Evaluating the Financial Performance of Timberland Investments in the United States - Bin Mei; Michael L. Clutter (Forest Science, 2010)
Timberland properties have gained increasing attention in recent decades. The attractiveness of this asset primarily lies in its unique feature—the biological growth, which is independent of traditional financial markets. Using both parametric and nonparametric approaches, in this study we reexamine the financial performance of private- and public-equity timberland investments in the United States. Private-equity timberland returns are proxied by the National Council of Real Estate Investment Fiduciaries Timberland Index, whereas public-equity timberland returns are proxied by the value-weighted returns on a dynamic portfolio of the US publicly traded forestry firms that had or have been managing timberlands. The parametric analyses reveal that private-equity timberland assets outperform the market and have low systematic risk, whereas public-equity timberland assets fare similarly to the market. The nonparametric analyses reveal that both private- and public-equity timberland assets have higher excess returns.

A Multilevel Approach to Individual Tree Survival Prediction - Charles E. Rose; Daniel B. Hall; Barry D. Shiver; Michael L. Clutter; Bruce Borders (Forest Science, 2006)
Traditionally, modeling of permanent plot individual tree survival has not considered the multiple sources of heterogeneity and correlation that may arise due to the multilevel data structure inherent in the design (e.g., clustering of trees within a plot). Permanent plots are sampled periodically; therefore, data are interval-censored because it is only known that a tree died between two successive measurement occasions. Here, we adopt the complementary log–log (CLL) function for modeling permanent plot interval-censored individual tree survival data. The CLL function is derived directly from the likelihood function of a fully specified statistical model that accounts for interval censoring. In addition, our CLL model considers silvicultural treatment effects on survival. Our data are from young permanent plot loblolly pine plantations that have been measured annually beginning at age 1 year. Each plot was randomly assigned one of four cultural treatments:control (C), herbicide (H), fertilization (F), and herbicide and fertilization (HF). Here we extend the individual tree survival CLL model to allow for trees within a plot and plot level random effects. We demonstrate individual tree survival predictions with and without the inclusion of random effects.

A Generalized Methodology for Developing Whole-Stand Survival Models - Charles E. Rose; Michael L. Clutter; Barry D. Shiver; Daniel B. Hall; Bruce Borders (Forest Science, 2004)
A large source of variability in yield predictions is due to estimation of future surviving trees per unit area. Previous whole-stand survival modeling efforts have concentrated on modeling the empirical survival curve. Modeling hazard functions, an approach to survival analysis commonly used in fields such as medicine and sociology, can be applicable to plantation survival estimation. We offer a generalized method for deriving whole-stand survival models that are capable of modeling complex underlying hazard functions. We use our knowledge of the empirical hazard function to limit our selection to appropriate functions. Integrating selected functions results in initial condition difference equations that, when fitted to our data, provide biologically reasonable whole-stand survival predictions and adequately represent the underlying hazard function. Our method is relatively easy to implement and can model a whole-stand survival curve with a complex underlying hazard function. FOR. SCI. 50(5):686–695.

Special Commentary: The Future of Digital Remote Sensing for Production Forestry Organizations - James L. Smith; Michael Clutter; Brent Keefer; Zhenkui Ma (Forest Science, 2003)
It cannot honestly be stated that digital imagery is a standard instrument in the repertoire of the professional natural resource manager. However, we believe that the opportunity to change that situation is rapidly approaching because a nexus of technology and need has finally occurred. However, pragmatic issues remain. The key to the successful adoption of any new tool, including digital imagery, is not just having the need, but having the tool be useful, usable and available to the great mass of users, (i.e., those in the field in the case of our profession). No forester thinks twice about using an analog aerial photograph, and we need to create that same “ho-hum” status for digital imagery. FOR. SCI. 49(3):455–456.