Breakup and re-formation of colony in the first-instar larvae of the winter cherry bug,Acanthocoris sordidus thunberg (Hemiptera: Coreidae), in relation to the defence against their enemies

The winter cherry bug, Acanthocoris sordidusThunberg , lives in aggregation especially in their early larval instars. Using the 1st-instar larvae of this species, the author tried to clarify both the processes and the mechanisms of the breakup and later re-formation of colony in relation to the defence against their enemies. The results obtained were summarized as follows.

1. In the field population, there is a high possibility of dispersal of the 1st-instar larvae from a colony possibly through the disturbance by some predators but they can re-form a colony with each other or join, with colonies of different instar larvae.
2. The individuals in a colony immediately disperse through the attack of predatory coccinellid beetle, Harmonica axyridis but tend to re-form a colony in a short time.
3. The breakup of colony is caused by the secretion from the attacked individual.
4. The formation of colony is attributed to the habit closely related with the senses of smell and/or contact.

From these results, it was concluded that the dispersal of 1st-instar larvae from a colony, followed by the re-formation of a colony, is an an adaptive behaviour to escape from the attack by their predators.     

On the Estimation of the Population Mean with Known Coefficient of Variation

For the estimation of population mean a class of estimators has been proposed when the coefficient of variation is known and its efficiency is compared with the usual unbiased estimator and the estimators suggested by various researchers. The properties of the proposed class of estimators have been also discussed in the case of normal population.     

Turnover and trends in butterfly communities on two British tidal islands: stochastic influences and deterministic factors

Aim Community trends were investigated for two small islands and two local mainland butterfly communities within the UK over a period of 20–30 years. Location Hilbre Island off the Wirral Peninsula at 53.33° N, 3.10° W; Lindisfarne, an island off the Northumberland coast at 56.41° N, 1.48° W; Leighton Moss at 54.08° N, 2.26° W; Wyre Forest at 52.23° N, 2.14° W, UK. Methods Butterfly species data were collected on Hilbre and two mainland sites (Leighton Moss and Wyre Forest) from 1983 to 2006, and on Lindisfarne from 1977 to 2006, as part of the National Habitat Survey, the UK Butterfly Monitoring Scheme and ‘Butterflies for the New Millennium Atlas’ recording. Matrices of associations (Sokal and Michener’s matching coefficient S_SM; resemblance coefficient) were computed between years and subject to non‐metric multidimensional scaling (NMDS) and Mantel tests. The pattern of extinctions and colonizations at sites were examined, their heterogeneity tested by applying a Friedman test to fractional incidences for the same years. Regression analysis (multiple regression and logit regression) was used to relate butterfly numbers and incidences to climate variables, time and previous records. Results Significant community trends based on population counts and species’ incidences were found for all four sites. There was a significant climatic signal for Hilbre; although this was not apparent for the remaining sites, significant associations occurred between records for a number of species and climatic variables at all sites. Substantial turnover of species on the islands was inversely related to numbers of records for species but not to their conspicuousness to recorders. Main conclusions We argue that time trends are widespread in butterfly communities, even for relatively short periods; they are largely generated by stochastic influences rather than by more substantive factors such as climate change. Potential biases in surveying and recording history are shown to be unlikely. A clear climate signal was found only for the small Hilbre Island, for which there was also evidence for the significant influence of colonization capability of individual source species. We conclude that for many species, small islands will be sinks or pseudosinks and their ‘populations’ vulnerable to small changes in source–sink dynamics.     

Historical and philosophical perspectives on the study of developmental bias

Throughout the recent history of research at the intersection of evolution and development, notions such as developmental constraint, evolutionary novelty, and evolvability have been prominent, but the term “developmental bias” has scarcely been used. And one may even doubt whether a unique and principled definition of bias is possible. I argue that the concept of developmental bias can still play a vital scientific role by means of setting an explanatory agenda that motivates investigation and guides the formulation of integrative explanatory frameworks. Less crucial is a definition that would classify patterns of phenotypic variation and unify variational patterns involving different traits and taxa as all being “bias.” Instead, what we should want is a concept that generates intellectual identity across various researchers, and that unites the diverse fields and approaches relevant to the study of developmental bias, from paleontology to behavioral biology. I point to some advantages of conducting research specifically under the label of “developmental bias,” compared with employing other, more common terms such as “evolvability.”     

A comparison of diversity estimators applied to a database of host–parasite associations

Understanding the drivers of biodiversity is important for forecasting changes in the distribution of life on earth. However, most studies of biodiversity are limited by uneven sampling effort, with some regions or taxa better sampled than others. Numerous methods have been developed to account for differences in sampling effort, but most methods were developed for systematic surveys in which all study units are sampled using the same design and assemblages are sampled randomly. Databases compiled from multiple sources, such as from the literature, often violate these assumptions because they are composed of studies that vary widely in their goals and methods. Here, we compared the performance of several popular methods for estimating parasite diversity based on a large and widely used parasite database, the Global Mammal Parasite Database (GMPD). We created artificial datasets of host–parasite interactions based on the structure of the GMPD, then used these datasets to evaluate which methods best control for differential sampling effort. We evaluated the precision and bias of seven methods, including species accumulation and nonparametric diversity estimators, compared to analyzing the raw data without controlling for sampling variation. We find that nonparametric estimators, and particularly the Chao2 and second-order jackknife estimators, perform better than other methods. However, these estimators still perform poorly relative to systematic sampling, and effect sizes should be interpreted with caution because they tend to be lower than actual effect sizes. Overall, these estimators are more effective in comparative studies than for producing true estimates of diversity. We make recommendations for future sampling strategies and statistical methods that would improve estimates of global parasite diversity.     

Meta‐replication,sampling bias,and multi‐scale model selection: A case study on snow leopard (Panthera uncia) in western China

Replicated multiple scale species distribution models (SDMs) have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi‐scale habitat relationships of the snow leopard (Panthera uncia) in two study areas on the Qinghai–Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape‐specific. We coupled univariate scale optimization and the maximum entropy algorithm to produce multivariate SDMs, inferring the relative suitability for the species by ensembling top performing models. We optimized the SDMs based on average omission rate across the top models and ensembles’ overlap with a simulated reference model. Comparison of SDMs in the two study areas highlighted landscape‐specific responses to limiting factors. These were dependent on the effects of the hydrological network, anthropogenic features, topographic complexity, and the heterogeneity of the landcover patch mosaic. Overall, even accounting for specific local differences, we found general landscape attributes associated with snow leopard ecological requirements, consisting of a positive association with uplands and ridges, aggregated low‐contrast landscapes, and large extents of grassy and herbaceous vegetation. As a means to evaluate the performance of two bias correction methods, we explored their effects on three datasets showing a range of bias intensities. The performance of corrections depends on the bias intensity; however, density kernels offered a reliable correction strategy under all circumstances. This study reveals the multi‐scale response of snow leopards to environmental attributes and confirms the role of meta‐replicated study designs for the identification of spatially varying limiting factors. Furthermore, this study makes important contributions to the ongoing discussion about the best approaches for sampling bias correction.     

Analysis of mitochondrial protein‐coding genes of Antheraea assamensis: Muga silkworm of Assam

To understand the synonymous codon usage pattern in mitochondrial genome of Antheraea assamensis, we analyzed the 13 mitochondrial protein‐coding genes of this species using a bioinformatic approach as no work was reported yet. The nucleotide composition analysis suggested that the percentages of A, T, G,and C were 33.73, 46.39, 9.7 and 10.17, respectively and the overall GC content was 19.86, that is, lower than 50% and the genes were AT rich. The mean effective number of codons of mitochondrial protein‐coding genes was 36.30 and it indicated low codon usage bias (CUB). Relative synonymous codon usage analysis suggested overrepresented and underrepresented codons in each gene and the pattern of codon usage was different among genes. Neutrality plot analysis revealed a narrow range of distribution for GC content at the third codon position and some points were diagonally distributed, suggesting both mutation pressure and natural selection influenced the CUB.