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15 results for “community matrix”
COSI-Article matrix: linking ISCB Communities of Special Interest to Wikipedia
<p>Wikipedia is regarded as one of the most important channels for the public communication of science; English Wikipedia has around 1,500 articles relating to computational biology, which are frequently accessed as an educational resource. Joint efforts between the International Society for Computational Biology (ISCB) and the Computational Biology taskforce of WikiProject Molecular Biology (a group of expert Wikipedia editors) have considerably improved computational biology representation on Wikipedia in recent years. However, there is still an urgent need for further quality improvement, primarily while comparing to related scientific fields such as genetics and medicine. Facilitating the involvement of members from ISCB COSIs (Communities of Special Interest) would improve a vital open educational resource in computational biology, additionally allowing COSIs to provide a quality educational resource particular to their subfield.</p> <p>This first version of the COSI-Article matrix is a binary matrix identifying relevant ISCB COSIs for all Wikipedia articles relating to computational biology, defining a domain-specific open educational resource for each COSI. In addition, quality and importance ratings for each article allow identification of areas where domain experts could improve computational biology representation.</p>
SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream.
SI Figure 2: Compositional differences among bacterial microinvertebrate external and internal microbiomes as well as mats they were isolated from using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars show centroids of microbiome types for each animal host. All host microbiomes (internal and external) are distinct from mat communities (P<0.05), but external microbiomes are more similar to mats than internal microbiomes are to mats. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 2: Compositional differences among bacterial microinvertebrate external and internal microbiomes as well as mats they were isolated from using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars show centroids of microbiome types for each animal host. All host microbiomes (internal and external) are distinct from mat communities (P<0.05), but external microbiomes are more similar to mats than internal microbiomes are to mats.
Fig. 3 in Composition and structure of the helminth community of rodents in matrix habitat areas of the Atlantic forest of southeastern Brazil
Fig. 3. Bipartite plot of the interactions between the mammal hosts and the helminth parasites identified in the present study.
Fig. 2 in Composition and structure of the helminth community of rodents in matrix habitat areas of the Atlantic forest of southeastern Brazil
Fig. 2. Species accumulation curve of the helminths recorded in each mammalian host: a. Akodon cursor b. Mus musculus c. Necromys lasiurus.
Fig. 1 in Composition and structure of the helminth community of rodents in matrix habitat areas of the Atlantic forest of southeastern Brazil
Fig. 1. Location of the sampling sites within the REBIO Poço das Antas and the APA-BRSJ in Rio de Janeiro state (RJ), southeastern Brazil, showing the distribution of the different vegetation types and the canals that separate the two reserves.
Amazonian epiphytic bryophytes: community matrix and tools to assess diversity across scales
<p><strong><em>Aim: </em></strong>Tropical forests are highly diverse at many spatial scales. In these forests, epiphytic bryophyte communities can be species-rich already within a few cm<sup>2</sup>, and their species numbers increase when expanding the sampling along the tree and the forest. Understanding how this diversity increase depends on scale and position within the tree is critical to evaluate the processes that maintain biodiversity. We, therefore, studied vertical zonation and alpha and beta diversity of epiphytic bryophytes across spatial scales ranging from 100-cm<sup>2</sup> quadrats to 24 trees up to 10 km apart.</p> <p><strong><em>Location:</em></strong> Tropical lowland forest in Yasuní National Park (Amazonian Ecuador).</p> <p><strong><em>Methods:</em></strong> We sampled epiphytic bryophytes in 100-cm<sup>2</sup> quadrats on 24 trees (15-22 sampling quadrats per tree), using a spatially hierarchical design. We applied ordination, indicator species analysis, linear mixed models, and beta partitioning to study alpha and beta diversity at different spatial grains and extents.</p> <p><strong><em>Results:</em></strong> At the scale of quadrats, tree crowns held more bryophyte species than trunks. Contrastingly, all crown quadrats together held fewer species than all trunk quadrats together (77 vs. 93 species), as species turnover among trunk quadrats exceeded that among crown quadrats. Across spatial extents, species turnover consistently dominated beta diversity over nestedness. Beta diversity was higher between crowns and trunks within trees than among crowns of different trees at all studied scales, while beta diversity among trunks exceeded vertical diversity when considering all 24 trees.</p> <p><strong><em>Main conclusions:</em></strong> These bryophyte communities experience two distinct vertical zones, trunks and crowns, which differ more among them than trees up to 10 km apart. Still, high species turnover makes their species composition highly unpredictable, especially on trunks. Chance processes appear to play an important role in shaping these communities, although analyses at even finer spatial grains may identify the importance of fine-scale habitat filters and species interactions.</p>
Community Maturation Matrix (Illustration): Professionalising Community Management Roles in Interdisciplinary Research Projects
<p>Figure 1 (.jpg) file, editable version (.pptx) and supplementary 1 (.xlsx) for the research article: Professionalising Community Management Roles in Interdisciplinary Research Projects (July, 2024)</p> <p>Figure 1: Community Maturation Indicator: This is a framework through which maturation status for a community can be indicated at any given time as “Level of Community Participation” and “Stage of Community Building”. The Levels of Community Participation is shown in the x-axis (spanning 6 levels): Level 1: Inform Community, Level 2: Invite Feedback, Level 3: Engage and Involve, Level 4: Mobilise and Connect, Level 5: Empower Groups, and Level 6: Decentralise Power. The Stages of Community Building are shown as y-axis (spanning 6 stages): Stage 1: Initiation, Stage 2: Planning and Design, Stage 3: Implementation, Stage 4: Growth and Scaling, Stage 5: Monitoring and Evaluation, and Stage 6: Sustainability or Sunsetting. </p> <p>Supplementary 1: An example of how a community may progress its maturation levels. After the level has been identified, a CoP can start applying targeted approaches to community building, which occurs in stages. For example, at the community initiation stage of a new CoP, an RCM shares information and communicates project goals (Stage 1); at the planning and design stage, they build stakeholder awareness plans and help to prioritise specific objectives (Stage 2); at the implementation stage, they provide collaborative opportunities for specific stakeholders (Stage 3); at the growth stage, they facilitate knowledge exchange and skill building (Stage 4); and at the evaluation stage, it assesses the success of the CoP through feedback data to inform plans (Stage 5). These stages collectively affect how the project and its community can be sustained in the future or whether it should be paused (sunsetting) (Stage 6). RCMs build effective community strategies and implement creative approaches to support the development of a CoP, advancing a community from one stage to the next (Supplementary 1, Column 1 of the Community Maturation Indicators).</p> <p> </p>
Amazonian epiphytic bryophytes: community matrix and tools to assess diversity across scales
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Confocal microscopy images for: Surface remodeling and inversion of cell-matrix interactions underlie community recognition and dispersal in Vibrio cholerae biofilms
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Data from: Temporal stability versus community matrix measures of stability and the role of weak interactions
<p>Relationships between different measures of stability are not well understood in part because empiricists and theoreticians tend to measure different aspects and most studies only explore a single form of stability. Using time-series data from experimental plankton communities, we compared temporal stability typically measured by empiricists (coefficient of variation of biomass) to stability measures typically measured by theoreticians derived from the community matrix (asymptotic resilience, initial resilience, and intrinsic stochastic invariability) using first-order multivariate autoregressive models (MAR). Community matrices were also used to derive estimates of interaction strengths between plankton groups. We found no relationship between temporal stability and stability measures derived from the community matrix. Weaker interaction strengths were generally associated with higher stability for community matrix measures of stability but were not consistently associated with higher temporal stability. Temporal stability and stability measures derived from the community matrix stability appear to represent different aspects of stability reflecting the multi-dimensionality of stability.</p>
Data from: Multi-driver and multi-scale assessment of vine community structure and composition across a complex tropical environmental matrix
Ecological communities are structured by multiple processes operating at multiple scales yet understanding the scale-dependency of these processes remains an open challenge. This might be particularly true for parasites, for which biotic rather than abiotic processes may play a primary role in structuring communities. Focusing on vines, a group of structural parasites that gain access to the canopy using different climbing mechanisms, we examined the influence of abiotic factors in tandem with host-parasite and parasite-parasite interactions in the assembly of tropical vine communities. Two synthetic variables, namely Climate1 and landscape Variety, were consistently important in explaining variation in species richness and diversity, as well as species composition, but their importance varied with scale. Whereas Climate1 summarizes the largest variability among climatic variables, landscape Variety expresses landscape heterogeneity within a neighborhood. Significant patterns of species co-occurrences suggest that vine-vine interactions also contribute to vine community assembly. Our results may be critical to understand vine proliferation and help design management strategies for their control.
Data from: Temporal stability versus community matrix measures of stability and the role of weak interactions
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Data from: Multi-driver and multi-scale assessment of vine community structure and composition across a complex tropical environmental matrix
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Pinus halepensis_Community Matrix
<p>The initial document comprises the community matrix dataset, encompassing plant co-occurrences and abundances within pinewood-burned areas. This data was gathered through the strategic placement of 10 permanent plots, each spanning 100 m2. These plots were systematically positioned at a minimum distance of 100 m, ensuring they were situated 50 meters away from the periphery of the burned areas. For one year, from late winter to early autumn in 2022, we conducted four distinct sampling sessions, each occurring bi-monthly.</p><p>As for the second file, it encompasses various traits pertinent to the study of each species.</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)
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.