A nexus-based emergy modeling framework for elucidating energy and material flows of macrophytes in a mountain...

Wetland ecosystems are characterized by intricate interconnections among hydrological processes, physicochemical interactions, and biological dynamics. Understanding these internal linkages is fundamental to effective wetland management. This study provides a framework for elucidating complex, previously unquantified flow dynamics. A nexus model based on emergy accounting (EMA) was developed to explicitly reveal and quantify the hidden flow relationships within wetland systems. Traditional EMA applications treat wetlands as "black boxes," overlooking their internal interconnections. In contrast, our framework opens the box by capturing nitrogen cycling across water, soil, and macrophyte biomass compartments, thereby clarifying how interconnected processes drive overall ecosystem functionality. When applied to a mountain wetland in Taiwan, the model demonstrates the potential of this approach to reveal internal nutrient dynamics. To evaluate model robustness, a comprehensive sensitivity analysis was conducted on key external assumptions, including renewable resource emergy allocation, nutrient uptake efficiency, and nitrogen uptake composition. The preliminary results suggest the following two trends: (1) wetland soil may serve as a more influential nitrogen contributor to macrophytes than does the water column, and (2) nitrogen transfer from aboveground to belowground biomass appears to exceed reverse transport, implying distinct nutrient allocation pathways. Beyond these preliminary insights, the nexus-based assessment yields biomass emergy values approximately two orders of magnitude higher than those estimated by conventional methods. This outcome highlights the capacity of the model to capture internal linkages that are often overlooked in traditional evaluations, underscoring its potential to enhance the accuracy and comprehensiveness of ecosystem valuation. Furthermore, the sensitivity analysis of key model assumptions confirms the overall robustness of the framework and identifies nutrient uptake efficiency as the most influential parameter governing the nitrogen dynamics within the system. We suggest that the framework provides a promising and cost-effective tool for environmental managers to analyze ecosystem functions, guide optimization efforts aligned with habitat management goals, and improve assessments of natural capital.