Disaggregating ecosystem services and disservices in the cultural landscapes of southwestern Ethiopia: a study of rural perceptions

Context: Cultural landscapes provide essential ecosystem services to local communities, especially in poor rural settings. However, potentially negative impacts of ecosystems—or disservices—remain inadequately understood. Similarly, how benefit–cost outcomes differ within communities is unclear, but potentially important for cultural landscape management. Objectives: Here we investigated whether distinct forest ecosystem service–disservice outcomes emerge within local communities. We aimed to characterize groups of community members according to service–disservice outcomes, and assessed their attitudes towards the forest. Methods: We interviewed 150 rural households in southwestern Ethiopia about locally relevant ecosystem services (provisioning services) and disservices (wildlife impacts). Households were grouped based on their ecosystem service–disservice profiles through hierarchical clustering. We used linear models to assess differences between groups in geographic and socioeconomic characteristics, as well as attitudes toward the forest. Results: We identified three groups with distinct ecosystem service–disservice profiles. Half of the households fell into a “lose–lose” profile (low benefits, high costs), while fewer had “lose–escape” (low benefits, low costs) and “win–lose” (high benefits, high costs) profiles. Location relative to forest and altitude explained differences between the “lose–escape” profile and other households. Socioeconomic factors were also important. “Win–lose” households appeared to be wealthier and had better forest use rights compared to “lose–lose” households. Attitudes towards the forest did not differ between profiles. Conclusions: Our study demonstrates the importance of disaggregating both ecosystem services and disservices, instead of assuming that communities receive benefits and costs homogenously. To manage cultural landscapes sustainably, such heterogeneity must be acknowledged and better understood.