Where will it grow? Bull Kelp distribution modeling in the Salish Sea
Mentor 1
Filipe Alberto
Start Date
16-4-2021 2:45 PM
Description
The bull kelp, Nereocystis luetkeana, is a foundational species for aquatic ecosystems in the Salish Sea on the border of Washington and British Columbia. Its ecological importance, population contractions, and the present environmental pressure in these bodies of water require an increased research effort on bull kelp dynamics in the Salish Sea. We’re approaching this issue by developing a species distribution model (SDM) to predict, in a spatially explicit way, the probability of N. luetkeana occurrence across the Salish Sea. SDM models are built from presence and absence species occurrence data (the response variable) and its association with a set of spatially explicit environmental data (the predictor variables). Environmental data were obtained from the Aqua-MODIS NASA satellite, the Bio-ORACLE global marine dataset, and local digital elevation models. Model development started summer 2019 and was finished fall 2020. The main technique used was generalized linear modeling, a form of multiple regression analysis better suited for presence-absence responses. Our top four predictors of presence are depth, photosynthetically active radiation, maximum spring sea surface temperature, and maximum primary productivity. An SDM model will be valuable to guide current restoration efforts by helping allocate resources more effectively to populations with long-term promise.
Where will it grow? Bull Kelp distribution modeling in the Salish Sea
The bull kelp, Nereocystis luetkeana, is a foundational species for aquatic ecosystems in the Salish Sea on the border of Washington and British Columbia. Its ecological importance, population contractions, and the present environmental pressure in these bodies of water require an increased research effort on bull kelp dynamics in the Salish Sea. We’re approaching this issue by developing a species distribution model (SDM) to predict, in a spatially explicit way, the probability of N. luetkeana occurrence across the Salish Sea. SDM models are built from presence and absence species occurrence data (the response variable) and its association with a set of spatially explicit environmental data (the predictor variables). Environmental data were obtained from the Aqua-MODIS NASA satellite, the Bio-ORACLE global marine dataset, and local digital elevation models. Model development started summer 2019 and was finished fall 2020. The main technique used was generalized linear modeling, a form of multiple regression analysis better suited for presence-absence responses. Our top four predictors of presence are depth, photosynthetically active radiation, maximum spring sea surface temperature, and maximum primary productivity. An SDM model will be valuable to guide current restoration efforts by helping allocate resources more effectively to populations with long-term promise.
