Spatial scale of local breeding habitat quality and adjustment of breeding decisions

Experimental studies provide evidence that, in spatially and temporally heterogeneous environments, individuals track variation in breeding habitat quality to adjust breeding decisions to local conditions. However, most experiments consider environmental variation at one spatial scale only, while the ability to detect the influence of a factor depends on the scale of analysis. We show that different breeding decisions by adults are based on information about habitat quality at different spatial scales. We manipulated (increased or decreased) local breeding habitat quality through food availability and parasite prevalence at a small (territory) and a large (patch) scale simultaneously in a wild population of Great Tits (Parus major). Females laid earlier in high-quality large-scale patches, but laying date did not depend on small-scale territory quality. Conversely, offspring sex ratio was higher (i.e., biased toward males) in high-quality, small-scale territories but did not depend on large-scale patch quality. Clutch size and territory occupancy probability did not depend on our experimental manipulation of habitat quality, but territories located at the edge of patches were more likely to be occupied than central territories. These results suggest that integrating different decisions taken by breeders according to environmental variation at different spatial scales is required to understand patterns of breeding strategy adjustment.     

Climate vs. soil factors in local adaptation of two common plant species

Evolutionary theory suggests that divergent natural selection in heterogeneous environments can result in locally adapted plant genotypes. To understand local adaptation it is important to study the ecological factors responsible for divergent selection. At a continental scale, variation in climate can be important while at a local scale soil properties could also play a role. We designed an experiment aimed to disentangle the role of climate and (abiotic and biotic) soil properties in local adaptation of two common plant species. A grass (Holcus lanatus) and a legume (Lotus corniculatus), as well as their local soils, were reciprocally transplanted between three sites across an Atlantic-Continental gradient in Europe and grown in common gardens in either their home soil or foreign soils. Growth and reproductive traits were measured over two growing seasons. In both species, we found significant environmental and genetic effects on most of the growth and reproductive traits and a significant interaction between the two environmental effects of soil and climate. The grass species showed significant home site advantage in most of the fitness components, which indicated adaptation to climate. We found no indication that the grass was adapted to local soil conditions. The legume showed a significant home soil advantage for number of fruits only and thus a weak indication of adaptation to soil and no adaptation to climate. Our results show that the importance of climate and soil factors as drivers of local adaptation is species-dependent. This could be related to differences in interactions between plant species and soil biota.     

Air monitoring of solvent exposed workers with passive samplers in comparison to “biological monitoring (BM)"†

A study was performed comparing ambient air monitoring (AM) and biological monitoring (BM) in order to evaluate the reliability of passive sampling (PS) in occupational medicine.

Five groups of persons (total number = 188) exposed to tetrachloroethene, isopropanol, toluene, xylene and styrene at the workplace were examined.

AM was performed over several hours using one or two brands of passive samplers (Monitor 3500 and/or ORSA 5). BM includes the determination of the solvent and specific metabolites resp. in blood or urine samples taken at the end of workshift. On the basis of our results we recommend that PS can supply relevant data for the estimation of external exposure to several solvents like chlorinated‐ and aromatic‐hydrocarbons.     

Geochemistry of trace elements in paddy (rice) soils of Sri Lanka – implications for iodine deficiency disorders (IDD)

Iodine Deficiency Disorders (IDD) are a common health problem prevalent in the wet zone of Sri Lanka with a prevalence of >25 of the population. In comparison, in the dry zone of Sri Lanka IDD occurs in <10 of the population. Seventy soil samples from 14 villages selected on the basis of the incidence of goitre, were collected and analysed for 13 trace elements using ICP-MS. In order to identify any prevailing differences in antecedent chemical environments, soil samples from each pre-selected village were classified into three groups in terms of their geographical location. Among the elements investigated, the total soil concentrations of Rb, Sr, Ba, Mn and Co are lower in the wet zone of Kalutara. In contrast, total soil Rb, Sr, Ba and Mn contents are higher in the dry zone of Anuradhapura. Further soil total Mo and Nb levels are relatively similar in all pre-selected study locations. The high endemic goitre regions (IDD >25 of the population) show low levels of Rb, Sr, Ba, and Mn and higher levels of V, Cr, Co, Ni, Cu, Zn and Pb as compared with moderate and non-goitre areas. Factor analysis was used to exploit the correlation structure present in data and yielded three groups in all cases. This indicated that most transition group elements and iodine are associated with the Mn phase in the low IDD areas whereas iodine shows a high affinity for the organic phase in high IDD regions. The variable distribution of trace elements, therefore, must be due to differences in mobility and capacity for incorporation into the structure of secondary minerals or organic phases.     

Biomechanical assessment of soft tissue neck injuries in cases with long sick leave times

A database was established by collecting 919 cases of claimed cervical spine disorders (CSDs) sustained in automotive accidents. All cases had a sick leave time of more than 4 weeks. Data was obtained from a major Swiss accident insurer. An assessment scheme was developed that took into account technical, medical, and biomechanical aspects. All cases were evaluated according to this scheme. The overall biomechanical assessment, that stated the extent to which the symptoms claimed could be explained by the impact, was found to be significantly influenced by the patient's history of CSD in terms of preexisting damage or preexisting symptoms. In 52% of the assessed cases, the CSD claimed could be explained with a combination of neck loading and also by considering the patient's medical history. Performing a solely technical analysis of the collision circumstances or a purely medical evaluation based on a Quebec Task Force (QTF) grade alone are insufficient to assess the accident-related explicability of claimed CSD. Biomechanically relevant individual factors have to be considered.     

Estimating uncertainties in the life cycle assessment of composting household biowaste and urban green waste in Germany

Life cycle assessment (LCA) of waste treatment processes is often associated with considerable uncertainties. The aim of this study is to estimate the total uncertainty in the modelled composting system and the influence of material and process parameters on the uncertainty. Four composting combinations with fresh (FC) and mature substrate compost (MSC) from partially enclosed (PEC) and open composting (OC) were investigated. Perturbation analysis was used to determine the effect of parameters on the result and Monte Carlo simulation was used to estimate the total uncertainty. This study showed that the production of MSC using PEC had the lowest overall impacts across all impact categories except ozone depletion. Results of the Monte Carlo simulation showed that comparing composting options was challenging. The sensitivity ratios obtained from the perturbation analysis showed that the process parameter percentage of carbon fraction degraded was the most influential for FC. In MSC, the moisture content in the input material and the substitution factor used for peat were the most influential. Monte Carlo simulations demonstrated the overall uncertainty of the model and its relevance when comparing results between combinations. The perturbation analysis identified the parameters that required more accurate data to reduce the uncertainty in the model.

Graphical abstract