# Simulating Ecological Functions of Vegetation Using a Dynamic Vegetation Model
## 4 Discussion  
At present, many studies on future ecological functions under climate change have been conducted worldwide [5; 6; 7]. However, these studies do not involve a particularly fine simulation of vegetation carbon and water flux and its structure, so the results are subject to considerable uncertainty. It is also difficult to achieve sustainable and efficient vegetation management and restoration plans. Therefore, this study addresses this knowledge gap by applying process-based dynamic vegetation models and high-resolution climate data to simulate and analyze the dynamic responses of ecological functions of vegetation to climate change in the LP. Compared with 2001-2020, the area converted from shrub and grass into forest land by 2081-2100 was modeled to be mainly distributed in the Lvliang and Taihang Mountains (Figure 3), and this conversion was mainly caused by climate warming and drought [32]. The bare land in the western area was projected to be converted to grass, and the proportion of bare land area decreased or even disappeared. These phenomena are explained by plant community conversion due to climate change [32]. Previous studies reported that although temperature and precipitation on the LP will increase in the future, the evaporation caused by temperature increase will be greater than the precipitation, leading to a dry climate in the future [28]. These climate changes would advance the conversion of forest, shrub, and grass vegetation. The conversion of vegetation types from the historical to the future periods means that future climate change will greatly affect the spatiotemporal distribution of the vegetation. Predicting shifts in vegetation types can help make vegetation management in an area more targeted and efficient. For example, in the Lvliang and Taihang Mountains, proper thinning management or pruning could support vegetation growth. In the high elevations of the west, grazing may be appropriate. The simulated trends of CS, SC, and WC in the future period under the two scenarios were quite different (Figure 4a-c). The reason is that we used scenarios with high and low forcing and greenhouse gas emissions to predict future ecological functions, and these scenarios included a range of possible future climatic changes such as temperature, precipitation, radiation, and carbon dioxide concentrations. The SSP119 scenario is represented by a low temperature, with the temperature rise in this century controlled at 1-2.4 degC and low atmospheric CO\({}_{2}\) concentrations. Under the SSP585 scenario, the temperature increase by the end of the century would be 2.8-5.7 degC. This leads to very different outcomes for the two future scenarios, and it is an approach that is often considered in current research aimed at predicting the future period [29; 43; 44]. The distributions of the CS, SC, and WC of the LP on the historical period were consistent with the results of existing research simulated by the InVEST model (Figure 5(a1,b1,c1)) [45; 46], specifically that the spatiotemporal distribution of the ecological functions is affected by the hydrothermal conditions of the LP. During 2081-2100, the CS of the LP was high in the southeast and low in the northwest, with the CS being the lowest in the west at Qilian Mountain owing to the sparse vegetation in this region (Figure S2(a1,a2)). Under the SSP119 scenario, the CS in the central and southeastern regions of the LP in 2081-2100 decreased compared with 2001-2020, but the CS in the central and southeastern parts of the LP in 2081-2100 was still greater than that of the northwest (Figure 5(a2)) because the precipitation in the southeast was higher than that in the northwest. There is a notable positive correlation between precipitation and the CS [47]. The distribution of the SC on the LP was higher in the southeast and lower in the northwest (Figure S2(b1,b2)). The main reason for this phenomenon was the effect of precipitation in the future period.