Short-term Forecasting in Marine Fish Stocks

1981 ◽  
Vol 38 (10) ◽  
pp. 1247-1254 ◽  
Author(s):  
Max Stocker ◽  
Ray Hilborn
Keyword(s):  
Time Series ◽  
Marine Fish ◽  
Management Practice ◽  
Model Fitting ◽  
Production Model ◽  
Catch Per Unit Effort ◽  
Short Term ◽  
Fish Stocks ◽  
Production Models ◽  
The Difference

The predictive power of stock production models and simple time series methods was considered for five marine fish stocks. The distinction between model fitting and forecasting future short-term catch is discussed, as is the difference between techniques to forecast short-term yield, and techniques to calculate long-term management practice. Fox's procedure for fitting Pella and Tomlinson's stock production model, Schnute's method for fitting Schaefer's model, and Gulland's method are all considered. We found that all methods except that of Gulland work well for some stocks, and the relative performance of the methods depends upon the exploitation history of the stock. In several instances one of the best forecasts of next year's catch per unit effort (CPUE) was the previous year's CPUE, emphasizing the fact that a good forecasting technique may have no utility in determining management policies.Key words: production models, catch and effort, fisheries, management, catch forecasting, time series

Are Age-Structured Models Appropriate for Catch-Effort Data?

1985 ◽  
Vol 42 (6) ◽  
pp. 1066-1072 ◽  
Author(s):  
Donald Ludwig ◽  
Carl J. Walters
Keyword(s):  
Simulated Data ◽  
Fishing Effort ◽  
Production Model ◽  
Model Structure ◽  
Catch Per Unit Effort ◽  
Unit Effort ◽  
Production Models ◽  
Stock Assessments ◽  
Age Structured ◽  
Age Structured Model

Simulated data have been used to evaluate the performance of schemes for estimating optimum fishing effort using a simple stock-production model and R. B. Deriso's age-structured model Even when the data are generated using Deriso's model, the simpler production model generally gives as good or better estimates for the optimal effort. The only exception to this result is when data are provided with unrealistically large contrasts in effort and catch per unit effort over time. The implication of these findings is that simple production models should often be used in stock assessments based on catch/effort data, even when more realistic and structurally correct models are available to the analyst; the best choice depends on how much contrast has occurred in the historical effort and catch per unit effort data, rather than on prior knowledge about which model structure is biologically more realistic.

scholarly journals Modeling and Forecasting of Lake Malombe Fish Biomass and Catch Per Unit Effort (CPUE)

2020 ◽  
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Phiri ◽  
...  
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Information Criterion ◽  
Fish Biomass ◽  
Catch Per Unit Effort ◽  
Potential Threat ◽  
Fish Stocks ◽  
Partial Autocorrelation Function ◽  
Precautionary Measures ◽  
Management Approaches

Lake Malombe fish stocks have been depleted by chronic overfishing. Various management approaches (co-management, command control, and ecosystem-based management to fisheries) have been used to manage the fishery. However, the lack of an accurate predictive model has hampered their success. Therefore, we developed and tested a time series model for Lake Malombe fishery. The seasonal fish biomass and CPUE trends were first observed and both were non-stationary. The second-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), and Akaike information criterion (AIC) were estimated, which led to the identification and construction of autoregressive integrated moving average (ARIMA) models, suitable in explaining the time series and forecasting. The results showed that ARIMA (1,2,1) provided a better prediction than its counterparts. The model satisfactorily predicted that by 2032, both fish biomass and CPUE will decrease to 3204.6 tons and 59.672 respectively, signifying the potential threat to Lake Malombe fishery. The model justified the necessity of taking precautionary measures to avoid the total collapse of the fishery.

FORECASTING FRESH WATER AND MARINE FISH PRODUCTION IN MALAYSIA USING ARIMA AND ARFIMA MODELS

2018 ◽  
Vol 3 (2) ◽  
pp. 81
Author(s):  
P J W Mah ◽  
N A M Ihwal ◽  
N Z Azizan
Keyword(s):  
Time Series ◽  
Marine Fish ◽  
Model Fitting ◽  
Forecast Model ◽  
Absolute Error ◽  
Percentage Error ◽  
Human Consumption ◽  
Fish Production ◽  
Arfima Models ◽  
Time Series Modelling

Malaysia is surrounded by sea, rivers and lakes which provide natural sources of fish for human consumption. Hence, fish is one source of protein supply to the country and fishery is a sub-sector that contribute to the national gross domestic product. Since fish forecasting is crucial in fisheries management for managers and scientists, time series modelling can be one useful tool. Time series modelling have been used in many fields of studies including the fields of fisheries. In a previous research, the ARIMA and ARFIMA models were used to model marine fish production in Malaysia and the ARFIMA model emerged to be a better forecast model. In this study, we consider fitting the ARIMA and ARFIMA to both the marine and freshwater fish production in Malaysia. The process of model fitting was done using the “ITSM 2000, version 7.0” software. The performance of the models were evaluated using the mean absolute error, root mean square error and mean absolute percentage error. It was found in this study that the selection of the best fit model depends on the forecast accuracy measures used.

scholarly journals Salud, trabajo y ambiente. Estrategias para el desarrollo regional

Locale ◽  
2017 ◽  
Vol 1 (1) ◽  
pp. 11-27
Author(s):  
Jorge Pickenhayn
Keyword(s):  
Regional Development ◽  
Spatial Models ◽  
Human Action ◽  
Production Model ◽  
Production Models ◽  
The Difference ◽  
Para Determinar ◽  
Planning Methodology ◽  
Regional Development Strategies ◽  
Taking Action

Toda acción humana genera un impacto en el ambiente. Los bienes de la naturaleza se re–significan cuando la sociedad les asigna el nombre de «recursos». También los modelos productivos implican «recurrir» a estrategias concretas que traen consigo necesarias acciones que producen cambios. Hay permanentes umbrales que establecen el quiebre entre un antes y un después para cada paisaje.La sociedad tiene metas que pone en juego para determinar sus proyectos de desarrollo, particularmente si las mejoras perseguidas involucran al territorio. Cuando nos preguntamos cuáles son esas metas aparece el «mito del Edén»: la respuesta es «vivir», concepto demasiado amplio y complejo que puede simplificarse si lo dividimos en: vivir bien, sano y mucho. Todo modelo productivo se inspira en el trabajo como instancia de transformación (o sea, vivir mejor). Para ello su agente, el hombre, necesita preservarse y perdurar (es decir, vivir sano y mucho).Cuando los especialistas en planeamiento piensan modelos de ordenación territorial para grandes superficies realizan comparaciones de muy diversa factura y concluyen en modelos de síntesis para el presente y sobre el futuro planificado. Se suelen, empero, descuidar los vínculos entre salud, trabajo y ambiente. Estimamos que esta triangulación es importante por lo que se propone una metodología de planificación que tenga en cuenta: a) el estudio de los impactos recíprocos entre salud, ambiente y trabajo; b) el análisis de problemas concretos asociados con la distancia y accesibilidad a lugares de empleo y centros de salud en relación con los espacios de residencia de la población, y c) propiciar un ordenamiento espacial que potencie los vínculos y minimice las dificultades por la relación de estos tres factores. Los puntos destacados merecen tratarse con mayor peso en las estrategias de desarrollo regional que propicien un planeamiento que apunte al desarrollo productivo.Palabras clave: salud; trabajo; desarrollo; ambiente. AbstractHEALTH, WORK AND ENVIROMENT. REGIONAL DEVELOPMENT STRATEGIESEvery human action has an impact on the environment. The society resignifies the goods the nature provides by calling them «resources». Production models also involve taking action that brings necessary changes. There are permanent thresholds that show the difference in time of each landscape.The society has objectives to establish its development projects, and it is particularly interested in improvements that involve the territory. When we wonder which those objectives are, the «myth of Eden» appears: the answer is «to live», a concept too broad and complex that can be simplified if we divide it into: live well, healthy and long. Every production model is inspired by work as an instance of transformation (i.e. live better). In order to accomplish this, the man needs to endure and preserve himself (i.e. live healthy and long).When planning specialists think about spatial models for large areas, they make many comparisons. They conclude synthesis models for the present and the future planned; but they tend to neglect the links between health, labour and environment. We estimate that this triangulation is important, so a planning methodology is proposed to take into account: a) the study of the reciprocal impacts between health, environment and labour; b) the analyses of specific problems associated with distance and accessibility to workplaces and health centres in relation to the spaces of residence of the population, and c) the promotion of a spatial planning to reinforce the links and to minimize the difficulties arisen due to these three factors. The highlights deserve to be treated in depth within regional development strategies that foster a planning point for a productive development.Keywords: health; work; development; enviroment. ResumoSAÚDE, TRABALHO E AMBIENTE. ESTRATÉGIAS DE DESENVOLVIMENTO REGIONALToda ação humana gera um impacto no ambiente. Os bens da natureza obtêm novo significado quando a sociedade lhes dá o nome de «recursos». Também os modelos produtivos implicam «recorrer» a estratégias concretas que trazem ações necessárias, as que produzem mudanças. Há permanentes umbrais que estabelecem o quebre entre um antes e um depois para cada paisagem.A sociedade tem metas que põe em jogo para estabelecer seus projetos de desenvolvimento, particularmente se as melhoras perseguidas envolvem ao território. Quando nos perguntamos quais são aquelas metas aparece o «mito do Éden»: a resposta é «viver», conceito muito amplo e complexo que pode se simplificar, se o dividimos em: viver bem, são e muito. Todo modelo produtivo inspira se no trabalho como instancia de transformação (o seja, viver melhor). Para isso seu agente, o homem, precisa se preservar e perdurar (o seja, viver são e muito).Quando os especialistas em planejamento pensam modelos de ordenação territorial para grandes superfícies realizam comparações de muito diversa fatura e concluem em modelos de síntese para o presente e sobre o futuro planejado. Mas às vezes se descuidam os vínculos entre saúde, trabalho e ambiente. Estimamos que esta triangulação é importante e propõe se uma metodologia de planificação que tomem em conta os pontos a seguir: a) o estudo dos impactos recíprocos entre saúde, ambiente e trabalho; b) o análise de problemas concretos associados à distancia e acessibilidade a lugares de trabalho e centros de saúde com relação aos espaços de residência da população, e c) propiciar um ordenamento espacial que potencie os vínculos e minimize as dificuldades pela relação entre estes três fatores. Os pontos destacados merecem ser tratados com maior peso nas estratégias de desenvolvimento regional que propiciem um planejamento orientado ao desenvolvimento produtivo.Palavras–chave: saúde; trabalho; desenvolvimento; ambiente.

scholarly journals The Term Structure of Bond Market Liquidity and Its Implications for Expected Bond Returns

2010 ◽  
Vol 46 (1) ◽  
pp. 111-139 ◽  
Author(s):  
Ruslan Goyenko ◽  
Avanidhar Subrahmanyam ◽  
Andrey Ukhov
Keyword(s):  
Time Series ◽  
Term Structure ◽  
Primary Source ◽  
Extended Period ◽  
Market Liquidity ◽  
Liquidity Premium ◽  
Short Term ◽  
Bond Returns ◽  
Treasury Market ◽  
The Difference

AbstractPrevious studies of Treasury market illiquidity span short time periods and focus on particular maturities. In contrast, we study the time series of illiquidity for different maturities over an extended period of time. We also compare time-series determinants of on-the-run and off-the-run illiquidity. Illiquidity increases and the difference between spreads of long- and short-term bonds significantly widens during recessions, suggesting a “flight to liquidity,” wherein investors shift into the more liquid short-term bonds during economic contractions. Macroeconomic variables such as inflation and federal funds rates forecast off-the-run illiquidity significantly but have only modest forecasting ability for on-the-run illiquidity. Bond returns across maturities are forecastable by off-the-run but not on-the-run bond illiquidity. Thus, off-the-run illiquidity, by reflecting macro shocks first, is the primary source of the liquidity premium in the Treasury market.

EVALUASI PROYEKSI DEMAND BARANG DAN PENUMPANG PELABUHAN DI PROVINSI MALUKU

2019 ◽  
Vol 19 (2) ◽  
pp. 101-110
Author(s):  
Adrian Firdaus ◽  
M. Dwi Yoga Sutanto ◽  
Rajin Sihombing ◽  
M. Weldy Hermawan
Keyword(s):  
Time Series ◽  
Projection Method ◽  
Development Plan ◽  
Master Plan ◽  
Port Development ◽  
Loading And Unloading ◽  
The Difference ◽  
Existing Data

Abstract Every port in Indonesia must have a Port Master Plan that contains an integrated port development plan. This study discusses one important aspect in the preparation of the Port Master Plan, namely the projected movement of goods and passengers, which can be used as a reference in determining the need for facilities at each stage of port development. The case study was conducted at a port located in a district in Maluku Province and aims to evaluate the analysis of projected demand for goods and passengers occurring at the port. The projection method used is time series and econometric projection. The projection results are then compared with the existing data in 2018. The results of this study show that the econometric projection gives adequate results in predicting loading and unloading activities as well as the number of passenger arrival and departure in 2018. This is indicated by the difference in the percentage of projection results towards the existing data, which is smaller than 10%. Whereas for loading and unloading activities, time series projections with logarithmic trends give better results than econometric projections. Keywords: port, port master plan, port development, unloading activities  Abstrak Setiap pelabuhan di Indonesia harus memiliki sebuah Rencana Induk Pelabuhan yang memuat rencana pengem-bangan pelabuhan secara terpadu. Studi ini membahas salah satu aspek penting dalam penyusunan Rencana Induk Pelabuhan, yaitu proyeksi pergerakan barang dan penumpang, yang dapat dipakai sebagai acuan dalam penentuan kebutuhan fasilitas di setiap tahap pengembangan pelabuhan. Studi kasus dilakukan pada sebuah pelabuhan yang terletak di sebuah kabupaten di Provinsi Maluku dan bertujuan untuk melakukan evaluasi ter-hadap analisis proyeksi demand barang dan penumpang yang terjadi di pelabuhan tersebut. Metode proyeksi yang dipakai adalah proyeksi deret waktu dan ekonometrik. Hasil proyeksi selanjutnya dibandingkan dengan data eksisting tahun 2018. Hasil studi ini menunjukkan bahwa proyeksi ekonometrik memberikan hasil yang cukup baik dalam memprediksi aktivitas bongkar barang serta jumlah penumpang naik dan turun di tahun 2018. Hal ini diindikasikan dengan selisih persentase hasil proyeksi terhadap data eksisting yang lebih kecil dari 10%. Sedangkan untuk aktivitas muat barang, proyeksi deret waktu dengan tren logaritmik memberikan hasil yang lebih baik daripada proyeksi ekonometrik. Kata-kata kunci: pelabuhan, rencana induk pelabuhan, pengembangan pelauhan, aktivitas bongkar barang

Oil pollution and fisheries

1982 ◽  
Vol 297 (1087) ◽  
pp. 401-411 ◽  
Keyword(s):  
Water Quality ◽  
Adverse Effects ◽  
Oil Pollution ◽  
Coastal Areas ◽  
Short Term ◽  
Fish Stocks ◽  
Local Impacts ◽  
Reduced Water ◽  
Long Term Adverse Effects

The term ‘pollution’ is taken in its broadest sense and effects are recognized to be due to interference, tainting and toxicity. Each of these types of impact is discussed and assessed. It is concluded that no long-term adverse effects on fish stocks can be attributed to oil but that local impacts can be extremely damaging in the short term and that produce from specific localities can be tainted and unmarketable for long periods. In some coastal areas oil can be one among several contributors to reduced water quality, and the implications of this are discussed.

279 WACSAW: A Statistical and Individually Adaptive Method to Determine Sleep and Wakefulness from Activity

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A111-A112
Author(s):  
Austin Vandegriffe ◽  
V A Samaranayake ◽  
Matthew Thimgan
Keyword(s):  
Time Series ◽  
Optimal Transport ◽  
Activity Patterns ◽  
Adaptive Method ◽  
Wasserstein Distance ◽  
Activity Data ◽  
Commercial Grade ◽  
Movement Data ◽  
The Difference ◽  
Levene Test

Abstract Introduction Technological innovations have broadened the type and amount of activity data that can be captured in the home and under normal living conditions. Yet, converting naturalistic activity patterns into sleep and wakefulness states has remained a challenge. Despite the successes of current algorithms, they do not fill all actigraphy needs. We have developed a novel statistical approach to determine sleep and wakefulness times, called the Wasserstein Algorithm for Classifying Sleep and Wakefulness (WACSAW), and validated the algorithm in a small cohort of healthy participants. Methods WACSAW functional routines: 1) Conversion of the triaxial movement data into a univariate time series; 2) Construction of a Wasserstein weighted sum (WSS) time series by measuring the Wasserstein distance between equidistant distributions of movement data before and after the time-point of interest; 3) Segmenting the time series by identifying changepoints based on the behavior of the WSS series; 4) Merging segments deemed similar by the Levene test; 5) Comparing segments by optimal transport methodology to determine the difference from a flat, invariant distribution at zero. The resulting histogram can be used to determine sleep and wakefulness parameters around a threshold determined for each individual based on histogram properties. To validate the algorithm, participants wore the GENEActiv and a commercial grade actigraphy watch for 48 hours. The accuracy of WACSAW was compared to a detailed activity log and benchmarked against the results of the output from commercial wrist actigraph. Results WACSAW performed with an average accuracy, sensitivity, and specificity of >95% compared to detailed activity logs in 10 healthy-sleeping individuals of mixed sexes and ages. We then compared WACSAW’s performance against a common wrist-worn, commercial sleep monitor. WACSAW outperformed the commercial grade system in each participant compared to activity logs and the variability between subjects was cut substantially. Conclusion The performance of WACSAW demonstrates good results in a small test cohort. In addition, WACSAW is 1) open-source, 2) individually adaptive, 3) indicates individual reliability, 4) based on the activity data stream, and 5) requires little human intervention. WACSAW is worthy of validating against polysomnography and in patients with sleep disorders to determine its overall effectiveness. Support (if any):

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