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At least 1,423 records · Page 79

Assessing Earthquake-Induced Tree Mortality in Temperate Forest Ecosystems: A Case Study from Wenchuan, China

Earthquakes can produce significant tree mortality, and consequently affect regional carbon dynamics. Unfortunately, detailed studies quantifying the influence of earthquake on forest mortality are currently rare. The committed forest biomass carbon loss associated with the 2008 Wenchuan earthquake in China is assessed by a synthetic approach in this study that integrated field investigation, remote sensing analysis, empirical models and Monte Carlo simulation. The newly developed approach significantly improved the forest disturbance evaluation by quantitatively defining the earthquake impact boundary and detailed field survey to validate the mortality models. Based on our approach, a total biomass carbon of 10.9 Tg·C was lost in Wenchuan earthquake, which offset 0.23% of the living biomass carbon stock in Chinese forests. Tree mortality was highly clustered at epicenter, and declined rapidly with distance away from the fault zone. It is suggested that earthquakes represent a signif icant driver to forest carbon dynamics, and the earthquake-induced biomass carbon loss should be included in estimating forest carbon budgets.

54 ENVIRONMENTAL SCIENCES↗

The Straightening of a River Meander Leads to Extensive Losses in Flow Complexity and Ecosystem Services

To assist river restoration efforts we need to slow the rate of river degradation. This study provides a detailed explanation of the hydraulic complexity loss when a meandering river is straightened in order to motivate the protection of river channel curvature. We used computational fluid dynamics (CFD) modeling to document the difference in flow dynamics in nine simulations with channel curvature (C) degrading from a well-established tight meander bend (C = 0.77) to a straight channel without curvature (C = 0). To control for covariates and slow the rate of loss to hydraulic complexity, each of the nine-channel realizations had equivalent bedform topography. The analyzed hydraulic variables included the flow surface elevation, streamwise and transverse unit discharge, flow velocity at streamwise, transverse, and vertical directions, bed shear stress, stream function, and the vertical hyporheic flux rates at the channel bed. The loss of hydraulic complexity occurred gradually when initially straightening the channel from C = 0.77 to C = 0.33 (i.e., the radius of the channel is three-times the channel width), and additional straightening incurred rapid losses to hydraulic complexity. Other studies have shown hydraulic complexity provides important riverine habitat and is positively correlated with biodiversity. This study demonstrates how hydraulic complexity can be gradually and then rapidly lost when unwinding a river, and hopefully will serve as a cautionary tale.

54 ENVIRONMENTAL SCIENCES↗

The Greater Taurus–Auriga Ecosystem. I. There is a Distributed Older Population

The census of Taurus–Auriga has been assembled over seven decades and inherited the biases and incompleteness of the input studies. The unusual shape of its inferred initial mass function (IMF) and the existence of isolated disk-bearing stars suggest that additional (likely disk-free) members remain to be discovered. We therefore have begun a global reassessment of the census of Taurus–Auriga that exploits new data and better definitions of youth and kinematic membership. As a first step, we reconsider the membership of all disk-free candidate members from the literature with spectral type ≥F0, 3{sup h}50{sup m}<α<5{sup h}40{sup m}, and 14{sup ∘}<δ<34{sup ∘}. We combine data from the literature with Keck/HIRES and UH88/SNIFS spectra to test the membership of these candidates using the positions in the Hertzsprung-Russel diagram, proper motions, radial velocities, Hα, lithium, and surface gravity. We find 218 confirmed or likely Taurus members, 160 confirmed or likely interlopers, and only 18 that lack sufficient evidence to draw firm conclusions. A significant fraction of these stars (81/218 = 37%) are not included in the most recent canonical member lists. There are few additional members to the immediate vicinity of the molecular clouds, preserving the IMFs that have been deemed anomalous in past work. Many of the likely Taurus members are instead distributed broadly across the search area. When combined with the known disk hosts, our updated census reveals two regimes: a high-density population with a high disk fraction (indicative of youth) that broadly traces the molecular clouds, and a low-density population with low disk fraction (hence likely older) that most likely represents previous generations of star formation.

79 ASTRONOMY AND ASTROPHYSICS↗

Data from: Legacy effects of land use on soil nitrous oxide emissions in annual crop and perennial grassland ecosystems

Land use conversions into and out of agriculture may influence soil-atmosphere greenhouse gas fluxes for many years. We tested the legacy effects of land use on cumulative soil nitrous oxide (N2O) fluxes for five years following conversion of 22 year-old Conservation Reserve Program (CRP) grasslands and conventionally tilled agricultural fields (AGR) to continuous no-till corn, switchgrass, and restored prairie. An unconverted CRP field served as a reference. We assessed the labile soil C pool of the upper 10 cm in 2009 (the conversion year) and in 2014 using short-term soil incubations. We also measured in situ soil N2O fluxes biweekly from 2009 through 2014 using static chambers except when soils were frozen. The labile C pool was ~2-fold higher in soils previously in CRP than in those formerly in tilled cropland. Five-year cumulative soil N2O emissions were ~3-fold higher in the corn system on former CRP than on former cropland despite similar fertilization rates (~184 kg N ha-1 yr-1). The lower cumulative emissions from corn on former cropland were similar to emissions from switchgrass that was fertilized less (~57 kg N ha-1 yr-1), regardless of former land use, and lowest emissions were observed from the unfertilized restored prairie and reference systems. Findings support the hypothesis that soil labile carbon levels modulate the response of soil N2O emissions to nitrogen inputs, with soils higher in labile carbon but otherwise similar – in this case reflecting land use history – responding more strongly to added nitrogen.

54 ENVIRONMENTAL SCIENCES↗

Data from: Can the results of biodiversity-ecosystem productivity studies be translated to bioenergy production?

Biodiversity experiments show that increases in plant diversity can lead to greater biomass production, and some researchers suggest that high diversity plantings should be used for bioenergy production. However, many methods used in past biodiversity experiments are impractical for bioenergy plantings. For example, biodiversity experiments often use intensive management such as hand weeding to maintain low diversity plantings and exclude unplanted species, but this would not be done for bioenergy plantings. Also, biodiversity experiments generally use high seeding densities that would be too expensive for bioenergy plantings. Here we report the effects of biodiversity on biomass production from two studies of more realistic bioenergy crop plantings in southern Michigan, USA. One study involved comparing production between switchgrass (Panicum virgatum) monocultures and species-rich prairie plantings on private farm fields that were managed similarly to bioenergy plantings. The other study was an experiment where switchgrass was planted in monoculture and in combination with increasingly species-rich native prairie mixtures. Overall, we found that bioenergy plantings with higher species richness did not produce more biomass than switchgrass monocultures. The lack of a positive relationship between planted species richness and production in our studies may be due to several factors. Non-planted species (weeds) were not removed from our studies and these non-planted species may have competed with planted species and also prevented realized species richness from equaling planted species richness. Also, we found that low seeding density of individual species limited the biomass production of these individual species. Production in future bioenergy plantings with high species richness may be increased by using a high density of inexpensive seed from switchgrass and other highly productive species, and future efforts to translate the results of biodiversity experiments to bioenergy plantings should consider the role of seeding density.

09 BIOMASS FUELS↗

Carbonyl sulfide exchange in soils for better estimates of ecosystem carbon uptake

Carbonyl sulfide (COS) measurements are one of the emerging tools to better quantify gross primary production (GPP), the largest flux in the global carbon cycle. COS is a gas with a similar structure to CO 2 ; COS uptake is thought to be a proxy for GPP. However, soils are a potential source or sink of COS. This study presents a framework for understanding soil–COS interactions. Excluding wetlands, most of the few observations of isolated soils that have been made show small uptake of atmospheric COS. Recently, a series of studies at an agricultural site in the central United States found soil COS production under hot conditions an order of magnitude greater than fluxes at other sites. To investigate the extent of this phenomenon, soils were collected from five new sites and incubated in a variety of soil moisture and temperature states. We found that soils from a desert, an oak savannah, a deciduous forest, and a rainforest exhibited small COS fluxes, behavior resembling previous studies. However, soil from an agricultural site in Illinois, >800 km away from the initial central US study site, demonstrated comparably large soil fluxes under similar conditions. These new data suggest that, for the most part, soil COS interaction is negligible compared to plant uptake of COS. We present a model that anticipates the large agricultural soil fluxes so that they may be taken into account. Furthermore, while COS air-monitoring data are consistent with the dominance of plant uptake, improved interpretation of these data should incorporate the soil flux parameterizations suggested here.

54 ENVIRONMENTAL SCIENCES↗

Technical note: 3-hourly temporal downscaling of monthly global terrestrial biosphere model net ecosystem exchange

Here, the land surface provides a boundary condition to atmospheric forward and flux inversion models. These models require prior estimates of CO 2 fluxes at relatively high temporal resolutions (e.g., 3-hourly) because of the high frequency of atmospheric mixing and wind heterogeneity. However, land surface model CO 2 fluxes are often provided at monthly time steps, typically because the land surface modeling community focuses more on time steps associated with plant phenology (e.g., seasonal) than on sub-daily phenomena. Here, we describe a new dataset created from 15 global land surface models and 4 ensemble products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), temporally downscaled from monthly to 3-hourly output. We provide 3-hourly output for each individual model over 7 years (2004–2010), as well as an ensemble mean, a weighted ensemble mean, and the multi-model standard deviation. Output is provided in three different spatial resolutions for user preferences: 0.5° × 0.5°, 2.0° × 2.5°, and 4.0° × 5.0° (latitude × longitude).

54 ENVIRONMENTAL SCIENCES↗

Role of CO 2 , climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis

We examined the net terrestrial carbon flux to the atmosphere (F TA ) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961-2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40g% compared to atmospheric inversions. Global F TA amplitude increase (19 ± 8%) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56%, -3 ± 74 and 20 ± 30% to rising CO 2 , climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO 2 fertilization is the strongest control -with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global < i > F TA : some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between < i > F TA amplitude increase and increase in land carbon sink ( < i > R 2 Combining double low line 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO 2 fertilization, climate change and land use/cover changes are crucial in determining the right mechanisms in seasonal carbon cycle change as well as mean sink change.

54 ENVIRONMENTAL SCIENCES↗

Impacts of microtopographic snow redistribution and lateral subsurface processes on hydrologic and thermal states in an Arctic polygonal ground ecosystem: a case study using ELM-3D v1.0

Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. In this study, we analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the E3SM to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ELM-3D v1.0). Multiple 10-year-long simulations were performed for a transect across a polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SR and subsurface process representation. When SR was included, model predictions better agreed (higher R 2 , lower bias and RMSE) with observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R 2 of 0.59°C, 1.82°C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ~ 10 cm shallower and ~ 5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on maximum thaw depths was modest, with mean absolute differences of ~ 3 cm. Our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the E3SM land model will facilitate a wide range of analyses heretofore impossible in an ESM context.

54 ENVIRONMENTAL SCIENCES↗

Soil-related developments of the Biome-BGCMuSo v6.2 terrestrial ecosystem model

Terrestrial biogeochemical models are essential tools to quantify climate–carbon cycle feedback and plant–soil relations from local to global scale. In this study, a theoretical basis is provided for the latest version of the Biome-BGCMuSo biogeochemical model (version 6.2). Biome-BGCMuSo is a branch of the original Biome-BGC model with a large number of developments and structural changes. Earlier model versions performed poorly in terms of soil water content (SWC) dynamics in different environments. Moreover, lack of detailed nitrogen cycle representation was a major limitation of the model. Since problems associated with these internal drivers might influence the final results and parameter estimation, additional structural improvements were necessary. In this paper the improved soil hydrology as well as the soil carbon and nitrogen cycle calculation methods are described in detail. Capabilities of the Biome-BGCMuSo v6.2 model are demonstrated via case studies focusing on soil hydrology, soil nitrogen cycle, and soil organic carbon content estimation. Soil-hydrology-related results are compared to observation data from an experimental lysimeter station. The results indicate improved performance for Biome-BGCMuSo v6.2 compared to v4.0 (explained variance increased from 0.121 to 0.8 for SWC and from 0.084 to 0.46 for soil evaporation; bias changed from -0.047 to -0.007 m 3 m -3 for SWC and from -0.68 to -0.2 mm d -1 for soil evaporation). Simulations related to nitrogen balance and soil CO 2 efflux were evaluated based on observations made in a long-term field experiment under crop rotation. The results indicated that the model is able to provide realistic nitrate content estimation for the topsoil. Soil nitrous oxide (N 2 O) efflux and soil respiration simulations were also realistic, with overall correspondence with the observations (for the N 2 O efflux simulation bias was between -0.13 and -0.1 mgNm -2 d -1 , and normalized root mean squared error (NRMSE) was 32.4 %–37.6 %; for CO 2 efflux simulations bias was 0.04–0.17 gCm -2 d -1 , while NRMSE was 34.1 %–40.1 %). Sensitivity analysis and optimization of the decomposition scheme are presented to support practical application of the model. The improved version of Biome-BGCMuSo has the ability to provide more realistic soil hydrology representation as well as nitrification and denitrification process estimation, which represents a major milestone.

58 GEOSCIENCES↗

Impacts of microtopographic snow-redistribution and lateral subsurface processeson hydrologic and thermal states in an Arctic polygonal ground ecosystem

Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. Here, we analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the ACME Earth System Model (ESM) to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ALMv0-3D). Three 10-years long simulations were performed for a transect across polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SR and subsurface process representation. When SR was included, model results show a better agreement (higher R 2 with lower bias and RMSE) for the observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R 2 of 0.59 &deg;C, 1.82 &deg;C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ~10 cm shallower and ~5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on active layer depths was modest with mean absolute difference of ~3 cm. Our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the ACME land model will facilitate a wide range of analyses heretofore impossible in an ESM context.

54 ENVIRONMENTAL SCIENCES↗

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which better represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties &ndash; including the distribution of permafrost and vegetation cover heterogeneity &ndash; are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.

54 ENVIRONMENTAL SCIENCES↗

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

Abstract. This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE = 2.9 cm), with a spatial sampling of 10 cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE = 6.0 cm) and a fine spatial sampling (4 cm × 4 cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE = 6.0 cm), at 0.5 m resolution and over the lidar domain (750 m × 700 m).

54 ENVIRONMENTAL SCIENCES↗

Campaign datasets for Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HISCALE)

Most of the instruments were deployed on the ARM Aerial Facility (AAF) Gulfstream-159 (G-1) aircraft, including those that measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions, and cloud condensation nuclei concentrations. Aerosol microphysical property measurements supplemented routine ARM aerosol measurements made at the surface. The G-1 completed transects over the SGP Central Facility at multiple altitudes within the boundary layer, and within and above clouds.

54 ENVIRONMENTAL SCIENCES↗