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151 results for “extreme events”
Increased frequency of extreme precipitation events in the North Atlantic during the PETM: Observations and theory
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Data from: Tackling extremes: challenges for ecological and evolutionary research on extreme climatic events
1. Extreme climatic events (ECEs) are predicted to become more frequent as the climate changes. A rapidly increasing number of studies - though few on animals - suggest that the biological consequences of ECEs can be severe. 2. However, ecological research on the impacts of extreme climatic events (ECEs) has been limited by a lack of cohesiveness and structure. ECEs are often poorly defined and have often been confusingly equated with climatic variability, making comparison between studies difficult. Additionally, a focus on short-term studies has provided us with little information on the long-term implications of ECEs, and the descriptive and anecdotal nature of many studies has meant it is still unclear what the key research questions are. 3. Synthesizing the current state of work is essential to identify ways to make progress. We conduct a synthesis of the literature and discuss conceptual and practical challenges faced by research on ECEs. 4. We consider three steps to advance research. First, we discuss the importance of choosing an ECE definition and identify the pros and cons of 'climatological' and 'biological' definitions of ECEs. Second, we advocate research beyond short-term descriptive studies to address questions concerning the long-term implications of ECEs, focussing on selective pressures and phenotypically plastic responses and how they might differ from responses to a changing climatic mean. Finally, we encourage a greater focus on multi-event studies that help us understand the implications of changing patterns of ECEs, through the combined use of modelling, experimental and observational field studies. 5. This paper aims to open a discussion on the definitions, questions and methods currently used to study ECEs, which will lead to a more cohesive approach to future ECE research.
Data from: Extreme climate events counteract the effects of climate and land-use changes in Alpine treelines
Climate change and extreme events, such as drought, threaten ecosystems world-wide and in particular mountain ecosystems, where species often live at their environmental tolerance limits. In the European Alps, plant communities are also influenced by land-use abandonment leading to woody encroachment of subalpine and alpine grasslands. In this study, we explored how the forest–grassland ecotone of Alpine tree lines will respond to gradual climate warming, drought events and land-use change in terms of forest expansion rates, taxonomic diversity and functional composition. We used a previously validated dynamic vegetation model, FATE-HD, parameterized for plant communities in the Ecrins National Park in the French Alps. Our results showed that intense drought counteracted the forest expansion at higher elevations driven by land-use abandonment and climate change, especially when combined with high drought frequency (occurring every 2 or less than 2 years). Furthermore, intense and frequent drought accelerated the rates of taxonomic change and resulted in overall higher taxonomic spatial heterogeneity of the ecotone than would be expected under gradual climate and land-use changes only. Synthesis and applications. The results from our model show that intense and frequent drought counteracts forest expansion driven by climate and land-use changes in the forest–grassland ecotone of Alpine tree lines. We argue that land-use planning must consider the effects of extreme events, such as drought, as well as climate and land-use changes, since extreme events might interfere with trends predicted under gradual climate warming and agricultural abandonment.
Extreme rainfall events and cooling of sea turtle clutches: implications in the face of climate warming
<p class="m-4193862355675860270msoplaintext">Understanding how climate change impacts species and ecosystems is integral to conservation. When studying impacts of climate change, warming temperatures are a research focus, with much less attention given to extreme weather events and their impacts. Here we show how localized, extreme rainfall events can have a major impact on a species that is endangered in many parts of its range. We report incubation temperatures from the world's largest green sea turtle rookery, during a breeding season when two extreme rainfall events occurred. Rainfall caused nest temperatures to drop suddenly and the maximum drop in temperature for each rain-induced cooling averaged 3.6°C (n = 79 nests, min = 1.0°C, max = 7.4°C). Since green sea turtles have temperature-dependent sex determination, with low incubation temperatures producing males, such major rainfall events may have a masculinization effect on primary sex ratios. Therefore, in some cases, extreme rainfall events may provide a "get-out-of-jail-free card" to avoid complete feminization of turtle populations as climate warming continues.</p>
Molecular food webs of bat-plant interactions during an extreme El Nino event
<p>Interaction network structure reflects the ecological mechanisms acting within biological communities, which are affected by environmental conditions. In tropical forests, higher precipitation usually increases fruit production, which may lead frugivores to increase specialization, resulting in more modular and less nested animal-plant networks. In these ecosystems, El Niño is a major driver of precipitation, however, we still lack knowledge of how species interactions change under this influence. To understand bat-plant network structure during an extreme ENSO event, we determined the links between frugivorous bat species and the plants they consume by DNA barcoding seeds and pulp in bat faeces. These interactions were recorded in the dry forest and rainforest of Costa Rica, during the dry and the wet seasons of an extreme El Niño year. From these we constructed seasonal and whole-year bat-plant networks and analyzed their structures and dissimilarities. In general, networks had low nestedness, high modularity, and were dominated by one large compartment which included most species and interactions. Contrary to our expectations, networks were less nested and more modular in drier conditions, both in the comparison between forest types and between seasons. We suggest that increased competition, when resources are scarce during drier seasons and habitats, lead to higher resource partitioning among bats and thus higher modularity. Moreover, we have found similar network structures between dry and rainforests during El Niño and non El Niño years. Finally, most interaction dissimilarity among networks occurred due to interaction rewiring among species, potentially driven by seasonal changes in resource availability.</p>
Data from: Early snowmelt by an extreme warm event affects understory more than overstory trees in Japanese temperate forests
<p><span>We conducted a warming experiment (four 20 m by 20 m plots) in temperate forests of Japan to determine the effects of earlier snowmelt on both understory dwarf bamboo plants and overstory birch trees. Our experimental treatment advanced snowmelt by about 10 days and increased soil temperatures that were associated with increased rates of soil nitrogen (N) mineralization and nitrification. Furthermore, these changes led to lower C:N ratios of leaves together with the greater growth of understory bamboo vegetation, with no changes in leaf C:N or growth rates of overstory birch trees. Together, our results demonstrate that advancing snowmelt by an extreme warm event in temperate forests is likely to affect N cycling and will benefit understory vegetation without a commensurate change in overstory vegetation, likely due to the increase in available soil N. </span>This is the dataset of plant growth, soil N properties, and plamnt leaf traits obtained by the field snowmelt manipulation experiment.</p>
Network Analysis to Identify Critical Links for Relief Activities During Extreme Weather Events
<p>As one of the principal lifeline systems, transportation networks are crucial for evacuation and delivering essential resources and services during the response and recovery phases of extreme weather events and must remain intact to enhance regional resiliency. The conventional evaluation measures that estimate the vulnerability or criticality of road network based on travel time or link volumes do not capture the community impacts due to disruptions. This study seeks to develop a framework to evaluate road network infrastructure criticality during extreme weather events by introducing measures that evaluate the vulnerability of roads users, rather than the physical aspects of link importance. The research develops an innovative approach that integrates three important concepts including hurricane evacuation behavior, community impacts, and road criticality to identify the critical links. Results show that the critical links for vulnerable populations during evacuation do not always align with conventional link-based measures. This highlights the importance of using a performance measure that takes the social vulnerability of road users into consideration when identifying the criticality of a road network and planning for fortification of links to avoid irreversible consequences for vulnerable population groups. Furthermore, decision-making that considers the risks to different communities may lead to a more effective distribution of resources and help support a timely and safe evacuation from disaster events by strengthening the preservation of critical infrastructure links.</p>
Supplementary material 3 from: Wübbelmann T, Bouwer LM, Förster K, Bender S, Burkhard B (2022) Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale. One Ecosystem 7: e87458. https://doi.org/10.3897/oneeco.7.e87458
Maps of the individual potential FRES demand indicators
Supplementary material 2 from: Wübbelmann T, Bouwer LM, Förster K, Bender S, Burkhard B (2022) Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale. One Ecosystem 7: e87458. https://doi.org/10.3897/oneeco.7.e87458
Table of the scaled Flood Regulating Ecosystem Services indicators and categories
Supplementary material 1 from: Wübbelmann T, Bouwer LM, Förster K, Bender S, Burkhard B (2022) Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale. One Ecosystem 7: e87458. https://doi.org/10.3897/oneeco.7.e87458
Ratio of FRES supply and flood hazard
Combining Virtual Reality and Machine Learning for Enhancing the Resiliency of Transportation Infrastructure in Extreme Events
<p>Corresponding data set for Tran-SET Project No. 18ITSLSU09. Abstract of the final report is stated below for reference:</p> <p>"Traffic management models that include route choice form the basis of traffic management systems. High-fidelity models that are based on rapidly evolving contextual conditions can have significant impact on smart and energy efficient transportation. Existing traffic/route choice models are generic and are calibrated on static contextual conditions. These models do not consider dynamic contextual conditions such as the location, failure of certain portions of the road network, the social network structure of population inhabiting the region, route choices made by other drivers, extreme conditions, etc. As a result, the model’s predictions are made at an aggregate level and for a fixed set of contextual factors. There is a clear need to develop traffic models that take into account local contexts and are closer to ground reality to provide government agencies the ability to make well-informed model-based decisions/policies.</p> <p>In this project: (1) used Immersive Virtual Environment (IVE) tools for generating context-aware and high-fidelity data related to drivers’ route choice behavior, (2) developed a novel approach for developing high-fidelity route choice models with increased predictive power by augmenting existing aggregate level baseline models with information on drivers' responses to contextual factors obtained from stated choice experiments carried out in an IVE through the use of knowledge distillation. To this end, the study used a virtual driving environment designed based on I-10 in Baton Rouge, LA. Five alternate routes were introduced to the participant. Ten experimental scenarios were conducted to produce initial data about drivers’ dynamic route choice behavior, given emerging contextual factors. Experimental results have demonstrated that the predictions of the augmented models produced by our approach are much closer to reality than that of the baseline. Our study demonstrates that existing route choice models based on econometric theories cannot accurately predict behavior in real world scenarios. For high-fidelity route choice models, one needs to combine existing route choice models with information about contextual factors gleaned from SCEs."</p>
Data for "Hydrodynamic and Geomorphological Responses of Tidal Flats to Extreme Climate Events with Implications for Coastal Managements"
<p>Data used for the plots can be found:</p> <p>1) <strong>uav_z.mat </strong>is used for producing figure 2 and 3.</p> <p>2) <strong>timeseries.mat </strong>is used for producing figure 5 and 6.</p>
Environmental data from: Potential distributions of invasive vertebrates in the Iberian Peninsula under projected changes in climate extreme events
<p>This dataset includes climatic variables representing extreme events indices defined by the World Meteorological Organization (<a href="https://public.wmo.int/en">https://public.wmo.int/en</a>). The variables were calculated based on five Regional Climate Models or RCMs (UAHE-REM, UCAN-WRA, UCAN-WRB, UCLM-PRO and UMUR-MM5) for the periods 1971-2000 ('current climate') and 2021-2050 ('future climate') under the SRES A1B Emissions Scenario. We used RCMs instead of global climate models (GCMs) because the latter have an overly coarse resolution compared to the spatial resolution of our species distribution data. Since RCMs downscale climate fields from GCMs, they provide information at fine (meso or micro) scales that are more accurate for studies of regional phenomena and for application to climate impact assessments. Climatic variables were calculated in collaboration with the Numerical Modelling Group for the Environment and Climate (MOMAC, <a href="https://www.uclm.es/grupos/momac">https://www.uclm.es/grupos/momac</a>) of the University of Castilla-La Mancha (UCLM).</p>
Codes and datasets associated with the paper "Simulating an extreme over-the-horizon optical propagation event over Lake Michigan using a coupled mesoscale modeling and ray tracing framework"
<p>Here, you will find some of the codes, images, and datasets utilized in the article: </p> <p>Basu (2017). "Simulating an extreme over-the-horizon optical propagation event over Lake Michigan using a coupled mesoscale modeling and ray tracing framework", Optical Engineering, 56(7), 071505 (https://doi.org/10.1117/1.OE.56.7.071505)</p> <p>WRF codes: namelist.wps, namelist.input, myoutfields.txt</p> <p>NCL codes: d02_terrain.ncl, wrf_SurfaceASTD_d02.ncl</p> <p>RADAR loop: KGRR.gif</p> <p>MATLAB codes: Plot_Buoy.m</p> <p>Note: buoy datasets are available publicly from https://www.ndbc.noaa.gov/ </p>
Identifying non-synergestic effect of temporal variations of margin and dependence between extremes on the projected risk of compound dry-hot events in Yellow River, China
<p>Site-based daily precipitation and temperature data in China</p>
Molecular food webs of bat-plant interactions during an extreme El Nino event
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Extreme rainfall events and cooling of sea turtle clutches: implications in the face of climate warming
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Data from: Extreme heat events and the vulnerability of endemic montane fishes to climate change
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Data from: Tackling extremes: challenges for ecological and evolutionary research on extreme climatic events
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Environmental data from: Potential distributions of invasive vertebrates in the Iberian Peninsula under projected changes in climate extreme events
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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.