28 research outputs found
Predation effects on mean time to extinction under demographic stochasticity
Methods for predicting the probability and timing of a species' extinction
are typically based on a combination of theoretical models and empirical data,
and focus on single species population dynamics. Of course, species also
interact with each other, forming more or less complex networks of
interactions. Models to assess extinction risk often lack explicit
incorporation of these interspecific interactions. We study a birth and death
process in which the death rate includes an effect from predation. This
predation rate is included via a general nonlinear expression for the
functional response of predation to prey density. We investigate the effects of
the foraging parameters (e.g. attack rate and handling time) on the mean time
to extinction. Mean time to extinction varies by orders of magnitude when we
alter the foraging parameters, even when we exclude the effects of these
parameters on the equilibrium population size. In particular we observe an
exponential dependence of the mean time to extinction on handling time. These
findings clearly show that accounting for the nature of interspecific
interactions is likely to be critically important when estimating extinction
risk.Comment: 11 pages, 4 figures; Typos removed. For further discussion about the
paper go to http://purl.org/net/extinctio
The intrinsic predictability of ecological time series and its potential to guide forecasting
Successfully predicting the future states of systems that are complex, stochastic, and potentially chaotic is a major challenge. Model forecasting error (FE) is the usual measure of success; however model predictions provide no insights into the potential for improvement. In short, the realized predictability of a specific model is uninformative about whether the system is inherently predictable or whether the chosen model is a poor match for the system and our observations thereof. Ideally, model proficiency would be judged with respect to the systems’ intrinsic predictability, the highest achievable predictability given the degree to which system dynamics are the result of deterministic vs. stochastic processes. Intrinsic predictability may be quantified with permutation entropy (PE), a model‐free, information‐theoretic measure of the complexity of a time series. By means of simulations, we show that a correlation exists between estimated PE and FE and show how stochasticity, process error, and chaotic dynamics affect the relationship. This relationship is verified for a data set of 461 empirical ecological time series. We show how deviations from the expected PE–FE relationship are related to covariates of data quality and the nonlinearity of ecological dynamics. These results demonstrate a theoretically grounded basis for a model‐free evaluation of a system's intrinsic predictability. Identifying the gap between the intrinsic and realized predictability of time series will enable researchers to understand whether forecasting proficiency is limited by the quality and quantity of their data or the ability of the chosen forecasting model to explain the data. Intrinsic predictability also provides a model‐free baseline of forecasting proficiency against which modeling efforts can be evaluated
The ecological forecast horizon, and examples of its uses and determinants
Forecasts of ecological dynamics in changing environments are increasingly important, and are available for a plethora of variables, such as species abundance and distribution, community structure and ecosystem processes. There is, however, a general absence of knowledge about how far into the future, or other dimensions (space, temperature, phylogenetic distance), useful ecological forecasts can be made, and about how features of ecological systems relate to these distances. The ecological forecast horizon is the dimensional distance for which useful forecasts can be made. Five case studies illustrate the influence of various sources of uncertainty (e.g. parameter uncertainty, environmental variation, demographic stochasticity and evolution), level of ecological organisation (e.g. population or community), and organismal properties (e.g. body size or number of trophic links) on temporal, spatial and phylogenetic forecast horizons. Insights from these case studies demonstrate that the ecological forecast horizon is a flexible and powerful tool for researching and communicating ecological predictability. It also has potential for motivating and guiding agenda setting for ecological forecasting research and development
Biodiversity increases and decreases ecosystem stability
International audienc
The Stochastic Nature of Functional Responses
27 páginas, 4 figuras.Functional responses are non-linear functions commonly used to describe the variation in
the rate of consumption of resources by a consumer. They have been widely used in both theoretical
and empirical studies, but a comprehensive understanding of their parameters at different levels
of description remains elusive. Here, by depicting consumers and resources as stochastic systems
of interacting particles, we present a minimal set of reactions for consumer resource dynamics. We
rigorously derived the corresponding system of ODEs, from which we obtained via asymptotic
expansions classical 2D consumer-resource dynamics, characterized by different functional responses.
We also derived functional responses by focusing on the subset of reactions describing only the
feeding process. This involves fixing the total number of consumers and resources, which we call
chemostatic conditions. By comparing these two ways of deriving functional responses, we showed
that classical functional response parameters in effective 2D consumer-resource dynamics differ from
the same parameters obtained by measuring (or deriving) functional responses for typical feeding
experiments under chemostatic conditions, which points to potential errors in interpreting empirical
data. We finally discuss possible generalizations of our models to systems with multiple consumers
and more complex population structures, including spatial dynamics. Our stochastic approach builds
on fundamental ecological processes and has natural connections to basic ecological theory.Peer reviewe
Prevention of recurrent respiratory infections : Inter-society Consensus
Recurrent respiratory infections (RRIs) are a common clinical condition in children, in fact about 25% of children under 1 year and 6% of children during the first 6 years of life have RRIs. In most cases, infections occur with mild clinical manifestations and the frequency of episodes tends to decrease over time with a complete resolution by 12 years of age. However, RRIs significantly reduce child and family quality of life and lead to significant medical and social costs. Despite the importance of this condition, there is currently no agreed definition of the term RRIs in the literature, especially concerning the frequency and type of infectious episodes to be considered. The aim of this consensus document is to propose an updated definition and provide recommendations with the intent of guiding the physician in the complex process of diagnosis, management and prevention of RRIs
Tracking the progressive spread of the SARS-CoV-2 Omicron variant in Italy, December 2021 to January 2022
The SARS-CoV-2 variant of concern Omicron was first detected in Italy in November 2021.AimTo comprehensively describe Omicron spread in Italy in the 2 subsequent months and its impact on the overall SARS-CoV-2 circulation at population level.MethodsWe analyse data from four genomic surveys conducted across the country between December 2021 and January 2022. Combining genomic sequencing results with epidemiological records collated by the National Integrated Surveillance System, the Omicron reproductive number and exponential growth rate are estimated, as well as SARS-CoV-2 transmissibility.ResultsOmicron became dominant in Italy less than 1 month after its first detection, representing on 3 January 76.9-80.2% of notified SARS-CoV-2 infections, with a doubling time of 2.7-3.3 days. As of 17 January 2022, Delta variant represented < 6% of cases. During the Omicron expansion in December 2021, the estimated mean net reproduction numbers respectively rose from 1.15 to a maximum of 1.83 for symptomatic cases and from 1.14 to 1.36 for hospitalised cases, while remaining relatively stable, between 0.93 and 1.21, for cases needing intensive care. Despite a reduction in relative proportion, Delta infections increased in absolute terms throughout December contributing to an increase in hospitalisations. A significant reproduction numbers' decline was found after mid-January, with average estimates dropping below 1 between 10 and 16 January 2022.ConclusionEstimates suggest a marked growth advantage of Omicron compared with Delta variant, but lower disease severity at population level possibly due to residual immunity against severe outcomes acquired from vaccination and prior infection
DUNE Offline Computing Conceptual Design Report
International audienceThis document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment