Application of multiple stable isotopes to aid identification of the origin of regional and organic animal products in Hesse, Germany.

There is an increasing global demand for regional and organic produce. However, the growth of these markets depends on consumers' trust. Thus, novel methods must be developed to aid the verification of the origin of produce. We built on our previous study to identify the geographical origin and production method of animal-derived food products. Thirty-samples of eggs, 99 of milk, 34 of beef, and 62 of pork were collected from different regions in central Germany and analysed for their stable isotopic composition. The analysis followed a single-variate authentification approach using five isotope signatures, δ18O, δ2H, δ13C, δ15N, and δ34S. The best-performing indicators for verification of the geographical origin were δ15N and δ34S for beef; δ18O, δ2H, and δ13C for milk, and δ2H and δ13C for pork. These tracers indicated statistically significant differences among regions with the exception of pork; the results recorded for eggs were inconclusive. It was possible to distinguish between production methods by means of δ15N and δ34S (beef); all five tracers (eggs), and δ13C, δ15N, and δ34S (milk). This study demonstrated how the analysis of stable isotopes can be employed to determine the geographic region of origin and production method of animal-derived products in Germany.

Assessment of multiple stable isotopes for tracking regional and organic authenticity of plant products in Hesse, Germany.

As demand for regional and organically produced foodstuff has increased in Europe, the need has arisen to verify the products' origin and production method. For food authenticity tracking (production method and origin), we examined 286 samples of wheat (Triticum aestivum), potatoes (Solanum tuberosum), and apples (Malus domestica) from different regions in Germany for their stable isotope compositions of oxygen, hydrogen, carbon, nitrogen and sulphur. Single-variate authentication methods were used. Suitable isotope tracers to determine wheat's regional origin were δ18O and δ34S. δ13C helped to distinguish between organic and conventional wheat samples. For the separation of the production regions of potatoes, several isotope tracers were suitable (e.g. δ18O, δ2H, δ15N, δ13C and δ34S isotopes in potato protein), but only protein δ15N was suitable to differentiate between organic and conventional potato samples. For the apple samples, 2H and 18O isotopes helped to identify production regions, but no significant statistical differences could be found between organically and conventionally farmed apples. For food authenticity tracking, our study showed the need to take the various isotopes into account. There is an urgent need for a broad reference database if isotope measurements are to become a main tool for determining product's origin.

Who Smells? Forecasting Taste and Odor in a Drinking Water Reservoir.

Taste and odor problems can impede public trust in drinking water and impose major costs on water utilities. The ability to forecast taste and odor events in source waters, in advance, is shown for the first time in this paper. This could allow water utilities to adapt treatment, and where effective treatment is not available, consumers could be warned. A unique 24-year time series, from an important drinking water reservoir in Saskatchewan, Canada, is used to develop forecasting models of odor using chlorophyll a, turbidity, total phosphorus, temperature, and the following odor producing algae taxa: Anabaena spp., Aphanizemenon spp., Oscillatoria spp., Chlorophyta, Cyclotella spp., and Asterionella spp. We demonstrate, using linear regression and random forest models, that odor events can be forecast at 0-26 week time lags, and that the models are able to capture a significant increase in threshold odor number in the mid-1990 s. Models with a fortnight time-lag show a high predictive capacity (R(2) = 0.71 for random forest; 0.52 for linear regression). Predictive skill declines for time lags from 0 to 15 weeks, then increases again, to R(2) values of 0.61 (random forest) and 0.48 (linear regression) at a 26-week lag. The random forest model is also able to provide accurate forecasting of TON levels requiring treatment 12 weeks in advance-93% true positive rate with a 0% false positive rate. Results of the random forest model demonstrate that phytoplankton taxonomic data outperform chlorophyll a in terms of predictive importance.

Beaver-mediated methane emission: The effects of population growth in Eurasia and the Americas.

Globally, greenhouse gas budgets are dominated by natural sources, and aquatic ecosystems are a prominent source of methane (CH(4)) to the atmosphere. Beaver (Castor canadensis and Castor fiber) populations have experienced human-driven change, and CH(4) emissions associated with their habitat remain uncertain. This study reports the effect of near extinction and recovery of beavers globally on aquatic CH4 emissions and habitat. Resurgence of native beaver populations and their introduction in other regions accounts for emission of 0.18-0.80 Tg CH(4) year(-1) (year 2000). This flux is approximately 200 times larger than emissions from the same systems (ponds and flowing waters that became ponds) circa 1900. Beaver population recovery was estimated to have led to the creation of 9500-42 000 km(2) of ponded water, and increased riparian interface length of >200 000 km. Continued range expansion and population growth in South America and Europe could further increase CH(4) emissions.