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26 results for “agricultural adaptation”
Farmer adaptive behavior and risk management in EU agriculture
<p>Risk and risk management are essential elements of agriculture and affect the wellbeing of farm households. Farmers react to production, market and institutional risks and challenges by taking measures on or off the farm. Such risk management measures are often costly and have implications for up- and downstream industries as well as the environment. The risk exposure of European farms is increasing. For example, climate change will increase the frequency and magnitude of extreme weather events like droughts, heatwaves and heavy rainfalls that potentially have detrimental effects on agricultural production. Thus, the adaptive capacity and risk management options in European agriculture need to be improved. Policy shall support this process. Policies are needed to support a diversity of risk management solutions and not only focus on a few solutions. Strategies to cope with risk often go beyond the level of the individual farm. Cooperation, learning and sharing of risks play a vital role in European agriculture and shall be strengthened. Thus, coordinated policies targeting beyond the individual farm and considering all the stakeholders involved in the risk management strategies are needed to ensure their effective implementation. Moreover, policies need to facilitate to take full advantage of the rapid technological progress and improved data availability (e.g. based on satellite imagery) to develop a wider set of risk management strategies.</p>
MADFORWATER: WP2: Adaptation of wastewater treatment technologies for agricultural reuse: Task2.4: Industrial wastewater treatment: Treatment of different types of wastewater by means of innovative resins: Subset2
<p>This dataset contains the data underlying the following publication: Li Qimeng, Wang Cheng, Hua Ming, Shuang Chendong, Li Aimin, Gao Canzhu. (2017). High-efficient removal of phthalate esters from aqueous solution with an easily regenerative magnetic resin: Hydrolytic degradation and simultaneous adsorption. <em>Journal of Cleaner Production</em><em>. </em> <a href="https://doi.org/10.1016/j.jclepro.2017.11.121">https://doi.org/10.1016/j.jclepro.2017.11.121</a></p>
MADFORWATER: WP3: Adaptation of technologies for efficient water management and treated wastewater reuse in agriculture: Task3.1: Reduction of crop water requirement and tools for irrigation management with treated WW: Subtask 3.1.1: Plant Growth Promotion (PGP) bacteria to enhance crop resistance to water stress and salinity: Subset1
<p>This dataset contains the data underlying the following publication: Mouna Mahjoubi, Simone Cappello, Yasmine Souissi, Atef Jaouani and Ameur Cherif (February 7th 2018). Microbial Bioremediation of Petroleum Hydrocarbon– Contaminated Marine Environments, Recent Insights in Petroleum Science and Engineering Mansoor Zoveidavianpoor, IntechOpen, DOI: 10.5772/intechopen.72207</p> <p> </p>
MADFORWATER: WP2: Adaptation of wastewater treatment technologies for agricultural reuse: Task2.4: Industrial wastewater treatment: Treatment of different types of wastewater by means of innovative resins: Subset5
<p>This dataset contains the data underlying the following publication: Yu Huang, Shi Cheng, Ya-Ping Wu, Ji Wu<sup> </sup>, Yan Li, Zong-Li Huo, Ji-Chun Wu<sub>­</sub>, Xian-Chuan Xie, Gregory V. Korshin , Ai-Min Li<sup> </sup>, Wen-Tao Li (2019)</p> <p>Developing surrogate indicators for predicting suppression of halophenols formation potential and abatement of estrogenic activity during ozonation of water and wastewater. <em>Water Research.</em> <a href="https://doi.org/10.1016/j.watres.2019.05.092">https://doi.org/10.1016/j.watres.2019.05.092</a></p>
MADFORWATER: WP2: Adaptation of wastewater treatment technologies for agricultural reuse: Task2.4: Industrial wastewater treatment: Treatment of different types of wastewater by means of innovative resins: Subset3
<p>This dataset contains the data underlying the following publication: Li Qimeng, Wu Ji, Hua Ming, Zhang Guang, Li Wentao, Shuang Chendong, Li Aimin. (2017). Preparation of Permanent Magnetic Resin Crosslinking by Diallyl Itaconate and Its Adsorptive and Anti-fouling Behaviors for Humic Acid Removal. <em>Scientific Report. </em> <a href="https://doi.org/10.1038/s41598-017-17360-8">https://doi.org/10.1038/s41598-017-17360-8</a></p>
MADFORWATER: WP3: Adaptation of technologies for efficient water management and treated wastewater reuse in agriculture: Task3.1: Reduction of crop water requirement and tools for irrigation management with treated WW: Subtask 3.1.1: Plant Growth Promotion (PGP) bacteria to enhance crop resistance to water stress and salinity: Subset2
<p>This dataset contains the data underlying the following publication: Hassen W, Neifar M, Cherif H, Najjari A, Chouchane H, Driouich RC, Salah A, Naili F, Mosbah A, Souissi Y, Raddadi N, Ouzari HI, Fava F and Cherif A (2018) Pseudomonas rhizophila S211, a New Plant Growth-Promoting Rhizobacterium with Potential in Pesticide-Bioremediation. Front. Microbiol. 9:34. doi: 10.3389/fmicb.2018.00034</p>
MADFORWATER: WP2: Adaptation of wastewater treatment technologies for agricultural reuse: Task2.4: Industrial wastewater treatment: Treatment of different types of wastewater by means of innovative resins: Subset1
<p>This dataset contains the data underlying the following publication: Li Wen-Tao, Cao Meng-Jie, Young Tessora, Ruffino Barbara, Dodd Michael, Li Ai-Min, Korshin Gregory. (2017).</p> <p>Application of UV absorbance and fluorescence indicators to assess the formation of biodegradable dissolved organic carbon and bromate during ozonation. Water Research 2017, 111, 154-162. <a href="http://dx.doi.org/10.1016/j.watres.2017.01.009">http://dx.doi.org/10.1016/j.watres.2017.01.009</a>.</p>
MADFORWATER: WP2: Adaptation of technologies for efficient water management and treated wastewater reuse in agriculture: Task 2.3–Agro-industrial wastewater treatment: Subtask 2.3.1. –Treatment of olive mill wastewater (OMWW): Aerobic biological treatment in sequenced batch reactors (SBRs): Subset 1
<p>This dataset contains the data underlying the following publication: Fatma AROUS, Chadlia HAMDI, Souhir KMIHA, Nadia KHAMMASSI, Amani AYARI, Mohamed NEIFAR, Tahar MECHICHI, Atef JAOUANI (2018). Treatment of olive mill wastewater through employing sequencing batch reactor: Performance and microbial diversity assessment. 3 Biotech 2018, 8, 481. https://doi.org/10.1007/s13205-018-1486-6.</p>
Data from: Can impacts of climate change and agricultural adaptation strategies be accurately quantified if crop models are annually re-initialized?
Estimates of climate change impacts on global food production are generally based on statistical or process-based models. Process-based models can provide robust predictions of agricultural yield responses to changing climate and management. However, applications of these models often suffer from bias due to the common practice of re-initializing soil conditions to the same state for each year of the forecast period. If simulations neglect to include year-to-year changes in initial soil conditions and water content related to agronomic management, adaptation and mitigation strategies designed to maintain stable yields under climate change cannot be properly evaluated. We apply a process-based crop system model that avoids re-initialization bias to demonstrate the importance of simulating both year-to-year and cumulative changes in pre-season soil carbon, nutrient, and water availability. Results are contrasted with simulations using annual re-initialization, and differences are striking. We then demonstrate the potential for the most likely adaptation strategy to offset climate change impacts on yields using continuous simulations through the end of the 21st century. Simulations that annually re-initialize pre-season soil carbon and water contents introduce an inappropriate yield bias that obscures the potential for agricultural management to ameliorate the deleterious effects of rising temperatures and greater rainfall variability.
Data from: Diet adaptation in dog reflects spread of prehistoric agriculture
Adaptations allowing dogs to thrive on a diet rich in starch, including a significant AMY2B copy number gain, constituted a crucial step in the evolution of the dog from the wolf. It is however not clear if this change was associated with the initial domestication or represents a secondary shift related to the subsequent development of agriculture. Previous efforts to study this process were based on geographically limited data sets and low-resolution methods and it is therefore not known to what extent the diet adaptations are universal among dogs and whether there are regional differences associated with alternative human subsistence strategies. Here we use droplet PCR to investigate worldwide AMY2B copy number diversity among indigenous as well as breed dogs and wolves to elucidate how a change in dog diet was associated with the domestication process and subsequent shifts in human subsistence. We find that AMY2B copy numbers are bimodally distributed with high copy numbers (median 2nAMY2B=11) in a majority of dogs but no, or few, duplications (median 2nAMY2B=3) in a small group of dogs originating mostly in Australia and the arctic. We show that this patterns correlates geographically to the spread of prehistoric agriculture and conclude that the diet change may not have been associated with initial domestication but rather the subsequent development and spread of agriculture to most, but not all regions of the globe.
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>
MADFORWATER: WP3: Adaptation of technologies for efficient water management and treated wastewater reuse in agriculture: Task3.1: Reduction of crop water requirement and tools for irrigation management with treated WW: Subtask 3.1.1: Plant Growth Promotion (PGP) bacteria to enhance crop resistance to water stress and salinity
<p>This dataset contains the data underlying the following publication: Hassen W, Neifar M, Cherif H, Najjari A, Chouchane H, Driouich RC, Salah A, Naili F, Mosbah A, Souissi Y, Raddadi N, Ouzari HI, Fava F and Cherif A (2018) Pseudomonas rhizophila S211, a New Plant Growth-Promoting Rhizobacterium with Potential in Pesticide-Bioremediation. Front. Microbiol. 9:34. doi: 10.3389/fmicb.2018.00034</p>
Data from: Diet adaptation in dog reflects spread of prehistoric agriculture
Open the record for dataset details and reuse information.
Agriculture is adapting to phenological shifts caused by climate change, but grassland songbirds are not
Open the record for dataset details and reuse information.
Data from: Can impacts of climate change and agricultural adaptation strategies be accurately quantified if crop models are annually re-initialized?
Open the record for dataset details and reuse information.
Data from: Agricultural adaptation in the native North American weed waterhemp, Amaranthus tuberculatus (Amaranthaceae)
<p>There is increasing interest in documenting adaptation of weedy plant species to agricultural ecosystems, beyond the evolution of herbicide resistance. Waterhemp (<i>Amaranthus tuberculatus</i>) is a native plant of the Midwestern U.S. that began infesting agricultural fields in the 20<sup>th</sup> century within the central portion of its range. We hypothesized that the vegetative growth and reproductive traits of waterhemp from this heavily infested central region provide differential fitness benefits in agricultural environments. We collected seeds from across the species' native range, representing regions with varying degrees of waterhemp infestation, and planted them together in common garden soybean plots. A 2010 common garden experiment was conducted within the range of agriculturally weedy waterhemp (in Missouri), and a 2011 common garden experiment was conducted outside of this range (in Ohio). Days to flowering and flowering plant height, mature plant size data (height, number of branches, and length of the longest branch), and above-ground biomass were measured to estimate relative fitness. In both common garden locations, plants from regions where waterhemp occurs as an agricultural weed — including those from the heavily infested Mississippi Valley region (Iowa, Illinois, and Missouri) and the less severely infested Plains region (Nebraska, Kansas, and Oklahoma) — had higher relative performance in almost all fitness-related measures than plants from the Northeast region (Ohio, Michigan, and Ontario), which had little to no agriculturally weedy waterhemp at the time of our study. Further analysis revealed that fewer days to flowering in the Northeast populations can be largely accounted for by latitude of origin, suggesting a strong genetic influence on this reproductive trait. These findings suggest intraspecific variation in agricultural adaptation in a native U.S. weed, and support the use of agricultural weeds to study adaptation.</p>
Data from: Slow and temperature-mediated pathogen adaptation to a non-specific fungicide in agricultural ecosystem
The spread of antimicrobial resistance and global change in air temperature represent two major phenomena that are exerting a disastrous impact on natural and social issues but investigation of the interaction between these phenomena in an evolutionary context is limited. In this study, a statistical genetic approach was used to investigate the evolution of antimicrobial resistance in agricultural ecosystem and its association with local air temperature. We found no resistance to mancozeb, a non-specific fungicide widely used in agriculture for more than half a century, in 215 Alternaria alternata isolates sampled from geographic locations along a climatic gradient and cropping system representing diverse ecotypes in China, consistent with low resistance risk in many non-specific fungicides. Genetic variance accounts for ~35% of phenotypic variation while genotype-environment interaction is negligible, suggesting that heritability plays a more important role in the evolution of resistance to mancozeb in plant pathogens than phenotypic plasticity. We also found that tolerance to mancozeb in agricultural ecosystem is under constraining selection and significantly associated with local air temperature, possibly resulting from a pleiotropic effect of tolerance with thermal and other ecological adaptations. The implication of these results for fungicide and other antimicrobial management in the context of global warming is discussed.
Data from: A resurrection experiment finds evidence of both reduced genetic diversity and potential adaptive evolution in the agricultural weed Ipomoea purpurea
Despite the negative economic and ecological impact of weeds, relatively little is known about the evolutionary mechanisms that influence their persistence in agricultural fields. Here, we use a resurrection approach to examine the potential for genotypic and phenotypic evolution in Ipomoea purpurea, an agricultural weed that is resistant to glyphosate, the most widely used herbicide in current-day agriculture. We found striking reductions in allelic diversity between cohorts sampled nine years apart (2003 vs. 2012), suggesting that populations of this species sampled from agricultural fields have experienced genetic bottleneck events that have led to lower neutral genetic diversity. Heterozygosity excess tests indicate that these bottlenecks may have occurred prior to 2003. A greenhouse assay of individuals sampled from the field as seed found that populations of this species, on average, exhibited modest increases in herbicide resistance over time. However, populations differed significantly between sampling years for resistance: some populations maintained high resistance between the sampling years whereas others exhibited increased or decreased resistance. Our results show that populations of this noxious weed, capable of adapting to strong selection imparted by herbicide application, may lose genetic variation as a result of this or other environmental factors. We probably uncovered only modest increases in resistance on average between sampling cohorts due to a strong and previously identified fitness cost of resistance in this species, along with the potential that nonresistant migrants germinate from the seed bank.
Agricultural adaptation to reconcile food security and water sustainability under climate change: the case of cereals in Iran
<p>In this study, we simulate the crop yield and water footprint (WF) of major food crops of Iran on irrigated and rainfed croplands for the historical and the future climate. We assesse the effects of three agricultural adaptation strategies to climate change in terms of potential blue water savings. We then evaluate to what extent these savings can reduce unsustainable blue WF. We find that cereal production increases under climate change in both irrigated and rainfed croplands (by 2.6-3.1 and 1.4-2.3 million t y<sup>-1</sup>, respectively) due to increased yields (6.6%-78.7%). Simultaneously, the unit WF (m<sup>3</sup> t<sup>-1</sup>) tends to decrease in most scenarios. However, the annual consumptive water use increases in both irrigated and rainfed croplands (by 0.3-1.8 and 0.5-1.7 billion m<sup>3</sup> y<sup>-1</sup>, respectively). This is most noticeable in the arid regions, where consumptive water use increases by roughly 70% under climate change. Off-season cultivation is the most effective adaptation strategy to alleviate additional pressure on blue water resources, with blue water savings of 14-15 billion m<sup>3</sup> y<sup>-1</sup>. The second most effective is WF benchmarking, which results in blue water savings of 1.1-3.5 billion m<sup>3</sup> y<sup>-1</sup>. The early planting strategy is less effective, but still leads to blue water savings of 1.7-1.9 billion m<sup>3</sup> y<sup>-1</sup>. In the same order of effectiveness, these three strategies can reduce blue water scarcity and unsustainable blue water use in Iran under current conditions. However, we find that these strategies do not mitigate water scarcity in all provinces per se, nor all months of the year.</p>
MADFORWATER: WP2: Adaptation of wastewater treatment technologies for agricultural reuse: Task2.4: Industrial wastewater treatment: Treatment of different types of wastewater by means of innovative resins: Subset4
<p>This dataset contains the data underlying the following publication: Ji Wu, Shi Cheng, Min-Hui Cai, Ya-Ping Wu, Yan Li, Ji-Chun Wu, Ai-Min Li, Wen-Tao Li(2018)</p> <p>Applying UV absorbance and fluorescence indices to estimate inactivation of bacteria and formation of bromate during ozonation of water and wastewater effluent. <em>Water Research. </em> <a href="https://doi.org/10.1016/j.watres.2018.08.030">https://doi.org/10.1016/j.watres.2018.08.030</a></p>
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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.