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This dataset contains predictions of habitat suitability of reed canarygrass (Phalaris arundinacea) in Upper Mississippi River floodplain forest understories from Pool 3 to Pool 13. Predictions were created using three machine learning algorithms (Bayesian additive regression trees, boosted trees, and random forest). This dataset contains rasters that provide habitat suitability predictions for each 12m raster cell that had forested landcover in 2010. In addition to one raster for each of the three algorithms an ensemble (mean prediction of all three algorithms) prediction raster for each pool is provided. The presence/absence observations used to train the model are contained in a .csv file with each plot location....
The dataset and accompanying analysis scripts accompany the article "Bayesian multistate models allow incorporation of spatial dynamics to improve invasive species management". The data are summarized detections from acoustic telemetry receivers (69 KHz) from 353 silver carp (Hypophthalmichthys molitrix) and 170 bighead carp (H. nobilis) surgically implanted with transmitters in the Illinois River, USA. The analysis scripts assess probability of detection, probability of monthly movement between navigation pools on the river, probability of apparent survival, and probability of operable transmitter battery through a Bayesian multistate hidden Markov model. First release: 2023 Revised: June 2024 (ver. 2.0)
Categories: Data,
Data Release - Revised;
Tags: Des Plaines River,
Illinois River,
Illinois Waterway,
North America,
USGS Science Data Catalog (SDC),
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