A meta-analysis of soil microbial biomass levels from established tree plantations over various land uses, climates and plant communities

A meta-analysis of soil microbial biomass levels from established tree plantations over various land uses, climates and plant communities

Catena 150 (2017) 256–260 Contents lists available at ScienceDirect Catena journal homepage: www.elsevier.com/locate/catena A meta-analysis of soil...

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Catena 150 (2017) 256–260

Contents lists available at ScienceDirect

Catena journal homepage: www.elsevier.com/locate/catena

A meta-analysis of soil microbial biomass levels from established tree plantations over various land uses, climates and plant communities Qian Zhang a,b, Junjie Yang c, Roger T. Koide d, Tao Li e, Haishui Yang f,⁎, Jianmin Chu a,b,⁎⁎ a

Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China Key Laboratory of Tree Breeding and Cultivation, State Forestry Administration, Beijing 100091, China State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China d Department of Biology, Brigham Young University, Provo, UT 84602, USA e Terrestrial Ecology Section, Department of Biology, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen, Denmark f Key Laboratory of Crop Physiology, Ecology and Production Management, Ministry of Agriculture/College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China b c

a r t i c l e

i n f o

Article history: Received 25 August 2015 Received in revised form 12 October 2016 Accepted 27 November 2016 Available online xxxx Keywords: Tree plantation Soil microbial biomass Previous land use Climate Plant species

a b s t r a c t Uncertainties remain as to the potential for tree plantations to affect soil microbial biomass. Our aim was to determine the factors accountable for the maintenance and the increase of soil microbial biomass following tree plantation. Based on mixed effect models, we conducted a meta-analysis with three fixed and two random factors to test the impact of tree plantation on soil microbial biomass. Previous land use was more important than climate or plant species in its effect on soil microbial biomass after tree plantation. There was a positive impact on soil microbial biomass for tree plantations on bare land but a negative impact for which on previously forested land. Climate and plant species were found to be not as important in their effects on soil microbial biomass. Our meta-analysis gives a general pattern that previous land use type is the major controlling factor of soil microbial biomass following tree plantations and promotes our understanding of the effects of rehabilitation of degraded sites on vegetation recruitment. © 2016 Elsevier B.V. All rights reserved.

1. Introduction Forest ecosystems cover approximately 40% of Earth's ice-free, terrestrial surface (Waring and Running, 2007) and tree plantations comprise approximately 5% of this area (FAO, 2002; Häggman et al., 2013). Deforestation, the removal of forest cover as a result of human activities, has resulted in many serious environmental problems, e.g., flooding and soil erosion, loss in soil carbon storage and habitat destruction for wildlife, etc. (Bhagwat et al., 2008; Godar et al., 2015; Jandl et al., 2007; Lindenmayer and Hobbs, 2004). Such degraded lands need proper ecological rehabilitation through which soils can be managed to support biological productivity. Plantation forestry is a method by which degraded sites can be rehabilitated to previous levels of productivity. There is a global trend of an increasing tree plantation surface throughout the world from 140 million hectares in 2005 to over 180 million hectares by 2020 (FAO, 2006). Tree plantations showed much positive effects on provision of ecosystem services (Ray et al., 2015), e.g., providing refuge for wildlife (Bhagwat et al., 2008; Lindenmayer and Hobbs, 2004), increasing carbon sequestration (Livesley et al., 2009), reducing natural

⁎ Correspondence to: H. Yang, College of Agriculture, Nanjing Agricultural University, No.1, Weigang Road, Xuanwu District, Nanjing 210095, China. ⁎⁎ Correspondence to: J. Chu, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China. E-mail addresses: [email protected] (H. Yang), [email protected] (J. Chu).

http://dx.doi.org/10.1016/j.catena.2016.11.028 0341-8162/© 2016 Elsevier B.V. All rights reserved.

disasters, such as flooding and soil erosions (Chirino et al., 2006), and producing woods for industry. As the support of forest ecosystem, soils are sensitive and vulnerable to forest degradation and deforestation. The most obvious forms of soil degradation in forest areas include nutrient depletion, soil erosion, etc. As soils are vulnerable to loss in aboveground biomass and diversity (e.g. de-forestation), it is important to elucidate factors affecting soil microbial biomass, a small but sensitive component of soil, following variations in aboveground biomass and diversity. Soil organic matter has an important impact on all soil functions and plays a central role in the global carbon cycle (Blume et al., 2016; Karmakar et al., 2016). Microbial biomass is the most active fraction of soil organic matter (Cuevas et al., 2013; Jenkinson and Ladd, 1981; Singh et al., 1989). In nearly all ecosystems, microorganisms are responsible for most of the respiration and a large portion of the nutrient cycling. Microorganisms are generally considered the driving force behind litter decomposition processes (DeAngelis et al., 2013a; Smith and Paul, 1990). They act as both a source and a sink for available nutrients (Diaz-Ravina et al., 1993; Smith and Paul, 1990) and play a major role in numerous ecosystem functions, such as organic matter turnover, nitrogen cycling, nutrient mobilization/immobilization, humification, degradation of pollutants and maintenance of the soil structure (DeAngelis et al., 2013b; Lejon et al., 2005; Moller et al., 1999; Preston et al., 2001; Stevenson, 1982). Measurement of soil microbial biomass can give an early indication of changes in total soil organic matter long

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before changes in total soil C or N can be reliably detected (Powlson et al., 1987). The effect of tree plantations on soil microbial biomass carbon (MBC) has previously been documented (Jesus et al., 2009; Smith et al., 2015), but the process remains poorly understood. Tree plantations have been found to have positive (Yao et al., 2006), negative (Cao et al., 2008) or no effects on soil MBC (Sparling et al., 1994). The inconsistent results from individual studies likely arise because the magnitude and direction of the change in soil microbial biomass are affected by multiple factors including climate, previous land use and tree species, etc. In order to better understand how and why tree plantation affects soil microbial biomass, it is undoubtedly necessary to determine the general patterns and the major controlling factors of soil microbial biomass. To our knowledge, there has been no meta-synthesis exploring the effects of tree plantations on soil MBC. In this study, field trials with a paired-site design were analyzed using a meta-analytical approach to quantitatively synthesize the soil MBC patterns in response to afforestation. Our objective was to explore whether there is a general pattern of soil MBC response to tree plantations. We hypothesized that the response of SMB to tree plantations depends on previous land use type, climate and the identity of trees planted. In order to test this hypothesis, we performed a meta-analysis with multi-factor statistical models which simultaneously estimate the relative magnitude of the effects of multiple predictor variables. 2. Materials and methods 2.1. Study selection The literature available on changes in soil microbial biomass following tree plantations was compiled. In this study, tree plantation includes both afforestation and reforestation, in which ‘afforestation’ refers to the establishment of a plantation (from seedlings or seeds) on treeless land, and reforestation is the intentional restocking of existing forests and woodlands that have been depleted. Natural regeneration without human intervention was excluded. The term ‘treeless land’ includes croplands used for food or fibre production, permanent pasture, natural grassland, and shrub and barren land. We only included studies which reported soil microbial biomass before and after tree plantations. Only studies including first-rotation plantations after the change in landuse were utilized. Databases from Blackwell, CNKI, Elsevier, Kluwer, JSTOR, Springer and Web of Science were searched for source data from January 1990 to August 2011 with the terms (afforestation OR reforestation OR plantation) AND microb*. In total, the dataset included 199 trials reported by 31 publications (see Appendix S1 and S2). Data presented in tables were directly extracted; graphed data was digitized with GetData software (http://getdata-graph-digitizer.com/). For each paper, the following information was compiled: sources of data, climate zone, previous land use, tree species, plantation age and soil sampling depth. When more than one depth was sampled in one specific study, soil microbial biomass at each depth was considered to be nested within the study, and treated as a random factor in the meta-analysis. When a particular chronosequence or retrospective study had observations at a number of plantation ages, each age was regarded as being nested within the study, and treated as a random factor in the meta-analysis.

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spray, infertility or toxic soil, or overexploitation by human. Climatic zones were classified into tropical, subtropical, temperate monsoon, temperate marine, temperate continental, Mediterranean and plateau (Laganiere et al., 2010). Tree species planted were categorized into pine, Eucalyptus, coniferous excluding pine and broadleaf excluding Eucalyptus. Tree species were selected according to the methods described by Laganiere et al. (2010). 2.3. Data analysis Soil microbial biomass carbon (MBC) was the most commonly reported measure of soil microbial biomass response to tree plantation in our analyses. Therefore, we used soil MBC to represent soil microbial biomass. For each experimental comparison between tree plantation and control, we calculated an effect size for soil microbial biomass carbon based on mean values. Especially, the effect size was calculated as the log response ratio of soil MBC in the tree plantation and control: ln (Xi/Xn), where Xi is the mean soil microbial biomass carbon in the plantation treatment and Xn is the mean biomass in the corresponding control. This metric is positive if tree plantation increased soil microbial biomass carbon, and negative if it decreased soil microbial biomass carbon. The MIXED procedure was used with restricted maximum likelihood estimation of parameters in SAS (SAS v. 9.1; SAS Institute, Inc., Cary, NC, USA). The overall weighted mean effect size (i.e. the log response ratio of soil microbial biomass carbon to tree plantation) and random between-studies variance component (sensu van Houwelingen et al., 2002) were estimated with a pure random-effects model. Each effect size estimate was weighted by the reciprocal of the within-study variance (which was estimated as the summed number of replicates in control and tree plantation) plus the maximum likelihood estimate of the residual between-studies variance component. This weighting method was used in lieu of the actual estimated effect size variance from each study, because most studies reported the levels of replication rather than the actual measures of variance (SD, SE or confidence intervals) which could be used to calculate variance (Hoeksema et al., 2010). Thus, we assumed higher levels of replication could provide more precise estimates of effect size and those studies were given higher weight in the meta-analysis. Since this variable can now be compared between different sites and different studies, a mixed linear model (PROC MIXED) was developed, including three factors as fixed explanatory variables (previous land use, climatic zone, species planted; MODEL statement) and two factors as random variables (sampling depth, plantation age; RANDOM statement). By adding these random variables to the model, we can control their effects on the dependent variable. 3. Results 3.1. Previous land use The land use history before tree plantation significantly affected soil microbial biomass (F = 27.62, P b 0.01; Table 1; Fig.1). Tree plantations significantly increased soil microbial biomass in barren land (t = 3.57, P b 0.01), but significantly decreased soil microbial biomass beneath the forest (t = −2.44, P b 0.01). However, no significant effects were found in pasture, woodland, grassland or cropland (P N 0.05).

2.2. Data category

3.2. Climate zone

We selected the following potential variables which might affect soil microbial biomass after tree plantations: (1) previous land use; (2) climatic zone; (3) tree species planted; (4) sampling depth and (5) plantation age. Previous land use type was grouped into barren land, natural forest, shrubland, pasture, grassland and cropland. Barren land is defined when the publication recorded it as “barren land”, an area with little or no vegetation due to high winds, harsh climate, salt

Soil MBC in tree plantations was found not to vary with climate zone (F = 1.19, P = 0.31, Table 1, Fig. 2). There was a significant effect of tree plantation on soil microbial biomass in the subtropical climate (t = 2.17, P = 0.03). However, no significant effects were found in temperate monsoon climate, temperate marine climate, plateau climate zone, tropical climate, temperate continental climate and Mediterranean climate zones (P N 0.05).

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Table 1 Results of the mixed linear model developed to identify the factors responsible for variation in soil microbial biomass following plantation practice (composed of three fixed factors and two random variables). Covariable

Estimate

Intercept Sampling depth Plantation age Residuals

0.46 0.03 0.07 30.08

Factor

Df

F

P

Previous land use Climate zone Tree species

5 6 3

27.62 1.19 2.39

b0.01 0.31 0.07

3.3. Plant species Species making up the plant community showed a marginally significant effect on MBC after tree plantations (F = 2.39, P = 0.07, Table 1, Fig.3). There was a significant rise in MBC beneath Eucalyptus spp. stands (t = 2.10, P = 0.04; Fig. 3), while a drop was noted in the pine plantations though not significantly (Fig.3). Moreover, plantations with broadleaf (excluding Eucalyptus spp) and coniferous (excluding pine) trees both had non-significant effects on soil microbial biomass (Fig.3).

3.4. Random factors In the mixed model, the covariance parameters of random effects of sampling depth were estimated as 0.032, which was about 1% of the total residuals. The covariance parameters of random effects of plantation age were estimated as 0.070, which was about 2% of the total residuals.

4. Discussion Previous studies have suggested that multiple factors can affect soil microbial biomass, including precipitation, temperature, soil texture and structure, succession time, plant species, residue amendments, land use intensity and anthropogenic disturbance (Bossio et al., 2005; Calderon et al., 2000; Cuevas et al., 2013; DeAngelis et al., 2013b; Wardle, 1992; Yu et al., 2012). However, our meta-analysis provided

Fig. 1. Influence of previous land use on changes in soil microbial biomass after tree plantation. The error bars are the standard errors of the mean. The number of observations is indicated in parentheses. *: significantly different from 0, and ns: not significantly different from 0.

Fig. 2. Influence of climate zone on changes in soil microbial biomass after tree plantations. The error bars are the standard errors of the mean. The number of observations is indicated in parentheses. *: significantly different from 0, and ns: not significantly different from 0. TR, tropical; STR, subtropical; TMS, temperate monsoon climate; TMR, temperate marine climate; TC, Temperate continental climate; MT, Mediterranean climate; PL, plateau.

solid evidence that previous land use type was more important than climate or plant species in its effect on soil MBC after tree plantations. Soil MBC is a sensitive indicator for changes in land-use (DeAngelis et al., 2013a; Smith et al., 2015; Yu et al., 2012). For example, both woodland and grassland have been shown to support higher levels of MBC than farmland, whereas conversion of natural forests to plantations has been found to reduce MBC (Bossio et al., 2005; Calderon et al., 2000; Yu et al., 2012). Our results showed that tree plantations on barren land resulted in elevated MBC, while a lower MBC was caused by tree plantations in natural forests, which suggested that previous land use may exert a large impact on soil MBC. For the barren land, the positive effects of tree plantations on soil MBC can be explained by two processes. Firstly, tree plantations may improve substrate availability for soil microbes. Soil microbial biomass from barren land is often low possibly because of the low level of carbon substrate which limits soil microbial growth (Materechera and Murovhi, 2011). However, tree plantations may input a large proportion of organic carbon into the soils through root exudates, root turnover and

Fig. 3. Influence of tree species planted on changes in soil microbial biomass after tree plantation. The error bars are the standard errors of the mean. The number of observations is indicated in parentheses. *: significantly different from 0, and ns: not significantly different from 0. Eucal, Eucalyptus spp.; Conif, coniferous (excluding pine); Broad, broadleaf (excluding Eucalyptus spp.).

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litters, which might greatly promote soil microbial growth and thus increase soil microbial biomass (Chen et al., 2005; Smith et al., 2014). Secondly, soil physicochemical properties might be improved by tree plantations. In the barren lands, soil temperature might fluctuate greatly between day and night. However, vegetation cover after tree plantations might reduce the magnitude of temperature fluctuation and maintain a relatively stable soil temperature, thus promoting soil microbial growth (Wardle, 1992). Tree plantations on the barren lands might reduce surface runoff and increase soil moisture content, which is possibly correlated to soil microbial biomass (Wardle and Parkinson, 1990). Organic acids from root exudates after tree plantations might reduce soil pH and activate nutrient availability for soil microbial growth (DeAngelis et al., 2013b; Grayston et al., 1997; Smith et al., 2014). Reduction in soil compaction and increase in aggregate size might improve aerobic conditions for microbial growth after tree plantations on the barren lands (Wardle, 1992). Thus, alterations in these soil physicochemical processes might make a contribution to soil microbial biomass after tree plantations on the barren lands. Several studies have found that soil microbial biomass is low in the tree plantations compared to the natural forest ecosystems (Animon et al., 1999; Behera and Sahani, 2003; Burton et al., 2010; Guo et al., 2016). This supports our findings that MBC was reduced by tree plantations on previously forested land. The reasons behind the decline of soil microbial biomass after plantation on the degraded forest soils may be explained as follows. First, tree plantations might cause loss of organic matter from previously forested soils. As is known, forest soil is rich in organic matter (Rovira and Vallejo, 2007), which acts as sufficient substrate for soil microbial growth. However, removal of litter and plowing before planting might result in a rapid and large loss of soil organic matter (Materechera and Murovhi, 2011), which might in turn decrease soil microbial growth and sustain lower microbial biomass on the previously forested lands. Further, loss of plant species richness might be another factor that contributes to the reduction of soil microbial biomass after tree plantations on previously forested lands. Leckie et al. (2004) have reported positive relationship between plant species richness and soil microbial biomass. Cong et al. (2015) have documented that higher plant species richness produces more diversified litters, which may enhance soil carbon accumulation and promote soil microbial growth. However, the conversion of forests to tree plantations will shift plant species richness from high to low levels (Leckie et al., 2004). This might cause reduction in soil microbial biomass through loss in litter species diversity. Finally, chemical composition of litters might affect litter decomposition, which further drives the differentiation of soil microbial growth between tree plantations and natural forests (Fan and Liang, 2014; Wallenstein et al., 2013). Burton et al. (2010) have found that soil MBC is negatively associated with C/N ratio and have thus argued that higher-quality organic matter input is one important determinant for higher MBC in natural forest than tree plantations. Some other studies have shown that allelochemicals released from leaves of the singletree plantations might exert harmful impact on soil microbial growth and thus decelerate litter decomposition (Animon et al., 1999; Behera and Sahani, 2003; Dellacassa et al., 1989). However, the allelochemical effect is possibly weak in the natural forests with mixed plant species. In contrast with bare land and natural forests, establishing tree plantations on shrub, pasture and grasslands had no significant impact on MBC. This is likely due to the fact that plants may allocate the majority of their biomass to roots in these ecosystems (Kuzyakov and Domanski, 2000; Bolinder et al., 2002), and that the turnover of the belowground (root) biomass is much faster than in forest environments (Kuzyakov and Domanski, 2000; Guo et al., 2007). Root C input is thus higher in shrubs and herbaceous plants than in trees. This indicates that it might be negligible for the impact of tree plantations on the accumulation of soil substrate C for microbial growth in these ecosystems. However, one limitation of our study is that the source data were collected from different soil depths. It is known that sampling depth is

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an important factor when considering the effect of tree plantation on soil microbial biomass (Laganiere et al., 2010). For example, trees have a deeper root system than crop plants or grassland plants, and this may influence soil microbial biomass as many soil microbes inhabit the rhizosphere (Wardle, 1992). Also, agricultural practices such as plowing can disturb the topsoil and affect soil microbes (Laganiere et al., 2010). In fact, we realized the weakness of inconsistent sampling depths embedded, which was determined by the source experimental designs. When constructing the mixed effect model, we included sampling depth as a random factor in order to control its effect on MBC. Although our estimation of the covariance parameters revealed that sampling depth did not explain a significant proportion of the data (Table 1), the lack of consistent soil sampling depth might still, to some extent, affect the interpretation of our results. 5. Conclusion Our meta-analysis showed that only previous land use exerted a significant impact on soil microbial biomass after tree plantations. There was a positive impact of tree plantation on barren land and a negative impact of tree plantation on natural forest land. Climatic zones and plant species were not determinants explaining the variation of MBC after tree plantations. However, the lack of consistent sampling depth and soil profile information might skew some of the results compared to other studies where more soil profile parameters were assessed. Understanding the factors that affect soil microbial biomass following tree plantation would help to increase our ability to predict the consequences of tree plantation establishment and monitor forest rehabilitation, as well as to evaluate sustainability of forest practices. Acknowledgement This work was supported by the Central Public-interest Scientific Institution Basal Research Fund (CAFYBB2016ZD001), the Natural Science Foundation of China (No. 31300105, 41071334 and 31400373), Natural Science Foundation of Jiangsu Province (No. 20140689), the National Scientific and Technological Project of China (No. 2015BAD07B07). Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.catena.2016.11.028. References Animon, M.M., Ashokan, P.K., Sudhakar, K., Jayashankar, S., Dhanesh, K.P., 1999. Physicochemical and biological properties of soil under Acacia auriculiformis and Eucalyptus tereticornis plantations. J. Trop. For. 15, 45–52. Behera, N., Sahani, U., 2003. Soil microbial biomass and activity in response to Eucalyptus plantation and natural regeneration on tropical soil. For. Ecol. Manag. 174, 1–11. Bhagwat, S.A., Willis, K.J., Birks, H.J.B., Whittaker, R.J., 2008. Agroforestry: a refuge for tropical biodiversity? Trends Ecol. Evol. 23, 261–267. Blume, H.P., Brümmer, G.W., Fleige, H., Horn, R., Kandeler, E., Kögel-Knabner, I., Kretzschmar, R., Stahr, K., Wilke, B.M., 2016. Soil organic matter. Scheffer/ Schachtschabel Soil Science. Springer, Berlin Heidelberg, pp. 55–86. Bolinder, M.A., Angers, D.A., Bélanger, G., Michaud, R., Laverdiére, M.R., 2002. Root biomass and shoot to root ratios of perennial forage crops in eastern Canada. Can. J. Plant Sci. 82, 731–737. Bossio, D.A., Girvan, M.S., Verchot, L., Bullimore, J., Borelli, T., Albrecht, A., Scow, K.M., Ball, A.S., Pretty, J.N., Osborn, A.M., 2005. Soil microbial community response to land use change in an agricultural landscape of Western Kenya. Microb. Ecol. 49, 50–62. Burton, J., Chen, C., Xu, Z., Ghadiri, H., 2010. Soil microbial biomass, activity and community composition in adjacent native and plantation forests of subtropical Australia. J. Soil. Sediment. 10, 1267–1277. Calderon, F.J., Jackson, L.E., Scow, K.M., Rolston, D.E., 2000. Microbial responses to simulated tillage and in cultivated and uncultivated soils. Soil Biol. Biochem. 32, 1547–1559. Cao, C.Y., Jiang, D.M., Teng, X.H., Jiang, Y., Liang, W.J., Cui, Z.B., 2008. Soil chemical and microbiological properties along a chronosequence of Caragana microphylla Lam. Plantations in the Horqin sandy land of Northeast China. Appl. Soil Ecol. 40, 78–85. Chen, T.H., Chiu, C.Y., Tian, G.L., 2005. Seasonal dynamics of soil microbial biomass in coastal sand dune forest. Pedobiologia 49, 645–653.

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