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

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

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

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

Towards connecting biodiversity and geodiversity across scales with satellite remote sensing

Issue Geodiversity (i.e., the variation in Earth\u27s abiotic processes and features) has strong effects on biodiversity patterns. However, major gaps remain in our understanding of how relationships between biodiversity and geodiversity vary over space and time. Biodiversity data are globally sparse and concentrated in particular regions. In contrast, many forms of geodiversity can be measured continuously across the globe with satellite remote sensing. Satellite remote sensing directly measures environmental variables with grain sizes as small as tens of metres and can therefore elucidate biodiversity–geodiversity relationships across scales. Evidence We show how one important geodiversity variable, elevation, relates to alpha, beta and gamma taxonomic diversity of trees across spatial scales. We use elevation from NASA\u27s Shuttle Radar Topography Mission (SRTM) and c. 16,000 Forest Inventory and Analysis plots to quantify spatial scaling relationships between biodiversity and geodiversity with generalized linear models (for alpha and gamma diversity) and beta regression (for beta diversity) across five spatial grains ranging from 5 to 100 km. We illustrate different relationships depending on the form of diversity; beta and gamma diversity show the strongest relationship with variation in elevation. Conclusion With the onset of climate change, it is more important than ever to examine geodiversity for its potential to foster biodiversity. Widely available satellite remotely sensed geodiversity data offer an important and expanding suite of measurements for understanding and predicting changes in different forms of biodiversity across scales. Interdisciplinary research teams spanning biodiversity, geoscience and remote sensing are well poised to advance understanding of biodiversity–geodiversity relationships across scales and guide the conservation of nature

Fire Promotes Pollinator Visitation: Implications for Ameliorating Declines of Pollination Services

Pollinators serve critical roles for the functioning of terrestrial ecosystems, and have an estimated annual value of over $150 billion for global agriculture. Mounting evidence from agricultural systems reveals that pollinators are declining in many regions of the world, and with a lack of information on whether pollinator communities in natural systems are following similar trends, identifying factors which support pollinator visitation and services are important for ameliorating the effects of the current global pollinator crisis. We investigated how fire affects resource structure and how that variation influences floral pollinator communities by comparing burn versus control treatments in a southeastern USA old-field system. We hypothesized and found a positive relationship between fire and plant density of a native forb, Verbesina alternifolia, as well as a significant difference in floral visitation of V. alternifolia between burn and control treatments. V. alternifolia density was 44% greater and floral visitation was 54% greater in burned treatments relative to control sites. When the density of V. alternifolia was experimentally reduced in the burn sites to equivalent densities observed in control sites, floral visitation in burned sites declined to rates found in control sites. Our results indicate that plant density is a proximal mechanism by which an imposed fire regime can indirectly impact floral visitation, suggesting its usefulness as a tool for management of pollination services. Although concerns surround the negative impacts of management, indirect positive effects may provide an important direction to explore for managing future ecological and conservation issues. Studies examining the interaction among resource concentration, plant apparency, and how fire affects the evolutionary consequences of altered patterns of floral visitation are overdue. DOI: 10.1371/journal.pone.007985

Conservative versus interventional treatment for spontaneous pneumothorax

BACKGROUND: Whether conservative management is an acceptable alternative to interventional management for uncomplicated, moderate-to-large primary spontaneous pneumothorax is unknown. METHODS: In this open-label, multicenter, noninferiority trial, we recruited patients 14 to 50 years of age with a first-known, unilateral, moderate-to-large primary spontaneous pneumothorax. Patients were randomly assigned to immediate interventional management of the pneumothorax (intervention group) or a conservative observational approach (conservative-management group) and were followed for 12 months. The primary outcome was lung reexpansion within 8 weeks. RESULTS: A total of 316 patients underwent randomization (154 patients to the intervention group and 162 to the conservative-management group). In the conservative-management group, 25 patients (15.4%) underwent interventions to manage the pneumothorax, for reasons prespecified in the protocol, and 137 (84.6%) did not undergo interventions. In a complete-case analysis in which data were not available for 23 patients in the intervention group and 37 in the conservative-management group, reexpansion within 8 weeks occurred in 129 of 131 patients (98.5%) with interventional management and in 118 of 125 (94.4%) with conservative management (risk difference, -4.1 percentage points; 95% confidence interval [CI], -8.6 to 0.5; P = 0.02 for noninferiority); the lower boundary of the 95% confidence interval was within the prespecified noninferiority margin of -9 percentage points. In a sensitivity analysis in which all missing data after 56 days were imputed as treatment failure (with reexpansion in 129 of 138 patients [93.5%] in the intervention group and in 118 of 143 [82.5%] in the conservative-management group), the risk difference of -11.0 percentage points (95% CI, -18.4 to -3.5) was outside the prespecified noninferiority margin. Conservative management resulted in a lower risk of serious adverse events or pneumothorax recurrence than interventional management. CONCLUSIONS: Although the primary outcome was not statistically robust to conservative assumptions about missing data, the trial provides modest evidence that conservative management of primary spontaneous pneumothorax was noninferior to interventional management, with a lower risk of serious adverse events. (Funded by the Emergency Medicine Foundation and others; PSP Australian New Zealand Clinical Trials Registry number, ACTRN12611000184976.)

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Evidence from Individual Inference for High-Dimensional Coexistence: Long-Term Experiments on Recruitment Response

Background: For competing species to coexist, individuals must compete more with others of the same species than with those of other species. Ecologists search for tradeoffs in how species might partition the environment. The negative correlations among competing species that would be indicative of tradeoffs are rarely observed. A recent analysis showed that evidence for partitioning the environment is available when responses are disaggregated to the individual scale, in terms of the covariance structure of responses to environmental variation. That study did not relate that variation to the variables to which individuals were responding. To understand how this pattern of variation is related to niche variables, we analyzed responses to canopy gaps, long viewed as a key variable responsible for species coexistence. Methodology/Principal Findings: A longitudinal intervention analysis of individual responses to experimental canopy gaps with 12 yr of pre-treatment and 8 yr post-treatment responses showed that species-level responses are positively correlated – species that grow fast on average in the understory also grow fast on average in response to gap formation. In other words, there is no tradeoff. However, the joint distribution of individual responses to understory and gap showed a negative correlation – species having individuals that respond most to gaps when previously growing slowly also have individuals that respond least to gaps when previously growing rapidly (e.g., Morus rubra), and vice versa (e.g., Quercus prinus). Conclusions/Significance: Because competition occurs at the individual scale, not the species scale, aggregated speciesleve