Biological integrity of mixed-grass prairie topsoils subjected to long-term stockpiling

Applied Soil Ecology xxx (xxxx) xxx–xxx

Contents lists available at ScienceDirect

Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil

Biological integrity of mixed-grass prairie topsoils subjected to long-term stockpiling ⁎

Pamela R. Blocka, Caley K. Gaschb, , Ryan F. Limba a b

Range Science Program, School of Natural Resource Sciences, North Dakota State University, Fargo, ND, United States of America Department of Soil Science, School of Natural Resource Sciences, North Dakota State University, Fargo, ND, United States of America

A R T I C LE I N FO

A B S T R A C T

Keywords: Restoration Seedbank Surface mining Soil microbial community PLFA Plant emergence

Surface mining often requires storage of topsoil in large piles for long periods of time (1–30 years). Such soil handling and storage results in physical and biogeochemical changes and may alter the soil biological integrity. Microbial activity regulates nutrient cycling and soil quality, and post-mining revegetation of most native forb species in the Northern Great Plains relies on a viable seedbank. Soil condition and biological viability influence the establishment and success of the aboveground plant community, and therefore should be considered in facilitating successful reclamation. In this study, we characterized soil biological integrity via the seed bank and microbial community structure in a topsoil stockpile (depths of 15 cm–750 cm). We measured microbial community structure using phospholipid fatty acid analysis and assessed the seed bank using the seedling emergence method under greenhouse conditions. We hypothesized with increasing depth, soil biota would decrease in abundance and perhaps exhibit a shift in community structure, and stockpiled soils would display different communities compared to an undisturbed reference site. Further, we hypothesized the soil seedbank would decrease with increasing depth and be less than the reference site. We found distinct shifts in microbial communities in terms of community structure and declines in overall abundance of organisms with increased depth using principal component analysis. Furthermore, overall microbial abundance within the top 15 cm of stockpiled soil was nearly one third less than our native undisturbed reference site, and soil at depth was increasingly depleted. Total seedling emergence from soil collected at all depths of the stockpile was lower (20 viable seeds) compared to the reference soil emergence (36 viable seeds). Our results demonstrate that stockpiling greatly affects soil microbial communities and that stockpiled topsoil is not a dependable source for forb seeds. Reclamation may require forb seeding and soil amendments to facilitate whole-system restoration.

1. Introduction Soils in the Northern Great Plains subject to surface mining and reclamation experience drastic physical disturbance, as soil is removed, handled, stored, and then re-spread. These activities leave the soil with high levels of compaction (Bohrer et al., 2017b), limited water infiltration and increased surface runoff (Gilley et al., 1977; Lang et al., 1984), and poor soil structure (Abdul-Kareem and McRae, 1984; Wick et al., 2009). In addition to these physical changes, such disturbances can impact soil nutrient pools and dynamics (Ingram et al., 2005; Anderson et al., 2008; Ganjegunte et al., 2009) and microbial community structure and abundance (Cundell, 1977; Persson and Funke, 1988; Mummey et al., 2002a; Mummey et al., 2002b; Dangi et al., 2012). These changes may then be reflected in sub-optimal

establishment and diversity of the vegetative community following reclamation. Even when reclaimed land may meet aboveground expectations for productivity (Hofmann et al., 1981), belowground ecosystem components may not recover to a similar degree or may impose limits on developing a sustainable, desired, and diverse plant community (Waaland and Allen, 1987; Ogle and Redente, 1988; Saxerud and Funke, 1991; Schladweiler et al., 2005; Bohrer et al., 2017a; Swab et al., 2017). The ultimate goal of reclamation is to reestablish a productive and healthy vegetative community that meets intended land use needs. Therefore, it is important to understand soil recovery in addition to vegetation communities to provide a more robust assessment of reclamation success, barriers to meeting goals, and overall ecosystem recovery. To promote soil conservation and facilitate reclamation success, pre-

Abbreviations: EC, electrical conductivity; F:B, fungal to bacterial ratio; PLFA, phospholipid fatty acid analysis; POXC, permanganate oxidizable carbon ⁎ Corresponding author at: NDSU Dept. 7680, PO Box 6050, Fargo, ND 58103, United States of America. E-mail address: [email protected] (C.K. Gasch). https://doi.org/10.1016/j.apsoil.2019.08.009 Received 18 April 2019; Received in revised form 20 August 2019; Accepted 28 August 2019 0929-1393/ © 2019 Elsevier B.V. All rights reserved.

Please cite this article as: Pamela R. Block, Caley K. Gasch and Ryan F. Limb, Applied Soil Ecology, https://doi.org/10.1016/j.apsoil.2019.08.009

Applied Soil Ecology xxx (xxxx) xxx–xxx

P.R. Block, et al.

the soil seed bank is also important to consider. The reestablishment of vegetation may benefit from the germination of seeds in the soil seedbank to propagate indigenous, native, species (Archibold, 1981; Schott and Hamburg, 1997). Seed viability may be reduced even after shortduration (one year) stockpiling (Iverson and Wali, 1982; Buss and Pinno, 2019). Since seed longevity influences recruitment (Stöcklin and Fischer, 1999), shorter-lived seeds may be lost in stockpiled soil, perhaps preventing their establishment upon soil re-spreading. Mines in the Northern Great Plains rely entirely on the seedbank for forb species reestablishment during reclamation. However, the viability and abundance of seeds exposed to long-term stockpiling is largely unknown. Therefore, understanding the relationship between long term storage in stockpiles and native plant persistence in the seedbank may facilitate reclamation success. We know that soil handling during surface mining impacts soil characteristics. These changes are most likely exacerbated via longterm stockpiling and may ultimately delay reclamation success. In practice, stockpiled soils that are dismantled and then re-spread are assumed to have physical, chemical, and biological characteristics equivalent to fresh topsoil, and which facilitate successful reclamation. Our study aims to address this according to the following objective: Assess soil microbial community structure and seed viability from multiple depths in a stockpile to understand effects of long-term topsoil storage on belowground biological integrity. We hypothesize that biological activity will be limited via stockpile physical and chemical conditions, which will differ with depth. We expect that the shallowest portion of the stockpile will be the most biologically viable, and that biological integrity will deteriorate with increasing stockpile depth.

and post- mining activities follow strict soil handling requirements, as regulated by the Surface Mining Control and Reclamation Act (Office of Surface Mining Reclamation and Enforcement, 1977). Top- and sub-soil are separated during the mining process to retain topsoil quality, and each type of soil is either directly re-spread on locations undergoing reclamation or stockpiled for future reclamation (Hargis and Redente, 1984; Munshower, 1994). In cases where the land is being reclaimed to a native plant community, vegetation is established through a combination of manual seeding, natural recolonization, and by viable seeds remaining in the soil (Munshower, 1994; Feagley and Rossner, 2000). When soils are re-spread immediately following excavation (referred to as direct-haul), changes to the physical, chemical and biological properties can be minimized (Koch, 2007). However, when soils are stockpiled for prolonged periods of time, soil properties are likely to change. Alterations may include changes in soil structure (Abdul-Kareem and McRae, 1984; Wick et al., 2009), nutrient exchange and air flow (Williamson and Johnson, 1990; Boyer et al., 2011), and shifts or losses in the soil microbial community (Gould and Liberta, 1981; Visser et al., 1984; Harris et al., 1989; Johnson et al., 1991). The destruction of aggregates is an immediate effect of soil disturbance, which controls porosity and influences water and air distribution throughout the soil. Microscale structure is critical to the growth and survival of diverse soil microbial communities (Mummey et al., 2006; Kuzyakov and Blagodatskaya, 2015). Destruction of soil aggregates, combined with topsoil mixing, results in an increase in carbon and nitrogen mineralization through the exposure of physically protected nutrients to microbes and oxygen (Williamson and Johnson, 1990; Ingram et al., 2005). Enhanced mineralization and soil mixing lead to net loss and dilution of nutrients in the disturbed soil, and longterm stockpiling may prevent soil properties from recovering to predisturbance levels. While soil structure is influenced by disturbance, vegetation plays a major role in improving disturbed soils over time, by providing structural stability and root-derived carbon inputs that facilitate soil recovery (Sheoran et al., 2010; Zhang et al., 2016). Due to the height and size of stockpiles, ranging from 5 to 18 m in height and 1–22 total hectares, the rooting depth of vegetation is limited to the shallow surface soil of the stockpile. Stockpile depth, combined with organic matter depletion during disturbance, may contribute to persistent low organic matter content in stockpiled soils (Abdul-Kareem and McRae, 1984; Schwenke et al., 2000; Bauman et al., 2019). In addition, compaction caused during the creation of the stockpile, combined with the lack of vegetative roots results in reduced air and water flow throughout the stockpile. Years of limited air and water exchange and reduced substrate inputs will likely hinder biological activity and may cause topsoil to become more characteristically like subsoil. With these foreseen changes in the physical and chemical environment caused by soil handling, and their potential to be exacerbated by long-term stockpiling, we expect soil disturbance and stockpiling to be associated with shifts in microbial abundance and community structure. Soil changes caused by mining and reclamation can influence postreclamation ecosystem processes, such as decomposition rates, carbon storage, and nitrogen fixation (Visser et al., 1984; Ussiri and Lal, 2005; Helingerová et al., 2010; Yuan et al., 2017), and soil microbes are integral to these processes. Microbial communities have the potential to influence and shape plant community structure (Reynolds et al., 2003), and they mediate most soil processes that affect nutrient availability, plant health, and primary production (summarized by Brussaard, 1997; van der Heijden et al., 2008). Furthermore, in the Northern Great Plains, much of the native vegetation (especially warm season grasses) are dependent on symbiotic and beneficial microorganism associations (Hetrick et al., 1988). Thus, understanding the biological integrity of stockpiled topsoil is important for long term reestablishment of a diverse native plant community. In addition to the changes expected in soil microbiological habitats, substrates, and communities as a result of stockpiling, the viability of

2. Materials and methods 2.1. Study site description Soils were collected from one topsoil stockpile at BNI Coal mine in central North Dakota, United States (47°3′13″N 101°19′45″W). This stockpile was 230 × 60 × 9.5 m, 1 ha in size, and a similar dimension to other stockpiles in this area. This study design uses pseudo-replication, where we extracted multiple cores from one stockpile. Ideally, this design would be replicated across multiple stockpiles, but that opportunity does not exist, since stockpiles with similar source soil, time since creation, and dismantling schedule do not exist. Despite this limitation, we believe the samples provide an opportunity to learn about soil properties within the studied stockpile. The BNI mine is an active lignite strip mine that has been in production for 48 years, located in Oliver County, North Dakota. The premined soil developed on siltstone or sandstone, with loamy to silty-clay loam textures, dominated by the Williams (Typic Argiustolls) and Cabba (Typic Ustorthents) soil series (Soil Survey Staff, 2019). In general, the soils in this area are deep, well-drained to moderately welldrained, with a friable loam subsoil and carbonate accumulation at depth (Weiser, 1975). Topsoil (A horizon) depths of the Williams and Cabba series vary between 7.5 and 15 cm depths. The area has a continental climate regime, with an annual mean temperature of 6.7 °C and precipitation of 406.4 mm. Minimum temperatures occur in January averaging −16.7 °C and maximum temperatures in July average 22.8 °C from 1991 to 2017 (North Dakota Agricultural Weather Network, 2019). 2.2. Field sampling methods To address soil microbial integrity of stockpiled soil, we collected soil samples in August of 2017 from a stockpile originally formed in 1992–1993. Pre-mining topsoil salvage and stockpiling aims to remove soil from the A horizon. Excavation equipment size and soil horizon depth variability may limit the precision of topsoil separation in this manner, and it is possible that some subsoil material may be mixed with 2

Applied Soil Ecology xxx (xxxx) xxx–xxx

P.R. Block, et al.

abundance.

salvaged topsoil. Following formation, the stockpile was planted with a mixture of native and non-native perennial vegetation (Thinopyrum intermedium, Medicago sativa, Nassella viridula and Panicum virgatum) for stabilization. At the time of sampling, no flowering forbs were present on the stockpile. The experimental design of this project used stratified random sampling of the single stockpile, and we defined soil “treatments” by sampling depth. Soil characteristics across sampling depths were compared to those of an undisturbed reference site. Soil samples were collected using a mechanical core extraction probe (3.5 cm diameter, Diedrich D-50, Diedrich Drill, LaPorte, IN) at ten locations randomly selected along a 100 m transect that traversed the top of the stockpile. Cores were segmented into seven depth increments (0–15 cm, 30–45 cm, 60–75 cm, 90–120 cm, 300–350 cm, 450–490 cm, 750–790 cm) at each of the ten locations (7 depths × 10 locations = 70 samples total). These sampling depths were chosen to represent the entire profile of the stockpile, which was 9.5 m tall. We also extracted soil with a hammer-driven corer (5 cm diameter, AMS, Inc., American Falls, ID) at three depths (0–15 cm, 90–120 cm, and 300–350 cm) for bulk density estimation. Samples were kept on ice while in the field and frozen (−20 °C) within 2 h of sampling. Additionally, we collected ten soil samples (0–15 cm) from an undisturbed native reference site at 10 m increments along a 100 m transect. The reference site has the same textural class, is approximately 7.2 km away and was assumed to be representative of the pre-disturbance state of the stockpiled soil. The reference areas serve as a vegetation benchmark for BNI and are not used specifically as a target for soil reclamation.

2.5. Soil chemical and physical analysis All soil samples used for soil physical and chemical analyses were air-dried and sieved to 2 mm. Soil pH and electrical conductivity (EC) were determined in a 1:1 soil:water slurry (Rhoades, 1996; Thomas, 1996) with a pH meter (Oakton Instruments, Vernon Hills, IL) and a conductivity meter (Thermo Orion Star A112, Beverly, MA). Bulk density was estimated from intact volumetric cores, oven-dried at 105 °C according to Blake and Hartge (1986). We used the pressure plate method (Richards and Fireman, 1943) to estimate gravimetric water content at field capacity (−1/3 Bar) of ground samples. Total carbon and inorganic carbon were analyzed using a high temperature catalytic combustion analyzer (Skalar Inc., Buford, GA). Soil organic carbon was calculated as the difference between the two pools. Permanganate oxidizable carbon (POXC) represents a labile, active fraction of non-living organic carbon and was assessed following Weil et al. (2003). We measured particle size analysis on a subset of samples (n = 3 per depth) using the hydrometer method (Gee and Bauder, 1986) in order to determine soil texture. 2.6. Statistical analysis We were interested in examining if soil properties changed with stockpile depth, so each depth increment was considered as an independent set of observations in the analysis (n = 10 observations per depth). Descriptive statistics were calculated for soil properties and seed viability within each depth. Differences in means across depths were determined using an analysis of variance (ANOVA) with Tukey's Honest Significant Difference post-hoc test. All data were assessed for normality and homoscedasticity prior to analysis, to the extent that they can be, given a small sample size. Bray-Curtis dissimilarity indices were calculated between the microbial community at each depth compared to the reference in absolute terms, representing differences in abundance and composition. To understand how the microbial communities and soil properties varied across depth, and in relation to one another, we conducted two multivariate analyses. To identify differences in microbial community composition across depth, we performed a principal component analysis on PLFA data alone. To explore how general soil properties varied and co-varied across depths, we used a linear discriminant analysis with the following input properties: pH, EC, field capacity, inorganic carbon, POXC, soil organic carbon, total nitrogen, total microbial abundance, and F:B. All data analysis was completed in R (R Core Team, 2019) using the ‘fields’ (Nychka et al., 2015), ‘ggord’ (Beck, 2017), ‘ggplot2’ (Wickham, 2009), ‘MASS’ (Venables and Ripley, 2002), ‘multcompView’ (Graves et al., 2015), ‘pastecs’ (Grosjean et al., 2018), ‘plyr’ (Wickham, 2011), ‘RColorBrewer’ (Neuwirth, 2014), ‘scales’ (Wickham, 2018), ‘vegan’ (Oksanen et al., 2019), and ‘zoo’ (Zeileis and Grothendieck, 2005) packages and their dependencies for data manipulation, statistical analysis, and visualizations.

2.3. Seedbank sampling and screening To survey the soil seed bank within the stockpile, we collected soil samples at five locations from the same seven depths during dismantle of the stockpile in September of 2017. We also collected soil samples from five locations along the transect established in the reference site (from 0 to 15 cm depth). Each sample was extracted, placed in a sterile plastic bag, and transported to the greenhouse in a tub under dark conditions. Fresh soil samples were weighed to 100 g and spread over 100 g of vermiculite to 1 cm thickness in germination trays (25 cm × 20 cm in surface area and 10 cm depth). Greenhouse conditions were set to 15 h days (26 °C) and 9 h nights (18 °C) and were watered twice daily until seedling emergence. Following emergence, seedlings were transplanted to individual pots (5 cm × 5 cm) containing potting mix and watered once per day. Individual plants were grown until species identification was possible. We calculated the sum of total germination by forb species or grass across all five replicate samples within each sampling depth and the reference. 2.4. Soil biological analysis Phospholipid fatty acid (PLFA) analysis was used to assess microbial group abundance of the stockpiled soil. This method provides abundance estimates of soil microbial groups at a broad taxonomic level (bacteria, saprophytic fungi, arbuscular mycorrhizal fungi, actinomycetes, and eukaryotic microbes), and it is a robust method for detecting microbial community differences across treatments (Ramsey et al., 2006). Frozen soil samples were lyophilized and ground to pass through a 2 mm sieve, then analyzed for PLFA identity and abundance by Microbial Identification (MIDI) Labs, Inc. (Newark, DE). The MIDI lab follows lipid extraction procedures described by Buyer and Sasser (2012), quantitative analysis with gas chromatography (HP6890, Hewlett Packard, Palo Alto, CA), and peak identification using Sherlock software version 6.2 and the PLFAD2 version 2.0 peak naming table. The abundance of each microbial group was treated in terms of absolute abundance (nmol fatty acid/g soil) as well as in relative terms (each group divided by the total abundance). The fungal to bacterial ratio (F:B) was also calculated as fungal abundance divided by bacterial

3. Results 3.1. Seed integrity Seedling diversity and viability in the stockpile was generally very low. Total seedling emergence from soil collected across all depths of the stockpile was lower (20 viable seeds) compared to the reference soil emergence (36 viable seeds) (Fig. 1). The shallowest depth (15 cm) had the highest number of seedlings emerge, with eight total seedlings. As depth increased, seedling emergence decreased steadily—with the second depth (45 cm) having half the seedling emergence of the top depth (15 cm). Three forb species (Hairy rock cress – Arabis pycnocarpa, 3

Applied Soil Ecology xxx (xxxx) xxx–xxx

P.R. Block, et al.

the shallowest depth (15 cm) and 6 nmol/g soil in the deepest depth (750 cm), both significantly lower than 134 nmol/g observed in the reference soil (Table 1). Total microbial abundance was significantly (p < 0.05) lower in all depths compared to the reference soil. Dissimilarity indices of absolute abundance indicated that community structure became less similar to the reference as depth increased (Fig. 2A). Moreover, we observed that the mean relative abundances of actinomycetes and Gram positive bacteria were generally higher with depth (300–350 and 450–490 cm for Gram positive and depths > 45 cm for actinomycetes), compared to the reference (Fig. 2B). Other groups tended to decrease as depth increased, with the exception of saprophytic fungi (Fig. 2B). The F:B can indicate community shifts, and the mean F:B generally decreased with increasing depth to the 300–350 cm depth (Table 1). The F:B was significantly lower in soils deeper than 75 cm depth, compared to the reference site, but displayed a spike to be equal to reference soils in the deepest depth. Similarly, we found that relative abundance of saprophytic fungi was highest at the deepest depth of the stockpile (Fig. 2B, Table 1). Principal component analysis of PLFAs revealed that the microbial community composition differed across stockpile depths (Fig. 3). The first two components explained 78% of the variance, with the first principal component accounting for 59.4% and the second principal component representing 18.6% of the variance across all observations. Observations (n = 10 per depth) tended to separate based on microbial group and depth. The shallow portion of the stockpile was most similar to the reference soil, with arbuscular mycorrhizal fungi, bacteria, and eukaryotic groups underlying those similarities along the first component. Abundance of Gram positive bacteria and actinomycetes were associated with the deeper depths of the stockpile, while fungi were associated with the second component and the deepest sampled depth.

Fig. 1. Heatmap representing emergence of vegetation from the seedbank in soils collected from multiple stockpile depths and an undisturbed reference (Ref) location (0–15 cm depth). Values represent total emergence of each species at each depth. FP – Field pennycress (Thlaspi arvense), G—grass (multiple species), HRC – Hairy rock cress (Arabis pycnocarpa), MEC – Mouse-ear chickweed (Cerastium vulgatum), WR—Western ragweed (Ambrosia psilostachya), YWS – Yellow wood sorrel (Oxalis stricta).

Mouse-ear chickweed – Cerastium vulgatum, and Western ragweed – Ambrosia psilostachya) emerged from stockpiled soils, only one of which was also present in the reference soil (Western ragweed – Ambrosia psilostachya). Grass species dominated the emergent vegetation in the reference soil, accounting for 50% of total emerged species.

3.2. Microbial community 3.3. Auxiliary soil properties Similar to seedling emergence, as stockpile depth increased, total microbial abundance significantly decreased (Fig. 2A, Table 1). The mean total microbial abundance concentration was 47 nmol/g soil in

Soil physical properties were only slightly variable throughout the stockpile. Particle size analysis indicated that soil texture was

Fig. 2. Microbial group abundances from a stockpile. (A) Concentration (nmol g-1 soil) of microbial groups (phospholipid fatty acid analysis) in soil collected from multiple depths of a stockpile (n = 10 soil samples per depth). Values are dissimilarity indices (Bray-Curtis) as compared to the reference site, based on the mean values of each group within a depth, showing that as depth increases, the microbial community becomes increasingly dissimilar to the reference community. (B) Relative abundance of microbial groups along with a nearby reference soil, calculated as the percent of each group in relation to the total microbial abundance. AMF – Arbuscular mycorrhizal fungi. 4

Applied Soil Ecology xxx (xxxx) xxx–xxx 0.17ab (0.01)

0.17a (0.07)

0.05d (0.02)

0.04d (0.02)

0.08 cd (0.02)

0.11bc (0.02)

0.14ab (0.03) 16.9b (4.6)

11.93c (2.08)

12.59bc (3.82)

9.05c (1.54)

7.88c (1.42)

2.21d (1.27)

48.53a (7.83)

2.52b (0.67)

1.38c (0.58)

0.95 cd (0.38)

0.35d (0.2)

0.35d (0.2)

0.5d (0.3)

9.69a (0.99)

8.67b (2.27) 7.67bc (2.87) 7.77bc (0.91) 7.61bcd (1.63) 5.17 cd (1.41) 5.05d (1.31) 1.54e (0.82) 19.85a (3.66) 17.04b (4.45) 2.25b (0.72)

47.05a (4.4) 5.53a (0.41) 36.08b (1.45) 7.28ab (0.71)

40.17ab (6.48) 9.19a (3.19)

44.28a (1.61) 2.09ce (1.5)

44.45a (5.11) 1.68de (0.76)

40.27ab (1.63) 3.04 cd (1.04)

38.23b (0.92) 4.35bc (1.36)

37.77b (4.87) 5.76b (1.47)

35.24a (1.36)

22.44d (4.64)

24.22 cd (2.26)

27.32bc (2.74)

29.49b (3.07)

28.67b (0.99)

Ref

750–790

450–490

300–350

90–120

60–75

30–45

Fig. 3. Biplot illustrating the principle component analysis for microbial communities across stockpile depth, with the proportion of variance explained by PC1 (59.4%) and PC2 (18.6%) of microbial groups. Axes on the bottom and left are associated with the separation of observations along PC1 (bottom) and PC2 (left), while axes on the top and right are associated with the structure loadings on the microbial variables, as depicted by arrows. The principal component analysis was created using relative abundance of microbial groupings in order to explore multivariate relationships between groups and depth in relative terms. Data shows that microbial composition varied across depth and shallow stockpiled soil is the most similar to the reference soil. Eukary – Eukaryotes, AMF – Arbuscular mycorrhizal fungi, G- – Gram negative bacteria, G+ – Gram positive bacteria, Actino – Actinomycetes. †Arbuscular Mycorrhizal Fungi. § Values with the same lower case letters within a column are not significantly different at p < 0.05.

1.21e (0.66) 0.05e (0.08)

5.5e (2.93) 134.01a (16.9)

4.31de (0.83) 0.23de (0.06) 17.82d (3.26)

5.59 cd (1.2) 0.27de (0.1) 20.42 cd (3.31)

9.5c (4.33) 0.69 cd (0.47) 31.47c (10.6)

8.94c (1.55) 0.81c (0.13) 31.15c (5.08)

15.3b (4.37) 1.7b (0.51) 44.81b (11.68)

16.23b (4.49) 1.82b (0.5) 46.94b (11.74)

18.48b (0.82) 17.15b (4.39) 25.16a (1.63) 24.83a (2.53) 25.26a (5.69) 28.13a (2.94) 27.59a (6.92) 14.73b (1.06) 36.2b (1.44) 0–15

cm

§

3.87a (0.48) 3.78a (0.54) 2.63b (0.22) 2.04bc (0.64) 1.3 cd (0.42) 1.28 cd (0.27) 0.62d (1.02) 4.16a (0.36)

Gram-

34.35a (1.5) 33.94a (1.73)

1.97ab (0.9) 1.6bc (0.34) 0.97 cd (0.7) 0.34de (0.48) 0e (0) 0e (0) 0e (0) 2.53a (0.58)

5.13bc (2.65)

%

Gram+ Eukaryotes

Fungi

0.93b (0.43) 0.73bc (0.27) 0.32c (0.26) 0.14c (0.25) 0c (0) 0c (0) 0c (0) 3.36a (0.8)

soil nmol FA g

Fungi

Gram+ −1

Eukaryotes GramAMF† Total abundance AMF†

Actinomycetes

Absolute abundance Relative abundance Depth

Table 1 Means with standard deviation in parenthesis of relative (%) and absolute (nmol g−1 soil) abundances of microbial groups in soils collected from multiple depths in a stockpile.

Actinomycetes

F:B

0.13a (0.05)

P.R. Block, et al.

consistently silty clay loam (Table 2). Bulk density was consistent throughout the stockpile (averages ranged from 1.66 to 1.71 g/cm3, Table 2); however, these values were significantly higher (p < 0.05) compared to the reference soil mean density (1.09 g/cm3). Field capacity of disturbed and ground soil samples was relatively uniform throughout the stockpile, however, estimates were lower than the reference value (Table 2). In general, soil chemical properties were different throughout the stockpile (Fig. 4). Soil pH and EC were variable at depths deeper than 75 cm. Total nitrogen was not significantly different throughout the stockpile, however it was significantly lower than the reference soil. Active carbon and soil organic carbon were low throughout the stockpile, compared to the reference site, and lowest in the deepest depth. Inorganic carbon was significantly different (p < 0.05) only in the deepest depth. The combined linear discriminant analysis explained 89% of the variability in multivariate properties across depths with 73 and 16% of the variability explained via LD1 and LD2 functions respectively. LD1 accounts for the most variance between stockpiled soils and the reference soil; we found that soil properties at all depths were distinctly different from the reference (Fig. 5). Active carbon (POXC), soil organic carbon, total nitrogen, and total microbial abundance had the strongest positive correlations with the LD1 coefficient, while electrical conductivity had the strongest negative correlation with LD1 (Table 3). Soil properties in shallower depths (0–15 cm, 30–45 cm, and 60–75 cm) were grouped together and were distinctly separated from deeper depths (90–120 cm, 300–350 cm, and 450–490 cm), with electrical conductivity, soil organic carbon, and the F:B underlying that separation (and correlated with LD2) (Fig. 5, Table 3). We also see in Fig. 5 that soil properties in the deepest depth (750–790 cm) overlapped all but the shallowest depths. 5

Applied Soil Ecology xxx (xxxx) xxx–xxx

P.R. Block, et al.

Table 2 Means with standard deviation in parenthesis of particle size analysis used to determine soil texture, averaged across subsamples (n = 3) for each depth, bulk density (n = 10 for select depths), and water content at field capacity (n = 10). Table shows that texture and bulk density remain consistent throughout the stockpile. Depth

Sand

Silt

Clay

cm

%

%

%

0–15 30–45 60–75 90–120 300–350 450–490 750–790 Reference

20 (1)a§ 18 (2)a 19 (1)a 18 (2)a 19 (1)a 22 (3)a 22 (1)a 19 (2)a

53 48 53 47 48 53 49 51

§

(0)a (1)a (8)a (1)a (4)a (2)a (7)a (1)a

27 34 28 35 33 25 29 30

(1)a (3)a (8)a (2)a (3)a (4)a (5)a (2)a

Texture

Silty Silty Silty Silty Silty Silty Silty Silty

clay clay clay clay clay clay clay clay

loam loam loam loam loam loam loam loam

Bulk density

Water content at field capacity

g cm−3

g H2O g−1 soil

1.68 (0.12)a NA NA 1.66 (0.10)a 1.71 (0.19)a NA NA 1.09 (0.04)b

0.18 (0.02)d 0.21 (0.03)cd 0.26 (0.03)b 0.22 (0.03)bc 0.22 (0.02)cd 0.21 (0.02)cd 0.23 (0.05)bc 0.31 (0.03)a

Values with the same lower case letters within a column are not significantly different at p < 0.05.

Fig. 4. Box-and-whisker plots of soil properties across stockpile depths. Chemical properties were generally different throughout the stockpile, with carbon content significantly reduced throughout all stockpile depths. [footnote] § Depths with the same lower case letters are not significantly different at p < 0.05. 6

Applied Soil Ecology xxx (xxxx) xxx–xxx

P.R. Block, et al.

topsoil. We observed low seedling emergence from soil samples in general, but especially from stockpiled soils (Fig. 1). The low seedling numbers observed in this study limit our ability to make conclusions about seed viability and seedling communities, but we can speculate that the resident seedbank of stockpiled soils will not likely facilitate revegetation after re-spread. Not only was seedling emergence in the entire stockpile low, seedling emergence did not exceed four seedlings total at 45 cm depths or deeper. Time and duration of stockpiling likely reduced seed viability, along with high levels of compaction and limited water availability (Baskin and Baskin, 2001). Mining companies operate under the working assumption that stockpiling does not affect the seedbank, and therefore do not seed forb species during reclamation. Understanding seedbank characteristics, prolificity, and viability in light of the severity of disturbance is essential for reclamation planning (Prach and Hobbs, 2008). Revegetation success also depends on re-colonization of the reclaimed sites from seed immigration (Iverson and Wali, 1982), and re-applied topsoil thickness and seed burial depth (Zhang et al., 2001). Our observations imply that stockpiled topsoil may not be a dependable source for forb seeds, and management should reflect this finding by seeding for forbs at an appropriate time after reclamation. In this study, we found that even the highest microbial abundance (found in the shallowest portions of the stockpile) was less than a third of the reference site (Fig. 2A, Table 1). Decreased biological activity in stockpiled soils will likely have a lasting impact on land reclaimed with stockpiled topsoil. Total microbial abundance and abundance of each microbial group in the stockpile (as indicated by PLFA), were low compared to a reference topsoil, and exhibited a drastic decline with increasing depth in the stockpile. This observation was in-line with our hypothesis, and we also anticipated community shifts across the broad taxonomic groups that the PLFA method measures. Gram negative bacteria decreased in relative abundance with depth throughout the stockpile, while Gram positive bacteria and actinomycetes, were relatively less impacted by depth (Fig. 2B, Table 1). Gram negative bacteria are more sensitive to water stress (drought) compared to Gram positive bacteria (summarized by Manzoni et al., 2012). The lesser impact on the Gram positive bacteria may be due to both being more tolerant of prolonged water stress (Hueso et al., 2012), along with the capability of spore formation, allowing them to be able to withstand the harsher conditions of stockpile depth over long periods of time. We also found decreased abundance of eukaryotes, with a complete lack of eukaryotes past 120 cm. This is likely due to complete lack of sunlight access (algae) and very limited water availability (protozoa). Though water content at field capacity was not drastically different throughout the profile (Table 2), this measurement does not reflect water holding capacity of structurally intact soil. We observed higher bulk density throughout the profile, which implies lower porosity and lower water infiltration and retention throughout the stockpile. Water availability is likely not the only cause of declining abundance in some of the microbial groups, and certainly the reduced organic matter, carbon, and nitrogen substrates in the stockpile (Fig. 4) may further limit microbial abundance. We did not measure oxygen concentration or exchange within the stockpile soils but given the higher bulk density of the pile (Table 2), we presume that oxygen availability may also decline with depth and negatively impact microbial abundance. We found the F:B to be similar to the reference soil in the shallow stockpile depths (0–15 and 30–45 cm), then it steadily decreased beyond 45 cm, eventually increasing in the deepest depth (Table 1). The F:B is an indicator of the major decomposer groups, and has been linked to soil carbon cycling and storage potential (Malik et al., 2016). Nutrient availability has been shown to be one of the biggest drivers of F:B (Bardgett and McAlister, 1999). We found that total nitrogen and carbon throughout the stockpile was minimal compared to the reference soil, but these pools did not display the same trend across depth as the fungal abundance or F:B. While we expected the distribution of

Fig. 5. Linear discriminant plot for edaphic properties (plus total microbial abundance and F:B ratio), including the first two discriminant functions (LD1 and LD2), which collectively explain 89% of the variability across observations. See Table 3 for how variables align with each discriminant function. Ellipses represent confidence intervals around the mean of each group (alpha = 0.05). Observations are grouped according to sample depth, or reference.

Table 3 Correlations between soil properties and linear discriminant coefficients (structure loadings), to explain drivers in group separation. Each sample, across all depths, was treated as an input observation into the model, so structure loadings reflect all depths and the reference samples. Percentages indicate the proportion of variability explained by each discriminant function. Correlations greater than ± 0.50 are bold. Soil property pH Electrical conductivity Field capacity Inorganic carbon POXC† Soil organic carbon Total nitrogen Total microbial abundance F:B

LD1–73% ⁎

−0.28 −0.56⁎⁎⁎ 0.44⁎⁎⁎ −0.24⁎ 0.71⁎⁎⁎ 0.79⁎⁎⁎ 0.82⁎⁎⁎ 0.98⁎⁎⁎ 0.41⁎⁎⁎

LD2–16% −0.56⁎⁎⁎ 0.73⁎⁎⁎ 0.07 −0.23 0.33⁎⁎ 0.53⁎⁎⁎ 0.07 0.12 −0.67⁎⁎⁎

†Permanganate oxidizable carbon. ⁎ Significant at the 0.05 probability level. ⁎⁎ Significant at the 0.01 probability level. ⁎⁎⁎ Significant at the 0.001 probability level.

4. Discussion Surface mining companies are mandated by law to keep topsoil separate from subsoil. When salvaged topsoil cannot be directly applied to an area undergoing reclamation, the soil is stored in stockpiles. The intention of stockpiling is to retain viable topsoil for use when mined areas are ready to be reclaimed. The objective of this study was to determine the effects of stockpiling on the soil microbial community, the soil seed bank, and auxiliary soil properties in order to assess whether stockpiling topsoil for long periods of time causes changes in important soil properties. We found that soil physical, chemical, and biological properties were not uniform within the stockpile, and that they were distinctly different from an undisturbed reference soil. These observations support the idea that soil subject to long-term stockpiling should not be considered to have the same characteristics as fresh 7

Applied Soil Ecology xxx (xxxx) xxx–xxx

P.R. Block, et al.

of the decreased biological activity, chemical variability, and physical destruction caused by stockpiling. Future research can focus on quantifying the recovery time of the soil microbial community and native plant re-establishment on reclaimed areas using stockpiled soil and explore ways to facilitate their successful reclamation.

organic carbon to be the main driver of decreased fungal presence (Bauman et al., 2019), perhaps the history of disturbance, high structural density of the stockpile, and patterns of pH (Fig. 4, Table 2) were more important in maintaining low fungal abundance. Bacteria may be more prevalent at depth, since they are less affected by drastic disturbance and have diverse metabolic strategies and niche requirements. The uptick in F:B at the deepest stockpile depth may be due to hyphae growing upwards into the stockpile from below, assuming that hyphae under the stockpile was never physically disturbed. We found that arbuscular mycorrhizal fungi were an important group for linking shallow stockpile soil to the reference soil in the principle component analysis (Fig. 3). Arbuscular mycorrhizal fungi are an important symbiont for native prairies (Hetrick et al., 1988; Hetrick et al., 1994; Smith et al., 1998; Eom et al., 2000). This association has been well-studied in disturbed and reclaimed soils (Allen and Allen, 1980; Johnson and McGraw, 1988; Stahl et al., 1988; Miller and Jastrow, 1992; Noyd et al., 1995; Frost et al., 2001). The fungi's filamentous growth structure is sensitive to physical damage and cannot survive long periods of time without a root host. However, recovery of a diverse plant community during reclamation might require the symbiosis. Thus, it is notable that we observed depletion of this group in the stockpile, and future research should examine impacts of this observation on revegetation success. Decreased microbial abundance is likely due to a combination of inhospitable physical and chemical conditions within the stockpile (Abdul-Kareem and McRae, 1984; Anderson et al., 2008), and this idea was supported by our observations. We found that bulk density and water content at field capacity did not drastically differ with stockpile depth but were different from the reference soils (Table 2). This could be due to repeated traffic with heavy machinery during stockpile creation, and a lack of root or water penetration to allow for any break up of compaction. However, despite the uniform bulk density throughout the stockpile, bulk density was significantly higher throughout the stockpile compared to the reference soil. Highly compacted soil in the stockpile will have limited nutrient and gas exchange due to decreased porosity and may be a cause of decreased microbial activity (Breland and Hansen, 1996). With regard to the chemical properties throughout the stockpile (Fig. 4), pH and EC were variable and did not display a predictable trend with depth or in relation to the reference soil. Conversely, organic carbon and nitrogen pools were distinctly lower than the reference levels. This observation agrees with the idea that organic matter and nutrient inputs into the stockpile are likely reduced upon disturbance (Ingram et al., 2005; Anderson et al., 2008; Ganjegunte et al., 2009; Wick et al., 2009; Yuan et al., 2017) and are maintained at a low level for the duration of stockpiling. It would be interesting to know how long these depletions, and all affected soil properties persist after the stockpile is dismantled and re-spread.

Acknowledgements This work was supported by the North Dakota Industrial Commission Lignite Energy Counsel. The authors wish to acknowledge BNI for providing the sites to for this research, along with all their friendly staff. For technical and conceptual assistance, we also thank Joel Bell, Rebecca Hebron, and Aaron Daigh. References Abdul-Kareem, A.W., McRae, S.G., 1984. The effects on topsoil of long-term storage in stockpiles. Plant Soil 76, 357–363. https://doi.org/10.1007/BF02205593. Allen, E.B., Allen, M.F., 1980. Natural re-establishment of vesicular-arbuscular mycorrhizae following stripmine reclamation in Wyoming. J. Appl. Ecol. 17, 139. https:// doi.org/10.2307/2402969. Anderson, J.D., Ingram, L.J., Stahl, P.D., 2008. Influence of reclamation management practices on microbial biomass carbon and soil organic carbon accumulation in semiarid mined lands of Wyoming. Appl. Soil Ecol. 40, 387–397. https://doi.org/10. 1016/j.apsoil.2008.06.008. Archibold, O.W., 1981. Buried viable propagules in native prairie and adjacent agricultural sites in central Saskatchewan. Can. J. Bot. 59, 701–706. https://doi.org/10. 1139/b81-099. Bardgett, R.D., McAlister, E., 1999. The measurement of soil fungal:bacterial biomass ratios as an indicator of ecosystem self-regulation in temperate meadow grasslands. Biol. Fertil. Soils 29, 282–290. https://doi.org/10.1007/s003740050554. Baskin, C.C., Baskin, J.M., 2001. Seeds: Ecology, Biogeography and Evolution of Dormancy and Germination. Academic Press, San Diego, CA. https://doi.org/10. 1023/A:1011465920842. Bauman, M.J., Hiremath, S., Santas, A., 2019. Abiotic and biotic factors in coal mine soils influence ectomycorrhizal composition and symbiosis. J. Am. Soc. Min. & Rec. 8, 1–22. doi.org/10.21000/JASMR19010023. Beck, M.B., 2017. ggord: ordination plots with ggplot2. R package version 1.0.0. https:// zenodo.org/badge/latestdoi/35334615. Blake, G.R., Hartge, K.H., 1986. Bulk density. In: Klute, A. (Ed.), Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods, Agronomy Monograph. American Society of Agronomy, Soil Science Society of America, Madison, WI, pp. 363–375. https://doi.org/10.2136/sssabookser5.1.2ed.c13. Bohrer, S.L., Limb, R.F., Daigh, A.L., Volk, J.M., Wick, A.F., 2017a. Fine and coarse-scale patterns of vegetation diversity on reclaimed surface mine-land over a 40-year chronosequence. Environ. Manag. 59, 431–439. https://doi.org/10.1007/s00267016-0795-y. Bohrer, S.L., Limb, R.F., Daigh, A.L.M., Volk, J.M., 2017b. Belowground attributes on reclaimed surface mine lands over a 40-year chronosequence. Land Degrad. Dev. 28, 2290–2297. https://doi.org/10.1002/ldr.2758. Boyer, S., Wratten, S., Pizey, M., Weber, P., 2011. Impact of soil stockpiling and mining rehabilitation on earthworm communities. Pedobiologia 54, S99–S102. https://doi. org/10.1016/j.pedobi.2011.09.006. Breland, T.A., Hansen, S., 1996. Nitrogen mineralization and microbial biomass as affected by soil compaction. Soil Biol. Biochem. 28, 655–663. https://doi.org/10.1016/ 0038-0717(95)00154-9. Brussaard, L., 1997. Biodiversity and ecosystem functioning in soil. Ambio 26, 563–570. http://www.jstor.org/stable/4314670. Buss, J., Pinno, D.B., 2019. Soil stockpile seed viability declines with depth and is impacted by surface vegetation. J. Am. Soc. Min. & Rec. 8, 23–44. https://doi.org/10. 21000/JASMR19010023. Buyer, J.S., Sasser, M., 2012. High throughput phospholipid fatty acid analysis of soils. Appl. Soil Ecol. 61, 127–130. https://doi.org/10.1016/j.apsoil.2012.06.005. Cundell, A.M., 1977. The role of microorganisms in the revegetation of strip-mined land in the western United States. J. Range Manag. 30, 299–305. https://doi.org/10. 2307/3897311. Dangi, S.R., Stahl, P.D., Wick, A.F., Ingram, L.J., Buyer, J.S., 2012. Soil microbial community recovery in reclaimed soils on a surface coal mine site. Soil Sci. Soc. Am. J. 76, 915–924. https://doi.org/10.2136/sssaj2011.0288. Eom, A.-H., Hartnett, D.C., Wilson, G.W.T., 2000. Host plant species effects on arbuscular mycorrhizal fungal communities in tallgrass prairie. Oecologia 122, 435–444. https://doi.org/10.1007/s004420050050. Feagley, S.E., Rossner, L.R., 2000. Reclamation of lignite mined lands. In: Barnhisel, R.I., Darmondy, R.G., Daniels, W.L. (Eds.), Reclamation of Drastically Disturbed Lands, Agronomy Monograph. American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, Madison, WI, pp. 415–432. https://doi. org/10.2134/agronmonogr41.c11. Frost, S.M., Stahl, P.D., Williams, S.E., 2001. Long-term reestablishment of arbuscular mycorrhizal fungi in a drastically disturbed semiarid surface mine soil. Arid Land Res. Manag. 15, 3–12. https://doi.org/10.1080/15324980119429. Ganjegunte, G.K., Wick, A.F., Stahl, P.D., Vance, G.F., 2009. Accumulation and

5. Conclusions Post-mining reclamation strategies should aim to minimize soil disturbance, stabilize the site, establish self-sustaining native vegetation stands, and maximize soil recovery. Mines currently attempt to limit stockpiling, but long-term soil storage is still necessary. We can conclude from this study that stockpiling negatively affects soil microbial abundance and causes distinct shifts in microbial community composition. In addition, the vegetative seed bank is negatively affected by stockpiling. If the purpose of stockpiling is to retain viable topsoil in order to have successful reclamation when this soil is re-spread, this study demonstrates that stockpiled topsoil more closely resembles subsoil and may not support a successful and fully restored ecosystem. We recommend only mandatory use of stockpiling, and to limit the height of these piles in order to promote maximum root-to-soil contact. Additionally, practitioners should consider adding supplemental organic matter to stockpiled soils during re-spread, to facilitate recovery 8

Applied Soil Ecology xxx (xxxx) xxx–xxx

P.R. Block, et al.

and indigenous arbuscular mycorrhizal fungi: implications for reclamation of taconite iron ore tailing. New Phytol. 129, 651–660. https://doi.org/10.1111/j.14698137.1995.tb03034.x. Nychka, D., Furrer, R., Sain, S., 2015. Fields: tools for spatial data. R package version 8.21. https://CRAN.R-project.org/package=fields. Office of Surface Mining Reclamation and Enforcement, 1977. Surface mining control and reclamation act (SMCRA). https://www.osmre.gov/. Ogle, P.R., Redente, E.F., 1988. Plant succession on surface mined lands in the west. Rangelands 10, 37–42. Oksanen, J., Blanchet, F.G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P.R., O'Hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.M., Szoecs, E., Wagner, H., 2019. Vegan: community ecology package. R package version 2.5-4. https:// CRAN.R-project.org/package=vegan. Persson, T.J., Funke, B.R., 1988. Microbiology of stored topsoil at North Dakota stripmining sites. Arid Soil Res. Rehab. 2, 235–250. https://doi.org/10.1080/ 15324988809381178. Prach, K., Hobbs, R.J., 2008. Spontaneous succession versus technical reclamation in the restoration of disturbed sites. Restor. Ecol. 363–366. https://doi.org/10.1111/j. [email protected]/(ISSN)1526-100X.2525thAnniversaryVI. R Core Team, 2019. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/. Ramsey, P.W., Rillig, M.C., Feris, K.P., Holben, W.E., Gannon, J.E., 2006. Choice of methods for soil microbial community analysis: PLFA maximizes power compared to CLPP and PCR-based approaches. Pedobiologia 50, 275–280. https://doi.org/10. 1016/j.pedobi.2006.03.003. Reynolds, H.L., Packer, A., Bever, J.D., Clay, K., 2003. Grassroots ecology: plant–microbe–soil interactions as drivers of plant community structure and dynamics. Ecol 84, 2281–2291. https://doi.org/10.1890/02-0298. Rhoades, J.D., 1996. Salinity: electrical conductivity and total dissolved solids. In: Sparks, D.L., Page, A.L., Helmke, P.A., Loeppert, R.H. (Eds.), Methods of Soil Analysis, Part 3. Chemical Methods, Agronomy Monograph. American Society of Agronomy, Soil Science Society of America, Madison, WI, pp. 417–435. https://doi.org/10.2136/ sssabookser5.3.c14. Richards, L.A., Fireman, M., 1943. Pressure-plate apparatus for measuring moisture sorption and transmission by soils. Soil Sci. 56, 395–404. Saxerud, M.H., Funke, B.R., 1991. Effects on plant growth of inoculation of stored stripmining topsoil in North Dakota with mycorrhizal fungi contained in native soils. Plant Soil 131, 135–141. https://doi.org/10.1007/BF00010428. Schladweiler, B.K., Vance, G.F., Legg, D.E., Munn, L.C., Haroian, R., 2005. Topsoil depth effects on reclaimed coal mine and native area vegetation in northeastern Wyoming. Rangeland Ecol. Manag. 58, 167–176. https://doi.org/10.2111/1551-5028(2005) 58<167:TDEORC>2.0.CO;2. Schott, G.W., Hamburg, S.P., 1997. The seed rain and seed bank of an adjacent native tallgrass prairie and old field. Can. J. Bot. 75, 1–7. https://doi.org/10.1139/b97-001. Schwenke, G.D., Mulligan, D.R., Bell, L.C., 2000. Soil stripping and replacement for the rehabilitation of bauxite-mined land at Weipa. I. Initial changes to soil organic matter and related parameters. Soil Res 38, 345–370. https://doi.org/10.1071/sr99043. Sheoran, V., Sheoran, A., Poonia, P., 2010. Soil reclamation of abandoned mine land by revegetation: a review. Int. J. Soil Sediment Water 3, 13. Smith, M.R., Charvat, I., Jacobson, R.L., 1998. Arbuscular mycorrhizae promote establishment of prairie species in a tallgrass prairie restoration. Can. J. Bot. 76, 1947–1954. https://doi.org/10.1139/b98-205. Soil Survey Staff, 2019. Natural Resource Conservation Service. US Department of Agriculture, Web Soil Survey. https://websoilsurvey.sc.egov.usda.gov/App/ HomePage.htm. Stahl, P.D., Williams, S.E., Christensen, M., 1988. Efficacy of native vesicular-arbuscular mycorrhizal fungi after severe soil disturbance. New Phytol. 110, 347–354. https:// doi.org/10.1111/j.1469-8137.1988.tb00271.x. Stöcklin, J., Fischer, M., 1999. Plants with longer-lived seeds have lower local extinction rates in grassland remnants 1950–1985. Oecologia 120, 539–543. https://doi.org/10. 1007/s004420050888. Swab, R.M., Lorenz, N., Burd, S., Dick, R., 2017. Native vegetation in reclamation: improving habitat and ecosystem function through using prairie species in mine land reclamation. Ecol. Eng. 108, 525–536. https://doi.org/10.1016/j.ecoleng.2017.05. 012. Thomas, G.W., 1996. Soil pH and soil acidity. In: Sparks, D.L., Page, A.L., Helmke, P.A., Loeppert, R.H. (Eds.), Methods of Soil Analysis, Part 3. Chemical Methods, Agronomy Monograph. American Society of Agronomy, Soil Science Society of America, Madison, WI, pp. 475–490. https://doi.org/10.2136/sssabookser5.3.c16. Ussiri, D.A.N., Lal, R., 2005. Carbon sequestration in reclaimed minesoils. Cr. Rev. Plant Sci. 24, 151–165. https://doi.org/10.1080/07352680591002147. van der Heijden, M.G.A., Bardgett, R.D., Straalen, N.M.V., 2008. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol. Lett. 11, 296–310. https://doi.org/10.1111/j.1461-0248.2007.01139.x. Venables, W.N., Ripley, B.D., 2002. Modern Applied Statistics With S, Fourth edition. Springer, New York, NY. Visser, S., Fujikawa, J., Griffiths, C.L., Parkinson, D., 1984. Effect of topsoil storage on microbial activity, primary production and decomposition potential. Plant Soil 82, 41–50. https://doi.org/10.1007/BF02220768. Waaland, M.E., Allen, E.B., 1987. Relationships between VA mycorrhizal fungi and plant cover following surface mining in Wyoming. J. Range Manag. 40, 271. https://doi. org/10.2307/3899096. Weil, R., Islam, K., Stine, M., Gruver, J., Samson-Liebig, S., 2003. Estimating active carbon for soil quality assessment: a simplified method for laboratory and field use. Am. J. Alternative Agr. 18, 3–17. https://doi.org/10.1079/AJAA200228. Weiser, P.K., 1975. Soil Survey of Oliver County, North Dakota. Soil Conservation Service,

composition of total organic carbon in reclaimed coal mine lands. Land Degrad. Dev. 20, 156–175. https://doi.org/10.1002/ldr.889. Gee, G.W., Bauder, J.W., 1986. Particle-size analysis. In: Klute, A. (Ed.), Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods, Agronomy Monograph. American Society of Agronomy, Soil Science Society of America, Madison, WI, pp. 383–411. https://doi.org/10.2136/sssabookser5.1.2ed.c15. Gilley, J.E., Gee, G.W., Bauer, A., Willis, W.O., Young, R.A., 1977. Runoff and erosion characteristics of surface-mined sites in western North Dakota. T. ASAE. 20, 697–0700. https://doi.org/10.13031/2013.35631. Gould, A.B., Liberta, A.E., 1981. Effects of topsoil storage during surface mining on the viability of vesicular-arbuscular mycorrhiza. Mycologia 73, 914–922. https://doi. org/10.2307/3759802. Graves, S., Piepho, H., Selzer, L., Dorai-Raj, S., 2015. multcompView: visualizations of paired comparisons. R package version 0.1-7. http://CRAN.R-project.org/package= multcompView. Grosjean, P., Ibanez, F., Etienne, M., 2018. pastecs: package for analysis of space-time ecological series. R package version 1.3.21. https://CRAN.R-project.org/package= pastecs. Hargis, N.E., Redente, E.F., 1984. Soil handling for surface mine reclamation. J. Soil Water Conserv. 39, 300–305. http://www.jswconline.org/content/39/5/300.extract. Harris, J.A., Birch, P., Short, K.C., 1989. Changes in the microbial community and physico-chemical characteristics of topsoils stockpiled during opencast mining. Soil Use Manag. 5, 161–168. https://doi.org/10.1111/j.1475-2743.1989.tb00778.x. Helingerová, M., Frouz, J., Šantrůčková, H., 2010. Microbial activity in reclaimed and unreclaimed post-mining sites near Sokolov (Czech Republic). Ecol. Eng. 36, 768–776. https://doi.org/10.1016/j.ecoleng.2010.01.007. Hetrick, B.A.D., Kitt, D.G., Wilson, G.T., 1988. Mycorrhizal dependence and growth habit of warm-season and cool-season tallgrass prairie plants. Can. J. Bot. 66, 1376–1380. https://doi.org/10.1139/b88-193. Hetrick, B.A.D., Hartnett, D.C., Wilson, G.W.T., Gibson, D.J., 1994. Effects of mycorrhizae, phosphorus availability, and plant density on yield relationships among competing tallgrass prairie grasses. Can. J. Bot. 72, 168–176. https://doi.org/10. 1139/b94-023. Hofmann, L., Ries, R.E., Lorenz, R.J., 1981. Livestock and vegetative performance on reclaimed and nonmined rangeland in North Dakota. J. Soil Water Conserv. 36, 41–44. http://www.jswconline.org/content/36/1/41.abstract. Hueso, S., García, C., Hernández, T., 2012. Severe drought conditions modify the microbial community structure, size and activity in amended and unamended soils. Soil Biol. Biochem. 50, 167–173. https://doi.org/10.1016/j.soilbio.2012.03.026. Ingram, L.J., Schuman, G.E., Stahl, P.D., Spackman, L.K., 2005. Microbial respiration and organic carbon indicate nutrient cycling recovery in reclaimed soils. Soil Sci. Soc. Am. J. 69, 1737–1745. https://doi.org/10.2136/sssaj2004.0371. Iverson, L.R., Wali, M.K., 1982. Buried, viable seeds and their relation to revegetation after surface mining. J. Range Manag. 35, 648. https://doi.org/10.2307/3898656. Johnson, N.C., McGraw, A.-C., 1988. Vesicular-arbuscular mycorrhizae in taconite tailings. I. Incidence and spread of endogonaceous fungi following reclamation. Agric. Ecosyst. Environ. 21, 135–142. https://doi.org/10.1016/0167-8809(88)90082-5. Johnson, D.B., Williamson, J.C., Bailey, A.J., 1991. Microbiology of soils at opencast coal sites. I. Short-and long-term transformations in stockpiled soils. J. Soil Sci. 42, 1–8. https://doi.org/10.1111/j.1365-2389.1991.tb00085.x. Koch, J.M., 2007. Restoring a Jarrah forest understorey vegetation after bauxite mining in Western Australia. Restor. Ecol. 15, S26–S39. https://doi.org/10.1111/j.1526-100X. 2007.00290.x. Kuzyakov, Y., Blagodatskaya, E., 2015. Microbial hotspots and hot moments in soil: concept & review. Soil Biol. Biochem. 83, 184–199. https://doi.org/10.1016/j. soilbio.2015.01.025. Lang, K.J., Prunty, L., Schroeder, S.A., Disrud, L.A., 1984. Interrill erosion as an index of mined land soil erodibility. T. ASAE. 27, 99–0104. https://doi.org/10.13031/2013. 32743. Malik, A.A., Chowdhury, S., Schlager, V., Oliver, A., Puissant, J., Vazquez, P.G.M., Jehmlich, N., von Bergen, M., Griffiths, R.I., Gleixner, G., 2016. Soil fungal:bacterial ratios are linked to altered carbon cycling. Front. Microbiol. 7, 1247. https://doi.org/ 10.3389/fmicb.2016.01247. Manzoni, S., Schimel, J.P., Porporato, A., 2012. Responses of soil microbial communities to water stress: results from a meta-analysis. Ecol 93, 930–938. https://doi.org/10. 1890/11-0026.1. Miller, R.M., Jastrow, J.D., 1992. The application of VA mycorrhizae to ecosystem restoration and reclamation. In: Allen, M.F. (Ed.), Mycorrhizal Functioning: An Integrative Plant-Fungal Process. Chapman & Hall, Ltd, New York, NY, pp. 438–467. Mummey, D.L., Stahl, P.D., Buyer, J.S., 2002a. Microbial biomarkers as an indicator of ecosystem recovery following surface mine reclamation. Appl. Soil Ecol. 21, 251–259. https://doi.org/10.1016/S0929-1393(02)00090-2. Mummey, D.L., Stahl, P.D., Buyer, J.S., 2002b. Soil microbiological properties 20 years after surface mine reclamation: spatial analysis of reclaimed and undisturbed sites. Soil Biol. Biochem. 34, 1717–1725. https://doi.org/10.1016/S0038-0717(02) 00158-X. Mummey, D., Holben, W., Six, J., Stahl, P., 2006. Spatial stratification of soil bacterial populations in aggregates of diverse soils. Microb. Ecol. 51, 404–411. https://doi. org/10.1007/s00248-006-9020-5. Munshower, F.F., 1994. Practical Handbook of Disturbed Land Revegetation. Lewis Publishers, Boca Raton, FL. Neuwirth, E., 2014. RColorBrewer: ColorBrewer palettes. R package version 1.1-2. https://cran.r-project.org/web/packages/RColorBrewer/index.html. North Dakota Agricultural Weather Network, 2019. NDAWN station: Hazen, ND. https:// ndawn.ndsu.nodak.edu/. Noyd, R.K., Pfleger, F.L., Russelle, M.P., 1995. Interactions between native prairie grasses

9

Applied Soil Ecology xxx (xxxx) xxx–xxx

P.R. Block, et al.

https://doi.org/10.1007/BF00011115. Yuan, Y., Zhao, Z., Zhang, P., Chen, L., Hu, T., Niu, S., Bai, Z., 2017. Soil organic carbon and nitrogen pools in reclaimed mine soils under forest and cropland ecosystems in the Loess Plateau, China. Ecol. Eng. 102, 137–144. https://doi.org/10.1016/j. ecoleng.2017.01.028. Zeileis, A., Grothendieck, G., 2005. Zoo: S3 infrastructure for regular and irregular time series. J. Stat. Softw. 14, 1–27. https://doi.org/10.18637/jss.v014.i06. Zhang, Z.Q., Shu, W.S., Lan, C.Y., Wong, M.H., 2001. Soil seed bank as an input of seed source in revegetation of lead/zinc mine tailings. Restor. Ecol. 9, 378–385. https:// doi.org/10.1046/j.1526-100X.2001.94007.x. Zhang, P., Cui, Y., Zhang, Y., Jia, J., Wang, X., Zhang, X., 2016. Changes in soil physical and chemical properties following surface mining and reclamation. Soil Sci. Soc. Am. J. 80, 1476–1485. https://doi.org/10.2136/sssaj2016.06.0167.

US Department of Agriculture and North Dakota Experiment Station. https://www. nrcs.usda.gov/Internet/FSE_MANUSCRIPTS/north_dakota/oliverND1975/ oliverND1975.pdf. Wick, A.F., Stahl, P.D., Ingram, L.J., Vicklund, L., 2009. Soil aggregation and organic carbon in short-term stockpiles. Soil Use Manag. 25, 311–319. https://doi.org/10. 1111/j.1475-2743.2009.00227.x. Wickham, H., 2009. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag, New York, NY. Wickham, H., 2011. The split-apply-combine strategy for data analysis. J. Stat. Softw. 40, 1–29. https://doi.org/10.18637/jss.v040.i01. Wickham, H., 2018. Scales: scale functions for visualizations. R package version 1.0.0. http://CRAN.R-project.org/package=scales. Williamson, J.C., Johnson, D.B., 1990. Mineralisation of organic matter in topsoils subjected to stockpiling and restoration at opencast coal sites. Plant Soil 128, 241–247.

10