Principal response curves technique for the analysis of multivariate biomonitoring time series

Although chemical and biological monitoring is often used to evaluate the quality of surface waters for regulatory purposes and/or to evaluate environmental status and trends, the resulting biological and chemical data sets are large and difficult to evaluate. Multivariate techniques have long been used to analyse complex data sets. This paper discusses the methods currently in use and introduces the principal response curves method, which overcomes the problem of cluttered graphical results representation that is a great drawback of most conventional methods. To illustrate this, two example data sets are analysed using two ordination techniques, principal component analysis and principal response curves. Whereas PCA results in a difficult-to-interpret diagram, principal response curves related methods are able to show changes in community composition in a diagram that is easy to read. The principal response curves method is used to show trends over time with an internal reference (overall mean or reference year) or external reference (e.g. preferred water quality or reference site). Advantages and disadvantages of both methods are discussed and illustrated.     

Fourth-corner correlation is a score test statistic in a log-linear trait–environment model that is useful in permutation testing

Ecologists wish to understand the role of traits of species in determining where each species occurs in the environment. For this, they wish to detect associations between species traits and environmental variables from three data tables, species count data from sites with associated environmental data and species trait data from data bases. These three tables leave a missing part, the fourth-corner. The fourth-corner correlations between quantitative traits and environmental variables, heuristically proposed 20 years ago, fill this corner. Generalized linear (mixed) models have been proposed more recently as a model-based alternative. This paper shows that the squared fourth-corner correlation times the total count is precisely the score test statistic for testing the linear-by-linear interaction in a Poisson log-linear model that also contains species and sites as main effects. For multiple traits and environmental variables, the score test statistic is proportional to the total inertia of a doubly constrained correspondence analysis. When the count data are over-dispersed compared to the Poisson or when there are other deviations from the model such as unobserved traits or environmental variables that interact with the observed ones, the score test statistic does not have the usual chi-square distribution. For these types of deviations, row- and column-based permutation methods (and their sequential combination) are proposed to control the type I error without undue loss of power (unless no deviation is present), as illustrated in a small simulation study. The issues for valid statistical testing are illustrated using the well-known Dutch Dune Meadow data set.     

Effective communication about complex environmental issues: Perceived quality of information about carbon dioxide capture and storage (CCS) depends on stakeholder collaboration

This experimental research addresses the effectiveness of communication about complex environmental issues, depending on whether the same information is provided by multiple collaborating or by individual organizations (i.e., stakeholders). The information provided pertains to carbon dioxide capture and storage (CCS) technology, as an example of a complex environmental issue. In Studies 1 (N = 75) and 2 (N = 66) we found that participants perceived factual information from collaborating stakeholders to be of higher quality than when the same information was provided by individual stakeholders. As predicted, the expectation of diverse perspectives being represented in the collaborative information mediated this effect. In addition, in Study 3 (N = 79) the perceived dissimilarity of collaborating stakeholders was shown to be an important precondition for the collaboration effect observed in Studies 1 and 2. Finally, these studies indicate that occasional collaboration between different stakeholders does not necessarily harm the perceived credibility of each individual stakeholder.     

Methylcyclopentadienyl Manganese Tricarbonyl as an Antiknock: Composition and Fate of Manganese Exhaust Products

Methylcyclopentadienyl manganese tricarbonyl (MMT) has been marketed as a combustion improver for fuel oil and turbine fuel. Use concentrations for this purpose are about 0.025 g manganese/gal in fuel oil and 0.08 to 0.5 g/gal in turbine fuels. In addition, it has been used to a small extent in gasoline.     

Effects of frequent mating on sex allocation in the simultaneously hermaphroditic great pond snail (Lymnaea stagnalis)

Simultaneous hermaphrodites have the opportunity to control the allocation of resources to the male and female function depending on the circumstances. Such flexibility also provides the possibility to influence sex allocation in the mating partner. To investigate this idea, we measured egg production (female investment) and sperm production as well as prostate gland size (both are part of male investment) under different mating regimes in the great pond snail Lymnaea stagnalis. We find no evidence for the prediction from sex allocation theory that sperm production increases with mating frequency. However, we do find that animals with more mating opporunities develop smaller prostate glands, in which seminal fluid is produced. Moreover, repeated mating increases egg production, thus shifting allocation towards the female function, and probably decreases growth. So, our data hint at a three-way trade-off between part of the male function (prostate gland), female function, and growth. Interestingly, sex allocation seems to be shifted in the opposite direction from the one predicted by theory. We discuss how this feminization is suggestive of a direct manipulation by the sperm donor, probably to stimulate immediate sperm use.     

Food waste in municipal mixed waste produced at household level: empirical evidence from the Czech Republic

Journal of Material Cycles and Waste Management - The problem of food waste is broadly discussed, but empirical data are still missing. The importance of this topic increases as the reporting of...     

The effect of the dumping of waste-acid from the titanium-dioxide production on the chlorophyl-a concentration of North Sea water: A time series analysis

Since 1963 the waste-acid of the German titanium dioxide industry is discharged off the Dutch coast. From March 1980 on the dumping takes place in an area situated 40–80 km from the coast. Although about 2 500 000 kg waste-acid is discharged every day, until now no effects could be found on the plankton.This paper describes the study on the effects of the dumping on the chlorophyl-a concentration of the seawater at a site north of the dumping area, with the help of time series analysis. It is shown that considerable changes in the chlorophyl concentration occur during the dumping period and that these changes coincide with certain events within the dumping history. However, it is most remarkable that the starting of the dumping itself does not show an effect on the chlorophyl concentrations. Explanations are suggested, but could not be investigated yet.This study shows also that collecting data without a proper statistical design make it impossible to draw unambiguous conclusions based on those data.     

Breeding Birds as a Farm Product

Abstract: Since the 1950s, meadowbird populations have been under increasing threat from radical changes in farming practices. We studied the possibilities for conserving meadowbirds on modern, intensive dairy farms in the Netherlands. Here, the conventional strategy for the conservation of meadowbirds is to restrict farming intensity and compensate farmers for their production losses. To increase the breeding success of meadowbirds, however, dairy farmers can fine-tune farming practices to yearly and local circumstances. Because this fine-tuning is difficult to enforce by legislation, we propose that farmers be paid for clutches bred on their land. Thus, farmers are paid for what they produce, but not restricted in their farming practices. The results of the first small-scale experiments, in which breeding success was compared between farms where farmers were paid for meadowbird clutches and farms where farmers were not paid, are encouraging. Breeding success of meadowbirds was significantly higher where farmers were paid than where they were not ( breeding success of Lapwing [   Vanellus vanellus ]: 64.7% on paid farms, 48.2% on unpaid farms; Black-tailed Godwit [   Limosa limosa ]: 63.1% paid, 39.3% unpaid). The effects on meadowbird populations could not yet be detected. The per-clutch payment system is less expensive than compensation for income losses: paying for clutches costs 40 Euro per clutch, whereas compensating for income losses costs 100–400 Euro per clutch (1 Euro is approximately equal to 1 U.S. dollar). Farmers are enthusiastic, and the system encourages cooperation between farmers and nature conservationists.     

Arthropod assemblages are best predicted by plant species composition

Insects and spiders comprise more than two-thirds of the Earth's total species diversity. There is wide concern, however, that the global diversity of arthropods may be declining even more rapidly than the diversity of vertebrates and plants. For adequate conservation planning, ecologists need to understand the driving factors for arthropod communities and devise methods, that provide reliable predictions when resources do not permit exhaustive ground surveys. Which factor most successfully predicts arthropod community structure is still a matter of debate, however. The purpose of this study was to identify the factor best predicting arthropod assemblage composition. We investigated the species composition of seven functionally different arthropod groups (epigeic spiders, grasshoppers, ground beetles, weevils, hoppers, hoverflies, and bees) at 47 sites in The Netherlands comprising a range of seminatural grassland types and one heathland type. We then compared the actual arthropod composition with predictions based on plant species composition, vegetation structure, environmental data, flower richness, and landscape composition. For this we used the recently published method of predictive co-correspondence analysis, and a predictive variant of canonical correspondence analysis, depending on the type of predictor data. Our results demonstrate that local plant species composition is the most effective predictor of arthropod assemblage composition, for all investigated groups. In predicting arthropod assemblages, plant community composition consistently outperforms both vegetation structure and environmental conditions (even when the two are combined), and also performs better than the surrounding landscape. These results run against a common expectation of vegetation structure as the decisive factor. Such expectations, however, have always been biased by the fact that until recently no methods existed that could use an entire (plant) species composition in the explanatory role. Although more recent experimental diversity work has reawakened interest in the role of plant species, these studies still have not used (or have not been able to use) entire species compositions. They only consider diversity measures, both for plant and insect assemblages, which may obscure relationships. The present study demonstrates that the species compositions of insect and plant communities are clearly linked.     

Bayesian model-based cluster analysis for predicting macrofaunal communities

To predict macrofaunal community composition from environmental data a two-step approach is often followed: (1) the water samples are clustered into groups on the basis of the macrofauna data and (2) the groups are related to the environmental data, e.g. by discriminant analysis. For the cluster analysis in step 1 many hard, seemingly arbitrary choices have to be made that nevertheless influence the solution (similarity measure, clustering strategy, number of clusters). The stability of the solution is often of concern, e.g. in clustering by the program. In the discriminant analysis of step 2 it can occur that a water sample is misclassified on the basis of the environmental data but on further inspection happens to be a borderline case in the cluster analysis. One would then rather reclassify such a sample and iterate the two steps. Bayesian latent class analysis is a flexible, extendable model-based cluster analysis approach that recently has gained popularity in the statistical literature and that has the potential to address these problems. It allows the macrofauna and environmental data to be modelled and analyzed in a single integrated analysis. An exciting extension is to incorporate in the analysis prior information on the habitat preferences of the macrofauna taxa such as is available in lists of indicator values. The output of the analysis is not a hard assignment of water samples to clusters but a probabilistic (fuzzy) assignment. The number of clusters is determined on the basis of the Bayes factor. A standard feature of the Bayesian method is to make predictions and to assess their uncertainty. We applied this approach to a data set consisting of 70 water samples, 484 macrofauna taxa and four environmental variables for which previously a five cluster solution had been proposed. The standard for Bayesian estimation, the Gibbs sampler, worked fine on a subset with only 12 selected taxa but did not converge on the full set with 484 taxa. This is due to many configurations in which the assignment probabilities are all very close to either 0 or 1. This convergence problem is comparable with the local optima problem in classical cluster optimization algorithms, including the EM algorithm used in Latent Gold, a Windows program for latent class analysis. The convergence problem needs to be solved before the benefits of Bayesian latent class analysis can come to fruition in this application. We discuss possible solutions.