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Developments of future scenarios of Antarctic ecosystems are still in their infancy, whilst predictions of the physical environment are recognized as being of global relevance and corresponding models are under continuous development. However, in the context of environmental change simulations of the future of the Antarctic biosphere are increasingly demanded by decision makers and the public, and are of fundamental scientific interest. This paper briefly reviews existing predictive models applied to Antarctic ecosystems before providing a conceptual framework for the further development of spatially and temporally explicit ecosystem models. The concept suggests how to improve approaches to relating species' habitat description to the physical environment, for which a case study on sea urchins is presented. In addition, the concept integrates existing and new ideas to consider dynamic components, particularly information on the natural history of key species, from physiological experiments and biomolecular analyses. Thereby, we identify and critically discuss gaps in knowledge and methodological limitations. These refer to process understanding of biological complexity, the need for high spatial resolution oceanographic data from the entire water column, and the use of data from biomolecular analyses in support of such ecological approaches. Our goal is to motivate the research community to contribute data and knowledge to a holistic, Antarctic-specific, macroecological framework. Such a framework will facilitate the integration of theoretical and empirical work in Antarctica, improving our mechanistic understanding of this globally influential ecoregion, and supporting actions to secure this biodiversity hotspot and its ecosystem services.
Multidirectional communicative interactions in social networks can have a profound effect on mate choice behavior. Male Atlantic molly Poecilia mexicana exhibit weaker mating preferences when an audience male is presented. This could be a male strategy to reduce sperm competition risk: interacting more equally with different females may be advantageous because rivals might copy mate choice decisions. In line with this hypothesis, a previous study found males to show a strong audience effect when being observed while exercising mate choice, but not when the rival was presented only before the choice tests. Audience effects on mate choice decisions have been quantified in poeciliid fishes using association preference designs, but it remains unknown if patterns found from measuring association times translate into actual mating behavior. Thus, we created five audience treatments simulating different forms of perceived sperm competition risk and determined focal males' mating preferences by scoring pre-mating (nipping) and mating behavior (gonopodial thrusting). Nipping did not reflect the pattern that was found when association preferences were measured, while a very similar pattern was uncovered in thrusting behavior. The strongest response was observed when the audience could eavesdrop on the focal male's behavior. A reduction in the strength of focal males' preferences was also seen after the rival male had an opportunity to mate with the focal male's preferred mate. In comparison, the reduction of mating preferences in response to an audience was greater when measuring association times than actual mating behavior. While measuring direct sexual interactions between the focal male and both stimulus females not only the male's motivational state is reflected but also females' behavior such as avoidance of male sexual harassment.
Ironsulfur clusters (ISCs) are important prosthetic groups that define the functions of many proteins. Proteins with ISCs (called ironsulfur or FeS proteins) are present in mitochondria, the cytosol, the endoplasmic reticulum and the nucleus. They participate in various biological pathways including oxidative phosphorylation (OXPHOS), the citric acid cycle, iron homeostasis, heme biosynthesis and DNA repair. Here, we report a homozygous mutation in LYRM4 in two patients with combined OXPHOS deficiency. LYRM4 encodes the ISD11 protein, which forms a complex with, and stabilizes, the sulfur donor NFS1. The homozygous mutation (c.203GT, p.R68L) was identified via massively parallel sequencing of 1000 mitochondrial genes (MitoExome sequencing) in a patient with deficiency of complexes I, II and III in muscle and liver. These three complexes contain ISCs. Sanger sequencing identified the same mutation in his similarly affected cousin, who had a more severe phenotype and died while a neonate. Complex IV was also deficient in her skeletal muscle. Several other FeS proteins were also affected in both patients, including the aconitases and ferrochelatase. Mutant ISD11 only partially complemented for an ISD11 deletion in yeast. Our in vitro studies showed that the l-cysteine desulfurase activity of NFS1 was barely present when co-expressed with mutant ISD11. Our findings are consistent with a defect in the early step of ISC assembly affecting a broad variety of FeS proteins. The differences in biochemical and clinical features between the two patients may relate to limited availability of cysteine in the newborn period and suggest a potential approach to therapy.
Observed streamflow of headwater catchments of the Tarim River (Central Asia) increased by about 30% over the period 1957-2004. This study aims at assessing to which extent these streamflow trends can be attributed to changes in air temperature or precipitation. The analysis includes a data-based approach using multiple linear regression and a simulation-based approach using a hydrological model. The hydrological model considers changes in both glacier area and surface elevation. It was calibrated using a multiobjective optimization algorithm with calibration criteria based on glacier mass balance and daily and interannual variations of discharge. The individual contributions to the overall streamflow trends from changes in glacier geometry, temperature, and precipitation were assessed using simulation experiments with a constant glacier geometry and with detrended temperature and precipitation time series. The results showed that the observed changes in streamflow were consistent with the changes in temperature and precipitation. In the Sari-Djaz catchment, increasing temperatures and related increase of glacier melt were identified as the dominant driver, while in the Kakshaal catchment, both increasing temperatures and increasing precipitation played a major role. Comparing the two approaches, an advantage of the simulation-based approach is the fact that it is based on process-based relationships implemented in the hydrological model instead of statistical links in the regression model. However, data-based approaches are less affected by model parameter and structural uncertainties and typically fast to apply. A complementary application of both approaches is recommended.
A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This paper provides a critical review of existing causative classifications of instrumental and preinstrumental series of flood events, discusses their validity and applications, and identifies opportunities for moving toward more comprehensive approaches. So far no unified definition of causative mechanisms of flood events exists. Existing frameworks for classification of instrumental and preinstrumental series of flood events adopt different perspectives: hydroclimatic (large-scale circulation patterns and atmospheric state at the time of the event), hydrological (catchment scale precipitation patterns and antecedent catchment state), and hydrograph-based (indirectly considering generating mechanisms through their effects on hydrograph characteristics). All of these approaches intend to capture the flood generating mechanisms and are useful for characterizing the flood processes at various spatial and temporal scales. However, uncertainty analyses with respect to indicators, classification methods, and data to assess the robustness of the classification are rarely performed which limits the transferability across different geographic regions. It is argued that more rigorous testing is needed. There are opportunities for extending classification methods to include indicators of space-time dynamics of rainfall, antecedent wetness, and routing effects, which will make the classification schemes even more useful for understanding and estimating floods. This article is categorized under: Science of Water > Water Extremes Science of Water > Hydrological Processes Science of Water > Methods
Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior.
This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage.
Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented.
In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice.
Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system.
We then discuss to which extent the current knowledge supports or contradicts these hypotheses.
We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms.
We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.
Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact-based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe.
This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators' experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes.