Swanside Beck, fisheries survey, 22nd September 1992

Swanside Beck is formed from a number of minor tributaries which rise in the Middop area to the west of Barnoldswick. The Beck is approximately 10 km long from the source of its longest tributary (SD. 850445) to the confluence with the River Ribble (SD. 769455). Swanside Beck has one major tributary, Ings Beck, which rises from a number of sources on Twiston Moor and is approximately 6km in length from the source of its longest tributary (SD. 812418) to the confluence with Swanside Beck (SD. 785453). Both Swanside and Ings Becks are important spawning and nursery areas for salmon and sea trout from the River Ribble. In recent years a perceived decline in the migratory fish population of the becks has been reported. This decline has been reported in terms of both adult returns and juvenile production and has been particularly noted in Swanside Beck. The aim of this survey was to assess the likely benefits to Fisheries and Conservation interests of the adoption of a set aside policy for agricultural land adjacent to Swanside Beck. The survey also formed part of an on-going Fisheries study of factors limiting juvenile migratory salmonid production in Swanside Beck. This section of the report deals with the Fisheries aspects of the survey.

Invasionsoft: a web-enabled tool for invasive species colonization predictions

Predicting and averting the spread of invasive species is a core focus of resource managers in all ecosystems. Patterns of invasion are difficult to forecast, compounded by a lack of user-friendly species distribution model (SDM) tools to help managers focus control efforts. This paper presents a web-based cellular automata hybrid modeling tool developed to study the invasion pattern of lionfish (Pterois volitans/miles) in the western Atlantic and is a natural extension our previous lionfish study. Our goal is to make publically available this hybrid SDM tool and demonstrate both a test case (P. volitans/miles) and a use case (Caulerpa taxifolia). The software derived from the model, titled Invasionsoft, is unique in its ability to examine multiple default or user-defined parameters, their relation to invasion patterns, and is presented in a rich web browser-based GUI with integrated results viewer. The beta version is not species-specific and includes a default parameter set that is tailored to the marine habitat. Invasionsoft is provided as copyright protected freeware at http://www.invasionsoft.com.

Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii

The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors potentially influence their spatial distribution, including aragonite saturation, alkalinity, pH, currents, water temperature, hard substrate availability and the availability of light at depth. Mesophotic corals and mesophotic coral ecosystems (MCEs) have increasingly been the subject of scientific study because they are being threatened by a growing number of anthropogenic stressors. They are the focus of this spatial modeling effort because the Hawaiian Islands Humpback Whale National Marine Sanctuary (HIHWNMS) is exploring the expansion of its scope—beyond the protection of the North Pacific Humpback Whale (Megaptera novaeangliae)—to include the conservation and management of these ecosystem components. The present study helps to address this need by examining the distribution of mesophotic corals in the Au‘au Channel region. This area is located between the islands of Maui, Lanai, Molokai and Kahoolawe, and includes parts of the Kealaikahiki, Alalākeiki and Kalohi Channels. It is unique, not only in terms of its geology, but also in terms of its physical oceanography and local weather patterns. Several physical conditions make it an ideal place for mesophotic hard corals, including consistently good water quality and clarity because it is flushed by tidal currents semi-diurnally; it has low amounts of rainfall and sediment run-off from the nearby land; and it is largely protected from seasonally strong wind and wave energy. Combined, these oceanographic and weather conditions create patches of comparatively warm, calm, clear waters that remain relatively stable through time. Freely available Maximum Entropy modeling software (MaxEnt 3.3.3e) was used to create four separate maps of predicted habitat suitability for: (1) all mesophotic hard corals combined, (2) Leptoseris, (3) Montipora and (4) Porites genera. MaxEnt works by analyzing the distribution of environmental variables where species are present, so it can find other areas that meet all of the same environmental constraints. Several steps (Figure 0.1) were required to produce and validate four ensemble predictive models (i.e., models with 10 replicates each). Approximately 2,000 georeferenced records containing information about mesophotic coral occurrence and 34 environmental predictors describing the seafloor’s depth, vertical structure, available light, surface temperature, currents and distance from shoreline at three spatial scales were used to train MaxEnt. Fifty percent of the 1,989 records were randomly chosen and set aside to assess each model replicate’s performance using Receiver Operating Characteristic (ROC), Area Under the Curve (AUC) values. An additional 1,646 records were also randomly chosen and set aside to independently assess the predictive accuracy of the four ensemble models. Suitability thresholds for these models (denoting where corals were predicted to be present/absent) were chosen by finding where the maximum number of correctly predicted presence and absence records intersected on each ROC curve. Permutation importance and jackknife analysis were used to quantify the contribution of each environmental variable to the four ensemble models.

Reported Trip Costs, Gross Revenues, and Net Returns for U.S. Atlantic Pelagic Longline Vessels

Logbook set and trip summary data (containing catch and cost information, respectively) collected by NOAA’s National Marine Fisheries Service (NMFS) were analyzed for U.S. pelagic longline vessels that participated in Atlantic fisheries in 1996. These data were augmented with vessel information from the U.S. Coast Guard. Mean fish weights and ex-vessel prices from NMFS observers and licensed seafood dealers, respectively, were used to estimate gross revenues. Comparisons revealed that net returns varied substantially by vessel size and fishing behavior (i.e. sets per trip, fishing location, season, and swordfish targeting). While the calculated economic effects of proposed regulations will depend on the descriptive statistic chosen for analysis, which itself depends on the type of analysis being conducted, results show that considering heterogeneity within this fleet can have a significant effect on predicted economic consequences.