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.

Berlin Brandenburg Institute of Advanced Biodiversity Research Berlin Germany

Chair of Nature Conservation and Landscape Ecology University of Freiburg Freiburg and the Senckenberg Biodiversity and Climate Research Centre Frankfurt am Main both in Germany

Department of Biodiversity Research and Systematic Botany University of Potsdam Potsdam Germany

Department of Biology York University York Canada as well as with the National Center for Ecological Analysis and Synthesis University of California Santa Barbara Santa Barbara California

Department of Plant Ecology and Nature Conservation University of Potsdam Potsdam Germany

Department of Restoration Ecology Technical University of Munich Freising Germany

Environment Agency Austria and University of Vienna's Division of Conservation Biology Vegetation and Landscape Ecology Vienna Austria and his third affiliation is with Community Ecology and Conservation Czech University of Life Sciences Prague Prague Czech Republic Finally

Instituto de Recursos Naturales y Agrobiología de Sevilla CSIC LINCGlobal Sevilla Spain

Paleontological Research Institution and the Department of Earth and Atmospheric Sciences at Cornell University Ithaca New York

School of Biological Sciences Southern Illinois University Carbondale Carbondale Illinois

Universidade Federal do Paraná Laboratório de Ecologia e Conservação Curitiba Brazil

University of Oslo's Centre for Ecological and Evolutionary Synthesis and with the Norwegian Scientific Committee for Food and Environment Norwegian Institute of Public Health both in Oslo Norway

Zobrazit více v PubMed

Bartram I, Jeschke JM. 2019. Do cancer stem cells exist? A pilot study combining a systematic review with the hierarchy-of-hypotheses approach. PLOS ONE 14: e0225898. PubMed PMC

Braga RR, Gómez-Aparicio L, Heger T, Vitule JRS, Jeschke JM. 2018. Structuring evidence for invasional meltdown: Broad support but with biases and gaps. Biological Invasions 20: 923–936.

Collaboration for Environmental Evidence . 2018. Guidelines and Standards for Evidence Synthesis in Environmental Management, version 5.0. Collaboration for Environmental Evidence. www.environmentalevidence.org/information-for-authors.

Cook CN, Nichols SJ, Webb JA, Fuller RA, Richards RM. 2017. Simplifying the selection of evidence synthesis methods to inform environmental decisions: A guide for decision makers and scientists. Biological Conservation 213: 135–145.

de Vrieze J. 2018. The metawars. Science 361: 1184–1188. PubMed

Dicks LV, et al. 2017. . Knowledge Synthesis for Environmental Decisions: An Evaluation of Existing Methods, and Guidance for Their Selection, Use, and Development. EKLIPSE Project.

Diefenderfer HL, Johnson GE, Thom RM, Bunenau KE, Weitkamp LA, Woodley CM, Borde AB, Kropp RK. 2016. Evidence-based evaluation of the cumulative effects of ecosystem restoration. Ecosphere 7: e01242.

Dietl GP. 2015. Evaluating the strength of escalation as a research program. Geological Society of America Abstracts with Programs 47: 427.

Elton C, Nicholson M. 1942. The ten-year cycle in numbers of lynx in Canada. Journal of Animal Ecology 11: 215–244.

Enders M, Hütt M-T, Jeschke JM. 2018. Drawing a map of invasion biology based on a network of hypotheses. Ecosphere 9: e02146.

Enders M, et al. 2020. . A conceptual map of invasion biology: Integrating hypotheses into a consensus network. Global Ecology and Biogeography 29: 978–999. PubMed PMC

Farji-Brener AG, Amador-Vargas S. 2018. Hierarchy of hypotheses or hierarchy of predictions? Clarifying key concepts in ecological research. Pages 19–22 in Jeschke JM, Heger T, eds. Invasion Biology: Hypotheses and Evidence. CAB International.

Giere RN, Bickle J, Mauldin R. 2005. Understanding Scientific Reasoning, 5th ed. Wadsworth Cengage Learning.

Grace J, Anderson T, Olff H, Scheiner S. 2010. On the specification of structural equation models for ecological systems. Ecological Monographs 80: 67–87.

Griesemer JR. 2013. Formalization and the meaning of “theory” in the inexact biological sciences. Biological Theory 7: 298–310.

Griesemer J. 2018. Mapping theoretical and evidential landscapes in ecological science: Levin's virtue trade-off and the hierarchy-of-hypotheses approach. Pages 23–29 in Jeschke JM, Heger T, eds. Invasion Biology: Hypotheses and Evidence. CAB International.

Gurevitch J, Fox GA, Wardle GM, Inderjit Taub D. 2011. Emergent insights from the synthesis of conceptual frameworks for biological invasions. Ecology Letters 14: 407–418. PubMed

Haddaway NR, Macura B, Whaley P, Pullin AS. 2018. ROSES: Reporting standards for systematic evidence syntheses: Pro forma, flow-diagram and descriptive summary of the plan and conduct of environmental systematic reviews and systematic maps. Environmental Evidence 7: 7.

Heger T, Jeschke JM. 2014. The enemy release hypothesis as a hierarchy of hypotheses. Oikos 123: 741–750.

Heger T, Jeschke JM. 2018a. Conclusions and outlook. Pages 167–172 in Jeschke JM, Heger T, eds. Invasion Biology: Hypotheses and Evidence. CAB International.

Heger T, Jeschke JM. 2018b. Enemy release hypothesis. Pages 92–102 in Jeschke JM, Heger T, eds. Invasion Biology: Hypotheses and Evidence. CAB International.

Heger T, Jeschke JM. 2018c. The hierarchy-of-hypotheses approach updated: A toolbox for structuring and analysing theory, research, and evidence. Pages 38–48 in Jeschke JM, Heger T, eds. Invasion Biology: Hypotheses and Evidence. CAB International.

Heger T, et al. 2013. Conceptual frameworks and methods for advancing invasion ecology. Ambio 42: 527–540. PubMed PMC

Heger T, et al. 2019. Towards an integrative, eco-evolutionary understanding of ecological novelty: Studying and communicating interlinked effects of global change. BioScience 69: 888–899. PubMed PMC

Howick J. 2011. The Philosophy of Evidence-based Medicine. Wiley-Blackwell.

Jeltsch F, et al. 2013. . How can we bring together empiricists and modelers in functional biodiversity research? Basic and Applied Ecology 14: 93–101.

Jeschke JM, Heger T, eds. 2018a. Invasion Biology: Hypotheses and Evidence. CAB International.

Jeschke JM, Heger T, eds. 2018b. Synthesis. Pages 157–166 in Jeschke JM, Heger T, eds. Invasion Biology. Hypotheses and Evidence. CAB International.

Jeschke JM, Pyšek P. 2018. Tens rule. Pages 124–132 in Jeschke JM, Heger T, eds. Invasion Biology: Hypotheses and Evidence. CAB International.

Jeschke JM, Gómez Aparicio L, Haider S, Heger T, Lortie CJ, Pyšek P, Strayer DL. 2012. Support for major hypotheses in invasion biology is uneven and declining. NeoBiota 14: 1–20.

Jeschke JM, Debille S, Lortie CJ. 2018a. Biotic resistance and island susceptibility hypotheses. Pages 60–70 in Jeschke JM, Heger T, eds. Invasion Biology: Hypotheses and Evidence. CAB International.

Jeschke JM, Enders M, Bagni M, Jeschke P, Zimmermann M, Heger T. 2018b. Hi Knowledge. Hi-Knowledge.org. www.hi-knowledge.org/invasion-biology

Jeschke JM, Lokatis S, Bartram I, Tockner K. 2019. Knowledge in the dark: Scientific challenges and ways forward. FACETS 4: 1–19.

Keane RM, Crawley MJ. 2002. Exotic plant invasions and the enemy release hypothesis. Trends in Ecology and Evolution 17: 164–170.

Koricheva J, Gurevitch J, Mengersen K, eds. 2013. Handbook of Meta-analysis in Ecology and Evolution. Princeton University Press.

Krebs CJ, Boonstra R, Boutin S. 2018. Using experimentation to understand the 10-year snowshoe hare cycle in the boreal forest of North America. Journal of Animal Ecology 87: 87–100. PubMed

Krebs CJ, Boonstra R, Boutin S, Sinclair ARE. 2001. What drives the 10-year cycle of snowshow hares? BioScience 51: 25–35.

Lortie CJ. 2014. Formalized synthesis opportunities for ecology: Systematic reviews and meta-analyses. Oikos 123: 897–902.

MacLulich DA. 1937. Fluctuation in numbers of the varying hare (Lepus americanus). Univ Toronto Studies Biol Series 43: 1–136.

Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA, PRISMA-P Group . 2015. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews 4: 1. PubMed PMC

Mupepele A-C, Walsh JC, Sutherland WJ, Dormann CF. 2016. An evidence assessment tool for ecosystem services and conservation studies. Ecological Applications 26: 1295–1301. PubMed

Nakagawa S, Samarasinghe G, Haddaway NR, Westgate MJ, O'Dea RE, Noble DWA, Lagisz M. 2019. Research weaving: Visualizing the future of research synthesis. Trends in Ecology and Evolution 34: 224–238. PubMed

Nesshöver C, et al. 2016. . The Network of Knowledge approach: Improving the science and society dialogue on biodiversity and ecosystem services in Europe. Biodiversity and Conservation 25: 1215–1233.

Norris RH, Webb JA, Nichols SJ, Stewardson MJ, Harrison ET. 2012. Analyzing cause and effect in environmental assessments: Using weighted evidence from the literature. Freshwater Science 31: 5–21.

Oli MK, Krebs CJ, Kenney AJ, Boonstra R, Boutin S, Hines JE. 2020. Demography of snowshoe hare population cycles. Ecology 101: e02969. doi:10.1002/ecy.2969. PubMed

Pickett STA, Kolasa J, Jones CG. 2007. Ecological Understanding: The Nature of Theory and the Theory of Nature, 2nd ed. Academic Press.

Platt JR. 1964. Strong inference. Science 146: 347–353. PubMed

Pullin A, et al. 2016. . Selecting appropriate methods of knowledge synthesis to inform biodiversity policy. Biodiversity and Conservation 25: 1285–1300.

Ryo M, Jeschke JM, Rillig MC, Heger T. 2019. Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions. Research Synthesis Methods 11: 66–73doi:10.1002/jrsm.1363. PubMed PMC

Scheiner SM. 2013. The ecological literature, an idea-free distribution. Ecology Letters 16: 1421–1423. PubMed

Scheiner SM, Fox GA. 2018. A hierarchy of hypotheses or a network of models. Pages 30–37 in Jeschke JM, Heger T, eds. Invasion Biology: Hypotheses and Evidence. CAB International.

Schulz AN, Lucardi RD, Marsico TD. 2019. Successful invasions and failed biocontrol: The role of antagonistic species interactions. BioScience 69: 711–724.

Silvertown JW, Charlesworth D. 2001. Introduction to Plant Population Biology. Blackwell Scientific.

Stenseth NC, Falck W, Bjørnstad ON, Krebs CJ. 1997. Population regulation in snowshoe hare and Canadian lynx: Asymmetric food web configurations between hare and lynx. Proceedings of the National Academy of Sciences of the United States of America 94: 5147–5152. PubMed PMC

Sutherland WJ. 2006. Predicting the ecological consequences of environmental change: A review of the methods. Journal of Applied Ecology 43: 599–616.

Sutherland WJ, et al. 2013. . Identification of 100 fundamental ecological questions. Journal of Ecology 101: 58–67.

Thompson JN. 2005. The Geographic Mosaic of Coevolution. University of Chicago Press.

Van Valen L. 1973. A new evolutionary law. Evolutionary Theory 1: 1–30.

Vermeij GJ. 1987. Evolution and Escalation: An Ecological History of Life. Princeton University Press.

Wu L, Huang I-C, Huang W-C, Du P-L. 2019. Aligning organizational culture and operations strategy to improve innovation outcomes: An integrated perspective in organizational management. Journal of Organizational Change Management 32: 224–250. doi:10.1108/JOCM-03-2018-0073.