A Bayesian Approach to Fitting Gibbs Processes with Temporal Random Effects

We consider spatial point pattern data that have been observed repeatedly over a period of time in an inhomogeneous environment. Each spatial point pattern can be regarded as a ??snapshot?? of the underlying point process at a series of times. Thus, the number of points and corresponding locations of points differ for each snapshot. Each snapshot can be analyzed independently, but in many cases there may be little information in the data relating to model parameters, particularly parameters relating to the interaction between points. Thus, we develop an integrated approach, simultaneously analyzing all snapshots within a single robust and consistent analysis. We assume that sufficient time has passed between observation dates so that the spatial point patterns can be regarded as independent replicates, given spatial covariates. We develop a joint mixed effects Gibbs point process model for the replicates of spatial point patterns by considering environmental covariates in the analysis as fixed effects, to model the heterogeneous environment, with a random effects (or hierarchical) component to account for the different observation days for the intensity function. We demonstrate how the model can be fitted within a Bayesian framework using an auxiliary variable approach to deal with the issue of the random effects component. We apply the methods to a data set of musk oxen herds and demonstrate the increased precision of the parameter estimates when considering all available data within a single integrated analysis.     

Deterioration of copper and bronze caused by acidifying air pollutants

The ‘ICP on effects on materials’ was launched in 1985, within the framework of the Convention on Long-range Transboundary Air Pollution with the aim to find an approach for clearing the main gaps in the knowledge about material degradation caused by environmental impacts. The project was organized as a staggered8 year's material exposure programme accompanied by an extensive measuring programme for environmental parameters. During the evaluation of the 4 years data set it took shape that the most efficient parameters for quantifying the material degradation are the mass loss and especially for copper the corrosion volumes. Bronze already reacts extremely sensitive on low SO₂ concentrations. The starting corrosion rate for copper is suprisingly high. A strong impact of chloride on the formation of pin holes for sheltered copper could be detected without showing high mass loss. At simultanous presence of ozone the corrosive action is catalysed by it's oxidation power and leads to severe mass loss. Based upon the 4 years data set for most of the materials preliminary dose-response-functions have been prepared. For the first time a synergetic effect of SO₂ and ozone has been demonstrated in a field exposure.     

Characteristics of an ozone deposition module II: Sensitivity analysis

An ozone deposition module is currently being developed which will allow the estimation of stomatal fluxes of ozone into a number of vegetation types. This model is designed to be linked into a regional chemical-transport model for use within the European Monitoring and Evaluation Programme (EMEP), to provide information on possible risks to vegetation across Europe. This paper investigates the sensitivity of this model to some of the important input parameters, for two land-cover classes (temperate coniferous forests, temperate cereals). Of the factors contributing to the stomatal conductance considered within this study, those controlling soil moisture seem to be the biggest source of uncertainty. As ozone damage is believed to be driven by flux into the leaf rather than by ambient concentrations, this study suggests that flux modelling may be a practical alternative to the use of the AOT40 concept which is currently used to guide assessments of vegetation risk.     

Passive Ozone Monitoring for Forest Health Assessment

Critical levels of tropospheric ozone, established for the protection of crops and other plants, are now reported as being exceeded over large forested areas, giving rise to the need for an extensive monitoring program to confirm ambient levels within the forest and to detect related forest health effects. The requirement for an inexpensive monitor that can be used in remote locations prompted the development of the Can Oxy Plate^TM passive ozone monitor and a monitoring protocol by the air pollution research group of the Canadian Forest Service, Forest Health Network. The monitors underwent initial trials in 1996 and operational trials during 1997 that involved two 2-3 week mid summer exposures in the canopy at selected forest health monitoring plots across Canada, and at adjacent forest openings. In both trials monitors were also co-located with the nearest instrumental ozone monitor. This allowed for the production of a field calibration for quality assurance assessment under field conditions. Results from 1996 indicate highly significant correlations with accumulated ambient ozone concentrations from the instrumental monitors at the co-located sites (r=0.88, p=0.0002). However, no such relationship was found between these sites and the forest plots which were up to 200 kilometres away. This may indicate spatial heterogeneity in ozone exposure between the continuous air quality monitoring sites and the forest plots. This information, together with our knowledge that strong gradients of ozone exposure are found within the canopy, underlines the importance of in situ monitoring of ozone exposure of forest health plots at risk to ozone effects.     

Development of vaccination strategies for the management of rabies in African wild dogs

The standard objective of a vaccination strategy is to reduce the reproductive ratio, R₀, defined as the number of secondary host infections arising directly from introduction of a single infected individual into an otherwise fully susceptible population, to below 1. This ensures that only very small outbreaks are likely to arise. However, this objective usually requires a high level of vaccination coverage that is often expensive and logistically difficult to achieve. For the purposes of conserving rare species that are threatened by outbreaks of infectious disease, population persistence may be assured by a vaccination strategy designed to suppress only the largest outbreaks of disease that reduce the population to below a minimum viable population size. Such strategies targeting only a viable minimal ‘core’ of the population are likely to be logistically less demanding. Here we explore how these core vaccination strategies might be designed for African wild dogs (Lycaon pictus), an endangered canid species whose remaining populations are threatened by rabies outbreaks. We develop and analyse a population viability model with an explicit epidemiological model embedded within it. The model predicts that core vaccination campaigns, using vaccines that provide two years of immunity, and targets 30-40% of individuals within a population every 1-2 years would be successful in ensuring persistence of small populations, and required coverage levels can be even lower in larger populations. This strategy appears robust to synchronized introduction of rabies into packs, possible Allee effects, and the use of vaccines providing only one year of immunity.     

Modelling populations of long-lived birds of prey for conservation: A study of imperial eagles (Aquila heliaca) in Kazakhstan

Eagle populations worldwide are in decline and their demography is generally poorly understood. We use novel sensitivity analysis of stochastic simulation models to analyse the demography of the worlds highest-density and longest-studied population of eastern imperial eagles (Aquila heliaca), at the Naurzum National Nature Reserve in Kazakhstan. Single variable perturbation (a simple elasticity-type analysis) showed that population growth was most sensitive to changes in adult survival but provided no information on how interactions between parameters may influence population growth. Multiple-variable perturbations (a more comprehensive elasticity-type analysis) suggested that population growth is relatively more sensitive to adult survival than is indicated by single-variable perturbation but also that when adult survival is within a biologically reasonable range, other parameters are still highly consequential to model outputs. For Naurzum’s imperial eagles, and for other structured populations of vertebrates, effective conservation and management likely requires an approach that addresses the importance of simultaneous variation in multiple vital rates including both survivorship and reproductive output.     

Yield Responses of Wheat to Ozone Exposure as Modified by Drought-Induced Differences in Ozone Uptake

Over a period of two years greenhouse experiments were carried out to quantify the interaction ozone exposure × water stress in winter wheat (Triticum aestivum L. cv. Perlo). Assessment of effects carried out on various yield parameters showed that abundant water supply made the plants most sensitive to ozone exposure. In well-watered plants (75%) of soil water capacity, s.w.c.), the AOT40 ozone exposure doses of 26.8 and 24.9 μmol mol^-1 hr^-1 (ppm.h) caused grain yield reductions by 35 and 39%. No reductions of yields were observed at severe water stress (35% of s.w.c.) condition. The decrease in ozone responsiveness under drought can be explained by a distinct reduction in ozone uptake (18 vs. 2 mmol m^-2 in well-watered vs. severely stressed plants at the same ozone exposure). The calculations of ozone uptake were based onrepeated measurements of leaf conductance. Generally curvi-linear regression functions explained the dependence of relative yield on ozone and on water stress better than multiple simple linear regression functions. The consideration of ozone uptake instead of ozone exposure improved the performances of the models further. For explaining grain yield, 96.8% of the variances could be explained by a model resulting from curvi-linear regression fitting. A suggestion for calculating correction factors to modify critical levels in the case of limited water supply is presented.     

Towards unravelling the complex interactions between microclimate,ozone dose,and ozone injury in clover

This paper describes the results of a series of experiments designed to identify the relative importance of various factors which modify the responses of a sensitive species to ozone. The experiments were conducted in a closed chamber exposure system, enabling clover plants (Trifolium subterraneum L. cv Geraldton) to be exposed to ozone doses ranging from 0 to 1800 ppb.h, accumulated over 40 ppb (AOT40), for 7 h d^?1, over 1 to 3 days. Microclimatic conditions during exposure ranged from 80 to 460 μmol m^?2 s^?1 photosynthetically active radiation (PAR), 26 to 61 percent relative humidity (%RJH) and 16 to 36 °C temperature. No clear dose response relationships were established for 1, 2 or 3 day exposures due to the influence of microclimatic and other factors during exposure. Artificial Neural Networks were used as a tool to identify patterns within the dose response data set and to clarify the effects of various microclimatic and dose topography responses, during multiple day exposures. Analysis of the trained neural network revealed that AOT40 on individual exposure days was the most important influences PAR on the first and third days of exposure, the mean relative humidity and the mean temperature for all days also had strong influences. Leaf age also had an influence but this was weaker. This paper describes these results in relation to the influences acting upon the plant and how these affect ozone uptake and resulting ozone injury.     

Full Open Population Capture–Recapture Models With Individual Covariates

Traditional analyses of capture–recapture data are based on likelihood functions that explicitly integrate out all missing data. We use a complete data likelihood (CDL) to show how a wide range of capture–recapture models can be easily fitted using readily available software JAGS/BUGS even when there are individual-specific time-varying covariates. The models we describe extend those that condition on first capture to include abundance parameters, or parameters related to abundance, such as population size, birth rates or lifetime. The use of a CDL means that any missing data, including uncertain individual covariates, can be included in models without the need for customized likelihood functions. This approach also facilitates modeling processes of demographic interest rather than the complexities caused by non-ignorable missing data. We illustrate using two examples, (i) open population modeling in the presence of a censored time-varying individual covariate in a full robust design, and (ii) full open population multi-state modeling in the presence of a partially observed categorical variable. Supplemental materials for this article are available online.     

Modelling and Mapping Ozone Deposition in Europe

A new dry deposition module has been developed for European-scale mapping and modelling of ozone deposition fluxes (Emberson et al., 2000a,b). The module is being implemented in the photochemical long-range transport model of EMEP that is currently used to estimate exceedance of the existing critical levels for ozone within the UN ECE LRTAP programme. The deposition model evaluates the atmospheric, boundary layer and surface resistances to ozone transfer with the calculation of the dry deposition velocity performed according to a standard resistance formulation. The approach differs from other existing methods through the use of a detailed stomatal uptake model that describes stomatal conductance as a function of plant species, phenology and four environmental variables (air temperature, solar radiation, water vapour pressure deficit and soil moisture deficit). Comparison of preliminary model outputs for selected land-cover types indicate that the model is capable of predicting the seasonal and diurnal range in deposition velocities that have been reported previously in the literature. The application of this deposition scheme enables calculations of ambient ozone concentrations to be made using a biologically based method that can distinguish stomatal and non-stomatal components of total ozone deposition. The ability to estimate stomatal ozone fluxes (according to vegetation type, phenology and spatial location) that are consistent with evaluations of atmospheric ozone concentrations will be helpful in future assessments of ozone impacts to vegetation.     

基于优先分配的玉米单个籽粒生长模拟

精确预测作物产量对于作物生产、栽培措施优化等具有重要意义。玉米单个籽粒的质量差异对玉米产量有显著影响,并且雌穗不同位置的籽粒获取同化物的能力不同。当前的玉米模型中由于缺乏基于单个籽粒生长机制的模拟过程,从而限制了其在更广泛环境下对产量的模拟精度和预测能力。为了量化雌穗不同位置籽粒对于同化物的竞争能力,基于源库理论建立了玉米单个籽粒灌浆过程的模型,并引入“优先权”方程量化雌穗一列籽粒中每个籽粒获取同化物的“优先”能力,整合进入潜在籽粒生长需求计算新的籽粒库强。通过多年多源库水平的玉米田间试验数据对模型的有效性进行系统评估。结果表明,引入“优先权”后明显提高不同位置籽粒的干质量的模拟精度。这为理解单个籽粒的生长发育过程、玉米产量形成过程提供基础依据。     

Assessing critical habitat: Evaluating the relative contribution of habitats to population persistence

A principal challenge of species conservation is to identify the specific habitats that are essential for long-term persistence or recovery of imperiled species. However, many commonly used approaches to identify important habitats do not provide direct insight into the contribution of those habitats to population persistence. To assess how habitats contribute to overall population viability and characterize their relative importance, a spatially-explicit population viability model was used to integrate a species occurrence model with habitat quality and demographic information to simulate the population dynamics of the Ord’s kangaroo rat (Dipodomys ordii) in Alberta, Canada. Long-term productivity (births-deaths) in each patch was simulated and iterative patch removal experiments were conducted to generate estimates of the relative contribution of habitat types to overall population viability. Our results indicated that natural dune habitats are crucial for population viability, while disturbed/human-created habitats make a minor contribution to population persistence. The results also suggest that the habitats currently available to Ord’s kangaroo rats in Alberta are unlikely to support long-term persistence. Our approach was useful for identifying habitats that did not contribute to population viability. A large proportion of habitat (39%) represented sinks and their removal increased estimated population viability. The integration of population dynamics with habitat quality and occurrence data can be invaluable when assessing critical habitat, particularly in regions with variable habitat quality. Approaches that do not incorporate population dynamics may undermine conservation efforts by under- or over-estimating the value of habitats, erroneously protecting sink habitats, or failing to prioritize key source habitats.     

Predicting Freshwater Critical Loads of Acidification at the Catchment Scale: An Empirical Model

Current applications of the critical loads concept are geared primarily toward targeting emission control strategies at a national and international level. Maps of critical loads for freshwaters have been produced in grid form based on water samples of representative sites within each grid square. However, the water chemistry data required to calculate freshwater critical loads are not always readily available at a national level and maps are therefore limited to catchments where such data exist. This paper describes the development of an approach that uses nationally available secondary data to predict freshwater critical loads for catchments lacking the appropriate water chemistry information. An empirical statistical model is calibrated using data from 78 catchments throughout Scotland. Water chemistry for each catchment has been determined. Each catchment is characterized according to a number of attributes. Redundancy analysis of these data shows clear relationships between catchment attributes and the critical load derived from the water chemistry. The key variables that explain most of the variation in critical load relate to soil, geology and land use within the catchment. Using these variables as predictors in a regression analysis, the critical load can be predicted across a broad gradient of sensitivity (R² _adj=0.81). The predictive power of the model was maintained when different combinations of explanatory variables were used. This accords the approach a degree of flexibility in that model parameterization can be geared toward availability of secondary data. There are limitations with the model as presently calibrated. However, the approach offers considerable scope for environmental managers to undertake national inventories of catchment sensitivity and specific assessments of individual catchments.     

Using integrated population modelling to quantify the implications of multiple threatening processes for a rapidly declining population

Many species of conservation concern are in decline due to threats from multiple sources. To quantify the conservation requirements of these species we need robust estimates of the impact of each threat on the rate of population decline. However, for the vast majority of species this information is lacking. Here we demonstrate the application of integrated population modelling as a means of deriving robust estimates of the impact of multiple threats for a rapidly declining koala (Phascolarctos cinereus) population in South-east Queensland, Australia. Integrated population modelling provides a basis for reducing uncertainty and bias by formally integrating information from multiple data sources into a single model. We quantify mortality rates due to threats from dog attacks, vehicle collisions and disease and the extent to which each of these mortality rates would need to be reduced, or how much habitat would need to be restored, to stop the population declining. We show that the integrated population modelling approach substantially reduces uncertainty. We also show that recovery actions that only address single threats would need to reduce those threats to implausibly low levels to recover the population. This indicates that strategies for simultaneously tackling multiple threats are necessary; a situation that is likely to be true for many of the world’s threatened species. This study provides an important framework for quantifying the conservation requirements of species undergoing declines due to multiple threats.     

European Population Exposure to Airborne Pollutants Based on a Multivariate Spatio-Temporal Model

In this paper, we estimate the distribution of population by exposure to multiple airborne pollutants, taking into account the spatio-temporal variability of daily air quality and the high-resolution spatial spread of human population around Europe. In particular, we consider monitoring network data for five pollutants, namely carbon monoxide, nitrogen dioxide, ozone, coarse and fine particulate matters. The spatial information contained in the large dataset of daily continental air quality is exploited using a multivariate spatio-temporal model capable to cover cross correlation among pollutants, covariates, and missing data as well as spatial and temporal variability and correlation. At the same time, the model is simple enough to be feasible for the large dataset of daily continental air quality over three years. Maximum likelihood estimation is performed using the EM algorithm, and kriging-like spatial estimates are used to compute high-resolution exposure distribution. Moreover, a novel semi-parametric bootstrap technique is used to assess the exposure distribution uncertainty. In this way, we compare the daily population exposure of 33 European countries and three important metropolitan areas in years 2009–2011 using a single flexible model. Extensive tabulations and graphs are reported in the supplementary material.     

A model ensemble approach to determine the humus building efficiency of organic amendments in incubation experiments

Organic amendments are important to sustain soil organic matter (SOM) and soil functions in agricultural soils. Information about the contribution of organic amendments to SOM can be derived from incubation experiments. In this study, data from 72 incubated organic amendments including plant residues, digestates and manure were analysed. The incubation data was compiled from three experimental setups with varying incubation times, soils and incubation temperatures, in which CO₂ release was measured continuously. The analysis of the incubation data was performed with an approach relying on conceptual parts of C-TOOL, CCB, Century, ICBM, RothC and Yasso which are all well-approved first-order carbon models that differ in structure and abstraction level. All models are an approximation of reality, whereby each model differs in understanding of the processes involved in soil carbon dynamics. To accumulate the advantages from each model a model ensemble was performed for each substrate. With the ability of each carbon model to compute the distribution of carbon into specific SOM pools a new approach for evaluating organic amendments in terms of humus building efficiency is presented that, depends on the weighted model fit of each ensemble member. Depending on the organic substrate added to the soil, the time course of CO₂ release in the incubation studies was predicted with different accuracy by the individual model concepts. Averaging the output of the individual models leads to more robust prediction of SOM dynamics. The E_HUM value is easy to interpret and the results are in accordance with the literature.     

Estimation of the uncertainty in crop loss predictions through statistical modelling of the AOT40 levels for ozone

Ozone critical levels in Europe are defined in terms of an accumulated exposure over a threshold of 40 ppb, AOT40. For agricultural crops, for example, the critical level is an AOT40 of 5300 ppb.h during daylight in May to July in the year with the highest cumulative exposure in the last five years. In a region of the size of the UK, however, the worst case year is not the same over the whole region and maps become difficult to interpret. Prediction of crop losses on the basis of a single year out of five also wastes potentially valuable information. An alternative approach estimates the distribution of aggregate exceedances over a threshold by means of a compound Poisson model for episodes of raised ozone concentration with linear modelling techniques used to allow direct incorporation of covariate information. The use of spatial and environmental covariates, along with temporal and spatially correlated random effects, is explored using data from the UK ozone monitoring network. The model produces results similar to those from other mapping methods. By combining this model with a crop loss relationship, crop losses of 5–15% for the UK are predicted but the errors range between 2% and 6% indicating that fine detail in crop loss mapping is unlikely to be very accurate.     

Modeling of Stomatal Conductance for Estimating Ozone Uptake of Fagus crenata Under Experimentally Enhanced Free-air Ozone Exposure

We examined a performance of the multiplicative stomatal conductance model to estimate the stomatal ozone uptake for Fagus crenata. Parameterization of the model was carried out by in-situ measurements in a free-air ozone exposure experiment. The model performed fairly well under ambient conditions, with low ozone concentration. However, the model overestimated stomatal conductance under enhanced ozone condition due to ozone-induced stomatal closure. A revised model that included a parameter representing ozone-induced stomatal closure showed better estimation of ozone uptake. Neglecting ozone-induced stomatal closure induced a 20?% overestimation of the stomatal uptake of ozone. The ozone-induced stomatal closure was closely related to stomatal ozone uptake rather than accumulated concentrations of ozone exceeding 40?nmol mol^?1. Our results suggest that ozone-induced stomatal closure should be implemented to stomatal conductance model for estimating ozone uptake for F. crenata. The implementation will contribute to adequate risk assessments of ozone impacts on F. crenata forests in Japan.     

Population genetic structure of Orchesella cincta (Collembola; Hexapoda) in NW Europe, as revealed by microsatellite markers

We studied genetic variation and population differentiation in the springtail Orchesella cincta L. An earlier approach, using allozymes, revealed extremely low variation among and within populations from NW Europe. Microsatellite marker analysis showed higher genetic variation than allozymes, and agreed with the previously reported low population differentiation in the species. Analysis of molecular variance showed that genetic variation within populations amounted to 96.5% of the total variation, whereas the remaining 3.5% is accounted for by population differentiation. Population differentiation, as described by microsatellite markers and with the exception of one population, can be explained by an isolation by distance. Although the microsatellites are short, viz. only up to 12 repeat units, they appear to be useful tools in revealing population genetic structures in O. cincta.     

Evidence of Elevated Ozone Concentrations on Forested Slopes of the Lower Fraser Valley, British Columbia, Canada

During the summers of 2001 and 2002, hourly average ozone concentrations were measured at three sites of differing elevation (188, 588, and 1221 m.a.s.l.) on the forested south-facing slopes of the Lower Fraser Valley (LFV), British Columbia. Sites experienced ozone concentrations ranging from 0 to 88 ppb in 2001, and 0 to 96 ppb in 2002. Daily patterns were in agreement with previous studies showing morning increases and late afternoon peaks. Reduced diurnal variation increased the exposure of higher-elevation forested sites. An upper-level ridge coinciding with a thermal coastal trough caused above-average ozone concentrations, and the ‘maximum acceptable’ 1-hour National Ambient Air Quality Objective (AQO) of 82 ppb to be exceeded. Maximum ozone concentrations and AQO exceedance frequency both increased with distance eastward in the valley. A preliminary survey of ozone-like injury symptoms on native shrubs suggested that the elevated ozone levels occurring in the LFV may cause injury to forest plants.