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Marine nematodes of the genus Anisakis are common parasites of a wide range of aquatic organisms. Public interest is primarily based on their importance as zoonotic agents of the human Anisakiasis, a severe infection of the gastro-intestinal tract as result of consuming live larvae in insufficiently cooked fish dishes. The diverse nature of external impacts unequally influencing larval and adult stages of marine endohelminth parasites requires the consideration of both abiotic and biotic factors. Whereas abiotic factors are generally more relevant for early life stages and might also be linked to intermediate hosts, definitive hosts are indispensable for a parasite’s reproduction. In order to better understand the uneven occurrence of parasites in fish species, we here use the maximum entropy approach (Maxent) to model the habitat suitability for nine Anisakis species accounting for abiotic parameters as well as biotic data (definitive hosts). The modelled habitat suitability reflects the observed distribution quite well for all Anisakis species, however, in some cases, habitat suitability exceeded the known geographical distribution, suggesting a wider distribution than presently recorded. We suggest that integrative modelling combining abiotic and biotic parameters is a valid approach for habitat suitability assessments of Anisakis, and potentially other marine parasite species.
Background: Worldwide, the number of recorded human hantavirus infections as well as the number of affected countries is on the rise. In Europe, most human hantavirus infections are caused by the Puumala virus (PUUV), with bank voles (Myodes glareolus) as reservoir hosts. Generally, infection outbreaks have been related to environmental conditions, particularly climatic conditions, food supply for the reservoir species and land use. However, although attempts have been made, the insufficient availability of environmental data is often hampering accurate temporal and spatially explicit models of human hantavirus infections.
Methods: In the present study, dynamics of human PUUV infections between 2001 and 2015 were explored using ArcGIS in order to identify spatio-temporal patterns.
Results: Percentage cover of forest area was identified as an important factor for the spatial pattern, whereas beech mast was found explaining temporal patterns of human PUUV infections in Germany. High numbers of infections were recorded in 2007, 2010 and 2012 and areas with highest records were located in Baden-Wuerttemberg (southwest Germany) and North Rhine-Westphalia (western Germany).
Conclusion: More reliable data on reservoir host distribution, pathogen verification as well as an increased awareness of physicians are some of the factors that should improve future human infection risk assessments in Germany.
Environmental niche modelling is an acclaimed method for estimating species’ present or future distributions. However, in marine environments the assembly of representative data from reliable and unbiased occurrences is challenging. Here, we aimed to model the environmental niche and distribution of marine, parasitic nematodes from the Pseudoterranova decipiens complex using the software Maxent. The distribution of these potentially zoonotic species is of interest, because they infect the muscle tissue of host species targeted by fisheries. To achieve the best possible model, we used two different approaches. The land distance (LD) model was based on abiotic data, whereas the definitive host distance (DHD) model included species-specific biotic data. To assess whether DHD is a suitable descriptor for Pseudoterranova spp., the niches of the parasites and their respective definitive hosts were analysed using ecospat. The performance of LD and DHD was compared based on the variables’ contribution to the model. The DHD-model clearly outperformed the LD-model. While the LD-model gave an estimate of the parasites’ niches, it only showed the potential distribution. The DHD-model produced an estimate of the species’ realised distribution and indicated that biotic variables can help to improve the modelling of data-poor, marine species.
Tick-borne diseases are a major health problem worldwide and could become even more important in Europe in the future. Due to changing climatic conditions, ticks are assumed to be able to expand their ranges in Europe towards higher latitudes and altitudes, which could result in an increased occurrence of tick-borne diseases.
There is a great interest to identify potential (new) areas of distribution of vector species in order to assess the future infection risk with vector-borne diseases, improve surveillance, to develop more targeted monitoring program, and, if required, control measures.
Based on an ecological niche modelling approach we project the climatic suitability for the three tick species Ixodes ricinus, Dermacentor reticulatus and Dermacentor marginatus under current and future climatic conditions in Europe. These common tick species also feed on humans and livestock and are vector competent for a number of pathogens.
For niche modelling, we used a comprehensive occurrence data set based on several databases and publications and six bioclimatic variables in a maximum entropy approach. For projections, we used the most recent IPCC data on current and future climatic conditions including four different scenarios of socio-economic developments.
Our models clearly support the assumption that the three tick species will benefit from climate change with projected range expansions towards north-eastern Europe and wide areas in central Europe with projected potential co-occurrence.
A higher tick biodiversity and locally higher abundances might increase the risk of tick-borne diseases, although other factors such as pathogen prevalence and host abundances are also important.
Background: Aedes albopictus and Ae. japonicus are two of the most widespread invasive mosquito species that have recently become established in western Europe. Both species are associated with the transmission of a number of serious diseases and are projected to continue their spread in Europe.
Methods: In the present study, we modelled the habitat suitability for both species under current and future climatic conditions by means of an Ensemble forecasting approach. We additionally compared the modelled MAXENT niches of Ae. albopictus and Ae. japonicus regarding temperature and precipitation requirements.
Results: Both species were modelled to find suitable habitat conditions in distinct areas within Europe: Ae. albopictus within the Mediterranean regions in southern Europe, Ae. japonicus within the more temperate regions of central Europe. Only in few regions, suitable habitat conditions were projected to overlap for both species. Whereas Ae. albopictus is projected to be generally promoted by climate change in Europe, the area modelled to be climatically suitable for Ae. japonicus is projected to decrease under climate change. This projection of range reduction under climate change relies on the assumption that Ae. japonicus is not able to adapt to warmer climatic conditions. The modelled MAXENT temperature niches of Ae. japonicus were found to be narrower with an optimum at lower temperatures compared to the niches of Ae. albopictus.
Conclusions: Species distribution models identifying areas with high habitat suitability can help improving monitoring programmes for invasive species currently in place. However, as mosquito species are known to be able to adapt to new environmental conditions within the invasion range quickly, niche evolution of invasive mosquito species should be closely followed upon in future studies.
The Asian tiger mosquito Aedes albopictus, native to South East Asia, is listed as one of the worst invasive vector species worldwide. In Europe the species is currently restricted to Southern Europe, but due to the ongoing climate change, Ae. albopictus is expected to expand its potential range further northwards. In addition to modelling the habitat suitability for Ae. albopictus under current and future climatic conditions in Europe by means of the maximum entropy approach, we here focused on the drivers of the habitat suitability prediction. We explored the most limiting factors for Aedes albopictus in Europe under current and future climatic conditions, a method which has been neglected in species distribution modelling so far. Ae. albopictus is one of the best-studied mosquito species, which allowed us to evaluate the applied Maxent approach for most limiting factor mapping. We identified three key limiting factors for Ae. albopictus in Europe under current climatic conditions: winter temperature in Eastern Europe, summer temperature in Southern Europe. Model findings were in good accordance with commonly known establishment thresholds in Europe based on climate chamber experiments and derived from the geographical distribution of the species. Under future climatic conditions low winter temperature were modelled to remain the most limiting factor in Eastern Europe, whereas in Central Europe annual mean temperature and summer temperatures were modelled to be replaced by summer precipitation, respectively, as most limiting factors. Changes in the climatic conditions in terms of the identified key limiting factors will be of great relevance regarding the invasive potential of the Ae. albopictus. Thus, our results may help to understand the key drivers of the suggested range expansion under climate change and may help to improve monitoring programmes. The applied approach of investigating limiting factors has proven to yield valuable results and may also provide valuable insights into the drivers of the prediction of current and future distribution of other species. This might be particularly interesting for other vector species that are of increasing public health concerns.
Erratum to doi:10.1186/s13071-016-1853-2
Biological invasions have been associated with niche changes; however, their occurrence is still debated. We assess whether climatic niches between native and non-native ranges have changed during the invasion process using two globally spread mosquitoes as model species, Aedes albopictus and Aedes aegypti. Considering the different time spans since their invasions (>300 vs. 30–40 years), niche changes were expected to be more likely for Ae. aegypti than for Ae. albopictus. We used temperature and precipitation variables as descriptors for the realized climatic niches and different niche metrics to detect niche dynamics in the native and non-native ranges. High niche stability, therefore, no niche expansion but niche conservatism was revealed for both species. High niche unfilling for Ae. albopictus indicates a great potential for further expansion. Highest niche occupancies in non-native ranges occurred either under more temperate (North America, Europe) or tropical conditions (South America, Africa). Aedes aegypti has been able to fill its native climatic niche in the non-native ranges, with very low unfilling. Our results challenge the assumption of rapid evolutionary change of climatic niches as a requirement for global invasions but support the use of native range-based niche models to project future invasion risk on a large scale.
The genus Ebolavirus comprises some of the deadliest viruses for primates and humans and associated disease outbreaks are increasing in Africa. Different evidence suggests that bats are putative reservoir hosts and play a major role in the transmission cycle of these filoviruses. Thus, detailed knowledge about their distribution might improve risk estimations of where future disease outbreaks might occur. A MaxEnt niche modelling approach based on climatic variables and land cover was used to investigate the potential distribution of 9 bat species associated to the Zaire ebolavirus. This viral species has led to major Ebola outbreaks in Africa and is known for causing high mortalities. Modelling results suggest suitable areas mainly in the areas near the coasts of West Africa with extensions into Central Africa, where almost all of the 9 species studied find suitable habitat conditions. Previous spillover events and outbreak sites of the virus are covered by the modelled distribution of 3 bat species that have been tested positive for the virus not only using serology tests but also PCR methods. Modelling the habitat suitability of the bats is an important step that can benefit public information campaigns and may ultimately help control future outbreaks of the disease.