Aims of the thesis

I will address three competing theories that might explain the invertebrate diversity of sadas

o That the entire region is characterised by widespread invertebrate species that do not differentiate between sadas and the adjoining forest

communities (the null hypothesis).

o That the sada fauna is simply a subset of the fauna present in directly adjacent forest (suggesting a seral origin for the sada fauna).

o That the sada fauna is endemic and characteristic of this unusual habitat type (suggesting a special habitat of long standing).

Ground dwelling invertebrates are used to test these hypotheses because a diverse range of orders are represented by this part of the fauna, each of which potentially represents an independent test of these theories.

In addition, the remote location of the study sites and the difficulty inherent in extended stays meant that a more comprehensive sampling of the invertebrate fauna was not feasible. For example, light trapping for nocturnal insects such as moths and beetles requires access to power sources and canopy sampling is dependent upon dry foliage which cannot be guaranteed at the time of the sampling visit.

2.3 Methods

2.3.1 Sampling

Pitfall traps arranged in transects were used to target ground-active invertebrates. A total of 12 traps (plastic drinking cups, 9 cm diameter, with 20 ml of ethylene glycol as preservative) were placed along a transect running through the sada and into the adjacent forest or woodland. Past research has shown that the most reliable way of monitoring invertebrate biodiversity is to sample entire invertebrate assemblages.

2-5 This usually involves a large number and a greater variety of specimens (Andersen et al. 2004). The limitations of pitfall traps have been discussed by many authors (e.g. Luff, 1975; Topping and Sunderland, 1992; Melbourne, 1999; Southwood and Henderson, 2000) however they are still widely used for sampling over extended periods and across target groups. Pitfall catches may be influenced by factors such as trap placements, vegetation type, weather conditions and interference by animals and humans who are curious. While pitfall traps do not provide an absolute estimate of abundance they have been shown to provide a good approximation of the relative number of species in a range of habitats. Sabu and Shiju, (2010) compared the efficacy of pitfall trapping, Winkler and Berlese extraction methods for measuring ground dwelling arthropods in moist-deciduous forests in the Western Ghats and found that highest abundance and frequency of most of the represented taxa indicated pitfall trapping as the ideal method for sampling of ground-dwelling arthropods. Sabu et al. (2011) concluded that pitfall trapping was most effective for qualitative

estimates of most ground-active invertebrate groups.

2.3.2 Sampling period

Field work was conducted over three distinct climatic seasons in order to account for seasonally restricted species, i.e. summer (March – May), post monsoon (September – November) and winter (December to February) over two years, 2008 and 2009. The wettest part of the year (June-August) could not be sampled due to temporary lack of vehicular access.

2.3.3 Sorting and identifying

Pitfall traps were left open for a period of two weeks in each season. The contents of each trap were transferred into 80% ethanol in order to preserve the specimens and carefully labelled with location and date. Once in the laboratory, the specimens were separated into morphospecies on the basis of characters observed under a dissecting microscope and then classified into broad taxa (Appendix 1). I used the resolution level of morphospecies in place of true species as unit taxa still allow thorough comparisons between samples and calculations of biodiversity. In many cases specimen names are unknown due to the non-availability of identification keys and field guides for many taxa. This approach has previously been found to be effective for poorly known and species-rich taxa such as spiders and other invertebrates (Oliver

2-6 and Beattie 1996; Krell 2004). Only adult specimens were included in the data due to taxonomic uncertainties pertaining to immature invertebrates.

Arthropods collected in the pitfall traps were identified using technical journals, reference books, the internet and the input of taxonomic specialists to assist identification where appropriate. Where possible as in the case of ant species, identification was done by Dr. T. Vargehese from the Centre for Ecological Studies (CES), other invertebrate groups were identified by Dr. Peter McQuillan, University of Tasmania; scorpions were identified by Aamod Zambre. Voucher specimens of my material are deposited at the Indian Institute of Science, Bangalore collection for future reference.

2.4 Analysis

This data set was used to compare total species richness and abundance between habitat types (sada and forest) and for analysis of assemblage composition and indicator taxa for both habitats. It also analyzed the species composition over seasons and noted significant differences between year one and two if any.

The total abundance of each taxon was tabulated from the data for each season in each year and were sorted in descending order according to total abundance and then summarised in rank-abundance bar graphs. An expected result in biologically diverse communities is that some taxa are present at very low abundance and can be

indicative of a variety of ongoing processes (i.e. indicators of truly rare species in the sampled habitat or accidently occur as migrating or vagrant species). Rare species (<0.5% of the total) were removed from the dataset for some comparative analyses in order to facilitate extraction of the main trends and community patterns.

Multivariate methods of analysis were used to extract further meaning from the data. Sample sites were ordinated using PC-ORD software (McCune & Mefford, 1999) on the basis of their invertebrate fauna. Ordination is a multivariate analytical method that arranges sampling units along axes such that similar sites are close together and dissimilar sites are far apart. The result is an objective summary of the relationship between sampling units in a low dimensional species space. The goal is to reveal underlying structure in the data that represent patterns of species occurrence as

2-7 determined by environmental variables. The Non-metric Multidimensional Scaling (NMS) used in this study is an ordination method that is well suited to data that are non normal or are on arbitrary, discontinuous, or otherwise questionable scales. NMS is generally regarded as the best ordination method for community data (Faith et al. 1987). A Monte Carlo test of significance was included.

A Multi-Response Permutation Procedures (MRPP) test which is a non-parametric procedure for testing the hypothesis of no difference between two or more groups of entities was also performed. I compared species composition between seasons during different seasons, sites and habitats.

An Indicator Species Analysis (Dufresne & Legendre, 1997) provided a simple, intuitive solution to the problem of evaluating species associated with groups of sample units. It combines information on the concentration of species abundance in a particular group and the faithfulness of occurrence of a species in a particular group. It produces indicator values for each species in each group. These are tested for statistical significance using a Monte Carlo technique.