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Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.
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Sequías/estadística & datos numéricos , Ecosistema , Internacionalidad , Análisis Espacio-Temporal , Biodiversidad , Dióxido de Carbono/análisis , Secuestro de Carbono , Sequías/historia , Calentamiento Global , Historia del Siglo XX , Historia del Siglo XXI , Lluvia , Suelo/química , Temperatura , Factores de Tiempo , Clima Tropical , Incendios ForestalesRESUMEN
In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data-model integration requires investment in accessible, scalable, and transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundations of community cyberinfrastructure; data ingest; calibration of models to data; model-data benchmarking; and data assimilation and ecological forecasting. This community-driven approach is a key to meeting the pressing needs of science and society in the 21st century.
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Ecosistema , Modelos Teóricos , PredicciónRESUMEN
We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon-climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km2 for the RCP4.5 climate and between 6 and 16 million km2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbon varied between 66-Pg C (1015-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. This assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon-climate feedback.
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Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon-nitrogen interactions tend to be more realistic. Using observation-based estimates of global photosynthesis, we quantify the global BP of non-cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model-estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).
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Ecosistema , Árboles , Biomasa , Carbono , Ciclo del Carbono , Dióxido de Carbono , Secuestro de CarbonoRESUMEN
Between about 55.5 and 52 million years ago, Earth experienced a series of sudden and extreme global warming events (hyperthermals) superimposed on a long-term warming trend. The first and largest of these events, the Palaeocene-Eocene Thermal Maximum (PETM), is characterized by a massive input of carbon, ocean acidification and an increase in global temperature of about 5 °C within a few thousand years. Although various explanations for the PETM have been proposed, a satisfactory model that accounts for the source, magnitude and timing of carbon release at the PETM and successive hyperthermals remains elusive. Here we use a new astronomically calibrated cyclostratigraphic record from central Italy to show that the Early Eocene hyperthermals occurred during orbits with a combination of high eccentricity and high obliquity. Corresponding climate-ecosystem-soil simulations accounting for rising concentrations of background greenhouse gases and orbital forcing show that the magnitude and timing of the PETM and subsequent hyperthermals can be explained by the orbitally triggered decomposition of soil organic carbon in circum-Arctic and Antarctic terrestrial permafrost. This massive carbon reservoir had the potential to repeatedly release thousands of petagrams (10(15) grams) of carbon to the atmosphere-ocean system, once a long-term warming threshold had been reached just before the PETM. Replenishment of permafrost soil carbon stocks following peak warming probably contributed to the rapid recovery from each event, while providing a sensitive carbon reservoir for the next hyperthermal. As background temperatures continued to rise following the PETM, the areal extent of permafrost steadily declined, resulting in an incrementally smaller available carbon pool and smaller hyperthermals at each successive orbital forcing maximum. A mechanism linking Earth's orbital properties with release of soil carbon from permafrost provides a unifying model accounting for the salient features of the hyperthermals.
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Carbono/análisis , Congelación , Calentamiento Global/historia , Efecto Invernadero/historia , Suelo/química , Temperatura , Regiones Antárticas , Regiones Árticas , Atmósfera/química , Calibración , Ciclo del Carbono , Ecosistema , Retroalimentación , Historia Antigua , Italia , Modelos Teóricos , Agua de Mar/químicaRESUMEN
Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO2 at multidecadal and centennial timescales 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 multidecadal and multicentennial timescales 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.
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Dióxido de Carbono , Cambio Climático , Ecosistema , Bosques , Clima , América del Norte , ÁrbolesRESUMEN
Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land-atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO2) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century-long (1901-2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project and two observation-based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111 Pg C (1 Pg = 1015 g) with a median value of 1158 Pg C in 2010. The models estimate a broad range of Rh from 35 to 69 Pg C yr-1 with a median value of 51 Pg C yr-1 during 2001-2010. The largest uncertainty in SOC stocks exists in the 40-65°N latitude whereas the largest cross-model divergence in Rh are in the tropics. The modeled SOC change during 1901-2010 ranges from -70 Pg C to 86 Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble-estimated mean residence time of SOC shows a reduction of 3.4 years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO2 and nitrogen deposition over intact ecosystems increased SOC stocks-even though the responses varied significantly among models. Model representations of temperature and moisture sensitivity, nutrient limitation, and land use partially explain the divergent estimates of global SOC stocks and soil C fluxes in this study. In addition, a major source of systematic error in model estimations relates to nonmodeled SOC storage in wetlands and peatlands, as well as to old C storage in deep soil layers.
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Obtaining an accurate assessment of a treatment system's antimicrobial efficacy in recreational water is difficult given the large scale and high flow rates of the water systems. A laboratory test system was designed to mimic the water conditions and potential microbial contaminants found in swimming pools. This system was utilized to evaluate the performance of an in situ ozone disinfection device against four microorganisms: Cryptosporidium parvum, bacteriophage MS2, Enterococcus faecium, and Pseudomonas aeruginosa. The sampling regimen evaluated the antimicrobial effectiveness in a single pass fashion, with samples being evaluated initially after exposure to the ozone unit, as well as at points downstream from the device. Based on the flow dynamics and log reductions, cycle threshold (Ct) values were calculated. The observed organism log reductions were as follows: >6.7 log for E. faecium and P. aeruginosa; >5.9 log for bacteriophage MS2; and between 2.7 and 4.1 log for C. parvum. The efficacy results indicate that the test system effectively functions as a secondary disinfection system as defined by the Centers for Disease Control and Prevention's Model Aquatic Health Code.
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Ozono/química , Recreación , Microbiología del Agua , Purificación del Agua/métodos , Técnicas Bacteriológicas , Playas , Cryptosporidium parvum/efectos de los fármacos , Enterococcus faecium/efectos de los fármacos , Humanos , Levivirus/efectos de los fármacos , Pseudomonas aeruginosa/efectos de los fármacos , PiscinasRESUMEN
Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901-2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.
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In addition to spaceborne Interferometric Synthetic Aperture Radar (InSAR), airborne data such as those obtained by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) have also been utilized to measure surface subsidence in permafrost areas in recent years. Motivated by the integration of multiplatform InSAR data, we generated two UAVSAR interferograms and one Advanced Land Observing Satellite (ALOS)-2 L-band interferogram over a permafrost area near Yellowknife, Canada, then compared the surface subsidence in the thaw seasons of 2017. The correlation coefficient and the root mean square error (RMSE) of subsidence difference are calculated to compare the airborne and spaceborne InSAR measurements. The results demonstrate that the two UAVSAR measurements are self-consistent, with the correlation coefficient between independent airborne measurements â¼0.7. While the RMSE of the difference between surface subsidence measured by UAVSAR and ALOS2 is â¼2.0 cm, and the correlation coefficients are less than 0.41, that is, a noticeable deviation exists between the UAVSAR and ALOS2 results possibly due to different spatial resolution and the calibration processing of airborne and spaceborne InSAR data. In addition, both UAVSAR and ALOS2 interferograms show larger surface subsidence within taiga needleleaf forest regions than in regions of other biome types (including needleleaf forest, shrubland, and grassland). The results demonstrate that a scheme for the elimination of systematic differences needs to be developed before merging multisource InSAR results. This intercomparison will provide valuable insights for narrowing the gap between radar-based measurements and planning the integration of airborne and satellite InSAR measurements in permafrost environments.
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Interferometric synthetic aperture radar (InSAR) has been used to quantify a range of surface and near surface physical properties in permafrost landscapes. Most previous InSAR studies have utilized spaceborne InSAR platforms, but InSAR datasets over permafrost landscapes collected from airborne platforms have been steadily growing in recent years. Most existing algorithms dedicated toward retrieval of permafrost physical properties were originally developed for spaceborne InSAR platforms. In this study, which is the first in a two part series, we introduce a series of calibration techniques developed to apply a novel joint retrieval algorithm for permafrost active layer thickness retrieval to an airborne InSAR dataset acquired in 2017 by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar over Alaska and Western Canada. We demonstrate how InSAR measurement uncertainties are mitigated by these calibration methods and quantify remaining measurement uncertainties with a novel method of modeling interferometric phase uncertainty using a Gaussian mixture model. Finally, we discuss the impact of native SAR resolution on InSAR measurements, the limitation of using few interferograms per retrieval, and the implications of our findings for cross-comparison of airborne and spaceborne InSAR datasets acquired over Arctic regions underlain by permafrost.
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Mercury (Hg) is a naturally occurring element that bonds with organic matter and, when converted to methylmercury, is a potent neurotoxicant. Here we estimate potential future releases of Hg from thawing permafrost for low and high greenhouse gas emissions scenarios using a mechanistic model. By 2200, the high emissions scenario shows annual permafrost Hg emissions to the atmosphere comparable to current global anthropogenic emissions. By 2100, simulated Hg concentrations in the Yukon River increase by 14% for the low emissions scenario, but double for the high emissions scenario. Fish Hg concentrations do not exceed United States Environmental Protection Agency guidelines for the low emissions scenario by 2300, but for the high emissions scenario, fish in the Yukon River exceed EPA guidelines by 2050. Our results indicate minimal impacts to Hg concentrations in water and fish for the low emissions scenario and high impacts for the high emissions scenario.
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An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Terrestrial vegetation removes CO2 from the atmosphere; an important climate regulation service that slows global warming. This 119 Pg C per annum transfer of CO2 into plants-gross primary productivity (GPP)-is the largest land carbon flux globally. While understanding past and anticipated future GPP changes is necessary to support carbon management, the factors driving long-term changes in GPP are largely unknown. Here we show that 1901 to 2010 changes in GPP have been dominated by anthropogenic activity. Our dual constraint attribution approach provides three insights into the spatiotemporal patterns of GPP change. First, anthropogenic controls on GPP change have increased from 57% (1901 decade) to 94% (2001 decade) of the vegetated land surface. Second, CO2 fertilization and nitro gen deposition are the most important drivers of change, 19.8 and 11.1 Pg C per annum (2001 decade) respectively, especially in the tropics and industrialized areas since the 1970's. Third, changes in climate have functioned as fertilization to enhance GPP (1.4 Pg C per annum in the 2001 decade). These findings suggest that, from a land carbon balance perspective, the Anthropocene began over 100 years ago and that global change drivers have allowed GPP uptake to keep pace with anthropogenic emissions.
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Arctic feedbacks accelerate climate change through carbon releases from thawing permafrost and higher solar absorption from reductions in the surface albedo, following loss of sea ice and land snow. Here, we include dynamic emulators of complex physical models in the integrated assessment model PAGE-ICE to explore nonlinear transitions in the Arctic feedbacks and their subsequent impacts on the global climate and economy under the Paris Agreement scenarios. The permafrost feedback is increasingly positive in warmer climates, while the albedo feedback weakens as the ice and snow melt. Combined, these two factors lead to significant increases in the mean discounted economic effect of climate change: +4.0% ($24.8 trillion) under the 1.5 °C scenario, +5.5% ($33.8 trillion) under the 2 °C scenario, and +4.8% ($66.9 trillion) under mitigation levels consistent with the current national pledges. Considering the nonlinear Arctic feedbacks makes the 1.5 °C target marginally more economically attractive than the 2 °C target, although both are statistically equivalent.
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The ability to accurately predict ecosystem drought response and recovery is necessary to produce reliable forecasts of land carbon uptake and future climate. Using a suite of models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we assessed modeled net primary productivity (NPP) response to, and recovery from, drought events against a benchmark derived from tree ring observations between 1948 and 2008 across forested regions of the US and Europe. We find short lag times (0-6 months) between climate anomalies and modeled NPP response. Although models accurately simulate the direction of drought legacy effects (i.e. NPP decreases), projected effects are approximately four times shorter and four times weaker than observations suggest. This discrepancy between observed and simulated vegetation recovery from drought reveals a potential critical model deficiency. Since productivity is a crucial component of the land carbon balance, models that underestimate drought recovery time could overestimate predictions of future land carbon sink strength and, consequently, underestimate forecasts of atmospheric CO2.
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Dióxido de Carbono/metabolismo , Sequías , Modelos Teóricos , Árboles/crecimiento & desarrollo , Ciclo del Carbono , Cambio ClimáticoRESUMEN
The annual peak growth of vegetation is critical in characterizing the capacity of terrestrial ecosystem productivity and shaping the seasonality of atmospheric CO2 concentrations. The recent greening of global lands suggests an increasing trend of terrestrial vegetation growth, but whether or not the peak growth has been globally enhanced still remains unclear. Here, we use two global datasets of gross primary productivity (GPP) and a satellite-derived Normalized Difference Vegetation Index (NDVI) to characterize recent changes in annual peak vegetation growth (that is, GPPmax and NDVImax). We demonstrate that the peak in the growth of global vegetation has been linearly increasing during the past three decades. About 65% of the NDVImax variation is evenly explained by expanding croplands (21%), rising CO2 (22%) and intensifying nitrogen deposition (22%). The contribution of expanding croplands to the peak growth trend is substantiated by measurements from eddy-flux towers, sun-induced chlorophyll fluorescence and a global database of plant traits, all of which demonstrate that croplands have a higher photosynthetic capacity than other vegetation types. The large contribution of CO2 is also supported by a meta-analysis of 466 manipulative experiments and 15 terrestrial biosphere models. Furthermore, we show that the contribution of GPPmax to the change in annual GPP is less in the tropics than in other regions. These multiple lines of evidence reveal an increasing trend in the peak growth of global vegetation. The findings highlight the important roles of agricultural intensification and atmospheric changes in reshaping the seasonality of global vegetation growth.
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Ecosistema , Fotosíntesis , Desarrollo de la Planta , Tecnología de Sensores Remotos , Estaciones del AñoRESUMEN
Severe droughts in the Northern Hemisphere cause widespread decline of agricultural yield, reduction of forest carbon uptake, and increased CO2 growth rates in the atmosphere. Plants respond to droughts by partially closing their stomata to limit their evaporative water loss, at the expense of carbon uptake by photosynthesis. This trade-off maximizes their water-use efficiency, as measured for many individual plants under laboratory conditions and field experiments. Here we analyze the 13C/12C stable isotope ratio in atmospheric CO2 (reported as δ13C) to provide new observational evidence of the impact of droughts on the water-use efficiency across areas of millions of km2 and spanning one decade of recent climate variability. We find strong and spatially coherent increases in water-use efficiency along with widespread reductions of net carbon uptake over the Northern Hemisphere during severe droughts that affected Europe, Russia, and the United States in 2001-2011. The impact of those droughts on water-use efficiency and carbon uptake by vegetation is substantially larger than simulated by the land-surface schemes of six state-of-the-art climate models. This suggests that drought induced carbon-climate feedbacks may be too small in these models and improvements to their vegetation dynamics using stable isotope observations can help to improve their drought response.
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Mitochondrial DNA polymerase (pol gamma) is the sole DNA polymerase responsible for replication and repair of animal mitochondrial DNA. Here, we address the molecular mechanism by which the human holoenzyme achieves high processivity in nucleotide polymerization. We have determined the crystal structure of human pol gamma-beta, the accessory subunit that binds with high affinity to the catalytic core, pol gamma-alpha, to stimulate its activity and enhance holoenzyme processivity. We find that human pol gamma-beta shares a high level of structural similarity to class IIa aminoacyl tRNA synthetases, and forms a dimer in the crystal. A human pol gamma/DNA complex model was developed using the structures of the pol gamma-beta dimer and the bacteriophage T7 DNA polymerase ternary complex, which suggests multiple regions of subunit interaction between pol gamma-beta and the human catalytic core that allow it to encircle the newly synthesized double-stranded DNA, and thereby enhance DNA binding affinity and holoenzyme processivity. Biochemical properties of a novel set of human pol gamma-beta mutants are explained by and test the model, and elucidate the role of the accessory subunit as a novel type of processivity factor in stimulating pol gamma activity and in enhancing processivity.
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ADN Polimerasa Dirigida por ADN/química , ADN Polimerasa Dirigida por ADN/metabolismo , ADN/biosíntesis , Secuencia de Aminoácidos , Sustitución de Aminoácidos , Secuencia de Bases , Dominio Catalítico/genética , Cristalografía por Rayos X , ADN/química , ADN/genética , ADN Polimerasa beta/química , ADN Polimerasa beta/genética , ADN Polimerasa beta/metabolismo , ADN Polimerasa gamma , ADN Polimerasa Dirigida por ADN/genética , Dimerización , Humanos , Técnicas In Vitro , Sustancias Macromoleculares , Mitocondrias/enzimología , Modelos Moleculares , Datos de Secuencia Molecular , Mutagénesis Sitio-Dirigida , Estructura Cuaternaria de Proteína , Subunidades de ProteínaRESUMEN
A series of combretastatin A-4 analogs derived from the ATP competitive, VEGF receptor tyrosine kinase inhibitor, SU5416 were synthesized. The cytotoxic effects of the analogs were evaluated against PC-3 and MDA-MB-231 cancer cell lines, as well as their abilities to inhibit tubulin polymerization. Results are compared to those of compound 1, our lead compound previously reported.