Enhanced Net Community Production With Sea Ice Loss in the Western Arctic Ocean Uncovered by Machine‐Learning‐Based Mapping

Abstract

In the Arctic Ocean (AO), net community production () has displayed spatially heterogeneous responses to sea ice reduction and associated environmental changes. Using a random forest machine learning model trained with >42,000 in situ measurements and concurrent, collocated environmental predictors, we reconstructed 19 years of 8‐day, 6‐km maps. During 2015–2021, the integrated between late‐May and early‐September () over the western AO was per year, with interannual variations positively tracking open water area. While the relationship between and open water area was quasi‐linear at high latitudes, strong nonlinearity was detected on the inflow shelf. The nonlinearity highlights that the increase resulted from area gain could be compounded by sea‐ice loss induced ecosystem adjustments. Additional retrospective analysis for 2003–2014 suggests a potential long‐term increase of export production and efficiency in the western AO with sea ice loss.