Why are estimates of the terrestrial carbon balance so different?

The carbon balance of the world's terrestrial ecosystems is uncertain. Both top‐down (atmospheric) and bottom‐up (forest inventory and land‐use change) approaches have been used to calculate the sign and magnitude of a net terrestrial flux. Different methods often include different processes, however, and comparisons can be misleading. Differences are not necessarily the result of uncertainties or errors, but often result from incomplete accounting inherent in some of the methods. Recent estimates are reviewed here. Overall, a northern mid‐latitude carbon sink of approximately 2 Pg C yr^?1 appears robust, although the mechanisms responsible are uncertain. Several lines of evidence point to environmentally enhanced rates of carbon accumulation. Other lines suggest that recovery from past disturbances is largely responsible for the sink. The tropics appear to be a small net source of carbon or nearly neutral, and the same uncertainties of mechanism exist. In addition, studies in the tropics do not permit an unequivocal choice between two alternatives: large emissions of carbon from deforestation offset by large sinks in undisturbed forests, or moderate emissions from land‐use change with essentially no change in the carbon balance in undisturbed forests. Resolution of these uncertainties is most likely to result from spatially detailed historical reconstructions of land‐use change and disturbance in selected northern mid‐latitude regions where such data are available, and from systematic monitoring of changes in the area of tropical forests with satellite data of high spatial resolution collected over the last decades and into the future.     

Why are individuals so different from each other?

An important contributor to the differences between individuals derives from their plasticity. Such plasticity is widespread in organisms from the simple to the most complex. Adaptability plasticity enables the organism to cope with a novel challenge not previously encountered by its ancestors. Conditional plasticity appears to have evolved from repeated challenges from the environment so that the organism responds in a particular manner to the environment in which it finds itself. The resulting phenotypic variation can be triggered during development in a variety of ways, some mediated through the parent''s phenotype. Sometimes the organism copes in suboptimal conditions trading off reproductive success against survival. Whatever the adaptedness of the phenotype, each of the many types of plasticity demonstrates how a given genotype will express itself differently in different environmental conditions—a field of biology referred to as the study of epigenetics. The ways in which epigenetic mechanisms may have evolved are discussed, as are the potential impacts on the evolution of their descendants.     

Why are human newborns so big and fat?

Human newborns and infants have morphological and physiological traits protecting them against hypothermia. These traits are unusual for primates, with some of them rarely seen in other mammals evolving in an African environment. We can include the following: 1.) A non-allometric, bigger size of the newborn, resulting in the decrease of surface to body mass ratio (S/W). 2.) Greater amount of subcutaneous fat tissue (SFT) increasing insulation. 3.) Greater amount of brown fat tissue increasing nonshivering thermogenesis. 4.) Active thermoregulation when sleeping. 5.) Thermal balance moved in the direction of heat conservation in a few months' old babies. I here present a hypothesis that it was the risk of nocturnal hypothermia in open habitats of late Pliocene that was the selective pressure promoting evolutionary emergence of these traits inHomo erectus. The inverse radiation at night in open habitats causes strong gradient of temperatures. In effect the temperatures near the ground (even in the tropics) can be low enough to endanger newborns and infants with hypothermia. If earlyHomo was naked, slept on the ground and if mortality of their babies caused by hypothermia was high, then selection pressures could have promoted those traits protecting infants against the risk of hypothermia. Since the most important traits (1. & 2.) in respect of heat conservation, depend on mother size, it is postulated that they appeared when female body size increased dramatically i.e. duringHomo erectus stage of human phylogeny.     

Why do imagery and perception look and feel so different?

Despite the past few decades of research providing convincing evidence of the similarities in function and neural mechanisms between imagery and perception, for most of us, the experience of the two are undeniably different, why? Here, we review and discuss the differences between imagery and perception and the possible underlying causes of these differences, from function to neural mechanisms. Specifically, we discuss the directional flow of information (top-down versus bottom-up), the differences in targeted cortical layers in primary visual cortex and possible different neural mechanisms of modulation versus excitation. For the first time in history, neuroscience is beginning to shed light on this long-held mystery of why imagery and perception look and feel so different.This article is part of the theme issue ‘Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation''.     

Why are so many trees hollow?

In many living trees, much of the interior of the trunk can be rotten or even hollowed out. Previously, this has been suggested to be adaptive, with microbial or animal consumption of interior wood producing a rain of nutrients to the soil beneath the tree that allows recycling of those nutrients into new growth via the trees roots. Here I propose an alternative (non-exclusive) explanation: such loss of wood comes at very little cost to the tree and so investment in costly chemical defence of this wood is not economic. I discuss how this theory can be tested empirically.     

Why are mammalian tendons so thick?

The maximum stresses to which a wide range of mammalian limb tendons could be subjected in life were estimated by considering the relative cross-sectional areas of each tendon and of the fibres of its muscle. These cross-sectional areas were derived from mass and length measurements on tendons and muscles assuming published values for the respective densities. The majority of the stresses are low. The distribution has a broad peak with maximum frequency at a stress of about 13 MPa, whereas the fracture stress for tendon in tension is about 100 MPa. Thus, the majority of tendons are far thicker than is necessary for adequate strength. Much higher stresses are found among those tendons which act as springs to store energy during locomotion. The acceptability of low safety factors in these tendons has been explained previously (Alexander, 1981). A new theory explains the thickness of the majority of tendons. The muscle with its tendon is considered as a combined system which delivers mechanical energy: the thickness of the tendon is optimized by minimizing the combined mass. A thinner tendon would stretch more. To take up this stretch, the muscle would require longer muscle fibres, which would increase the combined mass. The predicted maximum stress in a tendon of optimum thickness is about 10 MPa, which is within the main peak of the observed stress distribution. Individual variations from this value are to be expected and can be understood in terms of the functions of the various muscles.     

Why are the genomes of endosymbiotic bacteria so stable?

The comparative analysis of three strains of the endosymbiotic bacterium Buchnera aphidicola has revealed high genome stability associated with an almost complete absence of chromosomal rearrangements and horizontal gene transfer events during the past 150 million years. The loss of genes involved in DNA uptake and recombination in the initial stages of endosymbiosis probably underlies this stability. Gene loss, which was extensive during the initial steps of Buchnera evolution, has continued in the different Buchnera lineages since their divergence.     

Why use population entropy? It determines the rate of convergence

Summary The population entropy introduced by Demetrius is shown to have a precise dynamical meaning as a measure of convergence rate to the stable age distribution. First the Leslie population model is transformed exactly into a Markov chain on a state space of age-classes. Next the dynamics of convergence from a nonequilibrium state to the stable state are analyzed. The results provide the first clear biological reason why entropy is a broadly useful population statistic.     

Why do fast- and slow-growing grass species differ so little in their rate of root respiration,considering the large differences in rate of growth and ion uptake?

Herbaceous plants grown with free access to nutrients exhibit inherent differences in maximum relative growth rate (RGR) and rate of nutrient uptake. Measured rates of root respiration are higher in fast-growing species than in slow-growing ones. Fast-growing herbaceous species, however, exhibit lower rates of respiration than would be expected from their high rates of growth and nitrate uptake. We investigated why the difference in root O₂ uptake between fast- and slow-growing species is relatively small. Inhibition of respiration by the build-up of CO₂ in closed cuvettes, diurnal variation in respiration rates or an increasing ratio of respiratory CO₂ release to O₂ uptake (RQ) with increasing RGR failed to explain the relatively low root respiration rates in fast-growing grasses. Furthermore, differences in alternative pathway activity can at most only partly explain why the difference in root respiration between fast- and slow-growing grasses is relatively small. Although specific respiratory costs for maintenance of biomass are slightly higher in the fast-growing Dactylis glomerata L. than those in the slow-growing Festuca ovina L., they account for 50% of total root respiration in both species. The specific respiratory costs for ion uptake in the fast-growing grass are one-third of those in the slow-growing grass [0·41 versus 1·22 mol O₂ mol (NO₃^–)^–1]. We conclude that this is the major cause of the relatively low rates of root respiration in fast-growing grasses.     

How past and present influence the foraging of clonal plants?

Clonal plants spreading horizontally and forming a network structure of ramets exhibit complex growth patterns to maximize resource uptake from the environment. They respond to spatial heterogeneity by changing their internode length or branching frequency. Ramets definitively root in the soil but stay interconnected for a varying period of time thus allowing an exchange of spatial and temporal information. We quantified the foraging response of clonal plants depending on the local soil quality sampled by the rooting ramet (i.e. the present information) and the resource variability sampled by the older ramets (i.e. the past information). We demonstrated that two related species, Potentilla reptans and P. anserina, responded similarly to the local quality of their environment by decreasing their internode length in response to nutrient-rich soil. Only P. reptans responded to resource variability by decreasing its internode length. In both species, the experience acquired by older ramets influenced the plastic response of new rooted ramets: the internode length between ramets depended not only on the soil quality locally sampled but also on the soil quality previously sampled by older ramets. We quantified the effect of the information perceived at different time and space on the foraging behavior of clonal plants by showing a non-linear response of the ramet rooting in the soil of a given quality. These data suggest that the decision to grow a stolon or to root a ramet at a given distance from the older ramet results from the integration of the past and present information about the richness and the variability of the environment.     

Do complex population histories drive higher estimates of substitution rate in phylogenetic reconstructions?

Our curiosity about biodiversity compels us to reconstruct the evolutionary past of species. Molecular evolutionary theory now allows parameterization of mathematically sophisticated and detailed models of DNA evolution, which have resulted in a wealth of phylogenetic histories. But reconstructing how species and population histories have played out is critically dependent on the assumptions we make, such as the clock-like accumulation of genetic differences over time and the rate of accumulation of such differences. An important stumbling block in the reconstruction of evolutionary history has been the discordance in estimates of substitution rate between phylogenetic and pedigree-based studies. Ancient genetic data recovered directly from the past are intermediate in time scale between phylogenetics-based and pedigree-based calibrations of substitution rate. Recent analyses of such ancient genetic data suggest that substitution rates are closer to the higher, pedigree-based estimates. In this issue, Navascués & Emerson (2009) model genetic data from contemporary and ancient populations that deviate from a simple demographic history (including changes in population size and structure) using serial coalescent simulations. Furthermore, they show that when these data are used for calibration, we are likely to arrive at upwardly biased estimates of mutation rate.     

Why are there so many species of bumble bees at Dungeness?

WILLIAMS, P. H., 1989. Why are there so many species of bumble bees at Dungeness? Dungeness is unique in the British Isles in that it has more species of bumble bees than any other locality. Three ideas about what governs the number of species at a locality are examined by locking at patterns of flower visits at Dungeness in comparison with those at Shoreham, a species-poor locality also in Kent. The species of bumble bees that are present at Dungeness but absent from Shoreham show no association in their distributions among 2 km grid-squares in Kent with the species of food-plants that they prefer at Dungeness, nor is there any correlation between the diversity of bees and diversity of food-plants at Dungeness and Shoreham. From the information available, Dungeness is most likely to have more species of bumble bees because it has a particularly high density of the more nectar-rich flowers that bumble bees can use. Bumble bees feed most profitably from deep flowers because these contain more nectar than shallow flowers, although direct access to deeper flowers is ultimately limited by the length of each bee's proboscis. The distribution of worker proboscis lengths among species in the species-pool in Kent is clumped about a median of 7.9 mm. The best foraging conditions for the maximum number of species should be provided when flowers of similar depths are present in sufficiently large numbers for all foragers to make near-optimal flower choices. Although there is no difference in median between the distributions of the bees' proboscis lengths and the depths of the flowers they use at Dungeness, at Shoreham the flower depths used are shorter than the proboscis lengths. Among the food-plants at Dungeness, high densities of Teucrium scorodonia and Echium vulgare are likely to be especially important.     

Why are evergreen leaves so contrary about shade?

Leaf mass per area (LMA) is one of the most widely measured of all plant functional traits. In deciduous forests, there is similarity between plastic and evolutionary responses of LMA to light gradients. In evergreens, however, LMA is lower in shaded than sunlit individuals of the same species, whereas shade-tolerant evergreens have higher LMA than light-demanders grown under the same conditions. We suggest that this pattern of 'counter-gradient variation' results from some combination of (i) close evolutionary coordination of LMA with leaf lifespan, (ii) selection for different leaf constitutions (relative investment in cell walls versus cell contents) in sun and shade environments and/or (iii) constraints on plasticity as a result of genetic correlations between phenotypes expressed in sun and shade.