scholarly journals Evidence for an Allee effect in a declining fur seal population

2021 ◽  
Vol 288 (1947) ◽  
Author(s):  
Rebecca Nagel ◽  
Claire Stainfield ◽  
Cameron Fox-Clarke ◽  
Camille Toscani ◽  
Jaume Forcada ◽  
...  
Keyword(s):  
Time Series Data ◽  
Poor Quality ◽  
Weight Of Evidence ◽  
Series Data ◽  
Low Density ◽  
Allee Effects ◽  
Wild Populations ◽  
Fur Seal ◽  
Parallel Body ◽  
Pup Mortality

Allee effects play an important role in the dynamics of many populations and can increase the risk of local extinction. However, some authors have questioned the weight of evidence for Allee effects in wild populations. We therefore exploited a natural experiment provided by two adjacent breeding colonies of contrasting density to investigate the potential for Allee effects in an Antarctic fur seal ( Arctocephalus gazella ) population that is declining in response to climate change-induced reductions in food availability. Biometric time-series data were collected from 25 pups per colony during two consecutive breeding seasons, the first of which was among the worst on record in terms of breeding female numbers, pup birth weights and foraging trip durations. In previous decades when population densities were higher, pup mortality was consistently negatively density dependent, with rates of trauma and starvation scaling positively with density. However, we found the opposite, with higher pup mortality at low density and the majority of deaths attributable to predation. In parallel, body condition was depressed at low density, particularly in the poor-quality season. Our findings shed light on Allee effects in wild populations and highlight a potential emerging role of predators in the ongoing decline of a pinniped species.

scholarly journals Evidence for an Allee effect in a declining fur seal population

2020 ◽  
Author(s):  
Rebecca Nagel ◽  
Claire Stainfield ◽  
Cameron Fox-Clarke ◽  
Camille Toscani ◽  
Jaume Forcada ◽  
...  
Keyword(s):  
Time Series Data ◽  
Poor Quality ◽  
Weight Of Evidence ◽  
Series Data ◽  
Low Density ◽  
Allee Effects ◽  
Wild Populations ◽  
Fur Seal ◽  
Parallel Body ◽  
Pup Mortality

Allee effects play an important role in the dynamics of many populations and can increase the risk of local extinction. However, some authors have questioned the weight of evidence for Allee effects in wild populations. We therefore exploited a natural experiment provided by two adjacent breeding colonies of contrasting density to investigate the potential for Allee effects in an Antarctic fur seal (Arctocephalus gazella) population that is declining in response to climate-change induced reductions in food availability. Biometric time-series data were collected from 25 pups per colony during two consecutive breeding seasons, the first of which was amongst the worst on record in terms of breeding female numbers, pup birth weights and foraging trip durations. In previous decades when population densities were higher, pup mortality was consistently negatively density-dependent, with rates of trauma and starvation scaling positively with density. However, we found the opposite, with higher pup mortality at low density and the majority of deaths attributable to predation. In parallel, body condition was also depressed at low density, particularly in the poor-quality season. Our findings shed light on Allee effects in wild populations and highlight a potential emerging role of predators in the ongoing decline of a pinniped species.

scholarly journals Are predator-prey model predictions supported by empirical data? Evidence for a storm-driven shift to an alternative stable state in a crab-clam system

2020 ◽  
Vol 645 ◽  
pp. 83-90
Author(s):  
CN Glaspie ◽  
RD Seitz ◽  
RN Lipcius
Keyword(s):  
Time Series ◽  
Empirical Data ◽  
Time Series Data ◽  
Steady States ◽  
Series Data ◽  
Low Density ◽  
Predator Prey ◽  
Predator Prey Model ◽  
Model Predictions ◽  
Analysis Of Time Series

A dynamic systems approach can predict steady states in predator-prey interactions, but there are very few examples of predictions from predator-prey models conforming to empirical data. Here, we examined the evidence for the low-density steady state predicted by a Lotka-Volterra model of a crab-clam predator-prey system using data from long-term monitoring, and data from a previously published field survey and field predation experiment. Changepoint analysis of time series data indicate that a shift to low density occurred for the soft-shell clam Mya arenaria in 1972, the year of Tropical Storm Agnes. A possible mechanism for the shift is that Agnes altered predator-prey dynamics between M. arenaria and the blue crab Callinectes sapidus, shifting from a system controlled from the bottom up by prey resources, to a system controlled from the top down by predation pressure on bivalves, which is supported by a correlation analysis of time series data. Predator-prey ordinary differential equation models with these 2 species were analyzed for steady states, and low-density steady states were similar to previously published clam densities and mortality rates, consistent with the idea that C. sapidus is a major driver of M. arenaria population dynamics. Relatively simple models can predict shifts to alternative stable states, as shown by agreement between model predictions (this study) and published field data in this system. The preponderance of multispecies interactions exhibiting nonlinear dynamics indicates that this may be a general phenomenon.

scholarly journals The peculiarities of establishing the charter air transportation: European experience in Ukraine

2020 ◽  
Vol 16 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Tetyana Prymak ◽  
Liubov Ivchenko ◽  
Nataliia Pohuda ◽  
Valentyna Levchenko ◽  
Viktor Trynchuk
Keyword(s):  
Time Series Data ◽  
Air Transportation ◽  
Poor Quality ◽  
Series Data ◽  
Cross Sectional ◽  
Passenger Traffic ◽  
Market Participants ◽  
Marketing Analysis ◽  
Flight Delay ◽  
June July

This paper highlights the problems associated with the poor quality of services and the lack of effective marketing interaction between all the participants of the charter air transportation in the tourist summer season of 2018 in Ukraine. The paper aims to develop an algorithm for the actions of all participants of tourist services market in order to establish effective marketing interaction based on the analysis of the reasons influencing the destabilization of the tourist services market in the field of charter air transportation. Flight delay statistics were selected for June-July 2018 due to the fact that it was during this period that the problem manifested itself especially sharply. So, not time-series data, but cross-sectional data were selected for the analysis of the problem cause. At the same time, for confident conclusions about the increase in passenger traffic, 5-year periods were chosen, namely, the period 2014–2018 was compared with the period 2009–2013. During the research, statistical methods of one-factor linear correlation-regression analysis were used, as well as a comparative analysis of the indicators of the charter air transportation participants’ performance in Ukraine. The analysis of charter air transportation market showed that increasing the age of the aircraft in a year leads to a decrease in the proportion of timely flights by 2.5%. The marketing analysis proves that the rapid increase in the number of passengers was caused by the explosive increase in irregular flights. The results of the study also indicate that the well-organized interaction between the tour operator and the airlines significantly affects the timeliness of the flights. Based on defined problems of the charter air transportation market, a set of recommendations has been proposed for improving the marketing interaction of all market participants: tourists, tour operators, airlines and government agencies.

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

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

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

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.

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

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.

Economic Turmoil in Islamic Banking Investment

ETIKONOMI ◽  
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.

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Detection Method ◽  
Series Data

Macro-Economic Disequilibrium and Educational Development in Nigeria between 1980-2017

2019 ◽  
Vol 10 (08) ◽  
pp. 20592-21600
Author(s):  
Gbadebo Salako ◽  
Adejumo Musibau Ojo ◽  
Jaji Ayobami Francis
Keyword(s):  
Time Series Data ◽  
Educational Development ◽  
Negative Relationship ◽  
Series Data ◽  
Explanatory Variables ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Stationarity Test ◽  
Level I

This study empirically investigates the effects of macroeconomic disequilibrium on educational development in Nigeria. The study employed time series data between 1980 and 2017. Autoregressive Distributed Lag method of estimation was employed. The result revealed that the variables stationarity test were mixed between the first difference I(I) and level I(0). The cointegration result shows that there exist long run relationship between the variables. The result revealed that Balance of payment, Poverty, Debt rate inflation and unemployment exhibited negative relationship with educational development. The estimation result showed that all explanatory variables account for 88% variation of educational development in Nigeria. It is therefore recommended that government should fast track policies that can stabilize inflation and exchange rate in the country. Also, Policies must be formulated to reduce poverty and unemployment.

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