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2,260 results for “climate change”
Figure 1 in Distribution of microarthropods across altitude and aspect in the sub-Antarctic: climate change implications for an isolated oceanic island
Figure 1 Interaction plots of mite and springtail species richness (S) and abundance (N) at low, middle and high altitudes on the eastern and western aspect of Marion Island (weighted means ± 95 % confidence intervals). Groups not sharing letters differ significantly (p <0.05). Model results provided in Table 2 and Appendix 2.
Cereal yield response to climate change in key grain producing areas of the Northern Hemisphere
<p>Vulnerability mapping is a field of increasing importance as we search for an ecologically and economically sustainable<br> climate-smart land-use system, which is necessary for the development of green infrastructure and agricultuVulnerability<br> mapping is a growing field with increasing importance in developing an ecologically and economically sustainable climate-smart land-use system, which may serve the advancement of green infrastructure and agricultural production. The<br> transformation of the climatic regime has an undeniable impact on plant production, but we rarely have long enough data<br> series to scrutinize the unfolding effects of the microregional patterns of the global climate-cereal yield relationship. To fill this<br> gap, I will analyze three regions of the Northern Hemisphere under continental climate, which represent key landscapes<br> concerning global food production and security, contributing a multi-way knowledge transfer through training, teaching, and<br> different form of communication activities. The relationship between climate indices, maize, and wheat yields will be analyzed<br> applying high geographical resolution data from Northern China, Hungary, and northern states of the US Midwest at a<br> landscape scale by Köppen-Geiger zones using linear, local, and spatial regression and bootstrap resampling tests and<br> developed data visualization techniques. This offers a unique opportunity to comparatively analyze the differences in<br> climate-cereal yield associations by landscape types and regions. The expected results will provide highly supportive factors<br> for planning and managing an ecologically and economically sustainable land-use system. The intended publications,<br> lectures, and collaborative actions will have a positive impact on domestic and EU research. The planned training and the<br> expected results of the action will further strengthen my career opportunities and put me in a position where I will be<br> considered for a tenured position at a research institution in Hungary.</p>
Conservation of woody species in China under future climate and land-cover changes
<ol> <li>Climate and land-cover changes are major threats to biodiversity, and their impacts are expected to intensify in the future. Protected areas (PAs) are crucial for biodiversity conservation. However, their effectiveness under future climate and land-cover changes remains to be evaluated. Moreover, the impacts of climate and land-cover changes on multi-dimensions of biodiversity are rarely considered when expanding PAs.</li> <li>Using distributions of 8732 woody species in China and species distribution models, we identified species that will be threatened by future climate and land-cover changes (i.e. species with significant projected loss of suitable habitats by the 2070s) under different dispersal scenarios. We then estimated the geographical patterns in species richness (SR) and phylogenetic diversity (PD) of these threatened species, evaluated the effectiveness (i.e. the changes in SR and PD) of Chinese PAs, and identified conservation priorities for future PA expansion.</li> <li>Approximately 12-38% of woody species will be threatened under different scenarios. These species tend to be clustered in the tree of life, and their SR and PD show consistent spatial patterns, being highest at low latitudes. PAs currently protect 90% of these threatened species. However, their SR and PD of threatened species within PAs will decrease by 30-40% by the 2070s, which reduces the PA effectiveness, especially for PAs at low elevations and those with low topographic heterogeneity and high natural vegetation loss.</li> <li>The conservation priorities identified from the SR and PD of the threatened species are mainly in mountains in southern China, the Yunnan-Guizhou Plateau, and Taiwan Island. PA expansion and ecological corridors in these regions are needed to conserve these threatened species.</li> <li> <i>Synthesis and applications.</i> We present a systematic study of the impacts of future climate and land-cover changes on the conservation status of woody species and PA effectiveness in China. Our results suggest that future climate and land-cover changes will reduce PA effectiveness, and the spatial prioritization of biodiversity conservation should consider the influences of future global changes on biodiversity. These results shed new light on the conservation priorities for the post-2020 expansion of PAs in China.</li> </ol>
Reduced-form Climate Change Damage Functions
<p>Reduced-form Climate Change Damage Functions of impacts on: Agriculture, Fishery, Forestry, Sea level rise, Riverine floods, Transport, Energy supply, Energy demand, Labour productivity.</p>
Daily maximum VPD - supporting data for Jain et al. 2021, Nature Climate Change
<p>Global daily maximum Vapour Pressure Deficit (VPD) for 1979-2020 at 0.25 deg resolution. This data supports the analysis in "Observed increases in extreme fire weather driven by atmospheric humidity and temperature", Jain et al. 2021, accepted for publication in Nature Climate Change.</p> <p>VPD was calculated using the hourly ERA5 2m temperature and 2m dewpoint temperature using the Alduchov and Eskridge (1996) approximation as implemented in the R package ‘bigleaf’ (Knauer et al. 2018).</p> <p>Variables were processed using inputs from the ERA5 Reanalysis (hourly surface data from 1979–2020, available from <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview</a>). </p> <p>References</p> <p>Alduchov, O. A. & Eskridge, R. E., 1996: Improved Magnus form approximation of saturation vapor pressure. Journal of Applied Meteorology, 35, 601-609</p> <p>Knauer, J., El-Madany, T. S., Zaehle, S., & Migliavacca, M. (2018). Bigleaf—An R package for the calculation of physical and physiological ecosystem properties from eddy covariance data. <em>PloS one</em>, <em>13</em>(8), e0201114.</p> <p> </p> <p> </p>
Global diversity patterns of larger benthic foraminifera under future climate change
<p><span>Global warming threatens the viability of tropical coral reefs and associated marine calcifiers, including symbiont-bearing larger benthic foraminifera (LBF). The impacts of current climate change on LBF are debated because they were particularly diverse and abundant during past warm periods. Studies on the responses of selected LBF species to changing environmental conditions reveal varying results. </span><span>Based on a comprehensive review of the scientific literature on LBF species occurrences, we applied species distribution modeling using Maxent to estimate present-day and future species richness patterns on a global scale for the time periods 2040–2050 and 2090–2100. </span><span> </span><span>For our future projections, we focus on Representative Concentration Pathway 6.0 from the Intergovernmental Panel on Climate Change, which projects mean surface temperature changes of +2.2°C by the year 2100. This data set comprises all raw data and results. </span>Our results suggest that species richness in the Central Indo-Pacific is two to three times higher than in the Bahamian ecoregion, which we have identified as the present-day center of LBF diversity in the Atlantic. Our future predictions project a dramatic temperature-driven decline in low-latitude species richness and an increasing widening bimodal latitudinal pattern of species diversity. While the central Indo-Pacific, now the stronghold of LBF diversity, is expected to be most pushed outside of the currently realized niches of most species, refugia may be largely preserved in the Atlantic. LBF species will face large-scale non-analogous climatic conditions compared to currently realized climate space in the near future, as reflected in the extensive areas of extrapolation, particularly in the Indo-Pacific. Our study supports hypotheses that species richness and biogeographical patterns of LBF will fundamentally change under future climate conditions, possibly initiating a faunal turnover by the late 21st century.</p>
Data from: Species-specific traits mediate avian demographic responses under past climate change
<p>Anticipating species' responses to environmental change is a<span> pressing mission in biodiversity conservation. Despite decades of research investigating how climate change may affect population sizes, historical context is lacking and the traits which mediate demographic sensitivity to changing climate remain elusive. We use whole-genome sequence data to reconstruct the demographic histories of 263 bird species over the past million years and identify networks of interacting morphological and life-history traits associated with changes in effective population size (<em>N<sub>e</sub></em>) in response to climate warming and cooling. Our results identify direct and indirect effects of key traits representing survival, reproduction, and dispersal processes on long-term demographic responses to climate change and highlight traits most likely to influence population responses to ongoing climate warming.</span></p>
Urban nature-based solutions to climate change adaptation database
<p>This dataset is the result of a systematic mapping of the application of nature-based solutions (NbS) to climate change adaptation in urban areas across the world. We screened 823 potential urban NbS to climate adaptation, which resulted in the inclusion of 216 interventions worldwide from 130 cities in 55 countries within our dataset. We analysed each of the NbS according to key characteristics in terms of how these interventions are helping cities confront the grave climate change, biodiversity, and related social challenges they are facing. We further analyse the capacity for each NbS to affect change in the city it is implemented within, which ranges from incremental (shallow) change to reformistic (middle ground) and finally transformative (deep) change. The full range of climate, biodiversity, and social challenges, as well as further discussion on the meaning of these different levels of change, is described in the attached file in the coding template tab. </p> <p>The results and analysis of this database (v 1.0.0) appear in the following article:</p> <p>Goodwin, S., M. Olazabal, A. Castro, U. Pascual. "Global mapping of urban nature-based solutions for climate change adaptation". <em>Nature Sustainability. doi: <a href="http://doi.org/10.1038/s41893-022-01036-x">10.1038/s41893-022-01036-x </a></em></p> <p><strong>A read-only version of this article can be found online for free <a href="https://rdcu.be/c4tjk">here</a>.</strong></p> <p>For any use of this dataset, please cite this dataset along with the associated publication in Nature Sustainability. Please report any errors or omissions to Sean Goodwin.</p>
High trophic level feedbacks on global ocean carbon uptake and marine ecosystem dynamics under climate change (Dupont et al., GBC)
<p>Files used to make the analysis in the paper "High trophic level feedbacks on global ocean carbon uptake and marine ecosystem dynamics under climate change" (Dupont et al., accepted in GBC)</p> <p>- HTL_LTL_figures.ipynb is the python notebook in which are computed the different terms to make the figures of the paper </p> <p>- histrcp85.1-PISAPE-N-OW** and piCtrl2-PISAPE-N-OW** files contain the raw outputs of the one way (OW) simulation</p> <p>- histrcp85.1-PISAPE-N-TW* and piCtrl2-PISAPE-N-TW* files contain the raw outputs of the two way (TW) simulation</p> <p>- all files ending with *rmp_f.nc/ *regrid.nc/ *f20.nc are regridded files to make maps used in the paper. More details can be found in the python noteboook (briefly, dAT_* = change in active export, dDIC_*= change in dissolved inorganic carbon, dEPC200_* = change in carbon export at 200m depth, OW/TW_<a href="https://zenodo.org/api/files/cc2ae8cc-a150-4bc6-9125-04d9e3465859/TW_dBMapermp_f.nc">dBMape</a>* = OW/TW change in small high trophic levels biomass, OW/<a href="https://zenodo.org/api/files/cc2ae8cc-a150-4bc6-9125-04d9e3465859/TW_dBMapermp_f.nc">TW_dBM</a>meszo* = OW/TW change in mesozooplankton biomass)</p> <p>- <a href="https://zenodo.org/api/files/cc2ae8cc-a150-4bc6-9125-04d9e3465859/egestt2_2.nc">egestt2_2.nc</a>, excrett2_2.nc and graztt2_2.nc are the outputs of egestion, excretion and grazing terms used to compute the active export (AT). </p>
Data for: Predicting habitat suitability for Townsend's big-eared bats across California in relation to climate change
<p>Aim: Effective management decisions depend on knowledge of species distribution and habitat use. Maps generated from species distribution models are important in predicting previously unknown occurrences of protected species. However, if populations are seasonally dynamic or locally adapted, failing to consider population level differences could lead to erroneous determinations of occurrence probability and ineffective management. The study goal was to model the distribution of a species of special concern, Townsend's big-eared bats (Corynorhinus townsendii), in California. We incorporate seasonal and spatial differences to estimate the distribution under current and future climate conditions.</p> <p>Methods: We built species distribution models using all records from statewide roost surveys and by subsetting data to seasonal colonies, representing different phenological stages, and to Environmental Protection Agency Level III Ecoregions to understand how environmental needs vary based on these factors. We projected species' distribution for 2061-2080 in response to low and high emissions scenarios and calculated the expected range shifts.</p> <p>Results: The estimated distribution differed between the combined (full dataset) and phenologically-explicit models, while ecoregion-specific models were largely congruent with the combined model. Across the majority of models, precipitation was the most important variable predicting the presence of C. townsendii roosts. Under future climate scnearios, distribution of C. townsendii is expected to contract throughout the state, however suitable areas will expand within some ecoregions. Main conclusion: Comparison of phenologically-explicit models with combined models indicate the combined models better predict the extent of the known range of C. townsendii in California. However, life history-explicit models aid in understanding of different environmental needs and distribution of their major phenological stages. Differences between ecoregion-specific and statewide predictions of habitat contractions highlight the need to consider regional variation when forecasting species' responses to climate change. These models can aid in directing seasonally explicit surveys and predicting regions most vulnerable under future climate conditions.</p>
Experimental evaluation of how biological invasions and climate change interact to alter the vertical assembly of an amphibian community
<ol> <li>While biotic-abiotic interactions are increasingly documented in nature, a process-based understanding of how such interactions influence community assembly is lacking in the ecological literature. Perhaps the most emblematic and pervasive example of such interactions is the synergistic threat to biodiversity posed by climate change and invasive species. Invasive species often out-compete or prey on native species. Despite this long-standing and widespread issue, little is known about how abiotic conditions, such as climate change, will influence the frequency and severity of negative biotic interactions that threaten the persistence of native fauna.</li> <li>Treefrogs are a globally diverse group of amphibians that climb to complete life-cycle processes, such as foraging and reproduction, as well as to evade predators and competitors, resulting in frog communities that are vertically partitioned. Furthermore, treefrogs adjust their vertical position to maintain optimal body temperature and hydration in response to environmental change. Here, utilizing this model group, we designed a novel experiment to determine how extrinsic abiotic and biotic factors (changes to water availability and an introduced predator, respectively) interact with intrinsic biological traits, such as individual physiology and behavior, to influence treefrogs’ vertical niche. </li> <li>Our study found that treefrogs adjusted their vertical niche through displacement behaviors in accordance with abiotic resources. However, biotic interactions resulted in native treefrogs distancing themselves from abiotic resources to avoid the non-native species. Importantly, under altered abiotic conditions, both native species avoided the non-native species – more than they avoided their native counterpart. Additionally, exposure to the non-native species resulted in native species altering their tree climbing behaviors by and becoming more vertically dynamic to avoid the non-native antagonist.</li> <li>Our experiment determined that vertical niche selection and community interactions were most accurately represented by a biotic-abiotic interaction model, rather than a model that considers these factors to operate in an isolated (singular) or even additive manner. Our study provides evidence that native species may be resilient to interacting disturbances via physiological adaptations to local climate and plasticity in space-use behaviors that mediate the impact of the introduced predator. </li> </ol>
Dataset of Last Interglacial climate from publication "Modeled storm surge changes in a warmer world: the Last Interglacial" by P. Scussolini et al.
<p>Results from the simulation of Last Interglacial (Eemian) climate with climate model CESM1.2. Variables are: sea-level pressure (PSL); meridional wind (V), and zonal wind (U). Time step is 6-hourly.</p> <p>Detailed description of the methods are in the original publication:</p> <p>Scussolini, P., Dullaart, J., Muis, S., Rovere, A., Bakker, P., Coumou, D., Renssen, H., Ward, P. J., and Aerts, J. C. J. H.: Modelled storm surge changes in a warmer world: the Last Interglacial, EGUsphere, 2022, 1-20, 10.5194/egusphere-2022-101, 2022.</p>
Dataset of pre-industrial climate from publication "Modeled storm surge changes in a warmer world: the Last Interglacial" by P. Scussolini et al.
<p>Results from the simulation of pre-industrial climate with climate model CESM1.2. Variables are: sea-level pressure (PSL); meridional wind (V), and zonal wind (U). Time step is 6-hourly.</p> <p>Detailed description of the methods are in the original publication:</p> <p>Scussolini, P., Dullaart, J., Muis, S., Rovere, A., Bakker, P., Coumou, D., Renssen, H., Ward, P. J., and Aerts, J. C. J. H.: Modelled storm surge changes in a warmer world: the Last Interglacial, EGUsphere, 2022, 1-20, 10.5194/egusphere-2022-101, 2022.</p>
Data for: Genomic vulnerability to climate change in Quercus acutissima, a dominant tree species in East Asian deciduous forests
<p><span>Understanding the evolutionary processes that shape the landscape of genetic variation and influence the response of species to future climate change is critical for biodiversity conservation. Here, we sampled </span><span>27</span><span> populations across the distribution range of a dominant forest tree, <em>Quercus</em> <em>acutissima</em>, in East Asia, and applied genome-wide analyses to track the evolutionary history and predict the fate of populations under future climate. We found two genetic groups (East and West) in <em>Q</em>. <em>acutissima</em> that diverged during the Pliocene. </span><span>We also found</span><span> a heterogeneous landscape of genomic variation in this species</span><span>, which may have been shaped by </span><span>population demography and </span><span>linked selections</span><span>.</span><span> Using genotype-environment association analyses, we identified climate-associated SNPs in a diverse set of genes and functional categories, indicating a model of polygenic adaptation in <em>Q</em>. acutissima<em>.</em> We further estimated three genetic offset metrics to quantify genomic vulnerability of this species to climate change due to the complex interplay </span><span>between</span><span> local adaptation</span><span> and</span><span> migration</span><span>.</span><span> We found that marginal populations are under </span><span>higher</span><span> risk of local extinction</span><span> because of</span><span> future climate change</span><span>, and may not be able to track </span><span>suitable habitats </span><span>to maintain the gene-environment relationships observed under the current climate.</span><span> We also detected higher reverse genetic offsets in northern China, indicating that genetic variation currently present in the whole range of <em>Q</em>. <em>acutissima</em> may not adapt to future climate conditions in this area.</span> <span>Overall, this study</span><span> illustrates how evolutionary</span><span> processes </span><span>have</span><span> shaped the landscape of genomic variation, and</span><span> provides a comprehensive genome-wide view of climate maladaptation in <em>Q</em>. <em>acutissima</em>.</span></p>
Supplementary Data and Code: Determinants of range sizes pinpoint vulnerability of groundwater species to climate change: a case study on subterranean amphipods from the Dinarides
<p>Supplementary Data and R code for phylogenetic analyses for manuscript entitled <em>Determinants of range sizes pinpoint vulnerability of groundwater species to climate change: a case study on subterranean amphipods from the Dinarides.</em></p> <p><strong>The dataset contains</strong></p> <p><em>beast.tree</em> → data for import into R: maximum credibility phylogeny<br> <em>data_lambert.csv</em> → data for import into R: data on habitat and distribution for 52 <em>Niphargus </em>species<br> <em>morpho.csv</em> → data for import into R: morphometric data (body length) for 52 <em>Niphargus </em>species<br> <em>niphargus_ranges.Rmd</em> → fully reproducible R markdown file<br> <em>niphargus_ranges.html </em>→ html output of Rmd file</p> <p>To be able to run the analysis put the data files into folder <data> and run the Rmd script.</p>
Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use
<p>Changes in climate and land-use and land-cover (LULC) are expected to influence surface water runoff and nutrient characteristics of estuarine watersheds, but the extent to which estuaries are vulnerable to altered nutrient loading under future conditions is poorly understood. The present work aims to address this gap through the development of a new vulnerability assessment framework that accounts for (1) estuarine exposure to projected changes in total nitrogen (TN) and total phosphorus (TP) loads as a function of LULC and climate change under several scenarios to altered nutrient loads, (2) sensitivity (i.e., how responsive estuaries are to altered nutrient loads), and (3) adaptive capacity (i.e., how the socio-ecological system can use existing resources to reduce the impacts associated with increased exposure). The framework was applied to 112 estuaries and their contributing watersheds across the contiguous U.S., specifically to look at regional variability in estuarine vulnerability to nutrient loading. Study findings revealed that the largest increases in estuarine nutrient loads are expected in the North and South Atlantic regions and eastern Gulf of Mexico, while the lowest increase is expected in the North and South Pacific regions and the western Gulf of Mexico. However, the North Atlantic and the South Pacific had the highest adaptive capacity, which could potentially counteract the effects of LULC and climate change on nutrient loads. Our findings illustrate the benefits of integrating natural and socio-ecological factors to identify opportunities to develop adaptation plans and policies to mitigate ecological degradation in vitally important estuaries. A<a href="https://lisemontefiore.shinyapps.io/estuarine_vulnerability/"> web-based application</a> has been developed to visualize and download the data.</p>
Data from: Potential effects of future climate change on global reptile distributions and diversity
<p class="first-paragraph"><span><strong>Aim:</strong></span><span> Until recently, complete information on global reptile distributions has not been widely available. Here, we provide the first comprehensive climate impact assessment for reptiles on a global scale.</span></p> <p class="western"><span><strong>Location:</strong></span><span> Global, excluding Antarctica</span></p> <p class="western"><span><strong>Time period:</strong></span><span> 1995, 2050, 2080</span></p> <p class="western"><span><strong>Major taxa studied:</strong></span><span> Reptiles</span></p> <p class="western"><span><strong>Methods:</strong></span><span> We modelled the distribution of 6,296 reptile species and assessed potential global as well as realm-specific changes in species richness, the change in global species richness across climate space, and species-specific changes in range extent, overlap and position under future climate change. To assess the future climatic impact on 3,768 range-restricted species, which could not be modelled, we compared the future change in climatic conditions between both modelled and non-modelled species.</span></p> <p class="western"><span><strong>Results:</strong></span><span> Reptile richness was projected to decline significantly over time, globally but also for most zoogeographic realms, with the greatest decrease in Brazil, Australia and South Africa. Species richness was highest in warm and moist regions, with these regions being projected to shift further towards climate extremes in the future. Range extents were projected to decline considerably in the future, with a low overlap between current and future ranges. Shifts in range centroids differed among realms and taxa, with a dominating global poleward shift. Non-modelled species were significantly stronger affected by projected climatic changes than modelled species.</span></p> <p class="western"><span><strong>Main conclusions:</strong></span><span> With ongoing future climate change, reptile richness is likely to decrease significantly across most parts of the world. This effect as well as considerable impacts on species' range extent, overlap, and position were visible across lizards, snakes and turtles alike. Together with other anthropogenic impacts, such as habitat loss and harvesting of species, this is a cause for concern. Given the historical lack of global reptile distributions, this calls for a re-assessment of global reptile conservation efforts, with a specific focus on anticipated future climate change.</span></p>
Shifting environmental predictors of phenotypes under climate change: A case study of growth in high latitude seabirds
<p>Climate change is altering species' traits across the globe. To predict future trait changes and understand the consequences of those changes, we need to know the environmental drivers of phenotypic change. In the present study, we use multi-decadal long datasets to determine periods of within-year environmental variation that predict growth of three seabird species. We evaluate whether these periods changed over time and use them to predict future growth under climate change. We find that predictions of trait change could be improved by considering that 1) the timing of environmental factors used to predict traits (predictive-environmental features) can change over time, and 2) the type of predictive-environmental features can change over time. We find evidence of changes in the timing of environmental predictors in all populations studied and evidence for a change in the type of predictor in the studied Arctic murre population. Environmental models of growth predict that warming conditions will decrease growth rates and bird body sizes in two species (black-legged kittiwakem <em>Rissa</em> <em>tridactyla</em>, and glaucous-winged gullm <em>Larus</em> <em>glaucescens</em>), but not the third (thick-billed murrem <em>Uria</em> <em>lomvia</em>). Consequently, climate change is likely to decrease fledging rates in the gulls and kittiwakes. Further, we find that ice-cover historically predicted murre chick growth well, but no longer does – instead air temperature is now a better predictor of murre growth. Our study highlights a need to investigate whether environmental determinants of trait variation commonly shift in a changing climate and whether such changes have implications for adaptation to novel environments.</p>
Concordant and opposing effects of climate and land-use change on avian assemblages in California's most transformed landscapes
<p>Climate and land-use change could exhibit concordant effects that favor or disfavor the same species, which would amplify their impacts, or species may respond to each threat in a divergent manner, causing opposing effects that moderate their impacts in isolation. We used early 20th-century surveys of birds conducted by Joseph Grinnell paired with modern resurveys and land-use change reconstructed from historic maps to examine avian change in Los Angeles and California's Central Valley (and their surrounding foothills). Occupancy and species richness declined greatly in Los Angeles from urbanization, strong warming (+1.8°C) and drying (-77.2 mm), but remained stable in the Central Valley, despite large-scale agricultural development, average warming (+0.9°C), and increased precipitation (+11.2 mm). While climate was the main driver of species distributions a century ago, the combined impacts of land-use and climate change drove temporal changes in occupancy, with similar numbers of species experiencing concordant and opposing effects.</p>
A Dataset of UN Agencies' Public Communication about Climate Change on Twitter
<p>The present dataset contains the Twitter communication of eight international organizations (IOs) in different policy areas that are known to be central in communicating about climate change. The IOs are comparable in their communication, all being parts of the United Nations (UN). The IOs under consideration are:</p> <ul> <li>Food and Agriculture Organization (FAO),</li> <li>Office for the Coordination of Humanitarian Affairs (UNOCHA),</li> <li>UN Development Programme (UNDP),</li> <li>UN Office for Disaster Risk Reduction (UNDRR),</li> <li>UN Environmental Program (UNEP),</li> <li>UN International Children’s Emergency Fund (UNICEF),</li> <li>UN High Commissioner for Refugees (UNHCR),</li> <li>World Health Organization (WHO).</li> </ul> <p>The tweets were downloaded and parsed via the Twitter Academic Research API (<a href="https://developer.twitter.com/en/products/twitter-api/academic-research">link</a>). In total, the dataset contains 222,191 tweet IDs of the tweets posted by the above 8 UN organizations from their official accounts. This number represents the total number of tweets posted by these selected UN organizations since the beginning of their tweeting history until the end of 2019. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter and the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.</p> <p>The dataset consists of two parts:</p> <ul> <li>Unlabeled tweet IDs of the considered IOs (8 txt-files),</li> <li>Labeled dataset of tweet IDs with labels indicating whether tweets are about climate change or not (1 csv-file).</li> </ul> <p><strong>Unlabeled tweet IDs</strong></p> <p>The corresponding 8 txt-files contain tweet IDs of the corresponding tweets posted by the UN organizations. The files are summarised in Table 1 below. </p> <p> </p> <table align="center"> <caption><strong>Table 1</strong>. Summary of the collected dataset files.</caption> <tbody> <tr> <td><strong>File</strong></td> <td><strong>Organization</strong></td> <td><strong>Account</strong></td> <td><strong>Start date</strong></td> <td><strong>End date</strong></td> <td><strong>Tweet IDs</strong></td> </tr> <tr> <td><strong>tweet_ids_FAO_2009_2019.txt</strong></td> <td>FAO</td> <td>@FAO</td> <td>Jan. 2009</td> <td>Dec. 2019</td> <td>28,630</td> </tr> <tr> <td> <p><strong>tweet_ids_UNDP_2009_2019.txt</strong></p> </td> <td>UNDP</td> <td>@UNDP</td> <td>Jul. 2009</td> <td>Dec. 2019</td> <td>47,960</td> </tr> <tr> <td> <p><strong>tweet_ids_UNDRR_2009_2019.txt</strong></p> </td> <td>UNDRR</td> <td>@UNDRR</td> <td>Oct. 2010</td> <td>Dec. 2019</td> <td>9,735</td> </tr> <tr> <td> <p><strong>tweet_ids_UNEP_2009_2019.txt</strong></p> </td> <td>UNEP</td> <td>@UNEP</td> <td>May 2009</td> <td>Dec. 2019</td> <td>21,615</td> </tr> <tr> <td> <p><strong>tweet_ids_Refugees_2008_2019.txt</strong></p> </td> <td>UNHCR</td> <td>@Refugees</td> <td>Jun. 2008</td> <td>Dec. 2019</td> <td>42,882</td> </tr> <tr> <td> <p><strong>ttweet_ids_UNICEF_2009_2019.txt</strong></p> </td> <td>UNICEF</td> <td>@UNICEF</td> <td>Jul. 2009</td> <td>Nov. 2019</td> <td>34,288</td> </tr> <tr> <td> <p><strong>tweet_ids_UNOCHA_2011_2019.txt</strong></p> </td> <td>UNOCHA</td> <td>@UNOCHA</td> <td>Jul. 2011</td> <td>Jul. 2019</td> <td>12,521</td> </tr> <tr> <td> <p><strong>tweet_ids_WHO_2008_2019.txt</strong></p> </td> <td>WHO</td> <td>@WHO</td> <td>May 2008</td> <td>Dec. 2019</td> <td>24,560</td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td><strong>Total</strong></td> <td>222,191</td> </tr> </tbody> </table> <p>The dataset contains only tweet IDs to ensure compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The tweet IDs need to be hydrated to be used. For hydrating the present dataset, the Hydrator application (<a href="https://github.com/DocNow/hydrator/releases">link</a>) may be used; see a step-by-step tutorial on how to use Hydrator (<a href="http://towardsdatascience.com/learn-how-to-easily-hydrate-tweets-a0f393ed340e#:~:text=Hydrating%20Tweets">link</a>).</p> <p><strong>Labeled dataset related to climate change</strong></p> <p>This is a subset of the entire dataset described above. Namely, 5,750 tweets are randomly selected from the entire dataset and labeled manually as either "climate change-related" or "not climate change-related". The dataset is available in the file <strong>dataset_UN_climate_change_labeled.csv</strong> and is summarised in Table 2 below. </p> <table align="center"> <caption><strong>Table 2</strong>. Summary of the labeled dataset.</caption> <tbody> <tr> <td><strong>Organization</strong></td> <td><strong>Tweets</strong></td> </tr> <tr> <td>FAO</td> <td>753</td> </tr> <tr> <td>UNDP</td> <td>1,199</td> </tr> <tr> <td>UNDRR</td> <td>256</td> </tr> <tr> <td>UNEP</td> <td>540</td> </tr> <tr> <td>UNHCR</td> <td>1,114</td> </tr> <tr> <td>UNICEF</td> <td>910</td> </tr> <tr> <td>UNOCHA</td> <td>366</td> </tr> <tr> <td>WHO</td> <td>612</td> </tr> <tr> <td><strong>Total</strong></td> <td>5,750</td> </tr> </tbody> </table> <p> </p> <p> </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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OpenNeuro
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