scholarly journals A new terrestrial biosphere model with coupled carbon, nitrogen, and phosphorus cycles (QUINCY v1.0; revision 1772)

Author(s):  
Tea Thum ◽  
Silvia Caldararu ◽  
Jan Engel ◽  
Melanie Kern ◽  
Marleen Pallandt ◽  
...  

Abstract. The dynamics of terrestrial ecosystems are shaped by the coupled cycles of carbon, nitrogen and phosphorus, and strongly depend on the availability of water and energy. These interactions shape future terrestrial biosphere responses to global change. Many process-based models of the terrestrial biosphere have been gradually extended from considering carbon-water interactions to also including nitrogen, and later, phosphorus dynamics. This evolutionary model development has hindered full integration of these biogeochemical cycles and the feedbacks amongst them. Here we present a new terrestrial ecosystem model QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system), which is formulated around a consistent representation of element cycling in terrestrial ecosystems. This new model includes i) a representation of plant growth which separates source (e.g. photosynthesis) and sink (growth rate of individual tissues, constrained by nutrients, temperature, and water availability) processes; ii) the acclimation of many ecophysiological processes to meteorological conditions and/or nutrient availabilities; iii) an explicit representation of vertical soil processes to separate litter and soil organic matter dynamics; iv) a range of new diagnostics (leaf chlorophyll content; 13C, 14C, and 15N isotope tracers) to allow for a more in-depth model evaluation. We present the model structure and provide an assessment of its performance against a range of observations from global-scale ecosystem monitoring networks. We demonstrate that the framework is capable of consistently simulating ecosystem dynamics across a large gradient in climate and soil conditions, as well as across different plant functional types. To aid this understanding we provide an assessment of the model's sensitivity to its parameterisation and the associated uncertainty.

2019 ◽  
Vol 12 (11) ◽  
pp. 4781-4802 ◽  
Author(s):  
Tea Thum ◽  
Silvia Caldararu ◽  
Jan Engel ◽  
Melanie Kern ◽  
Marleen Pallandt ◽  
...  

Abstract. The dynamics of terrestrial ecosystems are shaped by the coupled cycles of carbon, nitrogen, and phosphorus, and these cycles are strongly dependent on the availability of water and energy. These interactions shape future terrestrial biosphere responses to global change. Here, we present a new terrestrial ecosystem model, QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system), which has been designed from scratch to allow for a seamless integration of the fully coupled carbon, nitrogen, and phosphorus cycles with each other and also with processes affecting the energy and water balances in terrestrial ecosystems. This new model includes (i) a representation of plant growth which separates source (e.g. photosynthesis) and sink (growth rate of individual tissues, constrained by temperature and the availability of water and nutrients) processes; (ii) the acclimation of many ecophysiological processes to meteorological conditions and/or nutrient availability; (iii) an explicit representation of vertical soil processes to separate litter and soil organic matter dynamics; (iv) a range of new diagnostics (leaf chlorophyll content; 13C, 14C, and 15N isotope tracers) to allow for a more in-depth model evaluation. In this paper, we present the model structure and provide an assessment of its performance against a range of observations from global-scale ecosystem monitoring networks. We demonstrate that QUINCY v1.0 is capable of simulating ecosystem dynamics across a wide climate gradient, as well as across different plant functional types. We further provide an assessment of the sensitivity of key model predictions to the model's parameterisation. This work lays the ground for future studies to test individual process hypotheses using the QUINCY v1.0 framework in the light of ecosystem manipulation observations, as well as global applications to investigate the large-scale consequences of nutrient-cycle interactions for projections of terrestrial biosphere dynamics.


2015 ◽  
Vol 6 (2) ◽  
pp. 1999-2042 ◽  
Author(s):  
S. Sippel ◽  
F. E. L. Otto ◽  
M. Forkel ◽  
M. R. Allen ◽  
B. P. Guillod ◽  
...  

Abstract. Understanding, quantifying and attributing the impacts of extreme weather and climate events in the terrestrial biosphere is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. In this study, we introduce a novel, resampling-based bias correction scheme that fully preserves the physical consistency and multivariate correlation structure of the model output. This procedure strongly improves the representation of climatic extremes and variability in a large regional climate model ensemble (HadRM3P, climateprediction.net/weatherathome), which is illustrated for summer extremes in temperature and rainfall over Central Europe. Moreover, we simulate biosphere–atmosphere fluxes of carbon and water using a terrestrial ecosystem model (LPJmL) driven by the bias corrected climate forcing. The resampling-based bias correction yields strongly improved statistical distributions of carbon and water fluxes, including the extremes. Our results thus highlight the importance to carefully consider statistical moments beyond the mean for climate impact simulations. In conclusion, the present study introduces an approach to alleviate climate model biases in a physically consistent way and demonstrates that this yields strongly improved simulations of climate extremes and associated impacts in the terrestrial biosphere. A wider uptake of our methodology by the climate and impact modelling community therefore seems desirable for accurately quantifying past, current and future extremes.


2011 ◽  
Vol 11 (2) ◽  
pp. 5379-5405 ◽  
Author(s):  
P. K. Patra ◽  
Y. Niwa ◽  
T. J. Schuck ◽  
C. A. M. Brenninkmeijer ◽  
T. Machida ◽  
...  

Abstract. Quantifying the fluxes of carbon dioxide (CO2) between the atmosphere and terrestrial ecosystems in all their diversity, across the continents, is important and urgent for implementing effective mitigating policies. Whereas much is known for Europe and North America for instance, in comparison, South Asia, with 1.6 billion inhabitants and considerable CO2 fluxes, remained terra incognita in this respect. We use regional measurements of atmospheric CO2 aboard a Lufthansa passenger aircraft between Frankfurt (Germany) and Chennai (India) at cruise altitude, in addition to the existing network sites for 2008, to estimate monthly fluxes for 64-regions using Bayesian inversion and transport model simulations. The applicability of the model's transport parameterization is confirmed using SF6, CH4 and N2O simulations for the CARIBIC datasets. The annual carbon flux obtained by including the aircraft data is twice as large as the fluxes simulated by a terrestrial ecosystem model that was applied to prescribe the fluxes used in the inversions. It is shown that South Asia sequestered carbon at a rate of 0.37±0.20 Pg C yr−1 (1Pg C = 1015 g of carbon in CO2) for the years 2007 and 2008. The seasonality and the strength of the calculated monthly fluxes are successfully validated using independent measurements of vertical CO2 profiles over Delhi and spatial variations at cruising altitude over Asia aboard Japan Airlines passenger aircraft.


2018 ◽  
Author(s):  
Yang Qu ◽  
Shamil Maksyutov ◽  
Qianlai Zhuang

Abstract. To better understand the role of terrestrial ecosystems in the global carbon cycle and their feedbacks to the global climate system, process-based biogeochemistry models need to be improved with respect to model parameterization and model structure. To achieve these improvements, the spin-up time for those differential equation-based models needs to be shortened. Here, an algorithm for a fast spin-up was developed and implemented in a biogeochemistry model, the Terrestrial Ecosystem Model (TEM). With the new spin-up algorithm, we showed that the model reached a steady state in less than 10 years of computing time, while the original method requires more than 200 years on average of model run. For the test sites with five different plant function types, the new method saves over 90 % of the original spin-up time in site-level simulations. In North America simulations, average spin-up time saving for all grid cells is 85 % for either daily or monthly version of TEM. The developed spin-up method shall greatly facilitate our future quantification of carbon dynamics at fine spatial and temporal scales.


2018 ◽  
Author(s):  
Hirokazu Toju ◽  
Hirotoshi Sato ◽  
Satoshi Yamamoto ◽  
Akifumi S. Tanabe

AbstractBackgroundBelow-ground linkage between plant and fungal communities is one of the major drivers of terrestrial ecosystem dynamics. However, we still have limited knowledge of how such plant–fungus associations vary in their community-scale properties depending on fungal functional groups and geographic locations.MethodsBased on high-throughput sequencing of root-associated fungi in eight forests along the Japanese Archipelago, we performed a comparative analysis of arbuscular mycorrhizal, ectomycorrhizal, and saprotrophic/endophytic associations across a latitudinal gradient from cool-temperate to subtropical regions.ResultsIn most of the plant–fungus networks analyzed, host–symbiont associations were significantly specialized but lacked “nested” architecture, which has been commonly reported in plant–pollinator and plant–seed disperser networks. Meanwhile, the structure of arbuscular mycorrhizal networks was differentiated from that of ectomycorrhizal and saprotrophic/endophytic networks, characterized by high connectance. Our data also suggested that geographic factors affected the organization of plant–fungus network structure. For example, the southernmost subtropical site analyzed in this study displayed lower network-level specificity of host–symbiont associations and higher (but still low) nestedness than northern localities.ConclusionsOur comparative analyses suggest that arbuscular mycorrhizal, ectomycorrhizal, and saprotrophic/endophytic plant–fungus associations often lack nested network architecture, while those associations can vary, to some extent, in their community-scale properties along a latitudinal gradient. Overall, this study provides a basis for future studies that will examine how different types of plant–fungus associations collectively structure terrestrial ecosystems.


2015 ◽  
Vol 19 (16) ◽  
pp. 1-21 ◽  
Author(s):  
Chang Liao ◽  
Qianlai Zhuang

Abstract Droughts dramatically affect plant production of global terrestrial ecosystems. To date, quantification of this impact remains a challenge because of the complex plant physiological and biochemical processes associated with drought. Here, this study incorporates a drought index into an existing process-based terrestrial ecosystem model to estimate the drought impact on global plant production for the period 2001–10. Global Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data products are used to constrain model parameters and verify the model algorithms. The verified model is then applied to evaluate the drought impact. The study indicates that droughts will reduce GPP by 9.8 g C m−2 month−1 during the study period. On average, drought reduces GPP by 10% globally. As a result, the global GPP decreased from 106.4 to 95.9 Pg C yr−1 while the global net primary production (NPP) decreased from 54.9 to 49.9 Pg C yr−1. This study revises the estimation of the global NPP and suggests that the future quantification of the global carbon budget of terrestrial ecosystems should take the drought impact into account.


2020 ◽  
Author(s):  
Pavel Šamonil ◽  
Pavel Daněk ◽  
James A. Lutz ◽  
Jakub Jaroš ◽  
Anna Rousová ◽  
...  

<p>Hillslope processes in terrestrial ecosystems are significantly modified by changes in climate and land use. At the same time they strongly influence ecosystem retention capacity, pedocomplexity and biodiversity. This undoubtedly makes hillslope processes one of the crucial components of terrestrial ecosystem dynamics. In this study we focus on the long overlooked biogeomorphological impact of tree death in forested landscapes. Tree uprooting caused by strong storms affects soil and regolith formation and movement quite differently from the decomposition of intact root systems of standing trees that died due to e.g. fire or bark beetle infestation. We quantify the biogeomorphic processes associated with tree death in various terrestrial forest ecosystems and specifically assess (i) the significance of these processes in hillslope dynamics (e.g. slope denudation) of forested landscapes and (ii) the extent to which infrequent severe disturbances can shape these dynamics.</p><p>We used data from repeated tree censuses carried out in ten permanent forest plots (13–74 ha in area) located in Central Europe and North America, differing in a range of characteristics such as tree species composition, climate and disturbance regime. In total, life history of more than 134,000 trees was recorded over periods of up to 47 years, during which about one third of these trees died. Using this information together with empirical models and allometric equations we were able to quantify the average areas and volumes of soil annually affected by dying trees. These quantities differed markedly between sites with different disturbance regimes. Tree uprooting-related volumes accounted annually for 0.01–13.5 m<sup>3</sup>ha<sup>−1</sup> reaching maximum values on sites with occurrence of infrequent strong windstorms (Zofin and Boubin primeval forests, Czech Republic). Volumes related to trees that died standing ranged anually between 0.17 and 20.7 m<sup>3</sup>ha<sup>−1</sup> and were highest in the presence of stand-replacing fires (Yosemite National Park, U.S.). Comparison of these quantities with long-term erosion rates derived using cosmogenic nuclides (<sup>10</sup>Be) suggests that on certain sites, over the last few millennia, tree uprooting can be the main driver of soil erosion.</p>


2011 ◽  
Vol 11 (9) ◽  
pp. 4163-4175 ◽  
Author(s):  
P. K. Patra ◽  
Y. Niwa ◽  
T. J. Schuck ◽  
C. A. M. Brenninkmeijer ◽  
T. Machida ◽  
...  

Abstract. Quantifying the fluxes of carbon dioxide (CO2) between the atmosphere and terrestrial ecosystems in all their diversity, across the continents, is important and urgent for implementing effective mitigating policies. Whereas much is known for Europe and North America for instance, in comparison, South Asia, with 1.6 billion inhabitants and considerable CO2 fluxes, remained terra incognita in this respect. We use regional measurements of atmospheric CO2 aboard a Lufthansa passenger aircraft between Frankfurt (Germany) and Chennai (India) at cruise altitude, in addition to the existing network sites for 2008, to estimate monthly fluxes for 64-regions using Bayesian inversion and transport model simulations. The applicability of the model's transport parameterization is confirmed using SF6, CH4 and N2O simulations for the CARIBIC datasets. The annual amplitude of carbon flux obtained by including the aircraft data is twice as large as the fluxes simulated by a terrestrial ecosystem model that was applied to prescribe the fluxes used in the inversions. It is shown that South Asia sequestered carbon at a rate of 0.37 ± 0.20 Pg C yr−1 (1 Pg C = 1015 g of carbon in CO2) for the years 2007 and 2008. The seasonality and the strength of the calculated monthly fluxes are successfully validated using independent measurements of vertical CO2 profiles over Delhi and spatial variations at cruising altitude over Asia aboard Japan Airlines passenger aircraft.


2016 ◽  
Vol 40 (2) ◽  
pp. 322-351 ◽  
Author(s):  
Jadunandan Dash ◽  
Booker O. Ogutu

Since the launch of the first Landsat satellite in the early 1970s, the field of space-borne optical remote sensing has made significant progress. Advances have been made in all aspects of optical remote sensing data, including improved spatial, temporal, spectral and radiometric resolutions, which have increased the uptake of these data by wider scientific communities. Flagship satellite missions such as NASA’s Terra and Aqua and ESA’s Envisat with their high temporal (<3days) and spectral (15–36 bands) resolutions opened new opportunities for routine monitoring of various aspects of terrestrial ecosystems at the global scale and have provided greater understanding of critical biophysical processes in the terrestrial ecosystem. The launch of new satellite sensors such as Landsat 8 and the European Space Agency’s Copernicus Sentinel missions (e.g. Sentinel 2 with improved spatial resolution (10–60 m) and potential revisit time of five days) is set to revolutionise the availability and use of remote sensing data in global terrestrial ecosystem monitoring. Furthermore, the recent move towards use of constellations of nanosatellites (e.g. the Flock missions by Planet Labs) to collect on-demand high spatial and temporal resolution optical remote sensing data would enable uptake of these data for operational monitoring. As a result of increase in data availability, optical remote sensing data are now increasingly used to support a number of operational services (e.g. land monitoring, atmosphere monitoring and climate change studies). However, many challenges still remain in exploiting the growing volume of optical remote sensing data to monitor global terrestrial ecosystems. These challenges include ensuring the highest data quality both in terms of the sensitivity of sensors and the derived biophysical products, affordability and availability of the data and continuity of data acquisition. This review provides an overview of the developments in space-borne optical remote sensing in the past decade and discusses a selection of aspects of global terrestrial ecosystems where the data are currently used. It concludes by highlighting some of the challenges and opportunities of using optical remote sensing data in monitoring global terrestrial ecosystems.


2012 ◽  
Vol 367 (1586) ◽  
pp. 222-235 ◽  
Author(s):  
David Medvigy ◽  
Paul R. Moorcroft

Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.


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