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.