Understory plant communities vary with tree productivity in two reclaimed boreal upland forest types in Canada

Forest Ecology and Management 453 (2019) 117577

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Understory plant communities vary with tree productivity in two reclaimed boreal upland forest types in Canada Min Duana,b,d, Jason Housed, Scott X. Changc,d,

T

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a

Key Laboratory of Ecology of Rare and Endangered Species and Environmental Protection (Guangxi Normal University), Ministry of Education, Guilin 541004, China Centre for Ecological Forecasting and Global Change, College of Forestry, Northwest A & F University, Yangling 712100, China c State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China d Department of Renewable Resources, University of Alberta, Edmonton T6G 2E3, Canada b

A R T I C LE I N FO

A B S T R A C T

Keywords: Disturbance Lodgepole pine Oil sands region Plant community Species diversity White spruce

The dynamics of understory plant communities in forest ecosystems with different tree productivities that are reclaimed after surface mining is poorly studied. In the Athabasca oil sands region of Canada, the cover, composition, diversity and foliar nutrient concentrations of understory vascular plant communities were examined on reclaimed sites (at least 15 years old since site reconstruction) with low, medium and high productivity that were planted to lodgepole pine (Pinus contorta) and white spruce (Picea glauca). Understory plant communities showed different responses to tree productivity classes in both pine and spruce stands. On pine sites, higher shrub and grass covers contributed to higher total cover on medium than on low and high productivity sites; however, low and high productivity sites had higher species richness and Shannon-Wiener index than medium productivity sites. In addition, shrub, grass and total covers were all positively correlated with cover soil thickness, soil dissolved organic carbon and inorganic nitrogen concentrations, but there was no relationship between any understory plant community variable and tree growth parameters. On spruce sites, lower shrub and forb covers and higher grass cover on high than on low and medium productivity sites resulted in no difference in total cover among productivity classes; however, species richness and Shannon-Wiener index were higher on medium than on low and high productivity sites. Additionally, forb cover, species richness and Shannon-Wiener index were all negatively correlated with leaf area index, and grass cover and species evenness were positively correlated with tree growth parameters such as height, diameter at breast height and aboveground biomass increments. We conclude that the relationships between tree productivity and understory plant communities in reclaimed forest ecosystems were site specific. Reclamation strategies such as adopting a proper planted tree spacing or fertilization should be used on sites with different tree productivities to balance overstory tree growth with understory plant community development in reclaiming surface-disturbed mining areas.

1. Introduction In forested regions, an important target for reclamation after mining is to revegetate plant communities that have similar appearance, species composition and diversity to nearby natural ecosystems in the region (Macdonald et al., 2015). Plant communities can affect ecosystem processes such as biomass production, soil organic matter decomposition and nutrient recycling by biologically capturing essential resources, including nutrients, water and light, and regularly returning leaf and root litter to the soil (Cardinale et al., 2012). High plant species diversity can enhance the recovery rate of forest ecosystems following disturbance, while low diversity may negatively influence the variety and stability of ecosystem functions and services (Loreau et al., 2001;

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Aerts and Honnay, 2011; Dhar et al., 2018). Moreover, differences in species composition can also influence productivity and other ecosystem properties (Smith and Knapp, 2003; Hooper et al., 2005; McLaren and Turkington, 2010). Creating diverse, self-sustaining and resilient native plant communities is one of the main goals of restoring local boreal forest ecosystems in the oil sands region of Canada (Alberta Government, 2005; Macdonald et al., 2015). Most research on the reclamation of mining disturbed sites has focused on the successful reforestation of planted tree species (Pinno et al., 2012; Duan and Chang, 2015; Pokharel et al., 2017). Less attention has been paid to the dynamics of understory plant communities that develop among the planted tree species (Dhar et al., 2018). Because reclamation is a relatively new endeavor in the oil sands region

Corresponding author at: Department of Renewable Resources, University of Alberta, Edmonton T6G 2E3, Canada. E-mail address: [email protected] (S.X. Chang).

https://doi.org/10.1016/j.foreco.2019.117577 Received 16 February 2019; Received in revised form 27 August 2019; Accepted 27 August 2019 0378-1127/ © 2019 Elsevier B.V. All rights reserved.

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communities would be positively related to resource availability on pine and spruce sites.

and there is limited availability of old reclaimed forest stands (> 15 years), most existing studies on understory plant communities are limited to recently reclaimed forest ecosystems (< 5 years) (Barbour et al., 2007b; Mackenzie and Naeth, 2010; Brown and Naeth, 2014). Investigating the characteristics of understory plant communities in older reclaimed forest ecosystems can provide strategies for restoration of understory plant communities in mining areas. In oil sands reclamation, understory vascular plant communities typically develop via seed and bud banks in the cover soil (Mackenzie and Naeth, 2010), via seed transported in from surrounding areas (Hardy BBT Ltd., 1990), and occasionally via direct seeding and/or planting as a part of a reclamation prescription (Naeth et al., 2011). Cover soils in reclaimed forest ecosystems initially provide the bulk of soil moisture and nutrients for plant establishment, survival and growth. In the Athabasca oil sands region (AOSR) of Alberta, Canada, the peat-mineral soil mix (PMM), made by mixing peat with mineral soil, is commonly used as a cover soil. Peat in PMM increases soil water holding capacity (Moskal et al., 2001) and its decomposition is the primary source of nutrients for plants (Hemstock et al., 2010). As the development of reclaimed sites proceeds, the planted trees and understory plant communities begin to interact with each other through interspecies competition for light, nutrients and water (Schwinning and Weiner, 1998; Halpern and Lutz, 2013) or through influencing soil nutrient availability by leaf and root litter input into the soil (Bartels and Chen, 2013; Feng et al., 2019), thus resulting in varied tree productivity and plant species diversity on reclaimed sites. In natural ecosystems, the relationship between productivity and species diversity is complicated and has been extensively studied and discussed (Abrams, 1995; Loreau et al., 2001; Tilman et al., 1997, 2001; Hooper et al., 2005; Cardinale et al., 2012; Reich et al., 2012; Liang et al., 2015; Zhang et al., 2017). A unimodal pattern, no pattern and monotonic increase or decrease relationship between productivity and species diversity were reported at varying hierarchical and spatial scales (Abrams, 1995; Loreau et al., 2001; Hooper et al., 2005; Cardinale et al., 2012). Tilman and Pacala (1993) and Huston and DeAngelis (1994) attributed the unimodal pattern to competitive exclusion due to changes of resource heterogeneity at different productivities. Reich et al. (2012) reported that productivity regulated understory diversity by affecting resource availability and heterogeneity in boreal forests, while Liang et al. (2015) found that diversity affected plant productivity through niche–efficiency. However, how understory plant communities vary with different tree productivities in reclaimed forest ecosystems has seldom been studied and their relationship is still not clear, as reclaimed forest ecosystems are examples of novel ecosystems (Hobbs et al., 2006; Aerts and Honnay, 2011), and their properties and successional trajectories are largely affected by anthropogenic factors such as the reshaping of the topography, PMM thickness, soil salinity, cover soil types and substrate material types (Sobey, 2014; Dhar et al., 2018, 2019). The objectives of this study were to: (1) Compare the cover and diversity of understory vascular plant communities with different tree productivities in reclaimed forest stands in the AOSR, which have been reclaimed at least 15 years since site reconstruction; (2) Explore potential factors affecting understory plant community cover and diversity in stands with low, medium and high productivity for planted lodgepole pine (Pinus contorta) and white spruce (Picea glauca). We hypothesized that the cover and diversity of understory plant communities would decrease monotonically from low to medium to high tree productivity sites, because understory plant species on sites with higher productivity may undergo more competition for light from planted trees than those on sites with lower productivity. Although lower productivity sites may have relatively lower nutrient and water availabilities, it seems that trees’ preemption of light has a more important influence than their preemption of nutrients and water on understory vegetation (Schwinning and Weiner, 1998; Reich et al., 2012). We also hypothesized that the cover and diversity of understory plant

2. Materials and methods 2.1. Site description and experimental design The research was conducted on an oil sands lease in the AOSR, about 22 km north of Fort McMurray in northeastern Alberta, Canada. The area has a continental boreal climate with short and cool summers and long and cold winters. The mean annual temperature from 1971 to 2000 was 0.7 °C, and the mean annual precipitation was 455.7 mm, with an average of 342.2 mm occurring as rainfall during the growing season (Environment Canada, 2013). A portion of oil sands disturbed lands was reconstructed, and then lodgepole pine or white spruce were planted in the 1980 s and 1990 s to reclaim disturbed lands to upland forest ecosystems. In June 2011, six lodgepole pine and six white spruce sites were located. In April 2012, three pine and three spruce sites were added to increase the sample size (Duan et al., 2015). Lodgepole pine is not indigenous to the oil sands region in northeastern Alberta (Fung and Macyk, 2000). The pine sites, located in areas where the PMM was placed as a cover soil over the tailings sand (TS) substrate material, were planted between 1991 and 1996 (Fig. S1 and Table S1). The spruce sites, located in the areas where the PMM was placed as a cover soil over overburden (OB) substrate material, were planted between 1982 and 1992 (Fig. S1 and Table S1). The nine sites for each tree species made up a tree productivity gradient from low, medium to high based on visual inspection of tree growth performance and the gradient was confirmed later by tree growth increment measurements. A single 10 m × 10 m plot was established on each site.

2.2. Tree and understory plant community measurements Within each plot, tree height and diameter at breast height (DBH, 1.3 m above the ground) were measured in September 2011 and 2012 for the first 12 established sites, and in May and September 2012 for the additional 6 established sites, assuming there was minimal growth during the winter season. Tree height was measured using a height pole and an ultrasonic hypsometer (Vertex III, Haglöf Sweden AB, Västernorrland, Sweden) and tree DBH was measured using a standard diameter measuring tape. Tree height and DBH were then entered into allometric equations from Lambert et al. (2005) and Ung et al. (2008) to calculate total aboveground biomass (AB) of trees. The sum of AB for all measured trees within the plot was the AB for each plot. The difference of tree height, DBH and AB between measurement intervals was the current annual increment of height (HI), diameter at breast height (DBHI) and aboveground biomass (ABI). Leaf area index (LAI) was measured in July 2012 with a plant canopy analyzer (LAI 2000, LI-COR Inc., Lincoln, NE) on overcast days at 30 cm above the ground surface on a 3 × 3 m grid (nine in total) in each plot with a matching open sky reading. Measurements were taken in the morning with the sensor facing west and in the afternoon facing east to avoid the sensor pointing towards the sun. An 180˚ view restrictor was placed on the sensor to reduce interference from the operator and direct sunlight. Five 1 × 1 m quadrats were randomly placed along the perimeter of the plot where there was no disturbance (foot traffic). An understory vegetation survey was conducted within each quadrat during the period of peak vegetation cover in July 2012. Understory vegetation including shrubs, forbs and grasses were identified to the species level. The percent cover of individual species was visually estimated by the same person to minimize variation. The cover of shrub, forb or grass layer (and the total cover) was the sum of all species covers within each category. 2

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2.5. Calculation of understory plant species occurrence, richness, evenness and diversity

2.3. Site characteristic measurements and soil and plant sampling The year of tree planting and the history of the site were obtained for each site from reclamation site reports of the oil company (Table S1). Two soil pits were dug in each plot to determine the thickness of the PMM cover soil applied. Bulk density of the PMM was determined in each soil pit using the steel ring method. Soil water content and temperature of the PMM were monitored using the time domain reflectometer (TDR) (CS616, Campbell Scientific Inc., Logan, UT) and type T thermocouple (Omega Engineering Inc., Montreal, Canada), respectively, in the initial 12 sites established in June 2011. The remaining sites were not monitored due to equipment availability. The sensors were installed 10 cm below the PMM from May 1 to September 30 in 2012. The data were recorded hourly by CR10X data loggers (Campbell Scientific Inc., Logan, UT). The mean soil water content and temperature of the PMM during the growing season on each site was calculated by averaging the data from May 1 to September 30 in 2012. In each plot, 0 to 20 cm PMM soil samples were collected using an auger in five randomly selected locations to obtain a composite PMM sample. Soil samples were placed in plastic bags immediately after sampling, stored in a cooler and taken back to the laboratory. To analyze nutrients of understory plant species, foliar samples of dandelion (Taraxacum officinale) were collected from each plot, placed in paper bags, stored in a cooler and transported to the laboratory for analyses. Although dandelion and sweet clover (Melilotus spp.) were both the most commonly observed understory plant species on pine and spruce sites (Fig. S2), only the dandelion was sampled, as sweet clover is a nitrogen (N)-fixing plant that may not reflect soil nutrient status, especially N.

Species occurrence was calculated as the percent of quadrats where a species occurred. Species richness was calculated as the total number of species in a quadrat. Species evenness in a quadrat was evaluated using the Evar (Smith and Wilson, 1996): s

Evar = 1 − 2/ π arctan

⎧ ∑ ⎨ i=1 ⎩

⎛ ⎜ln(x i ) − ⎝

s

2

∑ (xi)/s⎞⎟ i=1

⎠

/s

⎫ ⎬ ⎭

where s is the number of species and xi is the abundance of the ith species in a quadrat. The output ranges from 0 to 1. Species diversity was evaluated using the Shannon-Wiener index (Shannon and Wiener, 1963), which takes into account both species richness and their relative abundance: s

H ' = − ∑ pi ln(pi ) i=1

where s is the number of species in a quadrat and pi is the proportion of individual in the total sample belonging to the ith species. 2.6. Statistical analyses The average of five quadrats within each plot was a replicate for each treatment. Nine plots for each tree species were grouped into low, medium, and high productivity classes (r = 3 plots per tree productivity class per species) based on visual inspection of tree growth performance and later confirmed by ABI (Fig. S2). As pine and spruce plots were spatially segregated and had different substrates and planting dates, understory plant communities were not compared between pine and spruce sites. Within their respective areas, however, the pine plots and the spruce plots representing each of the three productivity classes were randomly distributed with no spatial structure (Fig. S1 and Table S1). A one-way analysis of variance (ANOVA) and Tukey’s multiple comparison were conducted to examine the statistical significance of tree growth parameters, soil properties, understory plant community cover, plant species richness, evenness and diversity and dandelion foliar nutrient concentrations among low, medium and high productivity classes within each tree species. Percent cover data were logarithmically transformed to meet assumptions of normal distribution and homogeneous variance before conducting the ANOVA. The non-transformed data are presented in this paper. Pearson correlation analyses were used to explore relationships between understory plant community variables (e.g. cover, plant species richness, evenness and diversity) and tree growth parameters (e.g. HI, DBHI, ABI) or soil properties (e.g. soil water content, soil temperature, PMM thickness, bulk density, soil EC, TC, TN, DOC, DON and inorganic N) on pine or spruce sites. An α value of 0.05 was chosen to indicate the statistical significance in all analyses. Statistical analyses were performed using SAS software (SAS 9.2, SAS Institute Inc., Cary, NC).

2.4. Analyses of soil and understory plant species foliage In the laboratory, fresh soil samples were passed through a 2 mm sieve and manually homogenized after removing coarse fragments and visible roots. The subsample of the sieved soil was air-dried at room temperature for soil total carbon (TC) and total N (TN) analyses and the rest was stored in a refrigerator at 4 °C for other analyses. Soil electrical conductivity (EC) was measured using an AP75 portable waterproof conductivity/TDS meter (Thermo Fisher Scientific Inc., Waltham, MA) with a soil to water ratio of 1:2 (w:v). The concentrations of soil NH4+N and NO3−-N were measured using a steam distillation and titration method after sieved soil samples were extracted with a 2 mol L−1 KCl solution. The concentrations of soil total dissolved C and total dissolved N were measured using a TOC/TN analyzer (Multi N/C®2100(S), Analytik Jena AG, Jena, Germany) after sieved soil samples were extracted with a 0.5 mol L−1 K2SO4 solution. The soil dissolved organic C (DOC) concentration was equal to soil total dissolved C concentration as no inorganic C was found in the soil. The soil dissolved organic N (DON) concentration was calculated by subtracting NH4+-N and NO3−N concentrations from the total dissolved N concentration. The concentrations of soil TC and TN were analyzed with a Carlo Erba NA 1500 elemental analyzer (Carlo Erba Instruments, Milano, Italy) after airdried soil samples were ground with a ball mill to pass through a 0.15 mm sieve. Fresh foliar samples were rinsed twice with distilled water and then oven-dried at 65 °C until constant weight. Samples were ground for foliar nutrient analyses. Concentration of foliar N was analyzed with a Carlo Erba NA 1500 elemental analyzer (Carlo Erba Instruments, Milano, Italy). Concentrations of foliar P, K, Ca and Mg were analyzed with a PerkinElmer Optima 3000 DV ICP–MS (PerkinElmer Inc., Shelton, CT) after digestion using concentrated HNO3 and 30% H2O2 at 125 °C for 4 h on a digestion block (Campbell and Plank, 1998).

3. Results 3.1. Tree growth and soil properties on pine and spruce sites There were great variations of tree growth and soil property parameters among low, medium and high productivity classes on lodgepole pine and white spruce sites (Table 1). On pine sites, tree height ranged from 3.2 to 5.2 m, DBH from 4.7 to 7.7 cm, increasing significantly from low to medium and high productivity classes (p = 0.039 and 0.026 for height and DBH, respectively). LAI was higher on medium and high than on low productivity class (p < 0.001). Soil water content and DON concentration of PMM on medium and high productivity classes were higher than those on low productivity class (p = 0.042 and 0.033 3

Forest Ecology and Management 453 (2019) 117577 a Pine, lodgepole pine sites reconstructed using tailings sand as a substrate below a peat-mineral soil mix cover soil; Spruce, white spruce sites reconstructed using overburden as a substrate below a peat-mineral soil mix cover soil. b Site class, lodgepole pine or white spruce sites were grouped into low, medium, and high productivity classes based on visual inspection of tree growth performance, which was later confirmed by the aboveground biomass increment measurement. c Tree size was measured at the beginning of the study. d DBH, diameter at breast height (1.3 m above the ground); LAI, leaf area index. e EC, electrical conductivity; DOC, dissolved organic carbon; DON, dissolved organic nitrogen. * Lowercase letters indicate significant differences (p < 0.05) among productivity classes within each tree species; Numbers in parentheses are standard errors of means (n = 3).

3.2 (0.4) a 4.8 (0.6) b 5.6 (0.7) b 5.2 (1.8) 4.6 (1.4) 8.8 (2.3) 3.6 (0.5) a 5.1 (0.4) b 6.6 (0.8) c Low Medium High Sprucea

4.3 (0.7) a 6.7 (0.4) b 8.3 (1.0) c

1.8 (0.5) a 2.2 (0.1) a 3.1 (0.3) b

21.8 (2.1) 19.8 (3.3) 28.3 (5.7)

1.1 (0.1) b 1.0 (0.1) ab 0.7 (0.2) a

18.1 (2.0) 16.9 (1.9) 16.1 (1.6)

3.3 (0.5) c 1.8 (0.3) b 1.2 (0.2) a

95.3 (16.6) a 150.3 (56.1) a 231.0 (30.0) b

105.8 (12.8) a 101.1 (20.3) a 199.2 (31.7) b

5.3 (0.7) a 8.9 (1.5) b 7.7 (1.2) b 106.4 (24.9) 145.8 (64.1) 94.5 (19.5) 4.4 (0.9) 5.5 (2.3) 4.5 (1.0) 99.0 (22.8) 139.0 (56.8) 114.7 (34.6) 3.2 (0.2) a* 4.8 (0.4) b 5.2 (0.6) b Low Medium High

Height(m)

Pinea

4.7 (0.4) a 6.1 (0.6) b 7.7 (0.7) c

0.7 (0.1) a 2.3 (0.2) b 2.8 (0.2) c

20.2 (4.8) 21.4 (5.3) 18.3 (3.1)

1.0 (0.1) 1.2 (0.2) 0.9 (0.1)

13.8 (0.4) a 16.0 (0.9) b 18.6 (1.2) b

1.2 (0.1) 1.2 (0.3) 0.8 (0.3)

Total N (Mg ha−1) Moisture(%, v v−1) Bulk density(g cm−3) Thickness(cm) DBHd (cm)

LAId (m2 m−2)

Peat-mineral soil mix Tree sizec Site classb Site type

Table 1 Tree size and soil properties of the studied lodgepole pine and white spruce sites in the Athabasca oil sands region.

Soil ECe (dS m−1)

Total C (Mg ha−1)

DOCe (g m−3)

DONe (g m−3)

M. Duan, et al.

for soil water content and DON, respectively). Otherwise, the soil parameters, including PMM thickness, bulk density, soil EC, TC, TN and DOC, did not show any differences among low, medium and high pine productivity classes (Table 1). On spruce sites, tree height and DBH ranged from 3.6 to 6.6 m and from 4.3 to 8.3 cm, respectively, which also showed a significant tree productivity gradient (p = 0.021 and 0.018 for height and DBH, respectively, Table 1). LAI on low and medium productivity classes was lower than that on high productivity class (p = 0.038). On high productivity class, bulk density and soil EC of PMM were lower than those on low and medium productivity classes (p = 0.045 and 0.008 for bulk density and soil EC, respectively), and concentrations of soil TC, DOC and DON were higher than those on low and medium productivity classes (p = 0.037, 0.029 and 0.040 for soil TC, DOC and DON concentrations, respectively, Table 1). There was no difference in PMM thickness, soil water content and TN concentration among low, medium and high spruce productivity classes.

3.2. Understory plant community cover on low, medium and high productivity pine and spruce sites The cover of understory plant communities, including shrubs, forbs and grasses, on both lodgepole pine and white spruce sites differed significantly among productivity classes (Fig. 1 and Table S2). On pine sites, the covers of shrubs and grasses were higher on medium than on low and high productivity classes (p = 0.030 and 0.023 for shrubs and grasses, respectively, Fig. 1), but there was no significant difference in shrub and grass covers between low and high productivity class. Forb cover was not different among productivity classes. Total cover was

Fig. 1. Shrub, forb, grass and total cover of understory plant communities on low, medium and high productivity lodgepole pine (Pine) and white spruce (Spruce) sites in the Athabasca oil sands region. Lowercase letters above each bar indicate significant differences among productivity classes for each plant layer within each tree species (p < 0.05). Error bars are standard errors of means (n = 3). 4

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(p = 0.223). Species evenness did not differ among productivity classes (Fig. 2b). H′ was lower on medium than on low and high productivity classes (p < 0.001, Fig. 2c). On spruce sites, mean species richness was the highest (7.1) on medium productivity class, followed by low (5.6) and high (4.2) productivity classes (p = 0.026, Fig. 2a). H′ was also the highest on medium productivity class (p = 0.003, Fig. 2c) and not significantly different between low and high productivity class (p = 0.310). There was no difference in species evenness among spruce productivity classes (Fig. 2b). 3.4. Relationships between understory plant communities and tree growth and soil properties on pine and spruce sites On pine sites, total, shrub and grass covers were significantly positively correlated with PMM thickness, soil DOC and inorganic N concentrations, while there were no significant relationships between forb cover or diversity measurements and any soil properties (Table 2). No significant correlation was observed between understory plant community parameters and tree growth variables, suggesting that understory vegetation is site productivity-related rather than tree productivity-related. On spruce sites, total cover was positively correlated with soil inorganic N concentration, but negatively correlated with soil EC (Table 2). Shrub cover was positively correlated with soil DON and inorganic N concentrations, while forb cover was negatively correlated with LAI only. Grass cover was positively correlated with HI, DBHI, ABI and LAI. There was a significant negative relationship between species richness or H′ and LAI. Species evenness was positively correlated with tree growth parameters, including HI, DBHI and ABI, but negatively correlated with soil EC. 3.5. Foliar nutrients of the most commonly observed understory plant species on pine and spruce sites There were significant differences in dandelion foliar nutrient concentrations among productivity classes on both pine and spruce sites (Fig. 3). On pine sites, foliar N and P were 20.6 and 2.3 mg g−1, respectively, on low productivity class, lower than those on medium and high productivity classes (p = 0.022 for foliar N and p < 0.001 for foliar P, Fig. 3a and b). Foliar K was lower on low and medium than on high productivity class (p < 0.001, Fig. 3c), but there was no difference in foliar Ca and Mg among productivity classes (Fig. 3d and e). On spruce sites, there was no difference in foliar N, K, Ca and Mg among low, medium and high productivity classes (Fig. 3a, c, d and e), but foliar P on low productivity class was lower than that on medium and high productivity classes (p < 0.001, Fig. 3b).

Fig. 2. (a) Richness, (b) evenness and (c) Shannon-Wiener index of understory plant species on low, medium and high productivity lodgepole pine (Pine) and white spruce (Spruce) sites in the Athabasca oil sands region. Lowercase letters above each bar indicate significant differences among productivity classes within each tree species (p < 0.05). Error bars are standard errors of means (n = 3).

4. Discussion Understory vegetation, as a forest ecosystem driver and an important part of total ecosystem biodiversity, contributes greatly to forest dynamics and forest ecosystem functions due, in part, to its high turnover rate (Nilsson and Wardle, 2005; Kumar et al., 2018a). This study is the first investigation of understory plant communities associated with different tree productivities in a reclaimed landscape. Understory plant communities showed different responses to tree productivity classes on both reclaimed pine and spruce sites. However, it should be noted that due to design limitations in the study, we are not able to distinguish between the effect of overstory trees and soil factors on understory vegetation, nor is it possible to distinguish between the effects of trees on understory vegetation and the effects of understory vegetation on trees. Tree species may influence the understory vegetation (Cavard et al., 2011). Although white spruce and lodgepole pine are both coniferous trees, and light levels under conifers are often low (Ross et al., 1986;

thus higher on medium (55.5%) than on low (16.7%) and high (39.2%) productivity classes (p < 0.001). On spruce sites, the covers of shrubs and forbs were higher on medium than on low and high productivity classes (p = 0.013 and 0.009 for shrubs and forbs, respectively, Fig. 1), whereas grass cover was lower on low and medium than on high productivity class (p < 0.001, Fig. 1), resulting in no difference in total cover among low, medium and high productivity classes. 3.3. Understory plant species richness, evenness and diversity on low, medium and high productivity pine and spruce sites On pine sites, mean species richness was 3.5 on medium productivity class, significantly lower than that on low and high productivity classes (p = 0.011, Fig. 2a), but there was no difference in species richness between low (5.5) and high (5.3) productivity class 5

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Table 2 Pearson correlation coefficients for relationships between understory plant community percent cover, species richness, species evenness, Shannon-Wiener index (H′) and tree growth parameters, soil properties on lodgepole pine and white spruce sites in the Athabasca oil sands region. Site type

Plant parameter

HIb

DBHIb

ABIb

LAIb

Msoilc

Tsoilc

Thickness

Bulk density

Soil ECd

Total C

Total N

DOCd

DONd

Inorganic N

Pinea

Total cover Shrub cover Forb cover Grass cover Richness Evenness H′

0.233 0.186 0.072 0.311 0.029 0.326 0.116

0.326 0.298 0.127 0.401 0.132 0.176 0.144

0.146 0.199 −0.110 0.076 −0.141 0.127 0.133

−0.241 0.012 0.117 −0.259 −0.204 0.124 0.227

0.402 0.327 0.213 0.434 0.112 0.228 0.163

0.240 0.319 0.174 0.356 0.108 0.273 0.348

0.644* 0.553 0.246 0.611 0.167 0.183 0.179

0.355 0.321 0.208 0.396 0.157 0.293 0.136

0.291 0.354 0.117 0.349 0.142 0.237 0.119

0.347 0.319 0.133 0.291 0.189 0.326 0.179

0.496 0.478 0.159 0.305 0.202 0.267 0.174

0.592 0.693 0.231 0.528 0.227 0.410 0.253

0.308 0.287 0.133 0.399 0.087 0.342 0.191

0.638 0.591 0.166 0.804 0.118 0.280 0.159

Sprucea

Total cover Shrub cover Forb cover Grass cover Richness Evenness H′

0.327 0.134 0.209 0.641 0.289 0.569 0.168

0.213 0.187 0.296 0.511 0.318 0.523 0.196

0.306 0.247 −0.156 0.569 0.322 0.568 0.244

−0.269 −0.306 −0.513 0.547 −0.532 0.462 −0.617

−0.409 −0.492 0.201 −0.482 0.229 0.262 0.128

0.221 0.170 0.381 0.322 0.210 0.238 0.344

−0.407 0.115 −0.225 0.203 0.181 0.206 −0.411

−0.233 0.147 0.441 0.097 0.433 0.126 0.378

−0.524 −0.341 −0.117 −0.416 −0.398 −0.701 −0.263

0.433 0.306 0.362 0.115 0.314 0.471 0.211

0.172 0.144 0.271 0.498 0.217 0.427 0.161

0.136 0.173 0.096 0.479 0.117 0.428 0.211

0.192 0.516 0.294 0.433 0.248 0.611 0.216

0.508 0.533 0.266 0.167 0.412 0.494 0.376

a Pine, lodgepole pine sites reconstructed using tailings sand as a substrate below a peat-mineral soil mix cover soil; Spruce, white spruce sites reconstructed using overburden as a substrate below a peat-mineral soil mix cover soil. b HI, height increment; DBHI, diameter at breast height (1.3 m above the ground) increment; ABI, aboveground biomass increment; LAI, leaf area index. c Msoil, soil moisture content; Tsoil, soil temperature. d EC, electrical conductivity; DOC, dissolved organic carbon; DON, dissolved organic nitrogen. * Values in bold font indicate significant correlation (p < 0.05).

Fig. 3. Foliar concentrations of (a) N, (b) P, (c) K, (d) Ca and (e) Mg of dandelion on low, medium and high productivity lodgepole pine (Pine) and white spruce (Spruce) sites in the Athabasca oil sands region. Lowercase letters above each bar indicate significant differences among productivity classes within each tree species (p < 0.05). Error bars are standard errors of means (n = 3). 6

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accounting for a majority of the percent cover. When tree productivity increases, competition for light may result in exclusion of other plant species, thus decreasing plant diversity and leaving the best competitor for light (Tilman and Pacala, 1993). The consistent pattern of plant cover and diversity on spruce sites suggests that competitive exclusion was not a dominant process on these sites. Previous studies showed that the dynamics of understory vegetation could be driven by the time since disturbance, resource quantity, competition intensity and microsite heterogeneity (Schwinning and Weiner, 1998; Bartels and Chen, 2010, 2013; Cavard et al., 2011; Dhar et al., 2018; Kumar et al., 2018a, 2018b). The positive relationships between shrub, grass or total cover and cover soil thickness, soil DOC or inorganic N concentration on pine sites partly support the hypothesis that understory plant community cover and diversity would be positively related to resource availability on pine and spruce sites. The low productivity pine sites had lower soil nutrient availabilities (Table 1 and S3) and foliar N and P concentrations in dandelion than medium productivity sites (Fig. 3), which reflects the limited nutrient status. However, as the productivity increased from medium to high, soil water and nutrient availabilities should have increased, but the enhanced inter- or intra-specific competition for those resources by trees might offset or exceed the beneficial effect of increased resource availability on understory vegetation growth, resulting in reduced understory cover (Schwinning and Weiner, 1998; Bartels and Chen, 2010; Reich et al., 2012; Kumar et al., 2018b). This result suggests that fertilizers or a thicker layer of PMM should be applied to improve resource availability on sites with low productivity, while tree spacing should be wider to decrease competition on sites with high productivity, if enhancing understory growth is one of the main objectives of reclamation. The negative relationships between forb cover, species richness or H′ and LAI on spruce sites suggests that understory vegetation is affected by the overstory as well, which is consistent with findings reported by other studies (McKenzie et al., 2000; Roberts and Zhu, 2002; Cavard et al., 2011; Halpern and Lutz, 2013; Kumar et al., 2018a). McKenzie et al. (2000) reported that herb cover was negatively correlated with canopy cover in mature natural forests. However, Bartels and Chen (2013) found that canopy cover had a positive influence on shrub and herb cover and herb richness in boreal mixed-wood forests, and attributed it to increased soil nutrients in the forest floor in forests with a denser canopy. The overstory can also change light availability and variability (Messier et al., 1998; Barbier et al., 2008; Kumar et al., 2018b), and regulate understory plant species distribution by eliminating some plant species with a slow growth rate and low shade tolerance ((Légaré et al., 2002; Lamb et al., 2009; Reich et al., 2012). In this study, on low productivity spruce sites with a lower LAI, shade intolerant plant species can get enough light and grow rapidly, whereas their growth may be limited on high productivity sites with a higher LAI. Moreover, the overstory may affect solar radiation and throughfall reaching the understory, thus influencing soil surface evaporation and water availability (Barbier et al., 2008; Naeth et al., 2011). However, the lack of relationships between understory vegetation variables and soil moisture content, and the lack of differences in soil moisture content among productivity classes suggest that the overstory did not influence soil water status, and water availability is not the controlling factor for understory vegetation growth in this study.

Messier et al., 1998), the plant communities growing under opencanopied pine are different from those growing under denser-canopied spruce (Messier et al., 1998). White spruce and lodgepole pine may also differ in their effects on soil chemical and physical properties and biochemical cycles through litterfall or root turnover (Aerts and Honnay, 2011), and they can differently compete for soil moisture and nutrients with the understory vegetation due to their different root architectures (Nienstaedt and Zasada, 1990; Lotan and Critchfield, 1990). Moreover, the soil properties of reclaimed sites established using TS versus OB substrates are also very different (Fung and Macyk, 2000; Duan et al., 2015). The TS substrate used on pine sites often has limited water and nutrient availability due to a coarse soil texture (Li et al., 2014; Duan et al., 2015), whereas the OB substrate used on spruce sites is normally highly compacted by heavy machinery (Fung and Macyk, 2000; Barbour et al., 2007a) and contains high concentrations of salts from the marine shale parent materials (Kessler et al., 2010; Jung et al., 2014). The lower water and nutrient availabilities of TS substrate on pine sites and higher bulk density and salinity of OB substrate on spruce sites in this study (data not shown) almost certainly confounds the influence of tree species on understory vegetation. Our finding that the total cover of understory vegetation varied among tree productivity classes on pine sites, but not on spruce sites is inconsistent with the hypothesis that understory vegetation cover would ubiquitously decrease from low to medium to high tree productivity sites. The higher total cover on medium than on low and high productivity pine sites is attributable to their higher shrub and grass covers. Although shrub and forb covers were the highest on medium productivity spruce sites, the lowest grass cover made the total cover not different among productivity classes. Naeth and Wilkinson (2004) reported that grasses could favor other vegetation growth by stabilizing exposed soil, preventing soil erosion and providing protection for seedlings from heat damage in summer and cold damage in winter. McLaren and Turkington (2010) also reported that grasses had a greater impact than forbs and legumes on light interception, soil moisture retention and nutrient availability. However, although high productivity spruce sites had the highest grass cover, their lower shrub and forb covers indicate that the facilitating effect of grasses was limited on spruce sites; grasses could compete strongly with other plant species for moisture and nutrients during early establishment and other factors may have played more important roles in understory vegetation growth. For example, shrub cover could increase litterfall production and contribute to soil C and N accumulation in degraded forests (Feng et al., 2019), or could reduce water stress by decreasing exposure to solar radiation and decrease the browsing of other understory vegetation (Castro et al., 2004). Some forbs such as sweet clover could symbiotically fix N, which may improve soil chemical and biological properties (Fung and Macyk, 2000). Together, those factors could influence understory vegetation growth and alter the cover of different vegetation layers on spruce sites in this study. The “U-shape” pattern of plant diversity on pine sites and unimodal or “hump-shape” pattern on spruce sites as tree productivity increased from low to medium to high is also inconsistent with the hypothesized decrease in plant diversity with productivity. Tilman and Pacala (1993) and Huston and DeAngelis (1994) both reported a unimodal relationship between productivity and species diversity, and attributed it to increased competitive exclusion due to decreased heterogeneity of limiting resources at high productivities. Overstory trees can accumulate large amounts of biomass, which may improve soil C and N availability due to increased litterfall (Feng et al., 2019), thereby benefiting the growth of some understory plants and affecting species diversity. Reich et al. (2012) reported that annual aboveground productivity could indirectly regulate understory species diversity by influencing light availability and heterogeneity in boreal forests. The asynchronous changes of understory vegetation cover and plant diversity on pine sites in this study indicates that the vegetation covers increased at the cost of plant diversity, with a few plant species

5. Conclusions Our findings suggest that the relationship between the growth of understory plant communities and tree productivity in the studied reclaimed forest ecosystems was site specific. The results failed to support one of our hypotheses that the cover and diversity of understory plant communities would decrease monotonically from low to medium to high tree productivity sites. Instead, the relationship between tree productivity and understory plant species diversity followed a unimodal curve on spruce sites, but a “U-shape” pattern on pine sites, 7

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indicating that other factors may play an important role together with tree productivity in affecting understory plant community diversity on reclaimed sites. The other hypothesis that the cover and diversity of understory plant communities would be positively related to resource availability was partly supported by the positive relationships between shrub, grass or total cover and cover soil thickness, soil DOC or inorganic N concentration on pine sites. The highest understory plant community growth on sites with a medium productivity, such as the highest total cover on pine sites and the highest plant diversity on spruce sites, suggests that reclamation strategies should balance the growth of both overstory trees and understory plants to achieve the objective of creating diverse and resilient plant communities in reclaimed forest ecosystems. For example, wider planted tree spacing should be used on sites with a high productivity to reduce competition, while fertilization and placement of thicker cover soils should be used on sites with a low productivity to improve soil nutrient availabilities and understory plant community development.

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