Ecology Transformed: The National Center for Ecological Analysis and Synthesis and the Changing Patterns of Ecological Research

Hackett, Edward J.; Parker, John N.; Conz, David; Rhoten, Diana; Parker, Andrew

doi:10.7551/mitpress/9780262151207.003.0016

Cited by 51 publications

(55 citation statements)

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“…For example, the 40 top priorities for science that can inform conservation and management policy in the USA rely principally on a sound foundation of ecological research [10]. As ecology expands its scope, it is becoming more collaborative and network and team based [11][12][13]. For example, research at individual long-term ecological research (LTER) sites in the USA is conducted collaboratively by teams consisting of an average of 18 cooperating investigators and 20 graduate students; inter-site and network-wide studies add further to the scope and scale of the LTER research enterprise [14].…”

Section: Ecology As An Evolving Disciplinementioning

confidence: 99%

“…Integrating source data from such studies is labor intensive and time consuming, because it requires understanding methodological differences, transforming data into a common representation, and manually converting and recoding data to compatible semantics before analysis can begin. Data integration for crosscutting studies is generally a manual process and can consume the majority of time involved in conducting collaborative research [1,11]. Although data integration is challenging, a set of approaches is emerging that explicitly encodes the semantics of observational data and then reasons across these semantics to semi-automate the process of data integration [44,45].…”

mentioning

confidence: 99%

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Ecoinformatics: supporting ecology as a data-intensive science

Michener

Jones

2012

Trends in Ecology & Evolution

357

324

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Section: Ecology As An Evolving Disciplinementioning

confidence: 99%

mentioning

confidence: 99%

Ecoinformatics: supporting ecology as a data-intensive science

Michener

Jones

2012

Trends in Ecology & Evolution

357

324

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“…The importance of face-to-face social interactions for rapid communication of ideas and information, building instrumental trust, i.e., trust associated with judgment of risk (Slovic 2000), and diffusing conflict (Hampton andParker 2011, Rubin andFornari 2011) are well recognized. A number of studies find that face-to-face group meetings are most effective in building team cohesiveness, developing trust, and increasing communication efficiency to accelerate idea generation (Hackett et al 2008, Hampton and Parker 2011, Rhoten 2003. Hampton and Parker (2011) report that the number of face-to-face meetings among team members is the strongest predictor of working group productivity and scientific impact, even when project total length of time is controlled for.…”

Section: Mechanisms To Connectmentioning

confidence: 99%

“…Large teams typically are organized explicitly into subteams focused on specific project objectives that provide the building blocks of collaboration (Rhoten 2003, Hackett et al 2008, Hampton and Parker 2011. They are represented in project organizational charts and provide the predetermined formal structure for organizing activities, for ensuring communication within the project, and for maintaining participant accountability.…”

Section: Goal-oriented Structuresmentioning

confidence: 99%

Architectures of adaptive integration in large collaborative projects

Morton¹,

Eigenbrode²,

Martin³

2015

E&S

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ABSTRACT. Collaborations to address complex societal problems associated with managing human-natural systems often require large teams comprised of scientists from multiple disciplines. For many such problems, large-scale, transdisciplinary projects whose members include scientists, stakeholders, and other professionals are necessary. The success of very large, transdisciplinary projects can be facilitated by attending to the diversity of types of collaboration that inevitably occur within them. As projects progress and evolve, the resulting dynamic collaborative heterogeneity within them constitutes architectures of adaptive integration (AAI). Management that acknowledges this dynamic and fosters and promotes awareness of it within a project can better facilitate the creativity and innovation required to address problems from a systems perspective. In successful large projects, AAI (1) functionally meets objectives and goals, (2) uses disciplinary expertise and concurrently bridges many disciplines, (3) has mechanisms to enable connection, (4) delineates boundaries to keep focus but retain flexibility, (5) continuously monitors and adapts, and (6) encourages project-wide awareness. These principles are illustrated using as case studies three large climate change and agriculture projects funded by the U.S. Department of Agriculture-National Institute of Food and Agriculture. Key Words: architectures of adaptive integration; collaborative science; team science INTRODUCTIONGeneration of innovative science and its applications to address complex societal problems associated with managing humannatural systems requires research approaches that mirror the complexity of these systems. However, the architecture of large, multidisciplinary, multi-institutional, multiyear projects that undertake this requisite systems approach research is not well understood, despite increasing public and private funding and a growing discourse on transdisciplinarity and team science. In this synthesis paper, diverse conceptions of the processes and structures associated with conducting collaborative research are used to develop architectures of adaptive integration (AAI) for large-scale projects. In this context AAI is defined as the explicit and implicit dynamic structures and processes that characterize collaborations among heterogeneous groups of scientists and stakeholders working to address a shared problem affecting complex systems over time.

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“…Miller et al (2008) addressed the causes behind this cultural distance, suggesting that LTER sites tend to have one dominant research paradigm that is not open to other ideas. The LTER Network has worked to encourage synthetic science across disciplines with the creation of the National Center for Ecological Analysis and Synthesis (Hackett et al 2008) and to fully integrate social science into the network . We suggest that these shifts do not always trickle down to the most junior levels of the network.…”

Section: Recommendation 2: Provide Network-level Support For Communitmentioning

confidence: 99%

The Next Generation of Scientists: Examining the Experiences of Graduate Students in Network-Level Social-Ecological Science

Romolini¹,

Record²,

Garvoille³

et al. 2013

E&S

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ABSTRACT. By integrating the research and resources of hundreds of scientists from dozens of institutions, network-level science is fast becoming one scientific model of choice to address complex problems. In the pursuit to confront pressing environmental issues such as climate change, many scientists, practitioners, policy makers, and institutions are promoting network-level research that integrates the social and ecological sciences. To understand how this scientific trend is unfolding among rising scientists, we examined how graduate students experienced one such emergent social-ecological research initiative, Integrated Science for Society and Environment, within the large-scale, geographically distributed Long Term Ecological Research (LTER) Network. Through workshops, surveys, and interviews, we found that graduate students faced challenges in how they conceptualized and practiced social-ecological research within the LTER Network. We have presented these conceptual challenges at three scales: the individual/project, the LTER site, and the LTER Network. The level of student engagement with and knowledge of the LTER Network was varied, and students faced different institutional, cultural, and logistic barriers to practicing social-ecological research. These types of challenges are unlikely to be unique to LTER graduate students; thus, our findings are relevant to other scientific networks implementing new social-ecological research initiatives.

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Ecology Transformed: The National Center for Ecological Analysis and Synthesis and the Changing Patterns of Ecological Research

Cited by 51 publications

References 0 publications

Ecoinformatics: supporting ecology as a data-intensive science

Ecoinformatics: supporting ecology as a data-intensive science

Architectures of adaptive integration in large collaborative projects

The Next Generation of Scientists: Examining the Experiences of Graduate Students in Network-Level Social-Ecological Science

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