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At least 271 records · Page 15

Accounting for herbaceous communities in process‐based models will advance our understanding of “grassy” ecosystems

Abstract Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process‐based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

59 BASIC BIOLOGICAL SCIENCES↗

Soil Carbon Saturation: What Do We Really Know?

Managing soils to increase organic carbon storage presents a potential opportunity to mitigate and adapt to global change challenges, while providing numerous co-benefits and ecosystem services. However, soils differ widely in their potential for carbon sequestration, and knowledge of biophysical limits to carbon accumulation may aid in informing priority regions. Consequently, there is great interest in assessing whether soils exhibit a maximum capacity for storing organic carbon, particularly within organo–mineral associations given the finite nature of reactive minerals in a soil. While the concept of soil carbon saturation has existed for over 25 years, recent studies have argued for and against its importance. Here, we summarize the conceptual understanding of soil carbon saturation at both micro- and macro-scales, define key terminology, and address common concerns and misconceptions. We review methods used to quantify soil carbon saturation, highlighting the theory and potential caveats of each approach. Critically, we explore the utility of the principles of soil carbon saturation for informing carbon accumulation, vulnerability to loss, and representations in process-based models. We highlight key knowledge gaps and propose next steps for furthering our mechanistic understanding of soil carbon saturation and its implications for soil management.

Environmental sciences↗

Wildfire‐Induced Losses of Soil Particulate and Mineral‐Associated Organic Carbon Persist for Over 4 Years in a Chaparral Ecosystem

ABSTRACT Wildfires can lower soil carbon (C) stocks directly through combustion, but also indirectly during post‐fire recovery if microbial C demands outpace photosynthetic C inputs. However, how much C is respired by soil microorganisms post‐fire may depend on wildfire effects on particulate organic carbon (POC; mostly plant material accessible to microbes) and/or mineral‐associated organic carbon (MAOC; considered C protected by minerals from decomposers), meaning assessment of wildfire impacts on these pools is necessary to predict microbial decomposition rates and, thus, the fate of soil C. Here, we measured POC, MAOC, pyrogenic organic matter C, plant cover, extracellular enzyme activity (EEA), and microbial community abundance and composition 17 days, and 1, 3, and 4 years after the Holy Fire burned 94 km 2 of fire‐adapted chaparral. The wildfire immediately decreased POC by 50% (from 51 ± 21 to 26 ± 6 g C kg −1 ) and MAOC by 33% (from 9.3 ± 0.9 to 6.3 ± 0.9 g C kg −1 ), consistent with MAOC being less vulnerable to loss than POC. POC decreased by another 38% 1 year post‐fire, consistent with increases in microbial abundance and EEA suggesting increased microbial decomposition. Between 1 and 4 years after the fire, cover of the dominant shrub (Arctostaphylos glandulosa) increased from 3.9% ± 1.6% to 16% ± 5.4% (compared to 58% ± 4.6% in unburned plots), marking the end of net soil C losses. Still, soil C did not increase between 1 and 4 years post‐fire, suggesting plant C inputs did not outpace microbial respiration, a finding consistent with isotopically heavier C from microorganisms raising bulk soil δ 13 C values. As global changes favor increases in wildfire frequency and severity, C losses via combustion and decomposition may outpace plant C inputs during the first 4 years post‐fire in chaparral, slowing the replenishment of soil C stocks.

Biodiversity & Conservation↗

Which Plant Traits Increase Soil Carbon Sequestration? Empirical Evidence From a Long‐Term Poplar Genetic Diversity Trial

Plants play a key role in mediating soil response to global change, and breeding or engineering crops to increase soil organic carbon (SOC) storage is a potential route to land-based carbon dioxide removal in agricultural systems. However, due to limited observational datasets plus shifting paradigms of SOC stabilization, it is unclear which plant traits are most important for enhancing different types of soil organic matter. Existing long-term common gardens of genetically diverse plant populations may provide an opportunity to evaluate biological controls on SOC, separate from environmental or management variability. Here we report on soil and root chemical data collected for 24 genotypes within a 13-year-old common garden in northwestern Oregon planted with a large natural variant population of Populus trichocarpa. Fractionating surface soil (0–15 cm) revealed substantial variation in stocks of mineral-associated organic matter (MAOM; 18–67 t C/ha) and particulate organic matter (POM; 2–22 t C/ha). Tree genotype explained 24% and 26% of the MAOM and POM stock variability, respectively, after controlling for background variability. We found minimal association between SOC concentration and either aboveground tree productivity or root biomass recalcitrance (C/N ratios and lignin content). In contrast, root elemental content appeared influential for MAOM-C concentration, which showed a strong positive association with root aluminum (Al) and a strong negative association with root boron (B) and magnesium (Mg). Furthermore, root concentrations of these elements were highly heritable (57%–78%) and not simply a reflection of background variation in soil elemental concentrations. We estimate that surface SOC stocks under these 24 genotypes have diverged at rates of up to 1.2–4.3 t C/ha/year. These results suggest that long-term genetic diversity trials have value for elucidating biological controls on soil organic matter dynamics, and that traits associated with root elemental content may be a useful target for enhancing biosequestration.

biomass recalcitrance↗

Eddy Covariance Theory: A Review

Eddy covariance (EC), the gold standard for measuring ecosystem scale gas and heat exchanges, has transformed our understanding of the breathing of the biosphere, and thus global change biology. Despite numerous methodological improvements and insights gained from the technique, the community faces persistent challenges that have been present since the first EC measurements. Here, we review the theoretical developments underpinning EC. We present theoretical developments in four important areas that have relevance to EC measurements of the net ecosystem exchanges (NEE) of gases and heat from a single tower: (i) measuring the total vertical flux density, (ii) flux attenuation, (iii) coordinate rotations, and (iv) energy balance closure. Persistent problems with EC measurements, such as the inability to close the energy budget, led us to identify two priorities for revisiting the theory underlying: (i) sensible heat flux calculations, and (ii) constraining the mean vertical wind velocity. We present a framework for improved calculation of sensible heat flux derived from first principles of fluid mechanics and thermodynamics that considers coupled heat and mass transfer so that conservation of both is obeyed. These refinements are motivated by the need for unbiased measurements of energy and mass transfer between the land surface and atmosphere for ecosystem research and to validate satellite observations and land surface models.

ecosystem fluxes↗

Mycorrhizal associations of tree species influence soil nitrogen dynamics via effects on soil acid–base chemistry

Across all spatial scales, ECM-dominated forests were associated with greater soil acidity. In particular, ECM-dominated soils exhibited lower soil pH and base cations, although the magnitude of mycorrhizal-associated differences in soil acid–base chemistry depended on the biomes, with differences being more pronounced in temperate than in sub/tropical forests. Higher lignin and lower base cations in ECM tree leaf litter were related to greater soil acidity in ECM-dominated forests. Moreover, the lower inorganic N concentrations and slower N transformation rates in ECM-dominated forests were associated with their greater soil acidity. Our results indicate that the scale-invariant feedbacks between plant nutrient-use strategies and soil properties have the potential to impact forest community assembly and ecosystem processes, particularly in the context of global change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?

Abstract Aim Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m). Location Eastern USA. Time period 2017–2018. Taxa studied Trees. Methods With a fusion of hyperspectral and lidar data from the NEON AOP, we assess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics. Results Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity. Main conclusions We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine‐resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above.

54 ENVIRONMENTAL SCIENCES↗

Short-term variation in leaf-level water use efficiency in a tropical forest

Here we report the representation of stomatal regulation of transpiration and CO 2 assimilation is key to forecasting terrestrial ecosystem responses to global change. Given its importance in determining the relationship between forest productivity and climate, accurate and mechanistic model representation of the relationship between stomatal conductance (g s ) and assimilation is crucial. We assess possible physiological and mechanistic controls on the estimation of the g 1 (stomatal slope, inversely proportional to water use efficiency) and g 0 (stomatal intercept) parameters, using diurnal gas exchange surveys and leaf level response curves of six tropical broadleaf evergreen tree species. g 1 estimated from ex-situ response curves averaged 50% less than g 1 estimated from survey data. While g 0 and g 1 varied between leaves of different phenological stages, the trend was not consistent among species. We identified a diurnal trend associated with g 1 and g 0 that significantly improved model projections of diurnal trends in transpiration. The accuracy of modelled g s can be improved by accounting for variation in stomatal behavior across diurnal periods, and between measurement approaches, rather than focusing on phenological variation in stomatal behavior. Additional investigation into the primary mechanisms responsible for diurnal variation in g 1 will be required to account for this phenomena in land surface models.

54 ENVIRONMENTAL SCIENCES↗

Catching up with the trees: empirical advancements to improve herbaceous representation in models

Ecosystems dominated by herbaceous vegetation (i.e. nonwoody species) represent c. 40% of the terrestrial land surface on Earth (White et al., 2000), facilitate large quantities of carbon sequestration (reviewed by Bai & Cotrufo, 2022), and provide much of the food production for humans (O'Mara, 2012). Many of these ecosystems are currently in danger of being lost due to global change drivers, shrub encroachment, and calls for afforestation (Bond et al., 2019). Furthermore, our predictive understanding of these systems is limited, which can be seen from high levels of uncertainty in modeled future carbon (C) storage of these systems (e.g. fig. 3 in McGuire et al., 2018).

59 BASIC BIOLOGICAL SCIENCES↗

Taxonomic distribution of metabolic functions in bacteria associated with Trichodesmium consortia

The photosynthetic and diazotrophic cyanobacterium Trichodesmium is a key contributor to marine biogeochemical cycles in the subtropical-oligotrophic oceans. Trichodesmium form colonies that harbor a distinct microbial community in comparison to the surrounding seawater. The presence of their associated bacteria can expand Trichodesmium’s functional potential and is predicted to influence the cycling of carbon, nitrogen, phosphorus, and iron (C, N, P, and Fe). To link the bacteria associated with Trichodesmium to key functional traits and elucidate how community structure can influence nutrient cycling, we characterized Red Sea Trichodesmium colonies using metagenomics and metaproteomics. Colonies harbored bacteria that typically associate with algae and particles, such as the ubiquitous Alteromonas macleodii, but also lineages specific to Trichodesmium, such as members from the order Balneolales. The majority of associated bacteria were auxotrophic for different vitamins, indicating their dependency on vitamin production by Trichodesmium. The associated bacteria carry functional traits including siderophore biosynthesis, reduced phosphorus metabolism, and denitrification pathways. The analysis supports Trichodesmium as an active hotspot for C, N, P, Fe, and vitamin exchange. In turn, Trichodesmium may rely on associated bacteria to meet its high Fe demand as several lineages synthesize photolabile siderophores (e.g., vibrioferrin, rhizoferrin, petrobactin) which can enhance the bioavailability of particulate Fe to the entire consortium. Collectively, the results indicate that Trichodesmium colonies provide a structure where these interactions can take place. While further studies are required to clarify the exact nature of these interactions, Trichodesmium’s reliance on particle and algae-associated bacteria and the observed redundancy of key functional traits likely underpins the resilience of Trichodesmium within an ever-changing global environment.

59 BASIC BIOLOGICAL SCIENCES↗

Interactions Between Climate Policy and Technology-influenced Travel Behavior: Mitigating Induced Demand from CACC

Advances in vehicle technology have influenced the development of automated vehicle systems, where vehicles that do not require human intervention are already deployed in the roadway networks. While these advances are proved to increase roadway safety and highway capacity, more research is needed to understand the long-term and regional-level impacts on mobility, land use, energy consumption, and emissions. This study proposes a multi-model approach to analyze the effect of vehicle automation and deep decarbonization policies over a period from 2020 to 2040 in Austin, Texas. We use the Global Change Analysis Model (GCAM) to develop internally the scenarios that are then passed to the SMART Mobility modeling workflow, a large-scale simulation framework combining the POLARIS activity-based travel demand model and mesoscopic traffic simulator with the Autonomie vehicle energy consumption model and the UrbanSim land use simulator. Results suggest that the introduction of vehicles with advanced automation could increase fuel consumption when no decarbonization policies are implemented. Also, advances in vehicle technology research and development could lead to a decline in energy use in the long-term. Energy pricing and vehicle electrification incentives could help reduce the impact of vehicle automation. Finally, our analysis indicates the relevance of introducing land use processes in longterm vehicle automation studies.

land use↗

Data from: Long-term yields in annual and perennial bioenergy crops in the Midwestern USA

Data sets relating to the manuscript “Long-term yields in annual and perennial bioenergy crops in the Midwestern USA” published in Global Change Biology Bioenergy. Field data, including annual peak biomass and harvest yields from maize/soy, miscanthus, switchgrass, and prairie field trials from 2008-2018 are included. Peak and harvest biomass for fertilized and unfertilized miscanthus are included from 2014-2018.

bioenergy↗

Data for "A 13-year record indicates differences in the duration and depth of soil carbon accrual among potential bioenergy crops"

Data sets for material included in "A 13-year record indicates differences in the duration and depth of soil carbon accrual among potential bioenergy crops" by Kantola et al., 2025, in Global Change Biology Bioenergy. Data include soil organic carbon (SOC), carbon stable isotope ratios, annual belowground biomass, and annual post-harvest litter for four crops, maize/soybean, miscanthus, switchgrass, and prairie, between 2008 and 2021.

bioenergy crops↗

Flux Seasonality Metrics Database: A companion dataset for FLUXNET annual product

This dataset include standardized phenological transition dates, and derived season lengths of active, dormant and transition seasons of ecosystem carbon and energy fluxes, as reported in FLUXNET. Such metrics are unique in that they characterize the seasonal dynamics of these fluxes in their own terms rather than in reference to traditional phenology indicators that mostly relate to vegetation structural characteristics. The Flux Seasonality Metrics Database (FSMD) generated 17 standardized seasonality metrics for 4 different fluxes including gross primary productivity (GPP), ecosystem respiration (RE), latent heat (LE) and sensible heat (H) reported in FLUXNET2015 Dataset for about 200 sites and 1500 site-years of data globally. Each metric is reported as an estimate and a confidence interval, which is a function of data coverage and flux variability. We anticipate that the FSMD will facilitate new model validation exercises, and stimulate new research in global change and Earth science disciplines where land-atmosphere exchange dynamics play a central role.

54 ENVIRONMENTAL SCIENCES↗

Surface soil temperature and water content from warming experiment located at the Rocky Mountain Biological Laboratory, Colorado, 2015 to 2019

This data package consists of soil temperature and soil water content sensor data from the warming experiment near the Rocky Mountain Biological Laboratory. Data range is from summer 2015 to summer 2019, when the warming manipulation was terminated. The location of the warming experiment is in the upper montane life zone and consists of meadow vegetation with a mixture of sagebrush (Artemisia tridentata), forb species (Erigeron speciosus, Helianthella quinquenervis, Lathyrus lanszwertii), and graminoid species (Festuca thurberi, Carex spps). Early studies showed that the heating treatment led to earlier snowmelt as well as warmer and drier surface soils, and changes in the functional composition of aboveground biomass favoring sagebrush over forb species (Harte and Shaw, 1995). These changes were mainly observed in the upper, naturally drier zone for the experimental plots. More recent observations of aboveground biomass, soil carbon, and microbial composition require concurrent information about the abiotic environment for interpretation and extrapolation to process-based models. This data package provides the plot- and zone-level abiotic context for the final years of the experiment and consists of csv files with hourly soil temperature (WM_ST.csv) and soil water content (WM_SWC.csv).

54 ENVIRONMENTAL SCIENCES↗

Seedling nitrogen uptake and rhizodeposition between mycorrhizal types

Tree mycorrhizal associations are associated with patterns in N cycling and soil organic matter (SOM) storage, however, we still lack a mechanistic understanding of what tree and fungal traits drive these patterns and how they will respond to global changes in soil N availability. To address this knowledge gap, we investigated how arbuscular mycorrhizal (AM)- and ectomycorrhizal (EcM)-associated seedlings alter rhizodeposition in response to increased inorganic N acquisition. Specifically, we conducted this greenhouse experiment in a sealed labeling chamber with an enriched 13Carbon atmosphere and 15Nitrogen enriched fertilizer over the course of five months from April 2021 - August 2021. To include the variability across tree species, we grew eight species of seedlings belonging to eight families that were either arbuscular (Acer rubrum, Nyssa sylvatica, Thuja occidentalis, and Prunus seritina) or ectomycorrhizal-associated (Quercus rubra, Tilia americana, Pinus strobus, and Betula lenta). We measured rhizodeposition (mg 13C), plant N uptake from fertilizer (mg N), net soil carbon, and the abundance of mycorrhizal fungi (ITS sequencing and qPCR). We also characterized fungal (ITS2) and bacterial (16S) soil communities.The data from this project are ".csv" files that can up downloaded into a folder, and then run in the associated R markdown scripts after changing the source folder location at the top of the script. These data include raw outputs and processed files (using the R markdown files) for seedling growth and biomass, 15N content, soil 13C content, raw reads and processed file versions for fungal and bacterial ASVS, and a final summary file used for modeling. R software is needed to run these data, and the packages needed are listed at the top of the R markdown file.

54 ENVIRONMENTAL SCIENCES↗

FATES size- and age-dependent mortality simulation output analysis scripts

This dataset contains python scripts to analyse outputs from the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) and accompanies the paper “Needham, J.F., Chambers, J., Fisher, R., Knox, R., and Koven, C. D., Forest responses to simulated elevated CO2 under alternate hypotheses of size- and age-dependent mortality, 2020, Global Change Biology”. These scripts process FATES outputs from size- and age-dependent mortality simulations which were run to test the effect of different mechanisms of mortality on forest response to elevated CO2 (eCO2). Specifically, these scripts will process single plant functional type (PFT) simulations in which mortality is either a constant background rate, size-dependent or age-dependent. In each case, a simulation with constant woody NPP is compared to a simulation in which woody NPP increases by 25% to simulate the growth response of forests to eCO2. In addition, the data package contains scripts to analyse ensemble simulations with size- and age-dependent mortality and two PFTs, that were run to test the impact of different demographic rates on coexistence and the forest response to eCO2. Finally, the dataset includes scripts for processing simulations testing the sensitivity of results to allometry and to the recruitment scheme.

54 ENVIRONMENTAL SCIENCES↗

FATES size- and age-dependent mortality simulation outputs, 2019

This dataset contains outputs from the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) and accompanies the paper “Needham, J.F., Chambers, J., Fisher, R., Knox, R., and Koven, C. D., Forest responses to simulated elevated CO2 under alternate hypotheses of size- and age-dependent mortality, 2020, Global Change Biology”. Data are unprocessed FATES outputs from size- and age-dependent mortality simulations which were run to test the effect of different mechanisms of mortality on forest response to elevated CO2 (eCO2). Specifically, this data package contains single plant functional type (PFT) simulations in which mortality is either a constant background rate, size-dependent or age-dependent. In each case, a simulation with constant woody NPP is compared to a simulation in which woody NPP increases by 25% to simulate the growth response of forests to eCO2. Ensemble simulations with size- and age-dependent mortality and two PFTs test the impact of different demographic rates on coexistence and the forest response to eCO2. Finally, the dataset includes simulations testing the sensitivity of results to allometry and to the recruitment scheme.

54 ENVIRONMENTAL SCIENCES↗