This is the output of GBM (Gradient Boosting Model) analyses of K. mikimotoi presence and absnece data done by MI OCIS and CoCliME project. This output dataset shows prediction of probability of K. mikimotoi presence in the future (2017 - 2035) in SW Ireland. The analyses was performed in R 3.6.3, with the packages tidyverse 1.3.0 for data handling and visualisation, and xgboost 1.2.0.1 for boosted regression analyses. The dataset used for analyses is available on MI data catalogue (http://data.marine.ie/geonetwork/srv/eng/catalog.search#/metadata/ie.marine.data:dataset.4445) and the dataset used for prediction is requested to be included in MI data catalogue ([20]. CDF-t Climate run (Climate_run_corr.rds) in CoCliME model SOP). This dataset is used to visualise the prediction on R Shiny application for present period (https://marine-institute-ireland.shinyapps.io/K_mikimotoi_probability/ ). None

Suggested Citation: Yamanaka, Tsuyuko; Cusack, Caroline; Clarke, Dave; Nolan, Glenn. (2022) CoClime - Probability of phytoplankton (Karenia mikimotoi) presence, Southwest Ireland - future prediction (2017 - 2035). Marine Institute, Ireland. doi:10/hvtc.