The use of path analysis to determine effects of environmental factors on the adult seasonality of Culicoides (Diptera: Ceratopogonidae) vector species in Spain

Culicoides biting midges (Diptera: Ceratopogonidae) are the main vectors of livestock diseases such as bluetongue (BT) which mainly affect sheep and cattle. In Spain, bluetongue virus (BTV) is transmitted by several Culicoides taxa, including Culicoides imicola, Obsoletus complex, Culicoides newsteadi and Culicoides pulicaris that vary in seasonality and distribution, affecting the distribution and dynamics of BT outbreaks. Path analysis is useful for separating direct and indirect, biotic and abiotic determinants of species' population performance and is ideal for understanding the sensitivity of adult Culicoides dynamics to multiple environmental drivers. Start, end of season and length of overwintering of adult Culicoides were analysed across 329 sites in Spain sampled from 2005 to 2010 during the National Entomosurveillance Program for BTV with path analysis, to determine the direct and indirect effects of land use, climate and host factor variables. Culicoides taxa had species-specific responses to environmental variables. While the seasonality of adult C. imicola was strongly affected by topography, temperature, cover of agro-forestry and sclerophyllous vegetation, rainfall, livestock density, photoperiod in autumn and the abundance of Culicoides females, Obsoletus complex species seasonality was affected by land-use variables such as cover of natural grassland and broad-leaved forest. Culicoides female abundance was the most explanatory variable for the seasonality of C. newsteadi, while C. pulicaris showed that temperature during winter and the photoperiod in November had a strong effect on the start of the season and the length of overwinter period of this species. These results indicate that the seasonal vector-free period (SVFP) in Spain will vary between competent vector taxa and geographic locations, dependent on the different responses of each taxa to environmental conditions

Two species with an unusual combination of traits dominate responses of British grasshoppers and crickets to environmental change

There are large variations in the responses of species to the environmental changes of recent decades, heightening interest in whether their traits may explain inter-specific differences in range expansions and contractions. Using a long-term distributional dataset, we calculated range changes of grasshoppers and crickets in Britain between the 1980s and the 2000s and assessed whether their traits (resource use, life history, dispersal ability, geographic location) explain relative performance of different species. Our analysis showed large changes in the distributions of some species, and we found a positive relationship between three traits and range change: ranges tended to increase for habitat generalists, species that oviposit in the vegetation above ground, and for those with a southerly distribution. These findings accord well with the nature of environmental changes over this period (climatic warming; reductions in the diversity and increases in the height of vegetation). However, the trait effects applied mainly to just two species, Conocephalus discolor and Metrioptera roeselii, which had shown the greatest range increases. Once they were omitted from the analysis, trait effects were no longer statistically significant. Previous studies on these two species emphasised wing-length dimorphism as the key to their success, resulting in a high phenotypic plasticity of dispersal and evolutionary-ecological feedback at their expanding range margins. This, combined with our results, suggests that an unusual combination of traits have enabled these two species to undertake extremely rapid responses to recent environmental changes. The fact that our results are dominated by two species only became apparent through cautious testing of the results’ robustness, not through standard statistical checks. We conclude that trait-based analyses may contribute to the assessment of species responses to environmental change and provide insights into underlying mechanisms, but results need to be interpreted with caution and may have limited predictive power

Evolutionary trait‐based approaches for predicting future global impacts of plant pathogens in the genus Phytophthora

Plant pathogens are introduced to new geographical regions ever more frequently as global connectivity increases. Predicting the threat they pose to plant health can be difficult without in‐depth knowledge of behaviour, distribution and spread. Here, we evaluate the potential for using biological traits and phylogeny to predict global threats from emerging pathogens. We use a species‐level trait database and phylogeny for 179 Phytophthora species: oomycete pathogens impacting natural, agricultural, horticultural and forestry settings. We compile host and distribution reports for Phytophthora species across 178 countries and evaluate the power of traits, phylogeny and time since description (reflecting species‐level knowledge) to explain and predict their international transport, maximum latitude and host breadth using Bayesian phylogenetic generalised linear mixed models. In the best‐performing models, traits, phylogeny and time since description together explained up to 90%, 97% and 87% of variance in number of countries reached, latitudinal limits and host range, respectively. Traits and phylogeny together explained up to 26%, 41% and 34% of variance in the number of countries reached, maximum latitude and host plant families affected, respectively, but time since description had the strongest effect. Root‐attacking species were reported in more countries, and on more host plant families than foliar‐attacking species. Host generalist pathogens had thicker‐walled resting structures (stress‐tolerant oospores) and faster growth rates at their optima. Cold‐tolerant species are reported in more countries and at higher latitudes, though more accurate interspecific empirical data are needed to confirm this finding. Policy implications. We evaluate the potential of an evolutionary trait‐based framework to support horizon‐scanning approaches for identifying pathogens with greater potential for global‐scale impacts. Potential future threats from Phytophthora include Phytophthora x heterohybrida, P. lactucae, P. glovera, P. x incrassata, P. amnicola and P. aquimorbida, which are recently described, possibly under‐reported species, with similar traits and/or phylogenetic proximity to other high‐impact species. Priority traits to measure for emerging species may be thermal minima, oospore wall index and growth rate at optimum temperature. Trait‐based horizon‐scanning approaches would benefit from the development of international and cross‐sectoral collaborations to deliver centralised databases incorporating pathogen distributions, traits and phylogeny

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data

Background. Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling

Spatio-temporal optimization of sampling for bluetongue vectors (<em>Culicoides</em>) near grazing livestock

BACKGROUND: Estimating the abundance of Culicoides using light traps is influenced by a large variation in abundance in time and place. This study investigates the optimal trapping strategy to estimate the abundance or presence/absence of Culicoides on a field with grazing animals. We used 45 light traps to sample specimens from the Culicoides obsoletus species complex on a 14 hectare field during 16 nights in 2009. FINDINGS: The large number of traps and catch nights enabled us to simulate a series of samples consisting of different numbers of traps (1-15) on each night. We also varied the number of catch nights when simulating the sampling, and sampled with increasing minimum distances between traps. We used resampling to generate a distribution of different mean and median abundance in each sample. Finally, we used the hypergeometric distribution to estimate the probability of falsely detecting absence of vectors on the field. The variation in the estimated abundance decreased steeply when using up to six traps, and was less pronounced when using more traps, although no clear cutoff was found. CONCLUSIONS: Despite spatial clustering in vector abundance, we found no effect of increasing the distance between traps. We found that 18 traps were generally required to reach 90% probability of a true positive catch when sampling just one night. But when sampling over two nights the same probability level was obtained with just three traps per night. The results are useful for the design of vector monitoring programmes on fields with grazing animals

Spatial abundance and clustering of Culicoides (Diptera: Ceratopogonidae) on a local scale

BACKGROUND: Biting midges, Culicoides, of the Obsoletus group and the Pulicaris group have been involved in recent outbreaks of bluetongue virus and the former was also involved in the Schmallenberg virus outbreak in northern Europe. METHODS: For the first time, here we investigate the local abundance pattern of these two species groups in the field by intensive sampling with a grid of light traps on 16 catch nights. Neighboring trap catches can be spatially dependent on each other, hence we developed a conditional autoregressive (CAR) model framework to test a number of spatial and non-spatial covariates expected to affect Culicoides abundance. RESULTS: The distance to sheep penned in the corner of the study field significantly increased the abundance level up to 200 meters away from the sheep. Spatial clustering was found to be significant but could not be explained by any known factors, and cluster locations shifted between catch nights. No significant temporal autocorrelation was detected. CAR models for both species groups identified a significant positive impact of humidity and significant negative impacts of precipitation and wind turbulence. Temperature was also found to be significant with a peak at just below 16 degrees Celcius. Surprisingly, there was a significant positive impact of wind speed. The CAR model for the Pulicaris group also identified a significant attraction to the smaller groups of sheep placed in the field. Furthermore, a large number of spatial covariates which were incorrectly found to be significant in ordinary regression models were not significant in the CAR models. The 95% C.I. on the prediction estimates ranged from 20.4% to 304.8%, underlining the difficulties of predicting the abundance of Culicoides. CONCLUSIONS: We found that significant spatial clusters of Culicoides moved around in a dynamic pattern varying between catch nights. This conforms with the modeling but was not explained by any of the tested covariates. The mean abundance within these clusters was up to 11 times higher for the Obsoletus group and 4 times higher for the Pulicaris group compared to the rest of the field

Lenalidomide treatment and prognostic markers in relapsed or refractory chronic lymphocytic leukemia: data from the prospective, multicenter phase-II CLL-009 trial

Efficacy of lenalidomide was investigated in 103 patients with relapsed/refractory chronic lymphocytic leukemia (CLL) treated on the prospective, multicenter randomized phase-II CLL-009 trial. Interphase cytogenetic and mutational analyses identified TP53 mutations, unmutated IGHV, or del(17p) in 36/96 (37.5%), 68/88 (77.3%) or 22/92 (23.9%) patients. The overall response rate (ORR) was 40.4% (42/104). ORRs were similar irrespective of TP53 mutation (36.1% (13/36) vs 43.3% (26/60) for patients with vs without mutation) or IGHV mutation status (45.0% (9/20) vs 39.1% (27/68)); however, patients with del(17p) had lower ORRs than those without del(17p) (21.7% (5/22) vs 47.1% (33/70); P=0.049). No significant differences in progression-free survival and overall survival (OS) were observed when comparing subgroups defined by the presence or absence of high-risk genetic characteristics. In multivariate analyses, only multiple prior therapies (greater than or equal to3 lines) significantly impacted outcomes (median OS: 21.2 months vs not reached; P=0.019). This analysis indicates that lenalidomide is active in patients with relapsed/refractory CLL with unfavorable genetic profiles, including TP53 inactivation or unmutated IGHV. (ClinicalTrials.gov identifier: NCT00963105)

Evaluation of host-derived volatiles for trapping Culicoides biting midges (Diptera: Ceratopogonidae)

Culicoides biting midges (Diptera: Ceratopognidae) cause pain and distress through blood feeding, and transmit viruses that threaten both animal and human health worldwide. There are few effective tools for monitoring and control of biting midges, with semiochemical-based strategies offering the advantage of targeting host-seeking populations. In previous studies, we identified the host preference of multiple Culicoides species, including Culicoides impunctatus, as well as cattle-derived compounds that modulate the behavioral responses of C. nubeculosus under laboratory conditions. Here, we test the efficacy of these compounds, when released at different rates, in attracting C. impunctatus under field conditions in Southern Sweden. Traps releasing 1-octen-3-ol, decanal, phenol, 4-methylphenol or 3-propylphenol, when combined with carbon dioxide (CO2), captured significantly higher numbers of C. impunctatus compared to control traps baited with CO2 alone, with low release rates (0.1 mg h−1, 1 mg h−1) being generally more attractive. In contrast, traps releasing octanal or (E)-2-nonenal at 1 mg h−1 and 10 mg h−1 collected significantly lower numbers of C. impunctatus than control traps baited with CO2 only. Nonanal and 2-ethylhexanol did not affect the attraction of C. impunctatus when compared to CO2 alone at any of the release rates tested. The potential use of these semiochemicals as attractants and repellents for biting midge control is discussed