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Tamara U. Wall, Alison M. Meadow, and Alexandra Horganic

Abstract

Resource managers and decision-makers are increasingly tasked with integrating climate change science into their decisions about resource management and policy development. This often requires climate scientists, resource managers, and decision-makers to work collaboratively throughout the research processes, an approach to knowledge development that is often called “coproduction of knowledge.” The goal of this paper is to synthesize the social science theory of coproduction of knowledge, the metrics currently used to evaluate usable or actionable science in several federal agencies, and insights from experienced climate researchers and program managers to develop a set of 45 indicators supporting an evaluation framework for coproduced usable climate science. Here the proposed indicators and results from two case studies that were used to test the indicators are presented, as well as lessons about the process of evaluating the coproduction of knowledge and collaboratively producing climate knowledge.

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Alison M. Meadow, Michael A. Crimmins, and Daniel B. Ferguson

To make decisions about drought declarations, status, and relief funds, decision makers need high-quality local-level drought impact data. In response to this need in Arizona the Arizona DroughtWatch program was created, which includes an online drought impacts reporting system. Despite extensive and intensive collaboration and consultation with the intended public participants, Arizona DroughtWatch has had few consistent users and has failed to live up to its goal of providing decision makers or the public with high-quality drought impacts data. Based on an evaluation of the DroughtWatch program, the authors found several weaknesses in the public-participation reporting-system model including that participation was reduced because of participants' over-commitment and time constraints, consultation fatigue, and confusion about the value of qualitative impact reports. Based on these findings, the authors recommend that professional resource agency personnel provide the backbone of drought impacts monitoring to ensure that decision makers receive the high-quality, consistent information they require. Public participation in impacts monitoring efforts can also be improved using this model. Professional observers can help attract volunteers who consider access to high-quality data an incentive to visit the Arizona DroughtWatch site and who may be more likely to participate in impacts monitoring if they see examples of how the information is being used by decision makers.

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Alison M. Meadow, Daniel B. Ferguson, Zack Guido, Alexandra Horangic, Gigi Owen, and Tamara Wall

Abstract

Coproduction of knowledge is believed to be an effective way to produce usable climate science knowledge through a process of collaboration between scientists and decision makers. While the general principles of coproduction—establishing long-term relationships between scientists and stakeholders, ensuring two-way communication between both groups, and keeping the focus on the production of usable science—are well understood, the mechanisms for achieving those goals have been discussed less. It is proposed here that a more deliberate approach to building the relationships and communication channels between scientists and stakeholders will yield better outcomes. The authors present five approaches to collaborative research that can be used to structure a coproduction process that each suit different types of research or management questions, decision-making contexts, and resources and skills available to contribute to the process of engagement. By using established collaborative research approaches scientists can be more effective in learning from stakeholders, can be more confident when engaging with stakeholders because there are guideposts to follow, and can assess both the process and outcomes of collaborative projects, which will help the whole community of stakeholder-engaged climate-scientists learn about coproduction of knowledge.

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Daniel B. Ferguson, Anna Masayesva, Alison M. Meadow, and Michael A. Crimmins

Abstract

Drought monitoring and drought planning are complex endeavors. Measures of precipitation or streamflow provide little context for understanding how social and environmental systems impacted by drought are responding. Here the authors report on collaborative work with the Hopi Tribe—a Native American community in the U.S. Southwest—to develop a drought information system that is responsive to local needs. A strategy is presented for developing a system that is based on an assessment of how drought is experienced by Hopi citizens and resource managers, that can incorporate local observations of drought impacts as well as conventional indicators, and that brings together local expertise with conventional science-based observations. The system described here is meant to harness as much available information as possible to inform tribal resource managers, political leaders, and citizens about drought conditions and to also engage these local drought stakeholders in observing, thinking about, and helping to guide planning for drought.

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Michael A. Crimmins, Daniel B. Ferguson, Alison M. Meadow, and Jeremy L. Weiss

Abstract

Monitoring drought conditions in arid and semiarid regions characterized by high levels of intra- and interannual hydroclimatic variability is a challenging task. Typical drought-monitoring indices that are based on monthly-scale data lack sufficient temporal resolution to detect hydroclimatic extremes and, when used operationally, may not provide adequate indication of drought status. In a case study focused on the Four Corners region of the southwestern United States, the authors used recently standardized World Meteorological Organization climate extremes indices to discern intra-annual hydroclimatic extremes and diagnose potential drought status in conjunction with the simple metric of annual total precipitation. By applying data-reduction methods to a suite of metrics calculated using daily data for 1950–2014, the authors identified five extremes indices that provided additional insight into interannual hydroclimatic variability. Annual time series of these indices revealed anomalous years characterized by shifts in the seasonal distribution of precipitation and in the intensity and frequency of individual events. The driest 4-yr intervals over the study period, characterized by similar annual and interval total precipitation anomalies, represent dramatically different assemblages of index values, which are interpreted as different “flavors” of drought. In turn, it is expected that varying drought impacts on ecosystems, agricultural systems, and water resources would emerge under these different flavors of drought. Results from this study indicate that operational drought monitoring and historical drought assessments in arid and semiarid regions would benefit from the additional insight that daily-based hydroclimatic extremes indices provide, especially in light of expected climate change–driven changes to the hydrologic cycle.

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