The performance of state-of-the-art modelling techniques depends on geographical distribution of species

We explored the effects of prevalence, latitudinal range and clumping (spatial autocorrelation) of species distribution patterns on the predictive accuracy of eight state-of-the-art modelling techniques: Generalized Linear Models (GLMs), Generalized Boosting Method (GBM), Generalized Additive Models (GAMs), Classification Tree Analysis (CTA), Artificial Neural Network (ANN), Multivariate Adaptive Regression Splines (MARS), Mixture Discriminant Analysis (MDA) and Random Forest (RF). One hundred species of Lepidoptera, selected from the Distribution Atlas of European Butterflies, and three climate variables were used to determine the bioclimatic envelope for each butterfly species. The data set consisting of 2620 grid squares 30′ × 60′ in size all over Europe was randomly split into the calibration and the evaluation data sets. The performance of different models was assessed using the area under the curve (AUC) of a receiver operating characteristic (ROC) plot. Observed differences in modelling accuracy among species were then related to the geographical attributes of the species using GAM. The modelling performance was negatively related to the latitudinal range and prevalence, whereas the effect of spatial autocorrelation on prediction accuracy depended on the modelling technique. These three geographical attributes accounted for 19–61% of the variation in the modelling accuracy. Predictive accuracy of GAM, GLM and MDA was highly influenced by the three geographical attributes, whereas RF, ANN and GBM were moderately, and MARS and CTA only slightly affected. The contrasting effects of geographical distribution of species on predictive performance of different modelling techniques represent one source of uncertainty in species spatial distribution models. This should be taken into account in biogeographical modelling studies and assessments of climate change impacts.     

The first fossil fungus gardens of Isoptera: oldest evidence of symbiotic termite fungiculture (Miocene, Chad basin)

Higher termites of the subfamily Macrotermitinae (fungus-growing termites) are known to build fungus gardens where a symbiotic fungus (Termitomyces sp.) is cultivated. The fungus grows on a substrate called fungus comb, a structure built with the termites’ own faeces. Here we present the first fossil fungus combs ever found in the world. They were extracted from 7-million-year-old continental sandstone (Chad basin). Fossilized fungus combs have an ovoid morphology with a more or less flattened concave base and a characteristic general alveolar aspect. Under lens, they display a typical millimetre-scale pelletal structure. The latter, as well as the general shape and alveolar aspect, are similar to the morphology of fungus combs from extant fungus-growing termites.     

Prenatal diagnosis of extrahepatic biliary duct atresia

A rare case of extrahepatic biliary atresia was diagnosed by a combination of prenatal ultrasound and measurements of fetal digestive enzymes in amniotic fluid. Ultrasound at 15 and 18 weeks' gestation failed to detect the gall bladder, and amniotic fluid digestive enzyme values were below the fifth percentile. The patient decided to terminate the pregnancy. Post-abortal pathological examination confirmed the diagnosis. Copyright © 2002 John Wiley & Sons, Ltd.     

Models relating individual and population response to contaminants

Even when present at sub‐lethal levels, toxic compounds have an effect on the dynamics of a population, expressed through altered growth and reproduction rates. We explore some of the potential effects of toxicants on populations, using a simple model that considers a generic toxicant and populations of two species, a primary producer, and a consumer living under food‐limited conditions. The toxicant is assumed to affect the consumers only, and it may enter them either directly from the environment or via their food, the latter opening the possibility of biomagnification. The initial response of the consumer to introduction of a toxicant is invariably a decline in its fecundity and density. However, in the longer term, the equilibrium densities of both producer and consumer may increase or decrease, depending on parameter values and ambient toxicant levels. The surprising case of an increased equilibrium in response to the toxicant occurs if, in the absence of toxicant, the consumers held the producers at a very low level, analogous to ‘overfishing’ in fishery studies. If the toxicant enters the consumer via food, multiple, non‐trivial equilibria are possible. The complex, but interpretable, dynamics exhibited by these simple models will be used to guide studies with more realistic models, for whose development this study forms a prelude.     

A framework for testing meso‐mediational relationships in Organizational Behavior

We advance a framework for testing mediational relationships that traverse levels of analysis. We differentiate mediation that functions within levels, as well as different forms of meso‐mediation that operate downward across levels of analysis. We discuss the preconditions and evidential basis for these meso‐mediational type relationships. We then provide an empirical example that illustrates the different types of mediation and conclude with recommendations and extensions for studying more complex meso‐mediational organizational phenomena. Copyright © 2007 John Wiley & Sons, Ltd.     

How floral odours are learned inside the bumblebee (Bombus terrestris) nest

Recruitment in social insects often involves not only inducing nestmates to leave the nest, but also communicating crucial information about finding profitable food sources. Although bumblebees transmit chemosensory information (floral scent), the transmission mechanism is unknown as mouth-to-mouth fluid transfer (as in honeybees) does not occur. Because recruiting bumblebees release a pheromone in the nest that triggers foraging in previously inactive workers, we tested whether this pheromone helps workers learn currently rewarding floral odours, as found in food social learning in rats. We exposed colonies to artificial recruitment pheromone, paired with anise scent. The pheromone did not facilitate learning of floral scent. However, we found that releasing floral scent in the air of the colony was sufficient to trigger learning and that learning performance was improved when the chemosensory cue was provided in the nectar in honeypots; probably because it guarantees a tighter link between scent and reward, and possibly because gustatory cues are involved in addition to olfaction. Scent learning was maximal when anise-scented nectar was brought into the nest by demonstrator foragers, suggesting that previously unidentified cues provided by successful foragers play an important role in nestmates learning new floral odours.     

A dynamic simulation model to support reduction in illegal trade within legal wildlife markets

Sustainable wildlife trade is critical for biodiversity conservation, livelihoods, and food security. Regulatory frameworks are needed to secure these diverse benefits of sustainable wildlife trade. However, regulations limiting trade can backfire, sparking illegal trade if demand is not met by legal trade alone. Assessing how regulations affect wildlife market participants’ incentives is key to controlling illegal trade. Although much research has assessed how incentives at both the harvester and consumer ends of markets are affected by regulations, little has been done to understand the incentives of traders (i.e., intermediaries). We built a dynamic simulation model to support reduction in illegal wildlife trade within legal markets by focusing on incentives traders face to trade legal or illegal products. We used an Approximate Bayesian Computation approach to infer illegal trading dynamics and parameters that might be unknown (e.g., price of illegal products). We showcased the utility of the approach with a small-scale fishery case study in Chile, where we disentangled within-year dynamics of legal and illegal trading and found that the majority (∼77%) of traded fish is illegal. We utilized the model to assess the effect of policy interventions to improve the fishery's sustainability and explore the trade-offs between ecological, economic, and social goals. Scenario simulations showed that even significant increases (over 200%) in parameters proxying for policy interventions enabled only moderate improvements in ecological and social sustainability of the fishery at substantial economic cost. These results expose how unbalanced trader incentives are toward trading illegal over legal products in this fishery. Our model provides a novel tool for promoting sustainable wildlife trade in data-limited settings, which explicitly considers traders as critical players in wildlife markets. Sustainable wildlife trade requires incentivizing legal over illegal wildlife trade and consideration of the social, ecological, and economic impacts of interventions.     

Effects of Exposure Conditions on Antioxidant Depletion,Tensile Strength,and Creep Modulus of Corrugated HDPE Pipes Made With or Without Recycled Resins

Journal of Polymers and the Environment - The service lifetime of corrugated high-density polyethylene (HDPE) pipes used in transportation infrastructure applications has been the subject of...     

Metal particle seeding on urban surface samples

Environmental Science and Pollution Research - In order to estimate the resuspension of the particles empirically, it is necessary to carry out a homogeneous distribution of the particles on the...