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7,081 results for “Habitats”
FIGURE 2 in Habitat associations of rainbow trout Oncorhynchus mykiss and brown trout Salmo trutta fry
FIGURE 2 Salmo trutta fry single-pass counts and associations with (a) D50, (b) depth and (c) velocity
Climate and habitat type interact to influence contemporary dispersal potential in Prairie Smoke (Geum triflorum)
<p>Understanding dispersal potential, or the probability a species will move a given distance, under different environmental conditions is essential to predicting species' ability to move across the landscape and track shifting ecological niches. Two important drivers of dispersal ability are climatic differences and variation in local habitat type. Despite the likelihood these global drivers act simultaneously on plant populations, and thus dispersal potential is likely to change as a result, their combined effects on dispersal are rarely examined. To understand the effect of climate and varying habitat types on dispersal potential, we studied <em>Geum triflorum</em> - a perennial grassland species that spans a wide range of environments, including both prairie and alvar habitats. We explored how the climate of the growing season and habitat type (prairie vs alvar) interact to alter dispersal potential. We found a consistent interactive effect of climate and habitat type on dispersal potential. Across prairie populations, an increased number of growing degree days favored traits that increase dispersal potential, or the probability of dispersing farther distances. However, for alvar populations, dispersal potential tended to decrease as the number of growing degree days increase. Our findings suggest that under continued warming, populations in prairie habitats will benefit from increased gene flow, while alvar populations will become increasingly segregated, with reduced potential to track shifting fitness optima.</p>
F I G U R E 1 in Pelagic observations of the midwater scorpionfish Ectreposebastes imus (Setarchidae) suggests a role in trophic coupling between deep-sea habitats
F I G U R E 1 Ectreposebastes imus (a) observed by submersible JAGO in midwater at 350 m off the island of Santo Ant~ ao, Cabo Verde. Side view of the fish in vertical position with head up, as it was observed when encountered by submersible, (b) observed by PELAGIOS in the horizontal position and (c) observed by PELAGIOS in the vertical position
FIGURE 4 in Habitat associations of rainbow trout Oncorhynchus mykiss and brown trout Salmo trutta fry
FIGURE 4 Oncorhynchus mykiss fry counts from sites in which O. mykiss were or were not (i.e., natural reproduction) stocked and associations with (a) D50 and (b) velocity. A trendline shows the relationship between each habitat variable and the fry count data for both the sites that were stocked (dotted line) and not stocked (solid line) () Not Stocked () Stocked
Figure 1. A-B, E in First record of the halobiontic Diplodontus semiperforatus (Acari, Hydrachnidia) from North Khorasan, with notes on water mites from saline habitats of Iran
Figure 1. A-B, E: Diplodontus semiperforatus (Walter, 1925), ♀, Qareh Ghan, Iran – A. Palp, lateral view; B. Chelicera; E. Photograph of genital field. C–D: Diplodontus scapularis Dugès, 1834, Messoussate, Morocco (C – ♀, F – ♂) – C. Chelicera; D. Photograph of genital field. F. Maximum Likelihood tree (GTR+I model) of the genus Diplodontus obtained from 6 nucleotide COI sequences.
Figure 3 in Diversity and community structure of oribatid mites (Acari: Oribatida) in the dominant habitats of Machakhela National Park (Georgia, Caucasus)
Figure 3. The results of the cluster analysis of the different forest habitats in Machakhela National Park.
Figure 1 in Diversity and community structure of oribatid mites (Acari: Oribatida) in the dominant habitats of Machakhela National Park (Georgia, Caucasus)
Figure 1. Distribution of the sites of the sample collection of the oribatid mite diversity in the Machakhela National Park.
Figure 2 in First record of the halobiontic Diplodontus semiperforatus (Acari, Hydrachnidia) from North Khorasan, with notes on water mites from saline habitats of Iran
Figure 2. Photograph of sampling site (Qareh Ghan, North Khorasan Province) of Diplodontus semiperforatus in northeastern Iran. Photo by V. Pešić.
Figure 2. Green and senescence N in Foliar resorption of nitrogen and phosphorus in Alcea apterocarpa (Malvaceae) in different habitats types
Figure 2. Green and senescence N:P ratio of A. apterocarpa in different habitat types. Means followed by the same letter are not significantly different at the 0.05 level using Tukey's HSD test.
Figure 1 in Foliar resorption of nitrogen and phosphorus in Alcea apterocarpa (Malvaceae) in different habitats types
Figure 1. Resorption proficiency and efficiency levels of A. apterocarpa according to all patterns. Habitat abbreviations are H1: riverbank, H2: meadow and H3: forest clearing. Minor letters followed by the same letter are not significantly different at the 0.05 level using Tukey's HSD test.
Dataset for Evaluating habitat-specific interference in automated radio telemetry systems: implications for animal movement studies
<h1>Abstract </h1> <p>Automated radio telemetry systems have become a popular and invaluable tool in tracking the activity and movement of wild animals. However, many environmental conditions can hinder accuracy when tracking with this technology. For instance, study sites may contain multiple habitat types, each habitat uniquely affecting the signal strength received from tagged species. To investigate the influence of a structurally diverse study site on an automated radio telemetry system, we conducted this project at a restored and managed pine barren habitat that consisted of a mix of mature pitch pine, treated pitch pine, scrub oak, and hardwood forests. This site, Montague Plains Wildlife Management Area, Montague, Massachusetts, is also a known breeding ground for Eastern whip-poor-will (Antrostomus vociferus). To measure the relationship of radio signal strength with distance across each habitat, we used radio telemetry equipment manufactured by Cellular Tracking Technologies. We produced negative exponential decay functions measuring radio signal strength over distance and tested for differences among habitat types on radio signal strength (RSS). We found that decay function parameters significantly differed by habitat type, prompting us to investigate if accounting for these differences improved location estimate accuracy. To test this, we estimated known locations using trilateration methods with and without habitat calibration. Comparing these tests indicates that habitat-specific adjustments significantly improved location accuracy. Lastly, we visualized estimated RSS-based locations of one week of whip-poor-will data and compared them to GPS data generated from the same individual. Previous studies have accounted for types of environmental interference (like elevation) in the field but have avoided incorporating habitat-specific factors by working with node networks covering a relatively small area, but in this study, we examined the potential to scale up for larger areas and in more complex habitats.</p> <p> </p>
F I G U R E 2 in Movement and habitat shift responses of juvenile Atlantic Salmon (Salmo salar) to annually permanent stream flooding
F I G U R E 2 Mahers River study reach, Newfoundland, showing the habitat conditions before (riffle run) and after (pool) annual flooding.
F I G U R E 1 in Movement and habitat shift responses of juvenile Atlantic Salmon (Salmo salar) to annually permanent stream flooding
F I G U R E 1 Mahers River and North Arm River, Newfoundland, Canada. The seasonally created pool (Flooded Pool reach) is located within Mahers River. Two control reaches were located in Mahers River; one immediately upriver of the created pool habitat (Riffle Above Pool reach) and another approximate 3 km upstream (Mahers Control reach) and two additional control reaches were located in the nearby North Arm River (North Arm 1 and 2).
Fig.5 in Distribution Of Five Interesting Woodland Key Habitat Bryophyte Indicator Species In Latvia
Fig.5. Jamesoniella autumnalis distribution in Geobotanical regions of Latvia in 5x5 km square network. (Latvian State Forest Service data (circle), personal database of Anna Mežaka (triangle), personal data base of Sanita Putna (square)). Geobotanical regions (Ramans 1994): A-Piejūra, B-Kursa, C-Ventas land, D - Austrumkursa, E-Rietumzemgale, F-Austrumzemgale, G-Dienvidvidzeme, H-Ziemeļvidzeme, I-Gaujas land, J- upland Vidzeme, K-Austrumvidzeme, L-Aiviekstes land, M-Augšzeme, N- upland Latgale, O-Austrumlatgale.
Fig.3 in Distribution Of Five Interesting Woodland Key Habitat Bryophyte Indicator Species In Latvia
Fig.3. Neckera pennata distribution in Geobotanical regions of Latvia in 5x5 km square network. (Latvian State Forest Service data (circle), personal database of Anna Mežaka (triangle), personal data base of Sanita Putna (square)). Geobotanical regions (Ramans 1994): A-Piejūra, B-Kursa, C-Ventas land, D - Austrumkursa, E-Rietumzemgale, F-Austrumzemgale, G-Dienvidvidzeme, H-Ziemeļvidzeme, I-Gaujas land, J- upland Vidzemes, K-Austrumvidzeme, L-Aiviekstes land, M-Augšzeme, N- upland Latgale, O-Austrumlatgale.
Fig.1 in Distribution Of Five Interesting Woodland Key Habitat Bryophyte Indicator Species In Latvia
Fig.1. Anomodon longifolius distribution in Geobotanical regions of Latvia in 5x5 km square network. (Latvian State Forest Service data (circle), personal database of Anna Mežaka (triangle), personal data base of Sanita Putna (square)). Geobotanical reģions (Ramans 1994): A-Piejūra, B-Kursa, C-Ventas land, D - Austrumnkursa, E-Rietumzemgale, F-Austrumzemgale, G-Dienvidvidzeme, H-Ziemeļvidzeme, I-Gaujas land, J-upland Vidzeme, K-Austrumvidzeme, L-Aiviekstes land, M-Augšzeme, N-upland Latgale, O-Austrumlatgale.
Fig.4 in Distribution Of Five Interesting Woodland Key Habitat Bryophyte Indicator Species In Latvia
Fig.4. Lejeunea cavifolia distribution in Geobotanical regions of Latvia in 5x5 km square network. (Latvian State Forest Service data (circle), personal database of Anna Mežaka (triangle), personal data base of Sanita Putna (square)). Geobotanical regions (Ramans 1994): A-Piejūra, B-Kursa, C-Ventas land, D - Austrumkursa, E-Rietumzemgale, F-Austrumzemgale, G-Dienvidvidzeme, H-Ziemeļvidzeme, I-Gaujas land, J- upland Vidzeme, K-Austrumvidzeme, L-Aiviekstes land, M-Augšzeme, N- upland Latgale, O-Austrumlatgale.
Fig.2 in Distribution Of Five Interesting Woodland Key Habitat Bryophyte Indicator Species In Latvia
Fig.2. Homalia trichomanoides distribution in Geobotanical regions of Latvia in 5x5 km square network. (Latvian State Forest Service data (circle), personal database of Anna Mežaka (triangle), personal data base of Sanita Putna (square)). Geobotanical regions (Ramans 1994): A-Piejūra, B-Kursa, C-Ventas land, D - Austrumkursa, E-Rietumzemgale, F-Austrumzemgale, G-Dienvidvidzeme, H-Ziemeļvidzeme, I-Gaujas land, J- upland Vidzeme, K-Austrumvidzeme, L-Aiviekstes land, M-Augšzeme, N- upland Latgale, O-Austrumlatgale.
РИС. 1. ОЗеро Дальнее (А) и место обнаруЖениЯ Beringiana beringiana в оЗере (B, С), песчаный грунт в месте обитаниЯ беЗЗубок (D). Стрелками обоЗначено место сбора моллюсков. FIG. 1. Lake Dalneye (A) with the sampling site (B, C), sandy bottom in the habitat of mollusks (D). The arrows indicate the site of material sampling. in Первые данные о морфологии глохидиев двустворчатых моллюсков Beringiana beringiana (Bivalvia, Unionidae) оЗера Дальнее, Камчатка
РИС. 1. ОЗеро Дальнее (А) и место обнаруЖениЯ Beringiana beringiana в оЗере (B, С), песчаный грунт в месте обитаниЯ беЗЗубок (D). Стрелками обоЗначено место сбора моллюсков. FIG. 1. Lake Dalneye (A) with the sampling site (B, C), sandy bottom in the habitat of mollusks (D). The arrows indicate the site of material sampling.
РИС. 1. СмеШаннаЯ колониЯ Monacha claustralis и M. cartusiana во Львове. А. Местообитание, основные места сбора улиток отмечены красными крестиками. B. НеполовоЗрелаЯ особь на ветке туи. C. Раковины анатомически определенных M. claustralis. D. То же длЯ M. cartusiana. МасШтаб 5 мм. FIG. 1. Mixed colony of Monacha claustralis and M. cartusiana in Lviv. A. Habitat, the main places of snail collecting marked with red crosses. B. Immature specimen on a thuja branch. C. Shells of anatomically identified M. claustralis. D. The same for M. cartusiana. Scale bar 5 mm. in Monacha claustralis и M. cartusiana (Gastropoda, Hygromiidae) - два криптических вида антропохорных наЗемных моллюсков на Западе Украины
РИС. 1. СмеШаннаЯ колониЯ Monacha claustralis и M. cartusiana во Львове. А. Местообитание, основные места сбора улиток отмечены красными крестиками. B. НеполовоЗрелаЯ особь на ветке туи. C. Раковины анатомически определенных M. claustralis. D. То же длЯ M. cartusiana. МасШтаб 5 мм. FIG. 1. Mixed colony of Monacha claustralis and M. cartusiana in Lviv. A. Habitat, the main places of snail collecting marked with red crosses. B. Immature specimen on a thuja branch. C. Shells of anatomically identified M. claustralis. D. The same for M. cartusiana. Scale bar 5 mm.
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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.