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Herbivory assessments were made at the plant community and species levels. We focused on three plant species with a widespread occurrence across the temperature gradient: cuckooflower (Cardamine pratensis, Linnaeus), common mouse-ear (Cerastium fontanum, Baumgerten), and marsh violet (Viola palustris, Linnaeus). For assessments of invertebrate herbivory at the species level, thirty individuals per species of C. pratensis, C. fontanum, and V. palustris were marked in each of ten plots, using a stratified random sampling method where individuals were randomly selected, but the full range of within-plot soil temperatures was represented. For assessments of invertebrate herbivory at the community level, five 50 × 50 cm quadrats were marked at random points in eight of the plots that best captured the full temperature gradient. The community-level herbivory assessment was conducted on 19th June. The number of damaged plants was recorded out of 100 random individuals, selected using a 10 × 10 grid within each 50 × 50 cm quadrat. For the species-level herbivory assessment, individual marked plants were surveyed for signs of invertebrate herbivory every two weeks from 30th May to 2nd July, generating three time-points per species. At each survey, all marked individuals for each species were assessed within a 48-hour period. Plants were recorded as damaged or not damaged by invertebrate herbivores at each time-point. Further details of how phenological stage of development, vegetation community composition, soil temperature, moisture, pH, nitrate, ammonium, and phosphate were recorded are provided in the supporting documentation. This is a dataset of environmental data, vegetation cover, and community- and species-level invertebrate herbivory, sampled at 14 experimental soil plots in the Hengill geothermal valley, Iceland, from May to July 2017. The plots span a temperature gradient of 5-35 °C on average over the sampling period, yet they occur within 1 km of each other and have similar soil moisture, pH, nitrate, ammonium, and phosphate.

Aim: Climate warming and biodiversity loss both alter plant productivity, yet we lack an understanding of how biodiversity regulates the responses of ecosystems to warming. In this study, we examine how plant diversity regulates the responses of grassland productivity to experimental warming using meta-analytic techniques. Location: Global Major taxa studied: Grassland ecosystems Methods: Our meta-analysis is based on warming responses of 40 different plant communities obtained from 20 independent studies on grasslands across five continents. Results: Our results show that plant diversity and its responses to warming were the most important factors regulating the warming effects on plant productivity, among all the factors considered (plant diversity, climate and experimental settings). Specifically, warming increased plant productivity when plant diversity (indicated by effective number of species) in grasslands was lesser than 10, whereas warming decreased plant productivity when plant diversity was greater than 10. Moreover, the structural equation modelling showed that the magnitude of warming enhanced plant productivity by increasing the performance of dominant plant species in grasslands of diversity lesser than 10. The negative effects of warming on productivity in grasslands with plant diversity greater than 10 were partly explained by diversity-induced decline in plant dominance. Main Conclusions: Our findings suggest that the positive or negative effect of warming on grassland productivity depends on how biodiverse a grassland is. This could mainly owe to differences in how warming may affect plant dominance and subsequent shifts in interspecific interactions in grasslands of different plant diversity levels.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.AerChemMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.

This dataset contains spatial predictions of the potential environmental spaces for pingos, ice-wedge polygons and rock glaciers across the Northern Hemisphere permafrost areas. The potential environmental spaces, i.e. conditions where climate, topography and soil properties are suitable for landform presence, were predicted with statistical ensemble modelling employing geospatial data on environmental conditions at 30 arc-second resolution (~1 km). In addition to the baseline period (1950-2000), the predictions are provided for 2041-2060 and 2061-2080 using climate-forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). The resulting dataset consists of five spatial predictions for each landform in GeoTIFF format.The data provide new information on 1) the fine-scale spatial distribution of permafrost landforms in the Northern Hemisphere, 2) the potential future alterations in the environmental suitability for permafrost landforms due to climate change, and 3) the circumpolar distribution of various ground ice types, and can 4) facilitate efforts to inventory permafrost landforms in incompletely mapped areas.

Figure 1data_Exp 2Figure 1 data: Condition of experimental seedlings in hummocks with contrasting shrub density and tree canopy in Experiment 2: No Trees - Low Shrub biomass (NTLS), No Trees - High Shrub biomass (NTHS), Present Trees - Low Shrub biomass (PTLS) and Present Trees - High shrub biomass (PTHS) during the warmest growing season (2011) and at the end of the experiment (2013). Seedling condition was defined as: healthy (< 50% of the needles turned yellow or brown) or unhealthy (> 50% of the needles turned yellow or brown). Seedlings were 1 month old at plantation time in the July 2010.Table 1_environmental conditions_Exp 1Table 1 data: Environmental conditions and vegetation characteristics in hummocks (circular and bands) and lawns for Experiment 1. Water table depth below surface is an average for the four growing seasons (2010-2013)Table 2_ photosynthesis data_Exp 1Table 2 photosynthesis data: Photosynthesis rates for experimental pine seedlings in hummocks (circular and bands) versus adjacent lawns for Experiment 1.Table 2_seedling responses_Exp 1Table 2 data: Responses of experimental pine seedlings in hummocks (circular and bands) versus adjacent lawns for Experiment 1 after 4 growing seasons. ST: Seeds inserted on top of moss; SB: Seeds inserted below moss; Small seedling (1 month old at plantation time); Large seedling (2 months old at plantation time). Emergence = % of planted seeds emerged after 1 year. Condition = % healthy seedlings. Stem growth corresponds to vertical stem growth for germinating (ST and SB) seedlings and new stem growth for older (small and large) seedlings.Table 3_regression seedling-environment_Exp 1Table 3 data for generalized linear models assessing the responses of experimental pine seedlings in hummocks (circular and bands) and adjacent lawns for Experiment 1 during the whole experimental period (2010-2013). ST: Seedlings from seeds inserted on top of moss; SB: Seedlings from seeds inserted below moss; Small seedling (1 month old at plantation time); Large seedling (2 months old at plantation time). Condition = % healthy seedlings. Growth = stem growth.Table 4_Environmental data_Exp 2Table 4: Environmental conditions in hummocks with contrasting shrub density and tree canopy in Experiment 2: No Trees - Low Shrub biomass (NTLS), No Trees - High Shrub biomass (NTHS), Present Trees - Low Shrub biomass (PTLS) and Present Trees - High shrub biomass (PTHS).Table 4 and Table S5a_seedling performance_Exp 2Table 4: Seedling performance in hummocks with contrasting shrub density and tree canopy in Experiment 2: No Trees - Low Shrub biomass (NTLS), No Trees - High Shrub biomass (NTHS), Present Trees - Low Shrub biomass (PTLS) and Present Trees - High shrub biomass (PTHS). Seedling emergence, condition and survival from seeds inserted below the moss (SB), and from small planted seedlings.Table S3_cox regression (survival analysis)_Exp 1Table S3: Data for Cox survival analysis for experimental pine seedlings in hummocks (circular and bands) versus adjacent lawns during 2010-2013. ST: Seedlings from seeds inserted on top of moss; SB: Seedlings from seeds inserted below moss; Small seedling (1 month old, 10 cm tall at plantation time); Large seedling (2 months old, 30 cm tall at plantation time).Table S4_ regression seedling-environment 2011_Exp 1Table S4: Data for generalized linear models assessing the responses of experimental pine seedlings in hummocks (circular and bands) and adjacent lawns for Experiment 1 in 2011. Small seedling (1 month old, 10 cm tall at plantation time); Large seedling (2 months old, 30 cm tall at plantation time). Condition = % healthy seedlings. Growth = stem growth. Boreal ecosystems are warming roughly twice as fast as the global average, resulting in woody expansion that could further speed up the climate warming. Boreal peatbogs are waterlogged systems that store more than 30% of the global soil carbon. Facilitative effects of shrubs and trees on the establishment of new individuals could increase tree cover with profound consequences for the structure and functioning of boreal peatbogs, carbon sequestration and climate. We conducted two field experiments in boreal peatbogs to assess the mechanisms that explain tree seedling recruitment and to estimate the strength of positive feedbacks between shrubs and trees. We planted seeds and seedlings of Pinus sylvestris in microsites with contrasting water-tables and woody cover and manipulated both shrub canopy and root competition. We monitored seedling emergence, growth and survival for up to four growing seasons and assessed how seedling responses related to abiotic and biotic conditions. We found that tree recruitment is more successful in drier topographical microsites with deeper water-tables. On these hummocks, shrubs have both positive and negative effects on tree seedling establishment. Shrub cover improved tree seedling condition, growth and survival during the warmest growing season. In turn, higher tree basal area correlates positively with soil nutrient availability, shrub biomass and abundance of tree juveniles. Synthesis. Our results suggest that shrubs facilitate tree colonization of peatbogs which further increases shrub growth. These facilitative effects seem to be stronger under warmer conditions suggesting that a higher frequency of warmer and dry summers may lead to stronger positive interactions between shrubs and trees that could eventually facilitate a shift from moss to tree-dominated systems.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.

Aim: Animal migration strategies balance trade-offs between mortality and reproduction in seasonal environments. Knowledge of broad-scale biogeographical patterns of animal migration is important for understanding ecological drivers of migratory behaviours. Here we present a flyway-scale assessment of the spatial structure and seasonal dynamics of the Afro-Palearctic bird migration system and explore how phenology of the environment guides long-distance migration. Location: Europe and Africa. Time period: 2009–2017. Major taxa studied: Birds. Methods: We compiled an individual-based dataset comprising 23 passerine and near-passerine species of 55 European breeding populations where a total of 564 individuals were tracked migrating between Europe and sub-Saharan Africa. In addition, we used remote sensed observations on primary productivity (NDVI) to estimate the timing of vegetation green-up in spring and senescence in autumn across Europe. First, we described how individual breeding and non-breeding sites and the migratory flyways link geographically. Second, we examined how migration timing along the two major Afro-Palearctic flyways is tuned with vegetation phenology en route and at the breeding sites. Results: While we found the longitudes of individual breeding and non-breeding sites to be strongly positively related, the latitudes of breeding and non-breeding sites were negatively related. In autumn, timing of migration was similar along the Western and the Eastern flyways and happened ahead of the autumnal senescence of vegetation. In spring, migration timing was approximately two weeks later along the Eastern flyway than on the Western flyway which coincided with the later spring green-up in Eastern Europe. Main Conclusions: Migration of the Afro-Palearctic landbirds follows a longitudinally parallel leap-frog migration pattern where migrants track vegetation green-up in spring and depart before vegetation senescence in autumn. However, the ongoing global change have the potential to disrupt this spatiotemporal synchronization between migration timing and spring green-up with variable effects on different migrant populations.

Supplementary material for the publication " Agricultural biogas plants as a hub to foster circular economy and bioenergy: An assessment using material substance and energy flow analysis" Burg, V., b, Rolli, C., Schnorf, V., Scharfy, D., Anspach, V., Bowman, G. Today's agro-food system is typically based on linear fluxes (e.g. mineral fertilizers importation), when a circular approach should be privileged. The production of biogas as a renewable energy source and digestate, used as an organic fertilizer, is essential for the circular economy in the agricultural sector. This study investigates the current utilization of wet biomass in agricultural anaerobic digestion plants in Switzerland in terms of mass, nutrients, and energy flows, to see how biomass use contributes to circular economy and climate change mitigation through the substitution effect of mineral fertilizers and fossil fuels. We quantify the system and its benefits in details and examine future developments of agricultural biogas plants using different scenarios. Our results demonstrate that agricultural anaerobic digestion could be largely increased, as it could provide ten times more biogas by 2050, while saving significant amounts of mineral fertilizer and GHG emissions.

Climate change interacts with local processes to threaten biodiversity by disrupting the complex network of ecological interactions. While changes in network interactions drastically affect ecosystems, how ecological networks respond to climate change, in particular warming and nutrient supply fluctuation, is largely unknown. Here, using an equation-free modeling approach on monthly plankton community data in ten Swiss lakes, we show that the number and strength of plankton community interactions fluctuate and respond nonlinearly to water temperature and phosphorus. While lakes show system-specific responses, warming generally reduces network interactions, particularly under high phosphate levels. This network reorganization shifts trophic control of food webs, leading to consumers being controlled by resources. Small grazers and cyanobacteria emerge as sensitive indicators of changes in plankton networks. By exposing the outcomes of a complex interplay between environmental drivers, our results provide tools for studying and advancing our understanding of how climate change impacts entire ecological communities.