**1. Introduction**

Globally, forest loss due to plantation forestry, agriculture, mining-related wildfires, and urbanization has enormous implications, particularly for climate change and biodiversity. As a result, governments, conservationists, and even private corporations are engaged in efforts to curb these losses and promote forest recovery [1–4]. In China, a series of ecological restoration programs have been implemented at the national, regional, and local scales over the past several decades, including the Grain for Green Program (1999–2020) and the Rocky Desertification Treatment Program (2008–2020) [5]. These interventions have greatly improved the sustainability of China's land systems, with the rate of forest cover increasing from 8.6% in 1949 to 23.04% in 2020 [6]. Substantial forest recovery has been detected through remote-sensing imagery, revealing an overall increase in greening since

**Citation:** Guo, X.; Chen, R.; Meadows, M.E.; Li, Q.; Xia, Z.; Pan, Z. Factors Influencing Four Decades of Forest Change in Guizhou Province, China. *Land* **2023**, *12*, 1004. https:// doi.org/10.3390/land12051004

Academic Editors: Xiaoyong Bai and Adrianos Retalis

Received: 29 March 2023 Revised: 15 April 2023 Accepted: 27 April 2023 Published: 3 May 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

2000, most notably in China and India [7]. This trend is particularly prominent in certain provinces, including Guizhou province, where the forest cover increased from 11.98% in 1949 to 61.5% in 2020 [8]. Ecological restoration interventions have significantly increased the vegetation growth and carbon stock in China more generally [9,10]. It is clear that continuous and long-term ecological restoration projects can, among other benefits, help forests accumulate nutrients [11], and that embracing the implications of restoration interventions can contribute to the United Nation's Sustainable Development Goals. It is the interaction between the natural environmental and socio-economic factors that determines forest dynamics, including recovery. Natural factors include those related to soil [12] and climate, especially the mean annual temperature and rainfall [13–15]. However, the spatial and temporal aspects of forest change in remote and environmentally fragile regions are not fully understood, and the trajectory of the forest changes in China as a whole is still subject to debate. While some locations have undergone 'greening,' others remain subject to forest clearance [16–18]. Therefore, it is important to establish the details of recent trends in forest cover, and their driving forces, especially in environmentally vulnerable regions, such as the karst area of southwestern China, which has historically endured significant levels of rocky desertification [19].

Guizhou province has a total area of 176,167 km2, of which 92.5% is hilly and 61.9% is karst [20], and it is considered to be among the most environmentally vulnerable regions in China. Karst topsoil is typically shallow, so if the forest vegetation is cleared, it is highly susceptible to erosion [21] and produces a particular form of land degradation, known as rocky desertification, which, in turn affects regional socioeconomic development. This has led Guizhou to become the least developed province in China [22]. China has responded to this land-degradation crisis in the karst region of its southwestern area, including Guizhou province, through an integrated portfolio of ecosystem-restoration programs since the 1980s. A number of previous studies described rocky desertification and associated spatio-temporal variations in land-use change, the mechanisms underlying these processes, and restoration responses [23–25]. Accelerated soil erosion and its underlying causes have been a particular focus [26–28]. However, relatively little attention has been paid to forest loss, which is an important element in land degradation and rocky desertification, particularly in Guizhou province. The forests of Guizhou Province, lying in the central part of southwestern China's karst area, play a crucial role in the ecological security and ecosystem services of a region that forms a part of an ecological safety barrier between the Pearl River and the Yangtze River catchments, which makes it ecologically critical, but highly vulnerable [29]. Understanding forest change is central to achieving sustainability and providing support for decisions regarding land-use management in the region.

Land-use and land-cover change (LULCC) is the alteration of natural or semi-natural landscapes due to human activities, such as urbanization, agricultural expansion, and deforestation [30]. In previous research, developed numerous models were developed to explore LULCC, in order to detect the changes in land use at specific locations and analyze its drivers [31,32]. From the perspective of landscape ecology, these models can be classified into three types: whole-landscape models, distributional models, and spatiallandscape models [33]. However, these focus mainly on ecological processes while tending to underplay or even ignore the role of human decision-making [34]. By the end of the 1990s, a considerable amount of tropical-deforestation-modeling work, represented by Lambin [35] and Kaimowitz and Angels [36] emerged that considered the role of human decision-making. Models of LULCC, including empirical–statistical models, stochastic models, optimization models, dynamic simulation models, and integrated models [37], can be categorized according to different criteria. Agarwal et al. [38] listed 19 models, including Markov models, spatial-simulation models, and regression models, based on their space, time, and decision-making characteristics. Among these, the Markov chain (MC) model is widely used in the spatiotemporal evaluation of LULC changes [39]. The choice of the model depends, to a large extent, on the particular scientific questions to be answered, along with data availability. Although LULCC modeling has made significant

progress in understanding the dynamics and effects of land-use change [40], there remains a pressing need for more interdisciplinary research that integrates multiple drivers and factors affecting land-use decisions. This includes the development of more advanced modeling techniques that combine multiple methods [41]. The understanding of the interaction between scales and across scales is likely to remain the research frontier of the modeling of land-use/cover changes in the future.

The aim of this paper is to evaluate the change in forest cover and the relative importance of selected contributing factors in Guizhou province over four decades (1980–2018), with a view to determining the relative influence of human and natural factors. Using a remote-sensing monitoring dataset of multi-period land use and land cover from Landsat, we employed a Markov model to analyze the forest change in the study area. Additionally, we considered a range of environmental (e.g., soil erosion, karstification intensity, drought index) and socio-economic (e.g., population, gross domestic product (GDP), and accessibility) data to investigate the factors that influence forest change through a correlation analysis and a generalized linear model (GLM) regression. The systematic understanding of the forest change in Guizhou province in this paper has the potential to be used more widely to develop ecological restoration strategies and promote more sustainable land-use management in the future.

#### **2. Materials and Methods**

#### *2.1. Study Area*

Guizhou (24◦37 –29◦13 N, 103◦36 –109◦35 E) is representative of China's southwestern karst region, with over 60% of its land area consisting of the karst landform [42] (Figure 1). The region encompasses a variety of landforms, including mountains, hilly areas, plateaus, basins, and river valleys. Unlike other karst provinces, there are no extensive plain areas, and the mean elevation is approximately 1100 m. The climate is classified as subtropical humid monsoon, with an average annual temperature of around 15 ◦C and an annual precipitation of approximately 1200 mm [43]. The environment is highly susceptible to degradation, and it is particularly prone to accelerated soil erosion, resulting in rocky desertification [44]. By 2016, karst-rock desertification in Guizhou was reported to extend across almost 250,000 km2 of the province, making it was the most degraded karst province in the country [45]. The region's economy has experienced significant growth in recent years. Agriculture, particularly cash crops such as oranges, peaches, and dragon fruit, contributes greatly to rural livelihoods, although, due to the area's ecological vulnerability, this focus on agriculture has led to environmental problems, such as ecosystem fragmentation, a decline in biodiversity, soil erosion, and reduced surface runoff [46]. With a population of 360 million in 2018, including a rural population of 189 million, the pressure on the land has become unbearable, exacerbating land degradation in the study area [47]. Furthermore, national policies have led to the improvement and proliferation of highways and high-speed railways, which have contributed to economic development, but they have also led to the removal of vegetation and loss of ecosystem services [44].

**Figure 1.** The geographical location of Guizhou province.
