Individual variation in plant traits drives species interactions, ecosystem functioning, and responses to global change

Ecologists have long sought to understand the processes that lead to the riotous diversity in communities of organisms that inhabit disparate climates and landscapes. Such a diversity of traits leads to a diversity of interactions among species in natural communities, which in turn generates a diversity of potential responses to ongoing global change. In this dissertation, I do three things: I explore the forces that structure plant communities and the ecosystem functions that they mediate, I describe patterns of variation among communities, species, and individual organisms across environmental contexts, and I disentangle the direct effects of global change from the indirect, cascading effects that result from disruptions of species interactions. I accomplish these goals through the synthesis of global data, the development of statistical and mathematical models, and the manipulation of global change drivers in field experiments. In the first chapter, I present a globe-spanning meta-analysis of plant functional trait patterns along elevational gradients. This meta-analysis shows that the plant traits that drive ecosystem function follow predictable trends with elevation due to climate filtering, and that much of this variation is at the level of the individual organism. In the second chapter, I present simulated data sets and illustrative experimental case studies that quantify how important individual-level variation is for explaining patterns in nature. In the third chapter, I present results from intensive plant sampling across a wide range of mountain environments; even in these harsh environments where only the hardiest species can survive, individual-level variation is so high that it makes predictions based on species identity nearly impossible. The fourth and fifth chapters consist of experimental evidence that ongoing human-caused global change is affecting montane plant communities, that species interactions mediate many of these effects, and that variation in the abiotic environment causes variation in both species interactions and in global change response. I demonstrate this through an experiment that combines nitrogen fertilization with removal of a dominant plant species in a montane meadow, and an experiment replicated at low and high elevations crossing dominant species removal with simulation of global warming

Study protocol for a randomised controlled trial of invasive versus conservative management of primary spontaneous pneumothorax

INTRODUCTION: Current management of primary spontaneous pneumothorax (PSP) is variable, with little evidence from randomised controlled trials to guide treatment. Guidelines emphasise intervention in many patients, which involves chest drain insertion, hospital admission and occasionally surgery. However, there is evidence that conservative management may be effective and safe, and it may also reduce the risk of recurrence. Significant questions remain regarding the optimal initial approach to the management of PSP

The non-relativistic geometric trinity of gravity

The geometric trinity of gravity comprises three distinct formulations of general relativity: (i) the standard formulation describing gravity in terms of spacetime curvature, (ii) the teleparallel equivalent of general relativity describing gravity in terms of spacetime torsion, and (iii) the symmetric teleparallel equivalent of general relativity (STEGR) describing gravity in terms of spacetime non-metricity. In this article, we complete a geometric trinity of non-relativistic gravity, by (a) taking the non-relativistic limit of STEGR to determine its non-relativistic analogue, and (b) demonstrating that this non-metric theory is equivalent to Newton–Cartan theory and its teleparallel equivalent, i.e., the curvature and the torsion based non-relativistic theories that are both geometrised versions of classical Newtonian gravity

Effects of ingested essential oils and propolis extracts on honey bee (Hymenoptera: Apidae) health and gut microbiota

Managed honey bee (Hymenoptera: Apidae: Apis mellifera Linnaeus) hives require frequent human inputs to maintain colony health and productivity. A variety of plant natural products (PNPs) are delivered via feeding to control diseases and reduce the use of synthetic chemical treatments. However, despite their prevalent use in beekeeping, there is limited information regarding the impact of ingested PNPs on bee health. Here, we tested the effects of different essential oils and propolis extracts on honey bee life span, nutrient assimilation, xenobiotic detoxification, and gut microbiota abundance. Brazilian propolis extract lengthened worker life span, while the other PNPs (Louisiana propolis extract, lemongrass oil, spearmint oil, and thyme oil) exerted variable and dose-dependent effects on life span. Vitellogenin (vg) gene expression was reduced by Brazilian propolis extract at high doses. Expression of CYP6AS1, a detoxification-related gene, was reduced by low doses of thyme oil. The abundances of 8 core gut microbiota taxa were largely unaffected by host consumption of PNPs. Our results suggest that in addition to propolis\u27s structural and immunomodulatory roles in the colony, it may also exert beneficial health effects when ingested. Thyme oil, a commonly used hive treatment, was toxic at field-realistic dosages, and its use as a feed additive should be viewed with caution until its effects on bee health are more thoroughly investigated. We conclude that the tested propolis extracts, lemongrass oil, and spearmint oil are generally safe for bee consumption, with some apparent health-promoting effects

Affine connections for Galilean and Carrollian structures: a unified perspective

We develop a classification of general Carrollian structures, permitting affine connections with both torsion and non-metricity. We compare with a recent classification of general Galilean structures in order to present a unified perspective on both. Moreover, we demonstrate how both sets of structures emerge from the most general possible Lorentzian structures in their respective limits, and we highlight the role of global hyperbolicity in constraining both structures. We then leverage this work in order to construct for the first time an ultra-relativistic geometric trinity of gravitational theories, and consider connections which are simultaneously compatible with Galilean and Carrollian structures. We close by outlining a number of open questions and future prospects

The Non-Relativistic Geometric Trinity of Gravity

The geometric trinity of gravity comprises three distinct formulations of general relativity: (i) the standard formulation which interprets gravity in terms of spacetime curvature, (ii) the teleparallel equivalent of general relativity which interprets gravity in terms of spacetime torsion, and (iii) the symmetric teleparallel equivalent of general relativity (STEGR) which interprets gravity in terms of spacetime non-metricity. In this article, we complete a non-relativistic geometric trinity of gravity, by (a) taking the non-relativistic limit of STEGR to determine its non-relativistic analogue, and (b) demonstrating that this non-metric theory is equivalent to Newton--Cartan theory and its teleparallel equivalent, i.e., the standard curvature and torsion based theories in the non-relativistic regime that are both geometrised versions of classical Newtonian gravity

The Non-Relativistic Geometric Trinity of Gravity

The geometric trinity of gravity comprises three distinct formulations of general relativity: (i) the standard formulation describing gravity in terms of spacetime curvature, (ii) the teleparallel equivalent of general relativity describing gravity in terms of spacetime torsion, and (iii) the symmetric teleparallel equivalent of general relativity (STEGR) describing gravity in terms of spacetime non-metricity. In this article, we complete a geometric trinity of non-relativistic gravity, by (a) taking the non-relativistic limit of STEGR to determine its non-relativistic analogue, and (b) demonstrating that this non-metric theory is equivalent to the Newton--Cartan theory and its teleparallel equivalent, i.e., the curvature and the torsion based non-relativistic theories that are both geometrised versions of classical Newtonian gravity

Mapping local and global variability in plant trait distributions

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration - specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∼50×50-km cells across the entire vegetated land surface. We do this in several ways - without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means

Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?

Aim: Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m).Location: Eastern USA.Time period: 2017– 2018.Taxa studied: Trees.Methods: With a fusion of hyperspectral and lidar data from the NEON AOP, we as-sess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics.Results: Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity.Main conclusions: We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine-resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above

Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing