Worldwide Research on Plant Defense against Biotic Stresses as Improvement for Sustainable Agriculture

Agriculture is the basis for food production on a global scale. Sustainable agriculture tries to improve or maintain the quality of food without compromising the environment. As sessile organisms, plants cannot avoid adverse environmental conditions and contact with other living organisms. The damage caused to plants by other living organisms such as parasites and pathogens (virus, bacteria, fungi, nematodes or insects) brings about what is known as biotic stress. Plants are constantly exposed to biotic stress, which causes changes in plant metabolism involving physiological damages that lead to a reduction of their productivity. To fight biotic stress, plants have developed sophisticated defense mechanisms. Thus, understanding plant defense mechanisms might prevent important crop and economic losses. In this article, a bibliometric analysis of biotic stress is carried out. Different aspects of the publications are analyzed, such as publication type, research field, journal type, countries and their institutions, as well as the keyword occurrence frequency, and finally special attention is paid to the plant studied by the leading countries and institutions. As expected, journals selected by authors to publish their relevant findings are plant-specific journals. However, it should be noted that the fourth position, in terms of the number of publications per journal, is occupied by BMC Genomics journal. Such a journal considers mainly articles on genomics, which indicates the involvement of genetic factors in the control of biotic stress. Analysis of the keywords used in publications about biotic stress shows the great interest in the biotic–abiotic stress interaction, in the gene expression regulation in plants as well as phytohormones in the current research. In short, the great effort made by the scientific community in the biotic and abiotic stresses field with the aim to understand, regulate and control plant damages caused by biotic stress agents will help in the development of sustainable agriculture

Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases

Networks offer a powerful tool for understanding and visualizing inter-species interactions within an ecology. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for such a methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease - Leishmaniasis. This data mining approach allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases

Predicting spring barley yield from variety-specific yield potential, disease resistance and straw length, and from environment-specific disease loads and weed pressure

Abstract For low-input crop production, well-characterised varieties increase the possibilities of managing diseases and weeds. This analysis aims at developing a framework for analyzing grain yield using external varietal information about disease resistance, weed competitiveness and yield potential and quantifying the impact of susceptibility grouping and straw length scores (as a measure for weed competitiveness) for predicting spring barley grain yield under variable biotic stress levels. The study comprised 52 spring barley varieties and 17 environments, i.e., combinations of location, growing system and year. Individual varieties and their interactions with environments were analysed by factorial regression of grain yield on external variety information combined with observed environmental disease loads and weed pressure. The external information was based on the official Danish VCU testing. The most parsimonious models explained about 50% of the yield variation among varieties including genotypeenvironment interactions. Disease resistance characteristics of varieties, weighted with disease loads of powdery mildew, leaf rust and net blotch, respectively, had a highly significant influence on grain yield. The extend to which increased susceptibility resulted in increased yield losses in environments with high disease loads of the respective diseases was predicted. The effect of externally determined straw length scores, weighted with weed pressure, was weaker although significant for weeds with creeping growth habit. Higher grain yield was thus predicted for taller plants under weed pressure. The results are discussed in relation to the model ramework, impact of the considered traits and use of information from conventional variety testing in organic cropping systems

Assembly processes of gastropod community change with horizontal and vertical zonation in ancient Lake Ohrid: a metacommunity speciation perspective

The Balkan Lake Ohrid is the oldest and most diverse freshwater lacustrine system in Europe. However, it remains unclear whether species community composition, as well as the diversification of its endemic taxa, is mainly driven by dispersal limitation, environmental filtering, or species interaction. This calls for a holistic perspective involving both evolutionary processes and ecological dynamics, as provided by the unifying framework of the “metacommunity speciation model”. The current study used the species-rich model taxon Gastropoda to assess how extant communities in Lake Ohrid are structured by performing process-based metacommunity analyses. Specifically, the study aimed (1) to identifying the relative importance of the three community assembly processes and (2) to test whether the importance of these individual processes changes gradually with lake depth or discontinuously with eco-zone shifts. Based on automated eco-zone detection and process-specific simulation steps, we demonstrated that dispersal limitation had the strongest influence on gastropod community composition. However, it was not the exclusive assembly process, but acted together with the other two processes – environmental filtering and species interaction. The relative importance of the community assembly processes varied both with lake depth and eco-zones, though the processes were better predicted by the latter. This suggests that environmental characteristics have a pronounced effect on shaping gastropod communities via assembly processes. Moreover, the study corroborated the high importance of dispersal limitation for both maintaining species richness in Lake Ohrid (through its impact on community composition) and generating endemic biodiversity (via its influence on diversification processes). However, according to the metacommunity speciation model, the inferred importance of environmental filtering and biotic interaction also suggests a small but significant influence of ecological speciation. These findings contribute to the main goal of the Scientific Collaboration on Past Speciation Conditions in Lake Ohrid (SCOPSCO) deep drilling initiative – inferring the drivers of biotic evolution – and might provide an integrative perspective on biological and limnological dynamics in ancient Lake Ohrid

The role of eco-evolutionary experience in invasion success

Invasion ecology has made considerable progress in identifying specific mechanisms that potentially determine success and failure of biological invasions. Increasingly, efforts are being made to interrelate or even synthesize the growing number of hypotheses in order to gain a more comprehensive and integrative understanding of invasions. We argue that adopting an eco-evolutionary perspective on invasions is a promising approach to achieve such integration. It emphasizes the evolutionary antecedents of invasions, i.e. the species’ evolutionary legacy and its role in shaping novel biotic interactions that arise due to invasions. We present a conceptual framework consisting of five hypothetical scenarios about the influence of so-called ‘eco-evolutionary experience’ in resident native and invading non-native species on invasion success, depending on the type of ecological interaction (predation, competition, mutualism, and commensalism). We show that several major ecological invasion hypotheses, including ‘enemy release’, ‘EICA’, ‘novel weapons’, ‘naive prey’, ‘new associations’, ‘missed mutualisms’ and ‘Darwin’s naturalization hypothesis’ can be integrated into this framework by uncovering their shared implicit reference to the concept of eco-evolutionary experience. We draft a routine for the assessment of eco-evolutionary experience in native and non-native species using a food web-based example and propose two indices (xpFocal index and xpResidents index) for the actual quantification of eco-evolutionary experience. Our study emphasizes the explanatory potential of an eco-evolutionary perspective on biological invasions

Challenges for the development of a biotic ligand model predicting copper toxicity in estuaries and seas

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2011 SETAC.An effort is ongoing to develop a biotic ligand model (BLM) that predicts copper (Cu) toxicity in estuarine and marine environments. At present, the BLM accounts for the effects of water chemistry on Cu speciation, but it does not consider the influence of water chemistry on the physiology of the organisms. We discuss how chemistry affects Cu toxicity not only by controlling its speciation, but also by affecting the osmoregulatory physiology of the organism, which varies according to salinity. In an attempt to understand the mechanisms of Cu toxicity and predict its impacts, we explore the hypothesis that the common factor linking the main toxic effects of Cu is the enzyme carbonic anhydrase (CA), because it is a Cu target with multiple functions and salinity-dependent expression and activity. According to this hypothesis, the site of action of Cu in marine fish may be not only the gill, but also the intestine, because in this tissue CA plays an important role in ion transport and water adsorption. Therefore, the BLM of Cu toxicity to marine fish should also consider the intestine as a biotic ligand. Finally, we underline the need to incorporate the osmotic gradient into the BLM calculations to account for the influence of physiology on Cu toxicity.Brunel Universit

ASSESSING THE RELATIVE INFLUENCES OF ABIOTIC AND BIOTIC FACTORS ON A SPECIES’ DISTRIBUTION USING PSEUDO-ABSENCE AND FUNCTIONAL TRAIT DATA: A CASE STUDY WITH THE AMERICAN EEL (Anguilla rostrata)

Species’ distributions are influenced by abiotic and biotic factors but direct comparison of their relative importance is difficult, particularly when working with complex, multi-species datasets. Here, we present a flexible method to compare abiotic and biotic influences at common scales. First, data representing abiotic and biotic factors are collected using a combination of geographic information system, remotely sensed, and species’ functional trait data. Next, the relative influences of each predictor variable on the occurrence of a focal species are compared. Specifically, ‘sample’ data from sites of known occurrence are compared with ‘background’ data (i.e. pseudo-absence data collected at sites where occurrence is unknown, combined with sample data). Predictor variables that may have the strongest influence on the focal species are identified as those where sample data are clearly distinct from the corresponding background distribution. To demonstrate the method, effects of hydrology, physical habitat, and co-occurring fish functional traits are assessed relative to the contemporary (1950 – 1990) distribution of the American Eel (Anguilla rostrata) in six Mid-Atlantic (USA) rivers. We find that Eel distribution has likely been influenced by the functional characteristics of co-occurring fishes and by local dam density, but not by other physical habitat or hydrologic factors

Hydro-chemical study of the evolution of interstellar pre-biotic molecules during the collapse of molecular clouds

One of the stumbling blocks for studying the evolution of interstellar molecules is the lack of adequate knowledge of the rate co-efficients of various reactions which take place in the Interstellar medium and molecular clouds. Some of the theoretical models of rate coefficients do exist in the literature for computing abundances of the complex pre-biotic molecules. So far these have been used to study the abundances of these molecules in space. However, in order to obtain more accurate final compositions in these media, we find out the rate coefficients for the formation of some of the most important interstellar pre-biotic molecules by using quantum chemical theory. We use these rates inside our hydro-chemical model to find out the chemical evolution and the final abundances of the pre-biotic species during the collapsing phase of a proto-star. We find that a significant amount of various pre-biotic molecules could be produced during the collapsing phase of a proto-star. We study extensively the formation these molecules via successive neutral-neutral and radical-radical/radical-molecular reactions. We present the time evolution of the chemical species with an emphasis on how the production of these molecules varies with the depth of a cloud. We compare the formation of adenine in the interstellar space using our rate-coefficients and using those obtained from the existing theoretical models. Formation routes of the pre-biotic molecules are found to be highly dependent on the abundances of the reactive species and the rate coefficients involved in the reactions. Presence of grains strongly affect the abundances of the gas phase species. We also carry out a comparative study between different pathways available for the synthesis of adenine, alanine, glycine and other molecules considered in our network.Comment: 12 pages, 4 figure

Can Ecological Interactions be Inferred from Spatial Data?

The characterisation and quantication of ecological interactions, and the construction of species distributions and their associated ecological niches, is of fundamental theoretical and practical importance. In this paper we give an overview of a Bayesian inference framework, developed over the last 10 years, which, using spatial data, offers a general formalism within which ecological interactions may be characterised and quantied. Interactions are identied through deviations of the spatial distribution of co-occurrences of spatial variables relative to a benchmark for the non-interacting system, and based on a statistical ensemble of spatial cells. The formalism allows for the integration of both biotic and abiotic factors of arbitrary resolution. We concentrate on the conceptual and mathematical underpinnings of the formalism, showing how, using the Naive Bayes approximation, it can be used to not only compare and contrast the relative contribution from each variable, but also to construct species distributions and niches based on arbitrary variable type. We show how the formalism can be used to quantify confounding and therefore help disentangle the complex causal chains that are present in ecosystems. We also show species distributions and their associated niches can be used to infer standard "micro" ecological interactions, such as predation and parasitism. We present several representative use cases that validate our framework, both in terms of being consistent with present knowledge of a set of known interactions, as well as making and validating predictions about new, previously unknown interactions in the case of zoonoses