Landscape as a model : the importance of geometry Export

@article{Holland2007a, abstract = {In all models, but especially those used to predict uncertain processes (e.g. climate change, non-native species establishment), it is important to identify and remove any sources of bias which may confound results. This is critical in models designed to help support decision making. The geometry used to represent virtual landscapes in spatially explicit models is a potential source of bias. The majority of spatial models use regular square geometry although regular hexagonal landscapes have been used. However, there are other ways in which space can be represented in spatially explicit models. For the first time, we explicitly compare the range of alternative geometries available to the modeller, and present a mechanism by which uncertainty in the representation of landscapes can be incorporated. We test how geometry can affect cell-to-cell movement across homogeneous virtual landscapes and compare regular geometries with a suite of irregular mosaics. We show that regular geometries have the potential to systematically bias the direction and distance of movement whilst even individual instances of landscapes with irregular geometry do not. We also examine how geometry can affect the gross representation of real-world landscapes, and again show that individual instances of regular geometries will always create qualitative and quantitative errors. These can be reduced by the use of multiple randomized instances, though this still creates scale dependent biases. In contrast, virtual landscapes formed using irregular geometries can represent complex real world landscapes without error. We found virtual landscapes with regular geometry to be a source of potential bias. This bias can be effectively eliminated by sub-dividing virtual landscapes using irregular geometry. The use of irregular geometry appears to offer spatial modellers other potential advantages, which are as yet underdeveloped. We recommend their use in all spatially explicit models, but especially for predictive models which are used in decision making.}, author = {Holland, Pen and Aegerter, James and Dytham, Calvin and Smith, Graham C.}, citeulike-article-id = {1624970}, citeulike-linkout-0 = {http://dx.doi.org/10.1371/journal.pcbi.0030200.eor}, citeulike-linkout-1 = {http://dx.doi.org/10.1371/journal.pcbi.0030200}, doi = {10.1371/journal.pcbi.0030200.eor}, journal = {PLoS Computational Biology}, keywords = {geographically-explicit, landscape, modeling, recommended, simulation, update-when-published}, month = {September}, number = {10}, pages = {e200+}, posted-at = {2007-09-05 19:56:27}, priority = {2}, title = {Landscape as a model : the importance of geometry}, url = {http://dx.doi.org/10.1371/journal.pcbi.0030200.eor}, volume = {3}, year = {2007} }

TY - JOUR ID - Holland2007a L3 - citeulike-article-id:1624970 N2 - In all models, but especially those used to predict uncertain processes (e.g. climate change, non-native species establishment), it is important to identify and remove any sources of bias which may confound results. This is critical in models designed to help support decision making. The geometry used to represent virtual landscapes in spatially explicit models is a potential source of bias. The majority of spatial models use regular square geometry although regular hexagonal landscapes have been used. However, there are other ways in which space can be represented in spatially explicit models. For the first time, we explicitly compare the range of alternative geometries available to the modeller, and present a mechanism by which uncertainty in the representation of landscapes can be incorporated. We test how geometry can affect cell-to-cell movement across homogeneous virtual landscapes and compare regular geometries with a suite of irregular mosaics. We show that regular geometries have the potential to systematically bias the direction and distance of movement whilst even individual instances of landscapes with irregular geometry do not. We also examine how geometry can affect the gross representation of real-world landscapes, and again show that individual instances of regular geometries will always create qualitative and quantitative errors. These can be reduced by the use of multiple randomized instances, though this still creates scale dependent biases. In contrast, virtual landscapes formed using irregular geometries can represent complex real world landscapes without error. We found virtual landscapes with regular geometry to be a source of potential bias. This bias can be effectively eliminated by sub-dividing virtual landscapes using irregular geometry. The use of irregular geometry appears to offer spatial modellers other potential advantages, which are as yet underdeveloped. We recommend their use in all spatially explicit models, but especially for predictive models which are used in decision making. IS - 10 JF - PLoS Computational Biology TI - Landscape as a model : the importance of geometry VL - 3 SP - e200 KW - geographically-explicit KW - landscape KW - modeling KW - recommended KW - simulation KW - update-when-published AU - Holland, Pen AU - Aegerter, James AU - Dytham, Calvin AU - Smith, Graham PY - 2007/09/01/ UR - http://dx.doi.org/10.1371/journal.pcbi.0030200.eor ER -