Growing into Interdisciplinarity: How to Converge Biology, Economics, and Social Science in Fisheries Research?

被引:49
作者
Haapasaari, Paivi [1 ]
Kulmala, Soile
Kuikka, Sakari [1 ]
机构
[1] Univ Helsinki, Fisheries & Environm Management Grp, Dept Environm Sci, FIN-00014 Helsinki, Finland
来源
ECOLOGY AND SOCIETY | 2012年 / 17卷 / 01期
关键词
Baltic Sea salmon fisheries; Bayesian belief networks; bioeconomic modeling; integrated model; interdisciplinarity; interdisciplinary learning; fisheries research; methodological epoche; multidisciplinarity; MANAGEMENT; KNOWLEDGE; EXPLOITATION; MODELS; RATES;
D O I
10.5751/ES-04503-170106
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
It has been acknowledged that natural sciences alone cannot provide an adequate basis for the management of complex environmental problems. The scientific knowledge base has to be expanded in a more holistic direction by incorporating social and economic issues. As well, the multifaceted knowledge has to be summarized in a form that can support science-based decision making. This is, however, difficult. Interdisciplinary skills, practices, and methodologies are needed that enable the integration of knowledge from conceptually different disciplines. Through a focus on our research process, we analyzed how and what kind of interdisciplinarity between natural scientists, environmental economists, and social scientists grew from the need to better understand the complexity and uncertainty inherent to the Baltic salmon fisheries, and how divergent knowledge was integrated in a form that can support science-based decision making. The empirical findings suggest that interdisciplinarity is an extensive learning process that takes place on three levels: between individuals, between disciplines, and between types of knowledge. Such a learning process is facilitated by agreeing to a methodological epoche and by formulating a global question at the outset of a process.
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收藏
页数:12
相关论文
共 63 条
[41]  
Michielsens C. G. J., 2005, P ICES ANN SCI C 20
[42]   Combining multiple Bayesian data analyses in a sequential framework for quantitative fisheries stock assessment [J].
Michielsens, Catherine G. J. ;
McAllister, Murdoch K. ;
Kuikka, Sakari ;
Mantyniemi, Samu ;
Romakkaniemi, Atso ;
Pakarinen, Tapani ;
Karlsson, Lars ;
Uusitalo, Laura .
CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES, 2008, 65 (05) :962-974
[43]   Estimation of annual mortality rates caused by early mortality syndromes (EMS) and their impact on salmonid stock-recruit relationships [J].
Michielsens, Catherine G. J. ;
Mantyneimi, Sarnu ;
Vuorinen, Pekka J. .
CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES, 2006, 63 (09) :1968-1981
[44]   A Bayesian state-space mark-recapture model to estimate exploitation rates in mixed-stock fisheries [J].
Michielsens, CGJ ;
McAllister, MK ;
Kuikka, S ;
Pakarinen, T ;
Karlsson, L ;
Romakkaniemi, A ;
Perä, I ;
Mäntyniemi, S .
CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES, 2006, 63 (02) :321-334
[45]  
Miller R.C., 1982, Issues in Integrative Studies, V1, P1
[46]   A perspective on interdisciplinary science [J].
Naiman, RJ .
ECOSYSTEMS, 1999, 2 (04) :292-295
[47]   Combining research styles of the natural and social sciences in agricultural research [J].
Nuijten, E. .
NJAS-WAGENINGEN JOURNAL OF LIFE SCIENCES, 2011, 57 (3-4) :197-205
[48]  
Pavao-Zuckerman M.A., 2000, Journal of Ecological Anthropology, V4, P31
[49]   Interdisciplinary research: Maintaining the constructive impulse in a culture of criticism [J].
Pickett, STA ;
Burch, WR ;
Grove, JM .
ECOSYSTEMS, 1999, 2 (04) :302-307
[50]  
Ranke W., 1999, BALTIC SALMON RIVERS