Geographical distribution of As-hyperaccumulator Pteris vittata in China: Environmental factors and climate changes

Xu, Wumei; Du, Qinglian; Yan, Shuang; Cao, Yue; Liu, Xue; Guan, Dong-Xing; Lena, Q.

doi:10.1016/j.scitotenv.2021.149864

Cited by 41 publications

(18 citation statements)

References 54 publications

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“…The processing of the data is also much more rapid when 2.5 arc-min data are used compared with 30 arc-s data. Data at a resolution of 2.5 arc min have been used in several previous studies that have estimated the potential distributions of species ( Wan et al, 2021 ; Xu et al, 2021 ; Jiang et al, 2022 ).…”

Section: Methodsmentioning

confidence: 99%

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Huang

Du²,

Wen³

et al. 2022

Front. Plant Sci.

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Astragalus variabilis is a locoweed of northwest China that can seriously impede livestock development. However, it also plays various ecological roles, such as wind protection and sand fixation. Here, we used an optimized MaxEnt model to predict the distribution of suitable habitat of A. variabilis under current (1970–2000) conditions and future (2021–2080) climate change scenarios based on recent occurrence records. The most important environmental variables (suitability ranges in parentheses) affecting the distribution of A. variabilis were average maximum temperature of February (–2.12–5.34°C), followed by total precipitation of June (2.06–37.33 mm), and topsoil organic carbon (0.36–0.69%). The habitat suitability of A. variabilis was significantly correlated with the frequency of livestock poisoning (p < 0.05). Under current climate conditions, the suitable environment of A. variabilis was distributed in central and western Inner Mongolia, Ningxia, central and northwestern Gansu, central and northwestern Qinghai, and the four basins around the Tianshan Mountains in Xinjiang. Under future climate conditions, the suitable habitat of A. variabilis shifted to higher latitudes and altitudes. No previous studies have used niche models to predict the suitable environment of this species nor analyzed the relationship between the habitat suitability of poisonous plants and the frequency of animal poisoning. Our findings provide new insights that will aid the prevention of livestock animal poisoning and the control of poisonous plants, promote the development of the livestock husbandry industry, and provide basic information that will facilitate the maintenance of the ecological balance of grassland ecosystems.

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Section: Methodsmentioning

confidence: 99%

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Huang

Du²,

Wen³

et al. 2022

Front. Plant Sci.

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“…Maxent is a machine-learning algorithm that uses presence-only data to determine the predicted suitability of local conditions for a given species ( Phillips et al, 2006 ). Maxent model has been used in previous studies to assess the distribution of species ( Xu et al, 2021 ; Yue et al, 2022 ; Zhu et al, 2022 ). This study aimed to explore the distribution of species screened under different conditions in Inner Mongolia.…”

Section: Methodsmentioning

confidence: 99%

“…In this study, the BCC-CSM-MR model (Beijing Climate Center Climate System Model) with strong simulation capability in China was selected as the future climate scenario ( Feng et al, 2021 ). The BCC-CSM-MR model published in the World Climate Research Program Coupled Model Intercomparison Project (CMIP6) contains four shared socioeconomic pathways (SSPs), green-growth paradigm (SSP126), middle-of-the-road development along historical pattern (SSP245), regionally-heterogeneous development (SSP370), and development path dominated by high energy demand supplied by fossil-fuel (SSP585) ( Zeng et al, 2020 ; Xu et al, 2021 ). Each scenario was divided into two future periods: the 2030s (2021–2070), the 2070s (2060–2080).…”

Section: Methodsmentioning

confidence: 99%

Complex ecological and socioeconomic impacts on medicinal plant diversity

Zhang

Chen²,

Guo³

et al. 2022

Front. Pharmacol.

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Medicinal plant diversity (MPD) is an important component of plant diversity. Over-collection based on medicinal and economic value has the potential to damage the stability of the regional ecosystem. It is important to understand the current distribution of MPD and the factors influencing it. However, it is still unclear whether environmental and socioeconomic conditions have an impact on their distribution. We selected the Inner Mongolia as a representative study area which covers a wide area, accounting for 12.29% of China’s national land area and 0.79% of the world’s land area. At the same time, the region is a long-standing traditional medicinal area for Mongolians in China. Therefore, the region is significantly influenced by changes in environmental factors and socio-economic factors. We used 9-years field survey of the distribution of medicinal plants in Inner Mongolia for assessing the distribution of MPD as influenced by environmental and socioeconomic activities by combining spatial analyses, species distribution models, and generalized additive models. The results from the spatial analysis show that the western region of Inner Mongolia is the main cold spot area of the MPD, and the central-eastern and northeastern regions of Inner Mongolia are the main hot spot areas of the MPD. At the same time, the distribution of cold spots and hot spots of MPD is more obvious at large spatial scales, and with the refinement of spatial scales, the cold spots in scattered areas are gradually revealed, which is indicative for the conservation and development of MPD at different spatial scales. Under the future climate change of shared socioeconomic pathways (SSP), areas with high habitat suitability for medicinal plants remain mainly dominated by the Yellow River, Yin Mountains, and Greater Khingan Range. Notably, the SSP245 development pathway remains the most significant concern in either long- or short-term development. The nonlinear relationship between the driving factors of MPD at different spatial scales shows that temperature, precipitation and socioeconomic development do have complex effects on MPD. The presence of a certain temperature, altitude, and precipitation range has an optimal facilitation effect on MPD, rather than a single facilitation effect. This complex nonlinear correlation provides a reference for further studies on plant diversity and sustainable development and management. In this study, the spatial distribution of medicinal plant resources and the extent to which they are driven by ecological and socioeconomic factors were analyzed through a macroscopic approach. This provides a reference for larger-scale studies on the environmental and socioeconomic influences on the distribution of plant resources.

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“…The results showed that the historical legacies significantly imprinted the functional dispersion and functional identity patterns. The utility of these historical environmental regime indices has resulted in tremendous applications in ecological research and also other lines of research (e.g., Tonkin et al 2018;Nguyen et al 2021;Torné s et al 2021;De Pauw et al 2022;Su et al 2022;Xu et al 2022).…”

Section: Introductionmentioning

confidence: 99%

SER: an R package to compute environmental regime over a certain time period

Zou

et al. 2022

Preprint

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SummaryEnvironmental regime (or environmental legacy or historical legacy) is the environmental dynamic characteristics over a given (either long or short) time period, such as frequency of mean or extreme events and rate of change, which might be masked by using only contemporary variables.We present SER, an R package for estimating environmental regimes for different environmental variables. Using the data included in the package, several examples are shown.SER is suitable for any types of environmental variables e.g., nutrient concentration, light, dissolved oxygen. In addition, by changing the argument “days_bf”, it is possible to compute environmental regimes in any interested time period, such as days, months or years.Our case study showed that inclusion of environmental regimes dramatically increased the explained variation of temporal β-diversity and its components. Environmental regimes, particularly in a given time period, are expected to advance the “environment - community” relationships in ecological studies. In addition, they can be implemented in other subjects, e.g., social science, socioeconomics, epidemiology, with important applied implications.

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Geographical distribution of As-hyperaccumulator Pteris vittata in China: Environmental factors and climate changes

Cited by 41 publications

References 54 publications

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Complex ecological and socioeconomic impacts on medicinal plant diversity

SER: an R package to compute environmental regime over a certain time period

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