# An Analysis of Spatial Variation in Human Impact on Forest Ecological Functions
## 1 Introduction  
Forests are the most important terrestrial ecosystem and are irreplaceable in preserving the human living environment and improving the climate conditions [1]. Forest ecologicalfunction (FEF) is a comprehensive concept, which refers to the ecological environment conditions and utility formed by the forest ecosystem and its ecological processes on which human beings rely for survival [2]. Specifically, the ecological service value in carbon sequestration [3], water retention [4], soil erosion control [5], climate regulation, environmental purification, and biodiversity protection [6] have made forests attract a great deal of attention. In recent years, forests face escalating pressure of ecosystem degradation due to intensified human activities associated with urbanization and industrialization, as well as climate change [7; 8; 9; 10]. In response, countries such as China have initiated ecological projects to create artificial forests, targeting both forest coverage expansion and sustainable resource provisioning [11]. According to the Forestry and Grassland Ecology Monitoring and Assessment Report in 2021, China contributed 5.51% to global forest coverage (fifth worldwide) and held a growing stock of 19.493 billion m\({}^{3}\), ranking sixth in the world [12]. However, despite its significant total volume, challenges persist in ecological efficiency. The forest ecological function index is 0.57, indicating an overall moderate level that still lags behind the global average [13]. In order to grasp the current status of forest resources more comprehensively, China has established a continuous forest inventory system since the 1970s, and the concept of the forest ecological function index (FEFI) was introduced in the Technical Provisions on the Continuous National Forest Inventory issued in 2004 [14]. FEFI includes factors such as forest productivity, naturalness, health, and the ratio of forest stand area to national land area, providing a comprehensive evaluation of FEF [2; 15]. Modern technologies such as GIS and WEBGIS are used to construct a system allowing for a swift and comprehensive evaluation of FEF. More specifically, ecosystem service assessment models, represented by the InVEST model, have been widely used to quantify different functions of forest ecosystems, such as carbon storage, water retention, and erosion control [16]. Inspired by the Gross Ecosystem Product (GEP), the Gross Forest Ecological Economic Product (GFEEP) framework was constructed to evaluate the economic value of forest ecological functions [17]. Researchers have long been concerned with the impacts of natural factors and human activities on forest ecosystems. Climatic changes such as temperature, precipitation, and duration of sunshine can strongly affect the productivity and resilience of the global forest ecosystem [18; 19; 20]. Anthropogenic activities have often yielded greater influence on forest ecosystems than climate change in recent years [21]. Accelerated economic growth, urban land expansion, and population explosion have caused severe damage to surface vegetation [22]. The huge demand for agroforestry products has led to the conversion of forests into arable land or alternative uses, thereby diminishing ecological functions [23]. Despite this, it is undeniable that economic development helps to optimize the forestry production structure and minimize the waste of forest resources in certain areas [24]. Additionally, forest policies and laws worldwide have led to significant expansions of forest coverage. In China and India, large-scale ecological restoration policies contributed significantly to maintaining and improving forest ecological functions [11]. Despite obvious progress in the understanding of FEF, several limitations persist within the existing literature. Firstly, assessments of integrated forest ecological services often rely on data from statistical reports, lacking a more intuitive evaluation grounded in sample plot data.