ArticleEcology and evolution2019
Evolution of interdisciplinarity in biodiversity science.
Article in Ecology and evolution, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep Learning in Plant Phenological Research: A Systematic Literature Review.Frontiers in plant science · 2022Pooled it
- Past and future uses of text mining in ecology and evolution.Proceedings. Biological sciences · 2022Review
- Interdisciplinary collaboration from diverse science teams can produce significant outcomes.PloS one · 2022Article
- The archives are half-empty: an assessment of the availability of microbial community sequencing data.Communications biology · 2020Article
- Recommendations for establishing global collaborative networks in soil ecology.Soil organisms · 2019Article
- Evolution of interdisciplinarity in biodiversity science.Ecology and evolution · 2019Article
- A multitrophic perspective on biodiversity-ecosystem functioning research.Advances in ecological research · 2019Article
- Pearl's causality for integrating ecological datasets: A case study onApplications in plant sciencesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The study of biodiversity has grown exponentially in the last thirty years in response to demands for greater understanding of the function and importance of Earth's biodiversity and finding solutions to conserve it. Here, we test the hypothesis that biodiversity science has become more interdisciplinary over time. To do so, we analyze 97,945 peer-reviewed articles over a twenty-two-year time period (1990-2012) with a continuous time dynamic model, which classifies articles into concepts (i.e., topics and ideas) based on word co-occurrences. Using the model output, we then quantify different aspects of interdisciplinarity: concept diversity, that is, the diversity of topics and ideas across subdisciplines in biodiversity science, subdiscipline diversity, that is, the diversity of subdisciplines across concepts, and network structure, which captures interactions between concepts and subdisciplines. We found that, on average, concept and subdiscipline diversity in biodiversity science were either stable or declining, patterns which were driven by the persistence of rare concepts and subdisciplines and a decline in the diversity of common concepts and subdisciplines, respectively. Moreover, our results provide evidence that conceptual homogenization, that is, decreases in temporal β concept diversity, underlies the observed trends in interdisciplinarity. Together, our results reveal that biodiversity science is undergoing a dynamic phase as a scientific discipline that is consolidating around a core set of concepts. Our results suggest that progress toward addressing the biodiversity crisis via greater interdisciplinarity during the study period may have been slowed by extrinsic factors, such as the failure to invest in research spanning across concepts and disciplines. However, recent initiatives such as the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) may attract broader support for biodiversity-related issues and hence interdisciplinary approaches to address scientific, political, and societal challenges in the coming years.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.