4 resultados para likelihood-based inference
em Publishing Network for Geoscientific
Resumo:
Introduction Many marine planktonic crustaceans such as copepods have been considered as widespread organisms. However, the growing evidence for cryptic and pseudo-cryptic speciation has emphasized the need of re-evaluating the status of copepod species complexes in molecular and morphological studies to get a clearer picture about pelagic marine species as evolutionary units and their distributions. This study analyses the molecular diversity of the ecologically important Paracalanus parvus species complex. Its seven currently recognized species are abundant and also often dominant in marine coastal regions worldwide from temperate to tropical oceans. Results COI and Cytochrome b sequences of 160 specimens of the Paracalanus parvus complex from all oceans were obtained. Furthermore, 42 COI sequences from GenBank were added for the genetic analyses. Thirteen distinct molecular operational taxonomic units (MOTU) and two single sequences were revealed with cladistic analyses (Maximum Likelihood, Bayesian Inference), of which seven were identical with results from species delimitation methods (barcode gaps, ABDG, GMYC, Rosenberg's P(AB)). In total, 10 to 12 putative species were detected and could be placed in three categories: (1) temperate geographically isolated, (2) warm-temperate to tropical wider spread and (3) circumglobal warm-water species. Conclusions The present study provides evidence of cryptic or pseudocryptic speciation in the Paracalanus parvus complex. One major insight is that the species Paracalanus parvus s.s. is not panmictic, but may be restricted in its distribution to the northeastern Atlantic.
Resumo:
Invasive alien species are among the primary causes of biodiversity change globally, with the risks thereof broadly understood for most regions of the world. They are similarly thought to be among the most significant conservation threats to Antarctica, especially as climate change proceeds in the region. However, no comprehensive, continent-wide evaluation of the risks to Antarctica posed by such species has been undertaken. Here we do so by sampling, identifying, and mapping the vascular plant propagules carried by all categories of visitors to Antarctica during the International Polar Year's first season (2007-2008) and assessing propagule establishment likelihood based on their identity and origins and on spatial variation in Antarctica's climate. For an evaluation of the situation in 2100, we use modeled climates based on the Intergovernmental Panel on Climate Change's Special Report on Emissions Scenarios Scenario A1B [Nakicenovic N, Swart R, eds (2000) Special Report on Emissions Scenarios: A Special Report of Working Group III of the Intergovernmental Panel on Climate Change (Cambridge University Press, Cambridge, UK)]. Visitors carrying seeds average 9.5 seeds per person, although as vectors, scientists carry greater propagule loads than tourists. Annual tourist numbers (~33,054) are higher than those of scientists (~7,085), thus tempering these differences in propagule load. Alien species establishment is currently most likely for the Western Antarctic Peninsula. Recent founder populations of several alien species in this area corroborate these findings. With climate change, risks will grow in the Antarctic Peninsula, Ross Sea, and East Antarctic coastal regions. Our evidence-based assessment demonstrates which parts of Antarctica are at growing risk from alien species that may become invasive and provides the means to mitigate this threat now and into the future as the continent's climate changes.
EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study
Resumo:
Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.
Resumo:
The increase in global mean temperatures resulting from climate change has wide reaching consequences for the earth's ecosystems and other natural systems. Many studies have been devoted to evaluating the distribution and effects of these changes. We go a step further and evaluate global changes to the heat index, a measure of temperature as perceived by humans. Heat index, which is computed from temperature and relative humidity, is more important than temperature for the health of humans and other animals. Even in cases where the heat index does not reach dangerous levels from a health perspective, it has been shown to be an important factor in worker productivity and thus in economic productivity. We compute heat index from dewpoint temperature and absolute temperature 2 m above ground from the ERA-Interim reanalysis dataset for the years 1979-2013. The data is provided aggregated to daily minima, means and maxima. Furthermore, the data is temporally aggregated to monthly and yearly values and spatially aggregated to the level of countries after being weighted by population density in order to demonstrate its usefulness for the analysis of its impact on human health and productivity. The resulting data deliver insights into the spatiotemporal development of near-ground heat index during the course of the past 3 decades. It is shown that the impact of changing heat index is unevenly distributed through space and time, affecting some areas differently than others. The likelihood of dangerous heat index events has increased globally. Also, heat index climate groups that would formerly be expected closer to the tropics have spread latitudinally to include areas closer to the poles. The data can serve in future studies as a basis for evaluating and understanding the evolution of heat index in the course of climate change, as well as its impact on human health and productivity.