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6,175 results for “Composite”
Data set for "Drought response of the boreal forest carbon sink is driven by understory-tree composition"
<p>This data set is a compilation of 1) environmental conditions, 2) biometric- and chamber-based annual CO<sub>2</sub> fluxes, 3) vegetation phenological greenness, and 4) forest-floor environmental conditions, all measured over the Krycklan Catchment Study (KCS, <a href="https://www.slu.se/Krycklan">https://www.slu.se/Krycklan</a>), a multi-scale long-term monitored boreal catchment spanning 68 km<sup>2</sup> in northern Sweden.</p> <p>The environmental measurements cover the period 1991–2020. Specifically, meteorological conditions measured close to the central part of the KCS at the Svartberget reference climate station (64°14′N, 19°46′E, 225 m.a.s.l.) included air temperature at 1.7 m above ground (Ta, °C), global radiation at 1.7 m above ground (Rg, MJ m<sup>-2</sup>), and precipitation (P, mm). Drought conditions were characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) computed at 3-month time scale. SPEI was retrieved from the 0.5° gridded dataset supplied in the Global SPEI Database (SPEIbase v2.8, <a href="https://spei.csic.es/database.html">https://spei.csic.es/database.html</a>). The data set comprises monthly values obtained during the long-term reference period 1991–2020 (LT<sub>91–20</sub>), the baseline period 2016–2017 (BL<sub>16–17</sub>), and the drought year 2018 (D<sub>18</sub>). The standardized anomaly (ɀ-score) was used to identify extreme environmental measurements during both the BL<sub>16–17 </sub>and D<sub>18</sub> periods relative to the LT<sub>91–20 </sub>period.</p> <p>Annual CO<sub>2</sub> flux estimates were collected in 50 forest stands located across the KCS during the period 2016–2018 using biometric- and chamber-based methods. However, to prevent confounding effects, one forest stand that was subjected to thinning operations in spring 2018 was excluded from the analysis. The selected forest stands encompassed different landscape attributes such as 1) soil type (i.e., sediment and till), 2) dominant tree species (i.e., pine and spruce), and 3) stand age classes (i.e., initiation, young, middle-aged, mature, and old-growth stands). The annual CO<sub>2</sub> fluxes included the net ecosystem production (NEP) and its component fluxes, i.e., net primary production (NPP), total heterotrophic respiration (RH), net primary production of trees (NPP<sub>t</sub>) and its above- and belowground components (ANPP<sub>t</sub> and BNPP<sub>t</sub>, respectively), and net primary production of understory (NPP<sub>u</sub>) and its above- and belowground components (ANPP<sub>u</sub> and BNPP<sub>u</sub>, respectively). The impact of drought on annual CO<sub>2</sub> fluxes was evaluated by calculating both the absolute and relative anomalies (∆X and δX, respectively) of D<sub>18</sub> relative to BL<sub>16–17</sub>. To identify the temporal shift of the dominant contributor to ∆NEP, a moving-window correlation was conducted between the absolute anomaly of NEP (∆NEP) and the absolute anomalies of understory and tree NPP (∆NPP<sub>u</sub> and ∆NPP<sub>t</sub>, respectively), using a 7-forest-stand window with 1-forest-stand step.</p> <p>The study assessed the phenological greenness of the understory and trees in a ⁓110 years-old mixed-species forest stand in the central part of the KCS from 2016 to 2018. The greenness index (gcc) was derived from hourly images collected through digital repeat photography at the Integrated Carbon Observation System (ICOS) Svartberget ecosystem station (SE-Svb, 64°15′N, 19°46′E, 270 m.a.s.l., <a href="https://www.icos-sweden.se/svartberget">https://www.icos-sweden.se/svartberget</a>). Web cameras were used to capture images below- and above-tree canopy to define the gcc index for understory (gcc<sub>u</sub>) and trees (gcc<sub>t</sub>), respectively. The gcc<sub>u</sub> and gcc<sub>t</sub> values were then normalized (0–1) to describe the seasonal minimum and maximum of vegetation biomass development. A locally estimated scatterplot smoothing (loess) curve fit was then used through the normalized data points to improve visualization. The impact of drought on mean estimates of gcc<sub>u</sub> and gcc<sub>t</sub> during the growing season was evaluated by calculating the absolute and relative anomalies (∆X and δX, respectively) of D<sub>18</sub> relative to BL<sub>16–17</sub>.</p> <p>Environmental conditions at the forest-floor interface were measured in each of the 50 forest stands located across the KCS during the period 2016–2018. As before, one forest stand that was subjected to thinning operations in spring 2018 was excluded from the analysis to prevent confounding effects. The measured conditions included the below-canopy air temperature (Ta<sub>bc</sub>, °C), soil temperature at 10 cm depth (Ts, °C), and soil volumetric water content at 5 cm depth (SWC, %). The data set includes mean monthly and mean May-August values estimated during the BL<sub>16–17</sub> and D<sub>18</sub> periods, for which the absolute and relative anomalies (∆X and δX, respectively) were calculated.</p> <p>This data set consists of four Microsoft Excel workbooks:</p> <p>1_dataset_environmental_conditions.xlxs</p> <p>2_dataset_biometric_&_chamber-based_CO2_fluxes.xlxs</p> <p>3_dataset_vegetation_phenological_greenness.xlxs</p> <p>4_dataset_forest-floor_environmental_conditions.xlxs</p> <p>Further details can be found in Martínez-García et al. “Drought response of the boreal forest carbon sink is driven by understory-tree composition” (Nature Geoscience, <a href="https://doi.org/10.1038/s41561-024-01374-9" target="_blank" rel="noopener noreferrer">https://doi.org/10.1038/s41561-024-01374-9</a>).</p> <p>Contact information:</p> <p>Ph.D. Eduardo Martínez García<sup>1,2</sup> (<a href="mailto:eduardo.martinez@slu.se">eduardo.martinez@slu.se</a>, <a href="eduardo.martinezgarcia@luke.fi">eduardo.martinezgarcia@luke.fi</a>, <a href="mailto:edu.martinez.garcia@gmail.com">edu.martinez.garcia@gmail.com</a>)</p> <p>Professor Matthias Peichl<sup>1</sup> (<a href="mailto:matthias.peichl@slu.se">matthias.peichl@slu.se</a>)</p> <p><sup>1</sup> Department of Forest Ecology and Management, Swedish University of Agricultural Sciences (SLU), Skogsmarksgränd 17, SE-901 83, Umeå, Sweden</p> <p><sup>2</sup> Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790, Helsinki, Finland</p>
Drivers of plant diversity, community composition, functional traits and soil processes along an alpine gradient in the central Chilean Andes
<p>The datasets in this repository include plant community surveys, hyperspectral reflectance data at the leaf and canopy level, leaf trait data, and soil chemistry data collected at five sites along an elevation gradient of 2400m-3500m in the Chilean Andes (33°S, 70°W). The purpose of this study was to evaluate the environmental drivers of community assembly processes along the elevation gradient.</p>
Quantifying the light-absorption properties and molecular composition of brown carbon aerosol from sub-Saharan African biomass combustion
<div> <p>Data presented in figures of the peer-reviewed journal article "Quantifying the light-absorption properties and molecular composition of brown carbon aerosol from sub-Saharan African biomass combustion" by Moschos et al.</p> <p>Disclaimer: Please contact the dataset creator prior to inclusion of data in any upcoming publication.</p> </div>
Fig. 2 in Daphnia Cucullata Sars, 1862 (Crustacea: Cladocera) Distribution And Location In Composition Of Zooplankton Cenosis In Lake Dridzis
Fig. 2. Redundancy analysis (RDA) ordination plot for zooplankton abundance from Lake Dridzis during the sampling period of May to September 2011. Abbreviations: ORP- Oxidation-reduction potential; NTU- Turbidity.
Fig. 1 in Daphnia Cucullata Sars, 1862 (Crustacea: Cladocera) Distribution And Location In Composition Of Zooplankton Cenosis In Lake Dridzis
Fig. 1. Redundancy analysis (RDA) ordination plot for zooplankton abundance from Lake Dridzis during the sampling period of May to September 2010. Abbreviations: ORP- Oxidation-reduction potential; NTU- Turbidity.
Determinants of microbiome composition: Insights from free-ranging hybrid zebras (Equus quagga × grevyi)
<p>The composition of mammalian gut microbiomes is highly conserved within species, yet the mechanisms by which microbiome composition is transmitted and maintained within lineages of wild animals remain unclear. Mutually compatible hypotheses exist, including that microbiome fidelity results from inherited dietary habits, shared environmental exposure, morphophysiological filtering, and/or maternal effects. Interspecific hybrids are a promising system in which to interrogate the determinants of microbiome composition because hybrids can decouple traits and processes that are otherwise co-inherited in their parent species. We used a population of free-living hybrid zebras (<em>Equus quagga</em> × <em>grevyi</em>) in Kenya to evaluate the roles of these four mechanisms in regulating microbiome composition. We analyzed fecal DNA for both the <em>trn</em>L-P6 and the 16S rRNA V4 region to characterize the diets and microbiomes of the hybrid zebra and of their parent species, plains zebra (<em>E. quagga</em>) and Grevy's zebra (<em>E. grevyi</em>). We found that both diet and microbiome composition clustered by species, and that hybrid diets and microbiomes were largely nested within those of the maternal species, plains zebra. Hybrid microbiomes were less variable than those of either parent species where they co-occurred. Diet and microbiome composition were strongly correlated, although the strength of this correlation varied between species. These patterns are most consistent with the maternal-effects hypothesis, somewhat consistent with the diet hypothesis, and largely inconsistent with the environmental-sourcing and morphophysiological-filtering hypotheses. Maternal transmittance likely operates in conjunction with inherited feeding habits to conserve microbiome composition within species.</p>
Fig. 2 in Feeding preference of adult females of ribbonfish Trichiurus lepturus through prey proximate-composition and caloric values
Fig. 2. Multivariate correspondence analysis considering the proximate-composition and prey species of Trichiurus lepturus in northern Rio de Janeiro State, Brazil. Cb: Chirocentrodon bleekerianus; Dp: Doryteuthis plei; Lg: Lycengraulis grossidens; Ph: Pellona harroweri; Pp: Peprilus paru; Tl: Trichiurus lepturus and Xk: Xiphopenaeus kroyeri. CAR = carbohydrate.
Fig. 1 in Feeding preference of adult females of ribbonfish Trichiurus lepturus through prey proximate-composition and caloric values
Fig. 1. Map of Brazil with Rio de Janeiro State and its northern coast, where adult female specimens of Trichiurus lepturus and their prey species were collected (21º18'S-22º25'S; until 50 m depth).
Fig. 2 in Fish assemblage of the Mamanguape Environmental Protection Area, NE Brazil: abundance, composition and microhabitat availability along the mangrove-reef gradient
Fig. 2. Ontogenetic patterns of habitat use in Abudefduf saxatilis, Anisotremus surinamensis, Lutjanus alexandrei, and L. jocu along the sub-areas of Mamanguape Mangrove-Reef system, NE Brazil, showing an increase in individual size classes from the Estuarine to the Reef zone. Mann Whitney U Test showed significant size differences between all sub-areas (for A. saxatilis, Transition vs. Reefs: U = 491, Z = -6.02, p = 0.00; for A. surinamensis, Transition vs. Reefs: U = 1338, Z = -6.83, p = 0.00; for L. alexandrei, Peixe-Boi vs. Transition: U = 0.00, Z = -3.39, p = 0.00; and Tanques vs. Transition: U = 0.00, Z = -2.92, p = 0.00; for L. jocu, Peixe-Boi vs. Transition: U = 7.5, Z = -3.38, p = 0.00), except between Tanques and Peixe-Boi for L. alexandrei (U = 65, Z = 0.76, p = 0.46).
Fig. 3 in Fish assemblage of the Mamanguape Environmental Protection Area, NE Brazil: abundance, composition and microhabitat availability along the mangrove-reef gradient
Fig. 3. Canonical Correspondence Analysis of fishes and environmental parameters from Mamanguape Mangrove-Reef system, NE Brazil: (a) fish species (symbols) in relation to microhabitat categories (vectors) - Eigenvalues: axis 1, 0.56; axis 2, 0,20; r species-environment: axis 1, 0.87; axis 2, 0.56; First two axes accounted for 64.9 % of the variance; (b) fish trophic groups and subareas (symbols) in relation to environmental categories (vectors) - Eigenvalues: axis 1, 0.49; axis 2, 0.39; r species-environment: axis 1, 0.79; axis 2, 0.76; First two axes accounted for 51.6 % of the variance. Monte-Carlo test of all canonical axes were significant (p <0.01), 999 permutations. Abbreviations as follows - fish species: Abusax: Abudefduf saxatilis; Acabah: Acanthurus bahianus; Acacoe: A. coeruleus; Achlin: Achirus lineatus; Anisur: Anisotremus surinamensis; Anivir: A. virginicus; Batsop: Bathygobius soporator; Centrop: Centropomus sp.; Cithspil - Citharichthys spilopterus; Corglau - Coryphopterus glaucofraenum; Dactvol - Dactylopterus volitans; Echnau: Echeneis naucrates; Epiadc: Epinephelus adscensionis; Eucmel: Eucinostomus melanopterus; Haepar: Haemulon parra; Hipprei: Hippocampus reidi; Lutana: Lutjanus analis; Lutale: L. alexandrei; Lutjoc: L. jocu; Micrbra: Microphis brachyurus; Myroce: Myrichthys ocellatus; Rypran: Rypticus randalli; Scarus: Scarus sp.; Sparis: Sparisoma sp.; Sphtes: Sphoeroides testudineus; Stefus: Stegastes fuscus; Stevar: S. variabilis; trophic groups: RH - Roving herbivore; TH - Territorial herbivore; OM - Omnivore; CA - Carnivore; IM - Invertivore of mobile prey.
Fig. 1 in Fish assemblage of the Mamanguape Environmental Protection Area, NE Brazil: abundance, composition and microhabitat availability along the mangrove-reef gradient
Fig. 1. Mamanguape estuary, State of Paraíba, NE Brazil, showing surveyed sub-areas: 1) Tanques; 2) Peixe-Boi; 3) Cação; 4) Transition; and 5) Reefs. Dashed areas represent sandbanks.
Dataset from 'Composite cores of monopoles and Alice rings in spin-2 Bose-Einstein condensates'
<p>Dataset associated with the publication 'Composite cores of monopoles and Alice rings in spin-2 Bose-Einstein condensates ' in Physical Review Research. <br>Source data for Figures 2-5 in the manuscript.</p>
Figure 5 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 5. Principal components analysis of the relative abundance (mol %, logit- transformed) of individual NLFAs of Trochosa ruricola using body size (small, large), flooding index (FI), plant species richness (SR), plant functional group richness (FG), presence of grasses (Gr), legumes (Leg), small herbs (SH) and tall herbs (TH) as supplementary variables.
Figure 4 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 4. Variations in δ15N signatures of Trochosa ruricola as affected by flooding index (P = 0.04, R2 = 0.12) and body size (small, large; P <0.01).
Figure 1 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 1. Variations in δ15N and δ13C signatures of Harpalus rufipes (black) and Trochosa ruricola (pink) across the study site of the Jena Experiment.
Figure 3 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 3. Principal components analysis of the relative abundance (mol %, logit-transformed) of individual NLFAs of Harpalus rufipes using flooding index (FI), plant species richness (SR), plant functional group richness (FG), presence of grasses (Gr), legumes (Leg), small herbs (SH) and tall herbs (TH) as supplementary variables.
Figure 5 in Species Composition, Diversity and Length Frequency of By-Catch Sharks from the Syrian Coast
Figure 5. Geographic distribution of possible nursery areas for three species (H. griseus; +, C. plumbeus; ×, M. mustelus; *, black circles; main cities) in Syrian marine waters.
Figure1 in Species Composition, Diversity and Length Frequency of By-Catch Sharks from the Syrian Coast
Figure1. Changes of diversity indices seasonally for by-catch sharks: (a); diversity index H, (b); qualitative richness factor D, (c); evenness factor
Figure 3 in Species Composition, Diversity and Length Frequency of By-Catch Sharks from the Syrian Coast
Figure 3. Size (TL) variations of abundant and common of by-catch sharks per season off Syria coast. Males (gray), females (white): (a); H. griseus,(b); H. perlo, (c); C. plumbeus, (d); M. mustelus (e); G. melastomus, (f); S. blainvillei, (g); C. granulosus, (h); C. uyato
Figure 4 in Species Composition, Diversity and Length Frequency of By-Catch Sharks from the Syrian Coast
Figure 4. Total length (TL) frequency distributions (percent of species catch) of the abundant and common bycatch sharks off Syrian coast. Males (black), females (white). Vertical lines indicate maturity size of males (sporadic) and females (continuous) following literature: (a); H. griseus,(b); H. perlo, (c); C. plumbeus, (d); M. mustelus (e); G. melastomus, (f); S. blainvillei, (g); C. granulosus, (h); C. uyato
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.