Title : Theory of Universal Soil Biodiversity Equation
Abstract:
Biodiversity in the soil as the largest gene bank of the world of life has received less attention. With the discovery of a new microorganism, 200 new genes that can be used for human well-being are offered to humanity. On the other hand, industrial life, including industrial agriculture, has accelerated the extinction of biological species. Having said that, quantifying the biological diversity in the soil, while helping to identify the areas prone to genetic erosion in the soil, will also greatly contribute to the well-being of the future generation of humans, and future generations will benefit from its results. Based on this, the preparation of the global equation for biodiversity in soil is the priority of global research in the field of biodiversity. According to this theory, digitized parameters are required in global dimensions, and based on these parameters, artificial neural network modeling is analyzed using JMP software in the form of a global equation. These three parameters include geomorphometric parameters, agricultural data and inputs, as well as climatic data, which at different levels determine the conditions governing the habitat of biological organisms, how to manage the soil ecosystem, and also the climatic conditions affecting soil organisms. .
Based on this theory, geomorphometric parameters including Slope, Aspect, Closed Depression, Analytical Hill shading, Plan Curvature, Profile Curvature, Convergence Index, Total Catchment Area, Topographic Wetness Index, LS Factor, Channel Network Base Level, Channel Network Distance, Valley Depth , Relative Slope Position, Normalized Difference Vegetation Index, Normalized Difference Salinity Index, Salinity Index, Clay Index, ... are extracted using satellite image processing. Parameters derived from agricultural data and inputs, including amounts of fertilizer, poison, water, seeds, traditional or industrial machinery, planting method, planting date, planting density, crop or garden yield, harvest index, fertilizer consumption efficiency, consumption efficiency water etc. Climatic parameters include maximum, minimum and average temperature (in degrees Celsius), monthly and annual rainfall during the plant growth period (in millimeters), relative air humidity (in percent), wind speed and direction (in meters per second), length (in hours), the number of sunny hours during the plant growth period, etc., which are collected from weather station information.
The geomorphometric parameters are subject to the inherent characteristics of the soil and are entered independently in this modeling and are considered as the conditions governing the habitat of biological organisms located in the soil ecosystem. The parameters derived from the agricultural data and inputs reflect the agricultural management and are related to the experience and expertise of the farmer, which are collected through asking the farmer. Climatic parameters reflect the prevailing climatic conditions in the region and directly affect the growth and survival of soil biological communities.
The desired data must be digitized (Digitizing) so that after collecting using advanced statistical software, artificial neural network modeling can be done. Different software series such as JMP can be used for artificial neural network modeling. Considering that the results of various studies in biological sciences have proven the applicability of artificial neural network modeling and it has a high capability in this field, therefore artificial network modeling is also used here to prepare the global equation of biodiversity in soil. . This equation, in the future of research, will help in the quantitative (not qualitative) identification of the soil ecosystem on a global scale, in order to identify the strengths and weaknesses of the management of different ecosystems on the planet, such as agriculture, gardens, forests, pastures, and the sea. lead to sustainable improvement (Hemostasis) in the planet's ecosystem and provide the basis for human well-being and peace in the coming years.
Keywords: soil ecosystem sustainability, agricultural industrial management, GIS, Finger Printing Methods
