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Research on the suitable habitat for Moschus berezovskii based on maximum entropy model（MaxEnt） in climatic background

ZHAO Jin-peng, WANG Qing, ZHENG Cheng-li, HU Jing-yuan, WANG Ru-lin, JIANG Gan

HUBEI AGRICULTURAL SCIENCES 2023, 62 (3): 218-223. DOI: 10.14088/j.cnki.issn0439-8114.2023.03.034

Abstract （257）

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According to the published geographic distribution data and habitat climate data of Moschus berezovskii in China, the key meteorological factors affecting the probability of existence of Moschus berezovskii were extracted by knife cutting method. The MaxEnt model and ArcGIS software were used to analyze the habitat range of Moschus berezovskii in China under different scenarios. The results showed that eight key climate factors had important influences on the distribution of Moschus berezovskii, including precipitation in the warmest season, mean temperature in the driest season, precipitation in the wettest season, annual average temperature, seasonal temperature difference, mean temperature in the wettest season, mean temperature in the warmest season and precipitation in the driest season; the habitat prediction model of Moschus berezovskii was examined by receiver operating characteristic curve, and the prediction results reached an excellent level （AUC=0.993）. Under the current scenario, the suitable area of Moschus berezovskii was mainly distributed in the south of Tengchong-Mohe line, with an area of 4.13×10⁶ km², accounting for 43% of China's land area; under the scenarios of RCP2.6, RCP4.5 and RCP8.5, the suitable area of Moschus berezovskii decreased in the 2050s（2040—2059）, and the lowly suitable area decreased up to 50%; compared with the 2050s, the suitable area of Moschus berezovski increased under RCP2.6 and RCP4.5 scenarios in 2080s（2070—2089）, but it decreased under RCP8.5 scenarios. The southeast region, which was dominated by plain and hilly landforms, would respond poorly to future climate change, while the southwest region, which was dominated by mountainous landforms, would respond well to future climate change. Therefore, it was suggested to establish a Moschus berezovskii reserve with the southwest region as the core, and strictly control the personnel entering the reserve, so as to achieve the purpose of better protecting the wild Moschus berezovskii.

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Evaluation of automatic observation technology for agricultural meteorology of winter wheat and summer corn

ZHANG Zhi-hong, SHI Gui-fen, LI Shu-ling

HUBEI AGRICULTURAL SCIENCES 2023, 62 (3): 224-229. DOI: 10.14088/j.cnki.issn0439-8114.2023.03.035

Abstract （284）

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In three national first-class agricultural meteorological observation test stations in Zhengzhou, Hebi and Huangfan district of Henan Province, 5 sets of observation equipment of Aerospace New Meteorological Technology Co., Ltd. and Henan Zhongyuan Optoelectronics Measurement and Control Technology Co., Ltd. were used to conduce continuous automatic observation experiments on the growth period, canopy height, density, leaf area index and dry matter of winter wheat and summer corn from 2016 to 2020, and at the same time, manual comparative observation was carried out. The results showed that the identification error of winter wheat in the growth period was usually within 4 days. The error in turning green and jointing period was more than 5 days, which should be supplemented by artificial observation. The average error of canopy height identification was less than 10 cm. The density fluctuated greatly during the growth period, and the effect of automatic identification was poor. The identification error of summer corn in the growth period was generally less than 4 days, and artificial observation was temporarily needed to assist in jointing, milk-ripening and ripening stages. The identification effect of the density and height was good. The identification effects on growth period, growth evaluation, canopy height and corn density of winter wheat and summer corn were good, which could be popularized and applied after optimization. However,the identification effect of the leaf area index and dry matter quality was poor, so there were no conditions for business promotion, and the algorithm or recognition technology should be improved.

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