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Record W2356730825 · doi:10.14288/1.0075274

Regeneration patterns on some old-growth and clearcut sites in the Mountain Hemlock zone of southern British Columbia

2009· article· en· W2356730825 on OpenAlexaboutno aff
Robert B. Brett

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRegeneration (biology)Western HemlockNatural regenerationLoggingGeographyGeologyForestryBiology

Abstract

fetched live from OpenAlex

Patterns of tree regeneration change with elevation in old-growth forest stands on British Columbia's southern coast. At lower elevations, where snow is infrequent, regeneration tends to be centred in canopy gaps caused by the death of one or more trees (the gap model). At higher elevations, where snow usually remains until early summer, regeneration is restricted to elevated microsites that emerge earliest from the snow (the tree-island model). Little is yet known about regeneration patterns in old-growth forest stands between these two systems, those within the forested Mountain Hemlock (MH) biogeoclimatic subzone. Our lack of knowledge has become more of a concern a s logging progresses into higher elevations of the subzone where there are ever-deeper snowpacks. To investigate these patterns, I established 12 study sites in the Tetrahedron Range near Sechelt, 50 km northwest of Vancouver. Six sites were in old-growth forest stands, and six were in naturally-regenerated clearcuts that had been logged 1.1-12 years prior to sampling. Six sites were steep ( - 5 0% slope) and six were flat (~ 2 5% slope). Elevations were slightly higher for old-growth sites (1080-1195 m) than clearcut sites (1060-1100 m). Old-Growth Sites: Trees were very slow-growing and took an average of almost 500 years to enter the canopy layer. Regeneration was most successful on mounds and near to a canopy tree. It was unaffected by overhead canopy cover (that is, the presence or absence of a canopy gap), apparently because of the prevalence of low-angle, diffuse light. In contrast to most forested ecosystems, almost all trees were growing on the undisturbed forest floor rather than on decaying wood or mineral soil. Overall, regeneration patterns were more consistent with the tree-island model than the gap model of regeneration since trees were most likely to survive on mounds and close to a canopy tree. Still, the presence of some regeneration in gaps, especially on steep sites, showed that the study sites occupied a transition between the gap and tree-island models. The tree-island model was best expressed on late-snowmelt sites that were most similar to high-elevation sites. It was also more apparent in the regeneration patterns of Chamaecyparis nootkatensis (Alaska yellow-cedar), a species near the upper limit of its elevational range, than those of Tsuga mertensiana (mountain hemlock), a species in the middle of its range. Clearcut Sites: Almost all trees >150 cm tall were A. amabilis (Pacific silver fir) which had been present in the previous old-growth stand before cutting. A surprisingly high proportion of trees (45%) established within a 3-year window from 1 year before logging through 1 year after logging, more than half of which were C. nootkatensis. Only 2 0% of regeneration established more than one year after logging, and none established >8 years after logging. This limited ingress likely resulted from the absence due to clearcutting of nearby seed-producing trees. There was much more friable forest floor and coarse woody debris (from logging slash) than in adjacent old-stands, but almost all regeneration was still found on undisturbed forest floor. Regeneration was less common on mounds in clearcuts than on mounds in adjacent oldgrowth stands, apparently because mounds were disturbed during logging more than other microsites. There was no evidence that Vaccinium spp. (blueberries and huckleberries) impeded regeneration since 8 4% of trees and seedlings were growing below or amidst Vaccinium and establishment and survival was higher where it was present. The stands that develop on these clearcuts will remain for many centuries dramatically different from the old-growth forest stands they replaced. Where cutting is appropriate, such negative features could be avoided by leaving an adequate seed source, retaining live and dead canopy trees, and protecting sub-canopy trees during cutting. Sites would then also retain many of the old-growth characteristics required by wildlife and other, non-timber values. Results from old-growth sites highlight the site-specific nature of regeneration patterns and the abruptness of the transition to tree-island patterns. Yet low-elevation cutting methods, especially clearcutting, are still used within this transition even where regeneration requires the protection of an overhead canopy. Any presence of regeneration patterns matching the treeisland model should warn forest managers of potential regeneration problems. In such areas, the decision to cut should not be automatic, especially given the slow growth and high non-timber values of these forests. Where cutting does occur, it should leave a s much of the subcanopy and canopy layers as possible. A s snow increases further and there is a greater presence of regeneration patterns matching the tree-island model, any cutting is inappropriate. The relationship between regeneration patterns and snow depths could provide an ecological basis for managing forests within the MH zone. Specifically, the presence of regeneration patterns that match the tree-island model (even if discrete tree islands are not present) is a reflection of severe growing conditions and potential regeneration problems. Simple measures of the relative abundance of tree-island patterns could be added during standard site diagnosis to determine the severity of growing conditions, e.g., the proportion of understory and sub-canopy trees that are growing near a canopy tree or on mounds. Such a classification would be applicable regardless of management objective.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.165
Teacher spread0.159 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2009
Admission routes1
Has abstractyes

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