Pine wilt disease is a devastating forest disease caused by the pinewood nematode
, which has been listed as the object of quarantine in China. Climate change influences species and may exacerbate ...the risk of forest diseases, such as the pine wilt disease. The maximum entropy (MaxEnt) model was used in this study to identify the current and potential distribution and habitat suitability of three pine species and
in China. Further, the potential distribution was modeled using the current (1970-2000) and the projected (2050 and 2070) climate data based on two representative concentration pathways (RCP 2.6 and RCP 8.5), and fairly robust prediction results were obtained. Our model identified that the area south of the Yangtze River in China was the most severely affected place by pine wilt disease, and the eastern foothills of the Tibetan Plateau acted as a geographical barrier to pest distribution. Bioclimatic variables related to temperature influenced pine trees' distribution, while those related to precipitation affected
's distribution. In the future, the suitable area of
will continue to increase; the shifts in the center of gravity of the suitable habitats of the three pine species and
will be different under climate change. The area ideal for pine trees will migrate slightly northward under RCP 8.5. The pine species will continue to face
threat in 2050 and 2070 under the two distinct climate change scenarios. Therefore, we should plan appropriate measures to prevent its expansion. Predicting the distribution of pine species and the impact of climate change on forest diseases is critical for controlling the pests according to local conditions. Thus, the MaxEnt model proposed in this study can be potentially used to forecast the species distribution and disease risks and provide guidance for the timely prevention and management of
.
Landslides are dangerous natural hazards. Because of their threat, a comprehensive landslide susceptibility map should be produced to reduce the possible damages to people and infrastructure. The ...quality of landslide susceptibility maps is influenced by many factors, such as the quality of input data and the selection of mathematical models. This study aimed to identify the optimal quantitative method for landslide susceptibility mapping in Mizunami City, Japan. Three mathematical methods, logistic regression (LR), bivariate statistical analysis (BS), and multivariate adaptive regression spline models (MARSplines), were used to create landslide-susceptibility maps by comparing the past landslide distribution and the conditioning factor thematic maps. A landslide inventory map with a total of 222 landslide locations was extracted from aerial photographs provided by NIED (National Research Institute for Earth Science and Disaster Prevention, Japan). Then, the landslide inventory was randomly divided into two datasets: 50% was used for training the models and the remaining 50% for validation purposes. The landslide inventory map provided by NIED and an area under the ROC curve were used to evaluate model performance. We found that the MARSpline method resulted in a better prediction rate (79%) when compared to LR (75%) and BS (77%). In addition, a higher percentage of landslide polygons were found in the high to very high classes using the MARSpline method. Therefore, we concluded that the MARSpline method was the most efficient method for landslide susceptibility mapping in this study area.
•This study provides three methods for landslide susceptibility mapping.•BS, LR, and MARSpline methods were used in this study.•MARSpline shows the most approximate results.
•Priority conservation region was established by balancing ecosystem services.•The selection of conservation priorities was proved to be reliable by analyzing spatiotemporal changes in ecosystem ...services.•The implementation of the Grain-for-Green Programme and the increase in rainfall have improved ecosystem services.•Forest land types should be taken into account for future forest management.
Ecosystems are severely damaged with rising global temperatures, the rapid increase in population and the continuous exploitation and utilization of natural resources. The selection of conservation priorities is of great significance to regional ecological security and sustainable development. Here we identified conservation priorities by balancing ecosystem services trade-offs and analyzed the spatiotemporal changes in ecosystem services. Water yield, soil conservation, carbon storage, habitat quality, and ecological recreation were quantified using the InVEST model. By comparing conservation efficiencies under each scenario, we found the conservation efficiencies of the conservation priorities for water yield, soil conservation, habitat quality, carbon storage, and ecological recreation to be 1.05, 1.76, 1.30, 1.37 and 1.41, respectively. The conservation efficiencies of ecosystem services were consistently greater than 1 during the years 2000–2015. The implementation of the Grain-for-Green Programme and increased rainfall have improved ecosystem services and our results are of great significance to regional ecological and environmental protection and the improvement of ecosystem services.
•Variation in soil properties at tree, bush, and grass sites in wetlands was examined.•Soil quality index (SQI) was characterized to assess soil quality at the three sites.•SQI in surface soils ...(0–10 cm) was higher at tree/grass site than that at bush site.•SQI in deeper soils (10–60 cm) was significantly lower than that in surface soils.•Soil organic carbon and total soil porosity were the key soil quality indicators.
Assessment of soil quality in different vegetation types of wetland ecosystems is essential for soil functioning, such as nutrient cycling and vegetation growth, particularly the maintenance of wetland ecosystem sustainability. Wetland degradation can extremely influence soil quality. However, prediction of soil quality in terms of soil quality index in wetland soils remains obscure. In this study with the fundamental goal to assess soil quality, we have intended to assemble a range of soil quality indicators to characterize the soil quality index (SQI). The minimum data set (MDS) from the Principal component analysis (PCA) was used to determine the SQI. With such objectives, three vegetation types: Robinia pseudoacacia community (tree), Tamarix chinensis community (bush), and Suaeda salsa community (grass) were selected in the Yellow River Delta wetland, eastern of China. A total of 108 soil samples 3 sites (tree, bush and grass)—3 field plots—3 replicates—4 soil depth layers: 0–10 cm, 10–20 cm, 20–40 cm, and 40–60 cm were collected for laboratory analyses. This study showed that there were high variations in soil physical and chemical properties among the three sites. Soil organic carbon (SOC), silt, clay, and pH at tree site, total soil porosity (TSP), soil organic carbon (SOC), pH, and soil bulk density (SBD) at bush site, and total soil porosity (TSP), silt, and soil electronic conductivity (SEC) at grass site were retained in the MDS. SOC and TSP were the key soil quality indicators. The values of the SQI at 0–10 cm soil depth at all three sites (2.236, 0.895, and 2.573 respectively) were the highest compared with other soil depths, indicating the best soil quality in the upper soil layers (0–10 cm). The values of the SQI at 0–10 cm soil depth at both tree site and grass site were similar, and they were higher than those at bush site. At tree site, the values of the SQI decreased with increasing soil depth, which indicated that soil quality became worse with depth. At bush site, the values of the SQI decreased with increasing soil depth (0–40 cm), while the values increased at 40–60 cm depth, indicating better soil quality in the deeper soil layers (40–60 cm). At grass site, the values of the SQI at 10–20 cm and 40–60 cm soil depth were lower than those at 20–40 cm soil depth, indicating better soil quality at 20–40 cm soil depth. It is concluded that the SQI can be compared more accurately in different vegetation types of wetland ecosystems based on its simplicity and quantitative flexibility. These findings are of importance because the assessment of the SQI allows to quantify different vegetation effects on soil quality.
Dendrobium, an important medicinal plant, is a source of widely used herbal medicine to nourish the stomach and treat throat inflammation. The present study is aimed at distinguishing and evaluating ...three major Dendrobium species by comparing physiochemical characteristics and understanding differences between different growth years in the Ta-pieh Mountains. Polysaccharides and total alkaloids of Dendrobium were determined, and the amino acids and trace elements were determined by UPLC (Ultra High-Performance Liquid Chromatography) and ICP-MS (Inductively coupled plasma mass spectrometry). It can be seen from the results that the polysaccharide content of these three kinds of Dendrobium in different growth years ranges from 249.31 mg·g-1 to 547.66 mg·g-1, and the highest content is in the 3-year-old Dendrobium huoshanense. The total alkaloid content ranges from 0.21 mg·g-1 to 0.54 mg·g-1, and the highest content is also the 3-year-old Dendrobium huoshanense. We determined the amino acid content of these three Dendrobium in different growth years, and we can see that each of the three kinds of Dendrobium contain seven kinds of amino acids required by the human body. We conducted a safety evaluation of the essential trace elements of Dendrobium, and the results showed that the dosage of 12g·d-1 Dendrobium prescribed in China Pharmacopoeia is in accordance with the recommended daily intake of trace elements recommended by the Food and Drug Administration of the United States, and will not cause trace element poisoning. Linear discriminant analysis was carried out on the basis of amino acids and trace elements and confirmed the applicability of multi-elemental analysis for identifying different Dendrobium species.
•The index of hydrological connectivity (IHC) changed both spatially and temporally.•The spatial distribution of high IHC has been extremely fragmented since 2010.•IHC could be treated as a novel ...indicator of the status of wetland degradation.•Soil property had larger influences on IHC than roots systems at root-soil interface.
In this study, an innovative method was used to assess the spatial and temporal patterns of the hydrological connectivity in soil profiles in the Yellow River Delta wetland. In this method, field dye-tracing experiments conducted in the study area (i.e., large LWa and small communities LWb of Phragmites australis and Suaeda glauca JP) were considered, and the root-soil interface in the region and the status of the wetland degradation were analyzed. The results revealed that the index of hydrological connectivity (IHC) significantly changed both spatially and temporally. The high IHC values reaching a 0.392 ± 0.209 gradient were concentrated in the middle and western parts of the study areas. The spatial distribution of the high hydrological connectivity has been extremely fragmented since 2010. The LWb (severely degraded wetland) and JP (extremely degraded wetland) were found to be more seriously degraded than the LWa (moderately degraded wetland) in the study area. The changes in the IHC were positively correlated with the principal component (PC) values of the wetland degradation. The IHC is a novel indicator of the status of wetland degradation. Furthermore, the soil holding capacity, soil non-capacity porosity, and soil ventilation were relatively important for the changes in the IHC. Compared with the soil properties, the hydrological responses of the roots systems can be neglected at the root-soil interface. Based on our results, we propose an alternative wetland restoration solution for the Yellow River Delta wetland: 1) a seepage layer in the surface soils (0–10 cm), shallow ploughing treatment, and litter or straw return to the soil surface should be conducted to increase the hydrological connectivity of the soil surface; 2) reeds should not be reaped every year to remove the nutrients from this area; and 3) appropriate freshwater inputs should be strengthened.
Acid rain is mainly caused by dissolution of sulfur dioxide and nitrogen oxides in the atmosphere, and has a significant negative effect on ecosystems. The relative composition of acid rain is ...changing gradually from sulfuric acid rain (SAR) to nitric acid rain (NAR) with the rapidly growing amount of nitrogen deposition. In this study, we investigated the impact of simulated SAR and NAR on litter decomposition and the soil microbial community over four seasons since March 2015. Results first showed that the effects of acid rain on litter decomposition and soil microbial were positive in the early period of the experiment, except for SAR on soil microbes. Second, soil pH with NAR decreased more rapidly with the amount of acid rain increased in summer than with SAR treatments. Only strongly acid rain (both SAR and NAR) was capable of depressing litter decomposition and its inhibitory effect was stronger on leaf than on fine root litter. Meanwhile, NAR had a higher inhibitory effect on litter decomposition than SAR. Third, in summer, autumn and winter, PLFAs were negatively impacted by the increased acidity level resulting from both SAR and NAR. However, higher acidity level of NAR (pH=2.5) had the strongest inhibitory impact on soil microbial activity, especially in summer. In addition, Gram-negative bacteria (cy19:0) and fungi (18:1ω9) were more sensitive to both SAR and NAR, and actinomycetes was more sensitive to SAR intensity. Finally, soil total carbon, total nitrogen and pH were the most important soil property factors affecting soil microbial activity, and high microbial indices (fungi/bacteria) with high soil pH. Our results suggest that the ratio of SO42− to NO3− in acid rain is an important factor which could affect litter decomposition and soil microbial in subtropical forest of China.
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•Sulfuric (SAR) and nitric acid rain (NAR) accelerated litter decomposition in the early phase of experiment.•SAR and NAR depressed litter decomposition and their inhibitory effects were stronger on leaf-litter.•High intensity NAR inhibited soil microbial more significantly than SAR during the rainy season.•Gram-negative bacteria and fungi were more sensitive to acid rain, actinomycetes was more sensitive to SAR intensity.
Forest conversion may affect the soil microbial community through impacts on soil properties. However, our understanding of the effects on the soil bacterial community remains limited. The objective ...of this study was to understand the impacts of forest conversion of native broad-leaved species on soil bacterial structure and diversity. The phylogeny structure and diversity of the soil bacterial communities were compared among four forest types. We found that the soil total nitrogen (TN) and C:N ratios were significantly different between a mixed forest and other forest types. The native forest and mixed forest contained a higher relative abundance of Actinobacteria, Gammaproteobacteria, and Acidimicrobiia compared with the Chinese fir and Bamboo forests, but more unique operational taxonomic units (OTUs) were found in the Chinese fir and Bamboo forests. Soil bacteria in bamboo forest and Chinese fir forest showing a higher diversity but a lower total sequencing number than native forest and mixed forest. Among the soil properties, pH was an important variable that contributing to both soil bacterial communities and soil alpha diversities. Our work suggests that after a long-tern forest conversion, both land-use history and vegetation species strongly influence soil bacteria communities, and soil pH is a main factor that influences soil bacterial structure.
•Forest conversion has a profound impact on soil bacterial composition.•Land use history has a long lasting influence on soil bacteria OTUs.•Change to a pure forest did not cause a decrease in soil bacterial diversity.
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•The relative contributions of climate and LULC change to ESs were distinguished.•The changes in water yield and soil retention were related to climate change.•The change in NPP was ...mainly dominated by LULC change.•Afforestation reduced water yield, while deforestation and urbanization increased it.•Decisions should consider the relative contributions of climate and LULC changes.
Understanding impacts of land use/cover (LULC) and climate change ecosystem services (ESs) is critical to human well-being. However, existing studies seldom determined the relative contributions of LULC and climate change to ESs from a geospatial perspective, and the impacts of different LULC conversions on ESs remain unclear. This study established a framework for distinguishing the relative spatial contributions of climate and LULC change to water yield, net primary productivity (NPP) and soil retention and applied it to Zhejiang Province. The results showed that all ESs showed an increasing trend from 2000 to 2020. Changes in water yield and soil retention were dominated by climate change, accounting for 75.22% and 77.69% of the total study area, respectively, while the changes in NPP were dominated by LULC changes, accounting for 82.70% of the total study area. We further quantified the impact of three major forms of LULC changes (urbanization, deforestation, and afforestation) on ESs in their respective regions. Deforestation and urbanization reduced NPP by 192 gC/m2 and 115.75 gC/m2, respectively, while afforestation increased NPP by 220.10 gC/m2. Afforestation reduced the water yield by 84.27%, while deforestation and urbanization increased it by 37.94% and 62.42%, respectively. Deforestation reduced soil retention by 38.28%, while urbanization and afforestation increased it by 3.91% and 63.28%, respectively. Five suggestions for improving ES management were proposed based on our results. This study can provide a detailed reference for decision-makers seeking sustainable ecosystem management strategies.
is widely used in traditional Chinese medicine, which contains many kinds of active ingredients. In recent years, many
transcriptomes have been sequenced. Hence, weighted gene co-expression network ...analysis (WGCNA) was used with the gene expression profiles of active ingredients to identify the modules and genes that may associate with particular species and tissues. Three kinds of Dendrobium species and three tissues were sampled for RNA-seq to generate a high-quality, full-length transcriptome database. Based on significant changes in gene expression, we constructed co-expression networks and revealed 19 gene modules. Among them, four modules with properties correlating to active ingredients regulation and biosynthesis, and several hub genes were selected for further functional investigation. This is the first time the WGCNA method has been used to analyze
transcriptome data. Further excavation of the gene module information will help us to further study the role and significance of key genes, key signaling pathways, and regulatory mechanisms between genes on the occurrence and development of medicinal components of
.
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