Climate-based empirical models show biased predictions of butterfly communities along environmental gradients

A better understanding of the factors that mould ecological community structure is required to accurately predict community composition and to anticipate threats to ecosystems due to global changes. We tested how well stacked climate-based species distribution models (S-SDMs) could predict butterfly communities in a mountain region. It has been suggested that climate is the main force driving butterfly distribution and community structure in mountain environments, and that, as a consequence, climate-based S-SDMs should yield unbiased predictions. In contrast to this expectation, at lower altitudes, climate-based S-SDMs overpredicted butterfly species richness at sites with low plant species richness and underpredicted species richness at sites with high plant species richness. According to two indices of composition accuracy, the Sorensen index and a matching coefficient considering both absences and presences, S-SDMs were more accurate in plant-rich grasslands. Butterflies display strong and often specialised trophic interactions with plants. At lower altitudes, where land use is more intense, considering climate alone without accounting for land use influences on grassland plant richness leads to erroneous predictions of butterfly presences and absences. In contrast, at higher altitudes, where climate is the main force filtering communities, there were fewer differences between observed and predicted butterfly richness. At high altitudes, even if stochastic processes decrease the accuracy of predictions of presence, climate-based S-SDMs are able to better filter out butterfly species that are unable to cope with severe climatic conditions, providing more accurate predictions of absences. Our results suggest that predictions should account for plants in disturbed habitats at lower altitudes but that stochastic processes and heterogeneity at high altitudes may limit prediction success of climate-based S-SDMs.

Frequency-dependent sexual selection with respect to offspring fitness returns is consistent with predictions from rock-paper-scissors dynamics in the European common lizard

Genetic polymorphism can be maintained over time by negative frequency-dependent (FD) selection induced by Rock-paper-scissors (RPS) social systems. RPS games produce cyclic dynamics, and have been suggested to exist in lizards, insects, isopods, plants, and bacteria. Sexual selection is predicted to accentuate the survival of the future progeny during negative FD survival selection. More specifically, females are predicted to select mates that produce progeny genotypes that exhibit highest survival during survival selection imposed by adult males. However, no empirical evidence demonstrates the existence of FD sexual selection with respect to fitness payoffs of genetic polymorphisms. Here we tested this prediction using the common lizard Zootoca vivipara, a species with three male color morphs (orange, white, yellow) that exhibit morph frequency cycles. In a first step we tested the congruence of the morph frequency change with the predicted change in three independent populations, differing in male color morph frequency and state of the FD morph cycle. Thereafter we ran standardized sexual selection assays in which we excluded alternative mechanisms that potentially induce negative FD selection, and we quantified inter-sexual behavior. The patterns of sexual selection and the observed behavior were in line with context-dependent female mate choice and male behavior played a minor role. Moreover, the strength of the sexual selection was within the magnitude of selection required to produce the observed 3-4-year and 6-8 year morph frequency cycles at low and high altitudes, respectively. In summary, the study provides the first experimental evidence that underpins the crucial assumption of the RPS games suggested to exist in lizards, insects, isopods, and plants; namely, that sexual selection produces negative-FD selection. This indicates that sexual selection, in our study exert by females, might be a crucial driver of the maintenance of genetic polymorphisms.

Fitness correlates with the extent of cheating in a bacterium.

There is growing awareness of the importance of cooperative behaviours in microbial communities. Empirical support for this insight comes from experiments using mutant strains, termed 'cheats', which exploit the cooperative behaviour of wild-type strains. However, little detailed work has gone into characterising the competitive dynamics of cooperative and cheating strains. We test three specific predictions about the fitness consequences of cheating to different extents by examining the production of the iron-scavenging siderophore molecule, pyoverdin, in the bacterium Pseudomonas aeruginosa. We create a collection of mutants that differ in the amount of pyoverdin that they produce (from 1% to 96% of the production of paired wild types) and demonstrate that these production levels correlate with both gene activity and the ability to bind iron. Across these mutants, we found that (1) when grown in a mixed culture with a cooperative wild-type strain, the relative fitness of a mutant is negatively correlated with the amount of pyoverdin that it produces; (2) the absolute and relative fitness of the wild-type strain in the mixed culture is positively correlated with the amount of pyoverdin that the mutant produces; and (3) when grown in a monoculture, the absolute fitness of the mutant is positively correlated with the amount of pyoverdin that it produces. Overall, we demonstrate that cooperative pyoverdin production is exploitable and illustrate how variation in a social behaviour determines fitness differently, depending on the social environment.

Microsatellites can be misleading: an empirical and simulation study.

It has been long recognized that highly polymorphic genetic markers can lead to underestimation of divergence between populations when migration is low. Microsatellite loci, which are characterized by extremely high mutation rates, are particularly likely to be affected. Here, we report genetic differentiation estimates in a contact zone between two chromosome races of the common shrew (Sorex araneus), based on 10 autosomal microsatellites, a newly developed Y-chromosome microsatellite, and mitochondrial DNA. These results are compared to previous data on proteins and karyotypes. Estimates of genetic differentiation based on F- and R-statistics are much lower for autosomal microsatellites than for all other genetic markers. We show by simulations that this discrepancy stems mainly from the high mutation rate of microsatellite markers for F-statistics and from deviations from a single-step mutation model for R-statistics. The sex-linked genetic markers show that all gene exchange between races is mediated by females. The absence of male-mediated gene flow most likely results from male hybrid sterility.

Spatial predictions of phylogenetic diversity in conservation decision making.

Considering genetic relatedness among species has long been argued as an important step toward measuring biological diversity more accurately, rather than relying solely on species richness. Some researchers have correlated measures of phylogenetic diversity and species richness across a series of sites and suggest that values of phylogenetic diversity do not differ enough from those of species richness to justify their inclusion in conservation planning. We compared predictions of species richness and 10 measures of phylogenetic diversity by creating distribution models for 168 individual species of a species-rich plant family, the Cape Proteaceae. When we used average amounts of land set aside for conservation to compare areas selected on the basis of species richness with areas selected on the basis of phylogenetic diversity, correlations between species richness and different measures of phylogenetic diversity varied considerably. Correlations between species richness and measures that were based on the length of phylogenetic tree branches and tree shape were weaker than those that were based on tree shape alone. Elevation explained up to 31% of the segregation of species rich versus phylogenetically rich areas. Given these results, the increased availability of molecular data, and the known ecological effect of phylogenetically rich communities, consideration of phylogenetic diversity in conservation decision making may be feasible and informative.

Warming experiments underpredict plant phenological responses to climate change.

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

Policy Credibility and Delegation to Independent Regulatory Agencies: A Comparative Empirical Analysis

Independent regulatory agencies are one of the main institutional features of the 'rising regulatory state' in Western Europe. Governments are increasingly willing to abandon their regulatory competencies and to delegate them to specialized institutions that are at least partially beyond their control. This article examines the empirical consistency of one particular explanation of this phenomenon, namely the credibility hypothesis, claiming that governments delegate powers so as to enhance the credibility of their policies. Three observable implications are derived from the general hypothesis, linking credibility and delegation to veto players, complexity and interdependence. An independence index is developed to measure agency independence, which is then used in a multivariate analysis where the impact of credibility concerns on delegation is tested. The analysis relies on an original data set comprising independence scores for thirty-three regulators. Results show that the credibility hypothesis can explain a good deal of the variation in delegation. The economic nature of regulation is a strong determinant of agency independence, but is mediated by national institutions in the form of veto players.

Authors' response to 'Limitless longevity': the contribution of rectangularization to the secular increase in life expectancy: an empirical study.

Related article : Letter to the Editor: Karin Modig, Sven Drefahl, and Anders Ahlbon.Limitless longevity: Comment on the Contribution of rectangularization to the secular increase of life expectancy

Understanding consumers repurchase in the context of online shopping: an empirical study

L'utilisation de l'Internet comme medium pour faire ses courses et achats a vu une croissance exponentielle. Cependant, 99% des nouveaux business en ligne échouent. La plupart des acheteurs en ligne ne reviennent pas pour un ré-achat et 60% abandonnent leur chariot avant de conclure l'achat. En effet, après le premier achat, la rétention du consommateur en ligne devient critique au succès du vendeur de commerce électronique. Retenir des consommateurs peut sauver des coûts, accroître les profits, et permet de gagner un avantage compétitif.Les recherches précédentes ont identifié la loyauté comme étant le facteur le plus important dans la rétention du consommateur, et l'engagement ("commitment") comme étant un des facteurs les plus importants en marketing relationnel, offrant une réflexion sur la loyauté. Pourtant, nous n'avons pu trouver d'étude en commerce électronique examinant l'impact de la loyauté en ligne et de l'engagement en ligne ("online commitment") sur le ré-achat en ligne. Un des avantages de l'achat en ligne c'est la capacité à chercher le meilleur prix avec un clic. Pourtant, nous n'avons pu trouver de recherche empirique en commerce électronique qui examinait l'impact de la perception post-achat du prix sur le ré-achat en ligne.L'objectif de cette recherche est de développer un modèle théorique visant à comprendre le ré-achat en ligne, ou la continuité d'achat ("purchase continuance") du même magasin en ligne.Notre modèle de recherche a été testé dans un contexte de commerce électronique réel, sur un échantillon total de 1,866 vrais acheteurs d'un même magasin en ligne. L'étude est centrée sur le ré-achat. Par conséquent, les répondants sélectionnés aléatoirement devaient avoir acheté au moins une fois de ce magasin en ligne avant le début de l'enquête. Cinq mois plus tard, nous avons suivi les répondants pour voir s'ils étaient effectivement revenus pour un ré-achat.Notre analyse démontre que l'intention de ré-achat en ligne n'a pas d'impact significatif sur le ré-achat en ligne. La perception post-achat du prix en ligne ("post-purchase Price perception") et l'engagement normatif en ligne ("Normative Commitment") n'ont pas d'impact significatif sur l'intention de ré-achat en ligne. L'engagement affectif en ligne ("Affective Commitment"), l'attitude loyale en ligne ("Attitudinal Loyalty"), le comportement loyal en ligne ("Behavioral Loyalty"), l'engagement calculé en ligne ("Calculative Commitment") ont un impact positif sur l'intention de ré-achat en ligne. De plus, l'attitude loyale en ligne a un effet de médiation partielle entre l'engagement affectif en ligne et l'intention de ré-achat en ligne. Le comportement loyal en ligne a un effet de mediation partielle entre l'attitude loyale en ligne et l'intention de ré-achat en ligne.Nous avons réalisé deux analyses complémentaires : 1) Sur un échantillon de premiers acheteurs, nous trouvons que la perception post-achat du prix en ligne a un impact positif sur l'intention de ré-achat en ligne. 2) Nous avons divisé l'échantillon de l'étude principale entre des acheteurs répétitifs Suisse-Romands et Suisse-Allemands. Les résultats démontrent que les Suisse-Romands montrent plus d'émotions durant l'achat en ligne que les Suisse-Allemands. Nos résultats contribuent à la recherche académique mais aussi aux praticiens de l'industrie e-commerce.AbstractThe use of the Internet as a shopping and purchasing medium has seen exceptional growth. However, 99% of new online businesses fail. Most online buyers do not comeback for a repurchase, and 60% abandon their shopping cart before checkout. Indeed, after the first purchase, online consumer retention becomes critical to the success of the e-commerce vendor. Retaining existing customers can save costs, increase profits, and is a means of gaining competitive advantage.Past research identified loyalty as the most important factor in achieving customer retention, and commitment as one of the most important factors in relationship marketing, providing a good description of what type of thinking leads to loyalty. Yet, we could not find an e-commerce study investing the impact of both online loyalty and online commitment on online repurchase. One of the advantages of online shopping is the ability of browsing for the best price with one click. Yet, we could not find an e- commerce empirical research investigating the impact of post-purchase price perception on online repurchase.The objective of this research is to develop a theoretical model aimed at understanding online repurchase, or purchase continuance from the same online store.Our model was tested in a real e-commerce context with an overall sample of 1, 866 real online buyers from the same online store.The study focuses on repurchase. Therefore, randomly selected respondents had purchased from the online store at least once prior to the survey. Five months later, we tracked respondents to see if they actually came back for a repurchase.Our findings show that online Intention to repurchase has a non-significant impact on online Repurchase. Online post-purchase Price perception and online Normative Commitment have a non-significant impact on online Intention to repurchase, whereas online Affective Commitment, online Attitudinal Loyalty, online Behavioral Loyalty, and online Calculative Commitment have a positive impact on online Intention to repurchase. Furthermore, online Attitudinal Loyalty partially mediates between online Affective Commitment and online Intention to repurchase, and online Behavioral Loyalty partially mediates between online Attitudinal Loyalty and online Intention to repurchase.We conducted two follow up analyses: 1) On a sample of first time buyers, we find that online post-purchase Price perception has a positive impact on Intention. 2) We divided the main study's sample into Swiss-French and Swiss-German repeated buyers. Results show that Swiss-French show more emotions when shopping online than Swiss- Germans. Our findings contribute to academic research but also to practice.