Process-based modeling to assess the nutrient removal efficiency of two endangered hydrophytes: Linking nutrient-cycle with a multiple-quotas approach
Graphical abstract
Introduction
Due to industrial development and urbanization over the past few decades, the amounts of nitrogen (N) and phosphorus (P) entering the natural ecosystems have increased by two and four times, respectively, compared with the pre-industrial levels (Afshar et al., 2012; Bracken et al., 2015). This excess of N and P has caused ecological disturbances, such as harmful algal blooms, eutrophication, and hypoxia, by disturbing nutrient cycling in aquatic ecosystems (Matinzadeh et al., 2017; Golden et al., 2019; Wu et al., 2019). Furthermore, since surface water, the primary water source for humans, is more vulnerable to these disturbances, the excess inflow of nutrients is a substantive threat to water security (Smith, 2003; Zhu et al., 2015). Therefore, much effort has been put into reducing N and P loads and restoring nutrient balance in aquatic ecosystems.
Planting of hydrophytes is an effective and inexpensive ecological approach for reducing N and P in aquatic ecosystems (Zhu et al., 2015). Hydrophytes play crucial roles in aquatic ecosystems, such as regulating the circulation of water and nutrients, maintaining the balance between the inflow and outflow of materials in both water and sediment layers, and increasing the diversity of aquatic organisms (Zhou et al., 2016). There have been many reports of successful reduction in nutrient levels through restoration or construction of wetlands and use of floating beds where hydrophytes are planted as monocultures or mixtures (Mayo et al., 2014; Mayo and Hanai, 2017; Nocetti et al., 2020). However, the utilization of hydrophytes is limited to specific species with high nutrient removal efficiencies. According to a literature review of 643 constructed wetlands (Vymazal, 2013), only three genera—Typha (Cattails, Typhaceae), Scirpus (Bulrush, Cyperaceae), and Phragmites (Common reed, Poaceae)—represented the majority of hydrophytes planted in constructed wetlands worldwide. It is reasonable that a high nutrient removal efficiency is a key consideration in selecting hydrophyte species, but the use of limited species can lead to other ecological problems, including decrease in hydrophyte diversity in aquatic ecosystems and degradation of habitat of other hydrophyte species. In addition, the use of limited hydrophyte species can decrease the overall biodiversity of aquatic ecosystems (Chambers et al., 1999). Considering that planting hydrophytes for reducing nutrients would artificially create new communities in natural ecosystems, efforts should be made to identify new candidate species and explore the potential use of endangered species to remove nutrients while preserving hydrophyte diversity in aquatic ecosystems.
Process-based models have been widely used to understand the roles of hydrophytes and their ability to remove nutrients from aquatic systems in which the physical, chemical, and biological processes are intricately intertwined (Matinzadeh et al., 2017; Wang et al., 2019). Since this modeling approach provides a mathematical description of all processes within and between hydrophytes, water layers, and sediment layers, it is powerful tool for improving our understanding of complex nutrient cycles in aquatic ecosystems (Wang et al., 2019). However, the conventional models reported to date have limitations in that the growth and nutrient uptake of hydrophytes are oversimplified as well as their interactions with environmental factors, such as temperature, pH, and nutrient concentrations, are neglected in these models. For example, the uptake processes of hydrophytes are often modeled as simple first-order kinetics, and the uptake mechanism for multiple nutrients is not well considered (e.g., Marimon et al., 2013; Mayo et al., 2014, Mayo et al., 2018; Matinzadeh et al., 2017). The lack of mechanism-based explanations for plant responses can lead to an inaccurate assessment of the ability of hydrophytes to remove nutrients (Paudel and Jawitz, 2012). In particular, the misevaluation of nutrient removal efficiency of hydrophytes will be even more pronounced in field conditions, where nutrient concentrations fluctuate greatly and excess nutrients are introduced.
Given the complexity of a hydrophyte's physiological mechanisms in response to nutrients, a solid theoretical foundation capable of simulating these mechanisms is essential for developing a process-based model. Recently, Wirtz and Kerimoglu (2016) proposed a multiple-quotas-based (hereafter referred to as MQ) approach, which provides a theoretical framework to conceptually explain the uptake and response of autotrophs to multiple nutrients. This approach describes the dynamic relationships between nutrients and autotrophs by incorporating the autotroph's internal regulatory functions based on the cell quota model (Droop, 1968), and the co-limitation mechanisms for multiple nutrients, proposed by Bloom et al. (1985) and established a more detailed conceptual framework by Saito et al. (2008) and Ågren et al. (2012). The integrated representation of nutrient uptake and allocation of autotrophs described by the MQ approach could be used as a submodel to fill the gaps between the simplified and actual plant growth, which are overlooked in conventional models. Wirtz and Kerimoglu (2016) previously noted that the MQ approach could be applied to unicellular populations as well as to higher organisms without altering the theoretical framework. Nonetheless, while the MQ approach has been intensively applied to phytoplankton (Kerimoglu et al., 2018; Taherzadeh et al., 2019), no studies on hydrophytes have been reported so far. In addition, case studies have not been reported in which changes in nutrient concentrations in the environment are incorporated into the approach.
Menyanthes trifoliata (Buckbean, Menyanthaceae) and Cicuta virosa (Cowbane, Apiaceae) are emergent hydrophyte species that inhabit freshwater ecosystems such as ponds, lakes, and wetlands. M. trifoliata is widely distributed from 40°N to the Arctic Circle (Hewett, 1964), and C. virosa is distributed in Europe, North America, and Asia (Mulligan and Munro, 1981). However, the populations of these species are continually declining worldwide due to habitat destruction. M. trifoliata is listed as a threatened or protected species in some European countries (Lange, 1998), and C. virosa population declines have been reported in Asian countries (Shin and Kim, 2013; Nagata et al., 2015). In Korea, both hydrophytes have been designated as local endangered species (Ministry of Environment, 2013). To maintain the habitat and populations of M. trifoliata and C. virosa, planting of these species for nutrient removal from aquatic ecosystems can be considered, but no studies on their nutrient removal efficiencies have been reported.
To this end, the objective of this study was to develop a new process-based model that can be used to explore the N and P removal efficiencies of hydrophytes. A modified MQ model that simulates the nutrient uptake and growth of hydrophytes was incorporated into the nutrient-cycle submodel. The developed process-based model was validated using microcosm experiments with two emergent hydrophytes, M. trifoliata and C. virosa. Using the model, the total ammonia + ammonium-nitrogen (NHx-N), nitrate-nitrogen (NO3-N), and P removal efficiencies of M. trifoliata and C. virosa in the water and sediment layers were simulated according to nutrient exposure level.
Section snippets
Model structure
In this study, a process-based model was developed to simulate the dynamics of N and P in a hydrophyte-planted aquatic system. Overall, the model was constructed by combining the nutrient-cycle (NC) and plant-growth (PG) submodels, which simulate nutrient dynamics in the environment and response of the hydrophyte, respectively. The combined model was designed to represent the transformation and transference of N and P within and between three compartments: water layer (W), sediment layer (S),
Parameter estimation
Parameters for the combined model were sequentially estimated in the order of the parameters of the NC submodel and then of the PG submodel, because the PG submodel must be linked to the NC submodel to simulate nutrient concentrations of the container in which the hydrophytes were planted. The parameters of the NC submodel were estimated using the N species and P concentrations measured in the containers without plants (Supplementary Fig. S7). The outputs of the NC submodel with the estimated
Discussion
In this study, a new process-based model was proposed that reflects the mechanisms of growth and uptake of multiple nutrients by hydrophytes as well as the N and P dynamics in the water and the sediment layers. The model well simulated the different growth characteristics of M. trifoliata and C. virosa and was useful for analyzing their N and P removal efficiencies. Our model provides mechanistic descriptions of nutrient uptake and growth of hydrophytes based on the MQ approach, thus, it can be
Conclusion
In this study, a new process-based model incorporating the MQ approach was developed to simulate the N and P removal efficiencies of hydrophytes in the water and sediment layers. The developed model was calibrated using microcosm experiments with emergent hydrophyte species, M. trifoliata and C. virosa. According to the experimental and simulation results, both hydrophyte species showed higher N and P removal efficiencies in the sediment layer than in the water layer, but the NHx-N removal
CRediT authorship contribution statement
Yongeun Kim: Conceptualization, Methodology, Formal analysis, Writing – original draft. Yun-Sik Lee: Investigation, Validation. June Wee: Investigation, Resources. Jinsol Hong: Data curation, Resources. Minyoung Lee: Methodology, Visualization. Jae Geun Kim: Conceptualization, Resources. Yeon Jae Bae: Conceptualization, Supervision. Kijong Cho: Conceptualization, Writing – review & editing, Supervision.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (NRF-2020R1I1A1A01074894, to Y.K.) and the Ministry of Science and ICT (NRF-2019R1A2C1009812, to K.C.). This research was also partially supported by a Korea University Grant and an OJERI (Ojeong Resilience Institute) Grant.
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