scholarly journals fitplc - an R package to fit hydraulic vulnerability curves

2017 ◽  
Vol 4 ◽  
pp. e002 ◽  
Author(s):  
Remko Duursma ◽  
Brendan Choat
Keyword(s):  
Water Potential ◽  
Traditional Approach ◽  
R Package ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Slope Parameter ◽  
Sigmoidal Function ◽  
Percent Loss ◽  
Hydraulic Vulnerability ◽  
Stem Water

We describe a toolkit to fit hydraulic vulnerability curves, such as the percent loss of xylem hydraulic conductivity ('PLC curves') as a function of the water potential. The toolkit is implemented as an R package, and is thus free to use and open source. The package fits the Weibull or sigmoidal function to measurements of PLC, conductance or conductivity, at corresponding leaf or stem water potentials. From the fitted curve, estimates of Px (the water potential at which x% conductivity is lost, e.g. the P50), and slope parameter (Sx) are provided together with confidence intervals (CI) around the fitted line. The CIs are estimated with the bootstrap. We also demonstrate the advantages of using mixed-effects models in situations where multiple individuals are measured on a species, as compared to the more traditional approach of fitting curves separately and averaging the parameters. We demonstrate the use of the new package with example data on seven species measured with two different techniques.

Leaf hydraulic vulnerability protects stem functionality under drought stress in Salvia officinalis

2016 ◽  
Vol 43 (4) ◽  
pp. 370 ◽  
Author(s):  
Tadeja Savi ◽  
Maria Marin ◽  
Jessica Luglio ◽  
Francesco Petruzzellis ◽  
Sefan Mayr ◽  
...  
Keyword(s):  
Water Potential ◽  
Water Transport ◽  
Salvia Officinalis ◽  
Summer Drought ◽  
Plant Organs ◽  
Transport Efficiency ◽  
Drought Tolerant ◽  
Hydraulic Vulnerability ◽  
Stem Water ◽  
Salvia Officinalis L

Functional coordination between leaf and stem hydraulics has been proposed as a key trait of drought-resistant plants. A balanced water transport efficiency and safety of different plant organs might be of particular importance for plant survival in the Mediterranean climate. We monitored seasonal changes of leaf and stem water relations of Salvia officinalis L. in order to highlight strategies adopted by this species to survive in harsh environmental conditions. During summer drought, the water potential dropped below the turgor loss point thus reducing water loss by transpiration, whereas the photosynthetic efficiency remained relatively high. Leaves lost their water transport efficiency earlier than stems, although in both plant organs P50 (water potential inducing 50% loss of hydraulic conductivity) indicated surprisingly high vulnerability when compared with other drought-tolerant species. The fast recovery of leaf turgor upon restoration of soil water availability suggests that the reduction of leaf hydraulic conductance is not only a consequence of vein embolism, but cell shrinkage and consequent increase of resistance in the extra-xylem pathway may play an important role. We conclude that the drought tolerance of S. officinalis arises at least partly as a consequence of vulnerability segmentation.

scholarly journals Understanding mixed effects models through data simulation

2019 ◽  
Author(s):  
Lisa Marie DeBruine ◽  
Dale J. Barr
Keyword(s):  
Random Effects ◽  
R Package ◽  
Mixed Effects ◽  
Experimental Designs ◽  
Mixed Effects Models ◽  
Data Simulation ◽  
Linear Mixed Effects ◽  
Power Calculations

Experimental designs that sample both subjects and stimuli from a larger population need to account for random effects of both subjects and stimuli using mixed effects models. However, much of this research is analyzed using ANOVA on aggregated responses because researchers are not confident specifying and interpreting mixed effects models. The tutorial will explain how to simulate data with random effects structure and analyse the data using linear mixed effects regression (with the lme4 R package), with a focus on interpreting the output in light of the simulated parameters. Data simulation can not only enhance understanding of how these models work, but also enables researchers to perform power calculations for complex designs. All materials associated with this article can be accessed at https://osf.io/3cz2e/.

scholarly journals Understanding Mixed-Effects Models Through Data Simulation

2021 ◽  
Vol 4 (1) ◽  
pp. 251524592096511
Author(s):  
Lisa M. DeBruine ◽  
Dale J. Barr
Keyword(s):  
Random Effects ◽  
Analysis Of Variance ◽  
R Package ◽  
Mixed Effects ◽  
Experimental Designs ◽  
Mixed Effects Models ◽  
Data Simulation ◽  
Linear Mixed Effects ◽  
Power Calculations

Experimental designs that sample both subjects and stimuli from a larger population need to account for random effects of both subjects and stimuli using mixed-effects models. However, much of this research is analyzed using analysis of variance on aggregated responses because researchers are not confident specifying and interpreting mixed-effects models. This Tutorial explains how to simulate data with random-effects structure and analyze the data using linear mixed-effects regression (with the lme4 R package), with a focus on interpreting the output in light of the simulated parameters. Data simulation not only can enhance understanding of how these models work, but also enables researchers to perform power calculations for complex designs. All materials associated with this article can be accessed at https://osf.io/3cz2e/ .

Population stochastic modelling (PSM)—An R package for mixed-effects models based on stochastic differential equations

2009 ◽  
Vol 94 (3) ◽  
pp. 279-289 ◽  
Author(s):  
Søren Klim ◽  
Stig Bousgaard Mortensen ◽  
Niels Rode Kristensen ◽  
Rune Viig Overgaard ◽  
Henrik Madsen
Keyword(s):  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Stochastic Modelling ◽  
R Package ◽  
Mixed Effects ◽  
Mixed Effects Models

scholarly journals Effect of tofogliflozin on arterial stiffness in patients with type 2 diabetes: prespecified sub-analysis of the prospective, randomized, open-label, parallel-group comparative UTOPIA trial

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Naoto Katakami ◽  
◽  
Tomoya Mita ◽  
Hidenori Yoshii ◽  
Toshihiko Shiraiwa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Conventional Treatment ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Open Label ◽  
Parallel Group ◽  
History Of

Abstract Background Tofogliflozin, an SGLT2 inhibitor, is associated with favorable metabolic effects, including improved glycemic control and serum lipid profile and decreased body weight, visceral adipose tissue, and blood pressure (BP). This study evaluated the effects of tofogliflozin on the brachial-ankle pulse wave velocity (baPWV) in patients with type 2 diabetes (T2DM) without a history of apparent cardiovascular disease. Methods The using tofogliflozin for possible better intervention against atherosclerosis for type 2 diabetes patients (UTOPIA) trial is a prospective, randomized, open-label, multicenter, parallel-group, comparative study. As one of the prespecified secondary outcomes, changes in baPWV over 104 weeks were evaluated in 154 individuals (80 in the tofogliflozin group and 74 in the conventional treatment group) who completed baPWV measurement at baseline. Results In a mixed-effects model, the progression in the right, left, and mean baPWV over 104 weeks was significantly attenuated with tofogliflozin compared to that with conventional treatment (– 109.3 [– 184.3, – 34.3] (mean change [95% CI] cm/s, p = 0.005; – 98.3 [– 172.6, – 24.1] cm/s, p = 0.010; – 104.7 [– 177.0, – 32.4] cm/s, p = 0.005, respectively). Similar findings were obtained even after adjusting the mixed-effects models for traditional cardiovascular risk factors, including body mass index (BMI), glycated hemoglobin (HbA1c), total cholesterol, high-density lipoprotein (HDL)-cholesterol, triglyceride, systolic blood pressure (SBP), hypertension, smoking, and/or administration of drugs, including hypoglycemic agents, antihypertensive agents, statins, and anti-platelets, at baseline. The findings of the analysis of covariance (ANCOVA) models, which included the treatment group, baseline baPWV, and traditional cardiovascular risk factors, resembled those generated by the mixed-effects models. Conclusions Tofogliflozin significantly inhibited the increased baPWV in patients with T2DM without a history of apparent cardiovascular disease, suggesting that tofogliflozin suppressed the progression of arterial stiffness. Trial Registration UMIN000017607. Registered 18 May 2015. (https://www.umin.ac.jp/icdr/index.html)

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