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192 results for “environmental modelling”
Fig. 4 in The ant fauna of Castelporziano Presidential Reserve (Rome, Italy) as a model for the analysis of ant community structure in relation to environmental variation in Mediterranean ecosystems
Fig. 4 Multidimentional scaling performed on abundance ranks of ant species during May and July 2006. Symbols represent the 28 transects analysed (see text for details) and they are sorted according to trapping period
Fig. 3 in The ant fauna of Castelporziano Presidential Reserve (Rome, Italy) as a model for the analysis of ant community structure in relation to environmental variation in Mediterranean ecosystems
Fig. 3 Overall ant abundance (mean) from pitfall trapping along the 7 sampled sites during May and July
Fig. 2 in The ant fauna of Castelporziano Presidential Reserve (Rome, Italy) as a model for the analysis of ant community structure in relation to environmental variation in Mediterranean ecosystems
Fig. 2 Ant species richness (mean) from pitfall trapping along the 7 sampled sites during May and July
Fig. 1 in The ant fauna of Castelporziano Presidential Reserve (Rome, Italy) as a model for the analysis of ant community structure in relation to environmental variation in Mediterranean ecosystems
Fig. 1 Species accumulation curves of low vegetation sites (A) and of high vegetation sites (B). The values on y-axis correspond to Sobs (Mao Tau) values as described in Colwell (2005). Each line represents a different site type
Abundance Trend Indicator - Models, Prediction, Stacked Environmental Data and Training Set Similarity
<p># Readme</p> <p>These trained models can be used to predict the abundance trends of New Zealand's forest species and can be used together with the code in https://github.com/lnilya/abundance-trend-indicator</p> <p>Since the process of using the models requires coding expertise and some setting up, please make sure to reach out to ilya.shabanov@vuw.ac.nz for any questions. All files will require the code in the repository to be read and used. </p> <p>If you want to explore the results generated with these models, please visit https://ati-nz-predictions-7e6f3d514735.herokuapp.com/ for a user-friendly, interactive UI.</p> <p>## Contents</p> <p>_models: Contains the trained models (Artificial Neural Network (ANN), Random Forest (RF), SVMW (Support vector machine) and GLM (logistic regression)) at different degrees of noise filtering, different datasets and variable sets. The model files also contain test and training scores. To load the files please refer to the readme in the code repository: ttps://github.com/lnilya/abundance-trend-indicator</p> <p><br>_predictions/_environment: Contains the predictor variables for the study area (New Zealand, 1950-2019) that are needed by the models to make predictions. </p> <p>_predictions/_similarity: Contains the masks of areas that can be predicted by models and are similar to the training set.</p> <p>_predictions/_ati: Contain the predicted results for the abundance trend. These can be explored on https://ati-nz-predictions-7e6f3d514735.herokuapp.com/ </p> <p> </p>
Environmentally induced lipidome adaptation in the bacterial model organism M. extorquens
<p>Cells, from microbes to man, adapt their membranes in response to the environment to maintain functionality. How cells sense environmental change/stimuli and adapt their membrane accordingly is unclear. In particular, how lipid composition changes and what lipid structural features are necessary for homeostatic adaptation remains relatively undefined. Here, we examine the simple yet adaptive lipidome of the plant-associated Gram-negative bacterium <em>Methylobacterium extorquens </em>over<em> </em>a range of chemical and physical conditions. Using shotgun lipidomics, we explored adaptivity over varying temperature, hyperosmotic and detergent stress, carbon sources, and cell density. Globally, we observed that as few as 10 lipids, representing ca. 30% of the lipidome, characterized by 9 structural features account for 90% of the total changes. We revealed that variations in lipid structural features are not monotonic over a given range of conditions (e.g. temperature) and are not evenly distributed across lipid classes. Thus, despite the compositional simplicity of this lipidome, the patterns in lipidomic remodeling suggest a highly adaptive mechanism with many degrees of freedom. Our observations reveal constraints on the minimal lipidomic requirements for an adaptive membrane and provide a resource for unraveling the design principles of living membranes.</p>
Supplementary data: model results for "Labor market evolution is a key determinant of global agroeconomic and environmental futures"
<p>This compressed dataset includes the queried CVS files from 16 GCAM data bases generated for the study titled "<strong>Labor market evolution is a key determinant of global agroeconomic and environmental futures</strong>".</p> <p>The data sets provided here came from the GCAM model output. Please find the model and code information at the GitHub repo: <a href="https://github.com/realxinzhao/paper-nc2024-LandBasedCDR-GCAM" target="_blank" rel="noopener">realxinzhao/paper-nc2024-LandBasedCDR-GCAM</a>.</p> <p>In addition, the data were used for generating results used in the paper. See more information at <a href="https://github.com/realxinzhao/paper-nfood2024-AgLaborEvolution-DisplayItems" target="_blank" rel="noopener">realxinzhao/paper-nfood2024-AgLaborEvolution-DisplayItems</a>.</p>
Figure 2 in Presence of the crab-eating fox Cerdocyon thous in La Rioja, Argentina, and implications for its geographic and environmental niche modeling
Figure 2: Cerdocyon thous present environmental niche models result maps. (A) South model. (B) Detail of model (A) for the province of La Rioja. (C) Complete model. (D) Detail of model (C) for the province of La Rioja. The color gradient indicates the suitability values, where white represents minimum values (0–10 %) and red the maximum values (76–100 %), as detailed in the figure.
Figure 1 in Presence of the crab-eating fox Cerdocyon thous in La Rioja, Argentina, and implications for its geographic and environmental niche modeling
Figure 1: New records Cerdocyon thous in La Rioja. (A–C) Photograps taken near Huaco River (2020–2021). (D) C. thous skin collected by Parodi in 1929, deposited as MACN 29.882 and label information.
Figure 3 in Presence of the crab-eating fox Cerdocyon thous in La Rioja, Argentina, and implications for its geographic and environmental niche modeling
Figure 3: Cerdocyon thous past environmental niche models for result maps. (A) Last interglacial model. (B) Last glacial maximum model. (C) Middle Holocene model. The color gradient indicates the suitability values, where white represents minimum values (0–10 %) and red the maximum values (76–100 %), as detailed in the figure.
Results and assumptions for: Modeling the Circular Economy in Environmentally Extended Input-Output Tables: methods, software and case study
<p>This dataset presents supplementary information for <em>"Modeling the Circular Economy in Environmentally Extended Input-Output Tables: methods, software and case study" </em><a href="https://doi.org/10.1016/j.resconrec.2019.104508">https://doi.org/10.1016/j.resconrec.2019.104508</a></p> <p>The data was processed and results were obtained through https://cmlplatform.github.io/pycirk/</p> <p> </p> <p><br> Annex I: Scenario assumptions and modeling choices and complete results (file Annex_I.xlsx) <br> Annex II: Contains analysis of other software, database modifications, and list of affected categories (file Annex_II.docx) <br> Results: settings, assumptions, results and their analysis from the case study presented in the paper (file Donati_CE_EEIO_Mo_SI.tar.gz)</p>
Data for: Habitat functionality: integrating environmental and geographic space in niche modelling for conservation planning
<p>Niche modelling is typically used to assess the effects of anthropogenic land use and climate change on species distributions and to inform spatial conservation planning. These models focus on the suitability of local biotic and abiotic conditions for a species in environmental space (E-space). Although movements also affect species occurrence, efforts to formally integrate geographic space (G-space) into niche modelling have been hindered by the lack of comprehensive theoretical frameworks. </p> <p>We propose the 'functional habitat' framework to define areas that are simultaneously of high-quality in E-space and functionally connected to other suitable habitat in G-space. Originating in metapopulation ecology, approaches have been developed to assess the amount of suitable connected habitat, based on the proximity between pairs of locations. Using network theory, which operates in topological space (T-space, defined by a network), we extended these metapopulation approaches to integrate movement constraints in G-space with niche modelling in E-space. </p> <p>We demonstrate the functional habitat framework using empirical data (GPS-tracking and population monitoring) throughout the European wild mountain reindeer (<em>Rangifer t. tarandus</em>) distribution range. We show that functional habitat outperforms traditional suitability in explaining the species' distribution. This approach integrates effects from habitat loss and fragmentation for spatial conservation planning and avoids overemphasizing small, inaccessible areas with locally suitable habitat. The functional habitat framework formally integrates biotic, abiotic, and movement constraints in niche modeling using network theory, thus opening a wide range of applications in spatial conservation planning.</p>
rMATS analysis of alternative splicing events in a mouse model of environmental liver disease
<p>rMATS (https://rnaseq-mats.sourceforge.io/) was used to identify differential alternative splicing events (ASEs) corresponding to all five major types of AS patterns, <em>i.e</em>., skipped exon (SE), mutually exclusive exons (MXE), alternative 3’ splice site (A3SS), alternative 5’ splice site (A5SS), and retained intron (RI), in the HFD-fed mouse livers exposed to Ar1260, PCB126, or Ar1260 + PCB126 co-exposure compared to vehicle control This dataset identifies differential ASEs corresponding to all five major types of AS patterns [<em>i.e.,</em> skipped exon (SE), mutually exclusive exons (MXE), alternative 3’ splice site (A3’SS), alternative 5’ splice site (A5’SS), and retained intron (RI)], between Ar1260, PCB126, and Ar1260 + PCB126-exposed samples and vehicle control. For each ASE, the estimation of the alternatively spliced region usage is defined as percent-spliced in (ψ or PSI). Each comparison was made to identify differential ASEs with an associated change in exon usage (∆ψ). Differential ASEs were detected with an FDR of <0.05 and |∆ψ| of≥5%. The difference in the proportion of the two isoforms of the transcript was expressed as the change in mean percentage spliced-inform included (mean ∆ψ).</p>
Community-Empowerment and Environmental Enrichment-based Co-management (CEEEC) Model and Mechanisms for Improving Health of Older Stroke Patients With Multimorbidity
ClinicalTrials.gov study NCT06975501. IPD Sharing: NO. Countries: 1. Publications: 7.
Explore Association Models Between Environmental Hormones andBreast Cancer
ClinicalTrials.gov study NCT06765395. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Ecological genomics meets community-level modeling of biodiversity: mapping the genomic landscape of current and future environmental adaptation
Open the record for dataset details and reuse information.
Data from: Correlation between genetic diversity and environmental suitability: taking uncertainty from ecological niche models into account
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Data from: Investigating the genetic architecture of conditional strategies using the environmental threshold model
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Data from: Development of a protocol for environmental impact studies using causal modelling
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Data from: Using occupancy modeling to compare environmental DNA to traditional field methods for regional-scale monitoring of an endangered aquatic species
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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.