Validation of the Brown Marmorated Stink Bug survey in Washington, Utah, North Carolina, and California
Data files
Nov 01, 2024 version files 22.05 MB
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BMSB_CA.asc
11.39 MB
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BMSB_NC.asc
3 MB
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BMSB_Utah.asc
3.79 MB
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BMSB_WA.asc
3.82 MB
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California.csv
6.84 KB
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GenRoute_CA.R
6.17 KB
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GenRoute_NC.R
6.15 KB
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GenRoute_Utah.R
6.23 KB
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GenRoute_WA.R
6.28 KB
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North_Carolina.csv
2.91 KB
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README.md
2.83 KB
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Utah.csv
4.97 KB
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Washington.csv
6.15 KB
Abstract
Invasive species are particularly problematic because it is often difficult to eradicate once established, it is crucial to economically and effectively allocate resources for early monitoring and eradication programs. Given that the cost to manage an invasive species after it is established is typically 10-15 times higher (or more) than the cost to eradicate the species early during an invasion, the failure to effectively allocate resources for monitoring remains a major impediment to effective invasive species management. Ecological niche models are often used to predict the distribution of invasive species before or after they have been detected in new regions. Such models should also be used to guide surveys to promote the early detection and eradication of invasive species. Here we propose a practical framework that seamlessly uses ecological niche models to develop sampling routes that promote detection of invasive species. Our framework uses habitat suitability predictions and occurrence data on incursion populations to generate potential survey sites, which are then prioritized for sampling based on their size and suitability. The generated survey route is then displayed on an open street map platform. Our framework was developed into the “enmRoute” R package and a user-friendly website to facilitate its application, and we validated our framework with a case study. We show that integrating ecological niche models with human transport routes promotes the identification of survey sites that are predicted to collect more individuals and have a greater potential for species detection than traditional sampling approaches. The data provided here is intended to validate our platform and to optimize the Brown Marmorated Stink Bug survey in Washington, Utah, North Carolina, and California. The habitat suitability predictions for this stinkbug and detection in these four states were provided, together with the scripts that were used to generate survey routes.
README: Validation of the Brown Marmorated Stink Bug Survey in Washington, Utah, North Carolina, and California
DOI: https://doi.org/10.5061/dryad.7pvmcvf3k
Description of the data and file structure:
enmRoute could seamlessly employ habitat suitability predictions for planning field surveys. The aim of this package is to use ecological niche model habitat suitability predictions to plan the field survey of invasive species in an expected area. Our platform would promote detection and facilitate earlier eradication programs in invasive species management. We hypothesize that field surveys that account for habitat suitability predictions could promote field collections and capture more individuals in the field. Our model-based survey route accounts for habitat suitability predictions and uses practicable driving time/distance to optimize survey efforts, we hope that this package and its accompanying shiny (https://losorio.shinyapps.io/enmroute) will help field biologists design sampling routes for regional and national surveys.
The data provided here is intended to validate our platform and to optimize the Brown Marmorated Stink Bug Survey in Washington, Utah, North Carolina, and California. The data include habitat suitability predictions for this stinkbug and detection in these four states were provided.
The habitat suitability predictions are GIS raster data (i.e., asc format), they can be read and manipulated in terra package and any GIS software, this suitability prediction can be attained from an ecological niche model. The detection data are distributional data (i.e., two columns of longitude and latitude), where the stinkbug was detected (i.e., csv format). These data were served as input data for running our model,
We also provide R scripts that can be used to generate survey routes for stinkbugs in these states.
Column information in csv data
scientific name: scientific name of species
longitude: longitude of the collection site
latitude: latitude of collection site
Year: The year when the stinkbugs were collected
State: US state where the stinkbugs were collected
Site_ID: the collection site ID
Crop: crop type where the stink bugs were collected
Total: total individuals were collected
Adults_tra: number of individuals collected per trap
Adults_t_1: number of individuals collected per trap per day
Sharing/Access information
These data are also available at https://doi.org/10.17605/OSF.IO/5R8PZ
Code/Software
R is required to run the script which was created using version 4.2.3.
Annotations are provided throughout the script through 1) library loading, 2) dataset loading and cleaning, 3) analyses, and 4) figure creation.
Methods
In our framework, candidate survey sites are assembled from occurrence data on incursion populations and habitat suitability models. The logistics of surveying these sites are then determined by linking habitat suitability predictions with data on human transport pathways (i.e., roads) to generate a survey route. Our framework requires that a habitat suitability model has been created for a species in question, whereas the inclusion of incursion populations is optional and depends on whether the invasive species has been established in survey areas. The most common method to create a habitat suitability model is to relate occurrence records to environmental variables. Ecological niche models are often used in invasion risk assessment because model development packages have been created that can be readily used to identify areas of potential establishment.
We used H. halys to demonstrate and validate that our framework could be employed for promoting the selection of sites to collect a maximum number of individuals for a given number of survey sites compared to routes designed without ecological niche models. To monitor the spread of this species, a standardized monitoring network was established in 17 states from 2017 to 2020. We used data from states that had extensive sampling in the western US: Washington, California, and Utah, for validating survey routes from our heuristic algorithm. In each state, H. halys were sampled with sticky panel traps baited with lures spaced at 50 m intervals and collected every two weeks. We standardized the counts for modeling analyses as average H. halys adults per trap per week.