Modeling the formation of periodic hypoxia in partially mixed estuaries and its response to oligotrophication and climate change

The development of hypoxia represents one of the most common and ecologically detrimental effects of anthropogenic nutrient enrichment in coastal marine ecosystems. Due to the physiological importance of oxygen as a key component of metabolic processes, the development and persistence of hypoxia can reduce the distribution of important species, modify food webs, decrease diversity and richness, and sub-lethally affect growth and reproductive rates. While many recent studies have focused on the global increase in hypoxia and highlighted the need for nutrient reduction strategies, some key processes associated with hypoxia remain understudied. of particular importance is the resolution of the major carbon sources fueling hypoxia in tributary estuaries, which receive inputs from the upland watershed, internal primary production, and advection from the main estuary, which may also be a source of hypoxic water. Development of well-constrained, intermediate complexity ecosystem models is also needed to provide realistic predictions of the response of hypoxia to nutrient reduction strategies, and to understand the interactive effects of these load reductions with ongoing climate change. The recent implementation of high spatial and temporal resolution water quality sampling instruments has confirmed the importance of the spring-neap tidal cycle and its effect on the formation and disruption of stratification and hypoxia in the York River estuary (YRE). However, these results have indicated that the advection of high-salinity hypoxic water into the lower YRE from the Chesapeake Bay (CB) may be as important as internal oxygen consumption. Additionally, previous studies have suggested that phytoplankton production in the YRE and similar tributary estuaries may be insufficient to explain the magnitude of hypoxia observed. This study synthesized in-situ measurements and high resolution water quality monitoring with an intermediate complexity model to examine the significance of these factors and how they interact to cause hypoxia within the YRE. Simulations were used to determine the magnitude of nutrient and/or organic matter (OM) reductions required to reduce the extent and severity of hypoxia in the presence of increasing temperatures resulting from climate change. A comparison of in-situ and computed oxygen concentrations for the YRE indicated that internal respiration was sufficient to drive hypoxia under stratified conditions, without the need for advection of hypoxic water from the CB. Phytoplankton production was the major source of organic carbon to the YRE and 1.5 times greater than advective inputs from CB, which were roughly balanced by exports. Watershed sources and microphytobenthos contributed comparatively little carbon to the whole system. Model simulations indicated that lower portions of the YRE tributaries are strongly influenced by watershed OM loading during summer, while the low mesohaline region is influenced by internal primary production and OM from the tributaries. The high meso- and polyhaline regions responded primarily to advected dissolved organic carbon from CB. Results indicate that different regions of the YRE require separate management strategies to control hypoxia, with the key issue in the lower estuary being the far field source of labile OM from outside the system. The model predicted increasing primary production under warmer conditions in winter and spring throughout most of the YRE, but decreasing production in summer and fall in the lower estuary. These changes together with increasing respiration resulted in increased autotrophy in the upper YRE, while NEM was predicted to decrease throughout the rest of the estuary. Warmer temperatures increased both the temporal and spatial extent of hypoxia in the model, suggesting the need for additional nutrient and OM load reductions in order to achieve the same level of improvement predicted without warming

Modeling estuarine response to load reductions in a warmer climate: York River Estuary, Virginia, USA

The impact of climate warming on shallow tributary estuaries will be influenced by the complex cycling of nutrients and organic matter, diversity of primary producers, and enhanced benthic-pelagic coupling typical of these systems, along with advection of nutrients, organic matter, and hypoxic water from adjacent systems. This study utilized a parsimonious, reduced-complexity model that combines mechanistic equations with robust, data-driven, empirical formulations to predict how phytoplankton net primary production (NPP), net ecosystem metabolism (NEM), and hypoxia will change under a range of warmer conditions in the York River Estuary, VA, USA, a sub-estuary of Chesapeake Bay. Modeled NPP peaked earlier and responded positively to warming in the winter and spring throughout most of the system due to increased rates of nutrient remineralization; NPP remained elevated during summer and fall in the upper estuary under warming but decreased in the lower estuary. These changes caused the upper estuary to become more autotrophic, while NEM decreased in the lower estuary due to greater stimulation of respiration relative to NPP. Warming increased the predicted temporal and spatial extent of hypoxia, with the upper estuary experiencing a relatively constant increase in the number of hypoxic days with increasing temperature. Hypoxia in the lower estuary increased more rapidly with temperature. Offsetting this increase in hypoxia with climate warming will require additional nutrient and organic matter load reductions from the surrounding watershed and Chesapeake Bay in order to achieve the same level of improvement predicted in the absence of a warming climate

Building Machines That Learn and Think Like People

Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it. Specifically, we argue that these machines should (a) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (b) ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned; and (c) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes towards these goals that can combine the strengths of recent neural network advances with more structured cognitive models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary proposals (until Nov. 22, 2016). https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar

Alternative mechanism for bacteriophage adsorption to the motile bacterium Caulobacter crescentus

2D and 3D cryo-electron microscopy, together with adsorption kinetics assays of ϕCb13 and ϕCbK phage-infected Caulobacter crescentus, provides insight into the mechanisms of infection. ϕCb13 and ϕCbK actively interact with the flagellum and subsequently attach to receptors on the cell pole. We present evidence that the first interaction of the phage with the bacterial flagellum takes place through a filament on the phage head. This contact with the flagellum facilitates concentration of phage particles around the receptor (i.e., the pilus portals) on the bacterial cell surface, thereby increasing the likelihood of infection. Phage head filaments have not been well characterized and their function is described here. Phage head filaments may systematically underlie the initial interactions of phages with their hosts in other systems and possibly represent a widespread mechanism of efficient phage propagation

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Estuaries and Coasts 39 (2016): 311-332, doi:10.1007/s12237-015-0011-y.Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.NKG, ALA, and RPS acknowledge support from the USGS Coastal and Marine Geology Program. DKR gratefully acknowledges support from NSF (OCE-1314642) and NIEHS (1P50-ES021923-01). MJB and JMPV gratefully acknowledge support from NOAA NOS NCCOS (NA05NOS4781201 and NA11NOS4780043). MJB and SJL gratefully acknowledge support from the Strategic Environmental Research and Development Program—Defense Coastal/Estuarine Research Program (RC-1413 and RC-2245)

Poplar GTL1 Is a Ca2+/Calmodulin-Binding Transcription Factor that Functions in Plant Water Use Efficiency and Drought Tolerance

Diminishing global fresh water availability has focused research to elucidate mechanisms of water use in poplar, an economically important species. A GT-2 family trihelix transcription factor that is a determinant of water use efficiency (WUE), PtaGTL1 (GT-2 like 1), was identified in Populus tremula × P. alba (clone 717-IB4). Like other GT-2 family members, PtaGTL1 contains both N- and C-terminal trihelix DNA binding domains. PtaGTL1 expression, driven by the Arabidopsis thaliana AtGTL1 promoter, suppressed the higher WUE and drought tolerance phenotypes of an Arabidopsis GTL1 loss-of-function mutation (gtl1-4). Genetic suppression of gtl1-4 was associated with increased stomatal density due to repression of Arabidopsis STOMATAL DENSITY AND DISTRIBUTION1 (AtSDD1), a negative regulator of stomatal development. Electrophoretic mobility shift assays (EMSA) indicated that a PtaGTL1 C-terminal DNA trihelix binding fragment (PtaGTL1-C) interacted with an AtSDD1 promoter fragment containing the GT3 box (GGTAAA), and this GT3 box was necessary for binding. PtaGTL1-C also interacted with a PtaSDD1 promoter fragment via the GT2 box (GGTAAT). PtaSDD1 encodes a protein with 60% primary sequence identity with AtSDD1. In vitro molecular interaction assays were used to determine that Ca2+-loaded calmodulin (CaM) binds to PtaGTL1-C, which was predicted to have a CaM-interaction domain in the first helix of the C-terminal trihelix DNA binding domain. These results indicate that, in Arabidopsis and poplar, GTL1 and SDD1 are fundamental components of stomatal lineage. In addition, PtaGTL1 is a Ca2+-CaM binding protein, which infers a mechanism by which environmental stimuli can induce Ca2+ signatures that would modulate stomatal development and regulate plant water use

Identification of CD4+ T Cell Epitopes in C. burnetii Antigens Targeted by Antibody Responses

Coxiella burnetii is an obligate intracellular Gram-negative bacterium that causes acute Q fever and chronic infections in humans. A killed, whole cell vaccine is efficacious, but vaccination can result in severe local or systemic adverse reactions. Although T cell responses are considered pivotal for vaccine derived protective immunity, the epitope targets of CD4+ T cell responses in C. burnetii vaccination have not been elucidated. Since mapping CD4+ epitopes in a genome with over 2,000 ORFs is resource intensive, we focused on 7 antigens that were known to be targeted by antibody responses. 117 candidate peptides were selected from these antigens based on bioinformatics predictions of binding to the murine MHC class II molecule H-2 IAb. We screened these peptides for recognition by IFN-γ producing CD4+ T cell in phase I C. burnetii whole cell vaccine (PI-WCV) vaccinated C57BL/6 mice and identified 8 distinct epitopes from four different proteins. The identified epitope targets account for 8% of the total vaccination induced IFN-γ producing CD4+ T cells. Given that less than 0.4% of the antigens contained in C. burnetii were screened, this suggests that prioritizing antigens targeted by antibody responses is an efficient strategy to identify at least a subset of CD4+ targets in large pathogens. Finally, we examined the nature of linkage between CD4+ T cell and antibody responses in PI-WCV vaccinated mice. We found a surprisingly non-uniform pattern in the help provided by epitope specific CD4+ T cells for antibody production, which can be specific for the epitope source antigen as well as non-specific. This suggests that a complete map of CD4+ response targets in PI-WCV vaccinated mice will likely include antigens against which no antibody responses are made

Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion

The personality traits of neuroticism and extraversion are predictive of a number of social and behavioural outcomes and psychiatric disorders. Twin and family studies have reported moderate heritability estimates for both traits. Few associations have been reported between genetic variants and neuroticism/extraversion, but hardly any have been replicated. Moreover, the ones that have been replicated explain only a small proportion of the heritability (<∼2%). Using genome-wide single-nucleotide polymorphism (SNP) data from ∼12 000 unrelated individuals we estimated the proportion of phenotypic variance explained by variants in linkage disequilibrium with common SNPs as 0.06 (s.e.=0.03) for neuroticism and 0.12 (s.e.=0.03) for extraversion. In an additional series of analyses in a family-based sample, we show that while for both traits ∼45% of the phenotypic variance can be explained by pedigree data (that is, expected genetic similarity) one third of this can be explained by SNP data (that is, realized genetic similarity). A part of the so-called ‘missing heritability' has now been accounted for, but some of the reported heritability is still unexplained. Possible explanations for the remaining missing heritability are that: (i) rare variants that are not captured by common SNPs on current genotype platforms make a major contribution; and/ or (ii) the estimates of narrow sense heritability from twin and family studies are biased upwards, for example, by not properly accounting for nonadditive genetic factors and/or (common) environmental factors