Dataset Information

Non-linear responses of net ecosystem productivity to gradient warming in a paddy field in Northeast China.

ABSTRACT: Global warming has a known impact on ecosystems but there is a lack of understanding about its impact on ecosystem processes. Net ecosystem productivity (NEP) and its components play a key part in the global carbon cycle. Analysing the impact of global warming on NEP will improve our understanding of how warming affects ecosystems. In our study, conducted in 2018, five warming treatments were manipulated (0 W, 500 W, 1000 W, 1500 W, and 3000 W) using three repetitions of far infrared open warming over a paddy field in Northeast China. NEP and its two related components, gross primary productivity (GPP) and ecosystem respiration (ER), were measured using the static chamber-infrared gas analyser method to explore the effects of different warming magnitudes on NEP. Results showed that measurement dates, warming treatments, and their interactions significantly affected NEP, ER, and GPP. Warming significantly increased NEP and its components but they showed a non-linear response to different warming magnitudes. The maximum increases in NEP and its components occurred at 1500 W warming. NEP is closely related to its components and the non-linear response of NEP may have primarily resulted from that of GPP. Gradient warming non-linearly increased GPP in the paddy field studied in Northeast China, resulting in the non-linear response of NEP. This study provides a basis for predicting the responses of carbon cycles in future climate events.

SUBMITTER: Sun Y

PROVIDER: S-EPMC7315621 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Non-linear responses of net ecosystem productivity to gradient warming in a paddy field in Northeast China.

Sun Yulu Y Qu Fuyao F Zhu Xianjin X Sun Bei B Wang Guojiao G Yin Hong H Wan Tao T Song Xiaowen X Chen Qian Q

PeerJ 20200610

Global warming has a known impact on ecosystems but there is a lack of understanding about its impact on ecosystem processes. Net ecosystem productivity (NEP) and its components play a key part in the global carbon cycle. Analysing the impact of global warming on NEP will improve our understanding of how warming affects ecosystems. In our study, conducted in 2018, five warming treatments were manipulated (0 W, 500 W, 1000 W, 1500 W, and 3000 W) using three repetitions of far infrared open warmin ...[more]

PMID: 32607282

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Project description:The allocation of the net primary productivity (NPP) of an ecosystem between canopy, woody tissue and fine roots is an important descriptor of the functioning of that ecosystem, and an important feature to correctly represent in terrestrial ecosystem models. Here, we collate and analyse a global dataset of NPP allocation in tropical forests, and compare this with the representation of NPP allocation in 13 terrestrial ecosystem models. On average, the data suggest an equal partitioning of allocation between all three main components (mean 34 ± 6% canopy, 39 ± 10% wood, 27 ± 11% fine roots), but there is substantial site-to-site variation in allocation to woody tissue versus allocation to fine roots. Allocation to canopy (leaves, flowers and fruit) shows much less variance. The mean allocation of the ecosystem models is close to the mean of the data, but the spread is much greater, with several models reporting allocation partitioning outside of the spread of the data. Where all main components of NPP cannot be measured, litterfall is a good predictor of overall NPP (r(2) = 0.83 for linear fit forced through origin), stem growth is a moderate predictor and fine root production a poor predictor. Across sites the major component of variation of allocation is a shifting allocation between wood and fine roots, with allocation to the canopy being a relatively invariant component of total NPP. This suggests the dominant allocation trade-off is a 'fine root versus wood' trade-off, as opposed to the expected 'root-shoot' trade-off; such a trade-off has recently been posited on theoretical grounds for old-growth forest stands. We conclude by discussing the systematic biases in estimates of allocation introduced by missing NPP components, including herbivory, large leaf litter and root exudates production. These biases have a moderate effect on overall carbon allocation estimates, but are smaller than the observed range in allocation values across sites.

Project description:BackgroundUnderstanding the nitrogen (N) mineralization process and applying appropriate model simulation are key factors in evaluating N mineralization. However, there are few studies of the N mineralization characteristics of paddy soils in Mollisols area of Northeast China.Materials and methodsThe soils were sampled from the counties of Qingan and Huachuan, which were located in Mollisols area of Northeast China. The sample soil was incubated under waterlogged at 30°C in a controlled temperature cabinet for 161 days (a 2: 1 water: soil ratio was maintained during incubation). Three models, i.e. the single first-order kinetics model, the double first-order kinetics model and the mixed first-order and zero-order kinetics model were used to simulate the cumulative mineralised N (NH4+-N and TSN) in the laboratory and waterlogged incubation.Principal resultsDuring 161 days of waterlogged incubation, the average cumulative total soluble N (TSN), ammonium N (NH4+-N), and soluble organic N (SON) was 122.2 mg kg-1, 85.9 mg kg-1, and 36.3 mg kg-1, respectively. Cumulative NH4+-N was significantly (P < 0.05) positively correlated with organic carbon (OC), total N (TN), pH, and exchangeable calcium (Ca), and cumulative TSN was significantly (P < 0.05) positively correlated with OC, TN, and exchangeable Ca, but was not significantly (P > 0.05) correlated with C/N ratio, cation exchange capacity (CEC), extractable iron (Fe), clay, and sand. When the cumulative NH4+-N and TSN were simulated, the single first-order kinetics model provided the least accurate simulation. The parameter of the double first-order kinetics model also did not represent the actual data well, but the mixed first-order and zero-order kinetics model provided the most accurate simulation, as demonstrated by the estimated standard error, F statistic values, parameter accuracy, and fitting effect.ConclusionsOverall, the results showed that SON was involved with N mineralization process, and the mixed first-order and zero-order kinetics model accurately simulates the N mineralization process of paddy soil in Mollisols area of Northeast China under waterlogged incubation.

Dataset Information

Non-linear responses of net ecosystem productivity to gradient warming in a paddy field in Northeast China.

Publications

Non-linear responses of net ecosystem productivity to gradient warming in a paddy field in Northeast China.

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