A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations

Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.     

Seasonal variations of monocarbonyl and dicarbonyl in urban and sub-urban sites of Xi’an,China

Seventeen airborne carbonyls including monocarbonyls and dicarbonyls were determined in urban and sub-urban sites of Xi’an, China in three seasons in 2010. In winter, acetone was the most abundant carbonyl in the urban site due to usage of organic solvents in constructions and laboratories and its slower atmospheric removal mechanisms by photolysis and reaction with hydroxyl radical than those of formaldehyde and acetaldehyde. In the sub-urban site, acetaldehyde was the most abundant carbonyl, followed by formaldehyde and acetone. During summer, however, formaldehyde was the most dominant carbonyl in both sites. The photooxidations of a wide range of volatile organic compounds (VOCs) yielded much more formaldehyde than other carbonyls under high solar radiation and temperature. In the urban site, the average concentrations of dicarbonyls (i.e., glyoxal and methyglyoxal) in spring and summer were higher than that in winter. Transformation of aromatic VOCs emitted from fuel evaporation leads to the formation of 1,2-dicarbonyls. A reverse trend was observed in sub-urban sites, as explained by the relatively low abundances and accumulations of VOC precursors in the rural atmosphere during warm seasons. Moreover, cumulative cancer risk based on measured outdoor carbonyls (formaldehyde and acetaldehyde) in Xi’an Jiaotong University and Heihe was estimated (8.82?×?10^?5 and 4.96?×?10^?5, respectively). This study provides a clear map on the abundances of carbonyls and their source interpretation in the largest and the most economic city in Northwestern China.     

Evaluation of give kids a boost: A school-based program to increase booster seat use among urban children in economically disadvantaged areas

Objective: This study evaluated the effectiveness of a series of 1-year multifaceted school-based programs aimed at increasing booster seat use among urban children 4–7 years of age in economically disadvantaged areas.

Methods: During 4 consecutive school years, 2011–2015, the Give Kids a Boost (GKB) program was implemented in a total of 8 schools with similar demographics in Dallas County. Observational surveys were conducted at project schools before project implementation (P₀), 1–4 weeks after the completion of project implementation (P₁), and 4–5 months later (P₂). Changes in booster seat use for the 3 time periods were compared for the 8 project and 14 comparison schools that received no intervention using a nonrandomized trial process.

The intervention included (1) train-the-trainer sessions with teachers and parents; (2) presentations about booster seat safety; (3) tailored communication to parents; (4) distribution of fact sheets/resources; (5) walk-around education; and (6) booster seat inspections.

The association between the GKB intervention and proper booster seat use was determined initially using univariate analysis. The association was also estimated using a generalized linear mixed model predicting a binomial outcome (booster seat use) for those aged 4 to 7 years, adjusted for child-level variables (age, sex, race/ethnicity) and car-level variables (vehicle type). The model incorporated the effects of clustering by site and by collection date to account for the possibility of repeated sampling.

Results: In the 8 project schools, booster seat use for children 4–7 years of age increased an average of 20.9 percentage points between P₀ and P₁ (P₀ = 4.8%, P₁ = 25.7%; odds ratio [OR] = 6.9; 95% confidence interval [CI], 5.5, 8.7; P < .001) and remained at that level in the P₂ time period (P₂ = 25.7%; P < .001, for P₀ vs. P₂) in the univariate analysis. The 14 comparison schools had minimal change in booster seat use. The multivariable model showed that children at the project schools were significantly more likely to be properly restrained in a booster seat after the intervention (OR = 2.7; 95% CI, 2.2, 3.3) compared to the P₀ time period and compared to the comparison schools.

Conclusion: Despite study limitations, the GKB program was positively associated with an increase in proper booster seat use for children 4–7 years of age in school settings among diverse populations in economically disadvantaged areas. These increases persisted into the following school year in a majority of the project schools. The GKB model may be a replicable strategy to increase booster seat use among school-age children in similar urban settings.     

Assessing the implications of a 1.5 °C temperature limit for the Jamaican agriculture sector

Despite recent calls to limit future increases in the global average temperature to well below 2 °C, little is known about how different climatic thresholds will impact human society. Future warming trends have significant global food security implications, particularly for small island developing states (SIDS) that are recognized as being among the most vulnerable to global climate change. In the case of the Caribbean, any significant change in the region’s climate is likely to have significant adverse effects on the agriculture sector. This paper explores the potential biophysical impacts of a +?1.5 °C warming scenario on several economically important crops grown in the Caribbean island of Jamaica. Also, it explores differences to a >?2.0 °C warming scenario, which is more likely, if the current policy agreements cannot be complied with by the international community. We use the ECOCROP niche model to estimate how predicted changes in future climate could affect the growing conditions of several commonly cultivated crops from both future scenarios. We then discuss some key policy considerations for Jamaica’s agriculture sector, specifically related to the challenges posed to future adaptation pathways amidst growing climate uncertainty and complexity. Our model results show that even an increase less than +?1.5 °C is expected to have an overall negative impact on crop suitability and a general reduction in the range of crops available to Jamaican farmers. This observation is instructive as increases above the +?1.5 °C threshold would likely lead to even more irreversible and potentially catastrophic changes to the sustainability of Jamaica’s agriculture sector. The paper concludes by outlining some key considerations for future action, paying keen attention to the policy relevance of a +?1.5 °C temperature limit. Given little room for optimism with respect to the imminent changes that SIDS will need to confront in the near future, broad-based policy engagement by stakeholders in these geographies is paramount, irrespective of the climate warming scenario.     

Research priorities for managing the impacts and dependencies of business upon food,energy, water and the environment

Delivering access to sufficient food, energy and water resources to ensure human wellbeing is a major concern for governments worldwide. However, it is crucial to account for the ‘nexus’ of interactions between these natural resources and the consequent implications for human wellbeing. The private sector has a critical role in driving positive change towards more sustainable nexus management and could reap considerable benefits from collaboration with researchers to devise solutions to some of the foremost sustainability challenges of today. Yet opportunities are missed because the private sector is rarely involved in the formulation of deliverable research priorities. We convened senior research scientists and influential business leaders to collaboratively identify the top forty questions that, if answered, would best help companies understand and manage their food-energy-water-environment nexus dependencies and impacts. Codification of the top order nexus themes highlighted research priorities around development of pragmatic yet credible tools that allow businesses to incorporate nexus interactions into their decision-making; demonstration of the business case for more sustainable nexus management; identification of the most effective levers for behaviour change; and understanding incentives or circumstances that allow individuals and businesses to take a leadership stance. Greater investment in the complex but productive relations between the private sector and research community will create deeper and more meaningful collaboration and cooperation.     

Decreased Runoff Response to Precipitation,Little Missouri River Basin,Northern Great Plains,USA

High variability in precipitation and streamflow in the semiarid northern Great Plains causes large uncertainty in water availability. This uncertainty is compounded by potential effects of future climate change. We examined historical variability in annual and growing season precipitation, temperature, and streamflow within the Little Missouri River Basin and identified differences in the runoff response to precipitation for the period 1976‐2012 compared to 1939‐1975 (n = 37 years in both cases). Computed mean values for the second half of the record showed little change (<5%) in annual or growing season precipitation, but average annual runoff at the basin outlet decreased by 22%, with 66% of the reduction in flow occurring during the growing season. Our results show a statistically significant (p < 0.10) 27% decrease in the annual runoff response to precipitation (runoff ratio). Surface‐water withdrawals for various uses appear to account for <12% of the reduction in average annual flow volume, and we found no published or reported evidence of substantial flow reduction caused by groundwater pumping in this basin. Results of our analysis suggest that increases in monthly average maximum and minimum temperatures, including >1°C increases in January through March, are the dominant driver of the observed decrease in runoff response to precipitation in the Little Missouri River Basin.     

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.     

Bovine Tuberculosis and Badger Culling in England: An Animal Rights-Based Analysis of Policy Options

Bovine tuberculosis (bovine TB) is an important and controversial animal health policy issue in England, which impacts humans, cattle and badgers. The government policy of badger culling has led to widespread opposition, in part due to the conclusions of a large field trial recommending against culling, and in part because badgers are a cherished wildlife species. Animal rights (AR) theorists argue that sentient nonhumans should be accorded fundamental rights against killing and suffering. In bovine TB policy, however, pro-culling actors claim that badgers must be culled to avoid the slaughter of cattle. The first part of the paper compares AR theories of Regan, Francione, Cochrane, Garner and Donaldson and Kymlicka in the context of wildlife species. The second part of the paper applies these AR theories to bovine TB and badger control. AR theories are applied to badger control policy options of (1) do nothing, (2) badger culling, and (3) badger vaccination. We conclude that AR theories are strongly opposed to badger culling. In general, culling is prohibited due to a badger’s right to life and its rights against suffering. The AR theories support a do-nothing, i.e. non-culling, non-vaccination approach to badger control. In the case of the AR theories of Regan and Francione, this is based on abolitionist positions with respect to farming. For Cochrane, Garner, and Donaldson and Kymlicka, the do-nothing policy option is preferred because badger vaccination causes a degree of suffering which generally is not for the individual’s benefit.     

Method for Rapidly Assessing the Overtopping Risk of Bridges Due to Flooding over a Large Geographic Region

Hydraulic events are a leading cause of bridge failures. While these hydraulic events are accounted for in bridge design, changing environmental and land use conditions require continual updating of this risk. For example, after a bridge has been constructed, streamflow can change in unanticipated ways as a result of land use changes, geomorphic changes, and climate change. The objective of this research was to create a screening method able to quickly and inexpensively estimate overtopping risk across a collection of bridges based on the current streamflow conditions. The method uses a geographic information system, nationally available and standardized datasets, and recent regression equations to quantify bridge vulnerability to overtopping for flooding with varying return periods. This screening method could also be used to assist decision makers in updating the Waterway Adequacy field in the National Bridge Inventory, which indicates the overtopping risk of bridges. The method was applied to a portion of the Hampton Roads region of Virginia, United States that includes 475 bridges. The results of the analysis, when combined with transportation data for bridges, aid decision makers to assign further resources to complete more detailed analyses of bridges identified as being at risk for overtopping.     

Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.