土壤中铜和镍的植物毒性预测模型的种间外推验证

在基于物种敏感性分布法推导土壤金属生态阈值过程中,利用毒性预测模型对来源于不同土壤的毒理学数据进行归一化处理可消除土壤性质差异的影响,但目前建立的毒性预测模型仅限于少数物种。本研究通过比较土壤中小白菜、西红柿和大麦的铜和镍的毒性预测模型应用于其他高等植物的预测效果,以及归一化前后各物种毒性阈值的种内变异程度,考察了土壤中铜和镍的植物毒性预测模型种间外推的可行性和适用范围,解决了铜和镍土壤生态阈值导出过程中的方法学问题。土壤中镍对小白菜的毒性预测模型能较好地预测芥菜和青椒的镍毒性阈值,利用该模型对芥菜和青椒在不同土壤中的镍毒性阈值进行归一化后亦能显著降低其种内变异,其种内变异系数分别从1.18和1.25降至0.31和0.06;但将镍对小白菜、西红柿和大麦的毒性预测模型应用于莴笋和莴苣的毒性阈值预测时,在pH<6.0的酸性土壤中其预测值均小于实测值,其实测值与预测值的比值在3.2到6.8之间。对小麦、黄瓜和青椒的铜毒性阈值而言,小白菜模型预测效果优于西红柿和大麦模型。利用西红柿模型归一化黄瓜铜毒性阈值,其毒性阈值的种内变异系数从0.83降至0.14。大麦的铜毒性预测模型能较准确地预测水稻、洋葱、芥菜、包菜和萝卜的毒性阈值,且这5个物种的铜毒性阈值经大麦模型归一化后其种内变异均显著降低。本研究结果可为土壤中铜和镍的植物毒性预测模型的种间外推提供科学依据。     

Regression models for exceedance data via the full likelihood

Many situations in practice require appropriate specification of operating characteristics under extreme conditions. Typical examples include environmental sciences where studies include extreme temperature, rainfall and river flow to name a few. In these cases, the effect of geographic and climatological inputs are likely to play a relevant role. This paper is concerned with the study of extreme data in the presence of relevant auxiliary information. The underlying model involves a mixture distribution: a generalized Pareto distribution is assumed for the exceedances beyond a high threshold and a non-parametric approach is assumed for the data below the threshold. Thus, the full likelihood including data below and above the threshold is considered in the estimation. The main novelty is the introduction of a regression structure to explain the variation of the exceedances through all tail parameters. Estimation is performed under the Bayesian paradigm and includes model choice. This allows for determination of higher quantiles under each covariate configuration and upper bounds for the data, where appropriate. Simulation results show that the models are appropriate and identifiable. The models are applied to the study of two temperature datasets: maxima in the U.S.A. and minima in Brazil, and compared to other related models.     

Information processing in models for density-dependent emigration: A comparison

Density-dependent emigration has been recognized as a fitness enhancing strategy. Yet, especially in the modelling literature there is no consensus about how density-dependent emigration should quantitatively be incorporated into metapopulation models. In this paper we compare the performance of five different dispersal strategies (defined by the functional link between density and emigration probability). Four of these strategies are based on published functional relationships between local population density and emigration probability, one assumes density-independent dispersal. We use individual-based simulations of time-discrete metapopulation dynamics and conduct evolution experiments for a broad range of values for dispersal mortality and environmental stochasticity. For each set of these conditions we analyze the evolution of emigration rates in ‘monoculture experiments’ (with only one type of dispersal strategy used by all individuals in the metapopulation) as well as in selection experiments that allow a pair-wise comparison of the performance of each functional type. We find that a single-parameter ‘asymptotic threshold’ strategy - derived from the marginal value theorem - with a decelerating increase of emigration rate with increasing population density, out-competes any other strategy, i.e. density-independent emigration, a ‘linear threshold’ strategy and a flexible three-parameter strategy. Only when environmental conditions select for extremely high emigration probabilities (close to one), strategies may perform approximately equally. A simple threshold strategy derived for the case of continuous population growth performs even worse than the density-independent strategy. As the functional type of the dispersal function implemented in metapopulation models may severely affect predictions concerning the survival of populations, range expansion, or community changes we clearly recommend to carefully select adequate functions to model density-dependent dispersal.     

An energetic perspective on the relationship between disturbance and ecosystem productivity

Previous ecological models for disturbance from energetic perspectives have focused on destructive pulses by which storages in a system are quickly drained during disturbance events and recovered thereafter. However, considering the wide range of disturbance intensities, frequencies, and durations in nature, disturbance effects on ecosystem energetics would be better understood by diversifying the disturbance effects on specific system configurations or energy pathways. Based on two hypotheses, we built simulation models of the variable disturbance-productivity relationships observed in a freshwater aquatic microcosm study. First, we hypothesized that disturbances will differentially alter the intrinsic rates of energy pathways in a system. Second, we hypothesized that there is a disturbance threshold where response of the intrinsic rates changes abruptly. Simulation results showed variable patterns of gross primary productivity (GPP) during the disturbance and post-disturbance periods under the diverse scenarios of disturbance effects on the intrinsic rates. Simulation results confirmed that the second hypothesis (i.e., disturbance threshold) was essential to achieve a U-shaped or peaked disturbance-productivity relationship. We evaluated the models by comparing them with the results of the microcosm tests, and suggested possible mechanisms of the variable disturbance-productivity relationships by varying parameters related to the disturbance effects on the intrinsic rates and the disturbance thresholds.     

Choice of threshold alters projections of species range shifts under climate change

One of the least explored sources of algorithmic uncertainty in bioclimatic envelope models (BEM) is the selection of thresholds to transform modelled probabilities of occurrence (or indices of suitability) into binary predictions of species presence and absence. We investigate the impacts of such thresholds in the specific context of climate change. BEM for European tree species were fitted combining 9 climatic models and emissions scenarios, 7 modelling techniques, and 14 threshold-setting techniques. We quantified sources of uncertainty in projections of turnover, and found that the choice of the modelling technique explained most of the variability (39%), while threshold choice explained 25% of the variability in the results, and their interaction an additional 19%. Choice of future climates explained 9% of total variability among projections. Estimated species range shifts obtained by applying different thresholds and models were grouped by IUCN-based categories of threat. Thresholds had a large impact on the inferred risks of extinction, producing 1.7- to 9.9-fold differences in the proportions of species projected to become threatened by climate change. Results demonstrate that threshold selection has large - albeit often unappreciated - consequences for estimating species range shifts under climate change.     

Thresholds in Songbird Occurrence in Relation to Landscape Structure

Abstract:  Theory predicts the occurrence of threshold levels of habitat in landscapes, below which ecological processes change abruptly. Simulation models indicate that below critical thresholds, fragmentation of habitat influences patch occupancy by decreasing colonization rates and increasing rates of local extinction. Uncovering such putative relationships is important for understanding the demography of species and in developing sound conservation strategies. Using segmented logistic regression, we tested for thresholds in occurrence of 15 bird species as a function of the amount of suitable habitat at multiple scales (150–2000-m radii). Suitable habitat was defined quantitatively based on previously derived, spatially explicit distribution models for each species. The occurrence of 10 out of 15 species was influenced by the amount of habitat at a landscape scale (≥500-m radius). Of these species all but one were best predicted by threshold models. Six out of nine species exhibited asymptotic thresholds; the effects of habitat loss intensified at low amounts of habitat in a landscape. Landscape thresholds ranged from 8.6% habitat to 28.7% (     = 18.5 ± 2.6%[95% CI]). For two species landscape thresholds coincided with sensitivity to fragmentation; both species were more likely to occur in large patches, but only when the amount of habitat in a landscape was low. This supports the fragmentation threshold hypothesis. Nevertheless, the occurrence of most species appeared to be unaffected by fragmentation, regardless of the amount of habitat present at landscape extents. The thresholds we identified may be useful to managers in establishing conservation targets. Our results indicate that findings of landscape-scale studies conducted in regions with relatively high proportions of habitat and low fragmentation may not be applicable in regions with low habitat proportions and high fragmentation.     

Modelling Ecological Presence–absence Data along an Environmental Gradient: Threshold Levels of the Environment

A methodology for estimating environmental thresholds of binary presence–absence data is presented where the level of the threshold is parameterised. Presence–absence data is fitted to three complementary different models: an independent null-model, a monotonically increasing or decreasing model, and an optimum model. The range of the three models is strictly between zero and one and the models are therefore well suited for modelling presence probabilities. The results of the three models may be combined by using Bayesian model selection methodologies. The proposed methodology is exemplified on observed binary presence–absence data of Bauera rubioides along an elevation gradient. Received: May 2005 / Revised: July 2005 An erratum to this article is available at.     

Experimental and environmental factors affect spurious detection of ecological thresholds

Threshold detection methods are increasingly popular for assessing nonlinear responses to environmental change, but their statistical performance remains poorly understood. We simulated linear change in stream benthic macroinvertebrate communities and evaluated the performance of commonly used threshold detection methods based on model fitting (piecewise quantile regression [PQR]), data partitioning (nonparametric change point analysis [NCPA]), and a hybrid approach (significant zero crossings [SiZer]). We demonstrated that false detection of ecological thresholds (type I errors) and inferences on threshold locations are influenced by sample size, rate of linear change, and frequency of observations across the environmental gradient (i.e., sample-environment distribution, SED). However, the relative importance of these factors varied among statistical methods and between inference types. False detection rates were influenced primarily by user-selected parameters for PQR (tau) and SiZer (bandwidth) and secondarily by sample size (for PQR) and SED (for SiZer). In contrast, the location of reported thresholds was influenced primarily by SED. Bootstrapped confidence intervals for NCPA threshold locations revealed strong correspondence to SED. We conclude that the choice of statistical methods for threshold detection should be matched to experimental and environmental constraints to minimize false detection rates and avoid spurious inferences regarding threshold location.     

Models for the physiological effects of short O3 exposures on plants

Some published effects of ozone on plant photosynthesis and evaporation are detailed, and attempts were made to develop explanatory models of increasing complexity. Stomatal regulation, which keeps the CO₂ concentration inside the lead constant, is assumed. The O₃ concentration inside the leaf is assumed to be neglible, so O₃ uptake, CO₂ uptake and stomatal conductance must be proportional. The suppression of photosynthesis is assumed to be proportional to the integrated effective O₃ uptake. For a first model, a differential equation is derived from these assumptions and a simple analytical solution is found. A second model includes a threshold O₃ flux. The repair process is discussed and three models are investigated with a constant repair rate, a repair rate dependent on the stage of injury, and with a repair rate dependent on the photosynthetic rate. A comparison of the analytical solutions of the appropriate differential equations with literature data shows that the model with repair dependent on photosytheesis is the most successful one, but a constant repair rate also gives a fair approximation. The model with repair dependent on photosynthesis implies the existence of a threshold level for the suppression of photosynthesis which separates reversible and irreversible O₃ effects. With the assumption of an inhomogeneous leaf a model to predict visible leaf injury is derived. The possible existence of a maximum leaf injury index for one exposure concentration is explained from the properties of the models. The restrictions and possible extensions of the models are discussed. The concept of a threshold O₃ flux and of a critical suppression of photosynthesis are shown to give possible explanations of antagonistic and synergistic effects of O₃, SO₂ and NO₂.     

Modelling the multiple nutrient limitation of algal growth

The way in which simultaneously limiting nutrients are supposed to act upon the algal growth rate is an important aspect of aquatic ecosystem modelling and research. Three different relations between the multiple nutrient limitation and two single nutrient limitations are developed from different biochemical models: a “multiplicative” relation, used in most dynamic ecosystem models, a new “sequential” relation and a “threshold” relation, sensu Liebig. The characteristics and practical consequences of these relations are investigated. By means of three experiments, derived from the literature, it is shown that the multiplicative relation yields the statistically significant worst growth rate predictions.     

Task-dependent influence of genetic architecture and mating frequency on division of labour in social insect societies

Division of labour is one of the most prominent features of social insects. The efficient allocation of individuals to different tasks requires dynamic adjustment in response to environmental perturbations. Theoretical models suggest that the colony-level flexibility in responding to external changes and internal perturbation may depend on the within-colony genetic diversity, which is affected by the number of breeding individuals. However, these models have not considered the genetic architecture underlying the propensity of workers to perform the various tasks. Here, we investigated how both within-colony genetic variability (stemming from variation in the number of matings by queens) and the number of genes influencing the stimulus (threshold) for a given task at which workers begin to perform that task jointly influence task allocation efficiency. We used a numerical agent-based model to investigate the situation where workers had to perform either a regulatory task or a foraging task. One hundred generations of artificial selection in populations consisting of 500 colonies revealed that an increased number of matings always improved colony performance, whatever the number of loci encoding the thresholds of the regulatory and foraging tasks. However, the beneficial effect of additional matings was particularly important when the genetic architecture of queens comprised one or a few genes for the foraging task’s threshold. By contrast, a higher number of genes encoding the foraging task reduced colony performance with the detrimental effect being stronger when queens had mated with several males. Finally, the number of genes encoding the threshold for the regulatory task only had a minor effect on colony performance. Overall, our numerical experiments support the importance of mating frequency on efficiency of division of labour and also reveal complex interactions between the number of matings and genetic architecture.     

厌氧条件下土壤中有机氯降解动力学模型及其参数优化——以五氯酚（PCP）为例

研究厌氧条件下土壤中有机氯降解动力学模型及其参数优化方法,对阐明有机氯降解的动力学反应机制具有十分重要的理论意义。文章以厌氧条件下土壤中五氯酚（PCP）降解为例,归纳介绍了两类用于描述土壤中PCP降解动力学过程的模型：一类模型是不考虑微生物生长的基质降解模式,以一级动力学模型最有代表性,但这类模型多数情况下没有或没有完全体现环境因素对PCP降解的抑制作用;另一类模型是考虑微生物生长的基质降解模式,以Monod动力学模型使用最普遍,但这类模型只在微生物生长的指数期适用,对延迟期、稳定期和衰亡期需经扩展才可应用。logistic动力学模型可广泛用于以上两类模型,是可以近似地描述微生物经适应过程和共代谢作用而致有机氯降解的简单模型。文章还总结了有机氯降解非线性模型参数的优化方法,并对其优缺点进行了分析和比较。针对目前土壤中有机氯降解动力学模型及其参数优化研究中存在的问题,对今后的研究方向进行了展望。     

种群水平生态风险评价方法概述及其在环境管理中的应用

生态风险评价的目的是保护生态系统功能的完整性、稳定性和持久性,为环境风险管理提供理论依据。然而,目前常见的用于保护生物的化学污染物浓度阈值大多是以个体水平的毒性试验结果为基础,忽略了物种在时间和空间相互作用等因素,不能够完全保护生态环境安全和生态系统功能的延续性。本文从生态风险评价的概念、目的和意义引出种群水平生态风险评价在环境管理应用的重要性,综述了种群水平生态风险评价的科学问题(如密度依赖、遗传变异和空间结构等),归纳了种群水平风险评价主要模型方法及其应用(如Euler-Lotka方程、预测矩阵、个体模型、空间模型和动态能量预算模型等),列举了各国现有法律法规中关于种群水平生态风险评价的规定,以期为种群水平生态风险评价方法研究及在环境管理中的应用提供有益借鉴。     

Parameter estimation for distributed delay based population models from laboratory data: egg hatching of Oulema duftschmidi Redthenbacher (Coleoptera,Chrysomelidae) as an example

The cohort development of poikilotherms under favorable temperature conditions may be described by the time-invariant distributed delay models that require three parameters, i.e. the thermal threshold T₀, the thermal constant W and the variability parameter H representing distributed maturation times, also known as time distributed or stochastic development. Here, a parsimonious method is developed that uses stage-frequency matrices obtained under controlled conditions. The analysis of these matrices permits the estimation of the three parameters, while the incorporation of both developmental threshold and thermal constant into the time-invariant distributed delay model permits the representation of stochastic cohort development under constant temperatures. The evaluated parameters can also be used in time-varying distributed delay models that are particularly useful for a wide range of fluctuating temperature conditions.We consider stage-frequency matrices obtained from cohorts of eggs and larvae of Oulema duftschmidi Redthenbacher at different constant temperatures. A visual inspection of the matrices clearly shows the temperature dependent as well as the time distributed passage from the egg to the larval stage. Under the current range of temperatures, a linear model for developmental rate satisfactorily describes egg development, and estimates the thermal threshold (T₀=11.2 °C), the thermal constant (W=81.3 day-degrees) and the delay order parameter (H=70). The resulting model can be used to represent the development of cohorts of O. duftschmidi eggs in a favorable temperature range.     

Spatially constrained clustering and upper level set scan hotspot detection in surveillance geoinformatics

We discuss upper level set (ULS) scan as a type of spatially constrained clustering in relation to two ways of imposing the spatial constraint, retrospectively versus progressively. We show that ULS scan produces the same results both ways; whereas two popular clustering techniques, single-linkage and K-means, can yield different results when spatial constraints are imposed retrospectively versus progressively. The ULS scan approach examines spatially connected components of a tessellation as a threshold is moved from the highest level (value) in the data to the lowest level. When the variable of interest on the tessellation is a rate of incidence, then a significance test is available based on binomial or Poisson null models and Monte Carlo techniques. This is a common context for detecting hotspots of diseases in epidemiological work. We also discuss an approach for extending the univariate methodology to accommodate multivariate contexts. Received: September 2005 / Revised: February 2006 This material is based upon work supported by (i) the National Science Foundation under Grant No. 0307010, (ii) the United States Environmental Protection Agency under Grant No. CR-83059301 and (iii) the Pennsylvania Department of Health using Tobacco Settlement Funds under Grant No. ME 01324. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the agencies.     

Age-size plasticity for reproduction in monocarpic plants

Empirical and theoretical investigations of monocarpy have usually addressed the question of minimum or threshold sizes for reproduction. However, the range of flowering sizes observed in many monocarpic species is extraordinarily large (well beyond what can be called a "threshold"), and the sizes of flowering and nonflowering plants may overlap greatly. We attempt to explain these reproductive patterns in terms of optimal reaction norms predicted by simple deterministic life history models. We assume that individuals differ in their growth trajectories due to the heterogeneous quality of microsites and ask how the optimal age and size at flowering varies with environmental variation in growth and for different assumptions about fecundity and mortality. Under two very different growth functions (one with no age- or size-related decline in growth rate and another with such a decline as size approaches an asymptote), the optimal reaction norms imply considerable plasticity for size at reproduction, particularly when poor growth is associated with higher mortality or lower asymptotic size. Deterministic models such as these may be more applicable to long-lived than to short-lived monocarps, because fitness potential should be less affected by stochastic variability in yearly growing condition in the former than in the latter. We consider the case of a tropical monocarpic and masting tree species, Cerberiopsis candelabra (Apocynaceae), and show that our model results can account for wide ranges of reproductive size and overlap in size of flowering and nonflowering plants, in accord with observation. We suggest that empirical attention to norms of reaction across growth environments will be a more profitable approach than investigation of size thresholds per se.     

On thresholds and environmental curve tensiometers

This paper considers distinctions between lognormal and mixture models. Emphasis is placed on two component mixtures where the lower valued subpopulation has a large mixing parameter. The density of this sort of mixture can be easily mistaken for a lognormal density. In order to compare such a mixture to a lognormal it is demonstrated that Galton's two parameter logmodel and Pearson's five parameternormal mixture are special, or limiting, cases of the same general mixture model. Consideration is given to the lognormal threshold parameter in order to devise a tool that can help distinguish mixtures from lognormals. Based on the threshold parameter, piloted procedures can help measure whether or not a curve is friable, in the sense that a brittle curve is better represented as a mixture than as a skewed lognormal. It is also shown that generalizations of Galton's product risk model can be represented interms of the threshold parameter Based on a tool called a curve tensiometer was designed to be applied as a graphical friability check in the ecological context of Fisher's classic Iris data and in the environmental context of a Santa Monica Bay fish consumption study.     

Age-dependent population dynamics with several interior variables and spatial spread

The problems of the asymptotic behavior of age-dependent population models with interior and spatial structures are considered. It is proved that the existence and uniqueness of the stable state and its exact form is founded for general linear models. Problems on the speed of convergence to stable state and transitional effects are investigated. Methods of solving two special classes of nonlinear models (separate models and models of the Gurtin-MacCami type) are suggested. A model of forest stand dynamics on the basis of conception of layer-mosaic characteristics of the spatial-temporal structure of stands is examined as an example of the application of given results.     

Emergence of increased division of labor as a function of group size

Empirical evidence suggests that division of labor in insect societies is positively related to group size both within and across taxa. Response threshold models (RTM) have been commonly used to analyze patterns of division of labor. However, these models have been explored empirically and theoretically for only a limited number of tasks, and few studies have examined predictions of the model as colony size and work availability change. We theoretically examine how group size influences division of labor using a fixed response-threshold model. We simultaneously explore how expected by-products of increased colony size, including demand (total work need relative to total work force available) and task number, affect this relationship. Our results indicate that both low demand and high task number positively influence division of labor. We suggest that these changes parallel what is observed within social groups as their size increases, and that, in part, the commonly observed increased division of labor with increasing group size is emergent.     

The Importance of Being Spatial (and Reserved): Assessing Northern Spotted Owl Habitat Relationships with Hierarchical Bayesian Models

Abstract:  Regional conservation planning increasingly draws on habitat suitability models to support decisions regarding land allocation and management. Nevertheless, statistical techniques commonly used for developing such models may give misleading results because they fail to account for 3 factors common in data sets of species distribution: spatial autocorrelation, the large number of sites where the species is absent (zero inflation), and uneven survey effort. We used spatial autoregressive models fit with Bayesian Markov Chain Monte Carlo techniques to assess the relationship between older coniferous forest and the abundance of Northern Spotted Owl nest and activity sites throughout the species' range. The spatial random-effect term incorporated in the autoregressive models successfully accounted for zero inflation and reduced the effect of survey bias on estimates of species–habitat associations. Our results support the hypothesis that the relationship between owl distribution and older forest varies with latitude. A quadratic relationship between owl abundance and older forest was evident in the southern portion of the range, and a pseudothreshold relationship was evident in the northern portion of the range. Our results suggest that proposed changes to the network of owl habitat reserves would reduce the proportion of the population protected by up to one-third, and that proposed guidelines for forest management within reserves underestimate the proportion of older forest associated with maximum owl abundance and inappropriately generalize threshold relationships among subregions. Bayesian spatial models can greatly enhance the utility of habitat analysis for conservation planning because they add the statistical flexibility necessary for analyzing regional survey data while retaining the interpretability of simpler models.