Reciprocal Oscillations in Densities of Larval Fish and Potential Predators: A Reflection of Present or Past Predation?

1985 ◽  
Vol 42 (11) ◽  
pp. 1841-1849 ◽  
Author(s):  
K. T. Frank ◽  
W. C. Leggett
Keyword(s):  
Time Series Data ◽  
Larval Fish ◽  
Empirical Support ◽  
Spatial Dimension ◽  
Temporal Variations ◽  
Series Data ◽  
Predator Prey ◽  
Larval Fishes ◽  
Prey Interaction ◽  
Predator Abundance

Reciprocity in time series data on the abundance of potentially interacting species has been one basis of empirical support for existing predator–prey theory. Evidence of this type has frequently been used to support the belief that predation by macroinvertebrates is one of the major causes of mortality among the early life stages of marine fishes. We question the validity of this generalization. We observed statistically significant inverse correlations between the abundance of macroinvertebrate predators and coastal ichthyoplankton in coastal Newfoundland both at the same site between years and at different sites in the same year. This correlation was shown to result not from a causal predator–prey interaction, but from occupation by the larvae and the macroinvertebrates of discrete water masses whose presence in the coastal area oscillates temporally in response to changes in wind conditions. Reevaluation of previously published reciprocal oscillations in the abundance of larval fish and potential predators, which had been cited as evidence of predatory regulation of larvae numbers, showed that in all cases available physical data suggest that these correlations too may have been spurious. We suggest that historical temporal variations in predator abundance may have served as a template for the evolution of adaptive strategies on the part of larval fishes which effectively isolate them from potential predators in either the temporal or spatial dimension. Our analyses suggest that such adaptations involve active behavioral responses to reliable physical and/or biological signals indicative of the existence of ecological "safe sites."

scholarly journals Reconsidering the importance of the past in predator–prey models: both numerical and functional responses depend on delayed prey densities

2013 ◽  
Vol 280 (1768) ◽  
pp. 20131389 ◽  
Author(s):  
Jiqiu Li ◽  
Andy Fenton ◽  
Lee Kettley ◽  
Phillip Roberts ◽  
David J. S. Montagnes
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Prey Abundance ◽  
Series Data ◽  
Functional Responses ◽  
New Approach ◽  
Predator Prey ◽  
The Past ◽  
Predator Prey Models ◽  
Underlying Mechanisms

We propose that delayed predator–prey models may provide superficially acceptable predictions for spurious reasons. Through experimentation and modelling, we offer a new approach: using a model experimental predator–prey system (the ciliates Didinium and Paramecium ), we determine the influence of past-prey abundance at a fixed delay (approx. one generation) on both functional and numerical responses (i.e. the influence of present : past-prey abundance on ingestion and growth, respectively). We reveal a nonlinear influence of past-prey abundance on both responses, with the two responding differently. Including these responses in a model indicated that delay in the numerical response drives population oscillations, supporting the accepted (but untested) notion that reproduction, not feeding, is highly dependent on the past. We next indicate how delays impact short- and long-term population dynamics. Critically, we show that although superficially the standard (parsimonious) approach to modelling can reasonably fit independently obtained time-series data, it does so by relying on biologically unrealistic parameter values. By contrast, including our fully parametrized delayed density dependence provides a better fit, offering insights into underlying mechanisms. We therefore present a new approach to explore time-series data and a revised framework for further theoretical studies.

scholarly journals Intra-Annual Patterns in the Benthic-Pelagic Fluxes of Dissolved and Particulate Matter

2020 ◽  
Vol 7 ◽  
Author(s):  
Saskia Rühl ◽  
Charlie E. L. Thompson ◽  
Ana M. Queirós ◽  
Stephen Widdicombe
Keyword(s):  
Time Series ◽  
Biological Activity ◽  
Particulate Matter ◽  
Time Series Data ◽  
Temporal Variations ◽  
Series Data ◽  
Downward Flux ◽  
Dissolved Matter ◽  
Upward Flux

In coastal temperate environments, many processes known to affect the exchange of particulate and dissolved matter between the seafloor and the water column follow cyclical patterns of intra-annual variation. This study assesses the extent to which these individual short term temporal variations affect specific direct drivers of seafloor-water exchanges, how they interact with one another throughout the year, and what the resulting seasonal variation in the direction and magnitude of benthic-pelagic exchange is. Existing data from a multidisciplinary long-term time-series from the Western Channel Observatory, United Kingdom, were combined with new experimental and in situ data collected throughout a full seasonal cycle. These data, in combination with and contextualized by time-series data, were used to define an average year, split into five ‘periods’ (winter, pre-bloom, bloom, post-bloom, and autumn) based around the known importance of pelagic primary production and hydrodynamically active phases of the year. Multivariate analyses were used to identify specific sub-sets of parameters that described the various direct drivers of seafloor-water exchanges. Both dissolved and particulate exchange showed three distinct periods of significant flux during the year, although the specific timings of these periods and the cause-effect relationships to the direct and indirect drivers differed between the two types of flux. Dissolved matter exchange was dominated by an upward flux in the pre-bloom period driven by diffusion, then a biologically induced upward flux during the bloom and an autumn downward flux. The latter was attributable to the interactions of hydrodynamic and biological activity on the seafloor. Particulate matter exchanges exhibited a strongly hydrologically influenced upward flux during the winter, followed by a biologically induced downward flux during the bloom and a second period of downward flux throughout post-bloom and autumn periods. This was driven primarily through interactions between biological activity, and physical and meteorological drivers. The integrated, holistic and quantitative data-based analysis of intra-annual variability in benthic/pelagic fluxes presented in this study in a representative temperate coastal environment, demonstrates not only the various process’ inter-connectivity, but also their relative importance to each other. Future investigations or modeling efforts of similar systems will benefit greatly from the relationships and baseline rules established in this study.

scholarly journals Fiscal Consolidation and Macroeconomic Variables in India: A Cointegration Analysis

2018 ◽  
Vol 4 (02) ◽  
Author(s):  
Chittaranjan Nayak ◽  
Manaswini Panda
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Empirical Support ◽  
Private Investment ◽  
Cointegration Analysis ◽  
Series Data ◽  
Crowding Out ◽  
Fiscal Deficit ◽  
Fiscal Consolidation ◽  
The Impact

Fiscal consolidation is in the forefront of policy discussion in India since 1990s. But the debate on fiscal consolidation and its real effects has been unable to attain any culmination so far on analytical as well as empirical grounds. The present paper tries to examine the impact of fiscal consolidation on growth, inflation, private investment, and exchange rate in India by analysing a time series data for the period from 1980-81 to 2013-14. The paper observes that there exists a long run relationship between GDP, fiscal consolidation, inflation and private investment. Fiscal deficit reduces GDP significantly. This finding gives empirical support to the neoclassical school of thought. However, the paper does not find any significant crowding-out evidence in India. The conclusion as such is sensitive to lag selection, and inclusion of variables. Although necessary diagnostic checking has been done, a robust analysis warrants a longer time series. The question remains inconclusive that if fiscal deficit does not cause significant crowding-out of private investment, then what are the channels of its negative influence on GDP.

scholarly journals A Robust Method for Generating High-Spatiotemporal-Resolution Surface Reflectance by Fusing MODIS and Landsat Data

2020 ◽  
Vol 12 (14) ◽  
pp. 2312
Author(s):  
Junming Yang ◽  
Yunjun Yao ◽  
Yongxia Wei ◽  
Yuhu Zhang ◽  
Kun Jia ◽  
...  
Keyword(s):  
Time Series ◽  
Data Fusion ◽  
Land Surface ◽  
Time Series Data ◽  
Temporal Variations ◽  
Series Data ◽  
Surface Reflectance ◽  
Spatiotemporal Resolution ◽  
Ecological Processes ◽  
Clustering Model

The methods for accurately fusing medium- and high-spatial-resolution satellite reflectance are vital for monitoring vegetation biomass, agricultural irrigation, ecological processes and climate change. However, the currently existing fusion methods cannot accurately capture the temporal variation in reflectance for heterogeneous landscapes. In this study, we proposed a new method, the spatial and temporal reflectance fusion method based on the unmixing theory and a fuzzy C-clustering model (FCMSTRFM), to generate Landsat-like time-series surface reflectance. Unlike other data fusion models, the FCMSTRFM improved the similarity of pixels grouped together by combining land cover maps and time-series data cluster algorithms to define endmembers. The proposed method was tested over a 2000 km2 study area in Heilongjiang Provence, China, in 2017 and 2018 using ten images. The results show that the accuracy of the FCMSTRFM is better than that of the popular enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) (correlation coefficient (R): 0.8413 vs. 0.7589; root mean square error (RMSE): 0.0267 vs. 0.0401) and the spatial-temporal data fusion approach (STDFA) (R: 0.8413 vs. 0.7666; RMSE: 0.0267 vs. 0.0307). Importantly, the FCMSTRFM was able to maintain the details of temporal variations in complicated landscapes. The proposed method provides an alternative method to monitor the dynamics of land surface variables over complicated heterogeneous regions.

The Impact of FinTech on Economic Performance and Financial Stability in MENA Zone

2020 ◽  
pp. 253-277 ◽  
Author(s):  
Souhaila Kammoun ◽  
Sahar Loukil ◽  
Youssra Ben Romdhane Loukil
Keyword(s):  
Economic Performance ◽  
Financial Stability ◽  
Time Series Data ◽  
Freedom Of Expression ◽  
Empirical Support ◽  
Multiple Regression Model ◽  
Series Data ◽  
Positive Role ◽  
The Impact

This chapter deliberates on the effects of FinTech on economic performance in the context of political instability in MENA zone countries. Using a multiple regression model to estimate time series data based on a sample of 10 MENA zone countries for 2011, 2014, and 2017, the study contends that FinTech's lending activities increase inflation and that this effect could be interestingly moderated by sound policies and regulations. In addition, the authors find empirical support for the FinTech's role as a driver of economic growth and a breeding ground for innovative projects in a context of freedom of expression, association, and media. In terms of practical implications, decision makers are asked to formulate and implement sound policies and regulations that permit and promote the positive role of FinTech in terms of economic performance.

Temporal variations in benthic assemblages and processes

2021 ◽  
pp. 105-118
Author(s):  
Simon F. Thrush ◽  
Judi E. Hewitt ◽  
Conrad A. Pilditch ◽  
Alf Norkko
Keyword(s):  
Time Series Data ◽  
Temporal Variations ◽  
Ecosystem Dynamics ◽  
Series Data ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Benthic Assemblages ◽  
Changes Over Time ◽  
Insight Into

Demonstrating changes over time in soft-sediment ecosystems is critical to understanding ecosystem dynamics and predicting how they may change. Monitoring is thus an essential process providing insight into how complex ecological systems change and has important implications in adaptive management, impact assessment and stewardship. The chapter describes how both slow and fast processes operate in soft sediments and drive changes across multiple time scales. The role of time series data in helping to understand detailed short-term studies is discussed. The interactions between space and time have important implications in study design, interpretation and accounting for inconsistency in results. The chapter finishes by discussing two types of temporal change of significant concern these days due to their implications for resilience and ecosystem dynamics: tipping points and hysteresis.

The Impact of FinTech on Economic Performance and Financial Stability in MENA Zone

2021 ◽  
pp. 70-93
Author(s):  
Souhaila Kammoun ◽  
Sahar Loukil ◽  
Youssra Ben Romdhane Loukil
Keyword(s):  
Economic Performance ◽  
Financial Stability ◽  
Time Series Data ◽  
Freedom Of Expression ◽  
Empirical Support ◽  
Multiple Regression Model ◽  
Series Data ◽  
Positive Role ◽  
The Impact

This chapter deliberates on the effects of FinTech on economic performance in the context of political instability in MENA zone countries. Using a multiple regression model to estimate time series data based on a sample of 10 MENA zone countries for 2011, 2014, and 2017, the study contends that FinTech's lending activities increase inflation and that this effect could be interestingly moderated by sound policies and regulations. In addition, the authors find empirical support for the FinTech's role as a driver of economic growth and a breeding ground for innovative projects in a context of freedom of expression, association, and media. In terms of practical implications, decision makers are asked to formulate and implement sound policies and regulations that permit and promote the positive role of FinTech in terms of economic performance.

Globalization, role of institutions and economic performance in Indian economy

2019 ◽  
Vol 11 (1) ◽  
pp. 82-100 ◽  
Author(s):  
Madhu Sehrawat ◽  
A.K. Giri
Keyword(s):  
Economic Growth ◽  
Economic Performance ◽  
Time Series Data ◽  
Empirical Support ◽  
Institutional Quality ◽  
Series Data ◽  
Content Type ◽  
Indian Economy ◽  
Integration Test ◽  
Short Run

PurposeUsing time series data for the period 1982-2016, this study aims to explore the effect of globalization, institutional quality on economic performance for Indian economy by endogenizing financial development.Design/methodology/approachThe stationarity properties of the variables are tested by Saikkonen and Lütkepohl unit root test, and the co-integration test proposed by Bayer–Hanck (2013) is used to check the long- and short-run relationship among the variables. The robustness is established by autoregressive distributed lag approach (ARDL), and the Granger causality test is used to assess the causal relationship among the variables.FindingsThe empirical findings indicate the existence of the co-integrating relationship among the variables, and the ARDL estimates reveal that both globalization and institutional quality act as important key drivers for India’s economic performance. However, the institutional quality does not affect the short-run economic growth.Research limitations/implicationsThe study finds that institutional quality and globalization index are crucial to accelerate economic performance. Therefore, policy efforts should be focused on the improvement of these indicators by offering protection of property rights, reduction in government corruption, reducing political instability, price stability and stable macroeconomic environment. This study recommends that policy should be geared toward development of financial sector, promotion of financial integration, which will create the environment for the efficient allocation of credit.Originality/valueThis study provides empirical support for the proposition that both globalization and institutional quality matter for India’s emerging economic growth by taking account of the structural break.

scholarly journals Are Fiscal Deficits Really Inflationary? An Investigation Into Ethiopia’s Experience

2020 ◽  
Vol 11 (3) ◽  
pp. 11-24
Author(s):  
Minyahil Alemu
Keyword(s):  
Money Supply ◽  
Time Series Data ◽  
Empirical Support ◽  
Developed Countries ◽  
Series Data ◽  
Budget Deficits ◽  
Least Squares Regression ◽  
Fiscal Deficits ◽  
Long Run ◽  
Domestic Capital

AbstractThis study establishes long-run relations between budget deficits and inflation, while controlling for money supply owing to the justified links between deficits and money supply especially for developing countries. We employed time series data with temporal coverage of 1980-2018. Augmented Dickey Fuller has tested nonstationary for all series, but with all stationary at first difference. The Engle-Granger (1981) methodology for Cointegration tested long-run relation between budget deficits, money supply and inflation. Due to Laney and Willet (1983), the conventional least squares regression was adopted to estimate parameters of long-run equation. The results evidenced that fiscal deficits and money supply have been at the root of galloping inflation in Ethiopia. Besides, budget deficits have been the root cause of money supply growth in Ethiopia; while giving empirical support to the hypothesis that, governments of least developed countries resort to monetize large portion of their deficits. There is a need to reform the fiscal aspect of the government, if the mounting rate of deficits has to be lessened. Budgetary imbalances can be rectified through enhancement of domestic capital market and setting limits on central bank borrowing. Besides, it could be vital to expand the tax base as well as intensify efficiency of the existing tax system in the country.

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