45 research outputs found
Modelling the introduction and spread of non-native species: international trade and climate change drive ragweed invasion
Biological invasions are a major driver of global change, for which models can attribute causes, assess impacts and guide management. However, invasion models typically focus on spread from known introduction points or non-native distributions and ignore the transport processes by which species arrive. Here, we developed a simulation model to understand and describe plant invasion at a continental scale, integrating repeated transport through trade pathways, unintentional release events and the population dynamics and local anthropogenic dispersal that drive subsequent spread. We used the model to simulate the invasion of Europe by common ragweed (Ambrosia artemisiifolia), a globally invasive plant that causes serious harm as an aeroallergen and crop weed. Simulations starting in 1950 accurately reproduced ragweed's current distribution, including the presence of records in climatically unsuitable areas as a result of repeated introduction. Furthermore, the model outputs were strongly correlated with spatial and temporal patterns of ragweed pollen concentrations, which are fully independent of the calibration data. The model suggests that recent trends for warmer summers and increased volumes of international trade have accelerated the ragweed invasion. For the latter, long distance dispersal because of trade within the invaded continent is highlighted as a key invasion process, in addition to import from the native range. Biosecurity simulations, whereby transport through trade pathways is halted, showed that effective control is only achieved by early action targeting all relevant pathways. We conclude that invasion models would benefit from integrating introduction processes (transport and release) with spread dynamics, to better represent propagule pressure from native sources as well as mechanisms for long-distance dispersal within invaded continents. Ultimately, such integration may facilitate better prediction of spatial and temporal variation in invasion risk and provide useful guidance for management strategies to reduce the impacts of invasion
Predicting daily ragweed pollen concentrations using Computational Intelligence techniques over two heavily polluted areas in Europe
Protocols for uncontrolled donation after circulatory death: a systematic review of international guidelines, practices and transplant outcomes
Effects of analogue insulin in multiple daily injection therapy of type 2 diabetes on postprandial glucose control and cardiac function compared to human insulin: a randomized controlled long-term study
Design principles of autocatalytic cycles constrain enzyme kinetics and force low substrate saturation at flux branch points
A set of chemical reactions that require a metabolite to synthesize more of that metabolite is an autocatalytic cycle. Here, we show that most of the reactions in the core of central carbon metabolism are part of compact autocatalytic cycles. Such metabolic designs must meet specific conditions to support stable fluxes, hence avoiding depletion of intermediate metabolites. As such, they are subjected to constraints that may seem counter-intuitive: the enzymes of branch reactions out of the cycle must be overexpressed and the affinity of these enzymes to their substrates must be relatively weak. We use recent quantitative proteomics and fluxomics measurements to show that the above conditions hold for functioning cycles in central carbon metabolism of E. coli. This work demonstrates that the topology of a metabolic network can shape kinetic parameters of enzymes and lead to seemingly wasteful enzyme usage.ISSN:2050-084