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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.
The Culex pipiens complex encompasses five species and subspecies of the genus Culex. Over time, a multitude of morphologically indistinguishable species has been assigned to this complex with several species being classified as important vectors for different diseases. Some species of this complex hibernate in subterranean habitats, and it has been proven that viruses can survive this phase of hibernation. However, studies focusing on the environmental requirements, ecology and spatial and temporal distribution patterns of mosquitos in underground habitats are sparse. Here, we investigate the main environmental factors and dependencies of Culex, considering the number of individuals and survival probabilities in underground habitats during the winter months. Methods. Since the State of Hesse, Germany harbors about 3500 to 4000 subterranean shelters ample availability of subterranean habitats there provides a good opportunity to conduct detailed investigations of the Culex pipiens complex. In this study, we identified a sample of 727 specimens of overwintering females within the Culex pipiens complex from 52 different underground sites collected over a period of 23 years using qPCR. A complete data set of samplings of hibernating mosquitos from 698 subterranean habitats in Central Germany over the same period was available to study the spatial and temporal patterns and the effect of temperature and precipitation conditions on these hibernating populations using a generalized linear model (GLM). Results. Our qPCR-results show, similar to aboveground studies of mosquitos, that Culex pipiens pipiens and Culex torrentium occur sympatrically. On the other hand, Culex pipiens molestus occurred very rarely. The GLM revealed no shifts in species composition over time, but different preferences for subterranean hibernacula, chemical effects on overwintering populations as well as effects of annual and seasonal mean temperature and precipitation during the active phase from March to November. Cx. p. pipiens and Cx. torrentium are the most common species within Hessian caves and other underground habitats during winter. They co-occur with different frequency without any patterns in species composition. Weather conditions influence the number of overwintering mosquitos during the activity phase. Depending on cave parameters, the number of mosquitos decreases during the winter months.
Future climate change is predicted to advance faster than the postglacial warming. Migration may therefore become a key driver for future development of biodiversity and ecosystem functioning. For 140 European plant species we computed past range shifts since the last glacial maximum and future range shifts for a variety of Intergovernmental Panel on Climate Change (IPCC) scenarios and global circulation models (GCMs). Range shift rates were estimated by means of species distribution modelling (SDM). With process-based seed dispersal models we estimated species-specific migration rates for 27 dispersal modes addressing dispersal by wind (anemochory) for different wind conditions, as well as dispersal by mammals (dispersal on animal's coat – epizoochory and dispersal by animals after feeding and digestion – endozoochory) considering different animal species. Our process-based modelled migration rates generally exceeded the postglacial range shift rates indicating that the process-based models we used are capable of predicting migration rates that are in accordance with realized past migration. For most of the considered species, the modelled migration rates were considerably lower than the expected future climate change induced range shift rates. This implies that most plant species will not entirely be able to follow future climate-change-induced range shifts due to dispersal limitation. Animals with large day- and home-ranges are highly important for achieving high migration rates for many plant species, whereas anemochory is relevant for only few species.
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.
1. During the last century, the practice of fur farming in Europe led to the introduction of two mammal species from opposite ends of the world. With their subsequent unintentional escape from captivity or intentional releases, the process of slow expansion and establishment in Europe began. The raccoon Procyon lotor and the raccoon dog Nyctereutes procyonoides are included on the European Union’s list of invasive alien species.
2. We characterised the current climatic niches of the two species in their native ranges in North America and Asia, and compared them with their non-native-range niches in Europe, where we also projected climatic suitability. The aim was to locate suitable habitats beyond their current ranges and assess where a range expansion can be expected.
3. Niche comparison and the projection of climatic suitability in Europe were based on eight bioclimatic variables and presence records from the Global Biodiversity Information Facility database. For niche modelling, we applied the maximum entropy approach (Maxent) and used the native-range data for training.
4. Minimum temperature of the coldest month (bio06) was identified as the most important bioclimatic variable in the habitat suitability models for both species. Different tolerance levels regarding this variable might explain small differences between the species’ projected ranges, especially in the north and east of Europe. The high niche unfilling for both species in Europe suggests a potential for expansion beyond their present ranges.
5. With only little understanding of their ecological impacts in their new ranges, including the potential risk of Nyctereutes procyonoides as SARS-CoV-2 reservoir hosts, further research and management is required at various spatial scales in Europe.
Highlights
• Three ecological groups were identified based on distributional patterns.
• Old assessments were confirmed with the latest occurrence data.
• For each group, we derived different population trends in times of global change.
• Global change elevates importance of vector-borne diseases.
• Our results serve as base for effective Simuliidae monitoring.
Abstract
The black fly genus Simulium includes medically and ecologically important species, characterized by a wide variation of ecological niches largely determining their distributional patterns. In a rapidly changing environment, species-specific niche characteristics determine whether a species benefits or not. With aquatic egg, larval and pupal stages followed by a terrestrial adult phase, their spatial arrangements depend upon the interplay of aquatic conditions and climatic-landscape parameters in the terrestrial realm. The aim of this study was to enhance the understanding of the distributional patterns among Simulium species and their ecological drivers. In an ecological niche modelling approach, we focused on 12 common black fly species with different ecological requirements. Our modelling was based on available distribution data along with five stream variables describing the climatic, land-cover, and topographic conditions of river catchments. The modelled freshwater habitat suitability was spatially interpolated to derive an estimate of the adult black flies' probability of occurrence. Based on similarities in the spatial patterns of modelled habitat suitability we were able to identify three biogeographical groups, which allows us to confirm old assessments with current occurrence data: (A) montane species, (B) broad range species and (C) lowland species. The five veterinary and human medical relevant species Simulium equinum, S. erythrocephalum, S. lineatum, S. ornatum and S. reptans are mainly classified in the lowland species group. In the course of climatic changes, it is expected that biocoenosis will slightly shift towards upstream regions, so that the lowland group will presumably emerge as the winner. This is mainly explained by wider ecological niches, including a higher temperature tolerance and tolerance to various pollutants. In conclusion, these findings have significant implications for human and animal health. As exposure to relevant Simulium species increases, it becomes imperative to remain vigilant, particularly in investigating the potential transmission of pathogens.
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.
Erratum to doi:10.1186/s13071-016-1853-2
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.