Assessing the impact of biological invasion on fish community structures in Japanese lakes: A macroecological approach using environmental DNA metabarcoding

doi:10.21203/rs.3.rs-3760411/v1

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Assessing the impact of biological invasion on fish community structures in Japanese lakes: A macroecological approach using environmental DNA metabarcoding

https://doi.org/10.21203/rs.3.rs-3760411/v1

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The biological invasion of aquatic ecosystems has negative effects on competition and predation. These ecological impacts on native communities may also affect two processes that are important in determining community structures, namely, the environmental and spatial processes. Here, we using lake fish community composition estimated through environmental DNA metabarcoding, we examined the effects of invasive species on the community structure determination processes in lakes. The objective was to describe the relationship between fish diversity and invasive species in lakes and to estimate the explanatory power of environmental factors with regard to variation in community composition among lakes using direct gradient analysis, i.e., distance-based redundancy analysis. Further, we employed variation partitioning to examine how the explanatory power of environmental factors and spatial structures for variation in community composition varied with the presence of invasive species. The environmental slope analysis showed that the explanatory power of environmental factors for variation in community composition among lakes was higher in communities without invasive species. A comparison of the relative importance of environmental factors and spatial structure in determining community composition between communities, excluding invasive species, and communities with invasive species showed that the relative importance of environmental factors was higher in communities without invasive species, highlighting the possibility of differences in dispersal abilities between native and invasive species.

eDNA

freshwater

invasive species

db-RDA

variation partitioning

Biological invasions can cause fundamental changes in ecological communities, biodiversity, and ecosystem functioning, processes, and services (Vander Zanden et al. 2016; Pukk et al. 2021; Pintar et al. 2023). In aquatic ecosystems, biological invasions have adverse effects on competition and predation, leading to decreased biodiversity and an increased risk of species extirpation (Mills et al. 2004; Grabowska et al. 2010). With regard to closed ecosystems such as lakes, fish communities may produce particularly pronounced responses to stressors such as biological invasion (Jackson et al. 2001). The introduction, establishment, and expansion of invasive species with competitive traits can markedly affect native communities in lakes and connected watersheds. Therefore, the management of invasive species is crucial for the conservation of lake ecosystems. Furthermore, studying the effects of invasive species on fish community structures is important for determining suitable methods to avoid detrimental effects on ecosystems.

Environmental conditions of habitats and their spatial structures are important factors governing the mechanisms that determine community structures, including those of invasive species (Holyoak et al. 2005). Lake morphology and geographic location are the main factors influencing fish communities in lakes. In particular, lake morphometrics and geographic location, such as area and depth, are strongly associated with water quality, ecological niches, and dispersal potential and thus have a profound impact on fish community composition and size (Holmgren and Appelberg 2000; Mehner et al. 2007; Brucet et al. 2013; Emmrich et al. 2014; Arranz et al. 2016). The ecological characteristics of the organisms that compose a community are strongly related to the influence of environmental and spatial structures on community-determining mechanisms and can change the relative importance of environmental factors and spatial structures to community-determining processes (Beisner et al. 2006; Soininen et al. 2007). The introduction and establishment of invasive species that possess ecological traits different from those of native communities can potentially interact with the environmental and spatial factors that affect fish community structures in lakes. Assessing the effect of invasive species on community structure from a macroecological perspective involves estimating their influence on the two primary processes governing community structure determination. In this study, we aimed to improve the general understanding of how invasive species contribute to the dynamics of fish community structures in lake ecosystems.

Here we used fish community information collected from 18 lakes covering a wide latitudinal gradient in Japan to assess the effects of invasive species on fish community decision structure. First, we estimated the alpha diversity of each lake using fish community composition data to assess the effects of invasive species on fish diversity. Second, we examined how the explanatory power of environmental factors for variations in lake fish community structure changed in native and invasive fish communities, using data on fish community structure, lake morphology, and local climate. Finally, we assessed the relative importance of environmental factors and spatial structure on community structure determination in the native and invasive fish communities. To this end, we used fish community data obtained through environmental DNA (eDNA) metabarcoding. eDNA metabarcoding has been successfully applied in various aquatic environments, such as oceans, rivers, and lakes to study organism abundances and community structures in aquatic ecosystems (Rees et al. 2014; Valentini et al. 2016; Pawlowski et al. 2022). eDNA methods can effectively detect rare species owing to their high sensitivity (Balasingham et al. 2018), and they are also suitable for detecting invasive species in the early stages of introduction (Goldberg et al. 2015). Therefore, eDNA metabarcoding can be considered an effective approach for estimating the effects of invasive species on the mechanisms determining fish community structures.

Fish community data

We used an eDNA dataset of fish communities from 18 lakes in Japan as previously reported (Doi et al. 2023). Details of the study sites, sampling, sample treatments, and DNA sequencing have been described by Doi et al. (2023). Briefly, 18 lakes across Japan were selected as study sites (Fig. 1), and six sampling sites were selected along the shores of each lake with equal distances between them. From 14-July to 4-Nov-2015, water samples were collected at each of the six sites. To obtain water samples, 1 liter of surface water was collected in a bottle. The samples were vacuum-filtered through 47-mm GF/F glass fiber filters (nominal pore size of 0.7 µm, manufactured by GE Healthcare) in the laboratory. eDNA was extracted from water filters as described by Uchii et al. (2016) and was subsequently purified using a DNeasy Blood and Tissue kit (Qiagen, Hilden, Germany). The two-step PCR procedure used for Illumina MiSeq sequencing (Illumina, San Diego, CA, USA) was performed as described by Fujii et al. (2019). The first PCR was carried out using MiFish-U-F and MiFish-U-R primers, followed by a second PCR of 12 cycles with a 12-µL reaction volume. Purified PCR products were analyzed by agarose gel electrophoresis and paired-end sequenced on a MiSeq platform (Illumina). The bioinformatics analysis procedure was described in detail by Fujii et al. (2019), including the removal of primer sequences and merging of identical sequences using UCLUST (usearch 7.0.1001). Taxonomic annotation was performed using a local BLASTN search in BLAST 2.2.29, based on an established reference database of fish species for processed reads (Miya et al. 2015). The identified species and genera were determined using previously described methods (Sato et al. 2017; Fujii et al. 2019).

Invasive fish species data

A list of invasive fish species was extracted from the Invasive Species of Japan database provided by the National Institute for Environmental Studies (https://www.nies.go.jp/biodiversity/invasive/DB/etoc5_fishes.html). The database was based on the invasive state of fish in Japan.

Environmental data

Environmental data on lake morphology as used by Doi et al. (2023) were used in the present study. Lake morphology data (surface area [km²], maximum water depth [m], altitude [m], and perimeter [km]) and lake type (trophic status and water type [brackish or freshwater]) were obtained from Tanaka (1992). An open climatic dataset from CRUTEM4.6.0.0-2019-12, which is based on Google Earth on a 0.5° latitude × 0.5° longitude grid, was used to obtain data on average monthly temperatures (Jones et al. 2012; Osborn and Jones 2014). For the analysis, we utilized time-series data pertaining to the target lakes, specifically focusing on the monthly mean temperature groups averaged from 1990 to the most recently recorded data.

Statistical analyses

All statistical analyses were performed using R software v4.3.0 (R Core Team 2023). To evaluate the diversity of fish communities in the lakes, the Shannon-Wiener and inverse Simpson’s diversity indices were calculated based on the eDNA sequencing data. Shannon and Simpson diversity indices are commonly used to measure alpha diversity—higher Shannon and higher inverse Simpson index values indicate greater community diversity. To estimate the relationship between richness and invasive species in the fish communities of the lakes, we estimated the relationship between the total number of detected fish species and the number of invasive species using Pearson’s correlation test with the "cor.test" function of R software. In addition, the relationship between the calculated diversity index, the percentage of invasive species in the fish community, and the location (latitude) of the lake was also estimated using a Pearson’s correlation test.

Distance-based redundancy analysis (db-RDA), as discussed by Legendre and Anderson (1999), was used to assess how environmental gradients correlated with the variation in fish community composition. Analyses were conducted using three groups: one containing all observed fish species, one excluding invasive species (i.e., only native species), and one excluding native species (i.e., only invasive species). The environmental variables in the db-RDA included monthly mean temperature, lake morphology data (surface area [km²], maximum water depth [m], and altitude [m]), and lake type (trophic status and water type [brackish or fresh water]). Bray-Curtis distances were calculated using the eDNA sequencing data of fish communities to perform db-RDA. The environmental variables in the db-RDA were standardized to remove arbitrariness in the units of measurement. In addition, collinearity was tested to select independent explanatory variables for statistical analyses using the variance inflation factor (VIF). For all explanatory variables, the VIF values ranged from 1.27 to 44.48. Therefore, one variable (lake perimeter) was excluded, and the VIF values were subsequently below five for all variables.

Variation partitioning (Borcard et al. 1992; Legendre and Legendre 2012) was applied to disentangle the relative contributions of environmental and spatial processes to the lake fish community composition. The spatial structure of sampling sites is typically described using Moran’s eigenvector maps (Dray et al. 2006), which produce a set of orthogonal spatial variables derived from the geographical coordinates of the study sites. These orthogonal spatial variables were used as explanatory variables to detect spatial signals. The same set of environmental variables for db-RDA was used for this analysis.

db-RDA and variation partitioning analyses were performed using R package vegan ver. 2.6.4 (Oksanen et al. 2019); the functions “dbrda” and “varpart” of the vegan package were used for these analyses, respectively.

Fish species diversity

The number of fish species in the fish community detected using eDNA metabarcoding in the 18 lakes ranged from 8 to 37 species per lake (Fig. 1). The minimum number of foreign invasive species detected per lake was 0, and the maximum was 11. The number of native and non-native fish species (richness and DNA reads) in all 18 lakes are shown in Fig. 2. Invasive species were detected in 17 of the 18 lakes, accounting for approximately 20% of the total number of species and DNA reads (Fig. 2; ESM. 1). A significant positive correlation was observed between the number of all detected fish species and the number of invasive species (Pearson's r = 0.53, p = 0.024). The Shannon and reverse Simpson indices for each lake ranged from 1.3 to 3.5 (Fig. 3) and from 1.6 to 8.9, respectively. Because the Shannon and inverse Simpson indices showed similar trends (Pearson's r = 0.95, p < 0.001), the Shannon index was used to perform the analyses described below. A non-significant negative correlation was observed between the Shannon index and the proportion of invasive species in each lake (Pearson's r = − 0.11, p = 0.676) as well as between the Shannon index and the latitude of each lake (Pearson's r= − 0.14, p = 0.57; Fig. 4).

db-RDA analysis

We conducted a db-RDA of the total fish assemblages identified in the 18 lakes. This ordination method employed six environmental variables as external criteria. The analysis produced a statistically significant model (p = 0.001; Fig. 5-a) illustrating the relationship between the six environmental variables and the variation observed in fish community composition across the 18 lakes. Based on the results of the calculation of the adjusted R² for this model, it explained 30.6% of the variation in the data. With the six environmental variables selected, the first two axes of the db-RDA explained 33.5% of the variability. The environmental gradient, which is considered to have the greatest influence on fish community composition, is represented by the first horizontal axis. The first axis (RDA1) was positively correlated with temperature, and the second axis (RDA2) was positively correlated with depth and with altitude (Fig. 5-a). In contrast, the lake surface area was less strongly correlated with either axis. Two gradients in the lake fish community structure were suggested: the first gradient was mainly oriented by temperature and water type, and the second gradient distinguished the variation between lake fish communities by depth, altitude, area, and lake type.

Under exclusion of invasive species, the db-RDA analysis yielded a statistically significant model (p = 0.002; Fig. 5-b) that demonstrated a relationship between changes in fish community composition and environmental factors. Based on the calculation of the adjusted R² for this model, this model explained 33.9% of the variation in the data. With the six environmental variables selected, the first two axes of the db-RDA analysis explained 35.9% of the variability. The first axis (RDA1) was positively correlated with temperature, and the second axis (RDA2) was positively correlated with depth, altitude, and area (Fig. 5-b). Two gradients in the fish community structure of the lake were suggested, similar to the results of the db-RAD analysis including all fish species.

When including exclusively invasive species in the fish communities, the db-RDA analysis yielded a statistically significant model (p = 0.002; Fig. 5-c), elucidating the connection between variations in fish community composition and environmental factors. Based on the calculation of the adjusted R² for this model, it model explained 32.3% of the variation in the data. With the six environmental variables selected, the first two axes of the db-RDA explained 23.9% of the variability. The first axis (RDA1) was positively correlated with temperature and area (Fig. 5-c,), and the second axis (RDA2) showed a stronger positive correlation with depth and altitude. Temperature and lake morphology were not correlated in the two previous RDA models; however, a weak negative correlation occurred between these variables in the analysis including only the invasive species.

Variation partitioning

Both, environmental variables and spatial structure influenced the determination of community structure in all three analysis modes: all species, native species only, and invasive species only (Fig. 6). For all species, environmental variables and spatial structure explained 46% of the variability in community structure (Fig. 6-a), with environmental variables exhibiting more explanatory power than spatial structure with regard to the degree of variability in community structure (27% environmental and 16% spatial). The interaction between the environmental variables and spatial structures explained a small fraction of the variance (4%). In the native community, environmental variables and spatial structures explained 51% of the variation in the community structure (Fig. 6-b), which was slightly higher than that in the total fish community (Fig. 6-a,b). The explanatory power was greater than that of all species, especially regarding environmental factors. In contrast, the explanatory power in the invasive community was 8% lower than that in the total fish community when analyzed for the invasive species-only community (Fig. 6-a,c). Explanatory power was lower in each of the environment and space, with a particularly larger decrease in the environment than in the space (environment: − 9%; space: − 2%). Furthermore, the explanatory power of the environment and space for community variation was 13% lower than that of the native species-only community. The explanatory power decreased for both environment and space, with environment in particular changing more than space (environment: − 15%; space: − 3%). The interaction between the environmental variables and spatial structures explained a small fraction of the variance (6%), followed by environmental variables or spatial structures alone. The proportion of covariance explained by the covariance of environmental factors and spatial structure was small, regardless of the presence or absence of invasive species.

We observed a significant positive correlation between fish community richness in the lakes and the number of invasive species. This confirms that invasive species may also lead to an increase in ecological diversity and not necessarily a decrease in species numbers (Thomas 2013). However, at some study sites, approximately 60% of the total species count and 80% of the total DNA reads were attributed to invasive species. Some lakes had a low percentage of invasive species in their fish community richness, but a larger percentage of total DNA reads was detected compared to other study sites. DNA read counts have been reported to be correlated with biomass (Stoeckle et al. 2021; Thomson-Laing et al. 2021). Because the high abundance and biomass of invasive species may reduce the abundance of native species through competition and predation (Cucherousset and Olden 2011), it is important to follow up the processes occurring in such lakes to further quantify community composition and predict future changes. The latitudinal gradient of biological diversity is well-established, and it decreases from low latitudes toward the poles (Fischer 1960). We found a similar pattern, which was, however, not statistically significant (Fig. 4-b). This result underscores the potential vulnerability of biogeographic patterns to contemporary anthropogenic effects on ecosystems. This pressing concern arises from the possibility that such effects may alter the observed latitudinal diversity gradient within lake fish communities.

We investigated the variation in fish community structures relative to environmental gradients using six environmental variables. Fish communities were placed along the axes according to the respective gradients of air temperature and lake morphology in three community patterns (native and invasive species, native species only, and invasive species only). Overall, there were small changes in the location of each lake along the axes and in the correlation of environmental variables with the axes among the three different community models. This means that the presence of invasive species may affect how environmental factors influence community structures. Changes in air temperature can be interpreted in terms of different latitudes. In fact, the latitude of study lakes and the monthly mean air temperature were strongly negatively correlated (Pearson’s r = -0.97, p < 0.001). A previous study on various European lakes showed that environmental characteristics such as dimension, turbidity, nutrient enrichment, connectivity, and the presence of non-native fish can alter the rate of fish assemblage change over a latitude gradient (Menezes et al. 2023). Our findings demonstrate that the presence of invasive species is a driving force of the variation in community structure along a latitudinal gradient. This conclusion was reinforced by the slight differences in the placement of each lake relative to the first axis (representing air temperature) across the three community patterns.

The impact of environmental factors and spatial structure on the variance in fish community structure among the lakes displayed fluctuations contingent on the existence of invasive species. The most prominent divergence in explanatory power occurred among communities composed solely of native or invasive species, with the greatest explanatory power observed in the native species communities. Notably, environmental factors consistently had more explanatory power than spatial structure, regardless of the presence of invasive species. The contrast in the relative importance of environmental factors and spatial structure was most significant in communities consisting solely of native species; this significance was reduced in communities containing only invasive species. These results highlight the complexity of fish community structures in response to invasion, emphasizing the importance of environmental factors, specifically among communities of native species. In addition, the significance of environmental factors in community structure determination is inversely related to dispersal capacity. Organisms with lower dispersal capacity are more affected by environmental factors (Beisner et al. 2006; Soininen et al. 2007). Furthermore, some surveyed lakes in densely populated areas are expected to experience high anthropogenic stress. Recent studies have suggested that aquatic habitats have undergone changes owing to anthropogenic stress, with pronounced benefits for highly competitive invasive species (Irz et al. 2004; Mor et al. 2022). The stressors include eutrophication, pollution, climate change, and introduction of invasive species. Overall, our findings elucidate the present conditions of several lakes with high potential for invasive species domination in the future. These insights bear significant implications for ecosystem management and conservation efforts, emphasizing the necessity of strategies that focus on fish community compositions of such lakes.

In this study, the effect of invasive species on the community structure of lake fish was assessed using eDNA metabarcoding data. For effective ecosystem conservation and management, it is essential to understand the interplay among variations in community structure, environmental factors, spatial organization, and ecological characteristics. Our results highlight the impact of non-native species on the fundamental processes that regulate fish populations in lakes, demonstrating the efficacy of eDNA metabarcoding as a reliable method for monitoring and modeling. Furthermore, they suggest that this approach can help predict future changes in fish communities, thus highlighting its value as a supplementary research tool. This approach provides important insights into the complex processes shaping fish community structures, thereby contributing to a comprehensive understanding of aquatic ecosystem dynamics.

Acknowledgements

We would like to acknowledge Doi et al. (2023) for providing the data.

Funding

This study was supported by the JSPS KAKENHI (grant number: 22K18429).

Conflicts of interest/competing interests

The authors have no conflict of interest to declare.

Ethics approval

Not applicable

Consent to participate

Not applicable

Consent for publication

Not applicable

Availability of data and material

The datasets used and/or analyzed in the current study are available from the corresponding author upon reasonable request.

Code availability

The datasets used and/or analyzed in the current study are available from the corresponding author upon reasonable request.

Authors’ contributions

Conceptualization: YO and HD. Data analysis: YO. Data interpretation: YO and HD. Preparation of Figures: YO. Writing: YO, HD.

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Assessing the impact of biological invasion on fish community structures in Japanese lakes: A macroecological approach using environmental DNA metabarcoding

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Abstract

Figures

Introduction

Materials and methods

Fish community data

Invasive fish species data

Environmental data

Statistical analyses

Results

Fish species diversity

db-RDA analysis

Variation partitioning

Discussion

Declarations

References

Supplementary Files

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