34 resultados para Ecosystems.
Resumo:
Horizontal spatial patterns of chlorophyll a in Meiziya Reservoir, Hubei Province, China were analyzed once each month during May, June and July 1997. Two geostatistical techniques, semivariance and fractal analysis, were used to determine variation in chlorophyll a over the whole study area (isotropic) and in different directions (anisotropic). Both techniques provided useful information for detecting and assessing spatial pattern changes of chlorophyll a in freshwater environments. Based on our case study, the distribution of chlorophyll a shifted from aggregated to random distribution in the case of small rainfall event, and then returned to the aggregated distribution after a large rainfall event. On the other hand, the distribution of chlorophyll a became more heterogeneous or random in the direction of water flow (S-N direction) when rainfall events occurred, which was enhanced by rainfall intensity. In contrast, the influence of water flow on the spatial patterns was weak in the E-W direction, and thus the distribution of chlorophyll a remained aggregate with a moderate spatial heterogeneity.
Resumo:
Seagrasses, marine flowering plants, have a long evolutionary history but are now challenged with rapid environmental changes as a result of coastal human population pressures. Seagrasses provide key ecological services, including organic carbon production and export, nutrient cycling, sediment stabilization, enhanced biodiversity, and trophic transfers to adjacent habitats in tropical and temperate regions. They also serve as “coastal canaries,” global biological sentinels of increasing anthropogenic influences in coastal ecosystems, with large-scale losses reported worldwide. Multiple stressors, including sediment and nutrient runoff, physical disturbance, invasive species, disease, commercial fishing practices, aquaculture, overgrazing, algal blooms, and global warming, cause seagrass declines at scales of square meters to hundreds of square kilometers. Reported seagrass losses have led to increased awareness of the need for seagrass protection, monitoring, management, and restoration. However, seagrass science, which has rapidly grown, is disconnected from public awareness of seagrasses, which has lagged behind awareness of other coastal ecosystems. There is a critical need for a targeted global conservation effort that includes a reduction of watershed nutrient and sediment inputs to seagrass habitats and a targeted educational program informing regulators and the public of the value of seagrass meadows.
Resumo:
Asia 3 Foresight Program [30721140307]; National Key Research and Development Program [2010CB833500]; National Natural Science Foundation of China [30590381, 30900198];
Resumo:
National Natural Science Foundation of China [30590381, 30670384]; Knowledge Innovation Project of the Chinese Academy of Sciences [KZCX2-YW-432]; National Key Research and Development Program [2002CB412501]; 'Hundred Talents' Program of the Chinese Acade
Resumo:
The Integrated Environmental Monitoring (IEM) project, part of the Asia-Pacific Environmental Innovation Strategy (APEIS) project, developed an integrated environmental monitoring system that can be used to detect, monitor, and assess environmental disasters, degradation, and their impacts in the Asia-Pacific region. The system primarily employs data from the moderate resolution imaging spectrometer (MODIS) sensor on the Earth Observation System- (EOS-) Terra/Aqua satellite,as well as those from ground observations at five sites in different ecological systems in China. From the preliminary data analysis on both annual and daily variations of water, heat and CO2 fluxes, we can confirm that this system basically has been working well. The results show that both latent flux and CO2 flux are much greater in the crop field than those in the grassland and the saline desert, whereas the sensible heat flux shows the opposite trend. Different data products from MODIS have very different correspondence, e.g. MODIS-derived land surface temperature has a close correlation with measured ones, but LAI and NPP are quite different from ground measurements, which suggests that the algorithms used to process MODIS data need to be revised by using the local dataset. We are now using the APEIS-FLUX data to develop an integrated model, which can simulate the regional water,heat, and carbon fluxes. Finally, we are expected to use this model to develop more precise high-order MODIS products in Asia-Pacific region.
Resumo:
Through 2-3-year (2003-2005) continuous eddy covariance measurements of carbon dioxide and water vapor fluxes, we examined the seasonal, inter-annual, and inter-ecosystem variations in the ecosystem-level water use efficiency (WUE, defined as the ratio of gross primary production, GPP, to evapotranspiration, ET) at four Chinese grassland ecosystems in the Qinghai-Tibet Plateau and North China. Representing the most prevalent grassland types in China, the four ecosystems are an alpine swamp meadow ecosystem, an alpine shrub-meadow ecosystem, an alpine meadow-steppe ecosystem, and a temperate steppe ecosystem, which illustrate a water availability gradient and thus provide us an opportunity to quantify environmental and biological controls on ecosystem WUE at different spatiotemporal scales. Seasonally, WUE tracked closely with GPP at the four ecosystems, being low at the beginning and the end of the growing seasons and high during the active periods of plant growth. Such consistent correspondence between WUE and GPP suggested that photosynthetic processes were the dominant regulator of the seasonal variations in WUE. Further investigation indicated that the regulations were mainly due to the effect of leaf area index (LAI) on carbon assimilation and on the ratio of transpiration to ET (T/ET). Besides, except for the swamp meadow, LAI also controlled the year-to-year and site-to-site variations in WUE in the same way, resulting in the years or sites with high productivity being accompanied by high WUE. The general good correlation between LAI and ecosystem WUE indicates that it may be possible to predict grassland ecosystem WUE simply with LAI. Our results also imply that climate change-induced shifts in vegetation structure, and consequently LAI may have a significant impact on the relationship between ecosystem carbon and water cycles in grasslands.