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116 results for “climate risk”
Water risks to hydropower projects in the face of climate change
<p>This repository hosts the main outputs from an analysis using the <a href="https://waterriskfilter.org/">WWF Water Risk Filter</a> to demonstrate how one such tool can be used to screen for a variety of risks at a global scale, including risks to riverine ecosystems from both climate change and hydropower as well as risks to hydropower projects — and operators, owners, and investors — from climate change and potential regulatory or reputational risk arising from negative impacts to ecosystems. The study <a href="https://www.mdpi.com/2073-4441/14/5/721">Using the WWF Water Risk Filter to Screen Existing and Projected Hydropower Projects for Climate and Biodiversity Risks (DOI 10.3390/w14050721) </a>was published in the special issue of the MDPI journal Water: <a href="https://www.mdpi.com/journal/water/special_issues/hydrometeorological_hazards">"Hydro-Meteorological Hazards under Climate Change"</a>.</p> <p>This product incorporates data from the GRanD v1.3 database which is © Global Water System Project (2011), and from the FHReD database beta version, both datasets available at <a href="http://globaldamwatch.org/">globaldamwatch.org</a> . The source code used in this study is available at <a href="https://github.com/rafaexx/hydropowerClimateChange">https://github.com/rafaexx/hydropowerClimateChange</a></p> <p>See the interactive maps using this data at <a href="https://rcamargo.shinyapps.io/HydropowerClimateChange">https://rcamargo.shinyapps.io/HydropowerClimateChange</a></p>
RICCH: An Interactive Analysis Tool for Risk and Impacts of Climate Change on Hydropower Database
<p>The "RICCH: An Interactive Analysis Tool for Risk and Impacts of Climate Change on Hydropower" Database, referred to as the RICCH Database, includes a "Hydropower Plants Database" and the incorporation of future hydropower usable capacity for 542 hydropower plants in the Global South. The "Hydropower Plants Database" includes the main design and location characteristics of 542 hydropower plants across 52 countries. Additionally, we incorporate the results of future usable capacity simulations using a multi-model ensemble of 21 Global Climate Models (GCMs) and two representative concentration pathways (RCPs). We use a multi-model ensemble of 21 GCMs from NASA's NEX GDDP dataset RCP 4.5 and RCP 8.5. We aggregate the mean monthly usable capacity (MW) for each model and scenario, for the early century (2010-2039), mid-century (2040-2069), and the end-of-the-century (2070-2099). We include these results for every power plant in the RICCH database. </p> <p><em>Example: Itaipu (power plant in Brazil) has a record for its simulated mean monthly usable capacity for January (1) in the early century (2010-2039), under GCM ACCESS1_0 and RCP 4.5.</em></p>
Data and code for 'Age structure of amphibian populations with endemic chytridiomycosis, across climatic regions with markedly different infection risk'
<p>This repository provides all data and R code from the analysis presented in the following paper:</p> <p>Turner, A., Heard, G., Hall, A., Wassens, S. (in review). Age structure of amphibian populations with endemic chytridiomycosis, across climatic regions with markedly different infection risk.</p> <p>The data are provided as a series of .csv files, R script and two zip folders of R packages (Surv_mod and VB_mod)</p> <p>1. <strong>Skeleto_dat_ready_Jan2021.csv</strong> Data from frog surveys conducted by Anna Turner</p> <p>2. <strong>Geoffs_data.csv</strong> Data from frog surveys conducted by Geoff Heard</p> <p>3. <strong>Environmental_variables_skeleto.csv</strong> Environmental data collected during surveys </p> <p>4. <strong>sk.dat_July21.csv</strong> Collated data from Anna and Geoff - created by 'Data_collation_for_analysis_2.R' ready for analysis</p> <p>5. <strong>Variables_that_are_highly_correlated_with_each_other_season_wide.csv</strong> Testing for correlation</p> <p>6. <strong>Model_structure_skeleto_2.csv </strong>creates model structure for analysis</p> <p>7. <strong>Model_selection_statistics_June_21.csv </strong>Output from model</p> <p>R code is provided seperately for each of the following components:</p> <p>1. <strong>Data_collation_for_analysis_2.R</strong> Collating data from Anna and Geoffs datasets</p> <p>2. <strong>Skeleto_analysis_5.R - </strong>First uses regression modelling to explore factors correlated with variation in age</p> <p> - Following Scheele et al. (2016) regression models with a poisson distribution</p> <p> - Use bayesian non-linear regression to fit the Von Bertalanffy growth model to size-at-age data</p> <p> - Plots male and female growth curves</p> <p> - Uses catch curve approach to estimate survival from best fitting regression model following Scroggie (2012) but with bayesian implementation</p>
Tree mortality risks under climate change in Europe: assessment of silviculture practices and genetic conservation networks
<p>General context: Climate change can positively or negatively affect abiotic and biotic drivers of tree mortality. Process-based models integrating these climatic effects are only seldom used at species distribution scale.</p> <p>Objective: The main objective of this study was to investigate the multi-causal mortality risk of five major European forest tree species across their distribution range from an ecophysiological perspective, to quantify the impact of forest management practices on this risk and to identify threats on the genetic conservation network.</p> <p><br> Methods: We used the process-based ecophysiological model CASTANEA to simulate the mortality risk of \textit{Fagus sylvatica}, \textit{Quercus petraea}, \textit{Pinus sylvestris}, \textit{Pinus pinaster} and \textit{Picea abies} under current and future climate conditions, while considering local silviculture practices. The mortality risk was assessed by a composite risk index \textit{(CRIM)} integrating the risks of carbon starvation, hydraulic failure and frost damage. We took into account extreme climatic events with the \textit{CRIM$_{max}$}, computed as the maximum annual value of the \textit{CRIM}.</p> <p><br> Results: The physiological processes' contributions to \textit{CRIM} differed among species: it was mainly driven by hydraulic failure for \textit{P. sylvestris} and \textit{Q. petraea}, by frost damage for \textit{P. abies}, by carbon starvation for \textit{P. pinaster}, and by a combination of hydraulic failure and frost damage for \textit{F. sylvatica}. Under future climate, projection showed an increase of \textit{CRIM} for \textit{P. pinaster} but a decrease for \textit{P. abies}, \textit{Q. petraea} and \textit{F. sylvatica}, and little variation for \textit{P. sylvestris}. Under the harshest future climatic scenario, forest management decreased the mean \textit{CRIM} for \textit{P. sylvestris}, increased it for \textit{P. abies} and \textit{P. pinaster} and had no major impact for the two broadleaved species. By the year 2100, 38\% to 90\% of the conservation units are at extinction threat (\textit{CRIM$_{max}$}=1), depending on the species.</p> <p><br> Conclusions: Using a process-based ecophysiological model allowed us to disentangle the multiple drivers of tree mortality under current and future climate. Taking into account the positive effect of increased CO$_2$ on fertilization and water use efficiency, the average risks may increase or decrease in the future depending on species and sites. However, considering extreme climatic events, future projections are as pessimistic than those obtained with bioclimatic niche models.</p> <p> </p> <p>Abbreviation for column:</p> <p>X Longitude<br> Y Latitude<br> LAImax Leaf area index max reach<br> Nha Density per hectar<br> Vha Volume per hectar<br> NEE Net ecosystem exchange<br> NPP net primary production<br> Reco Respiration ecosystem<br> GPP Gross primary production<br> Etveg Evapotranspiration canopy<br> Etsol Evapotranspiration sol<br> TR tree transpiration<br> ETP evapotranspiration potentiel<br> BiomassOfReserves Biomass of reserve<br> rw ring width<br> dbh diameter at breast heast<br> height height<br> BBday Budburst date<br> rFD risk of frost<br> CRIM_max Maximum combined risk index of mortality reach<br> rNSC risk of carbon starvation<br> rPLC risk of embolism<br> rPLC_max Maximum risk of embolism reach<br> CRIM combined risk index of mortality<br> Climate Climatic model<br> rNSC_max maximum risk of carbon starvation reach<br> rFD_max Maximum risk of frost reach<br> Scenario_Sylvicol null means no silvulcture simulated<br> species species<br> Country Country<br> alt_watch altitude of climate simulated<br> grid_watch number of the pixel point of WATCH<br> grid_eurocordex number of the pixel point of Eurocordex<br> Pinus_sylvestris 0 abscence ; 1 presence<br> Fagus_sylvatica 0 abscence ; 1 presence<br> Quercus_petraea 0 abscence ; 1 presence<br> Picea_abies 0 abscence ; 1 presence<br> Pinus_pinaster 0 abscence ; 1 presence</p> <p> </p>
Data from: Complex climate-mediated effects of urbanization on plant reproductive phenology and frost risk
<p>This dataset comprises crowdsourced data using digitized herbarium specimen images from two comprehensively digitized regional floras; the Consortium of Northeastern Herbaria (CNH; <a href="http://portal.neherbaria.org/portal/">http://portal.neherbaria.org/portal/</a>) and Southeast Regional Network of Expertise and Collections (SERNEC; <a href="http://sernecportal.org/portal/index.php">http://sernecportal.org/portal/index.php</a>) for 200 plant species in the eastern United States, and four reproductive phenophases (i.e., flowering, peak flowering, fruiting, and peak fruiting) extracted from the herbarium specimens with associated climate data from PRISM and human population density from US Census Bureau.</p>
Climate Change Risk Assessment Dataset for Serbian Agriculture
<p>This dataset contains the assessment of observed climate change to the agriculture in Serbia. Data are given on a lat/lon gird with 0.01° horizontal resolution in geotif format. Climatic and bioclimatic indices, as well as risk occurrence frequencies are calculated using interpolated daily observations of temperature and precipitation over Serbia in the period 1998-2017. Statistical significance of the climate indices change, change in category of viticultural indices and increase in risk occurrence is given as well. Analyzed species are: vine grape, fruits (peaches, apricots, cherries, plums, apples, pears and quinces) and crops (corn, sunflower, sugar beet and winter wheat). Calculated climatic indices are: mean annual, vegetational and summer temperature and precipitation; bioclimatic indices: Winkler index, Huglin index, Dryness index, and Cool nights index; risks: drought, frost in the beginning of vegetation, low temeperature during winter, high temperature during summer and intensive rainfall.</p>
A global flood risk modeling framework built with climate models and machine learning - Submission - Data Supplement
<p>This contribution contains data, fitted statistical models, and an analysis script for the submitted manuscript "A global flood risk modeling framework built with climate models and machine learning" by David A. Carozza and Mathieu Boudreault.</p>
Climate-driven thermal opportunities and risks for leaf miners in aspen canopies
In tree canopies, incoming solar radiation interacts with leaves and branches to generate temperature differences within and among leaves, presenting thermal opportunities and risks for leaf-dwelling ectotherms. Although leaf biophysics and insect thermal ecology are well understood, few studies have examined them together in single systems. We examined temperature variability in aspen canopies, Populus tremuloides, and its consequences for a common herbivore, the leaf-mining caterpillar Phyllocnistis populiella. We shaded leaves in the field and measured effects on leaf temperature and larval growth and survival. We also estimated larval thermal performance curves for feeding and growth and measured upper lethal temperatures. Sunlit leaves directly facing the incoming rays reached the highest temperatures, typically 3 – 8 °C above ambient air temperature. Irradiance driven increases in temperatures, however, were transient enough that they did not alter observed growth rates of leaf miners. Incubator and ramping experiments suggested that larval performance peaks between 25 and 32 °C and declines to zero between 35 and 40 °C, depending on duration of temperature exposure. Upper lethal temperatures during one-hour heat shocks were 42 – 43 °C. When larvae were active in early spring, temperatures generally were low enough to depress rates of feeding and growth below their maxima, and only rarely did estimated mine temperatures rise beyond optimal temperatures. Observed leaf or mine temperatures never approached larval upper lethal temperatures. At this site during our experiments, larvae thus appeared to have a significant thermal safety margin; the more pressing problem was inadequate heat. Detailed information on mine temperatures and larval performance curves, however, allowed us to leverage long-term data sets on air temperature to estimate potential future shifts in performance and longer-term risks to larvae from lethally high temperatures. This analysis suggests that, in the past 20 years, larval performance has often been limited by cold and that the risk of heat stress has been low. Future warming will raise mean rates of feeding and growth but also the risk of exposure to injuriously or lethally high temperatures.
Risk Assessment of Extreme Precipitation on to Low- and Medium-Voltage Electrical Infrastructure Under the Influence of Climate Change
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Mediterranean risk assessment data based on the concurrency between climate change, fisheries, stocks, and biodiversity
<p>Data associated to the paper "Detecting Ecosystem Risk Hotspots: A Mediterranean Case Study" by G. Coro, L. Pavirani, A. Ellenbroek.</p>
Supplements to "Digital traces of climate risks: assessing the communication impact of Paris resilience strategy".
<p>These supplements correspond the data used in the PhD thesis : “Digital traces of climate risks: assessing the impact of Paris resilience strategy”, published in 2019 on <a href="http://theses.fr/">theses.fr</a> by Rosa Vicari (HM&Co - École des Ponts ParisTech), under the supervision of Daniel Schertzer (HM&Co - École des Ponts ParisTech).</p> <p>More precisely the data set corresponds to the corpora and term lists that are used in the analysis (based on advanced text mining and graph representation) of press articles and tweets concerning flood events in France and strategic documents released by public authorities.</p> <p>The dataset includes the following files:</p> <p>- Suppl2-2016Parisflood-termlist.csv : the list of terms extracted from the corpus of press articles covering the 2016 Seine River flood.</p> <p>- Suppl6-Cotedazflood-termlist.csv: the list of terms extracted from the corpus of press articles covering the 2015 Côte-d'Azur flood.</p> <p>- Suppl7-Corpus-PA-Strategies.csv : the corpus of strategic documents released by public authorities to cope with flood risk in Paris.</p> <p>- Suppl8-Term-list-PA-Strategies.csv : the list of terms extracted from the corpus of strategic documents released by public authorities to cope with flood risk in Paris (2003 - 2017).</p> <p>The following files are not available and cannot be shared for copyright reasons:</p> <p>- Suppl1-2016Parisflood-corpus.csv : the corpus of press articles covering the 2016 Seine River flood.</p> <p>- Suppl3-2018Parisflood-corpus.csv : the corpus of press articles covering the 2018 Seine River flood.</p> <p>- Suppl5-Cotedazflood-corpus.csv : the corpus of press articles covering the 2015 Côte-d'Azur flood.</p> <p>The following file is not available and cannot be shared for privacy reasons:</p> <p>- Suppl4 - Tweet corpus - 2016 Paris flood.csv : the corpus of tweets covering the 2016 Seine River flood.</p>
Figure 2 in Pets or predators? climate change and invasion risk of red-eared slider (Trachemys scripta elgans)
Figure 2. PCA-env for native and Indian climate for Trachemys scripta elegans. A) The green polygon represents nice unfilling, the blue polygon represents niche overlap, and the red polygon denotes nice expansion. The arrow indicates the niche centroid change. B) The correlation circle shows the relative contribution of different variables. C) and D) represent niche similarity and equivalency.
Figure 1 in Pets or predators? climate change and invasion risk of red-eared slider (Trachemys scripta elgans)
Figure 1. Predicted potential distribution of Trachemys scripta elegans under current and two future climate change scenarios.
Figure 3 in Pets or predators? climate change and invasion risk of red-eared slider (Trachemys scripta elgans)
Figure 3. Map showing species richness of native freshwater turtles at the sub-basin level in India.
Nuclear Power Generation Phaseouts Redistribute U.S. Air Quality and Climate Related Mortality Risk, Data
<p>This dataset accompanies the publication, "Nuclear Power Generation Phaseouts Redistribute U.S. Air Quality and Climate Related Mortality Risk", and can be used with the code located at https://zenodo.org/badge/latestdoi/248010532 to reproduce our results.</p>
Data and code to next-generation ensemble projections reveal higher climate risks for marine ecosystems
<p>Data products: <strong>Tittensor et al. (2021). Next-generation ensemble projections reveal higher climate risks for marine ecosystems, Nature Climate Change. DOI: <a href="https://doi.org/10.1038/s41558-021-01173-9">https://doi.org/10.1038/s41558-021-01173-9</a> </strong></p> <p>This data was produced using R scripts available on the GitHub repository <a href="https://github.com/Fish-MIP/CMIP5vsCMIP6">https://github.com/Fish-MIP/CMIP5vsCMIP6</a>, and was used for analysis and plotting in Tittensor et al. (2021). These R scripts are also available here as CMIP5vsCMIP6_code.zip </p> <p>Data_CMIP5.Rdata and Data_CMIP6.RData include all data used to produce global maps of percentage change in total consumer biomass. </p> <p>Data_trends_CMIP5.Rdata and Data_trends_CMIP6.RData include all data used to produce temporal trends of percentage change in total consumer biomass. </p> <p>Data_inputs_CMIP5.Rdata and Data_trends_CMIP6.RData include all data used to produce global maps of percentage change in phytoplankton biomass, zooplankton biomass, net primary production and sea surface temperature. </p> <p>Data_trends_inputs_CMIP5.Rdata and Data_trends_CMIP6.RData include all data used to produce temporal trends of percentage change in phytoplankton biomass, zooplankton biomass, net primary production and sea surface temperature.</p> <p>The suffix _reducedModelSet refers to the case when only the subset of Fish-MIP models in Lotze et al. (2019) - Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change, PNAS, DOI: https://doi.org/10.1073/pnas.1900194116 - are considered. This data was used to produce some of the supplementary figures in Tittensor et al. (2021).</p> <p>Please contact Derek Tittensor (derek.tittensor@dal.ca), Camilla Novaglio (camilla.novaglio@gmail.com), or Julia Blanchard (julia.blanchard@utas.edu.au) for data interpretation and use. </p>
Extreme Climate Risks and Financial Tipping Points
<p>This repository contains the data and the source code for the simulations and figures of the article.</p> <p><strong>Abstract</strong></p> <p>Designing climate change policies requires considering the feedback loops between mitigation and adaptation, since more mitigation efforts today will trigger lower adaptation costs. In this framework, carbon taxes are often seen as promising tools but at the risk of financially overburdening the private sector, depriving it of important economic resources. However, analyzing the financial feasibility of mitigation-adaptation policies using conventional Integrated Assessment Models (IAM) is limited, as they do not simultaneously endogenize economic growth, emissions, and damages.</p> <p>Here, we present IDEE (Integrated Dynamic Environment-Economic), a new IAM based on the coupling of an Earth Model of Intermediate Complexity and a non-linear macroeconomic model in continuous time. Then, we analyze the simultaneous effects of carbon taxes and public spending, both on climate and on the world economy. We show that, above a warming about +2.3°C, damages drastically foster the need for additional investments in productive capital—an adaptation necessity—that potentially leads private firms to a debt overhang and a worldwide cascade of defaults. This suggests that the Paris Agreement target should not only be motivated by the climatic non-linearities and tipping points arising beyond the +2°C threshold, but also by the emergence of financial tipping points. We also show that, provided public subsidies are high enough, a tax of usd 300 per tCO<sub>2</sub>e by 2030 enables reaching net-zero emissions in 2050, preventing firms from suffering global bankruptcy.</p> <p>We anticipate IDEE to be a starting point for a new class of IAMs that better represent the reciprocal feedback loops between the environment and the economy.</p>
Climate change is an important predictor of extinction risk on macroevolutionary timescales
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Climate-driven thermal opportunities and risks for leaf miners in aspen canopies
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Range-wide climate risk and adaptive potential in an iconic cold-water species (Part 2/2)
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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.