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In most studies dealing with effects of toxic substances in saprotrophic isopods, animals are exposed to the test substance through contaminated food. Because these animals can be in a close contact with the soil surface, the substrate, as an exposure pathway, should not be neglected. Here the authors analyze the toxicokinetic behavior of lindane (␥-hexachlorocyclohexane [␥-HCH]) in the isopod species Porcellionides pruinosus, comparing two exposure routes: food and two soil types (artificial Organisation for Economic Cooperation and Development [OECD] soil and a natural agricultural soil). In the feeding experiment, a strong decrease of ␥-HCH concentration over time was observed on the food material, with the animals showing a broader range in chemical assimilation efficiency values (averaging 17.7% and ranging from 10 to 40%). The ␥-HCH bioaccumulation results indicate that when animals incubated under both soil types reached a steady state, they displayed much higher body burdens (1,359.60 pg/ animal on OECD soil and 1,085.30 pg/animal on natural soil) than those exposed to contaminated food (43.75 pg/animal). Kinetic models also revealed much lower assimilation and elimination rates in the food experiment (20.66 pg/d and 0.10 pg/d) than in both soil experiments (238.60 pg/d and 350.54 pg/d for the assimilation rate and 0.19 pg/d and 0.32 pg/d for the elimination rate). Differences in results between exposure routes are discussed according to equilibrium-partitioning theory and the enhanced relevance of the substrate exposure route is analyzed under future prospects on chemical toxicity testing using isopods.

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Projected climate change and rainfall variability will affect soil microbial communities, biogeochemical cycling and agriculture. Nitrogen (N) is the most limiting nutrient in agroecosystems and its cycling and availability is highly dependent on microbial driven processes. In agroecosystems, hydrolysis of organic nitrogen (N) is an important step in controlling soil N availability. We analyzed the effect of management (ecological intensive vs. conventional intensive) on N-cycling processes and involved microbial communities under climate change-induced rain regimes. Terrestrial model ecosystems originating from agroecosystems across Europe were subjected to four different rain regimes for 263 days. Using structural equation modelling we identified direct impacts of rain regimes on N-cycling processes, whereas N-related microbial communities were more resistant. In addition to rain regimes, management indirectly affected N-cycling processes via modifications of N-related microbial community composition. Ecological intensive management promoted a beneficial N-related microbial community composition involved in N-cycling processes under climate change-induced rain regimes. Exploratory analyses identified phosphorus-associated litter properties as possible drivers for the observed management effects on N-related microbial community composition. This work provides novel insights into mechanisms controlling agro-ecosystem functioning under climate change. As in many terrestrial ecosystems, nitrogen (N) is the most limiting nutrient for plant growth in agroecosystems 1-3. The last century has been characterized by a considerable increase of N inputs in agricultural soils 4-7 , mostly in mineral form (NH 4 +), making plant growth less dependent on microbial N provisioning. However, the increased amount of reactive N in the environment has severe environmental and human health consequences 7 .

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A B S T R A C TAssessing and comparing the pest killing capacity of predators is a crucial but laborious task during the implementation of sustainable farming systems. Critical attributes of assessment include quantifying predator's attack rate (a) and handling time (T h ). The maximum attack rate (T/T h ) (i.e. the maximum number of prey that can be attacked by a predator during the time interval (T) considered) could be a more precise and interpretable indicator of the potential suppression of pests exerted by a predator; however, its calculation only provides a point estimator usually derived from incomplete datasets (e.g. unbalanced or low replicated experimental designs) that could lead to draw wrong conclusions. We introduce simaR (simulation of maximum attack rates using R), an R library that generates 95% confidence intervals around estimates of the maximum attack rate that can be easily and intuitively used to compare across species. We validated the simulation method and used the empirical results of a controlled laboratory experiment to compare the maximum attack rates of spiders across a range of Medfly prey densities and illustrate how to use simaR with non-replicated partial data. Applying our method we found a significant effect of temperature on the maximum attack rate of two different guilds of spiders, the orb-weaver A. cucurbitina and the ambusher S. globosum that was not relevant regarding their attack rate and handling time. Our method compares different predator species and/or experimental conditions in a simple and reproducible procedure through an accurate, easy-to-use, fast and statistically robust analysis, based on simulation and bootstrapping, that can be used to assess the pest suppression potential of predators by simulating their functional responses from low-effort laboratory trials.