Equine immunity to cyathostome infections

To study the protective responses of cyathostome-infected ponies, two challenges were performed employing animals with different histories of exposure to these parasites. The hypothesis developed and to be tested in these experiments was that ponies that had longer exposure to cyathostome contaminated pastures would express acquired resistance to infection. The assumption behind this hypothesis was that helminth-naïve ponies infected with cyathostomes would eliminate the infection using only innate immune responses. Whereas previously exposed ponies would eliminate the infection with acquired immune responses, and these would be more effective in ponies with longer exposure to cyathostomes. Thus, helminth-naïve animals would acquire the largest number of worms, followed in decreasing order by young and then adult ponies. Two types of challenges were used: an experimental infection with 150,000 cyathostome infective third stage (L3) given over a period of 5 days, and the natural acquisition of infection by grazing a cyathostome contaminated pasture for 7 weeks. The natural challenge was performed to confirm the data obtained with the experimental challenge, therefore to validate its use. The parasitological data recovered showed that ponies with acquired resistance to cyathostome infections had reduced total number of worms, of developing larvae, luminal fourth stage larvae, adult parasites and of cyathostome species. The acquisition of resistance was also observed as elevations in the hypobiotic larvae numbers and of intestinal mast cells, intestinal and peripheral eosinophils, and antibody responses. These responses were consistent with increases in Th2 type cytokines, principally IL-4. The data obtained suggest that the immune mechanisms of resistance developed in ponies with acquired protection to cyathostome are slow to develop and are targeted against each parasite stage present in the host. These results warrant further research in the area, especially in the difference between immune mechanisms of helminth naïve ponies and animals with short exposures to cyathostome contaminated pastures

«Репетиции смерти» в стихотворениях “Блюз беженцев» У.Х. Одена и «Беженцы» Р. Джаррелла (к вопросу осмысления проблемы беженцев в американской поззии о второй мировой войне)

The article deals with the best American poems devoted to refugees of the world war II. The comparative analyses based on the thematic and stylistic similarity was carried out. Various forms of the main artistic device – repetition – were studied

Linking Vegetation-Climate-Fire Relationships in Sub-Saharan Africa to Key Ecological Processes in Two Dynamic Global Vegetation Models

Africa is largely influenced by fires, which play an important ecological role influencing the distribution and structure of grassland, savanna and forest biomes. Here vegetation strongly interacts with climate and other environmental factors, such as herbivory and humans. Fire-enabled Dynamic Global Vegetation Models (DGVMs) display high uncertainty in predicting the distribution of current tropical biomes and the associated transitions, mainly due to the way they represent the main ecological processes and feedbacks related to water and fire. The aim of this study is to evaluate the outcomes of two state-of-the–art DGVMs, LPJ-GUESS and JSBACH, also currently used in two Earth System Models (ESMs), in order to assess which key ecological processes need to be included or improved to represent realistic interactions between vegetation cover, precipitation and fires in sub-Saharan Africa. To this end, we compare models and remote-sensing data, analyzing the relationships between tree and grass cover, mean annual rainfall, average rainfall seasonality and average fire intervals, using generalized linear models, and we compare the patterns of grasslands, savannas, and forests in sub-Saharan Africa. Our analysis suggests that LPJ-GUESS (with a simple fire-model and complex vegetation description) performs well in regions of low precipitation, while in humid and mesic areas the representation of the fire process should probably be improved to obtain more open savannas. JSBACH (with a complex fire-model and a simple vegetation description) can simulate a vegetation-fire feedback that can maintain open savannas at intermediate and high precipitation, although this feedback seems to have stronger effects than observed, while at low precipitation JSBACH needs improvements in the representation of tree-grass competition and drought effects. This comparative process-based analysis permits to highlight the main factors that determine the tropical vegetation distribution in models and observations in sub-Saharan Africa, suggesting possible improvements in DGVMs and, consequently, in ESM simulations for future projections. Given the need to use carbon storage in vegetation as a climate mitigation measure, these models represent a valuable tool to improve our understanding of the sustainability of vegetation carbon pools as a carbon sink and the vulnerability to disturbances such as fire

Fire responses shape plant communities in a minimal model for fire ecosystems across the world

Across plant communities worldwide, fire regimes reflect a combination of climatic factors and plant characteristics. To shed new light on the complex relationships between plant characteristics and fire regimes, we developed a new conceptual, mechanistic model that includes plant competition, stochastic fires, and fire-vegetation feedback. Considering a single standing plant functional type, we observed that highly flammable and slowly colonizing plants can persist only when they have a strong fire response, while fast colonizing and less flammable plants can display a larger range of fire responses. At the community level, the fire response of the strongest competitor determines the existence of alternative ecological states, i.e. different plant communities, under the same environmental conditions. Specifically, when the strongest competitor had a very strong fire response, such as in Mediterranean forests, only one ecological state could be achieved. Conversely, when the strongest competitor was poorly fire-adapted, alternative ecological states emerged, for example between tropical humid savannas and forests, or between different types of boreal forests. These findings underline the importance of including the plant fire response when modeling fire ecosystems, e.g. to predict the vegetation response to invasive species or to climate change

Гоголевские традиции в творчестве М. Булгакова

Model studies suggest that semiarid ecosystems with patterned vegetation can respond in a nonlinear way to climate change. This means that gradual changes can result in a rapid transition to a desertified state. Previous model studies focused on the response of patterned semiarid ecosystems to changes in mean annual rainfall. The intensity of rain events, however, is projected to change as well in the coming decades. In this paper, we study the effect of changes in rainfall intensity on the functioning of patterned semiarid ecosystems with a spatially explicit model that captures rainwater partitioning and runoff-runon processes with simple event-based process descriptions. Analytical and numerical analyses of the model revealed that rainfall intensity is a key parameter in explaining patterning of vegetation in semiarid ecosystems as low mean rainfall intensities do not allow for vegetation patterning to occur. Surprisingly, we found that, for a constant annual rainfall rate, both an increase and a decrease in mean rainfall intensity can trigger desertification. An increase negatively affects productivity as a greater fraction of the rainwater is lost as runoff. This can result in a shift to a bare desert state only if the mean rainfall intensity exceeds the infiltration capacity of bare soil. On the other hand, a decrease in mean rainfall intensity leads to an increased fraction of rainwater infiltrating in bare soils, remaining unavailable to plants. Our findings suggest that considering rainfall intensity as a variable may help in assessing the proximity to regime shifts in patterned semiarid ecosystems and that monitoring losses of resource through runoff and bare soil infiltration could be used to determine ecosystem resilience. Key Points Rainfall intensity controls patterning and the resilience of arid ecosystems Both an increase and decrease in rainfall intensity can trigger desertification In line with observations, three types of rain events were identified in our mode

Rethinking tipping points in spatial ecosystems

The theory of alternative stable states and tipping points has garnered a lot of attention in the last decades. It predicts potential critical transitions from one ecosystem state to a completely different state under increasing environmental stress. However, typically ecosystem models that predict tipping do not resolve space explicitly. As ecosystems are inherently spatial, it is important to understand the effects of incorporating spatial processes in models, and how those insights translate to the real world. Moreover, spatial ecosystem structures, such as vegetation patterns, are important in the prediction of ecosystem response in the face of environmental change. Models and observations from real savanna ecosystems and drylands have suggested that they may exhibit both tipping behavior as well as spatial pattern formation. Hence, in this paper, we use mathematical models of humid savannas and drylands to illustrate several pattern formation phenomena that may arise when incorporating spatial dynamics in models that exhibit tipping without resolving space. We argue that such mechanisms challenge the notion of large scale critical transitions in response to global change and reveal a more resilient nature of spatial ecosystems

Intra-seasonal rainfall variability and herbivory affect the interaction outcome of two dryland plant species

Increases in drought frequency in combination with overgrazing may result in degradation of (semi-) arid ecosystems. Facilitative interactions between plants are a key mechanism in preventing degradation, but it is poorly understood how they respond to increased stress by combined drought and herbivory. In this study, we used an ecohydrological model, to simulate the plant growth of two plant species interacting with each other under different rainfall and herbivory pressure scenarios. The functional traits of the two modeled plants were based on a prior field experiment in southeastern Spain, in which an unpalatable “nurse” species protected a palatable protégé’ species from herbivory. Moreover, the nurse species was more drought-resistant; that is, it had a lower wilting point, whereas the protégé species had a higher optimal growth rate. Firstly, we investigated the coexistence of the two plant species growing under a single limiting resource, focusing on the effect of intra-seasonal rainfall variability. We found that longer periods without rainfall within the wet season resulted in stable coexistence, whereas nearly constant rainfall led to competitive exclusion of the protégé by the nurse species. Secondly, we investigated how plant interactions varied along our studied gradients. Using the neighbor effect intensity and importance indices, we found that competitive effects increased with more constant rainfall. Moreover, higher herbivory rates resulted in increased facilitative effects of the nurse on the protégé species, but facilitative effects could only prevail over competitive effects under currently observed or higher intra-seasonal rainfall variability. This study highlights the relevance of intra-seasonal rainfall variability in explaining coexistence of species in dryland ecosystems and shows that increasing intra-seasonal rainfall variability or herbivory pressure can result in more facilitative effects from a nurse species. This information is crucial to obtain a better insight into the long-term coexistence of species, and the resulting stability of dryland ecosystems in response to future climate change

Evasion of tipping in complex systems through spatial pattern formation

The concept of tipping points and critical transitions helps inform our understanding of the catastrophic effects that global change may have on ecosystems, Earth system components, and the whole Earth system. The search for early warning indicators is ongoing, and spatial self-organization has been interpreted as one such signal. Here, we review how spatial self-organization can aid complex systems to evade tipping points and can therefore be a signal of resilience instead. Evading tipping points through various pathways of spatial pattern formation may be relevant for many ecosystems and Earth system components that hitherto have been identified as tipping prone, including for the entire Earth system. We propose a systematic analysis that may reveal the broad range of conditions under which tipping is evaded and resilience emerges

Revealing patterns of local species richness along environmental gradients with a novel network tool

How species richness relates to environmental gradients at large extents is commonly investigated aggregating local site data to coarser grains. However, such relationships often change with the grain of analysis, potentially hiding the local signal. Here we show that a novel network technique, the “method of reflections”, could unveil the relationships between species richness and climate without such drawbacks. We introduced a new index related to potential species richness, which revealed large scale patterns by including at the local community level information about species distribution throughout the dataset (i.e., the network). The method effectively removed noise, identifying how far site richness was from potential. When applying it to study woody species richness patterns in Spain, we observed that annual precipitation and mean annual temperature explained large parts of the variance of the newly defined species richness, highlighting that, at the local scale, communities in drier and warmer areas were potentially the species richest. Our method went far beyond what geographical upscaling of the data could unfold, and the insights obtained strongly suggested that it is a powerful instrument to detect key factors underlying species richness patterns, and that it could have numerous applications in ecology and other fields