Do leaf surface characteristics affect<Emphasis Type="Italic">Agrobacterium</Emphasis> infection in tea [<Emphasis Type="Italic">Camellia sinensis</Emphasis> (L.) O Kuntze]?

The host range specificity ofAgrobacterium with five tea cultivars and an unrelated species (Artemisia parviflora) having extreme surface characteristics was evaluated in the present study. The degree ofAgrobacterium infection in the five cultivars of tea was affected by leaf wetness, micro-morphology and surface chemistry. Wettable leaf surfaces of TV1, Upasi-9 andKangra jat showed higher rate (75%) ofAgrobacterium infection compared to Upasi-10 and ST-449, whereas non-wettable leaves ofA. parviflora showed minimum (25%) infection. This indicated that the leaves with glabrous surface having lower 8 (larger surface area covered by water droplet), higher phenol and wax content were more suitable forAgrobacterium infection. Caffeine fraction of tea promotedAgrobacterium infection even in leaves poor in wax (Upasi-10), whereas caffeine-free wax inhibited bothAgrobacterium growth and infection. Thus, study suggests the importance of leaf surface features in influencing theAgrobacterium infection in tea leaf explants. Our study also provides a basis for the screening of a clone/cultivar of a particular species most suitable forAgrobacterium infection the first step inAgrobacterium-mediated genetic transformation.     

Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes

Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we propose to derive environmental data layers by mapping ecological indicator values in space. We combined ~6 million plant occurrences with expert-based plant ecological indicator values (EIVs) of 3600 species in Switzerland. EIVs representing local soil properties (pH, moisture, moisture variability, aeration, humus and nutrients) and climatic conditions (continentality, light) were modelled at 93 m spatial resolution with the Random Forest algorithm and 16 predictors representing meso-climate, land use, topography and geology. Models were evaluated and predictions of EIVs were compared with soil inventory data. We mapped each EIV separately and evaluated EIV importance in explaining the distribution of 500 plant species using SDMs with a set of 30 environmental predictors. Finally, we tested how they improve an ensemble of SDMs compared to a standard set of predictors for ca 60 plant species. All EIV models showed excellent performance (|r| > 0.9) and predictions were correlated reasonably (|r| > 0.4) to soil properties measured in the field. Resulting EIV maps were among the most important predictors in SDMs. Also, in ensemble SDMs overall predictive performance increased, mainly through improved model specificity reducing species range overestimation. Combining large citizen science databases to expert-based EIVs is a powerful and cost–effective approach for generalizing local edaphic and climatic conditions over large areas. Producing ecologically meaningful predictors is a first step for generating better predictions of species distribution which is of main importance for decision makers in conservation and environmental management projects.     

Morphological factors of the central whorl leaf associated with leaf surface wetness and resistance in sorghum to shoot fly,Atherigona soccata*

Earlier studies showed that leaf surface water on the central whorl leaf of sorghum seedlings is associated with resistance to shoot fly. In this study, the results of an experiment to determine if leaf surface wetness (LSW) originates from atmospheric condensation or from the plant are described. Morphological structures: trichomes, stomata, leaf cuticle and quantity of surface wax of the central whorl leaf were also examined for their role in LSW production. The results suggest that LSW of the central whorl leaf originates from the plant and is not due to condensation of atmospheric moisture. The presence of trichomes was indirectly associated with LSW and resistance to shoot fly but stomatal density was not associated with LSW production. The amount of wax extracted per 100 mg of fresh weight varied significantly between genotypes and seedling age. It was more in susceptible than in resistant genotypes; however, cuticular thickness was not associated with resistance. It is suggested that LSW could be the result of some form of cuticular movement of water to the leaf surface.     

Assessing the effect of landscape features on pond colonisation by an elusive amphibian invader using environmental DNA

1. Environmental DNA (eDNA) is becoming an essential tool for detecting aquatic invasive species and investigating their spread. Surprisingly, this technique has been very rarely used to investigate habitat selection, site occupancy, and colonisation despite its higher capacity to detect many species.
2. The African clawed frog (Xenopus laevis) is a principally aquatic amphibian introduced in several continents from South Africa. In western France, no recent systematic survey of the invasion range has been attempted, mainly because of the elusive nature of the species. Furthermore, the influence of landscape features on invasion has never been investigated, even if adults and juveniles are known to disperse overland and along river networks.
3. Using presence–absence data generated by an eDNA survey conducted across the known invasion front of X. laevis in western France, we aimed to determine whether and how the landscape features surrounding a pond influence the probability that a pond is colonised.
4. Xenopus laevis was detected well beyond the formerly known invasive distribution and at the outward end of some transects, suggesting that we did not reach the actual invasion front in these parts of the range. The landscape variables that best predicted the presence of X. laevis in a pond were topographic wetness index and grass cover within a buffer of 250 m.
5. Higher values of both topographic wetness index and grass cover were negatively related to the occurrence probability. The effects of these two variables more likely to reflect dispersal behaviour than habitat preferences at the pond scale.
6. By combining the high detection probability of eDNA survey techniques and a landscape ecology approach, we may gain valuable insight into the colonisation process of water bodies by elusive invasive species. Such information is crucial to prevent access to specific sites and locate invasion front areas where connectivity can be disrupted, thus increasing the effectiveness of management countermeasures.