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11,506 results for “Dynamics”
Data from: Compensatory dynamics of lotic algae break down nonlinearly with increasing nutrient enrichment
<p>One important mechanism governing the temporal maintenance of biodiversity is asynchrony in cooccurring competitors due to fluctuating environments (i.e. compensatory dynamics). Temporal niche partitioning has evolved in response to predictable oscillations in environmental conditions so that species may offset competition, but we do not yet have a clear understanding of how novel anthropogenic stressors alter seasonal patterns of succession. Many primary producers are nutrient-limited, and enrichment may decrease the importance of environmental fluctuations that govern which species are effective competitors under naturally low nutrient regimes. Consequently, elevated nutrient concentrations may synchronize species responses to seasonality. By studying benthic algal assemblages over two years from 35 streams that spanned a wide gradient of nutrient enrichment, we found that compensatory dynamics characterizing seasonal succession under natural nutrient regimes broke down at relatively low levels of total phosphorus (P) enrichment (~ 25 μg L<sup>-1</sup>). With increasing P more species were able to coexist at any given time, and seasonal variation in assemblage composition was characterized by synchronous swings in species biovolumes. We also observed much higher instability in assemblage biovolumes with declines in compensatory dynamics, which indicates that anthropogenic alteration of nutrient regimes can affect community stability by changing the dominant mode of seasonal succession. Our findings indicate that compensatory fluctuations of stream algae are driven by seasonality, and provide insight about how nutrient enrichment alters evolved drivers of species coexistence.</p>
Optimizing Continuous Integration by Dynamic Test Selection
<p>Replication package include source code and dataset.</p>
Supplementary material 6 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
SIMPER Analysis
Supplementary material 4 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Richness and abundance of Baraccone Cave invertebrate fauna
Supplementary material 3 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Monthly temperature, relative humidity and light intensity in Baraccone Cave for each sampling area
Supplementary material 2 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Fauna observed in Baraccone Cave
Supplementary material 5 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Percentage of minerals found in each sampling area
Figure 5 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Figure 5 A trend of Equitability (Pielou's evenness), Dominance (1-Simpson index) and Shannon diversity (H) indices from March 2017 to March 2018 B rarefaction curve (in red). In blue the 95% confidence interval.
Supplementary material 1 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Information on the study area
Figure 3 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Figure 3 A one-Way ANOSIM test. Wall in eight sites (A-H, Group 1–8), Ground in seven sites (A-E and G-H, Group 9–15) B similarity between ground (from AG to HG) and wall (from AW to HW) faunal samples (UPGMA clustering based on Jaccard similarity index - bootstrap values are shown under each node) C SIMPER Analysis. Taxa responsible for the observed differences between faunal assemblages in different sampling areas in percentage.
Figure 2 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Figure 2 Canonical Correspondence Analysis. Hypogean fauna related to environmental factors and mineral substratum A classes of ground fauna B orders of ground fauna (Arachnida, Entognatha and Insecta) with a number of specimens exceeding 5% of each considered class total C classes of parietal fauna D orders of parietal fauna (Arachnida and Insecta) with a number of specimens exceeding 5% of each considered class total.
Figure 1 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Figure 1 A Location of Baraccone Cave, Piedmont, Italy, and the entrance of the cave (photo by E. L.) B baraccone Cave map with monitoring areas. Red quadrats for ground fauna monitoring and blue triangles for parietal fauna monitoring (map by V. B. and R. Sella, photos by E. L. and V. B.).
Figure 4 from: Lessel T, Marx M, Eisenbeis G (2011) Effects of ecological flooding on the temporal and spatial dynamics of carabid beetles (Coleoptera, Carabidae) and springtails (Collembola) in a polder habitat. ZooKeys 100: 421-446. https://doi.org/10.3897/zookeys.100.1538
Figure 4 - Mean number of individuals of hygrophilic (A/B) and xerophilic/mesophilic (C/D) carabid beetle species at the fallow (A/C) and ruderal area (B/D) during different moisture conditions. Abbreviations: ef = ecological flooding (higher Rhine water levels); spe = flood caused by a strong precipitation event; dc = drought conditions; ° outliers. Different letters represent statistically significant differences (Mann-Whitney U-test).
Figure 3 from: Lessel T, Marx M, Eisenbeis G (2011) Effects of ecological flooding on the temporal and spatial dynamics of carabid beetles (Coleoptera, Carabidae) and springtails (Collembola) in a polder habitat. ZooKeys 100: 421-446. https://doi.org/10.3897/zookeys.100.1538
Figure 3 - Mean number of individuals per trap and day (± SE) and total carabid beetle species number at location 1 (fallow area) and location 6 (ruderal area) (n=3) during the vegetation period of 2008. Hygrophilic species (black bars) and xerophilic as well as mesophilic species (grey bars) are shown. Abbreviations: ef = ecological flooding; spe = strong precipitation event.
Figure 1 from: Lessel T, Marx M, Eisenbeis G (2011) Effects of ecological flooding on the temporal and spatial dynamics of carabid beetles (Coleoptera, Carabidae) and springtails (Collembola) in a polder habitat. ZooKeys 100: 421-446. https://doi.org/10.3897/zookeys.100.1538
Figure 1 - Location of the polder "Ingelheim" in Germany and location of the different areas and pitfall trap localities (L1–L6) within this polder (A). Abbreviations: LA 0: ruderal area; HB 0: fallow area; LA 0 + HB 0: transition area between LA 0 and HB 0; HA 0: agricultural fields; L1–6: locations of the six pitfall trap groups (three pitfall traps per locality). The pictures show the main flood gate (left) and the ecological flood gate (right), and an ecological flooding in March 2007 (B) and the fast drying event in the ruderal area after ecological flooding in April 2007 (C).
Figure 6 from: Lessel T, Marx M, Eisenbeis G (2011) Effects of ecological flooding on the temporal and spatial dynamics of carabid beetles (Coleoptera, Carabidae) and springtails (Collembola) in a polder habitat. ZooKeys 100: 421-446. https://doi.org/10.3897/zookeys.100.1538
Figure 6 - PCA of springtail communities in the fallow area (location 1) and the ruderal area (location 6) during ecological flooding, the flood caused by a strong precipitation event and drought conditions. Only species with more than 1% dominance value in at least one area are included. Abbreviations of the species: I.pal=Isotomurus palustris; I.vir=Isotoma viridis; L.cya=Lepidocyrtus cyaneus; O.vil=Orchesella villosa; P.aqu=Podura aquatica; S.aqu=Sminthurides aquaticus. Percentage variation explained by the two PCA axes are included.
Figure 2 from: Lessel T, Marx M, Eisenbeis G (2011) Effects of ecological flooding on the temporal and spatial dynamics of carabid beetles (Coleoptera, Carabidae) and springtails (Collembola) in a polder habitat. ZooKeys 100: 421-446. https://doi.org/10.3897/zookeys.100.1538
Figure 2 - PCA of carabid beetle communities in the fallow area (location 1) and the ruderal area (location 6) during ecological flooding, the flood caused by a strong precipitation event and drought conditions. Only species with more than 1% dominance value in at least one area are included. Abbreviations of the species: A.mar=Agonum marginatum; A.bif=Amara bifrons; A.sim=Amara similata; B.lam=Bembidion lampros; B.pro=Bembidion properans; B.qua=Bembidion quadrimaculatum; C.pur=Carabus purpurascens; H.aff=Harpalus affinis; H.ruf=Harpalus rufipes; H.sma=Harpalus smaragdinus; N.bre=Nebria brevicollis; O.ard=Ophonus ardosiacus; P.cup=Poecilus cupreus; P.ant=Pterostichus anthracinus; P.mel=Pterostichus melanarius; P.nig=Pterostichus nigrita. Percentage variation explained by the two PCA axes is included.
Figure 5 from: Lessel T, Marx M, Eisenbeis G (2011) Effects of ecological flooding on the temporal and spatial dynamics of carabid beetles (Coleoptera, Carabidae) and springtails (Collembola) in a polder habitat. ZooKeys 100: 421-446. https://doi.org/10.3897/zookeys.100.1538
Figure 5 - Mean individual numbers per trap and day (± SE) and total species numbers of springtails of the pitfall traps of location 1 and location 6 (n=3) over the vegetation period 2008. Hygrophilic and hygrotolerant species (black bars) and xerotolerant as well as mesophilic species (grey bars) are shown. Abbreviations: ef = ecological flooding; spe = strong precipitation event.
Figure 7 from: Lessel T, Marx M, Eisenbeis G (2011) Effects of ecological flooding on the temporal and spatial dynamics of carabid beetles (Coleoptera, Carabidae) and springtails (Collembola) in a polder habitat. ZooKeys 100: 421-446. https://doi.org/10.3897/zookeys.100.1538
Figure 7 - Mean number of individuals of hygrophilic/hygrotolerant (A/B) and xerotolerant/mesophilic (C/D) collembolan species at the fallow (A/C) and ruderal area (B/D) during different moisture conditions. Abbreviations: ef = ecological flooding (higher Rhine water levels); spe = flood caused by a strong precipitation event; dc = drought conditions; ° outliers. Different letters represent statistically significant differences (Mann-Whitney U-test).
A dataset to support dynamical modelling of the thermal dynamics of a super-insulated building
<p>This work consisted of controlled heating experiments for the purpose of control-oriented dynamical modelling. The building studied is the LivingLab at NTNU, which is a super-insulated single-family house. The dataset contains full details of the measurements, as well as preprocessed (reduced) data which can be readily used as input for dynamical modelling investigations.</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.