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1,457 results for “feedback”
Primary data for "Temperature-dependence of the clear-sky feedback in radiative-convective equilibrium"
<p>Primary data for the manuscript "Temperature-dependence of the clear-sky feedback in radiative-convective equilibrium".</p> <p>The archive is described in more detail in the enclosed README file.</p>
Root traits and soil microorganisms as drivers of plant-soil feedbacks within the sub-arctic tundra meadow
<p>Plant-soil feedback (PSF) can influence the composition of various soil microorganisms (antagonistic and mutualistic), which can have reciprocal effects on plants. At the same time, we do not understand the effects of fine root traits in moderating microbial-driven PSF. We therefore conducted a greenhouse study to aid in understanding the relationship between root traits, soil community composition (PLFAs and high-throughput sequencing data) and plant-soil feedback (PSF). These data therefore include datasets with fine root traits, raw sequence reads from high-throughput sequencing for soil fungi, phospholipid fatty acid data and biomass data after the plant-soil feedback study.</p>
Data for Past terrestrial hydroclimate sensitivity controlled by Earth System Feedbacks
<p>This folder contains PlioMIP2 ensemble data and CESM2 simulations used in Feng et al., Past terrestrial hydroclimate sensitivity controlled by Earth System Feedbacks (2022). Here is some useful information:</p> <p>1. Experiment IDs of CESM2 experiments are described in the Method section of the manuscript. The first dimension of variables in ensemble files reflects model IDs : "CCSM4", "CESM1", "CESM2", "COSMOS", "IPSL-CM6", "MIROC4m", "NorESM1-F", "HadCM3", "EC-Earth3.3", "IPSL-CM5", "IPSL-CM5A2", "HadGEM3", "GISS-E2-1G".</p> <p>2. The naming convention of variables in ensemble files follows CMIP6 convention. The naming convention of CESM2 variables follows the convention of the model.</p> <p>3. The script pe_budget_season_new.ncl produces moisture budget decomposition. The results are shown in Fig. 4 of the manuscript.</p>
Source data for "Drought self-propagation in drylands due to land–atmosphere feedbacks"
<p>Source data for the analysis performed for "Drought self-propagation in drylands due to land–atmosphere feedbacks". Please refer to https://doi.org/10.5281/zenodo.5839819 for the code.</p>
Data for "Snow albedo feedbacks enhance snow impurity-induced radiative forcing in the Sierra Nevada"
<p>This is the data prepared for submission of "<strong>Snow albedo feedbacks enhance snow impurity-induced radiative forcing in the Sierra Nevada</strong>". Three folders are included: 1) The model output with aerosol deposition in snow (aero); 2) The model output without aerosol deposition in snow (noaero) 3) processed observations used to validate the model results (SPIReS)</p>
Effectiveness of a multicomponent intervention consisting of education and feedback on reducing benzodiazepine prescriptions by general practitioners: BENZORED hybrid type I cluster randomized controlled trial.
<p>Complete dataset variables:</p> <p> </p> <p>GP_ID<br> Health_District<br> Health_District_name<br> PHC_ID<br> PHC_ID_name<br> Arm<br> DHD_Baseline<br> DHD_12m<br> PercentageBZD_baseline<br> PercentageBZD_12m<br> PercentageBZD_baseline_age65<br> PercentageBZD_12m_age65</p>
Linking genetic diversity and species diversity through plant-soil feedback
<p>Genetic diversity and species diversity are typically studied in isolation despite theory showing they likely influence one another. Here, we used simplified communities of one or two populations of one or two species to test whether linkages between genetic and species diversity can be mediated by interactions between plants and their soil microbiota, or microbe-mediated plant-soil feedback (PSF). Interspecific PSF promotes the maintenance of species diversity when plants grow better with heterospecific soil microbes than with conspecific microbes. Similarly, intraspecific PSF promotes the maintenance of genetic diversity when plants grow better with heterogenotypic than with congenotypic microbes. In a two-generation greenhouse experiment, we conditioned the soil microbial community with pairs of plants that were either two individuals of the same species (lower species diversity) or one individual of each of two species (higher species diversity), and with pairs of plants that were either two individuals from the same population (lower genetic diversity) or one individual from each of two populations (higher genetic diversity). We then tested the effects of these microbial communities on plant growth in a second generation. We found that higher genetic diversity reduced the ability of interspecific PSF to promote plant species diversity, and for one of our two study species, higher species diversity reduced the ability of intraspecific PSF to promote plant genetic diversity. If these patterns occur in more diverse communities, then our results suggest that PSF may dampen the negative effects of diversity loss by promoting diversity at other levels of biological organization.</p>
Reward-dependent selection of feedback gains impact rapid motor decisions
<p class="MsoNormal"><span>Target reward influences motor planning strategies through modulation of movement vigor. Considering current theories of sensorimotor control suggesting that movement planning consists in selecting a goal-directed control strategy, we sought to investigate the influence of reward on feedback control. Here we explored this question in three human reaching experiments. First, we altered the explicit reward associated with the goal target and found an overall increase in feedback gains for higher target rewards, highlighted by larger velocities, feedback responses to external loads, and background muscle activity. Then, we investigated whether the differences in target rewards across multiple goals impacted rapid motor decisions during movement. We observed idiosyncratic switching strategies dependent on both target rewards and, surprisingly, the feedback gains at perturbation onset: the more vigorous movements were less likely to switch to a new goal following perturbations. To gain further insight into a causal influence of the feedback gains on rapid motor decisions, we demonstrated that biasing the baseline activity and reflex gains by means of a background load evoked a larger proportion of target switches in the direction opposite to the background load associated with lower muscle activity. Together, our results demonstrate an impact of target reward on feedback control and highlight the competition between movement vigor and flexibility.</span></p>
Plant-soil feedback of the invasive Sorghum halepense on Hainan island, China
<div> <em>Sorghum halepense</em> is a perennial invasive weed causing great harm worldwide, including various regions on Hainan island. In this study, using two approaches, we examined plant-soil feedback of different <em>S. halepense</em> populations. In the first, rhizosphere soil of <em>S. halepense</em> from the field was either sterilized or not to study the role of soil biota on <em>S. halepense</em> growth. In the second, we first let <em>S. halepense</em> plants condition the soil, and then regrow plants on these conditioned soil to study the role of overall changes in soil properties in plant-soil feedback. Sterilization increased the growth of <em>S. halepense</em>, indicating that soil biota inhibited the growth of <em>S. halepense</em>. Soil biota from some populations inhibited the growth of <em>S. halepense</em> more than that from others. In most cases, the relative response of a <em>S. halepense</em> population when associated with its own soil vs. when associated with other soils was similar to the relative response of other populations across the same soils. In the second approach, the effect of conditioning on most soil chemical properties were not different among populations. The interactive effect of conditioning population and replanting population on plant biomass was not significant, indicating that the performance of different <em>S. halepense</em> populations did not depend on the population of <em>S. halepense</em> that conditioned the soil. These results indicate that on Hainan island, <em>S. halepense</em> can outburst and proliferate despite negative feedback with soil biota, and populations of <em>S. halepense</em> differ little in their interactions with soil.</div>
Plant landscape abundance and soil fungi modulate drought effects on plant-soil feedbacks
<p class="MsoNormal"><span>Plant-soil feedbacks (PSF) play an important role in determining plant community structure and dynamics. However, previous studies have provided mixed results for the relationship between PSF and plant landscape abundance (i.e., abundance across local communities). This may reflect the mediation of climate factors on PSF. Here, we tested how PSF of tree species varied with local abundances by growing seedlings in conspecific versus heterospecific soil and how simulated drought altered PSF-plant abundance relationships. Six tree species were selected and half of the seedlings were grown under ambient moisture conditions, while the others experienced a 2-month period of drought following 3-months of growth under ambient moisture conditions. Fungal communities in the rhizosphere soil were analysed using DNA </span><span>amplicon</span><span> sequencing to link shifts in soil fungi to the observed PSF. We found that drought reduced negative PSF for all plant species except one species (</span><em><span>Lithocarpus lohangwu</span></em><span>)</span><span>. In the drought treatments, PSF were positively correlated with the relative abundance of total putative pathogens, but negatively correlated with the proportion of unique pathogens (those pathogens that were present in conspecific soil rather than heterospecific soil, thereby potentially species-specific). </span><span>In addition, we found that PSF </span><span>only significantly predicted plant relative abundance in the drought treatment, indicating that abiotic stress made PSF a stronger predictor of plant landscape abundance. This finding also implies that future extreme drought events could promote the dominance of the abundant plant species, thereby leading to the loss of biodiversity.</span><span> Collectively, our results provide evidence for microbial mechanisms of PSF and suggest that accounting for abiotic stress can make PSF a stronger predictor of plant landscape abundance due to the omnipresence of stress under natural conditions.</span></p>
Effects of soil conditioning, root and shoot litter addition interact to determine the intensity of plant-soil feedback (dataset)
<p>Plant-soil feedback (PSF) is recognized as an important mechanism shaping plant communities and determining plant abundance and coexistence. Under natural conditions, plants affect the outcome of plant-soil interactions simultaneously by conditioning the soil by living roots and by litter inputs into the soil. However, most experimental studies only focus on one of the pathways, which limits our understanding of PSF in the field. </p> <p>Here, we simultaneously explored the effect of soil conditioning by living roots and of root and shoot litter addition on the performance of seven <em>Impatiens</em> species grown in a two-phase garden experiment. </p> <p>Soil conditioning negatively affected plant performance and the effect was at least partly explained by nutrient depletion. Root litter addition affected plant performance negatively and the results suggest that biotic effects such as pathogen transmission via the root litter played a role. The effects of root litter addition were more pronounced in control soil which, contrary to the conditioned soil, supposedly did not accumulate pathogens during the conditioning phase. Shoot litter addition increased soil nutrient levels, but had no impact on plant performance. However, presence of shoot litter aggravated the negative effects of root litter, probably due to increased amounts of nutrients available for soil biota and thus their faster growth and intensified effect on the plants. </p> <p><span></span></p> <p>Overall, our study suggests that root and shoot litter have contrasting roles in plant-soil interactions and understanding their separate and interactive effects together with effects of soil conditioning is crucial for assessing the complexity of PSF.</p>
Data from: Plant-litter-soil feedbacks in common grass species are slightly negative and only marginally modified by litter exposed to insect herbivory
<p>Purpose Insect herbivory affects plant growth, nutrient and secondary metabolite concentrations and litter quality. Changes to litter quality due to insect herbivory can alter decomposition, with knock on effects for plant growth mediated through the plantlitter- soil feedback pathway. </p> <p>Methods Using a multi-phase glasshouse experiment, we tested how changes in shoot and root litter quality of fast- and slow-growing grass caused by insect herbivores affect the performance of response plants in the soil in which the litter decomposed. </p> <p>Results We found that insect herbivory resulted in marginal changes to litter quality and did not affect growth when plants were grown with fast- versus slow-growing litter. Overall, presence of litter resulted in reduced root and shoot growth and this effect was significantly more negative in shoots versus roots. However, this effect was minimal, with a loss of c. 1.4% and 3.1% dry weight biomass in roots versus shoots, respectively. Further, shoot litter exposed to insect herbivory interacted with response plant identity to affect root growth.</p> <p>Conclusions Our results suggest that whether litter originates from plant tissues exposed to insect herbivory or not and its interaction with fast- versus slow-growing grasses is of little importance, but species-specific responses to herbivory-conditioned litter can occur. Taken collectively, the overall role of the plant-litter-soil feedbackpathway, as well as its interaction with insect herbivory, is unlikely to affect broader ecosystem processes in this system.</p>
Database for meta-analysis of herbivore impacts on plant-soil feedbacks
<p class="MsoNormal"><span>We conducted a meta-analysis to test for an interaction between plant-soil feedbacks and herbivory, including effects on the magnitude and direction of feedbacks, herbivore consumption and herbivore growth.</span></p> <p class="MsoNormal"><em><span> </span></em><span>We identified 197 studies to address herbivore impacts on plant-soil feedbacks and 189 studies to address plant-soil impacts on herbivores. We calculated Hedge's D values to assess three questions: 1) What is the plant-soil feedback value of plants exposed to herbivory or no herbivory? 2) What is the growth or biomass of herbivores feeding on plants exposed to home or away soils in plant-soil feedback studies? 3) How much plant tissue is consumed by herbivores on plants grown in home or away soils?</span></p> <p class="paragraph"><em> </em></p> <p class="paragraph"><span class="normaltextrun">We found an overall significant weak negative effect of herbivory on plant-soil feedbacks that varied by plant functional type. In legumes herbivory drove plant-soil feedbacks from positive to negative, but herbivory on forbs further decreased </span><span class="eop">negative feedbacks</span><span class="normaltextrun">.</span><span class="eop"> </span><span class="normaltextrun"> Herbivore consumption was generally greater on plants grown in away soils. However, herbivore consumption was greater in home soils conditioned by legumes but lower in home soils conditioned by forbs.</span></p> <p class="paragraph"><em> </em></p> <p class="paragraph"><span class="eop">Therefore plant functional type determines the impact of conditioned soil on feedbacks, and herbivore consumption explains these results for legumes but not forbs. </span></p>
Online Appendix of "Crowd-based Requirements Elicitation via Pull Feedback: Method and Case Studies"
<p>The online appendix contains the data sets used in the paper Crowd-based Requirements Elicitation via Pull Feedback: Method and Case Studies, by Jelle Wouters, Abel Menkveld, Sjaak Brinkkemper and Fabiano Dalpiaz. It consists of three data sets, a process-deliverable diagram, a file that contains charts, and two Jupyter (Python) notebook scripts. In this readme, we briefly explain how files should be read and interpreted.</p> <p><strong>Dataset-Tournify.xlsx</strong></p> <p>This file contains all data of the Tournify case. The following tabs are present:</p> <ul> <li> <p>Raw data: contains the raw data collected from the Tournify CrowdRE platform.</p> </li> <li> <p>Automatically translated data: The readability and vagueness measures were calculated using English text. Most of the ideas collected were in Dutch, so the raw data was translated into English using a Google Translator API.</p> </li> <li> <p>Readability scores: Consists of the Flesch and ARI readability scores, calculated using the Python scripts (see below). </p> </li> <li> <p>Vague hits: Consists of all the vague words found in the Tournify ideas. We identified those using a Python script. Using numbers we identified whether the hit was a True Positive (TP) or was a false positive, and in which category the false positive lied. </p> </li> <li> <p>Tagging-50-FD & Tagging-50-JW: These tabs contain the tagging of the ideas on qualities of the QUS-framework and the ISO/IEC 25010. Two researchers did this independently from another.</p> </li> <li> <p>Compare-50: This sheet consists of all ideas for which a disparity exists between the two fields. When a disagreement exists, the field is colored green. By text in the field, we indicated what the final decision was. </p> </li> <li> <p>Result-50: This tab combines the results and shows the final decision after deliberation between the two authors.</p> </li> <li> <p>Tagging-195-FB, Tagging-195-JW, Compare-195, Result-195: Same as above, but for the other 195 ideas in the case (we split this data set in two to try out the modus operandi first).</p> </li> <li> <p>Result-total: Combines the Result-50 and the Result-195 sheet. Colored cells indicate that we marked the idea to be considered to present verbatim in the paper. </p> </li> <li> <p>Kappa-scores: Calculates the Kappa-scores that are presented in the paper.</p> </li> </ul> <p><strong>Dataset-SSys.xlsx and Dataset-VSys.xlsx</strong></p> <p><strong>This file contains all data for respectively the S-Sys and V-Sys cases. The following tabs are present:</strong></p> <ul> <li> <p>Raw data: consists of the raw data collected in the CrowdRE platform of the case. As can be seen, some data is ‘not published’ (but was analyzed in the study and read by both researchers and therefore just redacted in the online appendix), and some data is ‘classified’ (and therefore not analyzed by both researchers as one researcher was not allowed to review the data). The classified ideas should be considered as non-existent in the rest of the data set. </p> </li> <li> <p>Automatically translated data, readability scores: These files are compiled in the same way as in the Tournify case.</p> </li> <li> <p>Vagueness: This file is compiled in the same way as in the Tournify case, although we do provide a small explanation that describes a part of the idea to show why a true or false positive was indicated.</p> </li> <li> <p>Tagging: The tagging of the QUS-framework and ISO/IEC 25010 was done here. As we did this in person, the small discussion held when discrepancies occurred is not presented in the file. The colored cells indicate ideas we considered for verbatim publication in the paper. The colors indicate why we want to publish a certain idea (for example, because it has all QUS-violations).</p> </li> <li> <p>Kappa-scores: This shows the kappa scores and the discrepancies between the individual tagging. This is indicated in colors. </p> </li> </ul> <p><strong>Graphs_readability.aspx</strong></p> <p>This file was used to construct the graphs as presented in figures six and seven in the paper. For this, the readability scores of the three data sets were combined in one tab (one for Flesch and one for ARI) and used in a boxplot.</p> <p><strong>CREUS-pdd.drawio</strong></p> <p>This is the source file for the PDD presented in the paper.</p> <p><strong>Python scripts</strong></p> <p>Two Jupyter notebooks that "S-Sys V-Sys.ipynb" and "Tournify.ipynb" that we used to calculate the readability scores and to identify the vague words. As the data sets were structured a bit differently, the scripts are a bit different between the three cases. In the Tournify case, the script and the output are both present in the Jupyter notebook. For the S-Sys and V-Sys cases, we do include the script but omit the output due to confidentiality.</p> <p><strong>Note:</strong></p> <p>The data sets are included in our paper to allow readers to explore the data themselves. Please contact the corresponding author if you wish to use the data set for other reasons to obtain an explicit permission, since these user stories should be analyzed with proper domain knowledge in order to draw meaningful conclusions.</p>
Greenhouse plant-soil feedback experiment at Cedar Creek Ecosystem Science Reserve
<p>We conducted a reciprocal greenhouse experiment to examine how the growth of prairie grass species depended on the soil communities conditioned by conspecific or heterospecific plant species in the field. The source soil came from monocultures in a long-term competition experiment (LTCE, Cedar Creek Ecosystem Science Reserve, MN, USA). Within the LTCE, six species of perennial prairie grasses were grown in monocultures or in eight pairwise competition plots for 12 years under conditions of low and high soil nitrogen availability. In six cases, one species clearly excluded the other; in two cases, the pair appeared to coexist. In year 12, we gathered soil from all 12 soil types (monocultures of six species by two nitrogen levels) and grew seedlings of all six species in each soil type for seven weeks.</p>
Oyster IPM w/Positive Feedbacks - Data
<p>Data used in: </p> <p>Moore, J.L., Puckett, B., and Schreiber, S.J. Restoration of Eastern oyster populations with positive density dependence. <em>Submitted to Ecological Applications December 2017.</em></p>
Oyster IPM w/Positive Feedbacks - Code
<p>Code used in: </p> <p>Moore, J.L., Puckett, B., and Schreiber, S.J. Restoration of Eastern oyster populations with positive density dependence. <em>Submitted to Ecological Applications December 2017.</em></p>
Supplemental Materials to "A Fine-grained Taxonomy of Code Review Feedback in TypeScript Projects"
<p>Supplemental Materials to the paper "A Fine-grained Taxonomy of Code Review Feedback in TypeScript Projects".</p>
Qualitative Partners Feedback on the AIDOaRt Architecture
<p>In the European collaborative research project AIDOaRt, we specified an architecture to capture all the use case requirements and solution capabilities and provide a common ground for collaboration, solution development and use case implementation and validation. To capture the practical implication of our architecture quality, as perceived by its users, we collected our AIDOaRt partners' feedback through a survey. This data set includes the raw collected data as well as statistics, qualitative feedback analysis, and charts to facilitate the study of the dataset. We prepared The dataset and analysis results for publication in a journal article on the assessment of our architecture quality.</p>
LFM User Groups Implicit Feedback
<p>This is a variant of the popular LFM User Groups dataset [1] used in the paper "The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias" [2]. Each user's listening events for an artist are scaled to values between 1 and 5 (the user's min. value being 1 and the max. value being 5). Then, scores above the mean are considered positive feedback whereas scores below the mean are considered as negative feedback. This dataset only includes the positive feedback data. The source-code for generating this dataset is available in our repository [3].</p> <p>[1] https://zenodo.org/records/3475975</p> <p>[2] https://link.springer.com/chapter/10.1007/978-3-031-56066-8_33</p> <p>[3] https://github.com/pmuellner/ImpactOfDP</p>
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