Expanding the table: The web as a tool for participatory adaptive management in California forests

Kelly, Maggi; Ferranto, Shasta; Lei, Shufei; Ueda, Ken-ichi; Huntsinger, Lynn

doi:10.1016/j.jenvman.2012.04.035

Cited by 31 publications

(19 citation statements)

References 79 publications

(92 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Five subcategories were identified based on existing literature and after assessing the papers: (i) improved biological conservation and ecosystem management outcomes (Walters 1997, Roux and; (ii) improved governance (Clark and Clarke 2011); (iii) improved public participation (Stringer et al 2006, Allen and Gunderson 2011, Roux and Foxcroft 2011, Kelly et al 2012. Two additional subcategories: (iv) learning and understanding (Johnson 2011), and (v) adaptation and responsiveness (PahlWostl 2009), although being inherent traits of adaptive management (Holling 1978), were nevertheless included to verify that papers had been correctly selected.…”

Section: The Main Aims Of Adaptive Managementmentioning

confidence: 99%

Learning in Adaptive Management: Insights from Published Practice

Fabricius¹,

Cundill²

2014

E&S

View full text Add to dashboard Cite

ABSTRACT. Adaptive management is often advocated as a solution to understanding and managing complexity in social-ecological systems. Given the centrality of learning in adaptive management, it remains unclear how learning in adaptive management is understood to occur, who learns, what they learn about, and how they learn. We conducted a systematic review using the Thomson Reuters Web of Science, and searched specifically for examples of the practical implementation of adaptive management between 2011 and 2013, i.e., excluding articles that suggested frameworks, models, or recommendations for future action. This provided a subset of 22 papers that were analyzed using five elements: the aims of adaptive management as stated in each paper; the reported achievements of adaptive management; what was learned; who learned; and how they learned. Our results indicate that, although most published adaptive management initiatives aimed at improvements in biological conservation or ecosystem management, scholars of adaptive management tend to report on learning more about governance and about learning, than about ecosystems or biological conservation. Whereas almost all the papers (91%) listed improvements in biological conservation and ecosystem management as aims, 59% reported these as achievements. Whereas only 27% listed improved governance as an aim, 73% mentioned this as an achievement. Conservation scientists and academics reporting on adaptive management tend to learn among themselves, and very seldom (18%) with external stakeholders. Adaptive ecosystem management is dominated by direct assessment and single-loop learning aimed at improving existing practices (86%), with about 50% engaged in double-loop learning and a similar number in deutero-learning (learning about learning). Some adaptive managers (36%) combined double-and single-loop learning and the majority of these (6/8) reported on conservation achievements. A possible explanation for these findings is that adaptive management is an evolutionary process and in most instances is still in an early pioneering stage, possibly held back by participants' capacity for learning. The constraint of learning capacity may also explain why so few adaptive management initiatives reported on learning with societal stakeholders.

show abstract

Section: The Main Aims Of Adaptive Managementmentioning

confidence: 99%

Learning in Adaptive Management: Insights from Published Practice

Fabricius¹,

Cundill²

2014

E&S

View full text Add to dashboard Cite

show abstract

“…The challenges and strategies described below summarize our analyses of the problems and the solutions we ultimately applied. Our efforts were supported by extensive documentation of meetings both among the UC science team, our agency partners, and with the public (Rodrigues 2008;Kelly et al 2012).…”

Section: Background/methodsmentioning

confidence: 99%

“…In SNAMP, the UC science team including principal investigators, their students, and staff spent much time preparing and delivering outreach in multiple forms and venues (Table 3). This effort was considered necessary to encourage public participation (Kelly et al 2012).…”

Section: ) Public Engagement Through Effective Communicationmentioning

confidence: 99%

A Word to the Wise: Advice for Scientists Engaged in Collaborative Adaptive Management

Hopkinson

Huber

Saah

2017

Environmental Management

View full text Add to dashboard Cite

Collaborative adaptive management (CAM) is a process for making decisions about the environment in the face of uncertainty and conflict. Scientists have a central role to play in these decisions. However, while scientists are well-trained to reduce uncertainty by discovering new knowledge, most lack experience with the means to mitigate conflict in contested situations. To address this gap, we drew from our efforts coordinating a large CAM effort, the Sierra Nevada Adaptive Management Project, to offer advice to our fellow environmental scientists. Key challenges posed by CAM include the confusion caused by multiple institutional cultures, the need to provide information at management-relevant scales, frequent turn-over in participants, fluctuations in enthusiasm among key constituencies, and diverse definitions of success among partners. Effective strategies included a dedication to consistency, a commitment to transparency, the willingness to communicate frequently via multiple forums, and the capacity for flexibility.CAM represents a promising, new model for scientific engagement with the public. Learning the lessons of effective collaboration in environmental management is an essential task to achieve the shared goal of a sustainable future.

show abstract

“…Such participation has engendered a need for a more transparent system of data collection and distribution. Contemporary large-scale citizen science efforts promote and alleviate some issues of data transparency and sharing by promoting open data collection, distribution, and assessment (Kearns et al 2003;Kelly et al 2012). Technological advances in computer science have increased our ability to query, visualize and use large heterogeneous collections in meaningful ways (Baird 2010;Fox and Hendler 2011;Reichman et al 2011;Hampton et al 2013).…”

Section: Open Data Frameworkmentioning

confidence: 99%

Rescuing and Sharing Historical Vegetation Data for Ecological Analysis: The California Vegetation Type Mapping Project

Kelly¹

2016

Biodiv. Inf.

Self Cite

View full text Add to dashboard Cite

Abstract.-Research efforts that synthesize historical and contemporary ecological data with modeling approaches improve our understanding of the complex response of species, communities, and landscapes to changing biophysical conditions through time and in space. Historical ecological data are particularly important in this respect. There are remaining barriers that limit such data synthesis, and technological improvements that make multiple diverse datasets more readily available for integration and synthesis are needed. This paper presents one case study of the Wieslander Vegetation Type Mapping project in California and highlights the importance of rescuing, digitizing and sharing historical datasets. We review the varied ecological uses of the historical collection: the vegetation maps have been used to understand legacies of land use change and plan for the future; the plot data have been used to examine changes to chaparral and forest communities around the state and to predict community structure and shifts under a changing climate; the photographs have been used to understand changing vegetation structure; and the voucher specimens in combination with other specimen collections have been used for large scale distribution modeling efforts. The digitization and sharing of the data via the web has broadened the scope and scale of the types of analysis performed. Yet, additional research avenues can be pursued using multiple types of VTM data, and by linking VTM data with contemporary data. The digital VTM collection is an example of a data infrastructure that expands the potential of large scale research through the integration and synthesis of data drawn from numerous data sources; its journey from analog to digital is a cautionary tale of the importance of finding historical data, digitizing it with best practices, linking it with other datasets, and sharing it with the research community.

show abstract

Expanding the table: The web as a tool for participatory adaptive management in California forests

Cited by 31 publications

References 79 publications

Learning in Adaptive Management: Insights from Published Practice

Learning in Adaptive Management: Insights from Published Practice

A Word to the Wise: Advice for Scientists Engaged in Collaborative Adaptive Management

Rescuing and Sharing Historical Vegetation Data for Ecological Analysis: The California Vegetation Type Mapping Project

Contact Info

Product

Resources

About