Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the ...future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25°×0.25°) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.
We have developed a dynamic land model (LM3V) able to simulate ecosystem dynamics and exchanges of water, energy, and CO2 between land and atmosphere. LM3V is specifically designed to address the ...consequences of land use and land management changes including cropland and pasture dynamics, shifting cultivation, logging, fire, and resulting patterns of secondary regrowth. Here we analyze the behavior of LM3V, forced with the output from the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model AM2, observed precipitation data, and four historic scenarios of land use change for 1700–2000. Our analysis suggests a net terrestrial carbon source due to land use activities from 1.1 to 1.3 GtC/a during the 1990s, where the range is due to the difference in the historic cropland distribution. This magnitude is substantially smaller than previous estimates from other models, largely due to our estimates of a secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating agricultural land clearing since the 1960s. For the 1990s, our estimates for the pastures' carbon flux vary from a source of 0.37 to a sink of 0.15 GtC/a, and for the croplands our model shows a carbon source of 0.6 to 0.9 GtC/a. Our process‐based model suggests a smaller net deforestation source than earlier bookkeeping models because it accounts for decelerated net conversion of primary forest to agriculture and for stronger secondary vegetation regrowth in tropical regions. The overall uncertainty is likely to be higher than the range reported here because of uncertainty in the biomass recovery under changing ambient conditions, including atmospheric CO2 concentration, nutrients availability, and climate.
Dairy manufacturing generates whey by-products, many of them considered waste; others, such as whey permeate, a powder high in lactose and minerals from deproteinated whey, have unrealized potential. ...This study identified yeast species capable of utilizing lactose from whey permeate to produce ethanol or organic acids, and identified fungal species that reduced the acidity of whey by-products. Reconstituted whey permeate was fermented anaerobically or aerobically for 34 days, using species from Cornell University’s Food Safety Lab, Alcaine Research Group, and Omega Labs. Yeast species: Kluyveromyces marxianus, Kluyveromyces lactis, Dekkera anomala, Brettanomyces claussenii, Brettanomyces bruxellensis; mold species: Mucor genevensis and Aureobasidium pullulans. Density, pH, cell concentrations, organic acids, ethanol, and sugar profiles were monitored. Under anoxic conditions, K. marxianus exhibited the greatest lactose utilization and ethanol production (day 20: lactose non-detectable; 4.52% ± 0.02 ethanol). Under oxic conditions, D. anomala produced the most acetic acid (day 34: 9.18 ± 3.38 g/L), and A. pullulans utilized the most lactic acid, increasing the fermentate’s pH (day 34: 0.26 ± 0.21 g/L, pH: 7.91 ± 0.51). This study demonstrates that fermentation of whey could produce value-added alcoholic or organic acid beverages, or increase the pH of acidic by-products, yielding new products and increasing sustainability.
In this paper, we present novel modeling approaches to investigate the sensitivity of radar interferometric coherence to variations in the vertical forest canopy profile. We introduce a common ...framework applicable to model radar microwave extinction and structure from lidar data. To perform this analysis, we make use of interferometric data from the uninhabited aerial vehicle synthetic aperture radar (UAVSAR) L-band radar and full waveform lidar data from laser vegetation imaging sensor (LVIS). The datasets were acquired over the Laurentides Wildlife Reserve Forest, Quebec, Canada. A twofold analysis of the framework to estimate interferometric coherence is undertaken. First, a sensitivity analysis is performed by incorporating lidar waveform Legendre descriptions into two adapted independent polarimetric interferometry models. Second, we examine the effectiveness of using lidar data in this novel way to model radar interferometric coherence. Where appropriate, coherence estimates are obtained using Legendre solutions up to fourth order and at resolutions up to 75 m. The maximum r<;sup>2<;/sup> values between modeled outputs and observed coherence across hh, vv, and hv polarizations are shown as 0.51(p <; 0.05) and 0.76(p <; 0.05) at 25 and 75 m pixel resolutions, respectively. The introduction of a common framework to combine lidar and radar enables an estimation of the impact of canopy structure on observed interferometric coherence and provides further insight into the feasibility of assuming uniform microwave extinction rates on different scales through forest canopy. The framework's potential lies in its use to assess performance of canopy structure estimates from future spaceborne radar interferometers in synergy with lidar data.
Computational modeling is a powerful tool to study normal, injured, and repaired joint function. Existing musculoskeletal models of the elbow have all limited their applicability by assuming fixed ...joint axes of rotation or prescribing specific kinematics. The purpose of this study was to develop and validate a model of the elbow and forearm whereby joint behavior was dictated by articular contact, ligamentous constraints, muscle loading, and external perturbations. A three-dimensional computer representation of the humerus, ulna, and radius was produced from computed tomography scans, ligaments were modeled as linear springs, select muscles were represented as constant-magnitude force vectors, and reaction forces were automatically applied at points of bone-to-bone contact. A commercial rigid body dynamics program was used to simulate joint function, and validation was accomplished through a comparison of model predictions to results obtained in published studies which explored elbow range of motion and the effects of coronoid process removal on joint stability. The computational model accurately predicted flexion-extension motion limits, and relationships between coronoid process removal, flexion angle, and varus constraining forces. The model was also able to compute parameters that the experimental investigations could not, such as forces within ligaments and contact forces between bones. The potential medical applications for this model and modeling approach are significant, and are anticipated to ultimately have value as a predictive clinical tool.
Terrestrial ecosystems and their vegetation are linked to climate. With the potential of accelerated climate change from anthropogenic forcing, there is a need to further evaluate the transient ...response of ecosystems, their vegetation, and their influence on the carbon balance, to this change. The equilibrium response of ecosystems to climate change has been estimated in previous studies in global domains. However, research on the transient response of terrestrial vegetation to climate change is often limited to domains at the sub-continent scale. Estimation of the transient response of vegetation requires the use of mechanistic models to predict the consequences of competition, dispersal, landscape heterogeneity, disturbance, and other factors, where it becomes computationally prohibitive at scales larger than sub-continental. Here, we used a pseudo-spatial ecosystem model with a vegetation migration sub-model that reduced computational intensity and predicted the transient response of vegetation and carbon to climate change in northern North America. The ecosystem model was first run with a current climatology at half-degree resolution for 1000 years to establish current vegetation and carbon distribution. From that distribution, climate was changed to a future climatology and the ecosystem model run for an additional 2000 simulation years. A model experimental design with different combinations of vegetation dispersal rates, dispersal modes, and disturbance rates produced 18 potential change scenarios. Results indicated that potential redistribution of terrestrial vegetation from climate change was strongly impacted by dispersal rates, moderately affected by disturbance rates, and marginally impacted by dispersal mode. For carbon, the sensitivities were opposite. A potential transient net carbon sink greater than that predicted by the equilibrium response was estimated on time scales of decades–centuries, but diminished over longer time scales. Continued research should further explore the interactions between competition, dispersal, and disturbance, particularly in regards to vegetation redistribution.
There are strong relationships between climate and ecosystems. With the prospect of anthropogenic forcing accelerating climate change, there is a need to understand how terrestrial vegetation ...responds to this change as it influences the carbon balance. Previous studies have primarily addressed this question using empirically based models relating the observed pattern of vegetation and climate, together with scenarios of potential future climate change, to predict how vegetation may redistribute. Unlike previous studies, here we use an advanced mechanistic, individually based, ecosystem model to predict the terrestrial vegetation response from future climate change. The use of such a model opens up opportunities to test with remote sensing data, and the possibility of simulating the transient response to climate change over large domains. The model was first run with a current climatology at half-degree resolution and compared to remote sensing data on dominant plant functional types for northern North America for validation. Future climate data were then used as inputs to predict the equilibrium response of vegetation in terms of dominant plant functional type and carbon redistribution. At the domain scale, total forest cover changed by ~2% and total carbon storage increased by ~8% in response to climate change. These domain level changes were the result of much larger gross changes within the domain. Evergreen forest cover decreased 48% and deciduous forest cover increased 77%. The dominant plant functional type changed on 58% of the sites, while total carbon in deciduous vegetation increased 107% and evergreen vegetation decreased 31%. The percent of terrestrial carbon from deciduous and evergreen plant functional types changed from 27%/73% under current climate conditions, to 54%/46% under future climate conditions. These large predicted changes in vegetation and carbon in response to future climate change are comparable to previous empirically based estimates, and motivate the need for future development with this mechanistic model to estimate the transient response to future climate changes.
Strong methane point source emissions generate large atmospheric concentrations that can be detected and quantified with infrared remote sensing and retrieval algorithms. Two standard and widely used ...retrieval algorithms for one class of observing platform, imaging spectrometers, include pixel-wise and column-wise approaches. In this study, we assess the performance of both approaches using the airborne imaging spectrometer (Global Airborne Observatory) observations of two extensive controlled-release experiments. We find that the column-wise retrieval algorithm is sensitive to the flight line length and can have a systematic low bias with short flight lines, which is not present in the pixel-wise retrieval algorithm. However, the pixel-wise retrieval is very computationally expensive, and the column-wise retrieval algorithms can produce good results when the flight line length is sufficiently long. Lastly, this study examines the methane plume detection performance of the Global Airborne Observatory with a column-wise retrieval algorithm and finds minimum detection limits of between 9 of 10 kg h−1 and 90 % probability of detection between 10 and 45 kg h−1. These results present a framework of rules for guiding proper concentration retrieval selection given conditions at the time of observation in order to ensure robust detection and quantification.
Terrestrial ecosystems play a critical role in the global carbon cycle but have highly uncertain future dynamics. Ecosystem modeling that includes the scaling up of underlying mechanistic ecological ...processes has the potential to improve the accuracy of future projections while retaining key process-level detail. Over the past two decades, multiple modeling advances have been made to meet this challenge, such as the Ecosystem Demography (ED) model and its derivatives, including ED2 and FATES. Here, we present the global evaluation of the Ecosystem Demography model (ED v3.0), which, like its predecessors, features the formal scaling of physiological processes for individual-based vegetation dynamics to ecosystem scales, together with integrated submodules of soil biogeochemistry and soil hydrology, while retaining explicit tracking of vegetation 3-D structure. This new model version builds on previous versions and provides the first global calibration and evaluation, global tracking of the effects of climate and land-use change on vegetation 3-D structure, spin-up process and input datasets, as well as numerous other advances. Model evaluation was performed with respect to a set of important benchmarking datasets, and model estimates were within observational constraints for multiple key variables, including (i) global patterns of dominant plant functional types (broadleaf vs. evergreen), (ii) the spatial distribution, seasonal cycle, and interannual trends for global gross primary production (GPP), (iii) the global interannual variability of net biome production (NBP) and (iv) global patterns of vertical structure, including leaf area and canopy height. With this global model version, it is now possible to simulate vegetation dynamics from local to global scales and from seconds to centuries with a consistent mechanistic modeling framework amendable to data from multiple traditional and new remote sensing sources, including lidar.
Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem ...models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.
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