Using Bayesian change point model to enhance understanding of the shifting nutrients-phytoplankton relationship

Liang, Zhongyao; Qian, Song S.; Wu, Sifeng; Chen, Huili; Liu, Yong; Yang, Yu; Yi, Xuan

doi:10.1016/j.ecolmodel.2018.12.008

Cited by 16 publications

(5 citation statements)

References 57 publications

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“…The yield of soybean present in the database was converted into relative yield (%) by taking into consideration each genotype and crop season to develop critical threshold estimation models. Models were developed on the boundary line [ 61 , 62 ] using Bayesian segmented quantile regression [ 31 ] to measure the association between dependent variables (yield) and Se concentration in soybean grains. Bayesian analysis was used to adjust the parameters of the regression models [ 63 ].…”

Section: Methodsmentioning

confidence: 99%

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Foliar Application of Selenium Associated with a Multi-Nutrient Fertilizer in Soybean: Yield, Grain Quality, and Critical Se Threshold

Silva

Sousa

Opbergen

et al. 2023

Plants

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Selenium uptake and its content in soybean grains are affected by Se application methods. This study evaluated the impact of Se foliar application combined with a multi-nutrient fertilizer (MNF) on soybean, establishing a Se threshold to better understand the relationship between Se content in grains and yield of two genotypes (58I60 Lança and M5917). Two trials were conducted in a 4 × 2 factorial design: four Se rates (0, 10, 40, 80 g Se ha−1) and two methods of foliar Se application (Se combined or not with MNF). Foliar fertilizers were applied twice, at phenological stages of beginning of pod development and grain filling. Grain yield increased with the application of MNF, yet Se rates increased Se contents linearly up to 80 g Se ha−1, regardless of the use of MNF. Lança and M5917 genotypes had grain Se critical thresholds of 1.0 and 3.0 mg kg−1, respectively. The application of Se favored higher contents of K, P, and S in grains of genotype Lança and higher contents of Mn and Fe in grains of genotype M5917. Our findings highlight the importance of addressing different Se fertilization strategies as well as genotypic variations when assessing the effects of Se on soybean yield and grain quality.

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Section: Methodsmentioning

confidence: 99%

“…Furthermore, it is unclear if there are critical threshold variations among soybean genotypes. These gaps can be filled by Bayesian modeling techniques combined with well-documented databases [ 31 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

Foliar Application of Selenium Associated with a Multi-Nutrient Fertilizer in Soybean: Yield, Grain Quality, and Critical Se Threshold

Silva

Sousa

Opbergen

et al. 2023

Plants

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“…Specifically, Carpenter and Lathrop [61] used the phosphorus dynamics (1) and the observations of the phosphorus budget of Lake Mendota for the last 30 years to estimate the probability distribution of the threshold for eutrophication and formulated suggestions for designing management strategies. Liang et al [63] specified 4 simple models with time-driven switching to identify the possibility of shifts in the nutrients-phytoplankton relationship in They identified a change in this relationship and showed that an increase in nutrients did not drive this change, while total phosphorus (TP) plays a more important role than total nitrogen in an increase in Chlorophyll a; and reducing nutrients is a better strategy than ecosystem recovery to effectively reduce the concentration of Chlorophyll a. Likewise, Yao et al [64] used a multidimensional similarity cloud model to assess the level of eutrophication on the basis of different indicators, including phosphorus concentration and chlorophyll levels.…”

Section: Estimation Of the Thresholds In Lake Dynamicsmentioning

confidence: 99%

Dynamics and Economics of Shallow Lakes: A Survey

Gromov

Upmann

2021

Sustainability

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We provide an overview of the results devoted to the analysis of the dynamics and economics of shallow lakes, spanning the period from 1999 until now. A shallow lake serves as a typical representative of an ecological system subject to (possibly irreversible) regime shifts. The dynamics of a shallow lake are described by a non-linear model with multiple steady states and multiple domains of attraction and is thus suitable to model the evolution of an ecosystem featuring both resilience within a domain of stability and an abrupt regime shift outside of it. Beyond this, the shallow lake model can also be viewed as a metaphor for many other ecological problems. Due to the broad applicability of this model, there is substantial interest in the management of shallow lakes and both their optimal regulation and competitive usage.

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“…The MIKE21 model had good application inter-face and good simulation effects, and was used in our study. Widely used statistical models included the back-propagation (BP) neural network, the random forest algorithm, the bayesian model, and the cart decision tree algorithm [18][19][20]. The BP neural network model was widely used, had good self-adaptive ability and memory function, could learn and store a large number of input-output mode mapping relationships, and had clear advantages in predicting nonlinear problems [21,22].…”

Section: Introductionmentioning

confidence: 99%

Short-Term Early Warning Method for Algal Bloom Risk Based on a Neural Network and a Two-Dimensional Hydrodynamic Model

Luo,

Gu,

Gao

et al. 2024

Pol. J. Environ. Stud.

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Eutrophication of lakes and reservoirs and the occurrence of cyanobacteria blooms are two of the major environmental problems facing the whole world. However, if cyanobacteria bloom outbreaks can be predicted in advance, there is enough time to implement various measures to reduce ecological harm and health risks and greatly reduce economic losses. Yuqiao Reservoir was a typical shallow-water lake reservoir that was also faced with a greater risk of cyanobacteria bloom outbreaks in summer and autumn. In this study, a BP neural network model and a two-dimensional hydrodynamic numerical model were constructed based on meteorological, hydrological, water quality, and terrain data for Yuqiao Reservoir. The neural network model was used to simulate the biogeneration and extinction processes of cyanobacteria bloom biomass, while the two-dimensional hydrodynamic numerical model was used to simulate the migration and accumulation processes of cyanobacteria. The two models were coupled by an algal attenuation coefficient for the shortterm warning of algal bloom. The results of the Nash coefficient evaluation showed that the coupled model had good overall efficiency and could effectively simulate the algal density both in time and space. The results of scenario analysis showed that the change in flow field in a shallow water reservoir had a great influence on algae migration and accumulation, and water transfer, wind speed, and direction all affected the flow field distribution and then the formation of bloom. The model application results showed that the short-term bloom prediction method constructed in this study had advantages in forecasting accuracy and displayed an effect.

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Using Bayesian change point model to enhance understanding of the shifting nutrients-phytoplankton relationship

Cited by 16 publications

References 57 publications

Foliar Application of Selenium Associated with a Multi-Nutrient Fertilizer in Soybean: Yield, Grain Quality, and Critical Se Threshold

Foliar Application of Selenium Associated with a Multi-Nutrient Fertilizer in Soybean: Yield, Grain Quality, and Critical Se Threshold

Dynamics and Economics of Shallow Lakes: A Survey

Short-Term Early Warning Method for Algal Bloom Risk Based on a Neural Network and a Two-Dimensional Hydrodynamic Model

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