Exploring the natural variation for reproductive thermotolerance in wild tomato species

Climate change has become a serious threat for crop productivity worldwide. The increased frequency of heat waves strongly affects reproductive success and thus yield for many crop species, implying that breeding for thermotolerant cultivars is critical for food security. Insight into the genetic architecture of reproductive heat tolerance contributes to our fundamental understanding of the stress sensitivity of this process and at the same time may have applied value. In the case of tomato (Solanum lycopersicum), germplasm screenings for thermotolerance have often used yield as the main measured trait. However, due to the complex nature of yield and the relatively narrow genetic variation present in the cultivated germplasm screened, there has been limited progress in understanding the genetic basis of reproductive heat tolerance. Extending the screening to wild accessions of related species that cover a range of climatic conditions might be an effective approach to find novel, more tolerant genetic resources. The purpose of this study was to provide insight into the sensitivity of individual reproductive key traits (i.e. the number of pollen per flower, pollen viability and style protrusion) to heat-wave like long-term mild heat (LTMH), and determine the extent to which genetic variation exists for these traits among wild tomato species. We found that these traits were highly variable among the screened accessions. Although no overall thermotolerant species were identified, several S. pimpinellifolium individuals outperformed the best performing cultivar in terms of pollen viability under LTMH. Furthermore, we reveal that there has been local adaptation of reproductive heat tolerance, as accessions from lower elevations and higher annual temperature are more likely to show high pollen viability under LTMH.     

Transient Middle Eocene atmospheric CO₂ and temperature variations

The long-term warmth of the Eocene (~56 to 34 million years ago) is commonly associated with elevated partial pressure of atmospheric carbon dioxide (pCO(2)). However, a direct relationship between the two has not been established for short-term climate perturbations. We reconstructed changes in both pCO(2) and temperature over an episode of transient global warming called the Middle Eocene Climatic Optimum (MECO; ~40 million years ago). Organic molecular paleothermometry indicates a warming of southwest Pacific sea surface temperatures (SSTs) by 3° to 6°C. Reconstructions of pCO(2) indicate a concomitant increase by a factor of 2 to 3. The marked consistency between SST and pCO(2) trends during the MECO suggests that elevated pCO(2) played a major role in global warming during the MECO.     

The transmission potential of Rift Valley fever virus among livestock in the Netherlands: a modelling study

Abstracts

Rift Valley fever virus (RVFV) is a zoonotic vector-borne infection and causes a potentially severe disease. Many mammals are susceptible to infection including important livestock species. Although currently confined to Africa and the near-East, this disease causes concern in countries in temperate climates where both hosts and potential vectors are present, such as the Netherlands. Currently, an assessment of the probability of an outbreak occurring in this country is missing. To evaluate the transmission potential of RVFV, a mathematical model was developed and used to determine the initial growth and the Floquet ratio, which are indicators of the probability of an outbreak and of persistence in a periodic changing environment caused by seasonality. We show that several areas of the Netherlands have a high transmission potential and risk of persistence of the infection. Counter-intuitively, these are the sparsely populated livestock areas, due to the high vector-host ratios in these areas. Culex pipiens s.l. is found to be the main driver of the spread and persistence, because it is by far the most abundant mosquito. Our investigation underscores the importance to determine the vector competence of this mosquito species for RVFV and its host preference.     

Fluorescein‐diacetate,a fluorescent dye compound stain for rapid evaluation of the viability of mammalian oocytes prior to in vitro studies

Summary

A method for a quantitative measurement of the fluorescence activity of porcine egg cells is described. The non‐polar fluorescein‐diacetate molecules enter the cell, are hydrolyzed by cell esterases, and fluorescein is produced. This polar compound can not leave the cell because it is unable to pass through the intact cell membrane, and it therefore accumulates in the cytoplasm of the cell. Damaged cells however show a distinct loss of fluorescein through the cell membrane. With the aid of a fluorescence microscope, a photometer and a recorder, the amount of radiated light can be measured. The advantages of this method in oocyte research are briefly discussed.     

EU-wide maps of growing stock and above-ground biomass in forests based on remote sensing and field measurements

The overall objective of this study was to combine national forest inventory data and remotely sensed data to produce pan-European maps on growing stock and above-ground woody biomass for the two species groups “broadleaves” and “conifers”. An automatic up-scaling approach making use of satellite remote sensing data and field measurement data was applied for EU-wide mapping of growing stock and above-ground biomass in forests. The approach is based on sampling and allows the direct combination of data with different measurement units such as forest inventory plot data and satellite remote sensing data. For the classification, data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used. Comprehensive field measurement data from national forest inventories for 98,979 locations from 16 countries were used for which tree species and growing stock estimates were available. The classification results were evaluated by comparison with regional estimates derived independently from the classification from national forest inventories. The validation at the regional level shows a high correlation between the classification results and the field based estimates with correlation coefficient r = 0.96 for coniferous, r = 0.94 for broadleaved and r = 0.97 for total growing stock per hectare. The mean absolute error of the estimations is 25 m³/ha for coniferous, 20 m³/ha for broadleaved and 25 m³/ha for total growing stock per hectare. Biomass conversion and expansion factors were applied to convert the growing stock classification results to carbon stock in above-ground biomass. As results of the classification, coniferous and broadleaved growing stock as well as carbon stock of the above-ground biomass is mapped on a wall-to-wall basis with a spatial resolution of 500 m × 500 m per grid cell. The mapped area is 5 million km², of which 2 million km² are forests, and covers the whole European Union, the EFTA countries, the Balkans, Belarus, the Ukraine, Moldova, Armenia, Azerbaijan, Georgia and Turkey.     

The local threshold for geographical spread of infectious diseases between farms

We investigated the influence of the spatial pattern of farms on the geographical spread of infectious livestock diseases, such as classical swine fever, foot-and-mouth disease and avian influenza in a combined analytical-numerical approach. Our purpose of this paper is to develop a method to identify the areas in which an infection has the potential to spread in an outbreak. In our model, each infected farm can infect neighbouring farms and the probability of transmission is a function of the inter-farm distance (spatial kernel). Therefore, the density of farms in an area is a good indicator for the probability of a major outbreak. In the epidemiological nomenclature, such density corresponds to a local reproduction ratio and we studied the critical behaviour of both the local density and the local reproduction ratio. We found that a threshold can be defined above which major outbreaks can occur, and the threshold value depends on the spatial kernel. Our expression for the threshold value is derived based on scaling arguments and contains two parameters in the exponents of the equation. We estimated these parameters from numerical results for the spatial spread using one particular mathematical function for the form of the spatial kernel. Subsequently, we show that our expression for the threshold using these estimated parameters agrees very well with numerical results for a number of different other functional forms of the spatial kernel (thus suggesting that we are dealing with universal parameters). As an illustration of the practical relevance of the presented method, we calculated the threshold value for avian influenza in the Netherlands and use it to produce a risk map for this disease.     

Risk based surveillance for early detection of low pathogenic avian influenza outbreaks in layer chickens

Current knowledge does not allow the prediction of when low pathogenic avian influenza virus (LPAIV) of the H5 and H7 subtypes infecting poultry will mutate to their highly pathogenic phenotype (HPAIV). This mutation may already take place in the first infected flock; hence early detection of LPAIV outbreaks will reduce the likelihood of pathogenicity mutations and large epidemics. The objective of this study was the development of a model for the design and evaluation of serological-surveillance programmes, with a particular focus on early detection of LPAIV infections in layer chicken flocks. Early detection is defined as the detection of an infected flock before it infects on average more than one other flock (between-flock reproduction ratio R_f < 1), hence a LPAI introduction will be detected when only one or a few other flocks are infected. We used a mathematical model that investigates the required sample size and sampling frequency for early detection by taking into account the LPAIV within- and between-flock infection dynamics as well as the diagnostic performance of the serological test used. Since layer flocks are the target of the surveillance, we also explored whether the use of eggs, is a good alternative to sera, as sample commodity. The model was used to refine the current Dutch serological-surveillance programme. LPAIV transmission-risk maps were constructed and used to target a risk-based surveillance strategy. In conclusion, we present a model that can be used to explore different sampling strategies, which combined with a cost-benefit analysis would enhance surveillance programmes for low pathogenic avian influenza.