Phenotypic evolution studied by layered stochastic differential equations

Time series of cell size evolution in unicellular marine algae (division Haptophyta; Coccolithus lineage), covering 57 million years, are studied by a system of linear stochastic differential equations of hierarchical structure. The data consists of size measurements of fossilized calcite platelets (coccoliths) that cover the living cell, found in deep-sea sediment cores from six sites in the world oceans and dated to irregular points in time. To accommodate biological theory of populations tracking their fitness optima, and to allow potentially interpretable correlations in time and space, the model framework allows for an upper layer of partially observed site-specific population means, a layer of site-specific theoretical fitness optima and a bottom layer representing environmental and ecological processes. While the modeled process has many components, it is Gaussian and analytically tractable. A total of 710 model specifications within this framework are compared and inference is drawn with respect to model structure, evolutionary speed and the effect of global temperature.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS559 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Territory location and quality, together with climate, affect the timing of breeding in the whitethroated dipper

Recent climate change has led to advanced spring phenology in many temperate regions. The phenological response to variation in the local environment, such as the habitat characteristics of the territories birds occupy, is less clear. The aim of this study is to understand how ecological conditions affect breeding time, and its consequences for reproduction, in a white-throated dipper Cinclus cinclus population in a river system in Norway during 34 years (1978–2011). Hatching date advanced almost nine days, indicating a response to higher temperatures and the advanced phenology in the area. Earlier breeding was found in warm springs and at lower altitudes. High population density facilitated earlier breeding close to the coast. Furthermore, when population density was low, breeding was early at territories that were rarely occupied, while in years with high density, breeding was early at territories that were frequently occupied. Also, when population density was low, earlier breeding occurred at territories that on average produced more offspring than other territories, while there was no difference in breeding time in high population years. Selection for early breeding was dependent on spring temperatures and high spring temperatures contributed to higher breeding success during the study period. We found that breeding phenology may have strong effects on fitness in the white-throated dipper, and thus that breeding time is an important ecological factor in a species that feeds mainly on aquatic rather than terrestrial prey.publishedVersio

Neutral processes related to regional bee commonness and dispersal distances are important predictors of plant–pollinator networks along gradients of climate and landscape conditions

Understanding how niche-based and neutral processes contribute to the spatial varia-tion in plant–pollinator interactions is central to designing effective pollination con-servation schemes. Such schemes are needed to reverse declines of wild bees and other pollinating insects, and to promote pollination services to wild and cultivated plants. We used data on wild bee interactions with plants belonging to the four tribes Loteae, Trifolieae, Anthemideae and either spring- or summer-flowering Cichorieae, sampled systematically along a 682 km latitudinal gradient to build models that allowed us to 1) predict occurrences of pairwise bee–flower interactions across 115 sampling locations, and 2) estimate the contribution of variables hypothesized to be related to niche-based assembly structuring processes (viz. annual mean temperature, landscape diversity, bee sociality, bee phenology and flower preferences of bees) and neutral processes (viz. regional commonness and dispersal distance to conspecifics). While neutral processes were important predictors of plant–pollinator distributions, niche-based processes were reflected in the contrasting distributions of solitary bee and bumble bees along the temperature gradient, and in the influence of bee flower preferences on the distri-bution of bee species across plant types. In particular, bee flower preferences separated bees into three main groups, albeit with some overlap: visitors to spring-flowering Cichorieae; visitors to Anthemideae and summer-flowering Cichorieae; and visitors to Trifolieae and Loteae. Our findings suggest that both neutral and niche-based pro-cesses are significant contributors to the spatial distribution of plant–pollinator inter-actions so that conservation actions in our region should be directed towards areas: Page 2 of 11near high concentrations of known occurrences of regionally rare bees; in mild climatic conditions; and that are surrounded by heterogenous landscapes. Given the observed niche-based differences, the proportion of functionally distinct plants in flower-mixes could be chosen to target bee species, or guilds, of conservation concern. Keywords: ecological networks, machine learning, plant–pollinator interactions, spatial, wild beesNeutral processes related to regional bee commonness and dispersal distances are important predictors of plant–pollinator networks along gradients of climate and landscape conditionspublishedVersionpublishedVersio

A Comparison of Methods for Streamflow Uncertainty Estimation

International audienceStreamflow time series are commonly derived from stage-discharge rating curves, but the uncertainty of the rating curve and resulting streamflow series are poorly understood. While different methods to quantify uncertainty in the stage-discharge relationship exist, there is limited understanding of how uncertainty estimates differ between methods due to different assumptions and methodological choices. We compared uncertainty estimates and stage-discharge rating curves from seven methods at three river locations of varying hydraulic complexity. Comparison of the estimated uncertainties revealed a wide range of estimates, particularly for high and low flows. At the simplest site on the Isère River (France), full width 95% uncertainties for the different methods ranged from 3 to 17% for median flows. In contrast, uncertainties were much higher and ranged from 41 to 200% for high flows in an extrapolated section of the rating curve at the Mahurangi River (New Zealand) and 28 to 101% for low flows at the Taf River (United Kingdom), where the hydraulic control is unstable at low flows. Differences between methods result from differences in the sources of uncertainty considered, differences in the handling of the time-varying nature of rating curves, differences in the extent of hydraulic knowledge assumed, and differences in assumptions when extrapolating rating curves above or below the observed gaugings. Ultimately, the selection of an uncertainty method requires a match between user requirements and the assumptions made by the uncertainty method. Given the significant differences in uncertainty estimates between methods, we suggest that a clear statement of uncertainty assumptions be presented alongside streamflow uncertainty estimates

Estimating the discharge rating curve by nonlinear regression - The frequentist approach

This report provides a discussion about the fundamentals of the frequentist approach to the classical nonlinear least squares head - discharge power-law rating curve model, which is a vital procedure in practical hydrology. It is shown that the multivariate minimization problem of the classical nonlinear least squares rating curve model is equivalent to the maximization of a single argument function. We propose four general criteria which the discharge measurements should meet if a trustable frequentist least squares rating curve estimate should exist. The proposed criteria are applied to a large number of real-life discharge measurements, which suggest that the criteria are particularly useful in practice. We also show that the breakdown of one of the criteria implies an exponential law relationship between the head and the discharge. Numerical maximization of the single argument function and inference are discussed

winlose_production_line_bic

The production line scripts were made in order to turn a file describing colony battle outcomes and the species of the two colonies into a response, explanation variable file fit for regression analysis. The explanation variables are trait differences (thus ensuring reshuffling symmetry) made using a separate trait file describing the traits of each species. Interaction terms are made in addtion, before a random subset of battles are reshuffled, meaning that the outcome and each explanation variable is reversed. This in order to make sure there are both wins and losses in the output file, which then can be used in regression. This production line was used for making a single regression file, usable for for instance (but not restricted to) BIC-based model search on regression models (as opposed to a training-validation-test-based model search)

winlose_analyze_tvt

This collection of files contains the training, validation and test regression data files (the result of running the production line scripts) and the analysis scripts for training-validation-test-based model search. It contains one analysis script for the set of simple explanation variables and another for the full explanation variable set (including interaction terms and using random search)

winlose_production_line_tvt

See the description for winlose_production_line_bic for details concerning turning a battle outcome and species trait file into a reshuffled regressison file. The training-validation-test (tvt) version of this production line separates the species into a training set (battles are in the training set if both combatants are in the training species set), a validation set (battles are in the validation set if at least one combatant is in the validation species set and none are in the test species set) and a test set (battles are in the test set if at least one combatant is in the test species set). Instead of one regression files, three are thus produced

winlose_analyze_bic

This collection of files contains the regression data (the result of running the production line scripts) and the analysis scripts for BIC-based model search. It contains one analysis script for the set of simple explanation variables and another for the full explanation variable set (including interaction terms and using random search). It also contains similar analysis scripts for the 3 external datasets