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203 results for “water stress”
Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouse
<p>Datasets and R source code of the article Depeux C, Branger A, Moulignier T, Moreau J, Lemaître J-F, Dechaume-Moncharmont F-X, Laverre T, Paulhac H, Gaillard J-M, Beltran-Bech S (2023) Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouse. <strong><em>Peer Community Journal</em></strong> 3:e7 http://dx.doi.org/<a href="https://doi.org/10.24072/pcjournal.228">10.24072/pcjournal.228</a></p> <p>This article previously appeared as preprint Depeux C, Branger A, Moulignier T, Moreau J, Lemaître J-F, Dechaume-Moncharmont F-X, Laverre T, Pauhlac H, Gaillard J-M, Beltran-Bech S (2022) Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouse. <em><strong>bioRxiv</strong>, 2022.09.26.509512 </em> https://doi.org/10.1101/2022.09.26.509512</p> <p><em>Peer-reviewed and recommended by <strong>Peer Community in Ecology</strong>: </em> Belsare A (2022) An experimental approach for understanding how terrestrial isopods respond to environmental stressors. <em>Peer Community in Ecology, 100506. </em><a href="https://doi.org/10.24072/pci.ecology.100506"><strong>https://doi.org/10.24072/pci.ecology.100506</strong></a></p>
Invasive buffel grass (Cenchrus ciliaris) increases water stress and reduces growth of native foothills palo verde (Parkinsonia microphylla) seedlings in pot experiments
Although buffel grass (Cenchrus ciliaris) invasions on several continents have significant ecological impacts, little information is available on its effect on seedling emergence and establishment of native vegetation. In highly impacted areas of the Sonoran Desert of North America, perennial plants are particularly vulnerable during their seedling stage. We studied the impact of buffel grass on the emergence, survival, and water stress in the seedlings of a locally dominant native tree, the foothills palo verde (Parkinsonia microphylla), using two pot experiments. In the first experiment, we compared the germination, growth, and survival of concentric rings of palo verde seedlings around mature individuals of buffel grass, a native shrub of a similar diameter and height to buffel grass, or in a pot with bare soil. In the second experiment, we compared the competitive effects of buffel grass seedlings on palo verde seedlings with the effects of conspecific seedlings, again using germination, growth, and survival as metrics. We followed up both experiments by quantifying the ratio of stable carbon isotopes in the tissues of the palo verde seedlings, which can be an indicator of water stress. We found evidence of relatively greater water stress in palo verde seedlings grown with buffel grass seedlings in pots than those grown with no competitor, and reduced survival of palo verde seedlings when grown with mature buffel grass. Our results highlight the need for more manipulative studies of density to improve mechanistic understanding of population dynamics, and to forecast how populations and communities will respond in the long term to perturbations such as invasion.
WER01 Elevated CO2 counteracts effects of water stress on woody rangeland-encroaching species at Konza Prairie
Woody plants are increasing prevalence and dominance in many rangelands around the world. The reason for their increase is various but two common drivers that have changed are an increase in CO2 concentrations and alteration to precipitation dynamics. We asked what the physiological growth dynamics of four juvenile woody plant species (Cornus drummondii, Rhus glabra, Gleditsia triacanthos and Juniperus osteosperma) when grown in elevated CO2 and chronically water stressed. We found that elevated CO2 counteracts much of the physiological effects of chronic water stress in the four different woody plant species measured. The alleviation of water stress from increased CO2 concentrations will result in juvenile woody plants continuing to expand and establish in North American rangelands. This information will aid land managers in making long-term management objectives for reducing woody plants in rangelands.
Data and code from: A mixture of grass-legume cover crop species may ameliorate water stress in a changing climate, a greenhouse experiment at Dickinson College in Carlisle, PA, USA, 2021.
Data and R code associated with a greenhouse study investigating the influence of water stress on growth, root traits, and biomass of rye and crimson clover seedlings grown separately or together. Data were collected in the Dr. Inge P. Stafford Greenhouse of Dickinson College (Carlisle PA, USA) in June 2021.
Fig. 3 in Water pH and hardness alter ATPases and oxidative stress in the gills and kidney of pacu (Piaractus mesopotamicus)
Fig. 3. Thiobarbituric acid reactive substances (TBARS) content (nmol TMP mg wet tissue-1) in a. gills and b. kidney of pacu (Piaractus mesopotamicus) juveniles under different water hardness and pH at different times. LWH = low water hardness (50 mg CaCO L-1); HWH = high water hardness (120 mg CaCO L-1). Data are presented as the means ± SEM (n = 3 3 9 fish treatment–1). Different uppercase letters indicate statistically differences between pH at the same hardness (P <0.05). Different lowercase letters indicate statistically differences between hardness at the same pH (P <0.05).
Fig. 2 in Water pH and hardness alter ATPases and oxidative stress in the gills and kidney of pacu (Piaractus mesopotamicus)
Fig. 2. Total antioxidant capacity against peroxyl radicals (ACAP) (relative area) in a. gills and b. kidney of pacu (Piaractus mesopotamicus) juveniles under different water hardness and pH at different times. LWH = low water hardness (50 mg CaCO L-1); HWH = high water hardness (120 mg CaCO L-1). Data are presented as the means ± SEM (n = 9 fish treatment–1). 3 3 Different uppercase letters indicate statistically differences between pH at the same hardness (P <0.05).
Data for 'Future Transboundary Water Stress and Its Drivers Under Climate Change: A Global Study'
<p><strong>This dataset is a supplement to the following publication (please cite that when using the data):</strong></p> <p>Munia et al. 2020. Future transboundary water stress and its drivers under climate change: a global study. Earth’s future. <a href="https://doi.org/10.1029/2019EF001321">https://doi.org/10.1029/2019EF001321</a></p> <p> </p> <p><strong>Water stress category data</strong></p> <p>Dataset presents the water stress category in transboundary basins at sub-basin level for different scenarios (see article for details):</p> <ul> <li> <p>stress_category_Historical.gpkg: stress for years 1980 and 2010</p> </li> <li> <p>stress_category_SSP1‐RCP26.gpkg: stress for year 2050, SSP1‐RCP2.6 scenario</p> </li> <li> <p>stress_category_SSP1‐RCP45.gpkg: stress for year 2050, SSP1‐RCP4.5 scenario</p> </li> <li> <p>stress_category_SSP2‐RCP60.gpkg: stress for year 2050, SSP2‐RCP6.0 scenario</p> </li> <li> <p>stress_category_SSP3‐RCP60.gpkg: stress for year 2050, SSP3‐RCP6.0 scenario</p> </li> </ul> <p> </p> <p><strong>Dataset specifications:</strong></p> <p>Type: geopackage (gpkg)</p> <p>Spatial extent: -165, 141.5, -54.5, 70.5 (xmin, xmax, ymin, ymax)</p> <p>Temporal extent: see above</p> <p>Projection: long/lat WGS84 (EPSG:4326)</p> <p>Information: sub-basin name, country, stress level, stress category</p> <p>Unit: -</p> <p> </p>
Climatic history, constraints, and the plasticity of phytochemical traits under water stress
<p><span>Environmental stress can induce changes in organismal traits and in resulting intraspecific variation. The nature of such effects will depend on the plasticity of trait expression and on any ecological constraints to such expression. Plants can mitigate abiotic stress, like drought, by changing their chemistry, but the ability to induce costly metabolites may be under strong local selection and ecologically constrained. Here we asked whether climate at the seed source predicts plant chemical plasticity in response to water stress and what the consequences are for intraspecific variation in phytochemical traits. To this end, we used common gardens of two widespread species of western milkweed (<em>Asclepias fascicularis </em>and <em>Asclepias speciosa</em>)<em> </em>that had been collected from sites across an aridity gradient. Both species produce high concentrations of leaf flavonols, which are hypothesized to mitigate water stress by functioning as antioxidants. These compounds were found in higher constitutive concentrations in plants sourced from drier sites, and both species responded to water stress in the common garden by increasing leaf flavonol concentrations. Interestingly, flavonol plasticity was higher in plants sourced from wetter sites in <em>A. fascicularis</em>, with similar, but weaker, patterns in <em>A. speciosa</em>. These opposing patterns in constitutive and induced flavonol expression reduced the variation between populations in leaf flavonol concentrations under water stress. </span><span>These results suggest that</span><span> local adaptation in plants can </span><span>shape phytochemical strategies for water limitation but that the cost of metabolite production may ultimately limit the range of phytochemical variation.</span></p>
Data supporting the manuscript entitled: 'Intermittent soil water stress history favors microbial traits that better mitigate wheat biomass losses during subsequent water stress.'
<p>Data living in this data repository supports the scientific article entitled: Intermittent soil water stress history favors microbial traits that better mitigate wheat biomass losses during subsequent water stress.</p> <p> </p> <p> </p> <p> </p>
Supplementary Materials of "Elementary mathematics helps to shed light on the transpiration budget under water stress"
<p>This directory contains the Jupyter notebook used to do complete analysis from our paper "Elementary mathematics sheds light on the transpiration budget under water stress" submitted to the Ecohydrology Journal at the Special Issues "ECOHYDROLOGY OF INLAND AND COASTAL WATERS in honor of Ignacio Rodriguez-Iturbe".</p> <p>These materials are referenced in the main text and supplemental text of the publication. The purpose of this repository is to facilitate replication of our analysis by any interested parties. </p> <p>Specifically, this directory contains ten files:</p> <ul> <li>From 0 to 5, Jupyter Notebook prepared and used for the analysis (please execute the notebooks in numerical sequence). </li> <li>"Table_S1.xlsx" Data From: Kröber, W., H. Heklau, and H. Bruelheide. 2015. “Leaf Morphology of 40 Evergreen and Deciduous Broadleaved Subtropical Tree Species and Relationships to Functional Ecophysiological Traits.” Plant Biology 17 (2): 373–83. <a href="https://doi.org/10.1111/plb.12250"><span>https://doi.org/10.1111/plb.12250</span></a>.</li> <li>"Richards_VG.csv" contains Van Genuchten Parameters for various soils.</li> <li>"The_Rosetta_Stone_of_the_Darcy_Buckingham_law.pdf" addresses the challenge of converting water flux units between Darcy-like soil and plant descriptions, where hydrologists use "head" units (meters) and plant physiologists use pressure potential (MPa). The aim is to clarify and perform the necessary unit conversions, with detailed explanations available in the relevant section on <a href="https://abouthydrology.blogspot.com/2022/10/my-water-management-in-agricolture.html"><span>this webpage</span></a>.</li> </ul>
Figure 7 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 7. Results from the sensitivity analysis depicting variations in the overall effect size estimates (mean ± 95% confidence intervals [CIs]) of water-stress effects on (A) weed germination/emergence, (B) seedling radicle/root length, (C) plant height, and (D) leaf area when a particular study is omitted from the analysis. The vertical black solid and dashed lines represent overall effect sizes (mean ± 95% CIs) with all studies included.
Figure 3 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 3. Overall water-stress effects on germination/emergence of grass and broadleaf weeds (top) and six weed families—Asteraceae, Fabaceae, Convolvulaceae, Amaranthaceae, Rubiaceae, and Poaceae (bottom). The vertical black dashed line represents zero effect. The black dots are overall mean effect sizes, and the black lines are 99% confidence intervals (CIs).The values in parentheses are the number of observations followed by the number of studies for each pair-wise comparison. The mean effect sizes were considered significantly different when their 99% CIs did not include zero.
Figure 4 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 4. The log response ratio for germination and seedling radicle length of broadleaf (green dots/line) and grass (red dots/line) weed species as a function of water-stress intensity. Water stress increased as solution osmotic potential (ψsolution) decreased and vice versa.The subgroups for germination are 0 to −0.2, −0.2 to −0.4, −0.4 to −0.6, −0.6 to −0.8, −0.8 to −1.0, −1.0 to −1.4, and <−1.4 MPa, while the subgroups for radicle length are 0 to −0.2, −0.2 to −0.4, −0.4 to −0.6, −0.6 to −1.0, and <−1.0 MPa. Only ψsolution-based studies were used in this analysis. For each subgroup, the solid dots and lines represent mean effect sizes and their corresponding 99% confidence intervals (CIs).The mean effect sizes were considered significantly different when their 99% CIs did not include zero. Similarly, the water-stress effects were significantly different for each subgroup and among weed types only when their 99% CIs did not overlap with one another. The fitted lines represent a four-parameter logistic regression model, and the coefficients of the models are presented in Table 2.
Figure 1 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses; Page and McKenzie 2021) flow diagram highlighting the selection procedure of 86 scientific published papers included in the meta-analysis.
Figure 8 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 8. Results from the sensitivity analysis depicting variations in the overall effect size estimates (mean ± 95% confidence intervals [CIs]) of water-stress effects on (A) branches/tillers per plant, (B) leaves per plant, (C) inflorescences per plant, (D) seeds per plant, (E) total biomass, (F) root biomass, (G) shoot biomass, and (H) root:shoot ratio, when a particular study is omitted from the analysis. The vertical black solid and dashed lines represent overall effect sizes (mean ± 95% CIs) with all studies included.
Figure 6 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 6. Density plots depicting the distribution of the individual effect sizes for all 12 response variables considered in this meta-analysis: (A) weed seed germination/emergence; (B) radicle/root length, plant height, and leaf area; (C) branches/tillers per plant, leaves per plant, inflorescences per plant, and seeds per plant; and (D) total biomass, root biomass, shoot biomass, and root:shoot ratio.
Figure 2 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 2. Overall water-stress effects on weed germination/emergence, growth characteristics, and seed production. The vertical black dashed line represents zero effect. The black dots are overall mean effect sizes, and the black lines are 95% confidence intervals (CIs). The values in parentheses are the number of observations followed by the number of studies for each pair-wise comparison. The mean effect sizes were considered significantly different when their 95% CIs did not include zero.
Figure 5 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 5. The log response ratio for weed growth characteristics (plant height, leaf area, branches/tillers per plant, leaves per plant,root biomass, shoot biomass, and root:shoot ratio) and seed production (inflorescences per plant and seeds per plant) as a function of water-stress intensity. Water stress increased as soil moisture (% field capacity) decreased and vice versa. The green and red dots represent broadleaf and grass weed species, respectively. The solid black points and the lines represent mean effect sizes and their 99% confidence intervals (CIs) for low (>60%), moderate (30%–60%), and severe (<30% field capacity) water-stress subgroups. The mean effect sizes were considered significantly different when their 99% CIs did not include zero. Similarly, the water-stress effects were significantly different for each subgroup and among weed types only when their 99% CIs did not overlap with one another.
Figure 1 in Effect of degree of water stress on growth and fecundity of velvetleaf (Abutilon theophrOsti) using soil moisture sensors
Figure 1. Soil moisture content in pots was measured using (A) Meter Group 5TM moisture sensors and (B) Em50 data loggers to determine degree of water stress on Abutilon threophrasti in a greenhouse study conducted at the University of Nebraska–Lincoln.
Figure 2. Passion fruit species under different irrigation intervals. A. Passiflora gibertii with a 4 in Development and physiological aspects of three species of passion fruit submitted to water stress
Figure 2. Passion fruit species under different irrigation intervals. A. Passiflora gibertii with a 4-day interval; B. P. gibertii with a 8-day interval; C. P. gibertii with a 12-day interval; D. P. foetida with a 4-day interval; E. P. foetida with a 8-day interval; F. P. foetida with a 12-day interval; G. P. edulis with a 4-day interval; H. P. edulis with a 8-day interval; I. P. edulis with a 12-day interval. Bar = 30 cm.
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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)
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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.