Moving from Data Poor to Data Rich: A Case Study of Community‐Based Data Collection for the San Diego Red Sea Urchin Fishery

Stephen C Schroeter,Michael Robinson,Nicolás L Gutiérrez,Peter Halmay,Ray Hilborn

doi:10.1577/c08-037.1

Abstract

AbstractResponding to the need for management of California's nearshore fisheries mandated in state law by the Marine Life Management and Marine Life Protection acts, the San Diego Watermen's Association (SDWA), which includes divers that target local red sea urchins Strongylocentrotus franciscanus, initiated a community‐based data collection program in 2001. In collaboration with independent scientists and biologists from the California Department of Fish and Game, the SDWA developed an ongoing program to gather, organize, and analyze both fishery‐dependent and fishery‐independent data on the local red sea urchin fishery. The goal of the program is to collect data that will support periodical stock assessments needed for sustainable management of existing nearshore fisheries (including red sea urchins) as well as the kelp forest ecosystem on which these fisheries depend. Here, we discuss sampling designs, methods for determining data quality (bias and precision), and methods for detecting change, and we provide some examples of results from the ongoing community‐based data collection program. We also report on (1) the design and implementation of scientifically valid sampling protocols; (2) data quality assurance and control collaboratively conducted with scientists and resource agency biologists; (3) calibration studies to determine accuracy and precision and the magnitude of detectable changes in red sea urchin populations; and (4) visualization and dissemination of data and results and incremental changes in protocols that would facilitate the monitoring of associated biological communities. Finally, we discuss keys for success in this cooperative‐based data collection program and its implications for stock assessment and management of the red sea urchin fishery in California.

Highlights

Abstract.—Responding to the need for management of California’s nearshore fisheries mandated in state law by the Marine Life Management and Marine Life Protection acts, the San Diego Watermen’s Association (SDWA), which includes divers that target local red sea urchins Strongylocentrotus franciscanus, initiated a community-based data collection program in 2001
The SDWA-3 was the most precise protocol, but this assessment was based on a single calibration, overestimating the true density by 80%
SDWA-2 was potentially much more accurate and precise than either SDWA-1 or California Department of Fish and Game (CDFG)/ Cooperative Research and Assessment of Nearshore Ecosystems (CRANE). The latter two protocols are similar with regard to average accuracy and precision (CDFG/ CRANE is on average slightly less accurate and precise than SDWA-1); CDFG/CRANE had a much greater range of positive and negative bias than SDWA-1

Summary

Introduction

Abstract.—Responding to the need for management of California’s nearshore fisheries mandated in state law by the Marine Life Management and Marine Life Protection acts, the San Diego Watermen’s Association (SDWA), which includes divers that target local red sea urchins Strongylocentrotus franciscanus, initiated a community-based data collection program in 2001. There is considerable interest in small-scale management of many marine resources (Castilla and Defeo 2005; Gunderson et al 2008), which might involve area-specific size limits, effort, or total allowable catch controls and possibly stocking or reseeding for invertebrates This emphasis on spatial structure requires the need to identify appropriate spatial scales for data gathering, analysis, and management of exploited sedentary or low-mobility invertebrate stocks. The San Diego Watermen’s Association (SDWA) has developed a sampling protocol that allows working divers to collect random samples of sea urchin density and size distributions during the course of normal harvesting operations These samples are intended to capture the relevant spatial variability that typically occurs within kelp forests. Combining density estimates with size data will enable estimates of changes in whatever size-class is of interest, including young-of-the-year and harvest-sized individuals

Methods

Results

Conclusion