scholarly journals Modeling and Monitoring Terrestrial Primary Production in a Changing Global Environment: Toward a Multiscale Synthesis of Observation and Simulation

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Shufen Pan ◽  
Hanqin Tian ◽  
Shree R. S. Dangal ◽  
Zhiyun Ouyang ◽  
Bo Tao ◽  
...  

There is a critical need to monitor and predict terrestrial primary production, the key indicator of ecosystem functioning, in a changing global environment. Here we provide a brief review of three major approaches to monitoring and predicting terrestrial primary production: (1) ground-based field measurements, (2) satellite-based observations, and (3) process-based ecosystem modelling. Much uncertainty exists in the multi-approach estimations of terrestrial gross primary production (GPP) and net primary production (NPP). To improve the capacity of model simulation and prediction, it is essential to evaluate ecosystem models against ground and satellite-based measurements and observations. As a case, we have shown the performance of the dynamic land ecosystem model (DLEM) at various scales from site to region to global. We also discuss how terrestrial primary production might respond to climate change and increasing atmospheric CO2and uncertainties associated with model and data. Further progress in monitoring and predicting terrestrial primary production requires a multiscale synthesis of observations and model simulations. In the Anthropocene era in which human activity has indeed changed the Earth’s biosphere, therefore, it is essential to incorporate the socioeconomic component into terrestrial ecosystem models for accurately estimating and predicting terrestrial primary production in a changing global environment.

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.


2015 ◽  
Vol 12 (2) ◽  
pp. 513-526 ◽  
Author(s):  
B. Bond-Lamberty ◽  
J. P. Fisk ◽  
J. A. Holm ◽  
V. Bailey ◽  
G. Bohrer ◽  
...  

Abstract. Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.


2020 ◽  
Author(s):  
Rodolfo Nóbrega ◽  
David Sandoval ◽  
Colin Prentice

<p>Root zone storage capacity (R<sub>z</sub>) is a parameter widely used in terrestrial ecosystem models that estimate the amount of soil moisture available for transpiration. However, R<sub>z</sub> is subject to large uncertainty, due to the lack of data on the distribution of soil properties and the depth of plant roots that actively take up water. Our study makes use of a mass-balance approach to investigate R<sub>z</sub> in different ecosystems, and changes in water fluxes caused by land-cover change. The method needs no land-cover or soil information, and uses precipitation (P) and evapotranspiration (ET) time series to estimate the seasonal water deficit. To account for some of the uncertainty in ET, we use different methods for ET estimation, including methods based on satellite estimates, and modelling approaches that back-calculate ET from other ecosystem fluxes. We show that reduced ET due to land-cover change reduces R<sub>z</sub>, which in turn increases baseflow in regions with a strong rainfall seasonality. This finding allows us to analyse the trade-off between gross primary production and hydrological fluxes at river basin scales. We also consider some ideas on how to use mass-balance R<sub>z</sub> in water-stress functions as incorporated in existing terrestrial ecosystem models.</p>


2018 ◽  
Author(s):  
Nicolas Vuichard ◽  
Palmira Messina ◽  
Sebastiaan Luyssaert ◽  
Bertrand Guenet ◽  
Sönke Zaehle ◽  
...  

Abstract. Nitrogen is an essential element controlling ecosystem carbon (C) productivity and its response to climate change and atmospheric [CO2] increase. This study presents the evaluation – focussing on gross primary production (GPP) – of a new version of the ORCHIDEE model that gathers the representation of the nitrogen cycle and of its interactions with the carbon cycle from the OCN model and the most recent developments from the ORCHIDEE trunk version. We quantify the model skills at 78 Fluxnet sites by simulating the observed mean seasonal cycle, daily mean flux variations, and annual mean average GPP flux for grasslands and forests. Accounting for carbon-nitrogen interactions does not substantially change the main skills of ORCHIDEE, except for the site-to-site annual mean GPP variations, for which the version with carbon-nitrogen interactions is in better agreement to observations. However, the simulated GPP response to idealized [CO2] enrichment simulations is highly sensitive to whether or not carbon-nitrogen interactions are accounted for. Doubling of the atmospheric [CO2] induces an increase of the GPP, but the site-averaged GPP response to CO2 increase projected by the model version with carbon-nitrogen interactions is half of the increase projected by the version without carbon-nitrogen interactions. This model's differentiated response has important consequences for the transpiration rate, which is on average 50 mm yr−1 lower with the version with carbon-nitrogen interactions. Simulated annual GPP for northern, tropical and southern latitudes shows good agreement with the observation-based MTE-GPP product for present-day conditions. An attribution experiment making use of this new version of ORCHIDEE for the time period 1860–2016 suggests that global GPP has increased by 50 %, the main driver being the enrichment of land in reactive nitrogen (through deposition and fertilization), followed by the [CO2] increase. Based on our factorial experiment and sensitivity analysis, we conclude that if carbon-nitrogen interactions are accounted for, the functional responses of ORCHIDEE r4999 better agrees with current understanding of photosynthesis than when the carbon-nitrogen interactions are not accounted for, and that carbon-nitrogen interactions are essential in understanding global terrestrial ecosystem productivity.


2019 ◽  
Vol 12 (11) ◽  
pp. 4751-4779 ◽  
Author(s):  
Nicolas Vuichard ◽  
Palmira Messina ◽  
Sebastiaan Luyssaert ◽  
Bertrand Guenet ◽  
Sönke Zaehle ◽  
...  

Abstract. Nitrogen is an essential element controlling ecosystem carbon (C) productivity and its response to climate change and atmospheric [CO2] increase. This study presents the evaluation – focussing on gross primary production (GPP) – of a new version of the ORCHIDEE model that gathers the representation of the nitrogen cycle and of its interactions with the carbon cycle from the OCN model and the most recent developments from the ORCHIDEE trunk version. We quantify the model skills at 78 FLUXNET sites by simulating the observed mean seasonal cycle, daily mean flux variations, and annual mean average GPP flux for grasslands and forests. Accounting for carbon–nitrogen interactions does not substantially change the main skills of ORCHIDEE, except for the site-to-site annual mean GPP variations, for which the version with carbon–nitrogen interactions is in better agreement with observations. However, the simulated GPP response to idealised [CO2] enrichment simulations is highly sensitive to whether or not carbon–nitrogen interactions are accounted for. Doubling of the atmospheric [CO2] induces an increase in the GPP, but the site-averaged GPP response to a CO2 increase projected by the model version with carbon–nitrogen interactions is half of the increase projected by the version without carbon–nitrogen interactions. This model's differentiated response has important consequences for the transpiration rate, which is on average 50 mm yr−1 lower with the version with carbon–nitrogen interactions. Simulated annual GPP for northern, tropical and southern latitudes shows good agreement with the observation-based MTE-GPP (model tree ensemble gross primary production) product for present-day conditions. An attribution experiment making use of this new version of ORCHIDEE for the time period 1860–2016 suggests that global GPP has increased by 50 %, the main driver being the enrichment of land in reactive nitrogen (through deposition and fertilisation), followed by the [CO2] increase. Based on our factorial experiment and sensitivity analysis, we conclude that if carbon–nitrogen interactions are accounted for, the functional responses of ORCHIDEE r4999 better agree with the current understanding of photosynthesis than when the carbon–nitrogen interactions are not accounted for and that carbon–nitrogen interactions are essential in understanding global terrestrial ecosystem productivity.


2017 ◽  
Vol 14 (23) ◽  
pp. 5441-5454 ◽  
Author(s):  
Yaner Yan ◽  
Xuhui Zhou ◽  
Lifeng Jiang ◽  
Yiqi Luo

Abstract. Carbon (C) turnover time is a key factor in determining C storage capacity in various plant and soil pools as well as terrestrial C sink in a changing climate. However, the effects of C turnover time on ecosystem C storage have not been well explored. In this study, we compared mean C turnover times (MTTs) of ecosystem and soil, examined their variability to climate, and then quantified the spatial variation in ecosystem C storage over time from changes in C turnover time and/or net primary production (NPP). Our results showed that mean ecosystem MTT based on gross primary production (GPP; MTTEC_GPP =  Cpool/GPP, 25.0 ± 2.7 years) was shorter than soil MTT (MTTsoil =  Csoil/NPP, 35.5 ± 1.2 years) and NPP-based ecosystem MTT (MTTEC_NPP =  Cpool/NPP, 50.8 ± 3 years; Cpool and Csoil referred to ecosystem or soil C storage, respectively). On the biome scale, temperature is the best predictor for MTTEC (R2 =  0.77, p < 0.001) and MTTsoil (R2 =  0.68, p < 0.001), while the inclusion of precipitation in the model did not improve the performance of MTTEC (R2 =  0.76, p < 0.001). Ecosystem MTT decreased by approximately 4 years from 1901 to 2011 when only temperature was considered, resulting in a large C release from terrestrial ecosystems. The resultant terrestrial C release caused by the decrease in MTT only accounted for about 13.5 % of that due to the change in NPP uptake (159.3 ± 1.45 vs. 1215.4 ± 11.0 Pg C). However, the larger uncertainties in the spatial variation of MTT than temporal changes could lead to a greater impact on ecosystem C storage, which deserves further study in the future.


2010 ◽  
Vol 7 (1) ◽  
pp. 1101-1129 ◽  
Author(s):  
T. Tagesson ◽  
M. Mastepanov ◽  
M. P. Tamstorf ◽  
L. Eklundh ◽  
P. Schubert ◽  
...  

Abstract. Arctic wetlands play a key role in the terrestrial carbon cycle. Recent studies have shown a greening trend and indicated an increase in CO2 uptake in boreal and sub- to low-arctic areas. Our aim was to combine satellite-based normalized difference vegetation index (NDVI) with ground-based flux measurements of CO2 to investigate a possible greening trend and potential changes in gross primary production (GPP) between 1992 and 2008 in a high arctic fen area. The study took place in Rylekaerene in the Zackenberg Research Area (74°28' N 20°34' W), located in the National park of North Eastern Greenland. We estimated the light use efficiency (ε) for the dominant vegetation types from field measured fractions of photosynthetic active radiation (FAPAR) and ground-based flux measurements of GPP. Measured FAPAR were correlated to satellite-based NDVI. The FAPAR-NDVI relationship in combination with ε was applied to satellite data to model GPP 1992–2008. The model was evaluated against field measured GPP. The model was a useful tool for up-scaling GPP and all basic requirements for the model were well met, e.g., FAPAR was well correlated to NDVI and modeled GPP was well correlated to field measurements. The studied high arctic fen area has experienced a strong increase in GPP between 1992 and 2008. The area has during this period also experienced a substantial increase in local air temperature. Consequently, the observed greening trend is most likely due to ongoing climatic change possibly in combination with CO2 fertilization, due to increasing atmospheric concentrations of CO2.


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