Spatiotemporal pattern of the tea industry in Sichuan Province and its driving forces based on the geographical detector

The growth of tea industry is the result of interactions between natural and social factors. An understanding of the spatiotemporal pattern of the tea industry and the effects of natural and socioeconomic factors provides an important basis for the adjustment of tea planting structures. Based on the statistical yearbook data of the tea industry in Sichuan Province over the last 40 years, from 1980 to 2019, the spatiotemporal pattern of tea industry in Sichuan Province and its driving forces were studied using industrial concentration, exploratory data analysis, and an industrial gravity model. Natural factors, such as elevation, soil pH, annual precipitation, accumulated temperature, average temperature of tea growing season, extreme minimum temperature of the overwintering period, and extreme maximum temperature of tea growing season; production factors, such as land use intensity, labor, fertilizer, pesticides, and irrigation; as well as socioeconomic factors, such as per capita disposable income, technology, and policy were statistically divided by the geographical detector. The impact of separate driving factors and the interactions between these factors on the spatial pattern of tea industry in Sichuan Province were systematically discussed. The results of this study were as follows: in the past 40 years, the tea industry in Sichuan Province had shown an expanding trend; the spatial distribution showed a high degree of concentration; and a wavelike increase with time (locational Gini index > 0.5). There was a significant geographical agglomeration on the county scale, showing a hot spatial structure in southern Sichuan and the southern Chengdu Plain (global Moran’s I > 0). The center of gravity of the tea industry in Sichuan migrated to the west. The modifiable areal unit problem (MAUP) is a fundamental issue in geographical detectors. To address this issue, both scale and zoning effects were tested to examine the MAUP before applying the geographical detector model in this study. Among the 15 influencing factors selected, land use intensity, labor, and fertilizer had the highest deciding power. The interactions between these factors mainly manifested as dual-factor enhancement and nonlinear enhancement types, and the average interaction of production factors and socioeconomic factors had the highest decisive power (0.8870). Thus, the tea industry in Sichuan Province was mainly driven by production factors. Evidence-based hypothetical solutions derived from these observations focused on three aspects: 1) Pay close attention to the influence of water shortage in the tea growth period, intense rainfall, and freezing damage on tea trees and react effectively. 2) Implement corresponding countermeasures, including strengthening the construction of machine-plucking tea gardens “suitable for mechanization” and establishing the concept of green development. 3) Accelerate the promotion and application of modern agricultural technology; breed new tea varieties that fit local conditions; and set up a system of steady land, labor, fertilizer, and pesticide input.