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.

scholarly journals An Individual-Tree Mortality Model for Complex Stands of Southeastern British Columbia

2005 ◽  
Vol 20 (2) ◽  
pp. 101-109 ◽  
Author(s):  
Hailemariam Temesgen ◽  
Stephen J. Mitchell
Keyword(s):  
British Columbia ◽  
Tree Species ◽  
Tree Mortality ◽  
Model Development ◽  
Mortality Rates ◽  
Average Deviation ◽  
Individual Tree ◽  
Permanent Sample Plots ◽  
Diameter Increment ◽  
Mortality Model

Abstract An individual-tree mortality model was developed for major tree species in complex stands (multi-cohort, multiaged, and mixed species) of southeastern British Columbia (BC), Canada. Data for 29,773 trees were obtained from permanent sample plots established in BC. Average annual diameter increment and mortality rates ranged from 0.08 to 0.17 cm/year and from 0.3 to 2.6%, respectively. Approximately 70% of the trees were used for model development and 30% for model evaluation. After evaluating the model, all 29,773 trees were used to fit the final model. A generalized logistic model was used to relate mortality to tree size, competition, and relative position of trees in a stand. The evaluation test demonstrated that the model appears to be well behaved and robust for the tree species considered in this study. For the eight tree species, the average deviation between observed and predicted annual mortality rates varied from −0.5 to 0.7% in the test data. West. J. Appl. For. 20(2):101–109.

scholarly journals Climatic information improves statistical individual-tree mortality models for three key species of Sichuan Province, China

2015 ◽  
Vol 72 (4) ◽  
pp. 443-455 ◽  
Author(s):  
Shuai Qiu ◽  
Ming Xu ◽  
Renqiang Li ◽  
Yunpu Zheng ◽  
Daniel Clark ◽  
...  
Keyword(s):  
Tree Mortality ◽  
Sichuan Province ◽  
Individual Tree ◽  
Mortality Models ◽  
Key Species ◽  
Climatic Information

scholarly journals Multi-scale assessment of post-fire tree mortality models

2019 ◽  
Vol 28 (1) ◽  
pp. 46 ◽  
Author(s):  
Tucker J. Furniss ◽  
Andrew J. Larson ◽  
Van R. Kane ◽  
James A. Lutz
Keyword(s):  
Spatial Pattern ◽  
Sierra Nevada ◽  
Tree Mortality ◽  
Spatial Scales ◽  
Large Diameter ◽  
Fire Effects ◽  
Point Pattern ◽  
Individual Tree ◽  
Mortality Models ◽  
Rim Fire

Post-fire tree mortality models are vital tools used by forest land managers to predict fire effects, estimate delayed mortality and develop management prescriptions. We evaluated the performance of mortality models within the First Order Fire Effects Model (FOFEM) software, and compared their performance to locally-parameterised models based on five different forms. We evaluated all models at the individual tree and stand levels with a dataset comprising 34174 trees from a mixed-conifer forest in the Sierra Nevada, California that burned in the 2013 Rim Fire. We compared stand-level accuracy across a range of spatial scales, and we used point pattern analysis to test the accuracy with which mortality models predict post-fire tree spatial pattern. FOFEM under-predicted mortality for the three conifers, possibly because of the timing of the Rim Fire during a severe multi-year drought. Locally-parameterised models based on crown scorch were most accurate in predicting individual tree mortality, but tree diameter-based models were more accurate at the stand level for Abies concolor and large-diameter Pinus lambertiana, the most abundant trees in this forest. Stand-level accuracy was reduced by spatially correlated error at small spatial scales, but stabilised at scales ≥1ha. The predictive error of FOFEM generated inaccurate predictions of post-fire spatial pattern at small scales, and this error could be reduced by improving FOFEM model accuracy for small trees.

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.

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.

Modeling individual tree mortality for white spruce in Alberta

2003 ◽  
Vol 163 (3) ◽  
pp. 209-222 ◽  
Author(s):  
Yuqing Yang ◽  
Stephen J Titus ◽  
Shongming Huang
Keyword(s):  
Tree Mortality ◽  
White Spruce ◽  
Individual Tree

scholarly journals Mendel’s pea crosses: varieties, traits and statistics

Hereditas ◽  
2019 ◽  
Vol 156 (1) ◽  
Author(s):  
T. H. Noel Ellis ◽  
Julie M. I. Hofer ◽  
Martin T. Swain ◽  
Peter J. van Dijk
Keyword(s):  
Statistical Analysis ◽  
Normal Distribution ◽  
Standard Normal Distribution ◽  
Data Sets ◽  
Crossing Experiments ◽  
Independent Variables ◽  
F2 Population ◽  
A Value ◽  
Segregation Ratios ◽  
Standard Normal

Abstract A controversy arose over Mendel’s pea crossing experiments after the statistician R.A. Fisher proposed how these may have been performed and criticised Mendel’s interpretation of his data. Here we re-examine Mendel’s experiments and investigate Fisher’s statistical criticisms of bias. We describe pea varieties available in Mendel’s time and show that these could readily provide all the material Mendel needed for his experiments; the characters he chose to follow were clearly described in catalogues at the time. The combination of character states available in these varieties, together with Eichling’s report of crosses Mendel performed, suggest that two of his F3 progeny test experiments may have involved the same F2 population, and therefore that these data should not be treated as independent variables in statistical analysis of Mendel’s data. A comprehensive re-examination of Mendel’s segregation ratios does not support previous suggestions that they differ remarkably from expectation. The χ2 values for his segregation ratios sum to a value close to the expectation and there is no deficiency of extreme segregation ratios. Overall the χ values for Mendel’s segregation ratios deviate slightly from the standard normal distribution; this is probably because of the variance associated with phenotypic rather than genotypic ratios and because Mendel excluded some data sets with small numbers of progeny, where he noted the ratios “deviate not insignificantly” from expectation.

scholarly journals Individual Tree Volume Equations for Red Pine in Michigan

1997 ◽  
Vol 14 (2) ◽  
pp. 53-58 ◽  
Author(s):  
Gary W. Fowler
Keyword(s):  
Red Pine ◽  
Data Sets ◽  
Regression Equations ◽  
Independent Data ◽  
Data Set ◽  
Individual Tree ◽  
Standing Trees ◽  
Pine Stands ◽  
Volume Estimates ◽  
Volume Equations

Abstract New total, pulpwood, sawtimber, and residual pulpwood cubic foot individual tree volume equations were developed for red pine in Michigan using nonlinear and multiple linear regression. Equations were also developed for Doyle, International 1/4 in., and Scribner bd ft volume, and a procedure for estimating pulpwood and residual pulpwood rough cord volumes from the appropriate cubic foot equations was described. Average ratios of residual pulpwood (i.e., topwood, cubic foot or cords) to mbf were developed for 7.6 and 9.6 in. sawtimber. Data used to develop these equations were collected during May-August 1983-1985 from 3,507 felled and/or standing trees from 27 stands in Michigan. Sixteen and 11 stands were located in the Upper and Lower Peninsulas, respectively. All equations were validated on an independent data set. Rough cord volume estimates based on the new pulpwood equation were compared with contemporary tables for 2 small cruise data sets. The new equations can be used to more accurately estimate total volume and volume per acre when cruising red pine stands. North. J. Appl. For. 14(2):53-58.

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