High-latitude ecosystems have the capacity to release large amounts of carbon dioxide (CO2) to the atmosphere in response to increasing temperatures, representing a potentially significant positive feedback within the climate system. Here, we combine aircraft and tower observations of atmospheric CO2 with remote sensing data and meteorological products to derive temporally and spatially resolved year-round CO2 fluxes across Alaska during 2012–2014. We find that tundra ecosystems were a net source of CO2 to the atmosphere annually, with especially high rates of respiration during early winter (October through December). Long-term records at Barrow, AK, suggest that CO2 emission rates from North Slope tundra have increased during the October through December period by 73% ± 11% since 1975, and are correlated with rising summer temperatures. Together, these results imply increasing early winter respiration and net annual emission of CO2 in Alaska, in response to climate warming. Our results provide evidence that the decadal-scale increase in the amplitude of the CO2 seasonal cycle may be linked with increasing biogenic emissions in the Arctic, following the growing season. Early winter respiration was not well simulated by the Earth System Models used to forecast future carbon fluxes in recent climate assessments. Therefore, these assessments may underestimate the carbon release from Arctic soils in response to a warming climate.

SummaryThe first generation of forest free-air CO 2 enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO 2 concentration in the atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR-FACE in a 150-yr-old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model-data interaction as an integral part of experimental design and to address a set of cross-site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity.

The response of terrestrial ecosystems to rising atmospheric CO2 concentration (Ca ), particularly under nutrient-limited conditions, is a major uncertainty in Earth System models. The Eucalyptus Free-Air CO2 Enrichment (EucFACE) experiment, recently established in a nutrient- and water-limited woodland presents a unique opportunity to address this uncertainty, but can best do so if key model uncertainties have been identified in advance. We applied seven vegetation models, which have previously been comprehensively assessed against earlier forest FACE experiments, to simulate a priori possible outcomes from EucFACE. Our goals were to provide quantitative projections against which to evaluate data as they are collected, and to identify key measurements that should be made in the experiment to allow discrimination among alternative model assumptions in a postexperiment model intercomparison. Simulated responses of annual net primary productivity (NPP) to elevated Ca ranged from 0.5 to 25% across models. The simulated reduction of NPP during a low-rainfall year also varied widely, from 24 to 70%. Key processes where assumptions caused disagreement among models included nutrient limitations to growth; feedbacks to nutrient uptake; autotrophic respiration; and the impact of low soil moisture availability on plant processes. Knowledge of the causes of variation among models is now guiding data collection in the experiment, with the expectation that the experimental data can optimally inform future model improvements.

Accurately quantifying the timing and magnitude of respiration and photosynthesis by high‐latitude ecosystems is important for understanding how a warming climate influences global carbon cycling. Data‐driven estimates of photosynthesis across Arctic regions often rely on satellite‐derived enhanced vegetation index (EVI); we find that satellite observations of solar‐induced chlorophyll fluorescence (SIF) provide a more direct proxy for photosynthesis. We model Alaskan tundra CO2 cycling (2012–2014) according to temperature and shortwave radiation and alternately input EVI or SIF to prescribe the annual seasonal cycle of photosynthesis. We find that EVI‐based seasonality indicates spring “green‐up” to occur 9 days prior to SIF‐based estimates, and that SIF‐based estimates agree with aircraft and tower measurements of CO2. Adopting SIF, instead of EVI, for modeling the seasonal cycle of tundra photosynthesis can result in more accurate estimates of growing season duration and net carbon uptake by arctic vegetation.

Increasing atmospheric CO2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO2-enrichment experiments in woody ecosystems that measured total NPP and biomass. CO2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m−2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO2 response of NPP (0.16 ± 0.03 kg C m−2 y−1) and the CO2-independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO2-independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO2 responses.