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Hybrid-poplar tree plantations provide a source for biofuel and biomass, but they also increase forest isoprene emissions. The consequences of increased isoprene emissions include higher rates of tropospheric ozone production, increases in the lifetime of methane, and increases in atmospheric aerosol production, all of which affect the global energy budget and/or lead to the degradation of air quality. Using RNA interference (RNAi) to suppress isoprene emission, we show that this trait, which is thought to be required for the tolerance of abiotic stress, is not required for high rates of photosynthesis and woody biomass production in the agroforest plantation environment, even in areas with high levels of climatic stress. Biomass production over 4 y in plantations in Arizona and Oregon was similar among genetic lines that emitted or did not emit significant amounts of isoprene. Lines that had substantially reduced isoprene emission rates also showed decreases in flavonol pigments, which reduce oxidative damage during extremes of abiotic stress, a pattern that would be expected to amplify metabolic dysfunction in the absence of isoprene production in stress-prone climate regimes. However, compensatory increases in the expression of other proteomic components, especially those associated with the production of protective compounds, such as carotenoids and terpenoids, and the fact that most biomass is produced prior to the hottest and driest part of the growing season explain the observed pattern of high biomass production with low isoprene emission. Our results show that it is possible to reduce the deleterious influences of isoprene on the atmosphere, while sustaining woody biomass production in temperate agroforest plantations.

The response of terrestrial carbon uptake to increasing atmospheric [CO2 ], that is the CO2 fertilization effect (CFE), remains a key area of uncertainty in carbon cycle science. Here we provide a perspective on how satellite observations could be better used to understand and constrain CFE. We then highlight data assimilation (DA) as an effective way to reconcile different satellite datasets and systematically constrain carbon uptake trends in Earth System Models. As a proof-of-concept, we show that joint DA of multiple independent satellite datasets reduced model ensemble error by better constraining unobservable processes and variables, including those directly impacted by CFE. DA of multiple satellite datasets offers a powerful technique that could improve understanding of CFE and enable more accurate forecasts of terrestrial carbon uptake.

Severe drought can cause lagged effects on tree physiology that negatively impact forest functioning for years. These "drought legacy effects" have been widely documented in tree-ring records and could have important implications for our understanding of broader scale forest carbon cycling. However, legacy effects in tree-ring increments may be decoupled from ecosystem fluxes due to (a) postdrought alterations in carbon allocation patterns; (b) temporal asynchrony between radial growth and carbon uptake; and (c) dendrochronological sampling biases. In order to link legacy effects from tree rings to whole forests, we leveraged a rich dataset from a Midwestern US forest that was severely impacted by a drought in 2012. At this site, we compiled tree-ring records, leaf-level gas exchange, eddy flux measurements, dendrometer band data, and satellite remote sensing estimates of greenness and leaf area before, during, and after the 2012 drought. After accounting for the relative abundance of tree species in the stand, we estimate that legacy effects led to ~10% reductions in tree-ring width increments in the year following the severe drought. Despite this stand-scale reduction in radial growth, we found that leaf-level photosynthesis, gross primary productivity (GPP), and vegetation greenness were not suppressed in the year following the 2012 drought. Neither temporal asynchrony between radial growth and carbon uptake nor sampling biases could explain our observations of legacy effects in tree rings but not in GPP. Instead, elevated leaf-level photosynthesis co-occurred with reduced leaf area in early 2013, indicating that resources may have been allocated away from radial growth in conjunction with postdrought upregulation of photosynthesis and repair of canopy damage. Collectively, our results indicate that tree-ring legacy effects were not observed in other canopy processes, and that postdrought canopy allocation could be an important mechanism that decouples tree-ring signals from GPP.

Despite their sparse vegetation, dryland regions exert a huge influence over global biogeochemical cycles because they cover more than 40% of the world surface (Schimel 2010 Science 327 418–9). It is thought that drylands dominate the inter-annual variability (IAV) and long-term trend in the global carbon (C) cycle (Poulter et al 2014 Nature 509 600–3, Ahlstrom et al 2015 Science 348 895–9, Zhang et al 2018 Glob. Change Biol. 24 3954–68). Projections of the global land C sink therefore rely on accurate representation of dryland C cycle processes; however, the dynamic global vegetation models (DGVMs) used in future projections have rarely been evaluated against dryland C flux data. Here, we carried out an evaluation of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 dryland flux sites in the southwestern US encompassing a range of ecosystem types (forests, shrub- and grasslands). We find that all the models underestimate both mean annual C uptake/release as well as the magnitude of NEE IAV, suggesting that improvements in representing dryland regions may improve global C cycle projections. Across all models, the sensitivity and timing of ecosystem C uptake to plant available moisture was at fault. Spring biases in gross primary production (GPP) dominate the underestimate of mean annual NEE, whereas models’ lack of GPP response to water availability in both spring and summer monsoon are responsible for inability to capture NEE IAV. Errors in GPP moisture sensitivity at high elevation forested sites were more prominent during the spring, while errors at the low elevation shrub and grass-dominated sites were more important during the monsoon. We propose a range of hypotheses for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future dryland DGVM developments. Our analysis suggests that improvements in modeling C cycle processes across more than a quarter of the Earth’s land surface could be achieved by addressing the moisture sensitivity of dryland C uptake.

International audience; Atmospheric carbon dioxide concentration ([CO 2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO 2] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO 2]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO 2] (iCO 2) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO 2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO 2 responses are high in comparison to experiments and predictions from theory. Plantmortality and soil carbon iCO 2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system. publishedVersion

Increasing water-use efficiency (WUE), the ratio of carbon gain to water loss, is a key mechanism that enhances carbon uptake by terrestrial vegetation under rising atmospheric CO2 (ca ). Existing theory and empirical evidence suggest a proportional WUE increase in response to rising ca as plants maintain a relatively constant ratio between the leaf intercellular (ci ) and ambient (ca ) partial CO2 pressure (ci /ca ). This has been hypothesized as the main driver of the strengthening of the terrestrial carbon sink over the recent decades. However, proportionality may not characterize CO2 effects on WUE on longer time-scales and the role of climate in modulating these effects is uncertain. Here, we evaluate long-term WUE responses to ca and climate from 1901 to 2012 CE by reconstructing intrinsic WUE (iWUE, the ratio of photosynthesis to stomatal conductance) using carbon isotopes in tree rings across temperate forests in the northeastern USA. We show that iWUE increased steadily from 1901 to 1975 CE but remained constant thereafter despite continuously rising ca . This finding is consistent with a passive physiological response to ca and coincides with a shift to significantly wetter conditions across the region. Tree physiology was driven by summer moisture at multi-decadal time-scales and did not maintain a constant ci /ca in response to rising ca indicating that a point was reached where rising CO2 had a diminishing effect on tree iWUE. Our results challenge the mechanism, magnitude, and persistence of CO2 's effect on iWUE with significant implications for projections of terrestrial productivity under a changing climate.

Forecasts of forest responses to climate variability are governed by climate exposure and ecosystem sensitivity, but ecosystem model projections and process representations are under-constrained by data at multidecadal and longer timescales. Here, we assess ecosystem sensitivity to centennial-scale hydroclimate variability, by comparing dendroclimatic and pollen-inferred reconstructions of drought, forest composition and biomass for the last millennium with five ecosystem model simulations. In both observations and models, spatial patterns in ecosystem responses to hydroclimate variability are strongly governed by ecosystem sensitivity rather than climate exposure. Ecosystem sensitivity was highest in simpler models and higher than observations, suggesting that interactions among biodiversity, demography, and ecophysiology processes dampen the sensitivity of forest composition and biomass to climate variability and change. By integrating ecosystem models with observations from timescales extending beyond the instrumental record, we can better understand and forecast the mechanisms regulating forest sensitivity to climate variability in a complex and changing world.

Coarse woody debris (CWD; i.e. downed limbs and boles) serves numerous ecosystem functions, which vary according to the degree of decay. CWD decay is often described using five categories based on readily observed physical characteristics ranging from freshly fallen (Class I) to advanced decay with little structural integrity (Class V). Though useful in categorizing downed wood in a forest, these categories do not necessarily provide information about time since death or the decay process. Dendrochronology can be used to assign death dates to CWD and begin to provide a temporal description of the decay process. We used standard dendrochronological techniques to determine the death dates of 94 CWD samples from five common hardwood taxa in southern Indiana. Across taxa, the time since death of Class I (1.4 ± 1.7 years; mean ± SD; least decayed class) was significantly shorter than Class II (5.2 ± 3.6 years), which was shorter than the more decayed classes (Class III: 11.5 ± 4.9, and Class IV: 11.2 ...

DOE's Office of Science; NASA [NNH16ZDA001N]; USDA [58-0111-17-013]; DOE's Regional and Global Climate Modeling Program [DE-SC0016011]

The response of understory trees to climate variability is key to understanding current and future forest dynamics. However, analyses of climatic effects on tree growth have primarily focused on the upper canopy, leaving understory dynamics unresolved. We analyzed differences in climate sensitivity based on canopy position of four common tree species (Acer rubrum, Fagus grandifolia, Quercus rubra, and Tsuga canadensis) using growth information from 1,084 trees across eight sites in the northeastern United States. Effects of canopy position on climate response varied, but were significant and often nonlinear, for all four species. Compared to overstory trees, understory trees showed stronger reductions in growth at high temperatures and varied shifts in precipitation response. This contradicts the prevailing assumption that climate responses, particularly to temperature, of understory trees are buffered by the overstory. Forest growth trajectories are uncertain in compositionally and structurally complex forests, and future demography and regeneration dynamics may be misinferred if not all canopy levels are represented in future forecasts.

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multi-model comparisons with data have largely focused on individual processes at sub-annual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO2 at multi-decadal and centennial time scales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO2 in ten ecosystem models with the sensitivities found in tree-ring reconstructions of NPP and raw ring-width series at six temperate forest sites. These model-data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree-ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm growing season temperatures while tree-ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO2, but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multi-decadal and multi-centennial time scales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO2 in individual models.

Plant isoprene emissions have been linked to several reaction pathways involved in atmospheric photochemistry. Evidence exists from a limited set of past observations that isoprene emission rate (I(sub s)) decreases as a function of increasing atmospheric CO2 concentration, and that increased temperature suppresses the CO2 effect. We studied interactions between intercellular CO2 concentration (C(sub I)) and temperature as they affect I(sub s) in field-grown hybrid poplar trees in one of the warmest climates on earth - the Sonoran Desert of the southwestern United States. We observed an unexpected midsummer down regulation of I(sub s) despite the persistence of relatively high temperatures. High temperature suppression of the I(sub s):C(sub I) relation occurred at all times during the growing season, but sensitivity of I(sub s) to increased C(sub I) was greatest during the midsummer period when I(subs) was lowest. We interpret the seasonal down regulation of I(sub s) and increased sensitivity of I(sub s) to C(sub I) as being caused by weather changes associated with the onset of a regional monsoon system. Our observations on the temperature suppression of the I(sub s):C(sub I) relation are best explained by the existence of a small pool of chloroplastic inorganic phosphate, balanced by several large, connected metabolic fluxes, which together, determine the C(sub I) and temperature dependencies of phosphoenolpyruvate import into the chloroplast.

Rapid changes to the biosphere are altering ecological processes worldwide. Developing informed policies for mitigating the impacts of environmental change requires an exponential increase in the quantity, diversity, and resolution of field-collected data, which, in turn, necessitates greater reliance on innovative technologies to monitor ecological processes across local to global scales. Automated digital time-lapse cameras – “phenocams” – can monitor vegetation status and environmental changes over long periods of time. Phenocams are ideal for documenting changes in phenology, snow cover, fire frequency, and other disturbance events. However, effective monitoring of global environmental change with phenocams requires adoption of data standards. New continental-scale ecological research networks, such as the US National Ecological Observatory Network (NEON) and the European Union's Integrated Carbon Observation System (ICOS), can serve as templates for developing rigorous data standards and extending the utility of phenocam data through standardized ground-truthing. Open-source tools for analysis, visualization, and collaboration will make phenocam data more widely usable.

© 2017 Elsevier B.V. AmeriFlux scientists were early adopters of a network-enabled approach to ecosystem science that continues to transform the study of land-atmosphere interactions. In the 20 years since its formation, AmeriFlux has grown to include more than 260 flux tower sites in the Americas that support continuous observation of ecosystem carbon, water, and energy fluxes. Many of these sites are co-located within a similar climate regime, and more than 50 have data records that exceed 10 years in length. In this prospective assessment of AmeriFlux's strengths in a new era of network-enabled ecosystem science, we discuss how the longevity and spatial distribution of AmeriFlux data make them exceptionally well suited for disentangling ecosystem response to slowly evolving changes in climate and land-cover, and to rare events like droughts and biological disturbances. More recently, flux towers have also been integrated into environmental observation networks that have broader scientific goals; in North America these include the National Ecological Observatory Network (NEON), Critical Zone Observatory network (CZO), and Long-Term Ecological Research network (LTER). AmeriFlux stands apart from these other networks in its reliance on voluntary participation of individual sites, which receive funding from diverse sources to pursue a wide, transdisciplinary array of research topics. This diffuse, grassroots approach fosters methodological and theoretical innovation, but also challenges network-level data synthesis and data sharing to the network. While AmeriFlux has had strong ties to other regional flux networks and FLUXNET, better integration with networks like NEON, CZO and LTER provides opportunities for new types of cooperation and synergies that could strengthen the scientific output of all these networks.

In the United States’ (US) Northern Rockies, synoptic pressure systems and atmospheric circulation drive interannual variation in seasonal temperature and precipitation. The radial growth of high-elevation trees in this semi-arid region captures this temperature and precipitation variability and provides long time series to contextualize instrumental-era variability in synoptic-scale climate patterns. Such variability in climate patterns can trigger extreme climate events, such as droughts, floods, and forest fires, which have a damaging impact on human and natural systems. We developed 11 tree-ring width (TRW) chronologies from multiple species and sites to investigate the seasonal climatic drivers of tree growth in the Bighorn Mountains, WY. A principal component analysis of the chronologies identified 54% of shared common variance (1894-2014). Tree growth (expressed by PC1) was driven by multiple seasonal climate variables: previous October and current July temperatures, as well as previous December and current April precipitation, had a positive influence on growth, whereas growth was limited by July precipitation. These seasonal growth-climate relationships corresponded to circulation patterns at higher atmospheric levels over the Bighorn Mountains. Tree growth was enhanced when the winter jet stream was in a northward position, which led to warmer winters, and when the spring jet stream was further south, which led to wetter springs. The second principal component, explaining 19% of the variance, clustered sites by elevation and was strongly related to summer temperature. We leverage this summer temperature signal in our TRW chronologies by combining it with an existing maximum latewood density (MXD) chronology in a nested approach. This allowed us to reconstruct Bighorn Mountains summer (June, July, and August) temperature (BMST) back to 1654, thus extending the instrumental temperature record by 250 years. Our BMST reconstruction explains 39-53% of the variance in regional summer temperature variability. The 1830s were the relatively coolest decade and the 1930s were the warmest decade over the reconstructed period (1654-1983 CE) – which excludes the most recent 3 decades. Our results contextualize recent drivers and trends of climate variability in the US Northern Rockies, which contributes to the information that managers of human and natural systems need in order to prepare for potential future variability.

[1] Forecasting the carbon uptake potential of terrestrial ecosystems in the face of future climate change has proven challenging. Process models, which have been increasingly used to study ecosystem-atmosphere carbon and water exchanges when conditioned with tower-based eddy covariance data, have the potential to inform us about biogeochemical processes in future climate regimes, but only if we can reconcile the spatial and temporal scales used for observed fluxes and projected climate. Here, we used weather generator and ecosystem process models conditioned on observed weather dynamics and carbon/water fluxes, and embedded them within climate projections from a suite of six Earth Systems Models. Using this combination of models, we studied carbon cycle processes in a subalpine forest within the context of future (2080–2099) climate regimes. The assimilation of daily averaged, observed net ecosystem CO2 exchange (NEE) and evapotranspiration (ET) into the ecosystem process model resulted in retrieval of projected NEE with a level of accuracy that was similar to that following the assimilation of half-daily averaged observations; the assimilation of 30 min averaged fluxes or monthly averaged fluxes caused degradation in the model's capacity to accurately simulate seasonal patterns in observed NEE. Using daily averaged flux data with daily averaged weather data projected for the period 2080–2099, we predicted greater forest net CO2 uptake in response to a lengthening of the growing season. These results contradict our previous observations of reduced CO2 uptake in response to longer growing seasons in the current (1999–2008) climate regime. The difference between these analyses is due to a projected increase in the frequency of rain versus snow during warmer winters of the future. Our results demonstrate the sensitivity of modeled processes to local variation in meteorology, which is often left unresolved in traditional approaches to earth systems modeling, and the importance of maintaining similarity in the timescales used in ecosystem process models driven by downscaled climate projections.

Earth's future carbon balance and regional carbon exchange dynamics are inextricably linked to plant photosynthesis. Spectral vegetation indices are widely used as proxies for vegetation greenness and to estimate state variables such as vegetation cover and leaf area index. However, the capacity of green leaves to take up carbon can change throughout the season. We quantify photosynthetic capacity as the maximum rate of RuBP carboxylation (Vcmax) and regeneration (Jmax). Vcmax and Jmax vary within-season due to interactions between ontogenetic processes and meteorological variables. Remote sensing-based estimation of Vcmax and Jmax using leaf reflectance spectra is promising, but temporal variation in relationships between these key determinants of photosynthetic capacity, leaf reflectance spectra, and the models that link these variables has not been evaluated. To address this issue, we studied hybrid poplar (Populus spp.) during a 7-week mid-summer period to quantify seasonally-dynamic relationships between Vcmax, Jmax, and leaf spectra. We compared in situ estimates of Vcmax and Jmax from gas exchange measurements to estimates of Vcmax and Jmax derived from partial least squares regression (PLSR) and fresh-leaf reflectance spectroscopy. PLSR models were robust despite dynamic temporal variation in Vcmax and Jmax throughout the study period. Within-population variation in plant stress modestly reduced PLSR model predictive capacity. Hyperspectral vegetation indices were well-correlated to Vcmax and Jmax, including the widely-used Normalized Difference Vegetation Index. Our results show that hyperspectral estimation of plant physiological traits using PLSR may be robust to temporal variation. Additionally, hyperspectral vegetation indices may be sufficient to detect temporal changes in photosynthetic capacity in contexts similar to those studied here. Overall, our results highlight the potential for hyperspectral remote sensing to estimate determinants of photosynthetic capacity during periods with dynamic temporal variations related to seasonality and plant stress, thereby improving estimates of plant productivity and characterization of the associated carbon budget.

In the southwest United States, the current prolonged warm drought is similar to the predicted future climate change scenarios for the region. This study aimed to determine patterns in vegetation response to the early 21st century drought across multiple biomes. We hypothesized that different biomes (forests, shrublands, and grasslands) would have different relative sensitivities to both climate drivers (precipitation and temperature) and legacy effects (previous‐year's productivity). We tested this hypothesis at eight Ameriflux sites in various Southwest biomes using NASA Moderate‐resolution Imaging Spectroradiometer Enhanced Vegetation Index (EVI) from 2001 to 2013. All sites experienced prolonged dry conditions during the study period. The impact of combined precipitation and temperature on Southwest ecosystems at both annual and sub‐annual timescales was tested using Standardized Precipitation Evapotranspiration Index (SPEI). All biomes studied had critical sub‐annual climate periods during which precipitation and temperature influenced production. In forests, annual peak greenness (EVImax) was best predicted by 9‐month SPEI calculated in July (i.e., January–July). In shrublands and grasslands, EVImax was best predicted by SPEI in July through September, with little effect of the previous year's EVImax. Daily gross ecosystem production (GEP) derived from flux tower data yielded further insights into the complex interplay between precipitation and temperature. In forests, GEP was driven by cool‐season precipitation and constrained by warm‐season maximum temperature. GEP in both shrublands and grasslands was driven by summer precipitation and constrained by high daily summer maximum temperatures. In grasslands, there was a negative relationship between temperature and GEP in July, but no relationship in August and September. Consideration of sub‐annual climate conditions and the inclusion of the effect of temperature on the water balance allowed us to generalize the functional responses of vegetation to predicted future climate conditions. We conclude that across biomes, drought conditions during critical sub‐annual climate periods could have a strong negative impact on vegetation production in the southwestern United States.

© 2016 Elmendorf et al. Phenology is an integrative science that comprises the study of recurring biological activities or events. In an era of rapidly changing climate, the relationship between the timing of those events and environmental cues such as temperature, snowmelt, water availability, or day length are of particular interest. This article provides an overview of the observer-based plant phenology sampling conducted by the U.S. National Ecological Observatory Network (NEON), the resulting data, and the rationale behind the design. Trained technicians will conduct regular in situ observations of plant phenology at all terrestrial NEON sites for the 30-yr life of the observatory. Standardized and coordinated data across the network of sites can be used to quantify the direction and magnitude of the relationships between phenology and environmental forcings, as well as the degree to which these relationships vary among sites, among species, among phenophases, and through time. Vegetation at NEON sites will also be monitored with tower-based cameras, satellite remote sensing, and annual high-resolution airborne remote sensing. Ground-based measurements can be used to calibrate and improve satellite-derived phenometrics. NEON's phenology monitoring design is complementary to existing phenology research efforts and citizen science initiatives throughout the world and will produce interoperable data. By collocating plant phenology observations with a suite of additional meteorological, biophysical, and ecological measurements (e.g., climate, carbon flux, plant productivity, population dynamics of consumers) at 47 terrestrial sites, the NEON design will enable continental-scale inference about the status, trends, causes, and ecological consequences of phenological change.

The earth’s future climate state is highly dependent upon changes in terrestrial C storage in response to rising concentrations of atmospheric CO2. Here we show that consistently enhanced rates of net primary production (NPP) are sustained by a C-cascade through the root-microbe-soil system; increases in the flux of C belowground under elevated CO2 stimulated microbial activity, accelerated the rate of soil organic matter decomposition and stimulated tree uptake of N bound to this SOM. This process set into motion a positive feedback maintaining greater C gain under elevated CO2 as a result of increases in canopy N content and higher photosynthetic N-use efficiency. The ecosystem-level consequence of the enhanced requirement for N and the exchange of plant C for N belowground is the dominance of C storage in tree biomass but the preclusion of a large C sink in the soil.

Regional-scale tree die-off events driven by drought and warming and associated pests and pathogens have occurred recently on all forested continents and are projected to increase in frequency and extent with future warming. Within areas where tree mortality has occurred, ecological, hydrological and meteorological consequences are increasingly being documented. However, the potential for tree die-off to impact vegetation processes and related carbon dynamics in areas remote to where die-off occurs has rarely been systematically evaluated, particularly for multiple distinct regions within a given continent. Such remote impacts can occur when climate effects of local vegetation change are propagated by atmospheric circulation—the phenomena of 'ecoclimate teleconnections'. We simulated tree die-off events in the 13 most densely forested US regions (selected from the 20 US National Ecological Observatory Network [NEON] domains) and found that tree die-off even for smaller regions has potential to affect climate and hence Gross Primary Productivity (GPP) in disparate regions (NEON domains), either positively or negatively. Some regions exhibited strong teleconnections to several others, and some regions were relatively sensitive to tree loss regardless of what other region the tree loss occurred in. For the US as a whole, loss of trees in the Pacific Southwest—an area undergoing rapid tree die-off—had the largest negative impact on remote US GPP whereas loss of trees in the Mid-Atlantic had the largest positive impact. This research lays a foundation for hypotheses that identify how the effects of tree die-off (or other types of tree loss such as deforestation) can ricochet across regions by revealing hot-spots of forcing and response. Such modes of connectivity have direct applicability for improving models of climate change impacts and for developing more informed and coordinated carbon accounting across regions.

Tree-ring records can provide valuable information to advance our understanding of contemporary terrestrial carbon cycling and to reconstruct key metrics in the decades preceding monitoring data. The growing use of tree rings in carbon-cycle research is being facilitated by increasing recognition of reciprocal benefits among research communities. Yet, basic questions persist regarding what tree rings represent at the ecosystem level, how to optimally integrate them with other data streams, and what related challenges need to be overcome. It is also apparent that considerable unexplored potential exists for tree rings to refine assessments of terrestrial carbon cycling across a range of temporal and spatial domains. Here, we summarize recent advances and highlight promising paths of investigation with respect to (1) growth phenology, (2) forest productivity trends and variability, (3) CO2 fertilization and water-use efficiency, (4) forest disturbances, and (5) comparisons between observational and computational forest productivity estimates. We encourage the integration of tree-ring data: with eddy-covariance measurements to investigate carbon allocation patterns and water-use efficiency; with remotely sensed observations to distinguish the timing of cambial growth and leaf phenology; and with forest inventories to develop continuous, annually-resolved and long-term carbon budgets. In addition, we note the potential of tree-ring records and derivatives thereof to help evaluate the performance of earth system models regarding the simulated magnitude and dynamics of forest carbon uptake, and inform these models about growth responses to (non-)climatic drivers. Such efforts are expected to improve our understanding of forest carbon cycling and place current developments into a long-term perspective.

The demand for large-scale and long-term information on tree growth is increasing rapidly as environmental change research strives to quantify and forecast the impacts of continued warming on forest ecosystems. This demand, combined with the now quasi-global availability of tree-ring observations, has inspired researchers to compile large tree-ring networks to address continental or even global-scale research questions. However, these emergent spatial objectives contrast with paleo-oriented research ideas that have guided the development of many existing records. A series of challenges related to how, where, and when samples have been collected is complicating the transition of tree rings from a local to a global resource on the question of tree growth. Herein, we review possibilities to scale tree-ring data (A) from the sample to the whole tree, (B) from the tree to the site, and (C) from the site to larger spatial domains. Representative tree-ring sampling supported by creative statistical approaches is thereby key to robustly capture the heterogeneity of climate-growth responses across forested landscapes. We highlight the benefits of combining the temporal information embedded in tree rings with the spatial information offered by forest inventories and earth observations to quantify tree growth and its drivers. In addition, we show how the continued development of mechanistic tree-ring models can help address some of the non-linearities and feedbacks that complicate making inference from tree-ring data. By embracing scaling issues, the discipline of dendrochronology will greatly increase its contributions to assessing climate impacts on forests and support the development of adaptation strategies.

How forest growth responds to climate change will impact the global carbon cycle. The sensitivity of tree growth and thus forest productivity to climate can be inferred from tree-ring increments, but individual tree responses may differ from the overall forest response. Tree-ring data have also been used to estimate interannual variability in aboveground biomass, but a shortage of robust uncertainty estimates often limits comparisons with other measurements of the carbon cycle across variable ecological settings. Here we identify and quantify four important sources of uncertainty that affect tree-ring-based aboveground biomass estimates: subsampling, allometry, forest density (sampling), and mortality. In addition, we investigate whether transforming rings widths into biomass affects the underlying growth-climate relationships at two coniferous forests located in the Valles Caldera in northern New Mexico. Allometric and mortality sources of uncertainty contributed most (34–57 and 24–42%, respectively) and subsampling uncertainty least (7–8%) to the total uncertainty for cumulative biomass estimates. Subsampling uncertainty, however, was the largest source of uncertainty for year-to-year variations in biomass estimates, and its large contribution indicates that between-tree growth variability remains influential to changes in year-to-year biomass estimates for a stand. The effect of the large contribution of the subsampling uncertainty is reflected by the different climate responses of large and small trees. Yet, the average influence of climate on tree growth persisted through the biomass transformation, and the biomass growth-climate relationship is comparable to that found in traditional climate reconstruction-oriented tree-ring chronologies. Including the uncertainties in estimates of aboveground biomass will aid comparisons of biomass increment across disparate forests, as well as further the use of these data in vegetation modeling frameworks.