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.     

Choosing the best method for stream bioassessment using macrophyte communities: Indices and predictive models

The bioassessment and monitoring of the ecological status of rivers using macrophytes has gained new momentum since macrophytes were recognised as biological quality elements for the implementation of the European Water Framework Directive (WFD; EU/2000/60).Our objectives were to test the suitability of two predictive modelling approaches to macrophyte communities as a tool for water quality assessment, and to compare their performance with other more common approaches—the use of macrophytes as indicators of the trophic status of rivers and multimetric indices. We used floristic and environmental data that were collected in the spring of 2004 and 2005 from around 400 sites on rivers across mainland Portugal, western Iberia.We build two predictive models: MACPACS (MACrophyte Prediction And Classification System) and MAC (Macrophyte Assessment and Classification) based on RIVPACS and the BEAST methods, respectively. Whereas MACPACS is derived from taxa occurrence data, MAC uses a quantitative measure of taxa abundance. Both models showed good performance in predicting reference sites to the correct group and low rate of misclassification errors. However, they performed differently. MAC depicts a reliable response to the overall human-mediated degradation of fluvial systems, as does the multimetric index (RVI, Riparian Vegetation Index), but MACPACS presented only a poor correlation with the Global Human Disturbance Index and with the nutrients input. The incorporation of abundance data in vegetation predictive models appears to be particularly important to the detection of high levels of degradation. The values for correlations with physical–chemical pressure variables were lower than expected for MTR (Mean Trophic Rank) due to an insufficient number of scoring species found in Portuguese fluvial systems. Our results suggest that the most effective methods for bioassessment in Mediterranean-type rivers are either the RVI or the MAC predictive model.     

Structure and Dynamics of a Benthic Invertebrate Community in an Intertidal Area of the Tagus Estuary, Western Portugal: A Six Year Data Series

A predictive model, incorporating macroinvertebrate and environmental data, similar to that developed for Australian rivers (AUSRIVAS) and British rivers (RIVPACS) was constructed using a dataset collected from 23 reference (least altered) wetlands on the Swan Coastal Plain, Western Australia, sampled in summer and spring, 1989 and spring, 1990. Four main groups of reference wetlands were identified by UPGMA classification (using the Bray–Curtis dissimilarity measure). Distinguishing environmental variables identified by Stepwise Multiple Discriminant Function Analysis were: calcium, colour (gilvin), latitude, longitude, sodium and organic carbon. Observed to expected ratios of taxa with a >50% chance of occurrence (OE50) derived from the model for a suite of 23 test wetlands sampled in spring, 1997, were significantly correlated with pH and the depth of the sampling sites. Greater discrimination between the test wetlands was provided by the OE50 ratios than either raw richness (number of families) or a biotic index (SWAMPS). Results obtained for a subset of 11 test wetlands sampled with both a rapid bioassessment protocol (incorporating field picking of 200 invertebrates collected in 2 min sweeps from selected habitats) and a semi-quantitative protocol (incorporating laboratory picking of all invertebrates collected in sweeps along 10 m transects at randomly allocated sites) were not significantly different, indicating that the former could be used to reduce the time and costs associated with macroinvertebrate-based wetland monitoring programs. In addition to providing an objective method of assessing wetland condition, predictive modelling provides a list of taxa expected to occur under reference conditions, which can be used as a target in wetland restoration programs. The probable impediment to widespread adoption of predictive modelling for wetland bioassessment is the need to produce models tailored to specific geographic regions and specific climatic conditions. This may incur significant costs in countries, such as Australia, which span a wide range of climatic zones.     

Assessment of the biological health of the Brantas River, East Java, Indonesia using the Australian River Assessment System (AUSRIVAS) methodology

This study aimed to evaluate the applicability of the Australian River Assessment System (AUSRIVAS) bioassessment methodology to assess the biological health of streams in the upper-middle Brantas River catchment, East Java, Indonesia. A total of 84 `minimally disturbed' reference sites were selected and sampled for macroinvertebrates in riffle habitats. Sampling of macroinvertebrates and identification to family level was conducted by local biologists following intensive training, and under supervision. A quality control protocol was introduced to ensure the data were reliable and reproducible. A suite of `potential predictor' and `monitoring' environmental variables were also measured at each site. The macroinvertebrate data were used to develop a predictive AUSRIVAS model for the upper-middle Brantas river, and the model was then used to assess the `health' of 15 test sites in the catchment. Bioassessment outputs – Observed (O)/Expected (E) ratios – were found to be broadly related to measures of physical disturbance from land use and riparian degradation. Through the process of local reference site selection and sampling, model development, validation and subsequent use, the Australian AUSRIVAS rapid bioassessment method was assessed as being highly applicable to the upper-middle catchment sections of Indonesian river systems.     

Sample Variability Influences on the Precision of Predictive Bioassessment

The rapid bioassessment technique we investigate (AUSRIVAS) requires a nationally standardized sampling protocol that uses a single collection of macroinvertebrates (without replication) taken from 10 m of specific habitats (e.g. stream edge and/or riffle) and sub-samples of 200 animals. The macroinvertebrate data are run through predictive models that provide an assessment of biological condition based on a comparison of the animals found in the collection (the observed) and those expected to be there given the site-specific characteristics of the stream (the O/E taxa score). The important questions are related to the conclusions regarding river condition that can be drawn from the biological assessment. Rapid bioassessment studies are generally of two types: those for assessment of individual sites and those where many sites are selected to collectively assess the potential impacts of some human activity such as forestry or agriculture. We wanted to identify the effects of sample variability on the outputs of this predictive bioassessment technique. We found that a single collection of benthic macroinvertebrates was sufficient for bioassessment when taken from a site that had a large area of nearly uniform substrate and was in good condition. Also, collections taken from a larger and smaller area of substrate (1.75, 3.5 or 7 m²) gave the same bioassessment. In other sites, not in such good condition, the variability in bioassessment from different collections could result in different interpretations of biological condition. For all sites, regardless of condition, much of the variation in bioassessment was derived from sub-sampling the macroinvertebrates. We develop a statistical sub-sampling and solver algorithm that provides a measure of variability and a statistically valid probability of impairment for a single site, without the need to actually collect the hundreds of replicated collections needed for this study. We found that assessment at impaired sites, where only 1 collection and 1 sub-sample are taken (a common situation in rapid assessment), the 95% confidence level for O/E taxa scores is estimated to be as much as ±0.22. At sites in reference condition, the 95% confidence interval may be much narrower (~±0.1 O/E units). Therefore, assessments of sites at, or near, reference condition will be more precise than for impaired sites. Power analysis revealed that where single sites are being assessed we recommend a sample collected from 3.5 m² of habitat, but replicate collections should be taken at a site (rather than one only) and we recommend replicate sub-samples of each collection (total of six sub-samples from a site). However, this would remove a ‘rapid’ component of the bioassessment. We recommend the addition of sub-sampling and solver algorithms to the predictive models such as AUSRIVAS to provide a statistical measure of probability of impairment. An adaptive sub-sampling regime could then be used to optimize sampling effort. For example, a single sub-sample may be sufficient for screening or the agency could use the sub-sample and solver algorithms to sub-sample the parent sample for a more precise estimate of the biological condition. Replication should be maximized at the spatial scale required for reporting: site, or regional. But as a general rule, catchment or land-use scale studies should maximize replicate sites, and site-scale assessments should maximize replication within sites.     

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.     

Water quality assessment of Portuguese streams: Regional or national predictive models?

The European Water Framework Directive (WFD 2000) brought the need in European Union countries to establish consistent quantitative methods for the water quality assessment of streams, using aquatic communities. With this work we aimed to develop predictive models using macroinvertebrate communities that could be used in Portugal as an alternative to the more traditional indices and metrics. We used data from 197 reference sites and 174 sites suspected of being impaired, which were obtained in a national survey conducted in 2004–2005 by the Instituto da Água (INAG, Portugal). The spatial scale at which to develop predictive models was an issue to address because the Portuguese territory covers a wide variety of landscapes in a small area. We built three models using the AUSRIVAS methods, a national and two regional (North and South) models that produced acceptable assessments. However, the regional models, predicted more taxa than the National model, were more accurate and had lower misclassification errors when placing sites into pre-defined groups. The regional models were also more sensitive to some disturbances related to water chemistry (e.g., nutrients, BOD₅, oxidability) and land use. The exception was for the northern costal area, which had few reference sites. In the northern costal area the National model provides more useful results than the regional model. The 5-class WFD quality assessment scheme, adapted from the AUSRIVAS bands, appears to be justified because of the good correspondence between the human disturbance level and the classes to which test sites were allocated. Elimination of the AUSRIVAS X band in the WFD scheme has produced a clearer relationship. The predictive models were able to detect a decline in river health, responded to several causes of degradation and provided site-specific assessments.     

Environmental and geographical constraints on common swift and barn swallow spring arrival patterns throughout the Iberian Peninsula

Aim Still poorly understood, the main migratory pathways for most trans‐Saharan species pass through the Iberian Peninsula, which acts as a gateway to the European–African migratory system. Arrival patterns in this region for the common swift (Apus apus) and barn swallow (Hirundo rustica), of similar morphology and flight capabilities, were described, and the environmental and geographical factors best explaining them were examined, in a search for common ecological constraints on these two migratory species. Location Latitude ranged from 36.02 to 43.68°N, longitude from 9.05°W to 3.17°E, and altitude from 0 to 1595 m a.s.l. for 482 common swift and 812 barn swallow Spanish localities spread widely over the Iberian breeding grounds of the two species. Methods Our data set, covering the years 1960–1990, consisted of 3206 first‐arrival dates for common swifts and 6036 for barn swallows. Forty topographical, climatic, river basin, geographical and spatial variables were used as explanatory variables in general regression models (GRMs). GRMs included polynomial terms up to cubic functions in all variables when they were significant. A backward stepwise selection procedure was applied in all models until only significant terms remained. GRMs were applied in two steps. First, we searched for the best model in each one of the five types of variables (topographical, climatic, river basin, geographical and spatial). To cope with the unavoidable correlation between explanatory variables, the relative importance of each type of variable was assessed by hierarchical variance partitioning. Secondly, we searched for that model able to explain the maximum amount of the observed variability in arrival date. To obtain this model all significant explanatory variables were subjected jointly to a GRM. Spatial variables were then added to this model to take any remaining spatial structure in the data into account. Moran's I autocorrelation coefficient was used to check for spatial autocorrelation. Results Both species arrived earlier in the south‐western Iberian Peninsula, where summers are warmer and drier. From there, both species followed the main southern Iberian river basins towards the north‐east; however, several mountainous regions impede the colonization of eastern Iberia. The best models for each type of variable explained 19–47% of the variability in common swift arrival dates and 14–44% in barn swallow arrival dates. Variance partitioning indicated that climatic and geographical variables best explained variability. The best predictive models built with all variables accounted for 52% of the variability in common swift arrival dates and 50% for the barn swallow. Residuals from both models were not spatially autocorrelated, an indication that all major spatially structured variation had been accounted for. Main conclusions Spring arrival patterns are highly dependent on the geographical configuration of the Iberian Peninsula. This spatial constraint forces both species to converge very closely in their spring migration, because common swifts and barn swallows are subject to a trade‐off between optimum migratory pathways and territories ecologically suitable for breeding.     

Consensual predictions of potential distributional areas for invasive species: a case study of Argentine ants in the Iberian Peninsula

Invasive species are known to influence the structure and function of invaded ecological communities, and preventive measures appear to be the most efficient means of controlling these effects. However, management of biological invasions requires use of adequate tools to understand and predict invasion patterns in recently introduced areas. The present study: (1) estimates the potential geographic distribution and ecological requirements of the Argentine ant (Linepithema humile Mayr), one of the most conspicuous invasive species throughout the world, in the Iberian Peninsula using ecological niche modeling, and (2) provides new insights into the process of selection of consensual areas among predictions from several modeling methodologies. Ecological niche models were developed using 5 modeling techniques: generalized linear models (GLM), generalized additive models (GAM), generalized boosted models (GBM), Genetic Algorithm for Rule-Set Prediction (GARP), and Maximum Entropy (Maxent). Models for the eastern and western portions of the Iberian Peninsula were built using subsets of occurrence and environmental data to investigate the potential for ecological niche differences between the invading populations. Our results indicate geographic differences between predictions of different approaches, and the utility of ensemble predictions in identifying areas of uncertainty regarding the species’ invasive potential. More generally, our models predict coastal areas and major river corridors as highly suitable for Argentine ants, and indicate that western and eastern Iberian Peninsula populations occupy similar environmental conditions.

Assessing the risk of freshwater fish introductions into the Iberian Peninsula

1. Preventing the introduction of species likely to become invaders is the best management option to deal with biological invasions. A data set consisting of native, introduced and species not currently present in Iberian Peninsula (n = 167 species) was used to identify freshwater fish species that are likely to be introduced and become successful invaders in the near future. 2. Principal component analysis (PCA) of species traits was used to determine species likely to be introduced, assuming that the traits of species introduced in the future will resemble those of previously introduced species. The likelihood of introduction was calculated as the proportion of neighbour species (in the space defined by the PCA) that have been introduced to the Iberian Peninsula and, together with metrics related to different stages of invasion, was used to construct a region‐specific risk index (Iberian risk index). 3. Introduced species had higher index values compared with native species or species currently absent from the region. The Iberian risk index was positively related to the results of an independent risk analysis for freshwater fish as well as to the geographical spread of species previously introduced to the Iberian Peninsula. 4. Iberian risk index values were used to establish a cut‐off value for estimating the probability of a successful invasion. This threshold value was used to construct a list of 20 species to be included in a ‘watch list’ to prevent freshwater fish invasions in the Iberian Peninsula.     

On the Iberian endemism <Emphasis Type="Italic">Eurylophella iberica</Emphasis> Keffermuller and Da Terra 1978 (Ephemeroptera,Ephemerellidae): current and future potential distributions,and assessment of the effectiveness of the Natura 2000 network on its protection

Eurylophella iberica Keffermüller and Da Terra, 1978 is an endemic insect species of the Iberian Peninsula whose distribution has been poorly studied to date with rather old and scattered records. Here we compiled all existing distribution records and add new records from recent sampling activities. We also used this updated distributional information and environmental data (climate and geology) to estimate both current and future potential distributions in different climate change scenarios. We found that currently ca. 50% of the total Iberian region could present suitable environmental conditions for E. iberica (all the Iberian Peninsula, save the most eastern and Mediterranean areas). However, the potential distributions estimated when considering future climate change scenarios showed a marked reduction in the areas with suitable environmental conditions for the species, especially in the south. The northwest part of the Iberian Peninsula is a crucial zone for the future survival of this endemic species. We also found that most populations that occur in areas with suitable (both current and future) environmental conditions fall outside the Natura 2000 network of protected areas. Our results represent the first attempt to estimate the potential distribution of this endemic species providing important insights for its conservation.     

Dissemination pathways of common bean (Phaseolus vulgaris,Fabaceae) deduced from phaseolin electrophoretic variability. II. Europe and Africa

Phaseolin type, determined by one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis, was used to suggest dissemination routes of common bean (Thaseolus vulgaris) cultivars from their areas of domestication to Europe and Africa. In the Iberian Peninsula, ‘C’ was the most frequent phaseolin type. Only in Chile has a comparably high ‘C’ frequency been observed previously, indicating that many Iberian cultivars may have been introduced from Chile, or that many Chilean cultivars may have come from the Iberian Peninsula. In Europe (outside the Iberian Peninsula), most cultivars exhibited a ‘T’ type. The high frequency of this type may be related to the high frequency of green pod cultivars among European cultivars. Most African cultivars exhibited a ‘T’ or a ‘C’ type and may have been introduced from Brazil, the Iberian Peninsula, or western Europe. ‘T’ or ‘C’ cultivars had larger seeds than ‘S’ cultivars. The phaseolin patterns of cultivars with different seed types and of early French cultivars are discussed.     

Reliability analysis of fish traits reveals discrepancies among databases

1. Trait-based approaches are commonly used in ecology to understand the relationship between biodiversity and ecosystem functioning, environmental filtering or biotic responses to anthropogenic perturbations. However, little is known about the reliability of assigned traits and the consistency of trait information among different databases currently in use.
2. Using 99 native and alien Iberian inland fish species, we investigated a total of 27 biological and ecological traits for their consistency among 19 different databases and identified less reliable traits, that is, traits with high disagreement among databases. Specifically, we used generalised linear models and inter-rater reliability statistics (Krippendorff's α) to test for differences in trait values among databases. We also identified well-studied versus data-deficient traits and species.
3. Our results show notable discrepancies and low reliability for several biological and ecological traits such as microhabitat preference, omnivory, invertivory, rheophily, and limnophily. Least reliable traits were mainly categorical (rather than continuous) and established by expert judgment and without a clear definition or a common methodology. Interestingly, categorical traits such as rheophily or limnophily, which showed significantly lower reliability, concurrently showed higher data availability and use than continuously scaled traits.
4. Such uncertainties in trait assignments could affect bioassessment and other ecological analyses. Species with smaller distributional ranges and those that have been described more recently, presented lower coverage and data availability in trait databases.
5. We encourage further standardisation of fish trait measurement protocols to help improve the robust application of bioassessment indices and trait-based approaches.

     

Cranial variation in the Iberian Peninsula and the Balearic Islands: Inferences about the history of the population

A multivariate analysis of four prehistoric and nine historic populations from the Iberian Peninsula and Balearic Islands with large sample sizes (n > 30 individuals for the neurocranium and n > 15 for the facial skeleton) is presented, considering 874 male and 557 female skulls and using 20 craniometric measurements. Cluster analyses have been undertaken using the squared Euclidean distance as a measure of proximity and the average linkage between groups (UPGMA), and neighbor-joining algorithms as a branching method, and a bootstrap analysis was used to assess the robustness of the clustering topology. The study was complemented with a principal coordinate analysis and with the application of the Mantel test to measure the degree of correspondence between the information furnished by the female and the male samples. The analyses show that the main source of morphometric variability in the Iberian Peninsula is the Basque population. The second source of variation is provided by two populations (Muslims and Jews), different from the rest from an archaeological and cultural point of view, and can probably be attributed to influences from sub-Saharan Africa. The massive deportations of the Jews in 1492 and of the Moors between the 15th and 17th centuries may have erased this source of variability from the present population of the Iberian Peninsula. The remaining studied populations, including samples from Castile, Cantabria, Andalusia, Catalonia and Balearic Islands, are grouped together, showing a notable morphological homogeneity, despite their temporal and geographic heterogeneity. These results are in general agreement with those obtained in synthetic maps, by analyzing multiple genetic markers. In such studies, the Basque population is described as the main source of genetic variability, not only in the Iberian Peninsula, but also in Western Europe. © 1996 Wiley-Liss, Inc.     

Morphological evolution and changes in foraging behaviour of island and mainland populations of Blue Tit (Parus caeruleus) — a test of convergence and ecomorphological hypotheses

Summary We study the leg morphology and feeding postures of two subspecies of the Blue Tit (Parus caeruleus; Tenerife island and the Iberian Peninsula) and the Coal Tit (Parus ater; Iberian Peninsula). We search for evidence supporting the hypothesis of convergent evolution in morphological and ecological traits and we discuss the role of ecomorphological hypotheses as predictors of foraging differences at the intraspecific level. To overcome the problems introduced by environmental characteristics not related to locomotion and competition, we make observations under controlled situations to manage food quality and food access. We determine that the island Blue Tit has a longer tarsometatarsus, larger foot span and a more proximal insertion of the tibialis cranialis muscle (flexor of the tarsometatarsus) than the mainland Blue Tit. These morphological differences are consistent with the more frequent use of hanging and clinging head-up postures by the Iberian Blue Tit. Several ecomorphological hypotheses obtained at the interspecific level with other taxa, have proved to be of high predictive value for explaining ecological differences considering morphological evolution. The Tenerife Blue Tit and the Iberian Coal Tit clearly show close convergence in both feeding postures and leg structure, although some differences in morphology were found between these two species. Convergence in foraging methods between the island Blue Tit and the mainland Coal Tit can be explained without considering current interspecific competition as a determinant of niche space.     

Temporal variability of stream bioassessments using benthic macroinvertebrates

1. When using benthic macroinvertebrate communities for bioassessment, temporal variation may influence judgement as to whether or not a site is degraded.
2. In a survey of sixteen reference and sixteen test sites in the upper Thames River catchment area (UTRCA) in south-western Ontario, Canada, consistent differences between summer and winter samples were found for taxon richness (increase; P = 0.06) and the Family Biotic Index (decrease; P = 0.11). A bioassessment based on these results would indicate better water quality in the same streams in winter relative to summer. No consistent pattern of seasonal difference was detected for Simpson's Diversity and Equitability, or percentage Dominant Taxon.
3. The Reference Condition Approach to bioassessment uses predictive modelling to explain variation in reference communities with the environmental conditions at these sites as predictors. The community at a test site is compared with that predicted by the model. Several predictive models were constructed using simple geographic and habitat characteristics (i.e. catchment area, distance to source, stream width, substrate and habitat diversity) as predictors. By including season of sampling in the models, we increased their predictive power and the ability of the bioassessment to detect degradation. The best results were achieved when separate predictive models were built for each sampling season.     

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.     

Blood parasite diversity (Apicomplexa: Haemogregarinidae) within the western populations of the European pond turtle Emys orbicularis

Systematic Parasitology - Molecular tools have revolutionized assessments of blood parasites in freshwater turtles. In the Iberian Peninsula and North Africa, two native species of terrapins occur,...