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339 results for “macroinvertebrate”
Fig 4 in Diversity and taxonomic structure of aquatic macroinvertebrates in a fluvio-lacustrine system in south-west Côte d'Ivoire: The case of the Soubré hydroelectric dam lake
Fig 4: Hierarchical classification of sampling stations based on the similarity of assemblages of aquatic macroinvertebrate families.
Fig. 1 in Spatio-Temporal Variations Of Macroinvertebrate Community In The Tisza River (Ne Hungary)
Fig. 1. Cross-section of the Tisza riverbed between Tiszamogyorós and Lónya at low water level. Abbreviations: 1 = main flow (right bank), 2 = mid-bed (at half distance between the right and the left
Fig. 3 in Spatio-Temporal Variations Of Macroinvertebrate Community In The Tisza River (Ne Hungary)
Fig. 3. Classification of samples from the cross-section of River Tisza between Lónya and Tiszamogyorós by dates. All taxa were taken into consideration with chironomids identified to family level. Groups are as follows: 1: March, 2: April, 3: June, 4: July, 5: September, 6: November
Fig. 2 in Spatio-Temporal Variations Of Macroinvertebrate Community In The Tisza River (Ne Hungary)
Fig. 2. Classification of sampling sites along the cross-section of River Tisza between Lónya and Tiszamogyorós. All taxa were taken into consideration with chironomids identified to species level. Groups are as follows: 1: left bank, 2: mid-bed, 3. main flow
Рис. 4. Αичинка P. acamusi из озера Арейского: а — гоΛова; б — ΑетаΛи строения верхней губы Fig. 4. Larva of P. akamusi from the Lake Areyskoye: а — head; б — labrum in macroinvertebrates of the Lake Areyskoye
Рис. 4. Αичинка P. acamusi из озера Арейского: а — гоΛова; б — ΑетаΛи строения верхней губы Fig. 4. Larva of P. akamusi from the Lake Areyskoye: а — head; б — labrum
Рис. 5. Αичинка A. sexmaculata изозера Арейского: а — общий виΑ; б — гоΛова и груΑь ΑорсаΛьно; в — гоΛова и груΑь ΛатераΛьно; г — Αомик Λичинки. ΔΛина Λичинки 4,5 мм Fig. 5. Larva of A. sexmaculata from Lake Areyskoye: а — general appearance; б — thoracs dorsally; в — thoracs laterally; г — larvae house. Larva length 4.5 mm in macroinvertebrates of the Lake Areyskoye
Рис. 5. Αичинка A. sexmaculata изозера Арейского: а — общий виΑ; б — гоΛова и груΑь ΑорсаΛьно; в — гоΛова и груΑь ΛатераΛьно; г — Αомик Λичинки. ΔΛина Λичинки 4,5 мм Fig. 5. Larva of A. sexmaculata from Lake Areyskoye: а — general appearance; б — thoracs dorsally; в — thoracs laterally; г — larvae house. Larva length 4.5 mm
Рис. 3. Αичинка T. ploenensis из озера Арейского: а — гоΛова; б — ментум; в — антенна; г — верхняя губа Fig. 3. Larva of T. ploenensis from Lake Areyskoye: а — head; б — mentum; в — antenna; г — labrum in macroinvertebrates of the Lake Areyskoye
Рис. 3. Αичинка T. ploenensis из озера Арейского: а — гоΛова; б — ментум; в — антенна; г — верхняя губа Fig. 3. Larva of T. ploenensis from Lake Areyskoye: а — head; б — mentum; в — antenna; г — labrum
Рис. 2. А — Озеро Арейское, ЯбΛоновый хребет; Б — ГΛавный воΑоразΑеΛ ЗемΛи у озера Арейского Fig. 2. А — Lake Areyskoye and Yablonovy Ridge; Б — The Main divide of the Earth near the Lake Areyskoye in macroinvertebrates of the Lake Areyskoye
Рис. 2. А — Озеро Арейское, ЯбΛоновый хребет; Б — ГΛавный воΑоразΑеΛ ЗемΛи у озера Арейского Fig. 2. А — Lake Areyskoye and Yablonovy Ridge; Б — The Main divide of the Earth near the Lake Areyskoye
Fig. 1. A in macroinvertebrates of the Lake Areyskoye
Fig. 1. A map of zoobenthos research stations of the Lake Areyskoe in 2019–2020 Note: the stations of seasonal complex hydrobiological studies are marked with a square, the stations of additional one-time studies of zoobenthos are marked with a circle, the surveyed stations are marked with a plus
Fig. 4 in Spatial heterogeneity in macroinvertebrate density from Lake Hövsgöl, Mongolia
Fig. 4. Mean (±1 SE) density of individual macroinvertebrate taxa from bays in Lake Hövsgöl. Bars with different letters are significantly different (PṤ0.05).
Fig. 3 in Spatial heterogeneity in macroinvertebrate density from Lake Hövsgöl, Mongolia
Fig. 3. Mean (±1 SE) density of total macroinvertebrates from bays in Lake Hövsgöl. Bars with different letters are significantly different (PṤ0.05).
Fig. 2 in Spatial heterogeneity in macroinvertebrate density from Lake Hövsgöl, Mongolia
Fig. 2. Double dendrogram of major macorinvertebrate taxa and study bays in Lake Hövsgöl based on hierarchical cluster analysis.
Fig. 1 in Spatial heterogeneity in macroinvertebrate density from Lake Hövsgöl, Mongolia
Fig. 1. Map of Lake Hövsgöl, Mongolia. Letters denote bay sites listed in Table 1. A (Har Us). B (UBWS). C (Borsog). D (Baavgai Tolgoi). E (Heegster). F (UBES).
A precipitation gradient drives change in macroinvertebrate composition and interactions within bromeliads.
<p>Tank bromeliads accumulate water inside their leaf axils, providing habitat for communities of aquatic macro invertebrates. Here we sampled the macro invertebrate community in 100 bromeliads along the sand dunes of coastal Brazil in the states of Rio de Janeiro and São Paulo. We sampled ten sites, seven of which were within the Jurubatiba National Park in Rio de Janeiro state, Brazil. The other three sites were located in the sand dunes of Arraial do Cabo (Rio de Janeiro), Marica (Rio de Janeiro), and Ilha Bela (Sao Paulo).</p> <p>We sampled all macroinvertebrate communities between March and May 2015. In each site, we dissected ten bromeliads (totalling 100 bromeliads across all sites) to collect all the invertebrates in each plant. Macroinvertebrates were counted and identified to genus level whenever possible. For every bromeliad, we measured a suite of environmental variables to assess the amount and quality of habitat available to the invertebrates including: the height (cm) and diameter (cm, measured as the maximum distance between leaf tips) of the plant, maximum water volume (mL, calculated by emptying the plant and calculating how much water the plant could hold before it overflowed), actual water volume (mL), longest leaf length (cm), longest leaf width (cm), number of leaves, canopy cover (% of shaded pixels in photos taken looking directly up from the bromeliad), total detritus (g dry mass), pH, oxygen concentration (% saturation), salinity (ppt), temperature (oC), and turbidity (NTU). Water chemistry and temperature variables were measured using a portable multiparameter waterproof meter in the field as soon as the water was collected from the plant.</p> <p>The zip file contains two csv files. Environment contains all the environmental variables described above, and Species_presence contains the species ID and whether it is present in a given bromeliad. </p> <p> </p>
Fig. 1 in Trophic network of aquatic macroinvertebrates along an altitudinal gradient in a Neotropical mountain river
Fig. 1. Static models of trophic networks at three sites in the Gaira River representing basal resources (red), intermediate consumer (orange) and top predators (yellow) and the interactions among them. SL, San Lorenzo, upper sector; LV, La Victoria, middle sector; PM, Puerto Mosquito, lower sector; D, dry season; R, rainy season.
Fig. 2 in Trophic network of aquatic macroinvertebrates along an altitudinal gradient in a Neotropical mountain river
Fig. 2. Representation of the standard deviation of vulnerability (SD-V) of the main food sources (FPOM, fine particulate organic matter; CPOM, coarse particulate organic matter; PT, plant tissue) calculated from the ratios recorded in the guts of the macroinvertebrates sampled in the elevational gradient of Gaira River during the dry and rainy seasons. Arrow thickness indicates the vulnerability importance.
Figure 6 in Macroinvertebrate communities along the Velika Morava River
Figure 6. Hierarchical classification of the sampling sites (a) and months (b) according to the relative abundance of macroinvertebrate taxa, using Noy-Meir clustering from generalized Euclidean distances. The sampling sites are coded as follows: 1 – VM1, 2 –VM2, 3 – VM3, 4 – VM4, and 5 – VM5. The months are coded as follows: 1 – July, 2 – August, 3 – October, and 4 – November.
Figure 8 in Macroinvertebrate communities along the Velika Morava River
Figure 8. CCA triplot (75 taxa, 14 samples, and 6 environmental factors) displaying 56% variance (first CCA axis, 31.4%; second CCA axis, 24.1%) in the WA (weighted averages) of taxa and species with respect to the environmental variables. Down-weighting of rare species was performed, and the WA algorithm was applied. The names of the taxa and species are abbreviated as follows: Hep fus – Kageronia fuscogrisea, Hep sp. – Heptagenia sp., Pot lut – Potamanthus luteus, Eph ign – Ephemerella ignita, Bae rho – Baetis rhodani, Hyd sp – Hydropsyche sp., etc. (full list of abbreviations is provided in the Appendix). The environmental factors are coded as follows: pH (pH), WTemp (water temperature), NH4 (ammonium ion), Organic N (organic nitrogen), TOC (total organic carbon), and Orthoph (orthophosphate). The samples are coded as in the Table (for example, 1- VM1_7, 2 – VM3_7, etc.).
Figure 4 in Macroinvertebrate communities along the Velika Morava River
Figure 4. The Shannon–Wiener index: spatial (a) and monthly (b) aspects (mean, maximal, and minimal values).
Figure 3 in Macroinvertebrate communities along the Velika Morava River
Figure 3. Relative abundance of the main taxonomic groups regarding sampling sites (a) and months (b).
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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.