Simple, inexpensive, and rapid approach to detect changes in the structure of soil free-living nematodes

Soil plays an important role in providing ecosystem services. Even if invisible to the human eye, soil nematodes are ubiquitous actors in most ecosystem services, acting as biocontrol agents in the transformation of organic matter or regulation of pest organism balance. Nematodes are found in all soil types thanks to their great morphological and functional adaptability. These features, combined with their abundance, found to be 3.2 million/m² (Van Den Hoogen, 2019), omnipresence in all the types of ecosystems (Dionísio et al., 2018) and the introduction of ecological and functional indices (Bongers, 1990; Ferris et al., 2001; Ferris & Bongers, 2009) have led to the intensive use of nematodes as bioindicators of quality and health of soil over the last 30 years (Du Preez et al., 2022). Bioindicators are organisms or communities of organisms that can be used or observed to evaluate an environmental condition or provide information about an ecosystem. Among the bioindicators, the ecological ones are taxa known to be sensitive to pollution, stresses or environmental disturbances and they are representative of the whole community (Gaugler & Bilgrami, 2004). Indeed, the permeable body wall gives free-living nematodes sensitivity to changes in the surrounding soil environment, making them able to detect possible variations and provide rapid responses (Pires et al., 2022). Furthermore, nematodes' generation time and short lifecycle, easy sampling methods and extraction procedures make them ideal test subjects. The study of the taxonomical and functional nematode structures as a bio-monitoring tool proves to be an effective approach to evaluating the ecological conditions, and as a result, numerous indices have been designed for the assessment of the ecosystem health status (e.g. enrichment, structure, basal and channel indices, see Ferris & Bongers, 2009; Du Preez et al., 2022 for review).

However, all of them are inferred through a morphological approach and require at least identification at the genus level. Certainly, as observers, we are used to judging from first sight what we are watching. For this reason, the primary identification and characterization of nematode communities rely on their morphological and anatomical differences (e.g. Platt, 1981). However, the absence of a simple and fast method based on the morphological approach cannot give the possibility to immediately and easily categorize these tiny animals. On the other hand, environmental DNA is often expected to solve this problem, the approach still has some gaps and cannot be routinely used (Cocozza di Montanara et al., 2022). Thus, it is necessary to conceive alternative methods that leverage easily applicable human abilities.

According to Violle et al. (2007), functional traits are defined as morpho-physio-phenological traits that impact fitness indirectly via their effects on growth, reproduction and survival. Since some morphological diagnostic characters of nematodes (buccal cavity morphology, amphid, cuticle/external body structure and tails) seem to fit these requirements (Wieser, 1953; Thistle et al., 1995; Thiele et al., 2009; Zullini & Semprucci, 2020). Semprucci et al. (2022) explored a cheaper and more user-friendly method based on a combination of morpho-functional traits to assess differences in nematode community structure in Mediterranean marine systems. Particularly, they emphasized the idea that the nematode community structure changes can be revealed by combining a few numbers of morphological diagnostic features in a code as a proxy for taxonomic identification.

Since the simplicity of the method allows us to avoid the time-consuming of activities without renouncing the reliability of results in marine ecosystems (see Semprucci et al., 2022; Justino et al., 2023), we tested the same approach to soil habitats. We considered four morphological characters e.g. buccal morphology, amphideal fovea size and shape, morphology of the cuticle and pharynx. We assume this last trait, as an additional trait since it has a crucial importance in the identification of soil free-living nematodes and its logical relation to feeding habits (Zullini, 2021). On the contrary to the traits selected for the marine nematodes, tail morphology was not considered due to the high variability of this feature, even between males and females of the same soil nematode species.

The aim of the present study is to demonstrate that the combining morpho-functional traits may efficiently mirror the changes in the nematode taxonomic structure, even in the soil system. To deal with this aim, we have considered data coming from different case studies. Since soil conditions affect the boundaries that include plant growth and consequently characteristics of soil biota (Usman & Muhammad, 2016), we decided to examine data from three different soil environments previously studied in three investigations: 1) a natural and temperate forest, 2) a grassland and 3) a field cultivated with maize. Each type of soil ecosystem and its land use can respond differently to potential perturbations, influencing the recovery time of the nematode community structure (Ferris et al., 2001). The diversity of each soil corresponds to a wide differentiation in management practices for maintaining soil quality and soil health. Particularly, food, water and temperature are the three main environmental variables that influence the level of nematode diversity and the faunal composition. The soil nematode community structure is mostly driven by the different responses of the various species to the habitat conditions (e.g. food resources, soil physicochemical properties, seasonal variations etc.), contributing to the variability in the ecological processes (Ferris et al., 2001; Gaugler & Bilgrami, 2004).

Therefore, we compared the results obtained from the different studied areas, considering all the correlated variables to verify whether, by combining the morphological traits, there is a correspondence that mirrors the taxonomic composition results in the soil nematode community identified at the genus level.

In the present study, data sets, were extracted by three previous surveys carried out in different types of ecosystems: grassland, arable soil and forest (Čerevková, 2006; Čerevková et al. 2018; Čerevková et al., 2021) in order to compare the effectiveness of the trait combination of nematodes for the detection of nematode structure changes.

All the information on the characteristic of ecosystems, localities and sampling design and routines is reported in the original papers and summarized in Table 1.

We used the three dataset of identified nematodes on genus level and selected a total of four morphological traits: 1. buccal cavity cuticularization occurrence, 2. amphideal fovea size and shape, 3. morphology of the cuticle and 4. morphology of the pharynx to obtain the trait combinations.

In detail, we identified five main categories in relation to the general morphology of the buccal cavity i.e. presence/absence or the look of the cuticularizations within the buccal cavity: 1. unarmed buccal cavity; 2. stylet; 3. odontostyle; 4. onchiostyle; 5. tooth or teeth (Fig. 1). In relation to amphids, we followed a distinction based on the shape and size of the amphideal fovea that were grouped into eight main categories: 1. amphid punctiform or not discernible; 2. circular/rounded or oval; 3. spiral; 4. thin, narrow slit or pore-like; 5. large slite-like & S-shape; 6. funnel-shape; 7. pouch-like; 8. caliciform (Fig. 2A). The cuticle morphology was recognized on the basis of its morphology and thickness in the following three types: 1. Smooth or nearly so; 2. annulated; 3. with outgrowths (Fig. 2B). Oesophageal shape was subdivided into seven categories: 1. oesophagus posteriorly expanded; 2. oesophagus cylindrical; 3. oesophagus with basal bulb; 4. oesophagus with cylindrical corpus and basal bulb; 5. oesophagus with median bulb; 6. oesophagus with swollen corpus and basal bulb; 7. oesophageal procorpus broad posteriorly expanded, bulb-like isthmus short basal bulb (Fig. 2C). Categorization of the buccal cavity cuticularizations, amphidial fovea and cuticle type were made according to Andrássy's books (Andrássy, 2005, 2007, 2009), while the oesophageal shape was based on Zullini guide (Zullini, 2021).

Fig. 1.

Fig. 2.

After defining of the various categories of each morpho-functional trait (buccal cavity, amphid, cuticle and pharynx), each genus was assigned to the most suitable category based on its morphological appearance and each taxon was given its own number code (Fig. 3).

Fig. 3.

Overall, 81 genera were assembled in 27 code combinations that were used to understand if this approach can really reflect changes in the taxonomic composition of soil nematodes. In Figures 4 – 6, it is possible to visualize the sample similarity plots of the taxonomic nematode structure and trait combination in light of the several ecological factors analysed. In the first study case from forest ecosystems, the type of forest was the most significant factor influencing both genus (ANOSIM, Global R = 0.29; p = 0.001) and trait code combination (Global R = 0.29; p = 0.001).

Fig. 4.

Fig. 5.

Fig. 6.

Although, there is a certain degree of overlap of the samples in Figure 4A – B, managed spruce forests (SPR) and unmanaged mixed forests (UNM) appeared at the plot extremes highlighting the highest level of dissimilarity. This is confirmed also by the ANOSIM pair-wise test, in which, SPR vs. UNM reported the most marked differences (Table 2). A lesser extent of differences was noticed according to forest age factor (genus structure: Global R = 0.15; p = 0.001 and trait code structure: Global R = 0.16; p = 0.001, Table 2), but a clear distinction of the old-growth forest in untouched areas was discernible by both nMDS plot and ANOSIM pair-wise results (Table 2). Remarkable, it is that trait combination revealed for forest dataset greater differences than the genus structure in many cases.

In the data set published by Čerevková (2021), the grassland with different ecosystem service (e.g. new and permanent meadows, and permanent pasture), sites, and periods were compared, but significant differences were found only for ecosystem types and localities (Table 2). The values of the global R and probability level for the trait combination were perfectly comparable to the outputs obtained by the genus composition and more marked differences were observed between localities (genus: R=0.24; p=0.002 versus trait combination: R=0.18; p=0.004) than between grasslands types (genus: R=0.12; p=0.005 versus trait combination: R=0.12; p=0.012) (Table 2). In detail, the site with the highest level of dissimilarity was Stropkov (Fig. 5; Table 2), while newly established meadows showed significant differences from both permanent meadows and permanent pastures. Instead, no significant differences were observed between these two types of grasslands (i.e. PM and PP) (Fig. 5 and Table 2).

The study case carried out to evaluate the possible disturbance effects of genetically modified maize did not reveal significant differences between maize Bt and isogenic (ISO) hybrids (Fig. 6; Table 2). Instead, marked differences were observed between countries (genus structure: R=0.38; p=0.001; trait combination: R=0.28; p=0.001) with the lowest significant differences noticed between Denmark, Slovakia and Sweden both by genera and traits (Table 2). Although, the temporal factor resulted significantly different also using traits, Global R resulted very low compared to genus structure results (genus structure: R=0.19; p=0.001; trait combination structure: R=0.07; p=0.002).

The above insights are confirmed also by the trends observable from the k-dominance curves, where nematode diversity is consistent among genus and code trait combination (Figs. 7 – 9). The only exception as remarked by the multivatiate analyses were the comparisons among countries in the study on modified maize (Fig. 9).

Fig. 7.

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Fig. 9.

The identification based on morphology is a time-consuming activity especially when reports must return in a short time, and large-scale biomonitoring surveys are required. Therefore, alternative methods must be explored and developed. Environmental DNA (eDNA) is a technique that will increase our ability to quantify ecosystem biodiversity and overcome labour-intensive traditional surveys. However, it cannot be the only forward way due to the existence of some possible problems such as imperfect detection and taxonomic assignment, species quantification, assessing ecological status (Beng & Corlett, 2020), and economic costs not always accessible to each research group or environmental agency. In this scientific context, the trait combination aims to provide a practical and easily accessible approach for reading and quantifying changes in the nematodes' community structure. This approach, coupled with advances in machine learning also referred to as deep learning or artificial intelligence (AI), could open a new avenue for nematode ecological assessment in future (Colin et al., 2017; Bogale et al., 2020). Indeed, the development of machine learning for the automated detection of a few morphological nematode traits and their immediate combination into a trait code could be even more easily calibrated than in case of genera (Shabrina et al., 2023) and species level (Thevenoux et al., 2021), allowing for the faster deployment of AI systems and the skipping of time-consuming steps in the usual identification process. Promising results have been documented in marine systems using the trait combination (Semprucci et al., 2022). This is the first time that trait combination is tested to detect the community changes in the soil free-living nematodes.

Multivariate analysis performed using the nematodes identified at genus level and compared with those obtained by trait combination revealed consistent results in all the three study cases analysed. In detail, in the forest ecosystem, both approaches showed that the type of forest management was the most relevant factor influencing the nematode structure, followed by the forest age. This supports the idea that forest management and the stand age play key roles in determining the soil nematode composition (Čerevková et al., 2021). Managed spruce forest (SPR) and the unmanaged mixed forest (UNM) showed the most significant differences that resulted associated also to a marked presence of tolerant nematode taxa in the coniferous SPR forest (Čerevková et al., 2021). Additionally, the combination of traits was more sensitive than taxonomic composition in detecting the differential successional stage of the forest vegetation. The age of the forests showed the highest level of dissimilarity likely due to the highest values of nematode richness, total abundance, biomass, and diversity were found in the youngest forest stands, regardless of forest type (Čerevková et al., 2021).

In the grassland system, a primary effect of the ecosystem's type was discovered in the succession from newly established meadows to permanent pastures and permanent meadows, while no significant differences were observed between permanent meadows and pastures (Čerevková, 2006). It is further noteworthy that the level of significance revealed by ANOSIM among ecosystems was perfectly the same (see Global R level). Furthermore, both approaches highlighted a greater geographic effect, with the Stropkov site revealed the most noticeable differences.

The statistical analysis performed on the response of soil nematode communities to Bt maize cultivation was the only case in which the R values of ANOSIM resulted visibly lower than those obtained by taxonomic identification. However, again, both the approaches revealed similar trends: the effect of the crop location and sampling periods on the soil nematode communities was more pronounced than that of the Bt genetic modification. Moreover, trait combination supports the idea that, in contrast with data collected by Neher et al. (2014) and Manachini and Lozzia (2002), Bt maize had no effect on soil nematode communities (Čerevková et al., 2018). Observing the k-dominance curves, trait combination perfectly mirrored the genus diversity trends with the only exception being the countries in the Bt maize cultivation study. That makes it possible to support the trait combination as indirect measure of biodiversity loss.

As demostrated, the present approach can certainly allow a survey of environmental disturbance effects on the soil nematodes community structure. Furthermore, even if, at the moment, it is not possible to assign an ecological quality status to an enviroment with this method, it could be in the future. Indeed, after the analysis of a wide data set of samples in well-discernible environmental disturbance gradient, it could be possible to find recurring combinations of morpho-functional traits that, therefore, could be regarded as indicators of good ecological quality or sentinels of pollution giving a further significant contribution to the biomonitoring assessment with soil nematodes.

Ecological and, above all, biomonitoring surveys require smart and rapid approaches to detect possible variations of the faunal communities after a perturbation. Recently, a combination of morpho-functional traits was proposed as an alternative method to document changes in the marine nematode community structure. By assigning together each trait with a single number, the authors have created a data matrix based on a series of codes that was able to perfectly mirror the taxonomic structure of the marine nematode community at the genus level. Therefore, the same approach has been used to understand if it is applicable to soil nematodes, but considering an adapted version of morphological traits such as: buccal cavity morphology, amphideal fovea size and shape, morphology of the cuticle, and pharynx. We demonstrated that the matrices based on genus level and trait combination gave the same results in all three study cases considered. Therefore, this approach makes it possible to suggest that its implementation, associated with advances in machine learning, could transform nematode ecological surveys.