Exploring plant diversity through soil DNA in Thai national parks for influencing land reform and agriculture planning

Introduction

Thailand has been ambitiously aiming to have a forest coverage of 40% throughout the country, but this goal, set in 1985, has yet to be accomplished. However, satellite data to assess forest changes in tree density indicate that areas surrounding forests, e.g., agricultural areas and neighboring settlements, had a net gain in tree density (Reytar, Stolle & Anderson, 2019). Forest loss is nevertheless outpacing forest gain in Thailand. Forest coverage has declined from approximately 70% in 1950 to 31% in 2018 (Royal Forest Department, 1999). Deforestation has been occurring to an extreme degree in many parts of Northern Thailand (Delang, 2002; Virapongse, 2017).

Numerous studies have shown that deforestation results in a loss of plant diversity (Barlow et al., 2016; Giam, 2017; Decaëns et al., 2018). Agricultural expansion is one of the major drivers for deforestation in Thailand and several other countries in Asia, which resulted in plant biodiversity loss having adverse effects on ecology and climate (Jayathilake et al., 2021; Hosonuma et al., 2012). Thailand was endowed with cultivable land covering over 50% of the country’s land area (Land Development Department, 2012). As a result, the change from subsistence agriculture to cash crops cultivation, required an expansion of the agricultural land base (Jamroenprucksa, 2007). Over the past few decades, the area of agricultural land has expanded at the expense of the forest biodiversity. Conservation of biodiversity depends on the biological monitoring of plant species distribution not only for preserving threatened species, but also for maintaining the resilience and health of the ecosystems. Species monitoring in empirical ecological studies has thus far been relied on the morphology-based species identification. This is usually performed by morphological investigation and by counting individuals in the field (Elliott & Jonathan Davies, 2014). Obtaining biodiversity data solely by existing conventional approaches is hindered by several factors, including lack of diagnostic characters, the requirement of taxonomic expertise, as well as the associated expenses (Yoccoz et al., 2012; Fahner et al., 2016). In order to improve our understanding on the state of forest diversity, novel assessment methods should be applied characterized by sensitivity, effectiveness and reliability.

The latest sequencing technologies have paved the way in diversity studies. High-throughput sequencing (HTS) of DNA barcode amplicons (DNA metabarcoding) has proved to be a robust, accurate and efficient approach to survey biodiversity (Epp et al., 2012; Taberlet et al., 2012a; Yoccoz et al., 2012). Traces of living organisms including animals, plants and fungi can be accumulated and detected in the environmental DNA (eDNA). eDNA metabarcoding has been used to analyze the complex DNA from environmental samples like soil, water, air and feces (Drummond et al., 2015; Creer et al., 2016). Several markers are now available for use in the eDNA metabarcoding for various groups of organisms (Drummond et al., 2015; Fahner et al., 2016). Given that eDNA metabarcoding is a powerful technique offering many possibilities, we have used this approach to explore soil eDNA, which is expected to reflect taxonomic richness and diversity of plants in the studied area.

Deforestation is an ongoing problem in Northern Thailand and especially the Doi Suthep-Pui National Park (Marod et al., 2014). Doi Suthep-Pui National Park is the 24th national park, located in Chiang Mai Province. There are different altitudes in the National Park ranging from 330 m to 1,685 m ASL, resulting to a great variety of flora and fauna. The forest ecosystem of the Doi Suthep-Pui National Park is known for its wide indigenous genetic diversity. The major forest types represented in Doi Suthep-Pui National Park include the deciduous forest of the lowlands (deciduous dipterocarp, bamboo deciduous forest and mixed evergreen deciduous forest) and the evergreen forest of the uplands (Maxwell & Elliott, 2001). Although the national park is protected by various conservation measures, it is still facing plant diversity loss due to deforestation. Thus, eDNA data on species diversity is required for effective monitoring of biodiversity in this area for conservation and management purposes.

Materials & Methods

Results

In this study, we used eDNA metabarcoding method to explore plant diversity from soil sampled at four forest types in Doi Suthep-Pui National Park. We obtained a total of 2,031,271 g/h sequence reads from 12 different samples including Coniferous (CA1-3), Dry dipterocarp (DD1-3), Dry evergreen (DE1-3), Hill evergreen (HE1-3) soils (Fig. 1). Numbers of processed reads over the downstream analysis of each sample are shown in Table 2.

Differences in diversity between samples were measured using the Shannon diversity index (Fig. 2). The alpha diversity results indicate that Coniferous (CA) and Hill Evergreen (HE) samples present higher mean species diversity, in comparison to Dry Dipterocarp (DD) and Dry Evergreen (DE) samples. Moreover, we performed Principal Component Analysis and Hierarchical clustering in order to investigate how are the samples clustered. To this end the OTU table was used on which Total Sum Scaling (TSS) normalization was applied. In Fig. 3A. The result of Hierarchical clustering with the Euclidean distance method and the Ward.D clustering method is shown. In Fig. 3B. all samples are projected in PC1–PC2 dimensional space. In both cases the Coniferous (CA) and Hill Evergreen (HE) samples are grouped together, in agreement with the alpha diversity results.

According to the species annotation results (1. 7578  × 10⁶ reads), the statistics of sequence number were placed in different classification levels i.e., genus and species. The dominant taxa among all samples, which were obtained from conventional survey and our analyses are displayed in Table 3. Interestingly, there are 31 plants that could not be identified at the species level and nine that were only visually identified but could not be detected by the eDNA method (Table 3). Analysis of DNA data from these 40 species in the GenBank database showed that none of those species had the trnL sequence deposited (Supplementary data 1).

Furthermore, results from our study on the trnL region compared with the available sequences in GenBank showed that in a total of 1,225 plant species in Dipterocarpaceae and 1,101 species in Fagaceae family, there were only 268 (21.9%), and 154 (14.0%) species having trnL sequences deposited in the database, respectively, thus hindering the eDNA metabarcoding identification for these species. There are three, nine, eight and five plant species found only in the coniferous (CA), dry dipterocarp (DD), dry evergreen (DE) and hill evergreen (HE) community, respectively. Nine species were found in all forest types (Fig. 4). Interestingly, our molecular analyses showed traces of crops that were not expected to be found in the forest including lettuce (Lactuca sativa), maize (Zea mays), wheat (Triticum timopheevii) and soybean (Glycine max). Additionally, these crop plant species, which were found in the soil samples, were not visually detected in situ during the collection of the soil samples.

Discussion

Herein, eDNA metabarcoding analysis revealed that unique plant groups are present in specific forest types, whereas some species were detected in all sample types. A strong congruence between the morphological- and eDNA-based data of plant diversity in the studied areas was also observed. The alpha diversity results indicate that Coniferous (CA) and Hill Evergreen (HE) samples present higher mean species diversity in comparison to Dry Dipterocarp (DD) and Dry Evergreen (DE) samples. Interestingly, morphological assessment only focusses on tree species and thus excludes the smaller plants like shrubs, herbs and grasses, such as Alloteropsis, Canavalia, Germainia and Miscanthus. However, the soil eDNA metabarcoding reveals both above- and below-ground species and assesses the composition and richness of plant communities from soil or sediment samples. Several studies reported higher eDNA-based diversity compared to traditional sampling approaches (Epp et al., 2012; Hiiesalu et al., 2012; Pansu et al., 2015; Alsos et al., 2018; Matesanz et al., 2019).

Two popularly used single-locus regions, trnL and rbcL, have been the markers of choice for plant eDNA metabarcoding. Although trnL gave better results of species richness in some studies, rbcL also showed higher sequence recovery of target taxa in others (Epp et al., 2012; Yoccoz et al., 2012; Fahner et al., 2016; Mallott, Garber & Malhi, 2018). Recently, the nuclear ribosomal internal transcribed spacer (ITS) is becoming popular marker of choice in the field, showing a high level of sequence divergence. The ITS2 region has greater coverage in vascular plant species sequences on GenBank when compared to the rbcL and trnL (Fahner et al., 2016). However, plant species have been misidentified as fungi in several studies given the limited nucleotide variation in the ITS2 region between fungi and plants. The main factor influencing eDNA metabarcoding results is the lack of relative DNA sequences in the databases (Edwards et al., 2018). For example, although Castanopsis acuminatissima, Lithocarpus elegans, and Quercus kerrii are common species in the study region, there was no available trnL reference sequence for these species, and thus could not be identified in our metabarcoding analysis. In addition, all 40 dominant plant taxa previously recorded in the Doi Suthep-Pui National Park lacked reference sequences in the GeneBank for trnL DNA barcoding region, thus none of them could have been identified through metabarcoding at species level in the soil samples (Supplementary data 1). DNA data of plants in Dipterocarpaceae and Fagaceae family are very scarce in the GeneBank. More comprehensive reference sequence database is required in order to increase species-level resolution for plant biodiversity assessments.

Herein, we report the identification of cultivated plant species, which were not visually detected during sampling. Plant DNA has been reported to remain in soil for up to 50 years and can be detected by metabarcoding (Yoccoz et al., 2012). The eDNA metabarcoding was able to detect crop plant species cultivated up to 8 years before soil sampling (Foucher et al., 2020). Interestingly, nearby lands and some areas in the Doi Suthep-Pui National Park used to be cultivated lands. Also, cultivated lands still exist within a 5–10 km radius of the forest areas where the soil cores samples were taken.

In addition, Christisonia, one of the rare plant genera of Thailand, was detected only in one replicate of soil samples collected from dry evergreen forest (DE). Inability to detect this species in some replicates might be due to the effects of PCR and variation in the soil material used for DNA extractions. Similar results have been previously published and thus sensitivity and reproducibility of the eDNA metabarcoding results have been a challenging issue (Boggs, Scheible & Meiklejohn, 2019). To avoid replicate variation, it has been suggested that performing technical replicates during PCR and pooling them before downstream processing could be effective (Lauber et al., 2013; Young, Weyrich & Cooper, 2016; Demanèche et al., 2017). Christisonia is a genus of root parasitic plants. The DNA concentration of these plants in the soil would be proportionally lower by the distance from host plant, as previous reported by (Osathanunkul, 2019) on an eDNA detection of a root parasitic species, Sapria himalayana. Some of the replicates of the DE sample were collected from areas far from the host plants, while the replicate in which Christisonia was detected was in close range. Therefore, the DNA concentration among the soil replicates was not equal and has led to variation in species detection.

The eDNA based method is more sensitive compared to the traditional morphology-based approaches. This is because it provides a comprehensive view of the targeted community, which is not only strongly reflecting current diversity, but also past biodiversity (Yoccoz et al., 2012; Smith et al., 2015; Foucher et al., 2020). Therefore, obtaining data from a soil DNA metabarcoding-based study would allow for better understanding of the studied areas. In our case, the presence of DNA from crop plant species in the soil samples collected from the forest still leads to a big question of whether we are now facing an agricultural intensification; however further investigation is needed.

Conclusions

The eDNA metabarcoding is a rapid method for monitoring biodiversity, which could greatly advance assessment and enable understanding of the threats to the ecosystems, and could lead to effective conservation strategies. The method was proven to be revolutionary in biodiversity research. Herein, we report a strong congruence between the conventional morphology- and eDNA-based data of plant diversity in the studied areas. In addition, traces of crops that were not expected to be found in the forest were found in the eDNA analyses but were not identified by visual detection. eDNA metabarcoding used for biodiversity studies could allow the understanding of possible biodiversity shifts and give an insight towards land use change. Thus, the presence of crop plant traces probably suggests that we might face an agricultural intensification, which might lead to loss of biodiversity. Nevertheless, land reform for agricultural use should be well-planned in order to preserve forest biodiversity and in this context, the eDNA-based technology could be of paramount importance in assisting correct policy measures and planning.

Supplemental Information