Integrated multi-trophic aquaculture mitigates the effects of ocean acidification: Seaweeds raise system pH and improve growth of juvenile abalone

Integrated multi-trophic aquaculture (IMTA) has the potential to enhance growth, reduce nutrient loads, and mitigate environmental conditions compared to traditional single-species culture techniques. The goal of this project was to develop a land-based system for the integrated culture of seaweeds and shellfish, to test the efficacy of integrated versus non-integrated designs, and to assess the potential for IMTA to mitigate the effects of climate change from ocean acidification on shellfish growth and physiology. We utilized the red abalone (Haliotis rufescens) and the red seaweed dulse (Devaleraea mollis) as our study species and designed integrated tanks at three different recirculation rates (0%, 30%, and 65% recirculation per hour) to test how an integrated design would affect growth rates of the abalone and seaweeds, modify nutrient levels, and change water chemistry. We specifically hypothesized that IMTA designs would raise seawater pH to benefit calcifying species. Our results indicated that juvenile abalone grew significantly faster in weight (22% increase) and shell area (11% increase) in 6 months in tanks with the highest recirculation rates (65%). The 65% recirculation treatment also exhibited a significant increase in mean seawater pH (0.2 pH units higher) due to the biological activity of the seaweed in the connected tanks. We found a significant positive relationship between the mean pH of seawater in the tanks and juvenile abalone growth rates across all treatments. There were no significant differences in the growth of dulse among treatments, but dulse growth did vary seasonally. Seawater phosphate and nitrate concentrations were depleted in the highest recirculation rate treatment, but ammonium concentrations were elevated, likely due to the abalone effluent. Overall, our results indicate that there are benefits to IMTA culture of seaweeds and abalone in terms of improving growth in land-based systems, which will reduce the time to market and buffer commercial abalone operations against the effects of ocean acidification during vulnerable early life stages

Brain-age in midlife is associated with accelerated biological aging and cognitive decline in a longitudinal birth-cohort

An individual’s brainAGE is the difference between chronological age and age predicted from machine-learning models of brain-imaging data. BrainAGE has been proposed as a biomarker of age-related deterioration of the brain. Having an older brainAGE has been linked to Alzheimer’s, dementia and mortality. However, these findings are largely based on cross-sectional associations which can confuse age differences with cohort differences. To illuminate the validity of brainAGE as a biomarker of accelerated brain aging, a study is needed of a large cohort all born in the same year who nevertheless vary on brainAGE. In the Dunedin Study, a population-representative 1972–73 birth cohort, we measured brainAGE at age 45 years, as well as the pace of biological aging and cognitive decline in longitudinal data from childhood to midlife (N=869). In this cohort, all chronological age 45 years, brainAGE was measured reliably (ICC=.81) and ranged from 24 to 72 years. Those with older midlife brainAGEs tended to have poorer cognitive function in both adulthood and childhood, as well as impaired brain health at age 3. Furthermore, those with older brainAGEs had an accelerated pace of biological aging, older facial appearance and early signs of cognitive decline from childhood to midlife. These findings help to validate brainAGE as a potential surrogate biomarker for midlife intervention studies that seek to measure dementia-prevention efforts in midlife. However, the findings also caution against the assumption that brainAGE scores represent only age-related deterioration of the brain as they may also index central nervous system variation present since childhood

Integrating Dynamic Subsurface Habitat Metrics Into Species Distribution Models

Species distribution models (SDMs) have become key tools for describing and predicting species habitats. In the marine domain, environmental data used in modeling species distributions are often remotely sensed, and as such have limited capacity for interpreting the vertical structure of the water column, or are sampled in situ, offering minimal spatial and temporal coverage. Advances in ocean models have improved our capacity to explore subsurface ocean features, yet there has been limited integration of such features in SDMs. Using output from a data-assimilative configuration of the Regional Ocean Modeling System, we examine the effect of including dynamic subsurface variables in SDMs to describe the habitats of four pelagic predators in the California Current System (swordfish Xiphias gladius, blue sharks Prionace glauca, common thresher sharks Alopias vulpinus, and shortfin mako sharks lsurus oxyrinchus). Species data were obtained from the California Drift Gillnet observer program (1997-2017). We used boosted regression trees to explore the incremental improvement enabled by dynamic subsurface variables that quantify the structure and stability of the water column: isothermal layer depth and bulk buoyancy frequency. The inclusion of these dynamic subsurface variables significantly improved model explanatory power for most species. Model predictive performance also significantly improved, but only for species that had strong affiliations with dynamic variables (swordfish and shortfin mako sharks) rather than static variables (blue sharks and common thresher sharks). Geospatial predictions for all species showed the integration of isothermal layer depth and bulk buoyancy frequency contributed value at the mesoscale level (\u3c 100 km) and varied spatially throughout the study domain. These results highlight the utility of including dynamic subsurface variables in SDM development and support the continuing ecological use of biophysical output from ocean circulation models

Characterizing Habitat Suitability for a Central‐Place Forager in a Dynamic Marine Environment

Characterizing habitat suitability for a marine predator requires an understanding of the environmental heterogeneity and variability over the range in which a population moves during a particular life cycle. Female California sea lions (Zalophus californianus) are central‐place foragers and are particularly constrained while provisioning their young. During this time, habitat selection is a function of prey availability and proximity to the rookery, which has important implications for reproductive and population success. We explore how lactating females may select habitat and respond to environmental variability over broad spatial and temporal scales within the California Current System. We combine near‐real‐time remotely sensed satellite oceanography, animal tracking data (n = 72) from November to February over multiple years (2003–2009) and Generalized Additive Mixed Models (GAMMs) to determine the probability of sea lion occurrence based on environmental covariates. Results indicate that sea lion presence is associated with cool (\u3c14°C), productive waters, shallow depths, increased eddy activity, and positive sea‐level anomalies. Predictive habitat maps generated from these biophysical associations suggest winter foraging areas are spatially consistent in the nearshore and offshore environments, except during the 2004–2005 winter, which coincided with an El Niño event. Here, we show how a species distribution model can provide broadscale information on the distribution of female California sea lions during an important life history stage and its implications for population dynamics and spatial management

Manacled to Identity: Cosmopolitanism, Class, and ‘The Culture Concept’ in Stephen Crane

This article begins with a close reading of Stephen Crane’s short story ‘Manacled’ from 1900, which situates this rarely considered short work within the context of contemporary debates about realism. I then proceed to argue that many of the debates raised by the tale have an afterlife in our own era of American literary studies, which has frequently focused on questions of ‘identity’ and ‘culture’ in its reading of realism and naturalism to the exclusion of the importance of cosmopolitan discourses of diffusion and exchange across national borders. I then offer a brief reading of Crane’s novel George’s Mother, which follows Walter Benn Michaels in suggesting that the recent critical attention paid to particularities of cultural difference in American studies have come to conflate ideas of class and social position with ideas of culture in ways that have ultimately obscured the presence of genuine historical inequalities in US society. In order to challenge this critical commonplace, I situate Crane’s work within a history of transatlantic cosmopolitanism associated with the ideas of Franz Boas and Matthew Arnold to demonstrate the ways in which Crane’s narratives sought out an experience of the universal within their treatments of the particular

Performance Evaluation of Cetacean Species Distribution Models Developed Using Generalized Additive Models and Boosted Regression Trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest

Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest

Properties of Blood, Porphyrins, and Exposure to Legacy and Emerging Persistent Organic Pollutants in Surf Scoters (Melanitta perspicillata) Overwintering on the South Coast of British Columbia, Canada

The surf scoter (Melanitta perspicillata) is a little-studied species of North American sea duck. Estimates suggest it has experienced a precipitous decline in breeding numbers over the latter half of the past century. To investigate the potential role of contaminant uptake and toxicity in the population decline, this study undertook to measure blood chemistry, porphyrin concentrations, EROD, and organic contaminants in mature surf scoters wintering in the Strait of Georgia, BC, Canada. Hepatic organochlorine pesticide, polychlorinated dibenzo-p-dioxin, polychlorinated dibenzofuran, polychlorinated biphenyl (PCB), polybrominated diphenyl ether, and nonylphenol concentrations were relatively low; for example, ΣTEQs (toxic equivalents) for PCBs, dioxins, and furans combined ranged from 4.7 ng/kg wet weight in reference-site (Baynes Sound) birds to 11.4 ng/kg wet weight in birds from Vancouver Harbour. Nonetheless, elevated EROD activity indicated that birds in Howe Sound were responding to an Ah-receptor-mediated stressor, which was also affecting hematocrit values and possibly vitamin A status. In addition, a low proportion of lymphocytes in individuals across locations in early spring samples was associated with poor body condition. The apparent loss of fitness just prior to the onset of northerly migrations to breeding grounds is of particular concern. Compromised health of mature birds at this point in the season might impact negatively on the productivity and survival of some individuals, particularly those overwintering in Howe Sound

Technical knowledge and water resources management: A comparative study of river basin councils, Brazil

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94603/1/wrcr12258.pd