ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

<p>Abstract</p> <p>Background</p> <p>Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability.</p> <p>Methods</p> <p>Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications <it>in silico </it>using simulated datasets.</p> <p>Results</p> <p>We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage.</p> <p>Conclusions</p> <p>We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait.</p

Adaptive behaviour of fishers to external perturbations: simulation of the Tasmanian rock lobster fishery

The rock lobster, Jasus edwardsii, lies on a global “hotspot” for climate change in the southeastern Australian state of Tasmania. The short-term effects of climate change are predicted to lead to an increasing exploitable biomass in the south and declining biomass in the north of the state. The future of the fishery is highly uncertain due to climate change, but also due to insecurities linked to the market conditions. The market for Tasmanian rock lobster is driven by the demand of a single market, China, which absorbs 75 % of the catch. This study examines how fishers can adapt to external perturbations that affect the social and economic viability of the fleet and the ecological dynamics of the stock. Three fleet dynamic models of increasing complexity are used to investigate the effects of climate change and lobster price changes on the fishery. There could be local depletion leading to negative short-term profit for the fleet if it is static and the proportion of the total catch taken in each region of the fishery does not respond to climate-induced-changes. Better outcomes would occur if the fleet adapts dynamically to environmental conditions, and fishing effort follows stock abundance, which would counter-act the short-term effects of climate change. Only a model with explicit representation of economic drivers can fully capture the local economic and social impacts of large scale global perturbations

Thirty years of fleet dynamics modelling using discrete-choice models: what have we learned?

Anticipating fisher behaviour is necessary for successful fisheries management. Ofthe different concepts that have been developed to understand individual fisherbehaviour, random utility models (RUMs) have attracted considerable attention inthe past three decades, and more particularly so since the 2000s. This study aimedat summarizing and analysing the information gathered from RUMs used duringthe last three decades around the globe. A methodology has been developed tostandardize information across different studies and compare RUM results. Thestudies selected focused on fishing effort allocation. Six types of fisher behaviourdrivers were considered: the presence of other vessels in the same fishing area, tradition,expected revenue, species targeting, costs, and risk-taking. Analyses wereperformed using three separate linear modelling approaches to assess the extent towhich these different drivers impacted fisher behaviour in three fleet types: fleetsfishing for demersal species using active gears, fleets fishing for demersal speciesusing passive gears and fleets fishing for pelagic species. Fishers are attracted byhigher expected revenue, tradition, species targeting and presence of others, butavoid choices involving large costs. Results also suggest that fishers fishing fordemersal species using active gears are generally more influenced by past seasonal(long-term) patterns than by the most recent (short-term) information. Finally, thecomparison of expected revenue with other fisher behaviour drivers highlights thatdemersal fishing vessels are risk-averse and that tradition and species targetinginfluence fisher decisions more than expected revenue

Climate change and European Fisheries and Aquaculture: 'CERES' Project Synthesis Report

Under this backdrop of climate impacts and international and European policy developments, the CERES project (Climate Change and European Aquatic Resources) was funded under the EU Horizon 2020 programme from 2016 to 2020. CERES was designed to advance a cause-and-effect understanding of how climate change will influence European fish and shellfish resources and the economic activities depending on them. More than 150 scientists from 26 partner institutions in 15 countries participated in this four-year project. Partners included national research laboratories, universities as well as industry members from the aquaculture and fisheries sectors and additional stakeholders. Focusing on the most commercially-valuable fish and shellfish, the project increased our knowledge and developed tools needed for adaptation planning for European fisheries and aquaculture sectors in marine and inland waters to anticipated climate change. The project identified not only risks but also opportunities as well as uncertainties of climate change impacts, information needed to enhance the resilience and support the development of sustainable management and governance systems in these Blue Growth sectors. CERES integrated physical, social, ecological and economic analyses relevant to both European fisheries and aquaculture sectors . The program studied the most valuable species and groups and associated businesses across ‘Storylines’ highlighting sector- and region-specific research findings. CERES developed 24 Storylines to capture the high diversity of European regions (from marine to freshwaters and from high to low latitudes) and commercially important species (from pelagic to demersal fisheries and from the culture of fish (Figure 2). Whereas Storylines form separate, stand-alone products, the present report summarises CERES findings across Storylines to compare and contrast the potential severity of effects of climate change (from risks to potential opportunities) across European marine and freshwaters. This synthesis report includes national-level comparisons of climate vulnerability for both sectors as well as analyses of the potential climate change impacts on the interaction between fisheries and aquaculture

The MSY concept in a multi-objective fisheries environment - Lessons from the North Sea

One of the most important goals in current fisheries management is to maintain or restore stocks above levels that can produce the maximum sustainable yield (MSY). However, it may not be feasible to achieve MSY simultaneously for multiple species because of trade-offs that result from interactions between species, mixed fisheries and the multiple objectives of stakeholders. The premise in this study is that MSY is a concept that needs adaptation, not wholesale replacement. The approach chosen to identify trade-offs and stakeholder preferences involved a process of consulting and discussing options with stakeholders as well as scenario modelling with bio-economic and multi-species models. It is difficult to intuitively anticipate the consequences of complex trade-offs and it is also complicated to address them from a political point of view. However, scenario modelling showed that the current approach of treating each stock separately and ignoring trade-offs may result in unacceptable ecosystem, economic or social effects in North Sea fisheries. Setting FMSY as a management target without any flexibility for compromises may lead to disappointment for some of the stakeholders. To treat FMSY no longer as a point estimate but rather as a “Pretty Good Yield” within sustainable ranges was seen as a promising way forward to avoid unacceptable outcomes when trying to fish all stocks simultaneously at FMSY. This study gives insights on how inclusive governance can help to reach consensus in difficult political processes, and how science can be used to make informed decisions inside a multi-dimensional trade-off space

Adaptation options for marine industries and coastal communities using community structure and dynamics

Identifying effective adaptation strategies for coastal communities dependent on marine resources and impacted by climate change can be difficult due to the dynamic nature of marine ecosystems. The task is more difficult if current and predicted shifts in social and economic trends are considered. Information about social and economic change is often limited to qualitative data. A combination of qualitative and quantitative models provide the flexibility to allow the assessment of current and future ecological and socio-economic risks and can provide information on alternative adaptations. Here, we demonstrate how stakeholder input, qualitative models and Bayesian belief networks (BBNs) can provide semi-quantitative predictions, including uncertainty levels, for the assessment of climate and non-climate-driven change in a case study community. Issues are identified, including the need to increase the capacity of the community to cope with change. Adaptation strategies are identified that alter positive feedback cycles contributing to a continued decline in population, local employment and retail spending. For instance, the diversification of employment opportunities and the attraction of new residents of different ages would be beneficial in preventing further population decline. Some impacts of climate change can be combated through recreational bag or size limits and monitoring of popular range-shifted species that are currently unmanaged, to reduce the potential for excessive removal. Our results also demonstrate that combining BBNs and qualitative models can assist with the effective communication of information between stakeholders and researchers. Furthermore, the combination of techniques provides a dynamic, learning-based, semi-quantitative approach for the assessment of climate and socio-economic impacts and the identification of potential adaptation strategies

Measurement of labile Cu in soil using stable isotope dilution and isotope ratio analysis by ICP-MS

Isotope dilution is a useful technique to measure the labile metal pool, which is the amount of metal in soil in rapid equilibrium (<7 days) with the soil solution. This is normally performed by equilibrating soil with a metal isotope, and sampling the labile metal pool by using an extraction (E value), or by growing plants (L value). For Cu, this procedure is problematic for E values, and impossible for L values, due to the short half-life of the 64Cu radioisotope (12.4 h), which makes access and handling very difficult. We therefore developed a technique using enriched 65Cu stable isotope and measurement of 63Cu/65Cu ratios by quadrupole inductively coupled plasma mass spectrometry (ICP-MS) to measure labile pools of Cu in soils using E value techniques. Mass spectral interferences in detection of 63Cu/65Cu ratios in soil extracts were found to be minimal. Isotope ratios determined by quadrupole ICP-MS compared well to those determined by high-resolution (magnetic sector) ICP-MS. E values determined using the stable isotope technique compared well to those determined using the radioisotope for both uncontaminated and Cu-contaminated soils.Annette L. Nolan, Yibing Ma, Enzo Lombi and Mike J. McLaughli