Introduction

Oases are the most productive, dynamic, and vulnerable systems in drylands that supply stable water resource, basic resources and conditions for human survival and living environments (Bie & Xie, 2020; Chen et al. , 2022; Xue et al. , 2015, 2019). Oases are also crucial ecological barriers in drylands defeating desertification (Abuzaid & Abdelatif, 2022), salinization (Li et al. , 2021), and sandy weather (An et al. , 2022). Since the 1950s, artificial oases had expanded due to the land reclamation and agriculture in northwest China (Wang, 2010), which contributed to sufficient and stable food production and economic growth (Zhou et al. , 2017), and caused series of eco-environment problems. Because of the extremely drought weather and limited water supply, oases had experienced groundwater reduction, desertification expansion, and grass degradation (Luo et al. , 2020; Ma et al. , 2022; Xue et al. , 2019; Yan et al. , 2021), which deeply influenced the stability of oasis systems. Therefore, it is necessary to quantify the oasis spatio-temporal patterns and its driving factors under natural and human impacts.
Previous studies have explored the spatio-temporal oasis patterns and the interactions between oasis and various factors (e.g., natural and human factors). Land use dynamic model and landscape pattern index were the common methods to quantify and forecast the oasis dynamic changes (Lü et al. , 2020; Xiao et al. , 2019; Chen et al. , 2023; Liu et al. , 2021). For examples, Amuti & Luo (2014) analyzed Hotan oasis temporal changes using land use/land cover (LULC) data and the main driving factors of oasis changes during 1990 and 2008, which found that intensified human activities reduced the desert-oasis ecotone. Tan et al. (2020) analyzed the oasis changes of Zhangye city from 1980 to 2015, and simulated the future oasis changes in 2030 applying future land use simulation model (FLUS), LULC data, geography and socioeconomic data; the authors found that main transfers of oasis transition existed in cropland, built up, waterbody and desert from 2015 to 2030. These methods mainly described oasis transitions from a specific land type to another in terms of type and quantity, ignoring the changing processes in the entire oasis transition system (Zhanget al. , 2021). Moreover, the identification of key land type mostly relies on the amount of the changed area and rate, which could not express the interactions among different oasis types, oasis and non-oasis types, even the oasis structural stability.
Therefore, the complex network model was introduced in this paper to analyze the dynamic processes within oasis types. As a theoretical method, a complex network is composed of a large number of interconnected nodes, performing substantial non-trivial topological features of the target system and quantifying the interactions among the sub-systems (Newman, 2003; Zhang et al. , 2020). It has demonstrated that the complex network is an effective tool in modeling and analyzing the land use change processes (e.g., urbanization, afforestation / deforestation) and identifying the key land types during those processes. Xu et al. (2023) studied the complex relationship in the procession of LULC using complex network, which concluded that key land types were more vulnerable to change and had greater impacts on land ecosystems. Zhang et al. (2020) constructed the complex network of landscape index and patch type index, and evaluated the stability of landscape and network in Pingshuo opencast mining area in China during 1986 and 2015. The authors found that the landscape heterogeneity tended to be unstable, and the network length became shorter, demonstrating more human activities in mining areas during the study period. So far, the applications of complex network in investigating oases transition and stability were scarce, especially on the long-term large scale.
In this study, we conducted oasis transition processes and structural stability investigation using the constructed oasis transition network and analyzed driving factors over Tuha Basin during 1990 and 2020. Our research aims to (1) find out the spatio-temporal patterns for different oasis types, (2) simulate the oasis transition processes and identify the key oasis types, and (3) discover the main driving factors for natural and artificial oasis.