Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison

Abstract. With the mining of polymetallic nodules from the deep-sea seafloor once more evoking commercial interest, decisions must be taken on how to most efficiently regulate and monitor physical and community disturbance in these remote ecosystems. Image-based approaches allow non-destructive assessment of the abundance of larger fauna to be derived from survey data, with repeat surveys of areas possible to allow time series data collection. At the time of writing, key underwater imaging platforms commonly used to map seafloor fauna abundances are autonomous underwater vehicles (AUVs), remotely operated vehicles (ROVs) and towed camera “ocean floor observation systems” (OFOSs). These systems are highly customisable, with cameras, illumination sources and deployment protocols changing rapidly, even during a survey cruise. In this study, eight image datasets were collected from a discrete area of polymetallic-nodule-rich seafloor by an AUV and several OFOSs deployed at various altitudes above the seafloor. A fauna identification catalogue was used by five annotators to estimate the abundances of 20 fauna categories from the different datasets. Results show that, for many categories of megafauna, differences in image resolution greatly influenced the estimations of fauna abundance determined by the annotators. This is an important finding for the development of future monitoring legislation for these areas. When and if commercial exploitation of these marine resources commences, robust and verifiable standards which incorporate developing technological advances in camera-based monitoring surveys should be key to developing appropriate management regulations for these regions.

Download Full-text

Megafauna community assessment of polymetallic nodule fields with cameras: Platform and methodology comparison

10.5194/bg-2019-363 ◽

2019 ◽

Author(s):

Timm Schoening ◽

Autun Purser ◽

Daniel Langenkämper ◽

Inken Suck ◽

James Taylor ◽

...

Keyword(s):

Time Series Data ◽

Image Resolution ◽

Series Data ◽

Data Sets ◽

Underwater Imaging ◽

Polymetallic Nodule ◽

Commercial Viability ◽

Polymetallic Nodules ◽

Observation Systems ◽

Discrete Area

Abstract. With the mining of polymetallic nodules from the deep sea seafloor again approaching commercial viability, decisions must be taken on how to most efficiently regulate and monitor physical and community disturbance in these remote ecosystems. Image based approaches allow non-destructive assessment of larger fauna abundances to be derived from survey data, with repeat surveys of areas possible to allow time series data collection. At time of writing key underwater imaging platforms commonly used to map seafloor fauna abundances are Automated Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs) and towed camera Ocean Floor Observation Systems (OFOSs). These systems are highly customisable, with mounted cameras, illumination systems and deployment protocols rapidly changing over time, and even within survey cruises. In this study 8 image datasets were collected from a discrete area of polymetallic nodule rich seafloor by an AUV and several OFOSs deployed at various altitudes above the seafloor. A fauna identification catalogue was used by 5 annotators to estimate the abundances of 20 fauna categories from the different data sets. Results show that for many categories of megafauna differences in image resolution greatly influenced the estimations of fauna abundance determined by the annotators. This is an important finding for the development of future monitoring legislation for these areas. When and if commercial exploitation of these marine resources commences, to ensure best monitoring practice, unambiguous rules on how camera-based monitoring surveys should be conducted, and with what equipment, must be put in place.

Download Full-text

Domestic and imports sources of supply to the US shrimp market and anti-dumping duties

Journal of Economic Studies ◽

10.1108/jes-06-2015-0109 ◽

2016 ◽

Vol 43 (6) ◽

pp. 1039-1056 ◽

Cited By ~ 4

Author(s):

Akbar Marvasti ◽

David W. Carter

Keyword(s):

Time Series Data ◽

Supply Curve ◽

Series Data ◽

Fuel Price ◽

Content Type ◽

Long Run ◽

Technological Advances ◽

The Us ◽

Pass Through ◽

Exchange Rate Pass Through

Purpose The purpose of this paper is to provide an economic analysis of the sources of supply to the US shrimp market. Design/methodology/approach The paper uses monthly time series data to estimate a simultaneous equations model with equations for domestic supplies from the Gulf of Mexico, imports, and prices. Findings Estimated long-run elasticities suggest that the domestic shrimp supply appears to be explained by seasons, diesel fuel price, hurricane activity, and shrimp price. The authors find evidence of a downward-slopping supply curve for the domestic harvesters that is likely to be temporary. Furthermore, anti-dumping duties have been ineffectual in curtailing imports produced by exploitation of natural shrimp biomass in developing countries and by technological advancements in aquaculture production. The authors also find evidence of a low exchange rate pass through. Finally, while domestic and import prices are not cointegrated, there is a two-way causality between them. Practical implications The authors found evidence that shrimp prices have fallen as import supply, due to technological advances in aquaculture, has risen faster than the US domestic demand over time suggesting a downward sloping supply curve. Also, the falling value of the US dollar has discouraged the imports, while the anti-dumping duties appear to have had little influence on the aggregate level of imports. Originality/value It provides a thorough investigation of the supply side of an important component of the US seafood market displaying the complexity of domestic producers’ reaction to falling prices, and ineffectual protectionism.

Download Full-text

STRATEGI PENINGKATAN PENERIMAAN RETRIBUSI ASET TETAP TANAH DI KABUPATEN LOMBOK BARAT

Elastisitas - Jurnal Ekonomi Pembangunan ◽

10.29303/e-jep.v1i2.12 ◽

2019 ◽

Vol 1 (2) ◽

pp. 91-105

Author(s):

Hailuddin Hailuddin ◽

Imam Kholbi ◽

Ade Paranata ◽

Sofiati Wardah

Keyword(s):

Local Government ◽

Swot Analysis ◽

Time Series Data ◽

Secondary Data ◽

Primary Data ◽

Series Data ◽

Regional Government ◽

Land Rental ◽

Technological Advances ◽

Fixed Assets

This research is about strategies to increase levies of fixed assets / land in West Lombok Regency, with the aim to find out strategies to increase levies from the management of fixed assets (land) in West Lombok Regency. The study is quantitative descriptive, using time series data for 6 years, 2012-2017. Besides using secondary data, it is also strengthened by primary data which is collected through library studies, documentation, interviews and questionnaires. Data analysis uses SWOT analysis by identifying internal factors to determine aspects of strengths and weaknesses, as well as external factors to determine aspects of opportunity and threats. The results showed that there were 9 strategies that could be used to increase revenue from user fees for land use, including utilizing scientific and technological advances, increasing the number and quality of human resources in managing levies, working with related parties, improving local government land certification, land inventory local government, increase land rental rates and improve supervision of land assets. The results of this study are expected to be followed up by the West Lombok Regional Government in order to increase revenue from the use of regional wealth that is getting better

Download Full-text

Integrating Remote Sensing into Wildlife Monitoring for Conservation

Environmental Conservation ◽

10.1017/s0376892919000092 ◽

2019 ◽

Vol 46 (03) ◽

pp. 181-183 ◽

Cited By ~ 5

Author(s):

PJ Stephenson

Keyword(s):

Remote Sensing ◽

Wildlife Conservation ◽

Time Series Data ◽

Decision Makers ◽

Series Data ◽

User Needs ◽

Wildlife Monitoring ◽

Use Of Data ◽

Technological Advances ◽

Local User

SummaryEffective wildlife monitoring is a prerequisite for effective wildlife conservation since, without time-series data on species populations and threats, evidence-based adaptive management will be difficult to achieve. Technological advances in remote sensing offer more opportunities for data collection than ever before. However, if we are to enhance data sharing and the use of data by decision-makers, methods must be relevant to local user needs and be integrated into monitoring schemes with appropriate goals and indicators.

Download Full-text

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

PsycEXTRA Dataset ◽

10.1037/e634372013-001 ◽

2013 ◽

Author(s):

Stephen J. Tueller ◽

Richard A. Van Dorn ◽

Georgiy Bobashev ◽

Barry Eggleston

Keyword(s):

Time Series ◽

Data Analysis ◽

Exploratory Data Analysis ◽

Time Series Data ◽

Series Data ◽

Exploratory Data

Download Full-text

Some statistical and CI models to predict chaotic high-frequency financial data

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189107 ◽

2020 ◽

Vol 39 (5) ◽

pp. 6419-6430

Author(s):

Dusan Marcek

Keyword(s):

Time Series Data ◽

Moving Average ◽

Methodological Approach ◽

Back Propagation ◽

Large Data ◽

Series Data ◽

Data Set ◽

Training Time ◽

Optimal Population ◽

Forecast Time

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.

Download Full-text

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

Jurnal Riset Manajemen Sekolah Tinggi Ilmu Ekonomi Widya Wiwaha Program Magister Manajemen ◽

10.32477/jrm.v1i2.72 ◽

2017 ◽

Vol 1 (2) ◽

pp. 177-191

Author(s):

Rizki Rahma Kusumadewi ◽

Wahyu Widayat

Keyword(s):

Time Series ◽

Exchange Rate ◽

Money Supply ◽

Time Series Data ◽

The United States ◽

Economic Conditions ◽

Series Data ◽

Arch Model ◽

United States Dollar ◽

The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

Download Full-text

Economic Turmoil in Islamic Banking Investment

ETIKONOMI ◽

10.15408/etk.v19i2.17206 ◽

2020 ◽

Vol 19 (2) ◽

Author(s):

Budiandru Budiandru ◽

Sari Yuniarti

Keyword(s):

Interest Rates ◽

Stock Price ◽

Time Series Data ◽

Series Data ◽

Islamic Banking ◽

Vector Error Correction ◽

Investment Financing ◽

Vector Error ◽

Operational Activities

Investment financing is one of the operational activities of Islamic banking to encourage the real sector. This study aims to analyze the effect of economic turmoil on investment financing, analyze the response to investment financing, and analyze each variable's contribution in explaining the diversity of investment financing. This study uses monthly time series data from 2009 to 2020 using the Vector Error Correction Model (VECM) analysis. The results show that the exchange rate, inflation, and interest rates significantly affect Islamic banking investment financing in the long term. The response to investment financing is the fastest to achieve stability when it responds to shocks to the composite stock price index. Inflation is the most significant contribution in explaining diversity in investment financing. Islamic banking should increase the proportion of funding for investment. Customers can have a larger business scale to encourage economic growth, with investment financing increasing.JEL Classification: E22, G11, G24How to Cite:Budiandru., & Yuniarti, S. (2020). Economic Turmoil in Islamic Banking Investment. Etikonomi: Jurnal Ekonomi, 19(2), xx – xx. https://doi.org/10.15408/etk.v19i2.17206.

Download Full-text