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Much of our biogeochemical understanding of forest disturbances comes from studies of severe or stand‐replacing events, which may have different impacts on coupled carbon (C) and nitrogen (N) cycling than subtler disturbances affecting only a fraction of the canopy. We measured a suite of interdependent C and N cycling processes following an experimental disturbance that accelerated mortality of the early successional canopy dominants (39% of basal area) in an aging secondary forest, hypothesizing that this subtle, spatially diffuse disturbance would temporarily decouple C and N cycles by decreasing belowground C allocation and thereby alter N cycling rates and pathways. We postulated that a short‐term decrease in ecosystem C uptake and an increase in N leaching would accompany this decoupling, but that concomitant increases in N availability and uptake by later successional species would promote rapid resilience of coupled C‐N cycles along new, stable trajectories. Disturbance decreased belowground C allocation and soil respiration, accelerated root turnover, and decreased root mass. These perturbations increased forest floor NH4+ and NO3− availability and NO emission, and declining root function caused water stress and N deficiency in senescent trees. Foliar N and leaf area increased in later successional trees, suggesting that enhanced N uptake supported new leaf area production. Two years after disturbance, N leaching losses and the decline in net ecosystem CO2 exchange were small, suggesting that coupled C‐N cycling was resilient to this subtle experimental disturbance. Therefore, compared with the severe disturbances reported in the literature, our subtle disturbance likely will have different effects on longer‐term forest biogeochemical trajectories. Key Points Subtle disturbances have subtle yet significant effects on CN cycling Short‐term responses to disturbance can set long‐term CN cycling trajectories Subtle and severe disturbances have different short‐ and long‐term effects on CN

$\\bullet$ Quantitative assessment of carbon (C) storage by forests requires an understanding of climatic controls over respiratory C loss. Ecosystem respiration can be estimated biometrically as the sum ($R_\\Sigma$) of soil (Rs), leaf ($R_l$) and wood (Rw) respiration, and meteorologically by measuring above-canopy nocturnal CO2 fluxes ($F_{cn}$). $\\bullet$ Here we estimated $R_\\Sigma$ over 5 yr in a forest in Michigan, USA, and compared $R_\\Sigma$ and $F_{cn}$ on turbulent nights. We also evaluated forest carbon-use efficiency ($E_c = P_{NP}/P_{GP}$) using biometric estimates of net primary production ($P_{NP}$) and $R_\\Sigma$ and $F_{cn}-derived$ estimates of gross primary production ($P_{GP}$). $\\bullet$ Interannual variation in $R_\\Sigma$ was modest ($142 g C m^{-2} yr^{-1}$). Mean annual $R_\\Sigma$ was $1425 g C m^{-2} yr^{-1}$; 71% from Rs, 18% from $R_l$, and 11% from Rw. Hourly $R_\\Sigma$ was well correlated with $F_{cn}$, but 11 to 58% greater depending on the time of year. Greater $R_\\Sigma$ compared with $F_{cn}$ resulted in higher estimated annual $P_{GP}$ and lower annual Ec (0.42 vs 0.54) using biometric and meteorological data, respectively. $\\bullet$ Our results provide one of the first multiyear estimates of $R_\\Sigma$ in a forested ecosystem, and document the responses of component respiratory C losses to major climatic drivers. They also provide the first assessment of Ec in a deciduous forest using independent estimates of $P_{GP}$.

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.

Earth system processes exhibit complex patterns across time, as do the models that seek to replicate these processes. Model output may or may not be significantly related to observations at different times and on different frequencies. Conventional model diagnostics provide an aggregate view of model–data agreement, but usually do not identify the time and frequency patterns of model–data disagreement, leaving unclear the steps required to improve model response to environmental drivers that vary on characteristic frequencies. Wavelet coherence can quantify the times and timescales at which two time series, for example time series of models and measurements, are significantly different. We applied wavelet coherence to interpret the predictions of 20 ecosystem models from the North American Carbon Program (NACP) Site-Level Interim Synthesis when confronted with eddy-covariance-measured net ecosystem exchange (NEE) from 10 ecosystems with multiple years of available data. Models were grouped into classes with similar approaches for incorporating phenology, the calculation of NEE, the inclusion of foliar nitrogen (N), and the use of model–data fusion. Models with prescribed, rather than prognostic, phenology often fit NEE observations better on annual to interannual timescales in grassland, wetland and agricultural ecosystems. Models that calculated NEE as net primary productivity (NPP) minus heterotrophic respiration (HR) rather than gross ecosystem productivity (GPP) minus ecosystem respiration (ER) fit better on annual timescales in grassland and wetland ecosystems, but models that calculated NEE as GPP minus ER were superior on monthly to seasonal timescales in two coniferous forests. Models that incorporated foliar nitrogen (N) data were successful at capturing NEE variability on interannual (multiple year) timescales at Howland Forest, Maine. The model that employed a model–data fusion approach often, but not always, resulted in improved fit to data, suggesting that improving model parameterization is important but not the only step for improving model performance. Combined with previous findings, our results suggest that the mechanisms driving daily and annual NEE variability tend to be correctly simulated, but the magnitude of these fluxes is often erroneous, suggesting that model parameterization must be improved. Few NACP models correctly predicted fluxes on seasonal and interannual timescales where spectral energy in NEE observations tends to be low, but where phenological events, multi-year oscillations in climatological drivers, and ecosystem succession are known to be important for determining ecosystem function. Mechanistic improvements to models must be made to replicate observed NEE variability on seasonal and interannual timescales.

Thermal adaptation of gross primary production and ecosystem respiration has been well documented over broad thermal gradients. However, no study has examined their interaction as a function of temperature, i.e. the thermal responses of net ecosystem exchange of carbon (NEE). In this study, we constructed temperature response curves of NEE against temperature using 380 site-years of eddy covariance data at 72 forest, grassland and shrubland ecosystems located at latitudes ranging from similar to 29 degrees N to 64 degrees N. The response curves were used to define two critical temperatures: transition temperature (T(b)) at which ecosystem transfer from carbon source to sink and optimal temperature (T(o)) at which carbon uptake is maximized. T(b) was strongly correlated with annual mean air temperature. T(o) was strongly correlated with mean temperature during the net carbon uptake period across the study ecosystems. Our results imply that the net ecosystem exchange of carbon adapts to the temperature across the geographical range due to intrinsic connections between vegetation primary production and ecosystem respiration.

This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles in the American Geophysical Union Biogeosciences section, and discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (a) Global collaboration, technology transfer, and application (Section 2), (b) Community engagement, community science, education, and stakeholder involvement (Section 3), and (c) Field, experimental, remote sensing, and real‐time data research and application (Section 4). We discuss needs and strategies for implementing ICON and outline short‐ and long‐term goals. The inclusion of global data and international community engagement are key to tackling grand challenges in biogeosciences. Although recent technological advances and growing open‐access information across the world have enabled global collaborations to some extent, several barriers, ranging from technical to organizational to cultural, have remained in advancing interoperability and tangible scientific progress in biogeosciences. Overcoming these hurdles is necessary to address pressing large‐scale research questions and applications in the biogeosciences, where ICON principles are essential. Here, we list several opportunities for ICON, including coordinated experimentation and field observations across global sites, that are ripe for implementation in biogeosciences as a means to scientific advancements and social progress. Plain Language Summary Biogeosciences is an interdisciplinary field that requires multiscale global data and concerted international community efforts to tackle grand challenges. However, several technical, institutional, and cultural hurdles have remained as major roadblocks toward scientific progress, hindering seamless global data acquisition and international community engagement. To bring a paradigm shift in biogeosciences, there is a need to implement integrated, coordinated, open, and networked efforts, collectively known as the Integrated, Coordinated, Open, Networked (ICON) principles. In this article, we present three related commentaries about the state of ICON, discuss needs to reduce geographical bias in data for enhancing scientific progress, and identify action items. Action items are primarily people‐centric and include but are not limited to: longer‐term funding priorities to institutionalize capacity and reduce entry costs, engagement of local stakeholders across the globe, incentivization of collaborations, and development of training and workshops for capacity building. Key Points Biogeosciences needs Integrated, Coordinated, Open, Networked (ICON) principles to address multiscale global problems and reduce geographical bias in scientific progress Much potential exists for emphasizing people‐centric capacity building, involving relevant stakeholders within an ICON framework Globally coordinated experimental and field data provide challenges and opportunities for scientific advancement in biogeosciences

We measured soil surface CO₂ efflux ($F_{\\text{s}}$) in loblolly pine stands (Pinus taeda L.) located on the Virginia Piedmont (VA) and South Carolina Coastal Plain (SC) in efforts to assess the impact climate, productivity, and cultural practices have on$F_{\\text{s}}$in the managed loblolly pine ecosystem. The effect of stand age on$F_{\\text{s}}$was examined using a replicated chronosequence approach in which stands ranging from 1 to 25 years since planting were investigated. Soil CO₂ efflux was measured on both VA and SC sites for over a year using a closed dynamic system. Multiple linear regression was used to evaluate$F_{\\text{s}}$correlates and examine the relationship between candidate explanatory variables and$F_{\\text{s}}$. Soil temperature (top 10 cm) was the major correlate with$F_{\\text{s}}$on both locations. We observed a positive age effect on$F_{\\text{s}}$in VA stands and no relationship between age and$F_{\\text{s}}$in SC stands. Annual soil C efflux declined with stand age in SC due to both reductions in soil temperatures as crown closure occurs and a diminishing heterotrophic C substrate pool. Annual estimated efflux ranges from 16.7 to 13.2 Mg C$\\text{ha}^{-1}$for 1 and 20-year-old stands, respectively. In contrast, annual soil C efflux increased with age in VA stands as a result of the positive relationship between stand age and$F_{\\text{s}}$, which appears to be related to an increase in the contribution of root respiration to total$F_{\\text{s}}$over time. In VA stands, efflux estimates range from 7.6 to 12.3 Mg C$\\text{ha}^{-1}$for 1 and 20-year-old stands, respectively. These results demonstrate the need to further consider the impact forest management and within-region variability have on soil C efflux over time when estimating C budgets.

The even‐aged northern hardwood forests of the Upper Great Lakes Region are undergoing an ecological transition during which structural and biotic complexity is increasing. Early‐successional aspen (Populus spp.) and birch (Betula papyrifera) are senescing at an accelerating rate and are being replaced by middle‐successional species including northern red oak (Quercus rubra), red maple (Acer rubrum), and white pine (Pinus strobus). Canopy structural complexity may increase due to forest age, canopy disturbances, and changing species diversity. More structurally complex canopies may enhance carbon (C) sequestration in old forests. We hypothesize that these biotic and structural alterations will result in increased structural complexity of the maturing canopy with implications for forest C uptake. At the University of Michigan Biological Station (UMBS), we combined a decade of observations of net primary productivity (NPP), leaf area index (LAI), site index, canopy tree‐species diversity, and stand age with canopy structure measurements made with portable canopy lidar (PCL) in 30 forested plots. We then evaluated the relative impact of stand characteristics on productivity through succession using data collected over a nine‐year period. We found that effects of canopy structural complexity on wood NPP (NPPW) were similar in magnitude to the effects of total leaf area and site quality. Furthermore, our results suggest that the effect of stand age on NPPW is mediated primarily through its effect on canopy structural complexity. Stand‐level diversity of canopy‐tree species was not significantly related to either canopy structure or NPPW. We conclude that increasing canopy structural complexity provides a mechanism for the potential maintenance of productivity in aging forests.

Abstract Net photosynthesis (Pn) of loblolly pine (Pinus taeda L.) foliage was monitored monthly in 14 yr old stands under near-ambient conditions over an entire year in upper and lower crowns and in both nonfertilized stands and stands receiving nutrient amendments for six consecutive years. Air temperature, humidity, vapor pressure deficit (VPD), photosynthetic photon flux density (PPFD), and plant water potential were monitored concurrently with Pn. Foliar nitrogen (N) concentration was also monitored. The effect of fertilization on Pn was inconsistent and generally not significant. Rates were consistently higher in the upper crown compared to the lower crown primarily due to variable light intensity. Multiple linear regression analysis shows that PPFD and VPD explain between 56% and 64% of the variability in foliar Pń, depending on the treatment. Little or no correlation between foliar N concentration and Pn was found, despite greater N concentrations in fertilized foliage, suggesting that fertilization does not enhance the photosynthetic capacity of loblolly pine foliage over the long term. Substantial amounts of carbon were fixed on measurement days during the winter season, even after freezing nights. Predicted light response curves indicate that foliar photosynthetic capacities are similar year-round, and gross primary productivity estimates (GPP) indicate that over 20% of the annual carbon fixation occurred during the nongrowing season. FOR. SCI. 50(1):1–9.

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr−1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr−1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×103 ± 0.9×103 km3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.