ORCID Profile
0000-0001-5058-8664
Current Organisation
Nanjing Forestry University
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Publisher: Springer Science and Business Media LLC
Date: 04-2016
Publisher: Springer Science and Business Media LLC
Date: 22-07-2021
DOI: 10.1007/S00468-021-02182-Z
Abstract: Plant–soil feedbacks in mangrove ecosystems are important for ecosystem resilience and can be investigated by establishing links between empirical and modelling studies. Plant–soil feedbacks are important as they provide valuable insights into ecosystem dynamics and ecosystems stability and resilience against multiple stressors and disturbances, including global climate change. In mangroves, plant–soil feedbacks are important for ecosystem resilience in the face of sea level rise, carbon sequestration, and to support successful ecosystem restoration. Despite the recognition of the importance of plant–soil feedbacks in mangroves, there is limited empirical data available. We reviewed empirical studies from mangrove ecosystems and evaluate numerical models addressing plant–soil feedbacks. The empirical evidence suggests that plant–soil feedbacks strongly influence ecological processes (e.g. seedling recruitment and soil elevation change) and forest structure in mangrove ecosystems. Numerical models, which successfully describe plant–soil feedbacks in mangrove and other ecosystems, can be used in future empirical studies to test mechanistic understanding and project outcomes of environmental change. Moreover, the combination of both, modelling and empirical approaches, can improve mechanistic understanding of plant–soil feedbacks and thereby ecosystem dynamics in mangrove ecosystems. This combination will help to support sustainable coastal management and conservation.
Publisher: Copernicus GmbH
Date: 18-02-2016
Abstract: Abstract. A number of nonlinear microbial models of soil carbon decomposition have been developed. Some of them have been applied globally but have yet to be shown to realistically represent soil carbon dynamics in the field. A thorough analysis of their key differences is needed to inform future model developments. Here we compare two nonlinear microbial models of soil carbon decomposition: one based on reverse Michaelis–Menten kinetics (model A) and the other on regular Michaelis–Menten kinetics (model B). Using analytic approximations and numerical solutions, we find that the oscillatory responses of carbon pools to a small perturbation in their initial pool sizes d en faster in model A than in model B. Soil warming always decreases carbon storage in model A, but in model B it predominantly decreases carbon storage in cool regions and increases carbon storage in warm regions. For both models, the CO2 efflux from soil carbon decomposition reaches a maximum value some time after increased carbon input (as in priming experiments). This maximum CO2 efflux (Fmax) decreases with an increase in soil temperature in both models. However, the sensitivity of Fmax to the increased amount of carbon input increases with soil temperature in model A but decreases monotonically with an increase in soil temperature in model B. These differences in the responses to soil warming and carbon input between the two nonlinear models can be used to discern which model is more realistic when compared to results from field or laboratory experiments. These insights will contribute to an improved understanding of the significance of soil microbial processes in soil carbon responses to future climate change.
Publisher: Springer Science and Business Media LLC
Date: 12-06-2020
DOI: 10.1007/S11273-020-09733-0
Abstract: It is commonly accepted that vegetation patterns and water supply mutually define each other. In mangroves, soil water salinity and the corresponding osmotic potential are the main drivers of plant water supply. Below-ground processes thus may be key for the structure and dynamics of mangrove stands. Nevertheless, existing simulation models describing mangrove forest dynamics do not quantify the water uptake of the single plant from the soil and traditionally neglect any feedback of the vegetation on the water availability, but instead use empirical, statistical models for plant competition affecting growth. We provide a brief review on the state of the art of mangrove forest models with an emphasis on how below-ground processes are regarded. We follow mainly two directions: (1) phenomenological concepts for competition for below-ground resources and (2) assessing the impact of salinity and water supply on the vegetation and possible feedback mechanisms from the vegetation to the below-ground conditions. We hypothesise that a coupled vegetation-groundwater model would avail us to better understand the dynamics and properties of mangrove systems, their capability to persist or rehabilitate under stressful hydrological conditions, as well as their response to environmental changes related to the groundwater system and transport. The benefits of such a joint approach would (i) constitute an intrinsic below-ground competition description close to the governing processes and (ii) concurrently exploit secondary, constraining information from vegetation patterns to derive a new concept to acquire knowledge on subsurface heterogeneity and parametrisation. The aim of this paper is to lay the theoretical groundwork and guidelines for future modellers to follow in the creation of a more realistic mangrove model coupling above- and below-ground processes. The proposed modelling approach has the potential to be useful for a broad audience based particularly in forest sciences and plant ecology in general, but also for hydrodynamic modelling (e.g. subsurface flow and transport detected by vegetation patterns as above-ground proxy).
Publisher: Copernicus GmbH
Date: 12-01-2017
Abstract: Abstract. Terrestrial ecosystems have absorbed roughly 30 % of anthropogenic CO2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Overall, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.
Location: United States of America
Location: United States of America
Location: No location found
No related grants have been discovered for Jiang Jiang.