The challenge of providing environmental flow rules to sustain river ecosystems.

Accounting for natural differences in flow variability among rivers, and understanding the importance of this for the protection of freshwater biodiversity and maintenance of goods and services that rivers provide, is a great challenge for water managers and scientists. Nevertheless, despite considerable progress in understanding how flow variability sustains river ecosystems, there is a growing temptation to ignore natural system complexity in favor of simplistic, static, environmental flow "rules" to resolve pressing river management issues. We argue that such approaches are misguided and will ultimately contribute to further degradation of river ecosystems. In the absence of detailed empirical information of environmental flow requirements for rivers, we propose a generic approach that incorporates essential aspects of natural flow variability shared across particular classes of rivers that can be validated with empirical biological data and other information in a calibration process. We argue that this approach can bridge the gap between simple hydrological "rules of thumb" and more comprehensive environmental flow assessments and experimental flow restoration projects.     

Stimulation of root formation in Posidonia oceanica cuttings by application of auxins (NAA and IBA)

At the present, the long period (from 3 up to 12 months) to form roots from rhizome cuttings of Posidonia oceanica is the major cause of transplant failure. To promote earlier rooting, the effects of different concentrations (5 and 10 mg/l) of two auxins, namely indole-3-butyric acid (IBA) and α-naphtalen aetic acid (NAA), and the time of collection on rooting of plagiotropic and orthotropic cuttings of P. oceanica were tested. Rooting, survival and growth of cuttings were assessed 1 month after planting in a mesocosm. Results demonstrated that the use of auxin was essential to achieve root initiation within the observation period. Irrespective of plant source and collection time, IBA and NAA (5 mg/l) treatments increased the rooting capacity in cuttings. The highest rooting success (i.e. percentage of the survived cuttings that rooted) obtained was 33%. Results also revealed that the survival rate and percentages of cuttings with leaf growth and emergence of new leaves on their terminal shoot were influenced by the collection time × plant source interaction, but were unaffected by the auxin treatment. Orthotropic cuttings taken in November and February showed the highest survival rate (100%). No differences in survival among months were detected for plagiotropic cuttings. In May and July, more plagiotropic cuttings survived (80±7 and 75±6%) compared to orthotropic cuttings (58±7 and 51±4%). Overall, more plagiotropic cuttings showed leaf elongation compared to orthotropic ones, but the inverse was observed in November. A higher percentage of cuttings with emergence of new leaves was observed in the plagiotropic type as compared to the orthotropic one, and in general February and November were the best months for leaf production (28±4 and 38±7%). Finally, the percentage of cuttings that had changed leaf growth orientation (from orthotropic to plagiotropic) was significantly higher in November (63±13%) compared to the other months and tended to be higher in cuttings treated with the auxins compared to controls. These preliminary findings indicate that exposure to IBA or NAA (5 mg/l) was effective in stimulating rooting in P. oceanica without inhibiting plant growth. Therefore, this simple pre-planting practice should be beneficial in restoration attempts. Based on the trend observed, rhizomes should be prepared preferably in late autumn–winter and then planted into restoration stands to achieve a prompt rooting response and the best survival rate. Clearly, future work is needed to maximize the rooting success of cuttings.     

Mobilization of arsenic in groundwater of Bangladesh: evidence from an incubation study

The extensive extraction of arsenic (As)-contaminated groundwaters for drinking, household and agricultural purposes represents a serious health concern in many districts of Bangladesh. This laboratory-based incubation study investigated the sources and mechanisms of As mobilization in these groundwaters. Several incubation studies were carried out using sediments collected from the Bangladesh aquifer that were supplemented, or not, with different nutrients, followed by an analysis of the sediment suspensions for pH, ORP (oxidation-reduction potential), EC (electrical conductivity) and As and Fe(ΙΙ) concentrations. In the substrate-amended sediment suspensions incubated under anaerobic environment, there was a mobilization of As (maximum: 50–67 μg/l) and Fe(ΙΙ) (maximum: 182 μg/l), while the ORP value decreased immediately and drastically (as much as −468 mV to −560 mV) within 5–6 days. In the sediment suspensions incubated under control and aerobic conditions, no significant As mobilization occurred. The simultaneous mobilization of As and Fe(ΙΙ) from sediments is a strong indication that their mobilization resulted from the reduction of Fe oxyhydroxide by the enhanced activity of indigenous bacteria present in the sediments; this phenomenon also provides insights on the mobilization mechanism of As in groundwater. The concentrations of As in the sediments used in the incubation studies were strongly linked to the gradients of redox potential development that was stimulated by the quantity of organic nutrient (glucose) used. The penetration of surface-derived organic matter into the shallow aquifer may stimulate the activity of microbial communities, thereby leading to a reduction of iron oxyhydroxide and As release.     

Propagation of olfactory information within the honeybee hive

Transfer of information about food source characteristics within insect societies is essential to colony-foraging success. The food odor communicated within honeybee hives has been shown to be important for food source exploitation. When successful foragers return to the nest and transfer the collected nectar to hive mates through mouth-to-mouth contacts (trophallaxis), potential recruits receiving these samples learn the food odor by associative learning. The food then becomes rapidly distributed among colony members, which is mainly a consequence of the numerous trophallaxes between hive-mates of all ages during food processing. We tested whether the distribution of food among hive mates causes a propagation of olfactory information within the hive. Using the proboscis extension response paradigm, we show that large proportions of bees of the age groups representing the main worker castes, 4 to 9-day-old bees (nurse-aged bees), 12 to 16-day-old bees (food processor-aged bees), and actual foragers (about 17+ day old bees) associatively learn the food odor in the course of processing food that has been collected by only a few foragers. Results further suggest that the information is shared more or less equally between bees of the three age groups. This shows that olfactory information about the flower species exploited by foragers is distributed within the entire colony and is acquired by bees of all age groups, which may influence many behaviors inside and outside the hive.     

Male approach and female avoidance as mechanisms of population discrimination in sagebrush lizards

Reproductive isolation and speciation can result from female choice for particular males. Isolation can also result, however, from male mating preferences or from aggressive encounters which then influence mating decisions. In this study, we use laboratory discrimination trials to study the behavioral mechanisms of population discrimination in sagebrush lizards (Sceloporus graciosus). We specifically ask three questions about population-level discrimination: (1) Does it vary in strength in relation to the geographic distance between the populations? (2) Is it more apparent in inter- or intra-sexual interactions? (3) Does it take the form of attraction or avoidance? We ran 890 trials that tested the ability of male and female sagebrush lizards from one population to discriminate their own population from four other populations. In addition, we utilized both sequential and simultaneous-choice designs, which enabled us to distinguish between attraction and avoidance. We found that most population-level discrimination was exhibited by male lizards preferring to associate with particular types of females, as well as female avoidance of particular types of males. The strength and direction of both discriminations depended on the populations compared and on whether the tests were conducted as sequential- or simultaneous-choice tests, producing a complex relationship between geographic distance and behavioral discrimination. Our results suggest that there are roles for male attraction and female avoidance in population discrimination, reproductive isolation, and speciation.     

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.     

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).     

Environmental pollution,hydropower and nuclear energy generation before and after catastrophe: Bathtub-Weibull curve and MS-VECM methods

In this paper, the life span of hydro and nuclear energy generations and the relationship between hydro and nuclear energy generations, environmental pollution, and economic growth were investigated for Japan covering the period of 1960–2018 by employing the Bathtub-Weibull curve and Markov switching-vector error correcting (MSVEC) method, respectively. According to the Bathtub-Weibull curve analysis, a rising failure rate for nuclear energy was found, indicating that the life of nuclear energy has expired, but a decreasing failure rate for hydroelectric energy has been detected. Then two different MSVEC models were used. The MSVEC method, unlike traditional approaches, determines the relationship between variables under different regimes. The results of MSVEC methods indicate three important points. First, regime-dependent asymmetry and regime changes are crucial for policy recommendations. Second, the shocks to hydropower and nuclear energy generations cause temporary deviations from the long-run growth path in both regimes. Lastly, the increase in hydropower generation leads to a decrease in environmental pollution and an increase in GDP, and an increase in nuclear power generation increases pollution and growth in both regimes.