Using Dynamic Modeling to Scope Environmental Problems and Build Consensus

/ This paper assesses the changing role of dynamic modeling for understanding and managing complex ecological economic systems. It discusses new modeling tools for problem scoping and consensus building among a broad range of stakeholders and describes four case studies in which dynamic modeling has been used to collect and organize data, synthesize knowledge, and build consensus about the management of complex systems. The case studies range from industrial systems (mining, smelting, and refining of iron and steel in the United States) to ecosystems (Louisiana coastal wetlands, and Fynbos ecosystems in South Africa) to linked ecological economic systems (Maryland's Patuxent River basin in the United States). They illustrate uses of dynamic modeling to include stakeholders in all stages of consensus building, ranging from initial problem scoping to model development. The resultant models are the first stage in a three-stage modeling process that includes research and management models as the later stages.KEY WORDS: Dynamic modeling; Scoping; Consensus building; Environmental management; Ecosystem management; Policy making; Graphical programming languages     

Sympatric size variants of the microcopepod Oncaea venusta exhibit distinct lineages in DNA sequences

We investigated the phylogenetic relationships among different size groups of the pelagic microcopepod Oncaea venusta Philippi, 1843, by comparing the patterns of genetic variation of specimens collected at five locations of the Indo-West Pacific Ocean. Phylogenetic analyses were based on sequence data obtained from two DNA markers: A 310 bp fragment of the mitochondrial cytochrome b (cyt b) gene and a 480 bp fragment of the nuclear internal transcribed spacer 1 (ITS1). The cyt b sequences showed a much higher level of variation than those from ITS1, but the conclusion from both genes was concordant. Four genetic clades could be differentiated. A small- and a large-size group were unambiguously assigned to two distinct clades or lineages. Unexpectedly, the medium-sized individuals could be divided into another two different genetic clades. All four lineages were supported by high bootstrap values. The high levels of sequence divergence under sympatric conditions indicated that at least the two main groups, the large and the small one, may be assigned to different species. For the medium-size group additional morphological studies and more sensitive nuclear markers are required to clarify their taxonomic status.     

Über den Blutzucker der Biene (Apis mellifica)

The Science of Nature -     

Die magnetischen Eigenschaften der Uranoxyde

The Science of Nature -     

Sources of bias in ecological studiesof non-rare events

Ecological studies investigate relationships at the level of the group, rather than at the level of the individual. Although such studies are a common design in epidemiology, it is well-known that estimates may be subject to ecological bias. Most discussion of ecological bias has focused on rare disease events, where the tractability of the loglinear model allows some characterization of the nature of different biases. This paper concentrates on non-rare events, where the Poisson approximation to the binomial distribution is not appropriate. We limit the discussion to bias that arises from within-area variability in exposures and confounders. Our aims are to investigate the likely sizes and directions of bias and, where possible, to suggest methods for controlling the bias or for addressing the sensitivity of inference to assumptions on the nature of the bias. We illustrate that for non-rare events it is much more difficult to characterize the direction of bias than in the rare case. A series of simple numerical examples based on a chronic study of respiratory health illustrate the ideas of the paper.     

Addressing analytical uncertainties in the determination of trichloroacetic acid in soil

Soil is an important compartment in the environmental cycling of trichloroacetic acid (TCA), but soil TCA concentration is a methodologically defined quantity; analytical methods either quantify TCA in an aqueous extract of the soil, or thermally decarboxylate TCA to chloroform in the whole soil sample. The former may underestimate the total soil TCA, whereas the latter may overestimate TCA if other soil components (e.g. humic material) liberate chloroform under the decarboxylation conditions. The aim of this work was to show that extraction and decarboxylation methods yield different TCA concentrations because the decarboxylation method can also determine "bound" TCA. Experiments with commercial humic acid solutions showed there was no additional chloroform formation under decarboxylation conditions, and that all TCA in a TCA-humic acid mixture could be quantitatively determined (108 +/- 13%). Anion exchange resin was used as a provider of solid-phase TCA binding; only 5 +/- 1% of a TCA solution mixed with the resin was present in the aqueous extract subsequently separated from the resin, yet the decarboxylation method yielded mass balance (123 +/- 22%) with TCA remaining in the resin. In aqueous extraction of a range of soil samples (with or without added TCA spike), the decarboxylation method was able to satisfactorily account for TCA in the extractant + residue post-extraction, compared with whole-soil TCA (+ spike) pre-extraction: e.g. mass balances for unspiked soil from Sikta spruce and larch forest were 99 +/- 8% and 93 +/- 6%, respectively, and for TCA-spiked forest and agricultural soils were 114 +/- 13% and 102 +/- 2%. In each case recovery of TCA in the extractant was substantially less than 100%(<20% for unspiked soils, <55% for spiked soils). Extraction efficiencies were generally lower in more organic soils. The results suggest that analytical methods which utilise aqueous extraction may underestimate whole-soil TCA concentrations. Application of both methodologies together may enhance insight into TCA behaviour in soil.