Biodiversity Conservation and Use

Factors Determining the Abundance of Red Swamp Crayfish (Procambarus clarkii) in a Large Lake Connected to the Yangzte River

  • WANG Yuyu , 1 ,
  • TAN Wenzhuo 1, 2 ,
  • LI Bin 1 ,
  • XIAO Yayu 1 ,
  • GUO Min 1 ,
  • LU Xiuyuan 1 ,
  • LEI Guangchun , 1, *
  • 1. School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
  • 2. Hubei Chenhu Wetland Nature Reserve Administration, Wuhan 430100, China
* LEI Guangchun, E-mail:

WANG Yuyu, E-mail:

Received date: 2021-07-31

  Accepted date: 2021-10-25

  Online published: 2022-01-08

Supported by

The Fundamental Research Funds for the Central Universities(2017ZY15)

The National Key Research and Development Program of China(2017YFC0405303)


Invasive species and habitat degradation are the main reasons for freshwater biodiversity loss. Reports on the habitat degradation and invasion ecology of Red Swamp crayfish (Procambarus clarkii) are few, although it is one of the most devastating invasive species in freshwater ecosystems. Based on a three-year investigation during 2017-2019 in West Dongting Lake, this study used Principal Component Analysis (PCA), Generalized Linear Model (GLM) and Bayesian model to analyze the relationships of P. clarkii stocks and environment factors in natural and modified wetlands. The results showed that the abundance of P. clarkii was positively correlated with total nitrogen, total phosphorus, water temperature, pH, water depth, and water transparency; while it was negatively correlated with dissolved oxygen and redox potential. The difference between P. clarkii stocks in natural and modified wetlands was nonsignificant. The P. clarkii stock decreased yearly, as levels in both 2018 and 2019 were significantly lower than in 2017. We concluded that inter-annual variation of the hydrological regime plays an important role in P. clarkii dynamics, and thus it is of great importance to ensure that the water level and flow velocity in summer to control the invasive P. clarkii.

Cite this article

WANG Yuyu , TAN Wenzhuo , LI Bin , XIAO Yayu , GUO Min , LU Xiuyuan , LEI Guangchun . Factors Determining the Abundance of Red Swamp Crayfish (Procambarus clarkii) in a Large Lake Connected to the Yangzte River[J]. Journal of Resources and Ecology, 2022 , 13(1) : 61 -67 . DOI: 10.5814/j.issn.1674-764x.2022.01.007

1 Introduction

Exotic species invasion is one of the major threats to global freshwater ecosystems (Dudgeon et al., 2006; Reid et al., 2018), and has become the main factor driving changes in the structure and function of freshwater ecosystems (Ehrenfeld, 2010). Invasive species change the composition of native communities by replacing or reducing the abundance of native species, thus affecting ecosystem processes and services (Tilman et al., 2014; Kingsford et al., 2016). Invasive species introduction is accelerated by human activities such as land cover changes and hydrological alteration.
The Red swamp crayfish (Procambarus clarkii) is a large omnivorous benthic animal, which adopts an r-type breeding strategy, with high fecundity, strong adaptability, high tolerance, and an ability to inhabit various aquatic environments (Oficialdegui et al., 2020). In 1929, it was introduced from Japan to Nanjing, China, and it has been treated as important aquaculture species in China since 1983, spreading throughout China during the 1980s to 1990s (Yue et al., 2010). P. clarkii can affect all levels of the freshwater food chain by reducing the abundance of macrophytes, preying on macroinvertebrates, and decreasing the abundances and growth of amphibians and fish (Gallardo et al., 2016). P. clarkii has great competitive superiority over the native species (Wang et al., 2021), although relatively few recent studies have reported its wild population distribution and abundance in the highly suitable habitats in the middle and lower reaches of the Yangtze River basin (Zhu et al., 2013).
West Dongting Lake is located on the highest terrain in Dongting Lake, and this aquatic ecosystem is facing severe challenges such as a decline in biodiversity, fragmentation of habitats, and invasions of exotic aquatic species due to high-intensity human activities (Jing et al., 2016; Dong et al., 2021). Since the 1990s, a large number of Populus nigra trees were planted by digging diches in the wetland (Jing et al., 2016), which artificially changed the topography of the lake and aggravated the fragmentation of the wetland. Studies have shown that the proportion of native wetland plants in poplar planting areas has been significantly reduced (Li et al., 2014), and the numbers of waterbirds and fish have been drastically reduced (Liu et al., 2013; Zhu et al., 2014). Although the poplars have been cut down, the ditches remain, cutting off the connections between modified wetlands and the mainstream, and the water level in the modified wetland is relative stable. The diversity of macrobenthos and fish in an artificially modified wetland is significantly lower than in the natural wetland (Dong et al., 2020; Li et al., 2020), and the species that are not sensitive to environmental changes become the main community components. Modified wetland has become an important shelter for the invasive P. clarkii and facilitates the population expansion of this species.
In order to protect freshwater ecosystem biodiversity in the Yangtze River Basin, the Chinese government announced the “Yangtze River Ten-Year Fishing Ban”, starting from January 1, 2020. During this ban productive fishery activity (including P. clarkii) is prohibited. P. clarkii used to be an important economic fishing target, but without human harvest pressure in the future, accurately predicting the distribution of P. clarkii needs solid scientific information. This study explored the distribution characteristics of the crayfish in the natural and modified wetlands of West Dongting Lake before the ten-year fishing ban in the Yangtze River, which provides a theoretical basis for the scientific evaluation and control of the impact of the P. clarkii invasion.

2 Materials and methods

2.1 Study site

Dongting Lake (111°40'‒113°10'E, 28°38'‒29°45'N, Fig. 1), China’s second largest freshwater lake, is one of two large lakes that are freely connected with the Yangtze River. It is an important biodiversity hot spot (Fang et al., 2006), providing foraging ground for hundreds of thousands of wintering migratory waterbirds (Guan et al., 2016). Due to sedimentation and intensive lake reclamation, the whole lake is divided into three sub-lakes, which are hydrologically connected through main river channels. Our study site, the West Dongting Lake (WDTL) (111°57'‒112°17'E, 28°47'‒29°07'N) is the most upstream section (Fig. 1). Dongting Lake hydrology is largely influenced by the prevailing subtropical monsoon climate, with large intra-annual variations in water level and flow. However, the Three Gorges Dam has greatly changed the relationship between Dongting Lake and the Yangtze River and influenced the Dongting Lake hydrological regime (Lu et al., 2018), resulting in great annual and seasonal hydrology variations (Fig. 2). According to the recorded data of Nanzui Hydrological Station in West Dongting Lake, the average annual water levels in lake in 2017, 2018 and 2019 were 30.4±1.5 m, 29.7±1.0 m, and 30.4±1.0 m, respectively; and the average annual flows in 2017, 2018 and 2019 were 2630.55± 1341.45 m3 s-1, 1975.26±1347.22 m3 s-1, and 2338.76± 1475.66 m3 s-1, respectively. In 2017, the average annual lake water level and flow were the highest among the three study years (Fig. 2).
Fig. 1 Aerial view and photos of the study site

Note: Blue arrows indicate the approximate flow direction. The photos on the right show the two types of habitats sampled in this study.

Fig. 2 Water level and flow of WDTL from March to November during 2017-2019

Note: Shadows in the figure represent 95% confidence intervals.

In the late 1980s, a planting program in WDTL was started using P. nigra, an introduced fast-growing tree for wood production. To ensure that the young trees would survive the summer flooding, high diches were dig by pushing up the lakebed sediments, leaving a network of artificial ditches with depths varying from 1.0 to 2.5 m. These ditches had substantially reduced the hydrological connectivity in comparison with other habitats (Dong et al., 2021), providing suitable habitat for P. clarkii (Li et al., 2020).

2.2 Sample collection

P. clarkii crayfish were sampled using fyke nets (1200 cm in length, 30 cm in width and 30 cm in depth, mesh size 1 cm, with two doors at both ends) during March to November from 2017 to 2019, except for the winter when P. clarkii stay in holes for wintering. Samples were collected at 24 locations across the WDTL, 17 of which were from the heavily modified ditches at P. nigra plantations (referred to as modified hereafter) and seven were from natural open water areas near the wet meadows (referred to as natural hereafter), with water depths of less than 2.5 m according to the crayfish habitat preferences (Fig. 1). We set three repetitions of nets at each sample site. The nets were set at 9:00-10:00 am for approximately 24 hours and retrieved the following morning. All samples were transferred to the laboratory for identification, counting, and weighing. Crayfish relative abundance (catch per unit effort, CPUE) was calculated for each site.

2.3 Environmental variable measurements

At each sample site, the water depth, water transparency, pH, water temperature, and redox potential (ORP) were measured in situ. Water depth was measured with a handheld sonar depth sounder SM-5A. Water transparency was measured using a Secchi disk. Water pH, temperature, and ORP were recorded using a YSI multiprobe (YSI Professional plus). Water samples of 5L were also taken for laboratory analysis of total nitrogen (TN) and total phosphorus (TP) following the standard methods of APHA (1998).

2.4 Data analysis

In this study, the t-test was used to analyze P. clarkii CPUE and environmental factor variation between natural and modified habitats. To analyze the relationships between habitat environmental factors and P. clarkii CPUE, we firstly used the Vegan package in R (4.0.4) to perform Principal Component Analysis (PCA) and select the key environmental gradients. Then, the relationships between the principal components and log-transformed crayfish CPUE during the three investigation years at the two types of habitats were analyzed using the Generalized Linear Model (GLM) (with the habitat type as a fixed factor, and the sampling time as a random factor). This analysis used the lmer function in the lme4 package, and the Bayesian mixed models were built using the brm function in the brms package to explore how crayfish stocks responded to each of the environmental factors.

3 Results

3.1 2017-2019 crayfish CPUE variations

P. clarkii was active from April to November, and its abundance was high from May to August, after spring mating and hatching (Fig. 3). The average P. clarkii CPUE for the three-years (2017-2019) was 13.45±26.94 (ind net-1). Crayfish abundance and average CPUE was largest in 2017 at 23.87±35.87 (ind net-1), and smallest in 2018 at 3.37±3.30 (ind net-1). The CPUE in 2017 was significantly higher than in 2018 and 2019 (Table 1), however, the differences in CPUE for different habitat types were insignificant (Fig. 4).
Fig. 3 Monthly P. clarkii CPUE from March to November during 2017-2019
Table 1 T-test results of P. clarkii CPUE (ind net-1) during 2017-2019
Year Mean-different SD P value
2017 2018 20.50 3.96 <0.001
2019 19.24 3.52 <0.001
2018 2017 -20.50 3.96 <0.001
2019 -1.27 4.27 0.953
2019 2017 -19.24 3.52 <0.001
2018 1.27 4.27 0.953
Fig. 4 T-test results of P. clarkii CPUE (ind net-1) during 2017-2019

3.2 PCA analysis of key water environmental factors

The PCA analysis results of nine environmental factors of WDTL are shown in Table 2 and Table 3. The first three axis interpretations show that PC1 explained 22.2%, PC2 explained 20.6%, and PC3 explained 13.8%, for a total of 56.6% of the variance of the environmental factors (Table 2).
Table 2 Analysis statistics of the PCA
Main component PC1 PC2 PC3
Eigenvalue 1.8 1.6 1.1
Variance explained (%) 22.2 20.6 13.8
Cumulative Variance explained (%) 22.2 42.8 56.6
Table 3 Correlations of water environmental factors and PCs
Water environment factor PC1 PC2 PC3
Water depth (Depth, cm) 0.09 -0.63 0.08
Water transparency (Trans, cm) 0.09 -0.40 -0.49
Water temperature (Temp, ℃) 0.45 -0.33 0.22
Dissolved oxygen (DO, %) -0.14 -0.03 -0.73
Acid-base degree (pH) 0.105 0.43 -0.27
Redox potential (ORP, mv) -0.36 -0.33 -0.11
Total nitrogen (TN, mg L-1) 0.62 0.15 -0.18
Total phosphorus (TP, μg L-1) 0.49 -0.09 -0.22
The main determinants of PC1 were TP and TN, which were positively correlated with PC1, and PC1 was negatively correlated with ORP and water temperature. PC2 was mainly determined by water depth and pH; while PC2 was negatively correlated with water depth, transparency, and water temperature, and positively correlated with pH (Fig. 5). PC3 was mainly determined by DO and water transparency, and was negatively correlated with these two factors (Table 3).
Fig. 5 PCA analysis of key environmental factors

3.3 GLM and Bayesian Model analysis results

A GLM model was established to analyze the influences of PC1-3, habitat type, survey year, and survey month on P. clarkii CPUE. The analysis found that PC1, PC2, PC3 and survey time all significantly affected crayfish CPUE (Table 4).
Table 4 GLM model results of the impacts of PC1, PC2, PC3, habitat type, survey time on the CPUE of P. clarkii.
Factor ValueGLM P value
Intersection 0.948 0.0521
PC1 0.433 0.0039
PC2 -0.316 0.0199
PC3 0.377 0.0027
Habitat type -0.470 0.0640
Year - 0.0028
Month - 0.0002

3.3.1 Relationships between P. clarkii CPUE and the main components of the water environment

The P. clarkii CPUE was positively correlated with PC1 and PC3, and negatively correlated with PC2 (Fig. 6), which suggested that P. clarkii CPUE was positively correlated with TP, TN, water temperature, pH, water depth, and transparency, and negatively correlated with DO and ORP.
Fig. 6 The relationships between CPUE of P. clarkii and PC1, PC2, PC3.

3.3.2 The impacts of habitat type and survey time on CPUE

The P. clarkii CPUE in 2017 was significantly different from 2018 and 2019 (Fig. 7). According to the results of the Bayesian model, there was no overlap between the confidence intervals of 2017 and 2019 (Fig. 7). The P. clarkii CPUE was the largest in 2017, and smallest in 2019. However, the P. clarkii CPUE in 2018 was not significantly different from either 2017 or 2019.
Fig. 7 The impact of sampling year on P. clarkii CPUE

Note: The black point is the average of the fitting results for each year, the black short horizontal line is the confidence interval, the blue vertical line is the average of all the fitting results, and the black dotted line is the distribution range of 95% of the fitting results.

From the perspective of different habitat types, the CPUE of the crayfish in the modified wetland was slightly higher than that in the natural wetland, but the difference was not significant (Fig. 8).
Fig. 8 The impact of habitat type on P. clarkii CPUE

4 Discussion

4.1 Relationships between the P. clarkii CPUE and environmental factors

Water column TN and TP were positively correlated with the P. clarkii CPUE, because as nutrient contents increase, the primary productivity increases correspondingly. On the other hand, P. clarkii activities such as burrowing and feeding would destroy the growth of large aquatic plants and increase the resuspension of sediments, so an increase in its abundance would aggravate the transition of shallow lakes from clear water dominated by large aquatic plants to turbid water dominated by phytoplankton, thus aggravating the eutrophication of water bodies (Matsuzaki et al., 2009). P. clarkii CPUE was negatively related with the DO content, which was consistent with studies on the rivers of Louisiana, USA, the hometown of P. clarkii, where the individual size and average CPUE of crayfish in a hypoxic environment are both smaller than in a normal dissolved oxygen environment (Bonvillain et al., 2015). Water ORP determines the forms of water nutrients and plays an important role in nutrient circulation. Its value can affect the oxidation degree of sediment, and thus affect the survival rate of macrobenthos which are also important food resources of P. clarkii. The results of this study indicated that P. clarkii CPUE was positively correlated with temperature. A review of P. clarkii global population temperature tolerance found that its optimal growth temperature range is 21.8-26.7 ℃, and its highest temperature tolerated is 35 ℃ (Westhoff and Rosenberger, 2016). P. clarkii is a native of tropical regions while the middle-low Yangtze River is a subtropical region, therefore its abundance showed an increasing trend with temperature. This study also found that the P. clarkii CPUE was positively correlated with water depth, which was consistent with the findings in the Pacific Northwest lakes of the United States (Larson and Olden, 2013), probably because a deep water depth could provide a more diversified habitat for P. clarkii as refuge. Submerged plant abundance at WDTL was positively related with water transparency (Guo et al., 2020), and since such plants provide shelter for living benthic animals, P. clarkii CPUE was also positively related to water transparency. Although P. clarkii can tolerate a low pH environment through its hard exoskeleton, as the pH decreases, phytoplankton, zooplankton and macrobenthos that are sensitive to water acidification would disappear, resulting in insufficient food resources for P. clarkii. For example, snails disappear when the pH drops to 5.2 due to an insufficient availability of Ca(HCO3)2. A survey of 54 American lakes found that average pH of lakes with P. clarkii survival was 7.2 (Larson and Olden, 2013).

4.2 Differences in the CPUE of crayfish in different survey years

P. clarkii prefers to live in waters with abundant vegetation, high nutrient content and slow water flow, while it is less inclined to inhabit areas with fast flow rates and wide water surfaces (Cai, 2011). The reduced sediment deposition due to fast flow leads to a lack of potential food resources for P. clarkii, and prevents P. clarkii from resisting the adverse effects of environmental changes through burrowing.
In this study, the P. clarkii CPUE varied annually along with the fluctuations in the water level. The water level of WDTL from March to April of 2017 was more consistent with the multi-year average water level, while the water levels during the P. clarkii breeding seasons in spring of 2018 and 2019 were lower than the multi-year average water level. A low water level in the breeding season was detrimental to the survival of the larvae of P. clarkii which hatched that year. Because the water depth was relatively shallow, sufficient refuge was not available, which would lead to fierce competition among species. The water levels in the summer and autumn of 2017 were higher than those in 2018 and 2019 at the same time. During the highwater time, the turbidity of the water is high, and the continuous highwater level causes large numbers of plants to die, thereby reducing the number of adult crayfish that successfully overwinter. Therefore, the abundance of P. clarkii in 2018 decreased. As the water level in the summer and autumn seasons of 2018 decreased, the number of adult P. clarkii which successfully overwintered increased. In 2019, the number of P. clarkii increased, but it was still lower than in 2017. Studies on the control strategy for P. clarkii in Italian ditches also found that increasing water level and flow velocity can help control the numbers of P. clarkii (Gavioli et al., 2018).

5 Conclusions

Based on an investigation in West Dongting Lake for three years (2017-2019) before the Yangtze River Ten-Year Fishing Ban Plan, we found that the P. clarkii CPUE was positively correlated with TP, TN, water temperature, pH, water depth, and water transparency, and negatively correlated with DO and ORP. This study also proved that the P. clarkii CPUE varied monthly and annually, and the stock decreased year by year. Inter-annual variation in the hydrological regime played an important role in influencing P. clarkii dynamics with the hydrologic regime. Restoring the hydrological connectivity of the wetland, as well as ensuring the highwater level and fast flow in summer will help to control the population of this crayfish.
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