range of Ndep (0.5–3.3 gN m−2 a−1 in 2000). The measured NPP estimates were compared with calculated values from the biogeochemical ecosystem model N14CP, which predicts that NPP depends strongly upon Ndep. The measured and modelled average total NPP values (gC m−2 a−1) from all data were 387 (standard deviation, SD = 193) and 377 (SD = 72) respectively. Measured and modelled averages for vegetation classes followed the sequence: broadleaved trees ~ needle-leaved trees > herbs (rough grassland + bracken) ~ shrubs. After averaging measured values for sites in individual model grid cells (5 km × 5 km) with 10 or more replicates, the measured and modelled NPP values were correlated (n = 26, r2 = 0.22, p = 0.011), with a slope close to unity. Significant linear relationships were found between measured ln NPP and cumulative Ndep for both herbs (n = 298, p = 0.021) and shrubs (n = 473, p = 0.006), with slopes comparable to those predicted with the model. The results suggest that semi-natural NPP in GB depends positively upon Ndep, in a manner that agrees quantitatively with N14CP predictions. Calculations with the model, using modelled temporal variation in Ndep, indicate that fertilisation by Ndep caused average increases in semi-natural NPP over the period 1800 to 2010 of 30% for shrubs, 71% for herbs, and 91% for broadleaved trees. Combined with previous published results for forests, our findings suggest a general and widespread vegetation response to fertilisation by Ndep.

Nitrogen (N) deposition poses a severe risk to global terrestrial ecosystems, and managing this threat is an important focus for air pollution science and policy. To understand and manage the impacts of N deposition, we need metrics which accurately reflect N deposition pressure on the environment, and are responsive to changes in both N deposition and its impacts over time. In the UK, the metric typically used is a measure of total N deposition over 1–3 years, despite evidence that N accumulates in many ecosystems and impacts from low-level exposure can take considerable time to develop. Improvements in N deposition modelling now allow the development of metrics which incorporate the long-term history of pollution, as well as current exposure. Here we test the potential of alternative N deposition metrics to explain vegetation compositional variability in British semi-natural habitats. We assembled 36 individual datasets representing 48,332 occurrence records in 5479 quadrats from 1683 sites, and used redundancy analyses to test the explanatory power of 33 alternative N metrics based on national pollutant deposition models. We find convincing evidence for N deposition impacts across datasets and habitats, even when accounting for other large-scale drivers of vegetation change. Metrics that incorporate long-term N deposition trajectories consistently explain greater compositional variance than 1–3 year N deposition. There is considerable variability in results across habitats and between similar metrics, but overall we propose that a thirty-year moving window of cumulative deposition is optimal to represent impacts on plant communities for application in science, policy and management.

Plant growth in nitrogen (N)-limited, unfertilised terrestrial ecosystems should respond to additional N inputs from atmospheric deposition (Ndep). We investigated this for sites in Great Britain (GB) by compiling 796 estimates of net primary productivity (NPP) from measured biomass production over the period 1932–2014, although the great majority were for 1990 onwards. The sites were largely vegetated with shrubs, grass and bracken, and had a wide range of Ndep (0.5–3.3 gN m−2 a−1 in 2000). The measured NPP estimates were compared with calculated values from the biogeochemical ecosystem model N14CP, which predicts that NPP depends strongly upon Ndep. The measured and modelled average total NPP values (gC m−2 a−1) from all data were 387 (standard deviation, SD = 193) and 377 (SD = 72) respectively. Measured and modelled averages for vegetation classes followed the sequence: broadleaved trees ~ needle-leaved trees > herbs (rough grassland + bracken) ~ shrubs. After averaging measured values for sites in individual model grid cells (5 km × 5 km) with 10 or more replicates, the measured and modelled NPP values were correlated (n = 26, r2 = 0.22, p = 0.011), with a slope close to unity. Significant linear relationships were found between measured ln NPP and cumulative Ndep for both herbs (n = 298, p = 0.021) and shrubs (n = 473, p = 0.006), with slopes comparable to those predicted with the model. The results suggest that semi-natural NPP in GB depends positively upon Ndep, in a manner that agrees quantitatively with N14CP predictions. Calculations with the model, using modelled temporal variation in Ndep, indicate that fertilisation by Ndep caused average increases in semi-natural NPP over the period 1800 to 2010 of 30% for shrubs, 71% for herbs, and 91% for broadleaved trees. Combined with previous published results for forests, our findings suggest a general and widespread vegetation response to fertilisation by Ndep.

CESTES is a global database for metaCommunity Ecology: Species, Traits, Environment and Space. It compiles 80 datasets from trait-based studies. Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. CESTES presents a harmonized structure and covers a diversity of ecosystem types (marine, terrestrial, freshwater), taxonomic groups (plants, vertebrates, invertebrates...), geographical regions, and spatial scales. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available (https://icestes.github.io/sharedata). A zipped folder called “CESTES.zip” includes two alternative formats for the CESTES database: - a “xCESTES” folder that includes 80 Excel files (one file per dataset), each named according to the following structure: “AuthorPublicationYear.xlsx” - a “rCESTES” folder that includes the CESTES core processed database (comm, traits, envir, coord matrices) as an R list object “CESTES.RData” plus two R scripts, and two metadata tables for data processing and exploration. This “CESTES.zip” folder also includes: - an extended metadata table, “CESTES_metadata.xlsx”, that provides the general metadata information of all the datasets, - a tutorial document, “HOW_TO_SHARE_MY_DATA_FOR_CESTES.pdf”, that explains how to share data for integrating future datasets in the database. A second zipped folder, called "ceste.zip", corresponds to the non-spatial ancillary to CESTES. We provide access to 10 additional datasets that were not completely suitable for the CESTES database, due to the absence of spatial information or insufficient metadata but that were potentially valuable for their three other data matrices (comm, traits, envir). They follow the same structure as CESTES, except that they do not present the “coord” sheet and sometimes include only partial metadat, CESTES is a global database for metaCommunity Ecology: Species, Traits, Environment and Space. It compiles 80 datasets from trait-based studies. Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. CESTES presents a harmonized structure and covers a diversity of ecosystem types (marine, terrestrial, freshwater), taxonomic groups (plants, vertebrates, invertebrates...), geographical regions, and spatial scales. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available (https://icestes.github.io/sharedata). A zipped folder called “CESTES.zip” includes two alternative formats for the CESTES database: - a “xCESTES” folder that includes 80 Excel files (one file per dataset), each named according to the following structure: “AuthorPublicationYear.xlsx” - a “rCESTES” folder that includes the CESTES core processed database (comm, traits, envir, coord matrices) as an R list object “CESTES.RData” plus two R scripts, and two metadata tables for data processing and exploration. This “CESTES.zip” folder also includes: - an extended metadata table, “CESTES_metadata.xlsx”, that provides the general metadata information of all the datasets, - a tutorial document, “HOW_TO_SHARE_MY_DATA_FOR_CESTES.pdf”, that explains how to share data for integrating future datasets in the database. A second zipped folder, called "ceste.zip", corresponds to the non-spatial ancillary to CESTES. We provide access to 10 additional datasets that were not completely suitable for the CESTES database, due to the absence of spatial information or insufficient metadata but that were potentially valuable for their three other data matrices (comm, traits, envir). They follow the same structure as CESTES, except that they do not present the “coord” sheet and sometimes include only partial metadat

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board.

1. Dispersal is essential for species to survive the threats of habitat destruction and climate change. Combining descriptions of dispersal ability with those of landscape structure, the concept of functional connectivity has been popular for understanding and predicting species' spatial responses to environmental change. 2. Following recent advances, the functional connectivity concept is now able to move beyond landscape structure to consider more explicitly how other external factors such as climate and resources affect species movement. We argue that these factors, in addition to a consideration of the complete dispersal process, are critical for an accurate understanding of functional connectivity for plant species in response to environmental change. 3. We use recent advances in dispersal, landscape and molecular ecology to describe how a range of external factors can influence effective dispersal in plant species, and how the resulting functional connectivity can be assessed. 4. Synthesis. We define plant functional connectivity as the effective dispersal of propagules or pollen among habitat patches in a landscape. Plant functional connectivity is determined by a combination of landscape structure, interactions between plant, environment and dispersal vectors, and the successful establishment of individuals. We hope that this consolidation of recent research will help focus future connectivity research and conservation.

Background: Intensive farming affects farmland biodiversity, and some arable plants in particular. Increasing crop genetic diversity can increase crop productivity or resilience and could also benefit rare arable plants. Aims: We examined whether barley presence, sowing density and genetic diversity impacted the rare plant Valerianella rimosa and explored possible underlying mechanisms. Methods: In a field study near Dundee, Scotland, we sowed plots of five single barley genotypes, and all five genotypes combined, at three densities; we also had barley-free plots. Valerianella seeds were sown into half of all plots. Measured responses included early-season cover and harvest biomass of barley and common weeds, abiotic parameters (soil moisture, light) and establishment, biomass and seed production by V. rimosa. Results: Barley presence promoted V. rimosa establishment early in the growing season, but without barley density or genetic diversity effects. By harvest, the impact of barley presence on V. rimosa abundance was lost; there were no effects on Valerianella seed production. Barley negatively impacted common weeds, but V. rimosa did not benefit from any indirect facilitation by barley, being bigger without barley. Conclusions: Early beneficial effects of barley on V. rimosa abundance appear offset by late-season competition. However, limited impacts of barley on V. rimosa reproductive success, and negative impacts on common weeds, indicate crops might play a role in conservation management of rare arable plants by creating space in the weed community.

Understanding the mechanisms of community assembly may provide evidence to improve crop management, and in particular how weeds impact on crop yields. Focussing on plant functional traits and their diversity, we analysed a crop–weed interaction study with different levels of weed species and barley cultivar diversity to assess how weed species and barley cultivars respond to competition. Pre-emption of light resources by the taller barley did not impact on the weeds, with both weeds and barley showing similar order of magnitude shifts in height, specific leaf area and leaf dry matter content in response to crop–weed competition. These shifts were to a more conservative growth pattern, and suggest in this study a greater importance of below- than above-ground interactions in driving trait responses. The mixture of barley cultivars shifted the weeds to a more conservative growth pattern compared to the cultivar monocultures. The results indicate that cultivar mixtures could result in less need for weed control in arable fields, and possibly that the development of complementary cultivar mixtures could reinforce this effect. This confirms the results of other studies which show that mixtures either improve yields or make yields less variable in response to weed competition.

Intercropping is a farming practice involving two or more crop species, or genotypes, growing together and coexisting for a time. On the fringes of modern intensive agriculture, intercropping is important in many subsistence or low-input/resource-limited agricultural systems. By allowing genuine yield gains without increased inputs, or greater stability of yield with decreased inputs, intercropping could be one route to delivering ‘sustainable intensification’. We discuss how recent knowledge from agronomy, plant physiology and ecology can be combined with the aim of improving intercropping systems. Recent advances in agronomy and plant physiology include better understanding of the mechanisms of interactions between crop genotypes and species – for example, enhanced resource availability through niche complementarity. Ecological advances include better understanding of the context-dependency of interactions, the mechanisms behind disease and pest avoidance, the links between above- and below-ground systems, and the role of microtopographic variation in coexistence. This improved understanding can guide approaches for improving intercropping systems, including breeding crops for intercropping. Although such advances can help to improve intercropping systems, we suggest that other topics also need addressing. These include better assessment of the wider benefits of intercropping in terms of multiple ecosystem services, collaboration with agricultural engineering, and more effective interdisciplinary research.

Summary Food security is currently considered a major global problem. However, increasing intensity of food production in agricultural systems has driven reductions in farmland biodiversity. A major challenge is to enable biodiversity conservation whilst addressing the problem of food security. Here we describe how facilitative plant-plant interactions in crop systems could be used to help strike this balance. An obvious example is that of intercropping systems, where combinations of crop species can – under some circumstances – deliver reduced inputs of agrochemicals (fertilisers, pesticides) per unit yield, with potential knock-on benefits for biodiversity conservation. Other facilitative processes can also play a role in biodiversity conservation. Increased intra-specific crop genetic diversity can help protect crops from pests and diseases. Although overlooked in facilitation research, we argue that the mechanisms operate in a manner which is directly analogous to associational defence against herbivores, a process well-recognised in the facilitation literature. As with intercropping, the benefits to nature conservation arise from reduced pesticide use per unit harvested crop. Crops may have facilitative effects on some arable weed species, particularly those that are currently considered rare in intensive farming systems. Work is in its early stages to understand the underlying mechanisms, but it appears that crops might create niche space to which some weed species are adapted. Increasing plant species diversity through niche space creation may then have cascading benefits for other components of farmland biodiversity. Our new understanding of facilitative processes arising from work on crop systems has lessons for the study of facilitative interactions in natural and semi-natural communities. We argue that, although easier to identify and quantify in crop systems, some of these facilitative processes have to date been overlooked in studies of non-crop systems