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Article

Preliminary Study on the Diversity of Soil Oribatid Mite (Acari: Oribatida) Community Reveals Both Longitudinal and Latitudinal Patterns in Paddy Fields along the Middle and Lower Reaches of Yangtze River, China

by
Jiahuan Sun
1,2,
Yifei Liu
1,2,
Yanyan Ye
1,2,
Jiangshan Lai
3,
Ye Zheng
4,
Dong Liu
5,* and
Meixiang Gao
1,2,*
1
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
2
Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo 315211, China
3
College of Ecology and Environment, Nanjing Forestry University, Nanjing 210037, China
4
Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
5
Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
*
Authors to whom correspondence should be addressed.
Agronomy 2023, 13(11), 2718; https://doi.org/10.3390/agronomy13112718
Submission received: 30 September 2023 / Revised: 24 October 2023 / Accepted: 26 October 2023 / Published: 28 October 2023
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Abstract

:
Soil biodiversity plays an important role in maintaining soil fertility and agricultural health. Exploring the patterns of soil fauna diversity across geographical gradients is a fundamental and crucial scientific topic for understanding the mechanisms of soil biodiversity in farmlands. However, the spatial pattern of soil fauna diversity across longitudinal gradients has received far less attention. In order to explore the longitudinal pattern (west to east) of the composition and diversity of the soil oribatid mite community in paddy fields along the middle and lower reaches of the Yangtze River (MLYR), an investigation was carried out in July 2021 at nine sites spanning a longitudinal range of 8.86° (906 km) in southeastern China. In total, 19 taxa and 2392 individuals were observed with a density of 1535.47/m2. Protoribates and Ceratozetes were the most dominant and widely distributed genera along MLYR. The distribution patterns of the richness, abundance, and diversity index were obvious across the longitudinal and latitudinal gradients. The longitudinal pattern showed a quadratic distribution of first increasing and then decreasing, while the latitudinal pattern showed an increasing pattern with the increase in latitude (unimodal pattern). The influence of latitude on the abundance of the soil oribatid mite community was greater than that of longitude, and the influence of longitude on richness and the corresponding diversity index was greater. The dominance index did not show a distribution pattern in the longitudinal and latitudinal directions, while the evenness index showed only the distribution pattern in the longitudinal direction, and the latitudinal pattern was not significant. The results of this study suggest that the diversity of the soil oribatid mite community along MLYR displays both longitudinal and latitudinal patterns in paddy fields. Moreover, we highlighted the importance of integrating longitudinal and latitudinal patterns into spatial patterns of the soil fauna community in farmlands at a regional scale.

1. Introduction

Exploring and understanding the geographical pattern of soil biodiversity is an important and long-standing task for biogeography and macroecology in the context of climate change in the Anthropocene. Patterns across latitudinal, longitudinal, and elevational gradients are of widespread concern for biodiversity, including plants [1], birds [2], mammals [3], and invertebrates [4] at genetic [5], species [6], community [7], and ecosystem [8] levels. However, the most studied and well documented gradients are latitudinal and elevational patterns in soil biodiversity for a long time [9]. One important reason for this status is the sensitivity of these patterns to climate change. Therefore, patterns of soil biodiversity across geological gradients have been recognized as important bioindicators responding to global climate change. Many studies have been demonstrated this phenomenon for soil collembola [10] and oribatid [11,12,13,14] across latitudinal gradients and for soil nematode [15], ground beetles [16,17], and earthworms [18,19] across elevational gradients. Little attention has been paid to the longitudinal pattern of soil biodiversity until now, which is a serious shortcoming in soil biodiversity research.
Some studies have attempted to depict longitudinal patterns in soil biodiversity. Soil microbial activities were significantly correlated with longitude, and the factor most influencing the soil microbial community was longitude compared with latitude [20]. Scientists have detected a distinctly spatial pattern across longitudinal gradients in the European continent for the collembolan community in species composition and range size [21], but not for the oribatid mite community in abundance and biomass [22]. A highly significant longitudinal pattern was observed in the phylogenetic relatedness of the darkling beetle (Tenebrionidae: Coleoptera) community in Europe [23]. Unfortunately, some studies have focused on the spatial pattern of soil fauna diversity along longitudinal gradients while not comparing the contribution of the latitude factor with other factors [22]. Furthermore, a broader understanding of the longitudinal gradient in soil biodiversity more widely can provide new insights into soil biodiversity maintenance and conservation in the face of global climatic change.
Latitude primarily serves as a surrogate variable for temperature regimes, which has been demonstrated to be an important factor driving the spatial patterns of soil biodiversity. Relevant studies show that the latitude factor is primarily associated with changes in temperature, which in turn affects the biomass and niche width of organisms [24]. Longitude often correlates with continentality gradients linked to absolute differences in precipitation and temperature [25], and also correlates with winter warming and summer heatwaves in the context of climate change [4]. There are good theoretical reasons to expect that longitude and its associated precipitation and temperature will likely be the determining factors for the spatial patterns of soil biodiversity [26]. In fact, both longitude and environmental factors were found to be important in structuring fungal community composition [14]. However, climate and longitude did not have significant effects on the abundance and biomass of oribatid mite communities in Europe along a longitudinal gradient [22]. Therefore, we speculate that the underlying processes linking longitude and soil biodiversity may be more complex and challenging than those related to latitude [27], especially on a large-scale basis with relatively wide longitudinal and narrow latitudinal gradients.
Soil oribatid mites were investigated in paddy fields along MLYR, as they are the most abundant and diverse among the soil mesofauna [28]. Soil oribatid mites exist in various agricultural ecosystems with different environmental conditions and play an important role in decomposition processes and nutrient cycling [29,30]. Previous studies on soil fauna in paddy fields have focused on nematodes [31], earthworms [32,33,34], springtails [35], gastropods, and Coleoptera [36]. However, few studies on soil oribatid mites have been conducted in paddy fields, especially across a longitudinal gradient. Additionally, the precipitation dynamics induced by climate change are the leading factors resulting in changes in annual runoff in MLYR [37]. Therefore, we expected that the diversity of the soil oribatid mite community along MLYR exhibited an obvious pattern across longitudinal gradients, and that longitude rather than latitude significantly affects the soil oribatid mite community.
In order to reveal the spatial pattern of soil fauna diversity along a longitudinal gradient, this study was conducted in the middle and lower reaches of the Yangtze River (MLYR) area. The Yangtze River serves as the connection between the world’s largest continent, Eurasia, and the largest ocean, the Pacific. It has a significant impact on the biogeochemical cycle at a large regional scale and even the material cycle of the global ecosystem [38]. The Yangtze River is the largest river in Asia and the third-longest river by discharge volume in the world [39,40]. The MLYR area is an important grain production base in China [41,42]. The rice planting area in MLYR area accounts for 49% of the total rice planting area in China [43]. Therefore, experiments were conducted in paddy fields in this study to help evaluate the soil biodiversity in paddy fields within this important agricultural production base.
In this study, our aim was to describe the composition and diversity of the soil oribatid mite community along MLYR across a longitudinal gradient. The objectives of this study were to determine whether the richness, abundance, and diversity index of the soil oribatid mite community were influenced more by longitude than by latitude, and to explore longitudinal patterns along MLYR.

2. Materials and Methods

2.1. Study Area

This study was conducted in the middle and lower reaches of the Yangtze River (MLYR) area (27°50′–34° N, 111°5′–123° E), which is the primary region for rice production in China. The study area has a subtropical humid monsoon climate that is influenced by the East Asian monsoon [44]. The annual average temperature and precipitation are approximately 14–20 °C and 1000–1400 mm, respectively [44,45]. Rice is one of the important food crops in the MLYR area, and its cultivated area accounts for 1/4 of the total rice cultivated area in China. The rice growing period lasts 210–260 days, with precipitation during the rice growing period ranging from 700–1600 mm [46]. The annual rice planting area of rice in MLYR is about 38,109,000 hectares, and the annual rice output is 157.2 million tons, which accounts for 23.9% of the total land rice output in China [31,32].

2.2. Study Area and Sample Collection

There are six provinces and one municipality in the MLYR area [32]. In this study, nine cities were selected as study sites along MLYR, spanning a longitudinal and latitudinal range of 8.86° (906 km) and 2.35° (261 km), respectively (Figure 1). The details of the nine sites are described in Table 1. In each site, three 250,000 m2 (500 m × 500 m) plots were randomly selected, each being more than 1000 m away from the others in the suburbs. The soil type in each plot is paddy soil. We ensured that there were no significant differences in the environmental conditions of the three plots within the same study sites; no large topographic fluctuations; and no human disturbances such as factories, livestock farms, and residential areas, and each plot was highly connected without fragmentation by roads, rivers, buildings, or villages. Each plot contained at least 5 parallel ridges at intervals of more than 50 m. In addition, the boundary of each plot was situated more than 100 m away from the surrounding roads, villages, or rivers to avoid edge effects. Soil samples were collected in each plot from 1 to 7 October 2021, during the maturity stage of the paddy field (Figure 1 and Table 1).
One sampling rectangle, measuring 1 m in length and 0.3 m in width, was set randomly on each ridge, with a distance of more than 50 m between the different rectangles. Within each sampling rectangle, three 0–15 cm soil columns were dug using a soil auger with a 7 cm inner diameter. The three soil columns were pooled into a Ziplock bag as one soil sample; thus, five soil samples were collected in each plot. These soil samples were transported to the laboratory for the extraction of soil oribatid mites. In total, 135 soil samples were collected (5 samples/plot × 3 plots/site × 9 sites).

2.3. Identification

The soil oribatid mites were extracted using the Berlese-Tullgren method in the laboratory and allowed to naturally air dry for 10 days. The extracted soil oribatid mites were preserved in 95% alcohol. The morphology of the soil oribatid mites was observed using a stereomicroscope (Olympus Lympus SZX16: manufacturer-Tokyo, Japan; equipment was sourced-China and Nikon Eclipse 80i: manufacturer-Shanghai, China; equipment was sourced-China). Classification was based on Yin et al. (1998) [47]. Adults and nymphs were counted separately, with only adults being used for subsequent analysis. The soil oribatid mites were identified at the genus and family levels.

2.4. Environmental Variable

The latitude and longitude of each sampling point were measured using GPS instruments. ArcGIS was utilized to convert the latitude and longitude coordinates of each sampling point into plane coordinates (Table 1).

2.5. Data Analysis

Taxonomic richness and abundance were used to assess the composition and diversity of the soil oribatid mite community at each site and the total soil oribatid mite community across all sites. The Raunkiaer frequency was calculated to determine the frequency with which a taxon occured in various locations, as the ratio of the number of occurrences of each taxon in each plot/site to the total number of plots/sites. This ratio is divided into five levels: 0–20% for Class A, 21–40% for Class B, 41–60% for Class C, 61–80% for Class D, and 81–100% for Class E [48].
Rarefaction curves for the soil oribatid mite community were plotted to validate the effectiveness of the experimental sampling by examining the relationship between soil oribatid mite taxa and sampling intensity (Figure 2). The results of the rarefaction curves indicate that the total soil oribatid mite community were relatively stable, suggesting that the sampling design used in this study was capable of capturing the richness along MLYR (Figure 2).
The community dominance degree was calculated to reveal the dominance of oribatid mites in terms of abundance. Taxa accounting for more than 10% of the total abundance of individuals are classified as dominant taxa (+++), those representing 1% to 10% are considered common taxa (++), and less than 1% are categorized as rare taxa (+) [49,50].
MGP analysis was utilized to classify soil oribatid mites based on their degree of evolution and to categorize the soil oribatid mite community in each site into seven types, i.e., M, G, P, MG, MP, GP, and O (Table 2) [51,52]. M, G, and P represent the Macropylina-, Gymnonota-, and Poronota-type oribatida, respectively [52].
Three diversity indices were used to analyze the soil oribatid mite community diversity. The Shannon−Wiener diversity index (H′) was calculated as follows [53]:
H ′ = − ∑ i = 1 s P i ln P i
where S is the number of taxa in the community and Pi is the ratio of the number of individuals of the i-th taxon to the total number of soil mites in the community.
The Simpson dominance index (C) was calculated as follows [54]:
C = ∑ i = 1 s ( n i / N ) 2
where N is the total number of the soil oribatid mites in the community, S is the number of taxa in the community, and ni is the number of individuals of the i-th species.
The Pielou’s evenness index (J) was calculated as follows [55]:
J = H’/lnS
where S is the number of taxa in the community. H′ is the Shannon−Wiener diversity index. During the calculation process, we found that the C and J values of some samples were invalid, and these invalid samples were excluded when calculating the correlation index and linear regression.
A ln (x + 1) transformation was performed to normalize abundance and richness data prior to statistical testing [56]. One-way ANOVA was used to analyze whether there were significant differences in the abundance and richness of the soil oribatid mite communities between different sites.
To test the effects of longitude and latitude on the richness, abundance, and diversity indices, a regression analysis was conducted using the lower values of Akaike’s information criterion (AIC). By assessing the AIC value, the quadratic function was selected to fit the longitude, and the primary function was chosen to fit the latitude. The multiple regression method was applied to model the abundance, species number, and diversity index of the oribatid mite community. The overall R2 was decomposed using the glmm.hp package to obtain individual interpretation R2 values for each geographical factor (longitude and latitude). The multiple regression method provides a better solution to the problem of collinearity between factors compared with common single regression.
The diversity indices were calculated using the diversity function in the “vegan” package. Violin charts were created using the “vector” and the “vioplot” functions from the “gapminder” and the “vioplot” packages [57]. One-way ANOVA was performed with the “aov” function in the “vegan” package [58]. Linear or quadratic model analysis and multiple regression were carried out with the “lm”, “lmorigin”, and “lm_eqn” functions from the “car”, “patchwork”, and “ape” packages [59,60,61]. The R2 values obtained by multiple regression were decomposed using the “glmm.hp” package [62]. The above analyses were conducted using the R 4.1.3 software platform.

3. Results

3.1. Composition and Diversity of the Soil Oribatid Mite Community along MLYR

A total of 2392 individuals from the soil oribatid mite community were obtained from nine cities, belonging to 19 taxa (Table 3).
Protoribates and Ceratozetes were dominant taxa in terms of abundance in the total soil oribatid mite community. These two taxa accounted for 78.64% of the total abundance and were widely distributed and were present at all sites along MLYR. Additionally, Oppiella, Pergalumna, Tectocepheus, and Perxylobates were also common taxa. The number of taxa falling into Raunkiaer frequency classes A, B, C, and D was 16 (84.21%), 1 (5.26%), 1 (5.26%), and 1 (5.26%), respectively, in the paddy fields along MLYR.
Based on the results of the MGP analysis, the P, G, and M types accounted for 82.567%, 16.137%, and 1.296% of the total soil oribatid mite community, respectively. Therefore, the primary forms of the total soil oribatid mite community were P and G types.
The richness of the soil oribatid mite communities in the different sites was the highest in the WX and SZ with 11 taxa and the lowest in the YY with 5 taxa. The highest richness was 2.2 times that of the lowest (Table 3). The richness of the soil oribatid mite communities significantly differed among the nine study sites (F = 3.406, p < 0.05) (Figure 3a). The mean richness in the WH was significantly higher than that in JZ, YY, SZ, and SH. In WX, it was significantly higher than that in YY, SZ, and SH. In JZ, NJ, and CZ, it was significantly higher than that in YY (p < 0.05) (Figure 3a).
The abundances of the soil oribatid mite communities at each site were the highest in the WH with 728 and the lowest in the YY with 26 (Table 3). The abundances of the soil oribatid mite communities significantly differed among the nine study sites (F = 2.528, p < 0.05) (Figure 3b). The abundance of the soil oribatid mite communities in WH was significantly higher than that in JZ, YY, JJ, CZ, SZ, and SH. In NJ and WX, it was significantly higher than that in YY and SZ (p < 0.05) (Figure 3b).
The results of the Shannon−Wiener (H′), Simpson dominance (C), and Pielou’s evenness indices (J) were 1.29, 2.08, and 0.45, respectively. The values of the H′ (F = 2.651, p < 0.05), C (F = 4.494, p < 0.05), and J (F = 2.73, p < 0.05) indices of the soil oribatid mite communities significantly differed among the nine sites. H′, C, and J in YY, SZ, and SH were smaller than those in the other study sites (Figure 4).

3.2. Correlation between Diversity and Geographical Variables

The preliminary results of the one-way ANOVA showed that the indices of soil oribatid mites did not exhibit a linear relationship with longitude, but tended to follow a quadratic function relationship. Through the test of AIC value, we found that in the multiple regression, the most ideal regression results were achieved when fitting longitude with a quadratic function and latitude with a primary function. The abundance of the total soil oribatid mite community was significantly positively correlated with latitude (R2 = 0.069, p < 0.001). According to the estimation of the slope of the quadratic function, the abundance of oribatid mites first increased and then decreased with the increase in longitude (R2 = 0.042, p < 0.05). The decomposition of R2 showed that the variability of the abundance of oribatid mites with latitude (R2 = 0.069, p < 0.001) was greater than that with longitude (R2 = 0.042, p < 0.05) (Table 4).
The richness of the soil oribatid mite community was significantly positively correlated with latitude (R2 = 0.039, p < 0.01). The richness of the oribatid mites first increased and then decreased with the increase in longitude (R2 = 0.066, p < 0.01). The decomposition of R2 showed that the variability of the richness of soil oribatid mites with longitude (R2 = 0.066, p < 0.01) was greater than that with latitude (R2 = 0.039, p < 0.01) (Table 4).
Shannon−Wiener diversity (H′) showed the same distribution pattern as diversity of the soil oribatid mite community, and the decomposition of R2 showed that the variability of the abundance of oribatid mites with longitude (R2 = 0.028, p < 0.05) was greater than that with latitude (R2 = 0.016, p < 0.05). Simpson dominance (C) showed no significant variation with latitude (R2 < 0) or longitude (R2 = 0.006, p > 0.05). Pielou’s evenness (J) showed an obvious distribution pattern of first increasing and then decreasing with the increase in longitude (R2 = 0.090 p < 0.001), but there was no obvious trend with latitude (R2 = 0.010, p > 0.05) (Table 4).

4. Discussion

4.1. Community Composition and Diversity along MLYR

The composition and diversity of the soil oribatid mite community in paddy fields are extremely important [63,64,65,66,67,68]. In this study, 19 taxa and 2392 individuals of the soil oribatid mite community were observed along MLYR. The density of the soil oribatid mite community in paddy fields was 1535.47/m2 in October along MLYR, a subtropical area, which was lower than the value (5700 ± 3100/m2) in November in Assam, India, a tropical area [69]. Compared with other relevant studies, the number of soil oribatid mites in our study was relatively small. The main reason is that the research area of this study was a paddy field. However, the number of soil mites would decrease sharply under the condition of rice flooding.
The soil oribatid mite community was mainly composed of a few dominant taxa, and most taxa were common, rare, and low frequency in the study area. This structure was consistent with the oribatid mite community in an arable field with alluvial soils [35], indicating that the paddy field along MLYR might be a strongly disturbed habitat for the soil oribatid mite community [70]. Protoribates and Ceratozetes were both dominant in abundance and the most widely distributed taxa in paddy field along MLYR, suggesting these two taxa had a wide ecological tolerance in the study area [35]. Although there were no studies on the large-scale distribution of soil mites along the longitudinal gradient, we found that it was different from testate amoebae communities along MLYR because no species occurred in all study sites [71]. The two taxa are also dominant in Romanian and Russian forests [72,73,74]. Additionally, changes in dominant taxa among the different study sites showed the impact of environmental variations on certain oribatid mite taxa, which will be more important for predicating the responses of soil biodiversity to environmental change in the study area.
The soil oribatid mite community was dominated by P and G ecotypes in the paddy field in the present study, indicating heavy human disturbances to the soil oribatid mite community along MLYR. This finding was similar to the results in grass cultivation ecosystems in subtropical areas [75], in degraded red soil ecosystems in subtropical areas [76], and in agricultural ecosystems of grassland in temperate areas [77]. The oribatid mite communities in seven study sites were P types, except in YY, where a G type was found, as most taxa were P type. More P type mites mean more human interference in the environment [78,79]. These results indicate that the soil oribatid mite community has been disturbed severely in paddy fields in the study area.
To our knowledge, no research has been done on soil fauna diversity along MLYR at a regional scale until now. The results of this study uncover that the taxonomic richness, abundance, and diversity indices of the soil oribatid mite community significantly vary along MLYR. This is similar to previous studies focused on soil microorganisms [80]. This phenomenon in paddy fields is in line with our expectations, and the main reason is that most of the mites in paddy fields may die in large numbers due to rice water injection. Although our study was conducted on a ridge, the influence of water factors on the abundance of soil mites cannot be ignored. The highest values of abundance and Shannon−Wiener diversity index were observed in WH, which were due to the great contributions of Protoribates and Oppiella. In fact, the abundance of Protoribates (p < 0.01) and Oppiella (p < 0.01) in WH was significantly higher than those in the other study sites. The lowest values of richness, abundance, Shannon−Wiener diversity, and Pielou’s evenness indices were observed in YY. The results of the MGP analysis showed that these two genera belong to P. We believe that these two genera have a strong tolerance to water, and can be used as key research objects to explore the survival mechanism of soil mites in paddy fields in the future.

4.2. Spatial Patterns of the Soil Oribatid Mite Community along MLYR

The examination of spatial patterns of soil fauna communities across geographical gradients is a primary focus of biogeographical and macroecological research [12,81]. We investigated the diversity of the soil oribatid mite community spanning both longitudinal (906 km) and latitudinal (261 km) ranges. The diversity of the soil oribatid mite community exhibited distinct spatial patterns along MLYR, across a longitudinal gradient, which were consistent with our expectations. Indeed, richness and abundance increased and then decreased with increasing longitude in the present study. Additionally, the Shannon−Wiener diversity and Pielou’s evenness indices were significantly influenced by longitude. Similar spatial patterns have been reported for various organisms along longitudinal gradients [82]. This part of the results can only demonstrate that the spatial pattern of soil mites existed in the longitude direction, and the longitude factor exerted a significant influence on the spatial distribution of soil mites. However, it is not rigorous enough to directly conclude that the contribution of the longitude factor to the richness of soil mites and other species diversity indicators was greater than that of the latitude factor through the simple comparisons of multiple regression R2 (Table 4) This is because the latitude span in this study was quite different from the longitude span, with the longitude change being more than three times the latitude change.
Nevertheless, the driving mechanism behind the display of the soil mites was unclear, and we speculate that it may be associated with climatic factors, such as temperature and precipitation. In fact, previous studies have suggested various factors as the main drivers for longitudinal patterns. A study across Europe along a longitudinal gradient indicated that climatic variables had a moderate impact on the abundance and biomass of oribatid communities, while continentality significantly determined actual species richness and functional structure from west to east [22]. For distinct invertebrate communities in the upper, middle, and lower reaches of the Altamaha catchment, the flood pulse was suggested as an important driver for the pattern spanning a 150 km longitudinal length [82]. It has also been confirmed that certain geographical geometric boundaries have significant effects on the spatial distribution of species [83]. Soil pH, SOM, N, and P were important factors filtering the arbuscular mycorrhizal fungal community in the paddy fields along MLYR [65]. However, we should consider environmental variables at local and regional scales, which may enable us to identify the underlying processes of the longitudinal pattern within the study area.
We were surprised to find strong linear patterns of richness and abundance of the soil oribatid mite community across a narrow latitudinal span (2.35°, 261 km). Previous studies have typically identified significant latitudinal trends in soil oribatid mite communities across broader latitudinal ranges. In contrast with the results of this study, the species richness of soil mites from Antarctica to Brazil showed a nonlinear relationship along latitude [84,85]. However, our study demonstrated that the latitudinal gradients of the soil oribatid mite community were also exhibited across a relatively narrow latitudinal range. The results show that the variation in soil mite abundance was more affected by latitude than longitude. This result provides valuable insights for our future research. When studying the large-scale spatial distribution pattern of a certain group, the influence of latitude (temperature) on its abundance changes must be considered more.
The latitudinal pattern of this study was the contrary to the well-known latitudinal biodiversity gradient (LBG). LBG is typically defined as an increase in species richness from the poles (high latitude) towards the equator (low latitude) [86,87]. However, we observed an increase in richness and abundance from the low latitude towards the high latitude along a relatively short longitudinal span in the subtropical area. We speculate that this result is closely related to the nutrient content and porosity of the soil and is influenced by local microhabitat variations and generalists’ preferences regarding habitat selection and feeding modes [85,88]. Our results further emphasize that despite the small spatial span, exploring the spatial pattern and its underlying processes of the soil oribatid mite community along the latitudinal gradient remains a striking and challenging task. The influence of latitude on the abundance of the soil oribatid mite community was found to be greater than that of longitude, while the impact of longitude was more significant on the richness and corresponding diversity indices (Table 4). This can be attributed to the significantly smaller latitude span compared with the longitude span in the study area, suggesting that it is premature to conclude that longitudinal variation contributes more to spatial variability in soil oribatid mite richness. However, we can confirm that latitude has a higher contribution rate towards spatial variability in the abundance of the oribatid mite community. Studies of soil mites in the British countryside have shown similar results [12,89]. This finding highlights the importance of latitude as a key factor influencing both the abundance and richness distribution patterns of the soil oribatid mite community. Notably, no apparent variation in richness was observed across different longitudes in the present study, thus indicating that a larger scale may be required for a clear display of longitudinal variations among soil oribatid mites.
However, the geographical variables showed low contributions to the diversity of the soil oribatid mite community along MLYR, indicating that other unmeasured factors were more important. Previous studies have demonstrated that soil parameters, river characteristics, and landform can affect the spatial patterns of soil biodiversity [90,91,92,93,94]. Thus, we suggest that these factors might be important in environmental filtering within longitudinal and latitudinal gradients. Additionally, the study area is part of the Yangtze River Economic Belt, characterized by a dense population, rapid economic development, and intensive agricultural management [95]. Therefore, various processes, such as agricultural management, industrial development, urbanization, traffic conditions, landscape fragmentation, and natural disasters, should be considered as stochastic processes that are important drivers for soil biodiversity patterns along MLYR [83].

5. Conclusions

This study aimed to explore the spatial pattern of the composition and diversity of the soil oribatid mite community in paddy fields along MLYR across a longitudinal gradient. In total, 19 taxa and 2392 individuals were observed. The composition and diversity of the soil oribatid mite community were significantly different among the nine study sites. The richness, abundance, and diversity indices exhibited significant longitudinal patterns. Unexpectedly, species richness and abundance also showed a latitudinal pattern. Both longitude and latitude significantly influenced the richness, abundance, and diversity indices. Therefore, the results of this study suggest that the soil oribatid mite community in paddy fields exhibits highly predictable longitudinal and latitudinal patterns along MLYR. The generally overlooked contribution of longitude in shaping soil fauna communities should receive more attention. Additionally, spatial patterns of soil fauna communities along longitudinal and latitudinal gradients should be considered, even across a relatively short latitudinal span. This study sheds light on soil biodiversity maintenance and conservation in agricultural ecosystems in the main crop-producing area in the subtropical region.

Author Contributions

Conceptualization, D.L. and M.G.; Methodology, J.L.; Software, J.L.; Validation, M.G.; Investigation, D.L.; Resources, Y.Z.; Data curation, J.S., Y.L. and Y.Y.; Writing—original draft, J.S.; Writing—review and editing, J.S., D.L. and M.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (42271051, 41871042), Zhejiang Public Welfare Technology Application Research Project (LGN22D010006) and Ningbo Natural Science Foundation of China (2021J129).

Data Availability Statement

Please contact the author of this article for data.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Maps of the study area: study sites (a), sampling point convergence area (b), and sampling strategy within each point (c).
Figure 1. Maps of the study area: study sites (a), sampling point convergence area (b), and sampling strategy within each point (c).
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Figure 2. Rarefaction curve for the soil oribatid mite community. The blue area represents a 95% confidence interval polygon, and a box diagram is generated for each sampling point. The box diagram illustrates the mean ± SEM of the taxonomic number between the sampling point and the previous accumulated sample points.
Figure 2. Rarefaction curve for the soil oribatid mite community. The blue area represents a 95% confidence interval polygon, and a box diagram is generated for each sampling point. The box diagram illustrates the mean ± SEM of the taxonomic number between the sampling point and the previous accumulated sample points.
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Figure 3. Taxonomic richness (a) and abundance (b) of the soil oribatid mite communities at different sites along MLYR (west to east). Please refer to Table 1 for the abbreviations. In each green violin figure, the white point represents the average value of the index corresponding to the sample point, the thick green line represents the range of mean ± SEM, and the range of the thin line represents the range of its actual value. The wider the width of the green area corresponding to the vertical coordinate, the higher the possibility of the sample point taking a value at this level. Within each series, columns marked by the same letter are not significant at p < 0.05.
Figure 3. Taxonomic richness (a) and abundance (b) of the soil oribatid mite communities at different sites along MLYR (west to east). Please refer to Table 1 for the abbreviations. In each green violin figure, the white point represents the average value of the index corresponding to the sample point, the thick green line represents the range of mean ± SEM, and the range of the thin line represents the range of its actual value. The wider the width of the green area corresponding to the vertical coordinate, the higher the possibility of the sample point taking a value at this level. Within each series, columns marked by the same letter are not significant at p < 0.05.
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Figure 4. Variation in Shannon−Wiener diversity (a), Simpson dominance (b), and Pielou’s evenness (c) indices in the soil mite communities at different sites (west to east) along MLYRA. Please refer to Table 1 for the abbreviations. In each green violin figure, the white point represents the average value of the index corresponding to the sample point, the thick green line represents the range of mean ± SEM, and the range of the thin line represents the range of its actual value. The wider the width of the green area corresponding to the vertical coordinate, the higher the possibility of the sample point taking a value at this level. Within each series, columns marked by the same letter are not significant at p < 0.05.
Figure 4. Variation in Shannon−Wiener diversity (a), Simpson dominance (b), and Pielou’s evenness (c) indices in the soil mite communities at different sites (west to east) along MLYRA. Please refer to Table 1 for the abbreviations. In each green violin figure, the white point represents the average value of the index corresponding to the sample point, the thick green line represents the range of mean ± SEM, and the range of the thin line represents the range of its actual value. The wider the width of the green area corresponding to the vertical coordinate, the higher the possibility of the sample point taking a value at this level. Within each series, columns marked by the same letter are not significant at p < 0.05.
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Table 1. Summary of the geographic characteristics of the study sites along MLYR.
Table 1. Summary of the geographic characteristics of the study sites along MLYR.
Site (Abbr.)Province (Municipality)Longitude
(°, E) a		Latitude
(°, N) b		MAT (°C)MAP (mm)
Jingzhou (JZ)Hubei112.312 ± 0.01230.211 ± 0.00317.0886.4
Yueyang (YY)Hunan113.027 ± 0.00129.484 ± 0.01218.91310.6
Jiujiang (JJ)Jiangxi115.817 ± 0.00429.606 ± 0.00220.41485.9
Chizhou (CZ)Anhui117.571 ± 0.01430.524 ± 0.00517.71556
Wuhu (WH)Anhui118.263 ± 0.00231.468 ± 0.00217.91248.1
Nanjing (NJ)Jiangsu118.680 ± 0.00131.827 ± 0.00117.61267.1
Wuxi (WX)Jiangsu120.541 ± 0.00131.765 ± 0.00118.01142.0
Suzhou (SZ)Jiangsu120.388 ± 0.00131.369 ± 0.00318.31318.6
Shanghai (SH)Shanghai121.170 ± 0.01831.204 ± 0.00218.11388.2
Note: a and b represent the values (mean ± SD) of longitude and latitude of the three plots in the study sites. MAT, mean temperature; MAP, mean annual precipitation.
Table 2. Classification of oribatid mite community.
Table 2. Classification of oribatid mite community.
Community TypeAbbr.Requirements
Macrophylina typeMThe number of M type mites is more than 50%.
Gymnonota typeGThe number of G type mites is more than 50%.
Poronota typePThe number of P type mites is more than 50%.
Overall typeOThe individual numbers of M, G, and P type mites are all in the range of 20–50%.
Macrophylina-Gymnonota typeMGThe individual numbers of type M and G type mites are in the range of 20–50%, while the individual numbers of P type mites are less than 20%.
Gymnonota-Poronota typeGPThe individual numbers of type G and P type mites are in the range of 20–50%, while the individual numbers of M type mites are less than 20%.
Macropylina-Poronota typeMPThe individual numbers of type M and P type mites are in the range of 20–50%, while the individual numbers of G type mites are less than 20%.
Table 3. Composition and abundance of the soil oribatid mite community along MLYR.
Table 3. Composition and abundance of the soil oribatid mite community along MLYR.
CZJZJJNJSHSZWHWXYYAbundancePercentage (%)DD
Protoribates Berlese, 19081257959681897273621079133.07+++
Eremobelba Berlese, 1908305200410150.63+
Ceratozetes Berlese, 1908895940179114714031296109045.57+++
Oppiella Jacot, 1937443192112701516.31++
Pergalumna Grandjean, 193631574393260883.68++
Tectocepheus Berlese, 189641498319110592.47++
Lohmannia Michael, 1898051104000110.46+
Perxylobates Hammer, 19721011213106311014.22++
Scheloribates Berlese, 19080011400700220.92+
Eremaeus Koch, 1835000100407120.50+
Oppiidae Grandjean, 195400000500270.29+
Punctoribatidae Thor, 193700000100010.04+
Mochlozetidae Grandjean, 196001000800090.38+
Epilohmanniidae Oudemans, 192300000120030.13+
Parakalummidae Grandjean, 19360000000110110.46+
Damaeidae Berlese, 189600000003030.13+
Tetracondylidae Aoki, 196100000001010.04+
Trhypochthoniidae Willmann, 193100000004040.17+
Euphthiracaridae Jacot, 19300020001100130.54+
Abundance297153131391147201728318262392
Richness7710106111011519
Density Individual/m25147.542651.762270.466776.722547.773483.6912,617.535511.50450.631535.47
Note: DD means dominance degree. See Table 1 for abbreviations. Dominant taxa (+++), common taxa (++), rare taxa (+).
Table 4. Multiple regression results between the diversity index and two geographical factors, and R2 decomposition results corresponding to each factor.
Table 4. Multiple regression results between the diversity index and two geographical factors, and R2 decomposition results corresponding to each factor.
Response VariableModelR2Slope
EstimateSEt Valuep-Value
Abundancelongitude0.021183,90087,0302.1140.036 *
longitude20.021−52822499−2.1140.036 *
latitude0.06924.97.3773.375<0.001 ***
Richnesslongitude0.033123,30038,1903.2280.002 **
longitude20.033−35401096−3.2280.002 **
latitude0.0399.1543.2372.8280.005 **
H′longitude0.01446,34019,4002.3890.018 *
longitude20.014−1331556.9−2.3890.018 *
latitude0.0163.5791.6442.1770.031 *
Clongitude0.00316,687.118,0830.9230.358
longitude20.003−479.2519.1−0.9230.358
Jlongitude0.04566,70018,7303.561<0.001 ***
longitude20.045−1915537.8−3.561<0.001 ***
latitude0.0103.0921.6171.9120.059
* p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.
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Sun, J.; Liu, Y.; Ye, Y.; Lai, J.; Zheng, Y.; Liu, D.; Gao, M. Preliminary Study on the Diversity of Soil Oribatid Mite (Acari: Oribatida) Community Reveals Both Longitudinal and Latitudinal Patterns in Paddy Fields along the Middle and Lower Reaches of Yangtze River, China. Agronomy 2023, 13, 2718. https://doi.org/10.3390/agronomy13112718

AMA Style

Sun J, Liu Y, Ye Y, Lai J, Zheng Y, Liu D, Gao M. Preliminary Study on the Diversity of Soil Oribatid Mite (Acari: Oribatida) Community Reveals Both Longitudinal and Latitudinal Patterns in Paddy Fields along the Middle and Lower Reaches of Yangtze River, China. Agronomy. 2023; 13(11):2718. https://doi.org/10.3390/agronomy13112718

Chicago/Turabian Style

Sun, Jiahuan, Yifei Liu, Yanyan Ye, Jiangshan Lai, Ye Zheng, Dong Liu, and Meixiang Gao. 2023. "Preliminary Study on the Diversity of Soil Oribatid Mite (Acari: Oribatida) Community Reveals Both Longitudinal and Latitudinal Patterns in Paddy Fields along the Middle and Lower Reaches of Yangtze River, China" Agronomy 13, no. 11: 2718. https://doi.org/10.3390/agronomy13112718

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