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Modeling bioavailable phosphorus via other phosphorus fractions in sediment cores from Jiulongkou Lake, China
Authors:Ling Liu  Ying Zhang  Aris Efting  Tadd Barrow  Bao Qian and Zejian Fang
Institution:(1) State Key Laboratory of Hydrology–Water Resources and Hydraulic Engineering, Hohai University, No. 1 Xikang Road, Nanjing, 210098, Gulou, China;(2) School of Natural Resources, University of Nebraska–Lincoln, Lincoln, NE 68583, USA;
Abstract:Bioavailable phosphorus (BAP) plays an important role in phosphorus (P) release from lake and river sediments, as well as serves as an indicator for the potential P-release risk in sediment. Developing a feasible model which could predict BAP via other P fractions is needed for the lakes and reservoirs without regular BAP monitoring. The algal available P (AAP), NaHCO3 extractable P (Olsen-P), water soluble P (WSP) and readily desorption P (RDP) are four fractions of BAP. The vertical and spatial distributions of BAP fractions of three sediment cores from Jiulongkou Lake were analyzed. In addition, the P fractions, including total P (TP), organic P (OP), inorganic P (IP), non-apatite inorganic P (NAIP), and apatite P (AP) were measured to develop a model for predicting BAP. The model for each BAP fraction was developed based on datasets from Jiulongkou Lake and validated by the datasets collected from Wujin and Wugong Lake. The results showed that all of the four BAP fractions decreased with depth, along the direction of contaminant transport. Their rank order was AAP > Olsen-P > WSP > RDP in all samples. The concentration of BAP was affected by the anthropogenic input and aquatic macrophyte growth. Each of the four BAP fractions could be simulated by different P fractions: both AAP and Olsen-P were expressed by NAIP and OP, WSP had a significant relationship with OP, and RDP had significant relationship with IP. NAIP and OP were the major sources of the BAP fraction. The simulated results in two other lakes further illustrated that this model could be used to successfully predict the BAP concentrations in lakes in the study area, and holds promise for predicting the BAP levels in other lakes and reservoirs as well.
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