Geospatial Analysis of the Distribution of Mangrove ...

_____________________________________________________________________________________________________ *Corresponding author: E-mail: [email protected];

Journal of Geography, Environment and Earth Science International 18(3): 1-22, 2018; Article no.JGEESI.45953 ISSN: 2454-7352

Geospatial Analysis of the Distribution of Mangrove Species along the Shoreline in Akwa Ibom State,

Nigeria

Robert Etim Ekpenyong1*, Imoh Ukpong1, Sola Olajide2, Idongesit Etuk2, Mbotidem Ebong1 and Edidiong Robert Etim3

1Department of Geography and Natural Resources Management, University of Uyo, Nigeria.

2Department of Forestry and Wildlife, University of Uyo,

Nigeria.

3School of Basic Studies, University of Uyo, Nigeria.

Authors’ contributions

This work was carried out in collaboration between all authors. All the authors were involved in the fieldwork. They identified the different species of mangrove in the quadrats and measured their abundance. The first author designed the study, produced the maps and wrote the draft of the

manuscript while the second author read and approved the final manuscript. All authors read and approved the final manuscript.

Article Information

DOI: 10.9734/JGEESI/2018/45953

Editor(s): (1) Dr. Wen-Cheng Liu, Department of Civil and Disaster Prevention Engineering, National United University, Taiwan and

Taiwan Typhoon and Flood Research Institute, National United University, Taipei, Taiwan. Reviewers:

(1) Atiyat Abdalla Fadoul Nuri, Red Sea University, Sudan. (2) Vartika Singh, Amity Institute of Global Warming and Ecological Studies, India.

Complete Peer review History: http://www.sciencedomain.org/review-history/28027

Received 05 October 2018 Accepted 17 December 2018

Published 31 December 2018

ABSTRACT

Mangrove forest is an ecosystem that offers many goods and services which can sustain mankind for eternity. Unfortunately, in Akwa Ibom State, this very important ecosystem is declining because of deforestation arising from over exploitation and development activities in the area. Aim: The aim of this study was to analyze the distribution of mangrove species along the shoreline in Akwa Ibom State using a geospatial approach. Methodology: Remote sensing, Global Positioning System and Geographical Information Systems techniques were used to determine, map and analyse the locations and distribution of mangrove forest in the area. Results: The results of the study revealed that most mature stands of the different mangrove species, mainly A. Africana and R. racemosa occur on the braided islands found within the Cross

Original Research Article

Ekpenyong et al.; JGEESI, 18(3): 1-22, 2018; Article no.JGEESI.45953

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River estuary in Okobo Local Government Area and along the Kwa Iboe Creek in Eastern Obolo Local Government Area. Conclusion: This study has shown how to map and analyze mangrove at the species level using geospatial technologies. It revealed the actual locations of the two dominant species of mangrove found along the Nigerian shoreline in Akwa Ibom State. With this approach, it is possible to monitor and manage mangrove ecosystem for sustainable goods and service provision, poverty alleviation and climate change mitigation.

Keywords: Geospatial; mangrove species; ecosystem goods and services; remote sensing;

geographic information systems.

1. INTRODUCTION

Remote sensing applications in mangrove studies include inventory and change detection [1]. The application at the species level is still inconclusive [2,3,4]. However, mapping mangroves at the species level is required for a thorough understanding of mangrove biodiversity and mangrove management [5]. From a spectral point of view, it is almost impossible at present to characterize each individual mangrove species [6,7,8,9,10,11,12]. However, because mangroves are difficult to differentiate among themselves and from adjoining vegetation communities, a proper understanding of the local situation requires ground-survey activities to verify image-analyses results. Furthermore, such intensive fieldwork is often hindered by the inaccessibility of areas within the mangrove ecosystem [2]. The word geospatial is a term that has recently been gaining popularity and is used to define the collective data that has a geographic component to it as well as the technology used to acquire, manipulate, and store the geographic information. Geographical Information Systems is one form of geospatial technology. Global Positioning System and Remote Sensing are other examples of geospatial technology. This study shows how these technologies/techniques can be combined to ascertain the locations/ distribution of mangrove species.

2. MATERIALS AND METHODS 2.1 Location of the Study Area

Akwa Ibom State is situated in South Eastern Nigeria. It lies between latitude 4°30" and 5°30"N and longitudes 7°30" and 8°30"E (Fig. 1). This location is within the tropical rainforest belt where deforestation destroys globally important carbon sinks that sequester carbon dioxide [CO2] from the atmosphere and are critical to future climate stabilization [13,14].

Furthermore, Akwa Ibom is drained by three major rivers namely, the Cross River, Kwa Iboe River and Imo River. The estuaries of these rivers are the habitats of mangroves. This is evident from the 1982 vegetation and landuse map of Akwa Ibom State (Fig. 2). Based on mangrove distribution information on this map, the estuaries became the focus of this study/ fieldwork.

2.2 Data Acquisition 2.2.1 Satellite data To determine and map the current distribution of mangrove forest ecosystems in Akwa Ibom State, land cover maps of the area for 2016 was produced. Land cover analysis and mapping requires medium spatial and temporal resolution satellite data. 30 m resolution landsat TM has become the standard. Consequently, orthorectified Landsat 8 satellite data for 2016 was acquired for use in land cover mapping and analysis. 2.2.2 Field data Prior to image classification to produce land cover maps, a reconnaissance survey of the area was carried out to identify training/test sites among other things. Cluster analysis/ unsupervised classification were carried out using the 2016 satellite imagery. This analysis allowed natural spectral clusters to be defined with high level of objectivity and reliability. This exercise helped in the pre-determination of training/test sites. Field verification was undertaken to determine coordinates of the sites with GPS as well as the type of land cover at such sites. This information was used in image classification and accuracy assessment [15,16]. The fieldwork to collect data on mangrove species took place between 20

th June 2017

and 26th August 2017 (i.e. during the rainy season).


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2.2.3 Data on mangrove species 2.2.3.1 Measuring vegetation Indices of

abundance Several vegetation attributes including density, biomass, cover and frequency can be estimated in quadrat. In this study, cover (also called canopy cover) was the attribute measured. Cover is a commonly used measure as it enables all

species to be compared irrespective of their size or abundance. There are a number of ways to estimate cover. When using quadrats, an observer estimates the proportion of the quadrat occupied by different species. In addition to estimating the actual percentage of the quadrat covered by different species, the observer can categorize cover estimates, for example into cover classes, percentage cover ranges, or cover categories.

Fig. 1. Location of Akwa Ibom State, Nigeria Source: Akwa Ibom State Surveys, 1997


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Fig. 2. Vegetation and landuse map of Akwa Ibom state as at 1982 Source: Extracted from the Map of Cross River Basin showing Vegetation and Landuse published in 1982 by

Cross River Basin Development Authority

Table 1. Cover estimates in the mangroves

Cover class Percentage cover range Cover category Very dense >75% 5 Dense 51–75% 4 Sparse 26–50% 3 Very sparse 6–25% 2 Isolated plants 1–5% 1 Absent 0% 0


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Transects and quadrats are ecological tools that can be used to quantify the relative abundance of organisms in an area. There are many types of quadrats but photoquadrat was used in this study. Photographs of the study sites sized to fit the quadrat frame were taken. Quadrats measuring 20 m x 20 m were placed at points along a transect line on the coastline that was traversed using GPS and estimates of what percent each item takes up within the frame made according to Table 1. The forestry literature recommends 400-1,000m² as a minimum area to adequately characterize forest communities [17].

There are many possible sampling schemes available for vegetation sampling with variations appropriate for all types of coastal vegetation. In most cases however the vegetation stands are selected subjectively, then sampled using quadrats that may be systematically or randomly located along established transects. Common variations according to Barbour et al. [18] include:

a) Locating quadrats in a completely random fashion

b) Locating quadrats in a restricted or stratified random manner (stratified random sampling).

This is often based on the plant community that is present. Placing quadrats randomly within the various community types helps ensure that habitat heterogeneity is adequately represented. In this study, stratified random sampling was adopted. Stratification involves dividing the area into non-overlapping areas (strata) and selecting a simple random sample (or samples) from each of the strata. The study area was first stratified based on the need to ensure that the heterogeneity of flora/vegetation types in the area was adequately represented. Then quadrats were randomly located within the identified strata. The strata identified in the study area included the following:

a) Areas dominated by true mangroves, b) Areas with both true mangroves,Nypa

fruticans and other associates, c) Areas dominated by Nypa fruticans

2.3 Data Analysis and Interpretation

2.3.1 Satellite data

Image classification was carried out to determine the distribution of mangrove and other land cover

types in the area. Definition of a classification scheme is an initial step in any classification project. In this project, the FAO Land Cover Classification System [LCCS] was used. Based on the ancillary data and information gathered from the field, the vegetation/land cover types in the study area were determined. They included mangrove swamp forest, freshwater swamp forest, secondary forest, rivers/water bodies, farms/fallow land and built-up area.

GIS and remote sensing technologies employing Landsat 8 satellite image and supervised classification algorithm were used to produce the land cover map for 2016 [15,16,19]. The map was then used as background for the display of the locations of photo-quadrats in the study.

3. ANALYSIS OF RESULTS

3.1 Cross River Estuary

Fig. 3 shows the extent and distribution of the ecosystem within the cross river estuary as well as the quadrat locations. This area was segmented as follows:

3.1.1 Okobo Island segment [Comprised 18 quadrats numbered 1 to 18]

The shoreline in the Okobo Island segment was largely dominated by Nypa fruticans (Table 2). However, in areas with mangrove, the dominant specie was A. africana. This is obvious from Table 2. Seven [7] out of the eighteen [18] quadrats in this area was dominated by matured stands of A. africana [see photoquadrat 4-8 in the appendix].

3.1.2 Oron – Esuk Ewang Segment [Comprised 10 quadrats numbered 19 to 28]

Table 3 revealed the fact that, all the quadrats in this area were dominated by Nypa fruticans without any co-dominant species. There were isolated stands of mainly R. racemosa and Laguncularia racemosa in some of the quadrats [for example, see photoquadrat 21 in the appendix for details].

3.1.3 Effiat Mbo Segment [Comprised 10 quadrats numbered 29 to 38]

It is obvious from Table 4 that the coastline in this area had been invaded by Nypa fruticans. Six [6] out of the ten [10] quadrats had more than 75% cover of Nypa fruticans. However, Table 4 also revealed the fact that the dominant species


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of mangrove in this area was R.racemosa and this was found mostly in the eastern side of Effiat

Mbo coastline [Fig. 3 and photoquadrat 34 and 35].

Fig. 3. Cross river estuary: Distribution of mangrove ecosystem as at 2016 and locations of Quadrats


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Table 2. Composition of mangrove species per quadrats in Okobo Island segment

Location/Quadrat Id on map

Co-ordinates [WGS84, UTM zone 32N] Mangrove species composition and abundance Northings Eastings

1 536854.9 412135.0 50% R. racemosa,40% Nypa fruticans,10% other plants 2 537485.2 411615.9 35% R. racemosa, 30% other plants, 20% A. Africana and 15% Nypa fruticans 3 537911.7 410688.9 40% Nypa fruticans, 25% R .racemosa, 25% A. africana, and 10% other plants 4 538820.1 410577.6 75% A. africana, 15% Nypa fruticans and 10% other plants 5 540562.9 410002.9 80% A. africana, 15% R. racemosa and 5% other plants 6 541063.5 409613.6 70% A. africana, 25% R. racemosa and 5% other plants 7 541842.2 408816.3 70% A. africana, 25% R. racemosa and 5% other plants 8 542064.7 409168.6 70% A. africana, 25% R. racemosa and 5% other plants 9 541693.8 409335.5 50% R. racemosa, 45% A. africana and 5% other plants 10 541545.5 409965.8 75% R. racemosa, 15% A. africana and 10% other plants 11 541842.2 410522.0 70% A. africana, 25% R. racemosa and 5% other plants 12 540507.3 411467.6 45% R. racemosa, 25% A. africana, 25% Nypa fruticans and 5% other plants 13 539246.6 412190.6 50% Nypa fruticans, 25% A. africana, 20% R. racemosa, and 5% other plants 14 538838.7 412987.9 50% Nypa fruticans, 25% A. africana, 20% R. racemosa, and 5% other plants 15 535186.3 415694.7 95% Nypa fruticans and 5% R. racemosa 16 535445.1 416373.7 95% Nypa fruticans and 5% R. racemosa 17 533443.5 416121.1 85% Nypa fruticans and 15% R. racemosa 18 533591.8 414953.1 50% R. racemosa and 50% Nypa fruticans

Table 3. Composition of mangrove species per quadrats in Esuk Ewang Segment

Location/ Quadrat Id on map Co-ordinates [Wgs84, Utm zone 32n] Mangrove species composition and abundance Northings Eastings

19 533573.3 415360.9 95% Nypa fruticans and 5% R. racemosa 20 532757.5 417400.4 100% Nypa fruticans 21 532423.8 418030.8 95% Nypa fruticans and 5% R. racemosa 22 532479.4 418605.5 95% Nypa fruticans and 5% R. racemosa 23 533091.2 420626.4 95% Nypa fruticans and 5% R. racemosa 24 532746.4 420560.7 95% Nypa fruticans and 5% R. racemosa 25 530662.8 421096.5 50% nypa and 50% other plants 26 515700.6 425539.5 50% nypa and 50% other plants 27 523858.3 424834.9 75% Nypa fruticans, 15% R. racemosa and 10% Laguncularia racemosa 28 525267.5 424204.6 90% Nypa fruticans and 10% Laguncularia racemosa


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Table 4. Composition of mangrove species per quadrats in Effiat Mbo segment

Location/ Quadrat Id on map Co-ordinates [WGS84, UTM zone 32N] Mangrove species composition and abundance Northings Eastings

29 516683.2 423833.8 100% Nypa fruticans 30 516386.6 423166.4 100% Nypa fruticans 31 511770.1 425965.9 100% Nypa fruticans 32 510719.8 425204.2 95% Nypa fruticans and 5% other plants 33 509449.8 424866.8 95% Nypa fruticans and 5% R.racemosa 34 509526.7 427374.9 75% R.racemosa, 15% Nypa fruticans and 10% other plants 35 509916.1 427226.7 75% R.racemosa, 15% Nypa fruticans and 10% other plants 36 510305.4 427245.2 50% R.racemosa,25% Nypa fruticans and 25% other plants 37 511621.8 426447.9 50% A. africana, 25% Nypa fruticans and 25% other plants 38 511643.6 426428.1 75% Nypa fruticans and 25% A. Africana

Table 5. Composition of mangrove species per quadrats in Kwa Iboe river estuary

Location/ Quadrat Id on map Co-ordinates [WGS84, UTM zone 32N] Mangrove species composition and abundance

Northings Eastings

39 502722.5 383787.2 100% Nypa fruticans 40 502648.4 383230.9 100% Nypa fruticans 41 502626.6 383263.7 75% Nypa fruticans and 25% other plants 42 503367.4 386901.7 75% Nypa fruticans and 25% other plants 43 503389.9 387476.6 75% Nypa fruticans and 25% R.racemosa 44 502611.3 388477.4 50% Nypa fruticans, 25% R.racemosa and 25% other plants


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Table 6. Composition of mangrove species per quadrats in Eastern Obolo segment

Location/ Quadrat Id on map

Co-ordinates [WGS84, UTM zone 32N] Mangrove species composition and abundance Northings Eastings

45 498828.7 362315.5 50% A. africana, 25% Nypa fruticans, 20% R. racemosa, and 5% other plants 46 498059.8 361973.8 50% A. africana, 25% Nypa fruticans, 20% R. racemosa and 5% other plants 47 498059.8 361840.9 50% Nypa fruticans, 40% A. africana, 5% R. racemosa, and 5% other plants 48 498012.4 361613.1 100% nypa 49 498040.8 360616.4 60% A. africana, 35% Nypa fruticans and 5% other plants 50 497737.1 359999.4 50% R. racemosa, 35% Nypa fruticans, 10% A. africana and 5% other plants 51 498040.8 359458.3 100% Nypa fruticans 52 498477.5 359107.1 70% A. africana, 30% Nypa fruticans 53 498629.4 357218.1 75% A. africana, 25% R. racemosa 54 498382.6 356458.6 75% R. racemosa, 25% A. africana 55 497841.5 355689.8 75% A. africana, 25% R. racemosa 56 498078.8 355395.5 75% R. racemosa, 25% A. africana 57 498363.6 355110.7 60% R. racemosa, 40% A. africana 58 498629.4 354768.9 60% R. racemosa, 40% A. africana 59 498714.8 354237.4 60% R. racemosa, 40% A. africana 60 498059.8 352652.1 40% R. racemosa, 30% A. africana and 30% Nypa fruticans 61 497993.4 352177.5 75% R. racemosa, 25% A. africana 62 498183.2 351389.6 100% Nypa fruticans 63 498297.1 351066.9 70% R. racemosa, 30% Nypa fruticans 64 498496.5 350829.6 100% regenerating R. racemosa 65 499047.0 350649.2 75% R. racemosa, 25% A. africana 66 499014.3 350675.7 40% R. racemosa, 30% A. africana and 30% Nypa fruticans 67 499091.3 353905.5 65% Nypa fruticans, 25% R. racemosa and 10% A. africana 68 498562.9 359220.9 70% R. racemosa, 30% Nypa fruticans 69 498107.3 359543.7 100% Nypa fruticans 70 497869.9 360084.8 40% R. racemosa, 30% A. africana and 30% Nypa fruticans 71 497964.9 360208.2 90% Nypa fruticans and 10% other plants 72 498088.3 360369.6 50% R. racemosa, 40% Nypa fruticans and 10% A. africana 73 498078.8 361005.6 90% Nypa fruticans and 10% other plants 74 498069.3 361024.6 75% Nypa fruticans and 25% R. racemosa


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Fig. 4. Kwa Iboe river estuary: Distribution of mangrove ecosystem as at 2016 and locations of Quadrats

3.2 Kwa Iboe Estuary [Comprised 6 Quadrats Numbered 39 to 44]

Table 5 shows that all the quadrats in the Kwa Iboe river estuary had more than 75% cover of Nypa fruticans. Few stands of R.racemosa were found behind nypa as shown in photoquadrat 43 in appendix.

3.3 Imo River Estuary [Comprised 29 Quadrats Numbered 45 to 74]

3.3.1 Eastern Obolo segment Table 6 shows that only 8 of the 30 quadrats in this area had higher percentage cover of Nypa fruticans. The remaining 22 quadrats were


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dominated by R. racemosa [in 15 quadrats] and A. Africana [in 7 quadrats]. These species of mangrove occurred in mature stands [for example, see photoquadrats 52-54 and 59 in the appendix]. Also revealed were some of the locations where indiscriminate mangrove harvesting was taking place [see photoquadrat 55 and 57 in the appendix].

4. DISCUSSION

Figs. 3, 4 and 5 show the distribution of mangrove forest ecosystem in Akwa Ibom State as at 2016. These maps give the impression that the entire areas in green color are areas/locations dominated by different species of mangroves. However, as shown in the quadrat analysis in Tables 2 to 6, this impression is misleading. This is because there are other plants in these locations having spectral reflectance that are similar to mangrove. This explains why mapping mangrove at species level

using remote sensing techniques is difficult and still inconclusive [2, 3, 4]. However, with the approach of combining image classification and photo-quadrat analysis as exemplified in this study, it is possible not only to map mangrove at species level but also monitor and manage mangroves at various locations to ensure sustainability. Furthermore, studies have revealed that the species of mangrove within the study area include R. racemosa, R. mangle, R harrisonii, A. africana, L. racemosa, P. reclinata and C. erectus [20,21]. However, it is evident from this study that only R. racemosa and A. Africana are found in the areas studied. This means that so much has been lost over the years as a result of mangrove deforestation. The result is that areas that were mangrove some years ago have been taken over completely by nypa fruticans (see photo-quadrat 21, 43 and 52).

Fig. 5. Imo river estuary: Distribution of mangrove ecosystem as at 2016 and locations of quadrats


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5. ASSESSMENT OF THE ACCURACY OF THE LAND COVER MAP

The tool used in determining the accuracy of maps produced from satellite imageries is called contingency table or confusion matrix. In a confusion matrix, classification results are compared to ground truth information. Using this tool, an accuracy assessment was carried out in order to check the accuracy of the land cover map produced and used in this study. High overall accuracy of 85.4% was achieved. The user's accuracy and the producer's accuracy for the mangrove class were 80% and 82.1% respectively. A user accuracy of 80% for mangrove class means that 80% of the pixels classified as mangrove are mangrove in reality (i.e approximately 80% of the ‘mangrove’ pixels in the classified image actually represent 'mangrove' on the ground). The user's accuracy is a measure of the reliability of the map. It informs the user how well the map represents what is really on the ground. It is the accuracy from the point of view of the map user. Producer's Accuracy is the map accuracy from the point of view of the map maker (the producer). It has to do with the probability that a certain land cover of an area on the ground is classified as such. A Producer's Accuracy of 82.1% for mangrove class means that approximately 82.1% of the ' mangrove forest' ground truth pixels also appear as ' mangrove forest' pixels in the classified image. This implies that a confusion of 17.9% was recorded in classifying the mangrove forest class. This value represents how well reference pixels of the ground cover type are classified [22,23,24,25]. The user and producer accuracy for any given class are not usually the same. In the above example the producer’s accuracy for the mangrove class was 82.1% while the user's accuracy was 80%. This means that even though 82.1% of the reference mangrove areas have been correctly identified as “mangrove”, only 80% percent of the areas identified as “mangrove” in the classification were actually mangrove. However, a target of an overall accuracy of 85% with no class less than 70% is considered as accurate [26]. The 85% target is often viewed by many as the standard of acceptability for thematic mapping from remotely sensed imagery [27,28,29,30,31]. This information is important so that users can evaluate how appropriate it is to use the classified map.

6. SUMMARY AND CONCLUSION This study has shown how to map and analyze the distribution of mangrove at the species level using geospatial technologies. It has revealed the actual locations of the different species of mangrove found along the Nigerian shoreline in Akwa Ibom State. Most mature stands of the different mangrove species, mainly A. Africana and R. racemosa occur on the braided islands found within the Cross River estuary in Okobo Local Government Area and along the Kwa Iboe Creek in Eastern Obolo Local Government Area. These two locations need to be monitored and managed for the preservation of mangrove biodiversity and genetic resources. This is in the interest of both the present and future generation. In particular, it is to ensure sustainable goods and service provision, poverty alleviation and climate change mitigation.

ACKNOWLEDGEMENT We are grateful to Tertiary Education Trust Fund [Tetfund], Nigeria for providing the research grant which enabled us to carry out this study.

COMPETING INTERESTS Authors have declared that no competing interests exist.

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APPENDIX

Locations with high density of mature mangrove species 1. Cross River Estuary

Location/Quadrat ID 4 75% A. africana, 15% nypa and 10% other plants

Location/Quadrat ID 5 80% A. africana, 15% R. racemosa and 5% other plants


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Location/Quadrat ID 21 5% R. racemosa and 95% nypa


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Location/Quadrat ID 34 75% R.racemosa, 15% nypa palm and 10% other plants

Location/Quadrat ID 35 75% R.racemosa, 15% nypa palm and 10% other plants


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2. Kwa Iboe River Estuary

Location/Quadrat ID 43 25% R. racemosa and 75% nypa

3. Imo River Estuary 3.1 Eastern Obolo Segment - Kwa Iboe Creek

Location/Quadrat ID 52 70% A. africana, 30% nypa


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Location/Quadrat ID 53 75% A. africana, 25% R. racemosa



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LOCATIONS WITH HIGH LEVEL OF INDISCRIMINATE MANGROVE DEFORESTATION



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_________________________________________________________________________________ © 2018 Ekpenyong et al.; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Peer-review history: The peer review history for this paper can be accessed here:

http://www.sciencedomain.org/review-history/28027

Geospatial Analysis of the Distribution of Mangrove ...

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