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Review
. 2018 Sep 28;13(9):e0204749.
doi: 10.1371/journal.pone.0204749. eCollection 2018.

Where communities intermingle, diversity grows - The evolution of topics in ecosystem service research

Nils Droste  1   2   3 , Dalia D'Amato  4 , Jessica J Goddard  5
Affiliations
Review

Where communities intermingle, diversity grows - The evolution of topics in ecosystem service research

Nils Droste et al. PLoS One. .

Abstract

We analyze how the content of ecosystem service research has evolved since the early 1990s. Conducting a computational bibliometric content analysis we process a corpus of 14,118 peer-reviewed scientific article abstracts on ecosystem services (ES) from Web of Science records. To provide a comprehensive content analysis of ES research literature, we employ a latent Dirichlet allocation algorithm. For three different time periods (1990-2000, 2001-2010, 2011-2016), we derive nine main ES topics arising from content analysis and elaborate on how they are related over time. The results show that natural science-based ES research analyzes oceanic, freshwater, agricultural, forest, and soil ecosystems. Pollination and land cover emerge as traceable standalone topics around 2001. Social science ES literature demonstrates a reflexive and critical lens on the role of ES research and includes critiques of market-oriented perspectives. The area where social and natural science converge most is about land use systems such as agriculture. Overall, we provide evidence of the strong natural science foundation, the highly interdisciplinary nature of ES research, and a shift in social ES research towards integrated assessments and governance approaches. Furthermore, we discuss potential reasons for observable topic developments.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. The growth in ES research.
Source: authors’ representation based on WOS data.
Fig 2
Fig 2. The geographical distribution of ES research.
Colour scales represent the count of author affiliation locations. Note the different fixed width logarithmic colour scale breaks. Source: authors’ own representation based on WoS.
Fig 3
Fig 3. Top author keywords for the research corpi in three periods.
Note the different x-axis-scale of the plots for each period. Source: authors’ own representation based on WoS data.
Fig 4
Fig 4. The development of ES topic clusters over time.
The height of the topic boxes represents the relative topic proportion within each period. Note that the number of assessed articles increases over time (1990–2000: N = 108, 2001–2010: N = 2,521, and 2011–2016: N = 11,489). The links between periods have interpretatively been deducted from LDA results. There is no particular order of topics except for clarity of linkage exposition. Source: authors’ elaboration based on WoS data.
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