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17 results for “Community theory”
Costless renewable energy distribution model based on cooperative game theory for energy communities considering its members' active contributions
<p>This dataset was used in the case study of the following publication:</p> <p> - Luis Gomes, Zita Vale, "Costless renewable energy distribution model based on cooperative game theory for energy communities considering its members’ active contributions," Sustainable Cities and Society, Volume 101, 2024, 105060, ISSN 2210-6707, <a href="https://doi.org/10.1016/j.scs.2023.105060">https://doi.org/10.1016/j.scs.2023.105060</a> </p> <p><em>(if you used this dataset in your publications, please send us your information so we can add your publication to the list above)</em></p> <p> </p> <p>The dataset is composed by energy generation, consumption, and forecast (for generation, and for consumption) expressed in Wh. The data considers an energy community of 10 prosumers in 30 days.</p> <p>The dataset also has energy prices that have been collected from MIBEL (Iberian Electricity Market).</p> <p> </p> <p>We would be grateful if you could acknowledge the use of this dataset in your publications. Please use the Zenodo publication to cite this work.</p>
Data from: Metacommunity theory review and its application in community assembly of soil animals
<p>We were interested in community assembly of soil animals and performed a literature study to find out what is known about soil metacommunities. We aimed to study keywords co-occurrence relationships of scientific journal articles in the field of "metacommunity" research from 1992-2017 as a whole. We also investigated the co-occurrence of the top 20 most frequent keywords in five 5-year time periods.</p> <p> </p> <p> </p> <p>In September 2017 we searched the Web of Science with ‘metacommunity’ as the only keyword, and found 1226 English papers published in international journals between January 1992 and September 2017. And we exported these papers from Web of Science as a plain text file (.txt) with the option ‘Full Record and Cited References’, which is archived here. The text file thus contains full records and cited references (in a concise format, so without the titles of the cited papers), and each field is prefaced by a two-character field tag. Afterwards we used the software ‘Citespace’ to create Table 1 and Figure 2 in Guo et al. (2018). We created that Figure 2 using the following settings in Citespace: we choose the “co-occurrence” function and “keyword” as node types, then created keywords co-occurrence relationships (Figure 2). Next, we created lists of the top 20 keywords in different periods, which can reveal the research hotspots (Table 1). The method for extracting the top 20 most frequent keywords was as follows: We use the Web of Science database to retrieve scientific papers from 1992 to 2017, taking into account the relationship between citation and publication time. We calculated the percentage of 200 most cited papers published in each of the 5-year periods. To do so we followed the following steps:</p> <p>Step1: we selected the 200 most cited papers from the entire datset (1226 in the 1992-2017 period).</p> <p>Step 2: we calculated the percentage of those 200 papers published each 5-year period.</p> <p>Step 3: we also calculated an correction coefficient by taking, for each 5-year period, the number of top-200 most cited papers published in that period, and dividing that number by the total number of papers (out of the 1226 selected papers) published in that period.</p> <p>Step 4 Last, we calculate the real keyword frequency by multiplying the keyword frequency in specific 5-year periods with the correction coefficient.</p>
Influence of conspiracy theories and distrust of community health volunteers on adherence to COVID-19 guidelines and vaccine uptake in Kenya
<p>This cross-sectional study collected data between 25 May –27 June 2021 n=447. It involved all registered community health volunteers (CHVs) who had participated in the COVID-19 vaccine hesitancy study. This data was collected as part of an Epidemic Ethics/WHO initiative that FCDO/Wellcome Grant 214711/Z/18/Z has supported. WHO’s specific grant number was 2020/1077878-0). The funders had no role in study design, data collection and analysis, decision to publish, or manuscript preparation. No authors received a salary from the funders.</p>
How nitrogen and phosphorus supply to nutrient-limited autotroph communities affects herbivore growth: testing stoichiometric and co-limitation theory across trophic levels
<p><span>Primary producer communities are often growth-limited by essential nutrients such as nitrogen (N) and phosphorus (P). The magnitude of </span><span>limitation and whether N, P, or both elements are limiting autotroph </span><span>growth depends on the supply and ratios of these essential nutrients. </span><span>Previous studies identified single, serial or co-limitation as predominant </span><span>limitation outcomes in autotroph communities by factorial nutrient </span><span>additions. Little is known about potential consequences of such scenarios </span><span>for herbivores and whether their growth is primarily affected by changes </span><span>in autotroph quantity or nutritional quality. We grew a community of </span><span>phytoplankton species differing in various food quality aspects in </span><span>experimental microcosms at varying N and P concentrations resulting in </span><span>three different N:P ratios. At carrying capacity, N, P, both nutrients or </span><span>none were added to reveal which nutrients were limiting. The nutrient supplied </span><span>communities were fed to the generalist herbivorous rotifer </span><span>Brachionus calyciflorus to investigate how changing phytoplankton </span><span>biomass and community composition affect herbivore abundance. We </span><span>found phytoplankton being growth-limited either by N alone (single </span><span>limitation) or serially, i.e. primarily by N and secondarily by P, altering </span><span>available food quantity for rotifers. Rotifer growth showed a different </span><span>response pattern compared to phytoplankton, suggesting that apart from </span><span>food quantity food quality aspects played a substantial role in the </span><span>transfer from primary to secondary production. The combined addition of </span><span>N and P to phytoplankton had generally a positive effect on herbivore </span><span>growth, whereas adding non-limiting nutrients had a rather detrimental </span><span>effect probably due to stoichiometrically imbalanced food in terms of </span><span>nutrient excess. Our experiment shows that adding various nutrients to </span><span>primary producer communities will not always lead to increased </span><span>autotroph and herbivore growth, and that differences between autotroph </span><span>and herbivore responses under co-limiting conditions can be partly well </span><span>explained by concepts of ecological stoichiometry theory.</span></p>
How nitrogen and phosphorus supply to nutrient-limited autotroph communities affects herbivore growth: testing stoichiometric and co-limitation theory across trophic levels
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Data from: Applying community ecological theory to maximize productivity of cultivated biocrusts
Degraded rangelands around the world may benefit from the reestablishment of lost biological soil crusts (biocrusts, soil surface cryptogamic-microbial communities). Cultivation of biocrust organisms is the first step in this process, and may benefit from harnessing species interactions. Species interactions are a dominant force structuring ecological communities. One key element of community structure, species richness, is itself important because it can promote the productivity of the entire community. Here, we use biological soil crusts as a model to test the effects of species interactions on production of biocrust materials for use in ecosystem rehabilitation. We screened eight different moss and lichen species from semi-arid rangelands of Montana, USA, for growth potential under two watering regimes. Mosses generally grew well, but we were unable to cultivate the selected lichen species. We produced a >400% increase in the biomass of one species (Ceratodon purpureus). We tested whether a parasite-host relationship between two lichens could be used to enhance productivity of the parasite species, but this also resulted in no net gain of lichen productivity. Finally, we constructed all possible community combinations from a pool of five moss species to test for overyielding (community productivity exceeding that expected from the growth of community members in monoculture), and to determine both if, and the mode in which, species richness increases productivity. Polycultures yielded more than would be expected based upon the production of community constituents in monoculture. Using structural equation models we determined that there was a modest effect of species richness on community productivity (r = 0.24-0.25), which was independent of a stronger effect of the identity of species in the community (r = 0.41-0.50). These results will contribute to the optimization of biocrust cultivation, promoting the development of this emerging ecological rehabilitation technology.
Data from: Using community composition and successional theory to guide site-specific coral reef management
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Data from: Applying community ecological theory to maximize productivity of cultivated biocrusts
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Data from: Predicting community structure in snakes on Eastern Nearctic islands using ecological neutral theory and phylogenetic methods
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Data from: Multiresponse algorithms for community-level modeling: review of theory, applications, and comparison to species distribution models
1.Community-level models (CLMs) consider multiple, co-occurring species in model fitting and are lesser known alternatives to species distribution models (SDMs) for analyzing and predicting biodiversity patterns. CLMs simultaneously model multiple species, including rare species, while reducing overfitting and implicitly considering drivers of co-occurrence. Many CLMs are direct extensions of well-known SDMs and therefore should be familiar to ecologists. However, CLMs remain underutilized, and there have been few tests of their potential benefits and no systematic reviews of their assumptions and implementations. Here we review this emerging field and provide examples in R to fit common CLMs. Our goal is to introduce CLMs to a broader audience, and discuss their attributes, benefits, and limitations relative to SDMs. 2.We review i) statistical implementations and applications of CLMs, ii) their advantages and limitations, and iii) comparative analyses of CLMs and SDMs. We also suggest directions for future research. 3.We identify seven CLM algorithms with similar data structures and predictive outputs as SDMs that should be most accessible to ecologists familiar with species-level modeling, including five methods that predict assemblage composition and individual species distributions and two methods that model compositional turnover along environmental gradients. CLMs have been applied to numerous taxa, regions, and spatial scales, and a variety of topics (e.g., studying drivers of community structure or assessing relationships between community composition and functional traits). Studies suggest that the relative benefits of CLMs and SDMs may be case specific, especially in terms of predicting species distributions and community composition. However, CLMs may offer advantages in terms of computational efficiency, modeling rare species, and projecting to no-analog climates. A major shortcoming of CLMs is their reliance on presence-absence community composition data. 4.Studies are needed to assess the relative merits of SDMs and CLMs, and different CLM algorithms, with a focus on three key areas: i) under which circumstances CLMs improve predictions for rare species, ii) how CLMs perform under different community compositions (e.g. relative abundance of rare vs. common species), including the extent to which co-occurrence patterns are structured by biotic interactions, and iii) ability to project across time/space.
Data from: Multiresponse algorithms for community-level modeling: review of theory, applications, and comparison to species distribution models
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The application of community ecology theory to co-infections in wildlife hosts
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Data from: The theory of island biogeography and soundscapes: species diversity and the organization of acoustic communities
Aim: On islands, species richness is reduced and interspecific competition relaxed in relation to the mainland, allowing species to use broader ecological niches. These factors are known to affect diet and morphology, but can also affect communication and acoustic signaling in particular. However, no study has ever compared insular and continental soundscapes to determine to which extent islands present reduced acoustic richness (number of co-vocalizing species) and fewer constraints for vocalizing species. Location: São Tomé Island, Mount Cameroon, Madeira Island, Southern France Taxon: Birds Methods: We compared two pairs of insular and continental soundscapes: one in a temperate zone, the other in the tropics. We recorded sounds produced in similar types of primary forests and measured acoustic richness and ambient noise profiles. We then assessed acoustic niche organization by computing, for each community, species turnover, temporal and frequency overlaps, and acoustic avoidance. Results: We found fewer species co-vocalizing on islands compared to mainland and in temperate compared to tropical region. Ambient noise was louder in the tropics and occupied a wider frequency range, especially on the mainland, thereby revealing a reduction in available acoustic space for tropical mainland birds. In this more crowded and noisy soundscape, species presented a higher acoustic turnover, overlapped less in time and in frequency with each other and acoustically avoided each other more when compared to the three other communities. Main conclusions: Soundscapes differed and imposed fewer constraints on vocalizing species along the species diversity gradient from tropical mainland to temperate island. Acoustic niche partitioning increased with species richness and was associated with increased levels of acoustic interference. Results set a scene for an effect of relaxed competition on song evolution on islands, especially in the tropics.
Theory Based Integrated Program on Medication Adherence Among Community Dwelling Schizophrenia
ClinicalTrials.gov study NCT05835583. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Digital Technology Combined With Blood Marker Screening and Diagnosis for Community Populations Based on Classification Theory: an Integrated Study
ClinicalTrials.gov study NCT07286812. IPD Sharing: YES. Countries: 1. Publications: 0.
A Theory-driven Visual Arts-based Intervention for Community-dwelling Stroke Survivors
ClinicalTrials.gov study NCT05806658. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: The theory of island biogeography and soundscapes: species diversity and the organization of acoustic communities
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.