Distribution of cavity trees in midwestern old-growth and second-growth forests

2003 ◽  
Vol 33 (8) ◽  
pp. 1481-1494 ◽  
Author(s):  
Zhaofei Fan ◽  
Stephen R Shifley ◽  
Martin A Spetich ◽  
Frank R Thompson III ◽  
David R Larsen

We used classification and regression tree analysis to determine the primary variables associated with the occurrence of cavity trees and the hierarchical structure among those variables. We applied that information to develop logistic models predicting cavity tree probability as a function of diameter, species group, and decay class. Inventories of cavity abundance in old-growth hardwood forests in Missouri, Illinois, and Indiana found that 8–11% of snags had at least one visible cavity (as visually detected from the ground; smallest opening [Formula: see text]2 cm diameter), about twice the percentage for live trees. Five percent of live trees and snags had cavities on mature ([Formula: see text]110 years) second-growth plots on timberland in Missouri. Because snags accounted for typically no more than 10% of standing trees on any of these sites, 80–85% of cavity trees are living trees. Within the subset of mature and old-growth forests, the presence of cavities was strongly related to tree diameter. Classification and regression tree models indicated that 30 cm diameter at breast height (DBH) was a threshold size useful in distinguishing cavity trees from noncavity trees in the old-growth sample. There were two diameter thresholds in the mature second-growth sample: 18 and 44 cm DBH. Cavity tree probability differed by species group and increased with increasing decay class.

2006 ◽  
Vol 36 (7) ◽  
pp. 1740-1748 ◽  
Author(s):  
Zhaofei Fan ◽  
John M Kabrick ◽  
Stephen R Shifley

Tree survival or mortality is a stochastic process and highly variable over time and space. Many factors contribute to this process, including tree age, tree size, competition, drought, insects, and diseases. Traditional parametric approaches to modeling tree survival or mortality are often unable to capture this variation, especially in natural, mixed-species forests. We analyzed tree survival in Missouri Ozark oak forests using a combination of classification and regression tree (CART) and survival analysis of more than 35 000 trees with DBH >11 cm measured four times between 1992 and 2002. We employed a log-rank test with CART to classify trees into seven disjoint survival groups and used a nonparametric Kaplan–Meier (product limit) method to estimate tree survival rate and construct confidence intervals for each survival group. We found that tree species, crown class, DBH, and basal area of larger trees were the variables most closely associated with differences in tree survival rates. In these mature oak forests, mortality for the red oak species group was three to six times greater than for the white oak, hickory, or shortleaf pine species group. The results provide practical information to guide development of silvicultural prescriptions to reduce losses to mortality.


2019 ◽  
Vol 83 (5) ◽  
pp. 875-880 ◽  
Author(s):  
Shaik Mohammad Naushad ◽  
Patchava Dorababu ◽  
Yedluri Rupasree ◽  
Addepalli Pavani ◽  
Digumarti Raghunadharao ◽  
...  

2016 ◽  
Vol 33 (1) ◽  
pp. 45-53 ◽  
Author(s):  
Manoj Khandelwal ◽  
Danial Jahed Armaghani ◽  
Roohollah Shirani Faradonbeh ◽  
Mohan Yellishetty ◽  
Muhd Zaimi Abd Majid ◽  
...  

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