MESHing ecosystem services – a new tool for policymakers and ecosystem services practitioners
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Mapping Ecosystem Services to Human well-being – MESH – is an ecosystem service assessment and mapping toolkit developed by Bioversity International, CGIAR, and the Natural Capital Project in support of a Science for Nature and People (SNAP) project on ‘Making Ecosystems Count in the Sustainable Development Goals (SDGs)’. Download MESH: http://www.naturalcapitalproject.org/mesh/
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MESHing ecosystem services – a new tool for policymakers and ecosystem services practitioners
- 1. MESH-ing Ecosystem Services & Human well-being for the SDGs Sarah Jones & Sylvia Wood
- 3. Agricultural Landscapes as Silver Bullet for SDGs?
- 4. Integrated Land Management Approach for the SDGs • Land & food systems an SDG “silver bullet” • Multi-sectoral planning and cooperation • ES link disparate Conservation & Development • Identify tradeoffs/opportunities across landscapes • Nudge needle on a number of SDGs Water Quality Human Nutrition Climate ChangeFood Security SDG 2 SDG 6 SDG 2 SDG 13
- 5. Carbon storage Food Production & Nutrition Water Availability Building materials Recreation!? Transport/h ydropower SDG 2 SDG 13 SDG 6 SDG 3 SDG 5? SDG 9 SDG 7 SDG 14 Disease? Biodiversity SDG 15 Eutrophication Designing multi-functional landscapes
- 6. To address ES- SDG Gap: SNAP project 1) How can we quantify ES for SDGs (relevant to policy needs)? 2) How can we evaluate them in an integrative manner demanded by the SDGs framework models
- 7. • SDG Symbols – select out relevant ones ES- SDG linkages
- 8. Ecosystem Services Scientific evidence Food Production Pollination Nutrient Cycling Erosion Prevention Carbon Sequestration Water Regulation Habitat Creation Temp Regulation Air Quality ??? ??? Potential indicators
- 9. Agriculture Transboundary water management Stakeholders: Volta basin focus Water scarcity and land degradation • Strong need and interest in finding cross- sectoral synergies - $ • Challenge of data and tools Nutrition Science-policy workshop
- 10. Crop production value per land unit ($/ha) Prevalence of undernourishment if food is sourced locally (calorie only) / (macro- nutrients only) / (micro-nutrients only) Agricultural land at high / low / no risk of land degradation (%) Crop production value per water unit ($/m3) SDG 2 (food) No. people without access to sufficient quantity of quality water SDG 3 (health) No. people living in malaria risk zone SDG 6 (water) Human water quality footprint (index) Population exposed to diarrhoeal disease Total annual gross soil erosion on ag land (t/ha) Ag land with low carbon emissions (%) SDG 15 (terrestrial) SDG 13 (climate) Pollination Regulation of water supply Pollutant filtration Nutrient retention Crop production Erosion control Habitat-based vector control ECOSYSTEM SERVICE MESH-SDG INDICATOR SDG Carbon storage Quantity of runoff in urban areas (mm/y) Urban water quality footprint (index) SDG 11 (cities)
- 11. Using Trade-Off Analysis for ILM Challenges 1. Data intensive 2. Technically challenging 3. Many steps & programs 4. Heavy pre- & post-processing
- 12. Mapping Ecosystem Services to Human wellbeing Aiming for: User-friendly interface Easy to alter parameters Speed Default datasets User-driven output formats Plug-in capacity for other ES models
- 13. MESH Model Interface 1. Scenario Generator 2. Select relevant ES 3. Run the models 4. Results output 5. Report
- 14. Links between ecosystem service supply and SDGs Nutrition Water quality Water yieldCarbon Sediment retention ?? SDG 2 SDG 3 SDG 6SDG 13 SDG 15 Scenario 1 Scenario 2 Scenario 3
- 15. THANK YOU Live Demo of MESH Check out Justin Johnson’s presentation T4a 3:30pm! MESH Webpage http://www.naturalcapitalproject.org/mesh/
Hinweis der Redaktion
- Boils down to challenge of achieving development AND conservation goals. Ecosystem services are a really useful linking concept. We wanted to find out whether measures of ES could be expressed in a way that is useful to policymakers seeking to achieve the SDGs, and explore ways to generate these measures. This work led to two main outputs which I’ll discuss now – a conceptual framework and a integrative ES modelling tool.
- We decided to home in on a subset of the SDGs that were most obviously linked to ecosystems.
- We identified where a change in an ecosystem service is likely to have an impact on one or more of these SDGs, and collated evidence for quantifiable links between each ES and each SDG, through scientific workshops and a literature review. We were interested in identifying ES that were measurable, ideally modelable, and whether existing measures could be improved to be of more relevance to policy makers interested in the SDGs, e.g. food production > nutrition content > distribution of this nutrition > no. people impacted. This work generated a list of potential indicators linking ES to the SDGs. Next we talked to existing and some new WLE in-country stakeholders to understand which of these indicators would be of interest and most useful for investment and policy decision-making, and what metrics were useful to stakeholders ($, yields, no. people etc).
- We chose to consult stakeholders in regions where Bioversity and other members of WLE are actively engaged, and focused on the Volta basin. This is an area where over 80% livelihoods part or wholly dependent on agriculture, there is increasing water scarcity, land degradation, low food security, and strong interest in finding integrated solutions particularly in the proactive water management authority. Stakeholders here, particularly in the conservation sector but also in more development orientated sectors like health and agriculture, want access to inofmraiton that shows the value of forests, wetlands, waterways and other ecosystems for livelihoods, and highlight cross-sector trade-offs in managing ES, e.g. agricultural expansion that increases sedimentation in reservoirs / hydropower, but also provides essential nutrition for food security. Emphasised the challenge of getting access to good data and suitable tools to monitor environmental change and livelihood impacts. 29 interviews with over 50 stakeholders, spanning 32 institutions Agriculture, water, health, environment sectors Private sector, research institutes, government bodies, international organisations and civil society organisations
- This is our conceptual framework for ES-SDG linkages. It shows that multiple ES are relevant for any one SDG, so finding ways to achieve one or more than one SDG requires understanding trends and trade-offs in several ES at a time. It is difficult to identify the best route for managing ES to achieve one or multiple SDGs because of the complexity of the linkages and quantifying trade-offs – but real demand for this information from stakeholders. This is where science can help, wouldn’t it be great if we had an integrative model…
- 2-LINE TITLE AND BULLETS If you have long headers, please use this slide. Font size and spacing between the two lines have been customized.
- Get updated interfance screen shot showing Africa in viewer!!!! Explain the MESH model interface components. Maybe add something about how each indicator will be presented along with a link to the SDG of relevance and a statement of its contribution….