Using MaxEnt Model to Guide Marsh Conservation in the Nenjiang River Basin, Northeast China

Wang, Zhiliang; Bai, Zhongke; Zhang, Xuezhen; Tian, Hongxu

doi:10.1007/s11769-019-1082-7

Cited by 9 publications

(4 citation statements)

References 49 publications

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“…Authors have used this method to support analysis of the urbanization process ( 34 , 35 ) and urban sprawl ( 36 , 34 ) and to identify environmental preservation areas ( 37 ). These studies considered Chinese cities, using data from environmental ( 37 ), socioeconomic ( 34 , 37 , 38 ), and urban infrastructure ( 34 ) with the results supporting legislative propositions concerning land use ( 35 ) and projections of the phenomena studied ( 37 ).…”

mentioning

confidence: 81%

Applying the Maximum Entropy Model to Urban Freight Transportation Planning: An Exploratory Analysis of Warehouse Location in the Belo Horizonte Metropolitan Region

Oliveira

Nóbrega

2021

Transportation Research Record: Journal of the Transportation R

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In Brazil, neglect and lack of data have complicated urban freight transportation planning. Belo Horizonte is one such example, where the administration’s disregard for urban freight transport has led to multiple negative externalities. Using the maximum entropy method, this study analyzed the influence of urban planning factors on warehouse location in the Belo Horizonte Metropolitan Region. Warehouse location was analyzed using 19 factors, with the results recorded on a map of logistic probabilities concerning locating warehouses. Given this is exploratory research, the model was validated by visual comparison to address the four hypotheses: (i) warehouses tend to be located near roads and railroads; (ii) warehouses tend to be located close to their consumer markets; (iii) warehouses tend to be located in urban areas; and (iv) warehouses tend to be located next to each other, creating clusters. These hypotheses were based on the extant literature and confirmed from observations of the Belo Horizonte Metropolitan Region. The results also demonstrated that the maximum entropy method can suitably model freight transportation in support of urban planning policy.

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mentioning

confidence: 81%

Applying the Maximum Entropy Model to Urban Freight Transportation Planning: An Exploratory Analysis of Warehouse Location in the Belo Horizonte Metropolitan Region

Oliveira

Nóbrega

2021

Transportation Research Record: Journal of the Transportation R

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“…Among them, the soil type data was set to be categorical, while the other 8 environmental variables were set to be continuous. For the distribution data, 25% was set as the test set and 75% is the training set; the selection was random by the model (Wang, Zhang et al., 2019). The knife‐cutting method was used to calculate the importance of each of the environmental variables.…”

Section: Methodsmentioning

confidence: 99%

Response of Camellia sinensis var.assamica suitable areas to climate change—Evidence from Yunnan province (China)

Gao

Dou³

et al. 2023

Agronomy Journal

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This study is an attempt to explore the regional resilience of Camellia sinensis var.assamica cultivation with climate change in Yunnan Province and delineate the scope of its potential suitable areas at three levels. Based on the maximum entropy (MaxEnt) model, combined with the distribution data of C. sinensis var.assamica species and environmental variable data, the main influencing factors of its distribution were figured out, and the suitable growing areas of C. sinensis var.assamica under the current and future climate conditions were predicted. The results show (1) the MaxEnt model can be deliberately constructed for the prediction of the suitable distribution areas of C. sinensis var.assamica in Yunnan. The dominant environmental factors affecting the planting of it are the average rainfall in October, the soil type and the mountain slope, having a contribution ratio of 84.9% with a total. (2) Under the current climate condition, the areas suitable for C. sinensis var.assamica are mainly in the west, southwest and south regions of Yunnan. The total suitable areas account for approximately 37.55% of Yunnan. The highly suitable areas are surrounded by moderately suitable areas which are surrounded by low suitable areas. (3) In the scenarios of RCP4.5 and RCP8.5, the total suitable area shows an increasing trend, reaching 41.76% and 52.30% of the land area of Yunnan Province, respectively. With higher carbon emissions, the increase in suitable area will be greater. The centroid of the suitable area would migrate toward higher altitude and higher latitude. The growers can adjust the suitable areas according to the local climate and terrain conditions and the conclusions of this paper to cope with impact of climate change on the yield of C. sinensis var.assamica.

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“…Species distribution models (SDMs) are a group of models that predict the potential geographic distribution pattern of a species from a relatively small set of records (Elith et al 2006, Elith and Leathwick 2009, Guisan et al 2017, Srivastava et al 2019, Lissovsky et al 2021). The development of SDMs has considerably benefited the study of ecology (Scattolini et al 2018), evolution (Diniz‐Filho et al 2010, Wang et al 2016), and biodiversity conservation (Smith et al 2012, Wang et al 2019, Kaky et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Mikrubi: a model for species distributions using region‐based records

2023

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Many species occurrence records from specimens and publications are based on regions such as administrative units. These region‐based records are accessible and dependable, and sometimes they are the only available data source; however, few species distribution models accept such data as direct input. In this paper, we present a method named Mikrubi for robust prediction of species distributions from region‐based occurrence data and a Julia package implementing the algorithms. The package ‘Mikrubi' requires a map describing disjoint regions, climatic raster layers, and a list of occupied regions. Mikrubi then rasterizes the regions, reduces the environmental dimensionality, parameterizes the niche, and finally estimates the parameters by maximizing the likelihood. In a simulation study, we find Mikrubi effective in accurate estimation in most cases; in a case study of Allium wallichii in China, Mikrubi significantly outperforms four modeling strategies that adapt region‐based records to conventional models according to different principles. The package has many prospective applications in addition to modeling distributions on region‐based records: 1) it accepts supplementary coordinates; 2) it is a new solution for distribution modeling using deviated coordinates; and 3) its probabilistic region‐based outputs have special uses in conservation and biodiversity science.

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Using MaxEnt Model to Guide Marsh Conservation in the Nenjiang River Basin, Northeast China

Cited by 9 publications

References 49 publications

Applying the Maximum Entropy Model to Urban Freight Transportation Planning: An Exploratory Analysis of Warehouse Location in the Belo Horizonte Metropolitan Region

Applying the Maximum Entropy Model to Urban Freight Transportation Planning: An Exploratory Analysis of Warehouse Location in the Belo Horizonte Metropolitan Region

Response of Camellia sinensis var.assamica suitable areas to climate change—Evidence from Yunnan province (China)

Mikrubi: a model for species distributions using region‐based records

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