Toward reassessing data‐deficient species

One in 6 species (13,465 species) on the International Union for Conservation of Nature (IUCN) Red List is classified as data deficient due to lack of information on their taxonomy, population status, or impact of threats. Despite the chance that many are at high risk of extinction, data‐deficient species are typically excluded from global and local conservation priorities, as well as funding schemes. The number of data‐deficient species will greatly increase as the IUCN Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of data‐deficient assessments. To develop this, we reviewed 2879 data‐deficient assessments in 6 animal groups and identified 8 main justifications for assigning data‐deficient status (type series, few records, old records, uncertain provenance, uncertain population status or distribution, uncertain threats, taxonomic uncertainty, and new species). Assigning a consistent set of justification tags (i.e., consistent assignment to assessment justifications) to species classified as data deficient is a simple way to achieve more strategic assessments. Such tags would clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for reassessment. With renewed efforts, it could be straightforward to prevent thousands of data‐deficient species slipping unnoticed toward extinction.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Source attribution and quantification of benzene event emissions in a Houston ship channel community based on real-time mobile monitoring of ambient air

A mobile laboratory equipped with a proton transfer reaction mass spectrometer (PTR-MS) operated in Galena Park, Texas, near the Houston Ship Channel during the Benzene and other Toxics Exposure Study (BEE-TEX). The mobile laboratory measured transient peaks of benzene of up to 37 ppb_v in the afternoon and evening of February 19, 2015. Plume reconstruction and source attribution were performed using the four-dimensional (4D) variational data assimilation technique and a three-dimensional (3D) micro-scale forward and adjoint air quality model based on mobile PTR-MS data and nearby stationary wind measurements at the Galena Park Continuous Air Monitoring Station (CAMS). The results of inverse modeling indicate that significant pipeline emissions of benzene may at least partly explain the ambient concentration peaks observed in Galena Park during BEE-TEX. Total pipeline emissions of benzene inferred within the 16-km² model domain exceeded point source emissions by roughly a factor of 2 during the observational episode. Besides pipeline leaks, the model also inferred significant benzene emissions from marine, railcar, and tank truck loading/unloading facilities, consistent with the presence of a tanker and barges in the Kinder Morgan port terminal during the afternoon and evening of February 19. Total domain emissions of benzene exceeded corresponding 2011 National Emissions Inventory (NEI) estimates by a factor of 2–6.

Implications:?Port operations involving petrochemicals may significantly increase emissions of air toxics from the transfer and storage of materials. Pipeline leaks, in particular, can lead to sporadic emissions greater than in emission inventories, resulting in higher ambient concentrations than are sampled by the existing monitoring network. The use of updated methods for ambient monitoring and source attribution in real time should be encouraged as an alternative to expanding the conventional monitoring network.     

Recycled sand in lime-based mortars

The increasing awareness of the society about safe guarding heritage buildings and at the same time protecting the environment promotes strategies of combining principles of restoration with environmentally friendly materials and techniques. Along these lines, an experimental program was carried out in order to investigate the possibility of producing repair, lime-based mortars used in historic buildings incorporating secondary materials. The alternative material tested was recycled fine aggregates originating from mixed construction and demolition waste. Extensive tests on the raw materials have been performed and mortar mixtures were produced using different binding systems with natural, standard and recycled sand in order to compare their mechanical, physical and microstructure properties. The study reveals the improved behavior of lime mortars, even at early ages, due to the reaction of lime with the Al and Si constituents of the fine recycled sand. The role of the recycled sand was more beneficial in lime mortars rather than the lime–pozzolan or lime–pozzolan–cement mortars as a decrease in their performance was recorded in the latter cases due to the mortars’ structure.     

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     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

Leaching behaviour of different scrap materials at recovery and recycling companies: Full-, pilot- and lab-scale investigation

Scrap material recovery and recycling companies are confronted with waste water that has a highly fluctuating flow rate and composition. Common pollutants, such as COD, nutrients and suspended solids, potentially toxic metals, polyaromatic hydrocarbons and poly chlorinated biphenyls can exceed the discharge limits. An analysis of the leaching behaviour of different scrap materials and scrap yard sweepings was performed at full-scale, pilot-scale and lab-scale in order to find possible preventive solutions for this waste water problem. The results of these leaching tests (with concentrations that frequently exceeded the Flemish discharge limits) showed the importance of regular sweeping campaigns at the company, leak proof or covered storage of specific scrap materials and oil/water separation on particular leachates. The particulate versus dissolved fraction was also studied for the pollutants. For example, up to 98% of the polyaromatic hydrocarbons, poly chlorinated biphenyls and some metals were in the particulate form. This confirms the (potential) applicability of sedimentation and filtration techniques for the treatment of the majority of the leachates, and as such the rainwater run-off as a whole.