AIR QUALITY AND GLOBAL CLIMATE CHANGE (PHASE 1)

EPA Science Inventory

Predicted changes in the global climate over the coming decades could alter weather patterns and, thus, impact land use, source emissions, and tropospheric air quality. The United States has a series of standards for criteria air pollutants and other air pollutants in place to s...

Structural salience and the nonaccidentality of a Gestalt.

PubMed

Strother, Lars; Kubovy, Michael

2012-08-01

We perceive structure through a process of perceptual organization. Here we report a new perceptual organization phenomenon-the facilitation of visual grouping by global curvature. Observers viewed patterns that they perceived as organized into collections of curves. The patterns were perceptually ambiguous such that the perceived orientation of the patterns varied from trial to trial. When patterns were sufficiently dense and proximity was equated for the predominant perceptual alternatives, observers tended to perceive the organization with the greatest curvature. This effect is tantamount to visual grouping by maximal curvature and thus demonstrates an unprecedented effect of global structure on perceptual organization. We account for this result with a model that predicts the perceived organization of a pattern as function of its nonaccidentality, which we define as the probability that it could have occurred by chance. Our findings demonstrate a novel relationship between the geometry of a pattern and the visual salience of global structure. (c) 2012 APA, all rights reserved.

All is not loss: plant biodiversity in the anthropocene.

PubMed

Ellis, Erle C; Antill, Erica C; Kreft, Holger

2012-01-01

Anthropogenic global changes in biodiversity are generally portrayed in terms of massive native species losses or invasions caused by recent human disturbance. Yet these biodiversity changes and others caused directly by human populations and their use of land tend to co-occur as long-term biodiversity change processes in the Anthropocene. Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. The patterns thus derived confirm that while native losses are likely significant across at least half of Earth's ice-free land, model predictions indicate that plant species richness has increased overall in most regional landscapes, mostly because species invasions tend to exceed native losses. While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. Effective global stewardship of plant biodiversity in the Anthropocene will require integrated frameworks for observing, modeling and forecasting the different forms of anthropogenic biodiversity change processes at regional landscape scales, towards conserving biodiversity within the novel plant communities created and sustained by human systems.

All Is Not Loss: Plant Biodiversity in the Anthropocene

PubMed Central

Ellis, Erle C.; Antill, Erica C.; Kreft, Holger

2012-01-01

Anthropogenic global changes in biodiversity are generally portrayed in terms of massive native species losses or invasions caused by recent human disturbance. Yet these biodiversity changes and others caused directly by human populations and their use of land tend to co-occur as long-term biodiversity change processes in the Anthropocene. Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. The patterns thus derived confirm that while native losses are likely significant across at least half of Earth's ice-free land, model predictions indicate that plant species richness has increased overall in most regional landscapes, mostly because species invasions tend to exceed native losses. While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. Effective global stewardship of plant biodiversity in the Anthropocene will require integrated frameworks for observing, modeling and forecasting the different forms of anthropogenic biodiversity change processes at regional landscape scales, towards conserving biodiversity within the novel plant communities created and sustained by human systems. PMID:22272360

Photosynthesis, growth and maize yields in the context of global change

USDA-ARS?s Scientific Manuscript database

Maize is the third most important grain crop behind wheat and rice. Global mean temperatures are rising primarily due to anthropogenic carbon dioxide emissions into the earth’s atmosphere. Warmer temperatures over major landmasses are predicted to alter precipitation patterns and to increase the f...

Few multiyear precipitation-reduction experiments find a shift in the productivity-precipitation relationship

USDA-ARS?s Scientific Manuscript database

Precipitation is a key driver of ecosystem net primary productivity and carbon cycling. Global warming is altering precipitation patterns globally, and longer and more intense drought episodes are projected for many temperate and Mediterranean regions. The challenge of predicting the effects of alt...

Predictiveness of Disease Risk in a Global Outreach Tourist Setting in Thailand Using Meteorological Data and Vector-Borne Disease Incidences

PubMed Central

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-01-01

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate. PMID:25325356

Predictiveness of disease risk in a global outreach tourist setting in Thailand using meteorological data and vector-borne disease incidences.

PubMed

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-10-16

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate.

Summer precipitation prediction in the source region of the Yellow River using climate indices

NASA Astrophysics Data System (ADS)

Yuan, F.

2016-12-01

The source region of the Yellow River contributes about 35% of the total water yield in the Yellow River basin playing an important role in meeting downstream water resources requirements. The summer precipitation from June to September in the source region of the Yellow River accounts for about 70% of the annual total, and its decrease would cause further water shortage problems. Consequently, the objectives of this study are to improve the understanding of the linkages between the precipitation in the source region of the Yellow River and global teleconnection patterns, and to predict the summer precipitation based on revealed teleconnections. Spatial variability of precipitation was investigated based on three homogeneous sub-regions. Principal component analysis and singular value decomposition were used to find significant relations between the precipitation in the source region of the Yellow River and global teleconnection patterns using climate indices. A back-propagation neural network was developed to predict the summer precipitation using significantly correlated climate indices. It was found that precipitation in the study area is positively related to North Atlantic Oscillation, West Pacific Pattern and El Nino Southern Oscillation, and inversely related to Polar Eurasian pattern. Summer precipitation was overall well predicted using these significantly correlated climate indices, and the Pearson correlation coefficient between predicted and observed summer precipitation was in general larger than 0.6. The results are useful for integrated water resources management in the Yellow River basin.

Cryptic biodiversity loss linked to global climate change

NASA Astrophysics Data System (ADS)

Bálint, M.; Domisch, S.; Engelhardt, C. H. M.; Haase, P.; Lehrian, S.; Sauer, J.; Theissinger, K.; Pauls, S. U.; Nowak, C.

2011-09-01

Global climate change (GCC) significantly affects distributional patterns of organisms, and considerable impacts on biodiversity are predicted for the next decades. Inferred effects include large-scale range shifts towards higher altitudes and latitudes, facilitation of biological invasions and species extinctions. Alterations of biotic patterns caused by GCC have usually been predicted on the scale of taxonomically recognized morphospecies. However, the effects of climate change at the most fundamental level of biodiversity--intraspecific genetic diversity--remain elusive. Here we show that the use of morphospecies-based assessments of GCC effects will result in underestimations of the true scale of biodiversity loss. Species distribution modelling and assessments of mitochondrial DNA variability in nine montane aquatic insect species in Europe indicate that future range contractions will be accompanied by severe losses of cryptic evolutionary lineages and genetic diversity within these lineages. These losses greatly exceed those at the scale of morphospecies. We also document that the extent of range reduction may be a useful proxy when predicting losses of genetic diversity. Our results demonstrate that intraspecific patterns of genetic diversity should be considered when estimating the effects of climate change on biodiversity.

Wetter subtropics in a warmer world: Contrasting past and future hydrological cycles

NASA Astrophysics Data System (ADS)

Burls, Natalie J.; Fedorov, Alexey V.

2017-12-01

During the warm Miocene and Pliocene Epochs, vast subtropical regions had enough precipitation to support rich vegetation and fauna. Only with global cooling and the onset of glacial cycles some 3 Mya, toward the end of the Pliocene, did the broad patterns of arid and semiarid subtropical regions become fully developed. However, current projections of future global warming caused by CO2 rise generally suggest the intensification of dry conditions over these subtropical regions, rather than the return to a wetter state. What makes future projections different from these past warm climates? Here, we investigate this question by comparing a typical quadrupling-of-CO2 experiment with a simulation driven by sea-surface temperatures closely resembling available reconstructions for the early Pliocene. Based on these two experiments and a suite of other perturbed climate simulations, we argue that this puzzle is explained by weaker atmospheric circulation in response to the different ocean surface temperature patterns of the Pliocene, specifically reduced meridional and zonal temperature gradients. Thus, our results highlight that accurately predicting the response of the hydrological cycle to global warming requires predicting not only how global mean temperature responds to elevated CO2 forcing (climate sensitivity) but also accurately quantifying how meridional sea-surface temperature patterns will change (structural climate sensitivity).

Synchronization of three electrochemical oscillators: From local to global coupling

NASA Astrophysics Data System (ADS)

Liu, Yifan; Sebek, Michael; Mori, Fumito; Kiss, István Z.

2018-04-01

We investigate the formation of synchronization patterns in an oscillatory nickel electrodissolution system in a network obtained by superimposing local and global coupling with three electrodes. We explored the behavior through numerical simulations using kinetic ordinary differential equations, Kuramoto type phase models, and experiments, in which the local to global coupling could be tuned by cross resistances between the three nickel wires. At intermediate coupling strength with predominant global coupling, two of the three oscillators, whose natural frequencies are closer, can synchronize. By adding even a relatively small amount of local coupling (about 9%-25%), a spatially organized partially synchronized state can occur where one of the two synchronized elements is in the center. A formula was derived for predicting the critical coupling strength at which full synchronization will occur independent of the permutation of the natural frequencies of the oscillators over the network. The formula correctly predicts the variation of the critical coupling strength as a function of the global coupling fraction, e.g., with local coupling the critical coupling strength is about twice than that required with global coupling. The results show the importance of the topology of the network on the synchronization properties in a simple three-oscillator setup and could provide guidelines for decrypting coupling topology from identification of synchronization patterns.

Tolerance adaptation and precipitation changes complicate latitudinal patterns of climate change impacts.

PubMed

Bonebrake, Timothy C; Mastrandrea, Michael D

2010-07-13

Global patterns of biodiversity and comparisons between tropical and temperate ecosystems have pervaded ecology from its inception. However, the urgency in understanding these global patterns has been accentuated by the threat of rapid climate change. We apply an adaptive model of environmental tolerance evolution to global climate data and climate change model projections to examine the relative impacts of climate change on different regions of the globe. Our results project more adverse impacts of warming on tropical populations due to environmental tolerance adaptation to conditions of low interannual variability in temperature. When applied to present variability and future forecasts of precipitation data, the tolerance adaptation model found large reductions in fitness predicted for populations in high-latitude northern hemisphere regions, although some tropical regions had comparable reductions in fitness. We formulated an evolutionary regional climate change index (ERCCI) to additionally incorporate the predicted changes in the interannual variability of temperature and precipitation. Based on this index, we suggest that the magnitude of climate change impacts could be much more heterogeneous across latitude than previously thought. Specifically, tropical regions are likely to be just as affected as temperate regions and, in some regions under some circumstances, possibly more so.

Title: Freshwater phytoplankton responses to global warming.

PubMed

Wagner, Heiko; Fanesi, Andrea; Wilhelm, Christian

2016-09-20

Global warming alters species composition and function of freshwater ecosystems. However, the impact of temperature on primary productivity is not sufficiently understood and water quality models need to be improved in order to assess the quantitative and qualitative changes of aquatic communities. On the basis of experimental data, we demonstrate that the commonly used photosynthetic and water chemistry parameters alone are not sufficient for modeling phytoplankton growth under changing temperature regimes. We present some new aspects of the acclimation process with respect to temperature and how contrasting responses may be explained by a more complete physiological knowledge of the energy flow from photons to new biomass. We further suggest including additional bio-markers/traits for algal growth such as carbon allocation patterns to increase the explanatory power of such models. Although carbon allocation patterns are promising and functional cellular traits for growth prediction under different nutrient and light conditions, their predictive power still waits to be tested with respect to temperature. A great challenge for the near future will be the prediction of primary production efficiencies under the global change scenario using a uniform model for phytoplankton assemblages. Copyright © 2016 Elsevier GmbH. All rights reserved.

A Systematic Review of Global Drivers of Ant Elevational Diversity

PubMed Central

Szewczyk, Tim; McCain, Christy M.

2016-01-01

Ant diversity shows a variety of patterns across elevational gradients, though the patterns and drivers have not been evaluated comprehensively. In this systematic review and reanalysis, we use published data on ant elevational diversity to detail the observed patterns and to test the predictions and interactions of four major diversity hypotheses: thermal energy, the mid-domain effect, area, and the elevational climate model. Of sixty-seven published datasets from the literature, only those with standardized, comprehensive sampling were used. Datasets included both local and regional ant diversity and spanned 80° in latitude across six biogeographical provinces. We used a combination of simulations, linear regressions, and non-parametric statistics to test multiple quantitative predictions of each hypothesis. We used an environmentally and geometrically constrained model as well as multiple regression to test their interactions. Ant diversity showed three distinct patterns across elevations: most common were hump-shaped mid-elevation peaks in diversity, followed by low-elevation plateaus and monotonic decreases in the number of ant species. The elevational climate model, which proposes that temperature and precipitation jointly drive diversity, and area were partially supported as independent drivers. Thermal energy and the mid-domain effect were not supported as primary drivers of ant diversity globally. The interaction models supported the influence of multiple drivers, though not a consistent set. In contrast to many vertebrate taxa, global ant elevational diversity patterns appear more complex, with the best environmental model contingent on precipitation levels. Differences in ecology and natural history among taxa may be crucial to the processes influencing broad-scale diversity patterns. PMID:27175999

Using biogeographic distributions and natural history to predict marine/estuarine species at risk to climate change

EPA Science Inventory

Effects of climate change on marine and estuarine species will vary with attributes of the species and the spatial patterns of environmental change at the habitat and global scales. To better predict which species are at greatest risk, we are developing a knowledge base of specie...

Global vegetation productivity response to climatic oscillations during the satellite era.

PubMed

Gonsamo, Alemu; Chen, Jing M; Lombardozzi, Danica

2016-10-01

Climate control on global vegetation productivity patterns has intensified in response to recent global warming. Yet, the contributions of the leading internal climatic variations to global vegetation productivity are poorly understood. Here, we use 30 years of global satellite observations to study climatic variations controls on continental and global vegetation productivity patterns. El Niño-Southern Oscillation (ENSO) phases (La Niña, neutral, and El Niño years) appear to be a weaker control on global-scale vegetation productivity than previously thought, although continental-scale responses are substantial. There is also clear evidence that other non-ENSO climatic variations have a strong control on spatial patterns of vegetation productivity mainly through their influence on temperature. Among the eight leading internal climatic variations, the East Atlantic/West Russia Pattern extensively controls the ensuing year vegetation productivity of the most productive tropical and temperate forest ecosystems of the Earth's vegetated surface through directionally consistent influence on vegetation greenness. The Community Climate System Model (CCSM4) simulations do not capture the observed patterns of vegetation productivity responses to internal climatic variations. Our analyses show the ubiquitous control of climatic variations on vegetation productivity and can further guide CCSM and other Earth system models developments to represent vegetation response patterns to unforced variability. Several winter time internal climatic variation indices show strong potentials on predicting growing season vegetation productivity two to six seasons ahead which enables national governments and farmers forecast crop yield to ensure supplies of affordable food, famine early warning, and plan management options to minimize yield losses ahead of time. © 2016 John Wiley & Sons Ltd.

How Much Global Burned Area Can Be Forecast on Seasonal Time Scales Using Sea Surface Temperatures?

NASA Technical Reports Server (NTRS)

Chen, Yang; Morton, Douglas C.; Andela, Niels; Giglio, Louis; Randerson, James T.

2016-01-01

Large-scale sea surface temperature (SST) patterns influence the interannual variability of burned area in many regions by means of climate controls on fuel continuity, amount, and moisture content. Some of the variability in burned area is predictable on seasonal timescales because fuel characteristics respond to the cumulative effects of climate prior to the onset of the fire season. Here we systematically evaluated the degree to which annual burned area from the Global Fire Emissions Database version 4 with small fires (GFED4s) can be predicted using SSTs from 14 different ocean regions. We found that about 48 of global burned area can be forecast with a correlation coefficient that is significant at a p < 0.01 level using a single ocean climate index (OCI) 3 or more months prior to the month of peak burning. Continental regions where burned area had a higher degree of predictability included equatorial Asia, where 92% of the burned area exceeded the correlation threshold, and Central America, where 86% of the burned area exceeded this threshold. Pacific Ocean indices describing the El Nino-Southern Oscillation were more important than indices from other ocean basins, accounting for about 1/3 of the total predictable global burned area. A model that combined two indices from different oceans considerably improved model performance, suggesting that fires in many regions respond to forcing from more than one ocean basin. Using OCI-burned area relationships and a clustering algorithm, we identified 12 hotspot regions in which fires had a consistent response to SST patterns. Annual burned area in these regions can be predicted with moderate confidence levels, suggesting operational forecasts may be possible with the aim of improving ecosystem management.

Modelling spatial patterns of urban growth in Africa

PubMed Central

Linard, Catherine; Tatem, Andrew J.; Gilbert, Marius

2013-01-01

The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers. PMID:25152552

Disease in a more variable and unpredictable climate

NASA Astrophysics Data System (ADS)

McMahon, T. A.; Raffel, T.; Rohr, J. R.; Halstead, N.; Venesky, M.; Romansic, J.

2014-12-01

Global climate change is shifting the dynamics of infectious diseases of humans and wildlife with potential adverse consequences for disease control. Despite this, the role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial. Climate change is expected to increase climate variability in addition to increasing mean temperatures, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments and field data on disease-associated frog declines in Latin America support this framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was inconsistent with the pattern of Bd growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. Consistent with our laboratory experiments, increased regional temperature variability associated with global El Niño climatic events was the best predictor of widespread amphibian losses in the genus Atelopus. Thus, incorporating the effects of small-scale temporal variability in climate can greatly improve our ability to predict the effects of climate change on disease.

Plant diversity increases with the strength of negative density dependence at the global scale

Treesearch

Joseph A. LaManna; Scott A. Mangan; Alfonso Alonso; Norman A. Bourg; Warren Y. Brockelman; Sarayudh Bunyavejchewin; Li-Wan Chang; Jyh-Min Chiang; George B. Chuyong; Keith Clay; Richard Condit; Susan Cordell; Stuart J. Davies; Tucker J. Furniss; Christian P. Giardina; I. A. U. Nimal Gunatilleke; C. V. Savitri Gunatilleke; Fangliang He; Robert W. Howe; Stephen P. Hubbell; Chang-Fu Hsieh; Faith M. Inman-Narahari; David Janík; Daniel J. Johnson; David Kenfack; Lisa Korte; Kamil Král; Andrew J. Larson; James A. Lutz; Sean M. McMahon; William J. McShea; Hervé R. Memiaghe; Anuttara Nathalang; Vojtech Novotny; Perry S. Ong; David A. Orwig; Rebecca Ostertag; Geoffrey G. Parker; Richard P. Phillips; Lawren Sack; I-Fang Sun; J. Sebastián Tello; Duncan W. Thomas; Benjamin L. Turner; Dilys M. Vela Díaz; Tomáš Vrška; George D. Weiblen; Amy Wolf; Sandra Yap; Jonathan A. Myers

2017-01-01

Theory predicts that higher biodiversity in the tropics is maintained by specialized interactions among plants and their natural enemies that result in conspecific negative density dependence (CNDD). By using more than 3000 species and nearly 2.4 million trees across 24 forest plots worldwide, we show that global patterns in tree species diversity reflect not only...

Global patterns and predictions of seafloor biomass using random forests.

PubMed

Wei, Chih-Lin; Rowe, Gilbert T; Escobar-Briones, Elva; Boetius, Antje; Soltwedel, Thomas; Caley, M Julian; Soliman, Yousria; Huettmann, Falk; Qu, Fangyuan; Yu, Zishan; Pitcher, C Roland; Haedrich, Richard L; Wicksten, Mary K; Rex, Michael A; Baguley, Jeffrey G; Sharma, Jyotsna; Danovaro, Roberto; MacDonald, Ian R; Nunnally, Clifton C; Deming, Jody W; Montagna, Paul; Lévesque, Mélanie; Weslawski, Jan Marcin; Wlodarska-Kowalczuk, Maria; Ingole, Baban S; Bett, Brian J; Billett, David S M; Yool, Andrew; Bluhm, Bodil A; Iken, Katrin; Narayanaswamy, Bhavani E

2010-12-30

A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML) field projects. The machine-learning algorithm, Random Forests, was employed to model and predict seafloor standing stocks from surface primary production, water-column integrated and export particulate organic matter (POM), seafloor relief, and bottom water properties. The predictive models explain 63% to 88% of stock variance among the major size groups. Individual and composite maps of predicted global seafloor biomass and abundance are generated for bacteria, meiofauna, macrofauna, and megafauna (invertebrates and fishes). Patterns of benthic standing stocks were positive functions of surface primary production and delivery of the particulate organic carbon (POC) flux to the seafloor. At a regional scale, the census maps illustrate that integrated biomass is highest at the poles, on continental margins associated with coastal upwelling and with broad zones associated with equatorial divergence. Lowest values are consistently encountered on the central abyssal plains of major ocean basins The shift of biomass dominance groups with depth is shown to be affected by the decrease in average body size rather than abundance, presumably due to decrease in quantity and quality of food supply. This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management.

Global Patterns and Predictions of Seafloor Biomass Using Random Forests

PubMed Central

Wei, Chih-Lin; Rowe, Gilbert T.; Escobar-Briones, Elva; Boetius, Antje; Soltwedel, Thomas; Caley, M. Julian; Soliman, Yousria; Huettmann, Falk; Qu, Fangyuan; Yu, Zishan; Pitcher, C. Roland; Haedrich, Richard L.; Wicksten, Mary K.; Rex, Michael A.; Baguley, Jeffrey G.; Sharma, Jyotsna; Danovaro, Roberto; MacDonald, Ian R.; Nunnally, Clifton C.; Deming, Jody W.; Montagna, Paul; Lévesque, Mélanie; Weslawski, Jan Marcin; Wlodarska-Kowalczuk, Maria; Ingole, Baban S.; Bett, Brian J.; Billett, David S. M.; Yool, Andrew; Bluhm, Bodil A.; Iken, Katrin; Narayanaswamy, Bhavani E.

2010-01-01

A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML) field projects. The machine-learning algorithm, Random Forests, was employed to model and predict seafloor standing stocks from surface primary production, water-column integrated and export particulate organic matter (POM), seafloor relief, and bottom water properties. The predictive models explain 63% to 88% of stock variance among the major size groups. Individual and composite maps of predicted global seafloor biomass and abundance are generated for bacteria, meiofauna, macrofauna, and megafauna (invertebrates and fishes). Patterns of benthic standing stocks were positive functions of surface primary production and delivery of the particulate organic carbon (POC) flux to the seafloor. At a regional scale, the census maps illustrate that integrated biomass is highest at the poles, on continental margins associated with coastal upwelling and with broad zones associated with equatorial divergence. Lowest values are consistently encountered on the central abyssal plains of major ocean basins The shift of biomass dominance groups with depth is shown to be affected by the decrease in average body size rather than abundance, presumably due to decrease in quantity and quality of food supply. This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management. PMID:21209928

The energetic and carbon economic origins of leaf thermoregulation.

PubMed

Michaletz, Sean T; Weiser, Michael D; McDowell, Nate G; Zhou, Jizhong; Kaspari, Michael; Helliker, Brent R; Enquist, Brian J

2016-08-22

Leaf thermoregulation has been documented in a handful of studies, but the generality and origins of this pattern are unclear. We suggest that leaf thermoregulation is widespread in both space and time, and originates from the optimization of leaf traits to maximize leaf carbon gain across and within variable environments. Here we use global data for leaf temperatures, traits and photosynthesis to evaluate predictions from a novel theory of thermoregulation that synthesizes energy budget and carbon economics theories. Our results reveal that variation in leaf temperatures and physiological performance are tightly linked to leaf traits and carbon economics. The theory, parameterized with global averaged leaf traits and microclimate, predicts a moderate level of leaf thermoregulation across a broad air temperature gradient. These predictions are supported by independent data for diverse taxa spanning a global air temperature range of ∼60 °C. Moreover, our theory predicts that net carbon assimilation can be maximized by means of a trade-off between leaf thermal stability and photosynthetic stability. This prediction is supported by globally distributed data for leaf thermal and photosynthetic traits. Our results demonstrate that the temperatures of plant tissues, and not just air, are vital to developing more accurate Earth system models.

Global biogeography and ecology of body size in birds.

PubMed

Olson, Valérie A; Davies, Richard G; Orme, C David L; Thomas, Gavin H; Meiri, Shai; Blackburn, Tim M; Gaston, Kevin J; Owens, Ian P F; Bennett, Peter M

2009-03-01

In 1847, Karl Bergmann proposed that temperature gradients are the key to understanding geographic variation in the body sizes of warm-blooded animals. Yet both the geographic patterns of body-size variation and their underlying mechanisms remain controversial. Here, we conduct the first assemblage-level global examination of 'Bergmann's rule' within an entire animal class. We generate global maps of avian body size and demonstrate a general pattern of larger body sizes at high latitudes, conforming to Bergmann's rule. We also show, however, that median body size within assemblages is systematically large on islands and small in species-rich areas. Similarly, while spatial models show that temperature is the single strongest environmental correlate of body size, there are secondary correlations with resource availability and a strong pattern of decreasing body size with increasing species richness. Finally, our results suggest that geographic patterns of body size are caused both by adaptation within lineages, as invoked by Bergmann, and by taxonomic turnover among lineages. Taken together, these results indicate that while Bergmann's prediction based on physiological scaling is remarkably accurate, it is far from the full picture. Global patterns of body size in avian assemblages are driven by interactions between the physiological demands of the environment, resource availability, species richness and taxonomic turnover among lineages.

Evaluation of automated global mapping of Reference Soil Groups of WRB2015

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Caspari, Thomas; Kempen, Bas; Schad, Peter; Eberhardt, Einar; Ruiperez Gonzalez, Maria

2017-04-01

SoilGrids is an automated system that provides global predictions for standard numeric soil properties at seven standard depths down to 200 cm, currently at spatial resolutions of 1km and 250m. In addition, the system provides predictions of depth to bedrock and distribution of soil classes based on WRB and USDA Soil Taxonomy (ST). In SoilGrids250m(1), soil classes (WRB, version 2006) consist of the RSG and the first prefix qualifier, whereas in SoilGrids1km(2), the soil class was assessed at RSG level. Automated mapping of World Reference Base (WRB) Reference Soil Groups (RSGs) at a global level has great advantages. Maps can be updated in a short time span with relatively little effort when new data become available. To translate soil names of older versions of FAO/WRB and national classification systems of the source data into names according to WRB 2006, correlation tables are used in SoilGrids. Soil properties and classes are predicted independently from each other. This means that the combinations of soil properties for the same cells or soil property-soil class combinations do not necessarily yield logical combinations when the map layers are studied jointly. The model prediction procedure is robust and probably has a low source of error in the prediction of RSGs. It seems that the quality of the original soil classification in the data and the use of correlation tables are the largest sources of error in mapping the RSG distribution patterns. Predicted patterns of dominant RSGs were evaluated in selected areas and sources of error were identified. Suggestions are made for improvement of WRB2015 RSG distribution predictions in SoilGrids. Keywords: Automated global mapping; World Reference Base for Soil Resources; Data evaluation; Data quality assurance References 1 Hengl T, de Jesus JM, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, et al. (2016) SoilGrids250m: global gridded soil information based on Machine Learning. Earth System Science Data (ESSD), in review. 2 Hengl T, de Jesus JM, MacMillan RA, Batjes NH, Heuvelink GBM, et al. (2014) SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992. doi:10.1371/journal.pone.0105992

Analysis of climate change impact on rainfall pattern of Sambas district, West Kalimantan

NASA Astrophysics Data System (ADS)

Berliana Sipayung, Sinta; Nurlatifah, Amalia; Siswanto, Bambang; Slamet S, Lilik

2018-05-01

Climate change is one of the most important issues being discussed globally. It caused by global warming and indirectly affecting the world climate cycle. This research discussed the effect of climate change on rainfall pattern of Sambas District and predicted the future rainfall pattern due to climate change. CRU and TRMM were used and has been validated using in situ data. This research was used Climate Modelling and Prediction using CCAM (Conformal Cubic Atmospheric Model) which also validated by in situ data (correlation= 0.81). The results show that temperature trends in Sambas regency increased to 0.082°C/yr from 1991-2014 according to CRU data. High temperature trigger changes in rainfall patterns. Rainfall pattern in Sambas District has an equatorial type where the peak occurs when the sun is right on the equator. Rainfall in Sambas reaches the maximum in March and September when the equinox occurs. The CCAM model is used to project rainfall in Sambas District in the future. The model results show that rainfall in Sambas District is projected to increase to 0.018 mm/month until 2055 so the flow rate increase 0.006 m3/month and the water balance increase 0.009 mm/month.

CFD simulation of local and global mixing time in an agitated tank

NASA Astrophysics Data System (ADS)

Li, Liangchao; Xu, Bin

2017-01-01

The Issue of mixing efficiency in agitated tanks has drawn serious concern in many industrial processes. The turbulence model is very critical to predicting mixing process in agitated tanks. On the basis of computational fluid dynamics(CFD) software package Fluent 6.2, the mixing characteristics in a tank agitated by dual six-blade-Rushton-turbines(6-DT) are predicted using the detached eddy simulation(DES) method. A sliding mesh(SM) approach is adopted to solve the rotation of the impeller. The simulated flow patterns and liquid velocities in the agitated tank are verified by experimental data in the literature. The simulation results indicate that the DES method can obtain more flow details than Reynolds-averaged Navier-Stokes(RANS) model. Local and global mixing time in the agitated tank is predicted by solving a tracer concentration scalar transport equation. The simulated results show that feeding points have great influence on mixing process and mixing time. Mixing efficiency is the highest for the feeding point at location of midway of the two impellers. Two methods are used to determine global mixing time and get close result. Dimensionless global mixing time remains unchanged with increasing of impeller speed. Parallel, merging and diverging flow pattern form in the agitated tank, respectively, by changing the impeller spacing and clearance of lower impeller from the bottom of the tank. The global mixing time is the shortest for the merging flow, followed by diverging flow, and the longest for parallel flow. The research presents helpful references for design, optimization and scale-up of agitated tanks with multi-impeller.

Conceptualizing psychological processes in response to globalization: Components, antecedents, and consequences of global orientations.

PubMed

Chen, Sylvia Xiaohua; Lam, Ben C P; Hui, Bryant P H; Ng, Jacky C K; Mak, Winnie W S; Guan, Yanjun; Buchtel, Emma E; Tang, Willie C S; Lau, Victor C Y

2016-02-01

The influences of globalization have permeated various aspects of life in contemporary society, from technical innovations, economic development, and lifestyles, to communication patterns. The present research proposed a construct termed global orientation to denote individual differences in the psychological processes of acculturating to the globalizing world. It encompasses multicultural acquisition as a proactive response and ethnic protection as a defensive response to globalization. Ten studies examined the applicability of global orientations among majority and minority groups, including immigrants and sojourners, in multicultural and relatively monocultural contexts, and across Eastern and Western cultures. Multicultural acquisition is positively correlated with both independent and interdependent self-construals, bilingual proficiency and usage, and dual cultural identifications. Multicultural acquisition is promotion-focused, while ethnic protection is prevention-focused and related to acculturative stress. Global orientations affect individuating and modest behavior over and above multicultural ideology, predict overlap with outgroups over and above political orientation, and predict psychological adaptation, sociocultural competence, tolerance, and attitudes toward ethnocultural groups over and above acculturation expectations/strategies. Global orientations also predict English and Chinese oral presentation performance in multilevel analyses and the frequency and pleasantness of intercultural contact in cross-lagged panel models. We discuss how the psychological study of global orientations contributes to theory and research on acculturation, cultural identity, and intergroup relations. (c) 2016 APA, all rights reserved).

Variability in modeled cloud feedback tied to differences in the climatological spatial pattern of clouds

NASA Astrophysics Data System (ADS)

Siler, Nicholas; Po-Chedley, Stephen; Bretherton, Christopher S.

2018-02-01

Despite the increasing sophistication of climate models, the amount of surface warming expected from a doubling of atmospheric CO_2 (equilibrium climate sensitivity) remains stubbornly uncertain, in part because of differences in how models simulate the change in global albedo due to clouds (the shortwave cloud feedback). Here, model differences in the shortwave cloud feedback are found to be closely related to the spatial pattern of the cloud contribution to albedo (α) in simulations of the current climate: high-feedback models exhibit lower (higher) α in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global-mean α as temperatures rise and warm regions expand. The spatial pattern of α is found to be strongly predictive (r=0.84) of a model's global cloud feedback, with satellite observations indicating a most-likely value of 0.58± 0.31 Wm^{-2} K^{-1} (90% confidence). This estimate is higher than the model-average cloud feedback of 0.43 Wm^{-2} K^{-1}, with half the range of uncertainty. The observational constraint on climate sensitivity is weaker but still significant, suggesting a likely value of 3.68 ± 1.30 K (90% confidence), which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds between regions of warm and cool SSTs in simulations of the current climate.

Madden–Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer

PubMed Central

Miyakawa, Tomoki; Satoh, Masaki; Miura, Hiroaki; Tomita, Hirofumi; Yashiro, Hisashi; Noda, Akira T.; Yamada, Yohei; Kodama, Chihiro; Kimoto, Masahide; Yoneyama, Kunio

2014-01-01

Global cloud/cloud system-resolving models are perceived to perform well in the prediction of the Madden–Julian Oscillation (MJO), a huge eastward -propagating atmospheric pulse that dominates intraseasonal variation of the tropics and affects the entire globe. However, owing to model complexity, detailed analysis is limited by computational power. Here we carry out a simulation series using a recently developed supercomputer, which enables the statistical evaluation of the MJO prediction skill of a costly new-generation model in a manner similar to operational forecast models. We estimate the current MJO predictability of the model as 27 days by conducting simulations including all winter MJO cases identified during 2003–2012. The simulated precipitation patterns associated with different MJO phases compare well with observations. An MJO case captured in a recent intensive observation is also well reproduced. Our results reveal that the global cloud-resolving approach is effective in understanding the MJO and in providing month-long tropical forecasts. PMID:24801254

Madden-Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer.

PubMed

Miyakawa, Tomoki; Satoh, Masaki; Miura, Hiroaki; Tomita, Hirofumi; Yashiro, Hisashi; Noda, Akira T; Yamada, Yohei; Kodama, Chihiro; Kimoto, Masahide; Yoneyama, Kunio

2014-05-06

Global cloud/cloud system-resolving models are perceived to perform well in the prediction of the Madden-Julian Oscillation (MJO), a huge eastward -propagating atmospheric pulse that dominates intraseasonal variation of the tropics and affects the entire globe. However, owing to model complexity, detailed analysis is limited by computational power. Here we carry out a simulation series using a recently developed supercomputer, which enables the statistical evaluation of the MJO prediction skill of a costly new-generation model in a manner similar to operational forecast models. We estimate the current MJO predictability of the model as 27 days by conducting simulations including all winter MJO cases identified during 2003-2012. The simulated precipitation patterns associated with different MJO phases compare well with observations. An MJO case captured in a recent intensive observation is also well reproduced. Our results reveal that the global cloud-resolving approach is effective in understanding the MJO and in providing month-long tropical forecasts.

Multi-scale Predictability with a New Coupled Non-hydrostatic Global Model over the Arctic Annual Report

DTIC Science & Technology

2013-09-30

tropopause polar vortices, which are prevalent circulation features over the Arctic that play a major role in the evolution of surface pressure anomalies...pressure and tropospheric circulation anomalies and will allow us to answer specific questions regarding its ability to reproduce the appropriate AO... circulation patterns (Fig. 1c). While the mean patterns are favorable regarding the ability of MPAS to encapsulate the overall patterns of these two

Amino acid pair- and triplet-wise groupings in the interior of α-helical segments in proteins.

PubMed

de Sousa, Miguel M; Munteanu, Cristian R; Pazos, Alejandro; Fonseca, Nuno A; Camacho, Rui; Magalhães, A L

2011-02-21

A statistical approach has been applied to analyse primary structure patterns at inner positions of α-helices in proteins. A systematic survey was carried out in a recent sample of non-redundant proteins selected from the Protein Data Bank, which were used to analyse α-helix structures for amino acid pairing patterns. Only residues more than three positions apart from both termini of the α-helix were considered as inner. Amino acid pairings i, i+k (k=1, 2, 3, 4, 5), were analysed and the corresponding 20×20 matrices of relative global propensities were constructed. An analysis of (i, i+4, i+8) and (i, i+3, i+4) triplet patterns was also performed. These analysis yielded information on a series of amino acid patterns (pairings and triplets) showing either high or low preference for α-helical motifs and suggested a novel approach to protein alphabet reduction. In addition, it has been shown that the individual amino acid propensities are not enough to define the statistical distribution of these patterns. Global pair propensities also depend on the type of pattern, its composition and orientation in the protein sequence. The data presented should prove useful to obtain and refine useful predictive rules which can further the development and fine-tuning of protein structure prediction algorithms and tools. Copyright © 2010 Elsevier Ltd. All rights reserved.

An extreme climatic event alters marine ecosystem structure in a global biodiversity hotspot

NASA Astrophysics Data System (ADS)

Wernberg, Thomas; Smale, Dan A.; Tuya, Fernando; Thomsen, Mads S.; Langlois, Timothy J.; de Bettignies, Thibaut; Bennett, Scott; Rousseaux, Cecile S.

2013-01-01

Extreme climatic events, such as heat waves, are predicted to increase in frequency and magnitude as a consequence of global warming but their ecological effects are poorly understood, particularly in marine ecosystems. In early 2011, the marine ecosystems along the west coast of Australia--a global hotspot of biodiversity and endemism--experienced the highest-magnitude warming event on record. Sea temperatures soared to unprecedented levels and warming anomalies of 2-4°C persisted for more than ten weeks along >2,000km of coastline. We show that biodiversity patterns of temperate seaweeds, sessile invertebrates and demersal fish were significantly different after the warming event, which led to a reduction in the abundance of habitat-forming seaweeds and a subsequent shift in community structure towards a depauperate state and a tropicalization of fish communities. We conclude that extreme climatic events are key drivers of biodiversity patterns and that the frequency and intensity of such episodes have major implications for predictive models of species distribution and ecosystem structure, which are largely based on gradual warming trends.

Analysis of Changes in the Lorenz Energy Budget of the Atmosphere

NASA Astrophysics Data System (ADS)

Ellis, T. D.

2009-12-01

Several recent papers have addressed the topic of changes in global precipitation rates related to changes in Earth's global energy balance. Less studied are the processes that may be governing the large-scale regional distribution of precipitation around the globe. This study uses the energy budget partition paradigm first put forth by Lorenz (1955) and follows the methodology of Arpé et al. (1986) and Oriol (1982) to identify latitude bands where the partition of energy amongst zonal and eddy kinetic and potential energy bins may account for the spatial patterns of precipitation change predicted by many IPCC AR4 models. In doing so, this study may help to identify whether or not the climate change predicted by these models is indeed creating enhanced baroclinic storms in the mid-latitudes or if there are other mechanisms at work producing the patterns of precipitation change.

Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

PubMed

Wen, Tanya; Liu, De-Cyuan; Hsieh, Shulan

2018-06-01

Multitasking is a fundamental aspect of everyday life activities. To achieve a complex, multi-component goal, the tasks must be subdivided into sub-tasks and component steps, a critical function of prefrontal networks. The prefrontal cortex is considered to be organized in a cascade of executive processes from the sensorimotor to anterior prefrontal cortex, which includes execution of specific goal-directed action, to encoding and maintaining task rules, and finally monitoring distal goals. In the current study, we used a virtual multitasking paradigm to tap into real-world performance and relate it to each individual's resting-state functional connectivity in fMRI. While did not find any correlation between global connectivity of any of the major networks with multitasking ability, global connectivity of the lateral prefrontal cortex (LPFC) was predictive of multitasking ability. Further analysis showed that multivariate connectivity patterns within the sensorimotor network (SMN), and between-network connectivity of the frontoparietal network (FPN) and dorsal attention network (DAN), predicted individual multitasking ability and could be generalized to novel individuals. Together, these results support previous research that prefrontal networks underlie multitasking abilities and show that connectivity patterns in the cascade of prefrontal networks may explain individual differences in performance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Improving strand pairing prediction through exploring folding cooperativity

PubMed Central

Jeong, Jieun; Berman, Piotr; Przytycka, Teresa M.

2008-01-01

The topology of β-sheets is defined by the pattern of hydrogen-bonded strand pairing. Therefore, predicting hydrogen bonded strand partners is a fundamental step towards predicting β-sheet topology. At the same time, finding the correct partners is very difficult due to long range interactions involved in strand pairing. Additionally, patterns of aminoacids observed in β-sheet formations are very general and therefore difficult to use for computational recognition of specific contacts between strands. In this work, we report a new strand pairing algorithm. To address above mentioned difficulties, our algorithm attempts to mimic elements of the folding process. Namely, in addition to ensuring that the predicted hydrogen bonded strand pairs satisfy basic global consistency constraints, it takes into account hypothetical folding pathways. Consistently with this view, introducing hydrogen bonds between a pair of strands changes the probabilities of forming hydrogen bonds between other pairs of strand. We demonstrate that this approach provides an improvement over previously proposed algorithms. We also compare the performance of this method to that of a global optimization algorithm that poses the problem as integer linear programming optimization problem and solves it using ILOG CPLEX™ package. PMID:18989036

Predicting Global Fund grant disbursements for procurement of artemisinin-based combination therapies

PubMed Central

Cohen, Justin M; Singh, Inder; O'Brien, Megan E

2008-01-01

Background An accurate forecast of global demand is essential to stabilize the market for artemisinin-based combination therapy (ACT) and to ensure access to high-quality, life-saving medications at the lowest sustainable prices by avoiding underproduction and excessive overproduction, each of which can have negative consequences for the availability of affordable drugs. A robust forecast requires an understanding of the resources available to support procurement of these relatively expensive antimalarials, in particular from the Global Fund, at present the single largest source of ACT funding. Methods Predictive regression models estimating the timing and rate of disbursements from the Global Fund to recipient countries for each malaria grant were derived using a repeated split-sample procedure intended to avoid over-fitting. Predictions were compared against actual disbursements in a group of validation grants, and forecasts of ACT procurement extrapolated from disbursement predictions were evaluated against actual procurement in two sub-Saharan countries. Results Quarterly forecasts were correlated highly with actual smoothed disbursement rates (r = 0.987, p < 0.0001). Additionally, predicted ACT procurement, extrapolated from forecasted disbursements, was correlated strongly with actual ACT procurement supported by two grants from the Global Fund's first (r = 0.945, p < 0.0001) and fourth (r = 0.938, p < 0.0001) funding rounds. Conclusion This analysis derived predictive regression models that successfully forecasted disbursement patterning for individual Global Fund malaria grants. These results indicate the utility of this approach for demand forecasting of ACT and, potentially, for other commodities procured using funding from the Global Fund. Further validation using data from other countries in different regions and environments will be necessary to confirm its generalizability. PMID:18831742

Local control of globally competing patterns in coupled Swift-Hohenberg equations

NASA Astrophysics Data System (ADS)

Becker, Maximilian; Frenzel, Thomas; Niedermayer, Thomas; Reichelt, Sina; Mielke, Alexander; Bär, Markus

2018-04-01

We present analytical and numerical investigations of two anti-symmetrically coupled 1D Swift-Hohenberg equations (SHEs) with cubic nonlinearities. The SHE provides a generic formulation for pattern formation at a characteristic length scale. A linear stability analysis of the homogeneous state reveals a wave instability in addition to the usual Turing instability of uncoupled SHEs. We performed weakly nonlinear analysis in the vicinity of the codimension-two point of the Turing-wave instability, resulting in a set of coupled amplitude equations for the Turing pattern as well as left- and right-traveling waves. In particular, these complex Ginzburg-Landau-type equations predict two major things: there exists a parameter regime where multiple different patterns are stable with respect to each other and that the amplitudes of different patterns interact by local mutual suppression. In consequence, different patterns can coexist in distinct spatial regions, separated by localized interfaces. We identified specific mechanisms for controlling the position of these interfaces, which distinguish what kinds of patterns the interface connects and thus allow for global pattern selection. Extensive simulations of the original SHEs confirm our results.

Global patterns in post-dispersal seed removal by invertebrates and vertebrates.

PubMed

Peco, Begoña; Laffan, Shawn W; Moles, Angela T

2014-01-01

It is commonly accepted that species interactions such as granivory are more intense in the tropics. However, this has rarely been tested. A global dataset of post-dispersal seed removal by invertebrates and vertebrates for 79 native plant species from semi-natural and natural terrestrial habitats ranging from 55° N to 45° S, was compiled from the global literature to test the hypothesis that post-dispersal seed removal by invertebrates and vertebrates is more intense at lower latitudes. We also quantified the relationship between post-dispersal seed removal by vertebrates and by invertebrates to global climatic features including temperature, actual evapotranspiration (AET) and rainfall seasonality. Linear mixed effect models were applied to describe the relationships between seed removal and latitude, hemisphere and climatic variables controlling for the effect of seed mass. Post-dispersal seed removal by invertebrates was negatively related to latitude. In contrast, post-dispersal seed removal by vertebrates was positively but weakly related to latitude. Mean annual temperature and actual evapotranspiration were positively related to post-dispersal seed removal by invertebrates, but not to post-dispersal seed removal by vertebrates, which was only marginally negatively related to rainfall seasonality. The inclusion of seed mass improved the fit of all models, but the term for seed mass was not significant in any model. Although a good climatic model for predicting post-dispersal seed predation by vertebrates at the global level was not found, our results suggest different and opposite latitudinal patterns of post-dispersal seed removal by invertebrates vs vertebrates. This is the first time that a negative relationship between post-dispersal seed removal by invertebrates and latitude, and a positive relationship with temperature and AET have been documented at a global-scale. These results have important implications for understanding global patterns in plant-animal interactions, and the factors that shape plant reproductive ecology, and also for predicting how this plant-animal interaction might respond to climate change.

Global Patterns in Post-Dispersal Seed Removal by Invertebrates and Vertebrates

PubMed Central

Peco, Begoña; Laffan, Shawn W.; Moles, Angela T.

2014-01-01

It is commonly accepted that species interactions such as granivory are more intense in the tropics. However, this has rarely been tested. A global dataset of post-dispersal seed removal by invertebrates and vertebrates for 79 native plant species from semi-natural and natural terrestrial habitats ranging from 55° N to 45° S, was compiled from the global literature to test the hypothesis that post-dispersal seed removal by invertebrates and vertebrates is more intense at lower latitudes. We also quantified the relationship between post-dispersal seed removal by vertebrates and by invertebrates to global climatic features including temperature, actual evapotranspiration (AET) and rainfall seasonality. Linear mixed effect models were applied to describe the relationships between seed removal and latitude, hemisphere and climatic variables controlling for the effect of seed mass. Post-dispersal seed removal by invertebrates was negatively related to latitude. In contrast, post-dispersal seed removal by vertebrates was positively but weakly related to latitude. Mean annual temperature and actual evapotranspiration were positively related to post-dispersal seed removal by invertebrates, but not to post-dispersal seed removal by vertebrates, which was only marginally negatively related to rainfall seasonality. The inclusion of seed mass improved the fit of all models, but the term for seed mass was not significant in any model. Although a good climatic model for predicting post-dispersal seed predation by vertebrates at the global level was not found, our results suggest different and opposite latitudinal patterns of post-dispersal seed removal by invertebrates vs vertebrates. This is the first time that a negative relationship between post-dispersal seed removal by invertebrates and latitude, and a positive relationship with temperature and AET have been documented at a global-scale. These results have important implications for understanding global patterns in plant-animal interactions, and the factors that shape plant reproductive ecology, and also for predicting how this plant-animal interaction might respond to climate change. PMID:24618879

Prediction of Human Activity by Discovering Temporal Sequence Patterns.

PubMed

Li, Kang; Fu, Yun

2014-08-01

Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

Global patterns of evolutionary distinct and globally endangered amphibians and mammals.

PubMed

Safi, Kamran; Armour-Marshall, Katrina; Baillie, Jonathan E M; Isaac, Nick J B

2013-01-01

Conservation of phylogenetic diversity allows maximising evolutionary information preserved within fauna and flora. The "EDGE of Existence" programme is the first institutional conservation initiative that prioritises species based on phylogenetic information. Species are ranked in two ways: one according to their evolutionary distinctiveness (ED) and second, by including IUCN extinction status, their evolutionary distinctiveness and global endangerment (EDGE). Here, we describe the global patterns in the spatial distribution of priority ED and EDGE species, in order to identify conservation areas for mammalian and amphibian communities. In addition, we investigate whether environmental conditions can predict the observed spatial pattern in ED and EDGE globally. Priority zones with high concentrations of ED and EDGE scores were defined using two different methods. The overlap between mammal and amphibian zones was very small, reflecting the different phylo-biogeographic histories. Mammal ED zones were predominantly found on the African continent and the neotropical forests, whereas in amphibians, ED zones were concentrated in North America. Mammal EDGE zones were mainly in South-East Asia, southern Africa and Madagascar; for amphibians they were in central and south America. The spatial pattern of ED and EDGE was poorly described by a suite of environmental variables. Mapping the spatial distribution of ED and EDGE provides an important step towards identifying priority areas for the conservation of mammalian and amphibian phylogenetic diversity in the EDGE of existence programme.

Forest turnover rates follow global and regional patterns of productivity

USGS Publications Warehouse

Stephenson, N.L.; van Mantgem, P.J.

2005-01-01

Using a global database, we found that forest turnover rates (the average of tree mortality and recruitment rates) parallel broad-scale patterns of net primary productivity. First, forest turnover was higher in tropical than in temperate forests. Second, as recently demonstrated by others, Amazonian forest turnover was higher on fertile than infertile soils. Third, within temperate latitudes, turnover was highest in angiosperm forests, intermediate in mixed forests, and lowest in gymnosperm forests. Finally, within a single forest physiognomic type, turnover declined sharply with elevation (hence with temperature). These patterns of turnover in populations of trees are broadly similar to the patterns of turnover in populations of plant organs (leaves and roots) found in other studies. Our findings suggest a link between forest mass balance and the population dynamics of trees, and have implications for understanding and predicting the effects of environmental changes on forest structure and terrestrial carbon dynamics. ??2005 Blackwell Publishing Ltd/CNRS.

The Tara Oceans voyage reveals global diversity and distribution patterns of marine planktonic ciliates

PubMed Central

Gimmler, Anna; Korn, Ralf; de Vargas, Colomban; Audic, Stéphane; Stoeck, Thorsten

2016-01-01

Illumina reads of the SSU-rDNA-V9 region obtained from the circumglobal Tara Oceans expedition allow the investigation of protistan plankton diversity patterns on a global scale. We analyzed 6,137,350 V9-amplicons from ocean surface waters and the deep chlorophyll maximum, which were taxonomically assigned to the phylum Ciliophora. For open ocean samples global planktonic ciliate diversity is relatively low (ca. 1,300 observed and predicted ciliate OTUs). We found that 17% of all detected ciliate OTUs occurred in all oceanic regions under study. On average, local ciliate OTU richness represented 27% of the global ciliate OTU richness, indicating that a large proportion of ciliates is widely distributed. Yet, more than half of these OTUs shared <90% sequence similarity with reference sequences of described ciliates. While alpha-diversity measures (richness and exp(Shannon H)) are hardly affected by contemporary environmental conditions, species (OTU) turnover and community similarity (β-diversity) across taxonomic groups showed strong correlation to environmental parameters. Logistic regression models predicted significant correlations between the occurrence of specific ciliate genera and individual nutrients, the oceanic carbonate system and temperature. Planktonic ciliates displayed distinct vertical distributions relative to chlorophyll a. In contrast, the Tara Oceans dataset did not reveal any evidence that latitude is structuring ciliate communities. PMID:27633177

Global patterns in endemism explained by past climatic change.

PubMed

Jansson, Roland

2003-03-22

I propose that global patterns in numbers of range-restricted endemic species are caused by variation in the amplitude of climatic change occurring on time-scales of 10-100 thousand years (Milankovitch oscillations). The smaller the climatic shifts, the more probable it is that palaeoendemics survive and that diverging gene pools persist without going extinct or merging, favouring the evolution of neoendemics. Using the change in mean annual temperature since the last glacial maximum, estimated from global circulation models, I show that the higher the temperature change in an area, the fewer endemic species of mammals, birds, reptiles, amphibians and vascular plants it harbours. This relationship was robust to variation in area (for areas greater than 10(4) km2), latitudinal position, extent of former glaciation and whether or not areas are oceanic islands. Past climatic change was a better predictor of endemism than annual temperature range in all phylads except amphibians, suggesting that Rapoport's rule (i.e. species range sizes increase with latitude) is best explained by the increase in the amplitude of climatic oscillations towards the poles. Globally, endemic-rich areas are predicted to warm less in response to greenhouse-gas emissions, but the predicted warming would cause many habitats to disappear regionally, leading to species extinctions.

Advanced in-production hotspot prediction and monitoring with micro-topography

NASA Astrophysics Data System (ADS)

Fanton, P.; Hasan, T.; Lakcher, A.; Le-Gratiet, B.; Prentice, C.; Simiz, J.-G.; La Greca, R.; Depre, L.; Hunsche, S.

2017-03-01

At 28nm technology node and below, hot spot prediction and process window control across production wafers have become increasingly critical to prevent hotspots from becoming yield-limiting defects. We previously established proof of concept for a systematic approach to identify the most critical pattern locations, i.e. hotspots, in a reticle layout by computational lithography and combining process window characteristics of these patterns with across-wafer process variation data to predict where hotspots may become yield impacting defects [1,2]. The current paper establishes the impact of micro-topography on a 28nm metal layer, and its correlation with hotspot best focus variations across a production chip layout. Detailed topography measurements are obtained from an offline tool, and pattern-dependent best focus (BF) shifts are determined from litho simulations that include mask-3D effects. We also establish hotspot metrology and defect verification by SEM image contour extraction and contour analysis. This enables detection of catastrophic defects as well as quantitative characterization of pattern variability, i.e. local and global CD uniformity, across a wafer to establish hotspot defect and variability maps. Finally, we combine defect prediction and verification capabilities for process monitoring by on-product, guided hotspot metrology, i.e. with sampling locations being determined from the defect prediction model and achieved prediction accuracy (capture rate) around 75%

Global patterns and predictors of fish species richness in estuaries.

PubMed

Vasconcelos, Rita P; Henriques, Sofia; França, Susana; Pasquaud, Stéphanie; Cardoso, Inês; Laborde, Marina; Cabral, Henrique N

2015-09-01

1. Knowledge of global patterns of biodiversity and regulating variables is indispensable to develop predictive models. 2. The present study used predictive modelling approaches to investigate hypotheses that explain the variation in fish species richness between estuaries over a worldwide spatial extent. Ultimately, such models will allow assessment of future changes in ecosystem structure and function as a result of environmental changes. 3. A comprehensive worldwide data base was compiled of the fish assemblage composition and environmental characteristics of estuaries. Generalized Linear Models were used to quantify how variation in species richness among estuaries is related to historical events, energy dynamics and ecosystem characteristics, while controlling for sampling effects. 4. At the global extent, species richness differed among marine biogeographic realms and continents and increased with mean sea surface temperature, terrestrial net primary productivity and the stability of connectivity with a marine ecosystem (open vs. temporarily open estuaries). At a smaller extent (within a marine biogeographic realm or continent), other characteristics were also important in predicting variation in species richness, with species richness increasing with estuary area and continental shelf width. 5. The results suggest that species richness in an estuary is defined by predictors that are spatially hierarchical. Over the largest spatial extents, species richness is influenced by the broader distributions and habitat use patterns of marine and freshwater species that can colonize estuaries, which are in turn governed by history contingency, energy dynamics and productivity variables. Species richness is also influenced by more regional and local parameters that can further affect the process of community colonization in an estuary including the connectivity of the estuary with the adjacent marine habitat, and, over smaller spatial extents, the size of these habitats. In summary, patterns of species richness in estuaries across large spatial extents seem to reflect from global to local processes acting on community colonization. The importance of considering spatial extent, sampling effects and of combining history and contemporary environmental characteristics when exploring biodiversity is highlighted. © 2015 The Authors. Journal of Animal Ecology published by John Wiley & Sons on behalf of the British Ecological Society.

Multi-nutrient, multi-group model of present and future oceanic phytoplankton communities

NASA Astrophysics Data System (ADS)

Litchman, E.; Klausmeier, C. A.; Miller, J. R.; Schofield, O. M.; Falkowski, P. G.

2006-11-01

Phytoplankton community composition profoundly affects patterns of nutrient cycling and the dynamics of marine food webs; therefore predicting present and future phytoplankton community structure is crucial to understand how ocean ecosystems respond to physical forcing and nutrient limitations. We develop a mechanistic model of phytoplankton communities that includes multiple taxonomic groups (diatoms, coccolithophores and prasinophytes), nutrients (nitrate, ammonium, phosphate, silicate and iron), light, and a generalist zooplankton grazer. Each taxonomic group was parameterized based on an extensive literature survey. We test the model at two contrasting sites in the modern ocean, the North Atlantic (North Atlantic Bloom Experiment, NABE) and subarctic North Pacific (ocean station Papa, OSP). The model successfully predicts general patterns of community composition and succession at both sites: In the North Atlantic, the model predicts a spring diatom bloom, followed by coccolithophore and prasinophyte blooms later in the season. In the North Pacific, the model reproduces the low chlorophyll community dominated by prasinophytes and coccolithophores, with low total biomass variability and high nutrient concentrations throughout the year. Sensitivity analysis revealed that the identity of the most sensitive parameters and the range of acceptable parameters differed between the two sites. We then use the model to predict community reorganization under different global change scenarios: a later onset and extended duration of stratification, with shallower mixed layer depths due to increased greenhouse gas concentrations; increase in deep water nitrogen; decrease in deep water phosphorus and increase or decrease in iron concentration. To estimate uncertainty in our predictions, we used a Monte Carlo sampling of the parameter space where future scenarios were run using parameter combinations that produced acceptable modern day outcomes and the robustness of the predictions was determined. Change in the onset and duration of stratification altered the timing and the magnitude of the spring diatom bloom in the North Atlantic and increased total phytoplankton and zooplankton biomass in the North Pacific. Changes in nutrient concentrations in some cases changed dominance patterns of major groups, as well as total chlorophyll and zooplankton biomass. Based on these scenarios, our model suggests that global environmental change will inevitably alter phytoplankton community structure and potentially impact global biogeochemical cycles.

Remote Sensing and halocene Vegetation: History of Global Change

NASA Technical Reports Server (NTRS)

D'Antoni, Hector L.; Schaebitz, Frank

1995-01-01

Predictions of the future evolution of the earth's atmospheric chemistry and its impact on global circulation patterns are based on Global Climate Models (GCMs) that integrate the complex interactions of the biosphere, atmosphere and the oceans. Most of the available records of climate and environment are short-term records (from decades to a few hundred years) with convolved information of real trends and short-term fluctuations. GCMs must be tested beyond the short-term record of climate and environment to insure that predictions are based on trends and therefore are appropriate to support long term policy making. Unfortunately different parts of the world, weather stations are scattered, records extend over a period of only few years, and there are no systematic climate records for large portions of the globe.

Speciation gradients and the distribution of biodiversity.

PubMed

Schluter, Dolph; Pennell, Matthew W

2017-05-31

Global patterns of biodiversity are influenced by spatial and environmental variations in the rate at which new species form. We relate variations in speciation rates to six key patterns of biodiversity worldwide, including the species-area relationship, latitudinal gradients in species and genetic diversity, and between-habitat differences in species richness. Although they sometimes mirror biodiversity patterns, recent rates of speciation, at the tip of the tree of life, are often highest where species richness is low. Speciation gradients therefore shape, but are also shaped by, biodiversity gradients and are often more useful for predicting future patterns of biodiversity than for interpreting the past.

A Prominence Puzzle Explained?

NASA Astrophysics Data System (ADS)

Yeates, A. R.; Mackay, D. H.; van Ballegooijen, A. A.

2009-02-01

Long-standing observations reveal a global organisation of the magnetic field direction in solar prominences (aka filaments), large clouds of cool dense plasma suspended in the Sun's hot corona. However, theorists have thus far been unable to explain the origin of this hemispheric pattern. In particular, simple shearing by large-scale surface motions would appear to lead to the wrong magnetic field direction. To explain the observations, we have developed a new model of the global magnetic field evolution in the solar corona over six months. For the first time our model can follow the build-up of magnetic helicity and shear on a global scale, driven by flux emergence and surface motions. The model is successful in predicting the correct magnetic field direction in the vast majority of prominences tested, and has enabled us to determine the key physical mechanisms behind the mysterious hemispheric pattern.

Testing the skill of numerical hydraulic modeling to simulate spatiotemporal flooding patterns in the Logone floodplain, Cameroon

NASA Astrophysics Data System (ADS)

Fernández, Alfonso; Najafi, Mohammad Reza; Durand, Michael; Mark, Bryan G.; Moritz, Mark; Jung, Hahn Chul; Neal, Jeffrey; Shastry, Apoorva; Laborde, Sarah; Phang, Sui Chian; Hamilton, Ian M.; Xiao, Ningchuan

2016-08-01

Recent innovations in hydraulic modeling have enabled global simulation of rivers, including simulation of their coupled wetlands and floodplains. Accurate simulations of floodplains using these approaches may imply tremendous advances in global hydrologic studies and in biogeochemical cycling. One such innovation is to explicitly treat sub-grid channels within two-dimensional models, given only remotely sensed data in areas with limited data availability. However, predicting inundated area in floodplains using a sub-grid model has not been rigorously validated. In this study, we applied the LISFLOOD-FP hydraulic model using a sub-grid channel parameterization to simulate inundation dynamics on the Logone River floodplain, in northern Cameroon, from 2001 to 2007. Our goal was to determine whether floodplain dynamics could be simulated with sufficient accuracy to understand human and natural contributions to current and future inundation patterns. Model inputs in this data-sparse region include in situ river discharge, satellite-derived rainfall, and the shuttle radar topography mission (SRTM) floodplain elevation. We found that the model accurately simulated total floodplain inundation, with a Pearson correlation coefficient greater than 0.9, and RMSE less than 700 km2, compared to peak inundation greater than 6000 km2. Predicted discharge downstream of the floodplain matched measurements (Nash-Sutcliffe efficiency of 0.81), and indicated that net flow from the channel to the floodplain was modeled accurately. However, the spatial pattern of inundation was not well simulated, apparently due to uncertainties in SRTM elevations. We evaluated model results at 250, 500 and 1000-m spatial resolutions, and found that results are insensitive to spatial resolution. We also compared the model output against results from a run of LISFLOOD-FP in which the sub-grid channel parameterization was disabled, finding that the sub-grid parameterization simulated more realistic dynamics. These results suggest that analysis of global inundation is feasible using a sub-grid model, but that spatial patterns at sub-kilometer resolutions still need to be adequately predicted.

Shell Tectonics: A Mechanical Model for Strike-slip Displacement on Europa

NASA Technical Reports Server (NTRS)

Rhoden, Alyssa Rose; Wurman, Gilead; Huff, Eric M.; Manga, Michael; Hurford, Terry A.

2012-01-01

We introduce a new mechanical model for producing tidally-driven strike-slip displacement along preexisting faults on Europa, which we call shell tectonics. This model differs from previous models of strike-slip on icy satellites by incorporating a Coulomb failure criterion, approximating a viscoelastic rheology, determining the slip direction based on the gradient of the tidal shear stress rather than its sign, and quantitatively determining the net offset over many orbits. This model allows us to predict the direction of net displacement along faults and determine relative accumulation rate of displacement. To test the shell tectonics model, we generate global predictions of slip direction and compare them with the observed global pattern of strike-slip displacement on Europa in which left-lateral faults dominate far north of the equator, right-lateral faults dominate in the far south, and near-equatorial regions display a mixture of both types of faults. The shell tectonics model reproduces this global pattern. Incorporating a small obliquity into calculations of tidal stresses, which are used as inputs to the shell tectonics model, can also explain regional differences in strike-slip fault populations. We also discuss implications for fault azimuths, fault depth, and Europa's tectonic history.

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models

NASA Astrophysics Data System (ADS)

Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin

2010-09-01

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models.

PubMed

Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin

2010-09-01

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.

Prognosis for a sick planet.

PubMed

Maslin, Mark

2008-12-01

Global warming is the most important science issue of the 21st century, challenging the very structure of our global society. The study of past climate has shown that the current global climate system is extremely sensitive to human-induced climate change. The burning of fossil fuels since the beginning of the industrial revolution has already caused changes with clear evidence for a 0.75 degrees C rise in global temperatures and 22 cm rise in sea level during the 20th century. The Intergovernmental Panel on Climate Change synthesis report (2007) predicts that global temperatures by 2100 could rise by between 1.1 degrees C and 6.4 degrees C. Sea level could rise by between 28 cm and 79 cm, more if the melting of the polar ice caps accelerates. In addition, weather patterns will become less predictable and the occurrence of extreme climate events, such as storms, floods, heat waves and droughts, will increase. The potential effects of global warming on human society are devastating. We do, however, already have many of the technological solutions to cure our sick planet.

Generation of fluoroscopic 3D images with a respiratory motion model based on an external surrogate signal

NASA Astrophysics Data System (ADS)

Hurwitz, Martina; Williams, Christopher L.; Mishra, Pankaj; Rottmann, Joerg; Dhou, Salam; Wagar, Matthew; Mannarino, Edward G.; Mak, Raymond H.; Lewis, John H.

2015-01-01

Respiratory motion during radiotherapy can cause uncertainties in definition of the target volume and in estimation of the dose delivered to the target and healthy tissue. In this paper, we generate volumetric images of the internal patient anatomy during treatment using only the motion of a surrogate signal. Pre-treatment four-dimensional CT imaging is used to create a patient-specific model correlating internal respiratory motion with the trajectory of an external surrogate placed on the chest. The performance of this model is assessed with digital and physical phantoms reproducing measured irregular patient breathing patterns. Ten patient breathing patterns are incorporated in a digital phantom. For each patient breathing pattern, the model is used to generate images over the course of thirty seconds. The tumor position predicted by the model is compared to ground truth information from the digital phantom. Over the ten patient breathing patterns, the average absolute error in the tumor centroid position predicted by the motion model is 1.4 mm. The corresponding error for one patient breathing pattern implemented in an anthropomorphic physical phantom was 0.6 mm. The global voxel intensity error was used to compare the full image to the ground truth and demonstrates good agreement between predicted and true images. The model also generates accurate predictions for breathing patterns with irregular phases or amplitudes.

Symmetries and stability of chimera states in small, globally-coupled networks

NASA Astrophysics Data System (ADS)

Hart, Joseph D.; Bansal, Kanika; Murphy, Thomas E.; Roy, Rajarshi

It has recently been demonstrated that symmetries in a network's topology can help predict the patterns of synchronized clusters that can emerge in a network of coupled oscillators. This and related discoveries have led to increased interest in both network symmetries and cluster synchronization. In parallel with these discoveries, interest in chimera states-dynamical patterns in which a network separates into coherent and incoherent portions-has grown, and chimeras have now been observed in a variety of experimental systems. We present an opto-electronic experiment in which both chimera states and synchronized clusters are observed in a small, globally-coupled network. We show that the symmetries and sub-symmetries of the network permit the formation of the chimera and cluster states. A recently developed group theoretical approach enables us to predict the stability of the observed chimera and cluster states, and highlights the close relationship between chimera and cluster states as belonging to the broader phenomenon of partial synchronization.

True polar wander on Europa from global-scale small-circle depressions.

PubMed

Schenk, Paul; Matsuyama, Isamu; Nimmo, Francis

2008-05-15

The tectonic patterns and stress history of Europa are exceedingly complex and many large-scale features remain unexplained. True polar wander, involving reorientation of Europa's floating outer ice shell about the tidal axis with Jupiter, has been proposed as a possible explanation for some of the features. This mechanism is possible if the icy shell is latitudinally variable in thickness and decoupled from the rocky interior. It would impose high stress levels on the shell, leading to predictable fracture patterns. No satisfactory match to global-scale features has hitherto been found for polar wander stress patterns. Here we describe broad arcuate troughs and depressions on Europa that do not fit other proposed stress mechanisms in their current position. Using imaging from three spacecraft, we have mapped two global-scale organized concentric antipodal sets of arcuate troughs up to hundreds of kilometres long and 300 m to approximately 1.5 km deep. An excellent match to these features is found with stresses caused by an episode of approximately 80 degrees true polar wander. These depressions also appear to be geographically related to other large-scale bright and dark lineaments, suggesting that many of Europa's tectonic patterns may also be related to true polar wander.

Insights into the diurnal cycle of global Earth outgoing radiation using a numerical weather prediction model

NASA Astrophysics Data System (ADS)

Gristey, Jake J.; Chiu, J. Christine; Gurney, Robert J.; Morcrette, Cyril J.; Hill, Peter G.; Russell, Jacqueline E.; Brindley, Helen E.

2018-04-01

A globally complete, high temporal resolution and multiple-variable approach is employed to analyse the diurnal cycle of Earth's outgoing energy flows. This is made possible via the use of Met Office model output for September 2010 that is assessed alongside regional satellite observations throughout. Principal component analysis applied to the long-wave component of modelled outgoing radiation reveals dominant diurnal patterns related to land surface heating and convective cloud development, respectively explaining 68.5 and 16.0 % of the variance at the global scale. The total variance explained by these first two patterns is markedly less than previous regional estimates from observations, and this analysis suggests that around half of the difference relates to the lack of global coverage in the observations. The first pattern is strongly and simultaneously coupled to the land surface temperature diurnal variations. The second pattern is strongly coupled to the cloud water content and height diurnal variations, but lags the cloud variations by several hours. We suggest that the mechanism controlling the delay is a moistening of the upper troposphere due to the evaporation of anvil cloud. The short-wave component of modelled outgoing radiation, analysed in terms of albedo, exhibits a very dominant pattern explaining 88.4 % of the variance that is related to the angle of incoming solar radiation, and a second pattern explaining 6.7 % of the variance that is related to compensating effects from convective cloud development and marine stratocumulus cloud dissipation. Similar patterns are found in regional satellite observations, but with slightly different timings due to known model biases. The first pattern is controlled by changes in surface and cloud albedo, and Rayleigh and aerosol scattering. The second pattern is strongly coupled to the diurnal variations in both cloud water content and height in convective regions but only cloud water content in marine stratocumulus regions, with substantially shorter lag times compared with the long-wave counterpart. This indicates that the short-wave radiation response to diurnal cloud development and dissipation is more rapid, which is found to be robust in the regional satellite observations. These global, diurnal radiation patterns and their coupling with other geophysical variables demonstrate the process-level understanding that can be gained using this approach and highlight a need for global, diurnal observing systems for Earth outgoing radiation in the future.

Global resistance and resilience of primary production following extreme drought are predicted by mean annual precipitation

NASA Astrophysics Data System (ADS)

Stuart-Haëntjens, E. J.; De Boeck, H. J.; Lemoine, N. P.; Gough, C. M.; Kröel-Dulay, G.; Mänd, P.; Jentsch, A.; Schmidt, I. K.; Bahn, M.; Lloret, F.; Kreyling, J.; Wohlgemuth, T.; Stampfli, A.; Anderegg, W.; Classen, A. T.; Smith, M. D.

2017-12-01

Extreme drought is increasing globally in frequency and intensity, with uncertain consequences for the resistance and resilience of key ecosystem functions, including primary production. Primary production resistance, the capacity of an ecosystem to withstand change in primary production following extreme climate, and resilience, the degree to which primary production recovers, vary among and within ecosystem types, obscuring global patterns of resistance and resilience to extreme drought. Past syntheses on resistance have focused climatic gradients or individual ecosystem types, without assessing interactions between the two. Theory and many empirical studies suggest that forest production is more resistant but less resilient than grassland production to extreme drought, though some empirical studies reveal that these trends are not universal. Here, we conducted a global meta-analysis of sixty-four grassland and forest sites, finding that primary production resistance to extreme drought is predicted by a common continuum of mean annual precipitation (MAP). However, grasslands and forests exhibit divergent production resilience relationships with MAP. We discuss the likely mechanisms underlying the mixed production resistance and resilience patterns of forests and grasslands, including different plant species turnover times and drought adaptive strategies. These findings demonstrate the primary production responses of forests and grasslands to extreme drought are mixed, with far-reaching implications for Earth System Models, ecosystem management, and future studies of extreme drought resistance and resilience.

Emergent Global Patterns of Ecosystem Structure and Function from a Mechanistic General Ecosystem Model

PubMed Central

Emmott, Stephen; Hutton, Jon; Lyutsarev, Vassily; Smith, Matthew J.; Scharlemann, Jörn P. W.; Purves, Drew W.

2014-01-01

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures. PMID:24756001

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model.

PubMed

Harfoot, Michael B J; Newbold, Tim; Tittensor, Derek P; Emmott, Stephen; Hutton, Jon; Lyutsarev, Vassily; Smith, Matthew J; Scharlemann, Jörn P W; Purves, Drew W

2014-04-01

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures.

Predicting risky choices from brain activity patterns

PubMed Central

Helfinstein, Sarah M.; Schonberg, Tom; Congdon, Eliza; Karlsgodt, Katherine H.; Mumford, Jeanette A.; Sabb, Fred W.; Cannon, Tyrone D.; London, Edythe D.; Bilder, Robert M.; Poldrack, Russell A.

2014-01-01

Previous research has implicated a large network of brain regions in the processing of risk during decision making. However, it has not yet been determined if activity in these regions is predictive of choices on future risky decisions. Here, we examined functional MRI data from a large sample of healthy subjects performing a naturalistic risk-taking task and used a classification analysis approach to predict whether individuals would choose risky or safe options on upcoming trials. We were able to predict choice category successfully in 71.8% of cases. Searchlight analysis revealed a network of brain regions where activity patterns were reliably predictive of subsequent risk-taking behavior, including a number of regions known to play a role in control processes. Searchlights with significant predictive accuracy were primarily located in regions more active when preparing to avoid a risk than when preparing to engage in one, suggesting that risk taking may be due, in part, to a failure of the control systems necessary to initiate a safe choice. Additional analyses revealed that subject choice can be successfully predicted with minimal decrements in accuracy using highly condensed data, suggesting that information relevant for risky choice behavior is encoded in coarse global patterns of activation as well as within highly local activation within searchlights. PMID:24550270

Factors influencing export of dissolved inorganic nitrogen by major rivers: A new seasonal, global-scale model

EPA Science Inventory

Understanding sub-annual patterns of catchment dissolved inorganic nitrogen (DIN) export is critical for predicting and mitigating impacts of coastal eutrophication, such as algal blooms and hypoxic areas, which are often seasonal phenomena. We developed the first calibrated glob...

Predictability of North Atlantic Multidecadal Climate Variability

PubMed

Griffies; Bryan

1997-01-10

Atmospheric weather systems become unpredictable beyond a few weeks, but climate variations can be predictable over much longer periods because of the coupling of the ocean and atmosphere. With the use of a global coupled ocean-atmosphere model, it is shown that the North Atlantic may have climatic predictability on the order of a decade or longer. These results suggest that variations of the dominant multidecadal sea surface temperature patterns in the North Atlantic, which have been associated with changes in climate over Eurasia, can be predicted if an adequate and sustainable system for monitoring the Atlantic Ocean exists.

Patterns and controls of inter-annual variability in the terrestrial carbon budget

NASA Astrophysics Data System (ADS)

Marcolla, Barbara; Rödenbeck, Christian; Cescatti, Alessandro

2017-08-01

The terrestrial carbon fluxes show the largest variability among the components of the global carbon cycle and drive most of the temporal variations in the growth rate of atmospheric CO2. Understanding the environmental controls and trends of the terrestrial carbon budget is therefore essential to predict the future trajectories of the CO2 airborne fraction and atmospheric concentrations. In the present work, patterns and controls of the inter-annual variability (IAV) of carbon net ecosystem exchange (NEE) have been analysed using three different data streams: ecosystem-level observations from the FLUXNET database (La Thuile and 2015 releases), the MPI-MTE (model tree ensemble) bottom-up product resulting from the global upscaling of site-level fluxes, and the Jena CarboScope Inversion, a top-down estimate of surface fluxes obtained from observed CO2 concentrations and an atmospheric transport model. Consistencies and discrepancies in the temporal and spatial patterns and in the climatic and physiological controls of IAV were investigated between the three data sources. Results show that the global average of IAV at FLUXNET sites, quantified as the standard deviation of annual NEE, peaks in arid ecosystems and amounts to ˜ 120 gC m-2 y-1, almost 6 times more than the values calculated from the two global products (15 and 20 gC m-2 y-1 for MPI-MTE and the Jena Inversion, respectively). Most of the temporal variability observed in the last three decades of the MPI-MTE and Jena Inversion products is due to yearly anomalies, whereas the temporal trends explain only about 15 and 20 % of the variability, respectively. Both at the site level and on a global scale, the IAV of NEE is driven by the gross primary productivity and in particular by the cumulative carbon flux during the months when land acts as a sink. Altogether these results offer a broad view on the magnitude, spatial patterns and environmental drivers of IAV from a variety of data sources that can be instrumental to improve our understanding of the terrestrial carbon budget and to validate the predictions of land surface models.

Plant diversity predicts beta but not alpha diversity of soil microbes across grasslands worldwide

USGS Publications Warehouse

Prober, Suzanne M.; Leff, Jonathan W.; Bates, Scott T.; Borer, Elizabeth T.; Firn, Jennifer; Harpole, W. Stanley; Lind, Eric M.; Seabloom, Eric W.; Adler, Peter B.; Bakker, Jonathan D.; Cleland, Elsa E.; DeCrappeo, Nicole; DeLorenze, Elizabeth; Hagenah, Nicole; Hautier, Yann; Hofmockel, Kirsten S.; Kirkman, Kevin P.; Knops, Johannes M. H.; La Pierre, Kimberly J.; MacDougall, Andrew S.; McCulley, Rebecca L.; Mitchell, Charles E.; Risch, Anita C.; Schuetz, Martin; Stevens, Carly J.; Williams, Ryan J.; Fierer, Noah

2015-01-01

Aboveground–belowground interactions exert critical controls on the composition and function of terrestrial ecosystems, yet the fundamental relationships between plant diversity and soil microbial diversity remain elusive. Theory predicts predominantly positive associations but tests within single sites have shown variable relationships, and associations between plant and microbial diversity across broad spatial scales remain largely unexplored. We compared the diversity of plant, bacterial, archaeal and fungal communities in one hundred and forty-five 1 m2 plots across 25 temperate grassland sites from four continents. Across sites, the plant alpha diversity patterns were poorly related to those observed for any soil microbial group. However, plant beta diversity (compositional dissimilarity between sites) was significantly correlated with the beta diversity of bacterial and fungal communities, even after controlling for environmental factors. Thus, across a global range of temperate grasslands, plant diversity can predict patterns in the composition of soil microbial communities, but not patterns in alpha diversity.

Identifying sensitive ranges in global warming precipitation change dependence on convective parameters

DOE PAGES

Bernstein, Diana N.; Neelin, J. David

2016-04-28

A branch-run perturbed-physics ensemble in the Community Earth System Model estimates impacts of parameters in the deep convection scheme on current hydroclimate and on end-of-century precipitation change projections under global warming. Regional precipitation change patterns prove highly sensitive to these parameters, especially in the tropics with local changes exceeding 3mm/d, comparable to the magnitude of the predicted change and to differences in global warming predictions among the Coupled Model Intercomparison Project phase 5 models. This sensitivity is distributed nonlinearly across the feasible parameter range, notably in the low-entrainment range of the parameter for turbulent entrainment in the deep convection scheme.more » This suggests that a useful target for parameter sensitivity studies is to identify such disproportionately sensitive dangerous ranges. Here, the low-entrainment range is used to illustrate the reduction in global warming regional precipitation sensitivity that could occur if this dangerous range can be excluded based on evidence from current climate.« less

Identifying sensitive ranges in global warming precipitation change dependence on convective parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernstein, Diana N.; Neelin, J. David

A branch-run perturbed-physics ensemble in the Community Earth System Model estimates impacts of parameters in the deep convection scheme on current hydroclimate and on end-of-century precipitation change projections under global warming. Regional precipitation change patterns prove highly sensitive to these parameters, especially in the tropics with local changes exceeding 3mm/d, comparable to the magnitude of the predicted change and to differences in global warming predictions among the Coupled Model Intercomparison Project phase 5 models. This sensitivity is distributed nonlinearly across the feasible parameter range, notably in the low-entrainment range of the parameter for turbulent entrainment in the deep convection scheme.more » This suggests that a useful target for parameter sensitivity studies is to identify such disproportionately sensitive dangerous ranges. Here, the low-entrainment range is used to illustrate the reduction in global warming regional precipitation sensitivity that could occur if this dangerous range can be excluded based on evidence from current climate.« less

Examining the last few decades of global hydroclimate for evidence of anthropogenic change amidst natural variability

NASA Astrophysics Data System (ADS)

Seager, R.; Naik, N.; Ting, M.; Kushnir, Y.; Kelley, C. P.

2011-12-01

Climate models robustly predict that the deep tropics and mid-latitude-to-subpolar regions will moisten, and the subtropical dry zones both dry and expand, as a consequence of global warming driven by rising greenhouse gases. The models also predict that this transition to a more extreme climatological mean global hydroclimate should already be underway. Given the importance of these predictions it is an imperative that the climate science community assess whether there is evidence within the observational record that they are correct. This task is made difficult by the tremendous natural variability of the hydrological cycle on seasonal to multidecadal timescales. Here we will use instrumental observations, reanalyses, sea surface temperature forced atmosphere models and coupled model simulations, and a variety of methodologies, to attempt to separate global radiatively-forced hydroclimate change from ongoing natural variability. The results will be applied to explain trends and recent events in key regions such as Mexico, the United States and the Mediterranean. It is concluded that the signal of anthropogenic change is small compared to the amplitude of natural variability but that it is a discernible contributor. Globally the evidence reveals that radiatively-forced hydroclimate change is occurring with an amplitude and spatial pattern largely consistent with the predictions by IPCC AR4 models of hydroclimate change to date. However it will also be shown that the radiatively-forced component does not in and of itself provide a useful prediction of near term hydroclimate change because for many regions the amplitude of natural decadal variability is as large or larger. Useful predictions need to account for how natural variability may evolve as well as forced change.

Evaluating the utility of mid-infrared spectral subspaces for predicting soil properties.

PubMed

Sila, Andrew M; Shepherd, Keith D; Pokhariyal, Ganesh P

2016-04-15

We propose four methods for finding local subspaces in large spectral libraries. The proposed four methods include (a) cosine angle spectral matching; (b) hit quality index spectral matching; (c) self-organizing maps and (d) archetypal analysis methods. Then evaluate prediction accuracies for global and subspaces calibration models. These methods were tested on a mid-infrared spectral library containing 1907 soil samples collected from 19 different countries under the Africa Soil Information Service project. Calibration models for pH, Mehlich-3 Ca, Mehlich-3 Al, total carbon and clay soil properties were developed for the whole library and for the subspace. Root mean square error of prediction was used to evaluate predictive performance of subspace and global models. The root mean square error of prediction was computed using a one-third-holdout validation set. Effect of pretreating spectra with different methods was tested for 1st and 2nd derivative Savitzky-Golay algorithm, multiplicative scatter correction, standard normal variate and standard normal variate followed by detrending methods. In summary, the results show that global models outperformed the subspace models. We, therefore, conclude that global models are more accurate than the local models except in few cases. For instance, sand and clay root mean square error values from local models from archetypal analysis method were 50% poorer than the global models except for subspace models obtained using multiplicative scatter corrected spectra with which were 12% better. However, the subspace approach provides novel methods for discovering data pattern that may exist in large spectral libraries.

Self-organized criticality in forest-landscape evolution

Treesearch

J.C. Sprott; Janine Bolliger; David J. Mladenoff

2002-01-01

A simple cellular automaton replicates the fractal pattern of a natural forest landscape and predicts its evolution. Spatial distributions and temporal fluctuations in global quantities show power-law spectra, implying scale-invariance, characteristic of self-organized criticality. The evolution toward the SOC state and the robustness of that state to perturbations...

Avifauna response to hurricanes: regional changes in community similarity

Treesearch

Chadwick D. Rittenhouse; Anna M. Pidgeon; Thomas P. Albright; Patrick D. Culbert; Murray K. Clayton; Curtis H. Flather; Chengquan Huang; Jeffrey G. Masek; Volker C. Radeloff

2010-01-01

Global climate models predict increases in the frequency and intensity of extreme climatic events such as hurricanes, which may abruptly alter ecological processes in forests and thus affect avian diversity. Developing appropriate conservation measures necessitates identifying patterns of avifauna response to hurricanes. We sought to answer two questions: (1) does...

Environmental interactions that influence secondary metabolism and development in the saprophytic crop pathogen Aspergillus flavus

USDA-ARS?s Scientific Manuscript database

Aspergillus flavus is a pathogenic and opportunistic fungus that can infect several crops of agricultural importance and has the potential to produce carcinogenic mycotoxins such as aflatoxin. Predicted changes in global temperatures, precipitation patterns and carbon dioxide levels are expected to ...

Predictable patterns of the May-June rainfall anomaly over East Asia

NASA Astrophysics Data System (ADS)

Xing, Wen; Wang, Bin; Yim, So-Young; Ha, Kyung-Ja

2017-02-01

During early summer (May-June, MJ), East Asia (EA) subtropical front is a defining feature of Asian monsoon, which produces the most prominent precipitation band in the global subtropics. Here we show that dynamical prediction of early summer EA (20°N-45°N, 100°E-130°E) rainfall made by four coupled climate models' ensemble hindcast (1979-2010) yields only a moderate skill and cannot be used to estimate predictability. The present study uses an alternative, empirical orthogonal function (EOF)-based physical-empirical (P-E) model approach to predict rainfall anomaly pattern and estimate its potential predictability. The first three leading modes are physically meaningful and can be, respectively, attributed to (a) the interaction between the anomalous western North Pacific subtropical high and underlying Indo-Pacific warm ocean, (b) the forcing associated with North Pacific sea surface temperature (SST) anomaly, and (c) the development of equatorial central Pacific SST anomalies. A suite of P-E models is established to forecast the first three leading principal components. All predictors are 0 month ahead of May, so the prediction here is named as a 0 month lead prediction. The cross-validated hindcast results demonstrate that these modes may be predicted with significant temporal correlation skills (0.48-0.72). Using the predicted principal components and the corresponding EOF patterns, the total MJ rainfall anomaly was hindcasted for the period of 1979-2015. The time-mean pattern correlation coefficient (PCC) score reaches 0.38, which is significantly higher than dynamical models' multimodel ensemble skill (0.21). The estimated potential maximum attainable PCC is around 0.65, suggesting that the dynamical prediction models may have large rooms to improve. Limitations and future work are discussed.

Strike-Slip Fault Patterns on Europa: Obliquity or Polar Wander?

NASA Technical Reports Server (NTRS)

Rhoden, Alyssa Rose; Hurford, Terry A.; Manga, Michael

2011-01-01

Variations in diurnal tidal stress due to Europa's eccentric orbit have been considered as the driver of strike-slip motion along pre-existing faults, but obliquity and physical libration have not been taken into account. The first objective of this work is to examine the effects of obliquity on the predicted global pattern of fault slip directions based on a tidal-tectonic formation model. Our second objective is to test the hypothesis that incorporating obliquity can reconcile theory and observations without requiring polar wander, which was previously invoked to explain the mismatch found between the slip directions of 192 faults on Europa and the global pattern predicted using the eccentricity-only model. We compute predictions for individual, observed faults at their current latitude, longitude, and azimuth with four different tidal models: eccentricity only, eccentricity plus obliquity, eccentricity plus physical libration, and a combination of all three effects. We then determine whether longitude migration, presumably due to non-synchronous rotation, is indicated in observed faults by repeating the comparisons with and without obliquity, this time also allowing longitude translation. We find that a tidal model including an obliquity of 1.2?, along with longitude migration, can predict the slip directions of all observed features in the survey. However, all but four faults can be fit with only 1? of obliquity so the value we find may represent the maximum departure from a lower time-averaged obliquity value. Adding physical libration to the obliquity model improves the accuracy of predictions at the current locations of the faults, but fails to predict the slip directions of six faults and requires additional degrees of freedom. The obliquity model with longitude migration is therefore our preferred model. Although the polar wander interpretation cannot be ruled out from these results alone, the obliquity model accounts for all observations with a value consistent with theoretical expectations and cycloid modeling.

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

NASA Technical Reports Server (NTRS)

Potter, C. S.

1997-01-01

This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

Winter Precipitation Forecast in the European and Mediterranean Regions Using Cluster Analysis

NASA Astrophysics Data System (ADS)

Totz, Sonja; Tziperman, Eli; Coumou, Dim; Pfeiffer, Karl; Cohen, Judah

2017-12-01

The European climate is changing under global warming, and especially the Mediterranean region has been identified as a hot spot for climate change with climate models projecting a reduction in winter rainfall and a very pronounced increase in summertime heat waves. These trends are already detectable over the historic period. Hence, it is beneficial to forecast seasonal droughts well in advance so that water managers and stakeholders can prepare to mitigate deleterious impacts. We developed a new cluster-based empirical forecast method to predict precipitation anomalies in winter. This algorithm considers not only the strength but also the pattern of the precursors. We compare our algorithm with dynamic forecast models and a canonical correlation analysis-based prediction method demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2.

PubMed

Lemey, Philippe; Rambaut, Andrew; Bedford, Trevor; Faria, Nuno; Bielejec, Filip; Baele, Guy; Russell, Colin A; Smith, Derek J; Pybus, Oliver G; Brockmann, Dirk; Suchard, Marc A

2014-02-01

Information on global human movement patterns is central to spatial epidemiological models used to predict the behavior of influenza and other infectious diseases. Yet it remains difficult to test which modes of dispersal drive pathogen spread at various geographic scales using standard epidemiological data alone. Evolutionary analyses of pathogen genome sequences increasingly provide insights into the spatial dynamics of influenza viruses, but to date they have largely neglected the wealth of information on human mobility, mainly because no statistical framework exists within which viral gene sequences and empirical data on host movement can be combined. Here, we address this problem by applying a phylogeographic approach to elucidate the global spread of human influenza subtype H3N2 and assess its ability to predict the spatial spread of human influenza A viruses worldwide. Using a framework that estimates the migration history of human influenza while simultaneously testing and quantifying a range of potential predictive variables of spatial spread, we show that the global dynamics of influenza H3N2 are driven by air passenger flows, whereas at more local scales spread is also determined by processes that correlate with geographic distance. Our analyses further confirm a central role for mainland China and Southeast Asia in maintaining a source population for global influenza diversity. By comparing model output with the known pandemic expansion of H1N1 during 2009, we demonstrate that predictions of influenza spatial spread are most accurate when data on human mobility and viral evolution are integrated. In conclusion, the global dynamics of influenza viruses are best explained by combining human mobility data with the spatial information inherent in sampled viral genomes. The integrated approach introduced here offers great potential for epidemiological surveillance through phylogeographic reconstructions and for improving predictive models of disease control.

Peak oil and health in low- and middle-income countries: impacts and potential responses.

PubMed

Winch, Peter; Stepnitz, Rebecca

2011-09-01

Peak oil refers to the predicted peak and subsequent decline in global production of petroleum products over the coming decades. We describe how peak oil will affect health, nutrition, and health systems in low- and middle-income countries along 5 pathways. The negative effects of peak oil on health and nutrition will be felt most acutely in the 58 low-income countries experiencing minimal or negative economic growth because of their patterns of sociopolitical, geographic, and economic vulnerability. The global health community needs to take additional steps to build resilience among the residents of low- and middle-income countries and maintain access to maternal and other health services in the face of predicted changes in availability and price of fossil fuels.

Mapping the global depth to bedrock for land surface modelling

NASA Astrophysics Data System (ADS)

Shangguan, W.; Hengl, T.; Yuan, H.; Dai, Y. J.; Zhang, S.

2017-12-01

Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of Depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 130,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surfacee reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forests and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.

Mapping the global depth to bedrock for land surface modeling

NASA Astrophysics Data System (ADS)

Shangguan, Wei; Hengl, Tomislav; Mendes de Jesus, Jorge; Yuan, Hua; Dai, Yongjiu

2017-03-01

Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 1,30,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surface reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forest and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250 m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.

Globally invasive, withdrawing at home: Aedes albopictus and Aedes japonicus facing the rise of Aedes flavopictus

NASA Astrophysics Data System (ADS)

Chaves, Luis Fernando

2016-11-01

It has been suggested that climate change may have facilitated the global expansion of invasive disease vectors, since several species have expanded their range as temperatures have warmed. Here, we present results from observations on two major global invasive mosquito vectors (Diptera: Culicidae), Aedes albopictus (Skuse) and Aedes japonicus (Theobald), across the altitudinal range of Mt. Konpira, Nagasaki, Japan, a location within their native range, where Aedes flavopictus Yamada, formerly a rare species, has now become dominant. Spatial abundance patterns of the three species suggest that temperature is an important factor influencing their adult distribution across the altitudinal range of Mt. Konpira. Temporal abundance patterns, by contrast, were associated with rainfall and showed signals of density-dependent regulation in the three species. The spatial and temporal analysis of abundance patterns showed that Ae. flavopictus and Ae. albopictus were negatively associated, even when accounting for differential impacts of weather and other environmental factors in their co-occurrence patterns. Our results highlight a contingency in the expansion of invasive vectors, the potential emergence of changes in their interactions with species in their native communities, and raise the question of whether these changes might be useful to predict the emergence of future invasive vectors.

On global gravity anomalies and two-scale mantle convection

NASA Technical Reports Server (NTRS)

Marsh, B. D.; Marsh, J. G.

1976-01-01

The two-scale model of mantle convection developed by Richter and Parsons (1975) predicts that if the depth of the convective layer is about 600 km, then for a plate moving at 10 cm/yr, longitudinal convective rolls will be produced in about 50 million years, and the strike of these rolls indicates the direction of motion of the plate relative to the upper mantle. The paper tests these predictions by examining a new global free air gravity model complete to the 30th degree and order. The free air gravity map developed shows a series of linear positive and negative anomalies (with transverse wavelengths of about 2000 km) spanning the Pacific Ocean, crossing the Pacific rise and striking parallel to the Hawaiian seamounts. It is suggested that the pattern of these anomalies may indicate the presence of longitudinal convective rolls beneath the Pacific plates, a result which tends to support the predictions of Richter and Parsons.

Global Symmetries of Naive and Staggered Fermions in Arbitrary Dimensions

NASA Astrophysics Data System (ADS)

Kieburg, Mario; Würfel, Tim R.

2018-03-01

It is well-known that staggered fermions do not necessarily satisfy the same global symmetries as the continuum theory. We analyze the mechanism behind this phenomenon for arbitrary dimension and gauge group representation. For this purpose we vary the number of lattice sites between even and odd parity in each single direction. Since the global symmetries are manifest in the lowest eigenvalues of the Dirac operator, the spectral statistics and also the symmetry breaking pattern will be affected. We analyze these effects and compare our predictions with Monte-Carlo simulations of naive Dirac operators in the strong coupling limit. This proceeding is a summary of our work [1].

Global Seasonality of Rotavirus Disease

PubMed Central

Patel, Manish M.; Pitzer, Virginia; Alonso, Wladimir J.; Vera, David; Lopman, Ben; Tate, Jacqueline; Viboud, Cecile; Parashar, Umesh D.

2012-01-01

Background A substantial number of surveillance studies have documented rotavirus prevalence among children admitted for dehydrating diarrhea. We sought to establish global seasonal patterns of rotavirus disease before widespread vaccine introduction. Methods We reviewed studies of rotavirus detection in children with diarrhea published since 1995. We assessed potential relationships between seasonal prevalence and locality by plotting the average monthly proportion of diarrhea cases positive for rotavirus according to geography, country development, and latitude. We used linear regression to identify variables that were potentially associated with the seasonal intensity of rotavirus. Results Among a total of 99 studies representing all six geographical regions of the world, patterns of year-round disease were more evident in low- and low-middle income countries compared with upper-middle and high income countries where disease was more likely to be seasonal. The level of country development was a stronger predictor of strength of seasonality (P=0.001) than geographical location or climate. However, the observation of distinctly different seasonal patterns of rotavirus disease in some countries with similar geographical location, climate and level of development indicate that a single unifying explanation for variation in seasonality of rotavirus disease is unlikely. Conclusion While no unifying explanation emerged for varying rotavirus seasonality globally, the country income level was somewhat more predictive of the likelihood of having seasonal disease than other factors. Future evaluation of the effect of rotavirus vaccination on seasonal patterns of disease in different settings may help understand factors that drive the global seasonality of rotavirus disease. PMID:23190782

A hydroclimatic model of global fire patterns

NASA Astrophysics Data System (ADS)

Boer, Matthias

2015-04-01

Satellite-based earth observation is providing an increasingly accurate picture of global fire patterns. The highest fire activity is observed in seasonally dry (sub-)tropical environments of South America, Africa and Australia, but fires occur with varying frequency, intensity and seasonality in almost all biomes on Earth. The particular combination of these fire characteristics, or fire regime, is known to emerge from the combined influences of climate, vegetation, terrain and land use, but has so far proven difficult to reproduce by global models. Uncertainty about the biophysical drivers and constraints that underlie current global fire patterns is propagated in model predictions of how ecosystems, fire regimes and biogeochemical cycles may respond to projected future climates. Here, I present a hydroclimatic model of global fire patterns that predicts the mean annual burned area fraction (F) of 0.25° x 0.25° grid cells as a function of the climatic water balance. Following Bradstock's four-switch model, long-term fire activity levels were assumed to be controlled by fuel productivity rates and the likelihood that the extant fuel is dry enough to burn. The frequency of ignitions and favourable fire weather were assumed to be non-limiting at long time scales. Fundamentally, fuel productivity and fuel dryness are a function of the local water and energy budgets available for the production and desiccation of plant biomass. The climatic water balance summarizes the simultaneous availability of biologically usable energy and water at a site, and may therefore be expected to explain a significant proportion of global variation in F. To capture the effect of the climatic water balance on fire activity I focused on the upper quantiles of F, i.e. the maximum level of fire activity for a given climatic water balance. Analysing GFED4 data for annual burned area together with gridded climate data, I found that nearly 80% of the global variation in the 0.99 quantile of F (i.e. F_0.99 ) was explained by two terms of the climatic water balance: i) mean annual actual evapotranspiration (AET), which is a proxy for fuel productivity, and ii) mean annual water deficit (D=PET-AET, where PET is mean annual potential evapotranspiration), which is a measure of fuel drying potential. As expected, F_0.99 was close to zero in environments of low AET (e.g. deserts) or low D (e.g. wet forests), due to strong fuel productivity or fuel dryness constraints, and maximum for environments of intermediate AET and D (e.g. tropical savannas). The topography of the F_0.99 response surface was analysed to explore how the relative importance of fuel productivity and fuel dryness constraints varied with the climatic water balance, and geographically across the continents. Consistent with current understanding of global pyrogeography, the hydroclimatic fire model predicted that fire activity is mostly constrained by fuel productivity in arid environments with grassy fuels and by fuel dryness in humid environments with litter fuels derived from woody shrubs and trees. The model provides a simple, yet biophysically-based, approach to evaluating potential for incremental change in fire activity or transformational change in fire types under future climate conditions.

Using dendrometer and dendroclimatology data to predict the growth response of Douglas-fir to climate change in the Pacific Northwest, USA

EPA Science Inventory

Altered seasonal climate patterns towards hotter, drier summers through the 21st century resulting from global climate change could affect the growth of coniferous forests in the Pacific Northwest (PNW) region of North America. The seasonal effects of temperature, precipitation,...

Geophysical imaging of watershed subsurface patterns and prediction of soil texture and water holding capacity

USDA-ARS?s Scientific Manuscript database

The extent to which soil resource availability, nutrients or moisture, contro1 the structure, function and diversity of plant communities has aroused considerableinterest in the past decade, and remains topical in light of global change. Numerous plant communities are controlled either by water or s...

Predicting Plausible Impacts of Sets of Climate and Land Use Change Scenario on Water Resources

EPA Science Inventory

As the new decade ushers in, there will be new challenges. The world’s population is increasing and the land use patterns are changing. Inevitably with these global changes, there will be various environmental consequences. For example, our water resources, both in terms of qu...

Local Patterns to Global Architectures: Influences of Network Topology on Human Learning.

PubMed

Karuza, Elisabeth A; Thompson-Schill, Sharon L; Bassett, Danielle S

2016-08-01

A core question in cognitive science concerns how humans acquire and represent knowledge about their environments. To this end, quantitative theories of learning processes have been formalized in an attempt to explain and predict changes in brain and behavior. We connect here statistical learning approaches in cognitive science, which are rooted in the sensitivity of learners to local distributional regularities, and network science approaches to characterizing global patterns and their emergent properties. We focus on innovative work that describes how learning is influenced by the topological properties underlying sensory input. The confluence of these theoretical approaches and this recent empirical evidence motivate the importance of scaling-up quantitative approaches to learning at both the behavioral and neural levels. Copyright © 2016 Elsevier Ltd. All rights reserved.

Higher predation risk for insect prey at low latitudes and elevations.

PubMed

Roslin, Tomas; Hardwick, Bess; Novotny, Vojtech; Petry, William K; Andrew, Nigel R; Asmus, Ashley; Barrio, Isabel C; Basset, Yves; Boesing, Andrea Larissa; Bonebrake, Timothy C; Cameron, Erin K; Dáttilo, Wesley; Donoso, David A; Drozd, Pavel; Gray, Claudia L; Hik, David S; Hill, Sarah J; Hopkins, Tapani; Huang, Shuyin; Koane, Bonny; Laird-Hopkins, Benita; Laukkanen, Liisa; Lewis, Owen T; Milne, Sol; Mwesige, Isaiah; Nakamura, Akihiro; Nell, Colleen S; Nichols, Elizabeth; Prokurat, Alena; Sam, Katerina; Schmidt, Niels M; Slade, Alison; Slade, Victor; Suchanková, Alžběta; Teder, Tiit; van Nouhuys, Saskya; Vandvik, Vigdis; Weissflog, Anita; Zhukovich, Vital; Slade, Eleanor M

2017-05-19

Biotic interactions underlie ecosystem structure and function, but predicting interaction outcomes is difficult. We tested the hypothesis that biotic interaction strength increases toward the equator, using a global experiment with model caterpillars to measure predation risk. Across an 11,660-kilometer latitudinal gradient spanning six continents, we found increasing predation toward the equator, with a parallel pattern of increasing predation toward lower elevations. Patterns across both latitude and elevation were driven by arthropod predators, with no systematic trend in attack rates by birds or mammals. These matching gradients at global and regional scales suggest consistent drivers of biotic interaction strength, a finding that needs to be integrated into general theories of herbivory, community organization, and life-history evolution. Copyright © 2017, American Association for the Advancement of Science.

Will surface winds weaken in response to global warming?

NASA Astrophysics Data System (ADS)

Ma, Jian; Foltz, Gregory R.; Soden, Brian J.; Huang, Gang; He, Jie; Dong, Changming

2016-12-01

The surface Walker and tropical tropospheric circulations have been inferred to slow down from historical observations and model projections, yet analysis of large-scale surface wind predictions is lacking. Satellite measurements of surface wind speed indicate strengthening trends averaged over the global and tropical oceans that are supported by precipitation and evaporation changes. Here we use corrected anemometer-based observations to show that the surface wind speed has not decreased in the averaged tropical oceans, despite its reduction in the region of the Walker circulation. Historical simulations and future projections for climate change also suggest a near-zero wind speed trend averaged in space, regardless of the Walker cell change. In the tropics, the sea surface temperature pattern effect acts against the large-scale circulation slow-down. For higher latitudes, the surface winds shift poleward along with the eddy-driven mid-latitude westerlies, resulting in a very small contribution to the global change in surface wind speed. Despite its importance for surface wind speed change, the influence of the SST pattern change on global-mean rainfall is insignificant since it cannot substantially alter the global energy balance. As a result, the precipitation response to global warming remains ‘muted’ relative to atmospheric moisture increase. Our results therefore show consistency between projections and observations of surface winds and precipitation.

Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks.

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2018-05-02

RNA-binding proteins (RBPs) take over 5∼10% of the eukaryotic proteome and play key roles in many biological processes, e.g. gene regulation. Experimental detection of RBP binding sites is still time-intensive and high-costly. Instead, computational prediction of the RBP binding sites using pattern learned from existing annotation knowledge is a fast approach. From the biological point of view, the local structure context derived from local sequences will be recognized by specific RBPs. However, in computational modeling using deep learning, to our best knowledge, only global representations of entire RNA sequences are employed. So far, the local sequence information is ignored in the deep model construction process. In this study, we present a computational method iDeepE to predict RNA-protein binding sites from RNA sequences by combining global and local convolutional neural networks (CNNs). For the global CNN, we pad the RNA sequences into the same length. For the local CNN, we split a RNA sequence into multiple overlapping fixed-length subsequences, where each subsequence is a signal channel of the whole sequence. Next, we train deep CNNs for multiple subsequences and the padded sequences to learn high-level features, respectively. Finally, the outputs from local and global CNNs are combined to improve the prediction. iDeepE demonstrates a better performance over state-of-the-art methods on two large-scale datasets derived from CLIP-seq. We also find that the local CNN run 1.8 times faster than the global CNN with comparable performance when using GPUs. Our results show that iDeepE has captured experimentally verified binding motifs. https://github.com/xypan1232/iDeepE. xypan172436@gmail.com or hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online.

Soybean kinome: functional classification and gene expression patterns

PubMed Central

Liu, Jinyi; Chen, Nana; Grant, Joshua N.; Cheng, Zong-Ming (Max); Stewart, C. Neal; Hewezi, Tarek

2015-01-01

The protein kinase (PK) gene family is one of the largest and most highly conserved gene families in plants and plays a role in nearly all biological functions. While a large number of genes have been predicted to encode PKs in soybean, a comprehensive functional classification and global analysis of expression patterns of this large gene family is lacking. In this study, we identified the entire soybean PK repertoire or kinome, which comprised 2166 putative PK genes, representing 4.67% of all soybean protein-coding genes. The soybean kinome was classified into 19 groups, 81 families, and 122 subfamilies. The receptor-like kinase (RLK) group was remarkably large, containing 1418 genes. Collinearity analysis indicated that whole-genome segmental duplication events may have played a key role in the expansion of the soybean kinome, whereas tandem duplications might have contributed to the expansion of specific subfamilies. Gene structure, subcellular localization prediction, and gene expression patterns indicated extensive functional divergence of PK subfamilies. Global gene expression analysis of soybean PK subfamilies revealed tissue- and stress-specific expression patterns, implying regulatory functions over a wide range of developmental and physiological processes. In addition, tissue and stress co-expression network analysis uncovered specific subfamilies with narrow or wide interconnected relationships, indicative of their association with particular or broad signalling pathways, respectively. Taken together, our analyses provide a foundation for further functional studies to reveal the biological and molecular functions of PKs in soybean. PMID:25614662

Discovery of a Transition to Global Spin-Up in EXO 2030+375

NASA Technical Reports Server (NTRS)

Wilson, Colleen A.; Fabregat, Juan; Coburn, Wayne

2005-01-01

EXO 2030+375, a 42 second transient X-ray pulsar with a Be star companion, has been observed to undergo an outburst at nearly every periastron passage for the last 13.5 years. From 1994 through 2002, the global trend in the pulsar spin frequency was spin-down. Using RXTE data from 2003 September, we have observed a transition to global spin-up in EXO 203G+375. Although the spin frequency observations are sparse, the relative spin-up between 2002 June and 2003 September observations along with an overall brightening of the outbursts since mid 2002 observed with the RXTE ASM accompanied by an increase in density of the disk indicated by infrared magnitudes suggest that the pattern observed with BATSE of a roughly constant spin frequency, followed by spin-up, followed by spin-down is repeating. If so this pattern has approximately an 11 year period, similar to the 15 plus or minus 3 year period derived by Wilson et al. (2002) for the precession period of a one-armed oscillation in the Be disk. If this pattern is indeed repeating, we predict a transition from spin-up to spin-down in 2005.

The decomposition of fine and coarse roots: their global patterns and controlling factors

PubMed Central

Zhang, Xinyue; Wang, Wei

2015-01-01

Fine root decomposition represents a large carbon (C) cost to plants, and serves as a potential soil C source, as well as a substantial proportion of net primary productivity. Coarse roots differ markedly from fine roots in morphology, nutrient concentrations, functions, and decomposition mechanisms. Still poorly understood is whether a consistent global pattern exists between the decomposition of fine (<2 mm root diameter) and coarse (≥2 mm) roots. A comprehensive terrestrial root decomposition dataset, including 530 observations from 71 sampling sites, was thus used to compare global patterns of decomposition of fine and coarse roots. Fine roots decomposed significantly faster than coarse roots in middle latitude areas, but their decomposition in low latitude regions was not significantly different from that of coarse roots. Coarse root decomposition showed more dependence on climate, especially mean annual temperature (MAT), than did fine roots. Initial litter lignin content was the most important predictor of fine root decomposition, while lignin to nitrogen ratios, MAT, and mean annual precipitation were the most important predictors of coarse root decomposition. Our study emphasizes the necessity of separating fine roots and coarse roots when predicting the response of belowground C release to future climate changes. PMID:25942391

A remote sensing research agenda for mapping and monitoring biodiversity

NASA Technical Reports Server (NTRS)

Stoms, D. M.; Estes, J. E.

1993-01-01

A remote sensing research agenda designed to expand the knowledge of the spatial distribution of species richness and its ecological determinants and to predict its response to global change is proposed. Emphasis is placed on current methods of mapping species richness of both plants and animals, hypotheses concerning the biophysical factors believed to determine patterns of species richness, and anthropogenic processes causing the accelerating rate of extinctions. It is concluded that biodiversity should be incorporated more prominently into the global change and earth system science paradigms.

Remote Sensing the Patterns of Vector-borne Disease in El Nino and non-El Nino Years

NASA Technical Reports Server (NTRS)

Wood, B. L.; Chang, J.; Lobitz, B.; Beck, L.; DAntoni, Hector (Technical Monitor)

1997-01-01

The relationship between El Nino and non-El Nino and the patterns of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are long term predictions of changing precipitation and temperature patterns at continental and global scales. At the opposite extreme are the local or site specific ecological changes associated with the long term events. In order to understand and address the human health consequences of El Nino events, especially the patterns of vector-borne diseases, it is necessary to combine both scales of observation. At a local or regional scale the patterns of vector-borne diseases are determined by temperature, precipitation, and habitat availability. These factors, as well as disease incidence can be altered by El Nino events. Remote sensing data such as that acquired by the NOAA AVHRR and Landsat TM sensors can be used to characterize and monitor changing ecological conditions and therefore predict vector-borne disease patterns. The authors present the results of preliminary work on the analysis of historical AVHRR and TM data acquired during El Nino and nonfatal Nino years to characterize ecological conditions in Peru on a monthly basis. This information will then be combined with disease data to determine the relationship between changes in ecological conditions and disease incidence. Our goal is to produce a sequence of remotely sensed images which can be used to show the ecological and disease patterns associated with long term El Nino events and predictions.

Curvature, metric and parametrization of origami tessellations: theory and application to the eggbox pattern.

PubMed

Nassar, H; Lebée, A; Monasse, L

2017-01-01

Origami tessellations are particular textured morphing shell structures. Their unique folding and unfolding mechanisms on a local scale aggregate and bring on large changes in shape, curvature and elongation on a global scale. The existence of these global deformation modes allows for origami tessellations to fit non-trivial surfaces thus inspiring applications across a wide range of domains including structural engineering, architectural design and aerospace engineering. The present paper suggests a homogenization-type two-scale asymptotic method which, combined with standard tools from differential geometry of surfaces, yields a macroscopic continuous characterization of the global deformation modes of origami tessellations and other similar periodic pin-jointed trusses. The outcome of the method is a set of nonlinear differential equations governing the parametrization, metric and curvature of surfaces that the initially discrete structure can fit. The theory is presented through a case study of a fairly generic example: the eggbox pattern. The proposed continuous model predicts correctly the existence of various fittings that are subsequently constructed and illustrated.

Curvature, metric and parametrization of origami tessellations: theory and application to the eggbox pattern

NASA Astrophysics Data System (ADS)

Nassar, H.; Lebée, A.; Monasse, L.

2017-01-01

Origami tessellations are particular textured morphing shell structures. Their unique folding and unfolding mechanisms on a local scale aggregate and bring on large changes in shape, curvature and elongation on a global scale. The existence of these global deformation modes allows for origami tessellations to fit non-trivial surfaces thus inspiring applications across a wide range of domains including structural engineering, architectural design and aerospace engineering. The present paper suggests a homogenization-type two-scale asymptotic method which, combined with standard tools from differential geometry of surfaces, yields a macroscopic continuous characterization of the global deformation modes of origami tessellations and other similar periodic pin-jointed trusses. The outcome of the method is a set of nonlinear differential equations governing the parametrization, metric and curvature of surfaces that the initially discrete structure can fit. The theory is presented through a case study of a fairly generic example: the eggbox pattern. The proposed continuous model predicts correctly the existence of various fittings that are subsequently constructed and illustrated.

The status and challenge of global fire modelling

DOE PAGES

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...

2016-06-09

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

The status and challenge of global fire modelling

NASA Astrophysics Data System (ADS)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao

2016-06-01

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

The status and challenge of global fire modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

NASA Technical Reports Server (NTRS)

Potter, C. S.; Brooks, V.

1997-01-01

This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.

Towards a Statistical Model of Tropical Cyclone Genesis

NASA Astrophysics Data System (ADS)

Fernandez, A.; Kashinath, K.; McAuliffe, J.; Prabhat, M.; Stark, P. B.; Wehner, M. F.

2017-12-01

Tropical Cyclones (TCs) are important extreme weather phenomena that have a strong impact on humans. TC forecasts are largely based on global numerical models that produce TC-like features. Aspects of Tropical Cyclones such as their formation/genesis, evolution, intensification and dissipation over land are important and challenging problems in climate science. This study investigates the environmental conditions associated with Tropical Cyclone Genesis (TCG) by testing how accurately a statistical model can predict TCG in the CAM5.1 climate model. TCG events are defined using TECA software @inproceedings{Prabhat2015teca, title={TECA: Petascale Pattern Recognition for Climate Science}, author={Prabhat and Byna, Surendra and Vishwanath, Venkatram and Dart, Eli and Wehner, Michael and Collins, William D}, booktitle={Computer Analysis of Images and Patterns}, pages={426-436}, year={2015}, organization={Springer}} to extract TC trajectories from CAM5.1. L1-regularized logistic regression (L1LR) is applied to the CAM5.1 output. The predictions have nearly perfect accuracy for data not associated with TC tracks and high accuracy differentiating between high vorticity and low vorticity systems. The model's active variables largely correspond to current hypotheses about important factors for TCG, such as wind field patterns and local pressure minima, and suggests new routes for investigation. Furthermore, our model's predictions of TC activity are competitive with the output of an instantaneous version of Emanuel and Nolan's Genesis Potential Index (GPI) @inproceedings{eman04, title = "Tropical cyclone activity and the global climate system", author = "Kerry Emanuel and Nolan, {David S.}", year = "2004", pages = "240-241", booktitle = "26th Conference on Hurricanes and Tropical Meteorology"}.

A new paradigm for predicting zonal-mean climate and climate change

NASA Astrophysics Data System (ADS)

Armour, K.; Roe, G.; Donohoe, A.; Siler, N.; Markle, B. R.; Liu, X.; Feldl, N.; Battisti, D. S.; Frierson, D. M.

2016-12-01

How will the pole-to-equator temperature gradient, or large-scale patterns of precipitation, change under global warming? Answering such questions typically involves numerical simulations with comprehensive general circulation models (GCMs) that represent the complexities of climate forcing, radiative feedbacks, and atmosphere and ocean dynamics. Yet, our understanding of these predictions hinges on our ability to explain them through the lens of simple models and physical theories. Here we present evidence that zonal-mean climate, and its changes, can be understood in terms of a moist energy balance model that represents atmospheric heat transport as a simple diffusion of latent and sensible heat (as a down-gradient transport of moist static energy, with a diffusivity coefficient that is nearly constant with latitude). We show that the theoretical underpinnings of this model derive from the principle of maximum entropy production; that its predictions are empirically supported by atmospheric reanalyses; and that it successfully predicts the behavior of a hierarchy of climate models - from a gray radiation aquaplanet moist GCM, to comprehensive GCMs participating in CMIP5. As an example of the power of this paradigm, we show that, given only patterns of local radiative feedbacks and climate forcing, the moist energy balance model accurately predicts the evolution of zonal-mean temperature and atmospheric heat transport as simulated by the CMIP5 ensemble. These results suggest that, despite all of its dynamical complexity, the atmosphere essentially responds to energy imbalances by simply diffusing latent and sensible heat down-gradient; this principle appears to explain zonal-mean climate and its changes under global warming.

[Intestinal parasitic diseases as a global health problem].

PubMed

Chacín-Bonilla, Leonor

2013-03-01

In today's world, parasitic disease agents are not restricted by geography or economy, and have become a significant global threat. The increasing globalization of the fresh produce market and greater international trade and travels, have contributed to the spread of these organisms in the industrialized world. Parasitic protozoa cause waterborne and foodborne outbreaks of diarrhea. The unprecedented flow of people introduces cultural and behavior patterns around the world; the increasing tendency to eat raw or undercooked meat and seafood, favors the dissemination of several parasitic pathogens. Climate changes are predicted to cause a global increase in soil-transmitted helminthiases. The multidisciplinary study of these agents, and the interaction among scientists, global health organizations and governments are imperative to reduce the burden of these diseases and improve the life of a large segment of the world population.

An effective drift correction for dynamical downscaling of decadal global climate predictions

NASA Astrophysics Data System (ADS)

Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

2018-04-01

Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

Personality patterns predict the risk of antisocial behavior in Spanish-speaking adolescents.

PubMed

Alcázar-Córcoles, Miguel A; Verdejo-García, Antonio; Bouso-Sáiz, José C; Revuelta-Menéndez, Javier; Ramírez-Lira, Ezequiel

2017-05-01

There is a renewed interest in incorporating personality variables in criminology theories in order to build models able to integrate personality variables and biological factors with psychosocial and sociocultural factors. The aim of this article is the assessment of personality dimensions that contribute to the prediction of antisocial behavior in adolescents. For this purpose, a sample of adolescents from El Salvador, Mexico, and Spain was obtained. The sample consisted of 1035 participants with a mean age of 16.2. There were 450 adolescents from a forensic population (those who committed a crime) and 585 adolescents from the normal population (no crime committed). All of participants answered personality tests about neuroticism, extraversion, psychoticism, sensation seeking, impulsivity, and violence risk. Principal component analysis of the data identified two independent factors: (i) the disinhibited behavior pattern (PDC), formed by the dimensions of neuroticism, psychoticism, impulsivity and risk of violence; and (ii) the extrovert behavior pattern (PEC), formed by the dimensions of sensation risk and extraversion. Both patterns significantly contributed to the prediction of adolescent antisocial behavior in a logistic regression model which properly classifies a global percentage of 81.9%, 86.8% for non-offense and 72.5% for offense behavior. The classification power of regression equations allows making very satisfactory predictions about adolescent offense commission. Educational level has been classified as a protective factor, while age and gender (male) have been classified as risk factors.

Increased evapotranspiration demand in a Mediterranean climate might cause a decline in fungal yields under global warming.

PubMed

Ágreda, Teresa; Águeda, Beatriz; Olano, José M; Vicente-Serrano, Sergio M; Fernández-Toirán, Marina

2015-09-01

Wild fungi play a critical role in forest ecosystems, and its recollection is a relevant economic activity. Understanding fungal response to climate is necessary in order to predict future fungal production in Mediterranean forests under climate change scenarios. We used a 15-year data set to model the relationship between climate and epigeous fungal abundance and productivity, for mycorrhizal and saprotrophic guilds in a Mediterranean pine forest. The obtained models were used to predict fungal productivity for the 2021-2080 period by means of regional climate change models. Simple models based on early spring temperature and summer-autumn rainfall could provide accurate estimates for fungal abundance and productivity. Models including rainfall and climatic water balance showed similar results and explanatory power for the analyzed 15-year period. However, their predictions for the 2021-2080 period diverged. Rainfall-based models predicted a maintenance of fungal yield, whereas water balance-based models predicted a steady decrease of fungal productivity under a global warming scenario. Under Mediterranean conditions fungi responded to weather conditions in two distinct periods: early spring and late summer-autumn, suggesting a bimodal pattern of growth. Saprotrophic and mycorrhizal fungi showed differences in the climatic control. Increased atmospheric evaporative demand due to global warming might lead to a drop in fungal yields during the 21st century. © 2015 John Wiley & Sons Ltd.

Seismic-geodynamic constraints on three-dimensional structure, vertical flow, and heat transfer in the mantle

USGS Publications Warehouse

Forte, A.M.; Woodward, R.L.

1997-01-01

Joint inversions of seismic and geodynamic data are carried out in which we simultaneously constrain global-scale seismic heterogeneity in the mantle as well as the amplitude of vertical mantle flow across the 670 km seismic discontinuity. These inversions reveal the existence of a family of three-dimensional (3-D) mantle models that satisfy the data while at the same time yielding predictions of layered mantle flow. The new 3-D mantle models we obtain demonstrate that the buoyancy forces due to the undulations of the 670 km phase-change boundary strongly inhibit the vertical flow between the upper and lower mantle. The strong stabilizing effect of the 670 km topography also has an important impact on the predicted dynamic topography of the Earth's solid surface and on the surface gravity anomalies. The new 3-D models that predict strongly or partially layered mantle flow provide essentially identical fits to the global seismic data as previous models that have, until now, predicted only whole-mantle flow. The convective vertical transport of heat across the mantle predicted on the basis of the new 3-D models shows that the heat flow is a minimum at 1000 km depth. This suggests the presence at this depth of a globally defined horizon across which the pattern of lateral heterogeneity changes rapidly. Copyright 1997 by the American Geophysical Union.

Breeding for sustainable production in a changing climate – understanding the physiological basis of genetic by environmental interactions

USDA-ARS?s Scientific Manuscript database

Abiotic stresses (drought, cold, heat, excess, water, salinity) result in loses in yield and quality of crops. In addition, these stresses limit the areas that can be cultivated because of yield instability and crop loss. Global warming models predict erratic weather patterns making the impact of th...

Repackaging precipitation into fewer, larger storms reduces ecosystem exchanges of CO2 and H2O in a semiarid steppe

USDA-ARS?s Scientific Manuscript database

Global circulation models predict that precipitation patterns will become more extreme, i.e. seasonal rainfall events tend to be larger in size, but fewer in number. Studies in North American grasslands have shown that above-ground net primary productivity (ANPP) was enhanced by such repackaging of ...

Prediction, Assessment of the Rift Valley fever Activity in East and Southern Africa 2006 - 2008 and Possible Vector Control Strategies

USDA-ARS?s Scientific Manuscript database

Historical outbreaks of Rift Valley fever (RVF) since the early 1950s have been associated with cyclical patterns of the El Nino/Southern Oscillation (ENSO) phenomenon which results in elevated and widespread rainfall over the RVF endemic areas of Africa. Using satellite measurements of global and ...

Blood/Brain Biomarkers of Inflammation After Stroke and Their Association With Outcome: From C-Reactive Protein to Damage-Associated Molecular Patterns.

PubMed

Bustamante, Alejandro; Simats, Alba; Vilar-Bergua, Andrea; García-Berrocoso, Teresa; Montaner, Joan

2016-10-01

Stroke represents one of the most important causes of disability and death in developed countries. However, there is a lack of prognostic tools in clinical practice to monitor the neurological condition and predict the final outcome. Blood biomarkers have been proposed and studied in this indication; however, no biomarker is currently used in clinical practice. The stroke-related neuroinflammatory processes have been associated with a poor outcome in stroke, as well as with poststroke complications. In this review, we focus on the most studied blood biomarkers of this inflammatory processes, cytokines, and C-reactive protein, evaluating its association with outcome and complications in stroke through the literature, and performing a systematic review on the association of C-reactive protein and functional outcome after stroke. Globally, we identified uncertainty with regard to the association of the evaluated biomarkers with stroke outcome, with little added value on top of clinical predictors such as age or stroke severity, which makes its implementation unlikely in clinical practice for global outcome prediction. Regarding poststroke complications, despite being more practical scenarios in which to make medical decisions following a biomarker prediction, not many studies have been performed, although there are now some candidates for prediction of poststroke infections. Finally, as potential new candidates, we reviewed the pathophysiological actions of damage-associated molecular patterns as triggers of the neuroinflammatory cascade of stroke, and their possible use as biomarkers.

Association mining of dependency between time series

NASA Astrophysics Data System (ADS)

Hafez, Alaaeldin

2001-03-01

Time series analysis is considered as a crucial component of strategic control over a broad variety of disciplines in business, science and engineering. Time series data is a sequence of observations collected over intervals of time. Each time series describes a phenomenon as a function of time. Analysis on time series data includes discovering trends (or patterns) in a time series sequence. In the last few years, data mining has emerged and been recognized as a new technology for data analysis. Data Mining is the process of discovering potentially valuable patterns, associations, trends, sequences and dependencies in data. Data mining techniques can discover information that many traditional business analysis and statistical techniques fail to deliver. In this paper, we adapt and innovate data mining techniques to analyze time series data. By using data mining techniques, maximal frequent patterns are discovered and used in predicting future sequences or trends, where trends describe the behavior of a sequence. In order to include different types of time series (e.g. irregular and non- systematic), we consider past frequent patterns of the same time sequences (local patterns) and of other dependent time sequences (global patterns). We use the word 'dependent' instead of the word 'similar' for emphasis on real life time series where two time series sequences could be completely different (in values, shapes, etc.), but they still react to the same conditions in a dependent way. In this paper, we propose the Dependence Mining Technique that could be used in predicting time series sequences. The proposed technique consists of three phases: (a) for all time series sequences, generate their trend sequences, (b) discover maximal frequent trend patterns, generate pattern vectors (to keep information of frequent trend patterns), use trend pattern vectors to predict future time series sequences.

Global patterns of predator diversity in the open oceans.

PubMed

Worm, Boris; Sandow, Marcel; Oschlies, Andreas; Lotze, Heike K; Myers, Ransom A

2005-08-26

The open oceans comprise most of the biosphere, yet patterns and trends of species diversity there are enigmatic. Here, we derive worldwide patterns of tuna and billfish diversity over the past 50 years, revealing distinct subtropical "hotspots" that appeared to hold generally for other predators and zooplankton. Diversity was positively correlated with thermal fronts and dissolved oxygen and a nonlinear function of temperature (approximately 25 degrees C optimum). Diversity declined between 10 and 50% in all oceans, a trend that coincided with increased fishing pressure, superimposed on strong El Niño-Southern Oscillation-driven variability across the Pacific. We conclude that predator diversity shows a predictable yet eroding pattern signaling ecosystem-wide changes linked to climate and fishing.

Adaptation of Land-Use Demands to the Impact of Climate Change on the Hydrological Processes of an Urbanized Watershed

PubMed Central

Lin, Yu-Pin; Hong, Nien-Ming; Chiang, Li-Chi; Liu, Yen-Lan; Chu, Hone-Jay

2012-01-01

The adaptation of land-use patterns is an essential aspect of minimizing the inevitable impact of climate change at regional and local scales; for example, adapting watershed land-use patterns to mitigate the impact of climate change on a region’s hydrology. The objective of this study is to simulate and assess a region’s ability to adapt to hydrological changes by modifying land-use patterns in the Wu-Du watershed in northern Taiwan. A hydrological GWLF (Generalized Watershed Loading Functions) model is used to simulate three hydrological components, namely, runoff, groundwater and streamflow, based on various land-use scenarios under six global climate models. The land-use allocations are simulated by the CLUE-s model for the various development scenarios. The simulation results show that runoff and streamflow are strongly related to the precipitation levels predicted by different global climate models for the wet and dry seasons, but groundwater cycles are more related to land-use. The effects of climate change on groundwater and runoff can be mitigated by modifying current land-use patterns; and slowing the rate of urbanization would also reduce the impact of climate change on hydrological components. Thus, land-use adaptation on a local/regional scale provides an alternative way to reduce the impacts of global climate change on local hydrology. PMID:23202833

The Role of Sociodemographic Risk and Maternal Behavior in the Prediction of Infant Attachment Disorganization

PubMed Central

Gedaly, Lindsey R.; Leerkes, Esther M.

2017-01-01

Predictors of infant attachment disorganization were examined among 203 primiparous mothers (52% European American, 48% African American) and their infants (104 female). The Strange Situation Procedure was administered at 1 year. Global maternal insensitivity and overtly negative maternal behavior were observed during distress-eliciting tasks when infants were 6 months and 1 year old. Mothers reported on their demographics to yield a measure of sociodemographic risk (i.e., age, education, income-to-needs). Overtly negative maternal behavior was positively associated with the infant attachment disorganization rating scale score, but did not predict being classified as disorganized. Global maternal insensitivity was associated with higher attachment disorganization, both the rating and the classification, when sociodemographic risk was high but not when sociodemographic risk was low. The pattern of results did not vary by maternal race. The results provide some support for the view that negative maternal behavior and the combination of sociodemographic risk and global maternal insensitivity play a role in the development of infant attachment disorganization. PMID:27477050

The role of sociodemographic risk and maternal behavior in the prediction of infant attachment disorganization.

PubMed

Gedaly, Lindsey R; Leerkes, Esther M

2016-12-01

Predictors of infant attachment disorganization were examined among 203 primiparous mothers (52% European American, 48% African American) and their infants (104 female). The Strange Situation Procedure was administered at one year. Global maternal insensitivity and overtly negative maternal behavior were observed during distress-eliciting tasks when infants were six months and one year old. Mothers reported on their demographics to yield a measure of sociodemographic risk (i.e., age, education, income-to-needs). Overtly negative maternal behavior was positively associated with the infant attachment disorganization rating scale score, but did not predict being classified as disorganized. Global maternal insensitivity was associated with higher attachment disorganization, both the rating and the classification, when sociodemographic risk was high but not when sociodemographic risk was low. The pattern of results did not vary by maternal race. The results provide some support for the view that negative maternal behavior and the combination of sociodemographic risk and global maternal insensitivity play a role in the development of infant attachment disorganization.

Medium-range Performance of the Global NWP Model

NASA Astrophysics Data System (ADS)

Kim, J.; Jang, T.; Kim, J.; Kim, Y.

2017-12-01

The medium-range performance of the global numerical weather prediction (NWP) model in the Korea Meteorological Administration (KMA) is investigated. The performance is based on the prediction of the extratropical circulation. The mean square error is expressed by sum of spatial variance of discrepancy between forecasts and observations and the square of the mean error (ME). Thus, it is important to investigate the ME effect in order to understand the model performance. The ME is expressed by the subtraction of an anomaly from forecast difference against the real climatology. It is found that the global model suffers from a severe systematic ME in medium-range forecasts. The systematic ME is dominant in the entire troposphere in all months. Such ME can explain at most 25% of root mean square error. We also compare the extratropical ME distribution with that from other NWP centers. NWP models exhibit similar spatial ME structure each other. It is found that the spatial ME pattern is highly correlated to that of an anomaly, implying that the ME varies with seasons. For example, the correlation coefficient between ME and anomaly ranges from -0.51 to -0.85 by months. The pattern of the extratropical circulation also has a high correlation to an anomaly. The global model has trouble in faithfully simulating extratropical cyclones and blockings in the medium-range forecast. In particular, the model has a hard to simulate an anomalous event in medium-range forecasts. If we choose an anomalous period for a test-bed experiment, we will suffer from a large error due to an anomaly.

Assessing the Effects of Climate on Global Fluvial Discharge Variability

NASA Astrophysics Data System (ADS)

Hansford, M. R.; Plink-Bjorklund, P.

2017-12-01

Plink-Bjorklund (2015) established the link between precipitation seasonality and river discharge variability in the monsoon domain and subtropical rivers (see also Leier et al, 2005; Fielding et al., 2009), resulting in distinct morphodynamic processes and a sedimentary record distinct from perennial precipitation zone in tropical rainforest zone and mid latitudes. This study further develops our understanding of discharge variability using a modern global river database created with data from the Global Runoff Data Centre (GRDC). The database consists of daily discharge for 595 river stations and examines them using a series of discharge variability indexes (DVI) on different temporal scales to examine how discharge variability occurs in river systems around the globe. These indexes examine discharge of individual days and monthly averages that allows for comparison of river systems against each other, regardless of size of the river. Comparing river discharge patterns in seven climate zones (arid, cold, humid subtropics, monsoonal, polar, rainforest, and temperate) based off the Koppen-Geiger climate classifications reveals a first order climatic control on discharge patterns and correspondingly sediment transport. Four groupings of discharge patterns emerge when coming climate zones and DVI: persistent, moderate, seasonal, and erratic. This dataset has incredible predictive power about the nature of discharge in fluvial systems around the world. These seasonal effects on surface water supply affects river morphodynamics and sedimentation on a wide timeframe, ranging from large single events to an inter-annual or even decadal timeframe. The resulting sedimentary deposits lead to differences in fluvial architecture on a range of depositional scales from sedimentary structures and bedforms to channel complex systems. These differences are important to accurately model for several reasons, ranging from stratigraphic and paleoenviromental reconstructions to more economic reasons, such as predicting reservoir presence, distribution, and connectivity in continental basins. The ultimate objective of this research is to develop differentiated fluvial facies and architecture based on the observed discharge patterns in the different climate zones.

Is Global Warming Accelerating?

NASA Astrophysics Data System (ADS)

Shukla, J.; Delsole, T. M.; Tippett, M. K.

2009-12-01

A global pattern that fluctuates naturally on decadal time scales is identified in climate simulations and observations. This newly discovered component, called the Global Multidecadal Oscillation (GMO), is related to the Atlantic Meridional Oscillation and shown to account for a substantial fraction of decadal fluctuations in the observed global average sea surface temperature. IPCC-class climate models generally underestimate the variance of the GMO, and hence underestimate the decadal fluctuations due to this component of natural variability. Decomposing observed sea surface temperature into a component due to anthropogenic and natural radiative forcing plus the GMO, reveals that most multidecadal fluctuations in the observed global average sea surface temperature can be accounted for by these two components alone. The fact that the GMO varies naturally on multidecadal time scales implies that it can be predicted with some skill on decadal time scales, which provides a scientific rationale for decadal predictions. Furthermore, the GMO is shown to account for about half of the warming in the last 25 years and hence a substantial fraction of the recent acceleration in the rate of increase in global average sea surface temperature. Nevertheless, in terms of the global average “well-observed” sea surface temperature, the GMO can account for only about 0.1° C in transient, decadal-scale fluctuations, not the century-long 1° C warming that has been observed during the twentieth century.

A Microfluidic Route to Breaking Chiral Symmetry: Theory and Experiment

NASA Astrophysics Data System (ADS)

Ocko, Samuel; Adams, Laura

A robust route for the biased production of single handed chiral structures has been found in generating non-spherical, multi-component double emulsions using glass microfluidic devices. The specific type of handedness is determined by the final packing geometry of four different inner drops inside an ultra-thin sheath of oil. Before the three dimensional chiral structures are formed, the quasi-one dimensional chain of four inner drops re-arranges in two dimensions into either checkerboard or stripe patterns. We derive an analytical model predicting which pattern is more likely and assembles in the least amount of time. Moreover, our model accurately predicts our experimental results and is based on local bending dynamics, rather than global surface energy minimization. We gratefully acknowledge Professors D. Weitz and L. Mahadevan's support.

Analysis of engagement behavior in children during dyadic interactions using prosodic cues⋆

PubMed Central

Gupta, Rahul; Bone, Daniel; Lee, Sungbok; Narayanan, Shrikanth

2017-01-01

Child engagement is defined as the interaction of a child with his/her environment in a contextually appropriate manner. Engagement behavior in children is linked to socio-emotional and cognitive state assessment with enhanced engagement identified with improved skills. A vast majority of studies however rely solely, and often implicitly, on subjective perceptual measures of engagement. Access to automatic quantification could assist researchers/clinicians to objectively interpret engagement with respect to a target behavior or condition, and furthermore inform mechanisms for improving engagement in various settings. In this paper, we present an engagement prediction system based exclusively on vocal cues observed during structured interaction between a child and a psychologist involving several tasks. Specifically, we derive prosodic cues that capture engagement levels across the various tasks. Our experiments suggest that a child’s engagement is reflected not only in the vocalizations, but also in the speech of the interacting psychologist. Moreover, we show that prosodic cues are informative of the engagement phenomena not only as characterized over the entire task (i.e., global cues), but also in short term patterns (i.e., local cues). We perform a classification experiment assigning the engagement of a child into three discrete levels achieving an unweighted average recall of 55.8% (chance is 33.3%). While the systems using global cues and local level cues are each statistically significant in predicting engagement, we obtain the best results after fusing these two components. We perform further analysis of the cues at local and global levels to achieve insights linking specific prosodic patterns to the engagement phenomenon. We observe that while the performance of our model varies with task setting and interacting psychologist, there exist universal prosodic patterns reflective of engagement. PMID:28713198

Analysis of engagement behavior in children during dyadic interactions using prosodic cues.

PubMed

Gupta, Rahul; Bone, Daniel; Lee, Sungbok; Narayanan, Shrikanth

2016-05-01

Child engagement is defined as the interaction of a child with his/her environment in a contextually appropriate manner. Engagement behavior in children is linked to socio-emotional and cognitive state assessment with enhanced engagement identified with improved skills. A vast majority of studies however rely solely, and often implicitly, on subjective perceptual measures of engagement. Access to automatic quantification could assist researchers/clinicians to objectively interpret engagement with respect to a target behavior or condition, and furthermore inform mechanisms for improving engagement in various settings. In this paper, we present an engagement prediction system based exclusively on vocal cues observed during structured interaction between a child and a psychologist involving several tasks. Specifically, we derive prosodic cues that capture engagement levels across the various tasks. Our experiments suggest that a child's engagement is reflected not only in the vocalizations, but also in the speech of the interacting psychologist. Moreover, we show that prosodic cues are informative of the engagement phenomena not only as characterized over the entire task (i.e., global cues), but also in short term patterns (i.e., local cues). We perform a classification experiment assigning the engagement of a child into three discrete levels achieving an unweighted average recall of 55.8% (chance is 33.3%). While the systems using global cues and local level cues are each statistically significant in predicting engagement, we obtain the best results after fusing these two components. We perform further analysis of the cues at local and global levels to achieve insights linking specific prosodic patterns to the engagement phenomenon. We observe that while the performance of our model varies with task setting and interacting psychologist, there exist universal prosodic patterns reflective of engagement.

Within-species patterns challenge our understanding of the causes and consequences of trait variation with implications for trait-based models

NASA Astrophysics Data System (ADS)

Anderegg, L. D.; Berner, L. T.; Badgley, G.; Hillerislambers, J.; Law, B. E.

2017-12-01

Functional traits could facilitate ecological prediction by provide scale-free tools for modeling ecosystem function. Yet much of their utility lies in three key assumptions: 1) that global patterns of trait covariation are the result of universal trade-offs independent of taxonomic scale, so empirical trait-trait relationships can be used to constrain vegetation models 2) that traits respond predictably to environmental gradients and can therefore be reliably quantified to parameterize models and 3) that well sampled traits influence productivity. We use an extensive dataset of within-species leaf trait variation in North American conifers combined with global leaf trait datasets to test these assumptions. We examine traits central to the `leaf economics spectrum', and quantify patterns of trait variation at multiple taxonomic scales. We also test whether site environment explains geographic trait variation within conifers, and ask whether foliar traits explain geographic variation in relative growth rates. We find that most leaf traits vary primarily between rather than within species globally, but that a large fraction of within-PFT trait variation is within-species. We also find that some leaf economics spectrum relationships differ in sign within versus between species, particularly the relationship between leaf lifespan and LMA. In conifers, we find weak and inconsistent relationships between site environment and leaf traits, making it difficult capture within-species leaf trait variation for regional model parameterization. Finally, we find limited relationships between tree relative growth rate and any foliar trait other than leaf lifespan, with leaf traits jointly explaining 42% of within-species growth variation but environmental factors explaining 77% of variation. We suggest that additional traits, particularly whole plant allometry/allocation traits may be better than leaf traits for improving vegetation model performance at smaller taxonomic and spatial scales.

The Space-Time Variation of Global Crop Yields, Detecting Simultaneous Outliers and Identifying the Teleconnections with Climatic Patterns

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Pal, I.; Khanbilvardi, R.

2017-12-01

An understanding of the climate factors that influence the space-time variability of crop yields is important for food security purposes and can help us predict global food availability. In this study, we address how the crop yield trends of countries globally were related to each other during the last several decades and the main climatic variables that triggered high/low crop yields simultaneously across the world. Robust Principal Component Analysis (rPCA) is used to identify the primary modes of variation in wheat, maize, sorghum, rice, soybeans, and barley yields. Relations between these modes of variability and important climatic variables, especially anomalous sea surface temperature (SSTa), are examined from 1964 to 2010. rPCA is also used to identify simultaneous outliers in each year, i.e. systematic high/low crop yields across the globe. The results demonstrated spatiotemporal patterns of these crop yields and the climate-related events that caused them as well as the connection of outliers with weather extremes. We find that among climatic variables, SST has had the most impact on creating simultaneous crop yields variability and yield outliers in many countries. An understanding of this phenomenon can benefit global crop trade networks.

Global warming and climate forcing by recent albedo changes on Mars

USGS Publications Warehouse

Fenton, L.K.; Geissler, P.E.; Haberle, R.M.

2007-01-01

For hundreds of years, scientists have tracked the changing appearance of Mars, first by hand drawings and later by photographs. Because of this historical record, many classical albedo patterns have long been known to shift in appearance over time. Decadal variations of the martian surface albedo are generally attributed to removal and deposition of small amounts of relatively bright dust on the surface. Large swaths of the surface (up to 56 million km2) have been observed to darken or brighten by 10 per cent or more. It is unknown, however, how these albedo changes affect wind circulation, dust transport and the feedback between these processes and the martian climate. Here we present predictions from a Mars general circulation model, indicating that the observed interannual albedo alterations strongly influence the martian environment. Results indicate enhanced wind stress in recently darkened areas and decreased wind stress in brightened areas, producing a positive feedback system in which the albedo changes strengthen the winds that generate the changes. The simulations also predict a net annual global warming of surface air temperatures by ???0.65 K, enhancing dust lifting by increasing the likelihood of dust devil generation. The increase in global dust lifting by both wind stress and dust devils may affect the mechanisms that trigger large dust storm initiation, a poorly understood phenomenon, unique to Mars. In addition, predicted increases in summertime air temperatures at high southern latitudes would contribute to the rapid and steady scarp retreat that has been observed in the south polar residual ice for the past four Mars years. Our results suggest that documented albedo changes affect recent climate change and large-scale weather patterns on Mars, and thus albedo variations are a necessary component of future atmospheric and climate studies. ??2007 Nature Publishing Group.

Global warming and climate forcing by recent albedo changes on Mars.

PubMed

Fenton, Lori K; Geissler, Paul E; Haberle, Robert M

2007-04-05

For hundreds of years, scientists have tracked the changing appearance of Mars, first by hand drawings and later by photographs. Because of this historical record, many classical albedo patterns have long been known to shift in appearance over time. Decadal variations of the martian surface albedo are generally attributed to removal and deposition of small amounts of relatively bright dust on the surface. Large swaths of the surface (up to 56 million km2) have been observed to darken or brighten by 10 per cent or more. It is unknown, however, how these albedo changes affect wind circulation, dust transport and the feedback between these processes and the martian climate. Here we present predictions from a Mars general circulation model, indicating that the observed interannual albedo alterations strongly influence the martian environment. Results indicate enhanced wind stress in recently darkened areas and decreased wind stress in brightened areas, producing a positive feedback system in which the albedo changes strengthen the winds that generate the changes. The simulations also predict a net annual global warming of surface air temperatures by approximately 0.65 K, enhancing dust lifting by increasing the likelihood of dust devil generation. The increase in global dust lifting by both wind stress and dust devils may affect the mechanisms that trigger large dust storm initiation, a poorly understood phenomenon, unique to Mars. In addition, predicted increases in summertime air temperatures at high southern latitudes would contribute to the rapid and steady scarp retreat that has been observed in the south polar residual ice for the past four Mars years. Our results suggest that documented albedo changes affect recent climate change and large-scale weather patterns on Mars, and thus albedo variations are a necessary component of future atmospheric and climate studies.

Climate Prediction Center global monthly soil moisture data set at 0.5° resolution for 1948 to present

NASA Astrophysics Data System (ADS)

Fan, Yun; van den Dool, Huug

2004-05-01

We have produced a 0.5° × 0.5° monthly global soil moisture data set for the period from 1948 to the present. The land model is a one-layer "bucket" water balance model, while the driving input fields are Climate Prediction Center monthly global precipitation over land, which uses over 17,000 gauges worldwide, and monthly global temperature from global Reanalysis. The output consists of global monthly soil moisture, evaporation, and runoff, starting from January 1948. A distinguishing feature of this data set is that all fields are updated monthly, which greatly enhances utility for near-real-time purposes. Data validation shows that the land model does well; both the simulated annual cycle and interannual variability of soil moisture are reasonably good against the limited observations in different regions. A data analysis reveals that, on average, the land surface water balance components have a stronger annual cycle in the Southern Hemisphere than those in the Northern Hemisphere. From the point of view of soil moisture, climates can be characterized into two types, monsoonal and midlatitude climates, with the monsoonal ones covering most of the low-latitude land areas and showing a more prominent annual variation. A global soil moisture empirical orthogonal function analysis and time series of hemisphere means reveal some interesting patterns (like El Niño-Southern Oscillation) and long-term trends in both regional and global scales.

Global seismic data reveal little water in the mantle transition zone

NASA Astrophysics Data System (ADS)

Houser, C.

2016-08-01

Knowledge of the Earth's present water content is necessary to constrain the amount of water and other volatiles the Earth acquired during its formation and the amount that is cycled back into the interior from the surface. This study compares 410 and 660 km discontinuity depth with shear wave tomography within the mantle transition zone to identify regions with seismic signals consistent with water. The depth of the 410 and 660 km discontinuities is determined from a large updated dataset of SS-S410S and SS-S660S differential travel times, known as SS precursors. The discontinuity depths measured from binning and stacking the SS precursor data are then compared to the shear velocity model HMSL-S06 in the transition zone. Mapping all the possible combinations, very few locations match the predictions from mineral physics for the effects of water on discontinuity depth and shear velocity. The predictions, although not yet measured at actual transition zone temperatures and pressures, are a shallow 410 km discontinuity, a deep 660 km discontinuity, and a slow shear velocity. Only 8% of the bins with high-quality data are consistent with these predictions, and the calculated average water content within these bins is around 0.6 wt.%. A few isolated locations have patterns of velocity/topography that are consistent with water, while there are large regional-scale patterns consistent with cold/hot temperature anomalies. Combining this global analysis of long period seismic data and the current mineral physics predictions for water in transition zone minerals, I find that the mantle transition zone is generally dry, containing less than one Earth ocean of water. Although subduction zones could be locally hydrated, the combined discontinuity and velocity data show no evidence that wadsleyite or ringwoodite have been globally hydrated by subduction or initial Earth conditions.

An Open-Access Modeled Passenger Flow Matrix for the Global Air Network in 2010

PubMed Central

Huang, Zhuojie; Wu, Xiao; Garcia, Andres J.; Fik, Timothy J.; Tatem, Andrew J.

2013-01-01

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data. PMID:23691194

An open-access modeled passenger flow matrix for the global air network in 2010.

PubMed

Huang, Zhuojie; Wu, Xiao; Garcia, Andres J; Fik, Timothy J; Tatem, Andrew J

2013-01-01

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data.

Chaos emerging in soil failure patterns observed during tillage: Normalized deterministic nonlinear prediction (NDNP) and its application.

PubMed

Sakai, Kenshi; Upadhyaya, Shrinivasa K; Andrade-Sanchez, Pedro; Sviridova, Nina V

2017-03-01

Real-world processes are often combinations of deterministic and stochastic processes. Soil failure observed during farm tillage is one example of this phenomenon. In this paper, we investigated the nonlinear features of soil failure patterns in a farm tillage process. We demonstrate emerging determinism in soil failure patterns from stochastic processes under specific soil conditions. We normalized the deterministic nonlinear prediction considering autocorrelation and propose it as a robust way of extracting a nonlinear dynamical system from noise contaminated motion. Soil is a typical granular material. The results obtained here are expected to be applicable to granular materials in general. From a global scale to nano scale, the granular material is featured in seismology, geotechnology, soil mechanics, and particle technology. The results and discussions presented here are applicable in these wide research areas. The proposed method and our findings are useful with respect to the application of nonlinear dynamics to investigate complex motions generated from granular materials.

Simultaneous prediction of enzyme orthologs from chemical transformation patterns for de novo metabolic pathway reconstruction

PubMed Central

Tabei, Yasuo; Yamanishi, Yoshihiro; Kotera, Masaaki

2016-01-01

Motivation: Metabolic pathways are an important class of molecular networks consisting of compounds, enzymes and their interactions. The understanding of global metabolic pathways is extremely important for various applications in ecology and pharmacology. However, large parts of metabolic pathways remain unknown, and most organism-specific pathways contain many missing enzymes. Results: In this study we propose a novel method to predict the enzyme orthologs that catalyze the putative reactions to facilitate the de novo reconstruction of metabolic pathways from metabolome-scale compound sets. The algorithm detects the chemical transformation patterns of substrate–product pairs using chemical graph alignments, and constructs a set of enzyme-specific classifiers to simultaneously predict all the enzyme orthologs that could catalyze the putative reactions of the substrate–product pairs in the joint learning framework. The originality of the method lies in its ability to make predictions for thousands of enzyme orthologs simultaneously, as well as its extraction of enzyme-specific chemical transformation patterns of substrate–product pairs. We demonstrate the usefulness of the proposed method by applying it to some ten thousands of metabolic compounds, and analyze the extracted chemical transformation patterns that provide insights into the characteristics and specificities of enzymes. The proposed method will open the door to both primary (central) and secondary metabolism in genomics research, increasing research productivity to tackle a wide variety of environmental and public health matters. Availability and Implementation: Contact: maskot@bio.titech.ac.jp PMID:27307627

Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia.

PubMed

Diuk, Carlos; Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew; Niv, Yael

2013-03-27

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.

The global obesity pandemic: shaped by global drivers and local environments.

PubMed

Swinburn, Boyd A; Sacks, Gary; Hall, Kevin D; McPherson, Klim; Finegood, Diane T; Moodie, Marjory L; Gortmaker, Steven L

2011-08-27

The simultaneous increases in obesity in almost all countries seem to be driven mainly by changes in the global food system, which is producing more processed, affordable, and effectively marketed food than ever before. This passive overconsumption of energy leading to obesity is a predictable outcome of market economies predicated on consumption-based growth. The global food system drivers interact with local environmental factors to create a wide variation in obesity prevalence between populations. Within populations, the interactions between environmental and individual factors, including genetic makeup, explain variability in body size between individuals. However, even with this individual variation, the epidemic has predictable patterns in subpopulations. In low-income countries, obesity mostly affects middle-aged adults (especially women) from wealthy, urban environments; whereas in high-income countries it affects both sexes and all ages, but is disproportionately greater in disadvantaged groups. Unlike other major causes of preventable death and disability, such as tobacco use, injuries, and infectious diseases, there are no exemplar populations in which the obesity epidemic has been reversed by public health measures. This absence increases the urgency for evidence-creating policy action, with a priority on reduction of the supply-side drivers. Copyright © 2011 Elsevier Ltd. All rights reserved.

The climatic effects of nuclear war

NASA Technical Reports Server (NTRS)

Turco, R. P.; Toon, O. B.; Ackerman, T. P.; Pollack, J. B.; Sagan, C.

1984-01-01

The effects of various US-USSR nuclear-exchange scenarios on global climate are investigated by means of computer simulations, summarizing the results of Turco et al. (1983) and follow-up studies using 3D global-circulation models. A nuclear-scenario model is used to determine the amounts of dust, smoke, radioactivity, and pyrotoxins generated by a particular type of nuclear exchange (such as a general 5,000-Mt exchange, a 1,000-Mt limited exchange, a 5,000-Mt hard-target counterforce attack, and a 100-Mt attack on cities only): a particle-microphysics model predicts the evolution of the dust and smoke particles; and a radiative-convective climate model estimates the effects of the dust and smoke clouds on the global radiation budget. The findings are presented in graphs, diagrams, and a table. Thick clouds blocking most sunlight over the Northern Hemisphere midlatitudes for weeks or months and producing ground-temperature reductions of 20-40 C, disruption of global circulation patterns, and rapid spread of clouds to the Southern Hemisphere are among the 'nuclear-winter' effects predicted for the 5,000-Mt baseline case. The catastrophic consequences for plant, animal, and human populations are considered, and the revision of superpower nuclear strategies is urged.

A neuronal model of a global workspace in effortful cognitive tasks.

PubMed

Dehaene, S; Kerszberg, M; Changeux, J P

1998-11-24

A minimal hypothesis is proposed concerning the brain processes underlying effortful tasks. It distinguishes two main computational spaces: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative, and attentional processors. Workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice. They selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously coactivated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. We outline predictions for spatio-temporal activation patterns during brain imaging, particularly about the contribution of dorsolateral prefrontal cortex and anterior cingulate to the workspace.

Arabidopsis roots and shoots show distinct temporal adaptation patterns toward nitrogen starvation.

PubMed

Krapp, Anne; Berthomé, Richard; Orsel, Mathilde; Mercey-Boutet, Stéphanie; Yu, Agnes; Castaings, Loren; Elftieh, Samira; Major, Hilary; Renou, Jean-Pierre; Daniel-Vedele, Françoise

2011-11-01

Nitrogen (N) is an essential macronutrient for plants. N levels in soil vary widely, and plants have developed strategies to cope with N deficiency. However, the regulation of these adaptive responses and the coordinating signals that underlie them are still poorly understood. The aim of this study was to characterize N starvation in adult Arabidopsis (Arabidopsis thaliana) plants in a spatiotemporal manner by an integrative, multilevel global approach analyzing growth, metabolites, enzyme activities, and transcript levels. We determined that the remobilization of N and carbon compounds to the growing roots occurred long before the internal N stores became depleted. A global metabolite analysis by gas chromatography-mass spectrometry revealed organ-specific differences in the metabolic adaptation to complete N starvation, for example, for several tricarboxylic acid cycle intermediates, but also for carbohydrates, secondary products, and phosphate. The activities of central N metabolism enzymes and the capacity for nitrate uptake adapted to N starvation by favoring N remobilization and by increasing the high-affinity nitrate uptake capacity after long-term starvation. Changes in the transcriptome confirmed earlier studies and added a new dimension by revealing specific spatiotemporal patterns and several unknown N starvation-regulated genes, including new predicted small RNA genes. No global correlation between metabolites, enzyme activities, and transcripts was evident. However, this multilevel spatiotemporal global study revealed numerous new patterns of adaptation mechanisms to N starvation. In the context of a sustainable agriculture, this work will give new insight for the production of crops with increased N use efficiency.

Diffusion of knowledge and globalization in the web of twentieth century science

NASA Astrophysics Data System (ADS)

Naumis, G. G.; Phillips, J. C.

2012-08-01

Scientific communication is an essential part of modern science: whereas Archimedes worked alone, Newton (correspondence with Hooke, 1676) acknowledged that “If I have seen a little further, it is by standing on the shoulders of Giants.” How is scientific communication reflected in the patterns of citations in scientific papers? How have these patterns changed in the 20th century, as both means of communication and individual transportation changed rapidly, compared to the earlier post-Newton 18th and 19th centuries? Here we discuss a diffusive model for scientific communications, based on a unique 2009 scientometric study of 25 million papers and 600 million citations that encapsulates the epistemology of modern science. The diffusive model predicts and explains, using no adjustable parameters, a surprisingly universal internal structure in the development of scientific research, which is essentially constant across the natural sciences, but which because of globalization changed qualitatively around 1960. Globalization corresponds physically to anomalous diffusion, which has been observed near the molecular glass transition, and can enhance molecular diffusion by factors as large as 100.

Climate-driven range shifts explain the distribution of extant gene pools and predict future loss of unique lineages in a marine brown alga.

PubMed

Assis, J; Serrão, E A; Claro, B; Perrin, C; Pearson, G A

2014-06-01

The climate-driven dynamics of species ranges is a critical research question in evolutionary ecology. We ask whether present intraspecific diversity is determined by the imprint of past climate. This is an ongoing debate requiring interdisciplinary examination of population genetic pools and persistence patterns across global ranges. Previously, contrasting inferences and predictions have resulted from distinct genomic coverage and/or geographical information. We aim to describe and explain the causes of geographical contrasts in genetic diversity and their consequences for the future baseline of the global genetic pool, by comparing present geographical distribution of genetic diversity and differentiation with predictive species distribution modelling (SDM) during past extremes, present time and future climate scenarios for a brown alga, Fucus vesiculosus. SDM showed that both atmospheric and oceanic variables shape the global distribution of intertidal species, revealing regions of persistence, extinction and expansion during glacial and postglacial periods. These explained the distribution and structure of present genetic diversity, consisting of differentiated genetic pools with maximal diversity in areas of long-term persistence. Most of the present species range comprises postglacial expansion zones and, in contrast to highly dispersive marine organisms, expansions involved only local fronts, leaving distinct genetic pools at rear edges. Besides unravelling a complex phylogeographical history and showing congruence between genetic diversity and persistent distribution zones, supporting the hypothesis of niche conservatism, range shifts and loss of unique genetic diversity at the rear edge were predicted for future climate scenarios, impoverishing the global gene pool. © 2014 John Wiley & Sons Ltd.

Spatial modeling of agricultural land use change at global scale

NASA Astrophysics Data System (ADS)

Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

2014-11-01

Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling communities.

Structure of high latitude currents in global magnetospheric-ionospheric models

USGS Publications Warehouse

Wiltberger, M; Rigler, E. J.; Merkin, V; Lyon, J. G

2016-01-01

Using three resolutions of the Lyon-Fedder-Mobarry global magnetosphere-ionosphere model (LFM) and the Weimer 2005 empirical model we examine the structure of the high latitude field-aligned current patterns. Each resolution was run for the entire Whole Heliosphere Interval which contained two high speed solar wind streams and modest interplanetary magnetic field strengths. Average states of the field-aligned current (FAC) patterns for 8 interplanetary magnetic field clock angle directions are computed using data from these runs. Generally speaking the patterns obtained agree well with results obtained from the Weimer 2005 computing using the solar wind and IMF conditions that correspond to each bin. As the simulation resolution increases the currents become more intense and narrow. A machine learning analysis of the FAC patterns shows that the ratio of Region 1 (R1) to Region 2 (R2) currents decreases as the simulation resolution increases. This brings the simulation results into better agreement with observational predictions and the Weimer 2005 model results. The increase in R2 current strengths also results in the cross polar cap potential (CPCP) pattern being concentrated in higher latitudes. Current-voltage relationships between the R1 and CPCP are quite similar at the higher resolution indicating the simulation is converging on a common solution. We conclude that LFM simulations are capable of reproducing the statistical features of FAC patterns.

fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli.

PubMed

Alink, Arjen; Krugliak, Alexandra; Walther, Alexander; Kriegeskorte, Nikolaus

2013-01-01

The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability might alternatively arise from global orientation-preference maps. Such global maps across V1 could result from bottom-up processing, if the preferences of V1 neurons were biased toward particular orientations (e.g., radial from fixation, or cardinal, i.e., vertical or horizontal). Global maps could also arise from local recurrent or top-down processing, reflecting pre-attentive perceptual grouping, attention spreading, or predictive coding of global form. Here we investigate whether fMRI orientation decoding with 2-mm voxels requires (a) globally coherent orientation stimuli and/or (b) global-scale patterns of V1 activity. We used opposite-orientation gratings (balanced about the cardinal orientations) and spirals (balanced about the radial orientation), along with novel patch-swapped variants of these stimuli. The two stimuli of a patch-swapped pair have opposite orientations everywhere (like their globally coherent parent stimuli). However, the two stimuli appear globally similar, a patchwork of opposite orientations. We find that all stimulus pairs are robustly decodable, demonstrating that fMRI orientation decoding does not require globally coherent orientation stimuli. Furthermore, decoding remained robust after spatial high-pass filtering for all stimuli, showing that fine-grained components of the fMRI patterns reflect visual orientations. Consistent with previous studies, we found evidence for global radial and vertical preference maps in V1. However, these were weak or absent for patch-swapped stimuli, suggesting that global preference maps depend on globally coherent orientations and might arise through recurrent or top-down processes related to the perception of global form.

Two-dimensional wave patterns of spreading depolarization: Retracting, re-entrant, and stationary waves

NASA Astrophysics Data System (ADS)

Dahlem, Markus A.; Graf, Rudolf; Strong, Anthony J.; Dreier, Jens P.; Dahlem, Yuliya A.; Sieber, Michaela; Hanke, Wolfgang; Podoll, Klaus; Schöll, Eckehard

2010-06-01

We present spatio-temporal characteristics of spreading depolarizations (SD) in two experimental systems: retracting SD wave segments observed with intrinsic optical signals in chicken retina, and spontaneously occurring re-entrant SD waves that repeatedly spread across gyrencephalic feline cortex observed by laser speckle flowmetry. A mathematical framework of reaction-diffusion systems with augmented transmission capabilities is developed to explain the emergence and transitions between these patterns. Our prediction is that the observed patterns are reaction-diffusion patterns controlled and modulated by weak nonlocal coupling such as long-range, time-delayed, and global coupling. The described spatio-temporal characteristics of SD are of important clinical relevance under conditions of migraine and stroke. In stroke, the emergence of re-entrant SD waves is believed to worsen outcome. In migraine, retracting SD wave segments cause neurological symptoms and transitions to stationary SD wave patterns may cause persistent symptoms without evidence from noninvasive imaging of infarction.

Population genetic structure and natural selection of Plasmodium falciparum apical membrane antigen-1 in Myanmar isolates.

PubMed

Kang, Jung-Mi; Lee, Jinyoung; Moe, Mya; Jun, Hojong; Lê, Hương Giang; Kim, Tae Im; Thái, Thị Lam; Sohn, Woon-Mok; Myint, Moe Kyaw; Lin, Khin; Shin, Ho-Joon; Kim, Tong-Soo; Na, Byoung-Kuk

2018-02-07

Plasmodium falciparum apical membrane antigen-1 (PfAMA-1) is one of leading blood stage malaria vaccine candidates. However, genetic variation and antigenic diversity identified in global PfAMA-1 are major hurdles in the development of an effective vaccine based on this antigen. In this study, genetic structure and the effect of natural selection of PfAMA-1 among Myanmar P. falciparum isolates were analysed. Blood samples were collected from 58 Myanmar patients with falciparum malaria. Full-length PfAMA-1 gene was amplified by polymerase chain reaction and cloned into a TA cloning vector. PfAMA-1 sequence of each isolate was sequenced. Polymorphic characteristics and effect of natural selection were analysed with using DNASTAR, MEGA4, and DnaSP programs. Polymorphic nature and natural selection in 459 global PfAMA-1 were also analysed. Thirty-seven different haplotypes of PfAMA-1 were identified in 58 Myanmar P. falciparum isolates. Most amino acid changes identified in Myanmar PfAMA-1 were found in domains I and III. Overall patterns of amino acid changes in Myanmar PfAMA-1 were similar to those in global PfAMA-1. However, frequencies of amino acid changes differed by country. Novel amino acid changes in Myanmar PfAMA-1 were also identified. Evidences for natural selection and recombination event were observed in global PfAMA-1. Among 51 commonly identified amino acid changes in global PfAMA-1 sequences, 43 were found in predicted RBC-binding sites, B-cell epitopes, or IUR regions. Myanmar PfAMA-1 showed similar patterns of nucleotide diversity and amino acid polymorphisms compared to those of global PfAMA-1. Balancing natural selection and intragenic recombination across PfAMA-1 are likely to play major roles in generating genetic diversity in global PfAMA-1. Most common amino acid changes in global PfAMA-1 were located in predicted B-cell epitopes where high levels of nucleotide diversity and balancing natural selection were found. These results highlight the strong selective pressure of host immunity on the PfAMA-1 gene. These results have significant implications in understanding the nature of Myanmar PfAMA-1 along with global PfAMA-1. They also provide useful information for the development of effective malaria vaccine based on this antigen.

Food transitions in last 50 years and related environmental implications

NASA Astrophysics Data System (ADS)

Pradhan, P.; Reusser, D. E.; Kropp, J. P.

2012-04-01

Food production is an important driver for global change processes such as land use change and green-house-gas emissions. We analyzed a global, long term data set on food consumption per country to identify typical patterns of diets for the last 50 years. From changes in these patterns, we derived food transitions on a global scale. Subsequently we assessed the environmental consequences from green-house-gas (GHG) emission and anthropogenic inputs. More specifically, we applied Self Organizing Maps (SOM) to identify the dietary patterns based on supply of 12 food groups from FAOSTAT dataset for a period 1961-2007. Using the data on energy output/input ratio for crop production and agricultural emission, we estimated fossil energy and GHG emission associated with the diets. We found 16 typical consumption patterns consisting of high, moderate, low and lowest calorie supply with varied food compositions. The high calorie diets are associated with a higher supply of cereals, animal-products, vegetable-oils and sugar-sweeteners featuring a total supply greater than 2800 kcal/cap/day. During the last 50 years, we observed food transitions from lower calories diets to higher calories diets. On the one hand, food transition towards affluent diet, sometime with shortcuts, occurred in developing countries. On the other hand, developed countries increased consumption of fruits and vegetables. Some of the developing countries are also stagnated in the low consumption level during the last 50 years. The high calorie diets also embed higher fossil energy (1800-3500 kcal/cap/day) and are associated with higher GHG emissions (3.7-6.1 kg CO2 eq/cap/day). However, their non-CO2 GHG emission intensities per kilo calorie of food are relatively low. Changes in dietary patterns are a part of the global change processes. Identification of past transitions is way to predict possible future transitions. This in turn supports policy processes and negotiations in the fields of climate change, water management and development goals.

Global Warming on Triton

NASA Technical Reports Server (NTRS)

Elliot, J. L.; Hammel, H. B.; Wasserman, L. H.; Franz, O. G.; McDonald, S. W.; Person, M. J.; Olkin, C. B.; Dunham, E. J.; Spencer, J. R.; Stansberry, J. A.;

Fifty Years of Water Cycle Change expressed in Ocean Salinity

NASA Astrophysics Data System (ADS)

Durack, P. J.; Wijffels, S.

2010-12-01

Using over 1.6 million profiles of salinity, potential temperature and density from historical archives and Argo, we derive the global field of linear change for ocean state properties over the period 1950-2008, taking care to minimise aliasing associated with seasonal and El Nino Southern Oscillation modes. We find large, robust and spatially coherent multi-decadal linear trends in ocean surface salinities. Increases are found in evaporation-dominated regions and freshening in precipitation-dominated regions. The spatial patterns of surface change strongly resemble the climatological mean surface salinity field, consistent with an amplification of the global water cycle. A robust amplification of the mean salinity pattern of 8% (to 200m depth) is found globally and 5-9% is found in each of the 3 key ocean basins. 20th century runs from the CMIP3 model suite support the relationship between amplified patterns of freshwater flux driving an amplified pattern of ocean surface salinity only in models that warm substantially. Models with volcanic aerosols show a diminished warming response and a corresponding weak response in ocean surface salinity change, which implies dampened changes to the global water cycle. The warming response represented in realistic (when compared to observations) 20th century simulations appear quite similar in their broad zonal patterns to those of the projected 21st century simulations, these projected runs being strongly forced by greenhouse gases. This pattern amplification is mostly absent from 20th century simulations which include volcanic forcing. While we confirm that global mean precipitation only weakly change with surface warming (2-3% K-1), the pattern amplification rate in both the freshwater flux and ocean salinity fields indicate larger responses. Our new observed salinity estimates suggest a change of between 8-16% K-1, close to, or greater than, the theoretical response described by the Clausius-Clapeyron relation. The underestimation of change patterns by the CMIP3 model suite is well documented in recent literature describing changes to the atmospheric and terrestrial arms of the global water cycle. These new observational ocean results add emphasis to the conclusion that the rate of observed changes in the 20th century are larger than CMIP3 models, and simplified physical theories predict. A) The 50-year linear surface salinity trend (pss/50-years). Contours every 0.25 pss are plotted in white. B) Ocean-atmosphere freshwater flux (m3 yr-1) averaged over 1980-1993 (Josey et al., 1998). Contours every 1 m3 yr-1 are in white. On both panels, the 1975 surface mean salinity is contoured black (contour interval 0.5 pss for thin lines, 1 for thick lines).

Large-scale solar magnetic fields and H-alpha patterns

NASA Technical Reports Server (NTRS)

Mcintosh, P. S.

1972-01-01

Coronal and interplanetary magnetic fields computed from measurements of large-scale photospheric magnetic fields suffer from interruptions in day-to-day observations and the limitation of using only measurements made near the solar central meridian. Procedures were devised for inferring the lines of polarity reversal from H-alpha solar patrol photographs that map the same large-scale features found on Mt. Wilson magnetograms. These features may be monitored without interruption by combining observations from the global network of observatories associated with NOAA's Space Environment Services Center. The patterns of inferred magnetic fields may be followed accurately as far as 60 deg from central meridian. Such patterns will be used to improve predictions of coronal features during the next solar eclipse.

Statistical-mechanical analysis of self-organization and pattern formation during the development of visual maps

NASA Astrophysics Data System (ADS)

Obermayer, K.; Blasdel, G. G.; Schulten, K.

1992-05-01

We report a detailed analytical and numerical model study of pattern formation during the development of visual maps, namely, the formation of topographic maps and orientation and ocular dominance columns in the striate cortex. Pattern formation is described by a stimulus-driven Markovian process, the self-organizing feature map. This algorithm generates topologically correct maps between a space of (visual) input signals and an array of formal ``neurons,'' which in our model represents the cortex. We define order parameters that are a function of the set of visual stimuli an animal perceives, and we demonstrate that the formation of orientation and ocular dominance columns is the result of a global instability of the retinoptic projection above a critical value of these order parameters. We characterize the spatial structure of the emerging patterns by power spectra, correlation functions, and Gabor transforms, and we compare model predictions with experimental data obtained from the striate cortex of the macaque monkey with optical imaging. Above the critical value of the order parameters the model predicts a lateral segregation of the striate cortex into (i) binocular regions with linear changes in orientation preference, where iso-orientation slabs run perpendicular to the ocular dominance bands, and (ii) monocular regions with low orientation specificity, which contain the singularities of the orientation map. Some of these predictions have already been verified by experiments.

Net Primary Production of Terrestrial Ecosystems from 2000 to 2009

NASA Technical Reports Server (NTRS)

Potter, Christopher; Klooster, Steven; Genovese, Vanessa

2012-01-01

The CASA (Carnegie-Ames-Stanford) ecosystem model has been used to estimate monthly carbon fluxes in terrestrial ecosystems from 2000 to 2009, with global data inputs from NASA's Terra Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation cover mapping. Net primary production (NPP) flux for atmospheric carbon dioxide has varied slightly from year-to-year, but was predicted to have increased over short multi-year periods in the regions of the high-latitude Northern Hemisphere, South Asia, Central Africa, and the western Amazon since the year 2000. These CASA results for global NPP were found to be in contrast to other recently published modeling trends for terrestrial NPP with high sensitivity to regional drying patterns. Nonetheless, periodic declines in regional NPP were predicted by CASA for the southern and western Untied States, the southern Amazon, and southern and eastern Africa. NPP in tropical forest zones was examined in greater detail to discover lower annual production values than previously reported in many global models across the tropical rainforest zones, likely due to the enhanced detection of lower production ecosystems replacing primary rainforest.

THE DYNAMICAL RELATIONSHIP BETWEEN THE BAR AND SPIRAL PATTERNS OF NGC 1365

DOE Office of Scientific and Technical Information (OSTI.GOV)

Speights, Jason C.; Rooke, Paul C., E-mail: jcspeights@frostburg.edu

2016-07-20

Theories that attempt to explain the dynamical relationship between bar and spiral patterns in galactic disks make different predictions about the radial profile of the pattern speed. These are tested for the H-alpha bar and spiral patterns of NGC 1365. The radial profile of the pattern speed is measured by fitting mathematical models that are based on the Tremaine–Weinberg method. The results show convincing evidence for the bar rotating at a faster rate than the spiral pattern, inconsistent with a global wave mode or a manifold. There is evidence for mode coupling of the bar and spiral patterns at themore » overlap of corotation and inner Lindblad resonances (ILRs), but the evidence is unreliable and inconsistent. The results are the most consistent with the bar and spiral patterns being dynamically distinct features. The pattern speed of the bar begins near an ILR and ends near the corotation resonance (CR). The radial profile of the pattern speed beyond the bar most closely resembles what is expected for coupled spiral modes and tidal interactions.« less

Global trends and patterns of commercial milk-based formula sales: is an unprecedented infant and young child feeding transition underway?

PubMed

Baker, Phillip; Smith, Julie; Salmon, Libby; Friel, Sharon; Kent, George; Iellamo, Alessandro; Dadhich, J P; Renfrew, Mary J

2016-10-01

The marketing of infant/child milk-based formulas (MF) contributes to suboptimal breast-feeding and adversely affects child and maternal health outcomes globally. However, little is known about recent changes in MF markets. The present study describes contemporary trends and patterns of MF sales at the global, regional and country levels. Descriptive statistics of trends and patterns in MF sales volume per infant/child for the years 2008-2013 and projections to 2018, using industry-sourced data. Eighty countries categorized by country income bracket, for developing countries by region, and in countries with the largest infant/child populations. MF categories included total (for ages 0-36 months), infant (0-6 months), follow-up (7-12 months), toddler (13-36 months) and special (0-6 months). In 2008-2013 world total MF sales grew by 40·8 % from 5·5 to 7·8 kg per infant/child/year, a figure predicted to increase to 10·8 kg by 2018. Growth was most rapid in East Asia particularly in China, Indonesia, Thailand and Vietnam and was led by the infant and follow-up formula categories. Sales volume per infant/child was positively associated with country income level although with wide variability between countries. A global infant and young child feeding (IYCF) transition towards diets higher in MF is underway and is expected to continue apace. The observed increase in MF sales raises serious concern for global child and maternal health, particularly in East Asia, and calls into question the efficacy of current regulatory regimes designed to protect and promote optimal IYCF. The observed changes have not been captured by existing IYCF monitoring systems.

A Simple Climate Model Program for High School Education

NASA Astrophysics Data System (ADS)

Dommenget, D.

2012-04-01

The future climate change projections of the IPCC AR4 are based on GCM simulations, which give a distinct global warming pattern, with an arctic winter amplification, an equilibrium land sea contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the IPCC predictions, the conceptual understanding of these predicted structures of climate change are very difficult to reach if only based on these highly complex GCM simulations and they are not accessible for ordinary people. In this study presented here we will introduce a very simple gridded globally resolved energy balance model based on strongly simplified physical processes, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the 1-dimensional energy balance models and the fully coupled 4-dimensional complex GCMs. It runs on standard PC computers computing globally resolved climate simulation with 2yrs per second or 100,000yrs per day. The program can compute typical global warming scenarios in a few minutes on a standard PC. The computer code is only 730 line long with very simple formulations that high school students should be able to understand. The simple model's climate sensitivity and the spatial structure of the warming pattern is within the uncertainties of the IPCC AR4 models simulations. It is capable of simulating the arctic winter amplification, the equilibrium land sea contrast and the inter-hemispheric warming gradient with good agreement to the IPCC AR4 models in amplitude and structure. The program can be used to do sensitivity studies in which students can change something (e.g. reduce the solar radiation, take away the clouds or make snow black) and see how it effects the climate or the climate response to changes in greenhouse gases. This program is available for every one and could be the basis for high school education. Partners for a high school project are wanted!

White matter tract covariance patterns predict age-declining cognitive abilities.

PubMed

Gazes, Yunglin; Bowman, F DuBois; Razlighi, Qolamreza R; O'Shea, Deirdre; Stern, Yaakov; Habeck, Christian

2016-01-15

Previous studies investigating the relationship of white matter (WM) integrity to cognitive abilities and aging have either focused on a global measure or a few selected WM tracts. Ideally, contribution from all of the WM tracts should be evaluated at the same time. However, the high collinearity among WM tracts precludes systematic examination of WM tracts simultaneously without sacrificing statistical power due to stringent multiple-comparison corrections. Multivariate covariance techniques enable comprehensive simultaneous examination of all WM tracts without being penalized for high collinearity among observations. In this study, Scaled Subprofile Modeling (SSM) was applied to the mean integrity of 18 major WM tracts to extract covariance patterns that optimally predicted four cognitive abilities (perceptual speed, episodic memory, fluid reasoning, and vocabulary) in 346 participants across ages 20 to 79years old. Using expression of the covariance patterns, age-independent effects of white matter integrity on cognition and the indirect effect of WM integrity on age-related differences in cognition were tested separately, but inferences from the indirect analyses were cautiously made given that cross-sectional data set was used in the analysis. A separate covariance pattern was identified that significantly predicted each cognitive ability after controlling for age except for vocabulary, but the age by WM covariance pattern interaction was not significant for any of the three abilities. Furthermore, each of the patterns mediated the effect of age on the respective cognitive ability. A distinct set of WM tracts was most influential in each of the three patterns. The WM covariance pattern accounting for fluid reasoning showed the most number of influential WM tracts whereas the episodic memory pattern showed the least number. Specific patterns of WM tracts make significant contributions to the age-related differences in perceptual speed, episodic memory, and fluid reasoning but not vocabulary. Other measures of brain health will need to be explored to reveal the major influences on the vocabulary ability. Copyright © 2015 Elsevier Inc. All rights reserved.

Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach.

PubMed

Domnich, Alexander; Arata, Lucia; Amicizia, Daniela; Signori, Alessio; Gasparini, Roberto; Panatto, Donatella

2016-11-16

Geographical accessibility is an important determinant for the utilisation of community pharmacies. The present study explored patterns of spatial accessibility with respect to pharmacies in Liguria, Italy, a region with particular geographical and demographic features. Municipal density of pharmacies was proxied as the number of pharmacies per capita and per km2, and spatial autocorrelation analysis was performed to identify spatial clusters. Both non-spatial and spatial models were constructed to predict the study outcome. Spatial autocorrelation analysis showed a highly significant clustered pattern in the density of pharmacies per capita (I=0.082) and per km2 (I=0.295). Potentially under-supplied areas were mostly located in the mountainous hinterland. Ordinary least-squares (OLS) regressions established a significant positive relationship between the density of pharmacies and income among municipalities located at high altitudes, while no such association was observed in lower-lying areas. However, residuals of the OLS models were spatially auto-correlated. The best-fitting mixed geographically weighted regression (GWR) models outperformed the corresponding OLS models. Pharmacies per capita were best predicted by two local predictors (altitude and proportion of immigrants) and two global ones (proportion of elderly residents and income), while the local terms population, mean altitude and rural status and the global term income functioned as independent variables predicting pharmacies per km2. The density of pharmacies in Liguria was found to be associated with both socio-economic and landscape factors. Mapping of mixed GWR results would be helpful to policy-makers.

Predicting features of breast cancer with gene expression patterns.

PubMed

Lu, Xuesong; Lu, Xin; Wang, Zhigang C; Iglehart, J Dirk; Zhang, Xuegong; Richardson, Andrea L

2008-03-01

Data from gene expression arrays hold an enormous amount of biological information. We sought to determine if global gene expression in primary breast cancers contained information about biologic, histologic, and anatomic features of the disease in individual patients. Microarray data from the tumors of 129 patients were analyzed for the ability to predict biomarkers [estrogen receptor (ER) and HER2], histologic features [grade and lymphatic-vascular invasion (LVI)], and stage parameters (tumor size and lymph node metastasis). Multiple statistical predictors were used and the prediction accuracy was determined by cross-validation error rate; multidimensional scaling (MDS) allowed visualization of the predicted states under study. Models built from gene expression data accurately predict ER and HER2 status, and divide tumor grade into high-grade and low-grade clusters; intermediate-grade tumors are not a unique group. In contrast, gene expression data is inaccurate at predicting tumor size, lymph node status or LVI. The best model for prediction of nodal status included tumor size, LVI status and pathologically defined tumor subtype (based on combinations of ER, HER2, and grade); the addition of microarray-based prediction to this model failed to improve the prediction accuracy. Global gene expression supports a binary division of ER, HER2, and grade, clearly separating tumors into two categories; intermediate values for these bio-indicators do not define intermediate tumor subsets. Results are consistent with a model of regional metastasis that depends on inherent biologic differences in metastatic propensity between breast cancer subtypes, upon which time and chance then operate.

Hierarchical Learning Induces Two Simultaneous, But Separable, Prediction Errors in Human Basal Ganglia

PubMed Central

Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew

2013-01-01

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously. PMID:23536092

Combined effects of the Pacific Decadal Oscillation and El Niño-Southern Oscillation on global land dry-wet changes.

PubMed

Wang, Shanshan; Huang, Jianping; He, Yongli; Guan, Yuping

2014-10-17

The effects of natural variability, especially El Niño-Southern Oscillation (ENSO) effects, have been the focus of several recent studies on the change of drought patterns with climate change. The interannual relationship between ENSO and the global climate is not stationary and can be modulated by the Pacific Decadal Oscillation (PDO). However, the global land distribution of the dry-wet changes associated with the combination of ENSO and the PDO remains unclear. In the present study, this is investigated using a revised Palmer Drought Severity Index dataset (sc_PDSI_pm). We find that the effect of ENSO on dry-wet changes varies with the PDO phase. When in phase with the PDO, ENSO-induced dry-wet changes are magnified with respect to the canonical pattern. When out of phase, these dry-wet variations weaken or even disappear. This remarkable contrast in ENSO's influence between the two phases of the PDO highlights exciting new avenues for obtaining improved global climate predictions. In recent decades, the PDO has turned negative with more La Niña events, implying more rain and flooding over land. La Niña-induced wet areas become wetter and the dry areas become drier and smaller due to the effects of the cold PDO phase.

Defaunation in the Anthropocene.

PubMed

Dirzo, Rodolfo; Young, Hillary S; Galetti, Mauro; Ceballos, Gerardo; Isaac, Nick J B; Collen, Ben

2014-07-25

We live amid a global wave of anthropogenically driven biodiversity loss: species and population extirpations and, critically, declines in local species abundance. Particularly, human impacts on animal biodiversity are an under-recognized form of global environmental change. Among terrestrial vertebrates, 322 species have become extinct since 1500, and populations of the remaining species show 25% average decline in abundance. Invertebrate patterns are equally dire: 67% of monitored populations show 45% mean abundance decline. Such animal declines will cascade onto ecosystem functioning and human well-being. Much remains unknown about this "Anthropocene defaunation"; these knowledge gaps hinder our capacity to predict and limit defaunation impacts. Clearly, however, defaunation is both a pervasive component of the planet's sixth mass extinction and also a major driver of global ecological change. Copyright © 2014, American Association for the Advancement of Science.

Impacts of climate change on distributions and diversity of ungulates on the Tibetan Plateau.

PubMed

Luo, Zhenhua; Jiang, Zhigang; Tang, Songhua

2015-01-01

Climate change has significant impacts on species' distributions and diversity patterns. Understanding range shifts and changes in richness gradients under climate change is crucial for conservation. The Tibetan Plateau, home to wild yak, chiru, and kiang, contains a biome with many endemic ungulates. It is highly sensitive to climate change and a region that merits particular attention with regard to the impacts of global climate change on its biomes. Maximum entropy approaches were used to estimate current and future potential distributions, in response to climate change, for 22 ungulate species. We used three general circulation (MK3, HADCM3, MIROC3_2-MED) and three emissions scenarios (Bl, A1B, A2) to derive estimated future measurements of 14 environmental variables over three time periods (2020, 2050, 2080), and then modeled species distributions using these predicted environmental measurements for each time period under two dispersal hypotheses (full and zero, respectively). This resulted in a total of 6160 prediction models. We found that these ungulates, on average, may lose 30-50% of their distributional areas, depending on the dispersal scenarios. In addition, 55-68% of the ungulate species were predicted to become locally endangered under the different dispersal assumptions, 23-32% to become locally critically endangered, and 4-7 endemic species to become globally endangered. Furthermore, ungulate species ranges may experience average poleward shifts of ~300 km. We also predict west-to-east reductions in species richness: southeastern mountainous areas currently have the highest species richness, but are predicted to face the greatest diversity losses, whereas the northern areas are predicted to see increasing numbers of ungulate species in the 21st century. Our study indicates much more severe range reductions of ungulates on the Tibetan Plateau than those anticipated elsewhere in the world, and species richness patterns will change dramatically with climate change. For conservation, we suggest (1) securing existing protected areas, and (2) establishing new nature reserves to counterbalance climate change impacts.

Modeling late rectal toxicities based on a parameterized representation of the 3D dose distribution

NASA Astrophysics Data System (ADS)

Buettner, Florian; Gulliford, Sarah L.; Webb, Steve; Partridge, Mike

2011-04-01

Many models exist for predicting toxicities based on dose-volume histograms (DVHs) or dose-surface histograms (DSHs). This approach has several drawbacks as firstly the reduction of the dose distribution to a histogram results in the loss of spatial information and secondly the bins of the histograms are highly correlated with each other. Furthermore, some of the complex nonlinear models proposed in the past lack a direct physical interpretation and the ability to predict probabilities rather than binary outcomes. We propose a parameterized representation of the 3D distribution of the dose to the rectal wall which explicitly includes geometrical information in the form of the eccentricity of the dose distribution as well as its lateral and longitudinal extent. We use a nonlinear kernel-based probabilistic model to predict late rectal toxicity based on the parameterized dose distribution and assessed its predictive power using data from the MRC RT01 trial (ISCTRN 47772397). The endpoints under consideration were rectal bleeding, loose stools, and a global toxicity score. We extract simple rules identifying 3D dose patterns related to a specifically low risk of complication. Normal tissue complication probability (NTCP) models based on parameterized representations of geometrical and volumetric measures resulted in areas under the curve (AUCs) of 0.66, 0.63 and 0.67 for predicting rectal bleeding, loose stools and global toxicity, respectively. In comparison, NTCP models based on standard DVHs performed worse and resulted in AUCs of 0.59 for all three endpoints. In conclusion, we have presented low-dimensional, interpretable and nonlinear NTCP models based on the parameterized representation of the dose to the rectal wall. These models had a higher predictive power than models based on standard DVHs and their low dimensionality allowed for the identification of 3D dose patterns related to a low risk of complication.

Modelling fast spreading patterns of airborne infectious diseases using complex networks

NASA Astrophysics Data System (ADS)

Brenner, Frank; Marwan, Norbert; Hoffmann, Peter

2017-04-01

The pandemics of SARS (2002/2003) and H1N1 (2009) have impressively shown the potential of epidemic outbreaks of infectious diseases in a world that is strongly connected. Global air travelling established an easy and fast opportunity for pathogens to migrate globally in only a few days. This made epidemiological prediction harder. By understanding this complex development and its link to climate change we can suggest actions to control a part of global human health affairs. In this study we combine the following data components to simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human: em{Global Air Traffic Network (from openflights.org) with information on airports, airport location, direct flight connection, airplane type} em{Global population dataset (from SEDAC, NASA)} em{Susceptible-Infected-Recovered (SIR) compartmental model to simulate disease spreading in the vicinity of airports. A modified Susceptible-Exposed-Infected-Recovered (SEIR) model to analyze the impact of the incubation period.} em{WATCH-Forcing-Data-ERA-Interim (WFDEI) climate data: temperature, specific humidity, surface air pressure, and water vapor pressure} These elements are implemented into a complex network. Nodes inside the network represent airports. Each single node is equipped with its own SIR/SEIR compartmental model with node specific attributes. Edges between those nodes represent direct flight connections that allow infected individuals to move between linked nodes. Therefore the interaction of the set of unique SIR models creates the model dynamics we will analyze. To better figure out the influence on climate change on disease spreading patterns, we focus on Influenza-like-Illnesses (ILI). The transmission rate of ILI has a dependency on climate parameters like humidity and temperature. Even small changes of environmental variables can trigger significant differences in the global outbreak behavior. Apart from the direct effect of climate change on the transmission of airborne diseases, there are indirect ramifications that alter spreading patterns. An example is seasonal human mobility behavior which will change with varied climate conditions. The direct and indirect effects of climate change on disease spreading patterns will be discussed in this study.

Beyond Corroboration: Strengthening Model Validation by Looking for Unexpected Patterns

PubMed Central

Chérel, Guillaume; Cottineau, Clémentine; Reuillon, Romain

2015-01-01

Models of emergent phenomena are designed to provide an explanation to global-scale phenomena from local-scale processes. Model validation is commonly done by verifying that the model is able to reproduce the patterns to be explained. We argue that robust validation must not only be based on corroboration, but also on attempting to falsify the model, i.e. making sure that the model behaves soundly for any reasonable input and parameter values. We propose an open-ended evolutionary method based on Novelty Search to look for the diverse patterns a model can produce. The Pattern Space Exploration method was tested on a model of collective motion and compared to three common a priori sampling experiment designs. The method successfully discovered all known qualitatively different kinds of collective motion, and performed much better than the a priori sampling methods. The method was then applied to a case study of city system dynamics to explore the model’s predicted values of city hierarchisation and population growth. This case study showed that the method can provide insights on potential predictive scenarios as well as falsifiers of the model when the simulated dynamics are highly unrealistic. PMID:26368917

Relative sea-level changes and crustal movements in Britain and Ireland since the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Shennan, Ian; Bradley, Sarah L.; Edwards, Robin

2018-05-01

The new sea-level database for Britain and Ireland contains >2100 data points from 86 regions and records relative sea-level (RSL) changes over the last 20 ka and across elevations ranging from ∼+40 to -55 m. It reveals radically different patterns of RSL as we move from regions near the centre of the Celtic ice sheet at the last glacial maximum to regions near and beyond the ice limits. Validated sea-level index points and limiting data show good agreement with the broad patterns of RSL change predicted by current glacial isostatic adjustment (GIA) models. The index points show no consistent pattern of synchronous coastal advance and retreat across different regions, ∼100-500 km scale, indicating that within-estuary processes, rather than decimetre- and centennial-scale oscillations in sea level, produce major controls on the temporal pattern of horizontal shifts in coastal sedimentary environments. Comparisons between the database and GIA model predictions for multiple regions provide potentially powerful constraints on various characteristics of global GIA models, including the magnitude of MWP1A, the final deglaciation of the Laurentide ice sheet and the continued melting of Antarctica after 7 ka BP.

Complete characterization of the stability of cluster synchronization in complex dynamical networks.

PubMed

Sorrentino, Francesco; Pecora, Louis M; Hagerstrom, Aaron M; Murphy, Thomas E; Roy, Rajarshi

2016-04-01

Synchronization is an important and prevalent phenomenon in natural and engineered systems. In many dynamical networks, the coupling is balanced or adjusted to admit global synchronization, a condition called Laplacian coupling. Many networks exhibit incomplete synchronization, where two or more clusters of synchronization persist, and computational group theory has recently proved to be valuable in discovering these cluster states based on the topology of the network. In the important case of Laplacian coupling, additional synchronization patterns can exist that would not be predicted from the group theory analysis alone. Understanding how and when clusters form, merge, and persist is essential for understanding collective dynamics, synchronization, and failure mechanisms of complex networks such as electric power grids, distributed control networks, and autonomous swarming vehicles. We describe a method to find and analyze all of the possible cluster synchronization patterns in a Laplacian-coupled network, by applying methods of computational group theory to dynamically equivalent networks. We present a general technique to evaluate the stability of each of the dynamically valid cluster synchronization patterns. Our results are validated in an optoelectronic experiment on a five-node network that confirms the synchronization patterns predicted by the theory.

Modeling urbanization patterns at a global scale with generative adversarial networks

NASA Astrophysics Data System (ADS)

Albert, A. T.; Strano, E.; Gonzalez, M.

2017-12-01

Current demographic projections show that, in the next 30 years, global population growth will mostly take place in developing countries. Coupled with a decrease in density, such population growth could potentially double the land occupied by settlements by 2050. The lack of reliable and globally consistent socio-demographic data, coupled with the limited predictive performance underlying traditional urban spatial explicit models, call for developing better predictive methods, calibrated using a globally-consistent dataset. Thus, richer models of the spatial interplay between the urban built-up land, population distribution and energy use are central to the discussion around the expansion and development of cities, and their impact on the environment in the context of a changing climate. In this talk we discuss methods for, and present an analysis of, urban form, defined as the spatial distribution of macroeconomic quantities that characterize a city, using modern machine learning methods and best-available remote-sensing data for the world's largest 25,000 cities. We first show that these cities may be described by a small set of patterns in radial building density, nighttime luminosity, and population density, which highlight, to first order, differences in development and land use across the world. We observe significant, spatially-dependent variance around these typical patterns, which would be difficult to model using traditional statistical methods. We take a first step in addressing this challenge by developing CityGAN, a conditional generative adversarial network model for simulating realistic urban forms. To guide learning and measure the quality of the simulated synthetic cities, we develop a specialized loss function for GAN optimization that incorporates standard spatial statistics used by urban analysis experts. Our framework is a stark departure from both the standard physics-based approaches in the literature (that view urban forms as fractals with a scale-free behavior), and the traditional statistical learning approaches (whereby values of individual pixels are modeled as functions of locally-defined, hand-engineered features). This is a first-of-its-kind analysis of urban forms using data at a planetary scale.

Ecosystem CO2/H2O fluxes are explained by hydraulically limited gas exchange during tree mortality from spruce bark beetles

Treesearch

John M. Frank; William J. Massman; Brent E. Ewers; Laurie S. Huckaby; Jose F. Negron

2014-01-01

Disturbances are increasing globally due to anthropogenic changes in land use and climate. This study determines whether a disturbance that affects the physiology of individual trees can be used to predict the response of the ecosystem by weighing two competing hypothesis at annual time scales: (a) changes in ecosystem fluxes are proportional to observable patterns of...

Changes in potential habitat of 147 North American breeding bird species in response to redistribution of trees and climate following predicted climate change

Treesearch

Stephen N. Matthews; Louis R. Iverson; Anantha M. Prasad; Matthew P. Peters

2011-01-01

Mounting evidence shows that organisms have already begun to respond to global climate change. Advances in our knowledge of how climate shapes species distributional patterns has helped us better understand the response of birds to climate change. However, the distribution of birds across the landscape is also driven by biotic and abiotic components, including habitat...

Filling gaps in large ecological databases: consequences for the study of global-scale plant functional trait patterns

NASA Astrophysics Data System (ADS)

Schrodt, Franziska; Shan, Hanhuai; Fazayeli, Farideh; Karpatne, Anuj; Kattge, Jens; Banerjee, Arindam; Reichstein, Markus; Reich, Peter

2013-04-01

With the advent of remotely sensed data and coordinated efforts to create global databases, the ecological community has progressively become more data-intensive. However, in contrast to other disciplines, statistical ways of handling these large data sets, especially the gaps which are inherent to them, are lacking. Widely used theoretical approaches, for example model averaging based on Akaike's information criterion (AIC), are sensitive to missing values. Yet, the most common way of handling sparse matrices - the deletion of cases with missing data (complete case analysis) - is known to severely reduce statistical power as well as inducing biased parameter estimates. In order to address these issues, we present novel approaches to gap filling in large ecological data sets using matrix factorization techniques. Factorization based matrix completion was developed in a recommender system context and has since been widely used to impute missing data in fields outside the ecological community. Here, we evaluate the effectiveness of probabilistic matrix factorization techniques for imputing missing data in ecological matrices using two imputation techniques. Hierarchical Probabilistic Matrix Factorization (HPMF) effectively incorporates hierarchical phylogenetic information (phylogenetic group, family, genus, species and individual plant) into the trait imputation. Advanced Hierarchical Probabilistic Matrix Factorization (aHPMF) on the other hand includes climate and soil information into the matrix factorization by regressing the environmental variables against residuals of the HPMF. One unique opportunity opened up by aHPMF is out-of-sample prediction, where traits can be predicted for specific species at locations different to those sampled in the past. This has potentially far-reaching consequences for the study of global-scale plant functional trait patterns. We test the accuracy and effectiveness of HPMF and aHPMF in filling sparse matrices, using the TRY database of plant functional traits (http://www.try-db.org). TRY is one of the largest global compilations of plant trait databases (750 traits of 1 million plants), encompassing data on morphological, anatomical, biochemical, phenological and physiological features of plants. However, despite of unprecedented coverage, the TRY database is still very sparse, severely limiting joint trait analyses. Plant traits are the key to understanding how plants as primary producers adjust to changes in environmental conditions and in turn influence them. Forming the basis for Dynamic Global Vegetation Models (DGVMs), plant traits are also fundamental in global change studies for predicting future ecosystem changes. It is thus imperative that missing data is imputed in as accurate and precise a way as possible. In this study, we show the advantages and disadvantages of applying probabilistic matrix factorization techniques in incorporating hierarchical and environmental information for the prediction of missing plant traits as compared to conventional imputation techniques such as the complete case and mean approaches. We will discuss the implications of using gap-filled data for global-scale studies of plant functional trait - environment relationship as opposed to the above-mentioned conventional techniques, using examples of out-of-sample predictions of foliar Nitrogen across several species' ranges and biomes.

An Approach to Flooding Inundation Combining the Streamflow Prediction Tool (SPT) and Downscaled Soil Moisture

NASA Astrophysics Data System (ADS)

Cotterman, K. A.; Follum, M. L.; Pradhan, N. R.; Niemann, J. D.

2017-12-01

Flooding impacts numerous aspects of society, from localized flash floods to continental-scale flood events. Many numerical flood models focus solely on riverine flooding, with some capable of capturing both localized and continental-scale flood events. However, these models neglect flooding away from channels that are related to excessive ponding, typically found in areas with flat terrain and poorly draining soils. In order to obtain a holistic view of flooding, we combine flood results from the Streamflow Prediction Tool (SPT), a riverine flood model, with soil moisture downscaling techniques to determine if a better representation of flooding is obtained. This allows for a more holistic understanding of potential flood prone areas, increasing the opportunity for more accurate warnings and evacuations during flooding conditions. Thirty-five years of near-global historical streamflow is reconstructed with continental-scale flow routing of runoff from global land surface models. Elevation data was also obtained worldwide, to establish a relationship between topographic attributes and soil moisture patterns. Derived soil moisture data is validated against observed soil moisture, increasing confidence in the ability to accurately capture soil moisture patterns. Potential flooding situations can be examined worldwide, with this study focusing on the United States, Central America, and the Philippines.

Capital market based warning indicators of bank runs

NASA Astrophysics Data System (ADS)

Vakhtina, Elena; Wosnitza, Jan Henrik

2015-01-01

In this investigation, we examine the univariate as well as the multivariate capabilities of the log-periodic [super-exponential] power law (LPPL) for the prediction of bank runs. The research is built upon daily CDS spreads of 40 international banks for the period from June 2007 to March 2010, i.e. at the heart of the global financial crisis. For this time period, 20 of the financial institutions received federal bailouts and are labeled as defaults while the remaining institutions are categorized as non-defaults. The employed multivariate pattern recognition approach represents a modification of the CORA3 algorithm. The approach is found to be robust regardless of reasonable changes of its inputs. Despite the fact that distinct alarm indices for banks do not clearly demonstrate predictive capabilities of the LPPL, the synchronized alarm indices confirm the multivariate discriminative power of LPPL patterns in CDS spread developments acknowledged by bootstrap intervals with 70% confidence level.

Plate tectonics drive tropical reef biodiversity dynamics

PubMed Central

Leprieur, Fabien; Descombes, Patrice; Gaboriau, Théo; Cowman, Peter F.; Parravicini, Valeriano; Kulbicki, Michel; Melián, Carlos J.; de Santana, Charles N.; Heine, Christian; Mouillot, David; Bellwood, David R.; Pellissier, Loïc

2016-01-01

The Cretaceous breakup of Gondwana strongly modified the global distribution of shallow tropical seas reshaping the geographic configuration of marine basins. However, the links between tropical reef availability, plate tectonic processes and marine biodiversity distribution patterns are still unknown. Here, we show that a spatial diversification model constrained by absolute plate motions for the past 140 million years predicts the emergence and movement of diversity hotspots on tropical reefs. The spatial dynamics of tropical reefs explains marine fauna diversification in the Tethyan Ocean during the Cretaceous and early Cenozoic, and identifies an eastward movement of ancestral marine lineages towards the Indo-Australian Archipelago in the Miocene. A mechanistic model based only on habitat-driven diversification and dispersal yields realistic predictions of current biodiversity patterns for both corals and fishes. As in terrestrial systems, we demonstrate that plate tectonics played a major role in driving tropical marine shallow reef biodiversity dynamics. PMID:27151103

Plate tectonics drive tropical reef biodiversity dynamics.

PubMed

Leprieur, Fabien; Descombes, Patrice; Gaboriau, Théo; Cowman, Peter F; Parravicini, Valeriano; Kulbicki, Michel; Melián, Carlos J; de Santana, Charles N; Heine, Christian; Mouillot, David; Bellwood, David R; Pellissier, Loïc

2016-05-06

The Cretaceous breakup of Gondwana strongly modified the global distribution of shallow tropical seas reshaping the geographic configuration of marine basins. However, the links between tropical reef availability, plate tectonic processes and marine biodiversity distribution patterns are still unknown. Here, we show that a spatial diversification model constrained by absolute plate motions for the past 140 million years predicts the emergence and movement of diversity hotspots on tropical reefs. The spatial dynamics of tropical reefs explains marine fauna diversification in the Tethyan Ocean during the Cretaceous and early Cenozoic, and identifies an eastward movement of ancestral marine lineages towards the Indo-Australian Archipelago in the Miocene. A mechanistic model based only on habitat-driven diversification and dispersal yields realistic predictions of current biodiversity patterns for both corals and fishes. As in terrestrial systems, we demonstrate that plate tectonics played a major role in driving tropical marine shallow reef biodiversity dynamics.

Comparison of subjective sleep and fatigue in breast- and bottle-feeding mothers.

PubMed

Tobback, Els; Behaeghel, Katoesjka; Hanoulle, Ignace; Delesie, Liesbeth; Loccufier, Anne; Van Holsbeeck, Ann; Vogelaers, Dirk; Mariman, An

2017-04-01

Artificial milk supplementation remains a popular practice in spite of the well documented and indisputable advantages of breast feeding for both mother and child. However, the association between maternal sleep, fatigue and feeding method is understudied and remains unclear. The aim of this study is to investigate whether perceived sleep and fatigue differ between breast- and bottle feeding post partum women. In addition, the relationship between subjective sleep characteristics and fatigue is examined. Post partum women (four to 16 weeks) filled out a socio-demographic questionnaire, the Pittsburgh Sleep Quality Index (PSQI) and the Checklist Individual Strength (CIS). Sixty-one within the past week exclusively breast- and 44 exclusively bottle-feeding mothers were included. The first group showed better subjective sleep quality, but lower habitual sleep efficiency as measured by the PSQI. Global PSQI, as well as subjective fatigue and global CIS, did not differ between the two groups. Significant positive correlations were found between global CIS and the number of night feeds and global PSQI. However, only global PSQI significantly predicted global CIS in relation to the number of night feeds. Within a general pattern of deteriorated sleep quality, breast-feeding women showed better subjective sleep quality, but lower habitual sleep efficiency, between four and fourteen weeks after childbirth. However, the PSQI component scores compensated for each other, resulting in absence of any difference in global PSQI sleep quality between the two groups. Global PSQI significantly predicted global CIS, resulting in an absence of any difference in post partum fatigue according to feeding method. Midwives and nurses should, together with the parents, continue to focus on exploring ways to improve maternal sleep quality and to reduce postnatal fatigue. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visual arts training is linked to flexible attention to local and global levels of visual stimuli.

PubMed

Chamberlain, Rebecca; Wagemans, Johan

2015-10-01

Observational drawing skill has been shown to be associated with the ability to focus on local visual details. It is unclear whether superior performance in local processing is indicative of the ability to attend to, and flexibly switch between, local and global levels of visual stimuli. It is also unknown whether these attentional enhancements remain specific to observational drawing skill or are a product of a wide range of artistic activities. The current study aimed to address these questions by testing if flexible visual processing predicts artistic group membership and observational drawing skill in a sample of first-year bachelor's degree art students (n=23) and non-art students (n=23). A pattern of local and global visual processing enhancements was found in relation to artistic group membership and drawing skill, with local processing ability found to be specifically related to individual differences in drawing skill. Enhanced global processing and more fluent switching between local and global levels of hierarchical stimuli predicted both drawing skill and artistic group membership, suggesting that these are beneficial attentional mechanisms for art-making in a range of domains. These findings support a top-down attentional model of artistic expertise and shed light on the domain specific and domain-general attentional enhancements induced by proficiency in the visual arts. Copyright © 2015 Elsevier B.V. All rights reserved.

Global Quantitative Modeling of Chromatin Factor Interactions

PubMed Central

Zhou, Jian; Troyanskaya, Olga G.

2014-01-01

Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

Observed and Projected Changes to the Precipitation Annual Cycle

DOE PAGES

Marvel, Kate; Biasutti, Michela; Bonfils, Celine; ...

2017-06-08

Anthropogenic climate change is predicted to cause spatial and temporal shifts in precipitation patterns. These may be apparent in changes to the annual cycle of zonal mean precipitation P. Trends in the amplitude and phase of the P annual cycle in two long-term, global satellite datasets are broadly similar. Model-derived fingerprints of externally forced changes to the amplitude and phase of the P seasonal cycle, combined with these observations, enable a formal detection and attribution analysis. Observed amplitude changes are inconsistent with model estimates of internal variability but not attributable to the model-predicted response to external forcing. This mismatch betweenmore » observed and predicted amplitude changes is consistent with the sustained La Niña–like conditions that characterize the recent slowdown in the rise of the global mean temperature. However, observed changes to the annual cycle phase do not seem to be driven by this recent hiatus. Furthermore these changes are consistent with model estimates of forced changes, are inconsistent (in one observational dataset) with estimates of internal variability, and may suggest the emergence of an externally forced signal.« less

Single and double production of the Higgs boson at hadron and lepton colliders in minimal composite Higgs models

NASA Astrophysics Data System (ADS)

Kanemura, Shinya; Kaneta, Kunio; Machida, Naoki; Odori, Shinya; Shindou, Tetsuo

2016-07-01

In the composite Higgs models, originally proposed by Georgi and Kaplan, the Higgs boson is a pseudo Nambu-Goldstone boson (pNGB) of spontaneous breaking of a global symmetry. In the minimal version of such models, global SO(5) symmetry is spontaneously broken to SO(4), and the pNGBs form an isospin doublet field, which corresponds to the Higgs doublet in the Standard Model (SM). Predicted coupling constants of the Higgs boson can in general deviate from the SM predictions, depending on the compositeness parameter. The deviation pattern is determined also by the detail of the matter sector. We comprehensively study how the model can be tested via measuring single and double production processes of the Higgs boson at the LHC and future electron-positron colliders. The possibility to distinguish the matter sector among the minimal composite Higgs models is also discussed. In addition, we point out differences in the cross section of double Higgs boson production from the prediction in other new physics models.

A distributed analysis of Human impact on global sediment dynamics

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Syvitski, J. P.

2012-12-01

Understanding riverine sediment dynamics is an important undertaking for both socially-relevant issues such as agriculture, water security and infrastructure management and for scientific analysis of landscapes, river ecology, oceanography and other disciplines. Providing good quantitative and predictive tools in therefore timely particularly in light of predicted climate and landuse changes. Ever increasing human activity during the Anthropocene have affected sediment dynamics in two major ways: (1) an increase is hillslope erosion due to agriculture, deforestation and landscape engineering and (2) trapping of sediment in dams and other man-made reservoirs. The intensity and dynamics between these man-made factors vary widely across the globe and in time and are therefore hard to predict. Using sophisticated numerical models is therefore warranted. Here we use a distributed global riverine sediment flux and water discharge model (WBMsed) to compare a pristine (without human input) and disturbed (with human input) simulations. Using these 50 year simulations we will show and discuss the complex spatial and temporal patterns of human effect on riverine sediment flux and water discharge.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marvel, Kate; Biasutti, Michela; Bonfils, Celine

Anthropogenic climate change is predicted to cause spatial and temporal shifts in precipitation patterns. These may be apparent in changes to the annual cycle of zonal mean precipitation P. Trends in the amplitude and phase of the P annual cycle in two long-term, global satellite datasets are broadly similar. Model-derived fingerprints of externally forced changes to the amplitude and phase of the P seasonal cycle, combined with these observations, enable a formal detection and attribution analysis. Observed amplitude changes are inconsistent with model estimates of internal variability but not attributable to the model-predicted response to external forcing. This mismatch betweenmore » observed and predicted amplitude changes is consistent with the sustained La Niña–like conditions that characterize the recent slowdown in the rise of the global mean temperature. However, observed changes to the annual cycle phase do not seem to be driven by this recent hiatus. Furthermore these changes are consistent with model estimates of forced changes, are inconsistent (in one observational dataset) with estimates of internal variability, and may suggest the emergence of an externally forced signal.« less

Statistical prediction of September Arctic Sea Ice minimum based on stable teleconnections with global climate and oceanic patterns

NASA Astrophysics Data System (ADS)

Ionita, M.; Grosfeld, K.; Scholz, P.; Lohmann, G.

2016-12-01

Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad information interest exists on sea ice, its coverage, variability and long term change. Knowledge on sea ice requires high quality data on ice extent, thickness and its dynamics. However, its predictability depends on various climate parameters and conditions. In order to provide insights into the potential development of a monthly/seasonal signal, we developed a robust statistical model based on ocean heat content, sea surface temperature and atmospheric variables to calculate an estimate of the September minimum sea ice extent for every year. Although previous statistical attempts at monthly/seasonal forecasts of September sea ice minimum show a relatively reduced skill, here it is shown that more than 97% (r = 0.98) of the September sea ice extent can predicted three months in advance by using previous months conditions via a multiple linear regression model based on global sea surface temperature (SST), mean sea level pressure (SLP), air temperature at 850hPa (TT850), surface winds and sea ice extent persistence. The statistical model is based on the identification of regions with stable teleconnections between the predictors (climatological parameters) and the predictand (here sea ice extent). The results based on our statistical model contribute to the sea ice prediction network for the sea ice outlook report (https://www.arcus.org/sipn) and could provide a tool for identifying relevant regions and climate parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.

Tropics accelerate the evolution of hybrid male sterility in Drosophila.

PubMed

Yukilevich, Roman

2013-06-01

Understanding the evolutionary mechanisms that facilitate speciation and explain global patterns of species diversity has remained a challenge for decades. The most general pattern of species biodiversity is the latitudinal gradient, whereby species richness increases toward the tropics. Although such a global pattern probably has a multitude of causes, recent attention has focused on the hypothesis that speciation and the evolution of reproductive isolation occur faster in the tropics. Here, I tested this prediction using a dataset on premating and postzygotic isolation between recently diverged Drosophila species. Results showed that while the evolution of premating isolation was not greater between tropical Drosophila relative to nontropical species, postzygotic isolation evolved faster in the tropics. In particular, hybrid male sterility was much greater among tropical Drosophila compared to nontropical species pairs of similar genetic age. Several testable explanations for the novel pattern are discussed, including greater role for sterility-inducing bacterial endosymbionts in the tropics and more intense sperm-sperm competition or sperm-egg sexual conflict in the tropics. The results imply that processes of speciation in the tropics may evolve at different rates or may even be somewhat different from those at higher latitudes. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

NASA Technical Reports Server (NTRS)

Crane, Robert G.; Hewitson, Bruce

1990-01-01

Model simulations of global climate change are seen as an essential component of any program aimed at understanding human impact on the global environment. A major weakness of current general circulation models (GCMs), however, is their inability to predict reliably the regional consequences of a global scale change, and it is these regional scale predictions that are necessary for studies of human/environmental response. This research is directed toward the development of a methodology for the validation of the synoptic scale climatology of GCMs. This is developed with regard to the Goddard Institute for Space Studies (GISS) GCM Model 2, with the specific objective of using the synoptic circulation form a doubles CO2 simulation to estimate regional climate change over North America, south of Hudson Bay. This progress report is specifically concerned with validating the synoptic climatology of the GISS GCM, and developing the transfer function to derive grid-point temperatures from the synoptic circulation. Principal Components Analysis is used to characterize the primary modes of the spatial and temporal variability in the observed and simulated climate, and the model validation is based on correlations between component loadings, and power spectral analysis of the component scores. The results show that the high resolution GISS model does an excellent job of simulating the synoptic circulation over the U.S., and that grid-point temperatures can be predicted with reasonable accuracy from the circulation patterns.

Methamphetamine-associated cardiomyopathy: patterns and predictors of recovery.

PubMed

Voskoboinik, A; Ihle, J F; Bloom, J E; Kaye, D M

2016-06-01

Methamphetamine abuse is a growing public health problem, and increasing numbers of patients are admitted with methamphetamine-associated cardiomyopathy (MAC). We sought to characterise the patterns of this disease and identify predictors of recovery. We retrospectively studied consecutive patients diagnosed with MAC between January 2006 and July 2015. We identified 20 patients (14 males, 6 females) with mean age 35 ± 9 years. Most had very severe systolic dysfunction (mean left ventricular ejection fraction (LVEF) 19.7 ± 11.4%) at presentation with 14 requiring inotropes and 5 requiring mechanical support. The pattern of systolic dysfunction was global in 14 patients, while 6 patients had a 'reverse Takotsubo' (RT) pattern with severely hypokinetic basal-mid segments and apical preservation. RT patients were predominantly female, had a short history of methamphetamine abuse and had higher cardiac enzyme levels. Patients with global dysfunction tended to have mid-wall fibrosis on cardiac magnetic resonance imaging. On follow-up transthoracic echocardiography, 6 out of 19 (32%) had normalisation of LVEF (LVEF ≥ 50%) within 6 weeks. Smaller left ventricular and left atrial size, shorter duration of methamphetamine use and RT pattern appeared to predict early recovery. A subset of MAC patients, particularly those with a RT pattern and lesser ventricular dilatation have the potential for early recovery of ventricular function. By contrast, those with evidence of myocardial fibrosis and ventricular enlargement have limited scope for recovery. © 2016 Royal Australasian College of Physicians.

Global Image Dissimilarity in Macaque Inferotemporal Cortex Predicts Human Visual Search Efficiency

PubMed Central

Sripati, Arun P.; Olson, Carl R.

2010-01-01

Finding a target in a visual scene can be easy or difficult depending on the nature of the distractors. Research in humans has suggested that search is more difficult the more similar the target and distractors are to each other. However, it has not yielded an objective definition of similarity. We hypothesized that visual search performance depends on similarity as determined by the degree to which two images elicit overlapping patterns of neuronal activity in visual cortex. To test this idea, we recorded from neurons in monkey inferotemporal cortex (IT) and assessed visual search performance in humans using pairs of images formed from the same local features in different global arrangements. The ability of IT neurons to discriminate between two images was strongly predictive of the ability of humans to discriminate between them during visual search, accounting overall for 90% of the variance in human performance. A simple physical measure of global similarity – the degree of overlap between the coarse footprints of a pair of images – largely explains both the neuronal and the behavioral results. To explain the relation between population activity and search behavior, we propose a model in which the efficiency of global oddball search depends on contrast-enhancing lateral interactions in high-order visual cortex. PMID:20107054

Forecasting of monsoon heavy rains: challenges in NWP

NASA Astrophysics Data System (ADS)

Sharma, Kuldeep; Ashrit, Raghavendra; Iyengar, Gopal; Bhatla, R.; Rajagopal, E. N.

2016-05-01

Last decade has seen a tremendous improvement in the forecasting skill of numerical weather prediction (NWP) models. This is attributed to increased sophistication in NWP models, which resolve complex physical processes, advanced data assimilation, increased grid resolution and satellite observations. However, prediction of heavy rains is still a challenge since the models exhibit large error in amounts as well as spatial and temporal distribution. Two state-of-art NWP models have been investigated over the Indian monsoon region to assess their ability in predicting the heavy rainfall events. The unified model operational at National Center for Medium Range Weather Forecasting (NCUM) and the unified model operational at the Australian Bureau of Meteorology (Australian Community Climate and Earth-System Simulator -- Global (ACCESS-G)) are used in this study. The recent (JJAS 2015) Indian monsoon season witnessed 6 depressions and 2 cyclonic storms which resulted in heavy rains and flooding. The CRA method of verification allows the decomposition of forecast errors in terms of error in the rainfall volume, pattern and location. The case by case study using CRA technique shows that contribution to the rainfall errors come from pattern and displacement is large while contribution due to error in predicted rainfall volume is least.

Upper Mantle Texture Patterns In Eastern North America From Seismic Anisotropy And Global Mantle Flow Calculations

NASA Astrophysics Data System (ADS)

Levin, V. L.; Moucha, R.; Yuan, H.

2013-12-01

Global seismic models show gradual and systematic changes in upper mantle seismic properties beneath North America. Faster and thicker lithosphere of the interior thins eastward. Upper mantle rock fabric reflected in observations of seismic anisotropy also varies. Near the coast apparent fast directions of split shear waves are nearly east-west, with considerable scatter. Further inland they are more uniform and align SW-NE, close to the absolute plate motion direction of North America. Mantle convection simulations driven by density inferred from global joint seismic-geodynamic tomography models exhibit complex flow beneath the eastern edge of the North American continent due to the ongoing descent of the Farallon slab deep beneath it (figure 1). Flow predicted beneath the coast is nearly horizontal with a small, though dynamically important, vertical component, while west of the Appalachians it turns downward. Long records of teleseismic observations accumulated at permanent seismic stations HRV, PAL and SSPA (figure 2) are inverted for vertical distribution of anisotropic parameters. We find preference for more than one layer of anisotropy beneath all sites, with significantly different parameters that could reflect either lateral variations in the lithospheric thickness, variations in the asthenospheric flow field, or both. Since we find considerable consistency in directional patterns of P-to-S mode converted waves associated with the lower part of the lithosphere, variations of asthenospheric flow seem to be a more plausible explanation. We explore the links between predicted flow and inferences from seismic data with additional observations of anisotropy and calculations of flow-induced rock fabric.

Nonrandom community assembly and high temporal turnover promote regional coexistence in tropics but not temperate zone.

PubMed

Freestone, Amy L; Inouye, Brian D

2015-01-01

A persistent challenge for ecologists is understanding the ecological mechanisms that maintain global patterns of biodiversity, particularly the latitudinal diversity gradient of peak species richness in the tropics. Spatial and temporal variation in community composition contribute to these patterns of biodiversity, but how this variation and its underlying processes change across latitude remains unresolved. Using a model system of sessile marine invertebrates across 25 degrees of latitude, from the temperate zone to the tropics, we tested the prediction that spatial and temporal patterns of taxonomic richness and composition, and the community assembly processes underlying these patterns, will differ across latitude. Specifically, we predicted that high beta diversity (spatial variation in composition) and high temporal turnover contribute to the high species richness of the tropics. Using a standardized experimental approach that controls for several confounding factors that hinder interpretation of prior studies, we present results that support our predictions. In the temperate zone, communities were more similar across spatial scales from centimeters to tens of kilometers and temporal scales up to one year than at lower latitudes. Since the patterns at northern latitudes were congruent with a null model, stochastic assembly processes are implicated. In contrast, the communities in the tropics were a dynamic spatial and temporal mosaic, with low similarity even across small spatial scales and high temporal turnover at both local and regional scales. Unlike the temperate zone, deterministic community assembly processes such as predation likely contributed to the high beta diversity in the tropics. Our results suggest that community assembly processes and temporal dynamics vary across latitude and help structure and maintain latitudinal patterns of diversity.

Rejecting probability summation for radial frequency patterns, not so Quick!

PubMed

Baldwin, Alex S; Schmidtmann, Gunnar; Kingdom, Frederick A A; Hess, Robert F

2016-05-01

Radial frequency (RF) patterns are used to assess how the visual system processes shape. They are thought to be detected globally. This is supported by studies that have found summation for RF patterns to be greater than what is possible if the parts were being independently detected and performance only then improved with an increasing number of cycles by probability summation between them. However, the model of probability summation employed in these previous studies was based on High Threshold Theory (HTT), rather than Signal Detection Theory (SDT). We conducted rating scale experiments to investigate the receiver operating characteristics. We find these are of the curved form predicted by SDT, rather than the straight lines predicted by HTT. This means that to test probability summation we must use a model based on SDT. We conducted a set of summation experiments finding that thresholds decrease as the number of modulated cycles increases at approximately the same rate as previously found. As this could be consistent with either additive or probability summation, we performed maximum-likelihood fitting of a set of summation models (Matlab code provided in our Supplementary material) and assessed the fits using cross validation. We find we are not able to distinguish whether the responses to the parts of an RF pattern are combined by additive or probability summation, because the predictions are too similar. We present similar results for summation between separate RF patterns, suggesting that the summation process there may be the same as that within a single RF. Copyright © 2016 Elsevier Ltd. All rights reserved.

Disease and thermal acclimation in a more variable and unpredictable climate

NASA Astrophysics Data System (ADS)

Raffel, Thomas R.; Romansic, John M.; Halstead, Neal T.; McMahon, Taegan A.; Venesky, Matthew D.; Rohr, Jason R.

2013-02-01

Global climate change is shifting the distribution of infectious diseases of humans and wildlife with potential adverse consequences for disease control. As well as increasing mean temperatures, climate change is expected to increase climate variability, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments conducted in 80 independent incubators, and field data on disease-associated frog declines in Latin America, support the framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis. Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was opposite to the pattern of growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. If similar acclimation responses influence other host-parasite systems, as seems likely, then present models, which generally ignore small-scale temporal variability in climate, might provide poor predictions for climate effects on disease.

The complex network of global cargo ship movements.

PubMed

Kaluza, Pablo; Kölzsch, Andrea; Gastner, Michael T; Blasius, Bernd

2010-07-06

Transportation networks play a crucial role in human mobility, the exchange of goods and the spread of invasive species. With 90 per cent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 16 363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features that set it apart from other transportation networks. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analysed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.

The complex network of global cargo ship movements

PubMed Central

Kaluza, Pablo; Kölzsch, Andrea; Gastner, Michael T.; Blasius, Bernd

2010-01-01

Transportation networks play a crucial role in human mobility, the exchange of goods and the spread of invasive species. With 90 per cent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 16 363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features that set it apart from other transportation networks. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analysed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion. PMID:20086053

Global patterns in the impact of marine herbivores on benthic primary producers.

PubMed

Poore, Alistair G B; Campbell, Alexandra H; Coleman, Ross A; Edgar, Graham J; Jormalainen, Veijo; Reynolds, Pamela L; Sotka, Erik E; Stachowicz, John J; Taylor, Richard B; Vanderklift, Mathew A; Duffy, J Emmett

2012-08-01

Despite the importance of consumers in structuring communities, and the widespread assumption that consumption is strongest at low latitudes, empirical tests for global scale patterns in the magnitude of consumer impacts are limited. In marine systems, the long tradition of experimentally excluding herbivores in their natural environments allows consumer impacts to be quantified on global scales using consistent methodology. We present a quantitative synthesis of 613 marine herbivore exclusion experiments to test the influence of consumer traits, producer traits and the environment on the strength of herbivore impacts on benthic producers. Across the globe, marine herbivores profoundly reduced producer abundance (by 68% on average), with strongest effects in rocky intertidal habitats and the weakest effects on habitats dominated by vascular plants. Unexpectedly, we found little or no influence of latitude or mean annual water temperature. Instead, herbivore impacts differed most consistently among producer taxonomic and morphological groups. Our results show that grazing impacts on plant abundance are better predicted by producer traits than by large-scale variation in habitat or mean temperature, and that there is a previously unrecognised degree of phylogenetic conservatism in producer susceptibility to consumption. © 2012 Blackwell Publishing Ltd/CNRS.

Analysing the teleconnection systems affecting the climate of the Carpathian Basin

NASA Astrophysics Data System (ADS)

Kristóf, Erzsébet; Bartholy, Judit; Pongrácz, Rita

2017-04-01

Nowadays, the increase of the global average near-surface air temperature is unequivocal. Atmospheric low-frequency variabilities have substantial impacts on climate variables such as air temperature and precipitation. Therefore, assessing their effects is essential to improve global and regional climate model simulations for the 21st century. The North Atlantic Oscillation (NAO) is one of the best-known atmospheric teleconnection patterns affecting the Carpathian Basin in Central Europe. Besides NAO, we aim to analyse other interannual-to-decadal teleconnection patterns, which might have significant impacts on the Carpathian Basin, namely, the East Atlantic/West Russia pattern, the Scandinavian pattern, the Mediterranean Oscillation, and the North-Sea Caspian Pattern. For this purpose primarily the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA-20C atmospheric reanalysis dataset and multivariate statistical methods are used. The indices of each teleconnection pattern and their correlations with temperature and precipitation will be calculated for the period of 1961-1990. On the basis of these data first the long range (i. e. seasonal and/or annual scale) forecast ability is evaluated. Then, we aim to calculate the same indices of the relevant teleconnection patterns for the historical and future simulations of Coupled Model Intercomparison Project Phase 5 (CMIP5) models and compare them against each other using statistical methods. Our ultimate goal is to examine all available CMIP5 models and evaluate their abilities to reproduce the selected teleconnection systems. Thus, climate predictions for the 21st century for the Carpathian Basin may be improved using the best-performing models among all CMIP5 model simulations.

Convergence of marine megafauna movement patterns in coastal and open oceans.

PubMed

Sequeira, A M M; Rodríguez, J P; Eguíluz, V M; Harcourt, R; Hindell, M; Sims, D W; Duarte, C M; Costa, D P; Fernández-Gracia, J; Ferreira, L C; Hays, G C; Heupel, M R; Meekan, M G; Aven, A; Bailleul, F; Baylis, A M M; Berumen, M L; Braun, C D; Burns, J; Caley, M J; Campbell, R; Carmichael, R H; Clua, E; Einoder, L D; Friedlaender, Ari; Goebel, M E; Goldsworthy, S D; Guinet, C; Gunn, J; Hamer, D; Hammerschlag, N; Hammill, M; Hückstädt, L A; Humphries, N E; Lea, M-A; Lowther, A; Mackay, A; McHuron, E; McKenzie, J; McLeay, L; McMahon, C R; Mengersen, K; Muelbert, M M C; Pagano, A M; Page, B; Queiroz, N; Robinson, P W; Shaffer, S A; Shivji, M; Skomal, G B; Thorrold, S R; Villegas-Amtmann, S; Weise, M; Wells, R; Wetherbee, B; Wiebkin, A; Wienecke, B; Thums, M

2018-03-20

The extent of increasing anthropogenic impacts on large marine vertebrates partly depends on the animals' movement patterns. Effective conservation requires identification of the key drivers of movement including intrinsic properties and extrinsic constraints associated with the dynamic nature of the environments the animals inhabit. However, the relative importance of intrinsic versus extrinsic factors remains elusive. We analyze a global dataset of ∼2.8 million locations from >2,600 tracked individuals across 50 marine vertebrates evolutionarily separated by millions of years and using different locomotion modes (fly, swim, walk/paddle). Strikingly, movement patterns show a remarkable convergence, being strongly conserved across species and independent of body length and mass, despite these traits ranging over 10 orders of magnitude among the species studied. This represents a fundamental difference between marine and terrestrial vertebrates not previously identified, likely linked to the reduced costs of locomotion in water. Movement patterns were primarily explained by the interaction between species-specific traits and the habitat(s) they move through, resulting in complex movement patterns when moving close to coasts compared with more predictable patterns when moving in open oceans. This distinct difference may be associated with greater complexity within coastal microhabitats, highlighting a critical role of preferred habitat in shaping marine vertebrate global movements. Efforts to develop understanding of the characteristics of vertebrate movement should consider the habitat(s) through which they move to identify how movement patterns will alter with forecasted severe ocean changes, such as reduced Arctic sea ice cover, sea level rise, and declining oxygen content.

Dryland photoautotrophic soil surface communities endangered by global change

USGS Publications Warehouse

Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina

2018-01-01

Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth’s terrestrial surface will decrease by about 25–40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.

Dryland photoautotrophic soil surface communities endangered by global change

NASA Astrophysics Data System (ADS)

Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina

2018-03-01

Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth's terrestrial surface will decrease by about 25-40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.

GLOBEC: Global Ocean Ecosystems Dynamics: A component of the US Global Change Research Program

NASA Technical Reports Server (NTRS)

1991-01-01

GLOBEC (GLOBal ocean ECosystems dynamics) is a research initiative proposed by the oceanographic and fisheries communities to address the question of how changes in global environment are expected to affect the abundance and production of animals in the sea. The approach to this problem is to develop a fundamental understanding of the mechanisms that determine both the abundance of key marine animal populations and their variances in space and time. The assumption is that the physical environment is a major contributor to patterns of abundance and production of marine animals, in large part because the planktonic life stages typical of most marine animals are intrinsically at the mercy of the fluid motions of the medium in which they live. Consequently, the authors reason that a logical approach to predicting the potential impact of a globally changing environment is to understand how the physical environment, both directly and indirectly, contributes to animal abundance and its variability in marine ecosystems. The plans for this coordinated study of of the potential impact of global change on ocean ecosystems dynamics are discussed.

The body electric 2.0: recent advances in developmental bioelectricity for regenerative and synthetic bioengineering.

PubMed

Mathews, Juanita; Levin, Michael

2018-04-20

Breakthroughs in biomedicine and synthetic bioengineering require predictive, rational control over anatomical structure and function. Recent successes in manipulating cellular and molecular hardware have not been matched by progress in understanding the patterning software implemented during embryogenesis and regeneration. A fundamental capability gap is driving desired changes in growth and form to address birth defects and traumatic injury. Here we review new tools, results, and conceptual advances in an exciting emerging field: endogenous non-neural bioelectric signaling, which enables cellular collectives to make global decisions and implement large-scale pattern homeostasis. Spatially distributed electric circuits regulate gene expression, organ morphogenesis, and body-wide axial patterning. Developmental bioelectricity facilitates the interface to organ-level modular control points that direct patterning in vivo. Cracking the bioelectric code will enable transformative progress in bioengineering and regenerative medicine. Copyright © 2018 Elsevier Ltd. All rights reserved.

Future ocean hypercapnia driven by anthropogenic amplification of the natural CO2 cycle.

PubMed

McNeil, Ben I; Sasse, Tristan P

2016-01-21

High carbon dioxide (CO2) concentrations in sea-water (ocean hypercapnia) can induce neurological, physiological and behavioural deficiencies in marine animals. Prediction of the onset and evolution of hypercapnia in the ocean requires a good understanding of annual variations in oceanic CO2 concentration, but there is a lack of relevant global observational data. Here we identify global ocean patterns of monthly variability in carbon concentration using observations that allow us to examine the evolution of surface-ocean CO2 levels over the entire annual cycle under increasing atmospheric CO2 concentrations. We predict that the present-day amplitude of the natural oscillations in oceanic CO2 concentration will be amplified by up to tenfold in some regions by 2100, if atmospheric CO2 concentrations continue to rise throughout this century (according to the RCP8.5 scenario of the Intergovernmental Panel on Climate Change). The findings from our data are broadly consistent with projections from Earth system climate models. Our predicted amplification of the annual CO2 cycle displays distinct global patterns that may expose major fisheries in the Southern, Pacific and North Atlantic oceans to hypercapnia many decades earlier than is expected from average atmospheric CO2 concentrations. We suggest that these ocean 'CO2 hotspots' evolve as a combination of the strong seasonal dynamics of CO2 concentration and the long-term effective storage of anthropogenic CO2 in the oceans that lowers the buffer capacity in these regions, causing a nonlinear amplification of CO2 concentration over the annual cycle. The onset of ocean hypercapnia (when the partial pressure of CO2 in sea-water exceeds 1,000 micro-atmospheres) is forecast for atmospheric CO2 concentrations that exceed 650 parts per million, with hypercapnia expected in up to half the surface ocean by 2100, assuming a high-emissions scenario (RCP8.5). Such extensive ocean hypercapnia has detrimental implications for fisheries during the twenty-first century.

Future ocean hypercapnia driven by anthropogenic amplification of the natural CO2 cycle

NASA Astrophysics Data System (ADS)

McNeil, Ben I.; Sasse, Tristan P.

2016-01-01

High carbon dioxide (CO2) concentrations in sea-water (ocean hypercapnia) can induce neurological, physiological and behavioural deficiencies in marine animals. Prediction of the onset and evolution of hypercapnia in the ocean requires a good understanding of annual variations in oceanic CO2 concentration, but there is a lack of relevant global observational data. Here we identify global ocean patterns of monthly variability in carbon concentration using observations that allow us to examine the evolution of surface-ocean CO2 levels over the entire annual cycle under increasing atmospheric CO2 concentrations. We predict that the present-day amplitude of the natural oscillations in oceanic CO2 concentration will be amplified by up to tenfold in some regions by 2100, if atmospheric CO2 concentrations continue to rise throughout this century (according to the RCP8.5 scenario of the Intergovernmental Panel on Climate Change). The findings from our data are broadly consistent with projections from Earth system climate models. Our predicted amplification of the annual CO2 cycle displays distinct global patterns that may expose major fisheries in the Southern, Pacific and North Atlantic oceans to hypercapnia many decades earlier than is expected from average atmospheric CO2 concentrations. We suggest that these ocean ‘CO2 hotspots’ evolve as a combination of the strong seasonal dynamics of CO2 concentration and the long-term effective storage of anthropogenic CO2 in the oceans that lowers the buffer capacity in these regions, causing a nonlinear amplification of CO2 concentration over the annual cycle. The onset of ocean hypercapnia (when the partial pressure of CO2 in sea-water exceeds 1,000 micro-atmospheres) is forecast for atmospheric CO2 concentrations that exceed 650 parts per million, with hypercapnia expected in up to half the surface ocean by 2100, assuming a high-emissions scenario (RCP8.5). Such extensive ocean hypercapnia has detrimental implications for fisheries during the twenty-first century.

Global Mapping of the Yeast Genetic Interaction Network

NASA Astrophysics Data System (ADS)

Tong, Amy Hin Yan; Lesage, Guillaume; Bader, Gary D.; Ding, Huiming; Xu, Hong; Xin, Xiaofeng; Young, James; Berriz, Gabriel F.; Brost, Renee L.; Chang, Michael; Chen, YiQun; Cheng, Xin; Chua, Gordon; Friesen, Helena; Goldberg, Debra S.; Haynes, Jennifer; Humphries, Christine; He, Grace; Hussein, Shamiza; Ke, Lizhu; Krogan, Nevan; Li, Zhijian; Levinson, Joshua N.; Lu, Hong; Ménard, Patrice; Munyana, Christella; Parsons, Ainslie B.; Ryan, Owen; Tonikian, Raffi; Roberts, Tania; Sdicu, Anne-Marie; Shapiro, Jesse; Sheikh, Bilal; Suter, Bernhard; Wong, Sharyl L.; Zhang, Lan V.; Zhu, Hongwei; Burd, Christopher G.; Munro, Sean; Sander, Chris; Rine, Jasper; Greenblatt, Jack; Peter, Matthias; Bretscher, Anthony; Bell, Graham; Roth, Frederick P.; Brown, Grant W.; Andrews, Brenda; Bussey, Howard; Boone, Charles

2004-02-01

A genetic interaction network containing ~1000 genes and ~4000 interactions was mapped by crossing mutations in 132 different query genes into a set of ~4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.

Global salinity predictors of western United States precipitation

NASA Astrophysics Data System (ADS)

Liu, T.; Schmitt, R. W.; Li, L.

2016-12-01

Moisture transport from the excess of evaporation over precipitation in the global ocean drives terrestrial precipitation patterns. Sea surface salinity (SSS) is sensitive to changes in ocean evaporation and precipitation, and therefore, to changes in the global water cycle. We use the Met Office Hadley Centre EN4.2.0 SSS dataset to search for teleconnections between autumn-lead seasonal salinity signals and winter precipitation over the western United States. NOAA CPC Unified observational US precipitation in winter months is extracted from bounding boxes over the northwest and southwest and averaged. Lead autumn SON SSS in ocean areas that are relatively highly correlated with winter DJF terrestrial precipitation are filtered by a size threshold and treated as individual predictors. After removing linear trends from the response and explanatory variables and accounting for multiple collinearity, we use best subsets regression and the Bayesian information criterion (BIC) to objectively select the best model to predict terrestrial precipitation using SSS and SST predictors. The combination of autumn SSS and SST predictors can skillfully predict western US winter terrestrial precipitation (R2 = 0.51 for the US Northwest and R2 = 0.7 for the US Southwest). In both cases, SSS is a better predictor than SST. Thus, incorporating SSS can greatly enhance the accuracy of existing precipitation prediction frameworks that use SST-based climate indices and by extension improve watershed management.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Anderson, C.; Bond-Lamberty, B. P.; Huang, M.; Xu, Y.; Stegen, J.

2016-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Antonarakis, A. S.; Bogan, S.; Moorcroft, P. R.

2017-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Merging Station Observations with Large-Scale Gridded Data to Improve Hydrological Predictions over Chile

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Verbist, K. M. J.

2016-12-01

Hydrological predictions at regional-to-global scales are often hampered by the lack of meteorological forcing data. The use of large-scale gridded meteorological data is able to overcome this limitation, but these data are subject to regional biases and unrealistic values at local scale. This is especially challenging in regions such as Chile, where climate exhibits high spatial heterogeneity as a result of long latitude span and dramatic elevation changes. However, regional station-based observational datasets are not fully exploited and have the potential of constraining biases and spatial patterns. This study aims at adjusting precipitation and temperature estimates from the Princeton University global meteorological forcing (PGF) gridded dataset to improve hydrological simulations over Chile, by assimilating 982 gauges from the Dirección General de Aguas (DGA). To merge station data with the gridded dataset, we use a state-space estimation method to produce optimal gridded estimates, considering both the error of the station measurements and the gridded PGF product. The PGF daily precipitation, maximum and minimum temperature at 0.25° spatial resolution are adjusted for the period of 1979-2010. Precipitation and temperature gauges with long and continuous records (>70% temporal coverage) are selected, while the remaining stations are used for validation. The leave-one-out cross validation verifies the robustness of this data assimilation approach. The merged dataset is then used to force the Variable Infiltration Capacity (VIC) hydrological model over Chile at daily time step which are compared to the observations of streamflow. Our initial results show that the station-merged PGF precipitation effectively captures drizzle and the spatial pattern of storms. Overall the merged dataset has significant improvements compared to the original PGF with reduced biases and stronger inter-annual variability. The invariant spatial pattern of errors between the station data and the gridded product opens up the possibility of merging real-time satellite and intermittent gauge observations to produce more accurate real-time hydrological predictions.

Shifting species interactions in terrestrial dryland ecosystems under altered water availability and climate change

USGS Publications Warehouse

McCluney, Kevin E.; Belnap, Jayne; Collins, Scott L.; González, Angélica L.; Hagen, Elizabeth M.; Holland, J. Nathaniel; Kotler, Burt P.; Maestre, Fernando T.; Smith, Stanley D.; Wolf, Blair O.

2012-01-01

Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems.

Assessment of local variability by high-throughput e-beam metrology for prediction of patterning defect probabilities

NASA Astrophysics Data System (ADS)

Wang, Fuming; Hunsche, Stefan; Anunciado, Roy; Corradi, Antonio; Tien, Hung Yu; Tang, Peng; Wei, Junwei; Wang, Yongjun; Fang, Wei; Wong, Patrick; van Oosten, Anton; van Ingen Schenau, Koen; Slachter, Bram

2018-03-01

We present an experimental study of pattern variability and defectivity, based on a large data set with more than 112 million SEM measurements from an HMI high-throughput e-beam tool. The test case is a 10nm node SRAM via array patterned with a DUV immersion LELE process, where we see a variation in mean size and litho sensitivities between different unique via patterns that leads to a seemingly qualitative differences in defectivity. The large available data volume enables further analysis to reliably distinguish global and local CDU variations, including a breakdown into local systematics and stochastics. A closer inspection of the tail end of the distributions and estimation of defect probabilities concludes that there is a common defect mechanism and defect threshold despite the observed differences of specific pattern characteristics. We expect that the analysis methodology can be applied for defect probability modeling as well as general process qualification in the future.

Biogeographic patterns in below-ground diversity in New York City's Central Park are similar to those observed globally

PubMed Central

Ramirez, Kelly S.; Leff, Jonathan W.; Barberán, Albert; Bates, Scott Thomas; Betley, Jason; Crowther, Thomas W.; Kelly, Eugene F.; Oldfield, Emily E.; Shaw, E. Ashley; Steenbock, Christopher; Bradford, Mark A.; Wall, Diana H.; Fierer, Noah

2014-01-01

Soil biota play key roles in the functioning of terrestrial ecosystems, however, compared to our knowledge of above-ground plant and animal diversity, the biodiversity found in soils remains largely uncharacterized. Here, we present an assessment of soil biodiversity and biogeographic patterns across Central Park in New York City that spanned all three domains of life, demonstrating that even an urban, managed system harbours large amounts of undescribed soil biodiversity. Despite high variability across the Park, below-ground diversity patterns were predictable based on soil characteristics, with prokaryotic and eukaryotic communities exhibiting overlapping biogeographic patterns. Further, Central Park soils harboured nearly as many distinct soil microbial phylotypes and types of soil communities as we found in biomes across the globe (including arctic, tropical and desert soils). This integrated cross-domain investigation highlights that the amount and patterning of novel and uncharacterized diversity at a single urban location matches that observed across natural ecosystems spanning multiple biomes and continents. PMID:25274366

Are species' responses to global change predicted by past niche evolution?

PubMed Central

Lavergne, Sébastien; Evans, Margaret E. K.; Burfield, Ian J.; Jiguet, Frederic; Thuiller, Wilfried

2013-01-01

Predicting how and when adaptive evolution might rescue species from global change, and integrating this process into tools of biodiversity forecasting, has now become an urgent task. Here, we explored whether recent population trends of species can be explained by their past rate of niche evolution, which can be inferred from increasingly available phylogenetic and niche data. We examined the assemblage of 409 European bird species for which estimates of demographic trends between 1970 and 2000 are available, along with a species-level phylogeny and data on climatic, habitat and trophic niches. We found that species' proneness to demographic decline is associated with slow evolution of the habitat niche in the past, in addition to certain current-day life-history and ecological traits. A similar result was found at a higher taxonomic level, where families prone to decline have had a history of slower evolution of climatic and habitat niches. Our results support the view that niche conservatism can prevent some species from coping with environmental change. Thus, linking patterns of past niche evolution and contemporary species dynamics for large species samples may provide insights into how niche evolution may rescue certain lineages in the face of global change. PMID:23209172

Influence of birth rates and transmission rates on the global seasonality of rotavirus incidence.

PubMed

Pitzer, Virginia E; Viboud, Cécile; Lopman, Ben A; Patel, Manish M; Parashar, Umesh D; Grenfell, Bryan T

2011-11-07

Rotavirus is a major cause of mortality in developing countries, and yet the dynamics of rotavirus in such settings are poorly understood. Rotavirus is typically less seasonal in the tropics, although recent observational studies have challenged the universality of this pattern. While numerous studies have examined the association between environmental factors and rotavirus incidence, here we explore the role of intrinsic factors. By fitting a mathematical model of rotavirus transmission dynamics to published age distributions of cases from 15 countries, we obtain estimates of local transmission rates. Model-predicted patterns of seasonal incidence based solely on differences in birth rates and transmission rates are significantly correlated with those observed (Spearman's ρ = 0.65, p < 0.05). We then examine seasonal patterns of rotavirus predicted across a range of different birth rates and transmission rates and explore how vaccination may impact these patterns. Our results suggest that the relative lack of rotavirus seasonality observed in many tropical countries may be due to the high birth rates and transmission rates typical of developing countries rather than being driven primarily by environmental conditions. While vaccination is expected to decrease the overall burden of disease, it may increase the degree of seasonal variation in the incidence of rotavirus in some settings.

Potential effects of elevated atmospheric carbon dioxide (CO2) on coastal wetlands

USGS Publications Warehouse

McKee, Karen

2006-01-01

Carbon dioxide (CO2) concentration in the atmosphere has steadily increased from 280 parts per million (ppm) in preindustrial times to 381 ppm today and is predicted by some models to double within the next century. Some of the important pathways whereby changes in atmospheric CO2 may impact coastal wetlands include changes in temperature, rainfall, and hurricane intensity (fig. 1). Increases in CO2 can contribute to global warming, which may (1) accelerate sea-level rise through melting of polar ice fields and steric expansion of oceans, (2) alter rainfall patterns and salinity regimes, and (3) change the intensity and frequency of tropical storms and hurricanes. Sea-level rise combined with changes in storm activity may affect erosion and sedimentation rates and patterns in coastal wetlands and maintenance of soil elevations.Feedback loops between plant growth and hydroedaphic conditions also contribute to maintenance of marsh elevations through accumulation of organic matter. Although increasing CO2 concentration may contribute to global warming and climate changes, it may also have a direct impact on plant growth and development by stimulating photosynthesis or improving water use efficiency. Scientists with the U.S. Geological Survey are examining responses of wetland plants to elevated CO2 concentration and other factors. This research will lead to a better understanding of future changes in marsh species composition, successional rates and patterns, ecological functioning, and vulnerability to sea-level rise and other global change factors.

Local thermodynamic equilibrium for globally disequilibrium open systems under stress

NASA Astrophysics Data System (ADS)

Podladchikov, Yury

2016-04-01

Predictive modeling of far and near equilibrium processes is essential for understanding of patterns formation and for quantifying of natural processes that are never in global equilibrium. Methods of both equilibrium and non-equilibrium thermodynamics are needed and have to be combined. For example, predicting temperature evolution due to heat conduction requires simultaneous use of equilibrium relationship between internal energy and temperature via heat capacity (the caloric equation of state) and disequilibrium relationship between heat flux and temperature gradient. Similarly, modeling of rocks deforming under stress, reactions in system open for the porous fluid flow, or kinetic overstepping of the equilibrium reaction boundary necessarily needs both equilibrium and disequilibrium material properties measured under fundamentally different laboratory conditions. Classical irreversible thermodynamics (CIT) is the well-developed discipline providing the working recipes for the combined application of mutually exclusive experimental data such as density and chemical potential at rest under constant pressure and temperature and viscosity of the flow under stress. Several examples will be presented.

Macrogenomic engineering via modulation of the scaling of chromatin packing density.

PubMed

Almassalha, Luay M; Bauer, Greta M; Wu, Wenli; Cherkezyan, Lusik; Zhang, Di; Kendra, Alexis; Gladstein, Scott; Chandler, John E; VanDerway, David; Seagle, Brandon-Luke L; Ugolkov, Andrey; Billadeau, Daniel D; O'Halloran, Thomas V; Mazar, Andrew P; Roy, Hemant K; Szleifer, Igal; Shahabi, Shohreh; Backman, Vadim

2017-11-01

Many human diseases result from the dysregulation of the complex interactions between tens to thousands of genes. However, approaches for the transcriptional modulation of many genes simultaneously in a predictive manner are lacking. Here, through the combination of simulations, systems modelling and in vitro experiments, we provide a physical regulatory framework based on chromatin packing-density heterogeneity for modulating the genomic information space. Because transcriptional interactions are essentially chemical reactions, they depend largely on the local physical nanoenvironment. We show that the regulation of the chromatin nanoenvironment allows for the predictable modulation of global patterns in gene expression. In particular, we show that the rational modulation of chromatin density fluctuations can lead to a decrease in global transcriptional activity and intercellular transcriptional heterogeneity in cancer cells during chemotherapeutic responses to achieve near-complete cancer cell killing in vitro. Our findings represent a 'macrogenomic engineering' approach to modulating the physical structure of chromatin for whole-scale transcriptional modulation.

Within-person variation in security of attachment: a self-determination theory perspective on attachment, need fulfillment, and well-being.

PubMed

La Guardia, J G; Ryan, R M; Couchman, C E; Deci, E L

2000-09-01

Attachment research has traditionally focused on individual differences in global patterns of attachment to important others. The current research instead focuses primarily on within-person variability in attachments across relational partners. It was predicted that within-person variability would be substantial, even among primary attachment figures of mother, father, romantic partner, and best friend. The prediction was supported in three studies. Furthermore, in line with self-determination theory, multilevel modeling and regression analyses showed that, at the relationship level, individuals' experience of fulfillment of the basic needs for autonomy, competence, and relatedness positively predicted overall attachment security, model of self, and model of other. Relations of both attachment and need satisfaction to well-being were also explored.

Mean annual precipitation predicts primary production resistance and resilience to extreme drought

DOE PAGES

Stuart-Haëntjens, Ellen; De Boeck, Hans J.; Lemoine, Nathan P.; ...

2018-09-01

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitationmore » (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought – a vulnerability that is expected to compound as extreme drought frequency increases in the future.« less

Mean annual precipitation predicts primary production resistance and resilience to extreme drought.

PubMed

Stuart-Haëntjens, Ellen; De Boeck, Hans J; Lemoine, Nathan P; Mänd, Pille; Kröel-Dulay, György; Schmidt, Inger K; Jentsch, Anke; Stampfli, Andreas; Anderegg, William R L; Bahn, Michael; Kreyling, Juergen; Wohlgemuth, Thomas; Lloret, Francisco; Classen, Aimée T; Gough, Christopher M; Smith, Melinda D

2018-04-27

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitation (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought - a vulnerability that is expected to compound as extreme drought frequency increases in the future. Copyright © 2018. Published by Elsevier B.V.

Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa.

PubMed

Redding, David W; Tiedt, Sonia; Lo Iacono, Gianni; Bett, Bernard; Jones, Kate E

2017-07-19

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'. © 2017 The Authors.

Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa

PubMed Central

2017-01-01

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources. This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’. PMID:28584173

Mean annual precipitation predicts primary production resistance and resilience to extreme drought

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stuart-Haëntjens, Ellen; De Boeck, Hans J.; Lemoine, Nathan P.

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitationmore » (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought – a vulnerability that is expected to compound as extreme drought frequency increases in the future.« less

Frost and leaf-size gradients in forests: global patterns and experimental evidence.

PubMed

Lusk, Christopher H; Clearwater, Michael J; Laughlin, Daniel C; Harrison, Sandy P; Prentice, Iain Colin; Nordenstahl, Marisa; Smith, Benjamin

2018-05-16

Explanations of leaf size variation commonly focus on water availability, yet leaf size also varies with latitude and elevation in environments where water is not strongly limiting. We provide the first conclusive test of a prediction of leaf energy balance theory that may explain this pattern: large leaves are more vulnerable to night-time chilling, because their thick boundary layers impede convective exchange with the surrounding air. Seedlings of 15 New Zealand evergreens spanning 12-fold variation in leaf width were exposed to clear night skies, and leaf temperatures were measured with thermocouples. We then used a global dataset to assess several climate variables as predictors of leaf size in forest assemblages. Leaf minus air temperature was strongly correlated with leaf width, ranging from -0.9 to -3.2°C in the smallest- and largest-leaved species, respectively. Mean annual temperature and frost-free period were good predictors of evergreen angiosperm leaf size in forest assemblages, but no climate variable predicted deciduous leaf size. Although winter deciduousness makes large leaves possible in strongly seasonal climates, large-leaved evergreens are largely confined to frost-free climates because of their susceptibility to radiative cooling. Evergreen leaf size data can therefore be used to enhance vegetation models, and to infer palaeotemperatures from fossil leaf assemblages. © 2018 The Authors New Phytologist © 2018 New Phytologist Trust.

Geometry of ‘standoffs’ in lattice models of the spatial Prisoner’s Dilemma and Snowdrift games

NASA Astrophysics Data System (ADS)

Laird, Robert A.; Goyal, Dipankar; Yazdani, Soroosh

2013-09-01

The Prisoner’s Dilemma and Snowdrift games are the main theoretical constructs used to study the evolutionary dynamics of cooperation. In large, well-mixed populations, mean-field models predict a stable equilibrium abundance of all defectors in the Prisoner’s Dilemma and a stable mixed-equilibrium of cooperators and defectors in the Snowdrift game. In the spatial extensions of these games, which can greatly modify the fates of populations (including allowing cooperators to persist in the Prisoner’s Dilemma, for example), lattice models are typically used to represent space, individuals play only with their nearest neighbours, and strategy replacement is a function of the differences in payoffs between neighbours. Interestingly, certain values of the cost-benefit ratio of cooperation, coupled with particular spatial configurations of cooperators and defectors, can lead to ‘global standoffs’, a situation in which all cooperator-defector neighbours have identical payoffs, leading to the development of static spatial patterns. We start by investigating the conditions that can lead to ‘local standoffs’ (i.e., in which isolated pairs of neighbouring cooperators and defectors cannot overtake one another), and then use exhaustive searches of small square lattices (4×4 and 6×6) of degree k=3,k=4, and k=6, to show that two main types of global standoff patterns-‘periodic’ and ‘aperiodic’-are possible by tiling local standoffs across entire spatially structured populations. Of these two types, we argue that only aperiodic global standoffs are likely to be potentially attracting, i.e., capable of emerging spontaneously from non-standoff conditions. Finally, we use stochastic simulation models with comparatively large lattices (100×100) to show that global standoffs in the Prisoner’s Dilemma and Snowdrift games do indeed only (but not always) emerge under the conditions predicted by the small-lattice analysis.

Persistence and storage of activity patterns in spiking recurrent cortical networks: modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine

PubMed Central

Palma, Jesse; Grossberg, Stephen; Versace, Massimiliano

2012-01-01

Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM). Theorems in the 1970's showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP) currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh) can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 ms or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all (WTA) stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners when the network stabilizes. PMID:22754524

Biodiversity mediates top-down control in eelgrass ecosystems: a global comparative-experimental approach.

PubMed

Duffy, J Emmett; Reynolds, Pamela L; Boström, Christoffer; Coyer, James A; Cusson, Mathieu; Donadi, Serena; Douglass, James G; Eklöf, Johan S; Engelen, Aschwin H; Eriksson, Britas Klemens; Fredriksen, Stein; Gamfeldt, Lars; Gustafsson, Camilla; Hoarau, Galice; Hori, Masakazu; Hovel, Kevin; Iken, Katrin; Lefcheck, Jonathan S; Moksnes, Per-Olav; Nakaoka, Masahiro; O'Connor, Mary I; Olsen, Jeanine L; Richardson, J Paul; Ruesink, Jennifer L; Sotka, Erik E; Thormar, Jonas; Whalen, Matthew A; Stachowicz, John J

2015-07-01

Nutrient pollution and reduced grazing each can stimulate algal blooms as shown by numerous experiments. But because experiments rarely incorporate natural variation in environmental factors and biodiversity, conditions determining the relative strength of bottom-up and top-down forcing remain unresolved. We factorially added nutrients and reduced grazing at 15 sites across the range of the marine foundation species eelgrass (Zostera marina) to quantify how top-down and bottom-up control interact with natural gradients in biodiversity and environmental forcing. Experiments confirmed modest top-down control of algae, whereas fertilisation had no general effect. Unexpectedly, grazer and algal biomass were better predicted by cross-site variation in grazer and eelgrass diversity than by global environmental gradients. Moreover, these large-scale patterns corresponded strikingly with prior small-scale experiments. Our results link global and local evidence that biodiversity and top-down control strongly influence functioning of threatened seagrass ecosystems, and suggest that biodiversity is comparably important to global change stressors. © 2015 John Wiley & Sons Ltd/CNRS.

Anthropogenic 129I in the atmosphere: overview over major sources, transport processes and deposition pattern.

PubMed

Reithmeier, H; Lazarev, V; Rühm, W; Nolte, E

2010-10-01

Wet and, to a lesser extent, dry deposition of atmospheric (129)I are known to represent the dominating processes responsible for (129)I in continental environmental samples that are remote from (129)I sources and not directly influenced by any liquid (129)I release of nuclear installations. Up to now, however, little is known about the major emitters and the related global deposition pattern of (129)I. In this work an overview over major sources of (129)I is given, and hitherto unknown time-dependent releases from these were estimated. Total gaseous (129)I releases from the US and former Soviet reprocessing facilities Hanford, Savannah River, Mayak, Seversk and Zheleznogorsk were found to have been 0.53, 0.27, 1.05, 0.23 and 0.14TBq, respectively. These facilities were thus identified as major airborne (129)I emitters. The global deposition pattern due to the (129)I released, depending on geographic latitude and longitude, and on time was studied using a box model describing the global atmospheric transport and deposition of (129)I. The model predictions are compared to (129)I concentrations measured by means of Accelerator Mass Spectrometry (AMS) in water samples that were collected from various lakes in Asia, Africa, America and New Zealand, and to published values. As a result, both pattern and temporal evolution of (129)I deposition values measured in and calculated for different types of environmental samples are, in general, in good agreement. This supports our estimate on atmospheric (129)I releases and the considered substantial transport and deposition mechanisms in our model calculations. Copyright 2010 Elsevier B.V. All rights reserved.

Deep-sea diversity patterns are shaped by energy availability.

PubMed

Woolley, Skipton N C; Tittensor, Derek P; Dunstan, Piers K; Guillera-Arroita, Gurutzeta; Lahoz-Monfort, José J; Wintle, Brendan A; Worm, Boris; O'Hara, Timothy D

2016-05-19

The deep ocean is the largest and least-explored ecosystem on Earth, and a uniquely energy-poor environment. The distribution, drivers and origins of deep-sea biodiversity remain unknown at global scales. Here we analyse a database of more than 165,000 distribution records of Ophiuroidea (brittle stars), a dominant component of sea-floor fauna, and find patterns of biodiversity unlike known terrestrial or coastal marine realms. Both patterns and environmental predictors of deep-sea (2,000-6,500 m) species richness fundamentally differ from those found in coastal (0-20 m), continental shelf (20-200 m), and upper-slope (200-2,000 m) waters. Continental shelf to upper-slope richness consistently peaks in tropical Indo-west Pacific and Caribbean (0-30°) latitudes, and is well explained by variations in water temperature. In contrast, deep-sea species show maximum richness at higher latitudes (30-50°), concentrated in areas of high carbon export flux and regions close to continental margins. We reconcile this structuring of oceanic biodiversity using a species-energy framework, with kinetic energy predicting shallow-water richness, while chemical energy (export productivity) and proximity to slope habitats drive deep-sea diversity. Our findings provide a global baseline for conservation efforts across the sea floor, and demonstrate that deep-sea ecosystems show a biodiversity pattern consistent with ecological theory, despite being different from other planetary-scale habitats.

Corn rootworms (Coleoptera: Chrysomelidae) in space and time

NASA Astrophysics Data System (ADS)

Park, Yong-Lak

Spatial dispersion is a main characteristic of insect populations. Dispersion pattern provides useful information for developing effective sampling and scouting programs because it affects sampling accuracy, efficiency, and precision. Insect dispersion, however, is dynamic in space and time and largely dependent upon interactions among insect, plant and environmental factors. This study investigated the spatial and temporal dynamics of corn rootworm dispersion at different spatial scales by using the global positioning system, the geographic information system, and geostatistics. Egg dispersion pattern was random or uniform in 8-ha cornfields, but could be aggregated at a smaller scale. Larval dispersion pattern was aggregated regardless of spatial scales used in this study. Soil moisture positively affected corn rootworm egg and larval dispersions. Adult dispersion tended to be aggregated during peak population period and random or uniform early and late in the season and corn plant phenology was a major factor to determine dispersion patterns. The dispersion pattern of root injury by corn rootworm larval feeding was aggregated and the degree of aggregation increased as the root injury increased within the range of root injury observed in microscale study. Between-year relationships in dispersion among eggs, larvae, adult, and environment provided a strategy that could predict potential root damage the subsequent year. The best prediction map for the subsequent year's potential root damage was the dispersion maps of adults during population peaked in the cornfield. The prediction map was used to develop site-specific pest management that can reduce chemical input and increase control efficiency by controlling pests only where management is needed. This study demonstrated the spatio-temporal dynamics of insect population and spatial interactions among insects, plants, and environment.

The role of atmospheric diagnosis and Big Data science in improving hydroclimatic extreme prediction and the merits of climate informed prediction for future water resources management

NASA Astrophysics Data System (ADS)

Lu, Mengqian; Lall, Upmanu

2017-04-01

The threats that hydroclimatic extremes pose to sustainable development, safety and operation of infrastructure are both severe and growing. Recent heavy precipitation triggered flood events in many regions and increasing frequency and intensity of extreme precipitation suggested by various climate projections highlight the importance of understanding the associated hydrometeorological patterns and space-time variability of such extreme events, and developing a new approach to improve predictability with a better estimation of uncertainty. This clear objective requires the optimal utility of Big Data analytics on multi-source datasets to extract informative predictors from the complex ocean-atmosphere coupled system and develop a statistical and physical based framework. The proposed presentation includes the essence of our selected works in the past two years, as part of our Global Floods Initiatives. Our approach for an improved extreme prediction begins with a better understanding of the associated atmospheric circulation patterns, under the influence and regulation of slowly changing oceanic boundary conditions [Lu et al., 2013, 2016a; Lu and Lall, 2016]. The study of the associated atmospheric circulation pattern and the regulation of teleconnected climate signals adopted data science techniques and statistical modeling recognizing the nonstationarity and nonlinearity of the system, as the underlying statistical assumptions of the classical extreme value frequency analysis are challenged in hydroclimatic studies. There are two main factors that are considered important for understanding how future flood risk will change. One is the consideration of moisture holding capacity as a function of temperature, as suggested by Clausius-Clapeyron equation. The other is the strength of the convergence or convection associated with extreme precipitation. As convergence or convection gets stronger, rain rates can be expected to increase if the moisture is available. For extreme rainfall events in the mid-latitudes, tropical moisture sources related to strong convection from equatorial oceans were identified together with atmospheric circulation conditions that in favor of consistent transport and convergence of moisture [Lu et al., 2013; Lu and Lall, 2016]. Further, [Lu et al., 2016a] linked the influence of the slowly changing oceanic boundary conditions with the development of the global atmospheric circulation and showed that (1) strong convection over the oceans and the atmospheric moisture transport and flow convergence indicated by atmospheric pressure fields can determine where and when extreme precipitation occurs; and (2) the time-lagged spatial relationship between teleconnected oceanic signals and synoptic atmospheric circulations can improve the predictability of extreme precipitation globally over the next 30 days; such a forecast would be potentially very useful for flood preparation at a lead time that is well beyond the lead time of meteorological forecasts, and it corresponds to a gap in the predictability between quantitative precipitation forecasts and seasonal-to-interannual climate prediction. Lastly, we will demonstrate our most recent results showing the merits of utilizing climate informed forecasts for water resources management, considering irrigation supply, hydropower and flood control, with marked-based financial instruments [Lu et al., 2016b].

Global land ice measurements from space (GLIMS): remote sensing and GIS investigations of the Earth's cryosphere

USGS Publications Warehouse

Bishop, Michael P.; Olsenholler, Jeffrey A.; Shroder, John F.; Barry, Roger G.; Rasup, Bruce H.; Bush, Andrew B. G.; Copland, Luke; Dwyer, John L.; Fountain, Andrew G.; Haeberli, Wilfried; Kääb, Andreas; Paul, Frank; Hall, Dorothy K.; Kargel, Jeffrey S.; Molnia, Bruce F.; Trabant, Dennis C.; Wessels, Rick L.

2004-01-01

Concerns over greenhouse‐gas forcing and global temperatures have initiated research into understanding climate forcing and associated Earth‐system responses. A significant component is the Earth's cryosphere, as glacier‐related, feedback mechanisms govern atmospheric, hydrospheric and lithospheric response. Predicting the human and natural dimensions of climate‐induced environmental change requires global, regional and local information about ice‐mass distribution, volumes, and fluctuations. The Global Land‐Ice Measurements from Space (GLIMS) project is specifically designed to produce and augment baseline information to facilitate glacier‐change studies. This requires addressing numerous issues, including the generation of topographic information, anisotropic‐reflectance correction of satellite imagery, data fusion and spatial analysis, and GIS‐based modeling. Field and satellite investigations indicate that many small glaciers and glaciers in temperate regions are downwasting and retreating, although detailed mapping and assessment are still required to ascertain regional and global patterns of ice‐mass variations. Such remote sensing/GIS studies, coupled with field investigations, are vital for producing baseline information on glacier changes, and improving our understanding of the complex linkages between atmospheric, lithospheric, and glaciological processes.

Quantification of increased flood risk due to global climate change for urban river management planning.

PubMed

Morita, M

2011-01-01

Global climate change is expected to affect future rainfall patterns. These changes should be taken into account when assessing future flooding risks. This study presents a method for quantifying the increase in flood risk caused by global climate change for use in urban flood risk management. Flood risk in this context is defined as the product of flood damage potential and the probability of its occurrence. The study uses a geographic information system-based flood damage prediction model to calculate the flood damage caused by design storms with different return periods. Estimation of the monetary damages these storms produce and their return periods are precursors to flood risk calculations. The design storms are developed from modified intensity-duration-frequency relationships generated by simulations of global climate change scenarios (e.g. CGCM2A2). The risk assessment method is applied to the Kanda River basin in Tokyo, Japan. The assessment provides insights not only into the flood risk cost increase due to global warming, and the impact that increase may have on flood control infrastructure planning.

Magnetic helicity of the global field in solar cycles 23 and 24

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pipin, V. V.; Pevtsov, A. A.

2014-07-01

For the first time we reconstruct the magnetic helicity density of the global axisymmetric field of the Sun using the method proposed by Brandenburg et al. and Pipin et al. To determine the components of the vector potential, we apply a gauge which is typically employed in mean-field dynamo models. This allows for a direct comparison of the reconstructed helicity with the predictions from the mean-field dynamo models. We apply this method to two different data sets: the synoptic maps of the line-of-sight magnetic field from the Michelson Doppler Imager (MDI) on board the Solar and Heliospheric Observatory (SOHO) andmore » vector magnetic field measurements from the Vector Spectromagnetograph (VSM) on the Synoptic Optical Long-term Investigations of the Sun (SOLIS) system. Based on the analysis of the MDI/SOHO data, we find that in solar cycle 23 the global magnetic field had positive (negative) magnetic helicity in the northern (southern) hemisphere. This hemispheric sign asymmetry is opposite to the helicity of the solar active regions, but it is in agreement with the predictions of mean-field dynamo models. The data also suggest that the hemispheric helicity rule may have reversed its sign during the early and late phases of cycle 23. Furthermore, the data indicate an imbalance in magnetic helicity between the northern and southern hemispheres. This imbalance seems to correlate with the total level of activity in each hemisphere in cycle 23. The magnetic helicity for the rising phase of cycle 24 is derived from SOLIS/VSM data, and qualitatively its latitudinal pattern is similar to the pattern derived from SOHO/MDI data for cycle 23.« less

Future ocean hypercapnia driven by anthropogenic amplification of the natural CO2 cycle

NASA Astrophysics Data System (ADS)

McNeil, B.

2016-02-01

Elevated carbon dioxide concentrations in seawater (hypercapnia) can induce neurological, physiological and behavioural deficiencies in marine animals. Prediction of the onset and evolution of hypercapnia in the ocean requires a good understanding of annual oceanic carbon dioxide variability, but relevant global observational data are sparse. Here we diagnose global ocean patterns of monthly carbon variability based on observations that allow us to examine the evolution of surface ocean CO2 levels over the entire annual cycle under increasing atmospheric CO2 concentrations. We find that some oceanic regions undergo an up to 10-fold amplification of the natural cycle of CO2 by 2100, if atmospheric carbon dioxide concentrations continue to rise throughout this century (RCP8.5). Projections from a suite of Earth System Climate Models are broadly consistent with the findings from our data based approach. Our predicted amplification in the annual CO2 cycle displays distinct global patterns that may expose major fisheries in the Southern, Pacific and North Atlantic Oceans to high CO2 events many decades earlier than expected from average atmospheric CO2 concentrations. We suggest that these ocean 'CO2 hotspots' evolve as a combination of the strong seasonal dynamics of CO2 and the long-term effective storage of anthropogenic CO2 that lowers the buffer capacity in those regions, causing a non-linear CO2 amplification over the annual cycle. The onset of ocean hypercapnia events (pCO2 >1000 µatm) is forecast for atmospheric CO2 concentrations that exceed 650 ppm, with hypercapnia spreading to up to one half of the surface ocean by the year 2100 under a high-emissions scenario (RCP8.5) with potential implications for fisheries over the coming century.

Frontiers in Decadal Climate Variability: Proceedings of a Workshop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purcell, Amanda

A number of studies indicate an apparent slowdown in the overall rise in global average surface temperature between roughly 1998 and 2014. Most models did not predict such a slowdown--a fact that stimulated a lot of new research on variability of Earth's climate system. At a September 2015 workshop, leading scientists gathered to discuss current understanding of climate variability on decadal timescales (10 to 30 years) and whether and how prediction of it might be improved. Many researchers have focused their attention on the climate system itself, which is known to vary across seasons, decades, and other timescales. Several naturalmore » variables produce "ups and downs" in the climate system, which are superimposed on the long-term warming trend due to human influence. Understanding decadal climate variability is important not only for assessing global climate change but also for improving decision making related to infrastructure, water resources, agriculture, energy, and other realms. Like the well-studied El Nino and La Nina interannual variations, decadal climate variability is associated with specific regional patterns of temperature and precipitation, such as heat waves, cold spells, and droughts. Several participants shared research that assesses decadal predictive capability of current models.« less

Frequency-dependent selection predicts patterns of radiations and biodiversity.

PubMed

Melián, Carlos J; Alonso, David; Vázquez, Diego P; Regetz, James; Allesina, Stefano

2010-08-26

Most empirical studies support a decline in speciation rates through time, although evidence for constant speciation rates also exists. Declining rates have been explained by invoking pre-existing niches, whereas constant rates have been attributed to non-adaptive processes such as sexual selection and mutation. Trends in speciation rate and the processes underlying it remain unclear, representing a critical information gap in understanding patterns of global diversity. Here we show that the temporal trend in the speciation rate can also be explained by frequency-dependent selection. We construct a frequency-dependent and DNA sequence-based model of speciation. We compare our model to empirical diversity patterns observed for cichlid fish and Darwin's finches, two classic systems for which speciation rates and richness data exist. Negative frequency-dependent selection predicts well both the declining speciation rate found in cichlid fish and explains their species richness. For groups like the Darwin's finches, in which speciation rates are constant and diversity is lower, speciation rate is better explained by a model without frequency-dependent selection. Our analysis shows that differences in diversity may be driven by incipient species abundance with frequency-dependent selection. Our results demonstrate that genetic-distance-based speciation and frequency-dependent selection are sufficient to explain the high diversity observed in natural systems and, importantly, predict decay through time in speciation rate in the absence of pre-existing niches.

Global patterns of the isotopic composition of soil and plant nitrogen

USGS Publications Warehouse

Amundson, Ronald; Austin, A.T.; Schuur, E.A.G.; Yoo, K.; Matzek, V.; Kendall, C.; Uebersax, A.; Brenner, D.; Baisden, W.T.

2003-01-01

We compiled new and published data on the natural abundance N isotope composition (??15N values) of soil and plant organic matter from around the world. Across a broad range of climate and ecosystem types, we found that soil and plant ??15N values systematically decreased with increasing mean annual precipitation (MAP) and decreasing mean annual temperature (MAT). Because most undisturbed soils are near N steady state, the observations suggest that an increasing fraction of ecosystem N losses are 15N-depleted forms (NO3, N2O, etc.) with decreasing MAP and increasing MAT. Wetter and colder ecosystems appear to be more efficient in conserving and recycling mineral N. Globally, plant ??15N values are more negative than soils, but the difference Nitrogen isotopes reflect time integrated measures of the controls on N storage that are critical for predictions of how these ecosystems will respond to human-mediated disturbances of the global N cycle.

Climatic crystal balls

NASA Astrophysics Data System (ADS)

What do anchovy and coffee prices have in common? They both are influenced by weather patterns. And so are a lot of other industries in the world of commodities. A new report from the National Research Council says it's time to protect these economic interests. The report outlines a new 15-year global research program that would help scientists make better seasonal and interannual climate predictions. Called the Global Ocean-Atmosphere-Land System or GOALS, the new program would be an extension of the decade-long international Tropical Ocean and Global Atmosphere (TOGA) program, which comes to an end this year. Besides studying the climatic effects of tropical phenomena such as the El Niño/Southern Oscillation, the program would expand these types of studies to Earth's higher latitudes and to additional physical processes, such as the effects of changes in upper ocean currents, soil moisture, vegetation, and land, snow, and sea-ice cover, among others.

A new Method for the Estimation of Initial Condition Uncertainty Structures in Mesoscale Models

NASA Astrophysics Data System (ADS)

Keller, J. D.; Bach, L.; Hense, A.

2012-12-01

The estimation of fast growing error modes of a system is a key interest of ensemble data assimilation when assessing uncertainty in initial conditions. Over the last two decades three methods (and variations of these methods) have evolved for global numerical weather prediction models: ensemble Kalman filter, singular vectors and breeding of growing modes (or now ensemble transform). While the former incorporates a priori model error information and observation error estimates to determine ensemble initial conditions, the latter two techniques directly address the error structures associated with Lyapunov vectors. However, in global models these structures are mainly associated with transient global wave patterns. When assessing initial condition uncertainty in mesoscale limited area models, several problems regarding the aforementioned techniques arise: (a) additional sources of uncertainty on the smaller scales contribute to the error and (b) error structures from the global scale may quickly move through the model domain (depending on the size of the domain). To address the latter problem, perturbation structures from global models are often included in the mesoscale predictions as perturbed boundary conditions. However, the initial perturbations (when used) are often generated with a variant of an ensemble Kalman filter which does not necessarily focus on the large scale error patterns. In the framework of the European regional reanalysis project of the Hans-Ertel-Center for Weather Research we use a mesoscale model with an implemented nudging data assimilation scheme which does not support ensemble data assimilation at all. In preparation of an ensemble-based regional reanalysis and for the estimation of three-dimensional atmospheric covariance structures, we implemented a new method for the assessment of fast growing error modes for mesoscale limited area models. The so-called self-breeding is development based on the breeding of growing modes technique. Initial perturbations are integrated forward for a short time period and then rescaled and added to the initial state again. Iterating this rapid breeding cycle provides estimates for the initial uncertainty structure (or local Lyapunov vectors) given a specific norm. To avoid that all ensemble perturbations converge towards the leading local Lyapunov vector we apply an ensemble transform variant to orthogonalize the perturbations in the sub-space spanned by the ensemble. By choosing different kind of norms to measure perturbation growth, this technique allows for estimating uncertainty patterns targeted at specific sources of errors (e.g. convection, turbulence). With case study experiments we show applications of the self-breeding method for different sources of uncertainty and different horizontal scales.

Many local pattern texture features: which is better for image-based multilabel human protein subcellular localization classification?

PubMed

Yang, Fan; Xu, Ying-Ying; Shen, Hong-Bin

2014-01-01

Human protein subcellular location prediction can provide critical knowledge for understanding a protein's function. Since significant progress has been made on digital microscopy, automated image-based protein subcellular location classification is urgently needed. In this paper, we aim to investigate more representative image features that can be effectively used for dealing with the multilabel subcellular image samples. We prepared a large multilabel immunohistochemistry (IHC) image benchmark from the Human Protein Atlas database and tested the performance of different local texture features, including completed local binary pattern, local tetra pattern, and the standard local binary pattern feature. According to our experimental results from binary relevance multilabel machine learning models, the completed local binary pattern, and local tetra pattern are more discriminative for describing IHC images when compared to the traditional local binary pattern descriptor. The combination of these two novel local pattern features and the conventional global texture features is also studied. The enhanced performance of final binary relevance classification model trained on the combined feature space demonstrates that different features are complementary to each other and thus capable of improving the accuracy of classification.

Prediction of tropical cyclogenesis in North Indian Ocean using Oceansat-2 scatterometer (OSCAT) winds

NASA Astrophysics Data System (ADS)

Jaiswal, Neeru; Kishtawal, C. M.; Pal, P. K.

2013-02-01

India's polar orbiting satellite Oceansat-2 was launched by Indian Space Research Organisation on 23 September 2009 for applications pertaining to ocean studies and meteorology. The wind scatterometer aboard the Oceansat-2 satellite (OSCAT) covers 90 % of the global ocean within a day. In the present study, the OSCAT-derived wind fields are used to predict the genesis of tropical cyclones over the North Indian Ocean using a new technique based on data mining. The technique is based on the premise that there is some degree of similarity in low-level wind circulation among developing systems, which can be utilized to distinguish them from non-developing systems. This similarity of wind patterns has been measured quantitatively by computing the "matching index" between the given wind pattern and the wind signatures of developing systems available from the past observations. The algorithm is used to predict the tropical cyclogenesis of cyclones formed during the period 2009-11 in the North Indian Ocean. All the tropical disturbances that developed into tropical storms during the above period (2009-11), viz. PHYAN, WARD, LAILA, BANDU, PHET, GIRI, JAL, KEILA, FOUR, FIVE and THANE were predicted using the proposed method. The mean prediction lead time of the technique was 63 h. Probability of detection of the technique was 100 %, while the false alarm ratio was 2 %.

Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species

NASA Astrophysics Data System (ADS)

Moon, Joon-Young; Kim, Junhyeok; Ko, Tae-Wook; Kim, Minkyung; Iturria-Medina, Yasser; Choi, Jee-Hyun; Lee, Joseph; Mashour, George A.; Lee, Uncheol

2017-04-01

Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.

Analytical investigation of adaptive control of radiated inlet noise from turbofan engines

NASA Technical Reports Server (NTRS)

Risi, John D.; Burdisso, Ricardo A.

1994-01-01

An analytical model has been developed to predict the resulting far field radiation from a turbofan engine inlet. A feedforward control algorithm was simulated to predict the controlled far field radiation from the destructive combination of fan noise and secondary control sources. Numerical results were developed for two system configurations, with the resulting controlled far field radiation patterns showing varying degrees of attenuation and spillover. With one axial station of twelve control sources and error sensors with equal relative angular positions, nearly global attenuation is achieved. Shifting the angular position of one error sensor resulted in an increase of spillover to the extreme sidelines. The complex control inputs for each configuration was investigated to identify the structure of the wave pattern created by the control sources, giving an indication of performance of the system configuration. It is deduced that the locations of the error sensors and the control source configuration are equally critical to the operation of the active noise control system.

Could the outcome of the 2016 US elections have been predicted from past voting patterns?

NASA Astrophysics Data System (ADS)

Schmitz, Peter M. U.; Holloway, Jennifer P.; Dudeni-Tlhone, Nontembeko; Ntlangu, Mbulelo B.; Koen, Renee

2018-05-01

In South Africa, a team of analysts has for some years been using statistical techniques to predict election outcomes during election nights in South Africa. The prediction method involves using statistical clusters based on past voting patterns to predict final election outcomes, using a small number of released vote counts. With the US presidential elections in November 2016 hitting the global media headlines during the time period directly after successful predictions were done for the South African elections, the team decided to investigate adapting their meth-od to forecast the final outcome in the US elections. In particular, it was felt that the time zone differences between states would affect the time at which results are released and thereby provide a window of opportunity for doing election night prediction using only the early results from the eastern side of the US. Testing the method on the US presidential elections would have two advantages: it would determine whether the core methodology could be generalised, and whether it would work to include a stronger spatial element in the modelling, since the early results released would be spatially biased due to time zone differences. This paper presents a high-level view of the overall methodology and how it was adapted to predict the results of the US presidential elections. A discussion on the clustering of spatial units within the US is also provided and the spatial distribution of results together with the Electoral College prediction results from both a `test-run' and the final 2016 presidential elections are given and analysed.

Global patterns of groundwater table depth.

PubMed

Fan, Y; Li, H; Miguez-Macho, G

2013-02-22

Shallow groundwater affects terrestrial ecosystems by sustaining river base-flow and root-zone soil water in the absence of rain, but little is known about the global patterns of water table depth and where it provides vital support for land ecosystems. We present global observations of water table depth compiled from government archives and literature, and fill in data gaps and infer patterns and processes using a groundwater model forced by modern climate, terrain, and sea level. Patterns in water table depth explain patterns in wetlands at the global scale and vegetation gradients at regional and local scales. Overall, shallow groundwater influences 22 to 32% of global land area, including ~15% as groundwater-fed surface water features and 7 to 17% with the water table or its capillary fringe within plant rooting depths.

Predicting plankton net community production in the Atlantic Ocean

NASA Astrophysics Data System (ADS)

Serret, Pablo; Robinson, Carol; Fernández, Emilio; Teira, Eva; Tilstone, Gavin; Pérez, Valesca

2009-07-01

We present, test and implement two contrasting models to predict euphotic zone net community production (NCP), which are based on 14C primary production (PO 14CP) to NCP relationships over two latitudinal (ca. 30°S-45°N) transects traversing highly productive and oligotrophic provinces of the Atlantic Ocean (NADR, CNRY, BENG, NAST-E, ETRA and SATL, Longhurst et al., 1995 [An estimation of global primary production in the ocean from satellite radiometer data. Journal of Plankton Research 17, 1245-1271]). The two models include similar ranges of PO 14CP and community structure, but differ in the relative influence of allochthonous organic matter in the oligotrophic provinces. Both models were used to predict NCP from PO 14CP measurements obtained during 11 local and three seasonal studies in the Atlantic, Pacific and Indian Oceans, and from satellite-derived estimates of PO 14CP. Comparison of these NCP predictions with concurrent in situ measurements and geochemical estimates of NCP showed that geographic and annual patterns of NCP can only be predicted when the relative trophic importance of local vs. distant processes is similar in both modeled and predicted ecosystems. The system-dependent ability of our models to predict NCP seasonality suggests that trophic-level dynamics are stronger than differences in hydrodynamic regime, taxonomic composition and phytoplankton growth. The regional differences in the predictive power of both models confirm the existence of biogeographic differences in the scale of trophic dynamics, which impede the use of a single generalized equation to estimate global marine plankton NCP. This paper shows the potential of a systematic empirical approach to predict plankton NCP from local and satellite-derived P estimates.

Macroscale patterns in body size of intertidal crustaceans provide insights on climate change effects.

PubMed

Jaramillo, Eduardo; Dugan, Jenifer E; Hubbard, David M; Contreras, Heraldo; Duarte, Cristian; Acuña, Emilio; Schoeman, David S

2017-01-01

Predicting responses of coastal ecosystems to altered sea surface temperatures (SST) associated with global climate change, requires knowledge of demographic responses of individual species. Body size is an excellent metric because it scales strongly with growth and fecundity for many ectotherms. These attributes can underpin demographic as well as community and ecosystem level processes, providing valuable insights for responses of vulnerable coastal ecosystems to changing climate. We investigated contemporary macroscale patterns in body size among widely distributed crustaceans that comprise the majority of intertidal abundance and biomass of sandy beach ecosystems of the eastern Pacific coasts of Chile and California, USA. We focused on ecologically important species representing different tidal zones, trophic guilds and developmental modes, including a high-shore macroalga-consuming talitrid amphipod (Orchestoidea tuberculata), two mid-shore scavenging cirolanid isopods (Excirolana braziliensis and E. hirsuticauda), and a low-shore suspension-feeding hippid crab (Emerita analoga) with an amphitropical distribution. Significant latitudinal patterns in body sizes were observed for all species in Chile (21° - 42°S), with similar but steeper patterns in Emerita analoga, in California (32°- 41°N). Sea surface temperature was a strong predictor of body size (-4% to -35% °C-1) in all species. Beach characteristics were subsidiary predictors of body size. Alterations in ocean temperatures of even a few degrees associated with global climate change are likely to affect body sizes of important intertidal ectotherms, with consequences for population demography, life history, community structure, trophic interactions, food-webs, and indirect effects such as ecosystem function. The consistency of results for body size and temperature across species with different life histories, feeding modes, ecological roles, and microhabitats inhabiting a single widespread coastal ecosystem, and for one species, across hemispheres in this space-for-time substitution, suggests predictions of ecosystem responses to thermal effects of climate change may potentially be generalised, with important implications for coastal conservation.

Macroscale patterns in body size of intertidal crustaceans provide insights on climate change effects

PubMed Central

Dugan, Jenifer E.; Hubbard, David M.; Contreras, Heraldo; Duarte, Cristian; Acuña, Emilio; Schoeman, David S.

2017-01-01

Predicting responses of coastal ecosystems to altered sea surface temperatures (SST) associated with global climate change, requires knowledge of demographic responses of individual species. Body size is an excellent metric because it scales strongly with growth and fecundity for many ectotherms. These attributes can underpin demographic as well as community and ecosystem level processes, providing valuable insights for responses of vulnerable coastal ecosystems to changing climate. We investigated contemporary macroscale patterns in body size among widely distributed crustaceans that comprise the majority of intertidal abundance and biomass of sandy beach ecosystems of the eastern Pacific coasts of Chile and California, USA. We focused on ecologically important species representing different tidal zones, trophic guilds and developmental modes, including a high-shore macroalga-consuming talitrid amphipod (Orchestoidea tuberculata), two mid-shore scavenging cirolanid isopods (Excirolana braziliensis and E. hirsuticauda), and a low-shore suspension-feeding hippid crab (Emerita analoga) with an amphitropical distribution. Significant latitudinal patterns in body sizes were observed for all species in Chile (21° - 42°S), with similar but steeper patterns in Emerita analoga, in California (32°- 41°N). Sea surface temperature was a strong predictor of body size (-4% to -35% °C-1) in all species. Beach characteristics were subsidiary predictors of body size. Alterations in ocean temperatures of even a few degrees associated with global climate change are likely to affect body sizes of important intertidal ectotherms, with consequences for population demography, life history, community structure, trophic interactions, food-webs, and indirect effects such as ecosystem function. The consistency of results for body size and temperature across species with different life histories, feeding modes, ecological roles, and microhabitats inhabiting a single widespread coastal ecosystem, and for one species, across hemispheres in this space-for-time substitution, suggests predictions of ecosystem responses to thermal effects of climate change may potentially be generalised, with important implications for coastal conservation. PMID:28481897

Global assessment of ocean carbon export by combining satellite observations and food-web models

NASA Astrophysics Data System (ADS)

Siegel, D. A.; Buesseler, K. O.; Doney, S. C.; Sailley, S. F.; Behrenfeld, M. J.; Boyd, P. W.

2014-03-01

The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of 6 Pg C yr-1. Global export estimates show small variation (typically < 10%) to factor of 2 changes in model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump.

Predicting long-term outcome of Internet-delivered cognitive behavior therapy for social anxiety disorder using fMRI and support vector machine learning.

PubMed

Månsson, K N T; Frick, A; Boraxbekk, C-J; Marquand, A F; Williams, S C R; Carlbring, P; Andersson, G; Furmark, T

2015-03-17

Cognitive behavior therapy (CBT) is an effective treatment for social anxiety disorder (SAD), but many patients do not respond sufficiently and a substantial proportion relapse after treatment has ended. Predicting an individual's long-term clinical response therefore remains an important challenge. This study aimed at assessing neural predictors of long-term treatment outcome in participants with SAD 1 year after completion of Internet-delivered CBT (iCBT). Twenty-six participants diagnosed with SAD underwent iCBT including attention bias modification for a total of 13 weeks. Support vector machines (SVMs), a supervised pattern recognition method allowing predictions at the individual level, were trained to separate long-term treatment responders from nonresponders based on blood oxygen level-dependent (BOLD) responses to self-referential criticism. The Clinical Global Impression-Improvement scale was the main instrument to determine treatment response at the 1-year follow-up. Results showed that the proportion of long-term responders was 52% (12/23). From multivariate BOLD responses in the dorsal anterior cingulate cortex (dACC) together with the amygdala, we were able to predict long-term response rate of iCBT with an accuracy of 92% (confidence interval 95% 73.2-97.6). This activation pattern was, however, not predictive of improvement in the continuous Liebowitz Social Anxiety Scale-Self-report version. Follow-up psychophysiological interaction analyses revealed that lower dACC-amygdala coupling was associated with better long-term treatment response. Thus, BOLD response patterns in the fear-expressing dACC-amygdala regions were highly predictive of long-term treatment outcome of iCBT, and the initial coupling between these regions differentiated long-term responders from nonresponders. The SVM-neuroimaging approach could be of particular clinical value as it allows for accurate prediction of treatment outcome at the level of the individual.

Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma.

PubMed

Wang, Mengyu; Pasquale, Louis R; Shen, Lucy Q; Boland, Michael V; Wellik, Sarah R; De Moraes, Carlos Gustavo; Myers, Jonathan S; Wang, Hui; Baniasadi, Neda; Li, Dian; Silva, Rafaella Nascimento E; Bex, Peter J; Elze, Tobias

2018-03-01

To develop a visual field (VF) feature model to predict the reversal of glaucoma hemifield test (GHT) results to within normal limits (WNL) after 2 consecutive outside normal limits (ONL) results. Retrospective cohort study. Visual fields of 44 503 eyes from 26 130 participants. Eyes with 3 or more consecutive reliable VFs measured with the Humphrey Field Analyzer (Swedish interactive threshold algorithm standard 24-2) were included. Eyes with ONL GHT results for the 2 baseline VFs were selected. We extracted 3 categories of VF features from the baseline tests: (1) VF global indices (mean deviation [MD] and pattern standard deviation), (2) mismatch between baseline VFs, and (3) VF loss patterns (archetypes). Logistic regression was applied to predict the GHT results reversal. Cross-validation was applied to evaluate the model on testing data by the area under the receiver operating characteristic curve (AUC). We ascertained clinical glaucoma status on a patient subset (n = 97) to determine the usefulness of our model. Predictive models for GHT results reversal using VF features. For the 16 604 eyes with 2 initial ONL results, the prevalence of a subsequent WNL result increased from 0.1% for MD < -12 dB to 13.8% for MD ≥-3 dB. Compared with models with VF global indices, the AUC of predictive models increased from 0.669 (MD ≥-3 dB) and 0.697 (-6 dB ≤ MD < -3 dB) to 0.770 and 0.820, respectively, by adding VF mismatch features and computationally derived VF archetypes (P < 0.001 for both). The GHT results reversal was associated with a large mismatch between baseline VFs. Moreover, the GHT results reversal was associated more with VF archetypes of nonglaucomatous loss, severe widespread loss, and lens rim artifacts. For a subset of 97 eyes, using our model to predict absence of glaucoma based on clinical evidence after 2 ONL results yielded significantly better prediction accuracy (87.7%; P < 0.001) than predicting GHT results reversal (68.8%) with a prescribed specificity 67.7%. Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results. Copyright © 2017 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Interannual Variability in Soil Trace Gas (CO2, N2O, NO) Fluxes and Analysis of Controllers

NASA Technical Reports Server (NTRS)

Potter, C.; Klooster, S.; Peterson, David L. (Technical Monitor)

1997-01-01

Interannual variability in flux rates of biogenic trace gases must be quantified in order to understand the differences between short-term trends and actual long-term change in biosphere-atmosphere interactions. We simulated interannual patterns (1983-1988) of global trace gas fluxes from soils using the NASA Ames model version of CASA (Carnegie-Ames-Stanford Approach) in a transient simulation mode. This ecosystem model has been recalibrated for simulations driven by satellite vegetation index data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) over the mid-1980s. The predicted interannual pattern of soil heterotropic CO2 emissions indicates that relatively large increases in global carbon flux from soils occurred about three years following the strong El Nino Southern Oscillation (ENSO) event of 1983. Results for the years 1986 and 1987 showed an annual increment of +1 Pg (1015 g) C-CO2 emitted from soils, which tended to dampen the estimated global increase in net ecosystem production with about a two year lag period relative to plant carbon fixation. Zonal discrimination of model results implies that 80-90 percent of the yearly positive increments in soil CO2 emission during 1986-87 were attributable to soil organic matter decomposition in the low-latitudes (between 30 N and 30 S). Soils of the northern middle-latitude zone (between 30 N and 60 N) accounted for the residual of these annual increments. Total annual emissions of nitrogen trace gases (N2O and NO) from soils were estimated to vary from 2-4 percent over the time period modeled, a level of variability which is consistent with predicted interannual fluctuations in global soil CO2 fluxes. Interannual variability of precipitation in tropical and subtropical zones (30 N to 20 S appeared to drive the dynamic inverse relationship between higher annual emissions of NO versus emissions of N2O. Global mean emission rates from natural (heterotrophic) soil sources over the period modeled (1983-1988) were estimated at 57.1 Pg C-CO2yr-1, 9.8Tg (1012 g) N-NO yr-1, and 9.7 Tg N-N2O yr-1. Chemical fertilizer contributions to global soil N gas fluxes were estimated at between 1.3 to 7.3 Tg N-NO yr-1, and 1.2 to 4.0 Tg N-N2O yr-1.

Species pool, human population, and global versus regional invasion patterns

Treesearch

Qinfeng Guo; Basil V. Iannone III; Gabriela C. Nunez-Mir; Kevin M. Potter; Christopher M. Oswalt; Songlin Fei

2017-01-01

Context Biological invasions are among the greatest global and regional threats to biomes in the Anthropocene. Islands, in particular, have been perceived to have higher vulnerability to invasions. Because of the dynamic nature of ongoing invasions, distinguishing regional patterns from global patterns and their underlying determinants remains a challenge. Objectives...

The Risk Implications of Globalisation: An Exploratory Analysis of 105 Major Industrial Incidents (1971-2010).

PubMed

Beck, Matthias

2016-03-10

This paper revisits work on the socio-political amplification of risk, which predicts that those living in developing countries are exposed to greater risk than residents of developed nations. This prediction contrasts with the neoliberal expectation that market driven improvements in working conditions within industrialising/developing nations will lead to global convergence of hazard exposure levels. It also contradicts the assumption of risk society theorists that there will be an ubiquitous increase in risk exposure across the globe, which will primarily affect technically more advanced countries. Reviewing qualitative evidence on the impact of structural adjustment reforms in industrialising countries, the export of waste and hazardous waste recycling to these countries and new patterns of domestic industrialisation, the paper suggests that workers in industrialising countries continue to face far greater levels of hazard exposure than those of developed countries. This view is confirmed when a data set including 105 major multi-fatality industrial disasters from 1971 to 2000 is examined. The paper concludes that there is empirical support for the predictions of socio-political amplification of risk theory, which finds clear expression in the data in a consistent pattern of significantly greater fatality rates per industrial incident in industrialising/developing countries.

Long-term species loss and homogenization of moth communities in Central Europe.

PubMed

Valtonen, Anu; Hirka, Anikó; Szőcs, Levente; Ayres, Matthew P; Roininen, Heikki; Csóka, György

2017-07-01

As global biodiversity continues to decline steeply, it is becoming increasingly important to understand diversity patterns at local and regional scales. Changes in land use and climate, nitrogen deposition and invasive species are the most important threats to global biodiversity. Because land use changes tend to benefit a few species but impede many, the expected outcome is generally decreasing population sizes, decreasing species richness at local and regional scales, and increasing similarity of species compositions across sites (biotic homogenization). Homogenization can be also driven by invasive species or effects of soil eutrophication propagating to higher trophic levels. In contrast, in the absence of increasing aridity, climate warming is predicted to generally increase abundances and species richness of poikilotherms at local and regional scales. We tested these predictions with data from one of the few existing monitoring programmes on biodiversity in the world dating to the 1960s, where the abundance of 878 species of macro-moths have been measured daily at seven sites across Hungary. Our analyses revealed a dramatic rate of regional species loss and homogenization of community compositions across sites. Species with restricted distribution range, specialized diet or dry grassland habitat were more likely than others to disappear from the community. In global context, the contrasting effects of climate change and land use changes could explain why the predicted enriching effects from climate warming are not always realized. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Adaptive self-organization of Bali's ancient rice terraces.

PubMed

Lansing, J Stephen; Thurner, Stefan; Chung, Ning Ning; Coudurier-Curveur, Aurélie; Karakaş, Çağil; Fesenmyer, Kurt A; Chew, Lock Yue

2017-06-20

Spatial patterning often occurs in ecosystems as a result of a self-organizing process caused by feedback between organisms and the physical environment. Here, we show that the spatial patterns observable in centuries-old Balinese rice terraces are also created by feedback between farmers' decisions and the ecology of the paddies, which triggers a transition from local to global-scale control of water shortages and rice pests. We propose an evolutionary game, based on local farmers' decisions that predicts specific power laws in spatial patterning that are also seen in a multispectral image analysis of Balinese rice terraces. The model shows how feedbacks between human decisions and ecosystem processes can evolve toward an optimal state in which total harvests are maximized and the system approaches Pareto optimality. It helps explain how multiscale cooperation from the community to the watershed scale could persist for centuries, and why the disruption of this self-organizing system by the Green Revolution caused chaos in irrigation and devastating losses from pests. The model shows that adaptation in a coupled human-natural system can trigger self-organized criticality (SOC). In previous exogenously driven SOC models, adaptation plays no role, and no optimization occurs. In contrast, adaptive SOC is a self-organizing process where local adaptations drive the system toward local and global optima.

Outputs of paired Gabor filters summed across the background frame of reference predict the direction of movement

NASA Technical Reports Server (NTRS)

Lawton, Teri B.

1989-01-01

A cortical neural network that computes the visibility of shifts in the direction of movement is proposed. The network computes: (1) the magnitude of the position difference between the test and background patterns, (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern, and (3) using global processes that pool the output from paired even- and odd-symmetric simple and complex cells across the spatial extent of the background frame of reference the direction a test pattern moved relative to a textured background. Evidence that magnocellular pathways are used to discriminate the direction of movement is presented. Since magnocellular pathways are used to discriminate the direction of movement, this task is not affected by small pattern changes such as jitter, short presentations, blurring, and different background contrasts that result when the veiling illumination in a scene changes.

The niche of an invasive marine microbe in a subtropical freshwater impoundment

PubMed Central

David Hambright, K; Beyer, Jessica E; Easton, James D; Zamor, Richard M; Easton, Anne C; Hallidayschult, Thayer C

2015-01-01

Growing attention in aquatic ecology is focusing on biogeographic patterns in microorganisms and whether these potential patterns can be explained within the framework of general ecology. The long-standing microbiologist's credo ‘Everything is everywhere, but, the environment selects' suggests that dispersal is not limiting for microbes, but that the environment is the primary determining factor in microbial community composition. Advances in molecular techniques have provided new evidence that biogeographic patterns exist in microbes and that dispersal limitation may actually have an important role, yet more recent study using extremely deep sequencing predicts that indeed everything is everywhere. Using a long-term field study of the ‘invasive' marine haptophyte Prymnesium parvum, we characterize the environmental niche of P. parvum in a subtropical impoundment in the southern United States. Our analysis contributes to a growing body of evidence that indicates a primary role for environmental conditions, but not dispersal, in the lake-wide abundances and seasonal bloom patterns in this globally important microbe. PMID:24950108

Modeling long period swell in Southern California: Practical boundary conditions from buoy observations and global wave model predictions

NASA Astrophysics Data System (ADS)

Crosby, S. C.; O'Reilly, W. C.; Guza, R. T.

2016-02-01

Accurate, unbiased, high-resolution (in space and time) nearshore wave predictions are needed to drive models of beach erosion, coastal flooding, and alongshore transport of sediment, biota and pollutants. On highly sheltered shorelines, wave predictions are sensitive to the directions of onshore propagating waves, and nearshore model prediction error is often dominated by uncertainty in offshore boundary conditions. Offshore islands and shoals, and coastline curvature, create complex sheltering patterns over the 250km span of southern California (SC) shoreline. Here, regional wave model skill in SC was compared for different offshore boundary conditions created using offshore buoy observations and global wave model hindcasts (National Oceanographic and Atmospheric Administration Wave Watch 3, WW3). Spectral ray-tracing methods were used to transform incident offshore swell (0.04-0.09Hz) energy at high directional resolution (1-deg). Model skill is assessed for predictions (wave height, direction, and alongshore radiation stress) at 16 nearshore buoy sites between 2000 and 2009. Model skill using buoy-derived boundary conditions is higher than with WW3-derived boundary conditions. Buoy-driven nearshore model results are similar with various assumptions about the true offshore directional distribution (maximum entropy, Bayesian direct, and 2nd derivative smoothness). Two methods combining offshore buoy observations with WW3 predictions in the offshore boundary condition did not improve nearshore skill above buoy-only methods. A case example at Oceanside harbor shows strong sensitivity of alongshore sediment transport predictions to different offshore boundary conditions. Despite this uncertainty in alongshore transport magnitude, alongshore gradients in transport (e.g. the location of model accretion and erosion zones) are determined by the local bathymetry, and are similar for all predictions.

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

DOE PAGES

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; ...

2016-10-04

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

NASA Astrophysics Data System (ADS)

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; Hu, Aixue; Hamlington, Benjamin; Kenigson, Jessica; Palanisamy, Hindumathi; Thompson, Philip

2017-01-01

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth's climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modes and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this paper, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.

PET Imaging of Tau Deposition in the Aging Human Brain

PubMed Central

Schonhaut, Daniel R.; O’Neil, James P.; Janabi, Mustafa; Ossenkoppele, Rik; Baker, Suzanne L.; Vogel, Jacob W.; Faria, Jamie; Schwimmer, Henry D.; Rabinovici, Gil D.; Jagust, William J.

2016-01-01

SUMMARY Tau pathology is a hallmark of Alzheimer’s disease (AD) but also occurs in normal cognitive aging. Using the tau PET agent 18F-AV-1451, we examined retention patterns in cognitively normal older people in relation to young controls and AD patients. Age and β-amyloid (measured using PiB PET) were differentially associated with tau tracer retention in healthy aging. Older age was related to increased tracer retention in regions of the medial temporal lobe, which predicted worse episodic memory performance. PET detection of tau in other isocortical regions required the presence of cortical β-amyloid, and was associated with decline in global cognition. Furthermore, patterns of tracer retention corresponded well with Braak staging of neurofibrillary tau pathology. The present study defined patterns of tau tracer retention in normal aging in relation to age, cognition, and β-amyloid deposition. PMID:26938442

PET Imaging of Tau Deposition in the Aging Human Brain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schöll, Michael; Lockhart, Samuel N.; Schonhaut, Daniel R.

Tau pathology is a hallmark of Alzheimer’s disease (AD) but also occurs in normal cognitive aging. In this study, using the tau PET agent 18F-AV-1451, we examined retention patterns in cognitively normal older people in relation to young controls and AD patients. Age and β-amyloid (measured using PiB PET) were differentially associated with tau tracer retention in healthy aging. Older age was related to increased tracer retention in regions of the medial temporal lobe, which predicted worse episodic memory performance. PET detection of tau in other isocortical regions required the presence of cortical β-amyloid and was associated with decline inmore » global cognition. Furthermore, patterns of tracer retention corresponded well with Braak staging of neurofibrillary tau pathology. In conclusion, the present study defined patterns of tau tracer retention in normal aging in relation to age, cognition, and β-amyloid deposition.« less

PET Imaging of Tau Deposition in the Aging Human Brain

DOE PAGES

Schöll, Michael; Lockhart, Samuel N.; Schonhaut, Daniel R.; ...

2016-03-02

Tau pathology is a hallmark of Alzheimer’s disease (AD) but also occurs in normal cognitive aging. In this study, using the tau PET agent 18F-AV-1451, we examined retention patterns in cognitively normal older people in relation to young controls and AD patients. Age and β-amyloid (measured using PiB PET) were differentially associated with tau tracer retention in healthy aging. Older age was related to increased tracer retention in regions of the medial temporal lobe, which predicted worse episodic memory performance. PET detection of tau in other isocortical regions required the presence of cortical β-amyloid and was associated with decline inmore » global cognition. Furthermore, patterns of tracer retention corresponded well with Braak staging of neurofibrillary tau pathology. In conclusion, the present study defined patterns of tau tracer retention in normal aging in relation to age, cognition, and β-amyloid deposition.« less

Can a linguistic serial founder effect originating in Africa explain the worldwide phonemic cline?

PubMed Central

2016-01-01

It has been proposed that a serial founder effect could have caused the present observed pattern of global phonemic diversity. Here we present a model that simulates the human range expansion out of Africa and the subsequent spatial linguistic dynamics until today. It does not assume copying errors, Darwinian competition, reduced contrastive possibilities or any other specific linguistic mechanism. We show that the decrease of linguistic diversity with distance (from the presumed origin of the expansion) arises under three assumptions, previously introduced by other authors: (i) an accumulation rate for phonemes; (ii) small phonemic inventories for the languages spoken before the out-of-Africa dispersal; (iii) an increase in the phonemic accumulation rate with the number of speakers per unit area. Numerical simulations show that the predictions of the model agree with the observed decrease of linguistic diversity with increasing distance from the most likely origin of the out-of-Africa dispersal. Thus, the proposal that a serial founder effect could have caused the present observed pattern of global phonemic diversity is viable, if three strong assumptions are satisfied. PMID:27122180

Spatial Patterns in the Efficiency of the Biological Pump: What Controls Export Ratios at the Global Scale?

NASA Astrophysics Data System (ADS)

Moore, J. K.

2016-02-01

The efficiency of the biological pump is influenced by complex interactions between chemical, biological, and physical processes. The efficiency of export out of surface waters and down through the water column to the deep ocean has been linked to a number of factors including biota community composition, production of mineral ballast components, physical aggregation and disaggregation processes, and ocean oxygen concentrations. I will examine spatial patterns in the export ratio and the efficiency of the biological pump at the global scale using the Community Earth System Model (CESM). There are strong spatial variations in the export efficiency as simulated by the CESM, which are strongly correlated with new nutrient inputs to the euphotic zone and their impacts on phytoplankton community structure. I will compare CESM simulations that include dynamic, variable export ratios driven by the phytoplankton community structure, with simulations that impose a near-constant export ratio to examine the effects of export efficiency on nutrient and surface chlorophyll distributions. The model predicted export ratios will also be compared with recent satellite-based estimates.

Synchronization in Random Pulse Oscillator Networks

NASA Astrophysics Data System (ADS)

Brown, Kevin; Hermundstad, Ann

Motivated by synchronization phenomena in neural systems, we study synchronization of random networks of coupled pulse oscillators. We begin by considering binomial random networks whose nodes have intrinsic linear dynamics. We quantify order in the network spiking dynamics using a new measure: the normalized Lev-Zimpel complexity (LZC) of the nodes' spike trains. Starting from a globally-synchronized state, we see two broad classes of behaviors. In one (''temporally random''), the LZC is high and nodes spike independently with no coherent pattern. In another (''temporally regular''), the network does not globally synchronize but instead forms coherent, repeating population firing patterns with low LZC. No topological feature of the network reliably predicts whether an individual network will show temporally random or regular behavior; however, we find evidence that degree heterogeneity in binomial networks has a strong effect on the resulting state. To confirm these findings, we generate random networks with independently-adjustable degree mean and variance. We find that the likelihood of temporally-random behavior increases as degree variance increases. Our results indicate the subtle and complex relationship between network structure and dynamics.

Validation of the Gravity Model in Predicting the Global Spread of Influenza

PubMed Central

Li, Xinhai; Tian, Huidong; Lai, Dejian; Zhang, Zhibin

2011-01-01

The gravity model is often used in predicting the spread of influenza. We use the data of influenza A (H1N1) to check the model’s performance and validation, in order to determine the scope of its application. In this article, we proposed to model the pattern of global spread of the virus via a few important socio-economic indicators. We applied the epidemic gravity model for modelling the virus spread globally through the estimation of parameters of a generalized linear model. We compiled the daily confirmed cases of influenza A (H1N1) in each country as reported to the WHO and each state in the USA, and established the model to describe the relationship between the confirmed cases and socio-economic factors such as population size, per capita gross domestic production (GDP), and the distance between the countries/states and the country where the first confirmed case was reported (i.e., Mexico). The covariates we selected for the model were all statistically significantly associated with the global spread of influenza A (H1N1). However, within the USA, the distance and GDP were not significantly associated with the number of confirmed cases. The combination of the gravity model and generalized linear model provided a quick assessment of pandemic spread globally. The gravity model is valid if the spread period is long enough for estimating the model parameters. Meanwhile, the distance between donor and recipient communities has a good gradient. Besides, the spread should be at the early stage if a single source is taking into account. PMID:21909295

Validation of the gravity model in predicting the global spread of influenza.

PubMed

Li, Xinhai; Tian, Huidong; Lai, Dejian; Zhang, Zhibin

2011-08-01

The gravity model is often used in predicting the spread of influenza. We use the data of influenza A (H1N1) to check the model's performance and validation, in order to determine the scope of its application. In this article, we proposed to model the pattern of global spread of the virus via a few important socio-economic indicators. We applied the epidemic gravity model for modelling the virus spread globally through the estimation of parameters of a generalized linear model. We compiled the daily confirmed cases of influenza A (H1N1) in each country as reported to the WHO and each state in the USA, and established the model to describe the relationship between the confirmed cases and socio-economic factors such as population size, per capita gross domestic production (GDP), and the distance between the countries/states and the country where the first confirmed case was reported (i.e., Mexico). The covariates we selected for the model were all statistically significantly associated with the global spread of influenza A (H1N1). However, within the USA, the distance and GDP were not significantly associated with the number of confirmed cases. The combination of the gravity model and generalized linear model provided a quick assessment of pandemic spread globally. The gravity model is valid if the spread period is long enough for estimating the model parameters. Meanwhile, the distance between donor and recipient communities has a good gradient. Besides, the spread should be at the early stage if a single source is taking into account.

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

DOE PAGES

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.; ...

2017-01-31

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Spatiotemporal patterns of terrestrial gross primary production: A review

NASA Astrophysics Data System (ADS)

Anav, Alessandro; Friedlingstein, Pierre; Beer, Christian; Ciais, Philippe; Harper, Anna; Jones, Chris; Murray-Tortarolo, Guillermo; Papale, Dario; Parazoo, Nicholas C.; Peylin, Philippe; Piao, Shilong; Sitch, Stephen; Viovy, Nicolas; Wiltshire, Andy; Zhao, Maosheng

2015-09-01

Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990-2009) from two observation-based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon-climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation-based data that show little IAV and trend, while the process-based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation-based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.

Conveying Global Circulation Patterns in HDTV

NASA Astrophysics Data System (ADS)

Gardiner, N.; Janowiak, J.; Kinzler, R.; Trakinski, V.

2006-12-01

The American Museum of Natural History has partnered with the National Centers for Environmental Prediction (NCEP) to educate general audiences about weather and climate using high definition video broadcasts built from half-hourly global mosaics of infrared (IR) data from five geostationary satellites. The dataset being featured was developed by NCEP to improve precipitation estimates from microwave data that have finer spatial resolution but poorer temporal coverage. The IR data span +/-60 degrees latitude and show circulation patterns at sufficient resolution to teach informal science center visitors about both weather and climate events and concepts. Design and editorial principles for this media program have been guided by lessons learned from production and annual updates of visualizations that cover eight themes in both biological and Earth system sciences. Two formative evaluations on two dates, including interviews and written surveys of 480 museum visitors ranging in age from 13 to over 60, helped refine the design and implementation of the weather and climate program and demonstrated that viewers understood the program's initial literacy objectives, including: (1) conveying the passage of time and currency of visualized data; (2) geographic relationships inherent to atmospheric circulation patterns; and (3) the authenticity of visualized data, i.e., their origin from earth-orbiting satellites. Surveys also indicated an interest and willingness to learn more about weather and climate principles and events. Expanded literacy goals guide ongoing, biweekly production and distribution of global cloud visualization pieces that reach combined audiences of approximately 10 million. Two more rounds of evaluation are planned over the next two years to assess the effectiveness of the media program in addressing these expanded literacy goals.

Updated Global Patterns of Drought and Heat-Induced Forest Die-off, and Ecohydrological Feedbacks

NASA Astrophysics Data System (ADS)

Allen, C. D.

2011-12-01

Ongoing climate changes - particularly increases in mean temperatures as well as frequencies, durations, and severities of extreme drought and heat - can amplify tree physiological stress and thereby drive increases in both background tree mortality rates and episodes of rapid, broad-scale forest die-off. Updates are presented to a recent global synthesis of documented tree mortality episodes attributed to drought and/or heat, further expanding the documented spatial distribution and demonstrating the vulnerability of all major forest types from tropical moist forests and savannas to temperate and boreal forests. Given that anthropogenic climate change is projected to drive substantial increases in both mean temperatures and the frequency/duration/severity of extreme drought and heat in many regions, recent episodes of broad-scale drought-induced forest mortality may reflect increasing global risks of forest die-off, even in environments not normally considered water-limited. Since vegetation cover patterns are closely and interactively linked with ecosystem water fluxes, episodes of massive forest die-off can be expected to significantly affect ecohydrological patterns and processes, ranging from runoff and erosion to evaporation and transpiration, often with nonlinear threshold responses expected. Diverse examples of such feedbacks between climate-induced forest mortality and ecohydrology are presented, ranging from detailed observations of linked changes in vegetation, runoff, and erosion in response to forest mortality in the southwestern US to Western Australia and Amazonian rainforest water cycling. Current research efforts to address the large knowledge gaps that at present hinder our ability to predict climate-induced forest mortality and associated ecohydrological responses are discussed.

Benchmarking carbon-nitrogen interactions in Earth System Models to observations: An inter-comparison of nitrogen limitation in global land surface models with carbon and nitrogen cycles (CLM-CN and O-CN)

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Zaehle, S.; Templer, P. H.; Goodale, C. L.

2011-12-01

Predictions of climate change depend on accurately modeling the feedbacks among the carbon cycle, nitrogen cycle, and climate system. Several global land surface models have shown that nitrogen limitation determines how land carbon fluxes respond to rising CO2, nitrogen deposition, and climate change, thereby influencing predictions of climate change. However, the magnitude of the carbon-nitrogen-climate feedbacks varies considerably by model, leading to critical and timely questions of why they differ and how they compare to field observations. To address these questions, we initiated a model inter-comparison of spatial patterns and drivers of nitrogen limitation. The experiment assessed the regional consequences of sustained nitrogen additions in a set of 25-year global nitrogen fertilization simulations. The model experiments were designed to cover effects from small changes in nitrogen inputs associated with plausible increases in nitrogen deposition to large changes associated with field-based nitrogen fertilization experiments. The analyses of model simulations included assessing the geographically varying degree of nitrogen limitation on plant and soil carbon cycling and the mechanisms underlying model differences. Here, we present results from two global land-surface models (CLM-CN and O-CN) with differing approaches to modeling carbon-nitrogen interactions. The predictions from each model were compared to a set of globally distributed observational data that includes nitrogen fertilization experiments, 15N tracer studies, small catchment nitrogen input-output studies, and syntheses across nitrogen deposition gradients. Together these datasets test many aspects of carbon-nitrogen coupling and are able to differentiate between the two models. Overall, this study is the first to explicitly benchmark carbon and nitrogen interactions in Earth System Models using a range of observations and is a foundation for future inter-comparisons.

Assessing the Impact of Observations on the Prediction of Effective Atmospheric Angular Momentum from NAVGEM

NASA Astrophysics Data System (ADS)

Baker, N. L.; Langland, R.

2016-12-01

Variations in Earth rotation are measured by comparing a time based on Earth's variable rotation rate about its axis to a time standard based on an internationally coordinated ensemble of atomic clocks that provide a uniform time scale. The variability of Earth's rotation is partly due to the changes in angular momentum that occur in the atmosphere and ocean as weather patterns and ocean features develop, propagate, and dissipate. The NAVGEM Effective Atmospheric Angular Momentum Functions (EAAMF) and their predictions are computed following Barnes et al. (1983), and provided to the U.S. Naval Observatory daily. These along with similar data from the NOAA GFS model are used to calculate and predict the Earth orientation parameters (Stamatakos et al., 2016). The Navy's high-resolution global weather prediction system consists of the Navy Global Environmental Model (NAVGEM; Hogan et al., 2014) and a hybrid four-dimensional variational data assimilation system (4DVar) (Kuhl et al., 2013). An important component of NAVGEM is the Forecast Sensitivity Observation Impact (FSOI). FSOI is a mathematical method to quantify the contribution of individual observations or sets of observations to the reduction in the 24-hr forecast error (Langland and Baker, 2004). The FSOI allows for dynamic monitoring of the relative quality and value of the observations assimilated by NAVGEM, and the relative ability of the data assimilation system to effectively use the observation information to generate an improved forecast. For this study, along with the FSOI based on the global moist energy error norm, we computed the FSOI using an error norm based on the Effective Angular Momentum Functions. This modification allowed us to assess which observations were most beneficial in reducing the 24-hr forecast error for the atmospheric angular momentum.

Predicting the persistence of coastal wetlands to global change stressors

USGS Publications Warehouse

Guntenspergen, G.; McKee, K.; Cahoon, D.; Grace, J.; Megonigal, P.

2006-01-01

Despite progress toward understanding the response of coastal wetlands to increases in relative sea-level rise and an improved understanding of the effect of elevated CO2 on plant species allocation patterns, we are limited in our ability to predict the response of coastal wetlands to the effects associated with global change. Static simulations of the response of coastal wetlands to sea-level rise using LIDAR and GIS lack the biological and physical feedback mechanisms present in such systems. Evidence from current research suggests that biotic processes are likely to have a major influence on marsh vulnerability to future accelerated rates of sea-level rise and the influence of biotic processes likely varies depending on hydrogeomorphic setting and external stressors. We have initiated a new research approach using a series of controlled mesocosm and field experiments, landscape scale studies, a comparative network of brackish coastal wetland monitoring sites and a suite of predictive models that address critical questions regarding the vulnerability of coastal brackish wetland systems to global change. Specifically, this research project evaluates the interaction of sea level rise and elevated CO2 concentrations with flooding, nutrient enrichment and disturbance effects. The study is organized in a hierarchical structure that links mesocosm, field, landscape and biogeographic levels so as to provide important new information that recognizes that coastal wetland systems respond to multiple interacting drivers and feedback effects controlling wetland surface elevation, habitat stability and ecosystem function. We also present a new statistical modelling technique (Structural Equation Modelling) that synthesizes and integrates our environmental and biotic measures in a predictive framework that forecasts ecosystem change and informs managers to consider adaptive shifts in strategies for the sustainable management of coastal wetlands.

[Predicting the impact of global warming on the geographical distribution pattern of Quercus variabilis in China].

PubMed

Li, Yao; Zhang, Xing-wang; Fang, Yan-ming

2014-12-01

The geographical distribution of Quercus variabilis in China with its climate characteristics was analyzed based on DIVA-GIS which was also used to estimate the response of future potential distribution to global warming by Bioclim and Domain models. Analysis results showed the geographical distribution of Q. variabilis could be divided into 7 subregions: Henduan Mountains, Yunnan-Guizhou Plateau, North China, East China, Liaodong-Shandong Peninsula, Taiwan Island, and Qinling-Daba Mountains. These subregions are across 7 temperature zones, 2 moisture regions and 17 climatic subregions, including 8 climate types. The modern abundance center of Q. variabilis is Qinling, Daba and Funiu mountains. The condition of mean annual temperature 7.5-19.8 degrees C annual precipitation 471-1511 mm, is suitable for Q. variabilis. Areas under the receiver operating characteristic curve (AUC values), of Domain and Boiclim models were 0.910, 0.779; the former predicted that the potential regions of high suitability for Q. variabilis are Qinling, Daba, Funiu, Tongbai, and Dabie mountains, eastern and western Yunnan-Guizhou Plateau, hills of southern Jiangsu and Anhui, part of the mountains in North China. Global warming might lead to the shrinking in suitable region and retreating from the south for Q. variabilis.

The impact of Cenozoic cooling on assemblage diversity in planktonic foraminifera

PubMed Central

Pearson, Paul N.; Dunkley Jones, Tom; Farnsworth, Alexander; Lunt, Daniel J.; Markwick, Paul; Purvis, Andy

2016-01-01

The Cenozoic planktonic foraminifera (PF) (calcareous zooplankton) have arguably the most detailed fossil record of any group. The quality of this record allows models of environmental controls on macroecology, developed for Recent assemblages, to be tested on intervals with profoundly different climatic conditions. These analyses shed light on the role of long-term global cooling in establishing the modern latitudinal diversity gradient (LDG)—one of the most powerful generalizations in biogeography and macroecology. Here, we test the transferability of environment-diversity models developed for modern PF assemblages to the Eocene epoch (approx. 56–34 Ma), a time of pronounced global warmth. Environmental variables from global climate models are combined with Recent environment–diversity models to predict Eocene richness gradients, which are then compared with observed patterns. The results indicate the modern LDG—lower richness towards the poles—developed through the Eocene. Three possible causes are suggested for the mismatch between statistical model predictions and data in the Early Eocene: the environmental estimates are inaccurate, the statistical model misses a relevant variable, or the intercorrelations among facets of diversity—e.g. richness, evenness, functional diversity—have changed over geological time. By the Late Eocene, environment–diversity relationships were much more similar to those found today. PMID:26977064

Climate-Induced Range Shifts and Possible Hybridisation Consequences in Insects

PubMed Central

Sánchez-Guillén, Rosa Ana; Muñoz, Jesús; Rodríguez-Tapia, Gerardo; Feria Arroyo, T. Patricia; Córdoba-Aguilar, Alex

2013-01-01

Many ectotherms have altered their geographic ranges in response to rising global temperatures. Current range shifts will likely increase the sympatry and hybridisation between recently diverged species. Here we predict future sympatric distributions and risk of hybridisation in seven Mediterranean ischnurid damselfly species (I. elegans, I. fountaineae, I. genei, I. graellsii, I. pumilio, I. saharensis and I. senegalensis). We used a maximum entropy modelling technique to predict future potential distribution under four different Global Circulation Models and a realistic emissions scenario of climate change. We carried out a comprehensive data compilation of reproductive isolation (habitat, temporal, sexual, mechanical and gametic) between the seven studied species. Combining the potential distribution and data of reproductive isolation at different instances (habitat, temporal, sexual, mechanical and gametic), we infer the risk of hybridisation in these insects. Our findings showed that all but I. graellsii will decrease in distributional extent and all species except I. senegalensis are predicted to have northern range shifts. Models of potential distribution predicted an increase of the likely overlapping ranges for 12 species combinations, out of a total of 42 combinations, 10 of which currently overlap. Moreover, the lack of complete reproductive isolation and the patterns of hybridisation detected between closely related ischnurids, could lead to local extinctions of native species if the hybrids or the introgressed colonising species become more successful. PMID:24260411

Biogeographic patterns in below-ground diversity in New York City's Central Park are similar to those observed globally.

PubMed

Ramirez, Kelly S; Leff, Jonathan W; Barberán, Albert; Bates, Scott Thomas; Betley, Jason; Crowther, Thomas W; Kelly, Eugene F; Oldfield, Emily E; Shaw, E Ashley; Steenbock, Christopher; Bradford, Mark A; Wall, Diana H; Fierer, Noah

2014-11-22

Soil biota play key roles in the functioning of terrestrial ecosystems, however, compared to our knowledge of above-ground plant and animal diversity, the biodiversity found in soils remains largely uncharacterized. Here, we present an assessment of soil biodiversity and biogeographic patterns across Central Park in New York City that spanned all three domains of life, demonstrating that even an urban, managed system harbours large amounts of undescribed soil biodiversity. Despite high variability across the Park, below-ground diversity patterns were predictable based on soil characteristics, with prokaryotic and eukaryotic communities exhibiting overlapping biogeographic patterns. Further, Central Park soils harboured nearly as many distinct soil microbial phylotypes and types of soil communities as we found in biomes across the globe (including arctic, tropical and desert soils). This integrated cross-domain investigation highlights that the amount and patterning of novel and uncharacterized diversity at a single urban location matches that observed across natural ecosystems spanning multiple biomes and continents. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Asian summer monsoon seasonal prediction skill in the Met Office GloSea5 model and its dependence on mean state biases

NASA Astrophysics Data System (ADS)

Bush, Stephanie; Turner, Andrew; Martin, Gill; Woolnough, Steve

2015-04-01

Predicting the circulation and precipitation features of the Asian monsoon on time scales of weeks to the season ahead remains a challenge for prediction centres. Current state-of-the-art models retain large biases, particularly dryness over India, which evolve rapidly from initialization and persist into centennial length climate integrations, illustrating the seamless nature of the monsoon problem. We present initial results from our Ministry of Earth Sciences Indian Monsoon Mission collaboration project to assess and improve weekly-to-seasonal forecasts in the Met Office Unified Model (MetUM) coupled initialized Global Seasonal Prediction System (GloSea5). Using a 14-year hindcast ensemble of integrations in which atmosphere, ocean and sea-ice components are initialized from May start dates, we assess the monsoon seasonal prediction skill and global mean state biases of GloSea5. Initial May and June biases include a lack of precipitation over the Indian peninsula, and a weakened monsoon flow, and these give way to a more robust pattern of excess precipitation in the western north Pacific, lack of precipitation over the Maritime Continent, excess westerlies across the Indian peninsula and Indochina, and cool SSTs in the eastern equatorial Indian Ocean and western north Pacific in July and August. Despite these mean state biases, the interannual correlation of predicted JJA all India rainfall from 1998 to 2009 with TRMM is fairly high at 0.68. Future work will focus on the prospects for further improving this skill with bias correction techniques.

Antarctic ice-sheet loss driven by basal melting of ice shelves.

PubMed

Pritchard, H D; Ligtenberg, S R M; Fricker, H A; Vaughan, D G; van den Broeke, M R; Padman, L

2012-04-25

Accurate prediction of global sea-level rise requires that we understand the cause of recent, widespread and intensifying glacier acceleration along Antarctic ice-sheet coastal margins. Atmospheric and oceanic forcing have the potential to reduce the thickness and extent of floating ice shelves, potentially limiting their ability to buttress the flow of grounded tributary glaciers. Indeed, recent ice-shelf collapse led to retreat and acceleration of several glaciers on the Antarctic Peninsula. But the extent and magnitude of ice-shelf thickness change, the underlying causes of such change, and its link to glacier flow rate are so poorly understood that its future impact on the ice sheets cannot yet be predicted. Here we use satellite laser altimetry and modelling of the surface firn layer to reveal the circum-Antarctic pattern of ice-shelf thinning through increased basal melt. We deduce that this increased melt is the primary control of Antarctic ice-sheet loss, through a reduction in buttressing of the adjacent ice sheet leading to accelerated glacier flow. The highest thinning rates occur where warm water at depth can access thick ice shelves via submarine troughs crossing the continental shelf. Wind forcing could explain the dominant patterns of both basal melting and the surface melting and collapse of Antarctic ice shelves, through ocean upwelling in the Amundsen and Bellingshausen seas, and atmospheric warming on the Antarctic Peninsula. This implies that climate forcing through changing winds influences Antarctic ice-sheet mass balance, and hence global sea level, on annual to decadal timescales.

The Determination of Children's Knowledge of Global Lunar Patterns from Online Essays Using Text Mining Analysis

ERIC Educational Resources Information Center

Cheon, Jongpil; Lee, Sangno; Smith, Walter; Song, Jaeki; Kim, Yongjin

2013-01-01

The purpose of this study was to use text mining analysis of early adolescents' online essays to determine their knowledge of global lunar patterns. Australian and American students in grades five to seven wrote about global lunar patterns they had discovered by sharing observations with each other via the Internet. These essays were analyzed for…

Regional mantle upwelling on Venus: The Beta-Atla-Themis anomaly and correlation with global tectonic patterns

NASA Technical Reports Server (NTRS)

Crumpler, L. S.; Head, J. W.; Aubele, Jayne C.

1993-01-01

The morphology and global distribution of volcanic centers and their association with other geological characteristics offers significant insight into the global patterns of geology, tectonic style, thermal state, and interior dynamics of Venus. Magellan data permit the detailed geological interpretation necessary to address questions about interior dynamics of Venus particularly as they reflect relatively physical, chemical, and thermal conditions of the interior. This paper focuses on the distribution of anomalous concentrations of volcanic centers on Venus and regional patterns of tectonic deformation as it may relate to the identification of global internal anomalies, including mantle dynamic, petrological, or thermal patterns.

Patterns of Activity in A Global Model of A Solar Active Region

NASA Technical Reports Server (NTRS)

Bradshaw, S. J.; Viall, N. M.

2016-01-01

In this work we investigate the global activity patterns predicted from a model active region heated by distributions of nanoflares that have a range of frequencies. What differs is the average frequency of the distributions. The activity patterns are manifested in time lag maps of narrow-band instrument channel pairs. We combine hydrodynamic and forward modeling codes with a magnetic field extrapolation to create a model active region and apply the time lag method to synthetic observations. Our aim is not to reproduce a particular set of observations in detail, but to recover some typical properties and patterns observed in active regions. Our key findings are the following. (1) Cooling dominates the time lag signature and the time lags between the channel pairs are generally consistent with observed values. (2) Shorter coronal loops in the core cool more quickly than longer loops at the periphery. (3) All channel pairs show zero time lag when the line of sight passes through coronal loop footpoints. (4) There is strong evidence that plasma must be re-energized on a timescale comparable to the cooling timescale to reproduce the observed coronal activity, but it is likely that a relatively broad spectrum of heating frequencies are operating across active regions. (5) Due to their highly dynamic nature, we find nanoflare trains produce zero time lags along entire flux tubes in our model active region that are seen between the same channel pairs in observed active regions.

Mechanisms of Age-Related Decline in Memory Search Across the Adult Life Span

PubMed Central

Hills, Thomas T.; Mata, Rui; Wilke, Andreas; Samanez-Larkin, Gregory R.

2013-01-01

Three alternative mechanisms for age-related decline in memory search have been proposed, which result from either reduced processing speed (global slowing hypothesis), overpersistence on categories (cluster-switching hypothesis), or the inability to maintain focus on local cues related to a decline in working memory (cue-maintenance hypothesis). We investigated these 3 hypotheses by formally modeling the semantic recall patterns of 185 adults between 27 to 99 years of age in the animal fluency task (Thurstone, 1938). The results indicate that people switch between global frequency-based retrieval cues and local item-based retrieval cues to navigate their semantic memory. Contrary to the global slowing hypothesis that predicts no qualitative differences in dynamic search processes and the cluster-switching hypothesis that predicts reduced switching between retrieval cues, the results indicate that as people age, they tend to switch more often between local and global cues per item recalled, supporting the cue-maintenance hypothesis. Additional support for the cue-maintenance hypothesis is provided by a negative correlation between switching and digit span scores and between switching and total items recalled, which suggests that cognitive control may be involved in cue maintenance and the effective search of memory. Overall, the results are consistent with age-related decline in memory search being a consequence of reduced cognitive control, consistent with models suggesting that working memory is related to goal perseveration and the ability to inhibit distracting information. PMID:23586941

Global estimates of boreal forest carbon stocks and flux

NASA Astrophysics Data System (ADS)

Bradshaw, Corey J. A.; Warkentin, Ian G.

2015-05-01

The boreal ecosystem is an important global reservoir of stored carbon and a haven for diverse biological communities. The natural disturbance dynamics there have historically been driven by fire and insects, with human-mediated disturbances increasing faster than in other biomes globally. Previous research on the total boreal carbon stock and predictions of its future flux reveal high uncertainty in regional patterns. We reviewed and standardised this extensive body of quantitative literature to provide the most up-to-date and comprehensive estimates of the global carbon balance in the boreal forest. We also compiled century-scale predictions of the carbon budget flux. Our review and standardisation confirmed high uncertainty in the available data, but there is evidence that the region's total carbon stock has been underestimated. We found a total carbon store of 367.3 to 1715.8 Pg (1015 g), the mid-point of which (1095 Pg) is between 1.3 and 3.8 times larger than any previous mean estimates. Most boreal carbon resides in its soils and peatlands, although estimates are highly uncertain. We found evidence that the region might become a net carbon source following a reduction in carbon uptake rate from at least the 1980s. Given that the boreal potentially constitutes the largest terrestrial carbon source in the world, in one of the most rapidly warming parts of the globe (Walsh, 2014), how we manage these stocks will be influential on future climate dynamics.

The structure of parasite communities in fish hosts: ecology meets geography and climate.

PubMed

Poulin, R

2007-09-01

Parasite communities in fish hosts are not uniform in space: their diversity, composition and abundance vary across the geographical range of a host species. Increasingly urgently, we need to understand the geographic component of parasite communities to better predict how they will respond to global climate change. Patterns of geographical variation in the abundance of parasite populations, and in the diversity and composition of parasite communities, are explored here, and the ways in which they may be affected by climate change are discussed. The time has come to transform fish parasite ecology from a mostly descriptive discipline into a predictive science, capable of integrating complex ecological data to generate forecasts about the future state of host-parasite systems.

A USCLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Wang, Hailan; Koster, Randal; Weaver, Scott; Gutzler, David; Dai, Aiguo; Delworth, Tom; Deser, Clara; Findell, Kristen; Fu, Rong;

Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate.

PubMed

Beer, Christian; Reichstein, Markus; Tomelleri, Enrico; Ciais, Philippe; Jung, Martin; Carvalhais, Nuno; Rödenbeck, Christian; Arain, M Altaf; Baldocchi, Dennis; Bonan, Gordon B; Bondeau, Alberte; Cescatti, Alessandro; Lasslop, Gitta; Lindroth, Anders; Lomas, Mark; Luyssaert, Sebastiaan; Margolis, Hank; Oleson, Keith W; Roupsard, Olivier; Veenendaal, Elmar; Viovy, Nicolas; Williams, Christopher; Woodward, F Ian; Papale, Dario

2010-08-13

Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.

Plant diversity increases with the strength of negative density dependence at the global scale

USGS Publications Warehouse

LaManna, Joseph A.; Mangan, Scott A.; Alonso, Alfonso; Bourg, Norman; Brockelman, Warren Y.; Bunyavejchewin, Sarayudh; Chang, Li-Wan; Chiang, Jyh-Min; Chuyong, George B.; Clay, Keith; Condit, Richard; Cordell, Susan; Davies, Stuart J.; Furniss, Tucker J.; Giardina, Christian P.; Gunatilleke, I.A.U. Nimal; Gunatilleke, C.V. Savitri; He, Fangliang; Howe, Robert W.; Hubbell, Stephen P.; Hsieh, Chang-Fu; Inman-Narahari, Faith M.; Janik, David; Johnson, Daniel J.; Kenfack, David; Korte, Lisa; Kral, Kamil; Larson, Andrew J.; Lutz, James A.; McMahon, Sean M.; McShea, William J.; Memiaghe, Herve R.; Nathalang, Anuttara; Novotny, Vojtech; Ong, Perry S.; Orwig, David A.; Ostertag, Rebecca; Parker, Geoffrey G.; Phillips, Richard P.; Sack, Lawren; Sun, I-Fang; Tello, J. Sebastian; Thomas, Duncan W.; Turner, Benjamin L.; Vela Diaz, Dilys M.; Vrska, Tomas; Weiblen, George D.; Wolf, Amy; Yap, Sandra; Myers, Jonathan A.

2017-01-01

Theory predicts that higher biodiversity in the tropics is maintained by specialized interactions among plants and their natural enemies that result in conspecific negative density dependence (CNDD). By using more than 3000 species and nearly 2.4 million trees across 24 forest plots worldwide, we show that global patterns in tree species diversity reflect not only stronger CNDD at tropical versus temperate latitudes but also a latitudinal shift in the relationship between CNDD and species abundance. CNDD was stronger for rare species at tropical versus temperate latitudes, potentially causing the persistence of greater numbers of rare species in the tropics. Our study reveals fundamental differences in the nature of local-scale biotic interactions that contribute to the maintenance of species diversity across temperate and tropical communities.

Global Neuromagnetic Cortical Fields Have Non-Zero Velocity

PubMed Central

Alexander, David M.; Nikolaev, Andrey R.; Jurica, Peter; Zvyagintsev, Mikhail; Mathiak, Klaus; van Leeuwen, Cees

2016-01-01

Globally coherent patterns of phase can be obscured by analysis techniques that aggregate brain activity measures across-trials, whether prior to source localization or for estimating inter-areal coherence. We analyzed, at single-trial level, whole head MEG recorded during an observer-triggered apparent motion task. Episodes of globally coherent activity occurred in the delta, theta, alpha and beta bands of the signal in the form of large-scale waves, which propagated with a variety of velocities. Their mean speed at each frequency band was proportional to temporal frequency, giving a range of 0.06 to 4.0 m/s, from delta to beta. The wave peaks moved over the entire measurement array, during both ongoing activity and task-relevant intervals; direction of motion was more predictable during the latter. A large proportion of the cortical signal, measurable at the scalp, exists as large-scale coherent motion. We argue that the distribution of observable phase velocities in MEG is dominated by spatial filtering considerations in combination with group velocity of cortical activity. Traveling waves may index processes involved in global coordination of cortical activity. PMID:26953886

Continental drift and climate change drive instability in insect assemblages

NASA Astrophysics Data System (ADS)

Li, Fengqing; Tierno de Figueroa, José Manuel; Lek, Sovan; Park, Young-Seuk

2015-06-01

Global change has already had observable effects on ecosystems worldwide, and the accelerated rate of global change is predicted in the future. However, the impacts of global change on the stability of biodiversity have not been systematically studied in terms of both large spatial (continental drift) and temporal (from the last inter-glacial period to the next century) scales. Therefore, we analyzed the current geographical distribution pattern of Plecoptera, a thermally sensitive insect group, and evaluated its stability when coping with global change across both space and time throughout the Mediterranean region—one of the first 25 global biodiversity hotspots. Regional biodiversity of Plecoptera reflected the geography in both the historical movements of continents and the current environmental conditions in the western Mediterranean region. The similarity of Plecoptera assemblages between areas in this region indicated that the uplift of new land and continental drift were the primary determinants of the stability of regional biodiversity. Our results revealed that climate change caused the biodiversity of Plecoptera to slowly diminish in the past and will cause remarkably accelerated biodiversity loss in the future. These findings support the theory that climate change has had its greatest impact on biodiversity over a long temporal scale.

Continental drift and climate change drive instability in insect assemblages

PubMed Central

Li, Fengqing; Tierno de Figueroa, José Manuel; Lek, Sovan; Park, Young-Seuk

2015-01-01

Global change has already had observable effects on ecosystems worldwide, and the accelerated rate of global change is predicted in the future. However, the impacts of global change on the stability of biodiversity have not been systematically studied in terms of both large spatial (continental drift) and temporal (from the last inter-glacial period to the next century) scales. Therefore, we analyzed the current geographical distribution pattern of Plecoptera, a thermally sensitive insect group, and evaluated its stability when coping with global change across both space and time throughout the Mediterranean region—one of the first 25 global biodiversity hotspots. Regional biodiversity of Plecoptera reflected the geography in both the historical movements of continents and the current environmental conditions in the western Mediterranean region. The similarity of Plecoptera assemblages between areas in this region indicated that the uplift of new land and continental drift were the primary determinants of the stability of regional biodiversity. Our results revealed that climate change caused the biodiversity of Plecoptera to slowly diminish in the past and will cause remarkably accelerated biodiversity loss in the future. These findings support the theory that climate change has had its greatest impact on biodiversity over a long temporal scale. PMID:26081036

Continental drift and climate change drive instability in insect assemblages.

PubMed

Li, Fengqing; Tierno de Figueroa, José Manuel; Lek, Sovan; Park, Young-Seuk

2015-06-17

Global change has already had observable effects on ecosystems worldwide, and the accelerated rate of global change is predicted in the future. However, the impacts of global change on the stability of biodiversity have not been systematically studied in terms of both large spatial (continental drift) and temporal (from the last inter-glacial period to the next century) scales. Therefore, we analyzed the current geographical distribution pattern of Plecoptera, a thermally sensitive insect group, and evaluated its stability when coping with global change across both space and time throughout the Mediterranean region--one of the first 25 global biodiversity hotspots. Regional biodiversity of Plecoptera reflected the geography in both the historical movements of continents and the current environmental conditions in the western Mediterranean region. The similarity of Plecoptera assemblages between areas in this region indicated that the uplift of new land and continental drift were the primary determinants of the stability of regional biodiversity. Our results revealed that climate change caused the biodiversity of Plecoptera to slowly diminish in the past and will cause remarkably accelerated biodiversity loss in the future. These findings support the theory that climate change has had its greatest impact on biodiversity over a long temporal scale.

Attachment, Symptom Severity, and Depression in Medically Unexplained Musculoskeletal Pain and Osteoarthritis: A Cross-Sectional Study

PubMed Central

Schroeter, Corinna; Ehrenthal, Johannes C.; Giulini, Martina; Neubauer, Eva; Gantz, Simone; Amelung, Dorothee; Balke, Doreen; Schiltenwolf, Marcus

2015-01-01

Background Attachment insecurity relates to the onset and course of chronic pain via dysfunctional reactions to pain. However, few studies have investigated the proportion of insecure attachment styles in different pain conditions, and results regarding associations between attachment, pain severity, and disability in chronic pain are inconsistent. This study aims to clarify the relationships between insecure attachment and occurrence or severity of chronic pain with and without clearly defined organic cause. To detect potential differences in the importance of global and romantic attachment representations, we included both concepts in our study. Methods 85 patients with medically unexplained musculoskeletal pain (UMP) and 89 patients with joint pain from osteoarthritis (OA) completed self-report measures of global and romantic attachment, pain intensity, physical functioning, and depression. Results Patients reporting global insecure attachment representations were more likely to suffer from medically unexplained musculoskeletal pain (OR 3.4), compared to securely attached patients. Romantic attachment did not differ between pain conditions. Pain intensity was associated with romantic attachment anxiety, and this relationship was more pronounced in the OA group compared to the UMP group. Both global and romantic attachment anxiety predicted depression, accounting for 15% and 17% of the variance, respectively. Disability was independent from attachment patterns. Conclusions Our results indicate that global insecure attachment is associated with the experience of medically unexplained musculoskeletal pain, but not with osteoarthritis. In contrast, insecure attachment patterns seem to be linked to pain intensity and pain-related depression in unexplained musculoskeletal pain and in osteoarthritis. These findings suggest that relationship-informed focused treatment strategies may alleviate pain severity and psychological distress in chronic pain independent of underlying pathology. PMID:25807172

Historical Pattern and Future Trajectories of Terrestrial N2O Emission driven by Multi-factor Global Changes

NASA Astrophysics Data System (ADS)

Lu, C.; Tian, H.; Yang, J.; Zhang, B.; Xu, R.

2015-12-01

Nitrous oxide (N2O) is among the most important greenhouse gases only next to carbon dioxide (CO2) and methane (CH4) due to its long life time and high radiative forcing (with a global warming potential 265 times as much as CO2 at 100-year time horizon). The Atmospheric concentration of N2O has increased by 20% since pre-industrial era, and this increase plays a significant role in shaping anthropogenic climate change. However, compared to CO2- and CH4-related research, fewer studies have been performed in assessing and predicting the spatiotemporal patterns of N2O emission from natural and agricultural soils. Here we used a coupled biogeochemical model, DLEM, to quantify the historical and future changes in global terrestrial N2O emissions resulting from natural and anthropogenic perturbations including climate variability, atmospheric CO2 concentration, nitrogen deposition, land use and land cover changes, and agricultural land management practices (i.e., synthetic nitrogen fertilizer use, manure application, and irrigation etc.) over the period 1900-2099. We focused on inter-annual variation and long-term trend of terrestrial N2O emission driven by individual and combined environmental changes during historical and future periods. The sensitivity of N2O emission to climate, atmospheric composition, and human activities has been examined at biome-, latitudinal, continental and global scales. Future projections were conducted to identify the hot spots and hot time periods of global N2O emission under two emission scenarios (RCP2.6 and RCP8.5). It provides a modeling perspective for understanding human-induced N2O emission growth and developing potential management strategies to mitigate further atmospheric N2O increase and climate warming.

Single-trial decoding of auditory novelty responses facilitates the detection of residual consciousness

PubMed Central

King, J.R.; Faugeras, F.; Gramfort, A.; Schurger, A.; El Karoui, I.; Sitt, J.D.; Rohaut, B.; Wacongne, C.; Labyt, E.; Bekinschtein, T.; Cohen, L.; Naccache, L.; Dehaene, S.

2017-01-01

Detecting residual consciousness in unresponsive patients is a major clinical concern and a challenge for theoretical neuroscience. To tackle this issue, we recently designed a paradigm that dissociates two electro-encephalographic (EEG) responses to auditory novelty. Whereas a local change in pitch automatically elicits a mismatch negativity (MMN), a change in global sound sequence leads to a late P300b response. The latter component is thought to be present only when subjects consciously perceive the global novelty. Unfortunately, it can be difficult to detect because individual variability is high, especially in clinical recordings. Here, we show that multivariate pattern classifiers can extract subject-specific EEG patterns and predict single-trial local or global novelty responses. We first validate our method with 38 high-density EEG, MEG and intracranial EEG recordings. We empirically demonstrate that our approach circumvents the issues associated with multiple comparisons and individual variability while improving the statistics. Moreover, we confirm in control subjects that local responses are robust to distraction whereas global responses depend on attention. We then investigate 104 vegetative state (VS), minimally conscious state (MCS) and conscious state (CS) patients recorded with high-density EEG. For the local response, the proportion of significant decoding scores (M = 60%) does not vary with the state of consciousness. By contrast, for the global response, only 14% of the VS patients' EEG recordings presented a significant effect, compared to 31% in MCS patients' and 52% in CS patients'. In conclusion, single-trial multivariate decoding of novelty responses provides valuable information in non-communicating patients and paves the way towards real-time monitoring of the state of consciousness. PMID:23859924

Satellite Sensed Skin Sea Surface Temperature

NASA Technical Reports Server (NTRS)

Donlon, Craig

1997-01-01

Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data.

Shifting species interactions in terrestrial dryland ecosystems under altered water availability and climate change.

PubMed

McCluney, Kevin E; Belnap, Jayne; Collins, Scott L; González, Angélica L; Hagen, Elizabeth M; Nathaniel Holland, J; Kotler, Burt P; Maestre, Fernando T; Smith, Stanley D; Wolf, Blair O

2012-08-01

Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems. © 2011 The Authors. Biological Reviews © 2011 Cambridge Philosophical Society.

Responses of Forest Vegetation to Unusual Drought in Wet Forest in Eastern Puerto Rico: A "Dry Run" for Climate Change?

NASA Astrophysics Data System (ADS)

Zimmerman, J. K.; Hogan, J. A.; Rifkin, S.; Stankavitch, S.

2016-12-01

Droughts occur rarely in wet tropical forests but are predicted to become more frequent under modeled global climate change scenarios. 2015 was unusually dry in northeastern Puerto Rico, resulting from one of the strongest recorded El Niño events in history. We used these long-term measurements to characterize the ecosystem responses to drought focusing on vegetation responses by contrasting the observed patterns from 2015 with patterns from previous decades. Rainfall was measured at El Verde Field Station (EVFS; 350 masl); stream flow was gauged in the nearby Quebrada Sonadora ( 400 m masl), and litterfall was collected in 3 replicate 0.09 ha plots located between 350 - 500 masl ( 1 km from EVFS). Reproductive phenology (120 flower/seed traps) and tree diameter growth (from the 1000 largest trees) were monitored in the 16-ha Luquillo Forest Dynamics Plot (LFDP; 333-428 masl and 0.5-1 km from EVFS). During all of 2015, rainfall was approximately 50% of normal. Departure from the 40-year average of cumulative rainfall was evident by April. Stream flows were well below 25-year average levels by early May and this departure was evident through early November. Litter fall exhibited a strong peak in mid-May followed by reduced inputs until early September, when Tropical Storm Erika brought down additional litter. The peak was 3.5-fold greater than the 12-yr average for May and was associated with large numbers of aborted fruits in seed/flower traps. Diameter increments of trees in the LFDP were 30% reduced in 2015 in contrast to the previous two years. Fall storms brought an end to meteorological drought and, eventually, the hydrological drought. The timing of the 2105 drought mimicked patterns predicted by global circulation models (GCMs), i.e., a much stronger mid-summer drought than has been normally observed (usually no more than a month in duration). The drought was clearly stressful for forest vegetation at this elevation in the Luquillo Mountains. Assuming these conditions become more common as currently predicted by GCMs, these forests would suffer significant alteration of phenology and tree growth at increasing frequency.

Incorporating Infrastructure and Vegetation Effects on Sea Level Rise Predictions in Low-Gradient Coastal Landscapes

NASA Astrophysics Data System (ADS)

Rodriguez, J. F.; Sandi Rojas, S.; Trivisonno, F.; Saco, P. M.; Riccardi, G.

2015-12-01

At the regional and global scales, coastal management and planning for future sea level rise scenarios is typically supported by modelling tools that predict the expected inundation extent. These tools rely on a number of simplifying assumptions that, in some cases, may result in important overestimation or underestimation of the inundation extent. One of such cases is coastal wetlands, where vegetation strongly affects both the magnitude and the timing of inundation. Many coastal wetlands display other forms of flow restrictions due to, for example, infrastructure or drainage works, which also alters the inundation patterns. In this contribution we explore the effects of flow restrictions on inundation patterns under sea level rise conditions in coastal wetlands. We use a dynamic wetland evolution model that not only incorporates the effects of flow restrictions due to culverts, bridges and weirs as well as vegetation, but also considers that vegetation changes as a consequence of increasing inundation. We apply our model to a coastal wetland in Australia and compare predictions of our model to predictions using conventional approaches. We found that some restrictions accentuate detrimental effects of sea level rise while others moderate them. We also found that some management strategies based on flow redistribution that provide short term solution may result more damaging in the long term if sea level rise is considered.

Soil Texture Mediates the Response of Tree Cover to Rainfall Intensity in African Savannas

NASA Astrophysics Data System (ADS)

Case, M. F.; Staver, A. C.

2017-12-01

Global circulation models predict widespread shifts in the frequency and intensity of rainfall, even where mean annual rainfall does not change. Resulting changes in soil moisture dynamics could have major consequences for plant communities and ecosystems, but the direction of potential vegetation responses can be challenging to predict. In tropical savannas, where tree and grasses coexist, contradictory lines of evidence have suggested that tree cover could respond either positively or negatively to less frequent, more intense rainfall. Here, we analyzed remote sensing data and continental-scale soils maps to examine whether soil texture or fire could explain heterogeneous responses of savanna tree cover to intra-annual rainfall variability across sub-Saharan Africa. We find that tree cover generally increases with mean wet-season rainfall, decreases with mean wet-season rainfall intensity, and decreases with fire frequency. However, soil sand content mediates these relationships: the response to rainfall intensity switches qualitatively depending on soil texture, such that tree cover decreases dramatically with less frequent, more intense rainfall on clay soils but increases with rainfall intensity on sandy soils in semi-arid savannas. We propose potential ecohydrological mechanisms for this heterogeneous response, and emphasize that predictions of savanna vegetation responses to global change should account for interactions between soil texture and changing rainfall patterns.

Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks.

PubMed

Heiser, Diane; Tan, Yee Sun; Kaplan, Ian; Godsey, Brian; Morisot, Sebastien; Cheng, Wen-Chih; Small, Donald; Civin, Curt I

2014-01-01

Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC) populations, as well as "myeloid" patterns associated with two branches of myeloid development.

There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task

PubMed Central

Miconi, Thomas; Groomes, Laura; Kreiman, Gabriel

2016-01-01

When searching for an object in a scene, how does the brain decide where to look next? Visual search theories suggest the existence of a global “priority map” that integrates bottom-up visual information with top-down, target-specific signals. We propose a mechanistic model of visual search that is consistent with recent neurophysiological evidence, can localize targets in cluttered images, and predicts single-trial behavior in a search task. This model posits that a high-level retinotopic area selective for shape features receives global, target-specific modulation and implements local normalization through divisive inhibition. The normalization step is critical to prevent highly salient bottom-up features from monopolizing attention. The resulting activity pattern constitues a priority map that tracks the correlation between local input and target features. The maximum of this priority map is selected as the locus of attention. The visual input is then spatially enhanced around the selected location, allowing object-selective visual areas to determine whether the target is present at this location. This model can localize objects both in array images and when objects are pasted in natural scenes. The model can also predict single-trial human fixations, including those in error and target-absent trials, in a search task involving complex objects. PMID:26092221

Measurement of sediment and crustal thickness corrected RDA for 2D profiles at rifted continental margins: Applications to the Iberian, Gulf of Aden and S Angolan margins

NASA Astrophysics Data System (ADS)

Cowie, Leanne; Kusznir, Nick

2014-05-01

Subsidence analysis of sedimentary basins and rifted continental margins requires a correction for the anomalous uplift or subsidence arising from mantle dynamic topography. Whilst different global model predictions of mantle dynamic topography may give a broadly similar pattern at long wavelengths, they differ substantially in the predicted amplitude and at shorter wavelengths. As a consequence the accuracy of predicted mantle dynamic topography is not sufficiently good to provide corrections for subsidence analysis. Measurements of present day anomalous subsidence, which we attribute to mantle dynamic topography, have been made for three rifted continental margins; offshore Iberia, the Gulf of Aden and southern Angola. We determine residual depth anomaly (RDA), corrected for sediment loading and crustal thickness variation for 2D profiles running from unequivocal oceanic crust across the continental ocean boundary onto thinned continental crust. Residual depth anomalies (RDA), corrected for sediment loading using flexural backstripping and decompaction, have been calculated by comparing observed and age predicted oceanic bathymetries at these margins. Age predicted bathymetric anomalies have been calculated using the thermal plate model predictions from Crosby & McKenzie (2009). Non-zero sediment corrected RDAs may result from anomalous oceanic crustal thickness with respect to the global average or from anomalous uplift or subsidence. Gravity anomaly inversion incorporating a lithosphere thermal gravity anomaly correction and sediment thickness from 2D seismic reflection data has been used to determine Moho depth, calibrated using seismic refraction, and oceanic crustal basement thickness. Crustal basement thicknesses derived from gravity inversion together with Airy isostasy have been used to correct for variations of crustal thickness from a standard oceanic thickness of 7km. The 2D profiles of RDA corrected for both sediment loading and non-standard crustal thickness provide a measurement of anomalous uplift or subsidence which we attribute to mantle dynamic topography. We compare our sediment and crustal thickness corrected RDA analysis results with published predictions of mantle dynamic topography from global models.

Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland

NASA Astrophysics Data System (ADS)

Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.

2015-05-01

Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing-canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.

Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland

NASA Astrophysics Data System (ADS)

Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.

2015-01-01

Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.

Diversity of deep-water cetaceans in relation to temperature: implications for ocean warming.

PubMed

Whitehead, Hal; McGill, Brian; Worm, Boris

2008-11-01

Understanding the effects of natural environmental variation on biodiversity can help predict response to future anthropogenic change. Here we analyse a large, long-term data set of sightings of deep-water cetaceans from the Atlantic, Pacific and Indian Oceans. Seasonal and geographic changes in the diversity of these genera are well predicted by a convex function of sea-surface temperature peaking at c. 21 degrees C. Thus, diversity is highest at intermediate latitudes - an emerging general pattern for the pelagic ocean. When applied to a range of Intergovernmental Panel on Climate Change global change scenarios, the predicted response is a decline of cetacean diversity across the tropics and increases at higher latitudes. This suggests that deep-water oceanic communities that dominate > 60% of the planet's surface may reorganize in response to ocean warming, with low-latitude losses of diversity and resilience.

Predictability of Extreme Climate Events via a Complex Network Approach

NASA Astrophysics Data System (ADS)

Muhkin, D.; Kurths, J.

2017-12-01

We analyse climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. This concept is then applied to Monsoon data; in particular, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. Applying this method, we uncover a new mechanism of extreme floods in the eastern Central Andes which could be used for operational forecasts. Moreover, we analyze the Indian Summer Monsoon (ISM) and identify two regions of high importance. By estimating an underlying critical point, this leads to an improved prediction of the onset of the ISM; this scheme was successful in 2016 and 2017.

Impact of switching from Caucasian to Indian reference equations for spirometry interpretation.

PubMed

Chhabra, S K; Madan, M

2018-03-01

In the absence of ethnically appropriate prediction equations, spirometry data in Indian subjects are often interpreted using equations for other ethnic populations. To evaluate the impact of switching from Caucasian (National Health and Nutrition Examination Survey III [NHANES III] and Global Lung Function Initiative [GLI]) equations to the recently published North Indian equations on spirometric interpretation, and to examine the suitability of GLI-Mixed equations for this population. Spirometry data on 12 323 North Indian patients were analysed using the North Indian equations as well as NHANES III, GLI-Caucasian and GLI-Mixed equations. Abnormalities and ventilatory patterns were categorised and agreement in interpretation was evaluated. The NHANES III and GLI-Caucasian equations and, to a lesser extent, the GLI-Mixed equations, predicted higher values and labelled more measurements as abnormal. In up to one third of the patients, these differed from Indian equations in the categorisation of ventilatory patterns, with more patients classified as having restrictive and mixed disease. The NHANES III and GLI-Caucasian equations substantially overdiagnose abnormalities and misclassify ventilatory patterns on spirometry in Indian patients. Such errors of interpretation, although less common with the GLI-Mixed equations, remain substantial and are clinically unacceptable. A switch to Indian equations will have a major impact on interpretation.

Prediction, Assessment of the Rift Valley Fever Activity in East and Southern Africa 2006–2008 and Possible Vector Control Strategies

PubMed Central

Anyamba, Assaf; Linthicum, Kenneth J.; Small, Jennifer; Britch, Seth C.; Pak, Edwin; de La Rocque, Stephane; Formenty, Pierre; Hightower, Allen W.; Breiman, Robert F.; Chretien, Jean-Paul; Tucker, Compton J.; Schnabel, David; Sang, Rosemary; Haagsma, Karl; Latham, Mark; Lewandowski, Henry B.; Magdi, Salih Osman; Mohamed, Mohamed Ally; Nguku, Patrick M.; Reynes, Jean-Marc; Swanepoel, Robert

2010-01-01

Historical outbreaks of Rift Valley fever (RVF) since the early 1950s have been associated with cyclical patterns of the El Niño/Southern Oscillation (ENSO) phenomenon, which results in elevated and widespread rainfall over the RVF endemic areas of Africa. Using satellite measurements of global and regional elevated sea surface temperatures, elevated rainfall, and satellite derived-normalized difference vegetation index data, we predicted with lead times of 2–4 months areas where outbreaks of RVF in humans and animals were expected and occurred in the Horn of Africa, Sudan, and Southern Africa at different time periods from September 2006 to March 2008. Predictions were confirmed by entomological field investigations of virus activity and by reported cases of RVF in human and livestock populations. This represents the first series of prospective predictions of RVF outbreaks and provides a baseline for improved early warning, control, response planning, and mitigation into the future. PMID:20682905

DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations.

PubMed

Kruthiventi, Srinivas S S; Ayush, Kumar; Babu, R Venkatesh

2017-09-01

Understanding and predicting the human visual attention mechanism is an active area of research in the fields of neuroscience and computer vision. In this paper, we propose DeepFix, a fully convolutional neural network, which models the bottom-up mechanism of visual attention via saliency prediction. Unlike classical works, which characterize the saliency map using various hand-crafted features, our model automatically learns features in a hierarchical fashion and predicts the saliency map in an end-to-end manner. DeepFix is designed to capture semantics at multiple scales while taking global context into account, by using network layers with very large receptive fields. Generally, fully convolutional nets are spatially invariant-this prevents them from modeling location-dependent patterns (e.g., centre-bias). Our network handles this by incorporating a novel location-biased convolutional layer. We evaluate our model on multiple challenging saliency data sets and show that it achieves the state-of-the-art results.

Comprehensive computational model for combining fluid hydrodynamics, light transport and biomass growth in a Taylor vortex algal photobioreactor: Lagrangian approach.

PubMed

Gao, Xi; Kong, Bo; Vigil, R Dennis

2017-01-01

A comprehensive quantitative model incorporating the effects of fluid flow patterns, light distribution, and algal growth kinetics on biomass growth rate is developed in order to predict the performance of a Taylor vortex algal photobioreactor for culturing Chlorella vulgaris. A commonly used Lagrangian strategy for coupling the various factors influencing algal growth was employed whereby results from computational fluid dynamics and radiation transport simulations were used to compute numerous microorganism light exposure histories, and this information in turn was used to estimate the global biomass specific growth rate. The simulations provide good quantitative agreement with experimental data and correctly predict the trend in reactor performance as a key reactor operating parameter is varied (inner cylinder rotation speed). However, biomass growth curves are consistently over-predicted and potential causes for these over-predictions and drawbacks of the Lagrangian approach are addressed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predictability of rainfall and teleconnections patterns influencing on Southwest Europe from sea surfaces temperatures

NASA Astrophysics Data System (ADS)

Lorenzo, M. N.; Iglesias, I.; Taboada, J. J.; Gómez-Gesteira, M.; Ramos, A. M.

2009-04-01

This work assesses the possibility of doing a forecast of rainfall and the main teleconnections patterns that influences climate in Southwest Europe by using sea surface temperature anomalies (SSTA). The area under study is located in the NW Iberian Peninsula. This region has a great oceanic influence on its climate and has an important dependency of the water resources. In this way if the different SST patterns are known, the different rainfall situations can be predicted. On the other hand, the teleconnection patterns, which have strong weight on rainfall, are influenced by the SSTA of different areas. In the light of this, the aim of this study is to explore the relationship between global SSTAs, rainfall and the main teleconnection patterns influencing on Europe. The SST data with a 2.0 degree resolution was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA. A monthly averaged data from 1 January 1951 through December 2006 was considered. The monthly precipitation data from 1951-2006 were obtained from the database CLIMA of the University of Santiago de Compostela with data from the Meteorological State Agency (AEMET) and the Regional Government of Galicia. The teleconnection indices were taken of the Climate Prediction Center of the NOAA between 1950 and 2006. A monthly and seasonal study was analysed considering up to three months of delay in the first case and up to four seasons of delay in the second case. The Pearson product-moment correlation coefficient r was considered to quantify linear associations between SSTA and precipitation and/or SSTA and teleconnection indices. A test for field-significance was applied considering the properties of finiteness and interdependence of the spatial grid to avoid spurious correlations. Analysing the results obtained with the global SSTA and the teleconnection indices, a great number of ocean regions with high correlations can be found. The spatial patterns show very high correlations with Indian Ocean waters which could be related with the Monsoon. Another area with high correlation is Equatorial Pacific Ocean, the area related with the ENSO phenomenon. These SSTAs could be used to forecast rainfall anomalies in spring season in the area of NW Iberian Peninsula. Results show that La Niña years almost always announces dry spring in NW Iberian Peninsula. Nevertheless, El Niño years do not preclude the appearance of wet spring. Because of the progress that has been made in its prediction, the relation between ENSO and climate in NW Iberian Peninsula is of interest with respect to potential seasonal predictability and the results can be extended to the south west of Europe. [1] Lorenzo, M.N. and J. J. Taboada (2005). Influences of atmospheric variability on freshwater input in Galician Rías in winter. Journal of Atmospheric and Ocean Science Vol 10, No 4, 377-387. [2] Lorenzo, M.N. I. Iglesias, J.J. Taboada and M. Gómez-Gesteira. Relationship between monthly rainfall in NW Iberian Peninsula and North Atlantic sea surface temperature. International Journal of Climatology. (Submitted to International Journal of Climatology). [3] Philips, I.D. and J. Thorpe (2006): Icelandic precipitation-North Atlantic sea-surface temperature associations. International Journal of Climatology 26: 1201-1221.

PaleoClim: new datasets to quantify the impact of past climate changes on modern biodiversity

NASA Astrophysics Data System (ADS)

Hill, D. J.; Brown, J. T.; Carnaval, A. C.; Haywood, A. M.

2017-12-01

Palaeoclimate history is an important driver of modern patterns of biodiversity and many ecological modelling studies have shown the predictive power of palaeoclimate information. However, a major limiting factor to such studies is the availability of global palaeoclimate reconstructions in the relevant bioclim layers. The primary source of such fields is from climate model simulations, which are currently limited to the key PMIP (Paleoclimate Modelling Intercomparison Project) intervals of the mid-Holocene (6ka), the Last Glacial Maximum (21ka) and the Last Interglaciation (130ka). The PaleoClim project will significantly increase the availability of pre-processed palaeoclimate bioclim information and provide a new platform for accessing the information. The first new PaleoClim time period will be the mid-Pliocene Warm Period (3Ma). This is the last period of sustained globally warmer than modern climate in Earth history and represents the last global warmth before the cooling into the Pleistocene ice ages. Being 3 million years ago this represents a significant lengthening of the time range of available bioclim layers and the first time these have been available over evolutionary timescales. PaleoClim will also greatly expand the available Pleistocene time periods, looking to both quantify the differences between the late Pleistocene interglacial periods and understand the role of orbital changes in modulating tropical precipitation and driving modern biodiversity patterns.

Vegetation root zone storage and rooting depth, derived from local calibration of a global hydrological model

NASA Astrophysics Data System (ADS)

van der Ent, R.; Van Beek, R.; Sutanudjaja, E.; Wang-Erlandsson, L.; Hessels, T.; Bastiaanssen, W.; Bierkens, M. F.

2017-12-01

The storage and dynamics of water in the root zone control many important hydrological processes such as saturation excess overland flow, interflow, recharge, capillary rise, soil evaporation and transpiration. These processes are parameterized in hydrological models or land-surface schemes and the effect on runoff prediction can be large. Root zone parameters in global hydrological models are very uncertain as they cannot be measured directly at the scale on which these models operate. In this paper we calibrate the global hydrological model PCR-GLOBWB using a state-of-the-art ensemble of evaporation fields derived by solving the energy balance for satellite observations. We focus our calibration on the root zone parameters of PCR-GLOBWB and derive spatial patterns of maximum root zone storage. We find these patterns to correspond well with previous research. The parameterization of our model allows for the conversion of maximum root zone storage to root zone depth and we find that these correspond quite well to the point observations where available. We conclude that climate and soil type should be taken into account when regionalizing measured root depth for a certain vegetation type. We equally find that using evaporation rather than discharge better allows for local adjustment of root zone parameters within a basin and thus provides orthogonal data to diagnose and optimize hydrological models and land surface schemes.

Vegetation root zone storage and rooting depth, derived from local calibration of a global hydrological model

NASA Astrophysics Data System (ADS)

van der Ent, Ruud; van Beek, Rens; Sutanudjaja, Edwin; Wang-Erlandsson, Lan; Hessels, Tim; Bastiaanssen, Wim; Bierkens, Marc

2017-04-01

The storage and dynamics of water in the root zone control many important hydrological processes such as saturation excess overland flow, interflow, recharge, capillary rise, soil evaporation and transpiration. These processes are parameterized in hydrological models or land-surface schemes and the effect on runoff prediction can be large. For root zone parameters in global hydrological models are very uncertain as they cannot be measured directly at the scale on which these models operate. In this paper we calibrate the global hydrological model PCR-GLOBWB using a state-of-the-art ensemble of evaporation fields derived by solving the energy balance for satellite observations. We focus our calibration on the root zone parameters of PCR-GLOBWB and derive spatial patterns of maximum root zone storage. We find these patterns to correspond well with previous research. The parameterization of our model allows for the conversion of maximum root zone storage to root zone depth and we find that these correspond quite well to the point observations where available. We conclude that climate and soil type should be taken into account when regionalizing measured root depth for a certain vegetation type. We equally find that using evaporation rather than discharge better allows for local adjustment of root zone parameters within a basin and thus provides orthogonal data to diagnose and optimize hydrological models and land surface schemes.

The Global Precipitation Patterns Associated with Short-Term Extratropical Climate Fluctuations

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.

1999-01-01

Two globally-complete, observation-only precipitation datasets have recently been developed for the Global Precipitation Climatology Project (GPCP). Both depend heavily on a variety of satellite input, as well as gauge data over land. The first, Version 2x79, provides monthly estimates on a 2.5 deg. x 2.5 deg. lat/long grid for the period 1979 through late 1999 (by the time of the conference). The second, the One-Degree Daily (1DD), provides daily estimates on a 1 deg. x l deg. grid for the period 1997 through late 1999 (by the time of the conference). Both are in beta test preparatory to release as official GPCP products. These datasets provide a unique perspective on the hydrological effects of the various atmospheric flow anomalies that have been identified by meteorologists. In this paper we discuss the regional precipitation effects that result from persistent extratropical flow anomalies. We will focus on the Pacific-North America (PNA) and North Atlantic Oscillation (NAO) patterns. Each characteristically becomes established on synoptic time scales, but then persists for periods that can exceed a month. The onset phase of each appears to have systematic mobile features, while the mature phase tend to be more stationary. Accordingly, composites of monthly data for outstanding positive and negative events (separately) contained in the 20-year record reveal the climatological structure of the precipitation during the mature phase. The climatological anomalies of the positive, negative, and (positive-negative) composites show the expected storm-track-related shifts in precipitation, and provide the advantage of putting the known precipitation effects over land in the context of the total pattern over land and ocean. As well, this global perspective points out some unexpected areas of correlation. Day-by-day composites of daily data anchored to the onset date demonstrate the systematic features during the onset. Although the 1DD has a fairly short record, some preliminary results are shown and compared to previous work with numerical weather prediction models.

A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Dorigo, Wouter; Lasslop, Gitta; Teubner, Irene; Chuvieco, Emilio; Thonicke, Kirsten

2017-12-01

Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data-driven modelling and model-data integration approaches can guide the future development of global process-oriented vegetation-fire models.

Cosmopolitan Species As Models for Ecophysiological Responses to Global Change: The Common Reed Phragmites australis.

PubMed

Eller, Franziska; Skálová, Hana; Caplan, Joshua S; Bhattarai, Ganesh P; Burger, Melissa K; Cronin, James T; Guo, Wen-Yong; Guo, Xiao; Hazelton, Eric L G; Kettenring, Karin M; Lambertini, Carla; McCormick, Melissa K; Meyerson, Laura A; Mozdzer, Thomas J; Pyšek, Petr; Sorrell, Brian K; Whigham, Dennis F; Brix, Hans

2017-01-01

Phragmites australis is a cosmopolitan grass and often the dominant species in the ecosystems it inhabits. Due to high intraspecific diversity and phenotypic plasticity, P. australis has an extensive ecological amplitude and a great capacity to acclimate to adverse environmental conditions; it can therefore offer valuable insights into plant responses to global change. Here we review the ecology and ecophysiology of prominent P. australis lineages and their responses to multiple forms of global change. Key findings of our review are that: (1) P. australis lineages are well-adapted to regions of their phylogeographic origin and therefore respond differently to changes in climatic conditions such as temperature or atmospheric CO 2 ; (2) each lineage consists of populations that may occur in geographically different habitats and contain multiple genotypes; (3) the phenotypic plasticity of functional and fitness-related traits of a genotype determine the responses to global change factors; (4) genotypes with high plasticity to environmental drivers may acclimate or even vastly expand their ranges, genotypes of medium plasticity must acclimate or experience range-shifts, and those with low plasticity may face local extinction; (5) responses to ancillary types of global change, like shifting levels of soil salinity, flooding, and drought, are not consistent within lineages and depend on adaptation of individual genotypes. These patterns suggest that the diverse lineages of P. australis will undergo intense selective pressure in the face of global change such that the distributions and interactions of co-occurring lineages, as well as those of genotypes within-lineages, are very likely to be altered. We propose that the strong latitudinal clines within and between P. australis lineages can be a useful tool for predicting plant responses to climate change in general and present a conceptual framework for using P. australis lineages to predict plant responses to global change and its consequences.

Global patterns of foliar nitrogen isotopes and their relationships with climate, mycorrhizal fungi, foliar nutrient concentrations, and nitrogen availability

Treesearch

Joseph M. Craine; Andrew J. Elmore; Marcos P. M. Aidar; Mercedes Bustamante; Todd E. Dawson; Erik A. Hobbie; Ansgar Kahmen; Michelle C. Mack; Kendra K. McLauchlan; Anders Michelsen; Gabriela Nardoto; Linda H. Pardo; Josep Penuelas; Peter B. Reich; Edward A.G. Schuur; William D. Stock; Pamela H. Templer; Ross A. Virginia; Jeffrey M. Welker; Ian J. Wright

2009-01-01

Ratios of nitrogen (N) isotopes in leaves could elucidate underlying patterns of N cycling across ecological gradients. To better understand global-scale patterns of N cycling, we compiled data on foliar N isotope ratios, foliar N concentrations, mycorrhizal type and climate for over 11 000 plants worldwide. Global-scale comparisons of other components of the N cycle...

Past and estimated future impact of invasive alien mammals on insular threatened vertebrate populations

PubMed Central

McCreless, Erin E.; Huff, David D.; Croll, Donald A.; Tershy, Bernie R.; Spatz, Dena R.; Holmes, Nick D.; Butchart, Stuart H. M.; Wilcox, Chris

2016-01-01

Invasive mammals on islands pose severe, ongoing threats to global biodiversity. However, the severity of threats from different mammals, and the role of interacting biotic and abiotic factors in driving extinctions, remain poorly understood at a global scale. Here we model global extirpation patterns for island populations of threatened and extinct vertebrates. Extirpations are driven by interacting factors including invasive rats, cats, pigs, mustelids and mongooses, native species taxonomic class and volancy, island size, precipitation and human presence. We show that controlling or eradicating the relevant invasive mammals could prevent 41–75% of predicted future extirpations. The magnitude of benefits varies across species and environments; for example, managing invasive mammals on small, dry islands could halve the extirpation risk for highly threatened birds and mammals, while doing so on large, wet islands may have little benefit. Our results provide quantitative estimates of conservation benefits and, when combined with costs in a return-on-investment framework, can guide efficient conservation strategies. PMID:27535095

Dynamics of melt crystal interface and thermal stresses in rotational Bridgman crystal growth process

NASA Astrophysics Data System (ADS)

Ma, Ronghui; Zhang, Hui; Larson, David J.; Mandal, Krishna C.

2004-05-01

The growth process of potassium bromide (KBr) single crystals in a vertical Bridgman furnace has been studied numerically using an integrated model that combines formulation of global heat transfer and thermal elastic stresses. The global heat transfer sub-model accounts for conduction, convection and interface movement in the multiphase system. Using the elastic stress sub-model, thermal stresses in the growing crystal caused by the non-uniform temperature distribution is predicted. Special attention is directed to the interaction between the crystal and the ampoule. The global temperature distribution in the furnace, the flow pattern in the melt and the interface shapes are presented. We also investigate the effects of the natural convection and rotational forced convection on the shape of the growth fronts. Furthermore, the state of the thermal stresses in the crystal is studied to understand the plastic deformation mechanisms during the cooling process. The influence of the wall contact on thermal stresses is also addressed.

Personality and gender differences in global perspective.

PubMed

Schmitt, David P; Long, Audrey E; McPhearson, Allante; O'Brien, Kirby; Remmert, Brooke; Shah, Seema H

2017-12-01

Men's and women's personalities appear to differ in several respects. Social role theories of development assume gender differences result primarily from perceived gender roles, gender socialization and sociostructural power differentials. As a consequence, social role theorists expect gender differences in personality to be smaller in cultures with more gender egalitarianism. Several large cross-cultural studies have generated sufficient data for evaluating these global personality predictions. Empirically, evidence suggests gender differences in most aspects of personality-Big Five traits, Dark Triad traits, self-esteem, subjective well-being, depression and values-are conspicuously larger in cultures with more egalitarian gender roles, gender socialization and sociopolitical gender equity. Similar patterns are evident when examining objectively measured attributes such as tested cognitive abilities and physical traits such as height and blood pressure. Social role theory appears inadequate for explaining some of the observed cultural variations in men's and women's personalities. Evolutionary theories regarding ecologically-evoked gender differences are described that may prove more useful in explaining global variation in human personality. © 2016 International Union of Psychological Science.

Global patterns of conservation research importance in different countries of the world.

PubMed

Doi, Hideyuki; Takahara, Teruhiko

2016-01-01

Conservation research is essential to help inform the science-based management of environments that support threatened and endangered wildlife; however, research effort is not necessarily uniform across countries globally. Here, we assessed how the research importance of conservation is distributed globally across different countries and what drives this variation. Specifically, we compared the number of conservation/ecological articles versus all scientific articles published for each country in relation to the number of endangered species, the protection status and number of ecosystems, and the economic status of each country (gross domestic product (GDP) per capita). We observed a significant and positive relationship between the proportion of conservation and ecology articles to all scientific articles with respect to the number of endangered species and the proportion of endangered species that are protected in a country, as well as GDP per capita. In conclusion, knowledge about the conservation and economic status of countries should be accounted for when predicting the research importance of conservation and ecology.

Hosting a Fourier Transform Spectrometer (FTS) on CubeSat Spacecraft Platforms for Global Measurements of Three-Dimensional Winds

NASA Astrophysics Data System (ADS)

Scott, D. K.; Neilsen, T. L.; Weston, C.; Frazier, C.; Smith, T.; Shumway, A.

2015-12-01

Global measurements of vertically-resolved atmospheric wind profiles offer the potential for improved weather forecasts and superior predictions of atmospheric wind patterns. A small-satellite constellation that uses a Fourier Transform Spectrometer (FTS) instrument onboard 12U CubeSats can provide measurements of global tropospheric wind profiles from space at a very low cost. These small satellites are called FTS CubeSats. This presentation will describe a spacecraft concept that provides a stable, robust platform to host the FTS payload. Of importance to the payload are power, data, station keeping, thermal, and accommodations that enable high spectral measurements to be made from a LEO orbit. The spacecraft concept draws on Space Dynamics Laboratory (SDL) heritage and the recent success of the Dynamic Ionosphere Cubesat Experiment (DICE) and HyperAngular Rainbow Polarimeter (HARP) missions. Working with team members, SDL built a prototype observatory (spacecraft and payload) for testing and proof of concept.

Atomistic modeling of the low-frequency mechanical modes and Raman spectra of icosahedral virus capsids

NASA Astrophysics Data System (ADS)

Dykeman, Eric C.; Sankey, Otto F.

2010-02-01

We describe a technique for calculating the low-frequency mechanical modes and frequencies of a large symmetric biological molecule where the eigenvectors of the Hessian matrix are determined with full atomic detail. The method, which follows order N methods used in electronic structure theory, determines the subset of lowest-frequency modes while using group theory to reduce the complexity of the problem. We apply the method to three icosahedral viruses of various T numbers and sizes; the human viruses polio and hepatitis B, and the cowpea chlorotic mottle virus, a plant virus. From the normal-mode eigenvectors, we use a bond polarizability model to predict a low-frequency Raman scattering profile for the viruses. The full atomic detail in the displacement patterns combined with an empirical potential-energy model allows a comparison of the fully atomic normal modes with elastic network models and normal-mode analysis with only dihedral degrees of freedom. We find that coarse-graining normal-mode analysis (particularly the elastic network model) can predict the displacement patterns for the first few (˜10) low-frequency modes that are global and cooperative.

Global-scale tectonic patterns on Pluto

NASA Astrophysics Data System (ADS)

Matsuyama, I.; Keane, J. T.; Kamata, S.

2016-12-01

The New Horizons spacecraft revealed a global-scale tectonic pattern on the surface of Pluto which is presumably related to its formation and early evolution. Changes in the rotational and tidal potentials, expansion, and loading can generate stresses capable of producing global-scale tectonic patterns. The current alignment of Sputnik Planum with the tidal axis suggests a reorientation of Pluto relative to the rotation and tidal axes, or true polar wander. This reorientation can be driven by mass loading associated with Sputnik Planum. We developed a general theoretical formalism for the calculation of tectonic patterns due to a variety of process including true polar wander, loading, and expansion. The formalism is general enough to be applicable to non-axisymmetric loads. We illustrate that the observed global-scale tectonic pattern can be explained by stresses generated by true polar wander, Sputnik Planum loading, and expansion.

Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

NASA Astrophysics Data System (ADS)

Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

2018-04-01

This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent deep-water formation in the Labrador Sea, resulting in overestimated North Atlantic SST variability. Concerning the influence of locally (isotropically) increased resolution, the ENSO pattern and index statistics improve significantly with higher resolution around the equator, illustrating the potential of the novel unstructured-mesh method for global climate modeling.

Correlation analyses revealed global microRNA-mRNA expression associations in human peripheral blood mononuclear cells.

PubMed

Wang, Lan; Zhu, Jiang; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Xiao-Wei; Xia, Wei; Xie, Fang-Fei; He, Pei; Bing, Peng-Fei; Qiu, Ying-Hua; Lin, Xiang; Lu, Xin; Zhang, Lei; Yi, Neng-Jun; Zhang, Yong-Hong; Lei, Shu-Feng

2018-02-01

MicroRNAs (miRNAs) can regulate gene expression through binding to complementary sites in the 3'-untranslated regions of target mRNAs, which will lead to existence of correlation in expression between miRNA and mRNA. However, the miRNA-mRNA correlation patterns are complex and remain largely unclear yet. To establish the global correlation patterns in human peripheral blood mononuclear cells (PBMCs), multiple miRNA-mRNA correlation analyses and expression quantitative trait locus (eQTL) analysis were conducted in this study. We predicted and achieved 861 miRNA-mRNA pairs (65 miRNAs, 412 mRNAs) using multiple bioinformatics programs, and found global negative miRNA-mRNA correlations in PBMC from all 46 study subjects. Among the 861 pairs of correlations, 19.5% were significant (P < 0.05) and ~70% were negative. The correlation network was complex and highlighted key miRNAs/genes in PBMC. Some miRNAs, such as hsa-miR-29a, hsa-miR-148a, regulate a cluster of target genes. Some genes, e.g., TNRC6A, are regulated by multiple miRNAs. The identified genes tend to be enriched in molecular functions of DNA and RNA binding, and biological processes such as protein transport, regulation of translation and chromatin modification. The results provided a global view of the miRNA-mRNA expression correlation profile in human PBMCs, which would facilitate in-depth investigation of biological functions of key miRNAs/mRNAs and better understanding of the pathogenesis underlying PBMC-related diseases.

Contrasting Patterns in Mammal–Bacteria Coevolution: Bartonella and Leptospira in Bats and Rodents

PubMed Central

Lei, Bonnie R.; Olival, Kevin J.

2014-01-01

Background Emerging bacterial zoonoses in bats and rodents remain relatively understudied. We conduct the first comparative host–pathogen coevolutionary analyses of bacterial pathogens in these hosts, using Bartonella spp. and Leptospira spp. as a model. Methodology/Principal Findings We used published genetic data for 51 Bartonella genotypes from 24 bat species, 129 Bartonella from 38 rodents, and 26 Leptospira from 20 bats. We generated maximum likelihood and Bayesian phylogenies for hosts and bacteria, and tested for coevoutionary congruence using programs ParaFit, PACO, and Jane. Bartonella spp. and their bat hosts had a significant coevolutionary fit (ParaFitGlobal = 1.9703, P≤0.001; m2 global value = 7.3320, P≤0.0001). Bartonella spp. and rodent hosts also indicated strong overall patterns of cospeciation (ParaFitGlobal = 102.4409, P≤0.001; m2 global value = 86.532, P≤0.0001). In contrast, we were unable to reject independence of speciation events in Leptospira and bats (ParaFitGlobal = 0.0042, P = 0.84; m2 global value = 4.6310, P = 0.5629). Separate analyses of New World and Old World data subsets yielded results congruent with analysis from entire datasets. We also conducted event-based cophylogeny analyses to reconstruct likely evolutionary histories for each group of pathogens and hosts. Leptospira and bats had the greatest number of host switches per parasite (0.731), while Bartonella and rodents had the fewest (0.264). Conclusions/Significance In both bat and rodent hosts, Bartonella exhibits significant coevolution with minimal host switching, while Leptospira in bats lacks evolutionary congruence with its host and has high number of host switches. Reasons underlying these variable coevolutionary patterns in host range are likely due to differences in disease-specific transmission and host ecology. Understanding the coevolutionary patterns and frequency of host-switching events between bacterial pathogens and their hosts will allow better prediction of spillover between mammal reservoirs, and ultimately to humans. PMID:24651646

ALM-FATES: Using dynamic vegetation and demography to capture changes in forest carbon cycling and competition at the global scale

NASA Astrophysics Data System (ADS)

Holm, J. A.; Knox, R. G.; Koven, C.; Riley, W. J.; Bisht, G.; Fisher, R.; Christoffersen, B. O.; Dietze, M.; Chambers, J. Q.

2017-12-01

The inclusion of dynamic vegetation demography in Earth System Models (ESMs) has been identified as a critical step in moving ESMs towards more realistic representations of plant ecology and the processes that govern climatically important fluxes of carbon, energy, and water. Successful application of dynamic vegetation models, and process-based approaches to simulate plant demography, succession, and response to disturbances without climate envelopes at the global scale is a challenging endeavor. We integrated demographic processes using the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) in the newly developed ACME Land Model (ALM). We then use an ALM-FATES globally gridded simulation for the first time to investigate plant functional type (PFT) distributions and dynamic turnover rates. Initial global simulations successfully include six interacting and competing PFTs (ranging from tropical to boreal, evergreen, deciduous, needleleaf and broadleaf); including more PFTs is planned. Global maps of net primary productivity, leaf area index, and total vegetation biomass by ALM-FATES matched patterns and values when compared to CLM4.5-BGC and MODIS estimates. We also present techniques for PFT parameterization based on the Predictive Ecosystem Analyzer (PEcAn), field based turnover rates, improved PFT groupings based on trait-tradeoffs, and improved representation of multiple canopy positions. Finally, we applied the improved ALM-FATES model at a central Amazon tropical and western U.S. temperate sites and demonstrate improvements in predicted PFT size- and age-structure and regional distribution. Results from the Amazon tropical site investigate the ability and magnitude of a tropical forest to act as a carbon sink by 2100 with a doubling of CO2, while results from the temperate sites investigate the response of forest mortality with increasing droughts.

Biogeography of Human Infectious Diseases: A Global Historical Analysis

PubMed Central

Cashdan, Elizabeth

2014-01-01

Objectives Human pathogen richness and prevalence vary widely across the globe, yet we know little about whether global patterns found in other taxa also predict diversity in this important group of organisms. This study (a) assesses the relative importance of temperature, precipitation, habitat diversity, and population density on the global distributions of human pathogens and (b) evaluates the species-area predictions of island biogeography for human pathogen distributions on oceanic islands. Methods Historical data were used in order to minimize the influence of differential access to modern health care on pathogen prevalence. The database includes coded data (pathogen, environmental and cultural) for a worldwide sample of 186 non-industrial cultures, including 37 on islands. Prevalence levels for 10 pathogens were combined into a pathogen prevalence index, and OLS regression was used to model the environmental determinants of the prevalence index and number of pathogens. Results Pathogens (number and prevalence index) showed the expected latitudinal gradient, but predictors varied by latitude. Pathogens increased with temperature in high-latitude zones, while mean annual precipitation was a more important predictor in low-latitude zones. Other environmental factors associated with more pathogens included seasonal dry extremes, frost-free climates, and human population density outside the tropics. Islands showed the expected species-area relationship for all but the smallest islands, and the relationship was not mediated by habitat diversity. Although geographic distributions of free-living and parasitic taxa typically have different determinants, these data show that variables that influence the distribution of free-living organisms also shape the global distribution of human pathogens. Understanding the cause of these distributions is potentially important, since geographical variation in human pathogens has an important influence on global disparities in human welfare. PMID:25271730

Biogeography of human infectious diseases: a global historical analysis.

PubMed

Cashdan, Elizabeth

2014-01-01

Human pathogen richness and prevalence vary widely across the globe, yet we know little about whether global patterns found in other taxa also predict diversity in this important group of organisms. This study (a) assesses the relative importance of temperature, precipitation, habitat diversity, and population density on the global distributions of human pathogens and (b) evaluates the species-area predictions of island biogeography for human pathogen distributions on oceanic islands. Historical data were used in order to minimize the influence of differential access to modern health care on pathogen prevalence. The database includes coded data (pathogen, environmental and cultural) for a worldwide sample of 186 non-industrial cultures, including 37 on islands. Prevalence levels for 10 pathogens were combined into a pathogen prevalence index, and OLS regression was used to model the environmental determinants of the prevalence index and number of pathogens. Pathogens (number and prevalence index) showed the expected latitudinal gradient, but predictors varied by latitude. Pathogens increased with temperature in high-latitude zones, while mean annual precipitation was a more important predictor in low-latitude zones. Other environmental factors associated with more pathogens included seasonal dry extremes, frost-free climates, and human population density outside the tropics. Islands showed the expected species-area relationship for all but the smallest islands, and the relationship was not mediated by habitat diversity. Although geographic distributions of free-living and parasitic taxa typically have different determinants, these data show that variables that influence the distribution of free-living organisms also shape the global distribution of human pathogens. Understanding the cause of these distributions is potentially important, since geographical variation in human pathogens has an important influence on global disparities in human welfare.

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

PubMed Central

Cocco, Simona; Monasson, Remi; Weigt, Martin

2013-01-01

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant ‘patterns’ of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold. PMID:23990764

Can we predict the property cycle? A study of securitized property market

NASA Astrophysics Data System (ADS)

Hui, Eddie Chi-Man; Wang, Ziyou

2015-05-01

Academia takes interest in cyclicality of real estate market. Compared to various findings on housing cycles, no literature takes insight into the cycles of securitized property markets. To address the issue, a nonlinear model is developed to probe into the characteristics of cycles in global markets (US, UK, Australia, Japan, Singapore and Hong Kong) over the last 23 years. The findings suggest that (a) cointegrating relationships influence the six markets in the long term and become stronger during bullish markets. (b) The short-term dynamics of each market is more likely to have a regime-switching structure. (c) The cyclical pattern shows differences between securitized property and housing markets, as well as between securitized property and general stock markets. Meanwhile, the cyclical pattern in developed markets is also different from that in developing markets. (d) The duration dependence shows a weak effect of the boom on predicting the occurrence of the upcoming bust. Instead, the magnitude of boom growth plays a significant role in predicting the duration of following bust. (e) The asymmetric analysis brings forward the "paralleling effect" which indicates that the asymmetry in returns is parallel with the movements of r. The methodology shall serve in providing detailed implications on the characters of cycle and duration forecast in securitized property markets for investors and governments.

Plant community, geographic distance and abiotic factors play different roles in predicting AMF biogeography at the regional scale in northern China.

PubMed

Xu, Tianle; Veresoglou, Stavros D; Chen, Yongliang; Rillig, Matthias C; Xiang, Dan; Ondřej, Daniel; Hao, Zhipeng; Liu, Lei; Deng, Ye; Hu, Yajun; Chen, Weiping; Wang, Juntao; He, Jizheng; Chen, Baodong

2016-12-01

Arbuscular mycorrhizal fungi (AMF) are ubiquitous mutualists of terrestrial plants and play key roles in regulating various ecosystem processes, but little is known about AMF biogeography at regional scale. This study aims at exploring the key predictors of AMF communities across a 5000-km transect in northern China. We determined the soil AMF species richness and community composition at 47 sites representative of four vegetation types (meadow steppe, typical steppe, desert steppe and desert) and related them to plant community characteristics, abiotic factors and geographic distance. The results showed that soil pH was the strongest predictor of AMF richness and phylogenetic diversity. However, abiotic factors only have a low predictive effect on AMF community composition or phylogenetic patterns. By contrast, we found a significant relationship between community composition of AMF and plants, which was a surprising result given the extent of heterogeneity in the plant community across this transect. Moreover, the geographic distance predominantly explained the AMF phylogenetic structure, implying that history evolutionary may play a role in shaping AMF biogeographic patterns. This study highlighted the different roles of main factors in predicting AMF biogeography, and bridge landscape-scale studies to more recent global-scale efforts. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

The Risk Implications of Globalisation: An Exploratory Analysis of 105 Major Industrial Incidents (1971–2010)

PubMed Central

Beck, Matthias

2016-01-01

This paper revisits work on the socio-political amplification of risk, which predicts that those living in developing countries are exposed to greater risk than residents of developed nations. This prediction contrasts with the neoliberal expectation that market driven improvements in working conditions within industrialising/developing nations will lead to global convergence of hazard exposure levels. It also contradicts the assumption of risk society theorists that there will be an ubiquitous increase in risk exposure across the globe, which will primarily affect technically more advanced countries. Reviewing qualitative evidence on the impact of structural adjustment reforms in industrialising countries, the export of waste and hazardous waste recycling to these countries and new patterns of domestic industrialisation, the paper suggests that workers in industrialising countries continue to face far greater levels of hazard exposure than those of developed countries. This view is confirmed when a data set including 105 major multi-fatality industrial disasters from 1971 to 2000 is examined. The paper concludes that there is empirical support for the predictions of socio-political amplification of risk theory, which finds clear expression in the data in a consistent pattern of significantly greater fatality rates per industrial incident in industrialising/developing countries. PMID:26978378

Seasonally Varying Predation Behavior and Climate Shifts Are Predicted to Affect Predator-Prey Cycles.

PubMed

Tyson, Rebecca; Lutscher, Frithjof

2016-11-01

The functional response of some predator species changes from a pattern characteristic for a generalist to that for a specialist according to seasonally varying prey availability. Current theory does not address the dynamic consequences of this phenomenon. Since season length correlates strongly with altitude and latitude and is predicted to change under future climate scenarios, including this phenomenon in theoretical models seems essential for correct prediction of future ecosystem dynamics. We develop and analyze a two-season model for the great horned owl (Bubo virginialis) and snowshoe hare (Lepus americanus). These species form a predator-prey system in which the generalist to specialist shift in predation pattern has been documented empirically. We study the qualitative behavior of this predator-prey model community as summer season length changes. We find that relatively small changes in summer season length can have a profound impact on the system. In particular, when the predator has sufficient alternative resources available during the summer season, it can drive the prey to extinction, there can be coexisting stable states, and there can be stable large-amplitude limit cycles coexisting with a stable steady state. Our results illustrate that the impacts of global change on local ecosystems can be driven by internal system dynamics and can potentially have catastrophic consequences.

Local patterns of biological N fixation and N-to-P limitations along steep atmospheric deposition gradients

NASA Astrophysics Data System (ADS)

Scott, Dalton; Bradley, Robert; Bellenger, Jean-Philippe; Kathrin, Rousk; Michael, Gundale; DeLuca, Tom

2017-04-01

A major challenge facing biogeochemists is being able to predict how environmental changes alter the functioning of forest ecosystems. In particular, atmospheric N deposition (AND) from fossil fuel combustion is fertilizing forest ecosystems worldwide at an unprecedented rate. While much attention has been paid to regional and continental-scale AND patterns, very little is known about local scale patterns resulting from human activities. For example, busy roads have recently been identified as hotspots for AND, with steep gradients occurring within 100-400 m margins along busy roadsides. It was previously found that such gradients along boreal forest roadsides correlated negatively with changes in biological N fixation (BNF) by moss dwelling cyanobacteria. Here, we present data from a recent experiment designed to answer specific questions regarding this phenomenon, namely: (1) Can AND lead to shifts from N to P limitation of BNF in mosses? (2) Can AND shift the stoichiometry of P and Mo (i.e. nitrogenase enzyme cofactor) limiting BNF in mosses? (3) Do roadside BNF patterns occur because of a down regulation in nitrogenase enzyme activity, or as the result of changes in moss biomass? (4) Do roadside AND and BNF patterns correlate predictably with the relative N-to-P limitation of trees? Preliminary results confirm that roadside BNF gradients are site specific, with moisture and light availability as major environmental controls. P-limitations of BNF were observed along roadside gradients on some sites, as were changes in spruce needle N and P concentrations. Decreases in BNF due to high AND may partly be due to changes in moss biomass. Collectively, our project provides important insights that improve our knowledge of site-specific stoichiometric gradients due to AND, which can be used to improve the precision of biogeochemical models required to predict ecosystem responses to global changes.

Topographic and Bioclimatic Determinants of the Occurrence of Forest and Grassland in Tropical Montane Forest-Grassland Mosaics of the Western Ghats, India

PubMed Central

Das, Arundhati; Nagendra, Harini; Anand, Madhur; Bunyan, Milind

2015-01-01

The objective of this analysis was to identify topographic and bioclimatic factors that predict occurrence of forest and grassland patches within tropical montane forest-grassland mosaics. We further investigated whether interactions between topography and bioclimate are important in determining vegetation pattern, and assessed the role of spatial scale in determining the relative importance of specific topographic features. Finally, we assessed the role of elevation in determining the relative importance of diverse explanatory factors. The study area consists of the central and southern regions of the Western Ghats of Southern India, a global biodiversity hotspot. Random forests were used to assess prediction accuracy and predictor importance. Conditional inference classification trees were used to interpret predictor effects and examine potential interactions between predictors. GLMs were used to confirm predictor importance and assess the strength of interaction terms. Overall, topographic and bioclimatic predictors classified vegetation pattern with approximately 70% accuracy. Prediction accuracy was higher for grassland than forest, and for mosaics at higher elevations. Elevation was the most important predictor, with mosaics above 2000m dominated largely by grassland. Relative topographic position measured at a local scale (within a 300m neighbourhood) was another important predictor of vegetation pattern. In high elevation mosaics, northness and concave land surface curvature were important predictors of forest occurrence. Important bioclimatic predictors were: dry quarter precipitation, annual temperature range and the interaction between the two. The results indicate complex interactions between topography and bioclimate and among topographic variables. Elevation and topography have a strong influence on vegetation pattern in these mosaics. There were marked regional differences in the roles of various topographic and bioclimatic predictors across the range of study mosaics, indicating that the same pattern of grass and forest seems to be generated by different sets of mechanisms across the region, depending on spatial scale and elevation. PMID:26121353

Topographic and Bioclimatic Determinants of the Occurrence of Forest and Grassland in Tropical Montane Forest-Grassland Mosaics of the Western Ghats, India.

PubMed

Das, Arundhati; Nagendra, Harini; Anand, Madhur; Bunyan, Milind

2015-01-01

The objective of this analysis was to identify topographic and bioclimatic factors that predict occurrence of forest and grassland patches within tropical montane forest-grassland mosaics. We further investigated whether interactions between topography and bioclimate are important in determining vegetation pattern, and assessed the role of spatial scale in determining the relative importance of specific topographic features. Finally, we assessed the role of elevation in determining the relative importance of diverse explanatory factors. The study area consists of the central and southern regions of the Western Ghats of Southern India, a global biodiversity hotspot. Random forests were used to assess prediction accuracy and predictor importance. Conditional inference classification trees were used to interpret predictor effects and examine potential interactions between predictors. GLMs were used to confirm predictor importance and assess the strength of interaction terms. Overall, topographic and bioclimatic predictors classified vegetation pattern with approximately 70% accuracy. Prediction accuracy was higher for grassland than forest, and for mosaics at higher elevations. Elevation was the most important predictor, with mosaics above 2000 m dominated largely by grassland. Relative topographic position measured at a local scale (within a 300 m neighbourhood) was another important predictor of vegetation pattern. In high elevation mosaics, northness and concave land surface curvature were important predictors of forest occurrence. Important bioclimatic predictors were: dry quarter precipitation, annual temperature range and the interaction between the two. The results indicate complex interactions between topography and bioclimate and among topographic variables. Elevation and topography have a strong influence on vegetation pattern in these mosaics. There were marked regional differences in the roles of various topographic and bioclimatic predictors across the range of study mosaics, indicating that the same pattern of grass and forest seems to be generated by different sets of mechanisms across the region, depending on spatial scale and elevation.

Seasonal climate change patterns due to cumulative CO2 emissions

NASA Astrophysics Data System (ADS)

Partanen, Antti-Ilari; Leduc, Martin; Damon Matthews, H.

2017-07-01

Cumulative CO2 emissions are near linearly related to both global and regional changes in annual-mean surface temperature. These relationships are known as the transient climate response to cumulative CO2 emissions (TCRE) and the regional TCRE (RTCRE), and have been shown to remain approximately constant over a wide range of cumulative emissions. Here, we assessed how well this relationship holds for seasonal patterns of temperature change, as well as for annual-mean and seasonal precipitation patterns. We analyzed an idealized scenario with CO2 concentration growing at an annual rate of 1% using data from 12 Earth system models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Seasonal RTCRE values for temperature varied considerably, with the highest seasonal variation evident in the Arctic, where RTCRE was about 5.5 °C per Tt C for boreal winter and about 2.0 °C per Tt C for boreal summer. Also the precipitation response in the Arctic during boreal winter was stronger than during other seasons. We found that emission-normalized seasonal patterns of temperature change were relatively robust with respect to time, though they were sub-linear with respect to emissions particularly near the Arctic. Moreover, RTCRE patterns for precipitation could not be quantified robustly due to the large internal variability of precipitation. Our results suggest that cumulative CO2 emissions are a useful metric to predict regional and seasonal changes in precipitation and temperature. This extension of the TCRE framework to seasonal and regional climate change is helpful for communicating the link between emissions and climate change to policy-makers and the general public, and is well-suited for impact studies that could make use of estimated regional-scale climate changes that are consistent with the carbon budgets associated with global temperature targets.

Unimodal Latitudinal Pattern of Land-Snail Species Richness across Northern Eurasian Lowlands

PubMed Central

Horsák, Michal; Chytrý, Milan

2014-01-01

Large-scale patterns of species richness and their causes are still poorly understood for most terrestrial invertebrates, although invertebrates can add important insights into the mechanisms that generate regional and global biodiversity patterns. Here we explore the general plausibility of the climate-based “water-energy dynamics” hypothesis using the latitudinal pattern of land-snail species richness across extensive topographically homogeneous lowlands of northern Eurasia. We established a 1480-km long latitudinal transect across the Western Siberian Plain (Russia) from the Russia-Kazakhstan border (54.5°N) to the Arctic Ocean (67.5°N), crossing eight latitudinal vegetation zones: steppe, forest-steppe, subtaiga, southern, middle and northern taiga, forest-tundra, and tundra. We sampled snails in forests and open habitats each half-degree of latitude and used generalized linear models to relate snail species richness to climatic variables and soil calcium content measured in situ. Contrary to the classical prediction of latitudinal biodiversity decrease, we found a striking unimodal pattern of snail species richness peaking in the subtaiga and southern-taiga zones between 57 and 59°N. The main south-to-north interchange of the two principal diversity constraints, i.e. drought stress vs. cold stress, explained most of the variance in the latitudinal diversity pattern. Water balance, calculated as annual precipitation minus potential evapotranspiration, was a single variable that could explain 81.7% of the variance in species richness. Our data suggest that the “water-energy dynamics” hypothesis can apply not only at the global scale but also at subcontinental scales of higher latitudes, as water availability was found to be the primary limiting factor also in this extratropical region with summer-warm and dry climate. A narrow zone with a sharp south-to-north switch in the two main diversity constraints seems to constitute the dominant and general pattern of terrestrial diversity across a large part of northern Eurasia, resulting in a subcontinental diversity hotspot of various taxa in this zone. PMID:25090628

Global patterns in lake ecosystem responses to warming based on the temperature dependence of metabolism.

PubMed

Kraemer, Benjamin M; Chandra, Sudeep; Dell, Anthony I; Dix, Margaret; Kuusisto, Esko; Livingstone, David M; Schladow, S Geoffrey; Silow, Eugene; Sitoki, Lewis M; Tamatamah, Rashid; McIntyre, Peter B

2017-05-01

Climate warming is expected to have large effects on ecosystems in part due to the temperature dependence of metabolism. The responses of metabolic rates to climate warming may be greatest in the tropics and at low elevations because mean temperatures are warmer there and metabolic rates respond exponentially to temperature (with exponents >1). However, if warming rates are sufficiently fast in higher latitude/elevation lakes, metabolic rate responses to warming may still be greater there even though metabolic rates respond exponentially to temperature. Thus, a wide range of global patterns in the magnitude of metabolic rate responses to warming could emerge depending on global patterns of temperature and warming rates. Here we use the Boltzmann-Arrhenius equation, published estimates of activation energy, and time series of temperature from 271 lakes to estimate long-term (1970-2010) changes in 64 metabolic processes in lakes. The estimated responses of metabolic processes to warming were usually greatest in tropical/low-elevation lakes even though surface temperatures in higher latitude/elevation lakes are warming faster. However, when the thermal sensitivity of a metabolic process is especially weak, higher latitude/elevation lakes had larger responses to warming in parallel with warming rates. Our results show that the sensitivity of a given response to temperature (as described by its activation energy) provides a simple heuristic for predicting whether tropical/low-elevation lakes will have larger or smaller metabolic responses to warming than higher latitude/elevation lakes. Overall, we conclude that the direct metabolic consequences of lake warming are likely to be felt most strongly at low latitudes and low elevations where metabolism-linked ecosystem services may be most affected. © 2016 John Wiley & Sons Ltd.

An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lynch, Cary D.; Hartin, Corinne A.; Bond-Lamberty, Benjamin

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We exploremore » the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.« less

An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology

DOE PAGES

Lynch, Cary D.; Hartin, Corinne A.; Bond-Lamberty, Benjamin; ...

2017-05-15

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We exploremore » the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.« less

Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome

PubMed Central

Low, Yen S; Caster, Ola; Bergvall, Tomas; Fourches, Denis; Zang, Xiaoling; Norén, G Niklas; Rusyn, Ivan; Edwards, Ralph

2016-01-01

Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models. Materials and Methods Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from drug molecular structures. Random Forest and Support Vector Machines methods were used to develop QSAR models, which were validated by external 5-fold cross validation. Models were employed for virtual screening of DrugBank to predict SJS actives and inactives, which were corroborated using knowledge bases like VigiBase, ChemoText, and MicroMedex (Truven Health Analytics Inc, Ann Arbor, Michigan). Results We developed QSAR models that could accurately predict if drugs were associated with SJS (area under the curve of 75%–81%). Our 10 most active and inactive predictions were substantiated by SJS reports (or lack thereof) in the literature. Discussion Interpretation of QSAR models in terms of significant chemical descriptors suggested novel SJS structural alerts. Conclusions We have demonstrated that QSAR models can accurately identify SJS active and inactive drugs. Requiring chemical structures only, QSAR models provide effective computational means to flag potentially harmful drugs for subsequent targeted surveillance and pharmacoepidemiologic investigations. PMID:26499102

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

DOE PAGES

Tramontana, Gianluca; Jung, Martin; Schwalm, Christopher R.; ...

2016-07-29

Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data andmore » (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange ( R 2 < 0.5), ecosystem respiration ( R 2 > 0.6), gross primary production ( R 2> 0.7), latent heat ( R 2 > 0.7), sensible heat ( R 2 > 0.7), and net radiation ( R 2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well ( R 2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted ( R 2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). Finally, the evaluated large ensemble of ML-based models will be the basis of new global flux products.« less

Decadal prediction of Sahel rainfall: where does the skill (or lack thereof) come from?

NASA Astrophysics Data System (ADS)

Mohino, Elsa; Keenlyside, Noel; Pohlmann, Holger

2016-12-01

Previous works suggest decadal predictions of Sahel rainfall could be skillful. However, the sources of such skill are still under debate. In addition, previous results are based on short validation periods (i.e. less than 50 years). In this work we propose a framework based on multi-linear regression analysis to study the potential sources of skill for predicting Sahel trends several years ahead. We apply it to an extended decadal hindcast performed with the MPI-ESM-LR model that span from 1901 to 2010 with 1 year sampling interval. Our results show that the skill mainly depends on how well we can predict the timing of the global warming (GW), the Atlantic multidecadal variability (AMV) and, to a lesser extent, the inter-decadal Pacific oscillation signals, and on how well the system simulates the associated SST and West African rainfall response patterns. In the case of the MPI-ESM-LR decadal extended hindcast, the observed timing is well reproduced only for the GW and AMV signals. However, only the West African rainfall response to the AMV is correctly reproduced. Thus, for most of the lead times the main source of skill in the decadal hindcast of West African rainfall is from the AMV. The GW signal degrades skill because the response of West African rainfall to GW is incorrectly captured. Our results also suggest that initialized decadal predictions of West African rainfall can be further improved by better simulating the response of global SST to GW and AMV. Furthermore, our approach may be applied to understand and attribute prediction skill for other variables and regions.

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tramontana, Gianluca; Jung, Martin; Schwalm, Christopher R.

Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data andmore » (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange ( R 2 < 0.5), ecosystem respiration ( R 2 > 0.6), gross primary production ( R 2> 0.7), latent heat ( R 2 > 0.7), sensible heat ( R 2 > 0.7), and net radiation ( R 2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well ( R 2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted ( R 2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). Finally, the evaluated large ensemble of ML-based models will be the basis of new global flux products.« less

U.S. GODAE: Global Ocean Prediction With the HYbrid Coordinate Ocean Model (HYCOM)

DTIC Science & Technology

2009-06-01

REPORT DATE (DD-MM- YYYY) 12-08-2009 2. REPORT TYPE Journal Article 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE U.S. GODAE: Global ...the lerformance and application of eddy-resolving, real-time global - and basin-scale ocean prediction systems using the HYbrid Coordinate Ocean...prediction system outputs. In addnion to providing real-time, eddy-resolving global - and basin-scale ocean prediction systems for the US Navy and NOAA, this

Explaining patterns in the ratification of global environmental treaties

NASA Technical Reports Server (NTRS)

Cook, David W.

1991-01-01

A study was made of the ratification behavior of 160 countries with respect to 38 global environmental treaties. The study identifies and explains patterns in the ratification of treaties, providing two means of assessing the likelihood that any given country will support global environmental treaties. National ratification totals reveal a pattern of high ratification by countries in Western Europe, North America, Japan, Australia, and New Zealand. A country's standing within the range of high to low ratification rates can be explained by the statistical model developed in the study. This research allows one to identify countries likely to support global environmental treaties.

"Modeled and measured carbon cycling in Mojave Desert soils: toward present and projected greenhouse gas budgets for arid regions

NASA Astrophysics Data System (ADS)

Maurer, G. E.; Amundson, R.; Lammers, L. N.; Mills, J.; Oerter, E.

2017-12-01

Drylands comprise roughly 35% of the Earth's surface, store globally significant amounts of carbon, and cycle this carbon at rates that vary greatly from year to year. Consequently, drylands are thought to contribute to inter-annual changes in the global atmospheric CO2 budget. Sparse measurements and limited process-based modeling have made quantifying dryland carbon cycling at regional or larger scales a major challenge. We parameterized and ran the DayCent model, an ecosystem model that simulates soil C and N cycling and greenhouse gas (GHG) fluxes, using long-term regional climate, soil, and vegetation data for the Mojave Desert region (southwest USA). DayCent predicted somewhat greater soil organic C than was observed in a database of 186 measured Mojave soil survey samples, but successfully recreated climate-driven patterns in soil carbon storage across the landscape. Modeled soil organic carbon storage increased by between 4.1 and 5.1 kg/m2 per km of elevation gained, while Mojave soil survey data indicated an increase of 4.6 kg/m2. Model predictions of soil CO2 flux were validated and calibrated against field observations from ten Mojave soil gas profile studies sampled intermittently between 1986 and the present. DayCent had a tendency to overestimate soil respiration measured at some sites by up to 600% compared to profile measurements. Modeled soil CO2 fluxes increased by between 1280 and 4141 kg/ha/yr per km of elevation gained.This elevational pattern did not match well with landscape-level changes in observed soil profile CO2 flux data, indicating further calibration of DayCent will be needed to produce regional estimates of GHG flux. This ongoing synthesis of modeling and measurements extends the current knowledge of the Mojave's contribution to the global GHG budget and will provide a basis from which to project future emissions from the Mojave and other dryland regions.

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models.

PubMed

Johnson, Michelle O; Galbraith, David; Gloor, Manuel; De Deurwaerder, Hannes; Guimberteau, Matthieu; Rammig, Anja; Thonicke, Kirsten; Verbeeck, Hans; von Randow, Celso; Monteagudo, Abel; Phillips, Oliver L; Brienen, Roel J W; Feldpausch, Ted R; Lopez Gonzalez, Gabriela; Fauset, Sophie; Quesada, Carlos A; Christoffersen, Bradley; Ciais, Philippe; Sampaio, Gilvan; Kruijt, Bart; Meir, Patrick; Moorcroft, Paul; Zhang, Ke; Alvarez-Davila, Esteban; Alves de Oliveira, Atila; Amaral, Ieda; Andrade, Ana; Aragao, Luiz E O C; Araujo-Murakami, Alejandro; Arets, Eric J M M; Arroyo, Luzmila; Aymard, Gerardo A; Baraloto, Christopher; Barroso, Jocely; Bonal, Damien; Boot, Rene; Camargo, Jose; Chave, Jerome; Cogollo, Alvaro; Cornejo Valverde, Fernando; Lola da Costa, Antonio C; Di Fiore, Anthony; Ferreira, Leandro; Higuchi, Niro; Honorio, Euridice N; Killeen, Tim J; Laurance, Susan G; Laurance, William F; Licona, Juan; Lovejoy, Thomas; Malhi, Yadvinder; Marimon, Bia; Marimon, Ben Hur; Matos, Darley C L; Mendoza, Casimiro; Neill, David A; Pardo, Guido; Peña-Claros, Marielos; Pitman, Nigel C A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Roopsind, Anand; Rudas, Agustin; Salomao, Rafael P; Silveira, Marcos; Stropp, Juliana; Ter Steege, Hans; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van der Heijden, Geertje M F; Vasquez, Rodolfo; Guimarães Vieira, Ima Cèlia; Vilanova, Emilio; Vos, Vincent A; Baker, Timothy R

2016-12-01

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Sea Level Change due to Time-Dependent Long-Wavelength Dynamic Topography Inferred from Plate Tectonic Reconstructions

NASA Astrophysics Data System (ADS)

Conrad, Clinton P.; Steinberger, Bernhard; Torsvik, Trond H.

2017-04-01

Earth's surface is deflected vertically by stresses associated with convective mantle flow. Although dynamic topography is important for both sea level change and continental uplift and subsidence, the time history of dynamic topography is difficult to constrain because the time-dependence of mantle flow is not known. However, the motions of the tectonic plates contain information about the mantle flow patterns that drive them. In particular, we show that the longest wavelengths of mantle flow are tightly linked to the dipole and quadrupole moments (harmonic degrees 1 and 2) of plate motions. This coupling allows us to infer patterns of long-wavelength mantle flow, and the associated dynamic topography, from tectonic plate motions. After calibrating this linkage using models of present-day mantle flow, we can use reconstructions of global plate motions to infer the basic patterns of long-wavelength dynamic topography back to 250 Ma. We find relatively stable dynamic uplift persists above large-scale mantle upwelling beneath Africa and the Central Pacific. Regions of major downwelling encircled the periphery of these stable upwellings, alternating between primarily east-west and north-south orientations. The amplitude of long-wavelength dynamic topography was likely largest in the Cretaceous, when global plate motions were fastest. Continental motions over this time-evolving dynamic topography predict patterns of continental uplift and subsidence that are confirmed by geological observations of continental surfaces relative to sea level. Net uplift or subsidence of the global seafloor can also induce eustatic sea level changes. We infer that dispersal of the Pangean supercontinent away from stable upwelling beneath Africa may have exposed the seafloor to an increasingly larger area of growing positive dynamic topography during the Mesozoic. This net uplift of the seafloor caused 60 m of sea level rise during the Triassic and Jurassic, ceasing in the Cenozoic once continents fully override degree-2 downwellings. These sea level changes represent a significant component of the estimated 200 m of sea level variations during the Phanerozoic, which exhibit a similar temporal pattern.

Mapping Plant Diversity and Composition Across North Carolina Piedmont Forest Landscapes Using Lidar-Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Hakkenberg, Christopher R.

Forest modification, from local stress to global change, has given rise to efforts to model, map, and monitor critical properties of forest communities like structure, composition, and diversity. Predictive models based on data from spatially-nested field plots and LiDAR-hyperspectral remote sensing systems are one particularly effective means towards the otherwise prohibitively resource-intensive task of consistently characterizing forest community dynamics at landscape scales. However, to date, most predictive models fail to account for actual (rather than idealized) species and community distributions, are unsuccessful in predicting understory components in structurally and taxonomically heterogeneous forests, and may suffer from diminished predictive accuracy due to incongruity in scale and precision between field plot samples, remotely-sensed data, and target biota of varying size and density. This three-part study addresses these and other concerns in the modeling and mapping of emergent properties of forest communities by shifting the scope of prediction from the individual or taxon to the whole stand or community. It is, after all, at the stand scale where emergent properties like functional processes, biodiversity, and habitat aggregate and manifest. In the first study, I explore the relationship between forest structure (a proxy for successional demographics and resource competition) and tree species diversity in the North Carolina Piedmont, highlighting the empirical basis and potential for utilizing forest structure from LiDAR in predictive models of tree species diversity. I then extend these conclusions to map landscape pattern in multi-scale vascular plant diversity as well as turnover in community-continua at varying compositional resolutions in a North Carolina Piedmont landscape using remotely-sensed LiDAR-hyperspectral estimates of topography, canopy structure, and foliar biochemistry. Recognizing that the distinction between correlation and causation mirrors that between knowledge and understanding, all three studies distinguish between prediction of pattern and inference of process. Thus, in addition to advancing mapping methodologies relevant to a range of forest ecosystem management and monitoring applications, all three studies are noteworthy for assessing the ecological relationship between environmental predictors and emergent landscape patterns in plant composition and diversity in North Carolina Piedmont forests.

Global linkages between teleconnection patterns and the terrestrial biosphere

NASA Astrophysics Data System (ADS)

Dahlin, Kyla M.; Ault, Toby R.

2018-07-01

Interannual variability in the global carbon cycle is largely due to variations in carbon uptake by terrestrial ecosystems, yet linkages between climate variability and variability in the terrestrial carbon cycle are not well understood at the global scale. Using a 30-year satellite record of semi-monthly leaf area index (LAI), we show that four modes of climate variability - El Niño/Southern Oscillation, the North Atlantic Oscillation, the Atlantic Meridional Mode, and the Indian Ocean Dipole Mode - strongly impact interannual vegetation growth patterns, with 68% of the land surface impacted by at least one of these teleconnection patterns, yet the spatial distribution of these impacts is heterogeneous. Considering the patterns' impacts by biome, none has an exclusively positive or negative relationship with LAI. Our findings imply that future changes in the frequency and/or magnitude of teleconnection patterns will lead to diverse changes to the terrestrial biosphere and the global carbon cycle.

Stable isotopes in barnacles as a tool to understand green sea turtle (Chelonia mydas) regional movement patterns

NASA Astrophysics Data System (ADS)

Detjen, M.; Sterling, E.; Gómez, A.

2015-12-01

Sea turtles are migratory animals that travel long distances between their feeding and breeding grounds. Traditional methods for researching sea turtle migratory behavior have important disadvantages, and the development of alternatives would enhance our ability to monitor and manage these globally endangered species. Here we report on the isotope signatures in green sea-turtle (Chelonia mydas) barnacles (Platylepas sp.) and discuss their potential relevance as tools with which to study green sea turtle migration and habitat use patterns. We analyzed oxygen (δ18O) and carbon (δ13C) isotope ratios in barnacle calcite layers from specimens collected from green turtles captured at the Palmyra Atoll National Wildlife Refuge (PANWR) in the central Pacific. Carbon isotopes were not informative in this study. However, the oxygen isotope results suggest likely regional movement patterns when mapped onto a predictive oxygen isotope map of the Pacific. Barnacle proxies could therefore complement other methods in understanding regional movement patterns, informing more effective conservation policy that takes into account connectivity between populations.

Stable isotopes in barnacles as a tool to understand green sea turtle (Chelonia mydas) regional movement patterns

NASA Astrophysics Data System (ADS)

Detjen, M.; Sterling, E.; Gómez, A.

2015-03-01

Sea turtles are migratory animals that travel long distances between their feeding and breeding grounds. Traditional methods for researching sea turtle migratory behavior have important disadvantages, and the development of alternatives would enhance our ability to monitor and manage these globally endangered species. Here we report on the isotope signatures in green sea turtle (Chelonia mydas) barnacles (Platylepas sp.) and discuss their potential relevance as tools with which to study green sea turtle migration and habitat use patterns. We analyzed oxygen (δ18O) and carbon (δ13C) isotope ratios in barnacle calcite layers from specimens collected from green turtles captured at the Palmyra Atoll National Wildlife Refuge (PANWR) in the Central Pacific. Carbon isotopes were not informative in this study. However, the oxygen isotope results suggest likely regional movement patterns when mapped onto a predictive oxygen isotope map of the Pacific. Barnacle proxies could therefore complement other methods in understanding regional movement patterns, informing more effective conservation policy that takes into account connectivity between populations.

Perceptual learning in a non-human primate model of artificial vision

PubMed Central

Killian, Nathaniel J.; Vurro, Milena; Keith, Sarah B.; Kyada, Margee J.; Pezaris, John S.

2016-01-01

Visual perceptual grouping, the process of forming global percepts from discrete elements, is experience-dependent. Here we show that the learning time course in an animal model of artificial vision is predicted primarily from the density of visual elements. Three naïve adult non-human primates were tasked with recognizing the letters of the Roman alphabet presented at variable size and visualized through patterns of discrete visual elements, specifically, simulated phosphenes mimicking a thalamic visual prosthesis. The animals viewed a spatially static letter using a gaze-contingent pattern and then chose, by gaze fixation, between a matching letter and a non-matching distractor. Months of learning were required for the animals to recognize letters using simulated phosphene vision. Learning rates increased in proportion to the mean density of the phosphenes in each pattern. Furthermore, skill acquisition transferred from trained to untrained patterns, not depending on the precise retinal layout of the simulated phosphenes. Taken together, the findings suggest that learning of perceptual grouping in a gaze-contingent visual prosthesis can be described simply by the density of visual activation. PMID:27874058

Arctic climatechange and its impacts on the ecology of the North Atlantic.

PubMed

Greene, Charles H; Pershing, Andrew J; Cronin, Thomas M; Ceci, Nicole

2008-11-01

Arctic climate change from the Paleocene epoch to the present is reconstructed with the objective of assessing its recent and future impacts on the ecology of the North Atlantic. A recurring theme in Earth's paleoclimate record is the importance of the Arctic atmosphere, ocean, and cryosphere in regulating global climate on a variety of spatial and temporal scales. A second recurring theme in this record is the importance of freshwater export from the Arctic in regulating global- to basin-scale ocean circulation patterns and climate. Since the 1970s, historically unprecedented changes have been observed in the Arctic as climate warming has increased precipitation, river discharge, and glacial as well as sea-ice melting. In addition, modal shifts in the atmosphere have altered Arctic Ocean circulation patterns and the export of freshwater into the North Atlantic. The combination of these processes has resulted in variable patterns of freshwater export from the Arctic Ocean and the emergence of salinity anomalies that have periodically freshened waters in the North Atlantic. Since the early 1990s, changes in Arctic Ocean circulation patterns and freshwater export have been associated with two types of ecological responses in the North Atlantic. The first of these responses has been an ongoing series of biogeographic range expansions by boreal plankton, including renewal of the trans-Arctic exchanges of Pacific species with the Atlantic. The second response was a dramatic regime shift in the shelf ecosystems of the Northwest Atlantic that occurred during the early 1990s. This regime shift resulted from freshening and stratification of the shelf waters, which in turn could be linked to changes in the abundances and seasonal cycles of phytoplankton, zooplankton, and higher trophic-level consumer populations. It is predicted that the recently observed ecological responses to Arctic climate change in the North Atlantic will continue into the near future if current trends in sea ice, freshwater export, and surface ocean salinity continue. It is more difficult to predict ecological responses to abrupt climate change in the more distant future as tipping points in the Earth's climate system are exceeded.

Partial synchronization of relaxation oscillators with repulsive coupling in autocatalytic integrate-and-fire model and electrochemical experiments

NASA Astrophysics Data System (ADS)

Kori, Hiroshi; Kiss, István Z.; Jain, Swati; Hudson, John L.

2018-04-01

Experiments and supporting theoretical analysis are presented to describe the synchronization patterns that can be observed with a population of globally coupled electrochemical oscillators close to a homoclinic, saddle-loop bifurcation, where the coupling is repulsive in the electrode potential. While attractive coupling generates phase clusters and desynchronized states, repulsive coupling results in synchronized oscillations. The experiments are interpreted with a phenomenological model that captures the waveform of the oscillations (exponential increase) followed by a refractory period. The globally coupled autocatalytic integrate-and-fire model predicts the development of partially synchronized states that occur through attracting heteroclinic cycles between out-of-phase two-cluster states. Similar behavior can be expected in many other systems where the oscillations occur close to a saddle-loop bifurcation, e.g., with Morris-Lecar neurons.

Is Social Categorization the Missing Link Between Weak Central Coherence and Mental State Inference Abilities in Autism? Preliminary Evidence from a General Population Sample.

PubMed

Skorich, Daniel P; May, Adrienne R; Talipski, Louisa A; Hall, Marnie H; Dolstra, Anita J; Gash, Tahlia B; Gunningham, Beth H

2016-03-01

We explore the relationship between the 'theory of mind' (ToM) and 'central coherence' difficulties of autism. We introduce covariation between hierarchically-embedded categories and social information--at the local level, the global level, or at both levels simultaneously--within a category confusion task. We then ask participants to infer the mental state of novel category members, and measure participants' autism-spectrum quotient (AQ). Results reveal a positive relationship between AQ and the degree of local/global social categorization, which in turn predicts the pattern of mental state inferences. These results provide preliminary evidence for a causal relationship between central coherence and ToM abilities. Implications with regard to ToM processes, social categorization, intervention, and the development of a unified account of autism are discussed.

Seasonal prediction of typhoon genesis frequency and track patterns in the North West Pacific area

NASA Astrophysics Data System (ADS)

Hyoun, Yoosun; Kang, Kiryong; Shin, Do-Shick

2014-05-01

This study is to investigate the performance of the typhoon seasonal predictability using a dynamical model. The check items are the monthly statistics for total number of typhoon genesis in Western North Pacific (WNP) area and possible threat to Korean peninsula among them, and the probability of each categorized track pattern. As the dynamical model the Florida State University/Center for Ocean-Atmospheric Prediction Studies (FSU/COAPS) was used, and it uses five ensemble members including control run are generated using time-lagged methods and the resolution of T126L27 (a Gaussian grid spacing of 0.94º). The model initial conditions are obtained from the National Center for Enviromental Prediction Global Forecast System (NCEP GFS) and the SST from Climate Forecast System with bias correction was used for ocean surface boundary condition. The summer (Jun-Jul-Aug) season prediction is made one month prior to target season. The detection of tropical cyclone used in this system is based on six criteria. First, the isolated vortex type minimum sea level pressure should be below 1008hPa. Second, the maximum wind speed is larger than 17m s-1. Third, the magnitude of the maximum relative vorticity at 850hPa exceeds 3.5x10-5s-1. Fourth, the average temperature difference from the area mean of surrounding region at 300hPa, 500hPa, 700hPa exceeds 2.5K. Fifth, the maximum wind speed at 850hPa is larger than that at 300hPa. Sixth, this identified vortex should last more than two days. These criteria were chosen after close examination from model-observation comparison. In this study, we will focus on performance of the system typhoon frequency and track pattern in the WNP area during 2004-2013.

Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers

PubMed Central

Jackson, Monica C; Huang, Lan; Luo, Jun; Hachey, Mark; Feuer, Eric

2009-01-01

Background The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated. Methods We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*pop; and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. Results For simulated data with outlier patterns, Tango's MEET, Moran's I and I*pop had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*pop (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. Conclusion SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*pop perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango's method should be used for global clustering evaluation instead of SaTScan. PMID:19822013

Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers.

PubMed

Jackson, Monica C; Huang, Lan; Luo, Jun; Hachey, Mark; Feuer, Eric

2009-10-12

The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated. We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*(pop); and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. For simulated data with outlier patterns, Tango's MEET, Moran's I and I*(pop) had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*(pop) (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*(pop) perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango's method should be used for global clustering evaluation instead of SaTScan.

Evidence for climate change in the satellite cloud record.

PubMed

Norris, Joel R; Allen, Robert J; Evan, Amato T; Zelinka, Mark D; O'Dell, Christopher W; Klein, Stephen A

2016-08-04

Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Evidence for climate change in the satellite cloud record

NASA Astrophysics Data System (ADS)

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; Zelinka, Mark D.; O'Dell, Christopher W.; Klein, Stephen A.

2016-08-01

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Environmental Predictors of Diversity in Recent Planktonic Foraminifera as Recorded in Marine Sediments

PubMed Central

Pearson, Paul N.; Dunkley Jones, Tom; Purvis, Andy

2016-01-01

Global diversity patterns are thought to result from a combination of environmental and historical factors. This study tests the set of ecological and evolutionary hypotheses proposed to explain the global variation in present-day coretop diversity in the macroperforate planktonic foraminifera, a clade with an exceptional fossil record. Within this group, marine surface sediment assemblages are thought to represent an accurate, although centennial to millennial time-averaged, representation of recent diversity patterns. Environmental variables chosen to capture ocean temperature, structure, productivity and seasonality were used to model a range of diversity measures across the world’s oceans. Spatial autoregressive models showed that the same broad suite of environmental variables were important in shaping each of the four largely independent diversity measures (rarefied species richness, Simpson’s evenness, functional richness and mean evolutionary age). Sea-surface temperature explains the largest portion of diversity in all four diversity measures, but not in the way predicted by the metabolic theory of ecology. Vertical structure could be linked to increased diversity through the strength of stratification, but not through the depth of the mixed layer. There is limited evidence that seasonal turnover explains diversity patterns. There is evidence for functional redundancy in the low-latitude sites. The evolutionary mechanism of deep-time stability finds mixed support whilst there is relatively little evidence for an out-of-the-tropics model. These results suggest the diversity patterns of planktonic foraminifera cannot be explained by any one environmental variable or proposed mechanism, but instead reflect multiple processes acting in concert. PMID:27851751

Environmental Predictors of Diversity in Recent Planktonic Foraminifera as Recorded in Marine Sediments.

PubMed

Fenton, Isabel S; Pearson, Paul N; Dunkley Jones, Tom; Purvis, Andy

2016-01-01

Global diversity patterns are thought to result from a combination of environmental and historical factors. This study tests the set of ecological and evolutionary hypotheses proposed to explain the global variation in present-day coretop diversity in the macroperforate planktonic foraminifera, a clade with an exceptional fossil record. Within this group, marine surface sediment assemblages are thought to represent an accurate, although centennial to millennial time-averaged, representation of recent diversity patterns. Environmental variables chosen to capture ocean temperature, structure, productivity and seasonality were used to model a range of diversity measures across the world's oceans. Spatial autoregressive models showed that the same broad suite of environmental variables were important in shaping each of the four largely independent diversity measures (rarefied species richness, Simpson's evenness, functional richness and mean evolutionary age). Sea-surface temperature explains the largest portion of diversity in all four diversity measures, but not in the way predicted by the metabolic theory of ecology. Vertical structure could be linked to increased diversity through the strength of stratification, but not through the depth of the mixed layer. There is limited evidence that seasonal turnover explains diversity patterns. There is evidence for functional redundancy in the low-latitude sites. The evolutionary mechanism of deep-time stability finds mixed support whilst there is relatively little evidence for an out-of-the-tropics model. These results suggest the diversity patterns of planktonic foraminifera cannot be explained by any one environmental variable or proposed mechanism, but instead reflect multiple processes acting in concert.

Relationships between large-scale circulation patterns and carbon dioxide exchange by a deciduous forest

NASA Astrophysics Data System (ADS)

Zhang, Jingyong; Wu, Lingyun; Huang, Gang; Notaro, Michael

2011-02-01

In this study, we focus on a deciduous forest in central Massachusetts and investigate the relationships between global climate indices and CO2 exchange using eddy-covariance flux measurements from 1992 to 2007. Results suggest that large-scale circulation patterns influence the annual CO2 exchange in the forest through their effects on the local surface climate. Annual gross ecosystem exchange (GEE) in the forest is closely associated with spring El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO), previous fall Atlantic Multidecadal Oscillation (AMO), and previous winter East Pacific-North Pacific (EP-NP) pattern. Annual net ecosystem exchange (NEE) responds to previous fall AMO and PDO, while annual respiration (R) is impacted by previous fall ENSO and Pacific/North American Oscillation (PNA). Regressions based on these relationships are developed to simulate the annual GEE, NEE, and R. To avoid problems of multicollinearity, we compute a "Composite Index for GEE (CIGEE)" based on a linear combination of spring ENSO and PDO, fall AMO, and winter EP-NP and a "Composite Index for R (CIR)" based on a linear combination of fall ENSO and PNA. CIGEE, CIR, and fall AMO and PDO can explain 41, 27, and 40% of the variance of the annual GEE, R, and NEE, respectively. We further apply the methodology to two other northern midlatitude forests and find that interannual variabilities in NEE of the two forests are largely controlled by large-scale circulation patterns. This study suggests that global climate indices provide the potential for predicting CO2 exchange variability in the northern midlatitude forests.

Simulation of South-Asian Summer Monsoon in a GCM

NASA Astrophysics Data System (ADS)

Ajayamohan, R. S.

2007-10-01

Major characteristics of Indian summer monsoon climate are analyzed using simulations from the upgraded version of Florida State University Global Spectral Model (FSUGSM). The Indian monsoon has been studied in terms of mean precipitation and low-level and upper-level circulation patterns and compared with observations. In addition, the model's fidelity in simulating observed monsoon intraseasonal variability, interannual variability and teleconnection patterns is examined. The model is successful in simulating the major rainbelts over the Indian monsoon region. However, the model exhibits bias in simulating the precipitation bands over the South China Sea and the West Pacific region. Seasonal mean circulation patterns of low-level and upper-level winds are consistent with the model's precipitation pattern. Basic features like onset and peak phase of monsoon are realistically simulated. However, model simulation indicates an early withdrawal of monsoon. Northward propagation of rainbelts over the Indian continent is simulated fairly well, but the propagation is weak over the ocean. The model simulates the meridional dipole structure associated with the monsoon intraseasonal variability realistically. The model is unable to capture the observed interannual variability of monsoon and its teleconnection patterns. Estimate of potential predictability of the model reveals the dominating influence of internal variability over the Indian monsoon region.

Inferred global connectivity of whale shark Rhincodon typus populations.

PubMed

Sequeira, A M M; Mellin, C; Meekan, M G; Sims, D W; Bradshaw, C J A

2013-02-01

Ten years have passed since the last synopsis of whale shark Rhincodon typus biogeography. While a recent review of the species' biology and ecology summarized the vast data collected since then, it is clear that information on population geographic connectivity, migration and demography of R. typus is still limited and scattered. Understanding R. typus migratory behaviour is central to its conservation management considering the genetic evidence suggesting local aggregations are connected at the generational scale over entire ocean basins. By collating available data on sightings, tracked movements and distribution information, this review provides evidence for the hypothesis of broad-scale connectivity among populations, and generates a model describing how the world's R. typus are part of a single, global meta-population. Rhincodon typus occurrence timings and distribution patterns make possible a connection between several aggregation sites in the Indian Ocean. The present conceptual model and validating data lend support to the hypothesis that R. typus are able to move among the three largest ocean basins with a minimum total travelling time of around 2-4 years. The model provides a worldwide perspective of possible R. typus migration routes, and suggests a modified focus for additional research to test its predictions. The framework can be used to trim the hypotheses for R. typus movements and aggregation timings, thereby isolating possible mating and breeding areas that are currently unknown. This will assist endeavours to predict the longer-term response of the species to ocean warming and changing patterns of human-induced mortality. © 2013 The Authors. Journal of Fish Biology © 2013 The Fisheries Society of the British Isles.

Nearest pattern interaction and global pattern formation

NASA Astrophysics Data System (ADS)

Jeong, Seong-Ok; Moon, Hie-Tae; Ko, Tae-Wook

2000-12-01

We studied the effect of nearest pattern interaction on a global pattern formation in a two-dimensional space, where patterns are to grow initially from a noise in the presence of a periodic supply of energy. Although our approach is general, we found that this study is relevant in particular to the pattern formation on a periodically vibrated granular layer, as it gives a unified perspective of the experimentally observed pattern dynamics such as oscillon and stripe formations, skew-varicose and crossroll instabilities, and also a kink formation and decoration.

Grand challenges in developing a predictive understanding of global fire dynamics

NASA Astrophysics Data System (ADS)

Randerson, J. T.; Chen, Y.; Wiggins, E. B.; Andela, N.; Morton, D. C.; Veraverbeke, S.; van der Werf, G.

2017-12-01

High quality satellite observations of burned area and fire thermal anomalies over the past two decades have transformed our understanding of climate, ecosystem, and human controls on the spatial and temporal distribution of landscape fires. The satellite observations provide evidence for a rapid and widespread loss of fire from grassland and savanna ecosystems worldwide. Continued expansion of industrial agriculture suggests that observed declines in global burned area are likely to continue in future decades, with profound consequences for ecosystem function and the habitat of many endangered species. Satellite time series also highlight the importance of El Niño-Southern Oscillation and other climate modes as drivers of interannual variability. In many regions, lead times between climate indices and fire activity are considerable, enabling the development of early warning prediction systems for fire season severity. With the recent availability of high-resolution observations from Suomi NPP, Landsat 8, and Sentinel 2, the field of global fire ecology is poised to make even more significant breakthroughs over the next decade. With these new observations, it may be possible to reduce uncertainties in the spatial pattern of burned area by several fold. It is difficult to overstate the importance of these new data constraints for improving our understanding of fire impacts on human health and radiative forcing of climate change. A key research challenge in this context is to understand how the loss of global burned area will affect magnitude of the terrestrial carbon sink and trends in atmospheric composition. Advances in prognostic fire modeling will require new approaches linking agriculture with landscape fire dynamics. A critical need in this context is the development of predictive models of road networks and other drivers of land fragmentation, and a closer integration of fragmentation information with algorithms predicting fire spread. Concurrently, a better representation of the influence of livestock on fuels and fire management is essential for modeling long-term trends. In northern ecosystems, climate-driven changes in lightning ignition may accelerate the northward migration of boreal forests into arctic tundra, increasing the vulnerability of permafrost carbon.

Climate change and environmental impacts on maternal and newborn health with focus on Arctic populations.

PubMed

Rylander, Charlotta; Odland, Jon Ø; Sandanger, Torkjel M

2011-01-01

In 2007, the Intergovernmental Panel on Climate Change (IPCC) presented a report on global warming and the impact of human activities on global warming. Later the Lancet commission identified six ways human health could be affected. Among these were not environmental factors which are also believed to be important for human health. In this paper we therefore focus on environmental factors, climate change and the predicted effects on maternal and newborn health. Arctic issues are discussed specifically considering their exposure and sensitivity to long range transported contaminants. Considering that the different parts of pregnancy are particularly sensitive time periods for the effects of environmental exposure, this review focuses on the impacts on maternal and newborn health. Environmental stressors known to affects human health and how these will change with the predicted climate change are addressed. Air pollution and food security are crucial issues for the pregnant population in a changing climate, especially indoor climate and food security in Arctic areas. The total number of environmental factors is today responsible for a large number of the global deaths, especially in young children. Climate change will most likely lead to an increase in this number. Exposure to the different environmental stressors especially air pollution will in most parts of the world increase with climate change, even though some areas might face lower exposure. Populations at risk today are believed to be most heavily affected. As for the persistent organic pollutants a warming climate leads to a remobilisation and a possible increase in food chain exposure in the Arctic and thus increased risk for Arctic populations. This is especially the case for mercury. The perspective for the next generations will be closely connected to the expected temperature changes; changes in housing conditions; changes in exposure patterns; predicted increased exposure to Mercury because of increased emissions and increased biological availability. A number of environmental stressors are predicted to increase with climate change and increasingly affecting human health. Efforts should be put on reducing risk for the next generation, thus global politics and research effort should focus on maternal and newborn health.

Global climate anomalies and potential infectious disease risks: 2014-2015.

PubMed

Chretien, Jean-Paul; Anyamba, Assaf; Small, Jennifer; Britch, Seth; Sanchez, Jose L; Halbach, Alaina C; Tucker, Compton; Linthicum, Kenneth J

2015-01-26

The El Niño/Southern Oscillation (ENSO) is a global climate phenomenon that impacts human infectious disease risk worldwide through droughts, floods, and other climate extremes. Throughout summer and fall 2014 and winter 2015, El Niño Watch, issued by the US National Oceanic and Atmospheric Administration, assessed likely El Niño development during the Northern Hemisphere fall and winter, persisting into spring 2015. We identified geographic regions where environmental conditions may increase infectious disease transmission if the predicted El Niño occurs using El Niño indicators (Sea Surface Temperature [SST], Outgoing Longwave Radiation [OLR], and rainfall anomalies) and literature review of El Niño-infectious disease associations. SSTs in the equatorial Pacific and western Indian Oceans were anomalously elevated during August-October 2014, consistent with a developing weak El Niño event. Teleconnections with local climate is evident in global precipitation patterns, with positive OLR anomalies (drier than average conditions) across Indonesia and coastal southeast Asia, and negative anomalies across northern China, the western Indian Ocean, central Asia, north-central and northeast Africa, Mexico/Central America, the southwestern United States, and the northeastern and southwestern tropical Pacific. Persistence of these conditions could produce environmental settings conducive to increased transmission of cholera, dengue, malaria, Rift Valley fever, and other infectious diseases in regional hotspots as during previous El Niño events. The current development of weak El Niño conditions may have significant potential implications for global public health in winter 2014-spring 2015. Enhanced surveillance and other preparedness measures in predicted infectious disease hotspots could mitigate health impacts.

Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model.

PubMed

Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher; Gail, Alexander

2015-04-01

Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement ("jump") consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. Copyright © 2015 the American Physiological Society.

Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model

PubMed Central

Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher

2015-01-01

Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement (“jump”) consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. PMID:25609106

Role of Tropical Atlantic SST Variability as a Modulator of El Nino Teleconnections

NASA Technical Reports Server (NTRS)

Ham, Yoo-Geun; Sung, Mi-Kyung; An, Soon-II; Schubert, Siegfried D.; Kug, Jong-Seong

2014-01-01

The present study suggests that the off-equatorial North Atlantic (NATL) SST warming plays a significant role in modulating El Niño teleconnection and its impact on the North Atlantic and European regions. The El Niño events accompanied by NATL SST warming exhibit south-north dipole pattern over the Western Europe to Atlantic, while the ENSO teleconnection pattern without NATL warming exhibits a Rossby wave-like pattern confined over the North Pacific and western Atlantic. Especially, the El Niño events with NATL warming show positive (negative) geopotential-height anomalies over the North Atlantic (Western Europe) which resemble the negative phase of the NAO. Consistently, it is shown using a simple statistical model that NATL SSTA in addition to the tropical Pacific SSTA leads to better prediction on regional climate variation over the North Atlantic and European regions. This role of NATL SST on ENSO teleconnection is also validated and discussed in a long term simulation of coupled global circulation model (CGCM).

Sampling capacity underlies individual differences in human associative learning.

PubMed

Byrom, Nicola C; Murphy, Robin A

2014-04-01

Though much work has studied how external factors, such as stimulus properties, influence generalization of associative strength, there has been limited exploration of the influence that internal dispositions may contribute to stimulus processing. Here we report 2 studies using a modified negative patterning discrimination to test the relationship between global processing and generalization. Global processing was associated with stronger negative patterning discrimination, indicative of limited generalization between distinct stimulus compounds and their constituent elements. In Experiment 2, participants pretrained to adopt global processing similarly showed strong negative patterning discrimination. These results demonstrate considerable individual difference in capacity to engage in negative patterning discrimination and suggest that the tendency toward global processing may be one factor explaining this variability. The need for models of learning to account for this variability in learning is discussed.

Multi-scale predictions of massive conifer mortality due to chronic temperature rise

NASA Astrophysics Data System (ADS)

McDowell, N. G.; Williams, A. P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, S.; Pangle, R.; Limousin, J.; Plaut, J.; Mackay, D. S.; Ogee, J.; Domec, J. C.; Allen, C. D.; Fisher, R. A.; Jiang, X.; Muss, J. D.; Breshears, D. D.; Rauscher, S. A.; Koven, C.

2016-03-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted >=50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

Multi-scale predictions of massive conifer mortality due to chronic temperature rise

USGS Publications Warehouse

McDowell, Nathan G.; Williams, A.P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, Sanna; Pangle, R.; Limousin, J.; Plaut, J.J.; Mackay, D.S.; Ogee, J.; Domec, Jean-Christophe; Allen, Craig D.; Fisher, Rosie A.; Jiang, X.; Muss, J.D.; Breshears, D.D.; Rauscher, Sara A.; Koven, C.

2016-01-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

Parallel Electric Field on Auroral Magnetic Field Lines.

NASA Astrophysics Data System (ADS)

Yeh, Huey-Ching Betty

1982-03-01

The interaction of Birkeland (magnetic-field-aligned) current carriers and the Earth's magnetic field results in electrostatic potential drops along magnetic field lines. The statistical distributions of the field-aligned potential difference (phi)(,(PARLL)) were determined from the energy spectra of electron inverted "V" events observed at ionospheric altitude for different conditions of geomagnetic activity as indicated by the AE index. Data of 1270 electron inverted "V"'s were obtained from Low-Energy Electron measurements of the Atmosphere Explorer-C and -D Satellite (despun mode) in the interval January 1974-April 1976. In general, (phi)(,(PARLL)) is largest in the dusk to pre-midnight sector, smaller in the post-midnight to dawn sector, and smallest in the near noon sector during quiet and disturbed geomagnetic conditions; there is a steady dusk-dawn-noon asymmetry of the global (phi)(,(PARLL)) distribution. As the geomagnetic activity level increases, the (phi)(,(PARLL)) pattern expands to lower invariant latitudes, and the magnitude of (phi)(,(PARLL)) in the 13-24 magnetic local time sector increases significantly. The spatial structure and intensity variation of the global (phi)(,(PARLL)) distribution are statistically more variable, and the magnitudes of (phi)(,(PARLL)) have smaller correlation with the AE-index, in the post-midnight to dawn sector. A strong correlation is found to exist between upward Birkeland current systems and global parallel potential drops, and between auroral electron precipitation patterns and parallel potential drops, regarding their mophology, their intensity and their dependence of geomagnetic activity. An analysis of the fine-scale simultaneous current-voltage relationship for upward Birkeland currents in Region 1 shows that typical field-aligned potential drops are consistent with model predictions based on linear acceleration of the charge carriers through an electrostatic potential drop along convergent magnetic field lines to maintain current continuity. In a steady state, this model of simple electrostatic acceleration without anomalous resistivity also predicts observable relations between global parallel currents and parallel potential drops and between global energy deposition and parallel potential drops. The temperature, density, and species of the unaccelerated charge carriers are the relevant parameters of the model. The dusk-dawn -noon asymmetry of the global (phi)(,(PARLL)) distribution can be explained by the above steady-state (phi)(,(PARLL)) process if we associate the source regions of upward Birkeland current carriers in Region 1, Region 2, and the cusp region with the plasma sheet boundary layer, the near-Earth plasma sheet, and the magnetosheath, respectively. The results of this study provide observational information on the global distribution of parallel potential drops and the prevailing process of generating and maintaining potential gradients (parallel electric fields) along auroral magnetic field lines.

Climate change and the global pattern of moraine-dammed glacial lake outburst floods

NASA Astrophysics Data System (ADS)

Harrison, Stephan; Kargel, Jeffrey S.; Huggel, Christian; Reynolds, John; Shugar, Dan H.; Betts, Richard A.; Emmer, Adam; Glasser, Neil; Haritashya, Umesh K.; Klimeš, Jan; Reinhardt, Liam; Schaub, Yvonne; Wiltshire, Andy; Regmi, Dhananjay; Vilímek, Vít

2018-04-01

Despite recent research identifying a clear anthropogenic impact on glacier recession, the effect of recent climate change on glacier-related hazards is at present unclear. Here we present the first global spatio-temporal assessment of glacial lake outburst floods (GLOFs) focusing explicitly on lake drainage following moraine dam failure. These floods occur as mountain glaciers recede and downwaste. GLOFs can have an enormous impact on downstream communities and infrastructure. Our assessment of GLOFs associated with the rapid drainage of moraine-dammed lakes provides insights into the historical trends of GLOFs and their distributions under current and future global climate change. We observe a clear global increase in GLOF frequency and their regularity around 1930, which likely represents a lagged response to post-Little Ice Age warming. Notably, we also show that GLOF frequency and regularity - rather unexpectedly - have declined in recent decades even during a time of rapid glacier recession. Although previous studies have suggested that GLOFs will increase in response to climate warming and glacier recession, our global results demonstrate that this has not yet clearly happened. From an assessment of the timing of climate forcing, lag times in glacier recession, lake formation and moraine-dam failure, we predict increased GLOF frequencies during the next decades and into the 22nd century.

Climate Drivers of Spatiotemporal Variability of Precipitation in the Source Region of Yangtze River

NASA Astrophysics Data System (ADS)

Du, Y.; Berndtsson, R.; An, D.; Yuan, F.

2017-12-01

Variability of precipitation regime has significant influence on the environment sustainability in the source region of Yangtze River, especially when the vegetation degradation and biodiversity reduction have already occurred. Understanding the linkage between variability of local precipitation and global teleconnection patterns is essential for water resources management. Based on physical reasoning, indices of the climate drivers can provide a practical way of predicting precipitation. Due to high seasonal variability of precipitation, climate drivers of the seasonal precipitation also varies. However, few reports have gone through the teleconnections between large scale patterns with seasonal precipitation in the source region of Yangtze River. The objectives of this study are therefore (1) assessment of temporal trend and spatial variability of precipitation in the source region of Yangtze River; (2) identification of climate indices with strong influence on seasonal precipitation anomalies; (3) prediction of seasonal precipitation based on revealed climate indices. Principal component analysis and Spearman rank correlation were used to detect significant relationships. A feed-forward artificial neural network(ANN) was developed to predict seasonal precipitation using significant correlated climate indices. Different influencing climate indices were revealed for precipitation in each season, with significant level and lag times. Significant influencing factors were selected to be the predictors for ANN model. With correlation coefficients between observed and simulated precipitation over 0.5, the results were eligible to predict the precipitation of spring, summer and winter using teleconnections, which can improve integrated water resources management in the source region of Yangtze River.

A Global Model for Bankruptcy Prediction

PubMed Central

Alaminos, David; del Castillo, Agustín; Fernández, Manuel Ángel

2016-01-01

The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the common characteristics shared by the affected companies. Nevertheless, few studies focus on the prediction of bankruptcies globally. In order to compensate for this lack of empirical literature, this study has used a methodological framework of logistic regression to construct predictive bankruptcy models for Asia, Europe and America, and other global models for the whole world. The objective is to construct a global model with a high capacity for predicting bankruptcy in any region of the world. The results obtained have allowed us to confirm the superiority of the global model in comparison to regional models over periods of up to three years prior to bankruptcy. PMID:27880810

Recent human history governs global ant invasion dynamics

Treesearch

Cleo Bertelsmeier; Sébastien Ollier; Andrew Liebhold; Laurent Keller

2017-01-01

Human trade and travel are breaking down biogeographic barriers, resulting in shifts in the geographical distribution of organisms, yet it remains largely unknown whether different alien species generally follow similar spatiotemporal colonization patterns and how such patterns are driven by trends in global trade. Here, we analyse the global distribution of 241 alien...

Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

PubMed

Magliocca, Nicholas R; Brown, Daniel G; Ellis, Erle C

2014-01-01

Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.

Development and Evaluation of an Integrated Hydrological Modeling Framework for Monitoring and Understanding Floods and Droughts

NASA Astrophysics Data System (ADS)

Yang, Z. L.; Wu, W. Y.; Lin, P.; Maidment, D. R.

2017-12-01

Extreme water events such as catastrophic floods and severe droughts have increased in recent decades. Mitigating the risk to lives, food security, infrastructure, energy supplies, as well as numerous other industries posed by these extreme events requires informed decision-making and planning based on sound science. We are developing a global water modeling capability by building models that will provide total operational water predictions (evapotranspiration, soil moisture, groundwater, channel flow, inundation, snow) at unprecedented spatial resolutions and updated frequencies. Toward this goal, this talk presents an integrated global hydrological modeling framework that takes advantage of gridded meteorological forcing, land surface modeling, channeled flow modeling, ground observations, and satellite remote sensing. Launched in August 2016, the National Water Model successfully incorporates weather forecasts to predict river flows for more than 2.7 million rivers across the continental United States, which transfers a "synoptic weather map" to a "synoptic river flow map" operationally. In this study, we apply a similar framework to a high-resolution global river network database, which is developed from a hierarchical Dominant River Tracing (DRT) algorithm, and runoff output from the Global Land Data Assimilation System (GLDAS) to a vector-based river routing model (The Routing Application for Parallel Computation of Discharge, RAPID) to produce river flows from 2001 to 2016 using Message Passing Interface (MPI) on Texas Advanced Computer Center's Stampede system. In this simulation, global river discharges for more than 177,000 rivers are computed every 30 minutes. The modeling framework's performance is evaluated with various observations including river flows at more than 400 gauge stations globally. Overall, the model exhibits a reasonably good performance in simulating the averaged patterns of terrestrial water storage, evapotranspiration and runoff. The system is appropriate for monitoring and studying floods and droughts. Directions for future research will be outlined and discussed.

Cross-Site Comparison of Land-Use Decision-Making and Its Consequences across Land Systems with a Generalized Agent-Based Model

PubMed Central

Magliocca, Nicholas R.; Brown, Daniel G.; Ellis, Erle C.

2014-01-01

Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement. PMID:24489696

Combining virtual observatory and equivalent source dipole approaches to describe the geomagnetic field with Swarm measurements

NASA Astrophysics Data System (ADS)

Saturnino, Diana; Langlais, Benoit; Amit, Hagay; Civet, François; Mandea, Mioara; Beucler, Éric

2018-03-01

A detailed description of the main geomagnetic field and of its temporal variations (i.e., the secular variation or SV) is crucial to understanding the geodynamo. Although the SV is known with high accuracy at ground magnetic observatory locations, the globally uneven distribution of the observatories hampers the determination of a detailed global pattern of the SV. Over the past two decades, satellites have provided global surveys of the geomagnetic field which have been used to derive global spherical harmonic (SH) models through some strict data selection schemes to minimise external field contributions. However, discrepancies remain between ground measurements and field predictions by these models; indeed the global models do not reproduce small spatial scales of the field temporal variations. To overcome this problem we propose to directly extract time series of the field and its temporal variation from satellite measurements as it is done at observatory locations. We follow a Virtual Observatory (VO) approach and define a global mesh of VOs at satellite altitude. For each VO and each given time interval we apply an Equivalent Source Dipole (ESD) technique to reduce all measurements to a unique location. Synthetic data are first used to validate the new VO-ESD approach. Then, we apply our scheme to data from the first two years of the Swarm mission. For the first time, a 2.5° resolution global mesh of VO time series is built. The VO-ESD derived time series are locally compared to ground observations as well as to satellite-based model predictions. Our approach is able to describe detailed temporal variations of the field at local scales. The VO-ESD time series are then used to derive global spherical harmonic models. For a simple SH parametrization the model describes well the secular trend of the magnetic field both at satellite altitude and at the surface. As more data will be made available, longer VO-ESD time series can be derived and consequently used to study sharp temporal variation features, such as geomagnetic jerks.

Auditory global-local processing: effects of attention and musical experience.

PubMed

Ouimet, Tia; Foster, Nicholas E V; Hyde, Krista L

2012-10-01

In vision, global (whole) features are typically processed before local (detail) features ("global precedence effect"). However, the distinction between global and local processing is less clear in the auditory domain. The aims of the present study were to investigate: (i) the effects of directed versus divided attention, and (ii) the effect musical training on auditory global-local processing in 16 adult musicians and 16 non-musicians. Participants were presented with short nine-tone melodies, each comprised of three triplet sequences (three-tone units). In a "directed attention" task, participants were asked to focus on either the global or local pitch pattern and had to determine if the pitch pattern went up or down. In a "divided attention" task, participants judged whether the target pattern (up or down) was present or absent. Overall, global structure was perceived faster and more accurately than local structure. The global precedence effect was observed regardless of whether attention was directed to a specific level or divided between levels. Musicians performed more accurately than non-musicians overall, but non-musicians showed a more pronounced global advantage. This study provides evidence for an auditory global precedence effect across attention tasks, and for differences in auditory global-local processing associated with musical experience.

The Not-So-Global Blood Oxygen Level-Dependent Signal.

PubMed

Billings, Jacob; Keilholz, Shella

2018-04-01

Global signal regression is a controversial processing step for resting-state functional magnetic resonance imaging, partly because the source of the global blood oxygen level-dependent (BOLD) signal remains unclear. On the one hand, nuisance factors such as motion can readily introduce coherent BOLD changes across the whole brain. On the other hand, the global signal has been linked to neural activity and vigilance levels, suggesting that it contains important neurophysiological information and should not be discarded. Any widespread pattern of coordinated activity is likely to contribute appreciably to the global signal. Such patterns may include large-scale quasiperiodic spatiotemporal patterns, known also to be tied to performance on vigilance tasks. This uncertainty surrounding the separability of the global BOLD signal from concurrent neurological processes motivated an examination of the global BOLD signal's spatial distribution. The results clarify that although the global signal collects information from all tissue classes, a diverse subset of the BOLD signal's independent components contribute the most to the global signal. Further, the timing of each network's contribution to the global signal is not consistent across volunteers, confirming the independence of a constituent process that comprises the global signal.

How surface functional groups influence fracturation in nanofluids droplets dry-outs

NASA Astrophysics Data System (ADS)

Brutin, David; Carle, Florian

2012-11-01

We report an experimental investigation of the drying of a deposited droplets of nanofluids with different surface functional groups. For identical nano-particles diameter, material and concentration, identical drying conditions, the substrate and the functional groups at the nano-particles surface are changed. Both flow motion, adhesion, gelation and fracturation occur during the evaporation of this complex matter leading to different final typical patterns. The differences in between the patterns are explained based on the surface chemical potential. Crack shapes and wavelengths are globally proportional to the electrical charges carried at the nano- particles surface which is a new parameter to implement in existing predicting models. Presently only the colloid concentration and softness and the deposit thickness are used (Allain and Limat, 1995). The authors gratefully acknowledge the help and the fruitful discussions raised with J.B. Lang.

For how long can we predict the weather? - Insights into atmospheric predictability from global convection-allowing simulations

NASA Astrophysics Data System (ADS)

Judt, Falko

2017-04-01

A tremendous increase in computing power has facilitated the advent of global convection-resolving numerical weather prediction (NWP) models. Although this technological breakthrough allows for the seamless prediction of weather from local to global scales, the predictability of multiscale weather phenomena in these models is not very well known. To address this issue, we conducted a global high-resolution (4-km) predictability experiment using the Model for Prediction Across Scales (MPAS), a state-of-the-art global NWP model developed at the National Center for Atmospheric Research. The goals of this experiment are to investigate error growth from convective to planetary scales and to quantify the intrinsic, scale-dependent predictability limits of atmospheric motions. The globally uniform resolution of 4 km allows for the explicit treatment of organized deep moist convection, alleviating grave limitations of previous predictability studies that either used high-resolution limited-area models or global simulations with coarser grids and cumulus parameterization. Error growth is analyzed within the context of an "identical twin" experiment setup: the error is defined as the difference between a 20-day long "nature run" and a simulation that was perturbed with small-amplitude noise, but is otherwise identical. It is found that in convectively active regions, errors grow by several orders of magnitude within the first 24 h ("super-exponential growth"). The errors then spread to larger scales and begin a phase of exponential growth after 2-3 days when contaminating the baroclinic zones. After 16 days, the globally averaged error saturates—suggesting that the intrinsic limit of atmospheric predictability (in a general sense) is about two weeks, which is in line with earlier estimates. However, error growth rates differ between the tropics and mid-latitudes as well as between the troposphere and stratosphere, highlighting that atmospheric predictability is a complex problem. The comparatively slower error growth in the tropics and in the stratosphere indicates that certain weather phenomena could potentially have longer predictability than currently thought.

Study of Regional Downscaled Climate and Air Quality in the United States

NASA Astrophysics Data System (ADS)

Gao, Y.; Fu, J. S.; Drake, J.; Lamarque, J.; Lam, Y.; Huang, K.

2011-12-01

Due to the increasing anthropogenic greenhouse gas emissions, the global and regional climate patterns have significantly changed. Climate change has exerted strong impact on ecosystem, air quality and human life. The global model Community Earth System Model (CESM v1.0) was used to predict future climate and chemistry under projected emission scenarios. Two new emission scenarios, Representative Community Pathways (RCP) 4.5 and RCP 8.5, were used in this study for climate and chemistry simulations. The projected global mean temperature will increase 1.2 and 1.7 degree Celcius for the RCP 4.5 and RCP 8.5 scenarios in 2050s, respectively. In order to take advantage of local detailed topography, land use data and conduct local climate impact on air quality, we downscaled CESM outputs to 4 km by 4 km Eastern US domain using Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality modeling system (CMAQ). The evaluations between regional model outputs and global model outputs, regional model outputs and observational data were conducted to verify the downscaled methodology. Future climate change and air quality impact were also examined on a 4 km by 4 km high resolution scale.

Determining the effect of key climate drivers on global hydropower production

NASA Astrophysics Data System (ADS)

Galelli, S.; Ng, J. Y.; Lee, D.; Block, P. J.

2017-12-01

Accounting for about 17% of total global electrical power production, hydropower is arguably the world's main renewable energy source and a key asset to meet Paris climate agreements. A key component of hydropower production is water availability, which depends on both precipitation and multiple drivers of climate variability acting at different spatial and temporal scales. To understand how these drivers impact global hydropower production, we study the relation between four patterns of ocean-atmosphere climate variability (i.e., El Niño Southern Oscillation, Pacific Decadal Oscillation, North Atlantic Oscillation, and Atlantic Multidecadal Oscillation) and monthly time series of electrical power production for over 1,500 hydropower reservoirs—obtained via simulation with a high-fidelity dam model forced with 20th century climate conditions. Notably significant relationships between electrical power productions and climate variability are found in many climate sensitive regions globally, including North and South America, East Asia, West Africa, and Europe. Coupled interactions from multiple, simultaneous climate drivers are also evaluated. Finally, we highlight the importance of using these climate drivers as an additional source of information within reservoir operating rules where the skillful predictability of inflow exists.

Defining pyromes and global syndromes of fire regimes.

PubMed

Archibald, Sally; Lehmann, Caroline E R; Gómez-Dans, Jose L; Bradstock, Ross A

2013-04-16

Fire is a ubiquitous component of the Earth system that is poorly understood. To date, a global-scale understanding of fire is largely limited to the annual extent of burning as detected by satellites. This is problematic because fire is multidimensional, and focus on a single metric belies its complexity and importance within the Earth system. To address this, we identified five key characteristics of fire regimes--size, frequency, intensity, season, and extent--and combined new and existing global datasets to represent each. We assessed how these global fire regime characteristics are related to patterns of climate, vegetation (biomes), and human activity. Cross-correlations demonstrate that only certain combinations of fire characteristics are possible, reflecting fundamental constraints in the types of fire regimes that can exist. A Bayesian clustering algorithm identified five global syndromes of fire regimes, or pyromes. Four pyromes represent distinctions between crown, litter, and grass-fueled fires, and the relationship of these to biomes and climate are not deterministic. Pyromes were partially discriminated on the basis of available moisture and rainfall seasonality. Human impacts also affected pyromes and are globally apparent as the driver of a fifth and unique pyrome that represents human-engineered modifications to fire characteristics. Differing biomes and climates may be represented within the same pyrome, implying that pathways of change in future fire regimes in response to changes in climate and human activity may be difficult to predict.

Defining pyromes and global syndromes of fire regimes

PubMed Central

Archibald, Sally; Lehmann, Caroline E. R.; Gómez-Dans, Jose L.; Bradstock, Ross A.

2013-01-01

Fire is a ubiquitous component of the Earth system that is poorly understood. To date, a global-scale understanding of fire is largely limited to the annual extent of burning as detected by satellites. This is problematic because fire is multidimensional, and focus on a single metric belies its complexity and importance within the Earth system. To address this, we identified five key characteristics of fire regimes—size, frequency, intensity, season, and extent—and combined new and existing global datasets to represent each. We assessed how these global fire regime characteristics are related to patterns of climate, vegetation (biomes), and human activity. Cross-correlations demonstrate that only certain combinations of fire characteristics are possible, reflecting fundamental constraints in the types of fire regimes that can exist. A Bayesian clustering algorithm identified five global syndromes of fire regimes, or pyromes. Four pyromes represent distinctions between crown, litter, and grass-fueled fires, and the relationship of these to biomes and climate are not deterministic. Pyromes were partially discriminated on the basis of available moisture and rainfall seasonality. Human impacts also affected pyromes and are globally apparent as the driver of a fifth and unique pyrome that represents human-engineered modifications to fire characteristics. Differing biomes and climates may be represented within the same pyrome, implying that pathways of change in future fire regimes in response to changes in climate and human activity may be difficult to predict. PMID:23559374

Globally Increased Crop Growth and Cropping Intensity from the Long-Term Satellite-Based Observations

NASA Astrophysics Data System (ADS)

Chen, Bin

2018-04-01

Understanding the spatiotemporal change trend of global crop growth and multiple cropping system under climate change scenarios is a critical requirement for supporting the food security issue that maintains the function of human society. Many studies have predicted the effects of climate changes on crop production using a combination of filed studies and models, but there has been limited evidence relating decadal-scale climate change to global crop growth and the spatiotemporal distribution of multiple cropping system. Using long-term satellite-derived Normalized Difference Vegetation Index (NDVI) and observed climate data from 1982 to 2012, we investigated the crop growth trend, spatiotemporal pattern trend of agricultural cropping intensity, and their potential correlations with respect to the climate change drivers at a global scale. Results show that 82.97 % of global cropland maximum NDVI witnesses an increased trend while 17.03 % of that shows a decreased trend over the past three decades. The spatial distribution of multiple cropping system is observed to expand from lower latitude to higher latitude, and the increased cropping intensity is also witnessed globally. In terms of regional major crop zones, results show that all nine selected zones have an obvious upward trend of crop maximum NDVI (p < 0.001), and as for climatic drivers, the gradual temperature and precipitation changes have had a measurable impact on the crop growth trend.

Predicting North American Scolytinae invasions in the Southern Hemisphere.

PubMed

Lantschner, Maria Victoria; Atkinson, Thomas H; Corley, Juan C; Liebhold, Andrew M

2017-01-01

Scolytinae species are recognized as one of the most important tree mortality agents in coniferous forests worldwide, and many are known invaders because they are easily transported in wood products. Nonnative trees planted in novel habitats often exhibit exceptional growth, in part because they escape herbivore (such as Scolytinae) pressure from their native range. Increasing accidental introductions of forest pest species as a consequence of international trade, however, is expected to diminish enemy release of nonnative forest trees. In this context, there is need to characterize patterns of forest herbivore species invasion risks at global scales. In this study, we analyze the establishment potential of 64 North American Scolytinae species in the Southern Hemisphere. We use climate-based ecological niche models (MaxEnt) to spatially define the potential distribution of these Scolytinae species in regions of the Southern Hemisphere were pines are planted. Our model predicts that all of the pine-growing regions of the Southern Hemisphere are capable of supporting some species of North American Scolytinae, but there are certain "hotspot" regions, southeastern Argentina, Bolivia, Chile, Peru and southwestern Australia, that appear to be suitable for a particularly large number of species. The species with the highest predicted risk of establishment were Dendroctonus valens, Xyleborus intrusus, Hylastes tenuis, Ips grandicollis, Gnathotrichus sulcatus, and Ips calligraphus. Given that global commerce is anticipated to continue to increase, we can expect that more Scolytinae species will continue to establish outside their range. Our results provide information useful for identifying a global list of potential invasive species in pine plantations, and may assist in the design of comprehensive strategies aimed at reducing pest establishment in Southern Hemisphere forest plantations. © 2016 by the Ecological Society of America.

Biophysical and Economic Uncertainty in the Analysis of Poverty Impacts of Climate Change

NASA Astrophysics Data System (ADS)

Hertel, T. W.; Lobell, D. B.; Verma, M.

2011-12-01

This paper seeks to understand the main sources of uncertainty in assessing the impacts of climate change on agricultural output, international trade, and poverty. We incorporate biophysical uncertainty by sampling from a distribution of global climate model predictions for temperature and precipitation for 2050. The implications of these realizations for crop yields around the globe are estimated using the recently published statistical crop yield functions provided by Lobell, Schlenker and Costa-Roberts (2011). By comparing these yields to those predicted under current climate, we obtain the likely change in crop yields owing to climate change. The economic uncertainty in our analysis relates to the response of the global economic system to these biophysical shocks. We use a modified version of the GTAP model to elicit the impact of the biophysical shocks on global patterns of production, consumption, trade and poverty. Uncertainty in these responses is reflected in the econometrically estimated parameters governing the responsiveness of international trade, consumption, production (and hence the intensive margin of supply response), and factor supplies (which govern the extensive margin of supply response). We sample from the distributions of these parameters as specified by Hertel et al. (2007) and Keeney and Hertel (2009). We find that, even though it is difficult to predict where in the world agricultural crops will be favorably affected by climate change, the responses of economic variables, including output and exports can be far more robust (Table 1). This is due to the fact that supply and demand decisions depend on relative prices, and relative prices depend on productivity changes relative to other crops in a given region, or relative to similar crops in other parts of the world. We also find that uncertainty in poverty impacts of climate change appears to be almost entirely driven by biophysical uncertainty.

Estimating large carnivore populations at global scale based on spatial predictions of density and distribution – Application to the jaguar (Panthera onca)

PubMed Central

Robinson, Hugh S.; Abarca, Maria; Zeller, Katherine A.; Velasquez, Grisel; Paemelaere, Evi A. D.; Goldberg, Joshua F.; Payan, Esteban; Hoogesteijn, Rafael; Boede, Ernesto O.; Schmidt, Krzysztof; Lampo, Margarita; Viloria, Ángel L.; Carreño, Rafael; Robinson, Nathaniel; Lukacs, Paul M.; Nowak, J. Joshua; Salom-Pérez, Roberto; Castañeda, Franklin; Boron, Valeria; Quigley, Howard

2018-01-01

Broad scale population estimates of declining species are desired for conservation efforts. However, for many secretive species including large carnivores, such estimates are often difficult. Based on published density estimates obtained through camera trapping, presence/absence data, and globally available predictive variables derived from satellite imagery, we modelled density and occurrence of a large carnivore, the jaguar, across the species’ entire range. We then combined these models in a hierarchical framework to estimate the total population. Our models indicate that potential jaguar density is best predicted by measures of primary productivity, with the highest densities in the most productive tropical habitats and a clear declining gradient with distance from the equator. Jaguar distribution, in contrast, is determined by the combined effects of human impacts and environmental factors: probability of jaguar occurrence increased with forest cover, mean temperature, and annual precipitation and declined with increases in human foot print index and human density. Probability of occurrence was also significantly higher for protected areas than outside of them. We estimated the world’s jaguar population at 173,000 (95% CI: 138,000–208,000) individuals, mostly concentrated in the Amazon Basin; elsewhere, populations tend to be small and fragmented. The high number of jaguars results from the large total area still occupied (almost 9 million km2) and low human densities (< 1 person/km2) coinciding with high primary productivity in the core area of jaguar range. Our results show the importance of protected areas for jaguar persistence. We conclude that combining modelling of density and distribution can reveal ecological patterns and processes at global scales, can provide robust estimates for use in species assessments, and can guide broad-scale conservation actions. PMID:29579129

Methane dynamics regulated by microbial community response to permafrost thaw.

PubMed

McCalley, Carmody K; Woodcroft, Ben J; Hodgkins, Suzanne B; Wehr, Richard A; Kim, Eun-Hae; Mondav, Rhiannon; Crill, Patrick M; Chanton, Jeffrey P; Rich, Virginia I; Tyson, Gene W; Saleska, Scott R

2014-10-23

Permafrost contains about 50% of the global soil carbon. It is thought that the thawing of permafrost can lead to a loss of soil carbon in the form of methane and carbon dioxide emissions. The magnitude of the resulting positive climate feedback of such greenhouse gas emissions is still unknown and may to a large extent depend on the poorly understood role of microbial community composition in regulating the metabolic processes that drive such ecosystem-scale greenhouse gas fluxes. Here we show that changes in vegetation and increasing methane emissions with permafrost thaw are associated with a switch from hydrogenotrophic to partly acetoclastic methanogenesis, resulting in a large shift in the δ(13)C signature (10-15‰) of emitted methane. We used a natural landscape gradient of permafrost thaw in northern Sweden as a model to investigate the role of microbial communities in regulating methane cycling, and to test whether a knowledge of community dynamics could improve predictions of carbon emissions under loss of permafrost. Abundance of the methanogen Candidatus 'Methanoflorens stordalenmirensis' is a key predictor of the shifts in methane isotopes, which in turn predicts the proportions of carbon emitted as methane and as carbon dioxide, an important factor for simulating the climate feedback associated with permafrost thaw in global models. By showing that the abundance of key microbial lineages can be used to predict atmospherically relevant patterns in methane isotopes and the proportion of carbon metabolized to methane during permafrost thaw, we establish a basis for scaling changing microbial communities to ecosystem isotope dynamics. Our findings indicate that microbial ecology may be important in ecosystem-scale responses to global change.

Multi-scale predictions of coniferous forest mortality in the northern hemisphere

NASA Astrophysics Data System (ADS)

McDowell, N. G.

2015-12-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our incomplete understanding of the fundamental physiological thresholds of vegetation mortality during drought limits our ability to accurately simulate future vegetation distributions and associated climate feedbacks. Here we integrate experimental evidence with models to show potential widespread loss of needleleaf evergreen trees (NET; ~ conifers) within the Southwest USA by 2100; with rising temperature being the primary cause of mortality. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ypd) thresholds (April-August mean) beyond which photosynthesis, stomatal and hydraulic conductance, and carbohydrate availability approached zero. Empirical and mechanistic models accurately predicted NET Ypd, and 91% of predictions (10/11) exceeded mortality thresholds within the 21st century due to temperature rise. Completely independent global models predicted >50% loss of northern hemisphere NET by 2100, consistent with the findings for Southwest USA. The global models disagreed with the ecosystem process models in regards to future mortality in Southwest USA, however, highlighting the potential underestimates of future NET mortality as simulated by the global models and signifying the importance of improving regional predictions. Taken together, these results from the validated regional predictions and the global simulations predict global-scale conifer loss in coming decades under projected global warming.

Think globally, act locally: the role of local demographics and vaccination coverage in the dynamic response of measles infection to control.

PubMed

Ferrari, M J; Grenfell, B T; Strebel, P M

2013-08-05

The global reduction of the burden of morbidity and mortality owing to measles has been a major triumph of public health. However, the continued persistence of measles infection probably not only reflects local variation in progress towards vaccination target goals, but may also reflect local variation in dynamic processes of transmission, susceptible replenishment through births and stochastic local extinction. Dynamic models predict that vaccination should increase the mean age of infection and increase inter-annual variability in incidence. Through a comparative approach, we assess national-level patterns in the mean age of infection and measles persistence. We find that while the classic predictions do hold in general, the impact of vaccination on the age distribution of cases and stochastic fadeout are mediated by local birth rate. Thus, broad-scale vaccine coverage goals are unlikely to have the same impact on the interruption of measles transmission in all demographic settings. Indeed, these results suggest that the achievement of further measles reduction or elimination goals is likely to require programmatic and vaccine coverage goals that are tailored to local demographic conditions.

Global Network of Slow Solar Wind

NASA Technical Reports Server (NTRS)

Crooker, N. U.; Antiochos, S. K.; Zhao, X.; Neugebauer, M.

2012-01-01

The streamer belt region surrounding the heliospheric current sheet (HCS) is generally treated as the primary or sole source of the slow solar wind. Synoptic maps of solar wind speed predicted by the Wang-Sheeley-Arge model during selected periods of solar cycle 23, however, show many areas of slow wind displaced from the streamer belt. These areas commonly have the form of an arc that is connected to the streamer belt at both ends. The arcs mark the boundaries between fields emanating from different coronal holes of the same polarity and thus trace the paths of belts of pseudostreamers, i.e., unipolar streamers that form over double arcades and lack current sheets. The arc pattern is consistent with the predicted topological mapping of the narrow open corridor or singular separator line that must connect the holes and, thus, consistent with the separatrix-web model of the slow solar wind. Near solar maximum, pseudostreamer belts stray far from the HCS-associated streamer belt and, together with it, form a global-wide web of slow wind. Recognition of pseudostreamer belts as prominent sources of slow wind provides a new template for understanding solar wind stream structure, especially near solar maximum.

An Assessment of the Potential Predictability of Drought Over the United States Based on Climate Model Simulations with Specified SST

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Wang, Hailan; Suarez, Max; Koster, Randal

2010-01-01

The USCLIV AR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. The runs were done with several global atmospheric models including NASA/NSIPP-l, NCEP/GFS, GFDLlAM2, and NCAR CCM3 and CAM3.5. Specific questions that the runs are designed to address include: What are mechanisms that maintain drought across the seasonal cycle and from one year to the next. To what extent can droughts develop independently of ocean variability due to year-to-year memory that may be inherent to the land. What is the role of the different ocean basins? Here we focus on the potential predictability of drought conditions over the United States. Specific issues addressed include the seasonality and regionality of the signal-to-noise ratios associated with Pacific and Atlantic SST forcing, and the sensitivity of the results to the climatological stationary waves simulated by the different AGCMs.

Atmospheric River Characteristics under Decadal Climate Variability

NASA Astrophysics Data System (ADS)

Done, J.; Ge, M.

2017-12-01

How does decadal climate variability change the nature and predictability of atmospheric river events? Decadal swings in atmospheric river frequency, or shifts in the proportion of precipitation falling as rain, could challenge current water resource and flood risk management practice. Physical multi-scale processes operating between Pacific sea surface temperatures (SSTs) and atmospheric rivers over the Western U.S. are explored using the global Model for Prediction Across Scales (MPAS). A 45km global mesh is refined over the Western U.S. to 12km to capture the major terrain effects on precipitation. The performance of the MPAS is first evaluated for a case study atmospheric river event over California. Atmospheric river characteristics are then compared in a pair of idealized simulations, each driven by Pacific SST patterns characteristic of opposite phases of the Interdecadal Pacific Oscillation (IPO). Given recent evidence that we have entered a positive phase of the IPO, implications for current reservoir management practice over the next decade will be discussed. This work contributes to the NSF-funded project UDECIDE (Understanding Decision-Climate Interactions on Decadal Scales). UDECIDE brings together practitioners, engineers, statisticians, and climate scientists to understand the role of decadal climate information for water management and decisions.

Native bees buffer the negative impact of climate warming on honey bee pollination of watermelon crops.

PubMed

Rader, Romina; Reilly, James; Bartomeus, Ignasi; Winfree, Rachael

2013-10-01

If climate change affects pollinator-dependent crop production, this will have important implications for global food security because insect pollinators contribute to production for 75% of the leading global food crops. We investigate whether climate warming could result in indirect impacts upon crop pollination services via an overlooked mechanism, namely temperature-induced shifts in the diurnal activity patterns of pollinators. Using a large data set on bee pollination of watermelon crops, we predict how pollination services might change under various climate change scenarios. Our results show that under the most extreme IPCC scenario (A1F1), pollination services by managed honey bees are expected to decline by 14.5%, whereas pollination services provided by most native, wild taxa are predicted to increase, resulting in an estimated aggregate change in pollination services of +4.5% by 2099. We demonstrate the importance of native biodiversity in buffering the impacts of climate change, because crop pollination services would decline more steeply without the native, wild pollinators. More generally, our study provides an important example of how biodiversity can stabilize ecosystem services against environmental change. © 2013 John Wiley & Sons Ltd.

Indirect downscaling of global circulation model data based on atmospheric circulation and temperature for projections of future precipitation in hourly resolution

NASA Astrophysics Data System (ADS)

Beck, F.; Bárdossy, A.

2013-07-01

Many hydraulic applications like the design of urban sewage systems require projections of future precipitation in high temporal resolution. We developed a method to predict the regional distribution of hourly precipitation sums based on daily mean sea level pressure and temperature data from a Global Circulation Model. It is an indirect downscaling method avoiding uncertain precipitation data from the model. It is based on a fuzzy-logic classification of atmospheric circulation patterns (CPs) that is further subdivided by means of the average daily temperature. The observed empirical distributions at 30 rain gauges to each CP-temperature class are assumed as constant and used for projections of the hourly precipitation sums in the future. The method was applied to the CP-temperature sequence derived from the 20th century run and the scenario A1B run of ECHAM5. According to ECHAM5, the summers in southwest Germany will become progressively drier. Nevertheless, the frequency of the highest hourly precipitation sums will increase. According to the predictions, estival water stress and the risk of extreme hourly precipitation will both increase simultaneously during the next decades.

Predicting Tree Mortality Die-off Events Associated with Hotter Drought and Assessing Their Global Consequences via Ecoclimate Teleconnections.

NASA Astrophysics Data System (ADS)

Breshears, D. D.; Allen, C. D.; McDowell, N. G.; Adams, H. D.; Barnes, M.; Barron-Gafford, G.; Bradford, J. B.; Cobb, N.; Field, J. P.; Froend, R.; Fontaine, J. B.; Garcia, E.; Hardy, G. E. S. J.; Huxman, T. E.; Kala, J.; Lague, M. M.; Martinez-Yrizar, A.; Matusick, G.; Minor, D. M.; Moore, D. J.; Ng, M.; Ruthrof, K. X.; Saleska, S. R.; Stark, S. C.; Swann, A. L. S.; Villegas, J. C.; Williams, A. P.; Zou, C.

2017-12-01

Evidence that tree mortality is increasingly likely occur in extensive die-off events across the terrestrial biosphere continues to mount. The consequences of such extensive mortality events are potentially profound, not only for the locations where die-off events occur, but also for other locations that could be impacted via ecoclimate teleconnections, whereby the land surface changes associated with die-off in one location could alter atmospheric circulation patterns and affect vegetation elsewhere. Here, we (1) recap the background of tree mortality as an emerging environmental issue, (2) highlight recent advances that could help us improve predictions of the vulnerability to tree mortality, including the underlying importance of hydraulic failure, the potential to develop climatic envelopes specific to tree mortality events, and consideration of the role of heat waves; and (3) initial bounding simulations that indicate the potential for tree die-off events in different locations to alter ecoclimate teleconnections. As we move toward globally coordinated carbon accounting and management, the high vulnerability to tree die-off events and the potential for such events to affect vegetation elsewhere will both need to be accounted for.

Structuring evolution: biochemical networks and metabolic diversification in birds.

PubMed

Morrison, Erin S; Badyaev, Alexander V

2016-08-25

Recurrence and predictability of evolution are thought to reflect the correspondence between genomic and phenotypic dimensions of organisms, and the connectivity in deterministic networks within these dimensions. Direct examination of the correspondence between opportunities for diversification imbedded in such networks and realized diversity is illuminating, but is empirically challenging because both the deterministic networks and phenotypic diversity are modified in the course of evolution. Here we overcome this problem by directly comparing the structure of a "global" carotenoid network - comprising of all known enzymatic reactions among naturally occurring carotenoids - with the patterns of evolutionary diversification in carotenoid-producing metabolic networks utilized by birds. We found that phenotypic diversification in carotenoid networks across 250 species was closely associated with enzymatic connectivity of the underlying biochemical network - compounds with greater connectivity occurred the most frequently across species and were the hotspots of metabolic pathway diversification. In contrast, we found no evidence for diversification along the metabolic pathways, corroborating findings that the utilization of the global carotenoid network was not strongly influenced by history in avian evolution. The finding that the diversification in species-specific carotenoid networks is qualitatively predictable from the connectivity of the underlying enzymatic network points to significant structural determinism in phenotypic evolution.

An open-access CMIP5 pattern library for temperature and precipitation: description and methodology

NASA Astrophysics Data System (ADS)

Lynch, Cary; Hartin, Corinne; Bond-Lamberty, Ben; Kravitz, Ben

2017-05-01

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squares regression methods. We explore the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90° N/S). Bias and mean errors between modeled and pattern-predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5 °C, but the choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. This paper describes our library of least squares regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns. The dataset and netCDF data generation code are available at doi:10.5281/zenodo.495632.

Sampling Capacity Underlies Individual Differences in Human Associative Learning

PubMed Central

2014-01-01

Though much work has studied how external factors, such as stimulus properties, influence generalization of associative strength, there has been limited exploration of the influence that internal dispositions may contribute to stimulus processing. Here we report 2 studies using a modified negative patterning discrimination to test the relationship between global processing and generalization. Global processing was associated with stronger negative patterning discrimination, indicative of limited generalization between distinct stimulus compounds and their constituent elements. In Experiment 2, participants pretrained to adopt global processing similarly showed strong negative patterning discrimination. These results demonstrate considerable individual difference in capacity to engage in negative patterning discrimination and suggest that the tendency toward global processing may be one factor explaining this variability. The need for models of learning to account for this variability in learning is discussed. PMID:24446699

Global circulation patterns of seasonal influenza viruses vary with antigenic drift

PubMed Central

Bedford, Trevor; Riley, Steven; Barr, Ian G.; Broor, Shobha; Chadha, Mandeep; Cox, Nancy J.; Daniels, Rodney S.; Gunasekaran, C. Palani; Hurt, Aeron C.; Kelso, Anne; Lewis, Nicola S.; Li, Xiyan; McCauley, John W.; Odagiri, Takato; Potdar, Varsha; Rambaut, Andrew; Shu, Yuelong; Skepner, Eugene; Smith, Derek J.; Suchard, Marc A.; Tashiro, Masato; Wang, Dayan; Xu, Xiyan; Lemey, Philippe; Russell, Colin A.

2015-01-01

Understanding the spatio-temporal patterns of emergence and circulation of new human seasonal influenza virus variants is a key scientific and public health challenge. The global circulation patterns of influenza A/H3N2 viruses are well-characterized1-7 but the patterns of A/H1N1 and B viruses have remained largely unexplored. Here, based on analyses of 9,604 hemagglutinin sequences of human seasonal influenza viruses from 2000–2012, we show that the global circulation patterns of A/H1N1 (up to 2009), B/Victoria, and B/Yamagata viruses differ substantially from those of A/H3N2 viruses. While genetic variants of A/H3N2 viruses did not persist locally between epidemics and were reseeded from East and Southeast (E-SE) Asia, genetic variants of A/H1N1 and B viruses persisted across multiple seasons and exhibited complex global dynamics with E-SE Asia playing a limited role in disseminating new variants. The less frequent global movement of influenza A/H1N1 and B viruses coincided with slower rates of antigenic evolution, lower ages of infection, and smaller less frequent epidemics compared to A/H3N2 viruses. Detailed epidemic models support differences in age of infection, combined with the less frequent travel of children, as likely drivers of the differences in the patterns of global circulation, suggesting a complex interaction between virus evolution, epidemiology and human behavior. PMID:26053121

Global circulation patterns of seasonal influenza viruses vary with antigenic drift

NASA Astrophysics Data System (ADS)

Bedford, Trevor; Riley, Steven; Barr, Ian G.; Broor, Shobha; Chadha, Mandeep; Cox, Nancy J.; Daniels, Rodney S.; Gunasekaran, C. Palani; Hurt, Aeron C.; Kelso, Anne; Klimov, Alexander; Lewis, Nicola S.; Li, Xiyan; McCauley, John W.; Odagiri, Takato; Potdar, Varsha; Rambaut, Andrew; Shu, Yuelong; Skepner, Eugene; Smith, Derek J.; Suchard, Marc A.; Tashiro, Masato; Wang, Dayan; Xu, Xiyan; Lemey, Philippe; Russell, Colin A.

2015-07-01

Understanding the spatiotemporal patterns of emergence and circulation of new human seasonal influenza virus variants is a key scientific and public health challenge. The global circulation patterns of influenza A/H3N2 viruses are well characterized, but the patterns of A/H1N1 and B viruses have remained largely unexplored. Here we show that the global circulation patterns of A/H1N1 (up to 2009), B/Victoria, and B/Yamagata viruses differ substantially from those of A/H3N2 viruses, on the basis of analyses of 9,604 haemagglutinin sequences of human seasonal influenza viruses from 2000 to 2012. Whereas genetic variants of A/H3N2 viruses did not persist locally between epidemics and were reseeded from East and Southeast Asia, genetic variants of A/H1N1 and B viruses persisted across several seasons and exhibited complex global dynamics with East and Southeast Asia playing a limited role in disseminating new variants. The less frequent global movement of influenza A/H1N1 and B viruses coincided with slower rates of antigenic evolution, lower ages of infection, and smaller, less frequent epidemics compared to A/H3N2 viruses. Detailed epidemic models support differences in age of infection, combined with the less frequent travel of children, as probable drivers of the differences in the patterns of global circulation, suggesting a complex interaction between virus evolution, epidemiology, and human behaviour.

Integrating metabolic performance, thermal tolerance, and plasticity enables for more accurate predictions on species vulnerability to acute and chronic effects of global warming.

PubMed

Magozzi, Sarah; Calosi, Piero

2015-01-01

Predicting species vulnerability to global warming requires a comprehensive, mechanistic understanding of sublethal and lethal thermal tolerances. To date, however, most studies investigating species physiological responses to increasing temperature have focused on the underlying physiological traits of either acute or chronic tolerance in isolation. Here we propose an integrative, synthetic approach including the investigation of multiple physiological traits (metabolic performance and thermal tolerance), and their plasticity, to provide more accurate and balanced predictions on species and assemblage vulnerability to both acute and chronic effects of global warming. We applied this approach to more accurately elucidate relative species vulnerability to warming within an assemblage of six caridean prawns occurring in the same geographic, hence macroclimatic, region, but living in different thermal habitats. Prawns were exposed to four incubation temperatures (10, 15, 20 and 25 °C) for 7 days, their metabolic rates and upper thermal limits were measured, and plasticity was calculated according to the concept of Reaction Norms, as well as Q10 for metabolism. Compared to species occupying narrower/more stable thermal niches, species inhabiting broader/more variable thermal environments (including the invasive Palaemon macrodactylus) are likely to be less vulnerable to extreme acute thermal events as a result of their higher upper thermal limits. Nevertheless, they may be at greater risk from chronic exposure to warming due to the greater metabolic costs they incur. Indeed, a trade-off between acute and chronic tolerance was apparent in the assemblage investigated. However, the invasive species P. macrodactylus represents an exception to this pattern, showing elevated thermal limits and plasticity of these limits, as well as a high metabolic control. In general, integrating multiple proxies for species physiological acute and chronic responses to increasing temperature helps providing more accurate predictions on species vulnerability to warming. © 2014 John Wiley & Sons Ltd.

Global Patterns of Tectonism on Titan from Mountain Chains and Virgae

NASA Technical Reports Server (NTRS)

Cook, C.; Barnes, J. W.; Radebaugh, J.; Hurford, T.; Ktatenhorn, S. A.

2012-01-01

This research is based on the exploration of tectonic patterns on Titan from a global perspective. Several moons in the outer solar system display patterns of surface tectonic features that imply global stress fields driven or modified by global forces. Patterns such as these are seen in Europa's tidally induced fracture patterns, Enceladus's tiger stripes, and Ganymede's global expansion induced normal fault bands. Given its proximity to Saturn, as well as its eccentric orbit, tectonic features and global stresses may be present on Titan as well. Titan displays possible tectonic structures, such as mountain chains along its equator (Radebaugh et al. 2007), as well as the unexplored dark linear streaks termed virgae by the IAU. Imaged by Cassini with the RADAR instrument, mountain chains near the equator are observed with a predominante east-west orientation (Liu et al. 2012, Mitri et al. 2010). Orientations such as these can be explained by modifications in the global tidal stress field induced by global contraction followed by rotational spin-up. Also, due to Titan's eccentric orbit, its current rotation rate may be in an equilibrium between tidal spin-up near periapsis and spin-down near apoapsis (Barnes and Fortney 2003). Additional stress from rotational spin-up provides an asymmetry to the stress field. This, combined with an isotropic stress from radial contraction, favors the formation of equatorial mountain chains in an east-west direction. The virgae, which have been imaged by Cassini with both the Visual and Infrared Mapping Spectrometer (VIMS) and Imaging Science Subsystem (ISS) instruments, are located predominately near 30 degrees latitude in either hemisphere. Oriented with a pronounced elongation in the east-west direction, all observed virgae display similar characteristics: similar relative albedos as the surrounding terrain however darkened with an apparent neutral absorber, broken-linear or rounded sharp edges, and connected, angular elements with distinct, linear edges. Virgae imaged during northern latitude passes are oriented with their long dimensions toward Titan's antiSaturn point. If the virgae are of tectonic origin, for instance if the turn out to be i.e. grabens, they could serve as markers to Titan's global stress field. Using them in this way allows for a mapping of global tectonic patterns. These patterns will be tested for consistency against the various sources of global stress and orientations of mountain chains. By determining what drives Titan's tectonics globally, we will be able to place Titan within the context of the other outer planet icy satellites.

Spontaneous Periodic Delamination of Thin Films To Form Crack-Free Metal and Silicon Ribbons with High Stretchability.

PubMed

Zhang, Qiuting; Tang, Yichao; Hajfathalian, Maryam; Chen, Chunxu; Turner, Kevin T; Dikin, Dmitriy A; Lin, Gaojian; Yin, Jie

2017-12-27

Design of electronic materials with high stretchability is of great importance for realizing soft and conformal electronics. One strategy of realizing stretchable metals and semiconductors is to exploit the buckling of materials bonded to elastomers. However, the level of stretchability is often limited by the cracking and fragmentation of the materials that occurs when constrained buckling occurs while bonded to the substrate. Here, we exploit a failure mechanism, spontaneous buckling-driven periodic delamination, to achieve high stretchability in metal and silicon films that are deposited on prestrained elastomer substrates. We find that both globally periodic buckle-delaminated pattern and ordered cracking patterns over large areas are observed in the spontaneously buckle-delaminated thin films. The geometry of periodic delaminated buckles and cracking periodicity can be predicted by theoretical models. By patterning the films into ribbons with widths smaller than the predicted cracking periodicity, we demonstrate the design of crack-free and spontaneous delaminated ribbons on highly prestrained elastomer substrates, which provides a high stretchability of about 120% and 400% in Si and Au ribbons, respectively. We find that the high stretchability is mainly attributed to the largely relaxed strain in the ribbons via spontaneous buckling-driven delamination, as made evident by the small maximum tensile strain in both ribbons, which is measured to be over 100 times smaller than that of the substrate prestrain.

Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data

DOE PAGES

Zhu, Lei; Gonder, Jeffrey; Lin, Lei

2017-08-16

With the development of and advances in smartphones and global positioning system (GPS) devices, travelers’ long-term travel behaviors are not impossible to obtain. This study investigates the pattern of individual travel behavior and its correlation with social-demographic features. For different social-demographic groups (e.g., full-time employees and students), the individual travel behavior may have specific temporal-spatial-mobile constraints. The study first extracts the home-based tours, including Home-to-Home and Home-to-Non-Home, from long-term raw GPS data. The travel behavior pattern is then delineated by home-based tour features, such as departure time, destination location entropy, travel time, and driving time ratio. The travel behavior variabilitymore » describes the variances of travelers’ activity behavior features for an extended period. After that, the variability pattern of an individual’s travel behavior is used for estimating the individual’s social-demographic information, such as social-demographic role, by a supervised learning approach, support vector machine. In this study, a long-term (18-month) recorded GPS data set from Puget Sound Regional Council is used. The experiment’s result is very promising. In conclusion, the sensitivity analysis shows that as the number of tours thresholds increases, the variability of most travel behavior features converges, while the prediction performance may not change for the fixed test data.« less

Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Gonder, Jeffrey; Lin, Lei

With the development of and advances in smartphones and global positioning system (GPS) devices, travelers’ long-term travel behaviors are not impossible to obtain. This study investigates the pattern of individual travel behavior and its correlation with social-demographic features. For different social-demographic groups (e.g., full-time employees and students), the individual travel behavior may have specific temporal-spatial-mobile constraints. The study first extracts the home-based tours, including Home-to-Home and Home-to-Non-Home, from long-term raw GPS data. The travel behavior pattern is then delineated by home-based tour features, such as departure time, destination location entropy, travel time, and driving time ratio. The travel behavior variabilitymore » describes the variances of travelers’ activity behavior features for an extended period. After that, the variability pattern of an individual’s travel behavior is used for estimating the individual’s social-demographic information, such as social-demographic role, by a supervised learning approach, support vector machine. In this study, a long-term (18-month) recorded GPS data set from Puget Sound Regional Council is used. The experiment’s result is very promising. In conclusion, the sensitivity analysis shows that as the number of tours thresholds increases, the variability of most travel behavior features converges, while the prediction performance may not change for the fixed test data.« less

Migration phenology and seasonal fidelity of an Arctic marine predator in relation to sea ice dynamics.

PubMed

Cherry, Seth G; Derocher, Andrew E; Thiemann, Gregory W; Lunn, Nicholas J

2013-07-01

Understanding how seasonal environmental conditions affect the timing and distribution of synchronized animal movement patterns is a central issue in animal ecology. Migration, a behavioural adaptation to seasonal environmental fluctuations, is a fundamental part of the life history of numerous species. However, global climate change can alter the spatiotemporal distribution of resources and thus affect the seasonal movement patterns of migratory animals. We examined sea ice dynamics relative to migration patterns and seasonal geographical fidelity of an Arctic marine predator, the polar bear (Ursus maritimus). Polar bear movement patterns were quantified using satellite-linked telemetry data collected from collars deployed between 1991-1997 and 2004-2009. We showed that specific sea ice characteristics can predict the timing of seasonal polar bear migration on and off terrestrial refugia. In addition, fidelity to specific onshore regions during the ice-free period was predicted by the spatial pattern of sea ice break-up but not by the timing of break-up. The timing of migration showed a trend towards earlier arrival of polar bears on shore and later departure from land, which has been driven by climate-induced declines in the availability of sea ice. Changes to the timing of migration have resulted in polar bears spending progressively longer periods of time on land without access to sea ice and their marine mammal prey. The links between increased atmospheric temperatures, sea ice dynamics, and the migratory behaviour of an ice-dependent species emphasizes the importance of quantifying and monitoring relationships between migratory wildlife and environmental cues that may be altered by climate change. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Analyzing Global Components in Developmental Dyscalculia and Dyslexia.

PubMed

Filippo, Gloria Di; Zoccolotti, Pierluigi

2018-01-01

The study examined whether developmental deficits in reading and numerical skills could be expressed in terms of global factors by reference to the rate and amount (RAM) and difference engine (DEM) models. From a sample of 325 fifth grade children, we identified 5 children with dyslexia, 16 with dyscalculia, 7 with a "mixed pattern," and 49 control children. Children were asked to read aloud words presented individually that varied for frequency and length and to respond (either vocally or manually) to a series of simple number tasks (addition, subtraction, number reading, and number comparisons). Reaction times were measured. Results indicated that the deficit of children with dyscalculia and children with a mixed pattern on numerical tasks could be explained by a single global factor, similarly to the reading deficit shown by children with dyslexia. As predicted by the DEM, increases in task difficulty were accompanied by a corresponding increase in inter-individual variability for both the reading and numerical tasks. These relationships were constant across the four groups of children but differed in terms of slope and intercept on the x -axis, indicating that two different general rules underlie performance in reading and numerical skills. The study shows for the first time that, as previously shown for reading, also numerical performance can be explained with reference to a global factor. The advantage of this approach is that it takes into account the over-additivity effect, i.e., the presence of larger group differences in the case of more difficult conditions over and above the characteristics of the experimental conditions. It is concluded that reference to models such as the RAM and DEM can be useful in delineating the characteristics of the dyscalculic deficit as well as in the description of co-morbid disturbances, as in the case of dyslexia and dyscalculia.

Past and future warming of a deep European lake (Lake Lugano): What are the climatic drivers?

USGS Publications Warehouse

Lepori, Fabio; Roberts, James J.

2015-01-01

We used four decades (1972–2013) of temperature data from Lake Lugano, Switzerland and Italy, to address the hypotheses that: [i] the lake has been warming; [ii] part of the warming reflects global trends and is independent from climatic oscillations and [iii] the lake will continue to warm until the end of the 21st century. During the time spanned by our data, the surface waters of the lake (0–5 m) warmed at rates of 0.2–0.9 °C per decade, depending on season. The temperature of the deep waters (50-m bottom) displayed a rising trend in a meromictic basin of the lake and a sawtooth pattern in the other basin, which is holomictic. Long-term variation in surfacewater temperature correlated to global warming and multidecadal variation in two climatic oscillations, the Atlantic Multidecadal Oscillation (AMO) and the East Atlantic Pattern (EA).However, we did not detect an influence of the EA on the lake's temperature (as separate from the effect of global warming). Moreover, the effect of the AMO, estimated to a maximum of +1 °C, was not sufficient to explain the observed temperature increase (+2–3 °C in summer). Based on regional climate projections, we predicted that the lake will continue to warm at least until the end of the 21st century. Our results strongly suggest that the warming of Lake Lugano is tied to globalclimate change. To sustain current ecosystem conditions in Lake Lugano, we suggest that manage- ment plans that curtail eutrophication and (or) mitigation of global warming be pursued.

Detection and Attribution of Temperature Trends in the Presence of Natural Variability

NASA Astrophysics Data System (ADS)

Wallace, J. M.

2014-12-01

The fingerprint of human-induced global warming stands out clearly above the noise In the time series of global-mean temperature, but not local temperature. At extratropical latitudes over land the standard error of 50-year linear temperature trends at a fixed point is as large as the cumulative rise in global-mean temperature over the past century. Much of the samping variability in local temperature trends is "dynamically-induced", i.e., attributable to the fact that the seasonally-varying mean circulation varies substantially from one year to the next and anomalous circulation patterns are generally accompanied by anomalous temperature patterns. In the presence of such large sampling variability it is virtually impossible to identify the spatial signature of greenhouse warming based on observational data or to partition observed local temperature trends into natural and human-induced components. It follows that previous IPCC assessments, which have focused on the deterministic signature of human-induced climate change, are inherently limited as to what they can tell us about the attribution of the past record of local temperature change or about how much the temperature at a particular place is likely to rise in the next few decades in response to global warming. To obtain more informative assessments of regional and local climate variability and change it will be necessary to take a probabilistic approach. Just as the use of the ensembles has contributed to more informative extended range weather predictions, large ensembles of climate model simulations can provide a statistical context for interpreting observed climate change and for framing projections of future climate. For some purposes, statistics relating to the interannual variability in the historical record can serve as a surrogate for statistics relating to the diversity of climate change scenarios in large ensembles.

REGIONAL AND GLOBAL PATTERNS OF POPULATION, LAND USE AND LAND COVER CHANGE: AN OVERVIEW OF STRESSORS AND IMPACTS

EPA Science Inventory

This paper provides an overview of land use and land cover (LULC) change and regional to global patterns of that change and responses. Human activities now dominate the Earth's global ecosystem and LULC change is one of the most pervasive and influential activities. LULC change a...

Future Climate Impacts of Direct Radiative Forcing Anthropogenic Aerosols, Tropospheric Ozone, and Long-lived Greenhouse Gases

NASA Technical Reports Server (NTRS)

Chen, Wei-Ting; Liao, Hong; Seinfeld, John H.

2007-01-01

Long-lived greenhouse gases (GHGs) are the most important driver of climate change over the next century. Aerosols and tropospheric ozone (O3) are expected to induce significant perturbations to the GHG-forced climate. To distinguish the equilibrium climate responses to changes in direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and GHG between present day and year 2100, four 80-year equilibrium climates are simulated using a unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 110. Concentrations of sulfate, nitrate, primary organic (POA) carbon, secondary organic (SOA) carbon, black carbon (BC) aerosols, and tropospheric ozone for present day and year 2100 are obtained a priori by coupled chemistry-aerosol GCM simulations, with emissions of aerosols, ozone, and precursors based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) A2. Changing anthropogenic aerosols, tropospheric ozone, and GHG from present day to year 2100 is predicted to perturb the global annual mean radiative forcing by +0.18 (considering aerosol direct effects only), +0.65, and +6.54 W m(sup -2) at the tropopause, and to induce an equilibrium global annual mean surface temperature change of +0.14, +0.32, and +5.31 K, respectively, with the largest temperature response occurring at northern high latitudes. Anthropogenic aerosols, through their direct effect, are predicted to alter the Hadley circulation owing to an increasing interhemispheric temperature gradient, leading to changes in tropical precipitation. When changes in both aerosols and tropospheric ozone are considered, the predicted patterns of change in global circulation and the hydrological cycle are similar to those induced by aerosols alone. GHG-induced climate changes, such as amplified warming over high latitudes, weakened Hadley circulation, and increasing precipitation over the Tropics and high latitudes, are consistent with predictions of a number of previous GCM studies. Finally, direct radiative forcing of anthropogenic aerosols is predicted to induce strong regional cooling over East and South Asia. Wintertime rainfall over southeastern China and the Indian subcontinent is predicted to decrease because of the increased atmospheric stability and decreased surface evaporation, while the geographic distribution of precipitation is also predicted to be altered as a result of aerosol-induced changes in wind flow.

Predicting River Macroinvertebrate Communities Distributional Shifts under Future Global Change Scenarios in the Spanish Mediterranean Area

PubMed Central

Sáinz-Bariáin, Marta; Poquet, José Manuel; Rodríguez-López, Roberto

2017-01-01

Several studies on global change over the next century predict increases in mean air temperatures of between 1°C to 5°C that would affect not only water temperature but also river flow. Climate is the predominant environmental driver of thermal and flow regimes of freshwater ecosystems, determining survival, growth, metabolism, phenology and behaviour as well as biotic interactions of aquatic fauna. Thus, these changes would also have consequences for species phenology, their distribution range, and the composition and dynamics of communities. These effects are expected to be especially severe in the Mediterranean basin due its particular climate conditions, seriously threatening Southern European ecosystems. In addition, species with restricted distributions and narrow ecological requirements, such as those living in the headwaters of rivers, will be severely affected. The study area corresponds to the Spanish Mediterranean and Balearic Islands, delimited by the Köppen climate boundary. With the application of the MEDPACS (MEDiterranean Prediction And Classification System) predictive approach, the macroinvertebrate community was predicted for current conditions and compared with three posible scenarios of watertemperature increase and its associated water flow reductions. The results indicate that the aquatic macroinvertebrate communities will undergo a drastic impact, with reductions in taxa richness for each scenario in relation to simulated current conditions, accompanied by changes in the taxa distribution pattern. Accordingly, the distribution area of most of the taxa (65.96%) inhabiting the mid-high elevations would contract and rise in altitude. Thus, families containing a great number of generalist species will move upstream to colonize new zones with lower water temperatures. By contrast, more vulnerable taxa will undergo reductions in their distribution area. PMID:28135280

Predicting the spatial extent of liquefaction from geospatial and earthquake specific parameters

USGS Publications Warehouse

Zhu, Jing; Baise, Laurie G.; Thompson, Eric M.; Wald, David J.; Knudsen, Keith L.; Deodatis, George; Ellingwood, Bruce R.; Frangopol, Dan M.

2014-01-01

The spatially extensive damage from the 2010-2011 Christchurch, New Zealand earthquake events are a reminder of the need for liquefaction hazard maps for anticipating damage from future earthquakes. Liquefaction hazard mapping as traditionally relied on detailed geologic mapping and expensive site studies. These traditional techniques are difficult to apply globally for rapid response or loss estimation. We have developed a logistic regression model to predict the probability of liquefaction occurrence in coastal sedimentary areas as a function of simple and globally available geospatial features (e.g., derived from digital elevation models) and standard earthquake-specific intensity data (e.g., peak ground acceleration). Some of the geospatial explanatory variables that we consider are taken from the hydrology community, which has a long tradition of using remotely sensed data as proxies for subsurface parameters. As a result of using high resolution, remotely-sensed, and spatially continuous data as a proxy for important subsurface parameters such as soil density and soil saturation, and by using a probabilistic modeling framework, our liquefaction model inherently includes the natural spatial variability of liquefaction occurrence and provides an estimate of spatial extent of liquefaction for a given earthquake. To provide a quantitative check on how the predicted probabilities relate to spatial extent of liquefaction, we report the frequency of observed liquefaction features within a range of predicted probabilities. The percentage of liquefaction is the areal extent of observed liquefaction within a given probability contour. The regional model and the results show that there is a strong relationship between the predicted probability and the observed percentage of liquefaction. Visual inspection of the probability contours for each event also indicates that the pattern of liquefaction is well represented by the model.

Optimal stomatal behaviour around the world

NASA Astrophysics Data System (ADS)

Lin, Yan-Shih; Medlyn, Belinda E.; Duursma, Remko A.; Prentice, I. Colin; Wang, Han; Baig, Sofia; Eamus, Derek; de Dios, Victor Resco; Mitchell, Patrick; Ellsworth, David S.; de Beeck, Maarten Op; Wallin, Göran; Uddling, Johan; Tarvainen, Lasse; Linderson, Maj-Lena; Cernusak, Lucas A.; Nippert, Jesse B.; Ocheltree, Troy W.; Tissue, David T.; Martin-Stpaul, Nicolas K.; Rogers, Alistair; Warren, Jeff M.; de Angelis, Paolo; Hikosaka, Kouki; Han, Qingmin; Onoda, Yusuke; Gimeno, Teresa E.; Barton, Craig V. M.; Bennie, Jonathan; Bonal, Damien; Bosc, Alexandre; Löw, Markus; Macinins-Ng, Cate; Rey, Ana; Rowland, Lucy; Setterfield, Samantha A.; Tausz-Posch, Sabine; Zaragoza-Castells, Joana; Broadmeadow, Mark S. J.; Drake, John E.; Freeman, Michael; Ghannoum, Oula; Hutley, Lindsay B.; Kelly, Jeff W.; Kikuzawa, Kihachiro; Kolari, Pasi; Koyama, Kohei; Limousin, Jean-Marc; Meir, Patrick; Lola da Costa, Antonio C.; Mikkelsen, Teis N.; Salinas, Norma; Sun, Wei; Wingate, Lisa

2015-05-01

Stomatal conductance (gs) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of gs in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of gs that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed gs obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model and the leaf and wood economics spectrum. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of gs across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.

Towards a Unified Framework in Hydroclimate Extremes Prediction in Changing Climate

NASA Astrophysics Data System (ADS)

Moradkhani, H.; Yan, H.; Zarekarizi, M.; Bracken, C.

2016-12-01

Spatio-temporal analysis and prediction of hydroclimate extremes are of paramount importance in disaster mitigation and emergency management. The IPCC special report on managing the risks of extreme events and disasters emphasizes that the global warming would change the frequency, severity, and spatial pattern of extremes. In addition to climate change, land use and land cover changes also influence the extreme characteristics at regional scale. Therefore, natural variability and anthropogenic changes to the hydroclimate system result in nonstationarity in hydroclimate variables. In this presentation recent advancements in developing and using Bayesian approaches to account for non-stationarity in hydroclimate extremes are discussed. Also, implications of these approaches in flood frequency analysis, treatment of spatial dependence, the impact of large-scale climate variability, the selection of cause-effect covariates, with quantification of model errors in extreme prediction is explained. Within this framework, the applicability and usefulness of the ensemble data assimilation for extreme flood predictions is also introduced. Finally, a practical and easy to use approach for better communication with decision-makers and emergency managers is presented.

Spatial correlations of interdecadal variation in global surface temperatures

NASA Technical Reports Server (NTRS)

Mann, Michael E.; Park, Jeffrey

1993-01-01

We have analyzed spatial correlation patterns of interdecadal global surface temperature variability from an empirical perspective. Using multitaper coherence estimates from 140-yr records, we find that correlations between hemispheres are significant at about 95 percent confidence for nonrandomness for most of the frequency band in the 0.06-0.24 cyc/yr range. Coherence estimates of pairs of 100-yr grid-point temperature data series near 5-yr period reveal teleconnection patterns consistent with known patterns of ENSO variability. Significant correlated variability is observed near 15 year period, with the dominant teleconnection pattern largely confined to the Northern Hemisphere. Peak-to-peak Delta-T is at about 0.5 deg, with simultaneous warming and cooling of discrete patches on the earth's surface. A global average of this pattern would largely cancel.

A human-driven decline in global burned area.

PubMed

Andela, N; Morton, D C; Giglio, L; Chen, Y; van der Werf, G R; Kasibhatla, P S; DeFries, R S; Collatz, G J; Hantson, S; Kloster, S; Bachelet, D; Forrest, M; Lasslop, G; Li, F; Mangeon, S; Melton, J R; Yue, C; Randerson, J T

2017-06-30

Fire is an essential Earth system process that alters ecosystem and atmospheric composition. Here we assessed long-term fire trends using multiple satellite data sets. We found that global burned area declined by 24.3 ± 8.8% over the past 18 years. The estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas. Agricultural expansion and intensification were primary drivers of declining fire activity. Fewer and smaller fires reduced aerosol concentrations, modified vegetation structure, and increased the magnitude of the terrestrial carbon sink. Fire models were unable to reproduce the pattern and magnitude of observed declines, suggesting that they may overestimate fire emissions in future projections. Using economic and demographic variables, we developed a conceptual model for predicting fire in human-dominated landscapes. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Globalization, land use and the invasion of West Nile virus

PubMed Central

Kilpatrick, A. Marm

2012-01-01

Many invasive species that have been spread through the globalization of trade and travel are infectious pathogens. A paradigmatic case is the introduction of West Nile virus (WNV) into North America in 1999. A decade of research on the ecology and evolution of WNV includes three findings that provide insight into the outcome of future viral introductions. First, WNV transmission in North America is highest in urbanized and agricultural habitats, in part because the hosts and vectors of WNV are abundant in human-modified areas. Second, after its introduction, the virus quickly adapted to infect local mosquito vectors more efficiently than the originally introduced strain. Third, highly focused feeding patterns of the mosquito vectors of WNV result in unexpected host species being important for transmission. These findings provide a framework for predicting and preventing the emergence of foreign vector-borne pathogens. PMID:22021850

Dual Coordination of Post Translational Modifications in Human Protein Networks

PubMed Central

Woodsmith, Jonathan; Kamburov, Atanas; Stelzl, Ulrich

2013-01-01

Post-translational modifications (PTMs) regulate protein activity, stability and interaction profiles and are critical for cellular functioning. Further regulation is gained through PTM interplay whereby modifications modulate the occurrence of other PTMs or act in combination. Integration of global acetylation, ubiquitination and tyrosine or serine/threonine phosphorylation datasets with protein interaction data identified hundreds of protein complexes that selectively accumulate each PTM, indicating coordinated targeting of specific molecular functions. A second layer of PTM coordination exists in these complexes, mediated by PTM integration (PTMi) spots. PTMi spots represent very dense modification patterns in disordered protein regions and showed an equally high mutation rate as functional protein domains in cancer, inferring equivocal importance for cellular functioning. Systematic PTMi spot identification highlighted more than 300 candidate proteins for combinatorial PTM regulation. This study reveals two global PTM coordination mechanisms and emphasizes dataset integration as requisite in proteomic PTM studies to better predict modification impact on cellular signaling. PMID:23505349

Plant diversity increases with the strength of negative density dependence at the global scale.

PubMed

LaManna, Joseph A; Mangan, Scott A; Alonso, Alfonso; Bourg, Norman A; Brockelman, Warren Y; Bunyavejchewin, Sarayudh; Chang, Li-Wan; Chiang, Jyh-Min; Chuyong, George B; Clay, Keith; Condit, Richard; Cordell, Susan; Davies, Stuart J; Furniss, Tucker J; Giardina, Christian P; Gunatilleke, I A U Nimal; Gunatilleke, C V Savitri; He, Fangliang; Howe, Robert W; Hubbell, Stephen P; Hsieh, Chang-Fu; Inman-Narahari, Faith M; Janík, David; Johnson, Daniel J; Kenfack, David; Korte, Lisa; Král, Kamil; Larson, Andrew J; Lutz, James A; McMahon, Sean M; McShea, William J; Memiaghe, Hervé R; Nathalang, Anuttara; Novotny, Vojtech; Ong, Perry S; Orwig, David A; Ostertag, Rebecca; Parker, Geoffrey G; Phillips, Richard P; Sack, Lawren; Sun, I-Fang; Tello, J Sebastián; Thomas, Duncan W; Turner, Benjamin L; Vela Díaz, Dilys M; Vrška, Tomáš; Weiblen, George D; Wolf, Amy; Yap, Sandra; Myers, Jonathan A

2017-06-30

Theory predicts that higher biodiversity in the tropics is maintained by specialized interactions among plants and their natural enemies that result in conspecific negative density dependence (CNDD). By using more than 3000 species and nearly 2.4 million trees across 24 forest plots worldwide, we show that global patterns in tree species diversity reflect not only stronger CNDD at tropical versus temperate latitudes but also a latitudinal shift in the relationship between CNDD and species abundance. CNDD was stronger for rare species at tropical versus temperate latitudes, potentially causing the persistence of greater numbers of rare species in the tropics. Our study reveals fundamental differences in the nature of local-scale biotic interactions that contribute to the maintenance of species diversity across temperate and tropical communities. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

New Martian climate constraints from radar reflectivity within the north polar layered deposits

NASA Astrophysics Data System (ADS)

Lalich, D. E.; Holt, J. W.

2017-01-01

The north polar layered deposits (NPLD) of Mars represent a global climate record reaching back millions of years, potentially recorded in visible layers and radar reflectors. However, little is known of the specific link between those layers, reflectors, and the global climate. To test the hypothesis that reflectors are caused by thick and indurated layers known as "marker beds," the reflectivity of three reflectors was measured, mapped, and compared to a reflectivity model. The measured reflectivities match the model and show a strong sensitivity to layer thickness, implying that radar reflectivity may be used as a proxy for short-term accumulation patterns and that regional climate plays a strong role in layer thickness variations. Comparisons to an orbitally forced NPLD accumulation model show a strong correlation with predicted marker bed formation, but dust content is higher than expected, implying a stronger role for dust in Mars polar climate than previously thought.

[Effects of global change on soil fauna diversity: A review].

PubMed

Wu, Ting-Juan

2013-02-01

Terrestrial ecosystem consists of aboveground and belowground components, whose interaction affects the ecosystem processes and functions. Soil fauna plays an important role in biogeochemical cycles. With the recognizing of the significance of soil fauna in ecosystem processes, increasing evidences demonstrated that global change has profound effects on soil faunima diversity. The alternation of land use type, the increasing temperature, and the changes in precipitation pattern can directly affect soil fauna diversity, while the increase of atmospheric CO2 concentration and nitrogen deposition can indirectly affect the soil fauna diversity by altering plant community composition, diversity, and nutrient contents. The interactions of different environmental factors can co-affect the soil fauna diversity. To understand the effects of different driving factors on soil fauna diversity under the background of climate change would facilitate us better predicting how the soil fauna diversity and related ecological processes changed in the future.

Range-expanding pests and pathogens in a warming world.

PubMed

Bebber, Daniel Patrick

2015-01-01

Crop pests and pathogens (CPPs) present a growing threat to food security and ecosystem management. The interactions between plants and their natural enemies are influenced by environmental conditions and thus global warming and climate change could affect CPP ranges and impact. Observations of changing CPP distributions over the twentieth century suggest that growing agricultural production and trade have been most important in disseminating CPPs, but there is some evidence for a latitudinal bias in range shifts that indicates a global warming signal. Species distribution models using climatic variables as drivers suggest that ranges will shift latitudinally in the future. The rapid spread of the Colorado potato beetle across Eurasia illustrates the importance of evolutionary adaptation, host distribution, and migration patterns in affecting the predictions of climate-based species distribution models. Understanding species range shifts in the framework of ecological niche theory may help to direct future research needs.

Divergent surface and total soil moisture projections under global warming

USGS Publications Warehouse

Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.

2017-01-01

Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.

A Serum Protein Profile Predictive of the Resistance to Neoadjuvant Chemotherapy in Advanced Breast Cancers*

PubMed Central

Hyung, Seok-Won; Lee, Min Young; Yu, Jong-Han; Shin, Byunghee; Jung, Hee-Jung; Park, Jong-Moon; Han, Wonshik; Lee, Kyung-Min; Moon, Hyeong-Gon; Zhang, Hui; Aebersold, Ruedi; Hwang, Daehee; Lee, Sang-Won; Yu, Myeong-Hee; Noh, Dong-Young

2011-01-01

Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to NACT) to discover serum biomarkers of chemoresistance using a label-free liquid chromatography-tandem MS method. By performing a series of statistical analyses of the proteomic data, we selected thirteen biomarker candidates and tested their differential serum levels by Western blotting in 13 independent samples (eight patients sensitive to and five patients resistant to NACT). Among the candidates, we then selected the final set of six potential serum biomarkers (AHSG, APOB, C3, C9, CP, and ORM1) whose differential expression was confirmed in the independent samples. Finally, we demonstrated that a multivariate classification model using the six proteins could predict responses to NACT and further predict relapse-free survival of patients. In summary, global N-glycoproteome profile in serum revealed a protein pattern predictive of the responses to NACT, which can be further validated in large clinical studies. PMID:21799047

A new precipitation and meteorological drought climatology based on weather patterns

NASA Astrophysics Data System (ADS)

Richardson, D.; Fowler, H. J.; Kilsby, C. G.; Neal, R.

2017-12-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterise the broad-scale atmospheric circulation over a given region. An analysis of regional UK precipitation and meteorological drought climatology with respect to a set of objectively defined weather patterns is presented. This classification system, introduced last year, is currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. The classification consists of 30 daily patterns derived from North Atlantic Ocean and European mean sea level pressure data. Clustering these 30 patterns yields another set of eight patterns that are intended for use in longer-range applications. Weather pattern definitions and daily occurrences are mapped to the commonly-used Lamb Weather Types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Drought index series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for different drought index thresholds, representing dry, wet and drought conditions. The set of 30 weather patterns is shown to be adequate for precipitation-based analyses in the UK, although the smaller set of clustered patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in the context of precipitation studies. Weather patterns associated with drought over the different UK regions are identified. This has potential forecasting application - if a model (e.g. a global seasonal forecast model) can predict weather pattern occurrences then regional drought outlooks may be derived from the forecasted weather patterns.

Assessing global radiative forcing due to regional emissions of tropospheric ozone precursors: a step towards climate credit for ozone reductions

NASA Astrophysics Data System (ADS)

Mauzerall, D. L.; Naik, V.; Horowitz, L. W.; Schwarzkopf, D.; Ramaswamy, V.; Oppenheimer, M.

2005-05-01

Carbon dioxide emissions from fossil-fuel consumption are presented for the five Asian countries that are among the global leaders in anthropogenic carbon emissions: China (13% of global total), Japan (5% of global total), India (5% of global total), South Korea (2% of global total), and Indonesia (1% of global total). Together, these five countries represent over a quarter of the world's fossil-fuel based carbon emissions. Moreover, these countries are rapidly developing and energy demand has grown dramatically in the last two decades. A method is developed to estimate the spatial and seasonal flux of fossil-fuel consumption, thereby greatly improving the temporal and spatial resolution of anthropogenic carbon dioxide emissions. Currently, only national annual data for anthropogenic carbon emissions are available, and as such, no understanding of seasonal or sub-national patterns of emissions are possible. This methodology employs fuel distribution data from representative sectors of the fossil-fuel market to determine the temporal and spatial patterns of fuel consumption. These patterns of fuel consumption are then converted to patterns of carbon emissions. The annual total emissions estimates produced by this method are consistent to those maintained by the United Nations. Improved estimates of temporal and spatial resolution of the human based carbon emissions allows for better projections about future energy demands, carbon emissions, and ultimately the global carbon cycle.

Predictive ethoinformatics reveals the complex migratory behaviour of a pelagic seabird, the Manx Shearwater

PubMed Central

Freeman, Robin; Dean, Ben; Kirk, Holly; Leonard, Kerry; Phillips, Richard A.; Perrins, Chris M.; Guilford, Tim

2013-01-01

Understanding the behaviour of animals in the wild is fundamental to conservation efforts. Advances in bio-logging technologies have offered insights into the behaviour of animals during foraging, migration and social interaction. However, broader application of these systems has been limited by device mass, cost and longevity. Here, we use information from multiple logger types to predict individual behaviour in a highly pelagic, migratory seabird, the Manx Shearwater (Puffinus puffinus). Using behavioural states resolved from GPS tracking of foraging during the breeding season, we demonstrate that individual behaviours can be accurately predicted during multi-year migrations from low cost, lightweight, salt-water immersion devices. This reveals a complex pattern of migratory stopovers: some involving high proportions of foraging, and others of rest behaviour. We use this technique to examine three consecutive years of global migrations, revealing the prominence of foraging behaviour during migration and the importance of highly productive waters during migratory stopover. PMID:23635496

Distributions and Abundances of Sublineages of the N2-Fixing Cyanobacterium Candidatus Atelocyanobacterium thalassa (UCYN-A) in the New Caledonian Coral Lagoon

PubMed Central

Henke, Britt A.; Turk-Kubo, Kendra A.; Bonnet, Sophie; Zehr, Jonathan P.

2018-01-01

Nitrogen (N2) fixation is a major source of nitrogen that supports primary production in the vast oligotrophic areas of the world’s oceans. The Western Tropical South Pacific has recently been identified as a hotspot for N2 fixation. In the Noumea lagoon (New Caledonia), high abundances of the unicellular N2-fixing cyanobacteria group A (UCYN-A), coupled with daytime N2 fixation rates associated with the <10 μm size fraction, suggest UCYN-A may be an important diazotroph (N2-fixer) in this region. However, little is known about the seasonal variability and diversity of UCYN-A there. To assess this, surface waters from a 12 km transect from the mouth of the Dumbea River to the Dumbea Pass were sampled monthly between July 2012 and March 2014. UCYN-A abundances for two of the defined sublineages, UCYN-A1 and UCYN-A2, were quantified using qPCR targeting the nifH gene, and the nifH-based diversity of UCYN-A was characterized by identifying oligotypes, alternative taxonomic units defined by nucleotide positions with high variability. UCYN-A abundances were dominated by the UCYN-A1 sublineage, peaked in September and October and could be predicted by a suite of nine environmental parameters. At the sublineage level, UCYN-A1 abundances could be predicted based on lower temperatures (<23°C), nitrate concentrations, precipitation, wind speed, while UCYN-A2 abundances could be predicted based on silica, and chlorophyll a concentrations, wind direction, precipitation, and wind speed. Using UCYN-A nifH oligotyping, similar environmental variables explained the relative abundances of sublineages and their associated oligotypes, with the notable exception of the UCYN-A2 oligotype (oligo43) which had relative abundance patterns distinct from the dominant UCYN-A2 oligotype (oligo3). The results support an emerging pattern that UCYN-A is comprised of a diverse group of strains, with sublineages that may have different ecological niches. By identifying environmental factors that influence the composition and abundance of UCYN-A sublineages, this study helps to explain global UCYN-A abundance patterns, and is important for understanding the significance of N2 fixation at local and global scales. PMID:29674998

Identifying polar bear resource selection patterns to inform offshore development in a dynamic and changing Arctic

USGS Publications Warehouse

Wilson, Ryan R.; Horne, Jon S.; Rode, Karyn D.; Regehr, Eric V.; Durner, George M.

2014-01-01

Although sea ice loss is the primary threat to polar bears (Ursus maritimus), little can be done to mitigate its effects without global efforts to reduce greenhouse gas emissions. Other factors, however, could exacerbate the impacts of sea ice loss on polar bears, such as exposure to increased industrial activity. The Arctic Ocean has enormous oil and gas potential, and its development is expected to increase in the coming decades. Estimates of polar bear resource selection will inform managers how bears use areas slated for oil development and to help guide conservation planning. We estimated temporally-varying resource selection patterns for non-denning adult female polar bears in the Chukchi Sea population (2008–2012) at two scales (i.e., home range and weekly steps) to identify factors predictive of polar bear use throughout the year, before any offshore development. From the best models at each scale, we estimated scale-integrated resource selection functions to predict polar bear space use across the population's range and determined when bears were most likely to use the region where offshore oil and gas development in the United States is slated to occur. Polar bears exhibited significant intra-annual variation in selection patterns at both scales but the strength and annual patterns of selection differed between scales for most variables. Bears were most likely to use the offshore oil and gas planning area during ice retreat and growth with the highest predicted use occurring in the southern portion of the planning area. The average proportion of predicted high-value habitat in the planning area was >15% of the total high-value habitat for the population during sea ice retreat and growth and reached a high of 50% during November 2010. Our results provide a baseline on which to judge future changes to non-denning adult female polar bear resource selection in the Chukchi Sea and help guide offshore development in the region. Lastly, our study provides a framework for assessing potential impacts of offshore oil and gas development to other polar bear populations around the Arctic.

Infrastructure effects on estuarine wetlands increase their vulnerability to sea level rise

NASA Astrophysics Data System (ADS)

Rodriguez, Jose; Saco, Patricia; Sandi, Steven; Saintilan, Neil; Riccardi, Gerardo

2017-04-01

At the regional and global scales, coastal management and planning for future sea level rise scenarios is typically supported by modelling tools that predict the expected inundation extent. These tools rely on a number of simplifying assumptions that, in some cases, may result in important miscalculation of the inundation effects. One of such cases is estuarine wetlands, where vegetation strongly depends on both the magnitude and the timing of inundation. Many coastal wetlands display flow restrictions due to infrastructure or drainage works, which produce alterations to the inundation patterns that can not be captured by conventional models. In this contribution we explore the effects of flow restrictions on inundation patterns under sea level rise conditions in estuarine wetlands. We use a spatially-distributed dynamic wetland ecogeomorphological model that not only incorporates the effects of flow restrictions due to culverts, bridges and weirs as well as vegetation, but also considers that vegetation changes as a consequence of increasing inundation. We also consider the ability of vegetation to capture sediment and produce accretion. We apply our model to an estuarine wetland in Australia and show that our model predicts a much faster wetland loss due to sea level rise than conventional approaches.

Protein-DNA binding dynamics predict transcriptional response to nutrients in archaea.

PubMed

Todor, Horia; Sharma, Kriti; Pittman, Adrianne M C; Schmid, Amy K

2013-10-01

Organisms across all three domains of life use gene regulatory networks (GRNs) to integrate varied stimuli into coherent transcriptional responses to environmental pressures. However, inferring GRN topology and regulatory causality remains a central challenge in systems biology. Previous work characterized TrmB as a global metabolic transcription factor in archaeal extremophiles. However, it remains unclear how TrmB dynamically regulates its ∼100 metabolic enzyme-coding gene targets. Using a dynamic perturbation approach, we elucidate the topology of the TrmB metabolic GRN in the model archaeon Halobacterium salinarum. Clustering of dynamic gene expression patterns reveals that TrmB functions alone to regulate central metabolic enzyme-coding genes but cooperates with various regulators to control peripheral metabolic pathways. Using a dynamical model, we predict gene expression patterns for some TrmB-dependent promoters and infer secondary regulators for others. Our data suggest feed-forward gene regulatory topology for cobalamin biosynthesis. In contrast, purine biosynthesis appears to require TrmB-independent regulators. We conclude that TrmB is an important component for mediating metabolic modularity, integrating nutrient status and regulating gene expression dynamics alone and in concert with secondary regulators.

From trees to forest: relational complexity network and workload of air traffic controllers.

PubMed

Zhang, Jingyu; Yang, Jiazhong; Wu, Changxu

2015-01-01

In this paper, we propose a relational complexity (RC) network framework based on RC metric and network theory to model controllers' workload in conflict detection and resolution. We suggest that, at the sector level, air traffic showing a centralised network pattern can provide cognitive benefits in visual search and resolution decision which will in turn result in lower workload. We found that the network centralisation index can account for more variance in predicting perceived workload and task completion time in both a static conflict detection task (Study 1) and a dynamic one (Study 2) in addition to other aircraft-level and pair-level factors. This finding suggests that linear combination of aircraft-level or dyad-level information may not be adequate and the global-pattern-based index is necessary. Theoretical and practical implications of using this framework to improve future workload modelling and management are discussed. We propose a RC network framework to model the workload of air traffic controllers. The effect of network centralisation was examined in both a static conflict detection task and a dynamic one. Network centralisation was predictive of perceived workload and task completion time over and above other control variables.

Terrestrial basking sea turtles are responding to spatio-temporal sea surface temperature patterns.

PubMed

Van Houtan, Kyle S; Halley, John M; Marks, Wendy

2015-01-01

Naturalists as early as Darwin observed terrestrial basking in green turtles (Chelonia mydas), but the distribution and environmental influences of this behaviour are poorly understood. Here, we examined 6 years of daily basking surveys in Hawaii and compared them with the phenology of local sea surface temperatures (SST). Data and models indicated basking peaks when SST is coolest, and we found this timeline consistent with bone stress markings. Next, we assessed the decadal SST profiles for the 11 global green turtle populations. Basking generally occurs when winter SST falls below 23°C. From 1990 to 2014, the SST for these populations warmed an average 0.04°C yr(-1) (range 0.01-0.09°C yr(-1)); roughly three times the observed global average over this period. Owing to projected future warming at basking sites, we estimated terrestrial basking in green turtles may cease globally by 2100. To predict and manage for future climate change, we encourage a more detailed understanding for how climate influences organismal biology. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Terrestrial basking sea turtles are responding to spatio-temporal sea surface temperature patterns

PubMed Central

Van Houtan, Kyle S.; Halley, John M.; Marks, Wendy

2015-01-01

Naturalists as early as Darwin observed terrestrial basking in green turtles (Chelonia mydas), but the distribution and environmental influences of this behaviour are poorly understood. Here, we examined 6 years of daily basking surveys in Hawaii and compared them with the phenology of local sea surface temperatures (SST). Data and models indicated basking peaks when SST is coolest, and we found this timeline consistent with bone stress markings. Next, we assessed the decadal SST profiles for the 11 global green turtle populations. Basking generally occurs when winter SST falls below 23°C. From 1990 to 2014, the SST for these populations warmed an average 0.04°C yr−1 (range 0.01–0.09°C yr−1); roughly three times the observed global average over this period. Owing to projected future warming at basking sites, we estimated terrestrial basking in green turtles may cease globally by 2100. To predict and manage for future climate change, we encourage a more detailed understanding for how climate influences organismal biology. PMID:25589483

Global health inequalities and breast cancer: an impending public health problem for developing countries.

PubMed

Igene, Helen

2008-01-01

The aim of the study was to provide information on the global health inequality pattern produced by the increasing incidence of breast cancer and its relationship with the health expenditure of developing countries with emphasis on sub-Saharan Africa. It examines the difference between the health expenditure of developed and developing countries, and how this affects breast cancer incidence and mortality. The data collected from the World Health Organization and World Bank were examined, using bivariate analysis, through scatter-plots and Pearson's product moment correlation coefficient. Multivariate analysis was carried out by multiple regression analysis. National income, health expenditure affects breast cancer incidence, particularly between the developed and developing countries. However, these factors do not adequately explain variations in mortality rates. The study reveals the risk posed to developing countries to solving the present and predicted burden of breast cancer, currently characterized by late presentation, inadequate health care systems, and high mortality. Findings from this study contribute to the knowledge of the burden of disease in developing countries, especially sub-Saharan Africa, and how that is related to globalization and health inequalities.

Dimethyl sulfide in the surface ocean and the marine atmosphere: a global view.

PubMed

Andreae, M O; Raemdonck, H

1983-08-19

Dimethyl sulfide (DMS) has been identified as the major volatile sulfur compound in 628 samples of surface seawater representing most of the major oceanic ecozones. In at least three respects, its vertical distribution, its local patchiness, and its distribution in oceanic ecozones, the concentration of DMS in the sea exhibits a pattern similar to that of primary production. The global weightedaverage concentration of DMS in surface seawater is 102 nanograms of sulfur (DMS) per liter, corresponding to a global sea-to-air flux of 39 x 10(12) grams of sulfur per year. When the biogenic sulfur contributions from the land surface are added, the biogenic sulfur gas flux is approximately equal to the anthropogenic flux of sulfur dioxide. The DMS concentration in air over the equatorial Pacific varies diurnally between 120 and 200 nanograms of sulfur (DMS) per cubic meter, in agreement with the predictions of photochemical models. The estimated source flux of DMS from the oceans to the marine atmosphere is in agreement with independently obtained estimates of the removal fluxes of DMS and its oxidation products from the atmosphere.

Dimethyl Sulfide in the Surface Ocean and the Marine Atmosphere: A Global View

NASA Astrophysics Data System (ADS)

Andreae, Meinrat O.; Raemdonck, Hans

1983-08-01

Dimethyl sulfide (DMS) has been identified as the major volatile sulfur compound in 628 samples of surface seawater representing most of the major oceanic ecozones. In at least three respects, its vertical distribution, its local patchiness, and its distribution in oceanic ecozones, the concentration of DMS in the sea exhibits a pattern similar to that of primary production. The global weighted-average concentration of DMS in surface seawater is 102 nanograms of sulfur (DMS) per liter, corresponding to a global sea-to-air flux of 39 × 1012 grams of sulfur per year. When the biogenic sulfur contributions from the land surface are added, the biogenic sulfur gas flux is approximately equal to the anthropogenic flux of sulfur dioxide. The DMS concentration in air over the equatorial Pacific varies diurnally between 120 and 200 nanograms of sulfur (DMS) per cubic meter, in agreement with the predictions of photochemical models. The estimated source flux of DMS from the oceans to the marine atmosphere is in agreement with independently obtained estimates of the removal fluxes of DMS and its oxidation products from the atmosphere.

Diverse Responses of Belowground Internal Nitrogen Cycling to Increasing Aridity

NASA Astrophysics Data System (ADS)

Kou, D.; Peng, Y.; Wang, G.; Ding, J.; Chen, Y.; Yang, G.; Fang, K.; Liu, L.; Zhang, B.; Müller, C.; Zhang, J.; Yang, Y.

2017-12-01

Belowground microbial nitrogen (N) dynamics play key roles in regulating structure and function of terrestrial ecosystems, however, our understanding on their responses to global change remains limited. This gap is particularly true for drylands, which constitute the largest biome in terrestrial ecosystems and are sensitive to predicted increase in aridity. Here, responding patterns and controls of six gross N transformation rates were explored along an aridity gradient in Tibetan drylands. Our results showed that gross N rates responded diversely to the changing aridity. Both mineralization (MN) and ammonium immobilization (INH4) declined as aridity increased. Aridity affected MN through its association with plant cover, clay content, soil organic matter (SOM), dissolved organic nitrogen (DON) and total microbial biomass, while regulated INH4 mainly through its effects on SOM and NH4+. Autotrophic nitrification (ONH4) exhibited a bell-shaped pattern along the gradient with a tipping point at aridity index = 0.47. Such a pattern was induced by aridity effects on the abundance of ammonia oxidizing archaea (AOA) and ammonia supplying capacity. Different from above N transformations, rates of nitrate immobilization (INO3) and dissimilatory nitrate reduction to ammonium (DNRA) had no responses to changing aridity, largely regulated by soil DON availability and clay content, respectively. Overall, these results suggest that predicted increase in aridity will exert different effects on various soil internal N cycling processes. The diverse patterns point to different responses of ecosystem N cycle with respect to aridity, and thus potentially have profound impact on structure and function of dryland ecosystems.

Time course of gene expression during mouse skeletal muscle hypertrophy

PubMed Central

Lee, Jonah D.; England, Jonathan H.; Esser, Karyn A.; McCarthy, John J.

2013-01-01

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy. PMID:23869057

Time course of gene expression during mouse skeletal muscle hypertrophy.

PubMed

Chaillou, Thomas; Lee, Jonah D; England, Jonathan H; Esser, Karyn A; McCarthy, John J

2013-10-01

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy.

Early differential sensitivity of evoked-potentials to local and global shape during the perception of three-dimensional objects.

PubMed

Leek, E Charles; Roberts, Mark; Oliver, Zoe J; Cristino, Filipe; Pegna, Alan J

2016-08-01

Here we investigated the time course underlying differential processing of local and global shape information during the perception of complex three-dimensional (3D) objects. Observers made shape matching judgments about pairs of sequentially presented multi-part novel objects. Event-related potentials (ERPs) were used to measure perceptual sensitivity to 3D shape differences in terms of local part structure and global shape configuration - based on predictions derived from hierarchical structural description models of object recognition. There were three types of different object trials in which stimulus pairs (1) shared local parts but differed in global shape configuration; (2) contained different local parts but shared global configuration or (3) shared neither local parts nor global configuration. Analyses of the ERP data showed differential amplitude modulation as a function of shape similarity as early as the N1 component between 146-215ms post-stimulus onset. These negative amplitude deflections were more similar between objects sharing global shape configuration than local part structure. Differentiation among all stimulus types was reflected in N2 amplitude modulations between 276-330ms. sLORETA inverse solutions showed stronger involvement of left occipitotemporal areas during the N1 for object discrimination weighted towards local part structure. The results suggest that the perception of 3D object shape involves parallel processing of information at local and global scales. This processing is characterised by relatively slow derivation of 'fine-grained' local shape structure, and fast derivation of 'coarse-grained' global shape configuration. We propose that the rapid early derivation of global shape attributes underlies the observed patterns of N1 amplitude modulations. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

AN OVERVIEW OF THE STRESSORS AND ECOLOGICAL IMPACTS ASSOCIATED WITH REGIONAL AND GLOBAL PATTERNS OF POPULATION, LAND USE, AND LAND COVER CHANGE

EPA Science Inventory

This report provides an overview of land use and land cover (LULC) change and re~ona1 to global patterns of that change and responses. Human activities now dominate the Earth's global ecosystem and LULC change is one of the most pervasive and influential of those activities. LULC...

Visual Attention to Global and Local Stimulus Properties in 6-Month-Old Infants: Individual Differences and Event-Related Potentials

ERIC Educational Resources Information Center

Guy, Maggie W.; Reynolds, Greg D.; Zhang, Dantong

2013-01-01

Event-related potentials (ERPs) were utilized in an investigation of 21 six-month-olds' attention to and processing of global and local properties of hierarchical patterns. Overall, infants demonstrated an advantage for processing the overall configuration (i.e., global properties) of local features of hierarchical patterns; however,…

Unraveling past impacts of climate change and land management on historic peatland development using proxy-based reconstruction, monitoring data and process modeling.

PubMed

Heinemeyer, Andreas; Swindles, Graeme T

2018-05-08

Peatlands represent globally significant soil carbon stores that have been accumulating for millennia under water-logged conditions. However, deepening water-table depths (WTD) from climate change or human-induced drainage could stimulate decomposition resulting in peatlands turning from carbon sinks to carbon sources. Contemporary WTD ranges of testate amoebae (TA) are commonly used to predict past WTD in peatlands using quantitative transfer function models. Here we present, for the first time, a study comparing TA-based WTD reconstructions to instrumentally monitored WTD and hydrological model predictions using the MILLENNIA peatland model to examine past peatland responses to climate change and land management. Although there was very good agreement between monitored and modeled WTD, TA-reconstructed water table was consistently deeper. Predictions from a larger European TA transfer function data set were wetter, but the overall directional fit to observed WTD was better for a TA transfer function based on data from northern England. We applied a regression-based offset correction to the reconstructed WTD for the validation period (1931-2010). We then predicted WTD using available climate records as MILLENNIA model input and compared the offset-corrected TA reconstruction to MILLENNIA WTD predictions over an extended period (1750-1931) with available climate reconstructions. Although the comparison revealed striking similarities in predicted overall WTD patterns, particularly for a recent drier period (1965-1995), there were clear periods when TA-based WTD predictions underestimated (i.e. drier during 1830-1930) and overestimated (i.e. wetter during 1760-1830) past WTD compared to MILLENNIA model predictions. Importantly, simulated grouse moor management scenarios may explain the drier TA WTD predictions, resulting in considerable model predicted carbon losses and reduced methane emissions, mainly due to drainage. This study demonstrates the value of a site-specific and combined data-model validation step toward using TA-derived moisture conditions to understand past climate-driven peatland development and carbon budgets alongside modeling likely management impacts. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.

PubMed

Vallat, Laurent; Kemper, Corey A; Jung, Nicolas; Maumy-Bertrand, Myriam; Bertrand, Frédéric; Meyer, Nicolas; Pocheville, Arnaud; Fisher, John W; Gribben, John G; Bahram, Seiamak

2013-01-08

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program.

iDBPs: a web server for the identification of DNA binding proteins.

PubMed

Nimrod, Guy; Schushan, Maya; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2010-03-01

The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outperformed related methods. On a dataset that reflects the fraction of DNA binding proteins (DBPs) in a proteome, the area under the ROC curve was 0.90. The application of the server to an updated version of the N-Func database, which contains proteins of unknown function with solved 3D-structure, suggested new putative DBPs for experimental studies. http://idbps.tau.ac.il/

A complete Holocene record of trematode-bivalve infection and implications for the response of parasitism to climate change

NASA Astrophysics Data System (ADS)

Huntley, John Warren; Fürsich, Franz T.; Alberti, Matthias; Hethke, Manja; Liu, Chunlian

2014-12-01

Increasing global temperature and sea-level rise have led to concern about expansions in the distribution and prevalence of complex-lifecycle parasites (CLPs). Indeed, numerous environmental variables can influence the infectivity and reproductive output of many pathogens. Digenean trematodes are CLPs with intermediate invertebrate and definitive vertebrate hosts. Global warming and sea level rise may affect these hosts to varying degrees, and the effect of increasing temperature on parasite prevalence has proven to be nonlinear and difficult to predict. Projecting the response of parasites to anthropogenic climate change is vital for human health, and a longer term perspective (104 y) offered by the subfossil record is necessary to complement the experimental and historical approaches of shorter temporal duration (10-1 to 103 y). We demonstrate, using a high-resolution 9,600-y record of trematode parasite traces in bivalve hosts from the Holocene Pearl River Delta, that prevalence was significantly higher during the earliest stages of sea level rise, significantly lower during the maximum transgression, and statistically indistinguishable in the other stages of sea-level rise and delta progradation. This stratigraphic paleobiological pattern represents the only long-term high-resolution record of pathogen response to global change, is consistent with fossil and recent data from other marine basins, and is instructive regarding the future of disease. We predict an increase in trematode prevalence concurrent with anthropogenic warming and marine transgression, with negative implications for estuarine macrobenthos, marine fisheries, and human health.

Global Climate Anomalies and Potential Infectious Disease Risks: 2014-2015

PubMed Central

Chretien, Jean-Paul; Anyamba, Assaf; Small, Jennifer; Britch, Seth; Sanchez, Jose L.; Halbach, Alaina C.; Tucker, Compton; Linthicum, Kenneth J.

2015-01-01

Background: The El Niño/Southern Oscillation (ENSO) is a global climate phenomenon that impacts human infectious disease risk worldwide through droughts, floods, and other climate extremes. Throughout summer and fall 2014 and winter 2015, El Niño Watch, issued by the US National Oceanic and Atmospheric Administration, assessed likely El Niño development during the Northern Hemisphere fall and winter, persisting into spring 2015. Methods: We identified geographic regions where environmental conditions may increase infectious disease transmission if the predicted El Niño occurs using El Niño indicators (Sea Surface Temperature [SST], Outgoing Longwave Radiation [OLR], and rainfall anomalies) and literature review of El Niño-infectious disease associations. Results: SSTs in the equatorial Pacific and western Indian Oceans were anomalously elevated during August-October 2014, consistent with a developing weak El Niño event. Teleconnections with local climate is evident in global precipitation patterns, with positive OLR anomalies (drier than average conditions) across Indonesia and coastal southeast Asia, and negative anomalies across northern China, the western Indian Ocean, central Asia, north-central and northeast Africa, Mexico/Central America, the southwestern United States, and the northeastern and southwestern tropical Pacific. Persistence of these conditions could produce environmental settings conducive to increased transmission of cholera, dengue, malaria, Rift Valley fever, and other infectious diseases in regional hotspots as during previous El Niño events. Discussion and Conclusions: The current development of weak El Niño conditions may have significant potential implications for global public health in winter 2014-spring 2015. Enhanced surveillance and other preparedness measures in predicted infectious disease hotspots could mitigate health impacts. PMID:25685635

Global and regional ecosystem modeling: comparison of model outputs and field measurements

NASA Astrophysics Data System (ADS)

Olson, R. J.; Hibbard, K.

2003-04-01

The Ecosystem Model-Data Intercomparison (EMDI) Workshops provide a venue for global ecosystem modeling groups to compare model outputs against measurements of net primary productivity (NPP). The objective of EMDI Workshops is to evaluate model performance relative to observations in order to improve confidence in global model projections terrestrial carbon cycling. The questions addressed by EMDI include: How does the simulated NPP compare with the field data across biome and environmental gradients? How sensitive are models to site-specific climate? Does additional mechanistic detail in models result in a better match with field measurements? How useful are the measures of NPP for evaluating model predictions? How well do models represent regional patterns of NPP? Initial EMDI results showed general agreement between model predictions and field measurements but with obvious differences that indicated areas for potential data and model improvement. The effort was built on the development and compilation of complete and consistent databases for model initialization and comparison. Database development improves the data as well as models; however, there is a need to incorporate additional observations and model outputs (LAI, hydrology, etc.) for comprehensive analyses of biogeochemical processes and their relationships to ecosystem structure and function. EMDI initialization and NPP data sets are available from the Oak Ridge National Laboratory Distributed Active Archive Center http://www.daac.ornl.gov/. Acknowledgements: This work was partially supported by the International Geosphere-Biosphere Programme - Data and Information System (IGBP-DIS); the IGBP-Global Analysis, Interpretation and Modelling Task Force (GAIM); the National Center for Ecological Analysis and Synthesis (NCEAS); and the National Aeronautics and Space Administration (NASA) Terrestrial Ecosystem Program. Oak Ridge National Laboratory is managed by UT-Battelle LLC for the U.S. Department of Energy under contract DE-AC05-00OR22725