Early environment influences later performance in fishes

Conditions fish encounter during embryogenesis and early life history can leave lasting effects not only on morphology, but also on growth rate, life‐history and behavioural traits. The ecology of offspring can be affected by conditions experienced by their parents and mother in particular. This review summarizes such early impacts and their ecological influences for a variety of teleost species, but with special reference to salmonids. Growth and adult body size, sex ratio, egg size, lifespan and tendency to migrate can all be affected by early influences. Mechanisms behind such phenotypically plastic impacts are not well known, but epigenetic change appears to be one central mechanism. The thermal regime during development and incubation is particularly important, but also early food consumption and intraspecific density can all be responsible for later life‐history variation. For behavioural traits, early experiences with effects on brain, sensory development and cognition appear essential. This may also influence boldness and other social behaviours such as mate choice. At the end of the review, several issues and questions for future studies are given.     

Accuracy of predicting genomic breeding values for carcass merit traits in Angus and Charolais beef cattle

Accuracy of predicting genomic breeding values for carcass merit traits including hot carcass weight, longissimus muscle area (REA), carcass average backfat thickness (AFAT), lean meat yield (LMY) and carcass marbling score (CMAR) was evaluated based on 543 Angus and 400 Charolais steers genotyped on the Illumina BovineSNP50 Beadchip. For the genomic prediction within Angus, the average accuracy was 0.35 with a range from 0.32 (LMY) to 0.37 (CMAR) across different training/validation data‐splitting strategies and statistical methods. The within‐breed genomic prediction for Charolais yielded an average accuracy of 0.36 with a range from 0.24 (REA) to 0.46 (AFAT). The across‐breed prediction had the lowest accuracy, which was on average near zero. When the data from the two breeds were combined to predict the breeding values of either breed, the prediction accuracy averaged 0.35 for Angus with a range from 0.33 (REA) to 0.39 (CMAR) and averaged 0.33 for Charolais with a range from 0.18 (REA) to 0.46 (AFAT). The prediction accuracy was slightly higher on average when the data were split by animal's birth year than when the data were split by sire family. These results demonstrate that the genetic relationship or relatedness of selection candidates with the training population has a great impact on the accuracy of predicting genomic breeding values under the density of the marker panel used in this study.     

Cub growth and maternal care in cheetahs

Using cub growth as an index, I examine the influence of maternalnutrition, litter size, and cub sex on maternal care in cheetahs(Acinonyx jubatus) and compare cub and litter growth rates withthose of other large feilds. Seventy-nine free-living cheetahcubs in 21 litters from 15 mothers were weighed at least oncebetween 6 and 48 days of age. Eleven litters were weighed atthe beginning and end of a 5-day observation of their mothers.The mean cub growth rate varied significantly between litters,due primarily to differences in maternal food intake. Growthdeclined sharply when maternal food intake was less than 1.5kg/ day, but did not increase with greater levels of food intake.Lower limits of growth rates may therefore have been set bythe mother's food intake, whereas upper limits may be set bythe intrinsic physiological ability of cubs to grow. Althoughmale cubs were heavier than female cubs in the same litter whenfirst weighed, major differences in growth rate between thesexes were not apparent at this stage. Both cheetah cubs andlitters grow fast relative to other large felids, and I arguethat this may be an adaptation to the high rate of cheetah juvenilemortality from predation.     

What is the optimal number of leaves when measuring leaf area of tree species in a forest community?

植物形态性状叶面积简单易测, 能够反映植物对环境的适应与响应, 指示生态系统的功能与过程。在野外测定叶面积时, 叶片取样数量往往采用约定俗成的10-20片, 但到底采集多少叶片才是最优和最具代表性, 却少有探究。该研究以浙江金华山常绿落叶阔叶混交林的优势树种木荷(Schima superba)与枫香树(Liquidambar formosana)为研究对象, 通过对5个胸径等级植株和每个植株6个方位开展大批量叶片取样(>2 500个), 分析两个树种的叶面积变异特征, 探讨叶片取样数量为多少才能最代表该森林类型的叶片大小性状规律。结果表明, 常绿乔木木荷平均叶面积与变幅均小于落叶乔木枫香树。木荷叶面积与胸径无显著相关性, 而枫香树叶面积与胸径有较显著相关性, 但两个树种均在中胸径等级(15-20 cm)差异不显著; 两个树种的叶面积与采样方位无显著相关性, 但在东、西和底部的差异不显著。因此, 综合考虑代表性与野外可操作性, 叶片采集首选中胸径成树的底部叶片。随机抽样统计可知, 树木叶面积测定的最适叶片采集数量因物种而异, 木荷的最适叶片采集数量为40, 而枫香树最少为170片。因此, 在叶面积测定时, 叶片采集的数量应该不能只局限在10-20片, 在人力、物力和时间等条件允许的情况下, 应该尽可能多地测定较多叶片的叶面积。     

Deconstructing occupancy frequency distributions in stream insects: effects of body size and niche characteristics in different geographical regions

1. Occupancy frequency distributions (OFDs) are one means to study species distribution patterns, allowing the delineation of rare and common species. Very few studies have deconstructed entire assemblages by ecological or biological characteristics and subsequently examined OFDs in subgroups of species. 2. The effect of deconstruction of entire assemblages by niche breadth, niche position or body size classes on OFDs in stream insects in three drainage basins was examined. It was hypothesized that OFDs should not vary between different drainage basins, but they should be affected by deconstruction into different niche breadth, niche position or body size classes. 3. The OFDs were typically strongly right‐skewed in all drainage basins. The set of small‐sized species was strongly dominated by rare species, whereas the importance of rare species decreased with increasing body size. Further, while the OFDs of sets of species with marginal niche position or small niche breadth were strongly dominated by rare species, those of species with non‐marginal niche position or large niche breadth showed highly variable degrees of occupancy. The OFDs of non‐marginal species were even uniform in the entire data and one drainage basin, providing partial support to the a priori hypothesis. 4. Niche‐based explanations are likely to account for occupancies of marginal and small‐niched species, whereas the distributions of non‐marginal and broad‐niched species may be not only affected by niche‐based mechanisms but also by spatial dynamics. Deconstruction of OFDs by ecological and biological traits thus showed that the patterns may vary between different subgroups of species.