Modelling a mesoscale forest: Can a regional growth model be applied to manage a small landscape?
Forest models can be developed from empirical relationships between stand attributes, including age, and yield. Empirical growth and yield (G&Y) models remain popular with forest managers for their simplicity and utility. It is important to apply models at the spatial levels at which they were d...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Canadian Institute of Forestry
2025-08-01
|
| Series: | The Forestry Chronicle |
| Subjects: | |
| Online Access: | https://pubs.cif-ifc.org/doi/10.5558/tfc2024-020 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Forest models can be developed from empirical relationships between stand attributes, including age, and yield. Empirical growth and yield (G&Y) models remain popular with forest managers for their simplicity and utility. It is important to apply models at the spatial levels at which they were developed to avoid the fallacy of disaggregation. This study attempted to determine whether regionally aggregated G&Y curves perform adequately when applied at the sub-regional scale, and if not, if their application can be modified to better model a mesoscale forest. We studied a mesoscale forested watershed in Nova Scotia, Canada, to determine if regional G&Y curves could predict stand merchantable volume (MV) using data available from a photogrammetric provincial forest inventory for initial stand conditions. Initial results demonstrated that curves significantly underestimated stand MV compared to 700 forest cruise point observations throughout the study area. Curves were reassigned based on observations and local knowledge, and subsequently generated estimates of stand MV not significantly different from observations. We found that while regional growth models are not ideal for mesoscale application, when properly calibrated through field observations, they can offer insights into current conditions and the future potential of a forest with minimal additional data collection required. |
|---|---|
| ISSN: | 0015-7546 1499-9315 |