Integrated Primary Production - Particulate (algorithm product)

Methods

NPP Algorithm

We investigated the processes driving variability in primary productivity in the California Current Ecosystem (CCE) in order to develop an algorithm for predicting C-14 net primary productivity from in situ irradiance, nutrient, and chlorophyll (chl) measurements. Primary productivity data from seven process cruises of the CCE Long-Term Ecological Research (CCE LTER) program were used to parameterize the algorithm. An initial algorithm was developed using only irradiance to predict chl-specific productivity was found to have model-data misfit that was correlated with NH4+ concentrations. We thus found that the best estimates of primary productivity were obtained using an equation including NH4+ and irradiance: PP/Chl = V0m×(1-exp(-α×PAR/V0m)×NH4/(NH4+KS), where PP/Chl is chlorophyll-specific primary production in units of mg C d-1 / mg Chl, PAR is photosynthetically active radiation (units of µEi m-2 s-1) , NH4+ is in units of μmol L-1, V0m = 66.5 mg C d-1 / mg Chl , α = 1.5, and KS = 0.025 μmol L-1. We then used this algorithm to compute primary productivity rates for the CCE-P1706 cruise on which in situ primary productivity samples were not available. We compared these estimates to independent productivity estimates derived from protistan grazing dilution experiments and found excellent agreement. The correlation between model-data misfits for samples from the same casts (0.18) was included in error propagation when determining 95% confidence intervals. For full description, see Stukel et al. 2019 (doi: 10.1101/590240)