Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling

Dormancy is an essential strategy for microorganisms to cope with environmental stress. However, global ecosystem models typically ignore microbial dormancy, resulting in major model uncertainties. To facilitate the consideration of dormancy in these large-scale models, we propose a new microbial physiology component that works for a wide range of substrate availabilities. This new model is based on microbial physiological states and is majorly parameterized with the maximum specific growth and maintenance rates of active microbes and the ratio of dormant to active maintenance rates. A major improvement of our model over extant models is that it can explain the low active microbial fractions commonly observed in undisturbed soils. Our new model shows that the exponentially-increasing respiration from substrate-induced respiration experiments can only be used to determine the maximum specific growth rate and initial active microbial biomass, while the respiration data representing both exponentially-increasing and non-exponentially-increasing phases can robustly determine a range of key parameters including the initial total live biomass, initial active fraction, the maximum specific growth and maintenance rates, and the half-saturation constant. Our new model can be incorporated into existing ecosystem models to account for dormancy in microbially-mediated processes and to provide improved estimates of microbial activities.Comment: 38 pages, 2 Tables, 4 Figure

Exact 1-D Model for Coherent Synchrotron Radiation with Shielding and Bunch Compression

Coherent Synchrotron Radiation has been studied effectively using a 1-dimensional model for the charge distribution in the realm of small angle approximations and high energies. Here we use Jefimenko's form of Maxwell's equations, without such approximations, to calculate the exact wake-fields due to this effect in multiple bends and drifts. It has been shown before that the influence of a drift can propagate well into a subsequent bend. We show, for reasonable parameters, that the influence of a previous bend can also propagate well into a subsequent bend, and that this is especially important at the beginning of a bend. Shielding by conducting parallel plates is simulated using the image charge method. We extend the formalism to situations with compressing and decompressing distributions, and conclude that simpler approximations to bunch compression usually overestimates the effect. Additionally, an exact formula for the coherent power radiated by a Gaussian bunch is derived by considering the coherent synchrotron radiation spectrum, and is used to check the accuracy of wake-field calculations

Extended 1D Method for Coherent Synchrotron Radiation including Shielding

Coherent Synchrotron Radiation can severely limit the performance of accelerators designed for high brightness and short bunch length. Examples include light sources based on ERLs or FELs, and bunch compressors for linear colliders. In order to better simulate Coherent Synchrotron Radiation, the established 1-dimensional formalism is extended to work at lower energies, at shorter bunch lengths, and for an arbitrary configuration of multiple bends. Wide vacuum chambers are simulated by means of vertical image charges. This formalism has been implemented in the general beam dynamics code "Bmad" and its results are here compared to analytical approximations, to numerical solutions of the Maxwell equations, and to the simulation code "elegant"

Going beyond the green : senesced vegetation material predicts basal area and biomass in remote sensing of tree cover conditions in an African tropical dry forest (miombo woodland) landscape

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Research Letters 12 (2017): 085004, doi:10.1088/1748-9326/aa7242.In sub-Saharan Africa (SSA), tropical dry forests and savannas cover over 2.5 million km2 and support livelihoods for millions in fast-growing nations. Intensifying land use pressures have driven rapid changes in tree cover structure (basal area, biomass) that remain poorly characterized at regional scales. Here, we posed the hypothesis that tree cover structure related strongly to senesced and non-photosynthetic (NPV) vegetation features in a SSA tropical dry forest landscape, offering improved means for satellite remote sensing of tree cover structure compared to vegetation greenness-based methods. Across regrowth miombo woodland sites in Tanzania, we analyzed relationships among field data on tree structure, land cover, and satellite indices of green and NPV features based on spectral mixture analyses and normalized difference vegetation index calculated from Landsat 8 data. From satellite-field data relationships, we mapped regional basal area and biomass using NPV and greenness-based metrics, and compared map performances at landscape scales. Total canopy cover related significantly to stem basal area (r 2 = 0.815, p  60%) at all sites. From these two conditions emerged a key inverse relationship: skyward exposure of NPV ground cover was high at sites with low tree basal area and biomass, and decreased with increasing stem basal area and biomass. This pattern scaled to Landsat NPV metrics, which showed strong inverse correlations to basal area (Pearson r = −0.85, p < 0.01) and biomass (r = −0.86, p < 0.01). Biomass estimates from Landsat NPV-based maps matched field data, and significantly differentiated landscape gradients in woody biomass that greenness metrics failed to track. The results suggest senesced vegetation metrics at Landsat scales are a promising means for improved monitoring of tree structure across disturbance and ecological gradients in African and other tropical dry forests.The project was funded by the US National Science Foundation Partnerships for International Research and Education (PIRE) program, project title 'Ecosystems and Human Well-Being' (Award # 0968211) PI Chris Neill. Additional research and dissertation support was provided to Marc Mayes from Brown University

Nitrogen cycle patterns during forest regrowth in an African Miombo woodland landscape

Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Biogeosciences, 124(6), (2019): 1591-1603, doi:10.1029/2018JG004803.Tropical dry forests in eastern and southern Africa cover 2.5 × 106 km2, support wildlife habitat and livelihoods of more than 150 million people, and face threats from land use and climate change. To inform conservation, we need better understanding of ecosystem processes like nutrient cycling that regulate forest productivity and biomass accumulation. Here we report on patterns in nitrogen (N) cycling across a 100‐year forest regrowth chronosequence in the Tanzanian Miombo woodlands. Soil and vegetation indicators showed that low ecosystem N availability for trees persisted across young to mature forests. Ammonium dominated soil mineral N pools from 0‐ to 15‐cm depth. Laboratory‐measured soil N mineralization rates across 3‐ to 40‐year regrowth sites showed no significant trends and were lower than mature forest rates. Aboveground tree N pools increased at 6 to 7 kg N·ha−1·yr−1, accounting for the majority of ecosystem N accumulation. Foliar δ15N <0‰ in an N‐fixing canopy tree across all sites suggested that N fixation may contribute to ecosystem N cycle recovery. These results contrast N cycling in wetter tropical and Neotropical dry forests, where indicators of N scarcity diminish after several decades of regrowth. Our findings suggest that minimizing woody biomass removal, litter layer, and topsoil disturbance may be important to promote N cycle recovery and natural regeneration in Miombo woodlands. Higher rates of N mineralization in the wet season indicated a potential that climate change‐altered rainfall leading to extended dry periods may lower N availability through soil moisture‐dependent N mineralization pathways, particularly for mature forests.This study depended on the knowledge, insights, and cooperation of many people and institutions. We thank the Millennium Villages Project‐Mbola site for providing introductions to the landscape and village headmen in many regions. We thank the ARI‐Tumbi staff (now TARI‐Tumbi) in Tabora, Tanzania for providing invaluable logistical support in identifying forest regrowth sites and help with labwork in Tabora, Tanzania. We thank other key local organizations, including Tabora Development Foundation Trust (Dick Mlimuka, Oscar Kisanji) and Tanzania Forest Service (Bw. Relingo), for logistical support and transportation. We thank many village headmen and farmers for access to forest sites within their lands for sampling. Finally, we would like to thank the MBL Stable Isotope laboratory and Dr. Marshall Otter for his expertise with producing and interpreting soil and leaf C, N and stable isotope data. This study was funded in part by NSF PIRE Grant OISE 0968211, a Dissertation Support Grant to Marc Mayes from Brown University (2015–2016), and completed with permission and cooperation from the Tanzania Commission on Science and Technology (COSTECH permits 2013‐261‐NA‐2014‐199 and 2015‐183‐ER‐2014‐199). Data and code for analyses can be accessed at a Github repository: https://github.com/mtm17/MiomboN.git.2019-11-0

Generalizing Microbial Parameters in Soil Biogeochemical Models: Insights From a Multi‐Site Incubation Experiment

Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case-specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial-ENzyme Decomposition model, this study aimed to test whether a common set of microbially-relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two-year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial-relevant parameters for large-scale soil model projections