Simulating Large-Scale Population Dynamics Using Small-Scale Data

2002 ◽  
pp. 275-301 ◽  
Author(s):  
Graham E. Forrester ◽  
Mark A. Steele ◽  
Richard R. Vance
1999 ◽  
Vol 382 ◽  
pp. 307-329 ◽  
Author(s):  
JUDITH K. FOSS ◽  
K. B. M. Q. ZAMAN

The large- and small-scale vortical motions produced by ‘delta tabs’ in a two-stream shear layer have been studied experimentally. An increase in mixing was observed when the base of the triangular shaped tab was affixed to the trailing edge of the splitter plate and the apex was pitched at some angle with respect to the flow axis. Such an arrangement produced a pair of counter-rotating streamwise vortices. Hot-wire measurements detailed the velocity, time-averaged vorticity (Ωx) and small-scale turbulence features in the three-dimensional space downstream of the tabs. The small-scale structures, whose scale corresponds to that of the peak in the dissipation spectrum, were identified and counted using the peak-valley-counting technique. The optimal pitch angle, θ, for a single tab and the optimal spanwise spacing, S, for a multiple tab array were identified. Since the goal was to increase mixing, the optimal tab configuration was determined from two properties of the flow field: (i) the large-scale motions with the maximum Ωx, and (ii) the largest number of small-scale motions in a given time period. The peak streamwise vorticity magnitude [mid ]Ωx−max[mid ] was found to have a unique relationship with the tab pitch angle. Furthermore, for all cases examined, the overall small-scale population was found to correlate directly with [mid ]Ωx−max[mid ]. Both quantities peaked at θ≈±45°. It is interesting to note that the peak magnitude of the corresponding circulation in the cross-sectional plane occurred for θ≈±90°. For an array of tabs, the two quantities also depended on the tab spacing. An array of contiguous tabs acted as a solid deflector producing the weakest streamwise vortices and the least small-scale population. For the measurement range covered, the optimal spacing was found to be S≈1.5 tab widths.


2005 ◽  
Vol 95 (6) ◽  
pp. 579-587 ◽  
Author(s):  
L. Winder ◽  
G.J.K. Griffiths ◽  
J.N. Perry ◽  
C.J. Alexander ◽  
J.M. Holland ◽  
...  

AbstractA field-scale study of the spatially explicit interaction between the carabid Poecilus cupreus Linnaeus, and two common aphid species (Sitobion avenae (Fabricius) and Metopolophium dirhodum (Walker)) in winter wheat was conducted. All three species showed considerable spatial pattern at the field scale. Activity-density of P. cupreus was an order of magnitude higher in the central part of the field compared to its periphery. Where P. cupreus activity-density was highest, S. avenae and M. dirhodum population peaks were delayed. Additionally, in the case of M. dirhodum, lower maximum counts were evident where P. cupreus activity-density was highest. An analysis of the movement of individual P. cupreus using release–recapture indicated that those beetles within the centre of the field exhibited reduced displacement, which may have caused the generation or maintenance of spatial pattern. Crop density was also measured throughout the field. Although crop density had no large-scale spatial pattern, its variability at the small-scale was consistent with an influence on aphid population dynamics. This study demonstrates empirically that both large-scale spatially explicit and small-scale localized processes influenced aphid population dynamics simultaneously.


Oikos ◽  
2015 ◽  
Vol 124 (9) ◽  
pp. 1160-1170 ◽  
Author(s):  
Maria A. Riolo ◽  
Pejman Rohani ◽  
Mark D. Hunter

Author(s):  
De-Ming Liang ◽  
Yu-Feng Li

Label propagation spreads the soft labels from few labeled data to a large amount of unlabeled data according to the intrinsic graph structure. Nonetheless, most label propagation solutions work under relatively small-scale data and fail to cope with many real applications, such as social network analysis, where graphs usually have millions of nodes. In this paper, we propose a novel algorithm named \algo to deal with large-scale data. A lightweight iterative process derived from the well-known stochastic gradient descent strategy is used to reduce memory overhead and accelerate the solving process. We also give a theoretical analysis on the necessity of the warm-start technique for label propagation. Experiments show that our algorithm can handle million-scale graphs in few seconds while achieving highly competitive performance with existing algorithms.


2005 ◽  
Vol 74 (1) ◽  
pp. 22-30 ◽  
Author(s):  
NICLAS JONZÉN ◽  
ANTHONY R. POPLE ◽  
GORDON C. GRIGG ◽  
HUGH P. POSSINGHAM

2009 ◽  
Vol 78 (1) ◽  
pp. 172-181 ◽  
Author(s):  
Benjamin Zuckerberg ◽  
William F. Porter ◽  
Kimberley Corwin

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