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Meta-analyses of the effects of major global change drivers on soil respiration across China
Atmospheric Environment 150 (2017) 181e186
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Short communication
Meta-analyses of the effects of major global change drivers on soil respiration across China Jiguang Feng a, b, Jingsheng Wang a, *, Lubin Ding b, Pingping Yao b, Mengping Qiao b, Shuaichen Yao a, b a
Qianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China School of Environment and Natural Resources, Renmin University of China, Beijing 100872, China
b
h i g h l i g h t s Simulated acid rain significantly decreased soil respiration (Rs) across China. Warming, N addition and precipitation increase significantly increased Rs. The responses of Rs varied with ecosystem types and experimental treatments. The responses of Rs under global change in China are similar to those in the global.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 12 May 2016 Received in revised form 23 November 2016 Accepted 24 November 2016 Available online 25 November 2016
Soil respiration (Rs) is affected largely by major global change drivers, global meta-analysis studies have synthesized the available information to determine how Rs responds to these drivers. However, little is known about the effects of these drivers on Rs across China. Here, we conducted a meta-analysis to synthesize 80 studies published in the literature with 301 paired comparisons to quantify the responses of Rs to simulated warming, nitrogen addition, precipitation increase and acid rain across Chinese terrestrial ecosystem. Results showed that global change drivers significantly changed Rs across Chinese ecosystems. Warming, nitrogen addition, and precipitation increase significantly increased Rs by 9.08%, 5.21%, 31.68%, respectively, while simulated acid rain decreased Rs by 7.06%. The responses of Rs to warming, nitrogen addition, and precipitation increase are similar in both direction and magnitude to those reported in global syntheses, except for higher response ratio under precipitation increase in China. In addition, the responses of Rs were different among ecosystem types, and among experimental treatments. Warming significantly increased Rs in croplands but did not change in forests and grasslands. The effect magnitude of N addition on Rs in grasslands and croplands was much higher than those in other ecosystems. In general, precipitation increase stimulated Rs in different ecosystems, and its effect magnitudes increased with changed precipitation levels. However, acid rain inhibited Rs in different biomes and intensities of acid rain. Our findings contribute to better understanding of how Rs will change under global change, and provide important parameters for carbon cycle model at the regional scale. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Soil respiration Warming Nitrogen addition Precipitation increase Simulated acid rain Meta-analysis
1. Introduction Soil respiration (Rs) represents CO2 release through the soil surface from autotrophic root respiration and heterotrophic respiration which is associated with the decomposition of litter, roots
* Corresponding author. E-mail address: [email protected] (J. Wang). http://dx.doi.org/10.1016/j.atmosenv.2016.11.060 1352-2310/© 2016 Elsevier Ltd. All rights reserved.
and soil organic matter (Boone et al., 1998; Kuzyakov, 2006; Schindlbacher et al., 2009). As one of the largest fluxes in the global carbon cycle (Raich and Schlesinger, 1992; Bond-Lamberty and Thomson, 2010), Rs plays a vitally important role in regulating atmospheric CO2 concentration and climatic dynamics in the Earth system (Davidson et al., 2002; Luo and Zhou, 2006). The rate of Rs is affected largely by global change drivers, including climate warming, increased nitrogen (N) deposition, elevated CO2 concentration and altered precipitation pattern, etc. (Bowden et al.,
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2004; Cardon et al., 2001; Deng et al., 2010). Therefore, understanding the regulations of Rs by multiple global change drivers is necessary to project global carbon cycling in the future (Deng et al., 2010). Several global meta-analysis studies have synthesized the available information to determine how Rs responds to these drivers. Their results showed that at the global scale, warming (Wu et al., 2011; Lu et al., 2013; Wang et al., 2014), N addition (Lu et al., 2011; Zhou et al., 2014), and increased precipitation (Wu et al., 2011; Liu et al., 2016) significantly stimulated Rs, while decreased precipitation reduced Rs (Lu et al., 2011; Liu et al., 2016). However, the impacts of these drivers on Rs were different, depending on ecosystem types and experimental treatments (e.g. N addition level, N form, etc.). These studies have greatly improved our understanding of global Rs response in a changing world; however, regional or local responses of Rs can be different. As the most populous country and the second largest economy in the world, China's rapid economic development, population growth and anthropogenic activities have accelerated the changes in climate and ecosystem processes, and have caused some serious environmental issues (Chapin et al., 2011; Chen et al., 2015a). The latest data show that the annual average air temperature in China has increased by 0.9e1.5 C during 1909e2011 and will rise continuously. By the end of this century, annual air temperature in China would increase by 1.3e5.0 C, which is higher than that in global with the average value of 1e3.7 C (TNRCC, 2015). In the past 100 years, the annual precipitation in China didn't show a significant change trend, but had obvious regional differentiation of precipitation distribution, with increasing precipitation in semiarid and arid areas during the past 30 years (TNRCC, 2015). The averaged N deposition in China had increased sharply between 1980s (13.2 kg N ha1) and 2000s (21.1 kg N ha1), and is projected to increase in the coming decades (Liu et al., 2013). Moreover, southern China has become the third largest area affected by acid rain, following Europe and the United States (Wang and Xu, 2009). Hence, the potential effects of these climate and environmental changes on the Rs should be different in Chinese terrestrial ecosystem, and need to be evaluated quantitatively. Recently, two meta-analyses related to Rs responses to major global change drivers across Chinese ecosystems have been conducted at the regional scale. Fu et al. (2015) found that precipitation increase significantly increased Rs, while N addition and warming did not affect Rs. However, Chen et al. (2015a) showed negative effect of N addition on Rs. To some extent, these findings can help us understand how Rs respond to N addition, warming and precipitation increase at the national scale. However, their results on N addition were inconsistent, and the effect of acid rain on Rs hasn't been evaluated yet. Moreover, China has diverse ecosystems types and vegetation communities. Therefore, the response of Rs may differ among ecosystems in direction or magnitude. Unfortunately, how Rs respond to global change drivers among ecosystem types, and among experimental treatments across China remains lacking. In this study, we used a meta-analysis approach to synthesize all available data relating to Rs responses to these drivers across Chinese terrestrial ecosystem. Our main objectives were to: (1) quantify the responses of Rs to major global change factors; (2) examine whether ecosystem types and experimental treatments influence the responses of Rs; (3) compare the responses of Chinese terrestrial ecosystem with those from previous global metaanalyses. 2. Materials and methods 2.1. Data collection Peer-reviewed journal articles and theses published before 10
March 2016 were searched using Web of Science (Thomson Reuters, New York, NY, USA) and the China Knowledge Resource Integrated Database (CNKI, available online: http://epub.cnki.net). The searches looked for relevant papers whose title, abstract, or keywords referred to: soil respiration, soil carbon flux/efflux/emission, root/autotrophic respiration, microbial/heterotrophic respiration; warming, elevated/increasing temperature, nitrogen (N) addition/ deposition/fertilization/input/enrichment/application, urea; simulated acid rain, acid rain simulation/deposition; increase/decrease precipitation (rain), enhance/exclude/reduce precipitation (rain), water add, watering, alter/changing precipitation (rain); elevated/ increased CO2, CO2 enrichment; global change experiment, China. The detailed keywords and search term combinations were listed in Supplementary Information Table S1. All field studies evaluating the effects of simulated global change drivers on Rs conducted in China were selected following the criteria as described in some meta-analyses (Zhou et al., 2014; Fu et al., 2015; Chen et al., 2015a; Yue et al., 2016). To avoid the influence of short-term noise, we only selected experiments where the duration of Rs measurements was longer than one growing season. We only compiled databases for studies related to warming, N addition, precipitation increase and simulated acid rain because of data limitations for elevated CO2 and precipitation decrease experiments in China. Our search criteria lead to 301 paired comparisons from 80 published papers, with 49 warming treatments, 136 N addition treatments, 49 precipitation increase treatments, and 67 treatments that simulated acid rain (Supplementary Information Table S2). The distribution of selected field experiments was shown in Fig. 1.
2.2. Meta-analysis The data were analyzed using the meta-analysis methods described by Hedges et al. (1999), Luo and Zhou (2006), and Liao et al. (2008). A response ratio (RR, natural log of the ratio of the mean value of Rs in treatment plot to that in control) was used to estimate the effect magnitude for each individual observation; RR and its variance (v) were calculated as:
. RR ¼ ln Xt X c
v¼
S2t nt Xt
2
þ
!
S2c nc Xc
2
¼ ln Xt ln Xc
(1)
(2)
where and Xc , Sc, and nc represent the mean, standard deviation, and sample size of Rs in the control group, respectively; Xt , St, and nt represent the mean, standard deviation, and sample size of Rs in the treatment group, respectively (Hedges et al., 1999). The reciprocal of its variance (1/v) was considered as the weight of each RR, and the weighted response ratio (RRþþ) was calculated from RR of individual pairwise comparison between control and treatment. To test whether the experimental conditions alter the response magnitude to the four simulated drivers, each treatment (e.g. N form) was further categorized into 2e4 groups (Table 1) based on previous studies (Lu et al., 2013; Liang et al., 2013; Chen et al., 2015a; Fu et al., 2015). RRþþ and its related 95% confidence interval (CI) were calculated using meta-analytical software MetaWin 2.1 (Sinauer Associates Sunderland, MA, USA). And we conducted our calculation using random-effects model because of high heterogeneity from individual studies in our database, which can partly eliminate heterogeneity effects. If the 95% CI did not overlap with zero, the effect on Rs was considered significant. We also used t-test to test whether the response ratio in treatment was
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Fig. 1. Geographic location of warming, N addition, precipitation increase, and simulated acid rain experiments selected in this meta-analysis. Vegetation types in the map were from Compilation Group of Vegetation Atlas of China (ECVC, 1980). The software ArcGIS 10.2.2 (ESRI Inc., CA, USA) was used to create the map. Details of individual studies are listed in Supplementary Information Table S2.
Table 1 Classifications of experimental treatments under warming, nitrogen addition, precipitation increase and acid rain. Item
N addition level (kg N ha1 a1) N fertilization forms Enhanced soil temperature ( C) Increased precipitation level (% mean annual precipitation) Intensity of acid rain (pH)
Classifications of experimental treatment A
B
C
60 (low N) Urea 1 (low temperature) 30 (low precipitation) 4 (weak acid)
60e120 (medium N) NH4NO3 1e3 (medium temperature) 30e60 (medium precipitation) 3e4 (medium acid)
>120 (high N)
significantly different from that in control. For a better explanation, RRþþ was transformed back to the percentage change using the formula: [exp(RRþþ) e 1] 100%. 3. Results and discussion 3.1. Effects of global change drivers on soil respiration The weighted response ratios of Rs across Chinese terrestrial ecosystem under warming, N addition, precipitation increase, and acid rain were 0.0869 ± 0.0398, 0.0508 ± 0.0364, 0.2752 ± 0.0532 and 0.0682 ± 0.0229, respectively (Fig. 2). Warming, N addition and precipitation increase significantly stimulated Rs by 9.08%
>3 (high temperature) >60 (high precipitation) <3 (strong acid)
(P < 0.001), 5.21% (P < 0.05) and 31.68% (P < 0.001), respectively, while acid rain decreased Rs by 7.06% (P < 0.001). In addition, the responses of Rs to these simulated drivers varied with ecosystem types in direction or magnitude (Fig. 2). Warming did not significantly affect Rs in forests and grasslands, while croplands displayed a positive response (Fig. 2a). N addition significantly stimulated Rs by 9.45% and 16.17% in grasslands and croplands, but it did not change Rs in forests (either tropical or temperate forests), wetlands and shrublands (Fig. 2b). Precipitation increase significantly increased Rs in grasslands and shrublands, whereas it had no significant effect in forests (Fig. 2c). Simulated acid rain did not significantly affect Rs in croplands, but decreased Rs by 7.08% in forests (Fig. 2d). The negative effects were significant for mixed and
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Fig. 2. Weighted response ratio (RRþþ) of soil respiration in response to major global change factors. (a) warming; (b) N addition; (c) precipitation increase; and (d) simulated acid rain. Bars represent RRþþ and 95% confidence intervals (CIs). The vertical lines were drawn at RRþþ ¼ 0. The sample size for each experimental treatment was shown next to the bar. If the 95% CI did not overlap with zero, the change was considered significant. Trop. indicates tropical and subtropical; Temp. indicates temperate; pre. indicates precipitation; Con. indicates Coniferous; and Broad. indicates broad-leaved forest. The global data for warming, N addition and precipitation increase were obtained from Lu et al., 2013; Lu et al., 2011; Liu et al., 2016, respectively.
broadleaved forests within different forest types (Fig. 2d). Furthermore, the response trends of Rs differed among experimental treatments (Fig. 2). Enhanced soil temperature with 1 C and 1e3 C significantly increased Rs, while the magnitude of >3 C did not affect Rs (Fig. 2a). Low N addition significantly stimulated Rs, while medium and high N addition had no significant effect on Rs (Fig. 2b). Compared with NH4NO3, the effect of urea was more pronounced (Fig. 2b). In terms of precipitation, the low, medium and high precipitation significantly stimulated Rs by different magnitude, with the effect magnitude increasing with increased precipitation level (Fig. 2c). In addition, the intensity of acid rain also affected Rs response, medium acid rain significantly inhibited Rs, while weak and strong acid rain had no significant effect on Rs (Fig. 2d). 3.2. Comparisons of Rs responses between China and the global 3.2.1. Comparisons of Rs response to warming The response of Rs to warming in China was similar in both direction and intensity to that reported in global synthesis (Lu et al., 2011). However, the responses in frosts, grasslands and tundra in China were different from the corresponding ecosystems in the
global (Fig .1a). Many studies reported that elevated temperatures increased Rs (Bronson et al., 2008; Yin et al., 2013) because warming increased soil organic matter and litter decomposition (Bronson et al., 2008; Luo et al., 2010). On contrary, the negative or neutral effects of warming on Rs were also founded (Yin et al., 2013; Liu et al., 2015). The effects of warming on Rs depend on soil moisture, which is stimulated in wet but suppressed in dry condition (Peng et al., 2015a). Soil respiration is positively correlated with soil moisture and soil drying can reduce the effect of warming on Rs (Liu et al., 2009; Shi et al., 2012). Thus, warming-induced soil drying may offset the effects of increased temperature effects in water-limited ecosystems, leading to non-significant effects in grasslands and temperate forests in China (Fig. 1a). In addition, significantly positive effect of warming on Rs occurred in croplands. This reason may be that the cropland Rs data in our database were mainly came from winter wheat, with relatively higher soil moisture and lower soil temperature in winter. 3.2.2. Comparisons of Rs response to N addition The response of Rs to N addition in China resembled that in the global (Lu et al., 2011). However, our result significantly differed
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from previous meta-analyses with respect to Rs responses to N addition in China (Supplementary Information Table S3). Chen et al. (2015a) found that N addition significantly decreased Rs across China by 5.3%, while Fu et al. (2015) found that N addition had no significant effect on Rs. On the contrary, our result showed significantly positive effect, which may partly result from the differences of data samples (Supplementary Information Table S3) and the exclusion of croplands in the two former studies (Chen et al., 2015a; Fu et al., 2015). Different ecosystems in China exhibited diverse responses of Rs to N addition (Fig. 2b), which were approximately consistent with the corresponding ecosystems reported in previous global synthesis (Zhou et al., 2014). These divergent effects may be related to dissimilar responses of autotrophic and heterotrophic respiration under N addition. Low levels of N addition have been shown to increase Rs in N-limited ecosystems, particularly in deserts, grasslands and croplands (Xu and Wan, 2008; Zhang et al., 2014; Zhou and Zhang, 2014). In N-saturated forests, low levels of N addition did not change Rs, while high levels of N addition significantly reduced Rs (Mo et al., 2008; Peng et al., 2015b). Similarly, this condition also founded in semiarid grasslands (Li et al., 2015; Zhu et al., 2016). A recent global meta-analysis indicated that N addition can significantly stimulate autotrophic respiration in croplands and grasslands, whereas depresses it in forests, especially in tropical forests (Zhou et al., 2014). Meanwhile, N addition decrease heterotrophic respiration by relatively consistent magnitude in different ecosystems (Zhou et al., 2014). Collectively, this may lead to higher response ratios in grasslands and croplands, and lower response ratio in high-level N addition in Chinese ecosystems. 3.2.3. Comparisons of Rs response to precipitation increase The response of Rs to precipitation increase across China was consistent with global ecosystems in direction (Liu et al., 2016), but its intensity was much higher than the results from Liu et al. (2016) and Fu et al. (2015) in the globe and China, respectively. Most of the precipitation increase experiments in China were conducted in grasslands and shrublands in semiarid and arid areas (Fig .1), where the mean annual precipitation (MAP) was less than 400 and 160 mm, respectively. Therefore, these two ecosystems are more water-limited compared with tropical forests (MAP > 1700 mm). Research has demonstrated that stimulating effect of precipitation on Rs is higher in dry ecosystems (Wu et al., 2011; Liu et al., 2016) and increase with changed precipitation (%MAP) (Liu et al., 2016). Our linear regression model showed that the effect magnitude significantly increased with precipitation increment level, and decreased with MAP (P < 0.001, R2 ¼ 0.641), which was consistent with the global result (Liu et al., 2016). Altogether, these lead to relatively high response intensities in shrublands and grasslands in China. Thus, most Rs data from these two ecosystems in our database intensified the response magnitude compared with previous studies (Fu et al., 2015; Liu et al., 2016). 3.2.4. Comparisons of Rs response to simulated acid rain Our results demonstrated that simulated acid rain significantly decreased Rs, but the response magnitudes varied with ecosystem types, intensities of acid rain, and forest types (Fig. 2d). Our study appears to be the first to show how acid rain affects Rs across terrestrial ecosystem using meta-analysis. Therefore, we could not compare our regional results with the results at global scale. Previous studies pointed that the different responses of Rs to simulated acid rain among forest types may result from their differences in soil and litter layer (Liang et al., 2013), including acid buffering abilities of soil and litter layer, and original soil pH, etc. In addition, the length of time in which the simulated acid rain is applied and Hþ loads also influence its effects on Rs (Chen et al., 2012). Our
185
results showed the low and strong acid rain did not significantly change Rs. The reason may be that acid rain treatments with shortterm duration and low intensity of acid are inadequate to affect Rs due to that soil could buffer the simulated acid rain effects on soil (Zhang et al., 2011). Several studies have showed that strong acid rain trends to decrease Rs (Zhang et al., 2011; Chen et al., 2012; Liang et al., 2016), whereas Chen et al. (2015b) found that even when strong acid rain with pH 2.0 was applied, annual Rs was not significantly influenced. This may be related to the compensation and acclimation mechanisms, acid rain mediate the processes of soil CO2 emission as different respiratory components (Chen et al., 2015b). Generally, the effects of acid rain on Rs have some uncertainties. How the two components of Rs respond to acid rain in different ecosystems and the key direct or indirect factors influencing Rs under acid rain remain unclear. Here, we suggest more related processes such as root growth, microbial activities, enzyme activities, and dynamics of C fluxes (autotrophic and heterotrophic respiration) and C pools should to be further studied. 3.3. Implications and future research In the present study, we used meta-analysis to synthesize the effects of major global change drivers on Rs across China. Our metaanalysis results suggested that Rs would be significantly affected by the four simulated factors, which help us understand how Rs will change under global change, and provide important parameters for carbon cycle model at the regional scale. However, these findings based on the currently available data are hampered by some uncertainties. Most of the selected studies lasted less than five years and were mainly conducted in eastern China (Fig .1). As we all know, Chinese ecosystems have high spatial heterogeneity and diverse biogeography, therefore, this would lead to difficulties of accurate assessment of the changes in soil carbon dynamics. Additionally, in the selected studies, the N addition level (10e450 kg N ha1 a1), increased precipitation rate (13e300%), and intensity of simulated acid rain (pH ¼ 2e4.5) used in manipulation experiments were much higher than the corresponding N deposition, precipitation change, acid deposition in natural conditions in China. Such intensive nitrogen, precipitation, and acid rain manipulations also contributed to some uncertainties. Thus, we suggest that follow-up studies should focus on long-term effects of major global change drivers on Rs and its two components using more realistic precipitation increments, N and acid deposition levels, and be equably conducted in different regions across China, especially in the alpine grassland and warm dessert steppe. Author contributions J.F. conceived and designed the study. L.D., P.Y., M.Q. and S.Y. extracted the data from the literature. J.F. and J.W. conducted the data analysis and wrote the first draft of the paper. All authors critically commented on the draft and provided interpretation. Acknowledgement This work was supported by the National Basic Research Program of China (973 Program, No. 2013CB956302), and the Key Technologies Research and Development Program of China (No. 2011BAC09B03). Appendix B. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.atmosenv.2016.11.060.
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Meteorol 180, 287e296. http:// dx.doi.org/10.1016/j.agrformet.2013.06.016. Yue, K., Peng, Y., Peng, C., Yang, W., Peng, X., Wu, F., 2016. Stimulation of terrestrial ecosystem carbon storage by nitrogen addition: a meta-analysis. Sci. Rep. 6 (19895). http://dx.doi.org/10.1038/srep19895. Zhang, C., Niu, D., Hall, S.J., Wen, H., Li, X., Fu, H., Wan, C., Elser, J.J., 2014. Effects of simulated nitrogen deposition on soil respiration components and their temperature sensitivities in a semiarid grassland. Soil Biol. Biochem. 75, 113e123. http://dx.doi.org/10.1016/j.soilbio.2014.04.013. Zhang, Y., Wang, L.X., Chen, S.T., Hu, Z.H., Shen, X.S., Shi, Y.S., 2011. Effects of simulated acid rain on soil respiration in a northern subtropical secondary forest. China Environ. Sci. 31 (9), 1541e1547. Zhou, L., Zhou, X., Zhang, B., Lu, M., Luo, Y., Liu, L., Li, B., 2014. Different responses of soil respiration and its components to nitrogen addition among biomes: a meta-analysis. Glob. 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Short communication
Meta-analyses of the effects of major global change drivers on soil respiration across China Jiguang Feng a, b, Jingsheng Wang a, *, Lubin Ding b, Pingping Yao b, Mengping Qiao b, Shuaichen Yao a, b a
Qianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China School of Environment and Natural Resources, Renmin University of China, Beijing 100872, China
b
h i g h l i g h t s Simulated acid rain significantly decreased soil respiration (Rs) across China. Warming, N addition and precipitation increase significantly increased Rs. The responses of Rs varied with ecosystem types and experimental treatments. The responses of Rs under global change in China are similar to those in the global.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 12 May 2016 Received in revised form 23 November 2016 Accepted 24 November 2016 Available online 25 November 2016
Soil respiration (Rs) is affected largely by major global change drivers, global meta-analysis studies have synthesized the available information to determine how Rs responds to these drivers. However, little is known about the effects of these drivers on Rs across China. Here, we conducted a meta-analysis to synthesize 80 studies published in the literature with 301 paired comparisons to quantify the responses of Rs to simulated warming, nitrogen addition, precipitation increase and acid rain across Chinese terrestrial ecosystem. Results showed that global change drivers significantly changed Rs across Chinese ecosystems. Warming, nitrogen addition, and precipitation increase significantly increased Rs by 9.08%, 5.21%, 31.68%, respectively, while simulated acid rain decreased Rs by 7.06%. The responses of Rs to warming, nitrogen addition, and precipitation increase are similar in both direction and magnitude to those reported in global syntheses, except for higher response ratio under precipitation increase in China. In addition, the responses of Rs were different among ecosystem types, and among experimental treatments. Warming significantly increased Rs in croplands but did not change in forests and grasslands. The effect magnitude of N addition on Rs in grasslands and croplands was much higher than those in other ecosystems. In general, precipitation increase stimulated Rs in different ecosystems, and its effect magnitudes increased with changed precipitation levels. However, acid rain inhibited Rs in different biomes and intensities of acid rain. Our findings contribute to better understanding of how Rs will change under global change, and provide important parameters for carbon cycle model at the regional scale. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Soil respiration Warming Nitrogen addition Precipitation increase Simulated acid rain Meta-analysis
1. Introduction Soil respiration (Rs) represents CO2 release through the soil surface from autotrophic root respiration and heterotrophic respiration which is associated with the decomposition of litter, roots
* Corresponding author. E-mail address: [email protected] (J. Wang). http://dx.doi.org/10.1016/j.atmosenv.2016.11.060 1352-2310/© 2016 Elsevier Ltd. All rights reserved.
and soil organic matter (Boone et al., 1998; Kuzyakov, 2006; Schindlbacher et al., 2009). As one of the largest fluxes in the global carbon cycle (Raich and Schlesinger, 1992; Bond-Lamberty and Thomson, 2010), Rs plays a vitally important role in regulating atmospheric CO2 concentration and climatic dynamics in the Earth system (Davidson et al., 2002; Luo and Zhou, 2006). The rate of Rs is affected largely by global change drivers, including climate warming, increased nitrogen (N) deposition, elevated CO2 concentration and altered precipitation pattern, etc. (Bowden et al.,
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2004; Cardon et al., 2001; Deng et al., 2010). Therefore, understanding the regulations of Rs by multiple global change drivers is necessary to project global carbon cycling in the future (Deng et al., 2010). Several global meta-analysis studies have synthesized the available information to determine how Rs responds to these drivers. Their results showed that at the global scale, warming (Wu et al., 2011; Lu et al., 2013; Wang et al., 2014), N addition (Lu et al., 2011; Zhou et al., 2014), and increased precipitation (Wu et al., 2011; Liu et al., 2016) significantly stimulated Rs, while decreased precipitation reduced Rs (Lu et al., 2011; Liu et al., 2016). However, the impacts of these drivers on Rs were different, depending on ecosystem types and experimental treatments (e.g. N addition level, N form, etc.). These studies have greatly improved our understanding of global Rs response in a changing world; however, regional or local responses of Rs can be different. As the most populous country and the second largest economy in the world, China's rapid economic development, population growth and anthropogenic activities have accelerated the changes in climate and ecosystem processes, and have caused some serious environmental issues (Chapin et al., 2011; Chen et al., 2015a). The latest data show that the annual average air temperature in China has increased by 0.9e1.5 C during 1909e2011 and will rise continuously. By the end of this century, annual air temperature in China would increase by 1.3e5.0 C, which is higher than that in global with the average value of 1e3.7 C (TNRCC, 2015). In the past 100 years, the annual precipitation in China didn't show a significant change trend, but had obvious regional differentiation of precipitation distribution, with increasing precipitation in semiarid and arid areas during the past 30 years (TNRCC, 2015). The averaged N deposition in China had increased sharply between 1980s (13.2 kg N ha1) and 2000s (21.1 kg N ha1), and is projected to increase in the coming decades (Liu et al., 2013). Moreover, southern China has become the third largest area affected by acid rain, following Europe and the United States (Wang and Xu, 2009). Hence, the potential effects of these climate and environmental changes on the Rs should be different in Chinese terrestrial ecosystem, and need to be evaluated quantitatively. Recently, two meta-analyses related to Rs responses to major global change drivers across Chinese ecosystems have been conducted at the regional scale. Fu et al. (2015) found that precipitation increase significantly increased Rs, while N addition and warming did not affect Rs. However, Chen et al. (2015a) showed negative effect of N addition on Rs. To some extent, these findings can help us understand how Rs respond to N addition, warming and precipitation increase at the national scale. However, their results on N addition were inconsistent, and the effect of acid rain on Rs hasn't been evaluated yet. Moreover, China has diverse ecosystems types and vegetation communities. Therefore, the response of Rs may differ among ecosystems in direction or magnitude. Unfortunately, how Rs respond to global change drivers among ecosystem types, and among experimental treatments across China remains lacking. In this study, we used a meta-analysis approach to synthesize all available data relating to Rs responses to these drivers across Chinese terrestrial ecosystem. Our main objectives were to: (1) quantify the responses of Rs to major global change factors; (2) examine whether ecosystem types and experimental treatments influence the responses of Rs; (3) compare the responses of Chinese terrestrial ecosystem with those from previous global metaanalyses. 2. Materials and methods 2.1. Data collection Peer-reviewed journal articles and theses published before 10
March 2016 were searched using Web of Science (Thomson Reuters, New York, NY, USA) and the China Knowledge Resource Integrated Database (CNKI, available online: http://epub.cnki.net). The searches looked for relevant papers whose title, abstract, or keywords referred to: soil respiration, soil carbon flux/efflux/emission, root/autotrophic respiration, microbial/heterotrophic respiration; warming, elevated/increasing temperature, nitrogen (N) addition/ deposition/fertilization/input/enrichment/application, urea; simulated acid rain, acid rain simulation/deposition; increase/decrease precipitation (rain), enhance/exclude/reduce precipitation (rain), water add, watering, alter/changing precipitation (rain); elevated/ increased CO2, CO2 enrichment; global change experiment, China. The detailed keywords and search term combinations were listed in Supplementary Information Table S1. All field studies evaluating the effects of simulated global change drivers on Rs conducted in China were selected following the criteria as described in some meta-analyses (Zhou et al., 2014; Fu et al., 2015; Chen et al., 2015a; Yue et al., 2016). To avoid the influence of short-term noise, we only selected experiments where the duration of Rs measurements was longer than one growing season. We only compiled databases for studies related to warming, N addition, precipitation increase and simulated acid rain because of data limitations for elevated CO2 and precipitation decrease experiments in China. Our search criteria lead to 301 paired comparisons from 80 published papers, with 49 warming treatments, 136 N addition treatments, 49 precipitation increase treatments, and 67 treatments that simulated acid rain (Supplementary Information Table S2). The distribution of selected field experiments was shown in Fig. 1.
2.2. Meta-analysis The data were analyzed using the meta-analysis methods described by Hedges et al. (1999), Luo and Zhou (2006), and Liao et al. (2008). A response ratio (RR, natural log of the ratio of the mean value of Rs in treatment plot to that in control) was used to estimate the effect magnitude for each individual observation; RR and its variance (v) were calculated as:
. RR ¼ ln Xt X c
v¼
S2t nt Xt
2
þ
!
S2c nc Xc
2
¼ ln Xt ln Xc
(1)
(2)
where and Xc , Sc, and nc represent the mean, standard deviation, and sample size of Rs in the control group, respectively; Xt , St, and nt represent the mean, standard deviation, and sample size of Rs in the treatment group, respectively (Hedges et al., 1999). The reciprocal of its variance (1/v) was considered as the weight of each RR, and the weighted response ratio (RRþþ) was calculated from RR of individual pairwise comparison between control and treatment. To test whether the experimental conditions alter the response magnitude to the four simulated drivers, each treatment (e.g. N form) was further categorized into 2e4 groups (Table 1) based on previous studies (Lu et al., 2013; Liang et al., 2013; Chen et al., 2015a; Fu et al., 2015). RRþþ and its related 95% confidence interval (CI) were calculated using meta-analytical software MetaWin 2.1 (Sinauer Associates Sunderland, MA, USA). And we conducted our calculation using random-effects model because of high heterogeneity from individual studies in our database, which can partly eliminate heterogeneity effects. If the 95% CI did not overlap with zero, the effect on Rs was considered significant. We also used t-test to test whether the response ratio in treatment was
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Fig. 1. Geographic location of warming, N addition, precipitation increase, and simulated acid rain experiments selected in this meta-analysis. Vegetation types in the map were from Compilation Group of Vegetation Atlas of China (ECVC, 1980). The software ArcGIS 10.2.2 (ESRI Inc., CA, USA) was used to create the map. Details of individual studies are listed in Supplementary Information Table S2.
Table 1 Classifications of experimental treatments under warming, nitrogen addition, precipitation increase and acid rain. Item
N addition level (kg N ha1 a1) N fertilization forms Enhanced soil temperature ( C) Increased precipitation level (% mean annual precipitation) Intensity of acid rain (pH)
Classifications of experimental treatment A
B
C
60 (low N) Urea 1 (low temperature) 30 (low precipitation) 4 (weak acid)
60e120 (medium N) NH4NO3 1e3 (medium temperature) 30e60 (medium precipitation) 3e4 (medium acid)
>120 (high N)
significantly different from that in control. For a better explanation, RRþþ was transformed back to the percentage change using the formula: [exp(RRþþ) e 1] 100%. 3. Results and discussion 3.1. Effects of global change drivers on soil respiration The weighted response ratios of Rs across Chinese terrestrial ecosystem under warming, N addition, precipitation increase, and acid rain were 0.0869 ± 0.0398, 0.0508 ± 0.0364, 0.2752 ± 0.0532 and 0.0682 ± 0.0229, respectively (Fig. 2). Warming, N addition and precipitation increase significantly stimulated Rs by 9.08%
>3 (high temperature) >60 (high precipitation) <3 (strong acid)
(P < 0.001), 5.21% (P < 0.05) and 31.68% (P < 0.001), respectively, while acid rain decreased Rs by 7.06% (P < 0.001). In addition, the responses of Rs to these simulated drivers varied with ecosystem types in direction or magnitude (Fig. 2). Warming did not significantly affect Rs in forests and grasslands, while croplands displayed a positive response (Fig. 2a). N addition significantly stimulated Rs by 9.45% and 16.17% in grasslands and croplands, but it did not change Rs in forests (either tropical or temperate forests), wetlands and shrublands (Fig. 2b). Precipitation increase significantly increased Rs in grasslands and shrublands, whereas it had no significant effect in forests (Fig. 2c). Simulated acid rain did not significantly affect Rs in croplands, but decreased Rs by 7.08% in forests (Fig. 2d). The negative effects were significant for mixed and
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Fig. 2. Weighted response ratio (RRþþ) of soil respiration in response to major global change factors. (a) warming; (b) N addition; (c) precipitation increase; and (d) simulated acid rain. Bars represent RRþþ and 95% confidence intervals (CIs). The vertical lines were drawn at RRþþ ¼ 0. The sample size for each experimental treatment was shown next to the bar. If the 95% CI did not overlap with zero, the change was considered significant. Trop. indicates tropical and subtropical; Temp. indicates temperate; pre. indicates precipitation; Con. indicates Coniferous; and Broad. indicates broad-leaved forest. The global data for warming, N addition and precipitation increase were obtained from Lu et al., 2013; Lu et al., 2011; Liu et al., 2016, respectively.
broadleaved forests within different forest types (Fig. 2d). Furthermore, the response trends of Rs differed among experimental treatments (Fig. 2). Enhanced soil temperature with 1 C and 1e3 C significantly increased Rs, while the magnitude of >3 C did not affect Rs (Fig. 2a). Low N addition significantly stimulated Rs, while medium and high N addition had no significant effect on Rs (Fig. 2b). Compared with NH4NO3, the effect of urea was more pronounced (Fig. 2b). In terms of precipitation, the low, medium and high precipitation significantly stimulated Rs by different magnitude, with the effect magnitude increasing with increased precipitation level (Fig. 2c). In addition, the intensity of acid rain also affected Rs response, medium acid rain significantly inhibited Rs, while weak and strong acid rain had no significant effect on Rs (Fig. 2d). 3.2. Comparisons of Rs responses between China and the global 3.2.1. Comparisons of Rs response to warming The response of Rs to warming in China was similar in both direction and intensity to that reported in global synthesis (Lu et al., 2011). However, the responses in frosts, grasslands and tundra in China were different from the corresponding ecosystems in the
global (Fig .1a). Many studies reported that elevated temperatures increased Rs (Bronson et al., 2008; Yin et al., 2013) because warming increased soil organic matter and litter decomposition (Bronson et al., 2008; Luo et al., 2010). On contrary, the negative or neutral effects of warming on Rs were also founded (Yin et al., 2013; Liu et al., 2015). The effects of warming on Rs depend on soil moisture, which is stimulated in wet but suppressed in dry condition (Peng et al., 2015a). Soil respiration is positively correlated with soil moisture and soil drying can reduce the effect of warming on Rs (Liu et al., 2009; Shi et al., 2012). Thus, warming-induced soil drying may offset the effects of increased temperature effects in water-limited ecosystems, leading to non-significant effects in grasslands and temperate forests in China (Fig. 1a). In addition, significantly positive effect of warming on Rs occurred in croplands. This reason may be that the cropland Rs data in our database were mainly came from winter wheat, with relatively higher soil moisture and lower soil temperature in winter. 3.2.2. Comparisons of Rs response to N addition The response of Rs to N addition in China resembled that in the global (Lu et al., 2011). However, our result significantly differed
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from previous meta-analyses with respect to Rs responses to N addition in China (Supplementary Information Table S3). Chen et al. (2015a) found that N addition significantly decreased Rs across China by 5.3%, while Fu et al. (2015) found that N addition had no significant effect on Rs. On the contrary, our result showed significantly positive effect, which may partly result from the differences of data samples (Supplementary Information Table S3) and the exclusion of croplands in the two former studies (Chen et al., 2015a; Fu et al., 2015). Different ecosystems in China exhibited diverse responses of Rs to N addition (Fig. 2b), which were approximately consistent with the corresponding ecosystems reported in previous global synthesis (Zhou et al., 2014). These divergent effects may be related to dissimilar responses of autotrophic and heterotrophic respiration under N addition. Low levels of N addition have been shown to increase Rs in N-limited ecosystems, particularly in deserts, grasslands and croplands (Xu and Wan, 2008; Zhang et al., 2014; Zhou and Zhang, 2014). In N-saturated forests, low levels of N addition did not change Rs, while high levels of N addition significantly reduced Rs (Mo et al., 2008; Peng et al., 2015b). Similarly, this condition also founded in semiarid grasslands (Li et al., 2015; Zhu et al., 2016). A recent global meta-analysis indicated that N addition can significantly stimulate autotrophic respiration in croplands and grasslands, whereas depresses it in forests, especially in tropical forests (Zhou et al., 2014). Meanwhile, N addition decrease heterotrophic respiration by relatively consistent magnitude in different ecosystems (Zhou et al., 2014). Collectively, this may lead to higher response ratios in grasslands and croplands, and lower response ratio in high-level N addition in Chinese ecosystems. 3.2.3. Comparisons of Rs response to precipitation increase The response of Rs to precipitation increase across China was consistent with global ecosystems in direction (Liu et al., 2016), but its intensity was much higher than the results from Liu et al. (2016) and Fu et al. (2015) in the globe and China, respectively. Most of the precipitation increase experiments in China were conducted in grasslands and shrublands in semiarid and arid areas (Fig .1), where the mean annual precipitation (MAP) was less than 400 and 160 mm, respectively. Therefore, these two ecosystems are more water-limited compared with tropical forests (MAP > 1700 mm). Research has demonstrated that stimulating effect of precipitation on Rs is higher in dry ecosystems (Wu et al., 2011; Liu et al., 2016) and increase with changed precipitation (%MAP) (Liu et al., 2016). Our linear regression model showed that the effect magnitude significantly increased with precipitation increment level, and decreased with MAP (P < 0.001, R2 ¼ 0.641), which was consistent with the global result (Liu et al., 2016). Altogether, these lead to relatively high response intensities in shrublands and grasslands in China. Thus, most Rs data from these two ecosystems in our database intensified the response magnitude compared with previous studies (Fu et al., 2015; Liu et al., 2016). 3.2.4. Comparisons of Rs response to simulated acid rain Our results demonstrated that simulated acid rain significantly decreased Rs, but the response magnitudes varied with ecosystem types, intensities of acid rain, and forest types (Fig. 2d). Our study appears to be the first to show how acid rain affects Rs across terrestrial ecosystem using meta-analysis. Therefore, we could not compare our regional results with the results at global scale. Previous studies pointed that the different responses of Rs to simulated acid rain among forest types may result from their differences in soil and litter layer (Liang et al., 2013), including acid buffering abilities of soil and litter layer, and original soil pH, etc. In addition, the length of time in which the simulated acid rain is applied and Hþ loads also influence its effects on Rs (Chen et al., 2012). Our
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results showed the low and strong acid rain did not significantly change Rs. The reason may be that acid rain treatments with shortterm duration and low intensity of acid are inadequate to affect Rs due to that soil could buffer the simulated acid rain effects on soil (Zhang et al., 2011). Several studies have showed that strong acid rain trends to decrease Rs (Zhang et al., 2011; Chen et al., 2012; Liang et al., 2016), whereas Chen et al. (2015b) found that even when strong acid rain with pH 2.0 was applied, annual Rs was not significantly influenced. This may be related to the compensation and acclimation mechanisms, acid rain mediate the processes of soil CO2 emission as different respiratory components (Chen et al., 2015b). Generally, the effects of acid rain on Rs have some uncertainties. How the two components of Rs respond to acid rain in different ecosystems and the key direct or indirect factors influencing Rs under acid rain remain unclear. Here, we suggest more related processes such as root growth, microbial activities, enzyme activities, and dynamics of C fluxes (autotrophic and heterotrophic respiration) and C pools should to be further studied. 3.3. Implications and future research In the present study, we used meta-analysis to synthesize the effects of major global change drivers on Rs across China. Our metaanalysis results suggested that Rs would be significantly affected by the four simulated factors, which help us understand how Rs will change under global change, and provide important parameters for carbon cycle model at the regional scale. However, these findings based on the currently available data are hampered by some uncertainties. Most of the selected studies lasted less than five years and were mainly conducted in eastern China (Fig .1). As we all know, Chinese ecosystems have high spatial heterogeneity and diverse biogeography, therefore, this would lead to difficulties of accurate assessment of the changes in soil carbon dynamics. Additionally, in the selected studies, the N addition level (10e450 kg N ha1 a1), increased precipitation rate (13e300%), and intensity of simulated acid rain (pH ¼ 2e4.5) used in manipulation experiments were much higher than the corresponding N deposition, precipitation change, acid deposition in natural conditions in China. Such intensive nitrogen, precipitation, and acid rain manipulations also contributed to some uncertainties. Thus, we suggest that follow-up studies should focus on long-term effects of major global change drivers on Rs and its two components using more realistic precipitation increments, N and acid deposition levels, and be equably conducted in different regions across China, especially in the alpine grassland and warm dessert steppe. Author contributions J.F. conceived and designed the study. L.D., P.Y., M.Q. and S.Y. extracted the data from the literature. J.F. and J.W. conducted the data analysis and wrote the first draft of the paper. All authors critically commented on the draft and provided interpretation. Acknowledgement This work was supported by the National Basic Research Program of China (973 Program, No. 2013CB956302), and the Key Technologies Research and Development Program of China (No. 2011BAC09B03). Appendix B. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.atmosenv.2016.11.060.
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