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32 results for “ecosystem accounting”
Dataset from "Natural capital accounting reveals ecosystems' role in water and energy security in Colombia's Sinú Basin"
<p>The data archived here are associated with the publication titled "Natural capital accounting reveals ecosystems' role in water and energy security in Colombia's Sinú Basin", available at: <a href="https://doi.org/10.1038/s43247-025-02254-9">https://doi.org/10.1038/s43247-025-02254-9</a>. The files within "Sinu_SDR_inputs.zip" and "Sinu_SWY_inputs.zip" were prepared and run in <a href="http://releases.naturalcapitalproject.org/?prefix=invest/3.12.0/">InVEST version 3.12.0</a>. "SDR" refers to the InVEST Sedimnet Delivery Ratio (SDR) model and "SWY" refers to the InVEST Seasonal Water Yield (SWY) model. Results of these model runs are found within "Sinu_SDR_results.zip" and "Sinu_SWY_results.zip" for the SDR and SWY models, respectively. These models were calibrated using observed data on average monthly water flows (from 1959 to 1992) and average annual sediment loads (from 1972 to 1992) from gauge stations on Colombia's Sinú River. Those observed data were obtained from Colombia's Institute of Hydrology, Meteorology, and Environmental Studies (IDEAM) hydrometeorological monitoring network <a href="http://dhime.ideam.gov.co/atencionciudadano/">webportal</a> and are summarized in the files included here, "MeanMonthlyObservedFlowsXgaugeStation.csv" for monthly water flows and "annualObservedSedimentXgaugeStation.csv" for annual sediment loads. "EcosystemTypeTable.xlsx" is the table of ecosystem values. "Cuenta_Sinu_SankeyData_v2_paper.xlsx" contains the Sankey and accounts tables.</p>
Quantitative account of social interactions in a mental health care ecosystem: cooperation, trust and collective action
<p>Mental disorders have an enormous impact in our society, both in personal terms and in the economic costs associated with their treatment. In order to scale up services and bring down costs, administrations are starting to promote social interactions as key to care provision. We analyze quantitatively the importance of communities for effective mental health care, considering all community members involved. By means of citizen science practices, we have designed a suite of games that allow to probe into different behavioral traits of the role groups of the ecosystem. The evidence reinforces the idea of community social capital, with caregivers and professionals playing a leading role. Yet, the cost of collective action is mainly supported by individuals with a mental condition - which unveils their vulnerability. The results are in general agreement with previous findings but, since we broaden the perspective of previous studies, we are also able to find marked differences in the social behavior of certain groups of mental disorders. We finally point to the conditions under which cooperation among members of the ecosystem is better sustained, suggesting how virtuous cycles of inclusion and participation can be promoted in a ’care in the community’ framework.</p>
Data from: Accounting for uncertainty in marine ecosystem service predictions for spatial prioritisation
<p>Spatial assessments of Ecosystem Services (ES) are increasingly used in environmental management and spatial planning, but rarely provide information on the accuracy of predictions. Uncertainty estimates are essential to allow for confidence in the quality and credibility of ES assessments to enable informed decision-making. In marine environments, the need for uncertainty assessments for ES is unparalleled as they are data scarce, poorly (spatially) defined, with complex interconnectivity of seascapes. This study illustrates the uncertainty associated with a principle-based method for ES modelling by accounting for model variability, data coverage, and uncertainty in thresholds and parameters. A sensitivity analysis was applied on ES models for marine bivalves (<em>Austrovenus stutchburyi</em> and <em>Paphies australis</em>) and their contribution to <em>Food provision, Water quality regulation, Nitrogen removal,</em> and <em>Sediment stabilisation</em>.<em> </em>ES estimates from the sensitivity analysis were compared against baseline ES predictions. Spatial uncertainty patterns were analysed for individual ES through bi-plots and multiple ES through spatial prioritisation using Zonation. Results showed spatially explicit differences in uncertainty patterns for ES and between species. <em>Food</em><em> provision</em> had highest maximum uncertainty (>5 points) but also the largest area of high ES and high certainty conditions. Zonation analysis conducted on baseline and conservative ES values showed overall robust outcomes of top 30% area, but important nuances through shifts in top 10% and top 5% area that allowed for a consistently better representation of ES when accounting for uncertainty. The spatial prioritisation in combination with the ES uncertainty biplots provide tools for spatial planning of individual and multiple ES to focus on area of highest value with highest certainty and can thereby help reduce risk and aid informed decision-making at acceptable confidence levels. This type of information is urgently needed in marine ES assessments and their management, but likewise extends to other environments to improve transparency. </p>
Data from: Accounting for uncertainty in marine ecosystem service predictions for spatial prioritisation
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Supplementary material 3 from: Grunewald K, Schweppe-Kraft B, Syrbe R-U, Meier S, Krüger T, Schorcht M, Walz U (2020) Hierarchical classification system of Germany's ecosystems as basis for an ecosystem accounting – methods and first results. One Ecosystem 5: e50648. https://doi.org/10.3897/oneeco.5.e50648
The area and share of main ecosystem types and sub ecosystem types (ETs, see Tab. 1)) in the German land cover model (LBM-DE) for the time periods 2012, 2015 and 2018. Linear elements such as small scale structures and infrastructures from the topographic-cartographic Information system (ATKIS) were added to the land cover model.
Supplementary material 4 from: Grunewald K, Schweppe-Kraft B, Syrbe R-U, Meier S, Krüger T, Schorcht M, Walz U (2020) Hierarchical classification system of Germany's ecosystems as basis for an ecosystem accounting – methods and first results. One Ecosystem 5: e50648. https://doi.org/10.3897/oneeco.5.e50648
Tab. D: Detailed matrix of pre- and post-use of settlement and transportation areas in Germany in the period 2013-2018 in hectare per day (ha/d). (Data source: IOER)
Supplementary material 1 from: Grunewald K, Schweppe-Kraft B, Syrbe R-U, Meier S, Krüger T, Schorcht M, Walz U (2020) Hierarchical classification system of Germany's ecosystems as basis for an ecosystem accounting – methods and first results. One Ecosystem 5: e50648. https://doi.org/10.3897/oneeco.5.e50648
Proposal of a classification system for ecosystem types (ETs) in Germany, assignment to the European ecosystem types according to EUNIS and to the CLC types of the database LBM-DE
Supplementary material 2 from: Grunewald K, Schweppe-Kraft B, Syrbe R-U, Meier S, Krüger T, Schorcht M, Walz U (2020) Hierarchical classification system of Germany's ecosystems as basis for an ecosystem accounting – methods and first results. One Ecosystem 5: e50648. https://doi.org/10.3897/oneeco.5.e50648
Supplementation of ecosystem types (ETs) by more differentiated spatially and non-spatially explicit data (system of assignment of biotope and habitat types relevant for nature conservation to ETs
Supplementary material 3 from: Gomez Cardona CJ, Moreno JY, Contreras A, Sanchez-Nuñez DA, Arciniegas Moreno N, Guerrero D, Viloria Maestre EA, Lopez Navarro J (2023) Accounting of marine and coastal ecosystems at the Ramsar Site, Estuarine Delta System of the Magdalena River, Ciénaga Grande de Santa Marta, Colombia. One Ecosystem 8: e98852. https://doi.org/10.3897/oneeco.8.e98852
Combined condition account for the mangrove ecosystem types present in the CGSM Ramsar site (2017-2019)
Supplementary material 4 from: Gomez Cardona CJ, Moreno JY, Contreras A, Sanchez-Nuñez DA, Arciniegas Moreno N, Guerrero D, Viloria Maestre EA, Lopez Navarro J (2023) Accounting of marine and coastal ecosystems at the Ramsar Site, Estuarine Delta System of the Magdalena River, Ciénaga Grande de Santa Marta, Colombia. One Ecosystem 8: e98852. https://doi.org/10.3897/oneeco.8.e98852
Combined condition account for the coastal lagoons ecosystem types present in the CGSM Ramsar site (2017-2019)
Supplementary material 3 from: Alarcon Blazquez MG, van der Veeren R, Gacutan J, James PAS (2023) Compiling preliminary SEEA Ecosystem Accounts for the OSPAR regional sea: experimental findings and lessons learned. One Ecosystem 8: e108030. https://doi.org/10.3897/oneeco.8.e108030
Overview of information on the state, policy relevance and gaps of the OSPAR contracting parties natural capital accounts.
Data from: Accounting for variation in temperature and oxygen availability when quantifying marine ecosystem metabolism
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Supplementary material 1 from: Maes J, Driver A, Czúcz B, Keith H, Jackson B, Nicholson E, Dasoo M (2020) A review of ecosystem condition accounts: lessons learned and options for further development. One Ecosystem 5: e53485. https://doi.org/10.3897/oneeco.5.e53485
Supplementary information
Data from: Evaluating the costs and benefits of marsh-management strategies while accounting for uncertain sea-level rise and ecosystem response
Prioritization of marsh-management strategies is a difficult task as it requires a manager to evaluate the relative benefits of each strategy given uncertainty in future sea-level rise and in dynamic marsh response. A modeling framework to evaluate the costs and benefits of management strategies while accounting for both of these uncertainties has been developed. The base data for the tool are high-resolution uncertainty-analysis results from SLAMM (the Sea-Level Affecting Marshes Model) under different adaptive-management strategies. These results are combined with an ecosystem-valuation assessment from stakeholders. Model results and stakeholder values are linked together using "utility functions" that characterize the relationship between stakeholder values and geometric metrics such as "marsh area," marsh edge," or "marsh width." The expected-value of each site's ecosystem benefits can then be calculated and compared using estimated costs for each strategy. Estimates of optimal marsh-management strategies may then be produced, maximizing the "ecosystem benefits per estimated costs" ratio.
Supplementary material 3 from: Farrell CA, Coleman L, Norton D, Kelly-Quinn M, Obst C, Eigenraam M, OʼDonoghue C, Kinsella S, Smith F, Sheehy I, Stout JC (2021) Developing peatland ecosystem accounts to guide targets for restoration. One Ecosystem 6: e76838. https://doi.org/10.3897/oneeco.6.e76838
Supporting data
Supplementary material 2 from: Farrell CA, Coleman L, Norton D, Kelly-Quinn M, Obst C, Eigenraam M, OʼDonoghue C, Kinsella S, Smith F, Sheehy I, Stout JC (2021) Developing peatland ecosystem accounts to guide targets for restoration. One Ecosystem 6: e76838. https://doi.org/10.3897/oneeco.6.e76838
Datasets
Supplementary material 1 from: Farrell CA, Coleman L, Norton D, Kelly-Quinn M, Obst C, Eigenraam M, OʼDonoghue C, Kinsella S, Smith F, Sheehy I, Stout JC (2021) Developing peatland ecosystem accounts to guide targets for restoration. One Ecosystem 6: e76838. https://doi.org/10.3897/oneeco.6.e76838
Conservation Status
Supplementary material 2 from: Gacutan J, Lal KK, Herath S, Lantz C, Taylor MD, Milligan BM (2022) Using Ocean Accounting towards an integrated assessment of ecosystem services and benefits within a coastal lake. One Ecosystem 7: e81855. https://doi.org/10.3897/oneeco.7.e81855
Ecosystem service assessment methods
Supplementary material 3 from: Gacutan J, Lal KK, Herath S, Lantz C, Taylor MD, Milligan BM (2022) Using Ocean Accounting towards an integrated assessment of ecosystem services and benefits within a coastal lake. One Ecosystem 7: e81855. https://doi.org/10.3897/oneeco.7.e81855
Fisheries - stable isotope calculations
Supplementary material 1 from: Gacutan J, Lal KK, Herath S, Lantz C, Taylor MD, Milligan BM (2022) Using Ocean Accounting towards an integrated assessment of ecosystem services and benefits within a coastal lake. One Ecosystem 7: e81855. https://doi.org/10.3897/oneeco.7.e81855
Definitions and data sources used
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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.