2023, Vol. 44
2. 中国科学院南京土壤研究所江苏常熟农田生态系统国家野外科学观测研究站, 南京 210008
, YANG Shi-long1 , WENG Xi-zhe1 , XU Ling-ying2 , LIU Xue-jian1 , DU Yun-tian1 , ZHANG Xue-chen1 , ZHENG Wei1 , ZHAI Bing-nian1 , WANG Zhao-hui1 , LI Zi-yan1
2. State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
土壤有机碳(soil organic carbon, SOC)储量约占陆地生态系统碳库的2/3, 是植被和大气碳储量的2~3倍[1, 2].因此, 土壤碳库的微小变化会对全球碳平衡产生重要影响[3].SOC作为表征土壤肥力的核心, 提高SOC储量已成为保障陆地生态系统可持续发展的重要目标[4].水蚀环境是指因降雨或地表径流造成土壤流失而形成的特有区域, 由自然水蚀环境和人文侵蚀环境组成的复合型环境系统[5, 6].水蚀将SOC从侵蚀源地随泥沙一起分离, 搬运至沉积环境中, 同时在分离和搬运过程中将团聚体破碎[7, 8].近年来, 农业用地过度侵占加剧水蚀过程, 严重降低了土壤固碳效应, 温室气体排放显著增加[9].水蚀已成为世界最严重的环境问题之一[10], 全球每年因水蚀造成的土地退化面积高达7.51亿hm2, SOC储量降低了4~6 Pg·a-1, 经济损失高达4 000亿美元[11, 12].
为解决这一问题, 政府制定一系列生态保护措施, 其中以退耕还林和退耕还草为代表的植被恢复措施广受关注.然而, 退耕还林和还草对于SOC累积的作用效果仍存在争议.如Liu等[13]在黄土高原水蚀环境的退耕还林还草研究中发现, 相较于退耕还林, 退耕还草下SOC增加更显著.而邓志豪[14]等在桂西北喀斯特区的研究结果则表明, 退耕还林更有利于提高SOC储量.Vesterdal等[15]研究认为, 长期(30 a)退耕还林并不会显著提高SOC库储量, 且SOC的变化是由于土壤剖面碳的重分配.显然, 以上结果差异与实验条件和外在环境等诸多因素密切相关, 但关键影响因素仍不清晰, 限制了对植被恢复土壤固碳策略方面的科学认识, 有待进一步研究.
土壤团聚体是土壤结构的基本单元, 土壤团聚体的团聚作用也是土壤有机碳固持的核心机制, 其大小和稳定性差异会造成微生物活动和土壤养分循环过程的改变, 进而影响土壤有机碳周转[16, 17].SOC是大团聚体形成的重要胶结物质[18], 大团聚体比例越高, 土壤肥力往往越好.有研究认为, 土壤大团聚体的SOC多以活性碳库为主, 对外源碳库的改变(如植被类型转变)更为敏感, 而微团聚体主要以闭蓄态的稳定有机碳库为主, 对人为措施的响应相对滞后[19], 因此明确土壤团聚体分布可以很好地解释植被恢复策略的土壤固碳效应差异[20].此外, 土壤的团聚体稳定性也与其抗侵蚀性密切相关, 被认为是研究侵蚀敏感性的有效指标[21].故而, 明确土壤有机碳和团聚体稳定性的变化及其两者联系对侵蚀区制定合适的“碳中和”的管理策略至关重要.
目前, 关于水蚀环境植被恢复策略对SOC储量和土壤团聚体稳定性影响的整合分析鲜见报道.基于此, 本文运用Meta分析方法以农田(或裸地)作为对照, 量化植被恢复政策对土壤有机碳储量和土壤团聚体稳定性的影响效果及其关键影响因素, 并探究二者间的内在联系, 旨在为退化生态系统的恢复与重建提供理论参考.
1 材料与方法 1.1 数据收集和筛选本文通过Web of Science (WOS)、中国知网(CNKI) 和谷歌学术(Google Scholar)等数据库对相关论文进行搜索.以“土地利用(land use)” “土地利用变化(land use change)” “土地利用方式(land use pattern)” “植被恢复(vegetation restoration)” “土壤理化性质(soil physical and chemical properties)” “土壤团聚体(soil aggregation)” “平均重量直径(mean weight diameter或MWD)” “平均几何直径(geometric mean diameter或GMD)” “土壤养分(soil nutrient)”和“土壤有机碳(soil organic carbon)”等关键词为搜索策略.为剔除不合格文献, 避免发表偏移, 保证每一项研究的完整性和科学性, 本文不仅尽最大可能收集与研究主题相关的文献, 并收集所得文献的参考文献和同一作者或研究团队的其它相关文献.
本文设置了以下筛选标准：①通过充分考察文献的研究背景或相同研究地的相关文献, 确定文献研究的实验小区属于水蚀区, 且保证每项研究独立; ②文献中必须具有对照组(农田或裸地)和最少一个实验组(植被恢复), 植被类型包括：草地, 林地; ③文献需有最少一个研究指标(土壤团聚体指标、土壤有机碳含量).④文献必须明确采样深度.如果文献只提供有机质含量, 则用1.724为系数进行有机碳含量换算[22]; ⑤如果数据以图表形式汇报, 则运用GetData Graph Digitize(Version 2.25, Russian Federation).
本文进行Meta分析的数据包含以下指标：①研究地点(经度和纬度); ②气候[年平均降水量(MAP)和年平均气温(MAT)]; ③土地利用类型(农田、裸地、草地、林地)、植被覆盖度和植被恢复年限; ④土壤砂、粉、黏粒含量、土壤容重和土壤深度; ⑤SOC储量、土壤团聚体[平均重量直径(MWD)、平均几何直径(GMD)]和团聚体测定方法.最终, 本文共纳入91篇同行评议论文, 包括717组SOC储量数据、411组MWD数据和337组GMD数据.图 1显示了研究地点的地理分布.
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图 1 研究样点分布示意 Fig. 1 Location of the study sites in this Meta-analysis |
本研究应用失安全数(Fail-safe number)和Egger's法对数据偏移进行量化[23, 24].若失安全数大于临界值(5n+10, n为文献收集到的研究组数)或Egger's回归结果PB大于0.05则代表数据不存在发表偏移.
土壤容重是计算SOC储量的必要指标之一, 但有研究未报告土壤容重数据.有研究表明, SOC和容重(BD)有着密切联系[25, 26].Hiederer等[27]研究表明, 在估算全球SOC储量时, SOC含量是估算BD的唯一参数.因此, 本文根据Wu等[28]的方法来估算土壤容重：
当ω(SOC) < 60 g·kg-1时:
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(1) |
当ω(SOC)>60g·kg-1时:
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(2) |
式中, BD为土壤容重, g·cm-3; ContentSOC为SOC含量, g·kg-1.
当有研究报告SOC含量的土壤深度分类不一致时, 需将不同土层深度分类的SOC含量调整为相同深度.因此, 本研究根据Shi等[29]的方法进行修正：
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(3) |
式中, ContentSOC-H为调整土壤深度后的SOC含量, g·kg-1; H为调整后的土壤深度, cm; ContentSOC-h为文献中原始土层深度的SOC含量, g·kg-1; h为文献中原始的土层深度, cm.
大部分SOC数据以含量形式给出, 只有少数文献报告了不同土层的SOC储量数据. 因此, SOC储量的计算公式如下：
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(4) |
式中, StockSOC为SOC储量, Mg·hm-2; H为土壤深度, cm; ContentSOC为SOC含量, g·kg-1.
如果文献没有提供数据的标准差(S)和标准误差(Se), 则用数据的1/10代替[30, 31].如果文献提供的数据包括标准误差(Se) 和重复次数(n), 则使用以下等式计算标准差(S)：
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(5) |
如果文献没有直接提供MWD或GMD, 只提供了各粒级分组和粒级分组的相对质量分数, 则分别使用以下等式计算MWD和GMD：
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(6) |
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(7) |
式中, d为各分组粒级的平均直径, mm; m为各粒级的质量分数, %.
本文运用自然对数转换响应比(RR)反映不同植被类型对SOC储量、MWD、GMD和WSA含量的影响, 计算公式如下[32]：
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(8) |
式中, Xn1和Xn2分别表示处理组和对照组的SOC储量、MWD、GMD和WSA含量的平均值. X的方差(Var) 计算如下：
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(9) |
式中, a1、a2、S1和S2分别表示处理组和对照组的重复次数和标准差.
本文运用随机效应模型的限制最大似然法(REML) 来计算效应值[33, 34].加权因子(W)、加权响应比(RR++)、RR++的标准误差(SE)和RR++的95%置信区间(CI) 计算如下[35, 36]：
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(10) |
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(11) |
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(12) |
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(13) |
为更直观地反映不同植被类型对SOC储量、MWD和GMD的影响, 将效应值转换为变量(Z)的百分数变化, 由下式计算[31]：
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(14) |
在统计分析之前对所有变量进行了异质性检验.为筛选异质性影响因素, 参考文献[37]进行计算.同时, 通过建立多个解释变量与结果变量之间的混合效应模型, 并根据小样本赤池信息量(AICC)的最低模型结果, 确定最优模型, 计算最优模型中各个影响因素的权重, 所有最优模型子集中每个因素的权重加权之和被确定为每个因素的相对重要性, 寻求最优模型中因素的重要性程度, 因素相对重要性＞0.8表示重要[37], 筛选导致异质性的重要影响因素.
所有数据分析和绘图均用R语言4.0(http://cran.r-project.org/)完成.
1.3 数据分类将采集数据进行统计及分类, 分析因素包括：土壤深度、土壤黏粒含量、年平均降雨量、年平均气温、恢复年份和植被覆盖率, 具体各数据分类如表 1所示.
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表 1 数据分组情况1) Table 1 Data grouping |
2 结果与分析 2.1 植被恢复对SOC储量、MWD和GMD的发表性偏倚检验
植被恢复下SOC储量、MWD和GMD的发表偏倚检验结果如表 2所示.结果表明, 各研究指标的失安全数均高于临界值, 且Egger's回归结果值均大于0.05.这表明研究指标结论可靠, 不存在发表偏倚.
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表 2 植被恢复对SOC储量、MWD和GMD的偏倚检验 Table 2 Publication bias test of vegetation restoration on SOC stock, MWD, and GMD |
2.2 植被恢复对SOC储量和土壤团聚体的影响
总体来看, 相比农田或裸地, 植被恢复可显著提高SOC储量、MWD和GMD(P < 0.05), 分别提高了33.32%、38.50%和34.11%.图 2(a)表明, 草地恢复和林地恢复分别显著提高SOC储量的33.22%和33.24%, 且林地与草地无显著性差异.图 2(b)和2(c)表明, 植被恢复可显著提高MWD和GMD, 草地恢复分别提高了52.12%和49.18%, 林地恢复分别提高了26.15%和22.45%, 且植被类型间均无显著差异.
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误差线表示95% 的置信区间; 括号中数值表示研究变量的样本量 图 2 植被恢复对SOC储量、MWD和GMD的影响 Fig. 2 Effects of vegetation restoration on SOC stocks, MWD, and GMD |
数据按年均气温、年降水量、植被覆盖度、恢复年限、土壤黏粒含量、土层深度和测定方法, 运用Meta回归分析分别对土壤SOC储量、MWD和GMD进行多因素分析, 寻求最优模型中影响因素重要性(图 3).图 3(a)表明, 各因素均是植被恢复下SOC储量的主要影响因子.图 3(b)和3(c)表明, 植被恢复下MWD和GMD主要影响因素是植被覆盖度和土壤黏粒含量.
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(a)SOC储量, (b)MWD, (c)GWD; 红色虚线表示相对重要线, 以估计相对重要影响因素 图 3 SOC储量、MWD和GMD对植被恢复响应相关变量的相对重要性 Fig. 3 Relative importance of variables for the response of SOC stock, MWD, and GMD to vegetation restoration |
图 4(a)表明, 林地恢复对SOC储量的正向效应随恢复年份增加而提高, 而草地在不同恢复年限间的固碳效应无显著变化.图 4(b)表明, 林地恢复对SOC储量的正向效应随土壤黏粒含量增加而提高, 在低土壤黏粒含量(< 20%)、中等土壤黏粒含量(20%~32%)和高土壤黏粒含量(>32%)的SOC储量分别显著提高了28.00%、32.60%和82.78%.草地恢复在中等土壤黏粒含量(20%~32%)和高土壤黏粒含量(>32%)下可显著提高SOC储量, 分别提高了41.18%和19.16%, 而在低土壤黏粒含量下的SOC储量无显著提高.植被恢复对SOC储量的正向效应随植被覆盖率增加而提高, 且草地恢复在不同覆盖率之间有显著差异[图 4(c)].植被覆盖率≤50%时, 林地显著提高了SOC储量44.87%, 而草地无显著变化.植被覆盖率>50%时, 林地和草地可显著提高SOC储量, 分别提高81.23%和87.46%.总体而言, 在各类气候因素条件下, 植被恢复对SOC储量都有积极影响, 但不同植被恢复类型的固碳效应变化规律不同[图 4(d)和4(e)].具体而言, 草地恢复对SOC储量的正向效应随MAP或MAT增加而分别提高或降低, 而林地均为先降低后升高, 且在气候条件适中(500~800 mm, 10~15℃)条件下的正向作用最弱.图 4(f)表明, 草地可显著提高0~20 cm和20~40 cm土层的SOC储量, 分别提高47.76%和21.60%, 而对40~60 cm土层的SOC储量无显著影响.林地显著提高0~60 cm的各土层SOC储量, 特别是0~20 cm和40~60 cm的SOC储量, 分别提高54.25%和29.89%.
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误差线表示95%的置信区间, 水平虚线表示无效线, 误差线与无效线没有交点时差异显著(P＜0.05); 括号中数值表示研究变量的样本量 图 4 不同因素对植被恢复下SOC储量的影响 Fig. 4 Effects of different factors on SOC stocks under vegetation restoration |
图 5(a)和5(b)表明, 植被恢复在各土壤黏粒含量下均可显著提高MWD和GMD, 且土壤黏粒含量为20%~32%下更为显著.图 5(c)和5(d)表明, 植被恢复对土壤MWD和GMD的影响效应随植被覆盖率增加而提高.在植被覆盖率≤50%时, 植被恢复下的MWD和GMD无显著变化.在植被覆盖率>50%时, 植被恢复显著提高MWD和GMD, 草地分别提高了78.91%和78.48%, 林地分别提高了23.65%和18.21%.
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误差线表示95%的置信区间, 水平虚线表示无效线, 误差线与无效线没有交点时差异显著(P＜0.05); 括号中数值表示研究变量的样本量 图 5 不同因素对植被恢复下MWD和GMD的影响 Fig. 5 Effects of different factors on MWD and GMD under vegetation restoration |
Meta回归结果表明, MWD和GMD效应值随SOC储量效应值提高显著增长(P < 0.01), SOC储量增长能分别解释25%和24%的MWD和GMD效应值变异[图 6(a)和6(b)].
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图 6 SOC效应值与MWD和GMD效应值的Meta回归分析 Fig. 6 Meta-regression analysis between effect size of SOC and effect size of MWD and GMD |
与农田(或裸地)相比, 植被恢复可显著提高土壤侵蚀区的SOC储量.这种差异可归结为碳输入和输出的通量大小不同.首先, 耕作等在内的农业管理措施都会加剧土壤侵蚀过程, 破坏土壤物理结构, 提高土壤碳矿化率[38, 39], 造成碳流失, 而植被恢复可通过减少土壤侵蚀和机械扰动降低碳流失.其次, 农田由于作物收获必然会带走一部分碳, 导致土壤碳输入减少[40, 41], 而草地和林地的生物量会通过植被残体、根系和枯枝落叶归于土壤, 进而减少土壤碳损失.最后, 微生物群落差异也是植被恢复固碳的重要原因.一般而言, 真菌是外源碳库向稳定SOC转化的重要通道[42].有研究表明, 植被恢复可显著提高真菌物种总数、Shannon指数和真菌/细菌残体比(不同生态系统的大小顺序为：林地>草地>农田), 且草地恢复显著提高子囊菌门(Ascomycota)丰度, 林地恢复显著提高担子菌门(Basidiomycota)[43, 44]丰度, 子囊菌门(Ascomycota)和担子菌门(Basidiomycota)均是植被残体的主要分解者[45, 46], 这两种真菌门类丰度的提高促进了SOC结构趋于稳定, 并提高了土壤固碳效率[42].
植被恢复策略的土壤固碳效应大小受不同自然因素的影响差异很大, 各要素的综合评判对科学预测生态系统的碳循环过程有着重要作用[47].多因素Meta回归结果表明, 土壤深度、土壤黏粒含量、气候条件、恢复年限和植被覆盖率是影响植被恢复土壤固碳的重要因素.
3.1.1 植被恢复年限对植被恢复下SOC储量影响分析本研究发现, 林地的固碳效应随着恢复年限增长而提高, 这与已有研究的结果一致[48, 49].相比幼林, 恢复年限更长的林地有更多的凋落物和根系分泌物, 增加了C输入量.此外, 由于林地富含木质素或纤维素的部分凋落物分解速率慢, 导致幼林期的固碳效应相对较低.然而, 不同恢复年限间的草地固碳效应无显著变化, 其原因可能是草地根系具有比林地更高的生物量和更快的周转速率, 从而促进了微生物的生长发育并提高了植被残体的分解速率和微生物残体累积量[50], 使得草地恢复初期(< 10 a)的固碳效应显著增加.同时, 受草地净初级生产力的限制, 恢复年限更长的草地土壤SOC储量无显著增长[51].因此, 当短期最大限度提高SOC储量是主要目标时, 建议以草地恢复为主要策略.
3.1.2 土壤黏粒含量对植被恢复下SOC储量影响分析土壤黏粒含量也是影响植被恢复固碳效率的重要因素.本研究发现, 不同植被类型在各黏粒含量下的变化规律不同.中等黏粒含量(20%~32%)下, 退耕还草对土壤SOC储量的正向效应更显著.这一结果可能是因为高黏度土壤保水保肥性好, 而过高的水分条件可能会抑制草本植物的生长, 进而影响固碳.同时, 土壤本身的C水平也会显著影响植物凋落物分解速率[52, 53].Hamer等[54]研究发现, 在SOC含量高的草地土壤下的根系残体分解速率较慢, 所以草本植物无法通过凋落物的快速分解来提高SOC储量.土壤中等黏粒含量条件下常具有适宜的孔隙度, 更有利于草本植物生长, 土壤微生物活性增强, 有机碳周转速率加快, 土壤固碳效率提高[55].然而, 退耕还林对土壤SOC储量的正向效应随黏粒含量(>32%)增加而更显著.这可能是因为林地SOC的主要来源是由枯枝落叶组成的地上凋落物, 导致容易形成一个基本没有土壤矿物质的有机层, 造成缺乏黏粒保护的SOC容易被微生物分解和利用[56, 57], 而黏粒含量(>32%)升高, 土壤颗粒更易与有机化合物相结合形成稳定的有机无机复合体, 有助于提高林地恢复对SOC的固存效应[58, 59].此外, 土壤黏粒含量也显著影响着植被分布、植物生长发育和功能组成等因素[60], 各要素间存在复杂的混杂效应, 后期仍需进一步分析.
3.1.3 植被覆盖率对植被恢复下SOC储量影响分析植被恢复对SOC储量的正向作用随植被覆盖率增加而增强, 但不同植被覆盖率间无显著差异[图 4(c)], 这与其它研究结果一致[61, 62].Laganière等[58]研究表明, 植被覆盖率对土壤小气候(温度、湿度)和植被凋落物数量有显著影响.植被覆盖度越高, 土壤单位面积的植被残体、根系分泌物、枯枝落叶量越多, 有机质输入量更高.同时, 适宜的土壤温度和湿度促进了微生物的生长代谢, 提高了植被残体的分解速率, 土壤固碳效率提高.其次, 植被覆盖率越高, 植被的减流减沙效果越显著, C流失越少[63].因此, 当SOC固存是植被恢复策略的主要目标之一时, 建议提高初始植被覆盖率, 以最大限度地快速提高SOC储量.
3.1.4 气候条件对植被恢复下SOC储量影响分析气候条件也会显著影响植被恢复的土壤固碳效应.总体来看, 不同气候条件下的林地恢复和草地恢复对SOC储量都有积极作用.相比林地, 草地下的SOC对MAT和MAP变化更敏感.具体而言, 草地恢复对SOC储量的正向效应随MAP升高而增加, 随MAT升高而降低, 这与许多研究结果一致[64, 65].MAP的升高有助于提高草地净初级生产力和降低C的分解速率[63], 而高温会限制植物的生长发育, 加快微生物的呼吸速率, 从而提高土壤C的矿化速率[66, 67].此外, 微生物残体(尤其真菌)也是SOC的主要来源之一, 草地在高MAT下的土壤真菌和细菌残体累积量显著小于低MAT累积量, 造成土壤碳输入量减少[44]; 然而, 林地的SOC储量在干旱或炎热(MAP<500 mm, MAT>15℃)气候条件下依然显著提高, 这与Loganière等[58]研究结果一致, 原因可归结为树木具有更深的根系和密集的林冠层, 可减少干旱和高温对林地固碳的负面影响[68, 69].因此, 在干旱寒冷或炎热潮湿条件下进行退耕还林, SOC的长期恢复效应可能更大.
3.1.5 土壤深度对植被恢复下SOC储量影响分析土壤深度是影响植被恢复土壤固碳效应的关键因素之一.显然, 植被恢复更有利于提高表层(0~20 cm)SOC储量, 且林地的固碳效果较草地更为显著[70, 71, 72], 这取决不同植被类型外源碳库输入的差异[71].林地的枯枝落叶等凋落物可能要高于草地的生物量输入, 更有利于提高表层土壤SOC储量.同时, 林下水土流失程度较弱, 地表凋落物较多, 土壤养分流失较少[73, 74].此外, 林地SOC储量在40~60 cm深度显著增加34.38%, 而草地SOC储量正向效应不显著.这可能与草本植物和木本植物的根系深度差异有关.草本植物根系较浅, 而树根可以深达40 cm及以下[67], 因此在40~60 cm深度林地仍可以通过根际分泌物和微生物/生物残体(根系腐烂)实现土壤固碳, 而草地却难以对这一深度的土壤固碳产生影响.
3.2 植被恢复对土壤团聚体稳定性的影响植被恢复可显著提高团聚体稳定性, 改善土壤结构.首先, 植被根系发达, 密集的根系与外部菌丝作为黏结剂可直接和间接驱动团聚体形成[75, 76].此外, 丛枝菌根真菌菌丝及其产生的球囊霉素蛋白作为结合剂是提高土壤颗粒团聚化过程的重要因素, 植被恢复则能显著增加丛枝菌根真菌浓度, 从而利于提高土壤团聚体稳定性[77].第二, 植被恢复下SOC增加可提高土壤团聚体稳定性(图 6).植被恢复可通过提高有机质数量和质量来增强SOC与土壤颗粒的结合以及土壤微生物活性, 进而提高土壤团聚体稳定性[78], 且SOC含量高的土壤内力低, 团聚体具有低湿润性, 减少了团聚体破碎[79]; 第三, 相比农田土壤经常受到机械扰动或土壤侵蚀, 植被永久覆盖可显著减少土壤侵蚀和机械扰动, 有效避免了土壤团聚体的破坏[80].
3.2.1 土壤黏粒含量对植被恢复下MWD和GMD影响分析本研究发现, 植被恢复在土壤黏粒含量为20%~32%的MWD和GMD提升效果更明显, 这与文献[81]的研究结果一致.植被恢复在中等土壤黏粒含量(20%~32%)下SOC储量提升效果最为显著[图 4(b)], 这改善了大团聚体比例, 从而提高了土壤团聚体稳定性[82, 83].其次, 中等黏粒含量土壤具有适中的孔隙度, 植被下的碳周转率和微生物活性高, 促进了水稳性团聚体形成[84].此外, 草地恢复在低土壤黏粒含量(<20%)下对团聚体的正向效应比高黏粒含量(>32%)更显著, 这与Su等[85]研究的结果一致.其原因可归结为草本植物根系更密集和具有更高的生物量, 而农田在高土壤黏粒含量下, 土壤团聚体的稳定性相对较高[86, 87], 造成植被恢复对土壤团聚体的影响很小.这说明, 与高土壤黏粒含量土壤相比, 草地在中低黏粒含量土壤下改善土壤结构的潜力更大.
3.2.2 植被覆盖率对植被恢复下MWD和GMD影响分析植被覆盖度≤50%时, 草地和林地恢复下MWD和GMD均无显著变化; 植被覆盖率>50%时, 草地和林地恢复下MWD和GMD均显著提高[图 5(d)].根据Bissonnais等[88]的研究表明, 土壤侵蚀是土壤团聚体破坏的主要原因, 而植被覆盖度与土壤侵蚀之间存在着阈值现象[89, 90].只有当植被覆盖度>50%, 植被才能有效防治土壤侵蚀[91], 保护土壤团聚体免遭破坏.此外, 高覆盖率植被层可有效阻止雨滴击溅破坏土壤团聚体, 并通过提高SOC含量更好地促进了团聚体的形成和稳定性[图 6(a)和6(b)].
4 结论(1) 在水蚀环境下, 植被恢复可显著提高SOC储量和团聚体稳定性.农业管理(植被恢复年限、植被覆盖率), 气候(年平均降雨量、年平均气温)和土壤(深度、黏粒含量)是影响植被恢复下SOC储量的主要因素; 高覆盖率下植被恢复更有利于显著提高SOC储量, 尤其是0~20 cm土层.中等土壤黏粒含量(20%~32%), MAP>500 mm和MAT < 15℃条件下更易促进草地固碳效应; 林地恢复在高土壤黏粒含量(20%~32%)下的固碳效应更高, 且林地固碳效应对气候条件的自适应性更强, 但可能存在时间的限制性.此外, 土壤黏粒含量和植被覆盖率也是影响植被恢复下土壤团聚体稳定性的主要因素, 且SOC增加可显著提高MWD和GMD.中等黏粒含量(20%~32%)下, 植被恢复对MWD和GMD的正向效应更显著; 且植被恢复对MWD和GMD的正向效应受植被覆盖率的限制.
(2) 综上, 在水蚀环境进行植被恢复是一种可持续提高SOC储量和改善土壤结构的策略.同时, 植被恢复策略应根据土壤和气候条件选择合适的植被类型, 以达到最大生态效益.
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