Open Access

A bibliometric analysis of global forest ecology research during 2002–2011

SpringerPlus20132:204

DOI: 10.1186/2193-1801-2-204

Received: 4 February 2013

Accepted: 16 April 2013

Published: 2 May 2013

Abstract

Bibliometric is increasingly used for the analysis of discipline dynamics and management related decision-making. This study analyzes 937,923 keywords from 78,986 articles concerning forest ecology and conducts a serial analysis of these articles’ characteristics. The articles’ records, published between 2002 and 2011, were downloaded from the Web of Science, and their keywords were exported by Java processing programs. The result shows that forest ecology studies focused on forest diversity, conservation, dynamics and vegetation in the last decade. Developed countries, such as the USA, Canada, and Germany, were the most productive countries in the field of forest ecology research. From 2002 to 2011, the number of articles published annually related to forest ecology grew at a stable rate, as indicated by the fit produced by a high determination coefficient (R2 = 0.9955). The findings of this study may be applicable for planning and managing forest ecology research and partners involved in such research may use this study as a reference.

Keywords

Article analysis Bibliometric Forest ecology Java Keyword frequency analysis

Introduction

Bibliometric analysis is an important part of reference and research services. Forest ecology is closely related to forest management and many studies have been performed from various perspectives, including studies of ecosystems at multiple forest spatial scales (Rodrigues et al. 2011;Sitzia et al. 2010), long term ecosystem change (Diaz et al. 2007;van Oudenhoven et al. 2012), climate change (Cheaib et al. 2012; Şekercioğlu et al.2012), soils (McLachlan and Bazely2003; Wang et al.2011), physiography (Morrissey et al.2009; Rubio and Escudero2005), carbon balance (Mitchell et al.2009; Sillett et al.2010), nutrient cycling (Berger et al.2009; XU and Chen2006), landscape ecology (Loucks et al.2001; Wintle et al.2005) and biodiversity (Hanberry et al.2012; Lamb et al.2005). In addition to these studies, a bibliometric analysis of global forest ecology could provide a fresh look at the current status of global forest ecology research and help identify hot spots.

In recent years, along with its continuously expanding range of application, bibliometric analysis plays an increasingly important role in management and decision-making in science and technology. It has been used to document the development of some research fields (Grandjean et al.2011; Hendrix2008; Narotsky et al.2012; van Eck et al.2010; van Raan2006), including forestry (Dobbertin and Nobis2010; Perez et al.2004).

In this study, we perform a bibliometric analysis of forest ecology research over the last 10 years (2002–2011) aimed at (1) examining the temporal hot topics of forest ecology research by keyword frequency analysis, (2) revealing the distribution of articles by country/region, organization, funding agency, research area, author, year and publication name for articles covering forest ecology research and revealing advancements in forest ecological research, and (3) providing a new keywords frequency analysis method, which may benefit future research.

Materials and methodology

Data collection

Literature records, our analytical objects, were derived from the Web of Science, an online academic citation index database provided by Thomson Reuters. To define search terms, we used the “thesaurus” tool of Commonwealth Agricultural Bureaux (CAB) Abstracts.

We conducted a search on the word “ecology” in CAB Abstracts and the search produced 41 terms, including 19 narrower terms and 22 other related terms (Figure 1). We selected terms with more than 200 hits and used Microsoft Excel to rank them in descending order. We then removed the words “ecology” and “forest” from the Excel sheet and added the terms “climate,” “soils,” “physiography,” “carbon balance” and “nutrient cycling,” based on the concepts related to forest ecology defined by Barnes et al. (1997). Then, we defined the remaining 43 search terms and constructed a new search query. The search was limited to “article” type publications published between 1 January 2002 and 31 December 2011 in English.
https://static-content.springer.com/image/art%3A10.1186%2F2193-1801-2-204/MediaObjects/40064_2013_Article_258_Fig1_HTML.jpg
Figure 1

Narrower terms and 22 related terms of ecology.

The search query included 43 terms (see Appendix A). This query was run in Web of Science, which is a citation database of the Web of Knowledge, and a total of 78,986 forest ecology-related articles were identified.

Using the Web of Science’s analysis tools, we exported the 78,986 articles by country/region, organization, funding agency, research area, author, year, and publication. The statistical methods used by the Web of Science for the above statistical indicators of multi-author articles do not distinguish between the order of author’s locations, which may result the sum of these statistical result was greater than 78,986. The article records, including title, author, keywords, abstract, and organization, were exported in full record mode from the Web of Science to text files. A total of 158 text files were created, because the Web of Science limits each export to 500 records. In every text file, “author keywords” were marked by “DE,” and “keywords plus” were provided by the Web of Science and marked by “ID”. Both these two kinds of keywords were considered in this study.

Keywords analysis

First, the frequency of each keyword was counted in each text file. We developed a java program named count.java (Additional file 1: Appendix B) using Eclipse software, a famous cross-platform integrated development environment. This java program can find and select keywords in the output text file by identifying parameters, and connect each keyword to a long string, while deleting the carriage returns. After detection, the keywords in the string were split by semicolons, and counted using HashMap traversal algorithm. The HashMap traversal result was saved to an array and sorted by the counters; then, the sorted result was exported to an intermediate file.

Second, the 158 intermediate files were merged, and the frequency of each keyword was counted. We developed a java program named merge.java (Additional file 1: Appendix C) using Eclipse software. When this program was run, the intermediate files defined in the input parameters were opened, and the keywords and their counters were saved to a HashMap. Then the keywords were counted again with HashMap traversal algorithm: the counters of the same keywords were added. Then, the HashMap traversal result was saved to an array, sorted by the counters, and exported into a result file.

Third, we developed a program (Additional file 1: Appendix D) to create a java package named frequency.jar to store the compiled java class files which were produced by compiling count.java and merge.java.

Fourth, we developed a batch program named count.bat (Additional file 1: Appendix E) to call the count.class with the input parameters “DE” and “ID”. All 158 text files were processed one by one. As a result, 158 intermediate files were created.

Fifth, we developed another batch program named merge.bat (Additional file 1: Appendix F) to call the merge.class with the input parameters, that is, the 158 intermediate files, to merge them. As a result, a final file was created, in which all keywords in 78,986 articles were counted and sorted.

After data processing, 937,923 keywords from those 78,986 articles were merged into 150,974 keywords. All of the keywords were sorted in reverse order based on their frequencies. The 100 most frequently used keywords became the focus of our study.

Results

Keywords analysis results

To narrow the research scope, the 100, 200, 300 most frequently used keywords were selected and analyzed. As a result, the 100 most frequently used keywords, 0.07% of the 150,974 unique keywords analyzed here represented 18.54% of the total (937,923) of all keywords harvested (Table 1). We focused on the top 100 keywords to examine the hot topics of forest ecology research (Table 2).
Table 1

The top 100, 200, 300 keyword ratio and their frequencies

Keywords number

Keywords ratio

Keywords frequencies

Frequencies Ratio (%)

100

0.07%(100/150974)

173925

18.54%(173925/937923)

200

0.13%(200/150974)

233042

24.85%(233042/937923)

300

0.20%(300/150974)

271233

28.92%(271233/937923)

Table 2

The top 100 keywords in forest ecology articles indexed using the Web of Science during 2002–2011

 

Keywords

Frequencies

1

forest

9302

2

diversity

5424

3

conservation

5135

4

dynamics

4886

5

vegetation

4720

6

biodiversity

4613

7

patterns

4166

8

growth

4069

9

rain-forest

3253

10

management

3236

11

nitrogen

3136

12

forests

3069

13

soil

2793

14

ecology

2677

15

communities

2596

16

carbon

2568

17

climate-change

2412

18

ecosystems

2407

19

disturbance

2389

20

species richness

2381

21

boreal forest

2334

22

landscape

2180

23

biomass

2130

24

model

2100

25

climate

2095

26

fire

2043

27

abundance

1855

28

united-states

1849

29

habitat

1846

30

temperature

1824

31

plants

1782

32

organic-matter

1755

33

populations

1733

34

decomposition

1603

35

climate change

1599

36

dispersal

1590

37

responses

1576

38

regeneration

1531

39

tropical forest

1513

40

land-use

1509

41

habitat fragmentation

1495

42

trees

1486

43

fragmentation

1473

44

forest soils

1441

45

evolution

1408

46

succession

1384

47

deforestation

1375

48

ecosystem

1362

49

birds

1333

50

population

1276

51

competition

1273

52

water

1235

53

variability

1210

54

deciduous forest

1190

55

forest management

1189

56

community structure

1178

57

behavior

1140

58

community

1131

59

restoration

1127

60

tropical forests

1107

61

photosynthesis

1093

62

seed dispersal

1081

63

usa

1067

64

productivity

1054

65

microbial biomass

1040

66

density

1034

67

impact

1019

68

brazil

1018

69

models

988

70

carbon-dioxide

978

71

phosphorus

971

72

size

971

73

predation

947

74

classification

943

75

respiration

932

76

scale

927

77

drought

920

78

national-park

918

79

plant

910

80

selection

909

81

tree

902

82

deposition

889

83

history

888

84

recruitment

875

85

norway spruce

874

86

soil respiration

870

87

australia

868

88

consequences

864

89

tropical rain-forest

839

90

survival

834

91

quality

830

92

mexico

819

93

costa-rica

813

94

impacts

812

95

new-zealand

796

96

forest soil

794

97

mortality

788

98

soils

787

99

grassland

786

100

assemblages

785

Articles analysis result

By country/region

The 78,986 articles were analyzed by countries or regions and sorted in reverse order by their total numbers and Table 3 lists the results for the top 20 countries. We supplemented a column in the original table and classified these 20 countries/regions by their respective continents, which showed that North America and 12 European countries had about 44.71% and 42.35% of all the articles, respectively, indicating published articles related to forest ecology in North America and Europe predominate.
Table 3

Top 20 countries/regions publishing articles on forest ecology indexed using the web of science during 2002–2011

 

Countries/Regions

Records

Ratio (%)

Continents

1

USA

28060

35.53

North America

2

Canada

7255

9.19

North America

3

Germany

6311

7.99

Europe

4

Brazil

4561

5.77

Africa

5

Australia

4375

5.54

Australia

6

England

4229

5.35

Europe

7

Peoples R China

4122

5.22

Asia

8

France

3930

4.98

Europe

9

Japan

3504

4.44

Asia

10

Spain

3402

4.31

Europe

11

Sweden

2708

3.43

Europe

12

Finland

2417

3.06

Europe

13

Italy

2230

2.82

Europe

14

Netherlands

1921

2.43

Europe

15

Switzerland

1871

2.37

Europe

16

India

1798

2.28

Asia

17

Mexico

1572

1.99

South America

18

Russia

1554

1.97

Europe

19

Scotland

1455

1.84

Europe

20

New Zealand

1421

1.80

Europe

The combined frequency of keywords related to tropical forest, represented by “rain-forest” (3,253), “tropical forest” (1,513), “tropical forests” (1,107), and “tropical rain-forest” (839), totaled 6,712 keyword entries, which was exceeded only by the keyword “forest” with 9,302 entries (Table 2). This indicates that tropical forest was the main focus of research in forest ecology studies. Tropical forest is mainly distributed in Southeast Asia, Central America, South America, Australia, Africa. However, the main countries with strong research capabilities related to tropical forest research were not located in those areas, but were found in North America and Europe.

By organization

Forest ecology studies were conducted by 7,598 organizations, and Table 4 lists the top 20 organizations and their related countries. The University of California System, the Chinese Academy of science, and US Forest Service produced the most articles. Eight organizations were from the USA, two each from Canada, Brazil, and Germany, and the remaining six were from China, Sweden, Finland, Russia, Spain, and France.
Table 4

Top 20 organizations publishing articles on forest ecology indexed using the web of science during 2002–2011

 

Organizations

Records

Ratio (%)

Counties

1

Univ Calif System

2749

3.48

USA

2

Chinese Acad SCI

2359

2.99

China

3

US Forest Serv

2203

2.79

USA

4

Swedish Univ Agr SCI

1342

1.70

Sweden

5

Oregon State Univ

1200

1.52

USA

6

Univ Helsinki

1055

1.34

Finland

7

Univ British Columbia

1008

1.28

Canada

8

Univ Wisconsin System

978

1.24

USA

9

Univ Alberta

973

1.23

Canada

10

Russian Acad SCI

925

1.17

Russia

11

Univ Florida

905

1.15

USA

12

USDA

905

1.15

USA

13

Univ Sao Paulo

896

1.13

Brazil

14

US Geol Survey

883

1.12

USA

15

Univ Fed Santa Maria

868

1.10

Brazil

16

Smithsonian Inst

867

1.10

USA

17

Max Planck Society

808

1.02

Germany

18

Univ Gottingen

785

0.99

Germany

19

INRA

771

0.98

France

20

CSIC

766

0.97

Spain

USDA United States department of agriculture, INRA Institut National de la recherche agronomique, CSIC consejo superior de investigaciones científicas.

By funding agency

6,356 funding agencies subsidized forest ecology studies, and the top 20 were exported for closer analysis. Because many articles used abbreviations for the funding agencies the top 20 were merged into 15 (Table 5). Examples include the National Science Foundation (NSF), the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), the European Union (EU), and the Natural Sciences and Engineering Research Council of Canada (NSERC).
Table 5

The 15 most productive agencies funding forest ecology research indexed by the web of science during 2002–2011

 

Funding agencies

Articles number

Ratio (%)

Countries

1

National Science Foundation

2240

2.84

USA

2

National Natural Science Foundation of China

831

1.05

China

3

Natural Sciences and Engineering Research Council of Canada

807

1.02

Canada

4

CNPq

744

0.94

Brazil

5

European Union

601

0.76

EU

6

Chinese Academy of Sciences

372

0.47

China

7

NASA

357

0.45

USA

8

European Commission

337

0.43

EC

9

Academy of Finland

311

0.39

Finland

10

Australian Research Council

265

0.34

Australia

11

CAPES

221

0.28

Brazil

12

National Basic Research Program of China

196

0.25

China

13

FAPESP

192

0.24

Brazil

14

Russian Foundation for Basic Research

185

0.23

Russia

15

USDA Forest Service

172

0.22

USA

CNPQ: Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil; NASA: National Aeronautics and Space Administration, USA; CAPES: Coordenação de Aperfeiçoamento de Pessoal de Nivel Superior, Brazil; FAPESP: Fundação de Amparo à Pesquisa do Estado de São Paulo, Brazil; EC: European Commission.

The National Science Foundation (USA), National Natural Science Foundation of China (China), Natural Sciences and Engineering Research Council of Canada (Canada), Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brazil), and European Commission were more prolific in forest ecology than other funding agencies. Combining the number of articles in Table 5 by country/region demonstrates that the USA (2,769), China (1,399), Brazil (1,157), Canada (807), and EU (601) were also the top five countries/regions and provided more financial aid to forest ecology research than other countries.

By research area

In the analysis, forest ecology was related to 72 research areas identified by the Web of Science data. Table 6 lists the top 20 research areas and clearly shows that forest ecology studies were related to a wide range of disciplines. Environmental sciences ecology (31,172 or 39.47% of all articles), forestry (13,164, 16.67%), agriculture (8,354, 10.58%), and plant sciences (8,027, 10.16%) were the top four major related research areas.
Table 6

The top 20 research areas related to forest ecology indexed using the web of science during 2002–2011

 

Research areas

Articles number

Ratio (%)

1

Environmental Sciences Ecology

31172

39.47

2

Forestry

13164

16.67

3

Agriculture

8354

10.58

4

Plant Sciences

8027

10.16

5

Zoology

6470

8.19

6

Biodiversity Conservation

6005

7.60

7

Geology

5660

7.17

8

Meteorology Atmospheric Sciences

3654

4.63

9

Physical Geography

3453

4.37

10

Water Resources

2521

3.19

11

Marine Freshwater Biology

2271

2.88

12

Entomology

2176

2.76

13

Engineering

1981

2.51

14

Life Sciences Biomedicine Other Topics

1650

2.09

15

Evolutionary Biology

1631

2.07

16

Remote Sensing

1611

2.04

17

Science Technology Other Topics

1319

1.67

18

Biochemistry Molecular Biology

1269

1.61

19

Imaging Science Photographic Technology

1205

1.53

20

Genetics Heredity

1079

1.37

By author

A total of 48,373 authors participated in forest ecology related studies. Among the 20 authors publishing the most articles, five were from the USA, four were from Canada, and two each were from Belgium, Finland, and England (Table 7).
Table 7

The 20 most productive authors of research papers related to forest ecology indexed using the Web of Science during 2002–2011

 

Authors

Authors’ countries

Articles number

Ratio (%)

1

Bergeron Y

Canada

146

0.19

2

Kulmala M

Finland

123

0.16

3

Hermy M

Belgium

114

0.14

4

Lindenmayer DB

Australia

110

0.14

5

Black TA

Canada

103

0.13

6

Coops NC

Canada

95

0.12

7

Asner GP

USA

91

0.12

8

Verheyen K

Belgium

91

0.12

9

Reich PB

USA

87

0.11

10

Penuelas J

Spain

85

0.11

11

Vesala T

Finland

85

0.11

12

Leuschner C

Germany

81

0.10

13

Peres CA

England

81

0.10

14

Chen JM

Canada

80

0.10

15

Ciais P

France

80

0.10

16

Groffman PM

USA

79

0.10

17

Law BE

USA

78

0.10

18

Malhi Y

England

78

0.10

19

Fahey TJ

USA

77

0.10

20

Yu GR

China

77

0.10

By year

From 2002 to 2011, the annual number of published articles about forest ecology was growing at a stable rate (Table 8), as the fit produced a high determination coefficient from the collected data (R2 = 0.9955). The best fit for forest ecology was found to be: y = 629.75x – 1.2557exp + 06, where y is the article number and x is the number of years since 2002. Extrapolating from the model, the number of articles about forest ecology in the following years could be forecasted (Figure 2).
Table 8

Annual number of articles on forest ecology indexed using the Web of Science during 2002–2011

 

Years

Articles number

Ratio (%)

1

2002

5245

6.64

2

2003

5729

7.25

3

2004

6250

7.91

4

2005

6816

8.63

5

2006

7555

9.57

6

2007

8098

10.25

7

2008

8970

11.36

8

2009

9311

11.79

9

2010

10096

12.78

10

2011

10915

13.82

https://static-content.springer.com/image/art%3A10.1186%2F2193-1801-2-204/MediaObjects/40064_2013_Article_258_Fig2_HTML.jpg
Figure 2

A linear relationship between articles number and years during 2002-2011.

By publication

The number of journals publishing forest ecology related articles each year increased from 430 in 2002 to 856 in 2011. Table 9 shows the top 20 major journals indicating that Forest Ecology and Management (3,876, 4.91%) was the top journal on forest ecology by article count, followed by Canadian Journal of Forest Research (1,399, 1.77%) and Biological Conservation (1,399, 1.77%).
Table 9

The top 20 journals related to forest ecology analyzed using the Web of Science during 2002–2011

 

Publications

Articles number

Ratio (%)

1

Forest Ecology and Management

3876

4.91

2

Canadian Journal of Forest Research

1399

1.77

3

Biological Conservation

933

1.18

4

Soil Biology Biochemistry

929

1.18

5

Biodiversity and Conservation

928

1.18

6

Global Change Biology

824

1.04

7

Ecology

750

0.95

8

Oecologia

741

0.94

9

Biotropica

666

0.84

10

Plant and Soil

653

0.83

11

Ecological Applications

636

0.81

12

Plant Ecology

614

0.78

13

Ecological Modeling

599

0.76

14

Remote Sensing of Environment

598

0.76

15

Argicultural and Forest Meteorology

589

0.75

16

Journal of Tropical Ecology

543

0.69

17

Journal of Geophysical Research Atmospheres

523

0.66

18

Conservation Biology

516

0.65

19

Journal of Biogeography

510

0.65

20

Tree Physiology

508

0.64

Discussion

The results of this study pointed to several significant hotspots in global research related to forest ecology based on an analysis of article keywords for articles published during 2002–2011, and revealed the distribution of the articles from seven aspects listed above. The keyword analysis method and the java analysis program could be extended to other related research fields.

In the keywords analysis, we presumed that a keyword appeared only once in the keywords list of an article (Campbell1963). Therefore the frequency of a keyword could show the number of articles that had used this keyword. For example, the frequency of “forest” was 9,302, meaning that 9,302 articles had used “forest” as a keyword in 73,740 articles.

It was undisputed that “forest” was the most frequently used keyword (9,302 articles). Most writers used this word to express the concept of “forest” instead of its plural “forests”; therefore, “forest” appeared in articles three times more than “forests” (3,069). The next four most frequently used words were “diversity” (5,424), “conservation” (5,135), “dynamics” (4,886), and “vegetation” (4,720) indicating forest diversity, forest conservation, forest dynamics and forest vegetation were the focus of forest ecological studies.

The frequency of “patterns” (4,166), “model” (2,100), and “models” (988) demonstrated that these words were widely used in forest developmental pattern and model studies. The keywords “management” (3,236), “ecology” (2,677), “ecosystems” (2,407), and “ecosystem” (1,362) were also frequently used in macro research (9,682 times), accounting for 1.03% in all keywords indicating large numbers of studies had been carried out in these aspects of forest research in last ten years.

USA” (2,916), “Brazil” (1,018), “Australia” (868), “Mexico” (819), “Costa Rica” (813) and “New Zealand” (796) appeared more frequently than the names of other countries showing that many studies focused on those countries. During the early twenty-first century, the warm droughts in the United States, Europe and Australia have been recognized as a considerable change from the climatological conditions and variability of the late twentieth century (Dai2011), and the focus of forest ecology studies in those regions were impacted accordingly. From a regional point of view, we can see that the total frequencies of “rain-forest” (3,253), “tropical forests” (1,107), and “tropical forest” (1,513) were 5,873, 2.5 times more frequent than “boreal forest” (2,334), indicating that forest ecology studies concerning tropical forests were produced more frequently than those related to boreal forests.

In 2005, large-scale, warm droughts occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security (Breshears2005). The words “nitrogen” (3,136), “carbon” (2,568), and “phosphorus” (971) were used frequently in the studies concerning elemental nutrients. There were numerous studies related to how the climate is affecting forest ecology, as indicated by the frequencies of “climate-change”, “climate”, and “climate change,” which were 2,412, 2,095 and 1,599, respectively.

This study did reveal some problem areas. Some keywords were not being used consistently, such as soil, soils, forest soil and forest soils, which all pointed to the same thing: forest soil. Another example was that tropical forest and tropical forests also expressed similar meanings. The use of multiple keywords for a single concept might be related to the writing styles and habits of different authors, but this creates difficulty in statistical analysis.

The USA, Canada, and Germany were the top three most productive countries of forest ecology related research. The most three productive organizations were the University of California System, Chinese Academy of Sciences, and the US Forest Service. The three most productive funding agencies were the National Science Foundation, the National Natural Science Foundation of China, and the Natural Sciences and Engineering Research Council of Canada. Environmental science / ecology, forestry, and agriculture were the top three most popular categories. The spatial clusters of authors were mainly in the USA and Canada. Forest Ecology and Management, Canadian Journal of Forest Research, and Biological Conservation were the top three journals with the most publications related to forest ecology research. In the article analysis, the results by country/region, organization, funding agency, author distribution, and sources titles, was clustered in developed countries, apparently because these countries have economic strength required to invest in science and technology.

In this study, the limitations of search term expressions and the English language made it impossible to include all related keywords in the field of forest ecology research, especially in other languages. This study did not analyze the effects of cooperation between authors and joint papers by authors from multiple nations. In the journal sort, the impact factor of the journal was not considered.

Conclusions

A serial java program was developed and applied to conduct keyword frequency analysis. That improved the efficiency of data processing and provided an analysis method. Keyword analysis offered insight into forest ecology research areas of interest, while the abundance of less frequent keywords suggested a lack of continuity in research and a wide disparity in the focus of forest ecology research. The top 100 keywords in the keyword analysis were almost all included in the top 20 research areas in the article analysis, so one could conclude that keyword frequency analysis is consistent with article research area analysis. Their difference is the former is concrete and the latter is abstract.Appendix A(TS = (habitats) or TS = (species diversity) or TS = (biodiversity) or TS = (species richness) or TS = (environmental factors) or TS = (ecosystems) or TS = (plant communities) or TS = (landscape) or TS = (phenology) or TS = (environmental degradation) or TS = (plant) or TS = (populations) or TS = (animal) or TS = (ecological disturbance) or TS = (landscape) or TS = (synecology) or TS = (palaeo ecology) or TS = (community) or TS = (biogeography) or TS = (population) or TS = (ecotypes) or TS = (predator prey relationships) or TS = (microbial) or TS = (freshwater) or TS = (food webs) or TS = (lowland areas) or TS = (restoration) or TS = (fire) or TS = (food chains) or TS = (autecology) or TS = (marine) or TS = (chemical) or TS = (human) or TS = (bioenergetics) or TS = (ecological balance) or TS = (bio coenosis) or TS = (microenvironments) or TS = (dendro ecology) or TS = (climate) or TS = (soils) or TS = (physiography) or TS = (carbon balance) or TS = (nutrient cycling) and (TS = (forest).

Declarations

Acknowledgements

This study was supported by the Forestry Commonweal Programs (No. 200904003) from State Forestry Administration, P.R.China. The authors greatly appreciate the technical support of Peng Shi, Yingni Zou, and Ying Pan. The authors are grateful to Yungang Liao for his helpful suggestions. The authors would also like to thank the chief editor of SpringerPlus and anonymous reviewers for their valuable comments.

Authors’ Affiliations

(1)
School of Information Science & Technology, Beijing Forestry University
(2)
Library of Beijing International Studies University

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© Song and Zhao; licensee Springer. 2013

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