scholarly journals Tree species diversity in the forest of Renikhayong para village in Bandarban, Bangladesh: a case study

2020 ◽  
Vol 5 (2) ◽  
pp. 115-126 ◽  
Author(s):  
M Jannat ◽  
M Kamruzzaman ◽  
MA Hossain ◽  
MK Hossain
Keyword(s):  
Species Diversity ◽  
Tree Species ◽  
Diversity Index ◽  
Sustainable Use ◽  
Tree Height ◽  
Diversity Indices ◽  
Tree Species Diversity ◽  
Height Range ◽  
Hill District ◽  
Number Of Individuals

The study was conducted to explore tree species diversity of Renikhayong para Village Common Forest (VCF) of Bandarban hill district. Stratified random sampling was carried out to assess the tree species diversity of the VCF. Renikhayong Para VCF with an area of 40 acres of land has more than 85 tree species belonging to 31 families, where Euphorbiaceae family was dominant containing 11 species followed by Rubiaceae (7 species), Moraceae (7 species), Meliaceae (5 species), Mimosaceae (5 species), Combretaceae (4 species), Lauraceae (4 species) and Anacardiaceae (3 species). Dominant tree species was Grewia nervosa. Renikhayong para VCF has diverse floristic resources that are known from the Shannon-Wiener’s diversity index (4.007), Simpson’s diversity index (0.028), Margalef’s richness index (13.21) and Species evenness index (0.90). However, number of species and number of individuals both were highest in the height range of 5 - <10 m. Similar trend was observed in dbh classes. Number of individuals were highest in dbh range of 5 - <15 cm and the lowest in ≥ 55 cm. The results depict the presence of maximum small trees in the VCF and decreasing the number of trees with the increase of tree height (m) and dbh (cm). Presence of diverse tree species and diversity indices indicate the importance and potential of the VCF for conservation and sustainable use. J. Biodivers. Conserv. Bioresour. Manag. 2019, 5(2): 115-126

scholarly journals Tree species diversity and structural composition: The case of village common forest in Bandarban District, Bangladesh

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Morgubatul Jannat ◽  
Md. Kamruzzaman ◽  
Mohammed Kamal Hossain
Keyword(s):  
Species Diversity ◽  
Tree Species ◽  
Diversity Index ◽  
Tree Species Diversity ◽  
Height Range ◽  
Structural Composition ◽  
Number Of Species ◽  
Indigenous Tree Species ◽  
Unidentified Species ◽  
Number Of Individuals

Abstract. Jannat M, Kamruzzaman MD, Hossain MK. 2020. Tree species diversity and structural composition: The case of village common forest in Bandarban District, Bangladesh. Asian J For 4: 76-83. The study was conducted to explore indigenous tree species diversity of Babu para village common forest (VCF) in Bandarban District. Tree species diversity was assessed through stratified random sampling method using sample plots of 20 m × 20 m in size. Babu para VCF with an area of 40 acres has more than 406 individuals of 74 tree species belonging to 30 families, including eight unidentified species. Euphorbiaceae and Moraceae were the dominant families containing 7 species followed by Anacardiaceae (5 species), Mimosaceae (6 species), and Meliaceae (5 species). Both the number of tree species and number of individuals decreased regularly with the increase of total height except ≥ 30 m height range. Number of species and number of individuals was highest in the height range of (5-<10) m. Similar trend was found for dbh (cm) class distribution. Both the number of species and number of individuals were highest in the dbh range of (5-<15) cm. Babu para VCF has diverse floristic resources that seemed from the Shannon-Wiener’s diversity index (3.94), Simpson’s diversity index (0.025), Margalef’s richness index (12.15) and Species evenness index (0.92). The results depict the presence of rich indigenous tree species diversity in studied VCF.

scholarly journals Tree Species Diversity and Abundance of Akure Forest Reserve, Ondo State, Nigeria

2021 ◽  
Vol 25 (8) ◽  
pp. 1415-1419
Author(s):  
O.M. Ogundele ◽  
P.O. Ige ◽  
Y.T. Owoeye ◽  
D.E. Abanikanda ◽  
O.O. Komolafe
Keyword(s):  
Species Diversity ◽  
Tree Species ◽  
Population Distribution ◽  
Diversity Index ◽  
Diversity Indices ◽  
Tree Species Diversity ◽  
Forest Reserve ◽  
Wiener Diversity Index ◽  
Permanent Sample Plot ◽  
Ondo State

This study was carried out to examine the tree species diversity and abundance in a natural forest ecosystem in the Southwestern region of Nigeria. Data were collected from a four equal size sampling plot of 50×50m in a permanent sample plot section of Akure Forest Reserve. All living trees with DBH ≥ 10cm were measured and identified. A total of 956 trees were encountered. These trees were from 42 genera and 20 families. Celtis zenkeri belonging to the family of Ulmaceae was the species with the highest population distribution while Sterculiaceae was the dominant family in the study area. The Shannon-Wiener Diversity Index (Hˈ) of 3.196 and species evenness of 0.84 were obtained from the study area. The high values of diversity indices obtained indicated that the forest is rich in biodiversity and hence should be protected from any forms of disturbance to enhance sustainability as well as protect the rare species in it from going into extinction.

scholarly journals Tree species diversity and structural composition: The case of Durgapur Hill Forest, Netrokona, Bangladesh

2019 ◽  
Vol 3 (1) ◽  
pp. 10-19 ◽  
Author(s):  
MD. RAYHANUR RAHMAN ◽  
Md. MIZANUR RAHMAN ◽  
Md. ARIF CHOWDHURY ◽  
JARIN AKHTER
Keyword(s):  
Species Diversity ◽  
Tree Species ◽  
Stand Structure ◽  
Diversity Index ◽  
Acacia Auriculiformis ◽  
Tree Species Diversity ◽  
Individual Tree ◽  
Height Range ◽  
Structural Composition ◽  
Shorea Robusta

Abstract. Rahman MdR, Rahman MdM, Chowdhury MdA, Akhter J. 2019. Tree species diversity and structural composition: The case of Durgapur Hill Forest, Netrokona, Bangladesh. Asian J For 3: 10-19. Tree species diversity and stand structure of Durgapur hill forest were assessed through stratified random sampling method using sample plots of 20 m x 20 m in size during the period of October 2017 to May 2018. A total of 1436 stems of ≥5 cm DBH of 56 tree species belonging to 50 genera and 29 families were enumerated from sample area. Density (855 stem ha-1) and Basal area (29.27 m2 ha-1) of tree species were enumerated. Besides, Shannon-Wiener’s, Margalef’s, Simpson’s and Pielou’s diversity index were recorded for all the tree species. The study showed that the most dominant 10 species have 58% of the total IVI (174.29 out of 300). Where, Acacia auriculiformis showed the maximum Importance Value Index (51.02) followed by Shorea robusta (24.23). Number of individual tree species were highest (49) in the height range of 7- <12 m whereas maximum (52) species were recorded in the DBH (cm) range of 5- <10 cm. However, Acacia auriculiformis, Shorea robusta, and Tectona grandis were found as the most dominant species based on hierarchical cluster analysis. Therefore, current study will be helpful to the future policymakers in formulating forest resource management plan of Durgapur hill forest.

scholarly journals Evaluating Multi-Sensors Spectral and Spatial Resolutions for Tree Species Diversity Prediction

2021 ◽  
Vol 13 (5) ◽  
pp. 1033
Author(s):  
Enoch Gyamfi-Ampadu ◽  
Michael Gebreslasie ◽  
Alma Mendoza-Ponce
Keyword(s):  
Species Richness ◽  
Species Diversity ◽  
Tree Species ◽  
Diversity Index ◽  
Diversity Indices ◽  
Shannon Index ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Tree Species Diversity ◽  
Sentinel 2

Forests contribute significantly to terrestrial biodiversity conservation. Monitoring of tree species diversity is vital due to climate change factors. Remote sensing imagery is a means of data collection for predicting diversity of tree species. Since various sensors have different spectral and spatial resolutions, it is worth comparing them to ascertain which could influence the accuracy of prediction of tree species diversity. Hence, this study evaluated the influence of the spectral and spatial resolutions of PlanetScope, RapidEye, Sentinel 2 and Landsat 8 images in diversity prediction based on the Shannon diversity index (H′), Simpson diversity Index (D1) and Species richness (S). The Random Forest regression was applied for the prediction using the spectral bands of the sensors as variables. The Sentinel 2 was the best image, producing the highest coefficient of determination (R2) under both the Shannon Index (R2 = 0.926) and the Species richness (R2 = 0.923). Both the Sentinel and RapidEye produced comparable higher accuracy for the Simpson Index (R2 = 0.917 and R2 = 0.915, respectively). The PlanetScope was the second-accurate for the Species richness (R2 = 0.90), whiles the Landsat 8 was the least accurate for the three diversity indices. The outcomes of this study suggest that both the spectral and spatial resolutions influence prediction accuracies of satellite imagery.

scholarly journals TREE SPECIES DIVERSITY IN A PRISTINE MONTANE FOREST PREVIOUSLY UNTOUCHED BY HUMAN ACTIVITIES IN FOJA MOUNTAINS, PAPUA, INDONESIA

REINWARDTIA ◽  
2018 ◽  
Vol 17 (2) ◽  
Author(s):  
Asep Sadili ◽  
Kuswata Kartawinata ◽  
Herwasono Soedjito ◽  
Edy Nasriadi Sambas
Keyword(s):  
Species Diversity ◽  
Tree Species ◽  
Human Activities ◽  
Diversity Index ◽  
Basal Area ◽  
Montane Forest ◽  
Tree Species Diversity ◽  
Importance Value ◽  
Montane Forests ◽  
Species Area

ADILI, A., KARTAWINATA, K., SOEDJITO, H. & SAMBAS, E. N. 2018. Tree species diversity in a pristine montane forest previously untouched by human activities in Foja Mountains, Papua, Indonesia. Reinwardtia 17(2): 133‒154. ‒‒ A study on structure and composition of the pristine montane forest previously untouched by human activities was conducted at the Foja Mountains in November 2008. We established a one-hectare plot divided into 100 subplots of 10 m × 10 m each. We enumerated all trees with DBH ≥ 10 cm which diameters were measured, heights were estimated and habitats were noted. We recorded 59 species, 42 genera and 27 families, comprising 693 trees with the total basal area (BA) of 41.35 m2/ha. The forest had lower species richness compared to those of lowland forests in Kalimantan, and Sumatra and montane forests in West Java. The Shannon-Wiener’s diversity index was 3.22. Nothofagus rubra (Importance Value, IV=47.89%) and Parinari corymbosa (IV=40.3%) were the dominant species, constituting the basis for designating the forest as the Nothofagus rubra - Parinari corymbosa association. To date, the dominance of N. rubra is unique to the Foja Mountains, as elsewhere in Papua the montane forests were dominated by N. pullei or other species. The species-area curve indicated a minimal area of 5000 m2. On the family level Fagaceae (IV=53.23%), Chrysobalanaceae (IV=40.53%) and Myristicaceae (IV=26.43%) were dominant. Verti-cally the forest consisted of four strata (A–D). In each stratum Nothofagus rubra, Platea latifolia, Parinari corymbosa and Myristica hollrungii were dominant. The diameter class distribution of Nothofagus rubra, Parinari corymbosa and Platea latifolia led us to assume that these species were regenerating well.

scholarly journals Deep Learning Approaches for the Mapping of Tree Species Diversity in a Tropical Wetland Using Airborne LiDAR and High-Spatial-Resolution Remote Sensing Images

Forests ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 1047 ◽  
Author(s):  
Ying Sun ◽  
Jianfeng Huang ◽  
Zurui Ao ◽  
Dazhao Lao ◽  
Qinchuan Xin
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
Species Diversity ◽  
Spatial Resolution ◽  
Tree Species ◽  
High Spatial Resolution ◽  
Diversity Index ◽  
Tree Species Diversity ◽  
Individual Tree ◽  
Rgb Images

The monitoring of tree species diversity is important for forest or wetland ecosystem service maintenance or resource management. Remote sensing is an efficient alternative to traditional field work to map tree species diversity over large areas. Previous studies have used light detection and ranging (LiDAR) and imaging spectroscopy (hyperspectral or multispectral remote sensing) for species richness prediction. The recent development of very high spatial resolution (VHR) RGB images has enabled detailed characterization of canopies and forest structures. In this study, we developed a three-step workflow for mapping tree species diversity, the aim of which was to increase knowledge of tree species diversity assessment using deep learning in a tropical wetland (Haizhu Wetland) in South China based on VHR-RGB images and LiDAR points. Firstly, individual trees were detected based on a canopy height model (CHM, derived from LiDAR points) by the local-maxima-based method in the FUSION software (Version 3.70, Seattle, USA). Then, tree species at the individual tree level were identified via a patch-based image input method, which cropped the RGB images into small patches (the individually detected trees) based on the tree apexes detected. Three different deep learning methods (i.e., AlexNet, VGG16, and ResNet50) were modified to classify the tree species, as they can make good use of the spatial context information. Finally, four diversity indices, namely, the Margalef richness index, the Shannon–Wiener diversity index, the Simpson diversity index, and the Pielou evenness index, were calculated from the fixed subset with a size of 30 × 30 m for assessment. In the classification phase, VGG16 had the best performance, with an overall accuracy of 73.25% for 18 tree species. Based on the classification results, mapping of tree species diversity showed reasonable agreement with field survey data (R2Margalef = 0.4562, root-mean-square error RMSEMargalef = 0.5629; R2Shannon–Wiener = 0.7948, RMSEShannon–Wiener = 0.7202; R2Simpson = 0.7907, RMSESimpson = 0.1038; and R2Pielou = 0.5875, RMSEPielou = 0.3053). While challenges remain for individual tree detection and species classification, the deep-learning-based solution shows potential for mapping tree species diversity.

scholarly journals Analyzing the Relationship, Distribution of Tree Species Diversity, and Above-Ground Biomass on the Chitwan-Annapurna Landscape in Nepal

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shiva Pokhrel ◽  
Chungla Sherpa
Keyword(s):  
Species Diversity ◽  
Sea Level ◽  
Tree Species ◽  
Diversity Index ◽  
Tree Species Diversity ◽  
Above Ground Biomass ◽  
Breast Height ◽  
Ground Biomass ◽  
The Relationship ◽  
Landscape Level

Forests provide numerous ecosystem goods and services. Their roles are considered as important for both climate mitigation and adaptation program. In Nepal, there are significant forest resources which are distributed in different regions; however, the studies on the spatial tree species distribution and the above-ground biomass and their relationship at the landscape level have not been well studied. This study aims to analyze the relationship, distribution of tree species diversity, and above-ground biomass at a landscape level. The data used for this study were obtained from the Forest Research and Training Center of Nepal, International Centre for Integrated Mountain Development (ICIMOD), and Worldwide Wildlife Fund (WWF-Nepal). The landscape has a mean of 191.89 tons ha−1 of the above-ground biomass. The highest amount of the above-ground biomass measured was 650 tons ha−1 with 96 individual trees, and the least was 3.428 tons ha−1. The measured mean height of the tree was 11.77 m, and diameter at breast height (DBH) was 18.59 cm. In the case of the spatial distribution of the above-ground biomass, plots distributed at the middle altitude range greater than 900 meters above sea level (m. a. s. l) to 3000 meters above sea level taking more amount of the above-ground biomass (AGB). Similarly, the highest plot-level Shannon diversity index (H’) was 2.75 with an average of 0.96 at the middle altitude region followed by the lower region with an average of 0.89 and least 0.87 at a higher elevation. Above-ground biomass (R2 = 0.48) and tree height (R2 = 0.506) significantly increased with increasing elevation up to a certain level increased of elevation. Diameter at breast height (DBH) showed significance (R2 = 0.364) but small increase with increasing elevation, while the relationship among tree species diversity index, above-ground biomass, and elevation showed a weak and very weak positive relationship with R2 = 0.018 and R2 = 0.002, respectively. Based on the overall results, it is concluded that elevation has some level of influence on the forest tree diversity and above-ground biomass. The finding of this study could be useful for landscape-level resource management and planning under various changes.

scholarly journals Community forestry adoption based on multipurpose tree species diversity towards to sustainable forest management in ICEF of University of Lampung, Indonesia

2018 ◽  
Vol 19 (3) ◽  
pp. 1102-1109 ◽  
Author(s):  
CHRISTINE WULANDARI ◽  
AFIF BINTORO ◽  
RUSITA RUSITA ◽  
TRIO SANTOSO ◽  
DURYAT DURYAT ◽  
...  
Keyword(s):  
Forest Management ◽  
Species Diversity ◽  
Tree Species ◽  
Sustainable Forest Management ◽  
Community Forestry ◽  
Diversity Index ◽  
Conservation Education ◽  
Tree Species Diversity ◽  
Multipurpose Tree ◽  
Multipurpose Tree Species

Wulandari C, Bintoro A, Rusita, Santoso T, Duryat, Kaskoyo H, Erwin, Budiono P. 2018. Community forestry adoption basedon multipurpose tree species diversity towards to sustainable forest management in ICEF of University of Lampung, Indonesia.Biodiversitas 19: 1102-1109. Integrated Conservation Education Forest (ICEF) of University of Lampung (Unila) at Wan AbdulRachman (WAR) Forest Park is a conservation forest which should be free from any kinds of human activities. In fact, more than 75%the area has been managed by community hence there is a need for management strategy through Community Forestry (CF). It is knownthat there are a lot of Multipurpose Tree Species (MPTS) that can be utilized for the community’s daily life. The research’s objectivesare to analyze the ability of the community to adopt CF scheme, to calculate the diversity index of MPTS and level of Skill KnowledgeAttitude (SKA) and to determine the correlation variables to sustainable CF. This study used Shannon-Wiener diversity index, analysisof SKA level and regression analysis for adoption level. The results of this study noted that at the research site has diversity index 0.115and 74.29% of plants are MPTS. Based on the data analysis, 168 respondents [89%] agree to adopt CF scheme and level of their SKA ismoderate therefore needs to increase this level towards to forest sustainability. There are three variables of community forestry adoptiontoward to sustainable forest management at ICEF: number of trees species, the volume of forest products that would be sold, and rolesof extension education.

scholarly journals Quantitative assessment of tree species diversity of Himchari National Park (HNP) in Cox’s Bazar, Bangladesh

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Saddam Hossen ◽  
Mohammed Kamal Hossain ◽  
Md. Akhter Hossain ◽  
Mohammad Fahim Uddin
Keyword(s):  
Species Diversity ◽  
Tree Species ◽  
National Park ◽  
Quantitative Assessment ◽  
Diversity Index ◽  
Tectona Grandis ◽  
The Other ◽  
Acacia Auriculiformis ◽  
Tree Species Diversity ◽  
Gmelina Arborea

Abstract. Hossen S, Hossain MK, Hossain MA, Uddin MF. 2020. Quantitative assessment of tree species diversity of Himchari National Park (HNP) in Cox’s Bazar, Bangladesh. Asian J For 5: 1-7. The aim of the study was to assess the tree species composition, dominance, and quantitative distribution of tree species of Himchari National Park, Cox’s Bazar in Bangladesh through stratified random sampling method using sample plots (51) of 20 m x 20 m in size during the period of January 2017 to May 2018. A total of 961 stems (dbh ≥ 5 cm) of 88 tree species belonging to 64 genera and 37 families were enumerated where the stem density and basal area were 457.39 stem ha-1 and 10.979 m2 ha-1 respectively. On the other hand, the species diversity index, Shannon-Wiener’s diversity index, Shannon’s maximum diversity index, species evenness index, Margalef’s diversity index, and Simpson’s diversity index were 0.092, 3.733 ± 0.0071, 4.477, 0.834, 12.667 and 0.039 ± 0.0003 respectively. The highest Importance Value Index (IVI) was found for Acacia auriculiformis (23.23) followed by Tectona grandis (13.05), Gmelina arborea (12.66), Syzygium fruticosum (12.34), Casuarina equisetifolia (10.57), and Dipterocarpus turbinatus (10.55). The IVI value represents that Acacia auriculiformis possess highest dominance that is followed by Tectona grandis and Gmelina arborea. Percentage distribution of tree individuals into different height classes found in quadrats showed that height range 3 - <8 m had the highest (59.83%) percentage of tree individuals. On the other hand, different dbh (having dbh ≥5 cm) classes showed that most of the trees (65.97%) belonged to dbh range 5 - <15 cm. The outcome of present study suggests for the protection, sustainable management, and conservation of the tree resources of HNP, Cox’s Bazar, Bangladesh.

scholarly journals Investigating the Relationship between Tree Species Diversity and Landsat-8 Spectral Heterogeneity across Multiple Phenological Stages

2021 ◽  
Vol 13 (13) ◽  
pp. 2467
Author(s):  
Sabelo Madonsela ◽  
Moses A. Cho ◽  
Abel Ramoelo ◽  
Onisimo Mutanga
Keyword(s):  
Species Diversity ◽  
Plant Species ◽  
Tree Species ◽  
Diversity Indices ◽  
Plant Species Diversity ◽  
Landsat 8 ◽  
Tree Species Diversity ◽  
Phenological Stages ◽  
Species Diversity Indices ◽  
The Relationship

The emergence of the spectral variation hypothesis (SVH) has gained widespread attention in the remote sensing community as a method for deriving biodiversity information from remotely sensed data. SVH states that spectral heterogeneity on remotely sensed imagery reflects environmental heterogeneity, which in turn is associated with high species diversity and, therefore, could be useful for characterizing landscape biodiversity. However, the effect of phenology has received relatively less attention despite being an important variable influencing plant species spectral responses. The study investigated (i) the effect of phenology on the relationship between spectral heterogeneity and plant species diversity and (ii) explored spectral angle mapper (SAM), the coefficient of variation (CV) and their interaction effect in estimating species diversity. Stratified random sampling was adopted to survey all tree species with a diameter at breast height of > 10 cm in 90 × 90 m plots distributed throughout the study site. Tree species diversity was quantified by the Shannon diversity index (H′), Simpson index of diversity (D2) and species richness (S). SAM and CV were employed on Landsat-8 data to compute spectral heterogeneity. The study applied linear regression models to investigate the relationship between spectral heterogeneity metrics and species diversity indices across four phenological stages. The results showed that the end of the growing season was the most ideal phenological stage for estimating species diversity, following the SVH concept. During this period, SAM and species diversity indices (S, H′, D2) had an r2 of 0.14, 0.24, and 0.20, respectively, while CV had an r2 of 0.22, 0.22, and 0.25, respectively. The interaction of SAM and CV improved the relationship between the spectral data and H′ and D2 (from r2 of 0.24 and 0.25 to r2 of 0.32 and 0.28, respectively) at the end of the growing season. The two spectral heterogeneity metrics showed differential sensitivity to components of plant diversity. SAM had a high relationship with H′ followed by D2 and then a lower relationship with S throughout the different phenological stages. Meanwhile, CV had a higher relationship with D2 than other plant diversity indices and its relationship with S and H′ remained similar. Although the coefficient of determination was comparatively low, the relationship between spectral heterogeneity metrics and species diversity indices was statistically significant (p < 0.05) and this supports the assertion that SVH could be implemented to characterize plant species diversity. Importantly, the application of SVH should consider (i) the choice of spectral heterogeneity metric in line with the purpose of the SVH application since these metrics relate to components of species diversity differently and (ii) vegetation phenology, which affects the relationship that spectral heterogeneity has with plant species diversity.

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