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We have developed a set of tools that operate within an aquatic geographic information system to improve the accessibility, and usability of remote-sensed satellite and computer-modeled oceanographic data for marine science and ecosystem-based management. The tools form the Pelagic Habitat Analysis Module (PHAM), which can be applied as a modeling platform, an investigative aid in scientific research, or utilized as a decision support system for marine ecological management. Applications include fisheries, marine biology, physical and biological oceanography, and marine spatial management. The GIS provides a home for diverse data types and automated tools for downloading remote sensed and global circulation model data. Within the GIS environment, PHAM provides a framework for seamless interactive four-dimensional visualization, for matching between disparate data types, for flexible statistic or mechanistic model development, and for dynamic application of user developed models for habitat, density, and probability predictions. Here we describe PHAM in the context of ecosystem-based fisheries management, and present results from case study projects which guided development. In the first, an analysis of the purse seine fishery for tropical tuna in the eastern Pacific Ocean revealed oceanographic drivers of the catch distribution and the influence of climate-driven circulation patterns on the location of fishing grounds. To support management of the Common Thresher Shark (Alopias vulpinus) in the California Current Ecosystem, a simple empirical habitat utilization model was developed and used to dynamically predict the seasonal range expansion of common thresher shark based on oceanographic conditions.

We developed an iterative sequential random utility model to investigate the social and environmental determinants of the spatiotemporal decision process of tuna purse-seine fishery fishing effort in the eastern Pacific Ocean. Operations of the fishing gear mark checkpoints in a continuous complex decision-making process. Individual fisher behavior is modeled by identifying diversified choices over decision-space for an entire fishing trip, which allows inclusion of prior and current vessel locations and conditions among the explanatory variables. Among these factors are vessel capacity; departure and arrival port; duration of the fishing trip; daily and cumulative distance travelled, which provides a proxy for operation costs; expected revenue; oceanographic conditions; and tons of fish on board. The model uses a two-step decision process to capture the probability of a vessel choosing a specific fishing region for the first set and the probability of switching to (or staying in) a specific region to fish before returning to its landing port. The model provides a means to anticipate the success of marine resource management, and it can be used to evaluate fleet diversity in fisher behavior, the impact of climate variability, and the stability and resilience of complex coupled human and natural systems.

In the Pacific, blue marlin are an incidental catch of longline fisheries and an important resource for big game recreational fishing. Over the past two decades, blue marlin assessments by different techniques have yielded results ranging from an indication of declining stock to a state of sustained yield at approximately the maximum average level. Longline fishing practices have changed over the years since the 1950s in response to changes in principal target species and to gear developments. Despite increasingly sophisticated attempts to standardize fishing effort with changing fishing practices, the stock assessments to date are likely confounded to a greater or lesser degree by changes in catchability for blue marlin. Yet, only data from commercial longline fisheries targeting tuna provide sufficient spatial and temporal coverage to allow assessment of this resource. To re-assess the blue marlin stocks in the Pacific and also to assess the efficacy of a habitat-based standardization of longline effort, a collaborative analysis was conducted involving scientists at the National Research Institute of Far Seas Fisheries, Shimizu, Japan, the Inter-American Tropical Tuna Commission, La Jolla, California, and the NOAA Fisheries Honolulu Laboratory, Honolulu, Hawaii. Using MULTIFAN-CL as an assessment tool, there was considerable uncertainty in quantifying the fishing effort levels that would produce a maximum sustainable yield. However, it was found that, at worst, blue marlin in the Pacific are close to a fully exploited state, that is the population and the fishery are somewhere near the top of the yield curve. Furthermore, it was found that effort standardization using a habitat-based model allowed estimation of parameters within reasonable bounds and with reduced confidence intervals about those values.

Swordfish (Xiphias gladius) are harvested in target and non-target fisheries throughout the eastern Pacific Ocean (east of 150°W). Analyses of trends in catch rates (catch per unit effort) standardized using general linear models indicate that there are two stocks in the eastern Pacific Ocean that have a north–south boundary at 5°S latitude; this is in striking contrast to the 10°N boundary that has generally been assumed by previous studies. Trends in standardized catch per unit effort have held relatively level for the north stock and have been increasing for the south stock. Considering these trends and given that annual catches have been fairly stable in the region since 1989, it appears that swordfish are not overfished in the eastern Pacific Ocean. Given the potential for rapid change in the nature of those gill-net and longline fisheries that are increasingly targeting swordfish in the region, the trends in standardized catch per unit effort should be closely monitored for indications of changing status of these stocks.