Evaluation of the policy-driven ecological network in the Three-North Shelterbelt region of China

Highlights

• We built a policy-driven regional ecological network in China.

• We evaluated the corridors in the network using the space syntax approach.

• We identified vulnerable regions from the ecological network.

• We applied the ecological network for human footprint and biodiversity analyses.

Abstract

The Three-North Shelterbelt (TNS) program is one of China's major ecological restoration projects over the past few decades. However, evaluation of the ecological network in the TNS region has not been explored yet, in the face of intensified human activities. This study evaluated the ecological network in the TNS region from a policy-driven perspective (i.e., nature reserves). First, we mapped the ecological resistance surface in the TNS region using multiple remotely sensed ecological indicators. Then, using the derived resistance surface, we generated the ecological network and evaluated its connectivity (e.g., corridors) using the space syntax approach. Finally, we investigated the intensity of human activities and the occurrence of species around the derived ecological network. We found the ecological network is denser in humid regions than in arid areas. There are several vulnerable regions in the southern part of the Qilian Mountains and the northern part of Shaanxi. Besides, we observed overall consistent decreasing trends of human activities and species numbers along with the increase of distance to the ecological network, suggesting these corridors of ecological network play a crucial role in maintaining the biodiversity, although they are also under severe stresses of intensified human activities. Our study provides a paradigm of generating the ecological network at a large scale (i.e., the entire TNS region), showing great potential to support the phase III TNS program for sustainable development of ecological resources.

Introduction

Global environmental change (e.g., biodiversity loss and global warming) has broad impacts on human societies' sustainable development (Yang et al., 2020). Forest is a crucial resource for regulating the terrestrial carbon cycle and alleviating global climate change. Thus, forest resource management is important for mitigating potential environmental and climate change risks in the future (Smith et al., 2020). Over the past decades, the Chinese government has promoted relevant environmental protection policies in multiple regions (Bryan et al., 2018). With decades of effort, these policies are working with promising improvements in most regions, e.g., China has contributed about 25% of the increase of greenness globally, of which around 42% benefited from the afforestation project (Chen et al., 2019). Despite the ecological benefit of greenness increment, the vulnerability of afforested areas to climate change in the future is also a rising concern to be addressed (Watts et al., 2018).

The Three-North Shelterbelt (TNS) program is one of China's large-scale and successful ecological projects (Bryan et al., 2018, Cao et al., 2020a). The program was initiated in 1978 and is continuously promoted until 2050. The TNS plays an essential role in mitigating against damaging sand storms and desertification. The broad impacts of TNS have been extensively explored in terms of the vegetation dynamics (Deng et al., 2019, Qiu et al., 2017), land use and land cover change (Yin et al., 2018), and climate change (Zhang et al., 2016). For example, the ecological security of the TNS program was studied by optimizing the distribution of ecosystem services at the regional scale (Xiao et al., 2020). Also, the ecological network and landscape dynamics have been deeply explored at the local scale to identify vulnerable regions in the TNS area (Babí Almenar et al., 2019, Lü et al., 2015). However, most of these studies were performed at moderate and coarse resolutions, whereas analyses of ecological networks at fine resolutions and large scales were limited (Yu et al., 2017).

Although network analysis is a powerful tool to evaluate the vulnerability of the ecological environment, widely applications have not been made at a large scale (Dong et al., 2020, Lü et al., 2020). The ecological network concept characterizes the connections and interactions among elements in the landscape (Poisot et al., 2016) and emerged in the 1970s as a tool to aid nature reserve planning (Opdam et al., 2006). It has common elements comprising hubs, buffers, and corridors (Isaac et al., 2018, Schleuning et al., 2016). The structure, connectivity, and dynamics of biomes in the ecological network can be quantitatively explored (Hu et al., 2019, Pilosof et al., 2017), which is helpful to identify any vulnerability in the network from a biodiversity or conservation perspective (Delmas et al., 2019). Nevertheless, existing studies always focus on a local scale with simplified networks, limiting ecological networks' capacity in characterizing the connectivity and complexity of ecological corridors in ecosystems (Bohan et al., 2017, Yang et al., 2020).

The relationship between the impact of the human footprint and biodiversity conservation (Jones et al., 2018, Venter et al., 2016b), need simultaneous exploration in ecological networks. The human footprint map provides information about humans imposing pressure on natural systems and altering natural states (Venter et al., 2016a). Presently, the human demands on natural systems are accelerating, resulting in an unbalanced natural system with noticeable biodiversity loss (Mu et al., 2021, Tucker et al., 2018). Hence, quantifying the relationship between human footprint (and species) and the ecological network can support sustainable planning such as national parks (Xu et al., 2017, Zube, 1995). Meanwhile, the land cover can also shape the network by altering the biodiversity, ecosystem functions, and services (Felipe-Lucia et al., 2020). Combining multiple factors simultaneously (e.g., human footprint, biodiversity, and land cover data) makes it feasible to conduct an integrated assessment of the ecological network for ecological protection.

This study developed an analysis framework with the construction of the ecological network in the entire TNS region. Using the derived network and remotely sensed indicators, vulnerable regions were identified and the impacts of human footprint and biodiversity on the ecological network were also quantitatively measured. Unlike most studies about ecological networks that were made from landscapes shaped by land covers (e.g., wildland and forest) (Cao et al., 2020b, Liu et al., 2018), here we used nature reserves as primary ecological sources to reflect policy-driven impacts on ecosystems (Cumming et al., 2017, Svancara et al., 2005). In this study, we aim to answer two questions: (1) where are ecologically vulnerable areas in the TNS region? and (2) can the derived ecological network be used to quantify the impacts of human activities on biodiversity? The remainder of this paper is organized as below: Section 2 introduces the study area and relevant datasets; Section 3 describes the proposed analysis framework; Section 4 and Section 5 present our results and discussion, respectively; and a conclusion mark is ended in Section 6.