生物多样性, 2022, 30(8): 22097 doi: 10.17520/biods.2022097

研究报告: 生态系统多样性

准噶尔荒漠土壤多功能性的空间变异特征及其驱动因素

张世航1,2, 陶冶1, 陈玉森2,3, 郭浩1,2, 陆永兴1,2, 郭星1,2, 刘朝红1,4, 周晓兵,1,*, 张元明,1,*

1.中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室, 乌鲁木齐 830011

2.中国科学院大学, 北京 100049

3.国家荒漠-绿洲生态建设工程技术研究中心, 乌鲁木齐 830011

4.新疆农业大学资源与环境学院, 乌鲁木齐 830052

Spatial pattern of soil multifunctionality and its correlation with environmental and vegetation factors in the Junggar Desert, China

Shihang Zhang1,2, Ye Tao1, Yusen Chen2,3, Hao Guo1,2, Yongxing Lu1,2, Xing Guo1,2, Chaohong Liu1,4, Xiaobing Zhou,1,*, Yuanming Zhang,1,*

1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011

2. University of Chinese Academy of Sciences, Beijing 100049

3. National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Urumqi 830011

4. Xinjiang Agricultural University College of resources and environment, Urumqi 830052

通讯作者: *共同通讯作者 E-mail:zhouxb@ms.xjb.ac.cn;zhangym@ms.xjb.ac.cn

编委: 邓建明

责任编辑: 李会丽

收稿日期: 2022-03-2   接受日期: 2022-07-14  

基金资助: 新疆杰出青年科学基金(2021D01E03)
国家自然科学基金(U2003214)
国家自然科学基金(41977099)

Corresponding authors: *Co-authors for correspondence. E-mail:zhouxb@ms.xjb.ac.cn;zhangym@ms.xjb.ac.cn

Received: 2022-03-2   Accepted: 2022-07-14  

摘要

荒漠是重要的陆地生态系统之一, 其生态系统极其脆弱, 极易发生荒漠化。荒漠土壤的稳定和功能对于荒漠生态系统结构和功能的维持至关重要。但在荒漠地区, 大多数土壤功能的研究还主要集中在单一的土壤功能性。本研究基于准噶尔荒漠79个样点的土壤有机碳(SOC)、氮(N)、磷(P)、有效氮(AN)和有效磷(AP)等指标, 通过平均值法和因子分析法计算土壤多功能(soil multifunctionality, SMF)指数, 研究SMF空间变异特征及驱动因素。空间分析所示从整体来看, 荒漠SMF在空间分布上具有较大的异质性, 自西向东, SMF总体呈现逐渐增加的趋势, 而从南向北, SMF呈现先增加后降低的趋势。最优拟合显示, SMF与年均降雨量(MAP)和年均温(MAT)呈显著二次函数关系, 随着MAP和MAT的增加表现出先降低后升高的趋势; SMF与pH和植被增强指数(EVI)呈显著线性关系, SMF随着pH的增加表现出显著降低趋势, 而随着EVI的增加表现为显著上升的趋势; SMF与Aridity (干旱度)之间既符合二次函数关系也呈现线性关系(二者R2相同), 随Aridity增加而减少。结构方程模型结果表明, 土壤含水率(SWC)是SMF变化的最重要的驱动因素, 其次为EVI。土壤pH、SWC、MAT、Aridity和EVI对荒漠SMF具有显著的直接效应, 其中SWC和EVI为显著正效应, 其他为负效应。MAP、经度(Lon)、纬度(Lat)和海拔(Alt)可通过影响MAT等指标对SMF产生间接效应。研究结果对深入理解准噶尔荒漠SMF的空间变异特征及驱动因素具有重要意义, 将有助于预测环境变化对荒漠生态系统多功能性的影响, 为生态系统科学管理服务。

关键词: 准噶尔荒漠; 土壤多功能性; 驱动因子; 空间变异

Abstract

Aims: This study was conducted to analyze the soil multifunctionality (SMF) pattern and their driving factors of the Junggar Desert. We tested that whether climate factors (temperature, precipitation and Aridity), soil environment (soil water content, soil temperature and pH) and vegetation factors would be the main driving factors of the spatial variability of SMF in the Junggar Desert.

Methods: The data of the sampling were collected from 79 sample sites of the Junggar Desert. The SMF indices were calculated by mean method and factor analysis method. The spatial characteristics of SMF in the Junggar Desert were obtained by using Kriging interpolation method in ArcGIS. Correlation analysis between single soil function and SMF was performed in R language software, and the best-fit model was used to fit the environmental factors and SMF of the 79 sample sites. The best-fit model was selected applied on the R2 and the AIC value of the model. Structural equation model (SEM) analysis was performed using the “Lavaan” package in R language. Direct and indirect effects of different variables on SMF were identified, and the driving factors of spatial variability of the SMF in the Junggar Desert were determined.

Results: Overall, the SMF in the Junggar Desert showed large heterogeneity in spatial distribution, with an increasing trend of SMF from west to east, and trend of increasing first and then decreasing from south to north of the desert. The best-fit model showed that SMF had a significant quadratic function with MAP (mean annual precipitation) and MAT (mean annual temperature), and showed a decreasing first and then increasing trend of with the increase in MAP and MAT. The SMF had a significant primary function with pH and EVI (enhanced vegetation index). Specially, SMF had a trend of significant decreasing along with the increase in pH, and a significant increasing trend along with the increase in EVI. The SMF and Aridity (drought) showed both quadratic and linear (R2 was the same for both) relationship, with SMF decreasing with the increase in Aridity. The results of structural equation modeling (SEM) indicated that, SWC was the most important driver of SMF change, followed by EVI. Soil pH, SWC (soil water content), MAT, Aridity and EVI had significant direct effects on SMF in the desert area, with SWC and EVI having significant positive effects and the others having negative effects. MAP, Lon (longitude), Lat (latitude) and Alt (altitude) had indirect effects on SMF by affecting factors such as MAT.

Conclusion: The results of this study indicate that the changes in SMF are caused by the combined effect of multiple environmental conditions. The results are important for the in-depth understanding of the spatial pattern and driving factors of the SMF in the Junggar Desert, which will be beneficial for the assessment of the effects of environmental changes on the multifunctionality and for the ecosystem managements of the desert ecosystems.

Keywords: Junggar Desert; soil multifunctionality; driving factors; spatial variation

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张世航, 陶冶, 陈玉森, 郭浩, 陆永兴, 郭星, 刘朝红, 周晓兵, 张元明 (2022) 准噶尔荒漠土壤多功能性的空间变异特征及其驱动因素. 生物多样性, 30, 22097. doi:10.17520/biods.2022097.

Shihang Zhang, Ye Tao, Yusen Chen, Hao Guo, Yongxing Lu, Xing Guo, Chaohong Liu, Xiaobing Zhou, Yuanming Zhang (2022) Spatial pattern of soil multifunctionality and its correlation with environmental and vegetation factors in the Junggar Desert, China. Biodiversity Science, 30, 22097. doi:10.17520/biods.2022097.

生态系统多功能性(ecosystem multifunctionality, EMF)是指生态系统具有同时维持多种生态系统功能和服务的能力(杨渺等, 2021), 即生态系统的整体功能(Zavaleta et al, 2010)。多功能研究是指对生态系统整体功能的评估, 可加深对生态系统功能和生态系统服务提供的综合理解(Manning et al, 2018), 弥补了传统方法的不足(Petchey & Gaston, 2006)。EMF概念首先由Sanderson等(2004)提出, 指生态系统同时执行多种功能的能力。随后, Hector和Bagchi (2007)提出生态系统的多种服务或过程就是生态系统的多功能。部分学者探讨和量化了生物多样性对维持多功能性的重要性, 深化了多功能是生态系统同时维持多个生态功能或服务能力的认识(Gamfeld et al, 2008; Zavaleta et al, 2010)。目前EMF主要集中在草地和旱区生态系统(张宏锦和王娓, 2021)。例如, 有研究表明, 生物多样性对维持草原的EMF具有极为重要的作用(Hector & Bagchi, 2007; Zavaleta et al, 2010)。随后相关研究逐渐扩展到旱区生态系统, Maestre等(2012)研究了全球干旱地区224个生态系统的丰富度及EMF, 解析了功能多样性对EMF的影响, 全球旱区EMF驱动因子研究等也得到更多学者关注(Valencia et al, 2015; Durán et al, 2018)。然而, 旱区的EMF的研究大多集中于热带和亚热带气候类型, 对温带旱区的研究较少。世界荒漠近1/3为温带荒漠, 80%以上分布在中亚(Zhang et al, 2016), 开展中亚地区温带荒漠EMF的相关研究, 对于丰富旱区EMF研究结果, 厘清主要驱动因子, 验证EMF相关的理论具有重要的现实意义。

在整个陆地生态系统中, 土壤发挥着极为重要的作用(Bui & Henderson, 2013; Condit et al, 2013), 对土壤多功能性(soil multifunctionality, SMF)的研究, 将有利于深入理解土壤的综合服务能力。在全球环境变化的大背景下, SMF空间变化可能源于土壤和植被的变化(Durán et al, 2018; Zheng et al, 2019)。已有研究发现, SMF在空间上受多个气候因素(如降水量及其季节性、干燥度和土壤湿度等)和土壤因素(如pH和含沙量等)影响, 并随植物或土壤微生物多样性的提高而增大(Eldridge et al, 2019; Ding & Eldridge, 2021; Hu et al, 2021)。这些气候、土壤和植被因素的相对重要性随着空间尺度发生变化。相关研究还表明, 在不同干旱梯度下(干旱程度为0.8), 同种环境因子对SMF空间变异表现出不同的效应(Hu et al, 2021)。因此, 影响SMF的因子较多(例如, 气候、土壤和植被), 不同尺度效应也不同。在同一气候背景下, 选择典型生态系统类型, 关注区域尺度下SMF的空间变异规律, 并探索其主要的驱动因子, 将有助于该类型生态系统稳定性的评估及生态系统的精细管理。

荒漠是重要的陆地生态系统之一, 其生态系统极其脆弱, 极易发生荒漠化(Liang et al, 2019)。荒漠土壤的稳定和功能, 对于荒漠生态系统结构和功能的维持至关重要(Wagg et al, 2014)。在荒漠地区, 大多数土壤功能性的研究还主要集中在单一的土壤功能性。然而, 土壤多功能比单一的土壤功能更具有代表性, 多功能性的研究可以为生态系统功能和生态系统服务提供综合理解(Manning et al, 2018), 也更有利于解析多种环境因子的共同驱动作用(兰洁等, 2021)。对于荒漠土壤SMF及其驱动因素的相关研究, 能更好地阐明荒漠生态系统的功能, 科学合理地对荒漠生态系统进行管理。准噶尔荒漠是中亚荒漠的重要组成部分, 也是中国唯一一个受北冰洋气流影响的荒漠, 其气候特征、植被组成和丰富度等与中国其他荒漠差异明显(陶冶等, 2016)。准噶尔荒漠不同区域海拔差异较大, 位于350‒1,100 m之间(魏鹏等, 2021), 导致温度和降水等气候条件具较大差异。同时, 准噶尔荒漠不同区域或不同季节植被覆盖存在较大差异(张立运和陈昌笃, 2002)。有研究表明, 不同干旱梯度下, 同种环境因素对SMF具有不同的效应(Hu et al, 2021), 而在干旱程度整体较高的准噶尔荒漠, 气候和植被等因子如何影响荒漠SMF, 还鲜见相关报道。同时, 荒漠不同区域土壤理化性质存在较大差异, 土壤性质的差异会同样影响SMF (Zheng et al, 2019)。综上所述, 在全球变暖和人类活动严重威胁生物多样性和生态系统功能及服务背景下, 在异质性较高的准噶尔荒漠, 探究环境变化与SMF空间变异的关系对于生态系统的评估具有极为重要的现实意义。

基于上述分析, 可以看出, 在研究内容上, 气候、土壤和植物对SMF空间变化的直接和间接影响的研究还相对较少; 在全球大尺度以及样点小尺度上开展了SMF空间变异主要驱动因素的研究, 但缺乏对准噶尔荒漠等中等区域尺度SMF的具体影响因素的相关研究; 在量化SMF的方法上, 各项研究使用的计算方法和选取的指标并不一致, 使得研究结果出现差异性, 不同区域SMF可比较性低。因此, 根据准噶尔荒漠区干旱水平较高、降水和温度差异较大等特征, 本研究试图回答以下问题: (1)准噶尔荒漠区SMF是否具有较大的空间异质性? 其变异特征如何? (2)在该研究区内, 空间变化、气候、土壤环境和植被众多影响因素中, SMF最重要的驱动因素是什么? 为回答上述问题, 本研究以准噶尔荒漠土壤为对象, 利用随机采集的79个样点的土壤实测数据, 分析准噶尔荒漠的SMF, 解析SMF空间变异特征。根据准噶尔荒漠不同区域气候环境差异较大, 以及不同干旱程度下植物始终与SMF呈正相关的结果(Hu et al, 2021), 我们假设: (1)准噶尔荒漠SMF具有较大的空间异质性; (2)气候、土壤环境和植被等环境因素等可显著影响SMF, 但植被是重要的驱动因素。研究将验证相关假设, 为准噶尔荒漠的生态系统评估和管理提供依据。

1 数据采集和处理方法

1.1 研究区概况

准噶尔盆地位于中国新疆的北部, 是中国第二大内陆盆地(范围为34°09′‒49°08′ N, 73°25′‒ 96°24′ E), 总面积约为3.8 × 104 km2。该区域受大陆性干旱气候的控制, 夏季炎热干燥, 冬季寒冷, 年均温6‒10℃, 年均降水量150 mm左右, 年日照时数为3,079 h, 6‒8月的日照时数超过10 h, 年均潜在蒸发量超过2,000 mm, 属于欧亚大陆腹地典型的温带大陆性荒漠气候(王丽娟等, 2011)。准噶尔荒漠主要土壤类型有风沙土、灰漠土、棕漠土、棕钙土、龟裂土、盐土等(中国科学院中国植被图编辑委员会, 2001)。植物类型主要由耐盐、耐碱和耐旱植物构成, 其中梭梭(Haloxylon ammodendron) 、白梭梭(H. persicum)是该区域的建群种, 还有柽柳(Tamarix chinensis)、白皮沙拐枣(Calligonum leucocladum)、琵琶柴(Reaumuria soongorica)、碱蓬(Suaeda acuminata)、角果藜(Ceratocarpus arenarius)、猪毛菜(Salsola arbuscula)等灌木和草本植物(张立运和陈昌笃, 2002)。

1.2 土壤多功能性量化指标的取样及测定

依据前人的相关研究, 本研究选取8个干旱区关键生态系统功能指标, 包括有机碳(SOC)、全氮(N)、全磷(P)、C∶N、C∶P、N∶P、速效氮(AN)和速效磷(AP)。这些指标与生态系统的碳、氮和磷元素的循环密切相关(Sanderson et al, 2004; Maestre et al, 2012; Yan et al, 2020), 可较大程度地反映生态系统的养分固存﹑水土保持﹑野生动植物承载力等多种功能(Soliveres et al, 2014; Valencia et al, 2015)。于2021年7‒8月在准噶尔荒漠区设置79个采样点(图1)。采样点的位置尽量按以下标准选择: (1)样点尽可能均匀地分布在整个准噶尔荒漠区; (2)采样点距离公路至少3 km, 减少干扰影响。

图1

图1   准噶尔荒漠土壤采样图

Fig. 1   Soil sampling sites in the Junggar Desert


每一个样点首先设置1个10 m × 10 m的大样方, 然后在大样方的四个角和中间位置各设置5个1 m × 1 m的小样方, 以消除小尺度空间异质性对土壤养分的影响(陶冶等, 2016)。在每个小样方内采集1份0‒10 cm层土壤样品, 然后将每个点5个小样方的土样混合为1份, 样品带回实验室风干。测量前, 土壤样品过2 mm的土壤筛, 挑除细根之后, 利用球磨仪研磨土壤样品, 并过0.15 mm的土壤筛。基于研磨后的土壤样品, 利用碳氮分析仪测定土壤有机碳, 利用AA3流动分析仪测量土壤全氮、全磷、速效氮和速效磷含量。利用pH计(水土比2.5∶1)测定土壤pH。采样过程中, 对每个样点进行定位, 获取样地经度(Lon)、纬度(Lat)和海拔(Ele)。

目前, 常见的生态系统多功能性的量化方法有多种, 如平均值法(Hooper & Vitousek, 2005)、功能物种替代法(Hector & Bagchi, 2007)、单阈值法(Gamfeldt et al, 2008)、多阈值法(Byrnes et al, 2014)、因子分析法(李静鹏等, 2016)等, 不同方法之间各有优缺点。本文首先采用平均值法和因子分析法两种方法来计算土壤多功能性指数。平均值法最早由Hooper和Vitousek (2005)提出, 也最早将多个生态系统过程运用一个综合指数来量化表征(徐炜等, 2016)。该方法通过计算不同生态系统功能的平均标准化得分(Z scores)来代表生态系统的多功能性, 对于量化同时维持多种生态系统功能的能力提供了一种直接且易于解释的方法, 但该方法没有考虑不同生态系统功能间的相互关系(Gamfeldt et al, 2008)。因子分析法可得到类似平均值法的多功能性指数(李静鹏等, 2016)。首先对功能指标参数进行降维, 做因子分析, 然后得到各因子得分, 再用各因子得分来表示多功能性, 此方法在一定程度上可以衡量各个功能间的权衡关系( 蔡艳 (2019) 水盐梯度下荒漠植物多样性与生态系统多功能性的关系。新疆大学, 乌鲁木齐。)。通过这两种方法的计算结果可知(图2), 两种多功能性计算方法的结果非常接近(Pearson r = 0.963), 并且均与8种单一土壤功能呈现显著正相关(表1)。因此, 我们选用因子分析法计算的土壤多功能性指数用于后续分析。

图2

图2   基于因子分析法(MF1)和平均值法(MF2)得到的土壤多功能指数之间的线性关系

Fig. 2   Linear relationship of the soil multifunctional index obtained determined by factor analysis (MF1) and mean method (MF2)


表1   单一土壤功能与土壤多功能性的相关性

Table 1  Correlation between single soil function and soil multifunctionality

有机碳
SOC

N

P
碳氮比
C∶N
碳磷比
C∶P
氮磷比
N∶P
速效氮
AN
速效磷
AP
MF1MF2
MF10.940**0.519**0.637**0.609**0.924**0.344**0.644**0.812**10.963**
MF20.845**0.723**0.569**0.396**0.828**0.572**0.511**0.786**0.963**1

MF1和MF2的含义见图2.

The meaning of MF1 and MF2 see Fig. 2. ** P < 0.01.

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1.3 环境因子的获取

环境因子参考相应的文献从各数据库获取。年均温(MAT)数据来自Modis数据中的MOD11A全球气温格网数据(https://doi.org/10.5067/MODIS/MOD11A1.006), MOD11A1 V6产品提供1 km网格中的每日地表温度(LSTV)和发射率值(Rodell et al, 2004)。年降雨数据(MAP)采用“University of Idaho”发布的Terra Climate数据集, 包括全球陆地表面月均气候和气候水平衡数据集, 也包括太阳辐射、潜在蒸散量、实际蒸散量等气候数据(https://doi:10.1038/sdata.2017.191)。干旱指数(aridity index, AI), 参考Hu等(2021)论文提及的AI和潜在蒸散量数据库, 干旱程度(Aridity)计算公式为1减去AI, 其中AI是降水量与潜在蒸散量的比值(https://cgiarcsi.community/) (Hu et al, 2021)。土壤含水率(soil water content, SWC)和土壤温度(soil temperature, ST)数据来自美国国家航空航天局(NASA)发布的FLDAS数据集(Rodell et al, 2004), 包括含水量、湿度、蒸散量、土壤平均温度、总降水率等气候相关变量的信息(https://doi:10.5067/5NHC22T9375G)。植被增强指数(EVI)数据通过Landsat遥感影像数据波段计算得出。

1.4 统计方法

对土壤养分和其他相关指标进行描述统计分析, 在ArcGIS (10.2版)中运用“Kriging”插值法获得准噶尔荒漠土壤多功能性的空间特征, 用IBM SPSS软件(22版)计算土壤多功能性指数; 使用R语言软件(4.1.1版), 分析单一土壤功能与土壤多功能性的相关性, 同时将所有变量都进行了标准化。为探究SMF与环境因子间的关系, 除了相关性分析外, 选择线性函数、二次函数、幂函数等多种模型关系对79个样地环境因子与SMF进行最优拟合, 最优拟合模型的选择依据模型的R2和AIC值来确定(Yuan et al, 2020)。同时使用R语言中“Lavaan”包做SEM分析, 分析不同变量对土壤多功能性的直接或间接影响, 探究准噶尔荒漠SMF的空间变异的驱动因子。SEM的在模型构建依据Durán等(2018) SEM模型的基础上, 按照变量间的相关关系进行了一些更改。

2 结果

2.1 准噶尔荒漠土壤、植被和气候变异特征

整个准噶尔荒漠不同样点土壤养分、气候变量等变化情况结果见表2。SOC、N、P、AN和AP的均值分别为5.73 g/kg、0.21 g/kg、0.35 g/kg、32.09 mg/kg和9.03 mg/kg, 不同样点间变异系数分别为0.75、0.37、0.10、0.84和0.87, 说明不同样点土壤的SOC、AN和AP的空间差异相对较大, 而不同土壤的N和P的变化相对较小。该区域各点的MAP和MAT的均值分别为140.06 mm和7.70℃; ST和SWC的均值分别为2.54℃和2.20%。Aridity均值为0.91, 按照干旱区域类型划分, 准噶尔荒漠属于极度干旱区域。整个区域的土壤pH均值为8.30, pH最小值为7.80, 该区土壤主要属于碱性土壤。EVI均值为0.09, 但是其变异系数为0.37。

表2   准噶尔荒漠土壤、植被和气候参数的描述统计表。ST: 土壤温度; SWC: 土壤含水率; EVI: 植被增强指数。CV: 变异系数。

Table 2  Descriptive statistics of desert soil, vegetation and climate parameters in the Junggar Desert. ST, soil temperature; SWC, Soil water content; EVI, Vegetation enhancement index. CV, Coefficient of variation.

参数
Parameter
有机碳
SOC
(g/kg)
全氮
N
(g/kg)
全磷
P
(g/kg)
速效氮
AN
(mg/kg)
速效磷
AP
(mg/kg)
年降水
MAP
(mm)
年均温
MAT
(℃)
干旱程度
Aridity
土壤温度
ST
(℃)
土壤含水率
SWC
(%)
pH植被增强
指数
EVI
平均值 Mean5.730.210.3532.099.03140.067.700.912.542.208.300.09
最大值 Max24.100.540.42155.5935.00192.6422.170.9514.462.608.800.22
最小值 Min0.900.070.268.462.2680.27‒4.760.84‒3.831.907.800.04
标准误差 SE4.330.080.0326.917.9020.096.110.022.200.010.200.03
变异系数 CV0.750.370.100.840.870.140.790.020.860.070.020.37

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2.2 准噶尔荒漠土壤多功能空间变异特征

准噶尔荒漠土壤SMF具有一定的空间异质性(图3), 整个荒漠的SMF范围为‒0.85至2.63, 该区约占70%面积的土壤SMF值分布于‒0.15至1.200.37。整个荒漠自西向东, SMF总体表现为逐渐增加的趋势, 而从南向北, SMF总体表现出先增加后降低的趋势。整个荒漠的西北区域、东北区域和东部区域的SMF较高, 而西南区域SMF较低。

图3

图3   准噶尔荒漠土壤多功能性(SMF)空间变异特征

Fig. 3   Spatial variation characteristics of soil multifunctionality (SMF) in the Junggar Desert


2.3 环境因子与土壤多功能性之间的关系

各环境因子与SMF之间的最优拟合显示(图4), Aridity与SMF之间既符合二次函数关系也呈现线性关系(二者R2相同) (图4b); MAT和MAP与SMF之间均为显著的二次函数关系(图4a、图4g), 且SMF随着MAP和MAT的增加表现出先降低后升高的趋势; pH和EVI与SMF之间均为显著的线性关系(图4e、4f), 但是随着pH和EVI的增加, SMF表现出来的趋势正好相反: 即SMF与pH为负的线性关系, SMF随着pH的增加表现出显著降低趋势(图4e), 而SMF与EVI为正的线性关系(图4f), SMF随着EVI的增加表现为显著上升的趋势; 而ST和SWC与SMF无明显的函数关系(P > 0.05) (图4c、4d)。

图4

图4   环境因子与土壤多功能性之间的线性或非线性关系

Fig. 4   Linear or nonlinear relationship between environmental factors and soil multifunctionality


SEM模型分析的结果表明, 模型对SMF的解释率达到了64% (图5)。在SMF的模型中, SWC和EVI对SMF具有显著的正效应, Aridity、pH和MAT对SMF具有显著的负效应, 其它变量对SMF均无显著的直接效应。空间变量通过显著影响气候变量和土壤环境, 从而间接显著影响SMF, 例如, Lon可通过对MAT显著负效应, 从而极显著影响SMF。同样, 气候和土壤环境中部分变量也通过相互影响, 从而间接显著影响SMF, 例如, SWC通过对pH的极显著负效应, 从而间接显著负影响SMF。总之, 土壤pH、SWC、MAT、Aridity和EVI对荒漠SMF具有显著的直接效应, 其中SWC和EVI为显著正效应, 其他为负效应。MAP、Lon、Lat和Alt可通过影响MAT等指标对SMF产生间接效应。

图5

图5   环境因子对土壤多功能性的直接和间接影响的SEM分析结果。

不同粗细与箭头旁载重系数成正比。RMSEA, 近似误差均方根。空间地理位置、气候、土壤(环境)的组成部分作为独立的可观测变量包含在模型中, 但为了图解的简单性, 我们将它们放在同一个方框。环境因子的缩写全程详见图4。

Fig. 5   SEM analysis results about direct and indirect effects of environmental factors on soil multifunctionality.

Different thickness is directly proportional to the load coefficient beside the arrow. RMSEA, Root mean square of approximate error. The components of spatial location, climate and soil (environment) are included in the model as independent observable variables, but for the simplicity of illustration, we put them in the same box. See Figure 4 for abbreviations of environmental factors. χ2 = 0.127, P = 0.881, GFI = 0.999, AGFI = 0.977, RMSEA = 0.018. * P < 0.05, ** P < 0.01, *** P < 0.001.


3 讨论

整体来看, 准噶尔荒漠SMF在空间分布上具有较大的异质性, 呈斑块状分布, 这与假设(1)一致。准噶尔荒漠不同区域海拔差异较大(魏鹏等, 2021), 随着海拔的改变, 温度和降水等环境因子将会随之发生改变(Tsui et al, 2004)。较大的环境差异将影响植被及土壤微生物的生存状态, 进而使土壤养分发生改变, 从而表现为与养分相关的SMF在空间分布上差异较大。例如, 随着海拔升高, 温度降低, 可能有利于土壤微生物及土壤动物维持的最适温度, 既保障对中海拔丰富的植被凋落物的分解, 也能降低过度的养分消耗, 从而有利于土壤养分的积累(张广帅等, 2016)和SMF的增加。由于准噶尔荒漠土壤SWC较低, 随着干旱的加剧, 微生物活动会相应减少(Maestre et al, 2012), 造成SMF发生变异。

影响准噶尔荒漠SMF的因素较多, 土壤环境、气候和植被等因素均可造成显著影响, 其中SWC和EVI的影响最大, 与本研究的假设(2)整体相符。有研究通过实验控制土壤水分供给, 证实土壤含水量下降是土壤多功能降低的主要驱动因素(Hu et al, 2021)。在旱区中, 土壤水分通常被认为是许多陆地生态系统过程中的限制因子, 也是植物生长和土壤微生物活动的主要驱动力, 因此强烈影响碳等养分的积累和循环(Moyano et al, 2013), 从而影响SMF。土壤水分是微生物群落组成的重要驱动因素, 可调节土壤的硝化和反硝化等过程(Chen et al, 2013), 显著影响土壤养分转化、气体交换和微生物生长(Mcdaniel et al, 2013)。土壤SWC直接受到外界降水量的影响。SEM模型结果表明, MAP对SWC表现为显著正效应, 且SWC显著影响SMF, 因此MAP可通过影响SWC而对SMF产生显著的间接影响。本研究中, SWC不仅可以直接影响SMF, 还可以影响植被从而间接影响SMF。同时, 除了SWC的影响外, 其他环境因素对SMF的变化也具有直接或间接的影响作用。

本研究中, 土壤pH对SMF表现出显著负效应, 且pH不仅能直接显著影响SMF, 还能通过影响EVI而间接影响SMF。土壤pH是影响土壤过程和性质的主要因素之一, 与土壤养分转化和有效性密切相关, 直接或间接地影响土壤C和N含量(Kemmitt et al, 2006), 从而显著影响SMF。整个荒漠的土壤为碱性土壤, 随着pH的增加, 土壤碱性加强, 除了部分盐生植物, 一般植物生存难度增加, 植被覆盖等随着土壤碱性增强而出现下降的趋势, 从而表现为pH也可通过直接影响EVI从而间接影响SMF。Ding和 Eldridge (2021)研究发现, 土壤pH对SMF的空间变化具有重要影响, 这与本研究结论一致。总之, 土壤pH也是SMF变化的重要驱动因素, pH既可以直接影响SMF, 还可通过影响植被间接影响SMF。

在本研究中, 准噶尔荒漠Aridity范围在0.84‒ 0.95, 属于典型的旱区(0.80 < Aridity < 0.95), 干旱程度较高。SMF与Aridity的回归分析表明, 随着Aridity的增加, SMF表现出明显的下降趋势。同样, 在SEM模型中, Aridity对SMF也表现为极显著的负效应。总之, Aridity是准噶尔荒漠SMF的重要驱动因素之一。Hu等(2021)研究同样表明, Aridity的增加降低了与养分循环相关的SMF。Aridity可影响陆地生态系统的关键过程, 如植物生长、水通量和所有元素的生物地球化学循环(Zhou et al, 2016; Hu et al, 2020)。Aridity可通过改变土壤微生物组成和酶活性, 并对土壤C和N平衡产生相应的影响(Zhou et al, 2016; Ren et al, 2017)。Aridity增加通常降低土壤微生物活性, 因此高Aridity条件下, 土壤养分可用性会降低(Delgado-Baquerizo et al, 2013), 从而降低了与养分循环相关的SMF。Yan等(2020)研究表明, Aridity对SMF有直接影响, 也有间接影响, 这与本研究结果一致。本研究中, Aridity除了直接影响SMF变化, 还可以通过影响植被等因素从而间接影响SMF。

MAT也是准噶尔荒漠SMF空间变化的重要的直接和间接驱动因素之一。全球变暖可能对土壤氮动态产生负效应, 但对土壤磷动态无影响或影响较小, 同时可能导致生态系统由磷限制向氮限制转变(Tan et al, 2021)。本研究SEM模型发现, MAT对SMF整体为显著的负效应, 但回归分析可以发现, SMF与MAT表现为显著的二次函数关系, 当MAT大于0.5 (标准化值) 时, SMF表现出随着MAT的增加而呈逐渐上升的趋势。推测在一定温度范围内, MAT的增加有助于土壤ST增加(本文SEM模型中, MAT对ST为极显著正效应), 从而有助于土壤微生物活动, 加速消耗土壤中的养分含量, 故MAT在一定温度范围内与SMF表现为负相关关系; 当MAT超过一定范围, 土壤微生物活动下降, 进而减少土壤养分的消耗, 因此当MAT超过0.5后, MAT与SMF表现为正相关关系。Durán等(2018)研究发现, 温度的变化是全球旱区SMF的空间变异主要驱动因素之一, 同时温度与SMF空间变异也表现为先增加后降低的趋势, 这与本研究结果一致。MAT和ST均为SMF的重要驱动因素, 两者均可直接或间接影响SMF。

Eldridge等(2019)的研究结果表明, SMF更多地受到降雨的限制, 而不是温度, 这可能是由于季节性降水造成土壤水分的变化所致。本研究,MAP未有显著影响, 因为准噶尔荒漠年降雨量较低, 且蒸散量较大, 仅靠降雨远远不足以维持生物的生存。目前, 大多研究表明, 准噶尔荒漠冬季的覆雪和春季融雪水对于沙漠地区高植被覆盖度的形成、生物多样性的发育以及沙漠稳定性的保持具有重要作用(张立运和陈昌笃, 2002; 王雪芹等, 2004; 范连连等, 2012)。因此, 在准噶尔荒漠, 降雪所提供的水分可能对植物及微生物的生长发育具有更为重要的意义, 将降雪作为荒漠SMF的驱动因素, 是进一步研究的重要内容。本研究中MAP变化对SMF的影响较小, 不是SMF空间变异的主要驱动因素, 但是, MAP通过直接影响Aridity而间接影响SMF。

本研究中, 植被是准噶尔荒漠SMF仅次于SWC的主要驱动因素。在Aridity程度较高的地区, 植物物种丰富度与SMF表现出正相关关系, 同时植物丰富度指数与EVI指数存在极显著正相关关系(Pau et al, 2012; Abatzoglou et al, 2018; Hu et al, 2021), 故推断EVI指数与SMF具有正相关关系。但是, 本研究结果的数据仅来源于准噶尔荒漠(Aridity值较高), 在更大范围(如西北干旱区, 包含半干旱区)内, EVI指数与SMF的具体关系还有待进一步研究。

4 结论

在区域尺度研究了准噶尔荒漠土壤多功能性及驱动因子, 结果表明(1)准噶尔荒漠SMF指数范围为‒0.85至2.63, 大部分区域集中在‒0.15至1.20; 荒漠自西向东, SMF总体表现为逐渐增加的趋势, 而从南向北, SMF总体表现出先逐渐增加后逐渐降低的趋势。整体来看, 准噶尔荒漠SMF在空间分布上具有较大的异质性。(2)环境因子中SWC、pH、MAT、Aridity和EVI是准噶尔荒漠的主要的直接驱动因素, 其中SWC和EVI对SMF具有显著的正效应, Aridity、pH和MAT对SMF具有显著的负效应, SWC是SMF变化的最重要驱动因素, 其次为EVI。MAP、Lon、Lat和Alt可通过影响MAT等其他环境变量从而对SMF的变化产生间接效应。(3) SMF的变化不是单一的环境改变造成的, 而是由于多种环境条件共同作用的结果。研究结果对理解准噶尔荒漠SMF的空间变异特征及驱动因素, 评估环境变化条件下温带荒漠生态系统功能具有重要意义。

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DOI:10.1002/ecy.2199      URL     [本文引用: 4]

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Response of the herbaceous layer to snow variability at the south margin of the Gurbantonggut Desert of China

Chinese Journal of Plant Ecology, 36, 126-135. (in Chinese with English abstract)

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[范连连, 马健, 吴林峰, 徐贵青, 李彦, 唐立松 (2012)

古尔班通古特沙漠南缘草本层对积雪变化的响应

植物生态学报, 36, 126-135.]

DOI:10.3724/SP.J.1258.2012.00126      [本文引用: 1]

草本层是古尔班通古特沙漠植物群落下层层片的构建者, 冬季积雪提供了其生长发育所需要的主要水分, 积雪的增加或减少对草本植物数量和生物量会产生显著的影响。该研究利用人工增减积雪的方法, 在古尔班通古特沙漠南缘设置了5个不同厚度的积雪处理: 0积雪、50%积雪、100%积雪、150%积雪和200%积雪, 其中100%积雪为自然积雪。采用1 m &times; 1 m的样方, 对草本层片的物种数、盖度、密度、高度进行了调查, 还采用收获法测定了草本层片的地上生物量和优势种小花荆芥(Nepeta micrantha)的单株地上生物量。对研究区内13个科29种草本植物的研究表明: 1)单位面积出土幼苗数量跟积雪厚度呈显著正相关关系, 草本层片的盖度、密度对积雪的变化响应显著, 随着积雪增加, 草本层片的密度和盖度呈递增趋势, 而草本层片的平均高度呈递减趋势, 但不同积雪处理间的物种数和总地上生物量没有显著差异; 2)积雪厚度与优势种的株高和地上生物量呈显著负相关关系, 积雪的增加导致优势种的单株生物量和株高显著降低; 3)积雪厚度的变化主要影响了草本层片植物种子萌发的数量, 但对物种数量没有显著影响。这表明: 虽然积雪是草本植物的主要水分来源之一, 但荒漠植物群落的草本植物对积雪的变化具有很强的缓冲能力, 即使积雪很少, 草本层片的物种构成也不会发生显著变化, 草本层片的净初级生产力也保持相对稳定。

Gamfeldt L, Hillebrand H, Jonsson PR (2008)

Multiple functions increase the importance of biodiversity for overall ecosystem functioning

Ecology, 89, 1223-1231.

PMID:18543617      [本文引用: 2]

Biodiversity is proposed to be important for the rate of ecosystem functions. Most biodiversity-ecosystem function studies, however, consider only one response variable at a time, and even when multiple variables are examined they are analyzed separately. This means that a very important aspect of biodiversity is overlooked: the possibility for different species to carry out different functions at any one time. We propose a conceptual model to explore the effects of species loss on overall ecosystem functioning, where overall functioning is defined as the joint effect of many ecosystem functions. We show that, due to multifunctional complementarity among species, overall functioning is more susceptible to species loss than are single functions. Modeled relationships between species richness and overall ecosystem functioning using five empirical data sets on monocultures reflected the range of effects of species loss on multiple functions predicted by the model. Furthermore, an exploration of the correlations across functions and the degree of redundancy within functions revealed that multifunctional redundancy was generally lower than single-function redundancy in these empirical data sets. We suggest that by shifting the focus to the variety of functions maintained by a diversity of species, the full importance of biodiversity for the functioning of ecosystems can be uncovered. Our results are thus important for conservation and management of biota and ecosystem services.

Hector A, Bagchi R (2007)

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Nature, 448, 188-190.

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Hu WG, Ran JZ, Dong LW, Du QJ, Ji MF, Yao SR, Sun Y, Gong CM, Hou QQ, Gong HY, Chen RF, Lu JL, Xie SB, Wang ZQ, Huang H, Li XW, Xiong JL, Xia R, Wei MH, Zhao DM, Zhang YH, Li JH, Yang HX, Wang XT, Deng Y, Sun Y, Li HL, Zhang L, Chu QP, Li XW, Aqeel M, Manan A, Akram MA, Liu XH, Li R, Li F, Hou C, Liu JQ, He JS, An LZ, Bardgett RD, Schmid B, Deng JM (2021)

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[兰洁, 雷相东, 何潇, 高文强, 李玉堂 (2021)

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[李静鹏, 郑志荣, 赵念席, 高玉葆 (2016)

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植物生态学报, 40, 735-747.]

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随着全球变化对生物多样性的影响不断加剧, 生物多样性与生态系统功能之间相互关系(BEF)的研究显得极为重要。过去的20多年, BEF的研究大多集中在对物种多样性与单一或少数生态系统功能之间关系的探讨, 但生态系统最为重要的价值是同时维持多种服务和功能的能力, 基于此, 该文首次在国内引入近年来不断完善的生态系统多功能性(multifunctionality)的概念, 并对目前主流的评价方法进行了改进, 从而对内蒙古三种利用方式(刈割、围封、放牧)下的草地群落进行了多功能性评价, 并探讨了多功能性与物种多样性之间的关系。结果显示本研究改进的方法和目前主流方法评价得出的多功能性指数在样方和样地尺度上都有很高的相关性(R<sup>2</sup> = 0.6956, p &#x0003C; 0.0001; R<sup>2</sup> = 0.9231, p &#x0003C; 0.0001), 表明该文作者改进后的方法是可靠的。重度放牧的草地群落物种多样性水平最低, 绝大多数土壤功能指标较差, 表现出退化特征; 7年的围封和刈割群落均有较高的物种多样性水平和改善的土壤功能指标; 三者的多功能性指数为刈割(0.2178) &#x0003E;围封(0.0704) &#x0003E;放牧(-0.8031)。植被样方主要沿水肥梯度分布; 多样性指数中, 均匀度指数(Pielou index)和丰富度指数(Margelf index)对多功能性的影响作用最大, 均为样方尺度(R<sup>2 </sup>= 0.1871, p &#x0003C; 0.0001; R<sup>2 </sup>= 0.1601, p &#x0003C; 0.0001)小于样地尺度(R<sup>2 </sup>= 0.5921, p = 0.0093; R<sup>2 </sup>= 0.7499, p = 0.0007), 有尺度依赖性; 多功能性在样方和样地尺度上均与物种均匀度呈线性正相关关系, 而与物种丰富度呈单峰曲线关系。该文研究结果表明, 相对于重度放牧和围封, 刈割更有利于维持该地区生态系统的多功能性; 物种丰富度适中且物种分布均匀的生态系统可能有更好的多功能性。

Liang MW, Chen JQ, Smith NG, Bai X, Jia CZ, Li ZY, Liang CZ (2019)

Changes and regulations of net ecosystem CO2 exchange across temporal scales in the Alxa Desert

Journal of Arid Environments, 164, 78-84.

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Plant species richness and ecosystem multifunctionality in global drylands

Science, 335, 214-218.

DOI:10.1126/science.1215442      URL     [本文引用: 3]

Manning P, van der Plas F, Soliveres S, Allan E, Maestre FT, Mace G, Whittingham MJ, Fischer M (2018)

Redefining ecosystem multifunctionality

Nature Ecology & Evolution, 2, 427-436.

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Mcdaniel MD, Kaye JP, Kaye MW (2013)

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Moyano FE, Manzoni S, Chenu C (2013)

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Pau S, Gillespie TW, Wolkovich EM (2012)

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Petchey OL, Gaston KJ (2006)

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Ecology Letters, 9, 741-758.

PMID:16706917      [本文引用: 1]

Functional diversity is a component of biodiversity that generally concerns the range of things that organisms do in communities and ecosystems. Here, we review how functional diversity can explain and predict the impact of organisms on ecosystems and thereby provide a mechanistic link between the two. Critical points in developing predictive measures of functional diversity are the choice of functional traits with which organisms are distinguished, how the diversity of that trait information is summarized into a measure of functional diversity, and that the measures of functional diversity are validated through quantitative analyses and experimental tests. There is a vast amount of trait information available for plant species and a substantial amount for animals. Choosing which traits to include in a particular measure of functional diversity will depend on the specific aims of a particular study. Quantitative methods for choosing traits and for assigning weighting to traits are being developed, but need much more work before we can be confident about trait choice. The number of ways of measuring functional diversity is growing rapidly. We divide them into four main groups. The first, the number of functional groups or types, has significant problems and researchers are more frequently using measures that do not require species to be grouped. Of these, some measure diversity by summarizing distances between species in trait space, some by estimating the size of the dendrogram required to describe the difference, and some include information about species' abundances. We show some new and important differences between these, as well as what they indicate about the responses of assemblages to loss of individuals. There is good experimental and analytical evidence that functional diversity can provide a link between organisms and ecosystems but greater validation of measures is required. We suggest that non-significant results have a range of alternate explanations that do not necessarily contradict positive effects of functional diversity. Finally, we suggest areas for development of techniques used to measure functional diversity, highlight some exciting questions that are being addressed using ideas about functional diversity, and suggest some directions for novel research.

Ren CJ, Zhao FZ, Shi Z, Chen J, Han XH, Yang GH, Feng YZ, Ren GX (2017)

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Soil Biology & Biochemistry, 115, 1-10.

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Rodell M, Houser PR, Jambor U, Gottschalck J, Mitchell K, Meng CJ, Arsenault K, Cosgrove B, Radakovich J, Bosilovich M, Entin JK, Walker JP, Lohmann D, Toll D (2004)

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Soliveres S, Maestre FT, Eldridge DJ, Delgado-Baquerizo M, Quero JL, Bowker MA, Gallardo A (2014)

Plant diversity and ecosystem multifunctionality peak at intermediate levels of woody cover in global drylands

Global Ecology and Biogeography, 23, 1408-1416.

PMID:25914607      [本文引用: 1]

The global spread of woody plants into grasslands is predicted to increase over the coming century. While there is general agreement regarding the anthropogenic causes of this phenomenon, its ecological consequences are less certain. We analyzed how woody vegetation of differing cover affects plant diversity (richness and evenness) and multiple ecosystem functions (multifunctionality) in global drylands, and how this changes with aridity.224 dryland sites from all continents except Antarctica widely differing in their environmental conditions (from arid to dry-subhumid sites) and woody covers (from 0 to 100%).Using a standardized field survey, we measured the cover, richness and evenness of perennial vegetation. At each site, we measured 14 ecosystem functions related to soil fertility and the build-up of nutrient pools. These functions are critical for maintaining ecosystem function in drylands.Species richness and ecosystem multifunctionality were strongly influenced by woody vegetation, with both variables peaking at relative woody covers (RWC) of 41-60%. This relationship shifted with aridity. We observed linear positive effects of RWC in dry-subhumid sites. These positive trends shifted to hump-shaped RWC-diversity and multifunctionality relationships under semiarid environments. Finally, hump-shaped (richness, evenness) or linear negative (multifunctionality) effects of RWC were found under the most arid conditions.Plant diversity and multifunctionality peaked at intermediate levels of woody cover, although this relationship became increasingly positive under wetter environments. This comprehensive study accounts for multiple ecosystem attributes across a range of woody covers and environmental conditions. Our results help us to reconcile contrasting views of woody encroachment found in current literature and can be used to improve predictions of the likely effects of encroachment on biodiversity and ecosystem services.

Tan QQ, Jia YF, Wang GA (2021)

Decoupling of soil nitrogen and phosphorus dynamics along a temperature gradient on the Qinghai-Tibetan Plateau

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Tao Y, Liu YB, Wu GL, Zhang YM (2016)

Regional-scale ecological stoichiometric characteristics and spatial distribution patterns of key elements in surface soils in the Junggar desert, China

Acta Prataculturae Sinica, 25, 13-23. (in Chinese with English abstract)

[本文引用: 2]

[陶冶, 刘耀斌, 吴甘霖, 张元明 (2016)

准噶尔荒漠区域尺度浅层土壤化学计量特征及其空间分布格局

草业学报, 25, 13-23.]

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Tsui CC, Chen ZS, Hsieh CF (2004)

Relationships between soil properties and landscape position in a lowland rainforest of southern Taiwan

Geoderma, 123, 131-142.

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Valencia E, Maestre FT le Bagousse-Pinguet Y, Quero JL, Tamme R, Börger L, García-Gómez M, Gross N (2015)

Functional diversity enhances the resistance of ecosystem multifunctionality to aridity in Mediterranean drylands

New Phytologist, 206, 660-671.

DOI:10.1111/nph.13268      PMID:25615801      [本文引用: 2]

We used a functional trait-based approach to assess the impacts of aridity and shrub encroachment on the functional structure of Mediterranean dryland communities (functional diversity (FD) and community-weighted mean trait values (CWM)), and to evaluate how these functional attributes ultimately affect multifunctionality (i.e. the provision of several ecosystem functions simultaneously). Shrub encroachment (the increase in the abundance/cover of shrubs) is a major land cover change that is taking place in grasslands worldwide. Studies conducted on drylands have reported positive or negative impacts of shrub encroachment depending on the functions and the traits of the sprouting or nonsprouting shrub species considered. FD and CWM were equally important as drivers of multifunctionality responses to both aridity and shrub encroachment. Size traits (e.g. vegetative height or lateral spread) and leaf traits (e.g. specific leaf area and leaf dry matter content) captured the effect of shrub encroachment on multifunctionality with a relative high accuracy (r(2) = 0.63). FD also improved the resistance of multifunctionality along the aridity gradient studied. Maintaining and enhancing FD in plant communities may help to buffer negative effects of ongoing global environmental change on dryland multifunctionality. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Wagg C, Bender SF, Widmer F,van der Heijden MGA (2014)

Soil biodiversity and soil community composition determine ecosystem multifunctionality

Proceedings of the National Academy of Sciences, USA, 111, 5266-5270.

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Wang LJ, Sun DY, Zhao CY, Li JY, Sheng Y (2011)

Plant architecture characteristics of Haloxylon ammodendron and Haloxylon persicum in Zhungar Basin

Acta Ecologica Sinica, 31, 4952-4960. (in Chinese with English abstract)

[本文引用: 1]

[王丽娟, 孙栋元, 赵成义, 李菊艳, 盛钰 (2011)

准噶尔盆地梭梭、白梭梭植物构型特征

生态学报, 31, 4952-4960.]

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Wang XQ, Jiang J, Lei JQ, Zhao CJ (2004)

Relationship between ephemeral plants distribution and soil moisture on longitudinal dune surface in Gurbantonggut desert

Chinese Journal of Applied Ecology, 15, 556-560. (in Chinese with English abstract)

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[王雪芹, 蒋进, 雷加强, 赵从举 (2004)

短命植物分布与沙垄表层土壤水分的关系——以古尔班通古特沙漠为例

应用生态学报, 15, 556-560.]

[本文引用: 1]

于2002年3月至2002年8月,对古尔班通古特沙漠南部短命植物分布和沙垄表层30cm厚土壤水分间的关系进行了系统监测和研究.结果表明,早春表层土壤水分在个体沙丘表面的分异直接影响到短命植物的分布.4月下旬,垄间、两坡和垄顶土壤含水率依次为4.62%、3.98%和2.01%,相应的短命植物平均盖度于5月中上旬依次为51.8%、38.2%和4.4%.5月中旬后,短命植物的分布又改变了表层土壤水分分布,上述各地貌部位的土壤含水率依次为1.00%、1.90%和2.45%,形成垄顶最高、两坡次之、垄间最差的新的空间分布格局.

Wei P, An SZ, Dong YQ, Bieerdawulieti Xi HR, Sun ZJ, Zheng FL (2021)

Plant diversity and its influencing factors of three typical plant formations in Junggar Desert

Chinese Journal of Grassland, 43, 27-33. (in Chinese with English abstract)

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[魏鹏, 安沙舟, 董乙强, 别尔达吾列提·希哈依, 孙宗玖, 郑逢令 (2021)

准噶尔荒漠3种典型植物群系植物多样性及其影响因素

草地学报, 43, 27-33.]

[本文引用: 2]

Xu W, Jing X, Ma ZY, He JS (2016)

A review on the measurement of ecosystem multifunctionality

Biodiversity Science, 24, 72-84. (in Chinese with English abstract)

DOI:10.17520/biods.2015170      URL     [本文引用: 1]

[徐炜, 井新, 马志远, 贺金生 (2016)

生态系统多功能性的测度方法

生物多样性, 24, 72-84.]

DOI:10.17520/biods.2015170      [本文引用: 1]

生物多样性与生态系统多功能性(biodiversity and ecosystem multifunctionality, BEMF)之间的关系是目前生态学研究的一个热点, 其中, 生态系统多功能性(EMF)的测度方法是研究该问题的技术关键。由于缺乏统一的认识, 目前存在多个多功能性的测度方法, 这使人们对生物多样性与生态系统多功能性之间关系的理解复杂化。本文介绍了国际上常用的单功能法、功能-物种替代法、平均值法、单阈值法、多阈值法、直系同源基因法和多元模型法的原理及其特点, 并对其中较难理解的多阈值法进行了举例说明, 希望能对理解EMF的测度方法有所帮助。本文按不同的EMF测度方法对已发表的有关文章进行了归类, 以期帮助读者更好地选择EMF的测度方法。由于缺乏相对统一的、代表各个层次的生态系统功能的测度方法, 导致不同的研究结果难以相互比较, 严重限制了生物多样性与生态系统多功能性研究的发展; 所以, 研发新的、具有普遍适用性的EMF测度方法已成为当务之急。

Yan YZ, Zhang Q, Buyantuev A, Liu QF, Niu JM (2020)

Plant functional β diversity is an important mediator of effects of aridity on soil multifunctionality

Science of the Total Environment, 726, 138529.

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