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[Display omitted] • Impacts of climate and land use change on the distribution of ticks were explored. • A model of different ticks showed diverse sensitivities to environmental factors. • The future distribution probability decreased under the scenario SSP5-RCP8.5. • The future potential distribution of ticks shifted further north in China. Ticks are known as vectors of several pathogens causing various human and animal diseases including Lyme borreliosis, tick-borne encephalitis, and Crimean-Congo hemorrhagic fever. While China is known to have more than 100 tick species well distributed over the country, our knowledge on the likely distribution of ticks in the future remains very limited, which hinders the prevention and control of the risk of tick-borne diseases. In this study, we selected four representative tick species which have different regional distribution foci in mainland China. i.e., Dermacentor marginatus , Dermacentor silvarum , Haemaphysalis longicornis and Ixodes granulatus. We used the MaxEnt model to identify the key environmental factors of tick occurrence and map their potential distributions in 2050 under four combined climate and socioeconomic scenarios (i.e., SSP1-RCP2.6, SSP2-RCP4.5, SSP3-RCP7.0 and SSP5-RCP8.5). We found that the extent of the urban fabric, cropland and forest, temperature annual range and precipitation of the driest month were the main determinants of the potential distributions of the four tick species. Under the combined scenarios, with climate warming, the potential distributions of ticks shifted to further north in China. Due to a decrease in the extent of forest, the distribution probability of ticks declined in central and southern China. In contrast with previous findings on an estimated amplification of tick distribution probability under the extreme emission scenario (RCP8.5), our studies projected an overall reduction in the distribution probability under RCP8.5, owing to an expected effect of land use. Our results could provide new data to help identify the emerging risk areas, with amplifying suitability for tick occurrence, for the prevention and control of tick-borne zoonoses in mainland China. Future directions are suggested towards improved quantity and quality of the tick occurrence database, comprehensiveness of factors and integration of different modelling approaches, and capability to model pathogen spillover at the human-tick interface. [ABSTRACT FROM AUTHOR]

Highlights • Yield per hectare of sweet sorghum are influence by temperature and precipitation. • Xinjiang and Inner Mongolia are suitable for planting sweet sorghum. • The 2020 and 2050 biofuel goal can be satisfied by certain scenarios in this paper. • Climate change and land-use change are critical to energy crop development plan. Abstract Biofuel from energy crops will play an important role in supplying carbon-neutral fuel for the transport sector. However, there are large uncertainties regarding energy crop development and the energy crop potential and distribution need to be evaluated more comprehensively and systematically. In this study, we propose an integrated approach using the AquaCrop model, a geographic information system approach, and a scenario analysis and we conduct a land availability assessment with multiple factors including climate change, land use, soil, topography, regional crop management, and technological improvement to shed light on the potential production, distribution, and temporal-spatial variation of land suitable for sweet sorghum production in China. We evaluate a full range of spatial scales from 1-km resolution to a national assessment in four representative concentration pathways from 2010 to 2100. The results show that most provinces can plant sweet sorghum. The most suitable provinces for sweet sorghum production are Xinjiang, Heilongjiang, Jilin, Inner Mongolia, Yunnan, and Sichuan. The biofuel potential of sweet sorghum in high-slope farmland (0.30–0.73 EJ) and marginal land (11.98–15.18 EJ) can satisfy the biofuel goal in 2020 (0.12 EJ) and 2050 (6.70–8.60 EJ). Climate change and land-use change are critical factors influencing for the current implementation and long-term planning of energy crops in China. [ABSTRACT FROM AUTHOR]

[Display omitted] • The climate suitability of cotton distribution is mapped using MaxEnt model. • The areas of improved climatic suitability comprised 38.08 % of the entire country. • Cotton production moved northward and expanded westward. • Consistency between climate suitability and production showed a decreasing trend. Understanding the varying distribution of climate-suitable areas of cotton (Gossypium hirsutum L.) can greatly aid in optimizing distribution of cotton production and sustainable production. Based on occurrence records, national meteorological data and the maximum entropy (MaxEnt) model (a species distribution model), we investigated for the first time the interdecadal variations in climate-suitable areas of cotton with changing climate in China from 1961 to 2017. Then, the gravity center and concentration index were employed to investigate the spatial-temporal variations of cotton production. The results revealed the dominant meteorological predictors affecting climate suitability of cotton to be ≥ 28℃ accumulated maximum temperature from April to October, average temperature in the warmest month, continuous days with daily average temperature ≥15 ℃ and annual precipitation days. The climate optimum areas were generally distributed in the eastern and northern parts of the Huanghe Valley and Northwest Inland cotton regions, respectively. The climatic suitability of cotton has increased in China in recent decades. In particular, the areas of improved climatic suitability of cotton encompassed 38.08 % of the whole country from the 1960s to 2010s. This increase was concentrated in the Huanghe Valley and Northwest Inland cotton regions. The distribution of climate-suitable areas moved northward and expanded westward. Meanwhile, the gravity center of the cotton production moved to the northwest at a distance of approximately 1283 km from 1985 to 2015. Although both the production and distribution of climate-suitable areas of cotton shifted towards the northwest, the proportions of inconsistency between planting areas and climate-suitable areas increased from 22.76 % in the 1980s to 32.38 % in the 2010s. The increasing planting acreage in areas of low climate suitability may pose a risk to cotton production, especially in emerging major planting areas of the Northwest Inland cotton region. The results of the present study can provide a theoretical reference for the optimization of planting distribution and ensure the sustainable production of the cotton industry. [ABSTRACT FROM AUTHOR]

• Zingiber species distribution and richness were studied based on accession records. • Key bioclimatic determinants of Zingiber species distribution were identified. • Present and future potential distribution of Zingiber species were examined. • Some species may will be considerably reduced, necessitating conservation efforts. Climate change has a crucial impact on plant resources distribution, especially on agricultural crops. Species belonging to genus Zingiber are important crop resources in China, and their rhizomes are widely used in medicine and food. In this study, the ecological distribution and richness of the genus Zingiber were analyzed using a DIVA-GIS analysis of 967 georeferenced herbarium records to produce present and future distribution simulations using the MaxEnt model. The results showed that the genus Zingiber is widely distributed in 28 provinces in China, with the greatest richness in Guangxi, Guangdong, and Yunnan. Based on our model, precipitation of the driest month, precipitation of the warmest quarter, and the minimum temperature of the coldest month were the most significant bioclimatic variables controlling the distribution of five selected Zingiber species. Future climate change will likely result in the increase of suitable habitat area for Zingiber officinale by 2.85%, but dramatically decrease that for Zingiber striolatum by 18.04%, Zingiber zerumbet by 17.87%, Zingiber corallinum by 12.40%, and Zingiber mioga by 9.46%. Thus, conservation measures should be taken to preserve these valuable resources. [ABSTRACT FROM AUTHOR]