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Contrasting pathways to tree longevity in gymnosperms and angiosperms
No full textTree longevity is thought to increase in growth-limiting, adverse environments, but a quantitative assessment of drivers of global variation in tree longevity is lacking. We assemble a global database of maximum longevity for 739 tree species and analyse associations between longevity and climate, soil, and species\u27 functional traits. Our results show two primary pathways towards long lifespans. The first is slow growth in resource-limited environments, consistent with the adversity begets longevity paradigm. The second pathway is through relief from abiotic constraints in productive environments. Despite notable exceptions, long-lived gymnosperms tend to follow the first path through slow growth in cold environments, whereas long-lived angiosperms tend to follow the second ( productivity ) path reaching maximum longevity generally in humid environments. For angiosperms, we identify two mechanisms for increased longevity under humid conditions. First, higher water availability increases species\u27 maximum tree height which is associated with greater longevities. Secondly, greater water availability increases stand density and inter-tree competition, limiting growth which may increase tree lifespan. The documented differences between gymnosperm and angiosperm longevity are likely rooted in intrinsic differences in hydraulic architecture that provide fitness advantages for gymnosperms under high abiotic stress, and for angiosperms under increased productivity or competition
Variability in Depth-mediated Shifts in Methanogen and Methanotroph Communities Across Tropical Andean Mountain Peatlands
No full textThe balance between methane producing and methane consuming microorganisms is partially responsible for the magnitude and direction of soil-atmosphere methane fluxes. Therefore, understanding the effects of vegetation and land use on relative abundance, community structure and vertical distribution of methane cycling microorganisms should help us interpret patterns of net emissions of methane. Mountain peatlands in the tropics are abundant and are important in global carbon cycling, but little is known about the communities of methane-cycling microorganisms in these ecosystems. We sampled peat from eight Andean peatlands in Peru, Ecuador and Colombia and described the dominant vegetation, grazing intensity and other site characteristics at each site. We characterised the microbial community of each peat sample at different depths and identified the methane cycling microorganisms. We observed a higher proportion of methanogens and methanogen:methanotroph in the shallow peat of grazed sites than ungrazed sites. At ungrazed sites we found relatively high methanotroph abundance relative to methanogens, even at the deepest sampling depths, suggesting plant aerenchymal oxygen transport structures communities at depth. We found changes in the methane cycling microbial communities among sites and with depth, e.g., in the superficial peat the hydrogenotrophic methanogens were more abundant but at depth there was more metabolic diversity. Our study provides new insights into the community structure of methane cycling microorganism of the tropical mountain peatlands, and raises interesting questions regarding the drivers of methanotroph abundance deeper in peat
Effect of Spatial Variability on Unconfined Compressive Strength of MICP-treated Soils
No full textSpatial variability has been identified as a major cause of uncertainties in determining the geotechnical properties of chemically and biologically treated soils. This can be attributed to the fact that in natural conditions, the grain and pore size distribution of soils exhibit sporadic spatial variation. This spatial variability, along with other factors, contributes to an uneven distribution of the stabilizing agents, resulting in further spatial variability in other properties of treated soils such as their strength. This paper aims to identify the extent to which spatial variability affects the strength of cylindrical soil samples that have been treated by the Microbially Induced Calcite Precipitation Method (MICP). A random finite volume method (RFVM) analysis was performed to simulate stress-strain behavior and the strength of MICP-treated soil samples to achieve this goal. In this RFVM model, the spatial variability in both the amount (percent by weight) and the extent (maximum precipitation distance from injection port) of precipitated calcite were considered. The results confirmed the adverse effects of both types of spatial variability on the stress-strain behavior and the peak (yield) stress of the treated samples. The results also showed that spatial variability in the extent of precipitated calcite plays a more significant role in the behavior of treated soils
The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics
Get PDFThe standard model of cosmology has provided a good phenomenological description of a wide range of observations both at astrophysical and cosmological scales for several decades. This concordance model is constructed by a universal cosmological constant and supported by a matter sector described by the standard model of particle physics and a cold dark matter contribution, as well as very early-time inflationary physics, and underpinned by gravitation through general relativity. There have always been open questions about the soundness of the foundations of the standard model. However, recent years have shown that there may also be questions from the observational sector with the emergence of differences between certain cosmological probes. In this White Paper, we identify the key objectives that need to be addressed over the coming decade together with the core science projects that aim to meet these challenges. These discordances primarily rest on the divergence in the measurement of core cosmological parameters with varying levels of statistical confidence. These possible statistical tensions may be partially accounted for by systematics in various measurements or cosmological probes but there is also a growing indication of potential new physics beyond the standard model. After reviewing the principal probes used in the measurement of cosmological parameters, as well as potential systematics, we discuss the most promising array of potential new physics that may be observable in upcoming surveys. We also discuss the growing set of novel data analysis approaches that go beyond traditional methods to test physical models. These new methods will become increasingly important in the coming years as the volume of survey data continues to increase, and as the degeneracy between predictions of different physical models grows. There are several perspectives on the divergences between the values of cosmological parameters, such as the model-independent probes in the late Universe and model-dependent measurements in the early Universe, which we cover at length. The White Paper closes with a number of recommendations for the community to focus on for the upcoming decade of observational cosmology, statistical data analysis, and fundamental physics developments. [Figure presented
Tuning the strength of exceptional points and their transition to diabolic points
No full textIn this work, we present a photonic scheme for controlling and tuning the strength of exceptional points (EPs) and their transition to diabolic points (DPs). The proposed scheme utilizes exceptional surface geometry in conjunction with a standard Mach–Zehnder interferometer to create a tunable mirror. The functionality of this structure is validated through full-wave simulations, demonstrating its potential for the dynamic manipulation of EPs and DPs. Importantly, our scheme can be implemented using standard on-chip photonics technology
Hourly Simulated Power Production Data with Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Single-Axis Tracking Systems in the U.S. Eastern Interconnection for Weather Year 2019
No full textUsing 2019 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata
Hourly Simulated Power Production Data with No Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Single-Axis Tracking Systems in the U.S. Eastern Interconnection for Weather Year 2022
No full textUsing 2022 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory\u27s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadat
Benchmarking Model Predictive Control and Reinforcement Learning-Based Control for Legged Robot Locomotion in MuJoCo Simulation
No full textModel Predictive Control (MPC) and Reinforcement Learning (RL) are two prominent strategies for controlling legged robots. RL learns control policies through system interaction, adapting to various scenarios, whereas MPC relies on a predefined mathematical model to solve optimization problems in real-time. Despite their widespread use, there is a lack of direct comparative analysis under standardized conditions. This work addresses this gap by benchmarking MPC and RL controllers on a Unitree Go1 quadruped robot within the MuJoCo simulation environment, focusing on a standardized task, straight walking at a constant velocity. Performance is evaluated based on disturbance rejection, energy efficiency, and terrain adaptability. The results show that RL excels in handling disturbances and maintaining energy efficiency but struggles with generalization to new terrains due to its dependence on learned policies tailored to specific environments. In contrast, MPC shows enhanced recovery capabilities from larger perturbations by leveraging its optimization-based approach, allowing for a balanced distribution of control efforts across the robot’s joints. The results present the advantages and limitations of both RL and MPC, offering insights into selecting an appropriate control strategy for legged robotic applications
Assessment of Sustainability of Locomotive Propulsion Technologies
No full textThe growing threat of global warming has created an urgent need to reduce the carbon footprint of transportation infrastructure. For the railroad industry, approximately 99% of the locomotives operate on diesel, which is a nonrenewable fossil fuel and can contribute considerable greenhouse gas emissions to the planet. The efforts to achieve sustainability are primarily focused on adopting cleaner fuel or electrifying existing railroads. This paper provides a comprehensive life cycle assessment (LCA) regarding the potential options. For alternative fuels, natural gas, biofuel, and hydrogen are considered. It was found that natural gas has the lowest life cycle cost, hydrogen can greatly lower the overall energy consumption, while biofuel is advantageous in reducing carbon footprint. For electrified railroads, the performance will largely depend on the type of power plants providing electricity. If the electricity of railroads is provided by a hydropower plant, the environmental impact will be reduced to a minimum. However, if the electricity is derived from hard coal, the carbon footprint will be even greater than conventional diesel locomotives. Social factors, such as stakeholder acceptance and safety concerns, although difficult to quantify, can also impact the adoption of certain propulsion technologies
Hourly Simulated Power Production Data with No Snow Loss Model at Existing Utility-Scale PV Sites (\u3e5 MW) in the U.S. Eastern Interconnection in 2019
No full textProject Summary: We ran PySAM power production simulations for utility-scale (\u3e5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2019. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory\u27s Utility-Scale Solar 2024 Edition dataset. See 2019_PV_existing_site_metadata.csv file for individual site metadata