Fundamental insights on when social network data are most critical for conservation planning

Abstract

As declines in biodiversity accelerate, there is an urgent imperative to ensure that every dollar spent on conservation counts toward species protection. Systematic conservation planning is a widely used approach to achieve this, but there is growing concern that it must better integrate the human social dimensions of conservation to be effective. Yet, fundamental insights about when social data are most critical to inform conservation planning decisions are lacking. To address this problem, we derived novel principles to guide strategic investment in social network information for systematic conservation planning. We considered the common conservation problem of identifying which social actors, in a social network, to engage with to incentivize conservation behavior that maximizes the number of species protected. We used simulations of social networks and species distributed across network nodes to identify the optimal state-dependent strategies and the value of social network information. We did this for a range of motif network structures and species distributions and applied the approach to a small-scale fishery in Kenya. The value of social network information depended strongly on both the distribution of species and social network structure. When species distributions were highly nested (i.e., when species-poor sites are subsets of species-rich sites), the value of social network information was almost always low. This suggests that information on how species are distributed across a network is critical for determining whether to invest in collecting social network data. In contrast, the value of social network information was greatest when social networks were highly centralized. Results for the small-scale fishery were consistent with the simulations. Our results suggest that strategic collection of social network data should be prioritized when species distributions are un-nested and when social networks are likely to be centralized.

Collaboration or Contravention? Ramifications For Effective Participatory Decision-Making in Collaborative Forest Management at Echuya Central Forest Reserve, South Western Uganda

“…This agrees with Pham et al (2015) who revealed that consultations ought to be conducted before implementing conservation projects. The findings are further in agreement with Rhodes et al (2020), who asserted that the participation of various stakeholders is essential as they are most conversant with forest management issues. Moreover, Dobrynin et al (2020) stated that effective collaborative forest management standards require consultations with local communities and indigenous people and mechanisms for resolving grievances.…”

“…This is contrary to the Charlene et al ( 2017) study, which showed that most community members who depended on forests were not offered a platform to contribute to forest management or action plan development. However, scholars (Rhodes et al, 2020;Zhang et al, 2020) opined that integrating opinions from local communities in conservation planning and development is an essential aspect of sustainable forest conservation. Lise (2009) consistently argued that effective community participation remains a mirage if community members are not involved in planning, implementation, monitoring, and evaluation processes.…”

“…However, in Liberia, most community members who depended on forests were not involved in developing action plans for managing and conserving the forests (Charlene et al, 2017). Yet, integrating opinions from local communities in conservation planning and development is essential to sustainable forest conservation (Rhodes et al, 2020;Zhang et al, 2020). As Lise (2009) noted, effective community participation remains a mirage if community members are not involved in planning, implementation, monitoring, and evaluation processes.…”

Combining simulation and empirical data to explore the scope for social network interventions in conservation

“…This approach may be valuable for refining large-scale interventions; in our case, this approach is cost-effective if a large number of villages are included in the intervention (although the absolute cost of data collection is still low). Simple value of information analyses combined with simulations can help to guide these decisions (Rhodes et al, 2020;Akbarpour, Malladi & Saberi, 2020;Canessa et al, 2015). Third, the large literature on network interventions (Valente, 2012) suggests improvements to intervention design that apply across contexts, such as the use of clustered targeting strategies (Centola, 2018).…”

Conceptualizing ecosystem services using social–ecological networks

“…[3], we argue that important information can be missed in ecosystem service studies that analyze only social or ecological networks rather than an integrated SEN [19,86,87], such as the role of social relationships in shaping management actions that affect the ecological network [88,89] or the complex ecological interactions underlying ecosystem service supply [5]. SENs can complement other integrated modeling frameworks (e.g., [90,91]) that acknowledge linkages between, and complexities within, both social and ecological layers.…”