Influence of geographical extent on typology- and model-based assessments of taxonomic completeness of river macroinvertebrates

1. River InVertebrate Prediction and Classification System (RIVPACS)‐type predictive models are increasingly used to assess the biological condition of freshwaters, but management schemes may also be based on a priori groupings of similar water bodies (typologies) to control for natural variation in biota. The two approaches may lead to disagreements of the biological status of a site, depending on, for example, the spatial scale at which assessments are conducted. 2. We used data from 96 reference and 134 potentially impacted sites from Western and Central Finland to compare RIVPACS‐type models and a simple size‐based typology of rivers for the assessment of taxonomic completeness (the quotient of the Observed‐to‐Expected number of predicted taxa, O / E) of riffle macroinvertebrates. We specifically examined how geographical extent influences bioassessment performance (accuracy, precision and sensitivity to detect impact) of the two approaches. To fully examine the behaviour of the O / E‐index with the two approaches at differing spatial scales, we performed all assessments with a full range of thresholds for predicted taxa occurrence probabilities (p_t from 0+ to 0.9). 3. Both approaches performed consistently better than the corresponding null models. At the larger extent (i.e. assessment encompassing the whole study area), the RIVPACS‐approach performed in all aspects better than the typology‐approach. However, at the smaller extent (i.e. regional assessments) the RIVPACS‐type models and the typologies showed similar accuracy to predict the actual fauna (mean E), similar precision (SD) of cross‐validated O / E and similar sensitivity to detect sites with human impairment. 4. SD(O / E) decreased (i.e. precision increased) consistently with increasing p_t. However, both approaches were most sensitive at intermediate p_t:s (c. 0.2–0.6) when taxa with low predicted occurrence probabilities were excluded. 5. Our results show that RIVPACS‐type predictive models are less susceptible to variations in spatial scale, whereas the performance of a priori typologies increases with decreasing spatial extent. Thus, RIVPACS‐type models are more efficient for large‐scale bioassessments, but at restricted spatial scales, or with an otherwise biologically meaningful stratification, simple a priori classifications can be equally useful for the assessment of taxonomic completeness of river macroinvertebrates.     

Evaluation of approaches for measuring taxonomic completeness of lake profundal macroinvertebrate assemblages

1. Benthic macroinvertebrates (MI) are commonly used to assess freshwater ecosystems with the reference condition approach. Such assessments necessitate control for natural community variation, either by categorical typologies or by predictive models that have been widely and successfully developed for running water biota but not previously for lake profundal invertebrates. 2. We evaluated four modelling techniques [multivariate regression tree (MRT), limiting environmental differences, nonparametric multiplicative regression (NPMR) and River Invertebrate Prediction And Classification System (RIVPACS) and the operative Finnish lake typology for assessing taxonomic completeness (observed‐to‐expected number of taxa, O/E) of profundal MI assemblages. We used data from 74 and 33 minimally disturbed reference lake basins for calibration and validation of the approaches, respectively, and 72 test basins subject to various anthropogenic pressures to evaluate sensitivity to detect impact. Either all predicted taxa (threshold probability of capture P_t = 0+) or only those predicted to be captured with ≥0.25 probability were used to calculate O/E. 3. With P_t = 0.25, all four modelling approaches were accurate (mean O/E = 0.966–1.053) but imprecise (SD of O/E = 0.279–0.304) in predicting the fauna actually observed in validation sites. All models were subtly more precise than a null model (mean 1.038, SD 0.343) or the typology (1.046, 0.327). The taxon‐specific NPMR model was slightly more precise than the other three models based on site groupings. 4. The O/E values correlated relatively weakly (r = 0.55–0.86) among the approaches, which thus produced contrasting lake‐specific assessments, despite their seemingly comparable performances. Indeed, typology, suggesting that MI assemblages were impaired in 56% of test sites, was more sensitive than the other approaches (26–46%) as an indicator of human‐induced deterioration. However, this greater ostensible sensitivity seemed to be biased, as lake morphometry, a main driver of natural community variation, remained uncontrolled by the typology. 5. Generally, our exercise illustrates the inconclusiveness of the common validation criteria for the assessment methods. The apparent poor predictability of the profundal fauna, irrespective of the method, may partly stem from large observation error, which could be alleviated by more intensive sampling. However, instead of an O/E‐taxa index, some other metric encompassing quantitative aspects might be preferable for assessing these species‐poor communities.     

Development of a RIVPACS-type predictive model for bioassessment of wadeable streams in Wyoming

RIVPACS models produce a community-level measure of biological condition known as O/E, which is derived from a comparison of the observed (O) biota with those expected (E) to occur in the absence of anthropogenic stress. We used benthic macroinvertebrate and environmental data collected at 925 stream monitoring stations, from 1993 to 2001, to develop, validate, and apply a RIVPACS model to assess the biological condition of wadeable streams in Wyoming. From this dataset, 296 samples were identified as reference, 157 of which were used to calibrate the model, 46 to validate it, and 93 to examine temporal variability in reference site O/E-values. We used cluster analyses to group the model development reference sites into biologically similar classes of streams and multiple discriminant function analysis to determine which environmental variables best discriminated among reference groups. A suite of 14 categorical and continuous environmental variables best discriminated among 15 reference groups and explained a large proportion of the natural variability in biota within the reference dataset. Eleven of the predictor variables were derived from GIS. As expected, mean O/E-values for reference sites used in model development and validation were near unity and statistically similar. Temporal variability in O/E-values for reference sites was low. Test site values ranged from 0 to 1.45 (mean = 0.73). The model was accurate in both space and time and precise enough (S.D. of O/E-values for calibration data = 0.17) to detect modest alteration in biota associated with anthropogenic stressors. Our model was comparable in performance to other RIVPACS models developed in the United States and can produce effective assessments of biological condition over a broad, ecologically diverse region. We also provide convincing evidence that RIVPACS models can be developed primarily with GIS-based predictor variables. This framework not only simplifies the extraction of predictor variable information while potentially reducing expenditures of time and money in the collection of predictor variable information, but opens the door for development and/or application of RIVPACS models in regions where there is a paucity of local-scale, abiotic information.     

Estimates and comparisons of the effects of sampling variation using ‘national’ macroinvertebrate sampling protocols on the precision of metrics used to assess ecological status

The Water Framework Directive (WFD) of the European Union requires all member countries to provide information on the level of confidence and precision of results in their river monitoring programmes to assess the ecological status class of river sites. As part of the European Union project STAR, the overall effects of sampling variation for a wide range of commonly used metrics and sampling methods were assessed. Replicate samples were taken in each of two seasons at 2–6 sites of varying ecological status class within each of 18 stream types spread over 12 countries, using both the STAR-AQEM method and a national sampling method or, where unavailable, the RIVPACS sampling protocol. The sampling precision of a combination of sampling method and metric was estimated by expressing the replicate sampling variance as a percentage P_samp of the total variance in metric values with a stream type; low values of P_samp indicate high precision. Most metrics had percentage sampling variances less than 20% for all or most stream types and methods. Most national methods including RIVPACS had sampling precisions at least as good as those for the STAR-AQEM method as used in their country at the same sites; the main exceptions were the national methods used in Latvia and Sweden. The national methods used in the Czech Republic, Denmark, France, Poland and the RIVPACS method used in the UK and Austria all had percentage sampling variances of less than 10% for the majority of metrics assessed. In contrast, none of the metrics had percentage sampling variances less than 10% when based on either the Italian (IBE) method, which used bank-side sorting, or the Latvian national method which identifies only a limited set of taxa. P_samp was lowest on average for the two stream types sampled in the Czech Republic using either the PERLA national method or the STAR-AQEM method. Averaged over all stream types and methods, the three Saprobic-based metrics had the lowest average percentage sampling variances (3–6%) amongst the 26 metrics assessed. These estimates of sampling standard deviation can be used to help assess the uncertainty in single or multi-metric systems for estimating site ecological status using the general STAR Bioassessment Guidance Software (STARBUGS) developed within the STAR project.     

Α comparison of alternative techniques for prediction of the fauna of running-water sites in Great Britain

1. Early versions of the river invertebrate prediction and classification system (RIVPACS) used TWINSPAN to classify reference sites based on the macro-invertebrate fauna, followed by multiple discriminant analysis (MDA) for prediction of the fauna to be expected at new sites from environmental variables. This paper examines some alternative methods for the initial site classification and a different technique for prediction. 2. A data set of 410 sites from RIVPACS II was used for initial screening of seventeen alternative methods of site classification. Multiple discriminant analysis was used to predict classification group from environmental variables. 3. Five of the classification–prediction systems which showed promise were developed further to facilitate prediction of taxa at species and at Biological Monitoring Working Party (BMWP) family level. 4. The predictive capability of these new systems, plus RIVPACS II, was tested on an independent data set of 101 sites from locations throughout Great Britain. 5. Differences between the methods were often marginal but two gave the most consistently reliable outputs: the original TWINSPAN method, and the ordination method semi-strong hybrid multidimensional scaling (SSH) followed by K-means clustering. 6. Logistic regression, an alternative approach to prediction which does not require the prior development of a classification system, was also examined. Although its performance fell within the range offered by the other five systems tested, it conveyed no advantages over them. 7. This study demonstrated that several different multivariate methods were suitable for developing a reliable system for predicting expected probability of occurrence of taxa. This is because the prediction system involves a weighted average smoothing across site groupings. 8. Hence, the two most promising procedures for site classification, coupled to MDA, were both used in the exploratory analyses for RIVPACS III development, which utilized over 600 reference sites.     

Effects of fixed-count size on macroinvertebrate richness,site separation,and bioassessment of Chinese monsoonal streams

Subsampling that counts and identifies a random subset of individuals from field samples is widespread yet controversial. We evaluated the effects of fixed-count size on macroinvertebrate richness, site separation, and performance of modeled and null (i.e., natural variation adjusted and unadjusted, respectively) biological indices in Chinese monsoonal stream sites. To do so, we estimated the fixed-count size that was adequate to collect 95% of the estimated true regional macroinvertebrate taxa richness, and we also evaluated the effects of fixed-count size on site and group (reference vs test) separation, and the precision, sensitivity and responsiveness of modeled and null multimetric indices (MMI) and observed/expected (O/E) indices. Random subsamples of individual fixed-count sizes ranged from 50 to 500. Mean cumulative taxa richness continued to increase with increasing fixed-count size. We found that 150 and 200 individuals were needed to collect 75% of estimated true species richness 75% and 95% of the time, respectively. We estimated that at least 1500 individuals per site were required for collecting 95% of estimated true species richness. Site and group separation and classification strength also improved with increased fixed-count size. Larger fixed-count sizes improved the performance of modeled and null O/E₅₀ (O/E calculated using taxa with probabilities of capture ≥0.5); however, they showed no significant difference for modeled and null MMIs and O/E₀ (O/E calculated using all taxa). Overall, we found that fixed-counts affected richness and site/group separation, but not index performance. Until China develops standard sampling methods, we recommend using fixed-count sizes of 500 individuals and rarefaction of ≥200 individuals to limit the effects of sampling error for site and group separation and for precise and accurate bioassessment, respectively.     

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r², intercept and slope. Second, the two models’ assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS‐ and RIVPACS‐type models, if not to replace them.     

Sampling variation in macroinvertebrate data and implications for river quality indices

SUMMARY 1. The EC Water Framework Directive (2000/60/EC) recognises the need for biological monitoring. Indices derived from standard samples of macroinvertebrates are frequently used for the appraisal of the ecological quality of rivers. However, information on the errors or chance variation that can influence the value of an index is also important. 2. This paper describes a study to quantify the observed sampling variation in three ecological indices based on the Biological Monitoring Working Party (BMWP) score system across a wide range of river types and qualities. The indices are number of BMWP taxa, BMWP score and Average Score Per Taxon (ASPT). 3. The study sites were selected to encompass the four major groups within the River InVertebrate Prediction And Classification System (RIVPACS) site classification for Britain. Within each group, four sites which differed in ecological quality grade were chosen (total of 16 sites). At each site three standard RIVPACS samples were taken in each of spring, summer and autumn by trained staff. In each season, two samples were taken by one biologist and the third by a different individual to allow for within and between‐operator variation. 4. The effects of sampling variation within a season on the number of taxa, BMWP score and ASPT across all sites, irrespective of operator, could be represented by some simple parameters. We found that the sampling SD of the square root of the number of taxa, square root of BMWP score and the untransformed ASPT were roughly constant in each case, irrespective of site type or quality. For each index, SD for two and three seasons combined samples were smaller than for single season samples. 5. Inter‐operator influences on sample values were negligible (4–12% of total sampling SD) in this study. This underlines the importance of adequate training for all staff involved in extensive monitoring programmes which use standard procedures from one year to the next, but may involve different staff. 6. Indices for number of taxa, BMWP score and ASPT were all estimated with greater precision from combined season samples than from the averages of two or three seasons' samples. 7. This study enables us to estimate confidence intervals for the values of the number of taxa, BMWP score and ASPT based on single season, two or three season combined samples collected using standard RIVPACS procedures for any river site in Britain. The results can also be used in simulation models which incorporate the effects of sampling variation into assessments of the ecological quality of river sites based on the ratio of observed to RIVPACS expected values of these BMWP indices.     

Additive genetic variance within populations derived by single-seed descent and pod-bulk descent

Summary Breeders of self-pollinated legumes commonly use single-seed descent (SSD) or pod-bulk descent (PBD) to produce segregating populations of highly inbred individuals. We presented equations for the expected value of the additive genetic variance within populations derived by SSD (E(V _A)_SSD) and PBD (E(V _A)_PBD) in terms of the initial population size (N ₀), the number of seed harvested per pod (M), the probability of survival of an individual (), and the generation at which the population is evaluated (S _t). Differences between (E(V _A)_SSD) and (E(V _A)_PBD) are due to differences in the expected amount of random drift which occurs with the two methods after the S ₀ generation. With both methods, random drift occurs when progeny are sampled from heterozygous parents. An additional component of random drift occurs when sampled progeny fail to survive during SSD, or when sampling occurs amoung families during PBD. For values of N ₀, M, , and S _t that are typical of soybean (Glycine max (L.) Merr.) breeding programs, (E(V _A)_SSD) will be greater than (E(V _A)_PBD). The ratio of (E(V _A)_SSD) to (E(V _A)_PBD) will: (1) increase as M and increase; (2) approach a value of 1.00 as N ₀ increases; and (3) be a curvilinear function of S _t. Plant breeders should compare SSD and PBD based upon values of (E(V _A)_SSD) and (E(V _A)_PBD) and the expected cost of carrying out the two methods.Contribution No. 2910 of the South Carolina Agricultural Experiment Station, Clemson University     

Allozyme variation of seed embryos and mating system in relict populations of scots pine (<Emphasis Type="Italic">Pinus sylvestris</Emphasis> L.) from the Kremenets Hill Ridge and Maloe Poles’e

Allozyme variation at ten polymorphic loci and mating system was studied in three small isolated relict populations (4.4 to 22 ha) and in three artificial stands of Pinus sylvestris from the Kremenets Hill Ridge and Maloe Poles’e. It was established that the mean heterozygosity of 130 to 140 year-old trees from natural populations (H _O = 0.288; H _E = 0.277) was substantially lower, compared to 30 to 40 year-old trees from artificial stands (H _O = 0.358; H _E = 0.330). The observed heterozygosity of seed embryos (H _O = 0.169 and 0.180) was substantially lower than of the mature trees from populations and artificial stands, respectively. In the embryo samples, irrespectively of the forest stand origin, substantial hetedrozygote deficiency was observed (at six to eight loci), compared to the Hardy-Weinberg expectations. The proportion of cross pollination in the populations and artificial stands was low, t _m = 0.588 to 0.721; and t _m = 0.455 to 0.837, respectively.     

Natural flow regime,temperature and the composition and richness of invertebrate assemblages in streams of the western United States

1. We tested how strongly aquatic macroinvertebrate taxa richness and composition were associated with natural variation in both flow regime and stream temperatures across streams of the western United States. 2. We used long‐term flow records from 543 minimally impacted gauged streams to quantify 12 streamflow variables thought to be ecologically important. A principal component analysis reduced the dimensionality of the data from 12 variables to seven principal component (PC) factors that characterised statistically independent aspects of streamflow: (1) zero flow days, (2) flow magnitude, (3) predictability, (4) flood duration, (5) seasonality, (6) flashiness and (7) base flow. K‐means clustering was used to group streams into 4–8 hydrologically different classes based on these seven factors. 3. We also used empirical models to estimate mean annual, mean summer and mean winter stream temperatures at each stream site. We then used invertebrate data from 63 sites to develop Random Forest models to predict taxa richness and taxon‐specific probabilities of capture at a site from flow and temperature. We used the predicted taxon‐specific probabilities of capture to estimate how well predicted assemblages matched observed assemblages as measured by RIVPACS‐type observed/expected (O/E) indices and Bray–Curtis dissimilarities. 4. Macroinvertebrate taxon richness was only weakly associated with streamflow and temperature variables, implying that other factors more strongly influenced taxa richness. 5. In contrast to taxa richness, taxa composition was strongly associated with streamflow and temperature. Predictions of taxa composition (O/E and Bray–Curtis) were most precise when both temperature and streamflow PC factors were used, although predictions based on either streamflow PC factors or temperature alone were also better than null model predictions. Of the seven aspects of the streamflow regime we examined, variation in baseflow conditions appeared to be most directly associated with invertebrate biotic composition. We were also able to predict assemblage composition from the conditional probabilities of hydrological class membership nearly as well as Random Forests models that were based directly on continuous PC factors. 6. Our results have direct implication for understanding the relative importance of streamflow and temperature in regulating the structure and composition of stream assemblages and for improving the accuracy and precision of biological assessments.     

Small sample bias in dynamic occupancy models

Occupancy models may be used to estimate the probability that a randomly selected site in an area of interest is occupied by a species (ψ), given imperfect detection (p). This method can be extended, given multiple survey periods, to permit the estimation of seasonal probabilities of ψ, colonization (γ), persistence (φ), and extinction (1 − φ) in season t. We evaluated the sampling properties of estimators of these parameters using simulated data across a range of the parameters, differing levels of sites and visits, with a published dynamic occupancy model (Royle and Kery 2007). Bias depended largely on p and the number of visits, but also on the number of sites, ψ_t, γ, and 1 − φ. To decrease bias in all parameters to near zero, our results suggest that the number of required visits will depend on p, such that the probability of detection at an occupied site is near 0.9, and the required number of sites will be near 60 for ψ_t estimation and 120 or greater for γ and 1 − φ estimation. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.     

Dissimilar patterns of genetic variation in two insular endemic plants sharing species characteristics,distribution, habitat,and ecological history

Camssonia guadalupensis ssp. clementina (Onagraceae) and Cryptantha traskiae (Boraginaceae) share many species characteristics that affect levels and pattern of genetic variation. In addition, they have a similar distribution, are found in the same habitat, and share ecological history by virtue of co-occurring at nearly all of the locations at which they are found. All populations of the two taxa on San Clemente Island were surveyed for genotypes at 16 allozyme loci, revealing generally low levels of genetic variation. However, Cam. g. clementina has more genetic variation than Cryp. traskiae at the taxon level (P = 37.5 versus 18.8, A = 1.69 versus 1.31, and H_E = 0.088 versus 0.003) and significantly more alleles and higher heterozygosity within populations (A = 1.09 versus 1.03, A_E = 1.02 versus 1.00; H_O = 0.013 versus 0.001 and H_E = 0.017 versus 0.003). Some populations of each taxon are monomorphic at all loci. Much greater differentiation among populations occurs in Cam. g. clementina (G_ST = 0.810) than in Cryp. traskiae (G_ST = 0.042). Locations of the more variable populations of each taxon do not coincide, and the pattern of genetic similarity of localities differs in the two taxa. Striking population genetic differences exist between these taxa despite shared species characteristics, distribution, habitat, and recent history.     

Blood respiratory properties of rainbow trout,Salmo gairdneri: Responses to hypoxia acclimation and anoxic incubation of blood in vitro

Summary Blood respiratory properties of rainbow trout were determined following acclimation to normoxia and two levels of hypoxia.The most prominent response appeared to be an increase in blood O₂ affinity graded to the level of hypoxia. TheP ₅₀ values (at pH 7.8 and 20°C) were 24.1 21.7 and 16.8 mm Hg when specimens were acclimated to water O₂ tensions of 150, 80 and 50 mm Hg, respectively. The blood O₂ affinity was closely correlated with the erythrocytic ATP concentration. The stepwise correlation of ATP andP ₅₀, when trout were exposed to graded oxygen lack in the water, indicates that the blood O₂ affinity is precisely regulated.Anoxic incubation of trout blood in vitro induced a rapid reduction in erythrocytic ATP concentration (t _1/2=75 min), which was closely correlated to theP ₅₀ value. The drop inP ₅₀ value during anoxic exposure can be explained partly by the direct allosteric effect of a decreased erythrocytic ATP concentration and partly by the modified Donnan distribution of protons across the red cell membrane. Reoxygenation of the incubated blood, however, only partly re-established the erythrocytic ATP concentration, with a concurrent rise inP ₅₀ value.The results invite discussion about the mechanism, by which fish regulate their blood O₂ affinity. It is concluded, that it is regulated at the organismal rather than at the red cell level.Abbreviation (E) erythrocytes, erythrocytic     

Inequalities for estimative and predictive probabilities

Let μE be the estimative and μP the predictive measures for assessing Gaussian probabilities. It is shown for convex symmetric sets A that _μE(A) _μP(A) and that similar inequalities hold between members of a sequence of predictive measures. An application yields inequalities for generalized indices of atypicality associated with the two methods.     

Isolation and characterization of microsatellite markers for Primulina tabacum, a critically endangered perennial herb

Primulina tabacum is a rare and endangered perennial herb with highly restricted limestone distribution in southern China. To enrich our scientific conservation for this species, we developed ten microsatellite markers using repetitive DNA enriched libraries. The number of alleles per microsatellite locus varied from two to six. The expected (H _E) and observed (H _O) heterozygosities varied from 0.4059 to 0.7294 and from 0.1364 to 0.5217, respectively. These markers will be employed in future studies of genetic structure in P. tabacum.     

How genetically variable are Neottia ovata (Orchidaceae) populations in northeast Poland?

Using 32 allozyme loci, we examined the genetic diversity of ten populations of Neottia ovata differing in size and located in different regions of northeast Poland. Within‐population genetic variation was low (P_pl = 9.4–31.2%, A = 1.09–1.34 and H_E = 0.044–0.128) relative to taxa with similar life histories. In the majority of N. ovata populations (excluding those in Biebrza), we noted high genotypic diversity (0.49?1.00) and high proportions of unique genotypes (86–100%). Neottia ovata shows a strong pattern of genetic differentiation among populations in northeast Poland, reflected in the high overall F_ST value (0.409). There was a weak, but significant, relationship between genetic and geographical distance (r = 0.09, P < 0.05). We discuss the breeding system, small population sizes and population subdivision as the most important factors affecting the genetic diversity of this species. © 2012 The Linnean Society of London, Botanical Journal of the Linnean Society, 2012, 170 , 40–49     

Energetics of swimming at maximal speeds in humans

The energy cost per unit of distance (C _s, kilojoules per metre) of the front-crawl, back, breast and butterfly strokes was assessed in 20 elite swimmers. At sub-maximal speeds (v), C _s was measured dividing steady-state oxygen consumption (V˙O₂) by the speed (v, metres per second). At supra-maximal v, C _s was calculated by dividing the total metabolic energy (E, kilojoules) spent in covering 45.7, 91.4 and 182.9 m by the distance. E was obtained as: E = E _an+V˙O_2max t _p−V˙O_2max(1−e^{−( t p/)}), where E _an was the amount of energy (kilojoules) derived from anaerobic sources, V˙O_2max litres per second was the maximal oxygen uptake, α (=20.9 kJ · l O₂ ⁻¹) was the energy equivalent of O₂, τ (24 s) was the time constant assumed for the attainment of V˙O_2max at muscle level at the onset of exercise, and t _p (seconds) was the performance time. The lactic acid component was assumed to increase exponentially with t _p to an asymptotic value of 0.418 kJ · kg⁻¹ of body mass for t _p ≥ 120 s. The lactic acid component of E _an was obtained from the net increase of lactate concentration after exercise (Δ[La]_b) assuming that, when Δ[La]_b = 1 mmol · l⁻¹ the net amount of metabolic energy released by lactate formation was 0.069 kJ · kg⁻¹. Over the entire range of v, front crawl was the least costly stroke. For example at 1 m · s⁻¹, C _s amounted, on average, to 0.70, 0.84, 0.82 and 0.124 kJ · m⁻¹ in front crawl, backstroke, butterfly and breaststroke, respectively; at 1.5 m · s⁻¹, C _s was 1.23, 1.47, 1.55 and 1.87 kJ · m⁻¹ in the four strokes, respectively. The C _s was a continuous function of the speed in all of the four strokes. It increased exponentially in crawl and backstroke, whereas in butterfly C _s attained a minimum at the two lowest v to increase exponentially at higher v. The C _s in breaststroke was a linear function of the v, probably because of the considerable amount of energy spent in this stroke for accelerating the body during the pushing phase so as to compensate for the loss of v occurring in the non-propulsive phase. Accepted: 14 April 1998     

Circulatory response to hyperthermia during acute normovolaemic haemodilution

 Cats anaesthetized with a mixture of chloralose and urethane were exposed to heat stress in two groups. In the first group (n=10) of control animals, the effect of heat stress on haemodynamic variables was recorded at control haematocrit (HCT) of 42.0±1.0%. In a second group, the effect of heat stress was studied after induction of acute normovolaemic haemodilution (HCT of 13.0±1.0%). Haemodilution was induced to a maximum of 60% replacement of blood with dextran (mol.wt. 150000). Heat stress was induced by surface heating and core body temperature was raised from 37° C to 42° C. The effect of heat stress and haemodilution on various haemodynamic variables, viz. left ventricular pressure (LVP), left ventricular contractility (LVdP/dt _max), heart rate (HR), cardiac output (CO), arterial blood pressure (ABP), right atrial pressure (RAP), and arterial blood PO₂, PCO₂ and pH was examined. Haemodilution produced significant (P<0.05) increases in HR and CO but there were no significant (P>0.05) changes in ABP, RAP, LVdP/dt _max and total peripherial resistance (TPR). Hyperthermia caused a significant fall (P<0.05) in TPR. However, the percentage fall in TPR was higher in the control group. On exposure to heat stress, there were significant (P<0.05I increases in HR and CO in both the groups; however, HR and CO values were significantly (P<0.05) higher in the haemodiluted group compared to the control. The latter findings could be due either to the higher basal values of these variables with the fall in HCT or to inefficient cardiovascular regulatory mechanisms. The lack of efficient regulatory control under such severe stress conditions makes the cardiovascular system of anaemic animals more vulnerable to heat stress. In conclusion, the results of the present study showed deleterious effects of heat stress in both the groups. The higher values of HR and CO in the haemodiluted group may be responsible for circulatory failure at low HCT values, indicating a higher risk in the haemodiluted group as compared to the control group. Received: 3 February 1997 / Revised: 16 September 1997 / Accepted: 18 November 1997     

Use of tolerance values to diagnose water-quality stressors to aquatic biota in New England streams

Identification of stressors related to biological impairment is critical to biological assessments. We applied nationally derived tolerance indicator values for four water-quality variables to fish and benthic macroinvertebrate assemblages at 29 sites along an urban gradient in New England. Tolerance indicator values (TIVs), as biologically based predictors of water-quality variables, were determined for dissolved oxygen, nitrite plus nitrate (nitrate), total phosphorus, and water temperature for each site based on observed biological assemblages (TIV_O), and for expected assemblages (TIV_E). The quotient method, based on a ratio of the TIVs for observed and expected assemblages (tolerance units), was used to diagnose potential water-quality stressors. In addition, the ratio of measured water-quality values to water-quality criteria (water-quality units) was calculated for each water-quality variable to assess measured water-quality stressors. Results from a RIVPACS predictive model for benthic macroinvertebrates and Bray-Curtis dissimilarity for fish were used to classify sites into categories of good or impaired ecological condition. Significant differences were detected between good and impaired sites for all biological tolerance units (fish and benthic macroinvertebrate assemblages averaged) except for nitrate (P = 0.480), and for all water-quality units except for nitrate (P = 0.183). Diagnosis of water-quality stressors at selected sites was, in general, consistent with State-reported causes of impairment. Tolerance units for benthic macroinvertebrate and fish assemblages were significantly correlated for water temperature (P = 0.001, r = 0.63), dissolved oxygen (P = 0.001, r = 0.61), and total phosphorus (P = 0.001, r = 0.61), but not for nitrate (P = 0.059, r = −0.35). Differences between the two assemblages in site-specific diagnosis of water-quality stressors may be the result of differences in nitrate tolerance.