Rapid Invasion of Spartina Alterniflora in the Coastal Zone of Mainland China: Spatiotemporal Patterns and Human Prevention

Given the extensive spread and ecological consequences of exotic Spartina alterniflora (S. alterniflora) over the coast of mainland China, monitoring its spatiotemporal invasion patterns is important for the sake of coastal ecosystem management and ecological security. In this study, Landsat series images from 1990 to 2015 were used to establish multi-temporal datasets for documenting the temporal dynamics of S. alterniflora invasion. Our observations revealed that S. alterniflora had a continuous expansion with the area increasing by 50,204 ha during the considered 25 years. The largest expansion was identified in Jiangsu Province during the period of 1990-2000, and in Zhejiang Province during the periods 2000-2010 and 2010-2015. Three noticeable hotspots for S. alterniflora invasion were Yancheng of Jiangsu, Chongming of Shanghai, and Ningbo of Zhejiang, and each had a net area increase larger than 5000 ha. Moreover, an obvious shrinkage of S. alterniflora was identified in three coastal cities including the city of Cangzhou of Hebei, Dongguan, and Jiangmen of Guangdong. S. alterniflora invaded mostly into mudflats (>93%) and shrank primarily due to aquaculture (55.5%). This study sheds light on the historical spatial patterns in S. alterniflora distribution and thus is helpful for understanding its invasion mechanism and invasive species management

Mapping Forest Cover in Northeast China from Chinese HJ-1 Satellite Data Using an Object-Based Algorithm

Forest plays a significant role in the global carbon budget and ecological processes. The precise mapping of forest cover can help significantly reduce uncertainties in the estimation of terrestrial carbon balance. A reliable and operational method is necessary for a rapid regional forest mapping. In this study, the goal relies on mapping forest and subcategories in Northeast China through the use of high spatio-temporal resolution HJ-1 imagery and time series vegetation indices within the context of an object-based image analysis and decision tree classification. Multi-temporal HJ-1 images obtained in a single year provide an opportunity to acquire phenology information. By analyzing the difference of spectral and phenology information between forest and non-forest, forest subcategories, decision trees using threshold values were finally proposed. The resultant forest map has a high overall accuracy of 0.91 ± 0.01 with a 95% confidence interval, based on the validation using ground truth data from field surveys. The forest map extracted from HJ-1 imagery was compared with two existing global land cover datasets: GlobCover 2009 and MCD12Q1 2009. The HJ-1-based forest area is larger than that of MCD12Q1 and GlobCover and more closely resembles the national statistics data on forest area, which accounts for more than 40% of the total area of the Northeast China. The spatial disagreement primarily occurs in the northern part of the Daxing'an Mountains, Sanjiang Plain and the southwestern part of the Songliao Plain. The compared result also indicated that the forest subcategories information from global land cover products may introduce large uncertainties for ecological modeling and these should be cautiously used in various ecological models. Given the higher spatial and temporal resolution, HJ-1-based forest products could be very useful as input to biogeochemical models (particularly carbon cycle models) that require accurate and updated estimates of forest area and type

Mapping Spatial Variations of Structure and Function Parameters for Forest Condition Assessment of the Changbai Mountain National Nature Reserve

Forest condition is the baseline information for ecological evaluation and management. The National Forest Inventory of China contains structural parameters, such as canopy closure, stand density and forest age, and functional parameters, such as stand volume and soil fertility. Conventionally forest conditions are assessed through parameters collected from field observations, which could be costly and spatially limited. It is crucial to develop modeling approaches in mapping forest assessment parameters from satellite remote sensing. This study mapped structure and function parameters for forest condition assessment in the Changbai Mountain National Nature Reserve (CMNNR). The mapping algorithms, including statistical regression, random forests, and random forest kriging, were employed with predictors from Advanced Land Observing Satellite (ALOS)-2, Sentinel-1, Sentinel-2 satellite sensors, digital surface model of ALOS, and 1803 field sampled forest plots. Combined predicted parameters and weights from principal component analysis, forest conditions were assessed. The models explained spatial dynamics and characteristics of forest parameters based on an independent validation with all r values above 0.75. The root mean square error (RMSE) values of canopy closure, stand density, stand volume, forest age and soil fertility were 4.6%, 33.8%, 29.4%, 20.5%, and 14.3%, respectively. The mean assessment score suggested that forest conditions in the CMNNR are mainly resulted from spatial variations of function parameters such as stand volume and soil fertility. This study provides a methodology on forest condition assessment at regional scales, as well as the up-to-date information for the forest ecosystem in the CMNNR

Monitoring the Invasion of Spartina alterniflora Using Multi-source High-resolution Imagery in the Zhangjiang Estuary, China

Spartina alterniflora (S. alterniflora) is one of the most harmful invasive plants in China. Google Earth (GE), as a free software, hosts high-resolution imagery for many areas of the world. To explore the use of GE imagery for monitoring S. alterniflora invasion and developing an understanding of the invasion process of S. alterniflora in the Zhangjiang Estuary, the object-oriented method and visual interpretation were applied to GE, SPOT-5, and Gaofen-1 (GF-1) images. In addition, landscape metrics of S. alterniflora patches adjacent to mangrove forests were calculated and mangrove gaps were recorded by checking whether S. alterniflora exists. The results showed that from 2003–2015, the areal extent of S. alterniflora in the Zhangjiang Estuary increased from 57.94 ha to 116.11 ha, which was mainly converted from mudflats and moved seaward significantly. Analyses of the S. alterniflora expansion patterns in the six subzones indicated that the expansion trends varied with different environmental circumstances and human activities. Land reclamation, mangrove replantation, and mudflat aquaculture caused significant losses of S. alterniflora. The number of invaded gaps increased and S. alterniflora patches adjacent to mangrove forests became much larger and more aggregated during 2003–2015 (the class area increased from 12.13 ha to 49.76 ha and the aggregation index increased from 91.15 to 94.65). We thus concluded that S. alterniflora invasion in the Zhangjiang Estuary had seriously increased and that measures should be taken considering the characteristics shown in different subzones. This study provides an example of applying GE imagery to monitor invasive plants and illustrates that this approach can aid in the development of governmental policies employed to control S. alterniflora invasion. View Full-Tex

Rapid Invasion of Spartina alterniflora in the Coastal Zone of Mainland China: New Observations from Landsat OLI Images

Plant invasion imposes significant threats to biodiversity and ecosystem function. Thus, monitoring the spatial pattern of invasive plants is vital for effective ecosystem management. Spartina alterniflora (S. alterniflora) has been one of the most prevalent invasive plants along the China coast, and its spread has had severe ecological consequences. Here, we provide new observation from Landsat operational land imager (OLI) images. Specifically, 43 Landsat-8 OLI images from 2014 to 2016, a combination of object-based image analysis (OBIA) and support vector machine (SVM) methods, and field surveys covering the whole coast were used to construct an up-to-date dataset for 2015 and investigate the spatial variability of S. alterniflora in the coastal zone of mainland China. The classification results achieved good estimation, with a kappa coefficient of 0.86 and 96% overall accuracy. Our results revealed that there was approximately 545.80 km2 of S. alterniflora distributed in the coastal zone of mainland China in 2015, from Hebei to Guangxi provinces. Nearly 92% of the total area of S. alterniflora was distributed within four provinces: Jiangsu, Shanghai, Zhejiang, and Fujian. Seven national nature reserves invaded by S. alterniflora encompassed approximately one-third (174.35 km2) of the total area of S. alterniflora over mainland China. The Yancheng National Nature Reserve exhibited the largest area of S. alterniflora (115.62 km2) among the reserves. Given the rapid and extensive expansion of S. alterniflora in the 40 years since its introduction and its various ecological effects, geospatially varied responding decisions are needed to promote sustainable coastal ecosystems

Large Ecosystem Service Benefits of Assisted Natural Regeneration

China manages the largest monoculture plantations in the world, with 24% being Chinese fir plantations. Maximizing the ecosystem services of Chinese fir plantations has important implications in global carbon cycle and biodiversity protection. Assisted natural regeneration (ANR) is a practice to convert degraded lands into more productive forests with great ecosystems services. However, the quantitative understanding of ANR ecosystem service benefits is very limited. We conducted a comprehensive field manipulation experiment to evaluate the ANR potentials. We quantified and compared key ecosystem services including surface runoff, sediment yield, dissolved organic carbon export, plant diversity, and aboveground carbon accumulation of ANR of secondary forests dominated by Castanopsis carlesii to that of Chinese fir and C. carlesii plantations. Our results showed that ANR of C. carlesii forest reduced surface runoff and sediment yield up to 50% compared with other young plantations in the first 3 years and substantially increased plant diversity. ANR also reduced the export of dissolved organic carbon by 60–90% in the first 2 years. Aboveground biomass of the young ANR forest was approximately 3–4 times of that of other young plantations, while aboveground biomass of mature ANR forests was approximately 1.4 times of that of mature Chinese fir plantations of the same age. If all Chinese fir plantations in China were replaced by ANR forests, potentially 0.7 Pg more carbon will be stored in aboveground in one rotation (25 years). The results indicate that ANR triggers positive feedbacks among soil and water conservation, biodiversity protection, and biomass accumulation and thereby enhances ecosystem services

Spatial Expansion and Soil Organic Carbon Storage Changes of Croplands in the Sanjiang Plain, China

Soil is the largest pool of terrestrial organic carbon in the biosphere and interacts strongly with the atmosphere, climate and land cover. Remote sensing (RS) and geographic information systems (GIS) were used to study the spatio-temporal dynamics of croplands and soil organic carbon density (SOCD) in the Sanjiang Plain, to estimate soil organic carbon (SOC) storage. Results show that croplands increased with 10,600.68 km2 from 1992 to 2012 in the Sanjiang Plain. Area of 13,959.43 km2 of dry farmlands were converted into paddy fields. Cropland SOC storage is estimated to be 1.29 ± 0.27 Pg C (1 Pg = 103 Tg = 1015 g) in 2012. Although the mean value of SOCD for croplands decreased from 1992 to 2012, the SOC storage of croplands in the top 1 m in the Sanjiang Plain increased by 70 Tg C (1220 to 1290). This is attributed to the area increases of cropland. The SOCD of paddy fields was higher and decreased more slowly than that of dry farmlands from 1992 to 2012. Conversion between dry farmlands and paddy fields and the agricultural reclamation from natural land-use types significantly affect the spatio-temporal patterns of cropland SOCD in the Sanjiang Plain. Regions with higher and lower SOCD values move northeast and westward, respectively, which is almost consistent with the movement direction of centroids for paddy fields and dry farmlands in the study area. Therefore, these results were verified. SOC storages in dry farmlands decreased by 17.5 Tg·year−1 from 1992 to 2012, whilst paddy fields increased by 21.0 Tg·C·year−1

Impacts of climate change on Tibetan lakes: patterns and processes

High-altitude inland-drainage lakes on the Tibetan Plateau (TP), the earth’s third pole, are very sensitive to climate change. Tibetan lakes are important natural resources with important religious, historical, and cultural significance. However, the spatial patterns and processes controlling the impacts of climate and associated changes on Tibetan lakes are largely unknown. This study used long time series and multi-temporal Landsat imagery to map the patterns of Tibetan lakes and glaciers in 1977, 1990, 2000, and 2014, and further to assess the spatiotemporal changes of lakes and glaciers in 17 TP watersheds between 1977 and 2014. Spatially variable changes in lake and glacier area as well as climatic factors were analyzed. We identified four modes of lake change in response to climate and associated changes. Lake expansion was predominantly attributed to increased precipitation and glacier melting, whereas lake shrinkage was a main consequence of a drier climate or permafrost degradation. These findings shed new light on the impacts of recent environmental changes on Tibetan lakes. They suggest that protecting these high-altitude lakes in the face of further environmental change will require spatially variable policies and management measures