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At least 37 records · Page 2

Forest regeneration within Earth system models: current process representations and ways forward

Earth system models must predict forest responses to global change in order to simulate future global climate, hydrology, and ecosystem dynamics. These models are increasingly adopting vegetation demographic approaches that explicitly represent tree growth, mortality, and recruitment, enabling advances in the projection of forest vulnerability and resilience, as well as evaluation with field data. To date, simulation of regeneration processes has received far less attention than simulation of processes that affect growth and mortality, in spite of their critical role maintaining forest structure, facilitating turnover in forest composition over space and time, enabling recovery from disturbance, and regulating climate-driven range shifts. Here, our critical review of regeneration process representations within current Earth system vegetation demographic models reveals the need to improve parameter values and algorithms for reproductive allocation, dispersal, seed survival and germination, environmental filtering in the seedling layer, and tree regeneration strategies adapted to wind, fire, and anthropogenic disturbance regimes. These improvements require synthesis of existing data, specific field data-collection protocols, and novel model algorithms compatible with global-scale simulations. Vegetation demographic models offer the opportunity to more fully integrate ecological understanding into Earth system prediction; regeneration processes need to be a critical part of the effort.

54 ENVIRONMENTAL SCIENCES↗

Drought-induced decoupling between carbon uptake and tree growth impacts forest carbon turnover time

The ability of forests to withstand, and recover from, acute drought stress is a critical uncertainty regarding the impacts of climate change on the terrestrial carbon (C) cycle, but it is unclear how drought responses scale from individual trees to whole forests. Here, we assembled a dataset of tree-ring chronologies co-located within the footprint of eddy covariance towers across North America and Europe, with the aim of quantifying the sensitivity of tree radial growth versus gross primary productivity (GPP) during and following drought. We found that drought induced a large decoupling across C cycle processes, whereby GPP was relatively resistant to water stress despite large reductions in tree-ring widths. This decoupling also occurred in the year following drought (i.e., a ‘drought legacy effect’), and was similar in magnitude in response to both summer and winter droughts. By modeling whole-forest C turnover time, we show that a radial growth-GPP decoupling has important ramifications for the forest C cycle, especially if the C not used to support radial growth is instead allocated towards pools with short residence times. Furthermore, our results demonstrate that quantifications of drought impacts that rely solely on C uptake are missing this fundamental pathway through which drought alters the forest C cycle and the resulting feedbacks to the climate system.

54 ENVIRONMENTAL SCIENCES↗

Continent-wide tree fecundity driven by indirect climate effects

Indirect climate effects on tree fecundity that come through variation in size and growth (climate-condition interactions) are not currently part of models used to predict future forests. Trends in species abundances predicted from meta-analyses and species distribution models will be misleading if they depend on the conditions of individuals. Here we find from a synthesis of tree species in North America that climate-condition interactions dominate responses through two pathways, i) effects of growth that depend on climate, and ii) effects of climate that depend on tree size. Because tree fecundity first increases and then declines with size, climate change that stimulates growth promotes a shift of small trees to more fecund sizes, but the opposite can be true for large sizes. Change the depresses growth also affects fecundity. We find a biogeographic divide, with these interactions reducing fecundity in the West and increasing it in the East. Continental-scale responses of these forests are thus driven largely by indirect effects, recommending management for climate change that considers multiple demographic rates.

54 ENVIRONMENTAL SCIENCES↗

Evolutionary constraints and climate variability jointly shape starch–sugar balance in woody plants

Nonstructural carbohydrates (NSC) buffer plants against carbon imbalances, yet their partitioning between storage and soluble pools remains elusive at global scales. Here, we compiled a dataset of starch to soluble sugar ratio (St : Su) for 308 woody species across 220 sites world-wide and introduce a dimensionless index that integrates storage and demand while minimizing methodological artifacts. St : Su was strongly associated with growth, identifying it as a key axis of carbon allocation. Foliage consistently exhibited lower St : Su than lignified organs, reflecting a division between transient and conservative pools. Conifers accumulated more starch in foliage but less in stems relative to angiosperms, while leaf habits and mycorrhizal associations further modulated organ-specific strategies. Contrary to expectation, foliar and root St : Su varied little among biomes, but stems exhibited higher ratios in tropical rainforests than in boreal or arid regions, reflecting differences in species composition and adaptive storage under disturbance. Phylogeny constrained stem storage, whereas climatic variability, rather than mean conditions, dominated allocation in leaves and roots. These findings establish St : Su as a robust functional trait linking allocation strategies, growth, and resilience, which can be used to improve vegetation model prediction of forest productivity and mortality under climate variability.

Li, Weibin [Lanzhou Univ. (China)] (ORCID:00000001↗

A field guide for aging passerine nestlings using growth data and predictive modeling

Abstract Background Accurate nestling age is valuable for studies on nesting strategies, productivity, and impacts on reproductive success. Most aging guides consist of descriptions and photographs that are time consuming to read and subjective to interpret. The Western Bluebird ( Sialia mexicana ) is a secondary cavity-nesting passerine that nests in coniferous and open deciduous forests. Nest box programs for cavity-nesting species have provided suitable nesting locations and opportunities for data collection on nestling growth and development. Methods We developed models for predicting the age of Western Bluebird nestlings from morphometric measurements using model training and validation. These were developed for mass, tarsus, and two different culmen measurements. Results Our models were accurate to within less than a day, and each model worked best for a specific age range. The mass and tarsus models can be used to estimate the ages of Western Bluebird nestlings 0–10 days old and were accurate to within 0.5 days for mass and 0.7 days for tarsus. The culmen models can be used to estimate ages of nestlings 0–15 days old and were also accurate to within less than a day. The daily mean, minimum, and maximum values of each morphometric measurement are provided and can be used in the field for accurate nestling age estimations in real time. Conclusions The model training and validation procedures used here demonstrate that this method can create aging models that are highly accurate. The methods can be applied to any passerine species provided sufficient nestling morphometric data are available.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling the Joint Effects of Vegetation Characteristics and Soil Properties on Ecosystem Dynamics in a Panama Tropical Forest

Abstract In tropical forests, both vegetation characteristics and soil properties are important not only for controlling energy, water, and gas exchanges directly but also determining the competition among species, successional dynamics, forest structure and composition. However, the joint effects of the two factors have received limited attention in Earth system model development. Here we use a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM‐FATES, to explore how plant traits and soil properties affect tropical forest growth and composition concurrently. A large ensemble of simulations with perturbed vegetation and soil hydrological parameters is conducted at the Barro Colorado Island, Panama. The simulations are compared against observed carbon, energy, and water fluxes. We find that soil hydrological parameters, particularly the scaling exponent of the soil retention curve ( B sw ), play crucial roles in controlling forest diversity, with higher B sw values (>7) favoring late successional species in competition, and lower B sw values (1 ∼ 7) promoting the coexistence of early and late successional plants. Considering the additional impact of soil properties resolves a systematic bias of FATES in simulating sensible/latent heat partitioning with repercussion on water budget and plant coexistence. A greater fraction of deeper tree roots can help maintain the dry‐season soil moisture and plant gas exchange. As soil properties are as important as vegetation parameters in predicting tropical forest dynamics, more efforts are needed to improve parameterizations of soil functions and belowground processes and their interactions with aboveground vegetation dynamics.

54 ENVIRONMENTAL SCIENCES↗

Peak radial growth of diffuse-porous species occurs during periods of lower water availability than for ring-porous and coniferous trees

Climate models project warmer summer temperatures will increase the frequency and heat severity of droughts in temperate forests of Eastern North America. Hotter droughts are increasingly documented to affect tree growth and forest dynamics, with critical impacts on tree mortality, carbon sequestration and timber provision. The growing acknowledgement of the dominant role of drought timing on tree vulnerability to water deficit raises the issue of our limited understanding of radial growth phenology for most temperate tree species. Here, we use well-replicated dendrometer band data sampled frequently during the growing season to assess the growth phenology of 610 trees from 15 temperate species over 6 years. Patterns of diameter growth follow a typical logistic shape, with growth rates reaching a maximum in June, and then decreasing until process termination. On average, we find that diffuse-porous species take 16–18 days less than other wood-structure types to put on 50% of their annual diameter growth. However, their peak growth rate occurs almost a full month later than ring-porous and conifer species (ca. 24 ± 4 days; mean ± 95% credible interval). Unlike other species, the growth phenology of diffuse-porous species in our dataset is highly correlated with their spring foliar phenology. We also find that the later window of growth in diffuse-porous species, coinciding with peak evapotranspiration and lower water availability, exposes them to a higher water deficit of 88 ± 19 mm (mean ± SE) during their peak growth than ring-porous and coniferous species (15 ± 35 mm and 30 ± 30 mm, respectively). Given the high climatic sensitivity of wood formation, our findings highlight the importance of wood porosity as one predictor of species climatic sensitivity to the projected intensification of the drought regime in the coming decades.

59 BASIC BIOLOGICAL SCIENCES↗

Phosphorus limitation of early growth differs between nitrogen‐fixing and nonfixing dry tropical forest tree species

Summary Tropical forests are often characterized by low soil phosphorus (P) availability, suggesting that P limits plant performance. However, how seedlings from different functional types respond to soil P availability is poorly known but important for understanding and modeling forest dynamics under changing environmental conditions. We grew four nitrogen (N)‐fixing Fabaceae and seven diverse non‐N‐fixing tropical dry forest tree species in a shade house under three P fertilization treatments and evaluated carbon (C) allocation responses, P demand, P‐use, investment in P acquisition traits, and correlations among P acquisition traits. Nitrogen fixers grew larger with increasing P addition in contrast to non‐N fixers, which showed fewer responses in C allocation and P use. Foliar P increased with P addition for both functional types, while P acquisition strategies did not vary among treatments but differed between functional types, with N fixers showing higher root phosphatase activity (RPA) than nonfixers. Growth responses suggest that N fixers are limited by P, but nonfixers may be limited by other resources. However, regardless of limitation, P acquisition traits such as mycorrhizal colonization and RPA were nonplastic across a steep P gradient. Differential limitation among plant functional types has implications for forest succession and earth system models.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS↗

Anthropogenic extremely low volatility organics (ELVOCs) Govern the Growth of Molecular Clusters over the Southern Great Plains during the Springtime

New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.

Shrivastava, ManishKumar B.↗

Sensitivity of Optical Satellites to Estimate Windthrow Tree-Mortality in a Central Amazon Forest

Windthrow (i.e., trees broken and uprooted by wind) is a major natural disturbance in Amazon forests. Images from medium-resolution optical satellites combined with extensive field data have allowed researchers to assess patterns of windthrow tree-mortality and to monitor forest recovery over decades of succession in different regions. Although satellites with high spatial-resolution have become available in the last decade, they have not yet been employed for the quantification of windthrow tree-mortality. Here, we address how increasing the spatial resolution of satellites affects plot-to-landscape estimates of windthrow tree-mortality. We combined forest inventory data with Landsat 8 (30 m pixel), Sentinel 2 (10 m), and WorldView 2 (2 m) imagery over an old-growth forest in the Central Amazon that was disturbed by a single windthrow event in November 2015. Remote sensing estimates of windthrow tree-mortality were produced from Spectral Mixture Analysis and evaluated with forest inventory data (i.e., ground true) by using Generalized Linear Models. Field measured windthrow tree-mortality (3 transects and 30 subplots) crossing the entire disturbance gradient was 26.9 ± 11.1% (mean ± 95% CI). Although the three satellites produced reliable and statistically similar estimates (from 26.5% to 30.3%, p < 0.001), Landsat 8 had the most accurate results and efficiently captured field-observed variations in windthrow tree-mortality across the entire gradient of disturbance (Sentinel 2 and WorldView 2 produced the second and third best results, respectively). As expected, mean-associated uncertainties decreased systematically with increasing spatial resolution (i.e., from Landsat 8 to Sentinel 2 and WorldView 2). However, the overall quality of model fits showed the opposite pattern. We suggest that this reflects the influence of a relatively minor disturbance, such as defoliation and crown damage, and the fast growth of natural regeneration, which were not measured in the field nor can be captured by coarser resolution imagery. Our results validate the reliability of Landsat imagery for assessing plot-to-landscape patterns of windthrow tree-mortality in dense and heterogeneous tropical forests. Satellites with high spatial resolution can improve estimates of windthrow severity by allowing the quantification of crown damage and mortality of lower canopy and understory trees. However, this requires the validation of remote sensing metrics using field data at compatible scales.

54 ENVIRONMENTAL SCIENCES↗

The response of coarse root biomass to long-term CO 2 enrichment and nitrogen application in a maturing Pinus taeda stand with a large broadleaved component

Elevated atmospheric CO 2 (eCO 2 ) typically increases aboveground growth in both growth chamber and free-air carbon enrichment (FACE) studies. We report on the impacts of eCO 2 and nitrogen amendment on coarse root biomass and net primary productivity (NPP) at the Duke FACE study, where half of the eight plots in a 30-year-old loblolly pine (Pinus taeda, L.) plantation, including competing naturally regenerated broadleaved species, were subjected to eCO 2 (ambient, aCO 2 plus 200 ppm) for 15–17 years, combined with annual nitrogen amendments (11.2 g N m -2 ) for 6 years. Allometric equations were developed following harvest to estimate coarse root (>2 mm diameter) biomass. Pine root biomass under eCO 2 increased 32%, 1.80 kg m -2 above the 5.66 kg m -2 observed in aCO 2 , largely accumulating in the top 30 cm of soil. In contrast, eCO2 increased broadleaved root biomass more than twofold (aCO 2 : 0.81, eCO 2 : 2.07 kg m -2 ), primarily accumulating in the 30–60 cm soil depth. Combined, pine and broadleaved root biomass increased 3.08 kg m -2 over aCO 2 of 6.46 kg m -2 , a 48% increase. Elevated CO 2 did not increase pine root:shoot ratio (average 0.24) but increased the ratio from 0.57 to 1.12 in broadleaved species. Averaged over the study (1997–2010), eCO 2 increased pine, broadleaved and total coarse root NPP by 49%, 373% and 86% respectively. Nitrogen amendment had smaller effects on any component, singly or interacting with eCO 2 . A sustained increase in root NPP under eCO 2 over the study period indicates that soil nutrients were sufficient to maintain root growth response to eCO 2 . These responses must be considered in computing coarse root carbon sequestration of the extensive southern pine and similar forests, and in modelling the responses of coarse root biomass of pine–broadleaved forests to CO 2 concentration over a range of soil N availability.

9 allometry↗

Biosynthesis of bioprivileged, linear molecules via novel carboligase reactions

Over the award period, we made progress on the three aims. We screened twenty-five carboligases for activity coupling twenty-one possible -keto acids (Aim 1). The carboligases were selected across a diverse set of protein sequences. Using Q-Exactive UHPLC-MS, we tested a total of 210 coupled products per enzyme and generated a dataset of 5250 enzyme-substrate activity relationships. We identified multiple enzymes that had activity for synthesizing suberic acid and heptanoic acid (Aim 2). We built a random forest model for predicting the activity of each enzyme toward substrates on which it was not tested using the data from Aim 1. Finally, we evaluated growth defects that occurred due to expression of different carboligases in E. coli (Aim 3). We were able to identify specific metabolites and putative pathways that, when supplemented in the media, recovered the growth defect associated with the presence of specific carboligases. We are in the process of publishing two manuscript describing the methods for high-throughput screening of enzyme promiscuity, using machine learning to predict activity on untested substrates, and enzyme activity data we collected. This project has produced enabling data for biosynthesis of a range of new-to-nature compounds to support biomanufacturing.

60 APPLIED LIFE SCIENCES↗

Hydraulically‐vulnerable trees survive on deep‐water access during droughts in a tropical forest

Summary Deep‐water access is arguably the most effective, but under‐studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep‐water access may delay plant dehydration. Here, we tested the role of deep‐water access in enabling survival within a diverse tropical forest community in Panama using a novel data‐model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990–2015) to vapor pressure deficit, water potentials in the whole‐soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water‐access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981–2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress‐related mortality risk through deep‐water access. The role of deep‐water access in mitigating mortality of hydraulically‐vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

54 ENVIRONMENTAL SCIENCES↗

Increasing atmospheric dryness reduces boreal forest tree growth

Rising atmospheric vapour pressure deficit (VPD) associated with climate change affects boreal forest growth via stomatal closure and soil dryness. However, the relationship between VPD and forest growth depends on the climatic context. Here we assess Canadian boreal forest responses to VPD changes from 1951-2018 using a well-replicated tree-growth increment network with approximately 5,000 species-site combinations. Of the 3,559 successful growth models, we observed a relationship between growth and concurrent summer VPD in one-third of the species-site combinations, and between growth and prior summer VPD in almost half of those combinations. The relationship between previous year VPD and current year growth was almost exclusively negative, while current year VPD also tended to reduce growth. Tree species, age, annual temperature, and soil moisture primarily determined tree VPD responses. Younger trees and species like white spruce and Douglas fir exhibited higher VPD sensitivity, as did areas with high annual temperature and low soil moisture. Since 1951, summer VPD increases in Canada have paralleled tree growth decreases, particularly in spruce species. Accelerating atmospheric dryness in the decades ahead will impair carbon storage and societal-economic services.

54 ENVIRONMENTAL SCIENCES↗

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]↗

Harmonising the land-use flux estimates of global models and national inventories for 2000–2020

As the focus of climate policy shifts from pledges to implementation, there is a growing need to track progress on climate change mitigation at the country level, particularly for the land-use sector. Despite new tools and models providing unprecedented monitoring opportunities, striking differences remain in estimations of anthropogenic land-use CO 2 fluxes between, on the one hand, the national greenhouse gas inventories (NGHGIs) used to assess compliance with national climate targets under the Paris Agreement and, on the other hand, the Global Carbon Budget and Intergovernmental Panel on Climate Change (IPCC) assessment reports, both based on global bookkeeping models (BMs). Recent studies have shown that these differences are mainly due to inconsistent definitions of anthropogenic CO 2 fluxes in managed forests. Countries assume larger areas of forest to be managed than BMs do, due to a broader definition of managed land in NGHGIs. Additionally, the fraction of the land sink caused by indirect effects of human-induced environmental change (e.g. fertilisation effect on vegetation growth due to increased atmospheric CO 2 concentration) on managed lands is treated as non-anthropogenic by BMs but as anthropogenic in most NGHGIs. We implement an approach that adds the CO 2 sink caused by environmental change in countries' managed forests (estimated by 16 dynamic global vegetation models, DGVMs) to the land-use fluxes from three BMs. This sum is conceptually more comparable to NGHGIs and is thus expected to be quantitatively more similar. Our analysis uses updated and more comprehensive data from NGHGIs than previous studies and provides model results at a greater level of disaggregation in terms of regions, countries and land categories (i.e. forest land, deforestation, organic soils, other land uses). Our results confirm a large difference (6.7 GtCO 2 yr —1 ) in global land-use CO 2 fluxes between the ensemble mean of the BMs, which estimate a source of 4.8 GtCO 2 yr —1 for the period 2000–2020, and NGHGIs, which estimate a sink of —1.9 GtCO 2 yr —1 in the same period. Most of the gap is found on forest land (3.5 GtCO 2 yr —1 ), with differences also for deforestation (2.4 GtCO 2 yr —1 ), for fluxes from other land uses (1.0 GtCO 2 yr —1 ) and to a lesser extent for fluxes from organic soils (0.2 GtCO 2 yr —1 ). By adding the DGVM ensemble mean sink arising from environmental change in managed forests (—6.4 GtCO 2 yr —1 ) to BM estimates, the gap between BMs and NGHGIs becomes substantially smaller both globally (residual gap: 0.3 GtCO 2 yr —1 ) and in most regions and countries. However, some discrepancies remain and deserve further investigation. For example, the BMs generally provide higher emissions from deforestation than NGHGIs and, when adjusted with the sink in managed forests estimated by DGVMs, yield a sink that is often greater than NGHGIs. In summary, this study provides a blueprint for harmonising the estimations of anthropogenic land-use fluxes, allowing for detailed comparisons between global models and national inventories at global, regional and country levels. This is crucial to increase confidence in land-use emissions estimates, support investments in land-based mitigation strategies and assess the countries' collective progress under the Global Stocktake of the Paris Agreement.

54 ENVIRONMENTAL SCIENCES↗

Generalizing Microbial Parameters in Soil Biogeochemical Models: Insights From a Multi‐Site Incubation Experiment

Abstract Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case‐specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial‐ENzyme Decomposition model, this study aimed to test whether a common set of microbially‐relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two‐year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial‐relevant parameters for large‐scale soil model projections.

58 GEOSCIENCES↗