Sensitivity and resilience of ecosystems to climate variability in the semi-arid to hyper-arid areas of Northern China: a case study in the Heihe River Basin

Exploring the spatiotemporal variations in regional rainwater harvesting potential resilience and actual available rainwater using a proposed method framework

Rainwater harvesting potential provides a basis for alleviating regional drought and water shortages. The resilience of rainwater harvesting potential is directly related to the sustainable level of actual available rainwater. Thus, SWAT model was combined with the proposed rainwater harvesting potential evaluation model to quantify rainwater harvesting potential, its resilience and actual available rainwater in the study area. The results showed that: (1) restoration of forest and grass increased the rainwater resource potential in the study area by 12.41 %, especially in the northeast, central and southwest of the study area. Although the surface runoff increased slightly in the past 20 years, it remained stable at 28.62 % of rainwater harvesting potential, which was benefited from the rainwater harvesting potential resilience to maintain the component stability; (2) rainwater harvesting potential resilience in the study area increased from class II to class III, which was closely related to the 17.93 % increase in the resilience intensity of the study area to resist external interference; and (3) surface runoff and net soil moisture content were the main components affecting the spatiotemporal variation of actual available rainwater, and lateral flow was also the main component affecting the spatial variation of actual available rainwater. In the past 20 years, the actual available rainwater has been increasing, and its conversion rate exceeded 89 %. The high level of actual available rainwater has been expanding to the western region with dense grassland coverage. This study provides a scientific basis for clarifying the sustainable utilization level of rainwater.

Study on Urban Resilience from the Perspective of the Complex Adaptive System Theory: A Case Study of the Lanzhou-Xining Urban Agglomeration

In the context of global environmental change and continuous urbanization, enhancing urban resilience is an important way to improve urban emergency management capacity and achieve sustainable development of urban systems. It is of great significance to clarify the mechanisms and effects of urban resilience and carry out resilience measurement to improve the level of urban system resilience and alleviate the pressure of environmental disturbances on the stable operation of urban systems. As an important part of the "Belt and Road" Initiative and one of the few leading economic regions in western China, promoting the high-quality development of the Lanzhou-Xining urban agglomeration is of profound significance for strengthening ethnic unity and stabilizing the northwest and southwest regions. Based on the complex adaptive system (CAS) theory and the adaptive cycle model, this study understands urban resilience as the comprehensive result of urban system stability, self-organization, learning adaptability and transformability, constructs a multi-level open index evaluation system, and analyzes the spatio-temporal evolution characteristics of urban resilience of the Lanzhou-Xining urban agglomeration from the proposed design to the formal planning in 2010-2017. The findings are as follows: (1) Research on the urban resilience of the Lanzhou-Xining urban agglomeration verifies the applicability of the evolutionary urban resilience analysis framework and makes preliminary findings on urban resilience based on CAS theory, which provide a certain theoretical reference for the research on the spatio-temporal evolution of urban resilience. (2) From 2010 to 2017, significant differences are observed between various urban attributes. Resilience exhibits an overall upward trend, and spatial evolution changes from a double core (Lanzhou and Xining) to three cores (Lanzhou, Xining and Haidong) and polycentric modes. (3) Based on urban resilience characteristics and an urban system adaptability cycle model, this paper divides the Lanzhou-Xining urban agglomeration cities into four types (exploitation-reorganization, conservation-release, conservation-exploitation and exploitation), and proposes corresponding adaptive management countermeasures. These could be adopted as a reference to promote the high-quality development of the Lanzhou-Xining urban agglomeration.

Resistance and Resilience of Desert Riparian Communities to Extreme Droughts

Changes in the resistance, recovery, and resilience of three desert riparian ecosystems to extreme droughts and the influence of ecological characteristics on them from 2000 to 2020 were analyzed within the Tarim River Basin, Xinjiang, China. The results showed that: (1) The resistance of the Populus euphratica forest community was the highest among the three plant communities. The recovery and resilience of the shrub community were the highest; (2) the resilience increased the most for the shrub community and decreased slightly for the Populus euphratica forest and herb communities as hydrological droughts waned; (3) the relative height and density significantly increased for Populus euphratica, decreased for herbs, and did not change for shrubs from 2000 to 2020; (4) the diversity indexes did not significantly change for the Populus euphratica forest and herb communities, and they increased for the shrub community from 2000 to 2020; (5) the resistance and resilience of the Populus euphratica forest, shrub, and herb communities were significantly affected by ecological characteristics, especially the Margalef richness index; and (6) the shrub community is more likely to rapidly recover (that is an increase of cover, height, and density) from future droughts in the Tarim River Basin, particularly with the implementation of new and more effective ecological restoration projects.

Interannual variability of vegetation sensitivity to climate in China

Many studies have assessed the relative sensitivity of ecosystems to climate change, and even optimized climate states from long-term averages to infer short-term changes, but how ecosystem sensitivity and its relationships with climate variability vary over time remains elusive. By combining the vegetation sensitivity index (VSI) and a 15 year moving window, we analyzed interannual variability in spatiotemporal patterns of vegetation sensitivity to short-term climate variability and its correlations with climatic factors in China over the past three decades (1982-2015). We demonstrated that vegetation sensitivity shows high spatial heterogeneity, and varies with vegetation type and climate region. Generally, vegetation in the southwest and mountainous regions was more sensitive, especially coniferous forests and isolated shrubland patches. Comparatively, vegetation in dry regions was less sensitive to climate variability than in wetter climates. Due to frequent climate variability in the early 1990s, a large increase in the VSI was detected in 1996. Significant increases in the interannual variability of vegetation sensitivity were observed in greater than 23.7% of vegetated areas and decreases in only 4.2%. Solar radiation was the dominant climate driver of vegetation sensitivity, followed by temperature and precipitation. However, climate controls are not invariable across a range of climatic conditions, such as precipitation exerted an increasing influence on changes of vegetation sensitivity. Quantitative analyses of ecosystem sensitivity to climate variability such as ours are vital to identify which regions and vegetation are most vulnerable to future climate variability.

Spatial Pattern Analysis of a Water-Related Ecosystem Service and Evaluation of the Grassland-Carrying Capacity of the Heihe River Basin under Land Use Change

A key challenge to the sustainability and security of grassland capacity is the protection of water-related ecosystem services (WESs). With the change of land use, the supply of aquatic ecosystem services has changed, and the grassland-carrying capacity has been affected. However, the correlation mechanism between WESs and the grassland-carrying capacity is not clear. In this study, we used the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model to evaluate the impact of land-use change on WESs, and made a tradeoff analysis between WESs and grassland-carrying capacity. Considering that the Heihe River Basin (HRB) was an important grassland vegetation zone, which was a milestone for the development of animal husbandry in China, HRB was taken as a case. The main findings are as follows: (1) the spatial distribution of WESs shows the dissimilation rule, the upper reaches are the main water yield area, the soil retention is weakening in the middle and lower reaches, and the pollution has further increased in the middle and upper reaches. (2) The carrying capacity of animal husbandry decreased in the upper reaches, increased in Shandan County and Zhangye City in the middle reaches, and decreased sharply in other regions. (3) There was a positive correlation between the livestock-carrying capacity and nitrogen export in 2018, which was increasing. As the change of land use has changed the evapotranspiration structure, WESs have undergone irreversible changes. Meanwhile, the development of large-scale irrigated farmland and human activities would be the source of a further intensification of regional soil erosion and water pollution. Therefore, it is necessary to trade off the WESs and animal husbandry under land-use change. This paper revealed how WESs changed from 2000 to 2018, the characteristics of the changes in the spatial and temporal distribution, and the carrying capacity. It aims to provide a scientific basis for coordinating the contradiction between grassland and livestock resources, improving the regional ecological security situation, and carrying out ecosystem management.

The effects of ecological rehabilitation projects on the resilience of an extremely drought-prone desert riparian forest ecosystem in the Tarim River Basin, Xinjiang, China

The Tarim River Basin in Xinjiang, China, has a typical desert riparian forest ecosystem. Analysis of the resilience of this type of ecosystem under extreme drought conditions and ecological rehabilitation projects could provide a theoretical basis for understanding ecosystem stability and resistance, and provide new ecological rehabilitation measures to improve ecosystem resilience. We employed a quantitative framework to assess net primary productivity (NPP) resilience, emphasizing four aspects of NPP dynamics: NPP, NPP stability, NPP resistance, and maximum NPP potential. We compared ecosystem resilience across four time periods: before the implementation of ecological rehabilitation projects (1990-2000), during construction and partial implementation of ecological rehabilitation projects (2001-2012), during the initial project stage of ecological rehabilitation (2013-2015), and during the late project stage of ecological rehabilitation (2016-2018). There are three main finding of this research. (1) Mean NPP was increased significantly from 2013 and was decreased from 2016, especially in the main stream of the Tarim River and in the basins of eight of its nine tributary rivers. (2) Ecosystem resilience in 2013-2018 was greater than in 1990-2012, with the greatest NPP stability, mean NPP and NPP resistance, especially in part one of the river basin (the Aksu River, the Weigan-Kuche River, the Dina River, the Kaidu-Konqi River, and the main stream of the Tarim River). Ecosystem resilience in 2001-2012 was lowest when compared to 1990-2000 and 2013-2018, with lowest mean NPP, NPP stability, NPP resistance and maximum NPP potential, particularly in part two of the river basin (the Kashigr River, the Yarkand River and the Hotan River basins). Therefore, part one was most affected by ecological restoration projects. When 2013-2018 was divided into two distinct stages, 2013-2015 and 2016-2018, resilience in the latter stage was the lowest, with lowest mean NPP, NPP resistance and maximum NPP potential, especially in the main stream of the Tarim River. This may be due to unreasonable water conveyance in 2014-2015. (3) Ecological resilience has increased significantly in 2013-2015 after the implementation of ecological water transfer projects, river regulation, and natural vegetation enclosure projects. Ecosystem resilience could continue to increase even more in the future with the continued implementation of reasonable ecological water transfer projects.

Variance of vegetation coverage and its sensitivity to climatic factors in the Irtysh River basin

Background

Climate change is an important factor driving vegetation changes in arid areas. Identifying the sensitivity of vegetation to climate variability is crucial for developing sustainable ecosystem management strategies. The Irtysh River is located in the westerly partition of China, and its vegetation cover is more sensitive to climate change. However, previous studies rarely studied the changes in the vegetation coverage of the Irtysh River and its sensitivity to climate factors from a spatiotemporal perspective.

Methods

We adopted a vegetation sensitivity index based on remote sensing datasets of high temporal resolution to study the sensitivity of vegetation to climatic factors in the Irtysh River basin, then reveal the driving mechanism of vegetation cover change.

Results

The results show that 88.09% of vegetated pixels show an increasing trend in vegetation coverage, and the sensitivity of vegetation to climate change presents spatial heterogeneity. Sensitivity of vegetation increases with the increase of coverage. Temperate steppe in the northern mountain and herbaceous swamp and broadleaf forest in the river valley, where the normalized difference vegetation index is the highest, show the strongest sensitivity, while the desert steppe in the northern plain, where the NDVI is the lowest, shows the strongest memory effect (or the strongest resilience). Relatively, the northern part of this area is more affected by a combination of precipitation and temperature, while the southern plains dominated by desert steppe are more sensitive to precipitation. The central river valley dominated by herbaceous swamp is more sensitive to temperature-vegetation dryness index. This study underscores that the sensitivity of vegetation cover to climate change is spatially differentiated at the regional scale.

Increasing sensitivity of alpine grasslands to climate variability along an elevational gradient on the Qinghai-Tibet Plateau

Monitoring and mapping the sensitivity of grassland ecosystems to climate change is crucial for developing sustainable local grassland management strategies. The sensitivity of alpine grasslands to climate change is considered to be high on the Qinghai-Tibet Plateau (QTP), yet little is known about its spatial pattern, and particularly the variations between different elevations. Here, based on the Normalized Difference Vegetation Index (NDVI) and three climate variables (air temperature, precipitation, and solar radiation), we modified a vegetation sensitivity index-approach to capture the relative sensitivity of alpine grassland productivity to climate variability on the QTP during 2000-2016. The results show that alpine grasslands on the southern QTP are more sensitive to climate variability overall, and that the climate factors driving alpine grassland dynamics are spatially heterogeneous. Alpine grasslands on the southern QTP are more sensitive to temperature variability, those on the northeastern QTP display strong responses to precipitation variability, and those on the central QTP are primarily influenced by a combination of radiation and temperature variability. The sensitivity of alpine grasslands to climate variability increases significantly along an elevational gradient, especially to temperature variability. This study underscores that alpine grasslands at higher elevations on the QTP are more sensitive to climate variability than those at lower elevations at the regional scale.

Assessing Water Availability in Mediterranean Regions Affected by Water Conflicts through MODIS Data Time Series Analysis

Water scarcity is a widespread problem in arid and semi-arid regions such as the western Mediterranean coastal areas. The irregularity of the precipitation generates frequent droughts that exacerbate the conflicts among agriculture, water supply and water demands for ecosystems maintenance. Besides, global climate models predict that climate change will cause Mediterranean arid and semi-arid regions to shift towards lower rainfall scenarios that may exacerbate water conflicts. The purpose of this study is to find a feasible methodology to assess current and monitor future water demands in order to better allocate limited water resources. The interdependency between a vegetation index (NDVI), land surface temperature (LST), precipitation (current and future), and surface water resources availability in two watersheds in southeastern Spain with serious difficulties in meeting water demands was investigated. MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI and LST products (as proxy of drought), precipitation maps (generated from climate station records) and reservoir storage gauging information were used to compute times series anomalies from 2001 to 2014 and generate regression images and spatial regression models. The temporal relationship between reservoir storage and time series of satellite images allowed the detection of different and contrasting water management practices in the two watersheds. In addition, a comparison of current precipitation rates and future precipitation conditions obtained from global climate models suggests high precipitation reductions, especially in areas that have the potential to contribute significantly to groundwater storage and surface runoff, and are thus critical to reservoir storage. Finally, spatial regression models minimized spatial autocorrelation effects, and their results suggested the great potential of our methodology combining NDVI and LST time series to predict future scenarios of water scarcity.