Marine Ecology Progress Series | |
Modelling kelp forest primary production using in situ photosynthesis, biomass and light measurements | |
Kirsten L. Rodgers1  Nick T. Shears1  | |
关键词: Primary productivity; Macroalgae; Modelling; Photosynthesis; Respiration; Biomass; Irradiance; Ecklonia radiata; | |
DOI : 10.3354/meps11801 | |
学科分类:海洋学与技术 | |
来源: Inter-Research | |
【 摘 要 】
ABSTRACT: Kelp forests are among the most productive ecosystems in the world. Accurately quantifying net primary productivity (NPP) of kelps is challenging, as the carbon being produced is continually being lost through erosion of tissue and as dissolved organic carbon. Here, we use a physiological model that incorporates in situ estimates of photosynthesis vs. irradiance (P-E) parameters, biomass and underwater irradiance to estimate NPP of a subsurface Ecklonia radiata kelp forest in northern New Zealand over the seasonal cycle and depth range. Model testing found that predicted gross primary production (GPP) based on seasonal and depth-specific P-E parameters, biomass and underwater irradiance levels was strongly related to rates of GPP measured on individual kelp in the field (r2 = 0.83). Sensitivity analysis indicated that NPP estimates were most sensitive to variation in biomass and photosynthetic parameters. Using this approach, estimated annual production (±SE) at 6 m (615 ± 183 g C m-2 yr-1) was found to be 1.6× greater than at 14 m depth (374 ± 102 g C m-2 yr-1), which was proportional to the difference in biomass between depths. This indicates that the greater photosynthetic abilities (higher maximum photosynthetic rates and photosynthetic efficiency) of deeper kelp offset the effects of reduced irradiance on overall NPP at depth. This study demonstrates how in situ P-E curves of adult kelp can be incorporated with biomass and irradiance data to estimate NPP of kelp forests, and highlights the importance of understanding depth-related variation in photosynthetic performance when estimating primary production of subsurface kelp forests.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201912010137003ZK.pdf | 8KB | download |