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At least 1,765 records · Page 98

Disturbances in North American boreal forest and Arctic tundra: impacts, interactions, and responses

Ecosystems in the North American Arctic-Boreal Zone (ABZ) experience a diverse set of disturbances associated with wildfire, permafrost dynamics, geomorphic processes, insect outbreaks and pathogens, extreme weather events, and human activity. Climate warming in the ABZ is occurring at over twice the rate of the global average, and as a result the extent, frequency, and severity of these disturbances are increasing rapidly. Disturbances in the ABZ span a wide gradient of spatiotemporal scales and have varying impacts on ecosystem properties and function. However, many ABZ disturbances are relatively understudied and have different sensitivities to climate and trajectories of recovery, resulting in considerable uncertainty in the impacts of climate warming and human land use on ABZ vegetation dynamics and in the interactions between disturbance types. Here we review the current knowledge of ABZ disturbances and their precursors, ecosystem impacts, temporal frequencies, spatial extents, and severity. We also summarize current knowledge of interactions and feedbacks among ABZ disturbances and characterize typical trajectories of vegetation loss and recovery in response to ecosystem disturbance using satellite time-series. We conclude with a summary of critical data and knowledge gaps and identify priorities for future study.

54 ENVIRONMENTAL SCIENCES↗

Disentangling the effects of sulfate and other seawater ions on microbial communities and greenhouse gas emissions in a coastal forested wetland

Seawater intrusion into freshwater wetlands causes changes in microbial communities and biogeochemistry, but the exact mechanisms driving these changes remain unclear. Here we use a manipulative laboratory microcosm experiment, combined with DNA sequencing and biogeochemical measurements, to tease apart the effects of sulfate from other seawater ions. We examined changes in microbial taxonomy and function as well as emissions of carbon dioxide, methane, and nitrous oxide in response to changes in ion concentrations. Greenhouse gas emissions and microbial richness and composition were altered by artificial seawater regardless of whether sulfate was present, whereas sulfate alone did not alter emissions or communities. Surprisingly, addition of sulfate alone did not lead to increases in the abundance of sulfate reducing bacteria or sulfur cycling genes. Similarly, genes involved in carbon, nitrogen, and phosphorus cycling responded more strongly to artificial seawater than to sulfate. These results suggest that other ions present in seawater, not sulfate, drive ecological and biogeochemical responses to seawater intrusion and may be drivers of increased methane emissions in soils that received artificial seawater addition. A better understanding of how the different components of salt water alter microbial community composition and function is necessary to forecast the consequences of coastal wetland salinization.

54 ENVIRONMENTAL SCIENCES↗

Random Forest Prediction of Crystal Structure from Electron Diffraction Patterns

Transmission electron microscopy (TEM) diffraction patterns are regularly used to determine the structure of crystalline materials. Electron diffraction is the most common method to solve for unknown or partially known crystal structures, as it provides direct and interpretable feedback on the orientation of crystal grains under the beam [1]. However, it remains a challenge to determine the crystal structure of a new material or even a new phase of an existing material. Analysis of such materials commonly requires manual exploration and comparison with simulated diffraction patterns. This is often a time consuming process with no obvious start point when many similar structures are possible, and this method cannot be used to determine crystal structure or orientation from structures not included in the diffraction libraries. Therefore, we have developed a machine learning model to determine the crystal structure of a material from its electron diffraction pattern.

36 MATERIALS SCIENCE↗

Optimal 1D Ly α forest power spectrum estimation – II. KODIAQ, SQUAD, and XQ-100

ABSTRACT We measure the 1D Ly α power spectrum P1D from Keck Observatory Database of Ionized Absorption toward Quasars (KODIAQ), The Spectral Quasar Absorption Database (SQUAD), and XQ-100 quasars using the optimal quadratic estimator. We combine KODIAQ and SQUAD at the spectrum level, but perform a separate XQ-100 estimation to control its large resolution corrections in check. Our final analysis measures P1D at scales k < 0.1 s km−1 between redshifts $z$ = 2.0–4.6 using 538 quasars. This sample provides the largest number of high-resolution, high-S/N observations; and combined with the power of optimal estimator it provides exceptional precision at small scales. These small-scale modes (k ≳ 0.02 s km−1), unavailable in Sloan Digital Sky Survey and Dark Energy Spectroscopic Instrument analyses, are sensitive to the thermal state and reionization history of the intergalactic medium, as well as the nature of dark matter. As an example, a simple Fisher forecast analysis estimates that our results can improve small-scale cut-off sensitivity by more than a factor of 2.

79 ASTRONOMY AND ASTROPHYSICS↗

Direct cosmological inference from three-dimensional correlations of the Lyman α forest

ABSTRACT When performing cosmological inference, standard analyses of the Lyman α (Ly α) three-dimensional correlation functions only consider the information carried by the distinct peak produced by baryon acoustic oscillations (BAO). In this work, we address whether this compression is sufficient to capture all the relevant cosmological information carried by these functions. We do this by performing a direct fit to the full shape, including all physical scales without compression, of synthetic Ly α autocorrelation functions and cross-correlations with quasars at effective redshift zeff = 2.3, assuming a DESI-like survey, and providing a comparison to the classic method applied to the same data set. Our approach leads to a $3.5{{\ \rm per\ cent}}$ constraint on the matter density ΩM, which is about three to four times better than what BAO alone can probe. The growth term fσ8(zeff) is constrained to the $10{{\ \rm per\ cent}}$ level, and the spectral index ns to $\sim 3-4{{\ \rm per\ cent}}$. We demonstrate that the extra information resulting from our ‘direct fit’ approach, except for the ns constraint, can be traced back to the Alcock–Paczynski effect and redshift space distortion information.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploring the role of biotic factors in regulating the spatial variability in land surface phenology across four temperate forest sites

Here, land surface phenology (LSP), the characterization of plant phenology with satellite data, is essential for understanding the effects of climate change on ecosystem functions. Considerable LSP variation is observed within local landscapes, and the role of biotic factors in regulating such variation remains underexplored. In this study, we selected four National Ecological Observatory Network terrestrial sites with minor topographic relief to investigate how biotic factors regulate intra-site LSP variability. We utilized plant functional type (PFT) maps, functional traits, and LSP data to assess the explanatory power of biotic factors for the start and end of season (SOS and EOS) variability. Our results indicate that PFTs alone explain only 0.8–23.4% of intra-site SOS and EOS variation, whereas including functional traits significantly improves explanatory power, with cross-validation correlations ranging from 0.50 to 0.85. While functional traits exhibited diverse effects on SOS and EOS across different sites, traits related to competitive ability and productivity were important for explaining both SOS and EOS variation at these sites. These findings reveal that plants exhibit diverse phenological responses to comparable environmental conditions, and functional traits significantly contribute to intra-site LSP variability, highlighting the importance of intrinsic biotic properties in regulating plant phenology.

60 APPLIED LIFE SCIENCES↗