Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

Circumpolar status of Arctic ptarmigan: Population dynamics and trends

Rock ptarmigan (Lagopus muta) and willow ptarmigan (L. lagopus) are Arctic birds with a circumpolar distribution but there is limited knowledge about their status and trends across their circumpolar distribution. Here, we compiled information from 90 ptarmigan study sites from 7 Arctic countries, where almost half of the sites are still monitored. Rock ptarmigan showed an overall negative trend on Iceland and Greenland, while Svalbard and Newfoundland had positive trends, and no significant trends in Alaska. For willow ptarmigan, there was a negative trend in mid-Sweden and eastern Russia, while northern Fennoscandia, North America and Newfoundland had no significant trends. Both species displayed some periods with population cycles (short 3–6 years and long 9–12 years), but cyclicity changed through time for both species. We propose that simple, cost-efficient systematic surveys that capture the main feature of ptarmigan population dynamics can form the basis for citizen science efforts in order to fill knowledge gaps for the many regions that lack systematic ptarmigan monitoring programs.

     

Modelling the Distribution and Quality of Sand and Gravel Resources in 3D: a Case Study in the Thames Basin,UK

Three-dimensional (3D) models are often utilised to assess the presence of sand and gravel deposits. Expanding these models to provide a better indication of the suitability of the deposit as aggregate for use in construction would be advantageous. This, however, leads to statistical challenges. To be effective, models must be able to reflect the interdependencies between different criteria (e.g. depth to deposit, thickness of deposit, ratio of mineral to waste, proportion of ‘fines’) as well as the inherent uncertainty introduced because models are derived from a limited set of boreholes in a study region. Using legacy borehole data collected during a systematic survey of sand and gravel deposits in the UK, we have developed a 3D model for a 2400 km² region close to Reading, southern England. In developing the model, we have reassessed the borehole grading data to reflect modern extraction criteria and explored the most suitable statistical modelling technique. The additive log-ratio transform and the linear model of coregionalization have been applied, techniques that have been previously used to map soil texture classes in two dimensions, to assess the quality of sand and gravel deposits in the area. The application of these statistical techniques leads to a model which can be used to generate thousands of plausible realisations of the deposit which fully reflect the extent of model uncertainty. The approach offers potential to improve regional-scale mineral planning by providing an enhanced understanding of sand and gravel deposits and the extent to which they meet current extraction criteria.

     

Adaptation of Climate Model Projections of Streamflow to Account for Upstream Anthropogenic Impairments

A statistical procedure is developed to adjust natural streamflows simulated by dynamical models in downstream reaches, to account for anthropogenic impairments to flow that are not considered in the model. The resulting normalized downstream flows are appropriate for use in assessments of future anthropogenically impaired flows in downstream reaches. The normalization is applied to assess the potential effects of climate change on future water availability on the Rio Grande at a gage just above the major storage reservoir on the river. Model‐simulated streamflow values were normalized using a statistical parameterization based on two constants that relate observed and simulated flows over a 50‐year historical baseline period (1964–2013). The first normalization constant is a ratio of the means, and the second constant is the ratio of interannual standard deviations between annual gaged and simulated flows. This procedure forces the gaged and simulated flows to have the same mean and variance over the baseline period. The normalization constants can be kept fixed for future flows, which effectively assumes that upstream water management does not change in the future, or projected management changes can be parameterized by adjusting the constants. At the gage considered in this study, the effect of the normalization is to reduce simulated historical flow values by an average of 72% over an ensemble of simulations, indicative of the large fraction of natural flow diverted from the river upstream from the gage. A weak tendency for declining flow emerges upon averaging over a large ensemble, with tremendous variability among the simulations. By the end of the 21st Century the higher‐emission scenarios show more pronounced declines in streamflow.     

Applying the zoo model to conservation of threatened exceptional plant species

Maintaining a living plant collection is the most common method of ex situ conservation for plant species that cannot be seed banked (i.e., exceptional species). Viability of living collections, and their value for future conservation efforts, can be limited without coordinated efforts to track and manage individuals across institutions. Using a pedigree-focused approach, the zoological community has established an inter-institutional infrastructure to support long-term viability of captive animal populations. We assessed the ability of this coordinated metacollection infrastructure to support the conservation of 4 plant species curated in living collections at multiple botanic gardens around the world. Limitations in current practices include the inability to compile, share, and analyze plant collections data at the individual level, as well as difficulty in tracking original provenance of ex situ material. The coordinated metacollection framework used by zoos can be adopted by the botanical community to improve conservation outcomes by minimizing the loss of genetic diversity in collections. We suggest actions to improve ex situ conservation of exceptional plant species, including developing a central database to aggregate data and track unique individuals of priority threatened species among institutions and adapting a pedigree-based population management tool that incorporates life-history aspects unique to plants. If approached collaboratively across regional, national, and global scales, these actions could transform ex situ conservation of threatened plant species.