Channel Islands marine protected areas first 5 years of monitoring: 2003-2008 [Report produced by the California Department of Fish and Game in collaboration with the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO), Channel Islands National Marine Sanctuary, and Channel Islands National Park]

The Channel Islands—sometimes called the Galapagos of North America—are known for their great beauty, rich biodiversity, cultural heritage, and recreational opportunities. In 1980, in recognition of the islands’ importance, the United States Congress established a national park encompassing 5 of California’s Channel Islands (Santa Barbara, Anacapa, Santa Cruz, Santa Rosa, and San Miguel Islands) and waters within 1 nautical mile of the islands. In the same year, Congress declared a national marine sanctuary around each of these islands, including waters up to 6 nautical miles offshore. Approximately 60,000 people visit the Channel Islands each year for aquatic recreation such as fishing, sailing, kayaking, wildlife watching, surfing, and diving. Another 30,000 people visit the islands for hiking, camping, and sightseeing. Dozens of commercial fishing boats based in Santa Barbara, Ventura, Oxnard, and other ports go to the Channel Islands to catch squid, spiny lobster, sea urchin, rockfish, crab, sheephead, flatfish, and sea cucumber, among other species. In the past few decades, advances in fishing technology and the rising number of fishermen, in conjunction with changing ocean conditions and diseases, have contributed to declines in some marine fishes and invertebrates at the Channel Islands. In 1998, citizens from Santa Barbara and Ventura proposed establishment of no-take marine reserves at the Channel Islands, beginning a 4-year process of public meetings, discussions, and scientific analyses. In 2003, the California Fish and Game Commission designated a network of marine protected areas (MPAs) in state waters around the northern Channel Islands. In 2006 and 2007, the National Oceanic and Atmospheric Administration (NOAA) extended the MPAs into the national marine sanctuary’s deeper, federal waters. To determine if the MPAs are protecting marine species and habitats, scientists are monitoring ecological changes. They are studying changes in habitats; abundance and size of species of interest; the ocean food web and ecosystem; and movement of fish and invertebrates from MPAs to surrounding waters. Additionally, scientists are monitoring human activities such as commercial and recreational fisheries, and compliance with MPA regulations. This booklet describes some results from the first 5 years of monitoring the Channel Islands MPAs. Although 5 years is not long enough to determine if the MPAs will accomplish all of their goals, this booklet offers a glimpse of the changes that are beginning to take place and illustrates the types of information that will eventually be used to assess the MPAs’ effectiveness. (PDF contains 24 pages.)

Cruise Report 70-S-5: Big Game Fish

(PDF contains 4 pages)

Cruise Report 70-S-7: Big Game Fisheries Investigations

(PDF contains 3 pages.)

Cruise Report 72-S-1: Big Game Fisheries Investigations

(PDF contains 5 pages.)

Cruise Report 72-S-4: Big Game Fish Investigations

(PDF contains 2 pages.)

Adaptive response of Peruvian Hake to overfishing

Compensatory mechanisms of the Peruvian hake population (Merluccius gayi peruanus) in response to heavy exploitation and changes in species interaction are discussed. Changes in the rate of cannibalism, diet composition, maximization of fecundity and behavioral adaptation are noted.

Blue Marlin, Makaira nigricans, Movements in the Western North Atlantic Ocean: Results of a Cooperative Game Fish Tagging Program, 1954-88

Blue marlin, Makaira nigricans, tag and recapture data are summarized for 1954-1988. During this period, 8,447 fish have been tagged and only 30 (0.35 percent) have been returned. Results of the tagging program indicate that blue marlin not only travel considerable distances (7,OOO km from the U. S. Virgin Islands to the Ivory Coast of West Africa), but have remained at large for up to 8 years. Seasonal movements, however, are difficult to determine accurately.

Training workshop proceedings: adaptive co-management of fisheries (January 21-25, Boyboison Lodge, Fijai, Ghana)

The Adaptive Collaborative Management of Fisheries Training workshop was held in Sekondi, Western Region of Ghana as part of the project “Integrated Coastal and Fisheries Governance Initiative” locally referred to as “H n Mpoano”. The aim of the project is to support the government of Ghana achieve its development objective of poverty reduction, food security, sustainable fisheries management and biodiversity conservation and contributes to its vision: Ghana’s coastal and marine ecosystems are sustainably managed to provide goods and services that generate long-term socioeconomic benefit to communities while sustaining biodiversity.

Applications in adaptive cluster sampling of Gulf of Alaska rockfish

Adaptive cluster sampling (ACS) has been the subject of many publications about sampling aggregated populations. Choosing the criterion value that invokes ACS remains problematic. We address this problem using data from a June 1999 ACS survey for rockfish, specifically for Pacific ocean perch (Sebastes alutus), and for shortraker (S. borealis) and rougheye (S. aleutianus) rockfish combined. Our hypotheses were that ACS would outperform simple random sampling (SRS) for S. alutus and would be more applicable for S. alutus than for S. borealis and S. aleutianus combined because populations of S. alutus are thought to be more aggregated. Three alternatives for choosing a criterion value were investigated. We chose the strategy that yielded the lowest criterion value and simulated the higher criterion values with the data after the survey. Systematic random sampling was conducted across the whole area to determine the lowest criterion value, and then a new systematic random sample was taken with adaptive sampling around each tow that exceeded the fixed criterion value. ACS yielded gains in precision (SE) over SRS. Bootstrapping showed that the distribution of an ACS estimator is approximately normal, whereas the SRS sampling distribution is skewed and bimodal. Simulation showed that a higher criterion value results in substantially less adaptive sampling with little tradeoff in precision. When time-efficiency was examined, ACS quickly added more samples, but sampling edge units caused this efficiency to be lessened, and the gain in efficiency did not measurably affect our conclusions. ACS for S. alutus should be incorporated with a fixed criterion value equal to the top quartile of previously collected survey data. The second hypothesis was confirmed because ACS did not prove to be more effective for S. borealis-S. aleutianus. Overall, our ACS results were not as optimistic as those previously published in the literature, and indicate the need for further study of this sampling method.