A Technique for Evaluating Forecasting Models

The paper presents a new methodology for evaluating the performance of a forecasting model. The evaluation-criterion utilizes a “credibility interval” centered at the model prediction. Given predicted and observed values, the length of the “credibility interval” is increased (or decreased) according as an observed value of the dependent random variable falls out of (or into) the interval. Based on that, various ways of assessing the rating of the model are discussed and illustrative examples are given.     

西北地区苹果褐斑病数学预测模型建立与分析

依据2001～2010年我国西北苹果主产区的气象数据与苹果褐斑病(Marssonina coronaria)病害发生流行数据,构建了平均气温(T)、相对湿度(Hm)、风速(Ws)及地表温度(St)影响下苹果褐斑病的流行趋势预测模型,并利用多元回归分析方法建立了苹果褐斑病预测模型.结果表明环境因素严重影响苹果褐斑病的发生和流行,苹果褐斑病预测模型为:f(T,Hm,Ws,St)=1.317T+0.002Hm+0.047Ws+0.001St-11.885[f(T,Hm,Ws,St)为病情指数].苹果褐斑病发生的T为14℃～15℃,Hm为45%,Ws为13m/s,St为10℃.大发生条件为T为20℃～23℃,Hm在70%～90%之间,Ws为0m/s～2m/s及St为22°.     

The Embedding Problem for Markov Models of Nucleotide Substitution

Continuous-time Markov processes are often used to model the complex natural phenomenon of sequence evolution. To make the process of sequence evolution tractable, simplifying assumptions are often made about the sequence properties and the underlying process. The validity of one such assumption, time-homogeneity, has never been explored. Violations of this assumption can be found by identifying non-embeddability. A process is non-embeddable if it can not be embedded in a continuous time-homogeneous Markov process. In this study, non-embeddability was demonstrated to exist when modelling sequence evolution with Markov models. Evidence of non-embeddability was found primarily at the third codon position, possibly resulting from changes in mutation rate over time. Outgroup edges and those with a deeper time depth were found to have an increased probability of the underlying process being non-embeddable. Overall, low levels of non-embeddability were detected when examining individual edges of triads across a diverse set of alignments. Subsequent phylogenetic reconstruction analyses demonstrated that non-embeddability could impact on the correct prediction of phylogenies, but at extremely low levels. Despite the existence of non-embeddability, there is minimal evidence of violations of the local time homogeneity assumption and consequently the impact is likely to be minor.     

Spatial Uncertainty and Ecological Models

Applied ecological models that are used to understand and manage natural systems often rely on spatial data as input. Spatial uncertainty in these data can propagate into model predictions. Uncertainty analysis, sensitivity analysis, error analysis, error budget analysis, spatial decision analysis, and hypothesis testing using neutral models are all techniques designed to explore the relationship between variation in model inputs and variation in model predictions. Although similar methods can be used to answer them, these approaches address different questions. These approaches differ in (a) whether the focus is forward or backward (forward to evaluate the magnitude of variation in model predictions propagated or backward to rank input parameters by their influence); (b) whether the question involves model robustness to large variations in spatial pattern or to small deviations from a reference map; and (c) whether processes that generate input uncertainty (for example, cartographic error) are of interest. In this commentary, we propose a taxonomy of approaches, all of which clarify the relationship between spatial uncertainty and the predictions of ecological models. We describe existing techniques and indicate a few areas where research is needed.     

Spatial Adaptation of Populations in Ecological Models

Biophysics - A discrete dynamic model of populations is described; in this model, spatial migration is specified by a finite-state Markov chain, while growth and nonlinear interactions are defined...     

Ecological and Genetic Models in Population Biophysics

Biophysics - Complex causal relationships occur between population dynamics and a change in a population genetic structure. In our study, a simple model was used to show that the evolutionary...     

生态学数学模型的研究进展

当前许多生态学的研究工作使用了数学的方法和手段。因为它可以对生态现象进行量化的研究,而且理论上的分析往往还能使研究结果得以深化。数学模型是数学的思想和方法应用于生态学研究的桥梁。自从60年代数学模型的研究在生态学上再次被人们重视以来,其发     

Using Non-Reversible Context-Dependent Evolutionary Models to Study Substitution Patterns in Primate Non-Coding Sequences

We discuss the importance of non-reversible evolutionary models when analyzing context-dependence. Given the inherent non-reversible nature of the well-known CpG-methylation-deamination process in mammalian evolution, non-reversible context-dependent evolutionary models may be well able to accurately model such a process. In particular, the lack of constraints on non-reversible substitution models might allow for more accurate estimation of context-dependent substitution parameters. To demonstrate this, we have developed different time-homogeneous context-dependent evolutionary models to analyze a large genomic dataset of primate ancestral repeats based on existing independent evolutionary models. We have calculated the difference in model fit for each of these models using Bayes Factors obtained via thermodynamic integration. We find that non-reversible context-dependent models can drastically increase model fit when compared to independent models and this on two primate non-coding datasets. Further, we show that further improvements are possible by clustering similar parameters across contexts.     

Use of Growth Indices in Markov Chain Models for Crop Yield Forecasting

An improved Markov chain model has been developed for forecasting of sugarcane yields in which growth indices of biometrical characters based on data from two stages simultaneously have been utilised. Comparisons were also made with the models in use viz. the regression model and the first order Markov chain model.     

Forecasting Ecological Genomics: High-Tech Animal Instrumentation Meets High-Throughput Sequencing

Recent advancements in animal tracking technology and high-throughput sequencing are rapidly changing the questions and scope of research in the biological sciences. The integration of genomic data with high-tech animal instrumentation comes as a natural progression of traditional work in ecological genetics, and we provide a framework for linking the separate data streams from these technologies. Such a merger will elucidate the genetic basis of adaptive behaviors like migration and hibernation and advance our understanding of fundamental ecological and evolutionary processes such as pathogen transmission, population responses to environmental change, and communication in natural populations.     

Population Floors and the Persistence of Chaos in Ecological Models

Chaotic dynamics have been observed in a wide range of population models. Here we describe the effects of perturbing several of these models so as to introduce a non-zero minimum population size. This perturbation generally reduces the likelihood of observing chaos, in both discrete and continuous time models. The extent of this effect depends on whether chaos is generated through period-doubling, quasiperiodicity, or intermittence. Chaos reached via the quasiperiodic route is more robust against the perturbation than period-doubling chaos, whilst the inclusion of a population floor in a model exhibiting intermittent chaos may increase the frequency of population bursts although these become non-chaotic.     

Developing Conceptual Models for Complex Ecological Risk Assessments

Conceptual models are representations of the assumed relationship between sources and effects. They serve three important purposes. (1) Their creation compels assessors to think through and clarify their assumptions concerning the activities being assessed. (2) They serve as a communication tool for conveying those assumptions to risk managers and stakeholders. (3) They provide a basis for organizing and conducting the risk assessment. Conceptual models for risk assessments of chemical contaminants have not been problematical because they simply portray the flow of the contaminant from a source to a receptor that experiences toxic effects. However, ecological risk assessments must increasingly deal with direct and indirect effects on multiple endpoint receptors and with multiple complex activities including both physical effects and toxic effects. This complexity may result in conceptual models that are incomplete, ambiguous, or simply too complex to be understood. This paper presents a strategy for creating conceptual models for complex ecological risk assessments that are not only complete but also clear and comprehensible. The strategy also promotes efficiency by creating modular component models for activities, sites, and receptors that can be reused in different combinations in different assessments.     

Updating Known Distribution Models for Forecasting Climate Change Impact on Endangered Species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli''s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species'' distribution, instead of building new models that are based on climate change variables only.     

Products and Ecological Models: A Population Ecology Perspective

Industrial ecology has used the systems ecology model, with its emphasis on the flows of energy and nutrients, as a tool to find ways to minimize the adverse environmental effects of industrial activity. A second ecosystem model, the population ecology model, emphasizes intra-and inter-specific interactions of many types. When applied to industrial systems, it suggests an increased focus on products. It therefore can provide a useful complement to the systems ecology approach. If industrial processes that are less harmful to the environment are to be successfully implemented, they will have to produce products that can successfully penetrate the marketplace. A number of historical examples are used to illustrate the many product interactions discussed.     

Combat and communication in the Everglades pygmy sunfish

Changes in population density and resource patterning affect the aggressive behaviour of pygmy sunfish (Elassoma everglaidei) in many ways. Increases in density significantly reduced the proportion of fights directly over clumped prey, the likelihood of initiators winning contests or acquiring clumped prey, and the length of contests. Increases in prey dispersion also reduce the proportion of resource fights in low-and high-density populations, the greater tendency for subordinates to initiate fights directly over resources, the likelihood of initiators acquiring a contested prey item in lowdensity populations, and the length of contests. Such increases, however, increase the likelihood of initiators winning contests at moderate competitive levels, and increase the effectiveness of rapid sequential communication in populations that abandon territoriality. In addition, some of these findings, such as the inverse relationship between contest length and both prey dispersion and rank differential, are consistent with predictions of cost-benefit models of fighting behaviour, namely, that escalated contests become more likely as asymmetries in fighting ability decrease and asymmetries in resource valuation simultaneously increase.