Self-organized sulfide-driven traveling pulses shape seagrass meadows.

Seagrasses provide multiple ecosystem services and act as intense carbon sinks in coastal regions around the globe but are threatened by multiple anthropogenic pressures, leading to enhanced seagrass mortality that reflects in the spatial self-organization of the meadows. Spontaneous spatial vegetation patterns appear in such different ecosystems as drylands, peatlands, salt marshes, or seagrass meadows, and the mechanisms behind this phenomenon are still an open question in many cases. Here, we report on the formation of vegetation traveling pulses creating complex spatiotemporal patterns and rings in Mediterranean seagrass meadows. We show that these structures emerge due to an excitable behavior resulting from the coupled dynamics of vegetation and porewater hydrogen sulfide, toxic to seagrass, in the sediment. The resulting spatiotemporal patterns resemble those formed in other physical, chemical, and biological excitable media, but on a much larger scale. Based on theory, we derive a model that reproduces the observed seascapes and predicts the annihilation of these circular structures as they collide, a distinctive feature of excitable pulses. We show also that the patterns in field images and the empirically resolved radial profiles of vegetation density and sediment sulfide concentration across the structures are consistent with predictions from the theoretical model, which shows these structures to have diagnostic value, acting as a harbinger of the terminal state of the seagrass meadows prior to their collapse.

Propagating spatiotemporal activity patterns across macaque motor cortex carry kinematic information.

Propagating spatiotemporal neural patterns are widely evident across sensory, motor, and association cortical areas. However, it remains unclear whether any characteristics of neural propagation carry information about specific behavioral details. Here, we provide the first evidence for a link between the direction of cortical propagation and specific behavioral features of an upcoming movement on a trial-by-trial basis. We recorded local field potentials (LFPs) from multielectrode arrays implanted in the primary motor cortex of two rhesus macaque monkeys while they performed a 2D reach task. Propagating patterns were extracted from the information-rich high-gamma band (200 to 400 Hz) envelopes in the LFP amplitude. We found that the exact direction of propagating patterns varied systematically according to initial movement direction, enabling kinematic predictions. Furthermore, characteristics of these propagation patterns provided additional predictive capability beyond the LFP amplitude themselves, which suggests the value of including mesoscopic spatiotemporal characteristics in refining brain-machine interfaces.

Hidden signatures of early fire at Evron Quarry (1.0 to 0.8 Mya).

Pyrotechnology is a key element of hominin evolution. The identification of fire in early hominin sites relies primarily on an initial visual assessment of artifacts' physical alterations, resulting in potential underestimation of the prevalence of fire in the archaeological record. Here, we used a suite of spectroscopic techniques to counter the absence of visual signatures for fire and demonstrate the presence of burnt fauna and lithics at the Lower Paleolithic (LP) open-air site of Evron Quarry (Israel), dated between 1.0 and 0.8 Mya and roughly contemporaneous to Gesher Benot Ya'aqov where early pyrotechnology has been documented. We propose reexamining finds from other LP sites lacking visual clues of pyrotechnology to yield a renewed perspective on the origin, evolution, and spatiotemporal dispersal of the relationship between early hominin behavior and fire use.

Spatiotemporal patterns of surface ozone exposure inequality in China.

Rising surface ozone (O3) levels in China are increasingly emphasizing the potential threats to public health, ecological balance, and economic sustainability. Using a 1 km × 1 km dataset of O3 concentrations, this research employs subpopulation demographic data combined with a population-weighted quality model. Its aim is to evaluate quantitatively the differences in O3 exposure among various subpopulations within China, both at a provincial and urban cluster level. Additionally, an exposure disparity indicator was devised to establish unambiguous exposure risks among significant urban agglomerations at varying O3 concentration levels. The findings reveal that as of 2018, the population-weighted average concentration of O3 for all subgroups has experienced a significant uptick, surpassing the average O3 concentration (118 µg/m3). Notably, the middle-aged demographic exhibited the highest O3 exposure level at 135.7 µg/m3, which is significantly elevated compared to other age brackets. Concurrently, there exists a prominent positive correlation between educational attainment and O3 exposure levels, with the medium-income bracket showing the greatest susceptibility to O3 exposure risks. From an industrial vantage point, the secondary sector demographic is the most adversely impacted by O3 exposure. In terms of urban-rural structure, urban groups in all regions had higher levels of exposure to O3 than rural areas, with North and East China having the most significant levels of exposure. These findings not only emphasize the intricate interplay between public health and environmental justice but further highlight the indispensability of segmented subgroup strategies in environmental health risk assessment. Moreover, this research furnishes invaluable scientific groundwork for crafting targeted public health interventions and sustainable air quality management policies.

Characterizing Complex Spatiotemporal Patterns from Entropy Measures.

In addition to their importance in statistical thermodynamics, probabilistic entropy measurements are crucial for understanding and analyzing complex systems, with diverse applications in time series and one-dimensional profiles. However, extending these methods to two- and three-dimensional data still requires further development. In this study, we present a new method for classifying spatiotemporal processes based on entropy measurements. To test and validate the method, we selected five classes of similar processes related to the evolution of random patterns: (i) white noise; (ii) red noise; (iii) weak turbulence from reaction to diffusion; (iv) hydrodynamic fully developed turbulence; and (v) plasma turbulence from MHD. Considering seven possible ways to measure entropy from a matrix, we present the method as a parameter space composed of the two best separating measures of the five selected classes. The results highlight better combined performance of Shannon permutation entropy (SHp) and a new approach based on Tsallis Spectral Permutation Entropy (Sqs). Notably, our observations reveal the segregation of reaction terms in this SHp×Sqs space, a result that identifies specific sectors for each class of dynamic process, and it can be used to train machine learning models for the automatic classification of complex spatiotemporal patterns.

A global satellite observation of phytoplankton taxonomic groups over the past two decades.

Marine phytoplankton fuel the oceanic biotic chain, determine the carbon sequestration levels, and are crucial for the global carbon cycle and climate change. In the present study, we show a near-two-decadal (2002-2022) spatiotemporal distribution of global phytoplankton abundance, proxy as dominant phytoplankton taxonomic groups (PTGs), with a newly developed remote sensing model. Globally, six chief PTGs, namely chlorophytes (~26%), diatoms (~24%), haptophytes (~15%), cryptophytes (~10%), cyanobacteria (~8%), and dinoflagellates (~3%), explain most of the variation (~86%) in phytoplankton assemblages. Spatially, diatoms generally dominate high latitudes, marginal seas, and coastal upwelling zones, whereas chlorophytes and haptophytes control the open oceans. Satellite observations reveal a gentle multi-annual trend of the PTGs in the major oceans, indicative of roughly "unchanged" conditions on the total biomass or compositions of the phytoplankton community. Jointly, "changed" status applies to a short-term (seasonal) timescale: (1) Fluctuations of PTGs exhibit different amplitudes among different subregions, together with a general rule-more intense vibration in the Northern Hemisphere and polar oceans than other zones; (2) diatoms and haptophytes vary more dramatically than other PTGs in a global-scale scope. These findings provide a clear picture of the global phytoplankton community composition and can improve our understanding of their state and further analysis of marine biological processes.

Integrating Augmented In Situ Measurements and a Spatiotemporal Machine Learning Model To Back Extrapolate Historical Particulate Matter Pollution over the United Kingdom: 1980-2019.

Historical PM2.5 data are essential for assessing the health effects of air pollution exposure across the life course or early life. However, a lack of high-quality data sources, such as satellite-based aerosol optical depth before 2000, has resulted in a gap in spatiotemporally resolved PM2.5 data for historical periods. Taking the United Kingdom as an example, we leveraged the light gradient boosting model to capture the spatiotemporal association between PM2.5 concentrations and multi-source geospatial predictors. Augmented PM2.5 from PM10 measurements expanded the spatiotemporal representativeness of the ground measurements. Observations before and after 2009 were used to train and test the models, respectively. Our model showed fair prediction accuracy from 2010 to 2019 [the ranges of coefficients of determination (R2) for the grid-based cross-validation are 0.71-0.85] and commendable back extrapolation performance from 1998 to 2009 (the ranges of R2 for the independent external testing are 0.32-0.65) at the daily level. The pollution episodes in the 1980s and pollution levels in the 1990s were also reproduced by our model. The 4-decade PM2.5 estimates demonstrated that most regions in England witnessed significant downward trends in PM2.5 pollution. The methods developed in this study are generalizable to other data-rich regions for historical air pollution exposure assessment.

Characterization of global fire activity and its spatiotemporal patterns for different land cover types from 2001 to 2020.

Fire is a widespread phenomenon that plays an important role in Earth's ecosystems. This study investigated the global spatiotemporal patterns of burned areas, daytime and nighttime fire counts, and fire radiative power (FRP) from 2001 to 2020. The month with the largest burned area, daytime fire count, and FRP presented a bimodal distribution worldwide, with dual peaks in early spring (April) and summer (July and August), while the month with the largest nighttime fire count and FRP showed a unimodal distribution, with a peak in July. Although the burned area showed decline at the global scale, a significant increase occurred in temperate and boreal forest regions, where nighttime fire occurrence and intensity have consistently increased in recent years. The relationships among burned area, fire count, and FRP were further quantified in 12 typical fire-prone regions. The burned area and fire count exhibited a humped relationship with FRP in most tropical regions, whereas the burned area and fire count constantly increased when the FRP was below approximately 220 MW in temperate and boreal forest regions. Meanwhile, the burned area and FRP generally increased with the fire count in most fire-prone regions, indicating an increased risk of more intense and larger fires as the fire count increased. The spatiotemporal dynamics of burned areas for different land cover types were also explored in this study. The results suggest that the burned areas in forest, grassland, and cropland showed dual peaks in April and from July to September while the burned areas in shrubland, bareland, and wetlands usually peaked in July or August. Significant increases in forest burned area were observed in temperate and boreal forest regions, especially in the western U.S. and Siberia, whereas significant increases in cropland burned area were found in India and northeastern China.

Distribution and trends of mercury in aquatic and terrestrial biota of New York, USA: a synthesis of 50 years of research and monitoring.

Mercury (Hg) inputs have particularly impacted the northeastern United States due to its proximity to anthropogenic emissions sources and abundant habitats that efficiently convert inorganic Hg into methylmercury. Intensive research and monitoring efforts over the past 50 years in New York State, USA, have informed the assessment of the extent and impacts of Hg exposure on fishes and wildlife. By synthesizing Hg data statewide, this study quantified temporal trends of Hg exposure, spatiotemporal patterns of risk, the role that habitat and Hg deposition play in producing spatial patterns of Hg exposure in fish and other wildlife, and the effectiveness of current monitoring approaches in describing Hg trends. Most temporal trends were stable, but we found significant declines in Hg exposure over time in some long-sampled fish. The Adirondack Mountains and Long Island showed the greatest number of aquatic and terrestrial species with elevated Hg concentrations, reflecting an unequal distribution of exposure risk to fauna across the state. Persistent hotspots were detected for aquatic species in central New York and the Adirondack Mountains. Elevated Hg concentrations were associated with open water, forests, and rural, developed habitats for aquatic species, and open water and forested habitats for terrestrial species. Areas of consistently elevated Hg were found in areas driven by atmospheric and local Hg inputs, and habitat played a significant role in translating those inputs into biotic exposure. Continued long-term monitoring will be important in evaluating how these patterns continue to change in the face of changing land cover, climate, and Hg emissions.

Climate drivers of seed rain phenology of subtropical forest communities along an elevational gradient.

Seed rain phenology (the start and end date of seed rain) is an essential component of plant phenology, critical for understanding population regeneration and community dynamics. However, intra- and inter-annual changes of seed rain phenology along environmental gradients have rarely been studied and the responses of seed rain phenology to climate variations are unclear. We monitored seed rain phenology of four forest communities in four years at different elevations (900 m, 1450 m, 1650 m, 1900 m a.s.l.) of a subtropical mountain in Central China. We analyzed the spatiotemporal patterns of seed rain phenology of 29 common woody plant species (total observed species in the seed rain), and related the phenological variations to seed number and climatic variables using mixed-effect models with the correlation matrix of phylogeny. We found that changes in the period length were mainly driven by the end rather than the start date. The end date and the period length of seed rain were significantly different between the mast and non-mast seeding years, while no significant elevation-related trend was detected in seed rain phenology variation. Seed number, mean temperature in spring (Tspr), and winter (Twin), summer precipitation (Psum) had significant effects on seed rain phenology. When Tspr increased, the start date of seed rain advanced, while the end date was delayed and the seed rain period length was mainly prolonged by a higher seed number, Twin and Psum. Forest canopy might have a buffering effect on understory climatic conditions, especially in precipitation that lead to difference in seed rain phenology between canopy and shrub species. Our novel evidence of seed rain phenology can improve prediction of community regeneration dynamics in responding to climate changes.

On the triad of air PM pollution, pathogenic bioaerosols, and lower respiratory infection.

Airborne particulate matter (PM) pollution, as a leading environmental health risk, causes millions of premature deaths globally every year. Lower respiratory infection (LRI) is a sensitive response to short-term exposure to outdoor PM pollution. The airborne transmission of etiological agents of LRI, as an important pathway for infection and morbidity, bridges the public health issues of air quality and pathogen infectivity, virulence, resistance, and others. Enormous efforts are underway to identify common pathogens and substances that are etiological agents for LRI and to understand the underlying toxicological and clinical basis of health effects by identifying mechanistic pathways. Seasonal variations and geographical disparities in the survival and infectivity of LRI pathogens are unsolved mysteries. Weather conditions in geographical areas may have a key effect, but also potentially connect LRI with short-term increases in ambient air PM pollution. Statistical associations show that short-term elevations in fine and coarse PM lead to increases in respiratory infections, but the causative agents could be chemical or microbiological and be present individually or in mixtures, and the interactions between chemical and microbiological agents remain undefined. Further investigations on high-resolution monitoring of airborne pathogens in relation to PM pollution for an integrated exposure-response assessment and mechanistic study are warranted. Improving our understanding of the spatiotemporal features of pathogenic bioaerosols and air pollutants and translating scientific evidence into effective policies is vital to reducing the health risks and devastating death toll from PM pollution.

Spatiotemporal Patterns of Anthrax, Vietnam, 1990-2015.

Anthrax is a priority zoonosis for control in Vietnam. The geographic distribution of anthrax remains to be defined, challenging our ability to target areas for control. We analyzed human anthrax cases in Vietnam to obtain anthrax incidence at the national and provincial level. Nationally, the trendline for cases remained at ≈61 cases/year throughout the 26 years of available data, indicating control efforts are not effectively reducing disease burden over time. Most anthrax cases occurred in the Northern Midlands and Mountainous regions, and the provinces of Lai Chau, Dien Bien, Lao Cai, Ha Giang, Cao Bang, and Son La experienced some of the highest incidence rates. Based on spatial Bayes smoothed maps, every region of Vietnam experienced human anthrax cases during the study period. Clarifying the distribution of anthrax in Vietnam will enable us to better identify risk areas for improved surveillance, rapid clinical care, and livestock vaccination campaigns.

Self-Organized Spatiotemporal Mineralization of Hydrogel: A Simulant of Osteon.

Nature creates fascinating self-organized spatiotemporal patterns through the delicate control of reaction-diffusion dynamics. As the primary unit of cortical bone, osteon has concentric lamellar architecture, which plays a crucial role in the mechanical and physiological functions of bone. However, it remains a great challenge to fabricate the osteon-like structure in a natural self-organization way. Taking advantage of the nonequilibrium reaction in hydrogels, a simple mineralization strategy to closely mimic the formation of osteon in a mild physiological condition is developed. By constructing two reverse concentration gradients of ions from periphery to interior of cylindrical hydrogel, spatiotemporal self-organization of calcium phosphate in concentric rings is generated. It is noteworthy that minerals in different layers possess diverse contents and crystalline phases, which further guide the adhesion and spread of osteoblasts on these patterns, resembling the architecture and cytological behavior of osteon. Besides, theoretical data indicates the predominate role of ion concentrations and pH values of solution, in good accordance with experimental results. Independent of precise instruments, this lifelike method is easily obtained, cost-efficient, and effectively imitates the mineral deposition in osteon from a physiochemical view. The strategy may be expanded to develop other functional material patterns via spatiotemporal self-organization.

Spatiotemporal Patterns of Spreading Depolarization and its Correlation with Brain Injury During the Acute Stage of Subarachnoid Hemorrhage in Mice.

OBJECTIVE: Spreading depolarization (SD) has been regarded as one cause of neuronal injury in subarachnoid hemorrhage (SAH). However, SD in the hyperacute phase of SAH is still unclear. The objective of this study was to detect real-time spatial-temporal patterns of SD, assess the effect of SD on cerebral blood flow, and test the relationship between SD and brain injury in the acute phase of SAH. METHODS: Twenty-eight mice were separated into two groups: 16 animals in the SAH group and 12 animals in the sham group. Experimental SAH was done with an endovascular filament perforation model. Changes in optical reflection were registered with intrinsic optical signal imaging (IOSI) after SAH. Spatial-temporal patterns of SDs were analyzed and brain injury including brain edema and infarction was tested. RESULTS: Totally, 117 SDs occurred after SAH. According to the hemodynamic response and duration, SDs could be classified into Type I (short SD), Type II (intermediate SD), and Type III (persistent SD). Most of SDs originated from the somatosensory and visual cortex. SDs demonstrated distinct spreading patterns. Moreover, the number and duration of SDs associated with brain water content (p < 0.05, p < 0.01). SDs, especially, persistent SDs associated with infarct volume in the hyperacute phase of SAH (p < 0.001, p < 0.001). CONCLUSION: Our results suggest that SD occurs with a high incidence during the acute stage of SAH in mice. And the lissencephalic mouse brain is capable of different SD propagation patterns. Additionally, SD may aggravate brain edema and induce brain infarction, contributing to early brain injury after SAH.

Interannual variability of vegetation sensitivity to climate in China.

Many studies have assessed the relative sensitivity of ecosystems to climate change, and even optimized climate states from long-term averages to infer short-term changes, but how ecosystem sensitivity and its relationships with climate variability vary over time remains elusive. By combining the vegetation sensitivity index (VSI) and a 15 year moving window, we analyzed interannual variability in spatiotemporal patterns of vegetation sensitivity to short-term climate variability and its correlations with climatic factors in China over the past three decades (1982-2015). We demonstrated that vegetation sensitivity shows high spatial heterogeneity, and varies with vegetation type and climate region. Generally, vegetation in the southwest and mountainous regions was more sensitive, especially coniferous forests and isolated shrubland patches. Comparatively, vegetation in dry regions was less sensitive to climate variability than in wetter climates. Due to frequent climate variability in the early 1990s, a large increase in the VSI was detected in 1996. Significant increases in the interannual variability of vegetation sensitivity were observed in greater than 23.7% of vegetated areas and decreases in only 4.2%. Solar radiation was the dominant climate driver of vegetation sensitivity, followed by temperature and precipitation. However, climate controls are not invariable across a range of climatic conditions, such as precipitation exerted an increasing influence on changes of vegetation sensitivity. Quantitative analyses of ecosystem sensitivity to climate variability such as ours are vital to identify which regions and vegetation are most vulnerable to future climate variability.

Daily Travel Distances of Unhabituated Grauer's Gorillas (Gorilla beringei graueri) in a Low Elevation Forest.

To accurately determine the space use of animals, we need to follow animal movements over prolonged periods, which is especially challenging for the critically endangered Grauer's gorillas (Gorilla beringei graueri) in eastern Democratic Republic of the Congo (DRC). As a consequence, we know little about Grauer's gorillas, particularly from the lower elevational parts of their range. Between 2016 and 2018, we tracked unhabituated Grauer's gorillas in lowland forests (500-1,000 m a.s.l.), at the community-managed Nkuba Conservation Area in Nord Kivu (DRC) to provide estimates of daily travel distances (DTD), daily displacement distances (DDD), and the linearity of recorded paths expressed as the Linearity Index (LI): DDD/DTD. We found an average DTD of ∼1.3 km (range 0.05-5.0 km), with temporal variation among monthly averages; specifically, an increase in travel distance over the June-August dry season resulting in peak travel distances at the beginning of the September-December wet season. Daily displacements showed similar temporal variation, which resulted in a lack of obvious temporal patterns in LI. We conclude that the movement patterns of Grauer's gorillas in lowland forests, which are characterized by larger DTD than those of Grauer's gorillas that inhabit highland habitats, show similarity to travel distances of other predominantly frugivorous gorillas. Moreover, the observed temporal patterns in space use may be tentatively linked to temporal changes in fruit availability or consumption. These observations have consequences for our understanding of the ecological role that Grauer's gorillas play and provide baseline data to estimate current and future distributions, abundances, and carrying capacities of this highly threatened animal.

Neural Signatures of Auditory Perceptual Bistability Revealed by Large-Scale Human Intracranial Recordings.

A key challenge in neuroscience is understanding how sensory stimuli give rise to perception, especially when the process is supported by neural activity from an extended network of brain areas. Perception is inherently subjective, so interrogating its neural signatures requires, ideally, a combination of three factors: (1) behavioral tasks that separate stimulus-driven activity from perception per se; (2) human subjects who self-report their percepts while performing those tasks; and (3) concurrent neural recordings acquired at high spatial and temporal resolution. In this study, we analyzed human electrocorticographic recordings obtained during an auditory task which supported mutually exclusive perceptual interpretations. Eight neurosurgical patients (5 male; 3 female) listened to sequences of repeated triplets where tones were separated in frequency by several semitones. Subjects reported spontaneous alternations between two auditory perceptual states, 1-stream and 2-stream, by pressing a button. We compared averaged auditory evoked potentials (AEPs) associated with 1-stream and 2-stream percepts and identified significant differences between them in primary and nonprimary auditory cortex, surrounding auditory-related temporoparietal cortex, and frontal areas. We developed classifiers to identify spatial maps of percept-related differences in the AEP, corroborating findings from statistical analysis. We used one-dimensional embedding spaces to perform the group-level analysis. Our data illustrate exemplar high temporal resolution AEP waveforms in auditory core region; explain inconsistencies in perceptual effects within auditory cortex, reported across noninvasive studies of streaming of triplets; show percept-related changes in frontoparietal areas previously highlighted by studies that focused on perceptual transitions; and demonstrate that auditory cortex encodes maintenance of percepts and switches between them.SIGNIFICANCE STATEMENT The human brain has the remarkable ability to discern complex and ambiguous stimuli from the external world by parsing mixed inputs into interpretable segments. However, one's perception can deviate from objective reality. But how do perceptual discrepancies occur? What are their anatomical substrates? To address these questions, we performed intracranial recordings in neurosurgical patients as they reported their perception of sounds associated with two mutually exclusive interpretations. We identified signatures of subjective percepts as distinct from sound-driven brain activity in core and non-core auditory cortex and frontoparietal cortex. These findings were compared with previous studies of auditory bistable perception and suggested that perceptual transitions and maintenance of perceptual states were supported by common neural substrates.

Spatiotemporal changes of carbon storage in forest carbon pools of Western Turkey: 1972-2016.

This study analyzes the impacts of spatiotemporal changes on C dynamics based on the various C pools and forest structure in western Turkey. The forest C dynamics were projected by forest inventory data between 1972 and 2016, and the spatial distribution of C storage was mapped by GIS. Total C storage increased from 1135.22 Gg in 1972 to 1816.60 Gg in 2016 with a net accumulation of 681.38 Gg. While the largest contribution to C pool was from soil organic carbon with 58.6% and 49.3% of the total C storage in 1972 and 1994, it was from living biomass with 54.0% and 57.7% in 2004 and 2016, respectively. The mean annual C sequestration was 1.57 Mg ha-1 year-1, including 1.49 Mg ha-1 year-1 in biomass and 0.08 Mg ha-1 year-1 in soil over four decades. The mixed cover type was the most significant contributor to biomass, soil, and total C storages. However, the hardwood cover type was the most significant contributor to C densities due to the higher growing stock. The mature development stages (35.6 Gg year-1), the fully covered areas (13.2 Gg year-1), and the older forests have played an essential role in C sequestration. The spatial distribution of C dynamics was heterogenic due to forest cover type, forest structure, and species composition. Monitoring spatiotemporal changes in forest ecosystems in terms of forest cover type, development stage, coverages, and age class distribution can provide opportunities in developing effective forest management policies based on the ecological sustainability of C pools and mitigating climate change effects.

Spatiotemporal patterns and risk factors concerning hepatitis B virus infections in the Beijing-Tianjin-Hebei area of China.

Beijing-Tianjin-Hebei is the largest urban agglomeration in northern China, but the spatiotemporal patterns and risk factors concerning hepatitis B virus (HBV) incidence in this area have been unclear. The present study aimed to reveal the spatiotemporal epidemiological features of HBV infection and quantify the association between HBV infection and socio-economic risk factors. The data on HBV cases in Beijing-Tianjin-Hebei from 2007 to 2012 was collected for each county. The Bayesian space-time hierarchy model and the GeoDetector method were used to reveal spatiotemporal patterns and detect risk factors. High-risk regions were mainly distributed in the underdeveloped rural areas in the north and mid-south of the study region, while low-risk regions were mainly distributed in the urban and western areas. The HBV annual incidence rate decreased substantially over the 6-year period, dropping from 7.34/105 to 5.51/105. Compared with this overall trend, 38.5% of high-risk counties showed a faster decrease, and 35.9% of high-risk counties exhibited a slower decrease. Meanwhile, 29.7% of low-risk counties had a faster decrease, and 44.6% of low-risk counties exhibited a slower decrease. Socio-economic factors were strongly associated with the spatiotemporal patterns and variation. The population density and gross domestic product per capita were negatively associated with HBV transmission, with determinant powers of 0.17 and 0.12, respectively. The proportion of primary industry and the number of healthcare workers were positively associated with the disease incidence, with determinant powers of 0.11 and 0.8, respectively. The interactive effect between population density and the other factors exerted a greater influence on HBV transmission than that of these factors measured independently.

Spatiotemporal dynamics of a reaction-diffusion model of pollen tube tip growth.

A reaction-diffusion model is proposed to describe the mechanisms underlying the spatial distributions of ROP1 and calcium on the pollen tube tip. The model assumes that the plasma membrane ROP1 activates itself through positive feedback loop, while the cytosolic calcium ions inhibit ROP1 via a negative feedback loop. Furthermore it is proposed that lateral movement of molecules on the plasma membrane are depicted by diffusion. It is shown that bistable or oscillatory dynamics could exist even in the non-spatial model, and stationary and oscillatory spatiotemporal patterns are found in the full spatial model which resemble the experimental data of pollen tube tip growth.