A cross‐scale view of N and P limitation using a Bayesian hierarchical model. (3rd August 2016) - Cha, YoonKyung; Alameddine, Ibrahim; Qian, Song S.; Stow, Craig A.
Abstract: We propose a bivariate Bayesian hierarchical model (BBHM), which adds a perspective on a century‐long subject of research, nitrogen (N) and phosphorus (P) dynamics in freshwater and coastal marine ecosystems. The BBHM is differentiated from existing approaches by modeling multiple aspects of N‐P relationships―N and P concentration variability, ratio, and correlation―simultaneously, allowing these aspects to vary by seasonal and/or spatial components. The BBHM is applied to three aquatic systems, Finnish Lakes, Saginaw Bay, and the Neuse Estuary, which exhibit differing landscapes and complexity of nutrient dynamics. Our model reveals N and P dynamics that are critical to inferring unknown N and P distributions for the overall system as well as for within system variability. For Finnish lakes, strong positive within‐ and among‐lake N and P correlations indicate that the rates of N and P biogeochemical cycles are closely coupled during summer across the different lake categories. In contrast, seasonal decoupling between N and P cycles in Saginaw Bay is evidenced by the large variability in monthly correlations and the seasonal changes in the N distribution. The results underscore the pivotal role that dreissenids have had on the cycling of nutrients and resurgence of eutrophication. The presence of clear seasonality and a spatial gradient in the distributions and N and P in the Neuse Estuary suggest that riverine N input is an important source in the season‐space N dynamics, while summer sediment release is a major process regulating seasonal P distribution.