Antiestrogenic activity of anthropogenic and natural chemicals

A number of natural and man-made chemicals possess antiestrogenic activity, i.e. they antagonize a broad spectrum of estrogen-induced responses in vertebrates. Examples of antiestrogens include dioxin, furan and PCB congeners, certain PAHs, pesticides and indol-3-carbinol derivatives. Major mechanisms of antiestrogenicity are antagonistic action of chemicals at the estrogen receptor, or binding of chemicals to the arylhydrocarbon (Ah) receptor and subsequent interaction with estrogen-responsive genes. Toxicological consequences resulting from antiestrogenic activity have not been conclusively demonstrated to date, although antiestrogenic compounds could critically affect sensitive reproductive and developmental processes.     

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

Fukushima fallout in Northwest German environmental media

Traces of short- and long-lived fallout isotopes (¹³¹I, ¹³⁴Cs and ¹³⁷Cs) were found in environmental samples collected in Northwest Germany (rain water, river sediment, soil, grass and cow milk) from March to May 2011, following the radioactivity releases after the nuclear accident in Fukushima, Japan. The measured concentrations are consistent with reported concentrations in air, amount of rainfall and expected values applying simple radioecological models. The [¹³⁴Cs]/[¹³⁷Cs] ratio reported for air (about 1) allows for discrimination between “recent” and “old” ¹³⁷Cs. Expected ¹³⁶Cs values fell below the detection limits of the instrumentation, despite large sample masses and long counting times.