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Research data keyboard_double_arrow_right Dataset 2022Publisher:Zenodo Bukoski, Jacob; Cook-Patton, Susan C.; Melikov, Cyril; Ban, Hongyi; Chen, Jessica Liu; Goldman, Elizabeth D.; Harris, Nancy L.; Potts, Matthew D.;This project systematically reviewed the literature for measurements of aboveground carbon stocks in monoculture plantation forests. The data compiled here are for monoculture (single-species) plantation forests, which are a subset of a broader review to identify empirical measurements of carbon stocks across all forest types. The database is structured similarly to that of the ForC (https://forc-db.github.io/) and GROA databases (https://github.com/forc-db/GROA). When using these data, please cite: Bukoski, J.J., Cook-Patton, S.C., Melikov, C., Ban, H., Liu, J.C., Harris, N., Goldman, E., and Potts, M.D. 2022. Rates and drivers of aboveground carbon accumulation in global monoculture plantation forests. Nature Communications 13(4206). doi: 10.1038/s41467-022-31380-7 The code for all analyses in Bukoski et al., 2022 (paper associated with this dataset) is available at https://github.com/jbukoski/GPFC (doi: 10.5281/zenodo.6588710).
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.6555216&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:NERC Environmental Information Data Centre Reinsch, S.; Koller, E.; Sowerby, A.; De Dato, G.; Estiarte, M.; Guidolotti, G.; Kovács-Láng, E.; Kröel-Dula, G; Lellei-Kovács, E.; Larsen, K.S.; Liberati, D.; Ogaya, R; Peñuelas, J.; Ransijn, J.; Robinson, D.A.; Schmidt, I.K.; Smith, A.R.; Tietema, A.; Dukes, J.S.; Beier, C.; Emmett, B.A.;The data consists of annual measurements of standing aboveground plant biomass, annual aboveground net primary productivity and annual soil respiration between 1998 and 2012. Data were collected from seven European shrublands that were subject to the climate manipulations drought and warming. Sites were located in the United Kingdom (UK), the Netherlands (NL), Denmark ( two sites, DK-B and DK-M), Hungary (HU), Spain (SP) and Italy (IT). All field sites consisted of untreated control plots, plots where the plant canopy air is artificially warmed during night time hours, and plots where rainfall is excluded from the plots at least during the plants growing season. Standing aboveground plant biomass (grams biomass per square metre) was measured in two undisturbed areas within the plots using the pin-point method (UK, DK-M, DK-B), or along a transect (IT, SP, HU, NL). Aboveground net primary productivity was calculated from measurements of standing aboveground plant biomass estimates and litterfall measurements. Soil respiration was measured in pre-installed opaque soil collars bi-weekly, monthly, or in measurement campaigns (SP only). The datasets provided are the basis for the data analysis presented in Reinsch et al. (2017) Shrubland primary production and soil respiration diverge along European climate gradient. Scientific Reports 7:43952 https://doi.org/10.1038/srep43952 Standing biomass was measured using the non-destructive pin-point method to assess aboveground biomass. Measurements were conducted at the state of peak biomass specific for each site. Litterfall was measured annually using litterfall traps. Litter collected in the traps was dried and the weight was measured. Aboveground biomass productivity was estimated as the difference between the measured standing biomass in year x minus the standing biomass measured the previous year. Soil respiration was measured bi-weekly or monthly, or in campaigns (Spain only). It was measured on permanently installed soil collars in treatment plots. The Gaussen Index of Aridity (an index that combines information on rainfall and temperature) was calculated using mean annual precipitation, mean annual temperature. The reduction in precipitation and increase in temperature for each site was used to calculate the Gaussen Index for the climate treatments for each site. Data of standing biomass and soil respiration was provided by the site responsible. Data from all sites were collated into one data file for data analysis. A summary data set was combined with information on the Gaussen Index of Aridity Data were then exported from these Excel spreadsheet to .csv files for ingestion into the EIDC.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 06 Jan 2022Publisher:Dryad Jarvie, Scott; Ingram, Travis; Chapple, David; Hitchmough, Rodney; Nielsen, Stuart; Monks, Joanne M.;Although GPS coordinates for current populations are not included due to the potential threat of poaching, the climate variables for each species are provided. The records for extant gecko and skinks mainly came from the New Zealand's Department of Conervation Herpetofauna Database. After updating the taxonomy and cleaning the data to reflect the taxonomy as at 2019 of 43 geckos speceis recognised across seven genera and 61 species in genus, we then thinned the occurrence records at a 1 km resolution for all species then predicted distributions for those with > 15 records using species distribution models. The climate variables for each species were selected among annual mean temperature (bio1), maximum temperature of the warmest month (bio5), minimum temperature of the coldest month (bio6), mean temperature of driest quarter (bio9), mean temperature of wettest quarter (bio10), and precipitation of the driest quarter (bio17). To reduce multicollinearity in species distribution models for each species, we only retained climate variables with a variable inflation factor < 10. The climate variables were from the CHELSA database (https://chelsa-climate.org/), which can be freely downloaded for current and future scenarios. We also provide MCC tree files for the geckos and skinks. The phylogenetic trees have been constructed for NZ geckos by (Nielsen et al., 2011) and for NZ skinks by (Chapple et al., 2009). For geckos we used a subset of the sequences used by Nielsen et al. (2011) for four genes, two nuclear (RAG 1, PDC) and two mitochondrial (16S, ND2 along with flanking tRNA sequences). For skinks, we used sequences from Chapple et al. (2009) for one nuclear (RAG 1) and five mitochondrial (ND2, ND4, Cyt b, 12S and 16S) genes, and additional ND2 sequences for taxa not included in the original phylogeny (Chapple et al., 2011, p. 201). In total we used sequences for all recognised extant taxa (Hitchmough et al., 2016) as at 2019 except for three species of skink (O. aff. inconspicuum “Okuru”, O. robinsoni, and O. aff. inconspicuum “North Otago”) and two species of gecko (M. “Cupola” and W. “Kaikouras”) for which genetic data were not available. Aim: The primary drivers of species and population extirpations have been habitat loss, overexploitation, and invasive species, but human-mediated climate change is expected to be a major driver in future. To minimise biodiversity loss, conservation managers should identify species vulnerable to climate change and prioritise their protection. Here, we estimate climatic suitability for two speciose taxonomic groups, then use phylogenetic analyses to assess vulnerability to climate change. Location: Aotearoa New Zealand (NZ) Taxa: NZ lizards: diplodactylid geckos and eugongylinae skinks Methods: We built correlative species distribution models (SDMs) for NZ geckos and skinks to estimate climatic suitability under current climate and 2070 future-climate scenarios. We then used Bayesian phylogenetic mixed models (BPMMs) to assess vulnerability for both groups with predictor variables for life history traits (body size and activity phase) and current distribution (elevation and latitude). We explored two scenarios: an unlimited dispersal scenario, where projections track climate, and a no-dispersal scenario, where projections are restricted to areas currently identified as suitable. Results: SDMs projected vulnerability to climate change for most modelled lizards. For species’ ranges projected to decline in climatically suitable areas, average decreases were between 42–45% for geckos and 33–91% for skinks, although area did increase or remain stable for a minority of species. For the no-dispersal scenario, the average decrease for geckos was 37–52% and for skinks was 33–52%. Our BPMMs showed phylogenetic signal in climate change vulnerability for both groups, with elevation increasing vulnerability for geckos, and body size reducing vulnerability for skinks. Main conclusions: NZ lizards showed variable vulnerability to climate change, with most species’ ranges predicted to decrease. For species whose suitable climatic space is projected to disappear from within their current range, managed relocation could be considered to establish populations in regions that will be suitable under future climates.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023 NetherlandsPublisher:DANS Data Station Social Sciences and Humanities Authors: Gao, X.; De Hoge, I.E.; Fischer, A.R.H.;Fashion products made from repurposed materials (e.g., backpacks made from pineapple leaves) have become more prevalent nowadays, and their environmental sustainability is one of the core advantages. Yet, it is currently unclear how consumers respond to products made from repurposed materials. We conducted three experiments to examine the effects of three material features, namely function, sustainability, and distinguishability, on consumer preferences for fashion products made from repurposed materials. The results indicate that, when the function of repurposed materials is as good as that of conventional materials, consumers prefer a product made from repurposed materials over the same product made from conventional materials. Also, consumers in general prefer repurposed materials to be less visually distinguishable. Finally, when the sustainability of the repurposed products is emphasized, consumers appear more likely to choose products made from repurposed materials, even when these products have an inferior function. In conclusion, to promote fashion products made from repurposed materials, marketers may emphasize the function and sustainability of repurposed materials, and producers may manufacture repurposed materials that visually resemble conventional materials.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Funded by:EC | PARIS REINFORCEEC| PARIS REINFORCEDoukas, Haris; Spiliotis, Evangelos; Jafari, Mohsen A.; Giarola, Sara; Nikas, Alexandros;This dataset contains the underlying data for the following publication: Doukas, H., Spiliotis, E., Jafari, M. A., Giarola, S. & Nikas, A. (2021). Low-cost emissions cuts in container shipping: Thinking inside the box. Transportation Research Part D: Transport and Environment, 94, 102815, https://doi.org/10.1016/j.trd.2021.102815.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:Zenodo Funded by:EC | REINFORCEEC| REINFORCEAuthors: Mina, Marco;Input files for the ForClim model (version 4.0.1) used in the associated paper. They can be used to to reproduce results of the simulation study. The ForClim model, including the source code, executable and documentation, is freely available under an Open Access license from the website of the original developers at https://ites-fe.ethz.ch/openaccess/. The original climatic dataset used to generate the ForClim input climate files at each site in South Tyrol is freely available at https://doi.pangaea.de/10.1594/PANGAEA.924502 while the CHELSA climate data for future scenarios are available at https://www.chelsa-climate.org. If interested in using this dataset for a research study or a project, please contact Marco Mina ----------------------------------------------------------------------- Hillebrand L, Marzini S, Crespi A, Hiltner U & Mina M (2023) Contrasting impacts of climate change on protection forests of the Italian Alps. Frontiers in Forests and Global Change, 6, 2023 https://doi.org/10.3389/ffgc.2023.1240235 ABSTRACT. Protection forests play a key role in protecting settlements, people, and infrastructures from gravitational hazards such as rockfalls and avalanches in mountain areas. Rapid climate change is challenging the role of protection forests by altering their dynamics, structure, and composition. Information on local- and regional-scale impacts of climate change on protection forests is critical for planning adaptations in forest management. We used a model of forest dynamics (ForClim) to assess the succession of mountain forests in the Eastern Alps and their protective effects under future climate change scenarios. We investigated eleven representative forest sites along an elevational gradient across multiple locations within an administrative region, covering wide differences in tree species structure, composition, altitude, and exposition. We evaluated protective performance against rockfall and avalanches using numerical indices (i.e., linker functions) quantifying the degree of protection from metrics of simulated forest structure and composition. Our findings reveal that climate warming has a contrasting impact on protective effects in mountain forests of the Eastern Alps. Climate change is likely to not affect negatively all protection forest stands but its impact depends on site and stand conditions. Impacts were highly contingent to the magnitude of climate warming, with increasing criticality under the most severe climate projections. Forests in lower-montane elevations and those located in dry continental valleys showed drastic changes in forest structure and composition due to drought-induced mortality while subalpine forests mostly profited from rising temperatures and a longer vegetation period. Overall, avalanche protection will likely be negatively affected by climate change, while the ability of forests to maintain rockfall protection depends on the severity of expected climate change and their vulnerability due to elevation and topography, with most subalpine forests less prone to loosing protective effects. Proactive measures in management should be taken in the near future to avoid losses of protective effects in the case of severe climate change in the Alps. Given the heterogeneous impact of climate warming, such adaptations can be aided by model-based projections and high local resolution studies to identify forest stand types that might require management priority for maintaining protective effects in the future.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:NSF Arctic Data Center Authors: Nelson, Peder;doi: 10.18739/a2jd4pp9c
The major goal of this EAGER project is to create a Big Data mining toolset for the Landsat Time Series that captures, labels, and maps glacier change for use in climate science, hydrology, and Earth science education. This pilot study demonstrates the potential for interactively mapping, visualizing, and labeling glacier changes. What is truly innovative is that IceTrendr not only maps the changes but also uses expert knowledge to label the changes and such labels can be applied to other glaciers exhibiting statistically similar changes. This is much more than just a simple "then and now" approach to glacier mapping. IceTrendr is a means of integrating the power of computing, remote sensing, and expert knowledge to "tell the story " of glacier changes. Our key findings are that the IceTrendr concept and software can provide important functionality for glaciologists and educators interested in studying glacier changes during the Landsat TM timeframe (1984-present). With additional time and funding, there is the exciting and innovative opportunity to build on the IceTrendr framework, to develop much greater utility for mapping glaciers and characterizing glacier change globally. Although this pilot study focused on just five glaciers, with some future funding and effort, IceTrendr will have the potential to map changing glaciers EVERYWHERE over the full Landsat TM timeframe (1984-present). Specifically, concerns with the Landsat TM imagery are that many images are missing during the period 1984-1995 and the automated cloud mask is not effective requiring the user to manually identify cloud-free images. We found that the visualization of the glacier in the IceTrendr window worked well with high-resolution satellite data from Google Earth and visualization was improved with additional high-resolution images from the Polar Geospatial Center. The automated clustering algorithm was a good first step in glacier mapping and when augmented with glacier outlines from the Randall Glacier Inventory, users could readily see changes in glacier extent, brightness, debris cover, as well as changes in surrounding area including glacial lakes and rivers, vegetation, and moraines.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Dryad Leahy, Lily; Scheffers, Brett R.; Andersen, Alan N.; Hirsch, Ben T.; Williams, Stephen E.;Aim: We propose that forest trees create a vertical dimension for ecological niche variation that generates different regimes of climatic exposure, which in turn drives species elevation distributions. We test this hypothesis by statistically modelling the vertical and elevation distributions and microclimate exposure of rainforest ants. Location: Wet Tropics Bioregion, Australia Methods: We conducted 60 ground-to-canopy surveys to determine the vertical (tree) and elevation distributions, and microclimate exposure of ants (101 species) at 15 sites along four mountain ranges. We statistically modelled elevation range size as a function of ant species’ vertical niche breadth and exposure to temperature variance for 55 species found at two or more trees. Results: We found a positive association between vertical niche and elevation range of ant species: for every 3 m increase in vertical niche breadth our models predict a ~150% increase in mean elevation range size. Temperature variance increased with vertical height along the arboreal gradient and ant species exposure to temperature variance explained some of the variation in elevation range size. Main Conclusions: We demonstrate that arboreal ants have broader elevation ranges than ground-dwelling ants and are likely to have increased resilience to climatic variance. The capacity of species to expand their niche by climbing trees could influence their ability to persist over broader elevation ranges. We propose that wherever vertical layering exists - from oceans to forest ecosystems - vertical niche breadth is a potential mechanism driving macrogeographic distribution patterns and resilience to climate change. Data_collections.csv Main survey collections data in a site by species matrix showing all data for all sites surveyed. Tuna baited vials were placed every three metres from ground to canopy in trees at elevation sites at four subregion mountain ranges of the Australian Wet Tropics Bioregion. Note data file includes empty vials that lacked ants. Microclimate_AthertonTemp.csv This file contains Atherton Uplands temperature data from ibuttons deployed at one tree per elevation (200, 400, 600, 800, 1000) at every three metres in height in Dec-Jan 2017- 2018 set to record every half hour. See file Metadata for details of column names and data values.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:Environmental System Science Data Infrastructure for a Virtual Ecosystem; Subalpine and Alpine Species Range Shifts with Climate Change: Temperature and Soil Moisture Manipulations to Test Species and Population Responses (Alpine Treeline Warming Experiment) Authors: Herzog, Sarah; Louthan, Allison; Kueppers, Lara;doi: 10.15485/2008461
Demographic data of Sedum lanceolatum under a climate manipulation experiment (heating and watering). Dataset includes one .csv with demographic data for 232 individuals monitored over 2013-2014 which was used, in part, to draw conclusions in "Elevation effects on vital rate sensitivities generate variation in neighbor effects on population growth rate in Sedum lanceolatum" by Herzog et al. (in review). All data was collected under a watering and warming experiment as part of the Alpine Treeline Warming Experiment at Niwot Ridge, Colorado, USA. There are two main data file formats in this archive: comma-separated values (.csv) which can be read using any simple text editor program, such as TextEdit (Mac) and Notepad (Windows). The .pdf data user’s guide can be read using Adobe Acrobat Reader, or any other compatible software.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Stouffer, Ronald;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.ScenarioMIP.UA.MCM-UA-1-0' 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 Manabe Climate Model v1.0 - University of Arizona climate model, released in 1991, includes the following components: aerosol: Modifies surface albedoes (Haywood et al. 1997, doi: 10.1175/1520-0442(1997)010<1562:GCMCOT>2.0.CO;2), atmos: R30L14 (3.75 X 2.5 degree (long-lat) configuration; 96 x 80 longitude/latitude; 14 levels; top level 0.015 sigma, 15 mb), land: Standard Manabe bucket hydrology scheme (Manabe 1969, doi: 10.1175/1520-0493(1969)097<0739:CATOC>2.3.CO;2), landIce: Specified location - invariant in time, has high albedo and latent heat capacity, ocean: MOM1.0 (MOM1, 1.875 X 2.5 deg; 192 x 80 longitude/latitude; 18 levels; top grid cell 0-40 m), seaIce: Thermodynamic ice model (free drift dynamics). The model was run by the Department of Geosciences, University of Arizona, Tucson, AZ 85721, USA (UA) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: 250 km, ocean: 250 km, seaIce: 250 km.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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Research data keyboard_double_arrow_right Dataset 2022Publisher:Zenodo Bukoski, Jacob; Cook-Patton, Susan C.; Melikov, Cyril; Ban, Hongyi; Chen, Jessica Liu; Goldman, Elizabeth D.; Harris, Nancy L.; Potts, Matthew D.;This project systematically reviewed the literature for measurements of aboveground carbon stocks in monoculture plantation forests. The data compiled here are for monoculture (single-species) plantation forests, which are a subset of a broader review to identify empirical measurements of carbon stocks across all forest types. The database is structured similarly to that of the ForC (https://forc-db.github.io/) and GROA databases (https://github.com/forc-db/GROA). When using these data, please cite: Bukoski, J.J., Cook-Patton, S.C., Melikov, C., Ban, H., Liu, J.C., Harris, N., Goldman, E., and Potts, M.D. 2022. Rates and drivers of aboveground carbon accumulation in global monoculture plantation forests. Nature Communications 13(4206). doi: 10.1038/s41467-022-31380-7 The code for all analyses in Bukoski et al., 2022 (paper associated with this dataset) is available at https://github.com/jbukoski/GPFC (doi: 10.5281/zenodo.6588710).
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.6555216&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:NERC Environmental Information Data Centre Reinsch, S.; Koller, E.; Sowerby, A.; De Dato, G.; Estiarte, M.; Guidolotti, G.; Kovács-Láng, E.; Kröel-Dula, G; Lellei-Kovács, E.; Larsen, K.S.; Liberati, D.; Ogaya, R; Peñuelas, J.; Ransijn, J.; Robinson, D.A.; Schmidt, I.K.; Smith, A.R.; Tietema, A.; Dukes, J.S.; Beier, C.; Emmett, B.A.;The data consists of annual measurements of standing aboveground plant biomass, annual aboveground net primary productivity and annual soil respiration between 1998 and 2012. Data were collected from seven European shrublands that were subject to the climate manipulations drought and warming. Sites were located in the United Kingdom (UK), the Netherlands (NL), Denmark ( two sites, DK-B and DK-M), Hungary (HU), Spain (SP) and Italy (IT). All field sites consisted of untreated control plots, plots where the plant canopy air is artificially warmed during night time hours, and plots where rainfall is excluded from the plots at least during the plants growing season. Standing aboveground plant biomass (grams biomass per square metre) was measured in two undisturbed areas within the plots using the pin-point method (UK, DK-M, DK-B), or along a transect (IT, SP, HU, NL). Aboveground net primary productivity was calculated from measurements of standing aboveground plant biomass estimates and litterfall measurements. Soil respiration was measured in pre-installed opaque soil collars bi-weekly, monthly, or in measurement campaigns (SP only). The datasets provided are the basis for the data analysis presented in Reinsch et al. (2017) Shrubland primary production and soil respiration diverge along European climate gradient. Scientific Reports 7:43952 https://doi.org/10.1038/srep43952 Standing biomass was measured using the non-destructive pin-point method to assess aboveground biomass. Measurements were conducted at the state of peak biomass specific for each site. Litterfall was measured annually using litterfall traps. Litter collected in the traps was dried and the weight was measured. Aboveground biomass productivity was estimated as the difference between the measured standing biomass in year x minus the standing biomass measured the previous year. Soil respiration was measured bi-weekly or monthly, or in campaigns (Spain only). It was measured on permanently installed soil collars in treatment plots. The Gaussen Index of Aridity (an index that combines information on rainfall and temperature) was calculated using mean annual precipitation, mean annual temperature. The reduction in precipitation and increase in temperature for each site was used to calculate the Gaussen Index for the climate treatments for each site. Data of standing biomass and soil respiration was provided by the site responsible. Data from all sites were collated into one data file for data analysis. A summary data set was combined with information on the Gaussen Index of Aridity Data were then exported from these Excel spreadsheet to .csv files for ingestion into the EIDC.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 06 Jan 2022Publisher:Dryad Jarvie, Scott; Ingram, Travis; Chapple, David; Hitchmough, Rodney; Nielsen, Stuart; Monks, Joanne M.;Although GPS coordinates for current populations are not included due to the potential threat of poaching, the climate variables for each species are provided. The records for extant gecko and skinks mainly came from the New Zealand's Department of Conervation Herpetofauna Database. After updating the taxonomy and cleaning the data to reflect the taxonomy as at 2019 of 43 geckos speceis recognised across seven genera and 61 species in genus, we then thinned the occurrence records at a 1 km resolution for all species then predicted distributions for those with > 15 records using species distribution models. The climate variables for each species were selected among annual mean temperature (bio1), maximum temperature of the warmest month (bio5), minimum temperature of the coldest month (bio6), mean temperature of driest quarter (bio9), mean temperature of wettest quarter (bio10), and precipitation of the driest quarter (bio17). To reduce multicollinearity in species distribution models for each species, we only retained climate variables with a variable inflation factor < 10. The climate variables were from the CHELSA database (https://chelsa-climate.org/), which can be freely downloaded for current and future scenarios. We also provide MCC tree files for the geckos and skinks. The phylogenetic trees have been constructed for NZ geckos by (Nielsen et al., 2011) and for NZ skinks by (Chapple et al., 2009). For geckos we used a subset of the sequences used by Nielsen et al. (2011) for four genes, two nuclear (RAG 1, PDC) and two mitochondrial (16S, ND2 along with flanking tRNA sequences). For skinks, we used sequences from Chapple et al. (2009) for one nuclear (RAG 1) and five mitochondrial (ND2, ND4, Cyt b, 12S and 16S) genes, and additional ND2 sequences for taxa not included in the original phylogeny (Chapple et al., 2011, p. 201). In total we used sequences for all recognised extant taxa (Hitchmough et al., 2016) as at 2019 except for three species of skink (O. aff. inconspicuum “Okuru”, O. robinsoni, and O. aff. inconspicuum “North Otago”) and two species of gecko (M. “Cupola” and W. “Kaikouras”) for which genetic data were not available. Aim: The primary drivers of species and population extirpations have been habitat loss, overexploitation, and invasive species, but human-mediated climate change is expected to be a major driver in future. To minimise biodiversity loss, conservation managers should identify species vulnerable to climate change and prioritise their protection. Here, we estimate climatic suitability for two speciose taxonomic groups, then use phylogenetic analyses to assess vulnerability to climate change. Location: Aotearoa New Zealand (NZ) Taxa: NZ lizards: diplodactylid geckos and eugongylinae skinks Methods: We built correlative species distribution models (SDMs) for NZ geckos and skinks to estimate climatic suitability under current climate and 2070 future-climate scenarios. We then used Bayesian phylogenetic mixed models (BPMMs) to assess vulnerability for both groups with predictor variables for life history traits (body size and activity phase) and current distribution (elevation and latitude). We explored two scenarios: an unlimited dispersal scenario, where projections track climate, and a no-dispersal scenario, where projections are restricted to areas currently identified as suitable. Results: SDMs projected vulnerability to climate change for most modelled lizards. For species’ ranges projected to decline in climatically suitable areas, average decreases were between 42–45% for geckos and 33–91% for skinks, although area did increase or remain stable for a minority of species. For the no-dispersal scenario, the average decrease for geckos was 37–52% and for skinks was 33–52%. Our BPMMs showed phylogenetic signal in climate change vulnerability for both groups, with elevation increasing vulnerability for geckos, and body size reducing vulnerability for skinks. Main conclusions: NZ lizards showed variable vulnerability to climate change, with most species’ ranges predicted to decrease. For species whose suitable climatic space is projected to disappear from within their current range, managed relocation could be considered to establish populations in regions that will be suitable under future climates.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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visibility 53visibility views 53 download downloads 15 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023 NetherlandsPublisher:DANS Data Station Social Sciences and Humanities Authors: Gao, X.; De Hoge, I.E.; Fischer, A.R.H.;Fashion products made from repurposed materials (e.g., backpacks made from pineapple leaves) have become more prevalent nowadays, and their environmental sustainability is one of the core advantages. Yet, it is currently unclear how consumers respond to products made from repurposed materials. We conducted three experiments to examine the effects of three material features, namely function, sustainability, and distinguishability, on consumer preferences for fashion products made from repurposed materials. The results indicate that, when the function of repurposed materials is as good as that of conventional materials, consumers prefer a product made from repurposed materials over the same product made from conventional materials. Also, consumers in general prefer repurposed materials to be less visually distinguishable. Finally, when the sustainability of the repurposed products is emphasized, consumers appear more likely to choose products made from repurposed materials, even when these products have an inferior function. In conclusion, to promote fashion products made from repurposed materials, marketers may emphasize the function and sustainability of repurposed materials, and producers may manufacture repurposed materials that visually resemble conventional materials.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.17026/dans-x7c-pyv9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Funded by:EC | PARIS REINFORCEEC| PARIS REINFORCEDoukas, Haris; Spiliotis, Evangelos; Jafari, Mohsen A.; Giarola, Sara; Nikas, Alexandros;This dataset contains the underlying data for the following publication: Doukas, H., Spiliotis, E., Jafari, M. A., Giarola, S. & Nikas, A. (2021). Low-cost emissions cuts in container shipping: Thinking inside the box. Transportation Research Part D: Transport and Environment, 94, 102815, https://doi.org/10.1016/j.trd.2021.102815.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.5666359&type=result"></script>'); --> </script>
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visibility 24visibility views 24 download downloads 1 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:Zenodo Funded by:EC | REINFORCEEC| REINFORCEAuthors: Mina, Marco;Input files for the ForClim model (version 4.0.1) used in the associated paper. They can be used to to reproduce results of the simulation study. The ForClim model, including the source code, executable and documentation, is freely available under an Open Access license from the website of the original developers at https://ites-fe.ethz.ch/openaccess/. The original climatic dataset used to generate the ForClim input climate files at each site in South Tyrol is freely available at https://doi.pangaea.de/10.1594/PANGAEA.924502 while the CHELSA climate data for future scenarios are available at https://www.chelsa-climate.org. If interested in using this dataset for a research study or a project, please contact Marco Mina ----------------------------------------------------------------------- Hillebrand L, Marzini S, Crespi A, Hiltner U & Mina M (2023) Contrasting impacts of climate change on protection forests of the Italian Alps. Frontiers in Forests and Global Change, 6, 2023 https://doi.org/10.3389/ffgc.2023.1240235 ABSTRACT. Protection forests play a key role in protecting settlements, people, and infrastructures from gravitational hazards such as rockfalls and avalanches in mountain areas. Rapid climate change is challenging the role of protection forests by altering their dynamics, structure, and composition. Information on local- and regional-scale impacts of climate change on protection forests is critical for planning adaptations in forest management. We used a model of forest dynamics (ForClim) to assess the succession of mountain forests in the Eastern Alps and their protective effects under future climate change scenarios. We investigated eleven representative forest sites along an elevational gradient across multiple locations within an administrative region, covering wide differences in tree species structure, composition, altitude, and exposition. We evaluated protective performance against rockfall and avalanches using numerical indices (i.e., linker functions) quantifying the degree of protection from metrics of simulated forest structure and composition. Our findings reveal that climate warming has a contrasting impact on protective effects in mountain forests of the Eastern Alps. Climate change is likely to not affect negatively all protection forest stands but its impact depends on site and stand conditions. Impacts were highly contingent to the magnitude of climate warming, with increasing criticality under the most severe climate projections. Forests in lower-montane elevations and those located in dry continental valleys showed drastic changes in forest structure and composition due to drought-induced mortality while subalpine forests mostly profited from rising temperatures and a longer vegetation period. Overall, avalanche protection will likely be negatively affected by climate change, while the ability of forests to maintain rockfall protection depends on the severity of expected climate change and their vulnerability due to elevation and topography, with most subalpine forests less prone to loosing protective effects. Proactive measures in management should be taken in the near future to avoid losses of protective effects in the case of severe climate change in the Alps. Given the heterogeneous impact of climate warming, such adaptations can be aided by model-based projections and high local resolution studies to identify forest stand types that might require management priority for maintaining protective effects in the future.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:NSF Arctic Data Center Authors: Nelson, Peder;doi: 10.18739/a2jd4pp9c
The major goal of this EAGER project is to create a Big Data mining toolset for the Landsat Time Series that captures, labels, and maps glacier change for use in climate science, hydrology, and Earth science education. This pilot study demonstrates the potential for interactively mapping, visualizing, and labeling glacier changes. What is truly innovative is that IceTrendr not only maps the changes but also uses expert knowledge to label the changes and such labels can be applied to other glaciers exhibiting statistically similar changes. This is much more than just a simple "then and now" approach to glacier mapping. IceTrendr is a means of integrating the power of computing, remote sensing, and expert knowledge to "tell the story " of glacier changes. Our key findings are that the IceTrendr concept and software can provide important functionality for glaciologists and educators interested in studying glacier changes during the Landsat TM timeframe (1984-present). With additional time and funding, there is the exciting and innovative opportunity to build on the IceTrendr framework, to develop much greater utility for mapping glaciers and characterizing glacier change globally. Although this pilot study focused on just five glaciers, with some future funding and effort, IceTrendr will have the potential to map changing glaciers EVERYWHERE over the full Landsat TM timeframe (1984-present). Specifically, concerns with the Landsat TM imagery are that many images are missing during the period 1984-1995 and the automated cloud mask is not effective requiring the user to manually identify cloud-free images. We found that the visualization of the glacier in the IceTrendr window worked well with high-resolution satellite data from Google Earth and visualization was improved with additional high-resolution images from the Polar Geospatial Center. The automated clustering algorithm was a good first step in glacier mapping and when augmented with glacier outlines from the Randall Glacier Inventory, users could readily see changes in glacier extent, brightness, debris cover, as well as changes in surrounding area including glacial lakes and rivers, vegetation, and moraines.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Dryad Leahy, Lily; Scheffers, Brett R.; Andersen, Alan N.; Hirsch, Ben T.; Williams, Stephen E.;Aim: We propose that forest trees create a vertical dimension for ecological niche variation that generates different regimes of climatic exposure, which in turn drives species elevation distributions. We test this hypothesis by statistically modelling the vertical and elevation distributions and microclimate exposure of rainforest ants. Location: Wet Tropics Bioregion, Australia Methods: We conducted 60 ground-to-canopy surveys to determine the vertical (tree) and elevation distributions, and microclimate exposure of ants (101 species) at 15 sites along four mountain ranges. We statistically modelled elevation range size as a function of ant species’ vertical niche breadth and exposure to temperature variance for 55 species found at two or more trees. Results: We found a positive association between vertical niche and elevation range of ant species: for every 3 m increase in vertical niche breadth our models predict a ~150% increase in mean elevation range size. Temperature variance increased with vertical height along the arboreal gradient and ant species exposure to temperature variance explained some of the variation in elevation range size. Main Conclusions: We demonstrate that arboreal ants have broader elevation ranges than ground-dwelling ants and are likely to have increased resilience to climatic variance. The capacity of species to expand their niche by climbing trees could influence their ability to persist over broader elevation ranges. We propose that wherever vertical layering exists - from oceans to forest ecosystems - vertical niche breadth is a potential mechanism driving macrogeographic distribution patterns and resilience to climate change. Data_collections.csv Main survey collections data in a site by species matrix showing all data for all sites surveyed. Tuna baited vials were placed every three metres from ground to canopy in trees at elevation sites at four subregion mountain ranges of the Australian Wet Tropics Bioregion. Note data file includes empty vials that lacked ants. Microclimate_AthertonTemp.csv This file contains Atherton Uplands temperature data from ibuttons deployed at one tree per elevation (200, 400, 600, 800, 1000) at every three metres in height in Dec-Jan 2017- 2018 set to record every half hour. See file Metadata for details of column names and data values.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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visibility 28visibility views 28 download downloads 34 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:Environmental System Science Data Infrastructure for a Virtual Ecosystem; Subalpine and Alpine Species Range Shifts with Climate Change: Temperature and Soil Moisture Manipulations to Test Species and Population Responses (Alpine Treeline Warming Experiment) Authors: Herzog, Sarah; Louthan, Allison; Kueppers, Lara;doi: 10.15485/2008461
Demographic data of Sedum lanceolatum under a climate manipulation experiment (heating and watering). Dataset includes one .csv with demographic data for 232 individuals monitored over 2013-2014 which was used, in part, to draw conclusions in "Elevation effects on vital rate sensitivities generate variation in neighbor effects on population growth rate in Sedum lanceolatum" by Herzog et al. (in review). All data was collected under a watering and warming experiment as part of the Alpine Treeline Warming Experiment at Niwot Ridge, Colorado, USA. There are two main data file formats in this archive: comma-separated values (.csv) which can be read using any simple text editor program, such as TextEdit (Mac) and Notepad (Windows). The .pdf data user’s guide can be read using Adobe Acrobat Reader, or any other compatible software.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.15485/2008461&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Stouffer, Ronald;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.ScenarioMIP.UA.MCM-UA-1-0' 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 Manabe Climate Model v1.0 - University of Arizona climate model, released in 1991, includes the following components: aerosol: Modifies surface albedoes (Haywood et al. 1997, doi: 10.1175/1520-0442(1997)010<1562:GCMCOT>2.0.CO;2), atmos: R30L14 (3.75 X 2.5 degree (long-lat) configuration; 96 x 80 longitude/latitude; 14 levels; top level 0.015 sigma, 15 mb), land: Standard Manabe bucket hydrology scheme (Manabe 1969, doi: 10.1175/1520-0493(1969)097<0739:CATOC>2.3.CO;2), landIce: Specified location - invariant in time, has high albedo and latent heat capacity, ocean: MOM1.0 (MOM1, 1.875 X 2.5 deg; 192 x 80 longitude/latitude; 18 levels; top grid cell 0-40 m), seaIce: Thermodynamic ice model (free drift dynamics). The model was run by the Department of Geosciences, University of Arizona, Tucson, AZ 85721, USA (UA) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: 250 km, ocean: 250 km, seaIce: 250 km.
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