scholarly journals Developing an Ecosystem Services Online Decision Support Tool to Assess the Impacts of Climate Change and Urban Growth in the Santa Cruz Watershed; Where We Live, Work, and Play

2010 ◽  
Vol 2 (7) ◽  
pp. 2044-2069 ◽  
Author(s):  
Laura Norman ◽  
Nita Tallent-Halsell ◽  
William Labiosa ◽  
Matt Weber ◽  
Amy McCoy ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Ecosystem Services ◽  
Urban Growth ◽  
Decision Support Tool ◽  
Santa Cruz ◽  
Support Tool ◽  
Impacts Of Climate Change

scholarly journals A Decision Support Tool for Assessing the Impact of Climate Change on Multiple Ecosystem Services

Forests ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 440 ◽  
Author(s):  
Irina Cristal ◽  
Aitor Ameztegui ◽  
Jose Ramon González-Olabarria ◽  
Jordi Garcia-Gonzalo
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Ecosystem Services ◽  
Forest Management ◽  
Decision Support Tool ◽  
Tree Level ◽  
Support Tool ◽  
Simulation Engine ◽  
User Centric ◽  
The Impact

In the climate change era, forest managers are challenged to use innovative tools to encourage a sustained provision of goods and services. Many decision support tools (DSTs), developed to address global changes in forest management practices, reflect the complexity of the scientific knowledge produced, a fact that could make it difficult for practitioners to understand and adopt them. Acknowledging the importance of knowledge transfer to forestry practitioners, this study describes a user-centric decision support software tool, aiming to assess forest management and climate change impacts on multiple ecosystem services (ESs) at a stand level. SORTIE-ND, a spatially explicit tree-level simulator for projecting stand dynamics that is sensitive to climate change, is encapsulated into the decision support tool and used as the simulation engine for stand development. Linking functions are implemented to evaluate ecosystem services and potential risks, and decision support is provided in form of interactive 2D and 3D visualizations. Five main components were identified to delineate the workflow and to shape the decision support tool: the information base, the alternative generator, the forest simulator, the ecosystem services calculator, and the visualization component. In order to improve the interaction design and general user satisfaction, the usability of the system was tested at an early stage of the development. While we have specifically focused on a management-oriented approach through user-centric interface design, the utilization of the product is likely to be of importance in facilitating education in the field of forest management.

A Model-Based Decision Support Tool Using Fuzzy Optimization for Climate Change

2011 ◽  
pp. 388-393 ◽  
Author(s):  
Omar S. Soliman ◽  
Aboul Ella Hassanien ◽  
Neveen I. Ghali ◽  
Nashwa El-Bendary ◽  
Ruhul A. Sarker
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Fuzzy Optimization ◽  
Decision Support Tool ◽  
Support Tool ◽  
Model Based

Ecosystem Services and Emergent Vulnerability in Managed Ecosystems: A Geospatial Decision-Support Tool

Ecosystems ◽  
2008 ◽  
Vol 11 (6) ◽  
pp. 923-938 ◽  
Author(s):  
Colin M. Beier ◽  
Trista M. Patterson ◽  
F. Stuart Chapin
Keyword(s):  
Decision Support ◽  
Ecosystem Services ◽  
Decision Support Tool ◽  
Support Tool ◽  
Managed Ecosystems

scholarly journals Application of flood risk modelling in a web-based geospatial decision support tool for coastal adaptation to climate change

2015 ◽  
Vol 15 (7) ◽  
pp. 1457-1471 ◽  
Author(s):  
P. J. Knight ◽  
T. Prime ◽  
J. M. Brown ◽  
K. Morrissey ◽  
A. J. Plater
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Sea Level Rise ◽  
Sea Level ◽  
Flood Risk ◽  
Decision Support Tool ◽  
Strategic Decision ◽  
Web Based ◽  
Essential Information ◽  
Support Tool

Abstract. A pressing problem facing coastal decision makers is the conversion of "high-level" but plausible climate change assessments into an effective basis for climate change adaptation at the local scale. Here, we describe a web-based, geospatial decision support tool (DST) that provides an assessment of the potential flood risk for populated coastal lowlands arising from future sea-level rise, coastal storms, and high river flows. This DST has been developed to support operational and strategic decision making by enabling the user to explore the flood hazard from extreme events, changes in the extent of the flood-prone areas with sea-level rise, and thresholds of sea-level rise where current policy and resource options are no longer viable. The DST is built in an open-source GIS that uses freely available geospatial data. Flood risk assessments from a combination of LISFLOOD-FP and SWAB (Shallow Water And Boussinesq) models are embedded within the tool; the user interface enables interrogation of different combinations of coastal and river events under rising-sea-level scenarios. Users can readily vary the input parameters (sea level, storms, wave height and river flow) relative to the present-day topography and infrastructure to identify combinations where significant regime shifts or "tipping points" occur. Two case studies demonstrate the attributes of the DST with respect to the wider coastal community and the UK energy sector. Examples report on the assets at risk and illustrate the extent of flooding in relation to infrastructure access. This informs an economic assessment of potential losses due to climate change and thus provides local authorities and energy operators with essential information on the feasibility of investment for building resilience into vulnerable components of their area of responsibility.

scholarly journals Integrating ecosystem services into spatial planning—A spatial decision support tool

2017 ◽  
Vol 165 ◽  
pp. 206-219 ◽  
Author(s):  
Adrienne Grêt-Regamey ◽  
Jürg Altwegg ◽  
Elina A. Sirén ◽  
Maarten J. van Strien ◽  
Bettina Weibel
Keyword(s):  
Decision Support ◽  
Ecosystem Services ◽  
Spatial Planning ◽  
Decision Support Tool ◽  
Spatial Decision Support ◽  
Support Tool

scholarly journals Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia

2020 ◽  
pp. 1-15 ◽  
Author(s):  
Kefyalew Sahle Kibret ◽  
Amare Haileslassie ◽  
Wolde Mekuria Bori ◽  
Petra Schmitter
Keyword(s):  
Land Use ◽  
Decision Support ◽  
Ecosystem Services ◽  
Land Degradation ◽  
Decision Support Tool ◽  
River Basins ◽  
Land Area ◽  
Support Tool ◽  
Ex Ante ◽  
Multicriteria Decision Support

Abstract Land degradation is a global challenge that affects lives and livelihoods in many communities. Since 1950, about 65% of Africa's cropland, on which millions of people depend, has been affected by land degradation caused by mining, poor farming practices and illegal logging. One-quarter of the land area of Ethiopia is severely degraded. As part of interventions to restore ecosystem services, exclosures have been implemented in Ethiopia since the 1980s. But the lack of tools to support prioritization and more efficient targeting of areas for large-scale exclosure-based interventions remains a challenge. Within that perspective, the overarching objectives of the current study were: (i) to develop a Geographic Information System-based multicriteria decision-support tool that would help in the identification of suitable areas for exclosure initiatives; (ii) to provide spatially explicit information, aggregated by river basin and agroecology, on potential areas for exclosure interventions and (iii) to conduct ex-ante analysis of the potential of exclosure areas for improving ecosystem services in terms of increase in above-ground biomass (AGB) production and carbon storage. The results of this study demonstrated that as much as 10% of Ethiopia's land area is suitable for establishing exclosures. This amounts to 11 million hectares (ha) of land depending on the criteria used to define suitability for exclosure. Of this total, a significant proportion (0.5–0.6 million ha) is currently under agricultural land-use systems. In terms of propriety river basins, we found that the largest amount of suitable area for exclosures falls in the Abay (2.6 million ha) and Tekeze (2.2 million ha) river basins, which are hosts to water infrastructure such as hydropower dams and are threatened by siltation. Ex-ante analysis of ecosystem services indicated that about 418 million tons of carbon can be stored in the AGB through exclosure land use. Ethiopia has voluntarily committed to the Bonn Challenge to restore 15 million ha of degraded land by 2025. The decision-support tool developed by the current study and the information so generated go toward supporting the planning, implementation and monitoring of these kinds of local and regional initiatives.

scholarly journals TURNING LOCAL KNOWLEDGE ON AGROFORESTRY INTO AN ONLINE DECISION-SUPPORT TOOL FOR TREE SELECTION IN SMALLHOLDERS’ FARMS

2016 ◽  
Vol 55 (S1) ◽  
pp. 50-66 ◽  
Author(s):  
JUST VAN DER WOLF ◽  
LAURENCE JASSOGNE ◽  
GIL GRAM ◽  
PHILIPPE VAAST
Keyword(s):  
Decision Support ◽  
Ecosystem Services ◽  
Tree Species ◽  
Smallholder Farmers ◽  
Decision Support Tool ◽  
Agroforestry Systems ◽  
Species Selection ◽  
Adaptation To Climate Change ◽  
Local Conditions ◽  
Support Tool

SUMMARYThis paper presents the main features of a unique decision-support tool developed for selecting tree species in coffee and cocoa agroforestry systems. This tool aims at assisting in the selection of appropriate shade trees taking into account local conditions as well as needs and preferences of smallholder farmers while maximizing ecosystem services from plot to landscape level. This user-friendly and practical tool provides site-specific recommendations on tree species selection via simple graphical displays and is targeted towards extension services and stakeholders directly involved in sustainable agroforestry and adaptation to climate change. The tool is based on a simple protocol to collect local agroforestry knowledge through farmers’ interviews and rankings of tree species with respect to locally perceived key ecosystem services. The data collected are first analysed using the BradleyTerry2 package in R, yielding the ranking scores that are used in the decision-support tool. Originally developed for coffee and cocoa systems of Uganda and Ghana, this tool can be extended to other producing regions of the world as well as to other cropping systems. The tool will be tested to see if repeated assessments show consistent ranking scores, and to see if the use of the tool by extension workers improves their shade tree advice to local farmers.

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