期刊
URBAN FORESTRY & URBAN GREENING
卷 61, 期 -, 页码 -出版社
ELSEVIER GMBH
DOI: 10.1016/j.ufug.2021.127093
关键词
Forest inventory; i-Tree; Storm preparation and response; Tree failure; Urban forestry; Wind and trees
资金
- National Science Foundation [DEB-1833041, DEB-1833018, DEB-1833149]
Urban trees are often influenced by factors like wind protection and sociodemographic context, with larger stem diameters and lower wind firmness being associated with higher likelihood of tree failure after hurricanes. Contrary to previous studies, higher species diversity was linked to increased tree failure. Geographically weighted regression models found that certain demographic factors were predictors of tree failure in some plots, but overall, the influence of neighboring trees or structures was not significant.
While often considered ?open grown,? urban trees are often found in relatively close proximity to neighboring trees, buildings, and other elements of urban infrastructure. These spatial arrangements may provide wind protection during severe weather events such as hurricanes. Beyond this very local scale, urban tree abundance and condition are often influenced by the greater sociodemographic context of the neighborhood or community where they are found. In an effort to assess the impact of these external factors on wind firmness after Hurricane Irma impacted Florida in 2017, we revisited three urban areas that had previously been inventoried using sample plots prior to the storm. At each plot we assessed storm damage and characterized surrounding protective elements (i.e., buildings and other trees) using a combination of ground-based and aerial approaches. This was then paired with block group level sociodemographic data derived from the United States Census. Logistic regression results confirmed previous research, showing that partial and whole tree failure were significantly more likely with a larger stem diameter (p = 0.001) and perceived/previously documented lower wind firmness (p = 0.004). However, our results disagreed with previous studies linking species diversity and resilience, showing tree failure was significantly more likely with higher Shannon Diversity Index (p = 0.008). A comparative geographically weighted logistic regression model also found that the higher proportions of African American residents and Hispanic residents, and the median age of residents were significant predictors of less likely tree failure in 30 %, 36 %, and 20 % of plots, respectively. However, this evidence was weak, compared to that of tree- and plot-level effects. Despite being a key predictor of interest, we did not see any significant protective effect from neighboring trees or structures.
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