# Simulating Ecological Functions of Vegetation Using a Dynamic Vegetation Model
###### Abstract
In this type of research, the dynamic vegetation model is recommended to simulate the vegetation pattern as well as ecological function patterns and relationships under future climate change. Process-based dynamic vegetation models can quantify the dynamics of ecosystem services under climate change and their related policy scenarios, and reflect the relationships between ecosystem services [11]. Process-based dynamic vegetation models can examine many climatic vegetation mechanisms such as leaf transpiration, soil evaporation, photosynthetic respiration, competition, death, community succession, and canopy structure dynamics. They have many applications in response to vegetation carbon and water fluxes and their structure under climate change [12]. At present, the common dynamic vegetation models include LPJ-DGVM (Lund-Potsdam-Jena Dynamic Global Vegetation Model) [13], SEIB-DGVM (Spatially Explicit Individual-Based Dynamic Global Vegetation Model) [14] and LPJ-GUESS (Lund-Potsdam Jena Universal Ecosystem Simulator) [15]. LPJ-GUESS is an updated edition of the LPJ-DGVM model that refines the simulation at the individual plant level. This makes the dynamic simulation of vegetation composition, structure, and function more accurate [12]. The LPJ-GUESS model can not only be used to examine the mechanisms of large-scale vegetation dynamics, but it has also been used to introduce gap model and patch concepts to refine vegetation dynamics. This includes the vegetation succession, species composition and density, and changes in the community morphological structure. Driven by monthly climate data, annual atmospheric CO\({}_{2}\) concentration data, soil data, and vegetation eco-physiological parameters, vegetation dynamics can be simulated and analyzed at the typical plant functional type (PFT) level. The community structure and its response to climate change can be predicted according to the preset composition of PFTs [16], so it has been universally used in vegetation research [16; 17; 18; 19].Therefore, the LPJ-GUESS model may be a powerful tool for implementing research on the ecological functions of vegetation under future climate change. The Loess Plateau (LP) is situated in the north of China and is a transition zone from a semi-humid to semi-arid climate, with the vegetation ecosystem being highly sensitive to climate change. The vegetation distribution sequence from the southeast to the northwest is the forest zone, the forest-grass transition zone, and the grass zone. The vegetation distribution shows a distinct zonal trend, and the vegetation system has a simple structure, low productivity [20], dry soil, and water shortages [21], resulting in a fragile ecological environment. Many studies have assessed historical ecological functions [22; 23; 24; 25; 26; 27],and the examination of examining future changes has based on ca-Markov models to predict land use change scenarios, and estimate ecological functions under future scenarios. However, these studies have predominantly excluded investigation into the dynamic impacts of climate change on vegetation structure. Furthermore, the prediction of the dynamic evolution of ecological functions under climate change is insufficiently accurate. Temperature and precipitation in the LP will increase and fluctuate considerably in the future, indicating a pronounced climate response to global warming in the region [28]. Therefore, the LP is an ideal research area to study the dynamic evolution of ecological functions of vegetation under climate change, with findings that hold the potential to improve the ecological environment in the region. Accordingly, taking the LP as the study area, the aim of this study were to verify the suitability of the LP-GUESS model for modelling the response of vegetation to climate change, and to use the model to simulate the changes in the vegetation distribution and ecological functions.