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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Impacts of climate and disturbance on nutrient fluxes and stoichiometry in mixed-conifer forests

Elucidating climatic impacts on stream nutrient export and stoichiometry will improve the understanding of forest carbon (C) storage in a warmer world. We constructed C, nitrogen (N), and phosphorus (P) budgets in four watersheds within a rain-snow transition site and another four within a higher-elevation, snow-dominated site, in California’s mixed-conifer zone. We used these two sites in a space-for-time substitution to assess the potential effects of warming on nutrient cycles in currently snow-dominated areas that will become more rain-dominated. During a non-drought period (water year (WY) 2004 – 2011), mean annual stream exports of C and N in particulate forms at the transition site were double that at the snow-dominated site, suggesting that sediment-associated nutrient losses may increase with warming. The transition site had 12% lower N but double the P content in mineral horizons, lower N:P mass ratios in organic horizons, and lower stream export of dissolved inorganic N than the snow-dominated site. Furthermore, these differences suggest that montane forests may receive lower supply of N relative to P with warming. In addition, given strong interests in forest thinning to increase drought resiliency, we examined changes in stream nutrient export after thinning and during a major drought period (WY 2013 – 2015). Stream exports of C, N, and P were similar between unthinned and thinned watersheds during drought, suggesting negligible thinning impacts on stream nutrient export during excessively dry periods. Taken together, our results suggest that as the climate warms, California’s montane forests may lose more nutrients through erosion and receive less N input than P.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Random Forests and Networks Analysis

Wilson (Proceedings of the twenty-eight annual acm symposium on the theory of computing, pp. 296–303, 1996) in the 1990s described a simple and efficient algorithm based on loop-erased random walks to sample uniform spanning trees and more generally weighted trees or forests spanning a given graph. This algorithm provides a powerful tool in analyzing structures on networks and along this line of thinking, in recent works (Avena and Gaudillière in A proof of the transfer-current theorem in absence of reversibility, in Stat. Probab. Lett. 142, 17–22 (2018); Avena and Gaudillière in J Theor Probab, 2017. https://doi.org/10.1007/s10959-017-0771-3 ; Avena et al. in Approximate and exact solutions of intertwining equations though random spanning forests, 2017. arXiv:1702.05992v1 ; Avena et al. in Intertwining wavelets or multiresolution analysis on graphs through random forests, 2017. arXiv:1707.04616 , to appear in ACHA (2018)) we focused on applications of spanning rooted forests on finite graphs. The resulting main conclusions are reviewed in this paper by collecting related theorems, algorithms, heuristics and numerical experiments. A first foundational part on determinantal structures and efficient sampling procedures is followed by four main applications: (1) a random-walk-based notion of well-distributed points in a graph, (2) a framework to describe metastable-like dynamics in finite settings by means of Markov intertwining dualities, (3) coarse graining schemes for networks and associated processes, (4) wavelets-like pyramidal algorithms for graph signals.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Quantifying and reducing the differences in forest CO 2 -fluxes estimated by eddy covariance, biometric and chamber methods: A global synthesis

Carbon dioxide (CO 2 ) fluxes between terrestrial ecosystems and the atmosphere are primarily measured with eddy covariance (EC), biometric, and chamber methods. However, it is unclear why the estimates of CO 2 -fluxes, when measured using these different methods, converge at some sites but diverge at others. We synthesized a novel global dataset of forest CO 2 -fluxes to evaluate the consistency between EC and biometric or chamber methods for quantifying CO 2 budget in forests. The EC approach, comparing with the other two methods, tended to produce 25% higher estimate of net ecosystem production (NEP, 0.52Mg C ha-1 yr-1), mainly resulting from lower EC-estimated Re; 10% lower ecosystem respiration (Re, 1.39Mg C ha-1 yr-1); and 3% lower gross primary production (0.48 Mg C ha-1 yr-1) The discrepancies between EC and the other methods were higher at sites with complex topography and dense canopies versus those with flat topography and open canopies. Forest age also influenced the discrepancy through the change of leaf area index. The open-path EC system induced >50% of the discrepancy in NEP, presumably due to its surface heating effect. These results provided strong evidence that EC produces biased estimates of NEP and Re in forest ecosystems. A global extrapolation suggested that the discrepancies in CO 2 fluxes between methods were consistent with a global underestimation of Re, and overestimation of NEP, by the EC method. Accounting for these discrepancies would substantially improve the our estimates of the terrestrial carbon budget .

Wang, Xingchang↗
DOE OSTI2018

Carbon fluxes and interannual drivers in a temperate forest ecosystem assessed through comparison of top-down and bottom-up approaches

Despite decades of research, gaining a comprehensive understanding of carbon (C) cycling in forests remains a considerable challenge. Uncertainties stem from persistent methodological limitations and the difficulty of resolving top-down estimates of ecosystem C exchange with bottom-up measurements of individual pools and fluxes. To address this, we derived estimates and associated uncertainties of ecosystem C fluxes for a 100–125 year old mixed temperate forest stand at the Bartlett Experimental Forest, New Hampshire, USA, using three different approaches: (1) tower-based eddy covariance, (2) a biometric approach involving C flux measurements of individual ecosystem subcomponents, and (3) an inventory approach involving changes in major C stocks over time. Our analysis made use of 13 years of data, collected over the period from 2004 to 2016. Estimates of mean annual net ecosystem production (NEP) ranged from 120 to 133 g C m -2 , demonstrating strong agreement among methods and suggesting that this aging forest acts as a moderate C sink. The use of multiple approaches to measure C fluxes and their uncertainties helped place constraints on difficult-to-measure processes such as aboveground contributions to ecosystem respiration and belowground allocation to mycorrhizal fungal biomass (which was estimated at 20% of net primary production). Analysis of interannual variability in C fluxes revealed a decoupling between annual wood growth and either current year or lagged NEP or GPP, suggesting that source limitation (C supply) is likely not controlling rates of wood production, at least on an interannual scale. Results also demonstrated a strong association between the maximum rate of C uptake during the growing season (Amax) and the length of the vernal window, defined as the period of time between soil thaw and the onset of photosynthesis. This suggests an important, but poorly understood, influence of winter and spring climate on mid-summer canopy physiology. Efforts to resolve the mechanisms responsible should be prioritized in light of ongoing and predicted changes in climate for the northeastern U.S. region, particularly during the winter and winter-spring transition period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Forest productivity varies with soil moisture more than temperature in a small montane watershed

Mountainous terrain creates variability in microclimate, including nocturnal cold air drainage and resultant temperature inversions. Driven by the elevational temperature gradient, vapor pressure deficit (VPD) also varies with elevation. Soil depth and moisture availability often increase from ridgetop to valley bottom. These variations complicate predictions of forest productivity and other biological responses. We analyzed spatiotemporal air temperature (T) and VPD variations in a forested, 27-km 2 catchment that varied from 1000 to 1650 m in elevation. Temperature inversions occurred on 76% of mornings in the growing season. The inversion had a clear upper boundary at midslope (~1370 m a.s.l.). Vapor pressure was relatively constant across elevations, therefore VPD was mainly controlled by T in the watershed. Here, we assessed the impact of microclimate and soil moisture on tree height, forest productivity, and carbon stable isotopes (δ 13 C) using a physiological forest growth model (3-PG). Simulated productivity and tree height were tested against observations derived from lidar data. The effects on photosynthetic gas-exchange of dramatic elevational variations in T and VPD largely cancelled as higher temperature (increasing productivity) accompanies higher VPD (reducing productivity). Although it was not measured, the simulations suggested that realistic elevational variations in soil moisture predicted the observed decline in productivity with elevation. Therefore, in this watershed, the model parameterization should have emphasized soil moisture rather than precise descriptions of temperature inversions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Snow-corrected vegetation indices for improved gross primary productivity assessment in North American evergreen forests

North American evergreen forests cover large areas and influence the global carbon cycle. Satellite remote sensing has been used to track the phenology of ecosystem photosynthesis of these forests by detecting variation in vegetation optical properties associated with physiological and structural features, and most of these methods have been closely tied to vegetation greenness. However, in evergreens, the application of satellite data to monitor photosynthetic phenology is often limited by the lack of sensitivity of greenness-based indices. In this study, we identified 47 evergreen forest flux sites in North America that had MODIS observation overlapping with the flux tower records. We then calculated four vegetation indices using MODIS MAIAC data (MCD19A1), including NDVI, CCI, NIRv, and kNDVI, for the 47 flux sites and evaluated relationships between gross primary productivity (GPP) and vegetation indices across the North American evergreen forests. Our results showed that snow had substantial effects on the performance of all vegetation indices in tracking GPP phenology, particularly in the early spring when rapid changes occurred to both GPP and snow cover. Furthermore, different vegetation indices were affected differently, indicating contradictory and confounding effects of snow on these indices. After correcting for the snow effects, both CCI and NIRv performed well in tracking GPP phenology, albeit for different reasons. CCI is sensitive to seasonal changes in the relative levels of chlorophyll and carotenoid pigments, which are closely tied to GPP phenology in evergreens. NIRv is sensitive to the absorbed photosynthetically active radiation and to the contribution of deciduous components to the overall optical properties. We also found that correlations between GPP and vegetation indices varied among ecoregions and climate classes. In general, regions with pronounced seasonal GPP patterns had stronger correlations between GPP and greenness-based indices than regions with weaker seasonal GPP patterns. These biome differences were less pronounced for CCI. The snow artifacts and complementary vegetation index effects reported here should be considered in any large-scale studies of GPP using reflectance-based indices from optical satellites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Differential effects of drought on nonstructural carbohydrate storage in seedlings and mature trees of four species in a subtropical forest

Nonstructural carbohydrates (NSC) play important roles in forest vulnerability to climate change, especially under increasing drought intensity and frequency. Understanding NSC dynamics is essential for accurately predicting the resistance and resilience of forests in response to drought. However, our knowledge of NSC re-sponses to drought is still limited due to the lack of research in trees of di?erent life stages. In this study, we conducted a throughfall exclusion experiment (TFE) with four subtropical evergreen tree species to examine drought e?ects on NSC in mature trees and understory seedlings. Our results showed the differential effects of drought on NSC dynamics of understory seedlings and mature trees. In the TFE experiment, mature trees of all four species were relatively homoeostatic with the insigni?cantly changed NSC pools, photosynthesis, and growth under the drought treatment compared to the control. In contrast, understory seedlings displayed sig-ni?cant decreases in total NSC and soluble sugars (-14.70 ± 3.66% and -16.93 ± 3.85%, respectively) with the exception of Lithocarpus glaber (L. glaber). The seedlings of L. glaber with the highest hydraulic resistance maintained or slightly increased NSC and its components in response to drought. Our study highlights the im-portance of life stage in assessing drought e?ects of trees on NSC storage and then forest C cycling, which could be incorporated into the dynamic global vegetation models (DGVMs) to better understand drought effects on forest C balance in the future.

Zhang, Peipei↗
DOE OSTI2022

Intra-annual variation in microclimatic conditions in relation to vegetation type and structure in two tropical dry forests undergoing secondary succession

Microclimate acts as a strong filter on species performance in restored and regenerating forests, particularly in seasonally dry tropical forests (SDTF). Yet few studies have measured microclimate patterns across succession in SDTF. Furthermore, although dynamic vegetation models simulate microclimate, evaluation of these simulated variables with field observations has been relatively uncommon. Here, we investigated the seasonal patterns of soil temperature and soil water in naturally regenerated and planted successional vegetation in SDTF in Costa Rica and Puerto Rico, using complementary approaches of intensive field observations and simulation modeling with the Ecosystem Demography model. We found that plots representing later successional stages were wetter on average, but only during the dry season. During the wet season, mean soil water did not differ across vegetation types, but open, early successional vegetation experienced more frequent extreme wet and dry conditions than older forest and plantations. Soil temperature tended to decline with forest structure, and later successional vegetation also experienced less extreme daily temperature fluctuations. Basal area and leaf area index were the best predictors of differences in soil water and temperature across plots. Model simulations were consistent with observations of wet season soil temperature and soil water, but the model failed to reproduce dry season soil moisture dynamics, suggesting that further work is needed to reduce model biases in microclimate variables. Collectively, our results imply that common assumptions about how microclimates influence successional processes in SDTF should be revisited.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

National forest timber bids and export price interlinkages in the USA: The bounds testing approach

We examine the interrelationships of national forest timber bid and log export prices for Douglas-fir (Region 6) in 2003–2021 and loblolly pine (Region 8) using time-series stationarity and bounds-testing approaches. The analysis shows the difference in time series properties across different geographies and time scales. Bid prices for these dominant species of timber in each of two Forest Service regions are found to be stationary, while log export prices for those same species appear to be non-stationary. Bounds testing conducted with autoregressive distributed lag modeling methods provides strong evidence for a cointegrating relationship between timber bid prices and log export prices in Forest Service Region 6. In Region 8, evidence for a cointegrating relationship was weak. Here, the share of salvage wood in national forest timber sales is a statistically significant control variable in all models estimated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Removal of introduced inorganic content from chipped forest residues via air classification

Inorganic content in biomass decreases the efficiency of conversion processes, especially thermochemical conversions. The combined concentrations of specific ash forming elements are the primary attributes that cause pine residues to be considered a degraded energy conversion feedstock, as compared to clean pine. Air classification is a potentially effective and economical tool to isolate high inorganic content biomass fractions away from primary feedstock sources to reduce their ash content. In this work, loblolly pine forest residues were air classified into 10 fractions whose ash content and composition were measured. Ash concentrations were highest in the lightest fractions (5.8–8.5 wt%), and in a heavy fraction of the fines (8.9–15.1 wt%). The removal of fractions with high inorganic content resulted in a substantial reduction in the ash content of the remaining biomass in forest thinnings (1.69–1.07 wt%) and logging residues (1.09–0.68 wt%). These high inorganic content fractions from both forest residue types represented less than 7.0 wt% of the total biomass, yet they contained greater than 40% of the ash content by mass. Elemental analysis of the air classified fractions revealed the lightest fractions were comprised of high concentrations of soil elements (silicon, aluminum, iron, sodium, and titanium). However, the elements of biological origin including calcium, potassium, magnesium, sulfur, manganese, and phosphorous were evenly distributed throughout all air classified fractions, making them more difficult to isolate into fractions with high mineral concentrations. Under the conditions reported in this study, an economic analysis revealed air classification could be used for ash removal for as little as $2.23 per ton of product biomass. As a result, this study suggests air classification is a potentially attractive technology for the removal of introduced soil minerals from pine forest residues.

09 BIOMASS FUELS↗
DOE OSTI2023

Mapping foliar photosynthetic capacity in sub-tropical and tropical forests with UAS-based imaging spectroscopy: Scaling from leaf to canopy

Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemical and morphological traits at the canopy scale, but there is only limited evidence for retrieving canopy photosynthetic capacity (e.g., maximum carboxylation rate, V c,max and maximum electron transport rate, J max ). Moreover, the effect of canopy structure within forest communities on scaling up spectra-trait relationships from leaf to canopy level is not well known. To advance the spectra-trait approach and enable the estimation of key traits using remote sensing, we collected imaging spectroscopy data from an Unoccupied Aerial System (UAS) platform over two forest sites in China (a subtropical forest in Mt. Dinghu and a tropical rainforest in Xishuangbanna). At these sites, we also collected ground measurements of leaf spectra and traits, including biochemical (leaf nitrogen, phosphorus, chlorophyll, and water content), morphological (leaf mass per area, LMA) and physiological (V c,max25 and J max25 ) traits (n=135 tree-crowns from 42 species across two sites). Using a partial least-squares regression (PLSR) approach, we built and tested spectra-trait models with repeated cross-validation. The spectral models developed with leaf spectra were directly transferred to canopy spectra to evaluate the effect of canopy structure. Here we further applied canopy spectral models to map these traits at individual tree-crown scale. The results demonstrate that (1) UAS-based canopy spectra can be used to estimate V c,max (R 2 =0.55, nRMSE=11.79%), Jmax (R 2 =0.54, nRMSE=12.34%), and five additional foliar traits (R 2 =0.38-0.60, nRMSE=10.11-13.56%) at the tree-crown scale with demonstrated generalizability across two sites; (2) canopy structure strongly affects the spectratrait relationships from leaf to canopy level, but the effects vary considerably across foliar traits and cannot be well captured by the 4SAIL canopy radiative transfer model. UAS-based imaging spectroscopy maps large variability in all foliar traits (including physiological traits) with spatially explicit information, reproducing the field-observed inter- and intra-specific variations. These results demonstrate the capability of using UAS-based imaging spectroscopy for characterizing the variability of foliar physiological traits at individual tree-crown scale over forest landscapes and highlight the similar generalizability but different biophysical mechanisms underlying spectra-trait relationships at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Bark beetle impacts on forest evapotranspiration and its partitioning

Insect outbreaks affect forest structure and function and represent a major category of forest disturbance globally. However, the resulting impacts on evapotranspiration (ET), and especially hydrological partitioning between the abiotic (evaporation) and biotic (transpiration) components of total ET, are not well constrained. As a result, we combined remote sensing, eddy covariance, and hydrological modeling approaches to determine the effects of bark beetle outbreak on ET and its partitioning at multiple scales throughout the Southern Rocky Mountain Ecoregion (SRME), USA. At the eddy covariance measurement scale, 85 % of the forest was affected by beetles, and water year ET as a fraction of precipitation (P) decreased by 30 % relative to a control site, with 31 % greater reductions in growing season transpiration relative to total ET. At the ecoregion scale, satellite remote sensing masked to areas of >80 % tree mortality showed corresponding ET/P reductions of 9–15 % that occurred 6–8 years post-disturbance, and indicated that the majority of the total reduction occurred during the growing season; the Variable Infiltration Capacity hydrological model showed an associated 9–18 % increase in the ecoregion runoff ratio. Long-term (16–18 year) ET and vegetation mortality datasets extend the length of previously published analyses and allowed for clear characterization of the forest recovery period. During that time, transpiration recovery outpaced total ET recovery, which was lagged in part due to persistently reduced winter sublimation, and there was associated evidence of increasing late summer vegetation moisture stress. Overall, comparison of three independent methods and two partitioning approaches demonstrated a net negative impact of bark beetles on ET, and a relatively greater negative impact on transpiration, following bark beetle outbreak in the SRME.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Solar-Induced Fluorescence Detects Interannual Variation in Gross Primary Production of Coniferous Forests in the Western United States

Quantifying gross primary production (GPP), the largest flux of the terrestrial carbon cycle, remains difficult at the landscape scale. Evergreen needleleaf (coniferous) forests in the western United States constitute an important carbon reservoir whose annual GPP varies from year-to-year due to drought, mortality, and other ecosystem disturbances. Evergreen forest productivity is challenging to determine via traditional remote sensing indices (i.e., NDVI and EVI), because detecting environmental stress conditions is difficult. We investigated the utility of solar-induced chlorophyll fluorescence (SIF) to detect year-to-year variation in GPP in four coniferous forests varying in species composition in the western United States (Sierra Nevada, Cascade, and Rocky Mountains). We show that annually averaged, satellite-based observations of SIF (retrieved from GOME-2) were significantly correlated with annual GPP observed at eddy covariance towers over several years. Further, SIF responded quantitatively to drought-induced mortality, suggesting that SIF may be capable of detecting ecosystem disturbance in coniferous forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Tower-Based Remote Sensing Reveals Mechanisms Behind a Two-phased Spring Transition in a Mixed-Species Boreal Forest

The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate Drives Modeled Forest Carbon Cycling Resistance and Resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond (resistance) and recover from (resilience) to rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the ED-2.2 model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900, and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes, and interacted with one another. We then calculated metrics of functional ecosystem stability. Modeled gross primary production exhibited a mean resistance of -0.13, -0.23, and -0.42 (unitless) in response to increasing disturbance severity of 45%, 65%, and 85% mortality, respectively; and resilience of 0.002, 0.004, 0.008 (yr-1) respectively. This pattern held true for other carbon fluxes, meaning that in general simulated GPP declined more initially but recovered more quickly from higher mortality. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA

We present meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains (USA) over three consecutive water years with different amounts of snow water equivalent (SWE) accumulation: A year with above average SWE (2019), a year with average SWE (2020), and a year with below average SWE (2021). This data set is distinguished by its emphasis on paired open-forest sites in a continental snow climate. Approximately once a month during February–May, we collected data from 15 to 20 snow pits and took 8 to 19 snow depth transects. Our sampling sites were in open and adjacent forested areas at 3,100 m and in a lower elevation aspen (3,035 m) and higher elevation conifer stand (3,395 m). In total, we recorded 270 individual snow pit density and temperature profiles and over 4,000 snow depth measurements. These data are complimented by continuous meteorological measurements from two weather stations: One in the open and one in the adjacent forest. Meteorology data—including incoming shortwave and longwave radiation, outgoing shortwave radiation, relative humidity, wind speed, snow depth, and air and infrared surface temperature—were quality controlled and the forcing data were gap-filled. These data are available to download from Bonner, Smyth, et al. at three levels of processing, including a level with downscaled, adjusted precipitation based on data assimilation using observed snow depth and a process-based snow model. We demonstrate the utility of these data with a modeling experiment that explores open-forest differences and identifies opportunities for improvements in model representation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modeling Mycorrhizal Carbon Costs in Temperate Forests: The Impacts of Functional Diversity and Global Change Factors

Mycorrhizal fungi form symbiotic relationships with most plant species, facilitating nutrient acquisition while consuming a significant fraction of the plant's photosynthetic carbon (C), which we define as the mycorrhizal C cost. Drivers of the mycorrhizal C cost, which is crucial for predicting environmental impacts on plant productivity, remain under-explored and difficult to quantify. Ecosystem models that incorporate mycorrhizae can offer insights into mycorrhizal C cost dynamics, but their predictions have rarely been validated against empirical data. Here, in this study, we used the Myco-CORPSE model, which explicitly simulates mycorrhizal processes alongside soil carbon and nitrogen cycling, to investigate the drivers of mycorrhizal C cost in temperate forests. Applying this model to over 1,800 forest inventory plots across the eastern United States, we found that the simulations matched published data, showing higher C allocation to ectomycorrhizal (ECM) fungi (16.0% of net primary production (NPP)) compared to arbuscular mycorrhizal (AM) fungi (5.8% of NPP). Further analysis showed that mixed forests, co-dominated by both AM and ECM trees, allocated less C to mycorrhizal fungi compared to forests dominated by either AM or ECM fungi alone, due to complementary nutrient acquisition strategies. Elevated Nitrogen (N) deposition and higher temperatures reduce mycorrhizal C costs, favoring AM strategies. Conversely, elevated CO 2 (eCO 2 ) increased plant N demand and mycorrhizal C costs, favoring ECM strategies that access organic N sources. These findings underscore the critical role of mycorrhizal functional diversity in plant nutrient acquisition and C dynamics, providing new insights into how mycorrhizal symbioses respond to global change.

Shao, Siya [Dartmouth College, Hanover, NH (United↗
DOE OSTI2017

Airborne observations reveal elevational gradient in tropical forest isoprene emissions

Terrestrial vegetation emits vast quantities of volatile organic compounds (VOCs) to he atmosphere1-3, which influence oxidants and aerosols leading to complex feedbacks on air quality and climate4-6. Isoprene dominates global non-methane VOC emissions with tropical regions contributing ~80% of global isoprene emissions2. Isoprene emission rates vary over several orders of magnitude for different plant species, and characterizing this immense biological chemodiversity is a challenge for estimating isoprene emission from tropical forests. Here we present the isoprene emission estimates from aircraft direct eddy covariance measurements over the pristine Amazon forest. We report isoprene emission rates that are 3 times higher than satellite top-down estimates and 35% higher than model predictions based on satellite land cover and vegetation specific emission factors (EFs). The results reveal strong correlations between observed isoprene emission rates and terrain elevations which are confirmed by similar correlations between satellite-derived isoprene emissions and terrain elevations. We propose that the elevational gradient in the Amazonian forest isoprene emission capacity is determined by plant species distributions and can explain a substantial degree of isoprene emission variability in tropical forests. Finally, we apply this approach over the central Amazon and use a model to demonstrate the impacts on regional air quality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗