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379 results for “environmental change”
Figure 1 in Perception of Amazonian fishers regarding environmental changes as causes of drastic events of fish mortality
Figure 1. Image of the Ilha do Careiro, immediately below the confluence of the Negro and Solimões rivers (Amazonas state), area of black and whitewaters mixing and, inside, the huge floodplain system known as Lago do Rei.
Figure 4. A - Sentinel 2 in Perception of Amazonian fishers regarding environmental changes as causes of drastic events of fish mortality
Figure 4. A - Sentinel 2 satellite image of Lago do Rei on 20th November 2018. B - Sentinel 2 satellite image of the Lago do Rei on 20th June 2018. C - Sentinel 2 satellite image of the Lago do Rei on 15th November 2019. D - Sentinel 2 satellite image of Lago do Rei on 6th January 2020.
Figure 2. A in Perception of Amazonian fishers regarding environmental changes as causes of drastic events of fish mortality
Figure 2. A biplot is showing the years by the number of days with river level below 18 meters and the amplitude (meters) of the annual flood pulse.
Figure 5 in Perception of Amazonian fishers regarding environmental changes as causes of drastic events of fish mortality
Figure 5. Relationship between the river level, measured in the Port of Manaus – Station 14990000, and the Oceanic Niño Index (ONI), from 2009 to 2020, taking as reference the level of disconnection between Lago do Rei and the Amazon River.
Figure 3 in Perception of Amazonian fishers regarding environmental changes as causes of drastic events of fish mortality
Figure 3. Analysis of the water surface of Lago do Rei using the modified normalized difference water index for the years 2015 to 2020.
Fig. 2 in Host manipulation in the face of environmental changes: Ecological consequences
Fig. 2. Examples of the impacts of temperature on a system of gammarid species infected by acanthocephalan parasites. Final host varies depending on parasite species (either a fish or a bird). Solid lines represent assumption supported by studies, while dotted lines are expectations that remain to be investigated. In this system, (1) the temperature widely influences the time of development or parasites within the intermediate hosts, which is likely to be driven by the metabolic rate of parasites (Tokeson and Holmes, 1982). Several studies suggested that (2) the time of development of parasites is linked to the intensity of their manipulation (Franceschi et al., 2010b, 2008), which in turn might (3) influence the increase of predation rate between the final host and the intermediate host. (4) Temperature is also likely to influence the final host metabolism (Bystr¨om et al., 2006), (5) influencing its predation rate (Bystr¨om et al., 2006). Altogether, (6) modifications in manipulation and predation rates are likely to induce changes in parasites' population. Meanwhile, (7) temperature also affects the metabolism of gammarid hosts (Issartel et al., 2005), inducing changes in their food consumption (Pellan et al., 2015). (8) Given that infection depends on food consumption, the risk of infection might vary accordingly, affecting parasites' population. Although its direct effect has not been investigated yet, (9) temperature is also likely to alter the intensity of manipulation, for instance through its effect on hosts' metabolism and activity, and therefore (10) secondarily impact parasite population dynamic.
Fig. 1 in Host manipulation in the face of environmental changes: Ecological consequences
Fig. 1. Schematic representation of all the interacting factors in a system involving parasite manipulation. The intensity of host manipulation induced by parasites is likely to be influenced by a variety of parameters concerning the parasites, their hosts and environmental properties. In return, manipulation can also have an impact on those parameters. Moreover, all components in the systems also interact with each other.
Environmental behavior of novel "smart" anti-corrosion nanomaterials in a global change scenario
<div>The present dataset contains dynamic light scattering data and quantification of anions (corrosion inhibitors) and target metals (Zn and Al) in saltwater dispersions aiming to assess and compare the environmental behavior of four anti-corrosion nanomaterials in the following conditions: “temperate seawater” (T=20 ºC, pH=8.0, without HA); “tropical seawater” (T=30 ºC, pH=8.0, without HA), “acidified temperate seawater” (T=20 ºC, pH=7.6, without HA), “acidified tropical seawater” (T=30 ºC, pH 7.6, without HA); “temperate seawater enriched with natural organic matter (NOM)” (T=20 ºC, pH=8.0, with HA); “tropical seawater enriched NOM” (T=30 ºC, pH=8.0, with HA).</div> <div> </div> <div> </div>
Figure 1 in Exploring the dynamics of small pelagic fish catches in the Marmara Sea in relation to changing environmental and bio-optical parameters
Figure 1. Time series of deseasonalised Chl-a, net primary productivity (NPP), and sea surface temperature (SST). Solid lines show the time series, dash-dot lines show the deseasonalised time series, dashed lines indicate their respective nonlinear trends, and flat solid lines show linear trend components.
Figure 2 in Exploring the dynamics of small pelagic fish catches in the Marmara Sea in relation to changing environmental and bio-optical parameters
Figure 2. Time series of fisheries catches (tons) and fishing effort in the Marmara Sea between 2000 and 2019. Flat solid lines indicate linear trends.
Figure 7 in Environmental niche modelling of the Chinese pond mussel invasion in Europe under climate change scenarios
Figure 7. Map of potential invasion range of S. woodiana in Europe under the RCP 8.5 climate change scenario at 2080-2100: green filling indicates areas defined as suitable using minimum presence (MP) threshold; orange filling indicates areas defined as suitable using 10th percentile presence (10P) threshold. Black dots indicate species record used for SDM.
Figure 6 in Environmental niche modelling of the Chinese pond mussel invasion in Europe under climate change scenarios
Figure 6. Map of potential invasion range of S. woodiana in Europe under the RCP 4.5 climate change scenario at 2080-2100: green filling indicates areas defined as suitable using minimum presence (MP) threshold; orange filling indicates areas defined as suitable using 10th percentile presence (10P) threshold. Black dots indicate species record used for SDM.
Figure 4 in Environmental niche modelling of the Chinese pond mussel invasion in Europe under climate change scenarios
Figure 4. Response curves of the environmental variables selected for prediction of S. woodiana distribution under the RCP 8.5 scenario. Each curve (green line) shows how the logistic prediction changes as each environmental variable is varied. The orange dashed line crosses the maximum value of the variable.
Figure 5 in Environmental niche modelling of the Chinese pond mussel invasion in Europe under climate change scenarios
Figure 5. Map of potential invasion range of S. woodiana in Europe under the recent climate conditions: green filling indicates areas defined as suitable using minimum presence (MP) threshold; orange filling indicates areas defined as suitable using 10th percentile presence (10P) threshold. Black dots indicate species record used for SDM.
Figure 3 in Environmental niche modelling of the Chinese pond mussel invasion in Europe under climate change scenarios
Figure 3. Response curves of the environmental variables selected for prediction of S. woodiana distribution under the RCP 4.5 scenario. Each curve (green line) shows how the logistic prediction changes as each environmental variable is varied. The orange dashed line crosses the maximum value of the variable.
Figure 1 in Environmental niche modelling of the Chinese pond mussel invasion in Europe under climate change scenarios
Figure 1. Map of records of S. woodiana in Europe obtained from GBIF database and published sources (Vikhrev et al., 2024).
Fig. 3 in Adaptations, life-history traits and ecological mechanisms of parasites to survive extremes and environmental unpredictability in the face of climate change
Fig. 3. Flow chart outlining factors that can influence the response of parasites to climate change.
Figure 7 in Effect of environmental change after the 2011 tsunami on the population dynamics of Japanese tubesnout Aulichthys japonicus (Gasterosteiformes)
Figure 7. – Photographs showing scraped an ascidian Halocynthia roretzi (A) and an egg mass (B) of the Japanese tubesnout Aulichthys japonicus, which was spawned and developed within the ascidians.
Figure 4 in Effect of environmental change after the 2011 tsunami on the population dynamics of Japanese tubesnout Aulichthys japonicus (Gasterosteiformes)
Figure 4. – Relationship between the occurrence of larvae of Aulichthys japonicus collected from 2012 to 2013 and water temperature (°C).
Figure 3 in Effect of environmental change after the 2011 tsunami on the population dynamics of Japanese tubesnout Aulichthys japonicus (Gasterosteiformes)
Figure 3. – Monthly changes in the number of individuals for larva, juvenile and young Aulichthys japonicus and water temperature collected at the seagrass bed in Namiita beach in 2012.
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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.