Applied statistical analysis as a tool for sustainable natural resources planning and management

This paper illustrates the use of applied statistical analysis for sustainable planning and management of a natural resource such as rice grain yield. Statistical implications in this study strongly suggest that natural factors are most influential in the sustainability of natural resource which can serve as a framework for regional planning and management of the same. The author purposely chose rice as a subject of the study, it being a common staple cereal eaten by most Filipinos and half of the world's population. Specifically, it aims to establish statistically the effect of some specific weather variable (e.g., irrigation, solar radiation, minimum and maximum temperatures) to rice grain production considering almost all provinces serviced by National Irrigation Administration and the weather data of the Provinces of Nueva Ecija, which now has increased stabilized rice areas and is considered one of the prime rice producers in the country. Simple, stepwise multiple and polynomial regression models have been derived using froward technique and significantly tested. The model Y = 5.9 + 0.28*SR + 0.22*TMAX adequately and significantly provided quantitative trends on the effect of solar radiation and maximum temperature on rice grain yield as the prominent weather determinants. The regression equation, however, will be valid for predictions only if the conditions (environment, varietal characteristics, soil fertility, management of inputs, etc.) are the same with the conditions in which the model was derived. Furthermore, the desirable regression results of this study are still dependent on the integrity and veracity of the data collated by the researcher. The result of this paper can be used as a management tool for sustainable use of the natural resources and help focus research and experimentation on improving rice grain production. Likewise, it is most useful to any planning agency involved in the development of an irrigation system, regional planning analysis and resource allocation.