Simulation of the effects of photodecay on long‐term litter decay using DayCent

Chen, Maosi; Parton, William J.; Adair, E. Carol; Asao, Shinichi; Hartman, Melannie D.; Gao, Wei

doi:10.1002/ecs2.1631

Cited by 30 publications

(44 citation statements)

References 101 publications

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“…It is based on a version of DayCent that simulates photosynthesis and hence gross primary production (Savage et al 2013, Chen et al 2016) using a simplified Farquhar model of SIPNET (Aber andFederer 1992, Braswell et al 2005). It is based on a version of DayCent that simulates photosynthesis and hence gross primary production (Savage et al 2013, Chen et al 2016) using a simplified Farquhar model of SIPNET (Aber andFederer 1992, Braswell et al 2005).…”

Section: Daycent-uvmentioning

confidence: 99%

“…DayCent is a biogeochemical model widely used to simulate the dynamics of various ecosystems, from agricultural fields to grasslands and forests, to examine a variety of topics, including organic matter decomposition, and N cycling and ecosystem responses to climate and land-use change (Gholz et al 2000, Parton et al 2007b, 2015, Luo et al 2008, Bontti et al 2009, Harmon et al 2009, Savage et al 2013). A detailed description and validation of DayCent-UV can be found in Chen et al (2016), and of DayCent in numerous sources (Parton et al 1993, 1996, 1998, Del Grosso et al 2001, 2008, Savage et al 2013. 1).…”

Section: Daycent-uvmentioning

confidence: 99%

“…The values of parameters involved were taken from Chen et al (2016). In the model, microbial turnover increases with solar radiation absorbed by aboveground litter pools that represent microbial biomass, until absorbed solar radiation reaches a maximum value when only a fraction of the microbial pool is killed (those at the surface, exposed to solar radiation).…”

Section: Daycent-uvmentioning

confidence: 99%

“…These mechanisms counteract, as direct degradation produces compounds that are more susceptible to subsequent microbial decomposition (Gallo et al 2009, Liu et al 2014, Wang et al 2015, Austin et al 2016. The mechanisms were incorporated into DayCent-UV, and the model was validated against observations from Long-Term Intersite Decomposition Experiment (LIDET) at three semi-arid sites in the western United States (Chen et al 2016). By incorporating photodegradation, DayCent-UV was better able to simulate the patterns of mass loss seen in the LIDET data for the semi-arid sties (Chen et al 2016).…”

Section: Introductionmentioning

confidence: 99%

“…The mechanisms were incorporated into DayCent-UV, and the model was validated against observations from Long-Term Intersite Decomposition Experiment (LIDET) at three semi-arid sites in the western United States (Chen et al 2016). By incorporating photodegradation, DayCent-UV was better able to simulate the patterns of mass loss seen in the LIDET data for the semi-arid sties (Chen et al 2016).…”

Section: Introductionmentioning

confidence: 99%

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Photodegradation accelerates ecosystem N cycling in a simulated California grassland

et al. 2018

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Photodegradation accelerates litter decay in arid grasslands where plant growth and litter decay are strongly controlled by precipitation and evapotranspiration. However, the effects of photodegradation on ecosystem C and N dynamics are not well understood. We examined the effects using an ecosystem biogeochemical model DayCent-UV with photodegradation explicitly represented and validated. The model was parameterized for a California grassland where photodegradation was documented to release CO 2 from litter. The model was parameterized with an inverse modeling approach using an extensive data set of six years of daily observed carbon and water gas exchange (gross primary production, ecosystem respiration, and evapotranspiration), soil temperature, and soil moisture. DayCent-UV correctly simulated the seasonal patterns of the observed gas exchange and closely simulated the inter-annual variation in the gas exchange and biomass production rates. The simulations suggested that the inter-annual variation is driven more by actual evapotranspiration than by precipitation because a large portion of precipitation is lost as runoff during wet years. Photodegradation in DayCent-UV accelerated C and N cycling, decreasing system C and N by 9.2% and 9.5% and C and N residence times by 9.4% and 18.2%. Accelerated N cycling made a greater fraction of system N available for plants, increasing net N mineralization and plant production for a given amount of system N. Increased net N mineralization was due to decreased immobilization by microbes in the aboveground organic matter. Photodegradation did not alter the control on plant production by evapotranspiration. These results suggest that at the ecosystem level, the central effect of photodegradation is to suppress microbial activity. We conclude that photodegradation accelerates N cycling at the expense of microbes in this grassland, making it more efficient in supporting plant growth for a given amount of N in the system.

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Section: Daycent-uvmentioning

confidence: 99%

Section: Daycent-uvmentioning

confidence: 99%

Section: Daycent-uvmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Photodegradation accelerates ecosystem N cycling in a simulated California grassland

et al. 2018

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Accounting for photodegradation dramatically improves prediction of carbon losses in dryland systems

et al. 2017

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. 2017. Accounting for photodegradation dramatically improves prediction of carbon losses in dryland systems. Ecosphere 8(7):e01892. 10. 1002/ecs2.1892 Abstract. Traditional models of decomposition fail to capture litter mass loss patterns in dryland systems. This shortcoming has stimulated research into alternative drivers of decomposition, including photodegradation. Here, we use aboveground litter decomposition data for dryland (arid) sites from the Long-term Intersite Decomposition Experiment Team data set to test hypotheses (models) about the mechanisms and impacts of photodegradation. Incorporating photodegradation into a traditional biotic decomposition model substantially improved model predictions for mass loss at these dryland sites, especially after four years. The best model accounted for the effects of solar radiation via photodegradation loss from the intermediate cellulosic and lignin pools and direct inhibition of microbial decomposition. Despite the concurrent impacts of photodegradation and inhibition on mass loss, the best photodegradation model increased mass loss by an average of 12% per year compared to the biotic-only decomposition model. The best model also allowed soil infiltration into litterbags to reduce photodegradation and inhibition of microbial decomposition by shading litter from solar radiation. Our modeling results did not entirely support the popular hypothesis that initial lignin content increases the effects of photodegradation on litter mass loss; surprisingly, higher initial lignin content decreased the rate of cellulosic photodegradation. Importantly, our results suggest that mass loss rates due to photodegradation may be comparable to biotic decomposition rates: Mass loss due to photodegradation alone resulted in litter mass losses of 6-15% per year, while mass loss due to biotic decomposition ranged from 20% per year during early-stage decomposition to 3% per year during late-stage decomposition. Overall, failing to account for the impacts of solar radiation on litter mass loss under-predicted long-term litter mass loss by approximately 26%. Thus, not including photodegradation in dryland decomposition models likely results in large underestimations of carbon loss from dryland systems.

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The signature of sea surface temperature anomalies on the dynamics of semiarid grassland productivity

et al. 2017

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Abstract. We used long-term observations of grassland aboveground net plant production (ANPP, 1939(ANPP, -2016, growing seasonal advanced very-high-resolution radiometer remote sensing normalized difference vegetation index (NDVI) data , and simulations of actual evapotranspiration to evaluate the impact of Pacific Decadal Oscillation (PDO) and El Niño-Southern Oscillation (ENSO) sea surface temperature (SST) anomalies on a semiarid grassland in northeastern Colorado. Because ANPP was well correlated (R 2 = 0.58) to cumulative April to July actual evapotranspiration (iAET) and cumulative growing season NDVI (iNDVI) was well correlated to iAET and ANPP (R 2 = 0.62 [quadratic model] and 0.59, respectively), we were able to quantify interactions between the long-duration (15-30 yr) PDO temperature cycles and annual-duration ENSO SST phases on ANPP. We found that during cold-phase PDOs, mean ANPP and iNDVI were lower, and the frequency of low ANPP years (drought years) was much higher, compared to warm-phase PDO years. In addition, ANPP, iNDVI, and iAET were highly variable during the cold-phase PDOs. When NINO-3 (ENSO index) values were negative, there was a higher frequency of droughts and lower frequency of wet years regardless of the PDO phase. PDO and NINO-3 anomalies reinforced each other resulting in a high frequency of above-normal iAET (52%) and low frequency of drought (20%) when both PDO and NINO-3 values were positive and the opposite pattern when both PDO and NINO-3 values were negative (24% frequency of above normal and 48% frequency of drought). Precipitation variability and subsequent ANPP dynamics in this grassland were dampened when PDO and NINO-3 SSTs had opposing signs. Thus, primary signatures of these SSTs in this semiarid grassland are (1) increased interannual variability in ANPP during cold-phase PDOs, (2) drought with low ANPP occurring in almost half of those years with negative values of PDO and NINO-3, and (3) high precipitation and ANPP common in years with positive PDO and NINO-3 values.

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Simulation of the effects of photodecay on long‐term litter decay using DayCent

Cited by 30 publications

References 101 publications

Photodegradation accelerates ecosystem N cycling in a simulated California grassland

Photodegradation accelerates ecosystem N cycling in a simulated California grassland

Accounting for photodegradation dramatically improves prediction of carbon losses in dryland systems

The signature of sea surface temperature anomalies on the dynamics of semiarid grassland productivity

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