Variation in ecophysiology and carbon economy of invasive and native woody vines of riparian zones in south-eastern Queensland

Exotic and invasive woody vines are major environmental weeds of riparian areas, rainforest communities and remnant natural vegetation in coastal eastern Australia, where they smother standing vegetation, including large trees, and cause canopy collapse. We investigated, through glasshouse resource manipulative experiments, the ecophysiological traits that might facilitate faster growth, better resource acquisition and/or utilization and thus dominance of four exotic and invasive vines of South East Queensland, Australia, compared with their native counterparts. Relative growth rate was not significantly different between the two groups but water use efficiency (WUE) was higher in the native species while the converse was observed for light use efficiency (quantum efficiency, AQE) and maximum photosynthesis on a mass basis (Amax mass). The invasive species, as a group, also exhibited higher respiration load, higher light compensation point and higher specific leaf area. There were stronger correlations of leaf traits and greater structural (but not physiological) plasticity in invasive species than in their native counterparts. The scaling coefficients of resource use efficiencies (WUE, AQE and respiration efficiency) as well as those of fitness (biomass accumulated) versus many of the performance traits examined did not differ between the two species-origin groups, but there were indications of significant shifts in elevation (intercept values) and shifts along common slopes in many of these relationships – signalling differences in carbon economy (revenue returned per unit energy invested) and/or resource usage. Using ordination and based on 14 ecophysiological attributes, a fair level of separation between the two groups was achieved (51.5% explanatory power), with AQE, light compensation point, respiration load, WUE, specific leaf area and leaf area ratio, in decreasing order, being the main drivers. This study suggests similarity in trait plasticity, especially for physiological traits, but there appear to be fundamental differences in carbon economy and resource conservation between native and invasive vine species.

Stochastic model for simulating maize yield

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment. © 2012 American Society of Agricultural and Biological Engineers.