scholarly journals Gamma Regression Model with Nuisance Baseline for Tree Growth Data

FORMATH ◽  
2021 ◽  
Vol 20 (0) ◽  
pp. n/a
Author(s):  
Tetsuji Tonda ◽  
Ken-ichi Kamo ◽  
Masayoshi Takahashi
Keyword(s):  
Regression Model ◽  
Tree Growth ◽  
Growth Data

Modeling the numerical relationships between chronic ambient sulphur dioxide exposures and tree growth

1996 ◽  
Vol 26 (4) ◽  
pp. 689-695 ◽  
Author(s):  
A.H. Legge ◽  
M. Nosal ◽  
S.V. Krupa
Keyword(s):  
Regression Model ◽  
Tree Growth ◽  
Basal Area ◽  
Basal Area Increment ◽  
Sampling Location ◽  
Model Parameters ◽  
Processing Plant ◽  
Pine Tree ◽  
Sampling Locations ◽  
Increment Growth

An exponential growth curve model was developed for Pinuscontorta Dougl. ex Loud. var. latifolia Engelm. × Pinusbanksiana Lamb, (lodgepole × jack pine) trees from basal area increment data collected from five ecologically analogous sampling locations (AI to AV) in the vicinity of a sulphur recovery sour gas processing plant emitting sulphur (S) gases (mainly SO2) in the West Whitecourt study area near the town of Whitecourt in west-central Alberta, Canada. The mean basal area increment growth declined by 1.2%, 1.4%, 0.8%, and 0.6% between 1959 and 1981 at sampling locations AI AII, AIII and AIV, respectively, in comparison to the reference sampling location, AV. Since 1974 there has been an increase in wood production at the impacted sites, AI to AIV. This was most likely the result of the significant and progressive reductions in total sulphur gas emissions from 1963 to 1981, of 58 403 to 6782 t S/year, respectively. A multivariate nonlinear, polynomial Fourier regression model was applied to explain the relationships between the ambient SO2 exposures at the five sampling locations and changes in pine tree basal area increment growth. The regression model included the ambient SO2 exposure parameters: (1) number of episodes (an episode is equivalent to single or successive occurrences of 0.5-h mean concentrations of ≥10 ppb); (2) cumulative integral of exposures (concentration with respect to time); and (3) peak episodal concentrations. The model parameters were estimated using the least squares approach. The MPF regression model captured the actual effects of the episodicity of SO2 exposures on radial tree growth of pine species and provided a high degree of forecasting power because of the use of the integral of the SO2 exposures. Peak episodal SO2 concentrations or the number of episodes appeared not to play as important a role in the model as the integral.

scholarly journals Geographic Patterns and Stand Variables Influencing Growth and Vigor of Populus tremuloides in the Sierra Nevada (USA)

ISRN Forestry ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
John-Pascal Berrill ◽  
Christa M. Dagley
Keyword(s):  
Sierra Nevada ◽  
Populus Tremuloides ◽  
Tree Growth ◽  
Stand Density ◽  
Tree Height ◽  
Lake Tahoe ◽  
Growth Data ◽  
Lake Tahoe Basin ◽  
Density Control ◽  
Geographic Patterns

Awareness of geographic patterns and stand variables that influence tree growth will help forest managers plan appropriate management and monitoring strategies. We quantified influences of stand location, species composition, stand density, and tree size on aspen tree growth and vigor around the Lake Tahoe Basin in the Sierra Nevada Mountains of California and Nevada, USA. Radial growth data were taken from increment cores. Aspen trees on the south and west sides of the lake grew 20–25% faster than aspen in north and east side stands. Diameter growth at 2,400 m elevation was 58% of growth at 1,900 m near lake level. Aspen grew faster with less competition from neighbor trees. At any level of competition, aspen growth was slower beside conifer neighbors and correlated with crown ratio (CR: length of live crown relative to total tree height, a proxy for tree vigor). Analysis of independent CR data for 707 aspen trees in nine additional stands indicated that aspen had smaller crowns in the presence of greater competition, and that composition of neighbor trees also affected CR: aspen trees had shorter crowns in the presence of conifer at higher stand densities. Taken collectively, our analyses point towards a cascading decline in aspen growth and vigor incited by succession of aspen stands to conifers. Our findings suggest that conifer removal and stand density control in aspen-conifer stands at Lake Tahoe will enhance aspen growth and vigor.

scholarly journals Novel insights from point-dendrometers in an urban setting: linking environmental variation to fluctuations in stem radius

2020 ◽  
Author(s):  
Kevin L. Griffin ◽  
Thomas G. Harris ◽  
Sarah Bruner ◽  
Patrick McKenzie ◽  
Jeremy Hise
Keyword(s):  
Ecosystem Services ◽  
Tree Growth ◽  
Ecological Systems ◽  
Urban Environments ◽  
Urban Setting ◽  
Live Streaming ◽  
Growth Data ◽  
Suburban Areas ◽  
Interaction Terms ◽  
Predictive Understanding

AbstractBackgroundThe unique environment of urban/suburban areas affects tree growth in surprising and currently unrecognized ways. Real-time monitoring of tree growth could provide novel information about these trees and the myriad ecosystem services they provide.MethodsInternet enabled, high-resolution point dendrometers were installed on four trees in Southampton, NY. The instruments, along with a weather station, streamed data to a project web page that was updated once an hour. (https://ecosensornetwork.com).ResultsRadial growth of spruce began April 14 after the accumulation of 69.7 °C growing degrees days and ended September 7th. Cedar growth began later (4/26), after the accumulation of 160.6 °C and ended later (11/3). During our observations, these three modest suburban trees sequestered 108.3 kg of CO2. Growth took place primarily at night and was best predicted by a combination of air temperature, soil moisture, VPD and interaction terms.ConclusionsThis project’s two-year time series provided insights into the growth of trees in a residential area. Linking tree growth to fluctuations in environmental conditions facilitates the development of a mechanistic predictive understanding useful for ecosystem management and growth forecasting across future altering climates. Live-streaming tree growth data enables a deeper appreciation of the biological activity of trees and the ecosystem services they provide in urban environments and thus can be a powerful tool connecting urban social and ecological systems.

scholarly journals Influence of Mine Soil Properties on White Oak Seedling Growth: A Proposed Mine Soil Classification Model

2007 ◽  
Vol 31 (2) ◽  
pp. 99-107 ◽  
Author(s):  
Julia M. Showalter ◽  
James A. Burger ◽  
Carl E. Zipper ◽  
John M. Galbraith ◽  
Patricia F. Donovan
Keyword(s):  
Regression Model ◽  
Soil Properties ◽  
Seedling Growth ◽  
Tree Growth ◽  
Tree Height ◽  
Soil Classification ◽  
Classification Model ◽  
Slope Aspect ◽  
Mine Soil ◽  
White Oak

Abstract Appalachian landowners are becoming increasingly interested in restoring native hardwood forest on reclaimed mined land. Trees are usually planted in topsoil substitutes consisting of blasted rock strata, and reforestation attempts using native hardwoods are often unsuccessful due to adverse soil properties. The purpose of this study was to determine which mine soil properties most influence white oak (Quercus alba L.) seedling growth, and to test whether these properties are reflected adequately in a proposed mine soil classification model developed for application in field assessments of mine soil suitability for reforestation. Seventy-two 3-year-old white oaks were randomly selected across a reclaimed site in southwestern Virginia that varied greatly in spoil/site properties. Tree height was measured and soil samples adjacent to each tree were analyzed for physical, chemical, and biological properties. Our proposed mined land classification model used rock type, compaction, and slope aspect as mapping criteria. Tree height, ranging from 15.2 to 125.0 cm, was regressed against mine soil and site properties. Mapping units were not well correlated with differences in tree height. Microbial biomass, pH, exchangeable potassium, extractable inorganic nitrogen, texture, aspect, and extractable phosphorous accounted for 52% of the variability in tree growth. The regression model shows that white oaks were most successful on northeast-facing aspects, in slightly acidic, sandy loam, fertile mine soils that are conducive to microbial activity. Nutrient availability, although found to be highly influential on tree growth, was not adequately represented in the classification model. We recommend that pH be included as a classification criterion, because it was correlated with all nutrient variables in the regression model.

Adjustment of estimated tree growth rates in northern California conifers for changes in precipitation levels

1998 ◽  
Vol 28 (8) ◽  
pp. 1241-1248 ◽  
Author(s):  
Lee C Wensel ◽  
Eric C Turnblom
Keyword(s):  
Tree Growth ◽  
Growth Rates ◽  
Initial Conditions ◽  
Growth Parameters ◽  
Forest Growth ◽  
Northern California ◽  
Growth Data ◽  
Short Term ◽  
Individual Tree ◽  
Periodic Growth

Even with similar initial conditions, observed forest growth rates on permanent sample plots in the conifer region of northern California differ for different periods. Thus, individual-tree growth models built with growth parameters estimated from data from one period may not produce accurate estimates for another period unless some allowance is made for this variation in growth rates. Variation in growth rates of northern California conifers through time has been shown to be correlated with precipitation changes. A method is presented that adjusts periodic growth estimates for variation in precipitation between periods. This provides a basis for adjusting short-term growth data for making long-term growth projections. Perhaps more importantly, short-term inventory updates might be made more accurately.

scholarly journals On the modelling of tropical tree growth: the importance of intra-specific trait variation, non-linear functions and phenotypic integration

2020 ◽  
Author(s):  
Jie Yang ◽  
Xiaoyang Song ◽  
Min Cao ◽  
Xiaobao Deng ◽  
Wenfu Zhang ◽  
...  
Keyword(s):  
Tree Growth ◽  
Bayesian Models ◽  
Species Level ◽  
Linear Functions ◽  
Plant Performance ◽  
Growth Data ◽  
Growth And Survival ◽  
Individual Level ◽  
The Individual ◽  
Individual Trees

Abstract Background and Aims The composition and dynamics of plant communities arise from individual-level demographic outcomes, which are driven by interactions between phenotypes and the environment. Functional traits that can be measured across plants are frequently used to model plant growth and survival. Perhaps surprisingly, species average trait values are often used in these studies and, in some cases, these trait values come from other regions or averages calculated from global databases. This data aggregation potentially results in a large loss of valuable information that probably results in models of plant performance that are weak or even misleading. Methods We present individual-level trait and fine-scale growth data from >500 co-occurring individual trees from 20 species in a Chinese tropical rain forest. We construct Bayesian models of growth informed by theory and construct hierarchical Bayesian models that utilize both individual- and species-level trait data, and compare these models with models only using individual-level data. Key Results We show that trait–growth relationships measured at the individual level vary across species, are often weak using commonly measured traits and do not align with the results of analyses conducted at the species level. However, when we construct individual-level models of growth using leaf area ratio approximations and integrated phenotypes, we generated strong predictive models of tree growth. Conclusions Here, we have shown that individual-level models of tree growth that are built using integrative traits always outperform individual-level models of tree growth that use commonly measured traits. Furthermore, individual-level models, generally, do not support the findings of trait–growth relationships quantified at the species level. This indicates that aggregating trait and growth data to the species level results in poorer and probably misleading models of how traits are related to tree performance.

Two-year tree growth patterns investigated from monthly girth records using dendrometer bands in a wet evergreen forest in India

2000 ◽  
Vol 16 (3) ◽  
pp. 429-446 ◽  
Author(s):  
Raphaël Pélissier ◽  
Jean-pierre Pascal
Keyword(s):  
Growth Rate ◽  
Tree Growth ◽  
Growth Patterns ◽  
Annual Growth ◽  
Evergreen Forest ◽  
Annual Growth Rate ◽  
Growth Data ◽  
Growth Profiles ◽  
Dendrometer Bands ◽  
The Mean

With the aim of characterizing tree growth patterns, this paper re-examines the growth data of 100 selected trees belonging to 24 species that were recorded monthly in a 0.2-ha plot of a wet evergreen forest in the Western Ghats of India during the period 1980–82 using dendrometer bands. The mean growth profile, combining all of the selected trees, showed: (a) a significantly lower annual growth rate during the second year of survey which seemed to be negatively related to monsoon precipitation; (b) significant intra-annual growth variation clearly related to the regular alternation between a period of heavy rain and a quite long dry season of the monsoon climatic regime. Analysis of the variability of the individual smoothed growth profiles representing the 2-y trend of the growth data showed that: (a) the mean growth rate depended on a combination of an intrinsic endogenous variable (the structural class grouping species according to their maximum size), a tree size variable (tree diameter at breast height, dbh) and a neighbourhood variable (the number of taller neighbours in a 10-m radius); (b) the sudden change in growth rate from one year to the other was not predictable using these variables. The amplitude of the seasonal variations, investigated from the detrended growth profiles, appeared to be dependent on a combination of tree dbh and the number of taller neighbours in a 10-m radius. A co-inertia analysis of the smoothed and the detrended growth profiles indicated that the trees with fast growth also exhibited high seasonal variation. It is suggested that fast growing trees are those with favourable crown positions, which are consequently subject to high transpiration rates due to radiation and wind exposure.

scholarly journals A likelihood perspective on tree-ring standardization: eliminating modern sample bias

2013 ◽  
Vol 9 (4) ◽  
pp. 4499-4551 ◽  
Author(s):  
J. Cecile ◽  
C. Pagnutti ◽  
M. Anand
Keyword(s):  
Tree Ring ◽  
Tree Growth ◽  
Fixed Effects ◽  
Information Criteria ◽  
Systematic Bias ◽  
Growth Data ◽  
Individual Tree ◽  
Regional Curve Standardization ◽  
Sample Bias ◽  
Modern Sample

Abstract. It has recently been suggested that non-random sampling and differences in mortality between trees of different growth rates is responsible for a widespread, systematic bias in dendrochronological reconstructions of tree growth known as modern sample bias. This poses a serious challenge for climate reconstruction and the detection of long-term changes in growth. Explicit use of growth models based on regional curve standardization allow us to investigate the effects on growth due to age (the regional curve), year (the standardized chronology or forcing) and a new effect, the productivity of each tree. Including a term for the productivity of each tree accounts for the underlying cause of modern sample bias, allowing for more reliable reconstruction of low-frequency variability in tree growth. This class of models describes a new standardization technique, fixed effects standardization, that contains both classical regional curve standardization and flat detrending. Signal-free standardization accounts for unbalanced experimental design and fits the same growth model as classical least-squares or maximum likelihood regression techniques. As a result, we can use powerful and transparent tools such as R2 and Akaike's Information Criteria to assess the quality of tree ring standardization, allowing for objective decisions between competing techniques. Analyzing 1200 randomly selected published chronologies, we find that regional curve standardization is improved by adding an effect for individual tree productivity in 99% of cases, reflecting widespread differing-contemporaneous-growth rate bias. Furthermore, modern sample bias produced a significant negative bias in estimated tree growth by time in 70.5% of chronologies and a significant positive bias in 29.5% of chronologies. This effect is largely concentrated in the last 300 yr of growth data, posing serious questions about the homogeneity of modern and ancient chronologies using traditional standardization techniques.

scholarly journals Inferência bootstrap para intervalo de confiança de modelo de regressão quadrática

2020 ◽  
Vol 42 ◽  
pp. e56
Author(s):  
Nicásio Gouveia ◽  
Ana Lúcia Souza Silva Mateus ◽  
Augusto Maciel da Silva ◽  
Leandro Ferreira ◽  
Suelen Carpenedo Aimi
Keyword(s):  
Confidence Interval ◽  
Regression Model ◽  
Critical Point ◽  
Confidence Intervals ◽  
Regression Models ◽  
Parametric Bootstrap ◽  
Height Growth ◽  
Point Estimate ◽  
Growth Data ◽  
Bootstrap Methodology

This study was carried out with the purpose of proposing a construction of confidence intervals for the critical point of a second degree regression model using a parametric bootstrap methodology. To obtain the distribution of the critical point, height growth data of the plants were used. From the analysis, the theoretical variables for the error and the confidence intervals were constructed. In addition, we examined different variance expressions with the purpose of the bootstrap-t confidence interval. The point estimate of the critical point was 10.7423 g L-1 of fertilizer doses without growth of C. canjerana plants. It was verified that the confidence intervals that considered the expression of the variance with the covariance between the regression models, present more satisfactory results, that is, results with more precision.

scholarly journals Tree Rings Reveal the Impact of Soil Temperature on Larch Growth in the Forest-Steppe of Siberia

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1765
Author(s):  
Liliana V. Belokopytova ◽  
Dina F. Zhirnova ◽  
David M. Meko ◽  
Elena A. Babushkina ◽  
Eugene A. Vaganov ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Tree Ring ◽  
Air Temperature ◽  
Tree Growth ◽  
Ring Width ◽  
Forest Steppe ◽  
Growth Data ◽  
Maximum Correlation ◽  
Substantial Impact ◽  
The Impact

Dendroclimatology has focused mainly on the tree growth response to atmospheric variables. However, the roots of trees directly sense the “underground climate,” which can be expected to be no less important to tree growth. Data from two meteorological stations approximately 140 km apart in southern Siberia were applied to characterize the spatiotemporal dynamics of soil temperature and the statistical relationships of soil temperature to the aboveground climate and tree-ring width (TRW) chronologies of Larix sibirica Ledeb. from three forest–steppe stands. Correlation analysis revealed a depth-dependent delay in the maximum correlation of TRW with soil temperature. Temperatures of both the air and soil (depths 20–80 cm) were shown to have strong and temporally stable correlations between stations. The maximum air temperature is inferred to have the most substantial impact during July–September (R = −0.46–−0.64) and early winter (R = 0.39–0.52). Tree-ring indices reached a maximum correlation with soil temperature at a depth of 40 cm (R = −0.49–−0.59 at 40 cm) during April–August. High correlations are favored by similar soil characteristics at meteorological stations and tree-ring sites. Cluster analysis of climate correlations for individual trees based on the K-means revealed groupings of trees driven by microsite conditions, competition, and age. The results support a possible advantage of soil temperature over air temperature for dendroclimatic analysis of larch growth in semiarid conditions during specific seasons.

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