Information Flows in Community-Based Monitoring Exercises in the Ecuadorian Amazon

Community-based monitoring schemes provide alternatives to costly scientific monitoring projects. While evidence shows that local community inhabitants can consistently measure environmental changes, few studies have examined how learned monitoring skills get passed on within communities. Here, we trained members of indigenous Kichwa communities in the Ecuadorian Amazon to measure fern and dung beetle species richness and examined how well they could pass on the information they had learned to other members of their community. We subsequently compared locally gathered species richness data to estimates gathered by trained biologists. Our results provide further evidence that devolved monitoring protocols can provide similar data to that gathered by scientists. In addition, our results show that local inhabitants can effectively pass on learned information to other community members, which is particularly important for the longevity of community-based monitoring initiatives. 1. Introduction Community-based monitoring schemes (CBMS) combine local traditional knowledge with existing organizational systems to measure ecological changes [1, 2]. Because CBMS can increase local understanding of environmental issues [3], they are considered capacity building exercises that provide evidence for local management decisions [4]. Evidence shows that, with appropriate training, CBMS can provide precise data on environmental processes. Danielsen et al. [5] show that trained community members are able to accurately monitor biomass and logging activities in India, Tanzania, and Madagascar. Similarly, Oldekop et al. [6] show that community inhabitants in Ecuador can use simple and cost-effective methodologies to provide fern species richness estimates that accurately reflect biodiversity patterns observed by scientists. What has not yet been addressed, however, is how information gained by those attending training schemes is passed on to other community members. In other words, we do not know whether trained community members can train other people within their communities. This information is important for the creation of long-term and decentralized CBMS, where the majority of the collection and interpretation of data is directly managed by local communities and stakeholders [1, 2]. Here, we use a CBMS exercise with indigenous Kichwa communities in the Ecuadorian Amazon to assess the ability of locally trained community members to train other residents within their communities. Specifically, we compare species richness estimates of two biodiversity indicators, ferns [7]