Modelling potential habitats for Artemisia sieberi and Artemisia aucheri in Poshtkouh area, central Iran using the maximum entropy model and geostatistics

Hosseini, Seyed Zeynalabedin; Kappas, Martin; Chahouki, Mohammad Ali Zare; Gerold, Gerhard; Erasmi, Stefan; Emam, Ammar Rafiei

doi:10.1016/j.ecoinf.2013.05.002

Cited by 38 publications

(32 citation statements)

References 33 publications

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“…The results of MaxEnt modeling provided key information about the environmental tolerances of the species that can be used for protecting susceptible habitats from future invasion and impacts of climate change. Also, conservation planners and rangelands managers of Iran could use the outputs of this research as base information for grazing management and rangelands rehabilitation (Hosseini et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

An evaluation of predictive habitat models performance of plant species in Hoze soltan rangelands of Qom province

Sahragard

Chahouki

2015

Ecological Modelling

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Section: Discussionmentioning

confidence: 99%

An evaluation of predictive habitat models performance of plant species in Hoze soltan rangelands of Qom province

Sahragard

Chahouki

2015

Ecological Modelling

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“…Some variables, such as soil EC and pH, made a small contribution to distribution of habitats compared with other environmental variables. The importance of soil properties in distribution of plant habitats has been emphasized by many studies Abd El-Ghani et al, 2011;Tatian et al, 2011;Hosseini et al, 2013;Piri Sahragard and Zare Chahouki, 2015). In addition, in some geographical conditions the role of physiographic factors such as altitude and slope has been emphasized in occurrence of plant species (Maltez-Mouro et al, 2005;Abdel Khalik et al, 2013;Hosseini et al, 2013;Piri Saharagard and Zare Chahouki, 2016a).…”

Section: Discussionmentioning

confidence: 99%

“…The importance of soil properties in distribution of plant habitats has been emphasized by many studies Abd El-Ghani et al, 2011;Tatian et al, 2011;Hosseini et al, 2013;Piri Sahragard and Zare Chahouki, 2015). In addition, in some geographical conditions the role of physiographic factors such as altitude and slope has been emphasized in occurrence of plant species (Maltez-Mouro et al, 2005;Abdel Khalik et al, 2013;Hosseini et al, 2013;Piri Saharagard and Zare Chahouki, 2016a). Scrutinizing the relationship between environmental variables and species distribution indicates that in flat parts of the studied area where Haloxylon persicum, Zygophyllum eurypterum, and Artemisia sieberi habitats were located the role of soil variables in plant distribution was greater.…”

Section: Discussionmentioning

confidence: 99%

“…Predictive models are cause and effect tools that construct a relationship between real distribution patterns of plants and environmental variables for prediction of plant species distribution (Elith and Graham, 2009). In addition, predictive models are widely used in wildlife management, determination of suitability of a habitat for a specific species, and rangeland improvement projects (Araujo and Guisan, 2006;Zare Chahouki and Khalasi Ahvazi, 2012;Hosseini et al, 2013;Ardestani et al, 2015;Piri Sahragard and Zare Chahouki, 2016b).…”

Section: Introductionmentioning

confidence: 99%

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A comparison of logistic regression and maximum entropy for distribution modeling of range plant species (a case study in rangelands of western Taftan, southeastern Iran)

Sahragard¹,

Ajorlo²

2018

Turk J Bot

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This study aimed to compare the efficiency of logistic regression and maximum entropy models for distribution modelling of plant species habitats in the rangelands of western Taftan, southeastern Iran. Vegetation cover was sampled using a systematicrandomized method. Soils were sampled at 0-30 and 30-60 cm depths through digging of eight soil profiles. The agreement between predictive maps generated by models with documented maps of habitats indicated that logistic regression was able to predict the distribution of Artemisia aucheri and Artemisia sieberi habitats at excellent (kappa value = 0.95) and weak (kappa value = 0.39) levels, respectively. On the other hand, the agreement between predicted maps generated by maximum entropy with documented maps was very good for Amygdalus scoparia and Artemisia aucheri habitats (kappa value = 0.82 and 0.76, respectively), and weak for Artemisi aucheri (kappa value = 0.55). This study indicates that logistic regression and maximum entropy methods had the same efficiency in distribution modelling of plant species with a limited ecological niche. However, the maximum entropy model can receive priority in distribution prediction of plant species with a limited ecological niche because it uses only presence data of plants and a small dataset.

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“…Se ha propuesto que cambios en el clima podrían ocasionar cambios en la fenología y abundancia de las especies, en sus patrones de distribución geográfica y en la composición de la comunidad o declives poblacionales (Araújo et al, 2006;Gibbon et al, 2008;Ihlow et al, 2012). Un gran número de trabajos han examinado la relación entre la distribución de las especies y el clima (e.g., Peterson y Vieglais, 2001;Escalante et al, 2007;Jones et al, 2012;Hosseini et al, 2013) y los posibles efectos del cambio climático global sobre la conformación de las áreas de distribución de las especies (e.g., Beaumont y Hughes, 2002;Araújo et al, 2006;Bystriakova et al, 2014;McDowell et al, 2014). El efecto del cambio climático no será homogéneo en todos los taxa, ni en todas las zonas geográficas, y dependerá de la tolerancia fisiológica de los organismos (Beaumont y Hughes, 2002).…”

Section: Introductionunclassified

Potential Distribution of Podocnemis lewyana (Reptilia:Podocnemididae) and Its Possible Fluctuation Under Different Global Climate Change Scenarios

Ortiz-Yusty¹,

Restrepo²,

Páez³

2014

Acta biol. colomb.

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RESUMENEn este estudio se implementó el modelaje de distribución de especies para establecer el rango de distribución potencial de Podocnemis lewyana, explorar los componentes del clima que pueden influenciar dicha distribución y evaluar posibles fluctuaciones de su distribución bajo escenarios de clima futuro. Los modelos obtenidos predicen una distribución continua de sur a norte por todo el río Magdalena, desde los municipios de Rivera y Palermo en el departamento de Huila, hasta los departamentos de Atlántico y Magdalena en el norte. La temperatura fue el elemento del clima que más influyó en la distribución de P. lewyana; esta especie tiende a estar presente en climas cálidos y con poca variabilidad en la temperatura. El modelo de distribución transferido a los escenarios de clima futuro predicen un aumento en el rango geográfico de P. lewyana. Sin embargo, teniendo en cuenta las preferencias de hábitat de esta especie y su fuerte asociación con los cuerpos de agua, este resultado debe tomarse con cautela, dado que el modelo solo tuvo en cuenta variables climáticas terrestres. Dadas las características de historia de vida de esta especie (presencia de determinación sexual dependiente de la temperatura, alta temperatura pivotal y un rango de transición de temperatura muy estrecho), y el efecto negativo de los cambios en los regímenes hidrológicos en la mortalidad embrionaria, la expansión del área potencial de P. lewyana en el futuro no significa que esta especie no vaya a verse afectada por el cambio climático global.Palabras clave: Maxent, modelación de nicho, variables ambientales. ABSTRACTWe implemented a species distribution modelling approach to establish the potential distribution of Podocnemis lewyana, to explore the climatic factors that may influence the species' distribution and to evaluate possible changes in distribution under future climate scenarios. The distribution models predicted a continuous distribution from south to north along the Magdalena River, from Rivera and Palermo in the department of Huila to the departments of Atlántico and Magdalena in the north. Temperature was the variable most influential in the distribution of P. lewyana; this species tends to be present in warm regions with low temperature variability. The distribution model predicted an increase in the geographic range of P. lewyana under climate change scenarios. However, taking into account the habitat preferences of this species and its strong

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Modelling potential habitats for Artemisia sieberi and Artemisia aucheri in Poshtkouh area, central Iran using the maximum entropy model and geostatistics

Cited by 38 publications

References 33 publications

An evaluation of predictive habitat models performance of plant species in Hoze soltan rangelands of Qom province

An evaluation of predictive habitat models performance of plant species in Hoze soltan rangelands of Qom province

A comparison of logistic regression and maximum entropy for distribution modeling of range plant species (a case study in rangelands of western Taftan, southeastern Iran)

Potential Distribution of Podocnemis lewyana (Reptilia:Podocnemididae) and Its Possible Fluctuation Under Different Global Climate Change Scenarios

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