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The case for embedding researchers in conservation agencies
Dirk J Roux1,2, Richard T Kingsford3, Carly N Cook4
1Scientific Services, South African National Parks, PO Box 4283, George, 6539, South Africa.
Embedding research scientists within conservation agencies enhances evidence-based conservation. This model fosters knowledge exchange but requires further research to evaluate its effectiveness and address challenges for sustainable conservation efforts.
Area of Science:
- Conservation Science
- Environmental Management
- Knowledge Exchange
Background:
- Protected areas face anthropogenic threats, necessitating effective conservation strategies.
- Evidence-based decision-making and knowledge exchange are crucial for conservation success.
- Embedding research scientists within conservation agencies is a promising model for knowledge exchange.
Purpose of the Study:
- To explore the benefits, challenges, and opportunities of embedding research scientists within conservation agencies.
- To identify research needs for evaluating the effectiveness of the embedding model.
- To understand how this model supports evidence-based conservation.
Main Methods:
- Literature review and synthesis of practical experiences across continents.
- Analysis of the roles and contributions of embedded researchers.
- Identification of challenges in implementing and evaluating the embedding model.
Main Results:
- Embedded researchers build social capital, facilitate knowledge flow, coordinate research, and support long-term monitoring.
- Declining research capacity in conservation agencies presents a significant challenge.
- The effectiveness and institutional arrangements of the embedding model are poorly evaluated.
Conclusions:
- Embedding research scientists offers substantial benefits for evidence-based conservation.
- Further systematic research is needed to understand the costs, benefits, and optimal implementation of knowledge exchange models.
- Addressing challenges related to researcher credibility and agency integration is vital for model success.
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