A simplified image of a small part of the ARIES knowledge base.

<p>The MEA ES categories on the left are broken down into the benefits in the middle, only some of which (in blue) are directly connected to beneficiaries. Dashed lines exemplify indirect relationships that, when taken as the description of legitimate ecosystem services, have the potential of causing “double counting” by identifying benefits that are “intermediate” and not “final”, i.e., not directly linked to beneficiaries. Beneficiaries are depicted on the right, with non-rival benefits in green and rival benefits in orange.</p

Relative values for open space proximity source, use, and flows source, under alternative urban growth scenarios Green-Duwamish watershed, WA, USA.

<p>Relative values for open space proximity source, use, and flows source, under alternative urban growth scenarios Green-Duwamish watershed, WA, USA.</p

Water supply sustainability (m³/year) for rice agriculture in the two areas considered.

<p>Water supply sustainability (m³/year) for rice agriculture in the two areas considered.</p

The ARIES conceptual model of ecosystem service flow dynamics.

<p>The ARIES conceptual model of ecosystem service flow dynamics.</p

Total estimated water budget (m³/year) for sample areas outside (1) and adjacent to (2) CAZ.

<p>Total estimated water budget (m³/year) for sample areas outside (1) and adjacent to (2) CAZ.</p

Open space proximity flows in the Green-Duwamish watershed under baseline conditions and constrained and open urban-growth scenarios.

<p>Theoretical values are in relative rankings, ranging from 0 to 100 for each cell. When multiple users have access to one source of proximity value, the value for this non-rival service is multiplied by the number of users, so total flow values can exceed 100.</p

Water supply and quality in the CAZ area of Madagascar.

<p>From the left: total water demand across sectors, surface-water flow that is used by beneficiaries, and amount of sediment that is transported by hydrologic flows. Regions 1 and 2 (outlined in red) show the areas selected for comparison; the CAZ boundary is shown in black.</p

Evaluative criteria to improve uptake and utility of ES quantification methods in decision-making.

<p>Evaluative criteria to improve uptake and utility of ES quantification methods in decision-making.</p

Flow characteristics for selected ecosystem services. Types are P (provisioning) or R (preventive). Rivalness is R (rival) or N (non-rival).

<p>Flow characteristics for selected ecosystem services. Types are P (provisioning) or R (preventive). Rivalness is R (rival) or N (non-rival).</p

Rapid Assessment of Ecosystem Service Co-Benefits of Biodiversity Priority Areas in Madagascar

<div><p>The importance of ecosystems for supporting human well-being is increasingly recognized by both the conservation and development sectors. Our ability to conserve ecosystems that people rely on is often limited by a lack of spatially explicit data on the location and distribution of ecosystem services (ES), the benefits provided by nature to people. Thus there is a need to map ES to guide conservation investments, to ensure these co-benefits are maintained. To target conservation investments most effectively, ES assessments must be rigorous enough to support conservation planning, rapid enough to respond to decision-making timelines, and often must rely on existing data. We developed a framework for rapid spatial assessment of ES that relies on expert and stakeholder consultation, available data, and spatial analyses in order to rapidly identify sites providing multiple benefits. We applied the framework in Madagascar, a country with globally significant biodiversity and a high level of human dependence on ecosystems. Our objective was to identify the ES co-benefits of biodiversity priority areas in order to guide the investment strategy of a global conservation fund. We assessed key provisioning (fisheries, hunting and non-timber forest products, and water for domestic use, agriculture, and hydropower), regulating (climate mitigation, flood risk reduction and coastal protection), and cultural (nature tourism) ES. We also conducted multi-criteria analyses to identify sites providing multiple benefits. While our approach has limitations, including the reliance on proximity-based indicators for several ES, the results were useful for targeting conservation investments by the Critical Ecosystem Partnership Fund (CEPF). Because our approach relies on available data, standardized methods for linking ES provision to ES use, and expert validation, it has the potential to quickly guide conservation planning and investment decisions in other data-poor regions.</p></div