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Institutional authority and responsibility for allocating water to ecosystems ("ecologically available water" [EAW]) is spread across local, state, and federal agencies, which operate under a range of statutes, mandates, and planning processes. We use a case study of the Upper Missouri Headwaters Basin in southwestern Montana, United States, to illustrate this fragmented institutional landscape. Our goals are to (a) describe the patchwork of agencies and institutional actors whose intersecting authorities and actions influence the EAW in the study basin; (b) describe the range of governance mechanisms these agencies use, including laws, policies, administrative programs, and planning processes; and (c) assess the extent to which the collective governance regime creates gaps in responsibility. We find the water governance regime includes a range of nested mechanisms that in various ways facilitate or hinder the governance of EAW. We conclude the current multilevel governance regime leaves certain aspects of EAW unaddressed and does not adequately account for the interconnections between water in different parts of the ecosystem, creating integrative gaps. We suggest that more intentional and robust coordination could provide a means to address these gaps. [ABSTRACT FROM AUTHOR]

The ecosystem performance approach, used in a previously published case study focusing on the Nebraska Sandhills, proved to minimize impacts of non-climatic factors (e.g., overgrazing, fire, pests) on the remotely-sensed signal of seasonal vegetation greenness resulting in a better attribution of its changes to climate variability. The current study validates the applicability of this approach for assessment of seasonal and interannual climate impacts on forage production in the western United States semi-arid grasslands. Using a piecewise regression tree model, we developed the Expected Ecosystem Performance (EEP), a proxy for annual forage production that reflects climatic influences while minimizing impacts of management and disturbances. The EEP model establishes relations between seasonal climate, site-specific growth potential, and long-term growth variability to capture changes in the growing season greenness measured via a time-integrated Normalized Difference Vegetation Index (NDVI) observed using a Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting 19 years of EEP were converted to expected biomass (EB, kg ha−1 year−1) using a newly-developed relation with the Soil Survey Geographic Database range production data (R2 = 0.7). Results were compared to ground-observed biomass datasets collected by the U.S. Department of Agriculture and University of Nebraska-Lincoln (R2 = 0.67). This study illustrated that this approach is transferable to other semi-arid and arid grasslands and can be used for creating timely, post-season forage production assessments. When combined with seasonal climate predictions, it can provide within-season estimates of annual forage production that can serve as a basis for more informed adaptive decision making by livestock producers and land managers. [ABSTRACT FROM AUTHOR]

Drought is an abstract and complex phenomenon that can be difficult for many people to comprehend. Proactive planning to improve response during drought events is necessary but complicated because it involves stakeholders and decision-makers with competing interests. A category of games, called serious games, have proven to be helpful when learning about abstract concepts, and for improving communication and conflict resolution with respect to water-related issues. In this study, we present a new in-person role-playing game that serves as a drought educational tool in both classroom and professional settings. The message of the game emphasizes the importance of communication and cooperation between various communities and sectors that can be affected by drought. Furthermore, it also encourages discussions and collaborations between stakeholders involved in drought planning and can serve as an icebreaker activity. The game has been played in a variety of settings including university classes, university extension workshops, and drought workshops. This study describes the game itself, its development, and the results of surveys from game participants that were used to evaluate the usability of the game as an educational and icebreaker activity. [ABSTRACT FROM AUTHOR]

Land management practices and disturbances (e.g. overgrazing, fire) have substantial effects on grassland forage production. When using satellite remote sensing to monitor climate impacts, such as drought stress on annual forage production, minimizing land management practices and disturbance effects sends a clear climate signal to the productivity data. This study investigates the effect of this climate signal by: (1) providing spatial estimates of expected biomass under specific climate conditions, (2) determining which drought indices explain the majority of interannual variability in this biomass, and (3) developing a predictive model that estimates the annual biomass early in the growing season. To address objective 1, this study uses an established methodology to determine Expected Ecosystem Performance (EEP) in the Nebraska Sandhills, US, representing annual forage levels after accounting for non-climatic influences. Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) data were used to approximate actual ecosystem performance. Seventeen years (2000–2016) of annual EEP was calculated using piecewise regression tree models of site potential and climate data. Expected biomass (EB), EEP converted to biomass in kg*ha−1*yr−1, was then used to examine the predictive capacity of several drought indices and the onset date of the growing season. Subsets of these indices were used to monitor and predict annual expected grassland biomass. Independent field-based biomass production data available from two Sandhills locations were used for validation of the EEP model. The EB was related to field-based biomass production (R2 = 0.66 and 0.57) and regional rangeland productivity statistics of the Soil Survey Geographic Database (SSURGO) dataset. The Evaporative Stress Index (ESI), the 3- and 6-month Standardized Precipitation Index (SPI), and the U.S. Drought Monitor (USDM), which represented moisture conditions during May, June and July, explained the majority of the interannual biomass variability in this grassland system (three-month ESI explained roughly 72% of the interannual biomass variability). A new model was developed to use drought indices from early in the growing season to predict the total EB for the whole growing season. This unique approach considers only climate-related drought signal on productivity. The capability to estimate annual EB by the end of May will potentially enable land managers to make informed decisions about stocking rates, hay purchase needs, and other management issues early in the season, minimizing their potential drought losses. [ABSTRACT FROM AUTHOR]