2,659 research outputs found
Quantifying fisher responses to environmental and regulatory dynamics in marine systems
Thesis (Ph.D.) University of Alaska Fairbanks, 2017Commercial fisheries are part of an inherently complicated cycle. As fishers have adopted new technologies and larger vessels to compete for resources, fisheries managers have adapted regulatory structures to sustain stocks and to mitigate unintended impacts of fishing (e.g., bycatch). Meanwhile, the ecosystems that are targeted by fishers are affected by a changing climate, which in turn forces fishers to further adapt, and subsequently, will require regulations to be updated. From the management side, one of the great limitations for understanding how changes in fishery environments or regulations impact fishers has been a lack of sufficient data for resolving their behaviors. In some fisheries, observer programs have provided sufficient data for monitoring the dynamics of fishing fleets, but these programs are expensive and often do not cover every trip or vessel. In the last two decades however, vessel monitoring systems (VMS) have begun to provide vessel location data at regular intervals such that fishing effort and behavioral decisions can be resolved across time and space for many fisheries. I demonstrate the utility of such data by examining the responses of two disparate fishing fleets to environmental and regulatory changes. This study was one of "big data" and required the development of nuanced approaches to process and model millions of records from multiple datasets. I thus present the work in three components: (1) How can we extract the information that we need? I present a detailed characterization of the types of data and an algorithm used to derive relevant behavioral aspects of fishing, like the duration and distances traveled during fishing trips; (2) How do fishers' spatial behaviors in the Bering Sea pollock fishery change in response to environmental variability; and (3) How were fisher behaviors and economic performances affected by a series of regulatory changes in the Gulf of Mexico grouper-tilefish longline fishery? I found a high degree of heterogeneity among vessel behaviors within the pollock fishery, underscoring the role that markets and processor-level decisions play in facilitating fisher responses to environmental change. In the Gulf of Mexico, my VMS-based approach estimated unobserved fishing effort with a high degree of accuracy and confirmed that the regulatory shift (e.g., the longline endorsement program and catch share program) yielded the intended impacts of reducing effort and improving both the economic performance and the overall harvest efficiency for the fleet. Overall, this work provides broadly applicable approaches for testing hypotheses regarding the dynamics of spatial behaviors in response to regulatory and environmental changes in a diversity of fisheries around the world.General introduction -- Chapter 1 Using vessel monitoring system data to identify and characterize trips made by fishing vessels in the United States North Pacific -- Chapter 2 Paths to resilience: Alaska pollock fleet uses multiple fishing strategies to buffer against environmental change in the Bering Sea -- Chapter 3 Vessel monitoring systems (VMS) reveal increased fishing efficiency following regulatory change in a bottom longline fishery -- General Conclusions
Atlas of Commercial Fisheries around Ireland, third edition
The Atlantic Ocean is the worldâs second-largest ocean and covers 20% of the earthâs surface. The waters around Ireland constitute a small part of that vast ocean but they are very productive; they support a diverse range of international fishing activities and contain important marine habitats and ecosystems. This resource requires careful management to protect vulnerable components whilst ensuring sustainable exploitation. This âAtlas of Commercial Fisheries around Irelandâ provides a series of detailed maps of fishing activity around Ireland with the aim of providing insights into fishing activities and fisheries resources. Fishing effort is mapped by gear and country. Irish landings of the key commercial species are mapped individually and by gear
Addressing Gaps in Small-Scale Fisheries: A Low-Cost Tracking System
none5During the last decade vessel-position-recording devices, such as the Vessel Monitoring System and the Automatic Identification System, have increasingly given accurate spatial and quantitative information of industrial fisheries. On the other hand, small-scale fisheries (vessels below 12 m) remain untracked and largely unregulated even though they play an important socio-economic and cultural role in European waters and coastal communities and account for most of the total EU fishing fleet. The typically low-technological capacity of these small-scale fishing boatsâfor which space and power onboard are often limitedâas well their reduced operative range encourage the development of efficient, low-cost, and low-burden tracking solutions. In this context, we designed a cost-effective and scalable prototypic architecture to gather and process positional data from small-scale vessels, making use of a LoRaWAN/cellular network. Data collected by our first installation are presented, as well as its preliminary processing. The emergence of a such low-cost and open-source technology coupled to artificial intelligence could open new opportunities for equipping small-scale vessels, collecting their trajectory data, and estimating their fishing effort (information which has historically not been present). It enables a new monitoring strategy that could effectively include small-scale fleets and support the design of new policies oriented to inform coastal resource and fisheries management.openAnna Nora Tassetti, Alessandro Galdelli, Jacopo Pulcinella, Adriano Mancini, Luca BologniniNora Tassetti, Anna; Galdelli, Alessandro; Pulcinella, Jacopo; Mancini, Adriano; Bolognini, Luc
Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors
The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone
Using Local Fishery Monitoring to Understand Small-Scale Coastal Fisheries in Tanzania
Nearshore marine fisheries provide the main source of protein for nearly 9 million people in the coastal villages of Tanzania, yet for decades the fisheries have shown signs of overexploitation. These fisheries are small-scale and co-managed by local coastal communities in groups known as Beach Management Units (BMUs). BMUs monitor individual fishing trip data (e.g. gear, vessel, taxa); however, these data have only been analyzed in nationally aggregated statistics and to our knowledge, are not presently used in management decision making. The present thesis aimed to identify the forms of data and information that local fishery monitoring can record about small-scale marine fisheries in Tanzania, and how that local monitoring data may be related to the spatial socio-ecological context of those fisheries. We collected all available fishing trip data from 2014 to 2017 from BMUs in fourteen villages in two spatially, socially, and ecologically distinct districts (Pangani and Rufiji) of the country. Our results found that each village had unique patterns of vessel-use, gear-use, and taxa landed, and that every village was specialized in some measure. Specifically, two villages in Pangani district landed octopus or parrotfish almost exclusively, suggesting potential trophic cascades after years of overexploitation. We then proposed a flexible modeling approach which incorporated the BMU landings data with spatial data to predict the spatial characteristics of the marine fisheries in Tanzania. The spatial models identified relationships between fishery landings and coral reef, seagrass, and mangrove habitat patch attributes, along with fisher density and a hydrologic index. Furthermore, the predicted spatial characteristics matched previously reported fishery characteristics in both districts. The maps developed by our modeling process provide a means for stakeholders and managers to understand the spatial distribution of their fisheries and in turn, focus on explicitly managing what, how, and where fishers operate. Overall, this thesis has shown that the catch data collected by BMUs were able to generate the first descriptions of village-based Tanzanian fishery characteristics. Thus, it is possible that the collection and analysis of local monitoring data can be used to promote the application of fishery regulations that are relevant to their socio-ecological context
From multiple aspect trajectories to predictive analysis: a case study on fishing vessels in the Northern Adriatic sea
In this paper we model spatio-temporal data describing the fishing activities in the Northern Adriatic Sea over four years. We build, implement and analyze a database based on the fusion of two complementary data sources: trajectories from fishing vessels (obtained from terrestrial Automatic Identification System, or AIS, data feed) and fish catch reports (i.e., the quantity and type of fish caught) of the main fishing market of the area. We present all the phases of the database creation, starting from the raw data and proceeding through data exploration, data cleaning, trajectory reconstruction and semantic enrichment. We implement the database by using MobilityDB, an open source geospatial trajectory data management and analysis platform. Subsequently, we perform various analyses on the resulting spatio-temporal database, with the goal of mapping the fishing activities on some key species, highlighting all the interesting information and inferring new knowledge that will be useful for fishery management. Furthermore, we investigate the use of machine learning methods for predicting the Catch Per Unit Effort (CPUE), an indicator of the fishing resources exploitation in order to drive specific policy design. A variety of prediction methods, taking as input the data in the database and environmental factors such as sea temperature, waves height and Clorophill-a, are put at work in order to assess their prediction ability in this field. To the best of our knowledge, our work represents the first attempt to integrate fishing ships trajectories derived from AIS data, environmental data and catch data for spatio-temporal prediction of CPUE â a challenging task
Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges
With the rapid development of marine activities, there has been an increasing
number of maritime mobile terminals, as well as a growing demand for high-speed
and ultra-reliable maritime communications to keep them connected.
Traditionally, the maritime Internet of Things (IoT) is enabled by maritime
satellites. However, satellites are seriously restricted by their high latency
and relatively low data rate. As an alternative, shore & island-based base
stations (BSs) can be built to extend the coverage of terrestrial networks
using fourth-generation (4G), fifth-generation (5G), and beyond 5G services.
Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs.
Despite of all these approaches, there are still open issues for an efficient
maritime communication network (MCN). For example, due to the complicated
electromagnetic propagation environment, the limited geometrically available BS
sites, and rigorous service demands from mission-critical applications,
conventional communication and networking theories and methods should be
tailored for maritime scenarios. Towards this end, we provide a survey on the
demand for maritime communications, the state-of-the-art MCNs, and key
technologies for enhancing transmission efficiency, extending network coverage,
and provisioning maritime-specific services. Future challenges in developing an
environment-aware, service-driven, and integrated satellite-air-ground MCN to
be smart enough to utilize external auxiliary information, e.g., sea state and
atmosphere conditions, are also discussed
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