Lianjun Zhang

Research Intereests:

1. Various aspects of forest growth and yield modeling, including stand level models, dbh or basal area class distribution models, individual tree level models, and models for the effects of silvicultural treatments such as fertilization, thinning, vegetation control, and site preparation.
2. Modeling the spatial distribution and temporal dynamics of mixed-species stands.
3. Application of statistical methods and techniques in forest growth and yield modeling.
4. Spatial statistics, analysis, and modeling of tree / stand / ecosystem.

1. Various Aspects of Forest Growth and Yield Modeling:
   1. Stand level:
      • Growth and yield equations (volume, basal area, height, mortality, regeneration, ingrowth)
      • Juvenile growth relationships
      • Stand density management tools (e.g. stand density management diagram or stocking chart) based on biological and ecological rationales (e.g. self-thinning, constant final yield, competition-density effects)
   2. Individual tree level:
      • Relationships between tree volume, tape, basal area, height, and crown
      • Tree survival / mortality
      • Inter- and intra-species competition
   3. Tree dbh or basal area class distributions:
      • Elationships between species components and whole stand dbh distributions;
      • Dynamics of dbh distribution over time
      • Dbh distributions of multi-species stand
      • Distribution changes due to silvicultural treatments
   4. Modeling the effects of silvicultural treatments:
      • Fertilization and thinning
      • Vegetation control and site preparation
2. Modeling spatial distribution of Mixed-Species Stands:
   • Point pattern analysis and marked point pattern analysis of tree distribution and stand structure
   • Spatial autocorrelation between tree variables
   • Local analysis and modeling of tree competition and growth
   • Multi-resolution or multi-scale analysis of tree distribution and stand structure
3. Application of Statistical Methods and Techniques in Forest Growth and Yield Modeling:
   • Finite mixture models
   • Neural network models and fuzzy set
   • Bivariate joint distributions
   • Generalized linear models
   • Generalized additive models
   • Nonparametric regression models
   • Wavelets and functional analysis
   • Spatial statistics, analysis and modeling

Expertise: forest biometrics, growth and yield modeling, spatial statistics and modeling, quantitative silviculture