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1,316 results for “Trade”
Data from: Behavioral trade-offs and multitasking by elk in relation to predation risk from Mexican gray wolves
<p>Non-consumptive effects of predation can alter foraging time, stress levels, and habitat use by prey, potentially resulting in reduced fitness. However, prey can mitigate the non-consumptive effects of predation by increasing vigilance, chewing and vigilance synchronization (i.e., multitasking), and spatiotemporal avoidance of predators. We quantified the effects of the Mexican wolf (<em>Canis lupus baileyi</em>) predation risk on elk (<em>Cervus canadensis</em>) behavior in the southwestern United States. We conducted behavioral observations on adult female elk and developed predation risk indices using Mexican wolf GPS collar data, locations of elk killed by Mexican wolves, and landscape covariates. We compared a priori models to determine the best predictors of adult female behavior and multitasking, separately. Metrics that quantified both spatial and temporal predation risk were top predictors in both datasets. Adult female vigilance was positively associated with increased predation risk. Increased predation risk had little effect on the probability of foraging, but resulted in decreased time spent resting. In a post hoc analysis, the effect of predation risk on foraging and resting differed across diurnal periods. During midday when wolf activity was relatively low, the probability of foraging increased while resting decreased, in areas with high spatial predation risk. During crepuscular periods when elk and wolves were most active, increased predation risk was associated with increased vigilance and slight decreases in foraging. Our results suggest elk are temporally avoiding predation risk from Mexican wolves by trading resting for foraging, a trade-off often not evaluated in behavioral studies. The probability of multitasking increased with predation risk, suggesting that adult female elk may be offsetting the non-consumptive effects of risk on feeding time. These results highlight potentially important but often excluded behaviors and trade-offs prey species may use to reduce the indirect effects of predation and contribute additional context to our understanding of predator-prey dynamics.</p>
Geocoded variant of United Nations Code for Trade and Transport Locations
<div></div> <div> <div> <div> <div>The <a href="https://unece.org/trade/uncefact/unlocode">United Nations Code for Trade and Transport Locations</a> dataset provides information on the codes known as "UN/LOCODE". </div> <div>This version of the dataset, based on the csv files of version 232, has extra information based on pycountry (names of administrative regions, country names, flags) and on most important on location.</div> <div> </div> <div> </div> <div>The dataset has the following extra fields:<br> <table> <tbody> <tr> <td>Column name</td> <td>Example</td> <td>Description</td> <td>Source</td> </tr> <tr> <td> <pre>alpha_2_country</pre> </td> <td> <pre>AD</pre> </td> <td>2 letter based country code, ISO 3166-1</td> <td>pycountry</td> </tr> <tr> <td> <pre>alpha_3_country</pre> </td> <td> <pre>AND</pre> </td> <td>3 letter based country code, ISO 3166-1</td> <td>pycountry</td> </tr> <tr> <td> <pre>flag_country</pre> </td> <td> <pre>🇦🇩</pre> </td> <td>unicode flag</td> <td>pycountry</td> </tr> <tr> <td> <pre>name_country</pre> </td> <td> <pre>Andorra</pre> </td> <td>Country name, ISO 3166-1</td> <td>pycountry</td> </tr> <tr> <td> <pre>numeric_country</pre> </td> <td> <pre>020</pre> </td> <td>Country code</td> <td>pycountry</td> </tr> <tr> <td> <pre>official_name_country</pre> </td> <td> <pre>Principality of Andorra</pre> </td> <td>Country official name</td> <td>pycountry</td> </tr> <tr> <td> <pre>score</pre> </td> <td>95</td> <td>Confidence code of geocoding [0-100/nan]</td> <td>ArcGIS</td> </tr> <tr> <td> <pre>geocoded</pre> </td> <td>True</td> <td>Was the coordinate derived from geocoding [true/false]</td> <td>ArcGIS</td> </tr> <tr> <td> <pre>geometry</pre> </td> <td> <pre>POINT (1.516666666666667 42.5)</pre> </td> <td>Point coordinate</td> <td>ArcGIS if geocoded else original UNLO </td> </tr> </tbody> </table> <br>The figure below shows the locations (n=23663) that have been geocoded in this dataset in green and the existing locations in pink. </div> <div><br></div> <div> </div> <div>Ownership of the original data recides at UNLO and the participants. </div> </div> </div> </div>
Data from: Extreme range in adult body size reveals hidden trade-offs among sexually selected traits
<p>Sexually selected weapons used to monopolize mating opportunities are predicted to trade-off with traits used in competition for fertilization. Yet, the limited size-range typically found among adults of a species often precludes clear comparisons between population-level and individual-level relative trait investment. The jousting weevil, <em>Brentus anchorago </em>(Coleoptera: Brentidae), varies more than 26-fold in body mass, which is among the most extreme adult body size ranges of any solitary terrestrial species. We reveal a trade-off at a population-level: hypermetric scaling in male weapons (slope =1.59) and a closely-mirrored reversal in allocation to post-copulatory traits (slope =0.54). Yet, at the individual-level we find the opposite pattern; males that invest relatively more in weapons for their size class also invest more in post-copulatory traits. In support of our findings from jousting weevils<em>, </em>across 36 dung beetle species we find the relative effect of population-level scaling increases in species with a larger range in adult body size. Our findings reveal that population-level allometries and individual level trade-offs can both be important in shaping relative trait allocation; we highlight that the adult body size range is rarely examined, but may be integral to gain a deeper understanding of trade-offs in reproductive allocation.</p>
Fungi and deadwood diversity: A test of the area-heterogeneity trade-off hypothesis
<p>Environmental heterogeneity is one of the most fundamental drivers of species diversity. For decades, ecologists have suggested that heterogeneity-diversity relationships are generally positive. But today, a greater variety of heterogeneity-diversity relationships is discussed. In this study, we contrasted two hypotheses for wood-inhabiting fungi: The classical heterogeneity-diversity hypothesis, that predicts positive relationships due to an increase in niche dimensionality with increasing heterogeneity. And the more recently stated area-heterogeneity trade-off hypothesis, that predicts a unimodal pattern due to an inherent trade-off between the number of occupied niches and the effective area per species. It allows positive and negative relationships only as special cases.</p> <p>We sampled 3,715 deadwood objects on 135 plots along a forest structure gradient in the Black Forest, Germany, and recorded 284 wood-inhabiting fungal species. To assess heterogeneity of deadwood structures, we calculated two multidimensional structural diversity indices: Structural richness was used as a measure of available niche space, and structural divergence as a measure of multivariate variance within that niche space. Those indices were then related to species richness estimates for rare, common, and dominant species, using the framework of Hill numbers.</p> <p>We found a linear, positive effect of structural richness and a unimodal effect for structural divergence on estimated species diversity. Structural richness, but not structural divergence was strongly correlated with the number of sampled deadwood objects. No clear differences between the responses of rare, common, and dominant species to the two heterogeneity gradients were found. We also estimated the mean abundance as proxy for mean population size, which decreased significantly with structural richness, but was non-significantly related to structural divergence.</p> <p><em>Synthesis: </em>In general, the results of this study suggest a unimodal heterogeneity-diversity relationship for deadwood-inhabiting fungi, and are thereby in line with the area-heterogeneity trade-off hypothesis. Thus, the negative effect of heterogeneity should lead to lower species richness and higher risk of stochastic extinctions at high levels of heterogeneity. However, as deadwood amount and deadwood diversity are often strongly correlated, we argue that the positive effect of resource availability on species richness may mask the negative effect of structural heterogeneity in some cases.</p>
Evolution of invasion syndrome in invasive goldenrod is not constrained by genetic trade-offs
<p>A suite of plant traits is thought to make weed populations highly invasive, including vigorous growth and reproduction, superior competitive ability, and high dispersal ability. Using a breeding design and a common garden experiment, we tested whether such an "invasion syndrome" has evolved in an invasive range of Solidago altissima, and whether the evolution is likely to be genetically constrained. We found an overall shift in invasive phenotypes between native North American and invasive Japanese populations. The invasive populations were taller and produced more leaves, suggesting a superior ability to exploit limited resources. The populations also produced more allelopathic compounds that can suppress competitor growth. Finally, invasive populations produced more seeds, which are smaller and are released from a greater height, indicating a potential for superior dispersal ability than the native populations. Quantitative genetics analyses found a large amount of additive genetic variation in most focal traits across native and invasive populations, with no systematic differences in its magnitude between the ranges. Genetic covariances among three traits representing invasion strategies (leaf mass, polyacetylene concentration and seed size) were small. The R metric, which measures the effect of genetic covariances on the rate of adaptation, indicated that the covariance neither constrains nor accelerates concerted evolution of these traits. The results suggest that the invasion syndrome in S. altissima has evolved in the novel range due to ample additive genetic variation, and relatively free from genetic trade-offs.</p>
Understanding Crypto Trading
<p>added initial Datasets used in the thesis.</p>
Replication files for "Distance(s) and the volatility of international trade(s) (2024)" by Arnaud Mehl, Giulia Sabbadini, Martin Schmitz, and Cedric Tille, European Economic Review 167
<p>Replication files for "Distance(s) and the volatility of international trade(s) (2024)" by Arnaud Mehl, Giulia Sabbadini, Martin Schmitz, and Cedric Tille, European Economic Review 167. Science direct : https://www.sciencedirect.com/science/article/pii/S0014292124000862?via%3Dihub</p> <p>Contains three folder, each with detailed steps: </p> <p>-Replication_country_level_results</p> <p>-Replication_product_level_results</p> <p>-Tables_figures</p>
Bridging the conservation and development trade-off?: A working landscape critique of a conservancy in the Maasai Mara
<p>The recent call to halt biodiversity loss by protecting half the planet has been hotly contested because of the extent to which people might be excluded from these landscapes. It is clear that incorporating landscapes that implicitly work for indigenous people is vital to achieving any sustainable targets.We examine an attempt to balance the trade-offs between conservation and development in Enonkishu Conservancy in the Maasai Mara, using a working landscape approach. Mobile livestock production strategies are theoretically consistent with wildlife-based activities and can present a win-win solution for both conservation and development. We explore the success and failings of Enonkishu's evolving attempts to achieve this: addressing the criticism of the conservation sector that it fails to learn from its mistakes. We found that Enonkishu has had considerable positive conservation outcomes, preventing the continued encroachment of farmland, maintaining and improving rangeland health relative to the surrounding area, while maintaining diverse and large populations of wildlife and livestock. The learning from certain ventures, that failed, particularly on livestock, has created institutions and governance that, while still evolving, are more robust and relevant for conservancy members, by being fluid and inclusive. Diverse revenue streams (beyond tourism, including a residential estate, livestock venture and philanthropy) enabled Enonkishu to withstand the pressures of Covid-19. Livestock is crucial for defining the vision of the conservancy, and the institutions and governance that underpin it.</p>
Dispersing low carbon technologies through trade; Have trade agreements helped?
<p>This dataset was used in a research paper which examines the impact of trade agreements on low carbon technologies trade.</p>
Historical Pollen Records from `The Productivity-Stability Trade-off in Global Food Systems'
<p>Historical pollen records from Europe used to detect evidence of agricultural development on plant pollen dynamics. </p>
Dataset on production, processing and trading activities in Ghana's cocoa value chain
<p>This covers data on production, processing and trading activities in Ghana's cocoa value chain that were used to populate a stock-and flow diagram representing the baseline model of the cocoa value chain. Data are retrieved from different secondary sources, collated in excel sheets</p>
The RESPECT Trade Similarity Index
<p>We use detailed product-level trade data from Eurostat to construct a Trade Similarity Index for each Member State of the European Union and each third country. The Trade Similarity Index takes values between 0 and 1. A higher value indicates that the trade pattern of the Member State is more similar to the average of the European Union. A value of 0 means that there is no product overlap between the exports (or imports) of the Member State and the rest of the EU. A value of 1 means that the Member State exports (or imports) every product in the same proportion as the rest of the EU.</p>
Continuous Non-Functional Requirements: Practices, Opportunities, and Trade-offs for Small, Agile Organizations
<p>This data represents two artifacts from our research in evaluating how small, agile organizations manage non-functional requirements in conjunction with continuous practices. It includes our base interview questions and the resulting codebook.</p> <p>This page includes supplementary materials associated with our paper entitled "Continuous Non-Functional Requirements: Practices, Opportunities, and Trade-offs for Small, Agile Organizations".</p>
Dataset for: Navigating Ecosystem Services Trade-offs: A Global Comprehensive Review
<p><strong>Methods</strong></p> <p>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).</p> <p>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:</p> <p>· We comprehensively review and further explore the global evidence of ES trade-offs and synergies focusing on all systems including terrestrial, freshwater, and marine.</p> <p>· We compiled the evidence on trade-offs and synergies among multiple ES interacting across various ecosystems.</p> <p>· 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.</p> <p>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.</p> <p>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.</p> <p>The <em>peer-reviewed </em>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:</p> <p>(“*ecosystem service*” OR “environment* service*” OR “ecosystem* approach*” OR “ecosystem good*” OR “environment* good*”)</p> <p>AND</p> <p>(“*trade-off*” OR “tradeoff*” OR “synerg*” OR “win-win*” OR “bundle*” OR “cost*and benefit*” OR “co-benefit*”) n=5194</p> <p>Papers were preliminarily coded with a semantic analysis using the R package Bibliometrix (<a href="http://www.bibliometrix.org">http://www.bibliometrix.org</a>).</p> <p>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.</p> <p>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).</p> <p>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.</p> <p>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).</p> <p>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).</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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).</p> <p>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.</p> <p>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 <em>dplyr </em>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.</p> <p><strong>References:</strong></p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>Millennium Ecosystem Assessment (MEA).(2005). Ecosystems and Human Well-Being: Synthesis. Island Press, Washington DC.</p> <p>Pullin, A. S., & Stewart, G. B. (2006). Guidelines for systematic review in conservation and environmental management. Conservation biology, 20(6), 1647-1656.</p> <p>Sukhdev, P. (2010). The economics of ecosystems & biodiversity: mainstreaming the economics of nature: a synthesis of the approach, conclusions, and recommendations of TEEB. UNEP.</p> <p>R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/</p> <p>Wallace K.J. (2007). Classification of ecosystem services: Problems and solutions. Biological Conservation 139, 235-246.</p> <p><strong>Dataset</strong></p> <p>Name of the file: MMartinez-Harms-Dataset-ESTrade-offs_Zenodofinal.xlsx</p> <p>Description: Complete database of the 3286 studies reviewed in this synthesis coded by:</p> <table> <tbody> <tr> <td><strong>N</strong></td> <td>Number of papers</td> </tr> <tr> <td><strong>AU</strong></td> <td>Authors</td> </tr> <tr> <td><strong>TI</strong></td> <td>Title</td> </tr> <tr> <td><strong>SO</strong></td> <td>Publication name</td> </tr> <tr> <td><strong>Included</strong></td> <td>identify papers that did alignd (yes) or did not (No) align with the review objectives.</td> </tr> <tr> <td><strong>JI</strong></td> <td>Scientific Journal</td> </tr> <tr> <td><strong>AB</strong></td> <td>Abstract</td> </tr> <tr> <td><strong>DE</strong></td> <td>Authors’ Keywords</td> </tr> <tr> <td><strong>ID</strong></td> <td>Keywords associated by ISI database</td> </tr> <tr> <td><strong>LA</strong></td> <td>Language</td> </tr> <tr> <td><strong>DT</strong></td> <td>Document Type (article, review, editorial, book chapter, letter, meeting abstract)</td> </tr> <tr> <td><strong>TC</strong></td> <td>Times Cited</td> </tr> <tr> <td><strong>PY</strong></td> <td>Publication Year</td> </tr> <tr> <td><strong>SC</strong></td> <td> Subject Categories</td> </tr> <tr> <td><strong>WC</strong></td> <td>Web of Science categories</td> </tr> <tr> <td><strong>System</strong></td> <td>Freshwater, terrestrial, marine, and other</td> </tr> <tr> <td><strong>Habitat</strong></td> <td>Habitat ES category</td> </tr> <tr> <td><strong>Regulating</strong></td> <td>Regulating ES category</td> </tr> <tr> <td><strong>Cultural</strong></td> <td>Cultural ES category</td> </tr> <tr> <td><strong>Provisionning</strong></td> <td>Provisionning ES category</td> </tr> <tr> <td><strong>Country_Classification</strong></td> <td>Country of study</td> </tr> <tr> <td><strong>Continent</strong></td> <td>Continent of study</td> </tr> <tr> <td><strong>Synergies_Trade-offs</strong></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><strong>Stakeholder_Participation</strong></td> <td>The study interacts with stakeholders at any moment of the study or policy decisions. </td> </tr> <tr> <td><strong>Critical_Appraisal</strong></td> <td>Articles are appraised to ensure that they are adequate for answering the research question</td> </tr> <tr> <td><strong>Relevance</strong></td> <td>Relevance to the review question (0 no relevance, 1 relevance)</td> </tr> <tr> <td><strong>Methodological_Transparency</strong></td> <td>Assessed based on the clarity and completeness of methodological descriptions</td> </tr> <tr> <td><strong>Significance</strong></td> <td>Significance of the contribution (are new ideas offered?)</td> </tr> <tr> <td><strong>Generalizability</strong></td> <td> Is the context specified, and do the ideas apply in other contexts?</td> </tr> <tr> <td><strong>Total_Score</strong></td> <td>The sum total score across all critical appraisal criteria </td> </tr> <tr> <td><strong>Category</strong></td> <td>Coastal, Urban, Wetlands, Forest, Mountain, Freshwater, Agroecosystems, and Others mainly represented multiple ecosystems</td> </tr> <tr> <td><strong>Uses_INVEST</strong></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>
Trade-offs Between Performance Efficiency and Costs While Using Function as a Service for Machine Learning Tasks: A Systematic Literature Review
<p>This repository contains all artifacts that were used for the systematic literature review (SLR) related to a the cost and performance trade-offs when Function as a Service (FaaS) for machine learning (ML) tasks.</p> <p>We selected and analyzed 65 papers and publications that were optained via Scopus. The study took place in 2024 from January to August 2024.</p>
Digitalization and Trade in Southeast Asia
<p>The dataset contains the data on various aspects of digitalization, including digital infrastructure, regulation policy, and international trade with focus on the digitally delivered trade in selected Souteast Asia countries.</p>
Export-Led Decay: The Trade Channel in the Gold Standard Era
<p>This package contains the data, programs and instructions to replicate manuscript "Export-Led Decay: The Trade Channel in the Gold Standard Era"by Bernardo Candia and Mathieu Pedemonte forthcoming at JEEA</p>
Replication package for: "Atlantic Trade and Conflict in Europe"
<p>Replication package for Reshad N. Ahsan, Laura Panza, and Yong Song "Atlantic Trade and Conflict in Europe", published in the Economic Journal<br><br></p>
Data from: Juvenile concentrations of IGF-1 predict life-history trade-offs in a wild mammal
Early postnatal development can have profound effects on life-history traits later in life. One mechanism hypothesized to mediate this relationship is the anabolic hormone, insulin-like growth factor-1 (IGF-1). IGF-1 contributes importantly to postnatal growth, and thus offers a means by which environmental and genetic variation might direct organismal development, reproduction and survival. We tested whether juvenile concentrations of IGF-1 can predict intraspecific variation in life-history traits later in life using longitudinal data from free-living female spotted hyenas (Crocuta crocuta). We found that juvenile concentrations of IGF-1 predicted heavier juvenile mass, which in turn predicted greater survival to reproductive maturity. However, independent of mass, higher juvenile concentrations of IGF-1 predicted earlier age at first parturition and reduced longevity in adulthood. Our results highlight the importance of early postnatal development as a determination period in mammals and suggest that concentrations of IGF-1 during this sensitive period can be used to predict important later-life trade-offs between growth, reproductive fitness and life span in wild, long-lived animals.
The future of coal investment, trade and stranded assets
<p>Dataset to support the publication "The future of coal investment, trade and stranded assets"</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.