Disentangling Climatic Factors and Human Activities in Governing the Old and New Forest Productivity

Abstract

Forest ecosystem plays a vital role in the global carbon cycle and maintaining climate stability. However, how net primary productivity (NPP) dynamics of different stand ages of forest respond to climatic change and residual (being other climate factors or human activities) still remain unclear. In this study, firstly, forests are divided into two categories based on their stand age: forests appeared before appeared before the research period (Fold), and forests appeared during the research period (Fnew). Secondly, we improved a quantitative method of basic partial derivatives to disentangle the relative contributions of climatic factors, other climate factors, and human activities to the NPP of Fold and Fnew. Then, different scenarios were simulated to identify the dominant drivers for forest restoration and degradation. In this study, we hypothesized the residual of Fold was other climate factors rather than human activities. Our results revealed that from 2000 to 2019, Fold and Fnew of NPP in Yangtze River Basin showed a significant increment trend and precipitation was the major positive contributor among all of the climatic factors. We found that, in Fold, climate change and other climate factors contributed 9.77% and 28.33%, respectively, in explaining NPP. This finding unsupported our initial hypothesis and implied that residuals should be human activities for Fold. Furthermore, we found that human activities dominate either restoration or degradation of Fnew. This result may be due to the attenuated human disturbances and strengthened forest management, such as ecological policies, forest tending, closing the land for reforestation, etc. Therefore, based on disentangling the two types of factors, we concluded that human activities govern the forest change, and imply that the environment-friendly forest managements may favorite to improving the forest NPP against the impacts of climate change. Thus, effective measures and policies are suggested implement in controlling forest degradation in facing climate change.

Quantifying the contributions of climate factors and human activities to variations of net primary productivity in China from 2000 to 2020

“…For most of the forestland in southern China, due to sufficient precipitation and high temperature in the growing season, vegetation cover represented by NDVI increased, and there was a correlation between NPP and NDVI (Sun et al, 2002), which led to the increase in NPP. Adequate precipitation also enhanced the carbon sequestration capacity of forestland in the Sichuan Basin to increase NPP (Chen et al, 2021a;Wang et al, 2021a). The NPP of forestland in the Greater Khingan Mountains and the Changbai Mountains in northeastern China was positively correlated with temperature and solar radiation, with temperature being the main limiting factor for vegetation growth in the cold temperate region, while increased solar radiation would also enhance vegetation photosynthetic capacity (Yan et al, 2021).…”

“…UF is residual value between S NPP ; C(C). In this study; UF is interpreted as the change rate of the contribution of human activities to NPP, namely; C(H) (Chen et al, 2021a;Ge et al, 2021).…”

The Relative Roles of Climate Variation and Human Activities in Vegetation Dynamics in Coastal China from 2000 to 2019

“…After strict quality control, the dataset is significantly improved in terms of the quality and integrity of the same data type; the correct rate is close to 100%. As for the time range of studies, due to data limitations, many studies have been carried out to 2015 or even earlier [55,56], and just a few studies have been conducted in the last 20 years [57,58]. We have extended the data to the recent 20 years in our research.…”

“…The response of vegetation to temperature, precipitation, and sunshine hours is nonlinear and the effect would change with various local conditions [67]. The impact of light or sunlight hours on vegetation change was rarely considered in climate-based vegetation models in previous studies [57,58,68]. Choosing a non-linear model requires observation of multiple data types and detailed statistical analysis, making the results difficult to interpret; besides, the multiple linear regression model also performs well in many studies [68,69].…”

Relation between Topography and Gap Characteristics in a Mixed Sessile Oak–Beech Old-Growth Forest

“…Tree species composition and productivity are controlled by the spatial and temporal distribution of climatic factors such as radiation, precipitation and temperature [26,[33][34][35]. One of the major factors influencing species composition is light, with different regimes in accordance with gap size, canopy height and aspect [36][37][38].…”