Estimation Of Primary Productivity Of Phytoplankton In Shallow Lake By Remote Sensing

Abstract:Phytoplankton is at the bottom of the food chain,creating fresh organic matter from inorganic nutrients,carbon dioxide and energy from sunlight,which strongly influence nutrient concentrations and support higher trophic levels such as zooplankton and filter feeder.When either system is employed,phytoplankton create organic matter from inorganic compounds and carbon dioxide,which is called phytoplankton primary production.The rate of phytoplankton primary production is a fundamental property of aquatic system and measurements of primary production are critical to our understanding of the carbon cycle.One of the major goals of modern biological oceanography is to acquire a better understanding of primary production in various oceanic provinces,with a special emphasis on marine carbon cycling and climate change on regional to global scales.As an important part of the global carbon cycle,estimating the primary production in lakes is also the major goals of modern limnology,and important for us to understand the regional ecological environment.Actually,lake primary production,which is commonly regarded as the photosynthetic capacity of Lake Phytoplankton for the unit volume,is an important parameter to describe Lake Ecosystem and environmental characteristics.Traditionally,the primary production of an aquatic environment was obtained from cruise samples.While in situ experiments provided accurate estimates of primary production in small volumes of water,they may not be easily extrapolated to lake-wide estimates.Moreover,these experiments provide an integrated measure of production that is dependent on many variables(e.g.phytoplankton biomass,light,temperature,etc.),thus limiting their predictive value.Early ways to estimate primary production for the great lakes may be biased because of deficiencies in traditional collection and incubation techniques.Satellite data have been widely used to derive several lake biogeochemical parameters,such as,total suspended matter,chlorophyll a(Chla),and diffuse attenuation coefficient of photosynthetically active radiation(Kd(PAR)).Satellite remote sensing has many advantages in estimation of lake biogeochemical parameters.The repeated coverage by remote sensing enables the detection of the temporal and spatial variation,which has proven beneficial for rapidly estimating lake biogeochemical parameters.Additionally,satellite remote sensing is more practical and economical than the other monitoring methods and also can be easily integrated into geographic information.However,remote sensing data cannot directly provide information on primary production without support of models.Vertically Generalized Productivity Model(VGPM)is the most widely used to estimate primary production due to its minimal input parameters,which has been validated by thousands of in situ measured data over several orders of magnitude.Among these input parameters,Chla and euphotic depth are could be derived from remote sensing data,providing a possibility for estimating primary production using remote sensing data.Many studies have successfully estimated phytoplankton primary production by combining remote sensing data to VGPM for Open Ocean.However,due to difficulty in retrieval of Chla and euphotic depth in complexly optical waters,there have been few applications of the VGPM to lakes.In recent years,we have calibrated and validated Chla and euphotic depth estimation model in Lake Taihu,made it possible for us to estimate the phytoplankton primary production based on the VGPM model.Therefore,the aims of ours study were to 1)assess the accuracy and feasibility of VGPM in Lake Taihu using in situ measurement data,2)estimate the phytoplankton primary production of Lake Taihu from 2003 to 2013 using MODIS-derived data,3)analyze the temporal and spatial variations in primary production in Lake Taihu and discuss the potential affecting factors.It turns out that the annual mean daily primary production of Lake Taihu from 2003 to 2013 was 1094.06±720.74 mg C/m2/d.Long-term primary production maps estimated from the MODIS data demonstrated marked temporal and spatial variations.Spatially,the primary production in bays,especially in Zhushan Bay and Meiliang Bay,was consistently higher than that in the open area of Lake Taihu,which was caused by chlorophyll-a concentrations resulting from high nutrient concentrations.Temporally,the seasonal variation of primary production from 2003 to 2013 was:summer>autumn>spring>winter,with significantly higherprimary production found in summer and autumn than in winter(p<0.005,t-test),primarily caused by seasonal variations in water temperature.On a monthly scale,the primary production exerts a clear character of bimodality,increasing from January to May,decreasing in June or July,and finally reaching its highest value during August or September.Wind is another important factor that could affect the spatial variations of primary production in the large,eutrophic and shallow Lake Taihu.