Locating suitable mangrove plantation sites along the Saudi Arabia Red Sea Coast

Monsef, Hesham Abd-El; Aguib, A.S.; Smith, Scot E.

doi:10.1016/j.jafrearsci.2013.02.005

Cited by 16 publications

(9 citation statements)

References 9 publications

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“…Muddy landform is the third factor linked to mangrove occurrence likelihood, which had been reported as an effective factor in similar studies, including Zahed and his colleague [4] and Monsef and his colleague [5]. One reason for the development of mangroves on muddy soil is the ability of these soils to absorb phosphates, and since soil phosphorus is one of the major factors in the growth of mangrove forest, mangrove forests prefer muddy soils as regions for their development [18].…”

Section: Running the Logistic Regression Modelmentioning

confidence: 92%

“…While mangroves are not directly affected by rainfall, rainfall indirectly has an important effect on the establishment of mangroves [5]. Rainfall washes excess salt from the soil and improves the growth of mangroves.…”

Section: -Precipitationmentioning

confidence: 99%

“…In general, if the tidal range of the coast is high, the possibility of a mangrove forest will increase because greater tidal range reduces the possibility of sediment formation [5]. This parameter prevents coastal salinity to the death threshold and this mechanism is vital for mangrove forests, which are arbitrary halophytes [3].…”

Section: Running the Logistic Regression Modelmentioning

confidence: 99%

“…In this regard, statistical algorithms such as the logistic regression modeling approach in conjunction with GIS spatial techniques is of potential importance for estimating occurrence probability of mangrove stands. The implementation of spatially explicit probabilistic models has attracted noticeable research interest in recent years [5][6][7], in which the land is evaluated in terms of environmental and climatic factors (explanatory variables) that are necessary to support the establishment and maintenance of a mangrove plantation program. Integration of GIS spatial analysis and statistical modeling techniques can help managers and decision-makers in identifying suitable sites for mangrove plantations at minimum possible cost [8].…”

Section: Introductionmentioning

confidence: 99%

“…One of the reasons for these failures is wrongly locating areas suitable for mangrove plantations because locating the proper place for mangrove natural forests is an important factor in protecting and developing natural mangrove forests. Based on a study conducted by Abd-El Monsef et al, using satellite imagery interpretation, topographic maps, and soil maps for locating suitable sites for mangrove plantations, they indicated that "mangrove occurrence is correlated with environmental parameters, including air temperature, water temperature, salinity, tidal, wave energy, land proneness to flash-flooding, and soil suitability" [5]. In order to determine factors affecting mangrove forest occurrence, we investigated related studies on mangrove occurrence indicators in the literature (Table 3).…”

Section: Introductionmentioning

confidence: 99%

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Investigating Environmental Factors for Locating Mangrove Ex-situ Conservation Zones Using GIS Spatial Techniques and the Logistic Regression Algorithm in Mangrove Forests in Iran

Petrosian¹,

Kar²,

Ashrafi³

et al. 2016

Pol. J. Environ. Stud.

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Along the coastal strip of tropical and subtropical regions, mangrove forests extend as one of the most productive coastal ecosystems. Iran is considered one of the most western coastal habitats of these communities in Asia. Unfortunately, in recent years, despite their economic and ecological importance, these forests have been threatened mainly due to human activities, which necessitate the need for protecting and developing these ecosystems. Ex-situ conservation, which aims to transfer a species to right place for preservation and development, is one of the most effective ways of protecting these forests. It is obvious that the successful transfer of a species in order to protect it as ex-situ conservation requires a comprehensive environmental assessment. The present paper employs a spatio-statistical methodology to delineate areas enriched with environmental parameters and weather factors necessary to support a mangrove ex-situ conservation plan in Hormozgan Province, Iran. With extensive effort in reviewing the related studies in the literature, we elicted a collection of 14 environmental and weather indicators critical to maintaining mangrove stands in a sustainable ecological environment. For screening the number of indicators to environmental variables with highest importance in our research, we used the Delphi method to quantify expert attitudes in order to develop a suitability index collection. Accordingly, an integrated application of GIS spatial analysis and a logistic regression algorithm were used to build an explicit spatial predictive model that evaluates the targeted area in terms of identified factors, thereby quantifying the potential of suitable zones for locating mangrove ex-situ conservation sites. Predictive performance of the developed model was evaluated based on Kappa index and omission error rate. According to our results, land proneness to a mangrove plantation has a high positive correlation with environmental attributes such as temperature fluctuation, land form, and mean tidal level, and has a negative correlation with slope and wave height. Our results should be considered advantageous for decision makers and planners in the field of mangrove ecosystems.

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Section: Running the Logistic Regression Modelmentioning

confidence: 92%

Section: -Precipitationmentioning

confidence: 99%

Section: Running the Logistic Regression Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Investigating Environmental Factors for Locating Mangrove Ex-situ Conservation Zones Using GIS Spatial Techniques and the Logistic Regression Algorithm in Mangrove Forests in Iran

Petrosian¹,

Kar²,

Ashrafi³

et al. 2016

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

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Investigating chlorophyll and nitrogen levels of mangroves at Al-Khor, Qatar: an integrated chemical analysis and remote sensing approach

Al-Naimi

Al-Ghouti

Balakrishnan

2016

Environ Monit Assess

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Mangroves are unique ecosystems that dominate tropical and subtropical coastlines around the world. They provide shelter and nursery to wide variety of species such as fish and birds. Around 73 species of mangroves were recognized around the world. In Qatar, there is only one mangrove species Avicennia marina that is predominant along the northeastern coast. Assessing the health of these valuable ecosystems is vital for protection, management, and conservation of those resources. In this study, an integrated approach of chemical and remote sensing analysis was implemented to investigate the current status of the mangrove trees in Al-Khor, Qatar. Fifteen different A. marina trees from different locations in the mangrove forest were examined for their chlorophyll and nitrogen content levels. Soil analysis was also conducted to understand the effect of moisture on nitrogen availability. Results shows that currently, mangroves are in a good status in terms of nitrogen availability and chlorophyll levels which are related and both are key factors for photosynthesis. Remote sensing techniques were used for chlorophyll prediction. The results showed that these methods have the potential to be used for chlorophyll prediction and estimation.

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Assessment of long-term mangrove distribution using optimised machine learning algorithms and landscape pattern analysis

Bindajam

Mallick

Naikoo

et al. 2023

Environ Sci Pollut Res

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Locating suitable mangrove plantation sites along the Saudi Arabia Red Sea Coast

Cited by 16 publications

References 9 publications

Investigating Environmental Factors for Locating Mangrove Ex-situ Conservation Zones Using GIS Spatial Techniques and the Logistic Regression Algorithm in Mangrove Forests in Iran

Investigating Environmental Factors for Locating Mangrove Ex-situ Conservation Zones Using GIS Spatial Techniques and the Logistic Regression Algorithm in Mangrove Forests in Iran

Investigating chlorophyll and nitrogen levels of mangroves at Al-Khor, Qatar: an integrated chemical analysis and remote sensing approach

Assessment of long-term mangrove distribution using optimised machine learning algorithms and landscape pattern analysis

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