A scalable simulator for forest dynamics

Models of forest ecosystems are needed to understand how climate and land-use change can impact biodiversity. In this paper we describe an individual-based, spatially-explicit forest simulator with full accounting of both landscape context and the fine-scale processes that influence forest dynamics. Unfortunately, performing realistic forest simulations of such models is computationally infeasible. We design efficient algorithms for computing seed dispersal and light, using a plethora of techniques. These include hierarchical spatial decomposition, monopole approximation and utilizing the graphics hardware for fast geometric computations. These algorithms allow us to simulate large landscapes for long periods of time.

[1]  S. Pacala,et al.  SEEDLING RECRUITMENT IN FORESTS: CALIBRATING MODELS TO PREDICT PATTERNS OF TREE SEEDLING DISPERSION' , 1994 .

[2]  Pankaj K. Agarwal,et al.  A scalable algorithm for dispersing population , 2007, Journal of Intelligent Information Systems.

[3]  Hanan Samet,et al.  Ranking in Spatial Databases , 1995, SSD.

[4]  S. Carpenter,et al.  Ecological forecasts: an emerging imperative. , 2001, Science.

[5]  Hanan Samet,et al.  Distance browsing in spatial databases , 1999, TODS.

[6]  Nabil H. Mustafa,et al.  Hardware-assisted view-dependent map simplification , 2001, SCG '01.

[7]  Janneke HilleRisLambers,et al.  Seed Dispersal Near and Far: Patterns Across Temperate and Tropical Forests , 1999 .

[8]  S. Pacala,et al.  Forest models defined by field measurements: I. The design of a northeastern forest simulator , 1993 .

[9]  Charles D. Canham,et al.  Causes and consequences of resource heterogeneity in forests : interspecific variation in light transmission by canopy trees , 1994 .

[10]  P. Strevens Iii , 1985 .

[11]  George C. Hurtt,et al.  Reid's Paradox of Rapid Plant Migration Dispersal theory and interpretation of paleoecological records , 1998 .

[12]  Michael Wolfe,et al.  J+ = J , 1994, ACM SIGPLAN Notices.

[13]  Jon Louis Bentley,et al.  Quad trees a data structure for retrieval on composite keys , 1974, Acta Informatica.

[14]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[15]  George C. Hurtt,et al.  The consequences of recruitment limitation: reconciling chance, history and competitive differences between plants , 1995 .

[16]  L. Greengard The Rapid Evaluation of Potential Fields in Particle Systems , 1988 .

[17]  Michael C. Dietze,et al.  COEXISTENCE: HOW TO IDENTIFY TROPHIC TRADE-OFFS , 2003 .

[18]  Thomas M. Smith,et al.  Spatial applications of gap models , 1991 .

[19]  Marc Olano,et al.  Interactive multi-pass programmable shading , 2000, SIGGRAPH.

[20]  James S. Clark,et al.  FECUNDITY OF TREES AND THE COLONIZATION–COMPETITION HYPOTHESIS , 2004 .

[21]  A. Cescatti Modelling the radiative transfer in discontinuous canopies of asymmetric crowns. I. Model structure and algorithms , 1997 .

[22]  Hanan Samet,et al.  Applications of spatial data structures , 1989 .

[23]  Hanan Samet,et al.  Applications of spatial data structures - computer graphics, image processing, and GIS , 1990 .

[24]  Piet Hut,et al.  A hierarchical O(N log N) force-calculation algorithm , 1986, Nature.

[25]  J. R. Wallis,et al.  Some ecological consequences of a computer model of forest growth , 1972 .

[26]  James S. Clark,et al.  Invasion by Extremes: Population Spread with Variation in Dispersal and Reproduction , 2001, The American Naturalist.

[27]  A. Hastings Disturbance, coexistence, history, and competition for space , 1980 .

[28]  Dinesh Manocha,et al.  Fast computation of generalized Voronoi diagrams using graphics hardware , 1999, SIGGRAPH.