First REP-LECOTOX Workshop—ecotoxicogenomics: the challenge of integrating genomics/proteomics/metabolomics into aquatic and terrestrial ecotoxicology

Environmental Science and Pollution Research -     

Testing for between individual correlations of personality and physiological traits in a wild bird

Recently, integration of personality traits into a ‘pace-of-life syndrome’ (POLS) context has been advocated. To be able to understand how an individual’s behavioural, physiological and life history traits may coevolve, we need to jointly quantify these traits in order to study their covariance. Few studies have established links between personality and immunity properties of an individual. We here examined covariation of a measure of skeletal size (tarsus length), three behavioural traits (activity, handling aggression and breath rate) and two immunological traits (IgG level and haematocrit), in 592 wild caught blue tits. Many individuals (201) were tested more than once, allowing quantification of individual consistency of all traits and partition of the covariances between the traits, using a multivariate mixed model, into between individual and residual covariances. We find individual consistency of all behavioural traits, indicating that these capture aspects of blue tit adult personality and also the physiological measures are repeatable. Contrary to the POLS expectation, we find no overall significant individual level correlation structure between these traits and a factor analytical approach confirmed that between individual correlations across traits were not due to a common (POLS) factor or driven by size (tarsus length). Based on a published power study, we conclude that there is no common syndrome of individual level covariance between personality and physiological traits in wild blue tits or that the effect sizes, such a syndrome generates, are too low (r?<?0.3) to detect. Future field-based work should be designed to explore low effect sizes and strive to measure specific traits whose involvement is implicated to have large effect sizes as based on, e.g. laboratory findings.     

Predictive Model of Avian Electrocution Risk on Overhead Power Lines

Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red‐tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution‐risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high‐risk poles for retrofitting. Modelo Predictivo del Riesgo de Electrocución de Aves en Líneas Eléctricas Elevadas