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387 results for “Climatic Adaptation”
Agriculture is adapting to phenological shifts caused by climate change, but grassland songbirds are not
<p>Migratory birds time their migration based on cues that signal resource availability for reproduction. However, with climate change, the timing of seasonal events may shift, potentially inhibiting the ability of some species to use them as accurate cues for migration. We studied the relationship between phenological shifts and reproduction by long- and short-distance migratory songbirds—Bobolinks (<i><span>Dolichonyx oryzivorus</span>) </i>and Savannah Sparrows (<i>Passerculus sandwichensis)</i>. Our study population breeds in hayfields and pastures in Vermont, USA, where farmers are also changing management activities in response to climate change. From 2002-2019 we monitored nest initiation dates to quantify correlations with environmental factors and the timing of nest initiation. We collected historical and projected precipitation and temperature data for the breeding grounds, and their respective wintering and stopover sites, the North Atlantic Oscillation (NAO) and the El Niño Southern Oscillation (ENSO). We predicted that winter conditions experienced by the short-distance migrant, the Savannah Sparrow, but not the long-distance migrant, the Bobolink, would explain the timing and success of nesting, however that this timing would be misaligned with changes in agricultural practices by hay farmers. Nest initiation dates did not show significant directional change for either species, but did vary among years. Interannual variation in Savannah Sparrow nest initiation dates was best explained by the interaction between precipitation on the breeding grounds and average wintering site (Wilmington, North Carolina). For Bobolinks, interannual variation in nest initiation dates was best explained by the interaction between breeding ground precipitation and average temperature in their fall stopover site (Barquisimieto, Venezuela). However, first haying dates in Vermont advanced by ~10 days over 18 years. These results suggest that the conflict between the timing of hay harvests and grassland songbird reproduction will increase, further threatening population processes for these species, as early harvests notably decrease annual productivity.</p>
Data: Reduced climate adaptation at range edges in North American Arabidopsis lyrata
<p><strong><span>Aim</span></strong><span>: Species' range limits, when not caused by dispersal limitation, are the result of constraints to the evolution of the ecological niche such that further range expansion is slow or not possible. An important evolutionary constraint at range edges may be the enhanced action of genetic drift. Here we tested whether a history of small population size and enhanced genetic drift was linked with reduced adaptation at range limits.</span></p> <p><strong><span>Location</span></strong><span>: Eastern North America</span></p> <p><strong><span>Time period</span></strong><span>: 2017-2019</span></p> <p><strong><span>Taxon</span></strong><span>: <em>Arabidopsis lyrata</em> subsp. <em>lyrata</em></span></p> <p><strong><span>Methods</span></strong><span>: We performed a latitudinal transplant experiment with sites </span><span>across and beyond the species distribution of North American <em>Arabidopsis lyrata</em>. Plants originated from the centre and the periphery, and the latter shared a history of range expansion or long-term isolation and had low genetic diversity. We tested for adaptation by considering climatic variables that had previously been associated with both niche and range limits. </span></p> <p><strong><span>Results</span></strong><span>: M</span><span>ultiplicative performance of plants was lower the more different the temperature regime at the transplant sites compared to home sites was, supporting climate adaptation. However, populations performed worse only when conditions were warmer at the transplant sites and better when conditions were colder, indicating that despite divergent adaptation to climate, the species seems to prefer living in cooler areas than where it is found currently. Finally, populations with low genetic diversity had a lower performance under a climate similar to that of their home sites, and performance declined stronger under warmer conditions. </span></p> <p><strong><span>Main conclusions</span></strong><span>: Our study supports that genetic drift reduces adaptation at species' range limits, and that populations with a history of genetic drift are especially vulnerable under global warming.</span></p>
MAgPIE model runs outputs: Climate change-driven global land-use system adaptation under CMIP6-based crop model projections
<p>Each folder contains the fulldata.gdx and the configuration files for each MAgPIE run based on the nine crop impact models and 5 gcms used in the paper.</p>
Data from Climate adaptability in hydrological models: variable storage capacity to improve performance under contrasting climates.
Open the record for dataset details and reuse information.
Data from: Forest management adaptation to climate change: a Cornelian dilemma between drought resistance and soil macro-detritivore functional diversity
1. Global warming induces new constraints on forest ecosystems and requires forest management adaptation. The reduction in stand density is currently debated as a potential tool to face increasing summer drought risk by improving forest resistance to climate change-induced tree mortality. However, few studies have yet assessed the impacts of this management change on soil biodiversity. 2. We conducted a large-scale, multi-site assessment of the response of soil macro-detritivore assemblages and soil functioning to experimental manipulations of stand density. A total of 33 stands were studied covering a wide gradient of stand density, that is stand basal area from 2·5 to 43·7 m2 ha−1, stand age, that is 18–171 years old, and local abiotic context. 3. We observed contrasting responses as a function of both taxonomic and functional groupings. Exploratory analysis using causal diagrams, that is path analysis, highlights that these changes were mainly related to alterations in understorey vegetation, microclimatic and soil pH conditions. The response of soil macro-detritivore assemblages to stand density manipulation was consistent over the gradient of stand ages. 4. Among the litter-dwelling macro-detritivores, millipede abundance and diversity decreased with stand density reduction, while woodlice and epigeic earthworms were unaffected. Further, a shift in soil-dwelling earthworm community composition was observed in mull stands. Endogeic earthworm abundance showed a sharp increase with stand density reduction, which translated into an increase in soil respiration. In contrast, anecic earthworm abundance decreased and was strongly associated with a decline of the rate of forest floor turnover. 5. Synthesis and applications. Our study provides strong evidence that reductions of stand density will have substantial impacts on soil macro-detritivore assemblages and cascading effects on soil functioning, particularly in mull stands. Managing stand density of oak forests at an intermediate level, that is 25 m2 ha−1, appears to be best to optimize the trade-off between improving forest resistance to climate change and ensuring the conservation of functional diversity to preserve forest ecosystem functioning and stability.
Data for: Sex-specific ornament evolution is a consistent feature of climatic adaptation across space and time in dragonflies
<p><span>Adaptation to different climates fuels the origins and maintenance of biodiversity. Detailing how organisms optimize fitness for their local climate is therefore an essential goal in biology. Although we increasingly understand how survival-related traits evolve as organisms adapt to climatic conditions, it is unclear if organisms also optimize traits that coordinate </span><span><span>mating</span></span><span> between the sexes. Here, we show that dragonflies consistently adapt to warmer climates across space and time by evolving less male melanin ornamentation—a mating-related trait that also absorbs solar radiation and heats individuals above ambient temperatures. Continent-wide macroevolutionary analyses reveal that species inhabiting warmer climates evolve less male ornamentation. Community-science observations across ten species indicate that populations adapt to warmer parts of species' ranges </span><span><span>through microevolution of</span></span><span> smaller male ornaments. Observations from 2005-2019 detail that contemporary selective pressures oppose male ornaments in warmer years; and our climate-warming projections predict further decreases by 2070. Conversely, our analyses show that female ornamentation responds idiosyncratically to temperature across space and time, indicating the sexes evolve in different ways to meet the demands of the local climate. Overall, these macro- and microevolutionary findings demonstrate that organisms predictably optimize their mating-related traits for the climate just as they do their survival-related traits.</span></p>
Replication package for Seawalls and Stilts: A Quantitative Macro Study of Climate Adaptation
<p>This replication package contains the data sets and code necessary to reproduce the results in Fried, Stephie. "Seawalls and Stilts: A Quantitative Macro Study of Climate Adaptation." accepted for publication at the Review of Economic Studies. </p> <p> </p>
Data for: Coral adaptive capacity insufficient to halt global transition of coral reefs into net erosion under climate change
<p>Projecting the effects of climate change on net reef calcium carbonate production is critical to understanding the future impacts on ecosystem function, but prior estimates have not included corals' natural adaptive capacity to such change. Here we estimate how the ability of symbionts to evolve tolerance to heat stress, or for coral hosts to shuffle to favourable symbionts, and their combination, may influence responses to the combined impacts of ocean warming and acidification under three representative concentration pathway emissions scenarios (RCP2.6, RCP4.5, RCP8.5). We show that symbiont evolution and shuffling both individually and when combined favours persistent positive net reef calcium carbonate production. However, our projections of future net calcium carbonate production under climate change vary both spatially and by RCP. For example, 19–35% of modelled coral reefs are still projected to have net positive net calcium carbonate production by 2050 if symbionts can evolve increased thermal tolerance, depending on the RCP. Without <span>symbiont adaptive capacity,</span> the number of coral reefs with positive net calcium carbonate production drops to 9–13% by 2050. Accounting for both symbiont evolution and shuffling, we project median positive net calcium carbonate production of coral reefs will still occur under low greenhouse emissions (RCP2.6) in the Indian Ocean, and even under moderate emissions (RCP4.5) in the Pacific Ocean. However, adaptive capacity will be insufficient to halt the transition of coral reefs globally into erosion by 2050 under severe emissions scenarios (RCP8.5).</p>
Data for the manuscript: Enabling Climate Change Adaptation in Coastal Systems. A Systematic Literature Review
<p>This dataset includes the list of publications, framework and dataset used for the paper "Enabling Climate Change Adaptation in Coastal Systems. A Systematic Literature Review"</p>
Data for "Assessing Climate Change Impacts on Crop Yields and Exploring Adaptation Strategies in Northeast China"
<p>The data contains some of the data necessary for this paper. and partly simulation results<br> </p>
UrbAlytics - Remote Sensing tools for Urban Heat Island Assessment and Climate Change Adaptation through Nature-Based Solutions
<p>Urban Heat Island (UHI) is considered one of the significant problems posed to human beings due to the urbanization and industrialization of human civilization. The leading causes of UHI are the vast amounts of heat urban structures produce as they absorb and re-radiate solar radiation and anthropogenic heat sources. The issue mainly affects cities or metropolises with a vast population and a thriving economy. The problem will worsen significantly in the future due to the predicted three billion people living in urban areas worldwide. Due to the severity of the problem, accessing up-to-date information layers that can support city planners and decision-makers in the context of climate resilience is a demanding problem nowadays.</p> <p><strong>UrbAlytics</strong> is an experimental sub-project of the H2020-funded project <a href="https://ai4copernicus-project.eu/"><strong>AI4Copernicus</strong></a> that aims to bridge Artificial Intelligence with Earth Observations, producing information layers that can support city planners and decision-makers in the context of climate resilience and related challenges in urban areas. This research investigates, thanks to the joint expertise of the partners <a href="https://www.latitudo40.com/"><strong>Latitudo 40</strong></a> and <a href="https://www.landsrl.com/land-research-lab"><strong>LAND Research Lab®</strong></a>, the Urban Heat Island (UHI) effect, evaluating its impacts on cities, assessing Ecosystem Services provided by Blue and Green Infrastructures and proposing a set of Nature-Based Solutions (NBS) for climate adaptation and extreme heat mitigation. </p> <p><strong>The dataset</strong></p> <p>This dataset is the tool's output of a fully automated workflow realized during the project and tested for the cities of <strong>Milan</strong> and <strong>Naples</strong>, pilot users of the experiment. The choice of Milan and Naples allows for different readiness levels, data availability, and urban-climatic conditions.<br> For each city, the dataset contains the following layers for the analysis period 2018-2022.</p> <p><strong> HEATWAVE POTENTIAL RISK (HPR)</strong></p> <p>Risk Assessment mapping concerning extreme heat, considering the severity of the heat island phenomenons, the exposure of sensitive age groups and the vulnerability due to city morphology and surface materials. The risk assessment is the first step in defining a methodology that aims to assess the effectiveness of mitigation and adaptation strategies to climate extremes. It's a value in [0,1], where the higher the value higher the risk.</p> <p><strong> MICROCLIMATIC PERFORMANCE INDEX (MPI)</strong></p> <p>The role of vegetation in the city in abating the Heat Island effect has been widely demonstrated. In this context, deploying Urban Green Infrastructure is recognized as one of the most important strategies to mitigate UHI and promote a resilient city environment. The significance of the mitigation role of the Heat Island phenomenon that vegetation assumes makes it necessary to map Urban Green Infrastructure to estimate a cooling potential. Estimating the microclimatic performance of urban vegetation is crucial to plan adaptation and mitigation actions for the UHI effect. In this work, up-to-date Tree Cover Density and Land Cover maps have been produced using machine learning applied to Sentinel-2 satellite imagery. Those maps have been interpolated and combined, creating 20 Blue and Green Infrastructures classes. Each category's microclimatic performance score was attributed based on evapotranspiration potential, shading and albedo. The output is a map with integer values in [1, 20], where the lower the value higher the microclimatic performance. </p> <p><strong> PARK COOL ISLANDS (PCI)</strong></p> <p>Park Cool Islands layer identifies the most performing areas during extreme summer heatwaves, according to their size and relevant characteristics, providing reliable information to citizens and urban planners about the safest and coolest areas during extreme heatwaves. Since the green areas' type and composition can influence their cooling effects, we considered both the size and composition of urban parks to identify the most performing green areas in terms of the Park Cool Island effect. <strong> </strong>The layer distinguishes between major and minor Park Cool Islands. <em>Major PCI</em> includes areas covered by at least 50% of tree canopy coverage and bigger than 2 hectares with an estimated cooling distance of 300 m buffer<strong>. </strong><em>Minor PCI</em> includes green areas whose surface is between 1 and 2 hectares as well as those green areas bigger than 2 hectares but covered by less than 50% of tree canopy coverage, with an estimated cooling distance of 100 m buffer.</p> <p> </p> <p><strong>Contact Information</strong></p> <p>If you would like further information about the dataset or if you experience any issues downloading files, please contact us <a href="mailto:giovanni.giacco@latitudo40.com">giovanni.giacco@latitudo40.com</a>, <a href="mailto:giulia.castellazzi@landsrl.com">giulia.castellazzi@landsrl.com</a></p>
Adaptive response of Siberian roe deer (Capreolus pygargus) to climate and altitude in the temperate forests of South Korea
<p><span>Understanding climatic effect on wildlife is essential to prediction and management of climate change's impact on the ecosystem. The climatic effect can interact with other environmental factors. This study aimed to determine effects of climate and altitude on Siberian roe deer (<em>Capreolus</em> <em>pygargus</em>) activity in temperate forests of South Korea. We conducted camera trapping to investigate roe deer's activity level from spring to fall. Logistic regressions were used to determine effects of diel period, temperature, rain, and altitude on the activity level. A negative relationship was noted between temperature and the activity level due to thermoregulatory costs. Roe deer activity exhibited nocturnal and crepuscular patterns during summer and the other seasons, respectively, possibly due to heat stress in summer. In addition, the effect of temperature differed between high- and low-altitude areas. In low-altitude areas, temperature affected negatively the activity level throughout the study period. Conversely, in high-altitude areas, temperature affected activity levels only in summer and early fall. Lower temperatures in higher altitudes favoured roe deer activity, resulting in roe deer's preference towards higher altitude areas. However, roe deer's movement toward lower altitudes was observed in summer. Reduced heat stress by changing activity pattern allowed them to access lower altitude areas with greater resource availability during summer. This study revealed how roe deer activity varied across seasons and altitudes, considering the interactions among weather, microclimate and resource availability. It provides insight into how montane species adapt to various climatic conditions, and this could have important implications for wildlife management and conservation efforts.</span></p>
Adaptation of sea turtles to climate warming: will phenological responses be sufficient to counteract changes in reproductive output?
<p>README: Supplementary Information</p> <p> </p> <p>In this document, we list the supplementary material that supports our results and conclusions and we provide a description of what each file contains.</p> <p> </p> <p>Supplementary Tables</p> <p> </p> <p><strong>Supp. Info. Table S1: metadata</strong></p> <p>This file contains various information about the nesting sites studied, including their location and respective Regional Management Unit (RMU, as per Wallace, B. P., et al. 2010. "Regional management units for marine turtles: a novel framework for prioritizing conservation and research across multiple scales." PLoS One 5(12): e15465), the number of nesting seasons with nest count data and how monitoring is conducted, the number of temperature loggers deployed, their type and where they were placed in the clutch, hatchling measurements in terms of straight carapace length (SCL in mm), and whether data from the literature (incubation experiments at constant temperature) was available at the RMU level to estimate thermal tolerance curves (see the column labeled ‘hatching success lab. data for this RMU (literature)’) and sex ratio thermal reaction norms (see the column labeled ‘sex ratio lab. data for this RMU (literature)’).</p> <p>The file also summarizes the parameters used to reconstruct nest temperature following the method in Monsinjon, J. R., et al. (2019) "The climatic debt of loggerhead sea turtle populations in a warming world." Ecological Indicators 107: 105657: mean diel thermal amplitude in °C (daily maxima minus daily minima), average time of daily min. temperatures in decimal hours, average time of daily max. temperatures in decimal hours, number of days lagged with sea surface temperature (SST), number of days lagged with two-meter air temperature (T2M), GLM coefficient of the Intercept, GLM coefficient of the relationship with SST, GLM coefficient of the relationship with T2M, GLM coefficient of the relationship with the proportion of incubation time used to infer metabolic heating (MH), and standard deviation of the coefficients of the nests from the GLMM random effect used to estimate the thermal heterogeneity.</p> <p>IPCC regions from which predicted increases in air and sea temperatures were extracted are indicated along with the values extracted for the future changes in temperature (median). The settings selected to extract the warming scenarios from the online interface are given below:</p> <ul> <li>IPCC's atlas: https://interactive-atlas.ipcc.ch/regional-information</li> <li>Dataset = CMIP6 (Model projections)</li> <li>Variable = Mean temperature (T) and Sea Surface Temperature (SST) anomalies (change in deg C)</li> <li>Region set = WGI reference-regions (or Small islands for Tetiaroa, French Polynesia)</li> <li>Uncertainty = Advanced</li> <li>Baseline period = 1981-2010</li> <li>Future period = 2081-2100</li> <li>Season = Annual</li> <li>Scenario “Middle of the road” (SSP2-4.5): Approximately in line with the upper end of combined pledges under the Paris Agreement. The scenario “deviates mildly from a ‘no-additional climate-policy’ reference scenario, resulting in a best-estimate warming around 2.7°C by the end of the 21st century”.</li> </ul> <p>The remaining columns show the shift (number of days) in nesting phenology estimated for the IPCC regions according to seawater warming scenarios, and using either the mean or the extreme (max.) coefficient of the negative linear relationship between nesting dates and sea water temperature (using the literature data presented in <strong>Supp. Info. Table S6</strong>).</p> <p> </p> <p><strong>Supp. Info. Table S2: hatching success literature data</strong></p> <p>This file contains the literature data on hatching success from incubation experiments conducted at various constant temperatures. For each species, the Regional Management Unit (RMU) is specified.</p> <p> </p> <p><strong>Supp. Info. Table S3: mean temperature and hatching success</strong></p> <p>This file contains in-situ hatching success data and associated mean temperatures during the whole incubation period. Data are from the literature and the present study (refer to <strong>Supp. Info. Table S1</strong> for the 3-letter beach codes). Note that the nesting season is specified only for the present study.</p> <p> </p> <p><strong>Supp. Info. Table S4:</strong> <strong>sex ratio literature data</strong></p> <p>This file contains the literature data on sex ratio from incubation experiments conducted at various constant temperatures. For each species, the Regional Management Unit (RMU) is specified.</p> <p> </p> <p><strong>Supp. Info. Table S5: in situ hatching success</strong></p> <p>This file contains in-situ hatching success data measured at 19 of our 24 study sites encompassing the four species considered for this study: <em>Caretta caretta</em>, <em>Chelonia mydas</em>, <em>Eretmochelys imbricata</em>, and <em>Lepidochelys olivacea</em> (refer to <strong>Supp. Info Table S1</strong> for the 3-letter beach codes). When the number of eggs was not available, we calculated the number that hatched by multiplying the survival proportion by 100 and rounding the value. And we calculated the number of eggs that did not hatch by subtracting the number that hatched from 100.</p> <p> </p> <p><strong>Supp. Info. Table S6: phenological shifts</strong></p> <p>This file contains the literature data on the relationship between nesting dates and thermal environmental cues. The grey rows (*) indicate cases that were not considered because the study reported either non-significant relationships or positive relationships between the proxy for nesting phenology and the environmental cue (i.e., a delay of nesting dates with increasing temperatures instead of a shift earlier as assumed in the present study).</p> <p> </p> <p><strong>Supp. Info. Table S7: required phenological shifts earlier and later in the nesting season</strong></p> <p>This file contains the estimated required phenological shifts (number of days earlier or later in the season to stay within present-day conditions) and associated rates (number of days earlier or later per 1°C increase in sea surface temperature) that would be necessary to achieve required shifts. Rates were calculated by dividing the required shifts by projected increases in sea surface temperature at our sites (see <strong>Supp. Info. Table S1</strong>). Required shifts and rates were calculated for our indicators of incubation temperature (IT in column labels; phenological shifts required for the future median incubation temperature index to remain below the 75<sup>th</sup> percentile of current conditions), hatching success (HS in column labels; phenological shifts required for the future median hatching success index to remain above the 25<sup>th</sup> percentile of current conditions), and sex ratio (SR in column labels; phenological shifts required for the future median sex ratio index, in proportion of males, to remain above the 25<sup>th</sup> percentile of current conditions). NAs mean that no shift was found to remain within present-day conditions. Refer to <strong>Supp. Info Table S1</strong> for the 3-letter beach codes.</p> <p> </p> <p><strong>Supp. Info. Table S8: hatching success and sex ratio ranges per site</strong></p> <p>This file contains statistics (minimum, median, and maximum) on hatching success (HS in survival proportion) and sex ratio (SR in male proportion) for each study site, and the climate (SSP2-4.5) and phenology (no shift, mean shift, and max. shift) scenarios presented in the core manuscript. For each study site (see <strong>Supp. Info. Table S1</strong> for the 3-letter beach codes in the first column), ranges are calculated between 2007-2020 for the present conditions and between 2059-2100 for the future conditions.</p> <p> </p> <p>Supplementary Figures</p> <p> </p> <p><strong>Supp. Info. Figure S1: hatching success and sex ratio reaction norms</strong></p> <p>This figure shows the hatching success and sex ratio thermal reaction norms estimated using literature data at controlled incubation temperatures (see data in <strong>Supp. Info. Table S2</strong> and <strong>Supp. Info. Table S4</strong>) for the four species considered here: <em>Caretta caretta</em>, <em>Chelonia mydas</em>, <em>Eretmochelys imbricata</em>, and <em>Lepidochelys olivacea</em>. Points are observations and error bars are their confidence intervals. Continuous lines are estimated curves with shades of grey being the confidence intervals. Reaction norms were fitted using data at the species-level (black) and the RMU-level (red) when available.</p> <p> </p> <p><strong>Supp. Info. Figure S2: output examples in 2018-2020</strong></p> <p>This figure shows five successive panels for each study site. In the first panel, we show reconstructed nest temperature without metabolic heating under present (black) and future (SSP2-4.5 in red) scenarios. The blue line shows the estimated pattern of nesting activity assuming no change in phenology and the purple and pink ones corresponds to those assuming a maximum shift (i.e., -18.85 d.°C<sup>-1</sup>) and a mean shift (i.e., -6.86 d.°C<sup>-1</sup>), respectively, in nesting dates under the SSP2-4.5 warming scenario (see median values in <strong>Supp. Info. Table S1</strong>). The following panels show the outputs for hatching success and sex ratio under the present and SSP2-4.5 climate scenarios. Information on the study sites is shown in the title (species, location, 3-letter beach codes).</p> <p> </p> <p><strong>Supp. Info. Figure S3: required shift for incubation temperature</strong></p> <p>This figure shows the backward (earlier nesting) and forward (later nesting) phenological shifts required (vertical arrows) for the future median incubation temperature index (the black continuous line, with grey shaded areas representing the 25<sup>th</sup> and 75<sup>th</sup> percentiles) to remain below the 75<sup>th</sup> percentile of current conditions. The black rectangle represents the 25<sup>th</sup> and 75<sup>th</sup> percentiles of current conditions and the black point is the median. The red point shows the median of future conditions under the SSP2-4.5 warming scenario assuming no phenological shift, the blue point according to the mean phenological shift, and the green point according to the maximum phenological shift. Refer to <strong>Supp. Info. Table S1</strong> for the 3-letter beach codes.</p> <p> </p> <p><strong>Supp. Info. Figure S4: required shift for hatching success</strong></p> <p>This figure shows the backward (earlier nesting) and forward (later nesting) phenological shifts required (vertical arrows) for the future median hatching success index (the black continuous line, with grey shaded areas representing the 25<sup>th</sup> and 75<sup>th</sup> percentiles) to remain above the 25<sup>th</sup> percentile of current conditions. The black rectangle represents the 25<sup>th</sup> and 75<sup>th</sup> percentiles of current conditions and the black point is the median. The red point shows the median of future conditions under the SSP2-4.5 warming scenario assuming no phenological shift, the blue point according to the mean phenological shift, and the green point according to the maximum phenological shift. Refer to <strong>Supp. Info. Table S1</strong> for the 3-letter beach codes.</p> <p> </p> <p><strong>Supp. Info. Figure S5: required shift for sex ratio</strong></p> <p>This figure shows the backward (earlier nesting) and forward (later nesting) phenological shifts required (vertical arrows) for the future median sex ratio index, in proportion of males (the black continuous line, with grey shaded areas representing the 25<sup>th</sup> and 75<sup>th</sup> percentiles), to remain above the 25<sup>th</sup> percentile of current conditions. The black rectangle represents the 25<sup>th</sup> and 75<sup>th</sup> percentiles of current conditions and the black point is the median. The red point shows the median of future conditions under the SSP2-4.5 warming scenario assuming no phenological shift, the blue point according to the mean phenological shift, and the green point according to the maximum phenological shift. Refer to <strong>Supp. Info. Table S1</strong> for the 3-letter beach codes.</p> <p> </p> <p><strong>Supp. Info. Figure S6: incubation temperature fit quality for each site</strong></p> <p>This figure shows the predicted vs observed daily mean incubation temperatures (individually for each site). The grey dashed line is the line of equality, and the red line shows the orthogonal regression. Refer to <strong>Supp. Info. Table S1</strong> for the 3-letter beach codes.</p> <p> </p> <p><strong>Supp. Info. Figure S7: sensitivity analysis</strong></p> <p>This figure shows the differences in hatching success (survival proportion) and sex ratio (male proportion) when predicted using laboratory data (from constant temperature experiments found in the literature: see <strong>Supp. Info. Table S2 </strong>and <strong>Supp. Info. Table S4</strong>) either at the species level or at the Regional Management Unit (RMU) level. Differences are plotted for two climate scenarios (present and SSP2-4.5) and three phenology scenarios (no shift, mean shift, max. shift: see values in number of days shifted earlier in <strong>Supp. Info. Table S1</strong>). We considered only predictions for <em>Caretta caretta</em> (Cc in orange), <em>Eretmochelys imbricata</em> (Ei in yellow) and <em>Lepidochelys olivacea</em> (Lo in green). Data at the RMU level were not available at our study sites for <em>Chelonia mydas</em>. Black dashed lines represent the line of equality.</p> <p> </p>
Data for "Early planting adaptation makes the coupled food-water system more sustainable under climate change"
<p>Data for submission "Early planting adaptation makes the coupled food-water system more sustainable under climate change"</p><p>All data are in netcdf format and can be read in ncl, python, R code capacity.</p><p> </p><p><strong>geo_em.d01.conus.corn:</strong></p><p>Domain setup file for the Noah-MP crop model in the US corn belt. Lat/lon location specified by "XLAT_<i>M" and "XLONG_M</i>" variable and corn planting area specified by "CROPTYPE" variable.</p><p> </p><p>Three zip files are uploaded containing data from model simulations and county-level yield and irrigation record:</p><p><strong>Yield_data.zip:</strong></p><p>yield data from model simulations (denoted by three scenarios, CTRL, PGW, TAVE), with irrigation (irr), and from USDA NASS (NASS).</p><p><strong>Irrigation_data.zip:</strong></p><p>Irrigation amount data from three scenarios (CTRL, PGW, TAVE for early planting), and from USGS water use record (2005 and 2010).</p><p><strong>TempPrecPET.zip:</strong></p><p>temperature and precipitation and potential evapotranspiration data (PET) for the CTRL and PGW climate scenarios. </p>
Health Impacts of a Climate Change Adaptation Strategy to Address Drinking-water Salinity in Coastal Bangladesh
ClinicalTrials.gov study NCT02746003. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Mating system and historical climate conditions affect population mean seed mass: evidence for adaptation and a new component of the selfing syndrome in Clarkia
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Data from: Lagging adaptation to climate change supersedes local adaptation to herbivory in an annual monkeyflower
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Data from: Standing genomic variation within coding and regulatory regions contributes to the adaptive capacity to climate in a foundation tree species
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Data from: Functional decoupling between flowers and leaves in the Ameroglossum pernambucense complex can facilitate local adaptation across a pollinator and climatic heterogeneous landscape
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Data from: Mountain building, climate cooling and the richness of cold-adapted plants in the northern hemisphere
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ScienceDex guides
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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.