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89 results for “nature-based solutions”
Database of indicators to evaluate the contribution of urban nature-based solutions to climate change adaptation, biodiversity conservation, and social justice
<p>Supplementary data used within the publication: Goodwin, S., Olazabal, M., Castro, A. J., & Pascual, U. (2024). Measuring the contribution of nature-based solutions beyond climate adaptation in cities. <em>Global Environmental Change</em>, <em>89</em>, 102939. <a href="https://doi.org/10.1016/j.gloenvcha.2024.102939">https://doi.org/10.1016/j.gloenvcha.2024.102939</a>. Please also cite this paper when citing this database.</p> <div> <div>Within this database, you can find a list of indicators used to evaluate the contribution of a collection of 74 nature-based solutions (NbS) to climate change adaptation and related biodiversity and social justice challenges in cities. This list of indicators may be useful to those working in cities to provide inspiration for similar indicators they may wish to use to evaluate NbS in their city. This collection of NbS was drawn from previous work published in <em>Nature Sustainability</em> <a href="https://rdcu.be/c4tjk">here</a>.</div> <div> </div> </div> <p><em>The project that gave rise to these results received the support of a fellowship from the “la Caixa” Foundation (ID 100010434). The fellowship code is “LCF/BQ/DI20/11780006”. Marta Olazabal’s research is funded by the European Union (ERC, IMAGINE adaptation, 101039429). This research is further supported by María de Maeztu Excellence Unit 2023-2027 (ref. CEX2021-001201-M), funded by the Ministerio de Ciencia, Innovación y Universidades/Agencia Estatal de Investigación (AEI) (Spain) (MCIN/AEI/10.13039/501100011033/); and by the Basque Government through the BERC 2022-2025 program. </em></p> <p><em>Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.</em></p>
The evolution and future of research on Nature-based Solutions to address societal challenges
<p>This dataset comprises the bibliographic text files used to analyse the Nature-based Solutions research landscape as presented in:</p> <ul> <li>Dunlop, T., Khojasteh, D., Cohen-Shacham, E., Glamore, W., Haghani, M., van den Bosch, M., Rizzi, D., Greve, P., Felder, S. The Evolution and Future of Research on Nature-based Solutions to Address Societal Challenges. <em>Communications Earth & Environment</em>. 2024.</li> </ul> <p>Excel spreadsheets containing data for the Global Water Security Index (Gain et al., 2016) presented in Figure 2 and the data required to reproduce Figures 1 and 2 in the paper above are also shared.</p>
Nature-Based Solutions Tools Catalogue
<p>The Adaptive Cities Through Integrated Nature-Based Solutions (ACT on NBS), EIT Climate KIC project made an inventory and assessment of NBS tools for climate resilient cities. The objectives of the catalogue are: 1) to increase organizational accessibility to data on NBS and climate resilience tools that have been developed and used in Europe and worldwide; 2) that different end-users become aware of several tools that already exist to plan, design, and implement NBS and make use of them to address specific environmental challenges and adaptation measures in their cities, neighborhoods or even regions.</p> <p>The NBS tools catalogue contains 70 tools collected. For this research, a “tool” is understood to be either a methodology, software, catalogue, repository, e-platform, guideline or handbook. The tools were identified through interviews with EU municipalities and workshops organized by ACT on NBS, and by additional desk research.</p> <p>The desk study entailed a combination of reviewing the websites from international organizations and EU granted projects related to cities dealing with NBSs, ecosystem services (ESs), green infrastructure, urban resilience and climate change, and reviewing peer-reviewed scientific journals, reports and grey literature.</p> <p>The latter search was implemented through Google search, Google scholar and Scopus in August 2020. This implies that tools that were developed and published before that date were collected. The search strategy was implemented using combinations of search terms such as: nature-based solutions, NBS, ecosystem-based adaptation, green infrastructure, climate adaptation, climate resilience, ecosystem services, climate hazards, urban biodiversity, urban nature, water and land management “AND” urban areas, cities “AND” tools, software, methodology, catalogue, repository, platform, handbook and guideline.</p> <p>For the assessment, tools were labeled on their descriptive characteristics and potential fields of application. The use of pre-defined indicators was chosen to support the characterization of the tools and to allow for their comparison. The categories and indicators were formulated based on the current literature and refined through expert judgements. The indicators were also, in some cases, further adapted through an iterative process of tools’ analysis.</p> <p>For more information on the NBS tools analysis please read our academic publication on “Nature-Based Solutions Tools for Planning Urban Climate Adaptation: State of the Art”.</p> <p><strong><a href="https://doi.org/10.3390/su13116381">https://doi.org/10.3390/su13116381</a></strong> </p>
Nature-based Solutions at OAL-UK
<p>Shapefile containing the spatial distribution of the planned NBS interventions at OAL-UK</p>
Urban nature-based solutions to climate change adaptation database
<p>This dataset is the result of a systematic mapping of the application of nature-based solutions (NbS) to climate change adaptation in urban areas across the world. We screened 823 potential urban NbS to climate adaptation, which resulted in the inclusion of 216 interventions worldwide from 130 cities in 55 countries within our dataset. We analysed each of the NbS according to key characteristics in terms of how these interventions are helping cities confront the grave climate change, biodiversity, and related social challenges they are facing. We further analyse the capacity for each NbS to affect change in the city it is implemented within, which ranges from incremental (shallow) change to reformistic (middle ground) and finally transformative (deep) change. The full range of climate, biodiversity, and social challenges, as well as further discussion on the meaning of these different levels of change, is described in the attached file in the coding template tab. </p> <p>The results and analysis of this database (v 1.0.0) appear in the following article:</p> <p>Goodwin, S., M. Olazabal, A. Castro, U. Pascual. "Global mapping of urban nature-based solutions for climate change adaptation". <em>Nature Sustainability. doi: <a href="http://doi.org/10.1038/s41893-022-01036-x">10.1038/s41893-022-01036-x </a></em></p> <p><strong>A read-only version of this article can be found online for free <a href="https://rdcu.be/c4tjk">here</a>.</strong></p> <p>For any use of this dataset, please cite this dataset along with the associated publication in Nature Sustainability. Please report any errors or omissions to Sean Goodwin.</p>
Data and code for: Nature-based climate solutions can help mitigate the radiative forcing that follows deforestation
Open the record for dataset details and reuse information.
Ottawa climate data for building simulations with urban heat island effects and nature-based solutions
<p>As cities face rising temperatures, increased frequency of extreme weather events, and altered precipitation patterns, buildings are subjected to increasing energy demand, heat stress, thermal comfort issues, and decreased service life. Therefore, evaluating building performance under changing climate conditions is essential for building sustainable and resilient communities. Unique climate characteristics of cities, such as the urban heat island effect, are not well simulated by global or regional climate models, and is therefore often not included in typical building analyses. Consequently, a computationally efficient approach is used to generate “urbanized” climate data, derived from regional climate models, to prepare building simulation climate data that incorporate urban effects. We demonstrate this process using existing climate data for Ottawa airport’s weather station and extend it to prepare projections for scenarios where nature-based solutions, such as increased greenery and albedo, were implemented. We find significant improvements in the representation of the urban heat island and subsequent cooling effects of nature-based solutions in the urbanized climate data. This dataset allows building practitioners to evaluate building performance under historical and potential future changes in climate, considering the complex interactions within the urban canopy and the implementation of mitigation efforts such as nature-based solutions.</p> <p>This dataset contains hourly historical and future weather files for use in building simulations for the city of Ottawa, Canada. While similar weather files are usually based on measurements taken at a city's nearby airport, the current dataset utilizes a novel statistical-dynamical downscaling technique which involves the use of the dynamical Weather Research and Forecasting (WRF) model combined with a statistical approach and climate projections from an ensemble of 15 Canadian Regional Climate Model 4 (CanRCM4) to generate urban climate data which includes the effects of the urban heat island and different nature-based solutions (NBS) as mitigation strategies (such as increasing surface albedo and greenery). Additionally, different levels of implementation of these mitigation strategies were produced, for example, when the albedo is increased to 0.40 (ALBD40) and 0.80 (ALBD80), and similarly for the green and combined scenarios, GRN40, GRN80, COMB40, and COMB80. The URBAN scenario is considered the control case where the urban heat island effects are accounted for in the data, but the NBS scenarios are not yet implemtned. </p> <p>The data are stored in large CSV files, where the rows consists of all 15 realizations of the CanRCM4 ensemble and the variables make up the columns. For example, each 31-year period is repeated 15 times, once for each of the RCM realizations. Therefore, there are 4,073,400 (15x31x8760) rows in each file. We recommend viewing the data using packages from Python or R. </p> <p> </p> <p>The historical and future global warming thresholds and their corresponding time periods are as follows:</p> <table> <tbody> <tr> <td> <p><strong>Global Warming Scenario</strong></p> </td> <td> <p><strong>Time Period</strong></p> </td> </tr> <tr> <td> <p><strong>Historical</strong></p> </td> <td> <p>1991-2021</p> </td> </tr> <tr> <td> <p><strong>Global Warming 0.5ºC</strong></p> </td> <td> <p>2003-2033</p> </td> </tr> <tr> <td> <p><strong>Global Warming 1.0ºC</strong></p> </td> <td> <p>2014-2044</p> </td> </tr> <tr> <td> <p><strong>Global Warming 1.5ºC</strong></p> </td> <td> <p>2024-2054</p> </td> </tr> <tr> <td> <p><strong>Global Warming 2.0ºC</strong></p> </td> <td> <p>2034-2064</p> </td> </tr> <tr> <td> <p><strong>Global Warming 2.5ºC</strong></p> </td> <td> <p>2042-2072</p> </td> </tr> <tr> <td> <p><strong>Global Warming 3.0ºC</strong></p> </td> <td> <p>2051-2081</p> </td> </tr> <tr> <td> <p><strong>Global Warming 3.5ºC</strong></p> </td> <td> <p>2064-2094</p> </td> </tr> </tbody> </table> <p> </p> <p>The following variables are included in the files:</p> <table> <tbody> <tr> <td><strong>Variable</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td><strong>RUN</strong></td> <td>Run number (R1-R15) of Canadian Regional Climate Model, CanRCM4 large ensemble associated with the selected reference year data</td> </tr> <tr> <td><strong>YEAR</strong></td> <td>Year associated with the record</td> </tr> <tr> <td><strong>MONTH</strong></td> <td>Month associated with the record</td> </tr> <tr> <td><strong>DAY</strong></td> <td>Day of the month associated with the record</td> </tr> <tr> <td><strong>HOUR</strong></td> <td>Hour associated with the record</td> </tr> <tr> <td><strong>YDAY</strong></td> <td>Day of the year associated with the record</td> </tr> <tr> <td><strong>DRI_kJPerM2</strong></td> <td>Direct horizontal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)</td> </tr> <tr> <td><strong>DHI_kJperM2</strong></td> <td>Diffused horizontal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)</td> </tr> <tr> <td><strong>DNI_kJperM2</strong></td> <td>Direct normal irradiance in kJ/m2 (total from previous HOUR to the <em>HOUR</em> indicated)</td> </tr> <tr> <td><strong>GHI_kJperM2</strong></td> <td>Global horizontal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)</td> </tr> <tr> <td><strong>TCC_Percent</strong></td> <td>Instantaneous total cloud cover at the HOUR in % (range: 0-100)</td> </tr> <tr> <td><strong>RAIN_Mm</strong></td> <td>Total rainfall in mm (total from previous HOUR to the HOUR indicated)</td> </tr> <tr> <td><strong>WDIR_ClockwiseDegFromNorth</strong></td> <td>Instantaneous wind direction at the HOUR in degrees (measured clockwise from the North)</td> </tr> <tr> <td><strong>WSP_MPerSec</strong></td> <td>Instantaneous wind speed at the HOUR in meters/sec</td> </tr> <tr> <td><strong>RHUM_Percent</strong></td> <td>Instantaneous relative humidity at the HOUR in %</td> </tr> <tr> <td><strong>TEMP_K</strong></td> <td>Instantaneous temperature at the HOUR in Kelvin</td> </tr> <tr> <td><strong>ATMPR_Pa</strong></td> <td>Instantaneous atmospheric pressure at the HOUR in Pascal</td> </tr> <tr> <td><strong>SnowC_Yes1No0 </strong></td> <td>Instantaneous snow-cover at the HOUR (1 - snow; 0 - no snow)</td> </tr> <tr> <td><strong>SNWD_Cm</strong></td> <td>Instantaneous snow depth at the HOUR in cm</td> </tr> </tbody> </table>
Shapefiles showing the locations of long-term climate change refugia and hotspots identified in the FutureMARES report "D6.3, Climate ready strategies for nature-based solutions"
<p>Shapefiles created for the report "D6.3, Climate ready strategies for nature-based solutions", a deliverable report from the Horizon Europe project FutureMARES</p> <p>These shapefiles summarise long-term patterns that emerge from the spatial-meta analysis of physical-biogeochemical and species distribution modelling data, providing an overview of the distribution of climate change refugia and climate change hotspots across six European case study areas between 2026 - 2069, and across the five scenarios considered in the FutureMARES project (Global Sustainability RCP2.6, National Enterprise RCP8.5, World Market RCP8.5, Status Quo RCP2.6 and Status Quo RCP8.5). </p> <p>Filenames refer to the case study area and scenario each set of shapefiles belong to. Details of the modelling datasets used in each of these analyses, the meta-analysis method and shapefile creation can be found in the relevant chapter in the report "D6.3, Climate ready strategies for nature-based solutions".</p>
Extract of the project data from the LIFE KPI webtool. Deliverable 2.5 of the LIFE NatuReef project: Nature-based reef solution for coastal protection and marine biodiversity enhancement. LIFE22-NAT-IT-LIFE-NatuReef/101113742
<p>Key performance indicator, a quantifiable measure of performance over time for a specific objective.</p>
Experimental study on the benefits of nature-based solutions for debris-flow mitigation via synergistic eco-geotechnical measures
<p>This supporting information provides the supplementary data (Raw data and videos) which were used to describe the effects of integrated eco-geotechnical measures on debris flow severity, flow rate, velocity, and particle size by various small-scale flume experiments.</p>
Archetypes of Nature-based Solutions (NbS) for farming in the North York Moors National Park
Open the record for dataset details and reuse information.
Supplementary material 11 from: Tomaskinova J, Dicks L, Collier M, Geneletti D, Grace M, Longato D, Sadula R, Stoev P, Sapundzhieva A, Balzan MV (2020) Capacity-building and networking events for nature-based solutions and re-naturing in Malta. Research Ideas and Outcomes 6: e60893. https://doi.org/10.3897/rio.6.e60893
Identifying priority knowledge needs for implementing nature-based solutions-results from Malta and other Mediterranean islands
Supplementary material 9 from: Tomaskinova J, Dicks L, Collier M, Geneletti D, Grace M, Longato D, Sadula R, Stoev P, Sapundzhieva A, Balzan MV (2020) Capacity-building and networking events for nature-based solutions and re-naturing in Malta. Research Ideas and Outcomes 6: e60893. https://doi.org/10.3897/rio.6.e60893
Management and restoration of Mediterranean wetlands to provide ecosystem services and other benefits
Supplementary material 12 from: Tomaskinova J, Dicks L, Collier M, Geneletti D, Grace M, Longato D, Sadula R, Stoev P, Sapundzhieva A, Balzan MV (2020) Capacity-building and networking events for nature-based solutions and re-naturing in Malta. Research Ideas and Outcomes 6: e60893. https://doi.org/10.3897/rio.6.e60893
Non-material ecosystem benefits of protected areas as a bridge to future challenges in sustainable development
Table of nature-based solution examples in Ireland
<p>A compendium of examples of nature-based solutions case studies, and actions that have been implemented through various schemes and projects, for the report "Identification and assessment of best practice in nature-based solutions for climate action and ecosystem restoration in Ireland". </p>
Supplementary material 2 from: Tomaskinova J, Geneletti D, Dicks LV, Grace M, Collier M, Longato D, Stoev P, Sapundzhieva A, Balzan MV (2021) Capacity-building as an instrument to foster the implementation of nature-based solutions. Research Ideas and Outcomes 7: e77666. https://doi.org/10.3897/rio.7.e77666
Assessing the effectiveness of urban ecosystems to prioritise nature-based interventions in a high-density urban area
Excel code for: Trading off nature for nature-based solutions: The bioeconomics of forest management for wildlife, timber and carbon
<p>This dataset contains MS Excel spreadsheet code used to analyze an integrative model that illustrates the inherent trade-offs that will arise among the competing values for landscape space in a boreal forest ecosystem involving interactions among the main trophic compartments of an intact boreal ecosystem, aka "nature". The model accounts for carbon accumulation via biomass growth of forest trees (timber), carbon loss due to controls from moose herbivory that varies with moose population density (hunting), and soil carbon inputs and release, which together determine net ecosystem productivity (NEP), a measure of carbon sink strength of the ecosystem. We examine how controls on carbon dynamics are altered by forest management for timber harvest, and by moose hunting. We link the ecological dynamics with an economic analysis by assigning a price to carbon stored within the intact boreal forest ecosystem. We then weigh these carbon impacts against the economic benefits of timber production and hunting across a range of moose population densities. Combined, this carbon-bioeconomic program calculates the total ecosystem benefit of a modelled boreal forest system, providing a framework for examining how different forest harvest and moose densities influence the achievement of carbon storage targets, under different levels of carbon pricing.</p>
"Building Resilient Coastal Communities through Nature-based Solutions and Empowerment Tools".
<p>This report provides an evidence base on how Nature-based Solutions (NbS) and Empowerment Tools (ET) can support resilience in coastal communities. Using a Rapid Evidence Assessment (REA), it synthesises the current state of the evidence concerning the role of NbS and community ET in addressing coastal challenges such as climate change across Europe. The outcomes and impacts of such approaches in fostering empowerment and resilience within these communities are presented, including methods and indicators to report and measure empowerment. This report was developed by an Eklipse Expert Working Group to respond to a request put forward by the Horizon Europe EmpowerUS project and is targeted for policy- and decisionmakers, researchers and practitioners, exploring the nexus between coastal resilience, NbS and empowerment. Through a great range of recommendations for research and policy, we hope to encourage to enhance resilience of coastal communities by ensure a wide dissemination of the knowledge to a broad set of stakeholders.</p>
Catalogue of Nature-based Solutions
<p>The Catalogue of NBS is a tool for decision support on Nexus-related NBS selection. The tool not only allows the identification of appropriate NBS, it also provides KPIs in order to assess their technical effectiveness; effectiveness in improving service under specific conditions, climate resilience of the solution and contribution to adaptation.</p> <p>You are able to explore a list of available NBS, search by keyword in order to find a specific NBS, as well as use filters in order to narrow down the results. Other than that, the tool contains guidelines for the development of a <a href="https://nbscatalogue.lenses-prima.eu/nbs-business-model-methodology" target="_blank" rel="noopener">business model</a> with the purpose of making the selected NBS more sustainable.</p> <p> </p>
Data for "Evaluation of Low Impact Development and Nature-Based Solutions for stormwater management: a fully distributed modelling approach"
<p>The data set corresponds the data used in the paper : “Evaluation of Low Impact Development and Nature-Based Solutions for stormwater management: a fully distributed modelling approach”, published in 2019 in the Journal “Hydrology and Earth System Sciences” (http://www.hydrol-earth-syst-sci.net/).</p> <p>More precisely it corresponds to the simulation input data that used in the Multi-Hydro model and the simulated discharge of the five scenarios investigated in the paper.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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