public lands management
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2022 ◽  
Author(s):  
Tyler A Beeton ◽  
Antony S Cheng ◽  
Melanie M Colavito

Abstract Collaboration is increasingly emphasized as a tool to realize national-level policy goals in public lands management. Yet, collaborative governance regimes (CGRs) are nested within traditional bureaucracies and are affected by internal and external disruptions. The extent to which CGRs adapt and remain resilient to these disruptions remains under-explored. Here, we distill insights from an assessment of the Collaborative Forest Landscape Restoration Program (CFLRP) projects and other CGRs. We asked (1) how do CGRs adapt to disruptions? and (2) what barriers constrained CGR resilience? Our analysis is informed by a synthesis of the literature, case examples and exemplars from focus groups, and a national CFLRP survey. CGRs demonstrated the ability to mobilize social capital, learning, resources, and flexibility to respond to disruptions. Yet authority, accountability, and capacity complicated collaborative resilience. We conclude with policy and practice recommendations to cultivate collaborative resilience moving forward. Study Implications Collaborative approaches between public lands management agencies and nongovernment organizations have become common in forest restoration. Yet collaborative progress may be affected by turnover, wildfire disturbances, or legal or policy changes. We assessed how forest collaboratives in the United States adapted to changes that affected their performance and documented the factors that constrained response. We found that forest collaboratives developed myriad strategies to adapt to these changes, although limited authority, capacity, and accountability constrain adaptation options. We offer policy and practice recommendations to overcome these constraints, increase adaptation options, and enhance the sustainability of forest collaboratives.


2008 ◽  
Vol 84 (2) ◽  
pp. 282-305 ◽  
Author(s):  
C. Mansfield ◽  
D. J. Phaneuf ◽  
F. R. Johnson ◽  
J.-C. Yang ◽  
R. Beach

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