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80 results for “environmental management”
Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat
<p>Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 < AUC < 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration. --</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.
Manageable Environmental Factors in Migraine
ClinicalTrials.gov study NCT06304675. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.
Health and Environmental Effects of Boiler Management Systems in Social Housing
ClinicalTrials.gov study NCT00874692. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Social and environmental impacts of forest management certification in Indonesia
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Data from: Vulnerability mapping as a tool to manage the environmental impacts of oil and gas extraction
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Data from: Land management modulates the environmental controls on global earthworm communities
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Landscape genomics of the streamside salamander: Implications for species management in the face of environmental change
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Data from: Environmental DNA for the enumeration and management of Pacific salmon
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Data from: Advanced technologies and data management practices in environmental science: lessons from academia
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Data from: A multi-taxa assessment of the effectiveness of agri-environmental schemes for biodiversity management
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Data from: Adapting environmental management to uncertain but inevitable change
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Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat
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Data from: Parallel evolution and adaptation to environmental factors in a marine flatfish: implications for fisheries and aquaculture management of the turbot (Scophthalmus maximus)
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Data from: Development and testing of an environmental DNA (eDNA) assay for endangered Atlantic sturgeon to assess its potential as a monitoring and management tool
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NH Department of Environmental Services (NHDES) Watershed Management Bureau Biology Section: Lake Trophic Survey Environmental Monitoring data, 1995-2014
This program was initially established in 1975 in order to identify the trophic state of NH lakes and ponds, as required by Section 314(a) of PL 92-500 (the Federal Water Pollution Control Act Amendments of 1972). The purpose of the program is to determine lake trophic class and monitor physical, chemical and biological water quality parameters. Each year, 40 different lakes and ponds are surveyed, once in the summer and once in the winter. The surveys are comprehensive physical, chemical and biological surveys, including electronic depth soundings, macrophyte identifications and abundance ratings, shoreline bacteria sampling and at the deep spot a temperature/dissolved oxygen/percent saturation profile, Secchi disk transparency reading, samples for chlorophyll, Ca, Mg Na, and K in the upper water layer, phytoplankton and zooplankton net hauls for identification and counts and discrete water samples at two or three depths for pH, acid neutralization capacity, apparent color, conductivity, TP, Total Kjeldahl nitrogen, nitrite+nitrate nitrogen, chloride, and sulfate. The surveys are designed to assess current baseline conditions and compliance with water quality criteria, identify the lake’s trophic status, determine acid rain impacts and the existence of exotic aquatic plants and provide information for gross long-term trend analyses.
NH Department of Environmental Studies (NHDES): Watershed Management Bureau Volunteer Lakes Assessment Program Lake Sunapee, 1986-2012
Data on Lake Sunapee were compiled by Kathleen Weathers’ Lab, Cary Institute of Ecosystem Studies. Data were collected by Lake Sunapee Protective Association (LSPA) and analyzed by NH Department of Environmental Services (NHDES). LSPA has been concerned with water quality since its founding in 1898, when the issues were sawdust and trash in the lake and the level of the lake water. In the 1950’s LSPA collected water samples and tested for E.coli in order to have Lake Sunapee meet the standards to be named a class A (drinking water quality) lake in New Hampshire. Starting in the 1980’s, LSPA volunteer water quality monitors have been regularly sampling Lake Sunapee’s water in cove and deep sites in Lake Sunapee, and more recently in its tributary streams. The samples are analyzed in LSPA’s Water Quality Laboratory at Colby-Sawyer College; NH Department of Environmental Services provides an annual water quality report based on its analysis of the data as part of the VLAP (Volunteer Lake Assessment) Program. The LSPA lab at Colby-Sawyer College, run by Bonnie Lewis under strict quality standards as a sister lab to the state lab at NH Department of Environmental Services, also processes water samples for about twenty five area lakes.
NH Department of Environmental Services (NHDES) Watershed Management Bureau Biology Section: Volunteer Lake Assessment Program (VLAP) Environmental Monitoring data, 1995-2014
The New Hampshire Volunteer Lake Assessment Program was initiated in 1985 in response to an expressed desire of lake associations to be involved in lake protection and watershed management. VLAP is a cooperative program between volunteer monitors and the DES which leads to local awareness of land use and human practices that may be detrimental to lake quality and also empowers communities in their decision-making regarding lake management issues. The three major partners are the NHDES Biology Section, numerous volunteer monitors located throughout the state, and the VLAP satellite laboratories. Sara Steiner, NHDES VLAP Coordinator (who reports directly to Jody Connor, the Limnology Center Director and VLAP Program Manager), has the overall responsibility for training the volunteer monitors throughout the state in sample collection and watershed monitoring, conducting annual site visits and training interns to conduct annual site visits. NHDES and the volunteer monitors will collect samples from their lake/pond and its watershed, and will then bring samples to the NHDES Limnology Center, the Lake Sunapee Region Laboratory at Colby Sawyer College in New London, or the Environmental Research Laboratory at Plymouth State University in Plymouth. The purpose of VLAP is to assess the chemical and biological characteristics of the lakes and ponds throughout the state to determine overall health of the system. Environmental results are measured by making comparisons to established means and ranges of water quality for the state of New Hampshire. Chemical, biological, and physical parameters are measured and compared to lakes throughout the state. This data is provided to NHDES and the volunteer monitors. The data is used by the NHDES for assessment, education, and reporting purposes. The data are used by the volunteer monitors for educational purposes and for guiding local lake management activities. Volunteers collect water at least once per month during the summer (June –
Data from: An environmental impact assessment of different management regimes in eucalypt plantations in southern China using Landscape Function Analysis
<p>There are global concerns regarding the detrimental environmental impacts of industrial forest plantations developed over the past 30 years. To address this concern, the Landscape Function Analysis methodology was used to rapidly assess indices of soil stability, water infiltration, and nutrient cycling within eucalypt plantations at different growth stages and under different management regimes in Guangxi Province, China. Results showed that these plantations under both regimes were approaching an ecologically functional state by the time of harvest. However, within the plantation management that included the burning of post-harvest biomass residues, indices of water infiltration, and nutrient cycling were significantly lower than within the plantation that retained post-harvest residues. Indicators of rain splash protection, perennial vegetation cover, and litter accumulation were all lower in the plantation that practiced residue burning and pre-planting cultivation. Retention of post-harvest residues improves landscape functionality at the time of re-planting. Our results indicate that burning and extensive cultivation prior to re-planting should be minimized.</p>
Data from: Women are underrepresented on the editorial boards of journals in environmental biology and natural resource management
Despite women earning similar numbers of graduate degrees as men in STEM disciplines, they are underrepresented in upper level positions in both academia and industry. Editorial board memberships are an important example of such positions; membership is both a professional honor in recognition of achievement and an opportunity for professional advancement. We surveyed 10 highly regarded journals in environmental biology, natural resource management, and plant sciences to quantify the number of women on their editorial boards and in positions of editorial leadership (i.e., Associate Editors and Editors-in-Chief) from 1985 to 2013. We found that during this time period only 16% of subject editors were women, with more pronounced disparities in positions of editorial leadership. Although the trend was towards improvement over time, there was surprising variation between journals, including those with similar disciplinary foci. While demographic changes in academia may reduce these disparities over time, we argue journals should proactively strive for gender parity on their editorial boards. This will both increase the number of women afforded the opportunities and benefits that accompany board membership and increase the number of role models and potential mentors for early-career scientists and students.
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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.