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opencc-by-4.0Aug 2020View details →

Citizens Assemble: A study on the impact of climate reporting in the Irish media 'before', 'during' and 'after' the Citizens' Assembly on 'How the State can make Ireland a leader in tackling climate change'.

This dataset contains the .csv file with raw coded data from 594 articles in four Irish media publications (Coded_2020.csv), the .csv file containing all 594 articles (All articles in full (594).csv) along with the associated R Notebook (Citizens Assemble.Rmd) allowing those interested to download the R code. File also contains the images that are used in the R document, and a pdf version of the R output (<a href="https://zenodo.org/api/files/069eeaa7-f82f-4806-a477-9dd1b494c990/Citizens%20Assembly%20R%20Output%20pdf%20format.pdf">Citizens Assembly R Output pdf format.pdf</a>). These files are associated with a manuscript titled: Citizens Assemble: A study on the impact of climate reporting in the Irish media ‘before’, ‘during’ and ‘after’ the Citizens’ Assembly on ‘How the State can make Ireland a leader in tackling climate change’.

opencc-zeroDec 2020View details →

Mating under climate change: impact of simulated heatwaves on the reproduction of model pollinators (Dataset)

<ol> <li>Climate change is related to an increase in frequency and intensity of extreme events such as heatwaves. It is well established that such events may worsen the current worldwide biodiversity decline. In many organisms, heat stress is associated with direct physiological perturbations and could lead to a decrease of fitness. In contrast to endotherms, heat stress resistance has been poorly investigated in heterotherms; especially in insects, in which the internal physiological mechanisms available to regulate body temperature are almost negligible making them sensitive to extreme temperature variations.</li> <li>Wild bees are crucial pollinators for wild plants and crops. Among them, bumblebees are experiencing a strong decline across the world. Therefore, the ongoing global decline of these insect pollinators partly due to climate change could cause major economic issues.</li> <li>Here, we assess how simulated heatwaves impact fertility and attractiveness (key parameters of sustainability) of bumblebee males. We used three model species: Bombus terrestris, a widespread and warm-adapted species, B. magnus and B. jonellus, two declining and cold-adapted species.</li> <li>We highlight that heat shock (40°C) negatively affects sperm viability and sperm DNA integrity only in the two cold-adapted species. Heat shock can also impact the structure of cephalic labial glands and the production of pheromones only in the declining species.</li> <li>The specific disruption in key reproductive traits we identify following simulated heatwave conditions could provide one important mechanistic explanation for why some pollinators are in decline through climate change.</li> </ol>

opencc-zeroJan 2021View details →

Pollution control can help mitigate future climate change impacts on European grayling in the UK

Aim We compare the performance of habitat suitability models using climate data only or climate data together with water chemistry, land cover and predation pressure data to model the distribution of European grayling (Thymallus thymallus). From these models, we (1) investigate the relationship between habitat suitability and genetic diversity; (2) project the distribution of grayling under future climate change and (3) model the effects of habitat mitigation on future distributions. Location United Kingdom Methods Maxent species distribution modelling was implemented using a Simple model (only climate parameters) or a Full model (climate, water chemistry, land-use and predation pressure parameters). Areas of high and low habitat suitability were designated. Associations between habitat suitability and genetic diversity for both neutral and adaptive markers were examined. Distribution under minimal and maximal future climate change scenarios was modelled for 2050, incorporating projections of future flow scenarios obtained from the Centre for Ecology and Hydrology. To examine potential mitigation effects within habitats, models were run with manipulation of orthophosphate, nitrite and copper concentrations. Results We mapped suitable habitat for grayling in the present and the future. The full model achieved substantially higher discriminative power than the Simple model. For low suitability habitat, higher levels of inbreeding were observed for adaptive, but not neutral loci. Future projections predict a significant contraction of highly suitable areas. Under habitat mitigation, modelling suggests that recovery of suitable habitat of up to 10% is possible. Main conclusions Extending the climate-only model improves estimates of habitat suitability. Significantly higher inbreeding coefficients were found at immune genes, but not neutral markers in low suitability habitat indicating a possible impact of environmental stress on evolutionary potential. The potential for habitat mitigation to alleviate distributional changes under future climate change is demonstrated and specific recommendations are made for habitat recovery on a regional basis.

opencc-zeroJan 2021View details →

How adaptive capacity shapes the Adapt, React, Cope Response to climate impacts: insights from small-scale fisheries

As the impacts of climate change on human society accelerate, coastal communities are vulnerable to changing environmental conditions. The capacity of communities and households to respond to these changes (i.e., their adaptive capacity) will determine the impacts of climate and co-occurring stressors. To date, empirical evidence linking theoretical measures of adaptive capacity to community and household responses remains limited. Here we conduct a global meta-analysis examining how metrics of adaptive capacity translate to human responses to change (Adapt, React, Cope Response) in 22 small-scale fishing case studies from 20 countries (n=191 responses). Using both thematic and Qualitative Comparative Analysis, we evaluate how responses to climate, environmental, and social change were influenced by domains of adaptive capacity. Our findings show that adaptive responses at the community level only occurred in situations where the community had Access to Assets, in combination with other domains including Diversity and Flexibility, Learning and Knowledge, and Natural Capital. In contrast, Access to Assets was nonessential for adaptive responses at the household level. Adaptive households demonstrated Diversity and Flexibility when supported by strong Governance or Institutions and were able often able to substitute Learning and Knowledge and Natural Capital with one another. Standardized metrics of adaptive capacity are essential to designing effective policies promoting resilience in natural resource-dependent communities and understanding how social and ecological aspects of communities interact to influence responses. Our framework describes how small-scale fishing communities and households respond to environmental changes and can inform policies that support vulnerable populations.

opencc-zeroDec 2015View details →

Data from: Climate and atmospheric change impacts on sap-feeding herbivores: a mechanistic explanation based on functional groups of primary metabolites

Global climate and atmospheric change are widely predicted to affect many ecosystems. Herbivorous insects account for 25% of the planet's species so their responses to environmental change are pivotal to how future ecosystems will function. Atmospheric change affects feeding guilds differently, however, with sap-feeding herbivores consistently identified as net beneficiaries of predicted increases in atmospheric carbon dioxide concentrations (eCO2). The mechanistic basis for these effects remains largely unknown, and our understanding about how multiple environmental changes, acting in tandem, shape plant–insect interactions is incomplete. This study investigated how increases in temperature (eT) and eCO2 affected the performance of the pea aphid (Acyrthosiphon pisum) via changes in amino acid concentrations in the model legume, lucerne (Medicago sativa). Aphid performance increased under eCO2 at ambient temperatures, whereby aphid fecundity, longevity, colonization success and rm increased by 42%, 30%, 25% and 21%, respectively. eT negated the positive effects of eCO2 on both fecundity and rm, however, and performance was similar to when aphids were reared at ambient CO2. We identified discrete functional groups of amino acids that underpinned the effects of climate and atmospheric change, in addition to plant genotype, on aphid performance. Effects of eT and eCO2 held true across five M. sativa genotypes, demonstrating the generality of their effects. Combining this knowledge with amino acid profiles of existing cultivars raises the possibility of predicting future susceptibility to aphids and preventing outbreaks of a global pest. Moreover, environmentally induced changes in the nutritional ecology of aphids have the capacity to change life-history strategies of aphids and their direct and indirect interactions with many other organisms, including mutualists and antagonists.

opencc-zeroDec 2017View details →

Data from: Climate change impacts on marine biodiversity, fisheries and society in the Arabian Gulf

Climate change - reflected in significant environmental changes such as warming, sea level rise, shifts in salinity, oxygen and other ocean conditions - is expected to impact marine organisms and associated fisheries. This study provides an assessment of the potential impacts on, and the vulnerability of, marine biodiversity and fisheries catches in the Arabian Gulf under climate change. To this end, using three separate niche modelling approaches under a 'business-as-usual' climate change scenario, we projected the future habitat suitability of the Arabian Gulf for 55 expert-identified priority species, including charismatic and non-fish species. Second, we conducted a vulnerability assessment of national economies to climate change impacts on fisheries. The modelling outputs suggested a high rate of local extinction (up to 35% of initial species richness) by 2090 relative to 2010. Spatially, projected local extinctions are highest in the southwestern part of the Arabian Gulf, off the coast of Saudi Arabia, Qatar and the United Arab Emirates (UAE). While the projected patterns provided useful indicators of climate change impacts on the region's diversity, the magnitude of changes in habitat suitability are more uncertain. Fisheries-specific results suggested reduced future catch potential for several countries on the western side of the Arabian Gulf, with projections differing only slightly between models. Qatar and the UAE were particularly affected, with more than a 26% drop in future fish catch potential. Integrating changes in catch potential with socio-economic indicators suggested the fisheries of Bahrain and Iran may be most vulnerable to climate change. We discuss limitations of the indicators and the methods used, as well as the implications of our overall findings for conservation and fisheries management policies in the region.

opencc-zeroDec 2017View details →

Data from: Phenotypic biomarkers of climatic impacts on declining insect populations: a key role for decadal drought, thermal buffering and amplification effects and host plant dynamics

1. Widespread population declines have been reported for diverse Mediterranean butterflies over the last three decades, and have been significantly associated to increased global change impacts. The specific landscape and climatic drivers of these declines remain uncertain for most declining species. 2. Here we analyse whether plastic phenotypic traits of a model butterfly species (Pieris napi) perform as reliable biomarkers of vulnerability to extreme temperature impacts in natural populations, showing contrasting trends in thermally exposed and thermally buffered populations. 3. We also examine whether improved descriptions of thermal exposure of insect populations can be achieved by combining multiple information sources (i.e. integrating measurements of habitat thermal buffering, habitat thermal amplification, host plant transpiration, and experimental assessments of thermal death time (TDT), thermal avoidance behaviour (TAB) and thermally induced trait plasticity). These integrative analyses are conducted in two demographically declining and two non-declining populations of P. napi. 4. The results show that plastic phenotypic traits (butterfly body mass and wing size) are reliable biomarkers of population vulnerability to extreme thermal conditions. Butterfly wing size is strongly reduced only in thermally exposed populations during summer drought periods. Lab rearing of these populations documented reduced wing size due to significant negative effects of increased temperatures affecting larval growth. We conclude that these thermal biomarkers are indicative of the population vulnerability to increasing global warming impacts, showing contrasting trends in thermally exposed and buffered populations. 5. Thermal effects in host plant microsites significantly differ between populations, with stressful thermal conditions only effectively ameliorated in mid-elevation populations. In lowland populations we observe a six-fold reduction in vegetation thermal buffering effects, and larval growth occurs in these populations at significantly higher temperatures. Lowland populations show reduced host plant quality (C/N ratio), reduced leaf transpiration rates and complete aboveground plant senescence during the peak of summer drought. Amplified host plant temperatures are observed in open microsites, reaching thermal thresholds that can affect larval survival. 6. Overall, our results suggest that butterfly population vulnerability to long-term drought periods is associated to multiple co-occurring and interrelated ecological factors, including limited vegetation thermal buffering effects at lowland sites, significant drought impacts on host plant transpiration and amplified leaf surface temperature, as well as reduced leaf quality linked to the seasonal advance of plant phenology. Our results also identify multi-annual summer droughts affecting larval growing periods as a key driver of the recently reported butterfly population declines in the Mediterranean biome.

Age-Specific Mortality Climate Impact Distributions

Percentiles of age-specific mortality impacts due to climate change, organized by level of aggregation, climate scenario, and time period. Mortality impacts are estimated by applying future climate data to dose-response functions of mortality rates for specific age bands. The uncertainty represented by these percentiles comes from a combination of statistical uncertainty in the dose-response functions, climate uncertainty across GCMs, and within-month weather realization, as sampled by Monte Carlo runs. The archive contains four folders: county_20a with county-level impacts, state_20yr with state-aggregated impacts, nca_20yr with NCA-region aggregated impacts, and national_20y with nationally aggregated impacts.  Aggregation is weighted by population within each region The files are labeled as follow: health-mortage-<BAND>-<RCP>-<YEAR><SUFFIX>. The age BAND is one of 0-0 (newborns), ages 1 - 44, 45 - 64, and 65-inf (older than 64).  The RCP may be RCP 2.6, RCP 4.5, RCP 6.0, or RCP 8.5; the years are "2020", for average impacts during 2020 - 2039, "2040" for impacts 2040 - 2059, and "2080" for impacts 2080 - 2099.  Files with the suffix 'b.csv' contain percent changes; those with the suffix '-absolute.csv' contain level changes in MT. The columns of these files specify the region (using the FIPS code for counties), and the quantiles from 1% ("q0.01") to 99% ("q0.99"). This data is provided for non-commercial research and educational purposes.

Total Agriculture Climate Impact Distributions

Percentiles of agricultural impacts due to climate change, organized by level of aggregation, climate scenario, and time period. Agricultural impacts are estimated by applying future climate data to dose-response functions of yields for maize, wheat, cotton, and soybeans, and combining them according to land area.  The dose-response functions include the effects of moderate and extreme temperatures, precipitation, and CO2 fertilization. The uncertainty represented by these percentiles comes from a combination of statistical uncertainty in the dose-response functions, climate uncertainty across GCMs, and within-month weather realization, as sampled by Monte Carlo runs. The archive contains four folders: county_20a with county-level impacts, state_20yr with state-aggregated impacts, nca_20yr with NCA-region aggregated impacts, and national_20y with nationally aggregated impacts.  Aggregation is weighted by planted area within each region The files are labeled as follow: yields-total-<RCP>-<YEAR><SUFFIX>. The RCP may be RCP 2.6, RCP 4.5, RCP 6.0, or RCP 8.5; the years are "2020", for average impacts during 2020 - 2039, "2040" for impacts 2040 - 2059, and "2080" for impacts 2080 - 2099.  Files with the suffix 'b.csv' contain percent changes; those with the suffix '-absolute.csv' contain level changes in MT. The columns of these files specify the region (using the FIPS code for counties), and the quantiles from 1% ("q0.01") to 99% ("q0.99"). This data is provided for non-commercial research and educational purposes.

Labor Productivity Climate Impact Distributions

Percentiles of labor productivity impacts due to climate change, organized by level of aggregation, climate scenario, and time period. Labor productivity impacts are estimated by applying future climate data to dose-response functions of absenteeism for low and high-sensitivity sectors. The uncertainty represented by these percentiles comes from a combination of statistical uncertainty in the dose-response functions, climate uncertainty across GCMs, and within-month weather realization, as sampled by Monte Carlo runs. The archive contains four folders: county_20a with county-level impacts, state_20yr with state-aggregated impacts, nca_20yr with NCA-region aggregated impacts, and national_20y with nationally aggregated impacts.  Aggregation is weighted by jobs within each region. The files are labeled as follow: labor-<SENSITIVITY>-<RCP>-<YEAR><SUFFIX>. The SENSITIVITY can be high, for outdoor jobs, or low for indoor tasks.  The RCP may be RCP 2.6, RCP 4.5, RCP 6.0, or RCP 8.5; the years are "2020", for average impacts during 2020 - 2039, "2040" for impacts 2040 - 2059, and "2080" for impacts 2080 - 2099.  Files with the suffix 'b.csv' contain percent changes; those with the suffix '-absolute.csv' contain level changes in MT. The columns of these files specify the region (using the FIPS code for counties), and the quantiles from 1% ("q0.01") to 99% ("q0.99"). This data is provided for non-commercial research and educational purposes.

Distributions of Uncertainty by Climate Impact

These summary tables describe the distributions of results produced by allowing only one of statistical, model, and weather uncertainty to vary, to determine the contributions of each. These files are extracted from the general ACP Monte Carlo results using scripts from https://github.com/ClimateImpactLab/acp-impacts/tree/master/extract as defined below: The contents of variation-split are produced by uncertain.py.  These results are organized into files with the filename template <VARIATION>-<IMPACT>--<RCP>-<YEAR>.csv.  VARIATION may be "impact", for the variation driven by statistical uncertainty; "model", for the uncertainty driven by GCM choice; "weather", for the variation driven by weather realization; or "total", allowing all of these to vary simultaneously.  IMPACT may be any of the estimated impacts, RCP can be RCP 2.6, RCP 4.5, RCP 6.0, or RCP 8.5, and YEAR is 2020, for an average from 2020 - 2039; 2040 for an average of 2040 - 2059; or 2080 for an average of 2080 - 2099. The contents of baseline-testing are produced by uncertain-test.py.  These results are organized into files with the filename template <IMPACT>-<VARIATION>-<GCM>-<RCP>-<YEAR>.csv.  The filename parts are as described above, with the addition of the name of the GCM that is held fixed when the GCM is not allowed to change. variation-split.tsv is produced by calcvar.py and is a summary of the results in variation-split/. baseline-testing.tsv is produced by calcvar-test.py and is a summary of the results in baseline-testing/. This data is provided for non-commercial research and educational purposes.

All-Age Mortality Climate Impact Distributions

Percentiles of all-age mortality impacts due to climate change, organized by level of aggregation, climate scenario, and time period. Mortality impacts are estimated by applying future climate data to dose-response functions of mortality rates. The uncertainty represented by these percentiles comes from a combination of statistical uncertainty in the dose-response functions, climate uncertainty across GCMs, and within-month weather realization, as sampled by Monte Carlo runs. The archive contains four folders: county_20a with county-level impacts, state_20yr with state-aggregated impacts, nca_20yr with NCA-region aggregated impacts, and national_20y with nationally aggregated impacts.  Aggregation is weighted by population within each region The files are labeled as follow: health-mortality-<RCP>-<YEAR><SUFFIX>. The RCP may be RCP 2.6, RCP 4.5, RCP 6.0, or RCP 8.5; the years are "2020", for average impacts during 2020 - 2039, "2040" for impacts 2040 - 2059, and "2080" for impacts 2080 - 2099.  Files with the suffix 'b.csv' contain percent changes; those with the suffix '-absolute.csv' contain level changes in MT. The columns of these files specify the region (using the FIPS code for counties), and the quantiles from 1% ("q0.01") to 99% ("q0.99"). This data is provided for non-commercial research and educational purposes.

Crime Climate Impact Distributions

Percentiles of crime impacts due to climate change, organized by level of aggregation, climate scenario, and time period. Crime impacts are estimated by applying future climate data to dose-response functions of property and violent crime rates, aggregated by population levels. The uncertainty represented by these percentiles comes from a combination of statistical uncertainty in the dose-response functions, climate uncertainty across GCMs, and within-month weather realization, as sampled by Monte Carlo runs. The archive contains four folders: county_20a with county-level impacts, state_20yr with state-aggregated impacts, nca_20yr with NCA-region aggregated impacts, and national_20y with nationally aggregated impacts.  Aggregation is weighted by crimes within each region. The files are labeled as follow: crime-<TYPE>-<RCP>-<YEAR><SUFFIX>. The TYPE can be property or violent crime.  The RCP may be RCP 2.6, RCP 4.5, RCP 6.0, or RCP 8.5; the years are "2020", for average impacts during 2020 - 2039, "2040" for impacts 2040 - 2059, and "2080" for impacts 2080 - 2099.  Files with the suffix 'b.csv' contain percent changes; those with the suffix '-absolute.csv' contain level changes in MT. The columns of these files specify the region (using the FIPS code for counties), and the quantiles from 1% ("q0.01") to 99% ("q0.99"). This data is provided for non-commercial research and educational purposes.

openDec 2023View details →

Data accompanying Jonko et al. "How will future climate change impact prescribed fire across the contiguous United States?"

This CSV file contains prescription information for 83 location across the United States which was analyzed in the publication Jonko, A., J. Oliveto, T. Beaty, A. Atchley, M.A. Battaglia, M.B. Dickinson, M.R. Gallagher, A. Gilbert, D. Godwin, J.A. Kupfer, J.K. Hiers, C. Hoffman, M. North, J. Restaino, C. Sieg, and N. Skowronski: "How will future climate change impact prescribed fire across the contiguous Unites States?", submitted to npj Climate and Atmospheric Science. Please contact the corresponding author at ajonko@lanl.gov if you are interested in using this data in your own research.

opencdla-permissive-1.0Dec 2023View details →

Supplementary files for Impact of climate change on leafhopper vectors of phytoplasmas in North America

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opencc-by-4.0Dec 2023View details →

Distinct Impacts of the Central and Eastern Atlantic Niño on the European Climate

Forcing and Output data of Linear Baroclinic Model (LBM).

opencc-by-4.0Jan 2024View details →

Literature review results for "Climate and land use change impacts on island ecosystem services"

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