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Concentrated conservation and utilization: Four medicinal crops for diabetes treatment showed similar habitat distribution patterns in China

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TLDR
A comprehensive evaluation on the potential geographical distribution of the four medicinal crops was conducted based on the maximum entropy (Maxent) modeling and it was found that A. membranaceus and R. glutinosa shared similar potential habitats which mainly located in northern China, while C. chinensis and S. ningpoensis shared similar potentially located in South and Central China.
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This article is published in Industrial Crops and Products.The article was published on 2020-09-15. It has received 13 citations till now.

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Growth years and post-harvest processing methods have critical roles on the contents of medicinal active ingredients of Scutellaria baicalensis.

TL;DR: A systematic analysis on the effects of growth years and post-harvest processing on the contents of medicinal active ingredients of S. baicalensis showed that the best harvesting period should be determined as 2–3 years based on comprehensive evaluation of active ingredient content, annual yield increment, and land use efficiency.
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Moderate warming will expand the suitable habitat of Ophiocordyceps sinensis and expand the area of O. sinensis with high adenosine content

TL;DR: Wang et al. as mentioned in this paper developed a comprehensive niche modeling approach to predict the spatial pattern of Ophiocordyceps sinensis quality, and they separately built a comprehensive habitat suitability model to identify suitable habitats and a spatial quality model to map the adenosine content pattern in O. sinensis.
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Increasing inconsistency between climate suitability and production of cotton (Gossypium hirsutum L.) in China

TL;DR: Based on occurrence records, national meteorological data and the maximum entropy (MaxEnt) model, this article investigated for the first time the interdecadal variations in climate-suitable areas of cotton with changing climate in China from 1961 to 2017.
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Future landscape of renewable fuel resources: Current and future conservation and utilization of main biofuel crops in China

TL;DR: Wang et al. as discussed by the authors conducted a comprehensive and systematic analysis on the distribution patterns of main biofuel crops in China, using 22,352 occurrence records of 31 biofuel plant species and thirty-year environmental variables with maximum entropy modeling, as well as nine-year field investigation of land use.
Journal ArticleDOI

Future landscape of renewable fuel resources: Current and future conservation and utilization of main biofuel crops in China

TL;DR: Wang et al. as mentioned in this paper conducted a comprehensive and systematic analysis on the distribution patterns of main biofuel crops in China, using 22,352 occurrence records of 31 biofuel plant species and thirty-year environmental variables with maximum entropy modeling, as well as nine-year field investigation of land use.
References
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Maximum entropy modeling of species geographic distributions

TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.
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Collinearity: a review of methods to deal with it and a simulation study evaluating their performance

TL;DR: It was found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection and the value of GLM in combination with penalised methods and thresholds when omitted variables are considered in the final interpretation.
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Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation

TL;DR: This paper presents a tuning method that uses presence-only data for parameter tuning, and introduces several concepts that improve the predictive accuracy and running time of Maxent and describes a new logistic output format that gives an estimate of probability of presence.
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Species Distribution Models: Ecological Explanation and Prediction Across Space and Time

TL;DR: Species distribution models (SDMs) as mentioned in this paper are numerical tools that combine observations of species occurrence or abundance with environmental estimates, and are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time.
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Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants

Bin Zhou, +497 more
- 09 Apr 2016 - 
TL;DR: In this article, the authors used a Bayesian hierarchical model to estimate trends in diabetes prevalence, defined as fasting plasma glucose of 7.0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs in 200 countries and territories in 21 regions, by sex and from 1980 to 2014.
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