Seasonal variation in the diversity and species richness of spiders in the Indian Thar desert.

doi:10.21203/rs.3.rs-3336485/v1

The Thar desert constitutes a unique ecosystem in India which supports distinct fauna adapted to it. But there is only limited information about the diversity of spiders in this area. A survey on spider fauna of the Thar desert of Rajasthan was conducted using collection methods like ground collection, aerial sampling, beating and litter sampling. Alpha diversity parameters such as indices, richness and abundance was also measured. Effect of seasons on spider population was also evaluated. This study revealed the presence of 127 species of spiders belonging to 61 genera and 17 families from the Thar desert. Maximum Shannon index was during summer and Simpson index during monsoon. Highest species richness was noticed during monsoon while abundance was higher during winter. This study reveals that the Thar desert ecosystem supports a variety of habitats facing species loss due to anthropogenic disturbances and the information on indicator species like spiders can be used for conservation planning for the native fauna.

Spiders

Diversity

Seasonal dynamics

Thar desert

Rajasthan

Diversity studies are important because Hotspots of biodiversity can be identified and protected by analyzing the species list of that region (McNeely et al., 1990). Also the presence of threatened, vulnerable or endangered species is also an important criteria for selection of protected area which can be done using species inventory. Monitoring changes in species composition of threatened or indicator species through diversity studies can help in maintaining the health of environment (Woodley et al., 1995). Clarke (1986) pointed out that monitoring should be done at each habitat type several times covering all seasons in a year. Assessment of biodiversity being a common objective of systematics and conservation biology, there is an urgent need of alliance between taxonomic research and conservation studies (Kim, 1993). Taxonomic and diversity studies provide many useful data about the biodiversity of a region which in turn helps in planning conservation programmes. As current biodiversity scenarios indicate continued decline in biodiversity in future (Pereira et al., 2010), and there is still many hidden species undiscovered (Costello et al., 2015) there is an immediate need to construct a global biodiversity inventory before they become extinct. For that, there should be more efforts for increasing taxonomic expertise in various animal groups especially invertebrates.

India is a mega diverse country bestowed with variety of ecosystems. Spider diversity studies in India have been reported from forests (Sen et al., 2010; Sudhikumar et al., 2005a), grasslands (Hore & Uniyal, 2008a; 2008b), island (Tikader, 1977), wetlands (Parmar & Acharya, 2015), mangroves (Sebastian et al., 2005a), cultivated areas (Sebastian et al., 2005b; Sudhikumar et al., 2005b), coastal (Majumder & Mridha, 2004) and riparian ecosystem (Sharma et al., 2010) etc. But very few studies have been reported from desert ecosystem. Indian desert or Thar desert is located in states of Rajasthan, Gujarat, Punjab and Haryana. This is a unique ecosystem characterized by erratic, scanty rainfall and extreme temperature. Fauna and flora of this region has characteristic adaptive features to acclimatize to this ecosystem. The fauna of the Thar desert is subjected to extreme diurnal and seasonal variation in temperatures ranging as low as -5 ^oC in winter to as high as 49 ^oC in summer, causing thermal stress. Rao et al. (2012) examined the climate change scenario of Thar desert and predicted 10 to 15% increase in annual rainfall of eastern fringe and 20 to 40% increase in south while 30% decrease in northwest region. The ecological scenario of the Thar desert is changing gradually from xeric to mesic due to introduction of Indira Gandhi Nahar Pariyojna irrigation canals (Sivaperuman et al., 2009). This is leading to the point of extinction of some native species by invasion of mesic species. These canals caused adverse environmental impacts like rising of water-table which resulted in water logging and soil salinisation. Indira Gandhi Canals have been bringing seeds and propagules of exotic species from its source, Beas river to the banks of canals entirely changing the desert scrub vegetation. Old xerophytic plants were replaced by new plants with high moisture requirements. This also resulted in spreading of new weed species. Indigenous fauna that depended on xerophytic flora were also being replaced (Ali & Singhvi, 2004). Since 1960, massive efforts are going on for stabilizing shifting sand dunes of Thar desert of India (Chauhan, 2003). A study by Wang et al. (2019) showed the effect of sand dune stabilization on desert vegetation and indicated that as active sand dunes act as specific habitat for some endemic and pioneer psammophyte species, stabilization will result in loss of such species. The native fauna associated with them will also be lost. In this context, there is an urgent need to document the biodiversity of the Thar desert before it disappears. So the present study was intended to assess the diversity and species richness of spider fauna of the Indian Thar desert region of Rajasthan.

Study area

The Indian Thar desert lies between 22^o 30’ N to 32^o 05’ N latitudes and 68^o 05’ E to 75^o 45’ E longitudes. This region is bounded by Great Rann of Kutch in south, riparian sub-Himalayan plains in north, fertile plains of Indus in Pakisthan in west and Aravalli ranges in east (Singhvi & Kar, 1992). The Thar desert covers about twelve percentage of India’s geographical area. It lies extended in the Indian states of Rajasthan, Gujarat, Punjab and Haryana. 61% of the Thar desert lies in the western part of Rajasthan state. Eleven districts of Rajasthan viz. Sriganganagar, Jhunjhunu, Sikar, Barmer, Bikaner, Jaisalmer, Churu, Jodhpur, Pali and Jalore comes under Thar desert region (Tewari, 1994). In Rajasthan, the Thar desert is bounded by three cities: Jaisalmer, Bikaner and Jodhpur which is known as desert triangle. Three different habitats of the Thar desert in Jodhpur district of Rajasthan were selected for the current study viz. Semistabilized sand dunes of Osian, Rocky hills near Kailana lake and Riparian ecosystem near Jojari river.

Climate data

The Thar desert region receives precipitation during south-west monsoon season. Monsoon generally sets over the region in the beginning of July and lasts up to September. Based on 1901–2010 rainfall data, the annual rainfall in western Rajasthan is 291mm. High rainfall variability and coefficient of variation result in frequent droughts in this area (Rao & Roy, 2012). Western Rajasthan faced a maximum of 34 droughts during 1875–2009 (Attri & Tyagi, 2010).

Solar radiation is abundant in this area. Average annual solar radiation is about 22MJ/m² per day. In winter it is 15–18 MJ/m² per day and in summer it is 23-26.5MJ/m² per day (Rao & Roy, 2012). Temperature of this region is very high due to the geographical location, sandy terrain, sparse vegetation and low soil and atmospheric moisture content. Hottest month is May with mean maximum temperature of 40–42 ^o C. During winter, mean minimum temperature ranges from 4 ^o C to 14 ^o C and mean maximum temperature ranges from 22 ^o C to 29 ^o C.

During summer and rainy season wind direction is southwest and during winter it is northeast. Wind speed is 3–4 km/h during winter and 9–12 km/h during May to July. Wind speed may reach 60–80 km/h during severe dust storms. Strong dust raising winds called “Andhis” are observed in this region occasionally due to formation of strong pressure gradient.

Collection methods

Sampling was conducted following a standardized, balanced design from March 2017 to February 2019. Same effort was practiced for each factor like sampling method and sampling time. Samples were collected three times per season. Thirty 1m² quadrates were placed randomly and preferably interior into each habitat to reduce the edge effects. Four sampling techniques viz. Ground collection, Aerial sampling, Beating and Litter sampling were used at all sites for the collection of spiders. Other methods like Pitfall trapping and Sweeping were not done. Pitfall trapping was impossible in sand dunes as wind will blow sand into the trap. Sweeping was not possible as the nets got torned by the thorny desert plants.

All the preserved specimens of spiders were identified under a stereomicroscope up to family and species level with the help of available literatures (Tikader & Malhotra, 1980; Tikader, 1982; Barrion & Litsinger, 1995; Jocqué & Dippenaar-Schoeman, 2006; Murphy, 2007; Metzner, 2020; Prószyński, 2017; Sebastian & Peter, 2009).

Statistical analysis

All the statistical analyses in this study were performed using R software (R Core Team, 2020). Shannon and Simpson indices were calculated using the diversity function in Vegan package of R. Both indices were estimated for different habitats and seasons. Shannon-Wiener index (H) (Shannon & Weaver, 1949) was calculated using the formula:

Where, p_i = proportion of individuals in each species and ln = natural logarithm.

Shannon index for normal communities often range between 1.5 and 3.5, however lower values have been recorded from habitats with extreme environments. Higher the value of index greater the diversity. Shannon index is more influenced by the number of rare species.

Simpson index was calculated as:

Where, p_i = proportion of individuals in each species.

As Simpson index is inversely proportional to species diversity, it was expressed as 1-D (complement index) known as Gini-Simpson index. Gini-Simpson index falls between 0 and 1. Gini-Simpson index is a dominance index which is influenced more by the number of common species.

Species richness of different habitats and seasons were estimated using specpool function in R package Vegan. Specpool estimates number of unobserved species and add to observed richness. Estimation techniques used here to extrapolate species richness are Chao, Jackknife 1 and Jackknife 2. Chao is an abundance based estimator. It make use of number of singletons and doubletons. While Jackknife 2 is based on number of uniques and duplicates. First order Jackknife estimator is based on number of unique species.

Rank abundance curve or Whittaker plot is a two dimensional chart used to display relative species abundance in different habitats during different seasons. It is plotted with abundance rank of species on X-axis and log scale measure of relative abundance on Y-axis. Magurran (2004) have suggested diverse range of species abundance models. Of these, Null, Lognormal, Mandelbrot, Preemption and Zipf models are used here. The function radfit in R package Vegan was used to construct RACs. The plot model with lowest Akaike’s information criterion (AIC) (Akaike, 1974) was selected as the best fit model. AIC value gives indication about the amount of information lost by a model. The quality of model depends on amount of information lost.

Species diversity index during different seasons

The present study documents 127 species of spiders under 61 genera and 17 families from the Indian Thar desert. The mean diversity values during each season is shown in the Table (1). Shannon-Wiener index indicated that diversity of spiders were lower during all seasons (Fig. 1). Maximum value of Shannon index recorded was during summer (0.32) followed by winter (0.26) and monsoon (0.22). Shannon indices during various seasons were compared using Kruskal-Wallis rank sum test. There was no considerable difference in Shannon index values during three different seasons (H (2) = 3.12, p = 0.21). Pairwise comparisons using Wilcoxon test also supported this result. There was no statistically significant difference between summer and monsoon (p = 0.230), summer and winter (p = 0.740) and monsoon and winter (p = 0.740). Calculation of Gini-Simpson index showed that maximum value was during monsoon (0.59) followed by summer (0.49) and winter (0.47). These values show that spider diversity was low during all seasons (Table 1 & Fig. 2). Unlike Shannon index, values of Gini-Simpson index showed substantial difference between three seasons in the Kruskal-Wallis test (H (2) = 6.50, p = 0.04). But pairwise comparisons of seasons using Wilcoxon test revealed that only the Gini-Simpson index values between summer and winter was significantly different (p = 0.061). Gini-Simpson indices of summer and monsoon (p = 0.740) and monsoon and winter (p = 0.790) did not differ significantly.

Table 1

Diversity indices of spiders during each season
Season	Shannon		Gini-Simpson
Season	Mean	SE	Mean	SE
Summer	0.32	0.50	0.49	0.42
Monsoon	0.22	0.43	0.59	0.43
Winter	0.26	0.44	0.47	0.43

Species richness of spiders during different seasons

Species richness varied during different seasons. During monsoon highest richness was noticed (89 species) followed by winter (87 species). Least richness was observed during summer (68 species). Species accumulation curve and three estimators of species richness (Chao, Jackknife1 and Jackknife2) suggested a total richness between 101 and 121 species during summer (Table 2). SAC did not approach asymptote suggesting that sampling was not adequate to represent the full spider species richness during summer (Fig. 3). Chao, Jackknife1 and Jackknife2 estimators were very far from asymptote with slopes of 2.91, 4.18 and 4.98 (Fig. 4). 21 species (30.8%) collected during summer were singletons, 13 species (19.1%) were doubletons, 35 (51.4%) were uniques and another 13 species (19.1%) were duplicates (Table 3).

Species accumulation curve during monsoon showed that the number of species didn’t approach asymptote, indicating a higher diversity of spiders than those sampled during the study (Fig. 5). Among the richness estimators Jackknife2 predicted highest number of 160.11 species. Chao estimated the total species pool to be 146.95 ± 23.03 and Jackknife1 estimated 133.39 ± 16.21 species (Table 2). Comparison of the Chao, Jackknife1 and Jackknife2 estimated values with the observed species richness revealed that the study sites were under-sampled during monsoon. All of the estimators did not approach asymptote (Fig. 6). Besides that, 34.8% (31 species) of the species collected during monsoon were represented by a single specimen (singletons) and 26.9% (24 species) by just two specimens (doubletons). 47 species (52.8%) were uniques and 18 species (20.2%) were duplicates (Table 3).

Species accumulation curve during winter suggested that further sampling might have added more species to the richness value (Fig. 7). Slope of the SAC (Slope = 2.56) revealed that the curve did not reached a plateu phase. Estimates of species richness by Chao, Jackknife1 and Jackknife2 proposed a total diversity of 205.06 ± 51.25 species, 134.22 ± 15.59 species and 170.30 species respectively during winter (Table 2). Estimated species richness of spiders by Chao, Jackknife1 and Jackknife2 were found to be greater than observed number of species. None of the estimators approached asymptote suggesting that the sampling was not sufficient during winter (Fig. 8). Species with at most one observation was 43.6% (38 species) and two observations was 13.7% (12 species) during winter. 57.4% (50 species) were encountered in only one sample and 11.4% (10 species) in two samples (Table 3).

Table 2

Richness estimates for each season using different estimators
Season	Observed richness	Chao ± SE	jack1 ± SE	jack2
SUM	68	112.50 ± 20.57	101.06 ± 10.60	121.29
MON	89	146.95 ± 23.03	133.39 ± 16.21	160.11
WIN	87	205.06 ± 51.25	134.22 ± 15.59	170.30

Table 3

Observed, Singleton, Doubleton, Unique and Duplicate species richness during different seasons
Season	Total no. of individuals	Observed no. of species	Singletons	Doubletons	Uniques	Duplicates
SUM	455	68	21	13	35	13
MON	627	89	31	24	47	18
WIN	643	87	38	12	50	10

Kruskal-Wallis analysis was done to evaluate whether there is difference in species richness between the three seasons. Outputs showed that there was a statistically significant difference between species richness of three different seasons (H (2) = 11.95, p = 0.003). Significant difference in species richness between seasons was reflected in the result of Kruskal-Wallis test but there was no clue about which pairs of seasons are different. For that, pairwise comparisons using Wilcoxon rank sum test was conducted. The pairwise comparison revealed that only the species richness between summer and monsoon are significantly different (p = 0.002). Species richness between summer and winter (p = 0.228) and monsoon and winter (p = 0.060) were not significantly different.

The study of seasonal dynamics revealed low diversity during all seasons. Observed species richness was highest during monsoon and lowest during summer. Soil moisture built up during monsoon results in increased vigour of desert vegetation and senescence at the end of monsoon (Potdar et al., 1993). Desert plants overcome the stressful period of hot dry summer by hibernation and dormancy and quick growth during monsoon. Satyanarayan & Gaur (1967) studied the changes of vegetation in the Thar desert and reported that species composition and density of desert plants is least in summer and greater in middle of monsoon due to fast growth of annuals and sprouting of perennials. Vegetation greenness may have promoted high species richness of spiders during monsoon in this study. Studies have shown that formation of new green leaves during monsoon result in population growth of phytophagous insects which in turn increase the density of entomophagous spiders (Wolda, 1978; Nakamura et al., 2005).

Abundance of spiders during different seasons

Tmarus kotigeharus was the most abundant species during summer with 86 individuals. After T. kotigeharus the two most abundant species were Mogrus rajasthanensis and Tmarus sp.1 with 29 and 24 individuals respectively. 20 species had extremely low abundance and were represented by only one individual during summer. During monsoon Oxyopes chittrae was the most abundant species with 81 individuals. After that Larinia phthisica and Oxyopes gujaratensis were equally abundant with 49 individuals each. In monsoon period 31 species had very low abundance with only one individual. T. kotigeharus was represented by 131 individuals, making it the most abundant species during winter. It was followed by Oecobius putus with 78 individuals and Tmarus sp.1 with 28 individuals. More species with extremely low abundance i.e. species represented by only one individual was found during winter (38 species). Highest number of individuals were collected during winter (643 individuals) making it the season with maximum abundance of spiders. After winter maximum number of individuals were recorded during monsoon (627 individuals) followed by summer (402 individuals). Maximum abundance of spiders was detected during winter season. The low evapotranspiration rate during winter which aided vegetation growth (Lamchin et al., 2018) may have indirectly affected spider abundance.

Rank abundance curves (RAC)

Rank abundance curves were constructed by plotting relative abundance of spider species against their rank in abundance. Five species abundance models viz. Null, Preemption, Lognormal, Zipf and Mandelbrot were tested. The model with lowest Akaike’s information criterion (AIC) value was considered as the best fit model.

The best fits of RAC were obtained for the Zipf model in all habitats during summer (Fig. 9). Rank abundance plots highlighted differences in evenness amongst three habitats during monsoon (Fig. 10). Theoretical models predicted Mandelbrot model as best fit for showing species abundance distribution in Osian and Kailana. The RAC of Jojari fitted better to the Zipf model. The best fit species abundance model for Osian and Jojari were found to be Zipf model and for Kailana the best fit was Mandelbrot during winter (Fig. 11.) (Table 4.).

Table 4

The AIC values for the five fitted models (Null, Preemption, Lognormal, Zipf and Mandelbrot) for each habitat during different seasons
Species abundance model	AIC Value during different seasons in each habitat
	Summer			Monsoon			Winter
	K	O	J	K	O	J	K	O	J
Null	115.82	16.62	34.56	68.04	77.31	35.08	34.93	135.66	243.38
Preemption	101.18	17.05	25.48	60.70	31.24	30.31	27.09	90.72	177.09
Lognormal	30.39	6.67	8.97	21.09	24.06	11.01	13.32	26.53	51.23
Zipf	10.79	4.10	4.48	9.05	36.45	2.76	10.37	6.20	25.06
Mandelbrot	10.79	4.23	5.55	6.43	5.17	2.97	4.02	6.20	25.06

Abbreviations: K-Kailana, O-Osian, J-Jojari

Rank abundance curves were steeper in all cases. The slope of RAC was considered as the measure of evenness. The best fits of RAC of spider assemblages in different habitats of the Thar desert ranged from Zipf model to Mandelbrot model indicating heterogenous and species rich environment (Do et al., 2014). Previous studies have reported good fitting results with Zipf and Mandelbrot models to many assemblages of animals. Species abundance distributions of insects associated with Cucurbit fruits in southern Cameroon showed Zipf-Mandelbrot to Mandelbrot models (Mokam et al., 2014). Rank abundance curves of butterfly communities in 5 habitat types in Thailand were fitted to Zipf-Mandelbrot models (Chaianunporn & Chaianunporn, 2019). Spider assemblages of canopy of north temperate hardwood forests were best fitted by Zipf-Mandelbrot rank abundance distribution model (Larrivee & Buddle, 2009).

The present study documents 127 species of spiders under 61 genera and 17 families from the Thar desert of Rajasthan. Shannon-Wiener index indicated that diversity of spiders were lower during all seasons. Maximum of Shannon index recorded was during summer (0.32) followed by winter (0.26) and monsoon (0.22). Calculation of Gini-Simpson index explained that maximum was found during monsoon (0.59) followed by summer (0.49) and winter (0.47). During monsoon highest observed richness was noticed (89 species) followed by winter (87 species). Least richness was observed during summer (68 species). Species accumulation curves during all seasons showed that the number of species did not approached asymptote, indicating a higher diversity of spiders than those sampled during the study. Highest number of individuals were collected during winter (643 individuals) making it the season with maximum abundance of spiders. The best fits of Rank abundance curves were obtained for the Zipf model in all habitats during summer. During monsoon theoretical models predicted Mandelbrot model as best fit for showing species abundance distribution in Osian and Kailana and that of Jojari fitted better to the Zipf model. The best fit species abundance model for Osian and Jojari were found to be Zipf model and for Kailana the best fit was Mandelbrot during winter. RACs of all habitats during all seasons were with steeper slopes except Osian during summer emphasizing low evenness.

Acknowledgments

Authors are thankful to the Principal Christ college, Irinjalakuda, Kerala for providing all the necessary facilities. We are very much indebted to lab members of Centre for animal taxonomy and ecology for their valuable suggestions.

No funding was received to assist with the preparation of this manuscript. Authors also declare that we have no conflict of interest.

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Seasonal variation in the diversity and species richness of spiders in the Indian Thar desert.

Status:

Version 1

Abstract

Figures

Introduction

Material and methods