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Sensitivity of forest mortality to drought in carbon-dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, the potential of temporal autocorrelation of high-frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site-year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave-one-out cross-validation R

Soil nutrients, especially nitrogen (N) and phosphorus (P), regulate plant growth and hence influence carbon fluxes between the land surface and atmosphere. However, how forests adjust biomass partitioning to leaves, wood, and fine roots in response to N and/or P fertilization remains puzzling. Recent work in tropical forests suggests that trees increase fine root production under P fertilization, but it is unclear whether mechanistic models can reproduce this dynamic. In order to better understand mechanisms governing nutrient effects on plant allocation and improve models, we used the nutrient enabled ED2 model to simulate a fertilization experiment being conducted in a secondary tropical dry forest in Costa Rica. We evaluated how different allocation parameterizations affected model performance. These parameterizations prescribed a linear relationship between relative allocation to fine roots and soil P concentrations. The slope of the linear relationship was allowed to be positive, negative, or zero. Some parameterizations realistically simulated leaf, wood and fine root production, and these parameterizations all assumed a positive relationship between relative allocation to fine roots and soil P concentration. On a thirty-year timescale, under unfertilized conditions, our model predicted the largest aboveground biomass (AGB) accumulation when relative allocation to fine roots was positively related to soil P concentration. However, this result was mostly driven by increased water use rather than decreased nutrient limitation. On a thirty-year timescale with P fertilization, the assumption of a positive correlation between relative allocation to fine roots and soil P concentration led to over-investment to fine roots and reductions in vegetation biomass. Our study demonstrates the need of simultaneous measurements of leaf, wood, and fine root production in nutrient fertilization experiments. Models that do not accurately represent allocation to fine roots may be highly biased in their simulations of AGB, especially when simulating a range of sites with significantly different soil P concentrations.

Across tropical ecosystems, global environmental change is causing drier climatic conditions and increased nutrient deposition. Such changes represent large uncertainties due to unknown interactions between drought and nutrient availability in controlling ecosystem net primary productivity (NPP). Using a large-scale manipulative experiment, we studied for 4 years whether nutrient availability affects the individual and integrated responses of aboveground and belowground ecosystem processes to throughfall exclusion in 30-year-old mixed plantations of tropical dry forest tree species in Guanacaste, Costa Rica. We used a factorial design with four treatments: control, fertilization (F), drought (D), and drought + fertilization (D + F). While we found that a 13 %–15 % reduction in soil moisture only led to weak effects in the studied ecosystem processes, NPP increased as a function of F and D + F. The relative contribution of each biomass flux to NPP varied depending on the treatment, with woody biomass being more important for F and root biomass for D + F and D. Moreover, the F treatment showed modest increases in maximum canopy cover. Plant functional type (i.e., N fixation or deciduousness) and not the experimental manipulations was the main source of variation in tree growth. Belowground processes also responded to experimental treatments, as we found a decrease in nodulation for F plots and an increase in microbial carbon use efficiency for F and D plots. Our results emphasize that nutrient availability, more so than modest reductions in soil moisture, limits ecosystem processes in tropical dry forests and that soil fertility interactions with other aspects of drought intensity (e.g., vapor pressure deficit) are yet to be explored.

Methane emissions from organic-rich soils in the Arctic have been extensively studied due to their potential to increase the atmospheric methane burden as permafrost thaws1–3. However, this methane source might have been overestimated without considering high-affinity methanotrophs (HAMs; methane-oxidizing bacteria) recently identified in Arctic mineral soils4–7. Herein we find that integrating the dynamics of HAMs and methanogens into a biogeochemistry model8–10 that includes permafrost soil organic carbon dynamics3 leads to the upland methane sink doubling (~5.5 Tg CH4 yr−1) north of 50 °N in simulations from 2000–2016. The increase is equivalent to at least half of the difference in net methane emissions estimated between process-based models and observation-based inversions11,12, and the revised estimates better match site-level and regional observations5,7,13–15. The new model projects doubled wetland methane emissions between 2017–2100 due to more accessible permafrost carbon16–18. However, most of the increase in wetland emissions is offset by a concordant increase in the upland sink, leading to only an 18% increase in net methane emission (from 29 to 35 Tg CH4 yr−1). The projected net methane emissions may decrease further due to different physiological responses between HAMs and methanogens in response to increasing temperature19,20. Models overestimate Arctic methane emissions compared to observations. Incorporating microbial dynamics into biogeochemistry models helps reconcile this discrepancy; high-affinity methanotrophs are an important part of the Arctic methane budget and double previous estimates of methane sinks.

Climatic extreme events are expected to occur more frequently and potentially be stronger in the future, increasing the likelihood of unprecedented climate extremes (UCEs), or record-breaking events such as prolonged droughts, to occur. To prepare for UCEs and their impacts, we need to develop a better understanding of terrestrial ecosystem responses to events such as extreme drought. We know that intense, extreme droughts can substantially affect ecosystem stability and carbon cycling through increased plant mortality and delaying ecosystem recovery. Our ability to predict such effects is limited due to the lack of experiments focusing on climatic excursions beyond the range of historical experience.We explore the response of forest ecosystems to UCEs using two dynamic vegetation demographic models (VDMs), ED2 and LPJ-GUESS, in which the abundances of different plant functional types, as well as tree size- and age-class structure, are emergent properties of resource competition. We investigate the hypothesis that ecosystem responses to UCEs (e.g., unprecedented droughts) cannot be extrapolated from ecosystem responses to milder extremes, as a result of non-linear ecosystem responses (e.g. due to plant plasticity, functional diversity, and trait combinations). We evaluate each model’s mechanisms and state variables prior, during, and after a continuum of drought intensities ultimately reaching very extreme drought scenarios (i.e., 0% to 100% reduction in precipitation for drought durations of 1-year, 2-year, and 4-year scenarios) at two dry forested sites: Palo Verde, Costa Rica (i.e. tropical) and EucFACE, Australia (i.e. temperate). Both models produce nonlinear responses to these UCEs. Due to differences in model structure and process representation, the model’s sensitivity of biomass loss diverged based on either duration or intensity of droughts, as well as different model responses at each site. Biomass losses in ED2 are sensitive to drought duration, while in LPJ-GUESS they are mainly driven by drought intensity. Elevated atmospheric CO2 concentrations alone did not buffer the ecosystems from carbon losses during UCEs in the majority of our simulations. Our findings highlight discrepancies in process formulations and uncertainties in models, notably related to availability in plant carbohydrate storage and the diversity of plant hydraulic schemes. This shows that different hypotheses of plant responses to UCEs exist in two similar models, reflecting knowledge gaps, which should be tested with gap-informed field experiments. This iterative modeling-experiment framework would help improve predictions of terrestrial ecosystem responses and climate feedbacks.

A major uncertainty in the land carbon cycle is whether symbiotic nitrogen fixation acts to enhance the tropical forest carbon sink. Nitrogen-fixing trees can supply vital quantities of the growth-limiting nutrient nitrogen, but the extent to which the resulting carbon–nitrogen feedback safeguards ecosystem carbon sequestration remains unclear. We combine (i) field observations from 112 plots spanning 300 years of succession in Panamanian tropical forests, and (ii) a new model that resolves nitrogen and light competition at the scale of individual trees. Fixation doubled carbon accumulation in early succession and enhanced total carbon in mature forests by ~10% (~12MgC ha−1) through two mechanisms: (i) a direct fixation effect on tree growth, and (ii) an indirect effect on the successional sequence of non-fixing trees. We estimate that including nitrogen-fixing trees in Neotropical reforestation projects could safeguard the sequestration of 6.7 Gt CO2 over the next 20 years. Our results highlight the connection between functional diversity of plant communities and the critical ecosystem service of carbon sequestration for mitigating climate change., The contribution of symbiotic dinitrogen fixation to the forest carbon sink could change throughout forest succession. Here the authors model nitrogen cycling and light competition between trees based on data from Panamanian forest plots, showing that fixation contributes substantially to the carbon sink in early successional stages.

There are two theories about how allocation of metabolic products occurs. The allometric biomass partitioning theory (APT) suggests that all plants follow common allometric scaling rules. The optimal partitioning theory (OPT) predicts that plants allocate more biomass to the organ capturing the most limiting resource. Whole-plant harvests of mature and juvenile tropical deciduous trees, evergreen trees, and lianas and model simulations were used to address the following knowledge gaps: (1) Do mature lianas comply with the APT scaling laws or do they invest less biomass in stems compared to trees? (2) Do juveniles follow the same allocation patterns as mature individuals? (3) Is either leaf phenology or life form a predictor of rooting depth? It was found that: (1) mature lianas followed the same allometric scaling laws as trees; (2) juveniles and mature individuals do not follow the same allocation patterns; and (3) mature lianas had shallowest coarse roots and evergreen trees had the deepest. It was demonstrated that: (1) mature lianas invested proportionally similar biomass to stems as trees and not less, as expected; (2) lianas were not deeper-rooted than trees as had been previously proposed; and (3) evergreen trees had the deepest roots, which is necessary to maintain canopy during simulated dry seasons.

The Ecosystem Demography model version 2.2 (ED-2.2) is a terrestrial biosphere model that simulates the biophysical, ecological, and biogeochemical dynamics of vertically and horizontally heterogeneous terrestrial ecosystems. In a companion paper (Longo et al., 2019a), we described how the model solves the energy, water, and carbon cycles, and verified the high degree of conservation of these properties in long-term simulations that include long-term (multi-decadal) vegetation dynamics. Here, we present a detailed assessment of the model's ability to represent multiple processes associated with the biophysical and biogeochemical cycles in Amazon forests. We use multiple measurements from eddy covariance towers, forest inventory plots, and regional remote-sensing products to assess the model's ability to represent biophysical, physiological, and ecological processes at multiple timescales, ranging from subdaily to century long. The ED-2.2 model accurately describes the vertical distribution of light, water fluxes, and the storage of water, energy, and carbon in the canopy air space, the regional distribution of biomass in tropical South America, and the variability of biomass as a function of environmental drivers. In addition, ED-2.2 qualitatively captures several emergent properties of the ecosystem found in observations, specifically observed relationships between aboveground biomass, mortality rates, and wood density; however, the slopes of these relationships were not accurately captured. We also identified several limitations, including the model's tendency to overestimate the magnitude and seasonality of heterotrophic respiration and to overestimate growth rates in a nutrient-poor tropical site. The evaluation presented here highlights the potential of incorporating structural and functional heterogeneity within biomes in Earth system models (ESMs) and to realistically represent their impacts on energy, water, and carbon cycles. We also identify several priorities for further model development.

Earth system models (ESMs) have been developed to represent the role of terrestrial ecosystems on the energy, water, and carbon cycles. However, many ESMs still lack representation of within-ecosystem heterogeneity and diversity. In this paper, we present the Ecosystem Demography model version 2.2 (ED-2.2). In ED-2.2, the biophysical and physiological processes account for the horizontal and vertical heterogeneity of the ecosystem: the energy, water, and carbon cycles are solved separately for a series of vegetation cohorts (groups of individual plants of similar size and plant functional type) distributed across a series of spatially implicit patches (representing collections of micro-environments that have a similar disturbance history). We define the equations that describe the energy, water, and carbon cycles in terms of total energy, water, and carbon, which simplifies the differential equations and guarantees excellent conservation of these quantities in long-term simulation (< 0.1 % error over 50 years). We also show examples of ED-2.2 simulation results at single sites and across tropical South America. These results demonstrate the model's ability to characterize the variability of ecosystem structure, composition, and functioning both at stand and continental scales. A detailed model evaluation was conducted and is presented in a companion paper (Longo et al., 2019a). Finally, we highlight some of the ongoing model developments designed to improve the model's accuracy and performance and to include processes hitherto not represented in the model.

Lianas, or woody vines, and trees dominate the canopy of tropical forests and comprise the majority of tropical aboveground carbon storage. These growth forms respond differently to contemporary variation in climate and resource availability, but their responses to future climate change are poorly understood because there are very few predictive ecosystem models representing lianas. We compile a database of liana functional traits (846 species) and use it to parameterize a mechanistic model of liana-tree competition. The substantial difference between liana and tree hydraulic conductivity represents a critical source of inter-growth form variation. Here, we show that lianas are many times more sensitive to drying atmospheric conditions than trees as a result of this trait difference. Further, we use our competition model and projections of tropical hydroclimate based on Representative Concentration Pathway 4.5 to show that lianas are more susceptible to reaching a hydraulic threshold for viability by 2100.

Leaf habit has been hypothesized to define a linkage between the slow-fast plant economic spectrum and the drought resistance-avoidance trade-off in tropical forests ('slow-safe vs fast-risky'). However, variation in hydraulic traits as a function of leaf habit has rarely been explored for a large number of species. We sampled leaf and branch functional traits of 97 tropical dry forest tree species from four sites to investigate whether patterns of trait variation varied consistently in relation to leaf habit along the 'slow-safe vs fast-risky' trade-off. Leaf habit explained from 0% to 43.69% of individual trait variation. We found that evergreen and semi-deciduous species differed in their location along the multivariate trait ordination when compared to deciduous species. While deciduous species showed consistent trait values, evergreen species trait values varied as a function of the site. Last, trait values varied in relation to the proportion of deciduous species in the plant community. We found that leaf habit describes the strategies that define drought avoidance and plant economics in tropical trees. However, leaf habit alone does not explain patterns of trait variation, which suggests quantifying site-specific or species-specific uncertainty in trait variation as the way forward.

Lianas, or woody vines, are abundant throughout forests worldwide, but are especially common in the tropics. Their presence can strongly suppress tree wood production, and presumably also reduce the strength of the tropical forest carbon sink. In intact neotropical forests, liana presence has been increasing over the past few decades, though the mechanisms remain under debate. Vexingly, lianas are not represented at all in current-day climate models. Better knowledge of liana morphology and allocation is required to unravel the mechanisms of below- and aboveground liana-tree competition in tropical forests. Such knowledge is also an essential step toward incorporating lianas into mechanistic forest dynamics models. To address these liana knowledge gaps, we have initiated a new project that integrates empirical and modeling work. Our objectives in this presentation are to compare observed liana allocation patterns to allocation patterns predicted by theory, and then to demonstrate how these results can be integrated into a numerical model.Empirical measurements are being carried out in tropical dry forests in Guanacaste, Costa Rica. These measurements will eventually include excavations of ~80 entire trees and lianas, which will enable measurements of belowground and aboveground biomass of co-occurring trees and lianas, coarse and fine root vertical distribution, and lateral root spread. Also being measured are liana traits (including several critical hydraulic traits), above- and belowground productivity, and species-level fine root productivity. The modeling work includes the incorporation of lianas into the TROLL model, which is a mechanistic, individual-based forest dynamics model. The model will simulate the unique features of lianas, accounting for their structural parasitism and their different allocation strategies and morphology compared to trees. The simulated trees and lianas will compete aboveground for light and belowground for water. Thus, the model will integrate above- and belowground processes and couple the carbon and water cycles. Traits measured as part of this project are being used to parameterize the model.Thus far, 33 mature, canopy-exposed individuals (18 trees and 15 lianas) have been harvested and analyzed. For both trees and lianas, biomass partitioning to roots, stems, and leaves were consistent with the predictions of allometric biomass partitioning theory. This result thwarted our initial expectation that lianas, with their narrow-diameter stems, would allocate proportionally less to stems than trees. We also found that vertical root profiles varied across life forms: lianas had the shallowest roots, evergreen trees had the deepest roots, and deciduous trees had intermediate rooting depths. The liana root systems also had notably broader lateral extents than the tree root systems. These results run contrary to previous work that reported that lianas were relatively deeply-rooted.Our empirical results have helped to motivate model development. Each of our modeled liana individuals is assigned a laterally-widespread root system that can potentially extend beneath many trees. The liana root system is then permitted to put up aboveground shoots that associate with trees within the footprint of the root system. Comparisons of simulated and observed above- and belowground productivity are currently being conducted to help evaluate model assumptions.

The mechanisms governing tree drought mortality and recovery remain a subject of inquiry and active debate given their role in the terrestrial carbon cycle and their concomitant impact on climate change. Counter-intuitively, many trees do not die during the drought itself. Indeed, observations globally have documented that trees often grow for several years after drought before mortality. A combination of meta-analysis and tree physiological models demonstrate that optimal carbon allocation after drought explains observed patterns of delayed tree mortality and provides a predictive recovery framework. Specifically, post-drought, trees attempt to repair water transport tissue and achieve positive carbon balance through regrowing drought-damaged xylem. Furthermore, the number of years of xylem regrowth required to recover function increases with tree size, explaining why drought mortality increases with size. These results indicate that tree resilience to drought-kill may increase in the future, provided that CO2 fertilisation facilitates more rapid xylem regrowth.

Leaf longevity (LL) varies more than 20-fold in tropical evergreen forests, but it remains unclear how to capture these variations using predictive models. Current theories of LL that are based on carbon optimisation principles are challenging to quantitatively assess because of uncertainty across species in the 'ageing rate:' the rate at which leaf photosynthetic capacity declines with age. Here, we present a meta-analysis of 49 species across temperate and tropical biomes, demonstrating that the ageing rate of photosynthetic capacity is positively correlated with the mass-based carboxylation rate of mature leaves. We assess an improved trait-driven carbon optimality model with in situLL data for 105 species in two Panamanian forests. We show that our model explains over 40% of the cross-species variation in LL under contrasting light environment. Collectively, our results reveal how variation in LL emerges from carbon optimisation constrained by both leaf structural traits and abiotic environment.

Deforestation in Amazonia has previously been linked to thermally driven precipitation increases. Satellite observations and model simulations now suggest a shift toward a dynamically driven hydroclimate, with enhanced rainfall seen downwind of deforested areas. More than 20% of the Amazon rainforest has been cleared in the past three decades1, triggering important hydroclimatic changes1,2,3,4,5,6. Small-scale (a few kilometres) deforestation in the 1980s has caused thermally triggered atmospheric circulations7 that increase regional cloudiness8,9,10 and precipitation frequency8. However, these circulations are predicted to diminish as deforestation increases11,12,13. Here we use multi-decadal satellite records14,15 and numerical model simulations to show a regime shift in the regional hydroclimate accompanying increasing deforestation in Rondonia, Brazil. Compared with the 1980s, present-day deforested areas in downwind western Rondonia are found to be wetter than upwind eastern deforested areas during the local dry season. The resultant precipitation change in the two regions is approximately ±25% of the deforested area mean. Meso-resolution simulations robustly reproduce this transition when forced with increasing deforestation alone, showing that large-scale climate variability plays a negligible role16. Furthermore, deforestation-induced surface roughness reduction is found to play an essential role in the present-day dry-season hydroclimate. Our study illustrates the strong scale sensitivity of the climatic response to Amazonian deforestation and suggests that deforestation is sufficiently advanced to have caused a shift from a thermally to a dynamically driven hydroclimatic regime.

Increases in atmospheric carbon dioxide (CO2 ) concentrations are expected to lead to increases in the rate of tree biomass accumulation, at least temporarily. On the one hand, trees may simply grow faster under higher CO2 concentrations, preserving the allometric relations that prevailed under lower CO2 concentrations. Alternatively, the allometric relations themselves may change. In this study, the effects of elevated CO2 (eCO2 ) on tree biomass and allometric relations were jointly assessed. Over 100 trees, grown at Duke Forest, NC, USA, were harvested from eight plots. Half of the plots had been subjected to CO2 enrichment from 1996 to 2010. Several subplots had also been subjected to nitrogen fertilization from 2005 to 2010. Allometric equations were developed to predict tree height, stem volume, and aboveground biomass components for loblolly pine (Pinus taeda L.), the dominant tree species, and broad-leaved species. Using the same diameter-based allometric equations for biomass, it was estimated that plots with eCO2 contained 21% more aboveground biomass, consistent with previous studies. However, eCO2 significantly affected allometry, and these changes had an additional effect on biomass. In particular, P. taeda trees at a given diameter were observed to be taller under eCO2 than under ambient CO2 due to changes in both the allometric scaling exponent and intercept. Accounting for allometric change increased the treatment effect of eCO2 on aboveground biomass from a 21% to a 27% increase. No allometric changes for the nondominant broad-leaved species were identified, nor were allometric changes associated with nitrogen fertilization. For P. taeda, it is concluded that eCO2 affects allometries, and that knowledge of allometry changes is necessary to accurately compute biomass under eCO2 . Further observations are needed to determine whether this assessment holds for other taxa.

Drought-related tree mortality is now a widespread phenomenon predicted to increase in magnitude with climate change. However, the patterns of which species and trees are most vulnerable to drought, and the underlying mechanisms have remained elusive, in part due to the lack of relevant data and difficulty of predicting the location of catastrophic drought years in advance. We used long-term demographic records and extensive databases of functional traits and distribution patterns to understand the responses of 20 to 53 species to an extreme drought in a seasonally dry tropical forest in Costa Rica, which occurred during the 2015 El Niño Southern Oscillation event. Overall, species-specific mortality rates during the drought ranged from 0% to 34%, and varied little as a function of tree size. By contrast, hydraulic safety margins correlated well with probability of mortality among species, while morphological or leaf economics spectrum traits did not. This firmly suggests hydraulic traits as targets for future research.

Wind power, a rapidly growing alternative energy source, has been threatened by reductions in global average surface wind speed, which have been occurring over land since the 1980s, a phenomenon known as global terrestrial stilling. Here, we use wind data from in situ stations worldwide to show that the stilling reversed around 2010 and that global wind speeds over land have recovered. We illustrate that decadal-scale variations of near-surface wind are probably determined by internal decadal ocean–atmosphere oscillations, rather than by vegetation growth and/or urbanization as hypothesized previously. The strengthening has increased potential wind energy by 17 ± 2% for 2010 to 2017, boosting the US wind power capacity factor by ~2.5% and explains half the increase in the US wind capacity factor since 2010. In the longer term, the use of ocean–atmosphere oscillations to anticipate future wind speeds could allow optimization of turbines for expected speeds during their productive life spans., This study was supported by the Strategic Priority Research Programme of Chinese Academy of Sciences (grant no. XDA20060402), the start-up fund provided by Southern University of Science and Technology (no. 29/Y01296122) and Lamsam–Thailand Sustain Development (no. B0891). L.Z.X.L. was partially supported by the National Key Research and Development Programme of China (grant no. 2018YFC1507704). J.L. was supported by the National Natural Science Foundation of China (grant no. 41625001). P.C. acknowledges support from the European Research Council Synergy project (SyG-2013-610028 IMBALANCE-P) and the ANR CLAND Convergence Institute. C.A.M. was supported by grants no. VR-2017-03780 and RTI2018-095749-A-I00 (MCIU/AEI/FEDER, UE).

Previous empirical work has shown that feedbacks between fire severity, soil organic layer thickness, tree recruitment, and forest growth are important factors controlling carbon accumulation after fire disturbance. However, current boreal forest models inadequately simulate this feedback. We address this deficiency by updating the ED2 model to include a dynamic feedback between soil organic layer thickness, tree recruitment, and forest growth. The model is validated against observations spanning monthly to centennial time scales and ranging from Alaska to Quebec. We then quantify differences in forest development after fire disturbance resulting from changes in soil organic layer accumulation, temperature, nitrogen availability, and atmospheric CO2. First, we find that ED2 accurately reproduces observations when a dynamic soil organic layer is included. Second, simulations indicate that the presence of a thick soil organic layer after a mild fire disturbance decreases decomposition and productivity. The combination of the biological and physical effects increases or decreases total ecosystem carbon depending on local conditions. Third, with a 4°C temperature increase, some forests transition from undergoing succession to needleleaf forests to recruiting multiple cohorts of broadleaf trees, decreasing total ecosystem carbon by ∼40% after 300 years. However, the presence of a thick soil organic layer due to a persistently mild fire regime can prevent this transition and mediate carbon losses even under warmer temperatures. Fourth, nitrogen availability regulates successional dynamics; broadleaf species are less competitive with needleleaf trees under low nitrogen regimes. Fifth, the boreal forest shows additional short-term capacity for carbon sequestration as atmospheric CO2 increases. This article is protected by copyright. All rights reserved.

Recent field studies have documented a surprisingly strong and consistent methane sink in arctic mineral soils, thought to be due to high-affinity methanotrophy. However, the distinctive physiology of these methanotrophs is poorly represented in mechanistic methane models. We developed a new model, constrained by microcosm experiments, to simulate the activity of high-affinity methanotrophs. The model was tested against soil core-thawing experiments and field-based measurements of methane fluxes and was compared to conventional mechanistic methane models. Our simulations show that high-affinity methanotrophy can be an important component of the net methane flux from arctic mineral soils. Simulations without this process overestimate methane emissions. Furthermore, simulations of methane flux seasonality are improved by dynamic simulation of active microbial biomass. Because a large fraction of the Arctic is characterized by mineral soils, high-affinity methanotrophy will likely have a strong effect on its net methane flux.

The world's ocean and land ecosystems act as sinks for anthropogenic CO2, and over the last half century their combined sink strength grew steadily with increasing CO2 emissions. Recent analyses of the global carbon budget, however, have uncovered an abrupt, substantial ( ∼ 1 PgC yr−1) and sustained increase in the land sink in the late 1980s whose origin remains unclear. In the absence of this prominent shift in the land sink, increases in atmospheric CO2 concentrations since the late 1980s would have been ∼ 30 % larger than observed (or ∼ 12 ppm above current levels). Global data analyses are limited in regards to attributing causes to changes in the land sink because different regions are likely responding to different drivers. Here, we address this challenge by using terrestrial biosphere models constrained by observations to determine if there is independent evidence for the abrupt strengthening of the land sink. We find that net primary production significantly increased in the late 1980s (more so than heterotrophic respiration), consistent with the inferred increase in the global land sink, and that large-scale climate anomalies are responsible for this shift. We identify two key regions in which climatic constraints on plant growth have eased: northern Eurasia experienced warming, and northern Africa received increased precipitation. Whether these changes in continental climates are connected is uncertain, but North Atlantic climate variability is important. Our findings suggest that improved understanding of climate variability in the North Atlantic may be essential for more credible projections of the land sink under climate change.

Censuses of tropical forest plots reveal large variation in biomass and plant composition. This paper evaluates whether such variation can emerge solely from realistic variation in a set of commonly measured soil chemical and physical properties. Controlled simulations were performed using a mechanistic model that includes forest dynamics, microbe-mediated biogeochemistry, and competition for nitrogen and phosphorus. Observations from 18 forest inventory plots in Guanacaste, Costa Rica were used to determine realistic variation in soil properties. In simulations of secondary succession, the across-plot range in plant biomass reached 30% of the mean and was attributable primarily to nutrient limitation and secondarily to soil texture differences that affected water availability. The contributions of different plant functional types to total biomass varied widely across plots and depended on soil nutrient status. In Central America, soil-induced variation in plant biomass increased with mean annual precipitation because of changes in nutrient limitation. In Central America, large variation in plant biomass and ecosystem composition arises mechanistically from realistic variation in soil properties. The degree of biomass and compositional variation is climate sensitive. In general, model predictions can be improved through better representation of soil nutrient processes, including their spatial variation.

The contemporary Arctic carbon balance is uncertain, and the potential for a permafrost carbon feedback of anywhere from 50 to 200 petagrams of carbon (Schuur et al., 2015) compromises accurate 21st-century global climate system projections. The 42-year record of atmospheric CO2 measurements at Barrow, Alaska (71.29 N, 156.79 W), reveals significant trends in regional land-surface CO2 anomalies (ΔCO2), indicating long-term changes in seasonal carbon uptake and respiration. Using a carbon balance model constrained by ΔCO2, we find a 13.4% decrease in mean carbon residence time (50% confidence range = 9.2 to 17.6%) in North Slope tundra ecosystems during the past four decades, suggesting a transition toward a boreal carbon cycling regime. Temperature dependencies of respiration and carbon uptake suggest that increases in cold season Arctic labile carbon release will likely continue to exceed increases in net growing season carbon uptake under continued warming trends.