Effect of human activities on biodiversity in Nabq Protected Area, South Sinai, Egypt

Mona, Mohamed H.; El‐Naggar, Hussein A.; El-Gayar, Ensaf E.; Masood, Mostafa F.; Mohamed, El-Sayed N.E.

doi:10.1016/j.ejar.2018.12.001

Cited by 42 publications

(33 citation statements)

References 10 publications

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“…Aquatic ecosystems are considered as the most impacted habitats as a result of human activities that represent one of the most important factors in shaping and limiting the abundance, diversity and community structure of organisms (Mona et al 2019). Lake Edku receives huge amounts of waste waters discharged from various effluents such as fish farms, agriculture and sewage discharges that could be affecting on its ecological and biological features.…”

Section: Discussionmentioning

confidence: 99%

Long-term variations of zooplankton community in Lake Edku, Egypt

Zakaria¹,

El‐Naggar²

2019

Egypt. J. of Aquatic Biolo. and Fish.

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Lake Edku receives huge amounts of waste waters discharged from various effluents that could be affecting on its ecological and biological features. Samples were collected seasonally for seven subsequent years (2009-2015) from 9 stations represent the different habitats in Lake Edku to assess the ecological status of the lake through long-term variations of zooplankton community. The data of physico-chemical parameters indicated that some parameters had wide variations in yearly average and others changed within narrow range. Lake Edku is considered among the highly eutrophic lakes as the average values of Chlorophyll-a concentrations all over the study period always higher than the eutrophication level. Zooplankton community in the lake comprised 77 species. Rotifera and Copepoda were the most abundant and diversified groups. Long-term variations of zooplankton abundance and diversity indicated that the lake is in continuous degradation. This also confirmed by the dominance of rotifer species belonging to genera Brachionus, Polyarthra, Keratella and Filinia which were considered as bioindicators of organic pollution. However, it would be concluded that Lake Edku is highly eutrophic basin, under severe conditions and their ecological status is too bad and needs repair.

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Section: Discussionmentioning

confidence: 99%

Long-term variations of zooplankton community in Lake Edku, Egypt

Zakaria¹,

El‐Naggar²

2019

Egypt. J. of Aquatic Biolo. and Fish.

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“…Coral get up 90% of their nutrient from their zooxanthellae. Zooxanthellae produce pigments visible through the clear body of the polyp and give the coral its beautiful color [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…These stressors are thought to cause coral diseases and bleaching leading to a loss of coral cover. Unfortunately, very little is currently known about the prevalence, distribution and pathology of coral disease in the Red Sea [1,6].…”

Section: Introductionmentioning

confidence: 99%

Human Impacts on Coral Reef Ecosystem

El‐Naggar¹

2021

Natural Resources Management and Biological Sciences

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Healthy, Coral reefs are the most spectacular, diverse and economically valuable marine ecosystems on the planet, Complex and productive, coral reefs are extremely important for biodiversity, providing a home to 35,000-60,000 species of plants and animals (over 25% of all marine life), many of which are undescribed by science. They are also vital for people and business. They provide nurseries for many species of commercially important fish, protection of coastal areas from storm waves. They are providing hundreds of billions of dollars in food, jobs and significant attraction for the tourism industry. Yet coral reef ecosystems have undergone phase shifts to alternate, degraded assemblages because of the combined human activates of unsustainable overfishing, intensive tourism, urbanization, sedimentation, declining water quality, pollution and primarily from the direct and indirect impacts of climate change. Most coral ecologists confirmed that coral reef degradation has increased dramatically during the last three decades due to enhanced anthropogenic disturbances and their interaction with natural stressors. So, it is necessary to recognize the threats facing coral reefs from anthropogenic activities and try to minimize and mitigate these impacts.

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“…Forest fires are one of the important disturbance factors in the global forest ecosystem [1], and it causes various degrees of negative impacts on the ecological environment, resources, human health, economy, and so on [2][3][4][5][6][7][8]. On March 30, 2019, there was a forest fire in Muli County, Liangshan Prefecture, Sichuan Province, China.…”

Section: Introductionmentioning

confidence: 99%

Application of the Artificial Neural Network and Support Vector Machines in Forest Fire Prediction in the Guangxi Autonomous Region, China

Zhong-ke

Chen

et al. 2020

Discrete Dynamics in Nature and Society

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The study of forest fire prediction is of great environmental and scientific significance. China’s Guangxi Autonomous Region has a high incidence rate of forest fires. At present, there is little research on forest fires in this area. The application of the artificial neural network and support vector machines (SVM) in forest fire prediction in this area can provide data for forest fire prevention and control in Guangxi. In this paper, based on Guangxi’s 2010–2018 satellite monitoring hotspot data, meteorology, terrain, vegetation, infrastructure, and socioeconomic data, the researchers determined the main forest fire driving factors in Guangxi. They used feature selection and backpropagation neural networks and radial basis SVM to build forest fire prediction models. Finally, the researchers use the accuracy, precision, and area under the characteristic curve (ROC-AUC) and other indicators to evaluate the predictive performance of the two models. The results showed that the prediction accuracy of the BP neural network and SVM is 92.16% and 89.89%, respectively. As both results are over 85%, the requirements of prediction accuracy is met. These results can be used for forest fire prediction in the Guangxi Autonomous Region. Specifically, the accuracy of the BP neural network was 0.93, which was higher than that of the SVM model (0.89); the recall of the SVM model was 0.84, which was lower than the BANN model (0.92), and the AUC value of the SVM model was 0.95, which was lower than the BP neural network model. The obtained results confirm that the BP neural network model can provide more prediction accuracy than support vector machines and is therefore more suitable for forest fire prediction in Guangxi, China. This research provides the necessary theoretical basis and data support for application in the field of forestry of the Guangxi Autonomous Region, China.

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Effect of human activities on biodiversity in Nabq Protected Area, South Sinai, Egypt

Cited by 42 publications

References 10 publications

Long-term variations of zooplankton community in Lake Edku, Egypt

Long-term variations of zooplankton community in Lake Edku, Egypt

Human Impacts on Coral Reef Ecosystem

Application of the Artificial Neural Network and Support Vector Machines in Forest Fire Prediction in the Guangxi Autonomous Region, China

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