A tale of two towers: comparing NEON and AmeriFlux data streams at Bartlett Experimental Forest - Yujie Liu; Paul Stoy; Housen Chu; Dave Y. Hollinger; Scott V. Ollinger; Andrew P. Ouimette; David J. Durden; Cove Sturtevant; Ben Lucas; Andrew D. Richardson (Agricultural and Forest Meteorology, 2026)

The role of surface energy fluxes in determining mixing layer heights - Eric R. Beamesderfer; Sebastien C. Biraud; Nathaniel A. Brunsell; Mark A. Friedl; Manuel Helbig; David Y. Hollinger; Thomas Milliman; David A. Rahn; Russell L. Scott; Paul C. Stoy; Jen L. Diehl; Andrew D. Richardson (Agricultural and Forest Meteorology, 2023)

Informing Nature‐based Climate Solutions for the United States with the best‐available science - Kimberly A. Novick; Stefan Metzger; William R. L. Anderegg; Mallory Barnes; Daniela S. Cala; Kaiyu Guan; Kyle S. Hemes; David Y. Hollinger; Jitendra Kumar; Marcy Litvak; Danica Lombardozzi; Caroline P. Normile; et al. (Global Change Biology, 2022)
Nature‐based Climate Solutions (NbCS) are managed alterations to ecosystems designed to increase carbon sequestration or reduce greenhouse gas emissions. While they have growing public and private support, the realizable benefits and unintended consequences of NbCS are not well understood. At regional scales where policy decisions are often made, NbCS benefits are estimated from soil and tree survey data that can miss important carbon sources and sinks within an ecosystem, and do not reveal the biophysical impacts of NbCS for local water and energy cycles. The only direct observations of ecosystem‐scale carbon fluxes, for example, by eddy covariance flux towers, have not yet been systematically assessed for what they can tell us about NbCS potentials, and state‐of‐the‐art remote sensing products and land‐surface models are not yet being widely used to inform NbCS policymaking or implementation. As a result, there is a critical mismatch between the point‐ and tree‐scale data most often used to assess NbCS benefits and impacts, the ecosystem and landscape scales where NbCS projects are implemented, and the regional to continental scales most relevant to policymaking. Here, we propose a research agenda to confront these gaps using data and tools that have long been used to understand the mechanisms driving ecosystem carbon and energy cycling, but have not yet been widely applied to NbCS. We outline steps for creating robust NbCS assessments at both local to regional scales that are informed by ecosystem‐scale observations, and which consider concurrent biophysical impacts, future climate feedbacks, and the need for equitable and inclusive NbCS implementation strategies. We contend that these research goals can largely be accomplished by shifting the scales at which pre‐existing tools are applied and blended together, although we also highlight some opportunities for more radical shifts in approach.

Canopy photosynthetic capacity drives contrasting age dynamics of resource use efficiencies between mature temperate evergreen and deciduous forests - Hang Xu; Jingfeng Xiao; Zhiqiang Zhang; Scott V. Ollinger; David Y. Hollinger; Yude Pan; Jiaming Wan (Global Change Biology, 2020)
Forest resource use efficiencies (RUEs) can vary with tree age, but the nature of these trends and their underlying mechanisms are not well understood. Understanding the age dynamics of forest RUEs and their drivers is vital for assessing the trade‐offs between forest functions and resource consumption, making rational management policy, and projecting ecosystem carbon dynamics. Here we used the FLUXNET2015 and AmeriFlux datasets and published literature to explore the age‐dependent variability of forest light use efficiency (LUE) and inherent water use efficiency as well as their main regulatory variables in temperate regions. Our results showed that evergreen forest RUEs initially increased before reaching the mature stage (i.e., around 90 years old), and then gradually declined; in contrast, RUEs continuously increased with age for mature deciduous forests. Changing canopy photosynthetic capacity ( A max ) was the primary cause of age‐related changes in RUEs across temperate forest sites. More importantly, soil nitrogen (N) increased in mature deciduous forests through time but decreased in older evergreen forests. The age‐dependent changes in soil N were closely linked with the age dynamics of A max for mature temperate forests. Additionally, soil nutrient conditions played a greater role in deciduous forest RUEs than evergreen forest RUEs. This study highlights the importance of stand age and forest type on temperate forest RUEs over the long term.

Solar‐induced chlorophyll fluorescence exhibits a universal relationship with gross primary productivity across a wide variety of biomes - Jingfeng Xiao; Xing Li; Binbin He; M. Altaf Arain; Jason Beringer; Ankur R. Desai; Carmen Emmel; David Y. Hollinger; Alisa Krasnova; Ivan Mammarella; Steffen M. Noe; Penélope Serrano Ortiz; et al. (Global Change Biology, 2019)

Solar‐induced chlorophyll fluorescence is strongly correlated with terrestrial photosynthesis for a wide variety of biomes: First global analysis based on OCO‐2 and flux tower observations - Xing Li; Jingfeng Xiao; Binbin He; M. Altaf Arain; Jason Beringer; Ankur R. Desai; Carmen Emmel; David Y. Hollinger; Alisa Krasnova; Ivan Mammarella; Steffen M. Noe; Penélope Serrano Ortiz; et al. (Global Change Biology, 2018)
Solar‐induced chlorophyll fluorescence (SIF) has been increasingly used as a proxy for terrestrial gross primary productivity (GPP). Previous work mainly evaluated the relationship between satellite‐observed SIF and gridded GPP products both based on coarse spatial resolutions. Finer resolution SIF (1.3 km × 2.25 km) measured from the Orbiting Carbon Observatory‐2 (OCO‐2) provides the first opportunity to examine the SIF–GPP relationship at the ecosystem scale using flux tower GPP data. However, it remains unclear how strong the relationship is for each biome and whether a robust, universal relationship exists across a variety of biomes. Here we conducted the first global analysis of the relationship between OCO‐2 SIF and tower GPP for a total of 64 flux sites across the globe encompassing eight major biomes. OCO‐2 SIF showed strong correlations with tower GPP at both midday and daily timescales, with the strongest relationship observed for daily SIF at the 757 nm ( R 2 = 0.72, p R 2 = 0.57–0.79, p R 2 = 0.16, p 4 grasslands and croplands than for C 3 ecosystems. The generally consistent slope of the relationship among biomes suggests a nearly universal rather than biome‐specific SIF–GPP relationship, and this finding is an important distinction and simplification compared to previous results. SIF was mainly driven by absorbed photosynthetically active radiation and was also influenced by environmental stresses (temperature and water stresses) that determine photosynthetic light use efficiency. OCO‐2 SIF generally had a better performance for predicting GPP than satellite‐derived vegetation indices and a light use efficiency model. The universal SIF–GPP relationship can potentially lead to more accurate GPP estimates regionally or globally. Our findings revealed the remarkable ability of finer resolution SIF observations from OCO‐2 and other new or future missions (e.g., TROPOMI, FLEX) for estimating terrestrial photosynthesis across a wide variety of biomes and identified their potential and limitations for ecosystem functioning and carbon cycle studies.

Assessing the interplay between canopy energy balance and photosynthesis with cellulose δ18O: large-scale patterns and independent ground-truthing - Brent R. Helliker; Xin Song; Michael L. Goulden; Kenneth Clark; Paul Bolstad; J. William Munger; Jiquan Chen; Asko Noormets; David Hollinger; Steve Wofsy; Timothy Martin; Dennis Baldocchi; et al. (Oecologia, 2018)

Quantifying climate–growth relationships at the stand level in a mature mixed‐species conifer forest - Aaron Teets; Shawn Fraver; Aaron R. Weiskittel; David Y. Hollinger (Global Change Biology, 2018)
A range of environmental factors regulate tree growth; however, climate is generally thought to most strongly influence year‐to‐year variability in growth. Numerous dendrochronological (tree‐ring) studies have identified climate factors that influence year‐to‐year variability in growth for given tree species and location. However, traditional dendrochronology methods have limitations that prevent them from adequately assessing stand‐level (as opposed to species‐level) growth. We argue that stand‐level growth analyses provide a more meaningful assessment of forest response to climate fluctuations, as well as the management options that may be employed to sustain forest productivity. Working in a mature, mixed‐species stand at the Howland Research Forest of central Maine, USA , we used two alternatives to traditional dendrochronological analyses by (1) selecting trees for coring using a stratified (by size and species), random sampling method that ensures a representative sample of the stand, and (2) converting ring widths to biomass increments, which once summed, produced a representation of stand‐level growth, while maintaining species identities or canopy position if needed. We then tested the relative influence of seasonal climate variables on year‐to‐year variability in the biomass increment using generalized least squares regression, while accounting for temporal autocorrelation. Our results indicate that stand‐level growth responded most strongly to previous summer and current spring climate variables, resulting from a combination of individualistic climate responses occurring at the species‐ and canopy‐position level. Our climate models were better fit to stand‐level biomass increment than to species‐level or canopy‐position summaries. The relative growth responses (i.e., percent change) predicted from the most influential climate variables indicate stand‐level growth varies less from to year‐to‐year than species‐level or canopy‐position growth responses. By assessing stand‐level growth response to climate, we provide an alternative perspective on climate–growth relationships of forests, improving our understanding of forest growth dynamics under a fluctuating climate.

Unique challenges and opportunities for northeastern US crop production in a changing climate - David W. Wolfe; Arthur T. DeGaetano; Gregory M. Peck; Mary Carey; Lewis H. Ziska; John Lea-Cox; Armen R. Kemanian; Michael P. Hoffmann; David Y. Hollinger (Climatic Change, 2018)

Variation in foliar nitrogen and albedo in response to nitrogen fertilization and elevated CO2 - Haley F. Wicklein; Scott V. Ollinger; Mary E. Martin; David Y. Hollinger; Lucie C. Lepine; Michelle C. Day; Megan K. Bartlett; Andrew D. Richardson; Richard J. Norby (Oecologia, 2012)

Terrestrial biosphere model performance for inter‐annual variability of land‐atmosphere CO 2 exchange - T.F. Keenan; Ian Baker; Alan Barr; Philippe Ciais; Ken Davis; Michael Dietze; Danillo Dragoni; Christopher M Gough; Robert Grant; David Hollinger; Koen Hufkens; Ben Poulter; et al. (Global Change Biology, 2012)
Interannual variability in biosphere‐atmosphere exchange of CO 2 is driven by a diverse range of biotic and abiotic factors. Replicating this variability thus represents the ‘acid test’ for terrestrial biosphere models. Although such models are commonly used to project responses to both normal and anomalous variability in climate, they are rarely tested explicitly against inter‐annual variability in observations. Herein, using standardized data from the N orth A merican Carbon Program, we assess the performance of 16 terrestrial biosphere models and 3 remote sensing products against long‐term measurements of biosphere‐atmosphere CO 2 exchange made with eddy‐covariance flux towers at 11 forested sites in N orth A merica. Instead of focusing on model‐data agreement we take a systematic, variability‐oriented approach and show that although the models tend to reproduce the mean magnitude of the observed annual flux variability, they fail to reproduce the timing. Large biases in modeled annual means are evident for all models. Observed interannual variability is found to commonly be on the order of magnitude of the mean fluxes. None of the models consistently reproduce observed interannual variability within measurement uncertainty. Underrepresentation of variability in spring phenology, soil thaw and snowpack melting, and difficulties in reproducing the lagged response to extreme climatic events are identified as systematic errors, common to all models included in this study.

Endogenous circadian regulation of carbon dioxide exchange in terrestrial ecosystems - Víctor Resco de Dios; Michael L. Goulden; Kiona Ogle; Andrew D. Richardson; David Y. Hollinger; Eric A. Davidson; Josu G. Alday; Greg A. Barron‐Gafford; Arnaud Carrara; Andrew S. Kowalski; Walt C. Oechel; Borja R. Reverter; et al. (Global Change Biology, 2012)
It is often assumed that daytime patterns of ecosystem carbon assimilation are mostly driven by direct physiological responses to exogenous environmental cues. Under limited environmental variability, little variation in carbon assimilation should thus be expected unless endogenous plant controls on carbon assimilation, which regulate photosynthesis in time, are active. We evaluated this assumption with eddy flux data, and we selected periods when net ecosystem exchange ( NEE ) was decoupled from environmental variability in seven sites from highly contrasting biomes across a 74° latitudinal gradient over a total of 36 site‐years. Under relatively constant conditions of light, temperature, and other environmental factors, significant diurnal NEE oscillations were observed at six sites, where daily NEE variation was between 20% and 90% of that under variable environmental conditions. These results are consistent with fluctuations driven by the circadian clock and other endogenous processes. Our results open a promising avenue of research for a more complete understanding of ecosystem fluxes that integrates from cellular to ecosystem processes.

Terrestrial biosphere models need better representation of vegetation phenology: results from the N orth A merican C arbon P rogram S ite S ynthesis - Andrew D. Richardson; Ryan S. Anderson; M. Altaf Arain; Alan G. Barr; Gil Bohrer; Guangsheng Chen; Jing M. Chen; Philippe Ciais; Kenneth J. Davis; Ankur R. Desai; Michael C. Dietze; Danilo Dragoni; et al. (Global Change Biology, 2012)
Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem‐scale CO 2 exchange, in 14 models participating in the N orth A merican C arbon P rogram S ite S ynthesis. Model predictions were evaluated using long‐term measurements (emphasizing the period 2000–2006) from 10 forested sites within the A meri F lux and F luxnet‐ C anada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over‐prediction of gross ecosystem photosynthesis by +160 ± 145 g C m −2 yr −1 during the spring transition period and +75 ± 130 g C m −2 yr −1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under‐predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO 2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere–atmosphere feedbacks and interactions in coupled global climate models.

Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints - Andrew D. Richardson; Mathew Williams; David Y. Hollinger; David J. P. Moore; D. Bryan Dail; Eric A. Davidson; Neal A. Scott; Robert S. Evans; Holly Hughes; John T. Lee; Charles Rodrigues; Kathleen Savage (Oecologia, 2010)

Interannual variation of carbon fluxes from three contrasting evergreen forests: the role of forest dynamics and climate - Carlos A. Sierra; Henry W. Loescher; Mark E. Harmon; Andrew D. Richardson; David Y. Hollinger; Steven S. Perakis (Ecology, 2009)
Interannual variation of carbon fluxes can be attributed to a number of biotic and abiotic controls that operate at different spatial and temporal scales. Type and frequency of disturbance, forest dynamics, and climate regimes are important sources of variability. Assessing the variability of carbon fluxes from these specific sources can enhance the interpretation of past and current observations. Being able to separate the variability caused by forest dynamics from that induced by climate will also give us the ability to determine if the current observed carbon fluxes are within an expected range or whether the ecosystem is undergoing unexpected change. Sources of interannual variation in ecosystem carbon fluxes from three evergreen ecosystems, a tropical, a temperate coniferous, and a boreal forest, were explored using the simulation model STANDCARB. We identified key processes that introduced variation in annual fluxes, but their relative importance differed among the ecosystems studied. In the tropical site, intrinsic forest dynamics contributed ∼30% of the total variation in annual carbon fluxes. In the temperate and boreal sites, where many forest processes occur over longer temporal scales than those at the tropical site, climate controlled more of the variation among annual fluxes. These results suggest that climate‐related variability affects the rates of carbon exchange differently among sites. Simulations in which temperature, precipitation, and radiation varied from year to year (based on historical records of climate variation) had less net carbon stores than simulations in which these variables were held constant (based on historical records of monthly average climate), a result caused by the functional relationship between temperature and respiration. This suggests that, under a more variable temperature regime, large respiratory pulses may become more frequent and high enough to cause a reduction in ecosystem carbon stores. Our results also show that the variation of annual carbon fluxes poses an important challenge in our ability to determine whether an ecosystem is a source, a sink, or is neutral in regard to CO 2 at longer timescales. In simulations where climate change negatively affected ecosystem carbon stores, there was a 20% chance of committing Type II error, even with 20 years of sequential data.

Distribution of nitrogen-15 tracers applied to the canopy of a mature spruce-hemlock stand, Howland, Maine, USA - David Bryan Dail; David Y. Hollinger; Eric A. Davidson; Ivan Fernandez; Herman C. Sievering; Neal A. Scott; Elizabeth Gaige (Oecologia, 2009)

Influence of Nocturnal Low-level Jets on Eddy-covariance Fluxes over a Tall Forest Canopy - Thara V. Prabha; Monique Y. Leclerc; Anandakumar Karipot; David Y. Hollinger; Erich Mursch-Radlgruber (Boundary-Layer Meteorology, 2008)

Use of digital webcam images to track spring green-up in a deciduous broadleaf forest - Andrew D. Richardson; Julian P. Jenkins; Bobby H. Braswell; David Y. Hollinger; Scott V. Ollinger; Marie-Louise Smith (Oecologia, 2007)

Environmental variation is directly responsible for short‐ but not long‐term variation in forest‐atmosphere carbon exchange - ANDREW D. RICHARDSON; DAVID Y. HOLLINGER; JOHN D. ABER; SCOTT V. OLLINGER; BOBBY H. BRASWELL (Global Change Biology, 2007)
Tower‐based eddy covariance measurements of forest‐atmosphere carbon dioxide (CO 2 ) exchange from many sites around the world indicate that there is considerable year‐to‐year variation in net ecosystem exchange (NEE). Here, we use a statistical modeling approach to partition the interannual variability in NEE (and its component fluxes, ecosystem respiration, R eco , and gross photosynthesis, P gross ) into two main effects: variation in environmental drivers (air and soil temperature, solar radiation, vapor pressure deficit, and soil water content) and variation in the biotic response to this environmental forcing (as characterized by the model parameters). The model is applied to a 9‐year data set from the Howland AmeriFlux site, a spruce‐dominated forest in Maine, USA. Gap‐filled flux measurements at this site indicate that the forest has been sequestering, on average, 190 g C m −2 yr −1 , with a range from 130 to 270 g C m −2 yr −1 . Our fitted model predicts somewhat more uptake (mean 270 g C m −2 yr −1 ), but interannual variation is similar, and wavelet variance analyses indicate good agreement between tower measurements and model predictions across a wide range of timescales (hours to years). Associated with the interannual variation in NEE are clear differences among years in model parameters for both R eco and P gross . Analysis of model predictions suggests that, at the annual time step, about 40% of the variance in modeled NEE can be attributed to variation in environmental drivers, and 55% to variation in the biotic response to this forcing. As model predictions are aggregated at longer timescales (from individual days to months to calendar year), variation in environmental drivers becomes progressively less important, and variation in the biotic response becomes progressively more important, in determining the modeled flux. There is a strong negative correlation between modeled annual P gross and R eco ( r =−0.93, P ≤0.001); two possible explanations for this correlation are discussed. The correlation promotes homeostasis of NEE: the interannual variation in modeled NEE is substantially less than that for either P gross or R eco

Linking flux network measurements to continental scale simulations: ecosystem carbon dioxide exchange capacity under non‐water‐stressed conditions - KATHERINE E. OWEN; JOHN TENHUNEN; MARKUS REICHSTEIN; QUAN WANG; EVA FALGE; RALF GEYER; XIANGMING XIAO; PAUL STOY; CHRISTOF AMMANN; ALTAF ARAIN; MARC AUBINET; MIKA AURELA; et al. (Global Change Biology, 2007)
This paper examines long‐term eddy covariance data from 18 European and 17 North American and Asian forest, wetland, tundra, grassland, and cropland sites under non‐water‐stressed conditions with an empirical rectangular hyperbolic light response model and a single layer two light‐class carboxylase‐based model. Relationships according to ecosystem functional type are demonstrated between empirical and physiological parameters, suggesting linkages between easily estimated parameters and those with greater potential for process interpretation. Relatively sparse documentation of leaf area index dynamics at flux tower sites is found to be a major difficulty in model inversion and flux interpretation. Therefore, a simplification of the physiological model is carried out for a subset of European network sites with extensive ancillary data. The results from these selected sites are used to derive a new parameter and means for comparing empirical and physiologically based methods across all sites, regardless of ancillary data. The results from the European analysis are then compared with results from the other Northern Hemisphere sites and similar relationships for the simplified process‐based parameter were found to hold for European, North American, and Asian temperate and boreal climate zones. This parameter is useful for bridging between flux network observations and continental scale spatial simulations of vegetation/atmosphere carbon dioxide exchange.

Environmental variation is directly responsible for short- but not long-term variation in forest-atmosphere carbon exchange - ANDREW D. RICHARDSON; DAVID Y. HOLLINGER; JOHN D. ABER; SCOTT V. OLLINGER; BOBBY H. BRASWELL (Global Change Biology, 2007)

Linking flux network measurements to continental scale simulations: ecosystem carbon dioxide exchange capacity under non-water-stressed conditions - KATHERINE E. OWEN; JOHN TENHUNEN; MARKUS REICHSTEIN; QUAN WANG; EVA FALGE; RALF GEYER; XIANGMING XIAO; PAUL STOY; CHRISTOF AMMANN; ALTAF ARAIN; MARC AUBINET; MIKA AURELA; et al. (Global Change Biology, 2007)

Changes in Carbon Storage and Net Carbon Exchange One Year After an Initial Shelterwood Harvest at Howland Forest, ME - Neal A. Scott; Charles A. Rodrigues; Holly Hughes; John T. Lee; Eric A. Davidson; D. Bryan Dail; Phil Malerba; David Y. Hollinger (Environmental Management, 2004)

Spatial Variability of Turbulent Fluxes in the Roughness Sublayer of an Even-Aged Pine Forest - Gabriel Katul; Cheng-I Hsieh; David Bowling; Kenneth Clark; Narasinha Shurpali; Andrew Turnipseed; John Albertson; Kevin Tu; Dave Hollinger; Bob Evans; Brian Offerle; Dean Anderson; et al. (Boundary-Layer Meteorology, 1999)