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.
176
datasets available to search
ShareScore release 0.9.0
Dataset results
176 results for “Biological communities”
Figure 5 from: Souza Silva M, Iniesta LFM, Ferreira RL (2020) Invertebrates diversity in mountain Neotropical quartzite caves: which factors can influence the composition, richness, and distribution of the cave communities? Subterranean Biology 33: 23-43. https://doi.org/10.3897/subtbiol.33.46444
Figure 5 Metric multidimensional scaling (MDS) ordination plot of the 20 quartzite caves with and without a stream using bootstrap regions for group means around their centroids (triangles). Average (Av).
Figure 1 from: Souza Silva M, Iniesta LFM, Ferreira RL (2020) Invertebrates diversity in mountain Neotropical quartzite caves: which factors can influence the composition, richness, and distribution of the cave communities? Subterranean Biology 33: 23-43. https://doi.org/10.3897/subtbiol.33.46444
Figure 1 Borders of the Ibitipoca Estadual Park (A), sampled caves (white dots) and altitudinal layers (red lines 1610–1780, blue lines 1460–1600, yellow lines 1310–1450, green lines 1124–1450, black lines 950–1100 meters). Vegetation types vary from slope forest (B) to grasslands (D and C) on the top of the hills.
Figure 4 from: Souza Silva M, Iniesta LFM, Ferreira RL (2020) Invertebrates diversity in mountain Neotropical quartzite caves: which factors can influence the composition, richness, and distribution of the cave communities? Subterranean Biology 33: 23-43. https://doi.org/10.3897/subtbiol.33.46444
Figure 4 Distance-based redundancy analysis (dbRDA) showing the influences of the environmental factors on cave fauna composition in the 20 studied caves. The two axes explained nearly 55% of the variability in the fitted model and nearly 17% of the total variation in the data cloud. The first overlay shows how the first dbRDA axis is strongly related to cave sampled extension.
Biological Data and Carbonate Chemistry used in 'Ocean acidification locks algal communities in a species-poor early successional stage'
<p>Long-term exposure to CO<sub>2</sub>-enriched waters can considerably alter marine biological community development, often resulting in simplified systems dominated by turf algae that possess reduced biodiversity and low ecological complexity. Current understanding of the underlying processes by which ocean acidification alters biological community development and stability remains limited, making the management of such shifts problematic. Here, we deployed recruitment tiles in reference (pH<sub>T</sub> 8.137 ± 0.056 SD) and CO<sub>2</sub>-enriched conditions (pH<sub>T</sub> 7.788 ± 0.105 SD) at a volcanic CO<sub>2</sub> seep in Japan in order to assess the underlying processes and patterns of algal community development. We assessed (i) algal community succession in two different seasons (Cooler months: January–July, and warmer months: July–January), (ii) the effects of initial community composition on subsequent community succession (by reciprocally transplanting pre-established communities for a further six months), and (iii) the community production of the resulting communities, in order to assess how their functioning is altered (following 12 months recruitment). Settlement tiles became dominated by turf algae under CO<sub>2</sub>-enrichment and had lower biomass, diversity and complexity, a pattern consistent across seasons, which locked the community in a species-poor early successional stage. In terms of community functioning, the elevated <em>p</em>CO<sub>2</sub> community exhibited greater net community production, and yet this apparent boost did not result in increased algal community cover, biomass, biodiversity or structural complexity. Taken together, this shows that both new and established communities become simplified with rising CO<sub>2</sub> levels. Our transplant of pre-established communities from enriched-CO<sub>2</sub> to reference conditions demonstrated their high resilience, since they became indistinguishable from communities maintained entirely in reference conditions. This shows that meaningful reductions in <em>p</em>CO<sub>2</sub> will enable the recovery of algal communities. By understanding the ecological processes responsible for driving shifts in community composition, we can better assess how communities are likely to be altered by ocean acidification.</p>
Biological productivity and community structure of phytoplankton in the oligotrophic Philippine Sea
<p>In the Philippine Sea, mesoscale eddies have been frequently observed, but little is known about their contributions to the biological productivity and community structure of phytoplankton in the region. In situ carbon and nitrogen uptake rates and phytoplankton community structure were investigated in the Philippine Sea based on the 13C-15N dual-tracer technique and photosynthetic pigment analysis from late August to September 2018. Based on the comparison of the phytoplankton community structure among the cold eddy, warm eddy, and outer area, we found that the phytoplankton composition was different in the warm eddy with relatively lower contributions of large phytoplankton. However, a distinct enhancement in phytoplankton biomass over the euphotic zone was not detected even in eddy occurrence. In terms of community, the picoplankton Prochlorococcus was persistently dominant, which was attributed to a low supply and chemical composition of nutrients. The average integrated primary productions (IPP) were 80.4, 75.9, and 76.3 mg C m−2 d−1 for the cold eddy, warm eddy, and outer area, respectively. The IPP under the eddy condition was not largely different from that in reference sites, even though the vertical distribution of productivity maximum was found to be different depending on eddy condition. These weak biological responses to mesoscale eddies might be attributed to the sustaining picoplankton-dominant community structure and no substantial upward inputs of nutrients to the euphotic zone. Our findings represent an important contribution to understanding the biological response of mesoscale eddies in the oligotrophic Philippine Sea.</p>
Supplementary material 1 from: Brasell KA, Pochon X, Howarth J, Pearman JK, Zaiko A, Thompson L, Vandergoes MJ, Simon KS, Wood SA (2022) Shifts in DNA yield and biological community composition in stored sediment: implications for paleogenomic studies. Metabarcoding and Metagenomics 6: e78128. https://doi.org/10.3897/mbmg.6.78128
Figures S1–S4
Supplementary material 2 from: Brasell KA, Pochon X, Howarth J, Pearman JK, Zaiko A, Thompson L, Vandergoes MJ, Simon KS, Wood SA (2022) Shifts in DNA yield and biological community composition in stored sediment: implications for paleogenomic studies. Metabarcoding and Metagenomics 6: e78128. https://doi.org/10.3897/mbmg.6.78128
Table S1
Figure 4 from: Mammola S, Piano E, Giachino PМ, Isaia M (2017) An ecological survey of the invertebrate community at the epigean/hypogean interface. Subterranean Biology 24: 27-52. https://doi.org/10.3897/subtbiol.24.21585
Figure 4 - Annual trends of temperatures in the Pugnetto hypogean complex. The shade of blues indicate the relative position of the dataloggers at each cave-triplet, from the outermost (lighter blues) to the innermost sections (darker blues). Records from only one MSS-triplet are shown.
Figure 3 from: Mammola S, Piano E, Giachino PМ, Isaia M (2017) An ecological survey of the invertebrate community at the epigean/hypogean interface. Subterranean Biology 24: 27-52. https://doi.org/10.3897/subtbiol.24.21585
Figure 3 - a sampling holes (details) b Blocking screw c installation of an MSS-triplet d SSD of three different length e MSS-triplet buried in the ground f, g renewing the pitfall trap inside the SSD. Photo credits: Elena Piano.
Figure 2 from: Mammola S, Piano E, Giachino PМ, Isaia M (2017) An ecological survey of the invertebrate community at the epigean/hypogean interface. Subterranean Biology 24: 27-52. https://doi.org/10.3897/subtbiol.24.21585
Figure 2 - Map of the study area. The shape and the topographic position of the four caves (Borna Maggiore di Pugnetto, Tana del Lupo, Creusa d'le Tampe, Tana della Volpe) was obtained from the original planimetric drawings of Muratore (1946). The position of the sampling plots in caves ("cave triplets", C1–C8), in the MSS ("MSS triplets", M1–M8) and in the leaf litter ("epigean", L1–L6) are represented by coloured dots. The different sectors of the cave are coloured with different shades of grey representing the subjacency – i.e., vertical distance from the surface – according to Motta and Motta (2015).
Figure 6 from: Mammola S, Piano E, Giachino PМ, Isaia M (2017) An ecological survey of the invertebrate community at the epigean/hypogean interface. Subterranean Biology 24: 27-52. https://doi.org/10.3897/subtbiol.24.21585
Figure 6 - Predicted values (black line) and 95% confidence intervals (grey surface) of the effect of the sampling series (Serie_i) on the abundance of external elements in the MSS (a), on the species richness of external elements in the MSS (b) and on the abundance of external elements in the cave at subjacency of 0–20m (c) derived from GAMM analyses. Only fixed effects are shown.
Figure 1 from: Mammola S, Piano E, Giachino PМ, Isaia M (2017) An ecological survey of the invertebrate community at the epigean/hypogean interface. Subterranean Biology 24: 27-52. https://doi.org/10.3897/subtbiol.24.21585
Figure 1 - a Main entrance of the Borna di Pugnetto (photo credit: Alberto Chiarle and Mauro Paschetta, 2014) b Main entrance of the Creusa d'le Tampe (photo credit: Elena Piano, 2013) c exposed soil/MSS profile in a fresh-cut along a slope in the vicinity of the Borna di Pugnetto (photo credit: Jacopo Orlandini, 2014) d the typical cave geo-morphology within the Borna di Pugnetto (photo credit: Alberto Chiarle and Mauro Paschetta, 2014) e detail of the MSS geo-morphological structure (photo credit: Jacopo Orlandini, 2014).
Figure 5 from: Mammola S, Piano E, Giachino PМ, Isaia M (2017) An ecological survey of the invertebrate community at the epigean/hypogean interface. Subterranean Biology 24: 27-52. https://doi.org/10.3897/subtbiol.24.21585
Figure 5 - Boxplots showing the results of the regression analysis of the MSS (a–c) and the cave (d–f) data. Outlying values are not shown. Significance codes: < 0.001 ***; < 0.005 **; < 0.05 *.
Figure 4 from: Mammola S, Isaia M (2018) Day–night and seasonal variations of a subterranean invertebrate community in the twilight zone. Subterranean Biology 27: 31-51. https://doi.org/10.3897/subtbiol.27.28909
Figure 4 Interaction plot showing the effect of the interaction between seasonality and the day–night cycle on the abundance of trogloxenes.
Figure 3 from: Mammola S, Isaia M (2018) Day–night and seasonal variations of a subterranean invertebrate community in the twilight zone. Subterranean Biology 27: 31-51. https://doi.org/10.3897/subtbiol.27.28909
Figure 3 Boxplots showing the difference between relative humidity values during the day (white boxes) and at night (grey boxes) in the four seasons. Significant differences are highlighted by asterisks (Signif. codes: *** p<0.001, ** p<0.01).
Figure 2 from: Mammola S, Isaia M (2018) Day–night and seasonal variations of a subterranean invertebrate community in the twilight zone. Subterranean Biology 27: 31-51. https://doi.org/10.3897/subtbiol.27.28909
Figure 2 Temperature variation in the study area. Data refer to record of temperature and relative humidity measured every 12 h (one measurement at midday and one at midnight). Top panel: annual trends of temperatures measured at the entrance (0 m; orange line) and inside the mine (10 and 20 m; purple and blue lines, respectively). Bottom panel: mean of monthly positive and negative temperature deviations at night, with respect to the daily temperature recorded during the same period.
Figure 1 from: Mammola S, Isaia M (2018) Day–night and seasonal variations of a subterranean invertebrate community in the twilight zone. Subterranean Biology 27: 31-51. https://doi.org/10.3897/subtbiol.27.28909
Figure 1 Map of the study area and groundplan of the Seinera mine, with indication of sampling plots and dataloggers.
Figure 5 from: Mammola S, Isaia M (2018) Day–night and seasonal variations of a subterranean invertebrate community in the twilight zone. Subterranean Biology 27: 31-51. https://doi.org/10.3897/subtbiol.27.28909
Figure 5 Predicted values (filled lines) and 95% confidence intervals (dotted lines) of the effect of distance from the main entrance in interaction with the sampling season on the abundance of troglophiles derived from the generalized linear mixed model (GLMM). Day and night trends are shown.
Figure 5 from: Simões MH, Souza-Silva M, Ferreira RL (2015) Cave physical attributes influencing the structure of terrestrial invertebrate communities in Neotropics. Subterranean Biology 16: 103-121. https://doi.org/10.3897/subtbiol.16.5470
Figure 5 - Non-metric multidimensional scaling (Jaccard index) using presence and absence of species sampled in 55 limestone caves of the Brazilian Savannah. The figure shows that the cave, despite dry most of the year, is subject to seasonal flooding (Deus Me Livre cave), and then was more similar to caves with streams.
Figure 4 from: Simões MH, Souza-Silva M, Ferreira RL (2015) Cave physical attributes influencing the structure of terrestrial invertebrate communities in Neotropics. Subterranean Biology 16: 103-121. https://doi.org/10.3897/subtbiol.16.5470
Figure 4 - Correlation between the richness of troglomorphic species and linear development and water body presence/absence. The barr represents the average and the trace the standard deviation. Different letters indicate significant differences in average richness.
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.