Maxent-directed field surveys identify new populations of narrowly endemic habitat specialists

Rhoden, Cody M.; Peterman, William E.; Taylor, Christopher A.

doi:10.7287/peerj.preprints.3082v1

Cited by 12 publications

(14 citation statements)

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“…Species distribution models are becoming important tools in public health research 12,17,[68][69][70][71][72][73][74][75][76][77] . We encourage public hearth researchers to apply SDMs in developing snakebite risk map using venomous snakes' habitat suitability as an indicator, especially in data poor regions of the world [51][52][53]78 . Our approach has the potential for practical application in other countries with high snakebite risk.…”

Section: Discussionmentioning

confidence: 99%

Applying species distribution models in public health research by predicting snakebite risk using venomous snakes’ habitat suitability as an indicating factor

Yousefi

Kafash

Khani³

et al. 2020

Sci Rep

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Snakebite envenoming is an important public health problem in Iran, despite its risk not being quantified. This study aims to use venomous snakes’ habitat suitability as an indicator of snakebite risk, to identify high-priority areas for snakebite management across the country. Thus, an ensemble approach using five distribution modelling methods: Generalized Boosted Models, Generalized Additive Models, Maximum Entropy Modelling, Generalized Linear Models, and Random Forest was applied to produce a spatial snakebite risk model for Iran. To achieve this, four venomous snakes’ habitat suitability (Macrovipera lebetinus, Echis carinatus, Pseudocerastes persicus and Naja oxiana) were modelled and then multiplied. These medically important snakes are responsible for the most snakebite incidents in Iran. Multiplying habitat suitability models of the four snakes showed that the northeast of Iran (west of Khorasan-e-Razavi province) has the highest snakebite risk in the country. In addition, villages that were at risk of envenoming from the four snakes were identified. Results revealed that 51,112 villages are at risk of envenoming from M. lebetinus, 30,339 from E. carinatus, 51,657 from P. persicus and 12,124 from N. oxiana. Precipitation seasonality was identified as the most important variable influencing distribution of the P. persicus, E. carinatus and M. lebetinus in Iran. Precipitation of the driest quarter was the most important predictor of suitable habitats of the N. oxiana. Since climatic variables play an important role in shaping the distribution of the four venomous snakes in Iran, thus their distribution may alter with changing climate. This paper demonstrates application of species distribution modelling in public health research and identified potential snakebite risk areas in Iran by using venomous snakes’ habitat suitability models as an indicating factor. Results of this study can be used in snakebite and human–snake conflict management in Iran. We recommend increasing public awareness of snakebite envenoming and education of local people in areas which identified with the highest snakebite risk.

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Section: Discussionmentioning

confidence: 99%

Applying species distribution models in public health research by predicting snakebite risk using venomous snakes’ habitat suitability as an indicating factor

Yousefi

Kafash

Khani³

et al. 2020

Sci Rep

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“…togoi in North America. However, models such as these can be used to inform survey efforts aimed at detection of additional populations of species of interest (Law et al 2017, Rhoden et al 2017. We propose that future survey efforts for Ae.…”

Section: Discussionmentioning

confidence: 99%

Modelling the Putative Ancient Distribution of the Coastal Rock Pool MosquitoAedes togoi

Peach

Matthews

2020

Preprint

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“…Species distribution models are becoming important tools in public health research [12, 94-103]. We encourage public hearth researchers to apply species distribution models in developing snakebite risk map using venomous snakes’ habitat suitability as an indicator, especially in data poor regions of the world [27, 52-54]. Our approach has the potential for practical application in other countries whit high snakebite risk.…”

Section: Discussionmentioning

confidence: 99%

“…They are employed in studying habitat suitability [39-41], identifying environmental drivers of species distribution [42-45] and predicting impacts of climate change on biodiversity [46-51]. SDMs are successfully used to identify suitable habitats of species even in areas with no distribution records [52-54]. Thus, these models can be used to identify suitable habitats of venomous snakes as proxies of snakebite risk [12, 55-57] in data poor regions like Iran.…”

Section: Introductionmentioning

confidence: 99%

Developing snakebite risk model using venomous snake habitat suitability as an indicating factor: An application of species distribution models in public health research

Yousefi

Kafash

Khani³

et al. 2020

Preprint

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22Snakebite envenoming is an important public health problem in Iran, despite its risk not 23 being quantified. This study aims to use venomous snakes' habitat suitability as an 24 indicator of snakebite risk, to identify high-priority areas for snakebite management 25 across the country. Thus, an ensemble approach using five distribution modeling 26 methods: Generalized Boosted Models, Generalized Additive Models, Maximum Entropy 27 Modeling Generalized Linear Models, and Random Forest was applied to produce a 28 spatial snakebite risk model for Iran. To achieve this, four venomous snakes' habitat 29 suitability (Macrovipera lebetina, Echis carinatus, Pseudocerastes persicus and Naja 30 oxiana) were modeled and then multiplied. These medically important snakes are 31 responsible for the most snakebite incidents in Iran. Multiplying habitat suitability 32 models of the four snakes showed that the northeast of Iran (west of Khorasan-e-Razavi 33 province) has the highest snakebite risk in the country. In addition, villages that were at 34 risk of envenoming from the four snakes were identified. Results revealed that 51,112 35 villages are at risk of envenoming from M. lebetina, 30,339 from E. carinatus, 51,657 36 from P. persicus and 12,124 from N. oxiana. This paper demonstrates application of 37 species distribution modeling in public health research and identified potential snakebite 38 risk areas in Iran by using venomous snakes' habitat suitability models as an indicating 39 factor. Results of this study can be used in snakebite and human-snake conflict 40 management in Iran. We recommend increasing public awareness of snakebite 3 41 envenoming and education of local people in areas which identified with the highest 42 snakebite risk. 43 4 62 identifying environmental drivers of species distribution [42−45] and predicting impacts 63 of climate change on biodiversity [46−51]. SDMs are successfully used to identify 64 suitable habitats of species even in areas with no distribution records [52−54]. Thus, 65 these models can be used to identify suitable habitats of venomous snakes as proxies of 66 snakebite risk [12, 55−57] in data poor regions like Iran. 67 The main goal of this paper was to apply SDMs and produce a spatial risk model 68 for snakebite in Iran. To do this, firstly, five distribution modeling methods [38]: 69 Generalized Boosted Models, Generalized Additive Models, Maximum Entropy 70 Modeling Generalized Linear Models, and Random Forest and distribution data of M. 71 lebetina, E. carinatus, P. persicus and N. oxiana were to produce their habitat suitability 72 models. Secondly, the five habitat suitability models [38−58] of each species were 73combined by ensemble approach and finally the four species ensemble models were 74 multiplied to identify potential snakebite risk. We also in addition, number of villages 75 that are at risk of envenoming by these four snakes determined in Iran. 76 77 Materials and methods 78 Occurrence data 79 Distribution records of the M. lebetina, E. carinatus, P. per...

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Maxent-directed field surveys identify new populations of narrowly endemic habitat specialists

Cited by 12 publications

References 0 publications

Applying species distribution models in public health research by predicting snakebite risk using venomous snakes’ habitat suitability as an indicating factor

Applying species distribution models in public health research by predicting snakebite risk using venomous snakes’ habitat suitability as an indicating factor

Modelling the Putative Ancient Distribution of the Coastal Rock Pool MosquitoAedes togoi

Developing snakebite risk model using venomous snake habitat suitability as an indicating factor: An application of species distribution models in public health research

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