| Literature DB >> 27388145 |
He Li1,2, Haihua Shen1, Leiyi Chen1, Taoyu Liu1,2, Huifeng Hu1, Xia Zhao1, Luhong Zhou1,2, Pujin Zhang1,3, Jingyun Fang1,4.
Abstract
This study aimed to evaluate the effect of shrub encroachment on soil organic carbon (SOC) content at broad scales and its controls. We conducted a meta-analysis using paired control data of shrub-encroached grassland (SEG) vs. non-SEG collected from 142 studies worldwide. SOC contents (0-50 cm) were altered by shrub encroachment, with changes ranging from -50% to + 300%, with an effect size of 0.15 (p < 0.01). The SOC contents increased in semi-arid and humid regions, and showed a greater rate of increase in grassland encroached by leguminous shrubs than by non-legumes. The SOC content decreased in silty and clay soils but increased in sand, sandy loam and sandy clay loam. The SOC content increment was significantly positively correlated with precipitation and temperature as well as with soil bulk density but significantly negatively correlated with soil total nitrogen. We conclude the main effects of shrub encroachment would be to increase topsoil organic carbon content. As structural equation model revealed, soils properties seem to be the primary factors responsible for the extent of the changes, coarse textured soils having a greater capacity than fine textured soils to increase the SOC content. This increased effect appears to be secondarily enhanced by climate and plant elements.Entities:
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Year: 2016 PMID: 27388145 PMCID: PMC4937411 DOI: 10.1038/srep28974
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Estimates of the effect size (log response ratios) of SOC content influenced by shrub encroachment for different variable classes across climate class, shrub type, soil texture and soil depth with 95% confidence intervals (CI).
| Variable class | Effect size | CI | ||
|---|---|---|---|---|
| Arid | 20 | 0.029 | −0.048~0.11 | 0.45 |
| Semi-arid | 109 | 0.16 | 0.15~0.34 | <0.0001 |
| Dry sub-humid | 3 | −0.0062 | −0.18~0.15 | 0.94 |
| Humid | 11 | 0.45 | 0.34~0.54 | <0.0001 |
| 6 | −0.40 | −0.69~−0.14 | <0.0001 | |
| 3 | 1.09 | 0.67~1.46 | <0.0001 | |
| 7 | −0.024 | −0.27~0.24 | 0.67 | |
| 5 | -0.26 | −0.54~0.06 | 0.0011 | |
| 2 | −0.49 | −0.95~−0.02 | <0.0001 | |
| 1 | 0.0028 | −0.66~0.66 | 0.98 | |
| 1 | −0.045 | −0.71~0.62 | 0.72 | |
| 9 | 0.16 | 0.11~0.58 | 0.00081 | |
| 18 | 0.059 | −0.15~0.22 | 0.12 | |
| 1 | −0.11 | −0.78~0.56 | 0.43 | |
| 3 | 1.22 | 1.16~1.86 | <0.0001 | |
| 33 | 0.61 | 0.49~0.73 | <0.0001 | |
| 37 | 0.037 | 0.06~0.31 | 0.23 | |
| 5 | 0.21 | −0.08~0.53 | 0.035 | |
| 11 | −0.12 | −0.32~0.10 | 0.024 | |
| Leguminosae | 84 | 0.21 | 0.17~0.27 | <0.0001 |
| Non-Leguminosae | 58 | 0.081 | 0.033~0.13 | 0.0008 |
| Clay loam | 3 | −0.045 | −0.29~0.21 | 0.72 |
| Loam | 33 | 0.075 | −0.03~0.15 | 0.058 |
| Sand | 4 | 0.42 | 0.27~0.58 | <0.0001 |
| Sandy clay loam | 25 | 0.59 | 0.50~0.67 | <0.0001 |
| Silt | 5 | 0.034 | −0.095~0.16 | 0.61 |
| Silty clay | 4 | −0.44 | −0.59~−0.30 | <0.0001 |
| Silty clay loam | 3 | 0.13 | −0.18~0.44 | 0.40 |
| Silty loam | 4 | 0.22 | −0.042~0.47 | 0.098 |
| Sandy loam | 36 | 0.19 | 0.13~0.24 | <0.0001 |
| 0–15 cm | 76 | 0.20 | 0.15~0.24 | 0.0023 |
| 15–30 cm | 66 | 0.073 | 0.026~0.16 | <0.0001 |
| 142 | 0.15 | 0.11~0.18 | <0.0001 | |
The number of observations (n) and significance levels (p) are reported for each variable.
Figure 1The relationships between the percentage of SOC content change (%) and the mean annual precipitation (MAP, a) and mean annual temperature (MAT, b).
Figure 2The relationship between the percentage of SOC content change (%) and the soil total nitrogen (STN) content (%).
Figure 3The relationship between the percentage of SOC content change (%) and the soil bulk density (Mg m−3).
Figure 4A structural equation model (SEM) showing the multivariate effects on SOC changes through hypothetical pathways of abiotic factors (climate and soil texture) and biotic factors (shrub types).
The solid and dashed arrows indicate significant (p < 0.05) and non-significant (p > 0.05) effects, respectively; values associated with the arrows represent standardized path coefficients. R2 values associated with the response variables indicate the proportion of variation explained by relationships with other variables. The exogenous unobserved variables e1 and e2 account for the unexplained error in the estimation of shrub types and SOC change, respectively.