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Actively managing mixed-species stands is becoming a worldwide trend. It is imperative to understand the ecological process of mixed-species stands for developing management decision-making tools. Few models or modeling strategies have been developed and evaluated for mixed-species stands. The first part of this book develops a principal component and cluster analysis procedure to group tree species for ecological and growth modeling. Using stem-mapped data, the second part characterizes tree spatial distributions and develops individual-based spatially explicit growth and survival models to…mehr

Produktbeschreibung
Actively managing mixed-species stands is becoming a worldwide trend. It is imperative to understand the ecological process of mixed-species stands for developing management decision-making tools. Few models or modeling strategies have been developed and evaluated for mixed-species stands. The first part of this book develops a principal component and cluster analysis procedure to group tree species for ecological and growth modeling. Using stem-mapped data, the second part characterizes tree spatial distributions and develops individual-based spatially explicit growth and survival models to quantify neighborhood effects in a natural temperate species-rich forest. The last part develops a multi-species density-dependent matrix growth model and individual-tree distance-independent growth and mortality models for the bottomland mixed-species hardwoods in the Lower Mississippi Alluvial Valley. The modeling strategies can help forest ecologists and managers better understand the ecological processes of mixed-species stands and develop management regimes for such stands.
Autorenporträt
Dehai Zhao is Assistant Research Scientist (Graduate Faculty) of Statistics and Forest Biometrics at the University of Georgia. Dr. Zhao holds PhD in Forest Biometrics and MS in Statistics from the University of Georgia, and MS in Forest Biometrics/Management and BS in Forestry from Nanjing Forestry University.