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103 results for “Resource management”
Data from: Non-brooding northern bobwhite resource selection during breeding season in a managed longleaf pine ecosystem
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The paradigm of tax-reward and tax-punishment strategies in the advancement of public resource management dynamics
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Management accounting practices mediate the relationship between enterprise resource planning system and sustainability performance under moderating role of corporate governance
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Raw sequence data and analytical resources for: Mitochondrial genome structure and composition in 70 fishes: a key resource for fisheries management in the South Atlantic
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Data for: A new GTSeq resource to facilitate multijurisdictional research and management of walleye Sander vitreus
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The Hidden Midden – Geoarchaeological investigation of sedimentation processes, waste disposal practices and resource management at the La Tène settlement of Basel-Gasfabrik (Switzerland) - Dataset
<p>Data set to the paper " The Hidden Midden – Geoarchaeological investigation of sedimentation processes, waste disposal practices and resource management at the La Tène settlement of Basel-Gasfabrik (Switzerland)" (Geoarchaeology; An International Journal).</p> <p>Supplementary Information 1: Profile photos, polished sections and thin sections scans</p> <p>Supplementary Information 2: Data set of the micromorpological analysis. Most of the data are given in a semiquantitative way: absent [0%] – single [<2%] – few [2–10%] – frequent [10–25%] – numerous [25–50%] – dominant [>50%]</p> <p> </p>
PID and LQR controllers evaluation for the resource utilization management
<p>PID and LQR controllers evaluation for the resource utilization management for the paper submitted to ACSOS-2020.</p>
Resource Management - Cloud Continuum
<p>Dataset and classification of articles and proceedings for Resource Management in the Edge-Fog and Cloud Continuum. Resource management aspects include data aggregation, offloading, P2P data sharing, scheduling (auto-scaling) and load-balancing.</p>
Dataset for: Buffer Management for Trust Computation in Resource-constrained IoT Networks
<p>Dataset for Buffer Management for Trust Computation in Resource-constrained IoT Networks</p>
Data from: Value of information in natural resource management: technical developments and application to pink-footed geese
The "value of information" (VOI) is a generic term for the increase in value resulting from better information to guide management, or alternatively, the value foregone under uncertainty about the impacts of management (Yokota and Thompson, Medical Decision Making 2004; 24: 287). The value of information can be characterized in terms of several metrics, including the expected value of perfect information and the expected value of partial information. We extend the technical framework for the value of information by further developing the relationship between value metrics for partial and perfect information and describing patterns of their performance. We use two different expressions for the expected value of partial information to highlight its relationship to the expected value of perfect information. We also develop the expected value of partial information for hierarchical uncertainties. We highlight patterns in the value of information for the Svalbard population of the pink-footed goose (Anser brachyrhynchus), a population that is subject to uncertainty in both reproduction and survival functions. The framework for valuing information is seen as having widespread potential in resource decision making, and serves as a motivation for resource monitoring, assessment, and collaboration.
Data from: Flower resource and land management drives hoverfly communities and bee abundance in semi-natural and agricultural grasslands
1. Pollination is a key ecosystem service, and appropriate management, particularly in agricultural systems, is essential to maintain a diversity of pollinator guilds. However, management recommendations frequently focus on maintaining plant communities, with the assumption that associated invertebrate populations will be sustained. 2. We tested whether plant community, flower resources and soil moisture would influence hoverfly (Syrphidae) abundance and species richness in floristically-rich semi-natural and floristically-impoverished agricultural grassland communities in Wales (U.K.), and compared these to two Hymenoptera genera, Bombus and Lasioglossum. Interactions between environmental variables were tested using generalised linear modelling, and hoverfly community composition examined using canonical correspondence analysis. 3. There was no difference in hoverfly abundance, species richness, or bee abundance, between grassland types. There was a positive association between hoverfly abundance, species richness and flower abundance in unimproved grasslands. However, this was not evident in agriculturally improved grassland, possibly reflecting intrinsically low flower resource in these habitats, or the presence of plant species with low or relatively inaccessible nectar resources. There was no association between soil moisture content and hoverfly abundance or species richness. 4. Hoverfly community composition was influenced by agricultural improvement and the amount of flower resource. Hoverfly species with semi-aquatic larvae were associated with both semi-natural and agricultural wet grasslands, possibly because of localised larval habitat. Despite the absence of differences in hoverfly abundance and species-richness, distinct hoverfly communities are associated with marshy grasslands, agriculturally improved marshy grasslands and unimproved dry grasslands, but not with improved dry grasslands. 5. Grassland plant community cannot be used as a proxy for pollinator community. Management of grasslands should aim to maximise the pollinator feeding resource, as well as maintain plant communities. Retaining waterlogged ground may enhance the number of hoverflies with semi-aquatic larvae.
Data from: Signatures of selection for bonamiosis resistance in European flat oyster (Ostrea edulis): new genomic tools for breeding programs and management of natural resources
The European flat oyster (Ostrea edulis) is a highly appreciated mollusk with an important aquaculture production throughout the 20th century, in addition to playing an important role on coastal ecosystems. Overexploitation of natural beds, habitat degradation, introduction of non-native species and epidemic outbreaks have severely affected this important resource, particularly, the protozoan parasite Bonamia ostreae, which is the main concern affecting its production and conservation. In order to identify genomic regions and markers potentially associated with bonamiosis resistance, six oyster beds distributed throughout the European Atlantic coast were sampled. Three of them have been exposed to this parasite since the early 1980's and showed some degree of innate resistance (long-term affected group, LTA), while the other three were free of B. ostreae at least until sampling date (naïve group, NV). A total of 14,065 SNPs were analyzed, including 37 markers from candidate genes and 14,028 from a medium density SNP array. Gene diversity was similar between LTA and NV groups suggesting no genetic erosion due to long term exposure to the parasite, and three population clusters were detected using the whole dataset. Tests for divergent selection between NV and LTA groups detected the presence of a very consistent set of 22 markers, located within a putative single genomic region, which suggests the presence of a major quantitative trait locus associated with B. ostreae resistance. Moreover, 324 outlier loci associated with factors other than bonamiosis were identified allowing fully discrimination of all the oyster beds. A practical tool which included the 84 highest discriminative markers for tracing O. edulis populations was developed and tested with empirical data. Results reported herein could assist the production of stocks with improved resistance to bonamiosis, and facilitate the management of oyster beds for recovery production and ecosystem services provided by this species.
Data from: Generic and specific facets of vulnerability for analyzing trade-offs and synergies in natural resource management
<p>1. The concept of vulnerability as the combination of exposure, sensitivity and adaptive capacity to a stressor is gaining traction outside of the climate realm, opening new avenues to address contemporary sustainability issues more holistically. Yet, critical notions that underpin vulnerability have yet to be integrated into its application to natural resource management and non-climatic stressors. In particular, the way generic and stressor-specific facets of vulnerability interact and can inform decision-makers about how interventions combine and/or trade-off remains unexplored.</p> <p>2. Here, we investigate the salience of the generic/specific framing in the context of Chilean artisanal fishing communities engaged in rights-based co-management and experiencing pressures from two stressors: poaching and market volatility. Specifically, we draw on market data combined with socioeconomic surveys conducted with 446 members and leaders from 42 fisher unions to quantitatively investigate potential trade-offs and synergies between facets of vulnerability to poaching and markets.</p> <p>3. Generic adaptive capacity (i.e. flexibility, assets, learning, organization and agency) likely facilitated stressor-specific adaptive capacities to both stressors. High levels of specific adaptive capacity to one stressor neither increased exposure nor undermined specific adaptive capacity to the other stressor. However, adaptive capacity did not translate into exposure reduction as expected, suggesting that adaptation barriers may prevent fishers from mobilizing adaptive capacity into effective adaptive action.</p> <p>4. This study illustrates how breaking down vulnerability into generic and specific facets can help us better anticipate important trade-offs and synergies in management interventions. More generally, it highlights the potential of the climate adaptation and vulnerability literatures in informing place-based management of natural resources.</p>
OpenET model data for assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications
<h2>Overview</h2> <p>This dataset includes daily and monthly evapotranspiration (ET) data from the remote sensing models that comprise the [OpenET](https://openetdata.org/) ensemble as described in Melton et al., 2022 (https://doi.org/10.1111/1752-1688.12956); these data were extracted at specific locations within the contiguous United States that coincide with *in situ* measurement stations, including eddy covaraiance, Bowen-ratio, and lysimeter stations. Model ET data where extracted at each site in this dataset using flux footprints as described in Volk et al., (2023) (https://doi.org/10.1016/j.agrformet.2023.109307). These model data alongside the corresponding *in situ* ET data (https://doi.org/10.1016/j.dib.2023.109274) were subsequently used in the manuscript for the OpenET Phase II Intercomparison and Accuracy Assessment (https://doi.org/10.1038/s44221-023-00181-7). </p> <h3><br>Description of the data and file structure</h3> <p>The dataset is in a compressed (zipped) archive titled "OpenET_PhaseII_model_ET_dataset", so first it needs to be downloaded and extracted. The dataset is comprised of just three files. The first file is a Microsoft Excel file "Station_metadata.xlsx" that contains information about the *in situ* ET measurement stations where the OpenET model data was extracted. This file contains information such as site ID's, coordinates, land cover information, and site principal investigator (PI) contact information. Again, the corresponding *in situ* ET data are not included in this dataset. The other two files are tab-delimited text files containing timeseries the OpenET model data themselves, namely the daily ET [mm/day] and monthly ET [mm/month] as extracted for each model and the ensemble value as used in the OpenET Phase II Intercomparison and Accuracy Assessment. </p> <h3><br>Access information and code/software</h3> <p>OpenET data that was used here was produced using operational methods that are implemented on the Google Earth Engine platform. Monthly OpenET model data can be retrieved through Google Earth Data Catalog (e.g., https://developers.google.com/earth-engine/datasets/catalog/OpenET_ENSEMBLE_CONUS_GRIDMET_MONTHLY_v2_0) or through the [online data explorer](https://openetdata.org/) or using the [OpenET API](https://openetdata.org/api-info/).</p>
Genomic survey of edible cockle (Cerastoderma edule) in the Northeast Atlantic: a baseline for sustainable management of its wild resources
<p>Knowledge on how environmental factors shape the genome of marine species is crucial for sustainable management of fisheries and wild populations. The edible cockle (Cerastoderma edule) is a marine bivalve distributed along the Northeast Atlantic coast of Europe and is an important resource from both commercial and ecological perspectives. We performed a population genomics screening using 2b-RAD genotyping on 9,309 SNPs localised in the cockle's genome on a sample of 536 specimens pertaining to 14 beds in the Northeast Atlantic Ocean to determine the genetic structure with regard to environmental variables. Larval dispersal modelling considering species behaviour and interannual / interseasonal variation in ocean conditions was carried out as an essential background to which compare genetic information. Cockle populations in the Northeast Atlantic displayed low but significant geographical differentiation between populations (FST = 0.0240; P < 0.001), albeit not across generations. We identified 742 and 36 outlier SNPs related to divergent and balancing selection in all the geographical scenarios inspected, and sea temperature and salinity were the main environmental drivers suggested. Highly significant linkage disequilibrium was detected at specific genomic regions against the very low values observed across the whole genome, suggestive of selective sweeps. Two main genetic groups were identified, northwards and southwards of French Brittany, in accordance with the larval dispersal modelling, which suggested a barrier for larval dispersal linked to the Ushant front. Further genetic subdivision was observed using outlier loci and considering larval behaviour. The northern group was divided into the Irish/Celtic Seas and the English Channel/North Sea, while the southern group was divided into three subgroups. This information represents the baseline for management of cockles, designing conservation strategies, founding broodstock for depleted beds, and producing suitable seed for aquaculture production.</p>
Data from: Human judgment vs. quantitative models for the management of ecological resources
Despite major advances in quantitative approaches to natural resource management, there has been resistance to using these tools in the actual practice of managing ecological populations. Given a managed system and a set of assumptions, translated into a model, optimization methods can be used to solve for the most cost-effective management actions. However, when the underlying assumptions are not met, such methods can potentially lead to decisions that harm the environment and economy. Managers who develop decisions based on past experience and judgment, without the aid of mathematical models, can potentially learn about the system and develop flexible management strategies. However, these strategies are often based on subjective criteria and equally invalid and often unstated assumptions. Given the drawbacks of both methods, it is unclear whether simple quantitative models improve environmental decision making over expert opinion. In this study, we explore how well students, using their experience and judgment, manage simulated fishery populations in an online computer game and compare their management outcomes to the performance of model-based decisions. We consider harvest decisions generated using four different quantitative models: (1) the model used to produce the simulated population dynamics observed in the game, with the values of all parameters known (as a control), (2) the same model, but with unknown parameter values that must be estimated during the game from observed data, (3) models that are structurally different from those used to simulate the population dynamics, and (4) a model that ignores age structure. Humans on average performed much worse than the models in cases 1–3, but in a small minority of scenarios, models produced worse outcomes than those resulting from students making decisions based on experience and judgment. When the models ignored age structure, they generated poorly performing management decisions, but still outperformed students using experience and judgment 66% of the time.
Appendix 5: Supplementary data for Chapter 4 in the thesis: 'Quantifying the natural resource requirements of terrestrial ecosystems for managing biodiversity alongside human development'
<p>Appendix 5: Supplementary data for Chapter 4 in the thesis: 'Quantifying the natural resource requirements of terrestrial ecosystems for managing biodiversity alongside human development' by Adam R. Mason, Department of Civil and Environmental Engineering, Imperial College London</p>
Appendix 4: Supplementary data for Chapter 3 in the thesis: 'Quantifying the natural resource requirements of terrestrial ecosystems for the management of biodiversity alongside human development'
<p>Appendix 4: Supplementary data for Chapter 3 in the thesis: 'Quantifying the natural resource requirements of terrestrial ecosystems for managing biodiversity alongside human development' by Adam R. Mason, Department of Civil and Environmental Engineering, Imperial College London</p>
Appendix 6: Supplementary data for Chapter 5 in the thesis: 'Quantifying the natural resource requirements of terrestrial ecosystems for managing biodiversity alongside human development'
<p>Appendix 6: Supplementary data for Chapter 5 in the thesis: 'Quantifying the natural resource requirements of terrestrial ecosystems for managing biodiversity alongside human development' by Adam R. Mason, Department of Civil and Environmental Engineering, Imperial College London</p>
Data from: Resource-mediated indirect effects of grassland management on arthropod diversity
Intensive land use is a driving force for biodiversity decline in many ecosystems. In semi-natural grasslands, land-use activities such as mowing, grazing and fertilization affect the diversity of plants and arthropods, but the combined effects of different drivers and the chain of effects are largely unknown. In this study we used structural equation modelling to analyse how the arthropod communities in managed grasslands respond to land use and whether these responses are mediated through changes in resource diversity or resource quantity (biomass). Plants were considered resources for herbivores which themselves were considered resources for predators. Plant and arthropod (herbivores and predators) communities were sampled on 141 meadows, pastures and mown pastures within three regions in Germany in 2008 and 2009. Increasing land-use intensity generally increased plant biomass and decreased plant diversity, mainly through increasing fertilization. Herbivore diversity decreased together with plant diversity but showed no response to changes in plant biomass. Hence, landuse effects on herbivore diversity were mediated through resource diversity rather than quantity. Land-use effects on predator diversity were mediated by both herbivore diversity (resource diversity) and herbivore quantity (herbivore biomass), but indirect effects through resource quantity were stronger. Our findings highlight the importance of assessing both direct and indirect effects of land-use intensity and mode on different trophic levels. In addition to the overall effects, there were subtle differences between the different regions, pointing to the importance of regional land-use specificities. Our study underlines the commonly observed strong effect of grassland land use on biodiversity. It also highlights that mechanistic approaches help us to understand how different land-use modes affect biodiversity.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.