An Extension of the Stepwise Stochastic Simulation Approach for Estimating Distributions of Missing Life
We expanded on the stepwise meta-analytical approach to combat the challenges associated with effective management of coastal fisheries learn what produces more accurate and precise results.
The limited resources and high species diversity associated with coastal fisheries present challenges to their effective management. Data-limited approaches to assessment of stocks are often used in these situations, but most assessments require basic life history information that is often unavailable. We expanded a stepwise meta-analytical approach in which statistical relationships between key life history traits are used to estimate parameters related to growth, maturity, and longevity. This approach was originally devised for 6 fish families and has been successfully implemented in the assessments of data-poor reef fish species in Hawaii and Guam. We expanded this approach to groupers, wrasses, grunts, and sharks and, here, present an R package that greatly simplifies its implementation. Further, we tested this expansion by selecting a species from each of these taxa and compared results from use of the stepwise approach to results from life history studies. Our results indicate agreement between the probability distributions from our stepwise approach and those from previous studies. Distributions from the stepwise simulation had higher variability but reasonable accuracy in estimating missing values of life history parameters. We also tested our approach against another meta-analytical life history approach that was recently published (and made available as the R package FishLife) and found our stepwise approach to be generally more precise and accurate.
Erickson KA, Nadon MO. 2021. An extension of the stepwise stochastic simulation approach for estimating distributions of missing life history parameter values for sharks, groupers, and other taxa. Fish. Bull. 119(1):77-92. https://doi.org/10.7755/FB.119.1.9.