Modeling potential habitats and predicting habitat connectivity for Leucanthemum vulgare Lam. in northwestern rangelands of Iran

Khanghah, Sahar Samadi; Moameri, Mehdi; Ghorbani, Ardavan; Mostafazadeh, Raoof; Biswas, Asim

doi:10.1007/s10661-021-09716-5

Cited by 5 publications

(3 citation statements)

References 38 publications

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“…As a specialized form of multiple regression, LR is particularly adept at analyzing discrete dependent variables. Presence-absence models, like logistic regression, frequently yield ecologically sound relationships, providing valuable insights into species distribution dynamics 61 , 62 . In this study, the logistic regression model, as represented by Eq.…”

Section: Methodsmentioning

confidence: 99%

Modeling habitat suitability of Dorema ammoniacum D Don. in the rangelands of central Iran

Zare,

Moameri,

Ghorbani

et al. 2024

Sci Rep

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The purpose of this study was to evaluate the predictive accuracy of habitat suitability models, identifying the potential distribution range of Dorema ammoniacum, and its habitat requirements in the rangelands of Yazd province, central Iran. Bafgh, Mehriz and Nadoushan, were three habitats that were identified, and sampling was conducted in each habitat using a random-systematic method. A set of 10 plots were established (at equal distances) along 350 m long 18 transects. Soil samples (two depths: 0–30 and 30–60 cm from 36 profiles) were collected and measured in the laboratory. Elevation, slope, and aspect maps were derived, and climate information was collected from nearby meteorological stations. The habitat prediction of the species was modeled using Logistic Regression (LR), Maximum Entropy (MaxEnt), and Artificial Neural Network (ANN). The Kappa coefficient and the area under the curve (AUC) were calculated to assess the accuracy of the forecasted maps. The LR model for habitat prediction of the studied species in Mehriz (K = 0.67) and Nadoushan (K = 0.56) habitats were identified as good. The MaxEnt model predicted the habitat distribution for the selected species in Bafgh and Mehriz habitats as excellent (K = 0.89, AUC = 0.76, K = 0.89, AUC = 0.98), and in the Nadoushan habitat as very good (K = 0.78, AUC = 0.85). However, the ANN model predicted Bafgh and Nadoushan habitats as excellent and Mehriz habitat as very good (K = 0.87, K = 0.90, and K = 0.63, respectively). In general, in order to protect species D. ammoniacum, the development of its habitats in other areas of Yazd province and the habitats under study in conservation programs should be given priority.

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Section: Methodsmentioning

confidence: 99%

Modeling habitat suitability of Dorema ammoniacum D Don. in the rangelands of central Iran

Zare,

Moameri,

Ghorbani

et al. 2024

Sci Rep

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show abstract

“…We derived the potential distribution from the best model, using the average performance evaluation indicators (AUC), partial ROC (receiver operating characteristic), omission rate, and the optimal complexity parameter (AIC‐Akaike Information Criterion; Bozdogan, 1987 ; Elith & Leathwick, 2009 ; Gutiérrez et al, 2018 ). We followed a logistic threshold for training presence clipping which corresponds to the 10% of data with the lowest probability value which is commonly used in conservation studies (Abba et al, 2012 ; Ancillotto et al, 2019 ; Khanghah et al, 2022 ). In addition, we used the trimming threshold (~24%–26%) of the present model, which approximates the distribution of the species according to Williams‐Linera et al ( 2000 ) and Rodríguez‐Ramírez et al ( 2021 ).…”

Section: Methodsmentioning

confidence: 99%

The effect of climate change on Arcto‐Tertiary Mexican beech forests: Exploring their past, present, and future distribution

Ames-Martínez

Luna‐Vega

Dieringer

et al. 2022

Ecology and Evolution

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Fagus mexicana Martínez (Mexican beech) is an endangered Arcto‐Tertiary Geoflora tree species that inhabit isolated and fragmented tropical montane cloud forests in eastern Mexico. Exploring past, present, and future climate change effects on the distribution of Mexican beech involves the study of spatial ecology and temporal patterns to develop conservation plans. These are key to understanding the niche conservatism of other forest communities with similar environmental requirements. For this study, we used species distribution models by combining occurrence records, to assess the distribution patterns and changes of the past (Last Glacial Maximum), present (1981–2010), and future (2040–2070) periods under two climate scenarios (SSP 3‐7.0 & SSP 5‐8.5). Next, we determined the habitat suitability and priority conservation areas of Mexican beech as associated with topography, land cover use, distance to the nearest town, and environmental variables. By considering the distribution of Mexican beech during different periods and under different climate scenarios, our study estimated that high‐impact areas of Mexican beech forests were restricted to specific areas of the Sierra Madre Oriental that constitute refugia from the Last Glacial Maximum. Regrettably, our results exhibited that Mexican beech distribution has decreased 71.3% since the Last Glacial Maximum and this trend will for the next 50 years, migrating to specific refugia at higher altitudes. This suggests that the states of Hidalgo, Veracruz, and Puebla will preserve the habitat suitability features as ecological refugia, related to high moisture and north‐facing slopes. For isolated and difficult‐to‐access areas, the proposed methods are powerful tools for relict‐tree species, which deserve further conservation.

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“…Compared with other SDMs, the advantage of the MaxEnt model is that it has a higher prediction accuracy and reliability when applied to the “existence-only” data of species occurrence. In addition, the MaxEnt model also had good prediction ability when a small amount of species distribution data were available [ 33 , 34 , 35 , 37 , 38 , 39 , 40 , 41 ]. However, previous studies have shown that the default parameters of the MaxEnt model may not be optimal for predicting species distribution [ 15 , 40 , 42 , 43 ].…”

Section: Introductionmentioning

confidence: 99%

Potentially Suitable Geographical Area for Monochamus alternatus under Current and Future Climatic Scenarios Based on Optimized MaxEnt Model

Gao

Liu

Zhao

et al. 2023

Insects

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M. alternatus is considered to be an important and effective insect vector for the spread of the important international forest quarantine pest, Bursaphelenchus xylophilus. The precise determination of potential suitable areas of M. alternatus is essential to monitor, prevent, and control M. alternatus worldwide. According to the distribution points and climatic variables, the optimized MaxEnt model and ArcGIS were used to predict the current and future potentially suitable areas of M. alternatus worldwide. The optimized MaxEnt model parameters were set as feature combination (FC) = LQHP and β = 1.5, which were determined by the values of AUCdiff, OR10, and ΔAICc. Bio2, Bio6, Bio10, Bio12, and Bio14 were the dominant bioclimatic variables affecting the distribution of M. alternatus. Under the current climate conditions, the potentially suitable habitats of M. alternatus were distributed across all continents except Antarctica, accounting for 4.17% of the Earth’s total land area. Under future climate scenarios, the potentially suitable habitats of M. alternatus increased significantly, spreading to a global scale. The results of this study could provide a theoretical basis for the risk analysis of the global distribution and dispersal of M. alternatus as well as the precise monitoring and prevention of this beetle.

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Modeling potential habitats and predicting habitat connectivity for Leucanthemum vulgare Lam. in northwestern rangelands of Iran

Cited by 5 publications

References 38 publications

Modeling habitat suitability of Dorema ammoniacum D Don. in the rangelands of central Iran

Modeling habitat suitability of Dorema ammoniacum D Don. in the rangelands of central Iran

The effect of climate change on Arcto‐Tertiary Mexican beech forests: Exploring their past, present, and future distribution

Potentially Suitable Geographical Area for Monochamus alternatus under Current and Future Climatic Scenarios Based on Optimized MaxEnt Model

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