A random-effects hurdle model for predicting bycatch of endangered marine species

Understanding and reducing the incidence of accidental bycatch, particularly for vulnerable species such as sharks, is a major challenge for contemporary fisheries management worldwide. Bycatch data, most often collected by at-sea observers during fishing trips, are clustered by trip and/or vessel and typically involve a large number of zero counts and very few positive counts. Though hurdle models are very popular for count data with excess zeros, models for clustered forms have received far less attention. Here we present a novel random-effects hurdle model for bycatch data that makes available accurate estimates of bycatch probabilities as well as other clusterspecific targets. These are essential for informing conservation and management decisions as well as for identifying bycatch hotspots, often considered the first step in attempting to protect endangered marine species. We validate our methodology through simulation and use it to analyze bycatch data on critically endangered hammerhead sharks from the U.S. National Marine Fisheries Service Pelagic Observer Program

Validation of close‐kin mark–recapture (CKMR) methods for estimating population abundance

Under embargo until: 2020-06-181. Knowing how many individuals there are in a population is a fundamental problem in the management and conservation of freshwater and marine fish. We compare abundance estimates (census size, Nc) in seven brook trout Salvelinus fontinalis populations using standard mark–recapture (MR) and the close‐kin mark–recapture (CKMR) method. Our purpose is to validate CKMR as a method for estimating population size. 2. Close‐kin mark–recapture is based on the principle that an individual's genotype can be considered a “recapture” of the genotypes of each of its parents. Assuming offspring and parents are sampled independently, the number of parent–offspring pairs (POPs) genetically identified in these samples can be used to estimate abundance. We genotyped (33 microsatellites) and aged c. 2,400 brook trout individuals collected over 5 consecutive years (2014–2018). 3. We provide an alternative interpretation of CKMR in terms of the Lincoln– Petersen estimator in which the parents are considered as tagging the offspring rather than the offspring “recapturing” the parents. 4. Despite various sources of uncertainty, we find close agreement between standard MR abundance estimates obtained through double‐pass electrofishing and CKMR estimates, which require information on age‐specific fecundity, and population‐ and age‐specific survival rates. Population sizes (N) are estimated to range between 300 and 6,000 adult individuals. Our study constitutes the first in situ validation of CKMR and establishes it as a useful method for estimating population size in aquatic systems where assumptions of random sampling and thorough mixing of individuals can be met.acceptedVersio

A single-particle characterization of a mobile Versatile Aerosol Concentration Enrichment System for exposure studies

BACKGROUND: An Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) was used to investigate the size and chemical composition of fine concentrated ambient particles (CAPs) in the size range 0.2–2.6 μm produced by a Versatile Aerosol Concentration Enrichment System (VACES) contained within the Mobile Ambient Particle Concentrator Exposure Laboratory (MAPCEL). The data were collected during a study of human exposure to CAPs, in Edinburgh (UK), in February-March 2004. The air flow prior to, and post, concentration in the VACES was sampled in turn into the ATOFMS, which provides simultaneous size and positive and negative mass spectral data on individual fine particles. RESULTS: The particle size distribution was unaltered by the concentrator over the size range 0.2–2.6 μm, with an average enrichment factor during this study of ~5 (after dilution of the final air stream). The mass spectra from single particles were objectively grouped into 20 clusters using the multivariate K-means algorithm and then further grouped manually, according to similarity in composition and time sequence, into 8 main clusters. The particle ensemble was dominated by pure and reacted sea salt and other coarse inorganic dusts (as a consequence of the prevailing maritime-source climatology during the study), with relatively minor contributions from carbonaceous and secondary material. Very minor variations in particle composition were noted pre- and post-particle concentration, but overall there was no evidence of any significant change in particle composition. CONCLUSION: These results confirm, via single particle analysis, the preservation of the size distribution and chemical composition of fine ambient PM in the size range 0.2–2.6 μm after passage through the VACES concentration instrumentation

Beneficial cardiovascular effects of reducing exposure to particulate air pollution with a simple facemask

<p>Abstract</p> <p>Background</p> <p>Exposure to air pollution is an important risk factor for cardiovascular morbidity and mortality, and is associated with increased blood pressure, reduced heart rate variability, endothelial dysfunction and myocardial ischaemia. Our objectives were to assess the cardiovascular effects of reducing air pollution exposure by wearing a facemask.</p> <p>Methods</p> <p>In an open-label cross-over randomised controlled trial, 15 healthy volunteers (median age 28 years) walked on a predefined city centre route in Beijing in the presence and absence of a highly efficient facemask. Personal exposure to ambient air pollution and exercise was assessed continuously using portable real-time monitors and global positional system tracking respectively. Cardiovascular effects were assessed by continuous 12-lead electrocardiographic and ambulatory blood pressure monitoring.</p> <p>Results</p> <p>Ambient exposure (PM_2.586 ± 61 <it>vs </it>140 ± 113 μg/m³; particle number 2.4 ± 0.4 <it>vs </it>2.3 ± 0.4 × 10⁴particles/cm³), temperature (29 ± 1 <it>vs </it>28 ± 3°C) and relative humidity (63 ± 10 <it>vs </it>64 ± 19%) were similar (P > 0.05 for all) on both study days. During the 2-hour city walk, systolic blood pressure was lower (114 ± 10 <it>vs </it>121 ± 11 mmHg, P < 0.01) when subjects wore a facemask, although heart rate was similar (91 ± 11 <it>vs </it>88 ± 11/min; P > 0.05). Over the 24-hour period heart rate variability increased (SDNN 65.6 ± 11.5 <it>vs </it>61.2 ± 11.4 ms, P < 0.05; LF-power 919 ± 352 <it>vs </it>816 ± 340 ms², P < 0.05) when subjects wore the facemask.</p> <p>Conclusion</p> <p>Wearing a facemask appears to abrogate the adverse effects of air pollution on blood pressure and heart rate variability. This simple intervention has the potential to protect susceptible individuals and prevent cardiovascular events in cities with high concentrations of ambient air pollution.</p

Modeling the Probability of Overlap Between Marine Fish Distributions and Marine Renewable Energy Infrastructure Using Acoustic Telemetry Data

Understanding the spatiotemporal distributions of migratory marine species at marine renewable energy sites is a crucial step towards assessing the potential impacts of tidal stream turbines and related infrastructure upon these species. However, the dynamic marine conditions that make tidal channels attractive for marine renewable power development also make it difficult to identify and follow species of marine fishes with existing technologies such as hydroacoustics and optical cameras. Acoustic telemetry can resolve some of these problems. Acoustic tags provide unique individual ID codes at an ultrasonic frequency, which are then detected and recorded by acoustic receivers deployed in the area of interest. By matching detection locations of fish species with environmental conditions at proposed sites for tidal energy infrastructure, species distribution models can be developed to predict the probability of species occurrence at sites of current and planned tidal power development. This information can be used to develop statistically robust encounter rate models to aid in quantifying the risk of tidal power development to migratory fish species. We used this approach to develop a predictive model of striped bass (Morone saxatilis) distribution within Minas Passage in the upper Bay of Fundy, Nova Scotia. Model results suggested increased probability of striped bass presence in Minas Passage during late ebb tide conditions and at relatively high water temperatures. We demonstrate the potential utility of species distribution modeling of acoustic tag detections in predicting interactions with renewable energy infrastructure, and show the importance of physical oceanographic variables influencing species distributions in a highly dynamic marine environment

Addressing Challenges in the Application of Animal Movement Ecology to Aquatic Conservation and Management

The dynamic nature of most environments forces many animals to move to meet their fundamental needs. This is especially true in aquatic environments where shifts in spatial ecology (which are a result of movements) are among the first adaptive responses of animals to changes in ecosystems. Changes in the movement and distribution of individuals will in turn alter population dynamics and ecosystem structure. Thus, understanding the drivers and impacts of variation in animal movements over time is critical to conservation and spatial planning. Here, we identify key challenges that impede aquatic animal movement science from informing management and conservation, and propose strategies for overcoming them. Challenges include: (1) Insufficient communication between terrestrial and aquatic movement scientists that could be increased through cross-pollination of analytical tools and development of new tools and outputs; (2) Incomplete coverage in many studies of animal space use (e.g., entire life span not considered); (3) Insufficient data archiving and availability; (4) Barriers to incorporating movement data into decision-making processes; and (5) Limited understanding of the value of movement data for management and conservation. We argue that the field of movement ecology is at present an under-tapped resource for aquatic decision-makers, but is poised to play a critical role in future management approaches and policy development

Envisioning the future of aquatic animal tracking: Technology, science, and application

Electronic tags are significantly improving our understanding of aquatic animal behavior and are emerging as key sources of information for conservation and management practices. Future aquatic integrative biology and ecology studies will increasingly rely on data from electronic tagging. Continued advances in tracking hardware and software are needed to provide the knowledge required by managers and policymakers to address the challenges posed by the world's changing aquatic ecosystems. We foresee multiplatform tracking systems for simultaneously monitoring the position, activity, and physiology of animals and the environment through which they are moving. Improved data collection will be accompanied by greater data accessibility and analytical tools for processing data, enabled by new infrastructure and cyberinfrastructure. To operationalize advances and facilitate integration into policy, there must be parallel developments in the accessibility of education and training, as well as solutions to key governance and legal issues

Inhaled Nanoparticles Accumulate at Sites of Vascular Disease

The development of engineered nanomaterials is growing exponentially, despite concerns over their potential similarities to environmental nanoparticles that are associated with significant cardiorespiratory morbidity and mortality. The mechanisms through which inhalation of nanoparticles could trigger acute cardiovascular events are emerging, but a fundamental unanswered question remains: Do inhaled nanoparticles translocate from the lung in man and directly contribute to the pathogenesis of cardiovascular disease? In complementary clinical and experimental studies, we used gold nanoparticles to evaluate particle translocation, permitting detection by high-resolution inductively coupled mass spectrometry and Raman microscopy. Healthy volunteers were exposed to nanoparticles by acute inhalation, followed by repeated sampling of blood and urine. Gold was detected in the blood and urine within 15 min to 24 h after exposure, and was still present 3 months after exposure. Levels were greater following inhalation of 5 nm (primary diameter) particles compared to 30 nm particles. Studies in mice demonstrated the accumulation in the blood and liver following pulmonary exposure to a broader size range of gold nanoparticles (2-200 nm primary diameter), with translocation markedly greater for particles <10 nm diameter. Gold nanoparticles preferentially accumulated in inflammation-rich vascular lesions of fat-fed apolipoproteinE-deficient mice. Furthermore, following inhalation, gold particles could be detected in surgical specimens of carotid artery disease from patients at risk of stroke. Translocation of inhaled nanoparticles into the systemic circulation and accumulation at sites of vascular inflammation provides a direct mechanism that can explain the link between environmental nanoparticles and cardiovascular disease and has major implications for risk management in the use of engineered nanomaterials

A guide to state-space modeling of ecological time series

State–space models (SSMs) are an important modeling framework for analyzing ecological time series. These hierarchical models are commonly used to model population dynamics, animal movement, and capture–recapture data, and are now increasingly being used to model other ecological processes. SSMs are popular because they are flexible and they model the natural variation in ecological processes separately from observation error. Their flexibility allows ecologists to model continuous, count, binary, and categorical data with linear or nonlinear processes that evolve in discrete or continuous time. Modeling the two sources of stochasticity separately allows researchers to differentiate between biological variation and imprecision in the sampling methodology, and generally provides better estimates of the ecological quantities of interest than if only one source of stochasticity is directly modeled. Since the introduction of SSMs, a broad range of fitting procedures have been proposed. However, the variety and complexity of these procedures can limit the ability of ecologists to formulate and fit their own SSMs. We provide the knowledge for ecologists to create SSMs that are robust to common, and often hidden, estimation problems, and the model selection and validation tools that can help them assess how well their models fit their data. We present a review of SSMs that will provide a strong foundation to ecologists interested in learning about SSMs, introduce new tools to veteran SSM users, and highlight promising research directions for statisticians interested in ecological applications. The review is accompanied by an in-depth tutorial that demonstrates how SSMs can be fitted and validated in R. Together, the review and tutorial present an introduction to SSMs that will help ecologists to formulate, fit, and validate their models