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18,658 results for “impacts”
Fig. 3 in Impact of ecotourism on the fish fauna of Bonito region (Mato Grosso do Sul State, Brazil): ecological, behavioural and physiological measures
Fig. 3. Image illustrating under water visibility at the beginning of the snorkeling excursion and the presence of tourists (Lima, 2008).
Fig. 1 in Impact of ecotourism on the fish fauna of Bonito region (Mato Grosso do Sul State, Brazil): ecological, behavioural and physiological measures
Fig. 1. Map showing the location of the study area: Sucuri River (C), município of Bonito area (B), Brazil (A). Adapted from Miranda & Coutinho (2004).
Fig. 8 in Impact of ecotourism on the fish fauna of Bonito region (Mato Grosso do Sul State, Brazil): ecological, behavioural and physiological measures
Fig. 8. Variation of behaviour patterns between before (8h00) and after (9h00) the first disturbance of tourists in the river (mean and SEM) for M. bonita; (a) Tourism and (b) No Tourism. Lighter bars = 8h00; darker bars = 9h00 (Mann-Whitney U-test). N = 70; * p <0.05; ** p <0.01.
Fig. 9 in Impact of ecotourism on the fish fauna of Bonito region (Mato Grosso do Sul State, Brazil): ecological, behavioural and physiological measures
Fig. 9. Variation (mean and SEM) of cortisol responses to restraining stress in Moenkhausia bonita individuals at the No Tourism and Tourism sites (Mann-Whitney U-test, N = 6; Z = -2.95; p <0.005).
Figure 5 in Study of ecosystem of the Sukhum Bay with emphasis anthropogenic impact, Abkhazian Black Sea coast
Figure 5. Numerical density of ichthyoplankton in vertical catches, ind./m2 (a) and horizontal catches, ind./100 m3 (b):: 1 – goatfish, 2 – horse mackerel, 3 – annular sea bream, 4 –anchovy, 5 – corb
Figure 4 in Study of ecosystem of the Sukhum Bay with emphasis anthropogenic impact, Abkhazian Black Sea coast
Figure 4. Dynamics of holoplankton (а): numerical abundance (N, 103∙ ind./m3), biomass (B, mg/m3) and meroplankton (b): numerical abundance (N, 103∙ ind./m3), biomass (B, mg/m3).
Figure 2 in Study of ecosystem of the Sukhum Bay with emphasis anthropogenic impact, Abkhazian Black Sea coast
Figure 2. Dynamics of phytoplankton (а): numerical abundance (N, 106∙ cell/m3), biomass (B, mg/m3), temperature of seawater (°C) and planktonic ciliates (b): numerical abundance (N, 106∙ ind./m3), biomass (B, mg/m3)
Figure 2 in Impact of poaching on the population structure and insect associates of the Endangered Encephalartos eugene-maraisii from South Africa
Figure 2. Insects associated with Encephalartos eugene-maraisii in Entabeni: A, B, Amorphocerus cf. setosus; C, D, Apinotropis verdoornae; E, F, Zerenopsis lepida. Photographs: P.D. Janse van Rensburg.
Figure 4 in Impact of poaching on the population structure and insect associates of the Endangered Encephalartos eugene-maraisii from South Africa
Figure 4. Large Encephalartos eugene-maraisii stem that was pushed over by poachers. Photographer: P.D. Janse van Rensburg.
Figure 1 in Impact of poaching on the population structure and insect associates of the Endangered Encephalartos eugene-maraisii from South Africa
Figure 1. Typical architecture of an Encephalartos eugene-maraisii plant. Photographer: P.D. Janse van Rensburg.
Figure 3 in Impact of poaching on the population structure and insect associates of the Endangered Encephalartos eugene-maraisii from South Africa
Figure 3. Distribution of Encephalartos eugene-maraisii in the Entabeni Safari Conservancy between 2021 and 2022, compared to 2008. A, heatmap of E. eugene-maraisii plants re-recorded between 2021 and 2022; B, heatmap of E. eugene-maraisii plants that were not relocated. Lines indicate the fence line. The map is given without a geographical reference because E. eugene-maraisii is vulnerable to poaching.
Figure 1 in The influence of land use-impacted tributaries on water quality and phytoplankton in the Mooi River, North West Province, South Africa
Figure 1: Catchment area of the Mooi River from its source to the confluence with the Vaal River, showing the position of sampling sites in the main stream (1–8) and in the tributaries (WFS, GM and WS). Different types of land use activities in the catchment are also indicated on the map.
Figure 3 in The influence of land use-impacted tributaries on water quality and phytoplankton in the Mooi River, North West Province, South Africa
Figure 3: Canonical Correspondence Analysis (CCA) of the physico-chemical environmental variables, natural log of the phytoplankton data, and the different sites located in the Mooi River for 2015.
Figure 4 in Impact of a large dam on reproduction of a non-migratory teleost species, Acestrorhynchus lacustris (Characiformes: Acestrorhynchidae)
Figure 4. Testis in different maturation stages and respective transversal sections stained by HE. (A) early maturation, (B) advanced maturation/mature, (C) partially spent; Z= spermatozoa; C2= secondary spermatocytes T= spermatids; ST= seminiferous tubules. Scale bars represent A= 100 µm, B= 200 µm and C= 500 µm.
Figure 3 in Impact of a large dam on reproduction of a non-migratory teleost species, Acestrorhynchus lacustris (Characiformes: Acestrorhynchidae)
Figure 3. Ovaries in different maturation stages and the respective transversal sections stained by HE.(A) resting, (B) initial maturation, (C) advanced maturation/mature, (D) partially spawned, (E) totally spawned ovaries, (F) post-ovulatory follicle, (G) yellow body. O1= early perinucleolar follicles; O2= late perinucleolar follicles; O3= pre-vitellogenic follicles; O4= vitellogenic follicles; POF= post-ovulatory follicle; YB= yellow body. Scales bars represent 100 µm.
Figure 2 in Impact of a large dam on reproduction of a non-migratory teleost species, Acestrorhynchus lacustris (Characiformes: Acestrorhynchidae)
Figure 2. Frequency (%) and size classes of vitelogenic follicles (µm) of A. lacustris from fully grown ovaries of A. lacustris. Different bar colours indicate statistically significant differences between the diameter classes (p<0.05).
Figure 1 in Impact of a large dam on reproduction of a non-migratory teleost species, Acestrorhynchus lacustris (Characiformes: Acestrorhynchidae)
Figure 1. Sampling sections of the São Francisco River, downstream from Três Marias Dam. Section 1: immediately downstream the Dam; Section 2: immediately after the confluence with Abaeté River. UTM coordinates.
Figure 4 in Impact of alien fishes on the distribution pattern of indigenous freshwater fishes of Punjab, Pakistan
Figure 4. Analysis of aliens' fish species impact on the diversity of native fish species through PCA.
Figure 1 in Impact of alien fishes on the distribution pattern of indigenous freshwater fishes of Punjab, Pakistan
Figure 1. Map of sampling sites along with four sampling sites i.e. Head Qadirabad (HQ), Head Baloki (HB), Islam Headworks (IH) and Rasul Barrage (RB).
Figure 4 in Plant age, crop stage and surrounding habitats: their impact on sucking pests and predators complex in cotton (Gossypium hirsutum L.) field plots in arid climate at district Layyah, Punjab, Pakistan
Figure 4. Means (±SE) number of sucking insect pests (jassid, thrips, whitefly) and predators (green lacewing, spider) in cotton field plots at three locations (five replications) with different surrounding habitats (sugarcane + sesame, monoculture, sesame) during cropping season of cotton from June 20 to September 18, 2018 at Layyah, Punjab, Pakistan.
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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)
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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.