Evolutionary implications of the human aldolase-A, -B, -C, and -pseudogene chromosome locations.

The aldolase genes represent an ancient gene family with tissue-specific isozymic forms expressed only in vertebrates. The chromosomal locations of the aldolase genes provide insight into their tissue-specific and developmentally regulated expression and evolution. DNA probes for the human aldolase-A and -C genes and for an aldolase pseudogene were used to quantify and map the aldolase loci in the haploid human genome. Genomic hybridization of restriction fragments determined that all the aldolase genes exist in single copy in the haploid human genome. Spot-blot analysis of sorted chromosomes mapped human aldolase A to chromosome 16, aldolase C to chromosome 17, the pseudogene to chromosome 10; it previously had mapped the aldolase-B gene to chromosome 9. All loci are unlinked and located on to two pairs of morphologically similar chromosomes, a situation consistent with tetraploidization during isozymic and vertebrate evolution. Sequence comparisons of expressed and flanking regions support this conclusion. These locations on similar chromosome pairs correctly predicted that the aldolase pseudogene arose when sequences from the aldolase-A gene were inserted into the homologous aldolase location on chromosome 10.     

High-temperature gas chromatography and gas chromatography-mass spectrometry of glycoprotein and glycosphingolipid oligosaccharides

High-temperature gas chromatography and gas chromatography-inass spectrometry for the analyses of oligosaccharides derived from glycoproteins or glycosphingolipids has been developed. Pcrmethylatcd oligosaccharides with up to about 12 sugar residues and masses up to 2500 Daltons can be analyzed. This approach is discussed and exemplified.     

Carryover effects from environmental change in early life: An overlooked driver of the amphibian extinction crisis?

Ecological carryover effects, or delayed effects of the environment on an organism's phenotype, are central predictors of individual fitness and a key issue in conservation biology. Climate change imposes increasingly variable environmental conditions that may be challenging to early life-history stages in animals with complex life histories, leading to detrimental physiological and fitness effects in later life. Yet, the latent nature of carryover effects, combined with the long temporal scales over which they can manifest, means that this phenomenon remains understudied and is often overlooked in short-term studies limited to single life-history stages. Herein, we review evidence for the physiological carryover effects induced by elevated ultraviolet radiation (UVR; 280–400 nm) as a potential contributor to recent amphibian population declines. UVR exposure causes a suite of molecular, cellular and physiological consequences known to underpin carryover effects in other taxa, but there is a lack of research linking embryonic and larval UVR exposures to fitness consequences post-metamorphosis in amphibians. We propose that the key impacts of UVR on disease-related amphibian declines are facilitated through carryover effects that bridge embryonic and larval UVR exposure with potential increased disease susceptibility post-metamorphosis. We conclude by identifying a practical direction for the study of ecological carryover effects in amphibians that could guide future ecological research in the broader field of conservation physiology. Only by addressing carryover effects can many of the mechanistic links between environmental change and population declines be elucidated.     

Directional Migration of Recirculating Lymphocytes through Lymph Nodes via Random Walks

Naive T lymphocytes exhibit extensive antigen-independent recirculation between blood and lymph nodes, where they may encounter dendritic cells carrying cognate antigen. We examine how long different T cells may spend in an individual lymph node by examining data from long term cannulation of blood and efferent lymphatics of a single lymph node in the sheep. We determine empirically the distribution of transit times of migrating T cells by applying the Least Absolute Shrinkage & Selection Operator () or regularised to fit experimental data describing the proportion of labelled infused cells in blood and efferent lymphatics over time. The optimal inferred solution reveals a distribution with high variance and strong skew. The mode transit time is typically between 10 and 20 hours, but a significant number of cells spend more than 70 hours before exiting. We complement the empirical machine learning based approach by modelling lymphocyte passage through the lymph node . On the basis of previous two photon analysis of lymphocyte movement, we optimised distributions which describe the transit times (first passage times) of discrete one dimensional and continuous (Brownian) three dimensional random walks with drift. The optimal fit is obtained when drift is small, i.e. the ratio of probabilities of migrating forward and backward within the node is close to one. These distributions are qualitatively similar to the inferred empirical distribution, with high variance and strong skew. In contrast, an optimised normal distribution of transit times (symmetrical around mean) fitted the data poorly. The results demonstrate that the rapid recirculation of lymphocytes observed at a macro level is compatible with predominantly randomised movement within lymph nodes, and significant probabilities of long transit times. We discuss how this pattern of migration may contribute to facilitating interactions between low frequency T cells and antigen presenting cells carrying cognate antigen.     

Brain size affects responsiveness in mating behaviour to variation in predation pressure and sex ratio

Despite ongoing advances in sexual selection theory, the evolution of mating decisions remains enigmatic. Cognitive processes often require simultaneous processing of multiple sources of information from environmental and social cues. However, little experimental data exist on how cognitive ability affects such fitness‐associated aspects of behaviour. Using advanced tracking techniques, we studied mating behaviours of guppies artificially selected for divergence in relative brain size, with known differences in cognitive ability, when predation threat and sex ratio was varied. In females, we found a general increase in copulation behaviour in when the sex ratio was female biased, but only large‐brained females responded with greater willingness to copulate under a low predation threat. In males, we found that small‐brained individuals courted more intensively and displayed more aggressive behaviours than large‐brained individuals. However, there were no differences in female response to males with different brain size. These results provide further evidence of a role for female brain size in optimal decision‐making in a mating context. In addition, our results indicate that brain size may affect mating display skill in male guppies. We suggest that it is important to consider the association between brain size, cognitive ability and sexual behaviour when studying how morphological and behavioural traits evolve in wild populations.     

Climate change and the optimal flowering time of annual plants in seasonal environments

Long‐term phenology monitoring has documented numerous examples of changing flowering dates during the last century. A pivotal question is whether these phenological responses are adaptive or not under directionally changing climatic conditions. We use a classic dynamic growth model for annual plants, based on optimal control theory, to find the fitness‐maximizing flowering time, defined as the switching time from vegetative to reproductive growth. In a typical scenario of global warming, with advanced growing season and increased productivity, optimal flowering time advances less than the start of the growing season. Interestingly, increased temporal spread in production over the season may either advance or delay the optimal flowering time depending on overall productivity or season length. We identify situations where large phenological changes are necessary for flowering time to remain optimal. Such changes also indicate changed selection pressures. In other situations, the model predicts advanced phenology on a calendar scale, but no selection for early flowering in relation to the start of the season. We also show that the optimum is more sensitive to increased productivity when productivity is low than when productivity is high. All our results are derived using a general, graphical method to calculate the optimal flowering time applicable for a large range of shapes of the seasonal production curve. The model can thus explain apparent maladaptation in phenological responses in a multitude of scenarios of climate change. We conclude that taking energy allocation trade‐offs and appropriate time scales into account is critical when interpreting phenological patterns.     

Mischaracterising density dependence biases estimated effects of coloured covariates on population dynamics

Environmental effects on population growth are often quantified by coupling environmental covariates with population time series, using statistical models that make particular assumptions about the shape of density dependence. We hypothesized that faulty assumptions about the shape of density dependence can bias estimated effect sizes of temporally autocorrelated covariates. We investigated the presence of bias using Monte Carlo simulations based on three common per capita growth functions with distinct density dependent forms (θ-Ricker, Ricker and Gompertz), autocorrelated (coloured) ‘known’ environmental covariates and uncorrelated (white) ‘unknown’ noise. Faulty assumptions about the shape of density dependence, combined with overcompensatory intrinsic population dynamics, can lead to strongly biased estimated effects of coloured covariates, associated with lower confidence interval coverage. Effects of negatively autocorrelated (blue) environmental covariates are overestimated, while those of positively autocorrelated (red) covariates can be underestimated, generally to a lesser extent. Prewhitening the focal environmental covariate effectively reduces the bias, at the expense of the estimate precision. Fitting models with flexible shapes of density dependence can also reduce bias, but increases model complexity and potentially introduces other problems of parameter identifiability. Model selection is a good option if an appropriate model is included in the set of candidate models. Under the specific and identifiable circumstances with high risk of bias, we recommend prewhitening or careful modelling of the shape of density dependence.     

Thermophilic (55°C) and moderately hyperthermophilic (65°C) fermentation of poultry manure triggers release of high heavy metal concentrations leading to enhanced genotoxicity

Proper disposal of waste from poultry industries may be done by thermophilic anaerobic digestion. Particularly, thermophilic fermentation exhibits pivotal advantages. However, not only the accrued waste material (digestate) serves as organic fertilizer but also poses environmental problems when the pollutant release is poorly synchronized with the environmental demand. To minimize environmental risks, additional hyperthermophilic (moderately hyperthermophilic) treatment of animal by‐products is necessary, but concurrent release of pollutants is notably increased. To estimate the quantity and quality of pollutants released, we analyzed various organic compounds as well as 21 metals and tested their genotoxic/mutagenic potential by using the Allium cepa assay and the Ames test. As, Cd, Ni, and W were not detected or had low concentration (0.01–0.47 mg/kg) and were considered of little relevance. Co, Cr, Ni, Pb, and Mo were detected at concentrations up to 5.76 mg/kg. Fe, Mn, Zn, and Cu had the highest concentrations and were accumulated to inhibitory levels. Phenolic compounds were detected in negligible concentrations. We found that approximately 30% of onion root chromosomes were permanently damaged by high heavy metal concentrations released from the digestates. Higher temperatures and longer fermentation times fostered an increased release of pollutants above permissible limits.     

Brain size predicts behavioural plasticity in guppies (Poecilia reticulata): An experiment

Understanding how animal personality (consistent between‐individual behavioural differences) arises has become a central topic in behavioural sciences. This endeavour is complicated by the fact that not only the mean behaviour of individuals (behavioural type) but also the strength of their reaction to environmental change (behavioural plasticity) varies consistently. Personality and cognitive abilities are linked, and we suggest that behavioural plasticity could also be explained by differences in brain size (a proxy for cognitive abilities), since accurate decisions are likely essential to make behavioural plasticity beneficial. We test this idea in guppies (Poecilia reticulata), artificially selected for large and small brain size, which show clear cognitive differences between selection lines. To test whether those lines differed in behavioural plasticity, we reared them in groups in structurally enriched environments and then placed adults individually into empty tanks, where we presented them daily with visual predator cues and monitored their behaviour for 20 days with video‐aided motion tracking. We found that individuals differed consistently in activity and risk‐taking, as well as in behavioural plasticity. In activity, only the large‐brained lines demonstrated habituation (increased activity) to the new environment, whereas in risk‐taking, we found sensitization (decreased risk‐taking) in both brain size lines. We conclude that brain size, potentially via increasing cognitive abilities, may increase behavioural plasticity, which in turn can improve habituation to novel environments. However, the effects seem to be behaviour‐specific. Our results suggest that brain size likely explains some of the variation in behavioural plasticity found at the intraspecific level.