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385 results for “Environmental factors”
Inter-Chemical Correlation results for the study: HHEARx2016-1432 (Micronutrient deficiencies, environmental exposures and severe malaria: Risk factors for adverse neurodevelopmental outcomes in Ugandan children)
Title: Micronutrient deficiencies, environmental exposures and severe malaria: Risk factors for adverse neurodevelopmental outcomes in Ugandan children <br>Species: Homo sapiens <br>Number of samples: 1256 <br>Number of named analytes: 51 <br>Datasource url: https://hheardatacenter.mssm.edu/PublicFile/ViewPublicFile?projectid=5 <br>
Role of environmental factors in the genetic structure of a highly mobile seabird
<p><strong>Aim:</strong> Environmental features can act as selection pressures and barriers to gene flow between populations. The genetic structuring of highly mobile but philopatric seabirds creates a paradox, and the role of oceanographic and geographic variables is still poorly understood. In this study, we investigate the influence of environmental and geographic variables in the genetic and phenotypic diversity of a pantropical seabird breeding in islands and archipelagos separated by different geographic distances, up to thousand kilometers, and which differ in environmental characteristics.</p> <p><strong>Location:</strong> Islands and archipelagos in the southwestern Atlantic Ocean.</p> <p><strong>Taxon:</strong> <em>Sula dactylatra</em>, Lesson, 1831 (masked booby)<em>.</em></p> <p><strong>Methods:</strong> The population structure of the species was accessed through mitochondrial and nuclear DNA. To test Isolation by Environment (IBE) <em>vs</em>. by Distance (IBD), sea surface temperature, primary productivity, and salinity, as well as isotopic niche based on carbon and nitrogen, and distances between colonies and from the continent, were used. We also tested the correlation between the genetic structure and the morphometry of individuals in each colony.</p> <p><strong>Results:</strong> We identified the presence of low genetic structure between populations. Nevertheless, differences were identified between inshore and offshore colonies, with the influence of landscape characteristics of these two types of environment. The morphometric and isotopic niche variations are consistent with this segregation.</p> <p><strong>Main conclusions:</strong> Environmental variables of coastal and oceanic environments seem to influence the genetic structure of masked boobies, even though it is low in the SW Atlantic Ocean, highlighting the role of environmental heterogeneity in shaping biodiversity.</p>
Demographic factors and the environmental Kuznets curve: global plastic pollution by 2050 could be 2 to 4 times worse than projected
<p>These data are made of two files. One file provides the observed data we collected and cleaned from the World Bank database. The second file provides the simulation results from the STIRPAT model we designed based on the observed data abovementioned. Our results can be summarised as follows:</p> <p>Since 2015, the detrimental effects of plastic pollution have attracted media, public, and governmental attention. Considering economic growth is inevitable and a key driver of plastic contamination, it is worthwhile to analyze the environmental Kuznets curve (EKC) relationship between economic development and plastic pollution. To this end, we contribute by being the first to (i) use the Stochastic Impacts by Regression on Population, Affluence, and technology model (STIRPAT model) to investigate this EKC relationship; (ii) provide a comprehensive analysis of how demographic factors affect plastic pollution; and (iii) use panel model techniques to examine the drivers of plastic pollution. Our empirical results support an inverted U-shaped relationship between plastic pollution and income. They show that at current trends, global plastic pollution (that is, annual discard of inadequately managed plastic waste) is expected to grow from 52 million tons per year in 2020 to 257 million tons per year in 2050.</p>
The influence of environmental factors on the distribution and density of invasive Centaurea stoebe across Northeastern USA, 2013 - 2018
Centaurea stoebe (Asteraceae; spotted knapweed) is an emerging invader in northeast US, and is a major invasive plant in the northern Midwest and western USA. Although it has been present in New York State (NYS) for over 100 years, its apparent recent population increases and spread provide a rare opportunity to study a plant in the early stages of invasion. Therefore, a study was carried out understand how distinct environmental factors influence the distribution, density and change in density C. stoebe at different spatial scales within its novel range in the northeastern USA. First, we collected field data on the occurrence, density and change in density of this species in North Eastern United States, from 2013 to 2014. Then, using species distribution models, we assessed the potential influence of environmental factors on the invasion of spotted knapweed in northeast US. Within different parts of C. stoebe‘s range, different factors explained its occurrence, density and change in density over 2 years. Across northeast US, climate and soil factors were the most influential predictors explaining C. stoebe‘s distribution, while within Long Island in southeastern NYS and the Adirondack Mountains in northern NYS, precipitation and disturbance respectively were the most important. These results are published in the paper titled The influence of environmental factors on the distribution and density of invasive Centaurea stoebe across Northeastern USA (Akin-Fajiye and Gurevitch, 2018).
Environmental and social factors influencing median income and BMI in the State of Geneva
<p>Hectometric grid (100m x 100m) covering the inhabited areas of the State of Geneva. It contains informations relative to the bmi and median income (GIREC) within the cells, together with a series of environmental and social factors, with which a correlation can be sought.</p>
Fig. 3 in Waterbird Distribution Patterns And Environmentally Impacted Factors In Reclaimed Coastal Wetlands Of The Eastern End Of Nanhui County, Shanghai, China
Fig. 3. Non-metricmulti-dimensionalscaling(NMDS) ordinationplotsshowingwaterbird communitystructurefromsixstudysites.
A global gross primary productivity product considering canopy nitrogen concentrations and multiple environmental factors from 2001 to 2018
<p>The <strong>NI-LUE GPP</strong> with 0.05° spatial resolution and at 8 days interval from 2001 to 2018 was generated based on an improved light use efficiency (LUE) model that simultaneously considered temperature, water, atmospheric CO<sub>2</sub> concentrations, radiation components, and nitrogen (N) index. In the model, a vegetation index capable of characterizing canopy N concentrations was selected to achieve dynamic mixmum LUE. In addition, global optimum temperature distributions mapped based on satellite-retrieved SIF were introduced to calculate the temperature stress factor. This dataset includes<strong> global GPP product</strong> and its <strong>uncertainty data</strong>.</p> <p>Period: 2001-2018</p> <p>Spatial resolution: 0.05°</p> <p>Temporal resolution: 8 days</p> <p>Projection: geographic latitude/longitude</p> <p>Data format: Tiff</p> <p>Upper left coordinates: -180°E, 90°N</p> <p>Scale factor: 1000</p> <p>Unit: gCm-2d-1</p>
Seascape genetics in a polychaete worm: Disentangling the roles of a biogeographic barrier and environmental factors
<p><strong>Aim:</strong> Seascape genomics studies aim to understand how environmental variables shape species diversity through genotype-environment associations. Identifying these effects on lecithotrophic larval species that live in intertidal zones is particularly challenging because they are subject to environmental heterogeneity and anthropogenic events. Here, we evaluate how biotic and abiotic features in the Southwest Atlantic littoral zone can affect a high dispersal species' present and historical demographic.</p> <p><strong>Taxon:</strong> <em>Perinereis ponteni.</em></p> <p><strong>Methods: </strong>We investigated population genetic diversity, connectivity, and past dynamics using 23,300 SNPs generated using Genotyping by sequencing. We tested whether environmental abiotic variables could explain the variance found in genotype frequencies using isolation-by-environment (IBE) and landscape association approaches. These data, combined with paleodistribution simulations and oceanic circulation modeling, were used to infer species demographic history and connectivity patterns.</p> <p><strong>Results:</strong> Along with high levels of connectivity detected, we found a genetic boundary in the southeastern region of Brazil around Cabo Frio (Rio de Janeiro) and a cline trend for some loci. The paleodistribution simulations reveal a spatial refuge in the southeast during the Last Glacial Maximum (21 kya), with the expansion of the northern region. We identified 1,421 SNPs with frequencies associated with eight environmental variables, most of which were related to temperature - the main environmental factor determining IBE.</p> <p><strong>Main conclusions:</strong> <em>Perinereis ponteni</em>, a polychaete with high gene flow capability responds to biogeographic barriers, highlighting the importance of biotic and abiotic factors in shaping population connectivity. Furthermore, the effect of temperature indicates that future climate change and ocean warming can hugely impact this species.</p>
Figure 5 in Effect of environmental factors on the germination and emergence of drunken horse grass (Achnotherum inebrions)
Figure 5. Effect of osmotic potential on the germination of Achnotherum inebrions seeds at 25 C. Vertical bars represent the standard error of the mean, and a logistic sigmoidal regression model is fit to the data.
Figure 6 in Effect of environmental factors on the germination and emergence of drunken horse grass (Achnotherum inebrions)
Figure 6. Germination of Achnotherum inebrions seeds at low osmotic potential. The vertical bars represent the standard error of the mean. Bars with the same letters indicate that there are no significant differences in the mean values by Fisher's protected LSD test (P ≤ 0.05).
Figure 7 in Effect of environmental factors on the germination and emergence of drunken horse grass (Achnotherum inebrions)
Figure 7. Effect of burial depth on the emergence of A. inebrions seeds at 25 C. Vertical bars represent the standard error of the mean,and a logistic sigmoidal regression model is fit to the data.
Figure 4 in Effect of environmental factors on the germination and emergence of drunken horse grass (Achnotherum inebrions)
Figure 4. Effect of buffered pH solutions on the germination of Achnotherum inebrions seeds at 25 C. The vertical bars represent the standard error of the mean. Bars with the same letters indicate that there are no significant differences in the mean values by Fisher's protected LSD test (P ≤ 0.05).
Figure 3 in Effect of environmental factors on the germination and emergence of drunken horse grass (Achnotherum inebrions)
Figure 3. Effects of different photoperiods on the germination of Achnotherum inebrions seeds under 25 C culture conditions. Bars with the same letters indicate that there are no significant differences in the mean values by Fisher's protected LSD test (P ≤ 0.05).
Figure 2 in Effect of environmental factors on the germination and emergence of drunken horse grass (Achnotherum inebrions)
Figure 2. Effect of rewarming on the germination of Achnotherum inebrions seeds at 30/20 C. Rewarming refers to the transfer of ungerminated seeds kept under a constant temperature of 10, 35, or 40 C to a growth chamber set at the optimal temperature, 25 C (CK). The vertical bars represent the standard error of the mean. Bars with
Figure 1 in Effect of environmental factors on the germination and emergence of drunken horse grass (Achnotherum inebrions)
Figure 1. Effect of rewarming on the germination of Achnotherum inebrions seeds at 25 C. Rewarming refers to the transfer of ungerminated seeds kept under a constant temperature of 10, 35, or 40 C to a growth chamber set at the optimal temperature, 25 C (CK). The vertical bars represent the standard error of the mean. Bars with the same
Figure 5 in Germination responses of the invasive hedge cactus (Cereus uruguoyonus) to environmental factors
Figure 5. Seed survival of two Cereus uruguoyonus accessions under controlled aging at 60% relative humidity and 45 C. Parameter estimates for the negative logistic regression model fit to the data are given in Table 1.
Figure 2 in Germination responses of the invasive hedge cactus (Cereus uruguoyonus) to environmental factors
Figure 2. Effect of salt stress on the cumulative germination of four seed accessions of Cereus uruguoyonus. Values with the same letter do not differ at a 5% level of significance.
Figure 3 in Germination responses of the invasive hedge cactus (Cereus uruguoyonus) to environmental factors
Figure 3. Effect of water stress on the cumulative germination of four seed accessions of Cereus uruguoyonus. Values with the same letter do not differ at a 5% level of significance.
Figure 7 in The relationship between Sardinella aurita landings and the environmental factors in Moroccan waters (21°-26°N)
Figure 7. – GAM smoothing curves fit- ted to effects of SST, Chl-a, and UI on S. aurita landings at latitude 22°N. The solid lines are the estimated smoother and the dashed lines represent 95% confidence intervals around the main effects. The black lines at the bottom of each plot indicate where the data values lie.
Fig. 1 in Influence of environmental factors and sessile biota on vagile epibionts: The case of amphipods in marinas across a regional scale Abstract
Fig. 1: Composition (percentage of total abundance) of amphipod assemblages occurred on pontoons of each marina (CHI = Chipiona, AME = Puerto. América, BAR = Barbate, LIN= La Línea, FUE = Fuengirola, ALM = Almería. Numbers represents the three pontoons). Exotic species are represented by red textures.
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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.