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Related Concept Videos

Observational Learning01:12

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Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
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Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
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Constructing a roadway embankment over uneven terrain requires precise leveling to ensure stability and proper drainage. Surveyors use a leveling instrument and staff to calculate ground elevations and determine the required fill material at each point along the embankment alignment.The process begins by positioning a leveling instrument near a benchmark with a known elevation. A backsight reading establishes the instrument height, which serves as a reference for subsequent measurements. A...
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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
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What is Conservation Biology?01:57

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The potential for double-loop learning to enable landscape conservation efforts.

Brian Petersen1, Jensen Montambault, Marni Koopman

  • 1Western Michigan University, 1903 W Michigan, Kalamazoo, MI, 49008-5419, USA, brian.petersen@wmich.edu.

Environmental Management
|July 24, 2014
PubMed
Summary
This summary is machine-generated.

Landscape Conservation Cooperatives (LCCs) utilize double-loop learning to navigate complex, multi-stakeholder collaborations. This approach addresses diverse viewpoints and accountability in large-scale conservation efforts.

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Area of Science:

  • Conservation Science
  • Environmental Management
  • Social Science

Background:

  • Landscape-level conservation necessitates complex, multi-agency, cross-boundary collaborations.
  • Traditional learning models are challenged by the scale and stakeholder diversity in modern conservation networks.

Purpose of the Study:

  • To examine learning structures within Landscape Conservation Cooperatives (LCCs).
  • To understand the evolution of goals and values in maturing multi-stakeholder conservation collaborations.

Main Methods:

  • Employed semi-structured interviews analyzed with NVivo software.
  • Utilized a charrette-style workshop to explore LCCs' original goals versus emergent values.

Main Results:

  • Identified a divergence between initial LCC objectives and the values that emerged during collaboration.
  • Highlighted the importance of considering accountability within multi-stakeholder learning frameworks.

Conclusions:

  • Double-loop learning provides a suitable theoretical framework for landscape-scale conservation.
  • Social science and public health methods can inform the practical implementation of collaborative learning in conservation.