Constraints in the restoration of ecological diversity in grassland and heathland communities

Species-rich grassland and heathland communities still occur in low-intensity farming systems in many European countries. Gradually, such systems have either been abandoned or more intensively exploited, with a subsequent decrease in species numbers. Until recently, it was thought that restoration of these communities would be straightforward. However, abiotic constraints (with respect to eutrophication and acidification) have hampered restoration more than previously thought. Moreover, very recent research has revealed that biotic constraints can also be important: many plant species are not present in the soil seed bank and their dispersal is limited in the present fragmented landscape.     

Environmental constraints and call evolution in torrent‐dwelling frogs

Although acoustic signals are important for communication in many taxa, signal propagation is affected by environmental properties. Strong environmental constraints should drive call evolution, favoring signals with greater transmission distance and content integrity in a given calling habitat. Yet, few empirical studies have verified this prediction, possibly due to a shortcoming in habitat characterization, which is often too broad. Here we assess the potential impact of environmental constraints on the evolution of advertisement call in four groups of torrent‐dwelling frogs in the family Ranidae. We reconstruct the evolution of calling site preferences, both broadly categorized and at a finer scale, onto a phylogenetic tree for 148 species with five markers (～3600 bp). We test models of evolution for six call traits for 79 species with regard to the reconstructed history of calling site preferences and estimate their ancestral states. We find that in spite of existing morphological constraints, vocalizations of torrent‐dwelling species are most probably constrained by the acoustic specificities of torrent habitats and particularly their high level of ambient noise. We also show that a fine‐scale characterization of calling sites allows a better perception of the impact of environmental constraints on call evolution.     

Application of dynamic metabolic flux analysis for process modeling: Robust flux estimation with regularization,confidence bounds,and selection of elementary modes

In macroscopic dynamic models of fermentation processes, elementary modes (EM) derived from metabolic networks are often used to describe the reaction stoichiometry in a simplified manner and to build predictive models by parameterizing kinetic rate equations for the EM. In this procedure, the selection of a set of EM is a key step which is followed by an estimation of their reaction rates and of the associated confidence bounds. In this paper, we present a method for the computation of reaction rates of cellular reactions and EM as well as an algorithm for the selection of EM for process modeling. The method is based on the dynamic metabolic flux analysis (DMFA) proposed by Leighty and Antoniewicz (2011, Metab Eng, 13(6), 745–755) with additional constraints, regularization and analysis of uncertainty. Instead of using estimated uptake or secretion rates, concentration measurements are used directly to avoid an amplification of measurement errors by numerical differentiation. It is shown that the regularized DMFA for EM method is significantly more robust against measurement noise than methods using estimated rates. The confidence intervals for the estimated reaction rates are obtained by bootstrapping. For the selection of a set of EM for a given st oichiometric model, the DMFA for EM method is combined with a multiobjective genetic algorithm. The method is applied to real data from a CHO fed-batch process. From measurements of six fed-batch experiments, 10 EM were identified as the smallest subset of EM based upon which the data can be described sufficiently accurately by a dynamic model. The estimated EM reaction rates and their confidence intervals at different process conditions provide useful information for the kinetic modeling and subsequent process optimization.     

Two eggs,two different constraints: a potential explanation for the puzzling intraclutch egg size dimorphism in Eudyptes penguins

Phenotypic plasticity and phenotypic stability are major components of the adaptive evolution of organisms to environmental variation. The invariant two-egg clutch size of Eudyptes penguins has recently been proposed to be a unique example of a maladaptive phenotypic stability, while their egg mass is a plastic trait. We tested whether this phenotypic plasticity during reproduction might result from constraints imposed by migration (migratory carry-over effect) and breeding (due to the depletion of female body reserves). For the first time, we examined whether these constraints differ between eggs within clutches and between egg components (yolk and albumen). The interval between colony return and clutch initiation positively influenced the yolk mass, the albumen mass, and the subsequent total egg mass of first-laid eggs. This time interval had only a slight negative influence on the yolk mass of second-laid eggs and no influence on their albumen and subsequent total masses. For both eggs, female body mass at laying positively influenced albumen and total egg masses. Female investment into the entire clutch was not related to the time in the colony before laying but increased with female body mass. These novel results suggest that the unique intraclutch egg size dimorphism exhibited in Eudyptes penguins, with first-laid eggs being consistently smaller than second-laid eggs, might be due to a combination of constraints: a migratory carry-over effect on the first-laid egg and a body reserve depletion effect on the second-laid egg. Both these constraints might explain why the timing of reproduction, especially egg formation, is narrow in migratory capital breeders.     

Maximal indirect development, set-aside cells, and levels of selection

The evolution of metazoan development as described by Davidson et al. (1995. Science 270:1319-1325) is readily interpretable in terms of levels-of-selection conflicts, for instance, as recently modeled by Michod (1999. Darwinian Dynamics, Princeton, NJ: Princeton University Press). Davidson et al. propose certain features of early bilaterians including small size, a small and fixed number of cell divisions during and subsequent to cleavage, and specification of cell fates prior to cell movement. These features suggest constraints on certain parameters of Michod's model, specifically t (the time available for cell division) and b (the benefit to cells of not cooperating in terms of their rate of replication). Such constraints clearly enhance between-cell cooperation and allow multicellularity to more easily evolve and be maintained. Nevertheless, these constraints are completely abrogated by the phenomenon of "set-aside cells," that is, undifferentiated cells that retain indefinite division potential. Levels-of-selection theory predicts that the evolution of these set-aside cells must be accompanied by features which alleviate cell-cell competition, and indeed the results of Ransick et al. (1996. Proc Natl Acad Sci USA 93:6759-6763) support this prediction: the evolution of "set-aside cells" in metazoans was accompanied by the evolution of the sequestration of the germ line.     

Tectonic blocks and molecular clocks

Evolutionary timescales have mainly used fossils for calibrating molecular clocks, though fossils only really provide minimum clade age constraints. In their place, phylogenetic trees can be calibrated by precisely dated geological events that have shaped biogeography. However, tectonic episodes are protracted, their role in vicariance is rarely justified, the biogeography of living clades and their antecedents may differ, and the impact of such events is contingent on ecology. Biogeographic calibrations are no panacea for the shortcomings of fossil calibrations, but their associated uncertainties can be accommodated. We provide examples of how biogeographic calibrations based on geological data can be established for the fragmentation of the Pangaean supercontinent: (i) for the uplift of the Isthmus of Panama, (ii) the separation of New Zealand from Gondwana, and (iii) for the opening of the Atlantic Ocean. Biogeographic and fossil calibrations are complementary, not competing, approaches to constraining molecular clock analyses, providing alternative constraints on the age of clades that are vital to avoiding circularity in investigating the role of biogeographic mechanisms in shaping modern biodiversity.This article is part of the themed issue ‘Dating species divergences using rocks and clocks’.     

Microsatellite Behavior with Range Constraints: Parameter Estimation and Improved Distances for Use in Phylogenetic Reconstruction

A symmetric stepwise mutation model with reflecting boundaries is employed to evaluate microsatellite evolution under range constraints. Methods of estimating range constraints and mutation rates under the assumptions of the model are developed. Least squares procedures are employed to improve molecular distance estimation for use in phylogenetic reconstruction in the case where range constraints and mutation rates vary across loci. The bias and accuracy of these methods are evaluated using computer simulations, and they are compared to previously existing methods which do not assume range constraints. Range constraints are seen to have a substantial impact on phylogenetic conclusions based on molecular distances, particularly for more divergent taxa. Results indicate that if range constraints are in effect, the methods developed here should be used in both the preliminary planning and final analysis of phylogenetic studies employing microsatellites. It is also seen that in order to make accurate phylogenetic inferences under range constraints, a larger number of loci are required than in their absence.     

Sedimentation equilibrium analysis of protein interactions with global implicit mass conservation constraints and systematic noise decomposition

Sedimentation equilibrium is a powerful tool for the characterization of protein self-association and heterogeneous protein interactions. Frequently, it is applied in a configuration with relatively long solution columns and with equilibrium profiles being acquired sequentially at several rotor speeds. The present study proposes computational tools, implemented in the software SEDPHAT, for the global analysis of equilibrium data at multiple rotor speeds with multiple concentrations and multiple optical detection methods. The detailed global modeling of such equilibrium data can be a nontrivial computational problem. It was shown previously that mass conservation constraints can significantly improve and extend the analysis of heterogeneous protein interactions. Here, a method for using conservation of mass constraints for the macromolecular redistribution is proposed in which the effective loading concentrations are calculated from the sedimentation equilibrium profiles. The approach is similar to that described by Roark (Biophys. Chem. 5 (1976) 185-196), but its utility is extended by determining the bottom position of the solution columns from the macromolecular redistribution. For analyzing heterogeneous associations at multiple protein concentrations, additional constraints that relate the effective loading concentrations of the different components or their molar ratio in the global analysis are introduced. Equilibrium profiles at multiple rotor speeds also permit the algebraic determination of radial-dependent baseline profiles, which can govern interference optical ultracentrifugation data, but usually also occur, to a smaller extent, in absorbance optical data. Finally, the global analysis of equilibrium profiles at multiple rotor speeds with implicit mass conservation and computation of the bottom of the solution column provides an unbiased scale for determining molar mass distributions of noninteracting species. The properties of these tools are studied with theoretical and experimental data sets.     

Heterogeneity in IBD allele sharing among covariate-defined subgroups: issues and findings for affected relatives

OBJECTIVES: Modelling of variation in identical-by-descent (IBD) allele sharing using covariates can increase power to detect linkage, identify covariate-defined subgroups linked to particular marker regions, and improve the design of subsequent studies to localize genes and characterize their effects. In this report, we highlight issues that arise in studies of families with affected relatives. METHODS: Mirea et al. [Genet Epidemiol 2003, in press] extended linear and exponential linkage likelihood models [Kong and Cox, Am J Hum Genet 1997;61: 1179-1188] to model variation in NPL scores among covariate-defined groups of families, and proposed likelihood ratio (LR) and t statistics to detect differences in allele sharing between groups defined by a binary covariate. Here we evaluate factors affecting the power of these tests analytically and by example, as well as effects of constraints, nuisance parameters, and incomplete data on test validity by simulation of locus heterogeneity in families with affected siblings or affected cousins. RESULTS: Provided constraints on the parameters are avoided, these tests are particularly useful when one subgroup has less than expected IBD sharing. The distribution of the LR statistic depends on the extent of linkage, particularly in the presence of constraints. The t statistic may be biased by group differences in information content. CONCLUSIONS: We recommend that constraints be applied cautiously, and covariate effects in IBD allele sharing models interpreted with care.     

Advances in the diagnosis of key gastrointestinal nematode infections of livestock,with an emphasis on small ruminants

Parasitic nematodes (roundworms) of livestock have major economic impact globally. In spite of the diseases caused by these nematodes and some advances in the design of new therapeutic agents (anthelmintics) and attempts to develop vaccines against some of them, there has been limited progress in the establishment of practical diagnostic techniques. The specific and sensitive diagnosis of gastrointestinal nematode infections of livestock underpins effective disease control, which is highly relevant now that anthelmintic resistance (AR) is a major problem. Traditional diagnostic techniques have major constraints, in terms of sensitivity and specificity. The purpose of this article is to provide a brief background on gastrointestinal nematodes (Strongylida) of livestock and their control; to summarize conventional methods used for the diagnosis and discuss their constraints; to review key molecular-diagnostic methods and recent progress in the development of advanced amplification-based and sequencing technologies, and their implications for epidemiological investigations and the control of parasitic diseases.     

Connectomic constraints on computation in feedforward networks of spiking neurons

Several efforts are currently underway to decipher the connectome or parts thereof in a variety of organisms. Ascertaining the detailed physiological properties of all the neurons in these connectomes, however, is out of the scope of such projects. It is therefore unclear to what extent knowledge of the connectome alone will advance a mechanistic understanding of computation occurring in these neural circuits, especially when the high-level function of the said circuit is unknown. We consider, here, the question of how the wiring diagram of neurons imposes constraints on what neural circuits can compute, when we cannot assume detailed information on the physiological response properties of the neurons. We call such constraints—that arise by virtue of the connectome—connectomic constraints on computation. For feedforward networks equipped with neurons that obey a deterministic spiking neuron model which satisfies a small number of properties, we ask if just by knowing the architecture of a network, we can rule out computations that it could be doing, no matter what response properties each of its neurons may have. We show results of this form, for certain classes of network architectures. On the other hand, we also prove that with the limited set of properties assumed for our model neurons, there are fundamental limits to the constraints imposed by network structure. Thus, our theory suggests that while connectomic constraints might restrict the computational ability of certain classes of network architectures, we may require more elaborate information on the properties of neurons in the network, before we can discern such results for other classes of networks.     

Three-dimensional structures of membrane proteins from genomic sequencing

We show that amino acid covariation in proteins, extracted from the evolutionary sequence record, can be used to fold transmembrane proteins. We use this technique to predict previously unknown 3D structures for 11 transmembrane proteins (with up to 14 helices) from their sequences alone. The prediction method (EVfold_membrane) applies a maximum entropy approach to infer evolutionary covariation in pairs of sequence positions within a protein family and then generates all-atom models with the derived pairwise distance constraints. We benchmark the approach with blinded de novo computation of known transmembrane protein structures from 23 families, demonstrating unprecedented accuracy of the method for large transmembrane proteins. We show how the method can predict oligomerization, functional sites, and conformational changes in transmembrane proteins. With the rapid rise in large-scale sequencing, more accurate and more comprehensive information on evolutionary constraints can be decoded from genetic variation, greatly expanding the repertoire of transmembrane proteins amenable to modeling by this method.     

Growth and Parasite Defence in Plants; the Balance between Resource Sequestration and Retention: In Lieu of a Guest Editorial

Abstract: A hypothesis on regulation of the balance between growth and parasite defence in plants is formulated, namely that plants regulate their resource allocation in a way where stress tolerance and resistance inherently lead to constraints on growth and competitiveness. Seven reviews and the subsequent article in this issue of Plant Biology contributing to this problem are briefly introduced in context.     

The development of numerical classification and ordination

Summary The paper reviews the constraints and influences which have affected the development of numerical classification and ordination of vegetation.Initial development of ordination techniques and their reception by ecologists was hindered by the mistaken idea that ordination involved acceptance of variation in vegetation as a continuum, as well as by a general suspicion of mathematical approaches.Three distinct approaches to ordination, largely unrecognised at the time, are apparent in earlier work: direct gradient analysis, reduction in dimensionality and path-seeking (catenation) (Dale 1975).Modifications of simple initial techniques made them more efficient at the cost of increased computation. Acceptance of heavier computation as computers increased in capacity and speed turned attention to prineipal component analysis and the superficially similar factor analysis. These have been widely misunderstood largely because they were initially applied in the same way as in the analysis of psychological data, in which different constraints and objectives apply. The initial failure to recognise that principal component analysis involves a preliminary data transformation, the form of which depends on answers to biological, not mathematical, questions, was particularly unfortunate.Principal component analysis has limitations as a technique of ordination resulting from its assumptions of linearity and additivity of plant responses. Attempts to devise more effective techniques raise questions about the practical importance of non-linearity if the objective is data-exploration rather than elucidating the nature of species-response curves and about the adequacy of using simulated data as test data when we do not know how to simulate realistic data.Data-exploration has been more prominent in practical uses of ordination but many methodological developments have concentrated rather on species-response curves.Numerical classification also met obstacles to its acceptance additional to a general aversion to numerical techniques. The first numerical techniques were presented in the context of the relationships of a particular set of data, rather than of a generally valid system, which was the more familiar concept in non-numerical classification.Both numerical and non-numerical classification aim to produce as homogeneous groups as possible. The distinctive contribution of numerical methods is to allow the data to indicate the most efficient criteria of classification; this was an unfamiliar idea.The strategy of classification may be either divisive or agglomerative and either monothetic or polythetic. Choice of strategy in earlier work was not only constrained by computational limitation but may also have been influenced by an author's previous experience of non-numerical classification. As with ordination, the distinction between preliminary data transformation and subsequent analysis was at first not appreciated.Numerical classification has been influenced by parallel numerical developments in formal taxonomy. Because objectives and assumptions are not always the same, this influence has not been altogether helpful.The limitations of real data suggest that developments of technique are at risk of becoming too concerned with refinements of methodology. Increasingly complex methods and increasing availability of programmes for such methods carry the risk that they may be used without adequate understanding of what they do.     

Common evolutionary trends for SINE RNA structures

Short interspersed elements (SINEs) and long interspersed elements (LINEs) are transposable elements in eukaryotic genomes that mobilize through an RNA intermediate. Understanding their evolution is important because of their impact on the host genome. Most eukaryotic SINEs are ancestrally related to tRNA genes, although the typical tRNA cloverleaf structure is not apparent for most SINE consensus RNAs. Using a cladistic method where RNA structural components were coded as polarized and ordered multistate characters, we showed that related structural motifs are present in most SINE RNAs from mammals, fishes and plants, suggesting common selective constraints imposed at the SINE RNA structural level. Based on these results, we propose a general multistep model for the evolution of tRNA-related SINEs in eukaryotes.     

Operations management in the home care services: a heuristic for the caregivers’ routing problem

Home Care Services (HCS) aim at providing complex coordinated health care for patients at their homes. This paper addresses the challenges of routing and scheduling HCS caregivers under precedence and coordination constraints, with patients receiving multiple caregivers. Moreover, the visits are performed simultaneously and possibly in a predefined order. The routing problem involves a fleet of vehicles to serve a number of customers at different locations. The objective is to find the minimal round for vehicle, while satisfying all the customers and without violating customers’ time windows. It has been proved that the complexity of the caregivers routing problem is linked to both (1) the number of care activities per caregiver ratio and (2) the temporal dependencies rate. Given the poor performance of the mathematical modeling based on exact approaches, a heuristic approach called the Caregivers Routing Heuristic (CRH) has been developed and tested using real size instances. In fact, the exact approaches are not able to solve real size instances. The performance of the CRH has been evaluated using real size instances. The numerical results show that the CRH is very efficient in terms of computation times. Otherwise, the CRH is less sensitive than the exact approaches to both complexity axes: the temporal dependencies constraints and the ratio of the number of care activities per caregiver.     

Effects of individual pre-fledging traits and environmental conditions on return patterns in juvenile king penguins

Despite the importance of early life stages in individuals' life history and population dynamics, very few studies have focused on the constraints to which these juvenile traits are subjected. Based on 10 years of automatic monitoring of over 2500 individuals, we present the first study on the effects of environmental conditions and individual pre-fledging traits on the post-fledging return of non-banded king penguins to their natal colony. Juvenile king penguins returned exclusively within one of the three austral summers following their departure. A key finding is that return rates (range 68-87%) were much higher than previously assumed for this species, importantly meaning that juvenile survival is very close to that of adults. Such high figures suggest little juvenile dispersal, and selection occurring mostly prior to fledging in king penguins. Pre-fledging conditions had a strong quadratic impact on juvenile return rates. As expected, cohorts reared under very unfavourable years (as inferred by the breeding success of the colony) exhibited low return rates but surprisingly, so did those fledged under very favourable conditions. Juvenile sojourns away from the colony were shorter under warm conditions and subsequent return rates higher, suggesting a positive effect of climate warming. The longer the post-fledging trip (1, 2 or 3 years), the earlier in the summer birds returned to their natal colony and the longer they stayed before leaving for the winter journey. The presence of juveniles in the colony was more than twice the duration required for moulting purposes, yet none attempted breeding in the year of their first return. Juvenile presence in the colony may be important for acquiring knowledge on the social and physical colonial environment and may play an important part in the learning process of mating behaviour. Further studies are required to investigate its potential implications on other life-history traits such as recruitment age.     

Kinetic constraints for formation of steady states in biochemical networks

The constraint-based analysis has emerged as a useful tool for analysis of biochemical networks. This work introduces the concept of kinetic constraints. It is shown that maximal reaction rates are appropriate constraints only for isolated enzymatic reactions. For biochemical networks, it is revealed that constraints for formation of a steady state require specific relationships between maximal reaction rates of all enzymes. The constraints for a branched network are significantly different from those for a cyclic network. Moreover, the constraints do not require Michaelis-Menten constants for most enzymes, and they only require the constants for the enzymes at the branching or cyclic point. Reversibility of reactions at system boundary or branching point may significantly impact on kinetic constraints. When enzymes are regulated, regulations may impose severe kinetic constraints for the formation of steady states. As the complexity of a network increases, kinetic constraints become more severe. In addition, it is demonstrated that kinetic constraints for networks with co-regulation can be analyzed using the approach. In general, co-regulation enhances the constraints and therefore larger fluctuations in fluxes can be accommodated in the networks with co-regulation. As a first example of the application, we derive the kinetic constraints for an actual network that describes sucrose accumulation in the sugar cane culm, and confirm their validity using numerical simulations.