Volume 68
Artificial Reef Fish Survey Methods: Counts vs. Log-Categories Yield Different Diversity Estimates
Authors
Hicks, D., C.E. Cintra-Buenrostro, R. Kline, D. Shively, and B. Shipley-Lozano Download PDF Open PDF in BrowserOther Information
Date: November, 2015
Pages: 74 - 79
Event: Proceedings of the Sixty eigth Annual Gulf and Caribbean Fisheries Institute
City: Panama City
Country: Panama
Abstract
Texas Parks and Wildlife Departments (TPWD) Artificial Reef Program (ARP) has utilized the roving diver technique (RDT) recording abundances as order of magnitude counts [REEF-type: Single (1); Few (2-10), Many (11-100), and Abundant (> 100), SFMA hereafter] for many years. However, because SFMA counts do not provide numerical abundances in catch per unit effort (CPUE) or density, these data cannot be integrated with other state coastal survey data for stock assessment (e.g., trawl fisheries, gill net, vertical long line). Accordingly, a comparison of exact and order-of-magnitude counts (SFMA) from paired divers was conducted during five consecutive sampling quarters at the USTS Texas Clipper Reef located 17 nm offshore of South Padre Island, Texas, USA. SFMA data were converted to numerical abundances and compared to exact counts via rank correlations of their similarity matrices on the assertion that if both survey methods capture similar species richness and relative abundance, their correlation should be high. In this study, which eliminated roving bias, biodiversity was greatest for the order-of-magnitude count method compared to exact counting which tended to underrepresent small cryptic reef fish as well as pelagic schooling fish. Exact counts by divers were found to underestimate species richness by 15 - 30% compared to the SFMA method. In addition, we found that both enumeration methods produced similar results in capturing relative abundances of large, abundant, and conspicuous species. The results of our survey method comparison indicate that the log-category census method is an effective technique when diversity estimates are a major goal.