Impact of climate factors on future distributions of Paeonia ostii across China estimated by MaxEnt

Zhang, Keliang; Yin, Zhiyong; Zhou, Chao; Meng, Jiasong; Sun, Jianqi; Zhou, Tianhua; Tao, Jun

doi:10.1016/j.ecoinf.2019.01.004

Cited by 61 publications

(50 citation statements)

References 23 publications

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“…An average of AUC = 0.95 was achieved, and considering models with "excellent" predictive performance (AUC = 0.914-0.985), these are equal to or more accurate than those reported in the literature for plant species such as Paeonia veitchii (0.958) [55], Paeonia ostii (0.960) [54], Daphne mucronata (0.95) [87], Rosa arabica (0.968 ± 0.009) [20], Aristolochia gigantea (0.924) [88], Justicia adhatoda (0.923) [57], Garcinia indica (mean 0.959 ± 0.023) [89], Euphorbia antisyphilitica (0.920 ± 0.039) [90], Abies pindrow (0.970 ± 0.019), and Betula utilis (0.984 ± 0.008) [28]. Even the "good" performance of C. montana (AUC = 0.868) is equal to or more accurate than those of Quercus sp.…”

Section: Discussionmentioning

confidence: 64%

“…Pearson's correlation coefficients (r) between the 19 bioclimatic variables, 3 topographic variables, 3 soil variables, and solar radiation were calculated in the R software (version 3.6) for multi-collinearity tests. The variables whose correlation coefficients were greater than 0.8 were eliminated not only to avoid the violation of statistical assumptions, but also to avoid model predictions induced by multi-collinearity between variables [54][55][56][57]. First, values of Euclidean distances were introduced from value extraction through the k-means classification tool using the factoextra package.…”

Section: Variable Correlation and Clusteringmentioning

confidence: 99%

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Distribution Models of Timber Species for Forest Conservation and Restoration in the Andean-Amazonian Landscape, North of Peru

et al. 2020

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The Andean-Amazonian landscape has been universally recognized for its wide biodiversity, and is considered as global repository of ecosystem services. However, the severe loss of forest cover and rapid reduction of the timber species seriously threaten this ecosystem and biodiversity. In this study, we have modeled the distribution of the ten most exploited timber forest species in Amazonas (Peru) to identify priority areas for forest conservation and restoration. Statistical and cartographic protocols were applied with 4454 species records and 26 environmental variables using a Maximum Entropy model (MaxEnt). The result showed that the altitudinal variable was the main regulatory factor that significantly controls the distribution of the species. We found that nine species are distributed below 1000 m above sea level (a.s.l.), except Cedrela montana, which was distributed above 1500 m a.s.l., covering 40.68%. Eight of 10 species can coexist, and the species with the highest percentage of potential restoration area is Cedrela montana (14.57% from Amazonas). However, less than 1.33% of the Amazon has a potential distribution of some species and is protected under some category of conservation. Our study will contribute as a tool for the sustainable management of forests and will provide geographic information to complement forest restoration and conservation plans.

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Section: Discussionmentioning

confidence: 64%

Section: Variable Correlation and Clusteringmentioning

confidence: 99%

Distribution Models of Timber Species for Forest Conservation and Restoration in the Andean-Amazonian Landscape, North of Peru

et al. 2020

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“…MaxEnt has the advantages of simple operation, fast operation speed, and good prediction results. MaxEnt can perform better than other models when faced with small sample sizes [ 13 , 38 , 39 , 40 ].…”

Section: Methodsmentioning

confidence: 99%

Predicting the Suitable Geographical Distribution of Sinadoxa Corydalifolia under Different Climate Change Scenarios in the Three-River Region Using the MaxEnt Model

Huang

Chen

et al. 2020

Plants

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Sinadoxa corydalifolia is a perennial grass with considerable academic value as a rare species owing to habitat destruction and a narrow distribution. However, its distribution remains unclear. In this study, we predicted the distribution of Sinadoxa corydalifolia in the three-river region (the source of the Yangtze River, Yellow River, and Lancang River) under the context of climate change using the maximum entropy (MaxEnt) model. Under the current climate scenario, the suitable distribution mainly occurred in Yushu County and Nangqian County. The suitable distribution area of Sinadoxa corydalifolia covered 3107 km2, accounting for 0.57% of the three-river region. The mean diurnal air temperature range (Bio2), temperature seasonality (Bio4), and mean air temperature of the driest quarter (Bio9) contributed the most to the distribution model for Sinadoxa corydalifolia, with a cumulative contribution of 81.4%. The highest suitability occurred when air temperature seasonality (Bio4) ranged from 6500 to 6900. The highest suitable mean air temperature of the driest quarter ranged from −5 to 0 °C. The highest suitable mean diurnal temperature (Bio2) ranged from 8.9 to 9.7 °C. In future (2041–2060) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: representative concentration pathway (RCP)26 (6171 km2) > RCP45 (6017 km2) > RCP80 (4238 km2) > RCP60 (2505 km2). In future (2061–2080) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: RCP26 (18,299 km2) > RCP60 (11,977 km2) > RCP45 (10,354 km2) > RCP80 (7539 km2). In general, the suitable distribution will increase in the future. The distribution area of Sinadoxa corydalifolia will generally be larger under low CO2 concentrations than under high CO2 concentrations. This study will facilitate the development of appropriate conservation measures for Sinadoxa corydalifolia in the three-river region.

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“…However, it is usually used as low value-added fertilizer or animal feed. It has been reported that PSP has favorable amino acid profiles and desirable physicochemical properties [ 2 , 8 ]. The essential amino acids of PSP account for 39.62% (( E / T ) essential amino acids to total amino acids), which is equal to soybean protein ( E / T , 39.33%) [ 9 ] and higher than FAO/WHO-suggested value ( E / T , 36.00%) [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Seed Proteomic Profiles of Three Paeonia Varieties and Evaluation of Peony Seed Protein as a Food Product

Ren

Shi

Xue

et al. 2020

BioMed Research International

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Peony (Paeonia) has high ornamental, edible, and medicinal values. In order to distinguish seeds varieties, describe the proteomic profiles correlated with stress tolerance, and evaluate peony seed protein (PSP) as a functional food product, we characterized the seed protein profiles of these three species and their glucosidase inhibition activities. Results showed that the intensity of protein bands in sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and specific protein ID (especially for specifically expressed proteins (SEPs)) was effective to distinguish these peony seed varieties. Proteomic analysis of the three species showed that P. ostii “Fengdan” has heat and pathogen tolerance-related proteins, while P. rockii has higher content of proteins related to cold resistance, which were all highly consistent with their adaptation of heat or cold habitat. Moreover, stress-related proteins were also accumulated in P. lactiflora Pall “Hangshao” seeds, showing its potential for stress resistance. Further protein analysis showed that the primary composition of PSP was albumin and globulin. And the solubility of PSP was good. Furthermore, PSP also showed high glucosidase inhibition activity, indicating that PSP might have some potential function for the remission of hyperglycemia. And P. ostii “Fengdan” seeds may be a better source for protein production than seeds of the other two species in terms of protein solubility and the content of total protein, albumin, and globulin. In addition, an optimal protocol of microwave-assisted alkali extraction was developed to produce PSP. In conclusion, the evaluated stress-related proteins in three peony seed species by proteomic analysis quite agreed with their adaptation of heat or cold stress; proteomics could also be a very useful tool for distinguishing species in the production; and peony seeds may be a good source for protein production.

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Impact of climate factors on future distributions of Paeonia ostii across China estimated by MaxEnt

Cited by 61 publications

References 23 publications

Distribution Models of Timber Species for Forest Conservation and Restoration in the Andean-Amazonian Landscape, North of Peru

Distribution Models of Timber Species for Forest Conservation and Restoration in the Andean-Amazonian Landscape, North of Peru

Predicting the Suitable Geographical Distribution of Sinadoxa Corydalifolia under Different Climate Change Scenarios in the Three-River Region Using the MaxEnt Model

Seed Proteomic Profiles of Three Paeonia Varieties and Evaluation of Peony Seed Protein as a Food Product

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