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Partitioning CO2 fluxes with isotopologue measurements and modeling to understand mechanisms of forest carbon sequestration

1. Objectives This project combines automated in situ observations of the isotopologues of CO2 with root observations, novel experimental manipulations of belowground processes, and isotope-enabled ecosystem modeling to investigate mechanisms of below- vs. aboveground carbon sequestration at the Harvard Forest Environmental Measurements Site (EMS). The proposed objectives, which have now been largely accomplished, include: A. Partitioning of net ecosystem CO2 exchange (NEE) into photosynthesis and respiration using long-term continuous observations of the isotopic composition of NEE, and analysis of their dynamics ; B. Investigation of the influence of vegetation phenology on the timing and magnitude of carbon allocated belowground using measurements of root growth and indices of belowground autotrophic vs. heterotrophic respiration (via trenched plots and isotope measurements); C. Testing whether plant allocation of carbon belowground stimulates the microbial decomposition of soil organic matter, using in situ rhizosphere simulation experiments wherein realistic quantities of artificial isotopically-labeled exudates are released into the soil; and D. Synthesis and interpretation of the above data using the Ecosystem Demography Model 2 (ED2). 2. Highlights Accomplishments: • Our isotopic eddy flux record has completed its 5th full year and has been used to independently estimate ecosystem-scale respiration and photosynthesis. • Soil surface chamber isotopic flux measurements were carried out during three growing seasons, in conjunction with a trenching manipulation. Key findings to date (listed by objective): A. Partitioning of Net Ecosystem Exchange: 1. Ecosystem respiration is lower during the day than at night—the first robust evidence of the inhibition of leaf respiration by light (the “Kok effect”) at the ecosystem scale. 2. Because it neglects the Kok effect, the standard NEE partitioning approach overestimates ecosystem photosynthesis (by ~25%) and daytime respiration (by ~100%) in the first half of the growing season at our site, and portrays ecosystem photosynthetic light-use efficiency as declining when in fact it is stable until autumnal senescence. B. Vegetation Phenology and belowground allocation: Findings: 1. Autotrophic respiration (Ra) showed a seasonal pattern, peaking in mid-summer when trees were most active. 2. The effective age of the substrate for belowground respiration is less than 2 weeks. 3. Above and belowground phenology are more synchronous in deciduous hardwood stands than evergreen hemlock stands. 4. The decline in root respiration rates in the fall is related to temperature rather than acclimation of root respiration or substrate limitations. Methodological Issues: 5. The isotopic signatures of autotrophic and heterotrophic respiration are too similar for isotopic partitioning of belowground respiration into these two components at our site—in keeping with the recent findings of Bowling et al. (2015) in a subalpine conifer forest. 6. Artifacts of the trenching method, such as changes in soil moisture and increased carbon substrate from the newly severed roots, are significant and need to be quantified when determining daily to annual estimates of autotrophic and heterotrophic respiration. C. Effects of simulated exudates on priming of microbial decomposition: The stoichiometry of root exudates influences both the amount and the mechanism by which priming occurs. At low C:N, SOC loss is caused by an increase in microbial efficiency. At high C:N, SOC loss is caused by an increase in microbial biomass. D. Modeling with the Ecosystem Demography Model (ED2): 1. Incorporation of 13C tracking to create an isotopically-enabled Ecosystem Demography v2 model (ED2) 2. State-of-the-art parameter optimization methodology developed for improving ED2 model predictions and parameters. 3. Significantly improved model predictions of growth- and maintenance-related carbon fluxes and 13C fluxes

54 ENVIRONMENTAL SCIENCES↗

Factors for Microbial Carbon Sources in Organic and Mineral Soils from Eastern United States Deciduous Forests

Forest soils represent a large portion of global terrestrial carbon; however, which soil carbon sources are used by soil microbes and respired as carbon dioxide (CO2) is not well known. This study will focus on characterizing microbial carbon sources from organic and mineral soils from four eastern United States deciduous forests using a unique radiocarbon (14C) tracer. Results from the dark incubation of organic and mineral soils are heavily influenced by site characteristics when incubated at optimal microbial activity temperature. Sites with considerable differences in temperature, texture, and location differ in carbon source attribution, indicating that site characteristics play a role in soil respiration.

14C↗

Water-carbon Links in a Tropical Forest: How Interbasin Groundwater Flow Affects Carbon Fluxes and Ecosystem Carbon Budgets

This report covers the outcomes from a quantitative, interdisciplinary field investigation of how carbon fluxes and budgets in a lowland tropical rainforest are affected by the discharge of old regional groundwater into streams, springs, and wetlands in the forest. The work was carried out in a lowland rainforest of Costa Rica, at La Selva Biological Station. The research shows that discharge of regional groundwater high in dissolved carbon dioxide represents a significant input of carbon to the rainforest "from below", an input that is on average larger than the carbon input "from above" from the atmosphere. A stream receiving discharge of regional groundwater had greatly elevated emissions of carbon dioxide (but not methane) to the overlying air, and elevated downstream export of carbon from its watershed with stream flow. The emission of deep geological carbon dioxide from stream water elevates the carbon dioxide concentrations in air above the streams. Carbon-14 tracing revealed the presence of geological carbon in the leaves and stems of some riparian plants near streams that receive inputs of regional groundwater. Also, discharge of regional groundwater is responsible for input of dissolved organic matter with distinctive chemistry to rainforest streams and wetlands. The discharge of regional groundwater in lowland surface waters has a major impact on the carbon cycle in this and likely other tropical and non-tropical forests.

54 ENVIRONMENTAL SCIENCES↗

Brazil-USA Collaborative Research: Modifications by Anthropogenic Pollution of the Natural Atmospheric Chemistry and Particle Microphysics of the Tropical Rain Forest During the GoAmazon Intensive Operating Periods (IOPs)

Manaus, a city of nearly two million people, represents an isolated urban area having a distinct urban pollution plume within the otherwise pristine Amazon Basin. The plume has high concentrations of oxides of nitrogen and sulfur, carbon monoxide, particle concentrations, and soot, among other pollutants. Critically, the distinct plume in the setting of the surrounding tropical rain forest serves as a natural laboratory to allow direct comparisons between periods of pollution influence to those of pristine conditions. The funded activity of this report is related to the Brazil-USA collaborative project during the two Intensive Operating Periods (wet season, 1 Feb - 31 Mar 2014; dry season, 15 Aug - 15 Oct 2014) of GoAmazon2014/5. The project addresses key science questions regarding the modification of the natural atmospheric chemistry and particle microphysics of the forest by present and future anthropogenic pollution. The first objective of the project was to understand and quantify the interactions of biogenic and anthropogenic emissions with respect to the production of secondary organic material. In clean conditions in the Amazon basin, secondary organic material dominates the diameter distribution of the submicron particles. How and why is the diameter distribution shifted by pollution? The second objective followed from the first in that, although the diameter distribution is dominated by secondary organic material, the actual source of new particle production remains uncertain (i.e., the number concentration). The second objective was to test the hypothesis that new particles under natural conditions are produced as a result of evaporation of primary particles emitted by fungal spores as well as to investigate any shifts in this mechanism under pollution conditions, e.g., in consequence to the high concentrations of SO 2 in the pollution plume. Combined, the number-diameter distribution is the key connection to upscaling to the effects of aerosol particles on clouds and climate. Understanding this upscaling under clean and pollution conditions, including differences, was the third objective.

54 ENVIRONMENTAL SCIENCES↗

Brazil-USA Collaborative Research: Modifications by Anthropogenic Pollution of the Natural Atmospheric Chemistry and Particle Microphysics of the Tropical Rain Forest During the GoAmazon Intensive Operating Periods (IOPs)

Manaus, a city of nearly two million people, represents an isolated urban area having a distinct urban pollution plume within the otherwise pristine Amazon Basin. The plume has high concentrations of oxides of nitrogen and sulfur, carbon monoxide, particle concentrations, and soot, among other pollutants. Critically, the distinct plume in the setting of the surrounding tropical rain forest serves as a natural laboratory to allow direct comparisons between periods of pollution influence to those of pristine conditions. The funded activity of this report is related to the Brazil-USA collaborative project during the two Intensive Operating Periods (wet season, 1 Feb - 31 Mar 2014; dry season, 15 Aug - 15 Oct 2014) of GoAmazon2014/5. The project addresses key science questions regarding the modification of the natural atmospheric chemistry and particle microphysics of the forest by present and future anthropogenic pollution.

54 ENVIRONMENTAL SCIENCES↗

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land-surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land-atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow-to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land-atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

54 ENVIRONMENTAL SCIENCES↗

Core Model Proposal #338: Regional Forest Markets and Crop Trade Updates

The main purpose of this proposal is to update the forest (i.e., Roundwood) trade modeling in GCAM from HOV (Heckscher-Ohlin Vanek) based fully integrated world market to segmented regional markets using the logit-based Armington approach. We also improve agricultural trade-related data, update trade (Armington) parameters based on literature information, and allow elastic forest demand responses. This CMP is an extension of previous GCAM agricultural trade CMPs (289 & 312).

99 GENERAL AND MISCELLANEOUS↗

Differential Organic Carbon Mineralization Responses to Soil Moisture in Three Different Soil Orders Under Mixed Forested System: Supporting Data

This data contains data from 90-day long incubation study which aimed to look at the soil moisture-texture relationship on soil organic carbon (SOC) cycling. Soils were collected from three distinct soil textures from mixed forests in 2017: sandy (Georgia, 2017-05-01), loamy (Missouri, 2017-06-14) and clayey (Texas, December 2017) were incubated at different soil moisture levels (air-dried, 25% water holding capacity (WHC), 50% WHC, 100% WHC and 175% WHC) at room temperature for a period of 90 days. Files contain microbial respiration, active and slow SOC pools, and their respective mineralization rates, extractable organic carbon (C), and C-acquiring extracellular enzymes. Findings from these data were used in Singh et al. (2021). This study aimed to examine the interactive effect of soil moisture and texture on SOC mineralization. Soil samples of three distinct textures (sandy, loamy, and clayey) were collected from mixed forests of Georgia, Missouri, and Texas, respectively. Soil cores of 5 cm diameter were collected from numerous random locations at each site from 0-15 cm depth after scraping the litter layer and mixed thoroughly to obtain a composite sample per site. Three additional soil cores were collected to determine the WHC using pressure plate extractors. Soil samples were composited, and triplicate soil samples were incubated in mason jars for a period of 90 days at room temperature under different moisture regimes: air dried, 25% WHC, 50% WHC, at WHC and 100% saturation. Soil respiration was measured weekly, and destructive sampling was conducted at 1, 15, 60, and 90 days to determine extractable organic C, C acquiring enzyme activity, and active and slow SOC pools with their respective mineralization rates. The C acquiring enzyme activity was the total activity of α-glucosidase, β-glucosidase, cellobiohydrolase, and β-xylosidase enzymes. Gas samples for microbial respiration measurements were collected from headspace of incubation jars through the sampling ports on the lids and then analyzed using a Shimadzu Gas Chromatograph (GC-2014). Prior to sampling, the vials were evacuated. Blank correction was also done by collecting gas samples from empty incubation jars. Double pool exponential decay model was used in SigmaPlot to determine the active and slow SOC pools and their mineralization rates (Farrar et al., 2012; Jagadamma et al., 2014). The C-acquiring extracellular enzymes were measured using the microplate method by German et al., (2011). Microbial community structure was determined using the phospholipid fatty acid (PLFA) and neutral lipid fatty acid (NLFA) analyses (Buyer and Sasser, 2012). This dataset has seven data files provided in comma-separate (*.csv) format. Additional metadata are provided: seven data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

Carbon acquiring enzyme activity↗

The Transcriptional Response of Soil Bacteria to Long-Term Warming and Short-Term Seasonal Fluctuations in a Terrestrial Forest

Terrestrial ecosystems are an important carbon store, and this carbon is vulnerable to microbial degradation with climate warming. After 30 years of experimental warming, carbon stocks in a temperate mixed deciduous forest were observed to be reduced by 30% in the heated plots relative to the controls. In addition, soil respiration was seasonal, as was the warming treatment effect. We therefore hypothesized that long-term warming will have higher expressions of genes related to carbohydrate and lipid metabolism due to increased utilization of recalcitrant carbon pools compared to controls. Because of the seasonal effect of soil respiration and the warming treatment, we further hypothesized that these patterns will be seasonal. We used RNA sequencing to show how the microbial community responds to long-term warming (~30 years) in Harvard Forest, MA. Total RNA was extracted from mineral and organic soil types from two treatment plots (+5°C heated and ambient control), at two time points (June and October) and sequenced using Illumina NextSeq technology. Treatment had a larger effect size on KEGG annotated transcripts than on CAZymes, while soil types more strongly affected CAZymes than KEGG annotated transcripts, though effect sizes overall were small. Although, warming showed a small effect on overall CAZymes expression, several carbohydrate-associated enzymes showed increased expression in heated soils (~68% of all differentially expressed transcripts). Further, exploratory analysis using an unconstrained method showed increased abundances of enzymes related to polysaccharide and lipid metabolism and decomposition in heated soils. Compared to long-term warming, we detected a relatively small effect of seasonal variation on community gene expression. Together, these results indicate that the higher carbohydrate degrading potential of bacteria in heated plots can possibly accelerate a self-reinforcing carbon cycle-temperature feedback in a warming climate.

54 ENVIRONMENTAL SCIENCES↗

Detection of Extreme Phenomena in the Stable Boundary Layer over the Amazonian Forest

We apply different methods for detection of extreme phenomena (EP) in air-turbulent time series measured in the nocturnal boundary layer above the Amazon forest. The methods used were: (a) a Morlet complex wavelet transform, which is often used in analysis of non-linear application processes. Through the use of the wavelet, it is possible to observe a phase singularity that involves a strong interaction between an extensive range of scales; (b) recurrence plot tests, which were used to identify a sudden change between different stable atmospheric states. (c) statistical analysis of early-warning signals, which verify simultaneous increases in the autocorrelation function and in the variance in the state variable; and (d) analysis of wind speed versus turbulent kinetic energy to identify different turbulent regimes in the stable boundary layer. We found it is adequate to use a threshold to classify the cases of strong turbulence regime, as a result of the occurrence of EP in the tropical atmosphere. All methods used corroborate and indicate synergy between events that culminate in what we classify as EP of the stable boundary layer above the tropical forest.

54 ENVIRONMENTAL SCIENCES↗

Life-cycle energy and GHG emissions of forest biomass harvest and transport for biofuel production in Michigan

High dependence on imported oil has increased U.S. strategic vulnerability and prompted more research in the area of renewable energy production. Ethanol production from renewable woody biomass, which could be a substitute for gasoline, has seen increased interest. This study analysed energy use and greenhouse gas emission impacts on the forest biomass supply chain activities within the State of Michigan. A life-cycle assessment of harvesting and transportation stages was completed utilizing peer-reviewed literature. Results for forest-delivered ethanol were compared with those for petroleum gasoline using data specific to the U.S. The analysis from a woody biomass feedstock supply perspective uncovered that ethanol production is more environmentally friendly (about 62% less greenhouse gas emissions) compared with petroleum based fossil fuel production. Sensitivity analysis was conducted with key inputs associated with harvesting and transportation operations. The results showed that research focused on improving biomass recovery efficiency and truck fuel economy further reduced GHG emissions and energy consumption.

09 BIOMASS FUELS↗

Synthesis Procedure of Highly Densely Packed Carbon Nanotube Forests on TiN

The goal of this research was to obtain high-density single-walled carbon nanotube forests (SWNTs) on conductive substrates for different applications, including field emission. For this, dip-coating was chosen as the catalyst deposition method, to subsequently grow SWNTs by Alcohol Catalytic Chemical Vapor Deposition (AC-CVD). Si (100) was chosen as the substrate, which was then coated with a TiN thin film. By sputtering with Ar, it was possible to generate alternating TiN and Si lanes, with a different wettability and, therefore, a different affinity for the catalysts. As a result, the Mo-Co catalyst was mainly deposited on TiN and not on sputtered-Si, which allowed the selective growth of SWNT forests on the TiN conductive surfaces. These as-synthesized SWNTs were used for field emission measurements in a high vacuum chamber.

36 MATERIALS SCIENCE↗

Iron and Manganese Biogeochemistry in Forested Coal Mine Spoil

Abandoned mine lands continue to serve as non-point sources of acid and metal contamination to water bodies long after mining operations have ended. Although soils formed from abandoned mine spoil can support forest vegetation, as observed throughout the Appalachian coal basin, the effects of vegetation on metal cycling in these regions remain poorly characterized. Iron (Fe) and manganese (Mn) biogeochemistry were examined at a former coal mine where deciduous trees grow on mine spoil deposited nearly a century ago. Forest vegetation growing on mine spoil effectively removed dissolved Mn from pore water; however, mineral weathering at a reaction front below the rooting zone resulted in high quantities of leached Mn. Iron was taken up in relatively low quantities by vegetation but was more readily mobilized by dissolved organic carbon produced in the surface soil. Dissolved Fe was low below the reaction front, suggesting that iron oxyhydroxide precipitation retains Fe within the system. These results indicate that mine spoil continues to produce Mn contamination, but vegetation can accumulate Mn and mitigate its leaching from shallow soils, potentially also decreasing Mn leaching from deeper soils by reducing infiltration. Vegetation had less impact on Fe mobility, which was retained as Fe oxides following oxidative weathering.

Herndon, Elizabeth (ORCID:0000000291945493)↗

Revealing the z ∼ 2.5 cosmic web with 3D Lyα forest tomography: a deformation tensor approach

Studies of cosmological objects should take into account their positions within the cosmic web of large-scale structure. Unfortunately, the cosmic web has only been extensively mapped at low redshifts (z<1), using galaxy redshifts as tracers of the underlying density field. At z>1, the required galaxy densities are inaccessible for the foreseeable future, but 3D reconstructions of Lyα forest absorption in closely separated background QSOs and star-forming galaxies already offer a detailed window into z∼2–3 large-scale structure. We quantify the utility of such maps for studying the cosmic web by using realistic z = 2.5 Lyα forest simulations matched to observational properties of upcoming surveys. A deformation tensor-based analysis is used to classify voids, sheets, filaments, and nodes in the flux, which are compared to those determined from the underlying dark matter (DM) field. We find an extremely good correspondence, with 70% of the volume in the flux maps correctly classified relative to the DM web, and 99% classified to within one eigenvalue. This compares favorably to the performance of galaxy-based classifiers with even the highest galaxy densities from low-redshift surveys. We find that narrow survey geometries can degrade the recovery of the cosmic web unless the survey is ≳60 h{sup −1} Mpc or ≳1 deg on the sky. We also examine halo abundances as a function of the cosmic web, and find a clear dependence as a function of flux overdensity, but little explicit dependence on the cosmic web. These methods will provide a new window on cosmological environments of galaxies at this very special time in galaxy formation, “high noon,” and on overall properties of cosmological structures at this epoch.

79 ASTRONOMY AND ASTROPHYSICS↗

Random Forests as a Viable Method to Select and Discover High-redshift Quasars

We present a method of selecting quasars up to redshift ≈6 with random forests, a supervised machine-learning method, applied to Pan-STARRS1 and WISE data. We find that, thanks to the increasing set of known quasars, we can assemble a training set that enables supervised machine-learning algorithms to become a competitive alternative to other methods up to this redshift. We present a candidate set for the redshift range 4.8–6.3, which includes the region around z = 5.5 where selecting quasars is difficult due to their photometric similarity to red and brown dwarfs. We demonstrate that, under our survey restrictions, we can reach a high completeness (66% ± 7% below redshift 5.6/83{sub -9}{sup +6}% above redshift 5.6) while maintaining a high selection efficiency (78{sub -8}{sup +10}%/94{sub -8}{sup +5}%). Our selection efficiency is estimated via a novel method based on the different distributions of quasars and contaminants on the sky. The final catalog of 515 candidates includes 225 known quasars. We predict the candidate catalog to contain additional 148{sub -33}{sup +41} new quasars below redshift 5.6 and 45{sub -8}{sup +5} above, and we make the catalog publicly available. Spectroscopic follow-up observations of 37 candidates led us to discover 20 new high redshift quasars (18 at 4.6 ≤ z ≤ 5.5, 2 z ~ 5.7). These observations are consistent with our predictions on efficiency. We argue that random forests can lead to higher completeness because our candidate set contains a number of objects that would be rejected by common color cuts, including one of the newly discovered redshift 5.7 quasars.

79 ASTRONOMY AND ASTROPHYSICS↗

A New Precision Measurement of the Small-scale Line-of-sight Power Spectrum of the Ly α Forest

We present a new measurement of the Lyα forest power spectrum at 1.8 < z < 3.4 using 74 Keck/HIRES and VLT/UVES high-resolution, high-signal-to-noise-ratio quasar spectra. We developed a custom pipeline to measure the power spectrum and its uncertainty, which fully accounts for finite resolution and noise and corrects for the bias induced by masking missing data, damped Lyα absorption systems, and metal absorption lines. Our measurement results in unprecedented precision on the small-scale modes $k\gt 0.02\,{\rm{s}}\,{\mathrm{km}}^{-1}$, inaccessible to previous SDSS/BOSS analyses. It is well known that these high-k modes are highly sensitive to the thermal state of the intergalactic medium, but contamination by narrow metal lines is a significant concern. We quantify the effect of metals on the small-scale power and find a modest effect on modes with $k\lt 0.1\,{\rm{s}}\,{\mathrm{km}}^{-1}$. As a result, by masking metals and restricting to $k\lt 0.1\,{\rm{s}}\,{\mathrm{km}}^{-1}$, their impact is completely mitigated. We present an end-to-end Bayesian forward-modeling framework whereby mock spectra with the same noise, resolution, and masking as our data are generated from Lyα forest simulations. These mock spectra are used to build a custom emulator, enabling us to interpolate between a sparse grid of models and perform Markov chain Monte Carlo fits. Our results agree well with BOSS on scales $k\lt 0.02\,{\rm{s}}\,{\mathrm{km}}^{-1}$, where the measurements overlap. The combination of the percent-level low-k precision of BOSS with our 5%–15% high-k measurements results in a powerful new data set for precisely constraining the thermal history of the intergalactic medium, cosmological parameters, and the nature of dark matter. Lastly, the power spectra and their covariance matrices are provided as electronic tables.

79 ASTRONOMY AND ASTROPHYSICS↗

New Constraints on IGM Thermal Evolution from the Ly α Forest Power Spectrum

We observe the thermal evolution of the intergalactic medium (IGM) over 3 Gyr of cosmic time $1.8\lt z\lt 5.4$ by comparing measurements of the Lyα forest power spectrum to a suite of ~70 hydrodynamical simulations. We conduct Bayesian inference of IGM thermal parameters using an end-to-end forward modeling framework whereby mock spectra generated from our simulation grid are used to build a custom emulator that interpolates the power spectrum between thermal grid points. The temperature at mean density T 0 rises steadily from ${T}_{0}\sim 6000\,{\rm{K}}$ at z = 5.4, peaks at 14,000 K for z ~ 3.4, and decreases at lower redshift, reaching T 0 ~ 7000 K by z ~ 1.8. This evolution provides conclusive evidence for photoionization heating resulting from the reionization of $\mathrm{He}\,{\rm{II}}$, as well as the subsequent cooling of the IGM due to the expansion of the universe after all reionization events are complete. Our findings are broadly consistent with previous measurements of thermal evolution based on a variety of approaches, but the sensitivity of the power spectrum, the combination of high-precision measurements of large-scale modes ($k\lesssim 0.02\,{\rm{s}}\ {\mathrm{km}}^{-1}$) from the Baryon Oscillation Spectroscopic Survey with our recent determination of the small-scale power, our large grid of models, and our careful statistical analysis enable us to break the well-known degeneracy between the temperature at mean density T 0 and the slope of the temperature–density relation γ that has plagued previous analyses. At the highest redshifts, z ≥ 5, we infer lower temperatures than expected from the standard picture of IGM thermal evolution leaving little room for additional smoothing of the Lyα forest by free streaming of warm dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗

A Novel Statistical Method for Measuring the Temperature–Density Relation in the IGM Using the b – N Hi Distribution of Absorbers in the Ly α Forest

We propose a new method for determining the thermal state of the intergalactic medium based on Voigt profile decomposition of the Lyα forest. The distribution of Doppler parameter and column density (b–N H i distribution) is sensitive to the temperature–density relation T = T 0 (ρ/ρ 0 ) γ-1 , and previous work has inferred T 0 and γ by fitting its low-b cutoff. This approach discards the majority of available data and is susceptible to systematics related to cutoff determination. We introduce an approach that exploits all information encoded in the b – N H i distribution by modeling its entire shape. We apply kernel density estimation to discrete absorption lines to generate model probability density functions, and then we use principal component decomposition to create an emulator that can be evaluated anywhere in thermal parameter space. We introduce a Bayesian likelihood based on these models enabling parameter inference via Markov Chain Monte Carlo. The method's robustness is tested by applying it to a large grid of thermal history simulations. By conducting 160 mock measurements, we establish that our approach delivers unbiased estimates and valid uncertainties for a 2D ( T 0 , γ) measurement. Furthermore, we conduct a pilot study applying this methodology to real observational data at z = 2. Using 200 absorbers, equivalent in path length to a single Lya forest spectrum, we measure $\mathrm{log}{T}_{0}={4.092}_{-0.055}^{+0.050}$ and $\gamma ={1.49}_{-0.074}^{+0.073}$ in excellent agreement with cutoff fitting determinations using the same data. Our method is far more sensitive than cutoff fitting, enabling measurements of log T 0 and γ with precision on $\mathrm{log}{T}_{0}$ (γ) nearly two (three) times higher for current data set sizes.

79 ASTRONOMY AND ASTROPHYSICS↗