Carbon transit through degradation networks

The decay of organic matter in natural ecosystems is controlled by a network of biologically, physically, and chemically driven processes. Decomposing organic matter is often described as a continuum that transforms and degrades over a wide range of rates, but it is difficult to quantify this heterogeneity in models. Most models of carbon degradation consider a network of only a few organic matter states that transform homogeneously at a single rate. These models may fail to capture the range of residence times of carbon in the soil organic matter continuum. Here we assume that organic matter is distributed among a continuous network of states that transform with stochastic, heterogeneous kinetics. We pose and solve an inverse problem in order to identify the rates of carbon exiting the underlying degradation network (exit rates) and apply this approach to plant matter decay throughout North America. This approach provides estimates of carbon retention in the network without knowing the details of underlying state transformations. We find that the exit rates are approximately lognormal, suggesting that carbon flow through a complex degradation network can be described with just a few parameters. These results indicate that the serial and feedback processes in natural degradation networks can be well approximated by a continuum of parallel decay rates.National Science Foundation (U.S.) (Grant EAR-0420592)United States. National Aeronautics and Space Administration (Grant NNA08CN84A

Inverse method for estimating respiration rates from decay time series

Long-term organic matter decomposition experiments typically measure the mass lost from decaying organic matter as a function of time. These experiments can provide information about the dynamics of carbon dioxide input to the atmosphere and controls on natural respiration processes. Decay slows down with time, suggesting that organic matter is composed of components (pools) with varied lability. Yet it is unclear how the appropriate rates, sizes, and number of pools vary with organic matter type, climate, and ecosystem. To better understand these relations, it is necessary to properly extract the decay rates from decomposition data. Here we present a regularized inverse method to identify an optimally-fitting distribution of decay rates associated with a decay time series. We motivate our study by first evaluating a standard, direct inversion of the data. The direct inversion identifies a discrete distribution of decay rates, where mass is concentrated in just a small number of discrete pools. It is consistent with identifying the best fitting "multi-pool" model, without prior assumption of the number of pools. However we find these multi-pool solutions are not robust to noise and are over-parametrized. We therefore introduce a method of regularized inversion, which identifies the solution which best fits the data but not the noise. This method shows that the data are described by a continuous distribution of rates, which we find is well approximated by a lognormal distribution, and consistent with the idea that decomposition results from a continuum of processes at different rates. The ubiquity of the lognormal distribution suggest that decay may be simply described by just two parameters: a mean and a variance of log rates. We conclude by describing a procedure that estimates these two lognormal parameters from decay data. Matlab codes for all numerical methods and procedures are provided

Emergent properties of heterogeneous decomposition networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 197-206).Organic matter respiration in natural ecosystems is controlled by a network of biologically, physically, and chemically driven processes. Often it is important to estimate total carbon flux from a degradation system or the decay of mass in the system as a function of time. Historically, mass dynamics are predicted by a compartmental model consisting of various degradation processes. This approach provides a complete picture of mass in the model system, but includes extra information unnecessary for modeling overall mass dynamics. Furthermore, these models quickly become highly parameterized and are kept tangible by reducing the number of processes and system states. This thesis suggests a different approach. I allow the degradation system to be inherently complex, but only consider a simple projection of the system necessary to characterize mass dynamics. Because decomposing organic matter is often described as a heterogeneous continuum which transforms and degrades over a wide range of rates, I model degradation as a network consisting of a large, quasi-continuum of states. The retention of carbon in the network is then estimated by using an eigenvalue projection to calculate the impulse response of the degradation system. For a continuous network, the impulse response can be expressed as a Laplace transform of an "exit rate function." I then pose and solve an inverse problem in order to identify the rates of exit of carbon from decomposing plant matter from across North America. Analysis of the calculated exit rate functions and their associated decay data suggest that plant matter decomposition can often be mathematically approximated by a continuum of parallel processes. Within this approximation, the solution of the inverse problem yields the discovery that exit rate functions are on average lognormal. This result suggests that the overall mass dynamics of complex decay networks often collapse to just two parameters: the mean and the variance of the order of magnitude of exit rates from the network. These parameters are then used to assess the effects of climate and litter chemistry on organic carbon turnover and on rate heterogeneity. I also use observed patterns to explain the effect of natural selection in microbial communities on degradation network kinetics.by David C. Forney, III.Ph.D

Diffusion in an absorbing porous medium : from microscopic geometry to macroscopic transport

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 71-73).Two physical models of diffusion in absorbing porous media are proposed on two length scales. One models diffusion in the pore space of a random medium with absorbing interfaces while the other is a reaction diffusion model where particles are absorbed in the bulk. Typical particle traveling distances and a bulk absorption coefficient are described in terms of general geometrical characteristics of a random medium and the analytical relations are found to compare well with numerical experiments. For the case of geometries consisting of randomly placed cubes, absorption in the bulk scales with the solid fraction to the two-thirds power. The statistical distribution of reaction rates in these models is found to be inversely related to the reaction rate. A quasi-static Monte-Carlo model is also investigated. The more complex problem of microbial extracellular enzyme distributions in marine sediment was an inspiration for this work.by David C. Forney, III.S.M

Optimal and Efficient Decoding of Concatenated Quantum Block Codes

We consider the problem of optimally decoding a quantum error correction code -- that is to find the optimal recovery procedure given the outcomes of partial "check" measurements on the system. In general, this problem is NP-hard. However, we demonstrate that for concatenated block codes, the optimal decoding can be efficiently computed using a message passing algorithm. We compare the performance of the message passing algorithm to that of the widespread blockwise hard decoding technique. Our Monte Carlo results using the 5 qubit and Steane's code on a depolarizing channel demonstrate significant advantages of the message passing algorithms in two respects. 1) Optimal decoding increases by as much as 94% the error threshold below which the error correction procedure can be used to reliably send information over a noisy channel. 2) For noise levels below these thresholds, the probability of error after optimal decoding is suppressed at a significantly higher rate, leading to a substantial reduction of the error correction overhead.Comment: Published versio

Common structure in the heterogeneity of plant-matter decay

Carbon removed from the atmosphere by photosynthesis is released back by respiration. Although some organic carbon is degraded quickly, older carbon persists; consequently carbon stocks are much larger than predicted by initial decomposition rates. This disparity can be traced to a wide range of first-order decay-rate constants, but the rate distributions and the mechanisms that determine them are unknown. Here, we pose and solve an inverse problem to find the rate distributions corresponding to the decomposition of plant matter throughout North America. We find that rate distributions are lognormal, with a mean and variance that depend on climatic conditions and substrate. Changes in temperature and precipitation scale all rates similarly, whereas the initial substrate composition sets the time scale of faster rates. These findings probably result from the interplay of stochastic processes and biochemical kinetics, suggesting that the intrinsic variability of decomposers, substrate and environment results in a predictable distribution of rates. Within this framework, turnover times increase exponentially with the kinetic heterogeneity of rates, thereby providing a theoretical expression for the persistence of recalcitrant organic carbon in the natural environment

Epigenetic and transcriptional dysregulation in CD4+ T cells in patients with atopic dermatitis

Atopic dermatitis (AD) is one of the most common skin disorders among children. Disease etiology involves genetic and environmental factors, with 29 independent AD risk loci enriched for risk allele-dependent gene expression in the skin and CD4+ T cell compartments. We investigated the potential epigenetic mechanisms responsible for the genetic susceptibility of CD4+ T cells. To understand the differences in gene regulatory activity in peripheral blood T cells in AD, we measured chromatin accessibility (an assay based on transposase-accessible chromatin sequencing, ATAC-seq), nuclear factor kappa B subunit 1 (NFKB1) binding (chromatin immunoprecipitation with sequencing, ChIP-seq), and gene expression levels (RNA-seq) in stimulated CD4+ T cells from subjects with active moderate-to-severe AD, as well as in age-matched non-allergic controls. Open chromatin regions in stimulated CD4+ T cells were highly enriched for AD genetic risk variants, with almost half of the AD risk loci overlapping AD-dependent ATAC-seq peaks. AD-specific open chromatin regions were strongly enriched for NF-κB DNA-binding motifs. ChIP-seq identified hundreds of NFKB1-occupied genomic loci that were AD- or control-specific. As expected, the AD-specific ChIP-seq peaks were strongly enriched for NF-κB DNA-binding motifs. Surprisingly, control-specific NFKB1 ChIP-seq peaks were not enriched for NFKB1 motifs, but instead contained motifs for other classes of human transcription factors, suggesting a mechanism involving altered indirect NFKB1 binding. Using DNA sequencing data, we identified 63 instances of altered genotype-dependent chromatin accessibility at 36 AD risk variant loci (30% of AD risk loci) that might lead to genotype-dependent gene expression. Based on these findings, we propose that CD4+ T cells respond to stimulation in an AD-specific manner, resulting in disease- and genotype-dependent chromatin accessibility alterations involving NFKB1 binding

Laboratory demonstration of a prozone-like effect in HRP2-detecting malaria rapid diagnostic tests: implications for clinical management

Background: Malaria rapid diagnostic tests (RDTs) are now widely used for prompt on-site diagnosis in remote endemic areas where reliable microscopy is absent. Aberrant results, whereby negative test results occur at high parasite densities, have been variously reported for over a decade and have led to questions regarding the reliability of the tests in clinical use. Methods. In the first trial, serial dilutions of recombinant HRP2 antigen were tested on an HRP2-detectiing RDT. In a second trial, serial dilutions of culture-derived Plasmodium falciparum parasites were tested against three HRP2-detecting RDTs. Results: A prozone-like effect occurred in RDTs at a high concentration of the target antigen, histidine-rich protein-2 (above 15,000 ng/ml), a level that corresponds to more than 312000 parasites per L. Similar results were noted on three RDT products using dilutions of cultured parasites up to a parasite density of 25%. While reduced line intensity was observed, no false negative results occurred. Conclusions: These results suggest that false-negative malaria RDT results will rarely occur due to a prozone-like effect in high-density infections, and other causes are more likely. However, RDT line intensity is poorly indicative of parasite density in high-density infections and RDTs should, therefore, not be considered quantitative. Immediate management of suspected severe malaria should rely on clinical assessment or microscopy. Evaluation against high concentrations of antigen should be considered in malaria RDT product development and lot-release testing, to ensure that very weak or false negative results will not occur at antigen concentrations that might be seen clinically