Global response patterns of plant photosynthesis to nitrogen addition: A meta‐analysis

2020 ◽  
Vol 26 (6) ◽  
pp. 3585-3600 ◽  
Author(s):  
Xingyun Liang ◽  
Tong Zhang ◽  
Xiankai Lu ◽  
David S. Ellsworth ◽  
Hormoz BassiriRad ◽  
...  
2021 ◽  
Vol 28 (2) ◽  
pp. 194-201
Author(s):  
Ahmad Kholis ◽  
Soetojo ◽  
Wahjoe Djatisoesanto

Objective: To evaluate the effectiveness of TNF-α inhibitor therapy in Bladder Pain Syndrome/Interstitial Cystitis (BPS/IC) patients compared to placebo, assessed using Global Response Assessment (GRA). Material & Methods: A systematic review and meta-analysis. Subjects were patients with moderate to severe diagnosis of BPS/IC who were given TNF-α inhibitor versus placebo, with the Global Response Assessment (GRA) (patient-reported self-reported BPS/IC treatment response scale). A systematic literature search was carried out on the English databases PubMed/MEDLINE and Science  Direct, published until September 2020. Data were extracted independently and assessed the bias and quality of each selected article. Results: Initially there were 124 studies. After further selection, 2 RCT studies were included in the criteria for this study. The number of samples obtained was 85 patients. There is 1 study that used 400 mg of certolizumab pegol subcutaneously and 1 study used adalimumab 80 mg subcutaneously and followed by 40 mg subcutaneously for 2 weeks. Both studies had statistically low heterogeneity with I2 = 0% (P = 0.34), so fixed effect statistical model was used to determine the result. Furthermore, there was no significant difference (P = 0.32) between the number of GRA responders from the TNF-α inhibitor and placebo therapy groups, with odds ratio of 1.61 (CI = 0.65-4.00). Conclusion: TNF-α inhibitor therapy did not increase GRA responders when compared to placebo.


2019 ◽  
Vol 7 (12) ◽  
pp. 1464-1480 ◽  
Author(s):  
Sara Minoli ◽  
Christoph Müller ◽  
Joshua Elliott ◽  
Alex C. Ruane ◽  
Jonas Jägermeyr ◽  
...  

Ecosystems ◽  
2016 ◽  
Vol 20 (5) ◽  
pp. 904-916 ◽  
Author(s):  
Deping Zhai ◽  
Wanyu Jin ◽  
Junjiong Shao ◽  
Yanghui He ◽  
Guodong Zhang ◽  
...  

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Chengming You ◽  
Fuzhong Wu ◽  
Youmin Gan ◽  
Wanqin Yang ◽  
Zhongmin Hu ◽  
...  

2014 ◽  
Vol 11 (8) ◽  
pp. 12375-12414 ◽  
Author(s):  
N. J Bouskill ◽  
W. J Riley ◽  
J. Tang

Abstract. Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the atmosphere. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the above and belowground high-latitude ecosystem responses to warming and nitrogen addition, and identified mechanisms absent, or poorly parameterized in CLM4.5. While the two model versions predicted similar trajectories for soil carbon stocks following both types of perturbation, other variables (e.g., belowground respiration) differed from the observations in both magnitude and direction, indicating the underlying mechanisms are inadequate for representing high-latitude ecosystems. The observational synthesis attribute these differences to missing representations of microbial dynamics, characterization of above and belowground functional processes, and nutrient competition. We use the observational meta-analyses to discuss potential approaches to improving the current models (e.g., the inclusion of dynamic vegetation or different microbial functional guilds), however, we also raise a cautionary note on the selection of data sets and experiments to be included in a meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average =72 kg ha−1 yr−1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which preclude a rigorous evaluation of the model responses to nitrogen perturbation. Overall, we demonstrate here that elucidating ecological mechanisms via meta-analysis can identify deficiencies in both ecosystem models and empirical experiments.


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