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91 results for “Resource partitioning”
Fig. 2 in Intraspecific food resource partitioning in Brazilian silverside Atherinella brasiliensis (Atheriniformes: Atherinopsidae) in a tropical estuary, Brazil
Fig. 2. Box-plot of spatial and temporal variation of number of individuals (CPUE average ±SE) and Biomass (±SE) of A. brasiliensis collected Mamanguape river estuary in Brazil. Bold lines indicate medians, hinges indicate the 25th and 75th percentiles, whiskers indicate the largest and smallest observation within a distance of 1.5 the box size. White bar= Wet season and Dark Gray bar= Dry season.
Fig. 5 in Intraspecific food resource partitioning in Brazilian silverside Atherinella brasiliensis (Atheriniformes: Atherinopsidae) in a tropical estuary, Brazil
Fig. 5. Principal coordinate analysis ordination (PCO) coded by habitat (a) and size classes (b) for Atherinella brasiliensis in the Mamanguape River estuary, Brazil. Symbols Habitat: Mud flat (Full Black Triangle); Tidal Creek 1 (Gray Square); Tidal Creek 2 (Black Circle); Symbols size classes: Small juveniles (Open Black Square); Juveniles (Light Gray Circle) and Adults (Dark Gray Circle).
Fig. 7 in Intraspecific food resource partitioning in Brazilian silverside Atherinella brasiliensis (Atheriniformes: Atherinopsidae) in a tropical estuary, Brazil
Fig. 7. Feeding strategy for Atherinella brasiliensis in Mamanguape river estuary: A= Mudflat; B= Tidal Creek 1 and C= Tidal Creek 2. Food items: Cyc, Cyclopoida; Cal, Calanoida; Dec, Decapoda; Decl, Decapoda larvae; Hym, Hymnoptera; Egf, Fish eggs; Cer, Ceratopogonidae larvae; Ost, Ostracoda; Gas, Gastropoda; Pol, Polychaeta; Esc, Scale. (TL1= small juveniles; TL2= juveniles and TL3= adult).
Fig. 4 in Food resource partitioning among species of Astyanax (Characiformes: Characidae) in the Lower Iguaçu River and tributaries, Brazil
Fig. 4. Relative frequency (%) of the diet overlap index of Astyanax species pairs in the Low Iguaçu River and tributaries in Brazil. Ab=A. bifasciatus; Ad=A. dissimilis; Ag=A. gymnodontus; Al=A. lacustris; Am=A. minor. Low <0.39; intermediate =0.40-0.59; high> 0.60.
Fig.1 in Food resource partitioning among species of Astyanax (Characiformes: Characidae) in the Lower Iguaçu River and tributaries, Brazil
Fig.1. Study area showing the sampling sites (numbers 1 to 25) in the Lower Iguaçu River and tributaries in Brazil.
FIGURE 2 in Evidence for dynamic resource partitioning between two sympatric reef shark species within the British Indian Ocean Territory
FIGURE 2 (a) Maximum likelihood standard ellipse areas (, 40% of the data) for isotopes δ13C v. δ15N in fin, (b) muscle, (c) red blood cell, (d) plasma and for isotope δ34S v. δ15C (e) and δ15N (f) of Carcharhinus amblyrhynchos () and Carcharhinus albimarginatus (). Convex hulls () are drawn between the centers of each group. Overlapping values, if present, are the proportion of overlapping area of the two ellipses. Potential competitor–prey teleost data are shown () with associated error bars (± 1 SD). Ellipses for red blood cell and plasma presented for reference but represent small sample sizes (<10) and therefore come with lower confidence
FIGURE 1 in Evidence for dynamic resource partitioning between two sympatric reef shark species within the British Indian Ocean Territory
FIGURE 1 Bayesian isotope mixing models were used to determine the extent that Carcharhinus amblyrhynchos and Carcharhinus albimarginatus were reliant on reef (blue) or pelagic (red) resources. End members were set as the most δ13C depleted (pelagic) and most δ13C enriched (reef) of the teleosts sampled (trevally (Carangidae) for reef, tuna (Scombridae) for pelagic). Posterior probability distributions indicate model predictions of reliance on a given source with higher values indicating greater reliance
Figure 5 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 5. Station-wise variation in the 0–500 m column integrated mesozooplankton abundance/density and biomass in the central (a) and western (b) Bay of Bengal during spring intermonsoon.
Figure 6 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 6. Depth-wise variation in the number of zooplankton groups at each station in the central (a) and western (b) Bay of Bengal during spring intermonsoon.
Figure 1 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 1. Map of the sampling site in the Bay of Bengal. Stations CB1 to CB5 are located along the central (88°E) and WB1 to WB4 along the western margin of the bay.
Figure 13 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 13. Multivariate cluster analysis of the data of all 129 copepod species combined from all the stations and depths in the central and western bay using the 30% cut-off level of Bray–Curtis similarity. Cluster/Group I are assemblages mostly from the mixed layer (M) and thermocline (T) from central and western transects. Group II comprises assemblages found between the thermocline and 500 m and Group III includes only a few species found exclusively from 200–300 m depth at stations CB3–CB5.
Figure 4 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 4. Vertical profiles of day (D) and night (N) zooplankton biovolume from multinet tows in the western Bay of Bengal during spring intermonsoon. ng: negligible biovolume; NO DATA is where the net failed to open/close. *At WB3, medusae (100 mL 100 m–3) and at WB4 salps (200 mL 100 m–3) were observed at the surface during the day.
Figure 9 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 9. Vertical distribution of abundance (log number 100 m–3) of the major copepod species in the central Bay of Bengal during spring intermonsoon.
Figure 3 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 3. Vertical profiles of day (D) and night (N) zooplankton biovolume from multinet tows in the central Bay of Bengal during spring intermonsoon. ng: Negligible biovolume; NO DATA is where the net failed to open/close. *Swarms of medusae were observed at CB3 (their biovolume 90 mL 100 m–3) and CB4 (200 mL 100 m–3) at the surface at night.
Figure 8 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 8. Vertical distribution of the various types (orders) of copepods in the central (a) and western (b) Bay of Bengal during the spring intermonsoon. The percentages at every depth are averages from 5 stations in the central and 4 stations in the western bay. Data are unavailable at 300–500 m in the central bay due to negligible abundance.
Figure 12 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 12. Variation in multivariate dispersion (MVDISP) indices between different depth strata (9 stations data combined) and between the central and western transects in the Bay of Bengal.
Figure 11 in Spatial structuring of zooplankton communities through partitioning of habitat and resources in the Bay of Bengal during spring intermonsoon
Figure 11. Variation in Shannon diversity (H'), species richness (d), and evenness (J') of copepods in different depth strata in the upper 500 m of the central (a) and western (b) Bay of Bengal.
FIGURE 3 in Damming in the Madeira River modifies the food spectrum of piscivorous and affects their resource partitioning
FIGURE 3 | Dietary niche breadth values of four piscivorous fishes before (pre-HPP) and after (post-HPP) dam construction in the Madeira River.
FIGURE 2 in Damming in the Madeira River modifies the food spectrum of piscivorous and affects their resource partitioning
FIGURE 2 | The percent volume of prey consumed by four piscivorous fishes in Madeira River. A. Acestrorhynchus falcirostris, B. Acestrorhynchus heterolepis, C. Hydrolycus scomberoides, and D. Rhaphiodon vulpinus. Blue bars correspond to the pre-damming period and red bars to the post-damming period. Items are Aces = Acestrorhynchidae, Cyno = Cynodontidae, Char = Characidae, Curi = Curimatidae, Ster = Sternopygidae, Hemi = Hemiodontidae, Lori = Loricariidae, Auch = Auchenipteridae, Dora = Doradidae, Pime = Pimelodidae, Inse = Insects, Vege = Vegetable.
FIGURE 1 in Damming in the Madeira River modifies the food spectrum of piscivorous and affects their resource partitioning
FIGURE 1 | Study area in the Madeira River portion. Black points representing fixed sampling sites for both pre-and post-damming phases. Triangles represent the sampling sites located in the reservoir area in the post-damming phase. Arrows indicate the river flow.
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
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DANDI Archive for NWB datasets
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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.