An integrative methodology framework for assessing regional ecological risk by land degradation using the case of the Qinghai–Tibet Plateau

Land degradation poses significant threats to the sustainability of ecosystem structures, functions, and services, leading to increasing ecological risks. However, integrative assessment of the ecological risk driven by land degradation remains a challenge. In this study, we established a methodological framework for assessing regional ecological risk by integrating degenerative land use transitions with multiple ecological indicators. Specifically, 11 degradation modes of land use transitions and 7 indicators on ecosystem structures, functions, and services are quantitatively integrated using remote sensing data from 2000 to 2020 in the Qinghai-Tibet Plateau of China. Results revealed that the comprehensive ecological risk of the plateau is higher in the southern and northern regions. Furthermore, we found that land development from forests towards cropland and degradation towards grasslands lead to higher ecological risks than grassland development and degradation. The ecological risk tends to show a significant distance decay pattern around the patches with land degradation. Our research framework provides an efficient, explicit, and transferable means of exploring spatiotemporal changes in ecological risk caused by degenerative land use transitions at the regional scale. It presents a constructive tool for facilitating regional-scale land use and ecosystem management planning and assessment.


Introduction
Land degradation is a major source of ecological risk (Blaikie and Brookfield 2015).Land use/cover (LULC) provides quantitative and essential natural resources, ecosystem services (ESs), and functions for human needs (Andrew et al 2015, Gaglio et al 2017).However, land degradation is accelerating with the rapid expansion of degenerative land use transitions such as those from natural or semi-natural ecosystems to built-up lands and croplands (Zhang et al 2007, Liu et al 2022a, Lin and Wang 2023).This can severely damage the ecosystem (Assessment 2005, Song and Deng 2017), strengthen biological homogenization (Sahraoui et al 2021), hinder ecological processes such as the water cycle, soil accumulation, and plant photosynthesis (Mascarenhas et al 2019, Lu et al 2022), affect the geochemical cycle (Dunn et al 2012, Guan et al 2021), and cause biodiversity losses, which exacerbate regional ecological risks (Foley et al 2005, Xie et al 2020).It is expected that the impact of land degradation will intensify in the future (Chen et al 2020, Mohamed and Worku 2020), highlighting the urgent need for prevention and control measures (Zhang et al 2018).
Land degradation currently affects 25% of the Earth's land and 40% of its cropland (Pacheco et al 2018).As a major global environmental challenge (Dube et al 2017), the United Nations estimates that land degradation causes economic losses of $490 billion annually (Baskan et al 2017).On multiple spatiotemporal scales, land degradation is costly for local owners and society as a whole (Sutton et al 2016).Prevention of land degradation and ecological risk management are effective measures to address the major challenges mentioned above.Global Goal 30 × 30 is a commitment included in the Kunming Montreal Global Biodiversity Framework to protect at least 30% of land and oceans by 2030, in order to prevent biodiversity decline and enhance resilience to climate change.Corresponding measures include sustainable land management practices that avoid or reduce degradation, as well as efforts to reverse degradation by restoring degraded land.However, effective land degradation and ecological risk assessment are prerequisites for achieving the above steps (Chen et al 2013, Piet et al 2017, Guo et al 2022).Ecological risk assessment is a flexible process for organizing and analyzing data, assumptions, and uncertainties to evaluate the probability of adverse ecological effects that may have occurred or may occur as a result of exposure to stressors (Assessment 1998, Suter 2016).The implementation of ecological risk assessment involves various organizational scale models, including sub-organisms, populations, communities, the entire ecosystem, and social-ecological systems (Chen et al 2013).The commonly used risk assessment methods involve building risk assessment models supported by indicator selection (Lou et al 2020, Chen et al 2023, Lin and Wang 2023).
There are currently many ecological risk assessment methods and indicator systems, however, these studies rarely take ecosystem structure, services (Díaz et al 2018), and functions integrately as risk receptors.This limitation may hinder ecological risk assessment's ability to support decision-making and practical applications in landscape planning.Although Liang and Song (2022) considered potential ESs in the ecological risk assessment of LULC changes, they did not provide detailed rules and results for the simulation of the LULC, making it challenging to clarify the relationship between the two and ecological risk.Similarly, Lu et al (2022) systematically and extensively studied the risk of ES degradation in Wuhan, China, from the perspective of land development, but the issue of spatiotemporal scale effects in the study has not been adequately addressed.Moreover, current research efforts do not couple fundamental ecosystem structural and functional indicators, nor do they provide comprehensive insights into the role of land development and degradation in supporting regional ecological risk assessment (Balvanera et al 2022).Considering that the existing ecological risk assessment of land degradation is primarily based on landscape pattern indices, there is a dearth of studies on coupling parameters such as ecosystem structurefunction-service indicators.
The United Nations Disaster Relief Coordination Office (UNDRO) emphasizes two crucial concepts: (1) the probability of natural disasters as destructive natural phenomena that occur within a given region during a specific time period; (2) the product of risks such as loss of life, personal injury, and property damage (Blaikie and Brookfield 2015).Accordingly, land degradation can be regarded as a risk source, and the resulting ecosystem structure-function-service indicators are risk receptors, the two types have the equal weight.Therefore, a new methodological framework can be formulated to address the above gaps in ecological risk assessment.Taking the Qinghai-Tibet Plateau (QTP) of China as a typical case, the aims of this paper are as follows: (1) establishment of a methodological framework on regional ecological risk assessment by integrating degenerative land use transitions and ecosystem attribute indicators; (2) characterization of the spatiotemporal changes of ecological risk in the QTP during the past 20 years; (3) discussion on the implications of the ecological risk assessment at the regional scale.

Study area
The QTP (26 1), encompasses 26.8% of the total area of China (Zhang et al 2002, Yao et al 2012).It is a prime example of an ecologically vulnerable area and serves as China's national ecological security shelter.The plateau boasts an average altitude of over 4000 m, widespread frozen soil, and a crisscrossed river system, earning it the monikers 'Third Pole of the Earth' and 'Asian Water Tower.' From southeast to northwest, the plateau develops into a horizontal zonal distribution from forests to shrubs, alpine cushions, alpine meadows, and alpine steppes, culminating in alpine deserts and barren land.The overall annual mean temperature is low (−5.6 • C-8.6 • C) and has a low annual mean precipitation (486 mm), but solar radiation is strong (5.86-8.37 × 10 9 J m −2 ) (Li et al 2020).Research shows that the plateau has experienced twice the global warming rate in recent years (Zhang et al 2021), hastening the retreat of glaciers.Furthermore, with the increase of the plateau population and the acceleration of urbanization, the land use structure has undergone changes and degradation, and ESs and ecosystem functions have shown severe degradation at the regional scale (Harris 2010, Yang et al 2010, Fayiah et al 2020).Consequently, regional ecological risks have increased (Liu et al 2022a), threatening the safety of China's national ecological shelter.

Data source
The data used in this study mainly include meteorological data, DEM, soil data, LULC data, leaf area index

Methodological framework
The UNDRO defines disaster risk as the likelihood of a disaster occurring and the product of the harm caused by the disaster (UNDRO 1991, Chen et al 2013).The probability of disaster occurrence is considered as the probability of risk occurrence, while harm refers to the loss inflicted on the ecosystem and human beings once the risk materializes (Liang and Song 2022).Enlightened by these concepts, we formulate a new methodological framework for regional ecological risk assessment pertinent to In this study, we examined 11 types of degenerative land use transitions using ArcGIS software (figure 3 and table S1).We used the dimidiate pixel model (Carlson and Ripley 1997, Gutman and Ignatov 1998, Wu et al 2014) to calculate FVC, while NPP was obtained based on the CASA model (Potter et al 1993, Peng et al 2016).Soil RH was calculated using the empirical formula (Pei et al 2009, Zhang et al 2023).WY and HQ were obtained based on the InVEST model (Su and Fu 2013, Terrado et al 2016, Wu et al 2021a).SE was quantized using the revised universal soil loss equation (RUSLE) model (Wischmeier andSmith 1965, Zhang et al 2015).All the aforementioned data were analyzed on an annual scale, with a consistent spatial resolution of 1 km (figure S1).Through comparative analysis of  2) from grassland to built-up land, (3) from cropland to built-up land, (4) from water to built-up land, (5) from forest to grassland, (6) from forest to barren, (7) from grassland to barren, (8) from cropland to barren, (9) from water to barren, (10) from forest to cropland, (11) from grassland to cropland.multi-source data (figures S2-5), we found that the settlement results of ecological factors have high accuracy and scientificity.As for EI, SE, and RH are subtraction operations, as their increase weakens ecological functions and exacerbates ecological risks.Subsequently, we conducted a slope analysis of a comprehensive ecosystem indicator based on the 7 structural or functional indicators.And ecosystem degradation can be detected when the slope is below zero.Finally, the ecological risk can be quantified by the land degradation probability (LD p ) and the status of ecosystem degradation (the EDI) (figure 2).In addition, we attempted to simulate the distance effect of the degenerative land-use transitions on ecological risks by buffer zone analysis (including 1 km, 3 km, 5 km, 10 km, 15 km, and 30 km buffers).The above research framework is simple and feasible, with strong portability (figure 2).

Quantification of ecological indicators 2.4.1. Quantification of FVC
FVC is the best indicator of vegetation growth status, with values between (−1, 1).It can be calculated based on the pixel binary model (Carlson and Ripley 1997, Gutman and Ignatov 1998, Wu et al 2014), which is defined as the following formula: where FVC c is the vegetation coverage fraction of the mixed pixel, NDVI is the NDVI of the mixed pixel, NDVI soil is the NDVI of the bare soil, and NDVI veg is the NDVI of the vegetation.

Quantification of RH
The carbon emissions from soil microbial respiration are calculated by regression equations of temperature, precipitation, and carbon emissions (Pei et al 2009, Zhang et al 2023).The calculation formula is as follows: where T represents temperature, R represents precipitation, 30 is the number of days of monthly meteorological data, and 46.5% is the proportion of soil respiration.

Quantification of NPP
NPP was obtained based on the CASA model (Potter et al 1993, Peng et al 2016).The calculation formula for this assessment is as follows: where NPP(x, t) is the NPP (gC/(m 2 of pixel x at time t; APAR is the photosynthetically active radiation absorbed by vegetation (MJ/(m 2 •a)); it is estimated from the total solar radiation (gC m −2 ) of SOL and the absorption ratio of vegetation to the fraction of photosynthetically active radiation (FPAR); and ε is the efficiency of converting FPAR into organic carbon (gC/MJ 2 ), which is calculated from the maximum light energy utilization rate (ε max ), temperature stress (Tε) and water stress (Wε).Finally, the annual NPP is the sum of the monthly NPP of the same year.

Quantification of WY
In this study, the WY module of the InVEST model (Su and Fu 2013) was used to quantify the annual WY of QTP from 2000 to 2020, and the calculation formula is as follows: where WY(x) is the annual WY (mm) of a specific land use type in pixel x (mm); AET(x) is the actual yearly evaporation of pixel x; P(x) is the annual precipitation (mm) of pixel x; PET(x) is the potential evapotranspiration of pixel x; ET O (x) is the reference (vegetation) evapotranspiration; K C (x) is the plant evapotranspiration coefficient; AWC(x) is the available water content of plants; w(x) is the empirical parameter; Z is the tension coefficient.

Quantification of SE
SE was calculated by the RUSLE model (Wischmeier andSmith 1965, Renard et al 1991), and the calculation formula is as follows: where SE is the soil erosion per pixel, whose units are t ; L and S are the slope length and slope factor; C is the vegetation coverage factor; and P is the conservation support practice factor.

Quantification of HQ
The calculation of HQ was using the HQ module in the InVEST model (Terrado et al 2016, Wu et al 2021a), and the calculation formula is as follows: where the sum of the total threat's level in a grid cell x of habitat type j provided a degradation score D xj for the cell (equation ( 9)) that was then used along with habitat suitability to compute a score of HQ HQ xj (equation ( 10)).z and k in equation ( 10) are scaling parameters.The values obtained for HQ after model application range from 0 to 1, with 1 meaning the highest HQ.

Quantification of ecological risk
Seven ecological indicators are integrated to quantify the general status of ecosystems at the regional scale.These indicators include FVC, LAI, NPP, RH, WY, SE, and HQ.The calculation formula is as follows: where EI j is the sum of seven ecological indicators standardized in grid j.EI ij is the standardized ith ecological indicator of the grid j using the minmax standardization method (Zou et al 2021, Li et al 2023b).The value range of EI j is 0-5.The higher the value, the better the ecosystem in structural and functional attributes.The value range of EI ij is 0-1, and the closer the value is to 1, the better for the ecosystem on specific structure or function indicators.
The ecosystem degradation index (EDI) is quantified using the following formula: Among them, i represents the year .This study's ultimate goal is to establish an ecological risk based on the perspective of likelihood and harm.We calculate the ecological risk according to the following formula: where ER is the ecological risk index, and LD p represents the probability of land degradation in a 3 km × 3 km grid.Finally, we standardized ecological risk also using the min-max method, and ecological risk is from 0 to 1 (Zou et al 2021, Li et al 2023b).The higher the ecological risk value, the higher the risk.

The land degradation represented by degenerative land use transitions
Over the past two decades, among the 11 types of land use transitions that can lead to land degradation in the QTP, the predominant transitions include grassland to barren (57 239 km 2 , 67.93%), water body to barren (14.60%), and grassland to cropland (6.50%), as illustrated in figures 4 and S6.The overall changes in land use types over different time scales at 5 year intervals show similar trends, with the primary types of transition being grassland to barren, water body to barren, forest to grassland, grassland to cropland, and forest to cropland.For the conversion probability of LULC, its spatiotemporal distribution has strong heterogeneity.From 2000 to 2010, its high-value areas were scattered in the northern and central southern parts of the QTP.However, the results in the last decade and 2000-2020 are relatively similar, and the high-value areas are relatively concentrated, mainly in the northern and central southern regions of the plateau.

Spatiotemporal distribution of EDI by land degradation
In the initial and recent 20 years, the areas with decreased EDI were mainly concentrated in the southern and northern parts of the plateau (figure 5).
During the period from 2005 to 2010, the degraded areas were also located in the western part of the plateau, the northern part in 2010-2015, and the southern part from 2015 to 2020.The results (figure 6) show that in the past 20 years, the conversion of forests to built-up land (−0.011) and cropland (−0.008) has led to the most significant ecological degradation, followed by the conversion of grasslands to built-up land (−0.007) and cropland (−0.004).
Overall, the degradation intensity of ecological indicators in land development (from natural or seminatural land cover to built-up areas) is higher than other transition types.Moreover, the direction and degree of the impact of land degradation on EDI vary across different research periods (figure 6).From 2000 to 2005, the transition of water bodies towards built-up land (−0.006) and forests towards cropland (−0.002) resulted in a decrease in EDI; From 2005 to 2010, the transformation of forests (−0.001) and grasslands to cropland (−0.001) resulted in a negative EDI, which is similar to the situation from 2010 to 2015.The results in 2015-2020 show that the transformation of forest (−0.001) and grassland to cropland (−0.001), as well as the transformation of grassland to barren (−0.001), has led to ecological degradation.In terms of intensity, the results for the years 2000-2005 are higher than those for the last 15 years.

Spatiotemporal distribution of ecological risk by land degradation
The spatial distribution of ecological risks in the QTP (figure 7) is determined by the probability distribution of the degenerative land use transitions and distribution of EDI.In 2000-2020, the high-value areas of ecological risk were mainly concentrated in the southeast parts of the plateau, as well as the vast areas in the central part.In the eastern old-growth forest area of the plateau, the risk value is low.In 2000-2005, the risk zone was mainly concentrated in the southern edge of the plateau, and in the following five years, the area was also located in a vast area in the northwest of the QTP.In 2010-2015, compared to the results of  the past 2 decades, the low-risk areas in the eastern region were relatively expanded.From 2015 to 2020, the ecological risk region of the plateau was mainly concentrated in the southern and northern parts.
The analysis of the overall situation (figure 8) shows that between 2000 and 2020, land development from forests to cropland (0.11) and land degradation from forests to grasslands (0.09) led to the most significant ecological risk, followed by grassland development (0.07) and degradation (0.06).The risk distribution in 2000-2005 and the following 5 years is roughly similar.Grassland and water degradation are the main risk sources, while forest degradation and development are secondary factors.From 2010 to 2015, the ecological risk values of various categories were higher than 0.10, and the degradation of forest to grassland resulted in an ecological risk of 0.26.In 2015-2020, the development of grassland to cropland resulted in a higher ecological risk (0.39).In addition, buffer analysis of six scenarios showed that from 2000 to 2020 and every five years, ecological risk gradually decreased with the increase of buffer width (figure S7), especially with a sharp decrease in ecological risk at 1 km.

The advantage and usability of the methodological framework
In this study, we formulated the ecological risk assessment framework for the quantification of regional ecological risk as the multiplication of degenerative land use transition probability and the EDI.This study does not focus on any specific one-dimensional aspects but instead uses multidimensional information to establish reasonable interrelationships among ecological risk, LULC, and ecosystem structurefunction-service factors.The framework can provide visual evidence for decision-making on ecological risk mitigation, serving as a novel method for land resource management research.The transition probability of LULC under this framework is obtained based on the moving window method, rather than approximating the probability using the entire plateau, which greatly improves the accuracy of results.The relevant research indicates that the LULC transition probability is not sensitive to window size (Li et al 2023a).Taking into account high accuracy and fast computation, we have selected an appropriate size (3 km × 3 km), which is comparable to other study (Li al 2023a).Secondly, our land degradation includes two connotations, representing the types of degenerative land use transition and land development, respectively.Eleven conversion rules (figure 3) basically cover all possible degradation situations in the plateau in the past decades.We noticed that the results of this method mainly depend on the selection of land degradation types and ecological indicators, so we comprehensively considered these aspects as much as possible based on the characteristics of the plateau, especially considering the widespread distribution of vegetation ecosystems on the plateau, although there may be issues of duplication and functional redundancy between factors (Wang et al 2021, Felix et al 2022).Therefore, the seven ecological indicators for ecological processes were carefully chosen.For multiple ecological factors, we conducted a comparative analysis of the data results to determine their accuracy (figures S2-5).Moreover, the spatiotemporal distribution pattern of our ecological risks is similar to the research results of Liang and Song (2022).The framework proposed by UNDRO is an outstanding workflow that integrates the above 18 indicators to comprehensively reflect ecological risks.There is little relevant research (Xie et al 2021), and our method is an improvement of this framework and an expansion of the existing literature on ecological risk assessment relevant to land degradation.
It is worth emphasizing that even in different regions around the world, the development and degradation types of land use have a certain similarity in land type conversion, and the selection of sub indicators in EDI indicators has a crucial impact on the determination of EDI (Assessment 1998, Gravley 2001, Wu et al 2021b).Especially different regions have different ecological and environmental structural characteristics, providing different ESs and functions.Therefore, we suggest that the selection of indicators should be careful and cautious.For example, the QTP and its similar regions should pay more attention to the degradation and disorderly development of natural ecosystems such as alpine grasslands; The Yellow River basin in China may focus on water production services in the upstream (Sun et al 2023) and soil conservation in the middle reaches and the degradation of NPP under human activity interference (Yang et al 2023b).The Green Revolution in India and the accompanying agricultural intensification have addressed food and nutritional security issues, but have exacerbated air pollution, soil degradation, eutrophication of water bodies, pollution, and biodiversity loss (Pandit et al 2007, Lal 2022).Due to large-scale deforestation in the Amazon Basin, carbon storage has been directly reduced, disrupting the regional water balance (Foley et al 2007).Facing different ecological issues and environmental characteristics, we believe that there are multiple key solutions to address different challenges.In addition, risk receptors can also be expanded to involve social and economic dimensions under a socio-ecological perspective (Wang et al 2022).Therefore, the newly developed methodological framework for regional ecological risk assessment in the present research is also open for adaptation according to different regional contexts and requirements.

Conservation and restoration to address regional ecological risks
Land degradation not only incurs ecological risks but also affects the quality of the ecological environment.With the acceleration of urbanization and the adjustment of agricultural structure in the QTP, human disturbances have significantly strengthened, leading to increased ecological risks, decreased vegetation coverage, HQ, and biodiversity (Zhang et al 2022).Our results indicate that the impact of land degradation on ecological risks is broad and profound.The risk level in land degradation is relatively high, especially in the southern and central parts of the plateau (figure 7).The land use change in the Hengduan Mountains (Wang et al 2018) of the southern plateau is relatively severe (figure 5), with the expansion of builtup land and the reduction of forest and grassland being the main factors leading to the occurrence of local ecological risk (figure 8).In addition, although many ecological protection and restoration projects have been carried out in the central part of QTP, such as returning grazing land to forests and establishment of nature reserves, which have greatly improved ecological restoration (Xia et al 2021, Zhang et al 2022), our results still show that grassland development and degradation in the region have led to higher ecological risk (figure 8).However, the Three-River Headwaters region (figure S8) is affected by national policies, and the regional ecological quality has been improved with low ecological risk, which is consistent with the relevant research results (Xue et al 2022).In addition to the aforementioned negative consequences, the expansion of cities and farmland will also enhance landscape fragmentation, thereby affecting the ecosystem functions and services provided by continuous landscapes ( figure 6; Jin et al 2019, Huang et al 2022).
Based on the results of this research, we suggest increasing efforts in forest protection and grassland management, strengthening the intensive development of cities and agriculture, and reducing the damage to the ecological environment caused by human activities.For forests in the southern part of the plateau, priority should be given to protecting the biodiversity of the area.Although the land resources suitable for agriculture are mainly concentrated in the valleys of the middle reaches of the Yarlung Zangbo River in the south of the plateau, and the valleys of the Nujiang River, Lancang River, Jinsha River, and other tributaries in the southeast, it is an effective strategy to reduce the development of forests to cropland (Wang et al 2019) and the degradation to grasslands in this region.For the grasslands in the plateau, it is necessary to comprehensively reduce the disorder of land development (i.e.mainly from grassland to cropland), intensive grazing (Li et al 2021), and grassland degradation.Using fences to reduce the impact of livestock grazing and trampling on the grasslands.Planting artificial grasslands in appropriate areas is also a necessary mitigation strategy.For areas with low ecological risks, the construction of nature reserves and national parks should continue to be maintained.Especially the internationally initiated 30 by 30 refers to the commitment of governments around the world to protect 30% of earth's land and oceans by 2030 to address the many challenges posed by climate change.Moreover, the Chinese government has recently actively called for the establishment of the Earth's Third Pole national park group and nature reserve system (Zhao et al 2020, Fu et al 2021, Sun et al 2021), we believe that strengthening the overall nature conservation network on the QTP will mitigate the regional ecological risks and may have a wide range of impacts both domestically and internationally.Furthermore, we believe that risk reduction is an action with long-term impacts, including any policies or actions to reduce future damage and losses (Saunders and Becker 2015, Azadi et al 2020).Reducing ecological risks requires cross departmental and multi-party cooperation, especially in understanding the cultural, economic, and institutional mechanisms underlying ecological risks, in order to strengthen government guidance and management, support sustainable development, and enhance resilience, which requires long-term and unremitting efforts.
In this study, we present a theoretical framework that couples multiple land development and degradation types with ecological degradation indicators to assess regional ecological risk.Our findings show that the southern and northern regions of the QTP have experienced high comprehensive risks over the past two decades, highlighting the need to address ecological degradation resulting from land development in this area.Specifically, our results show that land development from forests towards cropland (0.11) and degradation towards grasslands (0.09) lead to higher ecological risks than grassland development and degradation.Our suggestion is to comprehensively reduce the disorderly development of land and the comprehensive degradation of plateau forests and grasslands under the process of urbanization and population growth.Further, under the guidance of international and national policies, strengthening the establishment and management of protected areas is recommended.The above measures are necessary to prevent and control the ecological risks of the plateau and give full play to the plateau's ecological safety shelter function.
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Figure 1 .
Figure 1.Location and land use/cover of the Qinghai Tibet Plateau.

Figure 2 .
Figure 2. The methodological framework for ecological risk assessment.The framework is composed of three steps of calculation: the first step is to calculate the degradation probability of LULC (LDp); Step 2: Calculate the comprehensive ecological degradation index (EDI) based on multiple ecological factors; Step 3: According to the first two steps, ecological risk ER = LDp × EDI.

Figure 4 .
Figure 4. Distribution of land degradation probability in the Qinghai Tibet Plateau.

Figure 5 .
Figure 5. Distribution of ecosystem degradation in the Qinghai Tibet Plateau.

Figure 6 .
Figure 6.Land degradation relevant mean ecological degradation at different time scales in the Qinghai Tibet Plateau.

Figure 7 .
Figure 7. Distribution of comprehensive ecological risk in the Qinghai Tibet Plateau.

Figure 8 .
Figure 8. Mean ecological risk at different time scales in the Qinghai Tibet Plateau.
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