Fisheries Bycatch Risk to Marine Megafauna Is Intensified in Lagrangian Coherent Structures

Incidental catch of nontarget species (bycatch) is a major barrier to ecological and economic sustainability in marine capture fisheries. Key to mitigating bycatch is an understanding of the habitat requirements of target and nontarget species and the influence of heterogeneity and variability in the dynamic marine environment. While patterns of overlap among marine capture fisheries and habitats of a taxonomically diverse range of marine vertebrates have been reported, a mechanistic understanding of the real-time physical drivers of bycatch events is lacking. Moving from describing patterns toward understanding processes, we apply a Lagrangian analysis to a high-resolution ocean model output to elucidate the fundamental mechanisms that drive fisheries interactions. We find that the likelihood of marine megafauna bycatch is intensified in attracting Lagrangian coherent structures associated with submesoscale and mesoscale filaments, fronts, and eddies. These results highlight how the real-time tracking of dynamic structures in the oceans can support fisheries sustainability and advance ecosystem-based managemen

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

Fit to Predict? Ecoinformatics for Predicting the Catchability of a Pelagic Fish in Near Real-Time

The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing ecoinformatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 years (1990-2014) of NOAA fisheries\u27 observer data from the California drift gillnet fishery, we model relative probability of occurrence (presence-absence) and catchability (total catch) of broadbill swordfish Xiphias gladius in the California Current System (CCS). Using freely-available environmental datasets and open source software, we explore the physical drivers of regional swordfish distribution. Comparing models built upon remotely-sensed datasets with those built upon a data-assimilative configuration of the Regional Ocean Modelling System (ROMS), we explore trade-offs in model construction and address how physical data can affect predictive performance and operational capacity. Swordfish catchability was found to be highest in deeper waters (\u3e1500m) with surface temperatures in the 14-20 degrees C range, isothermal layer depth (ILD) of 20-40m, positive sea surface height anomalies and during the new moon

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

Beyond representing orthology relations by trees

Reconstructing the evolutionary past of a family of genes is an important aspect of many genomic studies. To help with this, simple relations on a set of sequences called orthology relations may be employed. In addition to being interesting from a practical point of view they are also attractive from a theoretical perspective in that e.\,g.\,a characterization is known for when such a relation is representable by a certain type of phylogenetic tree. For an orthology relation inferred from real biological data it is however generally too much to hope for that it satisfies that characterization. Rather than trying to correct the data in some way or another which has its own drawbacks, as an alternative, we propose to represent an orthology relation $\delta$ in terms of a structure more general than a phylogenetic tree called a phylogenetic network. To compute such a network in the form of a level-1 representation for $\delta$, we formalize an orthology relation in terms of the novel concept of a symbolic 3- dissimilarity which is motivated by the biological concept of a ``cluster of orthologous groups'', or COG for short. For such maps which assign symbols rather that real values to elements, we introduce the novel {\sc Network-Popping} algorithm which has several attractive properties. In addition, we characterize an orthology relation $\delta$ on some set $X$ that has a level-1 representation in terms of eight natural properties for $\delta$ as well as in terms of level-1 representations of orthology relations on certain subsets of $X$

Pattern and quality of care of cancer pain management. Results from the Cancer Pain Outcome Research Study Group

Most patients with advanced or metastatic cancer experience pain and despite several guidelines, undertreatment is well documented. A multicenter, open-label, prospective, non-randomised study was launched in Italy in 2006 to evaluate the epidemiology, patterns and quality of pain care of cancer patients. To assess the adequacy of analgesic care, we used a standardised measure, the pain management index (PMI), that compares the most potent analgesic prescribed for a patient with the reported level of the worst pain of that patient together with a selected list of clinical indicators. A total of 110 centres recruited 1801 valid cases. 61% of cases were received a WHO-level III opioid; 25.3% were classified as potentially undertreated, with wide variation (9.8–55.3%) according to the variables describing patients, centres and pattern of care. After adjustment with a multivariable logistic regression model, type of recruiting centre, receiving adjuvant therapy or not and type of patient recruited (new or already on follow-up) had a significant association with undertreatment. Non-compliance with the predefined set of clinical indicators was generally high, ranging from 41 to 76%. Despite intrinsic limitations of the PMI that may be considered as an indicator of the poor quality of cancer pain care, results suggest that the recourse to WHO third-level drugs still seems delayed in a substantial percentage of patients. This delay is probably related to several factors affecting practice in participating centres and suggests that the quality of cancer pain management in Italy deserves specific attention and interventions aimed at improving patients' outcomes

Vulnerability to climate change of managed stocks in the California Current large marine ecosystem

Introduction: Understanding how abundance, productivity and distribution of individual species may respond to climate change is a critical first step towards anticipating alterations in marine ecosystem structure and function, as well as developing strategies to adapt to the full range of potential changes. Methods: This study applies the NOAA (National Oceanic and Atmospheric Administration) Fisheries Climate Vulnerability Assessment method to 64 federally-managed species in the California Current Large Marine Ecosystem to assess their vulnerability to climate change, where vulnerability is a function of a species’ exposure to environmental change and its biological sensitivity to a set of environmental conditions, which includes components of its resiliency and adaptive capacity to respond to these new conditions. Results: Overall, two-thirds of the species were judged to have Moderate or greater vulnerability to climate change, and only one species was anticipated to have a positive response. Species classified as Highly or Very Highly vulnerable share one or more characteristics including: 1) having complex life histories that utilize a wide range of freshwater and marine habitats; 2) having habitat specialization, particularly for areas that are likely to experience increased hypoxia; 3) having long lifespans and low population growth rates; and/or 4) being of high commercial value combined with impacts from non-climate stressors such as anthropogenic habitat degradation. Species with Low or Moderate vulnerability are either habitat generalists, occupy deep-water habitats or are highly mobile and likely to shift their ranges. Discussion: As climate-related changes intensify, this work provides key information for both scientists and managers as they address the long-term sustainability of fisheries in the region. This information can inform near-term advice for prioritizing species-level data collection and research on climate impacts, help managers to determine when and where a precautionary approach might be warranted, in harvest or other management decisions, and help identify habitats or life history stages that might be especially effective to protect or restore

Conceptual robustness in simultaneous engineering: An extension of Taguchi's parameter design

Simultaneous engineering processes involve multifunctional teams; team members simultaneously make decisions about many parts of the product-production system and aspects of the product life cycle. This paper argues that such simultaneous distributed decisions should be based on communications about sets of possibilities rather than single solutions. By extending Taguchi's parameter design concepts, we develop a robust and distributed decision-making procedure based on such communications. The procedure shows how a member of a design team can make appropriate decisions based on incomplete information from the other members of the team. More specifically, it (1) treats variations among the designs considered by other members of the design team as conceptual noise; (2) shows how to incorporate such noises into decisions that are robust against these variations; (3) describes a method for using the same data to provide preference information back to the other team members; and (4) provides a procedure for determining whether to release the conceptually robust design or to wait for further decisions by others. The method is demonstrated by part of a distributed design process for a rotary CNC milling machine. While Taguchi's approach is used as a starting point because it is widely known, these results can be generalized to use other robust decision techniques.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45879/1/163_2005_Article_BF01608400.pd

Mammalian Glutaminase Gls2 Gene Encodes Two Functional Alternative Transcripts by a Surrogate Promoter Usage Mechanism

Glutaminase is expressed in most mammalian tissues and cancer cells, but the regulation of its expression is poorly understood. An essential step to accomplish this goal is the characterization of its species- and cell-specific isoenzyme pattern of expression. Our aim was to identify and characterize transcript variants of the mammalian glutaminase Gls2 gene.We demonstrate for the first time simultaneous expression of two transcript variants from the Gls2 gene in human, rat and mouse. A combination of RT-PCR, primer-extension analysis, bioinformatics, real-time PCR, in vitro transcription and translation and immunoblot analysis was applied to investigate GLS2 transcripts in mammalian tissues. Short (LGA) and long (GAB) transcript forms were isolated in brain and liver tissue of human, rat and mouse. The short LGA transcript arises by a combination of two mechanisms of transcriptional modulation: alternative transcription initiation and alternative promoter. The LGA variant contains both the transcription start site (TSS) and the alternative promoter in the first intron of the Gls2 gene. The full human LGA transcript has two in-frame ATGs in the first exon, which are missing in orthologous rat and mouse transcripts. In vitro transcription and translation of human LGA yielded two polypeptides of the predicted size, but only the canonical full-length protein displayed catalytic activity. Relative abundance of GAB and LGA transcripts showed marked variations depending on species and tissues analyzed.This is the first report demonstrating expression of alternative transcripts of the mammalian Gls2 gene. Transcriptional mechanisms giving rise to GLS2 variants and isolation of novel GLS2 transcripts in human, rat and mouse are presented. Results were also confirmed at the protein level, where catalytic activity was demonstrated for the human LGA protein. Relative abundance of GAB and LGA transcripts was species- and tissue-specific providing evidence of a differential regulation of GLS2 transcripts in mammals