Spatiotemporal Evolution of Ecological Quality in Typical Karst Ecologically Fragile Areas Based on Remote Sensing Ecological Indexes

Fast and effective remote sensing monitoring is an important means for analyzing the spatio-temporal changes in ecological quality in fragile karst regions.This study focuses on Guanling Autonomous County,a national-level demonstration county for comprehensive desertification control.Based on Landsat TM/OLI remote sensing image data from 2005,2010,2015,and 2020,remote sensing ecological indices were used to analyze the spatio-temporal changes in ecological quality in Guanling Autonomous County from 2005 to 2020.The results show that:①the variance contribution rates of the first principal component for the four periods were 66.31%,71.59%,63.18%,and 75.24%,indicating that PC1 integrated most of the characteristics of the four indices,making the RSEI suitable for evaluating ecological quality in karst mountain areas;②the remote sensing ecological index grades have been increasing year by year,with an overall trend of improving ecological quality.The area of higher-grade ecological quality has increased spatially,while fragmented patches have gradually decreased,becoming more concentrated in the low-altitude areas in the northwest and east,and there is a trend of expansion towards higher-altitude areas;③the ecological environment quality in most areas has improved,with the improvement in RSEI spatio-temporal variation becoming more noticeable with increasing slope.Areas of higher-grade quality appeared in 2010,and the range of higher-grade quality expanded with increasing slope.

Ecological environmental quality evaluation and driving factor analysis of the Lijiang River Basin,based on Google Earth Engine

For regional ecological management,it is important to evaluate the quality of ecosystems and analyze the underlying causes of ecological changes.Using the Google Earth Engine(GEE)platform,the remote sensing ecological index(RSEI)was calculated for the Lijiang River Basin in Guangxi Zhuang Autonomous Region for 1991,2001,2011,and 2021.Spatial autocorrelation analysis was employed to investigate spatiotemporal variations in the ecological environmental quality of the Lijiang River Basin.Furthermore,geographic detectors were used to quantitatively analyze influencing factors and their interaction effects on ecological environmental quality.The results verified that:1)From 1991 to 2021,the ecological environmental quality of the Lijiang River Basin demonstrated significant improvement.The area with good and excellent ecological environmental quality in proportion increased by 19.69%(3406.57 km^(2)),while the area with fair and poor ecological environmental quality in proportion decreased by 10.76%(1860.36 km^(2)).2)Spatially,the ecological environmental quality of the Lijiang River Basin exhibited a pattern of low quality in the central region and high quality in the periphery.Specifically,poor ecological environmental quality characterized the Guilin urban area,Pingle County,and Lingchuan County.3)From 1991 to 2021,a significant positive spatial correlation was observed in ecological environmental quality of the Lijiang River Basin.Areas with high-high agglomeration were predominantly forests and grasslands,indicating good ecological environmental quality,whereas areas with low-low agglomeration were dominated by cultivated land and construction land,indicating poor ecological environmental quality.4)Annual average precipitation and temperature exerted the most significant influence on the ecological environmental quality of the basin,and their interactions with other factors had the great influence.This study aimed to enhance understanding of the evolution of the ecological environment in the Lijiang River Basin of Guangxi Zhuang Autonomous Region and provide scientific guidance for decision-making and management related to ecology in the region.

Spatiotemporal Evolution of Ecological Quality in Alpine Freshwater Lake Nature Reserves in the Past 20 Years

The Caohai Nature Reserve is one of the three major plateau freshwater lakes in China.Since the 1950s,human activities such as land reclamation and population relocation have greatly damaged Caohai.A rapid evaluation of the spatiotemporal evolution trend of the ecological quality of the Caohai Nature Reserve is significant for the maintenance and construction of the ecosystem in this area.The research is based on the Google Earth Engine(GEE)remote sensing cloud computing platform.Landsat TM/OLI images from May to October in five time periods:2000-2002,2004-2006,2009-2011,2014-2016,and 2019-2021 were obtained to reconstruct the optimal cloud image set by averaging the images in each time period.By constructing four ecological indicators:Greenness(NDVI),Wetness(Wet),Hotness(LST),and Dryness(NDBSI),and using Principal Component Analysis(PCA)method to obtain the Remote Sensing Ecological Index(RSEI)for the corresponding years,the spatiotemporal variation of ecological quality in the Caohai Nature Reserve over 20 years was analyzed.The results indicate:①the mean value of RSEI increased from 0.460 in 2000-2002 to 0.772 in 2019-2021,a 67.83%increase,indicating a significant improvement in the ecological quality of the reserve over the 20 years;②from the perspective of functional zoning of the Caohai Nature Reserve,the ecological quality of the core area showed a degrading trend,while the ecological quality of the buffer zone and experimental zone significantly improved;③with the implementation of ecological restoration projects,the ecological quality of the reserve gradually recovered and improved from 2014 to 2021.The trend of RSEI value changes is well correlated with human interventions,indicating that the PCA-based RSEI model can be effectively used for ecological quality assessment in lake areas.

Spatiotemporal changes of eco-environmental quality based on remote sensing-based ecological index in the Hotan Oasis,Xinjiang

The rapid economic development that the Hotan Oasis in Xinjiang Uygur Autonomous Region,China has undergone in recent years may face some challenges in its ecological environment.Therefore,an analysis of the spatiotemporal changes in ecological environment of the Hotan Oasis is important for its sustainable development.First,we constructed an improved remote sensing-based ecological index(RSEI)in 1990,1995,2000,2005,2010,2015 and 2020 on the Google Earth Engine(GEE)platform and implemented change detection for their spatial distribution.Second,we performed a spatial autocorrelation analysis on RSEI distribution map and used land-use and land-cover change(LUCC)data to analyze the reasons of RSEI changes.Finally,we investigated the applicability of improved RSEI to arid area.The results showed that mean of RSEI rose from 0.41 to 0.50,showing a slight upward trend.During the 30-a period,2.66% of the regions improved significantly,10.74% improved moderately and 32.21% improved slightly,respectively.The global Moran's I were 0.891,0.889,0.847 and 0.777 for 1990,2000,2010 and 2020,respectively,and the local indicators of spatial autocorrelation(LISA)distribution map showed that the high-high cluster was mainly distributed in the central part of the Hotan Oasis,and the low-low cluster was mainly distributed in the outer edge of the oasis.RSEI at the periphery of the oasis changes from low to high with time,with the fragmentation of RSEI distribution within the oasis increasing.Its distribution and changes are predominantly driven by anthropologic factors,including the expansion of artificial oasis into the desert,the replacement of desert ecosystems by farmland ecosystems,and the increase in the distribution of impervious surfaces.The improved RSEI can reflect the eco-environmental quality effectively of the oasis in arid area with relatively high applicability.The high efficiency exhibited with this approach makes it convenient for rapid,high frequency and macroscopic monitoring of eco-environmental quality in study area.

Spatiotemporal variations in ecological quality of Otindag Sandy Land based on a new modified remote sensing ecological index

Otindag Sandy Land in China is an important ecological barrier to Beijing;the changes in its ecological quality are major concerns for sustainable development and planning of this area.Based on principal component analysis and path analysis,we first generated a modified remote sensing ecological index(MRSEI)coupled with satellite and ground observational data during 2001–2020 that integrated four local indicators(greenness,wetness,and heatness that reflect vegetation status,water,and heat conditions,respectively,as well as soil erosion).Then,we assessed the ecological quality in Otindag Sandy Land during 2001–2020 based on the MRSEI at different time scales(i.e.,the whole year,growing season,and non-growing season).MRSEI generally increased with an upward rate of 0.006/a during 2001–2020,with clear seasonal and spatial variations.Ecological quality was significantly improved in most regions of Otindag Sandy Land but degraded in the southern part.Regions with ecological degradation expanded to 18.64%of the total area in the non-growing season.The area with the worst grade of MRSEI shrunk by 15.83%of the total area from 2001 to 2020,while the area with the best grade of MRSEI increased by 9.77%of the total area.The temporal heterogeneity of ecological conditions indicated that the improvement process of ecological quality in the growing season may be interrupted or deteriorated in the following non-growing season.The implementation of ecological restoration measures in Otindag Sandy Land should not ignore the seasonal characteristics and spatial heterogeneity of local ecological quality.The results can explore the effectiveness of ecological restoration and provide scientific guides on sustainable development measures for drylands.

Development of a large-scale remote sensing ecological index in arid areas and its application in the Aral Sea Basin

The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia.It is of great significance to the ecological protection and sustainable development of Central Asia to carry out dynamic monitoring and effective evaluation of the eco-environmental quality of the Aral Sea Basin.In this study,the arid remote sensing ecological index(ARSEI)for large-scale arid areas was developed,which coupled the information of the greenness index,the salinity index,the humidity index,the heat index,and the land degradation index of arid areas.The ARSEI was used to monitor and evaluate the eco-environmental quality of the Aral Sea Basin from 2000 to 2019.The results show that the greenness index,the humidity index and the land degradation index had a positive impact on the quality of the ecological environment in the Aral Sea Basin,while the salinity index and the heat index exerted a negative impact on the quality of the ecological environment.The eco-environmental quality of the Aral Sea Basin demonstrated a trend of initial improvement,followed by deterioration,and finally further improvement.The spatial variation of these changes was significant.From 2000 to 2019,grassland and wasteland(saline alkali land and sandy land)in the central and western parts of the basin had the worst ecological environment quality.The areas with poor ecological environment quality are mainly distributed in rivers,wetlands,and cultivated land around lakes.During the period from 2000 to 2019,except for the surrounding areas of the Aral Sea,the ecological environment quality in other areas of the Aral Sea Basin has been improved in general.The correlation coefficients between the change in the eco-environmental quality and the heat index and between the change in the eco-environmental quality and the humidity index were–0.593 and 0.524,respectively.Climate conditions and human activities have led to different combinations of heat and humidity changes in the eco-environmental quality of the Aral Sea Basin.However,human activities had a greater impact.The ARSEI can quantitatively and intuitively reflect the scale and causes of large-scale and long-time period changes of the eco-environmental quality in arid areas;it is very suitable for the study of the eco-environmental quality in arid areas.

Assessment on eco-environmental quality of the Yellow River Basin by considering desertification index

Desertification has had a significant impact on the ecological environment of the Yellow River Basin(YRB)in China.However,previous studies on the evaluation of the ecological environment quality(EEQ)in the YRB have paid limited attention to the indicator of desertification.It is of great significance to incorporate the desertification index into the spatiotemporal assessment of the EEQ in the YRB in order to protect the ecological environment in the region.In this study,based on multi-source remote sensing data from 91 cities in the YRB,this article proposes a desertification remote sensing ecological index(DRSEI)model,which builds upon the traditional Remote Sensing Ecological Index(RSEI)model,to analyze the spatiotemporal changes in the EEQ in the YRB from 2001 to 2021.Furthermore,using the geographic detector(GD),and geographically and temporally weighted regression(GTWR)model,the study assesses the impact of human and natural factors on the EEQ in the YRB.The research findings indicate that:(1)Compared to the traditional RSEI,the improved DRSEI shows a decreasing trend in the evaluation results of the EEQ.Among the 24 cities,the change in DRSEI exceeds 0.05 compared to RSEI,accounting for 26.37%of the YRB.The remaining 67 cities have changes within a range of less than 0.05,accounting for 73.63%of the YRB.(2)The results of the GD for individual and interactive effects reveal that rainfall and elevation have significant individual and interactive effects on the EEQ.Furthermore,after the interaction with natural factors,the explanatory power of human factors gradually increases over time.The spatial heterogeneity results of GTWR demonstrate that rainfall has a strong direct positive impact on the EEQ,accounting for 98.90%of the influence,while temperature exhibits a more pronounced direct inhibitory effect,accounting for 76.92%of the influence.Human activities have a strong negative impact on the EEQ and a weak positive impact.

Assessment of ecological quality in Northwest China(2000-2020)using the Google Earth Engine platform:Climate factors and land use/land cover contribute to ecological quality

The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals(UN SDGs).The ecological environment of Northwest China is vulnerable to changes in climate and land use/land cover,and the changes in ecological quality in this arid region over the last two decades are not well understood.This makes it more difficult to advance the UN SDGs and develop appropriate measures at the regional level.In this study,we used the Moderate Resolution Imaging Spectroradiometer(MODIS)products to generate remote sensing ecological index(RSEI)on the Google Earth Engine(GEE)platform to examine the relationship between ecological quality and environment in Xinjiang during the last two decades(from 2000 to 2020).We analyzed a 21-year time series of the trends and spatial characteristics of ecological quality.We further assessed the importance of different environmental factors affecting ecological quality through the random forest algorithm using data from statistical yearbooks and land use products.Our results show that the RSEI constructed using the GEE platform can accurately reflect the ecological quality information in Xinjiang because the contribution of the first principal component was higher than 90.00%.The ecological quality in Xinjiang has increased significantly over the last two decades,with the northern part of this region having a better ecological quality than the southern part.The areas with slightly improved ecological quality accounted for 31.26%of the total land area of Xinjiang,whereas only 3.55%of the land area was classified as having a slightly worsen(3.16%)or worsen(0.39%)ecological quality.The vast majority of the deterioration in ecological quality mainly occurred in the barren areas Temperature,precipitation,closed shrublands,grasslands and savannas were the top five environmental factors affecting the changes in RSEI.Environmental factors were allocated different weights for different RSEI categories.In general,the recovery of ecological quality in Xinjiang has been controlled by climate and land use/land cover during the last two decades and policy-driven ecological restoration is therefore crucial.Rapid monitoring of inland ecological quality using the GEE platform is projected to aid in the advancement of the comprehensive assessment of the UN SDGs.

Forest landscape and its ecological quality:A stepwise spatiotemporal evaluation through patch-matrix model in Jhargram District,West Bengal State,India

Landscape conversion becomes a continuous process in a natural landscape for any strategic development.In a forest landscape mosaic,the conversion from non-forest land to forest land implies a constructive approach.Various bio-geographic processes are enriched and developed when the land was converted to forest land in a given landscape matrix.The present study evaluated how the increased forest cover improves the ecological quality of forest in Jhargram District of West Bengal State,India,from 1985 to 2015.The quality of forests includes dominance,fragmentation and connectivity,which are the basis ecological indicators of habitat structure.To address this issue,we extracted forest cover maps of 1985 and 2015 from land use/land cover classification.A grid framework was overlaid on these forest cover maps for patch-matrix model analysis.Reliable landscape ecological indices were used for the measurements of forest landscape quality in 1985 and 2015.Then a simple linear regression model was used to compare the results.Temporally,forest cover increased in Jhargram District from 1985 to 2015.The comparison of measurement indices depicts that although only a small amount of land was changed into forest land in the study area,this small change has greatly improved the structural compositional quality of the forest land.Compared with 1985,the forest land area increased by about 6930.56 hm^(2) in 2015.This increased forest cover improved the basic landscape ecological characters,such as inter patch connectivity,forest core area,forest habitat dependence,forest habitat dominance and forest edge effect.As a result,the ecosystem function in Jhargram District has been improved,which again attracts wildlife and enriches biodiversity.

Environmental Monitoring in Northern Aksu, China Based on Remote Sensing Ecological Index Model

In order to understand the development status of ecological environment quality in the Aksu region of China, to effectively adjust the ecological environment quality, so as to promote the sustainable development of its social economy and ecological environment protection. This paper selects the Landsat series remote sensing images of the northern Aksu region in 2013, 2016, and 2019, and uses the tools such as ENVI5.3 and ArcGIS 10.8.1 to process the image data accordingly. The principal component analysis method is used to calculate the Remote Sensing Ecological Index (RSEI) of the northern Aksu region. The data show that: 1) The ecological environment quality index in the northern Aksu region in 2013, 2016, and 2019 was 0.706087, 0.25243 and 0.362991 respectively;2) The areas where the ecological environment quality declined significantly in the northern Aksu region were the human settlements and the Gobi, fan-shaped land and other special terrain areas;3) The humidity index and the heat index are the two factors that have the greatest impact on the ecological environment quality in the northern Aksu area. The data as a whole show that the ecological environment in the northern part of the Aksu region has deteriorated seriously, and the severely deteriorated area is close to the human living area.

Development of a Water Quality Index (WQI) of an Artificial Aquatic Ecosystem in Mexico

A Water Quality Index (WQI) is a simple numeric expression reflecting the quality of water in any ecosystem at a given time. The objective of this study was to develop a WQI for the man-made dam Francisco I. Madero located in Chihuahua, Mexico. Eight points were randomly selected in the dam area and at each point water samples were collected monthly from March 2011 to February 2012 at three depths;0.30 m, 5 m and 10 m. The following physical-chemical variables were measured: potential hydrogen (pH), electrical conductivity (EC), dissolved oxygen (DO), temperature (T), turbidity, total dissolved solids (TDS), total hardness (TH) and chlorides (Cl-). In a first step for data analysis, an analysis of variance (ANOVA) was performed for each variable considering a factorial treatment design 12 × 3 in which factor A was the month with 12 levels (sampling months) and factor B was the depth with three levels (0.30 m, 5 m and 10 m). In a second statistical step, the WQI was calculated for each month only for the surface sampling (0.30 m) and the resulting value was classified under three categories;2.5 as excellent water. The results showed the following ranges for single variables: pH of 7.63 - 10.65, EC of 190 - 320 μS·cm-1, DO of 1.30 - 12.1 mg·L-1, T of 11.30°C - 30°C, Turbidity of 0-1, 120 NTU, TDS of 170 - 220 mg·L-1, TH of 240 - 900 mg·L-1 and Cl- of 7.28 - 7034 mg·L-1. The calculated WQI demonstrated that water quality varies seasonally and was classified as poor in the rainy season to good in winter season. We conclude that in general the water from the dam is acceptable and suitable for ecological and a broad spectrum of other purposes.

2001-2020年间河南省郑州市生态环境质量时空变化及驱动因素分析

生态环境质量是地区发展水平的重要组成部分,客观定量地对其进行长时序动态监测与分析,可为城市可持续发展和生态环境建设提供科学依据。基于Landsat遥感影像,通过主成分分析法构建遥感生态指数(remote sensing ecological index,RSEI)作为评价指标,运用Sen+Mann-Kendall趋势分析、Hurst指数、地理探测器探究河南省郑州市2001—2020年生态环境质量时空变化特征以及各驱动因子影响程度。研究表明:①2001—2020年间郑州市整体生态环境质量处于中等水平,生态环境指数呈先下降再上升再下降趋势,空间分布表现为东部平原低、西南山地丘陵高。除2010年受高温影响生态环境质量恶化面积大幅增加外,区域总体生态环境质量以不变和轻微改善为主。②2001—2020年间郑州市生态环境质量变化趋势显著,上升趋势区域占比56.34%,下降趋势区域占比42.26%。结合Hurst指数,东部生态环境质量下降趋势区域未来变化以持续性特征为主,西南部生态环境质量上升趋势区域未来变化以反持续性特征为主。③驱动力分析表明,2001—2020年间土地利用类型和人口密度是影响郑州市生态环境质量变化的主要因子,其解释力强度明显高于其他因素。高程和年均降水等自然因素影响力逐渐减弱,而反映城市化水平的夜间灯光指数影响力逐渐增强。研究可为郑州市生态环境评价与保护工作提供科学依据。

Spatiotemporal evolution of ecological environment quality and its drivers in the Helan Mountain,China

Understanding the ecological evolution is of great significance in addressing the impacts of climate change and human activities.However,the ecological evolution and its drivers remain inadequately explored in arid and semi-arid areas.This study took the Helan Mountain,a typical arid and semi-arid area in China,as the study area.By adopting an Enhanced Remote Sensing Ecological Index(ERSEI)that integrates the habitat quality(HQ)index with the Remote Sensing Ecological Index(RSEI),we quantified the ecological environment quality of the Helan Mountain during 2010-2022 and analyzed the driving factors behind the changes.Principal Component Analysis(PCA)was used to validate the composite ERSEI,enabling the extraction of key features and the reduction of redundant information.The results showed that the contributions of first principal component(PC1)for ERSEI and RSEI were 80.23%and 78.72%,respectively,indicating that the ERSEI can provide higher precision and more details than the RSEI in assessing ecological environment quality.Temporally,the ERSEI in the Helan Mountain exhibited an initial decline followed by an increase from 2010 to 2022,with the average value of ERSEI ranging between 0.298 and 0.346.Spatially,the ERSEI showed a trend of being higher in the southwest and lower in the northeast,with high-quality ecological environments mainly concentrated in the western foothills at higher altitudes.The centroid of ERSEI shifted northeastward toward Helan County from 2010 to 2022.Temperature and digital elevation model(DEM)emerged as the primary drivers of ERSEI changes.This study highlights the necessity of using comprehensive monitoring tools to guide policy-making and conservation strategies,ensuring the resilience of fragile ecosystems in the face of ongoing climatic and anthropogenic pressures.The findings offer valuable insights for the sustainable management and conservation in arid and semi-arid ecosystems.

成渝双城经济圈生态环境质量时空演变格局及其驱动力

成渝双城经济圈作为我国西部城镇化建设的重要示范区,探究其生态环境质量状况对推动区域社会经济高质量发展和长江上游生态环境保护意义重大。基于2000—2020年Landsat系列影像数据,运用绿度、湿度、热度、干度指标构建了遥感生态指数(Remote Sensing Ecological Index,RSEI),采用Sen(Theil⁃Sen median)斜率估计和MK(Mann⁃Kendall)检验相结合的趋势分析方法开展了区域生态环境质量时空变化特征研究。采用最优参数地理探测器模型(Optimal Parameters Geographic Detector,OPGD)优化了空间数据的尺度效应和分区效应,并对研究区生态环境质量的驱动力进行了分析。结果表明:(1)2000—2020年间,研究区生态环境质量整体较高,多年RSEI均值为0.63。生态环境质量以良和优为主,面积占比为61.37%。生态环境质量具有显著的空间异质性。在空间上呈“成都⁃重庆核心城市生态环境质量差,中间平原丘陵地区中等,四周质量优”的分布格局。(2)Sen⁃MK趋势分析表明,区域生态环境质量退化区域大于改善区域,两者面积之差占比为14.33%,表明研究区生态环境质量有显著下降趋势,应采取相应措施加强对区域生态环境的保护和修复。(3)最优参数地理探测器模型探测结果显示,驱动因子的最优空间尺度为5km,自然断点法、相等间隔分类、分位数分类、几何间隔分类和标准差分类5种离散方法有助于检测驱动因子的最优分类区间。绿度、湿度、热度、高程、坡度、年均气温是影响区域生态环境质量的主导因子,解释力q值大于56.95%。土地利用类型、人口密度、GDP、夜间灯光是次要驱动因子。驱动因子交互作用增强了对生态环境质量的影响。研究结果能为西部其他城市的发展提供借鉴,对推动长江上游生态环境保护和社会经济可持续、高质量发展提供科学依据。

2000-2023年关中平原城市群生态环境质量动态特征

[目的]掌握关中平原城市群的生态环境质量,优化城市格局和建设生态文明,进行生态环境变化动态监测。[方法]基于GEE云平台,运用2000-2023年MODIS数据集,构建遥感生态指数(RSEI),分析了关中平原城市群生态环境质量的空间分异性特征、演变趋势及未来发展动态,并探讨了影响生态环境质量的关键因素及其交互作用。[结果](1)关中平原城市群的RSEI整体呈上升趋势,RSEI均值增长率为0.0053/a,各市之间RSEI时空演变存在差异;(2)近24年来,关中平原城市群生态环境质量虽有改善,但优质区域有限且呈下降趋势;(3)关中平原城市群的生态环境质量主要受城市活动强度和坡度两个主导因子的影响,同时降水与土地利用的交互作用在多数年份中对生态环境质量的演变具有决定性影响。[结论]关中平原城市群的生态环境质量受到多种因素的影响,其中城市活动强度和坡度是主要因素,降水与土地利用的交互作用也起到了重要作用。为了维护和提升关中平原城市群的生态质量,应考虑在城市规划中融入生态保护措施。

黄河源区(玛曲)近20年生态环境质量动态评价

黄河源区(玛曲)是黄河上游重要的水源涵养区和补给区,对于维持区域生物多样性、生态系统平衡和社会经济高质量发展具有重要的作用。为揭示近20 a玛曲高寒草地生态系统动态变化特征及其区域差异性,基于GEE获取的Landsat 5、7、8数据集,应用遥感生态指数评价模型及一元回归趋势线法分析玛曲植被动态变化特征。结果表明:1)归一化植被指数、湿度、热度及干度4个指标在第一主成分贡献率均达90%以上,表明构建遥感生态指数(RSEI)评价玛曲县近20 a生态环境质量是可行的。2)2000—2021年玛曲县植被覆盖度整体上以增加趋势为主,2021年高植被覆盖度面积占研究区面积的93.44%。植被覆盖度显著改善区域主要分布在玛曲县东南边缘的齐哈玛乡、采日玛乡、曼日玛乡和黄河干流之间的大片区域,面积为4458.9 km^(2),占整个县域国土面积的38.36%。3)2000—2021年玛曲县遥感生态指数整体上呈上升趋势,上升了0.047,均值为0.788,表明玛曲县生态质量处于良好水平。4)玛曲县近20 a间生态环境质量变化特征为前期退化、后期改善。

Land cover change and eco-environmental quality response of different geomorphic units on the Chinese Loess Plateau

Land cover in the Chinese Loess Plateau has undergone dramatic changes since the late 1980s.Revealing the trend in land cover change and eco-environmental quality response of different geomorphic units in this stage is a realistic requirement for promoting sustainable development of the Chinese Loess Plateau.Based on the data of geomorphic units and land cover in 1990,2000,2010 and 2018 of the Chinese Loess Plateau,we studied the trend of land cover change and eco-environmental quality response of different geomorphic units by using a significance index of land cover change,a proportion index of land cover change and an eco-environmental response model.The results indicated that from 1990 to 2018,the areas of forestland and construction land substantially increased,whereas those of cropland,grassland,wetland and unused land considerably decreased.Land cover change exhibited large geomorphic differences,and the main conversion of land cover was from cropland into other land types.Unstable trend of land cover change in the loess tablelands and sandy loess hills declined,whereas the unstable trends in the other geomorphic units enhanced.Eco-environmental quality varied among different geomorphic units.The expansion of construction land and degradation of forestland,grassland and wetland resulted in the deterioration of eco-environmental quality.The conversion of cropland and unused land into forestland and grassland,and the conversion of grassland into forestland were the main factors that drove the improvement of eco-environmental quality.The findings of this study may provide theoretical reference and support decision making for the optimization of land use structure and the improvement of eco-environmental quality on the Chinese Loess Plateau.

A comparison of the applicability of the Shannon-Wiener index,AMBI and M-AMBI indices for assessing benthic habitat health in the Huanghe(Yellow River) Estuary and adjacent areas

From a dataset of macrobenthos obtained from 18 cruises from 2004 to 2013 in the Huanghe（Yellow River）Estuary and its adjacent areas,the composition and characteristics of macrobenthos were analyzed,and the applicability of the Shannon-Wiener Index（H′）,AZTI＇s Marine Biotic Index（AMBI） and multivariate AMBI（MAMBI） for assessing benthic habitat quality was compared.The results showed a total of 203 macrobenthos in the study area.The macrobenthos were dominated by polychaetes,followed by mollusks and crustaceans.The macrobenthic ecological groups were dominated by EGI,EGII and EGIII,which respectively accounted for 31.5%,36.0% and 21.2% of the total.There were significant differences between the evaluation results of the three indices.The ecological quality status（EQS） levels given by the AMBI were greater than those given by the H′ and M-AMBI.The AMBI could not reflect the differences between 11 sites but the H′ and M-AMBI could do.Moreover,the three indices responded well to the variations in salinity（S） and dissolved oxygen（DO） in the waters.The H′ and MAMBI also responded sensitively to the differences in physical parameters,such as water depth and sediment texture.The correlation between M-AMBI and environmental pressure gradient data was the strongest.The MAMBI could effectively distinguish degraded conditions from undegraded but the H′ and AMBI could not.Therefore,the M-AMBI reflected benthic habitat health well in the study areas.However,the objectivity of evaluation results of M-AMBI needs further verification by physical,chemical and biological methods.The thresholds also need further discussion.

Spatial-temporal changes and driving factors of eco-environmental quality in the Three-North region of China

Eco-environmental quality is a measure of the suitability of the ecological environment for human survival and socioeconomic development.Understanding the spatial-temporal distribution and variation trend of eco-environmental quality is essential for environmental protection and ecological balance.The remote sensing ecological index(RSEI)can quickly and objectively quantify eco-environmental quality and has been extensively utilized in regional ecological environment assessment.In this paper,Moderate Resolution Imaging Spectroradiometer(MODIS)images during the growing period(July-September)from 2000 to 2020 were obtained from the Google Earth Engine(GEE)platform to calculate the RSEI in the three northern regions of China(the Three-North region).The Theil-Sen median trend method combined with the Mann-Kendall test was used to analyze the spatial-temporal variation trend of eco-environmental quality,and the Hurst exponent and the Theil-Sen median trend were superimposed to predict the future evolution trend of eco-environmental quality.In addition,ten variables from two categories of natural and anthropogenic factors were analyzed to determine the drivers of the spatial differentiation of eco-environmental quality by the geographical detector.The results showed that from 2000 to 2020,the RSEI in the Three-North region exhibited obvious regional characteristics:the RSEI values in Northwest China were generally between 0.2 and 0.4;the RSEI values in North China gradually increased from north to south,ranging from 0.2 to 0.8;and the RSEI values in Northeast China were mostly above 0.6.The average RSEI value in the Three-North region increased at an average growth rate of 0.0016/a,showing the spatial distribution characteristics of overall improvement and local degradation in eco-environmental quality,of which the areas with improved,basically stable and degraded eco-environmental quality accounted for 65.39%,26.82%and 7.79%of the total study area,respectively.The Hurst exponent of the RSEI ranged from 0.20 to 0.76 and the future trend of eco-environmental quality was generally consistent with the trend over the past 21 years.However,the areas exhibiting an improvement trend in eco-environmental quality mainly had weak persistence,and there was a possibility of degradation in eco-environmental quality without strengthening ecological protection.Average relative humidity,accumulated precipitation and land use type were the dominant factors driving the spatial distribution of eco-environmental quality in the Three-North region,and two-factor interaction also had a greater influence on eco-environmental quality than single factors.The explanatory power of meteorological factors on the spatial distribution of eco-environmental quality was stronger than that of topographic factors.The effect of anthropogenic factors(such as population density and land use type)on eco-environmental quality gradually increased over time.This study can serve as a reference to protect the ecological environment in arid and semi-arid regions.

Assessing benthic habitat quality using biotic indices in the Laizhou Bay, China

As an important part of the Bohai economic rim,the Laizhou Bay has been stressed by serious eco-environmental problems in recent years.In this study,the Shannon-Wiener index(H′),AZTI’s marine biotic index(AMBI)and the multivariate AMBI(M-AMBI)were used to assess the ecological quality status(EQS)of the Laizhou Bay according to macrobenthos data collected annually in August 2011–2014.The results showed that the overall benthic habitat quality in the Laizhou Bay was assessed as“Good”.However,25%of the samples were classified as“Moderate”,“Bad”or“Poor”status under degraded conditions.Ecological group III(EGIII)species which had a certain tolerance to environmental disturbances had a higher proportion in each station,and most of them had appeared the pollution indicator species Capitella capitata.This indicated that the benthic habitat in the Laizhou Bay had been disturbed and polluted to some extent.The comparison of the three indices evaluation result and the RDA analysis showed that the H′and M-AMBI were more suitable when the relative abundance of the single species was high and the macrobenthic community was significantly imbalanced;when the relative abundance of opportunistic species(EGIV and EGV)was high,the AMBI and M-AMBI could reflected the EQS objectively;in an undisturbed and polluted environment,all the three indices could indicate the benthic habitats quality.In summary,the better correlation between the three indices and environmental factors showed that they were well responsive to the tendency of the benthic habitats quality in the Laizhou Bay.