Ecosystem Health Assessment at County-Scale Using the Pressure-State-Response Framework on the Loess Plateau, China

Liu, Delin; Hao, Shilong

doi:10.3390/ijerph14010002

Cited by 71 publications

(53 citation statements)

References 32 publications

(40 reference statements)

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“…And EV, EO, ER, and ESV respectively represent ecosystem vigor, ecosystem organization, ecosystem resilience and ecosystem services value. In order to eliminate the different dimensions of the index, EHI, PHI, EV, EO, ER, and ESV are normalized from 0 to 1 [34]. The natural break point method in GIS is used to divide the health level of the ecosystem into five levels: Degraded, Unhealthy, Average Health, Suboptimal Health, and Highest Health.…”

Section: Ecosystem Health Assessmentmentioning

confidence: 99%

Temporal–Spatial Distribution of Ecosystem Health and Its Response to Human Interference Based on Different Terrain Gradients: A Case Study in Gannan, China

2020

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The exploitation, utilization, and protection of land resources are some of the great social problems during the process of rapid urbanization in China. The status of land use directly affects ecosystem health (ESH). The evaluation of ESH and the spatial correlations between urbanization caused by human interference help us to analyze the influence of urbanization on ecosystems and also provide new insight into reasonable and scientific resource management. In this study, we evaluated the ESH of Gannan, in Jiangxi Province, China, based on ecosystem service values (ESV) and selected a series of indicators to detect the impact of urbanization on ecosystem health in 1990, 1995, 2000, 2005, 2010. and 2015. Remote sensing (RS) and the Geographic Information System (GIS) were used as processing tools to calculate basic data and to map the results based on different terrain gradients. The results show that ecosystem health suffered a downward trend from 1990 to 2015. Especially, the area proportion at an unhealthy level and average health (ave-health) level increased prominently, and the area of a well state decreased. Further, the results indicate that urbanization had a negative impact on ESH. The degree of a negative correlation increases with the process of urban sprawl. In addition, we found that from 1990 to 2015, the area proportion of a degraded level and unhealthy level was the highest on the first terrain gradient, and as the terrain gradient increased, this area proportion also decreased. However, the high interference region occupies a higher proportion in the lower terrain gradient. Consequently, the results could reveal the impact of urbanization on ecosystem health and could provide an even more effective service for a sustainable development.

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Section: Ecosystem Health Assessmentmentioning

confidence: 99%

Temporal–Spatial Distribution of Ecosystem Health and Its Response to Human Interference Based on Different Terrain Gradients: A Case Study in Gannan, China

2020

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“…The integrated application of multiple landscape indexes can avoid the limitation in some extent when individual landscape index was selected and can reduce the adverse effect on result analysis caused by remotely sensed data resolution and human factors. [9,[26][27][28], and according to the stability of the ecosystem structure, the resilience of the landscape, the service function of ecosystem, and the changing factors of landscape pattern. The established so-called pressure-state-responsepattern (PSRP) model system included target layer, criterion layer, index layer, and 12 single indexes [29,30].…”

Section: Methodsmentioning

confidence: 99%

“…The wildly accepted ecological security assessment system include the "ecological footprint" concept and model, the concept of pressure-state-response (PSR) framework model, and the concept of natureeconomy-society framework model [8,9].…”

Section: Introductionmentioning

confidence: 99%

Landscape Pattern and Ecological Security Assessment and Prediction Using Remote Sensing Approach

et al. 2018

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In this work, we present a processing chain for landscape pattern and ecological security status assessment and prediction based on cellular automata Markov (CA-Markov) and pressure status response pattern (PSRP) models using remotely sensed data (RSD) captured in 1986, 1996, 2006, 2016, and RSD simulated in 2026 over Zhengzhou city, Henan province, China. Three major findings can be withdrawn through the experiments. First, there is a significant changing of landscape type area, especially for building land. The area of building land is up to more than 5%, from 1986 to 2016. Secondly, the heterogeneity of landscape is increasing, and the diversity of landscape is becoming more and more diversifying and complex. Third, the changing trend of ecological security of Zhengzhou city shaped as decreasing and increasing gradually during the last 40 years. While the ecological security status, nowadays, appeared to a good trend by contrast of the previous stages. The predicted results with CAMarkov model show that the level of ecological security is still in moderate and has a trend of moving toward to the center in 2026.

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“…Such compounds originate from oil spills and from incomplete combustion. They are prone to biomagnification in addition to long-distance transport [3]. …”

Section: Introductionmentioning

confidence: 99%

Characterization of a Microbial Consortium for the Bioremoval of Polycyclic Aromatic Hydrocarbons (PAHs) in Water

Blanco-Enríquez

Serna

Peralta-Pérez

et al. 2018

IJERPH

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Pollution of freshwater ecosystems from polycyclic aromatic hydrocarbons (PAHs) is a global concern. The US Environmental Protection Agency (EPA) has included the PAHs pyrene, phenanthrene, and naphthalene among the 16 priority compounds of special concern for their toxicological effects. The aim of this study was to adapt and characterize a microbial consortium from ore waste with the potential to remove these three PAHs from water. This microbial consortium was exposed to the target PAHs at levels of 5, 10, 20, 50, and 100 mg L−1 for 14 days. PAH bioremoval was measured using the analytical technique of solid phase microextraction, followed by gas chromatography mass spectrometry (SPME-GC/MS). The results revealed that up to 90% of the target PAHs can be removed from water after 14 days at a concentration level of 100 mg L−1. The predominant group of microorganisms identified at the phylum taxonomic level were the Proteobacteria, while the Actinobacteria were the predominant subgroup. The removal of phenanthrene, naphthalene, and pyrene predominantly occurred in specimens of genera Stenotrophomonas, Williamsia, and Chitinophagaceae, respectively. This study demonstrates that the use of specific microorganisms is an alternative method of reducing PAH levels in water.

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Ecosystem Health Assessment at County-Scale Using the Pressure-State-Response Framework on the Loess Plateau, China

Cited by 71 publications

References 32 publications

Temporal–Spatial Distribution of Ecosystem Health and Its Response to Human Interference Based on Different Terrain Gradients: A Case Study in Gannan, China

Temporal–Spatial Distribution of Ecosystem Health and Its Response to Human Interference Based on Different Terrain Gradients: A Case Study in Gannan, China

Landscape Pattern and Ecological Security Assessment and Prediction Using Remote Sensing Approach

Characterization of a Microbial Consortium for the Bioremoval of Polycyclic Aromatic Hydrocarbons (PAHs) in Water

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