Ranking and classification of fishing areas using fuzzy models and techniques

Abstract Fuzzy‐logic‐based methods and fuzzy logic formalism have been demonstrated as appropriate to address the uncertainty and subjectivity in complex environmental problems. This study investigates the use of three fuzzy logic methods in fisheries analysis, aiming towards the grouping and ranking of fishing subareas, according to their fisheries yield. Initially, a simple fuzzy c‐means clustering model was applied to the fishing subareas examined. A rule‐based Mamdani‐type fuzzy inference system was then developed to allow the direct fishing subarea classification. Finally, a species‐economic value weighted global fuzzy membership model was introduced, serving as an indirect classification and ranking scheme. Global memberships were plotted on simple ternary diagrams, producing representations that serve as tools in fisheries management. All methods examined the performance of the Greek fishing subareas, based on the annual landings series of the 10 most abundant fish species in terms of landed biomass, during the period 1985–1999.     

Attending to spatial social–ecological sensitivities to improve trade‐off analysis in natural resource management

Balancing trade‐offs amongst social–ecological objectives is a central aim of natural resource management. However, objectives and resources often have spatial dimensions, which are usually ignored in trade‐off analyses. We examine how simultaneously integrating social–ecological benefits and their spatial complexities can improve trade‐off analysis. We use Pacific herring (Clupea pallasii, Clupeidae)—an ecologically important forage fish with social, cultural and economic value to communities and commercial fisheries—as a case study. By combining spatial management strategy evaluation with social benefits analysis, we illustrate when policies aimed at aggregate stocks versus spatially segregated substocks of fish fail to balance trade‐offs amongst social–ecological objectives. Spatial measures (e.g. area‐based closures) may achieve some objectives but produce alternative trade‐offs that are sensitive to assumptions about fish population dynamics and social complexities. Our analyses identify policies that are inefficient (e.g. yielding economic costs without producing social or ecological gains), highlight management strategies that generate trade‐offs and indicate when costs are distributed unequally for different user groups. We also point to strategies with outcomes that are robust to spatial uncertainties and reveal research priorities by identifying which performance metrics exhibit sensitivity to spatial ecological assumptions. Collectively, our analyses demonstrate how incorporating social objectives and spatial dynamics into management strategy evaluation can reveal trade‐offs and the implications of management decisions.     

Managing non‐native fish in the environment

Non‐native fishes are frequently used to enhance aquaculture and fisheries; if introduced into the wider environment, then the majority will have negligible effects on native biodiversity. However, a minority will become invasive, causing adverse ecological effects, and so management actions may be needed to minimize their dispersal and impacts. These actions include eradication attempts from specific waters or well‐defined spatial areas, population control by suppression (e.g. through removal programmes) and containment of existing populations to prevent their further spread. These remedial actions have generally only been undertaken across large spatial areas in developed countries; experience suggests a fundamental constraint is a lack of selective removal methods that target the non‐native fish species only. For example, eradication methods tend to be limited to low technology, ‘scorched‐earth’ techniques (e.g. biocide chemicals) whose use is generally constrained to relatively small and enclosed water bodies. Risk management of non‐native fishes should ensure that actions taken are commensurate with the level of risk posed by that species in the environment; although pre‐introduction risk assessment schemes have been developed, there remains a lack of decision support tools for post‐introduction situations. Although this inhibits the management of non‐native fishes in the environment, control programmes such as those against common carp Cyprinus carpio in Australia and topmouth gudgeon Pseudorasbora parva in England and Wales suggest there is potential for invasions to be managed and controlled within large spatial areas, even if their eradication may not be feasible.     

The pelagic habitat analysis module for ecosystem‐based fisheries science and management

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.     

Assessment and prediction of water quality in shrimp culture using signal processing techniques

In recent years, artificial intelligence methods have proved appropriate for the treatment of environmental problems. This paper presents a novel work for the assessment and prediction of water quality in shrimp aquaculture based on environmental pattern processing. Water quality studies are based on analyzing negative concentrations of compounds in shrimp ponds that inhibit good growth and reproduction of organisms. The physical–chemical variables are classified based on the negative ecological impact using the Gamma (Γ) classifier, which calculates the frequency and deviation of the measurements from a specific level. A fuzzy inference system processes the level classifications using a reasoning process that determines when a specific concentration is good or harmful for the organism and provides a water quality index, which describes the condition of the ecosystem: excellent, good, regular, and poor. An autoregressive model (AR) predicts a section of an environmental signal using historical information, and the set of predicted variables are assessed in order to estimate future water quality conditions in the system. This methodology emerges as a suitable and alternative tool to be used in developing effective water management plans.     

Population‐level consequences for wild fish exposed to sublethal concentrations of chemicals – a critical review

Concentrated chemical spills have been shown to impact adversely on fish populations and even cause localized population extinctions. Evaluating population‐level impacts of sublethal exposure concentrations is, however, complex and confounded by other environmental pressures. Applying effect measures derived from laboratory‐based chemical exposures to impacts in wild fish populations is constrained by uncertainty on how biochemical response measures (biomarkers) translate into health outcomes, lack of available data for chronic exposures and the many uncertainties in available fish population models. Furthermore, wild fish show phenotypic plasticity and local adaptations can occur that adds geographic and temporal variance on responses. Such population‐level factors are rarely considered in the chemical risk assessment process and can probably be derived only from studies on wild fish. Molecular technologies, including microsatellite and SNP genotyping, and RNASeq for gene expression studies, are advancing our understanding of mechanisms of eco‐toxicological response, tolerance, adaptation and selection in wild populations. We examine critically the application of such approaches with examples including using microsatellites that has identified roach (Rutilus rutilus) populations living in rivers contaminated with sewage effluents that are self‐sustaining, and studies of stickleback (Gasterosteus aculeatus) and killifish (Fundulus heteroclitus) that have identified genomic regions under selection putatively related to pollution tolerance. Integrating data on biological effects between laboratory‐based studies and wild populations, and building understanding on adaptive responses to sublethal exposure are some of the priority research areas for more effective evaluation of population risks and resilience to contaminant exposure.     

Classification and assessment of degradation in European running waters

Abstract  A pan-European, classification of the extent of environmental degradation from chemical, physical and biological pressures on fish communities as a precursor to assess the ecological status of running waters based on fish is proposed. Twenty-four potential pressures acting on fish communities at three different spatial scales (river basin, segment and site) were identified and class boundaries for high, good, moderate, poor and bad status, based on existing data and/or expert judgement, were defined. Four pressures (hydrological regime, morphological conditions, toxic or acid conditions, nutrients and organic load) were found to describe the majority of degradation at a specific site and these were combined into a single pressure variable to describe impact at each location. Principal Component Analysis showed that the four variables were correlated with other physical and chemical variables not included in the combined pressure variable. However, biological pressures, e.g. introduction of fish, and longitudinal connectivity were not well correlated, suggesting that two dimensions of human impact on stream fish were poorly accounted for. Low-resolution Geographical Information Systems (GIS) data (1 km grid) on land use and population density correlated well with the four chosen pressures, suggesting it is possible to use standardised GIS data to aid pre-classification of stream degradation.     

A review of ecological models for brown trout: towards a new demogenetic model

Abstract – Ecological models for stream fish range in scale from individual fish to entire populations. They have been used to assess habitat quality and to predict the demographic and genetic responses to management or disturbance. In this paper, we conduct the first comprehensive review and synthesis of the vast body of modelling literature on the brown trout, Salmo trutta L., with the aim of developing the framework for a demogenetic model, i.e., a model integrating both population dynamics and genetics. We use a bibliometric literature review to identify two main categories of models: population ecology (including population dynamics and population genetics) and population distribution (including habitat–hydraulic and spatial distribution). We assess how these models have previously been applied to stream fish, particularly brown trout, and how recent models have begun to integrate them to address two key management and conservation questions: (i) How can we predict fish population responses to management intervention? and (ii) How is the genetic structure of fish populations influenced by landscape characteristics? Because salmonid populations tend to show watershed scale variation in both demographic and genetic traits, we propose that models combining demographic, genetic and spatial data are promising tools for improving their management and conservation. We conclude with a framework for an individual‐based, spatially explicit demogenetic model that we will apply to stream‐dwelling brown trout populations in the near future.     

Influences of local habitat and stream spatial position on fish assemblages in a dammed watershed,the Qingyi Stream,China

Abstract – Identifying the underlying mechanisms that explain the spatial variation in stream fish assemblages is crucial for the protection of species diversity. The influences of local habitat and stream spatial position on fish assemblages were examined from first‐order through third‐order streams within a dammed watershed, the Qingyi Stream, China. Based on linear regression models, the most important environmental variables influencing fish species richness were water temperature and wetted width, but stream spatial position variables were less important. Using canonical correspondence analysis, five environmental variables were identified to significantly influence fish assemblages, including three habitats (elevation, substrate and water depth) and two spatial variables (C‐link and Link). Our results suggest that, in a heavily dammed watershed, by blocking the migration routes of fishes, dams weaken the influence of stream spatial position on fish species richness. However, fish species compositions are significantly influenced by both local habitat environment and stream spatial position, which is perhaps owing to the distribution of fish species according to ecological requirements not related to spatial processes.     

Review on European sea bass (Dicentrarchus labrax,Linnaeus, 1758) nutrition and feed management: a practical guide for optimizing feed formulation and farming protocols

As increasing amounts of novel raw materials are used in aquafeed production, it is important to measure their quality against existing ingredients and their effects upon production strategies. A first step to achieving this goal begins with an improved understanding of the underlying growth potential of each farmed species across a range of dietary ingredients and farming practices. Species‐specific physiological limitations and metabolic effects of both single chemicals and complex chemical matrixes are factors to be considered in producing robust fish and a healthy aquaculture sector. The industry must also consider ethical, environmental and economic issues and optimize feed management practices. This review summarizes current knowledge on European sea bass (Dicentrarchus labrax) nutritional requirements, presents current feed management practices for this species, gives insights on a secure framework for using plant ingredients in exchange for traditional marine raw materials and outlines its growth potential through a meta‐analysis of the best‐performance results available in peer‐reviewed scientific publications for this species. As the best‐performing fish were mostly those fed high fish meal fish oil control diets, the summarized results have the potential to be used as a quality control for benchmarking future scientific research in this fish species.