Using Local Ecological Knowledge to Inform Species Distribution Models: An Example with Gag Grouper

Wide-ranging fish stocks present particular problems in assessing the stock’s distribution at fine spatial scales but local ecological knowledge (LEK), such as that provided in fishing reports and angler diaries can provide meaningful environmental data while withholding traditional presence/absence information. We present a modeling framework and case study in Gag Grouper (Mycteroperca microlepis) to translate LEK from environmental space to geographic locations in the Gulf of Mexico. Distributions from LEK were created in relation to depth, temperature, season, and structure (salt marsh, seagrass, tidal flat, reef). We seeded the geographic space with an initial population of Gag based on these distributions in space and proportional by age using their survivorship and sexual transition. A GLM was used to define functional environmental relationships and to derive habitat suitability indices for the geographic space given 1000 random seeds. Using these relationships, an age-structured spatial population dynamics model was used to simulate 100 years of Gag movement based on density-dependence relationships derived from the explicit habitat suitability index. The realized distribution of Gag from this framework incorporates demographic and ecological spatiotemporal relationships (such as spawning and nursery habitats) as well as a novel method of formalizing LEK into stock distribution information.