Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Time perspective balance and team adaptation in dynamic task contexts

The concept of time perspective balance has attracted increased attention from scholars in the past decade, reflected in published evidence suggesting positive outcomes ranging from enhanced mood to life satisfaction for those individuals possessing balance among their past, present, and future time perspectives, and assumedly able to shift their time perspective to match situational demands. In this paper, we consider the notion of time perspective balance in an organizational setting within which much consequential adaptation often occurs—the team environment—and explore different configurations of time perspective balance in teams facing dynamic task contexts. Drawing from work on situational awareness, we first consider the mechanism by which time perspective balance likely influences individual adaptation in dynamic task-focused situations. Next, we postulate what types of team configurations—ones with more balanced time perspective uniformity or ones with more time perspective variety—might be more appropriate in dynamic contexts given key team conditions. We illustrate our analysis with examples from healthcare team settings and offer ideas for future research.     

Mapping Adolescents’ Sense of Place and Perceptions of Change in an Urban–Rural Transition Area

Environmental Management - Landscapes are changing, with rural areas becoming increasingly urbanized. Children and adolescents are underrepresented in the sense-of-place literature. Our study aimed...     

Optimization of capture–recapture monitoring of elusive species illustrated with a threatened grasshopper

Information on population sizes and trends of threatened species is essential for their conservation, but obtaining reliable estimates can be challenging. We devised a method to improve the precision of estimates of population size obtained from capture–recapture studies for species with low capture and recapture probabilities and short seasonal activity, illustrated with population data of an elusive grasshopper (Prionotropis rhodanica). We used data from 5 capture–recapture studies to identify methodological and environmental factors affecting capture and recapture probabilities and estimates of population size. In a simulation, we used the population size and capture and recapture probability estimates obtained from the field studies to identify the minimum number of sampling occasions needed to obtain unbiased and robust estimates of population size. Based on these results we optimized the capture–recapture design, implemented it in 2 additional studies, and compared their precision with those of the nonoptimized studies. Additionally, we simulated scenarios based on thresholds of population size in criteria C and D of the International Union for Conservation of Nature (IUCN) Red List to investigate whether estimates of population size for elusive species can reliably inform red-list assessments. Identifying parameters that affect capture and recapture probabilities (for the grasshopper time since emergence of first adults) and optimizing field protocols based on this information reduced study effort (−6% to −27% sampling occasions) and provided more precise estimates of population size (reduced coefficient of variation) compared with nonoptimized studies. Estimates of population size from the scenarios based on the IUCN thresholds were mostly unbiased and robust (only the combination of very small populations and little study effort produced unreliable estimates), suggesting capture–recapture can be considered reliable for informing red-list assessments. Although capture–recapture remains difficult and costly for elusive species, our optimization procedure can help determine efficient protocols to increase data quality and minimize monitoring effort.     

Conspecific brood parasitism in an upland-nesting bird: cues parasites use to select a nest

Behavioral Ecology and Sociobiology - In the animal kingdom, conspicuous colors are often used for inter- and intra-sexual communication. Even though primates are the most colorful mammalian taxon,...     

Muskox status,recent variation,and uncertain future

Ambio - Muskoxen (Ovibos moschatus) are an integral component of Arctic biodiversity. Given low genetic diversity, their ability to respond to future and rapid Arctic change is unknown, although...     

The tree species matters: Biodiversity and ecosystem service implications of replacing Scots pine production stands with Norway spruce

Ambio - The choice of tree species used in production forests matters for biodiversity and ecosystem services. In Sweden, damage to young production forests by large browsing herbivores is helping...     

Improving dialogue among researchers,local and indigenous peoples and decision-makers to address issues of climate change in the North

Ambio - The Circumpolar North has been changing rapidly within the last decades, and the socioeconomic systems of the Eurasian Arctic and Siberia in particular have displayed the most dramatic...