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At least 37 records · Page 2

Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison

To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.

54 ENVIRONMENTAL SCIENCES↗

Mission simulation as an approach to develop requirements for automation in Advanced Life Support Systems

This paper examines mission simulation as an approach to develop requirements for automation and robotics for Advanced Life Support Systems (ALSS). The focus is on requirements and applications for command and control, control and monitoring, situation assessment and response, diagnosis and recovery, adaptive planning and scheduling, and other automation applications in addition to mechanized equipment and robotics applications to reduce the excessive human labor requirements to operate and maintain an ALSS. Based on principles of systems engineering, an approach is proposed to assess requirements for automation and robotics using mission simulation tools. First, the story of a simulated mission is defined in terms of processes with attendant types of resources needed, including options for use of automation and robotic systems. Next, systems dynamics models are used in simulation to reveal the implications for selected resource allocation schemes in terms of resources required to complete operational tasks. The simulations not only help establish ALSS design criteria, but also may offer guidance to ALSS research efforts by identifying gaps in knowledge about procedures and/or biophysical processes. Simulations of a planned one-year mission with 4 crewmembers in a Human Rated Test Facility are presented as an approach to evaluation of mission feasibility and definition of automation and robotics requirements.

NASA Discipline Number 61-10↗

Sun‐induced Chl fluorescence and its importance for biophysical modeling of photosynthesis based on light reactions

Summary Recent progress in observing sun‐induced Chl fluorescence (SIF) provides an unprecedented opportunity to advance photosynthesis research in natural environments. However, we still lack an analytical framework to guide SIF studies and integration with the well‐developed active fluorescence approaches. Here, we derive a set of coupled fundamental equations to describe the dynamics of SIF and its relationship with C 3 and C 4 photosynthesis. These equations show that, although SIF is dynamically as complex as photosynthesis, the measured SIF simplifies photosynthetic modeling from the perspective of light reactions by integrating over the dynamic complexities of photosynthesis. Specifically, the measured SIF contains direct information about the actual electron transport from photosystem II to photosystem I, giving a quantifiable link between light and dark reactions. With much‐reduced requirements on inputs and parameters, the light‐reactions‐centric, SIF‐based biophysical model complements the traditional, dark‐reactions‐centric biochemical model of photosynthesis. The SIF–photosynthesis relationship, however, is nonlinear. This is because photosynthesis saturates at high light whereas SIF has a stronger tendency to keep increasing, as fluorescence quantum yield has a relatively muted sensitivity to light levels. Successful applications of the SIF‐based model of photosynthesis will depend on a predictive understanding of several previously underexplored physiological and biophysical processes. Advances can be facilitated by coordinated efforts in plant physiology, remote sensing, and eddy covariance flux observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biophysical principles of choanoflagellate self-organization

Inspired by the patterns of multicellularity in choanoflagellates, the closest living relatives of animals, we quantify the biophysical processes underlying the morphogenesis of rosette colonies in the choanoflagellate Salpingoeca rosetta . We find that rosettes reproducibly transition from an early stage of 2-dimensional (2D) growth to a later stage of 3D growth, despite the underlying variability of the cell lineages. Our perturbative experiments demonstrate the fundamental importance of a basally secreted extracellular matrix (ECM) for rosette morphogenesis and show that the interaction of the ECM with cells in the colony physically constrains the packing of proliferating cells and, thus, controls colony shape. Simulations of a biophysically inspired model that accounts for the size and shape of the individual cells, the fraction of ECM, and its stiffness relative to that of the cells suffices to explain our observations and yields a morphospace consistent with observations across a range of multicellular choanoflagellate colonies. Overall, our biophysical perspective on rosette development complements previous genetic perspectives and, thus, helps illuminate the interplay between cell biology and physics in regulating morphogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Data-driven prediction of α IIb β 3 integrin activation paths using manifold learning and deep generative modeling

The integrin heterodimer is a transmembrane protein critical for driving cellular process and is a therapeutic target in the treatment of multiple diseases linked to its malfunction. Activation of integrin involves conformational transitions between bent and extended states. Some of the conformations that are intermediate between bent and extended states of the heterodimer have been experimentally characterized, but the full activation pathways remain unresolved both experimentally due to their transient nature and computationally due to the challenges in simulating rare barrier crossing events in these large molecular systems. An understanding of the activation pathways can provide new fundamental understanding of the biophysical processes associated with the dynamic interconversions between bent and extended states and unveil new putative therapeutic targets. In this work, we apply nonlinear manifold learning to coarse-grained molecular dynamics simulations of bent, extended, and two intermediate states of αI I b β3 integrin to learn a low-dimensional embedding of the configurational phase space. We then train deep generative models to learn an inverse mapping between the low-dimensional embedding and high-dimensional molecular space and use these models to interpolate the molecular configurations constituting the activation pathways between the experimentally characterized states. Furthermore, this work furnishes plausible predictions of integrin activation pathways and reports a generic and transferable multi-scale technique to predict transition pathways for biomolecular systems.

97 MATHEMATICS AND COMPUTING↗

Future increase in compound soil drought-heat extremes exacerbated by vegetation greening

Compound soil drought and heat extremes are expected to occur more frequently with global warming, causing wide-ranging socio-ecological repercussions. Vegetation modulates air temperature and soil moisture through biophysical processes, thereby influencing the occurrence of such extremes. Global vegetation cover is broadly expected to increase under climate change, but it remains unclear whether vegetation greening will alleviate or aggravate future increases in compound soil drought-heat events. Here, using a suite of state-of-the-art model simulations, we show that the projected vegetation greening will increase the frequency of global compound soil drought-heat events, equivalent to 12-21% of the total increment at the end of 21st century. This increase is predominantly driven by reduced albedo and enhanced transpiration associated with increased leaf area. Although greening-induced transpiration enhancement has counteracting cooling and drying effects, the excessive water loss in the early growing season can lead to later soil moisture deficits, amplifying compound soil drought-heat extremes during the subsequent warm season. These changes are most pronounced in northern high latitudes and are dominated by the warming effect of CO 2 . Our study highlights the necessity of integrating vegetation biophysical effects into mitigation and adaptation strategies for addressing compound climate risks.

54 ENVIRONMENTAL SCIENCES↗

An overview of methods to identify and manage uncertainty for modelling problems in the water-environment-agriculture cross-sector

Uncertainty pervades the representation of systems in the water–environment–agriculture cross-sector. Successful methods to address uncertainties have largely focused on standard mathematical formulations of biophysical processes in a single sector, such as partial or ordinary differential equations. More attention to integrated models of such systems is warranted. Model components representing the different sectors of an integrated model can have less standard, and different, formulations to one another, as well as different levels of epistemic knowledge and data informativeness. Thus, uncertainty is not only pervasive but also crosses boundaries and propagates between system components. Uncertainty assessment (UA) cries out for more eclectic treatment in these circumstances, some of it being more qualitative and empirical. Here in this paper, we discuss the various sources of uncertainty in such a cross-sectoral setting and ways to assess and manage them. We have outlined a fast-growing set of methodologies, particularly in the computational mathematics literature on uncertainty quantification (UQ), that seem highly pertinent for uncertainty assessment. There appears to be considerable scope for advancing UA by integrating relevant UQ techniques into cross-sectoral problem applications. Of course this will entail considerable collaboration between domain specialists who often take first ownership of the problem and computational methods experts.

97 MATHEMATICS AND COMPUTING↗

Beneficiaries, equity, and trade-offs in estuarine and coastal ecosystem services

Estuarine and coastal ecosystems support human populations in myriad ways. Traditionally, researchers have focused on the biophysical processes that underlie these benefits and their economic values. In the decade since the 1st Treatise, the literature on cultural ecosystem services, human health benefits, and the equitable distribution of societal benefits and burdens has grown tremendously. In this chapter we outline three dimensions of equity as they relate to estuarine and coastal ecosystems: procedural, recognitional, and distributional equity. We then apply the dimensions of equity to a suite of provisioning, regulating, and cultural ecosystem services. Finally, we explore trade-offs and beneficiaries of these ecosystem services using three case studies that consider equity in a variety of estuarine and coastal management decisions.

beneficiaries↗

A novel approach to increase accuracy in remotely sensed evapotranspiration through basin water balance and flux tower constraints

Remote sensing-derived evapotranspiration (RSET) products capture the spatiotemporal variations of evapotranspiration (ET) from field to basin scales with unprecedented details. However, their accuracy varies across RSET estimation methods and diverse hydroclimate regions. While ET modeling efforts to account for biophysical processes and controlling parameters have made good progress in recent years, a parallel approach of integrating in-situ ET with RSET could reduce biases in RSET products. Basin water balance ET (WBET) and flux tower ET are widely applied to evaluate RSET accuracy, yet such ET measurements are rarely used for RSET bias corrections, especially for large area applications. To address this issue, we propose a novel approach: the water balance equivalence (WABE) method, which generates spatially continuous WBET for correcting biases in RSET products. The WABE method computes synthetic WBET by integrating observed WBET and flux tower-derived FLUXCOM ET, which fills the spatial gaps of observed WBET and generates a spatially continuous WBET dataset. Synthetic WBET (2002–2015 annual average) of eight-digit hydrologic unit code (HUC8) basins across the conterminous United States (CONUS), constituting 44 % (887 out of 2035 basins) of CONUS basins, was determined within 2.0 % (RMSE = 12 %) of observed WBET at CONUS and between 1–12 % (RMSE = 3–33 %) across 18 regions in CONUS. With WABE-based bias corrections, the overall annual bias of RSET decreased from 10 % (RMSE = 34 %) to 6 % (RMSE = 26 %) across 37 flux tower sites. The WABE method offers a new approach for RSET accuracy improvement and shows great promise for large area implementations with a potential to yield substantial benefits for building accurate basin water budgets and water management decisions.

Khand, Kul↗

Evaluating post-fire watershed response to varying burn severity and precipitation regimes using fully-distributed and integrated hydrologic models

Wildfires can cause significant changes in vegetation and soil, which may lead to increased surface runoff and soil erosion, thereby affecting water cycling within ecosystems. This study uses the Advanced Terrestrial Simulator (ATS), an integrated and fully distributed hydrologic model at the watershed scale, to examine post-fire hydrologic responses in selected watersheds with varying burn severities in the Pacific Northwest region of the United States. The model integrates surface overland flow, subsurface flow, and canopy biophysical processes. We have developed a new fire module in ATS to account for changes in soil hydraulic properties caused by fire in the topsoil layer. Modeling results indicate that, in the year following a high-severity burn, watershed-averaged evapotranspiration decreases by 25%. Additionally, post-fire peak flows increase by 18-29% in watersheds burned with medium to high severity due to changes in soil properties. Conversely, a low-severity burn results in less than a 1% increase in post-fire peak flow. Furthermore, a high-severity fire causes a 38% reduction in the infiltration rate within the affected watershed during the first post-fire wet season. Hypothetical numerical experiments with varying precipitation regimes after a high-severity fire show that post-fire peak flows can increase by 1-29% due to fire-induced changes in soil hydraulic properties. This study highlights the importance of using fully distributed hydrologic models to quantify disturbance-feedback loops, which are essential for understanding the complexities brought about by spatial heterogeneity in post-fire landscapes.

ATS↗

The underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems in the Northern and Eastern United States

Spring phenology of temperate ecosystems is highly sensitive to climate change, generating various impacts on many important terrestrial surface biophysical processes. Although various prognostic models relying on environmental variables of temperature and photoperiod have been developed for spring phenology, comprehensive ecosystem-scale evaluations over large landscapes and long-time periods remain lacking. Further, environmental variables other than temperature and photoperiod might also importantly constrain spring phenology modelling but remain under-investigation. To address these issues, we leveraged around 20-years datasets of environmental variables (from Daymet and GLDAS products) and the spring phenology metric (i.e., the greenup date) respectively derived from MODIS and PhenoCams across 108 sites in the Northern and Eastern United States. We firstly cross-compared MODIS-derived greenup date with official PhenoCams product with high accuracy (R 2 = 0.70). Then, we evaluated the three prognostic models (i.e., Growing Degree Date (GDD), Sequential (SEQ) and optimality-based (OPT)) with MODIS-derived spring phenology, assessed the model residuals and their associations with soil moisture, rainfall, and solar radiation, and revised the two photoperiod-relevant models (SEQ, OPT) by replacing the daylength variable with solar radiation, which was found to contribute the most to model residuals. We found that 1) all models demonstrated good capability in characterizing spring phenology, with OPT performing the best (RMSE = 8.04 ± 5.05 days), followed by SEQ (RMSE = 10.57 ± 7.77 days) and GDD (RMSE = 10.84 ± 8.42 days), 2) all models displayed high model residuals showing tight correlation with solar radiation (r = 0.45–0.75), and 3) the revised models that included solar radiation significantly performed better with an RMSE reduction by 22.08%. Such results are likely because solar radiation better constrains early growing season plant photosynthesis than photoperiod, supporting the hypothesis of spring phenology as an adaptive strategy to maximize photosynthetic carbon gain (approximated by solar radiation) while minimizing frost damage risk (captured by temperature). Collectively, our study here reveals the underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems, and suggests ways to improve spring phenology modelling and other phenology-related ecological processes.

54 ENVIRONMENTAL SCIENCES↗

Coarse-Grained Double-Stranded RNA Model from Quantum-Mechanical Calculations

A coarse-grained model for simulating structural properties of double-stranded RNA is developed with parameters obtained from quantum-mechanical calculations. This model follows previous parametrization for double stranded DNA, which is based on mapping the all-atom picture to a coarse-grained four-bead scheme. Chemical and structural differences between RNA and DNA have been taken into account for the model development. The parametrization is based on simulations using density functional theory (DFT) on separate units of the RNA molecule without implementing experimental data. The total energy is decomposed into four terms of physical significance: hydrogen bonding interaction, stacking interactions, backbone interactions, and electrostatic interactions. The first three interactions are treated within DFT, whereas the last one is included within a mean field approximation. Our double-stranded RNA coarse-grained model predicts stable helical structures for RNA. Other characteristics, such as structural or mechanical properties are reproduced with a very good accuracy. The development of the coarse-grained model for RNA allows extending the spatial and temporal length scales accessed by computer simulations and being able to model RNA-related biophysical processes, as well as novel RNA nanostructures.

Cruz-León, Sergio↗

A Century of Reforestation Reduced Anthropogenic Warming in the Eastern United States

Abstract Restoring and preserving the world's forests are promising natural pathways to mitigate some aspects of climate change. In addition to regulating atmospheric carbon dioxide concentrations, forests modify surface and near‐surface air temperatures through biophysical processes. In the eastern United States (EUS), widespread reforestation during the 20th century coincided with an anomalous lack of warming, raising questions about reforestation's contribution to local cooling and climate mitigation. Using new cross‐scale approaches and multiple independent sources of data, we uncovered links between reforestation and the response of both surface and air temperature in the EUS. Ground‐ and satellite‐based observations showed that EUS forests cool the land surface by 1–2°C annually compared to nearby grasslands and croplands, with the strongest cooling effect during midday in the growing season, when cooling is 2–5°C. Young forests (20–40 years) have the strongest cooling effect on surface temperature. Surface cooling extends to the near‐surface air, with forests reducing midday air temperature by up to 1°C compared to nearby non‐forests. Analyses of historical land cover and air temperature trends showed that the cooling benefits of reforestation extend across the landscape. Locations surrounded by reforestation were up to 1°C cooler than neighboring locations that did not undergo land cover change, and areas dominated by regrowing forests were associated with cooling temperature trends in much of the EUS. Our work indicates reforestation contributed to the historically slow pace of warming in the EUS, underscoring reforestation's potential as a local climate adaptation strategy in temperate regions.

Environmental Sciences & Ecology↗

Increasing large wildfires over the western United States linked to diminishing sea ice in the Arctic

Abstract The compound nature of large wildfires in combination with complex physical and biophysical processes affecting variations in hydroclimate and fuel conditions makes it difficult to directly connect wildfire changes over fire-prone regions like the western United States (U.S.) with anthropogenic climate change. Here we show that increasing large wildfires during autumn over the western U.S. are fueled by more fire-favorable weather associated with declines in Arctic sea ice during preceding months on both interannual and interdecadal time scales. Our analysis (based on observations, climate model sensitivity experiments, and a multi-model ensemble of climate simulations) demonstrates and explains the Arctic-driven teleconnection through regional circulation changes with the poleward-shifted polar jet stream and enhanced fire-favorable surface weather conditions. The fire weather changes driven by declining Arctic sea ice during the past four decades are of similar magnitude to other leading modes of climate variability such as the El Niño-Southern Oscillation that also influence fire weather in the western U.S.

54 ENVIRONMENTAL SCIENCES↗

Cooling outweighs warming across phenological transitions in the Northern Hemisphere

Vegetation phenology, i.e., seasonal biological events such as leaf-out and leaf-fall, regulates local climate through biophysical processes like evapotranspiration (ET) and albedo. However, the net surface temperature impact of these processes—whether ET cooling or albedo-induced warming predominates—and how the dominance changes across phenological transitions and regions remains poorly understood. Here, we investigated the effects of vegetation foliage on daytime land surface temperature (LST) following six phenological transitions, spanning from the start of season to end of season, in deciduous and mixed forests across the mid- to high-latitude Northern Hemisphere during 2013–2021 using multiple satellite products and ground observations. We quantified vegetation effect as the difference between observed LST and LST estimates from the Annual Temperature Cycle (ATC) model, representing a no-foliage scenario. We found that vegetation-induced cooling consistently outweighs warming following all phenological transitions except for the end of the season. Cooling intensity increased with vegetation greenness, ranging from 1.0 ± 0.5 °C (mean ± 0.15 SD) in 59% of forests after the start of the season (SOS) to 6.1 ± 0.8 °C in 89% of forests following the onset of maturity, before declining toward the end of the season. Over half of the regions experiencing cooling showed intensification of surface cooling with climate warming, suggesting an amplified vegetation-mediated cooling under future climate change. The findings provide a more precise understanding of the role of vegetation in modulating climate at the intraseasonal scale, highlighting the importance of integrating phenological impacts into climate adaptation strategies and Earth system modeling.

albedo↗

Distinct roles of land cover in regulating spatial variabilities of temperature responses to radiative effects of aerosols and clouds

Surface temperature responses to radiative perturbations due to aerosols and clouds are complicated by the land surface properties. To disentangle these complexities, this study, from a terrestrial surface energy budget perspective, isolates the underlying biophysical processes from the instantaneous radiative effects of aerosols and clouds on surface temperature using the National Center for Atmospheric Research Community Earth System Model version 1.2.1. It is found that in comparison with the global heterogeneous distributions of instantaneous radiative perturbations at the surface induced by aerosols and clouds, the spatial variations of the corresponding surface temperature responses to aerosol direct radiative effects (DRE) during the daytime and cloud radiative effects (CRE) during the nighttime are amplified. It is because of the consistent global distribution of the local surface climate sensitivity (a function of land cover properties such as surface roughness and Bowen ratio) with those of daytime DRE and nighttime CRE. By applying identical anthropogenic aerosol and precursor emissions over eight major past, present and projected future anthropogenic aerosol emitting regions (i.e. Brazil, China, East Africa, India, Indonesia, South Africa, United States and Western Europe), surface temperature responses to aerosol radiative cooling in the daytime and cloud radiative warming in the nighttime over these regions positively regulated by local surface climate sensitivities are prominent.

54 ENVIRONMENTAL SCIENCES↗

Metastable Prepores in Tension-Free Lipid Bilayers

The formation and closure of aqueous pores in lipid bilayers is a key step in various biophysical processes. Large pores are well described by classical nucleation theory, but the free-energy landscape of small, biologically relevant pores has remained largely unexplored. The existence of small and metastable “prepores” was hypothesized decades ago from electroporation experiments, but resolving metastable prepores from theoretical models remained challenging. Using two complementary methods—atomistic simulations and self-consistent field theory of a minimal lipid model—we determine the parameters for which metastable prepores occur in lipid membranes. Here, both methods consistently suggest that pore metastability depends on the relative volume ratio between the lipid head group and lipid tails: lipids with a larger head-group volume fraction (or shorter saturated tails) form metastable prepores, whereas lipids with a smaller head-group volume fraction (or longer unsaturated tails) form unstable prepores.

59 BASIC BIOLOGICAL SCIENCES↗

Three dimensional time-gated tracking of non-blinking quantum dots in live cells

Single particle tracking has provided a wealth of information about biophysical processes such as motor protein transport and diffusion in cell membranes. However, motion out of the plane of the microscope or blinking of the fluorescent probe used as a label generally limits observation times to several seconds. Here, we overcome these limitations by using novel non-blinking quantum dots as probes and employing a custom 3D tracking microscope to actively follow motion in three dimensions (3D) in live cells. As a result, signal-to-noise is improved in the cellular milieu through the use of pulsed excitation and time-gated detection.

59 BASIC BIOLOGICAL SCIENCES↗