Assessing ecosystem service outcomes from future deforestation threats and payment for hydrologic services program designs in forested watersheds

In programs making payments for hydrologic services (PHS), downstream users offer incentives to upstream service providers to adopt land management strategies that can promote continued or improved water supply or water quality benefits. The goal of this work is to inform the design of PHS policies by modeling future ecosystem services outcomes from PHS programs in watersheds with tropical montane cloud forests and areas converted to pasture, coffee, and other crops in Veracruz state, Mexico. We use results from local field and computational studies to quantify hydrologic services- provisioning of dry season water supplies- and other complementary ecosystem services- carbon storage and biodiversity- associated with different land cover configurations. We combine the land cover-specific ecosystem service values with a land change model that simulates land use change behavior in response to PHS program design. The resulting integrated model allows evaluation of the performance of alternative program designs relative to PHS payment amount, coverage, and targeting to prioritize hydrologic recharge zones or deforestation risk.

We found that the additionality of the PHS program is currently relatively low, as evidenced by the watershed-scale ecosystem services values, due to low deforestation risk in PHS areas. However, if faced with increasing future deforestation threats, the PHS program provides important protection of ecosystem services benefits. The PHS scenarios results indicate that targeting of lands to be selected for payments has a clear influence on levels of ecosystem services provisioning. The current targeting strategy performs better than the hydrologic recharge zones or deforestation risk in terms of gains in ecosystem services, relative to other strategies. However, PHS targeting using deforestation risk alone can result in unintended consequences, where forest cover classes with higher deforestation risks, but poorer ecosystem service values, are selected for payments. We show that integrated modeling can be a powerful tool for anticipating benefits and unintended consequences associated with policies aimed at conserving forests.