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R has been widely used by ecologists. It i … R has been widely used by ecologists. It is a powerful language to build statistical models. However, R applications in landscape ecology are relatively limited. In this model clinic, we will introduce R programming and two recently developed packages “NLMR” and “landscapetools” in generating and visualizing neutral landscapes. </br>Neutral models are useful tools for testing the effect of different spatial processes on observed patterns, as they create landscape patterns in the absence of specific processes. Comparisons between a landscape model and a neutral model simulation will provide insights into how these specific processes affect landscape patterns. Different algorithms exist to generate neutral landscapes and they have been traditionally included in different programs. Now the NLMR package in R integrated all these different algorithms into one place. </br>In addition to providing instructions on how to use R, “NLMR and “landscapetools packages”, we will showcase real-world examples on neutral landscapes’ applications in ecology, such as predicting coastal wetland change in response to sea-level rise.land change in response to sea-level rise. +
wei.wu@usm.edu +
CSDMS 2021: Changing Landscapes and Seascapes: Modeling for Discovery, Decision Making, and Communication +
The University of Southern Mississippi +
Clinic +
Mississippi +
Introduction to R programming and R applications in landscape ecology +
United States +
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15:55:05, 22 January 2021 +
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22:33:45, 11 June 2025 +
Terrestrial Working Group +, Coastal Working Group +, Marine Working Group +, Education and Knowledge Transfer (EKT) Working Group +, Cyberinformatics and Numerics Working Group +, Hydrology Focus Research Group +, Chesapeake Focus Research Group +, Critical Zone Focus Research Group +, Human Dimensions Focus Research Group +, Geodynamics Focus Research Group +, Ecosystem Dynamics Focus Research Group +, Coastal Vulnerability Initiative +, Continental Margin Initiative +, Artificial Intelligence & Machine Learning Initiative +, Modeling Platform Interoperability Initiative + and River Network Modeling Initiative +
