WISER: Which Ecosystem Service Models Best Capture the Needs of the Rural Poor?

Lead Research Organisation: Basque Centre for Climate Change
Department Name: Research

Abstract

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Planned Impact

The developmental impact of this project will be to contribute to poverty alleviation for the approximately 400 million people living in poverty in sub-Saharan Africa by improving the tools available to policy makers to manage ecosystem services (ES) to improve poor livelihoods in this region. More specifically, the findings of this project will enable decision makers to: 1) best use existing ES models to inform national and regional land use/cover change policies supporting ES management and promoting equality and justice amongst the beneficiaries of these services; and 2) set priorities determining where scarce resources should be invested to improve effective management of ES.
The main pathway to impact of WISER will be through improving the reliability of the tools and models that are used to manage the ES used by the rural poor in sub-Saharan Africa. Such an improvement in modelling will have direct impact on poverty alleviation by giving regional, national and international policy makers (the primary beneficiaries) the confidence to translate the multiple potential management actions that can be compared with such tools into evidence-based concrete policy actions which will allow alleviation of poverty through sustainable use of natural resources. In particular, WISER's tests of models that represent both the access to and utilisation of ES have the potential to have major impacts on poverty alleviation, given that this sort of disaggregation of beneficiaries of ES has been mostly overlooked in ES models, yet is clearly vital in devising pro-poor policies for ES management. The project is structured to ensure that the modelling needs of different types of policy makers are incorporated into the specific tests that we will conduct within the course of the project.
We will engage with both governmental and non-governmental organisations throughout the project via stakeholder interviews and workshops. WISER will actively listen to stakeholders throughout the project so they can identify their perceived needs for ES models: e.g. what outputs do they require and what spatial and temporal scale is needed? We will then use the results of these stakeholder engagements to inform our model comparison methods, ensuring we evaluate the ability of the ES models to fulfil the requirements of such decision makers. We will maintain regular communication with the stakeholders to help to build trust and provide the stakeholders with a sense of ownership and understanding of our results.
Our project team has a strong, grounded understanding of policy decision making at all levels. Our project partners include national staff members from Government Agencies, NGOs and civil society. Through collaboration with our project partners WISER will have access to local, regional and global dissemination networks that will help ensure that WISER deliver long lasting, poverty alleviating benefits, far beyond the lifetime and geographic span of the project.
The secondary beneficiaries include academics and researchers working in cognate fields. Results will be disseminated to academics via conferences, submission to professional newsletters and publication in international peer-reviewed journals. We aim publish in open access journals communicating research to the widest possible audience. Similarly, our data will be publicly available via an online repository.

Publications

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Balbi S (2015) Modeling trade-offs among ecosystem services in agricultural production systems in Environmental Modelling & Software

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Poppy GM (2014) Achieving food and environmental security: new approaches to close the gap. in Philosophical transactions of the Royal Society of London. Series B, Biological sciences

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Poppy GM (2014) Food security in a perfect storm: using the ecosystem services framework to increase understanding. in Philosophical transactions of the Royal Society of London. Series B, Biological sciences

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Villa F (2014) New perspectives in ecosystem services science as instruments to understand environmental securities. in Philosophical transactions of the Royal Society of London. Series B, Biological sciences

 
Title ARIES - ARtificial Intelligence for Ecosystem Services 
Description A web-accessible intelligent infrastructure to enable ecosystem services modeling on a larger scale and more adaptive approach than done before. 
Type Of Material Improvements to research infrastructure 
Year Produced 2014 
Provided To Others? Yes  
Impact See the ARIES web site (below) for a sample of case studies, publications and applications. 
URL http://aries.integratedmodelling.org
 
Title k.LAB semantic modelling platform 
Description Software infrastructure to enable cross-disciplinary, safe sharing of data and model artifacts and building of computational workflows to model concepts indicated by non-technical users. 
Type Of Material Improvements to research infrastructure 
Year Produced 2017 
Provided To Others? Yes  
Impact The ARIES project (http://aries.integratedmodelling.org) is one of the most well known results. 
URL http://www.integratedmodelling.org
 
Description Integrated Modelling Partnership 
Organisation Bangor University
Country United Kingdom 
Sector Academic/University 
PI Contribution I created the partnership with team members (including those from ESPA projects) to bring together institutions contributing to designing and building a fully integrated information landscape for the science of the future. The partnership develops and maintains the the k.LAB software stack that was employed and further developed in both my ESPA projects. It provides training in semantic modelling and supports partners and users in creating unprecedented model-data integration.
Collaborator Contribution The innovation and approach promoted and supported by the partnership were developed along with all partners as co-designers, promoters and testers.
Impact The k.LAB open-source software platform; The k.IM semantic annotation and modeling language; the IM worldview (ontologies) to describe data and model artifacts in an interoperable way. The collaboration is by nature multidisciplinary, being intended to enable dialogue between all disciplines through formal semantics, and there is no specific discipline it is targeted to, although the dialogue so far has involved the realm of sustainability - i.e., natural, social, economic, and climate sciences - more than others such as physics or astronomy.
Start Year 2018
 
Description Integrated Modelling Partnership 
Organisation US Geological Survey
Country United States 
Sector Public 
PI Contribution I created the partnership with team members (including those from ESPA projects) to bring together institutions contributing to designing and building a fully integrated information landscape for the science of the future. The partnership develops and maintains the the k.LAB software stack that was employed and further developed in both my ESPA projects. It provides training in semantic modelling and supports partners and users in creating unprecedented model-data integration.
Collaborator Contribution The innovation and approach promoted and supported by the partnership were developed along with all partners as co-designers, promoters and testers.
Impact The k.LAB open-source software platform; The k.IM semantic annotation and modeling language; the IM worldview (ontologies) to describe data and model artifacts in an interoperable way. The collaboration is by nature multidisciplinary, being intended to enable dialogue between all disciplines through formal semantics, and there is no specific discipline it is targeted to, although the dialogue so far has involved the realm of sustainability - i.e., natural, social, economic, and climate sciences - more than others such as physics or astronomy.
Start Year 2018
 
Description Integrated Modelling Partnership 
Organisation University of Vermont
Country United States 
Sector Academic/University 
PI Contribution I created the partnership with team members (including those from ESPA projects) to bring together institutions contributing to designing and building a fully integrated information landscape for the science of the future. The partnership develops and maintains the the k.LAB software stack that was employed and further developed in both my ESPA projects. It provides training in semantic modelling and supports partners and users in creating unprecedented model-data integration.
Collaborator Contribution The innovation and approach promoted and supported by the partnership were developed along with all partners as co-designers, promoters and testers.
Impact The k.LAB open-source software platform; The k.IM semantic annotation and modeling language; the IM worldview (ontologies) to describe data and model artifacts in an interoperable way. The collaboration is by nature multidisciplinary, being intended to enable dialogue between all disciplines through formal semantics, and there is no specific discipline it is targeted to, although the dialogue so far has involved the realm of sustainability - i.e., natural, social, economic, and climate sciences - more than others such as physics or astronomy.
Start Year 2018