Rule-based Adaptive Management

Rule-Based Adaptive Management is a formal decision-making framework within fisheries and natural resource management that belongs to the class of adaptive management strategies, distinguished by its reliance on pre-specified, quantitative rules to guide management actions in response to monitoring data, thereby enabling systematic and transparent adjustments to harvest policies in dynamic ecological systems.

15

Publications

648

Citations

60

Authors

32

Institutions

Publications per year

2017–2026

6

Authors

60

  1. EC
    Ernesto Carrella

    University of Oxford, United Kingdom

    2 publications · 35 citations

    2

    h-index

  2. RM
    Richard M. Bailey

    University of Oxford, United Kingdom

    2 publications · 35 citations

    2

    h-index

  3. JK
    Jens Koed Madsen

    University of Oxford, United Kingdom

    2 publications · 35 citations

    2

    h-index

  4. RB
    Reniel B. Cabral

    University of California, Santa Barbara, United States

    1 publications · 15 citations

    1

    h-index

  5. NH
    Neil Huth

    Commonwealth Scientific and Industrial Research Organisation, Australia

    1 publications · 65 citations

    1

    h-index

1–5 of 60

Venues

  1. Computers and Electronics in Agriculture

    2 publications · 114 citations

    2

    h-index

  2. Environmental Modelling & Software

    2 publications · 83 citations

    2

    h-index

  3. 1

    h-index

  4. Journal of Simulation

    JOS · 1 publications · 20 citations

    1

    h-index

  5. eTransportation

    1 publications · 78 citations

    1

    h-index

1–5