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Title: | The hierarchy-of-hypotheses approach: A synthesis method for enhancing theory development in ecology and evolution |
Authors: | Heger, T.; Aguilar, Carlos; Bartram, Isabelle; Braga, Raul Rennó; Dietl, Gregory P.; Enders, M.; Gibson, David J.; Gómez Aparicio, Lorena CSIC ORCID ; Gras, Pierre; Jax, Kurt; Lokatis, Sophie; Lortie, C. J.; Mupepele, Anne-Christine; Schindler, Stefan; Starrfelt, Jostein; Synodinos, Alexis; Jeschke, Jonathan M.; Jeschke, Jonathan M. | Keywords: | Hierarchy-of-hypotheses approach Knowledge synthesis Linking evidence to theory Structuring ideas Theory development |
Issue Date: | Apr-2021 | Publisher: | Oxford University Press | Citation: | Bioscience 71(4): 337-349 (2021) | Abstract: | In the current era of Big Data, existing synthesis tools such as formal meta-analyses are critical means to handle the deluge of information. However, there is a need for complementary tools that help to (a) organize evidence, (b) organize theory, and (c) closely connect evidence to theory. We present the hierarchy-of-hypotheses (HoH) approach to address these issues. In an HoH, hypotheses are conceptually and visually structured in a hierarchically nested way where the lower branches can be directly connected to empirical results. Used for organizing evidence, this tool allows researchers to conceptually connect empirical results derived through diverse approaches and to reveal under which circumstances hypotheses are applicable. Used for organizing theory, it allows researchers to uncover mechanistic components of hypotheses and previously neglected conceptual connections. In the present article, we offer guidance on how to build an HoH, provide examples from population and evolutionary biology and propose terminological clarifications. | Description: | 13 páginas.- 4 figuras.- referencias.- Supplemental material is available at BIOSCI online. https://doi.org/10.1093/biosci/biaa130 | Publisher version (URL): | http://dx.doi.org/10.1093/biosci/biaa130 | URI: | http://hdl.handle.net/10261/251309 | DOI: | 10.1093/biosci/biaa130 |
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