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Exercise: Phenological mapping and model validation

Authors: Barker, Brittany;

Exercise: Phenological mapping and model validation

Abstract

This exercise was developed for an Ecological Systems Modeling course taught at Oregon State University in 2023 and 2024 to provide an example of how multiple forms of phenology data can be integrated, visualized, and analyzed. It incorporates in situ phenology observations and gridded predictions of growing degree-days and phenophases to address the following learning outcomes: 1) describe and implement the steps in developing, implementing, and validating an ecological systems model; 2) visualize and critically evaluate model predictions and potential sources of model error; and 3) describe how models may be applied towards understanding and solving real-world ecological problems. The exercise has 10 questions that assess student learning outcomes. The exercise is an R Markdown file (.Rmd) that can be opened within RStudio (Posit). Required R packages are in the first code block in the R Markdown document. IMPORTANT: as currently written, the exercise uses the here package for project relative paths. You will need to follow the below instructions to use the lesson without editing any of the paths: Unzip the zip file - this will create a folder named "phenological_mapping" Open the R project ("phenological_mapping.Rproj") in RStudio Open the R Markdown file ("phenological_mapping.Rmd") in RStudio You should now be able to open files (e.g., in the "images" folder) and knit the document Do NOT move or delete any of the subfolders or files The time required for students to complete the exercise will depend on their level of experience with using R and on their knowledge of phenology and modeling. For a class composed of graduate students, it may take approximately 1 - 1.5 hours to complete.

Related Organizations
Keywords

model validation, lesson, modeling, insects, pests, phenology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average