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R package creation supports cutting edge science Active

By Upper Midwest Environmental Sciences Center December 11, 2023

R is a free software that is used to run statistical analyses and models as well as create figures such as graphs and maps that can be used to display the data collected. While using this software researchers can also use downloadable packages that increase the number of analyses and models they can perform. Statisticians and researchers collaborate to create new packages that can be used by other researchers while using R.

Example climatchR workflow
Sources/Usage: Public Domain. View Media Details
Conceptual diagram of workflow using climatchR. Input data examples are on the left. Example climatchR functions are listed in gray area, which are used to calculate the CLIMATCH scores, output by the package.

Climate matching with the climatchR R package

Principal Investigator – Richard Erickson

Climate matching is a method for understanding species distributions and ranges and may be used as part of horizon scanning. Horizon scanning is the process of examining potential risk of invasion of new invasive species. Preventing new invasive species invasion requires less time and resources than attempting to control and remove established invasive species. Horizon scanning allows resource managers at the U.S. Fish and Wildlife Service to identify new potential invasive species and create measures to prevent their invasion. Often resource managers use similarities in the climates of both current distributions of species and possible invasive species to determine new possible invasive species using horizon scanning and other risk assessment techniques. Current climate matching methods are labor-intensive because it requires handpicked data and heavy data manipulation. However, climate matching could be completed in a relatively inexpensive and quick way by automating the process.

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Example climatch scores for a species more likely to have climate matches with Florida and Texas in the United States.
Sources/Usage: Public Domain. View Media Details
Example climatch scores for a species across the contiguous United States.

Presence-absence surveys are commonly used to estimate the spatial distribution of a species. However, during a field survey some organisms, especially rare or elusive species, can be missed; increasing the chance of error in the data collected. To combat the potential error, researchers will regularly visit sites and collect more data that will later be analyzed using occupancy models. Occupancy models are used by researchers to estimate the true occupancy of a species and accounts for imperfect detection of organisms in a study. Typically, occupancy models are two levels, however, when using environmental DNA (eDNA) due to the sample processing methods a third level is added to the occupancy model. This project developed an R package to fit three level models.

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Image: Bighead Carp
Sources/Usage: Public Domain. View Media Details
Bighead carp are a large and troublesome invasive species from Asia found in the great rivers of the central United States.

Occupancy models are used by researchers to estimate the true occupancy of a species and accounts for imperfect detection of organisms in a study. Researchers will visit sampling sites to collect species detection data (e.g., species count). Occupancy models can predict the detection probability (probability of finding a species at a specific time and site) and occupancy (probability a species occurs at a site) of select species. Due to the sample processing methods to detect environmental DNA a third level is added to the occupancy models that typically contain two. This package expands upon EDNAOCCUPANCY package to allow greater freedom in prediction equations as well as using a different numerical method for fitting the model.

 

R is a free software that is used to run statistical analyses and models as well as create figures such as graphs and maps that can be used to display the data collected. While using this software researchers can also use downloadable packages that increase the number of analyses and models they can perform. Statisticians and researchers collaborate to create new packages that can be used by other researchers while using R.

Example climatchR workflow
Sources/Usage: Public Domain. View Media Details
Conceptual diagram of workflow using climatchR. Input data examples are on the left. Example climatchR functions are listed in gray area, which are used to calculate the CLIMATCH scores, output by the package.

Climate matching with the climatchR R package

Principal Investigator – Richard Erickson

Climate matching is a method for understanding species distributions and ranges and may be used as part of horizon scanning. Horizon scanning is the process of examining potential risk of invasion of new invasive species. Preventing new invasive species invasion requires less time and resources than attempting to control and remove established invasive species. Horizon scanning allows resource managers at the U.S. Fish and Wildlife Service to identify new potential invasive species and create measures to prevent their invasion. Often resource managers use similarities in the climates of both current distributions of species and possible invasive species to determine new possible invasive species using horizon scanning and other risk assessment techniques. Current climate matching methods are labor-intensive because it requires handpicked data and heavy data manipulation. However, climate matching could be completed in a relatively inexpensive and quick way by automating the process.

___________________________________________________________

Example climatch scores for a species more likely to have climate matches with Florida and Texas in the United States.
Sources/Usage: Public Domain. View Media Details
Example climatch scores for a species across the contiguous United States.

Presence-absence surveys are commonly used to estimate the spatial distribution of a species. However, during a field survey some organisms, especially rare or elusive species, can be missed; increasing the chance of error in the data collected. To combat the potential error, researchers will regularly visit sites and collect more data that will later be analyzed using occupancy models. Occupancy models are used by researchers to estimate the true occupancy of a species and accounts for imperfect detection of organisms in a study. Typically, occupancy models are two levels, however, when using environmental DNA (eDNA) due to the sample processing methods a third level is added to the occupancy model. This project developed an R package to fit three level models.

___________________________________________________________

Image: Bighead Carp
Sources/Usage: Public Domain. View Media Details
Bighead carp are a large and troublesome invasive species from Asia found in the great rivers of the central United States.

Occupancy models are used by researchers to estimate the true occupancy of a species and accounts for imperfect detection of organisms in a study. Researchers will visit sampling sites to collect species detection data (e.g., species count). Occupancy models can predict the detection probability (probability of finding a species at a specific time and site) and occupancy (probability a species occurs at a site) of select species. Due to the sample processing methods to detect environmental DNA a third level is added to the occupancy models that typically contain two. This package expands upon EDNAOCCUPANCY package to allow greater freedom in prediction equations as well as using a different numerical method for fitting the model.