Irrigated Rice Ecosystem Research Articles

Mapping soil texture classes using field textuing, particle size distribution and local knowledge by both conventional and geostatisical methods

SummaryWe investigated the utility of three interpolation techniques that ignored descriptive `soft' information and one that used it for mapping topsoil texture classes: re‐coding of soil map units within Geographical Information Systems (GIS), Thiessen polygons, and classifcation of probability vectors estimated by ordinary indicator kriging and simple indicator kriging with local prior means. The results were compared with texture maps based on a classifcation of kriged maps of particle size distribution. The methods were applied to two distinct regions, which represent large areas in rain‐fed rice ecosystems and irrigated rice ecosystems. The `hard' databases for both areas contained soil information needed for mapping at regional scales (1:100 000‐1:150 000). These data were complemented with 'soft' information derived from farmers and soil experts (Northeast Thailand) and soil maps (Nueva Ecija, Philippines). Interpolated maps agreed with the texture map based on interpolation of particle size distribution, and ®eld estimates of soil texture proved to be valuable surrogates for laboratory measurements of soil texture classes. The interpolation of categorical data such as soil texture classes allows for upgrading and increasing the resolution of maps in sparsely sampled regions by using simple field measurements. Validation using independent test sets showed that indicator kriging with local prior means performed best in the rain‐fed lands, whereas soft information did not improve the predictions in Nueva Ecija. Local knowledge in a formalized form was valuable in Northeast Thailand and the interpolated soil texture map for this area had an accuracy and resolution to support agronomic decisions at the village scale. The poor quality of the soil map and the fact that the gradually changing variability in young alluvial soils can be modelled with fewer data explained the lower accuracy of simple indicator kriging with local prior means in Nueva Ecija. Thiessen polygons performed well in the undulating rain‐fed lands but were not as reliable as indicator kriging in the gradually changing irrigated lands.

UV-B Effects on Crops: Response of the Irrigated Rice Ecosystem

Summary Increasing ultraviolet-B (UV-B) radiation resulting from depletion of the stratospheric ozone layer could have damaging effects on crops. This paper reviews recent findings on direct effects of UV-B on rice growth and yield as well as indirect effects via impacts on other organisms in the rice (Oryza sativa) agroecosystem. The findings are based on research by scientists at the International Rice Research Institute (IRRI) in Los Banos, the Philippines, and their collaborators in China and the United States; with comparison to research by scientists in other countries. Current results indicate that while enhanced UV-B directly impacts many aspects of rice growth, physiology, and biochemistry under controlled phytotron conditions; in general rice growth and yield are not affected under natural field conditions. The difference in response may be related both to the levels of UV-B exposure used in phytotron vs. field studies and the lower ratio of UV-A to UV-B in the phytotron compared to field. In terms of indirect effects on rice blast disease, enhanced UV-B affected both the fungus itself (Pyricularia grisea) and the susceptibility of the rice plant to the fungus. Based on these data, simulation models estimated potential impacts of higher UV-B levels on blast severity and rice yield in different countries of southeast and east Asia. Ultimately, results from rice studies can be used to identify strategies to minimize any negative effects of UV-B on rice productivity.

A Food Web Approach to Evaluating the Effect of Insecticide Spraying on Insect Pest Population Dynamics in a Philippine Irrigated Rice Ecosystem

Summary 1. Data from a 645-taxa Philippines-wide food web and multiple regression models were used to predict population fluctuations of insect pests in a rice field. Independent variables of pest models included the biomass of rice plants in the field, the abundance of each pest, and the abundances of five highly correlated enemies of the pest, all as functions of time. 2. To test the ability of the models to reveal effects of insecticide spraying, a rice field at the International Rice Research Institute (IRRI) in the Philippines was divided into deltamethrin-sprayed and unsprayed plots. Data on the abundance of seven pest species (Nephotettix virescens, Recilia dorsalis, Sogatella furcifera, Nilaparvata lugens, Hydrellia philippina, Ne. nigropictus and Cofana spectra) and their natural enemies (predators and parasitoids) were collected during the dry season of 1990. 3. Spraying insecticide disorganized the population dynamics of insect species feeding in the IRRI field. Multiple regression models were less able in the sprayed plot than in the unsprayed plot to forecast the population fluctuations of pest species on the basis of various numbers and combinations of independent variables. For example, current pest abundance, by itself, was a significant predictor of future pest abundance for four of the seven pests (Ne. virescens, R. dorsalis, S. furcifera, H. philippina) in the unsprayed plot, but significant fits were found for only two pests (R. dorsalis, H. philippina) in the insecticide-sprayed plot. 4. In the unsprayed plot, independent variables were significant predictors of future pest abundance in four of seven initial models compared to one of seven models in the sprayed plot. Step-wise removal of independent variables in the models enhanced their forecasting power in both the sprayed and unsprayed plots, but significant models in the unsprayed plot nearly always outnumbered those in the sprayed plot. 5. In the unsprayed plot, Ne. virescens retained five of seven independent variables as significant predictors, compared to four for S. furcifera, three for C. spectra, and one for the remaining four pests. Classical models that contain one or two species as independent variables may not be sufficient to forecast future abundances of some Philippine rice pests in unsprayed and sprayed plots. 6. In general, models that included interaction terms and either the presence or absence of sprays among the independent variables did not improve the forecasting power of models in either the sprayed or unsprayed plot. 7. The methods developed here for studying the impact of spraying on the organization of arthropod communities in rice fields could be applied to other interventions