SCALED CHRYSOPHYTES (CHRYSOPHYCEAE AND SYNUROPHYCEAE) FROM ADIRONDACK DRAINAGE LAKES AND THEIR RELATIONSHIP TO ENVIRONMENTAL VARIABLES1

The relationships between 23 scaled chrysophyte taxa (Chrysophyceae and Synurophyceae) and measured limnological variables in 62 Adirondack, New York, drainage lakes were examined by canonical correspondence analysis (CCA). The major proportion of variation in chrysophyte species distributions was strongly related to total monomeric Al (Al_m) and Mg concentrations, and their close correlates pH, Na, Ca, and acid-neutralizing capacity (ANC). Total monomeric Al concentrations explain a greater proportion of species variation than pH, suggesting that Al_m concentrations may be more important in governing the distribution of chrysophyte taxa in these lakes. Gaussian logit (GL) and linear logit (LL) regressions of the relative percentages of individual chrysophyte taxa to lakewater pH and Al_m concentrations and the examination of pH–Al_m response surfaces show that many chrysophyte taxa exhibit unique responses to these environmental gradients; taxa can be characterized as alkaline, circumneutral, acidic, and pH indifferent. Within each of these groups, taxa can be characterized further based upon their optima and tolerances to Al_m concentrations. Chrysophyte indicator species (i.e. a taxon with a strong statistical relationship to the environmental variable of interest, a well-defined optimum, and a narrow tolerance to the variable of interest) for pH include Mallomonas hindonii, M. crassisquama, M. pseudocoronata, and Synura uvella; M. hindonii, M. crassisquama, M. pseudocoronata, S. petersenii, and S. spinosa are good indicators of Al_m concentrations. Highly significant predictive models were developed to infer lakewater pH and Al_m concentrations from the relative percentages of chrysophyte scales in the study lakes. Model evaluation was based on their correlation coefficients and the root-mean-squared error of prediction (RMSE) derived from bootstrapping. Weighted averaging regression and calibration with tolerance down-weighting (i.e. weighting taxa inversely to their variance) produced superior results when compared to the computationally and data-demanding maximum likelihood methods and to simple weighted averaging regression and calibration.     

Surface sediment diatom assemblages and epilimnetic total phosphorus in large, shallow lakes of the Yangtze floodplain: their relationships and implications for assessing long-term eutrophication

1. The Yangtze floodplain (SE China) is characterized by a number of large shallow lakes, many of which have undergone eutrophication due to the intensification of agriculture and urban growth over recent decades. As monitoring data are limited and in order to determine lake baseline nutrient concentrations, 49 lakes were sampled, covering a total phosphorus (TP) gradient (c. 30–550 μg L⁻¹) to develop a diatom-based inference model. 2. There are three dominant diatom assemblages in these shallow lakes with a marked change in assemblage structure near the boundary between eutrophic and hypereutrophic nutrient levels (as indicated by their TP value). Canonical correspondence analysis indicated that TP was the most important and significant variable in explaining the diatom distributions, independently accounting for 9.5% variance of diatoms. 3. Forty-three lakes were used to generate a transfer function using weighted averaging (WA) with inverse deshrinking. This model had low predictive error (root mean squared error of prediction; RMSEP_jack = 0.12) and a high coefficient of prediction (R²_jack = 0.82), comparable with regional TP models elsewhere. The good performance of this TP model may reflect the low abundance of benthic diatom species which are commonly regarded as the main error source in European shallow lake WA models. 4. The WA model was used to reconstruct the past-TP concentrations for Taibai Lake, a shallow hypereutrophic lake in Hubei province. The results showed that TP concentration varied slightly (43–62 μg L⁻¹) prior to the 1920s, indicating an eutrophic state since the 1800s. A period of sustained eutrophication occurred after 1950, because of the development of agriculture, reflecting by maximum values of Aulacoseira alpigena and increased abundance of Cyclotella meneghiniana, C. atomus and Cyclostephanos dubius. The steep increase in nutrient concentration after 1970 was related to the overuse of chemical fertilizer and fish farming in the catchment. 5. The shift in fossil diatoms from epiphytic to planktonic forms in the lake sediment core during 1950–70 provides useful information on the transformation from macrophyte-dominated to alga-dominated states. It is plausible that the TP concentration of 80–110 μg L⁻¹ observed in this study is the critical range for switching between the two stable states in the lake. 6. The regional diatom-TP model developed in this study allows, therefore, the possibility of reconstructing historical background nutrient concentrations in lakes. It will provide an indication of the onset and development of eutrophication at any site. This is particularly important for the many lakes in the Yangtze floodplain where information about historical changes in water quality is lacking.     

Total phosphorus inference models and indices for coastal plain streams based on benthic diatom assemblages from artificial substrates

We investigated the potential for using diatoms to monitor and assess nutrient enrichment in coastal plain streams using weighted-averaging inference models and diatom trophic indices. Samples were collected from low-gradient, clay- to sand-bottom streams in New Jersey (NJ), USA, using artificial substrates (diatometers). Multivariate analysis showed that conductivity was overall the most important explanatory variable. Total phosphorus (TP) explained a significant proportion of the variation in diatom species composition. There was statistical justification for development of inference models for TP but not for total nitrogen (TN). We developed and tested models for inferring TP using weighted-averaging (WA) and weighted-averaging partial least squares (WA-PLS) regression and calibration techniques. We also created a diatom TP index by rescaling the inferred TP values. WA-PLS provided the best model (n = 38), which showed moderate predictive ability (r _boot² = 0.43; RMSEP_boot = 0.30 log₁₀ μg l⁻¹ TP); it performed best at lower TP concentrations and tended to underestimate values above 100 μg l⁻¹. The TP index performed well; it assigned the majority of the index scores to the correct nutrient category. TP models and indices developed for the Coastal Plain had lower predictive ability than those developed for northern NJ and streams in other comparable geographic regions of the US. This lower performance can be attributed primarily to a data gap in the TP gradient in the calibration dataset (lack of sites with TP concentrations between 240 and 560 μg l⁻¹), and a smaller number of samples. We conclude that diatom-based TP inference models and artificial substrate sampling are useful for assessing and monitoring nutrient enrichment in coastal plain streams. Given the worldwide distribution of streams similar to those in this study, these tools should be widely applicable. Handling editor: D. Ryder     

Inferring the minimum pH of streams from macroinvertebrates using weighted averaging regression and calibration

1. Data on macroinvertebrates and stream chemistry were collected from sixty-four streams in Finland. Weighted averaging (WA) regression and calibration models were constructed to infer the minimum pH of streams from their invertebrate assemblages. The purpose was to develop an instrument for biological assessment and monitoring of stream acidification. The WA method was compared with simpler approaches, based on qualitative invertebrate data and pH tolerance limits, that are widely used.
2. Performance of the two approaches was assessed in terms of correlation between the inferred and observed minimum pH within the 'training set', and in terms of root mean squared differences (predicted – observed) (RMSEP) estimated by cross-validation or bootstrap resampling techniques. The models were further tested using independent data from the literature representative of a wide geographical range.
3. The predictive power of the WA models was reasonable (RMSEP 0.40–0.44 pH units) in the training set and consistently better than that of the tolerance limit method. In contrast to the latter, the WA models were able to infer a minimum pH above 5.5, suggesting they could detect the early stages of acidification.
4. The WA models performed better than the tolerance limit method in inferring pH from the independent literature, further demonstrating the superiority and generality of the WA approach.
5. The weighted averaging technique could be an effective and widely applicable tool for contemporary biological monitoring and assessment using aquatic invertebrates.     

FRESHWATER DIATOMS FROM THE CANADIAN ARCTIC TREELINE AND DEVELOPMENT OF PALEOLIMNOLOGICAL INFERENCE MODELS1

Relationships between surface sediment diatom assemblages and measured environmental variables from 77 lakes in the central Canadian arctic treeline region were examined using multivariate statistical methods. Lakes were distributed across the arctic treeline from boreal forest to arctic tundra ecozones, along steep climatic and environmental gradients. Forward selection in canonical correspondence analysis determined that dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), total nitrogen (TN), lake surface area, silica, lake‐water depth, and iron explained significant portions of diatom species variation. Weighted‐averaging (WA) regression and calibration techniques were used to develop inference models for DIC, DOC, and TN from the estimated optima of the diatom taxa to these environmental variables. Simple WA models with classical deshrinking produced models with the strongest predictive abilities for all three variables based on the bootstrapped root mean squared errors of prediction (RMSEP). WA partial least squares showed little improvement over the simpler WA models as judged by the jackknifed RMSEP. These models suggest that it is possible to infer trends in DIC, DOC, and TN from fossil diatom assemblages from suitably chosen lakes in the central Canadian arctic treeline region.     

The fauna in the upper stony littoral of Danish lakes: macroinvertebrates as trophic indicators

1. The macroinvertebrate fauna living on stones in the exposed stony littorals of thirty-nine Danish lakes were examined by multivariate numerical methods. The data were derived from 125 semi-quantitative samples and a species list of 126 taxa. The mean number of individuals per sample was 960, and among the most common taxa were Asellus aquaticus, Gammarus, Oulimnius, Tinodes, Cricotopus and Dicrotendipes. 2. The total number of species and fourteen individual taxa were positively correlated to mean depth of the lakes and eleven taxa were correlated to the total phosphorus concentration. The Shannon diversity was negatively correlated to the chlorophyll a concentration ([Chl a]). 3. Community patterns were examined by detrended correspondence analysis (DCA), and the relationship between species data and selected environmental variables was analysed by canonical correspondence analysis (CCA). Mean lake depth was found to be the strongest environmental variable in explaining the species data. The [Chl a] and Secchi depth also explained significant variation in the distribution of the stony littoral invertebrates. Wind fetch and relative exposure did not explain any variation in the faunal composition among sites. 4. The abilities of the macroinvertebrates to predict the lake trophic state, expressed as log ([Chl a]), were explored by means of weighted averaging (WA) regression and calibration. Two tolerance-weighted WA models using inverse and classical regression for deshrinking are presented. The models were assessed by the root mean square error (RMSE) of prediction, using bootstrapping as cross validation, and by the correlation between observed and inferred log ([Chl a]). The model using inverse deshrinking had a RMSE_boot = 0.41 and r² = 0.63. By using classical regression, the predictability in the ends of the gradient was improved but the RMSE increased: RMSE_boot = 0.46. 5. Although the factors determining faunal distribution patterns in the Danish lowland lakes were highly multivariate and difficult to disentangle, it seems reasonable to use the WA estimated species optima and tolerances to [Chl a] in a bio-assessment model.     

黄河三角洲芦苇湿地底栖无脊椎动物与环境因子的关系研究——以石油开采区与淡水补给区为例

分别于2018年5月和8月对黄河三角洲芦苇湿地19(淡水补给区11处,石油开采区8处)处采样点的底栖无脊椎动物和水体理化指标进行调查采样,运用统计方法分析两个区域物种组成、优势种、多样性、群落结构以及与环境因子的关系。结果表明:两季共采集到底栖无脊椎动物54种,主要以水生昆虫、腹足纲和软甲纲为主,淡水补给区和石油开采区各类群组成差异明显。独立样本T检验表明淡水补给区和石油开采区水体理化指标间差异显著(P0.05)。双因子方差分析显示,昆虫纲和腹足纲密度在两区域差异显著(P0.05),软甲纲和腹足纲密度在季节上差异明显(P0.05)。底栖无脊椎动物优势种共10种,淡水补给区指示物种8种,而石油开采区未发现有指示物种。聚类和非参数多维排序(nM DS)显示,底栖无脊椎动物群落结构相似性较低; RDA结果表明:淡水补给区底栖无脊椎动物群落结构主要受Cond,TDS,Sal,pH,Eh,HCO_3~-,SO_4~(2-)等环境因子的影响。石油开采区底栖无脊椎动物群落结构影响较大的环境因子为HCO_3~-、NH_4-N。     

Inferring the minimum pH of streams from macroinvertebrates using weighted averaging regression and calibration

1. Data on macroinvertebrates and stream chemistry were collected from sixty-four streams in Finland. Weighted averaging (WA) regression and calibration models were constructed to infer the minimum pH of streams from their invertebrate assemblages. The purpose was to develop an instrument for biological assessment and monitoring of stream acidification. The WA method was compared with simpler approaches, based on qualitative invertebrate data and pH tolerance limits, that are widely used.
2. Performance of the two approaches was assessed in terms of correlation between the inferred and observed minimum pH within the 'training set', and in terms of root mean squared differences (predicted – observed) (RMSEP) estimated by cross-validation or bootstrap resampling techniques. The models were further tested using independent data from the literature representative of a wide geographical range.
3. The predictive power of the WA models was reasonable (RMSEP 0.40–0.44 pH units) in the training set and consistently better than that of the tolerance limit method. In contrast to the latter, the WA models were able to infer a minimum pH above 5.5, suggesting they could detect the early stages of acidification.
4. The WA models performed better than the tolerance limit method in inferring pH from the independent literature, further demonstrating the superiority and generality of the WA approach.
5. The weighted averaging technique could be an effective and widely applicable tool for contemporary biological monitoring and assessment using aquatic invertebrates.     

A weighted—averaging regression and calibration model for inferring total phosphorus concentration from diatoms in British Columbia (Canada) lakes

1. The relationship between surficial sediment diatom taxa (Bacillariophyceae) and measured limnological variables in forty-six British Columbia lakes was explored using canonical correspondence analysis (CCA). Lake-water total phosphorus concentration (TP), maximum lake depth, conductivity, and calcium concentration each accounted for independent and statistically significant directions of variation in the distribution of diatom taxa. 2. Weighted-averaging (WA) models were developed to infer lake-water TP from the relative abundances of 131 diatom taxa in the surficial sediments of thirty-seven lakes. WA regression and calibration with classical deshrinking provided the best model for TP reconstructions. 3. Our quantitative inference model has two major advantages over existing multiple linear-regression models: (i) inferences are based on the responses of individual taxa to TP, and do not involve grouping the taxa into a small number of ecological categories; and (ii) the model assumes that diatoms respond to TP in a unimodal, rather than a linear, fashion. 4. The WA model can now be used to infer past lake-water TP, within the range 5–28νgr1^?1, from diatoms preserved in the sediments of British Columbia lakes. The model can provide quantitative estimates of the onset, rate, and magnitude of lake eutrophication in response to natural processes and human disturbances.     

Using change-point analysis and weighted averaging approaches to explore the relationships between common benthic diatoms and in-stream environmental variables in mid-atlantic highlands streams,USA

Diatoms are increasingly being used in the bioassessment of aquatic systems. However, autecological information for many common taxa is incomplete. We explored the potential of classification (CT) and regression tree (RT) approaches to identify the hierarchical interaction among water quality variables in predicting the relative abundance of ten common stream diatom taxa in the Mid-Atlantic Highlands ecoregion. RT analysis was also used to identify environmental change points corresponding to major shifts in species abundances. We also used traditional weighted-averaging approaches (WA) to model taxon pH and total phosphorus (TP) optima. RT and WA approaches provided different, yet complementary, information on the complex relationships between common stream diatoms and environmental variables. Both RT and CT highlighted the interaction of stream acidity (pH, acid neutralizing capacity (ANC)), and TP in structuring the stream diatom assemblage. For the RT of taxa, where pH was an important predictor, higher pH predicted higher relative abundances. In contrast, higher TP predicted lower relative abundances for some diatom taxa (e.g., Achnanthidium minutissimum (Kütz.) Czarnecki), while predicting higher relative abundances for other taxa (e.g., Planothidium lanceolatum (Bréb.) Round & Bukht., Gomphonema parvulum (Kütz.) Kütz.). The environmental change point for pH derived from RT analysis was lower than WA optima for all species. We suggest that RT change point analysis can be used to complement traditional WA optima approaches, especially when diatom taxa’s abundances are affected by interactive environmental factors, to provide more refined information on stream diatom environmental preferences. Handling editor: L. Naselli-Flores     

USING EPILITHIC ALGAL COMMUNITIES TO ASSESS TROPHIC STATUS IN IRISH LAKES1

Relationships between taxonomic composition of shallow epilithic algal communities and nine environmental variables in 32 lakes of different trophic states in Ireland were explored using gradient analysis. A canonical correspondence analysis using four representative environmental variables, alkalinity (correlated with pH and conductivity), maximum phytoplankton chl a (CHL_max) (correlated with total P, total N, and chl), turbidity, and water color explained 21% of the variance in taxa distributions. The first two axes were significant and accounted for 77% of the variance in the periphyton–environmental relationship. The first axis was strongly related to alkalinity and color, which reflected geology and land use in the watersheds. The second axis was most correlated with CHL_max, and separation of lakes corresponded to their Organization for Economic Cooperation and Development (OECD) trophic classification based on water chemistry. Eutrophic lakes were characterized by cyanobacteria taxa and Stigeoclonium sp. Diatoms and desmids were generally more abundant in oligotrophic and mesotrophic lakes. Values for diatom trophic indices were poor indicators of trophic state. Weighted averaging regression and calibration techniques were used to develop transfer functions between 84 taxa and total P, total N, and CHL_max. The total P inference model predicted OECD trophic classification correctly for 84% of the lakes. Values for taxa preferences resulting from such models can provide the foundation for biomonitoring schemes using extant periphyton communities. The turnover time of periphyton taxa should integrate changes in environmental conditions at a temporal scale intermediate to surface‐sediment fossil diatom assemblages and water column variables, which may be more appropriate for detecting annual changes.     

Ecological optima and tolerances of Thelypteris limbosperma,Athyrium distentifolium,and Matteuccia struthiopteris along environmental gradients in Western Norway

The distribution and abundance of Thelypteris limbosperma, Athyrium distentifolium, and Matteuccia struthiopteris are modelled statistically in relation to 14 environmental variables along the major climatic, topographic, and edaphic gradients in western Norway. The data are from 624 stands from which measurements or estimates of mean January and mean July temperatures, humidity, altitude, aspect, and slope are available. From 182 of these stands eight soil variables have also been measured. The species responses are quantified by two numerical methods: Gaussian logit regression and weighted averaging (WA) regression. The estimated WA optima suggest that A. distentifolium has an ecological preference for low July and January temperatures, high altitudes, and soils of low-medium pH and base content. The species shows statistically significant Gaussian responses with summer temperature, humidity (= Martonnes humidity index), altitude, slope, aspect, pH, cation exchange capacity, and base saturation with optima of 8.7 °C, 188.9, 1220 m, 28°, 29°, 4.8, 13.77 mEq 100 g dry soil^-1, and 13.4%, respectively. These suggest that the occurrence and relative abundance of A. distentifolium are well predicted by summer temperature, topography, and soil pH and base status. T. limbosperma has WA optima that suggest that it favours moderately high winter and summer temperatures, high humidity, medium altitude, and soils of low pH and base content. It has significant Gaussian responses to summer temperature (optimum =12.6 °C), winter temperature (-1.8 °C), humidity (179.2), altitude (459.5 m), slope (22.5°), and Na (0.7 mg 100 g dry soil^-1). These suggest that climatic factors, altitude, and slope are significant predictors for its occurrence and abundance. M. struthiopteris has high WA optima for summer temperature, pH, Ca, Mg, K, Na, cation exchange capacity (CEC), and base saturation, and a low optima for humidity and winter temperature. Of these, summer temperature (16.0 °C), Ca (63.1 mg 100 g dry soil^-1), Mg (41.0 mg 100 g dry soil^-1), K (23.6 mg 100 g dry soil^-1), Na (5.0 mg 100 g dry soil^-1), CEC (60.7 mEq 100 g dry soil^-1), and base saturation (56.3%) have significant Gaussian logit responses, as do aspect (150.2°) and loss-on-ignition (9.4%). These results suggest that the occurrence and relative abundance of M. struthiopteris are well predicted by high soil base cations, a generally southern aspect, low organic content in the soil, and high July temperatures.     

Inferring pH from diatoms: a comparison of old and new calibration methods

Two new methods for inferring pH from diatoms are presented. Both are based on the observation that the relationships between diatom taxa and pH are often unimodal. The first method is maximum likelihood calibration based on Gaussian logit response curves of taxa against pH. The second is weighted averaging. In a lake with a particular pH, taxa with an optimum close to the lake pH will be most abundant, so an intuitively reasonable estimate of the lake pH is to take a weighted average of the pH optima of the species present.Optima and tolerances of diatom taxa were estimated from contemporary pH and proportional diatom counts in littoral zone samples from 97 pristine soft water lakes and pools in Western Europe. The optima showed a strong relation with Hustedt's pH preference groups. The two new methods were then compared with existing calibration methods on the basis of differences between inferred and observed pH in a test set of 62 additional samples taken between 1918 and 1983. The methods were ranked in order of performance as follows (between brackets the standard error of inferred pH in pH units); maximum likelihood (0.63) > weighted averaging (0.71) = multiple regression using pH groups (0.71) = the Gasse & Tekaia method (0.71) > Renberg & Hellberg's Index B (0.83) » multiple regression using taxa (2.2). The standard errors are larger than those usually obtained from surface sediment samples. The relatively large standard may be due to seasonal variation and to the effects of other factors such as humus content. The maximum likelihood method is statistically rigorous and can in principle be extended to allow for additional environmental factors. It is computer intensive however. The weighted averaging approach is a good approximation to the maximum likelihood method and is recommended as a practical and robust alternative.     

Spatial and seasonal variation in nutrient excretion by benthic invertebrates in a eutrophic reservoir

1. Nitrogen (N) and phosphorus (P) fluxes via excretion by benthic invertebrates were quantified in a eutrophic reservoir (Acton Lake, Ohio, U.S.A.). We quantified variation in nutrient fluxes seasonally (June until November 1997), spatially (three sites) and among taxa (chironomids, tubificid oligochaetes and Chaoborus). 2. The three taxa differed in spatial distribution and contribution to nutrient fluxes. Tubificids were the most abundant taxon at two oxic sites (1.5 and 4 m depth), and were exceedingly rare at an anoxic, hypolimnetic site (8 m). Chironomids were abundant only at the shallowest oxic site. Chaoborus was the only abundant taxon at the anoxic site. Total benthic invertebrate biomass was greatest at the shallowest site and lowest at the anoxic, hypolimnetic site. 3. Mass‐specific excretion rate [μmol NH₄–N or soluble reactive P (SRP) excreted mg dry mass^–1 h^–1] varied among experiments and was influenced by temperature. Differences among taxa were not significant. Thus, nutrient flux through benthic invertebrates was affected more by total invertebrate biomass and temperature than by species composition. 4. Fluxes of N and P via benthic invertebrate excretion (μmol NH₄–N or SRP m^–2 day^–1) were greatest at the oxic sites, where fluxes were dominated by the excretion of tubificids and chironomids. The N and P fluxes at the anoxic site were much lower, and were dominated by excretion by Chaoborus. The ratio of N and P excreted by the benthic invertebrate assemblage varied seasonally and was lowest at the anoxic site. 5. Comparison with other measured inputs shows that excretion by benthic invertebrates could be an important source of nutrients, especially of P. However, the relative importance of nutrient excretion by the benthos varies greatly spatially and temporally.     

Tracing lake trophic history with a chironomid–total phosphorus inference model

1. In the absence of historical water chemistry data, predictive biological indicator groups preserved in lake sediments can be employed to reconstruct the history of lake eutrophication. Diatoms are well established in this role, but to augment diatom‐based inferences of nutrient status we investigate the potential use of chironomid midges (Insecta: Chironomidae). 2. Canonical correspondence analysis (CCA) of modern chironomid assemblages in surface sediments from 44 lakes in the English Midlands and Wales, U.K., shows that five environmental variables (total phosphorus (TP), bottom dissolved oxygen, maximum lake depth, Secchi depth and surface water temperature) make a statistically significant (P < 0.05) contribution to explaining the variance in the chironomid data, of which TP makes the largest contribution (29%). 3. The relationship is used to develop a series of weighted averaging (WA) and partial least squares (PLS), (WA‐PLS) models to infer log₁₀TP. The models are evaluated by leave‐one‐out (jack‐knifing) cross‐validation. The simplest minimal adequate model is provided by WA with unweighted inverse deshrinking of root mean square error of prediction (RMSEP_jack=0.34 and r²_jack=0.60). 4. Using this model, the trophic history of Betton Pool, Shropshire, U.K., is reconstructed from the mid‐19th century to the present day and the results from the chironomid‐TP model are compared with inferences from a diatom‐TP model ( 13 ). Both reconstructions suggest that there was a gradual rise in TP since 1850 AD until about 1974, followed by a more pronounced and rapid increase that has continued until the present. Inferred TP values from the WA chironomid inference model agree with diatom‐inferred values. 5. The study demonstrates that fossil chironomid assemblages can be used to investigate quantitatively the trophic history of lakes.     

Invertebrate hydraulic preferences and predicted impacts of changes in discharge in a large river

• 1 Instream habitat models are attractive tools for assessing the impacts of flow restoration on aquatic organisms, but have been rarely used for invertebrates due to the lack of knowledge of their hydraulic preferences.
• 2 In this study, we provide quantitative models of the hydraulic preferences for 66 invertebrate taxa found in the Upper Rhône River (France), and combine these preferences with a statistical habitat model (FSTress) to predict the effects of minimum flow restoration on invertebrate abundances in two bypassed sections of the river.
• 3 Many taxa show marked preferences for particular hydraulic conditions. Average preferred hydraulic conditions were significantly related to those observed in smaller streams (R² = 0.37).
• 4 Our model predicted that habitat values of 27 taxa should be enhanced by restoration operations, but also predicted a decrease of habitat values in the main channel for 12 limnophilic taxa. However, these taxa are expected to maintain populations by finding refuges in restored cut‐off channels and overall invertebrate diversity is predicted to increase in the two bypassed sections studied here.

     

Aquatic macrophytes, macroinvertebrate associations and water levels in a lowland Tasmanian river

Aquatic macrophytes are a common habitat for macroinvertebrates and may occupy depth zones in the littoral region of lowland rivers. Studies have indicated that different species of macrophyte typically support different assemblages, abundances and numbers of species of macroinvertebrates. This has often been attributed to differences in the dissectedness of stems and leaves of the macrophytes, resulting in differences in the surface area and/or the number of microhabitats available to invertebrates. I set out to measure the abundance and taxonomic richness and to describe the macroinvertebrate assemblages associated with three species of aquatic macrophyte in a pool in the Macquarie River, Tasmania and to examine responses of these variables to changes in water levels over summer. The macrophyte species sampled wereMyriophyllum simulans/variifolium, Triglochin procera} and Eleocharis sphacelata, each one differing in the dissectedness of its stems and leaves and its location in the littoral zone. Whereas the greatest abundance of macroinvertebrates was found associated in all months (i.e. at all water levels) with the structurally complex and shallowest macrophyte species, Myriophyllum, the number of taxa associated with this species was in several cases lower than for the structurally simpler and deeper water Triglochin and Eleocharis. While water depth and total plant biomass of samples were often correlated with invertebrate abundance and richness, these relationships were different for each macrophyte species. Of the nine most common invertebrate taxa collected from all samples, the abundances of more than half showed consistent differences among macrophyte species across months, two showed differences among macrophytes, but with an interaction with month and two showed no differences among macrophytes. There were major differences in the invertebrate assemblages associated with each macrophyte species in any one month, however, there was also a large turnover of taxa associated with the species of macrophytes from one month to the next. Changes in water level and concomitant changes in environmental variables are suggested as factors influencing the invertebrate fauna in the littoral zone of the pool of the Macquarie River. It is thus important for river managers to be aware that species of macroinvertebrates are not evenly distributed across species of macrophyte and that water levels and their influence on macrophytes as invertebrate habitat may play an integral part in determining the abundance, richness and assemblage of invertebrates in rivers.     

Quantifying species indicator values for trophic diatom indices: a comparison of approaches

This study compares two approaches for constructing diatom-based indices for monitoring river eutrophication. The first approach is based on weighted averaging of species indicator values with the underlying assumption that species have symmetrical unimodal distributions along the nutrient gradient, and their distributions are sufficiently described by a single indicator value per species. The second approach uses multiple indicator values for individual taxa and is based on the possibility that species have complex asymmetrical response curves. Multiple indicator values represent relative probabilities that a species would be found within certain ranges of nutrient concentration. We used 155 benthic diatom samples collected from rivers in the Northern Piedmont ecoregion (Northeastern U.S.A.) to construct two datasets: one used for developing models and indices, and another for testing them. To characterize the shape of species response curves we analyzed changes in the relative abundance of 118 diatom taxa common in this dataset along the total phosphorus (TP) gradient by fitting parametric and non-parametric regression models. We found that only 34 diatoms had symmetrical unimodal response to TP. Among several indices that use a single indicator value for each species, the best was the weighted averaging partial least square (WA-PLS) inference model. The correlation coefficient between observed and inferred TP in the test dataset was 0.67. The best index that employed multiple indicator values for each species had approximately the same predictive power as the WA-PLS based index, but in addition, this index provided a sample-specific measure of uncertainty for the TP estimation.     

Influences of aquatic macrophytes on invertebrate community structure,guild structure,and microdistribution in streams

The aquatic macrophytes Ranunculus aquatilis and Rorippa nasturtium-aquaticum were transplanted into substrate trays and placed in a stream alongside unvegetated substrate. Macrophytes were observed to have significant effects on 1) invertebrate community structure, 2) guild structure, and 3) microdistribution. 1) Significantly higher taxa richness and community abundances were associated with macrophytes. 2) Significantly higher abundances of shredder, scraper, and predator guilds were associated with macrophytes in fall, and all guilds had higher abundances in macrophytes in spring. However, guild frequency distributions did not differ among habitats except in spring. 3) Enallagma, Gammarus, Gyraulus, Physa, and Pisidium exhibited a strong association with macrophytes, while Hydropsyche, Simulium, Baetis tricaudatus, Glossosoma velona, and Helicopsyche borealis appeared to avoid them. A strong correlation appeared to exist between current velocity preferences of these taxa and their selection or avoidance of vegetated habitat. Thus, the effect of macrophytes in reducing current velocities appeared to be the most important influence on invertebrate microdistribution. However, macrophytes also increase physical heterogeneity and their large surface areas benefit invertebrate community abundances by creating additional living spaces in the water column where none exist above unvegetated substrate.