Finding common ground: Bringing together ecosystem services, agricultural productivity and smallholder livelihoods in landscape planning
Poverty alleviation is being tackled in increasingly disparate ways that may conflict with each other: rural development projects may increase agricultural productivity while degrading the natural resource base upon which downstream communities rely, whereas programs promoting the delivery of ecosystem services to those that benefit from them may hinder needed gains from agricultural development. This stems from the trade-offs that exist between different types of ecosystem services – provisioning services like agricultural production can achieve dramatic gains through intensification, but regulating services like water purification and flow regulation - those that result in benefits to drinking water, fisheries, or other livelihoods downstream - may be compromised by the removal of natural habitat and increasing erosion a result of such intensification. If rural development programs do not explicitly recognize these trade-offs and synergies and plan for them in a stakeholder-engaged process, unintended consequences may result and these programs could hurt the very people they are intended to help—or miss important opportunities for win-win outcomes (poverty alleviation andecosystem service conservation).
We present an optimization framework that integrates sustainable agricultural intensification and livelihood objectives into an ecosystem service planning approach for prioritizing conservation and agricultural interventions. We apply this approach in two conservation programs (1) the Nairobi Water Fund (upper Tana River) in Kenya; and (2) a Peruvian pilot scheme on Rewards for Ecosystem Services in theCañete Basin. Including agricultural productivity explicitly into the prioritization approach for these conservation schemes changes the design strategy of management interventions as well as the resulting outcomes for both agricultural production and other ecosystem service objectives. The resulting trade-off curve between different management objectives allows for transparent decision-making around trade-offs and synergies in program design. We also consider how the same approach can be applied to agricultural development decision contexts, to prioritize where to incentivize agricultural best management practices and the arrangement of cropland and other habitats in agricultural growth corridors.