Diversity of antagonistic bacteria isolated from medicinal plant Peganum harmala L.

The antimicrobial activity of plant extract of Peganum harmala, a medicinal plant has been studied already. However, knowledge about bacterial diversity associated with different parts of host plant antagonistic to different human pathogenic bacteria is limited. In this study, bacteria were isolated from root, leaf and fruit of plant. Among 188 bacterial isolates isolated from different parts of the plant only 24 were found to be active against different pathogenic bacteria i.e. Escherichia coli, Methicillin-resistant Staphylococcus aureus (MRSA), Enterococcus faecium, Enterococcus faecalis and Pseudomonas aeruginosa. These active bacterial isolates were identified on the basis of 16S rRNA gene analysis. Total population of bacteria isolated from plant was high in root, following leaf and fruit. Antagonistic bacteria were also more abundant in root as compared to leaf and fruit. Two isolates (EA5 and EA18) exhibited antagonistic activity against most of the targeted pathogenic bacteria mentioned above. Some isolates showed strong inhibition for one targeted pathogenic bacterium while weak or no inhibition for others. Most of the antagonistic isolates were active against MRSA, following E. faecium, P. aeruginosa, E. coli and E. faecalis. Taken together, our results show that medicinal plants are good source of antagonistic bacteria having inhibitory effect against clinical bacterial pathogens.     

Estimation of gross primary production of irrigated maize using Landsat-8 imagery and Eddy Covariance data

A study was conducted to understand the potential of Landsat-8 in the estimation of gross primary production (GPP) and to quantify the productivity of maize crop cultivated under hyper-arid conditions of Saudi Arabia. The GPP of maize crop was estimated by using the Vegetation Photosynthesis Model (VPM) utilizing remote sensing data from Landsat-8 reflectance (GPP_VPM) as well as the meteorological data provided by Eddy Covariance (EC) system (GPP_EC), for the period from August to November 2015. Results revealed that the cumulative GPP_EC for the entire growth period of maize crop was 1871 g C m⁻². However, the cumulative GPP determined as a function of the enhanced vegetation index – EVI (GPP_EVI) was 1979 g C m⁻², and that determined as a function of the normalized difference vegetation index – NDVI (GPP_NDVI) was 1754 g C m⁻². These results indicated that the GPP_EVI was significantly higher than the GPP_EC (R² = 0.96, P = 0.0241 and RMSE = 12.6%). While, the GPP_NDVI was significantly lower than the GPP_EC (R² = 0.93, P = 0.0384 and RMSE = 19.7%). However, the recorded relative error between the GPP_EC and both the GPP_EVI and the GPP_NDVI was −6.22% and 5.76%, respectively. These results demonstrated the potential of the landsat-8 driven VPM model for the estimation of GPP, which is relevant to the productivity and carbon fluxes.     

Herbivore regulation of plant abundance in aquatic ecosystems

Herbivory is a fundamental process that controls primary producer abundance and regulates energy and nutrient flows to higher trophic levels. Despite the recent proliferation of small‐scale studies on herbivore effects on aquatic plants, there remains limited understanding of the factors that control consumer regulation of vascular plants in aquatic ecosystems. Our current knowledge of the regulation of primary producers has hindered efforts to understand the structure and functioning of aquatic ecosystems, and to manage such ecosystems effectively. We conducted a global meta‐analysis of the outcomes of plant–herbivore interactions using a data set comprised of 326 values from 163 studies, in order to test two mechanistic hypotheses: first, that greater negative changes in plant abundance would be associated with higher herbivore biomass densities; second, that the magnitude of changes in plant abundance would vary with herbivore taxonomic identity. We found evidence that plant abundance declined with increased herbivore density, with plants eliminated at high densities. Significant between‐taxa differences in impact were detected, with insects associated with smaller reductions in plant abundance than all other taxa. Similarly, birds caused smaller reductions in plant abundance than echinoderms, fish, or molluscs. Furthermore, larger reductions in plant abundance were detected for fish relative to crustaceans. We found a positive relationship between herbivore species richness and change in plant abundance, with the strongest reductions in plant abundance reported for low herbivore species richness, suggesting that greater herbivore diversity may protect against large reductions in plant abundance. Finally, we found that herbivore–plant nativeness was a key factor affecting the magnitude of herbivore impacts on plant abundance across a wide range of species assemblages. Assemblages comprised of invasive herbivores and native plant assemblages were associated with greater reductions in plant abundance compared with invasive herbivores and invasive plants, native herbivores and invasive plants, native herbivores and mixed‐nativeness plants, and native herbivores and native plants. By contrast, assemblages comprised of native herbivores and invasive plants were associated with lower reductions in plant abundance compared with both mixed‐nativeness herbivores and native plants, and native herbivores and native plants. However, the effects of herbivore–plant nativeness on changes in plant abundance were reduced at high herbivore densities. Our mean reductions in aquatic plant abundance are greater than those reported in the literature for terrestrial plants, but lower than aquatic algae. Our findings highlight the need for a substantial shift in how biologists incorporate plant–herbivore interactions into theories of aquatic ecosystem structure and functioning. Currently, the failure to incorporate top‐down effects continues to hinder our capacity to understand and manage the ecological dynamics of habitats that contain aquatic plants.     

Osmotic stress decreases complexity underlying the electrophysiological dynamic in soybean

• Studies on plant electrophysiology are mostly focused on specific traits of single cells. Inspired by the complexity of the signalling network in plants, and by analogy with neurons in human brains, we sought evidence of high complexity in the electrical dynamics of plant signalling and a likely relationship with environmental cues.
• An EEG‐like standard protocol was adopted for high‐resolution measurements of the electrical signal in Glycine max seedlings. The signals were continuously recorded in the same plants before and after osmotic stimuli with a ?2 MPa mannitol solution. Non‐linear time series analyses methods were used as follows: auto‐correlation and cross‐correlation function, power spectra density function, and complexity of the time series estimated as Approximate Entropy (ApEn).
• Using Approximate Entropy analysis we found that the level of temporal complexity of the electrical signals was affected by the environmental conditions, decreasing when the plant was subjected to a low osmotic potential. Electrical spikes observed only after stimuli followed a power law distribution, which is indicative of scale invariance.
• Our results suggest that changes in complexity of the electrical signals could be associated with water stress conditions in plants. We hypothesised that the power law distribution of the spikes could be explained by a self‐organised critical state (SOC) after osmotic stress.

     

Numerical exploration of the parameter plane in a discrete predator–prey model

We propose a variant of the discrete Lotka–Volterra model for predator–prey interactions. A detailed stability and numerical analysis of the model are presented to explore the long time behaviour as each of the control parameter is varied independently. We show how the condition for survival of the predator depends on the natural death rate of predator and the efficiency of predation. The model is found to support different dynamical regimes asymptotically including predator extinction, stable fixed point and limit cycle attractors for co-existence of predator and prey and more complex dynamics involving chaotic attractors. We are able to locate exactly the domain of chaos in the parameter plane using a dimensional analysis.