Filling the maize yield gap based on precision agriculture – A MaxEnt approach

Norberto, Marcos; Sillero, Neftalí; Coimbra, Joaquim Luís; Cunha, Mário

doi:10.1016/j.compag.2023.107970

Cited by 2 publications

(1 citation statement)

References 67 publications

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“…Many SDMs have been widely used, such as maximum entropy theory (MaxEnt), Random Forest (RF), Boosted Regression Tree (BRT), Bioclim, Generalized Linear Model (GLM) and CLIMEX (CL) ( Booth et al., 2014 ; Duan et al., 2014 ; Shabani et al., 2016 ). Among these SDMs, MaxEnt, proposed based on the maximum entropy theory, offers superior accuracy and reproducibility, at the same time, it is easier to operate and does not require expensive computing resources ( Ahmadi et al., 2023 ; Norberto et al., 2023 ). Hence, MaxEnt is highly regarded by researchers and many habitat predictions of plants and animals are made using it in recent years, such as Agastache rugosa, soybean, Hylomecon japonica, Buckwheat, Scutellaria baicalensis, and Rainfed Maize, etc ( Pearson et al., 2006 ; Kogo et al., 2019 ; Xu et al., 2020 ; Wen et al., 2021 ; Cuddington et al., 2022 ; Gong et al., 2022 ; Wang et al., 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Study on the change of global ecological distribution of Nicotiana tabacum L. based on MaxEnt model

Jia,

Sun,

et al. 2024

Front. Plant Sci.

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Nicotiana tabacum L. (tobacco) has extremely high economic value, medicinal value, scientific research value and some other uses. Though it has been widely cultivated throughout the world, classification and change of its suitable habitats is not that clear, especially in the context of global warming. In order to achieve rational cultivation and sustainable development of tobacco, current (average from 1970-2000) and future (2070, average from 2061-2080) potential suitable habitats of Nicotiana tabacum L. were forecasted with MaxEnt model and ArcGIS platform based on 854 occurrence data and 22 environmental factors in this study. The results revealed that mean temperature of warmest quarter (bio10), annual precipitation (bio12), solar radiation in September (Srad9), and clay content (CLAY) were the four decisive environment variables for the distribution of Nicotiana tabacum L. Under current climate conditions, suitable habitats of Nicotiana tabacum L. were mainly distributed in south-central Europe, south-central North America, most parts of South America, central Africa, south and southeast Asia, and southeast coast of Australia, and only 13.7% of these areas were highly suitable. By the year 2070, suitable habitats under SSP1-2.6, SSP3-7.0, and SSP5-8.5 climate scenarios would all increase with the largest increase found under SSP3-7.0 scenario, while suitable habitats would reduce under SSP2-4.5 climate scenario. Globally, the center of mass of suitable habitats would migrate to southeast to varying degrees within Libya under four different climate scenarios. The emergence of new habitats and the disappearance of old habitats would all occur simultaneously under each climate scenario, and the specific changes in each area, combined with the prediction results under current climate conditions, will provide an important reference for the adjustment of agronomic practices and rational cultivation of Nicotiana tabacum L. both currently and in the future.

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