journal of mountain science

Journal of Mountain Science（JMS） The Journal of Mountain Science (JMS), founded in

2004, is an international English-language journal on mountain sciences. JMS is supervised by the Chinese Academy of Sciences (CAS), sponsored by the Chengdu Institute of Mountain Hazards and Environment, CAS, published by Science Press China, and distributed by Springer exclusively throughout the world (excluding Mainland China).

The JMS is published bimonthly, fulltexted in SpringerLink and CNKI, indexed/abstracted by ISI-Web of Science, Chinese Science Citation Database, Geobase, Georef Database.

JMS publishes academic and technical papers as well as research reports concerning environmental changes and sustainable development in mountain areas under natural conditions or/and with the influence of human activities. Academic papers and research reports should display universal, strategic and innovative characteristics in both theory and practice.

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Journal of Mountain Science (Bimonthly, Started in 2004)

Volume 10 Number 3 June 2013

Contents 339-354 LI Wei-le, HUANG Run-qiu, TANG Chuan, XU Qiang, Cees van WESTEN

Co-seismic Landslide Inventory and Susceptibility Mapping in the 2008 Wenchuan Earthquake Disaster Area, China

355-362 LI Ying-kui Determining Topographic Shielding from Digital Elevation Models for Cosmogenic Nuclide Analysis: a GIS Approach and Field Validation

363-369 SONG Xin-zhang, PENG Chang-hui, ZHOU Guo-mo, JIANG Hong, WANG Wei-feng, XIANG Wen-hua Climate Warming-induced Upward Shift of Moso Bamboo Population on Tianmu Mountain, China

370-377 WU Yan-hong, LI Wei, ZHOU Jun, CAO Yang Temperature and Precipitation Variations at Two Meteorological Stations on Eastern Slope of Gongga Mountain, SW China in the Past Two Decades

378-387 ZHAO Jian, XU Min, LU Shi-lei, CAO Chun-xiang Human Settlement Evaluation in Mountain Areas Based on Remote Sensing, GIS and Ecological Niche Modeling

388-397 WANG Xu-feng, ZHANG Dong-sheng, ZHANG Cheng-guo, FAN Gang-wei Mechanism of Mining-induced Slope Movement for Gullies Overlaying Shallow Coal Seams

398-409 DI Bao-feng, ZHANG Kai-shan, TANG Ya，ZHANG Ming-hua, Susan L. USTIN The Development of a Geographic Information System (GIS) Database for Jiuzhaigou National Nature Reserve and Its Application

410-417 YANG Xiao-lin, ZHU Bo, LI Yi-ling Spatial and Temporal Patterns of Soil Nitrogen Distribution under Different Land Uses in a Watershed in the Hilly Area of Purple Soil, China

418-427 PENG Li, SU Chun-jiang, SUN Lian, LI Ping, FANG Yan, LIU Wei, WANG Xiao-lan Spatial-temporal Evolution Pattern of Agricultural Productivity in Northwestern Sichuan Plateau

428-436 JU Li, WEN An-bang, LONG Yi, YAN Dong-chun, GUO Jin Using 137Cs Tracing Methods to Estimate Soil Redistribution Rates and to Construct a Sediment Budget for a Small Agricultural Catchment in the Three Gorges Reservoir Region, China

437-444 XIE Xian-jian, WEI Fang-qiang Soil Aggregates and Fractal Features under Different Land Use Types in a Frequent Debris Flow Area

445-454 LIU Shao-quan, ZHANG Hai-qin, XIE Fang-ting, GUO Shi-li Current Situation and Influencing Factors of Pluriactivity in Mountainous and Hilly Rural Areas of Sichuan Province, China

455-463 FU Gang, SHEN Zhen-xi, ZHANG Xian-zhou, YU Cheng-qun, ZHOU Yu-ting, LI Yun-long, YANG Peng-wan Response of Ecosystem Respiration to Experimental Warming and Clipping at Daily Time Scale in an Alpine Meadow of Tibet

464-471 Deepak DHYANI, Shalini DHYANI, RK MAIKHURI Assessing anthropogenic pressure and its impact on Hippophae salicifolia pockets in Central Himalaya, Uttarakhand

472-481 Yashwant S. RAWAT, Colin S. EVERSON Availability and Use of Willow Species in Representative Cold Desert Areas of Northwestern Himalaya, India

482-493 TU Guo-xiang, HUANG Run-qiu, DENG Hui, LI Yan-rong Permeability and Sedimentation Characteristics of Pleistocene Fluvio-glacial Deposits in the Dadu River Valley, Southwest China

494 Erratum to: Snow Cover Variation and Streamflow Simulation in a Snow-fed River Basin of the Northwest Himalaya

Serial parameters: CN51-1668/X*2004*B*A4*156*en*P*50* *17*2013-6 http://jms.imde.ac.cn Email: [email protected] Tel: 028-85252044

Editorial Board

Editor in Chief

CUI Peng, Institute of Mountain Hazards and

Environment, CAS, China

E-mail: [email protected]

Executive Editor-in-Chief

QIU Dun-lian, Institute of Mountain Hazards and



Associate Editors in Chief

（in Alphabetic Order）

CHENG Gen-wei, Institute of Mountain Hazards and



Martin F. Price, Centre for Mountain Studies, Perth

College UHI Millennium Institute, UK

E-mail:[email protected]

Kevin M. Scott, CAS foreign expert from United

States Geological Survey, USA


Iain Taylor, Botanical Garden, University of British

Columbia, Canada


Member（in Alphabetic Order）

Harold C. Brookfield, Australian National

University, Australia


CAI Yun-long, College of Urban and Environmental

Sciences, Peking University, China


CHEN Su-chin, Department of Soil and Water

Conservation, Chung Hsing University, Chinese Taipei


CHEN Xi, XinJiang Institute of Ecology and

Geography, CAS, China


DENG Wei, Institute of Mountain Hazards and



FANG Xiao-min, Institute of Tibetan Plateau

Research, CAS, China


Wojciech A. Froehlich, Institute of Geography and

Spatial Organization, Polish Academy of Sciences,

Poland


James S. Gardner, Office of International Relations,

541H University Centre, University of Manitoba,

Canada


Edwin A. Gyasi, Department of Geography and

Resource Development University of Ghana, Ghana


Sarah J. Halvorson, Department of Geography, The

University of Montana, USA


David Laurence Higgit, National University of

Singapore, Singapore.


Jon Harbor, Department of Earth and Atmospheric

Sciences, Purdue University, USA


Yoshiharu Ishikawa, Institute of Symbiotic Science

and Technology, Tokyo University of Agriculture and

Technology, Japan


Steven M. de Jong, the Faculty of Geographical

Sciences, Utrecht University, The Netherlands


Hermann Kreutzmann, Department of Earth Studies,

Freie Universitat Berlin, Germany


Matthias Kuhle, Institute of Geography,

University of Göttingen, Germany


LI Lan-hai, Xinjiang Institute of Ecology and

Geography, CAS, China


Asif M. Khan，National Centre of Excellence in

Geology, University of Peshawar，Pakistan


LI Yong, Institute of Mountain Hazards and



LIANG Luo-hui, Environment and Sustainable

Development, United Nations University, Japan


LIU Jian, International Ecosystem Management

Partnership, United Nations Environment Programme


LIU Ko-Fei, Department of Civil Engineering,

National Taiwan University, Chinese Taipei


LIU Shi-yin, Cold and Arid Regions Environmental

and Engineering Research Institute, CAS, China


Marcus Nuesser, South Asia Institute, Department of

Geography, University of Heidelberg, Germany


K. G. Saxena, School of Environmental Science,

Jawaharlal Nehru University, India


Udo Schickhoff, Institute of Geography, University

of Hamburg, Germany


Michael A. Stocking, School of Development Studies,

University of East Anglia, UK


Olga Tutubalina, Laboratory of Aerospace Methods,

Faculty of Geography, Moscow State University, Russia


TANG Ya, College of Architecture and Environment,

Sichuan University, China


Des Walling, Department of Geography, School of

Geography and Archaeology, University of Exeter, UK


WANG Ye-qiao, Department of Natural Resources

Science, University of Rhode Island, USA


WEI Fangqiang, Institute of Mountain Hazards and



XU Jian-chu, Kunming Institute of Botany, CAS,

China


YANG Zi-sheng, Institute of Land & Resources and

Sustainable Development, Yunnan University of

Finance and Economics, China


YU Da-fu, Institute of Mountain Hazards and



ZHANG Bai-ping, Institute of Geography Sciences

and Natural Resources Research, CAS, China


Editorial Advisors（in Alphabetic Order）

Donald A. Friend, Department of Geography,

Minnesota State University, USA


Chack Fan Lee, Vice-Chancelloe’s Office,

University of Hong Kong, Hong Kong, China


QIN Da-he，China Meteorological Administration，

China


ZHENG Du, Institute of Geography Sciences &

Natural Resources Research, CAS, China


Scientific Editosr（in Alphabetic Order）

CAO Shu-you, State Key Laboratory of Hydraulics

and Mountain River Engineering, Sichuan University

Email: [email protected]

CHEN Ningsheng, Institute of Mountain Hazards and



CHEN Xiao-qin, Institute of Mountain Hazards and



FAN Jian-rong, Instituteof Mountain Hazards and



FANG Yi-ping, Institute of Mountain Hazards and



FENG Qi, Cold and Arid Region Environmental

Engineering Research Institute, CAS, China


GAO Yong-heng, Institute of Mountain Hazards and



HE Xiu-bin, Instituteof MountainHazards and

Environment,CAS, China


JIN Hui-jun, State Key Laboratory of Frozen Soils

Engineering, CAREERI, CAS, China


HU Kai-heng, Institute of Mountain Hazards and



LI Ai-nong, Instituteof Mountain Hazards and


E-mail: [email protected];

[email protected]

LI Li-hua, Instituteof Mountain Hazards and

Environment, CAS


LI Xin-po, Instituteof Mountain Hazards and



LIU Qiao, Institute of Mountain Hazards and

Environment, CAS


LIU Shao-quan, Instituteof Mountain Hazards and

Environment, CAS

E-mail: liushq@imde,ac,cn

SU Li-Jun, Instituteof Mountain Hazards and

Environment, CAS


TANG Chuan, Chengdu University of Technology,

China


Wang Gen-xu, Instituteof MountainHazards and



WANG Xiao-dan,Institute of Mountain Hazards and



WANG Yu-kuan, Institute of Mountain Hazards and

Environment (IMHE), CAS, China


WU Guang-jian, Institute of Tibetan Plateau

Research, CAS, China


WU Yan-hong, Institute of Mountain Hazards and

Environment, CAS


Sanjay Kumar Shukla, School of Engineering, Edith

Cowan University, Perth, Australia


YANG Kun, Institute of Tibetan Plateau Research,

CAS, China


ZHANG Fan, Institute of Tibetan Plateau Research,

CAS E-mail: [email protected]

ZHANG Xin-bao, Institute of Mountain Hazards and



ZHOU Gong-dan, Institute of Mountain Hazards and



ZHU Bo, Instituteof MountainHazards and



ZHU Wan-ze, Instituteof MountainHazards and



Mahmood Syed Amer, University of the Punjab,

Space Science, Department of space science,

Quaid-i-Azam campus, Lahore,Punjab,54590,

Pakistan


Vishwambhar Prasad Sati, Department of

Geography and Resource Management, Mizoram

Central University


Editorial Staff

WU Xue-mei, [email protected]

XIANG Li, [email protected]

YANG Yi, [email protected]

ZHONG Yu-qian, [email protected]

Contact us:

Editorial Office of Journal of Mountain Science

P. O. Box 417

Chengdu 610041, Sichuan, China


Tel &Fax: +86-28-85252044

http://jms.imde.ac.cn

Online submission:

http://mc03.manuscriptcentral.com/jmsjournal

J. Mt. Sci. (2013) 10(3): 455–463 DOI: 10.1007/s11629-013-2360-y

455

Abstract: The alpine meadow, as one of the typical vegetation types on the Tibetan Plateau, is one of the most sensitive terrestrial ecosystems to climate warming. However, how climate warming affects the carbon cycling of the alpine meadow on the Tibetan Plateau is not very clear. A field experiment under controlled experimental warming and clipping conditions was conducted in an alpine meadow on the Northern Tibetan Plateau since July 2008. Open top chambers (OTCs) were used to simulate climate warming. The main objective of this study was to examine the responses of ecosystem respiration (Reco) and its temperature sensitivity to experimental warming and clipping at daily time scale. Therefore, we measured Reco once or twice a month from July to September in 2010, from June to September in 2011 and from August to September in 2012. Air temperature dominated daily variation of Reco whether or not experimental warming and clipping were present. Air temperature was exponentially correlated with Reco and it could significantly explain 58~96% variation of Reco at daily time scale. Experimental warming and clipping decreased daily mean Reco by 5.8~37.7% and -11.9~23.0%, respectively, although not all these changes were significant. Experimental warming tended to decrease the temperature sensitivity of Reco, whereas clipping tended to increase the temperature sensitivity of Reco at daily time scale. Our findings suggest that Reco was

mainly controlled by air temperature and may acclimate to climate warming due to its lower temperature sensitivity under experimental warming at daily time scale. Keywords: Acclimation; Air temperature; Open top chamber; Temperature sensitivity; Respiration quotient (Q10)

Introduction

The Tibetan Plateau is referred to “the Third Pole of the Earth” due to its unique features, such as high altitude, thin air, high air transparency and strong solar radiation (Zhang et al. 2000). It covers about one-fourth of Chinese land (Zhuang et al. 2010) and is experiencing significant climate warming (Xie et al. 2010; Yang et al. 2010). The warming trend on the Tibetan Plateau is much greater than the average (IPCC 2007). Moreover, the Tibetan Plateau is a promoter region of climate change (Yao et al. 1991), so any changes on the Plateau can quickly spread to the surrounding area.

Recent studies have indicated that the alpine ecosystem is one of the terrestrial systems most sensitive to climate warming (Chen and Tian 2005; Saito et al. 2009; Suh et al. 2009). The alpine meadow generally accumulates vast amount of

Response of Ecosystem Respiration to Experimental

Warming and Clipping at Daily Time Scale in an Alpine

Meadow of Tibet

FU Gang1,2, SHEN Zhen-xi1, ZHANG Xian-zhou1*, YU Cheng-qun1, ZHOU Yu-ting1,2, LI Yun-long1, 2, YANG Peng-wan1,2

1 Lhasa Plateau Ecosystem 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

2 University of Chinese Academy of Sciences, Beijing 100049, China

*Corresponding author, e-mail: [email protected]; First author, e-mail: [email protected]; Tel: 86-10-64888176; Fax: 86-10-64854230

© Science Press and Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg 2013

Received: 10 December 2012 Accepted: 16 January 2013

J. Mt. Sci. (2013) 10(3): 455–463

456

carbon due to the low decomposition under low temperature (Zhang et al. 2005). In China, the alpine meadow is concentrated in the western and south-western regions, most on the Tibetan Plateau, in the whole China, containing 35.4 Pg of carbon (i.e., 26.4% of total carbon in grassland of China) (Ni 2002). About one-third of the Tibetan Plateau is covered with the alpine meadow, which is the major pastureland on the Tibetan Plateau (Cao et al. 2004). The alpine meadow may be a carbon sink if the carbon lost due to grazing was not significant (Kato et al. 2004). Furthermore, the alpine meadow plays a profound role in the regional carbon budget in China (Zhang et al. 2008) and even in global carbon budget (Kato et al. 2006).

Experimental warming is an important tool for understanding the responses of terrestrial ecosystems to climate warming (Hudson and Henry 2010). Several warming experiments have been performed on the Tibetan Plateau in order to understand the effects of climate warming on various alpine ecosystems (Fu et al. 2012b; Klein et al. 2004; Lin et al. 2011; Xu et al. 2009), whereas few studies examined the response of ecosystem respiration (Reco) to climate warming under controlled experimental warming and clipping conditions at daily time scale (Lin et al. 2011). Therefore, how climate warming affects the alpine meadow carbon cycling on the Tibetan Plateau is

not very clear. Temperature and water availability are the

most important abiotic factors controlling Reco (Hunt et al. 2002; Kato et al. 2004; Shi et al. 2006) and their relative importance could be dependent on which is more limited (Lin et al. 2011; Wohlfahrt et al. 2008). The objectives of this study were to examine (1) the relative contributions of soil and air temperatures and soil water content in controlling the daily variation of Reco and (2) the main and interactive effects of experimental warming and clipping on Reco and its temperature sensitivity at daily time scale in an alpine meadow on the Tibetan Plateau.

1 Materials and Methods

1.1 Study area

The study site (30°29′50″ N, 91°03′55″ E) was located in Damxung Grassland Observation Station, Tibetan Autonomous Region in China (Figure 1). The annual average sunlight is 2,880.9 h and the annual average solar radiation is 7,527.6 MJ m-2. Annual mean air temperature is 1.3 °C, with minimum monthly mean of -10.4 °C in January and maximum monthly mean of 10.7 °C in July. Annual average precipitation is around 476.8 mm,

Figure 1 Location of the study site

J. Mt. Sci. (2013) 10(3): 455–463

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with over 80% concentrated in the period from June to August. The annual potential evapotranspiration is about 1,725.7 mm. The soil texture is sandy loam and soil layer is 0.5~0.7 m thick, with organic matter of 0.3~11.2%, total nitrogen of 0.03~0.49% and pH of 6.0~6.7 (Fu et al. 2012c). The vegetation surrounding the site is C3-dominated alpine meadow (Xu et al. 2005) and the dominant species are Kobresia pygmaea, Stipa capillacea and Carex montis-everestii (Fu et al. 2012a).

1.2 Experimental design

The field experiment was based on a complete factorial design with experimental warming and clipping as treatments. Six open top chambers (OTCs) were randomly established at the alpine meadow experimental site in July 2008. The OTCs remained on the plots year round. One control plot was randomly set up in the vicinity of each OTC. There was about 3 m distance between plots. The bottom and top diameters and the height of OTCs are 1.5 m, 1.0 m and 0.40 m, respectively (Fu et al. 2012b). Clipping was conducted three times a year (generally in June, July and September) for the clipped plots since 2009. The aboveground parts of plants were clipped to about 0.01 m in height and removed for the clipped plots. The four treatments with three replicates were the control plots (C), the warmed plots (W), the clipped plots (CL) and the warmed plus clipped plots (W+CL), respectively.

Soil temperature (Ts) at the depth of 0.05 m, soil water content (SWC) at the depth of 0.10 m, air temperature (Ta) and relative humidity at the height of 0.15 m were continuously monitored using meteorological towers. All the channels were connected to data loggers (HOBO weather station, Onset Computer Corporation, USA). OTCs increased seasonal average Ts by 1.13 oC and Ta by 1.04 oC across the three consecutive growing seasons in 2010~2012 (three-way ANOVA, p < 0.05). These figures were comparable to previous observed results in alpine meadows on the Tibetan Plateau (Fu et al. 2012b; Klein et al. 2005; Shen et al. 2009). However, OTCs decreased seasonal average SWC by 28.30% (i.e., 0.05 m3 m-3) across the three consecutive growing seasons in 2010~2012 (three-way ANOVA, p < 0.05).

1.3 Measurement of Reco

A soil CO2 flux system (LI-8100, LI-COR Biosciences, Lincoln, NE, USA) with an opaque survey chamber of 20 cm in diameter was used to measure Reco. The measurement time was 90s for each sampling. The Reco was calculated based on CO2 concentration in the opaque survey chamber during the measurement and this process was auto-completed by the LI-8100. One polyvinyl chloride (PVC) collar (20 cm in diameter and 5 cm in height) was permanently inserted about 2~3 cm into the soil for each plot in May 2010. The opaque survey chamber was manually mounted on PVC collar in each plot for Reco. The internal height of the opaque survey chamber is approximately 25 cm, thus the opaque survey chamber is high enough to enclose all the plants within it. Daily change (18:00~18:00, local time) of Reco with 2h interval was measured once or twice a month from July to September in 2010 and 2011. Daily change of Reco with 2h interval was also measured once late in June 2011 and early in August and September 2012, respectively. Reco measurements were made at least 6 days after clipping.

1.4 Statistical analysis

For a specific treatment, a multiple stepwise regression analysis was applied between Reco and Ts, Ta and SWC in order to examine their relative contributions in controlling daily variation of Reco (Table 1). For a specific measuring date, repeated-measures analysis of variance with experimental warming and clipping as the between-subject factors and with measuring time as the within-subject factor for Reco was conducted (Table 2). Since Ta dominated the daily variation of Reco for most cases (Table 1), the temperature sensitivity of Reco was only assessed by relating Reco to Ta as follows for a specific measuring date.

abTecoR ae= (1)

where Reco is ecosystem respiration (µmol CO2 m-2 s-1), Ta is air temperature at the height of 15 cm, a is the intercept of Reco when Ta is zero, and b reflects the temperature sensitivity of Reco. The b values were used to calculate the respiration quotient (Q10), which can reflect the change of Reco with a 10 oC increase in Ta.

1010

bQ e= (2)

J. Mt. Sci. (2013) 10(3): 455–463

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Table 1 Multiple stepwise regression analyses between ecosystem respiration and soil temperature at the depth of 5 cm (Ts), soil water content at the depth of 10 cm (SWC) and air temperature at the height of 15 cm (Ta) at daily time scale

C W CL W+CL Measuring date Factor

R p R p R p R p Ts -0.45 0.14 -0.09 0.77 0.13 0.69 0.23 0.48 SWC 0.21 0.52 -0.28 0.37 0.20 0.53 0.01 0.97 2010-07-26~2010-07-27Ta 0.87 <0.001 0.90 <0.001 0.87 <0.001 0.89 <0.001Ts -0.44 0.18 0.44 0.16 -0.58 0.05 0.39 0.21 SWC 0.60 0.04 0.10 0.76 0.40 0.20 0.38 0.22 2010-08-05~2010-08-06Ta 0.94 <0.001 0.95 <0.001 0.91 <0.001 0.95 <0.001Ts -0.80 <0.01 -0.40 0.20 -0.27 0.40 -0.39 0.21 SWC -0.27 0.42 -0.53 0.08 0.43 0.17 -0.38 0.23 2010-08-25~2010-08-26Ta 0.97 <0.001 0.97 <0.001 0.98 <0.001 0.98 <0.001Ts -0.62 0.03 -0.59 0.04 -0.75 <0.01 -0.45 0.14 SWC 0.12 0.73 0.03 0.93 -0.02 0.95 0.13 0.69 2010-09-07~2010-09-08Ta 0.95 <0.001 0.93 <0.001 0.94 <0.001 0.90 <0.001Ts -0.64 0.03 0.20 0.53 -0.14 0.66 0.58 0.05 SWC -0.15 0.66 -0.33 0.30 0.48 0.11 -0.35 0.29 2010-09-18~2010-09-19Ta 0.94 <0.001 0.98 <0.001 0.94 <0.001 0.76 <0.01 Ts 0.17 0.60 0.36 0.26 0.45 0.14 0.95 <0.001SWC 0.09 0.77 0.34 0.29 0.39 0.21 0.12 0.71 2011-06-26~2011-06-27 Ta 0.91 <0.001 0.92 <0.001 0.94 <0.001 0.44 0.15 Ts 0.18 0.59 0.40 0.19 -0.19 0.55 0.37 0.23 SWC 0.47 0.12 0.41 0.19 0.52 0.08 0.37 0.23 2011-07-25~2011-07-26 Ta 0.91 <0.001 0.86 <0.001 0.95 <0.001 0.95 <0.001Ts 0.15 0.65 0.53 0.07 0.13 0.69 0.53 0.08 SWC 0.10 0.77 0.37 0.24 0.08 0.80 -0.32 0.31 2011-08-05~2011-08-06Ta 0.96 <0.001 0.91 <0.001 0.95 <0.001 0.94 <0.001Ts 0.18 0.58 0.61 0.04 0.37 0.24 0.95 <0.001SWC 0.34 0.29 0.41 0.21 0.34 0.28 0.63 0.03 2011-08-25~2011-08-26 Ta 0.93 <0.001 0.83 <0.01 0.90 <0.001 0.46 0.15 Ts -0.24 0.46 0.34 0.31 -0.62 0.04 0.94 <0.001SWC 0.05 0.88 0.76 <0.01 0.87 <0.001 0.44 0.15 2011-09-16~2011-09-17 Ta 0.86 <0.001 0.73 <0.01 0.90 <0.001 0.51 0.09 Ts -0.13 0.68 0.16 0.62 -0.31 0.33 0.44 0.15 SWC 0.18 0.57 0.52 0.08 -0.25 0.43 -0.25 0.43 2012-08-07~2012-08-08Ta 0.95 <0.001 0.93 <0.001 0.97 <0.001 0.96 <0.001Ts 0.33 0.30 0.61 0.04 0.64 0.03 0.90 <0.001SWC -0.17 0.59 0.31 0.35 0.12 0.72 0.51 0.09 2012-09-07~2012-09-08Ta 0.92 <0.001 0.67 0.02 0.67 0.02 0.42 0.18

Notes: C = the control plots; W = the warmed plots; CL = the clipped plots; W+CL = the warmed plus clipped plots; R = Partial correlation coefficient; p = significance probability

Table 2 Repeated-measures analysis of variance indicating F values and levels of significance (p) for the main and interactive effects of experimental warming (W), clipping (CL) and measuring time (T) on ecosystem respiration at daily time scale

Measuring date W CL T W×CL W×T CL×T W×CL×T 2010-07-26~2010-07-27 5.49* 0.10 24.24*** 0.37 3.36* 0.56 0.50 2010-08-05~2010-08-06 6.45* 0.57 48.01*** 1.88 3.94* 0.48 1.51 2010-08-25~2010-08-26 2.33 0.08 34.11*** 0.51 0.97 0.20 1.23 2010-09-07~2010-09-08 0.55 0.17 21.76*** 0.27 0.60 1.15 0.33 2010-09-18~2010-09-19 0.37 0.57 66.67*** 0.07 1.02 0.69 0.40 2011-06-26~2011-06-27 3.79 0.01 52.37*** 2.14 1.17 0.89 0.40 2011-07-25~2011-07-26 0.87 0.18 32.92*** 2.46 0.79 0.78 0.53 2011-08-05~2011-08-06 2.68 3.95 75.08*** 1.41 0.87 0.76 0.29 2011-08-25~2011-08-26 3.92 2.49 121.57*** 0.58 0.76 0.49 0.46 2011-09-16~2011-09-17 8.73* 4.74 39.21*** 0.06 1.90 1.68 0.72 2012-08-07~2012-08-08 0.32 3.47 96.94*** 1.98 1.91 1.67 1.63 2012-09-07~2012-09-08 0.14 0.10 28.78*** 0.27 1.06 0.59 0.33

Notes: * = p < 0.05; ** = p < 0.01; *** = p < 0.001

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A T-test was used to assess the significance of main and interactive effects of experimental warming and clipping on regression coefficient b (Table 3) (Zhou et al. 2006). Besides, two-way ANOVA was used to assess the main and interactive effects of experimental warming and clipping on the temperature sensitivity of Reco using daily Q10 values across all the measuring dates. All the statistical tests were performed using the SPSS software (version 16.0; SPSS Inc., Chicago, IL).

2 Results

Ecosystem respiration had significant daily variation (Figure 2, Table 2). The daily maximum and minimum values of Reco generally took place between 10:00 and 14:00 and between 2:00 and 6:00, respectively.

For most cases, Ta dominated the daily variation of Reco (Table 1). In contrast, Ta, Ts and/or SWC together controlled the daily variation of Reco for other cases (Table 1). In summary, temperature rather than SWC dominated the daily variation of Reco in this alpine meadow. The adjusted R2 values of the exponential regression analyses between Reco and Ta at daily time scale were 0.66~0.95, 0.66~0.94, 0.58~0.96 and 0.59~0.94 for the control plots, the warmed plots, the clipped plots and the warmed plus clipped plots, respectively (Table 3). In other words, air temperature could explain 66~95%, 66~94%, 58~96% and 59~94% daily variation of Reco for the control plots, the warmed plots, the clipped plots and the warmed plus clipped plots, respectively.

The response of Reco to experimental warming varied with measuring dates, whereas no main effect of clipping and interactive effect on Reco were found (Table 2). In detail, significant main effect of experimental warming on Reco was found in 3 out of the 12 measuring dates. Experimental warming decreased daily mean Reco by 5.8~37.7% (i.e., 0.12~0.88 µmol CO2 m-2 s-1 with an averaged value of 0.45 µmol CO2 m-2 s-1), whereas clipping reduced daily mean Reco by -11.9~23.0% (i.e., -0.21~0.77 µmol CO2 m-2 s-1 with an averaged value of 0.15 µmol CO2 m-2 s-1).

The Q10 ranges 0f Reco were 1.42~3.60, 1.43~3.10, 1.32~5.10 and 1.42~3.63 for the control plots, the warmed plots, the clipped plots and the warmed plus clipped plots, respectively.

The main effects of experimental warming and clipping on the exponential regression coefficient b varied with measuring dates, but the interaction had no effects in 12 out of the 12 measuring dates (Table 4). In detail, experimental warming significantly decreased exponential regression coefficient b in 3 out of the 12 measuring dates. In contrast, clipping significantly increased exponential regression coefficient b in 1 out of the 12 measuring dates. Two-way ANOVA showed that the main and interactive effects of experimental

Table 3 Exponential regression parameters between ecosystem respiration and air temperature at daily time scale (p < 0.01, n = 13)

Measuring date Factor C W CL W+CL

a 1.03 0.76 1.09 0.91 b 0.08 0.04 0.07 0.05

2010-07-26~ 2010-07-27

Adj R2 0.66 0.75 0.70 0.81 a 1.02 0.61 0.82 0.62 b 0.05 0.04 0.05 0.05

2010-08-05~ 2010-08-06

Adj R2 0.89 0.94 0.85 0.89 a 0.66 0.54 0.83 0.59 b 0.13 0.09 0.10 0.11

2010-08-25~ 2010-08-26

Adj R2 0.94 0.81 0.94 0.91 a 0.72 0.47 0.41 0.54 b 0.11 0.11 0.16 0.13

2010-09-07~ 2010-09-08

Adj R2 0.81 0.77 0.58 0.76 a 0.87 0.89 0.78 0.69 b 0.09 0.07 0.09 0.09

2010-09-18~ 2010-09-19

Adj R2 0.95 0.91 0.91 0.93 a 1.26 0.77 0.85 0.85 b 0.04 0.04 0.06 0.05

2011-06-26~ 2011-06-27

Adj R2 0.86 0.87 0.93 0.88 a 1.02 0.79 0.60 0.95 b 0.10 0.09 0.11 0.10

2011-07-25~ 2011-07-26

Adj R2 0.82 0.81 0.94 0.90 a 1.50 1.07 1.02 0.91 b 0.07 0.07 0.08 0.08

2011-08-05~ 2011-08-06

Adj R2 0.92 0.88 0.96 0.94 a 1.69 1.40 1.40 1.20 b 0.06 0.05 0.06 0.06

2011-08-25~ 2011-08-26

Adj R2 0.90 0.91 0.90 0.86 a 0.96 0.71 0.87 0.56 b 0.04 0.04 0.03 0.04

2011-09-16~ 2011-09-17

Adj R2 0.74 0.85 0.72 0.90 a 0.86 1.09 0.50 0.84 b 0.11 0.07 0.11 0.08

2012-08-07~ 2012-08-08

Adj R2 0.93 0.90 0.90 0.94 a 1.00 1.02 0.71 1.03 b 0.06 0.05 0.08 0.05

2012-09-07~ 2012-09-08

Adj R2 0.84 0.66 0.86 0.59

Notes: C = the control plots; W = the warmed plots; CL = the clipped plots; W+CL = the warmed plus clipped plots; a = the intercept of ecosystem respiration when air temperature is zero; b = reflecting the temperature sensitivity of ecosystem respiration; Adj R2 = adjusted R2

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warming and clipping had no effects on the Q10 of Reco (F = 2.19, p = 0.15 for experimental warming; F = 0.70, p = 0.41 for clipping and F = 0.01, p = 0.93 for interaction). Experimental warming tended to decrease the temperature sensitivity of Reco, while clipping tended to increase the temperature sensitivity of Reco at daily time scale.

3 Discussion

We compared the abiotic factors dominating the variation of ecosystem respiration with previous studies which were conducted near our study site. The daily variation of ecosystem respiration was mainly controlled by air temperature in our study. This finding was similar with one study which showed that half-hourly

Figure 2 Daily variation of ecosystem respiration (Reco) (mean ± SE, n = 3) on (a) July 26-27, 2010; (b) August 5-6, 2010; (c) August 25-26, 2010; (d) September 7-8, 2010; (e) September 18-19, 2010; (f) June 26-27, 2011; (g) July 25-26, 2011; (h) August 5-6, 2011; (i) August 25-26, 2011; (j) September 16-17, 2011; (k) August 7-8, 2012 (l) September 7-8, 2012

Table 4 T-test indicating t values and levels of significance (p) for the main and interactive effects of experimental warming (W) and clipping (CL) on exponential regression coefficient b

Measuring date W CL W×CL

2010-07-26~2010-07-27 -2.20* -0.22 0.76

2010-08-05~2010-08-06 -1.33 0.31 0.51

2010-08-25~2010-08-26 -1.25 -0.65 2.15

2010-09-07~2010-09-08 -0.63 1.35 -0.71

2010-09-18~2010-09-19 -1.54 0.81 1.40

2011-06-26~2011-06-27 -1.89 2.52* -1.05

2011-07-25~2011-07-26 -1.04 0.77 0.23

2011-08-05~2011-08-06 -0.47 1.10 0.00

2011-08-25~2011-08-26 -0.85 1.03 0.51

2011-09-16~2011-09-17 0.86 -0.86 0.65

2012-08-07~2012-08-08 -4.47*** 1.21 0.48

2012-09-07~2012-09-08 -2.51* 0.73 -0.84

Notes: * = p < 0.05; *** = p < 0.001

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average nighttime ecosystem respiration was controlled mainly by half-hourly average nighttime soil temperature and simultaneously by half-hourly average soil water content at several days time scale (Shi et al. 2006). In contrast, monthly average ecosystem respiration was not significantly correlated with monthly average air temperature during the period from May to September in 2004 and 2005 (Fu et al. 2009). These results supported that the factors controlling the variation of ecosystem respiration were different at different time scales (Lin et al. 2011).

The negative responses of daily average ecosystem respiration to experimental warming for this alpine meadow in this study were consistent with some previous studies. For example, experimental warming tended to decrease soil respiration by 7~15% in a semiarid temperate forest-steppe ecosystem (Lellei-Kovács et al. 2008), and significantly reduced leaf dark respiration of Gentiana straminea on the Tibetan Plateau (Shen et al. 2009). In contrast, a meta-analysis of ecosystem warming experiments concluded that experimental warming significantly increased ecosystem respiration by 27% (Wu et al. 2011a). Additionally, some previous studies indicated that experimental warming did not change seasonal average ecosystem respiration in temperate and alpine grasslands (Lin et al. 2011; Xia et al. 2009). The different responses of ecosystem respiration to experimental warming among these studies could be dependent on the different relative strengths of the experimental warming-induced positive and negative effects (Wu et al. 2011b).

In our study, clipping tended to reduce daily average ecosystem respiration by 0.15 µmol CO2 m-

2 s-1 across all the 12 measuring dates. The negative effect was in line with previous studies (Bahn et al. 2008; Owensby et al. 2006; Polley et al. 2008). Clipping can not only directly reduce canopy respiration by removing the aboveground parts of plants, but also indirectly reduced soil respiration by reducing the input of labile carbon to soil (Bahn et al. 2006; Wan and Luo 2003).

Q10 value of ecosystem respiration was 2.3±0.2 (ranged 1.4~3.6) for the control plots in this study, which was lower than the reported results in alpine meadow ecosystem on the Tibetan Plateau (ranged 3.1~5.6) (Kato et al. 2004; Lin et al. 2011; Shi et al. 2006). This may be related to the fact that mean

Q10 value estimated by using air temperature was lower than that by using soil temperature (Wang et al. 2010). In contrast, the Q10 value of ecosystem respiration in our study was close to the reported range of 1.31~1.78 in semi-arid grasslands of Inner Mongolia (Nakano et al. 2008) and the range of 1.0~2.3 in an alpine shrubland on the Tibetan Plateau (Zhao et al. 2006).

The negative effect of experimental warming on the temperature sensitivity of ecosystem respiration was in accord with the reported result in Lin et al. (2011). This could be attributed to experimental warming-induced increment in soil and air temperatures and decrement in soil water content because Q10 value was negatively correlated with temperature but positively correlated with soil water content (Conant et al. 2004; Xu and Qi 2001; Zhou et al. 2007). Besides, many studies showed that experimental warming could reduce the temperature sensitivity of soil respiration (Luo et al. 2001; Zhou et al. 2006). Therefore, ecosystem and soil respiration may acclimate to climate warming (Luo et al. 2001).

4 Conclusions

In this study, we measured 12 daily change of ecosystem respiration under controlled experimental warming and clipping conditions in an alpine meadow of Tibet during three consecutive growing seasons of 2010-2012. Open top chambers were used to simulate climate warming. We found that experimental warming and clipping could not alter the dominated factors controlling the daily variation of ecosystem respiration. Experimental warming significantly or insignificantly decreased daily mean Reco by 0.12~0.88 µmol CO2 m-2 s-1 with an average of 0.45 µmol CO2 m-2 s-1, while clipping tended to reduce daily mean Reco by -0.21~0.77 µmol CO2 m-2 s-1 with an average of 0.15 µmol CO2 m-2 s-1. The temperature sensitivity of ecosystem respiration tended to be negatively correlated with experimental warming but positively correlated with clipping at daily time scale.

Acknowledgements

This work was funded by the National Natural

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Science Foundation of China (Grant Nos. 41171084 and 40771121), Innovation Project of the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (Grant No. 2012ZD005), the Natural Science Foundation of the Tibet Autonomous Region (Name. the Response Experiment of the Alpine Meadow Vegetation to Climate Warming), the National

Basic Research Program of China (Grant No. 2010CB951704) and the National Science and Technology Plan Project of China (Grant No. 2011BAC09B03). We thank the anonymous reviewers for their insightful and valuable comments which have greatly improve the quality of this manuscript.

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Please refer to the following examples for the reference

1. Book or monograph

Shrestha TB, Joshi RM (1996) Rare, endemic and endangered plants of Nepal. Kathmandu: WWF, Nepal Program. p 244. Hao F, Quan J, Yang ZS, et al. (2000) Land Resources of Yunnan, Kunming, China. Yunnan Science and Technology Press. pp 60-62. (In Chinese)

2. Thesis

DeConto RM (1996) Late Cretaceous Climate, Vegetation, and Ocean Interactions: an Earth System Approach to Modeling an Extreme Climate. PhD thesis, University of Colorado, Boulder, Colorado. p 10

3. Paper from a proceedings or monograph

Smaling EMA, Nandwa SS, Janssen BH (1997) Soil fertility in Africa is at stake. In: Buresh RJ et al. (eds.), Replenishing Soil Fertility in Africa. SSSA Special Publication No. 51. Wisconsin, USA. pp 47-61.

4. Paper from a serial publication

Kuhle M, Kuhle S (2010) Review on dating methods: numerical dating in the quaternary geology of high Asia. Journal of Mountain Science 7: 105-122. DOI: 10.1007/s11629-010-1116-1 Cui P, Hu KH, Zhuang JQ, et al. (2011) Debris flow discharge calculation and inundation simulation. Journal of Mountain Science 8: 1-9. DOI: 10.1007/s11629-011-2040-8

Specific guidelines for academic paper

An academic paper usually has no more than 50000 characters, including title, abstract, keywords, author’s address, reference, figures, tables and blank spaces, and with less than 5 figures and as few tables as possible. Title is usually required within 100 characters (including blank spaces). Abstract should be less than 3000 characters with no tables.

Academic papers usually contain no color photos and figures. The Editorial Office of the journal has right to use or not to use color photos and/or figures.

Author(s) must be responsible for checking and examining all the numerical values, written text, figures and tables and references, as well as non-English citation and names.

Specific guidelines for technical paper

The requirements for technical paper are basically same as those for academic paper, but a technical paper has less than 30000 characters; if it’s of more local significant, its techniques and methods should be easily reproduced. There is no regulation for written style, but it must be easy to understand and suitable for all readers in different fields and professions.

Manuscript Submission and Processing

All manuscripts have to be submitted online to the manuscript system at http://mc03.manuscriptcentral.com/jmsjournal. The authors can check their manuscript status online.

journal of mountain science

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