It is of great significance to understand the extent and distribution of bamboo for its valuable ecological services and economic benefits. However, it is challenging to map bamboo using remote ...sensing images over a large area because of the similarity between bamboo and other vegetation types, the availability of clear optical images, huge workload of image processing, and sample collection. In this study, we use the Landsat 8 times series images archive to map bamboo forests in China via the Google Earth engine. Several spectral indices were calculated and used as classification features, including the normalized difference vegetation index (NDVI), the normalized difference moisture index (NDMI) and textural features of the gray-level co-occurrence matrix (GLCM). We found that the bamboo forest covered an area of 709.92 × 104 hectares, with the provinces of Fujian, Jiangxi, and Zhejiang containing the largest area concentrations. The bamboo forest map was accurate and reliable with an average producer’s accuracy of 89.97%, user’s accuracy of 78.45% and kappa coefficient of 0.7789. In addition, bamboo was mainly distributed in forests with an elevation of 300–1200 m above sea level, average annual precipitation of 1200–1500 mm and average day land surface temperature of 19–25 °C. The NDMI is particularly useful in differentiating bamboo from other vegetation because of the clear difference in canopy moisture content, whilst NDVI and elevation are also helpful to improve the bamboo classification accuracy. The bamboo forest map will be helpful for bamboo forest industry planning and could be used for evaluating the ecological service of the bamboo forest.
To study the fluvial interaction between Changjiang River and Poyang Lake, we analyze the observed changes of riverine flux of the mid-upstream of Changjiang River catchment, the five river systems ...of Poyang Lake and Poyang Lake basin. Inter-annual and seasonal variations of the water discharge and sediment exchange processes between Changjiang River and Poyang Lake are systematically explored to determine the influence of climate change as well as human impact (especially the Three Gorges Dam (TGD)). Results indicate that climate variation for the Changjiang catchment and Poyang Lake watershed is the main factor determining the changes of water exchanges between Changjiang River and Poyang Lake. However, human activities (including the emplacement of the TGD) accelerated this rate of change. Relative to previous years (1956–1989), the water discharge outflow from Poyang Lake during the dry season towards the Changjiang catchment increased by 8.98km3y−1 during 2003–2010. Evidently, the water discharge flowing into Poyang Lake during late April–late May decreased. As a consequence, water storage of Poyang Lake significantly reduced during late April–late May, resulting in frequent spring droughts after 2003. The freshwater flux of Changjiang River towards Poyang Lake is less during the flood season as well, significantly lowering the magnitude and frequency of the backflow of the Changjiang River during 2003–2010. Human activities, especially the emplacement and operation of the TGD and sand mining at Poyang Lake impose a major impact on the variation of sediment exchange between Changjiang main river and Poyang Lake. On average, sediments from Changjiang River deposited in Poyang Lake before 2000. After 2000, Changjiang River no longer supplied sediment to Poyang Lake. As a consequence, the sediment load of Changjiang River entering the sea increasingly exists of sediments from Lake Poyang during 2003–2010. As a result, Poyang Lake converted from a depositional to an erosional system, with a gross sediment loss of 120.19Mty−1 during 2001–2010, including sand mining.
•The river–lake interaction greatly changed after 2003.•Climate change exerted greater influence on water exchange between river and lake.•Human activities imposed more impact on sediment exchange between river and lake.•The forcing of Changjiang River on Poyang Lake significantly weakened after 2003.•The sediment contribution of Lake Poyang to Changjiang River greatly increased.
Remote sensing-based analyses of vegetation function such as photosynthesis and productivity are challenging in wetlands with complex cover and difficult field access. Recent advances in object-based ...image analysis (OBIA) and machine-learning algorithms offer new image classification tools; however, few comparisons of different approaches have been discussed to date. We applied OBIA to delineate wetland plant functional types (PFTs) for Poyang Lake, the largest freshwater lake in China and Ramsar wetland conservation site, from a spring 2008 Landsat TM image. We targeted major PFTs that represent dominant vegetation groups along wetland inundation gradients and affect ecosystem biogeochemical cycles and ecological habitats. Classification results were compared among: a) several “small” object segmentation scales (with average object sizes 1350–9000m2); b) algorithms from six families of statistical machine-learning classifiers (Bayesian, Logistic, Neural Network, Decision Trees, K-Nearest Neighbors and Support Vector Machines) and c) two hierarchical levels of vegetation classification, a generalized 3-class set and a more specific 6-class set. We also examined the response of classification accuracy to four basic object-level texture metrics. The highest accuracies (>85–90%) and best agreement among algorithms occurred at coarser object scales rather than close-to-pixel scales. No single machine-learning algorithm was consistently superior at all scales, although support vector machine, k-nearest neighbor and artificial neural network most frequently provided the highest overall and PFT-specific accuracies. Including texture metrics had both positive and negative low-magnitude effects on classification accuracy that were not consistent among scale values, algorithms or PFT classes. Individual PFTs differed in scales at which they were best discriminated from others, reflecting their unique landscape positions, ecology of dominant species and disturbance agents. There was a 29–35% disagreement between mapped areas of generalized PFTs and their respective subclasses, suggesting potential mismatches between the ecological classification scheme and PFT landscape patch structure, and raising concern on error propagation in multi-scale classifications. We conclude that OBIA with machine-learning classifiers is useful for landscape vegetation analyses, however, considerations of spatial scale and image segmentation outcomes are critical in mapping PFTs and should be more thoroughly investigated in future work.
► We used object-based image analysis to map wetland plant functional types (PFTs). ► Highest classification accuracy occurred at object scales coarser than pixel level. ► Classes differed in segmentation scales which maximized their individual accuracy. ► Success of several machine-learning classifiers varied among PFTs and object scales. ► Mismatches among mapped PFT levels suggest error propagation in multi-scale OBIA.
The net sediment flux in Poyang Lake, the largest freshwater lake in China, converted from positive to negative after 2000. Whether the effect of the Three Gorges Dam (TGD) or sand mining caused this ...change was disputed. We analyzed the trend of sediment input and output in Poyang Lake from 1956 to 2014, determined the annual numbers of sand dredgers by interpreting Landsat ETM + images, and calculated the changes to the annual net sediment flux (Sediment
diff
) after 2000. The decreased sediment input was mainly caused by decreased sediment concentrations in the five tributaries. The increased sediment output was caused by increased sediment concentrations, which was not related to the operation of the TGD, but strongly related to sand mining activities in the northern parts of the lake. The Sediment
diff
variation in different operational periods of the TGD showed that the TGD was not the main driver of the change to the net sediment flux trend in Poyang Lake. The strong positive correlation between the number of sand dredgers and Sediment
diff
indicated that sand mining activities in the northern parts of the lake were important drivers of the changes in the net sediment flux trend in Poyang Lake after 2000. It was sand mining activities, rather than the TGD, that altered the trend of the net sediment flux in Poyang Lake after 2000.
The thermal conductivity of boron nitride (BN) particulates reinforced high density polyethylene (HDPE) composites was investigated under a special dispersion state of BN particles in HDPE,
i.e., BN ...particles surrounding HDPE particles. The effects of BN content, particle size of HDPE and temperature on the thermal conductivity of the composites were discussed. The results indicate that the special dispersion of BN in matrix provides the composites with high thermal conductivity; moreover, the thermal conductivity of composites is higher for the larger size HDPE than for the smaller size one. The thermal conductivity increases with increasing filler content, and significantly deviates the predictions from the theoretic models. It is found also that the combined use of BN particles and alumina short fiber obtains higher thermal conductivity of composites compared to the BN particles used alone.
•We developed a spatiotemporal integration scheme for citrus planting dynamics monitoring.•A two-stage change pattern was revealed in Southeastern China between 1986 and 2018.•Agents and consequences ...of citrus planting dynamics were analyzed.
Across Southeastern China, the expansion of citrus plantation has underpinned substantial economic development at the expense of forest cover and associated ecosystem services. The high-order complexity of citrus planting dynamics requires more detailed observations. To achieve this goal, we developed a novel monitoring scheme by integrating multi-epoch land cover classification and continuous change detection on the Google Earth Engine (GEE) platform using all available Landsat archives (1986–2018). First, a stable/changed area masking approach was adopted. Then, the GEE-based Continuous Change Detection and Classification (GEE-CCDC) algorithm was applied to detect the timing and position of citrus planting-related land cover changes. Finally, the effectiveness of the scheme was validated both spatially and temporally. We applied the proposed scheme in Xunwu, a typical County in Southeastern China where continuous expansion was disrupted by an outbreak of Huanglongbing (HLB, a destructive citrus disease). The validation results indicate that the multi-epoch classification effectively identified the stable, abandoned, and newly cultivated areas related to citrus planting. Within these areas, our monitoring of citrus planting dynamics had an overall temporal accuracy of 90.59% and a mean detection date deviation of −13.21 days (leading). Based on the change detection results, we found a two-stage change pattern, namely a continuous expansion period (1986–2016) followed by a disturbance period (2017–2018). Moreover, almost half of the orchards were cultivated in regions with an elevation and slope of 301–400 m and 11–20°. During the continuous expansion period, a total of 497.85 km2 natural lands were converted for citrus planting. Affected by the HLB outbreak, both orchard abandonment (114.66 km2) and new orchard cultivation (36.87 km2) were detected during the disturbance period. The proposed scheme offers a useful tool for cash crops management, and highlights the value of dense satellite data in monitoring the extent of ongoing human appropriation of natural ecosystems at a large scale and long-term.
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•We proposed a framework integrating SSP-RCP scenarios, PLUS model and InVEST model.•The trends of land use and WESs under the three future SSP-RCP scenarios were different.•It was ...found that LUC was not the main influencing factor for the change of WESs in the PYLB.
A scientific understanding of the trends of water-related ecosystem services (WESs) under different scenarios is crucial to improving WESs and maintaining ecological security. However, there is a lack of high-resolution land use simulation and assessment of WESs under the SSP-RCP scenarios, and the impacts of different land-use change (LUC) on WESs are not clear. This study focused on the Poyang Lake Basin (PYLB), utilizing the SSP-RCP scenarios, the PLUS model and the InVEST model to explore the dynamic changes of land use and WESs historically and in the future, and to reveal the impacts of specific LUC on WESs from 2000 to 2020. The results demonstrated that: (1) The forest land increased under both SSP1-2.6 and SSP2-4.5 scenarios but increased first and then decreased under SSP5-8.5 scenarios; Cropland increased significantly under SSP5-8.5 scenarios, and the construction land showed an expansion trend under the three scenarios. (2) From 2000 to 2020, only the water purification capacity decreased, while the rest of the WESs increased. Under the SSP1-2.6 scenario, the overall benefits of the WESs in the PYLB were the highest. (3) Between 2000 and 2020, deforestation in the PYLB brought about the greatest increase in the water yield (+9.06 × 108 m3). The increase in the construction land brought about the most water conservation loss (−18.19 × 108 m3). Additionally, the forest expansion and cropland reduction brought about the largest increase in soil retention (+3.94 × 105 t and +4.79 × 105 t) and enhanced water purification, and the opposite was true for deforestation. The conclusions can provide an important basis for the ecological protection and high-quality development of the PYLB.
The Poyang Lake wetland in China is the largest wintering destination for Siberian cranes worldwide. Understanding the spatiotemporal characteristics of crane habitats is of great importance for ...ecological environment governance and biodiversity protection. The shallow water, grassland, and soft mudflat regions of the Poyang Lake wetland are ideal habitats for wintering Siberian cranes. Based on Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI) remote sensing images, habitat areas were extracted and associated with various water levels taken on multiple dates. Landscape metrics were applied to describe the spatial structural characteristics of the crane habitats, and spatial statistics are used to explore the cold and hot spots of their distribution. Moreover, three indicators including sustainability, stability, and variety were applied to evaluate the vulnerability of the crane habitats under different hydrological conditions. Our findings indicate: (a) The main crane habitats exhibit a gradual decreasing degree of fragmentation in time, an obvious uncertainty of shape complexity and a relatively stable connectivity. (b) The crane habitats have a consistent spatial pattern of highly aggregated distributions associated with various water levels. (c) The hot spots of the habitats formed multiple “sheet” belts centered on the “Lake Enclosed in Autumn” regions, while the cold spots indicate a spatial pattern of axial distributions. (d) The majority of the hot spots of the habitats were distributed in sub-lakes found in the southeast part of the Poyang Lake watershed and the Nanjishan and Wucheng nature reserves, while the cold spots were mainly distributed in the main channels of the basins of Poyang Lake. (e) The sustainable habitats were mainly distributed in the “Lake Enclosed in Autumn” regions and intensively aggregated in two national nature reserves. (f) Under conditions of extremely low to average water levels (5.3–11.46 m), an increase of water level causes a decrease of the stability and variety of the crane habitats and weakens the aggregation structure.
Cyclopiamides B–J (1–9), nine new oxindole alkaloids were isolated from the deep-sea-derived fungus Penicllium commune DFFSCS026. Their structures were elucidated by extensive spectroscopic data ...analysis. Compound 4 contains a rare 2H-pyrrole2,1-bpyridine unit, and compounds 8 and 9 are complex polycyclic and polyhydroxy alkaloids. The absolute configurations of 6 and 8 were established by molecular mechanics calculation, quantum chemical computations, and single crystal X-ray diffraction analysis, respectively.
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