Abstract
One of the cornerstones of the Biodiversity Guidebook (BGB) is the philosophy of protecting minimum proportions of specific forest age classes in the working forest. In the BGB, these minimum age class requirements are based on expert opinion, which consist of 1. an estimate of the average time between stand replacing events (SRI), and 2. an age class distribution generated from the SRI by a mathematical function - the negative exponential equation. The BGB notes that more precise determinations of natural age class distributions are the ideal basis for further refinements.
In practice, the BGB age class requirements are implemented using the operational forest inventory. Regional land use plans, landscape-level plans, and forest development plans must rely on this large database. However, over the past eighteen months, experienced planners in the Nelson Forest Region expressed concern about the levels of old growth suggested in the BGB. An evaluation of six of the seven Timber Supply Areas in the Nelson Forest Region determined that only 20.3% of all landscape unit/variants can presently meet BGB old-growth requirements.
The current project was initiated to determine if the inventory could quantitatively validate the BGB values for the Nelson Forest Region. This study was conducted in two stages. In stage one, potential problems associated with the operational inventory were explored. The factors examined included different definitions of stand age, past harvests, age bias in the operational inventory, and increases in fire frequency related to European settlement. It was possible to measure the impact on SRI of most of these factors, and it was concluded that the inventory could be used to determine the average age of stands, and the average age for most age classes. Additionally, the biases due to the various factors were relatively small with the exception of modern fire suppression, which increased the SRI derived from the inventory data. When aggregated, the sum of these biases are positive such that the observed SRI in the inventory data should exceed the natural SRI.
In the second stage, 4.05 million hectares of productive Crown forest were analyzed after correcting for recent harvest. Four different approaches were used to derive natural age class proportions. One approach involved using the age classes of the corrected inventory, as the "natural" benchmarks. A second approach used the negative exponential equation driven by the average age of the inventory. A third approach fitted three families of curves, a generic "best fit" equation drawn from a library of thousands of possible equations, a negative exponential, and a Weibull, using the age class data from the correct inventory. A fourth approach using mixed distribution curves to deal with the disjuncts visible in seven variants was not pursued when disjuncts in the curves were attributed, in part, to the practice of age class midpointing during operational inventories.
These alternative approaches gave somewhat different answers, but the trend was clear. When the inventory was corrected for 40 years of harvest, seven of 15 variants in the Nelson Forest Region still could not meet BGB old-growth requirements for low emphasis biodiversity. When a negative exponential model was used with the average inventory age, the average SRI for the region was 156.6 years as compared to the BGB estimate of 220 years. When specific inventory age classes were fitted against negative exponential curves, the average, derived SRI value for the region was 143.9 years. A different model, the Weibull equation, yielded curves with larger adjusted R2 values than the BGB negative exponential equation.
The analyses indicated that the BGB methodology yields larger proportions of older age classes than are contained in the local data. Three variants were within 20 years of the BGB SRI estimates, whereas five variants varied by 100+ years. One variant varied by 185 years. These discrepancies exceeded the estimates of bias determined in the first stage in the study. As well, derived SRI values from this study were within the range of the values found in 17 published studies, for 14 of 15 variants.
An average difference of 63 - 76 years separated the SRI estimates of this study from those of the BGB. Approximately 29 years could be explained by the BGB's use of maximum stand age while estimating SRIs. By comparison, this study used the mean stand age from the inventory.
The original BGB estimates of SRI are substantially higher than values obtained from corrected inventory data subjected to the same BGB methodology. Both larger initial estimates of SRI, and the choice of model (a negative exponential equation), contributed to larger old-growth requirements in the BGB. These factors may explain, in part, the widespread failure of many relatively undisturbed landscape units to meet BGB age class requirements.
In summary, this study has successfully linked the operational inventory data to the Biodiversity Guidebook and has objectively estimated natural age class proportions. While there are still differences of opinion concerning the reasons for the observed discrepancies (human-caused versus BGB methodologies), we suggest the sensitivity tests in this study explain many of the discrepancies noted by forest planners.
Several alternatives are presented to revise seral-stage requirements in the Nelson Forest Region. Modification of the BGB rules will be necessary as SRIs change. Specifically, lower age class breaks will be needed and the BGB Appendix 2 will have to be rephrased entirely if the Weibull or similar curves are adopted.
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Updated April 12, 2007
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