Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

PubMed Central

Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.

2010-01-01

Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. PMID:21124927

Mining local climate data to assess spatiotemporal dengue fever epidemic patterns in French Guiana

PubMed Central

Flamand, Claude; Fabregue, Mickael; Bringay, Sandra; Ardillon, Vanessa; Quénel, Philippe; Desenclos, Jean-Claude; Teisseire, Maguelonne

2014-01-01

Objective To identify local meteorological drivers of dengue fever in French Guiana, we applied an original data mining method to the available epidemiological and climatic data. Through this work, we also assessed the contribution of the data mining method to the understanding of factors associated with the dissemination of infectious diseases and their spatiotemporal spread. Methods We applied contextual sequential pattern extraction techniques to epidemiological and meteorological data to identify the most significant climatic factors for dengue fever, and we investigated the relevance of the extracted patterns for the early warning of dengue outbreaks in French Guiana. Results The maximum temperature, minimum relative humidity, global brilliance, and cumulative rainfall were identified as determinants of dengue outbreaks, and the precise intervals of their values and variations were quantified according to the epidemiologic context. The strongest significant correlations were observed between dengue incidence and meteorological drivers after a 4–6-week lag. Discussion We demonstrated the use of contextual sequential patterns to better understand the determinants of the spatiotemporal spread of dengue fever in French Guiana. Future work should integrate additional variables and explore the notion of neighborhood for extracting sequential patterns. Conclusions Dengue fever remains a major public health issue in French Guiana. The development of new methods to identify such specific characteristics becomes crucial in order to better understand and control spatiotemporal transmission. PMID:24549761

Response of North Atlantic Ocean Chlorophyll a to the Change of Atlantic Meridional Overturning Circulation

NASA Astrophysics Data System (ADS)

Zhang, Min; Zhang, Yuanling; Shu, Qi; Zhao, Chang; Wang, Gang; Wu, Zhaohua; Qiao, Fangli

2017-04-01

Changes in marine phytoplankton are a vital component in global carbon cycling. Despite this far-reaching importance, the variable trend in phytoplankton and its response to climate variability remain unclear. This work presents the spatiotemporal evolution of the chlorophyll a trend in the North Atlantic Ocean by using merged ocean color products for the period 1997-2016. We find a dipole pattern between the subpolar gyre and the Gulf Stream path,and chlorophyll a trend signal propagatedalong the opposite direction of the North Atlantic Current. Such a dipole pattern and opposite propagation of chlorophyll a signal are consistent with the recent distinctive signature of the slowdown of the Atlantic MeridionalOverturning Circulation (AMOC). It is suggested that the spatiotemporal evolution of chlorophyll a during the two most recent decades is a part of the multidecadal variation and regulated byAMOC, which could be used as an indicator of AMOC variations.

Modeling the spatio-temporal heterogeneity in the PM10-PM2.5 relationship

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Huang, Bo; Lin, Chuan-Yao

2015-02-01

This paper explores the spatio-temporal patterns of particulate matter (PM) in Taiwan based on a series of methods. Using fuzzy c-means clustering first, the spatial heterogeneity (six clusters) in the PM data collected between 2005 and 2009 in Taiwan are identified and the industrial and urban areas of Taiwan (southwestern, west central, northwestern, and northern Taiwan) are found to have high PM concentrations. The PM10-PM2.5 relationship is then modeled with global ordinary least squares regression, geographically weighted regression (GWR), and geographically and temporally weighted regression (GTWR). The GTWR and GWR produce consistent results; however, GTWR provides more detailed information of spatio-temporal variations of the PM10-PM2.5 relationship. The results also show that GTWR provides a relatively high goodness of fit and sufficient space-time explanatory power. In particular, the PM2.5 or PM10 varies with time and space, depending on weather conditions and the spatial distribution of land use and emission patterns in local areas. Such information can be used to determine patterns of spatio-temporal heterogeneity in PM that will allow the control of pollutants and the reduction of public exposure.

Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon

PubMed Central

Putman, Nathan F.; Jenkins, Erica S.; Michielsens, Catherine G. J.; Noakes, David L. G.

2014-01-01

Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. PMID:25056214

Spatio-temporal Analysis for New York State SPARCS Data

PubMed Central

Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng

2017-01-01

Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148

Distributional patterns in an insect community inhabiting a sandy beach of Uruguay

NASA Astrophysics Data System (ADS)

Mourglia, Virginia; González-Vainer, Patricia; Defeo, Omar

2015-12-01

Most studies of sandy beach macrofauna have been restricted to semiterrestrial species and do not include insects when providing species richness and abundance estimates. Particularly, spatio-temporal patterns of community structure of the entomofauna inhabiting these ecosystems have been scarcely documented. This study assessed spatio-temporal distributional patterns of the night active entomofauna on a beach-dune system of Uruguay, including variations in species richness, abundance and diversity, and their relationship with environmental factors. A deconstructive taxonomic analysis was also performed, considering richness and abundance patterns separately for the most abundant insect Orders (Hymenoptera and Coleoptera) to better understand the factors which drive their patterns. We found clear temporal and across-shore patterns in the insect community inhabiting a land-ocean interface, which matched spatiotemporal variations in the environment. Abundance and species richness were highest in spring and summer, concurrently with high temperatures and low values of sediment moisture and compaction. Multivariate ordinations showed two well-defined species groups, which separated summer, autumn and spring samples from winter ones. Generalized Linear Models allowed us to describe a clear segregation in space of the most important orders of the insect community, with specific preferences for the terrestrial (Hymenoptera) and beach (Coleoptera) fringes. Hymenoptera preferred the dune zone, characterized by high elevation and low sand moisture and compaction levels, whereas Coleoptera preferred gentle slopes and fine and humid sands of the beach. Our results suggest that beach and dune ecosystems operate as two separate components in regard to their physical and biological features. The high values of species richness and abundance of insects reveal that this group has a more significant ecological role than that originally considered so far in sandy beach ecology.

Spatiotemporal evolution of the chlorophyll a trend in the North Atlantic Ocean.

PubMed

Zhang, Min; Zhang, Yuanling; Shu, Qi; Zhao, Chang; Wang, Gang; Wu, Zhaohua; Qiao, Fangli

2018-01-15

Analyses of the chlorophyll a concentration (chla) from satellite ocean color products have suggested the decadal-scale variability of chla linked to the climate change. The decadal-scale variability in chla is both spatially and temporally non-uniform. We need to understand the spatiotemporal evolution of chla in decadal or multi-decadal timescales to better evaluate its linkage to climate variability. Here, the spatiotemporal evolution of the chla trend in the North Atlantic Ocean for the period 1997-2016 is analyzed using the multidimensional ensemble empirical mode decomposition method. We find that this variable trend signal of chla shows a dipole pattern between the subpolar gyre and along the Gulf Stream path, and propagation along the opposite direction of the North Atlantic Current. This propagation signal has an overlapping variability of approximately twenty years. Our findings suggest that the spatiotemporal evolution of chla during the two most recent decades is part of the multidecadal variations and possibly regulated by the changes of Atlantic Meridional Overturning Circulation, whereas the mechanisms of such evolution patterns still need to be explored. Copyright © 2017 Elsevier B.V. All rights reserved.

Giant panda foraging and movement patterns in response to bamboo shoot growth.

PubMed

Zhang, Mingchun; Zhang, Zhizhong; Li, Zhong; Hong, Mingsheng; Zhou, Xiaoping; Zhou, Shiqiang; Zhang, Jindong; Hull, Vanessa; Huang, Jinyan; Zhang, Hemin

2018-03-01

Diet plays a pivotal role in dictating behavioral patterns of herbivorous animals, particularly specialist species. The giant panda (Ailuropoda melanoleuca) is well-known as a bamboo specialist. In the present study, the response of giant pandas to spatiotemporal variation of bamboo shoots was explored using field surveys and GPS collar tracking. Results show the dynamics in panda-bamboo space-time relationships that have not been previously articulated. For instance, we found a higher bamboo stump height of foraged bamboo with increasing elevation, places where pandas foraged later in spring when bamboo shoots become more fibrous and woody. The time required for shoots to reach optimum height for foraging was significantly delayed as elevation increased, a pattern which corresponded with panda elevational migration patterns beginning from the lower elevational end of Fargesia robusta distribution and gradually shifting upward until the end of the shooting season. These results indicate that giant pandas can respond to spatiotemporal variation of bamboo resources, such as available shoots. Anthropogenic interference of low-elevation F. robusta habitat should be mitigated, and conservation attention and increased monitoring should be given to F. robusta areas at the low- and mid-elevation ranges, particularly in the spring shooting season.

Mining local climate data to assess spatiotemporal dengue fever epidemic patterns in French Guiana.

PubMed

Flamand, Claude; Fabregue, Mickael; Bringay, Sandra; Ardillon, Vanessa; Quénel, Philippe; Desenclos, Jean-Claude; Teisseire, Maguelonne

2014-10-01

To identify local meteorological drivers of dengue fever in French Guiana, we applied an original data mining method to the available epidemiological and climatic data. Through this work, we also assessed the contribution of the data mining method to the understanding of factors associated with the dissemination of infectious diseases and their spatiotemporal spread. We applied contextual sequential pattern extraction techniques to epidemiological and meteorological data to identify the most significant climatic factors for dengue fever, and we investigated the relevance of the extracted patterns for the early warning of dengue outbreaks in French Guiana. The maximum temperature, minimum relative humidity, global brilliance, and cumulative rainfall were identified as determinants of dengue outbreaks, and the precise intervals of their values and variations were quantified according to the epidemiologic context. The strongest significant correlations were observed between dengue incidence and meteorological drivers after a 4-6-week lag. We demonstrated the use of contextual sequential patterns to better understand the determinants of the spatiotemporal spread of dengue fever in French Guiana. Future work should integrate additional variables and explore the notion of neighborhood for extracting sequential patterns. Dengue fever remains a major public health issue in French Guiana. The development of new methods to identify such specific characteristics becomes crucial in order to better understand and control spatiotemporal transmission. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon.

PubMed

Putman, Nathan F; Jenkins, Erica S; Michielsens, Catherine G J; Noakes, David L G

2014-10-06

Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Climate-mediated spatiotemporal variability in the terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Mahecha, M. D.; Reichstein, M.; Ciais, P.; Wattenbach, M.; Babst, F.; Frank, D.; Zang, C.

2013-11-01

Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a~temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems.

Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy.

PubMed

Yu, Zhoulu; Wang, Yaohui; Deng, Jinsong; Shen, Zhangquan; Wang, Ke; Zhu, Jinxia; Gan, Muye

2017-06-06

Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heterogeneous urban environments. This paper uses the city of Hangzhou to demonstrate an analysis methodology that integrates sub-pixel mapping technology and landscape analysis to fully investigate the spatiotemporal pattern and variation of hierarchical urban green space patches. Firstly, multiple endmember spectral mixture analysis was applied to time series Landsat data to derive green space coverage at the sub-pixel level. Landscape metric analysis was then employed to characterize the variation pattern of urban green space patches. Results indicate that Hangzhou has experienced a significant loss of urban greenness, producing a more fragmented and isolated vegetation landscape. Additionally, a remarkable amelioration of urban greenness occurred in the city core from 2002 to 2013, characterized by the significant increase of small-sized green space patches. The green space network has been formed as a consequence of new urban greening strategies in Hangzhou. These strategies have greatly fragmented the built-up areas and enriched the diversity of the urban landscape. Gradient analysis further revealed a distinct pattern of urban green space landscape variation in the process of urbanization. By integrating both sub-pixel mapping technology and landscape analysis, our approach revealed the subtle variation of urban green space patches which are otherwise easy to overlook. Findings from this study will help us to refine our understanding of the evolution of heterogeneous urban environments.

Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy

PubMed Central

Yu, Zhoulu; Wang, Yaohui; Deng, Jinsong; Shen, Zhangquan; Wang, Ke; Zhu, Jinxia; Gan, Muye

2017-01-01

Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heterogeneous urban environments. This paper uses the city of Hangzhou to demonstrate an analysis methodology that integrates sub-pixel mapping technology and landscape analysis to fully investigate the spatiotemporal pattern and variation of hierarchical urban green space patches. Firstly, multiple endmember spectral mixture analysis was applied to time series Landsat data to derive green space coverage at the sub-pixel level. Landscape metric analysis was then employed to characterize the variation pattern of urban green space patches. Results indicate that Hangzhou has experienced a significant loss of urban greenness, producing a more fragmented and isolated vegetation landscape. Additionally, a remarkable amelioration of urban greenness occurred in the city core from 2002 to 2013, characterized by the significant increase of small-sized green space patches. The green space network has been formed as a consequence of new urban greening strategies in Hangzhou. These strategies have greatly fragmented the built-up areas and enriched the diversity of the urban landscape. Gradient analysis further revealed a distinct pattern of urban green space landscape variation in the process of urbanization. By integrating both sub-pixel mapping technology and landscape analysis, our approach revealed the subtle variation of urban green space patches which are otherwise easy to overlook. Findings from this study will help us to refine our understanding of the evolution of heterogeneous urban environments. PMID:28587309

Travelling waves and spatial hierarchies in measles epidemics

NASA Astrophysics Data System (ADS)

Grenfell, B. T.; Bjørnstad, O. N.; Kappey, J.

2001-12-01

Spatio-temporal travelling waves are striking manifestations of predator-prey and host-parasite dynamics. However, few systems are well enough documented both to detect repeated waves and to explain their interaction with spatio-temporal variations in population structure and demography. Here, we demonstrate recurrent epidemic travelling waves in an exhaustive spatio-temporal data set for measles in England and Wales. We use wavelet phase analysis, which allows for dynamical non-stationarity-a complication in interpreting spatio-temporal patterns in these and many other ecological time series. In the pre-vaccination era, conspicuous hierarchical waves of infection moved regionally from large cities to small towns; the introduction of measles vaccination restricted but did not eliminate this hierarchical contagion. A mechanistic stochastic model suggests a dynamical explanation for the waves-spread via infective `sparks' from large `core' cities to smaller `satellite' towns. Thus, the spatial hierarchy of host population structure is a prerequisite for these infection waves.

Climate-mediated spatiotemporal variability in terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Babst, F.; Ciais, P.; Frank, D.; Reichstein, M.; Wattenbach, M.; Zang, C.; Mahecha, M. D.

2014-06-01

Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from impacts of other mechanisms underlying the spatiotemporal patterns of IAV of the ecosystem productivity. In this study we investigated the spatiotemporal patterns of IAV of historical observations of European crop yields in tandem with a set of climate variables. We further evaluated if relevant remote-sensing retrievals of NDVI (normalized difference vegetation index) and FAPAR (fraction of absorbed photosynthetically active radiation) depict a similar behaviour. Our results reveal distinct spatial patterns in the IAV of the analysed proxies linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions in both crop yield and remote-sensing observations. Our results further indicate that variations in the water balance during the active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity-related variables in temperate Europe. Overall, we observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe during the 1975-2009 period. In the same regions, a simultaneous increase in the IAV of water availability was detected. These findings suggest intricate responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become potentially more sensitive to changes in water availability in the dry regions in Europe. The changing sensitivity of terrestrial productivity accompanied by the changing IAV of climate is expected to impact carbon stocks and the net carbon balance of European ecosystems.

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA.

PubMed

Cao, Xiaodong; MacNaughton, Piers; Deng, Zhengyi; Yin, Jie; Zhang, Xi; Allen, Joseph G

2018-02-02

Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users' sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions.

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA

PubMed Central

MacNaughton, Piers; Deng, Zhengyi; Yin, Jie; Zhang, Xi; Allen, Joseph G.

2018-01-01

Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users’ sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions. PMID:29393869

Stock-specific advection of larval walleye (Sander vitreus) in western Lake Erie: Implications for larval growth, mixing, and stock discrimination

USGS Publications Warehouse

Fraker, Michael E.; Anderson, Eric J.; May, Cassandra J.; Chen, Kuan-Yu; Davis, Jeremiah J.; DeVanna, Kristen M.; DuFour, Mark R.; Marschall, Elizabeth A.; Mayer, Christine M.; Miner, Jeffery G.; Pangle, Kevin L.; Pritt, Jeremy J.; Roseman, Edward F.; Tyson, Jeffrey T.; Zhao, Yingming; Ludsin, Stuart A

2015-01-01

Physical processes can generate spatiotemporal heterogeneity in habitat quality for fish and also influence the overlap of pre-recruit individuals (e.g., larvae) with high-quality habitat through hydrodynamic advection. In turn, individuals from different stocks that are produced in different spawning locations or at different times may experience dissimilar habitat conditions, which can underlie within- and among-stock variability in larval growth and survival. While such physically-mediated variation has been shown to be important in driving intra- and inter-annual patterns in recruitment in marine ecosystems, its role in governing larval advection, growth, survival, and recruitment has received less attention in large lake ecosystems such as the Laurentian Great Lakes. Herein, we used a hydrodynamic model linked to a larval walleye (Sander vitreus) individual-based model to explore how the timing and location of larval walleye emergence from several spawning sites in western Lake Erie (Maumee, Sandusky, and Detroit rivers; Ohio reef complex) can influence advection pathways and mixing among these local spawning populations (stocks), and how spatiotemporal variation in thermal habitat can influence stock-specific larval growth. While basin-wide advection patterns were fairly similar during 2011 and 2012, smaller scale advection patterns and the degree of stock mixing varied both within and between years. Additionally, differences in larval growth were evident among stocks and among cohorts within stocks which were attributed to spatiotemporal differences in water temperature. Using these findings, we discuss the value of linked physical–biological models for understanding the recruitment process and addressing fisheries management problems in the world's Great Lakes.

Spatiotemporal patterns of fire-induced forest mortality in boreal regions and its potential drivers

NASA Astrophysics Data System (ADS)

Yang, J.; Tian, H.; Pan, S.; Hansen, M.; Wang, Y.

2017-12-01

Wildfire is the major natural disturbance in boreal forests, which have substantially affected various biological and biophysical processes. Although a few previous studies examined fire severity in boreal regions and reported a higher fire-induced forest mortality in boreal North America than in boreal Eurasia, it remains unclear how this mortality changes over time and how environmental factors affect the temporal dynamics of mortality at a large scale. By using a combination of multiple sources of satellite observations, we investigate the spatiotemporal patterns of fire-induced forest mortality in boreal regions, and examine the contributions of potential drivers. Our results show that forest composition is the key factor influencing the spatial variations of fire mortality across ecoregions. For the temporal variations, we find that the late-season burning was associated with higher fire intensity, which lead to greater forest mortality than the early-season burning. Forests burned in the warm and dry years had greater mortality than those burned in the cool and wet years. Our findings suggest that climate warming and drying not only stimulated boreal fire frequency, but also enhanced fire severity and forest mortality. Due to the significant effects of forest mortality on vegetation structure and ecosystem carbon dynamics, the spatiotemporal changes of fire-induced forest mortality should be explicitly considered to better understand fire impacts on regional and global climate change.

Allergenic pollen season variations in the past two decades under changing climate in the United States

PubMed Central

Zhang, Yong; Bielory, Leonard; Mi, Zhongyuan; Cai, Ting; Robock, Alan; Georgopoulos, Panos

2014-01-01

Many diseases are linked with climate trends and variations. In particular, climate change is expected to alter the spatiotemporal dynamics of allergenic airborne pollen and potentially increase occurrence of allergic airway disease. Understanding the spatiotemporal patterns of changes in pollen season timing and levels is thus important in assessing climate impacts on aerobiology and allergy caused by allergenic airborne pollen. Here we describe the spatiotemporal patterns of changes in the seasonal timing and levels of allergenic airborne pollen for multiple taxa in different climate regions at a continental scale. The allergenic pollen seasons of representative trees, weeds and grass during the past decade (2001–2010) across the contiguous United States have been observed to start 3.0 (95% Confidence Interval (CI), 1.1–4.9) days earlier on average than in the 1990s (1994–2000). The average peak value and annual total of daily counted airborne pollen have increased by 42.4% (95% CI, 21.9%–62.9%) and 46.0% (95% CI, 21.5%–70.5%), respectively. Changes of pollen season timing and airborne levels depend on latitude, and are associated with changes of growing degree days, frost free days, and precipitation. These changes are likely due to recent climate change and particularly the enhanced warming and precipitation at higher latitudes in the contiguous United States. PMID:25266307

Are species photosynthetic characteristics good predictors of seedling post-hurricane demographic patterns and species spatiotemporal distribution in a hurricane impacted wet montane forest?

NASA Astrophysics Data System (ADS)

Luke, Denneko; McLaren, Kurt

2018-05-01

In situ measurements of leaf level photosynthetic response to light were collected from seedlings of ten tree species from a tropical montane wet forest, the John Crow Mountains, Jamaica. A model-based recursive partitioning ('mob') algorithm was then used to identify species associations based on their fitted photosynthetic response curves. Leaf area dark respiration (RD) and light saturated maximum photosynthetic (Amax) rates were also used as 'mob' partitioning variables, to identify species associations based on seedling demographic patterns (from June 2007 to May 2010) following a hurricane (Aug. 2007) and the spatiotemporal distribution patterns of stems in 2006 and 2012. RD and Amax rates ranged from 1.14 to 2.02 μmol (CO2) m-2s-1 and 2.97-5.87 μmol (CO2) m-2s-1, respectively, placing the ten species in the range of intermediate shade tolerance. Several parsimonious species 'mob' groups were formed based on 1) interspecific differences among species response curves, 2) variations in post-hurricane seedling demographic trends and 3) RD rates and species spatiotemporal distribution patterns at aspects that are more or less exposed to hurricanes. The composition of parsimonious groupings based on photosynthetic curves was not concordant with the groups based on demographic trends but was partially concordant with the RD - species spatiotemporal distribution groups. Our results indicated that the influence of photosynthetic characteristics on demographic traits and species distributions was not straightforward. Rather, there was a complex pattern of interaction between ecophysiological and demographic traits, which determined species successional status, post-hurricane response and ultimately, species distribution at our study site.

Spatio-temporal variation in stream water chemistry in a tropical urban watershed

Treesearch

A. Ramirez; K.G. Rosas; A.E. Lugo; O.M. Ramos-Gonzalez

2014-01-01

Urban activities and related infrastructure alter the natural patterns of stream physical and chemical conditions. According to the Urban Stream Syndrome, streams draining urban landscapes are characterized by high concentrations of nutrients and ions, and might have elevated water temperatures and variable oxygen concentrations. Here, we report temporal and spatial...

Spatio-temporal Patterns of Vegetation and Its Relationship with Precipitation and Temperature in the Yarlung Zangbo River Basin, China

NASA Astrophysics Data System (ADS)

LIU, X.; Xu, Z.; Peng, D.

2017-12-01

Vegetation growth plays a significant role on runoff variation at high altitude, and precipitation and temperature are both key factors affecting vegetation conditions. As one of the greatest international rivers in China, the Yarlung Zangbo River in the southern Qinghai-Tibetan Plateau was selected, and the spatio-temporal patterns of vegetation were analyzed by using NDVI (Normalized Difference Vegetation Index) during 1998 2014. The relationship between NDVI and precipitation as well as temperature was also investigated in this study. Results showed that the value of NDVI increases with the decrease of elevation and the largest value appears in the broadleaf forest cover. Almost all annual NDVI variations exhibit an increasing tendency, particularly for the broadleaf forest cover. On the viewpoint of statistics, only 29% pixels of NDVI with increasing tendency are of significance for the other cover, while for cultivated vegetation cover, around 82% pixels of NDVI were detected with significant increasing tendency. In addition, vegetation growth showed lagging response to precipitation, and the lag time is around one month. Moreover, in the region with elevation over 5000 m, negative relationship between NDVI and precipitation for alpine vegetation was found. Approximately 75% of NDVI variations are dominated by precipitation and temperature. These findings may provide a reference to investigate runoff variations and strengthen ecological protection for similar high-altitude areas in the future.

Detecting changes resulting from human pressure in a naturally quick-changing and heterogeneous environment: Spatial and temporal scales of variability in coastal lagoons

NASA Astrophysics Data System (ADS)

Pérez-Ruzafa, A.; Marcos, C.; Pérez-Ruzafa, I. M.; Barcala, E.; Hegazi, M. I.; Quispe, J.

2007-10-01

To detect changes in ecosystems due to human impact, experimental designs must include replicates at the appropriate scale to avoid pseudoreplication. Although coastal lagoons, with their highly variable environmental factors and biological assemblages, are relatively well-studied systems, very little is known about their natural scales of variation. In this study, we investigate the spatio-temporal scales of variability in the Mar Menor coastal lagoon (SE Spain) using structured hierarchical sampling designs, mixed and permutational multi-variate analyses of variance, and ordination multi-variate analyses applied to hydrographical parameters, nutrients, chlorophyll a and ichthyoplankton in the water column, and to macrophyte and fish benthic assemblages. Lagoon processes in the Mar Menor show heterogeneous patterns at different temporal and spatial scales. The water column characteristics (including nutrient concentration) showed small-scale spatio-temporal variability, from 10 0 to 10 1 km and from fortnightly to seasonally. Biological features (chlorophyll a concentration and ichthyoplankton assemblage descriptors) showed monthly changes and spatial patterns at the scale of 10 0 (chlorophyll a) - 10 1 km (ichthyoplankton). Benthic assemblages (macrophytes and fishes) showed significant differences between types of substrates in the same locality and between localities, according to horizontal gradients related with confinement in the lagoon, at the scale of 10 0-10 1 km. The vertical zonation of macrophyte assemblages (at scales of 10 1-10 2 cm) overlaps changes in substrata and horizontal gradients. Seasonal patterns in vegetation biomass were not significant, but the significant interaction between Locality and Season indicated that the seasons of maximum and minimum biomass depend on local environmental conditions. Benthic fish assemblages showed no significant patterns at the monthly scale but did show seasonal patterns.

Spatiotemporal variations in metal accumulation, RNA/DNA ratio and energy reserve in Perna viridis transplanted along a marine pollution gradient in Hong Kong.

PubMed

Yeung, Jamius W Y; Zhou, Guang-Jie; Leung, Kenneth M Y

2017-11-30

We examined spatiotemporal variations of metal levels and three growth related biomarkers, i.e., RNA/DNA ratio (RD), total energy reserve (Et) and condition index (CI), in green-lipped mussels Perna viridis transplanted into five locations along a pollution gradient in the marine environment of Hong Kong over 120days of deployment. There were significant differences in metal levels and biomarker responses among the five sites and six time points. Mussels in two clean sites displayed better CI and significantly lower levels of Ag, Cu, Pb and Zn in their tissues than the other sites. Temporal patterns of RD in P. viridis were found to be site-specific. Across all sites, Et decreased in P. viridis over the deployment period, though the rate of decrease varied significantly among the sites. Therefore, temporal variation of biomarkers should be taken to consideration in mussel-watch programs because such information can help discriminate pollution-induced change from natural variation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Looking for hotspots of marine metacommunity connectivity: a methodological framework

PubMed Central

Melià, Paco; Schiavina, Marcello; Rossetto, Marisa; Gatto, Marino; Fraschetti, Simonetta; Casagrandi, Renato

2016-01-01

Seascape connectivity critically affects the spatiotemporal dynamics of marine metacommunities. Understanding how connectivity patterns emerge from physically and biologically-mediated interactions is therefore crucial to conserve marine ecosystem functions and biodiversity. Here, we develop a set of biophysical models to explore connectivity in assemblages of species belonging to a typical Mediterranean community (Posidonia oceanica meadows) and characterized by different dispersing traits. We propose a novel methodological framework to synthesize species-specific results into a set of community connectivity metrics and show that spatiotemporal variation in magnitude and direction of the connections, as well as interspecific differences in dispersing traits, are key factors structuring community connectivity. We eventually demonstrate how these metrics can be used to characterize the functional role of each marine area in determining patterns of community connectivity at the basin level and to support marine conservation planning. PMID:27029563

Dynamical mechanisms for skeletal pattern formation in the vertebrate limb.

PubMed Central

Hentschel, H. G. E.; Glimm, Tilmann; Glazier, James A.; Newman, Stuart A.

2004-01-01

We describe a 'reactor-diffusion' mechanism for precartilage condensation based on recent experiments on chondrogenesis in the early vertebrate limb and additional hypotheses. Cellular differentiation of mesenchymal cells into subtypes with different fibroblast growth factor (FGF) receptors occurs in the presence of spatio-temporal variations of FGFs and transforming growth factor-betas (TGF-betas). One class of differentiated cells produces elevated quantities of the extracellular matrix protein fibronectin, which initiates adhesion-mediated preskeletal mesenchymal condensation. The same class of cells also produces an FGF-dependent laterally acting inhibitor that keeps condensations from expanding beyond a critical size. We show that this 'reactor-diffusion' mechanism leads naturally to patterning consistent with skeletal form, and describe simulations of spatio-temporal distribution of these differentiated cell types and the TGF-beta and inhibitor concentrations in the developing limb bud. PMID:15306292

Looking for hotspots of marine metacommunity connectivity: a methodological framework

NASA Astrophysics Data System (ADS)

Melià, Paco; Schiavina, Marcello; Rossetto, Marisa; Gatto, Marino; Fraschetti, Simonetta; Casagrandi, Renato

2016-03-01

Seascape connectivity critically affects the spatiotemporal dynamics of marine metacommunities. Understanding how connectivity patterns emerge from physically and biologically-mediated interactions is therefore crucial to conserve marine ecosystem functions and biodiversity. Here, we develop a set of biophysical models to explore connectivity in assemblages of species belonging to a typical Mediterranean community (Posidonia oceanica meadows) and characterized by different dispersing traits. We propose a novel methodological framework to synthesize species-specific results into a set of community connectivity metrics and show that spatiotemporal variation in magnitude and direction of the connections, as well as interspecific differences in dispersing traits, are key factors structuring community connectivity. We eventually demonstrate how these metrics can be used to characterize the functional role of each marine area in determining patterns of community connectivity at the basin level and to support marine conservation planning.

Moisture as a determinant of habitat quality for a nonbreeding Neotropical migratory songbird

Treesearch

Joseph A.M. Smith; Leonard R. Reitsma; Peter P. Marra

2010-01-01

Identifying the determinants of habitat quality for a species is essential for understanding how populations are limited and regulated. Spatiotemporal variation in moisture and its influence on food availability may drive patterns of habitat occupancy and demographic outcomes. Nonbreeding migratory birds in the neotropics occupy a range of habitat types that vary with...

[Mortality from Suicide in the Municipalities of Mainland Portugal: Spatio-Temporal Evolution between 1980 and 2015].

PubMed

Loureiro, Adriana; Almendra, Ricardo; Costa, Cláudia; Santana, Paula

2018-01-31

Suicide is considered a public health priority. It is a complex phenomenon resulting from the interaction of several factors, which do not depend solely on individual conditions. This study analyzes the spatio-temporal evolution of suicide mortality between 1980 and 2015, identifying areas of high risk, and their variation, in the 278 municipalities of Continental Portugal. Based on the number of self-inflicted injuries and deaths from suicide and the resident population, the spatio-temporal evolution of the suicide mortality rate was assessed via: i) a Poisson joinpoint regression model, and ii) spatio-temporal clustering methods. The suicide mortality rate evolution showed statistically significant increases over three periods (1980 - 1984; 1999 - 2002 and 2006 - 2015) and two statistically significant periods of decrease (1984 - 1995 and 1995 - 1999). The spatio-temporal analysis identified five clusters of high suicide risk (relative risk >1) and four clusters of low suicide risk (relative risk < 1). The periods when suicide mortality increases seem to overlap with times of economic and financial instability. The geographical pattern of suicide risk has changed: presently, the suicide rates from the municipalities in the Center and North are showing more similarity with those seen in the South, thus increasing the ruralization of the phenomenon of suicide. Between 1980 and 2015 the spacio-temporal pattern of mortality from suicide has been changing and is a phenomenon that is currently experiencing a growing trend (since 2006) and is of higher risk in rural areas.

Effects of land cover and regional climate variations on long-term spatiotemporal changes in sagebrush ecosystems

USGS Publications Warehouse

Xian, George Z.; Homer, Collin G.; Aldridge, Cameron L.

2012-01-01

This research investigated the effects of climate and land cover change on variation in sagebrush ecosystems. We combined information of multi-year sagebrush distribution derived from multitemporal remote sensing imagery and climate data to study the variation patterns of sagebrush ecosystems under different potential disturbances. We found that less than 40% of sagebrush ecosystem changes involved abrupt changes directly caused by landscape transformations and over 60% of the variations involved gradual changes directly related to climatic perturbations. The primary increases in bare ground and declines in sagebrush vegetation abundance were significantly correlated with the 1996-2006 decreasing trend in annual precipitation.

A BAYESIAN SPATIAL AND TEMPORAL MODELING APPROACH TO MAPPING GEOGRAPHIC VARIATION IN MORTALITY RATES FOR SUBNATIONAL AREAS WITH R-INLA.

PubMed

Khana, Diba; Rossen, Lauren M; Hedegaard, Holly; Warner, Margaret

2018-01-01

Hierarchical Bayes models have been used in disease mapping to examine small scale geographic variation. State level geographic variation for less common causes of mortality outcomes have been reported however county level variation is rarely examined. Due to concerns about statistical reliability and confidentiality, county-level mortality rates based on fewer than 20 deaths are suppressed based on Division of Vital Statistics, National Center for Health Statistics (NCHS) statistical reliability criteria, precluding an examination of spatio-temporal variation in less common causes of mortality outcomes such as suicide rates (SRs) at the county level using direct estimates. Existing Bayesian spatio-temporal modeling strategies can be applied via Integrated Nested Laplace Approximation (INLA) in R to a large number of rare causes of mortality outcomes to enable examination of spatio-temporal variations on smaller geographic scales such as counties. This method allows examination of spatiotemporal variation across the entire U.S., even where the data are sparse. We used mortality data from 2005-2015 to explore spatiotemporal variation in SRs, as one particular application of the Bayesian spatio-temporal modeling strategy in R-INLA to predict year and county-specific SRs. Specifically, hierarchical Bayesian spatio-temporal models were implemented with spatially structured and unstructured random effects, correlated time effects, time varying confounders and space-time interaction terms in the software R-INLA, borrowing strength across both counties and years to produce smoothed county level SRs. Model-based estimates of SRs were mapped to explore geographic variation.

Spatio-temporal patterns and source apportionment of pollution in Qiantang River (China) using neural-based modeling and multivariate statistical techniques

NASA Astrophysics Data System (ADS)

Su, Shiliang; Zhi, Junjun; Lou, Liping; Huang, Fang; Chen, Xia; Wu, Jiaping

Characterizing the spatio-temporal patterns and apportioning the pollution sources of water bodies are important for the management and protection of water resources. The main objective of this study is to describe the dynamics of water quality and provide references for improving river pollution control practices. Comprehensive application of neural-based modeling and different multivariate methods was used to evaluate the spatio-temporal patterns and source apportionment of pollution in Qiantang River, China. Measurement data were obtained and pretreated for 13 variables from 41 monitoring sites for the period of 2001-2004. A self-organizing map classified the 41 monitoring sites into three groups (Group A, B and C), representing different pollution characteristics. Four significant parameters (dissolved oxygen, biochemical oxygen demand, total phosphorus and total lead) were identified by discriminant analysis for distinguishing variations of different years, with about 80% correct assignment for temporal variation. Rotated principal component analysis (PCA) identified four potential pollution sources for Group A (domestic sewage and agricultural pollution, industrial wastewater pollution, mineral weathering, vehicle exhaust and sand mining), five for Group B (heavy metal pollution, agricultural runoff, vehicle exhaust and sand mining, mineral weathering, chemical plants discharge) and another five for Group C (vehicle exhaust and sand mining, chemical plants discharge, soil weathering, biochemical pollution, mineral weathering). The identified potential pollution sources explained 75.6% of the total variances for Group A, 75.0% for Group B and 80.0% for Group C, respectively. Receptor-based source apportionment was applied to further estimate source contributions for each pollution variable in the three groups, which facilitated and supported the PCA results. These results could assist managers to develop optimal strategies and determine priorities for river pollution control and effective water resources management.

The effect of long-term spatiotemporal variations in urbanization-induced eutrophication on a benthic ecosystem, Osaka Bay, Japan

USGS Publications Warehouse

Yasuhara, Moriaki; Yamazaki, Hideo; Tsujimoto, Akira; Hirose, K.

2007-01-01

Detailed spatiotemporal patterns of the influence of urbanization-induced eutrophication on a metazoan benthic community in Osaka Bay were determined using sediment cores and fossil ostracode assemblages from the last 200 yr. Results suggest that total abundance of ostracodes increased in the middle part of the bay as a result of the increase of food supply by eutrophication. Conversely, abundance decreased in the inner bay, likely because of bottom-water hypoxia by eutrophication. The variation in species composition among sites within the bay may have decreased because of the effect of eutrophication, i.e., the dominance of species that prefer food-rich environments throughout all sites. These eutrophication-induced changes occurred around 1900 as a result of Japan's industrial revolution and around 1960 as a result of rapid urbanization, depending upon location. ?? 2007, by the American Society of Limnology and Oceanography, Inc.

Understanding human activity patterns based on space-time-semantics

NASA Astrophysics Data System (ADS)

Huang, Wei; Li, Songnian

2016-11-01

Understanding human activity patterns plays a key role in various applications in an urban environment, such as transportation planning and traffic forecasting, urban planning, public health and safety, and emergency response. Most existing studies in modeling human activity patterns mainly focus on spatiotemporal dimensions, which lacks consideration of underlying semantic context. In fact, what people do and discuss at some places, inferring what is happening at the places, cannot be simple neglected because it is the root of human mobility patterns. We believe that the geo-tagged semantic context, representing what individuals do and discuss at a place and a specific time, drives a formation of specific human activity pattern. In this paper, we aim to model human activity patterns not only based on space and time but also with consideration of associated semantics, and attempt to prove a hypothesis that similar mobility patterns may have different motivations. We develop a spatiotemporal-semantic model to quantitatively express human activity patterns based on topic models, leading to an analysis of space, time and semantics. A case study is conducted using Twitter data in Toronto based on our model. Through computing the similarities between users in terms of spatiotemporal pattern, semantic pattern and spatiotemporal-semantic pattern, we find that only a small number of users (2.72%) have very similar activity patterns, while the majority (87.14%) show different activity patterns (i.e., similar spatiotemporal patterns and different semantic patterns, similar semantic patterns and different spatiotemporal patterns, or different in both). The population of users that has very similar activity patterns is decreased by 56.41% after incorporating semantic information in the corresponding spatiotemporal patterns, which can quantitatively prove the hypothesis.

Spatiotemporal patterns of infant bronchiolitis in a Tennessee Medicaid population.

PubMed

Sloan, Chantel D; Gebretsadik, Tebeb; Wu, Pingsheng; Carroll, Kecia N; Mitchel, Edward F; Hartert, Tina V

2013-09-01

Respiratory syncytial virus (RSV) is a major cause of worldwide morbidity and mortality in infants, primarily through the induction of bronchiolitis. RSV epidemics are highly seasonal, occurring in the winter months in the northern hemisphere. Within the United States, RSV epidemic dynamics vary both spatially and temporally. This analysis employs a retrospective space–time scan statistic to locate spatiotemporal clustering of infant bronchiolitis in a very large Tennessee (TN) Medicaid cohort. We studied infants less than 6 months of age (N = 52,468 infants) who had an outpatient visit, emergency department visit, or hospitalization for bronchiolitis between 1995 and 2008. The scan statistic revealed distinctive and consistent patterns of deviation in epidemic timing. Eastern TN (Knoxville area) showed clustering in January and February, and Central TN (Nashville area) in November and December. This is likely due to local variation in geography-associated factors which should be taken into consideration in future modeling of RSV epidemics.

Land surface phenological responses to land use and climate variation in a changing Central Asia

NASA Astrophysics Data System (ADS)

Kariyeva, Jahan

During the last few decades Central Asia has experienced widespread changes in land cover and land use following the socio-economic and institutional transformations of the region catalyzed by the USSR collapse in 1991. The decade-long drought events and steadily increasing temperature regimes in the region came on top of these institutional transformations, affecting the long term and landscape scale vegetation responses. This research is based on the need to better understand the potential ecological and policy implications of climate variation and land use practices in the contexts of landscape-scale changes dynamics and variability patterns of land surface phenology responses in Central Asia. The land surface phenology responses -- the spatio-temporal dynamics of terrestrial vegetation derived from the remotely sensed data -- provide measurements linked to the timing of vegetation growth cycles (e.g., start of growing season) and total vegetation productivity over the growing season, which are used as a proxy for the assessment of effects of variations in environmental settings. Local and regional scale assessment of the before and after the USSR collapse vegetation response patterns in the natural and agricultural systems of the Central Asian drylands was conducted to characterize newly emerging links (since 1991) between coupled human and natural systems, e.g., socio-economic and policy drivers of altered land and water use and distribution patterns. Spatio-temporal patterns of bioclimatic responses were examined to determine how phenology is associated with temperature and precipitation in different land use types, including rainfed and irrigated agricultural types. Phenological models were developed to examine relationship between environmental drivers and effect of their altitudinal and latitudinal gradients on the broad-scale vegetation response patterns in non-cropland ecosystems of the desert, steppe, and mountainous regional landscapes of Central Asia. The study results demonstrated that the satellite derived measurements of temporal cycles of vegetation greenness and productivity data was a valuable bioclimatic integrator of climatic and land use variation in Central Asia. The synthesis of broad-scale phenological changes in Central Asia showed that linkages of natural and human systems vary across space and time comprising complex and tightly integrated patterns and processes that are not evident when studied separately.

Variability in primary productivity determines metapopulation dynamics

PubMed Central

2016-01-01

Temporal variability in primary productivity can change habitat quality for consumer species by affecting the energy levels available as food resources. However, it remains unclear how habitat-quality fluctuations may determine the dynamics of spatially structured populations, where the effects of habitat size, quality and isolation have been customarily assessed assuming static habitats. We present the first empirical evaluation on the effects of stochastic fluctuations in primary productivity—a major outcome of ecosystem functions—on the metapopulation dynamics of a primary consumer. A unique 13-year dataset from an herbivore rodent was used to test the hypothesis that inter-annual variations in primary productivity determine spatiotemporal habitat occupancy patterns and colonization and extinction processes. Inter-annual variability in productivity and in the growing season phenology significantly influenced habitat colonization patterns and occupancy dynamics. These effects lead to changes in connectivity to other potentially occupied habitat patches, which then feed back into occupancy dynamics. According to the results, the dynamics of primary productivity accounted for more than 50% of the variation in occupancy probability, depending on patch size and landscape configuration. Evidence connecting primary productivity dynamics and spatiotemporal population processes has broad implications for metapopulation persistence in fluctuating and changing environments. PMID:27053739

Variability in primary productivity determines metapopulation dynamics.

PubMed

Fernández, Néstor; Román, Jacinto; Delibes, Miguel

2016-04-13

Temporal variability in primary productivity can change habitat quality for consumer species by affecting the energy levels available as food resources. However, it remains unclear how habitat-quality fluctuations may determine the dynamics of spatially structured populations, where the effects of habitat size, quality and isolation have been customarily assessed assuming static habitats. We present the first empirical evaluation on the effects of stochastic fluctuations in primary productivity--a major outcome of ecosystem functions--on the metapopulation dynamics of a primary consumer. A unique 13-year dataset from an herbivore rodent was used to test the hypothesis that inter-annual variations in primary productivity determine spatiotemporal habitat occupancy patterns and colonization and extinction processes. Inter-annual variability in productivity and in the growing season phenology significantly influenced habitat colonization patterns and occupancy dynamics. These effects lead to changes in connectivity to other potentially occupied habitat patches, which then feed back into occupancy dynamics. According to the results, the dynamics of primary productivity accounted for more than 50% of the variation in occupancy probability, depending on patch size and landscape configuration. Evidence connecting primary productivity dynamics and spatiotemporal population processes has broad implications for metapopulation persistence in fluctuating and changing environments. © 2016 The Authors.

Spatio-temporal variations in the diversity and abundance of commercially important Decapoda and Stomatopoda in subtropical Hong Kong waters

NASA Astrophysics Data System (ADS)

Lui, Karen K. Y.; Ng, Jasmine S. S.; Leung, Kenneth M. Y.

2007-05-01

In subtropical Hong Kong, western waters (WW) are strongly influenced by the freshwater input from the Pearl River estuary, especially during summer monsoon, whereas eastern waters (EW) are predominantly influenced by oceanic currents throughout the year. Such hydrographical differences may lead to spatio-temporal differences in biodiversity of benthic communities. This study investigated the diversity and abundance of commercially important decapods and stomatopods in EW (i.e. Tolo Harbour and Channel) and WW (i.e. Tuen Mun and Lantau Island) of Hong Kong using monthly trawl surveys (August 2003-May 2005). In total, 22 decapod and nine stomatopod species were recorded. The penaeid Metapenaeopsis sp. and stomatopod Oratosquillina interrupta were the most abundant and dominant crustaceans in EW and WW, respectively. Both univariate and multivariate analyses showed that WW supported significantly higher abundance, biomass and diversity of crustaceans than EW, although there were significant between-site and within-site variations in community structure. Higher abundance and biomass of crustaceans were recorded in summer than winter. Such spatio-temporal variations could be explained by differences in the hydrography, environmental conditions and anthropogenic impacts between the two areas. Temporal patterns in the abundance-biomass comparison curves and negative W-statistics suggest that the communities have been highly disturbed in both areas, probably due to anthropogenic activities such as bottom trawling and marine pollution.

Instabilities and spatiotemporal patterns behind predator invasions with nonlocal prey competition.

PubMed

Merchant, Sandra M; Nagata, Wayne

2011-12-01

We study the influence of nonlocal intraspecies prey competition on the spatiotemporal patterns arising behind predator invasions in two oscillatory reaction-diffusion integro-differential models. We use three common types of integral kernels as well as develop a caricature system, to describe the influence of the standard deviation and kurtosis of the kernel function on the patterns observed. We find that nonlocal competition can destabilize the spatially homogeneous state behind the invasion and lead to the formation of complex spatiotemporal patterns, including stationary spatially periodic patterns, wave trains and irregular spatiotemporal oscillations. In addition, the caricature system illustrates how large standard deviation and low kurtosis facilitate the formation of these spatiotemporal patterns. This suggests that nonlocal competition may be an important mechanism underlying spatial pattern formation, particularly in systems where the competition between individuals varies over space in a platykurtic manner. Copyright © 2011 Elsevier Inc. All rights reserved.

The Link between Microbial Diversity and Nitrogen Cycling in Marine Sediments Is Modulated by Macrofaunal Bioturbation

PubMed Central

Yazdani Foshtomi, Maryam; Braeckman, Ulrike; Derycke, Sofie; Sapp, Melanie; Van Gansbeke, Dirk; Sabbe, Koen; Willems, Anne; Vincx, Magda; Vanaverbeke, Jan

2015-01-01

Objectives The marine benthic nitrogen cycle is affected by both the presence and activity of macrofauna and the diversity of N-cycling microbes. However, integrated research simultaneously investigating macrofauna, microbes and N-cycling is lacking. We investigated spatio-temporal patterns in microbial community composition and diversity, macrofaunal abundance and their sediment reworking activity, and N-cycling in seven subtidal stations in the Southern North Sea. Spatio-Temporal Patterns of the Microbial Communities Our results indicated that bacteria (total and β-AOB) showed more spatio-temporal variation than archaea (total and AOA) as sedimentation of organic matter and the subsequent changes in the environment had a stronger impact on their community composition and diversity indices in our study area. However, spatio-temporal patterns of total bacterial and β-AOB communities were different and related to the availability of ammonium for the autotrophic β-AOB. Highest bacterial richness and diversity were observed in June at the timing of the phytoplankton bloom deposition, while richness of β-AOB as well as AOA peaked in September. Total archaeal community showed no temporal variation in diversity indices. Macrofauna, Microbes and the Benthic N-Cycle Distance based linear models revealed that, independent from the effect of grain size and the quality and quantity of sediment organic matter, nitrification and N-mineralization were affected by respectively the diversity of metabolically active β-AOB and AOA, and the total bacteria, near the sediment-water interface. Separate models demonstrated a significant and independent effect of macrofaunal activities on community composition and richness of total bacteria, and diversity indices of metabolically active AOA. Diversity of β-AOB was significantly affected by macrofaunal abundance. Our results support the link between microbial biodiversity and ecosystem functioning in marine sediments, and provided broad correlative support for the hypothesis that this relationship is modulated by macrofaunal activity. We hypothesized that the latter effect can be explained by their bioturbating and bio-irrigating activities, increasing the spatial complexity of the biogeochemical environment. PMID:26102286

Spatiotemporal causal modeling for the management of Dengue Fever

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Huang, Tailin; Lee, Chieh-Han

2015-04-01

Increasing climatic extremes have caused growing concerns about the health effects and disease outbreaks. The association between climate variation and the occurrence of epidemic diseases play an important role on a country's public health systems. Part of the impacts are direct casualties associated with the increasing frequency and intensity of typhoons, the proliferation of disease vectors and the short-term increase of clinic visits on gastro-intestinal discomforts, diarrhea, dermatosis, or psychological trauma. Other impacts come indirectly from the influence of disasters on the ecological and socio-economic systems, including the changes of air/water quality, living environment and employment condition. Previous risk assessment studies on dengue fever focus mostly on climatic and non-climatic factors and their association with vectors' reproducing pattern. The public-health implication may appear simple. Considering the seasonal changes and regional differences, however, the causality of the impacts is full of uncertainties. Without further investigation, the underlying dengue fever risk dynamics may not be assessed accurately. The objective of this study is to develop an epistemic framework for assessing dynamic dengue fever risk across space and time. The proposed framework integrates cross-departmental data, including public-health databases, precipitation data over time and various socio-economic data. We explore public-health issues induced by typhoon through literature review and spatiotemporal analytic techniques on public health databases. From those data, we identify relevant variables and possible causal relationships, and their spatiotemporal patterns derived from our proposed spatiotemporal techniques. Eventually, we create a spatiotemporal causal network and a framework for modeling dynamic dengue fever risk.

[Spatiotemporal variation of soil pH in Guangdong Province of China in past 30 years].

PubMed

Guo, Zhi-Xing; Wang, Jing; Chai, Min; Chen, Ze-Peng; Zhan, Zhen-Shou; Zheng, Wu-Ping; Wei, Xiu-Guo

2011-02-01

Based on the 1980s' soil inventory data and the 2002-2007 soil pH data of Guangdong Province, the spatiotemporal variation of soil pH in the Province in past 30 years was studied. In the study period, the spatial distribution pattern of soil pH in the Province had less change (mainly acidic), except that in Pearl River Delta and parts of Qingyuan and Shaoguan (weak alkaline). The overall variation of soil pH was represented as acidification, with the average pH value changed from 5.70 to 5.44. Among the soil types in the Province, alluvial soil had an increased pH, lateritic red soil, paddy soil, and red soil had a large decrement of pH value, and lime soil was most obvious in the decrease of pH value and its area percentage. The soil acidification was mainly induced by soil characteristics, some natural factors such as acid rain, and human factors such as unreasonable fertilization and urbanization. In addition, industrialization and mining increased the soil pH in some areas.

Spatiotemporal variation characteristics and related affecting factors of dissolved carbohydrates in the East China Sea

NASA Astrophysics Data System (ADS)

He, Zhen; Wang, Qi; Yang, Gui-Peng; Gao, Xian-Chi; Wu, Guan-Wei

2015-10-01

Carbohydrates are the largest identified fraction of dissolved organic carbon and play an important role in biogeochemical cycling in the ocean. Seawater samples were collected from the East China Sea (ECS) during June and October 2012 to study the spatiotemporal distributions of total dissolved carbohydrates (TCHOs) constituents, including dissolved monosaccharides (MCHOs) and polysaccharides (PCHOs). The concentrations of TCHOs, MCHOs and PCHOs showed significant differences between summer and autumn 2012, and exhibited an evident diurnal variation, with high values occurring in the daytime. Phytoplankton biomass was identified as the primary factor responsible for seasonal and diurnal variations of dissolved carbohydrates in the ECS. The TCHOs, MCHOs and PCHOs distributions in the study area displayed similar distribution patterns, with high concentrations appearing in the coastal water. The influences of chlorophyll-a, salinity and nutrients on the distributions of these carbohydrates were examined. A carbohydrate enrichment in the near-bottom water was found at some stations, implying that there might be an important source of carbohydrate in the deep water or bottom sediment.

Has the economic crisis widened the intraurban socioeconomic inequalities in mortality? The case of Barcelona, Spain.

PubMed

Maynou, Laia; Saez, Marc; Lopez-Casasnovas, Guillem

2016-02-01

There is considerable evidence demonstrating socioeconomic inequalities in mortality, some of which focuses on intraurban inequalities. However, all the studies assume that the spatial variation of inequalities is stable over the time. We challenge this assumption and propose two hypotheses: (i) have spatial variations in socioeconomic inequalities in mortality at an intraurban level changed over time? and (ii) as a result of the economic crisis, has the gap between such disparities widened? In this paper, our objective is to assess the effect of the economic recession on the spatio-temporal variation of socioeconomic inequalities in mortality in Barcelona (Catalonia, Spain). We used a spatio-temporal ecological design to analyse mortality inequalities at small area level in Barcelona. Mortality data and socioeconomic indicators correspond to the years 2005 and 2008-2011. We specified spatio-temporal ecological mixed regressions for both men and women using two indicators, neighbourhood and year. We allowed the coefficients of the socioeconomic variables to differ according to the levels and explicitly took into account spatio-temporal adjustment. For men and women both absolute and, above all, relative risks for mortality have increased since 2009. In relative terms, this means that the risk of dying has increased much more in the most economically deprived neighbourhoods than in the more affluent ones. Although the geographical pattern in relative risks for mortality in neighbourhoods in Barcelona remained very stable between 2005 and 2011, socioeconomic inequalities in mortality at an intraurban level have surged since 2009. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Spatiotemporal monitoring of soil water content profiles in an irrigated field using probabilistic inversion of time-lapse EMI data

NASA Astrophysics Data System (ADS)

Moghadas, Davood; Jadoon, Khan Zaib; McCabe, Matthew F.

2017-12-01

Monitoring spatiotemporal variations of soil water content (θ) is important across a range of research fields, including agricultural engineering, hydrology, meteorology and climatology. Low frequency electromagnetic induction (EMI) systems have proven to be useful tools in mapping soil apparent electrical conductivity (σa) and soil moisture. However, obtaining depth profile water content is an area that has not been fully explored using EMI. To examine this, we performed time-lapse EMI measurements using a CMD mini-Explorer sensor along a 10 m transect of a maize field over a 6 day period. Reference data were measured at the end of the profile via an excavated pit using 5TE capacitance sensors. In order to derive a time-lapse, depth-specific subsurface image of electrical conductivity (σ), we applied a probabilistic sampling approach, DREAM(ZS) , on the measured EMI data. The inversely estimated σ values were subsequently converted to θ using the Rhoades et al. (1976) petrophysical relationship. The uncertainties in measured σa, as well as inaccuracies in the inverted data, introduced some discrepancies between estimated σ and reference values in time and space. Moreover, the disparity between the measurement footprints of the 5TE and CMD Mini-Explorer sensors also led to differences. The obtained θ permitted an accurate monitoring of the spatiotemporal distribution and variation of soil water content due to root water uptake and evaporation. The proposed EMI measurement and modeling technique also allowed for detecting temporal root zone soil moisture variations. The time-lapse θ monitoring approach developed using DREAM(ZS) thus appears to be a useful technique to understand spatiotemporal patterns of soil water content and provide insights into linked soil moisture vegetation processes and the dynamics of soil moisture/infiltration processes.

Spatiotemporal variations of the twentieth century Tibetan Plateau precipitation based on the monthly 2.5° reconstructed data

NASA Astrophysics Data System (ADS)

Shen, Samuel S. P.; Clarke, Gregori; Shen, Bo-Wen; Yao, Tandong

2017-12-01

This paper studies the spatiotemporal variations of precipitation over the Tibetan Plateau (TP) region with latitude and longitude ranges of (25° N, 45° N) and (65° E, 105° E) of the twentieth century from January 1901-December 2000. A long-term (January 1901-December 2009) TP monthly precipitation dataset with 2.5° latitude-longitude resolution is generated in this paper using spectral optimal gridding (SOG) method. The method uses the Global Precipitation Climatology Center (GPCC) ground station data to anchor the basis of empirical orthogonal functions (EOFs) computed from the Global Precipitation Climatology Project (GPCP) data. Our gridding takes teleconnection into account and uses data from stations both within and outside of the TP region. While the annual total precipitation increased at an approximate rate of 2.6 mm per decade in the period of 1971-2000 exists, no significant increase of TP precipitation from 1901 to 2000 was found. Our rate is less than those of previous publications based only on the TP stations because our data consider the entire TP region, including desert and high-altitude areas. An analysis of extremes and spatiotemporal patterns of our data shows that our reconstructed data can properly quantify the reported disasters of flooding and droughts in India, Bangladesh, and China for the following events: flooding in 1988 and 1998 and drought in 1972. Our time-frequency analysis using the empirical mode decomposition method shows that our nonlinear trend agrees well with the linear trend in the period from 1971 to 2000. The spatiotemporal variation characteristics documented in this paper can help understand atmospheric circulations on TP precipitation and validate the TP precipitation in climate models.

Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

PubMed

Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

2016-06-01

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Do we really use rainfall observations consistent with reality in hydrological modelling?

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

2017-04-01

Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

a Spatiotemporal Aggregation Query Method Using Multi-Thread Parallel Technique Based on Regional Division

NASA Astrophysics Data System (ADS)

Liao, S.; Chen, L.; Li, J.; Xiong, W.; Wu, Q.

2015-07-01

Existing spatiotemporal database supports spatiotemporal aggregation query over massive moving objects datasets. Due to the large amounts of data and single-thread processing method, the query speed cannot meet the application requirements. On the other hand, the query efficiency is more sensitive to spatial variation then temporal variation. In this paper, we proposed a spatiotemporal aggregation query method using multi-thread parallel technique based on regional divison and implemented it on the server. Concretely, we divided the spatiotemporal domain into several spatiotemporal cubes, computed spatiotemporal aggregation on all cubes using the technique of multi-thread parallel processing, and then integrated the query results. By testing and analyzing on the real datasets, this method has improved the query speed significantly.

Spatio-temporal variation of coarse woody debris input in woodland key habitats in central Sweden

Treesearch

Mari Jonsson; Shawn Fraver; Bengt Gunnar. Jonsson

2011-01-01

The persistence of many saproxylic (wood-living) species depends on a readily available supply of coarse woody debris (CWD). Most studies of CWD inputs address stand-level patterns, despite the fact that many saproxylic species depend on landscape-level supplies of CWD. In the present study we used dated CWD inputs (tree mortality events) at each of 14 Norway spruce (...

Gene expression underlying adaptive variation in Heliconius wing patterns: non-modular regulation of overlapping cinnabar and vermilion prepatterns.

PubMed

Reed, Robert D; McMillan, W Owen; Nagy, Lisa M

2008-01-07

Geographical variation in the mimetic wing patterns of the butterfly Heliconius erato is a textbook example of adaptive polymorphism; however, little is known about how this variation is controlled developmentally. Using microarrays and qPCR, we identified and compared expression of candidate genes potentially involved with a red/yellow forewing band polymorphism in H. erato. We found that transcripts encoding the pigment synthesis enzymes cinnabar and vermilion showed pattern- and polymorphism-related expression patterns, respectively. cinnabar expression was associated with the forewing band regardless of pigment colour, providing the first gene expression pattern known to be correlated with a major Heliconius colour pattern. In contrast, vermilion expression changed spatially over time in red-banded butterflies, but was not expressed at detectable levels in yellow-banded butterflies, suggesting that regulation of this gene may be involved with the red/yellow polymorphism. Furthermore, we found that the yellow pigment, 3-hydroxykynurenine, is incorporated into wing scales from the haemolymph rather than being synthesized in situ. We propose that some aspects of Heliconius colour patterns are determined by spatio-temporal overlap of pigment gene transcription prepatterns and speculate that evolutionary changes in vermilion regulation may in part underlie an adaptive colour pattern polymorphism.

Benefiting from a migratory prey: spatio-temporal patterns in allochthonous subsidization of an Arctic predator.

PubMed

Giroux, Marie-Andrée; Berteaux, Dominique; Lecomte, Nicolas; Gauthier, Gilles; Szor, Guillaume; Bêty, Joël

2012-05-01

1. Flows of nutrients and energy across ecosystem boundaries have the potential to subsidize consumer populations and modify the dynamics of food webs, but how spatio-temporal variations in autochthonous and allochthonous resources affect consumers' subsidization remains largely unexplored. 2. We studied spatio-temporal patterns in the allochthonous subsidization of a predator living in a relatively simple ecosystem. We worked on Bylot Island (Nunavut, Canada), where arctic foxes (Vulpes lagopus L.) feed preferentially on lemmings (Lemmus trimucronatus and Dicrostonyx groenlandicus Traill), and alternatively on colonial greater snow geese (Anser caerulescens atlanticus L.). Geese migrate annually from their wintering grounds (where they feed on farmlands and marshes) to the Canadian Arctic, thus generating a strong flow of nutrients and energy across ecosystem boundaries. 3. We examined the influence of spatial variations in availability of geese on the diet of fox cubs (2003-2005) and on fox reproductive output (1996-2005) during different phases of the lemming cycle. 4. Using stable isotope analysis and a simple statistical routine developed to analyse the outputs of a multisource mixing model (SIAR), we showed that the contribution of geese to the diet of arctic fox cubs decreased with distance from the goose colony. 5. The probability that a den was used for reproduction by foxes decreased with distance from the subsidized goose colony and increased with lemming abundance. When lemmings were highly abundant, the effect of distance from the colony disappeared. The goose colony thus generated a spatial patterning of reproduction probability of foxes, while the lemming cycle generated a strong temporal variation of reproduction probability of foxes. 6. This study shows how the input of energy owing to the large-scale migration of prey affects the functional and reproductive responses of an opportunistic consumer, and how this input is spatially and temporally modulated through the foraging behaviour of the consumer. Thus, perspectives of both landscape and foraging ecology are needed to fully resolve the effects of subsidies on animal demographic processes and population dynamics. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

Dynamical Properties of Transient Spatio-Temporal Patterns in Bacterial Colony of Proteus mirabilis

NASA Astrophysics Data System (ADS)

Watanabe, Kazuhiko; Wakita, Jun-ichi; Itoh, Hiroto; Shimada, Hirotoshi; Kurosu, Sayuri; Ikeda, Takemasa; Yamazaki, Yoshihiro; Matsuyama, Tohey; Matsushita, Mitsugu

2002-02-01

Spatio-temporal patterns emerged inside a colony of bacterial species Proteus mirabilis on the surface of nutrient-rich semisolid agar medium have been investigated. We observed various patterns composed of the following basic types: propagating stripe, propagating stripe with fixed dislocation, expanding and shrinking target, and rotating spiral. The remarkable point is that the pattern changes immediately when we alter the position for observation, but it returns to the original if we restore the observing position within a few minutes. We further investigated mesoscopic and microscopic properties of the spatio-temporal patterns. It turned out that whenever the spatio-temporal patterns are observed in a colony, the areas are composed of two superimposed monolayers of elongated bacterial cells. In each area they are aligned almost parallel with each other like a two-dimensional nematic liquid crystal, and move collectively and independently of another layer. It has been found that the observed spatio-temporal patterns are explained as the moiré effect.

Response of frugivorous primates to changes in fruit supply in a northern Amazonian forest.

PubMed

Mourthé, I

2014-08-01

Few attempts have been made to understand how spatiotemporal changes in fruit supply influence frugivores in tropical forests. The marked spatiotemporal variation in fruit supply can affect frugivore abundance and distribution, but studies addressing the effects of this variation on primates are scarce. The present study aimed to investigate how the spatiotemporal distribution of fruits influences the local distribution of three frugivorous primates in the eastern part of the Maracá Ecological Station, a highly seasonal Amazonian rainforest. Specifically, it was hypothesised that primate distribution will track changes in fruit supply, resulting that sites with high fruit availability should be heavily used by primates. During a 1-year study, fruit supply (ground fruit surveys) and primate density (line-transects) were monitored in twelve 2 km-long transects at monthly intervals. Fruit supply varied seasonally, being low during the dry season. The density of Ateles belzebuth was positively related to fruit supply during fruit shortage, but Cebus olivaceus and Alouatta macconnelli did not follow the same pattern. The supply of Sapotaceae fruit was an important component determining local distribution of A. belzebuth during the overall fruit shortage. Highly frugivorous primates such as A. belzebuth respond to seasonal decline in fruit supply by congregating at places with high fruit supply in this forest, particularly, those with many individuals of species of Sapotaceae. This study underscores the importance of small-scale spatiotemporal changes of fruit supply as a key component of frugivorous primate ecology in highly seasonal environments.

Spatiotemporal Patterns Produced by Bacteria

NASA Astrophysics Data System (ADS)

Shimada, Yuji; Nakahara, Akio; Matsushita, Mitsugu; Matsuyama, Tohey

1995-06-01

Spatiotemporal patterns formed by a bacterial colony of Proteus mirabilis on an agar plate were observed. About half or one hour after the colony spread over the entire surface of the agar medium in a petridish, various patterns including target and spiral patterns appeared. They are very similar to those seen in other dissipative systems, such as chemical oscillations and electrohydrodynamic convective systems. Microscopic observations revealed that the collective motion of bacterial cells is responsible for the formation of these spatiotemporal patterns.

Probabilistic Common Spatial Patterns for Multichannel EEG Analysis

PubMed Central

Chen, Zhe; Gao, Xiaorong; Li, Yuanqing; Brown, Emery N.; Gao, Shangkai

2015-01-01

Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed framework enables us to resolve the overfitting issue of CSP in a principled manner. We derive statistical inference algorithms that can alleviate the issue of local optima. In particular, an efficient algorithm based on eigendecomposition is developed for maximum a posteriori (MAP) estimation in the case of isotropic noise. For more general cases, a variational algorithm is developed for group-wise sparse Bayesian learning for the P-CSP model and for automatically determining the model size. The two proposed algorithms are validated on a simulated data set. Their practical efficacy is also demonstrated by successful applications to single-trial classifications of three motor imagery EEG data sets and by the spatio-temporal pattern analysis of one EEG data set recorded in a Stroop color naming task. PMID:26005228

Complex, Dynamic Combination of Physical, Chemical and Nutritional Variables Controls Spatio-Temporal Variation of Sandy Beach Community Structure

PubMed Central

Ortega Cisneros, Kelly; Smit, Albertus J.; Laudien, Jürgen; Schoeman, David S.

2011-01-01

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right. PMID:21858213

Complex, dynamic combination of physical, chemical and nutritional variables controls spatio-temporal variation of sandy beach community structure.

PubMed

Ortega Cisneros, Kelly; Smit, Albertus J; Laudien, Jürgen; Schoeman, David S

2011-01-01

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right.

Spatio-temporal distribution and natural variation of metabolites in citrus fruits.

PubMed

Wang, Shouchuang; Tu, Hong; Wan, Jian; Chen, Wei; Liu, Xianqing; Luo, Jie; Xu, Juan; Zhang, Hongyan

2016-05-15

To study the natural variation and spatio-temporal accumulation of citrus metabolites, liquid chromatography tandem mass spectrometry (LC-MS) based metabolome analysis was performed on four fruit tissues (flavedo, albedo, segment membrane and juice sacs) and different Citrus species (lemon, pummelo and grapefruit, sweet orange and mandarin). Using a non-targeted metabolomics approach, more than 2000 metabolite signals were detected, from which more than 54 metabolites, including amino acids, flavonoids and limonoids, were identified/annotated. Differential accumulation patterns of both primary metabolites and secondary metabolites in various tissues and species were revealed by our study. Further investigation indicated that flavedo accumulates more flavonoids while juice sacs contain more amino acids. Besides this, cluster analysis based on the levels of metabolites detected in 47 individual Citrus accessions clearly grouped them into four distinct clusters: pummelos and grapefruits, lemons, sweet oranges and mandarins, while the cluster of pummelos and grapefruits lay distinctly apart from the other three species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatio-temporal dynamic climate model for Neoleucinodes elegantalis using CLIMEX

NASA Astrophysics Data System (ADS)

da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; da Silva, Ezio Marques; da Silva Galdino, Tarcisio Visintin; Picanço, Marcelo Coutinho

2017-05-01

Seasonal variations are important components in understanding the ecology of insect population of crops. Ecological studies through modeling may be a useful tool for enhancing knowledge of seasonal patterns of insects on field crops as well as seasonal patterns of favorable climatic conditions for species. Recently CLIMEX, a semi-mechanistic niche model, was upgraded and enhanced to consider spatio-temporal dynamics of climate suitability through time. In this study, attempts were made to determine monthly variations of climate suitability for Neoleucinodes elegantalis (Guenée) (Lepidoptera: Crambidae) in five commercial tomato crop localities through the latest version of CLIMEX. We observed that N. elegantalis displays seasonality with increased abundance in tomato crops during summer and autumn, corresponding to the first 6 months of the year in monitored areas in this study. Our model demonstrated a strong accord between the CLIMEX weekly growth index (GIw) and the density of N. elegantalis for this period, thus indicating a greater confidence in our model results. Our model shows a seasonal variability of climatic suitability for N. elegantalis and provides useful information for initiating methods for timely management, such as sampling strategies and control, during periods of high degree of suitability for N. elegantalis. In this study, we ensure that the simulation results are valid through our verification using field data.

Spatiotemporal Co-variability of Surface Climate for Renewable Energy across the Contiguous United States: Role of the North Atlantic Subtropical High

NASA Astrophysics Data System (ADS)

Doering, K.; Steinschneider, S.

2017-12-01

The variability of renewable energy supply and drivers of demand across space and time largely determines the energy balance within power systems with a high penetration of renewable technologies. This study examines the joint spatiotemporal variability of summertime climate linked to renewable energy production (precipitation, wind speeds, insolation) and energy demand (temperature) across the contiguous United States (CONUS) between 1948 and 2015. Canonical correlation analysis is used to identify the major modes of joint variability between summer wind speeds and precipitation and related patterns of insolation and temperature. Canonical variates are then related to circulation anomalies to identify common drivers of the joint modes of climate variability. Results show that the first two modes of joint variability between summer wind speeds and precipitation exhibit pan-US dipole patterns with centers of action located in the eastern and central CONUS. Temperature and insolation also exhibit related US-wide dipoles. The relationship between canonical variates and lower-tropospheric geopotential height indicates that these modes are related to variability in the North Atlantic subtropical high (NASH). This insight can inform optimal strategies for siting renewables in an interconnected electric grid, and has implications for the impacts of climate variability and change on renewable energy systems.

Mechanistic understanding of human-wildlife conflict through a novel application of dynamic occupancy models.

PubMed

Goswami, Varun R; Medhi, Kamal; Nichols, James D; Oli, Madan K

2015-08-01

Crop and livestock depredation by wildlife is a primary driver of human-wildlife conflict, a problem that threatens the coexistence of people and wildlife globally. Understanding mechanisms that underlie depredation patterns holds the key to mitigating conflicts across time and space. However, most studies do not consider imperfect detection and reporting of conflicts, which may lead to incorrect inference regarding its spatiotemporal drivers. We applied dynamic occupancy models to elephant crop depredation data from India between 2005 and 2011 to estimate crop depredation occurrence and model its underlying dynamics as a function of spatiotemporal covariates while accounting for imperfect detection of conflicts. The probability of detecting conflicts was consistently <1.0 and was negatively influenced by distance to roads and elevation gradient, averaging 0.08-0.56 across primary periods (distinct agricultural seasons within each year). The probability of crop depredation occurrence ranged from 0.29 (SE 0.09) to 0.96 (SE 0.04). The probability that sites raided by elephants in primary period t would not be raided in primary period t + 1 varied with elevation gradient in different seasons and was influenced negatively by mean rainfall and village density and positively by distance to forests. Negative effects of rainfall variation and distance to forests best explained variation in the probability that sites not raided by elephants in primary period t would be raided in primary period t + 1. With our novel application of occupancy models, we teased apart the spatiotemporal drivers of conflicts from factors that influence how they are observed, thereby allowing more reliable inference on mechanisms underlying observed conflict patterns. We found that factors associated with increased crop accessibility and availability (e.g., distance to forests and rainfall patterns) were key drivers of elephant crop depredation dynamics. Such an understanding is essential for rigorous prediction of future conflicts, a critical requirement for effective conflict management in the context of increasing human-wildlife interactions. © 2015 Society for Conservation Biology.

An Empirical Orthogonal Function Reanalysis of the Northern Polar External and Induced Magnetic Field During Solar Cycle 23

NASA Astrophysics Data System (ADS)

Shore, R. M.; Freeman, M. P.; Gjerloev, J. W.

2018-01-01

We apply the method of data-interpolating empirical orthogonal functions (EOFs) to ground-based magnetic vector data from the SuperMAG archive to produce a series of month length reanalyses of the surface external and induced magnetic field (SEIMF) in 110,000 km2 equal-area bins over the entire northern polar region at 5 min cadence over solar cycle 23, from 1997.0 to 2009.0. Each EOF reanalysis also decomposes the measured SEIMF variation into a hierarchy of spatiotemporal patterns which are ordered by their contribution to the monthly magnetic field variance. We find that the leading EOF patterns can each be (subjectively) interpreted as well-known SEIMF systems or their equivalent current systems. The relationship of the equivalent currents to the true current flow is not investigated. We track the leading SEIMF or equivalent current systems of similar type by intermonthly spatial correlation and apply graph theory to (objectively) group their appearance and relative importance throughout a solar cycle, revealing seasonal and solar cycle variation. In this way, we identify the spatiotemporal patterns that maximally contribute to SEIMF variability over a solar cycle. We propose this combination of EOF and graph theory as a powerful method for objectively defining and investigating the structure and variability of the SEIMF or their equivalent ionospheric currents for use in both geomagnetism and space weather applications. It is demonstrated here on solar cycle 23 but is extendable to any epoch with sufficient data coverage.

Baseline study of the spatio-temporal patterns of reef fish assemblages prior to a major mining project in New Caledonia (South Pacific).

PubMed

Chabanet, Pascale; Guillemot, Nicolas; Kulbicki, Michel; Vigliola, Laurent; Sarramegna, Sébastien

2010-01-01

From 2008 onwards, the coral reefs of Koné (New Caledonia) will be subjected to a major anthropogenic perturbation linked to development of a nickel mine. Dredging and sediment runoff may directly damage the reef environment whereas job creation should generate a large demographic increase and thus a rise in fishing activities. This study analyzed reef fish assemblages between 2002 and 2007 with a focus on spatio-temporal variability. Our results indicate strong spatial structure of fish assemblages through time. Total species richness, density and biomass were highly variable between years but temporal variations were consistent among biotopes. A remarkable spatio-temporal stability was observed for trophic (mean 4.6% piscivores, 53.1% carnivores, 30.8% herbivores and 11.4% planktivores) and home range structures of species abundance contributions. These results are discussed and compared with others sites of the South Pacific. For monitoring perspectives, some indicators related to expected disturbances are proposed. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Spatio-temporal variation in parasite communities maintains diversity at the major histocompatibility complex class IIβ in the endangered Rio Grande silvery minnow.

PubMed

Osborne, Megan J; Pilger, Tyler J; Lusk, Joel D; Turner, Thomas F

2017-01-01

Climate change will strongly impact aquatic ecosystems particularly in arid and semi-arid regions. Fish-parasite interactions will also be affected by predicted altered flow and temperature regimes, and other environmental stressors. Hence, identifying environmental and genetic factors associated with maintaining diversity at immune genes is critical for understanding species' adaptive capacity. Here, we combine genetic (MHC class IIβ and microsatellites), parasitological and ecological data to explore the relationship between these factors in the remnant wild Rio Grande silvery minnow (Hybognathus amarus) population, an endangered species found in the southwestern United States. Infections with multiple parasites on the gills were observed and there was spatio-temporal variation in parasite communities and patterns of infection among individuals. Despite its highly endangered status and chronically low genetic effective size, Rio Grande silvery minnow had high allelic diversity at MHC class IIβ with more alleles recognized at the presumptive DAB1 locus compared to the DAB3 locus. We identified significant associations between specific parasites and MHC alleles against a backdrop of generalist parasite prevalence. We also found that individuals with higher individual neutral heterozygosity and higher amino acid divergence between MHC alleles had lower parasite abundance and diversity. Taken together, these results suggest a role for fluctuating selection imposed by spatio-temporal variation in pathogen communities and divergent allele advantage in maintenance of high MHC polymorphism. Understanding the complex interaction of habitat, pathogens and immunity in protected species will require integrated experimental, genetic and field studies. © 2016 John Wiley & Sons Ltd.

Decadal period external magnetic field variations determined via eigenanalysis

NASA Astrophysics Data System (ADS)

Shore, R. M.; Whaler, K. A.; Macmillan, S.; Beggan, C.; Velímský, J.; Olsen, N.

2016-06-01

We perform a reanalysis of hourly mean magnetic data from ground-based observatories spanning 1997-2009 inclusive, in order to isolate (after removal of core and crustal field estimates) the spatiotemporal morphology of the external fields important to mantle induction, on (long) periods of months to a full solar cycle. Our analysis focuses on geomagnetically quiet days and middle to low latitudes. We use the climatological eigenanalysis technique called empirical orthogonal functions (EOFs), which allows us to identify discrete spatiotemporal patterns with no a priori specification of their geometry -- the form of the decomposition is controlled by the data. We apply a spherical harmonic analysis to the EOF outputs in a joint inversion for internal and external coefficients. The results justify our assumption that the EOF procedure responds primarily to the long-period external inducing field contributions. Though we cannot determine uniquely the contributory source regions of these inducing fields, we find that they have distinct temporal characteristics which enable some inference of sources. An identified annual-period pattern appears to stem from a north-south seasonal motion of the background mean external field distribution. Separate patterns of semiannual and solar-cycle-length periods appear to stem from the amplitude modulations of spatially fixed background fields.

Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

NASA Astrophysics Data System (ADS)

Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

2017-04-01

Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

Variations of the spatiotemporal patterns of CVOCs concentrations in northern karst of Puerto Rico

NASA Astrophysics Data System (ADS)

Yu, X.; Ghasemizadeh, R.; Padilla, I. Y.; Irizarry, C.; Yegen, C.; Kaeli, D.; Alshawabkeh, A. N.

2013-12-01

The northern Puerto Rico is characterized as karst topography, where the groundwater is a major source of water use to the island. Various types of Chlorinated Volatile Organic Compounds (CVOCs), which are due to improper disposal of industrial waste, are detected in these karst aquifers. It is important to study the spatiotemporal distribution patterns of the CVOCs in this region, which are posing a serious threat to both the ecological and human health. In this study, various historical CVOCs data from 264 wells across the northern karst region from January 1982 to December 2000 were collected from a number of reports and studies. We found that 38% (99 out of 264) of the sites had at least one sample with CVOC concentration above the standards established to protect human health over the study period. We found that the distribution of the CVOCs spatially varied with areas containing clusters of sites contaminated by different organic compound. The response of CVOC concentrations were occasionally retarded even though they were depleted significantly in the source zones. The study confirmed that the measured CVOC concentrations decreased during the study period at most of the sites. The source origin (toxics release locations and quantities) and the intrinsic characteristics of the karst (high heterogeneity and complex hydraulic behavior) are most likely related with the spatial and temporal distribution patterns of CVOCs. The study of the spatiotemporal patterns of CVOCs concentrations in the northern karst aquifers has important implications on the public water use, especially when it coincides with the recent population growth in this region. Locations of Puerto Rico, the northern karst region of Puerto Rico and 264 sampling sites in the karst region.

Data Flow Analysis and Visualization for Spatiotemporal Statistical Data without Trajectory Information.

PubMed

Kim, Seokyeon; Jeong, Seongmin; Woo, Insoo; Jang, Yun; Maciejewski, Ross; Ebert, David S

2018-03-01

Geographic visualization research has focused on a variety of techniques to represent and explore spatiotemporal data. The goal of those techniques is to enable users to explore events and interactions over space and time in order to facilitate the discovery of patterns, anomalies and relationships within the data. However, it is difficult to extract and visualize data flow patterns over time for non-directional statistical data without trajectory information. In this work, we develop a novel flow analysis technique to extract, represent, and analyze flow maps of non-directional spatiotemporal data unaccompanied by trajectory information. We estimate a continuous distribution of these events over space and time, and extract flow fields for spatial and temporal changes utilizing a gravity model. Then, we visualize the spatiotemporal patterns in the data by employing flow visualization techniques. The user is presented with temporal trends of geo-referenced discrete events on a map. As such, overall spatiotemporal data flow patterns help users analyze geo-referenced temporal events, such as disease outbreaks, crime patterns, etc. To validate our model, we discard the trajectory information in an origin-destination dataset and apply our technique to the data and compare the derived trajectories and the original. Finally, we present spatiotemporal trend analysis for statistical datasets including twitter data, maritime search and rescue events, and syndromic surveillance.

Dynamic Assessment on the Landscape Patterns and Spatio-temporal Change in the mainstream of Tarim River

NASA Astrophysics Data System (ADS)

Zhang, Hui; Xue, Lianqing; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Wei, Guanghui

2018-01-01

The Tarim River (TR), as the longest inland river at an arid area in China, is a typical regions of vegetation variation research and plays a crucial role in the sustainable development of regional ecological environment. In this paper, the newest dataset of MODND1M NDVI, at a resolution of 500m, were applied to calculate vegetation index in growing season during the period 2000-2015. Using a vegetation coverage index, a trend line analysis, and the local spatial autocorrelation analysis, this paper investigated the landscape patterns and spatio-temporal variation of vegetation coverage at regional and pixel scales over mainstream of the Tarim River, Xinjiang. The results showed that (1) The bare land area on both sides of Tarim River appeared to have a fluctuated downward trend and there were two obvious valley values in 2005 and 2012. (2) Spatially, the vegetation coverage improved areas is mostly distributed in upstream and the degraded areas is mainly distributed in the left bank of midstream and the end of Tarim River during 2000-2005. (3) The local spatial auto-correlation analysis revealed that vegetation coverage was spatially positive autocorrelated and spatial concentrated. The high-high self-related areas are mainly distributed in upstream, where vegetation cover are relatively good, and the low-low self-related areas are mostly with lower vegetation cover in the lower reaches of Tarim River.

Rapid evolution of fire melanism in replicated populations of pygmy grasshoppers.

PubMed

Forsman, Anders; Karlsson, Magnus; Wennersten, Lena; Johansson, Jenny; Karpestam, Einat

2011-09-01

Evolutionary theory predicts an interactive process whereby spatiotemporal environmental heterogeneity will maintain genetic variation, while genetic and phenotypic diversity will buffer populations against stress and allow for fast adaptive evolution in rapidly changing environments. Here, we study color polymorphism patterns in pygmy grasshoppers (Tetrix subulata) and show that the frequency of the melanistic (black) color variant was higher in areas that had been ravaged by fires the previous year than in nonburned habitats, that, in burned areas, the frequency of melanistic grasshoppers dropped from ca. 50% one year after a fire to 30% after four years, and that the variation in frequencies of melanistic individuals among and within populations was genetically based on and represented evolutionary modifications. Dark coloration may confer a selective benefit mediated by enhanced camouflage in recently fire-ravaged areas characterized by blackened visual backgrounds before vegetation has recovered. These findings provide rare evidence for unusually large, extremely rapid adaptive contemporary evolution in replicated natural populations in response to divergent and fluctuating selection associated with spatiotemporal environmental changes. © 2011 The Author(s).

Evapotranspiration patterns in complex upland forests reveal contrasting topographic thresholds of non-linearity

NASA Astrophysics Data System (ADS)

Metzen, D.; Sheridan, G. J.; Benyon, R. G.; Bolstad, P. V.; Nyman, P.; Lane, P. N. J.

2017-12-01

Large areas of forest are often treated as being homogeneous just because they fall in a single climate category. However, we observe strong vegetation patterns in relation to topography in SE Australian forests and thus hypothesise that ET will vary spatially as well. Spatial heterogeneity evolves over different temporal scales in response to climatic forcing with increasing time lag from soil moisture (sub-yearly), to vegetation (10s -100s of years) to soil properties and topography (>100s of years). Most importantly, these processes and time scales are not independent, creating feedbacks that result in "co-evolved stable states" which yield the current spatial terrain, vegetation and ET patterns. We used up-scaled sap flux and understory ET measurements from water-balance plots, as well as LiDAR derived terrain and vegetation information, to infer links between spatio-temporal energy and water fluxes, topography and vegetation patterns at small catchment scale. Topography caused variations in aridity index between polar and equatorial-facing slopes (1.3 vs 1.8), which in turn manifested in significant differences in sapwood area index (6.9 vs 5.8), overstory LAI (3.0 vs 2.3), understory LAI (0.5 vs 0.4), sub-canopy radiation load (4.6 vs 6.8 MJ m-2 d-1), overstory transpiration (501 vs 347 mm a-1) and understory ET (79 vs 155 mm a-1). Large spatial variation in overstory transpiration (195 to 891 mm a-1) was observed over very short distances (100s m); a range representative of diverse forests such as arid open woodlands and wet mountain ash forests. Contrasting, non-linear overstory and understory ET patterns were unveiled between aspects, and topographic thresholds were lower for overstory than understory ET. While ET partitioning remained stable on polar-facing slopes regardless of slope position, overstory contribution gradually decreased with increasing slope inclination on equatorial aspects. Further, we show that ET patterns and controls underlie strong seasonality and overstory LAI explained 61% of variations in ET partitioning over the entire domain. Strong links between vegetation, topography and energy and water fluxes offer the potential to exploit terrain and vegetation patterns to infer spatio-temporal ET dynamics ultimately helping manage water resources in a changing climate.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010.

PubMed

Zulu, Leo C; Kalipeni, Ezekiel; Johannes, Eliza

2014-05-23

Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi's estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across 'sub-epidemics' while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV "hotspots" clustered among eleven southern districts/cities while a "coldspot" captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010

PubMed Central

2014-01-01

Background Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi’s estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Methods Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Results Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across ‘sub-epidemics’ while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV “hotspots” clustered among eleven southern districts/cities while a “coldspot” captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Conclusions Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale. PMID:24886573

Land use pattern, socio-economic development, and assessment of their impacts on ecosystem service value: study on natural wetlands distribution area (NWDA) in Fuzhou city, southeastern China.

PubMed

Cai, Yuan-Bin; Zhang, Hao; Pan, Wen-Bin; Chen, Yan-Hong; Wang, Xiang-Rong

2013-06-01

This paper quantifies the allocation of ecosystem services value (ESV) associated with land use pattern and qualitatively examined impacts of land use changes and socio-economic factors on spatiotemporal variation of ESV in the Natural Wetland Distribution Area (NWDA), Fuzhou city, China. The results showed that total ESV of the study area decreased from 4,332.16 × 10(6) RMB Yuan in 1989 to 3,697.42 × 10(6) RMB Yuan in 2009, mainly due to the remarkable decreases in cropland (decreased by 55.3 %) and wetland (decreased by 74.2 %). Forest, water, and wetland played major roles in providing ecosystem services, accounting for over 90 % of the total ESV. Based on time series Landsat TM/ETM+ imagery, geographic information system, and historical data, analysis of the spatiotemporal variation of ESV from 1989 to 2009 was performed. It indicated that rapid expansion of urban areas along the Minjiang River resulted in significant changes in land use types, leading to a dramatic decline in ecosystem services. Meanwhile, because of land scarcity and unique ecosystem functions, the emergency of wetland and cropland protection in built-up area has become an urgent task of local authorities to the local government. Furthermore, there was still a significant negative correlation between ESV of cropland and wetland and the GDP. The results suggest that future planning of land use pattern should control encroachment of urban areas into cropland and wetland in addition to scientific and rational policies towards minimizing the adverse effects of urbanization.

Magma flow between summit and Pu`u `Ō`ō at K¯lauea Volcano, Hawai`i

NASA Astrophysics Data System (ADS)

Montagna, C. P.; Gonnermann, H. M.

2013-07-01

Volcanic eruptions are often accompanied by spatiotemporal migration of ground deformation, a consequence of pressure changes within magma reservoirs and pathways. We modeled the propagation of pressure variations through the east rift zone (ERZ) of K¯lauea Volcano, Hawai`i, caused by magma withdrawal during the early eruptive episodes (1983-1985) of the ongoing Pu`u `Ō`ō-Kupaianaha eruption. Eruptive activity at the Pu`u `Ō`ō vent was typically accompanied by abrupt deflation that lasted for several hours and was followed by a sudden onset of gradual inflation once the eruptive episode had ended. Similar patterns of deflation and inflation were recorded at K¯lauea's summit, approximately 15 km to the northwest, albeit with time delays of hours. These delay times can be reproduced by modeling the spatiotemporal changes in magma pressure and flow rate within an elastic-walled dike that traverses K¯lauea's ERZ. Key parameters that affect the behavior of the magma-dike system are the dike dimensions, the elasticity of the wall rock, the magma viscosity, and to a lesser degree the magnitude and duration of the pressure variations themselves. Combinations of these parameters define a transport efficiency and a pressure diffusivity, which vary somewhat from episode to episode, resulting in variations in delay times. The observed variations in transport efficiency are most easily explained by small, localized changes to the geometry of the magma pathway.

Multi-Spatiotemporal Patterns of Residential Burglary Crimes in Chicago: 2006-2016

NASA Astrophysics Data System (ADS)

Luo, J.

2017-10-01

This research attempts to explore the patterns of burglary crimes at multi-spatiotemporal scales in Chicago between 2006 and 2016. Two spatial scales are investigated that are census block and police beat area. At each spatial scale, three temporal scales are integrated to make spatiotemporal slices: hourly scale with two-hour time step from 12:00am to the end of the day; daily scale with one-day step from Sunday to Saturday within a week; monthly scale with one-month step from January to December. A total of six types of spatiotemporal slices will be created as the base for the analysis. Burglary crimes are spatiotemporally aggregated to spatiotemporal slices based on where and when they occurred. For each type of spatiotemporal slices with burglary occurrences integrated, spatiotemporal neighborhood will be defined and managed in a spatiotemporal matrix. Hot-spot analysis will identify spatiotemporal clusters of each type of spatiotemporal slices. Spatiotemporal trend analysis is conducted to indicate how the clusters shift in space and time. The analysis results will provide helpful information for better target policing and crime prevention policy such as police patrol scheduling regarding times and places covered.

An evaluation of space time cube representation of spatiotemporal patterns.

PubMed

Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

2009-01-01

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

Spatiotemporal change of sky polarization during the total solar eclipse on 29 March 2006 in Turkey: polarization patterns of the eclipsed sky observed by full-sky imaging polarimetry.

PubMed

Sipocz, Brigitta; Hegedüs, Ramón; Kriska, György; Horváth, Gábor

2008-12-01

Using 180 degrees field-of-view (full-sky) imaging polarimetry, we measured the spatiotemporal change of the polarization of skylight during the total solar eclipse on 29 March 2006 in Turkey. We present our observations here on the temporal variation of the celestial patterns of the degree p and angle alpha of linear polarization of the eclipsed sky measured in the red (650 nm), green (550 nm), and blue (450 nm) parts of the spectrum. We also report on the temporal and spectral change of the positions of neutral (unpolarized, p = 0) points, and points with local minima or maxima of p of the eclipsed sky. Our results are compared with the observations performed by the same polarimetric technique during the total solar eclipse on 11 August 1999 in Hungary. Practically the same characteristics of celestial polarization were encountered during both eclipses. This shows that the observed polarization phenomena of the eclipsed sky may be general.

Visual pattern recognition based on spatio-temporal patterns of retinal ganglion cells’ activities

PubMed Central

Jing, Wei; Liu, Wen-Zhong; Gong, Xin-Wei; Gong, Hai-Qing

2010-01-01

Neural information is processed based on integrated activities of relevant neurons. Concerted population activity is one of the important ways for retinal ganglion cells to efficiently organize and process visual information. In the present study, the spike activities of bullfrog retinal ganglion cells in response to three different visual patterns (checker-board, vertical gratings and horizontal gratings) were recorded using multi-electrode arrays. A measurement of subsequence distribution discrepancy (MSDD) was applied to identify the spatio-temporal patterns of retinal ganglion cells’ activities in response to different stimulation patterns. The results show that the population activity patterns were different in response to different stimulation patterns, such difference in activity pattern was consistently detectable even when visual adaptation occurred during repeated experimental trials. Therefore, the stimulus pattern can be reliably discriminated according to the spatio-temporal pattern of the neuronal activities calculated using the MSDD algorithm. PMID:21886670

Epidemic Distribution and Variation of Plasmodium falciparum and Plasmodium vivax Malaria in Hainan, China during 1995–2008

PubMed Central

Xiao, Dan; Long, Yong; Wang, Shanqing; Wu, Kejian; Xu, Dezhong; Li, Haitao; Wang, Guangze; Yan, Yongping

2012-01-01

Hainan Province is the main area threatened by malaria in China. However, the epidemiologic patterns of malaria in this region are not yet defined. In this study, we determined the spatio-temporal distribution and variation of Plasmodium falciparum and Plasmodium vivax malaria in Hainan during 1995–2008 by using wavelet and cluster quantitative approaches. The results indicated a decreasing secular trend and obvious seasonal fluctuation of malaria in Hainan. In addition, the characteristic annual peak of malaria could not be detected after 2005. The southcentral region of Hainan has remained an area of relatively high malaria risk, but the incidence of P. falciparum malaria increased significantly in the southeast and southwest regions during 2002–2008. These findings identify epidemic patterns of malaria in Hainan, and are applicable for designing an effective and dynamic public health campaign to combat malaria in this region. PMID:22869636

Quantitative Folding Pattern Analysis of Early Primary Sulci in Human Fetuses with Brain Abnormalities.

PubMed

Im, K; Guimaraes, A; Kim, Y; Cottrill, E; Gagoski, B; Rollins, C; Ortinau, C; Yang, E; Grant, P E

2017-07-01

Aberrant gyral folding is a key feature in the diagnosis of many cerebral malformations. However, in fetal life, it is particularly challenging to confidently diagnose aberrant folding because of the rapid spatiotemporal changes of gyral development. Currently, there is no resource to measure how an individual fetal brain compares with normal spatiotemporal variations. In this study, we assessed the potential for automatic analysis of early sulcal patterns to detect individual fetal brains with cerebral abnormalities. Triplane MR images were aligned to create a motion-corrected volume for each individual fetal brain, and cortical plate surfaces were extracted. Sulcal basins were automatically identified on the cortical plate surface and compared with a combined set generated from 9 normal fetal brain templates. Sulcal pattern similarities to the templates were quantified by using multivariate geometric features and intersulcal relationships for 14 normal fetal brains and 5 fetal brains that were proved to be abnormal on postnatal MR imaging. Results were compared with the gyrification index. Significantly reduced sulcal pattern similarities to normal templates were found in all abnormal individual fetuses compared with normal fetuses (mean similarity [normal, abnormal], left: 0.818, 0.752; P < .001; right: 0.810, 0.753; P < .01). Altered location and depth patterns of sulcal basins were the primary distinguishing features. The gyrification index was not significantly different between the normal and abnormal groups. Automated analysis of interrelated patterning of early primary sulci could outperform the traditional gyrification index and has the potential to quantitatively detect individual fetuses with emerging abnormal sulcal patterns. © 2017 by American Journal of Neuroradiology.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

PubMed

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

PubMed Central

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Spatiotemporal variation in resource selection: Insights from the American marten (Martes Americana)

Treesearch

Andrew J. Shirk; Martin G. Raphael; Samuel A. Cushman

2014-01-01

Behavioral and genetic adaptations to spatiotemporal variation in habitat conditions allow species to maximize their biogeographic range and persist over time in dynamic environments. An understanding of these local adaptations can be used to guide management and conservation of populations over broad extents encompassing diverse habitats. This understanding is often...

Dissipating Step Bunches during Crystallization under Transport Control

NASA Technical Reports Server (NTRS)

Lin, Hong; Yau, S.-T.; Vekilov, Peter, G.

2003-01-01

In studies of crystal formation by the generation and spreading of layers, equidistant step trains are considered unstable---bunches and other spatiotemporal patterns of the growth steps are viewed as ubiquitous. We provide an example to the opposite. We monitor the spatiotemporal dynamics of steps and the resulting step patterns during crystallization of the proteins ferritin and apoferritin using the atomic force microscope. The variations in step velocity and density are not correlated, indicating the lack of a long-range attraction between the steps. We show that (i) because of its coupling to bulk transport, nucleation of new layers is chaotic and occurs at the facet edges, where the interfacial supersaturation is higher; (ii) step bunches self-organize via the competition for supply from the solution; and, (iii) bunches of weakly interacting steps decay as they move along the face. Tests by numerical modeling support the conclusions about the mechanisms underlying our observations. The results from these systems suggest that during crystallization controlled by transport, with weakly or noninteracting growth steps, the stable kinetic state of the surface is an equidistant step train, and step bunches only arise during nucleation of new layers. Since nucleation only occurs at a few sites on the surface, the surface morphology may be controllably patterned or smoothened by locally controlling nucleation.

Spatiotemporal Patterns in a Predator-Prey Model with Cross-Diffusion Effect

NASA Astrophysics Data System (ADS)

Sambath, M.; Balachandran, K.; Guin, L. N.

The present research deals with the emergence of spatiotemporal patterns of a two-dimensional (2D) continuous predator-prey system with cross-diffusion effect. First, we work out the critical lines of Hopf and Turing bifurcations of the current model system in a 2D spatial domain by means of bifurcation theory. More specifically, the exact Turing region is specified in a two-parameter space. In effect, by choosing the cross-diffusion coefficient as one of the momentous parameter, we demonstrate that the model system undergoes a sequence of spatiotemporal patterns in a homogeneous environment through diffusion-driven instability. Our results via numerical simulation authenticate that cross-diffusion be able to create stationary patterns which enrich the findings of pattern formation in an ecosystem.

Modelling and formation of spatiotemporal patterns of fractional predation system in subdiffusion and superdiffusion scenarios

NASA Astrophysics Data System (ADS)

Owolabi, Kolade M.; Atangana, Abdon

2018-02-01

This paper primarily focused on the question of how population diffusion can affect the formation of the spatial patterns in the spatial fraction predator-prey system by Turing mechanisms. Our numerical findings assert that modeling by fractional reaction-diffusion equations should be considered as an appropriate tool for studying the fundamental mechanisms of complex spatiotemporal dynamics. We observe that pure Hopf instability gives rise to the formation of spiral patterns in 2D and pure Turing instability destroys the spiral pattern and results to the formation of chaotic or spatiotemporal spatial patterns. Existence and permanence of the species is also guaranteed with the 3D simulations at some instances of time for subdiffusive and superdiffusive scenarios.

Differentiating the Spatiotemporal Distribution of Natural and Anthropogenic Processes on River Water-Quality Variation Using a Self-Organizing Map With Factor Analysis.

PubMed

Wang, Yeuh-Bin; Liu, Chen-Wuing; Lee, Jin-Jing

2015-08-01

To elucidate the historical improvement and advanced measure of river water quality in the Taipei metropolitan area, this study applied the self-organizing map (SOM) technique with factor analysis (FA) to differentiate the spatiotemporal distribution of natural and anthropogenic processes on river water-quality variation spanning two decades. The SOM clustered river water quality into five groups: very low pollution, low pollution, moderate pollution, high pollution, and very high pollution. FA was then used to extract four latent factors that dominated water quality from 1991 to 2011 including three anthropogenic process factors (organic, industrial, and copper pollution) and one natural process factor [suspended solids (SS) pollution]. The SOM revealed that the water quality improved substantially over time. However, the downstream river water quality was still classified as high pollution because of an increase in anthropogenic activity. FA showed the spatiotemporal pattern of each factor score decreasing over time, but the organic pollution factor downstream of the Tamsui River, as well as the SS factor scores in the upstream major tributary (the Dahan Stream), remained within the high pollution level. Therefore, we suggest that public sewage-treatment plants should be upgraded from their current secondary biological processing to advanced treatment processing. The conservation of water and soil must also be reinforced to decrease the SS loading of the Dahan Stream from natural erosion processes in the future.

Method for detecting the signature of noise-induced structures in spatiotemporal data sets: an application to excitable media

NASA Astrophysics Data System (ADS)

Huett, Marc-Thorsten

2003-05-01

We formulate mathematical tools for analyzing spatiotemporal data sets. The tools are based on nearest-neighbor considerations similar to cellular automata. One of the analysis tools allows for reconstructing the noise intensity in a data set and is an appropriate method for detecting a variety of noise-induced phenomena in spatiotemporal data. The functioning of these methods is illustrated on sample data generated with the forest fire model and with networks of nonlinear oscillators. It is seen that these methods allow the characterization of spatiotemporal stochastic resonance (STSR) in experimental data. Application of these tools to biological spatiotemporal patterns is discussed. For one specific example, the slime mold Dictyostelium discoideum, it is seen, how transitions between different patterns are clearly marked by changes in the spatiotemporal observables.

Spatial and temporal patterns of locally-acquired dengue transmission in northern Queensland, Australia, 1993-2012.

PubMed

Naish, Suchithra; Dale, Pat; Mackenzie, John S; McBride, John; Mengersen, Kerrie; Tong, Shilu

2014-01-01

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993-2012. Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ(2) = 15.17, d.f.  = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas.

Spatial and Temporal Patterns of Locally-Acquired Dengue Transmission in Northern Queensland, Australia, 1993–2012

PubMed Central

Naish, Suchithra; Dale, Pat; Mackenzie, John S.; McBride, John; Mengersen, Kerrie; Tong, Shilu

2014-01-01

Background Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992–1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993–2012. Methods Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Results 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ2 = 15.17, d.f. = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Conclusions Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas. PMID:24691549

The Link between Microbial Diversity and Nitrogen Cycling in Marine Sediments Is Modulated by Macrofaunal Bioturbation.

PubMed

Yazdani Foshtomi, Maryam; Braeckman, Ulrike; Derycke, Sofie; Sapp, Melanie; Van Gansbeke, Dirk; Sabbe, Koen; Willems, Anne; Vincx, Magda; Vanaverbeke, Jan

2015-01-01

The marine benthic nitrogen cycle is affected by both the presence and activity of macrofauna and the diversity of N-cycling microbes. However, integrated research simultaneously investigating macrofauna, microbes and N-cycling is lacking. We investigated spatio-temporal patterns in microbial community composition and diversity, macrofaunal abundance and their sediment reworking activity, and N-cycling in seven subtidal stations in the Southern North Sea. Our results indicated that bacteria (total and β-AOB) showed more spatio-temporal variation than archaea (total and AOA) as sedimentation of organic matter and the subsequent changes in the environment had a stronger impact on their community composition and diversity indices in our study area. However, spatio-temporal patterns of total bacterial and β-AOB communities were different and related to the availability of ammonium for the autotrophic β-AOB. Highest bacterial richness and diversity were observed in June at the timing of the phytoplankton bloom deposition, while richness of β-AOB as well as AOA peaked in September. Total archaeal community showed no temporal variation in diversity indices. Distance based linear models revealed that, independent from the effect of grain size and the quality and quantity of sediment organic matter, nitrification and N-mineralization were affected by respectively the diversity of metabolically active β-AOB and AOA, and the total bacteria, near the sediment-water interface. Separate models demonstrated a significant and independent effect of macrofaunal activities on community composition and richness of total bacteria, and diversity indices of metabolically active AOA. Diversity of β-AOB was significantly affected by macrofaunal abundance. Our results support the link between microbial biodiversity and ecosystem functioning in marine sediments, and provided broad correlative support for the hypothesis that this relationship is modulated by macrofaunal activity. We hypothesized that the latter effect can be explained by their bioturbating and bio-irrigating activities, increasing the spatial complexity of the biogeochemical environment.

Demographic and spatiotemporal patterns of avian influenza infection at the continental scale, and in relation to annual life cycle of a migratory host

USGS Publications Warehouse

Nallar, Rodolfo; Papp, Zsuzsanna; Epp, Tasha; Leighton, Frederick A.; Swafford, Seth R.; DeLiberto, Thomas J.; Dusek, Robert J.; Ip, Hon S.; Hall, Jeffrey S.; Berhane, Yohannes; Gibbs, Samantha E.J.; Soos, Catherine

2015-01-01

Since the spread of highly pathogenic avian influenza (HPAI) H5N1 in the eastern hemisphere, numerous surveillance programs and studies have been undertaken to detect the occurrence, distribution, or spread of avian influenza viruses (AIV) in wild bird populations worldwide. To identify demographic determinants and spatiotemporal patterns of AIV infection in long distance migratory waterfowl in North America, we fitted generalized linear models with binominal distribution to analyze results from 13,574 blue-winged teal (Anas discors, BWTE) sampled in 2007 to 2010 year round during AIV surveillance programs in Canada and the United States. Our analyses revealed that during late summer staging (July-August) and fall migration (September-October), hatch year (HY) birds were more likely to be infected than after hatch year (AHY) birds, however there was no difference between age categories for the remainder of the year (winter, spring migration, and breeding period), likely due to maturing immune systems and newly acquired immunity of HY birds. Probability of infection increased non-linearly with latitude, and was highest in late summer prior to fall migration when densities of birds and the proportion of susceptible HY birds in the population are highest. Birds in the Central and Mississippi flyways were more likely to be infected compared to those in the Atlantic flyway. Seasonal cycles and spatial variation of AIV infection were largely driven by the dynamics of AIV infection in HY birds, which had more prominent cycles and spatial variation in infection compared to AHY birds. Our results demonstrate demographic as well as seasonal, latitudinal and flyway trends across Canada and the US, while illustrating the importance of migratory host life cycle and age in driving cyclical patterns of prevalence.

Spatiotemporal patterns of the fish assemblages downstream of the Gezhouba Dam on the Yangtze River.

PubMed

Tao, Jiangping; Gong, Yutian; Tan, Xichang; Yang, Zhi; Chang, Jianbo

2012-07-01

An explicit demonstration of the changes in fish assemblages is required to reveal the influence of damming on fish species. However, information from which to draw general conclusions regarding changes in fish assemblages is insufficient because of the limitations of available approaches. We used a combination of acoustic surveys, gillnet sampling, and geostatistical simulations to document the spatiotemporal variations in the fish assemblages downstream of the Gezhouba Dam, before and after the third impoundment of Three Gorges Reservoir (TGR). To conduct a hydroacoustic identification of individual species, we matched the size distributions of the fishes captured by gillnet with those of the acoustic surveys. An optimum threshold of target strength of -50 dB re 1 m(2) was defined, and acoustic surveys were purposefully extended to the selected fish assemblages (i.e., endemic Coreius species) that was acquired by the size and species selectivity of the gillnet sampling. The relative proportion of fish species in acoustic surveys was allocated based on the composition (%) of the harvest in the gillnet surveys. Geostatistical simulations were likewise used to generate spatial patterns of fish distribution, and to determine the absolute abundance of the selected fish assemblages. We observed both the species composition and the spatial distribution of the selected fish assemblages changed significantly after implementation of new flow regulation in the TGR, wherein an immediate sharp population decline in the Coreius occurred. Our results strongly suggested that the new flow regulation in the TGR impoundment adversely affected downstream fish species, particularly the endemic Coreius species. To determine the factors responsible for the decline, we associated the variation in the fish assemblage patterns with changes in the environment and determined that substrate erosion resulting from trapping practices in the TGR likely played a key role.

Spatiotemporal variations in litter mass and their relationships with climate in temperate grassland: A case study from Xilingol grassland, Inner Mongolia (China)

NASA Astrophysics Data System (ADS)

Ren, Hongrui; Zhang, Bei

2018-02-01

Clarifying spatiotemporal variations of litter mass and their relationships with climate factors will advance our understanding of ecosystem structure and functioning in grasslands. Our objective is to investigate the spatiotemporal variations of litter mass in the growing season and their relationships with precipitation and temperature in the Xilingol grassland using MOD09A1 data. With widely used STI (simple tillage index), we firstly estimated the litter mass of Xilingol grassland in the growing season from 2000 to 2014. Then we investigated the variations of litter mass in the growing season at regional and site scales. We further explored the spatiotemporal relationships between litter mass and precipitation and temperature at both scales. The litter mass increased with increasing mean annual precipitation and decreasing mean annual temperature at regional scale. The variations of litter mass at given sites followed quadratic function curves in the growing season, and litter mass generally attained maximums between August 1 and September 1. Positive spatial relationship was observed between litter mass variations and precipitation, and negative spatial relationship was found between litter mass variations and temperature in the growing season. There was no significant relationship between inter-annual variations of litter mass and precipitation and temperature at given sites. Results illustrate that precipitation and temperature are important drivers in shaping ecosystem functioning as reflected in litter mass at regional scale in the Xilingol grassland. Our findings also suggest the action of distinct mechanism in controlling litter mass variations at regional and sites scales.

Mining moving object trajectories in location-based services for spatio-temporal database update

NASA Astrophysics Data System (ADS)

Guo, Danhuai; Cui, Weihong

2008-10-01

Advances in wireless transmission and mobile technology applied to LBS (Location-based Services) flood us with amounts of moving objects data. Vast amounts of gathered data from position sensors of mobile phones, PDAs, or vehicles hide interesting and valuable knowledge and describe the behavior of moving objects. The correlation between temporal moving patterns of moving objects and geo-feature spatio-temporal attribute was ignored, and the value of spatio-temporal trajectory data was not fully exploited too. Urban expanding or frequent town plan change bring about a large amount of outdated or imprecise data in spatial database of LBS, and they cannot be updated timely and efficiently by manual processing. In this paper we introduce a data mining approach to movement pattern extraction of moving objects, build a model to describe the relationship between movement patterns of LBS mobile objects and their environment, and put up with a spatio-temporal database update strategy in LBS database based on trajectories spatiotemporal mining. Experimental evaluation reveals excellent performance of the proposed model and strategy. Our original contribution include formulation of model of interaction between trajectory and its environment, design of spatio-temporal database update strategy based on moving objects data mining, and the experimental application of spatio-temporal database update by mining moving objects trajectories.

A model for optimizing file access patterns using spatio-temporal parallelism

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

Boonthanome, Nouanesengsy; Patchett, John; Geveci, Berk

2013-01-01

For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible filemore » access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.« less

The gait standard deviation, a single measure of kinematic variability.

PubMed

Sangeux, Morgan; Passmore, Elyse; Graham, H Kerr; Tirosh, Oren

2016-05-01

Measurement of gait kinematic variability provides relevant clinical information in certain conditions affecting the neuromotor control of movement. In this article, we present a measure of overall gait kinematic variability, GaitSD, based on combination of waveforms' standard deviation. The waveform standard deviation is the common numerator in established indices of variability such as Kadaba's coefficient of multiple correlation or Winter's waveform coefficient of variation. Gait data were collected on typically developing children aged 6-17 years. Large number of strides was captured for each child, average 45 (SD: 11) for kinematics and 19 (SD: 5) for kinetics. We used a bootstrap procedure to determine the precision of GaitSD as a function of the number of strides processed. We compared the within-subject, stride-to-stride, variability with the, between-subject, variability of the normative pattern. Finally, we investigated the correlation between age and gait kinematic, kinetic and spatio-temporal variability. In typically developing children, the relative precision of GaitSD was 10% as soon as 6 strides were captured. As a comparison, spatio-temporal parameters required 30 strides to reach the same relative precision. The ratio stride-to-stride divided by normative pattern variability was smaller in kinematic variables (the smallest for pelvic tilt, 28%) than in kinetic and spatio-temporal variables (the largest for normalised stride length, 95%). GaitSD had a strong, negative correlation with age. We show that gait consistency may stabilise only at, or after, skeletal maturity. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantifying stimulus-response rehabilitation protocols by auditory feedback in Parkinson's disease gait pattern

NASA Astrophysics Data System (ADS)

Pineda, Gustavo; Atehortúa, Angélica; Iregui, Marcela; García-Arteaga, Juan D.; Romero, Eduardo

2017-11-01

External auditory cues stimulate motor related areas of the brain, activating motor ways parallel to the basal ganglia circuits and providing a temporary pattern for gait. In effect, patients may re-learn motor skills mediated by compensatory neuroplasticity mechanisms. However, long term functional gains are dependent on the nature of the pathology, follow-up is usually limited and reinforcement by healthcare professionals is crucial. Aiming to cope with these challenges, several researches and device implementations provide auditory or visual stimulation to improve Parkinsonian gait pattern, inside and outside clinical scenarios. The current work presents a semiautomated strategy for spatio-temporal feature extraction to study the relations between auditory temporal stimulation and spatiotemporal gait response. A protocol for auditory stimulation was built to evaluate the integrability of the strategy in the clinic practice. The method was evaluated in transversal measurement with an exploratory group of people with Parkinson's (n = 12 in stage 1, 2 and 3) and control subjects (n =6). The result showed a strong linear relation between auditory stimulation and cadence response in control subjects (R=0.98 +/-0.008) and PD subject in stage 2 (R=0.95 +/-0.03) and stage 3 (R=0.89 +/-0.05). Normalized step length showed a variable response between low and high gait velocity (0.2> R >0.97). The correlation between normalized mean velocity and stimulus was strong in all PD stage 2 (R>0.96) PD stage 3 (R>0.84) and controls (R>0.91) for all experimental conditions. Among participants, the largest variation from baseline was found in PD subject in stage 3 (53.61 +/-39.2 step/min, 0.12 +/- 0.06 in step length and 0.33 +/- 0.16 in mean velocity). In this group these values were higher than the own baseline. These variations are related with direct effect of metronome frequency on cadence and velocity. The variation of step length involves different regulation strategies and could need others specific external cues. In conclusion the current protocol (and their selected parameters, kind of sound time for training, step of variation, range of variation) provide a suitable gait facilitation method specially for patients with the highest gait disturbance (stage 2 and 3). The method should be adjusted for initial stages and evaluated in a rehabilitation program.

Ramet demography of a nurse bromeliad in Brazilian restingas.

PubMed

Sampaio, Michelle C; Picó, F Xavier; Scarano, Fabio R

2005-04-01

Restingas are sandy coastal plains that stand between the sea and the Brazilian Atlantic forest mountains. The predominant restinga vegetation type in northern Rio de Janeiro, Brazil, is characterized by the formation of islands that begins with colonization by some pioneer herbs and/or woody plants. Pioneer plants are stress-resistant and nurse many other less-resistant plant species. Determining the spatiotemporal variation in the dynamics of nurse plants is essential to understand the ecological functioning of restingas as a whole. The goal of this study was to analyze the spatiotemporal variation in population dynamics of the nurse bromeliad Aechmea nudicaulis. We monitored A. nudicaulis ramets in different habitats, microhabitats, and years. We analyzed the spatiotemporal variation in demographic traits and in population growth rate. Results showed young ramet traits were more variable at the microhabitat level, and when variable, vegetative ramet traits varied at all spatiotemporal scales. Overall, λ values indicated that A. nudicaulis basically remained spatiotemporally stable as most of the λ values did not significantly differ from unity. Hence, the stability of A. nudicaulis in different microhabitats and habitats in the restinga may create several settlement opportunities for many other less-resistant species.

Predictability of spatio-temporal patterns in a lattice of coupled FitzHugh–Nagumo oscillators

PubMed Central

Grace, Miriam; Hütt, Marc-Thorsten

2013-01-01

In many biological systems, variability of the components can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In pioneering work in the late 1990s, it was hypothesized that a drift of cellular parameters (along a ‘developmental path’), together with differences in cell properties (‘desynchronization’ of cells on the developmental path) can establish self-organized spatio-temporal patterns (in their example, spiral waves of cAMP in a colony of Dictyostelium discoideum cells) starting from a homogeneous state. Here, we embed a generic model of an excitable medium, a lattice of diffusively coupled FitzHugh–Nagumo oscillators, into a developmental-path framework. In this minimal model of spiral wave generation, we can now study the predictability of spatio-temporal patterns from cell properties as a function of desynchronization (or ‘spread’) of cells along the developmental path and the drift speed of cell properties on the path. As a function of drift speed and desynchronization, we observe systematically different routes towards fully established patterns, as well as strikingly different correlations between cell properties and pattern features. We show that the predictability of spatio-temporal patterns from cell properties contains important information on the pattern formation process as well as on the underlying dynamical system. PMID:23349439

Spatio-temporal variation in microclimate, the surface energy balance and ablation over a cirque glacier

NASA Astrophysics Data System (ADS)

Hannah, David M.; Gurnell, Angela M.; McGregor, Glenn R.

2000-06-01

Climatic processes, operating at a range of scales, drive energy fluxes at the glacier surface which control meltwater generation and ultimately runoff. Nevertheless, to date, most glacier microclimate research has been both temporally (short-term) and spatially (single station) restricted. This paper addresses this knowledge gap by reporting on a detailed, empirical study which characterizes spatio-temporal variations in and linkages between glacier microclimate, surface energy and mass exchanges within a small glacierized cirque (Taillon Glacier, French Pyrénées) over two melt seasons. Data collected at five automatic weather stations (AWSs) and over ablation stake networks suggest that topoclimates, altitude and transient snowline position primarily determine the distribution of glacier energy receipt and, in turn, snow- and ice-melt patterns. Generally net radiation is the dominant energy source, followed by sensible heat, while latent heat is an energy sink. However, the magnitude and partitioning of energy balance terms, and consequently ablation, vary across the glacier both seasonally and with prevailing weather conditions. Importantly, this paper demonstrates that such monitoring programmes are required to truly represent and provide a sound basis for modelling glacier energy and mass-balances in both space and time.

Spatiotemporal variation in survival rates: implications for population dynamics of yellow-bellied marmots.

PubMed

Ozgul, Arpat; Armitage, Kenneth B; Blumstein, Daniel T; Oli, Madan K

2006-04-01

Spatiotemporal variation in age-specific survival rates can profoundly influence population dynamics, but few studies of vertebrates have thoroughly investigated both spatial and temporal variability in age-specific survival rates. We used 28 years (1976-2003) of capture-mark-recapture (CMR) data from 17 locations to parameterize an age-structured Cormack-Jolly-Seber model, and investigated spatial and temporal variation in age-specific annual survival rates of yellow-bellied marmots (Marmota flaviventris). Survival rates varied both spatially and temporally, with survival of younger animals exhibiting the highest degree of variation. Juvenile survival rates varied from 0.52 +/- 0.05 to 0.78 +/- 0.10 among sites and from 0.15 +/- 0.14 to 0.89 +/- 0.06 over time. Adult survival rates varied from 0.62 +/- 0.09 to 0.80 +/- 0.03 among sites, but did not vary significantly over time. We used reverse-time CMR models to estimate the realized population growth rate (lamda), and to investigate the influence of the observed variation in age-specific survival rates on lamda. The realized growth rate of the population closely covaried with, and was significantly influenced by, spatiotemporal variation in juvenile survival rate. High variability in juvenile survival rates over space and time clearly influenced the dynamics of our study population and is also likely to be an important determinant of the spatiotemporal variation in the population dynamics of other mammals with similar life history characteristics.

Physical and biogeochemical correlates of spatio-temporal variation in the δ13C of marine macroalgae

NASA Astrophysics Data System (ADS)

Mackey, Andrew P.; Hyndes, Glenn A.; Carvalho, Matheus C.; Eyre, Bradley D.

2015-05-01

Carbon isotope ratios (13C/12C) can be used to trace sources of production supporting food chains, as δ13C undergoes relatively small and predictable increases (∼0.5‰) through each trophic level. However, for this technique to be precise, variation in δ13C signatures of different sources of production (baseline sources) must be clearly defined and distinct from each other. Despite this, δ13C in the primary producers of marine systems are highly variable over space and time, due to the complexity of physical and biogeochemical processes that drive δ13C variation at the base of these foodwebs. We measured spatial and temporal variation in the δ13C of two species of macroalgae that are important dietary components of grazers over temperate reefs: the small kelp Ecklonia radiata, and the red alga Plocamium preissianum, and related any variation to a suite of physical and biogeochemical variables. Patterns in δ13C variation, over different spatial (10 s m to 100 km) and temporal scales (weeks to seasons), differed greatly between taxa, but these were partly explained by the δ13C of dissolved inorganic carbon (DIC) and light. However, while the δ13C in E. radiata was not related to water temperature, a highly significant proportion of the spatio-temporal variation in δ13C of P. preissianum was explained by temperature alone. Accordingly, we applied this relationship to project (across temperate Australasia) and forecast (in time, south-western Australia) patterns in P. preissianum δ13C. The mean projected δ13C for P. preissianum in the study region varied by only ∼1‰ over a 12-month period, compared to ∼3‰ over 2000 km. This illustrates the potential scale in the shift of δ13C in baseline food sources over broad scales, and its implications to food web studies. While we show that those relationships differ across taxonomic groups, we recommend developing models to explain variability in δ13C of other baseline sources to facilitate the interpretation of variation in δ13C of consumers in food webs, particularly where data for baselines are absent over broad scales.

Abnormal early dynamic individual patterns of functional networks in low gamma band for depression recognition.

PubMed

Bi, Kun; Chattun, Mahammad Ridwan; Liu, Xiaoxue; Wang, Qiang; Tian, Shui; Zhang, Siqi; Lu, Qing; Yao, Zhijian

2018-06-13

The functional networks are associated with emotional processing in depression. The mapping of dynamic spatio-temporal brain networks is used to explore individual performance during early negative emotional processing. However, the dysfunctions of functional networks in low gamma band and their discriminative potentialities during early period of emotional face processing remain to be explored. Functional brain networks were constructed from the MEG recordings of 54 depressed patients and 54 controls in low gamma band (30-48 Hz). Dynamic connectivity regression (DCR) algorithm analyzed the individual change points of time series in response to emotional stimuli and constructed individualized spatio-temporal patterns. The nodal characteristics of patterns were calculated and fed into support vector machine (SVM). Performance of the classification algorithm in low gamma band was validated by dynamic topological characteristics of individual patterns in comparison to alpha and beta band. The best discrimination accuracy of individual spatio-temporal patterns was 91.01% in low gamma band. Individual temporal patterns had better results compared to group-averaged temporal patterns in all bands. The most important discriminative networks included affective network (AN) and fronto-parietal network (FPN) in low gamma band. The sample size is relatively small. High gamma band was not considered. The abnormal dynamic functional networks in low gamma band during early emotion processing enabled depression recognition. The individual information processing is crucial in the discovery of abnormal spatio-temporal patterns in depression during early negative emotional processing. Individual spatio-temporal patterns may reflect the real dynamic function of subjects while group-averaged data may neglect some individual information. Copyright © 2018. Published by Elsevier B.V.

Spatiotemporal analysis of dengue fever in Nepal from 2010 to 2014.

PubMed

Acharya, Bipin Kumar; Cao, ChunXiang; Lakes, Tobia; Chen, Wei; Naeem, Shahid

2016-08-22

Due to recent emergence, dengue is becoming one of the major public health problems in Nepal. The numbers of reported dengue cases in general and the area with reported dengue cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of dengue have not been investigated yet. This study aims to fill this gap by analyzing spatiotemporal patterns based on monthly surveillance data aggregated at district. Dengue cases from 2010 to 2014 at district level were collected from the Nepal government's health and mapping agencies respectively. GeoDa software was used to map crude incidence, excess hazard and spatially smoothed incidence. Cluster analysis was performed in SaTScan software to explore spatiotemporal clusters of dengue during the above-mentioned time period. Spatiotemporal distribution of dengue fever in Nepal from 2010 to 2014 was mapped at district level in terms of crude incidence, excess risk and spatially smoothed incidence. Results show that the distribution of dengue fever was not random but clustered in space and time. Chitwan district was identified as the most likely cluster and Jhapa district was the first secondary cluster in both spatial and spatiotemporal scan. July to September of 2010 was identified as a significant temporal cluster. This study assessed and mapped for the first time the spatiotemporal pattern of dengue fever in Nepal. Two districts namely Chitwan and Jhapa were found highly affected by dengue fever. The current study also demonstrated the importance of geospatial approach in epidemiological research. The initial result on dengue patterns and risk of this study may assist institutions and policy makers to develop better preventive strategies.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

NASA Astrophysics Data System (ADS)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.

Spatio-temporal analysis of irregular vocal fold oscillations: Biphonation due to desynchronization of spatial modes

NASA Astrophysics Data System (ADS)

Neubauer, Jürgen; Mergell, Patrick; Eysholdt, Ulrich; Herzel, Hanspeter

2001-12-01

This report is on direct observation and modal analysis of irregular spatio-temporal vibration patterns of vocal fold pathologies in vivo. The observed oscillation patterns are described quantitatively with multiline kymograms, spectral analysis, and spatio-temporal plots. The complex spatio-temporal vibration patterns are decomposed by empirical orthogonal functions into independent vibratory modes. It is shown quantitatively that biphonation can be induced either by left-right asymmetry or by desynchronized anterior-posterior vibratory modes, and the term ``AP (anterior-posterior) biphonation'' is introduced. The presented phonation examples show that for normal phonation the first two modes sufficiently explain the glottal dynamics. The spatio-temporal oscillation pattern associated with biphonation due to left-right asymmetry can be explained by the first three modes. Higher-order modes are required to describe the pattern for biphonation induced by anterior-posterior vibrations. Spatial irregularity is quantified by an entropy measure, which is significantly higher for irregular phonation than for normal phonation. Two asymmetry measures are introduced: the left-right asymmetry and the anterior-posterior asymmetry, as the ratios of the fundamental frequencies of left and right vocal fold and of anterior-posterior modes, respectively. These quantities clearly differentiate between left-right biphonation and anterior-posterior biphonation. This paper proposes methods to analyze quantitatively irregular vocal fold contour patterns in vivo and complements previous findings of desynchronization of vibration modes in computer modes and in in vitro experiments.

Spatiotemporal Patterns and Predictability of Cyberattacks

PubMed Central

Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

2015-01-01

A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term “spatio” refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack “fingerprints” and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches. PMID:25992837

Spatiotemporal patterns and predictability of cyberattacks.

PubMed

Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

2015-01-01

A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term "spatio" refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack "fingerprints" and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.

Evaluation of urban sprawl and urban landscape pattern in a rapidly developing region.

PubMed

Lv, Zhi-Qiang; Dai, Fu-Qiang; Sun, Cheng

2012-10-01

Urban sprawl is a worldwide phenomenon happening particularly in rapidly developing regions. A study on the spatiotemporal characteristics of urban sprawl and urban pattern is useful for the sustainable management of land management and urban land planning. The present research explores the spatiotemporal dynamics of urban sprawl in the context of a rapid urbanization process in a booming economic region of southern China from 1979 to 2005. Three urban sprawl types are distinguished by analyzing overlaid urban area maps of two adjacent study years which originated from the interpretation of remote sensed images and vector land use maps. Landscape metrics are used to analyze the spatiotemporal pattern of urban sprawl for each study period. Study results show that urban areas have expanded dramatically, and the spatiotemporal landscape pattern configured by the three sprawl types changed obviously. The different sprawl type patterns in five study periods have transformed significantly, with their proportions altered both in terms of quantity and of location. The present research proves that urban sprawl quantification and pattern analysis can provide a clear perspective of the urbanization process during a long time period. Particularly, the present study on urban sprawl and sprawl patterns can be used by land use and urban planners.

Considering spatial heterogeneity in the distributed lag non-linear model when analyzing spatiotemporal data.

PubMed

Chien, Lung-Chang; Guo, Yuming; Li, Xiao; Yu, Hwa-Lung

2018-01-01

The distributed lag non-linear (DLNM) model has been frequently used in time series environmental health research. However, its functionality for assessing spatial heterogeneity is still restricted, especially in analyzing spatiotemporal data. This study proposed a solution to take a spatial function into account in the DLNM, and compared the influence with and without considering spatial heterogeneity in a case study. This research applied the DLNM to investigate non-linear lag effect up to 7 days in a case study about the spatiotemporal impact of fine particulate matter (PM 2.5 ) on preschool children's acute respiratory infection in 41 districts of northern Taiwan during 2005 to 2007. We applied two spatiotemporal methods to impute missing air pollutant data, and included the Markov random fields to analyze district boundary data in the DLNM. When analyzing the original data without a spatial function, the overall PM 2.5 effect accumulated from all lag-specific effects had a slight variation at smaller PM 2.5 measurements, but eventually decreased to relative risk significantly <1 when PM 2.5 increased. While analyzing spatiotemporal imputed data without a spatial function, the overall PM 2.5 effect did not decrease but increased in monotone as PM 2.5 increased over 20 μg/m 3 . After adding a spatial function in the DLNM, spatiotemporal imputed data conducted similar results compared with the overall effect from the original data. Moreover, the spatial function showed a clear and uneven pattern in Taipei, revealing that preschool children living in 31 districts of Taipei were vulnerable to acute respiratory infection. Our findings suggest the necessity of including a spatial function in the DLNM to make a spatiotemporal analysis available and to conduct more reliable and explainable research. This study also revealed the analytical impact if spatial heterogeneity is ignored.

Monitoring the trajectory of urban nighttime light hotspots using a Gaussian volume model

NASA Astrophysics Data System (ADS)

Zheng, Qiming; Jiang, Ruowei; Wang, Ke; Huang, Lingyan; Ye, Ziran; Gan, Muye; Ji, Biyong

2018-03-01

Urban nighttime light hotspot is an ideal representation of the spatial heterogeneity of human activities within a city, which is sensitive to regional urban expansion pattern. However, most of previous studies related to nighttime light imageries focused on extracting urban extent, leaving the spatial variation of radiance intensity insufficiently explored. With the help of global radiance calibrated DMSP-OLS datasets (NTLgrc), we proposed an innovative framework to explore the spatio-temporal trajectory of polycentric urban nighttime light hotspots. Firstly, NTLgrc was inter-annually calibrated to improve the consistency. Secondly, multi-resolution segmentation and region-growing SVM classification were employed to remove blooming effect and to extract potential clusters. At last, the urban hotspots were identified by a Gaussian volume model, and the resulting parameters were used to quantitatively depict hotspot features (i.e., intensity, morphology and centroid dynamics). The result shows that our framework successfully captures hotspots in polycentric urban area, whose Ra2 are over 0.9. Meanwhile, the spatio-temporal dynamics of the hotspot features intuitively reveal the impact of the regional urban growth pattern and planning strategies on human activities. Compared to previous studies, our framework is more robust and offers an effective way to describe hotspot pattern. Also, it provides a more comprehensive and spatial-explicit understanding regarding the interaction between urbanization pattern and human activities. Our findings are expected to be beneficial to governors in term of sustainable urban planning and decision making.

Spatiotemporal dynamics of landscape pattern and hydrologic process in watershed systems

NASA Astrophysics Data System (ADS)

Randhir, Timothy O.; Tsvetkova, Olga

2011-06-01

SummaryLand use change is influenced by spatial and temporal factors that interact with watershed resources. Modeling these changes is critical to evaluate emerging land use patterns and to predict variation in water quantity and quality. The objective of this study is to model the nature and emergence of spatial patterns in land use and water resource impacts using a spatially explicit and dynamic landscape simulation. Temporal changes are predicted using a probabilistic Markovian process and spatial interaction through cellular automation. The MCMC (Monte Carlo Markov Chain) analysis with cellular automation is linked to hydrologic equations to simulate landscape patterns and processes. The spatiotemporal watershed dynamics (SWD) model is applied to a subwatershed in the Blackstone River watershed of Massachusetts to predict potential land use changes and expected runoff and sediment loading. Changes in watershed land use and water resources are evaluated over 100 years at a yearly time step. Results show high potential for rapid urbanization that could result in lowering of groundwater recharge and increased storm water peaks. The watershed faces potential decreases in agricultural and forest area that affect open space and pervious cover of the watershed system. Water quality deteriorated due to increased runoff which can also impact stream morphology. While overland erosion decreased, instream erosion increased from increased runoff from urban areas. Use of urban best management practices (BMPs) in sensitive locations, preventive strategies, and long-term conservation planning will be useful in sustaining the watershed system.

Regulation of Spatiotemporal Patterns by Biological Variability: General Principles and Applications to Dictyostelium discoideum

PubMed Central

Grace, Miriam; Hütt, Marc-Thorsten

2015-01-01

Spatiotemporal patterns often emerge from local interactions in a self-organizing fashion. In biology, the resulting patterns are also subject to the influence of the systematic differences between the system’s constituents (biological variability). This regulation of spatiotemporal patterns by biological variability is the topic of our review. We discuss several examples of correlations between cell properties and the self-organized spatiotemporal patterns, together with their relevance for biology. Our guiding, illustrative example will be spiral waves of cAMP in a colony of Dictyostelium discoideum cells. Analogous processes take place in diverse situations (such as cardiac tissue, where spiral waves occur in potentially fatal ventricular fibrillation) so a deeper understanding of this additional layer of self-organized pattern formation would be beneficial to a wide range of applications. One of the most striking differences between pattern-forming systems in physics or chemistry and those in biology is the potential importance of variability. In the former, system components are essentially identical with random fluctuations determining the details of the self-organization process and the resulting patterns. In biology, due to variability, the properties of potentially very few cells can have a driving influence on the resulting asymptotic collective state of the colony. Variability is one means of implementing a few-element control on the collective mode. Regulatory architectures, parameters of signaling cascades, and properties of structure formation processes can be "reverse-engineered" from observed spatiotemporal patterns, as different types of regulation and forms of interactions between the constituents can lead to markedly different correlations. The power of this biology-inspired view of pattern formation lies in building a bridge between two scales: the patterns as a collective state of a very large number of cells on the one hand, and the internal parameters of the single cells on the other. PMID:26562406

Finding Spatio-Temporal Patterns in Large Sensor Datasets

ERIC Educational Resources Information Center

McGuire, Michael Patrick

2010-01-01

Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is…

Fire, native species, and soil resource interactions influence the spatio-temporal invasion pattern of Bromus tectorum

Treesearch

Michael J. Gundale; Steve Sutherland; Thomas H. DeLuca; others

2008-01-01

Bromus tectorum (cheatgrass) is an invasive annual that occupies perennial grass and shrub communities throughout the western United States. Bromus tectorum exhibits an intriguing spatio-temporal pattern of invasion in low elevation ponderosa pine Pinus ponderosa/bunchgrass communities in western Montana where it...

[Spatio-temporal variations of origin, distribution and diffusion of Oncomelania hupensis in Yangtze River Basin].

PubMed

Deng, Chen; Li-Yong, Wen

2017-10-24

As the only intermediate host of Schistosoma japonicum, Oncomelania hupensis in China is mainly distributed in the Yangtze River Basin. The origin of the O. hupensis and the spatio-temporal variations of its distribution and diffusion in the Yangtze River Basin and the influencing factors, as well as significances in schistosomiasis elimination in China are reviewed in this paper.

Current understanding of the driving mechanisms for spatiotemporal variations of atmospheric speciated mercury: a review

NASA Astrophysics Data System (ADS)

Mao, Huiting; Cheng, Irene; Zhang, Leiming

2016-10-01

Atmospheric mercury (Hg) is a global pollutant and thought to be the main source of mercury in oceanic and remote terrestrial systems, where it becomes methylated and bioavailable; hence, atmospheric mercury pollution has global consequences for both human and ecosystem health. Understanding of spatial and temporal variations of atmospheric speciated mercury can advance our knowledge of mercury cycling in various environments. This review summarized spatiotemporal variations of total gaseous mercury or gaseous elemental mercury (TGM/GEM), gaseous oxidized mercury (GOM), and particulate-bound mercury (PBM) in various environments including oceans, continents, high elevation, the free troposphere, and low to high latitudes. In the marine boundary layer (MBL), the oxidation of GEM was generally thought to drive the diurnal and seasonal variations of TGM/GEM and GOM in most oceanic regions, leading to lower GEM and higher GOM from noon to afternoon and higher GEM during winter and higher GOM during spring-summer. At continental sites, the driving mechanisms of TGM/GEM diurnal patterns included surface and local emissions, boundary layer dynamics, GEM oxidation, and for high-elevation sites mountain-valley winds, while oxidation of GEM and entrainment of free tropospheric air appeared to control the diurnal patterns of GOM. No pronounced diurnal variation was found for Tekran measured PBM at MBL and continental sites. Seasonal variations in TGM/GEM at continental sites were attributed to increased winter combustion and summertime surface emissions, and monsoons in Asia, while those in GOM were controlled by GEM oxidation, free tropospheric transport, anthropogenic emissions, and wet deposition. Increased PBM at continental sites during winter was primarily due to local/regional coal and wood combustion emissions. Long-term TGM measurements from the MBL and continental sites indicated an overall declining trend. Limited measurements suggested TGM/GEM increasing from the Southern Hemisphere (SH) to the Northern Hemisphere (NH) due largely to the vast majority of mercury emissions in the NH, and the latitudinal gradient was insignificant in summer probably as a result of stronger meridional mixing. Aircraft measurements showed no significant vertical variation in GEM over the field campaign regions; however, depletion of GEM was observed in stratospherically influenced air masses. In examining the remaining questions and issues, recommendations for future research needs were provided, and among them is the most imminent need for GOM speciation measurements and fundamental understanding of multiphase redox kinetics.

Reference Canopy Stomatal Conductance Explains Spatiotemporal Patterns of Tree Transpiration

NASA Astrophysics Data System (ADS)

Loranty, M. M.; Mackay, D. S.; Ewers, B. E.; Kruger, E. L.; Traver, E.

2007-12-01

Increased heterogeneity in patterns of whole tree transpiration (EC) with increasing atmospheric vapor pressure deficit (D) suggests a dynamic response of sap flow velocity (JS) to environmental drivers. We hypothesized that differences in reference stomatal conductance (GSref), stomatal conductance at D = 1kPa, would explain the spatiotemporal dynamics of JS. Using a coupled model of plant hydraulic and biochemical processes we tested this hypothesis with sap flux data for 106 aspen ( Populus tremuloides) and 108 sugar maple ( Acer saccharum) trees collected from plots using in 2-D cyclic sampling scheme during the summer of 2005 in northern Wisconsin. Inverse modeling is used to estimate GSref for each tree. For each species, trees from across the ranges of JS and diameter distributions are compared. GSref explained temporal variability in spatial patterns of EC We explore several possible mechanistic explanations for differences in GSref among trees. Topoedaphic factors are considered to determine if location within a stand has an effect. We also consider competition with neighboring individuals as a possible explanation. Variations in GSref in aspen were explained in part by competition for light between neighboring individuals, while competition for light was not a significant factor for sugar maple. Based on simulation analysis we identify possible biochemical feedbacks as drivers of the variability in plant hydraulics. Other factors examined included micro-topography within both sites.

Applying spatio-temporal models to assess variations across health care areas and regions: Lessons from the decentralized Spanish National Health System.

PubMed

Librero, Julián; Ibañez, Berta; Martínez-Lizaga, Natalia; Peiró, Salvador; Bernal-Delgado, Enrique

2017-01-01

To illustrate the ability of hierarchical Bayesian spatio-temporal models in capturing different geo-temporal structures in order to explain hospital risk variations using three different conditions: Percutaneous Coronary Intervention (PCI), Colectomy in Colorectal Cancer (CCC) and Chronic Obstructive Pulmonary Disease (COPD). This is an observational population-based spatio-temporal study, from 2002 to 2013, with a two-level geographical structure, Autonomous Communities (AC) and Health Care Areas (HA). The Spanish National Health System, a quasi-federal structure with 17 regional governments (AC) with full responsibility in planning and financing, and 203 HA providing hospital and primary care to a defined population. A poisson-log normal mixed model in the Bayesian framework was fitted using the INLA efficient estimation procedure. The spatio-temporal hospitalization relative risks, the evolution of their variation, and the relative contribution (fraction of variation) of each of the model components (AC, HA, year and interaction AC-year). Following PCI-CCC-CODP order, the three conditions show differences in the initial hospitalization rates (from 4 to 21 per 10,000 person-years) and in their trends (upward, inverted V shape, downward). Most of the risk variation is captured by phenomena occurring at the HA level (fraction variance: 51.6, 54.7 and 56.9%). At AC level, the risk of PCI hospitalization follow a heterogeneous ascending dynamic (interaction AC-year: 17.7%), whereas in COPD the AC role is more homogenous and important (37%). In a system where the decisions loci are differentiated, the spatio-temporal modeling allows to assess the dynamic relative role of different levels of decision and their influence on health outcomes.

Oscillations and patterns in a model of simultaneous CO and C2H2 oxidation and NO(x) reduction in a cross-flow reactor.

PubMed

Hadač, Otto; Kohout, Martin; Havlica, Jaromír; Schreiber, Igor

2015-03-07

A model describing simultaneous catalytic oxidation of CO and C2H2 and reduction of NOx in a cross-flow tubular reactor is explored with the aim of relating spatiotemporal patterns to specific pathways in the mechanism. For that purpose, a detailed mechanism proposed for three-way catalytic converters is split into two subsystems, (i) simultaneous oxidation of CO and C2H2, and (ii) oxidation of CO combined with NOx reduction. The ability of these two subsystems to display mechanism-specific dynamical effects is studied initially by neglecting transport phenomena and applying stoichiometric network and bifurcation analyses. We obtain inlet temperature - inlet oxygen concentration bifurcation diagrams, where each region possessing specific dynamics - oscillatory, bistable and excitable - is associated with a dominant reaction pathway. Next, the spatiotemporal behaviour due to reaction kinetics combined with transport processes is studied. The observed spatiotemporal patterns include phase waves, travelling fronts, pulse waves and spatiotemporal chaos. Although these types of pattern occur generally when the kinetic scheme possesses autocatalysis, we find that some of their properties depend on the underlying dominant reaction pathway. The relation of patterns to specific reaction pathways is discussed.

Spatio-Temporal Clustering of Monitoring Network

NASA Astrophysics Data System (ADS)

Hussain, I.; Pilz, J.

2009-04-01

Pakistan has much diversity in seasonal variation of different locations. Some areas are in desserts and remain very hot and waterless, for example coastal areas are situated along the Arabian Sea and have very warm season and a little rainfall. Some areas are covered with mountains, have very low temperature and heavy rainfall; for instance Karakoram ranges. The most important variables that have an impact on the climate are temperature, precipitation, humidity, wind speed and elevation. Furthermore, it is hard to find homogeneous regions in Pakistan with respect to climate variation. Identification of homogeneous regions in Pakistan can be useful in many aspects. It can be helpful for prediction of the climate in the sub-regions and for optimizing the number of monitoring sites. In the earlier literature no one tried to identify homogeneous regions of Pakistan with respect to climate variation. There are only a few papers about spatio-temporal clustering of monitoring network. Steinhaus (1956) presented the well-known K-means clustering method. It can identify a predefined number of clusters by iteratively assigning centriods to clusters based. Castro et al. (1997) developed a genetic heuristic algorithm to solve medoids based clustering. Their method is based on genetic recombination upon random assorting recombination. The suggested method is appropriate for clustering the attributes which have genetic characteristics. Sap and Awan (2005) presented a robust weighted kernel K-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data. Soltani and Modarres (2006) used hierarchical and divisive cluster analysis to categorize patterns of rainfall in Iran. They only considered rainfall at twenty-eight monitoring sites and concluded that eight clusters existed. Soltani and Modarres (2006) classified the sites by using only average rainfall of sites, they did not consider time replications and spatial coordinates. Kerby et.al (2007) purposed spatial clustering method based on likelihood. They took account of the geographic locations through the variance covariance matrix. Their purposed method works like hierarchical clustering methods. Moreovere, it is inappropiriate for time replication data and could not perform well for large number of sites. Tuia.et.al (2008) used scan statistics for identifying spatio-temporal clusters for fire sequences in the Tuscany region in Italy. The scan statistics clustering method was developed by Kulldorff et al. (1997) to detect spatio-temporal clusters in epidemiology and assessing their significance. The purposed scan statistics method is used only for univariate discrete stochastic random variables. In this paper we make use of a very simple approach for spatio-temporal clustering which can create separable and homogeneous clusters. Most of the clustering methods are based on Euclidean distances. It is well known that geographic coordinates are spherical coordinates and estimating Euclidean distances from spherical coordinates is inappropriate. As a transformation from geographic coordinates to rectangular (D-plane) coordinates we use the Lambert projection method. The partition around medoids clustering method is incorporated on the data including D-plane coordinates. Ordinary kriging is taken as validity measure for the precipitation data. The kriging results for clusters are more accurate and have less variation compared to complete monitoring network precipitation data. References Casto.V.E and Murray.A.T (1997). Spatial Clustering with Data Mining with Genetic Algorithms. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.8573 Kaufman.L and Rousseeuw.P.J (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley series of Probability and Mathematical Statistics, New York. Kulldorf.M (1997). A spatial scan statistic. Commun. Stat.-Theor. Math. 26(6), 1481-1496 Kerby. A , Marx. D, Samal. A and Adamchuck. V. (2007). Spatial Clustering Using the Likelihood Function. Seventh IEEE International Conference on Data Mining - Workshops Steinhaus.H (1956). Sur la division des corp materiels en parties. Bull. Acad. Polon. Sci., C1. III vol IV:801- 804 Snyder, J. P. (1987). Map Projection: A Working Manual. U. S. Geological Survey Professional Paper 1395. Washington, DC: U. S. Government Printing Office, pp. 104-110 Sap.M.N and Awan. A.M (2005). Finding Spatio-Temporal Patterns in Climate Data Using Clustering. Proceedings of the International Conference on Cyberworlds (CW'05) Soltani.S and Modarres.R (2006). Classification of Spatio -Temporal Pattern of Rainfall in Iran: Using Hierarchical and Divisive Cluster Analysis. Journal of Spatial Hydrology Vol.6, No.2 Tuia.D, Ratle.F, Lasaponara.R, Telesca.L and Kanevski.M (2008). Scan Statistics Analysis for Forest Fire Clusters. Commun. in Nonlinear science and numerical simulation 13,1689-1694.

Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.

PubMed

Lee, Sungjun; Lim, Junseok; Park, Jonghun; Kim, Kwanho

2016-01-23

Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user's next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user's past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user's next places than the previous approaches considered in most cases.

Synchronization and spatiotemporal patterns in coupled phase oscillators on a weighted planar network

NASA Astrophysics Data System (ADS)

Kagawa, Yuki; Takamatsu, Atsuko

2009-04-01

To reveal the relation between network structures found in two-dimensional biological systems, such as protoplasmic tube networks in the plasmodium of true slime mold, and spatiotemporal oscillation patterns emerged on the networks, we constructed coupled phase oscillators on weighted planar networks and investigated their dynamics. Results showed that the distribution of edge weights in the networks strongly affects (i) the propensity for global synchronization and (ii) emerging ratios of oscillation patterns, such as traveling and concentric waves, even if the total weight is fixed. In-phase locking, traveling wave, and concentric wave patterns were, respectively, observed most frequently in uniformly weighted, center weighted treelike, and periphery weighted ring-shaped networks. Controlling the global spatiotemporal patterns with the weight distribution given by the local weighting (coupling) rules might be useful in biological network systems including the plasmodial networks and neural networks in the brain.

Spatiotemporal Patterns of Noise-Driven Confined Actin Waves in Living Cells.

PubMed

Bernitt, Erik; Döbereiner, Hans-Günther

2017-01-27

Cells utilize waves of polymerizing actin to reshape their morphologies, which is central to physiological and pathological processes alike. Here, we force dorsal actin waves to propagate on one-dimensional domains with periodic boundary conditions, which results in striking spatiotemporal patterns with a clear signature of noise-driven dynamics. We show that these patterns can be very closely reproduced with a noise-driven active medium at coherence resonance.

Chimera states in networks of logistic maps with hierarchical connectivities

NASA Astrophysics Data System (ADS)

zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2018-04-01

Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

Legacy introductions and climatic variation explain spatiotemporal patterns of invasive hybridization in a native trout.

PubMed

Muhlfeld, Clint C; Kovach, Ryan P; Al-Chokhachy, Robert; Amish, Stephen J; Kershner, Jeffrey L; Leary, Robb F; Lowe, Winsor H; Luikart, Gordon; Matson, Phil; Schmetterling, David A; Shepard, Bradley B; Westley, Peter A H; Whited, Diane; Whiteley, Andrew; Allendorf, Fred W

2017-11-01

Hybridization between invasive and native species, a significant threat to worldwide biodiversity, is predicted to increase due to climate-induced expansions of invasive species. Long-term research and monitoring are crucial for understanding the ecological and evolutionary processes that modulate the effects of invasive species. Using a large, multidecade genetics dataset (N = 582 sites, 12,878 individuals) with high-resolution climate predictions and extensive stocking records, we evaluate the spatiotemporal dynamics of hybridization between native cutthroat trout and invasive rainbow trout, the world's most widely introduced invasive fish, across the Northern Rocky Mountains of the United States. Historical effects of stocking and contemporary patterns of climatic variation were strongly related to the spread of hybridization across space and time. The probability of occurrence, extent of, and temporal changes in hybridization increased at sites in close proximity to historical stocking locations with greater rainbow trout propagule pressure, warmer water temperatures, and lower spring precipitation. Although locations with warmer water temperatures were more prone to hybridization, cold sites were not protected from invasion; 58% of hybridized sites had cold mean summer water temperatures (<11°C). Despite cessation of stocking over 40 years ago, hybridization increased over time at half (50%) of the locations with long-term data, the vast majority of which (74%) were initially nonhybridized, emphasizing the chronic, negative impacts of human-mediated hybridization. These results show that effects of climate change on biodiversity must be analyzed in the context of historical human impacts that set ecological and evolutionary trajectories. © 2017 John Wiley & Sons Ltd.

Legacy introductions and climatic variation explain spatiotemporal patterns of invasive hybridization in a native trout

USGS Publications Warehouse

Muhlfeld, Clint C.; Kovach, Ryan P.; Al-Chokhachy, Robert K.; Amish, Stephen J.; Kershner, Jeffrey L.; Leary, Robb F.; Lowe, Winsor H.; Luikart, Gordon; Matson, Phil; Schmetterling, David A.; Shepard, Bradley B.; Westley, Peter A. H.; Whited, Diane; Whiteley, Andrew R.; Allendorf, Fred W.

2017-01-01

Hybridization between invasive and native species, a significant threat to worldwide biodiversity, is predicted to increase due to climate-induced expansions of invasive species. Long-term research and monitoring are crucial for understanding the ecological and evolutionary processes that modulate the effects of invasive species. Using a large, multi-decade genetics dataset (N = 582 sites, 12,878 individuals) with high-resolution climate predictions and extensive stocking records, we evaluate the spatiotemporal dynamics of hybridization between native cutthroat trout and invasive rainbow trout, the world’s most widely introduced invasive fish, across the northern Rocky Mountains of the United States. Historical effects of stocking and contemporary patterns of climatic variation were strongly related to the spread of hybridization across space and time. The probability of occurrence, extent of, and temporal changes in hybridization increased at sites in close proximity to historical stocking locations with greater rainbow trout propagule pressure, warmer water temperatures, and lower spring precipitation. Although locations with warmer water temperatures were more prone to hybridization, cold sites were not protected from invasion; 58% of hybridized sites had cold mean summer water temperatures (<11°C). Despite cessation of stocking over 40 years ago, hybridization increased over time at half (50%) of the locations with long-term data, the vast majority of which (74%) were initially non-hybridized, emphasizing the chronic, negative impacts of human-mediated hybridization. These results show that effects of climate change on biodiversity must be analyzed in the context of historical human impacts that set ecological and evolutionary trajectories.

Temporally diverse firing patterns in olfactory receptor neurons underlie spatiotemporal neural codes for odors

PubMed Central

Raman, Baranidharan; Joseph, Joby; Tang, Jeff; Stopfer, Mark

2010-01-01

Odorants are represented as spatiotemporal patterns of spikes in neurons of the antennal lobe (AL, insects) and olfactory bulb (OB, vertebrates). These response patterns have been thought to arise primarily from interactions within the AL/OB, an idea supported, in part, by the assumption that olfactory receptor neurons (ORNs) respond to odorants with simple firing patterns. However, activating the AL directly with simple pulses of current evoked responses in AL neurons that were much less diverse, complex, and enduring than responses elicited by odorants. Similarly, models of the AL driven by simplistic inputs generated relatively simple output. How then are dynamic neural codes for odors generated? Consistent with recent results from several other species, our recordings from locust ORNs showed a great diversity of temporal structure. Further, we found that, viewed as a population, many response features of ORNs were remarkably similar to those observed within the AL. Using a set of computational models constrained by our electrophysiological recordings, we found that the temporal heterogeneity of responses of ORNs critically underlies the generation of spatiotemporal odor codes in the AL. A test then performed in vivo confirmed that, given temporally homogeneous input, the AL cannot create diverse spatiotemporal patterns on its own; however, given temporally heterogeneous input, the AL generated realistic firing patterns. Finally, given the temporally structured input provided by ORNs, we clarified several separate, additional contributions of the AL to olfactory information processing. Thus, our results demonstrate the origin and subsequent reformatting of spatiotemporal neural codes for odors. PMID:20147528

The Limits of Human Stereopsis in Space and Time

PubMed Central

Kane, David; Guan, Phillip

2014-01-01

To encode binocular disparity, the visual system determines the image patches in one eye that yield the highest correlation with patches in the other eye. The computation of interocular correlation occurs after spatiotemporal filtering of monocular signals, which leads to restrictions on disparity variations that can support depth perception. We quantified those restrictions by measuring humans' ability to see disparity variation at a wide range of spatial and temporal frequencies. Lower-disparity thresholds cut off at very low spatiotemporal frequencies, which is consistent with the behavior of V1 neurons. Those thresholds are space–time separable, suggesting that the underlying neural mechanisms are separable. We also found that upper-disparity limits were characterized by a spatiotemporal, disparity-gradient limit; to be visible, disparity variation cannot exceed a fixed amount for a given interval in space–time. Our results illustrate that the disparity variations that humans can see are very restricted compared with the corresponding luminance variations. The results also provide insight into the neural mechanisms underlying depth from disparity, such as why stimuli with long interocular delays can still yield clear depth percepts. PMID:24453329

Spatio-temporal Variations of Nitrogen Dioxide over Western China from Satellite Observations during 2005-2013

NASA Astrophysics Data System (ADS)

Cui, Y.; Lin, J.; Huang, B.; Song, C.

2015-12-01

Western China has experienced rapid urbanization and industrialization since the implementation of National Western Development Strategy by Chinese Government. Most resource-intensive industries and high-pollution factories had been moved from the east coast to Western China after 2000. In this research, the spatial and temporal variations of tropospheric NO2 concentration in 2005 - 2013 is analyzed based on the satellite observations by Ozone Measurement Instrument (OMI). The annual trends and seasonality of tropospheric NO2 over Western China are calculated. The results show that large increases are observed in urban areas and the polluted regions are expanding. Additionally, the seasonal patterns of some regions over Western China are changing significantly and more clean areas tend to changing from the characteristics of natural emissions to those of anthropogenic emissions. The spatial and temporal variations of NO2 concentrations are well responded to the rapid urbanization and industrialization over Western China.

Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

NASA Astrophysics Data System (ADS)

Daya Sagar, B. S.

2005-01-01

Spatio-temporal patterns of small water bodies (SWBs) under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs) controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

Spatiotemporal variation in reproductive parameters of yellow-bellied marmots.

PubMed

Ozgul, Arpat; Oli, Madan K; Olson, Lucretia E; Blumstein, Daniel T; Armitage, Kenneth B

2007-11-01

Spatiotemporal variation in reproductive rates is a common phenomenon in many wildlife populations, but the population dynamic consequences of spatial and temporal variability in different components of reproduction remain poorly understood. We used 43 years (1962-2004) of data from 17 locations and a capture-mark-recapture (CMR) modeling framework to investigate the spatiotemporal variation in reproductive parameters of yellow-bellied marmots (Marmota flaviventris), and its influence on the realized population growth rate. Specifically, we estimated and modeled breeding probabilities of two-year-old females (earliest age of first reproduction), >2-year-old females that have not reproduced before (subadults), and >2-year-old females that have reproduced before (adults), as well as the litter sizes of two-year old and >2-year-old females. Most reproductive parameters exhibited spatial and/or temporal variation. However, reproductive parameters differed with respect to their relative influence on the realized population growth rate (lambda). Litter size had a stronger influence than did breeding probabilities on both spatial and temporal variations in lambda. Our analysis indicated that lambda was proportionately more sensitive to survival than recruitment. However, the annual fluctuation in litter size, abetted by the breeding probabilities, accounted for most of the temporal variation in lambda.

Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data

ERIC Educational Resources Information Center

Li, Xun

2012-01-01

This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data…

Spatiotemporal Variation in Distance Dependent Animal Movement Contacts: One Size Doesn’t Fit All

PubMed Central

Brommesson, Peter; Wennergren, Uno; Lindström, Tom

2016-01-01

The structure of contacts that mediate transmission has a pronounced effect on the outbreak dynamics of infectious disease and simulation models are powerful tools to inform policy decisions. Most simulation models of livestock disease spread rely to some degree on predictions of animal movement between holdings. Typically, movements are more common between nearby farms than between those located far away from each other. Here, we assessed spatiotemporal variation in such distance dependence of animal movement contacts from an epidemiological perspective. We evaluated and compared nine statistical models, applied to Swedish movement data from 2008. The models differed in at what level (if at all), they accounted for regional and/or seasonal heterogeneities in the distance dependence of the contacts. Using a kernel approach to describe how probability of contacts between farms changes with distance, we developed a hierarchical Bayesian framework and estimated parameters by using Markov Chain Monte Carlo techniques. We evaluated models by three different approaches of model selection. First, we used Deviance Information Criterion to evaluate their performance relative to each other. Secondly, we estimated the log predictive posterior distribution, this was also used to evaluate their relative performance. Thirdly, we performed posterior predictive checks by simulating movements with each of the parameterized models and evaluated their ability to recapture relevant summary statistics. Independent of selection criteria, we found that accounting for regional heterogeneity improved model accuracy. We also found that accounting for seasonal heterogeneity was beneficial, in terms of model accuracy, according to two of three methods used for model selection. Our results have important implications for livestock disease spread models where movement is an important risk factor for between farm transmission. We argue that modelers should refrain from using methods to simulate animal movements that assume the same pattern across all regions and seasons without explicitly testing for spatiotemporal variation. PMID:27760155

Spatiotemporal chaos involving wave instability.

PubMed

Berenstein, Igal; Carballido-Landeira, Jorge

2017-01-01

In this paper, we investigate pattern formation in a model of a reaction confined in a microemulsion, in a regime where both Turing and wave instability occur. In one-dimensional systems, the pattern corresponds to spatiotemporal intermittency where the behavior of the systems alternates in both time and space between stationary Turing patterns and traveling waves. In two-dimensional systems, the behavior initially may correspond to Turing patterns, which then turn into wave patterns. The resulting pattern also corresponds to a chaotic state, where the system alternates in both space and time between standing wave patterns and traveling waves, and the local dynamics may show vanishing amplitude of the variables.

Spatiotemporal chaos involving wave instability

NASA Astrophysics Data System (ADS)

Berenstein, Igal; Carballido-Landeira, Jorge

2017-01-01

In this paper, we investigate pattern formation in a model of a reaction confined in a microemulsion, in a regime where both Turing and wave instability occur. In one-dimensional systems, the pattern corresponds to spatiotemporal intermittency where the behavior of the systems alternates in both time and space between stationary Turing patterns and traveling waves. In two-dimensional systems, the behavior initially may correspond to Turing patterns, which then turn into wave patterns. The resulting pattern also corresponds to a chaotic state, where the system alternates in both space and time between standing wave patterns and traveling waves, and the local dynamics may show vanishing amplitude of the variables.

Early perception and structural identity: neural implementation

NASA Astrophysics Data System (ADS)

Ligomenides, Panos A.

1992-03-01

It is suggested that there exists a minimal set of rules for the perceptual composition of the unending variety of spatio-temporal patterns in our perceptual world. Driven by perceptual discernment of "sudden change" and "unexpectedness", these rules specify conditions (such as co-linearity and virtual continuation) for perceptual grouping and for recursive compositions of perceptual "modalities" and "signatures". Beginning with a smallset of primitive perceptual elements, selected contextually at some relevant level of abstraction, perceptual compositions can graduate to an unlimited variety of spatiotemporal signatures, scenes and activities. Local discernible elements, often perceptually ambiguous by themselves, may be integrated into spatiotemporal compositions, which generate unambiguous perceptual separations between "figure" and "ground". The definition of computational algorithms for the effective instantiation of the rules of perceptual grouping remains a principal problem. In this paper we present our approach for solving the problem of perceptual recognition within the confines of one-D variational profiles. More specifically, concerning "early" (pre-attentive) recognition, we define the "structural identity of a k-norm, k ∈ K,"--SkID--as a tool for discerning and locating the instantiation of spatiotemporal objects or events. The SkID profile also serves a s a reference coordinate framework for the "perceptual focusing of attention" and the eventual assessment of resemblance. Neural network implementations of pre-attentive and attentive recognition are also discussed briefly. Our principles are exemplified by application to one-D perceptual profiles, which allows simplicity of definitions and of the rules of perceptual composition.

Temporal variations in supraglacial debris distribution on Baltoro Glacier, Karakoram between 2001 and 2012

NASA Astrophysics Data System (ADS)

Gibson, Morgan J.; Glasser, Neil F.; Quincey, Duncan J.; Mayer, Christoph; Rowan, Ann V.; Irvine-Fynn, Tristram D. L.

2017-10-01

Distribution of supraglacial debris in a glacier system varies spatially and temporally due to differing rates of debris input, transport and deposition. Supraglacial debris distribution governs the thickness of a supraglacial debris layer, an important control on the amount of ablation that occurs under such a debris layer. Characterising supraglacial debris layer thickness on a glacier is therefore key to calculating ablation across a glacier surface. The spatial pattern of debris thickness on Baltoro Glacier has previously been calculated for one discrete point in time (2004) using satellite thermal data and an empirically based relationship between supraglacial debris layer thickness and debris surface temperature identified in the field. Here, the same empirically based relationship was applied to two further datasets (2001, 2012) to calculate debris layer thickness across Baltoro Glacier for three discrete points over an 11-year period (2001, 2004, 2012). Surface velocity and sediment flux were also calculated, as well as debris thickness change between periods. Using these outputs, alongside geomorphological maps of Baltoro Glacier produced for 2001, 2004 and 2012, spatiotemporal changes in debris distribution for a sub-decadal timescale were investigated. Sediment flux remained constant throughout the 11-year period. The greatest changes in debris thickness occurred along medial moraines, the locations of mass movement deposition and areas of interaction between tributary glaciers and the main glacier tongue. The study confirms the occurrence of spatiotemporal changes in supraglacial debris layer thickness on sub-decadal timescales, independent of variation in surface velocity. Instead, variation in rates of debris distribution are primarily attributed to frequency and magnitude of mass movement events over decadal timescales, with climate, regional uplift and erosion rates expected to control debris inputs over centurial to millennial timescales. Inclusion of such spatiotemporal variations in debris thickness in distributed surface energy balance models would increase the accuracy of calculated ablation, leading to a more accurate simulation of glacier mass balance through time, and greater precision in quantification of the response of debris-covered glaciers to climatic change.

Changes in intrapopulation resource use patterns of an endangered raptor in response to a disease-mediated crash in prey abundance.

PubMed

Moleón, Marcos; Sebastián-González, Esther; Sánchez-Zapata, José A; Real, Joan; Pires, Mathias M; Gil-Sánchez, José M; Bautista, Jesús; Palma, Luís; Bayle, Patrick; Guimarães, Paulo R; Beja, Pedro

2012-11-01

1. A long-standing question in ecology is how natural populations respond to a changing environment. Emergent optimal foraging theory-based models for individual variation go beyond the population level and predict how its individuals would respond to disturbances that produce changes in resource availability. 2. Evaluating variations in resource use patterns at the intrapopulation level in wild populations under changing environmental conditions would allow to further advance in the research on foraging ecology and evolution by gaining a better idea of the underlying mechanisms explaining trophic diversity. 3. In this study, we use a large spatio-temporal scale data set (western continental Europe, 1968-2006) on the diet of Bonelli's Eagle Aquila fasciata breeding pairs to analyse the predator trophic responses at the intrapopulation level to a prey population crash. In particular, we borrow metrics from studies on network structure and intrapopulation variation to understand how an emerging infectious disease [the rabbit haemorrhagic disease (RHD)] that caused the density of the eagle's primary prey (rabbit Oryctolagus cuniculus) to dramatically drop across Europe impacted on resource use patterns of this endangered raptor. 4. Following the major RHD outbreak, substantial changes in Bonelli's Eagle's diet diversity and organisation patterns at the intrapopulation level took place. Dietary variation among breeding pairs was larger after than before the outbreak. Before RHD, there were no clusters of pairs with similar diets, but significant clustering emerged after RHD. Moreover, diets at the pair level presented a nested pattern before RHD, but not after. 5. Here, we reveal how intrapopulation patterns of resource use can quantitatively and qualitatively vary, given drastic changes in resource availability. 6. For the first time, we show that a pathogen of a prey species can indirectly impact the intrapopulation patterns of resource use of an endangered predator. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

Diet of a piscivorous seabird reveals spatiotemporal variation in abundance of forage fishes in the Monterey Bay region

NASA Astrophysics Data System (ADS)

Webb, Lisa A.; Harvey, James T.

2015-06-01

Brandt's Cormorant (Phalacrocorax penicillatus) diet was investigated using regurgitated pellets (n = 285) collected on 19 sampling days at three locations during the 2006-07 and 2007-08 nonbreeding seasons in the Monterey Bay region. The efficacy of using nested sieves and the all-structure technique to facilitate prey detection in the pellets was evaluated, but this method did not increase prey enumeration and greatly decreased efficiency. Although 29 prey species were consumed, northern anchovy (Engraulis mordax) dominated and speckled sanddab (Citharichthys stigmaeus) also was important in the diet. Few rockfishes (Sebastes spp.) and market squid (Doryteuthis opalescens) were consumed compared with great prevalence in previous studies during the 1970s. El Niño and La Niña during the study provided a unique opportunity to examine predator response to variation in prey availability. Patterns of prey number and diversity were not consistent among locations. Greatest number and diversity of prey occurred at locations within Monterey Bay during La Niña, results not evident at the outer coast location. Short-term specialization occurred but mean prey diversity indicated a generalist feeding mode. This study demonstrated the importance of periodic sampling at multiple locations within a region to detect spatiotemporal variability in the diet of opportunistic generalists.

Seasonal dynamics of bacterioplankton community in a large, shallow, highly dynamic freshwater lake.

PubMed

Kong, Zhaoyu; Kou, Wenbo; Ma, Yantian; Yu, Haotian; Ge, Gang; Wu, Lan

2018-05-23

The spatio-temporal shifts of bacterioplankton community can mirror their transition of functional traits in aquatic ecosystem. However, our understanding of spatio-temporal variation of bacterioplankton community composition structure (BCCs) within large, shallow and highly dynamic freshwater lake is still elusive. Here we examined the seasonal and spatial variability of BCCs in the Poyang Lake by 16S rRNA gene amplicon sequencing to explore how hydrological changes affect the BCCs. Principal coordinate analysis showed that the BCCs varied significantly among four sampling seasons, but not spatially. The seasonal changes of BCCs were mainly attributed to the differences between autumn and spring/winter. Higher alpha diversity indices were observed in autumn. Redundancy analysis indicated that the BCCs co-variated with water level, pH, temperature, total phosphorus, ammoniacal nitrogen, electrical conductivity, total nitrogen, and turbidity. Among them, water level was the key determinant separating autumn BCCs from the BCCs in other seasons. A significant lower relative abundance of Burkholderiales (betI and betVII) and a higher relative abundance of Actinomycetales (acI, acTH1 and acTH2) were found in autumn than in other seasons. Overall, our results suggest that water level changes associated with pH, temperature and nutrient status shaped the seasonal patterns of BCCs in the Poyang Lake.

Spatiotemporal distribution patterns of forest fires in northern Mexico

Treesearch

Gustavo Pérez-Verdin; M. A. Márquez-Linares; A. Cortes-Ortiz; M. Salmerón-Macias

2013-01-01

Using the 2000-2011 CONAFOR databases, a spatiotemporal analysis of the occurrence of forest fires in Durango, one of the most affected States in Mexico, was conducted. The Moran's index was used to determine a spatial distribution pattern; also, an analysis of seasonal and temporal autocorrelation of the data collected was completed. The geographically weighted...

Pacifier Stiffness Alters the Dynamics of the Suck Central Pattern Generator.

PubMed

Zimmerman, Emily; Barlow, Steven M

2008-06-01

Variation in pacifier stiffness on non-nutritive suck (NNS) dynamics was examined among infants born prematurely with a history of respiratory distress syndrome. Three types of silicone pacifiers used in the NICU were tested for stiffness, revealing the Super Soothie™ nipple is 7 times stiffer than the Wee™ or Soothie™ pacifiers even though shape and displaced volume are identical. Suck dynamics among 20 preterm infants were subsequently sampled using the Soothie™ and Super Soothie™ pacifiers during follow-up at approximately 3 months of age. ANOVA revealed significant differences in NNS cycles/min, NNS amplitude, NNS cycles/burst, and NNS cycle periods as a function of pacifier stiffness. Infants modify the spatiotemporal output of their suck central pattern generator when presented with pacifiers with significantly different mechanical properties. Infants show a non-preference to suck due to high stiffness in the selected pacifier. Therefore, excessive pacifier stiffness may decrease ororhythmic patterning and impact feeding outcomes.

Pacifier Stiffness Alters the Dynamics of the Suck Central Pattern Generator

PubMed Central

Zimmerman, Emily; Barlow, Steven M.

2008-01-01

Variation in pacifier stiffness on non-nutritive suck (NNS) dynamics was examined among infants born prematurely with a history of respiratory distress syndrome. Three types of silicone pacifiers used in the NICU were tested for stiffness, revealing the Super Soothie™ nipple is 7 times stiffer than the Wee™ or Soothie™ pacifiers even though shape and displaced volume are identical. Suck dynamics among 20 preterm infants were subsequently sampled using the Soothie™ and Super Soothie™ pacifiers during follow-up at approximately 3 months of age. ANOVA revealed significant differences in NNS cycles/min, NNS amplitude, NNS cycles/burst, and NNS cycle periods as a function of pacifier stiffness. Infants modify the spatiotemporal output of their suck central pattern generator when presented with pacifiers with significantly different mechanical properties. Infants show a non-preference to suck due to high stiffness in the selected pacifier. Therefore, excessive pacifier stiffness may decrease ororhythmic patterning and impact feeding outcomes. PMID:19492006

Frequency spirals.

PubMed

Ottino-Löffler, Bertrand; Strogatz, Steven H

2016-09-01

We study the dynamics of coupled phase oscillators on a two-dimensional Kuramoto lattice with periodic boundary conditions. For coupling strengths just below the transition to global phase-locking, we find localized spatiotemporal patterns that we call "frequency spirals." These patterns cannot be seen under time averaging; they become visible only when we examine the spatial variation of the oscillators' instantaneous frequencies, where they manifest themselves as two-armed rotating spirals. In the more familiar phase representation, they appear as wobbly periodic patterns surrounding a phase vortex. Unlike the stationary phase vortices seen in magnetic spin systems, or the rotating spiral waves seen in reaction-diffusion systems, frequency spirals librate: the phases of the oscillators surrounding the central vortex move forward and then backward, executing a periodic motion with zero winding number. We construct the simplest frequency spiral and characterize its properties using analytical and numerical methods. Simulations show that frequency spirals in large lattices behave much like this simple prototype.

Genetic drift and collective dispersal can result in chaotic genetic patchiness.

PubMed

Broquet, Thomas; Viard, Frédérique; Yearsley, Jonathan M

2013-06-01

Chaotic genetic patchiness denotes unexpected patterns of genetic differentiation that are observed at a fine scale and are not stable in time. These patterns have been described in marine species with free-living larvae, but are unexpected because they occur at a scale below the dispersal range of pelagic larvae. At the scale where most larvae are immigrants, theory predicts spatially homogeneous, temporally stable genetic variation. Empirical studies have suggested that genetic drift interacts with complex dispersal patterns to create chaotic genetic patchiness. Here we use a co-ancestry model and individual-based simulations to test this idea. We found that chaotic genetic patterns (qualified by global FST and spatio-temporal variation in FST's between pairs of samples) arise from the combined effects of (1) genetic drift created by the small local effective population sizes of the sessile phase and variance in contribution among breeding groups and (2) collective dispersal of related individuals in the larval phase. Simulations show that patchiness levels qualitatively comparable to empirical results can be produced by a combination of strong variance in reproductive success and mild collective dispersal. These results call for empirical studies of the effective number of breeders producing larval cohorts, and population genetics at the larval stage. © 2012 The Author(s). Evolution © 2012 The Society for the Study of Evolution.

Discovery of spatio-temporal patterns from location-based social networks

NASA Astrophysics Data System (ADS)

Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

2016-03-01

Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

Modeling how shark and dolphin skin patterns control transitional wall-turbulence vorticity patterns using spatiotemporal phase reset mechanisms

PubMed Central

Bandyopadhyay, Promode R.; Hellum, Aren M.

2014-01-01

Many slow-moving biological systems like seashells and zebrafish that do not contend with wall turbulence have somewhat organized pigmentation patterns flush with their outer surfaces that are formed by underlying autonomous reaction-diffusion (RD) mechanisms. In contrast, sharks and dolphins contend with wall turbulence, are fast swimmers, and have more organized skin patterns that are proud and sometimes vibrate. A nonlinear spatiotemporal analytical model is not available that explains the mechanism underlying control of flow with such proud patterns, despite the fact that shark and dolphin skins are major targets of reverse engineering mechanisms of drag and noise reduction. Comparable to RD, a minimal self-regulation model is given for wall turbulence regeneration in the transitional regime—laterally coupled, diffusively—which, although restricted to pre-breakdown durations and to a plane close and parallel to the wall, correctly reproduces many experimentally observed spatiotemporal organizations of vorticity in both laminar-to-turbulence transitioning and very low Reynolds number but turbulent regions. We further show that the onset of vorticity disorganization is delayed if the skin organization is treated as a spatiotemporal template of olivo-cerebellar phase reset mechanism. The model shows that the adaptation mechanisms of sharks and dolphins to their fluid environment have much in common. PMID:25338940

Modeling how shark and dolphin skin patterns control transitional wall-turbulence vorticity patterns using spatiotemporal phase reset mechanisms.

PubMed

Bandyopadhyay, Promode R; Hellum, Aren M

2014-10-23

Many slow-moving biological systems like seashells and zebrafish that do not contend with wall turbulence have somewhat organized pigmentation patterns flush with their outer surfaces that are formed by underlying autonomous reaction-diffusion (RD) mechanisms. In contrast, sharks and dolphins contend with wall turbulence, are fast swimmers, and have more organized skin patterns that are proud and sometimes vibrate. A nonlinear spatiotemporal analytical model is not available that explains the mechanism underlying control of flow with such proud patterns, despite the fact that shark and dolphin skins are major targets of reverse engineering mechanisms of drag and noise reduction. Comparable to RD, a minimal self-regulation model is given for wall turbulence regeneration in the transitional regime--laterally coupled, diffusively--which, although restricted to pre-breakdown durations and to a plane close and parallel to the wall, correctly reproduces many experimentally observed spatiotemporal organizations of vorticity in both laminar-to-turbulence transitioning and very low Reynolds number but turbulent regions. We further show that the onset of vorticity disorganization is delayed if the skin organization is treated as a spatiotemporal template of olivo-cerebellar phase reset mechanism. The model shows that the adaptation mechanisms of sharks and dolphins to their fluid environment have much in common.

Subject-specific longitudinal shape analysis by coupling spatiotemporal shape modeling with medial analysis

NASA Astrophysics Data System (ADS)

Hong, Sungmin; Fishbaugh, James; Rezanejad, Morteza; Siddiqi, Kaleem; Johnson, Hans; Paulsen, Jane; Kim, Eun Young; Gerig, Guido

2017-02-01

Modeling subject-specific shape change is one of the most important challenges in longitudinal shape analysis of disease progression. Whereas anatomical change over time can be a function of normal aging, anatomy can also be impacted by disease related degeneration. Anatomical shape change may also be affected by structural changes from neighboring shapes, which may cause non-linear variations in pose. In this paper, we propose a framework to analyze disease related shape changes by coupling extrinsic modeling of the ambient anatomical space via spatiotemporal deformations with intrinsic shape properties from medial surface analysis. We compare intrinsic shape properties of a subject-specific shape trajectory to a normative 4D shape atlas representing normal aging to isolate shape changes related to disease. The spatiotemporal shape modeling establishes inter/intra subject anatomical correspondence, which in turn enables comparisons between subjects and the 4D shape atlas, and also quantitative analysis of disease related shape change. The medial surface analysis captures intrinsic shape properties related to local patterns of deformation. The proposed framework jointly models extrinsic longitudinal shape changes in the ambient anatomical space, as well as intrinsic shape properties to give localized measurements of degeneration. Six high risk subjects and six controls are randomly sampled from a Huntington's disease image database for qualitative and quantitative comparison.

Pragmatic estimation of a spatio-temporal air quality model with irregular monitoring data

NASA Astrophysics Data System (ADS)

Sampson, Paul D.; Szpiro, Adam A.; Sheppard, Lianne; Lindström, Johan; Kaufman, Joel D.

2011-11-01

Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in "land use" regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM 2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.

Distribution Patterns of Microbial Community Structure Along a 7000-Mile Latitudinal Transect from the Mediterranean Sea Across the Atlantic Ocean to the Brazilian Coastal Sea.

PubMed

Zhou, Jin; Song, Xiao; Zhang, Chun-Yun; Chen, Guo-Fu; Lao, Yong-Min; Jin, Hui; Cai, Zhong-Hua

2018-02-14

A central goal in marine microecology is to understand the ecological factors shaping spatiotemporal microbial patterns and the underlying processes. We hypothesized that abiotic and/or biotic interactions are probably more important for explaining the distribution patterns of marine bacterioplankton than environmental filtering. In this study, surface seawater samples were collected about 7000 miles from the Mediterranean Sea, transecting the North Atlantic Ocean, to the Brazilian marginal sea. In bacterial biosphere, SAR11, SAR86, Rhodobacteraceae, and Rhodospiriaceae were predominant in the Mediterranean Sea; Prochlorococcus was more frequent in Atlantic Ocean; whereas in the Brazilian coastal sea, the main bacterial members were Synechococcus and SAR11. With respect to archaea, Euryarchaeota were predominant in the Atlantic Ocean and Thaumarchaeota in the Mediterranean Sea. With respect to the eukaryotes, Syndiniales, Spumellaria, Cryomonadida, and Chlorodendrales were predominant in the open ocean, while diatoms and microzooplankton were dominant in the coastal sea. Distinct clusters of prokaryotes and eukaryotes displayed clear spatial heterogeneity. Among the environmental parameters measured, temperature and salinity were key factors controlling bacterial and archaeal community structure, respectively, whereas N/P/Si contributed to eukaryotic variation. The relative contribution of environmental parameters to the microbial distribution pattern was 45.2%. Interaction analysis showed that Gammaproteobacteria, Alphaproteobacteria, and Flavobacteriia were the keystone taxa within the positive-correlation network, while Thermoplasmata was the main contributor in the negative-correlation network. Our study demonstrated that microbial communities are co-governed by environmental filtering and biotic interactions, which are the main deterministic driving factors modulating the spatiotemporal patterns of marine plankton synergistically at the regional or global levels.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons.

PubMed

Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

2016-12-27

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

PubMed Central

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

Cenozoic dynamics of shallow-marine biodiversity in the Western Pacific

NASA Astrophysics Data System (ADS)

Yasuhara, M.; Iwatani, H.; Hunt, G.; Okahashi, H.; Kase, T.; Hayashi, H.; Irizuki, T.; Aguilar, Y. M.; Fernando, A. G. S.; Renema, W.

2016-12-01

Cenozoic dynamics of large-scale species diversity patterns remain poorly understood, especially for the Western Pacific, in part because of the paucity of well-dated fossil records from the tropics. Here we show the spatiotemporal dynamics of species diversity in the Western Pacific through the Cenozoic, focusing on the tropical Indo-Australian Archipelago (IAA) biodiversity hotspot. We analysed well-preserved fossil ostracodes from the tropical Western Pacific and combined their diversity data with other published data from the region to reconstruct Cenozoic dynamics of species diversity in the tropical- and northwestern Pacific Ocean. We fit generalized additive models to test for differences in richness over time and across geographic regions while accounting for sample size variation among samples. Low-, mid- and high-latitude regions all show a similar diversity trajectory: diversity is low in the Eocene and Oligocene, increases from the Early Miocene to the Plio-Pleistocene but then declines to the present day. Present day high biodiversity in these regions was established during the Pliocene with a remarkable diversification at that time. Latitudinal diversity patterns are relatively flat and never show as simple decline from the tropics to higher latitudes. Western Pacific Cenozoic ostracodes exhibit a spatiotemporal pattern of species diversity that is inconsistent with the commonly reported and persistent pattern of declining diversity from the tropics to the extratropics. While this inconsistency could be interpreted as evidence that ostracodes are a contrarian clade, Atlantic ostracodes display a standard latitudinal species diversity gradient. Contrasting patterns between oceans suggests an important role for regional factors (e.g., plate tectonics and temporal geomorphological dynamics) in shaping the biodiversity of the Western Pacific.

Complex responses of spring alpine vegetation phenology to snow cover dynamics over the Tibetan Plateau, China.

PubMed

Wang, Siyuan; Wang, Xiaoyue; Chen, Guangsheng; Yang, Qichun; Wang, Bin; Ma, Yuanxu; Shen, Ming

2017-09-01

Snow cover dynamics are considered to play a key role on spring phenological shifts in the high-latitude, so investigating responses of spring phenology to snow cover dynamics is becoming an increasingly important way to identify and predict global ecosystem dynamics. In this study, we quantified the temporal trends and spatial variations of spring phenology and snow cover across the Tibetan Plateau by calibrating and analyzing time series of the NOAA AVHRR-derived normalized difference vegetation index (NDVI) during 1983-2012. We also examined how snow cover dynamics affect the spatio-temporal pattern of spring alpine vegetation phenology over the plateau. Our results indicated that 52.21% of the plateau experienced a significant advancing trend in the beginning of vegetation growing season (BGS) and 34.30% exhibited a delaying trend. Accordingly, the snow cover duration days (SCD) and snow cover melt date (SCM) showed similar patterns with a decreasing trend in the west and an increasing trend in the southeast, but the start date of snow cover (SCS) showed an opposite pattern. Meanwhile, the spatial patterns of the BGS, SCD, SCS and SCM varied in accordance with the gradients of temperature, precipitation and topography across the plateau. The response relationship of spring phenology to snow cover dynamics varied within different climate, terrain and alpine plant community zones, and the spatio-temporal response patterns were primarily controlled by the long-term local heat-water conditions and topographic conditions. Moreover, temperature and precipitation played a profound impact on diverse responses of spring phenology to snow cover dynamics. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatio-Temporal Analysis to Predict Environmental Influence on Malaria

NASA Astrophysics Data System (ADS)

Baig, S.; Sarfraz, M. S.

2018-05-01

Malaria is a vector borne disease which is a major cause of morbidity and mortality. It is one of the major diseases in the category of infectious diseases. The survival and bionomics of malaria is affected by environmental factors such as climatic, demographic and land-use/land-cover etc. Currently, a very few under developing countries are using Geo-informatics approaches to control this disease. Gujrat a district of Pakistan, is still under threat of malaria disease. Current research is carried on malaria incidents obtained from District Executive Officer of Health Gujrat. The objective of this study was to explore the spatio-temporal patterns of malaria in district Gujrat and to identify the areas being affected by Malaria. Furthermore, it has been also analyzed the relationship between malaria incident and environmental factors in highly favorable zones. Data is analyzed based on spatial and temporal patterns using (Moran's I). Moreover cluster and hot spots analysis were performed on the incident data. This study shows positive correlation with rainfall, vegetation index, population density and water bodies; while it shows positive and negative correlation with temperature in different seasons. However, variation between amount of vegetation and water bodies were observed. Finding of this research can help the decision makers to take preventive measures and reduce the morbidity and mortality related with malaria in Gujrat, Pakistan.

Spatiotemporal pattern of vegetation remote sensing phenology and its response to climatic factors on the Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

An, S.; Chen, X.

2015-12-01

Based on the MODIS MCD12Q2 remote sensing phenology product, we analyzed spatiotemporal variations of vegetation green-up, maturity, senescence and brown-off dates, and their relation to spatiotemporal patterns of air temperature and precipitation on the Qinghai-Tibet Plateau (QTP). From 2001 to 2012, phenological time series at about 11.7%~15.1% pixels indicate significant linear trends (P<0.1) with strong spatial consistency. Namely, pixels with significant phenological advancement and growing season lengthening are mainly distributed in the middle and eastern parts of the QTP, while pixels with significant phenological delay and growing season shortening are mainly distributed in the western and southern parts as well as the eastern edge of the QTP. Similar spatial patterns for positive and negative linear trends of the minimum and maximum EVI, and the time-integrated EVI during the growing season were detected in the above two regions, respectively. With regard to climatic factors, mean annual temperature shows an increased trend over the QTP except for the eastern edge, whereas annual precipitation displays an increased trend in the middle and eastern parts but a decreased trend in the western and southern parts as well as the eastern edge of the QTP. These findings suggest that phenological advancement, growing season lengthening, and vegetation activity enhancement in the middle and eastern parts might be attributed to coincident temperature and precipitation increase. By contrast, phenological delay, growing season shortening, and vegetation activity reduction in the western and southern parts as well as the eastern edge might be caused by opposite changes of temperature and precipitation, and strong evaporation induced water shortage. Furthermore, a partial correlation analysis indicates that green-up, maturity, and brown-off dates were influenced by preceding temperature and precipitation, while senescence date was affected by preceding precipitation.

Spatiotemporal Variance of Global Horizontal Moisture Transport and the Influence of Strong ENSO Events Using ERA-Interim Reanalysis

NASA Astrophysics Data System (ADS)

Kutta, E. J.; Hubbart, J. A.; Svoma, B. M.; Eichler, T. P.; Lupo, A. R.

2016-12-01

El Nino-Southern Oscillation (ENSO) is well documented as a leading source of seasonal to inter-annual variations in global weather and climate. Strong ENSO events have been shown to alter the location and magnitude of Hadley and Walker circulations that maintain equilibrium at tropical latitudes and regulate moisture transport into mid-latitude storm tracks. Broad impacts associated with ENSO events include anomalous regional precipitation (ARP) and temperature patterns and subsequent impacts to socioeconomic and human health systems. Potential socioeconomic and human health impacts range from regional changes in water resources and agricultural productivity to local storm water management, particularly in rapidly urbanizing watersheds. Evidence is mounting to suggest that anthropogenic climate change will increase the frequency of heavy precipitation events, which compounds impacts of ARP patterns associated with strong El Nino events. Therefore, the need exists to identify common regional patterns of spatiotemporal variance of horizontal moisture flux (HMF) during months (Oct-Feb) associated with the peak intensity (Oceanic Nino Index [ONI]) of the three strongest El Nino (ONI > µ + 2σ) and La Nina (ONI < µ - σ) events occurring between January 1979 and June 2016. ERA-Interim reanalysis output on model levels was used to quantify spatial and temporal covariance of HMF at 6-hourly resolution before taking the density weighted vertical average. Long term means (LTM; 1979-2015) were quantified and the influence of strong ENSO events was assessed by quantifying deviations from the LTM for each respective covariance property during months associated with the selected ENSO events. Results reveal regions of statistically significant (CI = 0.05) differences from the LTM for the vertically integrated HMF and each covariance quantity. Broader implications of this work include potential for improved seasonal precipitation forecasts at regional scales and subsequent improvements to local water resource management. There is potential for future work objectively comparing these results with output from Earth System Models to improve representation of ENSO's influence on spatiotemporal variance of horizontal moisture transport.

The role of soil communities in improving ecosystem services in organic farming

NASA Astrophysics Data System (ADS)

Zandbergen, Jelmer; Koorneef, Guusje; Veen, Cees; Schrama, Jan; van der Putten, Wim

2017-04-01

Worldwide soil fertility decreases and it is generally believed that organic matter (OM) addition to agricultural soils can improve soil properties leading to beneficial ecosystem services. However, it remains unknown under which conditions and how fast biotic, physical and chemical soil properties respond to varying quality and quantity of OM inputs. Therefore, the aims of this research project are (1) to unravel biotic, physical and chemical responses of soils to varying quantity and quality of OM addition; and (2) to understand how we can accelerate the response of soils in order to improve beneficial soil ecosystem services faster. The first step in our research project is to determine how small-scale spatio-temporal patterns in soil biotic, physical and chemical properties relate to crop production and quality. To do this we combine field measurements on soil properties with remote and proximate sensing measures on crop development and yield in a long-term farming systems experiment in the Netherlands (Vredepeel). We hypothesize that spatio-temporal variation in crop development and yield are strongly related to spatio-temporal variation in soil parameters. In the second step of our project we will use this information to identify biological interactions underlying improving soil functions in response to OM addition over time. We will specifically focus on the role of soil communities in driving nutrient cycling, disease suppression and the formation of soil structure, all crucial elements of key soil services in agricultural soils. The knowledge that will be generated in our project can be used to detect specific organic matter qualities that support the underlying ecological processes to accelerate the transition towards improved soil functioning thereby governing enhanced crop yields.

Nocturnal Near-Surface Temperature, but not Flow Dynamics, can be Predicted by Microtopography in a Mid-Range Mountain Valley

NASA Astrophysics Data System (ADS)

Pfister, Lena; Sigmund, Armin; Olesch, Johannes; Thomas, Christoph K.

2017-11-01

We investigate nocturnal flow dynamics and temperature behaviour near the surface of a 170-m long gentle slope in a mid-range mountain valley. In contrast to many existing studies focusing on locations with significant topographic variations, gentle slopes cover a greater spatial extent of the Earth's surface. Air temperatures were measured using the high-resolution distributed-temperature-sensing method within a two-dimensional fibre-optic array in the lowest metre above the surface. The main objectives are to characterize the spatio-temporal patterns in the near-surface temperature and flow dynamics, and quantify their responses to the microtopography and land cover. For the duration of the experiment, including even clear-sky nights with weak winds and strong radiative forcing, the classical cold-air drainage predicted by theory could not be detected. In contrast, we show that the airflow for the two dominant flow modes originates non-locally. The most abundant flow mode is characterized by vertically-decoupled layers featuring a near-surface flow perpendicular to the slope and strong stable stratification, which contradicts the expectation of a gravity-driven downslope flow of locally produced cold air. Differences in microtopography and land cover clearly affect spatio-temporal temperature perturbations. The second most abundant flow mode is characterized by strong mixing, leading to vertical coupling with airflow directed down the local slope. Here variations of microtopography and land cover lead to negligible near-surface temperature perturbations. We conclude that spatio-temporal temperature perturbations, but not flow dynamics, can be predicted by microtopography, which complicates the prediction of advective-heat components and the existence and dynamics of cold-air pools in gently sloped terrain in the absence of observations.

Spatiotemporal pattern formation in a prey-predator model under environmental driving forces

NASA Astrophysics Data System (ADS)

Sirohi, Anuj Kumar; Banerjee, Malay; Chakraborti, Anirban

2015-09-01

Many existing studies on pattern formation in the reaction-diffusion systems rely on deterministic models. However, environmental noise is often a major factor which leads to significant changes in the spatiotemporal dynamics. In this paper, we focus on the spatiotemporal patterns produced by the predator-prey model with ratio-dependent functional response and density dependent death rate of predator. We get the reaction-diffusion equations incorporating the self-diffusion terms, corresponding to random movement of the individuals within two dimensional habitats, into the growth equations for the prey and predator population. In order to have the noise added model, small amplitude heterogeneous perturbations to the linear intrinsic growth rates are introduced using uncorrelated Gaussian white noise terms. For the noise added system, we then observe spatial patterns for the parameter values lying outside the Turing instability region. With thorough numerical simulations we characterize the patterns corresponding to Turing and Turing-Hopf domain and study their dependence on different system parameters like noise-intensity, etc.

Spontaneous formation of spiral-like patterns with distinct periodic physical properties by confined electrodeposition of Co-In disks

NASA Astrophysics Data System (ADS)

Golvano-Escobal, Irati; Gonzalez-Rosillo, Juan Carlos; Domingo, Neus; Illa, Xavi; López-Barberá, José Francisco; Fornell, Jordina; Solsona, Pau; Aballe, Lucia; Foerster, Michael; Suriñach, Santiago; Baró, Maria Dolors; Puig, Teresa; Pané, Salvador; Nogués, Josep; Pellicer, Eva; Sort, Jordi

2016-07-01

Spatio-temporal patterns are ubiquitous in different areas of materials science and biological systems. However, typically the motifs in these types of systems present a random distribution with many possible different structures. Herein, we demonstrate that controlled spatio-temporal patterns, with reproducible spiral-like shapes, can be obtained by electrodeposition of Co-In alloys inside a confined circular geometry (i.e., in disks that are commensurate with the typical size of the spatio-temporal features). These patterns are mainly of compositional nature, i.e., with virtually no topographic features. Interestingly, the local changes in composition lead to a periodic modulation of the physical (electric, magnetic and mechanical) properties. Namely, the Co-rich areas show higher saturation magnetization and electrical conductivity and are mechanically harder than the In-rich ones. Thus, this work reveals that confined electrodeposition of this binary system constitutes an effective procedure to attain template-free magnetic, electric and mechanical surface patterning with specific and reproducible shapes.

Spatiotemporal Patterns of Schistosomiasis-Related Deaths, Brazil, 2000–2011

PubMed Central

Martins-Melo, Francisco Rogerlândio; Pinheiro, Marta Cristhiany Cunha; Ramos, Alberto Novaes; Alencar, Carlos Henrique; Bezerra, Fernando Schemelzer de Moraes

2015-01-01

We analyzed spatiotemporal patterns of 8,756 schistosomiasis-related deaths in Brazil during 2000–2011 and identified high-risk clusters of deaths, mainly in highly schistosomiasis-endemic areas along the coast of Brazil’s Northeast Region. Schistosomiasis remains a neglected public health problem with a high number of deaths in disease-endemic and emerging focal areas. PMID:26401716

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons.

PubMed

Oddo, Calogero M; Mazzoni, Alberto; Spanne, Anton; Enander, Jonas M D; Mogensen, Hannes; Bengtsson, Fredrik; Camboni, Domenico; Micera, Silvestro; Jörntell, Henrik

2017-04-04

Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models.

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons

PubMed Central

Oddo, Calogero M.; Mazzoni, Alberto; Spanne, Anton; Enander, Jonas M. D.; Mogensen, Hannes; Bengtsson, Fredrik; Camboni, Domenico; Micera, Silvestro; Jörntell, Henrik

2017-01-01

Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models. PMID:28374841

Understanding spatio-temporal variation of vegetation phenology and rainfall seasonality in the monsoon Southeast Asia.

PubMed

Suepa, Tanita; Qi, Jiaguo; Lawawirojwong, Siam; Messina, Joseph P

2016-05-01

The spatio-temporal characteristics of remote sensing are considered to be the primary advantage in environmental studies. With long-term and frequent satellite observations, it is possible to monitor changes in key biophysical attributes such as phenological characteristics, and relate them to climate change by examining their correlations. Although a number of remote sensing methods have been developed to quantify vegetation seasonal cycles using time-series of vegetation indices, there is limited effort to explore and monitor changes and trends of vegetation phenology in the Monsoon Southeast Asia, which is adversely affected by changes in the Asian monsoon climate. In this study, MODIS EVI and TRMM time series data, along with field survey data, were analyzed to quantify phenological patterns and trends in the Monsoon Southeast Asia during 2001-2010 period and assess their relationship with climate change in the region. The results revealed a great regional variability and inter-annual fluctuation in vegetation phenology. The phenological patterns varied spatially across the region and they were strongly correlated with climate variations and land use patterns. The overall phenological trends appeared to shift towards a later and slightly longer growing season up to 14 days from 2001 to 2010. Interestingly, the corresponding rainy season seemed to have started earlier and ended later, resulting in a slightly longer wet season extending up to 7 days, while the total amount of rainfall in the region decreased during the same time period. The phenological shifts and changes in vegetation growth appeared to be associated with climate events such as EL Niño in 2005. Furthermore, rainfall seemed to be the dominant force driving the phenological changes in naturally vegetated areas and rainfed croplands, whereas land use management was the key factor in irrigated agricultural areas. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

TRMM-TMI Satellite Observed Soil Moisture and Vegetation Density (1998-2005) Show Strong Connection with El Nino in Eastern Australia

NASA Technical Reports Server (NTRS)

Liu, Yi; van Dijk, Albert I.J.M.; Owe, Manfred

2007-01-01

Spatiotemporal patterns in soil moisture and vegetation water content across mainland Australia were investigated from 1998 through 2005, using TRMMITMI passive microwave observations. The Empirical Orthogonal Function technique was used to extract dominant spatial and temporal patterns in retrieved estimates of moisture content for the top 1-cm of soil (theta) and vegetation moisture content (via optical depth tau). The dominant temporal theta and tau patterns were strongly correlated to El Nino/Southern Oscillation (ENSO) in spring (3 = 0.90), and to a progressively lesser extent autumn, summer and winter. The Indian Ocean Dipole (IOD) index also explained part of the variation in spring 8 and z. Cluster analysis suggested that the regions most affected by ENS0 are mainly located in eastern Australia. The results suggest that the drought conditions experienced in eastern Australia since 2000 an clearly expressed in these satellite observations have a strong connection with ENSO patterns.

Combination of PCA and LORETA for sources analysis of ERP data: an emotional processing study

NASA Astrophysics Data System (ADS)

Hu, Jin; Tian, Jie; Yang, Lei; Pan, Xiaohong; Liu, Jiangang

2006-03-01

The purpose of this paper is to study spatiotemporal patterns of neuronal activity in emotional processing by analysis of ERP data. 108 pictures (categorized as positive, negative and neutral) were presented to 24 healthy, right-handed subjects while 128-channel EEG data were recorded. An analysis of two steps was applied to the ERP data. First, principal component analysis was performed to obtain significant ERP components. Then LORETA was applied to each component to localize their brain sources. The first six principal components were extracted, each of which showed different spatiotemporal patterns of neuronal activity. The results agree with other emotional study by fMRI or PET. The combination of PCA and LORETA can be used to analyze spatiotemporal patterns of ERP data in emotional processing.

Transition from propagating localized states to spatiotemporal chaos in phase dynamics

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

Brand, H.R.; Deissler, R.J.; Brand, H.R.

1998-10-01

We study the nonlinear phase equation for propagating patterns. We investigate the transition from a propagating localized pattern to a space-filling spatiotemporally disordered pattern and discuss in detail to what extent there are propagating localized states that breathe in time periodically, quasiperiodically, and chaotically. Differences and similarities to the phenomena occurring for the quintic complex Ginzburg-Landau equation are elucidated. We also discuss for which experimentally accessible systems one could observe the phenomena described. {copyright} {ital 1998} {ital The American Physical Society}

Spatio-Temporal Patterns in Colonies of Rod-Shaped Bacteria

NASA Astrophysics Data System (ADS)

Kitsunezaki, S.

In incubation experiments of bacterial colonies of Proteus Mirabilis, macroscopic spatio-temporal patterns, such as turbulent and unidirectional spiral patterns, appear in colonies. Considering only kinetic propeties of rod-shaped bacteria, we propose a phenomenological model for the directional and positional distributions. As the average density increases, homogeneous states bifurcate sub-critically into nonuniform states exhibiting localized collective motion, and spiral patterns appear for sufficiently large density. These patterns result from interactions between the local bacteria densities and the order parameter representing collective motion. Our model can be described by reduced equations using a perturbative method for large density. The unidirectionality of sprial rotation is also discussed.

Spatiotemporal variability of hydrologic soil properties and the implications for overland flow and land management in a peri-urban Mediterranean catchment

NASA Astrophysics Data System (ADS)

Ferreira, C. S. S.; Walsh, R. P. D.; Steenhuis, T. S.; Shakesby, R. A.; Nunes, J. P. N.; Coelho, C. O. A.; Ferreira, A. J. D.

2015-06-01

Planning of semi-urban developments is often hindered by a lack of knowledge on how changes in land-use affect catchment hydrological response. The temporal and spatial patterns of overland flow source areas and their connectivity in the landscape, particularly in a seasonal climate, remain comparatively poorly understood. This study investigates seasonal variations in factors influencing runoff response to rainfall in a peri-urban catchment in Portugal characterized by a mosaic of landscape units and a humid Mediterranean climate. Variations in surface soil moisture, hydrophobicity and infiltration capacity were measured in six different landscape units (defined by land-use on either sandstone or limestone) in nine monitoring campaigns at key times over a one-year period. Spatiotemporal patterns in overland flow mechanisms were found. Infiltration-excess overland flow was generated in rainfalls during the dry summer season in woodland on both sandstone and limestone and on agricultural soils on limestone due probably in large part to soil hydrophobicity. In wet periods, saturation overland flow occurred on urban and agricultural soils located in valley bottoms and on shallow soils upslope. Topography, water table rise and soil depth determined the location and extent of saturated areas. Overland flow generated in upslope source areas potentially can infiltrate in other landscape units downslope where infiltration capacity exceeds rainfall intensity. Hydrophilic urban and agricultural-sandstone soils were characterized by increased infiltration capacity during dry periods, while forest soils provided potential sinks for overland flow when hydrophilic in the winter wet season. Identifying the spatial and temporal variability of overland flow sources and sinks is an important step in understanding and modeling flow connectivity and catchment hydrologic response. Such information is important for land managers in order to improve urban planning to minimize flood risk.

Spatiotemporal Variation and the Role of Wildlife in Seasonal Water Quality Declines in the Chobe River, Botswana

PubMed Central

Fox, J. Tyler; Alexander, Kathleen A.

2015-01-01

Sustainable management of dryland river systems is often complicated by extreme variability of precipitation in time and space, especially across large catchment areas. Understanding regional water quality changes in southern African dryland rivers and wetland systems is especially important because of their high subsistence value and provision of ecosystem services essential to both public and animal health. We quantified seasonal variation of Escherichia coli (E. coli) and Total Suspended Solids (TSS) in the Chobe River using spatiotemporal and geostatistical modeling of water quality time series data collected along a transect spanning a mosaic of protected, urban, and developing urban land use. We found significant relationships in the dry season between E. coli concentrations and protected land use (p = 0.0009), floodplain habitat (p = 0.016), and fecal counts from elephant (p = 0.017) and other wildlife (p = 0.001). Dry season fecal loading by both elephant (p = 0.029) and other wildlife (p = 0.006) was also an important predictor of early wet season E. coli concentrations. Locations of high E. coli concentrations likewise showed close spatial agreement with estimates of wildlife biomass derived from aerial survey data. In contrast to the dry season, wet season bacterial water quality patterns were associated only with TSS (p<0.0001), suggesting storm water and sediment runoff significantly influence E. coli loads. Our data suggest that wildlife populations, and elephants in particular, can significantly modify river water quality patterns. Loss of habitat and limitation of wildlife access to perennial rivers and floodplains in water-restricted regions may increase the impact of species on surface water resources. Our findings have important implications to land use planning in southern Africa’s dryland river ecosystems. PMID:26460613

Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts

USGS Publications Warehouse

Conn, Paul B.; Johnson, Devin S.; Ver Hoef, Jay M.; Hooten, Mevin B.; London, Joshua M.; Boveng, Peter L.

2015-01-01

Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal (Phoca largha) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total abundance produced estimates that largely conformed to our a priori expectation. Although care must be taken to tailor models to match the study population and survey data available, we argue that hierarchical spatiotemporal statistical models represent a powerful way forward for estimating abundance and explaining variation in the distribution of dynamical populations.

Emergence and transitions of dynamic patterns of thickness oscillation of the plasmodium of the true slime mold Physarum polycephalum

NASA Astrophysics Data System (ADS)

Takagi, Seiji; Ueda, Tetsuo

2008-03-01

The emergence and transitions of various spatiotemporal patterns of thickness oscillation were studied in the freshly isolated protoplasm of the Physarum plasmodium. New patterns, such as standing waves, and chaotic and rotating spirals, developed successively before the well-documented synchronous pattern appeared. There was also a spontaneous opposite transition from synchrony to chaotic and rotating spirals. Rotating spiral waves were observed in the large migrating plasmodium, where the vein structures were being destroyed. Thus, the Physarum plasmodium exhibits versatile patterns, which are generally expected in coupled oscillator systems. This paper discusses the physiological roles of spatiotemporal patterns, comparing them with other biological systems.

Spatio-temporal scaling effects on longshore sediment transport pattern along the nearshore zone

NASA Astrophysics Data System (ADS)

Khorram, Saeed; Ergil, Mustafa

2018-03-01

A measure of uncertainties, entropy has been employed in such different applications as coastal engineering probability inferences. Entropy sediment transport integration theories present novel visions in coastal analyses/modeling the application and development of which are still far-reaching. Effort has been made in the present paper to propose a method that needs an entropy-power index for spatio-temporal patterns analyses. Results have shown that the index is suitable for marine/hydrological ecosystem components analyses based on a beach area case study. The method makes use of six Makran Coastal monthly data (1970-2015) and studies variables such as spatio-temporal patterns, LSTR (long-shore sediment transport rate), wind speed, and wave height all of which are time-dependent and play considerable roles in terrestrial coastal investigations; the mentioned variables show meaningful spatio-temporal variability most of the time, but explanation of their combined performance is not easy. Accordingly, the use of an entropy-power index can show considerable signals that facilitate the evaluation of water resources and will provide an insight regarding hydrological parameters' interactions at scales as large as beach areas. Results have revealed that an STDDPI (entropy based spatio-temporal disorder dynamics power index) can simulate wave, long-shore sediment transport rate, and wind when granulometry, concentration, and flow conditions vary.

Mining User spatiotemporal Behavior in Geospatial Cyberinfrastructure --using GEOSS Clearinghouse as an example

NASA Astrophysics Data System (ADS)

XIA, J.; Yang, C.; Liu, K.; Huang, Q.; Li, Z.

2013-12-01

Big Data becomes increasingly important in almost all scientific domains, especially in geoscience where hundreds to millions of sensors are collecting data of the Earth continuously (Whitehouse News 2012). With the explosive growth of data, various Geospatial Cyberinfrastructure (GCI) (Yang et al. 2010) components are developed to manage geospatial resources and provide data access for the public. These GCIs are accessed by different users intensively on a daily basis. However, little research has been done to analyze the spatiotemporal patterns of user behavior, which could be critical to the management of Big Data and the operation of GCIs (Yang et al. 2011). For example, the spatiotemporal distribution of end users helps us better arrange and locate GCI computing facilities. A better indexing and caching mechanism could be developed based on the spatiotemporal pattern of user queries. In this paper, we use GEOSS Clearinghouse as an example to investigate spatiotemporal patterns of user behavior in GCIs. The investigation results show that user behaviors are heterogeneous but with patterns across space and time. Identified patterns include (1) the high access frequency regions; (2) local interests; (3) periodical accesses and rush hours; (4) spiking access. Based on identified patterns, this presentation reports several solutions to better support the operation of the GEOSS Clearinghouse and other GCIs. Keywords: Big Data, EarthCube, CyberGIS, Spatiotemporal Thinking and Computing, Data Mining, User Behavior Reference: Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P., & Uthurusamy, R. 1996. Advances in knowledge discovery and data mining. Whitehouse. 2012. Obama administration unveils 'BIG DATA' initiative: announces $200 million in new R&D investments. Whitehouse. Retrieved from http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_press_release_final_2.pdf [Accessed 14 June 2013] Yang, C., Wu, H., Huang, Q., Li, Z., & Li, J. 2011. Using spatial principles to optimize distributed computing for enabling the physical science discoveries. Proceedings of the National Academy of Sciences, 108(14), 5498-5503. doi:10.1073/pnas.0909315108 Yang, C., Raskin, R., Goodchild, M., & Gahegan, M. 2010. Geospatial Cyberinfrastructure: Past, present and future. Computers, Environment and Urban Systems, 34(4), 264-277. doi:10.1016/j.compenvurbsys.2010.04.001

Mathematical Modeling the Geometric Regularity in Proteus Mirabilis Colonies

NASA Astrophysics Data System (ADS)

Zhang, Bin; Jiang, Yi; Minsu Kim Collaboration

Proteus Mirabilis colony exhibits striking spatiotemporal regularity, with concentric ring patterns with alternative high and low bacteria density in space, and periodicity for repetition process of growth and swarm in time. We present a simple mathematical model to explain the spatiotemporal regularity of P. Mirabilis colonies. We study a one-dimensional system. Using a reaction-diffusion model with thresholds in cell density and nutrient concentration, we recreated periodic growth and spread patterns, suggesting that the nutrient constraint and cell density regulation might be sufficient to explain the spatiotemporal periodicity in P. Mirabilis colonies. We further verify this result using a cell based model.

Spatio-temporal mapping of variation potentials in leaves of Helianthus annuus L. seedlings in situ using multi-electrode array

PubMed Central

Zhao, Dong-Jie; Wang, Zhong-Yi; Huang, Lan; Jia, Yong-Peng; Leng, John Q.

2014-01-01

Damaging thermal stimuli trigger long-lasting variation potentials (VPs) in higher plants. Owing to limitations in conventional plant electrophysiological recording techniques, recorded signals are composed of signals originating from all of the cells that are connected to an electrode. This limitation does not enable detailed spatio-temporal distributions of transmission and electrical activities in plants to be visualised. Multi-electrode array (MEA) enables the recording and imaging of dynamic spatio-temporal electrical activities in higher plants. Here, we used an 8 × 8 MEA with a polar distance of 450 μm to measure electrical activities from numerous cells simultaneously. The mapping of the data that were recorded from the MEA revealed the transfer mode of the thermally induced VPs in the leaves of Helianthus annuus L. seedlings in situ. These results suggest that MEA can enable recordings with high spatio-temporal resolution that facilitate the determination of the bioelectrical response mode of higher plants under stress. PMID:24961469

Spatio-temporal mapping of variation potentials in leaves of Helianthus annuus L. seedlings in situ using multi-electrode array.

PubMed

Zhao, Dong-Jie; Wang, Zhong-Yi; Huang, Lan; Jia, Yong-Peng; Leng, John Q

2014-06-25

Damaging thermal stimuli trigger long-lasting variation potentials (VPs) in higher plants. Owing to limitations in conventional plant electrophysiological recording techniques, recorded signals are composed of signals originating from all of the cells that are connected to an electrode. This limitation does not enable detailed spatio-temporal distributions of transmission and electrical activities in plants to be visualised. Multi-electrode array (MEA) enables the recording and imaging of dynamic spatio-temporal electrical activities in higher plants. Here, we used an 8 × 8 MEA with a polar distance of 450 μm to measure electrical activities from numerous cells simultaneously. The mapping of the data that were recorded from the MEA revealed the transfer mode of the thermally induced VPs in the leaves of Helianthus annuus L. seedlings in situ. These results suggest that MEA can enable recordings with high spatio-temporal resolution that facilitate the determination of the bioelectrical response mode of higher plants under stress.

Gait characteristics and spatio-temporal variables of climbing in bonobos (Pan paniscus).

PubMed

Schoonaert, Kirsten; D'Août, Kristiaan; Samuel, Diana; Talloen, Willem; Nauwelaerts, Sandra; Kivell, Tracy L; Aerts, Peter

2016-11-01

Although much is known about the terrestrial locomotion of great apes, their arboreal locomotion has been studied less extensively. This study investigates arboreal locomotion in bonobos (Pan paniscus), focusing on the gait characteristics and spatio-temporal variables associated with locomotion on a pole. These features are compared across different substrate inclinations (0°, 30°, 45°, 60°, and 90°), and horizontal quadrupedal walking is compared between an arboreal and a terrestrial substrate. Our results show greater variation in footfall patterns with increasing incline, resulting in more lateral gait sequences. During climbing on arboreal inclines, smaller steps and strides but higher stride frequencies and duty factors are found compared to horizontal arboreal walking. This may facilitate better balance control and dynamic stability on the arboreal substrate. We found no gradual change in spatio-temporal variables with increasing incline; instead, the results for all inclines were clustered together. Bonobos take larger strides at lower stride frequencies and lower duty factors on a horizontal arboreal substrate than on a flat terrestrial substrate. We suggest that these changes are the result of the better grip of the grasping feet on an arboreal substrate. Speed modulation of the spatio-temporal variables is similar across substrate inclinations and between substrate types, suggesting a comparable underlying motor control. Finally, we contrast these variables of arboreal inclined climbing with those of terrestrial bipedal locomotion, and briefly discuss the results with respect to the origin of habitual bipedalism. Am. J. Primatol. 78:1165-1177, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Unravelling spatio-temporal evapotranspiration patterns in topographically complex landscapes

NASA Astrophysics Data System (ADS)

Metzen, Daniel; Sheridan, Gary; Nyman, Petter; Lane, Patrick

2016-04-01

Vegetation co-evolves with soils and topography under a given long-term climatic forcing. Previous studies demonstrated a strong eco-hydrologic feedback between topography, vegetation and energy and water fluxes. Slope orientation (aspect and gradient) alter the magnitude of incoming solar radiation resulting in larger evaporative losses and less water availability on equator-facing slopes. Furthermore, non-local water inputs from upslope areas potentially contribute to available water at downslope positions. The combined effect of slope orientation and drainage position creates complex spatial patterns in biological productivity and pedogenesis, which in turn alter the local hydrology. In complex upland landscapes, topographic alteration of incoming radiation can cause substantial aridity index (ratio of potential evapotranspiration to precipitation) variations over small spatial extents. Most of the upland forests in south-east Australia are located in an aridity index (AI) range of 1-2, around the energy limited to water limited boundary, where forested systems are expected to be most sensitive to AI changes. In this research we aim to improve the fundamental understanding of spatio-temporal evolution of evapotranspiration (ET) patterns in complex terrain, accounting for local topographic effects on system properties (e.g. soil depth, sapwood area, leaf area) and variation in energy and water exchange processes due to slope orientation and drainage position. Six measurement plots were set-up in a mixed species eucalypt forest on a polar and equatorial-facing hillslope (AI ˜1.3 vs. 1.8) at varying drainage position (ridge, mid-slope, gully), while minimizing variations in other factors, e.g. geology and weather patterns. Sap flow, soil water content, incoming solar radiation and throughfall were continuously monitored at field sites spanning a wide range of soil depth (0.5 - >3m), maximum tree heights (17 - 51m) and LAI (1.2 - 4.6). Site-specific response curves of vapour pressure deficit and sap velocity emerged in relation to landscape position from spring until autumn, while the relationship collapsed into a single curve in winter. These patterns were amplified by more sapwood area per ha in wetter locations compared to drier locations. Topographically downscaled (20x20m pixels) monthly AI values were significantly correlated with monthly observations of sap velocity (R2 of 0.54 - 0.91) for all landscape positions except the equator-facing ridge position. Moreover, spatial vegetation and sap velocity patterns could be predicted using AI, topographic wetness index and elevation above stream (R2 of 0.67 and 0.59, respectively). Our findings emphasise the co-dependence of climate, topography and vegetation, and the need of a more holistic approach that includes terrain and vegetation characteristics to explain ET patterns. Our strong correlations with vegetation patterns and sap velocities demonstrate the potential use of spatially mappable climatic and topographic information to scale ET fluxes in complex terrain, and we anticipate that this approach is applicable across a wide range of ecosystems.

How can knowledge discovery methods uncover spatio-temporal patterns in environmental data?

NASA Astrophysics Data System (ADS)

Wachowicz, Monica

2000-04-01

This paper proposes the integration of KDD, GVis and STDB as a long-term strategy, which will allow users to apply knowledge discovery methods for uncovering spatio-temporal patterns in environmental data. The main goal is to combine innovative techniques and associated tools for exploring very large environmental data sets in order to arrive at valid, novel, potentially useful, and ultimately understandable spatio-temporal patterns. The GeoInsight approach is described using the principles and key developments in the research domains of KDD, GVis, and STDB. The GeoInsight approach aims at the integration of these research domains in order to provide tools for performing information retrieval, exploration, analysis, and visualization. The result is a knowledge-based design, which involves visual thinking (perceptual-cognitive process) and automated information processing (computer-analytical process).

A Biologically Constrained, Mathematical Model of Cortical Wave Propagation Preceding Seizure Termination

PubMed Central

González-Ramírez, Laura R.; Ahmed, Omar J.; Cash, Sydney S.; Wayne, C. Eugene; Kramer, Mark A.

2015-01-01

Epilepsy—the condition of recurrent, unprovoked seizures—manifests in brain voltage activity with characteristic spatiotemporal patterns. These patterns include stereotyped semi-rhythmic activity produced by aggregate neuronal populations, and organized spatiotemporal phenomena, including waves. To assess these spatiotemporal patterns, we develop a mathematical model consistent with the observed neuronal population activity and determine analytically the parameter configurations that support traveling wave solutions. We then utilize high-density local field potential data recorded in vivo from human cortex preceding seizure termination from three patients to constrain the model parameters, and propose basic mechanisms that contribute to the observed traveling waves. We conclude that a relatively simple and abstract mathematical model consisting of localized interactions between excitatory cells with slow adaptation captures the quantitative features of wave propagation observed in the human local field potential preceding seizure termination. PMID:25689136

Distinct patterns of seasonal Greenland glacier velocity

PubMed Central

Moon, Twila; Joughin, Ian; Smith, Ben; van den Broeke, Michiel R; van de Berg, Willem Jan; Noël, Brice; Usher, Mika

2014-01-01

Predicting Greenland Ice Sheet mass loss due to ice dynamics requires a complete understanding of spatiotemporal velocity fluctuations and related control mechanisms. We present a 5 year record of seasonal velocity measurements for 55 marine-terminating glaciers distributed around the ice sheet margin, along with ice-front position and runoff data sets for each glacier. Among glaciers with substantial speed variations, we find three distinct seasonal velocity patterns. One pattern indicates relatively high glacier sensitivity to ice-front position. The other two patterns are more prevalent and appear to be meltwater controlled. These patterns reveal differences in which some subglacial systems likely transition seasonally from inefficient, distributed hydrologic networks to efficient, channelized drainage, while others do not. The difference may be determined by meltwater availability, which in some regions may be influenced by perennial firn aquifers. Our results highlight the need to understand subglacial meltwater availability on an ice sheet-wide scale to predict future dynamic changes. Key Points First multi-region seasonal velocity measurements show regional differences Seasonal velocity fluctuations on most glaciers appear meltwater controlled Seasonal development of efficient subglacial drainage geographically divided PMID:25821275

Application of hierarchical clustering method to classify of space-time rainfall patterns

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Chang, Tu-Je

2010-05-01

Understanding the local precipitation patterns is essential to the water resources management and flooding mitigation. The precipitation patterns can vary in space and time depending upon the factors from different spatial scales such as local topological changes and macroscopic atmospheric circulation. The spatiotemporal variation of precipitation in Taiwan is significant due to its complex terrain and its location at west pacific and subtropical area, where is the boundary between the pacific ocean and Asia continent with the complex interactions among the climatic processes. This study characterizes local-scale precipitation patterns by classifying the historical space-time precipitation records. We applied the hierarchical ascending clustering method to analyze the precipitation records from 1960 to 2008 at the six rainfall stations located in Lan-yang catchment at the northeast of the island. Our results identify the four primary space-time precipitation types which may result from distinct driving forces from the changes of atmospheric variables and topology at different space-time scales. This study also presents an important application of the statistical downscaling to combine large-scale upper-air circulation with local space-time precipitation patterns.

Spatio-temporal variation in Helicoverpa egg parasitism by Trichogramma in a tropical Bt-transgenic cotton landscape

USDA-ARS?s Scientific Manuscript database

Understanding the spatio-temporal dynamics of insects in agroecosystems is crucial when developing effective management strategies that emphasise biological control of pests. Wild populations of Trichogramma Westwood egg parasitoids are utilised for biological suppression of the potentially resistan...

Home ranges of lions in the Kalahari, Botswana exhibit vast sizes and high temporal variability.

PubMed

Zehnder, André; Henley, Stephen; Weibel, Robert

2018-06-01

The central Kalahari region in Botswana is one of the few remaining ecosystems with a stable lion population. Yet, relatively little is known about the ecology of the lions there. As an entry point, home range estimations provide information about the space utilization of the studied animals. The home ranges of eight lions in this region were determined to investigate their spatial overlaps and spatiotemporal variations. We found that, except for MCP, all home range estimators yielded comparable results regarding size and shape. The home ranges of all individuals were located predominantly inside the protected reserves. Their areas were among the largest known for lions with 1131 - 4314km 2 (95%), with no significant differences between males and females. Numerous overlaps between lions of different sexes were detected, although these originate from different groups. A distance chart confirmed that most of these lions directly encountered each other once or several times. Strong temporal variations of the home ranges were observed that did not match a seasonal pattern. The exceptionally large home ranges are likely to be caused by the sparse and dynamic prey populations. Since the ungulates in the study area move in an opportunistic way, too, strong spatiotemporal home range variations emerge. This can lead to misleading home ranges. We therefore recommend clarifying the stability of the home ranges by applying several levels of temporal aggregation. The lack of strict territoriality is likely an adaptation to the variable prey base and the high energetic costs associated with defending a large area. Copyright © 2018 Elsevier GmbH. All rights reserved.

Analysis of the Spatiotemporal Characteristics of Hemorrhagic Fever with Renal Syndrome in Hubei Province, China

NASA Astrophysics Data System (ADS)

Fan, H.; Ge, L.; Song, L.; Zhao, Q.

2015-07-01

Hemorrhagic fever with renal syndrome(HFRS) is a worldwide fulminant infectious disease. Since the first HFRS cases in Hubei Province were reported in 1957, the disease has spread across the province and Hubei has become one of seriously affected areas in China. However, the epidemic characteristics of HFRS are still not entirely clear. Therefore, a systematic investigation of spatial and temporal distribution pattern of HFRS system is needed. In order to facilitate better prevention and control of HFRS in Hubei Province, in this paper, a GIS spatiotemporal analysis and modeling tool was developed to analyze the spatiotemporal dynamics of the HFRS epidemic, as well as providinga comprehensive examination the dynamic pattern of HFRS in Hubei over the past 30 years (1980-2009), to determine spatiotemporal change trends and the causes of HFRS. This paper describes the experiments and their results.

Spatiotemporal throughfall patterns beneath an urban tree row

NASA Astrophysics Data System (ADS)

Bogeholz, P.; Van Stan, J. T., II; Hildebrandt, A.; Friesen, J.; Dibble, M.; Norman, Z.

2016-12-01

Much recent research has focused on throughfall patterns in natural forests as they can influence the heterogeneity of surface ecohydrological and biogeochemical processes. However, to the knowledge of the authors, no work has assessed how urban forest structures affect the spatiotemporal variability of throughfall water flux. Urbanization greatly alters not only a significant portion of the land surface, but canopy structure, with the most typical urban forest configuration being landscaped tree rows along streets, swales, parking lot medians, etc. This study examines throughfall spatiotemporal patterns for a landscaped tree row of Pinus elliottii (Engelm., slash pine) on Georgia Southern University's campus (southeastern, USA) using 150 individual observations per storm. Throughfall correlation lengths beneath this tree row were similar to, but appeared to be more stable across storm size than, observations in past studies on natural forests. Individual tree overlap and the planting interval also may more strongly drive throughfall patterns in tree rows. Meteorological influences beyond storm magnitude (intensity, intermittency, wind conditions, and atmospheric moisture demand) are also examined.

A Modified Consumer Inkjet for Spatiotemporal Control of Gene Expression

PubMed Central

Cohen, Daniel J.; Morfino, Roberto C.; Maharbiz, Michel M.

2009-01-01

This paper presents a low-cost inkjet dosing system capable of continuous, two-dimensional spatiotemporal regulation of gene expression via delivery of diffusible regulators to a custom-mounted gel culture of E. coli. A consumer-grade, inkjet printer was adapted for chemical printing; E. coli cultures were grown on 750 µm thick agar embedded in micro-wells machined into commercial compact discs. Spatio-temporal regulation of the lac operon was demonstrated via the printing of patterns of lactose and glucose directly into the cultures; X-Gal blue patterns were used for visual feedback. We demonstrate how the bistable nature of the lac operon's feedback, when perturbed by patterning lactose (inducer) and glucose (inhibitor), can lead to coordination of cell expression patterns across a field in ways that mimic motifs seen in developmental biology. Examples of this include sharp boundaries and the generation of traveling waves of mRNA expression. To our knowledge, this is the first demonstration of reaction-diffusion effects in the well-studied lac operon. A finite element reaction-diffusion model of the lac operon is also presented which predicts pattern formation with good fidelity. PMID:19763256

Second-order processing of four-stroke apparent motion.

PubMed

Mather, G; Murdoch, L

1999-05-01

In four-stroke apparent motion displays, pattern elements oscillate between two adjacent positions and synchronously reverse in contrast, but appear to move unidirectionally. For example, if rightward shifts preserve contrast but leftward shifts reverse contrast, consistent rightward motion is seen. In conventional first-order displays, elements reverse in luminance contrast (e.g. light elements become dark, and vice-versa). The resulting perception can be explained by responses in elementary motion detectors turned to spatio-temporal orientation. Second-order motion displays contain texture-defined elements, and there is some evidence that they excite second-order motion detectors that extract spatio-temporal orientation following the application of a non-linear 'texture-grabbing' transform by the visual system. We generated a variety of second-order four-stroke displays, containing texture-contrast reversals instead of luminance contrast reversals, and used their effectiveness as a diagnostic test for the presence of various forms of non-linear transform in the second-order motion system. Displays containing only forward or only reversed phi motion sequences were also tested. Displays defined by variation in luminance, contrast, orientation, and size were effective. Displays defined by variation in motion, dynamism, and stereo were partially or wholly ineffective. Results obtained with contrast-reversing and four-stroke displays indicate that only relatively simple non-linear transforms (involving spatial filtering and rectification) are available during second-order energy-based motion analysis.

[Spatiotemporal variation characteristics and related affecting factors of actual evapotranspiration in the Hun-Taizi River Basin, Northeast China].

PubMed

Feng, Xue; Cai, Yan-Cong; Guan, De-Xin; Jin, Chang-Jie; Wang, An-Zhi; Wu, Jia-Bing; Yuan, Feng-Hui

2014-10-01

Based on the meteorological and hydrological data from 1970 to 2006, the advection-aridity (AA) model with calibrated parameters was used to calculate evapotranspiration in the Hun-Taizi River Basin in Northeast China. The original parameter of the AA model was tuned according to the water balance method and then four subbasins were selected to validate. Spatiotemporal variation characteristics of evapotranspiration and related affecting factors were analyzed using the methods of linear trend analysis, moving average, kriging interpolation and sensitivity analysis. The results showed that the empirical parameter value of 0.75 of AA model was suitable for the Hun-Taizi River Basin with an error of 11.4%. In the Hun-Taizi River Basin, the average annual actual evapotranspiration was 347.4 mm, which had a slightly upward trend with a rate of 1.58 mm · (10 a(-1)), but did not change significantly. It also indicated that the annual actual evapotranspiration presented a single-peaked pattern and its peak value occurred in July; the evapotranspiration in summer was higher than in spring and autumn, and it was the smallest in winter. The annual average evapotranspiration showed a decreasing trend from the northwest to the southeast in the Hun-Taizi River Basin from 1970 to 2006 with minor differences. Net radiation was largely responsible for the change of actual evapotranspiration in the Hun-Taizi River Basin.

Satellite observed global variations in ecosystem-scale plant water storage

NASA Astrophysics Data System (ADS)

Tian, F.; Wigneron, J. P.; Brandt, M.; Fensholt, R.

2017-12-01

Plant water storage is a key component in ecohydrological processes and tightly coupled with global carbon and energy budgets. Field measurements of individual trees have revealed diurnal and seasonal variations in plant water storage across different tree species and sizes. However, global estimation of plant water storage is challenged by up-scaling from individual trees to an ecosystem scale. The L-band passive microwaves are sensitive to water stored in the stems, branches and leaves, with dependence on the vegetation structure. Thus, the L-band vegetation optical depth (L-VOD) parameter retrieved from satellite passive microwave observations can be used as a proxy for ecosystem-scale plant water storage. Here, we employ the recently developed SMOS (Soil Moisture and Ocean Salinity) L-VOD dataset to investigate spatial patterns in global plant water storage and its diurnal and seasonal variations. In addition, we compare the spatiotemporal patterns between plant water storage and canopy greenness (i.e., enhanced vegetation indices, EVI) to gain ecohydrological insights among different territorial biomes, including boreal forest and tropical woodland. Generally, seasonal dynamics of plant water storage is much smaller than canopy greenness, yet the temporal coupling of these two traits is totally different between boreal and tropical regions, which could be related to their strategies in plant water regulation.

Modeling spatial variation in avian survival and residency probabilities

USGS Publications Warehouse

Saracco, James F.; Royle, J. Andrew; DeSante, David F.; Gardner, Beth

2010-01-01

The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.

Cross-Diffusion Induced Turing Instability and Amplitude Equation for a Toxic-Phytoplankton-Zooplankton Model with Nonmonotonic Functional Response

NASA Astrophysics Data System (ADS)

Han, Renji; Dai, Binxiang

2017-06-01

The spatiotemporal pattern induced by cross-diffusion of a toxic-phytoplankton-zooplankton model with nonmonotonic functional response is investigated in this paper. The linear stability analysis shows that cross-diffusion is the key mechanism for the formation of spatial patterns. By taking cross-diffusion rate as bifurcation parameter, we derive amplitude equations near the Turing bifurcation point for the excited modes in the framework of a weakly nonlinear theory, and the stability analysis of the amplitude equations interprets the structural transitions and stability of various forms of Turing patterns. Furthermore, we illustrate the theoretical results via numerical simulations. It is shown that the spatiotemporal distribution of the plankton is homogeneous in the absence of cross-diffusion. However, when the cross-diffusivity is greater than the critical value, the spatiotemporal distribution of all the plankton species becomes inhomogeneous in spaces and results in different kinds of patterns: spot, stripe, and the mixture of spot and stripe patterns depending on the cross-diffusivity. Simultaneously, the impact of toxin-producing rate of toxic-phytoplankton (TPP) species and natural death rate of zooplankton species on pattern selection is also explored.

Why Does Rhinopithecus bieti Prefer the Highest Elevation Range in Winter? A Test of the Sunshine Hypothesis

PubMed Central

Behm, Jocelyn E.; Wang, Lin; Huang, Yong; Long, Yongcheng; Zhu, Jianguo

2011-01-01

Environmental factors that affect spatiotemporal distribution patterns of animals usually include resource availability, temperature, and the risk of predation. However, they do not explain the counterintuitive preference of high elevation range in winter by the black-and-white snub-nosed monkey (Rhinopithecus bieti). We asked whether variation of sunshine along with elevations is the key driving force. To test this hypothesis, we conducted field surveys to demonstrate that there was a statistically significant pattern of high elevation use during winter. We then asked whether this pattern can be explained by certain environmental factors, namely temperature, sunshine duration and solar radiation. Finally, we concluded with a possible ecological mechanism for this pattern. In this study, we employed GIS technology to quantify solar radiation and sunshine duration across the monkey's range. Our results showed that: 1) R. bieti used the high altitude range between 4100–4400 m in winter although the yearly home range spanned from 3500–4500 m; 2) both solar radiation and sunshine duration increased with elevation while temperature decreased with elevation; 3) within the winter range, the use of range was significantly correlated with solar radiation and sunshine duration; 4) monkeys moved to the areas with high solar radiation and duration following a snowfall, where the snow melts faster and food is exposed earlier. We concluded that sunshine was the main factor that influences selection of high elevation habitat for R. bieti in winter. Since some other endotherms in the area exhibit similar winter distributional patterns, we developed a sunshine hypothesis to explain this phenomenon. In addition, our work also represented a new method of integrating GIS models into traditional field ecology research to study spatiotemporal distribution pattern of wildlife. We suggest that further theoretical and empirical studies are necessary for better understanding of sunshine influence on wildlife range use. PMID:21915329

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

Similarities and differences among half-marathon runners according to their performance level

PubMed Central

Morante, Juan Carlos; Gómez-Molina, Josué; García-López, Juan

2018-01-01

This study aimed to identify the similarities and differences among half-marathon runners in relation to their performance level. Forty-eight male runners were classified into 4 groups according to their performance level in a half-marathon (min): Group 1 (n = 11, < 70 min), Group 2 (n = 13, < 80 min), Group 3 (n = 13, < 90 min), Group 4 (n = 11, < 105 min). In two separate sessions, training-related, anthropometric, physiological, foot strike pattern and spatio-temporal variables were recorded. Significant differences (p<0.05) between groups (ES = 0.55–3.16) and correlations with performance were obtained (r = 0.34–0.92) in training-related (experience and running distance per week), anthropometric (mass, body mass index and sum of 6 skinfolds), physiological (VO2max, RCT and running economy), foot strike pattern and spatio-temporal variables (contact time, step rate and length). At standardized submaximal speeds (11, 13 and 15 km·h-1), no significant differences between groups were observed in step rate and length, neither in contact time when foot strike pattern was taken into account. In conclusion, apart from training-related, anthropometric and physiological variables, foot strike pattern and step length were the only biomechanical variables sensitive to half-marathon performance, which are essential to achieve high running speeds. However, when foot strike pattern and running speeds were controlled (submaximal test), the spatio-temporal variables were similar. This indicates that foot strike pattern and running speed are responsible for spatio-temporal differences among runners of different performance level. PMID:29364940

Macro-Scale Patterns in Upwelling/Downwelling Activity at North American West Coast

PubMed Central

Saldívar-Lucio, Romeo; Di Lorenzo, Emanuele; Nakamura, Miguel; Villalobos, Héctor; Lluch-Cota, Daniel; Del Monte-Luna, Pablo

2016-01-01

The seasonal and interannual variability of vertical transport (upwelling/downwelling) has been relatively well studied, mainly for the California Current System, including low-frequency changes and latitudinal heterogeneity. The aim of this work was to identify potentially predictable patterns in upwelling/downwelling activity along the North American west coast and discuss their plausible mechanisms. To this purpose we applied the min/max Autocorrelation Factor technique and time series analysis. We found that spatial co-variation of seawater vertical movements present three dominant low-frequency signals in the range of 33, 19 and 11 years, resembling periodicities of: atmospheric circulation, nodal moon tides and solar activity. Those periodicities might be related to the variability of vertical transport through their influence on dominant wind patterns, the position/intensity of pressure centers and the strength of atmospheric circulation cells (wind stress). The low-frequency signals identified in upwelling/downwelling are coherent with temporal patterns previously reported at the study region: sea surface temperature along the Pacific coast of North America, catch fluctuations of anchovy Engraulis mordax and sardine Sardinops sagax, the Pacific Decadal Oscillation, changes in abundance and distribution of salmon populations, and variations in the position and intensity of the Aleutian low. Since the vertical transport is an oceanographic process with strong biological relevance, the recognition of their spatio-temporal patterns might allow for some reasonable forecasting capacity, potentially useful for marine resources management of the region. PMID:27893826

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

Spatiotemporal Patterns of Ice Mass Variations and the Local Climatic Factors in the Riparian Zone of Central Valley, California

NASA Astrophysics Data System (ADS)

Inamdar, P.; Ambinakudige, S.

2016-12-01

Californian icefields are natural basins of fresh water. They provide irrigation water to the farms in the central valley. We analyzed the ice mass loss rates, air temperature and land surface temperature (LST) in Sacramento and San Joaquin basins in California. The digital elevation models from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to calculate ice mass loss rate between the years 2002 and 2015. Additionally, Landsat TIR data were used to extract the land surface temperature. Data from local weather stations were analyzed to understand the spatiotemporal trends in air temperature. The results showed an overall mass recession of -0.8 ± 0.7 m w.e.a-1. We also noticed an about 60% loss in areal extent of the glaciers in the study basins between 2000 and 2015. Local climatic factors, along with the global climate patterns might have influenced the negative trends in the ice mass loss. Overall, there was an increase in the air temperature by 0.07± 0.02 °C in the central valley between 2000 and 2015. Furthermore, LST increased by 0.34 ± 0.4 °C and 0.55± 0.1 °C in the Sacramento and San Joaquin basins. Our preliminary results show the decrease in area and mass of ice mass in the basins, and changing agricultural practices in the valley.

The Formation and Spatiotemporal Progress of the pH Wave Induced by the Temperature Gradient in the Thin-Layer H2O2-Na2S2O3-H2SO4-CuSO4 Dynamical System.

PubMed

Jędrusiak, Mikołaj; Orlik, Marek

2016-03-31

The H2O2-S2O3(2-)-H(+)-Cu(2+) dynamical system exhibits sustained oscillations under flow conditions but reveals only a single initial peak of the indicator electrode potential and pH variation under batch isothermal conditions. Thus, in the latter case, there is no possibility of the coupling of the oscillations and diffusion which could lead to formation of sustained spatiotemporal patterns in this process. However, in the inhomogeneous temperature field, due to dependence of the local reaction kinetics on temperature, spatial inhomogeneities of pH distribution can develop which, in the presence of an appropriate indicator, thymol blue, manifest themselves as the color front traveling along the quasi-one-dimensional reactor. In this work, we describe the experimental conditions under which the above-mentioned phenomena can be observed and present their numerical model based on thermokinetic coupling and spatial coordinate introduced to earlier isothermal homogeneous kinetic mechanism.

There is more to pollinator-mediated selection than pollen limitation.

PubMed

Sletvold, Nina; Agren, Jon

2014-07-01

Spatial variation in pollinator-mediated selection (Δβpoll ) is a major driver of floral diversification, but we lack a quantitative understanding of its link to pollen limitation (PL) and net selection on floral traits. For 2-5 years, we quantified Δβpoll on floral traits in two populations each of two orchid species differing in PL. In both species, spatiotemporal variation in Δβpoll explained much of the variation in net selection. Selection was consistently stronger and the proportion that was pollinator-mediated was higher in the severely pollen-limited deceptive species than in the rewarding species. Within species, variation in PL could not explain variation in Δβpoll for any trait, indicating that factors influencing the functional relationship between trait variation and pollination success govern a major part of the observed variation in Δβpoll . Separating the effects of variation in mean interaction intensity and in the functional significance of traits will be necessary to understand spatiotemporal variation in selection exerted by the biotic environment. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Spatial and Temporal Patterns In Ecohydrological Separation

NASA Astrophysics Data System (ADS)

Jarvis, S. K.; Barnard, H. R.; Singha, K.; Harmon, R. E.; Szutu, D.

2017-12-01

The model of ecohydrological separation suggests that trees source water from a different subsurface pool than what is contributing to stream flow during dry periods, however diel fluctuations in stream flow and transpiration are tightly coupled. To better understand the mechanism of this coupling, this study examines spatiotemporal patterns in water isotopic relationships between tree, soil, and stream water. Preliminary analysis of data collected in 2015 show a trend in δ18O enrichment in xylem water, suggesting an increased reliance on enriched soil water not flowing to the stream as the growing season progresses, while xylem samples from 2016, a particularly wet year, do not have this trend. Variations in these temporal trends are explored with regard to distance from stream, aspect of hillslope, position in the watershed, size of the tree, and soil depth. Additionally, a near-stream site is examined at high resolution using water isotope data, sap flow, and electrical resistivity surveying to examine soil moisture and water use patterns across the riparian-hillslope transition.

Frequency spirals

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

Ottino-Löffler, Bertrand; Strogatz, Steven H., E-mail: strogatz@cornell.edu

2016-09-15

We study the dynamics of coupled phase oscillators on a two-dimensional Kuramoto lattice with periodic boundary conditions. For coupling strengths just below the transition to global phase-locking, we find localized spatiotemporal patterns that we call “frequency spirals.” These patterns cannot be seen under time averaging; they become visible only when we examine the spatial variation of the oscillators' instantaneous frequencies, where they manifest themselves as two-armed rotating spirals. In the more familiar phase representation, they appear as wobbly periodic patterns surrounding a phase vortex. Unlike the stationary phase vortices seen in magnetic spin systems, or the rotating spiral waves seenmore » in reaction-diffusion systems, frequency spirals librate: the phases of the oscillators surrounding the central vortex move forward and then backward, executing a periodic motion with zero winding number. We construct the simplest frequency spiral and characterize its properties using analytical and numerical methods. Simulations show that frequency spirals in large lattices behave much like this simple prototype.« less

A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis

PubMed Central

2013-01-01

Background Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions. Results We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/. Conclusions Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods. PMID:24373308

Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities

NASA Astrophysics Data System (ADS)

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.

Spatio-temporal dynamics induced by competing instabilities in two asymmetrically coupled nonlinear evolution equations.

PubMed

Schüler, D; Alonso, S; Torcini, A; Bär, M

2014-12-01

Pattern formation often occurs in spatially extended physical, biological, and chemical systems due to an instability of the homogeneous steady state. The type of the instability usually prescribes the resulting spatio-temporal patterns and their characteristic length scales. However, patterns resulting from the simultaneous occurrence of instabilities cannot be expected to be simple superposition of the patterns associated with the considered instabilities. To address this issue, we design two simple models composed by two asymmetrically coupled equations of non-conserved (Swift-Hohenberg equations) or conserved (Cahn-Hilliard equations) order parameters with different characteristic wave lengths. The patterns arising in these systems range from coexisting static patterns of different wavelengths to traveling waves. A linear stability analysis allows to derive a two parameter phase diagram for the studied models, in particular, revealing for the Swift-Hohenberg equations, a co-dimension two bifurcation point of Turing and wave instability and a region of coexistence of stationary and traveling patterns. The nonlinear dynamics of the coupled evolution equations is investigated by performing accurate numerical simulations. These reveal more complex patterns, ranging from traveling waves with embedded Turing patterns domains to spatio-temporal chaos, and a wide hysteretic region, where waves or Turing patterns coexist. For the coupled Cahn-Hilliard equations the presence of a weak coupling is sufficient to arrest the coarsening process and to lead to the emergence of purely periodic patterns. The final states are characterized by domains with a characteristic length, which diverges logarithmically with the coupling amplitude.

Spatio-temporal Organization During Ventricular Fibrillation in the Human Heart.

PubMed

Robson, Jinny; Aram, Parham; Nash, Martyn P; Bradley, Chris P; Hayward, Martin; Paterson, David J; Taggart, Peter; Clayton, Richard H; Kadirkamanathan, Visakan

2018-06-01

In this paper, we present a novel approach to quantify the spatio-temporal organization of electrical activation during human ventricular fibrillation (VF). We propose three different methods based on correlation analysis, graph theoretical measures and hierarchical clustering. Using the proposed approach, we quantified the level of spatio-temporal organization during three episodes of VF in ten patients, recorded using multi-electrode epicardial recordings with 30 s coronary perfusion, 150 s global myocardial ischaemia and 30 s reflow. Our findings show a steady decline in spatio-temporal organization from the onset of VF with coronary perfusion. We observed transient increases in spatio-temporal organization during global myocardial ischaemia. However, the decline in spatio-temporal organization continued during reflow. Our results were consistent across all patients, and were consistent with the numbers of phase singularities. Our findings show that the complex spatio-temporal patterns can be studied using complex network analysis.

A Geographic Information Science (GISc) Approach to Characterizing Spatiotemporal Patterns of Terrorist Incidents in Iraq, 2004-2009

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

Medina, Richard M; Siebeneck, Laura K.; Hepner, George F.

2011-01-01

As terrorism on all scales continues, it is necessary to improve understanding of terrorist and insurgent activities. This article takes a Geographic Information Systems (GIS) approach to advance the understanding of spatial, social, political, and cultural triggers that influence terrorism incidents. Spatial, temporal, and spatiotemporal patterns of terrorist attacks are examined to improve knowledge about terrorist systems of training, planning, and actions. The results of this study aim to provide a foundation for understanding attack patterns and tactics in emerging havens as well as inform the creation and implementation of various counterterrorism measures.

Spatio-Temporal Neural Networks for Vision, Reasoning and Rapid Decision Making

DTIC Science & Technology

1994-08-31

something that is obviously not pattern for long-term knowledge base (LTKB) facts. As a matter possiblc in common neural networks (as units in a...Conferences on Neural Davis, P. (19W0) Application of op~tical chaos to temporal pattern search in a Networks . Piscataway, NJ. [SC] nonlinear optical...Science Institute PROJECT TITLE: Spatio-temporal Neural Networks for Vision, Reasoning and Rapid Decision Making (N00014-93-1-1149) Number of ONR

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

PubMed

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Precise-Spike-Driven Synaptic Plasticity: Learning Hetero-Association of Spatiotemporal Spike Patterns

PubMed Central

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe. PMID:24223789

Spatiotemporal patterns of severe fever with thrombocytopenia syndrome in China, 2011-2016.

PubMed

Sun, Jimin; Lu, Liang; Wu, Haixia; Yang, Jun; Liu, Keke; Liu, Qiyong

2018-05-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and the number of SFTS cases have increased year by year in China. However, spatiotemporal patterns and trends of SFTS are less clear up to date. In order to explore spatiotemporal patterns and predict SFTS incidences, we analyzed temporal trends of SFTS using autoregressive integrated moving average (ARIMA) model, spatial patterns, and spatiotemporal clusters of SFTS cases at the county level based on SFTS data in China during 2011-2016. We determined the optimal time series model was ARIMA (2, 0, 1) × (0, 0, 1) 12 which fitted the SFTS cases reasonably well during the training process and forecast process. In the spatial clustering analysis, the global autocorrelation suggested that SFTS cases were not of random distribution. Local spatial autocorrelation analysis of SFTS identified foci mainly concentrated in Hubei Province, Henan Province, Anhui Province, Shandong Province, Liaoning Province, and Zhejiang Province. A most likely cluster including 21 counties in Henan Province and Hubei Province was observed in the central region of China from April 2015 to August 2016. Our results will provide a sound evidence base for future prevention and control programs of SFTS such as allocation of the health resources, surveillance in high-risk regions, health education, improvement of diagnosis and so on. Copyright © 2018 Elsevier GmbH. All rights reserved.

Meteor tracking via local pattern clustering in spatio-temporal domain

NASA Astrophysics Data System (ADS)

Kukal, Jaromír.; Klimt, Martin; Švihlík, Jan; Fliegel, Karel

2016-09-01

Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).

Spatiotemporal shoreline dynamics of Namibian coastal lagoons derived by a dense remote sensing time series approach

NASA Astrophysics Data System (ADS)

Behling, Robert; Milewski, Robert; Chabrillat, Sabine

2018-06-01

This paper proposes the remote sensing time series approach WLMO (Water-Land MOnitor) to monitor spatiotemporal shoreline changes. The approach uses a hierarchical classification system based on temporal MNDWI-trajectories with the goal to accommodate typical uncertainties in remote sensing shoreline extraction techniques such as existence of clouds and geometric mismatches between images. Applied to a dense Landsat time series between 1984 and 2014 for the two Namibian coastal lagoons at Walvis Bay and Sandwich Harbour the WLMO was able to identify detailed accretion and erosion progressions at the sand spits forming these lagoons. For both lagoons a northward expansion of the sand spits of up to 1000 m was identified, which corresponds well with the prevailing northwards directed ocean current and wind processes that are responsible for the material transport along the shore. At Walvis Bay we could also show that in the 30 years of analysis the sand spit's width has decreased by more than a half from 750 m in 1984-360 m in 2014. This ongoing cross-shore erosion process is a severe risk for future sand spit breaching, which would expose parts of the lagoon and the city to the open ocean. One of the major advantages of WLMO is the opportunity to analyze detailed spatiotemporal shoreline changes. Thus, it could be shown that the observed long-term accretion and erosion processes underwent great variations over time and cannot a priori be assumed as linear processes. Such detailed spatiotemporal process patterns are a prerequisite to improve the understanding of the processes forming the Namibian shorelines. Moreover, the approach has also the potential to be used in other coastal areas, because the focus on MNDWI-trajectories allows the transfer to many multispectral satellite sensors (e.g. Sentinel-2, ASTER) available worldwide.

Changing and Differentiated Urban Landscape in China: Spatiotemporal Patterns and Driving Forces.

PubMed

Fang, Chuanglin; Li, Guangdong; Wang, Shaojian

2016-03-01

Urban landscape spatiotemporal change patterns and their driving mechanisms in China are poorly understood at the national level. Here we used remote sensing data, landscape metrics, and a spatial econometric model to characterize the spatiotemporal patterns of urban landscape change and investigate its driving forces in China between 1990 and 2005. The results showed that the urban landscape pattern has experienced drastic changes over the past 15 years. Total urban area has expanded approximately 1.61 times, with a 2.98% annual urban-growth rate. Compared to previous single-city studies, although urban areas are expanding rapidly, the overall fragmentation of the urban landscape is decreasing and is more irregular and complex at the national level. We also found a stair-stepping, urban-landscape changing pattern among eastern, central, and western counties. In addition, administrative level, urban size, and hierarchy have effects on the urban landscape pattern. We also found that a combination of landscape metrics can be used to supplement our understanding of the pattern of urbanization. The changes in these metrics are correlated with geographical indicators, socioeconomic factors, infrastructure variables, administrative level factors, policy factors, and historical factors. Our results indicate that the top priority should be strengthening the management of urban planning. A compact and congregate urban landscape may be a good choice of pattern for urban development in China.

Spatiotemporal modelling and mapping of the bubonic plague epidemic in India.

PubMed

Yu, Hwa-Lung; Christakos, George

2006-03-17

This work studies the spatiotemporal evolution of bubonic plague in India during 1896-1906 using stochastic concepts and geographical information science techniques. In the past, most investigations focused on selected cities to conduct different kinds of studies, such as the ecology of rats. No detailed maps existed incorporating the space-time dependence structure and uncertainty sources of the epidemic system and providing a composite space-time picture of the disease propagation characteristics. Informative spatiotemporal maps were generated that represented mortality rates and geographical spread of the disease, and epidemic indicator plots were derived that offered meaningful characterizations of the spatiotemporal disease distribution. The bubonic plague in India exhibited strong seasonal and geographical features. During its entire duration, the plague continued to invade new geographical areas, while it followed a re-emergence pattern at many localities; its rate changed significantly during each year and the mortality distribution exhibited space-time heterogeneous patterns; prevalence usually occurred in the autumn and spring, whereas the plague stopped moving towards new locations during the summers. Modern stochastic modelling and geographical information science provide powerful means to study the spatiotemporal distribution of the bubonic plague epidemic under conditions of uncertainty and multi-sourced databases; to account for various forms of interdisciplinary knowledge; and to generate informative space-time maps of mortality rates and propagation patterns. To the best of our knowledge, this kind of plague maps and plots become available for the first time, thus providing novel perspectives concerning the distribution and space-time propagation of the deadly epidemic. Furthermore, systematic maps and indicator plots make possible the comparison of the spatial-temporal propagation patterns of different diseases.

Spatiotemporal modelling and mapping of the bubonic plague epidemic in India

PubMed Central

Yu, Hwa-Lung; Christakos, George

2006-01-01

Background This work studies the spatiotemporal evolution of bubonic plague in India during 1896–1906 using stochastic concepts and geographical information science techniques. In the past, most investigations focused on selected cities to conduct different kinds of studies, such as the ecology of rats. No detailed maps existed incorporating the space-time dependence structure and uncertainty sources of the epidemic system and providing a composite space-time picture of the disease propagation characteristics. Results Informative spatiotemporal maps were generated that represented mortality rates and geographical spread of the disease, and epidemic indicator plots were derived that offered meaningful characterizations of the spatiotemporal disease distribution. The bubonic plague in India exhibited strong seasonal and geographical features. During its entire duration, the plague continued to invade new geographical areas, while it followed a re-emergence pattern at many localities; its rate changed significantly during each year and the mortality distribution exhibited space-time heterogeneous patterns; prevalence usually occurred in the autumn and spring, whereas the plague stopped moving towards new locations during the summers. Conclusion Modern stochastic modelling and geographical information science provide powerful means to study the spatiotemporal distribution of the bubonic plague epidemic under conditions of uncertainty and multi-sourced databases; to account for various forms of interdisciplinary knowledge; and to generate informative space-time maps of mortality rates and propagation patterns. To the best of our knowledge, this kind of plague maps and plots become available for the first time, thus providing novel perspectives concerning the distribution and space-time propagation of the deadly epidemic. Furthermore, systematic maps and indicator plots make possible the comparison of the spatial-temporal propagation patterns of different diseases. PMID:16545128

Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China

PubMed Central

Fan, Yaxin; Zhu, Xinyan; Guo, Wei; Guo, Tao

2018-01-01

The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions. PMID:29672551

The influence of natural factors on the spatio-temporal distribution of Oncomelania hupensis.

PubMed

Cheng, Gong; Li, Dan; Zhuang, Dafang; Wang, Yong

2016-12-01

We analyzed the influence of natural factors, such as temperature, rainfall, vegetation and hydrology, on the spatio-temporal distribution of Oncomelania hupensis and explored the leading factors influencing these parameters. The results will provide reference methods and theoretical a basis for the schistosomiasis control. GIS (Geographic Information System) spatial display and analysis were used to describe the spatio-temporal distribution of Oncomelania hupensis in the study area (Dongting Lake in Hunan Province) from 2004 to 2011. Correlation analysis was used to detect the natural factors associated with the spatio-temporal distribution of O. hupensis. Spatial regression analysis was used to quantitatively analyze the effects of related natural factors on the spatio-temporal distribution of snails and explore the dominant factors influencing this parameter. (1) Overall, the spatio-temporal distribution of O. hupensis was governed by the comprehensive effects of natural factors. In the study area, the average density of living snails showed a downward trend, with the exception of a slight rebound in 2009. The density of living snails showed significant spatial clustering, and the degree of aggregation was initially weak but enhanced later. Regions with high snail density and towns with an HH distribution pattern were mostly distributed in the plain areas in the northwestern and inlet and outlet of the lake. (2) There were space-time differences in the influence of natural factors on the spatio-temporal distribution of O. hupensis. Temporally, the comprehensive influence of natural factors on snail distribution increased first and then decreased. Natural factors played an important role in snail distribution in 2005, 2006, 2010 and 2011. Spatially, it decreased from the northeast to the southwest. Snail distributions in more than 20 towns located along the Yuanshui River and on the west side of the Lishui River were less affected by natural factors, whereas relatively larger in areas around the outlet of the lake (Chenglingji) were more affected. (3) The effects of natural factors on the spatio-temporal distribution of O. hupensis were spatio-temporally heterogeneous. Rainfall, land surface temperature, NDVI, and distance from water sources all played an important role in the spatio-temporal distribution of O. hupensis. In addition, due to the effects of the local geographical environment, the direction of the influences the average annual rainfall, land surface temperature, and NDVI had on the spatio-temporal distribution of O. hupensis were all spatio-temporally heterogeneous, and both the distance from water sources and the history of snail distribution always had positive effects on the distribution O. hupensis, but the direction of the influence was spatio-temporally heterogeneous. (4) Of all the natural factors, the leading factors influencing the spatio-temporal distribution of O. hupensis were rainfall and vegetation (NDVI), and the primary factor alternated between these two. The leading role of rainfall decreased year by year, while that of vegetation (NDVI) increased from 2004 to 2011. The spatio-temporal distribution of O. hupensis was significantly influenced by natural factors, and the influences were heterogeneous across space and time. Additionally, the variation in the spatial-temporal distribution of O. hupensis was mainly affected by rainfall and vegetation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Millimeter-scale epileptiform spike propagation patterns and their relationship to seizures

PubMed Central

Vanleer, Ann C; Blanco, Justin A; Wagenaar, Joost B; Viventi, Jonathan; Contreras, Diego; Litt, Brian

2016-01-01

Objective Current mapping of epileptic networks in patients prior to epilepsy surgery utilizes electrode arrays with sparse spatial sampling (∼1.0 cm inter-electrode spacing). Recent research demonstrates that sub-millimeter, cortical-column-scale domains have a role in seizure generation that may be clinically significant. We use high-resolution, active, flexible surface electrode arrays with 500 μm inter-electrode spacing to explore epileptiform local field potential spike propagation patterns in two dimensions recorded from subdural micro-electrocorticographic signals in vivo in cat. In this study, we aimed to develop methods to quantitatively characterize the spatiotemporal dynamics of epileptiform activity at high-resolution. Approach We topically administered a GABA-antagonist, picrotoxin, to induce acute neocortical epileptiform activity leading up to discrete electrographic seizures. We extracted features from local field potential spikes to characterize spatiotemporal patterns in these events. We then tested the hypothesis that two dimensional spike patterns during seizures were different from those between seizures. Main results We showed that spatially correlated events can be used to distinguish ictal versus interictal spikes. Significance We conclude that sub-millimeter-scale spatiotemporal spike patterns reveal network dynamics that are invisible to standard clinical recordings and contain information related to seizure-state. PMID:26859260

Millimeter-scale epileptiform spike propagation patterns and their relationship to seizures

NASA Astrophysics Data System (ADS)

Vanleer, Ann C.; Blanco, Justin A.; Wagenaar, Joost B.; Viventi, Jonathan; Contreras, Diego; Litt, Brian

2016-04-01

Objective. Current mapping of epileptic networks in patients prior to epilepsy surgery utilizes electrode arrays with sparse spatial sampling (∼1.0 cm inter-electrode spacing). Recent research demonstrates that sub-millimeter, cortical-column-scale domains have a role in seizure generation that may be clinically significant. We use high-resolution, active, flexible surface electrode arrays with 500 μm inter-electrode spacing to explore epileptiform local field potential (LFP) spike propagation patterns in two dimensions recorded from subdural micro-electrocorticographic signals in vivo in cat. In this study, we aimed to develop methods to quantitatively characterize the spatiotemporal dynamics of epileptiform activity at high-resolution. Approach. We topically administered a GABA-antagonist, picrotoxin, to induce acute neocortical epileptiform activity leading up to discrete electrographic seizures. We extracted features from LFP spikes to characterize spatiotemporal patterns in these events. We then tested the hypothesis that two-dimensional spike patterns during seizures were different from those between seizures. Main results. We showed that spatially correlated events can be used to distinguish ictal versus interictal spikes. Significance. We conclude that sub-millimeter-scale spatiotemporal spike patterns reveal network dynamics that are invisible to standard clinical recordings and contain information related to seizure-state.

Stability Switches, Hopf Bifurcations, and Spatio-temporal Patterns in a Delayed Neural Model with Bidirectional Coupling

NASA Astrophysics Data System (ADS)

Song, Yongli; Zhang, Tonghua; Tadé, Moses O.

2009-12-01

The dynamical behavior of a delayed neural network with bi-directional coupling is investigated by taking the delay as the bifurcating parameter. Some parameter regions are given for conditional/absolute stability and Hopf bifurcations by using the theory of functional differential equations. As the propagation time delay in the coupling varies, stability switches for the trivial solution are found. Conditions ensuring the stability and direction of the Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. We also discuss the spatio-temporal patterns of bifurcating periodic oscillations by using the symmetric bifurcation theory of delay differential equations combined with representation theory of Lie groups. In particular, we obtain that the spatio-temporal patterns of bifurcating periodic oscillations will alternate according to the change of the propagation time delay in the coupling, i.e., different ranges of delays correspond to different patterns of neural activities. Numerical simulations are given to illustrate the obtained results and show the existence of bursts in some interval of the time for large enough delay.

Excitatory Local Interneurons Enhance Tuning of Sensory Information

PubMed Central

Assisi, Collins; Stopfer, Mark; Bazhenov, Maxim

2012-01-01

Neurons in the insect antennal lobe represent odors as spatiotemporal patterns of activity that unfold over multiple time scales. As these patterns unspool they decrease the overlap between odor representations and thereby increase the ability of the olfactory system to discriminate odors. Using a realistic model of the insect antennal lobe we examined two competing components of this process –lateral excitation from local excitatory interneurons, and slow inhibition from local inhibitory interneurons. We found that lateral excitation amplified differences between representations of similar odors by recruiting projection neurons that did not receive direct input from olfactory receptors. However, this increased sensitivity also amplified noisy variations in input and compromised the ability of the system to respond reliably to multiple presentations of the same odor. Slow inhibition curtailed the spread of projection neuron activity and increased response reliability. These competing influences must be finely balanced in order to decorrelate odor representations. PMID:22807661

Capturing spatiotemporal variation in wildfires for improving postwildfire debris-flow hazard assessments: Chapter 20

USGS Publications Warehouse

Haas, Jessica R.; Thompson, Matthew P.; Tillery, Anne C.; Scott, Joe H.

2017-01-01

Wildfires can increase the frequency and magnitude of catastrophic debris flows. Integrated, proactive natural hazard assessment would therefore characterize landscapes based on the potential for the occurrence and interactions of wildfires and postwildfire debris flows. This chapter presents a new modeling effort that can quantify the variability surrounding a key input to postwildfire debris-flow modeling, the amount of watershed burned at moderate to high severity, in a prewildfire context. The use of stochastic wildfire simulation captures variability surrounding the timing and location of ignitions, fire weather patterns, and ultimately the spatial patterns of watershed area burned. Model results provide for enhanced estimates of postwildfire debris-flow hazard in a prewildfire context, and multiple hazard metrics are generated to characterize and contrast hazards across watersheds. Results can guide mitigation efforts by allowing planners to identify which factors may be contributing the most to the hazard rankings of watersheds.

Spatio-temporal variation in age structure and abundance of the endangered snail kite: Pooling across regions masks a declining and aging population

USGS Publications Warehouse

Reichert, Brian E.; Kendall, William L.; Fletcher, Robert J.; Kitchens, Wiley M.

2016-01-01

While variation in age structure over time and space has long been considered important for population dynamics and conservation, reliable estimates of such spatio-temporal variation in age structure have been elusive for wild vertebrate populations. This limitation has arisen because of problems of imperfect detection, the potential for temporary emigration impacting assessments of age structure, and limited information on age. However, identifying patterns in age structure is important for making reliable predictions of both short- and long-term dynamics of populations of conservation concern. Using a multistate superpopulation estimator, we estimated region-specific abundance and age structure (the proportion of individuals within each age class) of a highly endangered population of snail kites for two separate regions in Florida over 17 years (1997–2013). We find that in the southern region of the snail kite—a region known to be critical for the long-term persistence of the species—the population has declined significantly since 1997, and during this time, it has increasingly become dominated by older snail kites (> 12 years old). In contrast, in the northern region—a region historically thought to serve primarily as drought refugia—the population has increased significantly since 2007 and age structure is more evenly distributed among age classes. Given that snail kites show senescence at approximately 13 years of age, where individuals suffer higher mortality rates and lower breeding rates, these results reveal an alarming trend for the southern region. Our work illustrates the importance of accounting for spatial structure when assessing changes in abundance and age distribution and the need for monitoring of age structure in imperiled species.

Phase Transitions and Volunteering in Spatial Public Goods Games

NASA Astrophysics Data System (ADS)

Szabó, György; Hauert, Christoph

2002-08-01

We present a simple yet effective mechanism promoting cooperation under full anonymity by allowing for voluntary participation in public goods games. This natural extension leads to ``rock-scissors-paper''-type cyclic dominance of the three strategies, cooperate, defect, and loner. In spatial settings with players arranged on a regular lattice, this results in interesting dynamical properties and intriguing spatiotemporal patterns. In particular, variations of the value of the public good leads to transitions between one-, two-, and three-strategy states which either are in the class of directed percolation or show interesting analogies to Ising-type models. Although volunteering is incapable of stabilizing cooperation, it efficiently prevents successful spreading of selfish behavior.

A hybrid spatiotemporal drought forecasting model for operational use

NASA Astrophysics Data System (ADS)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers.

PubMed

Das, Koel; Giesbrecht, Barry; Eckstein, Miguel P

2010-07-15

Within the past decade computational approaches adopted from the field of machine learning have provided neuroscientists with powerful new tools for analyzing neural data. For instance, previous studies have applied pattern classification algorithms to electroencephalography data to predict the category of presented visual stimuli, human observer decision choices and task difficulty. Here, we quantitatively compare the ability of pattern classifiers and three ERP metrics (peak amplitude, mean amplitude, and onset latency of the face-selective N170) to predict variations across individuals' behavioral performance in a difficult perceptual task identifying images of faces and cars embedded in noise. We investigate three different pattern classifiers (Classwise Principal Component Analysis, CPCA; Linear Discriminant Analysis, LDA; and Support Vector Machine, SVM), five training methods differing in the selection of training data sets and three analyses procedures for the ERP measures. We show that all three pattern classifier algorithms surpass traditional ERP measurements in their ability to predict individual differences in performance. Although the differences across pattern classifiers were not large, the CPCA method with training data sets restricted to EEG activity for trials in which observers expressed high confidence about their decisions performed the highest at predicting perceptual performance of observers. We also show that the neural activity predicting the performance across individuals was distributed through time starting at 120ms, and unlike the face-selective ERP response, sustained for more than 400ms after stimulus presentation, indicating that both early and late components contain information correlated with observers' behavioral performance. Together, our results further demonstrate the potential of pattern classifiers compared to more traditional ERP techniques as an analysis tool for modeling spatiotemporal dynamics of the human brain and relating neural activity to behavior. Copyright 2010 Elsevier Inc. All rights reserved.

Spatio-temporal factors associated with meningococcal meningitis annual incidence at the health centre level in Niger, 2004-2010.

PubMed

Paireau, Juliette; Maïnassara, Halima B; Jusot, Jean-François; Collard, Jean-Marc; Idi, Issa; Moulia-Pelat, Jean-Paul; Mueller, Judith E; Fontanet, Arnaud

2014-05-01

Epidemics of meningococcal meningitis (MM) recurrently strike the African Meningitis Belt. This study aimed at investigating factors, still poorly understood, that influence annual incidence of MM serogroup A, the main etiologic agent over 2004-2010, at a fine spatial scale in Niger. To take into account data dependencies over space and time and control for unobserved confounding factors, we developed an explanatory Bayesian hierarchical model over 2004-2010 at the health centre catchment area (HCCA) level. The multivariate model revealed that both climatic and non-climatic factors were important for explaining spatio-temporal variations in incidence: mean relative humidity during November-June over the study region (posterior mean Incidence Rate Ratio (IRR) = 0.656, 95% Credible Interval (CI) 0.405-0.949) and occurrence of early rains in March in a HCCA (IRR = 0.353, 95% CI 0.239-0.502) were protective factors; a higher risk was associated with the percentage of neighbouring HCCAs having at least one MM A case during the same year (IRR = 2.365, 95% CI 2.078-2.695), the presence of a road crossing the HCCA (IRR = 1.743, 95% CI 1.173-2.474) and the occurrence of cases before 31 December in a HCCA (IRR = 6.801, 95% CI 4.004-10.910). At the study region level, higher annual incidence correlated with greater geographic spread and, to a lesser extent, with higher intensity of localized outbreaks. Based on these findings, we hypothesize that spatio-temporal variability of MM A incidence between years and HCCAs result from variations in the intensity or duration of the dry season climatic effects on disease risk, and is further impacted by factors of spatial contacts, representing facilitated pathogen transmission. Additional unexplained factors may contribute to the observed incidence patterns and should be further investigated.

To migrate, stay put, or wander? Varied movement strategies in bald eagles (Haliaeetus leucocephalus).

PubMed

Wheat, Rachel E; Lewis, Stephen B; Wang, Yiwei; Levi, Taal; Wilmers, Christopher C

2017-01-01

Quantifying individual variability in movement behavior is critical to understanding population-level patterns in animals. Here, we explore intraspecific variation in movement strategies of bald eagles ( Haliaeetus leucocephalus ) in the north Pacific, where there is high spatiotemporal resource variability. We tracked 28 bald eagles (five immature, 23 adult) using GPS transmitters between May 2010 and January 2016. We found evidence of four movement strategies among bald eagles in southeastern Alaska and western Canada: breeding individuals that were largely sedentary and remained near nest sites year-round, non-breeding migratory individuals that made regular seasonal travel between northern summer and southern winter ranges, non-breeding localized individuals that displayed fidelity to foraging sites, and non-breeding nomadic individuals with irregular movement. On average, males traveled farther per day than females. Most nomadic individuals were immature, and all residential individuals (i.e. breeders and localized birds) were adults. Alternative movement strategies among north Pacific eagles are likely associated with the age and sex class, as well as breeding status, of an individual. Intraspecific variation in movement strategies within the population results in different space use patterns among contingents, which has important implications for conservation and management.

Moving GIS Research Indoors: Spatiotemporal Analysis of Agricultural Animals

PubMed Central

Daigle, Courtney L.; Banerjee, Debasmit; Montgomery, Robert A.; Biswas, Subir; Siegford, Janice M.

2014-01-01

A proof of concept applying wildlife ecology techniques to animal welfare science in intensive agricultural environments was conducted using non-cage laying hens. Studies of wildlife ecology regularly use Geographic Information Systems (GIS) to assess wild animal movement and behavior within environments with relatively unlimited space and finite resources. However, rather than depicting landscapes, a GIS could be developed in animal production environments to provide insight into animal behavior as an indicator of animal welfare. We developed a GIS-based approach for studying agricultural animal behavior in an environment with finite space and unlimited resources. Concurrent data from wireless body-worn location tracking sensor and video-recording systems, which depicted spatially-explicit behavior of hens (135 hens/room) in two identical indoor enclosures, were collected. The spatial configuration of specific hen behaviors, variation in home range patterns, and variation in home range overlap show that individual hens respond to the same environment differently. Such information could catalyze management practice adjustments (e.g., modifying feeder design and/or location). Genetically-similar hens exhibited diverse behavioral and spatial patterns via a proof of concept approach enabling detailed examinations of individual non-cage laying hen behavior and welfare. PMID:25098421

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.

Effect of physico-chemical regimes and tropical cyclones on seasonal distribution of chlorophyll-a in the Chilika Lagoon, east coast of India.

PubMed

Sahoo, Subhashree; Baliarsingh, S K; Lotliker, Aneesh A; Pradhan, Umesh K; Thomas, C S; Sahu, K C

2017-04-01

A comprehensive analysis on spatiotemporal variation in physico-chemical variables and their control on chlorophyll-a during 2013-14 was carried out in the Chilika Lagoon. Spatiotemporal variation in physico-chemical regimes significantly controlled the phytoplankton biomass of the lagoon. Further, precipitation-induced river/terrestrial freshwater influx and marine influence controlled the physico-chemical regimes of the Chilika Lagoon, such as nutrients (NH 4 + , NO 3 - , NO 2 - , PO 4 3- and Si(OH) 4 ), temperature, salinity, total suspended matter and dissolved oxygen. This study revealed significant effects of tropical cyclones Phailin (2013) and Hudhud (2014) on physico-chemical regimes and in turn the phytoplankton biomass of the lagoon. Although both cyclones Phailin (2013) and Hudhud (2014) were intense, Phailin (2013) had a greater impact on the Chilika Lagoon due to the proximity of its landfall. Heavy precipitation caused an influx of nutrient-rich freshwater, both during each cyclone's passage, through rainfall, and after, through increased river flow and terrestrial run-off. The increase in nutrients, carried by the run-off, promoted phytoplankton growth, albeit in lag phase. In general, phytoplankton growth was controlled by nitrogenous nutrients. However, the addition of SiO 4 through terrigenous run-off fuelled preferential growth of diatoms. The salinity pattern (which can be considered a proxy for fresh and marine water influx) indicated injection of freshwater nutrients into the northern, southern and central sectors of the lagoon through riverine/terrestrial freshwater run-off; marine influx was restricted to the mouth of the lagoon. Present and past magnitudes of salinity and chlorophyll-a were also compared to better understand the pattern of variability. A significant change in salinity pattern was noticed after the opening of an artificial inlet, because of the resulting higher influx of marine water. The overall phytoplankton biomass (using chlorophyll-a concentration as a proxy) remained consistent in the lagoon pre- and post-restoration. Due to the wide range of salinity and temperature tolerance, diatoms remained dominant in both pre- and post-restoration periods, but the overall phytoplankton diversity increased after the artificial inlet was dredged.

Spatio-temporal dynamics induced by competing instabilities in two asymmetrically coupled nonlinear evolution equations

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

Schüler, D.; Alonso, S.; Bär, M.

2014-12-15

Pattern formation often occurs in spatially extended physical, biological, and chemical systems due to an instability of the homogeneous steady state. The type of the instability usually prescribes the resulting spatio-temporal patterns and their characteristic length scales. However, patterns resulting from the simultaneous occurrence of instabilities cannot be expected to be simple superposition of the patterns associated with the considered instabilities. To address this issue, we design two simple models composed by two asymmetrically coupled equations of non-conserved (Swift-Hohenberg equations) or conserved (Cahn-Hilliard equations) order parameters with different characteristic wave lengths. The patterns arising in these systems range from coexistingmore » static patterns of different wavelengths to traveling waves. A linear stability analysis allows to derive a two parameter phase diagram for the studied models, in particular, revealing for the Swift-Hohenberg equations, a co-dimension two bifurcation point of Turing and wave instability and a region of coexistence of stationary and traveling patterns. The nonlinear dynamics of the coupled evolution equations is investigated by performing accurate numerical simulations. These reveal more complex patterns, ranging from traveling waves with embedded Turing patterns domains to spatio-temporal chaos, and a wide hysteretic region, where waves or Turing patterns coexist. For the coupled Cahn-Hilliard equations the presence of a weak coupling is sufficient to arrest the coarsening process and to lead to the emergence of purely periodic patterns. The final states are characterized by domains with a characteristic length, which diverges logarithmically with the coupling amplitude.« less

Learning-automaton-based online discovery and tracking of spatiotemporal event patterns.

PubMed

Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, B John

2013-06-01

Discovering and tracking of spatiotemporal patterns in noisy sequences of events are difficult tasks that have become increasingly pertinent due to recent advances in ubiquitous computing, such as community-based social networking applications. The core activities for applications of this class include the sharing and notification of events, and the importance and usefulness of these functionalities increase as event sharing expands into larger areas of one's life. Ironically, instead of being helpful, an excessive number of event notifications can quickly render the functionality of event sharing to be obtrusive. Indeed, any notification of events that provides redundant information to the application/user can be seen to be an unnecessary distraction. In this paper, we introduce a new scheme for discovering and tracking noisy spatiotemporal event patterns, with the purpose of suppressing reoccurring patterns, while discerning novel events. Our scheme is based on maintaining a collection of hypotheses, each one conjecturing a specific spatiotemporal event pattern. A dedicated learning automaton (LA)--the spatiotemporal pattern LA (STPLA)--is associated with each hypothesis. By processing events as they unfold, we attempt to infer the correctness of each hypothesis through a real-time guided random walk. Consequently, the scheme that we present is computationally efficient, with a minimal memory footprint. Furthermore, it is ergodic, allowing adaptation. Empirical results involving extensive simulations demonstrate the superior convergence and adaptation speed of STPLA, as well as an ability to operate successfully with noise, including both the erroneous inclusion and omission of events. An empirical comparison study was performed and confirms the superiority of our scheme compared to a similar state-of-the-art approach. In particular, the robustness of the STPLA to inclusion as well as to omission noise constitutes a unique property compared to other related approaches. In addition, the results included, which involve the so-called " presence sharing" application, are both promising and, in our opinion, impressive. It is thus our opinion that the proposed STPLA scheme is, in general, ideal for improving the usefulness of event notification and sharing systems, since it is capable of significantly, robustly, and adaptively suppressing redundant information.

Virtual active touch using randomly patterned intracortical microstimulation.

PubMed

O'Doherty, Joseph E; Lebedev, Mikhail A; Li, Zheng; Nicolelis, Miguel A L

2012-01-01

Intracortical microstimulation (ICMS) has promise as a means for delivering somatosensory feedback in neuroprosthetic systems. Various tactile sensations could be encoded by temporal, spatial, or spatiotemporal patterns of ICMS. However, the applicability of temporal patterns of ICMS to artificial tactile sensation during active exploration is unknown, as is the minimum discriminable difference between temporally modulated ICMS patterns. We trained rhesus monkeys in an active exploration task in which they discriminated periodic pulse-trains of ICMS (200 Hz bursts at a 10 Hz secondary frequency) from pulse trains with the same average pulse rate, but distorted periodicity (200 Hz bursts at a variable instantaneous secondary frequency). The statistics of the aperiodic pulse trains were drawn from a gamma distribution with mean inter-burst intervals equal to those of the periodic pulse trains. The monkeys distinguished periodic pulse trains from aperiodic pulse trains with coefficients of variation 0.25 or greater. Reconstruction of movement kinematics, extracted from the activity of neuronal populations recorded in the sensorimotor cortex concurrent with the delivery of ICMS feedback, improved when the recording intervals affected by ICMS artifacts were removed from analysis. These results add to the growing evidence that temporally patterned ICMS can be used to simulate a tactile sense for neuroprosthetic devices.

Global-scale modes of surface temperature variability on interannual to century timescales

NASA Technical Reports Server (NTRS)

Mann, Michael E.; Park, Jeffrey

1994-01-01

Using 100 years of global temperature anomaly data, we have performed a singluar value decomposition of temperature variations in narrow frequency bands to isolate coherent spatio-temporal modes of global climate variability. Statistical significance is determined from confidence limits obtained by Monte Carlo simulations. Secular variance is dominated by a globally coherent trend; with nearly all grid points warming in phase at varying amplitude. A smaller, but significant, share of the secular variance corresponds to a pattern dominated by warming and subsequent cooling in the high latitude North Atlantic with a roughly centennial timescale. Spatial patterns associated with significant peaks in variance within a broad period range from 2.8 to 5.7 years exhibit characteristic El Nino-Southern Oscillation (ENSO) patterns. A recent transition to a regime of higher ENSO frequency is suggested by our analysis. An interdecadal mode in the 15-to-18 years period and a mode centered at 7-to-8 years period both exhibit predominantly a North Atlantic Oscillation (NAO) temperature pattern. A potentially significant decadal mode centered on 11-to-12 years period also exhibits an NAO temperature pattern and may be modulated by the century-scale North Atlantic variability.

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

Miller, Vonda H; Jansen, Ben H

2008-12-01

Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.

Spatiotemporal variation in the reproductive ecology of two parapatric subspecies of Oenothera cespitosa (Onagraceae).

PubMed

Artz, Derek R; Villagra, Cristian A; Raguso, Robert A

2010-09-01

• Flowering plants that rely on pollinators for most of their reproduction may experience unpredictable and inconsistent availability of effective pollinators throughout their reproductive lifetime. We investigated the reproductive ecology of two subspecies of the tufted evening primrose, Oenothera cespitosa, which occupy geographically and edaphically distinct habitats in western North America: O. cespitosa subsp. navajoensis inhabits sandstone soils on open sites or rocky slopes in the Colorado Plateau and O. cespitosa subsp. cespitosa grows in clay soils on talus slopes and exposed rocky ridges in the western Great Plains and northern Rocky Mountains of the United States. • Pollen augmentation and selfing experiments, floral visitor observations, and single-visit effectiveness experiments were conducted over 4 years to examine the breeding system and spatiotemporal variation in pollinator behavior, assemblage, and abundance at different populations for each subspecies. • Both subspecies of O. cespitosa were self-incompatible and pollen-limited, suggesting that the relative abundance, effectiveness, and movement patterns of different insects as pollinators influenced the quality and quantity of seed production in these plants. Medium-sized vespertine hawkmoths (Hyles lineata, Sphinx vashti) were effective pollinators when present, as were large matinal bees (Anthophora affabilis, A. dammersi, Xylocopa tabaniformis androleuca), whereas small oligolectic Lasioglossum bees primarily functioned as pollen thieves in the evening and morning. • These findings highlight the importance of variability of pollinator composition and abundance in the evolution of plant breeding systems and reproductive success at varying spatial and temporal scales.

Modelling catchment hydrological responses in a Himalayan Lake as a function of changing land use and land cover

NASA Astrophysics Data System (ADS)

Badar, Bazigha; Romshoo, Shakil A.; Khan, M. A.

2013-04-01

In this paper, we evaluate the impact of changing land use/land cover (LULC) on the hydrological processes in Dal lake catchment of Kashmir Himalayas by integrating remote sensing, simulation modelling and extensive field observations. Over the years, various anthropogenic pressures in the lake catchment have significantly altered the land system, impairing, inter-alia, sustained biotic communities and water quality of the lake. The primary objective of this paper was to help a better understanding of the LULC change, its driving forces and the overall impact on the hydrological response patterns. Multi-sensor and multi-temporal satellite data for 1992 and 2005 was used for determining the spatio-temporal dynamics of the lake catchment. Geographic Information System (GIS) based simulation model namely Generalized Watershed Loading Function (GWLF) was used to model the hydrological processes under the LULC conditions. We discuss spatio-temporal variations in LULC and identify factors contributing to these variations and analyze the corresponding impacts of the change on the hydrological processes like runoff, erosion and sedimentation. The simulated results on the hydrological responses reveal that depletion of the vegetation cover in the study area and increase in impervious and bare surface cover due to anthropogenic interventions are the primary reasons for the increased runoff, erosion and sediment discharges in the Dal lake catchment. This study concludes that LULC change in the catchment is a major concern that has disrupted the ecological stability and functioning of the Dal lake ecosystem.

Spatio-Temporal Variation in Landscape Composition May Speed Resistance Evolution of Pests to Bt Crops.

PubMed

Ives, Anthony R; Paull, Cate; Hulthen, Andrew; Downes, Sharon; Andow, David A; Haygood, Ralph; Zalucki, Myron P; Schellhorn, Nancy A

2017-01-01

Transgenic crops that express insecticide genes from Bacillus thuringiensis (Bt) are used worldwide against moth and beetle pests. Because these engineered plants can kill over 95% of susceptible larvae, they can rapidly select for resistance. Here, we use a model for a pyramid two-toxin Bt crop to explore the consequences of spatio-temporal variation in the area of Bt crop and non-Bt refuge habitat. We show that variability over time in the proportion of suitable non-Bt breeding habitat, Q, or in the total area of Bt and suitable non-Bt habitat, K, can increase the overall rate of resistance evolution by causing short-term surges of intense selection. These surges can be exacerbated when temporal variation in Q and/or K cause high larval densities in refuges that increase density-dependent mortality; this will give resistant larvae in Bt fields a relative advantage over susceptible larvae that largely depend on refuges. We address the effects of spatio-temporal variation in a management setting for two bollworm pests of cotton, Helicoverpa armigera and H. punctigera, and field data on landscape crop distributions from Australia. Even a small proportion of Bt fields available to egg-laying females when refuges are sparse may result in high exposure to Bt for just a single generation per year and cause a surge in selection. Therefore, rapid resistance evolution can occur when Bt crops are rare rather than common in the landscape. These results highlight the need to understand spatio-temporal fluctuations in the landscape composition of Bt crops and non-Bt habitats in order to design effective resistance management strategies.

Spatiotemporal variation of surface shortwave forcing from fire-induced albedo change in interior Alaska

USGS Publications Warehouse

Huang, Shengli; Dahal, Devendra; Liu, Heping; Jin, Suming; Young, Claudia J.; Liu, Shuang; Liu, Shu-Guang

2015-01-01

The albedo change caused by both fires and subsequent succession is spatially heterogeneous, leading to the need to assess the spatiotemporal variation of surface shortwave forcing (SSF) as a component to quantify the climate impacts of high-latitude fires. We used an image reconstruction approach to compare postfire albedo with the albedo assuming fires had not occurred. Combining the fire-caused albedo change from the 2001-2010 fires in interior Alaska and the monthly surface incoming solar radiation, we examined the spatiotemporal variation of SSF in the early successional stage of around 10 years. Our results showed that while postfire albedo generally increased in fall, winter, and spring, some burned areas could show an albedo decrease during these seasons. In summer, the albedo increased for several years and then declined again. The spring SSF distribution did not show a latitudinal decrease from south to north as previously reported. The results also indicated that although the SSF is usually largely negative in the early successional years, it may not be significant during the first postfire year. The annual 2005-2010 SSF for the 2004 fire scars was -1.30, -4.40, -3.31, -4.00, -3.42, and -2.47 Wm-2. The integrated annual SSF map showed significant spatial variation with a mean of -3.15 Wm-2 and a standard deviation of 3.26 Wm-2, 16% of burned areas having positive SSF. Our results suggest that boreal deciduous fires would be less positive for climate change than boreal evergreen fires. Future research is needed to comprehensively investigate the spatiotemporal radiative and non-radiative forcings to determine the effect of boreal fires on climate.

Spontaneous switching among multiple spatio-temporal patterns in three-oscillator systems constructed with oscillatory cells of true slime mold

NASA Astrophysics Data System (ADS)

Takamatsu, Atsuko

2006-11-01

Three-oscillator systems with plasmodia of true slime mold, Physarum polycephalum, which is an oscillatory amoeba-like unicellular organism, were experimentally constructed and their spatio-temporal patterns were investigated. Three typical spatio-temporal patterns were found: rotation ( R), partial in-phase ( PI), and partial anti-phase with double frequency ( PA). In pattern R, phase differences between adjacent oscillators were almost 120 ∘. In pattern PI, two oscillators were in-phase and the third oscillator showed anti-phase against the two oscillators. In pattern PA, two oscillators showed anti-phase and the third oscillator showed frequency doubling oscillation with small amplitude. Actually each pattern is not perfectly stable but quasi-stable. Interestingly, the system shows spontaneous switching among the multiple quasi-stable patterns. Statistical analyses revealed a characteristic in the residence time of each pattern: the histograms seem to have Gamma-like distribution form but with a sharp peak and a tail on the side of long period. That suggests the attractor of this system has complex structure composed of at least three types of sub-attractors: a “Gamma attractor”-involved with several Poisson processes, a “deterministic attractor”-the residence time is deterministic, and a “stable attractor”-each pattern is stable. When the coupling strength was small, only the Gamma attractor was observed and switching behavior among patterns R, PI, and PA almost always via an asynchronous pattern named O. A conjecture is as follows: Internal/external noise exposes each pattern of R, PI, and PA coexisting around bifurcation points: That is observed as the Gamma attractor. As coupling strength increases, the deterministic attractor appears then followed by the stable attractor, always accompanied with the Gamma attractor. Switching behavior could be caused by regular existence of the Gamma attractor.

Modeling spatio-temporal wildfire ignition point patterns

Treesearch

Amanda S. Hering; Cynthia L. Bell; Marc G. Genton

2009-01-01

We analyze and model the structure of spatio-temporal wildfire ignitions in the St. Johns River Water Management District in northeastern Florida. Previous studies, based on the K-function and an assumption of homogeneity, have shown that wildfire events occur in clusters. We revisit this analysis based on an inhomogeneous K-...

Spatiotemporal Coupling of the Tongue in Amyotrophic Lateral Sclerosis

ERIC Educational Resources Information Center

Kuruvilla, Mili S.; Green, Jordan R.; Yunusova, Yana; Hanford, Kathy

2012-01-01

Purpose: The primary aim of the investigation was to identify deficits in spatiotemporal coupling between tongue regions in amyotrophic lateral sclerosis (ALS). The relations between disease-related changes in tongue movement patterns and speech intelligibility were also determined. Methods: The authors recorded word productions from 11…

Ubiquitous Geo-Sensing for Context-Aware Analysis: Exploring Relationships between Environmental and Human Dynamics

PubMed Central

Sagl, Günther; Blaschke, Thomas; Beinat, Euro; Resch, Bernd

2012-01-01

Ubiquitous geo-sensing enables context-aware analyses of physical and social phenomena, i.e., analyzing one phenomenon in the context of another. Although such context-aware analysis can potentially enable a more holistic understanding of spatio-temporal processes, it is rarely documented in the scientific literature yet. In this paper we analyzed the collective human behavior in the context of the weather. We therefore explored the complex relationships between these two spatio-temporal phenomena to provide novel insights into the dynamics of urban systems. Aggregated mobile phone data, which served as a proxy for collective human behavior, was linked with the weather data from climate stations in the case study area, the city of Udine, Northern Italy. To identify and characterize potential patterns within the weather-human relationships, we developed a hybrid approach which integrates several spatio-temporal statistical analysis methods. Thereby we show that explanatory factor analysis, when applied to a number of meteorological variables, can be used to differentiate between normal and adverse weather conditions. Further, we measured the strength of the relationship between the ‘global’ adverse weather conditions and the spatially explicit effective variations in user-generated mobile network traffic for three distinct periods using the Maximal Information Coefficient (MIC). The analyses result in three spatially referenced maps of MICs which reveal interesting insights into collective human dynamics in the context of weather, but also initiate several new scientific challenges. PMID:23012571

Spatiotemporal patterns in reaction-diffusion system and in a vibrated granular bed

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

Swinney, H.L.; Lee, K.J.; McCormick, W.D.

Experiments on a quasi-two-dimensional reaction-diffusion system reveal transitions from a uniform state to stationary hexagonal, striped, and rhombic spatial patterns. For other reactor conditions lamellae and self-replicating spot patterns are observed. These patterns form in continuously fed thin gel reactors that can be maintained indefinitely in well-defined nonequilibrium states. Reaction-diffusion models with two chemical species yield patterns similar to those observed in the experiments. Pattern formation is also being examined in vertically oscillated thin granular layers (typically 3-30 particle diameters deep). For small acceleration amplitudes, a granular layer is flat, but above a well-defined critical acceleration amplitude, spatial patterns spontaneouslymore » form. Disordered time-dependent granular patterns are observed as well as regular patterns of squares, stripes, and hexagons. A one-dimensional model consisting of a completely inelastic ball colliding with a sinusoidally oscillating platform provides a semi-quantitative description of most of the observed bifurcations between the different spatiotemporal regimes.« less

Linkages of fracture network geometry and hydro-mechanical properties to spatio-temporal variations of seismicity in Koyna-Warna Seismic Zone

NASA Astrophysics Data System (ADS)

Selles, A.; Mikhailov, V. O.; Arora, K.; Ponomarev, A.; Gopinadh, D.; Smirnov, V.; Srinu, Y.; Satyavani, N.; Chadha, R. K.; Davulluri, S.; Rao, N. P.

2017-12-01

Well logging data and core samples from the deep boreholes in the Koyna-Warna Seismic Zone (KWSZ) provided a glimpse of the 3-D fracture network responsible for triggered earthquakes in the region. The space-time pattern of earthquakes during the last five decades show strong linkage of favourably oriented fractures system deciphered from airborne LiDAR and borehole structural logging to the seismicity. We used SAR interferometry data on surface displacements to estimate activity of the inferred faults. The failure in rocks at depths is largely governed by overlying lithostatic and pore fluid pressure in the rock matrix which are subject to change in space and time. While lithostatic pressure tends to increase with depth pore pressure is prone to fluctuations due to any change in the hydrological regime. Based on the earthquake catalogue data, the seasonal variations in seismic activity associated with annual fluctuations in the reservoir water level were analyzed over the time span of the entire history of seismological observations in this region. The regularities in the time changes in the structure of seasonal variations are revealed. An increase in pore fluid pressure can result in rock fracture and oscillating pore fluid pressures due to a reservoir loading and unloading cycles can cause iterative and cumulative damage, ultimately resulting in brittle failure under relatively low effective mean stress conditions. These regularities were verified by laboratory physical modeling. Based on our observations of main trends of spatio-temporal variations in seismicity as well as the spatial distribution of fracture network a conceptual model is presented to explain the triggered earthquakes in the KWSZ. The work was supported under the joint Russian-Indian project of the Russian Science Foundation (RSF) and the Department of Science and Technology (DST) of India (RSF project no. 16-47-02003 and DST project INT/RUS/RSF/P-13).

Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Manga, Edna; Awang, Norhashidah

2016-06-01

This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.

Flexible kinematic earthquake rupture inversion of tele-seismic waveforms: Application to the 2013 Balochistan, Pakistan earthquake

NASA Astrophysics Data System (ADS)

Shimizu, K.; Yagi, Y.; Okuwaki, R.; Kasahara, A.

2017-12-01

The kinematic earthquake rupture models are useful to derive statistics and scaling properties of the large and great earthquakes. However, the kinematic rupture models for the same earthquake are often different from one another. Such sensitivity of the modeling prevents us to understand the statistics and scaling properties of the earthquakes. Yagi and Fukahata (2011) introduces the uncertainty of Green's function into the tele-seismic waveform inversion, and shows that the stable spatiotemporal distribution of slip-rate can be obtained by using an empirical Bayesian scheme. One of the unsolved problems in the inversion rises from the modeling error originated from an uncertainty of a fault-model setting. Green's function near the nodal plane of focal mechanism is known to be sensitive to the slight change of the assumed fault geometry, and thus the spatiotemporal distribution of slip-rate should be distorted by the modeling error originated from the uncertainty of the fault model. We propose a new method accounting for the complexity in the fault geometry by additionally solving the focal mechanism on each space knot. Since a solution of finite source inversion gets unstable with an increasing of flexibility of the model, we try to estimate a stable spatiotemporal distribution of focal mechanism in the framework of Yagi and Fukahata (2011). We applied the proposed method to the 52 tele-seismic P-waveforms of the 2013 Balochistan, Pakistan earthquake. The inverted-potency distribution shows unilateral rupture propagation toward southwest of the epicenter, and the spatial variation of the focal mechanisms shares the same pattern as the fault-curvature along the tectonic fabric. On the other hand, the broad pattern of rupture process, including the direction of rupture propagation, cannot be reproduced by an inversion analysis under the assumption that the faulting occurred on a single flat plane. These results show that the modeling error caused by simplifying the fault model is non-negligible in the tele-seismic waveform inversion of the 2013 Balochistan, Pakistan earthquake.

Rotation-invariant image and video description with local binary pattern features.

PubMed

Zhao, Guoying; Ahonen, Timo; Matas, Jiří; Pietikäinen, Matti

2012-04-01

In this paper, we propose a novel approach to compute rotation-invariant features from histograms of local noninvariant patterns. We apply this approach to both static and dynamic local binary pattern (LBP) descriptors. For static-texture description, we present LBP histogram Fourier (LBP-HF) features, and for dynamic-texture recognition, we present two rotation-invariant descriptors computed from the LBPs from three orthogonal planes (LBP-TOP) features in the spatiotemporal domain. LBP-HF is a novel rotation-invariant image descriptor computed from discrete Fourier transforms of LBP histograms. The approach can be also generalized to embed any uniform features into this framework, and combining the supplementary information, e.g., sign and magnitude components of the LBP, together can improve the description ability. Moreover, two variants of rotation-invariant descriptors are proposed to the LBP-TOP, which is an effective descriptor for dynamic-texture recognition, as shown by its recent success in different application problems, but it is not rotation invariant. In the experiments, it is shown that the LBP-HF and its extensions outperform noninvariant and earlier versions of the rotation-invariant LBP in the rotation-invariant texture classification. In experiments on two dynamic-texture databases with rotations or view variations, the proposed video features can effectively deal with rotation variations of dynamic textures (DTs). They also are robust with respect to changes in viewpoint, outperforming recent methods proposed for view-invariant recognition of DTs.

Dynamical Networks Characterization of Geomagnetic Substorms and Transient Response to the Solar Wind State.

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Dods, J.; Gjerloev, J. W.

2017-12-01

Observations of how the solar wind interacts with earth's magnetosphere, and its dynamical response, are increasingly becoming a data analytics challenge. Constellations of satellites observe the solar corona, the upstream solar wind and throughout earth's magnetosphere. These data are multipoint in space and extended in time, so in principle are ideal for study using dynamical networks to characterize the full time evolving spatial pattern. We focus here on analysis of data from the full set of 100+ auroral ground based magnetometer stations that have been collated by SuperMAG. Spatio-temporal patterns of correlation between the magnetometer time series can be used to form a dynamical network [1]. The properties of the network can then be captured by (time dependent) network parameters. This offers the possibility of characterizing detailed spatio-temporal pattern by a few parameters, so that many events can then be compared [2] with each other. Whilst networks are in widespread use in the data analytics of societal and commercial data, there are additional challenges in their application to physical timeseries. Determining whether two nodes (here, ground based magnetometer stations) are connected in a network (seeing the same dynamics) requires normalization w.r.t. the detailed sensitivities and dynamical responses of specific observing stations and seasonal conductivity variations and we have developed methods to achieve this dynamical normalization. The detailed properties of the network capture time dependent spatial correlation in the magnetometer responses and we will show how this can be used to infer a transient current system response to magnetospheric activity. [l] Dods et al, J. Geophys. Res 120, doi:10.1002/2015JA02 (2015). [2] Dods et al, J. Geophys. Res. 122, doi:10.1002/2016JA02 (2017).

Holocene forest dynamics in central and western Mediterranean: periodicity, spatio-temporal patterns and climate influence.

PubMed

Di Rita, Federico; Fletcher, William J; Aranbarri, Josu; Margaritelli, Giulia; Lirer, Fabrizio; Magri, Donatella

2018-06-12

It is well-known that the Holocene exhibits a millennial-scale climate variability. However, its periodicity, spatio-temporal patterns and underlying processes are not fully deciphered yet. Here we focus on the central and western Mediterranean. We show that recurrent forest declines from the Gulf of Gaeta (central Tyrrhenian Sea) reveal a 1860-yr periodicity, consistent with a ca. 1800-yr climate fluctuation induced by large-scale changes in climate modes, linked to solar activity and/or AMOC intensity. We show that recurrent forest declines and dry events are also recorded in several pollen and palaeohydrological proxy-records in the south-central Mediterranean. We found coeval events also in several palaeohydrological records from the south-western Mediterranean, which however show generally wet climate conditions, indicating a spatio-temporal hydrological pattern opposite to the south-central Mediterranean and suggesting that different expressions of climate modes occurred in the two regions at the same time. We propose that these opposite hydroclimate regimes point to a complex interplay of the prevailing or predominant phases of NAO-like circulation, East Atlantic pattern, and extension and location of the North African anticyclone. At a larger geographical scale, displacements of the ITCZ, modulated by solar activity and/or AMOC intensity, may have also indirectly influenced the observed pattern.

Spatiotemporal drivers of dissolved organic matter in high alpine lakes: Role of Saharan dust inputs and bacterial activity.

PubMed

Mladenov, Natalie; Pulido-Villena, Elvira; Morales-Baquero, Rafael; Ortega-Retuerta, Eva; Sommaruga, Ruben; Reche, Isabel

2008-01-01

The effects of many environmental stressors such as UV radiation are mediated by dissolved organic matter (DOM) properties. Therefore, determining the factors shaping spatial and temporal patterns is particularly essential in the most susceptible, low dissolved organic carbon (DOC) lakes. We analyzed spatiotemporal variations in dissolved organic carbon concentration and dissolved organic matter optical properties (absorption and fluorescence) in 11 transparent lakes located above tree line in the Sierra Nevada Mountains (Spain), and we assessed potential external (evaporation and atmospheric deposition) and internal (bacterial abundance, bacterial production, chlorophyll a, and catchment vegetation) drivers of DOM patterns. At spatial and temporal scales, bacteria were related to chromophoric DOM (CDOM). At the temporal scale, water soluble organic carbon (WSOC) in dust deposition and evaporation were found to have a significant influence on DOC and CDOM in two Sierra Nevada lakes studied during the ice-free periods of 2000-2002. DOC concentrations and absorption coefficients at 320 nm were strongly correlated over the spatial scale (n = 11, R(2) = 0.86; p < 0.01), but inconsistently correlated over time, indicating seasonal and interannual variability in external factors and a differential response of DOC concentration and CDOM to these factors. At the continental scale, higher mean DOC concentrations and more CDOM in lakes of the Sierra Nevada than in lakes of the Pyrenees and Alps may be due to a combination of more extreme evaporation, and greater atmospheric dust deposition.

Spatiotemporal drivers of dissolved organic matter in high alpine lakes: Role of Saharan dust inputs and bacterial activity

PubMed Central

Mladenov, Natalie; Pulido-Villena, Elvira; Morales-Baquero, Rafael; Ortega-Retuerta, Eva; Sommaruga, Ruben; Reche, Isabel

2010-01-01

The effects of many environmental stressors such as UV radiation are mediated by dissolved organic matter (DOM) properties. Therefore, determining the factors shaping spatial and temporal patterns is particularly essential in the most susceptible, low dissolved organic carbon (DOC) lakes. We analyzed spatiotemporal variations in dissolved organic carbon concentration and dissolved organic matter optical properties (absorption and fluorescence) in 11 transparent lakes located above tree line in the Sierra Nevada Mountains (Spain), and we assessed potential external (evaporation and atmospheric deposition) and internal (bacterial abundance, bacterial production, chlorophyll a, and catchment vegetation) drivers of DOM patterns. At spatial and temporal scales, bacteria were related to chromophoric DOM (CDOM). At the temporal scale, water soluble organic carbon (WSOC) in dust deposition and evaporation were found to have a significant influence on DOC and CDOM in two Sierra Nevada lakes studied during the ice-free periods of 2000–2002. DOC concentrations and absorption coefficients at 320 nm were strongly correlated over the spatial scale (n = 11, R2 = 0.86; p < 0.01), but inconsistently correlated over time, indicating seasonal and interannual variability in external factors and a differential response of DOC concentration and CDOM to these factors. At the continental scale, higher mean DOC concentrations and more CDOM in lakes of the Sierra Nevada than in lakes of the Pyrenees and Alps may be due to a combination of more extreme evaporation, and greater atmospheric dust deposition. PMID:20582227

Local overfishing may be avoided by examining parameters of a spatio-temporal model

PubMed Central

Shackell, Nancy; Mills Flemming, Joanna

2017-01-01

Spatial erosion of stock structure through local overfishing can lead to stock collapse because fish often prefer certain locations, and fisheries tend to focus on those locations. Fishery managers are challenged to maintain the integrity of the entire stock and require scientific approaches that provide them with sound advice. Here we propose a Bayesian hierarchical spatio-temporal modelling framework for fish abundance data to estimate key parameters that define spatial stock structure: persistence (similarity of spatial structure over time), connectivity (coherence of temporal pattern over space), and spatial variance (variation across the seascape). The consideration of these spatial parameters in the stock assessment process can help identify the erosion of structure and assist in preventing local overfishing. We use Atlantic cod (Gadus morhua) in eastern Canada as a case study an examine the behaviour of these parameters from the height of the fishery through its collapse. We identify clear signals in parameter behaviour under circumstances of destructive stock erosion as well as for recovery of spatial structure even when combined with a non-recovery in abundance. Further, our model reveals the spatial pattern of areas of high and low density persists over the 41 years of available data and identifies the remnant patches. Models of this sort are crucial to recovery plans if we are to identify and protect remaining sources of recolonization for Atlantic cod. Our method is immediately applicable to other exploited species. PMID:28886179

Local overfishing may be avoided by examining parameters of a spatio-temporal model.

PubMed

Carson, Stuart; Shackell, Nancy; Mills Flemming, Joanna

2017-01-01

Spatial erosion of stock structure through local overfishing can lead to stock collapse because fish often prefer certain locations, and fisheries tend to focus on those locations. Fishery managers are challenged to maintain the integrity of the entire stock and require scientific approaches that provide them with sound advice. Here we propose a Bayesian hierarchical spatio-temporal modelling framework for fish abundance data to estimate key parameters that define spatial stock structure: persistence (similarity of spatial structure over time), connectivity (coherence of temporal pattern over space), and spatial variance (variation across the seascape). The consideration of these spatial parameters in the stock assessment process can help identify the erosion of structure and assist in preventing local overfishing. We use Atlantic cod (Gadus morhua) in eastern Canada as a case study an examine the behaviour of these parameters from the height of the fishery through its collapse. We identify clear signals in parameter behaviour under circumstances of destructive stock erosion as well as for recovery of spatial structure even when combined with a non-recovery in abundance. Further, our model reveals the spatial pattern of areas of high and low density persists over the 41 years of available data and identifies the remnant patches. Models of this sort are crucial to recovery plans if we are to identify and protect remaining sources of recolonization for Atlantic cod. Our method is immediately applicable to other exploited species.

Coexistence of collapse and stable spatiotemporal solitons in multimode fibers

NASA Astrophysics Data System (ADS)

Shtyrina, Olga V.; Fedoruk, Mikhail P.; Kivshar, Yuri S.; Turitsyn, Sergei K.

2018-01-01

We analyze spatiotemporal solitons in multimode optical fibers and demonstrate the existence of stable solitons, in a sharp contrast to earlier predictions of collapse of multidimensional solitons in three-dimensional media. We discuss the coexistence of blow-up solutions and collapse stabilization by a low-dimensional external potential in graded-index media, and also predict the existence of stable higher-order nonlinear waves such as dipole-mode spatiotemporal solitons. To support the main conclusions of our numerical studies we employ a variational approach and derive analytically the stability criterion for input powers for the collapse stabilization.

Visually driven chaining of elementary swim patterns into a goal-directed motor sequence: a virtual reality study of zebrafish prey capture.

PubMed

Trivedi, Chintan A; Bollmann, Johann H

2013-01-01

Prey capture behavior critically depends on rapid processing of sensory input in order to track, approach, and catch the target. When using vision, the nervous system faces the problem of extracting relevant information from a continuous stream of input in order to detect and categorize visible objects as potential prey and to select appropriate motor patterns for approach. For prey capture, many vertebrates exhibit intermittent locomotion, in which discrete motor patterns are chained into a sequence, interrupted by short periods of rest. Here, using high-speed recordings of full-length prey capture sequences performed by freely swimming zebrafish larvae in the presence of a single paramecium, we provide a detailed kinematic analysis of first and subsequent swim bouts during prey capture. Using Fourier analysis, we show that individual swim bouts represent an elementary motor pattern. Changes in orientation are directed toward the target on a graded scale and are implemented by an asymmetric tail bend component superimposed on this basic motor pattern. To further investigate the role of visual feedback on the efficiency and speed of this complex behavior, we developed a closed-loop virtual reality setup in which minimally restrained larvae recapitulated interconnected swim patterns closely resembling those observed during prey capture in freely moving fish. Systematic variation of stimulus properties showed that prey capture is initiated within a narrow range of stimulus size and velocity. Furthermore, variations in the delay and location of swim triggered visual feedback showed that the reaction time of secondary and later swims is shorter for stimuli that appear within a narrow spatio-temporal window following a swim. This suggests that the larva may generate an expectation of stimulus position, which enables accelerated motor sequencing if the expectation is met by appropriate visual feedback.

Quantitative and qualitative characterization of zigzag spatiotemporal chaos in a system of amplitude equations for nematic electroconvection.

PubMed

Oprea, Iuliana; Triandaf, Ioana; Dangelmayr, Gerhard; Schwartz, Ira B

2007-06-01

It has been suggested by experimentalists that a weakly nonlinear analysis of the recently introduced equations of motion for the nematic electroconvection by M. Treiber and L. Kramer [Phys. Rev. E 58, 1973 (1998)] has the potential to reproduce the dynamics of the zigzag-type extended spatiotemporal chaos and localized solutions observed near onset in experiments [M. Dennin, D. S. Cannell, and G. Ahlers, Phys. Rev. E 57, 638 (1998); J. T. Gleeson (private communication)]. In this paper, we study a complex spatiotemporal pattern, identified as spatiotemporal chaos, that bifurcates at the onset from a spatially uniform solution of a system of globally coupled complex Ginzburg-Landau equations governing the weakly nonlinear evolution of four traveling wave envelopes. The Ginzburg-Landau system can be derived directly from the weak electrolyte model for electroconvection in nematic liquid crystals when the primary instability is a Hopf bifurcation to oblique traveling rolls. The chaotic nature of the pattern and the resemblance to the observed experimental spatiotemporal chaos in the electroconvection of nematic liquid crystals are confirmed through a combination of techniques including the Karhunen-Loeve decomposition, time-series analysis of the amplitudes of the dominant modes, statistical descriptions, and normal form theory, showing good agreement between theory and experiments.

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago

PubMed Central

Zhou, Xiaolu

2015-01-01

The growing number of bike sharing systems (BSS) in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities. PMID:26445357

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago.

PubMed

Zhou, Xiaolu

2015-01-01

The growing number of bike sharing systems (BSS) in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.

An immunohistochemical study of APG-2 protein in the rat hippocampus after transient forebrain ischemia.

PubMed

Lee, Mun-Yong; Choi, Yun-Sik; Choi, Jeong-Sun; Min, Do Sik; Chun, Myung-Hoon; Kim, Ok Nyu; Lee, Sang Bok; Kim, Seong Yun

2002-01-11

The cellular localization and spatiotemporal expression pattern of APG-2 protein, a member of the heat shock protein 110 family, were investigated in the rat hippocampus after transient forebrain ischemia. The spatiotemporal patterns of immunoreactivity of both APG-2 and glial fibrillary acidic protein were very similar, indicating that reactive astrocytes express APG-2, which was confirmed by double immunofluorescence histochemistry. Colocalization of APG-2 and a neuronal marker NeuN in the neurons of the CA2 and CA3 subfields was also confirmed.

Mining spatiotemporal patterns of urban dwellers from taxi trajectory data

NASA Astrophysics Data System (ADS)

Mao, Feng; Ji, Minhe; Liu, Ting

2016-06-01

With the widespread adoption of locationaware technology, obtaining long-sequence, massive and high-accuracy spatiotemporal trajectory data of individuals has become increasingly popular in various geographic studies. Trajectory data of taxis, one of the most widely used inner-city travel modes, contain rich information about both road network traffic and travel behavior of passengers. Such data can be used to study the microscopic activity patterns of individuals as well as the macro system of urban spatial structures. This paper focuses on trajectories obtained from GPS-enabled taxis and their applications for mining urban commuting patterns. A novel approach is proposed to discover spatiotemporal patterns of household travel from the taxi trajectory dataset with a large number of point locations. The approach involves three critical steps: spatial clustering of taxi origin-destination (OD) based on urban traffic grids to discover potentially meaningful places, identifying threshold values from statistics of the OD clusters to extract urban jobs-housing structures, and visualization of analytic results to understand the spatial distribution and temporal trends of the revealed urban structures and implied household commuting behavior. A case study with a taxi trajectory dataset in Shanghai, China is presented to demonstrate and evaluate the proposed method.

Towards understanding of the spatio-temporal composition of Terrestrial Water Storage variations in Northern Latitudes using a model-data fusion approach

NASA Astrophysics Data System (ADS)

Trautmann, Tina; Koirala, Sujan; Carvalhais, Nuno; Niemann, Christoph; Fink, Manfred; Jung, Martin

2017-04-01

Understanding variations in the terrestrial water storage (TWS) and its components is essential to gain insights into the dynamics of the hydrological cycle, and to assess temporal and spatial variations of water availability under global changes. We investigated spatio-temporal patterns of TWS variations and their composition in the humid regions of northern mid-to-high latitudes during 2001-2014 by using a simple hydrological model with few effective parameters. Compared to traditional modelling studies, our simple model was informed and constrained by multiple state-of-the-art earth observation products including TWS from Gravity Recovery and Climate Experiment (GRACE) satellites (Wiese 2015), Snow Water Equivalent (SWE) from GlobSnow project (Loujous et al. 2014), evapotranspiration fluxes from eddy covariance measurements (Tramontana et al. 2016), and gridded runoff estimates for Europe (Gudmundsson & Seneviratne 2016). Thorough evaluation of model demonstrates that the model reproduces the observed patterns of hydrological fluxes and states well. The validated model results are then used to assess the contributions of snow pack, soil moisture and groundwater on the integrated TWS across spatial (local grid scale, spatially integrated) and temporal (seasonal, inter-annual) scales. Interestingly, our results show that TWS variations on different scales are dominated by different components. On both, seasonal and inter-annual time scales, the spatially integrated TWS signal mainly originates from dynamics of snow pack. On the local grid scale, mean seasonal TWS variations are driven by snow dynamics as well, whereas inter-annual variations are found to originate from soil moisture availability. Thus, we show that the determinants of TWS variations are scale-dependent, while coincidently underline the potential of model-data fusion techniques to gain insights into the complex hydrological system. References: Gudmundsson, L. and S. I. Seneviratne (2016): Observation-based gridded runoff estimates for Europe (E-RUN version 1.1). -Earth System Science Data, 8, 279-295. doi: 10.5194/essd-8-279-201. Loujous, K., Pulliainen, J., Takala, M., Lemmetyinen, J., Kangwa, M., Eskelinen, M., Metsämäki, S., Solberg, R., Salberg, A.-B., Bippus, G., Ripper, E., Nagler, T., Derksen, C., Wiesmann, A., Wunderle, S., Hüsler, F., Fontana, F., and Foppa, N., 2014: GlobSnow-2 Final Report, European Space Agency. Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Ráduly, B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L., Serrano-Ortiz, P., Sickert, S., Wolf, S., and Papale, D. (2016): Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms. -Biogeosciences, 13, 4291-4313. doi:10.5194/bg-13-4291-2016. D.N. Wiese (2015): GRACE monthly global water mass grids. NETCDF RELEASE 5.0. Ver. 5.0. PO.DAAC, CA, USA. Dataset accessed [2016-01-03] at http://dx.doi.org/10.5067/TEMSC-OCL05.

Spatio-Temporal Patterning in Primary Motor Cortex at Movement Onset.

PubMed

Best, Matthew D; Suminski, Aaron J; Takahashi, Kazutaka; Brown, Kevin A; Hatsopoulos, Nicholas G

2017-02-01

Voluntary movement initiation involves the engagement of large populations of motor cortical neurons around movement onset. Despite knowledge of the temporal dynamics that lead to movement, the spatial structure of these dynamics across the cortical surface remains unknown. In data from 4 rhesus macaques, we show that the timing of attenuation of beta frequency local field potential oscillations, a correlate of locally activated cortex, forms a spatial gradient across primary motor cortex (MI). We show that these spatio-temporal dynamics are recapitulated in the engagement order of ensembles of MI neurons. We demonstrate that these patterns are unique to movement onset and suggest that movement initiation requires a precise spatio-temporal sequential activation of neurons in MI. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Between-Site Differences in the Scale of Dispersal and Gene Flow in Red Oak

PubMed Central

Moran, Emily V.; Clark, James S.

2012-01-01

Background Nut-bearing trees, including oaks (Quercus spp.), are considered to be highly dispersal limited, leading to concerns about their ability to colonize new sites or migrate in response to climate change. However, estimating seed dispersal is challenging in species that are secondarily dispersed by animals, and differences in disperser abundance or behavior could lead to large spatio-temporal variation in dispersal ability. Parentage and dispersal analyses combining genetic and ecological data provide accurate estimates of current dispersal, while spatial genetic structure (SGS) can shed light on past patterns of dispersal and establishment. Methodology and Principal Findings In this study, we estimate seed and pollen dispersal and parentage for two mixed-species red oak populations using a hierarchical Bayesian approach. We compare these results to those of a genetic ML parentage model. We also test whether observed patterns of SGS in three size cohorts are consistent with known site history and current dispersal patterns. We find that, while pollen dispersal is extensive at both sites, the scale of seed dispersal differs substantially. Parentage results differ between models due to additional data included in Bayesian model and differing genotyping error assumptions, but both indicate between-site dispersal differences. Patterns of SGS in large adults, small adults, and seedlings are consistent with known site history (farmed vs. selectively harvested), and with long-term differences in seed dispersal. This difference is consistent with predator/disperser satiation due to higher acorn production at the low-dispersal site. While this site-to-site variation results in substantial differences in asymptotic spread rates, dispersal for both sites is substantially lower than required to track latitudinal temperature shifts. Conclusions Animal-dispersed trees can exhibit considerable spatial variation in seed dispersal, although patterns may be surprisingly constant over time. However, even under favorable conditions, migration in heavy-seeded species is likely to lag contemporary climate change. PMID:22563504

"Core Knowledges": A Dissociation between Spatiotemporal Knowledge and Contact-Mechanics in a Non-Human Primate?

ERIC Educational Resources Information Center

Santos, Laurie R.

2004-01-01

Human toddlers demonstrate striking failures when searching for hidden objects that interact with other objects, yet successfully locate hidden objects that do not undergo mechanical interactions. This pattern hints at a developmental dissociation between contact-mechanical and spatiotemporal knowledge. Recent studies suggest that adult non-human…

Mining patterns in persistent surveillance systems with smart query and visual analytics

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.; Shirkhodaie, Amir

2013-05-01

In Persistent Surveillance Systems (PSS) the ability to detect and characterize events geospatially help take pre-emptive steps to counter adversary's actions. Interactive Visual Analytic (VA) model offers this platform for pattern investigation and reasoning to comprehend and/or predict such occurrences. The need for identifying and offsetting these threats requires collecting information from diverse sources, which brings with it increasingly abstract data. These abstract semantic data have a degree of inherent uncertainty and imprecision, and require a method for their filtration before being processed further. In this paper, we have introduced an approach based on Vector Space Modeling (VSM) technique for classification of spatiotemporal sequential patterns of group activities. The feature vectors consist of an array of attributes extracted from generated sensors semantic annotated messages. To facilitate proper similarity matching and detection of time-varying spatiotemporal patterns, a Temporal-Dynamic Time Warping (DTW) method with Gaussian Mixture Model (GMM) for Expectation Maximization (EM) is introduced. DTW is intended for detection of event patterns from neighborhood-proximity semantic frames derived from established ontology. GMM with EM, on the other hand, is employed as a Bayesian probabilistic model to estimated probability of events associated with a detected spatiotemporal pattern. In this paper, we present a new visual analytic tool for testing and evaluation group activities detected under this control scheme. Experimental results demonstrate the effectiveness of proposed approach for discovery and matching of subsequences within sequentially generated patterns space of our experiments.

Urban air quality, meteorology and traffic linkages: Evidence from a sixteen-day particulate matter pollution event in December 2015, Beijing.

PubMed

Hu, Dongmei; Wu, Jianping; Tian, Kun; Liao, Lyuchao; Xu, Ming; Du, Yiman

2017-09-01

A heavy 16-day pollution episode occurred in Beijing from December 19, 2015 to January 3, 2016. The mean daily AQI and PM 2.5 were 240.44 and 203.6μg/m 3 . We analyzed the spatiotemporal characteristics of air pollutants, meteorology and road space speed during this period, then extended to reveal the combined effects of traffic restrictions and meteorology on urban air quality with observational data and a multivariate mutual information model. Results of spatiotemporal analysis showed that five pollution stages were identified with remarkable variation patterns based on evolution of PM 2.5 concentration and weather conditions. Southern sites (DX, YDM and DS) experienced heavier pollution than northern ones (DL, CP and WL). Stage P2 exhibited combined functions of meteorology and traffic restrictions which were delayed peak-clipping effects on PM 2.5 . Mutual information values of Air quality-Traffic-Meteorology (ATM-MI) revealed that additive functions of traffic restrictions, suitable relative humidity and temperature were more effective on the removal of fine particles and CO than NO 2 . Copyright © 2017. Published by Elsevier B.V.

Spatio-temporal patterns of genetic variations in populations of yellowtail kingfish Seriola lalandi from the south-eastern Pacific Ocean and potential implications for its fishery management.

PubMed

Sepúlveda, F A; González, M T

2017-01-01

The genetic population structure and genetic diversity of yellowtail kingfish Seriola lalandi from the coastal south-eastern Pacific Ocean (SEP) were evaluated at spatiotemporal scale in order to understand the ecology of this species. Between 2012 and 2015, temporal and spatial population genetic structure and a low genetic diversity were detected in S. lalandi from SEP. These results suggest that S. lalandi specimens arriving annually from offshore to the SEP coast could come from at least two genetically distinct populations, revealing a particular life strategy (i.e. reproductive or habitat segregation) for this fish species. Therefore, the SEP coast might constitute a point of population mixing for this species. Additionally, the low genetic diversity of S. lalandi in the SEP could be a result of a founder effect or overfishing. Regardless of the process explaining the genetic diversity and structure of S. lalandi in this geographical area, this new information should be considered in order to implement successful fishery management of this resource in the South Pacific. © 2016 The Fisheries Society of the British Isles.

Spatio-temporal pattern analysis for evaluation of the spread of human infections with avian influenza A(H7N9) virus in China, 2013-2014.

PubMed

Dong, Wen; Yang, Kun; Xu, Quanli; Liu, Lin; Chen, Juan

2017-10-24

A large number (n = 460) of A(H7N9) human infections have been reported in China from March 2013 through December 2014, and H7N9 outbreaks in humans became an emerging issue for China health, which have caused numerous disease outbreaks in domestic poultry and wild bird populations, and threatened human health severely. The aims of this study were to investigate the directional trend of the epidemic and to identify the significant presence of spatial-temporal clustering of influenza A(H7N9) human cases between March 2013 and December 2014. Three distinct epidemic phases of A(H7N9) human infections were identified in this study. In each phase, standard deviational ellipse analysis was conducted to examine the directional trend of disease spreading, and retrospective space-time permutation scan statistic was then used to identify the spatio-temporal cluster patterns of H7N9 outbreaks in humans. The ever-changing location and the increasing size of the three identified standard deviational ellipses showed that the epidemic moved from east to southeast coast, and hence to some central regions, with a future epidemiological trend of continue dispersing to more central regions of China, and a few new human cases might also appear in parts of the western China. Furthermore, A(H7N9) human infections were clustering in space and time in the first two phases with five significant spatio-temporal clusters (p < 0.05), but there was no significant cluster identified in phase III. There was a new epidemiologic pattern that the decrease in significant spatio-temporal cluster of A(H7N9) human infections was accompanied with an obvious spatial expansion of the outbreaks during the study period, and identification of the spatio-temporal patterns of the epidemic can provide valuable insights for better understanding the spreading dynamics of the disease in China.

Annotating spatio-temporal datasets for meaningful analysis in the Web

NASA Astrophysics Data System (ADS)

Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

2014-05-01

More and more environmental datasets that vary in space and time are available in the Web. This comes along with an advantage of using the data for other purposes than originally foreseen, but also with the danger that users may apply inappropriate analysis procedures due to lack of important assumptions made during the data collection process. In order to guide towards a meaningful (statistical) analysis of spatio-temporal datasets available in the Web, we have developed a Higher-Order-Logic formalism that captures some relevant assumptions in our previous work [1]. It allows to proof on meaningful spatial prediction and aggregation in a semi-automated fashion. In this poster presentation, we will present a concept for annotating spatio-temporal datasets available in the Web with concepts defined in our formalism. Therefore, we have defined a subset of the formalism as a Web Ontology Language (OWL) pattern. It allows capturing the distinction between the different spatio-temporal variable types, i.e. point patterns, fields, lattices and trajectories, that in turn determine whether a particular dataset can be interpolated or aggregated in a meaningful way using a certain procedure. The actual annotations that link spatio-temporal datasets with the concepts in the ontology pattern are provided as Linked Data. In order to allow data producers to add the annotations to their datasets, we have implemented a Web portal that uses a triple store at the backend to store the annotations and to make them available in the Linked Data cloud. Furthermore, we have implemented functions in the statistical environment R to retrieve the RDF annotations and, based on these annotations, to support a stronger typing of spatio-temporal datatypes guiding towards a meaningful analysis in R. [1] Stasch, C., Scheider, S., Pebesma, E., Kuhn, W. (2014): "Meaningful spatial prediction and aggregation", Environmental Modelling & Software, 51, 149-165.

Identifying food deserts and swamps based on relative healthy food access: a spatio-temporal Bayesian approach.

PubMed

Luan, Hui; Law, Jane; Quick, Matthew

2015-12-30

Obesity and other adverse health outcomes are influenced by individual- and neighbourhood-scale risk factors, including the food environment. At the small-area scale, past research has analysed spatial patterns of food environments for one time period, overlooking how food environments change over time. Further, past research has infrequently analysed relative healthy food access (RHFA), a measure that is more representative of food purchasing and consumption behaviours than absolute outlet density. This research applies a Bayesian hierarchical model to analyse the spatio-temporal patterns of RHFA in the Region of Waterloo, Canada, from 2011 to 2014 at the small-area level. RHFA is calculated as the proportion of healthy food outlets (healthy outlets/healthy + unhealthy outlets) within 4-km from each small-area. This model measures spatial autocorrelation of RHFA, temporal trend of RHFA for the study region, and spatio-temporal trends of RHFA for small-areas. For the study region, a significant decreasing trend in RHFA is observed (-0.024), suggesting that food swamps have become more prevalent during the study period. For small-areas, significant decreasing temporal trends in RHFA were observed for all small-areas. Specific small-areas located in south Waterloo, north Kitchener, and southeast Cambridge exhibited the steepest decreasing spatio-temporal trends and are classified as spatio-temporal food swamps. This research demonstrates a Bayesian spatio-temporal modelling approach to analyse RHFA at the small-area scale. Results suggest that food swamps are more prevalent than food deserts in the Region of Waterloo. Analysing spatio-temporal trends of RHFA improves understanding of local food environment, highlighting specific small-areas where policies should be targeted to increase RHFA and reduce risk factors of adverse health outcomes such as obesity.

[Spatiotemporal variation of typical red soil eroded landscape pattern: a case study in Changting County of Fujian Province].

PubMed

Wu, Guo-sheng; Lin, Hui-hua; Zhu, He-jian; Sha, Jin-ming; Dai, Wen-yuan

2011-07-01

Based on the 1988, 2000, and 2007 remote sensing images of a typical red soil eroded region (Changting County, Fujian Province) and the digital elevation model (DEM), the eroded landscape types were worked out, and the changes of the eroded landscape pattern in the region from 1988 to 2007 were analyzed with the spatial mathematics model. In 1988-2007, different eroded landscape types in the region had the characteristics of inter-transfer, mainly manifested in the transfer from seriously eroded to lightly eroded types but still existed small amount of the transference from lightly eroded to seriously eroded types. Little change was observed in the controid of the eroded landscape. In the County, Hetian Town was all along the eroded center. During the study period, the landscape pattern index showed a tendency of low heterogeneity, low fragmentation, and high regularization at landscape level, but an overall improvement and expansion of lightly eroded and easy-to-tackle patches as well as the partial improvement and fragmentation of seriously eroded and difficult-to-tackle patches at patch level.

Spatio-temporal variability of hydro-chemical characteristics of coastal waters of Gulf of Mannar Marine Biosphere Reserve (GoMMBR), South India

NASA Astrophysics Data System (ADS)

Kathiravan, K.; Natesan, Usha; Vishnunath, R.

2017-03-01

The intention of this study was to appraise the spatial and temporal variations in the physico-chemical parameters of coastal waters of Rameswaram Island, Gulf of Mannar Marine Biosphere Reserve, south India, using multivariate statistical techniques, such as cluster analysis, factor analysis and principal component analysis. Spatio-temporal variations among the physico-chemical parameters are observed in the coastal waters of Gulf of Mannar, especially during northeast and post monsoon seasons. It is inferred that the high loadings of pH, temperature, suspended particulate matter, salinity, dissolved oxygen, biochemical oxygen demand, chlorophyll a, nutrient species of nitrogen and phosphorus strongly determine the discrimination of coastal water quality. Results highlight the important role of monsoonal variations to determine the coastal water quality around Rameswaram Island.

Characterizing nonlinearity in invasive EEG recordings from temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Casdagli, M. C.; Iasemidis, L. D.; Sackellares, J. C.; Roper, S. N.; Gilmore, R. L.; Savit, R. S.

Invasive electroencephalographic (EEG) recordings from depth and subdural electrodes, performed in eight patients with temporal lobe epilepsy, are analyzed using a variety of nonlinear techniques. A surrogate data technique is used to find strong evidence for nonlinearities in epileptogenic regions of the brain. Most of these nonlinearities are characterized as “spiking” by a wavelet analysis. A small fraction of the nonlinearities are characterized as “recurrent” by a nonlinear prediction algorithm. Recurrent activity is found to occur in spatio-temporal patterns related to the location of the epileptogenic focus. Residual delay maps, used to characterize “lag-one nonlinearity”, are remarkably stationary for a given electrode, and exhibit striking variations among electrodes. The clinical and theoretical implications of these results are discussed.

Spatiotemporal variation in local adaptation of a specialist insect herbivore to its long-lived host plant.

PubMed

Kalske, Aino; Leimu, Roosa; Scheepens, J F; Mutikainen, Pia

2016-09-01

Local adaptation of interacting species to one another indicates geographically variable reciprocal selection. This process of adaptation is central in the organization and maintenance of genetic variation across populations. Given that the strength of selection and responses to it often vary in time and space, the strength of local adaptation should in theory vary between generations and among populations. However, such spatiotemporal variation has rarely been explicitly demonstrated in nature and local adaptation is commonly considered to be relatively static. We report persistent local adaptation of the short-lived herbivore Abrostola asclepiadis to its long-lived host plant Vincetoxicum hirundinaria over three successive generations in two studied populations and considerable temporal variation in local adaptation in six populations supporting the geographic mosaic theory. The observed variation in local adaptation among populations was best explained by geographic distance and population isolation, suggesting that gene flow reduces local adaptation. Changes in herbivore population size did not conclusively explain temporal variation in local adaptation. Our results also imply that short-term studies are likely to capture only a part of the existing variation in local adaptation. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Defining multiple, distinct, and shared spatiotemporal patterns of DNA replication and endoreduplication from 3D image analysis of developing maize (Zea mays L.) root tip nuclei.

PubMed

Bass, Hank W; Hoffman, Gregg G; Lee, Tae-Jin; Wear, Emily E; Joseph, Stacey R; Allen, George C; Hanley-Bowdoin, Linda; Thompson, William F

2015-11-01

Spatiotemporal patterns of DNA replication have been described for yeast and many types of cultured animal cells, frequently after cell cycle arrest to aid in synchronization. However, patterns of DNA replication in nuclei from plants or naturally developing organs remain largely uncharacterized. Here we report findings from 3D quantitative analysis of DNA replication and endoreduplication in nuclei from pulse-labeled developing maize root tips. In both early and middle S phase nuclei, flow-sorted on the basis of DNA content, replicative labeling was widely distributed across euchromatic regions of the nucleoplasm. We did not observe the perinuclear or perinucleolar replicative labeling patterns characteristic of middle S phase in mammals. Instead, the early versus middle S phase patterns in maize could be distinguished cytologically by correlating two quantitative, continuous variables, replicative labeling and DAPI staining. Early S nuclei exhibited widely distributed euchromatic labeling preferentially localized to regions with weak DAPI signals. Middle S nuclei also exhibited widely distributed euchromatic labeling, but the label was preferentially localized to regions with strong DAPI signals. Highly condensed heterochromatin, including knobs, replicated during late S phase as previously reported. Similar spatiotemporal replication patterns were observed for both mitotic and endocycling maize nuclei. These results revealed that maize euchromatin exists as an intermingled mixture of two components distinguished by their condensation state and replication timing. These different patterns might reflect a previously described genome organization pattern, with "gene islands" mostly replicating during early S phase followed by most of the intergenic repetitive regions replicating during middle S phase.

Spatio-temporal pattern clustering for skill assessment of the Korea Operational Oceanographic System

NASA Astrophysics Data System (ADS)

Kim, J.; Park, K.

2016-12-01

In order to evaluate the performance of operational forecast models in the Korea operational oceanographic system (KOOS) which has been developed by Korea Institute of Ocean Science and Technology (KIOST), a skill assessment (SA) tool has developed and provided multiple skill metrics including not only correlation and error skills by comparing predictions and observation but also pattern clustering with numerical models, satellite, and observation. The KOOS has produced 72 hours forecast information on atmospheric and hydrodynamic forecast variables of wind, pressure, current, tide, wave, temperature, and salinity at every 12 hours per day produced by operating numerical models such as WRF, ROMS, MOM5, WW-III, and SWAN and the SA has conducted to evaluate the forecasts. We have been operationally operated several kinds of numerical models such as WRF, ROMS, MOM5, MOHID, WW-III. Quantitative assessment of operational ocean forecast model is very important to provide accurate ocean forecast information not only to general public but also to support ocean-related problems. In this work, we propose a method of pattern clustering using machine learning method and GIS-based spatial analytics to evaluate spatial distribution of numerical models and spatial observation data such as satellite and HF radar. For the clustering, we use 10 or 15 years-long reanalysis data which was computed by the KOOS, ECMWF, and HYCOM to make best matching clusters which are classified physical meaning with time variation and then we compare it with forecast data. Moreover, for evaluating current, we develop extraction method of dominant flow and apply it to hydrodynamic models and HF radar's sea surface current data. By applying pattern clustering method, it allows more accurate and effective assessment of ocean forecast models' performance by comparing not only specific observation positions which are determined by observation stations but also spatio-temporal distribution of whole model areas. We believe that our proposed method will be very useful to examine and evaluate large amount of numerical modeling data as well as satellite data.

Bringing Together Evolution on Serpentine and Polyploidy: Spatiotemporal History of the Diploid-Tetraploid Complex of Knautia arvensis (Dipsacaceae)

PubMed Central

Kolář, Filip; Fér, Tomáš; Štech, Milan; Trávníček, Pavel; Dušková, Eva; Schönswetter, Peter; Suda, Jan

2012-01-01

Polyploidization is one of the leading forces in the evolution of land plants, providing opportunities for instant speciation and rapid gain of evolutionary novelties. Highly selective conditions of serpentine environments act as an important evolutionary trigger that can be involved in various speciation processes. Whereas the significance of both edaphic speciation on serpentine and polyploidy is widely acknowledged in plant evolution, the links between polyploid evolution and serpentine differentiation have not yet been examined. To fill this gap, we investigated the evolutionary history of the perennial herb Knautia arvensis (Dipsacaceae), a diploid-tetraploid complex that exhibits an intriguing pattern of eco-geographic differentiation. Using plastid DNA sequencing and AFLP genotyping of 336 previously cytotyped individuals from 40 populations from central Europe, we unravelled the patterns of genetic variation among the cytotypes and the edaphic types. Diploids showed the highest levels of genetic differentiation, likely as a result of long term persistence of several lineages in ecologically distinct refugia and/or independent immigration. Recurrent polyploidization, recorded in one serpentine island, seems to have opened new possibilities for the local serpentine genotype. Unlike diploids, the serpentine tetraploids were able to escape from the serpentine refugium and spread further; this was also attributable to hybridization with the neighbouring non-serpentine tetraploid lineages. The spatiotemporal history of K. arvensis allows tracing the interplay of polyploid evolution and ecological divergence on serpentine, resulting in a complex evolutionary pattern. Isolated serpentine outcrops can act as evolutionary capacitors, preserving distinct karyological and genetic diversity. The serpentine lineages, however, may not represent evolutionary ‘dead-ends’ but rather dynamic systems with a potential to further influence the surrounding populations, e.g., via independent polyplodization and hybridization. The complex eco-geographical pattern together with the incidence of both primary and secondary diploid-tetraploid contact zones makes K. arvensis a unique system for addressing general questions of polyploid research. PMID:22792207

Routes to spatiotemporal chaos in Kerr optical frequency combs.

PubMed

Coillet, Aurélien; Chembo, Yanne K

2014-03-01

We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato-Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

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.

Three-dimensional investigation of ozone pollution in the lower troposphere using an unmanned aerial vehicle platform.

PubMed

Li, Xiao-Bing; Wang, Dong-Sheng; Lu, Qing-Chang; Peng, Zhong-Ren; Lu, Si-Jia; Li, Bai; Li, Chao

2017-05-01

Potential utilities of instrumented lightweight unmanned aerial vehicles (UAVs) to quickly characterize tropospheric ozone pollution and meteorological factors including air temperature and relative humidity at three-dimensional scales are highlighted in this study. Both vertical and horizontal variations of ozone within the 1000 m lower troposphere at a local area of 4 × 4 km 2 are investigated during summer and autumn times. Results from field measurements show that the UAV platform has a sufficient reliability and precision in capturing spatiotemporal variations of ozone and meteorological factors. The results also reveal that ozone vertical variation is mainly linked to the vertical distribution patterns of air temperature and the horizontal transport of air masses from other regions. In addition, significant horizontal variations of ozone are also observed at different levels. Without major exhaust sources, ozone horizontal variation has a strong correlation with the vertical convection intensity of air masses within the lower troposphere. Higher air temperatures are usually related to lower ozone horizontal variations at the localized area, whereas underlying surface diversity has a week influence. Three-dimensional ozone maps are obtained using an interpolation method based on UAV collected samples, which are capable of clearly demonstrating the diurnal evolution processes of ozone within the 1000 m lower troposphere. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatiotemporal patterns of paddy rice croplands in China and India from 2000 to 2015.

PubMed

Zhang, Geli; Xiao, Xiangming; Biradar, Chandrashekhar M; Dong, Jinwei; Qin, Yuanwei; Menarguez, Michael A; Zhou, Yuting; Zhang, Yao; Jin, Cui; Wang, Jie; Doughty, Russell B; Ding, Mingjun; Moore, Berrien

2017-02-01

Due to rapid population growth and urbanization, paddy rice agriculture is experiencing substantial changes in the spatiotemporal pattern of planting areas in the two most populous countries-China and India-where food security is always the primary concern. However, there is no spatially explicit and continuous rice-planting information in either country. This knowledge gap clearly hinders our ability to understand the effects of spatial paddy rice area dynamics on the environment, such as food and water security, climate change, and zoonotic infectious disease transmission. To resolve this problem, we first generated annual maps of paddy rice planting areas for both countries from 2000 to 2015, which are derived from time series Moderate Resolution Imaging Spectroradiometer (MODIS) data and the phenology- and pixel-based rice mapping platform (RICE-MODIS), and analyzed the spatiotemporal pattern of paddy rice dynamics in the two countries. We found that China experienced a general decrease in paddy rice planting area with a rate of 0.72 million (m) ha/yr from 2000 to 2015, while a significant increase at a rate of 0.27mha/yr for the same time period happened in India. The spatial pattern of paddy rice agriculture in China shifted northeastward significantly, due to simultaneous expansions in paddy rice planting areas in northeastern China and contractions in southern China. India showed an expansion of paddy rice areas across the entire country, particularly in the northwestern region of the Indo-Gangetic Plain located in north India and the central and south plateau of India. In general, there has been a northwesterly shift in the spatial pattern of paddy rice agriculture in India. These changes in the spatiotemporal patterns of paddy rice planting area have raised new concerns on how the shift may affect national food security and environmental issues relevant to water, climate, and biodiversity. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatiotemporal changes of CVOC concentrations in karst aquifers: analysis of three decades of data from Puerto Rico

PubMed Central

Yu, Xue; Ghasemizadeh, Reza; Padilla, Ingrid; Irizarry, Celys; Kaeli, David; Alshawabkeh, Akram

2014-01-01

We studied the spatial and temporal distribution patterns of Chlorinated Volatile Organic Compounds (CVOCs) in the karst aquifers in northern Puerto Rico (1982-2013). Seventeen CVOCs were widely detected across the study area, with the most detected and persistent contaminated CVOCs including trichloroethylene (TCE), tetrachloroethylene (PCE), carbon tetrachloride (CT), chloroform (TCM), and methylene chloride (DCM). Historically, 471 (76%) and 319 (52%) of the 615 sampling sites have CVOC concentrations above the detection limit and maximum contamination level (MCL), respectively. The spatiotemporal patterns of the CVOC concentrations showed two clusters of contaminated areas, one near the Superfund site “Upjohn” and another near “Vega Alta Public Supply Wells.” Despite a decreasing trend in concentrations, there is a general northward movement and spreading of contaminants even beyond the extent of known sources of the Superfund and landfill sites. Our analyses suggest that, besides the source conditions, karst characteristics (high heterogeneity, complex hydraulic and biochemical environment) are linked to the long-term spatiotemporal patterns of CVOCs in groundwater. PMID:25522355

Geovisualization of Local and Regional Migration Using Web-mined Demographics

NASA Astrophysics Data System (ADS)

Schuermann, R. T.; Chow, T. E.

2014-11-01

The intent of this research was to augment and facilitate analyses, which gauges the feasibility of web-mined demographics to study spatio-temporal dynamics of migration. As a case study, we explored the spatio-temporal dynamics of Vietnamese Americans (VA) in Texas through geovisualization of mined demographic microdata from the World Wide Web. Based on string matching across all demographic attributes, including full name, address, date of birth, age and phone number, multiple records of the same entity (i.e. person) over time were resolved and reconciled into a database. Migration trajectories were geovisualized through animated sprites by connecting the different addresses associated with the same person and segmenting the trajectory into small fragments. Intra-metropolitan migration patterns appeared at the local scale within many metropolitan areas. At the scale of metropolitan area, varying degrees of immigration and emigration manifest different types of migration clusters. This paper presents a methodology incorporating GIS methods and cartographic design to produce geovisualization animation, enabling the cognitive identification of migration patterns at multiple scales. Identification of spatio-temporal patterns often stimulates further research to better understand the phenomenon and enhance subsequent modeling.

Spatio-Temporal Pattern Analysis for Regional Climate Change Using Mathematical Morphology

NASA Astrophysics Data System (ADS)

Das, M.; Ghosh, S. K.

2015-07-01

Of late, significant changes in climate with their grave consequences have posed great challenges on humankind. Thus, the detection and assessment of climatic changes on a regional scale is gaining importance, since it helps to adopt adequate mitigation and adaptation measures. In this paper, we have presented a novel approach for detecting spatio-temporal pattern of regional climate change by exploiting the theory of mathematical morphology. At first, the various climatic zones in the region have been identified by using multifractal cross-correlation analysis (MF-DXA) of different climate variables of interest. Then, the directional granulometry with four different structuring elements has been studied to detect the temporal changes in spatial distribution of the identified climatic zones in the region and further insights have been drawn with respect to morphological uncertainty index and Hurst exponent. The approach has been evaluated with the daily time series data of land surface temperature (LST) and precipitation rate, collected from Microsoft Research - Fetch Climate Explorer, to analyze the spatio-temporal climatic pattern-change in the Eastern and North-Eastern regions of India throughout four quarters of the 20th century.

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Upper-hybrid wave-driven Alfvenic turbulence in magnetized dusty plasmas

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

Misra, A. P.; Banerjee, S.

The nonlinear dynamics of coupled electrostatic upper-hybrid (UH) and Alfven waves (AWs) is revisited in a magnetized electron-ion plasma with charged dust impurities. A pair of nonlinear equations that describe the interaction of UH wave envelopes (including the relativistic electron mass increase) and the density as well as the compressional magnetic field perturbations associated with the AWs are solved numerically to show that many coherent solitary patterns can be excited and saturated due to modulational instability of unstable UH waves. The evolution of these solitary patterns is also shown to appear in the states of spatiotemporal coherence, temporal as wellmore » as spatiotemporal chaos, due to collision and fusion among the patterns in stochastic motion. Furthermore, these spatiotemporal features are demonstrated by the analysis of wavelet power spectra. It is found that a redistribution of wave energy takes place to higher harmonic modes with small wavelengths, which, in turn, results in the onset of Alfvenic turbulence in dusty magnetoplasmas. Such a scenario can occur in the vicinity of Saturn's magnetosphere as many electrostatic solitary structures have been observed there by the Cassini spacecraft.« less

Spatio-temporal cluster detection of chickenpox in Valencia, Spain in the period 2008-2012.

PubMed

Iftimi, Adina; Martínez-Ruiz, Francisco; Míguez Santiyán, Ana; Montes, Francisco

2015-05-18

Chickenpox is a highly contagious airborne disease caused by Varicella zoster, which affects nearly all non-immune children worldwide with an annual incidence estimated at 80-90 million cases. To analyze the spatiotemporal pattern of the chickenpox incidence in the city of Valencia, Spain two complementary statistical approaches were used. First, we evaluated the existence of clusters and spatio-temporal interaction; secondly, we used this information to find the locations of the spatio-temporal clusters via the space-time permutation model. The first method used detects any aggregation in our data but does not provide the spatial and temporal information. The second method gives the locations, areas and time-frame for the spatio-temporal clusters. An overall decreasing time trend, a pronounced 12-monthly periodicity and two complementary periods were observed. Several areas with high incidence, surrounding the center of the city were identified. The existence of aggregation in time and space was observed, and a number of spatio-temporal clusters were located.

Comparison of Spatiotemporal Mapping Techniques for Enormous Etl and Exploitation Patterns

NASA Astrophysics Data System (ADS)

Deiotte, R.; La Valley, R.

2017-10-01

The need to extract, transform, and exploit enormous volumes of spatiotemporal data has exploded with the rise of social media, advanced military sensors, wearables, automotive tracking, etc. However, current methods of spatiotemporal encoding and exploitation simultaneously limit the use of that information and increase computing complexity. Current spatiotemporal encoding methods from Niemeyer and Usher rely on a Z-order space filling curve, a relative of Peano's 1890 space filling curve, for spatial hashing and interleaving temporal hashes to generate a spatiotemporal encoding. However, there exist other space-filling curves, and that provide different manifold coverings that could promote better hashing techniques for spatial data and have the potential to map spatiotemporal data without interleaving. The concatenation of Niemeyer's and Usher's techniques provide a highly efficient space-time index. However, other methods have advantages and disadvantages regarding computational cost, efficiency, and utility. This paper explores the several methods using a range of sizes of data sets from 1K to 10M observations and provides a comparison of the methods.

Spatiotemporal Heterogeneity Analysis of Hemorrhagic Fever with Renal Syndrome in China Using Geographically Weighted Regression Models

PubMed Central

Li, Shujuan; Ren, Hongyan; Hu, Wensheng; Lu, Liang; Xu, Xinliang; Zhuang, Dafang; Liu, Qiyong

2014-01-01

Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in China. The identification of the spatiotemporal pattern of HFRS will provide a foundation for the effective control of the disease. Based on the incidence of HFRS, as well as environmental factors, and social-economic factors of China from 2005–2012, this paper identified the spatiotemporal characteristics of HFRS distribution and the factors that impact this distribution. The results indicate that the spatial distribution of HFRS had a significant, positive spatial correlation. The spatiotemporal heterogeneity was affected by the temperature, precipitation, humidity, NDVI of January, NDVI of August for the previous year, land use, and elevation in 2005–2009. However, these factors did not explain the spatiotemporal heterogeneity of HFRS incidences in 2010–2012. Spatiotemporal heterogeneity of provincial HFRS incidences and its relation to environmental factors would provide valuable information for hygiene authorities to design and implement effective measures for the prevention and control of HFRS in China. PMID:25429681

Geographical gradients in selection can reveal genetic constraints for evolutionary responses to ocean acidification

PubMed Central

Gaitán-Espitia, Juan Diego; Marshall, Dustin; Dupont, Sam; Bacigalupe, Leonardo D.; Bodrossy, Levente; Hobday, Alistair J.

2017-01-01

Geographical gradients in selection can shape different genetic architectures in natural populations, reflecting potential genetic constraints for adaptive evolution under climate change. Investigation of natural pH/pCO2 variation in upwelling regions reveals different spatio-temporal patterns of natural selection, generating genetic and phenotypic clines in populations, and potentially leading to local adaptation, relevant to understanding effects of ocean acidification (OA). Strong directional selection, associated with intense and continuous upwellings, may have depleted genetic variation in populations within these upwelling regions, favouring increased tolerances to low pH but with an associated cost in other traits. In contrast, diversifying or weak directional selection in populations with seasonal upwellings or outside major upwelling regions may have resulted in higher genetic variances and the lack of genetic correlations among traits. Testing this hypothesis in geographical regions with similar environmental conditions to those predicted under climate change will build insights into how selection may act in the future and how populations may respond to stressors such as OA. PMID:28148831

Spatiotemporal Aeration and Lung Injury Patterns Are Influenced by the First Inflation Strategy at Birth.

PubMed

Tingay, David G; Rajapaksa, Anushi; Zonneveld, C Elroy; Black, Don; Perkins, Elizabeth J; Adler, Andy; Grychtol, Bartłomiej; Lavizzari, Anna; Frerichs, Inéz; Zahra, Valerie A; Davis, Peter G

2016-02-01

Ineffective aeration during the first inflations at birth creates regional aeration and ventilation defects, initiating injurious pathways. This study aimed to compare a sustained first inflation at birth or dynamic end-expiratory supported recruitment during tidal inflations against ventilation without intentional recruitment on gas exchange, lung mechanics, spatiotemporal regional aeration and tidal ventilation, and regional lung injury in preterm lambs. Lambs (127 ± 2 d gestation), instrumented at birth, were ventilated for 60 minutes from birth with either lung-protective positive pressure ventilation (control) or as per control after either an initial 30 seconds of 40 cm H2O sustained inflation (SI) or an initial stepwise end-expiratory pressure recruitment maneuver during tidal inflations (duration 180 s; open lung ventilation [OLV]). At study completion, molecular markers of lung injury were analyzed. The initial use of an OLV maneuver, but not SI, at birth resulted in improved lung compliance, oxygenation, end-expiratory lung volume, and reduced ventilatory needs compared with control, persisting throughout the study. These changes were due to more uniform inter- and intrasubject gravity-dependent spatiotemporal patterns of aeration (measured using electrical impedance tomography). Spatial distribution of tidal ventilation was more stable after either recruitment maneuver. All strategies caused regional lung injury patterns that mirrored associated regional volume states. Irrespective of strategy, spatiotemporal volume loss was consistently associated with up-regulation of early growth response-1 expression. Our results show that mechanical and molecular consequences of lung aeration at birth are not simply related to rapidity of fluid clearance; they are also related to spatiotemporal pressure-volume interactions within the lung during inflation and deflation.

Use of Numerical Groundwater Model and Analytical Empirical Orthogonal Function for Calibrating Spatiotemporal pattern of Pumpage, Recharge and Parameter

NASA Astrophysics Data System (ADS)

Huang, C. L.; Hsu, N. S.; Hsu, F. C.; Liu, H. J.

2016-12-01

This study develops a novel methodology for the spatiotemporal groundwater calibration of mega-quantitative recharge and parameters by coupling a specialized numerical model and analytical empirical orthogonal function (EOF). The actual spatiotemporal patterns of groundwater pumpage are estimated by an originally developed back propagation neural network-based response matrix with the electrical consumption analysis. The spatiotemporal patterns of the recharge from surface water and hydrogeological parameters (i.e. horizontal hydraulic conductivity and vertical leakance) are calibrated by EOF with the simulated error hydrograph of groundwater storage, in order to qualify the multiple error sources and quantify the revised volume. The objective function of the optimization model is minimizing the root mean square error of the simulated storage error percentage across multiple aquifers, meanwhile subject to mass balance of groundwater budget and the governing equation in transient state. The established method was applied on the groundwater system of Chou-Shui River Alluvial Fan. The simulated period is from January 2012 to December 2014. The total numbers of hydraulic conductivity, vertical leakance and recharge from surface water among four aquifers are 126, 96 and 1080, respectively. Results showed that the RMSE during the calibration process was decreased dramatically and can quickly converse within 6th iteration, because of efficient filtration of the transmission induced by the estimated error and recharge across the boundary. Moreover, the average simulated error percentage according to groundwater level corresponding to the calibrated budget variables and parameters of aquifer one is as small as 0.11%. It represent that the developed methodology not only can effectively detect the flow tendency and error source in all aquifers to achieve accurately spatiotemporal calibration, but also can capture the peak and fluctuation of groundwater level in shallow aquifer.

Variation in predator foraging behavior changes predator-prey spatio-temporal dynamics

USDA-ARS?s Scientific Manuscript database

1. Foraging underlies the ability of all animals to acquire essential resources and, thus, provides a critical link to understanding population dynamics. A key issue is how variation in foraging behavior affects foraging efficiency and predator-prey interactions in spatially-heterogeneous environmen...

Probing the Spatio-Temporal Characteristics of Temporal Aliasing Errors and their Impact on Satellite Gravity Retrievals

NASA Astrophysics Data System (ADS)

Wiese, D. N.; McCullough, C. M.

2017-12-01

Studies have shown that both single pair low-low satellite-to-satellite tracking (LL-SST) and dual-pair LL-SST hypothetical future satellite gravimetry missions utilizing improved onboard measurement systems relative to the Gravity Recovery and Climate Experiment (GRACE) will be limited by temporal aliasing errors; that is, the error introduced through deficiencies in models of high frequency mass variations required for the data processing. Here, we probe the spatio-temporal characteristics of temporal aliasing errors to understand their impact on satellite gravity retrievals using high fidelity numerical simulations. We find that while aliasing errors are dominant at long wavelengths and multi-day timescales, improving knowledge of high frequency mass variations at these resolutions translates into only modest improvements (i.e. spatial resolution/accuracy) in the ability to measure temporal gravity variations at monthly timescales. This result highlights the reliance on accurate models of high frequency mass variations for gravity processing, and the difficult nature of reducing temporal aliasing errors and their impact on satellite gravity retrievals.

Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

PubMed Central

Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

2014-01-01

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

Mining Spatiotemporal Patterns of the Elder's Daily Movement

NASA Astrophysics Data System (ADS)

Chen, C. R.; Chen, C. F.; Liu, M. E.; Tsai, S. J.; Son, N. T.; Kinh, L. V.

2016-06-01

With rapid developments in wearable device technology, a vast amount of spatiotemporal data, such as people's movement and physical activities, are generated. Information derived from the data reveals important knowledge that can contribute a long-term care and psychological assessment of the elders' living condition especially in long-term care institutions. This study aims to develop a method to investigate the spatial-temporal movement patterns of the elders with their outdoor trajectory information. To achieve the goal, GPS based location data of the elderly subjects from long-term care institutions are collected and analysed with geographic information system (GIS). A GIS statistical model is developed to mine the elderly subjects' spatiotemporal patterns with the location data and represent their daily movement pattern at particular time. The proposed method first finds the meaningful trajectory and extracts the frequent patterns from the time-stamp location data. Then, a density-based clustering method is used to identify the major moving range and the gather/stay hotspot in both spatial and temporal dimensions. The preliminary results indicate that the major moving area of the elderly people encompasses their dorm and has a short moving distance who often stay in the same site. Subjects' outdoor appearance are corresponded to their life routine. The results can be useful for understanding elders' social network construction, risky area identification and medical care monitoring.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Modelling coastal processes by means of innovative integration of remote sensing and modelling analysis

NASA Astrophysics Data System (ADS)

Taramelli, A.; Zanuttigh, B.; Zucca, F.; Dejana, M.; Valentini, E.

2011-12-01

Coastal marine and inland landforms are dynamic systems undergoing adjustments in form at different time and space scales in response to varying conditions external to the system. Coastal emerged and shallow submerged nearshore areas, affected by short-term perturbations, return to their pre-disturbance morphology and generally reach a dynamic equilibrium. Worldwide in the last century we have experienced in increased coastal inundation, erosion and ecosystem losses. However, erosion can result from a number of other factors, such as altered wind and current patterns, high-energy waves, and reduced fluvial sediment inputs. Direct impacts of human activities, including reclamation of coastal wetlands, deforestation, damming, channelization, diversions of coastal waterways, construction of seawalls and other structures, alter circulation patterns. Also indirect human impacts such as land-uses changes through time (eg. from agricultural to industrial use) have affected coastal ecosystems. The objective of this research is to propose innovative remote sensing applications to monitor specific coastal processes in order to use them within a physical modelling to quantify and model their time evolution. The research was applied in two dynamic and densely populated deltas and coastal areas (the Po and the Plymouth delta) by combining multi-sensor spaceborne remote sensing (SAR and OPTICAL) to physical modelling. The main results are: a) deformation and spatiotemporal variations maps in coastal morphology with a special focus to point out the temporal subsidence evolution, b) inter and intra-annual change detection maps that are both used a to feed a coastal physical modelling (MIKE 21). The basic strategy was to highlight the different components of the coastal system environment through: 1) deformation and spatio-temporal variations maps of coastal morphology, by the use of time-stack from 1992 up today of ESA SAR data (ERS-1/2 and ENVISAT-ASAR sensors) were used to produce deformation maps and to point out the temporal evolution and 2) multitemporal hyperspectral endmembers fractions map of coastal morphology, 3) numerical model well-established through remote sensed based procedures and results in order to produce spatio-temporal scenario in coastal areas. The objective was to locate and characterize important coastal indicators for different regions using multitemporal data from the multi-hyperspectral sensors, as well as topographic elevation, SAR and derived products (eg. coherence) data. The identification of different indicators was based on land spectral properties, topography/landforms (low topography), disturbed areas (agricultural, construction), and vegetation distribution. Moreover, the indicators were assessed at seasonal and interannual time scales over two temporal decades horizons starting from 1990 and 2000.

Contrasting evolution patterns between glacier-fed and non-glacier-fed lakes in the central Tibetan Plateau and driving force analysis

NASA Astrophysics Data System (ADS)

Song, C.; Sheng, Y.

2015-12-01

High-altitude lakes in the Tibetan Plateau (TP) showed strong spatio-temporal variability during past decades. The lake dynamics can be associated with several key factors including lake type, supply of glacial meltwater, local climate variations. It is important to differentiate these factors when analyzing the driving force of lakes dynamics. With a focus on lakes over the Tanggula Mountains of the central TP, this study investigates the temporal evolution patterns of lake area and water level of different types: glacier-fed closed lake, non-glacier-fed closed lake and upstream lake (draining into closed lakes). We collected all available Landsat archive data and quantified the inter-annual variability of lake extents. Results show accelerated expansions of both glacier-fed and non-glacier-fed lakes during 1970s-2013, and different temporal patterns of the two types of lakes: the non-glacier-fed lakes displayed a batch-wise growth pattern, with obvious growth in 2002, 2005 and 2011 and slight changes in other years, while glacier-fed lakes showed steady expanding tendency. The contrasting patterns are confirmed by the distinction of lake level change between the two groups derived from satellite altimetry during 2003-2009. The upstream lakes remained largely stable due to natural drainage regulation. The intermittent expansions for non-glacier-fed lakes were found to be related to excessive precipitation events and positive "precipitation-evaporation". In contrast, glacier-fed lake changes showed weak correlations with precipitation variations, which imply a joint contribution from glacial meltwater to water budgets. A simple estimation reveals that the increased water storage for all of examined lakes contributed from precipitation/evaporation (0.31±0.09 Gt/yr) slightly overweighed the glacial meltwater supply (0.26±0.08 Gt/yr).

Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

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

Marre, O.; El Boustani, S.; Fregnac, Y.

We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogatesmore » that reproduce the spatial and temporal correlations of a given data set.« less

Geometric Morphometrics on Gene Expression Patterns Within Phenotypes: A Case Example on Limb Development

PubMed Central

Martínez-Abadías, Neus; Mateu, Roger; Niksic, Martina; Russo, Lucia; Sharpe, James

2016-01-01

How the genotype translates into the phenotype through development is critical to fully understand the evolution of phenotypes. We propose a novel approach to directly assess how changes in gene expression patterns are associated with changes in morphology using the limb as a case example. Our method combines molecular biology techniques, such as whole-mount in situ hybridization, with image and shape analysis, extending the use of Geometric Morphometrics to the analysis of nonanatomical shapes, such as gene expression domains. Elliptical Fourier and Procrustes-based semilandmark analyses were used to analyze the variation and covariation patterns of the limb bud shape with the expression patterns of two relevant genes for limb morphogenesis, Hoxa11 and Hoxa13. We devised a multiple thresholding method to semiautomatically segment gene domains at several expression levels in large samples of limb buds from C57Bl6 mouse embryos between 10 and 12 postfertilization days. Besides providing an accurate phenotyping tool to quantify the spatiotemporal dynamics of gene expression patterns within developing structures, our morphometric analyses revealed high, non-random, and gene-specific variation undergoing canalization during limb development. Our results demonstrate that Hoxa11 and Hoxa13, despite being paralogs with analogous functions in limb patterning, show clearly distinct dynamic patterns, both in shape and size, and are associated differently with the limb bud shape. The correspondence between our results and already well-established molecular processes underlying limb development confirms that this morphometric approach is a powerful tool to extract features of development regulating morphogenesis. Such multilevel analyses are promising in systems where not so much molecular information is available and will advance our understanding of the genotype–phenotype map. In systematics, this knowledge will increase our ability to infer how evolution modified a common developmental pattern to generate a wide diversity of morphologies, as in the vertebrate limb. PMID:26377442

Detection of contaminated pixels based on the short-term continuity of NDVI and correction using spatio-temporal continuity

NASA Astrophysics Data System (ADS)

Cho, A.-Ra; Suh, Myoung-Seok

2013-08-01

The present study developed and assessed a correction technique (CSaTC: Correction based on Spatial and Temporal Continuity) for the detection and correction of contaminated Normalized Difference Vegetation Index (NDVI) time series data. Global Inventory Modeling and Mapping Studies (GIMMS) NDVI data from 1982 to 2006 with a 15-day period and an 8-km spatial resolution was used. CSaTC utilizes short-term continuity of vegetation to detect contaminated pixels, and then, corrects the detected pixels using the spatio-temporal continuity of vegetation. CSaTC was applied to the NDVI data over the East Asian region, which exhibits diverse seasonal and interannual variations in vegetation activities. The correction skill of CSaTC was compared to two previously applied methods, IDR (iterative Interpolation for Data Reconstruction) and Park et al. (2011) using GIMMS NDVI data. CSaTC reasonably resolved the overcorrection and spreading phenomenon caused by excessive correction of Park et al. (2011). The validation using the simulated NDVI time series data showed that CSaTC shows a systematically better correction skill in bias and RMSE irrespective of phenology types of vegetation and noise levels. In general, CSaTC showed a good recovery of the contaminated data appearing over the short-term period on a level similar to that obtained using the IDR technique. In addition, it captured the multi-peak of NDVI, and the germination and defoliating patterns more accurately than that by IDR, which overly compensates for seasons with a high temporal variation and where NDVI data exhibit multi-peaks.

Spatio-temporal changes in precipitation over Beijing-Tianjin-Hebei region, China

NASA Astrophysics Data System (ADS)

Zhao, Na; Yue, Tianxiang; Li, Han; Zhang, Lili; Yin, Xiaozhe; Liu, Yi

2018-04-01

Changes in precipitation have a large effect on human society and are of primary importance for many scientific fields such as hydrology, agriculture and eco-environmental sciences. The present study intended to investigate the spatio-temporal characteristics of precipitation in Beijing-Tianjin-Hebei (BTH) region by using 316 meteorological stations during the period 1965-2014. Geographical Weighted Regression (GWR) method and High Accuracy Surface Modeling (HASM) method were applied to produce the precipitation patterns at different time scales. Mann-Kendall (MK) statistical test was applied to analyze the precipitation temporal variations. Results indicated that annual precipitation over the past 50 years appeared to be a non-periodic oscillation phenomenon; the number of wet years was approximately the same as that of dry years; significant positive trends were observed in spring during 1978-2014 and summer during 1996-2014; on the whole, precipitation in May, June, September, and December showed increasing trends at the 95% confidence level; and significant positive trends were also identified in July during 2000-2013 and August during 1997-2010, while slight decreasing trends were observed in February and November. Summer (June, July, and August) was the wettest season, accounting for 68.73% of annual totals in BTH. In general, northeastern BTH received the highest range of precipitation while northwestern area had the lowest. It was found that precipitation variation in this region had been closely linked to latitude, Digital Elevation Model (DEM), distance to the sea, and urbanization rate. In addition, land use played an important role in the decadal precipitation changes in BTH.

Virtual Active Touch Using Randomly Patterned Intracortical Microstimulation

PubMed Central

O’Doherty, Joseph E.; Lebedev, Mikhail A.; Li, Zheng; Nicolelis, Miguel A.L.

2012-01-01

Intracortical microstimulation (ICMS) has promise as a means for delivering somatosensory feedback in neuroprosthetic systems. Various tactile sensations could be encoded by temporal, spatial, or spatiotemporal patterns of ICMS. However, the applicability of temporal patterns of ICMS to artificial tactile sensation during active exploration is unknown, as is the minimum discriminable difference between temporally modulated ICMS patterns. We trained rhesus monkeys in an active exploration task in which they discriminated periodic pulse-trains of ICMS (200 Hz bursts at a 10 Hz secondary frequency) from pulse trains with the same average pulse rate, but distorted periodicity (200 Hz bursts at a variable instantaneous secondary frequency). The statistics of the aperiodic pulse trains were drawn from a gamma distribution with mean inter-burst intervals equal to those of the periodic pulse trains. The monkeys distinguished periodic pulse trains from aperiodic pulse trains with coefficients of variation 0.25 or greater. Reconstruction of movement kinematics, extracted from the activity of neuronal populations recorded in the sensorimotor cortex concurrent with the delivery of ICMS feedback, improved when the recording intervals affected by ICMS artifacts were removed from analysis. These results add to the growing evidence that temporally patterned ICMS can be used to simulate a tactile sense for neuroprosthetic devices. PMID:22207642

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities.

PubMed

Frelat, Romain; Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs.

Regionalization based on spatial and seasonal variation in ground-level ozone concentrations across China.

PubMed

Cheng, Linjun; Wang, Shuai; Gong, Zhengyu; Li, Hong; Yang, Qi; Wang, Yeyao

2018-05-01

Owing to the vast territory of China and strong regional characteristic of ozone pollution, it's desirable for policy makers to have a targeted and prioritized regulation and ozone pollution control strategy in China based on scientific evidences. It's important to assess its current pollution status as well as spatial and temporal variation patterns across China. Recent advances of national monitoring networks provide an opportunity to insight the actions of ozone pollution. Here, we present rotated empirical orthogonal function (REOF) analysis that was used on studying the spatiotemporal characteristics of daily ozone concentrations. Based on results of REOF analysis in pollution seasons for 3years' observations, twelve regions with clear patterns were identified in China. The patterns of temporal variation of ozone in each region were separated well and different from each other, reflecting local meteorological, photochemical or pollution features. A rising trend in annual averaged Eight-hour Average Ozone Concentrations (O 3 -8hr) from 2014 to 2016 was observed for all regions, except for the Tibetan Plateau. The mean values of annual and 90 percentile concentrations for all 338 cities were 82.6±14.6 and 133.9±25.8μg/m 3 , respectively, in 2015. The regionalization results of ozone were found to be influenced greatly by terrain features, indicating significant terrain and landform effects on ozone spatial correlations. Among 12 regions, North China Plain, Huanghuai Plain, Central Yangtze River Plain, Pearl River Delta and Sichuan Basin were realized as priority regions for mitigation strategies, due to their higher ozone concentrations and dense population. Copyright © 2017. Published by Elsevier B.V.

Spatiotemporal canards in neural field equations

NASA Astrophysics Data System (ADS)

Avitabile, D.; Desroches, M.; Knobloch, E.

2017-04-01

Canards are special solutions to ordinary differential equations that follow invariant repelling slow manifolds for long time intervals. In realistic biophysical single-cell models, canards are responsible for several complex neural rhythms observed experimentally, but their existence and role in spatially extended systems is largely unexplored. We identify and describe a type of coherent structure in which a spatial pattern displays temporal canard behavior. Using interfacial dynamics and geometric singular perturbation theory, we classify spatiotemporal canards and give conditions for the existence of folded-saddle and folded-node canards. We find that spatiotemporal canards are robust to changes in the synaptic connectivity and firing rate. The theory correctly predicts the existence of spatiotemporal canards with octahedral symmetry in a neural field model posed on the unit sphere.

Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

NASA Astrophysics Data System (ADS)

Bhushan, A.; Sharker, M. H.; Karimi, H. A.

2015-07-01

In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

Delayed seismicity rate changes controlled by static stress transfer

USGS Publications Warehouse

Kroll, Kayla A.; Richards-Dinger, Keith B.; Dieterich, James H.; Cochran, Elizabeth S.

2017-01-01

On 15 June 2010, a Mw5.7 earthquake occurred near Ocotillo, California, in the Yuha Desert. This event was the largest aftershock of the 4 April 2010 Mw7.2 El Mayor-Cucapah (EMC) earthquake in this region. The EMC mainshock and subsequent Ocotillo aftershock provide an opportunity to test the Coulomb failure hypothesis (CFS). We explore the spatiotemporal correlation between seismicity rate changes and regions of positive and negative CFS change imparted by the Ocotillo event. Based on simple CFS calculations we divide the Yuha Desert into three subregions, one triggering zone and two stress shadow zones. We find the nominal triggering zone displays immediate triggering, one stress shadowed region experiences immediate quiescence, and the other nominal stress shadow undergoes an immediate rate increase followed by a delayed shutdown. We quantitatively model the spatiotemporal variation of earthquake rates by combining calculations of CFS change with the rate-state earthquake rate formulation of Dieterich (1994), assuming that each subregion contains a mixture of nucleation sources that experienced a CFS change of differing signs. Our modeling reproduces the observations, including the observed delay in the stress shadow effect in the third region following the Ocotillo aftershock. The delayed shadow effect occurs because of intrinsic differences in the amplitude of the rate response to positive and negative stress changes and the time constants for return to background rates for the two populations. We find that rate-state models of time-dependent earthquake rates are in good agreement with the observed rates and thus explain the complex spatiotemporal patterns of seismicity.

Delayed Seismicity Rate Changes Controlled by Static Stress Transfer

NASA Astrophysics Data System (ADS)

Kroll, Kayla A.; Richards-Dinger, Keith B.; Dieterich, James H.; Cochran, Elizabeth S.

2017-10-01

On 15 June 2010, a Mw5.7 earthquake occurred near Ocotillo, California, in the Yuha Desert. This event was the largest aftershock of the 4 April 2010 Mw7.2 El Mayor-Cucapah (EMC) earthquake in this region. The EMC mainshock and subsequent Ocotillo aftershock provide an opportunity to test the Coulomb failure hypothesis (CFS). We explore the spatiotemporal correlation between seismicity rate changes and regions of positive and negative CFS change imparted by the Ocotillo event. Based on simple CFS calculations we divide the Yuha Desert into three subregions, one triggering zone and two stress shadow zones. We find the nominal triggering zone displays immediate triggering, one stress shadowed region experiences immediate quiescence, and the other nominal stress shadow undergoes an immediate rate increase followed by a delayed shutdown. We quantitatively model the spatiotemporal variation of earthquake rates by combining calculations of CFS change with the rate-state earthquake rate formulation of Dieterich (1994), assuming that each subregion contains a mixture of nucleation sources that experienced a CFS change of differing signs. Our modeling reproduces the observations, including the observed delay in the stress shadow effect in the third region following the Ocotillo aftershock. The delayed shadow effect occurs because of intrinsic differences in the amplitude of the rate response to positive and negative stress changes and the time constants for return to background rates for the two populations. We find that rate-state models of time-dependent earthquake rates are in good agreement with the observed rates and thus explain the complex spatiotemporal patterns of seismicity.

The Spatiotemporal pattern and driving forces of the paddy in the Northeastern China

NASA Astrophysics Data System (ADS)

Du, G.; Li, Q.; Chun, X.

2017-12-01

The cropland is the production place that protects the regional food security, and the paddy is the main part of the cropland. Since the 21st century, the China's socio-economy has been grown, the structure of the cropland has significantly changed. The Northeast region has gradually become one of the major commodity grain production bases. Meanwhile, the paddy also has gradually increased year by year. Therefore, it is necessary that analyze the tempo-spatial characteristics and the influencing factors of the northeast in China, and the results provide the basis that reveals the change of cropland structure and its causes.In this study, we use the spatial models of GIS and mathematical statistics methods to analyze the tempo-spatial characteristics and the influencing facts of the paddy in the Northeastern China with the spatial data from 2000 to 2015. In order to fully characterize the spatiotemporal characteristics of the paddy, we choose single land use type dynamic degree and land use extension index to quantitatively describe the change degree and the speed of the regional paddy, and the characteristics are visualized with "3S" means. Meanwhile, the relative change rate and the center of gravity model are chosen to explore the region differences and the distribution of the distribution center of paddy field change in Northeast China. In addition, in order to further reveal the cause of the paddy change, we use the OLS, SAM or SEM models to analyze the main influencing factors of spatiotemporal variation of the paddy field.

Walking variations in healthy women wearing high-heeled shoes: Shoe size and heel height effects.

PubMed

Di Sipio, Enrica; Piccinini, Giulia; Pecchioli, Cristiano; Germanotta, Marco; Iacovelli, Chiara; Simbolotti, Chiara; Cruciani, Arianna; Padua, Luca

2018-05-03

The use of high heels is widespread in modern society in professional and social contests. Literature showed that wearing high heels can produce injurious effects on several structures from the toes to the pelvis. No studies considered shoe length as an impacting factor on walking with high heels. The aim of this study is to evaluate walking parameters in young healthy women wearing high heels, considering not only the heel height but also the foot/shoe size. We evaluate spatio-temporal, kinematic and kinetic data, collected using a 8-camera motion capture system, in a sample of 21 healthy women in three different walking conditions: 1) barefoot, 2) wearing 12 cm high heel shoes independently from shoe size, and 3) wearing shoes with heel height based on shoe size, keeping the ankles' plantar flexion angle constant. The main outcome measures were: spatio-temporal parameters, gait harmony measurement, range of motion, flexion and extension maximal values, power and moment of lower limb joints. Comparing the three walking conditions, the Mixed Anova test, showed significant differences between both high heeled conditions (variable and constant height) and barefoot in spatio-temporal, kinematic and kinetic parameters. Regardless of the shoe size, both heeled conditions presented a similar gait pattern and were responsible for negative effects on walking parameters. Considering our results and the relevance of the heel height, further studies are needed to identify a threshold, over which it is possible to observe that wearing high heels could cause harmful effects, independently from the foot/shoe size. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatiotemporal evolution of water storage changes in India from the updated GRACE-derived gravity records

NASA Astrophysics Data System (ADS)

Panda, Dileep K.; Wahr, John

2016-01-01

Investigating changes in terrestrial water storage (TWS) is important for understanding response of the hydrological cycle to recent climate variability worldwide. This is particularly critical in India where the current economic development and food security greatly depend on its water resources. We use 129 monthly gravity solutions from NASA's Gravity Recovery and Climate Experiment (GRACE) satellites for the period of January 2003 to May 2014 to characterize spatiotemporal variations of TWS and groundwater storage (GWS). The spatiotemporal evolution of GRACE data reflects consistent patterns with that of several hydroclimatic variables and also shows that most of the water loss has occurred in the northern parts of India. Substantial GWS depletion at the rate of 1.25 and 2.1 cm yr-1 has taken place, respectively in the Ganges Basin and Punjab state, which are known as the India's grain bowl. Of particular concern is the Ganges Basin's storage loss in drought years, primarily due to anthropogenic groundwater withdrawals that sustain rice and wheat cultivation. We estimate these losses to be approximately 41, 44, and 42 km3 in 2004, 2009, and 2012, respectively. The GWS depletions that constitute about 90% of the observed TWS loss are also influenced by a marked rise in temperatures since 2008. A high degree of correspondence between GRACE-derived GWS and in situ groundwater levels from observation well validates the results. This validation increases confidence level in the application of GRACE observations in monitoring large-scale storage changes in intensely irrigated areas in India and other regions around the world.

Spatiotemporal analysis of the relationship between socioeconomic factors and stroke in the Portuguese mainland population under 65 years old.

PubMed

Oliveira, André; Cabral, António J R; Mendes, Jorge M; Martins, Maria R O; Cabral, Pedro

2015-11-04

Stroke risk has been shown to display varying patterns of geographic distribution amongst countries but also between regions of the same country. Traditionally a disease of older persons, a global 25% increase in incidence instead was noticed between 1990 and 2010 in persons aged 20-≤64 years, particularly in low- and medium-income countries. Understanding spatial disparities in the association between socioeconomic factors and stroke is critical to target public health initiatives aiming to mitigate or prevent this disease, including in younger persons. We aimed to identify socioeconomic determinants of geographic disparities of stroke risk in people <65 years old, in municipalities of mainland Portugal, and the spatiotemporal variation of the association between these determinants and stroke risk during two study periods (1992-1996 and 2002-2006). Poisson and negative binomial global regression models were used to explore determinants of disease risk. Geographically weighted regression (GWR) represents a distinctive approach, allowing estimation of local regression coefficients. Models for both study periods were identified. Significant variables included education attainment, work hours per week and unemployment. Local Poisson GWR models achieved the best fit and evidenced spatially varying regression coefficients. Spatiotemporal inequalities were observed in significant variables, with dissimilarities between men and women. This study contributes to a better understanding of the relationship between stroke and socioeconomic factors in the population <65 years of age, one age group seldom analysed separately. It can thus help to improve the targeting of public health initiatives, even more in a context of economic crisis.

Assessing the social and environmental determinants of pertussis epidemics in Queensland, Australia: a Bayesian spatio-temporal analysis.

PubMed

Huang, X; Lambert, S; Lau, C; Soares Magalhaes, R J; Marquess, J; Rajmokan, M; Milinovich, G; Hu, W

2017-04-01

Pertussis epidemics have displayed substantial spatial heterogeneity in countries with high socioeconomic conditions and high vaccine coverage. This study aims to investigate the relationship between pertussis risk and socio-environmental factors on the spatio-temporal variation underlying pertussis infection. We obtained daily case numbers of pertussis notifications from Queensland Health, Australia by postal area, for the period January 2006 to December 2012. A Bayesian spatio-temporal model was used to quantify the relationship between monthly pertussis incidence and socio-environmental factors. The socio-environmental factors included monthly mean minimum temperature (MIT), monthly mean vapour pressure (VAP), Queensland school calendar pattern (SCP), and socioeconomic index for area (SEIFA). An increase in pertussis incidence was observed from 2006 to 2010 and a slight decrease from 2011 to 2012. Spatial analyses showed pertussis incidence across Queensland postal area to be low and more spatially homogeneous during 2006-2008; incidence was higher and more spatially heterogeneous after 2009. The results also showed that the average decrease in monthly pertussis incidence was 3·1% [95% credible interval (CrI) 1·3-4·8] for each 1 °C increase in monthly MIT, while average increase in monthly pertussis incidences were 6·2% (95% CrI 0·4-12·4) and 2% (95% CrI 1-3) for SCP periods and for each 10-unit increase in SEIFA, respectively. This study demonstrated that pertussis transmission is significantly associated with MIT, SEIFA, and SCP. Mapping derived from this work highlights the potential for future investigation and areas for focusing future control strategies.

Spatiotemporal patterns of phytoplankton composition and abundance in the Maryland Coastal Bays: The influence of freshwater discharge and anthropogenic activities

NASA Astrophysics Data System (ADS)

Oseji, Ozuem F.; Chigbu, Paulinus; Oghenekaro, Efeturi; Waguespack, Yan; Chen, Nianhong

2018-07-01

The spatial and temporal variations in phytoplankton abundance and community structure in the northern and southern parts of the Maryland Coastal Bays (MCBs) that differ in anthropogenic activities and hydrological characteristics were studied in 2012 and 2013 using photosynthetic pigments as biomarkers. Phytoplankton pigment biomass and diversity were generally higher in the northern bays that receive high nutrient input from St. Martin River, than in the southern bays where nutrient levels were comparatively low. Sites close to the mouths of tributaries in northern and southern bays had higher nutrient levels, which favored the development of dinoflagellates, and nano- and picophytoplankton, than sites closer to the inlets. The microplankton dominated the phytoplankton community in spring (>90%) and decreased in relative abundance into fall (<60%) whereas nanoplankton peaked in summer or fall. Picoplankton relative abundance increased from late spring (<10%, March 2012 & 2013) to summer (40%, July 2012 and August 2013) and was correlated positively with NH4+ and negatively with salinity. The observed spatial and seasonal patterns of phytoplankton relative abundance and diversity are likely due to changes in nutrient concentrations and ratios, driven by variations in freshwater discharge, and selective grazing of phytoplankton. Water quality management in the MCBs should continue to focus on reducing nutrient inputs into the bays.

Hysteresis, neural avalanches, and critical behavior near a first-order transition of a spiking neural network

NASA Astrophysics Data System (ADS)

Scarpetta, Silvia; Apicella, Ilenia; Minati, Ludovico; de Candia, Antonio

2018-06-01

Many experimental results, both in vivo and in vitro, support the idea that the brain cortex operates near a critical point and at the same time works as a reservoir of precise spatiotemporal patterns. However, the mechanism at the basis of these observations is still not clear. In this paper we introduce a model which combines both these features, showing that scale-free avalanches are the signature of a system posed near the spinodal line of a first-order transition, with many spatiotemporal patterns stored as dynamical metastable attractors. Specifically, we studied a network of leaky integrate-and-fire neurons whose connections are the result of the learning of multiple spatiotemporal dynamical patterns, each with a randomly chosen ordering of the neurons. We found that the network shows a first-order transition between a low-spiking-rate disordered state (down), and a high-rate state characterized by the emergence of collective activity and the replay of one of the stored patterns (up). The transition is characterized by hysteresis, or alternation of up and down states, depending on the lifetime of the metastable states. In both cases, critical features and neural avalanches are observed. Notably, critical phenomena occur at the edge of a discontinuous phase transition, as recently observed in a network of glow lamps.

Dependence of evolutionary cooperation on the additive noise to the enhancement level in the spatial public goods game

NASA Astrophysics Data System (ADS)

Jia, Chun-Xiao; Liu, Run-Ran; Rong, Zhihai

2017-03-01

Either in societies or economic cycles, the benefits of a group can be affected by various unpredictable factors. We study effects of additive spatiotemporal random variations on the evolution of cooperation by introducing them to the enhancement level of the spatial public goods game. Players are located on the sites of a two-dimensional lattice and gain their payoffs from games with their neighbors by choosing cooperation or defection. We observe that a moderate intensity of variations can best favor cooperation at low enhancement levels, which resembles classical coherence resonance. Whereas for high enhancement levels, we find that the random variations cannot increase the cooperation level, but hamper cooperation instead. This discrepancy is attributed to the different roles the additive variations played in the early and late stages of evolution. In the early stage of evolution, the additive variations increase the survival probability of the players with lower average payoffs. However, in the late stage of evolution, the additive variations can promote defectors to destroy the cooperative clusters that have been formed. Our results indicate that additive spatiotemporal noise may not be as universally beneficial for cooperation as the spatial prisoner's dilemma game.

The ecological footprint of Acca sellowiana domestication maintains the residual vertebrate diversity in threatened highlands of Atlantic Forest

PubMed Central

2018-01-01

Past and contemporary human actions are causing numerous changes in patterns and processes at various ecosystem scales and trophic levels, including unintended downstream changes, such as species interactions. In its native range Acca sellowiana (Feijoa) combines some characteristics of human interactions: incipient domestication, restricted to subtropical Atlantic Forest highlands, associated with the threatened conifer Araucaria angustifolia (Araucaria), within a domesticated landscape with anthropogenic forest patches, and provides fruit at a time of resource shortage (Araucaria seeds—pinhão). We quantify the trophic relationships between Feijoa and vertebrates, and evaluate the influences on interactions caused by environmental variations, Feijoa domestication evidences, spatial distance and fruit availability. In four sites within protected areas, we selected 28 focal individuals of Feijoa (seven/site) and collected three temporal replicas between 2015 and 2016, when we measured productivity and frugivory via 45-second videos taken with camera traps. Using ecological network, rarefaction curves and variation partitioning analyses, we evaluate the frugivory network topology, the spatiotemporal structure of communities in relation to fruit availability and the influence of predictive variables on frugivory. We found a large spatiotemporal variation in productivity of Feijoa and that 20 species consumed Feijoa fruits, with a species degree of 2.8 (±5.7) and average Feijoa degree of 14.4 (±10.1), in a modular network with intermediary connectance. Rarefaction curves showed that richness and the independent records are congruent with the fruit amount. Variation partitioning showed that, for the focal individuals, canopy area, green coverage, patch size and distance to water influenced frugivory, and the Feijoa domestication influenced significantly the mammalian frugivory. Feijoa is an important resource that provides food during the time of year when Pinhão is absent, and attracts frugivores, maintain the residual diversity of vertebrates contributing to the structure of communities in highlands. Our insights allowed us to evaluate the magnitude of the interactions between vertebrates and an incipient domesticated tree, in a cultural landscape and highly threatened environment, under a basal foodweb approach with implications for bottom-up and top-down forces. The results contribute to understanding animal-plant relationships, including concepts that can be replicated for other sessile prey and mobile predators in any region or habitat under different gradients of management. Thus, this work shows how human actions can change not only patterns of distribution and abundance but also the diversity and direction of interspecific interactions among species. PMID:29617455

The ecological footprint of Acca sellowiana domestication maintains the residual vertebrate diversity in threatened highlands of Atlantic Forest.

PubMed

Bogoni, Juliano André; Graipel, Maurício Eduardo; Peroni, Nivaldo

2018-01-01

Past and contemporary human actions are causing numerous changes in patterns and processes at various ecosystem scales and trophic levels, including unintended downstream changes, such as species interactions. In its native range Acca sellowiana (Feijoa) combines some characteristics of human interactions: incipient domestication, restricted to subtropical Atlantic Forest highlands, associated with the threatened conifer Araucaria angustifolia (Araucaria), within a domesticated landscape with anthropogenic forest patches, and provides fruit at a time of resource shortage (Araucaria seeds-pinhão). We quantify the trophic relationships between Feijoa and vertebrates, and evaluate the influences on interactions caused by environmental variations, Feijoa domestication evidences, spatial distance and fruit availability. In four sites within protected areas, we selected 28 focal individuals of Feijoa (seven/site) and collected three temporal replicas between 2015 and 2016, when we measured productivity and frugivory via 45-second videos taken with camera traps. Using ecological network, rarefaction curves and variation partitioning analyses, we evaluate the frugivory network topology, the spatiotemporal structure of communities in relation to fruit availability and the influence of predictive variables on frugivory. We found a large spatiotemporal variation in productivity of Feijoa and that 20 species consumed Feijoa fruits, with a species degree of 2.8 (±5.7) and average Feijoa degree of 14.4 (±10.1), in a modular network with intermediary connectance. Rarefaction curves showed that richness and the independent records are congruent with the fruit amount. Variation partitioning showed that, for the focal individuals, canopy area, green coverage, patch size and distance to water influenced frugivory, and the Feijoa domestication influenced significantly the mammalian frugivory. Feijoa is an important resource that provides food during the time of year when Pinhão is absent, and attracts frugivores, maintain the residual diversity of vertebrates contributing to the structure of communities in highlands. Our insights allowed us to evaluate the magnitude of the interactions between vertebrates and an incipient domesticated tree, in a cultural landscape and highly threatened environment, under a basal foodweb approach with implications for bottom-up and top-down forces. The results contribute to understanding animal-plant relationships, including concepts that can be replicated for other sessile prey and mobile predators in any region or habitat under different gradients of management. Thus, this work shows how human actions can change not only patterns of distribution and abundance but also the diversity and direction of interspecific interactions among species.

Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space-time SIR-based model.

PubMed

Huang, Xiaodong; Clements, Archie C A; Williams, Gail; Mengersen, Kerrie; Tong, Shilu; Hu, Wenbiao

2016-04-01

A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7-December 31, 2009, at a postal area level in Queensland, Australia. We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space-time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: -0.341; 95% credible interval (CI): -0.370--0.311) and the socio-economic index for area (SEIFA) (posterior mean: -0.003; 95% CI: -0.004--0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007-0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Local SEIFA and local atmospheric conditions were associated with the transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period. Copyright © 2016 Elsevier Inc. All rights reserved.

High-resolution spatiotemporal strain mapping reveals non-uniform deformation in micropatterned elastomers

NASA Astrophysics Data System (ADS)

Aksoy, B.; Rehman, A.; Bayraktar, H.; Alaca, B. E.

2017-04-01

Micropatterns are generated on a vast selection of polymeric substrates for various applications ranging from stretchable electronics to cellular mechanobiological systems. When these patterned substrates are exposed to external loading, strain field is primarily affected by the presence of microfabricated structures and similarly by fabrication-related defects. The capturing of such nonhomogeneous strain fields is of utmost importance in cases where study of the mechanical behavior with a high spatial resolution is necessary. Image-based non-contact strain measurement techniques are favorable and have recently been extended to scanning tunneling microscope and scanning electron microscope images for the characterization of mechanical properties of metallic materials, e.g. steel and aluminum, at the microscale. A similar real-time analysis of strain heterogeneity in elastomers is yet to be achieved during the entire loading sequence. The available measurement methods for polymeric materials mostly depend on cross-head displacement or precalibrated strain values. Thus, they suffer either from the lack of any real-time analysis, spatiotemporal distribution or high resolution in addition to a combination of these factors. In this work, these challenges are addressed by integrating a tensile stretcher with an inverted optical microscope and developing a subpixel particle tracking algorithm. As a proof of concept, the patterns with a critical dimension of 200 µm are generated on polydimethylsiloxane substrates and strain distribution in the vicinity of the patterns is captured with a high spatiotemporal resolution. In the field of strain measurement, there is always a tradeoff between minimum measurable strain value and spatial resolution. Current noncontact techniques on elastomers can deliver a strain resolution of 0.001% over a minimum length of 5 cm. More importantly, inhomogeneities within this quite large region cannot be captured. The proposed technique can overcome this challenge and provides a displacement measurement resolution of 116 nm and a strain resolution of 0.04% over a gage length of 300 µm. Similarly, the ability to capture inhomogeneities is demonstrated by mapping strain around a thru-hole. The robustness of the technique is also evaluated, where no appreciable change in strain measurement is observed despite the significant variations imposed on the measurement mesh. The proposed approach introduces critical improvements for the determination of displacement and strain gradients in elastomers regarding the real-time nature of strain mapping with a microscale spatial resolution.

Spatio-temporal analysis of wildfire ignitions in the St. Johns River Water Management District, Florida

Treesearch

Marc G. Genton; David T. Butry; Marcia L. Gumpertz; Jeffrey P. Prestemon

2006-01-01

We analyse the spatio-temporal structure of wildfire ignitions in the St. Johns River Water Management District in north-eastern Florida. We show, using tools to analyse point patterns (e.g. the L-function), that wildfire events occur in clusters. Clustering of these events correlates with irregular distribution of fire ignitions, including lightning...

Spatiotemporal patterns of ring-width variability in the northern interior west

Treesearch

R. Justin DeRose; John D. Shaw; James N. Long

2015-01-01

A fundamental goal of forest biogeography is to understand the factors that drive spatiotemporal variability in forest growth across large areas (e.g., states or regions). The ancillary collection of increment cores as part of the IW FIA Program represents an important non-traditional role for the development of unprecedented data sets. Individual-tree growth data from...

Seasonal divergence in the interannual responses of Northern Hemisphere vegetation activity to variations in diurnal climate.

PubMed

Wu, Xiuchen; Liu, Hongyan; Li, Xiaoyan; Liang, Eryuan; Beck, Pieter S A; Huang, Yongmei

2016-01-11

Seasonal asymmetry in the interannual variations in the daytime and nighttime climate in the Northern Hemisphere (NH) is well documented, but its consequences for vegetation activity remain poorly understood. Here, we investigate the interannual responses of vegetation activity to variations of seasonal mean daytime and nighttime climate in NH (>30 °N) during the past decades using remote sensing retrievals, FLUXNET and tree ring data. Despite a generally significant and positive response of vegetation activity to seasonal mean maximum temperature (Tmax) in ~22-25% of the boreal (>50 °N) NH between spring and autumn, spring-summer progressive water limitations appear to decouple vegetation activity from the mean summer Tmax, particularly in climate zones with dry summers. Drought alleviation during autumn results in vegetation recovery from the marked warming-induced drought limitations observed in spring and summer across 24-26% of the temperate NH. Vegetation activity exhibits a pervasively negative correlation with the autumn mean minimum temperature, which is in contrast to the ambiguous patterns observed in spring and summer. Our findings provide new insights into how seasonal asymmetry in the interannual variations in the mean daytime and nighttime climate interacts with water limitations to produce spatiotemporally variable responses of vegetation growth.

Seasonal divergence in the interannual responses of Northern Hemisphere vegetation activity to variations in diurnal climate

PubMed Central

Wu, Xiuchen; Liu, Hongyan; Li, Xiaoyan; Liang, Eryuan; Beck, Pieter S. A.; Huang, Yongmei

2016-01-01

Seasonal asymmetry in the interannual variations in the daytime and nighttime climate in the Northern Hemisphere (NH) is well documented, but its consequences for vegetation activity remain poorly understood. Here, we investigate the interannual responses of vegetation activity to variations of seasonal mean daytime and nighttime climate in NH (>30 °N) during the past decades using remote sensing retrievals, FLUXNET and tree ring data. Despite a generally significant and positive response of vegetation activity to seasonal mean maximum temperature () in ~22–25% of the boreal (>50 °N) NH between spring and autumn, spring-summer progressive water limitations appear to decouple vegetation activity from the mean summer , particularly in climate zones with dry summers. Drought alleviation during autumn results in vegetation recovery from the marked warming-induced drought limitations observed in spring and summer across 24–26% of the temperate NH. Vegetation activity exhibits a pervasively negative correlation with the autumn mean minimum temperature, which is in contrast to the ambiguous patterns observed in spring and summer. Our findings provide new insights into how seasonal asymmetry in the interannual variations in the mean daytime and nighttime climate interacts with water limitations to produce spatiotemporally variable responses of vegetation growth. PMID:26751166

Spatiotemporal patterns, annual baseline and movement-related incidence of Streptococcus agalactiae infection in Danish dairy herds: 2000-2009.

PubMed

Mweu, Marshal M; Nielsen, Søren S; Halasa, Tariq; Toft, Nils

2014-02-01

Several decades after the inception of the five-point plan for the control of contagious mastitis pathogens, Streptococcus agalactiae (S. agalactiae) persists as a fundamental threat to the dairy industry in many countries. A better understanding of the relative importance of within- and between-herd sources of new herd infections coupled with the spatiotemporal distribution of the infection, may aid in effective targeting of control efforts. Thus, the objectives of this study were: (1) to describe the spatiotemporal patterns of infection with S. agalactiae in the population of Danish dairy herds from 2000 to 2009 and (2) to estimate the annual herd-level baseline and movement-related incidence risks of S. agalactiae infection over the 10-year period. The analysis involved registry data on bacteriological culture of all bulk tank milk samples collected as part of the mandatory Danish S. agalactiae surveillance scheme as well as live cattle movements into dairy herds during the specified 10-year period. The results indicated that the predicted risk of a herd becoming infected with S. agalactiae varied spatiotemporally; the risk being more homogeneous and higher in the period after 2005. Additionally, the annual baseline risks yielded significant yet distinctive patterns before and after 2005 - the risk of infection being higher in the latter phase. On the contrary, the annual movement-related risks revealed a non-significant pattern over the 10-year period. There was neither evidence for spatial clustering of cases relative to the population of herds at risk nor spatial dependency between herds. Nevertheless, the results signal a need to beef up within-herd biosecurity in order to reduce the risk of new herd infections. Copyright © 2013 Elsevier B.V. All rights reserved.

DNA-Demethylase Regulated Genes Show Methylation-Independent Spatiotemporal Expression Patterns

PubMed Central

Schumann, Ulrike; Lee, Joanne; Kazan, Kemal; Ayliffe, Michael; Wang, Ming-Bo

2017-01-01

Recent research has indicated that a subset of defense-related genes is downregulated in the Arabidopsis DNA demethylase triple mutant rdd (ros1 dml2 dml3) resulting in increased susceptibility to the fungal pathogen Fusarium oxysporum. In rdd plants these downregulated genes contain hypermethylated transposable element sequences (TE) in their promoters, suggesting that this methylation represses gene expression in the mutant and that these sequences are actively demethylated in wild-type plants to maintain gene expression. In this study, the tissue-specific and pathogen-inducible expression patterns of rdd-downregulated genes were investigated and the individual role of ROS1, DML2, and DML3 demethylases in these spatiotemporal regulation patterns was determined. Large differences in defense gene expression were observed between pathogen-infected and uninfected tissues and between root and shoot tissues in both WT and rdd plants, however, only subtle changes in promoter TE methylation patterns occurred. Therefore, while TE hypermethylation caused decreased gene expression in rdd plants it did not dramatically effect spatiotemporal gene regulation, suggesting that this latter regulation is largely methylation independent. Analysis of ros1-3, dml2-1, and dml3-1 single gene mutant lines showed that promoter TE hypermethylation and defense-related gene repression was predominantly, but not exclusively, due to loss of ROS1 activity. These data demonstrate that DNA demethylation of TE sequences, largely by ROS1, promotes defense-related gene expression but does not control spatiotemporal expression in Arabidopsis. Summary: Ros1-mediated DNA demethylation of promoter transposable elements is essential for activation of defense-related gene expression in response to fungal infection in Arabidopsis thaliana. PMID:28894455

Spatiotemporal Dynamics of Genetic Variation in the Iberian Lynx along Its Path to Extinction Reconstructed with Ancient DNA

PubMed Central

Casas-Marce, Mireia; Marmesat, Elena; Soriano, Laura; Martínez-Cruz, Begoña; Lucena-Perez, Maria; Nocete, Francisco; Rodríguez-Hidalgo, Antonio; Canals, Antoni; Nadal, Jordi; Detry, Cleia; Bernáldez-Sánchez, Eloísa; Fernández-Rodríguez, Carlos; Pérez-Ripoll, Manuel; Stiller, Mathias; Hofreiter, Michael; Rodríguez, Alejandro; Revilla, Eloy; Delibes, Miguel; Godoy, José A.

2017-01-01

Abstract There is the tendency to assume that endangered species have been both genetically and demographically healthier in the past, so that any genetic erosion observed today was caused by their recent decline. The Iberian lynx (Lynx pardinus) suffered a dramatic and continuous decline during the 20th century, and now shows extremely low genome- and species-wide genetic diversity among other signs of genomic erosion. We analyze ancient (N = 10), historical (N = 245), and contemporary (N = 172) samples with microsatellite and mitogenome data to reconstruct the species' demography and investigate patterns of genetic variation across space and time. Iberian lynx populations transitioned from low but significantly higher genetic diversity than today and shallow geographical differentiation millennia ago, through a structured metapopulation with varying levels of diversity during the last centuries, to two extremely genetically depauperate and differentiated remnant populations by 2002. The historical subpopulations show varying extents of genetic drift in relation to their recent size and time in isolation, but these do not predict whether the populations persisted or went finally extinct. In conclusion, current genetic patterns were mainly shaped by genetic drift, supporting the current admixture of the two genetic pools and calling for a comprehensive genetic management of the ongoing conservation program. This study illustrates how a retrospective analysis of demographic and genetic patterns of endangered species can shed light onto their evolutionary history and this, in turn, can inform conservation actions. PMID:28962023

Making teeth to order: conserved genes reveal an ancient molecular pattern in paddlefish (Actinopterygii)

PubMed Central

Smith, Moya M.; Johanson, Zerina; Butts, Thomas; Ericsson, Rolf; Modrell, Melinda; Tulenko, Frank J.; Davis, Marcus C.; Fraser, Gareth J.

2015-01-01

Ray-finned fishes (Actinopterygii) are the dominant vertebrate group today (+30 000 species, predominantly teleosts), with great morphological diversity, including their dentitions. How dental morphological variation evolved is best addressed by considering a range of taxa across actinopterygian phylogeny; here we examine the dentition of Polyodon spathula (American paddlefish), assigned to the basal group Acipenseriformes. Although teeth are present and functional in young individuals of Polyodon, they are completely absent in adults. Our current understanding of developmental genes operating in the dentition is primarily restricted to teleosts; we show that shh and bmp4, as highly conserved epithelial and mesenchymal genes for gnathostome tooth development, are similarly expressed at Polyodon tooth loci, thus extending this conserved developmental pattern within the Actinopterygii. These genes map spatio-temporal tooth initiation in Polyodon larvae and provide new data in both oral and pharyngeal tooth sites. Variation in cellular intensity of shh maps timing of tooth morphogenesis, revealing a second odontogenic wave as alternate sites within tooth rows, a dental pattern also present in more derived actinopterygians. Developmental timing for each tooth field in Polyodon follows a gradient, from rostral to caudal and ventral to dorsal, repeated during subsequent loss of teeth. The transitory Polyodon dentition is modified by cessation of tooth addition and loss. As such, Polyodon represents a basal actinopterygian model for the evolution of developmental novelty: initial conservation, followed by tooth loss, accommodating the adult trophic modification to filter-feeding. PMID:25788604

Joint modelling of potentially avoidable hospitalisation for five diseases accounting for spatiotemporal effects: A case study in New South Wales, Australia.

PubMed

Baker, Jannah; White, Nicole; Mengersen, Kerrie; Rolfe, Margaret; Morgan, Geoffrey G

2017-01-01

Three variant formulations of a spatiotemporal shared component model are proposed that allow examination of changes in shared underlying factors over time. Models are evaluated within the context of a case study examining hospitalisation rates for five chronic diseases for residents of a regional area in New South Wales: type II diabetes mellitus (DMII), chronic obstructive pulmonary disease (COPD), coronary arterial disease (CAD), hypertension (HT) and congestive heart failure (CHF) between 2001-2006. These represent ambulatory care sensitive (ACS) conditions, often used as a proxy for avoidable hospitalisations. Using a selected model, the effects of socio-economic status (SES) as a shared component are estimated and temporal patterns in the influence of the residual shared spatial component are examined. Choice of model depends upon the application. In the featured application, a model allowing for changing influence of the shared spatial component over time was found to have the best fit and was selected for further analyses. Hospitalisation rates were found to be increasing for COPD and DMII, decreasing for CHF and stable for CAD and HT. SES was substantively associated with hospitalisation rates, with differing degrees of influence for each disease. In general, most of the spatial variation in hospitalisation rates was explained by disease-specific spatial components, followed by the residual shared spatial component. Appropriate selection of a joint disease model allows for the examination of temporal patterns of disease outcomes and shared underlying spatial factors, and distinction between different shared spatial factors.

Diffraction contrast as a sensitive indicator of femtosecond sub-nanoscale motion in ultrafast transmission electron microscopy

NASA Astrophysics Data System (ADS)

Cremons, Daniel R.; Schliep, Karl B.; Flannigan, David J.

2013-09-01

With ultrafast transmission electron microscopy (UTEM), access can be gained to the spatiotemporal scales required to directly visualize rapid, non-equilibrium structural dynamics of materials. This is achieved by operating a transmission electron microscope (TEM) in a stroboscopic pump-probe fashion by photoelectrically generating coherent, well-timed electron packets in the gun region of the TEM. These probe photoelectrons are accelerated down the TEM column where they travel through the specimen before reaching a standard, commercially-available CCD detector. A second laser pulse is used to excite (pump) the specimen in situ. Structural changes are visualized by varying the arrival time of the pump laser pulse relative to the probe electron packet at the specimen. Here, we discuss how ultrafast nanoscale motions of crystalline materials can be visualized and precisely quantified using diffraction contrast in UTEM. Because diffraction contrast sensitively depends upon both crystal lattice orientation as well as incoming electron wavevector, minor spatial/directional variations in either will produce dynamic and often complex patterns in real-space images. This is because sections of the crystalline material that satisfy the Laue conditions may be heterogeneously distributed such that electron scattering vectors vary over nanoscale regions. Thus, minor changes in either crystal grain orientation, as occurs during specimen tilting, warping, or anisotropic expansion, or in the electron wavevector result in dramatic changes in the observed diffraction contrast. In this way, dynamic contrast patterns observed in UTEM images can be used as sensitive indicators of ultrafast specimen motion. Further, these motions can be spatiotemporally mapped such that direction and amplitude can be determined.

A population-based spatio-temporal analysis of Clostridium difficile infection in Queensland, Australia over a 10-year period.

PubMed

Furuya-Kanamori, Luis; Robson, Jenny; Soares Magalhães, Ricardo J; Yakob, Laith; McKenzie, Samantha J; Paterson, David L; Riley, Thomas V; Clements, Archie C A

2014-11-01

To identify the spatio-temporal patterns and environmental factors associated with Clostridium difficile infection (CDI) in Queensland, Australia. Data from patients tested for CDI were collected from 392 postcodes across Queensland between May 2003 and December 2012. A binomial logistic regression model, with CDI status as the outcome, was built in a Bayesian framework, incorporating fixed effects for sex, age, source of the sample (healthcare facility or community), elevation, rainfall, land surface temperature, seasons of the year, time in months and spatially unstructured random effects at the postcode level. C. difficile was identified in 13.1% of the samples, the proportion significantly increased over the study period from 5.9% in 2003 to 18.8% in 2012. CDI peaked in summer (14.6%) and was at its lowest in autumn (10.1%). Other factors significantly associated with CDI included female sex (OR: 1.08; 95%CI: 1.01-1.14), community source samples (OR: 1.12; 95%CI: 1.05-1.20), and higher rainfall (OR: 1.09; 95%CI: 1.02-1.17). There was no significant spatial variation in CDI after accounting for the fixed effects in the model. There was an increasing annual trend in CDI in Queensland from 2003 to 2012. Peaks of CDI were found in summer (December-February), which is at odds with the current epidemiological pattern described for northern hemisphere countries. Epidemiologically plausible explanations for this disparity require further investigation. Copyright © 2014 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

Spatiotemporal Patterns and Socioeconomic Dimensions of Shared Accommodations: the Case of Airbnb in LOS Angeles, California

NASA Astrophysics Data System (ADS)

Sarkar, A.; Koohikamali, M.; Pick, J. B.

2017-10-01

In recent years, disruptive innovation by peer-to-peer platforms in a variety of industries, notably transportation and hospitality have altered the way individuals consume everyday essential services. With growth in sharing economy platforms such as Uber for ridesharing and Airbnb for short-term accommodations, interest in examining spatiotemporal patterns of participation in the sharing economy by suppliers and consumers is increasing. This research is motivated by key questions: who are the sharing economy workers, where are they located, and does their location influence their participation in the sharing economy? This paper is the first systematic effort to analyze spatiotemporal patterns of participation by hosts in the shared accommodation-based economy. Using three different kinds of shared accommodations listed in a 3-year period in the popular short-term accommodation platform, Airbnb, we examine spatiotemporal dimensions of host participation in a major U.S. market, Los Angeles CA. The paper also develops a conceptual model by positing associations of demographic, socioeconomic, occupational, and social capital attributes of hosts, along with their attitudes toward trust and greener consumption with hosts' participation in a shared accommodation market. Results confirm host participation to be influenced by young dependency ratio, the potential of supplemental income, as well as the sustainability potential of collaborative consumption, along with finance, insurance, and real estate occupation, but not so much by trust for our overall study area. These results add new insights to limited prior knowledge about the sharing economy worker and have policy implications.

Self-organized mechano-chemical dynamics in amoeboid locomotion of Physarum fragments

NASA Astrophysics Data System (ADS)

Zhang, Shun; Guy, Robert D.; Lasheras, Juan C.; del Álamo, Juan C.

2017-05-01

The aim of this work is to quantify the spatio-temporal dynamics of flow-driven amoeboid locomotion in small (∼100 μm) fragments of the true slime mold Physarum polycephalum. In this model organism, cellular contraction drives intracellular flows, and these flows transport the chemical signals that regulate contraction in the first place. As a consequence of these non-linear interactions, a diversity of migratory behaviors can be observed in migrating Physarum fragments. To study these dynamics, we measure the spatio-temporal distributions of the velocities of the endoplasm and ectoplasm of each migrating fragment, the traction stresses it generates on the substratum, and the concentration of free intracellular calcium. Using these unprecedented experimental data, we classify migrating Physarum fragments according to their dynamics, finding that they often exhibit spontaneously coordinated waves of flow, contractility and chemical signaling. We show that Physarum fragments exhibiting symmetric spatio-temporal patterns of endoplasmic flow migrate significantly slower than fragments with asymmetric patterns. In addition, our joint measurements of ectoplasm velocity and traction stress at the substratum suggest that forward motion of the ectoplasm is enabled by a succession of stick-slip transitions, which we conjecture are also organized in the form of waves. Combining our experiments with a simplified convection-diffusion model, we show that the convective transport of calcium ions may be key for establishing and maintaining the spatio-temporal patterns of calcium concentration that regulate the generation of contractile forces.

Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections

NASA Astrophysics Data System (ADS)

Tan, Xuezhi; Gan, Thian Yew; Chen, Shu; Liu, Bingjun

2018-05-01

Climate change and large-scale climate patterns may result in changes in probability distributions of climate variables that are associated with changes in the mean and variability, and severity of extreme climate events. In this paper, we applied a flexible framework based on the Bayesian spatiotemporal quantile (BSTQR) model to identify climate changes at different quantile levels and their teleconnections to large-scale climate patterns such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Pacific-North American (PNA). Using the BSTQR model with time (year) as a covariate, we estimated changes in Canadian winter precipitation and their uncertainties at different quantile levels. There were some stations in eastern Canada showing distributional changes in winter precipitation such as an increase in low quantiles but a decrease in high quantiles. Because quantile functions in the BSTQR model vary with space and time and assimilate spatiotemporal precipitation data, the BSTQR model produced much spatially smoother and less uncertain quantile changes than the classic regression without considering spatiotemporal correlations. Using the BSTQR model with five teleconnection indices (i.e., SOI, PDO, PNA, NP and NAO) as covariates, we investigated effects of large-scale climate patterns on Canadian winter precipitation at different quantile levels. Winter precipitation responses to these five teleconnections were found to occur differently at different quantile levels. Effects of five teleconnections on Canadian winter precipitation were stronger at low and high than at medium quantile levels.

Spatio-temporal variation in foodscapes modifies deer browsing impact on vegetation

Treesearch

Alejandro A. Royo; David W. Kramer; Karl V. Miller; Nathan P. Nibbelink; Susan L. Stout

2017-01-01

Context. Ungulate browsers often alter plant composition and reduce diversity in forests worldwide, yet our ability to predict browse impact on vegetation remains equivocal. Theory suggests, however, that ungulate distribution and foraging impacts are shaped by scale-dependent decisions based on variation in habitat composition and structure...

A Spatio-Temporally Explicit Random Encounter Model for Large-Scale Population Surveys

PubMed Central

Jousimo, Jussi; Ovaskainen, Otso

2016-01-01

Random encounter models can be used to estimate population abundance from indirect data collected by non-invasive sampling methods, such as track counts or camera-trap data. The classical Formozov–Malyshev–Pereleshin (FMP) estimator converts track counts into an estimate of mean population density, assuming that data on the daily movement distances of the animals are available. We utilize generalized linear models with spatio-temporal error structures to extend the FMP estimator into a flexible Bayesian modelling approach that estimates not only total population size, but also spatio-temporal variation in population density. We also introduce a weighting scheme to estimate density on habitats that are not covered by survey transects, assuming that movement data on a subset of individuals is available. We test the performance of spatio-temporal and temporal approaches by a simulation study mimicking the Finnish winter track count survey. The results illustrate how the spatio-temporal modelling approach is able to borrow information from observations made on neighboring locations and times when estimating population density, and that spatio-temporal and temporal smoothing models can provide improved estimates of total population size compared to the FMP method. PMID:27611683

Three-dimensional spatiotemporal focusing of holographic patterns

PubMed Central

Hernandez, Oscar; Papagiakoumou, Eirini; Tanese, Dimitrii; Fidelin, Kevin; Wyart, Claire; Emiliani, Valentina

2016-01-01

Two-photon excitation with temporally focused pulses can be combined with phase-modulation approaches, such as computer-generated holography and generalized phase contrast, to efficiently distribute light into two-dimensional, axially confined, user-defined shapes. Adding lens-phase modulations to 2D-phase holograms enables remote axial pattern displacement as well as simultaneous pattern generation in multiple distinct planes. However, the axial confinement linearly degrades with lateral shape area in previous reports where axially shifted holographic shapes were not temporally focused. Here we report an optical system using two spatial light modulators to independently control transverse- and axial-target light distribution. This approach enables simultaneous axial translation of single or multiple spatiotemporally focused patterns across the sample volume while achieving the axial confinement of temporal focusing. We use the system's capability to photoconvert tens of Kaede-expressing neurons with single-cell resolution in live zebrafish larvae. PMID:27306044

High-resolution NMR in magnetic fields with unknown spatiotemporal variations.

PubMed

Pelupessy, Philippe; Rennella, Enrico; Bodenhausen, Geoffrey

2009-06-26

Nuclear magnetic resonance (NMR) experiments are usually carried out in homogeneous magnetic fields. In many cases, however, high-resolution spectra are virtually impossible to obtain because of the inherent heterogeneity of the samples or living organisms under investigation, as well as the poor homogeneity of the magnets (particularly when bulky samples must be placed outside their bores). Unstable power supplies and vibrations arising from cooling can lead to field fluctuations in time as well as space. We show how high-resolution NMR spectra can be obtained in inhomogeneous fields with unknown spatiotemporal variations. Our method, based on coherence transfer between spins, can accommodate spatial inhomogeneities of at least 11 gauss per centimeter and temporal fluctuations slower than 2 hertz.

New type of chimera and mutual synchronization of spatiotemporal structures in two coupled ensembles of nonlocally interacting chaotic maps

NASA Astrophysics Data System (ADS)

Bukh, Andrei; Rybalova, Elena; Semenova, Nadezhda; Strelkova, Galina; Anishchenko, Vadim

2017-11-01

We study numerically the dynamics of a network made of two coupled one-dimensional ensembles of discrete-time systems. The first ensemble is represented by a ring of nonlocally coupled Henon maps and the second one by a ring of nonlocally coupled Lozi maps. We find that the network of coupled ensembles can realize all the spatio-temporal structures which are observed both in the Henon map ensemble and in the Lozi map ensemble while uncoupled. Moreover, we reveal a new type of spatiotemporal structure, a solitary state chimera, in the considered network. We also establish and describe the effect of mutual synchronization of various complex spatiotemporal patterns in the system of two coupled ensembles of Henon and Lozi maps.

Spatiotemporal variations of hydrogeochemistry and its controlling factors in the Gandaki River Basin, Central Himalaya Nepal.

PubMed

Pant, Ramesh Raj; Zhang, Fan; Rehman, Faizan Ur; Wang, Guanxing; Ye, Ming; Zeng, Chen; Tang, Handuo

2018-05-01

The characterization and assessment of water quality in the head water region of Himalaya is necessary, given the immense importance of this region in sustaining livelihoods of people and maintaining ecological balance. A total of 165 water samples were collected from 55 sites during pre-monsoon, monsoon and post-monsoon seasons in 2016 from the Gandaki River Basin of the Central Himalaya, Nepal. The pH, EC values and TDS concentrations were measured in-situ and the concentrations of major ions (Ca 2+ , Mg 2+ , K + , Na + , Cl - , SO 4 2- , NO 3 - ) and Si were analyzed in laboratory. Correlation matrices, paired t-test, cluster analysis, principal component analysis (PCA), the Piper, Gibbs, and Mixing plots, and saturation index were applied to the measurements for evaluating spatiotemporal variation of the major ions. The results reveal mildly alkaline pH values and the following pattern of average ionic dominance: Ca 2+ >Mg 2+ >Na + >K + for cations and HCO 3 - >SO 4 2 - >Cl - >NO 3 - for anions. The results of PCA, Gibbs plot and the ionic relationships displayed the predominance of geogenic weathering processes in areas with carbonate dominant lithology. This conclusion is supported by geochemically different water facies identified in the Piper plot as Ca-HCO 3 (83.03%), mixed Ca-Mg-Cl (12.73.0%) and Ca-Cl (4.24%). Pronounced spatiotemporal heterogeneity demonstrates the influence of climatic, geogenic and anthropogenic conditions. For instance, the Ca 2+ -SO 4 2- , Mg 2+ -SO 4 2- and Na + -Cl - pairs exhibit strong positive correlation with each other in the upstream region, whereas relatively weak correlation in the downstream region, likely indicating the influence of evapo-crystallization processes in the upstream region. Analyses of the suitability of the water supply for drinking and irrigation reveal that the river has mostly retained its natural water quality but poses safety concern at a few locations. Knowledge obtained through this study can contribute to the sustainable management of water quality in the climatically and lithologically distinct segments of the Himalayan river basins. Copyright © 2017 Elsevier B.V. All rights reserved.

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

Concentric superlattice pattern in dielectric barrier discharge

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

Feng, Jianyu; Dong, Lifang, E-mail: donglfhbu@163.com; Wei, Lingyan

2016-09-15

The concentric superlattice pattern with three sub-lattices is observed in the dielectric barrier discharge in air/argon for the first time. Its spatiotemporal structure investigated by an intensified charge-coupled device shows that it is an interleaving of three different sub-lattices, which are concentric-ring, concentric-framework, and concentric-dot, respectively. The images of single-frame indicate that the concentric-ring and concentric-framework are composed of individual filaments. By using the optical emission spectrum method, it is found that plasma parameters of the concentric-dot are different from those of the concentric-ring and concentric-framework. The spatiotemporal dynamics of the concentric superlattice pattern is dependent upon the effective fieldmore » of the distribution of the wall charges field and the applied field.« less

Temporal variations in early developmental decisions: an engine of forebrain evolution.

PubMed

Bielen, H; Pal, S; Tole, S; Houart, C

2017-02-01

Tight control of developmental timing is pivotal to many major processes in developmental biology, such as patterning, fate specification, cell cycle dynamics, cell migration and connectivity. Temporal change in these ontogenetic sequences is known as heterochrony, a major force in the evolution of body plans and organogenesis. In the last 5 years, studies in fish and rodents indicate that heterochrony in signaling during early development generates diversity in forebrain size and complexity. Here, we summarize these findings and propose that, additionally to spatio-temporal tuning of neurogenesis, temporal and quantitative modulation of signaling events drive pivotal changes in shape, size and complexity of the forebrain across evolution, participating to the generation of diversity in animal behavior and emergence of cognition. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cellular automata rule characterization and classification using texture descriptors

NASA Astrophysics Data System (ADS)

Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.

2018-05-01

The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.

Assessing site-specific spatio-temporal variations in hydrogen and oxygen stable isotopes of human drinking water

NASA Astrophysics Data System (ADS)

Kennedy, C. D.; Bowen, G. J.; Ehleringer, J. R.

2008-12-01

Stable isotope ratios of hydrogen and oxygen (δ2H and δ18O) are environmental forensic tracers that can be used to constrain the origin and movement of animals, people, and products. The fundamental assumption underlying this method is that water resources at different geographic locations have distinct and characteristic isotopic signatures that are assimilated into organic tissues. Although much is known about regional-scale spatio-temporal variability in δ2H and δ18O of water, few studies have addressed the question of how distinct these geographic and seasonal patterns are for any given site. To address this question, a 2-year survey of δ2H and δ18O in tap water from across the contiguous U.S. and Canada was conducted. The data show that seasonal variability in δ2H and δ18O of tap water is generally low (<10 ‰ for δ2H), and those with the highest variability can be classified as: a) cities or towns in areas of high climate seasonality, or b) large cities in arid or seasonally arid regions which access and switch among multiple water sources throughout the year. The data suggest that inter-annual variation in tap water isotope ratios is typically low, with a median difference for month-month pairs during the 2 sampling years of 2.7 (δ2H). The results from this study confirm the existence of temporal variability in δ2H and δ18O of tap water, but suggest that this variability in human-managed systems is highly damped and may be amenable to classification, modeling, and prediction. In all, the data provide the foundation for incorporating temporal variation in predictive models of water and organic δ2H and δ18O, leading to more robust and statistically defensible tests of geographic origin.

Spatially varying density dependence drives a shifting mosaic of survival in a recovering apex predator (Canis lupus).

PubMed

O'Neil, Shawn T; Bump, Joseph K; Beyer, Dean E

2017-11-01

Understanding landscape patterns in mortality risk is crucial for promoting recovery of threatened and endangered species. Humans affect mortality risk in large carnivores such as wolves ( Canis lupus ), but spatiotemporally varying density dependence can significantly influence the landscape of survival. This potentially occurs when density varies spatially and risk is unevenly distributed. We quantified spatiotemporal sources of variation in survival rates of gray wolves ( C. lupus ) during a 21-year period of population recovery in the Upper Peninsula of Michigan, USA. We focused on mapping risk across time using Cox Proportional Hazards (CPH) models with time-dependent covariates, thus exploring a shifting mosaic of survival. Extended CPH models and time-dependent covariates revealed influences of seasonality, density dependence and experience, as well as individual-level factors and landscape predictors of risk. We used results to predict the shifting landscape of risk at the beginning, middle, and end of the wolf recovery time series. Survival rates varied spatially and declined over time. Long-term change was density-dependent, with landscape predictors such as agricultural land cover and edge densities contributing negatively to survival. Survival also varied seasonally and depended on individual experience, sex, and resident versus transient status. The shifting landscape of survival suggested that increasing density contributed to greater potential for human conflict and wolf mortality risk. Long-term spatial variation in key population vital rates is largely unquantified in many threatened, endangered, and recovering species. Variation in risk may indicate potential for source-sink population dynamics, especially where individuals preemptively occupy suitable territories, which forces new individuals into riskier habitat types as density increases. We encourage managers to explore relationships between adult survival and localized changes in population density. Density-dependent risk maps can identify increasing conflict areas or potential habitat sinks which may persist due to high recruitment in adjacent habitats.

Spatio-temporal patterns of tree establishment are indicative of biotic interactions during early invasion of a montane meadow

Treesearch

J.M. Rice; C.B. Halpern; J.A. Antos; J.A. Jones

2012-01-01

Tree invasions of grasslands are occurring globally, with profound consequences for ecosystem structure and function. We explore the spatio-temporal dynamics of tree invasion of a montane meadow in the Cascade Mountains of Oregon, where meadow loss is a conservation concern. We examine the early stages of invasion, where extrinsic and intrinsic processes can be clearly...

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

PubMed Central

Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O.; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A.; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs. PMID:29136658

Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012).

PubMed

Marek, Lukáš; Tuček, Pavel; Pászto, Vít

2015-01-28

Visual analytics aims to connect the processing power of information technologies and the user's ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution. We combined the complex joint spatio-temporal analysis with comprehensive visualisation. We analysed the spatio-temporal distribution of the campylobacteriosis in the Czech Republic between 2008 and 2012. We applied three main approaches in the study: (1) the geovisual analytics of the surveillance data that were visualised in the form of bubble chart; (2) the geovisual analytics of the disease's weekly incidence surfaces computed by spatio-temporal kriging and (3) the spatio-temporal scan statistics that was employed in order to identify high or low rates clusters of affected municipalities. The final data are stored in Keyhole Markup Language files and visualised in Google Earth™ in order to apply geovisual analytics. Using geovisual analytics we were able to display and retrieve information from complex dataset efficiently. Instead of searching for patterns in a series of static maps or using numerical statistics, we created the set of interactive visualisations in order to explore and communicate results of analyses to the wider audience. The results of the geovisual analytics identified periodical patterns in the behaviour of the disease as well as fourteen spatio-temporal clusters of increased relative risk. We prove that Google Earth™ software is a usable tool for the geovisual analysis of the disease distribution. Google Earth™ has many indisputable advantages (widespread, freely available, intuitive interface, space-time visualisation capabilities and animations, communication of results), nevertheless it is still needed to combine it with pre-processing tools that prepare the data into a form suitable for the geovisual analytics itself.

Introduction to the Focus Issue: Chemo-Hydrodynamic Patterns and Instabilities

NASA Astrophysics Data System (ADS)

De Wit, A.; Eckert, K.; Kalliadasis, S.

2012-09-01

Pattern forming instabilities are often encountered in a wide variety of natural phenomena and technological applications, from self-organization in biological and chemical systems to oceanic or atmospheric circulation and heat and mass transport processes in engineering systems. Spatio-temporal structures are ubiquitous in hydrodynamics where numerous different convective instabilities generate pattern formation and complex spatiotemporal dynamics, which have been much studied both theoretically and experimentally. In parallel, reaction-diffusion processes provide another large family of pattern forming instabilities and spatio-temporal structures which have been analyzed for several decades. At the intersection of these two fields, "chemo-hydrodynamic patterns and instabilities" resulting from the coupling of hydrodynamic and reaction-diffusion processes have been less studied. The exploration of the new instability and symmetry-breaking scenarios emerging from the interplay between chemical reactions, diffusion and convective motions is a burgeoning field in which numerous exciting problems have emerged during the last few years. These problems range from fingering instabilities of chemical fronts and reactive fluid-fluid interfaces to the dynamics of reaction-diffusion systems in the presence of chaotic mixing. The questions to be addressed are at the interface of hydrodynamics, chemistry, engineering or environmental sciences to name a few and, as a consequence, they have started to draw the attention of several communities including both the nonlinear chemical dynamics and hydrodynamics communities. The collection of papers gathered in this Focus Issue sheds new light on a wide range of phenomena in the general area of chemo-hydrodynamic patterns and instabilities. It also serves as an overview of the current research and state-of-the-art in the field.

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

Low-dose 4D cone-beam CT via joint spatiotemporal regularization of tensor framelet and nonlocal total variation

NASA Astrophysics Data System (ADS)

Han, Hao; Gao, Hao; Xing, Lei

2017-08-01

Excessive radiation exposure is still a major concern in 4D cone-beam computed tomography (4D-CBCT) due to its prolonged scanning duration. Radiation dose can be effectively reduced by either under-sampling the x-ray projections or reducing the x-ray flux. However, 4D-CBCT reconstruction under such low-dose protocols is prone to image artifacts and noise. In this work, we propose a novel joint regularization-based iterative reconstruction method for low-dose 4D-CBCT. To tackle the under-sampling problem, we employ spatiotemporal tensor framelet (STF) regularization to take advantage of the spatiotemporal coherence of the patient anatomy in 4D images. To simultaneously suppress the image noise caused by photon starvation, we also incorporate spatiotemporal nonlocal total variation (SNTV) regularization to make use of the nonlocal self-recursiveness of anatomical structures in the spatial and temporal domains. Under the joint STF-SNTV regularization, the proposed iterative reconstruction approach is evaluated first using two digital phantoms and then using physical experiment data in the low-dose context of both under-sampled and noisy projections. Compared with existing approaches via either STF or SNTV regularization alone, the presented hybrid approach achieves improved image quality, and is particularly effective for the reconstruction of low-dose 4D-CBCT data that are not only sparse but noisy.

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

Wang, Jiali; Swati, F. N. U.; Stein, Michael L.

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, andmore » time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.« less

Acute differences in foot strike and spatiotemporal variables for shod, barefoot or minimalist male runners.

PubMed

McCallion, Ciara; Donne, Bernard; Fleming, Neil; Blanksby, Brian

2014-05-01

This study compared stride length, stride frequency, contact time, flight time and foot-strike patterns (FSP) when running barefoot, and in minimalist and conventional running shoes. Habitually shod male athletes (n = 14; age 25 ± 6 yr; competitive running experience 8 ± 3 yr) completed a randomised order of 6 by 4-min treadmill runs at velocities (V1 and V2) equivalent to 70 and 85% of best 5-km race time, in the three conditions. Synchronous recording of 3-D joint kinematics and ground reaction force data examined spatiotemporal variables and FSP. Most participants adopted a mid-foot strike pattern, regardless of condition. Heel-toe latency was less at V2 than V1 (-6 ± 20 vs. -1 ± 13 ms, p < 0.05), which indicated a velocity related shift towards a more FFS pattern. Stride duration and flight time, when shod and in minimalist footwear, were greater than barefoot (713 ± 48 and 701 ± 49 vs. 679 ± 56 ms, p < 0.001; and 502 ± 45 and 503 ± 41 vs. 488 ±4 9 ms, p < 0.05, respectively). Contact time was significantly longer when running shod than barefoot or in minimalist footwear (211±30 vs. 191 ± 29 ms and 198 ± 33 ms, p < 0.001). When running barefoot, stride frequency was significantly higher (p < 0.001) than in conventional and minimalist footwear (89 ± 7 vs. 85 ± 6 and 86 ± 6 strides·min(-1)). In conclusion, differences in spatiotemporal variables occurred within a single running session, irrespective of barefoot running experience, and, without a detectable change in FSP. Key pointsDifferences in spatiotemporal variables occurred within a single running session, without a change in foot strike pattern.Stride duration and flight time were greater when shod and in minimalist footwear than when barefoot.Stride frequency when barefoot was higher than when shod or in minimalist footwear.Contact time when shod was longer than when barefoot or in minimalist footwear.Spatiotemporal variables when running in minimalist footwear more closely resemble shod than barefoot running.

Acute Differences in Foot Strike and Spatiotemporal Variables for Shod, Barefoot or Minimalist Male Runners

PubMed Central

McCallion, Ciara; Donne, Bernard; Fleming, Neil; Blanksby, Brian

2014-01-01

This study compared stride length, stride frequency, contact time, flight time and foot-strike patterns (FSP) when running barefoot, and in minimalist and conventional running shoes. Habitually shod male athletes (n = 14; age 25 ± 6 yr; competitive running experience 8 ± 3 yr) completed a randomised order of 6 by 4-min treadmill runs at velocities (V1 and V2) equivalent to 70 and 85% of best 5-km race time, in the three conditions. Synchronous recording of 3-D joint kinematics and ground reaction force data examined spatiotemporal variables and FSP. Most participants adopted a mid-foot strike pattern, regardless of condition. Heel-toe latency was less at V2 than V1 (-6 ± 20 vs. -1 ± 13 ms, p < 0.05), which indicated a velocity related shift towards a more FFS pattern. Stride duration and flight time, when shod and in minimalist footwear, were greater than barefoot (713 ± 48 and 701 ± 49 vs. 679 ± 56 ms, p < 0.001; and 502 ± 45 and 503 ± 41 vs. 488 ±4 9 ms, p < 0.05, respectively). Contact time was significantly longer when running shod than barefoot or in minimalist footwear (211±30 vs. 191 ± 29 ms and 198 ± 33 ms, p < 0.001). When running barefoot, stride frequency was significantly higher (p < 0.001) than in conventional and minimalist footwear (89 ± 7 vs. 85 ± 6 and 86 ± 6 strides·min-1). In conclusion, differences in spatiotemporal variables occurred within a single running session, irrespective of barefoot running experience, and, without a detectable change in FSP. Key points Differences in spatiotemporal variables occurred within a single running session, without a change in foot strike pattern. Stride duration and flight time were greater when shod and in minimalist footwear than when barefoot. Stride frequency when barefoot was higher than when shod or in minimalist footwear. Contact time when shod was longer than when barefoot or in minimalist footwear. Spatiotemporal variables when running in minimalist footwear more closely resemble shod than barefoot running. PMID:24790480

The statistics of local motion signals in naturalistic movies

PubMed Central

Nitzany, Eyal I.; Victor, Jonathan D.

2014-01-01

Extraction of motion from visual input plays an important role in many visual tasks, such as separation of figure from ground and navigation through space. Several kinds of local motion signals have been distinguished based on mathematical and computational considerations (e.g., motion based on spatiotemporal correlation of luminance, and motion based on spatiotemporal correlation of flicker), but little is known about the prevalence of these different kinds of signals in the real world. To address this question, we first note that different kinds of local motion signals (e.g., Fourier, non-Fourier, and glider) are characterized by second- and higher-order correlations in slanted spatiotemporal regions. The prevalence of local motion signals in natural scenes can thus be estimated by measuring the extent to which each of these correlations are present in space-time patches and whether they are coherent across spatiotemporal scales. We apply this technique to several popular movies. The results show that all three kinds of local motion signals are present in natural movies. While the balance of the different kinds of motion signals varies from segment to segment during the course of each movie, the overall pattern of prevalence of the different kinds of motion and their subtypes, and the correlations between them, is strikingly similar across movies (but is absent from white noise movies). In sum, naturalistic movies contain a diversity of local motion signals that occur with a consistent prevalence and pattern of covariation, indicating a substantial regularity of their high-order spatiotemporal image statistics. PMID:24732243

The statistics of local motion signals in naturalistic movies.

PubMed

Nitzany, Eyal I; Victor, Jonathan D

2014-04-14

Extraction of motion from visual input plays an important role in many visual tasks, such as separation of figure from ground and navigation through space. Several kinds of local motion signals have been distinguished based on mathematical and computational considerations (e.g., motion based on spatiotemporal correlation of luminance, and motion based on spatiotemporal correlation of flicker), but little is known about the prevalence of these different kinds of signals in the real world. To address this question, we first note that different kinds of local motion signals (e.g., Fourier, non-Fourier, and glider) are characterized by second- and higher-order correlations in slanted spatiotemporal regions. The prevalence of local motion signals in natural scenes can thus be estimated by measuring the extent to which each of these correlations are present in space-time patches and whether they are coherent across spatiotemporal scales. We apply this technique to several popular movies. The results show that all three kinds of local motion signals are present in natural movies. While the balance of the different kinds of motion signals varies from segment to segment during the course of each movie, the overall pattern of prevalence of the different kinds of motion and their subtypes, and the correlations between them, is strikingly similar across movies (but is absent from white noise movies). In sum, naturalistic movies contain a diversity of local motion signals that occur with a consistent prevalence and pattern of covariation, indicating a substantial regularity of their high-order spatiotemporal image statistics.

Simulations of Western North American Hydroclimate during the Little Ice Age and Medieval Climate Anomaly

NASA Astrophysics Data System (ADS)

Simon, S. M.; Mann, M. E.; Steinman, B. A.; Feng, S.; Zhang, Y.; Miller, S. K.

2013-12-01

Despite the immense impact that large, modern North American droughts, such as those of the 1930s and 1950s, have had on economic, social, aquacultural, and agricultural systems, they are smaller in duration and magnitude than the multidecadal megadroughts that affected North America, in particular the western United States, during the Medieval Climate Anomaly (MCA, ~ 900-1300 AD) and the Little Age (LIA, ~1450-1850 AD). Although various proxy records have been used to reconstruct the timing of these MCA and LIA megadroughts in the western United States, there still exists great uncertainty in the magnitude and spatial coherence of such droughts in the Pacific Northwest region, especially on decadal to centennial timescales. This uncertainty motivates the following study to establish a causal link between the climate forcing that induced these megadroughts and the spatiotemporal response of regional North American hydroclimates to this forcing. This study seeks to establish a better understanding of the influence of tropical Pacific and North Atlantic SSTs on North American drought during the MCA and LIA. We force NCAR's Community Atmospheric Model version 5.1.1 (CAM 5) with prescribed proxy-reconstructed tropical Pacific and North Atlantic SST anomalies from the MCA and LIA, in order to investigate the influence that these SST anomalies had on the spatiotemporal patterns of drought in North America. To isolate the effects of individual ocean basin SSTs on the North American climate system, the model experiments use a variety of SST permutations in the tropical Pacific and North Atlantic basin as external forcing. In order to quantify the spatiotemporal response of the North American climate system to these SST forcing permutations, temperature and precipitation data derived from the MCA and LIA model experiments are compared to lake sediment isotope and tree ring-based hydroclimate reconstructions from the Pacific Northwest. The spatiotemporal temperature and precipitation patterns from the model experiments indicate that in the Pacific Northwest, the MCA and LIA were anomalously wet and dry periods, respectively, a finding that is largely supported by the lake sediment records. This pattern contrasts with the dry MCA/wet LIA pattern diagnosed in model experiments for the U.S Southwest and indicated by tree ring-based proxy data. Thus, the CAM 5 model experiments confirm the wet/dry dipole pattern suggested by proxy data for the western U.S. during the MCA and LIA and highlights the role that the natural variability of tropical Pacific and North Atlantic SSTs played in driving this spatiotemporal climate pattern and its related teleconnections.

Spatio-temporal visualization of air-sea CO2 flux and carbon budget using volume rendering

NASA Astrophysics Data System (ADS)

Du, Zhenhong; Fang, Lei; Bai, Yan; Zhang, Feng; Liu, Renyi

2015-04-01

This paper presents a novel visualization method to show the spatio-temporal dynamics of carbon sinks and sources, and carbon fluxes in the ocean carbon cycle. The air-sea carbon budget and its process of accumulation are demonstrated in the spatial dimension, while the distribution pattern and variation of CO2 flux are expressed by color changes. In this way, we unite spatial and temporal characteristics of satellite data through visualization. A GPU-based direct volume rendering technique using half-angle slicing is adopted to dynamically visualize the released or absorbed CO2 gas with shadow effects. A data model is designed to generate four-dimensional (4D) data from satellite-derived air-sea CO2 flux products, and an out-of-core scheduling strategy is also proposed for on-the-fly rendering of time series of satellite data. The presented 4D visualization method is implemented on graphics cards with vertex, geometry and fragment shaders. It provides a visually realistic simulation and user interaction for real-time rendering. This approach has been integrated into the Information System of Ocean Satellite Monitoring for Air-sea CO2 Flux (IssCO2) for the research and assessment of air-sea CO2 flux in the China Seas.

Spatio-temporal distribution of net-collected phytoplankton community and its response to marine exploitation in Xiangshan Bay

NASA Astrophysics Data System (ADS)

Jiang, Zhibing; Zhu, Xuyu; Gao, Yu; Chen, Quanzhen; Zeng, Jiangning; Zhu, Genhai

2013-07-01

To explore the spatial-temporal distribution of the phytoplankton community and evaluate the combined effects of marine resource exploitation, net-collected phytoplankton and physical-chemical parameters were investigated in the Xiangshan Bay during the four seasons of 2010. A total of eight phyla, 97 genera, and 310 species were found, including 232 diatom species, 45 dinoflagellate species and 33 other taxa. The phytoplankton abundances presented a significant ( P<0.001) seasonal difference with the average of 60.66×104 cells/m3. Diatoms (mainly consisting of Coscinodiscus jonesianus, Cerataulina pelagica, Skeleto n ema costatum, and genus Chaetoceros) dominated the phytoplankton assemblage in all seasons. We found great spatio-temporal variation in community composition based on the multidimensional scaling and similarity analysis. Canonical correspondence analysis show that temperature, nutrition, illumination, and salinity were the main variables associated with microalgal assemblage. Compared with the previous studies, an increase in phytoplankton abundance and change in the dominant species coincided with increased exploitation activities in this bay (e.g. operation of coastal power plants, intensive mariculture, tidal flat reclamation, and industrial and agricultural development). The present findings suggest that the government should exercise caution when deciding upon developmental patterns in the sea-related economy.

Spatiotemporal Patterns and its Instability of Land Use Change in Five Chinese Node Cities of the Belt and Road

NASA Astrophysics Data System (ADS)

Quan, B.; Guo, T.; Liu, P. L.; Ren, H. G.

2017-09-01

It has long recognized that there exists three different terrain belt in China, i.e. east, central, and west can have very different impacts on the land use changes. It is therefore better understand how spatiotemporal patterns linked with processes and instability of land use change are evolving in China across different regions. This paper compares trends of the similarities and differences to understand the spatiotemporal characteristics and the linked processes i.e. states, incidents and instability of land use change of 5 Chinese cities which are located in the nodes of The Silk Road in China. The results show that on the whole, the more land transfer times and the more land categories involved changes happens in Quanzhou City, one of eastern China than those in central and western China. Basically, cities in central and western China such as Changsha, Kunming and Urumuqi City become instable while eastern city like Quanzhou City turns to be stable over time.

Electric organ discharges and near-field spatiotemporal patterns of the electromotive force in a sympatric assemblage of Neotropical electric knifefish.

PubMed

Waddell, Joseph C; Rodríguez-Cattáneo, Alejo; Caputi, Angel A; Crampton, William G R

2016-10-01

Descriptions of the head-to-tail electric organ discharge (ht-EOD) waveform - typically recorded with electrodes at a distance of approximately 1-2 body lengths from the center of the subject - have traditionally been used to characterize species diversity in gymnotiform electric fish. However, even taxa with relatively simple ht-EODs show spatiotemporally complex fields near the body surface that are determined by site-specific electrogenic properties of the electric organ and electric filtering properties of adjacent tissues and skin. In Brachyhypopomus, a pulse-discharging genus in the family Hypopomidae, the regional characteristics of the electric organ and the role that the complex 'near field' plays in communication and/or electrolocation are not well known. Here we describe, compare, and discuss the functional significance of diversity in the ht-EOD waveforms and near-field spatiotemporal patterns of the electromotive force (emf-EODs) among a species-rich sympatric community of Brachyhypopomus from the upper Amazon. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chimera states in spatiotemporal systems: Theory and Applications

NASA Astrophysics Data System (ADS)

Yao, Nan; Zheng, Zhigang

2016-03-01

In this paper, we propose a retrospective and summary on recent studies of chimera states. Chimera states demonstrate striking inhomogeneous spatiotemporal patterns emerging in homogeneous systems through unexpected spontaneous symmetry breaking, where the consequent spatiotemporal patterns are composed of both coherence and incoherence domains, respectively characterized by the synchronized and desynchronized motions of oscillators. Since the discovery of chimera states by Kuramoto and others, this striking collective behavior has attracted a great deal of research interest in the community of physics and related interdisciplinary fields from both theoretical and experimental viewpoints. In recent works exploring chimera states, rich phenomena such as the spiral wave chimera, multiple cluster chimera, amplitude chimera were observed from various types of model systems. Theoretical framework by means of self-consistency approach and Ott-Antonsen approach were proposed for further understanding to this symmetry-breaking-induced behavior. The stability and robustness of chimera states were also discussed. More importantly, experiments ranging from optical, chemical to mechanical designs successfully approve the existence of chimera states.

Discovering Coherent Structures Using Local Causal States

NASA Astrophysics Data System (ADS)

Rupe, Adam; Crutchfield, James P.; Kashinath, Karthik; Prabhat, Mr.

2017-11-01

Coherent structures were introduced in the study of fluid dynamics and were initially defined as regions characterized by high levels of coherent vorticity, i.e. regions where instantaneously space and phase correlated vorticity are high. In a more general spatiotemporal setting, coherent structures can be seen as localized broken symmetries which persist in time. Building off the computational mechanics framework, which integrates tools from computation and information theory to capture pattern and structure in nonlinear dynamical systems, we introduce a theory of coherent structures, in the more general sense. Central to computational mechanics is the causal equivalence relation, and a local spatiotemporal generalization of it is used to construct the local causal states, which are utilized to uncover a system's spatiotemporal symmetries. Coherent structures are then identified as persistent, localized deviations from these symmetries. We illustrate how novel patterns and structures can be discovered in cellular automata and outline the path from them to laminar, transitional and turbulent flows. Funded by Intel through the Big Data Center at LBNL and the IPCC at UC Davis.

Energy prediction using spatiotemporal pattern networks

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

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated bymore » the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.« less

Violence in the prehistoric period of Japan: the spatio-temporal pattern of skeletal evidence for violence in the Jomon period.

PubMed

Nakao, Hisashi; Tamura, Kohei; Arimatsu, Yui; Nakagawa, Tomomi; Matsumoto, Naoko; Matsugi, Takehiko

2016-03-01

Whether man is predisposed to lethal violence, ranging from homicide to warfare, and how that may have impacted human evolution, are among the most controversial topics of debate on human evolution. Although recent studies on the evolution of warfare have been based on various archaeological and ethnographic data, they have reported mixed results: it is unclear whether or not warfare among prehistoric hunter-gatherers was common enough to be a component of human nature and a selective pressure for the evolution of human behaviour. This paper reports the mortality attributable to violence, and the spatio-temporal pattern of violence thus shown among ancient hunter-gatherers using skeletal evidence in prehistoric Japan (the Jomon period: 13 000 cal BC-800 cal BC). Our results suggest that the mortality due to violence was low and spatio-temporally highly restricted in the Jomon period, which implies that violence including warfare in prehistoric Japan was not common. © 2016 The Author(s).

Violence in the prehistoric period of Japan: the spatio-temporal pattern of skeletal evidence for violence in the Jomon period

PubMed Central

Nakao, Hisashi; Tamura, Kohei; Arimatsu, Yui; Nakagawa, Tomomi; Matsumoto, Naoko; Matsugi, Takehiko

2016-01-01

Whether man is predisposed to lethal violence, ranging from homicide to warfare, and how that may have impacted human evolution, are among the most controversial topics of debate on human evolution. Although recent studies on the evolution of warfare have been based on various archaeological and ethnographic data, they have reported mixed results: it is unclear whether or not warfare among prehistoric hunter–gatherers was common enough to be a component of human nature and a selective pressure for the evolution of human behaviour. This paper reports the mortality attributable to violence, and the spatio-temporal pattern of violence thus shown among ancient hunter–gatherers using skeletal evidence in prehistoric Japan (the Jomon period: 13 000 cal BC–800 cal BC). Our results suggest that the mortality due to violence was low and spatio-temporally highly restricted in the Jomon period, which implies that violence including warfare in prehistoric Japan was not common. PMID:27029838

Early-warning signals for catastrophic soil degradation

NASA Astrophysics Data System (ADS)

Karssenberg, Derek

2010-05-01

Many earth systems have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been described, among others, for climate, vegetation, animal populations, and geomorphology. Predicting the timing of critical transitions before they are reached is of importance because of the large impact on nature and society associated with the transition. However, it is notably difficult to predict the timing of a transition. This is because the state variables of the system show little change before the threshold is reached. As a result, the precision of field observations is often too low to provide predictions of the timing of a transition. A possible solution is the use of spatio-temporal patterns in state variables as leading indicators of a transition. It is becoming clear that the critically slowing down of a system causes spatio-temporal autocorrelation and variance to increase before the transition. Thus, spatio-temporal patterns are important candidates for early-warning signals. In this research we will show that these early-warning signals also exist in geomorphological systems. We consider a modelled vegetation-soil system under a gradually increasing grazing pressure causing an abrupt shift towards extensive soil degradation. It is shown that changes in spatio-temporal patterns occur well ahead of this catastrophic transition. A distributed model describing the coupled processes of vegetation growth and geomorphological denudation is adapted. The model uses well-studied simple process representations for vegetation and geomorphology. A logistic growth model calculates vegetation cover as a function of grazing pressure and vegetation growth rate. Evolution of the soil thickness is modelled by soil creep and wash processes, as a function of net rain reaching the surface. The vegetation and soil system are coupled by 1) decreasing vegetation growth with decreasing soil thickness and 2) increasing soil wash with decreasing vegetation cover. The model describes a critical, catastrophic transition of an underexploited system with low grazing pressure towards an overexploited system. The underexploited state has high vegetation cover and well developed soils, while the overexploited state has low vegetation cover and largely degraded soils. We first show why spatio-temporal patterns in vegetation cover, morphology, erosion rate, and sediment load should be expected to change well before the critical transition towards the overexploited state. Subsequently, spatio-temporal patterns are quantified by calculating statistics, in particular first order statistics and autocorrelation in space and time. It is shown that these statistics gradually change before the transition is reached. This indicates that the statistics may serve as early-warning signals in real-world applications. We also discuss the potential use of remote sensing to predict the critical transition in real-world landscapes.

Exploiting temporal variability to understand tree recruitment response to climate change

Treesearch

Ines Ibanez; James S. Clark; Shannon LaDeau; Janneke Hill Ris Lambers

2007-01-01

Predicting vegetation shifts under climate change is a challenging endeavor, given the complex interactions between biotic and abiotic variables that influence demographic rates. To determine how current trends and variation in climate change affect seedling establishment, we analyzed demographic responses to spatiotemporal variation to temperature and soil moisture in...

[Spatiotemporal variation of vegetation in northern Shaanxi of Northwest China based on SPOT-VGT NDVI].

PubMed

Yang, Yan-Zheng; Zhao, Peng-Xiang; Hao, Hong-Ke; Chang, Ming

2012-07-01

By using 1998-2010 SPOT-VGT NDVI images, this paper analyzed the spatiotemporal variation of vegetation in northern Shaanxi. In 1998-2010, the NDVI in northern Shaanxi had an obvious seasonal variation. The average monthly NDVI was the minimum (0.14) in January and the maximum (0.46) in August, with a mean value of 0.28. The average annual NDVI presented an overall increasing trend, indicating that the vegetation in this area was in restoring. Spatially, the restoration of vegetation in this area was concentrated in central south part, and the degradation mainly occurred in the north of the Great Wall. Air temperature and precipitation were the important climate factors affecting the variation of vegetation, with the linear correlation coefficients to NDVI being 0.72 and 0.58, respectively. The regions with better restored vegetation were mainly on the slopes of 15 degrees-25 degrees, indicating that the Program of Conversion of Cropland to Forestland and Grassland had a favorable effect in the vegetation restoration in northern Shaanxi.

Predictive Feedback Can Account for Biphasic Responses in the Lateral Geniculate Nucleus

PubMed Central

Jehee, Janneke F. M.; Ballard, Dana H.

2009-01-01

Biphasic neural response properties, where the optimal stimulus for driving a neural response changes from one stimulus pattern to the opposite stimulus pattern over short periods of time, have been described in several visual areas, including lateral geniculate nucleus (LGN), primary visual cortex (V1), and middle temporal area (MT). We describe a hierarchical model of predictive coding and simulations that capture these temporal variations in neuronal response properties. We focus on the LGN-V1 circuit and find that after training on natural images the model exhibits the brain's LGN-V1 connectivity structure, in which the structure of V1 receptive fields is linked to the spatial alignment and properties of center-surround cells in the LGN. In addition, the spatio-temporal response profile of LGN model neurons is biphasic in structure, resembling the biphasic response structure of neurons in cat LGN. Moreover, the model displays a specific pattern of influence of feedback, where LGN receptive fields that are aligned over a simple cell receptive field zone of the same polarity decrease their responses while neurons of opposite polarity increase their responses with feedback. This phase-reversed pattern of influence was recently observed in neurophysiology. These results corroborate the idea that predictive feedback is a general coding strategy in the brain. PMID:19412529

Spatiotemporal Variations in Chronic Obstructive Pulmonary Disease Mortality in China: Multilevel Evidence from 2006 to 2012.

PubMed

Yin, Peng; Feng, Xiaoqi; Astell-Burt, Thomas; Qi, Fei; Liu, Yunning; Liu, Jiangmei; Page, Andrew; Wang, Limin; Liu, Shiwei; Wang, Lijun; Zhou, Maigeng

2016-06-01

Mortality of Chronic Obstructive Pulmonary Disease (COPD) is on the decline in China. It is not known if this trend occurs across all areas or whether spatiotemporal variations manifest. We used data from the nationally representative China Mortality Surveillance System to calculate annual COPD mortality counts (2006-2012) stratified by 5-year age groups (aged > 20), gender and time for 161 counties and districts (Disease Surveillance Points, or DSP). These counts were linked to annually adjusted denominator populations. Multilevel negative binomial regression with random intercepts and slopes were used to investigate spatiotemporal variation in COPD mortality adjusting for age, gender and area-level risk factors. COPD mortality rate decreased markedly from 105.1 to 73.7 per 100,000 during 2006 to 2012 and varied over two-fold between DSPs across China. Mortality rates were higher in the west compared with the east (Rate ratio (RR) 2.15, 95% confidence intervals (CI) 1.73, 2.68) and in rural compared with the urban (RR 1.87, 95% CI 1.55, 2.25). Adjustment for age, gender, urban/rural, region, smoking prevalence, indoor air pollution, mean body mass index and socioeconomic circumstances accounted for 67% of the geographical variation. Urban/rural differences in COPD mortality narrowed over time, but the magnitude of the east-west inequality persisted without change. Immediate action via large-scale interventions to enhance the prevention and management of COPD are needed specifically within China's western region in order to tackle this crucial health inequality and leading preventable cause of death.

Leaders and followers: quantifying consistency in spatio-temporal propagation patterns

NASA Astrophysics Data System (ADS)

Kreuz, Thomas; Satuvuori, Eero; Pofahl, Martin; Mulansky, Mario

2017-04-01

Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are called a synfire pattern. For any recording of sequences of discrete events (in neuroscience terminology: sets of spike trains) the questions arise how closely it resembles such a synfire pattern and which are the spike trains that lead/follow. Here we address these questions and introduce an algorithm built on two new indicators, termed SPIKE-order and spike train order, that define the synfire indicator value, which allows to sort multiple spike trains from leader to follower and to quantify the consistency of the temporal leader-follower relationships for both the original and the optimized sorting. We demonstrate our new approach using artificially generated datasets before we apply it to analyze the consistency of propagation patterns in two real datasets from neuroscience (giant depolarized potentials in mice slices) and climatology (El Niño sea surface temperature recordings). The new algorithm is distinguished by conceptual and practical simplicity, low computational cost, as well as flexibility and universality.

Between giant oscillations and uniform distribution of droplets: The role of varying lumen of channels in microfluidic networks.

PubMed

Cybulski, Olgierd; Jakiela, Slawomir; Garstecki, Piotr

2015-12-01

The simplest microfluidic network (a loop) comprises two parallel channels with a common inlet and a common outlet. Recent studies that assumed a constant cross section of the channels along their length have shown that the sequence of droplets entering the left (L) or right (R) arm of the loop can present either a uniform distribution of choices (e.g., RLRLRL...) or long sequences of repeated choices (RRR...LLL), with all the intermediate permutations being dynamically equivalent and virtually equally probable to be observed. We use experiments and computer simulations to show that even small variation of the cross section along channels completely shifts the dynamics either into the strong preference for highly grouped patterns (RRR...LLL) that generate system-size oscillations in flow or just the opposite-to patterns that distribute the droplets homogeneously between the arms of the loop. We also show the importance of noise in the process of self-organization of the spatiotemporal patterns of droplets. Our results provide guidelines for rational design of systems that reproducibly produce either grouped or homogeneous sequences of droplets flowing in microfluidic networks.

Late Quaternary variations in relative sea level due to glacial cycle polar wander

USGS Publications Warehouse

Bills, B.G.; James, T.S.

1996-01-01

Growth and decay of continental ice sheets can excite significant motion of the Earth's rotation pole and cause a complex spatio-temporal pattern of changes in relative sea level. These two effects have generally been considered separately, but may interact in important ways. In particular, a simple model of the melting of the Laurentide ice sheet causes a uniform eustatic sea level rise of 55 m, and also induces a motion of the rotation pole by 0.1 to 1 degree, depending on viscosity structure in the mantle. This motion produces a secular pole tide, which is a spherical harmonic degree 2, order 1 component of the relative sea level pattern, with peak-to-peak amplitude of 20 to 40 m. The maximum effect is along the great circle passing through the path of the pole and at latitudes of ??45??. This secular pole tide has been ignored in most previous attempts to estimate ice sheet loading history and mantle viscosity from global patterns of relative sea level change. It has a large influence along the East coast of North America and the West coast of South America, and significantly contributes to present day rates of relative sea level change.

Modelling Delta-Notch perturbations during zebrafish somitogenesis.

PubMed

Murray, Philip J; Maini, Philip K; Baker, Ruth E

2013-01-15

The discovery over the last 15 years of molecular clocks and gradients in the pre-somitic mesoderm of numerous vertebrate species has added significant weight to Cooke and Zeeman's 'clock and wavefront' model of somitogenesis, in which a travelling wavefront determines the spatial position of somite formation and the somitogenesis clock controls periodicity (Cooke and Zeeman, 1976). However, recent high-throughput measurements of spatiotemporal patterns of gene expression in different zebrafish mutant backgrounds allow further quantitative evaluation of the clock and wavefront hypothesis. In this study we describe how our recently proposed model, in which oscillator coupling drives the propagation of an emergent wavefront, can be used to provide mechanistic and testable explanations for the following observed phenomena in zebrafish embryos: (a) the variation in somite measurements across a number of zebrafish mutants; (b) the delayed formation of somites and the formation of 'salt and pepper' patterns of gene expression upon disruption of oscillator coupling; and (c) spatial correlations in the 'salt and pepper' patterns in Delta-Notch mutants. In light of our results, we propose a number of plausible experiments that could be used to further test the model. Copyright © 2012 Elsevier Inc. All rights reserved.

Occurrence, spatiotemporal distribution, and ecological risks of steroids in a large shallow Chinese lake, Lake Taihu.

PubMed

Zhou, Li-Jun; Zhang, Bei-Bei; Zhao, Yong-Gang; Wu, Qinglong L

2016-07-01

Steroids have been frequently detected in surface waters, and might pose adverse effects on aquatic organisms. However, little information is available regarding the occurrence and spatiotemporal distribution of steroids in lake environments. In addition to pollution sources, the occurrence and spatiotemporal distribution of steroids in lake environments might be related to lake types (shallow or deep), lake hydrodynamics, and sorption-desorption processes in the water-sediment systems. In this study, the occurrence, spatiotemporal distribution, and ecological risks of 36 steroids in a large shallow lake were evaluated by investigating surface water and sediment samples at 32 sites in Lake Taihu over two seasons. Twelve and 15 analytes were detected in aqueous and sedimentary phases, respectively, with total concentrations ranging from 0.86 to 116ng/L (water) and from 0.82 to 16.2ng/g (sediment, dry weight). Temporal variations of steroid concentrations in the water and sediments were statistically significant, with higher concentrations in winter. High concentrations of steroids were found in the seriously polluted bays rather than in the pelagic zone of the lake. Strong lake currents might mix pelagic waters, resulting in similar concentrations of steroids in the pelagic zone. Mass balance analysis showed that sediments in shallow lakes are in general an important sink for steroids. Steroids in the surface water and sediments of Lake Taihu might pose potential risks to aquatic organisms. Overall, our study indicated that the concentrations and spatiotemporal distribution of steroids in the large shallow lake are influenced simultaneously by pollution sources and lake hydrodynamics. Steroids in the large shallow Lake Taihu showed clear temporal and spatial variations and lake sediments may be a potential sink of steroids. Copyright © 2016 Elsevier B.V. All rights reserved.

Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010.

PubMed

Yang, Yuting; Guan, Huade; Shen, Miaogen; Liang, Wei; Jiang, Lei

2015-02-01

Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date (DOD) and its climate controls over temperate China were examined by analysing the satellite-derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over China's temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29-year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature-driven phenological models. © 2014 John Wiley & Sons Ltd.

Numerical Study on Interdecadal Modulations of ENSO-related Spring Rainfall over South China by the Pacific Decadal Oscillation

NASA Astrophysics Data System (ADS)

MAO, J.; WU, X.

2017-12-01

The spatio-temporal variations of eastern China spring rainfall are identified via empirical orthogonal function (EOF) analysis of rain-gauge (gridded) precipitation datasets for the period 1958-2013 (1920-2013). The interannual variations of the first two leading EOF modes are linked with the El Niño-Southern Oscillation (ENSO), with this linkage being modulated by the Pacific Decadal Oscillation (PDO). The EOF1 mode, characterized by predominant rainfall anomalies from the Yangtze River to North China (YNC), is more likely associated with out-of-phase PDO-ENSO events [i.e., El Niño during cold PDO (EN_CPDO) and La Niña during warm PDO (LN_WPDO)]. The sea surface temperature anomaly (SSTA) distributions of EN_CPDO (LN_WPDO) events induce a significant anomalous anticyclone (cyclone) over the western North Pacific stretching northwards to the Korean Peninsula and southern Japan, resulting in anomalous southwesterlies (northeasterlies) prevailing over eastern China and above-normal (below-normal) rainfall over YNC. In contrast, EOF2 exhibits a dipole pattern with predominantly positive rainfall anomalies over southern China along with negative anomalies over YNC, which is more likely connected to in-phase PDO-ENSO events [i.e., El Niño during warm PDO (EN_WPDO) and La Niña during cold PDO (LN_CPDO)]. EN_WPDO (LN_CPDO) events force a southwest-northeast oriented dipole-like circulation pattern leading to significant anomalous southwesterlies (northeasterlies) and above-normal (below-normal) rainfall over southern China. Numerical experiments with the CAM5 model forced by the SSTA patterns of EN_WPDO and EN_CPDO events reproduce reasonably well the corresponding anomalous atmospheric circulation patterns and spring rainfall modes over eastern China, validating the related mechanisms.

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Pyle, Ryan; Rosenbaum, Robert

2017-01-01

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

Spatio-Temporal Change Modeling of Lulc: a Semantic Kriging Approach

NASA Astrophysics Data System (ADS)

Bhattacharjee, S.; Ghosh, S. K.

2015-07-01

Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

Earth Observation for monitoring phenology for european land use and ecosystems over 1998-2011

NASA Astrophysics Data System (ADS)

Ceccherini, Guido; Gobron, Nadine

2013-04-01

Long-term measurements of plant phenology have been used to track vegetation responses to climate change but are often limited to particular species and locations and may not represent synoptic patterns. Given the limitations of working directly with in-situ data, many researchers have instead used available satellite remote sensing. Remote sensing extends the possible spatial coverage and temporal range of phenological assessments of environmental change due to the greater availability of observations. Variations and trends of vegetation dynamics are important because they alter the surface carbon, water and energy balance. For example, the net ecosystem CO2 exchange of vegetation is strongly linked to length of the growing season: extentions and decreases in length of growing season modify carbon uptake and the amount of CO2 in the atmosphere. Advances and delays in starting of growing season also affect the surface energy balance and consequently transpiration. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a key climate variable identified by Global Terrestrial Observing System (GTOS) that can be monitored from space. This dimensionless variable - varying between 0 and 1- is directly linked to the photosynthetic activity of vegetation, and therefore, can monitor changes in phenology. In this study, we identify the spatio/temporal patterns of vegetation dynamics using a long-term remotely sensed FAPAR dataset over Europe. Our aim is to provide a quantitative analysis of vegetation dynamics relevant to climate studies in Europe. As part of this analysis, six vegetation phenological metrics have been defined and made routinely in Europe. Over time, such metrics can track simple, yet critical, impacts of climate change on ecosystems. Validation has been performed through a direct comparison against ground-based data over ecological sites. Subsequently, using the spatio/temporal variability of this suite of metrics, we classify areas with similar vegetation dynamics. This permits assessment of variations and trends of vegetation dynamics over Europe. Statistical tests to assess the significance of temporal changes are used to evaluate trends in the metrics derived from the recorded time series of the FAPAR.

Long-term trends in Anopheles gambiae insecticide resistance in Côte d'Ivoire.

PubMed

Edi, Constant A V; Koudou, Benjamin G; Bellai, Louise; Adja, Akre M; Chouaibou, Mouhamadou; Bonfoh, Bassirou; Barry, Sarah J E; Johnson, Paul C D; Müller, Pie; Dongus, Stefan; N'Goran, Eliezer K; Ranson, Hilary; Weetman, David

2014-11-28

Malaria control is heavily dependent on the use of insecticides that target adult mosquito vectors via insecticide treated nets (ITNs) or indoor residual spraying (IRS). Four classes of insecticide are approved for IRS but only pyrethroids are available for ITNs. The rapid rise in insecticide resistance in African malaria vectors has raised alarms about the sustainability of existing malaria control activities. This problem might be particularly acute in Côte d'Ivoire where resistance to all four insecticide classes has recently been recorded. Here we investigate temporal trends in insecticide resistance across the ecological zones of Côte d'Ivoire to determine whether apparent pan-African patterns of increasing resistance are detectable and consistent across insecticides and areas. We combined data on insecticide resistance from a literature review, and bioassays conducted on field-caught Anopheles gambiae mosquitoes for the four WHO-approved insecticide classes for ITN/IRS. The data were then mapped using Geographical Information Systems (GIS) and the IR mapper tool to provide spatial and temporal distribution data on insecticide resistance in An. gambiae sensu lato from Côte d'Ivoire between 1993 and 2014. Bioassay mortality decreased over time for all insecticide classes, though with significant spatiotemporal variation, such that stronger declines were observed in the southern ecological zone for DDT and pyrethroids than in the central zone, but with an apparently opposite effect for the carbamate and organophosphate. Variation in relative abundance of the molecular forms, coupled with dramatic increase in kdr 1014F frequency in M forms (An. coluzzii) seems likely to be a contributory factor to these patterns. Although records of resistance across insecticide classes have become more common, the number of classes tested in studies has also increased, precluding a conclusion that multiple resistance has also increased. Our analyses attempted synthesis of 22 years of bioassay data from Côte d'Ivoire, and despite a number of caveats and potentially confounding variables, suggest significant but spatially-variable temporal trends in insecticide resistance. In the light of such spatio-temporal dynamics, regular, systematic and spatially-expanded monitoring is warranted to provide accurate information on insecticide resistance for control programme management.

Geographical Information System based assessment of spatiotemporal characteristics of groundwater quality of upland sub-watersheds of Meenachil River, parts of Western Ghats, Kottayam District, Kerala, India

NASA Astrophysics Data System (ADS)

Vijith, H.; Satheesh, R.

2007-09-01

Hydrogeochemistry of groundwater in upland sub-watersheds of Meenachil river, parts of Western Ghats, Kottayam, Kerala, India was used to assess the quality of groundwater for determining its suitability for drinking and agricultural purposes. The study area is dominated by rocks of Archaean age, and Charnonckite is dominated over other rocks. Rubber plantation dominated over other types of the vegetation in the area. Though the study area receives heavy rainfall, it frequently faces water scarcity as well as water quality problems. Hence, a Geographical Information System (GIS) based assessment of spatiotemporal behaviour of groundwater quality has been carried out in the region. Twenty-eight water samples were collected from different wells and analysed for major chemical constituents both in monsoon and post-monsoon seasons to determine the quality variation. Physical and chemical parameters of groundwater such as pH, dissolved oxygen (DO), total hardness (TH), chloride (Cl), nitrate (NO3) and phosphate (PO4) were determined. A surface map was prepared in the ArcGIS 8.3 (spatial analyst module) to assess the quality in terms of spatial variation, and it showed that the high and low regions of water quality varied spatially during the study period. The influence of lithology over the quality of groundwater is negligible in this region because majority of the area comes under single lithology, i.e. charnockite, and it was found that the extensive use of fertilizers and pesticides in the rubber, tea and other agricultural practices influenced the groundwater quality of the region. According to the overall assessment of the basin, all the parameters analysed are below the desirable limits of WHO and Indian standards for drinking water. Hence, considering the pH, the groundwater in the study area is not suitable for drinking but can be used for irrigation, industrial and domestic purposes. The spatial analysis of groundwater quality patterns of the study area shows seasonal fluctuations and these spatial patterns of physical and chemical constituents are useful in deciding water use strategies for various purposes.

An Online Atlas for Exploring Spatio-Temporal Patterns of Cancer Mortality (1972–2011) and Incidence (1995–2008) in Taiwan

PubMed Central

Ku, Wen-Yuan; Liaw, Yung-Po; Huang, Jing-Yang; Nfor, Oswald Ndi; Hsu, Shu-Yi; Ko, Pei-Chieh; Lee, Wen-Chung; Chen, Chien-Jen

2016-01-01

Abstract Public health mapping and Geographical Information Systems (GIS) are already being used to locate the geographical spread of diseases. This study describes the construction of an easy-to-use online atlas of cancer mortality (1972–2011) and incidence (1995–2008) in Taiwan. Two sets of color maps were made based on “age-adjusted mortality by rate” and “age-adjusted mortality by rank.” AJAX (Asynchronous JavaScript and XML), JSON (JavaScript Object Notation), and SVG (Scaling Vector Graphic) were used to create the online atlas. Spatio-temporal patterns of cancer mortality and incidence in Taiwan over the period from 1972 to 2011 and from 1995 to 2008. The constructed online atlas contains information on cancer mortality and incidence (http://taiwancancermap.csmu-liawyp.tw/). The common GIS functions include zoom and pan and identity tools. Users can easily customize the maps to explore the spatio-temporal trends of cancer mortality and incidence using different devices (such as personal computers, mobile phone, or pad). This study suggests an easy- to-use, low-cost, and independent platform for exploring cancer incidence and mortality. It is expected to serve as a reference tool for cancer prevention and risk assessment. This online atlas is a cheap and fast tool that integrates various cancer maps. Therefore, it can serve as a powerful tool that allows users to examine and compare spatio-temporal patterns of various maps. Furthermore, it is an-easy-to use tool for updating data and assessing risk factors of cancer in Taiwan. PMID:27227915

An Online Atlas for Exploring Spatio-Temporal Patterns of Cancer Mortality (1972-2011) and Incidence (1995-2008) in Taiwan.

PubMed

Ku, Wen-Yuan; Liaw, Yung-Po; Huang, Jing-Yang; Nfor, Oswald Ndi; Hsu, Shu-Yi; Ko, Pei-Chieh; Lee, Wen-Chung; Chen, Chien-Jen

2016-05-01

Public health mapping and Geographical Information Systems (GIS) are already being used to locate the geographical spread of diseases. This study describes the construction of an easy-to-use online atlas of cancer mortality (1972-2011) and incidence (1995-2008) in Taiwan.Two sets of color maps were made based on "age-adjusted mortality by rate" and "age-adjusted mortality by rank." AJAX (Asynchronous JavaScript and XML), JSON (JavaScript Object Notation), and SVG (Scaling Vector Graphic) were used to create the online atlas. Spatio-temporal patterns of cancer mortality and incidence in Taiwan over the period from 1972 to 2011 and from 1995 to 2008.The constructed online atlas contains information on cancer mortality and incidence (http://taiwancancermap.csmu-liawyp.tw/). The common GIS functions include zoom and pan and identity tools. Users can easily customize the maps to explore the spatio-temporal trends of cancer mortality and incidence using different devices (such as personal computers, mobile phone, or pad). This study suggests an easy- to-use, low-cost, and independent platform for exploring cancer incidence and mortality. It is expected to serve as a reference tool for cancer prevention and risk assessment.This online atlas is a cheap and fast tool that integrates various cancer maps. Therefore, it can serve as a powerful tool that allows users to examine and compare spatio-temporal patterns of various maps. Furthermore, it is an-easy-to use tool for updating data and assessing risk factors of cancer in Taiwan.

Impact of meteorological factors on the spatiotemporal patterns of dengue fever incidence.

PubMed

Chien, Lung-Chang; Yu, Hwa-Lung

2014-12-01

Dengue fever is one of the most widespread vector-borne diseases and has caused more than 50 million infections annually over the world. For the purposes of disease prevention and climate change health impact assessment, it is crucial to understand the weather-disease associations for dengue fever. This study investigated the nonlinear delayed impact of meteorological conditions on the spatiotemporal variations of dengue fever in southern Taiwan during 1998-2011. We present a novel integration of a distributed lag nonlinear model and Markov random fields to assess the nonlinear lagged effects of weather variables on temporal dynamics of dengue fever and to account for the geographical heterogeneity. This study identified the most significant meteorological measures to dengue fever variations, i.e., weekly minimum temperature, and the weekly maximum 24-hour rainfall, by obtaining the relative risk (RR) with respect to disease counts and a continuous 20-week lagged time. Results show that RR increased as minimum temperature increased, especially for the lagged period 5-18 weeks, and also suggest that the time to high disease risks can be decreased. Once the occurrence of maximum 24-hour rainfall is >50 mm, an associated increased RR lasted for up to 15 weeks. A temporary one-month decrease in the RR of dengue fever is noted following the extreme rain. In addition, the elevated incidence risk is identified in highly populated areas. Our results highlight the high nonlinearity of temporal lagged effects and magnitudes of temperature and rainfall on dengue fever epidemics. The results can be a practical reference for the early warning of dengue fever. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling land surface hydrology sensitivity in the Colorado River Basin to historical climate variability

NASA Astrophysics Data System (ADS)

Whitney, K. M.; Bohn, T. J.; Vivoni, E. R.

2017-12-01

Over the past century, the Colorado River Basin (CRB) has experienced substantial warming and interannual climate variations, including prolonged drought periods. These patterns are projected to accelerate in the 21st century, with major consequences for water resources in the southwestern U.S. and northwestern Mexico. To evaluate future projections appropriately, however, it is important to first quantify the regional hydrologic response to historical climate variability in the CRB. In the current effort, we force the Variable Infiltration Capacity (VIC) land surface hydrology model and a river routing model with historical meteorological data to estimate water balance components and naturalized streamflow response in the CRB at 1/16o spatial resolution and at an hourly time step over the period 1950-2013. We utilize data products from satellite remote sensing to specify spatiotemporal variations in vegetation parameters and include an irrigation scheme to account for evapotranspiration from croplands in the CRB. Furthermore, we apply recent modifications in VIC to more properly account for bare soil evaporation in arid and semiarid ecosystems. Analyses of the historical model simulations are focused on quantifying the spatiotemporal variability of the soil moisture, evapotranspiration, streamflow and snowmelt response and their linkages to extreme meteorological events. Here we characterize the annual and monthly distributions, trends, and statistical extremes and central tendencies of water balance terms averaged over the CRB and its sub-basins for the entire study period 1950-2013. By building a model-based hydrologic climatology and catalog of historical extreme events for the CRB, we aim to construct a basis for future activities that analyze the impact of statistically downscaled climate change projections on the hydrology of the CRB and its urban areas.

Spatiotemporal patterns of drought at various time scales in Shandong Province of Eastern China

NASA Astrophysics Data System (ADS)

Zuo, Depeng; Cai, Siyang; Xu, Zongxue; Li, Fulin; Sun, Wenchao; Yang, Xiaojing; Kan, Guangyuan; Liu, Pin

2018-01-01

The temporal variations and spatial patterns of drought in Shandong Province of Eastern China were investigated by calculating the standardized precipitation evapotranspiration index (SPEI) at 1-, 3-, 6-, 12-, and 24-month time scales. Monthly precipitation and air temperature time series during the period 1960-2012 were collected at 23 meteorological stations uniformly distributed over the region. The non-parametric Mann-Kendall test was used to explore the temporal trends of precipitation, air temperature, and the SPEI drought index. S-mode principal component analysis (PCA) was applied to identify the spatial patterns of drought. The results showed that an insignificant decreasing trend in annual total precipitation was detected at most stations, a significant increase of annual average air temperature occurred at all the 23 stations, and a significant decreasing trend in the SPEI was mainly detected at the coastal stations for all the time scales. The frequency of occurrence of extreme and severe drought at different time scales generally increased with decades; higher frequency and larger affected area of extreme and severe droughts occurred as the time scale increased, especially for the northwest of Shandong Province and Jiaodong peninsular. The spatial pattern of drought for SPEI-1 contains three regions: eastern Jiaodong Peninsular and northwestern and southern Shandong. As the time scale increased to 3, 6, and 12 months, the order of the three regions was transformed into another as northwestern Shandong, eastern Jiaodong Peninsular, and southern Shandong. For SPEI-24, the location identified by REOF1 was slightly shifted from northwestern Shandong to western Shandong, and REOF2 and REOF3 identified another two weak patterns in the south edge and north edge of Jiaodong Peninsular, respectively. The potential causes of drought and the impact of drought on agriculture in the study area have also been discussed. The temporal variations and spatial patterns of drought obtained in this study provide valuable information for water resources planning and drought disaster prevention and mitigation in Eastern China.

Visually driven chaining of elementary swim patterns into a goal-directed motor sequence: a virtual reality study of zebrafish prey capture

PubMed Central

Trivedi, Chintan A.; Bollmann, Johann H.

2013-01-01

Prey capture behavior critically depends on rapid processing of sensory input in order to track, approach, and catch the target. When using vision, the nervous system faces the problem of extracting relevant information from a continuous stream of input in order to detect and categorize visible objects as potential prey and to select appropriate motor patterns for approach. For prey capture, many vertebrates exhibit intermittent locomotion, in which discrete motor patterns are chained into a sequence, interrupted by short periods of rest. Here, using high-speed recordings of full-length prey capture sequences performed by freely swimming zebrafish larvae in the presence of a single paramecium, we provide a detailed kinematic analysis of first and subsequent swim bouts during prey capture. Using Fourier analysis, we show that individual swim bouts represent an elementary motor pattern. Changes in orientation are directed toward the target on a graded scale and are implemented by an asymmetric tail bend component superimposed on this basic motor pattern. To further investigate the role of visual feedback on the efficiency and speed of this complex behavior, we developed a closed-loop virtual reality setup in which minimally restrained larvae recapitulated interconnected swim patterns closely resembling those observed during prey capture in freely moving fish. Systematic variation of stimulus properties showed that prey capture is initiated within a narrow range of stimulus size and velocity. Furthermore, variations in the delay and location of swim triggered visual feedback showed that the reaction time of secondary and later swims is shorter for stimuli that appear within a narrow spatio-temporal window following a swim. This suggests that the larva may generate an expectation of stimulus position, which enables accelerated motor sequencing if the expectation is met by appropriate visual feedback. PMID:23675322

First Directly Retrieved Global Distribution of Tropospheric Column Ozone from GOME: Comparison with the GEOS-CHEM Model

NASA Technical Reports Server (NTRS)

Liu, Xiong; Chance, Kelly; Sioris, Christopher E.; Kurosu, Thomas P.; Spurr, Robert J. D.; Martin, Randall V.; Fu, Tzung-May; Logan, Jennifer A.; Jacob, Daniel J.; Palmer, Paul I.;

A Novel Lead Configuration for Optimal Spatio-Temporal Detection of Intracardiac Repolarization Alternans

PubMed Central

Weiss, Eric H.; Merchant, Faisal M.; d’Avila, Andre; Foley, Lori; Reddy, Vivek Y.; Singh, Jagmeet P.; Mela, Theofanie; Ruskin, Jeremy N.; Armoundas, Antonis A.

2011-01-01

Background Electrical alternans is a pattern of variation in the shape of electrocardiographic waveform that occurs every other beat. In humans, alternation in ventricular repolarization, known as repolarization alternans (RA), has been associated with increased vulnerability to ventricular tachycardia/fibrillation and sudden cardiac death. Methods and Results This study investigates the spatio-temporal variability of intracardiac RA and its relationship to body surface RA in an acute myocardial ischemia model in swine. We developed a real-time multi-channel repolarization signal acquisition, display and analysis system to record electrocardiographic signals from catheters in the right ventricle, coronary sinus, left ventricle, and epicardial surface prior to and following circumflex coronary artery balloon occlusion. We found that RA is detectable within 4 minutes following the onset ischemia, and is most prominently seen during the first half of the repolarization interval. Ischemia-induced RA was detectable on unipolar and bipolar leads (both in near- and far-field configurations) and on body surface leads. Far-field bipolar intracardiac leads were more sensitive for RA detection than body surface leads, with the probability of body surface RA detection increasing as the number of intracardiac leads detecting RA increased, approaching 100% when at least three intracardiac leads detected RA. We developed a novel, clinically-applicable intracardiac lead system based on a triangular arrangement of leads spanning the right ventricular (RV) and coronary sinus (CS) catheters which provided the highest sensitivity for intracardiac RA detection when compared to any other far-field bipolar sensing configurations (p < 0.0001). Conclusions In conclusion, intracardiac alternans, a complex spatio-temporal phenomenon associated with arrhythmia susceptibility and sudden cardiac death, can be reliably detected through a novel triangular RV-CS lead configuration. PMID:21430127

Understanding spatial and temporal patterning of astrocyte calcium transients via interactions between network transport and extracellular diffusion

NASA Astrophysics Data System (ADS)

Shtrahman, E.; Maruyama, D.; Olariu, E.; Fink, C. G.; Zochowski, M.

2017-02-01

Astrocytes form interconnected networks in the brain and communicate via calcium signaling. We investigate how modes of coupling between astrocytes influence the spatio-temporal patterns of calcium signaling within astrocyte networks and specifically how these network interactions promote coordination within this group of cells. To investigate these complex phenomena, we study reduced cultured networks of astrocytes and neurons. We image the spatial temporal patterns of astrocyte calcium activity and quantify how perturbing the coupling between astrocytes influences astrocyte activity patterns. To gain insight into the pattern formation observed in these cultured networks, we compare the experimentally observed calcium activity patterns to the patterns produced by a reduced computational model, where we represent astrocytes as simple units that integrate input through two mechanisms: gap junction coupling (network transport) and chemical release (extracellular diffusion). We examine the activity patterns in the simulated astrocyte network and their dependence upon these two coupling mechanisms. We find that gap junctions and extracellular chemical release interact in astrocyte networks to modulate the spatiotemporal patterns of their calcium dynamics. We show agreement between the computational and experimental findings, which suggests that the complex global patterns can be understood as a result of simple local coupling mechanisms.

A Developmental Systems Perspective on Epistasis: Computational Exploration of Mutational Interactions in Model Developmental Regulatory Networks

PubMed Central

Gutiérrez, Jayson

2009-01-01

The way in which the information contained in genotypes is translated into complex phenotypic traits (i.e. embryonic expression patterns) depends on its decoding by a multilayered hierarchy of biomolecular systems (regulatory networks). Each layer of this hierarchy displays its own regulatory schemes (i.e. operational rules such as +/− feedback) and associated control parameters, resulting in characteristic variational constraints. This process can be conceptualized as a mapping issue, and in the context of highly-dimensional genotype-phenotype mappings (GPMs) epistatic events have been shown to be ubiquitous, manifested in non-linear correspondences between changes in the genotype and their phenotypic effects. In this study I concentrate on epistatic phenomena pervading levels of biological organization above the genetic material, more specifically the realm of molecular networks. At this level, systems approaches to studying GPMs are specially suitable to shed light on the mechanistic basis of epistatic phenomena. To this aim, I constructed and analyzed ensembles of highly-modular (fully interconnected) networks with distinctive topologies, each displaying dynamic behaviors that were categorized as either arbitrary or functional according to early patterning processes in the Drosophila embryo. Spatio-temporal expression trajectories in virtual syncytial embryos were simulated via reaction-diffusion models. My in silico mutational experiments show that: 1) the average fitness decay tendency to successively accumulated mutations in ensembles of functional networks indicates the prevalence of positive epistasis, whereas in ensembles of arbitrary networks negative epistasis is the dominant tendency; and 2) the evaluation of epistatic coefficients of diverse interaction orders indicates that, both positive and negative epistasis are more prevalent in functional networks than in arbitrary ones. Overall, I conclude that the phenotypic and fitness effects of multiple perturbations are strongly conditioned by both the regulatory architecture (i.e. pattern of coupled feedback structures) and the dynamic nature of the spatio-temporal expression trajectories displayed by the simulated networks. PMID:19738908

Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease.

PubMed

Rohr, Jason R; Raffel, Thomas R

2010-05-04

The role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial, and the effect of climatic variability, in particular, has largely been ignored. For instance, it was recently revealed that the proposed link between climate change and widespread amphibian declines, putatively caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), was tenuous because it was based on a temporally confounded correlation. Here we provide temporally unconfounded evidence that global El Niño climatic events drive widespread amphibian losses in genus Atelopus via increased regional temperature variability, which can reduce amphibian defenses against pathogens. Of 26 climate variables tested, only factors associated with temperature variability could account for the spatiotemporal patterns of declines thought to be associated with Bd. Climatic predictors of declines became significant only after controlling for a pattern consistent with epidemic spread (by temporally detrending the data). This presumed spread accounted for 59% of the temporal variation in amphibian losses, whereas El Niño accounted for 59% of the remaining variation. Hence, we could account for 83% of the variation in declines with these two variables alone. Given that global climate change seems to increase temperature variability, extreme climatic events, and the strength of Central Pacific El Niño episodes, climate change might exacerbate worldwide enigmatic declines of amphibians, presumably by increasing susceptibility to disease. These results suggest that changes to temperature variability associated with climate change might be as significant to biodiversity losses and disease emergence as changes to mean temperature.

Diversification in the South American Pampas: the genetic and morphological variation of the widespread Petunia axillaris complex (Solanaceae).

PubMed

Turchetto, Caroline; Fagundes, Nelson J R; Segatto, Ana L A; Kuhlemeier, Cris; Solís Neffa, Viviana G; Speranza, Pablo R; Bonatto, Sandro L; Freitas, Loreta B

2014-02-01

Understanding the spatiotemporal distribution of genetic variation and the ways in which this distribution is connected to the ecological context of natural populations is fundamental for understanding the nature and mode of intraspecific and, ultimately, interspecific differentiation. The Petunia axillaris complex is endemic to the grasslands of southern South America and includes three subspecies: P. a. axillaris, P. a. parodii and P. a. subandina. These subspecies are traditionally delimited based on both geography and floral morphology, although the latter is highly variable. Here, we determined the patterns of genetic (nuclear and cpDNA), morphological and ecological (bioclimatic) variation of a large number of P. axillaris populations and found that they are mostly coincident with subspecies delimitation. The nuclear data suggest that the subspecies are likely independent evolutionary units, and their morphological differences may be associated with local adaptations to diverse climatic and/or edaphic conditions and population isolation. The demographic dynamics over time estimated by skyline plot analyses showed different patterns for each subspecies in the last 100 000 years, which is compatible with a divergence time between 35 000 and 107 000 years ago between P. a. axillaris and P. a. parodii, as estimated with the IMa program. Coalescent simulation tests using Approximate Bayesian Computation do not support previous suggestions of extensive gene flow between P. a. axillaris and P. a. parodii in their contact zone. © 2013 John Wiley & Sons Ltd.

Spatiotemporal distribution and variation of GPP in the Greater Khingan Mountains from 1982 to 2015

NASA Astrophysics Data System (ADS)

Hu, L.; Fan, W.; Liu, S.; Ren, H.; Xu, X.

2017-12-01

GPP (Gross Primary Productivity) is an important index to reflect the productivity of plants because it refers to the organic accumulated by green plants on land through assimilating the carbon dioxide in the atmosphere by photosynthesis and a serial of physiological processes in plants. Therefore, GPP plays a significant role in studying the carbon sink of terrestrial ecosystem and plants' reaction to global climate change. Remote sensing provides an efficient way to estimate GPP at regional and global scales and its products can be used to monitor the spatiotemporal variation of terrestrial ecosystem.As the Greater Khingan Mountains is the only bright coniferous forest of cool temperate zone in China and accounts for about 30% of the forest in China. This region is sensitive to climate change, but its forest coverage presented a significant variation due to fire disasters, excessive deforestation and so on. Here, we aimed at studying the variation pattern of GPP in the Greater Khingan Mountains and further found impact factors for the change in order to improve the understanding of what have and will happen on plants and carbon cycle under climate change.Based on GPP product from the GLASS program, we first studied spatial distribution of plants in the Greater Khingan Mountains from 1982 to 2015. With a linear regression model, seasonal and inter-annual GPP variability were explored on pixel and regional scale. We analyzed some climatic factors (e.g. temperature and precipitation) and terrain in order to find the driven factors for the GPP variations. The Growing Season Length (GSL) was also regarded as a factor and was retrieved from GIMMS 3g NDVI datasets using dynamic threshold method. We found that GPP in study area linearly decreased with the increasing elevation. Both annual accumulated GPP (AAG) and maximum daily GPP (during mid-June to mid-July) gained obvious improvement over the past 34 years under climate warming and drying (Fig.1 and Fig.2). Further studies showed temperature had positive correlation with GPP while precipitation had negative effect; Moreover, multi-regression results reflected that temperature rather than precipitation was the dominant climatic factor for plants in study area. The extension of GSL also increased the AAG.

Recharge signal identification based on groundwater level observations.

PubMed

Yu, Hwa-Lung; Chu, Hone-Jay

2012-10-01

This study applied a method of the rotated empirical orthogonal functions to directly decompose the space-time groundwater level variations and determine the potential recharge zones by investigating the correlation between the identified groundwater signals and the observed local rainfall records. The approach is used to analyze the spatiotemporal process of piezometric heads estimated by Bayesian maximum entropy method from monthly observations of 45 wells in 1999-2007 located in the Pingtung Plain of Taiwan. From the results, the primary potential recharge area is located at the proximal fan areas where the recharge process accounts for 88% of the spatiotemporal variations of piezometric heads in the study area. The decomposition of groundwater levels associated with rainfall can provide information on the recharge process since rainfall is an important contributor to groundwater recharge in semi-arid regions. Correlation analysis shows that the identified recharge closely associates with the temporal variation of the local precipitation with a delay of 1-2 months in the study area.

Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

PubMed

Henson, Michael A

2015-12-01

Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

Geographical gradients in selection can reveal genetic constraints for evolutionary responses to ocean acidification.

PubMed

Gaitán-Espitia, Juan Diego; Marshall, Dustin; Dupont, Sam; Bacigalupe, Leonardo D; Bodrossy, Levente; Hobday, Alistair J

2017-02-01

Geographical gradients in selection can shape different genetic architectures in natural populations, reflecting potential genetic constraints for adaptive evolution under climate change. Investigation of natural pH/pCO 2 variation in upwelling regions reveals different spatio-temporal patterns of natural selection, generating genetic and phenotypic clines in populations, and potentially leading to local adaptation, relevant to understanding effects of ocean acidification (OA). Strong directional selection, associated with intense and continuous upwellings, may have depleted genetic variation in populations within these upwelling regions, favouring increased tolerances to low pH but with an associated cost in other traits. In contrast, diversifying or weak directional selection in populations with seasonal upwellings or outside major upwelling regions may have resulted in higher genetic variances and the lack of genetic correlations among traits. Testing this hypothesis in geographical regions with similar environmental conditions to those predicted under climate change will build insights into how selection may act in the future and how populations may respond to stressors such as OA. © 2017 The Author(s).

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE.

PubMed

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis.

Spatio-temporal patterns of the effects of precipitation variability and land use/cover changes on long-term changes in sediment yield in the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Gao, Guangyao; Zhang, Jianjun; Liu, Yu; Ning, Zheng; Fu, Bojie; Sivapalan, Murugesu

2017-09-01

Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion and land degradation. As a result, annual streamflow, sediment yield, and sediment concentration have all decreased considerably. Human-induced land use/cover change (LUCC) was the dominant factor, contributing over 70 % of the sediment load reduction, whereas the contribution of precipitation was less than 30 %. In this study, we use 50-year time series data (1961-2011), showing decreasing trends in the annual sediment loads of 15 catchments, to generate spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield. The space-time variability of sediment yield was expressed notionally as a product of two factors representing (i) the effect of precipitation and (ii) the fraction of treated land surface area. Under minimal LUCC, the square root of annual sediment yield varied linearly with precipitation, with the precipitation-sediment load relationship showing coherent spatial patterns amongst the catchments. As the LUCC increased and took effect, the changes in sediment yield pattern depended more on engineering measures and vegetation restoration campaign, and the within-year rainfall patterns (especially storm events) also played an important role. The effect of LUCC is expressed in terms of a sediment coefficient, i.e., the ratio of annual sediment yield to annual precipitation. Sediment coefficients showed a steady decrease over the study period, following a linear decreasing function of the fraction of treated land surface area. In this way, the study has brought out the separate roles of precipitation variability and LUCC in controlling spatio-temporal patterns of sediment yield at catchment scale.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

PubMed Central

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M.; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis. PMID:28596729

Recruitment Variability of Coral Reef Sessile Communities of the Far North Great Barrier Reef

PubMed Central

Luter, Heidi M.; Duckworth, Alan R.; Wolff, Carsten W.; Evans-Illidge, Elizabeth; Whalan, Steve

2016-01-01

One of the key components in assessing marine sessile organism demography is determining recruitment patterns to benthic habitats. An analysis of serially deployed recruitment tiles across depth (6 and 12 m), seasons (summer and winter) and space (meters to kilometres) was used to quantify recruitment assemblage structure (abundance and percent cover) of corals, sponges, ascidians, algae and other sessile organisms from the northern sector of the Great Barrier Reef (GBR). Polychaetes were most abundant on recruitment titles, reaching almost 50% of total recruitment, yet covered <5% of each tile. In contrast, mean abundances of sponges, ascidians, algae, and bryozoans combined was generally less than 20% of total recruitment, with percentage cover ranging between 15–30% per tile. Coral recruitment was very low, with <1 recruit per tile identified. A hierarchal analysis of variation over a range of spatial and temporal scales showed significant spatio-temporal variation in recruitment patterns, but the highest variability occurred at the lowest spatial scale examined (1 m—among tiles). Temporal variability in recruitment of both numbers of taxa and percentage cover was also evident across both summer and winter. Recruitment across depth varied for some taxonomic groups like algae, sponges and ascidians, with greatest differences in summer. This study presents some of the first data on benthic recruitment within the northern GBR and provides a greater understanding of population ecology for coral reefs. PMID:27049650

Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests.

PubMed

Xu, Xiangtao; Medvigy, David; Powers, Jennifer S; Becknell, Justin M; Guan, Kaiyu

2016-10-01

We assessed whether diversity in plant hydraulic traits can explain the observed diversity in plant responses to water stress in seasonally dry tropical forests (SDTFs). The Ecosystem Demography model 2 (ED2) was updated with a trait-driven mechanistic plant hydraulic module, as well as novel drought-phenology and plant water stress schemes. Four plant functional types were parameterized on the basis of meta-analysis of plant hydraulic traits. Simulations from both the original and the updated ED2 were evaluated against 5 yr of field data from a Costa Rican SDTF site and remote-sensing data over Central America. The updated model generated realistic plant hydraulic dynamics, such as leaf water potential and stem sap flow. Compared with the original ED2, predictions from our novel trait-driven model matched better with observed growth, phenology and their variations among functional groups. Most notably, the original ED2 produced unrealistically small leaf area index (LAI) and underestimated cumulative leaf litter. Both of these biases were corrected by the updated model. The updated model was also better able to simulate spatial patterns of LAI dynamics in Central America. Plant hydraulic traits are intercorrelated in SDTFs. Mechanistic incorporation of plant hydraulic traits is necessary for the simulation of spatiotemporal patterns of vegetation dynamics in SDTFs in vegetation models. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Seasonal and among-stream variation in predator encounter rates for fish prey

Treesearch

Bret C. Harvey; Rodney J. Nakamoto

2013-01-01

Recognition that predators have indirect effects on prey populations that may exceed their direct consumptive effects highlights the need for a better understanding of spatiotemporal variation in predator–prey interactions. We used photographic monitoring of tethered Rainbow Trout Oncorhynchus mykiss and Cutthroat Trout O. clarkii to quantify predator encounter rates...

Empirical modeling of the impact of Mollisol soils variation on performance of Cuphea: A potential oilseed crop

USDA-ARS?s Scientific Manuscript database

Production potential of many soils is affected by low supply of nutrients due to adverse constraints or spatio-temporal variation of soil physical and chemical properties. New oilseed crops differ in their nutrient needs for maximum performance in different soils and may not be able to economically ...

Quantifying Diurnal and Spatial Variations in CO2 Concentrations and Partial Columns using High-Resolution Global Model Simulations

NASA Astrophysics Data System (ADS)

Pawson, S.; Nielsen, J.; Ott, L. E.; Darmenov, A.; Putman, W.

2015-12-01

Model-data fusion approaches, such as global inverse modeling for surface flux estimation, have traditionally been performed at spatial resolutions of several tens to a few hundreds of kilometers. Use of such coarse scales presents a fundamental limitation in reconciling the modeled field with both the atmospheric observations and the distribution of surface emissions and uptake. Emissions typically occur on small scales, including point sources (e.g. power plants, forest fires) or with inhomegeneous structure. Biological uptake can have spatial variations related to complex, diverse vegetation, etc. Atmospheric observations of CO2 are either surface based, providing information at a single point, or space based with a finite-sized footprint. For instance, GOSAT and OCO-2 have footprint sizes of around 10km and proposed active sensors (such as ASCENDS) will likely have even finer footprints. One important aspect of reconciling models to measurements is the representativeness of the observation for the model field, and this depends on the generally unknown spatio-temporal variations of the CO2 field around the measurement location and time. This work presents an assessment of the global spatio-temporal variations of the CO2 field using the "7km GEOS-5 Nature Run" (7km-G5NR), which includes CO2 emissions and uptake mapped to the finest possible resolution. Results are shown for surface CO2 concentrations, total-column CO2, and separate upper and lower tropospheric columns. Spatial variability is shown to be largest in regions with strong point sources and at night in regions with complex terrain, especially where biological processes dominate the local CO2 fluxes, where the day-night differences are also most marked. The spatio-temporal variations are strongest for surface concentrations and for lower tropospheric CO2. While these results are largely anticipated, these high resolution simulations provide quantitative estimates of the global nature of spatio-temporal CO2 variability. Implications for characterizing representativeness of passive CO2 observations will be discussed. Differences between daytime and nighttime structures will be considered in light of active CO2 sensors. Finally, some possible limitations of the model will be highlighted, using some global 3-km simulations.

Propagating wave and irregular dynamics: Spatiotemporal patterns of cholinergic theta oscillations in neocortex, in vitro

PubMed Central

Bao, Weili; Wu, Jian-young

2010-01-01

Neocortical “theta” oscillation (5- 12 Hz) has been observed in animals and human subjects but little is known about how the oscillation is organized in the cortical intrinsic networks. Here we use voltage-sensitive dye and optical imaging to study a carbachol/bicuculline induced theta (~8 Hz) oscillation in rat neocortical slices. The imaging has large signal-to-noise ratio, allowing us to map the phase distribution over the neocortical tissue during the oscillation. The oscillation was organized as spontaneous epochs and each epoch was composed of a “first spike”, a “regular” period (with relatively stable frequency and amplitude) and an “irregular” period (with variable frequency and amplitude) of oscillations. During each cycle of the regular oscillation one wave of activation propagated horizontally (parallel to the cortical lamina) across the cortical section at a velocity of ~50 mm/sec. Vertically the activity was synchronized through all cortical layers. This pattern of one propagating wave associated with one oscillation cycle was seen during all the regular cycles. The oscillation frequency varied noticeably at two neighboring horizontal locations (330 μm apart), suggesting that the oscillation is locally organized and each local oscillator is about equal or less than 300 μm wide horizontally. During irregular oscillations the spatiotemporal patterns were complex and sometimes the vertical synchronization decomposed, suggesting a de-coupling among local oscillators. Our data suggested that neocortical theta oscillation is sustained by multiple local oscillators. The coupling regime among the oscillators may determine the spatiotemporal pattern and switching between propagating waves and irregular patterns. PMID:12612003

Optogenetically induced spatiotemporal gamma oscillations and neuronal spiking activity in primate motor cortex.

PubMed

Lu, Yao; Truccolo, Wilson; Wagner, Fabien B; Vargas-Irwin, Carlos E; Ozden, Ilker; Zimmermann, Jonas B; May, Travis; Agha, Naubahar S; Wang, Jing; Nurmikko, Arto V

2015-06-01

Transient gamma-band (40-80 Hz) spatiotemporal patterns are hypothesized to play important roles in cortical function. Here we report the direct observation of gamma oscillations as spatiotemporal waves induced by targeted optogenetic stimulation, recorded by intracortical multichannel extracellular techniques in macaque monkeys during their awake resting states. Microelectrode arrays integrating an optical fiber at their center were chronically implanted in primary motor (M1) and ventral premotor (PMv) cortices of two subjects. Targeted brain tissue was transduced with the red-shifted opsin C1V1(T/T). Constant (1-s square pulses) and ramp stimulation induced narrowband gamma oscillations during awake resting states. Recordings across 95 microelectrodes (4 × 4-mm array) enabled us to track the transient gamma spatiotemporal patterns manifested, e.g., as concentric expanding and spiral waves. Gamma oscillations were induced well beyond the light stimulation volume, via network interactions at distal electrode sites, depending on optical power. Despite stimulation-related modulation in spiking rates, neuronal spiking remained highly asynchronous during induced gamma oscillations. In one subject we examined stimulation effects during preparation and execution of a motor task and observed that movement execution largely attenuated optically induced gamma oscillations. Our findings demonstrate that, beyond previously reported induced gamma activity under periodic drive, a prolonged constant stimulus above a certain threshold may carry primate motor cortex network dynamics into gamma oscillations, likely via a Hopf bifurcation. More broadly, the experimental capability in combining microelectrode array recordings and optogenetic stimulation provides an important approach for probing spatiotemporal dynamics in primate cortical networks during various physiological and behavioral conditions.

Optogenetically induced spatiotemporal gamma oscillations and neuronal spiking activity in primate motor cortex

PubMed Central

Lu, Yao; Truccolo, Wilson; Wagner, Fabien B.; Vargas-Irwin, Carlos E.; Ozden, Ilker; Zimmermann, Jonas B.; May, Travis; Agha, Naubahar S.; Wang, Jing

2015-01-01

Transient gamma-band (40–80 Hz) spatiotemporal patterns are hypothesized to play important roles in cortical function. Here we report the direct observation of gamma oscillations as spatiotemporal waves induced by targeted optogenetic stimulation, recorded by intracortical multichannel extracellular techniques in macaque monkeys during their awake resting states. Microelectrode arrays integrating an optical fiber at their center were chronically implanted in primary motor (M1) and ventral premotor (PMv) cortices of two subjects. Targeted brain tissue was transduced with the red-shifted opsin C1V1(T/T). Constant (1-s square pulses) and ramp stimulation induced narrowband gamma oscillations during awake resting states. Recordings across 95 microelectrodes (4 × 4-mm array) enabled us to track the transient gamma spatiotemporal patterns manifested, e.g., as concentric expanding and spiral waves. Gamma oscillations were induced well beyond the light stimulation volume, via network interactions at distal electrode sites, depending on optical power. Despite stimulation-related modulation in spiking rates, neuronal spiking remained highly asynchronous during induced gamma oscillations. In one subject we examined stimulation effects during preparation and execution of a motor task and observed that movement execution largely attenuated optically induced gamma oscillations. Our findings demonstrate that, beyond previously reported induced gamma activity under periodic drive, a prolonged constant stimulus above a certain threshold may carry primate motor cortex network dynamics into gamma oscillations, likely via a Hopf bifurcation. More broadly, the experimental capability in combining microelectrode array recordings and optogenetic stimulation provides an important approach for probing spatiotemporal dynamics in primate cortical networks during various physiological and behavioral conditions. PMID:25761956

Spatiotemporal Dynamics of Genetic Variation in the Iberian Lynx along Its Path to Extinction Reconstructed with Ancient DNA.

PubMed

Casas-Marce, Mireia; Marmesat, Elena; Soriano, Laura; Martínez-Cruz, Begoña; Lucena-Perez, Maria; Nocete, Francisco; Rodríguez-Hidalgo, Antonio; Canals, Antoni; Nadal, Jordi; Detry, Cleia; Bernáldez-Sánchez, Eloísa; Fernández-Rodríguez, Carlos; Pérez-Ripoll, Manuel; Stiller, Mathias; Hofreiter, Michael; Rodríguez, Alejandro; Revilla, Eloy; Delibes, Miguel; Godoy, José A

2017-11-01

There is the tendency to assume that endangered species have been both genetically and demographically healthier in the past, so that any genetic erosion observed today was caused by their recent decline. The Iberian lynx (Lynx pardinus) suffered a dramatic and continuous decline during the 20th century, and now shows extremely low genome- and species-wide genetic diversity among other signs of genomic erosion. We analyze ancient (N = 10), historical (N = 245), and contemporary (N = 172) samples with microsatellite and mitogenome data to reconstruct the species' demography and investigate patterns of genetic variation across space and time. Iberian lynx populations transitioned from low but significantly higher genetic diversity than today and shallow geographical differentiation millennia ago, through a structured metapopulation with varying levels of diversity during the last centuries, to two extremely genetically depauperate and differentiated remnant populations by 2002. The historical subpopulations show varying extents of genetic drift in relation to their recent size and time in isolation, but these do not predict whether the populations persisted or went finally extinct. In conclusion, current genetic patterns were mainly shaped by genetic drift, supporting the current admixture of the two genetic pools and calling for a comprehensive genetic management of the ongoing conservation program. This study illustrates how a retrospective analysis of demographic and genetic patterns of endangered species can shed light onto their evolutionary history and this, in turn, can inform conservation actions. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

NASA Astrophysics Data System (ADS)

Lu, Bing; He, Yuhong

2017-06-01

Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition, owing to its high spatial resolution. The overall accuracy is around 85% for images acquired at different times. Species composition is spatially attributed by topographical features and soil moisture conditions. Spatio-temporal variation of species composition implies the growing process and succession of different species, which is critical for understanding the evolutionary features of grassland ecosystems. Strengths and challenges of applying UAV-acquired imagery for vegetation studies are summarized at the end.

Spatiotemporal patterns and source attribution of nitrogen pollution in a typical headwater agricultural watershed in Southeastern China.

PubMed

Chen, Wenjun; He, Bin; Nover, Daniel; Duan, Weili; Luo, Chuan; Zhao, Kaiyan; Chen, Wen

2018-01-01

Excessive nitrogen (N) discharge from agriculture causes widespread problems in aquatic ecosystems. Knowledge of spatiotemporal patterns and source attribution of N pollution is critical for nutrient management programs but is poorly studied in headwaters with various small water bodies and mini-point pollution sources. Taking a typical small watershed in the low mountains of Southeastern China as an example, N pollution and source attribution were studied for a multipond system around a village using the Hydrological Simulation Program-Fortran (HSPF) model. The results exhibited distinctive spatio-seasonal variations with an overall seriousness rank for the three indicators: total nitrogen (TN) > nitrate/nitrite nitrogen (NO x - -N) > ammonia nitrogen (NH 3 -N), according to the Chinese Surface Water Quality Standard. TN pollution was severe for the entire watershed, while NO x - -N pollution was significant for ponds and ditches far from the village, and the NH 3 -N concentrations were acceptable except for the ponds near the village in summer. Although food and cash crop production accounted for the largest source of N loads, we discovered that mini-point pollution sources, including animal feeding operations, rural residential sewage, and waste, together contributed as high as 47% of the TN and NH 3 -N loads in ponds and ditches. So, apart from eco-fertilizer programs and concentrated animal feeding operations, the importance of environmental awareness building for resource management is highlighted for small farmers in headwater agricultural watersheds. As a first attempt to incorporate multipond systems into the process-based modeling of nonpoint source (NPS) pollution, this work can inform other hydro-environmental studies on scattered and small water bodies. The results are also useful to water quality improvement for entire river basins.

Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data

NASA Astrophysics Data System (ADS)

Manzo, Ciro; Braga, Federica; Zaggia, Luca; Brando, Vittorio Ernesto; Giardino, Claudia; Bresciani, Mariano; Bassani, Cristiana

2018-04-01

This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013-2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

The Effects of Weather Patterns on the Spatio-Temporal Distribution of SO2 over East Asia as Seen from Satellite Measurements

NASA Astrophysics Data System (ADS)

Dunlap, L.; Li, C.; Dickerson, R. R.; Krotkov, N. A.

2015-12-01

Weather systems, particularly mid-latitude wave cyclones, have been known to play an important role in the short-term variation of near-surface air pollution. Ground measurements and model simulations have demonstrated that stagnant air and minimal precipitation associated with high pressure systems are conducive to pollutant accumulation. With the passage of a cold front, built up pollution is transported downwind of the emission sources or washed out by precipitation. This concept is important to note when studying long-term changes in spatio-temporal pollution distribution, but has not been studied in detail from space. In this study, we focus on East Asia (especially the industrialized eastern China), where numerous large power plants and other point sources as well as area sources emit large amounts of SO2, an important gaseous pollutant and a precursor of aerosols. Using data from the Aura Ozone Monitoring Instrument (OMI) we show that such weather driven distribution can indeed be discerned from satellite data by utilizing probability distribution functions (PDFs) of SO2 column content. These PDFs are multimodal and give insight into the background pollution level at a given location and contribution from local and upwind emission sources. From these PDFs it is possible to determine the frequency for a given region to have SO2 loading that exceeds the background amount. By comparing OMI-observed long-term change in the frequency with meteorological data, we can gain insights into the effects of climate change (e.g., the weakening of Asian monsoon) on regional air quality. Such insight allows for better interpretation of satellite measurements as well as better prediction of future pollution distribution as a changing climate gives way to changing weather patterns.

Spatial comparability of drought characteristics and related return periods in mainland China over 1961-2013

NASA Astrophysics Data System (ADS)

Ayantobo, Olusola O.; Li, Yi; Song, Songbai; Yao, Ning

2017-07-01

The proper understanding of the spatiotemporal characteristics of multi-year droughts and return periods is important for drought risk assessment. This study evaluated and compared the spatiotemporal variations of drought characteristics and return periods within mainland China between 1961 and 2013. Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Composite Index (CI) were calculated at multiple timescales, the run theory was used for objective identification and characterization of drought events while Kendall's τ method was used to analyze their dependencies. Within the univariate framework, marginal distributions of duration, severity, and peak were derived by fitting Exponential, Weibull and GDP distributions respectively and the drought return periods was investigated and mapped. Comparison of drought indices showed that SPEI and CI performed better than SPI in delineating spatial patterns of drought characteristics. This might be attributed to the temperature effect on evapotranspiration and therefore on drought index. Considering the increasing trend in reference evapotranspiration in the 21st century, the importance of utilizing temperature-based drought index is imperative. Severe and extreme droughts occurred in the late 1990s in many places in China while persistent multi-year severe droughts occurred more frequently over North China, Northeast China, Northwest China and Southwest China. The spatial patterns showed that regions characterized by higher drought severity were associated with higher drought duration. The North China, Northwest China, and Southwest China had much longer drought durations during the 1990s and 2000s. As droughts normally cover large areas, regional drought return periods has been showed to be more effective in providing support for drought management than station based drought return periods. Studies on the spatial comparability of drought return periods across mainland China have therefore been undertaken for drought mitigation and effective utilization of water resources.

Movement reveals scale dependence in habitat selection of a large ungulate

USGS Publications Warehouse

Northrup, Joseph; Anderson, Charles R.; Hooten, Mevin B.; Wittemyer, George

2016-01-01

Ecological processes operate across temporal and spatial scales. Anthropogenic disturbances impact these processes, but examinations of scale dependence in impacts are infrequent. Such examinations can provide important insight to wildlife–human interactions and guide management efforts to reduce impacts. We assessed spatiotemporal scale dependence in habitat selection of mule deer (Odocoileus hemionus) in the Piceance Basin of Colorado, USA, an area of ongoing natural gas development. We employed a newly developed animal movement method to assess habitat selection across scales defined using animal-centric spatiotemporal definitions ranging from the local (defined from five hour movements) to the broad (defined from weekly movements). We extended our analysis to examine variation in scale dependence between night and day and assess functional responses in habitat selection patterns relative to the density of anthropogenic features. Mule deer displayed scale invariance in the direction of their response to energy development features, avoiding well pads and the areas closest to roads at all scales, though with increasing strength of avoidance at coarser scales. Deer displayed scale-dependent responses to most other habitat features, including land cover type and habitat edges. Selection differed between night and day at the finest scales, but homogenized as scale increased. Deer displayed functional responses to development, with deer inhabiting the least developed ranges more strongly avoiding development relative to those with more development in their ranges. Energy development was a primary driver of habitat selection patterns in mule deer, structuring their behaviors across all scales examined. Stronger avoidance at coarser scales suggests that deer behaviorally mediated their interaction with development, but only to a degree. At higher development densities than seen in this area, such mediation may not be possible and thus maintenance of sufficient habitat with lower development densities will be a critical best management practice as development expands globally.

Spatiotemporal changes in precipitation extremes over Yangtze River basin, China, considering the rainfall shift in the late 1970s

NASA Astrophysics Data System (ADS)

Gao, Tao; Xie, Lian

2016-12-01

Precipitation extremes are the dominated causes for the formation of severe flood disasters at regional and local scales under the background of global climate change. In the present study, five annual extreme precipitation events, including 1, 7 and 30 day annual maximum rainfall and 95th and 97.5th percentile threshold levels, are analyzed relating to the reference period 1960-2011 from 140 meteorological stations over Yangtze River basin (YRB). A generalized extreme value (GEV) distribution is applied to fit annual and percentile extreme precipitation events at each station with return periods up to 200 years. The entire time period is divided into preclimatic (preceding climatic) period 1960-1980 and aftclimatic (after climatic) period 1981-2011 by considering distinctly abrupt shift of precipitation regime in the late 1970s across YRB. And the Mann-Kendall trend test is adopted to conduct trend analysis during pre- and aftclimatic periods, respectively, for the purpose of exploring possible increasing/decreasing patterns in precipitation extremes. The results indicate that the increasing trends for return values during aftclimatic period change significantly in time and space in terms of different magnitudes of extreme precipitation, while the stations with significantly positive trends are mainly distributed in the vicinity of the mainstream and major tributaries as well as large lakes, this would result in more tremendous flood disasters in the mid-lower reaches of YRB, especially in southeast coastal regions. The increasing/decreasing linear trends based on annual maximum precipitation are also investigated in pre- and aftclimatic periods, respectively, whereas those changes are not significantly similar to the variations of return values during both subperiods. Moreover, spatiotemporal patterns of precipitation extremes become more uneven and unstable in the second half period over YRB.

Spatiotemporal Interpolation Methods for the Application of Estimating Population Exposure to Fine Particulate Matter in the Contiguous U.S. and a Real-Time Web Application.

PubMed

Li, Lixin; Zhou, Xiaolu; Kalo, Marc; Piltner, Reinhard

2016-07-25

Appropriate spatiotemporal interpolation is critical to the assessment of relationships between environmental exposures and health outcomes. A powerful assessment of human exposure to environmental agents would incorporate spatial and temporal dimensions simultaneously. This paper compares shape function (SF)-based and inverse distance weighting (IDW)-based spatiotemporal interpolation methods on a data set of PM2.5 data in the contiguous U.S. Particle pollution, also known as particulate matter (PM), is composed of microscopic solids or liquid droplets that are so small that they can get deep into the lungs and cause serious health problems. PM2.5 refers to particles with a mean aerodynamic diameter less than or equal to 2.5 micrometers. Based on the error statistics results of k-fold cross validation, the SF-based method performed better overall than the IDW-based method. The interpolation results generated by the SF-based method are combined with population data to estimate the population exposure to PM2.5 in the contiguous U.S. We investigated the seasonal variations, identified areas where annual and daily PM2.5 were above the standards, and calculated the population size in these areas. Finally, a web application is developed to interpolate and visualize in real time the spatiotemporal variation of ambient air pollution across the contiguous U.S. using air pollution data from the U.S. Environmental Protection Agency (EPA)'s AirNow program.

Spatiotemporal Interpolation Methods for the Application of Estimating Population Exposure to Fine Particulate Matter in the Contiguous U.S. and a Real-Time Web Application

PubMed Central

Li, Lixin; Zhou, Xiaolu; Kalo, Marc; Piltner, Reinhard

2016-01-01

Appropriate spatiotemporal interpolation is critical to the assessment of relationships between environmental exposures and health outcomes. A powerful assessment of human exposure to environmental agents would incorporate spatial and temporal dimensions simultaneously. This paper compares shape function (SF)-based and inverse distance weighting (IDW)-based spatiotemporal interpolation methods on a data set of PM2.5 data in the contiguous U.S. Particle pollution, also known as particulate matter (PM), is composed of microscopic solids or liquid droplets that are so small that they can get deep into the lungs and cause serious health problems. PM2.5 refers to particles with a mean aerodynamic diameter less than or equal to 2.5 micrometers. Based on the error statistics results of k-fold cross validation, the SF-based method performed better overall than the IDW-based method. The interpolation results generated by the SF-based method are combined with population data to estimate the population exposure to PM2.5 in the contiguous U.S. We investigated the seasonal variations, identified areas where annual and daily PM2.5 were above the standards, and calculated the population size in these areas. Finally, a web application is developed to interpolate and visualize in real time the spatiotemporal variation of ambient air pollution across the contiguous U.S. using air pollution data from the U.S. Environmental Protection Agency (EPA)’s AirNow program. PMID:27463722

Spatiotemporal patterns of population distribution as crucial element for risk management

NASA Astrophysics Data System (ADS)

Gokesch, Karin; Promper, Catrin; van Westen, Cees J.; Glade, Thomas

2014-05-01

The spatiotemporal distribution and presence of the population in a certain area is a crucial element within natural hazard risk management, especially in the case of rapid onset hazard events and emergency management. When fast onset hazards such as earthquakes, flash floods or industrial accidents occur, people may not have adequate time for evacuation and the emergency management requires a fast response and reaction. Therefore, information on detailed distribution of people affected by a certain hazard is important for a fast assessment of the situation including the number and the type of people (distinguishing between elderly or handicapped people, children, working population etc.) affected. This study thus aims at analyzing population distribution on an hourly basis for different days e.g. workday or holiday. The applied method combines the basic assessment of population distribution in a given area with specific location-related patterns of distribution-changes over time. The calculations are based on detailed information regarding the expected presence of certain groups of people, e.g. school children, working or elderly people, which all show different patterns of movement over certain time periods. The study area is the city of Waidhofen /Ybbs located in the Alpine foreland in the Southwest of Lower Austria. This city serves as a regional center providing basic infrastructure, shops and schools for the surrounding countryside. Therefore a lot of small and medium businesses are located in this area showing a rather high variation of population present at different times of the day. The available building footprint information was classified with respect to building type and occupancy type, which was used to estimate the expected residents within the buildings, based on the floorspace of the buildings and the average floorspace per person. Additional information on the distribution and the average duration of stay of the people in these buildings was assessed using general population statistics and specific information about selected buildings, such as schools, hospitals or homes for the elderly, to calculate the distribution patterns for each group of people over time.

Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes

PubMed Central

Hurtado, Rafael G.; Floría, Luis Mario

2016-01-01

We analyse the urban mobility in the cities of Medellín and Manizales (Colombia). Each city is represented by six mobility networks, each one encoding the origin-destination trips performed by a subset of the population corresponding to a particular socio-economic status. The nodes of each network are the different urban locations whereas links account for the existence of a trip between two different areas of the city. We study the main structural properties of these mobility networks by focusing on their spatio-temporal patterns. Our goal is to relate these patterns with the partition into six socio-economic compartments of these two societies. Our results show that spatial and temporal patterns vary across these socio-economic groups. In particular, the two datasets show that as wealth increases the early-morning activity is delayed, the midday peak becomes smoother and the spatial distribution of trips becomes more localized. PMID:27853531

High-resolution optical control of spatiotemporal neuronal activity patterns in zebrafish using a digital micromirror device.

PubMed

Zhu, Peixin; Fajardo, Otto; Shum, Jennifer; Zhang Schärer, Yan-Ping; Friedrich, Rainer W

2012-06-28

Optogenetic approaches allow the manipulation of neuronal activity patterns in space and time by light, particularly in small animals such as zebrafish. However, most techniques cannot control neuronal activity independently at different locations. Here we describe equipment and provide a protocol for single-photon patterned optical stimulation of neurons using a digital micromirror device (DMD). This method can create arbitrary spatiotemporal light patterns with spatial and temporal resolutions in the micrometer and submillisecond range, respectively. Different options to integrate a DMD into a multiphoton microscope are presented and compared. We also describe an ex vivo preparation of the adult zebrafish head that greatly facilitates optogenetic and other experiments. After assembly, the initial alignment takes about one day and the zebrafish preparation takes <30 min. The method has previously been used to activate channelrhodopsin-2 and manipulate oscillatory synchrony among spatially distributed neurons in the zebrafish olfactory bulb. It can be adapted easily to a wide range of other species, optogenetic probes and scientific applications.

Solitary states for coupled oscillators with inertia.

PubMed

Jaros, Patrycja; Brezetsky, Serhiy; Levchenko, Roman; Dudkowski, Dawid; Kapitaniak, Tomasz; Maistrenko, Yuri

2018-01-01

Networks of identical oscillators with inertia can display remarkable spatiotemporal patterns in which one or a few oscillators split off from the main synchronized cluster and oscillate with different averaged frequency. Such "solitary states" are impossible for the classical Kuramoto model with sinusoidal coupling. However, if inertia is introduced, these states represent a solid part of the system dynamics, where each solitary state is characterized by the number of isolated oscillators and their disposition in space. We present system parameter regions for the existence of solitary states in the case of local, non-local, and global network couplings and show that they preserve in both thermodynamic and conservative limits. We give evidence that solitary states arise in a homoclinic bifurcation of a saddle-type synchronized state and die eventually in a crisis bifurcation after essential variation of the parameters.

Solitary states for coupled oscillators with inertia

NASA Astrophysics Data System (ADS)

Jaros, Patrycja; Brezetsky, Serhiy; Levchenko, Roman; Dudkowski, Dawid; Kapitaniak, Tomasz; Maistrenko, Yuri

2018-01-01

Networks of identical oscillators with inertia can display remarkable spatiotemporal patterns in which one or a few oscillators split off from the main synchronized cluster and oscillate with different averaged frequency. Such "solitary states" are impossible for the classical Kuramoto model with sinusoidal coupling. However, if inertia is introduced, these states represent a solid part of the system dynamics, where each solitary state is characterized by the number of isolated oscillators and their disposition in space. We present system parameter regions for the existence of solitary states in the case of local, non-local, and global network couplings and show that they preserve in both thermodynamic and conservative limits. We give evidence that solitary states arise in a homoclinic bifurcation of a saddle-type synchronized state and die eventually in a crisis bifurcation after essential variation of the parameters.

Coral reef fish assemblages along a disturbance gradient in the northern Persian Gulf: A seasonal perspective.

PubMed

Ghazilou, Amir; Shokri, Mohammad Reza; Gladstone, William

2016-04-30

Seasonal dynamics of coral reef fish assemblages were assessed along a gradient of potential anthropogenic disturbance in the Northern Persian Gulf. Overall, the attributes of coral reef fish assemblages showed seasonality at two different levels: seasonal changes irrespective of the magnitude of disturbance level (e.g. species richness), and seasonal changes in response to disturbance level (e.g. total abundance and assemblage composition). The examined parameters mostly belonged to the second group, but the interpretation of the relationship between patterns of seasonal changes and the disturbance level was not straightforward. The abundance of carnivorous fishes did not vary among seasons. SIMPER identified the family Nemipteridae as the major contributor to the observed spatiotemporal variations in the composition of coral reef fish assemblages in the study area. Copyright © 2015 Elsevier Ltd. All rights reserved.

Space-time variation of respiratory cancers in South Carolina: a flexible multivariate mixture modeling approach to risk estimation.

PubMed

Carroll, Rachel; Lawson, Andrew B; Kirby, Russell S; Faes, Christel; Aregay, Mehreteab; Watjou, Kevin

2017-01-01

Many types of cancer have an underlying spatiotemporal distribution. Spatiotemporal mixture modeling can offer a flexible approach to risk estimation via the inclusion of latent variables. In this article, we examine the application and benefits of using four different spatiotemporal mixture modeling methods in the modeling of cancer of the lung and bronchus as well as "other" respiratory cancer incidences in the state of South Carolina. Of the methods tested, no single method outperforms the other methods; which method is best depends on the cancer under consideration. The lung and bronchus cancer incidence outcome is best described by the univariate modeling formulation, whereas the "other" respiratory cancer incidence outcome is best described by the multivariate modeling formulation. Spatiotemporal multivariate mixture methods can aid in the modeling of cancers with small and sparse incidences when including information from a related, more common type of cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Propagation and spatiotemporal coupling characteristics of ultra-short Gaussian vortex pulse

NASA Astrophysics Data System (ADS)

Nie, Jianye; Liu, Guodong; Zhang, Rongzhu

2018-05-01

Based on Collins diffraction integral formula, the propagation equation of ultra-short Gaussian vortex pulse beam has been derived. Using the equation, the intensity distribution variations of vortex pulse in the propagation process are calculated. Specially, the spatiotemporal coupling characteristics of ultra-short vortex beams are discussed in detail. The results show that some key parameters, such as transverse distance, transmission distance, pulse width and topological charge number will influence the spatiotemporal coupling characteristics significantly. With the increasing of transverse distance, the waveforms of the pulses distort obviously. And when transmission distance is far than 50 mm, the distribution curve of transverse intensity gradually changes into a Gaussian type. In addition, initial pulse width will affect the distribution of light field, however, when initial pulse width is larger than 3 fs, the spatiotemporal coupling effect will be insignificant. Topological charge number does not affect the time delay characteristics, since with the increasing of topological charge number, the waveform of the pulse distorts gradually but the time delay does not occur.

Impacts of cattle grazing on spatio-temporal variability of soil moisture and above-ground live plant biomass in mixed grasslands

NASA Astrophysics Data System (ADS)

Virk, Ravinder

Areas with relatively high spatial heterogeneity generally have more biodiversity than spatially homogeneous areas due to increased potential habitat. Management practices such as controlled grazing also affect the biodiversity in grasslands, but the nature of this impact is not well understood. Therefore this thesis studies the impacts of variation in grazing on soil moisture and biomass heterogeneity. These are not only important in terms of management of protected grasslands, but also for designing an effective grazing system from a livestock management point of view. This research is a part of the cattle grazing experiment underway in Grasslands National Park (GNP) of Canada since 2006, as part of the adaptive management process for restoring ecological integrity of the northern mixed-grass prairie region. An experimental approach using field measurements and remote sensing (Landsat) was combined with modelling (CENTURY) to examine and predict the impacts of grazing intensity on the spatial heterogeneity and patterns of above-ground live plant biomass (ALB) in experimental pastures in a mixed grassland ecosystem. The field-based research quantified the temporal patterns and spatial variability in both soil moisture (SM) and ALB, and the influence of local intra-seasonal weather variability and slope location on the spatio-temporal variability of SM and ALB at field plot scales. Significant impacts of intra-seasonal weather variability, slope position and grazing pressure on SM and ALB across a range of scales (plot and local (within pasture)) were found. Grazing intensity significantly affected the ALB even after controlling for the effect of slope position. Satellite-based analysis extended the scale of interest to full pastures and the surrounding region to assess the effects of grazing intensity on the spatio-temporal pattern of ALB in mixed grasslands. Overall, low to moderate grazing intensity showed increase in ALB heterogeneity whereas no change in ALB heterogeneity over time was observed for heavy grazing intensity. All grazing intensities showed decrease in spatial range (patch size) over time indicating that grazing is a patchy process. The study demonstrates that cattle grazing with variable intensity can maintain and change the spatial patterns of vegetation in the studied region. Using a modelling approach, the relative degrees to which grazing intensity and soil properties affect grassland productivity and carbon dynamics at longer time-periods were investigated. Both grass productivity and carbon dynamics are sensitive to variability in soil texture and grazing intensity. Moderate grazing is predicted to be the best option in terms of maintaining sufficient heterogeneity to support species diversity, as well as for carbon management in the mixed grassland ecosystem.

A review on the temporal pattern of deer-vehicle accidents: impact of seasonal, diurnal and lunar effects in cervids.

PubMed

Steiner, Wolfgang; Leisch, Friedrich; Hackländer, Klaus

2014-05-01

The increasing number of deer-vehicle-accidents (DVAs) and the resulting economic costs have promoted numerous studies on behavioural and environmental factors which may contribute to the quantity, spatiotemporal distribution and characteristics of DVAs. Contrary to the spatial pattern of DVAs, data of their temporal pattern is scarce and difficult to obtain because of insufficient accuracy in available datasets, missing standardization in data aquisition, legal terms and low reporting rates to authorities. Literature of deer-traffic collisions on roads and railways is reviewed to examine current understanding of DVA temporal trends. Seasonal, diurnal and lunar peak accident periods are identified for deer, although seasonal pattern are not consistent among and within species or regions and data on effects of lunar cycles on DVAs is almost non-existent. Cluster analysis of seasonal DVA data shows nine distinct clusters of different seasonal DVA pattern for cervid species within the reviewed literature. Studies analyzing the relationship between time-related traffic predictors and DVAs yield mixed results. Despite the seasonal dissimilarity, diurnal DVA pattern are comparatively constant in deer, resulting in pronounced DVA peaks during the hours of dusk and dawn frequently described as bimodal crepuscular pattern. Behavioural aspects in activity seem to have the highest impact in DVAs temporal trends. Differences and variations are related to habitat-, climatic- and traffic characteristics as well as effects of predation, hunting and disturbance. Knowledge of detailed temporal DVA pattern is essential for prevention management as well as for the application and evaluation of mitigation measures. Copyright © 2014 Elsevier Ltd. All rights reserved.

Surfing the Pacific Island chains: linking internal wave energetics to coral reef benthic community patterns.

NASA Astrophysics Data System (ADS)

Painter Jones, Matilda; Green, Mattias; Gove, Jamison; Williams, Gareth

2017-04-01

The ocean is saturated with internal waves at tidal frequency. The energy associated with conversion from barotropic to baroclinic can enhance mixing and upwelling at sites of generation and dissipation, which in turn can drive primary production. Hotspots of internal wave generation are located at sudden changes in topography with the Hawaiian archipelago identified as an area of intense internal wave activity. The role of internal waves as a driver of benthic reef community is unexplored and could be key to coral reefs survival in the unknown future. Using a Pacific wide map of internal wave flux and barotropic-to-baroclinic conversion at an unprecedented 1/30th degree resolution, energy budgets were developed for four islands to evaluate dissipation and generation of internal waves. Spatiotemporal variations in benthic community structure were plotted around each island and related to changes in internal wave energetics using a boosted regression tree. Contrasting spatial patterns and species assemblages were seen around islands with distinct internal wave regimes. The relative importance and influence of internal waves on coral reef ecosystems is evaluated.

Conserved and divergent functions of Pax6 underlie species-specific neurogenic patterns in the developing amniote brain.

PubMed

Yamashita, Wataru; Takahashi, Masanori; Kikkawa, Takako; Gotoh, Hitoshi; Osumi, Noriko; Ono, Katsuhiko; Nomura, Tadashi

2018-04-16

The evolution of unique organ structures is associated with changes in conserved developmental programs. However, characterizing the functional conservation and variation of homologous transcription factors (TFs) that dictate species-specific cellular dynamics has remained elusive. Here, we dissect shared and divergent functions of Pax6 during amniote brain development. Comparative functional analyses revealed that the neurogenic function of Pax6 is highly conserved in the developing mouse and chick pallium, whereas stage-specific binary functions of Pax6 in neurogenesis are unique to mouse neuronal progenitors, consistent with Pax6-dependent temporal regulation of Notch signaling. Furthermore, we identified that Pax6-dependent enhancer activity of Dbx1 is extensively conserved between mammals and chick, although Dbx1 expression in the developing pallium is highly divergent in these species. Our results suggest that spatiotemporal changes in Pax6-dependent regulatory programs contributed to species-specific neurogenic patterns in mammalian and avian lineages, which underlie the morphological divergence of the amniote pallial architectures. © 2018. Published by The Company of Biologists Ltd.

Event Networks and the Identification of Crime Pattern Motifs

PubMed Central

2015-01-01

In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

Gait Analysis Methods for Rodent Models of Arthritic Disorders: Reviews and Recommendations

PubMed Central

Lakes, Emily H.; Allen, Kyle D.

2016-01-01

Gait analysis is a useful tool to understand behavioral changes in preclinical arthritis models. While observational scoring and spatiotemporal gait parameters are the most widely performed gait analyses in rodents, commercially available systems can now provide quantitative assessments of spatiotemporal patterns. However, inconsistencies remain between testing platforms, and laboratories often select different gait pattern descriptors to report in the literature. Rodent gait can also be described through kinetic and kinematic analyses, but systems to analyze rodent kinetics and kinematics are typically custom made and often require sensitive, custom equipment. While the use of rodent gait analysis rapidly expands, it is important to remember that, while rodent gait analysis is a relatively modern behavioral assay, the study of quadrupedal gait is not new. Nearly all gait parameters are correlated, and a collection of gait parameters is needed to understand a compensatory gait pattern used by the animal. As such, a change in a single gait parameter is unlikely to tell the full biomechanical story; and to effectively use gait analysis, one must consider how multiple different parameters contribute to an altered gait pattern. The goal of this article is to review rodent gait analysis techniques and provide recommendations on how to use these technologies in rodent arthritis models, including discussions on the strengths and limitations of observational scoring, spatiotemporal, kinetic, and kinematic measures. Recognizing rodent gait analysis is an evolving tool, we also provide technical recommendations we hope will improve the utility of these analyses in the future. PMID:26995111

Adaptive changes in spatiotemporal gait characteristics in women during pregnancy.

PubMed

Błaszczyk, Janusz W; Opala-Berdzik, Agnieszka; Plewa, Michał

2016-01-01

Spatiotemporal gait cycle characteristics were assessed at early (P1), and late (P2) pregnancy, as well as at 2 months (PP1) and 6 months (PP2) postpartum. A substantial decrease in walking speed was observed throughout the pregnancy, with the slowest speed (1±0.2m/s) being during the third trimester. Walking at slower velocity resulted in complex adaptive adjustments to their spatiotemporal gait pattern, including a shorter step length and an increased duration of both their stance and double-support phases. Duration of the swing phase remained the least susceptible to changes. Habitual walking velocity (1.13±0.2m/s) and the optimal gait pattern were fully recovered 6 months after childbirth. Documented here adaptive changes in the preferred gait pattern seem to result mainly from the altered body anthropometry leading to temporary balance impairments. All the observed changes within stride cycle aimed to improve gait safety by focusing on its dynamic stability. The pregnant women preferred to walk at a slower velocity which allowed them to spend more time in double-support compared with their habitual pattern. Such changes provided pregnant women with a safer and more tentative ambulation that reduced the single-support period and, hence, the possibility of instability. As pregnancy progressed a significant increase in stance width and a decrease in step length was observed. Both factors allow also for gait stability improvement. Copyright © 2015 Elsevier B.V. All rights reserved.

Pattern formation in diffusive excitable systems under magnetic flow effects

NASA Astrophysics Data System (ADS)

Mvogo, Alain; Takembo, Clovis N.; Ekobena Fouda, H. P.; Kofané, Timoléon C.

2017-07-01

We study the spatiotemporal formation of patterns in a diffusive FitzHugh-Nagumo network where the effect of electromagnetic induction has been introduced in the standard mathematical model by using magnetic flux, and the modulation of magnetic flux on membrane potential is realized by using memristor coupling. We use the multi-scale expansion to show that the system equations can be reduced to a single differential-difference nonlinear equation. The linear stability analysis is performed and discussed with emphasis on the impact of magnetic flux. It is observed that the effect of memristor coupling importantly modifies the features of modulational instability. Our analytical results are supported by the numerical experiments, which reveal that the improved model can lead to nonlinear quasi-periodic spatiotemporal patterns with some features of synchronization. It is observed also the generation of pulses and rhythmics behaviors like breathing or swimming which are important in brain researches.

Spatiotemporal pattern in somitogenesis: a non-Turing scenario with wave propagation.

PubMed

Nagahara, Hiroki; Ma, Yue; Takenaka, Yoshiko; Kageyama, Ryoichiro; Yoshikawa, Kenichi

2009-08-01

Living organisms maintain their lives under far-from-equilibrium conditions by creating a rich variety of spatiotemporal structures in a self-organized manner, such as temporal rhythms, switching phenomena, and development of the body. In this paper, we focus on the dynamical process of morphogens in somitogenesis in mice where propagation of the gene expression level plays an essential role in creating the spatially periodic patterns of the vertebral columns. We present a simple discrete reaction-diffusion model which includes neighboring interaction through an activator, but not diffusion of an inhibitor. We can produce stationary periodic patterns by introducing the effect of spatial discreteness to the field. Based on the present model, we discuss the underlying physical principles that are independent of the details of biomolecular reactions. We also discuss the framework of spatial discreteness based on the reaction-diffusion model in relation to a cellular array, by comparison with an actual experimental observation.

The Spatiotemporal Structure of 20th Century Climate Variations in Observations and Reanalyses. Part 1; Long-term Trend

NASA Technical Reports Server (NTRS)

Chen, Junye; DelGenio, Anthony D.; Carlson, Barbara e.; Bosilovich, Michael G.

2007-01-01

The dominant interannual El Nino-Southern Oscillation phenomenon (ENSO) and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENS0 signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, we develop an ENSO-removal method through which the ENS0 signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations, namely, the global warming trend (GW) and the Pacific pan-decadal variability (PDV), are isolated at middle and low latitudes in the climate parameter fields from observed and reanalyses datasets. Except for known GW characteristics, the warming that occurs in the Pacific basin (approximately 0.4K in the 2oth century) is much weaker than in surrounding regions and the other two ocean basins (approximately 0.8K). The modest warming in the Pacific basin is likely due to its dynamic nature on the interannual and decadal time scales and/or the leakage of upper ocean water through the Indonesian Throughflow. Based on NCEP/NCAR and ERA-40 reanalyses, a comprehensive atmospheric structure associated with GW is given. Significant discrepancies exist between the two datasets, especially in the tightly coupled dynamic and water vapor fields. The dynamic field based on NCEP/NCAR reanalysis, which shows a change in the Walker Circulation, is consistent with the GW change in the surface temperature field. However, intensification in the Hadley Circulation is associated with GW trend in the ERA-40 reanalysis.

Spatio-temporal variation of seismicity before the 1971 San Fernando earthquake, California

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

Ishida, M.; Kanamori, H.

1977-08-01

The spatio-temporal variation of seismicity prior to the 1971 San Fernando, California, earthquake is studied for the area within 35 km of the epicenter. During the period from 1932 to 1961, the seismicity in this area was relatively low and random. A remarkable NE-SW trending alignment of activity occurred during the period from 1961 to 1964, the period corresponding to the inferred onset of the Palmdale uplift. During the period from 1965 to 1968, the seismicity around the epicentral area became extremely low; no event was located within 13 km from the epicenter. During the period from 1969 to themore » occurrence of the San Fernando earthquake, activity around the epicentral area increased. This activity may be considered to be foreshock activity in a broad sense.« less

Century-Long Warming Trends in the Upper Water Column of Lake Tanganyika.

PubMed

Kraemer, Benjamin M; Hook, Simon; Huttula, Timo; Kotilainen, Pekka; O'Reilly, Catherine M; Peltonen, Anu; Plisnier, Pierre-Denis; Sarvala, Jouko; Tamatamah, Rashid; Vadeboncoeur, Yvonne; Wehrli, Bernhard; McIntyre, Peter B

2015-01-01

Lake Tanganyika, the deepest and most voluminous lake in Africa, has warmed over the last century in response to climate change. Separate analyses of surface warming rates estimated from in situ instruments, satellites, and a paleolimnological temperature proxy (TEX86) disagree, leaving uncertainty about the thermal sensitivity of Lake Tanganyika to climate change. Here, we use a comprehensive database of in situ temperature data from the top 100 meters of the water column that span the lake's seasonal range and lateral extent to demonstrate that long-term temperature trends in Lake Tanganyika depend strongly on depth, season, and latitude. The observed spatiotemporal variation in surface warming rates accounts for small differences between warming rate estimates from in situ instruments and satellite data. However, after accounting for spatiotemporal variation in temperature and warming rates, the TEX86 paleolimnological proxy yields lower surface temperatures (1.46 °C lower on average) and faster warming rates (by a factor of three) than in situ measurements. Based on the ecology of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy), we offer a reinterpretation of the TEX86 data from Lake Tanganyika as the temperature of the low-oxygen zone, rather than of the lake surface temperature as has been suggested previously. Our analyses provide a thorough accounting of spatiotemporal variation in warming rates, offering strong evidence that thermal and ecological shifts observed in this massive tropical lake over the last century are robust and in step with global climate change.

Spatiotemporal variations of radar glacier zones in the Karakoram Mountains

NASA Astrophysics Data System (ADS)

Lund, Jewell

2017-04-01

Glaciers of the Karakoram Mountains are important climate indicators for densely populated South Central Asia. Glacial meltwater is a significant source of runoff in the Indus River Basin, upon which 60 million people rely for food security, economy and hydropower in Pakistan and India. Contrary to worldwide and also Himalayan trends, Karakoram glaciers have recently been verified in near balance, with some glaciers even gaining mass or surging. This 'Karakoram anomaly' is of interest, and many hypotheses exist for its causes. Complex climatology, coupled with the challenges of field study in this region, illicit notable uncertainties both in observation and prediction of glacial status. Constraining spatiotemporal variations in glacial mass balance will elucidate the extent and possible longevity of this anomaly, and its implications for water resources, as climate continues to change. Depending on snowpack conditions during image acquisition, different snow and ice zones on a glacier are identifiable in synthetic aperture radar (SAR) images. The identification and monitoring of radar glacier zones over time can provide indicators of relative glacial mass balance to compliment field studies in a region with sparse field measurement. We will present spatiotemporal evolution of basic radar glacier zones such as wet snow, bare ice, percolation, and firn for glaciers feeding into the Upper Indus Basin. We will incorporate both ascending and descending passes of Sentinel-1 series C -band sensors, and possibly ALOS-2 PALSAR-2 L-band images. We may also explore the impacts of these variations on timing and intensity of runoff.

Spatiotemporal chaos and two-dimensional dissipative rogue waves in Lugiato-Lefever model

NASA Astrophysics Data System (ADS)

Panajotov, Krassimir; Clerc, Marcel G.; Tlidi, Mustapha

2017-06-01

Driven nonlinear optical cavities can exhibit complex spatiotemporal dynamics. We consider the paradigmatic Lugiato-Lefever model describing driven nonlinear optical resonator. This model is one of the most-studied nonlinear equations in optics. It describes a large spectrum of nonlinear phenomena from bistability, to periodic patterns, localized structures, self-pulsating localized structures and to a complex spatiotemporal behavior. The model is considered also as prototype model to describe several optical nonlinear devices such as Kerr media, liquid crystals, left handed materials, nonlinear fiber cavity, and frequency comb generation. We focus our analysis on a spatiotemporal chaotic dynamics in one-dimension. We identify a route to spatiotemporal chaos through an extended quasiperiodicity. We have estimated the Kaplan-Yorke dimension that provides a measure of the strange attractor complexity. Likewise, we show that the Lugiato-Leferver equation supports rogues waves in two-dimensional settings. We characterize rogue-wave formation by computing the probability distribution of the pulse height. Contribution to the Topical Issue "Theory and Applications of the Lugiato-Lefever Equation", edited by Yanne K. Chembo, Damia Gomila, Mustapha Tlidi, Curtis R. Menyuk.

GF-1 and Landsat observed a 40-year wetland spatiotemporal variation and its coupled environmental factors in Yangtze River estuary

NASA Astrophysics Data System (ADS)

Sun, Nan; Zhu, Weining; Cheng, Qian

2018-07-01

Wetlands are health indicators of aquatic ecosystems and also vulnerable to regional environmental and socio-economic changes. For exploring wetland spatiotemporal variations in estuarine and coastal regions of the Yangtze River, we extracted wetland information from 40-year time-series images of Landsat, GF-1, and other satellites, using the classification method of decision tree. Potential environmental and socio-economic factors which may drive wetland variations were analyzed. Results show that the wetland area in Yangtze River estuary has increased 663 km2, but it was only contributed by the increasing of human-made wetlands (767 km2), which were mostly caused by economic growth and constructions of human-made hydro-projects in Yangtze Delta. In comparison, natural wetlands, such as tidal flats and marshes, have decreased 163 km2. Land reclamation has changed these natural wetlands into reservoirs, aquaculture ponds and paddy fields. Wetlands in Shanghai and Qidong urban regions were mainly affected by human activities, while wetland variations in Chongming Island were mainly controlled by natural factors such as the upstream discharge, precipitation, diurnal variation of tidal level and long-term sea level rising. The general trend is that the natural wetland was transformed into the human-made wetland, and the human-made wetland was transformed into construction land.

Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005–2014

PubMed Central

Mahara, Gehendra; Wang, Chao; Huo, Da; Xu, Qin; Huang, Fangfang; Tao, Lixin; Guo, Jin; Cao, Kai; Long, Liu; Chhetri, Jagadish K.; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-01-01

Objective: To probe the spatiotemporal patterns of the incidence of scarlet fever in Beijing, China, from 2005 to 2014. Methods: A spatiotemporal analysis was conducted at the district/county level in the Beijing region based on the reported cases of scarlet fever during the study period. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation of scarlet fever, whereas the Getis-Ord Gi* statistic was used to determine the hotspot incidence of scarlet fever. Likewise, the space-time scan statistic was used to detect the space-time clusters, including the relative risk of scarlet fever incidence across all settings. Results: A total of 26,860 scarlet fever cases were reported in Beijing during the study period (2005–2014). The average annual incidence of scarlet fever was 14.25 per 100,000 population (range, 6.76 to 32.03 per 100,000). The incidence among males was higher than that among females, and more than two-thirds of scarlet fever cases (83.8%) were among children 3–8 years old. The seasonal incidence peaks occurred from March to July. A higher relative risk area was mainly in the city and urban districts of Beijing. The most likely space-time clusters and secondary clusters were detected to be diversely distributed in every study year. Conclusions: The spatiotemporal patterns of scarlet fever were relatively unsteady in Beijing from 2005 to 2014. The at-risk population was mainly scattered in urban settings and dense districts with high population, indicating a positive relationship between population density and increased risk of scarlet fever exposure. Children under 15 years of age were the most susceptible to scarlet fever. PMID:26784213

Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005-2014.

PubMed

Mahara, Gehendra; Wang, Chao; Huo, Da; Xu, Qin; Huang, Fangfang; Tao, Lixin; Guo, Jin; Cao, Kai; Long, Liu; Chhetri, Jagadish K; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-01-15

To probe the spatiotemporal patterns of the incidence of scarlet fever in Beijing, China, from 2005 to 2014. A spatiotemporal analysis was conducted at the district/county level in the Beijing region based on the reported cases of scarlet fever during the study period. Moran's autocorrelation coefficient was used to examine the spatial autocorrelation of scarlet fever, whereas the Getis-Ord Gi* statistic was used to determine the hotspot incidence of scarlet fever. Likewise, the space-time scan statistic was used to detect the space-time clusters, including the relative risk of scarlet fever incidence across all settings. A total of 26,860 scarlet fever cases were reported in Beijing during the study period (2005-2014). The average annual incidence of scarlet fever was 14.25 per 100,000 population (range, 6.76 to 32.03 per 100,000). The incidence among males was higher than that among females, and more than two-thirds of scarlet fever cases (83.8%) were among children 3-8 years old. The seasonal incidence peaks occurred from March to July. A higher relative risk area was mainly in the city and urban districts of Beijing. The most likely space-time clusters and secondary clusters were detected to be diversely distributed in every study year. The spatiotemporal patterns of scarlet fever were relatively unsteady in Beijing from 2005 to 2014. The at-risk population was mainly scattered in urban settings and dense districts with high population, indicating a positive relationship between population density and increased risk of scarlet fever exposure. Children under 15 years of age were the most susceptible to scarlet fever.

How innate is locomotion in precocial animals? A study on the early development of spatio-temporal gait variables and gait symmetry in piglets.

PubMed

Vanden Hole, Charlotte; Goyens, Jana; Prims, Sara; Fransen, Erik; Ayuso Hernando, Miriam; Van Cruchten, Steven; Aerts, Peter; Van Ginneken, Chris

2017-08-01

Locomotion is one of the most important ecological functions in animals. Precocial animals, such as pigs, are capable of independent locomotion shortly after birth. This raises the question whether coordinated movement patterns and the underlying muscular control in these animals is fully innate or whether there still exists a rapid maturation. We addressed this question by studying gait development in neonatal pigs through the analysis of spatio-temporal gait characteristics during locomotion at self-selected speed. To this end, we made video recordings of piglets walking along a corridor at several time points (from 0 h to 96 h). After digitization of the footfalls, we analysed self-selected speed and spatio-temporal characteristics (e.g. stride and step lengths, stride frequency and duty factor) to study dynamic similarity, intralimb coordination and interlimb coordination. To assess the variability of the gait pattern, left-right asymmetry was studied. To distinguish neuromotor maturation from effects caused by growth, both absolute and normalized data (according to the dynamic similarity concept) were included in the analysis. All normalized spatio-temporal variables reached stable values within 4 h of birth, with most of them showing little change after the age of 2 h. Most asymmetry indices showed stable values, hovering around 10%, within 8 h of birth. These results indicate that coordinated movement patterns are not entirely innate, but that a rapid neuromotor maturation, potentially also the result of the rearrangement or recombination of existing motor modules, takes place in these precocial animals. © 2017. Published by The Company of Biologists Ltd.

Effective and efficient analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

Zhang, Zhongnan

Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen very soon. This dissertation is composed of three parts: an introduction, some basic knowledges and relative works, and my own three contributions to the development of approaches for spatio-temporal data mining: DYSTAL algorithm, STARSI algorithm, and COSTCOP+ algorithm.

Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.

PubMed

Kolovos, Alexander; Skupin, André; Jerrett, Michael; Christakos, George

2010-09-01

Space-time data analysis and assimilation techniques in atmospheric sciences typically consider input from monitoring measurements. The input is often processed in a manner that acknowledges characteristics of the measurements (e.g., underlying patterns, fluctuation features) under conditions of uncertainty; it also leads to the derivation of secondary information that serves study-oriented goals, and provides input to space-time prediction techniques. We present a novel approach that blends a rigorous space-time prediction model (Bayesian maximum entropy, BME) with a cognitively informed visualization of high-dimensional data (spatialization). The combined BME and spatialization approach (BME-S) is used to study monthly averaged NO2 and mean annual SO4 measurements in California over the 15-year period 1988-2002. Using the original scattered measurements of these two pollutants BME generates spatiotemporal predictions on a regular grid across the state. Subsequently, the prediction network undergoes the spatialization transformation into a lower-dimensional geometric representation, aimed at revealing patterns and relationships that exist within the input data. The proposed BME-S provides a powerful spatiotemporal framework to study a variety of air pollution data sources.

Spatiotemporal topology and temporal sequence identification with an adaptive time-delay neural network

NASA Astrophysics Data System (ADS)

Lin, Daw-Tung; Ligomenides, Panos A.; Dayhoff, Judith E.

1993-08-01

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

Spatio-Temporal Dynamics of Fructan Metabolism in Developing Barley Grains[W

PubMed Central

Peukert, Manuela; Thiel, Johannes; Peshev, Darin; Weschke, Winfriede; Van den Ende, Wim; Mock, Hans-Peter; Matros, Andrea

2014-01-01

Barley (Hordeum vulgare) grain development follows a series of defined morphological and physiological stages and depends on the supply of assimilates (mainly sucrose) from the mother plant. Here, spatio-temporal patterns of sugar distributions were investigated by mass spectrometric imaging, targeted metabolite analyses, and transcript profiling of microdissected grain tissues. Distinct spatio-temporal sugar balances were observed, which may relate to differentiation and grain filling processes. Notably, various types of oligofructans showed specific distribution patterns. Levan- and graminan-type oligofructans were synthesized in the cellularized endosperm prior to the commencement of starch biosynthesis, while during the storage phase, inulin-type oligofructans accumulated to a high concentration in and around the nascent endosperm cavity. In the shrunken endosperm mutant seg8, with a decreased sucrose flux toward the endosperm, fructan accumulation was impaired. The tight partitioning of oligofructan biosynthesis hints at distinct functions of the various fructan types in the young endosperm prior to starch accumulation and in the endosperm transfer cells that accomplish the assimilate supply toward the endosperm at the storage phase. PMID:25271242

Spatio-temporal genetic variation of the biting midge vector species Culicoides imicola (Ceratopogonidae) Kieffer in France.

PubMed

Jacquet, Stéphanie; Huber, Karine; Guis, Hélène; Setier-Rio, Marie-Laure; Goffredo, Maria; Allène, Xavier; Rakotoarivony, Ignace; Chevillon, Christine; Bouyer, Jérémy; Baldet, Thierry; Balenghien, Thomas; Garros, Claire

2016-03-11

Introduction of vector species into new areas represents a main driver for the emergence and worldwide spread of vector-borne diseases. This poses a substantial threat to livestock economies and public health. Culicoides imicola Kieffer, a major vector species of economically important animal viruses, is described with an apparent range expansion in Europe where it has been recorded in south-eastern continental France, its known northern distribution edge. This questioned on further C. imicola population extension and establishment into new territories. Studying the spatio-temporal genetic variation of expanding populations can provide valuable information for the design of reliable models of future spread. Entomological surveys and population genetic approaches were used to assess the spatio-temporal population dynamics of C. imicola in France. Entomological surveys (2-3 consecutive years) were used to evaluate population abundances and local spread in continental France (28 sites in the Var department) and in Corsica (4 sites). We also genotyped at nine microsatellite loci insects from 3 locations in the Var department over 3 years (2008, 2010 and 2012) and from 6 locations in Corsica over 4 years (2002, 2008, 2010 and 2012). Entomological surveys confirmed the establishment of C. imicola populations in Var department, but indicated low abundances and no apparent expansion there within the studied period. Higher population abundances were recorded in Corsica. Our genetic data suggested the absence of spatio-temporal genetic changes within each region but a significant increase of the genetic differentiation between Corsican and Var populations through time. The lack of intra-region population structure may result from strong gene flow among populations. We discussed the observed temporal variation between Corsica and Var as being the result of genetic drift following introduction, and/or the genetic characteristics of populations at their range edge. Our results suggest that local range expansion of C. imicola in continental France may be slowed by the low population abundances and unsuitable climatic and environmental conditions.

Spatiotemporal variation in deer browse and tolerance in a woodland herb

Treesearch

Holly R. Prendeville; Janet C. Steven; Laura F. Galloway

2015-01-01

Herbivory can shape the dynamics of plant populations, including effects on survival and reproduction, and is in turn affected by environmental factors that vary in space and time. White-tailed deer are significant herbivores in North America that have been broadly documented to affect plant reproductive success. If variation in the frequency and impact of herbivory by...

[Spatiotemporal characteristics of photosynthetically active radiation in understory of Korean pine and broadleaved mixed forest in Changbai Mountains].

PubMed

Yuan, Feng-Hui; Guan, De-Xin; Wu, Jia-Bing; Wang, An-Zhi; Shi, Ting-Ting; Zhang, Xiao-Jing

2008-02-01

Based on the data of three years successive automatic measurement with five horizontal quantum PAR sensors, this paper studied the spatiotemporal characteristics of photosynthetically active radiation (PAR) in the understory of Korean pine and broadleaved mixed forest in Changbai Mountains, in contrast with above-canopy PAR. It was found that the annual dynamics of above-canopy PAR showed two or more peaks, which was mainly affected by the weather conditions such as cloudy, foggy and rainy events. The annual dynamics of understory PAR followed the same trend of above-canopy PAR in non-growth season, but was steady and lower in numerical value in growth season. On clear days, larger differences were observed in the diurnal variation and frequency distribution of the understory PAR. As for the spatial variation of the understory PAR, the coefficient of variation (CV) was smaller in non-growth season (about 0.15) than in growth season (> 0.22), with the greatest in August. On the clear days in growth season, the understory PAR had a greater spatial variation when the solar elevation angle was between 38 degrees and 48 degrees (at 9:00-10:00 or 13:00-14:00).

Spatiotemporal drought forecasting using nonlinear models

NASA Astrophysics Data System (ADS)

Vasiliades, Lampros; Loukas, Athanasios

2010-05-01

Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with increase in lead time. Finally, the developed nonlinear models could be used in an early warning system for risk and decision analyses at the study area.

A spatiotemporal model to assess the introduction risk of African horse sickness by import of animals and vectors in France.

PubMed

Faverjon, C; Leblond, A; Hendrikx, P; Balenghien, T; de Vos, C J; Fischer, E A J; de Koeijer, A A

2015-06-04

African horse sickness (AHS) is a major, Culicoides-borne viral disease in equines whose introduction into Europe could have dramatic consequences. The disease is considered to be endemic in sub-Saharan Africa. Recent introductions of other Culicoides-borne viruses (bluetongue and Schmallenberg) into northern Europe have highlighted the risk that AHS may arrive in Europe as well. The aim of our study was to provide a spatiotemporal quantitative risk model of AHS introduction into France. The study focused on two pathways of introduction: the arrival of an infectious host (PW-host) and the arrival of an infectious Culicoides midge via the livestock trade (PW-vector). The risk of introduction was calculated by determining the probability of an infectious animal or vector entering the country and the probability of the virus then becoming established: i.e., the virus's arrival in France resulting in at least one local equine host being infected by one local vector. This risk was assessed using data from three consecutive years (2010 to 2012) for 22 regions in France. The results of the model indicate that the annual risk of AHS being introduced to France is very low but that major spatiotemporal differences exist. For both introduction pathways, risk is higher from July to October and peaks in July. In general, regions with warmer climates are more at risk, as are colder regions with larger equine populations; however, regional variation in animal importation patterns (number and species) also play a major role in determining risk. Despite the low probability that AHSV is present in the EU, intra-EU trade of equines contributes most to the risk of AHSV introduction to France because it involves a large number of horse movements. It is important to address spatiotemporal differences when assessing the risk of ASH introduction and thus also when implementing efficient surveillance efforts. The methods and results of this study may help develop surveillance techniques and other risk reduction measures that will prevent the introduction of AHS or minimize AHS' potential impact once introduced, both in France and the rest of Europe.

Partitioning the factors of spatial variation in regeneration density of shade-tolerant tree species.

PubMed

Gravel, Dominique; Beaudet, Marilou; Messier, Christian

2008-10-01

Understanding coexistence of highly shade-tolerant tree species is a longstanding challenge for forest ecologists. A conceptual model for the coexistence of sugar maple (Acer saccharum) and American beech (Fagus grandibfolia) has been proposed, based on a low-light survival/high-light growth trade-off, which interacts with soil fertility and small-scale spatiotemporal variation in the environment. In this study, we first tested whether the spatial distribution of seedlings and saplings can be predicted by the spatiotemporal variability of light availability and soil fertility, and second, the manner in which the process of environmental filtering changes with regeneration size. We evaluate the support for this hypothesis relative to the one for a neutral model, i.e., for seed rain density predicted from the distribution of adult trees. To do so, we performed intensive sampling over 86 quadrats (5 x 5 m) in a 0.24-ha plot in a mature maple-beech community in Quebec, Canada. Maple and beech abundance, soil characteristics, light availability, and growth history (used as a proxy for spatiotemporal variation in light availability) were finely measured to model variation in sapling composition across different size classes. Results indicate that the variables selected to model species distribution do effectively change with size, but not as predicted by the conceptual model. Our results show that variability in the environment is not sufficient to differentiate these species' distributions in space. Although species differ in their spatial distribution in the small size classes, they tend to correlate at the larger size class in which recruitment occurs. Overall, the results are not supportive of a model of coexistence based on small-scale variations in the environment. We propose that, at the scale of a local stand, the lack of fit of the model could result from the high similarity of species in the range of environmental conditions encountered, and we suggest that coexistence would be stable only at larger spatial scales at which variability in the environment is greater.

The Influence of Weather and Lemmings on Spatiotemporal Variation in the Abundance of Multiple Avian Guilds in the Arctic

PubMed Central

Robinson, Barry G.; Franke, Alastair; Derocher, Andrew E.

2014-01-01

Climate change is occurring more rapidly in the Arctic than other places in the world, which is likely to alter the distribution and abundance of migratory birds breeding there. A warming climate can provide benefits to birds by decreasing spring snow cover, but increases in the frequency of summer rainstorms, another product of climate change, may reduce foraging opportunities for insectivorous birds. Cyclic lemming populations in the Arctic also influence bird abundance because Arctic foxes begin consuming bird eggs when lemmings decline. The complex interaction between summer temperature, precipitation, and the lemming cycle hinder our ability to predict how Arctic-breeding birds will respond to climate change. The main objective of this study was to investigate the relationship between annual variation in weather, spring snow cover, lemming abundance and spatiotemporal variation in the abundance of multiple avian guilds in a tundra ecosystem in central Nunavut, Canada: songbirds, shorebirds, gulls, loons, and geese. We spatially stratified our study area based on vegetation productivity, terrain ruggedness, and freshwater abundance, and conducted distance sampling to estimate strata-specific densities of each guild during the summers of 2010–2012. We also monitored temperature, rainfall, spring snow cover, and lemming abundance each year. Spatial variation in bird abundance matched what was expected based on previous ecological knowledge, but weather and lemming abundance also significantly influenced the abundance of some guilds. In particular, songbirds were less abundant during the cool, wet summer with moderate snow cover, and shorebirds and gulls declined with lemming abundance. The abundance of geese did not vary over time, possibly because benefits created by moderate spring snow cover were offset by increased fox predation when lemmings were scarce. Our study provides an example of a simple way to monitor the correlation between weather, spring snow cover, lemming abundance, and spatiotemporal variations in Arctic-breeding birds. PMID:24983471

Assessment of microscale spatio-temporal variation of air pollution at an urban hotspot in Madrid (Spain) through an extensive field campaign

NASA Astrophysics Data System (ADS)

Borge, Rafael; Narros, Adolfo; Artíñano, Begoña; Yagüe, Carlos; Gómez-Moreno, Francisco Javier; de la Paz, David; Román-Cascón, Carlos; Díaz, Elías; Maqueda, Gregorio; Sastre, Mariano; Quaassdorff, Christina; Dimitroulopoulou, Chrysanthi; Vardoulakis, Sotiris

2016-09-01

Poor urban air quality is one of the main environmental concerns worldwide due to its implications for population exposure and health-related issues. However, the development of effective abatement strategies in cities requires a consistent and holistic assessment of air pollution processes, taking into account all the relevant scales within a city. This contribution presents the methodology and main results of an intensive experimental campaign carried out in a complex pollution hotspot in Madrid (Spain) under the TECNAIRE-CM research project, which aimed at understanding the microscale spatio-temporal variation of ambient concentration levels in areas where high pollution values are recorded. A variety of instruments were deployed during a three-week field campaign to provide detailed information on meteorological and micrometeorological parameters and spatio-temporal variations of the most relevant pollutants (NO2 and PM) along with relevant information needed to simulate pedestrian fluxes. The results show the strong dependence of ambient concentrations on local emissions and meteorology that turns out in strong spatial and temporal variations, with gradients up to 2 μg m-3 m-1 for NO2 and 55 μg m-3 min-1 for PM10. Pedestrian exposure to these pollutants also presents strong variations temporally and spatially but it concentrates on pedestrian crossings and bus stops. The analysis of the results show that the high concentration levels found in urban hotspots depend on extremely complex dynamic processes that cannot be captured by routinely measurements made by air quality monitoring stations used for regulatory compliance assessment. The large influence from local traffic in the concentration fields highlights the need for a detailed description of specific variables that determine emissions and dispersion at microscale level. This also indicates that city-scale interventions may be complemented with local control measures and exposure management, to improve air quality and reduce air pollution health effects more effectively.

The influence of weather and lemmings on spatiotemporal variation in the abundance of multiple avian guilds in the arctic.

PubMed

Robinson, Barry G; Franke, Alastair; Derocher, Andrew E

2014-01-01

Climate change is occurring more rapidly in the Arctic than other places in the world, which is likely to alter the distribution and abundance of migratory birds breeding there. A warming climate can provide benefits to birds by decreasing spring snow cover, but increases in the frequency of summer rainstorms, another product of climate change, may reduce foraging opportunities for insectivorous birds. Cyclic lemming populations in the Arctic also influence bird abundance because Arctic foxes begin consuming bird eggs when lemmings decline. The complex interaction between summer temperature, precipitation, and the lemming cycle hinder our ability to predict how Arctic-breeding birds will respond to climate change. The main objective of this study was to investigate the relationship between annual variation in weather, spring snow cover, lemming abundance and spatiotemporal variation in the abundance of multiple avian guilds in a tundra ecosystem in central Nunavut, Canada: songbirds, shorebirds, gulls, loons, and geese. We spatially stratified our study area based on vegetation productivity, terrain ruggedness, and freshwater abundance, and conducted distance sampling to estimate strata-specific densities of each guild during the summers of 2010-2012. We also monitored temperature, rainfall, spring snow cover, and lemming abundance each year. Spatial variation in bird abundance matched what was expected based on previous ecological knowledge, but weather and lemming abundance also significantly influenced the abundance of some guilds. In particular, songbirds were less abundant during the cool, wet summer with moderate snow cover, and shorebirds and gulls declined with lemming abundance. The abundance of geese did not vary over time, possibly because benefits created by moderate spring snow cover were offset by increased fox predation when lemmings were scarce. Our study provides an example of a simple way to monitor the correlation between weather, spring snow cover, lemming abundance, and spatiotemporal variations in Arctic-breeding birds.

Spatiotemporal variation in diabetes mortality in China: multilevel evidence from 2006 and 2012.

PubMed

Zhou, Maigeng; Astell-Burt, Thomas; Yin, Peng; Feng, Xiaoqi; Page, Andrew; Liu, Yunning; Liu, Jiangmei; Li, Yichong; Liu, Shiwei; Wang, Limin; Wang, Lijun; Wang, Linhong

2015-07-10

Despite previous studies reporting spatial in equality in diabetes prevalence across China, potential geographic variations in diabetes mortality have not been explored. Age and gender stratified annual diabetes mortality counts for 161 counties were extracted from the China Mortality Surveillance System and interrogated using multilevel negative binomial regression. Random slopes were used to investigate spatiotemporal variation and the proportion of variance explained was used to assess the relative importance of geographical region, urbanization, mean temperature, local diabetes prevalence, behavioral risk factors and relevant biomarkers. Diabetes mortality tended to reduce between 2006 and 2012, though there appeared to be an increase in diabetes mortality in urban (age standardized rate (ASR) 2006-2012: 10.5-13.6) and rural (ASR 10.8-13.0) areas in the Southwest region. A Median Rate Ratio of 1.47, slope variance of 0.006 (SE 0.001) and covariance of 0.268 (SE 0.007) indicated spatiotemporal variation. Fully adjusted models accounted for 37% of this geographical variation, with diabetes mortality higher in the Northwest (RR 2.55, 95% CI 1.74, 3.73) and Northeast (RR 2.68, 95% CI 1.70, 4.21) compared with the South. Diabetes mortality was higher in urbanized areas (RR tertile 3 versus tertile 1 ('RRt3vs1') 1.39, 95% CI 1.17, 1.66), with higher mean body mass index (RRt3vs1 1.46, 95% CI 1.18, 1.80) and with higher average temperatures (RR 1.05 95% CI 1.03, 1.08). Diabetes mortality was lower where consumption of alcohol was excessive (RRt3vs1 0.84, 95% CI 0.72, 0.99). No association was observed with smoking, overconsumption of red meat, high mean sedentary time, systolic blood pressure, cholesterol, and diabetes prevalence. Declines in diabetes mortality between 2006 and 2012 have been unequally distributed across China, which may imply differentials in diagnosis, management, and the provision of services that warrant further investigation.

Spatial and temporal variations of thaw layer thickness and its controlling factors identified using time-lapse electrical resistivity tomography and hydro-thermal modeling

NASA Astrophysics Data System (ADS)

Tran, Anh Phuong; Dafflon, Baptiste; Bisht, Gautam; Hubbard, Susan S.

2018-06-01

Quantitative understanding of controls on thaw layer thickness (TLT) dynamics in the Arctic peninsula is essential for predictive understanding of permafrost degradation feedbacks to global warming and hydrobiochemical processes. This study jointly interprets electrical resistivity tomography (ERT) measurements and hydro-thermal numerical simulation results to assess spatiotemporal variations of TLT and to determine its controlling factors in Barrow, Alaska. Time-lapse ERT measurements along a 35-m transect were autonomously collected from 2013 to 2015 and inverted to obtain soil electrical resistivity. Based on several probe-based TLT measurements and co-located soil electrical resistivity, we estimated the electrical resistivity thresholds associated with the boundary between the thaw layer and permafrost using a grid search optimization algorithm. Then, we used the obtained thresholds to derive the TLT from all soil electrical resistivity images. The spatiotemporal analysis of the ERT-derived TLT shows that the TLT at high-centered polygons (HCPs) is smaller than that at low-centered polygons (LCPs), and that both thawing and freezing occur earlier at the HCPs compared to the LCPs. In order to provide a physical explanation for dynamics in the thaw layer, we performed 1-D hydro-thermal simulations using the community land model (CLM). Simulation results showed that air temperature and precipitation jointly govern the temporal variations of TLT, while the topsoil organic content (SOC) and polygon morphology are responsible for its spatial variations. When the topsoil SOC and its thickness increase, TLT decreases. Meanwhile, at LCPs, a thicker snow layer and saturated soil contribute to a thicker TLT and extend the time needed for TLT to freeze and thaw. This research highlights the importance of combination of measurements and numerical modeling to improve our understanding spatiotemporal variations and key controls of TLT in cold regions.

Temporal variation of autotrophic picoplankton contribution to coastal phytoplankton communities over a seasonal cycle: A case study

NASA Astrophysics Data System (ADS)

Koçum, Esra

2017-04-01

Autotrophic pico-plankton form the smallest component of phytoplankton and refers to cells smaller than 2 µM. It is phylogenetically diverse and have both prokaryotic and eukaryotic components. Prokaryotic pico-autotrophs are unicellular cyanobacteria, represented mainly by Prochlorococcus and Synechococcus genera. Pico-eukaryotes are more diverse and include members of Chlorophyta, Cryptophyta, Haptophyta and Heterokontophyta. Owing to their higher nutrient acquisition capacity, relative share of pico-plankton in autotrophic production and biomass can be significant and even dominant in oligotrophic regions such as in warm tropical waters. They also fare better than larger members of phytoplankton communities under light limitation and under increasing temperature. Recent work has shown that autotrophic pico-plankton can be a significant component of coastal phytoplankton. In view of the global warming related increase in the sea surface temperature and nutrient enrichment of coastal waters, it is necessary to understand variation in the relative share of different sized groups in phytoplankton communities of coastal ecosystems including pico-plankton biomass as it shows the potential for development of microbial food web. Here, an interpretation of temporal patterns detected in the biomass and the relative contribution of pico-sized (< 2 µm) members of phytoplankton was made using data collected from two coastal sites over a year. The findings revealed the significant spatio-temporal variation in both actual pico-plankton biomass and its relative share in phytoplankton. The average biomass values of pico-plankton were 0.23 ± 0.02 µ g chl a L-1 and 0.15 ± 0.01 µg chl a L-1 at nutrient-poor and nutrient-rich sites; respectively. The temporal pattern of change displayed by picoplankton biomass was not seasonal at nutrient rich site while at nutrient poor site it was seasonal with low values measured over winter suggesting it was the seasonal changes leading to the emergence of temporal pattern of change in pico-plankton abundance observed at this site.

Spatio-temporal patterns of soil water storage under dryland agriculture at the watershed scale

USDA-ARS?s Scientific Manuscript database

Soil water patterns vary significantly due to precipitation, soil properties, topographic features, and land use. We used empirical orthogonal function (EOF) analysis to characterize the spatial variability of soil water across a 37-ha field of the Washington State University Cook Agronomy Farm near...

Temporal Stability of Rotors and Atrial Activation Patterns in Persistent Human Atrial Fibrillation: A High-Density Epicardial Mapping Study of Prolonged Recordings.

PubMed

Walters, Tomos E; Lee, Geoffrey; Morris, Gwilym; Spence, Steven; Larobina, Marco; Atkinson, Victoria; Antippa, Phillip; Goldblatt, John; Royse, Alistair; O'Keefe, Michael; Sanders, Prashanthan; Morton, Joseph B; Kistler, Peter M; Kalman, Jonathan M

This study aimed to determine the spatiotemporal stability of rotors and other atrial activation patterns over 10 min in longstanding, persistent AF, along with the relationship of rotors to short cycle-length (CL) activity. The prevalence, stability, and mechanistic importance of rotors in human atrial fibrillation (AF) remain unclear. Epicardial mapping was performed in 10 patients undergoing cardiac surgery, with bipolar electrograms recorded over 10 min using a triangular plaque (area: 6.75 cm 2 ; 117 bipoles; spacing: 2.5 mm) applied to the left atrial posterior wall (n = 9) and the right atrial free wall (n = 4). Activations were identified throughout 6 discrete 10-s segments of AF spanning 10 min, and dynamic activation mapping was performed. The distributions of 4,557 generated activation patterns within each mapped region were compared between the 6 segments. The dominant activation pattern was the simultaneous presence of multiple narrow wave fronts (26%). Twelve percent of activations represented transient rotors, seen in 85% of mapped regions with a median duration of 3 rotations. A total of 87% were centered on an area of short CL activity (<100 ms), although such activity had a positive predictive value for rotors of only 0.12. The distribution of activation patterns and wave-front directionality were highly stable over time, with a single dominant pattern within a 10-s AF segment recurring across all 6 segments in 62% of mapped regions. In patients with longstanding, persistent AF, activation patterns are spatiotemporally stable over 10 min. Transient rotors can be demonstrated in the majority of mapped regions, are spatiotemporally associated with short CL activity, and, when recurrent, demonstrate anatomical determinism. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.