Understanding Past and Present Vegetation Dynamics Using the Palynological Approach: An Introductory Discourse

*Sylvester Onoriode Obigba*

## **Abstract**

Palynology is a multi-disciplinary field of science that deals with the study and application of extinct, [fossilised] and extant palynomorphs (pollen and spore) and other related microscopic biological entities in the environment. It is divided into palaeo- and actuo-palynology, and provides substantial proxies to understanding past and present vegetation dynamics respectively. With reference to the two geological principles of uniformitarianism and of the evolution of fauna/flora, the distribution of plant indicators across ecological zones, palynomorph morphology and pollen analysis, palynology can be used to identify the change in past and present local and regional vegetation and climate and humans impact on the environment. Other supportive areas of endeavour like radiocarbon dating, sedimentology, taphonomic processes and geomorphology can be used to triangulate inferences drawn from palynological data. Palynomorphs are made of outer cell walls embedded with an inert, complex and resistant biopolymeric signature (called sporopollenin) which helps to facilitate long term preservation in different environmental matrices under favourable conditions, hence its widespread applicability. Palynology have proven to very reliable in reconstructing past vegetation, decrypting essential honeybee plants and understanding the impact of climate on plant population using pollen analysis, for which is the basis for the application of palynology in environmental studies. The application of palynology in climate, vegetation and anthropogenic studies begins with the selection of matrix (sediments from lake, river, ocean, excavation, relatively intact soil profile, bee products), coring or collection of samples, subjection to a series of chemically aided digestion, separation, physical filtration, decanting, accumulating of palynomorphs, microscopic study and ends with the interpretation of recovered information. Literature review on the application of palynology for understanding vegetation and climate interactions is presented in this paper.

**Keywords:** Palynology, vegetation dynamics, pollen, spores, palynomorphs, palaeo-vegetation, pollen analysis, environmental reconstruction, climate, Quaternary

#### **1. Introduction**

In this review, vegetation dynamics is the succession pattern, spatial distribution, diversity and interaction of plants with humans traceable by pollen footprints in

terrestrial ecosystems. Kim [1] opined that vegetation dynamics is greatly influenced by climatic factors and patterns of land use by humans. The changes in vegetation pattern occur rapidly or gradually, and palynology can be used to study these changes. Palynology provides fair playing ground for participatory and collaborative research bordering on understanding past and recent changes in the vegetation of an area. By virtue of the principles of palynology and of pollen analysis, pollen grains and spores are best applied to resolving environmental puzzles especially those related to vegetation change. It is important to emphasise that palynology is highly preferred and considered rich in providing indices on the change in vegetation in a place for several reasons; the chemically resistant compound embedded in the outer walls of pollen and spores facilitating preservation, the ubiquitous nature of pollen and spore, high pollen productivity, distinctiveness in the morphology of pollen types helping in identification of parent flora among others. The organic compound in the pollen is resistant to microbial attack, temperature regimes and pressure when buried in the soil and lastly because palynomorphs are produced in abundance, transported by wind, human, insects (and other animals) or water to different environments and ubiquitous in nature. The ubiquitous characteristic nature of pollen is a function of its productivity and there is currently very limited data on it. Unpublished data with Sowunmi [2] and Obigba [3] has revealed that the pollen productivity for *Tridax procumbens* L. is 116,270, *Ricinus communis* L. - 1.7 million, *Bombax buonopozense* P. Beauv. - 5.3 million, *Adansonia digitata* L. - 2.6 million, *Annona senegalensis* Pers. *-* 796,791, *Vitellaria paradoxa* C.F. Gaertn. *-* 793,529, *Elaeis guineensis* Jacq. *-* 111,640, *Vitex doniana* Sweet *-* 31,160, *Parkia biglobosa* (Jacq.) D. Don. *-* 6,306 and *Bridelia ferruginea* Benth. *–* 740 in a single flower irrespective of the size of the pollen grain and the flower. This is indicative of that fact that a single flower in a tree can produce millions of pollen grains and by this singular action; it is now possible to find pollen in different environmental matrices.

#### **1.1 Palynology and its applications**

The term palynology was first introduced in 1944 [4]. The word palynology was derived from two Greek words "*paluno"* meaning "to sprinkle" or 'dust' supposedly related to airborne or wind dispersed pollens and '*logos'* meaning 'study'. Palynology as simply pronounced as 'pal-uh-NOL-uh-jee' is the study of pollen, spores and microscopic sized entities of biological and uncertain origin (ranging from 5 to 500 μm). These entities have resistant cell wall capable of withstanding routine pollen analytical processes involving strong acids treatment. It is also referred to the study of fossilised and extant microscopic structures and their application in the environment [5]. These entities include pollen, spore, algae and their spores, dinoflagellates and their cysts, amoeba and acritarchs of unknown origin. Their ability to withstand the actions of strong acids (hydrochloric, hydrofluoric and sulphuric acids) is credited to the presence of a cellulosic chemical compound called sporopollenin [6], a compound word for the chemically similar CHO compound in spores – sporonin and pollen – pollenin [7].

Sowunmi [2] defined palynology as

*'the study of extant or fossil microscopic-sized structures, palynomorphs, which cannot be dissolved by hydrofluoric and hydrochloric acids and which are generally resistant to degradation in acidic and non-oxidative sediments or deposits, their dispersal and the applications thereof' (p. 2).*

It is primarily divided into two (past – palaeopalynology and present actuopalynology), and has become highly applicable in several other emerging *Understanding Past and Present Vegetation Dynamics Using the Palynological… DOI: http://dx.doi.org/10.5772/intechopen.97755*

fields but only those involving vegetation dynamics will be discussed here. Palaeovegetation (or palaeoecology), petrolipalynology, palynostratigraphy, archaeopalynology, forensic palynology, pharmaceutical palynology, melissopalynology, paleobotany, palynotaxonomy or systematic palynology, and aeropalynology are some of the areas of research in palynology. There are several other emerging fields of interdisciplinary research in palynology which has spanned into plant systematics, apiculture, public health, earth sciences, climatology, environmental reconstruction and archaeology, however, other supportive mechanisms like radiocarbon dating, sedimentology, taphonomic processes and geomorphology can be used to triangulate inferences drawn from recovered palynomorphs.

#### **1.2 Palaeovegetation and environmental reconstruction**

This area of research is centred on understanding past ecological dynamics in view to elucidating the past and present legacies of humans, the changes in the regional and local ecosystems, the impact of climate variability and how these information can be used in predicting future changes or current patterns. Palynology has been used for decades for understanding palaeovegetation dynamics and changes from analysing different substrates like guano deposits [8, 9], climate changes in forests [10], rock shelters [11], lakes sediments [12] or surface sediments [13]. The word 'palaeo' means 'past, ancient, old or prehistoric', so, it will be acceptable to say palaeovegetation is vegetation of the past or prehistoric vegetation. One of the way in understanding change in vegetation is by studying palynomorph abundance and variability in undisturbed stratified sediments. Two geological principles are used to support palaeovegetation studies. The first is the Principle of Uniformitarianism which proposes that the natural geologic laws or processes that exist in the present day are same or at one time were observed in the universe in the past, and these changes apply to every other area on earth. The inference is that, the earth has always had uniform changes and that the present changes can be used to uncover changes that occurred in the past and vice versa. Therefore, the changes that occurred in past in terms of vegetation are almost same as at today. The second law is the 'Evolution of fauna and flora' which says that in a vertically stratified sedimentary soil profile, the stratum on top is younger in age and formation than the one below. What this means is that, the farther the stratum down the earth, the older the soil and the closer the stratum to the surface, the younger it will be. This also implies that these strata are embedded with fossilised plant and animal remains preserved over time. In recent times, the law has been referred to as the 'principle of fauna/flora succession' [14, 15] where fossilised materials succeed themselves in the vertical strata. That is, the fossilised fauna and flora beneath evolved to the next stratum just next to it (on top) and so on till it gets to the earth surface or top soil. This order occurs in a reliable format except for disturbed and distorted soil profile. This principle is applied to paleo-vegetation up to what I called 'actuo-vegetation' using pollen analysis of each stratum referred to as sub sample. Since inception several studies have been conducted on this. Novello *et al.* [16] described how palynology was used to decipher last glacial (115,000 years before present) to Holocene (about 12,000 years before present) vegetation and environmental change in South America using cave deposits. Using certain pollen types, the palaeovegetation changes with respect to pollen abundance in sediments through routine pollen analysis are presented below. These reviews provide clues to the vegetation dynamics based on the presence or absence of pollen grains in the sediments and possible factors influencing their abundance in the sampled regions.

#### **1.3 Melissopalynology and conservation of bee flora**

Melissopalynology is the branch of palynology that deals with the study of palynomorphs in honey and other honeybee products like propolis, beewax and bee breed. The aim is to find out the botanical and geographical origin of the honey [17]. Honey is produced by the action of eusocial honeybees foraging for proteins and carbohydrates. They visit 'nectariferous' and 'polliniferous' flowers (**Figure 1**, No 6 & 8) for pollen and nectar and sweet fruits like pineapple, mango, water melon and others (**Figure 1**, No. 1–5 & 7) for natural sugars. Honeybees are regular visitors of very colourfully scented flowers for nectar or pollen because their larval and adult dietary requirements depend on it [18]. Pollen is the bee's major source of protein, fat, minerals and vitamins, while nectar is the major source of carbohydrates from which honeybees source for energy. In the course these foraging expedition, the honeybees collects pollen and other non-pollen materials (honeydew elements) co-incidentally for the production of honey in their hives. The pollen is the focus for this aspect of palynology and its usefulness for vegetation dynamics of the present day. Preliminarily, pollen grains are the male microgametophyte of either unicellular or multicellular form that is produced in the flowers with the primary responsibility of pollination and fertilisation. This invariably means they can be used to track flowering patterns for honeybee plants. Honey bees are major pollinators among flying insects and are so essential in conserving plant diversity.

Apiculture is the aspect of agriculture that covers this part of biological sciences. Melissopalynology thus deals the representation of pollen types (that is flowering plants visited by honeybees) in honeys collected and marketed for humans. Depending on the rate of foraging and seasonality of flowering in honeybees plants, honeybee farmers can collect or extract honey from honeycombs or artificially manufactured hives on a weekly or monthly basis. The taste, colour, texture and fragrance of the honey are dependent on the type of flora visited. If the honey is derived from a single flora, it is called unifloral and if it is from several floras, it is referred to as multifloral or polyfloral honey. In understanding flora dynamics, mulitfloral honeys

#### **Figure 1.**

*Honey bee foraging for nectar and/or pollen: 1:* Citrullus lanatus *(Thunb.) Matsum. & Nakal (water melon) fruit, 2–3:* Mangifera indica *(mango) fruit, 4–5:* Anacardium occidentale *L. (cashew) fruit. 7:* Antigonon leptopus *Hook. & Arn. (Mexican creeper) flower, 7:* Ananas comosus *(L.) Merr. (pineapple) fruit, 8:*  Canthium danlapii *flower. (Source: Author original photos).*

*Understanding Past and Present Vegetation Dynamics Using the Palynological… DOI: http://dx.doi.org/10.5772/intechopen.97755*

are best for analysis. This can reflect the yearly pollen calendar for a locality where plants are cultivated or grown in the wild. Several studies have been carried out in this aspect by many researchers. Vegetation dynamics *vis-a-vis* floral diversity can be safely constructed using melissopalynology to show flowering pattern for important bee plants. Flora that needs to be conserved for enhancing health of honeybee colonies and the production of economically and medicinally important honey can be revealed through melissopalynology. A perfect example is presented in Lau *et al*. [19] paper where they studied the annual spatial and temporal dynamics in the vegetation of urban and suburban areas in Texas, Florida, Michigan and California by collecting pollen foraged by honeybees. Hence, pollen is an essential tool in the analysis of honey as it indicates the major and minor plant taxa utilised by honeybees.

#### **1.4 Aeropalynology**

The atmosphere is made of several airborne particulate matter of which pollen and spores are part of. Wind dispersed pollen and spores are released from lower green and flowering plants respectively at different times in the year and can be used to trace seasonality and presence of pollen in the atmosphere for public health reasons. Aeropalynology as the name implies is the study of airborne palynomorphs sampled through a pollen trap. This study is important if deleterious allergy triggers must be identified. One of the founding fathers of palynology, Erdtman, defined aeropalynology as the study of pollen and spores in the atmosphere [20]. In Ezike *et al*. [21], a monthly survey airborne palynomorphs in North Central Nigeria was carried for one year with the aim of finding the abundance, diversity and variation of wind pollinated flora in the region. The study attempted to the link pollen dispersal and meteorological environmental changes using a pollen trap. Fern spores, pollen types, algal cysts and diatoms were recovered with varying abundance across the year. Aeropalynology can be used to identify phytoecological groups in the atmosphere which is supposed to be a representation of the regional vegetation. In Anyigba, Kogi State, Essien and Nkang [22] recovered 47 airborne palynomorphs (pollen types) from 29 plant families through the pollen analysis after collecting samples for both dry and wet seasons. They found three major vegetation types (forest, savanna and human impacted). Thus, airborne palynomorphs can be used as indicators for regional flora or of the immediate environment. Monthly retrieval of airborne palynomorphs can be used to infer the flowering seasonality of wind dispersed or pollinated plants in that region.

#### **1.5 Archaeopalynolgy**

This area of research is in environmental archaeology where the interaction of humans with their environment (particularly the plants) in antiquity is deciphered by detail analysis of pit excavations. The archaeological materials alongside with the palynomorphs recovered are used to interpret past interactions of humans with their flora. There are anthropological studies available on this aspect involving the use of palynology e.g. farming history and prehistoric weapon production and furnace use [11, 23]. Johnston [24] mentioned that archaeologists in the course of their study find fossilised pollen and spores of different shapes in excavations; hence, archaeopalynology is the study of palynomorphs in archaeological sites in an attempt to reconstruct the ancient lifestyle (diets, farming practices, raw material sourcing), food sources, physical landscape, domestication attempts and the understanding the impact of humans on earth. The methods in the analysing archaeopalynological samples are outlined in the paper by Dontella and Federico [25]. It includes removal of organic and inorganic matter, microscopy, identification and counting. Based on the pollen types found, the vegetation types and interaction of humans with the flora can be

elucidated. The law of geologic laws of uniformitarianism and flora/fauna succession is also applied here. It is important to succinctly note that pollen analysis remains the basis for the application of palynology in vegetation studies. Some important archaeopalynological works has been carried out in Nigeria like those of Orijemie [11, 23].

## **2. Pollen analysis, identification and vegetation-climate interaction**

#### **2.1 Pollen (or palynomorph) analysis**

The application of palynology in any field is basically dependent on the use of pollen analysis for deducing inference on vegetation-climate-human interactions. Pollen analysis is relatively laborious, time consuming and expertise demanding. The purpose for pollen analysis is to disintegrate the palynomorphs from their matrices and concentrate them for proper identification. It is only the series of analytical procedures commencing with the collection of palynomoprh embedded substrates (honeybee products – pollen pellet, honey, propolis, terrestrial and aquatic sediments, air borne particulate matter, excavations, anther from flowers, faecal matter, drug samples and rocks) from the field to laboratory processing of the substrates (**Figure 2**). Microscopy which helps to determine relative abundance of one palynomorph type in comparison to other follows immediately after the laboratory processing. Depending on the type of matrix and the aim of the analysis, different laboratory procedures are employed. For example, the qualitative study of palynomorphs requires acetolytic (chemical removal of protosplamic content using 9:1 of acetic anhydride and concentrated hydrochloric acid) processing for elucidation of exine ornamentations or patterns. This may not be necessary for quantitative study of pollen and spores in honey or sediments. They type of matrix determines the number of treatments to be used. For soil matrices, the numbers of chemical processes are more than other matrices like honey, drugs samples, or pollen pellet.

**Figure 2.** *Illustrating the stages involved in pollen analysis.*

*Understanding Past and Present Vegetation Dynamics Using the Palynological… DOI: http://dx.doi.org/10.5772/intechopen.97755*


**Table 1.**

*Palynomorph quantitative representation and interpretation in vegetation studies.*

Erdtman [20] and Faegri and Iversen [26] gives full description of pollen analysis, however, the figure below shows a summarised procedure for pollen analysis of palynomorph embedded samples.

In the interpretation of results from pollen analysis, there are several limiting factors. These factors influence the representation of palynomorphs when recovered. Some of them are pollen dispersal mechanism, pollen productivity, and differential preservation capacity against environment induced deterioration. In interpreting of pollen analysis, microscopy, identification and counting are used as the quantification presented in **Table 1**. In counting and providing information about the abundance of a particular pollen type, Jones and Byrant [27] and Louveaux, *et al*. [28] formula is used as shown in **Table 1** above.

#### **2.2 Pollen identification**

The application of palynology on every other area of research is largely dependent on the accurate identification which is powered by the impeccable description of the morphological features of the pollen types recovered from the environmental matrix. Pollen grains are unicellular to multicellular units composed of a cell wall and protoplasm. The morphological features and their distinctiveness are found on the cell wall especially in the outer cell wall called the exine. The parameters used in describing pollen grains are polarity, symmetry, aperture types, pollen class, pollen size, and exine ornamentation (details in **Figure 3**). Expert experience is highly in identification since some pollen types may have close resemblance but represent different vegetation types e.g. *Lophira alata* Banks ex Gaertn. is found in tropical freshwater swamp forests and *Lophira lanceolata* is representative of wooded savanna. Pollen from the Melastomaceae and Combretaceae are almost indistinguishable, hence are classified into one group even though other gross morphological feature are different. Palynomorph identification is carried out using pollen albums, reference pollen collections and published atlases [29–31].

#### **2.3 Late quaternary climate vegetation interaction in tropical West Africa**

According to the geological time scale, the Late Quaternary is from 65,000 years BP (before present) to date. During the period, the plant communities were greatly influenced based on their response to climate change. Information on the fluctuation in mangrove and freshwater swamp forests, the relative dominance of other forms of forests and savanna is provided. As provided in details in Sowunmi [32] paper, the following were some of the vegetation-climate changes that had occurred basically in the expansion and contraction of forests and savanna and a wet-dry climate cycle. These changes were categorised into six time frames as presented in **Table 2**.

#### **Figure 3.**

*Pollen grains (or types) of different flora and their morphological distinctiveness: 1–2:* Parkia biglobosa, *3–4:*  Acacia *sp. Martius, 5–6:* Securidaea *sp. 7–8:* Zea mays, *9–10:* Elaeis guineensis, *11–12: Asteraceae grain, 13:* Talinum triangulare*, 14: Loranthaceae– cf.* Tapinanthus *sp. (Blume) Rchb. 15:* Annona sengalensis, *16:* Parinari *sp. 17:* Bombax costatum *Pellegr. & Vuill. (Source: Author original photomicrographs).*

#### **3. Empirical studies**

#### **3.1 Palynomorphs, human-plant interactions and vegetation change**

Anthropocentric (human cultural) and the anthropocene (climate/human induced) forces have altered ecosystems, plant growth response, habitat characteristics, and behaviour of plants in recent times. In West Africa, there are evident


*Understanding Past and Present Vegetation Dynamics Using the Palynological… DOI: http://dx.doi.org/10.5772/intechopen.97755*

#### **Table 2.**

*Climate vegetation changes in West Africa in the late quaternary.*

adaptive changes in certain plants including their survival and growth in diverse vegetation zones. Today, many savanna species are found growing favourably in residential areas in mangrove and fresh water swamp regions in West Africa. Although a few species are still considered useful in deciphering vegetation dynamics during pollen analysis as presented in **Table 3**. This is particularly noticed in


*Understanding Past and Present Vegetation Dynamics Using the Palynological… DOI: http://dx.doi.org/10.5772/intechopen.97755*

the way savanna species thrive and survive in forest regions in southern Nigeria, although the survival of forest species in savanna has not been convincingly proven. Anthropogenic factors has led to the opening of forests canopies and planting of savanna (including ornamental) plants species and the guinea savanna region and deciduous low land rain forest is fast becoming a forest-savanna mosaic sometimes referred to as forest savanna transition. The availability of water, human interference through cultivation, burning, soil spatial variations, or herbivory pressure characterise this transition zone. Depending on the microclimate and anthropogenic impact, savanna and forest plant species co-exist, hence the presence of other vegetation-specific plant indicators are used to make decisions. Spores are usually used as bio-indicator for microclimates hence; the percentage of pollen and spore are good indices for understanding vegetation change and climate variability. Correct pollen identification is crucial to this application. **Table 2** shows the plant or pollen indicators that can be used to different vegetation types if there abundance in sediments is measured on the basis of **Table 1** above.

#### **3.2 Understanding vegetation dynamics using percentage representation of palynomorphs recovered from environmental matrices**

As earlier established in this review, pollen and spore percentage representation can be used to understand vegetation changes. This section will focus on changes in the abundance of certain pollen types (inferably, the plant species) in different environments across the globe and the possible factors influencing these changes. Some of these plants in *Typha* spp., *Elaeis guineensis, Bridelia* spp. *Annona* spp., Cyperaceae, Chenopodiaceae, Asteraceae, and Amaranthaceae to mention but a few. Haung et al. [37] in their study on pollen distribution in a large freshwater lake (Boston Lake) in the arid regions of Xinjiang, China using 61 surface samples found *Typha* L. to have average percentage representation (8.6%) when Chenopodiaceae had *ca.* 50%. Remarkably, *Typha* and *Phragmites* plants were abundant on the west side of the lake, and they asserted that hydrodynamic conditions affect *Typha* pollen. This indicates that lithological factors could moderate the representation of palynomorphs in sediments for some plant species just like the factors influencing the dominance of some plants in a region over others.

In Cameroun, Assi-kaudjhis [38] studied vegetational evolution in the Crater Lake Bambili which lies in the volcanic zone through the pollen analysis of sediments cored from two sites around the lake, a region located in the Guinean-Congolian forest belt. An inventory of the plant biodiversity was taken, and *Annona senegalensis, Bridelia ferruginea,* and *Typha* were found from 1600 m – 800 m asl as savanna elements within the local vegetation. Two cores of 13.5 m and 14.01 m depths, respectively, were taken from a few meters from the lake in 2007 and 2010. The results from pollen analysis revealed that *Bridelia*-type pollen was recorded (7.82%), Amaranthaceae/Chenopodiaceae, Poaceae (75.68–34.44%) and undifferentiated Asteraceae pollen was recovered from the sediments (30.29%). There was generally low amount of tree pollen. The distinctive pollen of *Annona senegalensis* and *Typha* were not found in the core while *Bridelia* was under-represented. Njokuocha [12] studied a 116 cm core from Holocene deposits in Lake Obayi in Nguru, Nsukka, which yielded 78 pollen types from 47 families. Njokuocha [12] found that *Elaeis guineensis* was well represented n sediments at depth 88–116 cm (*ca.* 40%) with Poaceae which was continually abundant in the core with specific abundance ranging from 20 to 40% representation in depths between 25 and 45 cm.

Marlon *et al.* [39] carried out high resolution sedimentological, geochemical and pollen analysis on a 5.75 m sediment core from the coastal plains of the Doce River, southeastern Brazil, which was characterised by many valleys resulting

from Quaternary deposition of silt. The region was composed of tropical rainforest like Annonaceae, pioneering freshwater species like *Cyperus* sp. L. (*ca.* 80%), Asteraceae (*ca.* 18%) and Amaranthaceae (*ca.* 2%). From depth 5.5–1.5 m, five ecological groups were observed where *Typha* was only *ca.* 2% with Cyperaceae (3–30%), Poaceae (30–80%). Within lake regions of 1.5–0.8 m depth, *Typha* was only *ca.* 2% represented while Poaceae was 14–40%. The herbaceous plain of depth 0.7–0 m on the surface also yielded under-representation of *Typha* and *Hydrocleis* pollen (< 2%). No detailed discussion was reported on why the *Typha* pollen was under-represented.

In India's Lonar Crater Lake, Riedel *et al.* [40] investigated modern pollen vegetation relationships using Holocene lacustrine sediments and surface samples. They found *Typha augustata* L. near the site of coring and *Annona squamosa* L. characterised the steep faces above the dry deciduous forest in around the site which made up *ca*. 30% of the local vegetation. Results revealed strong differences in pollen assemblages and studied trapping media samples although local arboreal vegetation was adequately represented in soil samples. The pollen of *Typha* and Cyperaceae pollen accounted for 33% of the total pollen present. Poaceae was overpresented while the pollen of *Annona* L. appeared scattered or with single grains even when it formed part of the local vegetation. Channel and surface run off water transport influence pollen assemblages.

Travedi *et al.* [41] reported the under-representation of *Annona cf. squamosa* whilst attempting to establish modern pollen rain vegetation relationship from ten surface samples from Chaudhari-Ka-Tal, Raebareli District, Utter Pradesh of India. They averred that low pollen productivity owing to its entomophilous mode of pollination may have been the factor responsible for the under-representation. There was sparse abundance of *Annona* plants in the local vegetation. Pollen spectra from three of the surface samples revealed that *Annona* pollen was merely 0.65% while *Typha* pollen ranged from 3.2 to 28% from the southern flank samples analysed from the lake. From the western flank, *Annona* pollen was merely 1.65% in the sediments and *Typha* ranging from 17.6 to 22%. The eastern flank of the lake recorded the highest occurrence of *Typha* pollen (ranging from 22.3 to 39%) probably due to the marshy nature of the lake. They however argued that the under-representation of tree taxa could be attributed to low pollen productivity when compared with grasses and herbaceous taxa. Chenopodiaceae/Amaranthaceae pollen was reported to be over-represented also. The increase in fungal spores may have indicated microbial attack, however, there was no certainty on the possible causes of underrepresentation mentioned and also no further studies were carried out on the exine chemistry to substantiate on the variations in percentage occurrence in the same lake.

#### **3.3 Climate variability induced vegetation dynamism and interactions**

The succession of one vegetation type by another is influenced by climatic, human or edaphic factors, or a combination of the triad. Across the globe, the phenomenal change and succession of vegetation in the past and present have been revealed through palynological studies. Few empirical studies are reported in this chapter for clearer understanding.

In Maya region of southern Mexico and Central America, Franco-Gaviria *et al.*  [42] investigated the impact of climate variability and human activities on the vegetation communities from two sediment sequences collected from two lakes (Lakes San Lorenzo and Esmeralda) in the highlands of Chiapas, Mexico during the late Holocene. The records reveal a long-term trend towards drier conditions with superimposed centennial-scale droughts. A declining moisture trend from 3,400

*Understanding Past and Present Vegetation Dynamics Using the Palynological… DOI: http://dx.doi.org/10.5772/intechopen.97755*

to 1,500 cal yr. BP consistent with southward displacement of the Intertropical Convergence Zone was reported. According to them, the climatic conditions with dense human occupation converted the vegetation from forest to more open systems. From paleoecological records of the area, cultural abandonment of the area which occurred ca. 1500 cal yr. BP probably favoured the forest recovery process at that time. About 600 cal yr. BP, wetter conditions promoted the establishment of modern montane cloud forests, with a diverse mixture of temperate and tropical elements. Some of the palynomorphs found in abundance were *Pinus* sp. L. and Cyperaceae pollen (at 3400–3200 cal yr. BP), *Pinus* sp. (over 200%)*, Myrica* sp. L. (5–12%)*, Quercus* L. (22–68%) and *Alnus* sp. Mill (2–8%) pollen (3200– 2400 cal yr. BP). *Alchornea* Sw.*,* Poaceae and *Quercus* aboreal elements peaked at ca. 2500–1500 cal yr. BP. Herbaceous taxa like Amaranthaceae, Asteraceae, Poaceae decreased from 1200 to 600 yr. BP at Lake san Lorenzo. Charcoal concentrations were low generally, but had peaks at ca. 2,500, 1600 and 1100 yr. cal BP. They concluded that the importance of microhabitats is in the maintenance biodiversity through time, even under scenarios of high climate variability and anthropogenic pressure.

In south western region of Nigeria, Orijemie [43] investigated climate-vegetation dynamics using an 8 m-core drilled in Ikorigho with comparison with Ahanve to provided evidence of late Holocene mangrove dynamics and environmental changes. The vegetation was found to have changed from mangrove to low land rainforest. Mangrove swamp forest species were indicated by pollen and spore of *Rhizophora* spp. L., *Avicennia* spp. L. and *Acrostichum aureum* L.; freshwater swamp forest include *Uapaca* Baill., *Mitragyna ciliata* Aubrev. & Pellegr. and *Symphonia globulifera* L.f. and a few lowland rainforest taxa (*Celtis brownie* Rendle*, Pycnanthus angolensis* (Welw.) Warb). There were marked reduction in *Rhizophora* spp. at certain periods which almost always coincided with an upsurge in Poaceae and Cyperaceae pollen obviously indicative of prevailing drier climate, and lowered sea level. In constrast, Sowunmi [44] reported that the environment in Ahanve – Badagry, experienced a very reduced or complete disappearance of mangrove species ca. 3100 yrs. B.P. Non-pollen palynomorphs like few charcoal particles at the lowest sections, and significant increase in charcoal particles in the topmost sections were found of the core providing evidence of relatively recent history of human interactions like tree felling, bush burning and agriculture.

In central Gabon, Ngomanda *et al.* [45] investigated vegetation changes during the past 1300 years are reconstructed in western equatorial Africa using a highresolution pollen record from Lake Kamalete. The Kamalete pollen data showed the persistence over the past 1300 years of a relatively stable forest-savanna mosaic, associated with significant changes of the forest component. Three successive stages of forest dynamics was found. First, at 1325 yrs. BP, moist semi-evergreen rainforest existed around the catchment of Lake Kamalete. There was consistent presence of above 70% Gramineae pollen that the site was always primarily in savanna. Secondly, from c. 1240 to 550 yr. BP, a noticeable increase in shade-intolerant plant species indicate openings in the rainforest canopy. Thirdly, at 550 cal BP, a mature forest was re-established, corresponding to progressive savanna colonisation by forest pioneer species such as *Aucoumea klaineana* Pierre, *Lophira alata* and *Fagara macrophylla* (Oliv.) Engl. This new phase of forest expansion coincided with a marked lithological change, indicating an increase in lake-level. It was concluded that the major vegetation changes observed were due to climatic variability, and anthropogenic action had limited influence.

In Benin Republic in West Africa, Tossou *et al.* [46] was able to present information on the coastal halophytic mangrove vegetation history based on palynological data collected. They found that the mangrove swamp went through several

physiognomic changes from the middle to late Holocene. In the course of the middle Holocene that is from 7500 to 2500 yr. BP. They found that the mangrove was extensive, and with high density of monospecific mangrove species dominated by Rhizophora. During the late Holocene, the mangrove regressed around 3000 years BP which indicated a period of drop in sea level and disappeared about 2500 yr. BP. It has been replaced by swamp meadows dominated by *Paspalum vaginatum* Sw. and a fresh water environment colonised by taxa such as *Persicaria* Mill., *Typha*, *Ludwigia* L., and *Nymphaea lotus* indicating a return of wetter climate drop in sea level.

In Lake Chad region, Amaral *et al.* [47] reported palynological evidences on the climate and vegetation changes that occurred in the Sahara – Sahel boundary which shifted northwards during the termination period of the African Humid Period (AHP). Dates obtained for sediments where between ca. 6700 and ca. 5000 yr. BP which encompassed part of the termination of the AHP. Results showed that, between ca. 6700 and ca. 6050 yr. BP, the vegetation close to humid savanna woodland, including elements currently found further southward, thrived in the vicinity of the Mega-Lake Chad in place of the modern dry woodland, steppe and desert vegetation. At the same time, the montane forest populations extended further southward on the Adamawa Plateau. The high abundance of lowland humid pollen taxa, particularly of *Uapaca*, was interpreted as the result of a northward migration of the corresponding plants during the AHP. The data retrieved indicated that between ca. 6700 and ca. 5000 yr. BP vegetation and climate changes must have occurred progressively, but that century-scale climate variability was superimposed on this long-term mid-Holocene drying trend as observed around ca. 6300 yr. BP, where pollen data indicate more humid conditions.

In Ghana, West Africa, Miller and Gosling [48] presented a fossil pollen record from sediment cores extracted from Lake Bosumtwi. The record covered the last c. 520,000 yrs. BP making it a apart of the Late Quaternary. The fossil pollen assemblages revealed that there was a dynamic vegetation change which can be broadly characterised as indicative of shifts between savanna and forest which also reflected the glacial – interglacial period. Savanna elements which heavily dominated the vegetation included Poaceae pollen (>55%) and was associated typically associated with Cyperaceae, Chenopodiaceaee/Amaranthaceae and Caryophyllaceae. Forest formations are were more diverse than the savanna, with the key taxa occurring in multiple forest zones being Moraceae, *Celtis* sp., *Uapaca* sp., *Macaranga* and *Trema* spp. Lour. The fossil pollen data indicated that over the last c. 520,000 yr. BP, the vegetation of lowland tropical West Africa has mainly been savanna; however six periods of forest expansion were evident which most likely correspond to global interglacial periods. A comparison of the forest assemblage composition within each interglacial suggests that the Holocene (11,000 yrs) forest occurred under the wettest climate, while the forest which occurred at the time of Marine Isotope Stage 7 probably under the driest climate.

In Cameroun, Lebamba *et al.* [49] investigated the vegetation dynamics and human interference of the Adamawa Plateau which is in between the Guineo-Congolian rain forest and Sudanian savanna in Central Cameroun from African Humid Period to the present day through the analysis of pollen and spores. They presented a 4000-yr old pollen sequence derived from the Lake Tizong sediments that extended from the end of the. Pollen sequence were distinguished into two major short-duration forested phases that lasted between ca. 3900–3000 yr. BP, and ca. 1900–1450 yr. BP. Within 4000–3000 yr. BP, arboreal/montane forest plants (*Podocarpus* sp. L'Her ex Pers., *Olea* sp. L., and *Rubus pinnatus* Willd.) dominated the vegetation, with associated semi-deciduous forest elements like *Celtis* sp. indicative of dry climate. A decrease in tree taxa was noticed and increase in freshwater forest taxa (Cyperaceae) around 3000–1900 yr. BP indicating a wet climate at that time with a slight increase in arboreal plants. From 1450 yr. till present savanna

*Understanding Past and Present Vegetation Dynamics Using the Palynological… DOI: http://dx.doi.org/10.5772/intechopen.97755*

elements (e.g. *Hymenocardia* sp.) become more dominant. It was also found that a critical ecological threshold occurred around 3000 yr. BP when Poaceae reached higher percentages than forest taxa. Savanna was established until the present day with a brief expansion of lowland semi-deciduous forest, dominated by *Myrianthus arboreus* P.Beauv.-type pollen, between ca. 1000–700 cal. yr. BP. Although, human impacts and climatic factors driving vegetation change were difficult to differentiate, the late Holocene on the Adamawa plateau was characterised by a variable climate that resulted in significant vegetation transitions.

#### **3.4 Honey, pollen and vegetation representation**

Pollen analysis of honey samples started a long time ago dating back to late 1970 with Sowunmi [50] as foremost. Several reports are available on the melissopalynological analysis of honeys from different parts of Nigeria as reviewed as follows. One of the earliest studies was that of Agwu and Akanbi [51] in view to understanding the botanical origin of the honeys from Bichi, Edem-Ani, Nanka, Nimo Nsukka and Ogbomosho including Ohafia and Port Harcourt. They found out that 56 pollen types were identified in all belonging to 14 families, genera and tribes. Ogbomosho had the highest (29) number of pollen types. The study revealed that most of the honeys were rich in pollen apart from the Port-Harcourt and Ohafia honeys that were adulterated. The species that were dominant or most preferred by honeybees include *Vitellaria paradoxa, Lannea* sp. A. Rich. in Guillem, *Elaeis guineensis, Parkia clappertoniana* Keay*, Prosopis africana* (Gull. & Perr.) Taub.*, Crossopteryx febrifuga* (Afzel. ex G. Don) Benth. and *Nicotiana tabacum* L. The vendors claim were verified as the pollen representation showed the vegetation where the honeys were produced. After this time, several others have been published.

Agwu *et al.* [52] analysed honey samples from four honey samples from different localities in Kogi State (Olowa, Ajogoni, Itama and Ojowu), Nigeria to determine their floral sources, ecological origin and season of production. Grains counts of 532, 589, 1033 and 720 were recovered respectively. Thirty-two pollen types encountered, 23 were identified to family level and two were unidentified. The predominant pollen types include those of *Acanthus* spp. L., *Alchornea cordifolia* (Schum. & Thonn.) Mull.Arg., *Anacardium occidentale* L., *Cassia mimosoides* L., *Elaeis guineensis*, *Hymenocardia acida* Tul., *Phyllanthus niruri* L., *Mangifera indica* L., *Tridax procumbens*, and *Zea mays* L. Results suggested vegetation types reflecting the lowland rainforest and secondary grassland and of quality. Kayode and Oyeyemi [53] undertook a study to determine the pollen quality of eight honey samples collected from Odigbo and Okitipupa areas of Ondo State, Nigeria. The result showed diverse pollen types that were visited by worker bees for their nectar and pollen source. The most frequently represented families were Fabaceae and Euphorbiaceae with 14 taxa and eleven taxa of pollen grains respectively. Some important plant taxa identified that are frequently visited by the bees include, *Lannae* sp., *Nauclea* sp. L., *Pericopsis* sp. Thwaites, *Lophira lanceolata* Tiegh. ex Keay, *Phyllanthus discoides* (Baill.) Mull.Arg, *Elaeis guineensis*, *Nauclea diderrichii* (De Wild. & T.Durand) Merr., *Brachystegia eurycoma* Harms and members of Combretaceae or Melastomataceae. These plants were found to be of great importance to the bees for honey production.

Melissopalynological analysis of four honey samples from four localities of Kogi State (Idah, Ajaka, Igalamela–Odolu and Inachalo-Oforachi) was carried out by Aina *et al.* [54] in a bid to ascertain the species of plants which were incorporated into honey. Pollen grain counts of 2274 to 3,195 were recorded. A total of 21 pollen types were recorded, 19 of which were identified to family level. Some predominant pollen types included *Leuceanea glauca* (Lam.) de Wit, *Parkia biglobosa*, *Elaeis guineensis*, *Phyllanthus* sp. and *Bombax buonopozense*. The four honey samples were

found to be unadulterated and certified to be of quality. From the pollen identifications, the botanical and geographical origin as well as the season of honey production of each sample were determined and also associated with definite vegetation types which reflected the vegetation of low land rainforest/Guinea savanna.

Oyeyemi [55] collected three honey samples from an apiary for three months to determine the change in pollen content for the months of October to December in Ado Ekiti. The study revealed that pollen count ranged from 106,962 to 171,487. The honey samples were found to be multifloral in source and had abundant *Nauclea* sp., *Entada* sp. Adans., *Vitellaria paradoxa, Lannea* sp. members of the Rutaceae and Combretaceae or Melastomaceae which indicated that these plants were available at the locality where the apiary is situated to serve as pollen and nectar sources. Other pollen types encountered include *Vitex doniana*, Poaceae, and *Irvingia* sp. Hook.f. There was variation in the total pollen count for the months of sampling; however, the honeys indicated a high richness in pollen diversity and quality.

Adekanmbi and Ogundipe [56] analysed three honey samples bought from open markets in Lagos, Nigeria. The proportion of pollen from each of the honey samples varied from 196 to 280. The most abundant taxa were *Tridax procumbens* and *Elaeis guineensis.* The pollen grains in the Palmae and Asteraceae plant families are of great importance to the bees for honey production; this can be seen in the abundance displayed. Other pollen taxa recovered belong to the families Mimosaceae, Euphorbiaceae, Sapotaceae and Anacardiaceae providing clue on the ecological origin of the pollen grains in the honey sample. Pollen analysis of honey proved to be useful in deciphering nectar sources of honeybee *Apis mellifera adansonii* Latreille.

#### **4. Conclusion**

The genetically conscripted chemical signature called sporopollenin in the outer cell walls enhances the ability of palynomorphs to retain their shapes even after subjection to heat and pressure in sediment treatment with concentrated acid during routine palynological procedures. This enables clear identification of pollen types and in extension the vegetation dynamics. The identification of pollen flora in honey is currently been considered as good means of understanding economically and traditionally important plants for conservation and reforestation. The daily dispersal of pollen (including the allergenic ones) in the atmosphere sheds light on the seasonally of vegetation, their flowering, productivity of pollen and contamination of atmospheric quality. Studying cores from lakes, rivers and soil profiles provides evidence for the change in vegetation in relation to climate, plant response to stress and human interference in the past. This is applied based to vegetation science by virtue of the percentage representation pattern of palynomorphs. Although caution must be exercised in interpreting palynological data due to the moderating factors like differential preservation of pollen grains based inertness of the chemical compound in its outer wall, limited knowledge on pollen productivity of flowering plants, dispersal mechanisms which affects the quantity of grains recovered from soil and honey or atmospheric samples, issues of pollen morphological similarities. Describing and attributing vegetation characteristics to a locality or region, the modern behaviour of plants is to be considered.

#### **Acknowledgements**

The author's special appreciation goes to Prof (Canon) M. Adebisi Sowunmi for laying the academic foundation for the understanding of palynology. Her academic, *Understanding Past and Present Vegetation Dynamics Using the Palynological… DOI: http://dx.doi.org/10.5772/intechopen.97755*

career-based and motherly advices were so helpful and she is so highly appreciated. Her contributions were highly transformative. The author is also grateful to Dr. E.A. Orijemie and Mr. P.C. Opara for their support, encouragement and support. To my parents Mr. and Mrs. Austin O. Kobi, I express my gratitude for the prayers and financial support.

## **Author details**

Sylvester Onoriode Obigba Palynology Unit, Department of Botany, University of Ibadan, Ibadan, Oyo State, Nigeria

\*Address all correspondence to: obigbasylvester@gmail.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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#### **Chapter 13**

## Forest Vegetation and Dynamics Studies in India

*Madan Prasad Singh, Manohara Tattekere Nanjappa, Sukumar Raman, Suresh Hebbalalu Satyanatayana, Ayyappan Narayanan, Ganesan Renagaian and Sreejith Kalpuzha Ashtamoorthy*

#### **Abstract**

Forests across the globe have been exploited for resouces, and over the years the demand has increased, and forests are rather exploited instead of sustainable use. Focussed research on vegetation and forerst dynamics is necessary to preserve biodiversity and functioning of forests for sustanence of human life on Earth.This article emphasis that the India has a long history of traditional knowledge on forest and plants, and explorations from 17th century on forests and provided subsequent scientific approach on classification of forests. This also explains the developments of quantitative approach on the understanding of vegetation and forest diversity. Four case studies viz., Mudumalai, Sholayar, Uppangala, Kakachi permanent plots in the forests of Western Ghats has been explained in detail about their sampling methods with a note on the results of forest monitoring. In the case of deciduous forests, the population of plant species showed considerable fluctuations but basal area has been steadily increasing over time, and this is reflecting carbon sequestration. In Sholayar, a total of 25390 individuals of 106 woody species was recorded for < 1 cm diameter at breast height in the first census of the 10 ha plot in the tropical evergreen forest. In Uppangala, 1) a 27- year long investigation revealed that residual impact of logging in the evergreen forests and such forests would take more time to resemble unlogged forests in terms of composition and structure; 2) across a similar temporal scale, the unlogged plots trees < 30 cm gbh showed a more or less similar trend in mortality (an average of 0.8% year-1) and recruitment (1%). The Kakachi plot study revealed that 1) endemic species showed least change in stem density and basal area whereas widely distributed species showed greater change in both; 2) The overall recruitment of trees was 0.86 % per year and mortality 0.56% per year resulting in an annual turnover of 0.71% ; 3) majority of the gap species had high levels of recruitment and mortality resulting in a high turnover.Such studies can be used as early warning system to understand how the response of individual plants, species and forests with the climatic variability. In conclusion, the necessity of implementation of national level projects, the way forward of two such studies: 1) impact of climate change on Indian forests through Indian Council of Forestry Research and Education (ICFRE) colloborations and 2) Indian long term ecological observatorion, including the sampling protocols of such studies. This will be the first of its kind in India to address climate change issues at national and international level and helps to trace footprints of climate change impacts through vegetation and also reveals to what extent our forests are resilient to changes in the climate.

**Keywords:** climate change, episodic recruitment, monitoring, permanent plots, trees, Western Ghats

#### **1. Introduction**

Forests across the globe have been utilized and many times exploited by humans ever since life style changed from nomadism to settled agri-based system. Forests used to supply many resources including fuel wood, medicine, timber, food etc. But over the years the demand has increased and forests are rather exploited instead of sustainable use.

Historically Indian forests attracted traders for its diversity in spices. The discovery of sea route to India resulted in exodus of European traders. The Portuguese, English, Dutch, French and Germans arrived in India in their quest for the plant species that were important as spices. Records are available that Romans and Arabs were briskly trading with Kings especially along the Western Ghats for variety of spices such as pepper, ginger, cardamom and other condiments.

#### **1.1 Vegetation studies in India**

India is richly endowed with climatic, edaphic and orographic gradients. Geographical extent of India ranges from tropical latitude to temperate latitude with tropic of Cancer passing through India dividing into almost half with one part predominantly tropical nature while the other is subtropical and temperate in nature. Hence the natural vegetation of India is also ranging from rainforests in the Western Ghats and Eastern Himalayas to desert in Rajasthan.

Ancient description of vegetation largely confined to composition of species primarily of medicinal use and utilization in rituals. Ancient India had a rich tradition of life sciences. There are reviews relating to the knowledge of plant sciences in ancient India [1]. The study of plants in ancent India was mainly under two heads namely, 1. Plants utilized for medicinal purposes and 2. Plants relating to agriculture [1]. However, the study on description of plants and animals was not popular. Takshashila University encouraged the collection, identifying and description of plants found around Takshashila. The traditional medicine in India which is primarily plant based has description of several plant species occurring in different forest types. Though, the descriptions largely confined to medicinal properties and parts of the plants used.

#### **1.2 Studies on plant systematics**

Significant contribution to botany of India was made during the colonial period with a strong pursuit of harvesting botanical resources. There were several European botanists and explorers contributed to the knowledge of botanical resources of India. Van Rheede H. A. (17th Century) the then Dutch Governor of Cochin made an effort to scientifically document the wealth of plants and indigenous medical knowledge with the native Malabaris. He produced a well written book, '*Hortus Malabaricus'* published during 1678–1693 [2]. This book contained scientific description and life size illustrations of about 742 native plants in Malabar (Kerala) and of which about 650 are of medicinal value. This book was used by several European botanists such as Linnaeus, De Candole, De Jussieu, Adanson, Blume and Wight to describe many species from India and Asia [3]. Some of the important

*Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*

names include, Johann Gerhard Koenig (1768) who made extensive collections from India, Robert Kydd (1787) who was instrumental in starting the Royal Botaical Gardens at Calcutta and Sir Joseph Hooker who wrote monumental book "*Flora of British India*" and Gamble and Fischer (1915-36) who wrote a comprehensive flora for the region of the presidency of Madras [4]. There were several Europeans who made collections and described many plant species from different parts of India. The development of science under colonial period is well described by Kochhar [4, 5]. Important component in development of plant science in India under colonial rule was establishment of botanical gardens not only in Calcutta but in several places across India with major focus on breeding and maintenance of economically important species from different colonial parts of southeast Asia.

#### **1.3 Indian forest types**

First systematic classification of Indian forest types was by Sir. H.G. Champion in 1936 which was later revised in the year 1968 by Champion H.G. and S.K. Seth [6]. They identified 16 major forest types based on rainfall and temperature (**Table 1**). Contemporaneously, the French Institute of Pondicherry (IFP; http://www.ifpindia. org) produced vegetation maps at the one million scale for peninsular India (by publishing 12 sheets between 1959 and 1973) in collaboration with Indian Council of Agricultural Research. Subsequently published six vegetation maps (scale 1: 250000) covering south and central Western Ghats region in collaboration with state forest departments of Karnataka, Kerala and Tamil Nadu [7–12]. These maps were produced considering bioclimate of the region, floristic series (dominant species based on climax species, structural and floristic composition) of the forest types, limits of forest types, altitudinal zonation, degree of degradation of forests, relationships between different stages of succession and the potentiality of a disturbed forest to return to the climax. Since then there are studies to improve the classification of forest types considering the feasibility for the forest managers to manage their forests. Attempts have been made by the Forest Survey of India (FSI) to revisit different forest types and reassign the forest types based on ground survey [13] (**Table 2**). In 2014, Indian Council of Forestry Research and Education (ICFRE) has revisited Champion and Seth [6] forest type classification by rapid assessment mode.

#### **1.4 Major developments in understanding vegetation of India**

There was a discernible change in describing vegetation in India. The trend was not to describe species found in any vegetation type but quantitatively describe the vegetation of a locality. There were several studies on quantitative description of vegetation in India. It was initiated by Rai [16], who inventoried all trees ≥10 cm dbh in four plots of 2.7, 2.7, 2.63 and 1.09 hectares respectively at Devimane, Malemane, Kodkani and Katlekan areas of the Western Ghats. Most such studies in the Indian evergreen forests have been conducted during the last decade of the 20th century, and many of them are once census plots. Interest in tree mortality and forest dynamics has increased recently because forest dynamics is thought to be involved in determining tree species diversity [17], and also thought to be related to global climate change, in particular [18]. Phillips and Gentry (*l.c.*) concluded that tree turnover rates have increased in tropical forests during the latter part of the 20th century. This has proved to be a controversial finding (e.g. [19, 20]), but one which could have important implications for biodiversity and atmospheric change. Apart from the global plot networks such as CTFS and Rainfor, India also made





#### **Table 1.**

*Major forest types in India with their sub types according to Champion and Seth [6] and characterstic species composition of different forests. Species composition follows Reddy et al. [14, 15].*

efforts to understand the vegetation and its dynamics. There are some examples describing the efforts to understand the vegetation.

#### **2. Forest dynamics study by Indian Institute of Science (IISc), Bengaluru, Karnataka, India**

India's first biosphere reserve the Nilgiri Biosphere Reserve (NBR) was established in 1986 and the responsibility of conducting research was given to Center for Ecological Sciences (CES), Indian Institute of Science (IISc). As a principle institute responsible in setting NBR, IISc has a commitment towards ecological research in the biosphere. The climatic and altitudinal gradient in NBR harbours different vegetation types ranging from dry thorn forests to rainforests. The altitudinal range has dry forests in the lower elevation to high altitude montane forests. Hence there is a tremendous variation in species composition across both climatic and altitudinal gradient.

When IISc began its research in NBR there were several issues regarding the choice of study area. Based on both logistical and academic reasons, IISc decided to join the international network of 50-ha forest dynamics plots promoted by Prof. Hubbell [21]. CES selected species poor deciduous forests of Mudumalai for variety of reasons. Firstly, Mudumalai would complement plot at Barro Colorado Island (BCI), Panama (tropical semi-evergreen forest, neotropics) and Malaysian plot, FRIM, Malaysia (equatorial rainforest). Secondly the factors influencing the


#### **Table 2.**

*Standard forest types of India according Forest Survey of India (FSI) classification.*

dynamics in dry forests are totally different from factors influencing dynamics of forests at both Panama and Malaysia [22].

#### **2.1 Choice of the site**

IISc has selected 50 hectare area in 17th compartment of the Kargudi range in Mudumalai Tiger Reserve as because, 1. The area is relatively free of anthropogenic disturbances as settlements are far off, 2. This area was selectively felled during late 1960s and we could identify the trees that were removed from the plot. They could identify the species of the stumps left behind and map them spatially in the plot, 3. This area lies in the transition zone between dry and moist deciduous vegetation and has both elements represented in the plot.

#### **2.2 Methods**

Establishment of plot involved two steps a. gridding and b. enumeration of the plot. Gridding involves dividing the plot into blocks of 20 X 20 metres after correcting for slope. Correction for slope is important to give equal opportunity for all individuals to compete for resources.

Enumeration involves measuring of all woody individuals and mapping them. Block of 20 X 20 meters is further divided into blocks of 10 X 10 meters temporarily by laying ropes. All woody individuals >1 cm dbh (diameter at breast height) are

identified, measured for size, marked with unique number and mapped by taking X and Y coordinates. Point of measurement (POM) was marked where size measurement was made.

#### **2.3 Results**

There were 25,929 stems duing the first census belonging to 71 species. Most abundant species was understorey tree *Kydia calycina* (Malvaceae) with 5175 individuals accounting for 20% of total abundance. Dominant canopy species such as *Anogeissus latifolia* (2280), *Lagerstroemia microcarpa* (3980). *Tectona grandis* (2143) and *Terminalia crenulata* (2776) accounted for 55.9% of total abundance. The genus *Ficus* (Moraceae) had five species and followed by *Terminalia* (Combretaceae) with three species. Relative abundance cumulative abundance of top ten species is listed in the **Table 3**. Top ten species accounted for 87.52% of the total abundance. There were 21 species with less than 10 individuals in the plot and 7 species had one individual in the entire 50 hectare plot (**Table 3**).

Most species showed clumped dispersion. *Kydia calycina, Lagerstroemia microarpa,Terminalia elliptica, Helicteres isora, Anogeissus latifolia, Catunaregam spinosa* and *Shorea roxburghii* are species that showed highly clumped distribution at 1 hectare scale while species such as *Tectona grandis, Emlica officinalis, Grewia tiliifolia, Syzygium cumini, Diospyros montana, Schleichera oleosa,Terminalia chebula* and *Gmelina arborea* showed lesser degree of clumping at one hectare scale.

#### **2.4 Forest dynamics (1988–2016)**

Population of woody species in the plot has shown considerable fluctuations over different census periods. Population has grown from 25,935 individuals >1 cm dbh in 1988 to 48,360 individuals in 2016 (**Figure 1**). The population across different census years has shown fluctuations. There was a negative trend during


#### **Table 3.**

*Top ten dominant species in the plot during the first census (1988–1989).*

1988–1992 (31.9%), 1992–1996 (13.2%) and 2000–2004 (14.2%). There was huge surge of 138.9% in populations between 2004 and 2008 census. There was a positive trend during 1996–2000 (18.3%), 2008–2012 (1.1%), 2012–2016 (28.7%).

There is an overall increase of 86.4% with the total population during 1988– 2016. However, individual species showed an interesting trend in the populations (**Table 4**). Among canopy species *Dalbergia latifolia* has shown a large change of 469.3% (population changed from 75 individuals in 1988 to 427 individuals in 2016). Among the four dominant canopy species except for *Lagerstroemia microcarpa* (13.4%) others such as *Anogeissus latifolia* (25.3%),*Tectona grandis* (17.4%) and *Terminalia elliptica* (22.2%) have shown negative change. Other species that have significant change include *Gmelina arborea* (72.8%), *Ougeinia oojensis* (89.3%) and *Shorea roxburghii* (82.0%).

Among the understorey species, *Helicteres isora* (776.1%) and *Randia dumetorum* (679.0%) registered exceptionally higher population growth. *Helicteres isora* increased from 2573 individuals in 1988 to 22,543 individuals in 2016 while *Randia dumetorum* from 770 individuals in 1988 to 5999 individuals in 2016. There was a significant reduction in population of *Eriolaena quinquelocularis* from 249 individuals in 1988 to 7 individuals in 2016.

#### *2.4.1 Patterns in mortality and recruitment*

Entire plot (50 hectares) was annually censused for mortality and recruitment till 2008. Since 2009, annual census was done in sample plots of 40 meters X 40 meters inside the plot. There were 100 such randomly placed plots accounting for little more than 1/3rd of the total area. The reports on annual mortality for the plot from sample plots from 1989 to 2016 were published [23].

The community wide mean annual mortality rate was 7.675.75% (range 1.57–21.5%, N = 28) while mean annual recruitment rate was 11.114.0% range = 0.65–58.5%, N = 28). Though recruitment rate was higher than the mortality

**Figure 1.** *Total population in different census years (all woody stems >1 cm dbh).*

#### *Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*


#### **Table 4.**

*Population changes observed among several canopy and understorey species in the 50 ha plot, Mudumalai.*

rate, recruitment rate had high variability compared to mortality rate. There was considerable fluctuation in the mortality and recruitment rate across census periods (**Table 5**). Mean annual mortality due to fire across different census years was 2.875.75% (range = 0–20.6%, N = 28). Elephants resulted in mortality rate of 2.332.04% (range = 0.28–7.56%, N = 28) while mortality due to other causes was 2.472.49 (range = 0.46–12.58%). Mortality rates due to fire spiked in the years of dry season fire (1991, 1992, 1996, 2002 and 2010), resulting in mortality rates over 10%. Highest mortality of 12.58% was seen in the year 2016 where there was no dry season fire. Elephant related mortality was high in year 2008 after the massive "episodic recruitment" observed in one of the favoured speies *Helicteres isora.*

The community wide mean mortality rate was high during the first census (1989–1992) which had two years of consecutive dry season fires across different


**Table 5.**

*Mean overall mortality and recruitment rates in the 50 hectare forest dynamics plot, Mudumalai.*


**Table 6.**

*Mean mortality rate due to different causes in the 50 hectare forest dynamics plot, Mudumalai.*

census period. Lowe mortality rate with low variability was seen during the third census (1996–2000). Recruitment rate also showed considerable fluctuation across different census periods ranging from as low as 2.3% during first census (1989– 1992) to 38.76% during fifth census (2004–2008). Variability was high during the seventh census (2012–2016) (**Table 5**).

Mean mortality rates due to different causes across census periods is tabulated in the **Table 6**. Mean rate of mortality due to fire during the census period between (2004–2008) and (2012–2016) was zero suggesting fire did not result in the mortality of any individual. There was a considerable variability in mortality rates across other census periods (**Table 6**). Elephant related mortality rate was high during the first census period (1989–1992) and 5th census period (2004–2008) owing to abundance of elephant favoured species such as *Kydia calycina* and *Helicteres isora*. The mortality rate inflicted by other causes also showed considerable fluctuation with high variability during the 7th census period (2012–2016).

#### *2.4.2 Basal area changes and biomass across census periods*

The basal area in the plot has been steadily increasing over time (**Figure 2**). Above Ground Biomass (AGB) and hence carbon stock also shows a similar trend (**Figure 3**), with both the native woody vegetation and invasive ground vegetation showing increment. Basal area changes do not necessarily translate to AGB changes: for instance, the slight decline in basal area during 1992–1996 is not reflected in AGB, which may be partly due to differences in wood densities (e.g. hardwoods growing more than softwoods). Native woody vegetation biomass in 2004 shows a slight reduction owing to a severe drought in the preceding years and a large fire in 2002. However, the invasive *Lantana camara* L. increased substantially following the drought, and therefore the total biomass remained at the 2000 census level. Large increment in biomass were seen in all subsequent censuses: 2008, which followed a period of higher than average precipitation and no fires, 2012, despite a fire in 2010 and only 807 mm precipitation in 2012 (compared to the long-term average of 1260 mm), and 2016, which follows a fire-free census interval. The

**Figure 2.** *Native woody-plant basal area (per hectare) in the 50-ha plot.*

**Figure 3.**

*Aboveground biomass (per hectare) in the 50-ha plot, showing contributions from native woody-plants as well as other ground vegetation.*

estimates for basal area and biomass for the census period 2016 to 2020 is based is based on first 10 Ha.

#### **3. Long-term monitoring programme of Kerala Forest Research Institute (KFRI), Peechi, Thrissur, Kerala**

Being a part of Western Ghats range of mountains, one of the global biodiversity hotspots, Kerala has bestowed with diverse forest ecosystem with high degree of endemism. Kerala Forest Research Institute (KFRI) currently having more than 40 permanent plots across the state representing all major forest ecosystems (**Figure 4**) and more plots are coming up as a part of various ongoing research projects. KFRI Long-term monitoring programme represents all major ecosystems like mangrove, moist deciduous, dry deciduous, wet evergreen, montane shola forests and grasslands. As of now, the programme covers 50,309 woody individuals of more than 350 species. Majority of our plots are smaller in size (≤1 ha) in which survey would be conducted at five year intervals. These plots were established in different time

periods under various research projects undertaken by KFRI. The oldest set of plots was established was during 2000–2002. Recently a large 10 Ha permanent plot was established in wet evergreen forests, Sholayar range. Vazhachal Forest Division, Kerala (**Figure 4**).

## **3.1 Sholayar 10 ha plot**

A permanent plot of 10 ha (500 200 m2 ) size was established in a tropical evergreen forest at Karadichola, Sholayar Range, Vazhachal Forest Division, Kerala in Southern Western Ghats. Plot establishment and baseline data collection were done based on the Forest-GEO [24] (CTFS) protocol during 2016–2017. Comparison of Sholayar plot with other sites which are following Forest-GEO protocol is summarized as **Table 7**. Complete inventory of woody individuals ≥1 cm dbh were

**Figure 4.**

*Distribution of Long-term monitoring plots of KFRI in Southern Western Ghats.*


#### *Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*

#### **Table 7.**

*Comparison of vegetation parameters of 10 ha plot at Sholayar, Kerala with other Forest-GEO (CTFS) sites around Globe.*

done and each individual was permanently tagged with sequentially numbered aluminium tags. In the 10-ha plot, a total of 25,390 individuals of 106 woody species were recorded [25]. These individuals were belonging to 44 families and 81 genera.

Small-diameter class (1 cm ≤dbh<10 cm)were 3.6 times more abundant than largediameter (dbh ≥10 cm) ones. There were 19,975 small-diameter plants (78.67% of all stems), averaging 1997 individuals/ha, while large-diameter trees had an abundance of 5415 plants and density of only 546 individuals/ha. The family Rubiaceae, is the most abundant, with densities >900 individuals/ha, followed by Euphorbiaceae, Urticaceae, Sapotaceae, Meliaceae, Malvaceae, and Putranjivaceae. Among tree genera *Palaquium, Cullenia*, of family Sapotaceae and Malvaceae respectively, were the most abundant, with >100 individuals/ha, followed by *Drypetes, Mesua, Aglaia, Vateria, Syzygium* and *Agrostistachys*. At tree species level, *Palaquium ellipticum, Cullenia exarillata, Mesua ferrea* were the most abundant, followed by *Aglaia tomentosa* and *Vateria indica.* Out of the 106 species, 38 species are endemic to Western Ghats and 20 are listed in IUCN categories. Among trees, *Palaquium ellipticum*, *Cullenia exarillata* and *Vateria indica* were dominant in terms of Importance Value Index (IVI) while among shrubs *Psychotria nudiflora* was the dominant, followed by *Dendrocnide sinuata* and *Psychotria anamalayana*. Total basal area (in 10 ha) was 477.24 m2 (47.72 7.58 m2 /ha) and family wise it was higher in Malvaceae (9.69 m2 /ha) and Sapotaceae (9.6 m2 /ha) followed by Dipterocarpaceae, Calophyllaceae, Putranjivaceae and Sapindaceae. The dominant genera by basal area were *Cullenia, Palaquium, Vateria, Mesua, Drypetes* and *Dimocarpus*. At species level, *Cullenia exarillata* and *Palaquium elipticum* were the most important followed by *Vateria indica, Mesua ferrea, Dimocarpus longan, Drypetes wightii* and *Holigarna nigra*. Small-diameter trees contributed 4.89% of the total basal area. Species level contribution to density and importance value index is summarized in **Table 2**. Girth class distribution pattern indicates it as a relatively undisturbed forest patch with healthy regeneration. Ecological and Ecophysiological studies are ongoing on the structure, function and dynamics of this system in the context of climate change (**Table 8**).


#### *Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*



*Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*


#### **Table 8.**

*Species- level contribution to the community in the 10 ha. plot, Sholayar, Kerala.*

#### **4. Forest dyanmics study by the French Institute of Pondicherry**

#### **4.1 A case study: Uppangala Permanent sampling plots**

Since the early 1980s, the French Institute of Pondicherry has been in collaboration with the Forest Department of Kerala and Karnataka to explore structure and diversity of wet evergreen forests of the Western Ghats. In 1979–80, a total of 147 trees ≥ 30 cm girth at breast height was monitored untill 1982 for growth (with a precision of 0.02 mm) at monthly intervals in a 0.2 ha plot at Attapadi. Monitoring the plot in the region was stopped for logistic reasons. Subsequently, IFP has established two sets of sample plots in low elevation wet evergreen forest in Kadamakkal RF, Sampaje Range, Kodagu (ca. 12°32<sup>0</sup> <sup>15</sup>″N, 12° 33' N, 75°39'4″E; **Figure 1a**). Currently this area comes under the Pushpagiri Wildlife Sanctuary in Kodagu district. The study area, the Uppangala was subjected to selective logging, between 1974 and 1983 [26]. During the logging operation, the forest was divided into compartments of 28 ha each, 237 to 359 large trees (stems ≥ 180 cm) of medium wood (> 0.5 but ≤ 0.72 g cm�<sup>3</sup> ) *Dipterocarp* species viz., *Dipterocarpus indicus* and *Vateria indica* were logged per compartment. An average of 8 to 13 dipterocarp trees ha�<sup>1</sup> were logged manually and hauled using elephants locally, a method that causes much less damage than mechanized skidding. A few patches of forest remain unlogged. The elevation ranges between 400 and 600 m a.s.l. It belongs to the *Dipterocarpus indicus*-*Kingiodendron pinnatum*-*Humboldtia brunonis* type of wet evergreen forests and is a part of the West Coast Tropical Forests of Champion and Seth's classification. Uppangala receives slightly more than 5100 mm per year and the dry season lasts 4.5 months.

The first set of sample plots was installed in 1984 to study the post-logging effects on the forest dynamics of a once logged 30-ha compartment (**Figure 5b**). It consists of 14 plots of 600 m<sup>2</sup> (20 x 30 m). All trees ≥ 10 cm girth at breast height (gbh) were recorded during the first census. All the plots were recensused (except 4 plots, which were recorded as burnt) in 1988 and 1993 for recruitment and mortality. In 1989, a second set of sample plots was established in another 30-ha compartment (**Figure 5c**), which had escaped logging operation due to the ban on selective felling from 1987 in the forest of Western Ghats.

The unlogged compartment probably represents the last example of old-growth low-elevation *Dipterocarp* forest in the entire Western Ghats. Five north–south oriented transects (viz., A, B, C, D and E; **Figure 5c**) of 20 m wide, 180 to 370 m

#### **Figure 5.**

*(a-e) Uppangala study site, (a) Location of Uppangala study site in the central Western Ghats, Karnataka, India. Sampling designs for the inventory of trees: (b) systematic sampling in logged and (c) sampling plots and transects in unlogged (d) fifteen 1 ha plots in both compartments and (e) contiguous 9.9 ha plot in the unlogged compartment of the low elevation wet evergreen forests.*

long and 100 m apart from each other were established to inventory trees ≥30 cm gbh. Collectively they represent a 3.12 ha<sup>1</sup> systematic sample. Subsequently, additional rectangular sampling plots viz., H, R and S, which overlap with sampling area of the transects and represent an additional area of 1.95 ha, were established between 1990 and 1993 to study the forest dynamics according to topography (slope and more or less flat terrain). Totally 3870 trees were identified, mapped and installed with dendrometric belt (precision of 0.2 mm) for growth monitoring, which has no equivalent in any other tropical forest in the world. The sampling area has been monitored annually for recruitment and mortality. In 2010–2011, fifteen 1 ha plots was established to appraise allometric relationship of tree diameter and tree crown (for trees ≥ 30 cm gbh) and to estimate above ground biomass. These 1 ha plots were sampled randomly in both the logged and unlogged forests. Of these, four plots were selected to understand the residual impact of logging on species composition, population structure and biomass. In 2013–2014, the sampling area of the unlogged compartment has been increased to 9.9 ha and all trees ≥ 30 cm gbh were inventoried within a 330 x 300 m<sup>2</sup> area (**Figure 5d**). All the trees were identified, girth measured and mapped.

#### **4.2 Results of three decade long research in Uppangala**

#### *4.2.1 Tree density and diversity*

The systematic sampling plots of logged compartment was recorded with a total of 2748 trees ≥ 10 cm girth at breast height (gbh) during the first census in 1985 [27].

#### *Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*

Similarly, a total of 1981 trees ≥ 30 cm gbh were recorded with 91 species in the first census of 3.14 ha area of the unlogged compartment in 1990 [28]. Pronounced species hierarchy is another characteristic feature of the forest. Just 10 most abundant species contributed 71% for the forest stand (**Table 9**). Subsequent additional sampling area allow us to monitor more number of trees in the unlogged compartment. Totally 3870 trees were enumerated in the 5.07 ha during 1994 census and all those trees fitted with stainless dendrometric belts for measuring growth with a precision of 0.2 mm. At present we are monitoring 6672 trees (of which 3127 trees were installed with dendrometer bands) representing 111 species in the unlogged forest plot. The forest is characterized by high tree density and basal area (661 stems ha<sup>1</sup> ; 43 m2 ha<sup>1</sup> ). Pronounced species hierarchy is another characteristic feature of the forest. Just four species namely, *Dipterocarpus indicus* (emergent layer), *Vateria indica* (upper canopy and emergent), *Myristica dactyloides* (intermedidate) and *Humboldtia brunonis* (understorey) dominate the forest stand, and they collectively account for greater than 50% of density and basal area of the forest.

#### *4.2.2 Impact of logging on tree diversity*

A decade long monitoring of logged and unlogged forest for trees ≥ 30 cm gbh revealed the logged compartment had 347 trees and 54 species in 0.6 ha (1986) whereas the unlogged compartment had 1891 trees and 88 species in 3.12 ha in 1990 [29]. Initial stand density and basal area of the trees were slightly lower in the logged forest (578 stems ha<sup>1</sup> ; 34.8 m<sup>2</sup> ha<sup>1</sup> ) than in the unlogged forest (606 stems ha<sup>1</sup> ; 39.3 m<sup>2</sup> ha<sup>1</sup> ). Mean density and basal area for the 20 30 m<sup>2</sup> samples of the two compartments displayed no significant difference (t-tests, P>0.25). The mortality rate was more or less similar for the compartments (0.89% for logged and 0.87% for unlogged), which is lower than the rates observed in other tropical forests. Annual recruitment rate of logged (1.68%) and unlogged forests (1.34%) were not significantly different. Mean diameter increment was 2.1 mm and 2.9 mm yr.<sup>1</sup> for unlogged and logged compartments. In the logged forest, *Antiaris toxicaria*, *Aphanamixis polystachya*, *Beilschmiedia wightii* disappeared while *Cinnamomum malabatrum*, *Holigarna arnottiana*, *Microtropis stocksii*, *Sterculia*


#### **Table 9.**

*Top-ten dominant species in the unlogged compartment plot during the first census 1990.*

*guttata* and *Vitex altissima.* In the same time, unlogged plots showed no disappearance of species and appearance of three new species namely, *Agrostistachys borneansis*, *Clerodendrum viscosum* and *Syzygium hemisphericum*. This decade long investigation suggested that the logged compartment gradually recovered and resemble unlogged forest within 20 years. However the recent inventories of the logged compartment at 1 ha scale shows the residual impact of logging even after 27 years (**Table 10**; [30]). Logged plots had low floristic similarity between them (0.45 to 0.56%) and also with the unlogged plots (0.41 to 0.43%). Mantel and partial Mantel tests proved that logging was the main driver for the species composition rather than the elevation and spatial distance. Higher abundance of species belonging to canopy, intermediate and light wood categories and lower density of emergent, understory and medium wood types were recorded in the logged plots. As compared to unlogged plots, logged plots had 20–59% less above ground biomass (AGB) due to paucity of large trees, especially in the emergent and medium wood types. However, the logged plots had higher AGB in canopy and hardwood categories. These findings indicated that the compositional shifts has occurred in the logged patches and the recovery process may depend on the resurgence of emergent and medium wood categories (**Figure 6**).

#### *4.2.3 Forest dynamics in unlogged forest*

In the unlogged forest, over the study period of 1990–2016, mortality rates ranged from 0.7 to 1.2% yr.<sup>1</sup> with an average of 0.8% yr.<sup>1</sup> while the recruitment ranged from 0.4 to 1.2% yr.<sup>1</sup> with an average of 1% yr.<sup>1</sup> (**Figure 7**). The basal area of the stand showed a loss of 13.8% due to tree death and an addition of 21.6% basal area by growth of trees. Overall, it shows an increment by 7.8% of the stand basal area. During the period of 26 years, four species *Memecylon wightii* Thwaites, *Goniothalamus cardiopetalus* (Dalz.) J. Hk. & Thoms., *Clerodendrum viscosum* Vent. and *Walsura trifolia* (A. Juss.) Harms. disappeared by tree deaths and one species *Diospyros assimilis* Bedd. appeared by new recruits. A total of 73 species have registered either recruitment and/or mortality, while population density of the remaining 18 species was unchanged during 26 year period. Of these, 44 species showed decline in population density. Notable among them includes *Myristica dactyloides, Humboldtia brunonis, Palaquium ellipticum* and *Knema attenuata*, lost more than 10 individuals during the study period. Nineteen species showed increase in population density. They include *Kingiodendron pinnatum, Holigarna nigra*, *Diospyros bourdillonii* and *Leptonychia caudata* each was recorded with increase in population density of 5 individuals.


#### **Table 10.**

*Impact of selective logging on tree species richness, composition and structure, after 27 years in comparison with unlogged forest at 1 ha scale (based on census 2010–2011; [30]).*

*Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*

**Figure 6.** *Summarized results of a decade long monitoring study of logged and unlogged plots [31].*

**Figure 7.** *Recruitment and mortality rates for trees* ≥ *30 cm gbh in the unlogged forest.*

#### *4.2.4 Biomass estimation*

Live Above Ground Biomass (AGB) of individual trees were determined using the regression equation of tropical moist forest stands: AGB = exp.(2.977 + ln (ρD2H)).

Where D is the diameter at breast height in cm, H is total height in m and ρ is wood density in g cm<sup>3</sup> [32]. The estimated value ranged from 268 to 491 Mg ha<sup>1</sup> for those plots in the logged compartments and 611 to 649 Mg ha<sup>1</sup> for the unlogged compartment **Table 10**. The AGB ha<sup>1</sup> of unlogged plots of the present study is high compared to the available data on Indian forests and the other tropical forests across the continents: a mean of 287.8 105.0 Mg ha<sup>1</sup> for South America, 393

109.3 Mg ha<sup>1</sup> in Asia and 418 91.8 Mg ha<sup>1</sup> in Africa for trees 10 cm dbh [33]. In summary, the continued monitoring of the plot will enhance our capacities to understand the forest dynamics in space and time, and response of the forest to the influence of climate change.

#### **5. Forest dynamics plots in Kakachi forest, Kalakad Mundanthurai Tiger Reserve, Western Ghats**

Small scale forest dynamic plots were established in the wet evergreen forest at Kakachi in Kalakad Mundanthurai Tiger Reserve (hereafter KMTR) (8<sup>o</sup> 33' N. Lat. 77o 23'E. Long, **Figure 8**). It covers an area of 887 km<sup>2</sup> along the eastern slopes of Agasthyamalai range. The altitude ranges from 100 to 1890 m with generally steep slopes and deep valleys. KMTR supports large stretches of evergreen forests, which are contiguous to the rest of the WG, and endowed with large number of endemic and rare plant species, and provide habitats for rare animals such as Lion Tailed Macaque, Nilgiri langur, Tiger, Elephants etc. KMTR receives both South-West and North-East monsoons and being a major watershed, seven major rivers originates from the forest. These rivers meet the water requirements of the arid regions of south Tamil Nadu. Kakachi is located at 1300 m amsl and receives an annual rainfall of over 3500 mm. The rainfall is spread over 8 to 10 months in a year. The spread out of the rainfall in the study site is due to Southwest monsoon and Northeast monsoon rains. Mean maximum temperature is 24o C and minimum about 16o C [34].

*Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*

The terrain is highly undulating and is traversed by numerous mountain streams. The vegetation is characterized by three dominant tree species, *Cullenia exarillata, Palaquium ellipticum* and *Aglaia bourdillonii* [34]. Between 1993 and 1994 three 1 ha forest dynamic plots were established in an undisturbed wet evergreen forests at Kakachi, Kalakad Mundanthurai Tiger Reserve (KMTR) of Agasthyamalai range.

The principal objective of this study was to measure the changes in diversity, structure, recruitment and mortality of tree species compared to other forests within WG as well as globally. Following are the specific objectives:

(1) Determine the diversity and population structure of trees at Kakachi (2) Compare diversity and density of endemic with the widely distributed species in the site (3) Determine the overall recruitment, mortality and turnover rates of tree species.

Three 1-ha plots of 250 m x 40 m dimension were established within the wet evergreen forest during 1993 and 1994. A minimum distance of 1 km, spatially separated these plots. The plots were permanently marked using PVC pipes and all trees above 10 cm dbh at 1.3 m above ground were enumerated and tagged.

#### **5.1 Floristics and species diversity**

A total of 68 tree species >10 cm dbh were recorded from the 3 ha. The sixtyeight tree species belonged to 52 genus and 31 families. The most species rich family was Lauraceae with 12 species followed by Euphorbiaceae (7 sp.) and Myrtaceae (6 sp.). Seventeen families had only one species. *Syzygium* was the most common genus with 6 species followed by *Litsea* with 4 species. Genus with single species represented over 90% of the total genus. Shannon diversity index was 2.79 (=4.02 log<sup>2</sup> ) and the evenness index was 0.66. The number of species recorded per ha was 46.

#### **5.2 Stem density**

A total of 2116 live stems were encountered in the 3 ha at an average of 705 stems ha<sup>1</sup> . Three species *Agrostistachys borneensis* (19%), *Cullenia exarillata* (16%) and *Palaquium ellipticum* (13%) represented 45% of the stems, while the other 65 species accounted for the remaining 55%. The species abundance relationship shows that majority of the species had a density between 4 and 8 individuals per 3 ha. Seventy percent of the species had less than 10 individuals in the 3 ha plot and only 10% (7 species) had over 100 individuals. Over 3.5% of the stems were dead during the first enumeration.

#### **5.3 Basal area**

Total basal area of all the trees was 60.51 m<sup>2</sup> ha<sup>1</sup> . Two dominant species *Cullenia exarillata* and *Palaquium ellipticum* accounted for over 58% of the total basal area, while all other species individually accounted for less than 5%. Mean basal area of individual trees was 0.0769 m<sup>2</sup> ha<sup>1</sup> and ranged from 0.026 m<sup>2</sup> ha<sup>1</sup> to 0.3233 m<sup>2</sup> ha<sup>1</sup> .

#### **5.4 Life forms**

Of the 68 tree species 42 were canopy trees and 23 (35%) were understorey trees. Maximum height of canopy trees was 40 m. The tallest species is *Cullenia exarillata* with a mean height of 22 m. Canopy trees were at a higher density than understorey trees. Many of the common canopy trees were dominant component of the stand. Canopy species such as *Cullenia exarillata, Aglaia bourdillonii* and *Palaquium ellipticum* accounted for 66% (808) of the canopy trees. Among the understorey tree species *Agrostistachyis borneensis, Gomphandra coriacea,* and *Epiprinus mallotiformis* accounted for over 80% (663) of the total stems. Canopy trees were also larger in girth besides being more abundant, therefore contributed to higher total basal area 49.04 m<sup>2</sup> ha<sup>1</sup> compared to understorey trees 8.4 m<sup>2</sup> ha<sup>1</sup> .

#### **5.5 Habitat**

In terms of habit preferences there were 36 closed forest species and 33 gap species. Nineteen of the closed forest trees were canopy species and remaining 17 were gap invaders. Similarly in the understorey 14 were closed canopy species and 15 were gap species. The closed forest species were 11 times (1840) more abundant than gap species (144) and majority of the gap species contributed to less than 7 individuals per ha. Basal area of closed forest species was 22 times greater than gap species.

#### **5.6 Endemic species richness gradient**

#### *5.6.1 Species*

Thirty-three of the total 68 identified tree species (49%) in the plots were endemic to the Western Ghats. The endemic species richness increases from localised endemics to more widely distributed endemic species. Greater proportion (76%) of the species were endemic to the entire Western Ghats (EWGE, Entire Western Ghats Endemic), 18% to southern Western Ghats, (SWGE Southern Western Ghats Endemic comprising of Nilgiris and south of the Palghat gap) and 6% to Agasthyamalai (AGME Agasthyamalai Endemic) region alone (localized endemic). Some of the common endemic species are *Palaquium ellipticum*- endemic to whole of Western Ghats, *Litsea keralana* - restricted to southern Western Ghats and *Aglaia bourdillonii* - endemic to Agasthyamalai.

#### *5.6.2 Density*

Endemic species of the Western Ghats accounted for 51% (1079) of the total stems encountered in the 3 ha. EWGE were the most numerous, and accounted for 83% (893) of the stems followed by 16% (172) for AGME species and only 1.3% (14) to SWGE. The density of trees under the 3 endemic gradients is significantly different (KW = 9.84, p < 0.01). The WGE species were significantly more abundant than SWG species (Dunn's test p < 0.01). The median density value was 8 for EWGE species and 2 for SWGE species. Localized AGME species such as *Aglaia bourdillonii* was at high density. Contrary to species richness, density is high for local endemic species and highest for EWGE species but very low for SWGE species.

#### *5.6.3 Basal area*

Basal area of endemic species accounted for 94% of the total basal area, of which 95% were EWGE, 0.6% SWGE endemic and 5% AGME. Though there were only two species endemic to Agasthyamalai, one of them *Aglaia bourdilonii* was a highdensity species but accounted for only 3.3% of the basal area. Trend in basal area was also similar to density; EWGE highest followed by AGME and finally SWGE.

*Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*


**Table 11.**

*Demographic parameters across the 3 one ha plots.*

#### **5.7 Changes in recruitment, mortality and turnover of tree species over time**

Endemic species showed least change in stem density and basal area whereas widely distributed species showed greater change in both. The overall recruitment of trees was 0.86% per year and mortality 0.56% per year resulting in an annual turnover of 0.71% (**Table 11**). Thirty-three species did not show any recruitment and mortality. Forty species showed no recruitment and 37 species no mortality. The dominant species such as *Cullenia exarillata, Palaquium ellipticum, Agrostistachys borneensis* and *Aglaia bourdillonii* had low recruitment and mortality rate.

Majority of the gap species had high levels of recruitment and mortality resulting in a high turnover. Some closed forest and canopy species such as *Nageia wallichiana* (Podocarpus), *Elaeocarpus tuberculatus* and understorey species such as *Antidesma menasu, Syzygium mundagam* and *Miliusa wightiana* showed high levels of recruitment. Gap species had higher mortality and recruitment than closed forest species. Recruitment and mortality was not significantly different between canopy and understorey species. In general gap species was the major contributor to the turnover in the forest.

#### **6. Way forward**

Long-term data is essential for undestanding vegetation dynamics. Vegetation dynamics is directly related to climate variability that an ecosystem experience. Extreme events such as floods, drought and snowfall forms part of long-term variability in climate. Vegetation response to such extreme events depends upon the type and intensity of an event. Government of India has initiated two major national projects to undestand and combat the impacts of varibility in climate through understanding natural vegetation dynamics. They are, (a) Indian Long-Term Ecological Obsevatories (ILTEO) and (b) Studies of impact of climate change on Indian Forest System through long-term monitoring, an All India Coordinated Research Project (AICRP) managed by Indian Council for Forestry Research and Education (ICFRE), Dehradun. ICFRE with its nine Institutes, Forest Research Institute (FRI), Dehradun, Institute of Forest Genetics and Tree Breeding (IFGTB), Coimbatore, Institute of Wood Science and Technology (IWST), Bengaluru; Institute of Forest Biodiversity (IFB), Hyderabad; Rain Forest Research Institute (RFRI), Jorhat; Tropical Forest Research Institute (TFRI), Jabalpur; Himalayan Forest Research Institute (HFRI), Shimla; Institute of Forest Productivity (IFP), Ranchi; and other Institutions like Ashoka Trust for Research in Ecology and Environment (ATREE), Bengaluru; Indian Institute of Science (IISc) Bengaluru; French Institute, Pondicherry; and Kerala Forest Research Institute (KFRI), Peechi, Thrissur, Kerala have initiated long-term ecological monitoring studies on the effects of climatic variability on the forest ecosystem. This will be the first of its

kind in India to address climate change issues at national and international level and helps to trace footprints of climate change impacts through vegetation and also reveals to what extent our forests are resilient to change in the climate. Further it will also address the issues flagged by UNFCCC, IPCC, NAPCC, SAPCC etc.

Major objectives of the programme includes establishment of Permanent Preservation Plots (PPP) to observe and understand the changes in species diversity, composition and growth pattern due to climate change over a period of time. The methodology for selection and laying of sample plots, assessment, identification and tagging of plants is based on Centre for Tropical Forest Science (CTFS) protocol. Aimed at precision, uniformity, and large scale of international acceptance, it was decided to laydown country wide permanent plots (preferably 10 Hectare size) in major forest types of the country wherein woody individuals >1 cm diamter at breast height (DBH) would be monitored for vital parameters such as recruitment, mortality and growth in relation to climate. The study also includes dendrochronology, edaphic factors, survivality, regeneration, invasive species, dynamics of soil microflora, phenological studies, insect-pest incidence, disease infection, pollinators etc in the pemanent plot and surrounding forest area.

Complementary to this initiative Indian Government launched a new pan India research program- Indian Long Term Ecological Observatories (ILTEO) with a larger goal of assessing the influence of climate change on the biodiversity at national level. To address issues related to climate change the Government of India has set up Indian Network for Climate Change Assesment (INCCA) to provide frame work to monitor impacts of climate change, assess the drivers of climate change and to develop decision support system. It is been recognzed that climate change of one of major drivers, Long-term ecological monitoring is required to identify pattern and drivers of change. Moreover long term monitoring is required to frame the national policies and signing international conventions such as United Nations Framework Convention on Climate Change (UNFCC). There are several isolated programs monitoring the changes. However, there is a need for unified multidisplinery national level program to address the issues of climate change. All India Coordinated Research project under ICFRE is one such national level effort to address encouragement and research to climate change.

#### **Acknowledgements**

Authors are thankful to Director General, ICFRE, Dehradun, for granting All India Coordinated Research Project on Climate Change (AICRP-31). Authors also thankful to Shri Nirmalya Bala, FRI, Dehradun, National Project Coordinator for the encouragement and support. We also thank State Forest Departments of Karnataka, Kerala and Tamil Nadu for encouragement and research permissions.

*Forest Vegetation and Dynamics Studies in India DOI: http://dx.doi.org/10.5772/intechopen.97724*

#### **Author details**

Madan Prasad Singh<sup>1</sup> \*, Manohara Tattekere Nanjappa<sup>1</sup> , Sukumar Raman<sup>2</sup> , Suresh Hebbalalu Satyanatayana<sup>2</sup> , Ayyappan Narayanan<sup>3</sup> , Ganesan Renagaian<sup>4</sup> and Sreejith Kalpuzha Ashtamoorthy<sup>5</sup>

1 Institute of Wood Science and Technology (IWST), Bengaluru Karnataka, India

2 Centre for Ecological Sciences and Divecha Center for Climate Change, Indian Institute of Science, Bangalore, Karnataka, India

3 Research Scientist, French Institute, Pondicherry, India

4 Ashoka Trust for Research in Ecology and the Environment, Bangalore, Karnataka, India

5 Kerala Forest Research Institute, Peechi, Thrissur, Kerala, India

\*Address all correspondence to: mpsinghifs1989@gmail.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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