One Ecosystem :
Short Communication
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Corresponding author: Francisco Javier Ancin-Murguzur (francisco.j.murguzur@uit.no)
Academic editor: Petteri Vihervaara
Received: 31 Jul 2020 | Accepted: 25 Aug 2020 | Published: 18 Sep 2020
© 2020 Francisco Ancin-Murguzur, Vera Hausner
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Ancin-Murguzur FJ, Hausner VH (2020) Research gaps and trends in the Arctic tundra: a topic-modelling approach. One Ecosystem 5: e57117. https://doi.org/10.3897/oneeco.5.e57117
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Climate change is affecting the biodiversity, ecosystem services and the well-being of people that live in the Arctic tundra. Understanding the societal implications and adapting to these changes depend on knowledge produced by multiple disciplines. We analysed peer-reviewed publications to identify the main research themes relating to the Arctic tundra and assessed to what extent current research build on multiple disciplines to confront the upcoming challenges of rapid environmental changes. We used a topic-modelling approach, based on the Latent Dirichlet Allocation algorithm to detect topics based on semantic similarity. We found that plant and soil ecology dominate the tundra research and are highly connected to other ecological disciplines and biophysical sciences. Despite the fivefold increase in the number of publications during the past decades, the proportion of studies that address societal implications of climate change remains low. The strong scientific interest in the tundra reflects the concern of the rapid warming of the Arctic, but few studies include the cross-disciplinary approach necessary to fully assess the implications of these changes for society.
Topic modelling, research gaps, climate change, socio-economic system, LDA
In the coming decades, climate warming will rapidly transform the tundra ecosystems in the Arctic. Thawing permafrost, snow icing events, snow cover decrease, rainfall patterns and hydrological cycles, intensification of wildfires, shifts in growing and flowering seasons and expansion of shrubs and trees are all observable changes that are impacting Arctic tundra ecosystems (
Several authors have worked with the identification of research gaps in the tundra biome:
Although the biological aspects of climate change are routinely studied, societal implications of climate change in the Arctic have received less attention.
In this study, we quantitatively assess the temporal trends of different research disciplines and identify the main knowledge gaps for understanding the implications of a rapid Arctic warming for tundra ecosystems and societies. We use machine learning and a bibliometric approach to synthesise trends and the topics of relevance across all disciplines and geographical regions. We use Latent Dirichlet Allocation (LDA) (
Our study aims to complement the more detailed reviews that target a limited set of topics and disciplines to identify knowledge gaps and the degree to which research addresses more than one discipline, with the purpose of better understanding the societal implications of climate change.
We used bibliometric analysis, which quantitatively assesses trends, based on metadata (e.g. author, year or keywords) and visualise temporal trends, based on the information retrieved. The corpus of these documents can be used for topic discovery using text analysis tools. We used Latent Dirichlet Allocation (LDA), as a probabilistic model that assumes the presence of every word in every topic and the presence of all topics in a given document with varying probabilities (
We searched the Elsevier Scopus (Scopus) database for relevant publications using the search string TITLE-ABS-KEY (tundra) on 26 November 2019. We selected Scopus as a search database due to its wider coverage compared to other search engines (
First, we removed articles for which abstracts were not retrieved from the database. We converted all words starting with “graz” and “herbiv” to “grazing” to avoid confusion between these two terms. Additionally, we removed the journal names and copyright notices that are written at the end of the abstracts in order to reduce noise in the topics that may be associated with each journal’s publication scope. In addition, we processed the database with a lemmatisation process, where different manners of writing a word (or, for example, verb tenses) are consolidated into a single, consistent word (i.e. the lemmatisation of the words runner, running and ran becomes run) that simplifies the text to fewer words. For that purpose, we used the English lemmatisation tool from the udpipe package in R (
The statistical analyses were performed using the package bibliometrix (
We defined the number of topics (k) as 50 topics: we considered that four to five topics would allow us to identify the disciplines, thus deciding on 50 topics as a conservative estimate of k. We pooled these 50 topics into nine disciplines (modified from
Finally, we estimated the closeness between disciplines by means of the cosine correlation. For that purpose, we aggregated all the keywords for each discipline and calculated the cosine correlations for all the disciplines combinations. This approach allowed us to find which disciplines are more closely correlated and thus more easily interconnected and which disciplines have weaker connections between them as a proxy for gaps in interdisciplinary collaboration.
The search resulted in 9274 articles that specifically use the word tundra in their research, after removing 253 records with no abstract and nine duplicated records. The interest in tundra research has grown 5-fold during the last 20 years from less than 100 articles per year in the 1990s to over 500 articles per year in 2018 (Fig.
Manual tagging of disciplines, based on the top 20 words, resulted in a coherent topic classification (Suppl. material
Summary of topics belonging to a discipline, mean coherence for each topic group and the number of articles where only one discipline had a probability higher than 20%.
Discipline |
Subtopics |
Coherence (mean) |
n |
Plant_ecology |
14 |
0.06 |
1384 |
Soil_ecology |
11 |
0.07 |
1181 |
Paleoecology |
8 |
0.10 |
1059 |
Animal_ecology |
5 |
0.07 |
489 |
Biogeochemistry |
6 |
0.05 |
474 |
SES |
3 |
0.02 |
282 |
Remote_sensing |
1 |
0.03 |
81 |
Plant_herbivore |
1 |
0.10 |
69 |
Geosciences |
1 |
0.10 |
58 |
The temporal trends in research disciplines show an erratic pattern until the 1980s (Fig.
Cosine correlation coefficients show how the topics are closely interconnected (Fig.
Societal implications of a changing Arctic tundra are studied in a total of 873 articles overall, either as the main topic (n = 282 articles) or otherwise. This discipline had the lowest coherence score, reflecting a highly-fragmented field of research drawing on a broad range of perspectives. This represents less than 10% of the research done in the tundra, showing that human dimensions are under-represented in the tundra research as a whole. The cosine correlation coefficients show that SES are weakly correlated to most disciplines, except for animal ecology (cosine correlation = 0.68) and plant ecology (cosine correlation = 0.53), emphasising that the link between humans and nature is poorly understood.
Our study presents a quantitative assessment of research topics and trends in the tundra ecosystem. The research interest in the tundra has increased 5-fold since the early 1980s. This is a strong increase compared to the publication rates globally (
In our study, more than half of the analysed articles (n = 5077) were assigned to a single discipline. More integrative studies are needed with a stronger multidisciplinary or interdisciplinary focus to strengthen the present information flow between disciplines and that directly aim to bridge the gaps between the single-focus disciplines (even closely-related disciplines, such as plant and soil ecology) to achieve a more efficient, information-driven management. The potential effects of the expected shifts in the tundra ecosystem (
The low coherence for all topics indicates sparsity of the language used in the different articles. The specificity of each article to a given ecosystem process, for example, the tundra plant ecology, can cover the forest-tundra ecotone, the dwarf shrub tundra or the nutrient intake of plants under different biotic and abiotic conditions, amongst others. On the other hand, the language specificity facilitates assigning a discipline to each topic, based on the top keywords, since these keywords are strong representatives of their corresponding discipline, for example, forest growth is a clear representative of the plant ecology discipline. The low coherence score in the SES topic (0.02) shows that the field of research most relevant for understanding societal implications is fragmentary and less prevalent compared to the traditional disciplines, which is related to the fact that SES research trades pieces of knowledge between disciplines.
The cosine similarity analysis (Fig.
Our study presents a description of the current status and historical trends of the research in the tundra ecosystem. We show how plant ecology dominates the research in tundra ecosystems and we identify a gap in research showing that there is a need for more multidisciplinary approaches that integrate the expertise of different disciplines to achieve a broader understanding and more efficient management of ecosystem shifts and the societal impacts of climate change.
The data underpinning the analysis reported in this paper are deposited at UiT - The Arctic University of Norway's data management system at https://doi.org/10.18710/WBKY7Q
This article was supported by the Fram Center flagship Effects of climate change on ecosystems, landscape local communities and indigenous people grant nr. 369903, Project EcoShift: Scenarios for linking biodiversity, ecosystem services and adaptive actions and the Norwegian research council grant nr. 296987, project Future ArcTic Ecosystems (FATE): drivers of diversity and future scenarios from ethnoecology, contemporary ecology and ancient DNA
The publication charges for this article have been funded by a grant from the publication fund of UiT The Arctic University of Norway
Both authors contributed equally to the completion of this manuscript.
The authors declare no conflicts of interest.
Supplementary table 1 Results from the topic-modelling procedure where the topic coherence (Coherence column), manually assigned discipline (Discipline column) and the keywords that define each topic (Top terms) are presented for each topic.