**2. Materials and methods**

#### **2.1 Study site**

957 random plots spread across Eastern Ghats of Andhra Pradesh were used in this study (Fig. 2). To typify the Eastern Ghats of Andhra Pradesh at landscape level it was classified in

b c

Fig. 1. Illustration of the matching components providing the basis for binary similarity measures a) the number of species shared by two compared units, b) the number of species unique to one of the compared plots, c) the number of species unique to the other one of the compared plots, d) the number of species not found in the two compared plots but in the

(Dis) similarity indices, which take unshared species into account, mingle different ideas of differentiation diversity (additive partitioning, multiplicative partitioning, turnover, see Jurasinski, 2007). Furthermore, they tend to be less specific as the values show less variance because d is far bigger than a, b, or c for most of the datasets recorded in the field. "Including double-zeros in the comparison between sites would result in high values of similarity for the many pairs of sites holding only a few species; this would not reflect the situation adequately" (Legendre and Legendre, 1998). Furthermore is the total inventory diversity (gamma) as a background for the calculation of d often difficult to define. When temporal changes are addressed, the question arises, whether the species pool of one time step or the whole species pool as recorded over several time steps should be regarded.

From the previous studies mentioned above it is obvious that a measure of diversity should

It compares the similarity of a focal plot to several other plots, e.g. its surrounding

It yields a single value as result, which can be directly attributed to the investigated

Its values should range between 0 and 1 for the sake of standardization and ease of

From the multi-plot similarity measures found in the literature and introduced above, none meets all these properties. Thus, we propose a new multi-plot similarity measure, which is discussed in the method section. We call it simply the coefficient of multi-plot similarity. The performance of this new measure regarding the detection of typical pattern is tested for the random and continuous datasets carried out in the Eastern Ghats of Andhra Pradesh

957 random plots spread across Eastern Ghats of Andhra Pradesh were used in this study (Fig. 2). To typify the Eastern Ghats of Andhra Pradesh at landscape level it was classified in

whole dataset (unshared species).

**1.1.3 Required features for a (Dis) similarity measures** 

neighbors taking species identity into account.

possess the following three properties:

focal plot.

(India).

**2.1 Study site** 

interpretation.

**2. Materials and methods** 

a

d

two zones viz., northern Eastern Ghats (Zone-1) and southern Eastern Ghats (Zone-2). Following the gradient in the geology, soil, bioclimatic (temperature and precipitation), altitude and degree of disturbance, the zones were characterized and analysed. For continuous enumeration a total of six transects were laid and data collected was used for analysis. These transects were laid both in zone-1 and zone-2 and distributed evenly in deciduous ecosystems.

Fig. 2. Location map of the six transects and zones of the northern and southern Eastern Ghats for random plots in the state of Andhra Pradesh, India

The areas studied are three 0.5-ha plots, which are located in the Sileru-Maredumilli ranges of the Northern Eastern Ghats of Andhra Pradesh (zone-1) and Nallamalais-Seshachalam-Nigidi hill ranges of Southern Eastern Ghats of Andhra Pradesh (zone-2) (Fig. 2). These forests are classified as South Indian Moist Deciduous and Orissa Semi evergreen forests (Champion & Seth, 1968). Three 0.5ha plots area was established at three different sites: Site 1 is located about 2 km from Sukkumamidi, a tribal hamlet in Khammam district, which receives mean annual rainfall about 1200-1400mm and elevation ranging from 400-600m. Site 2 is located about 6 km from Maredumilli tribal village in East Godavari district, receives mean annual rainfall about 1400-1600mm with an elevation of 600-800m. Site 3 is located about 2 km from Lankapakala tribal hamlet in Visakhapatnam district receives mean annual rainfall 1600-1800mm and an elevation of 800-1100m is shown in Table 1. All the three study sites were undisturbed. There are no records on the intensity and the extent of disturbance.

The next set of sample plots were laid in Southern Eastern of Andhra Pradesh (zone-2). These forests are classified as Tropical Dry Deciduous by Champion & Seth (1968). Three 0.5ha plots area were established at three different sites: Site 4 is located about 3km from

Spatial Patterns of Phytodiversity - Assessing Vegetation Using (Dis) Similarity Measures 153

inhabit Eastern Ghats region (MoEF, 1997). The Eastern Ghats also harbours one of the

Andhra Pradesh ranks first amongst the states and Union Territories in terms of area under tree cover (SFR, 2001). The total forest area of the state is 44,637 km2, which occupies 16% of the total geographical area of 2,75,068 km2 (SFR, 2001). The forests in the region are broadly classified into Semi Evergreen, Moist Deciduous, Dry Deciduous, Thorn and Scrub forests

Eastern Ghats is not formed of one particular geological formation but consist of rocks varying in origin and structure according to the location. Geologically, zone-1 is mainly of Charnockites and Khondalites (Krishnan, 1960) having red and black soil, while, zone-2 is made up of Quartzite and Slate formations with red, mixed red, black and lateritic soil. Climate of zone-1 is warm and humid with an annual precipitation of 1200-1700 mm compared to zone-2 which is hot and dry with lesser precipitation of 600-1000 mm. Topographically, zone-1 has higher altitudinal range (100-1672m) compared to zone-2 (100-

Eastern Ghats of Andhra Pradesh has 1 National Park (i.e., Sri Venkateshwara National Park) and 6 wildlife sanctuaries (viz., Papikonda Wild Life Sanctuary (WLS), Kolleru WLS, Nagarjunsagar Srisailam Tiger Reserve (NSTR) WLS, Gundla Brahmeshwarm WLS, Sri Lankamalleshwara WLS and Sri Penunsila Narsimha WLS) of these only Kolleru WLS is the largest fresh water lake in the country and also treated as one of the Ramsar convention

For the analysis of data the methodology is same as discussed in chapter-2. Six transects were laid (10 x 500m) and the individuals with 10cm were enumerated. For each of these plots the GPS location was collected using handheld Garmin E-trex GPS and other biotic and abiotic environmental parameters (slope, aspect and altitude) were gathered. The

For evaluating distance decay relationships one basically plots similarity between sites against their geographical distance (Nekola & White, 1999). So the first to calculate are similarities between sample locations. There exists a multitude of coefficients for the

Sørensen similarity (Sørensen, 1948) is used to calculate compositional similarity based on plot inventories of all tree species throughout the presented study. Sørensen similarity does satisfy the criteria of linearity, homogeneity (if all values are multiplied by the same factor the value is not changing), symmetry (independence from calculation direction, after (Janson and Vegelius, 1981) and scaling between 0 and 1 (Koleff et al., 2003). It is well

and are comparable with the existing (Champion & Seth, 1968) classification.

richest Bauxite deposits in the world.

**2.1.3 Geology, Soil and bioclimate** 

1000m).

**2.1.4 Protected area** 

wetland sites in the world.

**2.2.1 Phytosociology data analysis** 

fieldwork was conducted in January 2006 to March 2007.

**2.2.2 General considerations for statistical analysis** 

calculation of compositional resemblance of species samples.

**2.2 Methodology** 

**2.1.2 Vegetation distribution** 

Peddacheruvu, a chenchu tribal hamlet in Nallamalais of Kurnool district which receives mean annual rainfall about 900-1000mm. Site 5 is located about 4km from Talakona, a Yanadi tribal hamlet in Seshachalam hills of Chittoor district which receives mean annual rainfall 800-900mm. Site 6 is located about 2km from Kuntlapalli village, Anantapur district receives mean annual rainfall about 600-700mm. The rocks are of Kurnool-Cuddapah formations (quartzite and slate formation predominate) and altitude ranges from 400-600m. Thus, these sites show variability in rainfall pattern even though phytogeographical range is contiguous.


Table 1. Study area detail for the continuous plots on its forest type, elevation and rainfall pattern in Northern and Southern Eastern Ghats of Andhra Pradesh, India
