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Background: The presence of the recently introduced primary dengue virus vector mosquito Aedes aegypti in Nepal, in association with the likely indigenous secondary vector Aedes albopictus, raises public health concerns. Chikungunya fever cases have also been reported in Nepal, and the virus causing this disease is also transmitted by these mosquito species. Here we report the results of a study on the risk factors for the presence of chikungunya and dengue virus vectors, their elevational ceiling of distribution, and climatic determinants of their abundance in central Nepal.
Methodology/Principal findings: We collected immature stages of mosquitoes during six monthly cross-sectional surveys covering six administrative districts along an altitudinal transect in central Nepal that extended from Birgunj (80 m above sea level [asl]) to Dhunche (highest altitude sampled: 2,100 m asl). The dengue vectors Ae. aegypti and Ae. albopictus were commonly found up to 1,350 m asl in Kathmandu valley and were present but rarely found from 1,750 to 2,100 m asl in Dhunche. The lymphatic filariasis vector Culex quinquefasciatus was commonly found throughout the study transect. Physiographic region, month of collection, collection station and container type were significant predictors of the occurrence and co-occurrence of Ae. aegypti and Ae. albopictus. The climatic variables rainfall, temperature, and relative humidity were significant predictors of chikungunya and dengue virus vectors abundance.
Conclusions/Significance: We conclude that chikungunya and dengue virus vectors have already established their populations up to the High Mountain region of Nepal and that this may be attributed to the environmental and climate change that has been observed over the decades in Nepal. The rapid expansion of the distribution of these important disease vectors in the High Mountain region, previously considered to be non-endemic for dengue and chikungunya fever, calls for urgent actions to protect the health of local people and tourists travelling in the central Himalayas.
Understanding how temperature affects cod (Gadus morhua) ecology is important for forecasting how populations will develop as climate changes in future. The effects of spawning-season temperature and habitat size on cod recruitment dynamics have been investigated across the North Atlantic. Ricker and Beverton and Holt stock–recruitment (SR) models were extended by applying hierarchical methods, mixed-effects models, and Bayesian inference to incorporate the influence of these ecosystem factors on model parameters representing cod maximum reproductive rate and carrying capacity. We identified the pattern of temperature effects on cod productivity at the species level and estimated SR model parameters with increased precision. Temperature impacts vary geographically, being positive in areas where temperatures are <5°C, and negative for higher temperatures. Using the relationship derived, it is possible to predict expected changes in population-specific reproductive rates and carrying capacities resulting from temperature increases. Further, carrying capacity covaries with available habitat size, explaining at least half its variability across stocks. These patterns improve our understanding of environmental impacts on key population parameters, which is required for an ecosystem approach to cod management, particularly under ocean-warming scenarios. Key words: carrying capacity , cod , hierarchical models , North Atlantic , temperature , uncertainty
Temporal variation in the detectability of a species can bias estimates of relative abundance if not handled correctly. For example, when effort varies in space and/or time it becomes necessary to take variation in detectability into account when data are analyzed. We demonstrate the importance of incorporating seasonality into the analysis of data with unequal sample sizes due to lost traps at a particular density of a species. A case study of count data was simulated using a spring-active carabid beetle. Traps were ‘lost’ randomly during high beetle activity in high abundance sites and during low beetle activity in low abundance sites. Five different models were fitted to datasets with different levels of loss. If sample sizes were unequal and a seasonality variable was not included in models that assumed the number of individuals was log-normally distributed, the models severely under- or overestimated the true effect size. Results did not improve when seasonality and number of trapping days were included in these models as offset terms, but only performed well when the response variable was specified as following a negative binomial distribution. Finally, if seasonal variation of a species is unknown, which is often the case, seasonality can be added as a free factor, resulting in well-performing negative binomial models. Based on these results we recommend (a) add sampling effort (number of trapping days in our example) to the models as an offset term, (b) if precise information is available on seasonal variation in detectability of a study object, add seasonality to the models as an offset term; (c) if information on seasonal variation in detectability is inadequate, add seasonality as a free factor; and (d) specify the response variable of count data as following a negative binomial or over-dispersed Poisson distribution.
Background: Environmental noise is ubiquitous in population growth processes, with a well acknowledged potential to affect populations regardless of their sizes. It therefore deserves consideration in population dynamics modelling. The usual approach to incorporating noise into population dynamical models is to make some model parameter(s) (typically the growth rate, the carrying capacity, or both) stochastic and responsive to environment fluctuations. It is however still unclear whether including noise in one or/and another parameter makes a difference to the model performance. Here we investigated this issue with a focus on model fit and predictive accuracy. To do this, we developed three population dynamical models of the Ricker type with the noise included in the growth rate (Model 1), in the carrying capacity (Model 2), and in both (Model 3). We generated several population time series under each model, and used a Bayesian approach to fit the three models to the simulated data. We then compared the model performances in fitting to the data and in forecasting future observations. Results: When the mean intrinsic growth rate, r, in the data was low, the three models had roughly comparable performances, irrespective of the true model and the level of noise. As r increased, Models 1 performed best on data generated from it, and Model 3 tended to perform best on data generated from either Models 2 or Model 3. Model 2 was uniformly outcompeted by the other two models, regardless of the true model and the level of noise. The correlation between the deviance information criterion (DIC) and the mean square error (MSE) used respectively as measure of fit and predictive accuracy was broadly positive. Conclusion: Our results suggested that the way environmental noise is incorporated into a population dynamical model may profoundly affect its performance. Overall, we found that including noise in one or/and another parameter does not matter as long as the mean intrinsic growth rate, r, is low. As r increased, however, the three models performed differently. Models 1 and 3 broadly outperformed Model 2, the first having the advantage of being simple and more computationally tractable. A comforting result emerging from our analysis is the broad positive correlation between MSEs and DICs, suggesting that the latter may also be informative about the predictive performance of a model.
Background: The invasive temperate mosquito Aedes japonicus japonicus is a potential vector for various infectious diseases and therefore a target of vector control measures. Even though established in Germany, it is unclear whether the species has already reached its full distribution potential. The possible range of the species, its annual population dynamics, the success of vector control measures and future expansions due to climate change still remain poorly understood. While numerous studies on occurrence have been conducted, they used mainly presence data from relatively few locations. In contrast, we used experimental life history data to model the dynamics of a continuous stage-structured population to infer potential seasonal densities and ask whether stable populations are likely to establish over a period of more than one year. In addition, we used climate change models to infer future ranges. Finally, we evaluated the effectiveness of various stage-specific vector control measures.
Results: Aedes j. japonicus has already established stable populations in the southwest and west of Germany. Our models predict a spread of Ae. j. japonicus beyond the currently observed range, but likely not much further eastwards under current climatic conditions. Climate change models, however, will expand this range substantially and higher annual densities can be expected. Applying vector control measures to oviposition, survival of eggs, larvae or adults showed that application of adulticides for 30 days between late spring and early autumn, while ambient temperatures are above 9 °C, can reduce population density by 75%. Continuous application of larvicide showed similar results in population reduction. Most importantly, we showed that with the consequent application of a mixed strategy, it should be possible to significantly reduce or even extinguish existing populations with reasonable effort.
Conclusion: Our study provides valuable insights into the mechanisms concerning the establishment of stable populations in invasive species. In order to minimise the hazard to public health, we recommend vector control measures to be applied in ‘high risk areas’ which are predicted to allow establishment of stable populations to establish.
Foliar fungal communities of plants are diverse and ubiquitous. In grasses endophytes may increase host fitness; in trees, their ecological roles are poorly understood. We investigated whether the genotype of the host tree influences community structure of foliar fungi. We sampled leaves from genotyped balsam poplars from across the species' range, and applied 454 amplicon sequencing to characterize foliar fungal communities. At the time of the sampling the poplars had been growing in a common garden for two years. We found diverse fungal communities associated with the poplar leaves. Linear discriminant analysis and generalized linear models showed that host genotypes had a structuring effect on the composition of foliar fungal communities. The observed patterns may be explained by a filtering mechanism which allows the trees to selectively recruit fungal strains from the environment. Alternatively, host genotype-specific fungal communities may be present in the tree systemically, and persist in the host even after two clonal reproductions. Both scenarios are consistent with host tree adaptation to specific foliar fungal communities and suggest that there is a functional basis for the strong biotic interaction.
Given the ever-increasing human impact through land use and climate change on the environment, we crucially need to achieve a better understanding of those factors that influence the questing activity of ixodid ticks, a major disease-transmitting vector in temperate forests. We investigated variation in the relative questing nymph densities of Ixodes ricinus in differently managed forest types for three years (2008–2010) in SW Germany by drag sampling. We used a hierarchical Bayesian modeling approach to examine the relative effects of habitat and weather and to consider possible nested structures of habitat and climate forces. The questing activity of nymphs was considerably larger in young forest successional stages of thicket compared with pole wood and timber stages. Questing nymph density increased markedly with milder winter temperatures. Generally, the relative strength of the various environmental forces on questing nymph density differed across years. In particular, winter temperature had a negative effect on tick activity across sites in 2008 in contrast to the overall effect of temperature across years. Our results suggest that forest management practices have important impacts on questing nymph density. Variable weather conditions, however, might override the effects of forest management practices on the fluctuations and dynamics of tick populations and activity over years, in particular, the preceding winter temperatures. Therefore, robust predictions and the detection of possible interactions and nested structures of habitat and climate forces can only be quantified through the collection of long-term data. Such data are particularly important with regard to future scenarios of forest management and climate warming.
The use of parasites as biological tags for discrimination of fish stocks has become a commonly used approach in fisheries management. Metazoan parasite community analysis and anisakid nematode population genetics based on a mitochondrial cytochrome marker were applied in order to assess the usefulness of the two parasitological methods for stock discrimination of beaked redfish Sebastes mentella of three fishing grounds in the North East Atlantic. Multivariate, model-based approaches demonstrated that the metazoan parasite fauna of beaked redfish from East Greenland differed from Tampen, northern North Sea, and Bear Island, Barents Sea. A joint model (latent variable model) was used to estimate the effects of covariates on parasite species and identified four parasite species as main source of differences among fishing grounds; namely Chondracanthus nodosus, Anisakis simplex s.s., Hysterothylacium aduncum, and Bothriocephalus scorpii. Due to its high abundance and differences between fishing grounds, Anisakis simplex s.s. was considered as a major biological tag for host stock differentiation. Whilst the sole examination of Anisakis simplex s.s. on a population genetic level is only of limited use, anisakid nematodes (in particular, A. simplex s.s.) can serve as biological tags on a parasite community level. This study confirmed the use of multivariate analyses as a tool to evaluate parasite infra-communities and to identify parasite species that might serve as biological tags. The present study suggests that S. mentella in the northern North Sea and Barents Sea is not sub-structured.
Recovery of an ecosystem following disturbance can be severely hampered or even shift altogether when a point disturbance exceeds a certain spatial threshold. Such scale-dependent dynamics may be caused by preemptive competition, but may also result from diminished self-facilitation due to weakened ecosystem engineering. Moreover, disturbance can facilitate colonization by engineering species that alter abiotic conditions in ways that exacerbate stress on the original species. Consequently, establishment of such counteracting engineers might reduce the spatial threshold for the disturbance, by effectively slowing recovery and increasing the risk for ecosystem shifts to alternative states. We tested these predictions in an intertidal mudflat characterized by a two-state mosaic of hummocks (humps exposed during low tide) dominated by the sediment-stabilizing seagrass Zostera noltii) and hollows (low-tide waterlogged depressions dominated by the bioturbating lugworm Arenicola marina). In contrast to expectations, seagrass recolonized both natural and experimental clearings via lateral expansion and seemed unaffected by both clearing size and lugworm addition. Near the end of the growth season, however, an additional disturbance (most likely waterfowl grazing and/or strong hydrodynamics) selectively impacted recolonizing seagrass in the largest (1 m2) clearings (regardless of lugworm addition), and in those medium (0.25 m2) clearings where lugworms had been added nearly five months earlier. Further analyses showed that the risk for the disturbance increased with hollow size, with a threshold of 0.24 m2. Hollows of that size were caused by seagrass removal alone in the largest clearings, and by a weaker seagrass removal effect exacerbated by lugworm bioturbation in the medium clearings. Consequently, a sufficiently large disturbance increased the vulnerability of recolonizing seagrass to additional disturbance by weakening seagrass engineering effects (sediment stabilization). Meanwhile, the counteracting ecosystem engineering (lugworm bioturbation) reduced that threshold size. Therefore, scale-dependent interactions between habitat-mediated facilitation, competition and disturbance seem to maintain the spatial two-state mosaic in this ecosystem.
One of the major problems in evolutionary biology is to elucidate the relationships between historical events and the tempo and mode of lineage divergence. The development of relaxed molecular clock models and the increasing availability of DNA sequences resulted in more accurate estimations of taxa divergence times. However, finding the link between competing historical events and divergence is still challenging. Here we investigate assigning constrained-age priors to nodes of interest in a time-calibrated phylogeny as a means of hypothesis comparison. These priors are equivalent to historic scenarios for lineage origin. The hypothesis that best explains the data can be selected by comparing the likelihood values of the competing hypotheses, modelled with different priors. A simulation approach was taken to evaluate the performance of the prior-based method and to compare it with an unconstrained approach. We explored the effect of DNA sequence length and the temporal placement and span of competing hypotheses (i.e. historic scenarios) on selection of the correct hypothesis and the strength of the inference. Competing hypotheses were compared applying a posterior simulation analogue of the Akaike Information Criterion and Bayes factors (obtained after calculation of the marginal likelihood with three estimators: Harmonic Mean, Stepping Stone and Path Sampling). We illustrate the potential application of the prior-based method on an empirical data set to compare competing geological hypotheses explaining the biogeographic patterns in Pleurodeles newts. The correct hypothesis was selected on average 89% times. The best performance was observed with DNA sequence length of 3500-10000 bp. The prior-based method is most reliable when the hypotheses compared are not temporally too close. The strongest inferences were obtained when using the Stepping Stone and Path Sampling estimators. The prior-based approach proved effective in discriminating between competing hypotheses when used on empirical data. The unconstrained analyses performed well but it probably requires additional computational effort. Researchers applying this approach should rely only on inferences with moderate to strong support. The prior-based approach could be applied on biogeographical and phylogeographical studies where robust methods for historical inferences are still lacking.
