Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
12
datasets available to search
ShareScore release 0.9.0
Dataset results
12 results for “Environmental matrix”
Data from: Sorting states of environmental DNA: Effects of isolation method and water matrix on recovery of membrane-bound, dissolved, and adsorbed states of eDNA
<p>Environmental DNA (eDNA) once shed can exist in numerous states with varying behaviors including degradation rates and transport potential. In this study we consider three states of eDNA: 1) a membrane-bound state referring to DNA enveloped in a cellular or organellar membrane, 2) a dissolved state defined as the extracellular DNA molecule in the environment without any interaction with other particles, and 3) an adsorbed state defined as extracellular DNA adsorbed to a particle surface in the environment. Capturing, isolating, and analyzing a target state of eDNA provides utility for better interpretation of eDNA degradation rates and transport potential. While methods for separating different states of DNA have been developed, they remain poorly evaluated due to the lack of state-controlled experimentation. We evaluated the methods for separating states of eDNA from a single sample by spiking DNA from three different species to represent the three states of eDNA as state-specific controls. We used chicken DNA to represent the dissolved state, cultured mouse cells for the membrane-bound state, and salmon DNA adsorbed to clay particles as the adsorbed state. We performed the separation in three water matrices, two environmental and one synthetic, spiked with the three eDNA states. The membrane-bound state was the only state that was isolated with minimal contamination from non-target states. The membrane-bound state also had the highest recovery (54.11 ± 19.24 %), followed by the adsorbed state (5.08 ± 2.28 %), and the dissolved state had the lowest total recovery (2.21 ± 2.36 %). This study highlights the potential to sort the states of eDNA from a single sample and independently analyze them for more informed biodiversity assessments. However, further method development is needed to improve recovery and reduce cross-contamination.</p>
Data from: Sorting states of environmental DNA: Effects of isolation method and water matrix on recovery of membrane-bound, dissolved, and adsorbed states of eDNA
Open the record for dataset details and reuse information.
Species matrix of Indonesian litter and soil Collembola with environmental factors
<p>Collembola are among the most abundant and diverse microarthropods that affect litter decomposition, control microbial functioning and support invertebrate predators. Rainforest conversion and expansion of plantations in tropical regions are associated with changes in microclimate and biodiversity decline, but information on the impact of tropical land use on Collembola communities and their seasonal fluctuations is very limited. Here, we investigated seasonal fluctuations in density and community composition of Collembola in rainforest, and in rubber and oil palm plantations in Jambi province (Sumatra, Indonesia), a region with moderate seasonality (wet and dry seasons) that experienced one of the strongest deforestations globally during the last decades. Samples were taken at the end of the wet season (March), the beginning of the dry season (June), the end of the dry season (August) and the beginning of the wet season (November). Collembola density in the litter was at a maximum at the beginning of the wet season, whereas in soil it generally varied little. Densities of euedaphic (soil-adapted) and epedaphic species (upper litter-adapted) fluctuated less with season than hemiedaphic (lower litter-adapted) and atmobiotic species (aboveground-adapted). Collembola community composition changed with season in each of the land-use systems, with the differences being more pronounced in litter than in soil. Differences in community composition among all three land-use systems were most pronounced at the beginning of the dry season. Water content, pH, fungal and bacterial biomarkers, C/N ratio and root biomass were identified as factors related to seasonal variations in species composition of Collembola in different systems. Our results show that Collembola density and community composition often fluctuate in a similar way across land-use systems, indicating that they are driven by common environmental factors, with water content, pH and food availability being of prominent importance. Notably, differences in Collembola community composition between rainforest and plantation systems were most pronounced in the dry season (June, August), indicating that the conversion of rainforest into plantation systems aggravates detrimental effects of low moisture on soil animal communities. Fluctuations in Collembola communities were generally stronger in litter than in soil, reflecting that Collembola in litter are less buffered against climatic variations than those in soil. Overall, the results document the sensitivity of tropical soil animal communities to seasonal climatic variations, which <span>intensifies</span> the effects of the conversion of rainforest into plantation systems on soil biodiversity.</p>
Species matrix of Indonesian litter and soil Collembola with environmental factors
Open the record for dataset details and reuse information.
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.
Indonesian soil and litter Collembola species and trait matrix with environmental data
<p>Rainforest conversion and expansion of plantations in tropical regions is associated with changes in animal communities and biodiversity decline. In soil, Collembola are one of the most numerous invertebrate groups that control microbial processes and support arthropod predators. Despite that, information on the impact of changes in land use in the tropics on species and trait composition of Collembola communities is very limited. We investigated the response of Collembola to the conversion of rainforest into rubber agroforest ('junge rubber'), rubber and oil palm plantations in Jambi province (Sumatra, Indonesia), a region that experienced one of the strongest deforestation globally during the last decades. Collembola from litter and soil layers were collected in 2013 and 2016 using heat extraction. In the litter layer, density and species richness in plantation systems declined by 25-38% and 30-40%, respectively, compared to rainforest. By contrast, in the soil layer, density, species richness and trait diversity of Collembola were only slightly affected by land-use change contrasting the response of many other animal groups. Species and trait composition of Collembola communities in litter and soil layers differed between all land-use systems. Water content and pH were identified as main factors related to the differences in species and trait composition both in litter and soil layers, followed by the density of micro- and macropredators. Dominant Collembola species in rainforest and jungle rubber were characterized by small body size, absence of furca and absent or intense pigmentation, while in plantations larger species with long furca and diffuse or patterned coloration were more abundant. The trait-based responses were similar to those observed in Collembola from temperate regions and to those in a similar study on spiders at our study sites. Overall, land-use change negatively affected Collembola communities in the litter layer, but only little affected Collembola communities in soil. Several pantropical Collembola genera (i.e., <i>Isotomiella</i>, <i>Pseudosinella</i> and <i>Folsomides</i>) dominated across land-use systems, reflecting their high environmental adaptability or efficient dispersal calling for studies on their ecology and genetic diversity. The decline in species richness and density of litter-dwelling Collembola with the conversion of rainforest into plantation systems calls for management practices mitigating negative effects of the deterioration of the litter layer in rubber but in particular in oil palm plantations.</p>
Indonesian soil and litter Collembola species and trait matrix with environmental data
Open the record for dataset details and reuse information.
Data from: Multi-driver and multi-scale assessment of vine community structure and composition across a complex tropical environmental matrix
Open the record for dataset details and reuse information.
Data from: Environmental effects on the structure of the G-matrix
Genetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. While individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance-covariance (G) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between-environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between-population differences. Neither environmental novelty nor the difference in mean phenotype predicted these differences in G. Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments.
Chinook salmon environmental data and allele frequency matrix
<p><span><span><span><span><span><span><span><span><span><span><span>Many species that undergo long breeding migrations, such as anadromous fishes, face highly heterogeneous environments along their migration corridors and at their spawning sites. These environmental challenges encountered at different life stages may act as strong selective pressures and drive local adaptation. However, the relative influence of environmental conditions along the migration corridor compared to the conditions at spawning sites on driving selection is still unknown. In this study, we performed genome-environment associations (GEA) to understand the relationship between landscape and environmental conditions driving selection in seven populations of the anadromous Chinook salmon (<i>Oncorhynchus tshawytscha)–</i>a species of important economic, social, cultural and ecological value–in the Columbia River basin. We extracted environmental variables for the shared migration corridors and at distinct spawning sites for each population, and used a Pool-seq approach to perform whole genome resequencing. Bayesian and univariate genome-environment association tests with migration-specific and spawning site-specific environmental variables indicated many more candidate SNPs associated with environmental conditions of the migration corridor compared to spawning sites. Specifically, variables associated with temperature, precipitation, terrain roughness, and elevation variables of the migration corridor were the most significant drivers of environmental selection. Additional analyses of neutral loci revealed two distinct clusters representing populations from different geographic regions of the drainage that also exhibit differences in adult migration timing (summer vs. fall). Tests for genomic regions under selection revealed a strong peak on chromosome 28, corresponding to the GREB1L/ROCK1 region that has been identified previously in salmonids as a region associated with adult migration timing. Our results show that environmental variation experienced throughout migration corridors imposed a greater selective pressure on Chinook salmon than environmental conditions at spawning sites.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Environmental effects on the structure of the G-matrix
Open the record for dataset details and reuse information.
Chinook salmon environmental data and allele frequency matrix
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.