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SDM performance varied for different range dynamics. Prediction accuracies decreased when abrupt range shifts occurred as species were outpaced by the rate of climate change, and increased again when a new equilibrium situation was realised. When ranges contracted, prediction accuracies increased as the absences were predicted well. Far- dispersing species were faster in tracking climate change, and were predicted more accurately by SDMs than short- dispersing species. BRTs mostly outperformed GLMs. The presence of a predator, and the inclusion of its incidence as an environmental predictor, made BRTs and GLMs perform similarly. Results are discussed in light of other studies dealing with effects of ecological traits and processes on SDM performance. Perspectives are given on further advancements of SDMs and for possible interfaces with more mechanistic approaches in order to improve predictions under environmental change.
Data limitations can lead to unrealistic fits of predictive species distribution models (SDMs) and spurious extrapolation to novel environments. Here, we want to draw attention to novel combinations of environmental predictors that are within the sampled range of individual predictors but are nevertheless outside the sample space. These tend to be overlooked when visualizing model behaviour. They may be a cause of differing model transferability and environmental change predictions between methods, a problem described in some studies but generally not well understood. We here use a simple simulated data example to illustrate the problem and provide new and complementary visualization techniques to explore model behaviour and predictions to novel environments. We then apply these in a more complex real-world example. Our results underscore the necessity of scrutinizing model fits, ecological theory and environmental novelty.
Density regulation influences population dynamics through its effects on demographic rates and consequently constitutes a key mechanism explaining the response of organisms to environmental changes. Yet, it is difficult to establish the exact form of density dependence from empirical data. Here, we developed an individual-based model to explore how resource limitation and behavioural processes determine the spatial structure of white stork Ciconia ciconia populations and regulate reproductive rates. We found that the form of density dependence differed considerably between landscapes with the same overall resource availability and between home range selection strategies, highlighting the importance of fine-scale resource distribution in interaction with behaviour. In accordance with theories of density dependence, breeding output generally decreased with density but this effect was highly variable and strongly affected by optimal foraging strategy, resource detection probability and colonial behaviour. Moreover, our results uncovered an overlooked consequence of density dependence by showing that high early nestling mortality in storks, assumed to be the outcome of harsh weather, may actually result from density dependent effects on food provision. Our findings emphasize that accounting for interactive effects of individual behaviour and local environmental factors is crucial for understanding density-dependent processes within spatially structured populations. Enhanced understanding of the ways animal populations are regulated in general, and how habitat conditions and behaviour may dictate spatial population structure and demographic rates is critically needed for predicting the dynamics of populations, communities and ecosystems under changing environmental conditions.
The ability of some plant species to dominate communities in new biogeographical ranges has been attributed to an innate higher competitive ability and release from co-evolved specialist enemies. Specifically, invasive success in the new range might be explained by release from biotic negative soil-feedbacks, which control potentially dominant species in their native range. To test this hypothesis, we grew individuals from sixteen phylogenetically paired European grassland species that became either invasive or naturalized in new ranges, in either sterilized soil or in sterilized soil with unsterilized soil inoculum from their native home range. We found that although the native members of invasive species generally performed better than those of naturalized species, these native members of invasive species also responded more negatively to native soil inoculum than did the native members of naturalized species. This supports our hypothesis that potentially invasive species in their native range are held in check by negative soil-feedbacks. However, contrary to expectation, negative soil-feedbacks in potentially invasive species were not much increased by interspecific competition. There was no significant variation among families between invasive and naturalized species regarding their feedback response (negative vs. neutral). Therefore, we conclude that the observed negative soil feedbacks in potentially invasive species may be quite widespread in European families of typical grassland species.
Bacterial molybdoenzymes are key enzymes involved in the global sulphur, nitrogen and carbon cycles. These enzymes require the insertion of the molybdenum cofactor (Moco) into their active sites and are able to catalyse a large range of redox-reactions. Escherichia coli harbours nineteen different molybdoenzymes that require a tight regulation of their synthesis according to substrate availability, oxygen availability and the cellular concentration of molybdenum and iron. The synthesis and assembly of active molybdoenzymes are regulated at the level of transcription of the structural genes and of translation in addition to the genes involved in Moco biosynthesis. The action of global transcriptional regulators like FNR, NarXL/QP, Fur and ArcA and their roles on the expression of these genes is described in detail. In this review we focus on what is known about the molybdenum- and iron-dependent regulation of molybdoenzyme and Moco biosynthesis genes in the model organism E. coli. The gene regulation in E. coli is compared to two other well studied model organisms Rhodobacter capsulatus and Shewanella oneidensis.
Molybdenum cofactor (Moco) biosynthesis is a complex process that involves the coordinated function of several proteins. In recent years it has become obvious that the availability of iron plays an important role in the biosynthesis of Moco. First, the MoaA protein binds two (4Fe-4S] clusters per monomer. Second, the expression of the moaABCDE and moeAB operons is regulated by FNR, which senses the availability of oxygen via a functional NFe-4S) cluster. Finally, the conversion of cyclic pyranopterin monophosphate to molybdopterin requires the availability of the L-cysteine desulfurase IscS, which is a shared protein with a main role in the assembly of Fe-S clusters. In this report, we investigated the transcriptional regulation of the moaABCDE operon by focusing on its dependence on cellular iron availability. While the abundance of selected molybdoenzymes is largely decreased under iron-limiting conditions, our data show that the regulation of the moaABCDE operon at the level of transcription is only marginally influenced by the availability of iron. Nevertheless, intracellular levels of Moco were decreased under iron-limiting conditions, likely based on an inactive MoaA protein in addition to lower levels of the L-cysteine desulfurase IscS, which simultaneously reduces the sulfur availability for Moco production. IMPORTANCE FNR is a very important transcriptional factor that represents the master switch for the expression of target genes in response to anaerobiosis. Among the FNR-regulated operons in Escherichia coli is the moaABCDE operon, involved in Moco biosynthesis. Molybdoenzymes have essential roles in eukaryotic and prokaryotic organisms. In bacteria, molybdoenzymes are crucial for anaerobic respiration using alternative electron acceptors. This work investigates the connection of iron availability to the biosynthesis of Moco and the production of active molybdoenzymes.
The c-Fosc-Jun complex forms the activator protein 1 transcription factor, a therapeutic target in the treatment of cancer. Various synthetic peptides have been designed to try to selectively disrupt the interaction between c-Fos and c-Jun at its leucine zipper domain. To evaluate the binding affinity between these synthetic peptides and c-Fos, polarizable and nonpolarizable molecular dynamics (MD) simulations were conducted, and the resulting conformations were analyzed using the molecular mechanics generalized Born surface area (MM/GBSA) method to compute free energies of binding. In contrast to empirical and semiempirical approaches, the estimation of free energies of binding using a combination of MD simulations and the MM/GBSA approach takes into account dynamical properties such as conformational changes, as well as solvation effects and hydrophobic and hydrophilic interactions. The predicted binding affinities of the series of c-Jun-based peptides targeting the c-Fos peptide show good correlation with experimental melting temperatures. This provides the basis for the rational design of peptides based on internal, van der Waals, and electrostatic interactions.
Background: Protein kinases constitute a particularly large protein family in Arabidopsis with important functions in cellular signal transduction networks. At the same time Arabidopsis is a model plant with high frequencies of gene duplications. Here, we have conducted a systematic analysis of the Arabidopsis kinase complement, the kinome, with particular focus on gene duplication events. We matched Arabidopsis proteins to a Hidden-Markov Model of eukaryotic kinases and computed a phylogeny of 942 Arabidopsis protein kinase domains and mapped their origin by gene duplication.
Results: The phylogeny showed two major clades of receptor kinases and soluble kinases, each of which was divided into functional subclades. Based on this phylogeny, association of yet uncharacterized kinases to families was possible which extended functional annotation of unknowns. Classification of gene duplications within these protein kinases revealed that representatives of cytosolic subfamilies showed a tendency to maintain segmentally duplicated genes, while some subfamilies of the receptor kinases were enriched for tandem duplicates. Although functional diversification is observed throughout most subfamilies, some instances of functional conservation among genes transposed from the same ancestor were observed. In general, a significant enrichment of essential genes was found among genes encoding for protein kinases.
Conclusions: The inferred phylogeny allowed classification and annotation of yet uncharacterized kinases. The prediction and analysis of syntenic blocks and duplication events within gene families of interest can be used to link functional biology to insights from an evolutionary viewpoint. The approach undertaken here can be applied to any gene family in any organism with an annotated genome.
In high-value sweet cherry (Prunus avium), the red coloration - determined by the anthocyanins content - is correlated with the fruit ripeness stage and market value. Non-destructive spectroscopy has been introduced in practice and may be utilized as a tool to assess the fruit pigments in the supply chain processes. From the fruit spectrum in the visible (Vis) wavelength range, the pigment contents are analyzed separately at their specific absorbance wavelengths.
A drawback of the method is the need for re-calibration due to varying optical properties of the fruit tissue. In order to correct for the scattering differences, most often the spectral intensity in the visible spectrum is normalized by wavelengths in the near infrared (NIR) range, or pre-processing methods are applied in multivariate calibrations.
In the present study, the influence of the fruit scattering properties on the Vis/NIR fruit spectrum were corrected by the effective pathlength in the fruit tissue obtained from time-resolved readings of the distribution of time-of-flight (DTOF). Pigment analysis was carried out according to Lambert-Beer law, considering fruit spectral intensities, effective pathlength, and refractive index. Results were compared to commonly applied linear color and multivariate partial least squares (PLS) regression analysis. The approaches were validated on fruits at different ripeness stages, providing variation in the scattering coefficient and refractive index exceeding the calibration sample set.
In the validation, the measuring uncertainty of non-destructively analyzing fruits with Vis/NIR spectra by means of PLS or Lambert-Beer in comparison with combined application of Vis/NIR spectroscopy and DTOF measurements showed a dramatic bias reduction as well as enhanced coefficients of determination when using both, the spectral intensities and apparent information on the scattering influence by means of DTOF readings. Corrections for the refractive index did not render improved results.