The rise and fall of the Irish orange roughy fishery: An economic analysis

An Irish commercial fishery for orange roughy began in the Northeast Atlantic in 2001 with the assistance of government grants. The fishery began as an open access, non-quota fishery. The rapid boom and bust of many deep water fisheries was experienced. Landings peaked in 2002 and then dropped significantly the following year. Many vessels were forced out of the fishery due to high costs and rapidly declining stocks. By 2005 the fishery was largely closed. Applying a bioeconomic analysis, this paper shows why the fishery no longer exists and discusses both the external and opportunity costs of the fishery. A bioeconomic model is applied to the available data to assess the open access effort and harvest with and without government grant aid. The results suggest that in the absence of subsidies, deep water trawling would not have been viable. In addition to the financial costs such as high fuel consumption, there are also externalities associated with deep water trawling. Orange roughy is closely associated with deep water ecosystems such as seamounts and cold water corals. This paper examines the costs of damage to cold water corals. These costs include the loss of fish habitats and lost future use and preservation values.     

Why do certain species dominate? What we can learn from a rare case of Microdictyon dominance on a Caribbean reef

Many Caribbean reefs have shifted from coral dominance to macroalgal dominance, often by brown algae such as Dictyota and Lobophora. However, the north side of Cayman Brac in the Cayman Islands is dominated seasonally by the green macroalga Microdictyon (percent cover of Microdictyon is 4% in the winter and ~40% of the reef in the summer), although it is absent from the south side of the island and the remainder of the country. Indeed, Microdictyon is rare in much of the Caribbean, so this situation on Cayman Brac provides an opportunity to investigate the conditions that facilitate its distribution and dominance. The impact of herbivory, competition, nutrient input and other abiotic conditions were examined as factors that could influence the distribution and dominance of Microdictyon. While herbivory or nutrient input are frequently found to be key drivers of benthic community composition on coral reefs, here consumption of Microdictyon by herbivores was low, and thus, the alga was not subject to strong top-down control by herbivory. So, in this case, neither herbivore abundance nor feeding preference appeared to influence the distribution of Microdictyon. Nutrient input was also similar to both sides of the island suggesting nutrients played little role in differential distribution. But, in a controlled transplant experiment where Microdictyon was protected from herbivory and competition, it experienced almost complete mortality (93.3%) when transplanted to the south side, compared to only 11.8% mortality on the north. The south side was exposed to the strongest wave action 92% of the days in our study and was on average a slight, but significant 0.2°C warmer. Thus, these data suggest physical forcing (i.e. wave exposure) is the most likely factor dictating Microdictyon distribution. Conversely, a combination of reduced herbivory and increased competitive strength may explain the seasonal dominance of Microdictyon on the north side of Cayman Brac. Microdictyon was a competitive inferior to the other common algae in winter but increased in competitive strength to equal other species in summer. These results add to the literature on Microdictyon and on the forces impacting benthic community structure of coral reefs.     

The changing environment of fisheries policy in Europe

This paper presents how environmental concerns emanating outside the Common Fisheries Policy (CFP) are increasingly setting the stage for EU fisheries management. This is illustrated via what is termed the exogenous entrance of environmental concerns through the implementation of directives in EU policy. More endogenous entrance of environmental concerns occurs via stakeholder participation in Regional Advisory Councils (RACs) as well as market mechanisms, such as ecolabelling and traceability. This study discusses how these latter channels of environmental concern may have become a more potent and efficient way of reaching environmental goals, outside of the primacy of the CFP.     

Winds and tides of Ligeia Mare,with application to the drift of the proposed time TiME (Titan Mare Explorer) capsule

We use two independent General Circulation Models (GCMs) to estimate surface winds at Titan’s Ligeia Mare (78° N, 250° W), motivated by a proposed mission to land a floating capsule in this ～500 km hydrocarbon sea. The models agree on the overall magnitude (～0.5–1 m/s) and seasonal variation (strongest in summer) of windspeeds, but details of seasonal and diurnal variation of windspeed and direction differ somewhat, with the role of surface exchanges being more significant than that of gravitational tides in the atmosphere. We also investigate the tidal dynamics in the sea using a numerical ocean dynamics model: assuming a rigid lithosphere, the tidal amplitude is up to ～0.8 m. Tidal currents are overall proportional to the reciprocal of depth—with an assumed central depth of 300 m, the characteristic tidal currents are ～1 cm/s, with notable motions being a slosh between Ligeia’s eastern and western lobes, and a clockwise flow pattern.We find that a capsule will drift at approximately one tenth of the windspeed, unless measures are adopted to augment the drag areas above or below the waterline. Thus motion of a floating capsule is dominated by the wind, and is likely to be several km per Earth day, a rate that will be readily measured from Earth by radio navigation methods. In some instances, the wind vector rotates diurnally such that the drift trajectory is epicyclic.     

Dangers of multiyear averaging in analyses of long-term climate trends

Multiyear averaging in studies seeking long-term trends can be risky and misleading. It is shown here that a change of 1 year in the starting point of the averaging done in generating a multiyear-average sequence can make a dramatic difference in the appearance of the sequence, even including whether the apparent trend is upward or downward. An example is given in which the same time series, when grouped to 3-year averages by starting in turn at the first, second, and third points of the series, yields one 3-year-average sequence that is monotonically increasing, a second 3-year-average sequence that is monotonically decreasing, and a third 3-year-average sequence that has constant values. Furthermore, it is proven in general that such series can be created for n-year averages for any integer n > 2, and can be extended to exceed any desired length. Finally, historical sea-ice data from Iceland are used to illustrate with a long-term climate data set the misrepresentation of climate statistics which can occur through selective multiyear averaging.     

Infometric and statistical diagnostics to provide artificially-intelligent support for spatial analysis: the example of interpolation

The wider uptake of GIS tools by many application areas outside GIScience means that many newer users of GIS will have high-level knowledge of the wider task, and low-level knowledge of specific system commands as given in reference manuals. However, these newer users may not have the intermediate knowledge that experts in GI science have gained from working with GI systems over several years. Such intermediate knowledge includes an understanding of the assumptions implied by the use of certain functions, and an appreciation of how to combine functions appropriately to create a workflow that suits both the data and overall goals of the geographical analysis task.

Focusing on the common but non-trivial task of interpolating spatial data, this paper considers how to help users gain the necessary knowledge to complete their task and minimise the possibility of methodological error. We observe that both infometric (or cognitive) knowledge and statistical knowledge are usually required to find a solution that jointly and efficiently meets the requirements of a particular user and data set. Using the class of interpolation methods as an example, we outline an approach that combines knowledge from multiple sources and argue the case for designing a prototype ‘intelligent’ module that can sit between a user and a given GIS.

The knowledge needed to assist with the task of interpolation is constructed as a network of rules, structured as a binary decision tree, that assist the user in selecting an appropriate method according to task-related knowledge (or ‘purpose’) and the characteristics of the data sets. The decision tree triggers exploratory diagnostics that are run on the data sets when a rule requires to be evaluated. Following evaluation of the rules, the user is advised which interpolation method might be and should not be considered for the data set. Any parameters required to interpolate the particular data set (e.g. a distance decay parameter for Inverse Distance Weighting) are also supplied through subsequent optimisation and model selection routines. The rationale of the decision process may be examined, so the ‘intelligent interpolator’ also acts as a learning tool.