Floral Diversity of Abandoned Mansions and the Influence of Soil Properties on These Unique Vegetations

Abstract

Abandoned land and mansions are always a matter of curiosity to the human beings. They are treated as haunted places in many societies. In the present research, three decrepit abandoned mansions from the southern Bangladesh were investigated to measure their floral diversity, physico-chemical properties of soil and the soil-plant interrelationship which is responsible for the diversification of wild flora within the regions. From Shannon and Simpson diversity indexes, it can be deducted that the floral diversity within the abandoned mansions has a positive relationship with their territory size. The high values of Margalef’s and Menhinick’s species richness indexes confirmed that these areas are a rich source of a large number of plant species. A great variation in soil physico-chemical properties has been observed during the analysis. Soil organic matter, nitrogen, phosphorus, potassium & moisture contents were varied significantly from one quadrat to another in every site. Biplot analysis showed that the distribution of plant species in abandoned mansions is primarily determined by the organic matter, pH, moisture and potassium contents of soil. As these factors were present in versatile distribution within the studied regions, a great number of plants can grow in the same area simultaneously. So these areas should be protected from human intervention to process natural selection and in situ conservation of plant species.

Share and Cite:

Islam, M. , Hasan, M. , Laskar, M. , Das, S. and Sultana, T. (2021) Floral Diversity of Abandoned Mansions and the Influence of Soil Properties on These Unique Vegetations. American Journal of Plant Sciences, 12, 1559-1600. doi: 10.4236/ajps.2021.1210110.

1. Introduction

Land is a fundamental element for the survival of human on earth. Construction & agriculture are totally dependent on the availability of suitable land. During the early civilization era, a large amount of land came under agriculture by deforestation [1] [2]. But in the recent past centuries, a retrogressive situation has been observed. Due to the migration of rural people to the urban areas in search of livelihood, many farmlands were abandoned throughout the world, particularly in Europe [3] ‎ [4] [5]. The process is still so pronounced that researches predict, it will be continued for next few decades [6] [7] [8]. Around 210 million hectare farmland area had been abandoned in Europe, North America and Oceania till 1990, with the most critical condition in Europe where abandoned areas comprised of one-third of the total arable land [9] [10]. Land abandonment is one kind of ecological restoration processes that transform cultivated land into wild vegetation [11].

In recent years, there were few works carried out on abandoned areas in Asia by researchers. Due to low public access, wild flora and fauna get sufficient opportunities to flourish in these regions. Though these areas are much rich in species diversity as compared to the farm and fellow lands, very few researches have conducted on them to evaluate their floral richness. Moreover, none of the researches have concluded any finding to reveal the exact reasons behind the plant species diversity in these regions. Passive re-vegetation in permanently abandoned arable land (called secondary succession) is characterized by the re-placement species of a variety of habitat species of habitat dispersed species of habitat shapes [12]. Such secondary succession initially starts with annual or biannual plants, is then followed by perennial forbs, grasses and shrubs, and finally under usual Central European conditions ending up in a forest (climax stage). Abandonment of agricultural land is a significant change in land use from cultivation to a complex of plant successions. In most of Europe, the vegetation of deserted farmland has evolved into a dense forest or shrub. The expansion of vegetation explains, in part, the perceived decline in water resources, reductions in soil loss, and the progressive improvement of soil characteristics [5].

Biodiversity has developed as a complex concept recently. Plant biodiversity is an obscure understanding that represents heterogeneity and wide variations. Determination of species richness of an area is essential to measure its importance in biodiversity conservation [13]. There are a number of diversity indexes exist which are used as bioindicators in studies on both aquatic and terrestrial ecosystems [14]. A comprehensive list of all living organisms of an area along with their present conservation status and future improvement plan is essential to conserve and maintain biodiversity in a wild region. Continuous monitoring on wild ecosystems have a significant impact on national biodiversity assessment [15]. Floral diversity of an area plays a vital role on soil microclimate modification and nutrient recycling [16]. The interrelationship between soil and plant has been considered as a major mystery of nature and investigated by different researchers [17] [18] [19] [20].

Studies of plant variety have shown that secondary succession patterns depend upon the species that are initially present, their persistence or extinction and on the organization of latest species from native or regional species pools [21]. Similar patterns in secondary succession may be expected for soil organizations. However, spatial and temporal scales of spreading and formation take issue between plant and soil organisms similarly as between phyletic cluster of soil organisms. This could end in totally different national diversity patterns for plants and soil organization. A stronger understanding of the mechanism that drives soil diversity patterns will increase our understanding of the relationships between plant diversity and soil. But it seems to be different for each plant species [22]. The pattern of plant distribution & dynamics of biological resources determine the rational design and choice development of plant succession pathways within an ecosystem [23]. Introducing a new species without maintaining this manner may cause severe anomaly to its natural surroundings [24]. Explanation of vegetation type, composition of species, comment or prediction on the classification and pattern of vegetations in a purposeful manner are the basic objectives of phytosociology [25]. It is the study of distribution, composition, classification and interrelationship of plant communities [26]. The pattern and classification of plant communities within an ecosystem is regarded as phytosociology [25] [27]. It is a very useful tool to track changes in vegetation composition and how it alters edaphic components. Succession of plant species & their interactions are affected by several abiotic variables like soil texture, moisture, availability of nutrients, temperature, exposure to light and wind etc. Phytosociological study is regarded as the most advanced and economical method to exploit useful plant species from natural habitats [28].

Due to the balanced progression of plant succession and soil erosion, a wide range of environments occur in the abandoned regions simultaneously [5] [29]. If the environmental factors remain favorable for plant communities, development of forest ecosystem can occur within a short period of time. Land abandonment has several benefits including 1) expansion of vegetation cover that recovers the damaged ecosystem caused by deforestation [30] [31]; 2) higher absorption rate of carbon dioxide (CO2) which is the main culprit for global warming [32]; 3) increase of vegetation diversity during the secondary succession of plant species [33] [34] [35] [36]; 4) improvement of water infiltration and interception that reduces the chance of flooding [5] [37]; 5) better regulation of water cycle within the area that reduces soil erosion and ensures high quality runoff [5] [38]; 6) promotes higher longevity of adjacent reservoirs as it renders sediment contribution by discontinuing sediment transport network and protecting the soil surface from direct splash [39] [40]. As the plant taxonomy and ecology has a prominent importance in different conservation programs, the present research was conducted with the following objectives: a) analysis of phytosociological attributes of some abandoned mansions’ natural vegetations and b) assessment of the interrelationship between floral diversity and soil physico-chemical properties within the abandoned sites.

2. Materials and Methods

2.1. Selection of the Study Sites

The study was planned to be meted out within the following areas of Bangladesh in Barisal division: Kritipasa abandoned land, Duttapara abandoned land and Lakutia abandoned land. It’s been chosen, as a result of those 3 area unit as are acknowledge for his or her sensible natural forest condition, vegetation conservation activities:- Kritipasa (site-1), Duttapara (site-2), Lakutia (site-3).

2.1.1. Kritipasa Abandoned Land

Kritipasa was named when king krity Narayan. Ramjibonsen based the kritipasapalace. Kritipasa abandoned land is found at the village Kritipasa of Jhalokhati district. This can be most likely a century recent house. Now a days, it’s abandoned and in an exceedingly ramshackle conditiom. The zamindarbari (landlord’s house) five kilometers northwest of Jhalakhati.

Climate: The typical annual temperature is 26.0˚C (78.7˚F). The downfall is around 2165 millimeter (85.2 inch) annually1.

2.1.2. Duttapara Abandoned Land

The abandoned land settled on fifty acres of land in Duttapara village beneath Banaripara upazila in Barisal district. It’s domestically called Bhutterbari or Satkina Hindubari.

Climate: It’s a tropical climate. The summer here have an honest deal of rainfall, whereas the winters have little. The typical annual temperature in 25.9˚C (79.6˚F). Precipitation here is regarding 2021 millimeter (79.6 inch) annually2.

2.1.3. Lakutia Abandoned Land

The abandoned land settled on 49.50 acres of land in Lakutia village beneath Babuganj upazila in Barisal district, was designed by Rup Chandra Roy within the one seventh century. It’s located about 8 km north of Barisal city.

Climate: It’s a tropical climate. In winter, there’s a lot of less downfall than in summer. The typical annual temperature is 25.9˚C (78.7˚F). The annual downfall is 2184 millimeter (86.0 inch).

2.2. Vegetation Sampling

Vegetation analysis and soil sampling were done in October, 2019 to December, 2020. To collect vegetation data (4 m × 4 m) size quadrats were used in all the study sites. A total of nine quadrats were applied at randomly abandoned land of Kritipasa (site-1), six quadrats were at Duttapara (site-2) and four quadrats at Lakutia (site-3) at 10 m distance from one another. Then amount of plant species and number of individual of various species were recorded in every quadrat. The value of density, relative density, frequency, relative frequency and abundance was calculated. Vegetation data were collected from 9, 6 and 4 different locations from site-1, site-2 and site-3 respectively by placing (4 m × 4 m) quadrats randomly at a distance 10 m from each other.

2.3. Identification of Plant Species

As these areas have no legal owners at present, permission had been obtained from the local village authorities to collect plant materials from the study sites. This studt was compiled with Bangladesh Biodiversity Act, 2017 (part 2) as a national guideline. Voucher specimens for each plant species were collected and processed according to the standard herbarium techniques [41] [42]. Mr. Ashikur Rahman Laskar, Research Scholar, Department of Botany, University of Barisal, identified the collected plant samples consulting a number of Floras [43] - [51]. The voucher specimens are preserved at Barisal University Herbarium (BUH) for future reference.

2.4. Data Analysis

Following field data collection, the information was processed and compiled using Microsoft Excel and SPSS. Soil properties were used as an environmental variable for vegetation structure analyses. Of the two main ordination techniques of Redundancy Discriminant Analysis (RDA) and Canonical Correspondence Analysis (CCA)), RDA explained more interspecific variation in soil properties data than the CCA in the present study. Therefore, RDA was used for ordination analysis using log-transformed abundance data each species. The analyzed were performed using the R-Studio software. Species richness rarefaction curve, dominance (D) curve and diversity profile and hierarchical cluster (Dendogram) analysis were conducted using Paleontological Statistics (PAST) software package version 2.17 [52]. Phytosociological analysis were conducted following the formulas [53] [54] [55].

2.4.1. Analysis of Vegetation

After field data were collected, data on quantitative characteristics were compiled and processed for the diversity index. The basal area of the tree species has been calculated using the following equation [56].

Basal area = πD2/4;

where, D = Diameter at breast height, π = 3.1416.

For each species, relative density, relative frequency, relative abundance and significance index (IIV) were calculated. Identified plants have been arranged taxonomically and classified according to their usual form.

Functional diversity is defined as the variety of interactions within ecological process and can be quantified by determining the nature and extent to which functional groups are represented in an ecological system [57]. Functional diversity, evenness and richness were measured using different methods.

Generally, species diversity is determined not only by the number of species within a biological community, such as; species richness, but also by the relative abundance of individuals in that community. Species abundance is the number of individuals per species, and relative abundance refers to the uniform distribution of individuals across species within a community. Two communities may be equally rich in species but differ in relative abundance [58].

Four diversity indices, such as, Shannon Wienner Diversity Index (H), Margalef’s richness index (BX Simpon’s Diversity Index (D). Pielou’s Species Evenness Index (E) and Menhinick’s richness index (DI) and similarity index were analyzed to get a picture of vegetation of abandoned land [59] [60] [61] [62] [63].

2.4.2. Soil Sampling and Analysis

Soil samples were collected at 0 - 15 cm depth from center of every quadrat. Collected soil samples were unbroken in plastic baggage, right away when assortment, soil samples were brought at the Soil Research Development Institute (SRDI) in Barishal division. The collected soil samples was sieved through a 2 mm-mesh screen to get rid of plant roots, rocks etc. when sieving, soil samples were analyzed for physico-chemical properties. Soil pH, conductivity, moisture, total nitrogen, potassium phosphorus and organic matter were determined.

The soil PH was determined using digital pH meter. Electrical conductivity was determined by EC meter. Soil moisture content was determined using 10 g fresh soil at 80˚C. Total percentage of nitrogen, organic carbon, available phosphorus and potassium were determined by standard protocols [64] [65] [66] [67].

3. Results

3.1. Phytosociological Analysis of Plant Species

The plant species survey at the site-1 recorded 46 species under 29 families (Table 1). In Duttapara (study site-2), 48 plant species under 32 families were recorded (Table 2). A total 28 plant species under 22 families were recorded in Lakutia (Study site-3) (Table 3).

3.1.1. Density and Relative Density

The most densely populated populated species at site-1 (Table 4) were Vernonia cinerea (density of 10.25 and relative density of 9.601) followed by Chromolaena odorata (density of 9.74 and relative density of 9.134), Ardisia solanacea (density of 8 and relative density of 7.495), Mikania micrantha (density of 6.25 and relative density of 5.855), Alocasia acuminata (density of 5.75 and relative density of 5.387), Glycosmis pentaphylla (density of 5.5 and relative density of 5.152). Spathodea campanulata and Ficus benghalensis exhibited least density and relative density (0.25 and 0.234) followed by Alstonia scholaris, Borassus flabellifer.

On the other hand at site-2 (Table 5) Piper longum was most densely populated species (density of 9 and relative density of 9) followed by Adiantum philippense (density of 8.75 and relative density of 8.57), Mikania micrantha (density of 7 and relative density of 6.86), Achyranthes aspera (density of 6 and relative density of 5.88%) and Phyllanthus niruri (density of 5.5 and relative density of 5.39). Ficus racemosa and Nyctanthes arbor-tristis exhibited least density and relative density (0.25 and 0.24) followed by Carica papaya, Diospyros malabarica,

Table 1. Composition and distribution of plant species at site-1.

Table 2. Composition and distribution of plant species at site-2.

Table 3. Composition and distribution of plant species at site-3.

Table 4. Phyto-sociological association among the plant species found at site-1.

Note: DN = Density, RD = Relative Density, F = Frequency, FC = Frequency Class, RF = Relative Frequency, DS = Distribution, BA = Basal Area, RDo = Relative Dominance, IVI = Important Value Index, C = Contagious distribution, Re = Regular distribution, Ra = Random distribution.

Table 5. Phyto-sociological association among the plant species found at site-2.

Note: DN = Density, RD = Relative Density, F = Frequency, FC = Frequency Class, RF = Relative Frequency, DS = Distribution, BA = Basal Area, RDo = Relative Dominance, IVI = Important Value Index, C = Contagious distribution, Re = Regular distribution, Ra = Random distribution.

Calamus tenuis and Citrus maxima.

Site-3 (Table 6) represents that most densely populated species were Pteris vittata (density of 2.5 and relative density of 2.04) and Clerodendrum viscosum (density of 2 and relative density of 2 and relative density of 1.64) followed by Solanum indicum (density of 2 and relative density of 1.64), Lepidagathis linearis (density of 1.75 and relative density of 1.43), Synedrella nodifilia ( density of 1.75 and relative density of 1.43) and Urtica nivea (density of 2 and relative density of 1.43). Scoparia dulchis exhibited least density and relative density (0.25 and 0.20) followed by Persicaria lapathifolia, Passiflora foetida, Morinda citrifolia and Solanum torvum.

3.1.2. Frequency and Relative Frequency

The most frequent species at site-1 (Table 4) was Alocasia acuminata (frequency of 77.77 and relative frequency of 7.29) followed by Ardisia solanacea (frequency of 66.66 and relative frequency of 6.25), Chromolaena odorota (frequency of 55.55 and relative frequency of 5.20), Mikania micrantha (frequency of 55.55 and relative frequency of 5.20) and Glycosmis pentaphylla (frequency of 55.55 and relative frequency of 5.20). Percentage of frequency and relative frequency as ( 11.11 and 1.04) exhibited by most of species followed by Sida acuta, Oxalis corniculata, Ageratum conyzoides, Centella asiatica, Solanum indicum, Adiantum tenerum, Christella dentata, Ficus benghalensis, Alastonia scholaris, Ficus rumphii, Borassus flabellifer, Cyperus rotundus, Xanthosoma violaceum, Cayratia trifolia, Smilax macrophylla, Calophyllum inophyllum, Ficus microcarpa and Ardisia humilis.

On the other hand at site-2 (Table 5) was Mikania micrantha (frequency of 66.66 and relative frequency of 7.68) followed by Ficus hispida (frequency of 50 and relative frequency of 5.77), Ficus benghalensis (frequency of 33.33 and relative frequency of 3.84), Alocasia acuminata (frquency of 33.33 and relative frequency of 3.84), Achyranthes aspera (frequency of 33.33 and relative frequency 3.84), Stachytarpheta jamaicensis (frequency of. 33.33 and relative frequency of 3.84), Aphanamixis polystachya (frequency of 33.33 and relative frequency of 3.84), Glycosmis triphylla (frequency of 33.33 and relative frequency of 3.84) and Tiliacora acuminata (frequency of 33.33 and relative frequency of 3.84).

Percentage of frquency and relative frequency as (16.66 and 1.92) was exhibited by most of species followed by Operculina turpethum, Bryophullum pinnatum, Phyllanthus reticulatus, Commelina benghalensis, Ficus racemosa, Clerodendrum viscosum, Cassia fistula,Phyllanthus niruri,Breynia vitis-idaea, Urena lobata,Curcuma longa,Oxalis corniculata, Xanthosoma violaceum, Crinum asiaticum, Carica papaya, Syzygium fruticosum, Diospyros malabarica, Turnea ulmifolia, Nyctanthes arbor-tristis, Dioscorea pentaphylla, Adiantum capillus-veneris, Dioscorea esculenta, Piper longum,Ardisia solanacea, Vitex negundo, Curcuma zedoaria, Zehneria japonica, Urginea indica,Adiantum philippense, Glycosmis pentaphylla, Ardisia humilis, Paperomia pellucida, Drynaria quercifolia, Microsorum punctatum, Musa acuminata, Calamus tenuis, Colocasia

Table 6. Phyto-sociological association among the plant species found at site-3.

Note: DN = Density, RD = Relative Density, F = Frequency, FC = Frequency Class, RF = Relative Frequency, DS = Distribution, BA = Basal Area, RDo = Relative Dominance, IVI = Important Value Index, C = Contagious distribution, Re = Regular distribution, Ra = Random distribution.

esculenta, Clinogyne dichotoma, Citrus maxima.

At site-3 (Table 6) the most frequent species was Sloanum indicum (frequency of 100 and relative frequency of 8) followed by Artocarpus heterophyllus (frequency of 75 and relative frequency of 6), Pteris vittata (frequency of 75 and relative frequency of 6) and Lepidagathis linearis (frequency of 75 and relative frequency of 6). Percentage of frequency and relative frequency as (50 and 4) exhibited by most of species followed by Albizia richardiana, Urtica nivea, Dioscorea alata,Oxalis corniculata, Tabernaemontana divaricata, Synedrella nodiflora,Desmodium gangeticum, Nyctanthes arbor-tristis, Rungia pectinata, Nephrolepis cordifolia, Alstonia scholaris, Capparis zeylanica, Clerodendrum viscosum respectively.

3.1.3. Abundance

The most abundant species at site-1 (Table 4) was Vernonia cinerea with an abundance of 13.66 followed by Piper longum and Ageratum conyzoides with an abundance of 10 each. On the other hand at site-2 (Table 5) the most abundant species was piper longum with an abundance of 36 followed by Adiantum philippense (35), Phyllanthus niruri (22) and Phyllanthus reticulatus (21) respectively. At site-3 (Table 6) most abundant Species were exhibited by Mikania micrantha, Clerodendrum viscosum, Piper longum, Ardisia solanacea, Glycosmis triphylla.

Relative Dominance: The highest relative dominance was occupied by Clerodendrum viscosum, Mikania micrantha, Glycosmis pentaphylla, Polyalthia suberosa, Mikania cordata, Ficus hispida and Ficus religiosa respectively. The lowest relative dominance were represented by Pothos scandens, Piper longum, Ardisia humilis and Adiantum tenerum respectively. Site-2 (Table 5) represents that highest relative dominance was occupied by Mikania micrantha, Cassia fistulosa, Clerodendrum viscosum, Phyllanthus niruri, Ficus hispida and Ficus benghalensis respectively. The lowest relative dominance was represented by Drynaria quercifolia, Curcuma longa, Zehneria japonica, Paperomia pellucida, Xanthosoma violaceum respectively. On the other hand, Site-3 (Table 5) highet relative dominance were exhibited by Microlepia speluncae, Albizia richardiana, Solanum indicum, Tabernaemontana divaricata, Clerodendrum viscosum, Alastonia scholaris, Glycolysis triphylla and Artocarpus heterophyllus respectively.

3.1.4. Distribution

The maximum value of distribution were exhibited by Piper longum (0.90), Ardisia humilis (0.63), Centella asiatica (0.54), Oxalis corniculata (0.54), Stephania japonica (0.45) and Calophyllum inophyllum and least distribution were exhibited by Alocasia acuminata, Ficus virens, Morinda citrifolia at site-2 (Table 4). Piper longum exhibited maximum value of distribution at site-2 followed by Adiantum philippense, Phyllanthus niruri and Phyllanthus reticulatus. Lowest distribution were represented by Ardisia humilis, Ficus benghalensis, Ficus racemosa, Diospyros malabarica, Carica papaya, Nyctanthes arbor-tristis, Calamus tenuis and citrus maxima. On the other hand at site-3 maximum value of distribution occupied by Glycosmis triphylla, Ardisia solanacea and Microlepia speluncae and the lowest values represented by Artocarpus heterophyllus and Solanum indicum.

3.1.5. Important Value Index (IVI)

IVI was the highest for Clerodendrum viscosum as 39.66 (at site-1) followed by Mikania micrantha as 26.05, Glycosmis pentaphylla as 23.36, Chromolaena odorata as 16.99, Polyalthia suberosa as 14.49, Ardisia solanacea as 14.21, Vernonia cinerea as 13.18, Alocasia acuminata as 13.14 respectively. IVI were obtained highet for Mikania micrantha as 29.94, Cassia fistulosa as 26.77, Phyllanthus niruri as 16, Clerodendrum viscosum as 13.56, Ficus hispida 13.18, Piper longum as 12.56, Achyranthes aspera as 10.87 respectively at site 2 (Table 5). On the other hand at site 3, IVI was the highest represented by Sloanum indicum (22.59), Albizia richardiana (19.03), Microlepia speluncae (18.72), Tabernaemontana divaricata (16.58), Clerodendrum viscosum (14.99) and Alstonia scholaris (11.77) respectively (Table 6).

3.1.6. Preparation of Frequency Diagram

Raunkiaer (1934) recognized five frequency classes of plant species in the community on the of their frequency percentages. These are as follows:

Class A-1 to 20% frequency,

Class B-21 to 40% frequency,

Class C-41 to 60% frequency,

Class D -61 to 80% frequency,

Class E-81 to 100% frequency.

The frequency values refer to the values of Raunkier’s formula: A > B > C > D (site -1), A > B > C = D (site-2) and B < C > D > A (Site-3) (Table 7). The present ecological study shows that the given vegetation is heterogeneous in nature.

3.1.7. Abundance of Plant Families

There were in total 30 families found at the site-1 (Figure 1(a)), 31 families were also found at site-2 (Figure 1(b)) and 21 families at the site-3 (Figure 1(c)).

Figure 2 shows that more shrubs (38.93%) and climbers (16.10%) were available at site 1. A lot of herbs (60.5%) were found at site-2. at site-3 the highest tree percentage (11.38%) in comparison to the other study areas was observed.

Figure 3 depicts various diversity indices regarding the phytosociological aspects of plant communities from abandoned mansions.

3.1.8. Species Diversity & Distribution

Diversity and Dominance of species at site-1(Figure 4, Figure 5): A total of 46 plant species with (H = 3.47) diversity value were recorded at site-1. The maximum IVI distribution analysis of the plant species of abandoned land showed that the dominant was Clerodendrum viscosum. The co-dominant species were Mikania micrantha, Glycosmis pentaphylla, Chromolaena odorata, Polyalthia suberosa, Ardisia solanacea, Vernonia cinerea, Alocasia acuminata respectively (Table 1).

Diversity and Dominance of species at site-2 (Figure 4, Figure 5): A total of 48 plant species with (H = 3.20) diversity value were recorded at site-3. The maximum IVI distribution analysis of the plant species of abandoned land showed that the dominant was Mikania micrantha. The co-dominant species were Cassia fistulosa, Phyllanthus niruri, Clerodendrum viscosum, Ficus hispida,

Figure 1. Abundance of families found at site-1 (a), site-2 (b) and site-3 (c).

Piper longum, Achyranthes aspera respectively (Table 2).

Diversity and Dominance of species at site-3 (Figure 4, Figure 5): A total of 48 plant species with (H= 2.45) diversity value were recorded at site-3. The maximum IVI distribution analysis of the plant species of abandoned land showed that the dominant was Sloanum indicum. The co-dominant species were Albizia richardiana, Microlepia speluncae, Tabernaemontana divaricata, Clerodendrum viscosum and Alstonia scholaris respectively (Table 3).

3.1.9. Species Richness

The species rarefaction curve of the species richness was found to be higher in the quadrat-5 followed by q9, q8 at site-1. However, the trends of species richness were

Figure 2. Average herb, shrub, climber and tree percentage.

Figure 3. Diversity indices.

found to be greater in the quadrat-1 followed by q4, q3 at site-2 and species richness also found higher at q1 at site-3 (Figure 6).

3.1.10. Hierarchical Cluster of the Species Based on the Dominance of the Species

In order to determine the dominance of the tree species, produced the hierarchical cluster. Figureshows that recorded species in abandoned land of three different sites. Clerodendrum viscosum are most dominant species which are the

Figure 4. Dominance (D) curve of vegetation species at (a) site-1, (b) site-2, (c) site-3.

Figure 5. Diversity profile of Plant species at (a) site-1 (b) site-2 (c) site-3.

Table 7. Frequency class of plant at three different study site.

member of first cluster and rest of the species (Alocasia acuminata, Chromolaena odorata, Ardisia solanacea and Vernonia cinerea) were co-dominating species at site-1.The rest of species form 2nd, 3rd, 4th, 5th cluster (Figure 7).

At site-2, Figureshows that recorded species produced species hierarchical cluster. Mikania micrantha and Cassia fistula are most dominant species which are the member of first cluster and rest of species form 2nd, 3rd, 4th and 5th cluster (Figure8).

On the other hand, at site-3 Solanum indicum and Clerodendrum viscosum are most dominant within member of first cluster (Figure 9). Microlepia speluncae, Albizia richardiana and Tabernae-montana divaricata form the second dominant cluster of species in the study site-3. All these species are of natural origin. This signifies the importance of the abandoned land for native tree diversity conservation.

3.2. Ecological Characterization

3.2.1. Soil Properties

Within the three study sites, sandy loam and sandy clay loam type soils were prominent. Usually these soil types have high fertility and provide suitable environment for different insects and micro-organisms.

3.2.2. Soil Color

Figure 10 shows that in the 3 completely different study areas, brownish soil color was the most dominant, followed by brownish to blackish, grayish to blackish and brownish to reddish. Some of the site showed reddish soil color with little rocks, that limits the expansion and survivals of plants, insects and microorganisms, and it’s indicated by little or no ground vegetation. Some wetlands had loamy, clayey, blackish soil.

3.2.3. Soil Physico-Chemical Attributes

· pH: The pH of all soil samples were found to be ranged in between 7.4 to 8.1 (for site-1), 7.1 to 7.7 (site-2), 7.2 to 7.6 (site-3) within average value 7.8, 7.43, 7.44 respectively. The lowest value (7.1) was observed at the quadrat no. 01 within site-2 and the highest value was (8.1) at quadrat no. 09, 05 within site-1 (Table 8).

· Salinity (EC): Values of soil electrical conductivity ranged largely between the lowest 0.59 and the highest 2.04 dS/m at site-1, 0.60 to 2.23 dS/m at site-2 and 0.88 to 2.20 dS/m site-3 within mean values 1.0, 1.34, 1.40 dS/m.

Figure 6. Rarefaction curves of cumulative increase of Plant species richness for (a) site-1, (b) site-2, (c) site-3.

Figure 7. Hierarchical cluster of the species at site-1.

Figure 8. Hierarchical cluster of the species at site-2.

· Organic matter: Percentage of organic matter of all soil samples were found to be ranged between 0.30% to 13.39% with the average value 3.05% (at site-1), 2.00% to 12.00% with the average value 8.40% (site-2), (Table 8). 4.23% to 13.00% with average value 9.78% (site-3).

· Nitrogen: It was observed that percentage of total nitrogen of the soil samples were 0.015% to 0.699% within average value 0.15% (at site-1), 0.100% to 0.600% wihin average value 0.42% (site-2) and 0.100% to 0.600% within average value 0.23% (site-3), (Table 9).

· Potassium: The potassium (K) concentration of the soil samples were 0.28 to 1.00 meq /100 g soil (at site-1), 0.56 to 1.14 meq/100 g soil (site-2) and 0.55 to 1.10 meq/100 g soil (site-3) within mean values 0.85, 0.81 and 0.57 meq/100 g soil.

Figure 9. Hierarchical cluster of the species at site-3.

Figure 10. Soil samples collected from study sites.

Table 8. Physico-chemical properties of the soil of abandoned land at site-1.

Table 9. Physico-chemical properties of the soil of abandoned land at site-2.

Table 10. Physico-chemical properties of the soil of abandoned land at site-3.

· Phosphorus: The highest concentration (84.7µg/g soil) of phophorus was observed at quadrat no.08 at site-1 within average value of 27.9 µg/g (Table 8). The lowest concentration (2.5 µg/g) of phophorus also observed at quadrat no.05 at site-2 (Table 9) within average value of 20.7 µg/g soil. It was observed that concentration of total phophorus at site-3 were 2.8 to 25.8 µg/g soil with in average value 11.7 µg/g soil (Table 10).

· Moisture: Present study showed that percentage of moisture of all soil samples were 10.2 to 37.45% within average value 11.84% (at site-1), 20.6 to 35.3% within average value 27.6% (site-2) and 12.29 to 17.20% within average value 14.86% (site-3).

3.3. Relationship between Vegetation Spatial Distribution and Environmental Factor

RDA was used to analyze the relationship between the soil factors and abandoned land vegetation distribution in Barishal. Biplot score of the plant species derived from RDA analysis where soil properties were used as environmental variable shown in Figures 11-13 respectively.

3.3.1. Relationship between Vegetation and Soil Factors at Site-1

RDA analysis showed that soil moisture, electric conductivity, potassium,

Note: Ac = Alocasia acuminata, As = Ardisia solanacea, Mm = Mikania micrantha, Fh = Ficus hispida, Sj = Stephania japonica, Ap = Adiantum philippense, Pl = Piper longum, Cv = Clerodendrum viscosum, Co = Chromolaena odorata, Gp = Glycosmis pentaphylla, Fv = Ficus virens, St = Solanum torvum, Sc = Spathodea campanulata, Ps = Polyalthia suberosa, Ct = Calamus tenuis, Ti = Tragia involucrata, Sa = Sida acuta, Ps = Pothos scandens, Fr = Ficus religiosa, Mc = Morinda citrifolia, Ce = Colocasia esculenta, Li = Laportea interrupta, Oc = Oxalis corniculata, Da = Dioscorea alata, Tu = Turnea ulmifolia, Ag = Ageratum conyzoides, Ca = Centella asiatica, Ih = Ipomoea hederifolis, Sv = Solanum violaceum, Lr = Lepisanthes rubiginosa, Pv = Pteris vittata, At = Adiantum tenerum, Cd = Christella dentata, Fb = Ficus benghalensis, As = Alstonia scholaris, Fr = Ficus rumphii, Bf = Borassus flabellifer, Pr = Phyllanthus reticulatus, Cr = Cyperus rotundus, Xv = Xanthosoma violaceum, Ct = Cayratia trifolia, So = Smilax ovalifolia, Mc = Mikania cordata, Ci = Calophyllum inophyllum, Fm= Ficus microcarpa, Ah = Ardisia humilis. (EC = Electric conductivity, K = potassium, P = phosphorus, N = Nitrogen, OM = organic matter).

Figure 11. Biplot scores of plant species derived from the RDA using species abundance data and soil properties at site-1.

organic matter, nitrogen, phosphorus and pH were significantly correlated with species data at site-1 (Figure 11).Ardidisia solanacea,Alocasia acuminata showed significant correlation with soil potassium. The distribution of Laportea interrupta,Ageratum conyzoides,Centella asiatica,Adiantum philippense was mainly affected by soil pH and electric conductivity. The distribution of Mikania micrantha,Ipomoea hederifolia was mainly affected by soil moisture. Pteris vittata,Phyllanthus reticulatus,Xanthosoma violaceum and Calophyllum inophyllum showed significant correlation with soil organic matter, phosphorus and nitrogen.

3.3.2. Relationship between Vegetation and Soil Factors at Site-2

The distribution of Phyllanthus niruri,Cassia fistula,Achyranthes aspera, Mikania micrantha,Clerodendrum viscosum,Alocasia acuminata,Phyllanthus reticulatus,Stachytarpheta jamaicensis andFicus hispida mainly affected with soil electric conductivity, organic matter, nitrogen and potassium (Figure 12).

3.3.3. Relationship between Vegetation and Soil Factors at Site-3

The distribution of Clerodendrum viscosum,Dioscorea alata,Urtica nivea and

Note: Fb = Ficus benghalensis, Fh = Ficus hispida, Aa = Alocasia acuminata, Aca = Achyranthes aspera, Sj = Stachytarpheta jamaicensis, Ot = Operculina turpethum, Bp= Bryophyllum pinnatum, Pr = Phyllanthus reticulatus, Mm = Mikania micrantha, Cb = Commelina benghalensis, Fr = Ficus racemosa, Ap = Aphanamixis polystachya, Gt= Glycosmis triphylla, Cv = Clerodendrum viscosum, Cf = Cassia fistula, Pn= Phyllanthus niruri, Ta = Tiliacora acuminata, Bv = Breynia vitis-idaea, Ul = Urena lobata, Cl = Curcuma longa, Oc = Oxalis corniculata, Xv = Xanthosoma violaceum, Ca = Crinum asiaticum, Cp = Carica papaya, Sf = Syzygium fruticosum, Dm = Diospyros malabarica, Tu = Turnea ulmifolia, Na = Nyctanthes arbor-tristis, Dp = Dioscorea pentaphylla, Ac = Adiantum capillus-veneris, De = Dioscorea esculenta, Pl = Piper longum, As = Ardisia solanacea, Vn = Vitex negundo, Cz = Curcuma zedoaria, Zj = Zehneria japonica, Ui = Urginea indica, Ap = Adiantum philippense, Gp= Glycosmis pentaphylla, Ah = Ardisia humilis, Pap = Paperomia pellucida, Dq = Drynaria quercifolia, Mp = Microsorum punctatum, Ma = Musa acuminata, Ct = Calamus tenuis, Ce= Colocasia esculenta, Sc = Schumannianthus dichotomus, Cm = Citrus maxima. (OM = Organic matter, N = Nitrogen, EC = Electric conductivity, K = potassium).

Figure 12. Biplot scores of plant species derived from the RDA using species abundance data and soil properties at site-2.

Microlepia speluncae was mainly affected by soil organic matter. Synedrella nodifolia,Desmodium gangeticum and Piper longum showed significant correlation with soil electric conductivity. The distribution ofRungia pectinata was mainly affected by soil pH (Figure 13).

4. Discussion

Phytosociology is the branch of science which deals with plant communities, their composition and development, and therefore the relations between species. The structure of a community is set chiefly by the dominant plant species and not by different characteristics [25]. All of these species don’t seem to be equally necessary however there are solely a couple of overtopping species that by their bulk and growth modify the home ground and management the expansion of different species of the community as these species are known as dominants [68]. The current analysis is an attempt to assess composition, structure and diversity of plant species in abandoned land. The research analysis of information revealed

Note: Alr = Albizia richardiana, Urn = Urtica nivea, Dia = Dioscorea alata, Scd = Scoparia dulchis, Oxc = Oxalis corniculata, Pel = Persicaria lapathifolia, Tad = Tabernaemontana divaricata, Syn = Synedrella nodiflora, Glp = Glycosmis pentaphylla, Raa = Raphidophora aurea, Deg = Desmodium gangeticum, Nya = Nyctanthes arbor-tristis, Paf = Passiflora foetida, Rup = Rungia pectinata, Aca = Acacia auriculiformis, Ani = Anisomeles indica, Glt = Glycosmis triphylla, Nec = Nephrolepis cordifolia, Ptv = Pteris vittata, Sic = Sida cordifolia, Als = Alstonia scholaris, Pil = Piper longum, Caz = Capparis zeylanica, Clv = Clerodendrum viscosum, Mis = Microlepia speluncae, Arh = Artocarpus heterophyllus, Soi = Solanum indicum. (EC = Electric conductivity, OM = Organic matter).

Figure 13. Biplot scores of plant species derived from the RDA using species abundance data and soil properties at site-3.

that most herb species were recorded from the study sites.

There were in total thirty families found at the site-1 (Figure 1(a)), family of Moraceae possessed the highest number of species followed by Asteraceae and Araceae.There are also thirty families were also found at site-2 (Figure 1(b)) and family of Verbanaceae possessed highest number of species followed by Moraceae, Euphorbiaceae and 21 families at the site 3 (Figure 1(c)). Family Verbenaceae, Acanthaceae, Apocynaceae, Mimosaceae and Rutaceae possessed highest number of species. Analysis of IVI provides data concerning the status of a species and may be recognized as patterns of association of dominant species during a community [69]. Throughout the present study it had been found that each one of the 3 sites were dominated by Clerodendrum viscosum, Mikania micrantha, Solanum indicum with the utmost IVI value. It’s dominance at the particular sites was probably on account of awareness of optimum conditions for its growth. Higher IVI of a species confers dominance over a vegetation by that species and plants having low IVI are entangled by the dominating ones. However, every species in a plant community has a specific role and there is always a qualitative interrelationship present between the rare and abundant species [70]. Sorenson constant (S) value of the three survey regions was 0.0245 which indicates that there was only about 2.5% similarity present regarding their species composition. Diversity means number of species, their richness, abundance, spatial and temporal variations within an ecosystem. When a large number of plant species occurs in a restricted region with high richness and evenness values, it demonstrated that the vegetation flourishes under favorable environment [71]. In site-1, Moraceae was the most dominant family in terms of species number. This family comprises of about forty genera and well-stablished in the tropical Old World [72] [73].

Evidences from molecular and morphological studies ensure that it is a monophyletic family [74] [75] [76]. The second most dominating plant families were Asteraceae and Araceae. Members of the Asteraceae family comprised of different growth forms that allow them to dominate during the primary stages of plant succession. Usually plants under Araceae family possess a compact covering near the ground level and fashioned like short umbrella with well-defined petioles [77]. Members of the Araceae family were widespread throughout the world during the Cretaceous [78] - [85]. Most of them are still dominant in the tropical regions along with some subtropical and temperate regions’ representatives. Divergent evolution among the enclosed representatives were confirmed by molecular and morphological analyses [86] [87]. Family of family Verbenaceae emerged as dominant species at site-3. This may be as a results of Verbenaceae that includes the following ingredients: 1) spreading of seeds for long distances by several native and introduced birds; 2) toxicity of its fruit for several mammals, that limits damage by herbivore; 3) its ability to sprout smartly following harm (e.g., by trampling); 4) its ability to invade a wide range of habitats; 5) production of allopathic substances, that improves its competitive ability; and 6) its ability to flower copiously for long periods, therefore attracting pollinators and making certain copious seed set.

The quantitative relationship between abundance and frequency (A/F) indicated the contiguous distribution of plant species rather than regular distribution. Perhaps, contiguous distribution pattern is a notable characteristic of natural ecosystems [25] [70] [88] - [93]. Species richness generally will increase throughout secondary succession once environmental and edaphic conditions area unit favorable with low fluctuations [89]. Uniform environment usually supports regular distribution pattern of species while contiguous distribution pattern occurs in a place where a severe competition for resources exists. Though in such competition, plant species prefer vegetative reproduction over sexuality, they can’t solely depend on vegetative multiplication as there are multiple factors present regarding new generation establishment [91].

Patterns of distribution rely both on physico-chemical nature of the environment and the biological peculiarities of the organisms [25]. The study site shows that more shrubs (38.93%), climber (16.10%) available at site 1. A lot of herbs (60.5%) were found at site 2. A low density of woody species has been shown to improve soil nutrient status and thus develop grass-growing conditions [94] [95].

Diversity indexes provide valuable information regarding the composition and quality of vegetation in a study area and thus ultimately help us to understand the community structure of a natural ecosystem. The values of Shannon-Wieners diversity index of the three sites were 3.47, 3.20 and 2.45 respectively which indicates that these are relatively diversity rich area as the values laid between 1.5 to 3.5 range [79]. The values of Simpson’s diversity index were also found extremely high as 0.99, 0.99 and 0.96 respectively (Figure 3) which means if we take two plant samples randomly from two different quadrats, there are at least 96% chance that the samples we choose are two different species [80]. The Margalef’s Richness Index (7.43, 7.82, 5.62) and Menhinick’s Richness Index (2.23, 2.38, 2.53) of the three study sites (Figure 3) reflect their high species richness. The Pielou’s Evenness Index values were 0.26, 0.83 and 0.88 respectively for the study sites (Figure 3) which indicate that the continuity of vegetation varies significantly from one place to another. However, all these values were considerably higher than that obtained from different studies on the natural forests of Bangladesh [96] - [101]. One of the probable reasons behind this phenomenon is that, natural forests are well-stablished ecosystem sustaining over a long time while vegetations of abandoned mansions are comparatively recent establishments via secondary succession of plant species. Thus, there are a large number of competitor species gather to run a struggle for existence and ensure survival of the fittest on that territory. There is a part of society which gives positive response to conserve abandoned lands, which assists these locations to achieve aesthetic look [102] [103] [104].

Natural forest conservation requires authentic and consistent information on species composition and diversity pattern. Multivariate statistical methods including clustering of species are well developed in vegetation ecology [105] [106] [107]. Hierarchical cluster of the species based on dominance of the species shown Solanum indicum, Tabernaemontana divaricata, Albizia richardiana, Mikania micrantha, Cassia fistula, Clerodendrum viscosum were most dominant. All these species are of natural origin. Plant species found in this study are of natural origin, which indicates the importance of indigenous plant species conservation in abandoned land ecosystem.

The pH of all soil samples was found to be ranged in between 7.4 to 8.1 (site -1), 7.1 to 7.7 (site-2), 7.2 to 7.6 (site-3) with the average value of 7.8, 7.43, 7.44 respectively which indicates slightly alkaline soil. In most cases, pH range of 6.0-7.5 is optimum for the adequate availability of nutrients in the soil [108]. Values of EC ranged largely between the lowest one 0.59 and the highest 2.04 dS/m at site-1, 0.60 to 2.23 dS/m at site-2 and 0.88 to 2.20 dS/m site-3 within mean values 1.0, 1.34, 1.40 dS/m. Soil EC values range from 0-2 dS/m indicates non saline soil [109]. Percentage of organic matter of all soil samples in mean values 3.05% (site-1), 8.40% (site-2) and 9.78% (site-3), respectively. High (>3.4%) soil organic matter status indicates suitable for crop production [108]. It was observed that percentage of total nitrogen of the soil samples within average values 0.15% (site-1), 0.42% (site-2) and 0.23% (site-3). It indicates that all nitrogen status were nearly to optimum (0.271% to 0.36%) level. Mean Phosphorus status were 27.9 µg/g (site-1), 20.7 µg/g (site-2), and 11.7 µg/g (site-3) respectively. All the P status except site-1 indicates were lower than optimum (22.51 to 18.1 µg/g soil) level. Potassium status within mean values 0.85, 0.81 and 0.57 meq/100g soil at site-1, site-2 and site-3 respectively. Mean K status indicates were higher than the optimum level [108].

The relationship of vegetation to environmental soil factors assessed using RDA ordinations. The variability of physical and chemical soil properties across sites indicates that abandoned terrestrial vegetation is not uniform in the vicinity. The soils associated with vegetation constitute the most remarkable resources in the ecosystem. Quantification of variation in species diversity and community composition as a function of their location resulted in inferring effective mechanisms for assembling plant communities [110] [111] [112]. Similar results were observed in lowlands, temperate forests, dry prairies, beech forests and natural forests [113] [114]. We also found that the most factors touching vegetation distribution were soil organic matter, conductivity, pH, total N, phosphorus and moisture provides nutrients to plant ensures plant production and development and plays a very important role within the property development of the land. Soil pH has a prominent role in determining physical properties and fertility of soil, which have direct effect on plant growth [115]. Soil pH determines the productivity of soil and separation of the plant clusters growth [116]. Direct effects of the soil pH can be confirmed via plant forms, nutrient metabolism, growth, quality and quantity of yield, while indirect effects can be observed by the impact of physical, chemical and biological properties of soil on vegetation development [117] [118]. Phosphorus has a key role in plant nutrition and hence the concentration and availability of P is responsible for the fertility and productivity of soil to a great extent as P is needed by plants in a comparatively large amount.

Phosphorus with the distribution of plant species in northeast America while it was the most common problem in plant communities in Brazil [119] [120]. The nutrients generally contend a serious role within the classification of plant cluster. Phosphorus within the soil will be absorbed by the plant component; several different studies have noted the role of available phosphorus within the distribution pattern of plant communities [121] [122]. In soil-vegetation systems, soil and vegetation are interacted to one another. Soil affects vegetation and restricts soil [123] [124]. The results not only showed that the soil factors contend a very important role within the vegetation community succession method, but also additionally discovered that the vegetation community contends a very important role in soil restoration and reconstruction. Spatial distribution and aggregation of plant communities were affected by their dynamic state and spatial heterogeneity to a great extent during this process [125] [126]. We mainly focused on the interaction between the distribution pattern of plant communities and the physico-chemical properties of soil with some relatively remarkable effects of this interaction on population dynamics.

5. Conclusion & Recommendation

This study gives us insight into the floral richness hiddened inside the abandoned mansions that have never been explored before. If these vegetations are kept outside from human exploitation for a longer time, their soil will get more chances to be fortified with organic matter and will flourish with more plant species over time. By implementing the knowledge of soil-plant interaction discovered in the present study, in-situ conservation can be improvised to save a large amount of germplasm within a limited area. Moreover, these sites can be studied as a model ecosystem because of secondary succession of plant species in human intervened regions. Data obtained from this survey can also be utilized efficiently to develop new technologies regarding ex-situ conservation of plant species in botanical gardens to cope up with other modern conservation strategies.

Author Contributions Statement

M.M.H. collected data and performed statistical analysis; M.A.R.L. identified species and analysis; T.S. contributed substantially to revisions and supervised; S.K.D provided resources and supervised; M.T.I. collected data, analysis, processed the raw data and wrote the manuscript.

NOTES

1Bangladesh Meteorological Department.

2Bangladesh Meteorological Department.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References

[1] Grove, A.O. and Rackham, O. (2000) The Nature of Mediterranean Europe: An Ecological History. Yale University Press, New Haven.
[2] Roberts, N. (2014) The Holocene: An Environmental History. 3rd Edition, Wiley-Blackwell, Hoboken, 376.
[3] MacDonald, D., et al. (2000) Agricultural Abandonment in Mountain Areas of Europe: Environmental Consequences and Policy Response. Journal of Environmental Management, 59, 47-69.
https://doi.org/10.1006/jema.1999.0335
[4] Serra, P., Pons, X. and Sauri, D. (2008) Land-Cover and Land-Use Change in a Mediterranean Landscape: A Spatial Analysis of Driving Forces Integrating Biophysical and Human Factors. Applied Geography, 28, 189-209.
https://doi.org/10.1016/j.apgeog.2008.02.001
[5] García-Ruiz, J.M., et al. (2008) Flood Generation and Sediment Transport in Experimental Catchments along a Plant Cover Gradient in the Central Pyrenees. Journal of Hydrology, 356, 245-260.
https://doi.org/10.1016/j.jhydrol.2008.04.013
[6] Rounsevell, M.D.A., et al. (2006) A Coherent Set of Future Land Use Change Scenarios for Europe. Agriculture, Ecosystem and Environment, 114, 57-68.
https://doi.org/10.1016/j.agee.2005.11.027
[7] Nowicki, P.L., et al. (2007) Scenar 2020: Scenario Study on Agriculture and the Rural World.
[8] Pointereau, P., et al. (2008) Analysis of Farmland Abandonment and the Extent and Location of Agricultural Areas That Are Actually Abandoned or Are in Risk to Be Abandoned. JRC Scientific and Technical Reports.
[9] Cramer, V.A., Hobbs, R.J. and Standish, R.J. (2008) What’s New about Old Fields? Land Abandonment and Ecosystem Assembly. Trends in Ecology and Evolution, 23, 104-112.
https://doi.org/10.1016/j.tree.2007.10.005
[10] Queiroz, C., Beilin, R., Folke, C. and Lindborg, R. (2014) Farm Land Abandonment: Threat or Opportunity for Biodiversity Conservation? A Global Review. Frontiers in Ecology and the Environment, 12, 288-296.
https://doi.org/10.1890/120348
[11] Cerdà, A., et al. (2018) Long-Term Impact of Rainfed Agricultural Land Abandonment on Soil Erosion in the Western Mediterranean Basin. Progress in Physical Geography, 42, 202-219.
https://doi.org/10.1177/0309133318758521
[12] Csecserits, A., et al. (2011) Regeneration of Sandy Old-Fields in the Forest Steppe Region of Hungary. Plant Biosystematics, 145, 715-729.
https://doi.org/10.1080/11263504.2011.601340
[13] Rahman, M.H., Khan, M., Roy, B. and Fardusi, M.J. (2011) Assesment of Natural Regeneration Status Anddiversity of Tree Species in the Biodiversity Conservation Areas of Northeastern Bangladesh. Journal of Forestry Research, 22, 551-559.
https://doi.org/10.1007/s11676-011-0198-0
[14] Giavelli, G., Rossi, O. and Sartore, F. (1986) Comparative Evaluation of Four Species Diversity Indices Related to 10 Specific Ecological Situations. FSC, 6, 429-438.
[15] M Nath, T.K., Hossain, M.K. and Alam, M.K. (2000) Assessment of Tree Species Diversity of Sitapahar Forest Reserve, Chittagong Hill Tracts (South) Forest Division, Bangladesh. Indian Forestry, 126, 16-21.
[16] Benning, T.L. and Seastedt, T.R. (1995) Landscape-Level Interactions between Topoedaphic Features and Nitrogen Limitation in Tallgrass Prairie. Landscape Ecology, 10, 337-348.
https://doi.org/10.1007/BF00130211
[17] Juan, J.G., Carlos, R.L. and Donaldo, E.B. (2011) Vegetation Composition and Its Relationship with the Environment in Mallines of North Patagonia, Argentina. Wetland Ecology Management, 19, 121-130.
https://doi.org/10.1007/s11273-010-9205-z
[18] Mellado, A. and Zamora, R. (2015) Spatial Heterogeneity of a Parasitic Plant Drives the Seed-Dispersal Pattern of a Zoochorous Plant Community in a Generalist Dispersal System. Functional Ecology, 30, 459-467.
https://doi.org/10.1111/1365-2435.12524
[19] Liu, Q.S., Liu, G.H., Huang, C., Yao, Z.J. and Huang, H.Q. (2016) Spatial Distribution of Vegetation and Soil Properties on the Ulan Bator-Fengzhen Transect on the Mongolian Plateau. Resources Science, 38, 982-993.
[20] Lucie, H., Jana, K. and Zuzana, M. (2016) Assessment of Habitat Suitability Is Affected by Plant-Soil Feedback: Comparison of Field and Garden Experiment. PLoS ONE, 11, e0157800.
https://doi.org/10.1371/journal.pone.0157800
[21] Egler, F.E. (1954) Vegetation Science Concepts I. Initial Floristic Composition. A Factor in Old-Field Vegetation Development. Vegetation, 4, 412-417.
https://doi.org/10.1007/BF00275587
[22] De Deyn, G.B. and van der Putten, W.H. (2005) Linking Aboveground and Belowground Diversity. Trends in Ecology and Evolution, 20, 625-633.
https://doi.org/10.1016/j.tree.2005.08.009
[23] Gairola, S., Sharma, C.M., Suyal, S. and Ghildiyal, S.K. (2011) Composition and Diversity of Five Major Forest Types in Moist Temperate Climate of the Western Himalayas. Forestry Studies in China, 13, 139-153.
https://doi.org/10.1007/s11632-011-0207-6
[24] Khoshoo, T.N. (1992) Plant Diversity in the Himalaya: Conservation and Utilization. Govind Ballabh Pant Institute of Himalayan Environment and Development, Almora.
[25] Odum, E.P. (1971) Fundamentals of Ecology. 3rd Edition, Saunders, Philadelphia.
[26] Mifflin, H. (1992) American Heritage Dictionary of English Language. 3rd Edition.
[27] Braun-Blanquet, J. (1932) Plant Sociology. McGraw-Hill, London.
[28] Katsuno, T. (1977) Phytosociological Studies on the Roadside Vegetation, Part 1. Bulletin of the College of Agriculture and Veterinary Medicine Nihon University, 34, 311-343.
[29] Hobbs, R.J. and Cramer, V.A. (2007) Why Old Fields? Socioeconomic and Ecological Causes and Consequences of Land Abandonment. In: Cramer, V.A. and Hobbs, R.J., Eds., Old Fields, Dynamics and Restoration of Abandoned Farmland, Society for Ecological Restoration International, Island Press, Washington DC, 334.
[30] MEA: Millennium Ecosystem Assessment (2005) Ecosystems and Human Well-Being. Island Press, Washington DC.
[31] Cayuela, L., Rey-Benayas, J.M. and Echeverría, C. (2006) Clearance and Fragmentation of Tropical Montane Forests in the Highlands of Chiapas, México (1975-2000). Forest Ecology Management, 226, 208-218.
https://doi.org/10.1016/j.foreco.2006.01.047
[32] Schroter, D., et al. (2005) Ecosystem Service Supply and Vulnerability to Global Change in Europe. Science, 310, 1333-1337.
https://doi.org/10.1126/science.1115233
[33] Sickel, H., Ihse, M., Norderhang, A. and Sickel, M.A.K. (2003) How to Monitor Semi-Natural Key Habitats in Relation to Grazing Preferences of Cattle in Mountain Summer Farming Areas. An Aerial Photo and GPS Method Study. Landscape Urban Plan, 67, 67-77.
https://doi.org/10.1016/S0169-2046(03)00029-X
[34] Suárez-Seoane, S., Osborne, P.E. and Baudry, J. (2002) Responses of Birds of Different Biogeographic Origins and Habitat Requirements to Agricultural Land Abandonment in Northern Spain. Biological Conservation, 105, 333-344.
https://doi.org/10.1016/S0006-3207(01)00213-0
[35] Suárez-Seoane, S., Osborne, P.E. and Baudry, J. (2005) Wilderness: What It Means When It Becomes a Reality—A Case Study from the Southwestern Alps. Landscape Urban Plan, 70, 85-95.
https://doi.org/10.1016/j.landurbplan.2003.10.006
[36] Zaravali, M.P., Yakoulaki, M.D. and Papansatasis, V.P. (2007) Effects of Shrub Encroachment on Herbage Production and Nutritive Value in Semi-Arid Mediterranean Grasslands. Grass and Forage Science, 62, 355-363.
https://doi.org/10.1111/j.1365-2494.2007.00590.x
[37] Cosandey, C., et al. (2005) The Hydrological Impact of the Mediterranean Forest: A Review of French Research. Journal of Hydrology, 301, 235-249.
https://doi.org/10.1016/j.jhydrol.2004.06.040
[38] Nadal-Romero, E., Lasanta, T. and García-Ruiz, J.M. (2013) Runoff and Sediment Yield from Land under Various Uses in a Mediterranean Mountain Area. Long-Term Results from an Experimental Station. Earth Surface Processes and Landforms, 38, 346-355.
https://doi.org/10.1002/esp.3281
[39] López-Moreno, J.I., García-Ruiz, J.M. and Beniston, M. (2008) Environmental Change and Water Management in the Pyrenees. Facts and Future Perspectives for Mediterranean Mountains. Global Planet Change, 66, 300-312.
https://doi.org/10.1016/j.gloplacha.2007.10.004
[40] López-Moreno, J.I. (2011) Impact of Climate Evolution and Land Use Changes on Water Yield in the Ebro Basin. Hydrology and Earth System Sciences, 15, 311-322.
https://doi.org/10.5194/hess-15-311-2011
[41] Hyland, B.P.M. (1972) A Technique for Collecting Botanical Specimens in Rain Forest. Flora Malesiana Bulletin, 26, 2038-2040.
[42] Alexiades, M.N. (1996) Selected Guidelines for Ethno Botanical Research: A Field Manual. The New York Botanical Garden, New York, 1-306.
[43] Hooker, J.D. (1872-1897) Flora of British India, Vol. 1-7. First Indian Reprint (1973). Bishen Singh Mahendra Pal Singh, Dehra Dun.
[44] Prain, D. (1903) Bengal Plants, Vol. 1-2. First Indian Reprint (1963), Bishen Singh, Mahendra Pal Singh, Dehra Dun.
[45] Siddiqui, K.U., et al. (2007) Encyclopedia of Flora and Fauna of Bangladesh, Vol. 11. Angiosperms: Monocotyledons (Agavaceae-Najadaceae). Asiatic Society of Bangladesh, Dhaka, 1-399.
[46] Ahmed, Z.U., et al. (2008) Encyclopedia of Flora and Fauna of Bangladesh, Vol. 6. Angiosperms: Dicotyledons (Acanthaceae-Asteraceae). Asiatic Society of Bangladesh, Dhaka, 1-408.
[47] Ahmed, Z.U., et al. (2008) Encyclopedia of Flora and Fauna of Bangladesh, Vol. 12. Angiosperms: Monocotyledons (Orchidaceae-Zingiberaceae). Asiatic Society of Bangladesh, Dhaka, 1-552.
[48] Ahmed, Z.U., et al. (2009) Encyclopedia of Flora and Fauna of Bangladesh, Vol. 7. Angiosperms: Dicotyledons (Balsaminaceae-Euphorbiaceae). Asiatic Society of Bangladesh, Dhaka, 1-546.
[49] Ahmed, Z.U., et al. (2009) Encyclopedia of Flora and Fauna of Bangladesh, Vol. 8. Angiosperms: Dicotyledons (Fabaceae-Lythraceae). Asiatic Society of Bangladesh, Dhaka, 1-478.
[50] Ahmed, Z.U., et al. (2009) Encyclopedia of Flora and Fauna of Bangladesh, Vol. 9. Angiosperms: Dicotyledons (Magnoliaceae-Punicaceae). Asiatic Society of Bangladesh, Dhaka, 1-488.
[51] Ahmed, Z.U., et al. (2009) Encyclopedia of Flora and Fauna of Bangladesh, Vol. 10. Angiosperms: Dicotyledons (Ranunculaceae-Zygophyllaceae). Asiatic Society of Bangladesh, Dhaka, 1-580.
[52] Hammer, O., Harper, D.A.T. and Ryan, P.D. (2001) PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica, 4, 9.
[53] Moore, P.D. and Chapman, S.B. (1986) Methods in Plant Ecology. Blackwell Scientific Publication, Hoboken, 550.
[54] Shukla, R.S. and Chandel, P.S. (1980) Plant Ecology. S. Chand and Company Ltd., New Delhi, 197.
[55] Dallmeier, F., Kabel, M. and Rice, R. (1992) Methods for Long Term Biodiversity Inventory Plots in Protected Tropical Forests. In: Dallmeier, F., Ed., Long-Term Monitoring of Biological Diversity in Tropical Forest Areas: Methods for Establishment and Inventory of Permanent Plots, UNESCO, Paris, 14-16.
[56] Thakur, N.S., Gupta, N.K. and Gupta, B. (2008) Volume and Biomass Prediction Mio Dels for 4 C4 CL4 C4 Tech U Willid. In Agro Forestry Systemis of North West Himalaya. Journal of Non-Timber Froest Products, 15, 1-9.
[57] Petchey, O.L. and Gaston, K.J. (2006) Functional Diversity: Back to Basics and Looking Forward. Ecology Letters, 9, 741-758.
https://doi.org/10.1111/j.1461-0248.2006.00924.x
[58] Colin, P. (2018) Biogeographic Region. In: Encyclopedia Britannica.
[59] Margalef, D.R. (1958) Information Theory in Ecology. General Systems, 3, 36-71.
[60] Pielou, E.C. (1984) The Interpretation of Ecological Data: A Primer on Classification and Ordination. John Wiley and Sons, Hoboken.
[61] Shannon, C.E. and Weiner, W. (1963) The Mathematical Theory of Communication. Urban University, Illinois Press, Champaign, 125.
[62] Simpson, E.H. (1949) Measurement of Diversity. Nature, 163, 688.
https://doi.org/10.1038/163688a0
[63] Sørensen, T. (1957) A Method of Establishing Groups of Equal Amplitude in Plant Sociology Based on Similarity of Species and Its Application to Analyses of the Vegetation on Danish Commons. Biologiske Skrifter, 5, 1-34.
[64] Kjeldahl, J.Z. (1883) A New Method for the Determination of Nitrogen in Organic Matter. Zeitschrift für Analytische Chemie, 22, 366-382.
https://doi.org/10.1007/BF01338151
[65] Walkley, A. and Black, I.A. (1934) An Examination of the Degtjareff Method for Determining Soil Organic Matter and a Proposed Modification of the Chromic Acid Titration Method. Soil Science, 37, 29-38.
https://doi.org/10.1097/00010694-193401000-00003
[66] Olsen, S.R. and Sommers, L.E. (1982) Phosphorus. In: Page, A.L., et al., Eds., Methods of Soil Analysis: Part 2. Chemical and Microbiological Properties, Agronomy Monographs 9, 2nd Edition, ASA and SSSA, Madison, 403-430.
https://doi.org/10.2134/agronmonogr9.2.2ed.c24
[67] Rural Development (2005) Service Technical Advice Note, Defra, 31.
[68] Gatson, K.J. (2000) Global Patterns in Biodiversity. Nature, 405, 220-227.
https://doi.org/10.1038/35012228
[69] Parthasarathy, N. and Karthikeyan, R. (1997) Biodiversity and Population Density of Woody Species in a Tropical Evergreen Forest in Courtallum Reserve Forest, Western Ghats, India. Tropical Ecology, 38, 297-306.
[70] Bhandari, B.S., Nautiyal, D.C. and Gaur, R.D. (1999) Structural Attributes and Productivity Potential of an Alpine Pasture of Garhwal Himalaya. Journal of Indian Botanical Society, 78, 321-329.
[71] Kharkwal, G. and Rawat, Y.S. (2010) Structure and Composition of Vegetation in Subtropical Forest of Kumaun Himalaya. African Journal of Plant Science, 4, 116-121.
[72] Zhang, Q., Onstein, R.E., Little, S.A. and Sauquet, H. (2018) Estimating Divergence Times and Ancestral Breeding Systems in Ficus and Moraceae. Annals of Botany, 123, 191-204.
https://doi.org/10.1093/aob/mcy159
[73] Zerega, N.J.C., Nur Supardi, M.N. and Motley, T.J. (2010) Phylogeny and Recircumscription of Artocarpeae (Moraceae) with a Focus on Artocarpus. Systematic Botany, 35, 766-782.
https://doi.org/10.1600/036364410X539853
[74] Datwyler, S.L. and Weiblen, G.D. (2004) On the Origin of the Fig: Phylogenetic Relationships of Moraceae from ndhF Sequences. American Journal of Botany, 91, 767-777.
https://doi.org/10.3732/ajb.91.5.767
[75] Zerega, N.J.C., Clement, W.L., Datwyler, S.L. and Weiblen, G.D. (2005) Biogeography and Divergence Times in the Mulberry Family (Moraceae). Molecular Phylogenetics and Evolution, 37, 402-416.
https://doi.org/10.1016/j.ympev.2005.07.004
[76] Clement, W.L. and Weiblen, G.D. (2009) Morphological Evolution in the Mulberry Family (Moraceae). Systematic Botany, 34, 530-552.
https://doi.org/10.1600/036364409789271155
[77] Mehrotra, P. (1988) Adaptive Significance of Leaf in Relation to Other Parts in Oak Forest Herbs of Kumaun Himalaya. Ph.D. Thesis, Kumaun University, Nainital.
[78] Stockey, R.A., Rothwell, G.W. and Johnson, K.R. (2007) Cobbania corrugata gen. et comb. nov. (Araceae): A Floating Aquatic Monocot from the Upper Cretaceous of Western North America. American Journal of Botany, 94, 609-624.
https://doi.org/10.3732/ajb.94.4.609
[79] Friis, E.M., Pedersen, K.R. and Crane, P.R. (2004) Araceae from the Early Cretaceous of Portugal: Evidence on the Emergence of Monocotyledons. PNAS USA, 101, 16565-16570.
https://doi.org/10.1073/pnas.0407174101
[80] Friis, E.M., Pedersen, K.R. and Crane, P.R. (2006) Cretaceous Angiosperm Flowers: Innovation and Evolution in Plant Reproduction. Palaeogeography, Palaeoclimatology and Palaeoecology, 232, 251-293.
https://doi.org/10.1016/j.palaeo.2005.07.006
[81] Friis, E.M., Pedersen, K.R. and Crane, P.R. (2010) Diversity in Obscurity: Fossil Flowers and the Early History of Angiosperms. Philosophical Transactions of the Royal Society B: Biological Sciences, 365, 369-373.
https://doi.org/10.1098/rstb.2009.0227
[82] Bogner, J., Hoffman, G.L. and Aulenback, K.R. (2002) A Fossilized Aroid Infructescence, Albertarumpueri gen. nov. et sp. nov. of Late Cretaceous (Late Campanian) Age from the Horseshoe Canyon Formation of Southern Alberta, Canada. Canadian Journal of Botany, 83, 591-598.
https://doi.org/10.1139/b05-033
[83] Bogner, J., Johnson, K.R., Kvacek, Z. and Upchurch, G.R. (2007) New Fossil Leaves of Araceae from the Late Cretaceous and Paleogene of Western North America. Zitteliana, 47, 133-147.
[84] Wilde, V., Kvaček, Z. and Bogner, J. (2005) Fossil Leaves of the Araceae from the European Eocene and Notes on Other Aroid Fossils. International Journal of Plant Sciences, 166, 157-183.
https://doi.org/10.1086/425673
[85] Herrera, F.A., Jaramillo, C.A., Dilcher, D.L., Wing, S.L. and Gómez, N.C. (2008) Fossil Araceae from a Paleocene Neotropical Rainforest in Colombia. American Journal of Botany, 95, 1569-1583.
https://doi.org/10.3732/ajb.0800172
[86] Cabrera, L.I., Salazar, G.A., Chase, M.W., Mayo, S.J., Bogner, J. and Davila, P. (2008) Phylogenetic Relationships of Aroids and Duckweeds (Araceae) Inferred from Coding and Noncoding Plastid DNA. American Journal of Botany, 95, 1153-1165.
https://doi.org/10.3732/ajb.0800073
[87] Cusimano, N. (2011) Relationships within the Araceae: Comparisons of Morphological Patterns with Molecular Phylogenies. American Journal of Botany, 98, 654-668.
https://doi.org/10.3732/ajb.1000158
[88] Joshi, N.K. and Tiwar, S.C. (1990) Phytosociological Analysis of Woody Vegetation along an Altitudinal Gradient in Garhwal. Indian Journal of Forestry, 13, 322-328.
[89] Bhandari, B.S. (1995) Vegetation Structure under Different Management Regimes in a Grazing Land at Srinagar Garhwal. Journal of Hill Research, 8, 39-46.
[90] Pande, P.K. (1996) Plant Species Diversity and Vegetation Analysis in Moist Temperate Himalayan Forests. Abstracts of First Indian Ecological Congress, New Delhi, 51.
[91] Kershaw, K.A. (1973) Quantitative and Dynamic Plant-Ecology. 3rd Edition, ELBS and Edward Arnold Ltd., London.
[92] Singh, J.S. and Yadava, P.S. (1974) Seasonal Variation in Composition, Plant Biomass and Net Primary Productivity of a Tropical Grassland at Kurukshetra, India. Ecology Monograph, 44, 351-375.
https://doi.org/10.2307/2937034
[93] Kunhikannan, C., Verma, R.K., Verma, R.J., Khatri, P.K. and Totey, N.G. (1998) Ground Flora, Soil Micro-Flora and Fauna Diversity under Plantation Ecosystem on Bhata Land of Bilaspur, Madhya Radesh. Environment and Ecology, 16, 539-548.
[94] Belsky, A.J., et al. (1989) The Effects of Trees on Their Physical, Chemical, and Biological Environment in a Semi-Arid Savanna in Kenya. Journal of Applied Ecology, 26, 1005-1024.
https://doi.org/10.2307/2403708
[95] Treydte, A.C., Looringh van Beeck, F., Ludwig, F. and Heitkönig, L.M.A. (2008) Improved Beneath-Crown Grass Quality in South African Savannas Varying Locally and Over Seasons. Journal of Vegetation Science, 19, 663-670.
https://doi.org/10.3170/2008-8-18435
[96] Hossain, M.A., Hossain, M.K., Salam, M.A. and Rahman, S. (2013) Composition and Diversity of Tree Species in Dudh Pukur-Do Pachori Wildlife Sanctuary of Chittagong (South) Forest Division, Bangladesh. Research Journal of Pharmaceutical, Biological and Chemical Sciences, 4, 1447-1457.
[97] Hossain, M.A., Hossain, M.K., Alam, M.S. and Uddin, M.M. (2015) Composition and Diversity of Tree Species in Kamalachari Natural Forest of Chittagong South Forest Division, Bangladesh. Journal of Forestry and Environmental Sciences, 31, 192-201.
https://doi.org/10.7747/JFES.2015.31.3.192
[98] Nath, T.K., Jashimuddin, M. and Inoue, M. (2016) Community-Based Forest Management (CBFM) in Bangladesh. Springer, Berlin.
https://doi.org/10.1007/978-3-319-42387-6
[99] Nath, T.K., et al. (2016) Phytosociological Characteristics and Diversity of Trees in a Comanaged Protected Area of Bangladesh: Implications for Conservation. Journal of Sustainable Forestry, 35, 562-577.
https://doi.org/10.1080/10549811.2016.1231615
[100] Rahman, M.M., Mahmud, M.A.A. and Ahmed, F.U. (2017) Restoration of Degraded Forest Ecosystem through Non-Forestry Livelihood Supports: Experience from the Chunati Wildlife Sanctuary in Bangladesh. Forest Science and Technology, 13, 109-115.
https://doi.org/10.1080/21580103.2017.1349003
[101] Rahman, M.M., Mahmud, M.A.A., Shahidullah, M., Nath, T.K. and Jashimuddin, M. (2016) The Competitiveness of the Phytosociological Attributes of the Protected Areas in Bangladesh with That in the Other Tropical Countries. Journal of Sustainable Forestry, 35, 431-450.
https://doi.org/10.1080/10549811.2016.1202841
[102] Rogge, E., Nevens, F. and Gulinck, H. (2007) Perception of Rural Landscapes in Flanders: Looking beyond Aesthetics. Landscape Urban Plan, 82, 159-174.
https://doi.org/10.1016/j.landurbplan.2007.02.006
[103] Nijnik, M. and Mather, A. (2008) Analyzing Public Preferences Concerning Woodland Development in Rural Landscapes in Scotland. Landscape Urban Plan, 86, 267-275.
https://doi.org/10.1016/j.landurbplan.2008.03.007
[104] Nassauer (2011) Care and Stewardship: From Home to Planet. Landscape Urban Plan, 100, 321-323.
https://doi.org/10.1016/j.landurbplan.2011.02.022
[105] Legendre, P. and Legendre, L. (2012) Developments in Environmental Modeling. In: Numerical Ecology, 3rd Edition, Elsevier, Amsterdam.
[106] Borcard, D., Gillet, F. and Legendre, P. (2011) Numerical Ecology with R Media. Springer, Berlin.
https://doi.org/10.1007/978-1-4419-7976-6
[107] Wildi, O. (2013) Data Analysis in Vegetation Ecology. 2nd Edition, Wiley-Black-well, Hoboken.
https://doi.org/10.1002/9781118562543
[108] BARC-Bangladesh Agricultural Research Council (2018) Fertilizer Recommendation Guide. Bangladesh Agricultural Research Council (BARC), Farmgate, Dhaka.
[109] SRDI-Soil Resources Development Institute (2010) Saline Soils of Bangladesh. SRMAF Project, Ministry of Agriculture, Dhaka.
[110] Kadowaki, K., Sato, H., Yamamoto, S., Tanabe, A.S., Hidaka, A. and Toju, H. (2014) Detection of the Horizontal Spatial Structure of Soil Fungal Communities in a Natural Forest. Popular Ecology, 56, 301-310.
https://doi.org/10.1007/s10144-013-0424-z
[111] Reid, M.A., Reid, M.C. and Thoms, M.C. (2016) Ecological Significance of Hydrological Connectivity for Wetland Plant Communities on a Dryland Floodplain River, MacIntyre River, Australia. Aquatic Sciences, 78, 139-158.
https://doi.org/10.1007/s00027-015-0414-7
[112] Yamaji, Y., Honda, H., Hanai, R. and Inoue, J. (2016) Soil and Environmental Factors Affecting the Efficacy of 1 in Wetland Pyroxasulfone for Weed Control. Journal of Pesticide Science, 41, 1-5.
https://doi.org/10.1584/jpestics.D15-047
[113] Peres-Neto, P.R., Legendre, P., Dray, S. and Borcard, D. (2006) Variation Partitioning of Species Data Matrices: Estimation and Comparison of Fractions. Ecology, 87, 2614-2625.
https://doi.org/10.1890/0012-9658(2006)87[2614:VPOSDM]2.0.CO;2
[114] Dwirek, A., Kauffman, J.B. and Baham, J.E. (2006) Plant Species Distribution in Relation to Water-Table Depth and Soil Redox Potential in Montane Riparian Situ St Meadows. Wetlands, 26, 131-146.
https://doi.org/10.1672/0277-5212(2006)26[131:PSDIRT]2.0.CO;2
[115] Jager, N.R.D., Rohweder, J.J., Yao, Y. and Hoy, E. (2015) The Upper Mississippi River Floodscape: Spatial Patterns of Flood Inundation and Associated Plant Community Distributions. Applied Vegetation Sciences, 19, 164-172.
https://doi.org/10.1111/avsc.12189
[116] Dong, L., Xu, L.G., Xu, J.X., Xu, J., Wang, X.L. and Zhang, Q. (2014) Effects of Soil Environmental Factors on Vegetation Distribution in Shoaly Wetlands Typical to Poyang Lake. Acta Pedol Sin, 51, 618-626.
[117] Kashian, D.M., Barnes, B.V. and Walker, W.S. (2003) Ecological Species Groups of Landform-Level Ecosystems Dominated by Jack Pine in Northern Lower Michigan, USA. Plant Ecology, 166, 75-91.
https://doi.org/10.1023/A:1023265012964
[118] Rola, K., Osyczka, P. and Nobis, M. (2015) How Do Soil Factors Sp Determine Vegetation Structure and Species Richness in Post-Smelting Dumps? Ecological Engineering, 75, 332-342.
https://doi.org/10.1016/j.ecoleng.2014.11.026
[119] Bigelow, S.W. and Canham, C.D. (2002) Community Organization of Tree Species along Soil Gradients in a North-Eastern USA Forest. Journal of Ecology, 90, 188-200.
https://doi.org/10.1046/j.0022-0477.2001.00655.x
[120] Amorim, P.K. and Batalha, M.A. (2007) Soil-Vegetation Relationships in Hyperseasonal Cerrado, Seasonal Cerrado, and Wet Grassland in Emas National Park (Central Brazil). Acta Oecologia, 32, 319-327.
https://doi.org/10.1016/j.actao.2007.06.003
[121] Hammersmark, C.T., Rains, M.C., Wickland, A.C. and Mount, J.F. (2009) Vegetation and Water Table Relationships in a Hydrologically Restored Riparian Meadow. Wetlands, 29, 785-797.
https://doi.org/10.1672/08-15.1
[122] Onur, S. and Suha, B. (2016) Crop Yield Prediction under Soil Salinity Using Satellite Derived Vegetation Indices. Field Crops Research, 192, 134-143.
https://doi.org/10.1016/j.fcr.2016.04.028
[123] Sarah, P., Zhevelev, H.M. and Atar, O.Z. (2015) Urban Park Soil and Vegetation: Effects of Natural and Anthropogenic Factors. Pedosphere, 25, 392-404.
https://doi.org/10.1016/S1002-0160(15)30007-2
[124] Zielke, M., Solheim, B., Spjelkavik, S. and Olsen, R.A. (2015) Nitrogen Fixation in the High Arctic: Role of Vegetation and Environmental Conditions. Arctic, Antarctic and Alpine Research, 37, 372-378.
https://doi.org/10.1657/1523-0430(2005)037[0372:NFITHA]2.0.CO;2
[125] Sui, Z., Chang, Y., Li, Y.H., Man, H.Y., Miao, L. and Wei, C.H. (2010) Relationships of Arctium lappa Community Distribution and Species Composition with Eco-Environ Mental Factors. Chinese Journal of Ecology, 29, 215-220.
[126] Boy, J., et al. (2016) Successional Patterns along Soil Development Gradients Formed by Glacier Retreat in the Maritime Antarctic, King George Island. Revista Chilena de Historia Natural, 89, Article No. 6.
https://doi.org/10.1186/s40693-016-0056-8

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.