Ethanol outperforms multiple solvents in the extraction of chlorophyll-a from biological soil crusts

Short Communication

Shubin Lan a ,b ,Li Wu a ,b ,Delu Zhang a ,c ,Chunxiang Hu a ,*,Yongding Liu a

State Key Laboratory of Freshwater Ecology and Biotechnology,Institute of Hydrobiology,Chinese Academy of Sciences,Wuhan 430072,China b

Graduate School of Chinese Academy of Sciences,Beijing 100039,China c

Department of Biological Science and Biotechnology,Wuhan University of Technology,Wuhan 430070,China

a r t i c l e i n f o

Article history:

Received 8October 2010Received in revised form 2December 2010

Accepted 6December 2010

Available online 23December 2010Keywords:

Photoautotrophic biomass Extraction ef ?ciency Mass of sample

Development and succession Soil characteristics

a b s t r a c t

In order to estimate the biomass of photoautotrophic organisms in biological soil crusts (BSCs),based on the extraction and determination of phytoplanktonic chlorophyll-a (Chl-a )in aquatic ecosystems,this paper comparatively studied the Chl-a extraction ef ?ciencies in ethanol,acetone,N,N -dimethyl -formamide (DMF)and dimethyl sulphoxide (DMSO)from algae,lichen,and moss crusts,analyzed the effects of domi-nant organisms or development degree of BSCs,mass of sample,and soil characteristics on the extraction ef ?ciency.The results showed that the extraction ef ?ciencies of different organic solvents were signi ?cantly different,and such ef ?ciencies declined with the increase of mass of sample.DMSO resulted in the greatest extraction ef ?ciency,but was not suitable for lichen crusts;DMF strongly underestimated the Chl-a content of man-made crusts relative to the other extractants,and was particularly affected by interfering pigments from the well-developed crusts.Generally,the extraction ef ?ciency of ethanol was greater than that of acetone,and ethanol method showed the greatest stability compared with other 3solvents.In addition,Chl-a content showed an increasing trend with the succession of BSCs when it was expressed on an areal basis.On the basis of this and related experiments we suggest Chl-a content of BSCs be extracted by ethanol and expressed on an areal basis.

Biological soil crusts (BSCs),are manifest as a complex association of soil particles and organisms within the uppermost millimetres of the soil surface,and are distributed in arid and semiarid areas throughout the world.They are mainly composed of cyanobacteria,algae,bacteria,fungi,lichens,liverworts and mosses.BSCs play signi ?cant functional roles in desert ecosystems,such as accelerating soil formation,changing water and nutrient cycling rates,enhancing soil stability and thus preventing erosion by wind or water,in ?u-encing the establishment and performance of vascular plants,and also serving as habitats for dependent foodwebs (Eldridge and Greene,1994;Evans and Johansen,1999;Hu et al.,2002;Rao et al.,2009;Lan et al.,2010).In BSCs,algae (sensu lato ,including both eukaryotic algae and prokaryotic cyanobacteria),lichens,liverworts and mosses are all photoautotrophic organisms,and their biomass generally re ?ects the potential primary productivity,represents the ability to recovery from disturbance,and also relates to the degree of development and succession of the crusts.Therefore,reliable esti-mators of the crust photoautotrophic biomass are informative and

required.Although direct count and biovolume can directly re ?ect the biomass (Hu and Liu,2003;Langhans et al.,2009),extant tech-niques to obtain such data are tedious,labour-intensive,and may require specialized taxonomic knowledge.By contrast,the determi-nation of chlorophyll-a (Chl-a )content is a simple,fast and stable (i.e.typically less variable among replicates)method,and has been widely used in monitoring of phytoplankton and BSCs (e.g.Wright et al.,1997;Hawkes,2001;Bowker et al.,2002;Liu et al.,2008).However,it is dif ?cult to compare such Chl-a data between different studies,because ethanol (Chen et al.,2006;Xie et al.,2007),acetone (Tsujimura et al.,2000),DMF (Wang et al.,2007)and DMSO (Büdel et al.,2009;Langhans et al.,2009)have all been used as Chl-a solvents in such studies.The extraction ef ?ciencies of different solvents have been con ?rmed to be different in aquatic ecosystems (including the pure algae cultures;Shoaf,1976;Schumann et al.,2005;Li et al.,2006;Yang et al.,2007),but have not been adequately examined in BSCs or soils.Soil samples are far more complex than the water samples and pure cultures due to the vari-ance caused by soil texture,abundant pigments,humus,poly-saccharides,and especially the different dominant organisms (alga,lichen and moss possessing different pigments).We also hypothesize that the ideal organic solvent may differ with degree of development

*Corresponding author.Tel./fax:t862768780866.E-mail address:cxhu@https://www.360docs.net/doc/7515878440.html, (C.

Hu).

Contents lists available at ScienceDirect

Soil Biology &Biochemistry

journal h omepage:www.elsevier.co m/lo cate/soilb

Soil Biology &Biochemistry 43(2011)857e 861

or with the speci ?c type of BSC organism being examined.In this study our objectives were to comparatively analyze the ef ?ciencies of Chl-a extracted using different organic solvents from BSCs;to determine the effects of dominant organisms or development degree of BSCs,mass of sample,and soil characteristics on the extraction ef ?ciency.

Samples of BSCs were procured from Dalateqi Field Experiment Station of Institute of Hydrobiology (located at the eastern edge of Qubqi Desert,40 210N,109 510E)and Shapotou Desert Research and Experiment Station of the Chinese Academy of Sciences (located at the southeast fringe of Tengger Desert,37 320N,105 020E).We used both man-made crusts and natural crusts,representing 3different succession stages (algae,lichen and moss crusts dominated by algae,lichens and mosses respectively;Table 1).The man-made crusts were constructed with Microcoleus vaginatus Gom.and Scytonema javanicum (Kütz.)Born et Flah.,which were inoculated and cultured 45d on the shifting sand surface of Dalateqi.

The collected samples were ?rst air-dried in shade conditions,and then kept in desiccators.Before extraction of Chl-a ,all samples were ground with mortar and pestle,and ?ve subsamples of different masses (0.5,1,1.5,2and 3?0.05g)for each kind of BSCs were prepared for extractions with each of the four solvents,then the Chl-a contents were extracted and determined by ethanol,acetone (Chen and Gao,2000),DMF (Yang et al.,2007)and DMSO method (Hawkes,2001)respectively with an UV-1800Spectro-photometer (Shimazu,Japan).Three independent replicates were adopted in each instance.

We determined crust Chl-a contents according to published spectrophotometry (Chen and Gao,2000;Hawkes,2001;Yang et al.,2007),then compared the results obtained by different solvents to determine their extraction ef ?ciency.Variance of Chl-a extraction ef ?ciencies was analyzed using one-way Analysis of Variance (ANOVA)taking the 95%signi ?cance level.Correlations between Chl-a extraction ef ?ciency and mass of sample was analyzed using Bivariate Correlations.Data variation among different masses of sample was indicated by the subset numbers of Student-Newman e Keuls ’(SNK)test.All data analyses were carried out using SPSS 13.0software.In addition,we derived a ‘Chl-a vari-ation index ’(CVI)to evaluate the variation of Chl-a content caused by the two factors:extraction solvent and developmental level,the higher the CVI,the greater the variation.In a certain study region,CVI associate with extraction solvent was calculated by formula CVI s ?C i /C j ,where the CVI s was CVI arisen from extraction solvent;C i was the greatest Chl-a content obtained from the extraction solvent i;C j was the lowest one obtained from the extraction solvent j in the same type of BSCs.CVI associate with develop-mental level was calculated by formula CVI d ?C l /C e ,where the CVI d was CVI arisen from developmental level;C l was the greatest Chl-a content occurring in later developmental BSCs;C e was the lowest one in early developmental BSCs,extracted with the same solvent.

In all crusts,Chl-a extraction ef ?ciencies between the different organic solvents showed signi ?cant differences (P <0.001,Fig.1),which was also found in a study by Castle et al.(2010).Among 4solvents,DMSO resulted in the greatest extraction ef ?ciency,but it was not suitable for lichen crusts,in which the abnormally high values appeared.This may have been due to the substantial

Table 1

The characteristics of biological soil crusts in the experiment.Crust types

Man-made

crusts (Dalateqi)Algae crusts in Dalateqi Moss crusts in Dalateqi Algae crusts in Shapotou Lichen crusts in Shapotou Moss crusts in Shapotou Ages

45d 7a 7a 11a 45a 45a Alga cover (%)100100010034.60Lichen cover (%)000065.40Moss cover (%)0010000100Thickness (mm)

1.48 4.369.05 4.73 6.2614.54Bulk density (g cm à3) 1.54 1.34 1.01 1.53 1.20 1.04Sand (%)99.5084.4568.2585.3158.0553.72Silt (%)0.331

2.5922.5912.7635.3535.69Clay (%)

0.17

2.96

9.16

1.93

6.60

10.59

a a a a

b b a

a b c

5 10 15 20 25 30 35 40 45

Man-made crusts

- l h C f o t n e t n o C a g g μ ( 1

- )

DMF method

DMSO method

B A a a a b

15 20

Algae crusts

- l h C f o t n e t n o C a g g μ ( 1 - )

Ethanol method

Acetone method Moss crusts

Algae crusts

Moss crusts

Lichen crusts

Fig.1.Chl-a content extracted by different methods in biological soil crusts in Dalateqi (A)and Shapotou (B).The bars indicate the standard errors of the means (n ?3).The values with different letters are signi ?cantly different at 0.05level (P <0.05);*indicates the abnormal value (omitted).

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proportion of co-extractable pigments in the lichen crusts.The ef ?ciency of DMF was just lower than that of DMSO in natural crusts,but was the lowest in man-made crusts.That implies that DMF not only has a low extraction ef ?ciency,but also the ef ?ciency is easily affected by the interfering pigments of well-developed crusts.With regard to ethanol and acetone,their extraction ef ?-ciencies were similar to the results of Chen and Gao (2000),Wasmund et al.(2006)and Yang et al.(2007)in water bodies and pure cultures.The ef ?ciency of ethanol was higher than that of acetone.Roijackers (1981)also suggested ethanol had several advantages over acetone as an extractant (e.g.requiring a short extraction period and cheaper procedure),although the acetone-based method had a higher extraction ef ?ciency in his study.

We also found spectral characteristics of DMSO in lichen crusts were abnormal (Fig.2B),occurring abnormally high value at 665nm comparing with the other 3solvents.In addition,Fig.2showed Chl-a had absorption peaks at about 430nm and 665nm,and the highest values at 665nm all occurred in DMSO-extracted samples,the lowest values in Ace-extracted samples

(0.7g sample in 10mL solvents).From the curve shape,the char-acteristic peaks of Fig.2(A)and (C)were obvious,while the absorption peaks at about 430nm in Fig.2(B)were not so.

Mass of sample and soil characteristics also were potential factors affecting the Chl-a extraction ef ?ciencies.In the 6crusts,the correlations between Chl-a extraction ef ?ciency and mass of sample are shown in Table 2.We found that there was a negative correlation between the extraction ef ?ciency and mass of sample and the correlation was signi ?cant (P <0.05)in 87.5%cases.That means the extraction ef ?ciency declined with the increase of mass of sample,which may be due to the increasing interference of humus,polysaccharide and clay.In these situations,we would possibly underestimate the Chl-a content in the crusts.On the other hand,the Chl-a content also would possibly be overestimated because of some co-extractable pigments (e.g.lichen pigments)and pigments from vascular plant litter (Tsujimura et al.,2000).In addition,among the 4solvents,the extraction ef ?ciency of ethanol was the most stable,because it displayed the least data variation among different masses of sample.SNK test showed that the extraction ef ?ciency of ethanol was in homogeneous subset in man-made crusts,algae crusts in both Dalateqi and Shapotou,in two subsets in moss crusts of Shapotou,and in three subsets in moss crusts of Dalateqi and lichen crusts of Shapotou among different masses of sample (Table 3).In addition to the stability of estimates derived form ethanol extraction,ethanol has the addi-tional advantage of being non-toxic.

In the Shapotou site,algae,lichen,and moss crusts represented 3distinct successional stages.In contrast,in Dalateqi no lichen crusts were found.Rather algae crusts developed to moss crusts directly in some microhabitats.Thus the collected samples in this part of experiment had 3successional seres from Shapotou and

Fig.2.The absorption spectra of algae crusts (A),lichen crusts (B)and moss crusts (C)in four methods (from Shapotou).j denotes the absorption peaks of Chl-a at about 430nm and 665nm.

Table 2

Correlation analysis between the Chl-a extraction ef ?ciency and mass of sample.The correlation coef ?cients (R )and their signi ?cances (P )between the Chl-a extraction ef ?ciency and mass of sample are shown in following tables.

Ethanol method

Acetone method DMF method DMSO method Man-made crusts R à0.317a à0.974à0.714à0.555P 0.249<0.0010.0030.039Algae crusts in Dalateqi R à0.710à0.849à0.708à0.749P 0.003<0.0010.0030.001Moss crusts in Dalateqi R à0.906à0.842à0.775à0.901P <0.001<0.0010.001<0.001Algae crusts in Shapotou R à0.582à0.801à0.376à0.172P 0.023<0.0010.2280.574Lichen crusts in Shapotou R à0.774à0.776à0.904à0.945P 0.0010.001<0.001<0.001Moss crusts in Shapotou

R à0.674à0.788à0.916à0.783P

0.006

<0.001

0.007

The negative correlation between the extraction ef ?ciency and mass of sample means the extraction ef ?ciency declines with the increase of mass of sample.

Table 3

Student-Newman e Keuls ’(SNK)test of effects of mass of sample on Chl-a extraction ef ?ciency.Subset numbers of SNK test are shown in following tables.

Ethanol method

Acetone method DMF method DMSO method Man-made crusts

1a 511Algae crusts in Dalateqi 1222Moss crusts in Dalateqi 3225Algae crusts in Shapotou 1212Lichen crusts in Shapotou 3245Moss crusts in Shapotou

The subset number of SNK test indicates the variation of Chl-a extraction ef ?-ciency among different masses of sample,the higher the number,the greater the variation.

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from Dalateqi.The results showed that when it was expressed on a per area basis,Chl-a content ranged from70.3to470mg mà2and always showed an increasing trend over the course of succession of BSCs.When expressed on a per mass basis this range was from12.2 to36.2m g gà1and no difference was observed between the lichen and moss crusts in Shapotou(Fig.3).This was due to the obvious increase of crust thickness in moss crusts(about 2.3times comparing with lichen crusts),but the increase of photosynthetic biomass in per area did not relate to the increase of thickness.Therefore,we suggest Chl-a content of BSCs be expressed on an areal basis taking account of the wide variation of crust thickness, which is mainly due to the crust itself development and succession, and also may be to the arti?cial sampling difference.

Compared to other studies in Asia,Africa,Europe,America and Australia(Table4),we found the Chl-a content of BSCs was highly variable.So far as we know,Zaady et al.(2010)reported the highest Chl-a content of5900mg mà2in the Northwestern Negev Desert (Egyptian-Israeli border).The lowest content,6.3mg mà2,

was

Shapotou Dalateqi

(

)

100

200

300

400

500

Shapotou Dalateqi

(

)

A B

Algae crusts

Lichen crusts

Moss crusts

Algae crusts

Lichen crusts

Moss crusts

Fig.3.Changes of Chl-a content in different successional stages of biological soil crusts(based on the ethanol method).Data in(A)expressed on a per mass basis and in(B)on a per area basis.The bars indicate the standard errors of the means(n?3).The values with different letters are signi?cantly different at0.05level(P<0.05).

Table4

Reports of Chl-a data in biological soil crusts.

Locations Crust types Chl-a contents References Extraction solvents Dalateqi,Qubqi Desert,China Algae and moss crusts10.67e50.45m g g This study DMSO

Dalateqi,Qubqi Desert,China Algae and moss crusts11.19e38.46m g gà1This study DMF

Dalateqi,Qubqi Desert,China Algae and moss crusts10.62e39.70m g gà1This study Ethanol

Dalateqi,Qubqi Desert,China Algae and moss crusts7.89e32.42m g gà1This study Acetone Shapotou,Tengger Desert,China Algae,lichen and moss crusts17.54e22.56m g gà1This study DMSO Shapotou,Tengger Desert,China Algae,lichen and moss crusts12.53e20.53m g gà1This study DMF

Shapotou,Tengger Desert,China Algae,lichen and moss crusts11.43e19.80m g gà1This study Ethanol Shapotou,Tengger Desert,China Algae,lichen and moss crusts8.22e15.94m g gà1This study Acetone

Dalateqi,Qubqi Desert,China Algae and moss crusts68.91e475.37mg mà2This study Ethanol

Shapotou,Tengger Desert,China Algae,lichen and moss crusts86.61e266.16mg mà2This study Ethanol Northwestern Inner Mongolia,China Algae crusts97?82mg mà2Garcia-Pichel et al.(2003)a Unknown Transect,Mongolia Algae crusts22?175mg mà2Garcia-Pichel et al.(2003)a Unknown

Different regions of India Algae crusts121e284m g gà1Tirkey and Adhikary(2005)Methanol

Different regions of India Algae crusts248e282mg mà2Tirkey and Adhikary(2005)Methanol

North central region of Oman Algae crusts0.5e1m g gà1Abed et al.(2010)Acetone

Negev Desert,Israel Algae and moss crusts17e53mg mà2Kidron et al.(2000)Unknown Northwestern Negev Desert,

Egyptian-Israeli border

Algae,lichen and moss crusts1400e5900mg mà2Zaady et al.(2010)Ethanol Southwestern region of Africa Algae,lichen and moss crusts20e160mg mà2Büdel et al.(2009)DMSO

Serengeti,Africa Algae crusts58?44mg mà2Garcia-Pichel et al.(2003)a Unknown

Sahel Desert,Niger Algae crusts41e57mg mà2Issa et al.(2001)Unknown

Bardena Blanca,Spain Algae crusts39?25mg mà2Garcia-Pichel et al.(2003)a Unknown

Sand ecosystems of Darmstadt,

Darmstadt,Germany

Algae and moss crusts16.6e28.8m g gà1Langhans et al.(2009)DMSO

Sand ecosystems of Darmstadt,

Darmstadt,Germany

Algae and moss crusts82.9e114.0mg mà2Langhans et al.(2009)DMSO

Hell’s Canyon National Recreation Area,

HCNRA,U.S.A.

Algae,lichen and moss crusts 1.61e3.71m g gà1Bowker et al.(2004)Acetone Canyonlands National Park,Utah,U.S.A.Algae,lichen and moss crusts7.58e23.42m g gà1Bowker et al.(2002)Acetone

Colorado Plateau,Utah,U.S.A.Algae and lichen crusts 2.26e10.1m g gà1Barger et al.(2005)Acetone

Arches National Park,Utah,U.S.A.Algae crusts 6.3e31.6mg mà2Garcia-Pichel and Belnap(1996)Acetone

San Nicolas,California,U.S.A.Algae crusts151?98mg mà2Garcia-Pichel et al.(2003)a Unknown

Holloman New Mexico,U.S.A.Algae crusts33?49mg mà2Garcia-Pichel et al.(2003)a Unknown

Jornada New Mexico,U.S.A.Algae crusts273?157mg mà2Garcia-Pichel et al.(2003)a Unknown

Lower Sonoran,Desert,Arizona U.S.A.Algae crusts20?13mg mà2Garcia-Pichel et al.(2003)a Unknown

Central Australia Algae crusts130e169mg mà2Lange(2001)a Unknown

Lake Mere,Australia Algae crusts89?70mg mà2Garcia-Pichel et al.(2003)a Unknown

a The algae crusts in the reports of Lange(2001)and Garcia-Pichel et al.(2003)may include some cyanolichens.

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860

shown by Garcia-Pichel and Belnap(1996)in samples from Arches National Park in Utah.The huge variation is mostly attributed to the different crust types in the different sampling zones,including some difference arisen by arti?cial operation.However,in the same research region,the variation of Chl-a content we think is mainly caused by the developmental levels or successional stages of crusts and the extraction methods.When the other factors were left out of account,comparing the collected and our data,we found the developmental levels or successional stages of crusts accounted for 68.8?37.7%of the variation(CVI d was3.38? 1.85),and the difference of extraction solvents for31.2? 3.31%(CVI s was 1.53?0.16).In addition,the variation may also be due to the interfering materials and sampling time.It has been veri?ed that photosynthetic biomass of BSCs could?uctuate widely in response to seasonal changes in temperature and moisture(Bowker et al., 2002;Barger et al.,2005;Belnap et al.,2006);as well as may be due to the storage conditions,e.g.dry or not,deepfreeze or not, length of storage,etc.

Acknowledgements

We gratefully acknowledge Matthew A.Bowker(Colorado Plateau Field Station,US Geological Survey,Flagstaff,Arizona,USA) for his valuable comments and careful corrections.This study was supported by the National Natural Science Foundation of China (30870470),National Principal Expert Program(2008ZX07103-004;2009ZX07106-001-003;2009ZX07210-009;2008ZX07103-007),and partly by Wuhan Science and Technology Bureau and Inner Mongolia Planning Committee on high-tech industrialization. References

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