Ecosystem services dynamics and their influencing factors: Synergies/tradeoffs interactions and implications, the case of upper Blue Nile basin, Ethiopia.

Understanding the relationships among ecosystem services (ESs) and their interactions with influencing factors is essential for spatially targeted ecosystem governance. However, classifying the spatial distribution of these diverse interactions still needs improvement. Furthermore, existing studies have insufficiently addressed the specific impacts of bidirectional land cover transitions on ESs. Taking the upper Blue Nile basin as a study area, we estimated the spatiotemporal distribution of annual water yield (AWY), carbon storage (CS), habitat quality (HQ), and soil retention (SR) from 2000 to 2020, using InVEST models and associated formulas. Changes in ESs per inward-outward land cover transition were quantified based on the Cross-Tabulation Matrix. An improved pairwise method was employed to assess the spatially diverse interactions between ESs pairs and their relationship with influencing factors. The statistical significance of influencing factors was evaluated using partial least square regression. The findings indicated that high HQ values were prevalent in the west, while they were in the east for SR. The central and southern areas experienced higher CS and AWY values. During the study period, variations were observed in the mean values of SR (ranging from 22.89 to 23.88 × 102 t/ha/y), AWY (32.13-42.2 × 102 mm/ha/y), CS (90.5-102.9 × 103gC/ha/y) and HQ (0.62-0.64). Synergies were predominant in AWY-CS, AWY-SR, and CS-SR pairs. HQ revealed more of a no-effect and tradeoff relationship with other ESs. The interactions between ESs and influencing factors were dominated by synergies, followed by tradeoffs and no-effect. The influence of landscape structure (gyrate and landscape shape index) and land surface temperature on all ESs and precipitation on AWY and SR was significant (1.049 ≤ Variable Importance in the Projection ≤ 1.371). Overall, the spatiotemporal dynamics of key ESs and the modeling of their drivers are essential policy information for taking spatially explicit conservation measures. This study will also serve as a valuable methodological reference for future research.

The response of ecological security to land use change in east and west subtropical China.

Regional land use change and ecological security have received considerable attention in recent years. The rapid economic development of Kunming and Fuzhou has resulted in environmental damage such as water pollution and urban heat island effect. It is thus important to conduct a comparative analysis of the ecological security response to land use/land cover change (LUCC) in different natural zones. Using the Google Earth Engine (GEE) platform, random forest and support vector machine methods were used to classify land cover types in the study area, after which the ArcGIS platform was used to analyze LUCC. The driving force-pressure-state-impact-response (DPSIR) model and entropy weight method were used to construct an ecological security evaluation system, and gray correlation was used to compare the ecological security responses to LUCC in Kunming and Fuzhou. The findings revealed that: (1) The average dynamic degrees of comprehensive land use in Kunming and Fuzhou from 1995 to 2020 were 1.05% and 0.55%, respectively; (2) From 1995 to 2020, the ecological security index values for Kunming and Fuzhou increased from 0.42 to 0.52 and from 0.36 to 0.68, respectively, indicating that Fuzhou's index is rising more rapidly; and (3)There is a strong correlation between LUCC and ecological security, the correlation between the woodland and the ecological security index is very strong in both places. The expansion of construction land may be an important reason for the reduced ecological security level in Fuzhou City, while water resources have a significant impact on the ecological security level of Kunming City.

Ecological security assessment at different spatial scales in central Yunnan Province, China.

Healthy ecosystems are the basis of social and economic development. It is of great significance to conduct ecological security assessments in rapidly urbanization areas. Based on the driving forces, pressure, state, impact, and response (DPSIR) model, five years (1995, 2000, 2005, 2010 and 2015) of remote sensing images, social and economic statistics, and field survey data were used to establish an ecological security assessment index system. The ecological security assessment of central Yunnan Province (CYP) urban agglomeration was conducted at the 1 km × 1 km pixel scale and at the county scale based on the multilevel weighted comprehensive index method. The results showed that: (1) With 2005 as the turning point, the ecological security situation in CYP first decreased and then increased. (2) The ecological security at the county scale was mainly categorized as unsafe. At the pixel scale, ecologically unsafe and relatively unsafe areas were mainly distributed in central, northern, and western CYP. (3) The ecological security deterioration and strengthened spatial distribution differences were caused by habitat fragmentation, different physical geographical conditions, and population agglomeration. These results can provide a basis for the coordination and sustainability of economic development and environmental protection in urban agglomerations with rapid urbanization.

[Temporal and spatial variations of impervious surface landscape pattern and the driving factors in Xiamen City, China]. / åŽ¦é—¨å¸‚ä¸é€æ°´é¢æ™¯è§‚æ ¼å±€æ—¶ç©ºå˜åŒ–åŠé©±åŠ¨åŠ›åˆ†æž.

Xiamen is one of China's five major special economic zones and is the core city of Haixi Economic Zone, with a high level of urbanization. Monitoring and driving force analysis of impervious surfaces can increase our understanding of urbanization process and have important significance for urban landscape pattern research and urban ecological environment construction. We used the Landsat remote sensing image data from 1978 to 2018 to reveal the temporal and spatial variation characteristics of the impervious surface landscape in Xiamen in the past 40 years, using the full-restricted least squares method, landscape pattern analysis, slope gradient analysis and correlation analysis. We further analyzed its relationship with social and economic factors. The results showed that, during 1978-2018, the impervious surface of Xiamen increased by 348.96 km2, with a mean annual increase of 8.72 km2. The impervious surface dynamics reached a maximum of 9.0% in 2005-2010. More than 86.6% of the impervious surface of Xiamen was distributed within 6° of slope, with a tendency to expand to a greater slope in 2010-2018. With the increases of slope, the proportion of impervious surface decreased, the density of plaque decreased with the shape tending to be regular and continuous, the degree of fragmentation of the impervious surface increased. The increases of impervious surface in Xiamen was significantly related to the regional economic aggregate and population. In the study period, the spatial pattern of impervious surface in Xiamen significantly altered. In the future urban planning process, the extent and speed of impervious surface expansion should be coordinated to avoid ecological problems caused by excessive impervious surface to meet the need for sustainable development of Xiamen.

Review of the Spatial Distribution, Source and Extent of Heavy Metal Pollution of Soil in China: Impacts and Mitigation Approaches.

BACKGROUND: China has undergone a rapid industrial revolution and urbanization during the past three decades. This expansion is largely responsible for the release of a large amount of heavy metals into soils and is increasingly raising concerns over the potential effects on human health and the environment. The problem is drawing increasing attention, especially after an extensive nationwide soil survey report in 2014. A number of studies have examined soil contamination by heavy metals in China. However, most of these studies have been small in scale and it is therefore challenging to get a general overview of the level of contamination across the entire country. OBJECTIVES: The present study is aimed at presenting a synthesized overview of the extent, pattern, and impact of heavy metal contamination of soils in China, including mitigation approaches. METHODS: Eighty-six journal articles and other literature such as reports, internet sources, and statistical yearbooks were narratively and critically synthesized to compile a holistic summary of sources of heavy metals, the extent of pollution, spatial distribution and impact of heavy metal contamination in China. The major findings from these studies are presented, along with mitigation approaches applicable to China. DISCUSSION: A synthesis of major findings from recent scientific journals shows that about 10.18% of farmland soils which supports 13.86% of grain production in China is affected by heavy metals. The main sources of pollution are anthropogenic activities. Even though the spatial distribution of pollution is highly variable owing to natural and human factors, provinces with intensive industrial activities such as Henan, Shandong, and Sichuan are more highly polluted than others. These regions are top grain producing areas and hence require close follow-up for development of feasible approaches to mitigating crop contamination and associated health risks emerging in parts of China. The government recently launched a program aimed at determining sound reclamation strategies. CONCLUSION: Mitigation of heavy metal contamination in China requires coordination of different actors and integration of all feasible reclamation approaches. COMPETING INTERESTS: The authors declare no competing financial interests.

Monitoring of beach litter by automatic interpretation of unmanned aerial vehicle images using the segmentation threshold method.

This study was aimed at monitoring beach litter using an unmanned aerial vehicle (UAV) in the coastal city of Fuzhou, China. The data analysis shows that the optical images obtained by digital cameras on the UAV can help to identify and monitor beach litter using remote sensing and GIS technologies. The threshold method can effectively segment the UAV image in the beach area. It is useful for quickly monitoring the distribution of beach litter in the area of interest, and hence it can help to provide effective technical support for the investigation and assessment of coastal beach litter.

[Spectral inversion models for prediction of total chromium content in subtropical soil].

With the high requirements and long test cycle of traditional testing method of soil heavy metal, this paper tries to es-tablish the quantitative prediction model between soil hyperspectral and soil chromium content( tested by ICP-MS) to realize thIeprediction of soil chromium element quickly and accurately. The paper studied the hyperspectral response characteristics of re dsoil, with 135 soil samples in Fuzhou city. After monitoring the hypersectral reflection of soil samples with ASD (analytica lspectral device) and total chromium contents with ICP-MS, the paper gained the spectral reflection data between 350 and 2 500 nm and soil total chromium contents. Then the paper treated the hyperspectral reflection data with 6 mathematic changes such as reciprocal logarithmic change, differentials and continuum removal in advance. The next step was to calculate the correlation co-fficient of soil chromium and the above spectral information, and select the sensitive spectral bands according to the highest cor-elation coefficient. Finally, six kinds of models were selected to build the soil total chromium content model, and the final opti-al mathematic model between soil chromium and hyperspectral information was significantly determined. Results showed that 520--30, 1 440-- 450, 2 010-- 020, and 2 230-- 240 nm were the main sensitive bands to soil total chromium, y= 120. 68Ce (-7.037x)was the optimal soil total chromium predicting model( in the model, the correlation coefficient R and the RIME of total chromium were 0. 68 and 0. 19 Cµ1(-,) and the inspection correlation coefficient R and the RMSE were 0. 84 µ ?xg-('1) nd 1. 26 Iµ ?xg-(1 )respectively). The model can be used to rapidly monitor soil total chromium with hyperspectral reflection in Fuzhou. area.

[Spectral inversion models for prediction of red soil total nitrogen content in subtropical region (Fuzhou)].

The present paper studied the hyperspectral response characteristics of red soil, with 135 soil samples in Fuzhou city. After monitoring the hypersectral reflection of soil samples with ASD (analytical spectral device) and total nitrogen contents with Vario MAX (for nitrogen and carbon analysis), the paper gained the spectral reflection data between 350-2 500 nm (resolution is 1 nm) and soil total nitrogen contents. Then the paper treated the hyperspectral reflection data with 5 mathematic conversions such as first derivative and second derivative conversions of original reflection, reciprocal logarithmic conversion and its first derivative and second derivative conversion in advance. The next step was to calculate the correlation coefficient of soil nitrogen and the above spectral information, and select the sensitive spectral bands according to the highest correlation coefficient. Finally, by designing different proportions of modeling and validation sample data sets, the paper established the quantitative linear models between soil total nitrogen contents and hyperspectral reflection and its 5 converted information, the final optimal mathematic model between soil nitrogen and hyperspectral information was significantly determined. Results showed that 634-688, 872, 873, 1 414 and 1 415 nm were the main sensitive bands for soil total nitrogen, and Y = 5.384X(664) -1.039 (Y represents soil nitrogen content, X664 is the soil spectral absorbance value at 664 nm) was the optimal soil total nitrogen predicting model (in the model, the determination coefficients R2 and the RMSE of total nitrogen were 0.616 and 0.422 mg X g(-1), the inspection coefficient R2 and the RMSE were 0.608 and 0.546 mg x g(-1) respectively). The model can be used to rapidly monitor soil total nitrogen with hyperspectral reflection in Fuzhou area.

[Spatiotemporal variation of typical red soil eroded landscape pattern: a case study in Changting County of Fujian Province].

Based on the 1988, 2000, and 2007 remote sensing images of a typical red soil eroded region (Changting County, Fujian Province) and the digital elevation model (DEM), the eroded landscape types were worked out, and the changes of the eroded landscape pattern in the region from 1988 to 2007 were analyzed with the spatial mathematics model. In 1988-2007, different eroded landscape types in the region had the characteristics of inter-transfer, mainly manifested in the transfer from seriously eroded to lightly eroded types but still existed small amount of the transference from lightly eroded to seriously eroded types. Little change was observed in the controid of the eroded landscape. In the County, Hetian Town was all along the eroded center. During the study period, the landscape pattern index showed a tendency of low heterogeneity, low fragmentation, and high regularization at landscape level, but an overall improvement and expansion of lightly eroded and easy-to-tackle patches as well as the partial improvement and fragmentation of seriously eroded and difficult-to-tackle patches at patch level.

[Evaluation of eco-environmental quality based on artificial neural network and remote sensing techniques].

In the present study, vegetation, soil brightness, and moisture indices were extracted from Landsat ETM remote sensing image, heat indices were extracted from MODIS land surface temperature product, and climate index and other auxiliary geographical information were selected as the input of neural network. The remote sensing eco-environmental background value of standard interest region evaluated in situ was selected as the output of neural network, and the back propagation (BP) neural network prediction model containing three layers was designed. The network was trained, and the remote sensing eco-environmental background value of Fuzhou in China was predicted by using software MATLAB. The class mapping of remote sensing eco-environmental background values based on evaluation standard showed that the total classification accuracy was 87. 8%. The method with a scheme of prediction first and classification then could provide acceptable results in accord with the regional eco-environment types.