Find research datasets worth reusing

opencc-by-4.0Dec 2021View details →

"Agricultural trade and its impacts on cropland use and the global loss of species habitat." - Supplementary data

This dataset and code is part of the following publication: Schwarzmueller, F. & Kastner, T (2022), Agricultural trade and its impact on cropland use and the global loss of species' habitats. Sustainability Science, doi: 10.1007/s11625-022-01138-7   There are three zip-folders accompanying this publication: Code.zip contains all the R-Scripts and input files neccessary for the calculation that were written by the authors. Data.zip contains the FAO-input data (as dowloaded in 2021). This exact data is not available anymore from the FAOSTAT website, which is why we included it in this repository. TradeMatrixFeed_import_dry_matter_1986-2013.zip contains the results from the calculation as shown in the paper.

opencc-by-4.0Nov 2021View details →

The SPIN covid19 RMRIO dataset: Global trade network data for the years 2016-2026 reflecting macroeconomic effects of the covid19 pandemic - B. Data for 2020 - 2026 - Covid scenario

opencc-by-4.0Nov 2021View details →

The SPIN covid19 RMRIO dataset: Global trade network data for the years 2016-2026 reflecting macroeconomic effects of the covid19 pandemic - A. Code and data for 2016-2019

The SPIN covid19 RMRIO dataset is a time series of MRIO tables covering years from 2016-2026 on a yearly basis. The dataset covers 163 sectors in 155 countries. This repository includes data for years from 2016 to 2019 (hist scenario) and the corresponding labels. Data for years 2020 to 2026 are stored in the corresponding repositories: <ul> <li>covid: <a href="https://doi.org/10.5281/zenodo.5713825">10.5281/zenodo.5713825</a></li> <li>counterfactual: <a href="https://doi.org/10.5281/zenodo.5713839">10.5281/zenodo.5713839</a></li> </ul> Tables are generated using the <a href="https://github.com/TBeaufils/SPIN">SPIN method</a>, based on the <a href="https://doi.org/10.5281/ZENODO.3993659">RMRIO tables</a> for the year 2015, GDP, imports and exports data from the <a href="https://data.imf.org/?sk=4c514d48-b6ba-49ed-8ab9-52b0c1a0179b">International Financial Statistics</a> (IFS) and the World Economic Outlooks (WEO) of <a href="https://www.imf.org/en/Publications/WEO/weo-database/2019/October">October 2019</a> and <a href="https://www.imf.org/en/Publications/WEO/weo-database/2021/April">April 2021</a>. From 2020 to 2026, the dataset includes two diverging scenarios. The covid scenario is in line with April 2021 WEO's data and includes the macroeconomic effects of Covid 19. The counterfactual scenario is in line with October 2019 WEO's data and simulates the global economy without Covid 19. Tables from 2016 to 2019 are labelled as hist. The Projections folder includes the generated tables for years from 2016 to 2019 (hist scenario) and the corresponding labels. The Sources folder contains the data records from the IFS and WEO databases. The Method data contains the data files used to generate the tables with the SPIN method and the following Python scripts: <ul> <li>SPIN_covid19_MRIO_files_preparation.py generates the data files from the source data.</li> <li>SPIN_covid19_RMRIO runs.py is the command to run the SPIN method and generate the dataset.</li> <li>figures.py is a script to produce figures reflecting the consistency of the projected tables and the evolution of macroeconomic figures in the 2016-2026 period for a selection of countries.</li> </ul> All tables are labelled in 2015 US$ and valued in basic prices.

opencc-by-4.0Nov 2021View details →

The SPIN covid19 RMRIO dataset: Global trade network data for the years 2016-2026 reflecting macroeconomic effects of the covid19 pandemic - C. Data for 2020 - 2026 - Counterfactual scenario

opencc-by-4.0Sep 2021View details →

Data supplement for "Global agricultural trade and land system sustainability: implications for ecosystem carbon storage, biodiversity and human nutrition"

This data supplements the publication "Global agricultural trade and land system sustainability: implications for ecosystem carbon storage, biodiversity and human nutrition" by Thomas Kastner, Abhishek Chaudhary, Simone Gingrich, Alexandra Marques, U. Martin Persson, Giorgio Bidoglio, Gaëtane Le Provost, Florian Schwarzmüller, available here: <a href="https://doi.org/10.1016/j.oneear.2021.09.006">https://doi.org/10.1016/j.oneear.2021.09.006</a> For details, please refer to that publication.

opencc-by-4.0Mar 2023View details →

Trade policy announcements can increase price volatility in global food commodity markets (Replication Data)

Replication data for "Trade policy announcements can increase price volatility in global food commodity markets": <ul> <li>Original dataset on trade policy announcements from 2005 to 2017 for wheat and maize (corn) (details in codebook)</li> <li>Daily price ranges based on the highest and lowest price recorded for wheat and corn futures (traded at the Chicago Board of Trade, CBOT)</li> <li>Stocks-to-use data for the United States, which is compiled by the United States Department for Agriculture (USDA) and available at monthly frequency from their World Supply and Demand Estimates report</li> </ul>

zenodo40/100

Kuempel et al. (2024) Quantifying global redundant fisheries trade to streamline seafood supply chains

Species trade data to accompany the publication "Quantifying global redundant fisheries trade to streamline seafood supply chains" by Kuempel et al. (2024) and the associated github repository https://github.com/cdkuempel/Redundant_fisheries_trade

opencc-by-4.0Jun 2024View details →

zenodo40/100

Trade network dynamics and alien plant pest introductions: A global analysis

This is a supplement to "Trade network dynamics and alien plant pest introductions: A global analysis", Diversity and Distributions (<a href="https://doi.org/10.1111/ddi.13963">https://doi.org/10.1111/ddi.13963</a>). These data were partially derived from the following resources available in the public domain: <a href="http://www.cepii.fr/CEPII/fr/welcome.asp">www.cepii.fr/CEPII/fr/welcome.asp</a>; Seebens et al. (2017) (dataset DOI: <a href="https://doi.org/10.12761/sgn.2016.01.022">https://doi.org/10.12761/sgn.2016.01.022</a>); Fenn-Moltu et al. 2022 (dataset DOI: <a href="https://doi.org/10.5061/dryad.8931zcrrq">https://doi.org/10.5061/dryad.8931zcrrq</a>).

opencc-by-4.0Oct 2024View details →

dryad40/100

Global flows of insect transport and establishment: the role of biogeography, trade, and regulations

Aim: Non-native species are part of almost every biological community worldwide, yet numbers of species establishments have an uneven global distribution. Asymmetrical exchanges of species between regions are likely influenced by a range of mechanisms, including propagule pressure, native species pools, environmental conditions, and biosecurity. While the importance of different mechanisms is likely to vary among invasion stages, those occurring prior to establishment are difficult to account for. We used records of unintentional insect introductions to test 1) whether insects from some biogeographic regions are more likely to be successful invaders, 2) whether the intensity of trade flows between regions determines how many species are intercepted and how many successfully establish, and 3) whether the variables driving invasion success differ pre- and post-introduction. Location: Canada, mainland USA, Hawaii, Japan, Australia, New Zealand, Great Britain, South Korea, South Africa. Methods: To disentangle processes occurring during the transport and establishment stages, we analysed border interceptions of 8,199 insect species as a proxy for transported species flows, and lists of 2,076 established non-native insect species in eight areas. Results: During transport, the largest species flows generally originated from the Nearctic, Panamanian and Neotropical regions. Insects native to eight of twelve biogeographic regions were able to establish, with the largest flows of established species on average coming from the Western Palearctic, Neotropical, and Australasian/Oceanian regions. Both the biogeographic region of origin and trade intensity significantly influenced the size of species flows between regions during transport and establishment. The transported species richness increased with Gross National Income in the source country and decreased with geographic distance. More species were able to establish when introduced within their native biogeographic region. Main conclusions: Our results suggest that accounting for processes occurring prior to establishment is crucial for understanding invasion asymmetry in insects, and quantifying regional biosecurity risks.

opencc-zeroSep 2023View details →

dryad40/100

Global flows of insect transport and establishment: the role of biogeography, trade, and regulations

Open the record for dataset details and reuse information.

publicOct 2023View details →

opencc-zeroApr 2024View details →

Does fortune follow function? Exploring how consumer preferences drive the functional trait composition of the global songbird trade

Defaunation and extinction undermine the resilience and functioning of ecological communities and ecosystems. Relative to other disturbances, overexploitation for the global wildlife trade presents a unique case of trait-based selection, as demand for specific individuals is often tied to unique morphological or aesthetic traits desired by consumers ("market traits"). Because evolutionary history leads to species that share both market and functional traits, we posit that non-random patterns of exploitation will result in non-random loss of functional diversity. We applied a trait-based framework to the global songbird trade for 4616 species, 148 of which are plausibly threatened by the trade. We quantified select market traits, such as unique coloration and song quality, and ecological traits related to body size, diet, and foraging strategy to assess whether the trade disproportionately threatens particular functional groups. We additionally looked for patterns of association between market traits and functional traits to assess whether selection on certain market traits could drive selection on associated functional traits. We found that overexploited birds are a distinct functional subset of the global songbird pool, with the trade disproportionately threatening large bodied, frugivorous, and seed eating birds. Across all songbirds, there were multiple non-random associations between market traits and functional traits, with the strongest associations observed among trade-threatened birds; this was consistent with our theory that consumer-driven selection on market traits could theoretically result in selection on functional traits. However, there was mixed evidence for this hypothesis at a global scale, suggesting that disproportionate threat to functional diversity may be more likely in regions where there is heavy demand for associated market traits. Policy Implications: Our results highlight the need for increased focus on the mechanistic drivers of trait-based selection on the consumer side of wildlife trade, and how patterns of overexploitation can systematically affect ecological communities and ecosystem services.

opencc-zeroSep 2022View details →

Global potential invasion maps of traded birds under climate and land-cover change

Biological invasions rank among the top five threatening factors affecting biodiversity, but ongoing changes in climate and land cover might exacerbate risks. We used species distribution models for 609 traded bird species on the CITES list to examine the combined effects of projected climate change and land-cover change worldwide on the potential range expansion of bird species with commercial value as pets. The maps of potential invasion (may be inferred as the invasion risk) have been provided in the main manuscript and here, the potential invasion dataset for the current and future times is provided including the species distribution maps, all as GeoTiff files. The maps for the future time are provided for different future years and over a range of climate scenarios (SSP245, SSP370, and SSP585).

opencc-by-4.0Jul 2024View details →

Historical Pollen Records from `The Productivity-Stability Trade-off in Global Food Systems'

Historical pollen records from Europe used to detect evidence of agricultural development on plant pollen dynamics.

opencc-by-4.0Aug 2024View details →

Dataset for: Navigating Ecosystem Services Trade-offs: A Global Comprehensive Review

Methods The dataset is the output of a comprehensive literature-based search that aims to collate all the evidence on where ES relationships have been mentioned and addressed. We applied systematic mapping which is based on the “Guidelines for Systematic Review in Environmental Management” developed by the Centre for Evidence-Based Conservation at Bangor University (Pullin and Stewart 2006). The methodological framework followed the standard stages outlined for systematic mapping in environmental sciences (James et al. 2016). Briefly, we defined the scope and objectives: ·       We comprehensively review and further explore the global evidence of ES trade-offs and synergies focusing on all systems including terrestrial, freshwater, and marine. ·       We compiled the evidence on trade-offs and synergies among multiple ES interacting across various ecosystems. ·       We performed a geographical and temporal trend analysis exploring the distribution of studies across the world examining how the focus on various ecosystem types and ES categories has evolved to highlight gaps and biases. Then we set the criteria for study inclusion (Table 1), searched the evidence, coded, and produced the database. Extracted article information including the specific criteria is detailed in Table 1. The first step was to search the ISI Web of Knowledge core collection (http://apps.webofknowledge.com) database, targeting the search on the ecosystem services literature and studies dealing with trade-offs/synergies, win-win outcomes or bundles when managing different ecosystem services in the landscape/seascape. All peer-reviewed journal articles written in English and Spanish have been considered for review. The peer-reviewed literature from 2005 to 2021 was reviewed identifying relevant studies according to specific search terms. The relevant search terms and descriptive words derived from (Howe et al. 2014) adding “bundles” and “co-benefits”. Boolean nomenclatures ‘*’ = all letters were allowed after the *, were used on the root of words where several different endings applied (Figure 1). Search terms used were: (“*ecosystem service*” OR “environment* service*” OR “ecosystem* approach*” OR “ecosystem good*” OR “environment* good*”) AND (“*trade-off*” OR “tradeoff*” OR “synerg*” OR “win-win*” OR “bundle*” OR “cost*and benefit*” OR “co-benefit*”) n=5194 Papers were preliminarily coded with a semantic analysis using the R package Bibliometrix (<a href="http://www.bibliometrix.org">http://www.bibliometrix.org</a>). In the second step (Figure 1) papers were preliminarily coded with a semantic analysis using the R package Bibliometrix (http://www.bibliometrix.org). Papers were classified according to three systems: terrestrial, marine, and freshwater (Table 1). Papers with multiple systems, transitional habitats or those that could not be classified were classified as “other” (Mazor et al. 2018). Articles were classified based on the occurrence of the most frequent system words in their title, keywords, and abstract (Mazor et al. 2018). The set of system-specific words was determined by extracting the 250 most frequently used keywords from all considered articles and assigning each word to either system (articles could fall into just one of the four categories). Using this technique, we managed to classify 100% of the papers. To further enrich the dataset and make it a useful repository for science and policy, an additional sub-classification was performed, categorizing papers into the following categories: Coastal, Urban, Wetlands, Forest, Mountain, Freshwater, Agroecosystems, and Others that mainly represented multiple ecosystems (Table S1). This comprehensive classification approach enhances the dataset’s utility for various scientific and policy-making applications. In the third step (Figure 1), applying the same technique, we classified the papers into four ES categories: habitat (supporting biodiversity related), provisioning, regulating, and cultural services (De Groot et al. 2010; MEA 2005; Sukhdev 2010; Wallace 2007). For the classification into ES categories, articles could fall into one or more of the four categories (see Table 1 for example the keywords used to classify ecosystems, ES categories, and countries). Applying this technique, we excluded 2149 papers that weren’t classified in any of the ecosystem services types categories resulting in 3629 papers (see Figure 1). In the fourth step (Figure 1), an initial screening was conducted to identify papers that did not align with the review objectives of assessing ecosystem services trade-offs and synergies to inform policy and management decisions. We manually reviewed the titles of each paper in the dataset, excluding those that were from other fields or did not align with the review objectives. In this initial assessment, we excluded 347 papers, leaving a total of 3,286 papers for further review. A descriptive analysis of this 3286 article dataset was performed to examine the distribution of ES categories within each ecosystem type over the specified period. This analysis allowed us to conclude the prevalence of each ecosystem service category in different ecosystem types, identifying temporal trends and patterns. The number of occurrences was calculated for each ES category within each ecosystem type, expressed as counts. This allowed for the comparison of ecosystem service distributions across the selected ecosystem types. In the fifth step (Figure 1), we employed an approach to visually represent the geographical distribution and focus of ES studies across the world. With the classification of studies in ES categories and the types of ecosystems, the papers were coded according to the country where the study was performed. It was possible to assign a specific country to 2636 studies, removing 650 studies that did not specify the country of study. From these 2636 papers classified, a proportion were global studies that consider several countries under study (499 global studies). We developed global maps (Figure 1), each offering a unique perspective on the ES research landscape. The first map presents the total number of ES trade-off studies conducted worldwide, illustrating the geographical spread and concentration of research efforts to provide a clear overview of regions that have been extensively studied and those that may require more attention in future research. Additionally, we calculated two key metrics to assess research productivity more comprehensively: the number of research papers per capita and the number of research papers relative to Gross Domestic Product (GDP). For population and GDP, we used the most recent available data from the World Bank (https://data.worldbank.org). These alternative metrics normalize the data based on economic output and population size, providing a more balanced view of research activity across different countries (Figures S3). Detailed maps were created featuring pie charts that highlight the different categories of ES and ecosystem types addressed for each country. These charts offer an understanding of how various ES categories and ecosystems are represented in different parts of the world. Finally, we assessed ES trade-off studies to world regions (Africa, Antarctica, Asia, Australasia, Europe, Latin America, and North America) looking at the relationships between the categories of ES. We considered papers that evaluated more than one category of ES and the papers that considered only one category of ES. This country-level analysis offers insights into regional research trends and priorities, contributing to a more localized understanding of ES studies. In the sixth step (Figure 1), each publication in this review was critically appraised to evaluate the quality of the papers included in the review. The foundation for our critical appraisal stems from the comprehensive and multidimensional approach of Belcher et al. (2016) that is framed to evaluate research quality, which aligns well with the interdisciplinary nature of our study. Belcher et al. (2016) developed a robust framework that incorporates essential principles and criteria for assessing the quality of transdisciplinary research. This is particularly relevant for ecosystem services science and our review that contributes to advancing current knowledge by systematically synthesizing evidence on relationships among various ES across these diverse systems. The Belcher et al. (2016) framework emphasizes four main principles: relevance, credibility (which we have adapted as methodological transparency), legitimacy (generalizability in our context), and effectiveness (significance). A continuous scoring system (ranging from 0 to 1) was applied for the four main criteria to maintain simplicity and consistency across the large number of studies. In this system, a value closer to 0 indicates that the criteria are not met, while a value closer to 1 indicates that the criteria are more closely met. This scoring method was a useful indicator of the overall quality of the paper and how well the article met the review's goals overall. Methodological Transparency was assessed based on the clarity and completeness of methodological descriptions, including data availability, the rigor of statistical analyses, methodological detail, and reproducibility of the findings. This criterion assesses the transparency and rigor of the study's methodology, including data collection, analysis, and reporting (Belcher et al. 2016). Relevance was evaluated by the study's alignment with the review's objectives, its importance to the field, and its practical applicability. This includes the extent to which the study addresses pertinent research questions of the study (Belcher et al. 2016). Significance was determined by the novelty of the study, its theoretical contributions, and practical implications. This includes evaluating whether the study presents new ideas, concepts, or frameworks that advance the field of ES relationships (Belcher et al. 2016). Generalizability was judged based on the contextual applicability and transferability of the study's findings to other settings. This includes assessing whether the study's results can be applied broadly and whether the context is sufficiently described to understand its applicability (Belcher et al. 2016). In the final seventh step (Figure 1) a detailed assessment was performed incorporating sub-categories within each main critical appraisal criteria to allow for a more comprehensive analysis (Table S2). To this end, a random sample of 20% of the studies was selected (574 papers) and a thorough revision by subcategories for each main criteria was performed (see Table S2). For the random selection of 20% of the studies from the dataset, we loaded the dataset into R and set a random seed to ensure reproducibility. We then calculated the sample size as 20% of the total dataset and used the sample function to select this subset of studies randomly. This method ensured an unbiased and representative sample. The selected subset was assessed for a further detailed critical appraisal adding sub-categories to each criterion (Table S2). A qualitative assessment sub-category was also inclded to explain the rationale behind each assigned score in the dataset. We finally created a heatmap to visualize average scores by continent across the four criteria. Utilizing R programming (R Core Team 2023) for data aggregation with the dplyr package, the study computed mean scores for each criterion by continent. The aggregated data was visualized using a heatmap created with the ggplot2 package, where the color intensity of each cell represented the mean scores, facilitating a visual comparison across continents. This analysis offers a quantitative foundation for identifying areas of strength, evaluating performance by continent and potential for improvement, and further elucidating the different quality and focus of research within the ES trade-offs research. References: Belcher, B. M., Rasmussen, K. E., Kemshaw, M. R., & Zornes, D. A. (2016). Defining and assessing research quality in a transdisciplinary context. Research Evaluation, 25(1), 1-17. De Groot, R. S., Alkemade, R., Braat, L., Hein, L., & Willemen, L. (2010). Challenges in integrating the concept of ecosystem services and values in landscape planning, management, and decision-making. Ecological Complexity, 7, 260-272. Howe, C., Suich, H., Vira, B., Mace, G.M., 2014. Creating win-wins from trade-offs? Ecosystem services for human well-being: A meta-analysis of ecosystem service trade-offs and synergies in the real world. Global Environmental Change 28, 263-275. Mazor, T.A.-O., Doropoulos, C.A.-O., Schwarzmueller, F.A.-O., Gladish, D.A.-O.X., Kumaran, N.A.-O., Merkel, K.A.-O.X., Di Marco, M., Gagic, V.A.-O. (2018). Global mismatch of policy and research on drivers of biodiversity loss. Nature Ecology & Evolution 2, 1071-1074. Millennium Ecosystem Assessment (MEA).(2005). Ecosystems and Human Well-Being: Synthesis. Island Press, Washington DC. Pullin, A. S., & Stewart, G. B. (2006). Guidelines for systematic review in conservation and environmental management. Conservation biology, 20(6), 1647-1656. Sukhdev, P. (2010). The economics of ecosystems & biodiversity: mainstreaming the economics of nature: a synthesis of the approach, conclusions, and recommendations of TEEB. UNEP. R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/ Wallace K.J. (2007). Classification of ecosystem services: Problems and solutions. Biological Conservation 139, 235-246. Dataset Name of the file: MMartinez-Harms-Dataset-ESTrade-offs_Zenodofinal.xlsx Description: Complete database of the 3286  studies reviewed in this synthesis coded by: <table> <tbody> <tr> <td>N</td> <td>Number of papers</td> </tr> <tr> <td>AU</td> <td>Authors</td> </tr> <tr> <td>TI</td> <td>Title</td> </tr> <tr> <td>SO</td> <td>Publication name</td> </tr> <tr> <td>Included</td> <td>identify papers that did alignd (yes) or did not (No) align with the review objectives.</td> </tr> <tr> <td>JI</td> <td>Scientific Journal</td> </tr> <tr> <td>AB</td> <td>Abstract</td> </tr> <tr> <td>DE</td> <td>Authors’ Keywords</td> </tr> <tr> <td>ID</td> <td>Keywords associated by  ISI database</td> </tr> <tr> <td>LA</td> <td>Language</td> </tr> <tr> <td>DT</td> <td>Document Type (article, review, editorial, book chapter, letter, meeting abstract)</td> </tr> <tr> <td>TC</td> <td>Times Cited</td> </tr> <tr> <td>PY</td> <td>Publication Year</td> </tr> <tr> <td>SC</td> <td> Subject Categories</td> </tr> <tr> <td>WC</td> <td>Web of Science categories</td> </tr> <tr> <td>System</td> <td>Freshwater, terrestrial, marine, and other</td> </tr> <tr> <td>Habitat</td> <td>Habitat ES category</td> </tr> <tr> <td>Regulating</td> <td>Regulating ES category</td> </tr> <tr> <td>Cultural</td> <td>Cultural ES category</td> </tr> <tr> <td>Provisionning</td> <td>Provisionning ES category</td> </tr> <tr> <td>Country_Classification</td> <td>Country of study</td> </tr> <tr> <td>Continent</td> <td>Continent of study</td> </tr> <tr> <td>Synergies_Trade-offs</td> <td>The term trade-off involves losing one quality or aspect of something in return for gaining another quality or aspect. Synergy is a situation where the use of one ES directly increases the benefits supplied by another ES or a win-win situation</td> </tr> <tr> <td>Stakeholder_Participation</td> <td>The study interacts with stakeholders at any moment of the study or policy  decisions. </td> </tr> <tr> <td>Critical_Appraisal</td> <td>Articles are appraised to ensure that they are adequate for answering the research question</td> </tr> <tr> <td>Relevance</td> <td>Relevance to the review question (0 no relevance, 1 relevance)</td> </tr> <tr> <td>Methodological_Transparency</td> <td>Assessed based on the clarity and completeness of methodological descriptions</td> </tr> <tr> <td>Significance</td> <td>Significance of the contribution (are new ideas offered?)</td> </tr> <tr> <td>Generalizability</td> <td> Is the context specified, and do the ideas apply in other contexts?</td> </tr> <tr> <td>Total_Score</td> <td>The sum total score across all critical appraisal criteria </td> </tr> <tr> <td>Category</td> <td>Coastal, Urban, Wetlands, Forest, Mountain, Freshwater, Agroecosystems, and Others mainly represented multiple ecosystems</td> </tr> <tr> <td>Uses_INVEST</td> <td>This paper uses the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) tool from the Natural Capital Project to assess ecosystem services (Yes) or Not (No)</td> </tr> </tbody> </table>

opencc-by-4.0Apr 2023View details →

Global trade data of highly hazardous chemicals after data treatment and Python codes used for error analysis and mirror analysis

This database includes all global trade data of the three types of highly hazaroudous chemicals listed under the Rotterdam Convention after error analysis and mirror analysis. Python codes used for error analysis and mirror analysis are also available.    Corresponding authors: <a href="mailto:hongyan.zou@tjnu.edu.cn">hongyan.zou@tjnu.edu.cn</a>; <a href="mailto:Zhanyun.wang@empa.ch">Zhanyun.wang@empa.ch</a>

opencc-by-4.0Sep 2023View details →

The Future Evolution of Global Natural Gas Trade Output Data

This data repository contains the GCAM output databases for the paper: Yarlagadda, B., G. Iyer, M. Binsted, P. Patel, M. Wise, and J. McLeod. (2023). The Future Evolution of Global Natural Gas Trade.

publicApr 2024View details →

Does fortune follow function? Exploring how consumer preferences drive the functional trait composition of the global songbird trade

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publicMar 2024View details →

Hotter drought and trade-off between fast and slow growth strategies as major drivers of tree-ring growth variability of global conifers

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publicMay 2021View details →

Global change shifts trade-offs among ecosystem functions in woodlands restored for multifunctionality

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