WISER: Which Ecosystem Service Models Best Capture the Needs of the Rural Poor?
Lead Research Organisation:
University of Southampton
Department Name: Centre for Biological Sciences
Abstract
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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.
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.
Organisations
Publications

Bryant B
(2018)
Transparent and feasible uncertainty assessment adds value to applied ecosystem services modeling
in Ecosystem Services

Cooper GS
(2020)
Regime shifts occur disproportionately faster in larger ecosystems.
in Nature communications

Hooftman D
(2022)
Reducing uncertainty in ecosystem service modelling through weighted ensembles
in Ecosystem Services

Hooftman D
(2023)
National scale mapping of supply and demand for recreational ecosystem services
in Ecological Indicators

Martínez-López J
(2019)
Towards globally customizable ecosystem service models.
in The Science of the total environment

Willcock S
(2016)
Do ecosystem service maps and models meet stakeholders' needs? A preliminary survey across sub-Saharan Africa
in Ecosystem Services

Willcock S
(2020)
Ensembles of ecosystem service models can improve accuracy and indicate uncertainty.
in The Science of the total environment

Willcock S
(2023)
Model ensembles of ecosystem services fill global certainty and capacity gaps.
in Science advances

Willcock S
(2019)
A Continental-Scale Validation of Ecosystem Service Models
in Ecosystems

Willcock S
(2018)
Machine learning for ecosystem services
in Ecosystem Services
Title | Ensembles of ecosystem service models |
Description | We produced a 90sec animation describing the benefits of using ensembles of ecosystem service models. This was released as the video abstract of a paper, but also shared with key decision makers |
Type Of Art | Film/Video/Animation |
Year Produced | 2021 |
Impact | None to date |
URL | https://www.sciencedirect.com/science/article/pii/S221204162100156X |
Description | The aim of this project was to test if current modelling approaches for mapping key natural resources used by people (ecosystem services - ES) in sub-Saharan Africa were sufficiently good to inform policy. Our first output was a survey of current users (stakeholders) of existing ES models to see if they thought that the information they needed was being adequately provided, and if not, why. The main finding was that only 27% of the people we surveyed reported that adequate data existed for their policy needs. The second output - the main output of the project - was to use existing modelling approaches, as well new models based on simple modifications of existing models to better take users of natural resources into account, and test how well these predicted water availability, carbon stocks, firewood and charcoal use, and grazing resources across sub-Saharan Africa. We were particularly interested in seeing if more 'complex' models provided better predictive power with the goal of identifying minimum adequate models. This analysis - which used over 1600 datapoints from 16 separate datasets showed that existing modelling approaches were quite good at mapping the biophysical supply of natural resources, but much less good at identifying use of natural resources. We also found some evidence that complex models were often better and never worse than less complex models in predicting distributions of ES. Our findings are important as they show both that in some cases existing models do seem to provide useful information for policy makers - important in a data-poor region - but also that more effort is required to build better models linking demand for natural resources to their distributions. Finally, in follow on work we show that ensembles of multiple ES models generally out-perform individual models, and are a promising approach for improving performance of ES models, particularly if validation data is lacking. |
Exploitation Route | Our findings are important as they show both that in some cases existing models do seem to provide useful information for policy makers - important in a data-poor region - but also that more effort is required to build better models linking demand for natural resources to their distributions. So far, the overall PI on the project (Prof James Bullock) has taken some of our work and turned into a policy brief (http://www.wri.org/publication/guide-selecting-ecosystem-service-models-decision-making-lessons-sub-saharan-africa) in collaboration with the large international NGO World Resource Institute. We anticipate the findings will be of widespread interest in both the academic and modelling community once published (the main paper is currently in review) |
Sectors | Environment |
URL | http://dx.doi.org/10.5285/11689000-f791-4fdb-8e12-08a7d87ad75f |
Description | The PI on the project has turned some of our key outputs into a policy brief in collaboration with the major international environmental NGO World Resources Institute: http://www.wri.org/publication/guide-selecting-ecosystem-service-models-decision-making-lessons-sub-saharan-africa The same resource is also available on the ESPA website: https://www.espa.ac.uk/publications/guide-selecting-ecosystem-service-models-decision-making-lessons-sub-saharan-africa |
Sector | Environment |
Impact Types | Societal |
Description | Between environmental concerns and compliance: How does media messaging affect motivation and choice between disposable versus reusable facemasks? |
Amount | £343,974 (GBP) |
Funding ID | AH/W003813/1 |
Organisation | Arts & Humanities Research Council (AHRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2021 |
End | 05/2022 |
Description | ERC Starting Grant |
Amount | € 1,485,000 (EUR) |
Funding ID | 680176 |
Organisation | European Research Council (ERC) |
Sector | Public |
Country | Belgium |
Start | 06/2016 |
End | 07/2021 |
Description | EnsemblES - Using ensemble techniques to capture the accuracy and sensitivity of ecosystem service models |
Amount | £47,862 (GBP) |
Funding ID | NE/T00391X/1 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 08/2019 |
End | 08/2020 |
Description | MobilES - Using mobile-phone technology to capture ecosystem service information |
Amount | £218,797 (GBP) |
Funding ID | ES/R009279/1 |
Organisation | Economic and Social Research Council |
Sector | Public |
Country | United Kingdom |
Start | 09/2018 |
End | 07/2021 |
Description | Rurality as a vehicle for Urban Sanitation Transformation (RUST) |
Amount | £431,400 (GBP) |
Funding ID | ES/R006865/1 |
Organisation | Economic and Social Research Council |
Sector | Public |
Country | United Kingdom |
Start | 04/2018 |
End | 05/2020 |
Description | Scaling up Off-Grid Sanitation |
Amount | £1,749,830 (GBP) |
Funding ID | ES/T007877/1 |
Organisation | Economic and Social Research Council |
Sector | Public |
Country | United Kingdom |
Start | 06/2020 |
End | 09/2024 |
Description | The impact of Covid-19 restrictions on recreation and use of green space in Wales |
Amount | £10,877 (GBP) |
Funding ID | ES/V004077/1 |
Organisation | Economic and Social Research Council |
Sector | Public |
Country | United Kingdom |
Start | 05/2020 |
End | 11/2021 |
Title | Ensemble outputs from Ecosystem Service models |
Description | Ensemble outputs from Ecosystem Service models for water supply, aboveground carbon storage and use of water, grazing, charcoal and firewood by beneficiaries in sub-Saharan Africa. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | Underpins a paper - https://www.sciencedirect.com/science/article/pii/S0048969720345356 |
URL | https://eprints.soton.ac.uk/446323/ |
Title | Global ensembles of Ecosystem Service map outputs modelled at 1km resolution for water supply, recreation, carbon storage, fuelwood and forage production |
Description | This data set contains Global maps of five ecosystem services using 6 different among-model ensemble approaches: the provisioning services of water supply, biomass for fuelwood and forage production, the regulating service Carbon Storage for CO2 retention and the cultural non-material service Recreation. For water, the data comes as one shapefile with polygons per watershed, each polygon containing seven ensemble estimates. The other services - recreation, carbon storage, biomass for fuelwood and forage production - come as seven tiff- maps at a 1-km2 resolution with associated world files for each tiff-map contains 43,200 x 18,600 pixels for one ensemble approach, with LZW compressed file sizes between 400MB and 950MB. For all maps, 600dpi jpg depictions are added to the supporting information with uniform colour scaling set for the median ensemble per service. Ensemble output maps were calculated with different approaches following the supporting documentation and associated publication. Uncertainty estimates for these services are included as variation among contributing model outputs and among the employed ensemble approaches. |
Type Of Material | Database/Collection of data |
Year Produced | 2023 |
Provided To Others? | Yes |
Impact | None yet (associated publication is still in-review) |
URL | https://catalogue.ceh.ac.uk/documents/bd940dad-9bf4-40d9-891b-161f3dfe8e86 |