Lattice-based Monte Carlo simulation of the effects of nutrient concentration and magnetic field exposure on yeast colony growth and morphology.

Yeasts exist in communities that expand over space and time to form complex structures and patterns. We developed a lattice-based framework to perform spatial-temporal Monte Carlo simulations of budding yeast colonies exposed to different nutrient and magnetic field conditions. The budding patterns of haploid and diploid yeast cells were incorporated into the framework, as well as the filamentous growth that occurs in yeast colonies under nutrient limiting conditions. Simulation of the framework predicted that magnetic fields decrease colony growth rate, solidity, and roundness. Magnetic field simulations further predicted that colony elongation and boundary fluctuations increase in a nutrient- and ploidy-dependent manner. These in-silico predictions are an important step towards understanding the effects of the physico-chemical environment on microbial colonies and for informing bioelectromagnetic experiments on yeast colony biofilms and fungal pathogens.

Spatial-temporal clustering of malaria using routinely collected health facility data on the Kenyan Coast.

BACKGROUND: The over-distributed pattern of malaria transmission has led to attempts to define malaria "hotspots" that could be targeted for purposes of malaria control in Africa. However, few studies have investigated the use of routine health facility data in the more stable, endemic areas of Africa as a low-cost strategy to identify hotspots. Here the objective was to explore the spatial and temporal dynamics of fever positive rapid diagnostic test (RDT) malaria cases routinely collected along the Kenyan Coast. METHODS: Data on fever positive RDT cases between March 2018 and February 2019 were obtained from patients presenting to six out-patients health-facilities in a rural area of Kilifi County on the Kenyan Coast. To quantify spatial clustering, homestead level geocoded addresses were used as well as aggregated homesteads level data at enumeration zone. Data were sub-divided into quarterly intervals. Kulldorff's spatial scan statistics using Bernoulli probability model was used to detect hotspots of fever positive RDTs across all ages, where cases were febrile individuals with a positive test and controls were individuals with a negative test. RESULTS: Across 12 months of surveillance, there were nine significant clusters that were identified using the spatial scan statistics among RDT positive fevers. These clusters included 52% of all fever positive RDT cases detected in 29% of the geocoded homesteads in the study area. When the resolution of the data was aggregated at enumeration zone (village) level the hotspots identified were located in the same areas. Only two of the nine hotspots were temporally stable accounting for 2.7% of the homesteads and included 10.8% of all fever positive RDT cases detected. CONCLUSION: Taking together the temporal instability of spatial hotspots and the relatively modest fraction of the malaria cases that they account for; it would seem inadvisable to re-design the sub-county control strategies around targeting hotspots.

Modeling the relative role of human mobility, land-use and climate factors on dengue outbreak emergence in Sri Lanka.

BACKGROUND: More than 80,000 dengue cases including 215 deaths were reported nationally in less than 7 months between 2016 and 2017, a fourfold increase in the number of reported cases compared to the average number over 2010-2016. The region of Negombo, located in the Western province, experienced the greatest number of dengue cases in the country and is the focus area of our study, where we aim to capture the spatial-temporal dynamics of dengue transmission. METHODS: We present a statistical modeling framework to evaluate the spatial-temporal dynamics of the 2016-2017 dengue outbreak in the Negombo region of Sri Lanka as a function of human mobility, land-use, and climate patterns. The analysis was conducted at a 1 km × 1 km spatial resolution and a weekly temporal resolution. RESULTS: Our results indicate human mobility to be a stronger indicator for local outbreak clusters than land-use or climate variables. The minimum daily temperature was identified as the most influential climate variable on dengue cases in the region; while among the set of land-use patterns considered, urban areas were found to be most prone to dengue outbreak, followed by areas with stagnant water and then coastal areas. The results are shown to be robust across spatial resolutions. CONCLUSIONS: Our study highlights the potential value of using travel data to target vector control within a region. In addition to illustrating the relative relationship between various potential risk factors for dengue outbreaks, the results of our study can be used to inform where and when new cases of dengue are likely to occur within a region, and thus help more effectively and innovatively, plan for disease surveillance and vector control.

Scenario modeling for spatial-temporal change detection of carbon storage and sequestration in a forested landscape in Northern Iran.

The present study was conducted, based on scenario modeling approach, in the Do-hezar and Se-hezar forested landscape in the Mazandaran Province in Northern Iran in order to detect spatial-temporal changes of carbon storage and sequestration in four different carbon pools, i.e., aboveground and belowground biomasses, dead organic matter, and organic soils. For this purpose, firstly, the changing trend of land use/land cover (LULC) was detected by analyzing and comparing remotely sensed data of the landscape during the period of 1984-2016. Then, the impacts of future LULC changes on carbon storage and sequestration were predicted and valued using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model under two future plausible scenarios of business as usual (BAU) and balanced development (BD). According to the results of BAU scenario, continuation of the current trend will lead to a significant reduction in the carbon sequestration and a huge amount of social cost due to the loss of carbon stored in the landscape and its release to the atmosphere. The BD scenario which refers to the principled and under control development of human settlements simultaneously with forest conservational and restoration activities, could potentially reverse the downtrend of carbon sequestration service and avoid future socioeconomic costs, hence add to the economic value of the forest landscape in terms of providing a better sink for carbon storage. The results of this research can facilitate the quantitative and accurate assessment of carbon storage and sequestration relying on more precise biophysical and economic data as well as provide insight for effective land-use planning.

Spatial-Temporal Dynamics of Cropping Frequency in Hubei Province over 2001-2015.

Mapping crop patterns with remote sensing data is of great importance for agricultural production, food security and agricultural sustainability. In this paper, a hierarchical clustering method was proposed to map cropping frequency from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Indices (EVI) data and the spatial and temporal patterns of cropping frequency from 2001 to 2015 in Hubei Province of China were analyzed. The results are as follows: (1) The total double crop areas decreased slightly, while total single crop areas decreased significantly during 2001 and 2015; (2) The transfer between double crop and single crop was frequent in Hubei with about 11~15% croplands changed their cropping frequency every 5 years; (3) The crop system has obvious regional differentiation for their change trend at the county level.

Dynamic models in research and management of biological invasions.

Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales.

Rich diversity and active spatial-temporal dynamics of Thalassiosira species revealed by time-series metabarcoding analysis.

Thalassiosira is a species-rich genus in Bacillariophyta that not only contributes positively as primary producer, but also poses negative impacts on ecosystems by causing harmful algal blooms. Although taxonomical studies have identified a large number of Thalassiosira species, however, the composition of Thalassiosira species and their geographical distribution in marine ecosystems were not well understood due primarily to the lack of resolution of morphology-based approaches used previously in ecological expeditions. In this study, we systematically analyzed the composition and spatial-temporal dynamic distributions of Thalassiosira in the model marine ecosystem Jiaozhou Bay by applying metabarcoding analysis. Through analyzing samples collected monthly from 12 sampling sites, 14 Thalassiosira species were identified, including five species that were not previously reported in Jiaozhou Bay, demonstrating the resolution and effectiveness of metabarcoding analysis in ecological research. Many Thalassiosira species showed prominent temporal preferences in Jiaozhou Bay, with some displaying spring-winter preference represented by Thalassiosira tenera, while others displaying summer-autumn preference represented by Thalassiosira lundiana and Thalassiosira minuscula, indicating that the temperature is an important driving factor in the temporal dynamics. The application of metabarcoding analysis, equipped with appropriate molecular markers with high resolution and high specificity and databases of reference molecular marker sequences for potential all Thalassiosira species, will revolutionize ecological research of Thalassiosira species in Jiaozhou Bay and other marine ecosystems.

Spatial simulations in systems biology: from molecules to cells.

Cells are highly organized objects containing millions of molecules. Each biomolecule has a specific shape in order to interact with others in the complex machinery. Spatial dynamics emerge in this system on length and time scales which can not yet be modeled with full atomic detail. This review gives an overview of methods which can be used to simulate the complete cell at least with molecular detail, especially Brownian dynamics simulations. Such simulations require correct implementation of the diffusion-controlled reaction scheme occurring on this level. Implementations and applications of spatial simulations are presented, and finally it is discussed how the atomic level can be included for instance in multi-scale simulation methods.

Modeling Effects of Vertebrate Host Exclosures and Host-Targeted Acaricides on Lone Star Tick (Amblyomma americanum, L.) Infestations.

We used a spatially explicit model to simulate the potential effects of exclosures and acaricides targeted at medium-sized mammalian hosts on the local distribution and abundance of lone star ticks (Amblyomma americanum) within forestlands of the southeastern United States. Both exclosures and acaricides were successful in markedly reducing the densities of all off-host tick life stages inside the treatment areas. Densities dropped to almost zero immediately inside the edges of the exclosures, with noticeably depressed densities extending outward 30 to 60 m from the exclosures, and the simulated exclosures maintained their effectiveness as their sizes were decreased from 4.5 to 2.25 to 0.8 ha. Densities exhibited a smooth gradient across the edges of the acaricide-treated areas, with depressed densities extending ≈100 m outward from the edges, but with perceptible densities extending ≈60 m inward from the edges; thus, the simulated acaricide areas lost their effectiveness as size was decreased to slightly less than one-half the diameter of the activity range of the targeted host. Our simulation results indicated that off-host nymph densities responded to reductions of medium-sized host densities. These results suggest that targeting acaricides at medium-sized hosts may be an effective, and currently under-utilized, method for tick suppression.

Dynamic spreading of chromatin-mediated gene silencing and reactivation between neighboring genes in single cells.

In mammalian cells genes that are in close proximity can be transcriptionally coupled: silencing or activating one gene can affect its neighbors. Understanding these dynamics is important for natural processes, such as heterochromatin spreading during development and aging, and when designing synthetic gene regulation circuits. Here, we systematically dissect this process in single cells by recruiting and releasing repressive chromatin regulators at dual-gene synthetic reporters, and measuring how fast gene silencing and reactivation spread as a function of intergenic distance and configuration of insulator elements. We find that silencing by KRAB, associated with histone methylation, spreads between two genes within hours, with a time delay that increases with distance. This fast KRAB-mediated spreading is not blocked by the classical cHS4 insulators. Silencing by histone deacetylase HDAC4 of the upstream gene can also facilitate background silencing of the downstream gene by PRC2, but with a days-long delay that does not change with distance. This slower silencing can sometimes be stopped by insulators. Gene reactivation of neighboring genes is also coupled, with strong promoters and insulators determining the order of reactivation. Our data can be described by a model of multi-gene regulation that builds upon previous knowledge of heterochromatin spreading, where both gene silencing and gene reactivation can act at a distance, allowing for coordinated dynamics via chromatin regulator recruitment.

Evaluation of Potential for Nature-Based Recreation in the Qinghai-Tibet Plateau: A Spatial-Temporal Perspective.

Nature-based recreation (NBR) is an important cultural ecosystem service providing human well-being from natural environments. As the most concentrated and high-quality wilderness in China, the Qinghai-Tibet Plateau (QTP) has unique advantages for NBR. In this study, we designed an integrated nature-based recreation potential index (INRPI) based on four aspects: nature-based recreation resources, landscape attractiveness, recreation comfort and opportunity, and recreation reception ability. A combination of the analytic hierarchy process (AHP) and entropy evaluation method was adopted to assess the NBR potential in the QTP from 2000 to 2020. The research shows that: (i) The INRPI for the QTP decreases gradually from southeast to northwest and increases slightly from 2000 to 2020. (ii) The INRPI displays a pronounced difference on either side of the Qilian-Gyirong line. The areas with very high and high potentials mainly distributed in the southeast of the line, while areas with very low and low potentials distributed in the northwest. (iii) The construction of protected areas effectively improves NBR potential. Areas of INRPI at diverse levels within protected areas obviously increased in 2020. (iv) Increasing altitude has a notable effect on INRPI, and 3000 m is a critical dividing line for the NBR in the QTP. These findings can contribute to decision-makers in guiding rational use and spatial planning of natural land and promoting sustainable recreational development.

Composition and spatial-temporal dynamics of phytoplankton community shaped by environmental selection and interactions in the Jiaozhou Bay.

The Jiaozhou Bay as a model marine ecosystem in China has been intensively investigated over the last 90 years. However, detailed phytoplankton community composition, spatial-temporal dynamics, and its assembly mechanism were still unclear. To address these, we systematically examined the composition and spatial-temporal dynamics of phytoplankton in the Jiaozhou Bay through high-throughput sequencing of 18S rDNA V4. Analysis of 468 samples from 12 sampling sites over one full year revealed much higher phytoplankton diversity than previous reports, and strong seasonal succession patterns. Some phytoplankton also showed spatial variations, although the phytoplankton community didn't show significant distance-decay pattern. Environmental factors (especially temperature), species-species interrelationships and unique resting stages were uncovered to be the main contributors instead of stochastic process in shaping the phytoplankton community assembly. The overwhelming positive correlations between phytoplankton and other protists suggested that coevolution might be critical in this marine ecosystem. Complementary distributions of different amplicon sequence variants (ASVs) of same genera, such as Skeletonema marinoi (ASV_2) and Skeletonema tropicum (ASV_263) of the genus Skeletonema, suggested that phytoplankton have evolved differentially to exploit a wide range of ecological niches. This study laid a solid foundation for asertaining phytoplankton composition and spatial-temporal dynamics in temperate seawaters and mechanisms underlying phytoplankton community assembly, allowing in-depth studies of marine ecology.

Influences of impervious surfaces on ecological risks and controlling strategies in rapidly urbanizing regions.

Reducing ecological risks is important for promoting regional sustainable development. However, studies on the influence of impervious surfaces on ecological risks and risk control strategies in regions undergoing rapid urbanization are limited. Therefore, this study aimed to demonstrate the spatial-temporal dynamics of regional ecological risks using Beijing as a case study to reveal the influence of impervious surfaces and explore the controlling strategies of risks. We first characterized the ecological risks in Beijing based on the ecosystem service values and mapped the risk levels and temporal variations in risks. We then identified the ecological risk increases caused by impervious surface expansion and built linear regression models for impervious surface coverage (ISC) and risk index. Finally, we formulated ecological risk control strategies for the strategy categories identified based on the ISC thresholds. The results show that the mountainous areas mainly exhibited low ecological risk levels, and the plain areas mainly showed high levels. The expansion of impervious surface was the main cause of the relatively large temporal increase in ecological risks from 2005 to 2015. Moreover, the strategies for ecological risk control can be divided into four categories based on the division of ISC, with 30%, 70%, and 90% as the thresholds. For risk control strategies, reducing ISC is the most important measure to reduce ecological risks for the category with an ISC range of 90%-100%, and increasing the area proportions of forests and water bodies is the most effective measure for the category with an ISC range of 0%-30%. For the other two categories, controlling the ISC and other strategies are required. Our study can increase the understanding of the influences of impervious surfaces on ecological risks in rapidly urbanizing regions and help inform the formulation of strategies for controlling the ecological risks in Beijing.

Biodiversity and Spatial-Temporal Dynamics of Margalefidinium Species in Jiaozhou Bay, China.

Many Margalefidinium species are cosmopolitan harmful algal bloom (HAB) species that have caused huge economic and ecological damage. Despite extensive research on Margalefidinium species, the biodiversity and spatial-temporal dynamics of these species remain obscure. Jiaozhou Bay is an ideal area for HAB research, being one of the earliest marine survey areas in China. In this study, we carried out the first metabarcoding study on the temporal and spatial dynamics of Margalefidinium species using the 18S rDNA V4 region as the molecular marker and samples collected monthly at 12 sampling sites in Jiaozhou Bay in 2019. Two harmful Margalefidinium species (M. polykrikoides and M. fulvescens) were identified with potentially high genetic diversity (although we cannot rule out the possibility of intra-genome sequence variations). Both M. polykrikoides and M. fulvescens demonstrated strong temporal preference with a sharp peak of abundance in early autumn (September), but without showing strong location preference in Jiaozhou Bay. Our results revealed that temperature might be the main driver for their temporal dynamics. Knowledge of biodiversity and spatial-temporal dynamics of the Margalefidinium species may shed light on the understanding of mechanisms underlying strongly biased occurrences of Margalefidinium blooms recorded globally.

Context-dependent dynamic functional connectivity alteration of lateral occipital cortex in schizophrenia.

Schizophrenia has long been associated with dysfunction in visual perception. One important region underlying this is lateral occipital cortex (LOC), a mid-level visual region critical for object recognition. Although LOC of patients has exhibited structural and functional abnormalities in MR brain imaging studies, how it interacts with other networks over time under rest and with task demands remains to be clarified. The present study investigated the spatial-temporal interaction of LOC with other brain networks by examining functional connectivity communities of the brain over time. We found increased temporal instability of LOC connectivity over time under both resting and task-switching conditions in patients. In the resting state, LOC of patients had increased interaction with the frontoparietal task-control network (FPTC) and thalamus compared with controls, while during task switching, LOC showed increased interaction with the default mode network (DMN). Temporal instability of LOC connectivity was positively correlated with patients' switching cost during task performance and with hallucination severity. These results indicate that reduced stability of LOC connectivity may be an important factor underlying neurocognitive dysfunctions and symptom severity in schizophrenia.

Vegetation responses to extreme climatic indices in coastal China from 1986 to 2015.

Climate extremes have resulted in substantial vegetation changes in the marine-terrestrial transitional zone. As a climatically-sensitive region, coastal China is currently experiencing prominent environmental climate change. To identify how climatic extremes affect ecosystem function, we calculated eleven indices of climatic extremes and four mean indices for six sub-regions of coastal China. Deseasonalized thirty-year (1986-2015) net primary productivity (NPP) was used as an indicator of ecosystem productivity, and its relationships with the climate indices were investigated at multiple scales (annual and seasonal) explicitly. The results demonstrated that: (1) annual NPP indicated an overall greening trend (in 73.71% of the study area) and partial degradation (in 26.29% of the study area) over the last thirty decades years; (2) coastal areas had experienced warming overall, with higher increases in nighttime temperatures relative to daytime temperatures; (3) in southern areas, maximum/ minimum daily maximum temperature had driven increases in NPP, whereas in northern areas, this effect varied between vegetation types; (4) Diurnal temperature range (DTR) and NPP were negatively correlated in the north and positively correlated in the south; and (5) Maximum 1-day precipitation promoted vegetation production across the whole study area. Maximum 5-day precipitation promoted vegetation growth in the north but had the opposite effect in the south. Our study advances understanding of vegetation dynamics and its driving mechanisms, and provides support for scientifically informed ecological management practices in coastal China.

Dynamic monitoring of aeolian desertification based on multiple indicators in Horqin Sandy Land, China.

Aeolian desertification has become one of the most serious environmental and socioeconomic problems facing the world today. Quantitative remote sensing technology is an important means to achieve the development trends of aeolian desertified land (ADL). To compensate for the shortcomings in the time scale of Landsat Thematic Mapper and other high-spatial-resolution remote sensing data, this study introduces Moderate Resolution Imaging Spectroradiometer time series data and products to invert the monitoring indicators of ADL. The QUEST (quick, unbiased, and efficient statistical tree) classification method was used to establish the extraction model of ADL based on multiple indicators. The ADL time series dataset was extracted from 2000 to 2015, and the characteristics of ADL and its spatial-temporal dynamics were analyzed. These results were combined with meteorological data and socioeconomic statistics to discuss the main factors influencing ADL. The results showed that, by the end of 2015, the total area of ADL was 32,633 km2, accounting for 26.02% of the study area. The slight, moderate, severe, and extremely severe ADL accounted for 51.39%, 34.11%, 10.31%, and 4.20%, respectively. The total area of ADL decreased significantly at a rate of 2388.60 km2 y-1 from 2000 to 2015. The decreasing area was dominated by the slight and moderate ADL. The reversal of ADL exhibited significant correlations with an increase of annual precipitation and a decrease of annual maximum wind velocity (p < 0.01). The impact of annual maximum wind velocity on ADL is more important than annual precipitation. Increases in population density and the number of livestock did not promote the development of ADL. A series of ecological protection projects and policies created advantageous conditions for the reversal of ADL. This research provides a new method for monitoring ADL and useful information for controlling and managing aeolian desertification in this region.

Modeling the spatial and temporal dynamics of riparian vegetation induced by river flow fluctuation.

River flow fluctuation has an important influence on riparian vegetation dynamics. A temporally segmented stochastic model focusing on a same-aged population is developed for the purpose of describing both spatial and temporal dynamics of riparian vegetation. In the model, the growth rate of population, rather than carrying capacity, is modeled as the random variable. This model has explicit physical meaning. The model deduces a process-based solution. From the solution process, the probability density of spatial distribution can be derived; therefore, the spatial distribution of population abundance can be described. The lifespan of a same-aged population and the age structure of the species-specific population can also be studied with the aid of this temporally segmented model. The influence of correlation time of river flow fluctuation is also quantified according to the model. The calibration of model parameters and model application are discussed. The model provides a computer-aided method to simulate and predict vegetation dynamics during river flow disturbances. Meanwhile, the model is open and allows for more accurate and concrete modeling of growth rate. Because of the Markov property involved in the process-based solution, the model also has the ability to deal with cases of nonstationary disturbances.

[Spatial-temporal dynamics of rainstorm in East China based on spatial-temporal data mining technology]. / 基于时空数据挖掘技术的华东区域暴雨时空特征.

Based on TRMM 3B42 precipitation data, 5 time series at annual scale were constructed. Then the spatial and temporal dynamics of rainstorm in East China region from 2003 to 2015 were evaluated in the support of data mining and GIS spatial analysis technology. The results showed that, the spatial distributions of annual precipitation and annual rainstorm precipitation were similar during 2003-2015. Annual precipitation exhibited a slight increase trend while annual rainstorm ratio showed significant fluctuation. The imbalanced distribution of rainstorm in latitudinal direction was more obvious than that of longitudinal direction. Annual rainstorm frequency changed smoothly with significant spatial difference. Rainstorm showed a tendency of moving to north in the past 13 years. The changing trends of the five variables showed significant spatial differences, and most pixels showed non-significant increasing (or decreasing) trends.

[Succession of Phytoplankton Assemblages and Its Influencing Factors in Tangpu Reservoir, Zhejiang Province].

In order to explore the spatial-temporal dynamics of phytoplankton assemblages and its influencing factors in Tangpu Reservoir, phytoplankton and environmental variables were monthly monitored in 2011. The results showed that a total of 115 species of phytoplankton were identified, which belonged to 7 phyla and 62 genera. Phytoplankton abundance varied monthly with the maximum value (20.88×106 cells·L-1) in April and minimum (0.59×106 cells·L-1) in June. Variation partitioning of species data matrix showed that the variation of phytoplankton communities among months (account for 72.3%) was much larger than that among sampling sites (account for 2.5%), which indicated that phytoplankton communities had a high temporal but low spatial heterogeneity. Dominant species showed a marked seasonal succession pattern: diatom and blue-green algae species in spring, blue-green algae and green algae species in summer, diatom and cryptomonads species in autumn and winter. Result of multivariate analysis (RDA) indicated that HRT was the key factor affecting the shift between hydrological disturbance sensitive and tolerant species, and the formation of spring algal bloom; SiO2, WT and N:P were the key factors affecting the shift from diatom and cryptomonads species to blue-green algae and green algae species.