LIFE TABLE ANALYSIS OF DIAPHORINA CITRI (HEMIPTERA: PSYLLIDAE) INFESTING SWEET ORANGE (CITRUS SINENSIS) IN SAO PAULO

An ecological life table for eggs and nymphs of Diaphorina citri Kuwayama (Hemiptera: Psyllidae) was constructed with data obtained from orange orchards (Citrus sinensis Osbeck) in 2 regions of the State of Sao Paulo, over 4 generations in the period from XI-2006 to V-2007, comprising spring, summer, and fall seasons. Young growing shoots with D. citri eggs present were identified, and live individuals were counted until adult emergence. No predatory arthropods were observed in association with D. citri eggs and nymphs during the study. The mean parasitism of fourth- and fifth-instar nymphs by Tamarixia radiata Waterston (Hymenoptera: Eulophidae) was 2.3%. The durations of the egg-adult period were similar among the 4 generations, ranging from 18.0 to 24.7 d (at mean temperatures ranging from 21.6 to 26.0 degrees C) and followed the temperature requirement models obtained in the laboratory for D. citri. However, survival from the egg to the adult stage for the same period varied considerably from 1.7 to 21.4%; the highest mortalities were observed in the egg and small nymphal (first- to thirdinstar) stages, which were considered to be key phases for population growth of the pest.

Integration of spatial and temporal models to predict extreme water table depths

The objective of this work was to evaluate extreme water table depths in a watershed, using methods for geographical spatial data analysis. Groundwater spatio-temporal dynamics was evaluated in an outcrop of the Guarani Aquifer System. Water table depths were estimated from monitoring of water levels in 23 piezometers and time series modeling available from April 2004 to April 2011. For generation of spatial scenarios, geostatistical techniques were used, which incorporated into the prediction ancillary information related to the geomorphological patterns of the watershed, using a digital elevation model. This procedure improved estimates, due to the high correlation between water levels and elevation, and aggregated physical sense to predictions. The scenarios showed differences regarding the extreme levels - too deep or too shallow ones - and can subsidize water planning, efficient water use, and sustainable water management in the watershed.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.