A new species of Stenobiella Tillyard (Neuroptera, Berothidae) from Australia

Stenobiella variola sp. n., a new species of beaded lacewing (Neuroptera: Berothidae), is described and figured from south-eastern Australia. A preliminary key to Stenobiella species is presented

Accurate Optimization of Weighted Nuclear Norm for Non-Rigid Structure from Motion

Fitting a matrix of a given rank to data in a least squares sense can be done very effectively using 2nd order methods such as Levenberg-Marquardt by explicitly optimizing over a bilinear parameterization of the matrix. In contrast, when applying more general singular value penalties, such as weighted nuclear norm priors, direct optimization over the elements of the matrix is typically used. Due to non-differentiability of the resulting objective function, first order sub-gradient or splitting methods are predominantly used. While these offer rapid iterations it is well known that they become inefficent near the minimum due to zig-zagging and in practice one is therefore often forced to settle for an approximate solution. In this paper we show that more accurate results can in many cases be achieved with 2nd order methods. Our main result shows how to construct bilinear formulations, for a general class of regularizers including weighted nuclear norm penalties, that are provably equivalent to the original problems. With these formulations the regularizing function becomes twice differentiable and 2nd order methods can be applied. We show experimentally, on a number of structure from motion problems, that our approach outperforms state-of-the-art methods

Arbuscular mycorrhizal fungal community composition is altered by long-term litter removal but not litter addition in a lowland tropical forest

Tropical forest productivity is sustained by the cycling of nutrients through decomposing organic matter. Arbuscular mycorrhizal (AM) fungi play a key role in the nutrition of tropical trees, yet there has been little experimental investigation into the role of AM fungi in nutrient cycling via decomposing organic material in tropical forests. We evaluated the responses of AM fungi in a long-term leaf litter addition and removal experiment in a tropical forest in Panama. We described AM fungal communities using 454-pyrosequencing, quantified the proportion of root length colonised by AM fungi using microscopy, and estimated AM fungal biomass using a lipid biomarker. AM fungal community composition was altered by litter removal but not litter addition. Root colonisation was substantially greater in the superficial organic layer compared with the mineral soil. Overall colonisation was lower in the litter removal treatment, which lacked an organic layer. There was no effect of litter manipulation on the concentration of the AM fungal lipid biomarker in the mineral soil. We hypothesise that reductions in organic matter brought about by litter removal may lead to AM fungi obtaining nutrients from recalcitrant organic or mineral sources in the soil, besides increasing fungal competition for progressively limited resources.Smithsonian Tropical Research Institute; Cambridge Home and European Scholarship; Department of Plant Sciences, Cambridge; Cambridge Philosophical Society; European Research Council; European Union's Seventh Framework Programme. Grant Number: FP/2007-201

Arbuscular mycorrhizal fungal community composition is altered by long-term litter removal but not litter addition in a lowland tropical forest

Tropical forest productivity is sustained by the cycling of nutrients through decomposing organic matter. Arbuscular mycorrhizal (AM) fungi play a key role in the nutrition of tropical trees, yet there has been little experimental investigation into the role of AM fungi in nutrient cycling via decomposing organic material in tropical forests. We evaluated the responses of AM fungi in a long-term leaf litter addition and removal experiment in a tropical forest in Panama. We described AM fungal communities using 454-pyrosequencing, quantified the proportion of root length colonised by AM fungi using microscopy, and estimated AM fungal biomass using a lipid biomarker. AM fungal community composition was altered by litter removal but not litter addition. Root colonisation was substantially greater in the superficial organic layer compared with the mineral soil. Overall colonisation was lower in the litter removal treatment, which lacked an organic layer. There was no effect of litter manipulation on the concentration of the AM fungal lipid biomarker in the mineral soil. We hypothesise that reductions in organic matter brought about by litter removal may lead to AM fungi obtaining nutrients from recalcitrant organic or mineral sources in the soil, besides increasing fungal competition for progressively limited resources.Smithsonian Tropical Research Institute; Cambridge Home and European Scholarship; Department of Plant Sciences, Cambridge; Cambridge Philosophical Society; European Research Council; European Union's Seventh Framework Programme. Grant Number: FP/2007-201

Truth tracking performance of social networks: how connectivity and clustering can make groups less competent

Our beliefs and opinions are shaped by others, making our social networks crucial in determining what we believe to be true. Sometimes this is for the good because our peers help us form a more accurate opinion. Sometimes it is for the worse because we are led astray. In this context, we address via agent-based computer simulations the extent to which patterns of connectivity within our social networks affect the likelihood that initially undecided agents in a network converge on a true opinion following group deliberation. The model incorporates a fine-grained and realistic representation of belief (opinion) and trust, and it allows agents to consult outside information sources. We study a wide range of network structures and provide a detailed statistical analysis concerning the exact contribution of various network metrics to collective competence. Our results highlight and explain the collective risks involved in an overly networked or partitioned society. Specifically, we find that 96% of the variation in collective competence across networks can be attributed to differences in amount of connectivity (average degree) and clustering, which are negatively correlated with collective competence. A study of bandwagon or “group think” effects indicates that both connectivity and clustering increase the probability that the network, wholly or partly, locks into a false opinion. Our work is interestingly related to Gerhard Schurz’s work on meta-induction and can be seen as broadly addressing a practical limitation of his approach