Objective Phellodendron amurense, a special species in Northeast Asia, is the source of the wild medicinal Phellodendri Amurensis Cortex, the second-level key protection in China. Because of its dual value of medicine and timber, it has been cut in large quantities, resulting in a sharp decline in wild resources. It has been listed as a national first-class rare tree species. Here, we aim to plan protection area and wild tending area for Chinese P. amurense in the context of climate change. Method In this study, based on the Biomod2 model, the main environmental factors affecting the distribution and the potentially suitable areas of the current and future were investigated. Furthermore, the correlation between the main environmental factors and the chemical components was determined by full subset regression. Habitat quality and landscape pattern change were determined by InVEST and Fragstats software based on the land use data in 1980, 2000, and 2020. Then, Zonation software was used to plan the priority protection and wild tending areas. Results The results showed that in the future, the potential habitat of P. amurense will gradually move to the high latitude and high altitude areas in the northwest direction, and the high suitability area will decrease sharply. Since 1980, the habitat quality of P. amurense habitat has gradually deteriorated, and the fragmentation has gradually intensified. In the future, the central part of the Greater Khingan Mountains and the forest area of the Lesser Khingan Mountains will be the long-term stable sanctuary. Fengcheng City and Tonghua County are the most suitable for the wild tending areas. Conclusion The existing nature reserve only contains 6.01% of the priority protection area, so we propose to expand the area to cover a larger proportion of the sanctuary and implement management and restoration plans to increase the suitability and connectivity. These results can support the protection action and provide a reference and scientific basis for further research, rational development, and utilization of P. amurense.

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Optimizing the distribution pattern of species under climate change: the protection and management of Phellodendron amurense in China

Climate change, especially climate extremes, can increase the uncertainty of locust outbreaks. The Italian locust (Calliptamus italicus (Linnaeus, 1758)), Asian migratory locust (Locusta migratoria migratoria Linnaeus, 1758), and Siberian locust (Gomphocerus sibiricus (Linnaeus, 1767)) are common pests widely distributed in the semidesert grasslands of Central Asia and its surrounding regions. Predicting the geographic distribution changes and future habitats of locusts in the context of climate warming is essential to effectively prevent large and sudden locust outbreaks. In this study, the optimized maximum entropy (MaxEnt) model, employing a combination of climatic, soil, and topographic factors, was used to predict the potential fitness areas of typical locusts in the 2030s and 2050s, assuming four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) in the CMIP6 model. Modeling results showed that the mean area under the curve (AUC) and true statistical skill (TSS) of the MaxEnt model reached 0.933 and 0.7651, respectively, indicating that the model exhibited good prediction performance. Our results showed that soil surface sand content, slope, mean precipitation during the hottest season, and precipitation seasonality were the key environmental variables affecting locust distribution in the region. The three locust species were mainly distributed in the upstream region of the Irtysh River, the Alatao Mountain region, the northern slopes of the Tianshan Mountains, around Sayram Lake, the eastern part of the Alakol Lake region, the Tekes River region, the western part of Ulungur Lake, the Ili River, and the upstream region of the Tarim River. According to several climate projections, the area of potential habitat for the three most common locust species will decrease by 3.9 × 104-4.6 × 104 km2 by the 2030s and by 6.4 × 104-10.6 × 104 km2 by the 2050s. As the climate becomes more extreme, the suitable area will shrink, but the highly suitable area will expand; thus, the risk of infestation should be taken seriously. Our study present a timely investigation to add to extensive literature currently appearing regarding the myriad ways climate change may affect species. While this naturally details a limited range of taxa, methods and potential impacts may be more broadly applicable to other locust species. 

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Predictions Based on Different Climate Change Scenarios: The Habitat of Typical Locust Species Is Shrinking in Kazakhstan and Xinjiang, China

Distribution pattern and change prediction of Saposhnikovia divaricata suitable area in China under climate change

Distribution change and protected area planning of Tilia amurensis in China: A study of integrating the climate change and present habitat landscape pattern

A Doppler scatterometer is a kind of rotating radar, which uses a real aperture system and has a high pulse repetition frequency (PRF), so it has the ability to provide useful Doppler information for ocean current field estimation. In previous studies, the Doppler centroid estimation of the Doppler scatterometer was calculated by the average cross-correlation coefficient (ACCC) method. Although this method is fast and robust, it does not make full use of the shape characteristics of the antenna pattern. The estimation method based on the Doppler spectrum can improve accuracy. However, this method is mainly used in radar systems with fixed azimuth, but the antenna of the Doppler scatterometer is always rotating, so this method cannot be directly applied. To improve the estimation accuracy of the Doppler centroid, this paper proposes an optimal estimator method for the Doppler centroid based on deramping and gives the estimation accuracy model of this method based on the Cramer-Rao bound. Doppler centroid estimation based on the Doppler spectrum requires a large scanning accumulation time to obtain high-precision results, and the bandwidth will increase with the increase of accumulation time, eventually exceeding the PRF, resulting in Doppler ambiguity. This method sets a reference function through deramping to move the Doppler centroid of each target to near zero frequency. In this way, the bandwidth is only related to the illumination time of the target, but independent of the scanning accumulation time. The effectiveness, feasibility and accuracy of the method are verified by simulation experiments. It is verified that this method not only solves the Doppler ambiguity caused by azimuth scanning but also improves the estimation accuracy of the Doppler centroid. Compared with the classical ACCC method, the estimation accuracy of this method is improved by 26.15%.

Chen Wang

Papers

Distribution pattern and change prediction of Saposhnikovia divaricata suitable area in China under climate change

Distribution change and protected area planning of Tilia amurensis in China: A study of integrating the climate change and present habitat landscape pattern

Optimizing the distribution pattern of species under climate change: the protection and management of Phellodendron amurense in China

Doppler centroid estimation of Doppler scatterometer based on deramping