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Ecological Niche Modelling Predicts Southward Expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), Vector of Leishmania (Leishmania) amazonensis in South America, under Climate Change.

Carvalho BM, Rangel EF, Ready PD, Vale MM - PLoS ONE (2015)

Bottom Line: Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases.The use of species absence data substantially improved model performance.These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region.

View Article: PubMed Central - PubMed

Affiliation: Laboratório de Vertebrados, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.

ABSTRACT
Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector's climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest). Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: "stabilization" and "high increase". Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador, Colombia and Venezuela. These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region.

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Climate suitability for Lutzomyia flaviscutellata in South America under current conditions from six modelling algorithms.Continuous output: stretched values of climate suitability. Binary output: suitable areas after the application of the threshold that maximizes model sensitivity and specificity.
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pone.0143282.g002: Climate suitability for Lutzomyia flaviscutellata in South America under current conditions from six modelling algorithms.Continuous output: stretched values of climate suitability. Binary output: suitable areas after the application of the threshold that maximizes model sensitivity and specificity.

Mentions: Model performance ranged from fair to excellent (0.4 < TSS > 1; 0.3 < kappa > 1, Fig 1). Outputs with higher values of both TSS and kappa were selected to produce the ensemble models; all of them were significantly better than random predictions (binary probabilities, p< 0.001). For predictions under current climatic conditions, the different algorithms showed a common general pattern with some regional variation (Fig 2). Testing different threshold rule methods showed differences in binary outputs, more evidently in DOMAIN and GLM, while in Random Forests the difference could barely be noticed (S4 Fig). Masking out the predictor values outside the ranges of the input variables showed that models produced by all algorithms had little to no areas of model extrapolation (S5 Fig).


Ecological Niche Modelling Predicts Southward Expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), Vector of Leishmania (Leishmania) amazonensis in South America, under Climate Change.

Carvalho BM, Rangel EF, Ready PD, Vale MM - PLoS ONE (2015)

Climate suitability for Lutzomyia flaviscutellata in South America under current conditions from six modelling algorithms.Continuous output: stretched values of climate suitability. Binary output: suitable areas after the application of the threshold that maximizes model sensitivity and specificity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664266&req=5

pone.0143282.g002: Climate suitability for Lutzomyia flaviscutellata in South America under current conditions from six modelling algorithms.Continuous output: stretched values of climate suitability. Binary output: suitable areas after the application of the threshold that maximizes model sensitivity and specificity.
Mentions: Model performance ranged from fair to excellent (0.4 < TSS > 1; 0.3 < kappa > 1, Fig 1). Outputs with higher values of both TSS and kappa were selected to produce the ensemble models; all of them were significantly better than random predictions (binary probabilities, p< 0.001). For predictions under current climatic conditions, the different algorithms showed a common general pattern with some regional variation (Fig 2). Testing different threshold rule methods showed differences in binary outputs, more evidently in DOMAIN and GLM, while in Random Forests the difference could barely be noticed (S4 Fig). Masking out the predictor values outside the ranges of the input variables showed that models produced by all algorithms had little to no areas of model extrapolation (S5 Fig).

Bottom Line: Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases.The use of species absence data substantially improved model performance.These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region.

View Article: PubMed Central - PubMed

Affiliation: Laboratório de Vertebrados, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.

ABSTRACT
Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector's climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest). Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: "stabilization" and "high increase". Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador, Colombia and Venezuela. These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region.

Show MeSH
Related in: MedlinePlus