Random projection ensemble classification with high-dimensional time series.

Multivariate time-series (MTS) data are prevalent in diverse domains and often high dimensional. We propose new random projection ensemble classifiers with high-dimensional MTS. The method first applies dimension reduction in the time domain via randomly projecting the time-series variables into some low-dimensional space, followed by measuring the disparity via some novel base classifier between the data and the candidate generating processes in the projected space. Our contributions are twofold: (i) We derive optimal weighted majority voting schemes for pooling information from the base classifiers for multiclass classification and (ii) we introduce new base frequency-domain classifiers based on Whittle likelihood (WL), Kullback-Leibler (KL) divergence, eigen-distance (ED), and Chernoff (CH) divergence. Both simulations for binary and multiclass problems, and an Electroencephalogram (EEG) application demonstrate the efficacy of the proposed methods in constructing accurate classifiers with high-dimensional MTS.

Climate variation drives dengue dynamics.

Dengue, a viral infection transmitted between people by mosquitoes, is one of the most rapidly spreading diseases in the world. Here, we report the analyses covering 11 y (2005-2015) from the city of Guangzhou in southern China. Using the first 8 y of data to develop an ecologically based model for the dengue system, we reliably predict the following 3 y of dengue dynamics-years with exceptionally extensive dengue outbreaks. We demonstrate that climate conditions, through the effects of rainfall and temperature on mosquito abundance and dengue transmission rate, play key roles in explaining the temporal dynamics of dengue incidence in the human population. Our study thus contributes to a better understanding of dengue dynamics and provides a predictive tool for preventive dengue reduction strategies.

Detection of smoothly distributed spatial outliers, with applications to identifying the distribution of parenchymal hyperinflation following an airway challenge in asthmatics.

Methacholine challenge tests are used to measure changes in pulmonary function that indicate symptoms of asthma. In addition to pulmonary function tests, which measure global changes in pulmonary function, computed tomography images taken at full inspiration before and after administration of methacholine provide local air volume changes (hyper-inflation post methacholine) at individual acinar units, indicating local airway hyperresponsiveness. Some of the acini may have extreme air volume changes relative to the global average, indicating hyperresponsiveness, and those extreme values may occur in clusters. We propose a Gaussian mixture model with a spatial smoothness penalty to improve prediction of hyperresponsive locations that occur in spatial clusters. A simulation study provides evidence that the spatial smoothness penalty improves prediction under different data-generating mechanisms. We apply this method to computed tomography data from Seoul National University Hospital on five healthy and ten asthmatic subjects. Copyright © 2017 John Wiley & Sons, Ltd.

Total Phosphorus Concentration Trends in 40 Iowa Rivers, 1999 to 2013.

Excessive phosphorus (P) in rivers is prompting states to develop strategies to reduce P concentrations and export. The goal of this study was to assess the current condition by analyzing trends in total P (TP) concentrations at 40 river monitoring sites in Iowa for the period 1998 to 2013. We used monthly river monitoring data collected by the State of Iowa at ambient sites located beyond the influence of point sources or cities. Study objectives were to assess the presence of any linear trends in the TP concentration data using a time-series method that accounted for temporal correlation in the data and discharge and to combine the trend information from individual sites into an assessment of the statewide rate of change in river TP concentrations. Results indicated that annual TP concentrations were significantly decreasing at 12 sites ( < 0.05), with concentrations ranging from 7.5% (Maple River) to 2.6% (Boyer River) and averaging 4.1% for the 12 sites. No statistically significant change was measured at 28 sites ( > 0.05), although all but four of these sites had decreasing concentrations. As a population of sampled rivers across Iowa, TP concentrations were declining at an annual rate of approximately 2.6%. The decreasing trends are consistent with reported reductions in sediment concentrations measured in the Raccoon River and with decreasing trends detected in other midwestern rivers. We attribute the decreasing TP trends primarily to improvements in conservation and land management. Although reducing nonpoint source TP concentrations in Iowa rivers will be a tremendous challenge for the agricultural community, progress is being made toward meeting this goal with existing programs.

Testing for effects of climate change on competitive relationships and coexistence between two bird species.

Climate change is expected to have profound ecological effects, yet shifts in competitive abilities among species are rarely studied in this context. Blue tits (Cyanistes caeruleus) and great tits (Parus major) compete for food and roosting sites, yet coexist across much of their range. Climate change might thus change the competitive relationships and coexistence between these two species. Analysing four of the highest-quality, long-term datasets available on these species across Europe, we extend the textbook example of coexistence between competing species to include the dynamic effects of long-term climate variation. Using threshold time-series statistical modelling, we demonstrate that long-term climate variation affects species demography through different influences on density-dependent and density-independent processes. The competitive interaction between blue tits and great tits has shifted in one of the studied sites, creating conditions that alter the relative equilibrium densities between the two species, potentially disrupting long-term coexistence. Our analyses show that long-term climate change can, but does not always, generate local differences in the equilibrium conditions of spatially structured species assemblages. We demonstrate how long-term data can be used to better understand whether (and how), for instance, climate change might change the relationships between coexisting species. However, the studied populations are rather robust against competitive exclusion.

Climate and population density drive changes in cod body size throughout a century on the Norwegian coast.

Understanding how populations respond to changes in climate requires long-term, high-quality datasets, which are rare for marine systems. We estimated the effects of climate warming on cod lengths and length variability using a unique 91-y time series of more than 100,000 individual juvenile cod lengths from surveys that began in 1919 along the Norwegian Skagerrak coast. Using linear mixed-effects models, we accounted for spatial population structure and the nested structure of the survey data to reveal opposite effects of spring and summer warming on juvenile cod lengths. Warm summer temperatures in the coastal Skagerrak have limited juvenile growth. In contrast, warmer springs have resulted in larger juvenile cod, with less variation in lengths within a cohort, possibly because of a temperature-driven contraction in the spring spawning period. A density-dependent reduction in length was evident only at the highest population densities in the time series, which have rarely been observed in the last decade. If temperatures rise because of global warming, nonlinearities in the opposing temperature effects suggest that negative effects of warmer summers will increasingly outweigh positive effects of warmer springs, and the coastal Skagerrak will become ill-suited for Atlantic cod.

Nonlinear effect of climate on plague during the third pandemic in China.

Over the years, plague has caused a large number of deaths worldwide and subsequently changed history, not the least during the period of the Black Death. Of the three plague pandemics, the third is believed to have originated in China. Using the spatial and temporal human plague records in China from 1850 to 1964, we investigated the association of human plague intensity (plague cases per year) with proxy data on climate condition (specifically an index for dryness/wetness). Our modeling analysis demonstrates that the responses of plague intensity to dry/wet conditions were different in northern and southern China. In northern China, plague intensity generally increased when wetness increased, for both the current and the previous year, except for low intensity during extremely wet conditions in the current year (reflecting a dome-shaped response to current-year dryness/wetness). In southern China, plague intensity generally decreased when wetness increased, except for high intensity during extremely wet conditions of the current year. These opposite effects are likely related to the different climates and rodent communities in the two parts of China: In northern China (arid climate), rodents are expected to respond positively to high precipitation, whereas in southern China (humid climate), high precipitation is likely to have a negative effect. Our results suggest that associations between human plague intensity and precipitation are nonlinear: positive in dry conditions, but negative in wet conditions.

Dynamics of the plague-wildlife-human system in Central Asia are controlled by two epidemiological thresholds.

Plague (caused by the bacterium Yersinia pestis) is a zoonotic reemerging infectious disease with reservoirs in rodent populations worldwide. Using one-half of a century of unique data (1949-1995) from Kazakhstan on plague dynamics, including data on the main rodent host reservoir (great gerbil), main vector (flea), human cases, and external (climate) conditions, we analyze the full ecoepidemiological (bubonic) plague system. We show that two epidemiological threshold quantities play key roles: one threshold relating to the dynamics in the host reservoir, and the second threshold relating to the spillover of the plague bacteria into the human population.

Nitrate Concentration Trends in Iowa's Rivers, 1998 to 2012: What Challenges Await Nutrient Reduction Initiatives?

Nitrate-nitrogen (NO-N) concentrations threaten water supplies and contribute to impairments of surface water resources. In this study, we analyzed concentration trends at 60 ambient river monitoring sites in Iowa for the years 1998 to 2012 to assess the presence of linear trends in the NO-N concentration data using a time-series method that accounted for temporal correlation and combined the trend information from individual sites into an assessment of the state-wide rate of change in river NO-N concentrations. Forty-six of the sites had sufficient records for trend analysis. Study results indicated that 37 out of 46 sites (80%) did not have statistically significant trends over the monitoring period ( > 0.1). Six monitoring sites in western Iowa had statistically significant increasing trends ( < 0.05), and three additional sites located in western and southern Iowa showed nominally significant increasing trends ( < 0.1). The rate of statistically significant increases ranged from 0.15 to 0.33 mg L yr. Aggregated across the state, the overall trend of NO-N concentrations in Iowa rivers is increasing, with an average and median rate of 0.05 and 0.03 mg L yr, respectively. Increasing concentration is likely associated with increasing trends in fertilizer sales and animal production, but better tracking is needed to establish a definitive relation. Reducing NO-N concentrations using conservation practices is a major focus of the recently proposed Iowa Nutrient Reduction Strategy, and our study provides an important milestone preceding implementation of the strategy.

Dynamic regression modeling of daily nitrate-nitrogen concentrations in a large agricultural watershed.

Nitrate-nitrogen concentrations in rivers represent challenges for water supplies that use surface water sources. Nitrate concentrations are often modeled using time-series approaches, but previous efforts have typically relied on monthly time steps. In this study, we developed a dynamic regression model of daily nitrate concentrations in the Raccoon River, Iowa, that incorporated contemporaneous and lags of precipitation and discharge occurring at several locations around the basin. Results suggested that 95 % of the variation in daily nitrate concentrations measured at the outlet of a large agricultural watershed can be explained by time-series patterns of precipitation and discharge occurring in the basin. Discharge was found to be a more important regression variable than precipitation in our model but both regression parameters were strongly correlated with nitrate concentrations. The time-series model was consistent with known patterns of nitrate behavior in the watershed, successfully identifying contemporaneous dilution mechanisms from higher relief and urban areas of the basin while incorporating the delayed contribution of nitrate from tile-drained regions in a lagged response. The first difference of the model errors were modeled as an AR(16) process and suggest that daily nitrate concentration changes remain temporally correlated for more than 2 weeks although temporal correlation was stronger in the first few days before tapering off. Consequently, daily nitrate concentrations are non-stationary, i.e. of strong memory. Using time-series models to reliably forecast daily nitrate concentrations in a river based on patterns of precipitation and discharge occurring in its basin may be of great interest to water suppliers.

Imaging-based assessment of lung function in a population cooking indoors with biomass fuel: a pilot study.

Biomass fuels (wood) are commonly used indoors in underventilated environments for cooking in the developing world, but the impact on lung physiology is poorly understood. Quantitative computed tomography (qCT) can provide sensitive metrics to compare the lungs of women cooking with wood vs. liquified petroleum gas (LPG). We prospectively assessed (qCT and spirometry) 23 primary female cooks (18 biomass, 5 LPG) with no history of cardiopulmonary disease in Thanjavur, India. CT was obtained at coached total lung capacity (TLC) and residual volume (RV). qCT assessment included texture-derived ground glass opacity [GGO: Adaptive Multiple Feature Method (AMFM)], air-trapping (expiratory voxels ≤ -856HU) and image registration-based assessment [Disease Probability Measure (DPM)] of emphysema, functional small airways disease (%AirTrapDPM), and regional lung mechanics. In addition, within-kitchen exposure assessments included particulate matter <2.5 µm(PM2.5), black carbon, ß-(1, 3)-d-glucan (surrogate for fungi), and endotoxin. Air-trapping went undetected at RV via the threshold-based measure (voxels ≤ -856HU), possibly due to density shifts in the presence of inflammation. However, DPM, utilizing image-matching, demonstrated significant air-trapping in biomass vs. LPG cooks (P = 0.049). A subset of biomass cooks (6/18), identified using k-means clustering, had markedly altered DPM-metrics: greater air-trapping (P < 0.001), lower TLC-RV volume change (P < 0.001), a lower mean anisotropic deformation index (ADI; P < 0.001), and elevated % GGO (P < 0.02). Across all subjects, a texture measure of bronchovascular bundles was correlated to the log-transformed ß-(1, 3)-d-glucan concentration (P = 0.026, R = 0.46), and black carbon (P = 0.04, R = 0.44). This pilot study identified environmental links with qCT-based lung pathologies and a cluster of biomass cooks (33%) with significant small airways disease.NEW & NOTEWORTHY Quantitative computed tomography has identified a cluster of women (33%) cooking with biomass fuels (wood) with image-based markers of functional small airways disease and associated alterations in regional lung mechanics. Texture and image registration-based metrics of lung function may allow for early detection of potential inflammatory processes that may arise in response to inhaled biomass smoke, and help identify phenotypes of chronic lung disease prevalent in nonsmoking women in the developing world.

Non-additive and non-stationary properties in the spatial distribution of a large marine fish population.

Density-independent and density-dependent variables both affect the spatial distributions of species. However, their effects are often separately addressed using different analytical techniques. We apply a spatially explicit regression framework that incorporates localized, interactive and threshold effects of both density-independent (water temperature) and density-dependent (population abundance) variables, to study the spatial distribution of a well-monitored flatfish population in the eastern Bering Sea. Results indicate that when population biomass was beyond a threshold a further increase in biomass-promoted habitat expansion in a non-additive fashion with water temperature. In contrast, during years of low population size, habitat occupancy was affected positively only by water temperature. These results reveal the spatial signature of intraspecific abundance distribution relationships as well as the non-additive and non-stationary responses of species spatial dynamics. Furthermore, these results underscore the importance of implementing analytical techniques that can simultaneously account for density-dependent and density-independent sources of variability when studying geographical distribution patterns.

Functional responses and scaling in predator-prey interactions of marine fishes: contemporary issues and emerging concepts.

Predator-prey interactions are a primary structuring force vital to the resilience of marine communities and sustainability of the world's oceans. Human influences on marine ecosystems mediate changes in species interactions. This generality is evinced by the cascading effects of overharvesting top predators on the structure and function of marine ecosystems. It follows that ecological forecasting, ecosystem management, and marine spatial planning require a better understanding of food web relationships. Characterising and scaling predator-prey interactions for use in tactical and strategic tools (i.e. multi-species management and ecosystem models) are paramount in this effort. Here, we explore what issues are involved and must be considered to advance the use of predator-prey theory in the context of marine fisheries science. We address pertinent contemporary ecological issues including (1) the approaches and complexities of evaluating predator responses in marine systems; (2) the 'scaling up' of predator-prey interactions to the population, community, and ecosystem level; (3) the role of predator-prey theory in contemporary fisheries and ecosystem modelling approaches; and (4) directions for the future. Our intent is to point out needed research directions that will improve our understanding of predator-prey interactions in the context of the sustainable marine fisheries and ecosystem management.

Spawning stock and recruitment in North Sea cod shaped by food and climate.

In order to provide better fisheries management and conservation decisions, there is a need to discern the underlying relationship between the spawning stock and recruitment of marine fishes, a relationship which is influenced by the environmental conditions. Here, we demonstrate how the environmental conditions (temperature and the food availability for fish larvae) influence the stock-recruitment relationship and indeed what kind of stock-recruitment relationship we might see under different environmental conditions. Using unique zooplankton data from the Continuous Plankton Recorder, we find that food availability (i.e. zooplankton) in essence determines which model applies for the once large North Sea cod (Gadus morhua) stock. Further, we show that recruitment is strengthened during cold years and weakened during warm years. Our combined model explained 45 per cent of the total variance in cod recruitment, while the traditional Ricker and Beverton-Holt models only explained about 10 per cent. Specifically, our approach predicts that a full recovery of the North Sea cod stock might not be expected until the environment becomes more favourable.

Ontogenetic and sex-specific differences in density-dependent habitat selection of a marine fish population.

The spatial dynamics of species are the result of complex interactions between density-independent and density-dependent sources of variability. Disentangling these two sources of variability has challenged ecologists working in both terrestrial and aquatic ecosystems. Using a novel spatially explicit statistical model, we tested for the presence of density-independent and density-dependent habitat selection in yellowfin sole (Limanda aspera) in the eastern Bering Sea. We found specificities in the density-dependent processes operating across ontogeny and particularly with gender. Density-dependent habitat expansion occurred primarily in females, and to a lesser degree in males. These patterns were especially evident in adult stages, while juvenile stages of both sexes exhibited a mix of different dynamics. Association of yellowfin sole with substrate type also varied by sex and to a lesser degree with size, with large females distributed over a wider range of substrates than males. Moreover, yellowfin sole expanded northward as cold subsurface waters retracted in summer, suggesting high sensitivity to arctic warming. Our findings illustrate how marginal habitats can play an important role in buffering density-dependent habitat expansion, with direct implications for resource management. Our spatially explicit modeling approach is effective in evaluating density-dependent spatial dynamics, and can easily be used to test similar hypotheses from a variety of aquatic and terrestrial ecosystems.

Metabolic derangement in polycystic kidney disease mouse models is ameliorated by mitochondrial-targeted antioxidants.

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressively enlarging cysts. Here we elucidate the interplay between oxidative stress, mitochondrial dysfunction, and metabolic derangement using two mouse models of PKD1 mutation, PKD1RC/null and PKD1RC/RC. Mouse kidneys with PKD1 mutation have decreased mitochondrial complexes activity. Targeted proteomics analysis shows a significant decrease in proteins involved in the TCA cycle, fatty acid oxidation (FAO), respiratory complexes, and endogenous antioxidants. Overexpressing mitochondrial-targeted catalase (mCAT) using adeno-associated virus reduces mitochondrial ROS, oxidative damage, ameliorates the progression of PKD and partially restores expression of proteins involved in FAO and the TCA cycle. In human ADPKD cells, inducing mitochondrial ROS increased ERK1/2 phosphorylation and decreased AMPK phosphorylation, whereas the converse was observed with increased scavenging of ROS in the mitochondria. Treatment with the mitochondrial protective peptide, SS31, recapitulates the beneficial effects of mCAT, supporting its potential application as a novel therapeutic for ADPKD.

Direct and indirect climate forcing in a multi-species marine system.

Interactions within and between species complicate quantification of climate effects, by causing indirect, often delayed, effects of climate fluctuations and compensation of mortality. Here we identify direct and indirect climate effects by analysing unique Russian time-series data from the Norwegian Sea-Barents Sea ecosystem on the first life stages of cod, capelin, herring and haddock, their predators, competitors and zooplanktonic prey. By analysing growth and survival from one life stage to the next (eggs-larvae-juveniles-recruits), we find evidence for both bottom-up, direct and top-down effects of climate. Ambient zooplankton biomass predicts survival of all species, whereas ambient temperature mainly affects survival through effects on growth. In warm years, all species experienced improved growth and feeding conditions. Cohorts born following a warm year will, however, experience increased predation and competition because of increased densities of subadult cod and herring, leading to delayed climate effects. While climate thus affects early growth and survival through several mechanisms, only some of the identified mechanisms were found to be significant predictors of population growth. In particular, our findings exemplify that climate impacts are barely propagated to later life stages when density dependence is strong.

Glutathione peroxidase-1 overexpression reduces oxidative stress, and improves pathology and proteome remodeling in the kidneys of old mice.

This study investigated the direct roles of hydrogen peroxide (H2 O2 ) in kidney aging using transgenic mice overexpressing glutathione peroxidase-1 (GPX1 TG). We demonstrated that kidneys in old mice recapitulated kidneys in elderly humans and were characterized by glomerulosclerosis, tubular atrophy, interstitial fibrosis, and loss of cortical mass. Scavenging H2 O2 by GPX1 TG significantly reduced mitochondrial and total cellular reactive oxygen species (ROS) and mitigated oxidative damage, thus improving these pathologies. The potential mechanisms by which ROS are increased in the aged kidney include a decreased abundance of an anti-aging hormone, Klotho, in kidney tissue, and decreased expression of nuclear respiratory factor 2 (Nrf2), a master regulator of the stress response. Decreased Klotho or Nrf2 was not improved in the kidneys of old GPX1 TG mice, even though mitochondrial morphology was better preserved. Using laser capture microdissection followed by label-free shotgun proteomics analysis, we show that the glomerular proteome in old mice was characterized by decreased abundance of cytoskeletal proteins (critical for maintaining normal glomerular function) and heat shock proteins, leading to increased accumulation of apolipoprotein E and inflammatory molecules. Targeted proteomic analysis of kidney tubules from old mice showed decreased abundance of fatty acid oxidation enzymes and antioxidant proteins, as well as increased abundance of glycolytic enzymes and molecular chaperones. GPX1 TG partially attenuated the remodeling of glomerular and tubule proteomes in aged kidneys. In summary, mitochondria from GPX1 TG mice are protected and kidney aging is ameliorated via its antioxidant activities, independent and downstream of Nrf2 or Klotho signaling.

Density dependence and density independence during the early life stages of four marine fish stocks.

Recruitment variability caused by density-dependent and density-independent processes is an important area within the study of fish dynamics. These processes can exhibit nonlinearities and nonadditive properties that may have profound dynamic effects. We investigate the importance of population density (i.e., density dependence) and environmental forcing (i.e., density independence) on the age-0 and age-1 abundance of capelin (Mallotus villosus), northeast Arctic cod (Gadus morhua), northeast Arctic haddock (Melanogrammus aeglefinus), and Norwegian spring spawning herring (Clupea harengus) in the Barents Sea. We use statistical methods that explicitly account for nonlinearities and nonadditive interactions between internal and external variables in the abundance of these two pre-recruitment stages. Our results indicate that, during their first five months of life, cod, haddock, and herring experience higher density-dependent survival than capelin. The abundance of age-0 cod depends on the mean age and biomass of the spawning stock, a result which has implications for the management of the entire cod stock. Temperature is another important factor influencing the abundance at age-0 and age-1 of all four species, except herring at age-1. Between age-0 and age-1, there is an attenuation of density-dependent survival for cod and herring, while haddock and capelin experience density dependence at high and low temperatures, respectively. Predation by subadult cod is important for both capelin and cod at age-1. We found strong indications for interactions among the studied species, pointing to the importance of viewing the problem of species recruitment variability as a community, rather than as a population phenomenon.

Spatial anatomy of species survival: effects of predation and climate-driven environmental variability.

The majority of survival analyses focus on temporal scales. Consequently, there is a limited understanding of how species survival varies over space and, ultimately, how spatial variability in the environment affects the temporal dynamics of species abundance. Using data from the Barents Sea, we study the spatiotemporal variability of the juvenile Atlantic cod (Gadus morhua) survival. We develop an index of spatial survival based on changes of juvenile cod distribution through their first winter of life (from age-0 to age-1) and study its variability in relation to biotic and abiotic factors. Over the 25 years analyzed (1980-2004), we found that, once the effect of passive drift due to dominant currents is accounted for, the area where age-0 cod survival was lowest coincided with the area of highest abundance of older cod. Within this critical region, the survival of age-0 cod was negatively affected by its own abundance, by that of older cod, and by bottom depth. Furthermore, during cold years, age-0 cod survival increased in the eastern and coldest portion of the examined area, which was typically avoided by older conspecifics. Based on these results we propose that within the examined area top-down mechanisms and predation-driven density dependence can strongly affect the spatial pattern of age-0 cod survival. Climate-related variables can also influence the spatial survival of age-0 cod by affecting their distribution and that of their predators. Results from these and similar studies, focusing on the spatial variability of survival rates, can be used to characterize species habitat quality of marine renewable resources.