Browsing by Author "Poulter, Benjamin"

Now showing 1 - 20 of 30

1982–2010 Trends of Light Use Efficiency and Inherent Water Use Efficiency in African vegetation: Sensitivity to Climate and Atmospheric CO2 Concentrations
(MDPI, 2014) Traore, Abdoul Khadre; Ciais, Philippe; Vuichard, Nicolas; McBean, Natasha; Dardel, Cecile; Poulter, Benjamin; Piao, Shilong; Fisher, Joshua; Viovy, Nicolas; Jung, Martin; Myneni, Ranga B.
Light and water use by vegetation at the ecosystem level, are key components for understanding the carbon and water cycles particularly in regions with high climate variability and dry climates such as Africa. The objective of this study is to examine recent trends over the last 30 years in Light Use Efficiency (LUE) and inherent Water Use Efficiency (iWUE*) for the major biomes of Africa, including their sensitivities to climate and CO2. LUE and iWUE* trends are analyzed using a combination of NOAA-AVHRR NDVI3g and fAPAR3g, and a data-driven model of monthly evapotranspiration and Gross Primary Productivity (based on flux tower measurements and remote sensing fAPAR, yet with no flux tower data in Africa) and the ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) process-based land surface model driven by variable CO2 and two different gridded climate fields. The iWUE* data product increases by 10%–20% per decade during the 1982–2010 period over the northern savannas (due to positive trend of vegetation productivity) and the central African forest (due to positive trend of vapor pressure deficit). In contrast to the iWUE*, the LUE trends are not statistically significant. The process-based model simulations only show a positive linear trend in iWUE* and LUE over the central African forest. Additionally, factorial model simulations were conducted to attribute trends in iWUE and LUE to climate change and rising CO2 concentrations. We found that the increase of atmospheric CO2 by 52.8 ppm during the period of study explains 30%–50% of the increase in iWUE* and >90% of the LUE trend over the central African forest. The modeled iWUE* trend exhibits a high sensitivity to the climate forcing and environmental conditions, whereas the LUE trend has a smaller sensitivity to the selected climate forcing.
Aboveground and belowground responses to cyanobacterial biofertilizer supplement in a semi-arid, perennial bioenergy cropping system
(Wiley, 2021-08) Goemann, Hannah M.; Gay, Justin D.; Mueller, Rebecca C.; Brookshire, E. N. Jack; Miller, Perry; Poulter, Benjamin; Peyton, Brent M.
The need for sustainable agricultural practices to meet the food, feed, and fuel demands of a growing global population while reducing detrimental environmental impacts has driven research in multi‐faceted approaches to agricultural sustainability. Perennial cropping systems and microbial biofertilizer supplements are two emerging strategies to increase agricultural sustainability that are studied in tandem for the first time in this study. During the establishment phase of a perennial switchgrass stand in SW Montana, USA, we supplemented synthetic fertilization with a nitrogen‐fixing cyanobacterial biofertilizer (CBF) and were able to maintain aboveground crop productivity in comparison to a synthetic only (urea) fertilizer treatment. Soil chemical analysis conducted at the end of the growing season revealed that late‐season nitrogen availability in CBF‐supplemented field plots increased relative to urea‐only plots. High‐throughput sequencing of bacterial/archaeal and fungal communities suggested fine‐scale responses of the microbial community and sensitivity to fertilization among arbuscular mycorrhizal fungi, Planctomycetes, Proteobacteria, and Actinobacteria. Given their critical role in plant productivity and soil nutrient cycling, soil microbiome monitoring is vital to understand the impacts of implementation of alternative agricultural practices on soil health.
Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass
(2017-07) Joetzjer, Emilie; Pillet, Michiel; Ciais, Philippe; Barbier, N.; Chave, Jerome; Schlund, M.; Maignan, F.; Barichivich, Jonathan; Luyssaert, Sebastiaan; Hérault, Bruno; Poncet, F.; Poulter, Benjamin
Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.
Bioenergy with Carbon Capture and Storage (BECCS) in the Upper Missouri River Basin
(Montana State University, 2017-04) Bauer, Brad; Poulter, Benjamin; Royem, Alisa; Stoy, Paul C.; Taylor, Suzi
A team of scientists from Montana State University (MSU), the University of Wyoming (UW) and the University of South Dakota (USD) has received funding from the National Science Foundation that is bringing $6 million to these states. The team will use computer models and field experiments to study what might happen over the next 100 years if we adopt a new energy system called BECCS. The project’s study region is the Upper River Missouri Basin, but the findings could help all regions better understand the impacts of BECCS on communities and citizens, agriculture and ecosystem services.
Carbon Implications of Converting Cropland to Bioenergy Crops or Forest for Climate Mitigation: a Global Assessment
(2015-02) Albanito, Fabrizio; Beringer, Tim; Corstanje, Ronald; Poulter, Benjamin; Stephenson, Anna; Zawadzka, Joanna; Smith, Pete
The potential for climate change mitigation by bioenergy crops and terrestrial carbon sinks has been the object of intensive research in the past decade. There has been much debate about whether energy crops used to offset fossil fuel use, or carbon sequestration in forests, would provide the best climate mitigation benefit. Most current food cropland is unlikely to be used for bioenergy, but in many regions of the world, a proportion of cropland is being abandoned, particularly marginal croplands, and some of this land is now being used for bioenergy. In this study, we assess the consequences of land-use change on cropland. We first identify areas where cropland is so productive that it may never be converted and assess the potential of the remaining cropland to mitigate climate change by identifying which alternative land use provides the best climate benefit: C4 grass bioenergy crops, coppiced woody energy crops or allowing forest regrowth to create a carbon sink. We do not present this as a scenario of land-use change – we simply assess the best option in any given global location should a land-use change occur. To do this, we use global biomass potential studies based on food crop productivity, forest inventory data and dynamic global vegetation models to provide, for the first time, a global comparison of the climate change implications of either deploying bioenergy crops or allowing forest regeneration on current crop land, over a period of 20 years starting in the nominal year of 2000 ad. Globally, the extent of cropland on which conversion to energy crops or forest would result in a net carbon loss, and therefore likely always to remain as cropland, was estimated to be about 420.1 Mha, or 35.6% of the total cropland in Africa, 40.3% in Asia and Russia Federation, 30.8% in Europe-25, 48.4% in North America, 13.7% in South America and 58.5% in Oceania. Fast growing C4 grasses such as Miscanthus and switch-grass cultivars are the bioenergy feedstock with the highest climate mitigation potential. Fast growing C4 grasses such as Miscanthus and switch-grass cultivars provide the best climate mitigation option on ≈485 Mha of cropland worldwide with ~42% of this land characterized by a terrain slope equal or above 20%. If that land-use change did occur, it would displace ≈58.1 Pg fossil fuel C equivalent (Ceq oil). Woody energy crops such as poplar, willow and Eucalyptus species would be the best option on only 2.4% (≈26.3 Mha) of current cropland, and if this land-use change occurred, it would displace ≈0.9 Pg Ceq oil. Allowing cropland to revert to forest would be the best climate mitigation option on ≈17% of current cropland (≈184.5 Mha), and if this land-use change occurred, it would sequester ≈5.8 Pg C in biomass in the 20-year-old forest and ≈2.7 Pg C in soil. This study is spatially explicit, so also serves to identify the regional differences in the efficacy of different climate mitigation options, informing policymakers developing regionally or nationally appropriate mitigation actions.
Challenges in developing a computationally efficient plant physiological height-class-structured forest model
(Elsevier BV, 2014-09) Poulter, Benjamin; Scherstjanoi, M.; Kaplan, J.O.; Lischke, H.
Ongoing and future climate change may be of sufficient magnitude to significantly impact global forest ecosystems. In order to anticipate the potential range of changes to forests in the future and to better understand the development and state of forest ecosystems at present, a variety of forest ecosystem models of varying complexity have been developed over the past 40 years. While most of these models focus on representing either forest demographics including age and height structure, or forest biogeochemistry including plant physiology and ecosystem carbon cycling, it is increasingly seen as crucial that forest ecosystem models include equally good representations of both. However, only few models currently include detailed representations of both biogeochemistry and demographics, and those mostly have high computational demands. Here, we present TreeM-LPJ, a first step towards a new, computationally efficient forest dynamics model. We combine the height-class scheme of the forest landscape model TreeMig with the biogeochemistry of the dynamic global vegetation model LPJ-GUESS. The resulting model is able to simulate forest growth by considering vertical spatial variability without stochastic functions, considerably reducing computational demand. Discretization errors are kept small by using a numerical algorithm that extrapolates growth success in height, and thereby dynamically updates the state variables of the trees in the different height classes. We demonstrate TreeM-LPJ in an application on a transect in the central Swiss Alps where we show results from the new model compare favorably with the more complex LPJ-GUESS. TreeM-LPJ provides a combination of biological detail and computational efficiency that can serve as a useful basis for large-scale vegetation modeling.
Change in terrestrial ecosystem water-use efficiency over the last three decades
(2015-03) Huang, Mengtian; Piao, Shilong; Sun, Yan; Ciais, Philippe; Cheng, Lei; Mao, Jiafu; Poulter, Benjamin
Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations and process-oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C mâˆ’2 mmâˆ’1 yrâˆ’1 under the single effect of rising CO2 (â€˜CO2â€™), climate change (â€˜CLIMâ€™) and nitrogen deposition (â€˜NDEPâ€™), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (âˆ’0.0005 g C mâˆ’2 mmâˆ’1 yrâˆ’1), which differs from process-model (0.0064 g C mâˆ’2 mmâˆ’1 yrâˆ’1) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Change in water-use efficiency defined from transpiration-based WUEt (GPP/TR) and inherent water-use efficiency (IWUEt, GPPÃ—VPD/TR) in response to rising CO2, climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbonâ€“water interactions over terrestrial ecosystems under global change.
Characterizing the performance of ecosystem models across time scales: A spectral analysis of the North American Carbon Program site‐level synthesis
(2011-12-20) Dietze, Michael C.; Vargas, Rodrigo; Richardson, Andrew D.; Stoy, Paul C.; Barr, Alan G.; Anderson, Ryan S.; M. Altaf Arain, M. Altaf; Baker, Ian T.; Blac, T. Andrew; Chen, Jing M.; Ciais, Philippe; Flanagan, Lawrence B.; Gough, Christopher M.; Grant, Robert F.; Hollinger, David Y.; Izaurralde, R. Cesar; Kucharik, Christopher J.; Lafleur, Peter; Liu, Shuguang; Lokupitiya, Erandathie; Luo, Yiqi; Munger, J. William; Peng, Changhui; Poulter, Benjamin; Price, David T.; Ricciuto, Daniel M.; Riley, William J.; Sahoo, Alok Kumar; Schaefer, Kevin; Suyker, Andrew E.; Tain, Hanqin; Tonitto, Christina; Verbeeck, Hans; Verma, Shashi B.; Weifeng, Wang; Weng, Ensheng
Ecosystem models are important tools for diagnosing the carbon cycle and projecting its behavior across space and time. Despite the fact that ecosystems respond to drivers at multiple time scales, most assessments of model performance do not discriminate different time scales. Spectral methods, such as wavelet analyses, present an alternative approach that enables the identification of the dominant time scales contributing to model performance in the frequency domain. In this study we used wavelet analyses to synthesize the performance of 21 ecosystem models at 9 eddy covariance towers as part of the North American Carbon Program's site-level intercomparison. This study expands upon previous single-site and single-model analyses to determine what patterns of model error are consistent across a diverse range of models and sites. To assess the significance of model error at different time scales, a novel Monte Carlo approach was developed to incorporate flux observation error. Failing to account for observation error leads to a misidentification of the time scales that dominate model error. These analyses show that model error (1) is largest at the annual and 20–120 day scales, (2) has a clear peak at the diurnal scale, and (3) shows large variability among models in the 2–20 day scales. Errors at the annual scale were consistent across time, diurnal errors were predominantly during the growing season, and intermediate-scale errors were largely event driven. Breaking spectra into discrete temporal bands revealed a significant model-by-band effect but also a nonsignificant model-by-site effect, which together suggest that individual models show consistency in their error patterns. Differences among models were related to model time step, soil hydrology, and the representation of photosynthesis and phenology but not the soil carbon or nitrogen cycles. These factors had the greatest impact on diurnal errors, were less important at annual scales, and had the least impact at intermediate time scales.
Climate change and European forests: What do we know, what are the uncertainties, and what are the implications for forest management?
(Elsevier BV, 2014-12) Lindner, Marcus; Fitzgerald, Joanne B.; Zimmermann, Niklaus E.; Reyer, Christopher; Delzon, Sylvain; van der Maaten, Ernst; Schelhaas, Mart-Jan; Lasch, Petra; Eggers, Jeanette; van der Maaten-Theunissen, Marieke; Suckow, Felicitas; Psomas, Achilleas; Poulter, Benjamin; Hanewinkel, Marc
The knowledge about potential climate change impacts on forests is continuously expanding and some changes in growth, drought induced mortality and species distribution have been observed. However despite a signiﬁcant body of research, a knowledge and communication gap exists between scientists and non-scientists as to how climate change impact scenarios can be interpreted and what they imply for European forests. It is still challenging to advise forest decision makers on how best to plan for climate change as many uncertainties and unknowns remain and it is difﬁcult to communicate these to practitioners and other decision makers while retaining emphasis on the importance of planning for adaptation. In this paper, recent developments in climate change observations and projections, observed and projected impacts on European forests and the associated uncertainties are reviewed and synthesised with a view to understanding the implications for forest management. Current impact assessments with simulation models contain several simpliﬁcations, which explain the discrepancy between results of many simulation studies and the rapidly increasing body of evidence about already observed changes in forest productivity and species distribution. In simulation models uncertainties tend to cascade onto one another; from estimating what future societies will be like and general circulation models (GCMs) at the global level, down to forest models and forest management at the local level. Individual climate change impact studies should not be uncritically used for decision-making without reﬂection on possible shortcomings in system understanding, model accuracy and other assumptions made. It is important for decision makers in forest management to realise that they have to take long-lasting management decisions while uncertainty about climate change impacts are still large. We discuss how to communicate about uncertainty e which is imperative for decision making e without diluting the overall message. Considering the range of possible trends and uncertainties in adaptive forest management requires expert knowledge and enhanced efforts for providing science-based decision support.
Climate mitigation potential and soil microbial response of cyanobacteria‐fertilized bioenergy crops in a cool semi‐arid cropland
(Wiley, 2022-10) Gay, Justin D.; Goemann, Hannah M.; Currey, Bryce; Stoy, Paul C.; Christiansen, Jesper Riis; Miller, Perry R.; Poulter, Benjamin; Peyton, Brent M.; Brookshire, E. N. Jack
Bioenergy carbon capture and storage (BECCS) systems can serve as decarbonization pathways for climate mitigation. Perennial grasses are a promising second-generation lignocellulosic bioenergy feedstock for BECCS expansion, but optimizing their sustainability, productivity, and climate mitigation potential requires an evaluation of how nitrogen (N) fertilizer strategies interact with greenhouse gas (GHG) and soil organic carbon (SOC) dynamics. Furthermore, crop and fertilizer choice can affect the soil microbiome which is critical to soil organic matter turnover, nutrient cycling, and sustaining crop productivity but these feedbacks are poorly understood due to the paucity of data from certain agroecosystems. Here, we examine the climate mitigation potential and soil microbiome response to establishing two functionally different perennial grasses, switchgrass (Panicum virgatum, C4) and tall wheatgrass (Thinopyrum ponticum, C3), in a cool semi-arid agroecosystem under two fertilizer applications, a novel cyanobacterial biofertilizer (CBF) and urea. We find that in contrast to the C4 grass, the C3 grass achieved 98% greater productivity and had a higher N use efficiency when fertilized. For both crops, the CBF produced the same biomass enhancement as urea. Non-CO2 GHG fluxes across all treatments were low and we observed a 3-year net loss of SOC under the C4 crop and a net gain under the C3 crop at a 0–30 cm soil depth regardless of fertilization. Finally, we detected crop-specific changes in the soil microbiome, including an increased relative abundance of arbuscular mycorrhizal fungi under the C3, and potentially pathogenic fungi in the C4 grass. Taken together, these findings highlight the potential of CBF-fertilized C3 crops as a second-generation bioenergy feedstock in semi-arid regions as a part of a climate mitigation strategy.
Comparing tree-ring and permanent plot estimates of aboveground net primary production in three eastern US forests
(2016-09) Dye, Alex; Plotkin, Audrey Barker; Bishop, Daniel; Pederson, Neil; Poulter, Benjamin; Hessl, Amy
Forests account for a large portion of sequestered carbon, much of which is stored as wood in trees. The rate of carbon accumulation in aboveground plant material, or aboveground net primary productivity (aNPP), quantifies annual to decadal variations in forest carbon sequestration. Permanent plots are often used to estimate aNPP but are usually not annually resolved and take many years to develop a long data set. Tree rings are a unique and infrequently used source for measuring aNPP, and benefit from fine spatial (individual trees) and temporal (annual) resolution. Because of this precision, tree rings are complementary to permanent plots and the suite of tools used to study forest productivity. Here we evaluate whether annual estimates of aNPP developed from tree rings approximate estimates derived from colocated permanent plots. We studied a lowland evergreen (Howland, Maine), mixed deciduous (Harvard Forest, Massachusetts), and mixed mesophytic (Fernow, West Virginia) forest in the eastern United States. Permanent plots at the sites cover an area of 2-3 ha, and we use these areas as benchmarks indicative of the forest stand. We simulate random draws of permanent plot subsets to describe the distribution of aNPP estimates given a sampling area size equivalent to the tree-ring plots. Though mean tree-ring aNPP underestimates permanent plot aNPP slightly at Howland and Fernow and overestimates at Harvard Forest when compared with the entire permanent plot, it is within the 95% confidence interval of the random draws of equal-sized sampling area at all sites. To investigate whether tree-ring aNPP can be upscaled to the stand, we conducted a second random draw of permanent plot subsets simulating a twofold increase in sampling area. aNPP estimates from this distribution were not significantly different from results of the initial sampling area, though variance decreased as sampling area approaches stand area. Despite several concerns to consider when using tree rings to reconstruct aNPP (e.g., upscaling, allometric, and sampling uncertainties), the benefits are apparent, and we call for the continued application of tree rings in carbon cycle studies across a broader range of species diversity, productivity, and disturbance histories to fully develop this potential.
Detection and Attribution of Vegetation Greening Trend in China over the Last 30 Years
(2015-04) Piao, Shilong; Yin, Guodong; Tan, Jianguang; Cheng, Lei; Huang, Mengtian; Li, Yue; Liu, Ronggao; Mao, Jiafu; Myneni, Ranga B.; Peng, Shushi; Poulter, Benjamin
The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite-derived Leaf Area Index (LAI) datasets for detection as well as five different process-based ecosystem models for attribution. Rising atmospheric CO2 concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing-season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr−1, ranging from 0.0035 yr−1 to 0.0127 yr−1), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGS at the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai–Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS (P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO2 concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.
Disentangling climate and disturbance effects on regional vegetation greening trends
(2018-11) Emmett, Kristen; Poulter, Benjamin; Renwick, Katherine
Productivity of northern latitude forests is an important driver of the terrestrial carbon cycle and is already responding to climate change. Studies of the satellite-derived Normalized Difference Vegetation Index (NDVI) for northern latitudes indicate recent changes in plant productivity. These detected greening and browning trends are often attributed to a lengthening of the growing season from warming temperatures. Yet, disturbance-recovery dynamics are strong drivers of productivity and can mask direct effects of climate change. Here, we analyze 1-km resolution NDVI data from 1989 to 2014 for the northern latitude forests of the Greater Yellowstone Ecosystem for changes in plant productivity to address the following questions: (1) To what degree has greening taken place in the GYE over the past three decades? and (2) What is the relative importance of disturbance and climate in explaining NDVI trends? We found that the spatial extents of statistically significant productivity trends were limited to local greening and browning areas. Disturbance history, predominately fire disturbance, was a major driver of these detected NDVI trends. After accounting for fire-, insect-, and human-caused disturbances, increasing productivity trends remained. Productivity of northern latitude forests is generally considered temperature-limited; yet, we found that precipitation was a key driver of greening in the GYE.
Drought rapidly diminishes the large net CO2 uptake in 2011 over semi-arid Australia
(2016-11) ma, Xuanlong; Huete, Alfredo; Cleverly, James; Eamus, Derek; Chevallier, Frederic; Joiner, Joanna; Poulter, Benjamin; Zhang, Yongguang; Guanter, Luis; Meyer, Wayne; Xie, Zunyi; Ponce-Campos, Guillermo
Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO2 and photosynthesis and in-situ flux tower measures. We show the 2010-11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010-11 net CO2 uptake was highly transient with rapid dissipation through drought. The size of the 2010-11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011-12, and was nearly eliminated in 2012-13 (0.08 Pg). We further report evidence of an earlier 2000-01 large net CO2 uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle.
Emerging role of wetland methane emissions in driving 21st century climate change
(2017-09) Zhang, Zhen; Zimmermann, Niklaus E.; Stenke, Andrea; Li, Xin; Hodson, Elke L.; Zhu, Gaofeng; Huang, Chunlin; Poulter, Benjamin
Wetland methane (CH4) emissions are the largest natural source in the global CH4 budget, contributing to roughly one third of total natural and anthropogenic emissions. As the second most important anthropogenic greenhouse gas in the atmosphere after CO2, CH4 is strongly associated with climate feedbacks. However, due to the paucity of data, wetland CH4 feedbacks were not fully assessed in the Intergovernmental Panel on Climate Change Fifth Assessment Report. The degree to which future expansion of wetlands and CH4 emissions will evolve and consequently drive climate feedbacks is thus a question of major concern. Here we present an ensemble estimate of wetland CH4 emissions driven by 38 general circulation models for the 21st century. We find that climate change-induced increases in boreal wetland extent and temperature-driven increases in tropical CH4 emissions will dominate anthropogenic CH4 emissions by 38 to 56% toward the end of the 21st century under the Representative Concentration Pathway (RCP2.6). Depending on scenarios, wetland CH4 feedbacks translate to an increase in additional global mean radiative forcing of 0.04W.m(-2) to 0.19W.m(-2) by the end of the 21st century. Under the \worst-case\" RCP8.5 scenario, with no climate mitigation, boreal CH4 emissions are enhanced by 18.05 Tg to 41.69 Tg, due to thawing of inundated areas during the cold season (December to May) and rising temperature, while tropical CH4 emissions accelerate with a total increment of 48.36 Tg to 87.37 Tg by 2099. Our results suggest that climate mitigation policies must consider mitigation of wetland CH4 feedbacks to maintain average global warming below 2 degrees C.
Evaluating the agreement between measurements and models of net ecosystem exchange at different times and time scales using wavelet coherence: an example using data from the North American Carbon Program Site-Level Interim Synthesis
(2013-11) Stoy, Paul C.; Dietze, Michael C.; Richardson, Andrew D.; Vargas, Rodrigo; Barr, Alan G.; Anderson, R. S.; Arain, M. Altaf; Baker, Ian T.; Black, T. A; Chen, Jing M.; Cook, R. B.; Gough, Christopher M.; Grant, Robert F.; Hollinger, David Y.; Izaurralde, R. Cesar; Kucharik, Christopher J.; Lafleur, Peter; Law, Beverly E.; Liu, Shuguang; Lokupitiya, Erandathie; Luo, Yiqi; Munger, J. William; Peng, Changhui; Poulter, Benjamin; Price, David T.; Ricciuto, Daniel M.; Riley, William J.; Sahoo, Alok Kumar; Schaefer, Kevin; Schwalm, C. R.; Tian, Hui; Verbeeck, Hans; Weng, Ensheng
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.
Global patterns and climate drivers of water-use efficiency in terrestrial ecosystems deduced from satellite-based datasets and carbon cycle models
(2016-03) Sun, Yan; Piao, Shilong; Huang, Mengtian; Ciais, Philippe; Zeng, Zhenzhong; Cheng, Lei; Li, Xiran; Zhang, Xinping; Mao, Jiafu; Peng, Shushi; Poulter, Benjamin; Shi, Xiaoying; Wang, Xuhui; Wang, Ying-Ping; Zeng, Hui
Aim: To investigate how ecosystem water-use efficiency (WUE) varies spatially under different climate conditions, and how spatial variations in WUE differ from those of transpiration-based water-use efficiency (WUEt) and transpiration-based inherent water-use efficiency (IWUEt). Location: Global terrestrial ecosystems. Methods: We investigated spatial patterns of WUE using two datasets of gross primary productivity (GPP) and evapotranspiration (ET) and four biosphere model estimates of GPP and ET. Spatial relationships between WUE and climate variables were further explored through regression analyses. Results: Global WUE estimated by two satellite-based datasets is 1.9 ± 0.1 and 1.8 ± 0.6 g C m−2 mm−1 lower than the simulations from four process-based models (2.0 ± 0.3 g C m−2 mm−1) but comparable within the uncertainty of both approaches. In both satellite-based datasets and process models, precipitation is more strongly associated with spatial gradients of WUE for temperate and tropical regions, but temperature dominates north of 50° N. WUE also increases with increasing solar radiation at high latitudes. The values of WUE from datasets and process-based models are systematically higher in wet regions (with higher GPP) than in dry regions. WUEt shows a lower precipitation sensitivity than WUE, which is contrary to leaf- and plant-level observations. IWUEt, the product of WUEt and water vapour deficit, is found to be rather conservative with spatially increasing precipitation, in agreement with leaf- and plant-level measurements. Main conclusions: WUE, WUEt and IWUEt produce different spatial relationships with climate variables. In dry ecosystems, water losses from evaporation from bare soil, uncorrelated with productivity, tend to make WUE lower than in wetter regions. Yet canopy conductance is intrinsically efficient in those ecosystems and maintains a higher IWUEt. This suggests that the responses of each component flux of evapotranspiration should be analysed separately when investigating regional gradients in WUE, its temporal variability and its trends.
How well do terrestrial biosphere models simulate coarse-scale runoff in the contiguous United States?
(2015-05) Schwalm, C. R.; Huntzinger, D. N.; Cook, R. B.; Wei, Y.; Baker, I. T.; Neilson, Ronald P.; Poulter, Benjamin; Caldwell, Peter; Sun, G.; Tian, H. Q.; Zeng, Ning
Significant changes in the water cycle are expected under current global environmental change. Robust assessment of present-day water cycle dynamics at continental to global scales is confounded by shortcomings in the observed record. Modeled assessments also yield conflicting results which are linked to differences in model structure and simulation protocol. Here we compare simulated gridded (1Â° spatial resolution) runoff from six terrestrial biosphere models (TBMs), seven reanalysis products, and one gridded surface station product in the contiguous United States (CONUS) from 2001 to 2005. We evaluate the consistency of these 14 estimates with stream gauge data, both as depleted flow and corrected for net withdrawals (2005 only), at the CONUS and water resource region scale, as well as examining similarity across TBMs and reanalysis products at the grid cell scale. Mean runoff across all simulated products and regions varies widely (range: 71 to 356 mm yrâˆ’1) relative to observed continental-scale runoff (209 or 280 mm yrâˆ’1 when corrected for net withdrawals). Across all 14 products 8 exhibit Nashâ€“Sutcliffe efficiency values in excess of 0.8 and three are within 10% of the observed value. Region-level mismatch exhibits a weak pattern of overestimation in western and underestimation in eastern regionsâ€”although two products are systematically biased across all regionsâ€”and largely scales with water use. Although gridded composite TBM and reanalysis runoff show some regional similarities, individual product values are highly variable. At the coarse scales used here we find that progress in better constraining simulated runoff requires standardized forcing data and the explicit incorporation of human effects (e.g., water withdrawals by source, fire, and land use change).
Interannual variability of ecosystem carbon exchange: From observation to prediction
(2017-09) Niu, Shuli; Zheng, Fu; Yiqi, Luo; Stoy, Paul C.; Keenan, Trevor F.; Poulter, Benjamin; Zhang, Leiming; Piao, Shilong; Zhou, Xuhui; Zheng, Han; Han, Jiayin; Wang, Qiufeng; Yu, Guirui
Aim Terrestrial ecosystems have sequestered, on average, the equivalent of 30% of anthropogenic carbon (C) emissions during the past decades, but annual sequestration varies from year to year. For effective C management, it is imperative to develop a predictive understanding of the interannual variability (IAV) of terrestrial net ecosystem C exchange (NEE). Location Global terrestrial ecosystems. Methods We conducted a comprehensive review to examine the IAV of NEE at global, regional and ecosystem scales. Then we outlined a conceptual framework for understanding how anomalies in climate factors impact ecological processes of C cycling and thus influence the IAV of NEE through biogeochemical regulation. Results The phenomenon of IAV in land NEE has been ubiquitously observed at global, regional and ecosystem scales. Global IAV is often attributable to either tropical or semi‐arid regions, or to some combination thereof, which is still under debate. Previous studies focus on identifying climate factors as driving forces of IAV, whereas biological mechanisms underlying the IAV of ecosystem NEE are less clear. We found that climate anomalies affect the IAV of NEE primarily through their differential impacts on ecosystem C uptake and respiration. Moreover, recent studies suggest that the carbon uptake period makes less contribution than the carbon uptake amplitude to IAV in NEE. Although land models incorporate most processes underlying IAV, their efficacy to predict the IAV in NEE remains low. Main conclusions To improve our ability to predict future IAV of the terrestrial C cycle, we have to understand biological mechanisms through which anomalies in climate factors cause the IAV of NEE. Future research needs to pay more attention not only to the differential effects of climate anomalies on photosynthesis and respiration but also to the relative importance of the C uptake period and amplitude in causing the IAV of NEE. Ultimately, we need multiple independent approaches, such as benchmark analysis, data assimilation and time‐series statistics, to integrate data, modelling frameworks and theory to improve our ability to predict future IAV in the terrestrial C cycle.
Land use change and El Niño-Southern Oscillation drive decadal carbon balance shifts in Southeast Asia
(2018-03) Kondo, Masayuki; Ichii, Kazuhito; Patra, Prabir K.; Canadell, Joseph G.; Poulter, Benjamin; Stitch, Stephen; Calle, Leonardo; Liu, Yi Y.; van Dijk, Albert I. J. M.; Saeki, Tazu; Saigusa, Nobuko; Friedlingstein, Pierre; Arneth, Almut; Harper, Anna B.; Jain, Atul K.; Kato, Etsushi; Koven, Charles D.; Li, Fang; Pugh, Thomas A. M.; Zaehle, Sonke; Wiltshire, Andy; Chevallier, Frederic; Maki, Takashi; Nakamura, Takashi; Niwa, Yosuke; Rödenbeck, Christian
An integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks.