Predicting mangrove forest dynamics across a soil salinity gradient using an individual-based vegetation model linked with plant hydraulics

Abstract

Abstract. In mangrove forests, soil salinity is one of the most significant environmental factors determining mangrove forest distribution and productivity as it limits plant water uptake and carbon gain. However, salinity control on mangrove productivity through plant hydraulics has not been investigated by existing mangrove models. Thus, we present a new individual-based model linked with plant hydraulics to incorporate physiological characterization of mangrove growth under salt stress. Plant hydraulics was associated with mangroves nutrient uptake and biomass allocation apart from water flux and carbon gain. The developed model was performed for two-coexisting species of Rhizophora stylosa and Bruguiera gymnorrhiza in a subtropical mangrove forest in Japan. The model predicted that the productivity of both species was affected by soil salinity through downregulation of stomatal conductance, while B. gymnorrhiza trees grow faster and suppress the growth of R. stylosa trees by shading that resulted in a B. gymnorrhiza-dominated forest under low soil salinity conditions (< 28 ‰). Alternatively, the increase in soil salinity significantly reduced the productivity of B. gymnorrhiza compared to R. stylosa, leading to an increase in biomass of R. stylosa despite the enhanced salt stress (> 30 ‰). These predicted patterns in forest structures across soil salinity gradient remarkably agreed with field data, highlighting the control of salinity on productivity and tree competition as factors that shape the mangrove forest structures. The model reproducibility of forest structures was also supported by the predicted self-thinning processes, which likewise agreed with field data. In addition, the mangroves morphological adjustment to increasing soil salinity – by decreasing transpiration and increasing hydraulic conductance – was reasonably predicted. Aside from the soil salinity, seasonal dynamics in atmospheric variables (solar radiation and temperature) was highlighted as factors influencing mangrove productivity in a subtropical region. The physiological principle-based improved model has the potential to be extended to other mangrove forests in various environmental settings, thus contributing to a better understanding of mangrove dynamics under future global climate change.

Supplementary material to "Representing the impact of Rhizophora mangroves on flow and sediment transport in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures"

“…The site Fuk is a natural mangrove forest vegetated by Rhizophora stylosa and Buruguiera gymnorrhiza. Along with the soil salinity gradient, a notable change in the forest structural variables (stem diameter, tree height, species composition) was observed at this forest (Yoshikai et al, 2022b). As described in Suwa et al (2021), a 7-m radius circular plot was established and the stem diameter at 1.3-m height (D stem ) was measured for all the trees.…”

Field Measurement and Prediction of Drag in a Planted Rhizophora Mangrove Forest

“…However, we noticed that such conditions could change with flow direction; in fact, trees in our site are not necessarily located just downstream of a tree (see Figure 2a), thus it is uncertain whether the drag coefficient derived in this study reflects such effect or can be applied to natural Rhizophora mangrove forests (usually in random distribution). Also, it is not particularly rare in natural mangrove forests that the Rhizophora trees inhabit with other mangrove genera (e.g., Avicennia and Bruguiera ) which have different root morphological structures (Horstman et al., 2015; Yoshikai et al., 2022), and flow and drag characteristics in such conditions are still uncertain. Additional investigations in natural mangrove forests are therefore needed to consider these aspects.…”

Processes and mechanisms of coastal woody‐plant mortality

“…Integration of these frameworks with mechanistic modeling of the physiological responses to hypoxia and salinity (e.g. Yoshikai et al, 2021) could enable representation of the compounding plant responses to rising CO 2 , temperature, VPD, and droughts (McDowell et al, 2020). Integrating these disparate sets of knowledge can additionally provide a road map for future research into the formation of ghost forests under a changing environment.…”