scholarly journals An improved neutral landscape model for recreating real landscapes and generating landscape series for spatial ecological simulations

2016 ◽  
Vol 6 (11) ◽  
pp. 3808-3821 ◽  
Author(s):  
Maarten J. van Strien ◽  
Cornelis T. J. Slager ◽  
Bauke de Vries ◽  
Adrienne Grêt-Regamey
2019 ◽  
Vol 117 ◽  
pp. 1-13 ◽  
Author(s):  
Patrick F. McKenzie ◽  
Matthew J. Duveneck ◽  
Luca L. Morreale ◽  
Jonathan R. Thompson

2005 ◽  
Vol 37 (4) ◽  
pp. 441-444 ◽  
Author(s):  
Darin R Rokyta ◽  
Paul Joyce ◽  
S Brian Caudle ◽  
Holly A Wichman

2017 ◽  
Vol 609 ◽  
pp. 1483-1499 ◽  
Author(s):  
Kevin Coleman ◽  
Shibu E. Muhammed ◽  
Alice E. Milne ◽  
Lindsay C. Todman ◽  
A. Gordon Dailey ◽  
...  

2019 ◽  
Vol 44 (3) ◽  
pp. 92-95
Author(s):  
Hua Wei

In order to find a way to combine traditional culture with modern living needs, taking “Chinese painting” as the breakthrough point, through the study of the development process and artistic characteristics of Chinese painting, four aspects of classical philosophy, natural landscape image, brush and ink composition artistic conception, and abstract aesthetic conception contained in Chinese painting are summed up. The results of the study provide enlightenment for contemporary residential landscape design, and summarize the methods of creating Chinese paintings in residential landscape design. Thus, a residential landscape model with the characteristics of “Chinese painting” is found out.


Author(s):  
Carl Fitz ◽  
Fred Sklar ◽  
T. Waring ◽  
Alexey Voinov ◽  
Robert Costanza ◽  
...  
Keyword(s):  

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Dehua Gao ◽  
Flaminio Squazzoni ◽  
Xiuquan Deng

Organizational routines are means through which organizations can reutilize best practices and so their replication, i.e., duplicating beneficial routines across context, is a key value-creating strategy. However, it is difficult to map network effects on routine replication. Here, we investigated routine replicating dynamics considering two types of network contexts, namely, (1) connections between different (geographically distributed) units in a decentralized organization and (2) the coupling relation between routines, i.e., a bundle of different routines involved in each unit. By considering routine replication as one kind of template-based activities between different units, we examined interrelations between routines with a NK-based fitness landscape model. Our results show that when there is an appropriate level of absorptive capacities (i.e., when organizations are capable of identifying and acquiring externally generated knowledge), there is an optimal combination of these two types of networks, which is beneficial to routine replicating practices and organization adaptation. Furthermore, we also found that intraorganizational variations, including template-duplicating errors and innovative activities, are instrumental to enhance adaptive changes. Our findings suggest measures to control and manage best practice diffusion across organizations.


2015 ◽  
Vol 8 (7) ◽  
pp. 5535-5575
Author(s):  
J. E. M. S. Nabel

Abstract. Models used to investigate impacts of climatic changes on spatio-temporal vegetation dynamics need to balance required accuracy with computational feasibility. To enhance the computational efficiency of these models, upscaling methods are required that maintain key fine-scale processes influencing vegetation dynamics. In this paper, an adjustable method – the dynamic two-layer classification concept (D2C) – for the upscaling of time- and space-discrete models is presented. D2C aims to separate potentially repetitive calculations from those specific to single grid cells. The underlying idea is to extract processes that do not require information about a grid cell's neighbourhood to a reduced-size non-spatial layer, which is dynamically coupled to the original two-dimensional layer. The size of the non-spatial layer is thereby adaptive and depends on dynamic classifications according to pre-specified similarity criteria. I present how D2C can be used in a model implementation on the example of TreeMig-2L, a new, efficient version of the intermediate-complexity forest-landscape model TreeMig. To discuss the trade-off between computational expenses and accuracy, as well as the applicability of D2C, I compare different model stages of TreeMig-2L via simulations of two different application scenarios. This comparison of different model stages demonstrates that applying D2C can strongly reduce computational expenses of processes calculated on the new non-spatial layer. D2C is thus a valuable upscaling method for models and applications in which processes requiring information about the neighbourhood constitute the minor share of the overall computational expenses.


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