A Global Crisis for Seagrass Ecosystems

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.

Impact of cloudiness on net ecosystem exchange of carbon dioxide in different types of forest ecosystems in China

Asia 3 Foresight Program [30721140307]; National Key Research and Development Program [2010CB833500]; National Natural Science Foundation of China [30590381, 30900198];

Environmental controls over carbon exchange of three forest ecosystems in eastern China

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

Monitoring and simulation of water, heat,and CO2 fluxes in terrestrial ecosystems based on the APEIS-FLUX system

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.

Effects of vegetation control on ecosystem water use efficiency within and among four grassland ecosystems in China

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.

Net primary productivity and spatial distribution of vegetation in an alpine wetland, Qinghai-Tibetan Plateau

To initially describe vegetation structure and spatial variation in plant biomass in a typical alpine wetland of the Qinghai-Tibetan Plateau, net primary productivity and vegetation in relationship to environmental factors were investigated. In 2002, the wetland remained flooded to an average water depth of 25 cm during the growing season, from July to mid-September. We mapped the floodline and vegetation distribution using GPS (global positioning system). Coverage of vegetation in the wetland was 100%, and the vegetation was zonally distributed along a water depth gradient, with three emergent plant zones (Hippuris vulgaris-dominated zone, Scirpus distigmaticus-dominated zone, and Carex allivescers-dominated zone) and one submerged plant zone (Potamogeton pectinatus-dominated zone). Both aboveground and belowground biomass varied temporally within and among the vegetation zones. Further, net primary productivity (NPP) as estimated by peak biomass also differed among the vegetation zones; aboveground NPP was highest in the Carex-dominated zone with shallowest water and lowest in the Potamogeton zone with deepest water. The area occupied by each zone was 73.5% for P. pectinatus, 2.6% for H. vulgaris, 20.5% for S. distigmaticus, and 3.4% for C. allivescers. Morphological features in relationship to gas-transport efficiency of the aerial part differed among the emergent plants. Of the three emergent plants, H. vulgaris, which dominated in the deeper water, showed greater morphological adaptability to deep water than the other two emergent plants.

Modeling gross primary production of alpine ecosystems in the Tibetan Plateau using MODIS images and climate data

The eddy covariance technique provides measurements of net ecosystem exchange (NEE) Of CO2 between the atmosphere and terrestrial ecosystems, which is widely used to estimate ecosystem respiration and gross primary production (GPP) at a number Of CO2 eddy flux tower sites. In this paper, canopy-level maximum light use efficiency, a key parameter in the satellite-based Vegetation Photosynthesis Model (VPM), was estimated by using the observed CO2 flux data and photosynthetically active radiation (PAR) data from eddy flux tower sites in an alpine swamp ecosystem, an alpine shrub ecosystem and an alpine meadow ecosystem in Qinghai-Tibetan Plateau, China. The VPM model uses two improved vegetation indices (Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI)) derived from the Moderate Resolution Imaging Spectral radiometer (MODIS) data and climate data at the flux tower sites, and estimated the seasonal dynamics of GPP of the three alpine grassland ecosystems in Qinghai-Tibetan Plateau. The seasonal dynamics of GPP predicted by the VPM model agreed well with estimated GPP from eddy flux towers. These results demonstrated the potential of the satellite-driven VPM model for scaling-up GPP of alpine grassland ecosystems, a key component for the study of the carbon cycle at regional and global scales. (c) 2006 Elsevier Inc. All rights reserved.