scholarly journals Hipsometric relationship modeling using data sampled in tree scaling and inventory plots

2011 ◽  
Vol 35 (1) ◽  
pp. 157-164 ◽  
Author(s):  
Valdir Carlos Lima de Andrade ◽  
Helio Garcia Leite
Keyword(s):  
Standard Error ◽  
Tree Height ◽  
Forest Stands ◽  
F Test ◽  
Graphic Analysis ◽  
Using Data

This work evaluated eight hypsometric models to represent tree height-diameter relationship, using data obtained from the scaling of 118 trees and 25 inventory plots. Residue graphic analysis and percent deviation mean criteria, qui-square test precision, residual standard error between real and estimated heights and the graybill f test were adopted. The identity of the hypsometric models was also verified by applying the F(Ho) test on the plot data grouped to the scaling data. It was concluded that better accuracy can be obtained by using the model prodan, with h and d1,3 data measured in 10 trees by plots grouped into these scaling data measurements of even-aged forest stands.

scholarly journals Analisis Kontribusi Transaksi Pariwisata terhadap Produk Domestik Bruto (PDB) Sektor Pariwisata

Media Wisata ◽  
2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Budi Hermawan
Keyword(s):  
Standard Error ◽  
F Test

Pariwisata merupakan sector yang sangat strategis dalam perekonomian Indonesia dan merupakan sector yang relative tahan terhadap krisis ekonomi. Apabila komponen – komponen ekonomi pariwisata dapat tumbuh pesat maka kontribusi terhadap pertumbuhan perekonomian nasional akan sangat dominan. Indikator terbaik untuk menunjukkan performa ekonomi suatu negara yaitu Produk Domestik Bruto (PDB). PDB Nasional yang diperoleh sangat dipengaruhi oleh PDB sevtor pariwisata. Pariwisata merupakan sector yang tidak berdiri sendiri, akan tetapi didukung oleh sektor ekonomi lainnya. Transaksi – transaksi pariwisata untuk pengukuran PDB sector pariwisata sesuia dengan rumusan Nesparnas yaitu: konsumsi wisatawan mancanegara; konsumsi wisatawan nusantara; Investasi pariwisata; pengeluaran wisatawan nasional (pre + posttrip); dan promosi pariwisata. Oleh karena itu fokus utama penelitian ini dirumuskan : Seberapa besarkah kekuatan konsumsi wisatawan manca negara, konsumsi wisatawan, investasi pariwisata, pengeluaran wisatawan nasional dan pengeluaran promosi pariwisata mampu merubah PDB sektor pariwisata dan kontribusinya terhadap PDB Nasional dimasa depan ?. Data dalam penelitian inimenggunakan data skunder Nesparnas tahun 2000 – 2009. Alat analisis yang digunakan yaitu regresi; uji F dan uji t.Analisis tersebut dapat menggambarkan kontribusi dan pengaruh transaksi pariwisata terhadap perolehan PDB sector pariwisata. Ajusted R square sebesar 0,972, berarti bahwa 97,2%dari PDB pariwisata dapat dijelaskan oleh variasi dari transaksi konsumsi wisatawan mancanegara; konsumsi wisatawan nusantara; pengeluaran investasi pariwisata; dan pengeluaran wisatawan nasional. F test (Anova) sebesar 78,050 > 4,7725 (tabel F). Dengan signifikansi sebesar 0.000 jauh lebih kecil dari 0,05, maka model regresi dapat digunakan untuk memprediksi PDB sektor pariwisata. Hal tersebut menunjukkan bahwa transaksi konsumsi wisatawan mancanegara ; konsumsi wisatawan nusantara; pengeluaran investasi pariwisata; dan pengeluaran wisatawan nasional secara simultan menpengaruhi Produk Domestik Bruto (PDB)sektor pariwisata Uji t pada variabel konsumsi wisatawan mancanegara (XI) sebagai penduga sangat representative sebab nilai standard error sebesar 0,059 < 1,96 dan t –hitung sebesar 7.700 > t- table sebesar 2,262 dan signifikansi sebesar 0,001. Hal ini menunjukkan bahwa variabel konsumsi wisatawan mancanegara mempunyai pengaruh yang kuat (signifikan) terhadap PDB sektor Pariwisata. Variabel konsumsi wisatawan nusantara(X2) sebagai penduga sangat representative sebab nilai standard error sebesar 0,117 < 1,96 dan t-hitung sebesar 2,927 > t-table sebesar 2,262 (tabel t df=9 du a 0,025) dan signifikansi sebesar 0,033. Hal ini menunjukkan bahwa variable konsumsi wisatawan nusantara mempunyai pengaruh yang kuat terhadap PDB sektor pariwisata. Variable investasi pariwisata (X3) sebagai penduga cukup representative sebab nilai standard error sebesar 0,179 < 1,96 dan t- hitung sebesar 1,675 < t-table sebesar2,262 dan signifikansi sebesar 0,155. Hal ini menunjukkan bahwa variable investasi pariwisata tidak mempunyai pengaruh yang kuat terhadap PDB sektor pariwisata. Variable wisatawan nasional (X$) sebagai penduga tidak cukup representative sebab nilai standard error sebesar 0,124 < 1,96 dan t-hitung sebesar 1,975 < t-table sebesar 2,262 dan signifikansi sebesar 0,105. Hal ini menunjukkan bahwa variable wisatawan nasional tidak mempunyai pengaruh yang kuat terhadap PDB sektor Pariwisata.

scholarly journals SANITARY CONDITION OF PICEA ABIES (L. ) KARST. YOUNG FOREST STANDS DEPENDING ON THE SPATIAL SPECIFICITY

AGROFOR ◽  
2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Jelena RUBA ◽  
Olga MIEZITE ◽  
Imants LIEPA
Keyword(s):  
Risk Factors ◽  
Picea Abies ◽  
Tree Height ◽  
Impact Factors ◽  
Forest Stands ◽  
Sanitary Condition ◽  
Young Forest ◽  
Young Forests ◽  
Spatial Specificity ◽  
Sanitary State

As a result of nature resources intensive use, most of ecosystems have beenconverted. Anthropogenic impact includes changes of forest stands structure andtheir spatial specificity in the forest area. Accordingly the sanitary state of Norwayspruce young forest stands can be affected by different risk impact factors ofmanagement. The aim of the research was to analyze the spruce Picea abies (L. )Karst. young forest stands sanitary condition depending on forest plots spatialspecificity and location in the forest areas. The data were collected in 4 regions ofLatvia in spruce young forest stands (1 - 40 years old). The research was conductedin young natural and artificial stands (pure – 44, mixed – 42). In total 502 sampleplots with a total area of 28250 mwere installed. The particular plot size (25, 50,100 and 200 m) were selected depending on the stand average tree height, whiletheir number depended on the forest stand area. A total area of investigated foreststands were 127. 5 hectares. Results showed that the expression of spatial specificsdepended on risk factors and their intensity, as well as the environmentalcharacteristics. Damages caused by abiotic risk factors at different forest standswere not the same regarding intensity, nature and volume, but more or less closelywere related to all site conditions. Spatial specificity of forest stands area (regularand irregular), as well as their location in the forest massif significantly affects thespruce young forests sanitary status (respectively p=0. 027 and p=0. 002). Differentrisk factors damage to forests, bordering with spruce or pine young growths,cutovers and various types of infrastructure, were identified as much moreimportant.

scholarly journals Height-Diameter Equations for Thirteen Midwestern Bottomland Hardwood Species

2002 ◽  
Vol 19 (4) ◽  
pp. 171-176 ◽  
Author(s):  
Kenneth C. Colbert ◽  
David R. Larsen ◽  
James R. Lootens
Keyword(s):  
Tree Height ◽  
Average Height ◽  
Bottomland Hardwood ◽  
Bottomland Hardwood Forests ◽  
Des Moines ◽  
Hardwood Species ◽  
Riparian Tree ◽  
Regression Techniques ◽  
Using Data ◽  
Total Tree

Abstract Height-diameter equations are often used to predict the mean total tree height for trees when only diameter at breast height (dbh) is measured. Measuring dbh is much easier and is subject to less measurement error than total tree height. However, predicted heights only reflect the average height for trees of a particular diameter. In this study, we present a set of height-diameter equations for 13 riparian tree species using data obtained from bottomland hardwood forests along the Mississippi, Missouri, Illinois, and Des Moines rivers. Nonlinear regression techniques were used to develop the equations. The resulting equations provide a reasonable means of predicting unknown tree heights, given dbh, for these species.

Modeling Tree Mortality Following Wildfire in Pinus ponderosa Forests in the Central Sierra-Nevada of California

1993 ◽  
Vol 3 (3) ◽  
pp. 139 ◽  
Author(s):  
JC Regelbrugge ◽  
SG Conard
Keyword(s):  
Sierra Nevada ◽  
Pinus Ponderosa ◽  
Tree Mortality ◽  
Fire Severity ◽  
Tree Height ◽  
Roc Curves ◽  
Stem Bark ◽  
Mortality Probability ◽  
Using Data ◽  
Bark Char

We modeled tree mortality occurring two years following wildfire in Pinus ponderosa forests using data from 1275 trees in 25 stands burned during the 1987 Stanislaus Complex fires. We used logistic regression analysis to develop models relating the probability of wildfire-induced mortality with tree size and fire severity for Pinus ponderosa, Calocedrus decurrens, Quercus chrysolepis, and Q. kelloggii. One set of models predicts mortality probability as a function of DBH and height of stem-bark char, a second set of models uses relative char height (height of stem-bark char as a proportion of tree height) as the predictor. Probability of mortality increased with increasing height of stem-bark char and decreased with increasing tree DBH and height. Analysis of receiver operating characteristic (ROC) curves indicated that both sets of models perform well for all species, with 83 to 96 percent concordance between predicted probabilities and observed outcomes. The models can be used to predict die probability of post-wildfire mortality of four tree species common in Pinus ponderosa forests in the central Sierra Nevada of California.

Comparison of non-exercise cardiorespiratory fitness prediction equations in apparently healthy adults

2019 ◽  
pp. 204748731988124 ◽  
Author(s):  
James E Peterman ◽  
Mitchell H Whaley ◽  
Matthew P Harber ◽  
Bradley S Fleenor ◽  
Mary T Imboden ◽  
...  
Keyword(s):  
Cardiorespiratory Fitness ◽  
Standard Error ◽  
Prediction Equation ◽  
Cardiopulmonary Exercise Test ◽  
Healthy Adults ◽  
Future Research ◽  
Prediction Equations ◽  
Test Analysis ◽  
Using Data ◽  
Apparently Healthy

Aims A recent scientific statement suggests clinicians should routinely assess cardiorespiratory fitness using at least non-exercise prediction equations. However, no study has comprehensively compared the many non-exercise cardiorespiratory fitness prediction equations to directly-measured cardiorespiratory fitness using data from a single cohort. Our purpose was to compare the accuracy of non-exercise prediction equations to directly-measured cardiorespiratory fitness and evaluate their ability to classify an individual's cardiorespiratory fitness. Methods The sample included 2529 tests from apparently healthy adults (42% female, aged 45.4 ± 13.1 years (mean±standard deviation). Estimated cardiorespiratory fitness from 28 distinct non-exercise prediction equations was compared with directly-measured cardiorespiratory fitness, determined from a cardiopulmonary exercise test. Analysis included the Benjamini–Hochberg procedure to compare estimated cardiorespiratory fitness with directly-measured cardiorespiratory fitness, Pearson product moment correlations, standard error of estimate values, and the percentage of participants correctly placed into three fitness categories. Results All of the estimated cardiorespiratory fitness values from the equations were correlated to directly measured cardiorespiratory fitness ( p < 0.001) although the R2 values ranged from 0.25–0.70 and the estimated cardiorespiratory fitness values from 27 out of 28 equations were statistically different compared with directly-measured cardiorespiratory fitness. The range of standard error of estimate values was 4.1–6.2 ml·kg−1·min−1. On average, only 52% of participants were correctly classified into the three fitness categories when using estimated cardiorespiratory fitness. Conclusion Differences exist between non-exercise prediction equations, which influences the accuracy of estimated cardiorespiratory fitness. The present analysis can assist researchers and clinicians with choosing a non-exercise prediction equation appropriate for epidemiological or population research. However, the error and misclassification associated with estimated cardiorespiratory fitness suggests future research is needed on the clinical utility of estimated cardiorespiratory fitness.

scholarly journals The importance of forest structure to biodiversity–productivity relationships

2017 ◽  
Vol 4 (1) ◽  
pp. 160521 ◽  
Author(s):  
Friedrich J. Bohn ◽  
Andreas Huth
Keyword(s):  
Species Distribution ◽  
Forest Structure ◽  
Basal Area ◽  
Tree Height ◽  
National Forest Inventory ◽  
National Forest ◽  
Forest Stands ◽  
Annual Productivity ◽  
Structure Indices ◽  
Modelling Approach

While various relationships between productivity and biodiversity are found in forests, the processes underlying these relationships remain unclear and theory struggles to coherently explain them. In this work, we analyse diversity–productivity relationships through an examination of forest structure (described by basal area and tree height heterogeneity). We use a new modelling approach, called ‘forest factory’, which generates various forest stands and calculates their annual productivity (above-ground wood increment). Analysing approximately 300 000 forest stands, we find that mean forest productivity does not increase with species diversity. Instead forest structure emerges as the key variable. Similar patterns can be observed by analysing 5054 forest plots of the German National Forest Inventory. Furthermore, we group the forest stands into nine forest structure classes, in which we find increasing, decreasing, invariant and even bell-shaped relationships between productivity and diversity. In addition, we introduce a new index, called optimal species distribution, which describes the ratio of realized to the maximal possible productivity (by shuffling species identities). The optimal species distribution and forest structure indices explain the obtained productivity values quite well ( R 2 between 0.7 and 0.95), whereby the influence of these attributes varies within the nine forest structure classes.

Factors affecting the availability of thick epiphyte mats and other potential nest platforms for Marbled Murrelets in British Columbia

2010 ◽  
Vol 40 (4) ◽  
pp. 727-746 ◽  
Author(s):  
Alan E. Burger ◽  
Robert A. Ronconi ◽  
Michael P. Silvergieter ◽  
Catherine Conroy ◽  
Volker Bahn ◽  
...  
Keyword(s):  
British Columbia ◽  
Forest Canopy ◽  
Tree Height ◽  
Suitable Habitat ◽  
Factors Affecting ◽  
Marbled Murrelet ◽  
Pooled Data ◽  
Model Predictions ◽  
Using Data ◽  
Marbled Murrelets

Nest platforms (mossy pads, limbs, and deformities >15 cm in diameter) are key requirements in the forest nesting habitat of the threatened Marbled Murrelet ( Brachyramphus marmoratus (J.F. Gmelin, 1789)). Little is known about factors that affect the availability of platforms or the growth of canopy epiphytes that provide platforms. We examined variables affecting these parameters in coastal trees in British Columbia using data from 29 763 trees at 1412 sites in 170 watersheds. Tree diameter (diameter at breast height (DBH)) was the most important predictor of platform availability in the pooled data and within each of six regions. In most regions, platforms become available at DBH > 60 cm, but on East Vancouver Island, DBH needs to be >96 cm and possibly on the Central Coast >82 cm. Other regional predictors of platforms included tree height, tree species, and to a lesser extent elevation, slope, and latitude. Most (72%) trees providing platforms had epiphytes (mainly moss) covering one third or more of branch surfaces and 81% had intermediate or thick epiphyte mats. Mistletoe deformities provided <7% of platforms. Our model predictions help to define and manage suitable habitat for nesting Marbled Murrelets and also contribute to understanding forest canopy ecosystems.

scholarly journals Fitting Tree Height Distributions in Natural Beech Forest Stands of Guilan (Case Study: Masal)

2019 ◽  
Vol 7 (14) ◽  
pp. 1-9
Author(s):  
Iraj Hassanzad Navroodi ◽  
◽  
Ismaeil moradi ◽  
Keyword(s):  
Tree Height ◽  
Beech Forest ◽  
Forest Stands

scholarly journals Pengaruh Lokasi dan Kualitas Pelayanan Terhadap Kepuasan Pelanggan Pada Jasa Pengiriman J & T di Muara Bulian

2019 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
M Aziz Mukhlis
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Data Processing ◽  
Qualitative Analysis ◽  
Hypothesis Test ◽  
F Test ◽  
Independent Variables ◽  
Using Data

Bussiness world competition currently is more progressively tight. It is also perceived by  services J & T In muara bulian. J & T is demanded to understand about the factors that can influence their customer’s satisfaction. J & T have to make some improvement and innovation that can increasing their customer’s satisfaction. The research aims to analyze how the influence of service quality, and location toward customer satisfaction. Sample of the research is 81 customer and then an analysis is performed toward the obtained data by using data analysis quantitatively and qualitatively. Quantitatively analysis includes: validity and realibility test, classical assumption test, multiple regression analysis and hypothesis test through t and F test, and determination coefficient analysis (R²). Qualitative analysis is an interpretation of the obtained data within research and the result of data processing has been implemented by providing information and explanation. Data has complied validity, realibility and classical test is processed, so that those are resulting regression equation as follows: Where, Y = a + b1 X1 + b2 X2 Customer Satisfaction (Y), Service Quality variable (X1), service qualitu variable (X2), and Location variable (X3). Hyphothesis test uses t test demonstrates that the three of examined independent variables is proved significantly have a partially effect on dependent variable of Customer Satisfaction. Then, follow the F test can be recognized that the three of examined independent variables has a simultaneously effect on dependent variable of Customer Satisfaction

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