Climate change and irrigation water requirement at Jaguaribe river basin, semi-arid northeast of Brazil.

Summary: Climate change has a potential to impact rainfall, temperature and air humidity, which have relation to plant evapotranspiration and crop water requirement. The purpose of this research is to assess climate change impacts on irrigation water demand, based on future scenarios derived from the PRECIS (Providing Regional Climates for Impacts Studies), using boundary conditions of the HadCM3 submitted to a dynamic downscaling nested to the Hadley Centre regional circulation model HadRM3P. Monthly time series for average temperature and rainfall were generated for 1961-90 (baseline) and the future (2040). The reference evapotranspiration was estimated using monthly average temperature. Projected climate change impact on irrigation water demand demonstrated to be a result of evapotranspiration and rainfall trend. Impacts were mapped over the target region by using geostatistical methods. An increase of the average crop water needs was estimated to be 18.7% and 22.2% higher for 2040 A2 and B2 scenarios, respectively. Objective ? To analyze the climate change impacts on irrigation water requirements, using downscaling techniques of a climate change model, at the river basin scale. Method: The study area was delimited between 4º39?30? and 5º40?00? South and 37º35?30? and 38º27?00? West. The crop pattern in the target area was characterized, regarding type of irrigated crops, respective areas and cropping schedules, as well as the area and type of irrigation systems adopted. The PRECIS (Providing Regional Climates for Impacts Studies) system (Jones et al., 2004) was used for generating climate predictions for the target area, using the boundary conditions of the Hadley Centre model HadCM3 (Johns et al., 2003). The considered time scale of interest for climate change impacts evaluation was the year of 2040, representing the period of 2025 to 2055. The output data from the climate model was interpolated, considering latitude/longitude, by applying ordinary kriging tools available at a Geographic Information System, in order to produce thematic maps.

Plasticity in leaf-level water relations of tropical rainforest trees in response to experimental drought.

The tropics are predicted to become warmer and drier, and understanding the sensitivity of tree species to drought is important for characterizing the risk to forests of climate change. This study makes use of a long-term drought experiment in the Amazon rainforest to evaluate the role of leaf-level water relations, leaf anatomy and their plasticity in response to drought in six tree genera. The variables (osmotic potential at full turgor, turgor loss point, capacitance, elastic modulus, relative water content and saturated water content) were compared between seasons and between plots (control and through-fall exclusion) enabling a comparison between short- and long-term plasticity in traits. Leaf anatomical traits were correlated with water relation parameters to determine whether water relations differed among tissues. The key findings were: osmotic adjustment occurred in response to the long-term drought treatment; species resistant to drought stress showed less osmotic adjustment than drought-sensitive species; and water relation traits were correlated with tissue properties, especially the thickness of the abaxial epidermis and the spongy mesophyll. These findings demonstrate that cell-level water relation traits can acclimate to long-term water stress, and highlight the limitations of extrapolating the results of short-term studies to temporal scales associated with climate change.

Pesticide bioconcentration modelling for fruit trees.

The model presented allows simulating the pesticide concentration in fruit trees and estimating the pesticide bioconcentration factor in fruits of woody species. The model allows estimating the pesticide uptake by plants through the water transpiration stream and also the time in which maximum pesticide concentration occur in the fruits. The equation proposed presents the relationships between bioconcentration factor (BCF) and the following variables: plant water transpiration volume (Q), pesticide transpiration stream concentration factor (TSCF), pesticide stem-water partition coefficient (KWood,w), stem dry biomass (M) and pesticide dissipation rate in the soil-plant system (kEGS). The modeling started and was developed from a previous model ?Fruit Tree Model? (FTM), reported by Trapp and collaborators in 2003, to which was added the hypothesis that the pesticide degradation in the soil follows a first order kinetic equation. The model fitness was evaluated through the sensitivity analysis of the pesticide BCF values in fruits with respect to the model entry data variability.

Spondias tuberosa trees grown in tropical, wet environments are more susceptible to drought than those grown in arid environments.

In this study, we investigated the different responses of Spondias tuberosa (umbu) trees, which grow in two different ecological life zones in northeast Brazil: tropical wet and tropical arid ecosystems. We evaluated the responses of plants grown under humid and dry conditions by measuring the photosynthesis, water status, fluorescence parameters, carbon isotopes and antioxidant system activity. The higher net photosynthesis values were recorded contemporaneously with the lower VPD values. The highest internal-to-ambient CO2 concentration and the absence of typical changes in the fluorescence parameters suggested an onset of a nonstomatal limitation in the photosynthesis. Our results showed that umbu plants can adjust their antioxidant activity during the dry season as a defensive strategy against the deleterious effects of water stress. This evidence is supported by the observed modifications in the pigment concentrations, increased accumulation of hydrogen peroxide and malondialdehyde, high levels of electrolyte leakage, increased antioxidant activity, and decreased carbon isotope discrimination in the umbu trees during the dry season. Supported by multivariate analysis of variance, significantly effect of interaction between categorical months of collect and location predicts a strong ?dry season effect? on our dataset. Taken together, our data show that umbu trees grown in a wet tropical environment are more susceptible to drought, as compared with their tropical arid counterparts.