Long-Lived Iteroparous Species, Ecological, Demographic and Genetic Complexity: Acquisition, Management and Analytical Challenges Associated with Big Data

Successful management of long-lived iteroparous fish species necessitates collection, curation and analysis of large and multi-faceted data sets.  Increasing accessibility of remotely censused data, enhanced abilities to interrogate biotic communities, and tools to quantify genetic diversity during several life stages, over multiple spatial scales, and over long periods of time pose data acquisition, management and analytical challenges. Using decadal data collected from a population of lake sturgeon (Acipenser fulvescens) inhabiting Black Lake, MI we highlight why collection of time series data associated with ecological, demographic, and genetic complexities is required to understand generational patterns in recruitment dynamics of long-lived fishes.  We highlight issues associated with collection, curation, sharing, transfer, analysis and visualization of Big Data with emphasis on the need for development and testing of models that integrate data from across life stages and that account for spatial non-independence.