The long-term goal of the SOFIA program is to provide a central archive of data and products for all Department of Interior products related to the south Florida Ecosystem restoration program.The primary objectives of this project were to 1) provide a central location for the archive of all products and data collected as part of the USGS PES program and related work for the restoration of the South Florida Ecosystem; and 2) provide a means for customers to obtain the archived information. The database was been developed using PostgreSQL, an open source relational database management system. PostgreSQL was selected because it is freely available, widely used, actively maintained and supported, and runs on all modern UNIX-like and Windows based computer systems. As projects were completed or data sets were made available to the public, the data was to be loaded into the database.

US Fish and Wildlife Service (FWS) Servcat Documents: Topic: Relational Database

This deposit contains an archive of documents from the US Fish and Wildlife Service (FWS) Servcat system. The documents were obtained by scraping the FWS Servcat system, which is a database of documents related to the management of fish and wildlife resources in the United States. The documents include reports, memos, and other materials related to the management of fish and wildlife resources.

The documents are organized here by general topic, and are contained in a zip file. If the original general topic contained more than 50 Gb of data, the documents are split into multiple zip files. The zip files are named according to the original general topic, and are numbered sequentially when more than one zip file is created. For example, if the original general topic was Geospatial_Dataset, and there were three zip files created, the zip files would be named Geospatial_Dataset_part1.zip, Geospatial_Dataset_part2.zip, and Geospatial_Dataset_part3.zip. If only one zip file is created, it will be named by that general topic, e.g. Geospatial_Dataset.zip.

description: The long-term goal of the SOFIA program is to provide a central archive of data and products for all Department of Interior products related to the south Florida Ecosystem restoration program. The primary objectives of this project were to 1) provide a central location for the archive of all products and data collected as part of the USGS PES program and related work for the restoration of the South Florida Ecosystem; and 2) provide a means for customers to obtain the archived information. The database was been developed using PostgreSQL, an open source relational database management system. PostgreSQL was selected because it is freely available, widely used, actively maintained and supported, and runs on all modern UNIX-like and Windows based computer systems. As projects were completed or data sets were made available to the public, the data was to be loaded into the database.; abstract: The long-term goal of the SOFIA program is to provide a central archive of data and products for all Department of Interior products related to the south Florida Ecosystem restoration program. The primary objectives of this project were to 1) provide a central location for the archive of all products and data collected as part of the USGS PES program and related work for the restoration of the South Florida Ecosystem; and 2) provide a means for customers to obtain the archived information. The database was been developed using PostgreSQL, an open source relational database management system. PostgreSQL was selected because it is freely available, widely used, actively maintained and supported, and runs on all modern UNIX-like and Windows based computer systems. As projects were completed or data sets were made available to the public, the data was to be loaded into the database.

Serious games are increasingly explored as collaborative tools to enhance social learning on sustainable management of land and natural resources. A systematic literature review was conducted to examine the current state of the art of the different methods and procedures used to assess social learning outcomes of collaborative serious games. 42 publications were identified and included in the review following study selection and quality assessment steps. Extracted data from the publications were categorized in relation to five research questions. The categorizations were subsequently used to identify approaches used to assess cognitive, normative and relational learning outcomes of collaborative serious games. As a result, these approaches distinguishes between the nature of learning in the assessment of collaborative serious games. Combined, these approaches provide an overview of how to assess social learning outcomes of collaborative serious games, including the methods and procedures that can be used, and may serve as a reference for scholars designing and evaluating collaborative serious games.

As a sub-sector of nonprofit organizations (NPOs), social service nonprofits (SSNs) are essential agents in delivering human services and contributing to social welfare. However, they are struggling with acquiring and maintaining sustainable financial resources as a result of continuous welfare retrenchment. To date, little research has examined SSN-funder relations, relational management strategies, and their impact on organizational financial sustainability in non-democratic regimes characterized by contentious state-NPO relations and stringent regulations. This thesis is guided by an overarching research question: “How do social service nonprofit organizations manage their relations with multiple funders to achieve financial sustainability in a non-democratic context?” This thesis comprises three interconnected studies. First, a scoping review (Chapter 2) of 32 selected articles unearths the theoretical and empirical landscape of research on SSN–funder relations. This review synthesizes existing evidence and generates a new typology of SSN–funder relations: contract-based, partnership-based, transactional, and transformational. It also identifies both externally- and internally- oriented relational management strategies. Finally, this review theorizes the impact of SSN-Funder relations across four dimensions: service continuity, environmental adaptability, social impact expansion, and sustainable financial performance. Second, informed by Resource Dependence Theory and Embeddedness Theory, a quantitative study (Chapter 3) uses a cross-sectional secondary dataset of 681 SSNs in China to examine the impact of SSN-funder relations on organizational financial sustainability. Results found that greater reliance on a dominant funder was significantly associated with lower revenue generation (β = -0.5, p < 0.05), reduced surplus retention (β =-0.7, p < 0.001), and decreased operational efficiency (β = -0.0, p < 0.001). Revenue diversification was negatively related to surplus retention (β = -0.6, p < 0.01). Moreover, Party (β = 0.5, p < 0.001) and corporate embeddedness (β = 0.2, p < 0.001) were positively associated with revenue generation, while government embeddedness was negatively associated with revenue generation (β = -0.4, p < 0.001).Third, informed by Relationship Management Theory, a qualitative study (Chapter 4) comprising 30 in-depth interviews with SSN practitioners explores how various relational management strategies with funders impact organizational financial sustainability in China. It identifies a “relational strategy portfolio” with four strategies: trust-building, alignment, commitment reinforcement, and power-balancing. This study further conceptualized an inverted U-shaped relationship between the relational strategy complexity and organizational financial sustainability: as organizations choose to move from single to dual and then bundled strategies, their financial outcomes tend to improve. However, overly complex relational strategies may strain organizational capacity, leading to diminishing returns or even operational inefficiencies.This thesis makes three important contributions: Theoretically, it extends Resource Dependence Theory, Embeddedness Theory, and Relationship Management Theory by demonstrating how each offers complementary insights into SSN-funder relations and nonprofit financial sustainability in a non-democratic context. Empirically, this thesis identifies the typologies of SSN–funder relations and demonstrates how different relational management strategies shape organizational financial outcomes. Practically, this study provides actionable guidance for nonprofit practitioners, emphasizing the importance of a relational mindset and management strategies used to foster nonprofit financial sustainability in the social service sector and beyond.

This is database for the SPSS software in .Sav extension and this database contains 187 responses obtained from the maquiladora industry in northern Mexico. The questionnaire is available in https://doi.org/10.6084/m9.figshare.14328269.v1

Description: Report on EU socio-ecological systems (Deliverable 4.2; WP4; EU H2020 MAGIC Project)

Subject and Keywords: nexus (i.e. food, water, energy, land use, climate and environment); quantitative story telling (QST); metabolic pattern; robustness of narratives; EU’ sustainability strategy

Abstract: The sustainability agenda builds on key components (i.e. food, water, energy, land use, climate and environment) that are inherently interconnected in a Nexus. MAGIC uses an innovative approach to test the robustness of narratives about the Nexus in Europe and focuses on the EU sustainable strategy. The aim of this deliverable is to operationalize and test a tool-kit to structure the quantitative analysis of the metabolic pattern of social-ecological systems in relation to their sustainability and the Nexus, at different levels of aggregation and spatial scales (EU, country or regional level). We use “quantitative story telling” as an alternative approach to use scientific information generated and better inform policy-makers. This deliverable build on the methodological approach and the basic features of the theoretical framework of accounting called Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM). The application of the tool-kit in this deliverable has the only goal of illustrating the potentiality of the approach. In a series of chapters we i) present the theoretical background and features of the tool-kit used to characterize the state-of-the-play (diagnostic analysis) with regard to the sustainability of SES; ii) provide an overview of the results obtained in the analysis of 8 EU countries (i.e. France, Germany, Italy, Netherlands, Romania, Spain, Sweden and United Kingdom); iii) demonstrate the capability of the toolkit to perform the analysis at different scales (in this case, at a lower aggregated level -NUTS2-); and iv) highlight the methodological breakthrough provided by relational analysis and its relevance for policy making with regard to the water-energy-food-environment Nexus

Publisher: MAGIC

Contributors: 18 co-authors from 4 organisations

Citation: Ripoll-Bosch and Giampietro (Editors). 2019. Report on EU socio-ecological systems. MAGIC (H2020–GA 689669) Project Deliverable 4.2, Revision

Date: March/18

Language: English

Rights Management: The access is open

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

A dataset for "The Effects of Contractual and Relational Governance on Public-Private Partnership Sustainability"

Replication Data for: Do Investors Really Care About Sustainability? Evidence from European Companies on the Relationship Between ESG Performance and Stock Liquidity

For policy and decision makers working in the environmental governance space. This guidance presents a briefing on the research undertaken by Tapsell (2022) which explored the dual issue of care (for each other and for the environment) that needs to be addressed in environmental governance and policy systems. The guidance explains the background and context of this research and also provides a toolbox for policy and decisions makers to use practically.

The dataset includes three decision-matrices with performance values collected for 26 countries including 25 European countries and USA in relation to sustainable healthcare systems for three years: 2020, 2021, and 2022. Each decision matrix is two-dimensional and contains data for 26 countries placed in rows in relation to 9 criteria assessment placed in columns. Data is available in XLSX and CSV files for each considered year. Detailed dataset description is provided in PDF file.

The complexity of agricultural long-term experiments (LTE) has made relational databases indispensable for organizing and analyzing vast amounts of LTE data. These databases provide a robust framework for managing highly valuable research data for the agricultural community while ensuring consistency, and enabling comprehensive, large-scale analyses. Moreover, relational databases are critical for aligning agricultural data management with the FAIR principles—Findable, Accessible, Interoperable, and Reusable. These principles promote the integration of datasets from diverse sources and ensure that data can be shared, reused, and analyzed across multiple studies. In this context, the BonaRes LTE Data Schema has been specifically designed and continuously refined to meet the evolving needs of agricultural research. This schema includes the description of a complex data model that can be used to set up a relational database to manage LTE data. Initially developed to standardize and harmonize LTE data, the schema has recently been expanded to encompass a wider range of data types. These include commonly collected information such as yield, plot characteristics, crop varieties, treatments, and more specialized datasets derived from fewer experiments. Although some specific datasets from LTE are collected less often, they follow consistent methodologies to maintain uniformity and reliability across studies. The development of a standardized data schema offers multiple advantages for agricultural research. By harmonizing the structure, metadata, keywords, parameter names, and format of experimental data, it facilitates meaningful comparisons across different studies and geographical locations. This is particularly important for drawing robust conclusions about agricultural and environmental systems. Furthermore, a well-structured schema ensures transparency and clear attribution of complex data, a critical factor for scientific reproducibility and the credibility of agricultural and environmental models. As agricultural research increasingly relies on data-driven approaches, the adoption and refinement of such schemas will play a pivotal role in advancing the understanding of complex agricultural systems, promoting sustainable farming practices, and addressing global challenges such as food security and climate change. The BonaRes LTE Data Schema exemplifies this effort, demonstrating how well-structured and FAIR-aligned relational databases can empower researchers to generate actionable insights from long-term agricultural experiments.

The Mobile Source Observation Database (MSOD) is a relational database being developed by the Assessment and Standards Division (ASD) of the US Environmental Protection Agency Office of Transportation and Air Quality (formerly the Office of Mobile Sources). The MSOD contains emission test data from in-use mobile air- pollution sources such as cars, trucks, and engines from trucks and nonroad vehicles. Data in the database was collected from 1982 to the present. The data is intended to be representative of in-use vehicle emissions in the United States.

Temporal changes in environmental conditions may play a major role in the year-to-year variation in fitness consequences of behaviours. Identifying environmental drivers of such variation is crucial to understand the evolutionary trajectories of behaviours in natural contexts. However, our understanding of how environmental variation influences behaviours in the wild remains limited. Using data collected over 14 breeding seasons from a collared flycatcher (Ficedula albicollis) population, we examined the effect of environmental variation on the relationship between survival and risk-taking behaviour, a highly variable behavioural trait with great evolutionary and ecological significance. Specifically, using annual recapture probability as a proxy of survival, we evaluated the specific effect of predation pressure, food availability and mean temperature on the relationship between annual recapture probability and risk-taking behaviour (measured as flight initiation distance, FID). We found a negative trend, as the relationship between annual recapture probability and FID decreased over the study years, and changed from positive to negative. Specifically, in the early years of the study, risk-avoiding individuals exhibited a higher annual recapture probability, whereas in the later years, risk-avoiders had a lower annual recapture probability. However, we did not find evidence that any of the considered environmental factors mediated the variation in the relationship between survival and risk-taking behaviour.

FooDrugs database is a development done by the Computational Biology Group at IMDEA Food Institute (Madrid, Spain), in the context of the Food Nutrition Security Cloud (FNS-Cloud) project. Food Nutrition Security Cloud (FNS-Cloud) has received funding from the European Union's Horizon 2020 Research and Innovation programme (H2020-EU.3.2.2.3. – A sustainable and competitive agri-food industry) under Grant Agreement No. 863059 – www.fns-cloud.eu (See more details about FNS-Cloud below)

FooDrugs stores information extracted from transcriptomics and text documents for foo-drug interactiosn and it is part of a demonstrator to be done in the FNS-Cloud project. The database was built using MySQL, an open source relational database management system. FooDrugs host information for a total of 161 transcriptomics GEO series with 585 conditions for food or bioactive compounds. Each condition is defined as a food/biocomponent per time point, per concentration, per cell line, primary culture or biopsy per study. FooDrugs includes information about a bipartite network with 510 nodes and their similarity scores (tau score; https://clue.io/connectopedia/connectivity_scores) related with possible drug interactions with drugs assayed in conectivity map (https://www.broadinstitute.org/connectivity-map-cmap). The information is stored in eight tables:

Table “study” : This table contains basic information about study identifiers from GEO, pubmed or platform, study type, title and abstract

Table “sample”: This table contains basic information about the different experiments in a study, like the identifier of the sample, treatment, origin type, time point or concentration.

Table “misc_study”: This table contains additional information about different attributes of the study.

Table “misc_sample”: This table contains additional information about different attributes of the sample.

Table “cmap”: This table contains information about 70895 nodes, compromising drugs, foods or bioactives, overexpressed and knockdown genes (see section 3.4). The information includes cell line, compound and perturbation type.

Table “cmap_foodrugs”: This table contains information about the tau score (see section 3.4) that relates food with drugs or genes and the node identifier in the FooDrugs network.

Table “topTable”: This table contains information about 150 over and underexpressed genes from each GEO study condition, used to calculate the tau score (see section 3.4). The information stored is the logarithmic fold change, average expression, t-statistic, p-value, adjusted p-value and if the gene is up or downregulated.

Table “nodes”: This table stores the information about the identification of the sample and the node in the bipartite network connecting the tables “sample”, “cmap_foodrugs” and “topTable”.

In addition, FooDrugs database stores a total of 6422 food/drug interactions from 2849 text documents, obtained from three different sources: 2312 documents from PubMed, 285 from DrugBank, and 252 from drugs.com. These documents describe potential interactions between 1464 food/bioactive compounds and 3009 drugs. The information is stored in two tables:

Table “texts”: This table contains all the documents with its identifiers where interactions have been identified with strategy described in section 4.

Table “TM_interactions”: This table contains information about interaction identifiers, the food and drug entities, and the start and the end positions of the context for the interaction in the document.

FNS-Cloud will overcome fragmentation problems by integrating existing FNS data, which is essential for high-end, pan-European FNS research, addressing FNS, diet, health, and consumer behaviours as well as on sustainable agriculture and the bio-economy. Current fragmented FNS resources not only result in knowledge gaps that inhibit public health and agricultural policy, and the food industry from developing effective solutions, making production sustainable and consumption healthier, but also do not enable exploitation of FNS knowledge for the benefit of European citizens. FNS-Cloud will, through three Demonstrators; Agri-Food, Nutrition & Lifestyle and NCDs & the Microbiome to facilitate: (1) Analyses of regional and country-specific differences in diet including nutrition, (epi)genetics, microbiota, consumer behaviours, culture and lifestyle and their effects on health (obesity, NCDs, ethnic and traditional foods), which are essential for public health and agri-food and health policies; (2) Improved understanding agricultural differences within Europe and what these means in terms of creating a sustainable, resilient food systems for healthy diets; and (3) Clear definitions of boundaries and how these affect the compositions of foods and consumer choices and, ultimately, personal and public health in the future. Long-term sustainability of the FNS-Cloud will be based on Services that have the capacity to link with new resources and enable cross-talk amongst them; access to FNS-Cloud data will be open access, underpinned by FAIR principles (findable, accessible, interoperable and re-useable). FNS-Cloud will work closely with the proposed Food, Nutrition and Health Research Infrastructure (FNHRI) as well as METROFOOD-RI and other existing ESFRI RIs (e.g. ELIXIR, ECRIN) in which several FNS-Cloud Beneficiaries are involved directly. (https://cordis.europa.eu/project/id/863059)

***** changes between version FooDrugs_v2 and FooDrugs_V3 (31st January 2023) are:

Increased the amount of text documents by 85.675 from PubMed and ClinicalTrials.gov, and the amount of Text Mining interactions by 168.826.

Increased the amount of transcriptomic studies by 32 GEO series.

Removed all rows in table cmap_foodrugs representing interactions with values of tau=0

Removed 43 GEO series that after manually checking didn't correspond to food compounds.

Added a new column to the table texts: citation to hold the citation of the text.

Added these columns to the table study: contributor to contain the authors of the study, publication_date to store the date of publication of the study in GEO and pubmed_id to reference the publication associated with the study if any.

Added a new column to topTable to hold the top 150 up-regulated and 150 down-regulated genes.

No data generated. This dataset is not publicly accessible because: There was no new data generated. It can be accessed through the following means: None available. Format: Since this was a review article, no new data was generated.

This dataset is associated with the following publication: Vesper , S. The relationship between environmental relative moldiness index values and asthma. INTERNATIONAL JOURNAL OF HYGIENE AND ENVIRONMENTAL HEALTH. Urban & Fischer Verlag Jena, Jena, GERMANY, 219(1): 233-238, (2016).

This dataset includes CSV data files containing environmental data that may be associated with the occurrence and toxicity of the diatom Pseudo nitzschia in Frenchman Bay, Maine, that can form harmful algal blooms and produce the toxin domoic acid. The dataset covers the period 2010 through 2022 or shorter period depending on the variable. Elevated concentrations of domoic acid in Pseudo nitzschia can lead to the contamination of shellfish, threats to human health and closures of shellfish harvesting areas. This dataset was compiled in cooperation with the National Park Service.XXXXXXXXXXXXXXXXXXXXXXXXXXX The file “Site_Infomation_v4.csv” contains the latitudes and longitudes for the locations where Pseudo nitzschia cells were enumerated, water quality and mussel tissue samples were collected, nutrient loads were estimated, and ocean temperature and salinity were measured.XXXXXXXXXXXXXXXXXXXXXXXXXXX The file “Pn_Cells_Ancillary_vars_v2.csv” contains Pseudo nitzschia monitoring dat ...

Governments have been concerned with balancing economic growth and environmental sustainability. Nevertheless, it has been noted that sustainable development is interconnected with economic variables, the institutional framework, and the efficacy of ecological regulatory measures. This study experimentally examines the correlation of economic policy uncertainty (EPU), financial development (FD), ecological innovation (EI), corruption (IQ), foreign direct investment (FDI), trade openness (TR), natural resource rent (NRR), and CO2 emission. We utilized longitudinal data from the Organization for Economic Cooperation and Development (OECD) countries from 2003 to 2021 to address the existing research void. This study used sequential processes of the linear panel data model (SELPDM) and the SYS-GMM approaches in obtaining consistent and efficient results. The inverse U-shaped relationship between FD and environmental degradation (ED) is confirmed by the long-term elasticity estimates generated by the SELPDM method Elasticity estimates for the long-run show that rigorous ecological regulations, higher renewable energy utilization, higher FD and less corruption, an interaction between FD and rigorous ecological regulations all contribute to reduced ED. Its also being observed that both EPU, FDI and trade openness are positively affecting the ED. It confirms the idea of pollution refuge between the OECD countries. The causality test results show that corruption and FD had reciprocal links with ED, while FDI, trade openness and strict environmental policies were also found to have bidirectional linkage with ED. To achieve sustainable development and prevent environmental degradation in the long term, we propose implementing an institutional financial framework and FD in OECD nations. This may be accomplished by focusing on the effectiveness of environmental regulatory laws and creating a conducive institutional environment.

This dataset is a compilation of geographic rasters from multiple environmental data sources. It aims at making the life of SDM users easier. All rasters cover the metropolitan French territory, but have varying resolutions and projections. Each directory inside the main directory "0_mydata" contain a single environmental raster. Punctual extraction of raster values can be easily done for large sets of WGS84-(longitude,latitude) points coordinates and for multiple rasters at the same time through the R function get_variables of script _functions.R from Github repository: https://github.com/ChrisBotella/SamplingEffort. All data sources are accessible on the web and free of use, at least for scientific purpose. They have various conditions of citations. Anyone diffusing a work using the present data must reference along with the present DOI, the original source data employed. Those source data are described in the paragraphs below. We provide the articles to cite, when required, and webpages for access.

Pedologic Descriptors of the ESDB v2: 1 km × 1 km Raster Library : The library contains multiple soil pedology (physico-chemical properties of the soil) descriptors raster layers covering Eurasia at a resolution of 1 km. We selected 11 descriptors from the library. They come from the PTRDB. The PTRDB variables have been directly derived from the initial soil classification of the Soil Geographical Data Base of Europe (SGDBE) using expert rules. For more details, see [1, 2] and [3]. The data is maintained and distributed freely for scientific use by the European Soil Data Centre (ESDAC) at http://eusoils.jrc.ec.europa.eu/content/european-soil-databasev2-raster. The 11 rasters are in the directories "awc_top", "bs_top", "cec_top", "dimp", "crusting", "erodi", "dgh", "text", "vs", "oc_top", "pd_top".

Corine Land Cover 2012, Version 18.5.1, 12/2016 : It is a raster layer describing soil occupation with 48 categories across Europe (25 countries) at a resolution of 100 m. This data base of the European Union is freely accessible online for all use at http://land.copernicus.eu/pan-european/corine-land-cover/clc-2012. The raster of this variable is in the directory "clc".

Hydrographic Descriptor of BD Carthage v3: BD Carthage is a spatial relational database holding many informations on the structure and nature of the french metropolitan hydrological network. For the purpose of plants ecological niche, we focus on the geometric segments representing watercourses, and polygons representing hydrographic fresh surfaces. The data has been produced by the Institut National de l’information Géographique et forestière (IGN) from an interpretation of the BD Ortho IGN. It is maintained by the SANDRE under free license for non-profit use and downloadable at:
http://services.sandre.eaufrance.fr/telechargement/geo/ETH/BDCarthage/FX
From this shapefile, we derived a raster containing the binary value raster proxi_eau_fast, i.e. proximity to fresh water, all over France.We used qgis to rasterize to a 12.5m resolution, with a buffer of 50m, the shapefile COURS_D_EAU.shp on
one hand, and the polygons of SURFACES_HYDROGRAPHIQUES.shp with attribute NATURE=“Eau douce
permanente” on the other hand.We then created the maximum raster of the previous ones (So the value of 1 correspond to an approximate distance of less than 50m to a watercourse or hydrographic surface of fresh water). The raster is in the directory named "proxi_eau_fast".

USGS Digital Elevation Data : The Shuttle Radar Topography Mission achieved in 2010 by Endeavour shuttle measured elevation at three arc second resolution over most of the earth surface. Raw measures have been post-processed by NASA and NGA in order to correct detection anomalies. The data is available from the U.S. Geological Survey, and downloadable on the Earthexplorer (https://earthexplorer.usgs.gov/). One may refer to https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-shuttle-radar-topography-mission-srtm-void?qt-science_center_objects=0#qt-science_center_objects for more informations. the elevation raster is in the directory named "alti".

Potential Evapotranspiration of CGIAR-CSI ETP : The CGIAR-CSI distributes this worldwide monthly potential-evapotranspiration raster data. It is pulled from a model developed by Antonio Trabucco [4, 5]. Those are estimated by the Hargreaves formula, using mean monthly surface temperatures and standard deviation from WorldClim 1:4 (http://www.worldclim. org/), and radiation on top of atmosphere. The raster is at a 1km resolution, and is
freely downloadable for a nonprofit use at: http://www.cgiar-csi.org/data/global-aridity-and-pet-database#description. This raster is in the directory "etp".

Bioclimatic Descriptors of Chelsea Climate Data 1.1: Those are raster data with worldwide coverage and 1 km resolution. A mechanistical climatic model is used to make spatial predictions of monthly mean-max-min temperatures, mean precipitations and 19 bioclimatic variables, which are downscaled with statistical models integrating historical measures of meteorologic stations from 1979 to today. The exact method is explained in the reference papers [6] and [7]. The data is under Creative Commons Attribution 4.0 International License and downloadable at (http://chelsa-climate.org/downloads/). The 19 bioclimatic rasters are located in the directories named "chbio_X".

ROUTE500 1.1: This database register classified road linkages between cities (highways, national roads, and departmental roads) in France in shapefile format, representing approxi-mately 500,000 km of roads. It is produced under free license (all uses) by the IGN. Data are available online at http://osm13.openstreetmap.fr/~cquest/route500/. For deriving the variable “droute_fast”, the distance to the main roads networks, we computed with qGis the distance raster to the union of all elements of the shapefile ROUTES.shp (segments).

References :

[1] Panagos, P. (2006). The European soil database. GEO: connexion, 5(7), 32–33.

[2] Panagos, P., Van Liedekerke, M., Jones, A., Montanarella, L. (2012). European Soil Data
Centre: Response to European policy support and public data requirements. Land Use Policy,
29(2),329–338.

[3] Van Liedekerke, M. Jones, A. & Panagos, P. (2006). ESDBv2 Raster Library-a set of rasters
derived from the European Soil Database distribution v2. 0. European Commission and the
European Soil Bureau Network, CDROM, EUR, 19945.

[4] Zomer, R., Bossio, D., Trabucco, A., Yuanjie, L., Gupta, D. & Singh, V. (2007). Trees and
water: smallholder agroforestry on irrigated lands in Northern India.

[5] Zomer, R., Trabucco, A., Bossio, D. & Verchot, L. (2008). Climate change mitigation: A
spatial analysis of global land suitability for clean development mechanism afforestation and
reforestation. Agriculture, ecosystems & environment, 126(1), 67–80.

[6] Karger, D. N., Conrad, O., Bohner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W. & Kessler,
M. (2016). Climatologies at high resolution for the earth’s land surface areas. arXiv preprint
arXiv:1607.00217.

[7] Karger, D. N., Conrad, O., Bohner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W. & Kessler, M.
(2016). CHELSEA climatologies at high resolution for the earth’s land surface areas (Version
1.1).