Revealing Hidden Diversity and Community Dynamics of Land Snails through DNA Barcoding: Implications for Conservation and Ecological Studies

doi:10.21203/rs.3.rs-3084235/v1

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Revealing Hidden Diversity and Community Dynamics of Land Snails through DNA Barcoding: Implications for Conservation and Ecological Studies

https://doi.org/10.21203/rs.3.rs-3084235/v1

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published 16 Apr, 2024

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Land snails play a crucial role in maintaining ecosystem sustainability within their habitats. Therefore, understanding the characteristics of their communities is vital for ecological studies and the development of effective conservation strategies. In this study, we employed DNA barcoding (COI gene) to identify land snails inhabiting the Hyrcanian Forest. Furthermore, we examined the variations in their community composition along elevational gradients. Snail samples were collected from three distinct elevations in three different forest locations within the Hyrcanian area of Iran. Through our comprehensive analysis, we identified a total of 10 OTUs, which were further classified into seven families and nine genera. Remarkably, five of these genera had never been reported in the study region before. By employing statistical analyses such as ANOVA and PERMANOVA, we determined significant differences in the features of snail communities across different elevations. Interestingly, we observed a decline in OTU richness with increasing elevation; however, the maximum abundance of snails was found at higher elevations. The unique climatic conditions and spatial distribution of precipitation from lowlands to highlands, as well as from west to east, make the Hyrcanian forests an ideal case study area for understanding the dynamics of land snail communities. In summary, this study provides novel insights into the land snail communities thriving in the Hyrcanian forests. The findings from our research can contribute significantly to the development of effective conservation management strategies for forest ecosystems. By understanding the factors influencing the distribution and composition of land snail communities, we can make informed decisions to protect and preserve these valuable organisms and the balance they maintain within their habitats.

Earth and environmental sciences/Ecology

Earth and environmental sciences/Environmental sciences

land snail

forest

DNA barcoding

community composition

elevational incline

Conservation

Land snails belong to the Mollusca phylum, with more than 24,000 recognized species standing as one of the most diverse groups of animals on Earth (Brown, and Lydeard 2010; Chavhan et al., 2015). These ancient species due to their position in the food web as decomposers and their role as an important calcium source for other animals like birds, snakes, and mammals, play a vital role in ensuring the sustainability of their habitat (Rull et al., 2019; Dempsey et al., 2020). This group of gastropods inhabits a variety of terrestrial environments, including leaf litter, soil, rocks, and trees. Different species have specific habitat preferences based on factors such as moisture, temperature, and soil composition (Jurickova et al., 2008). Soil chemical parameters, particularly calcium availability, play an important role in their population density and shell formation (Millar and Waite, 2002; Hotopp, 2002). Additionally, land snails’ dispersal and activity are influenced by elevation. Many studies have shown a decrease in land snail species richness towards high elevations, accompanied by changes in abundance and species composition (Aubry et al., 2005; Wronski and Hausdorf, 2008; Liew et al., 2010; Dourson and Langdon, 2012).

Their specific habitat needs and limited mobility make them reliable indicators for evaluating environmental conditions and habitat quality. Furthermore, land snails serve as an ideal model for ecological genetic studies because of their ecological responses to environmental challenges like climate change, introduced species, and habitat fragmentation (Shimizu and Ueshima, 2000). Gaining a comprehensive understanding of the correlation between snail communities and environmental factors, especially in spatial dimensions like altitudinal gradients, provides conservation managers with valuable insights for protecting biodiversity and habitat conservation (Mathias et al., 2001; Goodacre, 2002; Arnaud et al., 2003; Jackson and Blois 2015; Nicolai and Ansart, 2017).

Land snails are one of the indispensable components of forest ecosystems. In recent years due to several reasons like the presence of invasive or non-native species and, climate change the global forest cover has faced a drastic reduction (da Silva et al., 2019). since land snails serve as a bioindicator that offers valuable insights into the overall health and diversity of their ecosystem, evaluating their biodiversity and community characteristics in forest ecosystems yields valuable information for effective forest conservation.

In this regard, the Hyrcanian forest of Iran provides a fascinating case study. This forest is the most important remnant of the Cenozoic forests and a refuge for ancient species in the last ice age (Tarkhnishvili et al., 2012; Dufresnes et al., 2016; Ahmadzadeh et al. 2020; Amiri et al., 2021; Saberi-Pirooz et al., 2021) and also a unique habitat for endemic land snails. While some studies have identified land snail species in the Hyrcanian forest, there is limited research on community composition and ecological analyses of these snails, with approximately 40 species reported thus far (Issel, 1865; Forcart, 1935; Starmuhlner and Edlauer, 1957; Yasini, 1976; Eliazian et al., 1979; Mansourian, 2005; Ahmadi, 2012).

Furthermore, the identification of snails in these studies was primarily based on morphological characteristics. Despite the extensive research conducted on land snail identification using morphological features in various regions, there remain numerous species with an uncertain systematic status. This lack of clarity can pose significant challenges for ecological studies (Tattersfield et al., 2001). Land snail morphological identification, which relies on conchology (the study of shells), is prone to frequent misidentification, particularly for small species, due to shell variations influenced by habitat-specific environmental factors (Nekola and Coles, 2010; Smith and Hendricks, 2013). In addition, land snails, like numerous other organisms, can possess cryptic species that exhibit close morphological resemblance despite significant genetic differentiation. Additionally, the expertise required to accurately recall species names and identify morphological aspects of land snails is limited among biologists. (Waugh, 2007; Zeng et al., 2017; Mouahid et al., 2018). Exclusively relying on morphological characteristics for species identification can lead to misidentification, significantly impacting biodiversity evaluation crucial for conservation management (Bickford et al., 2007). To address these challenges, integrating morphological identification with other methods, such as DNA barcoding and molecular techniques, can improve the efficiency of land snail species identification. In the past decade, DNA barcoding has emerged as a rapid and highly accurate method for species identification, surpassing traditional morphology-based approaches (Ezzine et al., 2018; Galan et al., 2018; Nantarat et al., 2019).

In this study, our objective was to identify terrestrial snails inhabiting the Hyrcanian forest by employing the DNA barcode method, targeting the COI gene. Following that we assessed their abundance, species richness, and composition along a gradient of elevation, comprising three distinct elevational levels within our study area. By conducting this analysis, we aimed to gain insights into the distribution patterns and ecological dynamics of land snails across different elevations within the forest. We also attempted to determine whether soil parameters were correlated with the presence of land snails. Eventually, we aimed to contribute to a deeper understanding of the ecological dynamics, species composition, and environmental interactions of land snails within this unique forest ecosystem. Such knowledge can be invaluable for conservation efforts, ecosystem management, and the preservation of biodiversity in the Hyrcanian forest and similar habitats.

Study area

Hyrcanian forests which are known as one of the most important biomes of the world extend from the Talish region in the southeast of the Republic of Azerbaijan to the Golestan Province in the northeast of Iran, with an area of approximately 50000 km². These forests stretch from sea level to elevations of 2800 meters, three altitudinal belts were recognized across the Hyrcanian forests, i.e. lowland, sub-montane, and montane forests (Hamzeh’ee et al., 2008; Siadati et al., 2010). Spatial analysis of seasonal precipitation shows that the Hyrcanian region has different patterns in the western and eastern parts and annual rainfall decreases from west to east (Akhani et al., 2010). The ecological coefficient of drought in the region is insignificant, as a whole, the Hyrcanian climate in the east is the warm Mediterranean, and in the central and western parts is temperate and semi-temperate Mediterranean, and from time to time temperate and dry (Talebi et al., 2014). This special natural world heritage is a unique source of biodiversity for the Northern Hemisphere which has universal importance beyond political boundaries (Gutleb and Wieser, 2002). Furthermore, these forests provide valuable ecosystem services that are vital for local people and these benefits depend on the biodiversity of these forests (Scharnweber et al., 2007; Tohidfar et al., 2016).

Sampling

Snail collecting was carried out in Spring 2021. Due to land snails being nocturnal, sampling was performed on cloudy days (Sallam and El-Wakeil 2012). Three locations were selected for sampling along with Caspian Hyrcanian forests in Kordkoy (Forest 1), Amol (Forest 2), and Tonekabon (Forest 3). At each location, three sampling sites were specified in an elevation slope approximately 170m to 1600m height from sea level (Elevation 1, Elevation 2, and Elevation 3 that demonstrate the highest elevation to lowest elevation in each location respectively) (Fig. 1 and Table 1). Three plots of 3m×3m were applied over an area of about 150m² in each elevation (Clergeau et al., 2011; Horsak et al., 2013; Nurinsiyah et al., 2016). Snail species were collected by hand and then relaxed in the water for a day. Subsequently, they were preserved in 96% ethanol. A total of 679 samples were collected from 27 plots across nine elevations. Furthermore, topsoil was collected from each plot and transported in a plastic bag to the laboratory for measurement of some physicochemical parameters. In the following F1, F2, and, F3 refer to Forest 1, Forest 2, and Forest 3, and also E1, E2, and E3 refer to Elevation 1, Elevation 2, and Elevation 3 respectively.

Table 1

Locations of the sampling sites
Location	Elevation (m)	Latitude	Longitude	Code
Kordkoy	1097	36.701583 N	54.10025 E	F1-E1
Kordkoy	609	36.714306 N	54.105917 E	F1-E2
Kordkoy	169	36.743389 N	54.117028 E	F1-E3
Amol	560	36.358169 N	52.313897 E	F2-E1
Amol	423	36.369101 N	52.320888 E	F2-E2
Amol	225	36.396889 N	52.3405 E	F2-E3
Tonekabon	1611	36.480142 N	50.856114 E	F3-E1
Tonekabon	833	36.591972 N	50.835333 E	F3-E2
Tonekabon	492	36.662722 N	50.812583 E	F3-E3

Laboratory procedures

Land snail samples were assigned into morphospecies in the laboratory. The identification of individuals was done by available morphological keys identification (Eliazian et al., 1979; Dourson and Dourson, 2006; Perez et al., 2008; Getz et al., 2018). A total of 16 morphospecies were distinguished from the collected samples within the study area. For the molecular investigation, 37 specimens (a minimum of two samples from each morphospecies) were chosen. Total DNA of selected samples was extracted using a high-salt method (Sambrook and Russell, 2001). A fragment of the mitochondrial cytochrome c oxidase subunit 1 (COI) gene was used for the barcoding study. The primers employed in this study encompassed LCO 1490/HCO 2198 (Folmer et al., 1994) and HCO2198-JJ/LCO1490-JJ (Astrin and Stüben, 2008). Polymerase chain reactions (PCRs) were applied in a total volume of 25 µl, including 10.5 µl of ddH₂O, 12.5 µl of Mastermix Red, (Amplicon, Copenhagen, Denmark) 0.5-1 µl of each primer (10 pmol/µl) and 1 µl of template DNA. PCR cycling for LCO 1490/HCO 2198 was run under the following condition: 94˚C for 5 min, 94˚C for 30 S (repeated for 35 cycles), 48˚C for 30 S, 72˚C for 1 min, and finally, an extension cycle at 72˚C for 5 min and the PCR condition for HCO2198-JJ/LCO1490-JJ was 94˚C for 1 min, 94˚C for 30 S (repeated for 5 cycles), 47˚C for 90 S, 72˚C for 1 min, 94˚C for 30 S (repeated for 35 cycles), 51˚C for 90 S, 72˚C for 1 min and a final extension cycle at 72˚C for 5 min. PCR products quality were surveyed using 1% agarose gel stained with Safe-Red. Then the acceptable amplicons were sent to Pishgam Company (Tehran, Iran) for purification and sequencing.

Measurement of soil Physico-chemical properties

Soil samples were obtained from the central area of each plot using a spade, reaching a depth of up to 10 cm, to assess the physicochemical properties of the soil. The collected soil samples from three plots of each elevation were combined. Six factors including soil pH, %saturation moisture, total calcium (Ca), exchangeable calcium (Ca⁺⁺), total magnesium (Mg), and exchangeable magnesium (Mg⁺⁺) measured using standard methods by Research Institute of Forest and Rangeland (Tehran, Iran).

Genetic analysis

DNA sequences of 36 individuals were edited using Geneious Prime v. 2022.1.1 (www.geneious.com). All newly obtained sequences were deposited to GenBank (Table 2). The sequences were checked in NCBI (https://blast.ncbi.nlm.nih.gov/) by the Standard Nucleotide Basic Local Alignment Search Tool (BLASTn) (Altschul et al., 1990) and also Barcode of Life Data Systems (BOLD) (Ratnasingham and Hebert, 200; https://www.boldsystems.org/). Alignments were obtained with MAFFT 7 online version (Katoh et al., 2002). The best-fit evolutionary model was determined GTR + I + G model using MrModeltest V.2.3 (Nylander, 2004) according to Akaike’s Information Criterion (Akaike, 1974). Phylogenetic trees were constructed using both Bayesian Inference (BI) and maximum likelihood (ML) methods. Enchytraeidae sp. was considered as an outgroup. MrBayes was accomplished with MrBayes version 3.2. (Ronquist et al., 2012) under two independent runs (four chains for each run) for 5×10⁶ generations and sampling trees every 100 generations. Finally, 10% of the trees were cast off as burn-in. Tracer V.1.7 (Rambaut et al., 2018) was used to assess the efficiency of runs. Maximum Likelihood tree was programmed with RAxML v.8.2 (Stamatakis, 2014) under the GTRGAMMA model with 1000 pseudoreplicates. Uncorrected genetic distances (p-distances) among species were calculated by MEGA11 (Tamura et al., 2021).

Table 2

List of land snails identified in this study
Code ID	OTU	Family	Genus	Species	Location Code	Accession number
ES3422	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F3-E1	OR189157
ES3432	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F3-E3	OR189158
ES3388	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F3-E3	OR189159
ES3317	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F1-E1	OR189150
ES3353	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F1-E3	OR189156
ES3303	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F1-E1	OR189151
ES3337	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F1-E2	OR189152
ES3302	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F2-E3	OR189149
ES3350	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F1-E3	OR189155
ES3338	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F1-E2	OR189153
ES3293	OTU 1	Cyclophoridae	Caspicyclotus	Caspicyclotus sieversi	F2-E2	OR189147
ES3342	OTU 2	Pomatiidae	Pomatias	Pomatias Rivulare	F1-E3	OR189154
ES3299	OTU 2	Pomatiidae	Pomatias	Pomatias Rivulare	F2-E1	OR189148
ES3260	OTU 2	Pomatiidae	Pomatias	Pomatias Rivulare	F3-E1	OR189145
ES3276	OTU 2	Pomatiidae	Pomatias	Pomatias Rivulare	F2-E2	OR189146
ES3419	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E1	OR189170
ES3421	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E1	OR189171
ES3426	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E1	OR189173
ES3435	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E3	OR189176
ES3439	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E3	OR189180
ES3438	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E3	OR189179
ES3364	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E3	OR189161
ES3436	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F2-E3	OR189177
ES3379	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E3	OR189168
ES3437	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E3	OR189178
ES3371	OTU 3	Helicidae	Caucasotachea	Caucasotachea Leuaranea	F3-E3	OR189162
ES3387	OTU 4	Hygromiidae	Pyrenaearia	-	F3-E3	OR189169
ES3375	OTU 4	Hygromiidae	Pyrenaearia	-	F3-E3	OR189165
ES3376	OTU 4	Hygromiidae	Pyrenaearia	-	F3-E3	OR189166
ES3377	OTU 5	Hygromiidae	Pyrenaearia	-	F3-E3	OR189167
ES3440	OTU 6	Helicidae	Theba	-	F3-E3	OR189181
ES3373	OTU 6	Helicidae	Theba	-	F3-E3	OR189164
ES3434	OTU 7	Hygromiidae	Dioscuria	-	F3-E3	OR189175
ES3431	OTU 8	Pupillidae	Pupilla	-	F1-E3	OR189174
ES3425	OTU 8	Pupillidae	Pupilla	-	F3-E2	OR189172
ES3360	OTU 9	Orculidae	Schileykula	-	F3-E3	OR189160
ES3328	OTU 10	Oxychilidae	Oxychilus	Oxychilus filicum -	F1-E2	OR189163

Species-delimitation

To infer hypothetical candidate species, two widely-used statistical methods of species delimitation were employed (automatic barcode gap discovery (ABGD (Puillandre et al., 2012)) and Bayesian implementation of the Poisson tree processes (bPTP (Zhang et al., 2013))). ABGD analysis is a clustering method based on the pairwise distance between species sequences. It was performed on ABGD Web Server (https://bioinfo.mnhn.fr/abi/public/abgd/abgdweb.html) using Kimura (K80) distance with the default Ts/Tv ratio (2.0) and the following conditions: range of prior intraspecific divergence from 0.01(Pmin) to 0.1 (Pmax) with 20 steps in between, X (relative gap width): 0.05 and Nbin: 10 (Mason et al., 2020).

bPTP is a tree-based method that required a non-ultrametric phylogenetic tree as input. Analysis was carried out on the bPTP web server (Species delimitation server (h-its.org)) using a rooted RAxML tree for 500,000 MCMC generations, with 0.1 of samples conservatively discarded as burn-in (Mason et al., 2020).

Statistical Analyses

Statistical analysis was performed using R v. 4.0.3 (R Core Team., 2020). Two-way analysis of variance (two-way ANOVA), followed by two-sided Tukey HSD tests, was conducted to assess the differences in total snail density, total OTUs diversity, and Shannon-Wiener diversity index (biodiversity metrics) among different elevations (three levels) in each forest. The statistical analyses were conducted using the "aov()" function in R. Assumptions of homogeneity of variances (tested with Levene's test, p > 0.05) and normality of residuals (tested with Shapiro-Wilk test, p > 0.05) were checked using the R package v. 1.2-7 in R (Fox et al., 2007).

To assess the dissimilarities among snail communities at different elevations within each forest (β-diversity), we utilized the betapart package (Baselga et al., 2018) in R with the Jaccard dissimilarity index. β-diversity was employed to measure how species compositions among samples have changed across the area (Graham and Fine, 2008). This approach offers a theoretical framework for partitioning total dissimilarity into nestedness (species gains or losses) and turnover components (species replacement) (Baselga, 2010).

Biodiversity metrics were calculated to assess the snail communities using various measures. The Shannon-Wiener diversity index (H) was calculated using the vegan package (v. 1.17-8) in R. Additionally, the R package Picante (Kembel et al., 2010) was utilized to calculate phylogenetic diversity (PD) and mean pairwise distance (MPD) between pairs of communities.

To examine the spatial compositional differences in snail compositions, permutational multivariate analysis of variance (PERMANOVA) was employed. Permutations of residuals (n = 9999) were performed under the reduced model, following the same factorial design as the univariate analysis. The Sorensen dissimilarity matrices were used for the analysis. In cases where significant differences were found, the SIMPER routine was applied to determine the proportional contribution of each species and main group to the observed pairwise dissimilarity in composition. The SIMPER results included species with a cumulative dissimilarity cut-off of 70% (Clarke, 1993). Both the PERMANOVA and SIMPER analyses were conducted using the vegan package.

Additionally, Canonical Correspondence Analysis (CCA) was employed as a multivariate statistical approach to investigate the relationship between species and environmental variables. The analysis utilized a dataset containing the Operational OTUs present in each forest, and six soil variables were selected as explanatory factors. Before conducting the analysis, the environmental data underwent initial screening using the Principal Component Analysis (PCA) methodology. The entire variation in the environmental data was explained by the initial six principal components (PCs). Prominent variables were identified by considering the highest absolute loading values within each PC. Subsequently, two parameters were chosen for further analysis after the screening process.

Molecular and phylogenetic analyses

Based on Cytochrome oxidase I (COI) (596bp) sequences of 37 individuals, three sequences could be assigned to species named Pomatias rivulare, Oxychilus filicum, and Caucasotachea leucoranea and six of them were assigned to five genera named Pyrenaearia, Theba, Dioscuria, Pupilla, and Schileykula. one Sequences weren’t assigned with any sequences in NCBI and BOLD data sets which means it’s the first barcoding study on this species. Based on shell features this OTU was identified as Caspicyclotus sieversi (see Table 2). The p-distance between OTUs ranged from 0.016 to 0.35. Our criterion for categorization of sequences to OTU was more than eight percent genetic distances among sequences (Table 3). Species delimitation with bPTP resulted in 10 putative species for the dataset and most of them were supported with high values (> 80%). The ABGD analysis yielded 7–17 hypothetical OTU using about 0.1–0.01 maximum intraspecific divergence (Fig. S1). Furthermore, the phylogenetic tree revealed similar terminals (Fig. 2). Totally, 10 OTUs were recognized in this study which is categorized into seven families named Cyclophoridae, Pomatiidae, Helicidae, Hygromiidae, Pupillidae, Orculidae, and Oxychilidae.

Table 3

Uncorrected genetic distances (p - distances) between land snail OTUs based on COI gene
	OTU 1	OTU 2	OTU 3	OTU 4	OTU 5	OTU 6	OTU 7	OTU 8
OTU 1
OTU 2	0.27
OTU 3	0.31	0.31
OTU 4	0.32	0.29	0.2
OTU 5	0.31	0.31	0.2	0.09
OTU 6	0.32	0.28	0.21	0.11	0.11
OTU 7	0.31	0.28	0.19	0.08	0.09	0.11
OTU 8	0.3	0.3	0.23	0.2	0.19	0.2	0.18
OTU 9	0.32	0.33	0.26	0.27	0.25	0.26	0.26	0.23
OTU 10	0.31	0.28	0.23	0.19	0.21	0.19	0.19	0.21	0.25

Comparison of land snail abundance and OTUs diversity

Exploring the abundance of land snails between three forests shows a considerable difference in snail abundance in Forest 3. As the bar chart illustrates (Fig. 3) there is a bit of decline in abundance from Forest 1 to Forets 2 then it rises by far in Forest 3. In addition, comparing three elevations in each forest demonstrate that lowlands have less abundance than the highest elevations in all forests. Comparing OTUs richness in all forests indicated the number of OTUs had decreased in high elevations (Fig. 4). Overall, the highest elevation in Forest 3 (F3-E1) shows the most abundance and the maximum number of OTUs found in the lowest elevation of this forest.

The results of ANOVA indicated significant effects of elevations, forests, and interaction (Table 4). Based on the total OUTs diversity and also Shannon-Wiener diversity dataset, t-test analysis showed that there was a significant difference between high elevation (E1) and lowland (E3) in Forest 2. Additionally, the highest elevation in Forest 1 exhibited significant differences when compared to the mid and low elevations within this forest (E2 and E3). Furthermore, the density of OTUs in the lower elevation of Forest 3 (E3) differed significantly from both the high elevation (E1) and mid-elevation (E2) in this forest, also Forest 3 was different from the other two locations in the density of OTUs. In addition, the results indicate a significant different between highlands and lowlands in Forest 2 and Forest 3 (See Table S1).

Table 4

Summary of statistical analysis of ANOVA including Density of total snails, diversity of OTUs, and Shannon-Wiener diversity index
Data set	ANOVA
Data set	Forest	Elevation	Forest: Elevation
Density of total snails	F_2,18 = 170.67 p = 1.99e-12	F_2,18 = 152.22 p = 5.26e-12	F_4,18 = 87.89 p = 1.48e-11
Diversity of total OTUs	F_2,18 = 19.44 p = 3.18e-05	F_2,18 = 49.78 p = 4.63e-08	F_4,18 = 12.44 p = 5.00e-05
Shannon-Wiener diversity index	F_2,18 = 10.693 p = 0.00087	F_2,18 = 55.988 p = 1.87e-08	F_4,18 = 3.928 p = 0.01831

Investigation of β-diversity partitioning figured out that the spatial turnover portion occurred between three elevations in Forest 3. However, Forest 2 and Forest 1 had different results, and nestedness was also detected. Generally, the β-diversity index was between 0.5 to 0.8 in all datasets (Table 5). All forests showed an increase in PD values as elevation increased. Conversely, the MPD values remained relatively consistent across the three elevations within each forest. The result of the Shannon-Wiener diversity index is shown in Table S2.

Table 5

β-diversity, phylogenetic diversity (PD), mean pairwise distance (MPD) for each forest and every elevation
Location	Date Set	Beta diversity			PD	MPD
Location	Date Set	Turnover	Nestedness	Total β-diversity	PD	MPD
Forest 1	(E1 and E2) (E1 and E3) (E2 and E3)	0.00 0.25 0.40	0.50 0.50 0.35	0.50 0.75 0.75	E1: 0.16 E2: 0.42 E3: 0.59	0.20 0.22 0.24
Forest 2	(E1 and E2) (E1 and E3) (E2 and E3)	0.00 0.44 0.36	0.66 0.17 0.16	0.66 0.61 0.53	E1: 0.15 E2: 0.30 E3: 0.30	0.00 0.10 0.10
Forest 3	(E1 and E2) (E1 and E3) (E2 and E3)	0.70 0.76 0.75	0.90 0.06 0.06	0.8275 0.82 0.82	E1: 0.46 E2: 0.60 E3: 0.67	0.23 0.25 0.25

Assemblage composition

The PERMANOVA indicated significant effects of elevation levels (F_2,3= 3.8246, p = 0.004), forests (F_1,3= 7.5693, p = 0.001), and their interactions (F_1,3= 6.0400, p = 0.001) on the OTUs composition OTUs. SIMPER analysis indicated that three OTUs including OUT 1, OUT 2, and OUT 3 were the most responsible groups for the observed significant difference between all of the comparisons (elevation levels and forests). The list of OTUs that have differences between elevations and forests is shown in Table 6.

Table 6

Output from SIMPER analysis of the difference in OTUs composition between three forests and three elevations
SIMPER
Data set	Responsible species
Forest 1Forest 2 Forest 1Forest 3 Forest 2Forest 3 Elevation 1Elevation 2 Elevation 1Elevation 3 Elevation 2Elevation 3	OTU 1, OTU 2, OTU3 OTU 1, OTU 2, OTU3, OTU 8, OTU 10 OTU 1, OTU 2, OTU3, OTU 8 OTU 1, OTU 2, OTU3, OTU 8 OTU 1, OTU 2, OTU3, OTU 4, OTU 5 OTU 1, OTU 2, OTU3, OTU 4, OTU 8, OTU 10

Relationship between snail communities and environmental variables

The measurement of soil parameters (pH, Ca, Mg, Ca⁺⁺, Mg⁺⁺. and %saturation moisture) are shown in Table S3. The range of pH values were varied from 6.1 (F1-E1) to 7.7 (F3-E1). According to our results, Forest 2 had the highest Ca content (44 mg) observed in E3, and Forest 1 at E2 had the lowest amount (16 mg). The Ca⁺⁺ content (6.09%) was found in F2-E1 and the minimum amount (0.79%) was recorded in F3-E2. Forest 1 exhibited the highest Mg content (44 meq/lit) at E1, whereas F3-E1 had the lowest amount (4 meq/lit). The highest Mg⁺⁺ content (2.21%) was observed in F3-E1, and the lowest amount (0.49%) was recorded in F2-E3. The highest content of %saturation moisture (= 95) was recorded in F3-E3 and the lowest amount (= 51.9) was observed in F3-E1.

To determine the environmental factors responsible for shaping the composition of snail communities in each forest, CCA was conducted using OTUs data and the selected environmental parameters after PCA analysis. According to PCA analysis, %saturation moisture and Ca in Forest 1, %saturation moisture and Mg in Forest 2, and in Forest 3, Ca and Mg have more contribution to each forest. In Forest 1, the selected variables explained 88% of the total variation in OTUs composition. Following that in Forest 2 and Forest 3, the physicochemical variables explained 53% and 69% of the total variation in OTU composition. The comparison of variations explained by constrained and unconstrained axes revealed > 82% efficiency of the constrained axes 1 and 2 in all three forests (Fig. 5).

This study is the first genetic investigation on terrestrial snail diversity in the Hyrcanian forest (in the northern part of Iran), which lead to the identification of 10 OTUs in the area based on COI gene sequences. Furthermore, land snails abundance and OTUs diversity were compared in an elevational incline and the results showed that elevation affected snail communities. In addition, the survey on soil physicochemical parameters displayed a correlation between some soil features and land snails' presence.

Identifying land snails

In our current research, both morphological and molecular approaches were employed to identify land snails and assess their species diversity. A total of 679 individuals were investigated, and 37 sequences were analyzed, leading to the recognition of seven families, nine genera, and four species (see Table 2). The ABGD and bPTP methods were used to analyze species delimitation, resulting in the identification of approximately 7 to 17 potential species and also 10 putative species through ABGD and bPTP respectively. By considering our findings on morphology, species delimitations, genetic distances, and the phylogenetic tree, we have determined 10 OTUs within the collected samples.

Among 10 OTUs identified in our research four of them including OUT 1, OUT 2, OUT 3, and OUT 10 refer to Caspicylotus sieversi, Pomatias rivulare, Caucasotachea leuaranea, and Oxychilus filicum respectively reported in the previous studies from the region (Issel 1865; Forcart 1935; Starmuhlner and Edlauer 1957; Yassini 1976; Eliazian et al., 1979; Mansoorian, 2005; Ahmadi; 2012). It is worth noting that the remaining six OTUs which referred to five genera named Pyrenaearia, Theba, Dioscuria, Pupilla, and Shileykula are the first documented occurrences of these genera in the Hyrcanian Forest of Iran. All of the aforementioned studies, just relied on morphological approaches, however in this study we used molecular methods too. We believe that recognition of snails using morphological approach may lead to misidentification because of their morphological variety and cryptic diversity. Therefore we suggest that a combination of molecular approaches and morphological taxonomy should be employed as the primary method for species identification, aiming to achieve more dependable results in land snail identification.

Although land snails exhibit substantial mitochondrial diversity and are among the most diverse animals, there have been limited barcoding studies conducted on them, with the majority of investigations focusing on marine gastropods (Meyer and Paulary, 2005; Kelly et al., 2007; Campbell et al., 2008). Consequently, there is a lack of comprehensive genetic data available in the GenBank dataset for barcoding studies and the COI gene dataset alone cannot currently serve as a practical method for identifying land snail species. However, it can serve as a reliable tool for assessing their biodiversity (Davison et al., 2009; Ranasinghe et al., 2022).

Statistical analysis

The ANOVA analysis revealed significant differences in the total density of land snails among different elevations within each forest. In addition, evaluating the abundance in three elevations at each forest indicates the abundance of snails in the highest elevation is more than in the lowlands (Fig. 6 (A)). A possible explanation for this difference is precipitation patterns and humidity levels in this area. Highlands in Hyrcanian forests are more humid, and also precipitation increases at higher elevations (Talebi et al., 2014). In line with our findings, Tattersfield et al (2006) found out land snail abundance increases in high-elevation sets. In addition, De Chavez and De Lara (2010) observed a positive relationship between land snail abundance and elevation in the Mount Makiling rainforest in the Philippines based on their observation. Although, in some cases has been obtained different results. Tattersfield et al., (2001) expressed that land snail abundance in Forest habitats in mountain Kenya decreases with enhancing elevation and also Liew et al. (2010) concluded that there is no relationship between land snail abundance and elevation.

Comparing OTUs richness in each forest displays that the number of OTUs gradually increases from high elevation to low elevation (Fig. 6 (B)). Additionally, the ANOVA revealed a significant distinction in Shannon-wiener diversity and total diversity of OTUs between three elevations across all forests. Similarly, the PD analyses confirm this pattern, showing an inverse relationship between PD values and increasing elevation. This pattern follows the common law for the most group of organisms in all environments (Gaston, 2000). As elevation affects many climatic variations including temperature and precipitation it can play an important role in habitat suitability. Precipitation enhancement, the longer period of cold temperatures besides less productivity in highlands cause a decrease in the amount of available energy in these areas. Thus the species-energy relationship (the relationship between energy availability and species richness) may clarify this pattern between species richness and elevation. Receiving a specified content of energy can preserve a specified number of species which means higher elevations shelter fewer species than lowlands (Gaston, 2000; Whittaker et al., 2001; Willis and Whittaker, 2002; Aubry et al., 2005).

Several investigations reported an increase in land snails species richness and species density in an elevation slope; Tattersfield et al. (2001) achieve the same result for forest habitats in Kenya, they remarked rainfall as the most important factor for land snail communities, as well as Aubry et al. (2005) observed the same pattern in south-eastern France. Based on their research different factors such as climate altitudinal slope and also land cover heterogeneities can explain this pattern. Liew et al. (2010) reported a decline in land snail and slugs species density with elevation as a result of lessen nich diversity in high elevations and also historical events which lead to snail upward migration. However, Tattersfield et al. (2006) observed an increase in land snail richness and species density in elevation in Mwanihana Forest in Tanzania.

Comparing three forests altogether revealed that Forest 3 which is located in the western part of the study area was different from the two other forests with higher OTUs richness and abundance. Considering that land snails are highly dependent on humidity, the observed differences can be explained by the decreasing precipitation pattern along the southern Caspian Sea shoreline from east to west. In addition, ecological dryness declined from the east toward the west of the Hyrcanian Forests and the climate in the western part is more humid than the eastern part (Shimizu and Ueshima, 2000; Talebi et al., 2014).

Based on the PERMANOVA analysis there were significant differences in snail composition across various elevations and among the three forests under investigation. These findings highlight the intricate ecological patterns and distinct species assemblages within each forest ecosystem. In general, some OTUs were exclusively identified in certain forests, indicating unique ecological characteristics that allow them to thrive in specific habitats. Five OTUs including OTU 4, OTU 5, OTU 6, OTU 7, and OTU 9 were observed only in Forest 3 and Forest 1 exhibited the exclusive presence of OTU 10. Furthermore, three OTUs (OTU 1, OTU 2, and OTU 3) were observed, across all forests. The SIMPER analysis highlighted these three OTUs are responsible for observed differences among forests and elevation levels. Additionally, the β-diversity partitioning results showed that the spatial turnover component played a dominant role in driving dissimilarity within Forest 2 and Forest 3 (Table 5). This finding implies that species replacement exerts a more substantial influence on the observed variation than differences in species richness. Conversely, in Forest 1, dissimilarity was primarily attributed to nestedness, indicating that dissimilarities were influenced by disparities in species richness.

Environmental variable

The result of PCA revealed that Ca, Mg, and %saturation moisture have more contribution in physicochemical soil factors. These factors exhibited positive trends with most of OTUs (see CCA results, Fig. 5). Because these environmental factors play a crucial role in shaping the distribution and diversity of snail populations. Calcium and magnesium are essential for land snails' shell development and overall functions. Evidence from previous studies consistently supports the notion that land snail abundance and species richness tend to be higher in areas characterized by elevated levels of calcium (Ca), magnesium (Mg), and moisture (Silvan et al., 2000; Hotopp, 2002). Snails flourish in regions with ample soil levels of these minerals, resulting in larger populations and more diverse species (Nekola and Smith, 2000; Millar and Waite, 2002). Moisture availability also plays a significant role in determining snail abundance and richness. Areas with higher moisture content in the soil create favorable conditions for snails, as it provides them with a suitable microhabitat (Getz and Uetz, 1994; Morecroft et al., 2002).

This survey represents the first barcoding study conducted on land snail species within the Hyrcanian Forest, resulting in the identification of 10 OTUs across the region. Notably, this study reports the occurrence of five genera, namely Pyrenaearia, Theba, Dioscuria, Pupilla, and Schileykula, for the first time within this geographical area. Furthermore, the examination of land snail communities along a gradient of elevation revealed significant alternation in their abundance, richness, and community composition. Soil physicochemical parameters analyses revealed that Ca, Mg, and %saturation moisture are the most important factors which impact snail distribution. This foundational study offers new insights into the snail community within the Hyrcanian forest, providing valuable data that can be utilized for future research in this globally significant world heritage site and similar habitats elsewhere. Further barcoding studies in different parts of the region is recomeded for future studies to uncover additional species as well as consider other environmental factors such as climatic variables can contribute to a better understanding of land snail communities along elevational slopes. These efforts will play a significant role in offering valuable insights into the conservation of snail biodiversity and the preservation of their habitats.

Data availability statement

The datasets generated during the current study are available in the [NCBI] repository, [ACCESSION NUMBERs are represented in table 2 in the article]. Additionally, the datasets generated in this study are accessible upon request from the corresponding author ([email protected]) in accordance with reasonable terms.

Acknowledgments

We wish to express our gratitude to everyone who contributed to the completion of this article. Special thanks go to Reihaneh Saberi-Pirooz for her invaluable assistance in data analysis and the preparation of the paper. Her expertise and dedication significantly enhanced the quality of our research. Furthermore, we would like to express our profound appreciation to Khashayar Allahbedashti for his unwavering support and significant contributions during the sampling phase of this study.

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No competing interests reported.

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Revealing Hidden Diversity and Community Dynamics of Land Snails through DNA Barcoding: Implications for Conservation and Ecological Studies

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Material and Methods

Study area

Sampling

Laboratory procedures

Measurement of soil Physico-chemical properties

Genetic analysis

Species-delimitation

Statistical Analyses

Results

Molecular and phylogenetic analyses

Comparison of land snail abundance and OTUs diversity

Assemblage composition

Relationship between snail communities and environmental variables

Discussion

Identifying land snails

Statistical analysis

Environmental variable

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1