Maintaining ecological resilience on a regional scale

Herbert, Roger J.H.; Ross, Kathryn; Whetter, Talwyn; Bone, Jessica R.

doi:10.1016/b978-0-08-102698-4.00032-0

Cited by 3 publications

(3 citation statements)

References 20 publications

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“…as a wetland of importance for conservation, as it meets Ramsar conservation criteria 1, 2, 3, and 7 [28]. Coastal lagoons are particularly vulnerable to environmental changes for being relatively closed and protected habitats with limited seawater exchange [31]. Mangroves forests are classified as coastal wetlands and provide widely known ecosystem services such as flood control and wildlife refuge [32].…”

Section: Study Areamentioning

confidence: 99%

“…During the northerly wind season (NWS hereafter), the emission plume from the CT-PALM flows in a southerly direction, producing a gradient of higher to lower concentration of atmospheric pollutants in this same direction; during the dry season (DS hereafter), the plume flows The Tampamachoco Lagoon was declared a Ramsar site (designation number 1602), as a wetland of importance for conservation, as it meets Ramsar conservation criteria 1, 2, 3, and 7 [28]. Coastal lagoons are particularly vulnerable to environmental changes for being relatively closed and protected habitats with limited seawater exchange [31]. Mangroves forests are classified as coastal wetlands and provide widely known ecosystem services such as flood control and wildlife refuge [32].…”

Section: Meteorological Analysis Pollutant Dispersion Modeling and Mo...mentioning

confidence: 99%

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Impact of Particulate Matter (PM10 and PM2.5) from a Thermoelectric Power Plant on Morpho-Functional Traits of Rhizophora mangle L. Leaves

Ayala-Cortés,

Barrera-Huertas,

Sedeño-Díaz

et al. 2023

Forests

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A conventional thermoelectric plant (TP) in the sandy bar of the Tampamachoco Lagoon (Gulf of Mexico slope) emits particulate matter (PM) transporting trace metals that affect a mangrove forest. Wind transports the emission plume from north to south in the northerly wind season (NWS); the dry season (DS) showed calm periods. We analyzed whether PM2.5 and PM10 emissions from the TP and their trace metals impact Rhizophora mangle leaves. The experimental design included three sampling sites along the main lagoon axis (north to south) during the NWS and DS. Mangrove leaves were collected; PM was obtained with a cascade impactor and trace elements were analyzed by atomic absorption spectrophotometry. Leaves were measured and tested for metal and chlorophyll content, and for metal detection with SEM-EDX. Calm periods in the DS promote high atmospheric PM concentrations. Wet deposition in the NWS caused the highest trace metal deposition on mangrove leaves. A north-to-south gradient was identified on the mangrove forest, being the south site of the lagoon where lower chlorophyll and leaf area, higher stomatal width and density, and higher Cd concentrations were recorded. The morpho-physiological modifications observed on mangrove leaves affect functions such as photosynthesis and gas exchange.

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Section: Study Areamentioning

confidence: 99%

Section: Meteorological Analysis Pollutant Dispersion Modeling and Mo...mentioning

confidence: 99%

Impact of Particulate Matter (PM10 and PM2.5) from a Thermoelectric Power Plant on Morpho-Functional Traits of Rhizophora mangle L. Leaves

Ayala-Cortés,

Barrera-Huertas,

Sedeño-Díaz

et al. 2023

Forests

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“…High levels of stress result in environmental threats to these treasured ecosystems [22]. Among recent environmental problems of coastal lagoons are affected biodiversity patterns and loss of habitats and rare species [23,24], as well as disrupted land cover patterns due to climate effects. Examples of pollution include organic, chemical, and biological types such as microplastic [25,26] or heavy metals [27].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data

Lemenkova

2024

JMSE

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This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in the Ramsar site due to its rich biodiversity, productivity, and precious habitat for migrating birds and rare species. The vulnerable ecosystems of the Chilika Lagoon are subject to climate effects (monsoon effects) and anthropogenic activities (overexploitation through fishing and pollution by microplastics). Such environmental pressure results in the eutrophication of the lake, coastal erosion, fluctuations in size, and changes in land cover types in the surrounding landscapes. The habitat monitoring of the coastal lagoons is complex and difficult to implement with conventional Geographic Information System (GIS) methods. In particular, landscape variability, patch fragmentation, and landscape dynamics play a crucial role in environmental dynamics along the eastern coasts of the Bay of Bengal, which is strongly affected by the Indian monsoon system, which controls the precipitation pattern and ecosystem structure. To improve methods of environmental monitoring of coastal areas, this study employs the methods of ML and Artificial Neural Networks (ANNs), which present a powerful tool for computer vision, image classification, and analysis of Earth Observation (EO) data. Multispectral satellite data were processed by several ML image classification methods, including Random Forest (RF), Support Vector Machine (SVM), and the ANN-based MultiLayer Perceptron (MLP) Classifier. The results are compared and discussed. The ANN-based approach outperformed the other methods in terms of accuracy and precision of mapping. Ten land cover classes around the Chilika coastal lagoon were identified via spatio-temporal variations in land cover types from 2019 until 2024. This study provides ML-based maps implemented using Geographic Resources Analysis Support System (GRASS) GIS image analysis software and aims to support ML-based mapping approach of environmental processes over the Chilika Lake coastal lagoon, India.

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Positive Spillover of Political and Technological Crises on Persons, Organizations, and Destinations across Covid-19: A Data Triangulation Study

Onyeama¹

2021

OJPS

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Crises are now parts of daily experience, peoples, organizations, and destinations experience crises. Most times, it occurs without realizing it, and even when people take note, it is the negative spillovers that are often emphasized more than the positive spillovers. Little do people realize that the crisis they are in today prepares them for tomorrow's strength. Unfortunately, there is little or no literature on the positive spillovers of crises. This study aims to fill the literature on the positive spillover of crises on peoples, organizations, and destinations using a qualitative data triangulation, comprising face-to-face interviews and textual data. The study employed spillover effect and resilience theories to justify the arguments. Findings from stage 1 analysis revealed three themes, and stage 2 analyzes supported the findings. Most times, survivors of crises end up becoming resilient after an experience. This study discussed managerial and practical implications, as well as limitations and future studies.

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Maintaining ecological resilience on a regional scale

Cited by 3 publications

References 20 publications

Impact of Particulate Matter (PM10 and PM2.5) from a Thermoelectric Power Plant on Morpho-Functional Traits of Rhizophora mangle L. Leaves

Impact of Particulate Matter (PM10 and PM2.5) from a Thermoelectric Power Plant on Morpho-Functional Traits of Rhizophora mangle L. Leaves

Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data

Positive Spillover of Political and Technological Crises on Persons, Organizations, and Destinations across Covid-19: A Data Triangulation Study

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