Lateral Picea shadow effects on Populus tremuloides understory vegetation in central Yukon, Canada

Forest Ecology and Management 261 (2011) 1866–1875

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Lateral Picea shadow effects on Populus tremuloides understory vegetation in central Yukon, Canada W.L Strong ∗ Arctic Institute of North America and University of Calgary, Faculty of Environmental Design, 2500 University Drive N.W., Calgary, Alberta T2N 1N4, Canada

a r t i c l e

i n f o

Article history: Received 4 November 2010 Received in revised form 5 February 2011 Accepted 8 February 2011 Available online 5 March 2011 Keywords: Boreal forest Shade Spruce Succession Trembling aspen Understory

a b s t r a c t Laterally cast Picea albertiana ssp. albertiana (western white spruce) shadows were analyzed to determine their effect on understory plant abundance in two high-latitude (62.7◦ N) boreal Populus tremuloides (trembling aspen) forest stands. Each stand had a uniform and continuous overstory, and occurred on level to gently sloping terrain with a submesic moisture regime. Picea >1 m tall had <20% cover in each stand, with few trees equalling or exceeding the height of the P. tremuloides canopy. Understory vegetation composition was sampled in 30-m × 30-m plots that were subdivided into 1.5-m × 1.5-m cells (200 sampled per plot). Picea shadow locations and their areal extent were determined on an hourly basis (7:00–19:00 h Pacific Standard Time on the summer solstice) for individual plot cells using silhouette diagrams constructed from tree height and canopy-related data (n = 140 trees). Shadow data were analyzed using the lower- (QL , minimum to first-quartile values) and upper-most (QU , third-quartile values to maximum) portions of each species’ abundance distribution. Kruskal–Wallis tests (P < 0.001) indicated that greater Arctostaphylos uva-ursi (bearberry) abundance occurred where shadow cover was the least (daytime average ∼24%); whereas Geocaulon lividum (toadflax), Hylocomium splendens (stairstep moss), and Shepherdia canadensis (buffaloberry) incurred the most shadows (>34% cover) and had the shortest periods of continuous (<6 h) sunlight exposure with <30% Picea shadow cover. Hylocomium and Shepherdia also occurred nearer Picea than Arctostaphylos. Rosa acicularis (wild rose), Linnaea borealis (twinflower), Vaccinium vitis-idaea (bog cranberry), Chamerion angustifolium (fireweed), and Calamagrostis purpurascens (purple reedgrass) incurred intermediate amounts of shadow. Differences in hourly shadow abundance values (QU minus QL plot cells) were greatest for Arctostaphylos (−14.7%) and Rosa (−10.8%), but H. splendens (+3.8%) and Geocaulon had the least (+1.7%). Greater Hylocomium and Shepherdia abundance occurred in plot cells with more shadow indicating a tolerance for shade, which was contrary to the other species. These differences may represent examples of niche partitioning based on relative light availability. Individual understory species based on percent cover and species richness were more strongly correlated with Picea shadow cover than canopy cover. As a direct representation of impeded light transmittance, assessment of lateral tree shadows may represent a viable approach for investigating within stand compositional variation and temporal change among forest understory species, when a distinct physiognomic difference occurs between seral and climax overstory species. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Forest communities are dynamic ecological systems with respect to stand structure and species composition. Overstory changes occur in response to the establishment and development of late-successional trees, which promote responses by understory plants (e.g., Oliver, 1981). The progression from seral to climax vegetation in deciduous boreal forest stands of western Canada results

∗ Correspondence address: P.O. Box 40186 Station Main, Whitehorse, Yukon Y1A 6M9, Canada. Tel.: +1 867 667 2924; fax: +1 867 667 2924. E-mail address: [email protected] 0378-1127/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2011.02.009

in a striking change in stand physiognomy due to the involved trees – a progression from broad-canopied deciduous trees (Populus tremuloides – trembling aspen) to narrow, elongated conical evergreen trees (Picea spp. – spruces). This is unlike seral deciduous to climax deciduous (Leak, 1991) or seral conifer to climax conifer (Pfister et al., 1977) succession that occurs on zonal sites in the eastern and western regions of North America, respectively. As well, medium height and low-growing herbs and shrubs (≤1 m tall) in northern boreal stands are often severely suppressed during succession and replaced with bryophytes during the development of Picea trees (Viereck, 1970; Beckingham et al., 1996; Strong, 2009). During the early stages of climax tree establishment and growth, changes in vascular understory species cover, density, stature, and

W.L Strong / Forest Ecology and Management 261 (2011) 1866–1875

vigor sometimes appear more widespread in P. tremuloides stands than might be expected based on the local abundance of Picea. Such reductions in understory biomass among 13 P. tremuloides community types with a limited occurrence of late-successional conifers (e.g., <10% cover) have been documented in the western United States (Stam et al., 2008), but no mechanism to explain this phenomenon was offered by the authors. The disproportionate reduction in biomass relative to the abundance of conifers suggests Picea have an indirect influence on understory species that extends an unknown distance beyond the physical limits of their canopy. These changes could be due to temporal effects, but this should not the case because P. tremuloides stands and presumably their understory vegetation are capable of persisting much longer than the cohort of trees that initially formed the vegetation, when latesuccessional coniferous trees are absent (Cumming et al., 2000). Light availability has been long considered an important ecological influence on understory plants in boreal P. tremuloides stand succession, particularly with regards to increasing Picea abundance (e.g., Rowe, 1956), hence the common use of terms such as shadeintolerant and shade-tolerant to characterize understory species. Both the quantity and spectral qualities of light reaching the forest floor have been investigated in boreal ecosystems (e.g., Ross et al., 1986; Messier et al., 1998), and some studies have determined the minimum requirement for selected species. From these studies, it is known that understory species such as Chamerion angustifolium (fireweed), Calamagrostis canadensis (northern reedgrass), Rosa acicularis (wild rose), Shepherdia canadensis (buffaloberry), and Viburnum edule (low-bush cranberry) require more than 7–10% of full sunlight to survive (Lieffers and Stadt, 1994), whereas late-successional feathermosses such as Hylocomium splendens (stairstep moss) and Pleurozium schreberi (Schreber’s moss) need only ∼1.7% (Sonesson et al., 1992; Startsev et al., 2008). It has also been observed that mixed P. tremuloides–Picea overstories (60:40 basal area ratio) transmit about half as much light to their understory vegetation (∼15% of available) as P. tremuloides monocultures (∼20–35%) at mid-day during summer (Lieffers and Stadt, 1994; Constabel and Lieffers, 1996). Even at the higher levels of light transmittance, the forest overstory likely imposes some growth constraints on understory species. As a measure of potential effect, however, percent Picea canopy cover is less well correlated with understory species abundance than the physical size or canopy profile area (tree height × canopy width/2) of the trees (Strong, 2011). Intuitively, this suggests laterally cast Picea shadows, rather than the trees themselves, might be responsible for understory vegetation changes during boreal forest succession. The relevance of lateral shadows has been studied in agroforestry and agronomic systems, as they relate to tree density effects and ground-level crop production (e.g., Kuuluvainen and Pukkala, 1987; Meloni and Sinoquet, 1997). However, few, if any, studies have evaluated diurnal Picea shadow patterns in natural ecosystems to determine how effective they might be for explaining botanical variation in understory vegetation, although some researchers have alluded to their potential importance (e.g., Canham et al., 1994; Meloni and Sinoquet, 1997; Haugo and Halpern, 2010). If the abundance (i.e., percent cover) and the physical size (e.g., canopy profile area) of Picea in a forest stand determines the amount of light reaching the forest floor, it is hypothesized that variation in the diurnal location and extent of laterally cast Picea shadows will create spatial variation in individual understory species abundance within shade-intolerant P. tremuloides forest stands. The uneven distribution of Picea shadows and any associated effects (e.g., changes in temperature, Barbier et al., 2008) would also be expected to increase compositional heterogeneity in the understory vegetation relative to P. tremuloides stand, due to differential responses by individual species. A combination of vegetation quadrat sampling, Picea tree morphometric data,

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and tree shadow modelling were chosen as the basis for this analysis. 2. Methods and materials 2.1. Study sites Two study stands were located 16 and 10 km (Plot A – 62.684◦ N, 136.750◦ W, Plot B – 62.745◦ N, 136.666◦ W, respectively) southwest of Pelly Crossing, along the Klondike Highway (No. 2), near Von Wilczek Lakes (a.k.a. Lhútsäw Lake and Rock Island Lake) in central Yukon, Canada. This area occurs in the Northern Boreal-Cordilleran (NCb) ecoclimatic region (Ecoregions Working Group, 1989). Each stand occurred on the crest of a low ridge at an elevation of ∼595 m. More than half of the northwest portion of each plot had relatively level topography, with the remainder inclined to the southeast at a gradient of ≤1.5◦ ; except the extreme southeast corner or 5–10% of Plot A had a ∼2.5◦ gradient. The surficial geology of the sites was similar and consisted of a fine sandy loam stratum ∼50 cm thick over deep gravelly sandy loam deposits. The associated Eluviated Eutric Brunisolic soils were well drained (submesic), with a low-grade mesotropic nutrient regime (terminology based on Soil Classification Working Group, 1998 and Luttmerding et al., 1990). Each stand was structurally similar and in the early maturing stage of successional development (Luttmerding et al., 1990, pp. 52, 55), with a relative continuous and uniform tree canopy. Preference was given to stands with a scattered distribution and a low frequency of Picea of various heights. The current vegetation developed following wildfires prior to 1896 (Plot A) and 1921 (Plot B). Both stands were members of the P. tremuloides//Calamagrostis purpurascens–Arctostaphylos uva-ursi vegetation type described by Strong (2009) in central Yukon, and intermediate to the P. tremuloides/S. canadensis–R. acicularis and P. tremuloides/R. acicularis–A. uva-ursi types recognized by Chambers (2010) in the Takhini Valley of southern Yukon. No evidence of disease, natural disturbances such as wind-throw, overly maturity trees, or obvious evidence of human activity occurred in either stand. 2.2. Vegetation sampling To sample the understory vegetation, a 30-m × 30-m plot was established in each stand, with the east edge oriented in a north–south direction. Plots were divided into 20 rows and 20 columns of 1.5-m × 1.5-m cells. A 1-m × 1-m quadrat centrally located in alternate, non-adjoining cells (n = 200) was used to determine the composition and abundance of overstory (>1 m tall), and vascular (≤1 m tall) and terrestrial nonvascular understory plants. Species abundance was assessed according to percent canopy cover (sensu Daubenmire, 1968, p. 43), based on ocular estimates during the first half of July 2010. The location of all Picea >1 m tall was determined in and within 12 m of each 30-m × 30-m plot. The peripheral areas were assessed to account for tree shadows that might be projected into the plots. Individual tree locations were determined by (i) establishing a line transect at a known location relative to the plot edges using a 30 m measuring tape, (ii) measuring the right-angle distance either to the left or right of the tape (maximum 3 m) between the stump center and line transect, and (iii) recording the right-angle intercepting distance from the start of each transect. Transects were initially positioned parallel to and 3 m from the north plot edge, and then subsequently located at 6 m intervals both within and around a plot. The height, canopy width, height of the lower canopy above the forest floor, and basal diameter were measured for each tree. Picea canopy width was determined by measuring across the widest section of the canopy, which typically occurred on the lower

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Fig. 1. Relative size and orientation of Picea albertiana shadows from 7:00 to 19:00 h on June 21 at 62.7◦ N latitude in central Yukon.

portion of the stem. The heights of trees <4 m tall were determined using a 10-cm incremented 2-m ruler, but a measuring tape and clinometer were used for taller trees. Basal diameter was measured directly above the root collar. Similar dimensional data were not collected for P. tremuloides trees, because it was assumed that their canopy shadows were evenly distributed across each plot, thus not differentially affecting understory vegetation composition. Vascular plant, Picea albertiana, and moss nomenclature were based on Kartesz (1998), Strong and Hills (2006), and Anderson et al. (1990), respectively. 2.3. Picea shadow compilation Hourly solar elevations (degrees above the horizon) and azimuths (compass orientation) for June 21 were used to model the location and extent of shadows cast by Picea trees. June 21, or the summer solstice in the northern hemisphere, was chosen for analysis because it represents the date when the maximum annual elevation of the sun occurs (∼50.7◦ in the study area) and when diurnal tree shadows are smallest. Although the sweep of shadows can be a continuous process during the daylight period, hourly intervals from 7:00 to 19:00 h were used to facilitate the calculation of tree shadow areas. During this diurnal timeframe, solar elevations exceeded 15◦ and it was assumed that the sky was cloudfree. Solar elevation and azimuth values specific to the study area were obtained from a predictive model developed by the United States National Oceanic & Atmospheric Administration (Cornwall et al., 2010). Individual shadow silhouettes were constructed for each Picea tree in and within 12-m of each plot, and for each of the 13 time increments (Fig. 1), based on the collected tree height (Hi ), canopy width, and lower canopy height (Li ) data. Picea were assumed to have a triangular profile. Overall shadow length (Sij ) was estimated based on the following algorithm: Si,j =

Hi [Ej /45◦ ]

where Ej is the solar elevation in degrees; i represents individual trees from 1 to n; and j is an hourly increment between 7:00 and 19:00 h, inclusive. To determine the distance between the lower limit of a shadow and the tree base (Xi,j ), the height of the lower tree canopy above the forest floor (Li ) was weighed according to the overall shadow length:



Xi,j = Li

Si,j



Hi

This factor was included in the construction of silhouettes to avoid over-representing the amount of shadow area associated with each tree. To determine the amount of shadow within plot cells, each silhouette was overlain on a scale-model (R.F. 1:100) of the vegetation sampling plot and the amount of overlap determined. Because more

than one tree shadow occurred in most plot cell, the largest shadow value for a given hour was used for analysis, unless otherwise stated. Preliminary evaluations of the data using either the largest shadow values or total shadow areas by plot cell yielded similar results, but use of the largest shadow values avoided concerns related to overlapping and multiply occurring shadows within a plot cell. The potential affect of Picea tree location on understory species abundance was assessed by measuring the azimuth and distance between each Picea tree and the center of the nearest plot cell that had been sampled for vegetation composition. To be acceptable for inclusion, a plot cell had to occur north of an east–west line through the center of the assessed tree. 2.4. Data analysis Comparisons of Picea shadow values were made using the lower- (QL, minimum to first-quartile values) and upper-most (QU , third-quartile values to maximum) portions of each species’ abundance distribution. Use of these portions of the plot cell data allowed a comparison of shadow abundance values relative to the cover extremes of each understory species. Samples equal to the quartile value, but outside the 25th and 75th percentile limits were included in the assessed data. As a result, the number of plot cells per compared group was greater than one-fourth of the data (i.e., >100). All comparative analyses were based on combined Plot A and Plot B data, and included only species with ≥30% frequency among plot cells. Mann–Whitney and Kruskal–Wallis tests were used to compare paired groups and data sets with >2 group, respectively. These statistical procedures were used because individual groups did not conform to a normal distribution based on Kolmogorov–Smirnov tests. Furthermore, a single transformation function could not be found that was simultaneously applicable to several groups to create normality. Nonparametric Scheffé rank tests (Miller, 1966, p. 166 – formula 110) at the ˛ 0.050 level were used to identify differences among groups within significant Kruskal–Wallis tests. Polynomial regression based on Microsoft Office Excel edition 2003 software was used to model temporal trends in shadow data. Individual regression models were limited to two beta-coefficients to maximize the comparability of the resulting curves. The inclusion of additional beta-coefficients did not substantially improve the degree of fit to the data. Spearman rank order correlation (rs ) was used to determine the numerical strength between variables and their relative association. Probability values (P) < 0.050 were considered to represent significant differences between or among tested groups. Cluster analysis based on relative Euclidean distance and Ward’s method, and detrended correspondence analysis were used to group and ordinate plot cells based on understory species composition and percent cover (McCune and Mefford, 1999). Descriptive statistics were compiled and most comparative tests were conducted using STATISTICA software (Statsoft, 1995). Scheffé rank and Kruskal–Wallis tests (Sokal and Rohlf, 1981, p. 431) with >8000 cases were manually determined due to STATISTICA software limitations. Dominance concentration among species was calculated based on the method described by Strong (2002). 3. Results 3.1. Vegetation characteristics Both sampled stands were dominated by a relatively continuous P. tremuloides tree canopy that reached a height of ∼17 m. Plot A contained the equivalent of 1733 P. tremuloides stems/ha compared to 1200 stem/ha in Plot B, although Plot B had greater overstory

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Table 1 Composition, average percent cover [standard deviation], and percent frequency of species among plot cells in two central Yukon Populus tremuloides plots. Species comparisons based on Mann–Whitney U-tests. Species Overstory plants >1 m tall Populus tremuloides Picea albertiana Salix spp. Understory plants ≤1 m tall Achillea millefolium Arctostaphylos uva-ursi [ARUV]b Arnica lonchophylla Bromus inermis ssp. pumpellianus Calamagrostis canadensis Calamagrostis purpurascens [CAPU] Chamerion angustifolium [CHAN] Cnidium cnidiifolium Corallorhiza trifida Galium boreale Geocaulon lividum [GELI] Hedysarum alpinum Hylocomium splendens [HYSP] Leymus innovatus Linnaea borealis [LIBO] Lupinus arcticus Mertensia paniculata Orthilia secunda Pedicularis labradorica Picea albertiana Picea mariana Populus balsamifera Populus tremuloides Ptilium crista-castrensis Pyrola chlorantha Rosa acicularis [ROAC] Salix spp. Shepherdia canadensis [SHCA] Solidago simplex Vaccinium vitis-idaea [VAVI] Viburnum edule Zigadenus elegans Number of trees >1 m tall Populus tremuloides Picea albertiana Basal area (m2 /ha) Populus tremuloides Picea albertiana Stand age (years) Understory characteristics Total average percent cover Richness (species per quadrat) Dominance concentration Number of quadrats a b

Plot A 50[32]87 14[29]32 3[15]7

Plot B Mean[sd] Frequency 66[28]95 19[32]36 2[9]7

P <0.001 <0.003 0.970

0 26[29]85 +[+]6 1[4]29 +[+]2 6[7]77 2[3]73 0 0 +[+]2 6[9]65 0 1[3]28 +[+]<1 4[7]94 2[5]45 +[1]23 +[+]21 <1[3]18 +[2]6 +[+]<1 +[+]1 +[2]7 +[+]1 0 11[10]95 0 17[20]80 0 3[6]65 +[2]3 1[2]40

+[+]+a 8[16]47 +[+]7 0 0 5[7]45 2[3]57 +[+]16 +[+]+ 0 3[7]34 +[1]7 2[4]46 0 +[+]<1 +[<1]3 1[3]33 +[1]7 0 +[+]5 0 +[+]<1 +[+]2 0 +[+]1 +[2]8 +[3]3 32[24]87 +[+]<1 0 0 0

0.317 <0.001 0.671 <0.001 0.045 <0.001 0.030 <0.001 0.317 0.082 <0.001 <0.001 <0.001 0.317 <0.001 <0.001 0.003 <0.001 <0.001 0.810 0.317 0.561 0.030 0.317 0.157 <0.001 0.014 <0.001 0.317 <0.001 0.025 <0.001

156 62

108 78

– –

25.9 3.9 114

16.2 7.0 89

– – –

82[32] 8.6[2.0] 0.592 200

54[27] 4.1[1.8] 0.653 200

– – – –

A “+” equal to or less than 0.55. Bracketed letters are acronyms for species referred to in the text.

cover (Table 1). P. albertiana ssp. albertiana (western white spruce, hereafter referred to as Picea) were scattered throughout each plot, with no obvious pattern of occurrence. A total of 62 and 78 Picea occurred in each plot, or the equivalent of 689 and 867 stems/ha, respectively. Picea >1 m tall had <20% tree canopy cover (Table 1), with only one tree in each plot equalling or exceeding the height of the P. tremuloides overstory (Fig. 2). Trees 1–3 m tall were more frequent in Plot A than Plot B and represented half the Picea in Plot A. In Plot B, up to 15 Picea occurred in the 3–13 m height classes, but fewer (3–10) were present in Plot A. An average Picea tree was 6 m tall and had a basal diameter of 7.7 cm, with a canopy width of 155 cm that occurred 67 cm above the forest floor. P. tremuloides trees had basal areas equal to 25.9 and 16.2 m2 /ha in Plot A and Plot B (W.L Strong, published 2009 field data), with Picea comprising an additional 3.9 and 7.0 m2 /ha, respectively. The difference in P. tremuloides basal area was driven by stem densities, because both stand had trees with an average basal diameter of ∼13.75 cm.

Fig. 2. Frequency distribution of Picea albertiana trees by height class based on data from two 30-m × 30-m Populus tremuloides plots located in central Yukon.

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Fig. 4. Frequency distribution of percent Picea albertiana shadow cover values (n = 5200) based on 400 plot cells from two Populus tremuloides stands on June 21 between 7:00 and 19:00 h, inclusive.

Fig. 3. Ordination and classification of 400 Populus tremuloides plot cells based on understory species composition and percent cover. Naming of groups was based on the most abundant species. See Table 1 for species names.

of the sampled area was covered with shadows at 7:00 and 19:00 h, respectively, but only 24% occurred at 13:00 h. Plot A incurred less (28%) Picea shadow than did Plot B (38%). Approximately 45% (n = 1170) and 32% (n = 837) of the cells in Plot A and B, respectively, had <10% Picea shadow cover at sometime during the day (Fig. 4). On average, 177 (±41) cells per plot occurred in each of the >10% Picea shadow cover classes, with Plot A consistently having fewer occurrences in classes with >30% cover than Plot B. 3.3. QU species abundance and Picea shadows

The understory vegetation of Plot A was dominated by a combination of S. canadensis (SHCA), R. acicularis (ROAC), Calamagrostis purpurascens (purple reedgrass – CAPU), and Arctostaphylos uva-ursi (bearberry – ARUV). These four species comprised threefourths of the total understory plant cover (Table 1). Plot B contained the same species, but ROAC and ARUV had substantially reduced covers and SHCA was twice as abundant compared to Plot A. SHCA composed almost two-thirds of the total understory plant cover in Plot B. Other significant differences between the plots were largely limited to taxa with ≤3% average cover (Table 1). Nonvascular species represented up to 2% cover in both plots. The understory vegetation in both plots seldom exceeded a height of 50 cm, excluding trees and Salix spp. Plot A was floristically twice as richer with less dominance concentration among understory species than Plot B (Table 1). A continuum of botanical composition occurred among the 400 sampled plot cells, although three species groupings were identifiable based on cluster analysis (Fig. 3). SHCA-dominated (average 44% cover, 100% frequency) plot cells (n = 185) occurred on the left-side of the detrended correspondence analysis ordination, with ARUV–ROAC plot cells (n = 104) on the right-side. The latter species group was dominated by ARUV with 52% cover (100% frequency) and lesser amounts of ROAC (10%) and CAPU (6%) cover, with frequency values of 79 and 76%, respectively. Between these opposing groups (Fig. 3) occurred plots cells (n = 111) that included a complex of species (ROAC, SHCA, CAPU, and C. angustifolium – CHAN) with 70–80% frequency and mean cover values ranging from 3 to 10%. Both plots contained multiple occurrences of the three species groupings. Differences in species composition and abundance explained 61.8% the total variance among plot cells in the ordination, with the x-axis explaining 44%. 3.2. Picea shadows among plot cells Picea shadows intercepted the 400 sampled plot cells 7384 times, with an average of 47% (range 30–83%) cover throughout the day, although the actual area of cover was less due to shadow overlap (33%). Based on the largest value per plot cell, 46 and 48%

Nine understory species with >30% frequency occurred among plots cells: ARUV; CAPU; CHAN; H. splendens (HYSP); Geocaulon lividum (toadflax – GELI); Linnaea borealis (twinflower – LIBO); ROAC; SHCA; and Vaccinium vitis-idaea (bog cranberry – VAVI). The amount of Picea shadow associated with these species varied during daylight hours. At 7:00 h, ARUV, ROAC, LIBO, and VAVI incurred ∼35–40% shadow cover. By 12:00–13:00 h, ARUV had <12% shadow cover, which was less than the other species. No differences (P > 0.050) occurred in the amount of shadow associated with ROAC, LIBO, or VAVI with 20–22% shadow cover at the solar zenith (Fig. 5 and Table 2). Plot cells with greater abundances of GELI, HYSP, and SHCA were covered with >45% shadow at 7:00 h, which was significantly more than the amount associated with the previous species. Although the extent of Picea shadow decreased from 7:00 h to 12:00–13:00 h, no differentiation occurred among GELI, HYSP, and SHCA (Fig. 5). Furthermore, the amount of incurred mid-day (11:00–14:00 h) Picea shadow remained greater than occurred with the other species. Plot cells with greater amounts of CHAN cover had Picea shadow values between ARUV and ROAC at mid-day, with early morning and late afternoon levels similar to SHCA values (Fig. 5). Mid-day Picea shadow values for CAPU occurred between VAVI and SHCA based on polynomial regression modelling (Fig. 5). The increase in shadow area after 13:00 h generally paralleled the patterns of decrease during the morning hours. Between 11:00 and 14:00 h, each understory species incurred not more than 30% Picea shadow (Table 2 and Fig. 5). Fig. 6A illustrates the relative relationships among understory species with respect to the amount of Picea shadow each incurred between 7:00 and 19:00 h on June 21. One separate and three partially overlapping groups of species occurred. GELI, HYSP, and SHCA were segregated from the other species, based on the greater amount of shadow they incurred during the day (>33%). These species also received <6 continuous hours of sunlight with <30% Picea shadow. ROAC, LIBO, VAVI, and CHAN incurred intermediate amount of shadow relative to ARUV and CAPU, with CAPU transitional to the three most shaded species. ARUV and ROAC were associated with the least amount of Picea shadow at <26% and

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Table 2 Average amount of Picea albertiana shadow cover among plot cells in the upper portion (QU ) of each species abundance distribution. Comparisons among species based on Kruskal–Wallis tests. Species values followed by the same letter(s) do not differ at the ˛ 0.05 level based on Scheffé rank tests. Understory speciesa ARUV 112

n

CAPU 110

CHAN 127

GELI 106

HYSP 117

LIBO 122

ROAC 106

SHCA 116

VAVI 130

Percent Picea albertiana shadow coverb

Hour

P

7:00

38a

45b

46bc

48bc

49bc

39a

38a

51c

39a

0.010

8:00

30a

37b

38b

42b

43b

32a

26a

42b

30a

<0.001

9:00

23a

30b

32bc

34bcd

37d

24a

23a

33cd

23a

<0.001

10:00

19a

31c

23b

32c

31c

22ab

22ab

31c

23b

<0.001

11:00

15a

28ef

20b

30f

29f

22bcd

22bc

26def

23cde

<0.001

12:00

8a

24cde

14b

28ef

23def

21c

22cd

28f

20cd

<0.001

13:00

11a

24de

16b

27f

28ef

20bc

23cde

26ef

22cd

<0.001

14:00

14a

23b

19b

29cd

31d

19b

19b

28c

21b

<0.001

15:00

23abc

19a

20ab

28de

29e

24bcd

19abc

30e

25cd

0.004

16:00 17:00

20a 28ab

25a 34bc

27a 33bc

29a 37cd

31a 35c

23a 35c

24a 27a

33a 42d

25a 34c

0.091 0.026

18:00

41bc

38ab

42cd

44cd

45d

39bc

33a

47d

36ab

0.033

19:00

46bc

51c

47bc

46b

48bc

41a

39a

50bc

37a

0.006

3–30

6–50

1–30

1–45

8–45

40–90

0.3–50

6

15

4

6

17

56

4

Range of percent cover 25–95 8–35 Average percent species cover 53 16 a b

See Table 1 for full species names. Underscored and double-underscored values identify species with the least and most shadow, respectively.

Fig. 6. Relative relationships among nine Populus tremuloides understory species based on (A) hourly percent Picea albertiana shadow cover values (7:00–19:00 h) on June 21 (QU data), and (B) distances between Picea albertiana trees and the nearest northward plot cell used for understory vegetation sampling. Comparisons made using Kruskal–Wallis tests (P < 0.001). Underscored species were not significantly different at ˛ 0.05 level based on Scheffé rank tests. a See Table 1 for full species names; b n = 1378–1690 cases per species; c n = 97–120 cases per species.

Fig. 5. Polynomial regression models for nine Populus tremuloides understory species based on average hourly percent Picea albertiana shadow cover values (QU data). Individual regression coefficients (R) ranging from 0.932 to 0.990 (P < 0.001, n = 13 per species). See Table 1 for full species names.

>9 h of continuous light exposure. The top-to-bottom sequence of understory species at mid-day in Fig. 5 was similar to the left-toright sequence in Fig. 6A, with one major difference; the CHAN regression curve occurred between ARUV and ROAC, but was more closely associated with CAPU in Fig. 6A. The alternative analysis of Picea shadow cover based on averaged hourly values by plot cell also indicated a significant difference (P < 0.001) occurred among species. An associated Scheffé rank analysis identified two groupings with the following memberships: ARUV, ROSA, VAVI, LIBO, CHAN, and CAPU; and CHAN, CAPU, HYSP, GELI, and SHCA. Based on QU data, ARUV occurred further from Picea trees than HYSP and SHCA, with the other species occupying intermediate distances (Fig. 6B). The relative distance between Picea and the most abundant occurrences of HYSP or SHCA was on average equal to one-third (3:1 ratio) the height of the nearest Picea, whereas ARUV occurred at distances equal to ∼56% (1.8:1 ratio). None of the understory species were associated with any particular azimuth north of the nearest occurring Picea tree.

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Table 3 Differences in Picea albertiana shadow cover between QU and QL species abundance groups. Understory speciesa

n (QU ) n (QL )

ARUV 112 135

Hour

Difference in percent shadow (mean QU minus mean QL )b , c

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 Average Pd

CAPU 110 155

−14.5* −14.4* −13.9* −15.7* −18.5* −25.3* −21.9* −22.0* −10.9* −16.5* −9.3* −3.2 −4.7 −14.7 <0.001

−0.3 −3.8 −2.5 −2.6† −0.5 −4.8† −2.8 −5.7* −12.5* −9.8* −4.0† −8.1* +2.3 −4.2 <0.001

CHAN 127 140

−4.4 −3.4 −3.5 −10.0* −10.8* −16.8* −14.7* −14.9* −14.6* −11.2* −6.9* −1.8 −1.4 −8.8 <0.001

GELI 106 203

HYSP 117 252

LIBO 122 211

ROAC 106 201

SHCA 116 112

VAVI 130 270

−0.2 +1.9 +1.9 +4.3 +3.3 +2.9 +2.9 +0.8 +1.0 −0.8 +4.3 +2.6 −2.6 +1.7 0.078

+5.3 +7.5† +7.6* +3.0 +3.8 −1.2 +5.6 +7.1* +4.4† +2.1 −0.9 +4.4 +0.3 +3.8 <0.001

−13.0* −14.4* −14.2* −11.3* −5.4 −5.6* −7.3* −13.5* −7.5* −5.5† −4.1 −7.8* −13.0* −9.4 <0.001

−11.5* −18.2* −15.3* −10.1* −5.3 −3.9 −3.2 −11.8* −11.8* −9.9* −11.7* −13.7* −13.5* −10.8 <0.001

+11.1* +6.8 +3.6 +5.2 +2.8 +7.2 +3.6 +3.7 +4.2 +11.6* +14.1* +11.7* +8.3 +7.2 <0.001

−11.1* −12.6* −13.6* −8.3* −4.4 −5.1 −3.2 −8.3* −3.8 −5.9* −2.6 −9.9* −15.8* −8.0 <0.001

a

See Table 1 for full species names. Asterisks (*) identify both significant (P < 0.050) differences between hourly QL and QU values based on Mann–Whitney U-tests and where percent species cover and percent shadow cover were significantly correlated (maximum r ≤ 0.225, P < 0.05, n = 400). c A cross (†) identifies where percent species cover and percent shadow cover were significantly correlated (maximum r ≤ 0.225, P < 0.05, n = 400). d Analyses based on the comparisons of diurnal QU and QL shadow data using Mann–Whitney U-tests, with sample sizes by group equal to n × 13. b

3.4. QL species abundance and Picea shadows In the QL data set, eight of nine understory species had average plant cover values of 0%. Approximately, one-fourth (n = 46) of the QL SHCA data set included cover values between 0.3 and 3%, which were very small quantities compared to the corresponding QU data range (Table 2). Significant differences in the amount of incurred Picea shadow occurred between QL and QU plot cells for all the assessed understory species, except GELI (Table 3). ARUV had the largest differential, with significantly less Picea shadow (P ≤ 0.001) occurring throughout the day until 17:00 h and ∼22–25% less shadow from 12:00 to 14:00 h in plot cells where the plant was most abundant (QU data) (Table 3). Plot cells with greater CHAN plant cover incurred 10–17% less Picea shadow between 10:00 and 15:00 h than those lacking the species (QL data). In contrast, sites with greater ROAC or VAVI cover incurred less Picea shadow from 7:00 to 10:00 and 14:00 to 19:00 h than plot cells without their cover, although VAVI afternoon differences were discontinuous (Table 3). Plot cells with LIBO incurred less Picea shadow during the day than those without, except immediately before and after mid-day. Greater CAPU abundance occurred in plot cells that received less afternoon shadow. Although diurnal QL and QU shadow values for HYSP and SHCA were significantly different, they were unlike the other understory species, because their QL sites received less shadow than QU plot cells. These species also had few hourly values that differed with respect to the amount of incurred shadow, although plot cells with greater SHCA abundance received ∼12–14% more Picea shadow in the late afternoon (Table 3). Species-based polynomial regressions of the QL data produced curves similar in configuration to those presented in Fig. 5. Compared to the QU data (Fig. 5), however, they were collectively at a lower elevation (i.e., incurred more shadow) and the mid-day peaks of the sequences were reversed (i.e., ARUV at bottom and GELI, HYSP, and SHCA at top).

Table 4 Spearman rank order correlations (rs ) between percent Picea albertiana canopy and average shadow cover (7:00–19:00 h), and selected Populus tremuloides understory variables (n = 400). Picea albertiana Understory variables

Canopy cover (%)

rs coefficienta

Percent species cover Arctostaphylos uva-ursi Calamagrostis purpurascens Chamerion angustifolium Geocaulon lividum Hylocomium splendens Linnaea borealis Rosa acicularis Shepherdia canadensis Vaccinium vitis-idaea Total understory cover Richness (taxa/plot cell)

Average shadow cover (%)

−0.233c

−0.424c −0.155b −0.260c

nsd −0.203c nsd nsd

nsd −0.109a

nsd −0.138b −0.136b −0.379c −0.245c

+0.146b −0.310c −0.340c +0.192c −0.261c −0.367c −0.375c

a Probability values (P): a = <0.05, b = <0.01, and c = <0.001; nsd – no significant difference.

and richness values were uncorrelated (P > 0.050) or weakly and negatively correlated with percent Picea canopy cover. Picea canopy cover was most strongly correlated with ARUV cover (Table 4). Picea shadow cover explained more variance (rs2 , 1.7–8×) in understory species cover and species richness than did Picea canopy cover, although rs coefficients did not exceed 0.43. ARUV and ROAC were most strongly correlated with shadow cover. Most understory species were negatively correlated with Picea shadow cover, except HYSP and SHCA which were positively correlated. Picea canopy and shadow cover were also inversely related with respect to SHCA cover. Only GELI was correlated with neither Picea canopy nor average diurnal shadow cover. Differences in understory species cover among quadrats were frequently correlated with the amount of incurred Picea shadow based on hourly values (Table 4).

3.5. Understory species correlations 4. Discussion Total understory vegetation cover among plot cells was inversely and similarly correlated with average Picea shadow and total canopy cover (Table 4). Individual understory species cover

The hypothesis that laterally cast Picea shadows influence the abundance of understory species in high-latitude P. tremuloides

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stands was accepted based on results of the data analysis. This acceptance, however, must be qualified to include shadow-effects from previous growing-seasons (Thomas et al., 1999). It was the strong differences in the diurnal distribution and overall abundance of Picea shadows among understory species (Fig. 6A), and the statistically significant disparities in hourly shadow values between plot cells with and without a given species (i.e., QU minus QL values, Table 3) that provided the best corroboration. Acceptance of the hypothesis was not unexpected due to the physiological importance of light for plant survival (Hart and Chen, 2006). Although chronologically younger, Plot B was considered successional more advanced than Plot A, due to the greater frequency, size, and canopy cover of Picea, and the correspondingly greater abundance of SHCA in Plot B. The latter was considered an early seral stage of mixedwood stand development. The inconsistency of stand ages with respect to development status supports the concept that P. tremuloides forest succession rates are a function of when late-successional trees establish rather than stand age (Cumming et al., 2000; Strand et al., 2009). From a plant community perspective, P. tremuloides trees partially limit light transmittance to their understory vegetation, which allows only selected species of the locally flora to occur (i.e., a phytocoenosis), within site limits (e.g., soil moisture regime). Therefore, it appears that shadows resulting from impeded light transmittance through Picea more than their physical presence, often represented by vertical canopy cover, disrupt this ecological balance in the P. tremuloides stand, which facilitates understory change. As a result, once Picea are established and of sufficient size, their shadows are a better predictor of successional change than canopy cover. The better explanatory ability of Picea shadows may be due to their greater areal extent (e.g., 20–25:1 ratio), which provides more opportunity to influence light availability than does vertical canopy cover. The stronger ecological effect of Picea on understory plants, than the more extensive P. tremuloides overstory, may be related to their canopy architecture. Breshears and Ludwig (2010) found that low stature Eucalyptus trees were more effective at reducing ground-level light availability than those with branches and foliage at a higher elevation. This may be the result of lower stature trees having a more compact canopy, and the shorter distance between trees and the ground surface may minimize the amount of diffuse light intrusion in the shadow area. The architecture of Picea may make them efficient at limiting ground-level light available (Kuuluvainen, 1992), because the largest and widest portion of their canopy profile is located on the lower half of the stem, which often begins <1 m from the forest floor. In addition, their branches and needle-shaped leaves in the lower portion of a tree can be dense and multi-layered when viewed from a downward oblique angle. Because of their dense canopy, a few strategically located trees may have a disproportionately greater effect on understory vegetation than individual trees during the early stages of Picea development in a P. tremuloides stand. For example, two juxtaposed trees could increase the duration and possibly the intensity of understory shading where their shadow zone’s overlap, which could accelerate the rate of stand succession. The occurrence of multiple Picea trees would create a complex pattern of overlapping shadow that would be unique to a stand due to differences in tree location, size, and density. Under these conditions, sunlight would only directly reach the forest floor by chance circumstances. An estimate derived from a P. tremuloides basal area-driven regression model developed by Maundrell and Hawkins (2004) indicates that understory plants in Plot A and Plot B would receive 20% and 28%, respectively, of the total mid-day photosynthetic flux on June 21, ignoring the presence of Picea. An alterative model by Comeau (2001), based on light data collected later in the summer, estimated understory light availability at ∼18% and 33%, respectively. These values were similar to light measurements reported in

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other P. tremuloides stands (e.g., 14–40% – Lieffers and Stadt, 1994; 19–32% – Constabel and Lieffers, 1996; daily average 18% – Carlson and Groot, 1997), but were more than double those measured (8.2–13.4%) by Messier et al. (1998). From a successional perspective, the increase in overstory light transmittance from Plot A to Plot B was inconsistent with the reduction in understory species abundance and floristic diversity (richness and dominance concentration), because greater light availability beneath P. tremuloides stands is associated with greater understory cover and diversity (Hart and Chen, 2008). To reduce diversity, the amount of light impeded by Picea trees in Plot B would have needed to exceed the differential between the two plots (i.e., 28% reduced to <20%). This suggests the architecture and dense foliage of Picea make them important regulators of understory light availability where their shadows occur, even when inferior in height and abundance relative to overstory trees. In addition to changing floristic diversity, the development of Picea also increased understory heterogeneity due the uneven distribution of shadows. Prior to the occurrence of Picea, the understory vegetation in Plot B was probably dominated by the ARUV–ROAC and SHCA–ROAC–CAPU–EPAN species groups, like Plot A, but now include a substantial proportion of SHCAdominated patches. The SHCA-dominated patches will likely continue to increase in abundance in both plots, but will eventually be suppressed by greater amounts of shadow resulting from the continued height growth of existing Picea and the establishment of additional trees. In the general absence of vascular understory plants and the demise of major leaf litter producers such as P. tremuloides (Startsev et al., 2008), HYSP cover could expand. Expansion of HYSP would lead to the formation of late-successional Picea/HYSP stands (Rowe, 1956; Viereck, 1970; Strong, 2009). Four types of understory plants occurred in the studied stands with respect to the relative abundance of Picea shadows (Fig. 6A): (1) intolerant (ARUV); (2) partially tolerant (CAPU, CHAN, LIBO, ROAC, and VAVI); (3) tolerant (HYSP and SHCA); and (4) indifferent (GELI) species (cf. Table 3, Figs. 5 and 6A). The similarity of SHCA and HYSP with respect to Picea shadow abundance was probably the most unexpected result. HYSP is known to be very shade-tolerant (Sonesson et al., 1992), whereas SHCA is often associated with open-canopied (30–50% cover) shade-intolerant evergreen (e.g., ecosite LFc1.1) and deciduous (LFc2.1) forests as well as nonforest vegetation (LFa1.1), although Picea/HYSP stands with a modest SHCA cover (12%) have been reported (UFc4.1) (Beckingham et al., 1996). This implies that SHCA has a broad physiological tolerance range for light exposure and a low photosynthesis compensation point, probably between 1.7% (HYSP, Sonesson et al., 1992) and 7–10% (CHAN, Lieffers and Stadt, 1994) of full sunlight. The lack of differentiation in GELI cover with respect to Picea shadow abundance (Fig. 6A and Table 3) may be due to its root parasitizing habit, which includes Picea spp., P. tremuloides, and ARUV as hosts (Warrington, 1970); therefore, the distribution of GELI would not be independent of its host’s root system with respect to light availability. Classifying the diurnal light regime of individual understory species may be more complex than just categorizing them as either shadow/shade-tolerant or -intolerant plants, based on the hourly shadow differences identified in Table 3. Species such as ARUV might readily fit such a classification, but others that receive extra light during afternoon hours (CAPU), or twice (ROAC) versus once (CHAN) during the day compared to sites where they are absent are not as easily categorized. In addition, these differences in shadow regime do not consider ecological factors such as interspecific competition that may have systematically biased the abundance of individual species. It is not known how representative the described species shadow regimes are compared to the full growing-season (Tables 2 and 3), because no long-term diurnal

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or summer analyses were available for comparison. In the study area, however, the solar zenith was 49.2◦ (±1.5◦ ) from May 21 to July 21 (Cornwall et al., 2010), which suggests no major variations occurred in the sizes of hourly Picea shadows during most of the growing season. The measurement of light availability at no specified time or only during mid-day (e.g., Lieffers and Stadt, 1994; Maundrell and Hawkins, 2004) may not provide sufficient information to differentiate or characterize the photosynthetic niche of individual species (cf. CHAN and ROAC – Table 3) or understory vegetation types. Whereas light measurements within fixed time limits allow greater sample comparability, they do not account for diurnal differences in abundance or photosynthetic spectra, which vary with sun elevation (Messier et al., 1998; Gendron et al., 2006). Several species also did not differ in the amount of incurred midday shadow relative to plot cells where they were absent. For these reasons, it may be necessary to assess the full diurnal light regime of understory species to properly classify their shade-tolerance. The identified differences in lateral Picea shadow abundance may offer a viable technique for evaluating variation in understory vegetation structure and species composition within and between forest stands. This possibility stems from the strong correlation that occurs between understory vegetation cover and light availability (Messier et al., 1998, p. 515). Analysis of shadows may offer advantages over conventional instrumentation methods based on photometer measurements. For instance, an instrumented analysis using the current study’s sampling design would have require the simultaneous and repeated measurement of light availability in 200 cells per study plot. Besides the potentially substantial cost of equipment, comparability among hourly readings might be difficult to achieve without consistent atmospheric conditions throughout the day. Shadow analyses supplemented with light measurements could represent a robust approach to studying forest overstory–understory plant relationships in mixed P. tremuloides–Picea stands. 5. Conclusions The study results show that laterally cast Picea shadows have an effect on the composition and distribution of understory plants beneath P. tremuloides trees, even when Picea are of low abundance and subdominant members of the overstory. An analysis of Picea shadows may be a useful approach for studying temporal change and within stand species variation in conjunction with, or in the absence of, comprehensive solar radiation measurements and known photosynthesis compensation points for individual species. As an analytical variable, the use of lateral shadows may be difficult to apply, except at the stand-level due to the localized effects of individual trees. Picea shadows also appear a better measure than Picea canopy cover for such analyses. A greater appreciation of understory species change in response to increasing Picea abundance could facilitate a better understanding of mixedwood stand ecology. Such knowledge would enable the development of more comprehensive forest succession models and better site classification systems than currently exist. Such tools would be useful to a variety of landscape managers including foresters and wildlife habitat biologists. Acknowledgements An anonymous reviewer provided comments that improved the clarity of the final manuscript. References Anderson, L.E., Crum, H.A., Buck, W.R., 1990. Checklist of mosses of North America north of Mexico. Bryologist 93, 448–499.

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