The impact of climate change on the geographical distribution of two vectors of Chagas disease: implications for the force of infection.
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ABSTRACT:
SUBMITTER: Medone P
PROVIDER: S-EPMC4342964 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Mepraia gajardoi and Mepraia spinolai are endemic triatomine vector species of Trypanosoma cruzi, a parasite that causes Chagas disease. These vectors inhabit arid, semiarid and Mediterranean areas of Chile. Mepraia gajardoi occurs from 18° to 25°S, and M. spinolai from 26° to 34°S. Even though both species are involved in T. cruzi transmission in the Pacific side of the Southern Cone of South America, no study has modelled their distributions at a regional scale. Therefore, the aim of this study is to estimate the potential geographical distribution of M. spinolai and M. gajardoi under current and future climate scenarios. METHODS:We used the Maxent algorithm to model the ecological niche of M. spinolai and M. gajardoi, estimating their potential distributions from current climate information and projecting their distributions to future climatic conditions under representative concentration pathways (RCP) 2.6, 4.5, 6.0 and 8.5 scenarios. Future predictions of suitability were constructed considering both higher and lower public health risk situations. RESULTS:The current potential distributions of both species were broader than their known ranges. For both species, climate change projections for 2070 in RCP 2.6, 4.5, 6.0 and 8.5 scenarios showed different results depending on the methodology used. The higher risk situation showed new suitable areas, but the lower risk situation modelled a net reduction in the future potential distribution areas of M. spinolai and M. gajardoi. CONCLUSIONS:The suitable areas for both species may be greater than currently known, generating new challenges in terms of vector control and prevention. Under future climate conditions, these species could modify their potential geographical range. Preventive measures to avoid accidental human vectorial transmission by wild vectors of T. cruzi become critical considering the uncertainty of future suitable areas projected in this study.
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Project description:Xylosandrus compactus and X. crassiusculus are two polyphagous ambrosia beetles originating from Asia and invasive in circumtropical regions worldwide. Both species were recently reported in Italy and further invaded several other European countries in the following years. We used the MaxEnt algorithm to estimate the suitable areas worldwide for both species under the current climate. We also made future projections for years 2050 and 2070 using 11 different General Circulation Models, for 4 Representative Concentration Pathways (2.6, 4.5, 6.0 and 8.5). Our analyses showed that X. compactus has not been reported in all potentially suitable areas yet. Its current distribution in Europe is localised, whereas our results predicted that most of the periphery of the Mediterranean Sea and most of the Atlantic coast of France could be suitable. Outside Europe, our results also predicted Central America, all islands in Southeast Asia and some Oceanian coasts as suitable. Even though our results when modelling its potential distribution under future climates were more variable, the models predicted an increase in suitability poleward and more uncertainty in the circumtropical regions. For X. crassiusculus, the same method only yielded poor results, and the models thus could not be used for predictions. We discuss here these results and propose advice about risk prevention and invasion management of both species.
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Project description:India has witnessed a five-fold increase in dengue incidence in the past decade. However, the nation-wide distribution of dengue vectors, and the impacts of climate change are not known. In this study, species distribution modeling was used to predict the baseline and future distribution of Aedine vectors in India on the basis of biologically relevant climatic indicators. Known occurrences of Aedes aegypti and Aedes albopictus were obtained from the Global Biodiversity Information Facility database and previous literature. Bio-climatic variables were used as the potential predictors of vector distribution. After eliminating collinear and low contributing predictors, the baseline and future prevalence of Aedes aegypti and Aedes albopictus was determined, under three Representative Concentration Pathway scenarios (RCP 2.6, RCP 4.5 and RCP 8.5), using the MaxEnt species distribution model. Aedes aegypti was found prevalent in most parts of the southern peninsula, the eastern coastline, north eastern states and the northern plains. In contrast, Aedes albopictus has localized distribution along the eastern and western coastlines, north eastern states and in the lower Himalayas. Under future scenarios of climate change, Aedes aegypti is projected to expand into unsuitable regions of the Thar desert, whereas Aedes albopictus is projected to expand to the upper and trans Himalaya regions of the north. Overall, the results provide a reliable assessment of vectors prevalence in most parts of the country that can be used to guide surveillance efforts, despite minor disagreements with dengue incidence in Rajasthan and the north east, possibly due to behavioral practices and sampling efforts.
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Project description:Two ecologically and economically important, and threatened Dipterocarp trees Sal (Shorea robusta) and Garjan (Dipterocarpus turbinatus) form mono-specific canopies in dry deciduous, moist deciduous, evergreen, and semievergreen forests across South Asia and continental parts of Southeast Asia. They provide valuable timber and play an important role in the economy of many Asian countries. However, both Dipterocarp trees are threatened by continuing forest clearing, habitat alteration, and global climate change. While climatic regimes in the Asian tropics are changing, research on climate change-driven shifts in the distribution of tropical Asian trees is limited. We applied a bioclimatic modeling approach to these two Dipterocarp trees Sal and Garjan. We used presence-only records for the tree species, five bioclimatic variables, and selected two climatic scenarios (RCP4.5: an optimistic scenario and RCP8.5: a pessimistic scenario) and three global climate models (GCMs) to encompass the full range of variation in the models. We modeled climate space suitability for both species, projected to 2070, using a climate envelope modeling tool "MaxEnt" (the maximum entropy algorithm). Annual precipitation was the key bioclimatic variable in all GCMs for explaining the current and future distributions of Sal and Garjan (Sal: 49.97 ± 1.33; Garjan: 37.63 ± 1.19). Our models predict that suitable climate space for Sal will decline by 24% and 34% (the mean of the three GCMs) by 2070 under RCP4.5 and RCP8.5, respectively. In contrast, the consequences of imminent climate change appear less severe for Garjan, with a decline of 17% and 27% under RCP4.5 and RCP8.5, respectively. The findings of this study can be used to set conservation guidelines for Sal and Garjan by identifying vulnerable habitats in the region. In addition, the natural habitats of Sal and Garjan can be categorized as low to high risk under changing climates where artificial regeneration should be undertaken for forest restoration.
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Project description:Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution.
| S-EPMC3948226 | biostudies-literature
Project description:BackgroundThe medicinal plants of Radix et Rhizoma Nardostachyos include Nardostachys jatamansi and N. chinensis. Traditionally, the two plants have been used to treat many diseases. Because of their special aroma, they are also commonly used in the food and cosmetics industry. Recently, N. jatamansi and N. chinensis have been overexploited due to their economic importance, resulting in a sharp decline in their wild resources. Predicting potential distributions of the genus Nardostachys under different climate scenarios and understanding its preferred habitat are of great significance for their conservation, artificial cultivation, and assessment of their value.MethodsThe Maxent model was used to predict the potential geographical distributions of the genus Nardostachys under current and future climatic conditions based on two representative concentration pathways (RCP2.6 and RCP8.5) for the 2050s and 2070s. These data were used to study the effects of climate variables.ResultsThe results show that the potential distribution of the two species will increase, thus more suitable habitats will be present in China. The suitable habitat for N. chinensis presents a relatively stable growth compared to N. jatamansi. In addition, precipitation plays a crucial role in modeling the effects of climate change on the genus Nardostachys. This study provides theoretical guidance for the cultivation of N. chinensis.
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Project description:Climate change significantly affects geographic distribution of plants pests and diseases worldwide. Understanding the influence of future climate change on the suitable areas of Diaphorina citri (Kuwayama) in our country and taking timely countermeasures are crucial for improving the effectiveness of control of pest. Based on the occurrence points of D. citri and the selected environmental variables, the potential suitable areas of this pest under climate change scenarios in China were predicted by using MaxEnt and GIS tools. Our results showed that the higly suitable area were mainly located in Guangxi, Guangdong, Fujian, Southern Zhejiang, Southern Jiangxi, Eastern Hunan, Southwestern Guizhou, and the area was 43.7?×?104 km2. Areas of moderate and low suitability were centered on areas of high suitability and radiate to the North successively, with an area of 59.28?×?104 km2 and 93.46?×?104 km2 respectively. From current to 2070?s, the areas of the highly suitable areas will increase, and the geometric center of the highly and total suitable areas will move to north under three climate change scenarios.
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Project description:Climate change will significantly affect plant distribution as well as the quality of medicinal plants. Although numerous studies have analyzed the effect of climate change on future habitats of plants through species distribution models (SDMs), few of them have incorporated the change of effective content of medicinal plants. Schisandra sphenanthera Rehd. et Wils. is an endangered traditional Chinese medical plant which is mainly located in the Qinling Mountains. Combining fuzzy theory and a maximum entropy model, we obtained current spatial distribution of quality assessment for S. spenanthera. Moreover, the future quality and distribution of S. spenanthera were also projected for the periods 2020s, 2050s and 2080s under three different climate change scenarios (SRES-A1B, SRES-A2 and SRES-B1 emission scenarios) described in the Special Report on Emissions Scenarios (SRES) of IPCC (Intergovernmental Panel on Climate Change). The results showed that the moderately suitable habitat of S. sphenanthera under all climate change scenarios remained relatively stable in the study area. The highly suitable habitat of S. sphenanthera would gradually decrease in the future and a higher decline rate of the highly suitable habitat area would occur under climate change scenarios SRES-A1B and SRES-A2. The result suggested that in the study area, there would be no more highly suitable habitat areas for S. sphenanthera when the annual mean temperature exceeds 20 °C or its annual precipitation exceeds 1,200 mm. Our results will be influential in the future ecological conservation and management of S. sphenanthera and can be taken as a reference for habitat suitability assessment research for other medicinal plants.
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Project description:Fritillaria species, a well-known Chinese traditional medicine for more than 2,000 years, have become rare resources due to excessive harvesting. In order to balance the economical requirement and ecological protection of Fritillaria species, it is necessary to determine (1) the important environmental variables that were responsible for the spatial distribution, (2) distribution change in response to climate change in the future, (3) ecological niche overlap between various Fritillaria species, and (4) the correlation between spatial distribution and phylogenies as well. In this study, the areas with potential ecological suitability for Fritillaria cirrhosa, Fritillaria unibracteata, and Fritillaria przewalskii were predicted using MaxEnt based on the current occurrence records and bioclimatic variables. The result indicated that precipitation and elevation were the most important environmental variables for the three species. Moreover, the current suitable habitats of F. cirrhosa, F. unibracteata, and F. przewalskii encompassed 681,951, 481,607, and 349,199 km2, respectively. Under the scenario of the highest concentration of greenhouse gas emission (SSP585), the whole suitable habitats of F. cirrhosa and F. przewalskii reach the maximum from 2021 to 2100, while those of F. unibracteata reach the maximum from 2021 to 2100 under the scenario of moderate emission (SSP370) from 2021 to 2100. The MaxEnt data were also used to predict the ecological niche overlap, and thus high overlap occurring among three Fritillaria species was observed. The niche overlap of three Fritillaria species was related to the phylogenetic analysis despite the non-significance (P > 0.05), indicating that spatial distribution was one of the factors that contributed to the speciation diversification. Additionally, we predicted species-specific habitats to decrease habitat competition. Overall, the information obtained in this study provided new insight into the potential distribution and ecological niche of three species for the conservation and management in the future.
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Project description:In the Maasai Steppe, public health and economy are threatened by African Trypanosomiasis, a debilitating and fatal disease to livestock (African Animal Trypanosomiasis -AAT) and humans (Human African Trypanosomiasis-HAT), if not treated. The tsetse fly is the primary vector for both HAT and AAT and climate is an important predictor of their occurrence and the parasites they carry. While understanding tsetse fly distribution is essential for informing vector and disease control strategies, existing distribution maps are old and were based on coarse spatial resolution data, consequently, inaccurately representing vector and disease dynamics necessary to design and implement fit-for-purpose mitigation strategies. Also, the assertion that climate change is altering tsetse fly distribution in Tanzania lacks empirical evidence. Despite tsetse flies posing public health risks and economic hardship, no study has modelled their distributions at a scale needed for local planning. This study used MaxEnt species distribution modelling (SDM) and ecological niche modeling tools to predict potential distribution of three tsetse fly species in Tanzania's Maasai Steppe from current climate information, and project their distributions to midcentury climatic conditions under representative concentration pathways (RCP) 4.5 scenarios. Current climate results predicted that G. m. morsitans, G. pallidipes and G swynnertoni cover 19,225 km2, 7,113 km2 and 32,335 km2 and future prediction indicated that by the year 2050, the habitable area may decrease by up to 23.13%, 12.9% and 22.8% of current habitable area, respectively. This information can serve as a useful predictor of potential HAT and AAT hotspots and inform surveillance strategies. Distribution maps generated by this study can be useful in guiding tsetse fly control managers, and health, livestock and wildlife officers when setting surveys and surveillance programs. The maps can also inform protected area managers of potential encroachment into the protected areas (PAs) due to shrinkage of tsetse fly habitats outside PAs.
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