Modelling adaptive, spatially aware, and mobile agents: Elk migration in Yellowstone

Bennett, David A.; Tang, Wenwu

doi:10.1080/13658810600830806

Cited by 95 publications

(88 citation statements)

References 67 publications

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“…Whilst some landscape ecological studies have incorporated the effect of temporal environmental dynamics (e.g. [286][287][288][289]), such studies are rare and have generally focussed on environmental variability over short time periods. Where the longer term impacts of environmental or landscape change on animal populations are considered, studies rarely treat the landscape as a temporally dynamic system [262,290], instead running separate simulations with and without a prescribed landscape change (e.g.…”

Section: Discussionmentioning

confidence: 99%

Emerging Opportunities for Landscape Ecological Modelling

Synes

Brown

Watts

et al. 2016

Curr Landscape Ecol Rep

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Landscape ecological modelling provides a vital means for understanding the interactions between geographical, climatic, and socio-economic drivers of land-use and the dynamics of ecological systems. This growing field is playing an increasing role in informing landscape spatial planning and management. Here, we review the key modelling approaches that are used in landscape modelling and in ecological modelling. We identify an emerging theme of increasingly detailed representation of process in both landscape and ecological modelling, with complementary suites of modelling approaches ranging from correlative, through aggregated process based approaches to models with much greater structural realism that often represent behaviours at the level of agents or individuals. We provide examples of the considerable progress that has been made at the intersection of landscape modelling and ecological modelling, while also highlighting that the majority of this work has to date exploited a relatively small number of the possible combinations of model types from each discipline. We use this review to identify key gaps in existing landscape ecological modelling effort and highlight emerging opportunities, in particular for future work to progress in novel directions by combining classes of landscape models and ecological models that have rarely been used together.

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Section: Discussionmentioning

confidence: 99%

Emerging Opportunities for Landscape Ecological Modelling

Synes

Brown

Watts

et al. 2016

Curr Landscape Ecol Rep

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“…In addition, because ABMs incorporate ecological theory, and deal with processes and mechanisms at the level of the individual, the resultant hierarchical phenomena that emerge from agents' interactions with others and their environment can naturally accommodate issues of scale (Breckling et al 2006). As an illustrative example, Bennett and Tang (2006) combined cell-and patch-based approaches to represent multi-scale environmental representation in their elk migration model. Agent elk performed local movement at the cell level, but were capable of perceiving and using greater scale, patch-level information to guide their long-distance winter migration.…”

Section: Extent Versus Resolutionmentioning

confidence: 99%

Integrating Spatial Behavioral Ecology in Agent-Based Models for Species Conservation

Semeniuk¹,

Musiani²,

Marceau³

2011

Biodiversity

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“…The model evolves in discrete time steps, with the cell states updated synchronously. The discrete and dynamic nature of CA models allows broad applications in a variety of natural phenomena and human activities, such as urban planning (Li et al, 2014), resource management (Bone and Dragićević, 2010), forest fire spread prediction (Alexandridis et al, 2008;Yassemi et al, 2008), plant invasion (Cannas et al, 2003), insect propagation (Bone et al, 2006;Pérez and Dragićević, 2011), animal migration patterns (Bennett and Tang, 2006), and landscape ecology (Parker et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Integrating remote sensing, GIS and dynamic models for landscape-level simulation of forest insect disturbance

Huang

et al. 2017

Ecological Modelling

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Huabing, "Integrating remote sensing, GIS and dynamic models for landscape-level simulation of forest insect disturbance" (2017 Cellular automata (CA) is a powerful tool for modeling the evolution of macroscopic scale phenomena as it couples time, space, and variables together while remaining in a simplified form. However, such application has remained challenging in forest insect epidemics due to the highly dynamic nature of insect behavior. Recent advances in temporal trajectory-based image analysis offer an alternative way to obtain high-frequency model calibration data. In this study, we propose an insect-CA modeling framework that integrates cellular automata, remote sensing, and Geographic Information System to understand the insect ecological processes, and tested it with measured data of mountain pine beetle (MPB) in the Rocky Mountains. The overall accuracy of the predicted MPB mortality pattern in the test years ranged from 88% to 94%, which illuminates its effectiveness in modeling forest insect dynamics. We further conducted sensitivity analysis to examine responses of model performance to various parameter settings. In our case, the ensemble random forest algorithm outperforms the traditional linear regression in constructing the suitability surface. Small neighborhood size is more effective in simulating the MPB movement behavior, indicating that short-distance is the dominating dispersal mode of MPB. The introduction of a stochastic perturbation component did not improve the model performance after testing a broad range of randomness degree, reflecting a relative compact dispersal pattern rather than isolated outbreaks. We conclude that CA with remote sensing observation is useful for landscape insect movement analyses; however, consideration of several key parameters is critical in the modeling process and should be more thoroughly investigated in future work.

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Modelling adaptive, spatially aware, and mobile agents: Elk migration in Yellowstone

Cited by 95 publications

References 67 publications

Emerging Opportunities for Landscape Ecological Modelling

Emerging Opportunities for Landscape Ecological Modelling

Integrating Spatial Behavioral Ecology in Agent-Based Models for Species Conservation

Integrating remote sensing, GIS and dynamic models for landscape-level simulation of forest insect disturbance

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