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Over the last two decades, macroecology the analysis of large-scale, multi-species ecological patterns and processes has established itself as a major line of biological research. Analyses of statistical links between environmental variables and biotic responses have long and successfully been employed as a main approach, but new developments are due to be utilized. Scanning the horizon of macroecology, we identified four challenges that will probably play a major role in the future. We support our claims by examples and bibliographic analyses. 1) Integrating the past into macroecological analyses, e.g. by using paleontological or phylogenetic information or by applying methods from historical biogeography, will sharpen our understanding of the underlying reasons for contemporary patterns. 2) Explicit consideration of the local processes that lead to the observed larger-scale patterns is necessary to understand the fine-grain variability found in nature, and will enable better prediction of future patterns (e.g. under environmental change conditions). 3) Macroecology is dependent on large-scale, high quality data from a broad spectrum of taxa and regions. More available data sources need to be tapped and new, small-grain large-extent data need to be collected. 4) Although macroecology already lead to mainstreaming cutting-edge statistical analysis techniques, we find that more sophisticated methods are needed to account for the biases inherent to sampling at large scale. Bayesian methods may be particularly suitable to address these challenges. To continue the vigorous development of the macroecological research agenda, it is time to address these challenges and to avoid becoming too complacent with current achievements.
Aim Biotic interactions within guilds or across trophic levels have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of species interaction distribution models (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices. Location Local to global. Methods We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions. Results Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co-occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non-stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio-temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species effect and response traits. Main conclusions There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co-occurrence datasets across large-scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio-temporal data on biotic interactions in multispecies communities.
Although intensification of toxic cyanobacterial blooms over the last decade is a matter of growing concern due to bloom impact on water quality, the biological role of most of the toxins produced is not known. In this critical review we focus primarily on the biological role of two toxins, microcystins and cylindrospermopsin, in inter- and intra-species communication and in nutrient acquisition. We examine the experimental evidence supporting some of the dogmas in the field and raise several open questions to be dealt with in future research. We do not discuss the health and environmental implications of toxin presence in the water body.
The blowfly salivary gland - A model system for analyzing the regulation of plasma membrane V-ATPase
(2012)
Vacuolar H+-ATPases (V-ATPases) are heteromultimeric proteins that use the energy of ATP hydrolysis for the electrogenic transport of protons across membranes. They are common to all eukaryotic cells and are located in the plasma membrane or in membranes of acid organelles. In many insect epithelia, V-ATPase molecules reside in large numbers in the apical plasma membrane and create an electrochemical proton gradient that is used for the acidification or alkalinization of the extracellular space, the secretion or reabsorption of ions and fluids, the import of nutrients, and diverse other cellular activities. Here, we summarize our results on the functions and regulation of V-ATPase in the tubular salivary gland of the blowfly Calliphora vicina. In this gland, V-ATPase activity energizes the secretion of a KCl-rich saliva in response to the neurohormone serotonin (5-HT). Because of particular morphological and physiological features, the blowfly salivary glands are a superior and exemplary system for the analysis of the intracellular signaling pathways and mechanisms that modulate V-ATPase activity and solute transport in an insect epithelium.