scholarly journals Interregional Crown Width Models for Individual Trees Growing in Pure and Mixed Stands in Austria

Forests ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 114 ◽  
Author(s):  
Rafael Buchacher ◽  
Thomas Ledermann
Keyword(s):  
Species Composition ◽  
Predictor Variable ◽  
Forest Growth ◽  
Silver Fir ◽  
Mixed Stands ◽  
Data Set ◽  
Individual Tree ◽  
Crown Width ◽  
Site Characteristics ◽  
The Relationship

Crown width is a functional trait that is commonly used to improve the estimation of above-ground biomass of forests and is often included as a predictor variable in forest growth models. Most of the existing crown width models reflect the relationship between crown width, tree size and competition variables, but do not consider the effect of species mixture. In this study, we developed crown width models for individual-tree of the major tree species growing in Austria. Because these models should be applicable for mixed and pure stands and should also take into account the characteristics of different sites, the relationship between crown width, site variables and species composition was investigated. For that purpose, we used data from a sub-sample of the Austrian National Forest Inventory, which comprises crown width measurements of about 8900 trees from 1508 sample plots. Because of the hierarchical structure of the data set (i.e., trees nested within the plot) which destroys the independencies between observations, linear mixed-effects models were used. The species composition of the stand was included via the species-specific relative proportions of basal area. To describe the interregional variability of crown width, dummy variables were introduced, which account for region-specific differences. Site characteristics were incorporated through the altitude, slope and aspect of the site. For Norway spruce, silver fir, Scots pine, European larch, European beech, oak species and ash/maple species it was possible to develop crown width models, which reflect the effects of site characteristics and species composition of the stand. The crown widths of shade-tolerant species reacted mainly positively to admixture, whereas light-demanding species reacted with decreasing crown widths. Coniferous species were not as strongly affected by mixture as broadleaf species.

scholarly journals Tree Species Composition and Diversity in Oban Forest Reserve, Nigeria

2014 ◽  
Vol 3 (1) ◽  
pp. 10 ◽  
Author(s):  
Humphrey Igbinosa Aigbe ◽  
Godwin Ejakhe Omokhua
Keyword(s):  
Species Richness ◽  
Species Composition ◽  
Tree Species ◽  
Basal Area ◽  
Growth Cycle ◽  
Forest Growth ◽  
Population Densities ◽  
Individual Tree ◽  
Forest Reserve ◽  
Tree Species Composition

Tree species composition and diversity were assessed in Oban Forest Reserve. Three stage sampling procedure was used to collect data on tree parameters – diameter at breast height (dbh); diameters over bark at the base, middle and top; merchantable height and total height using a minimum dbh limit of ≥10 cm in the tertiary sample plots. A total of 808 trees were measured and 72 species identified in the study area. Stand level parameters were estimated and tree diversity assessed. Results indicate that an average number of stems encountered per hectare were 306. Population densities of individual tree species ranged from 1 to 22 ha-1. Population densities of species were poor. The basal area/ha estimated is 34.67m2 and the species richness index obtained was 10.605, which indicate high species richness. The value of Shannon’s Index (HI) is 3.795 which is quite high.The results show that the forest reserve is a well-stocked tropical rainforest in Nigeria. The relative richness of the forest reserve in terms of individual tree species does not correlate well with the abundance because the abundance of each of the species was quite low and density poor. While there is paucity of most species, Staudtia stipitata was the most abundant (22 tree/ha). The forest has reverted back to the turbulent agrading stage of the forest growth cycle. 

scholarly journals Individual tree measurements by means of digital aerial photogrammetry

2004 ◽  
Vol 2004 (3) ◽  
Author(s):  
Ilkka Korpela
Keyword(s):  
Measurement Errors ◽  
Aerial Photographs ◽  
Tree Level ◽  
Stem Volume ◽  
Species Classification ◽  
Mixed Stands ◽  
Individual Tree ◽  
Crown Width ◽  
The Individual ◽  
Positioning Algorithm

This study explores the plausibility of the use of multi-scale, CIR aerial photographs to conduct forest inventory at the individual tree level. Multiple digitised aerial photographs are used for manual and semi-automatic 3D positioning of tree tops, for species classification, and for measurements on tree height and crown width. A new tree top positioning algorithm is presented and tested. It incorporates template matching in a 3D search space. Also, a new method is presented for tree species classification. In it, a partition of the image space according to the continuously varying image-object-sun geometry of aerial views is performed. Discernibility of trees in aerial images is studied. The measurement accuracy and overall measurability of crown width by using manual image measurements is investigated. A simulation study is used to examine the combined effects of discernibility and photogrammetric measurement errors on stand variables. The study material contained large-scale colour and CIR image material and 7708 trees from 24 fully mapped plots in Southern Finland. The results of the discernibility analysis suggest that 88–100% of the total stem volume is measurable when using multiple aerial photographs. The structure and density of the forest were found to affect discernibility. The best hit-rates when using the semi-automatic tree top positioning algorithm ranged from 77 to 100% of the visually discernible trees. Systematic underestimation of the crown width was observed and the measurability of crown width was best near the image nadir. Species classification was tested in mixed stands of Scots pine, Norway spruce, and silver birch. The Kappa-coefficients ranged from 0.71 to 0.86. The results of the simulation suggest that very high accuracy at the individual tree level cannot be expected. However, if the photogrammetric measurements are unbiased, the aggregate stand variables can be very accurate. An accurate species recognition method is needed in the mixed stands in order to achieve unbiased estimates for the small strata.

scholarly journals Development of species composition in long term simulations with an individual-tree growth simulator

2009 ◽  
Vol 55 (No. 5) ◽  
pp. 194-200 ◽  
Author(s):  
M. Huber ◽  
H. Sterba
Keyword(s):  
Species Composition ◽  
Tree Growth ◽  
Management Practices ◽  
Forest Ecosystems ◽  
Vegetation Type ◽  
Natural Vegetation ◽  
Silver Fir ◽  
Potential Natural Vegetation ◽  
Individual Tree ◽  
Individual Tree Growth

The spruce-fir-beech dominated forest stands in Litschau in the Austrian part of the Bohemian Massif were converted by former forest management practices into pure Norway spruce stands and are now discussed to be reconverted into the potential natural vegetation type. The targeted potential natural vegetation type is usually defined by experts in vegetation sciences. Because meanwhile individual-tree growth simulators are a well acknowledged tool for predicting future forest stand development, in this study we investigate if PROGNAUS can also be used to predict the redevelopment of managed forest ecosystems into natural forest ecosystems regarding species composition. The development of 23 stands in Litschau has been simulated over 1,000 years under the “no-management” option. Generally, the simulated species distribution agrees quite well with the expectations of the potential natural vegetation type. However, the predicted amounts of silver fir and maple species are lower than expected, which probably is due to browsing and management effects represented in the parameterization data for PROGNAUS.

scholarly journals Seoseid puistu juurdekasvu ja koosseisu vahel hariliku männi (Pinus sylvestris L.) enamusega segametsades / Relationships between stand volume growth and composition in mixed stands dominated by Scots Pine (Pinus sylvestris L.)

2011 ◽  
Vol 54 (1) ◽  
pp. 18-27
Author(s):  
Ando Lilleleht
Keyword(s):  
Species Composition ◽  
Pinus Sylvestris ◽  
Scots Pine ◽  
Linear Regression Analysis ◽  
Volume Growth ◽  
Basal Area ◽  
Height Growth ◽  
Forest Growth ◽  
Mixed Stands ◽  
Study Results

Abstract. Relationships between the volume growth of mixed stands and their species composition were analyzed in order to examine the so-called “mixture effect” on stand productivity. The influence of co-species was studied using multiple linear regression analysis. Stand level basal area and height growth models were constructed in order to find out which stand characteristics can be used to describe mixture-effects. The study material originates from the Estonian network of permanent forest growth plots, only stands consisting of mainly (≥ 50% of volume) Scots Pine with Norway spruce and/or Birch spp. as co-species were used. Sample size was 139 5-year measurement periods on 88 plots; stand ages range from 14 to 167 years. The study results indicate that an increasing proportion of birch in the stand causes a negative effect on both basal area and height growth. Spruce seems to be a weaker competitor than other pines as its trend in the model is positive. Also, height growth is more rapid when the mean diameter of spruce is smaller than that of pine. Species composition coefficients for co-species (calculated by standing volume) proved to be the most significant variables that describe stand composition in the models

Identifying Physico-Chemical Laws from the Robotically Collected Data

2019 ◽  
Author(s):  
Liwei Cao ◽  
Danilo Russo ◽  
Vassilios S. Vassiliadis ◽  
Alexei Lapkin
Keyword(s):  
Experimental Data ◽  
Numerical Models ◽  
Predictor Variable ◽  
Physical Models ◽  
Training Data ◽  
Mixed Integer ◽  
Physico Chemical ◽  
Data Points ◽  
Future Work ◽  
The Relationship

<p>A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor variables and training data points. The globally optimal search was extended to identify physical models and to cope with noise in the experimental data predictor variable. The methodology was coupled with the collection of experimental data in an automated fashion, and was proven to be successful in identifying the correct physical models describing the relationship between the shear stress and shear rate for both Newtonian and non-Newtonian fluids, and simple kinetic laws of reactions. Future work will focus on addressing the limitations of the formulation presented in this work, by extending it to be able to address larger complex physical models.</p><p><br></p>

scholarly journals Classification of Tree Species as Well as Standing Dead Trees Using Triple Wavelength ALS in a Temperate Forest

2019 ◽  
Vol 11 (22) ◽  
pp. 2614 ◽  
Author(s):  
Nina Amiri ◽  
Peter Krzystek ◽  
Marco Heurich ◽  
Andrew Skidmore
Keyword(s):  
Tree Species ◽  
Feature Selection Method ◽  
Silver Fir ◽  
Maximum Point ◽  
Individual Tree ◽  
Dead Trees ◽  
Multi Wavelength ◽  
Standing Dead ◽  
Standing Dead Trees ◽  
532 Nm

Knowledge about forest structures, particularly of deadwood, is fundamental for understanding, protecting, and conserving forest biodiversity. While individual tree-based approaches using single wavelength airborne laserscanning (ALS) can successfully distinguish broadleaf and coniferous trees, they still perform multiple tree species classifications with limited accuracy. Moreover, the mapping of standing dead trees is becoming increasingly important for damage calculation after pest infestation or biodiversity assessment. Recent advances in sensor technology have led to the development of new ALS systems that provide up to three different wavelengths. In this study, we present a novel method which classifies three tree species (Norway spruce, European beech, Silver fir), and dead spruce trees with crowns using full waveform ALS data acquired from three different sensors (wavelengths 532 nm, 1064 nm, 1550 nm). The ALS data were acquired in the Bavarian Forest National Park (Germany) under leaf-on conditions with a maximum point density of 200 points/m 2 . To avoid overfitting of the classifier and to find the most prominent features, we embed a forward feature selection method. We tested our classification procedure using 20 sample plots with 586 measured reference trees. Using single wavelength datasets, the highest accuracy achieved was 74% (wavelength = 1064 nm), followed by 69% (wavelength = 1550 nm) and 65% (wavelength = 532 nm). An improvement of 8–17% over single wavelength datasets was achieved when the multi wavelength data were used. Overall, the contribution of the waveform-based features to the classification accuracy was higher than that of the geometric features by approximately 10%. Our results show that the features derived from a multi wavelength ALS point cloud significantly improve the detailed mapping of tree species and standing dead trees.

scholarly journals Effect of Competition and Climatic Conditions on the Growth of Beech in the Mixed Pine Beech Stand: Lithuanian Case Study

2020 ◽  
Vol 3 (1) ◽  
pp. 49
Author(s):  
Edgaras Linkevičius ◽  
Gerda Junevičiūtė
Keyword(s):  
Intraspecific Competition ◽  
Tree Species ◽  
Forest Growth ◽  
Competition Effect ◽  
Diameter Increment ◽  
Cart Analysis ◽  
Crown Width ◽  
Beech Stand ◽  
Negative Effect ◽  
The Impact

Climate change and warming will potentially have profound effects on forest growth and yield, especially for pure stands in the near future. Thus, increased attention has been paid to mixed stands, e.g., pine and beech mixtures. However, the interaction of tree species growing in mixtures still remains unknown. Thus, the aim of this study was to investigate the impact of the interspecific and intraspecific competition to diameter, height, and crown width of pine and beech trees growing in mixtures, as well as to evaluate the impact of climatic indicators to the beech radial diameter increment. The data was collected in 2017 at the mixed mature pine beech double layer stand, located in the western part of Lithuania. The sample plot of 1.2 hectare was established and tree species, diameter at the breast height, tree height, height-to-crown base, height-to-crown width, and position were measured for all 836 trees. Additionally, a representative sample of radial diameter increments were estimated only for the beech trees by taking out core discs at the height of 1 m when the stand was partially cut. Competition analysis was based on the distance-dependent competition index, which was further based on crown parameters. Climatic effect was evaluated using classification and regression tree (CART) analysis. We found almost no interspecific competition effect to diameter, height, or crown width for both tree species growing in the first layer. However, it had an effect on beeches growing in the second layer. The intraspecific competition effect was important for pine and beech trees, showing a negative effect for both of them. Our results show the possible coexistence of these tree species due to niche differentiation. An analysis of climatic indicators from 1991–2005 revealed that precipitation from February–May of the current vegetation year and mean temperatures from July to September expressed radial diameter increment effects for beech trees. Low temperatures during March and April, as well as high precipitation during January, had a negative effect on beech radial increments. From 2006–2016, the highest effect on radial diameter increments was the mean temperatures from July to September, as well as the precipitation in January of the current year. From 1991–2016, the highest effect on radial diameter increments was the temperature from July to September 1991–2016 and the precipitation in June 1991–2016. Generally, cool temperatures and higher precipitation in June had a positive effect on beech radial increments. Therefore, our results show a sensitivity to high temperatures and droughts during summer amid Lithuanian’s growth conditions.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

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