scholarly journals Genetic Variation and Tree Improvement of Konishii fir (Cunninghamia lanceolata (Lamb.) Hook. var. konishii) in Taiwan

2011 ◽  
Vol 60 (1-6) ◽  
pp. 196-205 ◽  
Author(s):  
Jeng-Der Chung ◽  
Gordon Nigh ◽  
Ching-Te Chien ◽  
Cheng C. Ying
Keyword(s):  
Genetic Parameters ◽  
Tree Height ◽  
Tree Improvement ◽  
Cunninghamia Lanceolata ◽  
Tree Plantations ◽  
Average Height ◽  
Individual Tree ◽  
Candidate Species ◽  
Variable Species ◽  
Selection For

AbstractWe analyzed a 21-year old progeny test of Konishii fir (Cunninghamia lanceolata(Lamb.) Hook. var.konishii) involving 75 families. Tree height and diameter at breast height (DBH) were periodically recorded. At age 21, average height, DBH, and volume were 15.2 m, 20.2 cm, and 278 dm3, respectively. At this age, family accounted for 9, 12, and 11% of the total variance in height, DBH and volume, respectively. Also at age 21, individual tree heritability was 0.35, 0.49, and 0.45 for height, DBH and volume, respectively, and family heritability was 0.53, 0.69, and 0.66 for the three respective characteristics. The age trend for all genetic parameters was more stable for DBH than for height and volume. Family (backward) selection for DBH at age 21 resulted in a 9.6% gain and indirectly 5.1 and 21.0% gains for height and volume, respectively, compared to 5.2 and 20.1% gains for height and volume, respectively, when selection for these characteristics is done directly. DBH is an effective proxy trait for selection in growth. DBH is also less susceptible than height to typhoon damage, which frequently afflicts tree plantations in Taiwan. Therefore, DBH should be considered as the primary trait for selection for Konishii fir in Taiwan. Konishii fir is a genetically variable species despite its limited geographic range, and is fast growing which makes it a viable candidate species for tree improvement.

scholarly journals Estimation of Genetic Parameters and Selection of Superior Genotypes in a 12-Year-Old Clonal Norway Spruce Field Trial after Phenotypic Assessment Using a UAV

Forests ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 992
Author(s):  
Mateusz Liziniewicz ◽  
Liviu Theodor Ene ◽  
Johan Malm ◽  
Jens Lindberg ◽  
Andreas Helmersson ◽  
...  
Keyword(s):  
Norway Spruce ◽  
Field Trial ◽  
Measurement Techniques ◽  
Tree Height ◽  
Tree Breeding ◽  
Breeding Program ◽  
Average Height ◽  
Individual Tree ◽  
Breeding Populations ◽  
Additive Regression

Height is a key trait in the indices applied when selecting genotypes for use in both tree breeding populations and production populations in seed orchards. Thus, measurement of tree height is an important activity in the Swedish Norway spruce breeding program. However, traditional measurement techniques are time-consuming, expensive, and often involve work in bad weather, so automatization of the data acquisition would be beneficial. Possibilities for such automatization have been opened by advances in unmanned aerial vehicle (UAV) technology. Therefore, to test its applicability in breeding programs, images acquired by a consumer-level UAV (DJI Phantom 4 Pro V2.0) system were used to predict the height and breast height diameter of Norway spruce trees in a 12-year-old genetic field trial established with 2.0 × 2.0 m initial spacing. The tree heights were also measured in the field using an ultrasonic system. Three additive regression models with different numbers of predictor variables were used to estimate heights of individual trees. On stand level, the average height estimate derived from UAV data was 2% higher than the field-measured average. The estimation of family means was very accurate, but the genotype-level accuracy, which is crucial for selection in the Norway spruce breeding program, was not high enough. There was just ca. 60% matching of genotypes in groups selected using actual and estimated heights. In addition, heritability values calculated from the predicted values were underestimated and overestimated for height and diameter, respectively, with deviations from measurement-based estimates ranging between −19% and +12%. However, the use of more sophisticated UAV and camera equipment could significantly improve the results and enable automatic individual tree detection.

Individual Tree Basal Area Increment and Total Height Equations for Appalachian Mixed Hardwoods After Thinning

1986 ◽  
Vol 10 (2) ◽  
pp. 99-104 ◽  
Author(s):  
Wade C. Harrison ◽  
Thomas E. Burk ◽  
Donald E. Beck
Keyword(s):  
Basal Area ◽  
Tree Height ◽  
Basal Area Increment ◽  
Average Height ◽  
Regression Equations ◽  
White Oak ◽  
Annual Increment ◽  
Individual Tree ◽  
Total Height ◽  
Stand Basal Area

Abstract Growth response of various species to thinning in even-aged stands of Appalachian mixed hardwoods was predicted with species-specific regression equations. Periodic annual increment over a five-year period was expressed as a linear function of original tree basal area divided by breast height age and a thinning or competition index based on stand basal area. For most species, a combination of stand basal area before and after thinning served as the thinning index; for the five oak species studied, the index was simply stand basal area after thinning. Nonlinear regression equations were formulated to express total tree height as a function of dbh and average height of dominant and codominant white oak. The equations for tree basal area increment and total height may be applied to predict growth after thinning in Appalachian mixed hardwood stands. South J. Appl. For. 10:99-104, May 1986

Variable selection for estimating individual tree height using genetic algorithm and random forest

2022 ◽  
Vol 504 ◽  
pp. 119828
Author(s):  
Evandro Nunes Miranda ◽  
Bruno Henrique Groenner Barbosa ◽  
Sergio Henrique Godinho Silva ◽  
Cassio Augusto Ussi Monti ◽  
David Yue Phin Tng ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Random Forest ◽  
Variable Selection ◽  
Tree Height ◽  
Individual Tree ◽  
Selection For

Determining Site Index and Estimating Timber Volumes Without Measuring Heights

1994 ◽  
Vol 18 (1) ◽  
pp. 15-18 ◽  
Author(s):  
Robert L. Bailey ◽  
John R. Brooks
Keyword(s):  
Tree Height ◽  
Pinus Elliottii ◽  
Site Index ◽  
Slash Pine ◽  
Diameter Distribution ◽  
Stem Volume ◽  
Average Height ◽  
Time Saving ◽  
Individual Tree ◽  
Dominant Height

Abstract We present a time-saving method for predicting average dominant height, and thus site index, and predicting yield of a slash pine (Pinus elliottii Engelm.) plantation without measuring any tree heights. We identify a segment in the upper end of the diameter distribution where the average height of all trees is equal to average dominant height. The arithmetic mean diameter of these trees, called dominant height diameter (DHD), is used in a regression to predict average dominant height. With individual tree height prediction equations that use average dominant height and tree volume or weight equations that use tree height and dbh, plot volumes or weights can then be predicted. For 922 plots in slash pine plantations, total-stem volume per acre was predicted with an R2 of 0.978 with this method. South. J. Appl. For. 18(1):15-18.

scholarly journals Genetic parameters and efficiency of early selection for half rotation-aged growth and form traits in Pinus taeda in China

2013 ◽  
Vol 62 (1-6) ◽  
pp. 277-284 ◽  
Author(s):  
Huixiao Yang ◽  
Tianyi Liu ◽  
Chunxin Liu ◽  
Jinbang Wang ◽  
Kaer Chen ◽  
...  
Keyword(s):  
Pinus Taeda ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Early Selection ◽  
Direct Selection ◽  
Individual Tree ◽  
Stem Straightness ◽  
Selection For ◽  
Heritability Estimates

Abstract Genetic parameters for height (H), diameter at breast height (DBH), stem straightness (STR), and under crown clear bole height (CH) of loblolly pine (Pinus taeda L.) were estimated for 255 families (209 open pollinated (OP) and 46 controlled pollinated (CP) families) using a family model and an individual tree model at age 1, 2, 3, 5, 11, and 15 years. Heritability estimates for growth traits of individual trees at age 11 years were the highest (0.17-0.78), and those at age 15 years were the lowest (0.05-0.74). Heritability estimates for DBH, STR, and CH were lower than those for H. Genetic correlations between H and DBH were generally strongly positive, attained a maximum values at age 2 to 3, and declined slightly thereafter. The genetic correlations between CH at age 11 and both H and DBH at different ages were moderate. Age-age genetic correlations for growth traits were moderate to high (0.56-0.91) at age 5 for half-rotation age (15 years), indicating the opportunity exists for early selection. Indirect selection from the age 5 to 11 years for H and DBH could be expected to produce gains of over 50% and 35% respectively, for these two ages, relative to direct selection at age 15. Efficiencies of early selection for H and DBH indicated that growth at maturity could be improved by early selection.

scholarly journals Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications

2020 ◽  
Vol 13 (1) ◽  
pp. 77
Author(s):  
Tianyu Hu ◽  
Xiliang Sun ◽  
Yanjun Su ◽  
Hongcan Guan ◽  
Qianhui Sun ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Low Cost ◽  
Canopy Cover ◽  
Tree Height ◽  
Flying Height ◽  
Tree Level ◽  
Forest Site ◽  
Lidar System ◽  
Individual Tree ◽  
Gap Fraction

Accurate and repeated forest inventory data are critical to understand forest ecosystem processes and manage forest resources. In recent years, unmanned aerial vehicle (UAV)-borne light detection and ranging (lidar) systems have demonstrated effectiveness at deriving forest inventory attributes. However, their high cost has largely prevented them from being used in large-scale forest applications. Here, we developed a very low-cost UAV lidar system that integrates a recently emerged DJI Livox MID40 laser scanner (~$600 USD) and evaluated its capability in estimating both individual tree-level (i.e., tree height) and plot-level forest inventory attributes (i.e., canopy cover, gap fraction, and leaf area index (LAI)). Moreover, a comprehensive comparison was conducted between the developed DJI Livox system and four other UAV lidar systems equipped with high-end laser scanners (i.e., RIEGL VUX-1 UAV, RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE). Using these instruments, we surveyed a coniferous forest site and a broadleaved forest site, with tree densities ranging from 500 trees/ha to 3000 trees/ha, with 52 UAV flights at different flying height and speed combinations. The developed DJI Livox MID40 system effectively captured the upper canopy structure and terrain surface information at both forest sites. The estimated individual tree height was highly correlated with field measurements (coniferous site: R2 = 0.96, root mean squared error/RMSE = 0.59 m; broadleaved site: R2 = 0.70, RMSE = 1.63 m). The plot-level estimates of canopy cover, gap fraction, and LAI corresponded well with those derived from the high-end RIEGL VUX-1 UAV system but tended to have systematic biases in areas with medium to high canopy densities. Overall, the DJI Livox MID40 system performed comparably to the RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE systems in the coniferous site and to the Velodyne Puck LITE system in the broadleaved forest. Despite its apparent weaknesses of limited sensitivity to low-intensity returns and narrow field of view, we believe that the very low-cost system developed by this study can largely broaden the potential use of UAV lidar in forest inventory applications. This study also provides guidance for the selection of the appropriate UAV lidar system and flight specifications for forest research and management.

scholarly journals Adjudicating Perspectives on Forest Structure: How Do Airborne, Terrestrial, and Mobile Lidar-Derived Estimates Compare?

2021 ◽  
Vol 13 (12) ◽  
pp. 2297
Author(s):  
Jonathon J. Donager ◽  
Andrew J. Sánchez Meador ◽  
Ryan C. Blackburn
Keyword(s):  
Ponderosa Pine ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Basal Area ◽  
Tree Height ◽  
Absolute Error ◽  
Forest Monitoring ◽  
Individual Tree ◽  
Structural Configurations ◽  
Individual Trees

Applications of lidar in ecosystem conservation and management continue to expand as technology has rapidly evolved. An accounting of relative accuracy and errors among lidar platforms within a range of forest types and structural configurations was needed. Within a ponderosa pine forest in northern Arizona, we compare vegetation attributes at the tree-, plot-, and stand-scales derived from three lidar platforms: fixed-wing airborne (ALS), fixed-location terrestrial (TLS), and hand-held mobile laser scanning (MLS). We present a methodology to segment individual trees from TLS and MLS datasets, incorporating eigen-value and density metrics to locate trees, then assigning point returns to trees using a graph-theory shortest-path approach. Overall, we found MLS consistently provided more accurate structural metrics at the tree- (e.g., mean absolute error for DBH in cm was 4.8, 5.0, and 9.1 for MLS, TLS and ALS, respectively) and plot-scale (e.g., R2 for field observed and lidar-derived basal area, m2 ha−1, was 0.986, 0.974, and 0.851 for MLS, TLS, and ALS, respectively) as compared to ALS and TLS. While TLS data produced estimates similar to MLS, attributes derived from TLS often underpredicted structural values due to occlusion. Additionally, ALS data provided accurate estimates of tree height for larger trees, yet consistently missed and underpredicted small trees (≤35 cm). MLS produced accurate estimates of canopy cover and landscape metrics up to 50 m from plot center. TLS tended to underpredict both canopy cover and patch metrics with constant bias due to occlusion. Taking full advantage of minimal occlusion effects, MLS data consistently provided the best individual tree and plot-based metrics, with ALS providing the best estimates for volume, biomass, and canopy cover. Overall, we found MLS data logistically simple, quickly acquirable, and accurate for small area inventories, assessments, and monitoring activities. We suggest further work exploring the active use of MLS for forest monitoring and inventory.

Selection for rate and efficiency of lean gain in Hereford cattle 1. Selection pressure applied and direct responses

1990 ◽  
Vol 51 (1) ◽  
pp. 23-34 ◽  
Author(s):  
R. A. Mrode ◽  
C. Smith ◽  
R. Thompson
Keyword(s):  
Genetic Parameters ◽  
Control Line ◽  
Correlated Responses ◽  
Direct Response ◽  
Lean Growth ◽  
Hereford Cattle ◽  
Frozen Semen ◽  
Phenotypic Standard Deviation ◽  
Selection For ◽  
Selection Of

ABSTRACTSelection of bulls for rate and efficiency of lean gain was studied in a herd of Hereford cattle. There were two selection lines, one selected for lean growth rate (LGR) from birth to 400 days and the other for lean food conversion ratio (LFCR) from 200 to 400 days of age, for a period of 8 years. A control line bred by frozen semen from foundation bulls was also maintained. Generation interval was about 2·4 years and average male selection differentials, per generation were 1·2 and — 1·1 phenotypic standard deviation units for LGR and LFCR respectively.Genetic parameters and responses to selection were estimated from the deviation of the selected lines from a control line and by restricted maximum likelihood (REML) techniques on the same material. Realized heritabilities were 0·40 (s.e. 0·12) for LGR and 0·40 (s.e. 0·13) for LFCR using the control line. Corresponding estimates from REML were 0·42 (s.e. 0·10) and 0·37 (s.e. 0·14). The estimate of the genetic correlation between LGR and LFCR was about — 0·69 (s.e. 0·12) using REML.The estimates of direct annual genetic change using deviations from the control were 3·6 (s.e. 1·3) g/day for LGR and — 0·14 (s.e. 0·07) kg food per kg lean gain for LFCR. Corrsponding estimates from REML were similar but more precisely estimated. The correlated responses for LFCR in the LGR line was higher than the direct response for LFCR.

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