Initial Responses of Forest Understories to Varying Levels and Patterns of Green-tree Retention

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Introduction

Considerable attention has been devoted to understanding the effects of traditional silvicultural practices on forest understory communities in many temperate and boreal ecosystems. In coniferous forests of the Pacific Northwest, many understory species are tolerant of the physical disturbances and microclimatic changes associated with clearcut logging and site preparation. However, some species — particularly those associated with late-seral forests — are sensitive to both ground disturbance and canopy removal, and timber harvest may result in local extirpation. Variable retention harvest, in which a proportion of the live or “green-trees” are retained, may ameliorate these impacts. In this study we explore the initial responses of the understory to two basic elements of overstory retention: level of retention (proportion of original basal area) and spatial pattern of retention (trees in 1-ha patches vs. dispersed).

Response Variables

We focus on 12 understory response variables. Five of these represent the abundance (cover, density) or height of major growth forms

• total cover of the herb and tall shrub layers,
• height of the tall shrub layer,
• density of tree seedlings (<10 cm tall) and saplings (0.1 – 1.0 m tall).

Species in the herb layer were also analyzed by “seral status” to distinguish among taxa with differing successional roles and sensitivities to disturbance. Species were classified as:

• early seral herbs ¾ annual, biennial, and perennial herbs that typically dominate early successional communities and are characterized by long-distance seed dispersal, rapid growth, and high fecundity (a total of 76 taxa);
• forest herbs ¾ typical understory species found beneath a broad range of canopy conditions and through most stages of stand development (66 taxa);
• late-seral herbs ¾ species that reach maximum abundance in old forests and are sensitive to canopy removal or disturbance (42 taxa).

For each of these groups we calculated a plot-level “summed frequency” (the sum of the frequencies of all species in a plot) and richness (number of species per plot), which yielded six additional response variables (i.e. the frequency and richness of each group). The final response variable, compositional change, was computed as the percent dissimilarity (PD) between the pre- and post-harvest composition of the herb layer within each plot. PD derives from the quantitative form of Sørensen’s community coefficient.

Experimental Design and Hypotheses

The full experimental design consists of six, 13-ha green-tree retention treatments, including a control (see Experimental Design), replicated at each of the six blocks (locations; see Study Areas). In this study we utilize five of the treatments: the control (100% retention) for reference, and four that can be analyzed as a fully balanced, two-factor design that contrasts retention (a) at two levels: 15% (the minimum required by the Northwest Forest Plan) and 40%, and (b) two spatial patterns: as 1-ha aggregates (or patches) or as uniformly dispersed trees. We hypothesized the following responses:

Hypothesis 1. — Treatment-level responses. Mean changes in understory abundance, richness, and composition (a) will be greater at 15% than at 40% retention, and (b) will be greater in dispersed than in aggregated treatments (changes within retained patches of forest will be small). (c) Late-seral herbs will be particularly sensitivity to level and pattern of retention.

Hypothesis 2. — Forest aggregates vs. adjacent harvest areas. In aggregated retention treatments, changes in understory abundance, richness, and composition will be smaller in the forest aggregates than in adjacent areas of harvest.

Hypothesis 3. — Responses in the harvested portions of treatment units. Within the harvested portions of treatments, mean changes in understory abundance, richness, and composition (a) will be greater at 15% than at 40% retention, and (b) will be greater in aggregated than in dispersed treatments (reflecting more complete removal of trees from the former).

Sampling Design

Within each treatment unit, a grid system (40-m spacing) was installed prior to harvest. At a subset of grid points, permanent vegetation plots were established, varying in number (32-27) and spatial distribution by treatment (Figure 1). At each sampled grid point, understory variables were sampled with a series of transects and nested subplots. For aggregated retention treatments, post-harvest means are weighted averages that account for unequal areas and sampling intensities of the two post-harvest environments (aggregates and adjacent harvest areas).

Figure 1.  Sampling grid and understory sampling design for (a) dispersed and control (100%) treatments, and (b) aggregated treatments.  Plus signs denote sampled grid points.  (c) Transect and subplot layout at sampled grid points.  (d) Transect lines for cover and height of tall shrubs.  (e) Subplot for sapling density.  (f) Microplots for herb frequency, cover, and tree seedling density.

Analyses

Detrended correspondence analysis (DCA) ordination was used to portray the overall compositional response of the herb layer. Separate ordinations were run for each block using a sample-by-species matrix with 10 samples representing the average composition of each of the four treatments (plus the control), before and after harvest. Average frequency was used as the measure of species abundance.

Analysis of variance (ANOVA) was used to test for effects of level and pattern of retention (and their interaction) on our 12 primary response variables.

For each of the 42 species classified as late-seral, we compared patterns of local extirpation by tabulating all cases in which a species was completely lost from all sample plots within a treatment unit. Losses were recorded separately for the two post-harvest environments in aggregated retention treatments.

Results

Compositional change

• We observed similar patterns of compositional response to treatments among the 6 blocks (Figure 2).
• Controls showed little change in composition.
• Direction of compositional change was similar among treatments within a block, with the magnitude of change greater for 15% than for 40% retention, however responses to pattern of retention were less consistent.

Figure 2.  DCA ordinations portraying changes in the average species composition of five retention treatments at each of the six study blocks.  Filled symbols represent pre-harvest compositions and open symbols, post-harvest compositions; arrows indicate the direction and magnitude of compositional change.

Mean treatment-level responses

• Most plant groups showed large declines in abundance, stature (height), or richness in response to treatments (Figure 3).
• Early seral herbs were the only group to increase in frequency and richness, but these changes were relatively small.
• Responses to level of retention were consistent with our expectation: changes were typically smaller at 40% than at 15% retention (significant differences observed for 5 of 12 variables).
• Responses to pattern of retention were not consistent with our expectation: changes were not more pronounced in dispersed than in aggregated treatments.
• As predicted, late-seral herbs were sensitive to both level and pattern of retention (as measured by species richness), however, responses to retention pattern were opposite of those predicted.

Figure 3.  Mean changes (pre- minus post-harvest value, ± 1 SE) for a subset of   understory variables showing significant responses to treatments (level and pattern of retention).  P values are from two-way ANOVA models.  Mean changes (± 1 SE) for the control treatment (open triangle) are presented for reference.

Forest aggregates vs. adjacent harvest areas

• As predicted, we observed large, statistically significant differences in understory response in forest aggregates and adjacent areas of harvest (Figure 4).
• Although some variables showed small changes within forest aggregates (similar to those of controls), changes were significantly larger in adjacent harvest areas.

Figure 4.  Mean changes (+ 1 SE) in forest aggregates and adjacent harvest areas for each of the 12 understory variables.  P values are from one-way ANOVA models comparing responses in aggregates and harvest areas.  Mean changes (+ 1 SE) for the control treatment (black bar) are presented for reference.

Responses in the harvested portions of treatment units

• Within the harvested portions of treatment units, only 2 of 12 variables showed significantly greater change at lower levels of retention in contrast to our expectation (Figure 5).
• Effects of pattern of retention were significant for 4 variables, with larger changes in aggregated treatments (as predicted). Frequency and richness of late-seral herbs declined more in the harvested portions of aggregated treatments than in dispersed treatments.

Figure 5.  Mean changes within the harvested portions of treatment units for a subset of understory variables showing significant responses to treatments (level and pattern of retention).  P values are from two-way ANOVA models.  Mean changes (± 1 SE) for the control treatment (open triangle) are presented for reference.

Local extirpation of late-seral species

• We observed numerous instances in which late-seral herbs were lost from all plots within treatments or from the harvested areas of aggregated treatments.
• Rates of extirpation were comparable among treatments (12-15 species per treatment). However, in aggregated treatments, species were more often lost from harvest areas (25-26 cases) than from aggregates (6-10 cases).
• The most sensitive species were the orchids, Corallorhiza maculata, Goodyera oblongifolia, and Listera caurina, and the ericads, Chimaphila menziesii and Pyrola secunda.

Discussion

In this study, we tested a simple conceptual model in which forest understory responses to green-tree retention are influenced both by the proportion of live trees retained through harvest and the spatial pattern in which they are retained. To our knowledge, ours is the first experimental study to explicitly consider the relative contributions of level and pattern of retention to understory response.

Direction of compositional change was similar among treatments within each block, but the magnitude of change was consistently larger at 15 than at 40% retention. Likewise, for many understory groups, declines in abundance (cover, density) or species richness were significantly greater at 15 than at 40% retention. In contrast, pattern of retention had surprisingly little effect on treatment-level responses: although changes within forest aggregates were small, declines in adjacent areas of harvest were generally greater than those in the dispersed treatments. Late-seral herbs were particularly sensitive to these effects, with more frequent extirpations from plots within the harvested portions of aggregated treatments than from dispersed treatments. Thus the short-term benefits of aggregated retention are predictably localized. Perhaps the clearest illustration of these tradeoffs emerged from our analysis of species’ extirpations: in aggregated treatments, species were lost more than twice as often from harvested areas as from forest aggregates. As a result, extirpations were no more common in dispersed than in aggregated treatments, contrary to our initial expectation.

We suspect that these initial responses are mediated, in large part, by associated patterns of disturbance and slash accumulation that differ significantly with level and pattern of retention (see Halpern and McKenzie 2001).

Do our results suggest a clear difference in the response of the forest understory to different levels or spatial patterns of retention? Clearly, the magnitude of change in understory composition and structure was notably reduced from 15 to 40% retention, but for most elements of the understory, aggregated retention appeared to offer few short-term benefits over dispersed retention. The latter result was particularly surprising with respect to loss of late-seral species, the group for which aggregated retention of the overstory was presumed to be most relevant. Yet, we must temper these conclusions by acknowledging the short-term nature of our results. As the immediate effects of disturbance diminish with time, the effects of overstory structure are likely to become increasingly important. Longer-term observations will be necessary to distinguish between the initial effects of disturbance and the more persistent influences of residual overstory trees.