A systematic method for hypothesis synthesis and conceptual model development

被引:4
作者
Grames, Eliza M. [1 ,2 ]
Schwartz, Danielle [1 ]
Elphick, Chris S. [1 ]
机构
[1] Univ Connecticut, Dept Ecol & Evolutionary Biol, Storrs, CT 06269 USA
[2] Univ Nevada, Dept Biol, Reno, NV 89557 USA
来源
METHODS IN ECOLOGY AND EVOLUTION | 2022年 / 13卷 / 09期
基金
美国国家科学基金会;
关键词
conceptual model; hypothesis development; network analysis; synthesis methods; ECOLOGY;
D O I
10.1111/2041-210X.13940
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
1. Conceptual models are necessary to synthesize what is known about a topic, identify gaps in knowledge and improve understanding. The process of developing conceptual models that summarize the literature using ad hoc approaches has high potential to be incomplete due to the challenges of tracking information and hypotheses across the literature. 2. We present a novel, systematic approach to conceptual model development through qualitative synthesis and graphical analysis of hypotheses already present in the scientific literature. Our approach has five stages: researchers explicitly define the scope of the question, conduct a systematic review, extract hypotheses from prior studies, assemble hypotheses into a single network model and analyse trends in the model through network analysis. 3. The resulting network can be analysed to identify shifts in thinking over time, variation in the application of ideas over different axes of investigation (e.g. geography, taxonomy, ecosystem type) and the most important hypotheses based on the network structure. To illustrate the approach, we present examples from a case study that applied the method to synthesize decades of research on the effects of forest fragmentation on birds. 4. This approach can be used to synthesize scientific thinking across any field of research, guide future research to fill knowledge gaps efficiently and help researchers systematically build conceptual models representing alternative hypotheses.
引用
收藏
页码:2078 / 2087
页数:10
相关论文
共 45 条
[11]   Meta-analytic structural equation modeling: A two-stage approach [J].
Cheung, MWL ;
Chan, W .
PSYCHOLOGICAL METHODS, 2005, 10 (01) :40-64
[12]   The mid-domain effect and species richness patterns: What have we learned so far? [J].
Colwell, RK ;
Rahbek, C ;
Gotelli, NJ .
AMERICAN NATURALIST, 2004, 163 (03) :E1-E23
[13]   Classifying drivers of global forest loss [J].
Curtis, Philip G. ;
Slay, Christy M. ;
Harris, Nancy L. ;
Tyukavina, Alexandra ;
Hansen, Matthew C. .
SCIENCE, 2018, 361 (6407) :1108-1111
[14]  
Dijkstra E. W., 2022, Edsger Wybe Dijkstra: His Life, Work, and Legacy, V45, P287
[15]   Developing multiple hypotheses in behavioral ecology [J].
Dochtermann, Ned A. ;
Jenkins, Stephen H. .
BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY, 2011, 65 (01) :37-45
[16]   Toward rigorous use of expert knowledge in ecological research [J].
Drescher, M. ;
Perera, A. H. ;
Johnson, C. J. ;
Buse, L. J. ;
Drew, C. A. ;
Burgman, M. A. .
ECOSPHERE, 2013, 4 (07)
[17]   A conceptual map of invasion biology: Integrating hypotheses into a consensus network [J].
Enders, Martin ;
Havemann, Frank ;
Ruland, Florian ;
Bernard-Verdier, Maud ;
Catford, Jane A. ;
Gomez-Aparicio, Lorena ;
Haider, Sylvia ;
Heger, Tina ;
Kueffer, Christoph ;
Kuehn, Ingolf ;
Meyerson, Laura A. ;
Musseau, Camille ;
Novoa, Ana ;
Ricciardi, Anthony ;
Sagouis, Alban ;
Schittko, Conrad ;
Strayer, David L. ;
Vila, Montserrat ;
Essl, Franz ;
Hulme, Philip E. ;
Kleunen, Mark ;
Kumschick, Sabrina ;
Lockwood, Julie L. ;
Mabey, Abigail L. ;
McGeoch, Melodie A. ;
Palma, Estibaliz ;
Pysek, Petr ;
Saul, Wolf-Christian ;
Yannelli, Florencia A. ;
Jeschke, Jonathan M. .
GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2020, 29 (06) :978-991
[18]   Hydrogeological conceptual model building and testing: A review [J].
Enemark, Trine ;
Peeters, Luk J. M. ;
Mallants, Dirk ;
Batelaan, Okke .
JOURNAL OF HYDROLOGY, 2019, 569 :310-329
[19]   CENTRALITY IN SOCIAL NETWORKS CONCEPTUAL CLARIFICATION [J].
FREEMAN, LC .
SOCIAL NETWORKS, 1979, 1 (03) :215-239
[20]  
Grames, 2021, THESIS U CONNECTICUT