Biophysical Processes Research Articles

A Theoretical Framework to Quantify Ecosystem Pressure-Volume Relationships.

'Water potential' is the biophysically relevant measure of water status in vegetation relating to stomatal, canopy and hydraulic conductance, as well as mortality thresholds; yet, this cannot be directly related to measured and modelled fluxes of water at plot- to landscape-scale without understanding its relationship with 'water content'. The capacity for detecting vegetation water content via microwave remote sensing further increases the need to understand the link between water content and ecosystem function. In this review, we explore how the fundamental measures of water status, water potential and water content are linked at ecosystem-scale drawing on the existing theory of pressure-volume (PV) relationships. We define and evaluate the concept and limitations of applying PV relationships to ecosystems where the quantity of water can vary on short timescales with respect to plant water status, and over longer timescales and over larger areas due to structural changes in vegetation. As a proof of concept, plot-scale aboveground vegetation PV curves were generated from equilibrium (e.g., predawn) water potentials and water content of the above ground biomass of nine plots, including tropical rainforest, savanna, temperate forest, and a long-term Amazonian rainforest drought experiment. Initial findings suggest that the stored water and ecosystem capacitance scale linearly with biomass across diverse systems, while the relative values of ecosystem hydraulic capacitance and physiologically accessible water storage do not vary systematically with biomass. The bottom-up scaling approach to ecosystem water relations identified the need to characterise the distribution of water potentials within a community and also revealed the relevance of community-level plant tissue fractions to ecosystem water relations. We believe that this theory will be instrumental in linking our detailed understanding of biophysical processes at tissue-scale to the scale at which land surface models operate and at which tower-based, airborne and satellite remote sensing can provide information.

Predicting the sequence-dependent backbone dynamics of intrinsically disordered proteins.

How the sequences of intrinsically disordered proteins (IDPs) code for functions is still an enigma. Dynamics, in particular residue-specific dynamics, holds crucial clues. Enormous efforts have been spent to characterize residue-specific dynamics of IDPs, mainly through NMR spin relaxation experiments. Here, we present a sequence-based method, SeqDYN, for predicting residue-specific backbone dynamics of IDPs. SeqDYN employs a mathematical model with 21 parameters: one is a correlation length and 20 are the contributions of the amino acids to slow dynamics. Training on a set of 45 IDPs reveals aromatic, Arg, and long-branched aliphatic amino acids as the most active in slow dynamics whereas Gly and short polar amino acids as the least active. SeqDYN predictions not only provide an accurate and insightful characterization of sequence-dependent IDP dynamics but may also serve as indicators in a host of biophysical processes, including the propensities of IDP sequences to undergo phase separation.

Predicting the sequence-dependent backbone dynamics of intrinsically disordered proteins

How the sequences of intrinsically disordered proteins (IDPs) code for functions is still an enigma. Dynamics, in particular residue-specific dynamics, holds crucial clues. Enormous efforts have been spent to characterize residue-specific dynamics of IDPs, mainly through NMR spin relaxation experiments. Here, we present a sequence-based method, SeqDYN, for predicting residue-specific backbone dynamics of IDPs. SeqDYN employs a mathematical model with 21 parameters: one is a correlation length and 20 are the contributions of the amino acids to slow dynamics. Training on a set of 45 IDPs reveals aromatic, Arg, and long-branched aliphatic amino acids as the most active in slow dynamics whereas Gly and short polar amino acids as the least active. SeqDYN predictions not only provide an accurate and insightful characterization of sequence-dependent IDP dynamics but may also serve as indicators in a host of biophysical processes, including the propensities of IDP sequences to undergo phase separation.

Light attenuation parameterization in a highly turbid mega estuary and its impact on the coastal planktonic ecosystem

Light is essential for phytoplankton photosynthesis and many other biogeochemical processes in the aquatic system. However, light regimes vary greatly in the estuaries and coasts due to the optical complexity of the Case-2 waters. In this study, observed vertical profiles of photosynthetically active radiation (PAR; 400-700 nm) in a highly turbid mega estuary, the Changjiang (Yangtze River) Estuary, are used to quantify the effects of sedimentary and biogeochemical components on PAR attenuation in the water column and associated ecological impacts. The in-situ data suggest suspended sediment plays the most crucial role in light diffuse attenuation coefficient (Kd) distribution, followed by salinity (i.e., an index for colored dissolved organic matter) and phytoplankton chlorophyll-a. A new parameterization of Kd, based on suspended sediment, chlorophyll-a concentration, and salinity, is fitted using multiple linear regression. The previous and new Kd parameterizations are further applied to a coupled hydrodynamics-sediment-ecosystem model to simulate spring phytoplankton blooms. Comparative model runs reveal that the new Kd parameterization resulted in a better representation of the spring bloom patterns in magnitude, horizontal distribution, and vertical thickness of the high chlorophyll-a band offshore the turbidity maximum zone during the spring bloom. In summary, accurate representations of underwater light fields in the optically complex Case-2 water are critical in understanding biophysical processes that control planktonic ecosystem dynamics in the estuaries and coastal seas.

Influence of soil microplastic contamination on maize (Zea mays) development and microbial dynamics

BackgroundMicroplastics are contaminants in soil ecosystems that alter biophysical processes, affect plant growth, ecosystems and humans in the long run. This study was conducted to investigate the influence of soil microplastic contamination on the growth, development, and microbial dynamics of maize (Zea mays).Composite soil samples were collected from the farm from 0 to 10 cm depth. Physicochemical properties were assessed before maize seed sowing. Three soil weight categories were treated with 30 g, 20 g and 10 g microplastics. Soil physicochemical properties and heavy metal content in maize plants were analyzed. Morphological parameters, microbial counts, and microorganism identification were conducted. FTIR analysis was carried out in selected plant parts.ResultsThe study revealed a pH range of 5.00–6.70, electrical conductivity of 70–158 µS/cm, organic carbon and organic matter, total nitrogen, average phosphorus content, clay and silt content. The concentrations of heavy metals in plant parts were within WHO standard limits of 425.5 and 500 mg/kg for iron and manganese, but above the limits of 40, 60, and 350 mg/kg for copper, zinc and magnesium. The plant had various leaf sizes and heights, with chlorosis and necrotic activity ranging from 0.33 to 2.67, and a range of 1.33 to 6.33, respectively. Soil samples showed a total bacterial count (TBC) of 2.00 × 103 cfu/g to 7.60 × 104 cfu/g and a total fungal count (TFC) of 4.00 × 103 cfu/g to 2.20 × 104 cfu/g. Pseudomonas aeruginosa, Bacillus subtilis, Escherichia coli, Staphylococcus epidermidis, Proteus mirabilis and Bacillus cereus had percentage occurrences of 44.31, 21.17, 9.12, and 3.26%, respectively. Penicillium notatum was the most prevalent, while Fusarium spp. was the least prevalent. The FTIR analysis of maize seeds from soil samples A, B, and C revealed various organic compounds, with opium powder and streptomycin sulphate being the most abundant. The study revealed that pot B had the highest microplastic concentration at 1 WAS, while pot C had the lowest at 0.10 mg/kg, indicating a differential soil microplastic accumulation.ConclusionMicroplastics impact soil health, plant growth, and nutrient cycling, necessitating sustainable agriculture. Long-term research is needed to understand ecological and physiological impacts and explore remediation techniques.

Memory Effects Explain the Fractional Viscosity Dependence of Rates Associated with Internal Friction: Simple Models and Applications to Butane Dihedral Rotation.

Barrier-crossing rates of biophysical processes, ranging from simple conformational changes to protein folding, often deviate from the Kramers prediction of an inverse viscosity dependence. In many recent studies, this has been attributed to the presence of internal friction within the system. Previously, we showed that memory-dependent friction arising from the nonequilibrium solvation of a single particle crossing a smooth one-dimensional barrier can also cause such a deviation and be misinterpreted as internal friction. Here we introduce a simple diatom model and show that even in the absence of explicit solvent, internal memory effects arise due to coupling of the reaction coordinate motion with frictionally orthogonal degrees of freedom. This results in a fractional viscosity dependence and a deviation from Kramers' theory, typically attributed to the presence of internal friction. This model therefore mimics several biological processes where a local conformational change of a biomolecule is often influenced by its surroundings. This gives rise to an apparent "internal friction" commonly measured in terms of empirical fitting parameters α and σ. We propose a microscopic measure of this internal friction using Grote-Hynes theory which employs memory-dependent friction. We use butane to demonstrate the effect of coupling strength on the internal friction in realistic systems. This model therefore can serve the purpose of understanding internal friction in biological systems in terms of such coupling.

Water compression induced ionic negative differential resistance in nanopores.

The mass transport behavior through nanoscale channels, greatly influenced by the structures and dynamics of nanoconfined water, plays an essential role in many biophysical processes. However, the dynamics of nanoconfined water under an external field and its effects are still not fully understood. Here, on the basis of molecular dynamics simulations, we theoretically show that the ionic current of [Bmim][PF6] through narrow pores in graphene membrane exhibits an ionic negative differential resistance effect-the ionic current decreases as the voltage increases over a certain threshold. This effect arises from the violation of traditional fluid dynamics as the assumption of continuity and homogeneity of fluids is no longer effective in ultrathin nanopores. The gradient of electric field around the atomic-thin layer produces a strong gradient force on the polarized water inside the nanopore. This dielectrophoretically compressed water leads to a hydrostatic force that repels ions from entering the nanopore. Our findings may advance the understanding of hydrostatic mechanism, which governs ion transport through nanopores.

Transition Processes in Dutch Spatial Planning and Water Management: A Shift to the Natural

Climate change is causing more extreme weather conditions in the Netherlands. In response, local governments such as Provinces, Municipalities, and regional Water Boards are encouraged to explore more nature-inclusive ways to keep society safe from flooding and drought. This is considered a transition from the earlier belief that environmental and societal challenges can be solved solely through technical engineering. Instead, landscape-based, climate-adaptive visions offer alternatives on how Dutch regions can maintain water security while also incorporating space for biodiversity, climate mitigation, healthy livelihood and expanding populations. So far, not much is known about the challenges project leaders from different organisations and local governments are facing during the development and implementation of such visions. To address this gap, we used the concept of learning history to build an archive capturing the insider perspective of project leaders tasked with co-creating landscape-based, climate-adaptive visions for future spatial planning and water management across four regions of the Netherlands. By observing and interviewing project leaders, we noticed how co-creating long-term visions enabled more climate-conscious dialogues between local government authorities and civil stakeholder groups. Reflecting on this archive, we gained insights into the strategic challenges associated with adopting biophysical processes as a foundational framework for future spatial development and policy-making. Furthermore, we documented examples of tactical approaches employed by project leaders to navigate these challenges effectively.

Growth, Evapotranspiration, Gas Exchange and Chl a Fluorescence of Ipê-Rosa Seedlings at Different Levels of Water Replacement.

In general, young plants in the establishment phase demonstrate sensitivity to changes in environmental conditions, especially regarding water availability. The effects of the seasonality of biophysical processes on plant physiology can trigger differential responses, even within the same region, making it necessary to conduct studies that characterize the physiological performance of the species at different spatial and temporal scales, making it possible to understand their needs and growth limits under water stress conditions. This paper aimed to evaluate the growth, gas exchange and Chl a fluorescence in ipê-rosa seedlings subjected to levels of water replacement (LWRs) of 100, 75, 50 and 25% in a greenhouse. The morphometric variables of plant height, diameter at stem height, numbers of leaves and leaflets, root length and volume, plant dry mass and leaf area were evaluated. The potential evapotranspiration of seedlings (ETc) was obtained using direct weighing, considering the water replacement of 100% of the mass variation between subsequent days as a reference; the cultivation coefficients (kc) were obtained using the ratio between ETc and the reference evapotranspiration (ETo) obtained by the Penman-Monteith FAO-56 method. Biomass and evapotranspiration data were combined to determine water sensitivity. Diurnal fluxes of gas exchange (net photosynthesis rate, transpiration rate, stomatal conductance, internal and atmospheric carbon ratio, water use efficiency and leaf temperature) and Chl a fluorescence (Fv/Fm, ΦPSII, ETR, Fv'/Fm', NPQ and qL) were evaluated. Water restriction caused reductions of 90.9 and 84.7% in the increase in height and diameter of seedlings subjected to 25% water replacement when compared to seedlings with 100% water replacement. In comparison, biomass accumulation was reduced by 96.9%. The kc values increased throughout the seedling production cycle, ranging from 0.59 to 2.86. Maximum water sensitivity occurred at 50% water replacement, with Ky = 1.62. Maximum carbon assimilation rates occurred in the morning, ranging from 6.11 to 12.50 µmol m-2 s-1. Ipê-rosa seedlings regulate the physiology of growth, gas exchange and Chl a fluorescence depending on the amount of water available, and only 25% of the water replacement in the substrate allows the seedlings to survive.

A Pressure-Based Model of IV Fluid Therapy Kinetics.

The kinetics of intravenous (IV) fluid therapy and how it affects the movement of fluids within humans and animals is an ongoing research topic. Clinical researchers have in the past used a mathematical model adopted from pharmacokinetics that attempts to mimic these kinetics. This linear model is based on the ideas that the body tries to maintain fluid levels in various compartments at some baseline targets and that fluid movement between compartments is driven by differences between the actual volumes and the targets. Here a nonlinear pressure-based model is introduced, where the driving force of fluid movement out of the blood stream is the pressure differences, both hydrostatic and oncotic, between the capillaries and the interstitial space. This model is, like the linear model, a coarse representation of fluid movement on the whole body scale, but, unlike the linear model, it is based on some of the body's biophysical processes. The abilities of both models to fit data from experiments on both awake and anesthetized cats was analyzed. The pressure-based model fit the data better than the linear model in all but one case, and was deemed statistically significantly better in a third of the cases.

Life, Death and Energy: What Does Nature Select?

Evolutionary biology is poised for a third major synthesis. The first presented Darwin's evidence from natural history. The second incorporated genetic mechanisms. The third will be based on energy and biophysical processes. It should include the equal fitness paradigm (EFP), which quantifies how organisms convert biomass into surviving offspring. Natural selection tends to maximise energetic fitness, , where is mass-specific rate of cohort biomass production, is generation time, is fraction of cohort production that is passed to surviving offspring, and is energy density of biomas. At steady state, parents replace themselves with offspring of equal mass-specific energy content, ≈ 22.4 kJ/g, and biomass, ≈ 1 g/g. The EFP highlights: (i) the energetic basis of survival and reproduction; (ii) how natural selection acts directly on the parameters of ; (iii) why there is no inherent intrinsic fitness advantage for higher metabolic power, ontogenetic or population growth rate, fecundity, longevity, or resource use efficiency; and (iv) the role of energy in animals with a variety of life histories. Underlying the spectacular diversity of living things is pervasive similarity in how energy is acquired from the environment and used to leave descendants offspring in future generations.

Elucidating the link between binding statistics and Shannon information in biological networks.

The response of a biological network to ligand binding is of crucial importance for regulatory control in various cellular biophysical processes that is achieved with information transmission through the different ligand-bound states of such networks. In this work, we address a vital issue regarding the link between the information content of such network states and the experimentally measurable binding statistics. Several fundamental networks of cooperative ligand binding, with the bound states being adjacent in time only and in both space and time, are considered for this purpose using the chemical master equation approach. To express the binding characteristics in the language of information, a quantity denoted as differential information index is employed based on the Shannon information. The index, determined for the whole network, follows a linear relationship with (logarithmic) ligand concentration with a slope equal to the size of the system. On the other hand, the variation of Shannon information associated with the individual network states and the logarithmic sensitivity of its slope are shown to have generic forms related to the average binding number and variance, respectively, the latter yielding the Hill slope, the phenomenological measure of cooperativity. Furthermore, the variation of Shannon information entropy, the average of Shannon information, is also shown to be related to the average binding.

Pine woodland fire dynamics mirror industrial history at New River Gorge National Park and Preserve, West Virginia, USA

Fire is an important biophysical process in pine (Pinus) and mixed pine-oak (Quercus) forests and woodlands across the Central Appalachian Mountains. Decades of fire exclusion, however, particularly on public lands, have resulted in a well-documented homogenization of species composition and forest structure. Our objective was to inform management and restoration efforts by expanding on previous dendroecological research at New River Gorge National Park and Preserve and adjacent Babcock State Park in southern West Virginia. Specifically, we assessed pine woodland fire activity in the context of local industrial history, land management, and regional drought. Samples cut from 110 fire-scarred pine trees, distributed across four sites, were used to develop a fire-scar record that spans the period 1842–2010; however, sample depth diminishes rapidly before the 1860s. Fires occurred frequently and extensively in the early–mid 20th century, coinciding with peak coal production and population density. Eleven major fires, or years when at least two trees and 25 % of samples recorded a fire scar at an individual site, were documented in the tree-ring record, but none occurred during the federal land management era (1978–present). Synchronous fire events recorded at two or more sites were associated with drier than average September–May (‘dormant season’) climate conditions. Our results indicate that, since the late 19th century, fire activity in pine woodlands at the New River Gorge has been driven primarily by human ignitions associated with industrial activities, and that periods of drought have amplified landscape-scale fire occurrence. Land managers should consider these historical fire patterns when developing restoration strategies that may include prescribed fire, thinning treatments, and managed wildfires.

The local cooling potential of land restoration in Africa

Land restoration is becoming increasingly popular as a climate change mitigation and adaptation measure. It is suggested that resulting vegetation changes can impact the local surface temperature through biophysical processes such as albedo warming and evaporative cooling. Yet, the potential effect of land restoration on the local surface temperature in Africa remains uncertain. In this study, we use Terra MODIS time series of vegetation, albedo, and land surface temperature to determine vegetation-temperature relationships at a continental scale. We show that vegetation-albedo and vegetation-temperature relationships do not only vary spatially across Africa but also temporally over different time scales, with strong cooling effects in semi-arid environments. Furthermore, we predict that land restoration can decrease local land surface temperature by around 0.2 Kelvin on average. This study gives a more detailed insight into where future land restoration provides additional positive climate impacts, and where land restoration may instead warm the local environment.

Manipulating long-term fates of sonoporated cells by regulating intracellular calcium for improving sonoporation-based delivery

Sonoporation-based delivery has great promise for noninvasive drug and gene therapy. After short-term membrane resealing, the long-term function recovery of sonoporated cells affects the efficiency and biosafety of sonoporation-based delivery. It is necessary to identify the key early biological signals that influence cell fate and to develop strategies for manipulating the long-term fates of sonoporated cells. Here, we used a customized experimental platform with a single cavitating microbubble induced by a single ultrasound pulse (frequency: 1.5 MHz, pulse length:13.33 μs, peak negative pressure: ∼0.40 MPa) to elicit single-site reversible sonoporation on a single HeLa cell model. We used a living-cell microscopic imaging system to trace the long-term fates of sonoporated HeLa cells in real-time for 48 h. Fluorescence from intracellular propidium iodide and Fluo-4 was used to evaluate the degree of sonoporation and intracellular calcium fluctuation (ICF), respectively. Changes in cell morphology were used to assess the long-term cell fates (i.e., proliferation, arrest, or death). We found that heterogeneously sonoporated cells had different long-term fates. With increasing degree of sonoporation, the probability of normal (proliferation) and abnormal fates (arrest and death) in sonoporated cells decreased and increased, respectively. We identified ICF as an important early event for triggering different long-term fates. Reversibly sonoporated cells exhibited stronger proliferation and restoration at lower extents of ICF. We then regulated ICF dynamics in sonoporated cells using 2-APB or BAPTA treatment to reduce calcium release from intracellular organelles and enhance intracellular calcium clearance, respectively. This significantly enhanced the proliferation and restoration of sonoporated cells and reduced the occurrence of cell-cycle arrest and death. Finally, we found that the long-term fates of sonoporated cells at multiple sites and neighboring cells were also dependent on the extent of ICF, and that 2-APB significantly enhanced their viability and reduced death. Thus, using a single HeLa cell model, we demonstrated that regulating intracellular calcium can effectively enhance the proliferation and restoration capabilities of sonoporated cells, therefore rescuing the long-term viability of sonoporated cells. These findings add to our understanding of the biophysical process of sonoporation and help design new strategies for improving the efficiency and biosafety of sonoporation-based delivery.

Structural visualization of inhibitor binding in prolyl oligopeptidase.

The association and dissociation of proteins and ligands are crucial in biophysics for potential drug development [Baron and McCammon, Annu. Rev. Phys. Chem. 64, 151-175 (2013)]. However, identifying and characterizing the reaction pathways for these rare events has been a long-standing challenge. Molecular dynamics (MD) simulations are limited in exploring biophysical processes on experimental timescales, so ligand transport processes through complex transient tunnels formed by proteins during dynamics are often simulated using enhanced sampling MD [Rydzewski and Nowak, Phys. Life Rev. 22-23, 58-74 (2017)]. Erroneously identified ligand binding pathways can affect thermodynamic and kinetic characteristics calculated from MD trajectories. A system that has the potential to be a therapeutic target for neurodegenerative diseases is prolyl oligopeptidase (PREP). This is due to its involvement in promoting protein aggregation and disrupting cellular function through affecting protein-protein interactions (PPI). The recent discovery of a new type of PREP inhibitor that targets PPI raises important questions about the diversity of ligand binding pathways in PREP and their impact on protein dynamics [Pätsi et al., J. Med. Chem. 67, 5421-5436 (2024); Kilpeläinen et al., J. Med. Chem. 66, 7475-7496 (2023); and Walczewska-Szewc et al., Phys. Chem. Chem. Phys. 24, 4366-4373 (2022)]. In this article, using results from enhanced sampling MD, we visually present how the binding process in PREP depends on subtle changes in inhibitors, which could be crucial in treating neurodegenerative disorders.

Rapid flowing cells localization enabled by spatiotemporal manipulation of their holographic patterns.

Lab-on-a-Chip microfluidic devices present an innovative and cost-effective platform in the current trend of miniaturization and simplification of imaging flow cytometry; they are excellent candidates for high-throughput single-cell analysis. In such microfluidic platforms, cell tracking becomes a fundamental tool for investigating biophysical processes, from intracellular dynamics to the characterization of cell motility and migration. However, high-throughput and long-term cell tracking puts a high demand on the consumption of computing resources. Here, we propose a novel strategy to achieve rapid 3D cell localizations along the microfluidic channel. This method is based on the spatiotemporal manipulation of recorded holographic interference fringes, and it allows fast and precise localization of cells without performing complete holographic reconstruction. Conventional holographic tracking is typically based on the phase contrast obtained by decoupling the calculation of optical axial and transverse coordinates. Computing time and resource consumption may increase because all the frames need to be calculated in the Fourier domain. In our proposed method, the 2D transverse positions are directly located by morphological calculation based on the hologram. The complex-amplitude wavefronts are directly reconstructed by spatiotemporal phase shifting to calculate the axial position by the refocusing criterion. Only spatial calculation is considered in the proposed method. We demonstrate that the computational time of transverse tracking is only one-tenth of the conventional method, while the total computational time of the proposed method decreases up to 54% with respect to the conventional approach. The proposed approach can open the route for analyzing flow cytometry in quantitative phase microscopy assays.

A Diagnostic Accountability of the Proportional Contribution Rate of Extent of Biophysical Processes of Desertification and the Landscape Changes in the Drylands of North Eastern Zone of Nigeria

A Diagnostic Accountability of the Proportional Contribution Rate of Extent of Biophysical Processes of Desertification and the Landscape Changes in the Drylands of North Eastern Zone of Nigeria

Decreased cloud cover partially offsets the cooling effects of surface albedo change due to deforestation

Biophysical processes of forests affect climate through the regulation of surface water and heat fluxes, which leads to further effects through the adjustment of clouds and water cycles. These indirect biophysical effects of forests on clouds and their radiative forcing are poorly understood but highly relevant in the context of large-scale deforestation or afforestation, respectively. Here, we provide evidence for local decreases in global low-level clouds and tropical high-level clouds from deforestation through both idealized deforestation simulations with climate models and from observations-driven reanalysis using space-for-time substitution. The decreased cloud cover can be explained by alterations in surface turbulent heat flux, which diminishes uplift and moisture to varying extents. Deforestation-induced reduction in cloud cover warms the climate, partially counteracting the cooling effects of increased surface albedo. The findings from idealized deforestation experiments and space-for-time substitution exhibit disparities, with global average offsets of, respectively, approximately 44% and 26%, suggesting the necessity for further constraints.

Integration of prognostic sowing and harvesting schemes to enhance crop dynamic growth simulation in Noah-MP-Crop model

Detailed sowing and harvesting (S&H) information is crucial for climate-coupled crop models to accurately simulate dynamic crop growth. The timing of intra-annual crop growth not only reflects adaptation to climate change but also significantly influences terrestrial biophysical and biochemical processes, as well as the local climate. However, accurately providing sowing and harvesting dates in crop models is challenging due to the limited availability of S&H observations worldwide. In this study, we integrated a prognostic S&H scheme into the Noah-MP-Crop model to eliminate the need for prescribed S&H dates and optimised key crop-related parameters to better reproduce dynamic maize and soybean growth in the U.S. Corn Belt. Results indicated that the bias in estimating site-level S&H dates was within one week. The prognostic S&H schemes, along with optimised crop-related parameters, effectively captured maize and soybean growth at the site scale, as evidenced by leaf area index (LAI) and gross primary production (GPP) simulations. The determination coefficient (R2) for GPP ranged from 0.88 to 0.91 for maize and from 0.70 to 0.82 for soybean at two flux stations. Moreover, the prognostic schemes exhibited better regional LAI and GPP simulations at the beginning and end of the growing season compared to those using state-level median S&H dates, with significant improvements in correlation coefficients ranging from 0 to 0.6, particularly in maize-dominated regions. However, the accuracy in reproducing latent heat flux and sensible heat flux was less satisfactory and showed little association with crop growth status. This work provides an alternative approach to obtaining crop sowing and harvesting information in the Noah-MP-Crop model and facilitates studies on interactions between dynamic crop growth and the climate system, particularly when coupled with the widely used Weather Research and Forecasting (WRF) model.