2016
DOI: 10.1007/s10021-016-0066-z
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Spatially Explicit Modeling in Ecology: A Review

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Cited by 106 publications
(74 citation statements)
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“…Predicting how feedbacks may change the stability of tropical forests and savannas in a future with stronger and more frequent climatic extremes (Bathiany, Dakos, Scheffer, & Lenton, ; Huang, Xie, Hu, Huang, & Huang, ) is an urgent challenge. To better understand the emergent effects of feedbacks between fire, herbivores, and tree cover, we need a modeling framework that can well integrate spatial dynamics (DeAngelis & Yurek, ) across rainfall gradients. Small‐scale theoretical models, including spatially explicit ones (e.g., Schertzer et al., ), have been used to study complex fire dynamics, but they lack a large‐scale quantification of the complete feedback loop.…”
Section: Introductionmentioning
confidence: 99%
“…Predicting how feedbacks may change the stability of tropical forests and savannas in a future with stronger and more frequent climatic extremes (Bathiany, Dakos, Scheffer, & Lenton, ; Huang, Xie, Hu, Huang, & Huang, ) is an urgent challenge. To better understand the emergent effects of feedbacks between fire, herbivores, and tree cover, we need a modeling framework that can well integrate spatial dynamics (DeAngelis & Yurek, ) across rainfall gradients. Small‐scale theoretical models, including spatially explicit ones (e.g., Schertzer et al., ), have been used to study complex fire dynamics, but they lack a large‐scale quantification of the complete feedback loop.…”
Section: Introductionmentioning
confidence: 99%
“…Nevertheless, most classifications of quantitative models typically combine features of two main axes, which are sufficient to recognize differences between quantitative models and establish the basis for the simplified taxonomy that frames this review ( Figure 1). Highly detailed mechanistic models include individual-based models, such as those exploring potential strategies for using gene-drives to eradicate populations of invasive species, whereas correlative models are examples of more simple models (DeAngelis & Yurek, 2017;Dormann et al, 2012;Evans et al, 2013;Peck, 2000;Prowse et al, 2017). Highly detailed mechanistic models include individual-based models, such as those exploring potential strategies for using gene-drives to eradicate populations of invasive species, whereas correlative models are examples of more simple models (DeAngelis & Yurek, 2017;Dormann et al, 2012;Evans et al, 2013;Peck, 2000;Prowse et al, 2017).…”
Section: A Concise Taxonomy Of Quantitative Modelsmentioning
confidence: 99%
“…Balancing the use of all the relevant available data with model complexity supports conservation management in a "wicked world". For instance, an overly complex model could result in model over-fitting (e.g., in species distribution models; Radosavljevic & Anderson, 2014) and difficulties in assessing the influence of different sub-processes on the overall system dynamics (e.g., spatially-explicit individual-based simulation models; Prowse et al, 2016;DeAngelis & Yurek, 2017). It is therefore helpful to incorporate as much pertinent information as possible in the model.…”
Section: Model Specificationmentioning
confidence: 99%
“…Laniak and others (2013) described the goal of integrated environmental modeling as "to develop and organize relevant knowledge and information and apply it to explain, explore, and predict the behavior of environmental systems in response to human and natural sources of stress" (page 3). Some examples of modeling relevant to the resource interrelationships that might be considered in an MRA include (1) models of how land-use change affects water quality (Booth and others, 2011), (2) spatially explicit population models that evaluate the links between landscape and habitat changes and the populations of specific animals of interest (Turner and others, 1995;Chandler and Clark, 2014;DeAngelis and Yurek, 2017), (3) models of the impacts of energy development on the landscape (Hernandez and others, 2015) and on habitats and species (Copeland and others, 2009), and (4) models that connect soil and water conditions to watershed -scale issues and to ecosystem services (Francesconi and others, 2016). Although much exciting work is being done in this area, robust integrated modeling has also been identified as one of the "grand challenges" for integrated science at the USGS (Jenni and others, 2017).…”
Section: Development Of Multi-resource Analysis Components 47mentioning
confidence: 99%