Study of trace metal contamination and ecological risk assessment in the sediments of a tropical river estuary, Southwestern India

Nishitha, D'Souza; Amrish, Vadakkeveedu Narayan; Kumar, Arun; Warrier, Anish Kumar; Udayashankar, H N; Balakrishna, Keshava

doi:10.1007/s10661-021-09728-1

Cited by 24 publications

(8 citation statements)

References 43 publications

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“…At present, landscape risk assessments at locally and abroad mainly focus on rivers (Dale et al, 2000, Walker et al, 2001, Ayre and Landis, 2012, Yanes et al, 2019 and coasts (André et al, 2021, Yanjie et al, 2022, D'Souza et al, 2022, Yanes et al, 2019. Many scholars have conducted forest landscape risk assessments on climate change (Rasoul and R., 2022) and fire (Hua et al, 2021) .…”

Section: Introductionmentioning

confidence: 99%

Based on ecological risk assessment of landscape from the perspective of Saihanba landscape pattern changes

Kang,

Yang,

Qing

et al. 2024

Preprint

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Examining the Saihanba Mechanical Forest Farm, this study utilized landsat remote sensing data from 1987, 1997, 2001, 2013, and 2020 to interpret land use from the vector machine method, and to decipher evolving land use patterns over the last four decades. Grounded in landscape ecology theory, an innovative evaluation index for landscape ecological risk was introduced, leading to the delineation of 382 ecological risk evaluation units based on the degree of global landscape risk. Employing landscape pattern indices and a method around spatial autocorrelation, we analyzed the spatial and temporal distribution characteristics and spatial correlation patterns of landscape ecological risk across five distinct periods. Geostatistical approaches were used to explore the driving factors of landscape risk. Results indicate significant shifts in land use types since 1987, notably with a evident increase in forest landscape predominantly at the expense of grassland and sandy land. Over the 1987 to 2020 period, landscape risk demonstrated a gradual decline, with mid-high and high-risk areas clustering in specific locales, while the broader region predominantly featured low landscape risk. The landscape ecological risks in each period of the study area showed a positive spatial correlation and tended to gather in space. Since its establishment in 1962, the landscape changes caused by human factors such as afforestation projects and scientific forest management methods have reduced the ecological risk of the landscape. A comprehensive exploration using geographic detectors identified nine ecological driving factors, with soil type emerging as the principal risk determinant, and its synergistic interaction with precipitation and other factors surpassing the individual factor effects.

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Section: Introductionmentioning

confidence: 99%

Based on ecological risk assessment of landscape from the perspective of Saihanba landscape pattern changes

Kang,

Yang,

Qing

et al. 2024

Preprint

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“…At present, landscape risk assessments locally and abroad mainly focus on rivers [14][15][16][17] and coasts [17][18][19][20]. Many scholars have conducted forest landscape risk assessments on climate change [21], strong winds [22], regulated floodplains [23], population [24], and fire [25].…”

Section: Introductionmentioning

confidence: 99%

Landscape Ecological Risk Assessment of Saihanba under the Change in Forest Landscape Pattern

Kang,

Yang,

Qing

et al. 2024

Forests

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Examining the Saihanba Mechanical Forest Farm, this study utilized Landsat remote sensing data from 1987, 1997, 2001, 2013, and 2020 to interpret land use from the Support Vector Machine (SVM) method, and to decipher evolving land use patterns over the last four decades. Grounded in landscape ecology theory, an innovative evaluation index for landscape ecological risk was introduced, leading to the delineation of 382 ecological risk evaluation units. Employing landscape pattern indices and a method of spatial autocorrelation, we analyzed the spatial and temporal distribution characteristics and spatial correlation patterns of landscape ecological risk across five distinct periods. Geostatistical approaches were used to explore the driving factors of landscape risk. The results indicate that since 1987, there have been significant changes in land use types, especially in forest landscapes, their proportion increasing from 23.19% to 74.55%. In 1987, the proportion of high-risk areas was 72.30%, but in 2020, high-risk areas had significantly decreased and clustered in specific locations. The landscape ecological risks in each period of the study area showed a positive spatial correlation and tended to gather in space. After comprehensive exploration using a geographic detector, we found that landscape type, temperature, and vegetation coverage are the main risk factors. Among them, landscape type has the greatest impact on the landscape and works together with slope, aspect, and precipitation. In forest farm management, only the adaptation and adjustment of single factors are often paid attention to, while the compound effects of multiple factors are ignored. The results of this study bring important reference value to the operation and development of forest farms.

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“…Ecological risk assessment entails estimating the potential effects of human activities on a natural resource (Nishitha et al, 2022). These activities include various industrial, mining and agricultural practices, pharmaceuticals, and urban runoff (Ozbay et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Ecological risk evaluation of spent engine oil pollution using earthworm and microbial bioassays

Nnawuike,

Udebuani,

Chibuike

et al. 2024

SJES

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The study aimed to assess the ecotoxicological risk associated with the indiscriminate disposal of spent engine oil on terrestrial ecosystem using earthworm and microbial assays. Soil samples were collected from a depth of 0-20 cm and subjected to standard analytical protocols for analysis. Earthworms (assessed by mortality rate) and microorganisms (evaluated for inhibitory effects) covered a wide range of short-term lethal and sub-lethal endpoints used for risk characterization, analyzed through Probit analysis. The result of acute toxicity assay revealed that microbial absorbance rated depended on the dose and type of organism, ranking in the order: Acinetobacter > Enterobacter > Bacillus species >Pseudomonas. Aas oil concentratoin increase, mortality among earthworm was observed. Risk Quotient (RQ) values for Zea mays, Vigna unguiculata, Glycine max and earthworm varied from low to very high risk based on estimated Predicted No Effect Concentration (PNEC) values. Microorganisms exhibited differing level of biotolerance to spent engine oil exposure as indicated by respective risk quotient values. Exposure to spent engine oil posed minimal risk to Pseudomonas sp., Bacillus sp., and Acinetobacter sp., with RQ values below unity (< 1). Conversely, Enterobacter sp. Showed a high risk with values above unity. Earthworms play a pivotal role in agriculture due to their numerous economic benefots. Soil microorganisms are essential for maintening soil quality by performing vital processes. The antimicrobial properties of spent engine oil on soil may distort microbial activities, potentially inhibiting their growth and leading to alterations in ecological functionality of the soil.

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Study of trace metal contamination and ecological risk assessment in the sediments of a tropical river estuary, Southwestern India

Cited by 24 publications

References 43 publications

Based on ecological risk assessment of landscape from the perspective of Saihanba landscape pattern changes

Based on ecological risk assessment of landscape from the perspective of Saihanba landscape pattern changes

Landscape Ecological Risk Assessment of Saihanba under the Change in Forest Landscape Pattern

Ecological risk evaluation of spent engine oil pollution using earthworm and microbial bioassays

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