Growth-dependent tree mortality models based on tree rings

2003 ◽  
Vol 33 (2) ◽  
pp. 210-221 ◽  
Author(s):  
Christof Bigler ◽  
Harald Bugmann
Keyword(s):  
Norway Spruce ◽  
Tree Mortality ◽  
Time Windows ◽  
Growth Patterns ◽  
Linear Regression Models ◽  
Growth Trends ◽  
Mortality Model ◽  
Recent Growth ◽  
Mortality Models ◽  
The Impact

Mortality is a crucial element of population dynamics. However, tree mortality is not well understood, particularly at the individual level. The objectives of this study were to (i) determine growth patterns (growth levels and growth trends) over different time windows that can be used to discriminate between dead and living Norway spruce (Picea abies (L.) Karst.) trees, (ii) optimize the selection of growth variables in logistic mortality models, and (iii) assess the impact of competition on recent growth in linear regression models. The logistic mortality model that we developed for mature stands classified an average of nearly 80% of the 119 trees from one site correctly as being dead or alive. While more than 50% of the variability of recent growth of living trees can be attributed to the influence of competition, this percentage was only 25% for standing dead trees. The predictive power of the logistic mortality model was validated successfully at two additional sites, where 29 of 41 (71%) and 34 of 42 (81%) trees were classified correctly, respectively. This supports the generality of the mortality model for Norway spruce in subalpine forests of the Alps. We conclude that growth trends in addition to the commonly used growth level significantly improve the prediction of growth-dependent tree mortality of Norway spruce.

Improving tree mortality models by accounting for environmental influences

2007 ◽  
Vol 37 (11) ◽  
pp. 2106-2114 ◽  
Author(s):  
Henrik Hartmann ◽  
Christian Messier ◽  
Marilou Beaudet
Keyword(s):  
Tree Mortality ◽  
External Validation ◽  
Growth Patterns ◽  
External Factors ◽  
Model Parameters ◽  
Similar Frequency ◽  
Growth Series ◽  
Recent Growth ◽  
Dead Trees ◽  
The Impact

Tree-ring chronologies have been widely used in studies of tree mortality where variables of recent growth act as an indicator of tree physiological vigour. Comparing recent radial growth of live and dead trees thus allows estimating probabilities of tree mortality. Sampling of mature dead trees usually provides death-year distributions that may span over years or decades. Recent growth of dead trees (prior to death) is then computed during a number of periods, whereas recent growth (prior to sampling) for live trees is computed for identical periods. Because recent growth of live and dead trees is then computed for different periods, external factors such as disturbance or climate may influence growth rates and, thus, mortality probability estimations. To counteract this problem, we propose the truncating of live-growth series to obtain similar frequency distributions of the “last year of growth” for the populations of live and dead trees. In this paper, we use different growth scenarios from several tree species, from several geographic sources, and from trees with different growth patterns to evaluate the impact of truncating on predictor variables and their selection in logistic regression analysis. Also, we assess the ability of the resulting models to accurately predict the status of trees through internal and external validation. Our results suggest that the truncating of live-growth series helps decrease the influence of external factors on growth comparisons. By doing so, it reinforces the growth–vigour link of the mortality model and enhances the model’s accuracy as well as its general applicability. Hence, if model parameters are to be integrated in simulation models of greater geographical extent, truncating may be used to increase model robustness.

scholarly journals Radial Growth Patterns Associated with Tree Mortality in Nothofagus pumilio Forest

Forests ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 489 ◽  
Author(s):  
Milagros Rodríguez-Catón ◽  
Ricardo Villalba ◽  
Ana Srur ◽  
A. Park Williams
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Forest Dynamics ◽  
Radial Growth ◽  
Tree Mortality ◽  
Growth Patterns ◽  
Severe Drought ◽  
Nothofagus Pumilio ◽  
Total Size ◽  
Growth Trends

Tree mortality is a key process in forest dynamics. Despite decades of effort to understand this process, many uncertainties remain. South American broadleaf species are particularly under-represented in global studies on mortality and forest dynamics. We sampled monospecific broadleaf Nothofagus pumilio forests in northern Patagonia to predict tree mortality based on stem growth. Live or dead conditions in N. pumilio trees can be predicted with high accuracy using growth rate as an explanatory variable in logistic models. In Paso Córdova (CO), Argentina, where the models were calibrated, the probability of death was a strong negative function of radial growth, particularly during the six years prior to death. In addition, negative growth trends during 30 to 45 years prior to death increased the accuracy of the models. The CO site was affected by an extreme drought during the summer 1978–1979, triggering negative trends in radial growth of many trees. Individuals showing below-average and persistent negative trends in radial growth are more likely to die than those showing high growth rates and positive growth trends in recent decades, indicating the key role of droughts in inducing mortality. The models calibrated at the CO site showed high verification skill by accurately predicting tree mortality at two independent sites 76 and 141 km away. Models based on relative growth rates showed the highest and most balanced accuracy for both live and dead individuals. Thus, the death of individuals across different N. pumilio sites was largely determined by the growth rate relative to the total size of the individuals. Our findings highlight episodic severe drought as a triggering mechanism for growth decline and eventual death for N. pumilio, similar to results found previously for several other species around the globe. In the coming decades, many forests globally will be exposed to more frequent and/or severe episodes of reduced warm-season soil moisture. Tree-ring studies such as this one can aid prediction of future changes in forest productivity, mortality, and composition.

Optimisation of tree mortality models based on growth patterns

2006 ◽  
Vol 197 (1-2) ◽  
pp. 196-206 ◽  
Author(s):  
Jan Wunder ◽  
Christof Bigler ◽  
Björn Reineking ◽  
Lorenz Fahse ◽  
Harald Bugmann
Keyword(s):  
Tree Mortality ◽  
Growth Patterns ◽  
Mortality Models

Extending the range of applicability of an individual tree mortality model

1990 ◽  
Vol 20 (8) ◽  
pp. 1212-1218 ◽  
Author(s):  
David A. Hamilton Jr.
Keyword(s):  
Tree Mortality ◽  
Data Sets ◽  
Habitat Types ◽  
Individual Tree ◽  
Independent Variables ◽  
Mortality Model ◽  
Mortality Models ◽  
Range Of Values

Limits are frequently encountered in the range of values of independent variables included in data sets used to develop individual tree mortality models. If the resulting model is to be utilized, its ability to extrapolate to conditions outside these limits must be evaluated. This paper describes the development and evaluation of six assumptions required to extend the range of applicability of an individual tree mortality model previously described. The assumptions deal with mortality in very dense stands, mortality for very small trees, mortality on habitat types and regions poorly represented in the data, and mortality for species poorly represented in the data.

Differential impacts of calcium and aluminum treatments on sugar maple and American beech growth dynamics

2015 ◽  
Vol 45 (1) ◽  
pp. 52-59 ◽  
Author(s):  
Joshua M. Halman ◽  
Paul G. Schaberg ◽  
Gary J. Hawley ◽  
Christopher F. Hansen ◽  
Timothy J. Fahey
Keyword(s):  
Sugar Maple ◽  
Tree Mortality ◽  
Growth Dynamics ◽  
Growth Patterns ◽  
Forest Composition ◽  
Ice Storm ◽  
Al Tolerance ◽  
Annual Increment ◽  
American Beech ◽  
The Impact

Acid deposition induced losses of calcium (Ca) from northeastern forests have had negative effects on forest health for decades, including the mobilization of potentially phytotoxic aluminum (Al) from soils. To evaluate the impact of changes in Ca and Al availability on sugar maple (Acer saccharum Marsh.) and American beech (Fagus grandifolia Ehrh.) growth and forest composition following a major ice storm in 1998, we measured xylem annual increment, foliar cation concentrations, American beech root sprouting, and tree mortality at the Hubbard Brook Experimental Forest (Thornton, New Hampshire) in control plots and in plots amended with Ca or Al (treated plots) beginning in 1995. Dominant sugar maple trees were unaffected by the treatment, but nondominant sugar maple tree growth responded positively to Ca treatment. Although plots were mainly composed of sugar maple, American beech experienced the greatest growth on Al-treated plots. Increases in tree mortality on Al-treated plots may have released surviving American beech and increased their growth. The Al tolerance of American beech and the Ca:Al sensitivity of sugar maple contributed to divergent growth patterns that influenced stand productivity and composition. Given that acidic inputs are expected to continue, the growth dynamics associated with Al treatment may have direct relevance to future conditions in native forests.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Análise da relação entre O3, NO e NO2 usando técnicas de regressão linear múltipla.

GEOgraphia ◽  
2018 ◽  
Vol 20 (43) ◽  
pp. 124
Author(s):  
Amaury De Souza ◽  
Priscilla V Ikefuti ◽  
Ana Paula Garcia ◽  
Debora A.S Santos ◽  
Soetania Oliveira
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Nitrogen Dioxide ◽  
Multiple Linear Regression ◽  
Quality Parameters ◽  
Environmental Pollutant ◽  
Environmental Research ◽  
Linear Regression Models ◽  
Mato Grosso ◽  
The Impact

Análise e previsão de parâmetros de qualidade do ar são tópicos importantes da pesquisa atmosférica e ambiental atual, devido ao impacto causado pela poluição do ar na saúde humana. Este estudo examina a transformação do dióxido de nitrogênio (NO2) em ozônio (O3) no ambiente urbano, usando o diagrama de séries temporais. Foram utilizados dados de concentração de poluentes ambientais e variáveis meteorológicas para prever a concentração de O3 na atmosfera. Foi testado o emprego de modelos de regressão linear múltipla como ferramenta para a predição da concentração de O3. Os resultados indicam que o valor da temperatura e a presença de NO2 influenciam na concentração de O3 em Campo Grande, capital do Estado do Mato Grosso do Sul. Palavras-chave: Ozônio. Dióxido de nitrogênio. Séries cronológicas. Regressões. ANALYSIS OF THE RELATIONSHIP BETWEEN O3, NO AND NO2 USING MULTIPLE LINEAR REGRESSION TECHNIQUES.Abstract: Analysis and prediction of air quality parameters are important topics of current atmospheric and environmental research due to the impact caused by air pollution on human health. This study examines the transformation of nitrogen dioxide (NO2) into ozone (O3) in the urban environment, using the time series diagram. Environmental pollutant concentration and meteorological variables were used to predict the O3 concentration in the atmosphere. The use of multiple linear regression models was tested as a tool to predict O3 concentration. The results indicate that the temperature value and the presence of NO2 influence the O3 concentration in Campo Grande, capital of the State of Mato Grosso do Sul.Keywords: Ozone. Nitrogen dioxide. Time series. Regressions. ANÁLISIS DE LA RELACIÓN ENTRE O3, NO Y NO2 UTILIZANDO MÚLTIPLES TÉCNICAS DE REGRESIÓN LINEAL.Resumen: Análisis y previsión de los parámetros de calidad del aire son temas importantes de la actual investigación de la atmósfera y el medio ambiente, debido al impacto de la contaminación atmosférica sobre la salud humana. Este estudio examina la transformación del dióxido de nitrógeno (NO2) en ozono (O3) en el entorno urbano, utilizando el diagrama de series de tiempo. Las concentraciones de los contaminantes ambientales de datos y variables climáticas fueron utilizadas para predecir la concentración de O3 en la atmósfera. El uso de múltiples modelos de regresión lineal como herramienta para predecir la concentración de O3 se puso a prueba. Los resultados indican que el valor de la temperatura y la presencia de NO2 influyen en la concentración de O3 en Campo Grande, capital del Estado de Mato Grosso do Sul.Palabras clave: Ozono. Dióxido de nitrógeno. Series de tiempo. Regresiones.

scholarly journals Reply to “Comment on ‘The Impact of Recent Forcing and Ocean Heat Uptake Data on Estimates of Climate Sensitivity’”

2020 ◽  
Vol 33 (1) ◽  
pp. 397-404 ◽  
Author(s):  
Nicholas Lewis ◽  
Judith Curry
Keyword(s):  
Time Windows ◽  
Internal Variability ◽  
Historical Record ◽  
Cmip5 Models ◽  
Temperature Record ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Total Uncertainty ◽  
The Impact ◽  
The Relationship

AbstractCowtan and Jacobs assert that the method used by Lewis and Curry in 2018 (LC18) to estimate the climate system’s transient climate response (TCR) from changes between two time windows is less robust—in particular against sea surface temperature bias correction uncertainty—than a method that uses the entire historical record. We demonstrate that TCR estimated using all data from the temperature record is closely in line with that estimated using the LC18 windows, as is the median TCR estimate using all pairs of individual years. We also show that the median TCR estimate from all pairs of decade-plus-length windows is closely in line with that estimated using the LC18 windows and that incorporating window selection uncertainty would make little difference to total uncertainty in TCR estimation. We find that, when differences in the evolution of forcing are accounted for, the relationship over time between warming in CMIP5 models and observations is consistent with the relationship between CMIP5 TCR and LC18’s TCR estimate but fluctuates as a result of multidecadal internal variability and volcanism. We also show that various other matters raised by Cowtan and Jacobs have negligible implications for TCR estimation in LC18.

scholarly journals A large database supports the use of simple models of post-fire tree mortality for thick-barked conifers, with less support for other species

Fire Ecology ◽  
2020 ◽  
Vol 16 (1) ◽  
Author(s):  
C. Alina Cansler ◽  
Sharon M. Hood ◽  
Phillip J. van Mantgem ◽  
J. Morgan Varner
Keyword(s):  
Tree Mortality ◽  
Characteristic Curve ◽  
Small Diameter ◽  
Fire Effects ◽  
Tree Level ◽  
Clear Understanding ◽  
Bark Thickness ◽  
Mortality Models ◽  
Species Specific ◽  
Stem Mortality

Abstract Background Predictive models of post-fire tree and stem mortality are vital for management planning and understanding fire effects. Post-fire tree and stem mortality have been traditionally modeled as a simple empirical function of tree defenses (e.g., bark thickness) and fire injury (e.g., crown scorch). We used the Fire and Tree Mortality database (FTM)—which includes observations of tree mortality in obligate seeders and stem mortality in basal resprouting species from across the USA—to evaluate the accuracy of post-fire mortality models used in the First Order Fire Effects Model (FOFEM) software system. The basic model in FOFEM, the Ryan and Amman (R-A) model, uses bark thickness and percentage of crown volume scorched to predict post-fire mortality and can be applied to any species for which bark thickness can be calculated (184 species-level coefficients are included in the program). FOFEM (v6.7) also includes 38 species-specific tree mortality models (26 for gymnosperms, 12 for angiosperms), with unique predictors and coefficients. We assessed accuracy of the R-A model for 44 tree species and accuracy of 24 species-specific models for 13 species, using data from 93 438 tree-level observations and 351 fires that occurred from 1981 to 2016. Results For each model, we calculated performance statistics and provided an assessment of the representativeness of the evaluation data. We identified probability thresholds for which the model performed best, and the best thresholds with either ≥80% sensitivity or specificity. Of the 68 models evaluated, 43 had Area Under the Receiver Operating Characteristic Curve (AUC) values ≥0.80, indicating excellent performance, and 14 had AUCs <0.7, indicating poor performance. The R-A model often over-predicted mortality for angiosperms; 5 of 11 angiosperms had AUCs <0.7. For conifers, R-A over-predicted mortality for thin-barked species and for small diameter trees. The species-specific models had significantly higher AUCs than the R-A models for 10 of the 22 models, and five additional species-specific models had more balanced errors than R-A models, even though their AUCs were not significantly different or were significantly lower. Conclusions Approximately 75% of models tested had acceptable, excellent, or outstanding predictive ability. The models that performed poorly were primarily models predicting stem mortality of angiosperms or tree mortality of thin-barked conifers. This suggests that different approaches—such as different model forms, better estimates of bark thickness, and additional predictors—may be warranted for these taxa. Future data collection and research should target the geographical and taxonomic data gaps and poorly performing models identified in this study. Our evaluation of post-fire tree mortality models is the most comprehensive effort to date and allows users to have a clear understanding of the expected accuracy in predicting tree death from fire for 44 species.

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