This study mapped the areal extent, identified the species composition, and analyzed the changes of salt marshes in the intertidal zone of China during the period 1985–2019. With the aid of the cloud ...platform of the Google Earth Engine, we selected Landsat 5/8 and Sentinel-2 images and used the support vector machine classification method to extract salt marsh information for the years of 1985, 1990, 1995, 2000, 2005, 2010, 2015, and 2019. Seven major species of salt marshes:
Phragmites australis
,
Suaeda
spp.,
Spartina alterniflora
,
Scirpus mariqueter
,
Tamarix chinensis
,
Cyperus malaccensis
, and
Sesuvium portulacastrum
were identified. Our results showed that salt marshes are mainly distributed in Liaoning, Shandong, Jiangsu, Shanghai, and Zhejiang, with varying patterns of shrinking, expansion, or wavering in different places. The distribution of salt marshes has declined considerably from 151,324 ha in 1985 to 115,397 ha in 2019, a drop of 23.7%. During the same period, the area of native species has dropped 95.4% from 77,741 ha to 3,563 ha for
Suaeda
spp. and 45.1% from 60,511 ha to 33,193 ha for
P. australis
; on the contrary, the area of exotic species,
S. alterniflora
, has exhibited a sharp rise from just 99 ha to 67,527 ha. For the past 35 years, the driving factors causing salt marsh changes are mainly land reclamation, variations in water and sand fluxes, and interspecific competition and succession of salt marsh vegetation. These results provide fundamental reference information and could form the scientific basis for formulating policies for the conservation and utilization of salt marsh resources in China.
Breast cancer (BC) is the most common female malignant tumor. Previous studies have suggested a big incidence disparity among different cities in China. The present work selected a typical city, ...Hangzhou, to study BC incidence disparity within the city.
Totally, 8784 female breast cancer cases were obtained from the Hangzhou Center for Disease Control and Prevention during the period 2008-2012. Analysis of Variance and Poisson Regression were the statistical tools implemented to compare incidence disparity in the space-time domain (reference group: township residents during 2008, area: subdistrict, town, and township, time frame: 2008-2012), space-time scan statistics was employed to detect significant spatiotemporal clusters of BC compared to the null hypothesis that the probability of cases diagnosed at a particular location was equal to the probability of cases diagnosed in the whole study area. Geographical Information System (GIS) was used to generate BC spatial distribution and cluster maps at the township level.
The subdistrict populations were found to have the highest and most stable BC incidence. Although town and township populations had a relatively low incidence, it displayed a significant increasing trend from 2008 to 2012. The BC incidence distribution was spatially heterogeneous and clustered with a trend-surface from the southwest low area to the northeast high area. High clusters were located in the northeastern Hangzhou area, whereas low clusters were observed in the southwestern area during the time considered.
Better healthcare service and lifestyle changes may be responsible for the increasing BC incidence observed in towns and townships. One high incidence cluster (Linping subdistrict) and two low incidence clusters (middle Hangzhou) were detected. The low clusters may be attributable mainly to developmental level disparity, whereas the high cluster could be associated with other risk factors, such as environmental pollution.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Soil sealing (loss of soil resources due to extensive land covering for the purpose of house building, road construction etc.) and subsequent soil landscape pattern changes constitute typical ...environmental problems in many places worldwide. Previous studies concentrated on soil sealing in urbanized regions, whereas rural areas have not been given sufficient attention. Accordingly, this paper studies soil landscape pattern dynamics (i.e., landscape pattern changes in response to rural anthropogenic activities) in the Tiaoxi watershed (Zhejiang province, eastern China), in which surface sealing is by far the predominant component of human forcing with respect to environmental change. A novel approach of quantifying the impacts of rural anthropogenic activities on soil resources is presented. Specifically, quantitative relationships were derived between five soil landscape pattern metrics (patch density, edge density, shape index, Shannon's diversity index and aggregation index) and three rural anthropogenic activity indicators (anthropogenic activity intensity, distance to towns, and distance to roads) at two landscape block scales (3 and 5 km) between 1985 and 2010. The results showed that the Tiaoxi watershed experienced extensive rural settlement expansion and high rates of soil sealing. Soil landscapes became more fragmented, more irregular, more isolated, and less diverse. Relationships between soil landscape pattern changes and rural anthropogenic activities differed with the scale (spatial and temporal) and variable considered. In particular, the anthropogenic activity intensity was found to be the most important indicator explaining social development intensity, whereas the other two proximity indicators had a significant impact at certain temporal interval. In combination with scale effects, spatial dependency (correlation) was shown to play a key role that should be carefully taken into consideration in any relevant environmental study. Overall, the findings of this work suggest that soil sealing can be a critical human forcing issue with considerable consequences deserving serious attention by the experts, the public and the government alike.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Long- and short-term exposure to PM2.5 is of great concern in China due to its adverse population health effects. Characteristic of the severity of the situation in China is that in the Jing-Jin-Ji ...region considered in this work a total of 2725 excess deaths have been attributed to short-term PM2.5 exposure during the period January 10–31, 2013. Technically, the processing of large space-time PM2.5 datasets and the mapping of the space-time distribution of PM2.5 concentrations often constitute high-cost projects. To address this situation, we propose a synthetic modeling framework based on the integration of (a) the Bayesian maximum entropy method that assimilates auxiliary information from land-use regression and artificial neural network (ANN) model outputs based on PM2.5 monitoring, satellite remote sensing data, land use and geographical records, with (b) a space-time projection technique that transforms the PM2.5 concentration values from the original spatiotemporal domain onto a spatial domain that moves along the direction of the PM2.5 velocity spread. An interesting methodological feature of the synthetic approach is that its components (methods or models) are complementary, i.e., one component can compensate for the occasional limitations of another component. Insight is gained in terms of a PM2.5 case study covering the severe haze Jing-Jin-Ji region during October 1–31, 2015. The proposed synthetic approach explicitly accounted for physical space-time dependencies of the PM2.5 distribution. Moreover, the assimilation of auxiliary information and the dimensionality reduction achieved by the synthetic approach produced rather impressive results: It generated PM2.5 concentration maps with low estimation uncertainty (even at counties and villages far away from the monitoring stations, whereas during the haze periods the uncertainty reduction was over 50% compared to standard PM2.5 mapping techniques); and it also proved to be computationally very efficient (the reduction in computational time was over 20% compared to standard mapping techniques).
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•A synthetic approach for assessing and mapping PM2.5 distribution is presented.•Informative PM2.5 concentration maps with low mapping uncertainty are obtained.•Introducing remote sensing technique can reduce the uncertainty of PM2.5 prediction.•Remote sensing stations can be set to evaluate current and historical ground PM2.5.•This approach is proved to be computationally efficient for handling large datasets.
Compared to standard techniques, the synthetic approach generated PM2.5 concentration maps with over 50% estimation uncertainty reduction and over 20% computational time reduction.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Macrobenthos organisms are vital ecological components of intertidal wetlands. This work studied effects of non-native mangrove rehabilitation (
Kandelia obovata
) and salt marsh invasion (
Spartina ...alterniflora
) on macrobenthos communities in Ximen Island (Zhejiang, China). The macrobenthos communities were compared between rehabilitated
K. obovata
forests of five different stand ages (2-, 8-, 11-, 16-, and 60-year-old) and adjacent
S. alterniflora
marsh and non-vegetated mudflat. Compared to the mudflat,
S. alterniflora
increased the abundance, Shannon–Wiener diversity index (
H’
), and Margalef's richness index (
d’
) of macrobenthos. Gastropoda abundance was high in the
S. alterniflora
marsh, whereas, malacostraca biomass was low. Within mangrove forests, macrobenthos abundance was positively correlated with the stand age of mangroves (Spearman Correlation,
P
< 0.05), but the corresponding
H’
,
d’
and Pielou's evenness index (
J’
) showed negative correlations. Gastropoda dominated over macrobenthos in the younger stands (2–11 years in age), whereas, phascolosomatidea and bivalvia were more abundant in the older stands (16 and 60 years in age). Noticeably, the highest biomass for malacostraca was recorded from the 11-year-old stand. Macrobenthos communities differed among habitats, with the divergence in community structure between the
S. alterniflora
marsh and mangrove stands increasing with mangrove stand age, to be significantly different for stands planted over 16 years ago. Since the 16-year-old stand exhibited similar macrobenthos features to the 60-year-old stand, we speculated that, in the case of macrobenthos, a rehabilitated
K. obovata
forest can reach its maturity level at a time period of about 15 years in Ximen Island.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Spartina alterniflora has extensively invaded the coastline of China, including in Maoyan Island of Zhejiang Province. Ecological restoration has been conducted using non-native mangrove Kandelia ...obovata to replace S. alterniflora in an attempt to restore the impacted intertidal zones. To illustrate the ecological effectiveness of the restoration projects, macrobenthos communities were studied among different habitats within the restored areas, including one non-restored S. alterniflora marsh (SA) and three differently-aged restored K. obovata stands planted in 2003, 2009, and 2011 respectively (KF14, KF8, and KF6). Besides, one unvegetated mudflat (MF) adjacent to the non-restored S. alterniflora marsh and one K. obovata forest transplanted in 2006 (RKF) at a previously barren mudflat without invasion history of S. alterniflora were set as reference sites. A total of 69 species of macrobenthos were collected from Maoyan Island, and the species richness was dominated by gastropoda (23 species), polychaeta (18 species), and malacostraca (16 species). There was no significant difference between the six sites in terms of the abundance of macrobenthos, with the average values of abundance peaking in KF6 (734.7 ind m−2) and being lowest in RKF (341.3 ind m−2). The six sites had significant differences in terms of the biomass of macrobenthos. The KF8 site contained the highest average biomass (168.3 g m−2), whereas the MF site had the lowest (54.3 g m−2). The Shannon-Wiener diversity index and Pielou’s evenness index of the macrobenthos did not exhibit significant differences among the six sites. However, the results of permutational multivariate analysis of variance (PERMANOVA) revealed significant spatial differences in the macrobenthos community structure between the sites. Since KF14 shared a similar macrobenthos community structure with RKF, while representing a strikingly different structure from SA, we infer that ecological restoration using K. obovata can restore the macrobenthos community to resemble to a normally planted K. obovata forest about 15 years after restoration.
Seaweed aquaculture is vital in protecting the marine eco-environment and mitigating climate change. China generates more than half of the world's total seaweed production. However, despite multiple ...local studies, accurate and reliable information on broad-scale seaweed farms is still scarce. Using an object-based method to classify 3 m spatial resolution Planet Scope images along offshore China, a total of 129,494 ha of cultured seaweed was identified and delineated with an overall accuracy of 95.70% and a KAPPA index of 0.912, respectively. Then, a seaweed map in offshore China in 2018-2019 was developed. The results provided basic information about seaweed farms in China. The approach reported in this work is accurate and efficient, which can be used to replace the conventional method to obtain the culture seaweed information. This study can be of reference for mapping seaweed on a broader or global scale.
This paper is concerned with the modeling of infectious disease spread in a composite space-time domain under conditions of uncertainty. We focus on stochastic modeling that accounts for basic ...mechanisms of disease distribution and multi-sourced in situ uncertainties. Starting from the general formulation of population migration dynamics and the specification of transmission and recovery rates, the model studies the functional formulation of the evolution of the fractions of susceptible-infected-recovered individuals. The suggested approach is capable of: a) modeling population dynamics within and across localities, b) integrating the disease representation (i.e. susceptible-infected-recovered individuals) with observation time series at different geographical locations and other sources of information (e.g. hard and soft data, empirical relationships, secondary information), and c) generating predictions of disease spread and associated parameters in real time, while considering model and observation uncertainties. Key aspects of the proposed approach are illustrated by means of simulations (i.e. synthetic studies), and a real-world application using hand-foot-mouth disease (HFMD) data from China.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The Hand-Foot-Mouth Disease (HFMD) is the most common infectious disease in China, its total incidence being around 500,000~1,000,000 cases per year. The composite space-time disease variation is the ...result of underlining attribute mechanisms that could provide clues about the physiologic and demographic determinants of disease transmission and also guide the appropriate allocation of medical resources to control the disease.
HFMD cases were aggregated into 1456 counties and during a period of 11 months. Suspected climate attributes to HFMD were recorded monthly at 674 stations throughout the country and subsequently interpolated within 1456 × 11 cells across space-time (same as the number of HFMD cases) using the Bayesian Maximum Entropy (BME) method while taking into consideration the relevant uncertainty sources. The dimensionalities of the two datasets together with the integrated dataset combining the two previous ones are very high when the topologies of the space-time relationships between cells are taken into account. Using a self-organizing map (SOM) algorithm the dataset dimensionality was effectively reduced into 2 dimensions, while the spatiotemporal attribute structure was maintained. 16 types of spatiotemporal HFMD transmission were identified, and 3-4 high spatial incidence clusters of the HFMD types were found throughout China, which are basically within the scope of the monthly climate (precipitation) types.
HFMD propagates in a composite space-time domain rather than showing a purely spatial and purely temporal variation. There is a clear relationship between HFMD occurrence and climate. HFMD cases are geographically clustered and closely linked to the monthly precipitation types of the region. The occurrence of the former depends on the later.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background: Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in China, especially in Heilongjiang province (90% of all reported HFRS cases worldwide occur in China). The dynamic ...identification of high HFRS incidence spatiotemporal regions and the quantitative assessment of HFRS associations with climate change in Heilongjiang province can provide valuable guidance for HFRS monitoring, preventing and control. Yet, so far there exist very few and of limited scope quantitative studies of the spatiotemporal HFRS spread and its climatic associations in Heilongjiang province. Making up for this lack of quantitative studies is the reason for the development of the present work.Method: To address this need, the well-known Bayesian maximum entropy (BME) method of space-time modeling and mapping together with its recently proposed variant, the projected BME (P-BME) method, were employed in this work to perform a composite space-time analysis and mapping of HFRS incidence in Heilongjiang province during the years 2005–2013. Also, using multivariate El Niño-Southern Oscillation index as a proxy, we proposed a combination of Hilbert-Huang transform and wavelet analysis to study the “HFRS incidence-climate change” associations.Results: The main results of this work were two-fold: (1) three core areas were identified with high HFRS incidences that were spatially distributed and exhibited distinct biomodal temporal patterns in the eastern, western, and southern parts of Heilongjiang province; and (2) there exists a considerable association between HFRS incidence and climate change, particularly, an ~6 months period coherency was clearly detected.Conclusions: The combination of modern space-time modeling and mapping techniques (P-BME theory, Hilbert-Huang spectrum analysis, and wavelet analysis) used in this work led to valuable quantitative findings concerning the spatiotemporal spread of HFRS incidence in Heilongjiang province and its association with climate change. Our essential findings include the identification of three core areas with high HFRS incidences in Heilongjiang province, and considerable evidence that HFRS incidence is closely related to climate change.
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