scholarly journals How many measurements are needed to estimate accurate daily and annual soil respiration fluxes? Analysis using data from a temperate rainforest

2016 ◽  
Vol 13 (24) ◽  
pp. 6599-6609 ◽  
Author(s):  
Jorge F. Perez-Quezada ◽  
Carla E. Brito ◽  
Julián Cabezas ◽  
Mauricio Galleguillos ◽  
Juan P. Fuentes ◽  
...  

Abstract. Making accurate estimations of daily and annual Rs fluxes is key for understanding the carbon cycle process and projecting effects of climate change. In this study we used high-frequency sampling (24 measurements per day) of Rs in a temperate rainforest during 1 year, with the objective of answering the questions of when and how often measurements should be made to obtain accurate estimations of daily and annual Rs. We randomly selected data to simulate samplings of 1, 2, 4 or 6 measurements per day (distributed either during the whole day or only during daytime), combined with 4, 6, 12, 26 or 52 measurements per year. Based on the comparison of partial-data series with the full-data series, we estimated the performance of different partial sampling strategies based on bias, precision and accuracy. In the case of annual Rs estimation, we compared the performance of interpolation vs. using non-linear modelling based on soil temperature. The results show that, under our study conditions, sampling twice a day was enough to accurately estimate daily Rs (RMSE  <  10 % of average daily flux), even if both measurements were done during daytime. The highest reduction in RMSE for the estimation of annual Rs was achieved when increasing from four to six measurements per year, but reductions were still relevant when further increasing the frequency of sampling. We found that increasing the number of field campaigns was more effective than increasing the number of measurements per day, provided a minimum of two measurements per day was used. Including night-time measurements significantly reduced the bias and was relevant in reducing the number of field campaigns when a lower level of acceptable error (RMSE  <  5 %) was established. Using non-linear modelling instead of linear interpolation did improve the estimation of annual Rs, but not as expected. In conclusion, given that most of the studies of Rs use manual sampling techniques and apply only one measurement per day, we suggest performing an intensive sampling at the beginning of the study to determine minimum daily and annual frequencies of sampling.

2016 ◽  
Author(s):  
Jorge F. Perez-Quezada ◽  
Carla E. Brito ◽  
Julián Cabezas ◽  
Mauricio Galleguillos ◽  
Juan P. Fuentes ◽  
...  

Abstract. Making accurate estimations of daily and annual Rs fluxes is key for understanding the carbon cycle process and projecting effects of climate change. In this study we used high-frequency sampling (24-measurements per day) of Rs in a temperate rainforest during one year, with the objective of answering the questions of when and how often measurements should be made to obtain accurate estimations of daily and annual Rs. In this aim, we randomly selected data to simulate samplings of 1, 2, 4 or 6 measurements per day (distributed either during the whole day or only during daytime) combined with 4, 6, 12, 26 or 52 measurements per year. Based on the comparison of partial-data series with the full-data series, we estimated the performance of different partial sampling strategies based on bias, precision and accuracy. In the case of annual Rs estimation, we compared the performance of interpolation vs. using non-linear modelling based on soil temperature. The results show that, under our study conditions, sampling twice a day was enough to accurately estimate daily Rs (RMSE 


2020 ◽  
Author(s):  
Calvin Howes ◽  
Pablo Saide ◽  
Paquita Zuidema ◽  
Jianhao Zhang ◽  
Michael Diamond ◽  
...  

2013 ◽  
Vol 35 (1-2) ◽  
pp. 255-278 ◽  
Author(s):  
Stefano Pagano ◽  
Riccardo Russo ◽  
Salvatore Strano ◽  
Mario Terzo

2018 ◽  
Vol 81 (2) ◽  
pp. 167-173 ◽  
Author(s):  
Luciano Rodrigo Lanssanova ◽  
Sebastião do Amaral Machado ◽  
Alexandre Techy de Almeida Garrett ◽  
Izabel Passos Bonete ◽  
Allan Libanio Pelissari ◽  
...  

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242336
Author(s):  
Peter R. Browne ◽  
Carl T. Woods ◽  
Alice J. Sweeting ◽  
Sam Robertson

Representative learning design proposes that a training task should represent informational constraints present within a competitive environment. To assess the level of representativeness of a training task, the frequency and interaction of constraints should be measured. This study compared constraint interactions and their frequencies in training (match simulations and small sided games) with competition environments in elite Australian football. The extent to which constraints influenced kick and handball effectiveness between competition matches, match simulations and small sided games was determined. The constraints of pressure and time in possession were assessed, alongside disposal effectiveness, through an association rule algorithm. These rules were then expanded to determine whether a disposal was influenced by the preceding disposal. Disposal type differed between training and competition environments, with match simulations yielding greater representativeness compared to small sided games. The subsequent disposal was generally more effective in small sided games compared to the match simulations and competition matches. These findings offer insight into the measurement of representative learning designs through the non-linear modelling of constraint interactions. The analytical techniques utilised may assist other practitioners with the design and monitoring of training tasks intended to facilitate skill transfer from preparation to competition.


2021 ◽  
Vol 39 (3) ◽  
pp. 250-257
Author(s):  
Alessandro Dal’Col Lúcio ◽  
Maria Inês Diel ◽  
Bruno G Sari

ABSTRACT Biologically based growth models can be an alternative in identifying the productive response of multiple harvest vegetables. By interpreting the estimates of the parameters of the models, it is possible to estimate the total production, the rate of fruit production, and the moment when the crop reaches its maximum production potential. Besides, by estimating confidence intervals, these responses can be compared between genotypes or between different treatments. Therefore, the purpose of this manuscript is to present a literature review, and a detailed step-by-step, to interpreting the evolution of the production cycle of vegetables with multiple harvests crops based on non-linear regression. All the requirements that must be met in this type of analysis were presented in detail based on non-linear regression, providing the necessary steps for this type of analysis in details. Demonstration is given using data from strawberry cultivation along with the associated R scripts and interpretation of analysis output in material supplemental. This approach can allow for more relevant inferences than standard means analyses through better examination and modeling of the underlying biological processes.


1962 ◽  
Vol 16 (79) ◽  
pp. 379
Author(s):  
J. W. W. ◽  
Herbert E. Salzer ◽  
Charles H. Richards

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