Seasonal controls on net branch CO2 assimilation in sub-Arctic Mountain Birch (Betula pubescens ssp. czerepanovii (Orlova) Hamet-Ahti)

Forests at northern high latitudes are experiencing climate-induced changes in growth and productivity, but our knowledge on the underlying mechanisms driving seasonal CO2 fluxes in northern boreal trees comes almost exclusively from ecosystem-level studies on evergreen conifers. In this study, we measured growing season whole-branch CO2 exchange in a deciduous tree species of the tundra-taiga ecotone, Mountain Birch (Betula pubescens ssp. czerepanovii (Orlova) Hamet-Ahti), at two locations in northern Fennoscandia: Abisko (Sweden) and Kevo (Finland). We identified strong seasonal and environmental controls on both photosynthesis and respiration by analysing the parameters of light response curves. Branch-level photosynthetic parameters showed a delayed response to temperature, and, at Kevo, they were well described by sigmoid functions of the state of acclimation (S). Temperature acclimation was slower (time constant, τ = 7 days) for maximum photosynthesis (βbr) than for quantum efficiency (αbr) (τ = 5 days). High temperature-independent values of the respiration parameter (γbr) during leaf and shoot expansion were consistent with associated higher growth respiration rates. The ratio γbr/βbr was positively related to temperature, a result consistent with substrate-induced variations in leaf respiration rates at the branch level. Differences in stand structure and within-site variation in the active period of C uptake determined the spatiotemporal patterns in net assimilation amongst branches. Growing season CO2 uptake of individual branches on a leaf area basis did not show a significant relationship with total incident photosynthetically active radiation, and did not differ across sites, averaging ca. 640 g CO2 m−2

Fast and flexible Bayesian species distribution modelling using Gaussian processes

1. Species distribution modelling (SDM) is widely used in ecology, and predictions of species distributions inform both policy and ecological debates. Therefore, methods with high predictive accuracy and those that enable biological interpretation are preferable. Gaussian processes (GPs) are a highly flexible approach to statistical modelling and have recently been proposed for SDM. GP models fit smooth, but potentially complex response functions that can account for high-dimensional interactions between predictors. We propose fitting GP SDMs using deterministic numerical approximations, rather than Markov chain Monte Carlo methods in order to make GPs more computationally efficient and easy to use. 2. We introduce GP models and their application to SDM, illustrate how ecological knowledge can be incorporated into GP SDMs via Bayesian priors and formulate a simple GP SDM that can be fitted efficiently. This model can be fitted either by learning the hyperparameters or by using a fixed approximation to them. Using a subset of the North American Breeding Bird Survey data set, we compare the out-of-sample predictive accuracy of these models with several commonly used SDM approaches for both presence/absence and presence-only data. 3. Predictive accuracy of GP SDMs fitted by Laplace approximation was greater than boosted regression trees, generalized additive models (GAMs) and logistic regression when trained on presence/absence data and greater than all of these models plus MaxEnt when trained on presence-only data. GP SDMs fitted using a fixed approximation to hyperparameters were no less accurate than those with MAP estimation and on average 70 times faster, equivalent in speed to GAMs. 4. As well as having strong predictive power for this data set, GP SDMs offer a convenient method for incorporating prior knowledge of the species' ecology. By fitting these methods using efficient numerical approximations, they may easily be applied to large data sets and automatically for many species. An r package, GRaF, is provided to enable SDM users to fit GP models

Climatic Disequilibrium Threatens Conservation Priority Forests

AcceptedArticle in PressThis is the final version of the article. Available from Wiley Open Access via the DOI in this record.© 2017 Wiley Periodicals, Inc.We test the hypothesis that climatic changes since 1800 have resulted in unrealized potential vegetation changes that represent a "climatic debt" for many ecosystems. Caledonian pinewoods, an EU priority forest type, are used as a model system to explore potential impacts of two centuries of climatic change upon sites of conservation importance and surrounding landscapes. Using methods that estimate topographic microclimate, current and preindustrial climates were estimated for 50 m grid cells and simulations made using a dynamic vegetation model. Core Caledonian pinewood areas are now less suitable for growth of pine and more favorable for oak than in 1800, whereas landscapes as a whole are on average more favorable for both. The most favorable areas for pine are now mainly outside areas designated to conserve historical pinewoods. A paradigm shift is needed in formulating conservation strategies to avoid catastrophic losses of this habitat, and of many others globally with trees or other long-lived perennials as keystone species.Natural Environment Research Council. Grant Number: NE/I011234/

Smoothing effect and delocalization of interacting Bose-Einstein condensates in random potentials

We theoretically investigate the physics of interacting Bose-Einstein condensates at equilibrium in a weak (possibly random) potential. We develop a perturbation approach to derive the condensate wavefunction for an amplitude of the potential smaller than the chemical potential of the condensate and for an arbitrary spatial variation scale of the potential. Applying this theory to disordered potentials, we find in particular that, if the healing length is smaller than the correlation length of the disorder, the condensate assumes a delocalized Thomas-Fermi profile. In the opposite situation where the correlation length is smaller than the healing length, we show that the random potential can be significantly smoothed and, in the meanfield regime, the condensate wavefunction can remain delocalized, even for very small correlation lengths of the disorder.Comment: The word "screening" has been changed to "smoothing" to avoid confusions with other effects discussed in the literature. This does not affect the content of paper, nor the results, nor the physical discussio

Subject preferences of fifth-grade children.

Thesis (Ed.M.)--Boston University N.B.:Pages 155 and 309 are missing from original thesis

A Bayesian palaeoenvironmental transfer function model for acidified lakes

A Bayesian approach to palaeoecological environmental reconstruction deriving from the unimodal responses generally exhibited by organisms to an environmental gradient is described. The approach uses Bayesian model selection to calculate a collection of probability-weighted, species-specific response curves (SRCs) for each taxon within a training set, with an explicit treatment for zero abundances. These SRCs are used to reconstruct the environmental variable from sub-fossilised assemblages. The approach enables a substantial increase in computational efficiency (several orders of magnitude) over existing Bayesian methodologies. The model is developed from the Surface Water Acidification Programme (SWAP) training set and is demonstrated to exhibit comparable predictive power to existing Weighted Averaging and Maximum Likelihood methodologies, though with improvements in bias; the additional explanatory power of the Bayesian approach lies in an explicit calculation of uncertainty for each individual reconstruction. The model is applied to reconstruct the Holocene acidification history of the Round Loch of Glenhead, including a reconstruction of recent recovery derived from sediment trap data.The Bayesian reconstructions display similar trends to conventional (Weighted Averaging Partial Least Squares) reconstructions but provide a better reconstruction of extreme pH and are more sensitive to small changes in diatom assemblages. The validity of the posteriors as an apparently meaningful representation of assemblage-specific uncertainty and the high computational efficiency of the approach open up the possibility of highly constrained multiproxy reconstructions

Submesoscale Kinematic Properties in Summer and Winter Surface Flows in the Northern Gulf of Mexico

Statistical properties of near-surface horizontal velocity gradients are obtained from four drifter experiments conducted in the Gulf of Mexico during Summer 2012 and Winter 2016. The data density provided by the near-simultaneous deployments of 90-326 surface drifters in each allows direct, drifter-based estimates of the scale dependence of velocity gradients at separation scales ranging from 200 m to 5 km. The robustness of these estimates, derived from uniquley sampled, nearly equilateral triplets, is confirmed by comparisons with estimates produced from larger drifter clusters, and with estimates based on concurrent Eulerian X-band radar observations. The winter launches were deployed above a ∼80 m deep mixed layer, one in a region with nearly homogeneous horizontal density structure, the other in a region of strong surface density gradients associated with filaments of fresh Mississippi River water. The summer launches occurred in a shallow (10m) mixed layer, one launched across a mesoscale frontal jet separating regions of horizontally homogeneous density and the other, similar to the corresponding winter launch, also in a region filamented by shallow lenses of cold, fresh water. Seasonal differences are observed, with larger velocity fluctuations and greater variance in divergence and vorticity, especially at the smallest scales, in winter. Differences between same-season launches are, however, as large as seasonal differences. In both seasons, observations sampling regions directly impacted by fresh water fluxes show strongly skewed vorticity distributions, with cyclonic vorticity dominating strain. For the other launches, one in each season, strain dominated minimally skewed vorticity

Numerical study of one-dimensional and interacting Bose-Einstein condensates in a random potential

We present a detailed numerical study of the effect of a disordered potential on a confined one-dimensional Bose-Einstein condensate, in the framework of a mean-field description. For repulsive interactions, we consider the Thomas-Fermi and Gaussian limits and for attractive interactions the behavior of soliton solutions. We find that the disorder average spatial extension of the stationary density profile decreases with an increasing strength of the disordered potential both for repulsive and attractive interactions among bosons. In the Thomas Fermi limit, the suppression of transport is accompanied by a strong localization of the bosons around the state k=0 in momentum space. The time dependent density profiles differ considerably in the cases we have considered. For attractive Bose-Einstein condensates, a bright soliton exists with an overall unchanged shape, but a disorder dependent width. For weak disorder, the soliton moves on and for a stronger disorder, it bounces back and forth between high potential barriers.Comment: 13 pages, 13 figures, few typos correcte

Precision Charmonium Spectroscopy From Lattice QCD

We present results for Charmonium spectroscopy using Non-Relativistic QCD (NRQCD). For the NRQCD action the leading order spin-dependent and next to leading order spin-independent interactions have been included with tadpole-improved coefficients. We use multi-exponential fits to multiple correlation functions to extract ground and excited $S$ states. Splittings between the lowest $S$, $P$ and $D$ states are given and we have accurate values for the $S$ state hyperfine splitting and the $\chi_c$ fine structure. Agreement with experiment is good - the remaining systematic errors are discussed.Comment: 23 pages uuencoded latex file. Contains figures in late