Live Crown Ratio as an Indicator for Tree Vigor and Stability of Turkey Oak (Quercus cerris L.): A Case Study

Stability of forests represents a significant objective for climate change mitigation. As stand stability is influenced by the stability of individual trees, promoting stable trees is vital for a sustainable forest management. However, inside stands, trees experience intense competition. As a result, the crown recedes and diameter growth is affected, the trees becoming slender and more susceptible to biotic and abiotic disturbances. Finding effective indicators for tree vigor and stability is therefore important. This study aimed to assess the performance of the live crown ratio as an indicator in deciding the timing of tending operations for obtaining and maintaining vigorous Turkey oak trees. Live crown ratio (LCR) and height to diameter ratio (HDR) were determined for 80 sampled Turkey oak trees. A threshold of 100 for HDR was chosen to classify trees as slender or not slender. Next, conditional inference tree and logistic regression were used to determine the LCR threshold value where trees become slender. As the sample included small trees, using breast height to measure diameter may have affected the results. Therefore, small and large trees were also analyzed separately. For the entire dataset, the methods reached quite different results (LCR threshold of 0.371 for conditional inference tree and of 0.434 for the logistic regression), and relatively high values compared to the literature. For tall trees (height > 12.5 m), the methods reached similar results: 0.386 for the conditional inference tree and 0.382 for the logistic regression. For small trees (height < 12.5 m), the conditional inference tree method could not calculate any LCR threshold estimate, while the one from the logistic regression was unrealistically large (0.628). This confirms that using DBH for small trees to compute slenderness brings systematic errors. The live crown ratio was a good indicator of growth vigor for Turkey oak trees. Therefore, for stable trees (HDR < 100), a LCR of 0.36–0.39 must be maintained and could be used to decide the timing for thinning in Turkey oak stands.

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Rising Stars and Underdogs: The Role Race and Parental Education Play in Predicting Mentorship

Youth & Society ◽

10.1177/0044118x211004637 ◽

2021 ◽

pp. 0044118X2110046

Author(s):

Veronica Fruiht ◽

Jordan Boeder ◽

Thomas Chan

Keyword(s):

Critical Race Theory ◽

Parental Education ◽

Individual Characteristics ◽

Conditional Inference ◽

Youth Of Color ◽

Social Success ◽

Conditional Inference Tree ◽

Tree Models ◽

Nationally Representative ◽

Inference Tree

Research suggests that youth with more financial and social resources are more likely to have access to mentorship. Conversely, the rising star hypothesis posits that youth who show promise through their individual successes are more likely to be mentored. Utilizing a nationally representative sample ( N = 4,882), we tested whether demographic characteristics (e.g., race, SES) or personal resources (e.g., academic/social success) are better predictors of receiving mentorship. Regression analyses suggested that demographic, contextual, and individual characteristics all significantly predicted access to mentorship, specifically by non-familial mentors. However, conditional inference tree models that explored the interaction of mentorship predictors by race showed that individual characteristics mattered less for Black and Latino/a youth. Therefore, the rising star hypothesis may hold true for White youth, but the story of mentoring is more complicated for youth of color. Findings highlight the implications of Critical Race Theory for mentoring research and practice.

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Appropriate Treatment For Non-Pedunculated Colorectal Polyps > 20 MM According To Western And Eastern Approach: Conditional Inference-Tree From A Prospective Multicenter Cohort

10.1055/s-0041-1724478 ◽

2021 ◽

Author(s):

J da Costa-Seixas ◽

M López-Cerón ◽

A Arnau ◽

Ò Rosiñol ◽

M Cuatrecasas ◽

...

Keyword(s):

Colorectal Polyps ◽

Conditional Inference ◽

Conditional Inference Tree ◽

Multicenter Cohort ◽

Appropriate Treatment ◽

Inference Tree

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A Conditional Inference Tree Model for Predicting Sleep-Related Breathing Disorders in Patients With Chiari Malformation Type 1: Description and External Validation

Journal of Clinical Sleep Medicine ◽

10.5664/jcsm.7578 ◽

2019 ◽

Vol 15 (01) ◽

pp. 89-99 ◽

Cited By ~ 1

Author(s):

Álex Ferré ◽

María A. Poca ◽

María Dolores de la Calzada ◽

Dulce Moncho ◽

Aintzane Urbizu ◽

...

Keyword(s):

Chiari Malformation ◽

External Validation ◽

Conditional Inference ◽

Tree Model ◽

Sleep Related Breathing Disorders ◽

Conditional Inference Tree ◽

Breathing Disorders ◽

Chiari Malformation Type 1 ◽

Inference Tree

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Forecasting Stock Price Using Conditional Inference Tree

2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN) ◽

10.1109/icacccn.2018.8748383 ◽

2018 ◽

Author(s):

Shivam Thakur ◽

Shekar singh ◽

Seema Sharma

Keyword(s):

Stock Price ◽

Conditional Inference ◽

Conditional Inference Tree ◽

Inference Tree

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Localization value of seizure semiology analyzed by the conditional inference tree method

Epilepsy Research ◽

10.1016/j.eplepsyres.2015.05.012 ◽

2015 ◽

Vol 115 ◽

pp. 81-87 ◽

Cited By ~ 5

Author(s):

Dong Wook Kim ◽

Ki-Young Jung ◽

Kon Chu ◽

So-Hee Park ◽

Seo-Young Lee ◽

...

Keyword(s):

Conditional Inference ◽

Seizure Semiology ◽

Conditional Inference Tree ◽

Tree Method ◽

Inference Tree

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COMPARISON OF THREE MODELS FOR PREDICTING THE SPATIAL DISTRIBUTION OF SOIL ORGANIC CARBON IN BOALEMO REGENCY, SULAWESI

Jurnal Ilmu Tanah dan Lingkungan ◽

10.29244/jitl.18.1.42-48 ◽

2016 ◽

Vol 18 (1) ◽

pp. 42 ◽

Cited By ~ 2

Author(s):

Eloise Mason ◽

Yiyi Sulaeman

Keyword(s):

Linear Regression ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Multiple Linear Regression ◽

Regression Tree ◽

Digital Soil Mapping ◽

Conditional Inference ◽

Conditional Inference Tree ◽

Soil Landscape ◽

Inference Tree

Information on the spatial distribution of soil organic carbon content is required for sustainable land management. But, creating this map is time consuming and costly. Digital soil mapping methodology make use legacy soil data to create provisional soil organic carbon map. This map helps soil surveyors in allocating next soil observation. This study aimed: (i) to develop predictive statistical soil organic carbon models for Sulawesi, and (ii) to evaluate the best model between the three obtained models. Boalemo Regeny in Gorontalo Province (Sulawesi) was selected as studying area due to abundant legacy soil data. The study covered dataset preparation, model development, and model comparison. Dataset of soil organic carbon at 6 different depths as target was established from 176 soil proﬁles and 7 terrain parameters were selected as predictors. Soil-landscape models for each soil depth were created using regression tree, conditional inference tree, and multiple linear regression technique. Result showed that model performance differed among 3 modelling techniques and soil depths. The tree models were better than the multiple linear regression model as they have the lowest RMSE index. The best model in the mountanious area seems to be the regression tree model, whereas in the plains it may be the conditional inference tree. In creating provisional map, several model should be developed and the median of predicted value is used as provisional map. Keywords: Digital soil mapping, multiple linear regression, regression tree, soil-landscape model, soil organic carbon map

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Effect of Postoperative Radiotherapy in Thymoma Patients: A SEER-Based Study

Oncology Research and Treatment ◽

10.1159/000508311 ◽

2020 ◽

pp. 1-7

Author(s):

Haibo Mou ◽

Yiyao Kong ◽

Yingfang Wu ◽

Ying Wu ◽

Lanfang Yu

Keyword(s):

Cox Regression ◽

Postoperative Radiotherapy ◽

Population Based ◽

Conditional Inference ◽

Postoperative Radiation Therapy ◽

Cancer Specific Survival ◽

Prognostic Effect ◽

Conditional Inference Tree ◽

Masaoka Stage ◽

Inference Tree

Introduction: The role of postoperative radiation therapy (PORT) for thymoma is under debate, especially in patients aged ≥60 years with an advanced stage (Masaoka stages III and IV). We aimed to evaluate the efficacy of PORT for thymoma in a population-based registry. Methods: A retrospective analysis of the Surveillance, Epidemiology, and End Results (SEER) database was conducted to compare the outcomes of thymoma patients with or without PORT. The primary outcomes were overall survival (OS) and cancer-specific survival (CSS). Conditional inference tree analyses were performed for risk classification according to the study variables. Cox regression was performed to evaluate the prognostic effect of PORT in the specific subgroups. Results: A total of 2,236 patients were included. The conditional inference tree analysis identified that an age ≥60, a Masaoka stage ≥3, and the year of diagnosis were important factors when classifying patients into prognostic subgroups. PORT was found to be a protective predictor of OS in patients aged ≥60 years, those with a Masaoka stage III—IV, and those diagnosed after 2005. Further subgroup analyses revealed that PORT was significantly associated with a better OS (HR = 0.77) in patients aged ≥60 years, whereas it was not significantly associated with CSS. Conclusions: An older age (≥60 years) is critical for predicting survival outcomes in thymoma patients. Moreover, patients aged ≥60 years could benefit from PORT in terms of OS.

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A Conditional Inference Tree Analysis of Can and May in Korean EFL Learners’ Writings

English Language and Linguistics ◽

10.17960/ell.2018.24.3.008 ◽

2018 ◽

Vol 24 (3) ◽

pp. 165-187

Author(s):

Lee,Yong-hun

Keyword(s):

Conditional Inference ◽

Tree Analysis ◽

Efl Learners ◽

Conditional Inference Tree ◽

Korean Efl Learners ◽

Inference Tree

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Local knowledge and attitude towards the Vulnerable Bhutan takin Budorcas whitei among residents living within its seasonal range

Oryx ◽

10.1017/s0030605318000418 ◽

2019 ◽

Vol 54 (3) ◽

pp. 359-365

Author(s):

Tiger Sangay ◽

Rajaratnam Rajanathan ◽

Karl Vernes ◽

Matthew Tighe

Keyword(s):

Local Knowledge ◽

National Park ◽

Conditional Inference ◽

Secondary Response ◽

Winter Range ◽

Conditional Inference Tree ◽

Awareness Raising ◽

Positive Feelings ◽

Knowledge And Attitude ◽

Inference Tree

AbstractWe assessed local knowledge of and attitudes towards a large, endemic bovid, the Bhutan takin Budorcas whitei, within its seasonal range in Jigme Dorji National Park, Bhutan. Using semi-structured questionnaires, data were collected in March 2015 from interviews with 169 park residents. A conditional inference tree analysis was used to explore associations between demography, locality, and secondary response variables through questions relating to respondents’ knowledge of the takin's status as a protected species, a Vulnerable species, and as the national animal. Most respondents knew the takin was Bhutan's national animal, and of those, a significantly high proportion also knew of its protected status. Significantly more respondents residing in the species’ summer, rather than winter, range were aware of the takin's Vulnerable status. Most respondents expressed positive feelings towards the takin and supported its protection. This strong positive attitude, in conjunction with awareness-raising efforts, could be valuable for promoting the takin as a montane flagship species.

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