Dynamic Diurnal Changes in Green Algae Biomass in the Southern Yellow Sea Based on GOCI Images

Macroalgae blooms of Ulva prolifera have occurred every summer in the southern Yellow Sea since 2007,inducing severe ecological problems and huge economic losses.Genesis and secular movement of green algae blooms have been well monitored by using remote sensing and other methods.In this study,green algae were detected and traced by using Geostationary Ocean Color Imager(GOCI),and a novel biomass estimation model was developed from the relationship between biomass measurements and previously published satellite-derived biomass indexes.The results show that the green algae biomass can be determined most accurately with the biomass index of green algae for GOCI(BIGAG),which is calculated from the Rsurf data that had been atmospherically corrected by ENVI/QUAC method.For the first time,dynamic changes in green algae biomass were studied over an hourly scale.Short-term biomass changes were highly influenced by Photosynthetically Available Radiation(PAR)and tidal phases,but less by sea surface temperature variations on a daily timescale.A new parameter of biomass changes(PBC),calculated by the ratio of the biomass growth rate to movement velocity,could provide an effective way to assess and forecast green tide in the southern Yellow Sea and similar areas.

Spatial impacts of climate factors on regional agricultural and forestry biomass resources in north-eastern province of China

The dynamics of agricultural and forestry biomass are highly sensitive to climate change, particularly in high latitude regions. Heilongjiang Province was selected as research area in North-east China. We explored the trend of regional climate warming and distribution feature of biomass resources, and then analyzed on the spatial relationship between climate factors and biomass resources. Net primary productivity （NPP） is one of the key indicators of vegetation productivity, and was simulated as base data to calculate the distribution of agricultural and forestry biomass. The results show that temperatures rose by up to 0.37℃/10a from 1961 to 2013. Spatially, the variation of agricultural biomass per unit area changed from -1.93 to 5.85 t.km^-2.a^-1 during 2000,2013. More than 85% of farmland areas showed a positive relationship be.tween agricultural biomass and precipitation. The results suggest that precipitation exerts an overwhelming climate influence on agricultural biomass. The mean density of forestry biomass varied from 10 to 30 t·km^-2. Temperature had a significant negative effect on forestry biomass in Lesser Khingan and northern Changbai Mountain, because increased temperature leads to decreased Rubisco activity and increased respiration in these areas. Precipitation had a significant positive relationship with forestry biomass in south-western Changbai Mountain, because this area had a wanner climate and stress from insufficient precipitation may induce xylem cavitation. Understanding the effects of climate factors on regional biomass resources is of great significance in improving environmental management and promoting sustainable development of further biomass resource use.