Publications by authors named "Florian Hartig"

Understanding the genetics of kidney function decline, or trait change in general, is hampered by scarce longitudinal data for GWAS (longGWAS) and uncertainty about how to analyze such data. We use longitudinal UK Biobank data for creatinine-based estimated glomerular filtration rate from 348,275 individuals to search for genetic variants associated with eGFR-decline. This search was performed both among 595 variants previously associated with eGFR in cross-sectional GWAS and genome-wide.

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Conspecific density dependence (CDD) in plant populations is widespread, most likely caused by local-scale biotic interactions, and has potentially important implications for biodiversity, community composition, and ecosystem processes. However, progress in this important area of ecology has been hindered by differing viewpoints on CDD across subfields in ecology, lack of synthesis across CDD-related frameworks, and misunderstandings about how empirical measurements of local CDD fit within the context of broader ecological theories on community assembly and diversity maintenance. Here, we propose a conceptual synthesis of local-scale CDD and its causes, including species-specific antagonistic and mutualistic interactions.

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Generating spatial predictions of species distribution is a central task for research and policy. Currently, correlative species distribution models (cSDMs) are among the most widely used tools for this purpose. However, a fundamental assumption of cSDMs, that species distributions are in equilibrium with their environment, is rarely fulfilled in real data and limits the applicability of cSDMs for dynamic projections.

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Numerous studies have shown reduced performance in plants that are surrounded by neighbours of the same species, a phenomenon known as conspecific negative density dependence (CNDD). A long-held ecological hypothesis posits that CNDD is more pronounced in tropical than in temperate forests, which increases community stabilization, species coexistence and the diversity of local tree species. Previous analyses supporting such a latitudinal gradient in CNDD have suffered from methodological limitations related to the use of static data.

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New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce 'novel community data' as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation.

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Rationale: Oxygen is essential for cellular energy metabolism. Neurons are particularly vulnerable to hypoxia. Increasing oxygen supply shortly after stroke onset could preserve the ischemic penumbra until revascularization occurs.

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Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure.

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A lot of what we know about past speciation and extinction dynamics is based on statistically fitting birth-death processes to phylogenies of extant species. Despite their wide use, the reliability of these tools is regularly questioned. It was recently demonstrated that vast 'congruent' sets of alternative diversification histories cannot be distinguished (i.

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Estimates of the percentage of species "committed to extinction" by climate change range from 15% to 37%. The question is whether factors other than climate need to be included in models predicting species' range change. We created demographic range models that include climate vs.

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Understanding the origins of biodiversity has been an aspiration since the days of early naturalists. The immense complexity of ecological, evolutionary, and spatial processes, however, has made this goal elusive to this day. Computer models serve progress in many scientific fields, but in the fields of macroecology and macroevolution, eco-evolutionary models are comparatively less developed.

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Siberia has undergone dramatic climatic changes due to global warming in recent decades. Yet, the ecological responses to these climatic changes are still poorly understood due to a lack of data. Here, we use a unique data set from the Russian 'Chronicles of Nature' network to analyse the long-term (1976-2018) phenological shifts in leaf out, flowering, fruiting and senescence of 67 common Siberian plant species.

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It has long been anticipated that relating functional traits to species demography would be a cornerstone for achieving large-scale predictability of ecological systems. If such a relationship existed, species demography could be modeled only by measuring functional traits, transforming our ability to predict states and dynamics of species-rich communities with process-based community models. Here, we introduce a new method that links empirical functional traits with the demographic parameters of a process-based model by calibrating a transfer function through inverse modeling.

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Background: Results of randomized controlled trials (RCT) do not provide definite guidance for secondary prevention after ischemic stroke (IS)/transient ischemic attack (TIA) attributed to patent foramen ovale (PFO). No recommendations can be made for patients > 60 years. We aimed to compare interventional and medical PFO-management in cryptogenic IS/TIA patients, including patients > 60 years.

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Ecologists increasingly rely on complex computer simulations to forecast ecological systems. To make such forecasts precise, uncertainties in model parameters and structure must be reduced and correctly propagated to model outputs. Naively using standard statistical techniques for this task, however, can lead to bias and underestimation of uncertainties in parameters and predictions.

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Background: Direct oral anticoagulants (DOAC) including edoxaban are increasingly used for stroke prevention in atrial fibrillation. Despite treatment, annual stroke rate in these patients remains 1-2%. Rapid assessment of coagulation would be useful to guide thrombolysis or reversal therapy in this growing population of DOAC/edoxaban-treated stroke patients.

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Article Synopsis
  • Janzen and Connell's hypothesis from 50 years ago suggests that diverse tree species in tropical forests are supported by specialized natural enemies, which can create negative density dependence among species.
  • Many studies have looked into conspecific negative density dependence (CNDD), but its significance in maintaining overall species diversity is still debated.
  • To better understand how CNDD influences biodiversity at both local and global levels, improved statistical methods and new research designs are necessary.
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Background And Purpose:  Accurate and rapid assessment of coagulation status is necessary to guide thrombolysis or reversal of anticoagulation in stroke patients, but commercially available point-of-care (POC) assays are not suited for coagulation testing in patients treated with direct oral anticoagulants (DOACs). We aimed to evaluate the direct thrombin monitoring (DTM) test card by Helena Laboratories (Texas, United States) for anti-IIa-specific POC coagulation testing, hypothesizing that its POC-ecarin clotting time (POC-ECT) accurately reflects dabigatran plasma concentrations.

Methods:  A prospective single-center diagnostic study (ClinicalTrials.

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Current regulatory guidelines for pesticide risk assessment recommend that nonsignificant results should be complemented by the minimum detectable difference (MDD), a statistical indicator that is used to decide whether the experiment could have detected biologically relevant effects. We review the statistical theory of the MDD and perform simulations to understand its properties and error rates. Most importantly, we compare the skill of the MDD in distinguishing between true and false negatives (i.

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Background: Temperate forest understorey vegetation poses an excellent study system to investigate whether increases in resource availability lead to an increase in plant species richness. Most sunlight is absorbed by the species-poor tree canopy, making the much more species-rich understorey species inhabit a severely resource-limited habitat. Additionally, the heterogeneity of light availability, resulting from management-moderated tree composition and age structure, may contribute to species coexistence.

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Edoxaban, alongside other direct oral anticoagulants (DOAC), is increasingly used for prevention of thromboembolism, including stroke. Despite DOAC therapy, however, annual stroke rate in patients with atrial fibrillation remains 1-2%. Rapid exclusion of relevant anticoagulation is necessary to guide thrombolysis or reversal therapy but, so far, no data exists on the effect of edoxaban on available point-of-care test systems (POCT).

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Article Synopsis
  • Dispersal is important for plants, but we still don’t fully understand how it affects their survival and spread.
  • It’s tough to predict how seeds move around because it depends on many different factors like the environment and time.
  • To really get better at studying seed dispersal, we need to consider all the different ways plants grow and change over time, and work together across different fields of science.
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Purpose: Time is the key criterion in the management of non-arteritic central retinal artery occlusion (NA-CRAO). However, the precise onset of vision loss is often difficult to determine. This study aimed to evaluate the temporal changes of retinal thickness in acute NA-CRAO and the potential of this parameter to be used as a surrogate marker to estimate the onset of retinal ischaemia.

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The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long-term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3-PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes.

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Plant trait variability, emerging from eco-evolutionary dynamics that range from alleles to macroecological scales, is one of the most elusive, but possibly most consequential, aspects of biodiversity. Plasticity, epigenetics, and genetic diversity are major determinants of how plants will respond to climate change, yet these processes are rarely represented in current vegetation models. Here, we provide an overview of the challenges associated with understanding the causes and consequences of plant trait variability, and review current developments to include plasticity and evolutionary mechanisms in vegetation models.

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