scholarly journals Impact of Biotic and Abiotic Factors on the Population Dynamics of Bemisia tabaci (Genn.) and Tetranychus urticae (Koch) Infested Tomato Plant Lycopersicon esculentum L. at kafr El sheikh Governorate

2018 ◽  
Vol 11 (4) ◽  
pp. 41-50
Author(s):  
Afaf Abasse ◽  
Abd-El wahab H. ◽  
Naema A. ◽  
Sawsan A. ◽  
Mohammed M.
Keyword(s):  
Population Dynamics ◽  
Lycopersicon Esculentum ◽  
Tetranychus Urticae ◽  
Bemisia Tabaci ◽  
Tomato Plant ◽  
Abiotic Factors ◽  
Biotic And Abiotic Factors ◽  
Tetranychus Urticae Koch

Toxicity of essential oil vapours to two greenhouse pests, Tetranychus urticae Koch and Bemisia tabaci Genn.

2004 ◽  
Vol 19 (2) ◽  
pp. 167-173 ◽  
Author(s):  
İrfan Aslan ◽  
Hikmet Özbek ◽  
Önder Çalmaşur ◽  
Fikrettin Şahi̇n
Keyword(s):  
Essential Oil ◽  
Tetranychus Urticae ◽  
Bemisia Tabaci ◽  
Tetranychus Urticae Koch

scholarly journals Causal drivers of Barents Sea capelin (Mallotus villosus) population dynamics on different time scales

2017 ◽  
Vol 75 (2) ◽  
pp. 621-630 ◽  
Author(s):  
Hiroko K Solvang ◽  
Sam Subbey ◽  
Anna S J Frank
Keyword(s):  
Population Dynamics ◽  
Time Scales ◽  
Barents Sea ◽  
Abiotic Factors ◽  
Time Frame ◽  
Model Fit ◽  
Statistical Methodology ◽  
Biotic And Abiotic Factors ◽  
Causal Direction ◽  
Capelin Mallotus Villosus

Abstract The dynamics of marine populations are usually forced by biotic and abiotic factors occurring at different intensity levels and time scales. Deriving the time frame within which each factor has a causal influence is important for predicting population trajectories. This paper presents a statistical methodology for establishing (i) the strength of causal coupling between population dynamics and environmental (biotic and abiotic) factors, and (ii) the time scales over which causal covariates have significant influence on the population dynamics. The methodology is based on combining a multivariate autoregressive model fit to data (to determine causal direction) with a quantification of the RPC of covariates in frequency domain (to quantify the strength of connection). The methodology is applied to test the existence of causal coupling between the capelin biomass and a selected number of covariates identified in the literature.

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