An innovative computer design for modeling forest landscape change in very large spatial extents with fine resolutions
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Ecological Modelling. 222(15): 2623-2630.
Although forest landscape models (FLMs) have benefited greatly from ongoing advances of computer technology and software engineering, computing capacity remains a bottleneck in the design and development of FLMs. Computer memory overhead and run time efficiency are primary limiting factors when applying forest landscape models to simulate large landscapes with fine spatial resolutions and great vegetation detail. We introduce LANDIS PRO 6.0, a landscape model that simulates forest succession and disturbances on a wide range of spatial and temporal scales. LANDIS PRO 6.0 improves on existing forest landscape models with two new data structures and algorithms (hash table and run-length compression). The innovative computer design enables LANDIS PRO 6.0 to simulate very large (>108 ha) landscapes with a 30-m spatial resolution, which to our knowledge no other raster forest landscape models can do. We demonstrate model behavior and performance through application to five nested forest landscapes with varying sizes (from 1 million to 100 million 0.09-ha cells) in the southern Missouri Ozarks. The simulation results showed significant and variable effects of changing spatial extent on simulated forest succession patterns. Results highlighted the utility of a model like LANDIS PRO 6.0 that is capable of efficiently simulating large landscapes and scaling up forest landscape processes to a common regional scale of analysis. The programming methodology presented here may significantly advance the development of next generation of forest landscape models.
KeywordsForest landscape model; Simulation extent; Data structure; Scaling; LANDIS PRO
Yang, Jian; He, Hong S.; Shifley, R. Stephen; Thompson, Frank R.; Zhang, Yangjian. 2011. An innovative computer design for modeling forest landscape change in very large spatial extents with fine resolutions. Ecological Modelling. 222(15): 2623-2630. https://doi.org/10.1016/j.ecolmodel.2011.04.032.