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274 results for “climate change responses”

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dryad32/100

Data from: Plant functional indicators of vegetation response to climate change, past present and future: I. Trends, emerging hypotheses and plant functional modality

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publicMay 2019View details →
dryad32/100

Data from: Adaptation to climate change: trade-offs among responses to multiple stressors in an intertidal crustacean

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publicMay 2016View details →
dryad32/100

Data from: Climate and anthropogenic factors determine site occupancy in Scotland's Northern-range badger population: implications of context-dependent responses under environmental change

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publicFeb 2018View details →
dryad32/100

Data from: Transgenerational and within-generation plasticity in response to climate change: insights from a manipulative field experiment across an elevational gradient

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publicJul 2018View details →
dryad32/100

Data from: A review and meta-analysis of intraspecific differences in phenotypic plasticity: implications to forecast plant responses to climate change

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publicJul 2019View details →
dryad32/100

The importance of considering the duration of extreme temperatures when investigating responses to climate change

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publicOct 2022View details →
dryad32/100

Data from: Highly contrasted responses of Mediterranean octocorals to climate change along a depth gradient

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publicMay 2015View details →
dryad32/100

Differential response of Sichuan snub-nosed monkeys to climate change and human activities

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publicSep 2022View details →
dryad32/100

Response of northern populations of black spruce and jack pine to southward seed transfers: Implications for climate change

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publicJun 2022View details →
dryad32/100

Data from: Meta‐analyzing the likely cross‐species responses to climate change

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publicAug 2019View details →
dryad32/100

Data from: Exploring the universal ecological responses to climate change in a univoltine butterfly

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publicJan 2017View details →
dryad32/100

Data from: Blue mussel (Genus Mytilus) transcriptome response to simulated climate change in the Gulf of Maine

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publicJan 2020View details →
dryad32/100

Forecasting climate change response in an alpine specialist songbird reveals the importance of considering novel climate

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publicJan 2024View details →
dryad32/100

Data from: Ecological co-associations influence species’ responses to past climatic change: an example from a Sonoran Desert bark beetle

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publicMar 2013View details →
dryad32/100

Data from: Accounting for groundwater in stream fish thermal habitat responses to climate change

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publicDec 2014View details →
dryad32/100

A specialist bee and its host plants experience phenological shifts at different rates in response to climate change

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publicJan 2022View details →
dryad32/100

In transition: avian biogeographic responses to a century of climate change across desert biomes

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publicFeb 2020View details →
zenodo28/100

An iron cycle cascade governs the response of equatorial Pacific ecosystems to climate change

<p>Net primary production time series for simulations conducted with the NEMO-PISCES model under RCP85 forcing.</p>

opencc-by-4.0Aug 2020View details →
dryad28/100

Predicting hydrologic responses to climate changes in highly glacierized and mountainous region Upper Indus Basin

<p><span>The Upper Indus Basin (UIB) is a major source of supplying water to different areas because of snow and glaciers melt and</span><span> is also enduring the regional impacts of global climate change. The expected changes in temperature, precipitation, and snowmelt </span><span>could be reasons for further escalation of the problem. </span><span>Therefore, estimation of hydrological processes </span><span>is </span><span>critical for UIB. The objectives of this paper were to estimate the impacts of climate change on water resources and future projection for surface water under different climatic scenarios using Soil and Water Assessment Tool (SWAT). The methodology includes</span><span>:</span><span> (i) development of SWAT model using </span><span>land cover, soil and meteorological data; (ii) calibration of the model using daily flow data from </span><span>1978-1993; (iii) model validation for the time 1994-2003; (iv) bias correction of Regional Climate Model (v) </span><span>utilization of </span><span>bias corrected RCM for future assessment under RCP4.5 and RCP8.5 </span><span>for mid (2041-2070) and late century (2071-2100). The results of the study revealed a strong correlation between simulated and observed flow </span><span>with R<sup>2</sup> and NSE equals 0.85 each for daily flow</span><span>. For validation, R<sup>2</sup> and NSE were found to be 0.84 and 0.80 respectively. Compared to baseline period (1976-2005), the result of RCM showed an increase in temperature ranging from 2.36°C to 3.50°C and 2.92°C to 5.23°C for RCP4.5 and RCP8.5 respectively, till the end of 21<sup>st</sup> century. Likewise, the increase in annual average precipitation is 2.4% to 2.5% and 6.0% to 4.6% (mid to late century) under RCP 4.5 and 8.5 respectively. The model simulation results for RCP4.5 showed increase in flow by 19.24% and 16.78% for mid and late century respectively. For RCP8.5, the increase in flow is 20.13% and 15.86% during mid and late century respectively. The model was more sensitive towards available moisture and snowmelt parameters. Thus, SWAT model </span><span>could </span><span>be used as effective tool for climate change valuation and for sustainable management of water resources in future.</span></p>

opencc-zeroAug 2020View details →
dryad28/100

Responses of four dominant dryland plant species to climate change in the Junggar Basin, north-west China

<p>Aim Dryland ecosystems are exceedingly sensitive to climate change. Desertification induced by both climate changes and human activities seriously threatens the dryland vegetation. However, the impact of climate change on distributions of dryland plant species has not been well documented. Here, we studied the potential distributions of four representative dryland plant species (<i>Haloxylon ammodendron</i>, <i>Anabasis aphylla</i>, <i>Calligonum mongolicum</i>, and <i>Populus euphratica</i>) under current and future climate scenarios in a temperate desert region, aiming to improve our understanding of the responses of dryland plant species to climate change and provide guidance for dryland conservation and afforestation. Location Junggar Basin, a large desert region in north-western China. Methods Occurrence data of the studied species were collected from an extensive field investigation of 2516 sampling sites in the Junggar Basin. Ensemble species distribution models using 10 algorithms were developed and used to predict the potential distribution of each studied species under current and future climate scenarios. Result <i>H. ammodendron</i> and <i>A. aphylla</i> were likely to lose most of their current suitable habitats under future climate scenarios, while <i>C. mongolicum</i> and <i>P. euphratica</i> were likely to expand their ranges or remain relatively stationary. Variable importance evaluation showed that the most important climate variables influencing species distributions differed across the studied species. These results may be explained by the different ecophysiological characteristics and adaptation strategies to the environment of the four studied species. Main conclusions We explored the responses of the representative dryland plant species to climate change in the Junggar Basin in north-western China. The different changes in suitability of different species imply that policymakers may need to reconsider the selection and combination of the afforestation species used in this area. This study can provide valuable reference for the management and conservation of dryland ecosystems under future climate change scenarios.</p>

opencc-zeroOct 2020View details →

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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.

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Last verified 2026-04-29Open record

OpenNeuro

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Last verified 2026-04-29Open record