植物生态学报, 2021, 45(12): 1314-1328 doi: 10.17521/cjpe.2021.0211

研究论文

降雨变化对高寒草甸不同植物功能群凋落物质量及其分解的影响

杨德春, 胡雷, 宋小艳, 王长庭,*

西南民族大学青藏高原研究院, 成都 610041

Effects of changing precipitation on litter quality and decomposition of different plant functional groups in an alpine meadow

YANG De-Chun, HU Lei, SONG Xiao-Yan, WANG Chang-Ting,*

Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu 610041, China

通讯作者: *(wangct@swun.edu.cn)

编委: 刘国方(特邀)

责任编辑: 赵航

收稿日期: 2021-06-3   接受日期: 2021-08-18  

基金资助: 国家自然科学基金(U20A2008)
国家自然科学基金(31870407)
第二次青藏高原综合科学考察研究项目(2019QZKK0302)

Corresponding authors: *(wangct@swun.edu.cn)

Received: 2021-06-3   Accepted: 2021-08-18  

Fund supported: National Natural Science Foundation of China(U20A2008)
National Natural Science Foundation of China(31870407)
Second Tibetan Plateau Scientific Expedition and Research (STEP) Program(2019QZKK0302)

摘要

凋落物分解是生态系统物质循环的重要过程, 探究降雨变化对高寒草甸不同植物功能群凋落物分解的影响, 有助于了解高寒草甸物质循环对降雨变化的响应规律和机制。该研究设置减雨90% (Pr-90)、减雨50% (Pr-50)、减雨30% (Pr-30)、自然降雨(CK)和增雨50% (Pr+50) 5个降雨处理, 采用网袋分解法, 对青藏高原东部高寒草甸的3种植物功能群(禾本科、莎草科、杂类草)及群落凋落物的化学性质、质量损失和养分释放动态进行研究。结果表明: 1)减雨处理(Pr-90、Pr-50和Pr-30)显著增加禾本科凋落物的初始氮(N)含量, 显著降低碳氮比(C:N)和木质素氮比(木质素:N); 增雨处理(Pr+50)显著增加各类型凋落物初始磷(P)含量。2)根据Olson负指数模型拟合, 不同降雨处理下, 杂类草凋落物分解最快, 分解95%的时间为3.49-7.45年; 群落和莎草科次之, 分别为4.07-8.05和4.65-7.74年; 禾本科分解最慢, 为5.84-11.18年。3)极端减雨(Pr-90)抑制各类型凋落物分解, 适度降雨变化(Pr-50、Pr-30和Pr+50)抑制禾本科分解而对莎草科、杂类草和群落无显著影响, 仅增雨(Pr+50)明显促进杂类草分解。4)各类型凋落物C释放在减雨(Pr-90和Pr-30)下受到抑制, 增雨或减雨均促进禾本科N和P释放, 对于莎草科、杂类草和群落凋落物而言, Pr-30促进N释放, Pr-90抑制P释放, Pr+50促进P释放。5)结构方程模型(SEM)表明, 质量和养分残留率受降雨量的直接负效应, 也受凋落物初始C、N、P和木质素、纤维素、半纤维素含量的间接影响。综上所述, 高寒草甸凋落物质量损失及养分释放受凋落物类型和降雨量的共同影响。考虑到禾本科分解最慢且对降雨变化的响应最为敏感, 未来应关注气候变化尤其是极端减雨下禾本科的质量损失及养分释放对高寒草甸有机质输入及C、N、P循环的影响。

关键词: 凋落物分解; 降雨量; 养分释放; 高寒草甸

Abstract

Aims Litter decomposition plays a vital role in material cycling of ecosystems. However, the responses of litter decomposition to changing precipitation in alpine meadows and the mechanisms underlying these responses are still not clear. Thus this study was designed to address the effect of changing precipitation on litter decomposition of different plant functional groups in alpine meadows.

Methods We used the litter bag method to investigate changes of initial nutrient content, mass loss and nutrient release in the litter of three plant functional groups (grass, sedge and forb) and in communities in an alpine meadow of Eastern Qingzang Plateau, in response to five precipitation treatments, including 90%, 50% and 30% decrease (Pr-90, Pr-50, Pr-30), ambient control (CK) and 50% increase (Pr+50).

Important findings The results showed that: 1) Precipitation decrease (Pr-90, Pr-50, Pr-30) significantly increased the initial nitrogen (N) content, carbon (C):N and lignin:N ratios of grass litters, while precipitation increase (Pr+50) significantly increased the initial phosphorus (P) content of all litter types. 2) According to the Olson negative exponential model, under different precipitation, the forbs decomposed the fastest, with the 95% decomposition time of 3.49-7.45 a; the decomposition of the communities and of the sedge species were the second fastest, with the 95% decomposition time of 4.07-8.05 and 4.65-7.74 a, respectively; grasses decomposed most slowly, 5.84-11.18 a. 3) Extreme precipitation decrease (Pr-90) inhibited the decomposition of all litter types, while moderate precipitation change (Pr-50, Pr-30, Pr+50) inhibited the decomposition of grass litter, but had no significant effects on sedge, forb and community litter, only precipitation increase (Pr+50) promoted the decomposition of forb litter. 4) C release was inhibited under precipitation decrease (Pr-90, Pr-30) in all litter types. N and P release of grass litters were promoted under both precipitation increase and decrease. Pr-30 promoted N release, Pr-90 inhibited P release and Pr+50 promoted P release in sedge, forb and community litters. 5) Structural equation models (SEM) showed that the mass and nutrient remaining rate were directly negatively affected by precipitation, and indirectly affected by litter types through initial C, N, P, lignin, cellulose and hemicellulose content. In conclusion, both litter types and precipitation can affect the mass loss and nutrient release of litters in an alpine meadow. Decomposition was slower and the response to precipitation was more sensitive in grass than that in other litter types. In the future, we should pay attention to the effects of mass loss and nutrient release of grass litter under climate change, especially extreme precipitation decrease, on organic matter input and C, N and P cycling in an alpine meadow.

Keywords: litter decomposition; precipitation; nutrient release; alpine meadow

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引用本文

杨德春, 胡雷, 宋小艳, 王长庭. 降雨变化对高寒草甸不同植物功能群凋落物质量及其分解的影响. 植物生态学报, 2021, 45(12): 1314-1328. DOI: 10.17521/cjpe.2021.0211

YANG De-Chun, HU Lei, SONG Xiao-Yan, WANG Chang-Ting. Effects of changing precipitation on litter quality and decomposition of different plant functional groups in an alpine meadow. Chinese Journal of Plant Ecology, 2021, 45(12): 1314-1328. DOI: 10.17521/cjpe.2021.0211

凋落物是生态系统的重要组成成分, 其分解在生态系统物质循环与能量流动中具有重要作用。据统计, 凋落物分解释放的CO2约占全球年碳通量的70%, 是生态系统碳(C)循环中的重要环节(Raich & Schlesinger, 1992)。陆地生态系统中约90%的净初级生产力以凋落物的形式归还给土壤, 因而凋落物是土壤有机质的重要来源(Wardle et al., 2004)。同时, 植物吸收的养分中90%以上的氮(N)、磷(P)和60%以上的其他矿质元素都来自凋落物(Chapin III et al., 2011)。因此, 凋落物是连接地上与地下的重要纽带, 深入研究凋落物分解这一生态过程对于理解陆地生态系统的结构和功能至关重要。

凋落物分解主要包括淋溶、破碎和微生物分解代谢3个过程(Gavazov, 2010), 受到气候条件(Zhang & Wang, 2015)、凋落物类型和质量(Cornwell et al., 2008)、分解者生物量和活性(Xiao et al., 2020)等因素的影响。其中, 降雨是重要的影响因素, 降雨通过影响淋溶作用和物理破碎直接影响分解过程, 也通过调控分解者的群落结构、生物量与活性间接影响凋落物分解(Schimel et al., 2007)。此外, 降雨量还能改变凋落物质量进而调控分解过程, 如García- Palacios等(2016)发现减雨降低凋落物总酚和缩合单宁含量进而促进分解; Austin和Vitousek (2000)发现随降雨量增加, P含量降低, 木质素含量增加, 进而抑制分解。然而由于不同地区气候条件、土壤理化性质、凋落物理化性质、土壤生物的种类和数量的差异(王相娥等, 2009), 目前关于降雨对凋落物分解影响的研究结果之间存在较大差异。如在内蒙古半干旱温带草原和华西雨屏区, 降雨量增加促进凋落物分解(向元彬等, 2017; Yan et al., 2018); 在广西南亚热带林地, 降雨变化并不影响凋落物分解(舒韦维等, 2020); 而在长白山森林生态系统, 降雨量增加甚至抑制凋落物分解(李雪峰等, 2007)。

青藏高原平均海拔4 000 m以上, 被称为“世界第三极”, 其脆弱的生态系统对气候变化响应敏感且强烈, 是生态学及其相关科学的重点研究区域之一(姚檀栋和朱立平, 2006)。基于青藏高原72个气象站点的降水特征分析表明, 1961-2015年青藏高原年降水量、年最大日降水量都在以一定速率显著增加, 且未来在青藏高原不同地区可能出现不同程度的极端降水、强降水和干旱事件(冀钦等, 2018)。降雨变化改变土壤水分和养分状况从而影响凋落物质量(Schuster, 2016), 并改变养分淋溶和微生物活动, 从而影响生态系统物质循环(Bloor & Bardgett, 2012)。然而, 目前针对青藏高原凋落物分解的研究主要集中在对温度(Xu et al., 2010; Duan et al., 2013)、施肥(Zhu et al., 2016)和放牧(Sun et al., 2018)等的响应, 以及物种间分解速率的差异(Zheng et al., 2021), 而在影响凋落物分解的诸多环境因子中, 有关降雨变化对不同植物功能群凋落物分解影响的研究鲜见报道。因此, 本研究选取青藏高原高寒草甸中的3种植物功能群(禾本科、莎草科和杂类草)及群落凋落物作为研究对象, 设置不同降雨处理, 利用网袋分解法进行野外原位控制试验, 对供试凋落物初始化学性质及分解特性进行研究, 旨在探讨降雨变化下: 1)高寒草甸不同植物功能群及群落凋落物化学性质的变化特征; 2)不同功能群及群落凋落物质量损失规律; 3)不同功能群及群落凋落物C、N、P释放动态。通过以上研究, 以期进一步揭示高寒草甸凋落物分解对降雨变化的响应规律和机制, 探究降雨变化对高寒草甸生态系统C、N、P输入的影响。

1 材料和方法

1.1 研究区概况

研究区位于四川省阿坝州红原县西南民族大学青藏高原生态保护与畜牧业高科技创新实践研发基地内, 地处青藏高原东部。地理坐标为32.83° N, 103.59° E, 平均海拔3 500 m。草地类型属于高寒草甸, 气候类型属于寒温带高原季风气候, 年平均气温1.1 ℃, 年降水量860.8 mm, 80%的降水集中在5-9月。植物种类主要包括禾本科的发草(Deschampsia cespitosa)和剪股颖(Agrostis clavata), 莎草科的高山嵩草(Kobresia pygmaea)和四川嵩草(Kobresia setschwanensis), 杂类草中的匙叶银莲花(Anemone trullifolia)、钝苞雪莲(Saussurea nigrescens)和蕨麻(Potentilla anserina)等(Zi et al., 2018)。

1.2 试验设计

于2015年在研究区内选择地势相对一致、地上植被分布均匀的高寒草甸作为试验样地, 并用围栏保护。以研究区所处的红原县1970-2010年降水量减少(Yang et al., 2014)和青藏高原1961-2015年降水量增加(冀钦等, 2018)的趋势为依据, 设置5个降雨处理, 分别是减雨90% (Pr-90), 减雨50% (Pr-50), 减雨30% (Pr-30), 自然降雨(CK)和增雨50% (Pr+50), 每个处理6次重复, 随机区组排列。小区面积2 m × 2 m, 小区四周均使用铝皮深埋到40 cm, 以阻止水分的横向流动。减雨处理使用减雨棚实现, 减雨棚最低处距地面1 m, 以保证近地表空气流通, 最高处为2 m, 以便观测采样。采用均匀放置的面积为小区面积90%、50%和30%的高透光有机玻璃挡水板, 实现Pr-90、Pr-50和Pr-30 3个减雨处理, 其中将Pr-50处理下挡水板截留的自然降雨收集在集雨桶中, 均匀洒在增雨小区, 实现Pr+50的增雨处理。

1.3 试验材料与方法

供试凋落物样品于2017年10月10日进行人工采集。在每个小区中选择两个25 cm × 25 cm具有代表性的小样方, 齐地面全部刈割, 进行全株收割。因为基于单一物种凋落物分解的研究难以反映混合凋落物作为整体进行分解的实际特征(王其兵等, 2000), 而且同一功能群对环境和主要生态系统过程有相似的响应和作用(胡楠等, 2008), 本研究将第一个小样方中的凋落物按功能群进行分类采集, 包括禾本科、莎草科和杂类草(因豆科植物较少, 样品无法进行养分含量测定, 故未单独采集豆科凋落物), 另一个小样方中的所有凋落物不进行分类作为群落凋落物样品。其中禾本科的主要物种为发草和剪股颖, 莎草科的主要物种为矮生嵩草(Kobresia humilis)和双柱头藨草(Trichophorum distigmaticum), 杂类草的主要物种为钝苞雪莲和条叶银莲花(Anemone coelestina var. linearis)。植物群落凋落物中主要的功能群为杂类草, 其在不同降雨处理下占群落凋落物生物量的62.21%-77.19%, 禾本科占11.08%-24.65%, 莎草科占8.59%-19.36%。采集的凋落物按降雨处理和凋落物类型进行标记、分类, 置于室外自然风干。风干后, 分别精确称取禾本科、莎草科、杂类草及群落凋落物各15 g装入孔径为1 mm的尼龙网袋(15 cm × 15 cm), 每个降雨处理下的各类型凋落物分别称取12袋, 共计240袋。各处理下各类型凋落物分别留取3袋, 共计60袋, 用于测定凋落物初始化学性质。每个处理随机选取3个小区进行凋落物分解试验, 于2017年10月15日用铁钉将各类型凋落物袋随机固定在对应降雨处理小区土壤表面, 各类型凋落物在每个对应处理小区中随机放置3袋。分别于2018年5月3日、8月5日、10月15日即分解第200、294、365天进行采样。每次采样, 每个处理下的3个小区中不同类型凋落物各随机采集1袋。

凋落物C含量使用高温外加热重铬酸钾氧化外加热法测定。凋落物经H2SO4-H2O2扩散法消煮后, 使用总有机碳分析仪(TOC-L CPH CN200, Shimadzu, Kyoto, Japan)测定N含量; 使用流动分析仪(Proxima, AMS Alliance, Paris, France)测定P含量(鲁如坤, 1999)。木质素、纤维素、半纤维素含量使用范氏洗涤纤维法进行测定(Van Soest, 1963)。

1.4 数据处理

凋落物质量残留率(MR)计算公式(陈思路等, 2020):

$MR={{M}_{t}}\text{/}{{M}_{0}}\times 100\text{ }\!\!%\!\!\text{ }$

式中, Mtt时刻的凋落物质量(g), M0是凋落物初始质量(g)。

凋落物分解系数用Olson负指数衰减模型(Olson, 1963)进行拟合:

${{M}_{t}}\text{/}{{M}_{0}}={{\text{e}}^{-kt}}$

式中, k是分解系数, t是分解时间(a)。分解50% (t0.5)和95% (t0.95)的时间分别是:

${{t}_{0.5}}=-\text{ln}(1-0.5)\text{/}k$
${{t}_{0.95}}=-\text{ln}(1-0.95)\text{/}k$

养分含量残留率(NR)计算公式:

$NR=({{C}_{t}}\times {{M}_{t}})\text{/}({{C}_{0}}\times {{M}_{0}})\times 100%$

式中, Ctt时刻凋落物养分含量(mg·g-1), C0为初始养分含量(mg·g-1)。

采用SPSS 20.0对凋落物初始化学性质(C、N、P、木质素、纤维素、半纤维素含量、C:N、C:P、N:P、木质素:N)、质量残留率及养分残留率(C、N、P残留率)进行单因素方差分析, 降雨量和凋落物类型对凋落物初始化学性质的影响采用双因素方差分析, 凋落物类型、分解时间和降雨量对质量残留率和养分残留率的影响采用重复测量方差分析, 采用最小显著差数(LSD)法对不同降雨处理间变量的差异进行显著性检验(p < 0.05)。用Origin 2019对凋落物质量残留率随时间的负指数衰减模型和分解速率与降雨量的一元线性回归进行拟合。采用结构方程模型(SEM)分析降雨量和凋落物类型与凋落物初始化学性质以及质量残留率、养分残留率的关系, SEM的计算和建立采用AMOS 23.0。所有图表绘制均在Origin 2019中进行。

2 结果和分析

2.1 降雨变化下不同植物功能群及群落凋落物初始化学性质

在所有凋落物类型中, 初始C含量在各类型凋落物中无明显差异, 而N、P含量在禾本科中最低(图1A-1C)。降雨变化改变了凋落物C、N、P含量, 且影响因凋落物类型而异: 与自然降雨(CK)相比, 增雨或减雨对各类型凋落物C含量均无显著影响; 减雨处理(Pr-90、Pr-50、Pr-30)、Pr-30处理、Pr-50和Pr-30处理分别显著增加禾本科、杂类草和群落凋落物N含量, 而Pr-90显著降低群落N含量(p < 0.05); 增雨(Pr+50)显著增加各类型凋落物P含量, Pr-50、Pr-30均显著增加禾本科和群落凋落物P含量, Pr-50显著增加莎草科P含量。

图1

图1   不同降雨处理下不同功能群及群落凋落物初始化学组成(平均值±标准误, n = 3)。不同小写字母表示不同降雨处理间差异显著(p < 0.05)。CK, 自然降雨; Pr-90, 减雨90%; Pr-50, 减雨50%; Pr-30, 减雨30%; Pr+50, 增雨50%。

Fig. 1   Initial litter chemical composition in different plant functional groups and communities under different precipitation (mean ± SE, n = 3). Different lowercase letters indicate significant differences under different precipitation treatments (p < 0.05). CK, ambient control; Pr-90, 90% decrease of precipitation; Pr-50, 50% decrease of precipitation; Pr-30, 30% decrease of precipitation; Pr+50, 50% increase of precipitation.


在所有凋落物类型中, 木质素含量在莎草科凋落物中最低, 纤维素和半纤维素含量在杂类草和群落凋落物中低于禾本科和莎草科凋落物(图1D-1F)。降雨变化对木质素、纤维素、半纤维素含量的影响较小: 与CK相比, Pr-90和Pr-50显著降低禾本科凋落物木质素含量, Pr-30显著增加莎草科和杂类草凋落物木质素含量(p < 0.05); Pr-50和Pr-30显著降低禾本科凋落物纤维素含量; Pr-90和Pr+50分别显著降低禾本科和杂类草凋落物半纤维素含量。

表1所示, C:N、C:P、木质素:N在禾本科中较其他类型凋落物更高, N:P在各类型凋落物中无明显差异。增雨下各类型凋落物C:P、N:P均显著降低(p < 0.05), 而减雨对计量比的影响在凋落物类型中存在差异。禾本科凋落物在减雨处理下C:N、C:P、N:P和木质素:N显著降低, 仅Pr-90对N:P无显著影响; 莎草科中减雨处理显著降低C:P, Pr-50显著降低N:P, Pr-30显著增加木质素:N; 杂类草凋落物Pr-30下C:N显著降低、木质素:N显著增加; 群落凋落物中Pr-90显著增加C:N, Pr-50显著降低C:P和N:P, Pr-30显著降低C:N和C:P。

表1   不同降雨处理下不同功能群及群落凋落物初始化学计量比(平均值±标准误, n = 3)

Table 1  Initial stoichiometric ratio of litters in different plant functional groups and communities under different precipitation treatments (mean ± SE, n = 3)

凋落物类型 Litter type降雨处理 Precipitation treatment碳氮比 C:N碳磷比 C:P氮磷比 N:P木质素氮比 Lignin:N
禾本科 GrassPr-9039.89 ± 7.83b284.72 ± 5.46b7.29 ± 0.66a4.63 ± 1.14b
Pr-5040.61 ± 5.20b218.11 ± 10.87bc5.40 ± 0.21b4.35 ± 0.32b
Pr-3034.56 ± 11.61b205.99 ± 32.36bc5.05 ± 0.62bc4.96 ± 0.69b
CK59.29 ± 6.13a422.31 ± 31.38a7.13 ± 0.39a8.78 ± 0.79a
Pr+5058.95 ± 5.53a214.73 ± 14.81c3.68 ± 0.37c7.59 ± 1.19a
莎草科 SedgePr-9032.00 ± 7.20a187.68 ± 7.32bc6.02 ± 0.60ab2.10 ± 0.27b
Pr-5029.73 ± 7.44a157.00 ± 12.52cd5.42 ± 0.61bc1.75 ± 0.31b
Pr-3036.08 ± 5.33a203.36 ± 4.81b5.72 ± 0.55abc3.20 ± 0.72a
CK35.10 ± 6.74a262.80 ± 15.30a7.57 ± 0.38a2.01 ± 0.24b
Pr+5037.79 ± 7.89a135.70 ± 12.49d3.76 ± 0.80c2.10 ± 0.39b
杂类草 ForbPr-9032.51 ± 3.28ab196.31 ± 29.32ab5.98 ± 0.62ab3.76 ± 0.68abc
Pr-5034.20 ± 1.58ab184.84 ± 2.23ab5.41 ± 0.14ab4.04 ± 0.21ab
Pr-3029.63 ± 0.79b187.40 ± 3.94ab6.32 ± 0.07a4.48 ± 0.12a
CK35.53 ± 1.09a230.84 ± 8.03a6.50 ± 0.23a3.61 ± 0.30bc
Pr+5032.69 ± 4.11ab153.42 ± 13.25b4.79 ± 0.70b3.18 ± 0.09c
群落 CommunityPr-9038.53 ± 2.91a265.60 ± 16.99a6.90 ± 0.37ab4.12 ± 0.40a
Pr-5029.90 ± 2.54cd177.17 ± 10.97b5.92 ± 0.21b3.16 ± 0.56b
Pr-3026.51 ± 3.14d166.29 ± 16.61bc6.26 ± 0.29ab3.38 ± 0.40ab
CK32.51 ± 1.25bc231.13 ± 2.96a7.12 ± 0.18a3.87 ± 0.16ab
Pr+5034.59 ± 1.49ab128.28 ± 19.92c3.69 ± 0.51c3.94 ± 0.50ab

同列不同小写字母表示差异显著(p < 0.05)。CK, 自然降雨; Pr-90, 减雨90%; Pr-50, 减雨50%; Pr-30, 减雨30%; Pr+50, 增雨50%。

Different lowercase letters in the same column indicate significant differences at p < 0.05. CK, ambient control; Pr-90, 90% decrease of precipitation; Pr-50, 50% decrease of precipitation; Pr-30, 30% decrease of precipitation; Pr+50, 50% increase of precipitation.

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以凋落物类型和降雨量为自变量, 对凋落物初始化学性质进行双因素方差分析(表2)。除初始N:P外, 凋落物类型对其他初始化学性质均有显著影响(p < 0.05); 降雨量对初始N、P、木质素含量和C:N、C:P、N:P有显著影响; 除初始C、P含量和N:P、木质素:N外, 两因素的交互作用对其他初始化学性质均有显著影响。

表2   凋落物类型和降雨量对凋落物初始化学性质的双因素方差分析

Table 2  Two-way ANOVA between initial litter properties and litter types and precipitation treatments (mean ± SE, n = 3)

凋落物化学性质
Litter property
LPrL × Pr
FpFpFp
碳含量
Carbon (C) content
6.7580.0011.3910.2551.4440.187
氮含量
Nitrogen (N) content
20.094<0.0016.986<0.0012.2870.025
磷含量
Phosphorus (P) content
6.7080.00119.042<0.0011.7670.088
木质素含量
Lignin content
86.889<0.0016.828<0.0013.7470.001
纤维素含量
Cellulose content
289.576<0.0011.4830.2253.2270.003
半纤维素含量
Hemicellulose content
575.796<0.0011.9220.1262.2820.025
碳氮比 C:N23.248<0.0016.978<0.0013.4260.002
碳磷比 C:P28.676<0.00138.313<0.0015.335<0.001
氮磷比 N:P0.3720.77325.016<0.0011.3910.210
木质素氮比 Lignin:N6.6480.0011.1190.3611.6040.130

显著影响(p < 0.05)用粗体表示。L, 凋落物类型; Pr, 降雨量。

The significant effect (p < 0.05) is expressed in bold. L, litter type; Pr, precipitation.

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2.2 降雨变化对不同功能群及群落凋落物分解过程质量损失的影响

表3表明, 分解时间、凋落物类型、降雨量及其交互作用对凋落物质量损失均有显著影响(p < 0.05)。凋落物质量残留率随时间逐渐下降, 且前期(0-200 d)下降慢, 中期(201-294 d)快速下降, 后期(295-365 d)下降速度减慢(图2)。分解365 d后, CK下杂类草凋落物分解最快, 群落次之, 莎草科较慢, 禾本科最慢, 质量残留率分别为43.96%、45.01%、53.61%、56.28%。降雨变化对质量损失的影响因凋落物类型而异, 与CK相比, 禾本科中增雨(Pr+50)或减雨(Pr-90、Pr-50、Pr-30)均在中期和后期显著抑制分解(p < 0.01), 365 d后质量残留率分别增加10.75%、19.22%、3.15%、10.76%; 而在莎草科、杂类草和群落凋落物中Pr-90抑制分解, 365 d后质量残留率分别增加12.39%、22.80%、17.32%; 此外, 杂类草凋落物中Pr+50明显促进分解, 且在分解前期影响显著。

表3   凋落物类型、分解时间和降雨量对质量损失和养分释放的重复测量方差分析

Table 3  Repeated measures ANOVA of litter type, decomposition time and precipitation on mass loss and nutrient release

差异来源
Source of
variation
MR (%)RC (%)RN (%)RP (%)
FpFpFpFp
L51.072<0.00123.9660.001138.895<0.00173.247<0.001
T334.324<0.001284.117<0.00149.0100.002239.147<0.001
Pr34.481<0.00160.966<0.001104.726<0.001158.340<0.001
L × T3.5500.0293.5290.0303.4890.0316.8710.002
L × Pr3.6320.0031.9240.08314.058<0.00127.063<0.001
T × Pr7.714<0.0016.3500.0019.822<0.00173.057<0.001
L × T × Pr3.077<0.0011.8550.0343.762<0.0015.484<0.001

显著影响(p < 0.05)用粗体表示。L, 凋落物类型; Pr, 降雨量; T, 分解时间。MR, 质量残留率; RC, 碳残留率; RN, 氮残留率; RP, 磷残留率。

The significant effect (p < 0.05) is expressed in bold. L, litter type; Pr, precipitation; T, decomposition time. MR, mass remaining rate; RC, carbon remaining rate; RN, nitrogen remaining rate; RP, phosphorus remaining rate.

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图2

图2   不同降雨处理下不同功能群及群落凋落物的质量残留率(平均值±标准误, n = 3)。CK, 自然降雨; Pr-90, 减雨90%; Pr-50, 减雨50%; Pr-30, 减雨30%; Pr+50, 增雨50%。**, p < 0.01。

Fig. 2   Mass remaining rate of litters in different plant functional groups and communities under different precipitation treatments (mean ± SE, n = 3). CK, ambient control; Pr-90, 90% decrease of precipitation; Pr-50, 50% decrease of precipitation; Pr-30, 30% decrease of precipitation; Pr+50, 50% increase of precipitation. **, p < 0.01.


2.3 降雨变化对不同功能群及群落凋落物分解过程养分释放的影响

分解时间、凋落物类型和降雨量及其交互作用均对C、N、P释放有显著影响(p < 0.05), 仅凋落物类型和降雨量的交互作用对C残留率无显著影响(表3)。

C在分解过程中主要为直接释放模式, C残留率随时间下降(图3A-3D)。Pr-90和Pr-30抑制C释放, 且影响主要发生在中后期。分解365 d后, CK下C残留率在禾本科中为54.28%, 显著低于Pr-90、Pr-30和Pr+50 (p < 0.05); 在莎草科中为49.96%, 降雨变化与CK相比无显著差异; 在杂类草中为40.30%, Pr-90下C残留率显著高于其他处理; 在群落中为42.46%, 各处理间无显著差异。

图3

图3   不同降雨处理下凋落物碳(C)、氮(N)、磷(P)残留率(平均值±标准误, n = 3)。CK, 自然降雨; Pr-90, 减雨90%; Pr-50, 减雨50%; Pr-30, 减雨30%; Pr+50, 增雨50%。*, p < 0.05; **, p < 0.01。

Fig. 3   Carbon (C), nitrogen (N) and phosphorus (P) remaining rate under different precipitation treatments (mean ± SE, n = 3). CK, ambient control; Pr-90, 90% decrease of precipitation; Pr-50, 50% decrease of precipitation; Pr-30, 30% decrease of precipitation; Pr+50, 50% increase of precipitation. *, p < 0.05; **, p < 0.01.


N在分解各阶段均出现富集, 分解前期禾本科CK和Pr+50、杂类草Pr-50下N率先富集, 中期和后期主要在减雨下出现富集(图3E-3H)。禾本科中增雨或减雨均促进N释放, 且分解各个阶段均存在显著影响, 而莎草科、杂类草和群落凋落物中仅Pr-30促进各类型凋落物N释放。分解365 d后CK下N残留率在禾本科中为95.38%, 显著大于其他处理; 在莎草科和群落凋落物中分别为63.50%、65.53%, 各降雨处理间均无显著差异; 杂类草中为77.41%, 显著大于Pr-30。

P在分解各阶段均出现富集, 分解前期禾本科凋落物Pr-90和CK、群落凋落物Pr-90下P率先富集, 分解中期各类型凋落物在Pr-30下均显著富集(图3I-3L)。增雨或减雨均促进禾本科凋落物P释放, 而莎草科、杂类草和群落凋落物中Pr-90和Pr+50分别抑制和促进P释放, Pr-50也促进莎草科P释放,分解各时期降雨处理间均存在显著差异。分解365 d后CK下P残留率在禾本科中为114.04%, 高于初始含量, 也显著高于其他处理; 莎草科、杂类草和群落中分别为54.01%、44.28%、43.59%, 均显著低于Pr-90, 显著高于Pr+50。

2.4 降雨变化对不同类型凋落物分解速率的影响

负指数衰减模型能较好地预测凋落物分解过程, 且R2的范围为0.888-0.989, 表明拟合方程可以较好地表示每种凋落物的分解速率(表4)。分解系数k越大, 凋落物分解速率越快, 分解50%和95%所需时间越短。各凋落物k差异较大, 为0.268-0.858·a-1。不同降雨处理下禾本科凋落物周转期(t0.95)为5.84- 11.18年, 莎草科为4.65-7.74年, 杂类草为3.49-7.45年, 群落为4.07-8.05年。各类型凋落物周转期均在Pr-90下最长, 禾本科凋落物在CK下最短, 而莎草科、杂类草和群落凋落物在Pr+50下最短。总体来看, 分解最快的是Pr+50下的杂类草凋落物, 周转期为3.492年, 最慢的是Pr-90下的禾本科凋落物, 周转期为11.178年。

表4   不同降雨处理下不同类型凋落物质量残留率随时间的指数回归方程

Table 4  Exponential regression equations between mass remaining rate of different litter types and time under different precipitation treatments

凋落物类型
Litter type
降雨处理
Precipitation treatment
回归方程
Regression equation
R2分解系数
Decomposition coefficient (k)
半分解时间
t0.5 (a)
分解95%时间
t0.95 (a)
禾本科 GrassPr-90y = e-0.268t0.9550.2682.5911.18
Pr-50y = e-0.438t0.9350.4381.586.84
Pr-30y = e-0.373t0.9870.3731.868.03
CKy = e-0.513t0.8980.5131.355.84
Pr+50y = e-0.391t0.9470.3911.777.66
莎草科 SedgePr-90y = e-0.387t0.9890.3871.797.74
Pr-50y = e-0.591t0.9450.5911.175.07
Pr-30y = e-0.581t0.9810.5811.195.16
CKy = e-0.568t0.9390.5681.225.27
Pr+50y = e-0.644t0.9080.6441.084.65
杂类草 ForbPr-90y = e-0.402t0.9580.4021.727.45
Pr-50y = e-0.628t0.9620.6281.104.77
Pr-30y = e-0.668t0.8940.6681.044.49
CKy = e-0.699t0.9330.6990.994.29
Pr+50y = e-0.858t0.9780.8580.813.49
群落 CommunityPr-90y = e-0.372t0.8880.3721.868.05
Pr-50y = e-0.626t0.9480.6261.114.79
Pr-30y = e-0.695t0.9420.6951.004.31
CKy = e-0.710t0.9590.7100.984.22
Pr+50y = e-0.737t0.9450.7370.944.07

CK, 自然降雨; Pr-90, 减雨90%; Pr-50, 减雨50%; Pr-30, 减雨30%; Pr+50, 增雨50%。

CK, ambient control; Pr-90, 90% decrease of precipitation; Pr-50, 50% decrease of precipitation; Pr-30, 30% decrease of precipitation; Pr+50, 50% increase of precipitation. t0.5, time of 50% decomposition; t0.95, time of 95% decomposition.

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相关分析表明, 在莎草科、杂类草和群落凋落物中分解速率与降雨量显著线性正相关(p < 0.05), 而在禾本科中降雨量对分解速率无显著线性相关性(图4)。

图4

图4   不同类型凋落物分解速率与降雨量的线性回归。CK, 自然降雨; Pr-90, 减雨90%; Pr-50, 减雨50%; Pr-30, 减雨30%; Pr+50, 增雨50%。**, p < 0.01; ***, p < 0.001。

Fig. 4   Linear regressions between decomposition rate of different litter types and precipitation treatments. CK, ambient control; Pr-90, 90% decrease of precipitation; Pr-50, 50% decrease of precipitation; Pr-30, 30% decrease of precipitation; Pr+50, 50% increase of precipitation. **, p < 0.01; ***, p < 0.001.


2.5 降雨量与凋落物类型对分解特性的相关性分析

采用因子分析对数据进行降维处理, 降维后凋落物初始元素(C、N、P)含量的第1主成分解释率为55.969%, 难溶性物质(木质素、纤维素、半纤维素)含量的第1主成分解释率为66.673%, 元素残留率(RCRNRP)的第1主成分解释率为67.770%。

构建标准化结构方程模型分析降雨量、凋落物类型、初始元素含量、初始难溶性物质含量含量、质量残留率和养分残留率之间的相互影响关系(图5)。结构方程模型卡方自由度比(CHI/DF) = 0.944, 拟合优势度指数(GFI) = 0.971, 调整拟合优势度指数(AGFI) = 0.900, 近似误差均方根(RMSEA) = 0.000, p = 0.462, 说明该模型能够较好地适配研究数据以及路径分析体系。结果显示, 结构方程模型解释了初始元素含量26%的变化, 初始难溶性物质含量83%的变化, 元素残留率43%的变化, 质量残留率57%的变化。降雨量对质量残留率和养分残留率都有直接的极显著负效应(p < 0.001), 而凋落物类型则通过对初始元素含量的正效应和对初始养分组成的负效应(p < 0.001)间接影响质量残留量和养分残留率。杂类草元素含量较高、难溶性物质含量较低、质量损失和养分释放较快, 而禾本科较低的元素含量和较高的难溶性物质含量使其质量损失和养分释放较慢。

图5

图5   降雨量、凋落物类型、凋落物初始化学性质与凋落物分解特性的结构方程模型。图中线条粗细表示影响效应大小, 实线表示显著路径, 虚线表示不显著路径, 红色表示正效应, 蓝色表示负效应, R2表示模型解释率, 线上的数字表示标准化路径系数。***, p < 0.001。

Fig. 5   Structural equation model between precipitation, litter types, initial chemical properties and litter decomposition characteristics. Line thickness indicates relative effect size. Solid lines indicate significant paths, whereas dotted lines indicate non-significant paths. Red indicates positive effects, while blue indicates negative effects. R2 indicates variation explained, and numbers on lines are standardized path coefficients. ***, p < 0.001.


3 讨论

3.1 降雨变化对凋落物初始化学性质的影响

降雨变化影响土壤理化性质和微生物群落结构, 进而改变植物对养分的吸收利用方式与代谢过程, 并引起凋落物化学性质的变化(Semmartin et al., 2004; Guo et al., 2015)。本研究中, 降雨变化对各类型凋落物的初始C含量均无显著影响, 与He等(2006)草地植物C含量与降雨量无直接相关性的结果一致, 可能是因为C在植物体内主要起骨架作用, 基本不参与生产活动, 变化程度不大。除C含量, 降雨变化对其他初始化学性质均有显著影响。减雨处理显著增加禾本科(Pr-90、Pr-50、Pr-30)、杂类草(Pr-30)和群落凋落物(Pr-50、Pr-30) N含量, 这与丁小慧等(2012)的研究结果一致。一方面, 减雨减少土壤N流失、增加土壤速效N含量, 促进植物对N的吸收, 利于植物N的累积(樊才睿等, 2020); 另一方面, 植物叶片通过功能性状的改变适应环境变化, 减雨处理下, 植物生长受到水分胁迫, 通过增加单位质量叶N含量提高水分利用效率, 从而适应干旱少雨的环境(岳喜元等, 2018; 张治国和魏海霞, 2019)。与N的变化规律不同, 增雨或减雨均使各类型凋落物初始P含量显著增加, 可能是因为减雨阻碍土壤P流失; 而增雨通过增加微生物生物量和活性, 提高土壤微生物生物量P含量, 缩短土壤微生物生物量P周转期, 提高土壤P含量及养分有效性, 促进植物对P的吸收(Zhang et al., 2020; 朱晓亚等, 2020)。

C:N和C:P反映了植物对N、P的利用效率, N:P则反映N、P养分限制状况(Yuan & Chen, 2009)。本研究中, 除CK和Pr+50处理下的禾本科凋落物N含量和C:N, 其余凋落物初始C含量、C:N、C:P均低于全球凋落叶平均水平, 而N、P含量均高于全球平均水平, 说明高寒草甸中植物对N、P的养分利用效率低, 吸收营养过程中对C的同化能力较弱(Vitousek, 1982; Yuan & Chen, 2009)。且减雨处理下的禾本科、Pr-30下的杂类草和群落凋落物C:N都显著降低, 表明减雨降低了N利用效率; 相比之下增雨对各类型凋落物C:N均无显著影响, 表明高寒草甸植物对水分较高的环境有更强的生理生态适应性, 且降雨增加或减少对莎草科C:N均无显著影响, 说明莎草科植物对降雨变化有更强的内稳性(张仁懿等, 2015)。增雨或减雨均显著降低C:P, 反映了降雨变化下植物对P的利用效率下降。增雨使各类型凋落物N:P显著降低, 植物生长在增雨下更易受N限制, 与黄菊莹等(2018)的研究结果相同。

禾本科凋落物木质素含量在减雨处理下降低, 可能因为干旱导致植物体内活性氧产生和降解失衡, 影响木质素生物合成过程(焦敏和申卫军, 2014)。而莎草科和杂类草木质素含量在减雨下增加, 与大多数研究结果(杨予静等, 2018)一致, 干旱胁迫诱导木质素生物合成途径中一些关键基因的表达上调, 导致木质素含量增加(尹能文等, 2017)。此外, 干旱胁迫会抑制编码纤维素和半纤维素基因的表达(Jiang et al., 2012), 因此减雨处理下禾本科纤维素、半纤维素含量降低。但降雨变化如何影响高寒草甸不同植物功能群木质素、纤维素、半纤维素的生物合成过程尚不明确, 有待进一步深入研究以揭示其影响机制。

3.2 降雨量对凋落物质量损失的影响

凋落物分解主要包括破碎、淋溶和微生物分解3个过程, 受到气候条件、凋落物类型、凋落物化学组成、土壤动物和微生物等因素的影响(Gavazov, 2010)。各类型凋落物的分解在不同分解时期总体呈现先慢后快再慢的趋势, 与已有的研究结果(王云霞等, 2020)一致。因为分解前期(0-200 d)凋落物的质量损失主要通过非结构性化合物的淋溶实现(Cotrufo et al., 2015), 而该时期研究区处于季节性冻融期, 降雨量较小, 淋溶作用较弱, 加之气温较低, 不利于微生物生存, 导致分解缓慢。分解中期(201-294 d)研究区处于夏季, 雨热同期, 气温升高, 降雨量增加, 可能通过增强淋溶作用加速凋落物的分解, 也可能通过良好的水热条件增加微生物的生物量及活性从而加速凋落物的分解, 并且在分解前期冻融作用使凋落物物理结构破碎, 利于可溶性化合物的淋溶, 也有利于分解者接触, 加速凋落物的分解(邓仁菊等, 2009; 周晓庆等, 2011)。分解后期(295-365 d), 凋落物中易分解成分减少, 气候对分解的影响减弱, 木质素、纤维素、半纤维素等难分解物质的积累阻碍了分解(Du et al., 2020)。

各植物功能群凋落物中, 杂类草分解最快, 禾本科分解最慢, 与Cornwell等(2008)的结果一致。一方面是因为分解快慢与凋落物基质质量有关, 高质量的凋落物通常具有较高的N、P含量和较低的木质素、纤维素、半纤维素含量、C:N、木质素:N, 分解也较快(Zhu et al., 2016; Wang et al., 2017); 本研究中杂类草纤维素和半纤维素含量较低, 易于分解。另一方面分解快慢与功能群的物理性质有关, 禾本科和莎草科的比叶面积较低, 叶片较厚, 角质类物质较多, 不利于降雨淋溶、土壤动物破碎和菌丝入侵, 而杂类草较大的比叶面积利于微生物定居而分解较快(严海元等, 2010; 石明明等, 2017)。群落水平上, 凋落物分解速率介于杂类草和莎草科之间, 明显快于禾本科, 这可能是因为群落中杂类草生物量比例较大, 化学性质也与杂类草相似, 纤维素和半纤维素含量较低, 因而分解较快。

凋落物分解在不同降雨幅度下存在明显差异。降雨变化改变淋溶、破碎过程直接影响分解, 也通过改变微生物群落组成、生物量、酶活性和凋落物基质质量间接影响分解(Austin & Vitousek, 2000; Schimel et al., 2007)。Pr-90下淋溶作用弱, 且不利的水分条件抑制了微生物的生存繁殖与活性, 也减少了线虫等小型土壤动物的丰富度和活性, 抑制凋落物分解(Salamanca et al., 2003; Wang et al., 2021); 尤其在中期, 研究区处于雨季, Pr-90的抑制作用更为显著。增雨明显促进杂类草凋落物分解, 一方面是因为杂类草纤维素、半纤维素含量低, 另一方面增雨显著增加杂类草P含量, 降低半纤维素含量, 其分解更易受降雨增加的影响。除增雨促进杂类草凋落物分解, 适度降雨变化对莎草科、杂类草和群落凋落物分解无显著影响, 与魏晴等(2013)在高寒矮嵩草草甸的研究结果一致, 而在荒漠草原增雨30%促进分解、减雨30%抑制分解(霍利霞等, 2019), 这可能与研究区水分状况有关, 本研究区属高寒草甸, 降雨充沛, 适度降雨变化并不显著影响分解。适度降雨变化却抑制禾本科凋落物分解, 可能与其较低的N、P含量和较高的木质素、纤维素、半纤维素含量有关, 研究表明不稳定化合物与难分解物质比例越小, 凋落物分解对降雨的敏感性越高(Suseela et al., 2013), 因此适度减雨(Pr-50、Pr-30)下禾本科分解更加敏感, 受到抑制; 此外增雨也抑制禾本科分解, 可能是因为其含量较高的木质素由好氧微生物分解, 增雨不利于好氧微生物的生存, 从而抑制分解(王新源等, 2013)。这些结果表明, 降雨变化对凋落物分解的影响强弱受降雨变化幅度、生态系统水分状况、凋落物类型及化学性质的共同影响。

3.3 降雨量对凋落物养分释放的影响

本研究中C总体表现为直接释放, 与凋落物质量残留率变化规律一致。Pr-90和Pr-30显著影响C释放, 而其他处理对C释放无显著影响。Pr-90在禾本科凋落物分解中后期、莎草科和群落凋落物分解中期以及杂类草凋落物分解各个时期均显著抑制C释放, 这是因为Pr-90抑制了可溶性有机质与非结构性碳水化合物的淋溶与微生物利用(谷利茶等, 2017)。Pr-30抑制了禾本科凋落物中后期、莎草科凋落物中期、杂类草凋落物前中期的C释放, 是因为这3种类型凋落物在Pr-30处理下木质素含量较高, 不利于降雨淋溶。

N则在分解过程中出现明显的富集现象。分解前期, CK和Pr+50处理下的禾本科凋落物首先发生N的显著富集, 这与其更低的初始N含量和更高的初始C:N有关。有研究表明, 凋落物初始N含量与凋落物N固持或释放的格局密切相关, 凋落物初始N含量越低越容易发生富集(Parton et al., 2007); 并且凋落物中C:N大于30时, 微生物得不到足够的养分维持自身生长, 会从周围环境中固持N (Vigil & Kisse, 1991)。由于减雨处理显著增加了禾本科凋落物的初始N含量、显著降低了禾本科凋落物的初始C:N, 使N释放过程发生显著改变。各类型凋落物N的富集主要发生在分解中后期, 是因为前期研究区气候寒旱, 中后期水热条件得到改善, 微生物大量定殖, 而凋落物中的N不足以满足微生物的需求, 促使微生物从环境中固持N (王云霞等, 2020)。除了影响N释放模式, 降雨量变化也影响N残留率, 且与C残留率相似, 影响主要发生在减雨处理下。减雨处理在禾本科分解的各阶段均显著促进N释放, Pr-30显著促进了杂类草分解前期和后期N释放, 这皆与CK下初始N含量显著高于其他处理有关, 初始N含量高的凋落物更倾向于释放N (李巧玲和曾辉, 2017)。

P在分解过程也出现明显的富集现象。其中, Pr-90、CK下的禾本科和Pr-90下的群落凋落物P率先富集, 是因为凋落物初始P含量和C:P是影响P释放模式的重要因素。与N一样, P也是微生物不可或缺的营养元素, 初始P含量低时微生物将从环境中固持P以满足自身需求, 导致P富集(宋豪威等, 2021); 且Cromank和Monk (1975)将C:P为240作为分解过程中P富集的临界值。本研究中Pr-90、CK下的禾本科和Pr-90下的群落凋落物初始P含量较低且C:P高于240, 故在分解初期首先发生P的富集。分解中期, 各类型凋落物P在Pr-30下均显著富集, 这可能与Pr-30处理下各类型凋落物较高的初始木质素含量、C:N、木质素:N有关。P主要分布在难降解物质中, 并与木质素和纤维素结合, 形成难分解的复合物, 使P富集(Suzuki et al., 2001; 刘尉等, 2017)。马志良等(2015)的研究也指出, 较高的初始木质素含量、C:N和木质素:N在雨季前期引起P的富集, 在雨季后期引起P的释放。莎草科、杂类草和群落凋落物中Pr-90抑制P释放, Pr+50促进P释放, 是因为Pr-90下P淋溶减弱, Pr+50下淋溶增强且初始P含量显著增加、C:P降低, 较高的P含量和较低的C:P利于P释放(Moore et al., 2011)。禾本科中增雨或减雨均促进P释放, 这可能也与其增雨或减雨下较高的P含量和显著降低的C:P有关。

淋溶的直接作用与植物功能群及群落凋落物基质质量的间接作用, 影响了高寒草甸有机质输入及C、N、P循环。但整体来看, Pr-50到Pr+50范围内的降雨变化对分解的影响较小, Pr-90对凋落物质量损失和养分释放影响较大, 且禾本科凋落物基质质量、质量损失及养分释放对降雨变化更加敏感。已有研究表明, 不同物种凋落物在分解过程中可能存在混合效应, 也可能正负效应彼此平衡, 导致凋落物混合后分解特征发生改变(李宜浓等, 2016); 且降雨变化可能改变高寒草甸物种多样性(武建双等, 2012)。因此分析物种水平及不同物种的混合分解可以更清晰地认识降雨变化对分解的影响机制。而本研究仅探讨功能群及群落水平凋落物分解对降雨变化的响应, 未涉及物种水平的分解及物种间的混合效应。未来的研究可结合降雨变化下不同功能群物种多样性及组成的变化, 以及分解过程中分泌分解产物影响其他物种或微生物的特异物种的变化, 进行单一物种及其混合凋落物的分解。此外, 分解是一个漫长的过程, 而本研究的分解试验仅进行了一年, 未来可进行长期分解研究, 以更清晰和完整地认识高寒草甸凋落物分解的动态变化过程。

4 结论

本研究分析不同降雨处理下不同功能群及群落凋落物的基质质量、质量损失及养分释放, 探究降雨变化对高寒草甸生态系统C、N、P输入与输出动态, 主要结论如下:

1)极端减雨(Pr-90)抑制各类型凋落物分解, 适度降雨变化(Pr-50、Pr-30、Pr+50)抑制禾本科凋落物分解而对莎草科、杂类草和群落凋落物无明显影响, 仅增雨(Pr+50)明显促进杂类草凋落物分解。

2)各类型凋落物C释放对降雨变化响应一致, 均在减雨处理(Pr-90、Pr-30)下受抑制。N、P释放则在凋落物类型中存在差异, 禾本科中降雨变化均促进N、P释放; 莎草科、杂类草和群落中适度降雨变化促进N (Pr-30)、P (Pr+50)释放, 极端减雨则抑制P释放。

3)降雨变化未改变C释放模式, 却改变了N、P释放模式及其富集时间。N在各分解时期出现富集, P在Pr-30下分解中期(201-294 d)显著富集, 尤其在禾本科凋落物中N、P富集由前期(0-200 d)变为中后期(201-365 d)甚至不富集。

4)降雨量主要通过直接作用促进凋落物质量损失和养分释放, 凋落物初始化学性质对分解的影响则主要受凋落物类型影响。

致谢

感谢西南民族大学研究生“创新型科研项目”重点项目(CX2020SZ25)的资助。

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[ 尹能文, 李加纳, 刘雪, 练剑平, 付春, 李威, 蒋佳怡, 薛雨飞, 王君, 柴友荣 (2017).

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以正常生长和高温干旱复合胁迫下甘蓝型油菜中双10号的茎和根为材料,采用组织化学、生物化学、气相色谱-质谱联用(GC-MS)分析技术,研究了木质部结构和木质素成分的胁迫应答规律及其在茎和根中的差别。冰冻切片组织化学染色显示,与正常生长的网室植株(正常植株)相比,高温干旱下生长的温室植株(胁迫植株)的茎和根中木质部均显著加厚,染色更深;与此对应,溴乙酰法测定的茎木质素总量比对照增加31.64%。此外,胁迫茎中的导管孔径明显变小,但根中的导管孔径和导管数量均明显增加。硫代酸解法测定木质素单体表明,胁迫茎中被解离出的木质素单体总量比对照降低40.08%,说明有更高的缩合键比例;S/G值(1.82)比对照(1.29)大大增高,说明S型木质素比例增加而G型木质素比例下降。油菜茎与根木质化性状比较显示,根木质素比茎木质素含有更高比例的缩合键,茎中S型木质素占主体(S/G=1.29),而根中G型木质素占主体(S/G=0.49)且H型木质素含量(7.43%)比茎中(0.83%)高近10倍。H型和G型木质素单体的苯环甲基化程度比S型低,单体间更容易形成缩合键,根中高比例H型和G型木质素单体可能是导致其具有高比例缩合键的主要原因。

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Effects of nitrogen deposition and increased precipitation on soil phosphorus dynamics in a temperate forest

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干旱区植物在如何提高水分利用效率与降低叶建成成本之间可能存在一种权衡。我们假设: 与湿润区植物相比, 干旱区植物能通过调节叶功能性状之间的关系(如通过提高单位面积叶氮含量(N<sub>area</sub>)), 实现在相同的叶建成成本下具有更高的水分利用效率。为了验证这一假设, 该研究以毛乌素沙地的广布物种油蒿(Artemisia ordosica)为研究对象, 分析了油蒿叶建成成本沿降水梯度的变化规律及其与比叶面积(SLA)、单位质量叶氮含量(N<sub>mass</sub>)、N<sub>area</sub>和叶碳稳定同位素比率(δ <sup>13</sup>C)的关系。结果表明: 油蒿单位质量叶建成成本(CC<sub>m</sub>)在不同降水条件下差异不显著, 而单位面积叶建成成本(CC<sub>a</sub>)在不同降水条件下虽有显著差异, 但并未随降水减少而明显增加。油蒿CC<sub>m</sub>与SLA无显著相关性, 与叶δ <sup>13</sup>C值呈显著正相关关系。油蒿叶建成成本与N<sub>area</sub>呈显著正相关关系, 但这种关系格局在低降水量(264 mm)区与高降水量(310-370 mm)区之间存在策略位移现象——即在相同叶建成成本下, 低降水量区植物比高降水量区植物具有更高的N<sub>area</sub>。以上结果表明, 尽管高水分利用效率与高叶建成成本相关, 但与高降水量区植物相比, 低降水量区植物具有较高的N<sub>area</sub>并没有导致其叶建成成本增加。

Zheng HF, Chen YM, Liu Y, Heděnec P, Peng Y, Xu ZF, Tan B, Zhang L, Guo L, Wang LF, Vesterdal L (2021).

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Scientific Reports, 6, 34290. DOI: 10.1038/ srep34290.

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Acta Ecologica Sinica, 40, 2655-2661.

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模拟不同春季降雨量下典型草原土壤微生物磷周转特征

生态学报, 40, 2655-2661.]

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