Modeling individual tree growth by fusing diameter tape and increment core data

Tree growth estimation is a challenging task as difficulties associated with data collection and inference often result in inaccurate estimates. Two main methods for tree growth estimation are diameter tape measurements and increment cores. The former involves repeatedly measuring tree diameters with a cloth or metal tape whose scale has been adjusted to give diameter readings directly. This approach has the advantage that diameters can be measured rapidly. However, because of the substantial error involved during tape measurements, negative diameter increments are often observed. Alternatively, annual radius increment data can be obtained by taking tree cores and averaging repeated measurements of the ring widths. Acquiring and analyzing tree cores is a time-consuming process, and taking multiple cores may have adverse effects on tree health. Therefore, radius increment data are typically only available for a subset of trees within a stand. We offer a fusion of the data sources, which enables us to accommodate missingness and to borrow strength across individuals. It enables individual tree-level inference as well as average or stand level inference. Our model recognizes that tree growth in a given year depends upon tree size at the start of the year as well as levels of appropriate covariates operating in that year. We apply our modeling to a fairly large dataset taken from two forest stands at Coweeta Hydrologic Laboratory in the southern Appalachians collected from 1991 to 2011. s

Duke Scholars

Author Alan E. Gelfand Statistical Science

Author Fan Li Statistical Science