An individual and a sex odor signature in kittiwakes? Study of the semiochemical composition of preen secretion and preen down feathers

The importance of olfaction in birds’ social behavior has long been denied. Avian chemical signaling has thus been relatively unexplored. The black-legged kittiwake provides a particularly appropriate model for investigating this topic. Kittiwakes preferentially mate with genetically dissimilar individuals, but the cues used to assess genetic characteristics remain unknown. As in other vertebrates, their body odors may carry individual and sexual signatures thus potentially reliably signaling individual genetic makeup. Here, we test whether body odors in preen gland secretion and preen down feathers in kittiwakes may provide a sex and an individual signature. Using gas chromatography and mass spectrometry, we found that male and female odors differ quantitatively, suggesting that scent may be one of the multiple cues used by birds to discriminate between sexes. We further detected an individual signature in the volatile and nonvolatile fractions of preen secretion and preen down feathers. These results suggest that kittiwake body odor may function as a signal associated with mate recognition. It further suggests that preen odor might broadcast the genetic makeup of individuals, and could be used in mate choice to assess the genetic compatibility of potential mates.     

Minimizing leakage from a smelter off-gas system by enhanced control

The off-gas handling system is a vital component of a smelter and it is essential that it operates in accordance with environmental regulations. A key feature of the off-gas management system is maintaining a slightly negative system pressure to prevent gas leakage, such as SO₂, out into the work and external environments. To enhance sustainable development, there is also growing interest in capturing and reusing the significant amount of heat and CO₂ contained within off-gas. The potential incorporation of heat and CO₂ recovery systems places importance on enhancing control to minimize the risk of both gas leakage and disturbance of the smelting process. With these requirements in mind, an easily implementable feedforward control enhancement to existing control schemes is proposed to help provide improved performance.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Optimal control of soybean aphid in the presence of natural enemies and the implied value of their ecosystem services

By suppressing pest populations, natural enemies provide an important ecosystem service that maintains the stability of agricultural ecosystems systems and potentially mitigates producers' pest control costs. Integrating natural control services into decisions about pesticide-based control has the potential to significantly improve the economic efficiency of pesticide use, with socially desirable outcomes. Two gaps have hindered the incorporation of natural enemies into pest management decision rules: (1) insufficient knowledge of pest and predator population dynamics and (2) lack of a decision framework for the economic tradeoffs among pest control options. Using a new intra-seasonal, dynamic bioeconomic optimization model, this study assesses how predation by natural enemies contributes to profit-maximizing pest management strategies. The model is applied to the management of the invasive soybean aphid, the most significant serious insect threat to soybean production in North America. The resulting lower bound estimate of the value of natural pest control ecosystem services was estimated at $84 million for the states of Illinois, Indiana, Iowa, Michigan and Minnesota in 2005.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Characterization of hard- and softwood biochars pyrolyzed at high temperature

A wide range of waste biomass/waste wood feedstocks abundantly available at mine sites provide the opportunity to produce biochars for cost-effective improvement of mine tailings and contaminated land at metal mines. In the present study, soft- and hardwood biochars derived from pine and jarrah woods at high temperature (700 °C) were characterized for their physiochemical properties including chemical components, electrical conductivity, pH, zeta potential, cation-exchange capacity (CEC), alkalinity, BET surface area and surface morphology. Evaluating and comparing these characteristics with available data from the literature have affirmed the strong dictation of precursor type on the physiochemical properties of the biochars. The pine and jarrah wood feedstocks are mainly different in their proportions of cellulose, hemicellulose and lignin, resulting in biochars with heterogeneous physiochemical properties. The hardwood jarrah biochar exhibits much higher microporosity, alkalinity and electrostatic capacity than the softwood pine. Correlation analysis and principal component analysis also show a good correlation between CEC–BET–alkalinity, and alkalinity–ash content. These comprehensive characterization and analysis results on biochars’ properties from feedstocks of hardwood (from forest land clearance at mine construction) and waste pine wood (from mining operations) will provide a good guide for tailoring biochar functionalities for remediating metal mine tailings. The relatively inert high-temperature biochars can be stored for a long term at mine closure after decades of operations.     

Ecological risk of anthropogenic pollutants to reptiles: Evaluating assumptions of sensitivity and exposure

A large data gap for reptile ecotoxicology still persists; therefore, ecological risk assessments of reptiles usually incorporate the use of surrogate species. This necessitates that (1) the surrogate is at least as sensitive as the target taxon and/or (2) exposures to the surrogate are greater than that of the target taxon. We evaluated these assumptions for the use of birds as surrogates for reptiles. Based on a survey of the literature, birds were more sensitive than reptiles in less than 1/4 of the chemicals investigated. Dietary and dermal exposure modeling indicated that exposure to reptiles was relatively high, particularly when the dermal route was considered. We conclude that caution is warranted in the use of avian receptors as surrogates for reptiles in ecological risk assessment and emphasize the need to better understand the magnitude and mechanism of contaminant exposure in reptiles to improve exposure and risk estimation.