Limitations of the Korean conventional fisheries management regime and expanding Korean TAC system toward output control systems

In this paper, we focus on the status and trends of the current Korean fisheries management regime. Specifically, this paper briefly introduces the Korean conventional fisheries management regime (KCFMR) and discusses its problems and limitations. In describing policy evolution, this paper finds reasons why the Korean government has chosen a TAC system, an output control approach, besides input control approaches in force for almost a century. This paper also describes the evolution of the Korean TAC system, which is carrying out a pivotal role in Korean fisheries development, and analyzes problems of the Korean TAC system. Finally, this paper gives a perspective on expanding the Korean TAC system toward Output Control Systems (OCSs) such as Individual Quotas (IQs), Individual Vessel Quotas (IVQs), Individual Transferable Traps (ITTs), Community Quotas (CQs), and Individual Transferable Quotas (ITQs).     

Results from a Multi-disciplinary Sedimentary Pilot Study of Tectonic Lake Iznik (NW Turkey) – Geochemistry and Paleolimnology of the Recent Past

A limnogeological reconnaissance study was carried out on Lake Iznik, located in the southeast of the Marmara region of Turkey, involving a seismic survey and collection of short sediment cores. This lake is located on the middle branch of the North Anatolian Fault Zone (NAFZ), a transform plate boundary between the Eurasian and Anatolian Plates. It is, therefore, tectonically active and offers an opportunity to investigate the interplay of sedimentary and seismo-tectonic processes, as well as climate change and human impact in the region. Short cores of the three sub-basins, maximum length of 35.5 cm, recovered non-laminated, blackish clays and silts with varying amounts of biogenic and minerogenic (allochthonous, autochthonous) material, which documented almost the last 80 years of deposition and environmental history. High sedimentation rates in the deeper core sections are accompanied by changes in land use (conversion of woodland to farmland) in the northern areas of Lake Iznik, which caused the deposition of more weathered material (high K/Na ratios) and higher contents of Mn in the lake. A tendency towards eutrophic conditions within the last 20 years is indicated by high nutrient content (N, TOC, P), decreasing C/N-ratios, and characteristic diatom and cladoceran associations. Also increased pollution is revealed by higher Pb, Cu, and Zn contents and increased supply of human and animal faeces (high coprostanol content) during the last two decades. But simultaneous lower sedimentation rates towards the core tops complicate the reconstruction of recent and past eutrophication and pollution states of Lake Iznik. This requires an extension of the pilot study and deeper sediment cores, to recover non-anthropogenic influenced sediment levels.     

Wave velocities and attenuation of shaley sandstones as a function of pore pressure and partial saturation

We obtain the wave velocities and quality factors of clay‐bearing sandstones as a function of pore pressure, frequency and partial saturation. The model is based on a Biot‐type three‐phase theory that considers the coexistence of two solids (sand grains and clay particles) and a fluid mixture. Additional attenuation is described with the constant‐Q model and viscodynamic functions to model the high‐frequency behaviour. We apply a uniform gas/fluid mixing law that satisfies the Wood and Voigt averages at low and high frequencies, respectively. Pressure effects are accounted for by using an effective stress law. By fitting a permeability model of the Kozeny– Carman type to core data, the model is able to predict wave velocity and attenuation from seismic to ultrasonic frequencies, including the effects of partial saturation. Testing of the model with laboratory data shows good agreement between predictions and measurements.     

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

A study of coral reef resilience and implications of adaptive management and rehabilitation in Khanh Hoa Province, Vietnam

The Province of Khanh Hoa, Vietnam, is located in the western South China Sea and boasts a shoreline of 385 km and many islands. Previous studies have indicated the extreme diversity and abundance of coral reefs in its waters as compared with other coastal provinces of Vietnam. A study on the resilience of coral reefs against increased surface water temperature and anthropogenic impact is conducted at 19 reef sites in 2015. At each site, a series of parameters (e.g., coral covers, genus diversity, and coral recruitment, substratum heterogeneity, depth, water exchange level, and sediment deposit and water temperature) are measured quantitatively or semi-quantitatively. The measured data are rated based on the relationship between the parameter values and coral susceptibility; the consideration that reef health reflects the biological capability to adapt to environmental changes and the recruitment potential if bleached; and positive or negative influences of physical factors in the mitigation of thermal stress and protecting corals from bleaching. A cumulative analysis enables researchers to divide the studied reefs into four categories based on varying levels of reef health to support resilience, recovery, and vulnerability in the case of increased water temperature. Relevant management interventions for each category and other supporting activities are suggested to enhance management effectiveness and to plan the rehabilitation of coral reefs for biodiversity conservation and touristic development, taking into account the involvement of related stakeholders.     

Prediction of Rock Size Distribution in Mine Bench Blasting Using a Novel Ant Colony Optimization-Based Boosted Regression Tree Technique

Natural Resources Research - In this paper, we used artificial intelligence (AI) techniques to investigate the relation between the rock size distribution (RSD) and blasting parameters for rock...