Spatial pattern of the ecological environment in Yunnan Province.
Ontology highlight
ABSTRACT:
SUBMITTER: Wang D
PROVIDER: S-EPMC8219156 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Yunnan Province, China is thought to be the original source of biovar Orientalis of Yersinia pestis, the causative agent of the third plague pandemic that has spread globally since the end of the 19th century. Although encompassing a large area of natural plague foci, Y. pestis strains have rarely been found in live rodents during surveillance in Yunnan, and most isolates are from rodent corpses and their fleas. In 2017, 10 Y. pestis strains were isolated from seven live rodents and three fleas in Heqing County (HQ) of Yunnan. These strains were supposed to have low virulence to local rodents Eothenomys miletus and Apodemus chevrieri because the rodents were healthy and no dead animals were found in surrounding areas, as had occurred in previous epizootic disease. We performed microscopic and biochemical examinations of the isolates,and compared their whole-genome sequences and transcriptome with those of 10 high virulence Y. pestis strains that were isolated from the adjacent city (Lijiang). We analyzed the phenotypic, genomic, and transcriptomic characteristics of live rodent isolates. The isolates formed a previously undefined monophyletic branch of Y. pestis that was named 1.IN5. Six SNPs, two indels, and one copy number variation were detected between live rodent isolates and the high virulence neighbors. No obvious functional consequence of these variations was found according to the known annotation information. Among the genes that were differentially expressed between the live rodent isolates and their high virulence neighbors, we detected five iron transfer-related genes that were significantly up-regulated in live rodent isolates compared with high virulence isolates (|log2 (FC) | >1, p.adjust <0.05), indicating these genes may be related to the low-virulence phenotype. The novel genotype of Y. pestis reported here provides further insights into the evolution and spread of plague as well as clues that may help to decipher the virulence mechanism of this notorious pathogen.
2021-04-20 | GSE161888 | GEO
Project description:Pollinating butterflies are an important asset to agriculture, which still depends on wild resources. Yunnan Province in Southwest China is a region with typical montane agriculture, but this resource is poorly investigated. From literature reference and specimen examination, the present study identified 554 species of pollinating butterflies (50.8% of the total butterflies) from Yunnan, with family Nymphalidae possessing the least number of pollinators (80 species, 16.0%), while the remaining four families are pollinator-rich (>73%). Tropical lowlands and mountain-valley areas possess higher species richness than those with plain terrains. The species richness of pollinating butterflies in Yunnan does not simply decline with the increase of latitude, nor is significantly different between West and East Yunnan. Zonation of pollinating butterflies using the parsimony analysis of endemicity (PAE) identified nine distribution zones and ten subzones. Most areas of endemism (AOE) are found in lowlands or mountain-valley areas, complexity of terrains, climates, and vegetation types are believed to be the main causes of such endemicity. The potential pollinating service of these butterflies could be great to montane agriculture with expanding areas of cash crops and fruit horticulture. Conservation strategies for pollinating butterflies may consist of preserving habitats and establishing butterfly-friendly agriculture based on local traditions.
| S-EPMC7469173 | biostudies-literature
Project description:The ecological security pattern construction could effectively regulate ecological processes and ensure ecological functions, then rationally allocate natural resources and green infrastructure, and, finally, realize ecological security. In view of serious soil erosion, accelerated land desertification, soil pollution and habitat degradation in Shanxi Province, the spatial distribution of six key ecosystem services, including water conservation (WC), soil conservation (SC), sand fixation (SF), carbon storage (CS), net primary productivity (NPP) and habitat quality (HQ), was analyzed by using multiple models. The comprehensive ability of multiple ecosystem services in different regions was quantified by calculating multiple ecosystem services landscape index (MESLI). Combined with ecosystem services hotspots, the ecological security pattern of Shanxi Province was constructed by using the minimum cumulative resistance model. The results showed that the spatial differences in ecosystem services in Shanxi Province were obvious, which was low in the seven major basins and Fen River valley, and high in the mountains (especially Taihang and Lvliang Mountains) for WC, SC, CS, NPP and HQ, while high SF was only distributed in the northern Shanxi. The MESLI showed that the ability to provide multiple ecosystem services simultaneously was low in Shanxi Province, with the medium and low grade MESLI regions accounting for 58.61%, and only 18.07% for the high grade MESLI regions. The important protected areas and ecological sources of the ecological security pattern were concentrated in the Lvliang and Taihang Mountains, which were consistent with the key areas of ecosystem services. The ecological corridors illustrated network distribution with ecological sources as the center, the low-, medium- and high-level buffers accounted for 26.34%, 17.03% and 16.35%, respectively. The results will provide important implications for economic transformation, high-quality development and ecological sustainable development in resource-based regions worldwide.
| S-EPMC10049408 | biostudies-literature
Project description:BackgroundTuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS). The aim of this study was to identify the spatial-temporal dynamic process and high-risk region of notified pulmonary tuberculosis (PTB), sputum smear-positive tuberculosis (SSP-TB) and sputum smear-negative tuberculosis (SSN-TB) cases in Yunnan, the south-western of China between years of 2005 to 2018. Meanwhile, to evaluate the similarity of prevalence pattern for TB among GMS.MethodsData for notified PTB were extracted from the China Information System for Disease Control and Prevention (CISDCP) correspond to population information in 129 counties of Yunnan between 2005 to 2018. Seasonally adjusted time series defined the trend cycle and seasonality of PTB prevalence. Kulldorff's space-time scan statistics was applied to identify temporal, spatial and spatial-temporal PTB prevalence clusters at county-level of Yunnan. Pearson correlation coefficient and hierarchical clustering were applied to define the similarity of TB prevalence among borders with GMS.ResultThere were a total of 381,855 notified PTB cases in Yunnan, and the average prevalence was 59.1 per 100,000 population between 2005 to 2018. A declined long-term trend with seasonality of a peak in spring and a trough in winter for PTB was observed. Spatial-temporal scan statistics detected the significant clusters of PTB prevalence, the most likely cluster concentrated in the northeastern angle of Yunnan between 2011 to 2015 (RR = 2.6, P < 0.01), though the most recent cluster for PTB and spatial cluster for SSP-TB was in borders with GMS. There were six potential TB prevalence patterns among GMS.ConclusionThis study detected aggregated time interval and regions for PTB, SSP-TB, and SSN-TB at county-level of Yunnan province. Similarity prevalence pattern was found in borders and GMS. The localized prevention strategy should focus on cross-boundary transmission and SSN-TB control.
| S-EPMC6925503 | biostudies-literature
Project description:ObjectiveThis study aimed to investigate the spatial distribution of drug-resistant tuberculosis (DR-TB) in Hunan province, China.MethodsAn ecological study was conducted using DR-TB data collected from the Tuberculosis Control Institute of Hunan Province between 2012 and 2018. Spatial clustering of DR-TB was explored using the Getis-Ord statistic. A Poisson regression model was fitted with a conditional autoregressive prior structure, and with posterior parameters estimated using a Bayesian Markov chain Monte Carlo simulation, to quantify associations with possible risk factors and identify clusters of high DR-TB risk.ResultsA total of 2649 DR-TB patients were reported to Hunan TB Control Institute between 2012 and 2018. The majority of the patients were male (74.8%, n=1983) and had a history of TB treatment (88.53%, n=2345). The proportion of extensively DR-TB among all DR-TB was 3.3% (95% CI 2.7% to 4.1%), which increased from 2.8% in 2012 to 4.4% in 2018. Of 1287 DR-TB patients with registered treatment outcomes, 434 (33.8%) were cured, 198 (15.3%) completed treatment, 92 (7.1%) died, 108 (8.3%) had treatment failure and 455 (35.3%) were lost to follow-up. Half (50.9%, n=655) had poor treatment outcomes. The annual cumulative incidence rate of notified DR-TB increased over time from 0.25 per 100 000 people in 2012 to 0.83 per 100 000 people in 2018. Substantial spatial heterogeneity was observed, and hotspots were detected in counties located in the North and East parts of Hunan province. The cumulative incidence of notified DR-TB was significantly associated with urban communities.ConclusionThe annual incidence of notified DR-TB increased over time in Hunan province. Spatial clustering of DR-TB was detected and significantly associated with urbanisation. This finding suggests that targeting interventions to the highest risk areas and population groups would be effective in reducing the burden and ongoing transmission of DR-TB.
| S-EPMC8021748 | biostudies-literature
Project description:BackgroundFollowing its resurgence in 1982, rodent plague has been linked to a wide range of circulation risks in Yunnan Province. The most serious public health concern associated with effective plague control is determining how various ecological variables influence the differential risk of transmission.MethodsWe investigated the population dynamics of the hosts and vectors using large-scale epidemiological surveillance data. In a seasonal eco-epidemiological model, we evaluated the impact of ecological conditions on the vectored flea index (VFI) to determine the rate of plague transmission.ResultsThe findings revealed a changing species composition in natural foci over time. Additionally, shifting distributional ranges of species by elevation may be vital in modulating the VFI. The model estimates indicate that the dynamic VFI contributes to spatiotemporal variance in transmission.ConclusionsThe VFI could be a critical ecological indicator, allowing for real-time tracking and prompt intervention in the circulation of rodent plague. Understanding eco-epidemiological diversity can provide essential insights into effective responses to future plague resurgence.
| S-EPMC10287002 | biostudies-literature
Project description:The analysis of status and major sources of human pressures on natural reserves (NRs) is important for optimizing their management. This study selected population density, gross domestic product (GDP) density and areal percentage of human land use to reveal the human pressures of national and provincial NRs (NNRs and PNRs) in Yunnan Province, China. We calculated three types of internal and external human pressure index (HPI) and comprehensive HPI (CHPI) for NRs. Human pressures on most of NRs were slight and light, indicating that most of NRs were well protected. Human pressures on PNRs were higher than on NNRs; with respect to five types of NRs, geological relict NRs were facing the highest human pressures, followed by wetland ecosystem NRs. Land use and population density were the main human pressures on these NRs. Yunnan Province should put the highest emphasis on three NNRs and two Ramsar site PNRs with severe CHPI, secondly pay attention to eight conservation-oriented PNRs with extreme or severe CHPI. It's urgent for Yunnan to implement scientific policies and measures to reduce land use and population density pressures of NRs, especially with severe and extreme CHPI, by transforming internal land use and/or implementing residents' eco-migration.
| S-EPMC5818542 | biostudies-other
Project description:Ecological conservation red line (ECRL) is gaining increasing academic attention as delimiting the minimum space scope of ecological protection and the bottom line of ecological security. Taking Nanjing as a case study, we divided the territory into ecological and non-ecological redline areas (ERAs and NERAs, respectively). This paper highlights two key research issues based on the 2005, 2010, 2015 and 2018 annual remote sensing data: (i) quantitative analysis of the Ecological Redline Policy (ERP) validity by conducting a horizontal comparison of the ERAs and NERAs; and (ii) exploration of the land-use transitions and spatial pattern changes affecting ecosystem service value (ESV). Results showed that delineating ECRL could effectively slow down the decline rate of ESV. The trend of eco-quality deterioration was greater than eco-quality improvement in Nanjing, presenting an ESV that declined slightly in the whole. According to our findings, we suggest that reasonably increasing eco-lands (woodland and water area) and decreasing construction land will enhance the regional ESV. Meanwhile, promoting the transition from production space to ecological space and depressing the encroachment of living space on other space types, will be instrumental in mitigating the ESV decline. The results of this study are expected to provide valuable implications for spatial planning and sustainable development in Nanjing.
| S-EPMC8073379 | biostudies-literature
Project description:Venerable trees are important natural resources and cultural heritage, offering historical, ecological, social and economic value. However, global warming and anthropogenic activities have threatened their welfare and survival. A comprehensive understanding of their current and future spatial patterns, vis-á-vis environmental conditions, can inform the co-management of sustainable resource use and conservation. We employed the existing spatial occurrence data and environmental variables (bioclimate and elevation) to simulate the optimal habitats for venerable trees in China’s Sichuan Province. We evaluated the current and future climate scenarios of 2100 with double CO2 concentration. The BIOCLIM and QGIS spatial analyses assessed the primary factors of geographical distribution. The results identified 10,720 venerable trees from 123 species, 81 genera and 42 families. Cupressus funebris dominated, with the maximum importance value, followed by Ginkgo biloba, Ficus virens var. sublanceolata, and Phoebe zhennan. The elevation distribution of tree abundance and species richness demonstrated a unimodal pattern, skewing to the low-elevation end, with a concentration in the 600–1500 m low-medium altitude. The majority of trees and excellent habitats were found in eastern Sichuan with a less harsh terrain and climate. The bio3 (isothermality) and bio7 (temperature annual range) factors significantly influenced tree occurrence. Temperature imposed a greater effect on distribution than moisture under the current climate scenario. For the future climate-change scenario, the suitable habitats were predicted to maintain an overall stable pattern, with largely contiguous expansions of better habitats. However, climate warming would shrink the excellent habitats on the plains. The findings can inform strategies and guidelines for venerable-tree conservation in Sichuan. Furthermore, vulnerable areas could be identified. The future range expansion sites could be enlisted to cultivate new trees to replenish the venerable-tree pool. Habitat patches that remain sustainable could provide refugia with the potential for protected-area designation.
| S-EPMC9780929 | biostudies-literature
Project description:The ongoing global warming trajectory poses extensive challenges to plant ecosystems, with rubber plantations particularly vulnerable due to their influence on not only the longevity of the growth cycle and rubber yield, but also the complex interplay of carbon, water, and energy exchanges between the forest canopy and atmosphere. However, the response mechanism of phenology in rubber plantations to climate change remains unclear. This study concentrates on sub-optimal environment rubber plantations in Yunnan province, Southwest China. Utilizing the Google Earth Engine (GEE) cloud platform, multi-source remote sensing images were synthesized at 8-day intervals with a spatial resolution of 30-meters. The Normalized Difference Vegetation Index (NDVI) time series was reconstructed using the Savitzky-Golay (S-G) filter, coupled with the application of the seasonal amplitude method to extract three crucial phenological indicators, namely the start of the growing season (SOS), the end of the growing season (EOS), and the length of the growing season (LOS). Linear regression method, Pearson correlation coefficient, multiple stepwise regression analysis were used to extract of the phenology trend and find the relationship between SOS, EOS and climate factors. The findings demonstrated that 1) the phenology of rubber plantations has undergone dynamic changes over the past two decades. Specifically, the SOS advanced by 9.4 days per decade (R2 = 0.42, p< 0.01), whereas the EOS was delayed by 3.8 days per decade (R2 = 0.35, p< 0.01). Additionally, the LOS was extended by 13.2 days per decade (R2 = 0.55, p< 0.01); 2) rubber phenology demonstrated a notable sensitivity to temperature fluctuations during the dry season and precipitation patterns during the rainy season. The SOS advanced 2.0 days (r =-0.19, p< 0.01) and the EOS advanced 2.8 days (r =-0.35, p< 0.01) for every 1°C increase in the cool-dry season. Whereas a 100 mm increase in rainy season precipitation caused the SOS to be delayed by 2.0 days (r = 0.24, p< 0.01), a 100 mm increase in hot-dry season precipitation caused the EOS to be advanced by 7.0 days (r =-0.28, p< 0.01); 3) rubber phenology displayed a legacy effect of preseason climate variations. Changes in temperature during the fourth preseason month and precipitation during the fourth and eleventh preseason months are predominantly responsible for the variation in SOS. Meanwhile, temperature changes during the second, fourth, and ninth preseason months are primarily responsible for the variation in EOS. The study aims to enhance our understanding of how rubber plantations respond to climate change in sub-optimal environments and provide valuable insights for sustainable rubber production management in the face of changing environmental conditions.
| S-EPMC10752945 | biostudies-literature