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248 results for “assemblage structure”
SBC LTER: Reef: Community structure and productivity of subtidal turf and foliose algal assemblages at Naples Reef, 2006
This dataset contains abundance, primary production and respiration of macroalgal and turf assemblages at Naples Reef (Santa Barbara County, CA) during 2006. It includes abundance of macroalgae is in terms of biomass (dry weight), and abundance of animals is in numbers of individuals and biomass (ash-free dry weight). Primary production and respiration of the benthos were measured in situ as changes in oxygen in closed chambers that covered 0.1m2 of the bottom. Species richness data are for macroalgae only. Abundance and diversity were measured for the same plots where oxygen measurements were recorded. These data were presented in: <ulink url="http://dx.doi.org/10.3354/meps08131">Miller, R.J., D. Reed, and M. Brzezinski. 2009. Community structure and productivity of subtidal turf and foliose algal assemblages. Marine Ecology Progress Series 388:1-11 doi: 10.3354/meps08131</ulink>.
Fig. 5 in Seasonal and longitudinal variation in fish assemblage structure along an unregulated stretch of the Middle Uruguay River
Fig. 5. Detrended Correspondence Analysis (DCA) applied to ordinate samples according to variations in fish composition and abundance along the Uruguay River. Rectangles depict groups confirmed by a Multiple Response Permutation Procedure (Tab. 2). Sites: S1 = upstream; S6 = downstream. Seasons: Au= Autumn; Sp= Spring; Su= Summer and Wi= Winter.
Fig. 2 in Seasonal and longitudinal variation in fish assemblage structure along an unregulated stretch of the Middle Uruguay River
Fig. 2. Variation (mean ±standard deviation) in species richness and biomass (CPUEb/100m2) along the river channel (A and C) and among seasons (B and D), in the Middle Uruguay River. Sites: S1 = upstream; S6 = downstream. Different letters indicate statistical difference (p <0.05).
Fig. 8 in Optimal fishing samplers to reveal the morphological structure of a fish assemblage in a subtropical tidal flat
Fig. 8. Redundancy analysis (RDA): individual species-gear relationships explained by morphological shape variability, using incidence data. In blue, fishing gear acronyms: beach seine (BS), cast net (CN), fish trap (FT), hook and line (HL), inner encircling gillnet (EG1), large gillnet (LG), marginal encircling gillnet (EG2), otter trawl (OT), small gillnet (SG).
Fig. 4 in Optimal fishing samplers to reveal the morphological structure of a fish assemblage in a subtropical tidal flat
Fig. 4. Morphospace represented by shape variation of all species in the nine fishing gears grouped, using the relative warps: a. 1 and 2; b. 1 and 3. Acronyms: Anc tri, Anchoa tricolor; Bat sop, Bathygobius soporator; Bot oce, Bothus ocellatus; Cen par, Centropomus parallelus; Chi spi, Chilomycterus spinosus; Dia rho, Diapterus rhombeus; Elo sau, Elops saurus; Epi mar, Epinephelus marginatus; Hip rei, Hippocampus reidi; Lut ana, Lutjanus analis; Lut cya, Lutjanus cyanopterus; Mal del, Malacoctenus delalandii; Myr pun, Myrophis punctatus; Oph gom, Ophichthus gomesii; Pol vir, Polydactylus virginicus; Sca cri, Scartella cristata; Sco bra, Scomberomorus brasiliensis; Sel set, Selene setapinnis; Sel vom, Selene vomer; Sph tes, Sphoeroides testudineus; Str mar, Strongylura marina; Sym tes, Symphurus tesselatus; Tra myo, Trachinocephalus myops. Threatened species (Hip rei, Lut ana, Lut cya, Epi mar) are highlighted in red.
Fig. 2 in Changes In The Structure Of Assemblages Of Three Liolaemus Lizards (Iguania, Liolaemidae) In A Protected Area Of South-Central Chile Affected By A Mixed-Severity Wildfire
Fig. 2. Species of Liolaemus lizards recorded in the study area. A — L. tenuis (© G. Zúñiga); B — L. pictus (© A. H. Zúñiga); C — L. lemniscatus (© A. H. Zúñiga).
Fig. 3 in Changes In The Structure Of Assemblages Of Three Liolaemus Lizards (Iguania, Liolaemidae) In A Protected Area Of South-Central Chile Affected By A Mixed-Severity Wildfire
Fig. 3. Percentages of microhabitat use by lizards in study area according to severity of damage caused by fire.
Fig. 1 in Changes In The Structure Of Assemblages Of Three Liolaemus Lizards (Iguania, Liolaemidae) In A Protected Area Of South-Central Chile Affected By A Mixed-Severity Wildfire
Fig. 1. Study area: A — Geographical context; B — Mosaic of areas of different degrees of severity (modified from CONAF, 2014, 2015).
FIGURE 7 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 7 | The first two axes from the distance-based redundancy analysis (dbRDA) that correlate the structure of the shallow water fish assemblage and predictors (in bold; from the fitted model) sampled from May 2000 to April 2001 in the north-south axis of the Paranaguá Bay Estuarine Complex (southern Brazilian coast). ED = early dry season (April–June), LD = Late dry season (July–September), EW = early rainy season (October–December) and LW = late rainy season (January–March). Achirus lineatus = Ac.li; Bathygobius soporator = Ba.so; Chaetodipterus faber = Ch.fa; Eucinostomus argenteus = Eu.ar; Menticirrhus americanus = Me.am; M. littoralis = Me.li; Sphoeroides greeleyi = Sp.gr; S. testudineus = Sp.te; Trachinotus carolinus = Tr.ca; T. falcatus = Tr.fa; T. goodei = Tr.go; T. marginatus = Tr.ma. Only species with Pearson correlation coefficient |r| ≥ 0.3 with the axes are shown. Percentage explained by the axis (fitted) and total variation explained by the model are provided on the axes.
FIGURE 4 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 4 | Cumulative species curve calculated with fish samples sampled from May 2000 to April 2001 at eight sites along the estuarine gradient of shallow areas of the northsouth axis of the PEC. In gray, the modeled curve based on the Coleman Estimator (Coleman et al., 1982). Boxplots were generated from mean. Crosses represent outliers.
FIGURE 2 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 2 | Salintity, tranparency (Transp) and dissolved oxygen (DO) along the estuarine gradient of shallow areas of the north-south axis of the PEC from monthly sampling of May 2000 to April 2001. For a better visualisation, the values were averaged by seasons and the error bars were omitted. ED = early dry season (April–June), LD = Late Dry season (July– September), EW = early rainy season (October–December) and LW = late rainy season (January– March).
FIGURE 1 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 1 | Maps of study area, their location in the coast of Paraná (Southestern Brazil) and, in detail, the sampling points (1–8) along the north-south axis of the Paranaguá Bay Estuarine Complex. The geographical limits of the Guaraqueçaba Area of Enviromental Protection (in Portuguese acronimous – APA) and Superagui National Park are also shown. To compute the values of distance from the mouth of the estuary and the sampling point (see methods), we used the ocean-turned face of the Island Mel as the reference of the mouth of the estuary. Distance from the estuarine mouth: Site 1 = 33.97 km, Site 2 = 34.41, Site 3 = 26.27 km, Site 4 = 29.2 km, Site 5 = 24.85 km, Site 6 = 19.30 km, Site 7 = 7.5 km, Site 8 = 5.18 km.
FIGURE 6 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 6 | Abundance (n) relationship with the environmental variables that formed the most parsimonious linear model. Line represents the modeled values, and a gray area corresponds to the standard deviation. l.n = number of individuals in logscale. Temp = temperature; Sal = salinity; Time = succession of days from beginning to end of the sampling surveys; D = distance from the mouth of the estuary (see Material and Methods section for details).
FIGURE 3 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 3 | Monthly variation in the mean historical rainfall data (monthly average between 1975 and 2015) and mean water temperature sampled from May 2000 to April 2001 at eight sites along the estuarine gradient of shallow areas of the northsouth axis of the PEC. For temperature, the values were averaged by month and bars represent standard deviation. Months were ordered according to the sequence of the sampling surveys.
FIGURE 5 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 5 | Richness (S) relationship with the environmental variables that formed the most parsimonious GLM. Line represents the modeled values, and a gray area corresponds to the standard deviation. Temp = temperature; Transp = transparency; Sal = salinity; Time = succession of days from beginning to end of the sampling surveys (see Material and Methods section for details).
Fig. 2 in Trophic organization and fish assemblage structure as disturbance indicators in headwater streams of lower Sorocaba River basin, São Paulo, Brazil
Fig. 2. Average values and confidence interval (IC95%) of individuals' density, Shannon and Margalef Indices for each treatment, structurally complex streams (TT) and simplified stream (TC).
Fig. 1 in Trophic organization and fish assemblage structure as disturbance indicators in headwater streams of lower Sorocaba River basin, São Paulo, Brazil
Fig. 1. Map of the study area showing São Paulo State within Brazil (top left panel); Sorocaba River basin (shaded) and sample region (square) within São Paulo State (bottom left panel); and elevation profile and hydrography with position of the sampled sites (circles) in the sample region (right panel).
Fig. 3 in Trophic organization and fish assemblage structure as disturbance indicators in headwater streams of lower Sorocaba River basin, São Paulo, Brazil
Fig. 3. Projections of the Non-Metric Multidimensional Scaling (NMDS) and the smallest convex hulls that contain all data of the structurally complex streams (TT1, TT2 and TT3) and simplified stream (TC) according to a) taxonomic structure and b) trophic groups.
Fig. 2 in Patterns in fish species composition and assemblage structure in the upper Salado River lakes, Pampa Plain, Argentina
Fig. 2. Relationship between diversity and species richness in fish assemblages and the NO3:NH 4 ratio.
Fig. 3 in Patterns in fish species composition and assemblage structure in the upper Salado River lakes, Pampa Plain, Argentina
Fig. 3. Bar chart showing the distribution of total fish collected of each species within the upper Salado River lakes. Species codes as listed in Table 2. Species are intentionally sorted by means of their spatial distribution to ease the interpretation. From left to right, from clear to dark filled bars: Mch = Mar Chiquita, Go = Gómez, Crp = Carpincho, and Rch = Rocha.
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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.