Introduction to a Special Section: Spatial Analysis, Mapping, and Management of Marine Fisheries

The Magnuson–Stevens Fishery Conservation and Management Act of 1996 mandated that the National Marine Fisheries Service develop guidelines to assist fisheries management councils nationwide in the creation of essential fish habitat (EFH) regulations (NMFS 1996). The amended act (Magnuson–Stevens Fishery Conservation and Management Reauthorization Act of 2006) required regional fishery management councils to set annual catch limits (ACLs) and accountability measures (AM) by 2011 for all managed species to ensure that overfishing would not occur. It also required that the councils create fisheries ecosystem plans to better relate fishery species to their supporting ecosystems through ecosystem-based fisheries management. Unfortunately, due to limitations on funding, resources, and available data, it is difficult to fully implement these requirements. Most of the marine fisheries data used to support stock assessments and management are collected by fisheriesdependent monitoring (FDM) when the fish are landed. The fishermen report their catches from large statistical zones as either catch per day or catch per trip. In most cases, no associated environmental, habitat, or geographically specific fishing location data are reported. An alternative is to collect georeferenced catch, effort, and environmental data at sea using government-sponsored fishery-independent monitoring (FIM). But FIM surveys are expensive and funding is becoming more difficult to obtain. While it is obvious to most anglers and commercial fishermen that estuarine and marine species occupy various habitats throughout their life histories, single-species stock assessment models often do not include georeferenced catch-per-uniteffort (CPUE) and associated environmental data. Part of the problem has been that better analytical tools were needed to quantify fish–habitat relationships. Fortunately, there have been large improvements in GIS software, models, statistical approaches, and computing capabilities. The papers presented in this special section demonstrate recent developments in modeling and mapping to better support the spatial management of marine fisheries. Bryan et al. (2016) describe the feasibility of a regionwide FIM probability survey of coral reef fishes in Puerto Rico and the U.S. Virgin Islands. Four years of underwater visual survey data were collected and used in conjunction with detailed bathymetric maps and bottom habitat maps to develop a probability sampling design. Stratification by depth and habitat produced a more efficient survey design for estimating fish density. These authors found that controlling survey precision over a region required less sampling effort than controlling precision for smaller areas within the larger survey frame. The regional sampling design thus allowed more cost-effective surveys with higher precision. The article shows the importance of defining management objectives prior to the development of FIM surveys. Harford et al. (2016) studied cross-shelf occupancy probabilities for juvenile groupers in the Florida Keys. A FIM-based diver visual survey was used to quantify the occupancy patterns of Black Grouper Mycteroperca bonaci and Red Grouper Epinephelus morio below minimum size limits. Logistic regression and site occupancy models were used to quantify predicted occurrence probability with respect to latitude and across depth and vertical relief gradients. Multilevel models revealed variance structures of fish distributions not revealed by fixed-effects models. Both grouper species demonstrated occurrence responses that varied with the regional topographic features of the reef tract.