Detecting change in local ecological knowledge: An application of an index of taxonomic distinctness to an ethnoichthyological classification in the Solomon Islands

The global accelerating loss of biodiversity is having immediate repercussions for ecosystems and human wellbeing, particularly in areas where people depend intimately on their natural environment for their livelihoods. Dovetailing this loss is the demise of local/traditional knowledge systems resulting from factors such as changing lifestyle and the transformation of local belief systems. While the importance of local ecological knowledge (LEK) for documentation of biodiversity and environmental change and development of management responses is well established, quantitative tools to analyze and systematically compare LEK are scarce. In this research, we analyze the complexity of local ecological knowledge used by respondents to classify locally-recognized marine species. We do so by applying a modified index of taxonomic distinctness to an ethnoichthyological classification in coastal communities in the Solomon Islands. In addition, we assess simple taxonomic diversity (richness in locally-recognized species names) by comparing taxonomies collected in 1992–1995 and 2014–2015. Results indicate that both endogenous (gender, age) and exogenous (proximity to market) factors have discernible effects on folk taxonomic knowledge in the region, with younger respondents and communities closer to a regional market center displaying a significantly lower richness of local species names. Folk taxonomic distinctness was significantly reduced closer to the regional market. The modified index of taxonomic distinctness applied in this research provides a useful tool to explore facets of local ecological knowledge in addition to simple richness of terms, and to compare across different regions and cultural backgrounds. Understanding changes in LEK is important because such knowledge enables communities who are highly dependent on living natural resources to harvest and manage resources more efficiently and also to detect and react to environmental change.