Photosynthetic Responses to Inorganic Carbon in Ulva lactuca Under Aquatic and Aerial States

Intertidal macroalgae experience continual alternation of photosynthesis between aquatic state at high tide and aerial state at low tide. The comparative photosynthetic responses to inorganic carbon were investigated in the common intertidal macroalga Ulva lactuca L. along the coast of Shantou between aquatic and aerial state. The inorganic carbon dissolved in seawater at present could fully (at 10 ℃ or 20 ℃) or nearly (at 30 ℃) saturate the aquatic photosynthesis of U. lactuca . However, the aerial photosynthesis was limited by current ambient atmospheric CO 2 level, and such a limitation was more severe at higher temperature (20-30 ℃) than at lower temperature (10 ℃). The carbon_saturated maximal photosynthesis of U. lactuca under aerial state was much greater than that under aquatic state at 10 ℃ and 20 ℃, while the maximal photosynthesis under both states was similar at 30 ℃. The aerial values of K m (CO 2) for photosynthesis were higher than the aquatic values. On the contrary, the values of apparent photosynthetic CO 2 conductance under aerial state were considerably lower than that under aquatic state. It was concluded that the increase of atmospheric CO 2 would enhance the primary productivity of U. lactuca through stimulating the photosynthesis under aerial state during low tide.

A multi-state weather generator for daily precipitation for the Torne River basin, northern Sweden/western Finland

This paper describes a new weather generator e the 10-state empirical model e that combines a 10-state, first-order Markov chain with a non-parametric precipitation amounts model. Using a doubly-stochastic transition-matrix results in a weather generator for which the overall precipitation distribution(including both wet and dry days) and the temporal-correlation can be modified independently for climate change studies. This paper assesses the ability of the 10-state empirical model to simulate daily area-average precipitation in the Torne River catchment in northern Sweden/western Finland in the context of 3 other models: a 10-state model with a parametric(Gamma) amounts model; a wet/dry chain with the empirical amounts model; and a wet/dry chain with the parametric amounts model. The ability to accurately simulate the distribution of multi-day precipitation in the catchment is the primary consideration.Results showed that the 10-state empirical model represented accumulated 2- to 14-day precipitation most realistically. Further, the distribution of precipitation on wet days in the catchment is related to the placement of a wet day within a wet-spell, and the 10-state models represented this realistically, while the wet/dry models did not. Although all four models accurately reproduced the annual and monthly averages in the training data, all models underestimated inter-annual and inter-seasonal variance. Even so, the 10-state empirical model performed best.We conclude that the multi-state model is a promising candidate for hydrological applications, as it simulates multi-day precipitation well, but that further development is required to improve the simulation of interannual variation.