Naicheng Wu

Changes in benthic algal communities following construction of a run-of-river dam

Abstract Ecological responses to dam construction are poorly understood, especially for downstream benthic algal communities. We examined the responses of benthic algal communities in downstream reaches of a tributary of the Xiangxi River, China, to the construction of a small run-of-river dam. From February 2003 to August 2006, benthic algae, chemical factors, and habitat characteristics were monitored upstream and downstream of the dam site. This period spanned 6 mo before dam construction and 37 mo after dam construction. Benthic algal sampling yielded 199 taxa in 59 genera that belonged to Bacillariophyta, Chlorophyta, and Cyanophyta. Some physical factors (flow velocity, water depth, and channel width) and 3 algal metrics (diatom species richness, Margalef diversity, and % erect individuals) were significantly affected by the dam construction, whereas chemical factors (e.g., NH4-N, total N, SiO2) were not. Nonmetric multidimensional scaling (NMS) ordinations showed that overall algal assemblage structure downstream of the dam sites was similar to that of upstream control sites before dam construction and for 1 year after dam construction (p > 0.05). However, sites belonging to upstream and downstream reaches were well separated on NMS axis 1 during the 2nd and 3rd years after dam construction. Our results suggest that impacts of dam construction on benthic algal communities took 2 to 3 y to emerge. Further development of a complete set of indicators is needed to address the impact of small-dam construction. Our observations underscore the need for additional studies that quantify ecological responses to dam construction over longer time spans.

Impacts of cascade run-of-river dams on benthic diatoms in the Xiangxi River, China

The ecological effects of small run-of-river dams on aquatic ecosystems are poorly understood, especially on downstream benthic algal communities. We examined impacts of such dams on the benthic diatom community at a regional scale in the Xiangxi River, China. A total of 90 sites were visited, which were divided into five habitats (H1–H5) according to impact extent of each dam. Using partial least squares (PLS) modeling, we developed two predictive models (diatom species richness and total diatom density) based on environmental variables of an unregulated habitat (H1). These models were then used to predict species richness and total densities at impacted habitats (H2–H5) and residuals, i.e. the differences between observed and predicted values, were used to evaluate impact strength of flow regulation. Significant impacts of flow regulation on diatom species richness were detected at three impacted habitats (H3–H5), where observed species richness were significantly higher—70.6, 63.9 and 46.6%, respectively—than predicted values. Then, possible mechanisms for observed impacts were discussed. Further research is necessary to address the potential negative impacts of cascade run-of-river dams on other aquatic organisms in different seasons, and to explore more appropriate mechanisms for such impacts, which may lead to sustainable management strategies and help to determine the optimal ecological water requirement for the Xiangxi River.

Modeling daily chlorophyll a dynamics in a German lowland river using artificial neural networks and multiple linear regression approaches

Phytoplankton biomass is an important indicator for water quality, and predicting its dynamics is thus regarded as one of the important issues in the domain of river ecology and management. However, the vast majority of models in river systems have focused mostly on flow prediction and water quality with very few applications to biotic parameters such as chlorophyll a (Chl a). Based on a 1.5-year measured dataset of Chl a and environmental variables, we developed two modeling approaches [artificial neural networks (ANN) and multiple linear regression (MLR)] to simulate the daily Chl a dynamics in a German lowland river. In general, the developed ANN and MLR models achieved satisfactory accuracy in predicting daily dynamics of Chl a concentrations. Although some peaks and lows were not predicted, the predicted and the observed data matched closely by the MLR model with the coefficient of determination (R2), Nash–Sutcliffe efficiency (NS), and the root mean square error (RMSE) of 0.53, 0.53, and 2.75 for the calibration period and 0.63, 0.62, and 1.94 for the validation period, respectively. Likewise, the results of the ANN model also illustrated a good agreement between observed and predicted data during calibration and validation periods, which was demonstrated by R2, NS, and RMSE values (0.68, 0.68, and 2.27 for the calibration period, 0.55, 0.66 and 2.12 for the validation period, respectively). According to the sensitivity analysis, Chl a concentration was highly sensitive to dissolved inorganic nitrogen, nitrate–nitrogen, autoregressive Chl a, chloride, sulfate, and total phosphorus. We concluded that it was possible to predict the daily Chl a dynamics in the German lowland river based on relevant environmental factors using either ANN or MLR models. The ANN model is well suited for solving non-linear and complex problems, while the MLR model can explicitly explore the coefficients between independent and dependent variables. Further studies are still needed to improve the accuracy of the developed models.

Spatial distribution of benthic algae in the Gangqu River, Shangrila, China

This study consisted of sampling benthic algae at 32 sites in the Gangqu River, an important upstream tributary of the Yangtze River. Our aims were to characterize the benthic algae communities and relationships with environmental variables. Among the 162 taxa observed, Achnanthes linearis and Achnanthes lanceolata var. elliptica were the dominant species (17.10% and 14.30% of the total relative abundance, respectively). Major gradients and principal patterns of variation within the environmental variables were detected by principal component analysis (PCA). Then non-metric multidimensional scaling (NMS) divided all the sites into three groups, which were validated by multi-response permutation procedures (MRPP). Canonical correspondence analysis (CCA) indicated that three environmental variables (TN, TDS, and TP) significantly affected the distribution of benthic algae. Weighted averaging regression and cross-calibration produced strong models for predicting TN and TDS concentration, which enabled selection of algae taxa as potentially sensitive indicators of certain TN and TDS levels: for TN, Achnanthes lanceolata, Achnanthes lanceolata var. elliptica, and Cymbella ventricosa var. semicircularis; for TDS, Cocconeis placentula, Cymbella alpina var. minuta, and Fragilaria virescens. The present study represents an early step in establishing baseline conditions. Further monitoring is suggested to gain a better understanding of this region.

Temporal impacts of a small hydropower plant on benthic algal community

To explore the temporal impacts of a small hydropower plant (SHP) on benthic algal community, monthly samples from November 2005 to June 2006 were taken in a reach of the Xiangxi River, China. During the study period, a total of 116 taxa were recorded and diatoms were the most abundant group, accounting for 60.42 % of total taxa. Our study showed that operation of the SHP had significant impacts on river systems: (1) distinct physicochemical conditions between control and impaired sites; (2) remarkable increase of chlorophyll-a concentration, total algal densities, and decrease of Shannon-Wiener diversity index, evenness at impaired sites during the dry period (e. g., November, December, January, February and March); (3) profound impacts on overall benthic algal community in dry periods (e. g., November, December, January, February, March, May and June). However, the rainfall or the periodical connectivity of channel appeared to decrease the impacts of the SHP on the benthic algal community (e. g., April and May). We suggest that a minimal discharge should be preserved during the dry period and a basal flow kept for the maintenance of fluvial connectivity of the river water, which would provide more sustainability to the benthic algal community as well as other aquatic organisms.

Importance of sampling frequency when collecting diatoms

There has been increasing interest in diatom-based bio-assessment but we still lack a comprehensive understanding of how to capture diatoms’ temporal dynamics with an appropriate sampling frequency (ASF). To cover this research gap, we collected and analyzed daily riverine diatom samples over a 1-year period (25 April 2013–30 April 2014) at the outlet of a German lowland river. The samples were classified into five clusters (1–5) by a Kohonen Self-Organizing Map (SOM) method based on similarity between species compositions over time. ASFs were determined to be 25 days at Cluster 2 (June-July 2013) and 13 days at Cluster 5 (February-April 2014), whereas no specific ASFs were found at Cluster 1 (April-May 2013), 3 (August-November 2013) (>30 days) and Cluster 4 (December 2013 - January 2014) (<1 day). ASFs showed dramatic seasonality and were negatively related to hydrological wetness conditions, suggesting that sampling interval should be reduced with increasing catchment wetness. A key implication of our findings for freshwater management is that long-term bio-monitoring protocols should be developed with the knowledge of tracking algal temporal dynamics with an appropriate sampling frequency.

Contribution of microspatial factors to benthic diatom communities

Spatial factors can play important and potentially confounding roles governing the presence, the absence, and the abundance of the diatom species and consequently influence the diatom-based bioassessment. To examine how spatial factors affect diatom community and biomonitoring, diatom community was sampled in three catchments with similar river length and watershed area across a large spatial scale along the Yangtze River, China. Redundancy analysis (RDA) showed that patterns of diatom distribution could be attributed not only to environmental variables (e.g., NO3–N, TN, WT, and COD), but also to spatial factors (e.g., elevation, latitude, and longitude). Partial RDAs partitioned the total variance of diatom data explained (64.7%) into three parts: pure spatial variables contributed the highest proportion (19.8%), followed by pure environmental variables (5.4%), and the shared effects by environmental and spatial sets explained a large proportion of diatom variance (39.5%). Recognizing the potential influences of spatial factors, further accumulations of diatom data within different regions would allow for the development of better diatom-based monitoring methods for watershed diagnosis and management.

Riverine phytoplankton shifting along a lentic-lotic continuum under hydrological, physiochemical conditions and species dispersal

The importance of phytoplankton-based bio-assessment has been recently recognized in lowland rivers which are affected by multi-environmental factors. However, some basic questions remain unclear to date, such as: (i) spatial and temporal variations of phytoplankton, (ii) the impact of upstream lakes on downstream community, (iii) the main drivers for species composition or (iv) the regional biodiversity along a lentic-lotic continuum. To answer these questions, we collected and analyzed the fluvial phytoplankton communities along a lentic-lotic continuum from a German lowland catchment, where a well-established ecohydrological modeling predicted long-term discharges at each sampling site. Our results revealed very high spatial and temporal variations of phytoplankton community. The changes of a lake on downstream phytoplankton assemblages were significant, especially the nearest reach after the lake. However, these influences varied along with seasons and limited in a relatively short distance to the lake. Redundancy analysis and Mantel tests showed that phytoplankton composition and dissimilarities along the lentic-lotic continuum attributed more to local hydrological and physicochemical variables than species dispersal, which confirmed the suitability of lowland phytoplankton-based bioassessment. In addition, our findings highlighted the importance of flow regime in shaping phytoplankton community composition and regional beta diversities. This study emphasized the necessity to include the hydrological variables and their relationship with phytoplankton community in future bio-monitoring investigations.

Benthic Algae of the Gangqu River, Shangrila, China

ABSTRACT We surveyed the benthic algae at 32 sites in the Gangqu River system during May 2005. Among the 162 different taxa observed, 88.8% were diatoms. Achnanthes linearis and Achnanthes lanceolata var. elliptica were the dominant species, comprising 17.1% and 14.3% of the total relative abundance, respectively.

Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae

Abstract There has been increasing interest in algae‐based bioassessment, particularly, trait‐based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well‐proven ecohydrological modeling enabled to predict long‐term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait‐based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long‐term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.