An ecological correction to marine reserves boundaries in the US Virgin Islands

Marine protected areas (MPAs) are important tools for management of marine ecosystems. While desired, ecological and biological criteria are not always feasible to consider when establishing protected areas. In 2001, the Virgin Islands Coral Reef National Monument (VICR) in St. John, US Virgin Islands was established by Executive Order. VICR boundaries were based on administrative determination of Territorial Sea boundaries and land ownership at the time of the Territorial Submerged Lands Act of 1974. VICR prohibits almost all fishing and other extractive uses. Surveys of habitat and fishes inside and outside of VICR were conducted in 2002-07. Based on these surveys, areas outside VICR had significantly more hard corals; greater habitat complexity; and greater richness, abundance and biomass of reef fishes than areas within VICR, further supporting results from 2002-2004 (Monaco et al., 2007). The administrative (political) process used to establish VICR did not allow a robust ecological characterization of the area to determine the boundaries of the MPA. Efforts are underway to increase amounts of complex reef habitat within VICR by swapping a part of VICR that has little coral reef habitat for a Territorially-owned area within VICR that contains a coral reef with higher coral cover.

A method to improve size estimates of walleye pollock (Theragra chalcogramma) Atka mackerel (Pleurogrammus monopterygius) consumed by pinnipeds: digestion correction factors applied to bones and otoliths recovered in scats

The lengths of otoliths and other skeletal structures recovered from the scats of pinnipeds, such as Steller sea lions (Eumetopias jubatus), correlate with body size and can be used to estimate the length of prey consumed. Unfortunately, otoliths are often found in too few scats or are too digested to usefully estimate prey size. Alternative diagnostic bones are frequently recovered, but few bone-size to prey-size correlations exist and bones are also reduced in size by various degrees owing to digestion. To prevent underestimates in prey sizes consumed techniques are required to account for the degree of digestion of alternative bones prior to estimating prey size. We developed a method (using defined criteria and photo-reference material) to assign the degree of digestion for key cranial structures of two prey species: walleye pollock (Theragra chalcogramma) and Atka mackerel (Pleurogrammus monopterygius). The method grades each structure into one of three condition categories; good, fair or poor. We also conducted feeding trials with captive Steller sea lions, feeding both fish species to determine the extent of erosion of each structure and to derive condition-specific digestion correction factors to reconstruct the original sizes of the structures consumed. In general, larger structures were relatively more digested than smaller ones. Mean size reduction varied between different types of structures (3.3−26.3%), but was not influenced by the size of the prey consumed. Results from the observations and experiments were combined to be able to reconstruct the size of prey consumed by sea lions and other pinnipeds. The proposed method has four steps: 1) measure the recovered structures and grade the extent of digestion by using defined criteria and photo-reference collection; 2) exclude structures graded in poor condition; 3) multiply measurements of structures in good and fair condition by their appropriate digestion correction factors to derive their original size; and 4) calculate the size of prey from allometric regressions relating corrected structure measurements to body lengths. This technique can be readily applied to piscivore dietary studies that use hard remains of fish.

The measurement error in marine survey catches: the bottom trawl case

We have formulated a model for analyzing the measurement error in marine survey abundance estimates by using data from parallel surveys (trawl haul or acoustic measurement). The measurement error is defined as the component of the variability that cannot be explained by covariates such as temperature, depth, bottom type, etc. The method presented is general, but we concentrate on bottom trawl catches of cod (Gadus morhua). Catches of cod from 10 parallel trawling experiments in the Barents Sea with a total of 130 paired hauls were used to estimate the measurement error in trawl hauls. Based on the experimental data, the measurement error is fairly constant in size on the logarithmic scale and is independent of location, time, and fish density. Compared with the total variability of the winter and autumn surveys in the Barents Sea, the measurement error is small (approximately 2–5%, on the log scale, in terms of variance of catch per towed distance). Thus, the cod catch rate is a fairly precise measure of fish density at a given site at a given time.

Probabilistic fault identification using vibration data and neural networks

Bayesian formulated neural networks are implemented using hybrid Monte Carlo method for probabilistic fault identification in cylindrical shells. Each of the 20 nominally identical cylindrical shells is divided into three substructures. Holes of (12±2) mm in diameter are introduced in each of the substructures and vibration data are measured. Modal properties and the Coordinate Modal Assurance Criterion (COMAC) are utilized to train the two modal-property-neural-networks. These COMAC are calculated by taking the natural-frequency-vector to be an additional mode. Modal energies are calculated by determining the integrals of the real and imaginary components of the frequency response functions over bandwidths of 12% of the natural frequencies. The modal energies and the Coordinate Modal Energy Assurance Criterion (COMEAC) are used to train the two frequency-response-function-neural-networks. The averages of the two sets of trained-networks (COMAC and COMEAC as well as modal properties and modal energies) form two committees of networks. The COMEAC and the COMAC are found to be better identification data than using modal properties and modal energies directly. The committee approach is observed to give lower standard deviations than the individual methods. The main advantage of the Bayesian formulation is that it gives identities of damage and their respective confidence intervals.

Towards probabilistic performance metrics for climate change impact studies

This paper explores the current state-of-the-art in performance indicators and use of probabilistic approaches used in climate change impact studies. It presents a critical review of recent publications in this field, focussing on (1) metrics for energy use for heating and cooling, emissions, overheating and high-level performance aspects, and (2) uptake of uncertainty and risk analysis. This is followed by a case study, which is used to explore some of the contextual issues around the broader uptake of climate change impact studies in practice. The work concludes that probabilistic predictions of the impact of climate change are feasible, but only based on strict and explicitly stated assumptions. © 2011 Elsevier B.V. All rights reserved.