1. Introduction
Habitat quality (HQ) refers to the ability of ecosystems to supply and support essential goods and services for both individuals and groups [
1,
2], which is reflected in the status of regional biodiversity to a certain extent [
3,
4]. Biodiversity includes the diversity of animals, plants, and microorganisms at the genetic, species, and ecosystem levels, providing regulating, supporting, and cultural ecosystem services [
5]. The increase in human activities has led to widespread biodiversity loss and disintegration of ecological and socioeconomic systems [
6,
7], which harm the well-being of local communities [
8]. In developing countries, the pressure is even greater, with the majority of the poor being dependent on natural resources for their livelihoods [
9]. Land-use and land-cover (LULC) changes are essential manifestations of human activities, which pose a significant risk factor for HQ [
10,
11]. LULC changes, including changes in proportions, structures, and intensity, fundamentally alter the composition and configuration of ecosystems and, ultimately, influence the energy flow and material circulation between habitat patches [
12,
13]. Therefore, habitat conservation is increasingly threatened by anthropogenic impacts, particularly human-dominated LULC changes that are regarded as a key factor influencing HQ decline [
14].
HQ is a significant foundation for ecosystem service capacity and biodiversity maintenance [
15]. Early research on habitats mainly focused on the habitat status of specific species and habitat impacts on species [
16,
17]. With the development of environmental science, many models, such as the HIS model [
18], the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model [
2], and the Social Values for Ecosystem Services (SolVES) model [
19], have emerged to efficiently calculate HQ attributes at various scales. The “HQ” module in the InVEST model (InVEST-HQ) is a widely used ecological function assessment model [
20] that assesses HQ by combining habitat suitability with anthropogenic threats to biodiversity and provides more detailed information regarding biodiversity status [
17,
21]. The main advantages of the InVEST-HQ are that the assessment module parameters are readily available and the results are accurately analyzed, thereby reflecting habitat distribution and degradation status of different landscape types [
22].
Topography is an important natural factor, which substantially influences the spatial pattern differentiation of ecosystem services and HQ [
23]. Furthermore, terrain factors have major impacts on nutrient exchange and energy circulation in habitat systems [
24]. Numerous studies have focused on the impact of land-use change on HQ in watersheds [
18], hilly areas [
22], and cities [
25] to highlight the relationship between HQ and land use, and landscape patterns and topographic factors [
26,
27]. However, few studies have explored variations in HQ with topographic gradients.
The Key Biodiversity Conservation Project Area of Wuling Mountains (KBCPW) is an important region for ecological protection and restoration located in Guizhou province, China. The KBCPW is a typical karst plateau mountain area characterized by a unique landform consisting of mountains and hills. As an important part of the terrestrial ecosystem, mountainous areas are rich in biodiversity and provide strong support for regional economic development. However, plateau ecosystems are exposed to many risks, such as habitat loss and environmental degradation [
28]. The ecological environment in mountainous areas is increasingly becoming vulnerable to the irrational use of resources by humans, which has led to several ecological problems and hindered local economic development. The distribution of mountainous habitats is influenced more by topographic factors than that of plain agricultural areas. Therefore, an assessment of HQ in ecologically sensitive mountainous areas from a topographic perspective is crucial for understanding the spatiotemporal differentiation characteristics of HQ and enhancing effective ecosystem management.
The protection and maintenance of biodiversity, as well as satisfaction of human demands, have become of increasing concern [
29]. Understanding the response of HQ to LULC change is important for maintaining biodiversity and land management; therefore, it is necessary for policymakers to predict habitat protection based on the exploration of habitats changes [
30]. In this study, we mapped and identified the HQ of the KBCPW and analyzed the variations in HQ during the 1900–2018 period based on the land-use data from 1990, 2000, 2010, and 2018. Subsequently, the terrain gradient effect on HQ was analyzed to reveal the variations in HQ using the topographic position index.
4. Discussion
The ecological environment in mountainous areas is harsh and habitats are poor due to the impact of human activities and natural factors. Specifically, the contradiction between humans and land in mountainous areas dominated by karst ecosystems is prominent. Mountain ecosystems are fragile, and high habitat heterogeneity and severe rocky desertification enhance their fragility [
44,
45]. In this study, the KBCPW in Guizhou Province was considered an example of a karst plateau mountainous area. Our results revealed variations in the spatiotemporal characteristics of HQ in the KBCPW from 1990 to 2018, which are caused by land-use change and the distribution characteristics of HQ from a topographic perspective. The results provide a scientific basis for territorial space planning and habitat protection in mountainous areas, which is crucial for the rational and sustainable use of land resources, as well as the construction of ecological civilization.
According to the results of the present study, land-use change in the KBCPW over the 1990–2018 period was characterized by an increase in construction and cultivated lands, and a decrease in forestland and grassland. The main land-use changes in the KBCPW were the conversion of cultivated land to construction land and forestland, and the mutual conversion between grassland and forestland. These changes improved landscape heterogeneity and the degree of fragmentation. The HQ of the KBCPW was generally high, with a significant spatial difference being observed. Furthermore, the high HQ was mainly distributed in forestland and grassland, while low and medium HQ were distributed in cultivated and construction lands. With regard to the topographic gradient, the topography of the study area is complex, characterized by a large topographic gradient in the northwest and southern edges and central areas, and a relatively small spatial pattern of topographic gradient in the eastern region, which still reflects the supporting or limiting effect of geographical environment, such as topography and geomorphology, on HQ and change [
46]. Low HQ was dominant in low topographic gradients, whereas high HQ was dominant in high topographic gradients, which could be because HQ is correlated with terrain and land-use type. Mountainous terrain varies greatly, and changes in elevation gradients lead to vertical distribution patterns of vegetation [
47]. Therefore, the elevational distribution of regional HQ depends on the spatial distribution of LULC. In addition, the results of the present study revealed that LULC changes substantially affected HQ.
Regional HQ has a direct impact on local human welfare. With increased socioeconomic development and population growth, the demand for land and the impact of human interference on habitats are increasing. Despite the implementation of policies, such as "returning cultivated land to forestland" and "closing mountains through reforestation", the HQ in the KBCPW has improved significantly. The LULC in the study area underwent drastic changes from 1990 to 2018: the area of forestland decreased by 134.4km2, the shape of forestland became more complex, and the degree of agglomeration decreased; the area of grassland decreased by 241km2 and the fragmentation of grassland patches increased; and the construction land area increased rapidly by 4.5-fold and cultivated land increased by 0.23%. Rapid urbanization and a large amount of cultivated land demand have made a large number of forestland and grassland areas in this area occupied by construction land and cultivated land, resulting in habitat loss and fragmentation, which, in turn, has led to an increase in low HQ areas in the region. The KBCPW experienced habitat degradation during the 1990–2018 period. The areas with HQ decrease are largely located in the northeastern and eastern regions of the KBCPW due to the accelerated urbanization, rapid expansion of construction land, and the loss of large areas of forestland. The changes in land use consequently threaten the surrounding habitats, leading to increased habitat fragmentation and poor connectivity, and ultimately habitat degradation in the region. The areas with improved HQ are located in the southern and northern parts of the KBCPW, which could be due to the implementation of projects, such as “returning cultivated land to forestland” and “closing mountains for afforestation and grass cultivation”. Although conservation policies promote the improvement of ecological environments in some areas, the positive impact of policy interventions on environmental protection cannot compensate for the negative impact of human activities. Therefore, to promote a balance between sustainable development and environmental protection, political and economic policies should be formulated from the perspective of ecosystems.
The InVEST model is relatively mature and has certain advantages over other traditional methods in terms of spatial expression and dynamic research [
39,
48]; however, there is a certain subjectivity in the parameter setting in the calculation, and the parameter verification and rationality evaluation are worth discussing in depth. The HQ assessment results obtained using the InVEST-HQ model depended on land-use classification. Land use was classified into six categories and the datasets did not take into account the internal heterogeneity of each land-use type. In the present study, the model is based on the assumption that regions with high HQ have high biodiversity, while regions with low HQ have low biodiversity [
35]. However, in reality, areas with good regional HQ do not necessarily have a rich species diversity and the principles of the module are more inclined toward vegetation diversity, which presents certain limitations when calculating regional HQ [
13]. Although the InVEST model has limitations in assessing HQ, it can be calculated by inputting land-use parameters, thereby providing basic information for guiding ecological environment protection.
5. Conclusions
Understanding the spatial and temporal changes of HQ is of great significance for regional sustainable development. The present study used the InVEST model to explore the spatiotemporal variations in HQ and its response to topographic gradient effect in the KBCPW in Guizhou Province during the 1990–2018 period. The results were as follows:
(1) Cultivated land, grassland, and forestland were the main land-use type in the KBCPW during the 1990–2018 period. The major land-use changes in the study area were the conversion of cultivated land to construction land and forestland and the conversion of forestland to cultivated land and grassland.
(2) Cultivated land was the dominant landscape in the KBCPW, followed by forestland. Landscape patches tended to fragment, which, in turn, shaped complexity and variety and decreased connectivity. Land-use types exhibited varying trends in their landscape patterns.
(3) The HQ of KBCPW showed a downward trend from 1990 to 2018, although the overall HQ was high, which was attributed to the high HQ of the areas covered. Spatial differentiation in the study area was significant. High HQ was observed in areas dominated by forestland, while relatively low HQ was observed in construction and cultivated lands, which were the major land-use types and were closely associated with human activities.
(4) HQ exhibited varying spatiotemporal patterns with topographic gradients and HQ degradation was predominantly distributed in low terrain areas. Generally, HQ degradation in low terrain areas was relatively high, slight degradation was observed in the medium terrain areas, and HQ in the high terrain areas was stable.