Linking chronic wasting disease to mule deer movement scales: a hierarchical Bayesian approach.

Observed spatial patterns in natural systems may result from processes acting across multiple spatial and temporal scales. Although spatially explicit data on processes that generate ecological patterns, such as the distribution of disease over a landscape, are frequently unavailable, information about the scales over which processes operate can be used to understand the link between pattern and process. Our goal was to identify scales of mule deer (Odocoileus hemionus) movement and mixing that exerted the greatest influence on the spatial pattern of chronic wasting disease (CWD) in northcentral Colorado, USA. We hypothesized that three scales of mixing (individual, winter subpopulation, or summer subpopulation) might control spatial variation in disease prevalence. We developed a fully Bayesian hierarchical model to compare the strength of evidence for each mixing scale. We found strong evidence that the finest mixing scale corresponded best to the spatial distribution of CWD infection. There was also evidence that land ownership and habitat use play a role in exacerbating the disease, along with the known effects of sex and age. Our analysis demonstrates how information on the scales of spatial processes that generate observed patterns can be used to gain insight when process data are sparse or unavailable.     

Dynamics of prion disease transmission in mule deer.

Chronic wasting disease (CWD), a contagious prion disease of the deer family, has the potential to severely harm deer populations and disrupt ecosystems where deer occur in abundance. Consequently, understanding the dynamics of this emerging infectious disease, and particularly the dynamics of its transmission, has emerged as an important challenge for contemporary ecologists and wildlife managers. Although CWD is contagious among deer, the relative importance of pathways for its transmission remains unclear. We developed seven competing models, and then used data from two CWD outbreaks in captive mule deer and model selection to compare them. We found that models portraying indirect transmission through the environment had 3.8 times more support in the data than models representing transmission by direct contact between infected and susceptible deer. Model-averaged estimates of the basic reproductive number (R0) were 1.3 or greater, indicating likely local persistence of CWD in natural populations under conditions resembling those we studied. Our findings demonstrate the apparent importance of indirect, environmental transmission in CWD and the challenges this presents for controlling the disease.     

Modelling landscape effects on density-contact rate relationships of deer in eastern Alberta: Implications for chronic wasting disease

Managing wildlife diseases requires an understanding of disease transmission, which may be strongly affected by host population density and landscape features. Transmission models are typically fit from time-series disease prevalence data and modelled based on how the contact rate among hosts is affected by density, which is often assumed to be a linear (density-dependent transmission) or constant (frequency-dependent transmission) relationship. However, long-term time-series data is unavailable for emerging diseases, and this approach cannot account for independent effects of landscape. We developed a mechanistic model based on ecological data to empirically derive the contact rate-density relationship in white-tailed and mule deer in an enzootic region of chronic wasting disease (CWD) in Alberta, Canada and to determine whether it was affected by landscape. Using data collected from aerial surveys and GPS-telemetry, we developed empirical relationships predicting deer group size, home range size, and habitat selection to iteratively simulate deer distributions across a range of densities and landscapes. We calculated a relative measure of total per-capita contact rate, which is proportional to the number of other deer contacted per individual per unit time, for each distribution as the sum of pairwise contact rates between a target deer and all other individuals. Each pairwise contact rate was estimated from an empirical relationship developed from GPS-telemetry data predicting pairwise contact rates as a function of home range overlap and landscape structure. Total per-capita contact rates increased as a saturating function of density, supporting a transmission model intermediate between density- and frequency-dependent transmission. This pattern resulted from group sizes that reached an asymptote with increasing deer density, although this relationship was mediated by tree and shrub coverage in the landscape, such that in heavily wooded areas, the contact rate saturated at much lower densities. These results suggest that CWD management based on herd reductions, which require a density-dependent contact rate to be effective, may have variable effects on disease across a single management region. The novel mechanistic approach we employed for estimating effects of density and landscape on transmission is a powerful complement to typical data-fitting approaches for modelling disease transmission.     

A dynamical approach to evaluate risk in resource management.

With the depletion of many natural resources, we are growing aware of the need to understand the risks that stem from different management decisions. Here, we outline an approach to test the ability of different dynamical signatures to characterize time-series data: how likely is it that a natural population is declining, sustainable, or increasing, and at what rates are these temporal changes likely occurring? These dynamical signatures can serve as a robust foundation on which to formulate alternative scenarios in a decision analysis. They take account of much of the uncertainty in model parameters and have precise mathematical underpinnings with associated risks. We present methods to evaluate the likelihood of these scenarios, and ways that the analysis can be graphically represented. We discuss different ecological factors such as climate variability, life history, ecosystem interactions, and a changing population age structure, all of which impact the dynamics of natural populations. Considering the types of dynamical signatures that emerge from these factors can change our understanding of risk and the decisions that we make.     

Uncertainty in age-specific harvest estimates and consequences for white-tailed deer management

Age structure proportions (proportion of harvested individuals within each age class) are commonly used as support for regulatory restrictions and input for deer population models. Such use requires critical evaluation when harvest regulations force hunters to selectively harvest specific age classes, due to impact on the underlying population age structure. We used a stochastic population simulation model to evaluate the impact of using harvest proportions to evaluate changes in population age structure under a selective harvest management program at two scales. Using harvest proportions to parameterize the age-specific harvest segment of the model for the local scale showed that predictions of post-harvest age structure did not vary dependent upon whether selective harvest criteria were in use or not. At the county scale, yearling frequency in the post-harvest population increased, but model predictions indicated that post-harvest population size of 2.5 years old males would decline below levels found before implementation of the antler restriction, reducing the number of individuals recruited into older age classes. Across the range of age-specific harvest rates modeled, our simulation predicted that underestimation of age-specific harvest rates has considerable influence on predictions of post-harvest population age structure. We found that the consequence of uncertainty in harvest rates corresponds to uncertainty in predictions of residual population structure, and this correspondence is proportional to scale. Our simulations also indicate that regardless of use of harvest proportions or harvest rates, at either the local or county scale the modeled SHC had a high probability (>0.60 and >0.75, respectively) of eliminating recruitment into >2.5 years old age classes. Although frequently used to increase population age structure, our modeling indicated that selective harvest criteria can decrease or eliminate the number of white-tailed deer recruited into older age classes. Thus, we suggest that using harvest proportions for management planning and evaluation should be viewed with caution. In addition, we recommend that managers focus more attention on estimation of age-specific harvest rates, and modeling approaches which combine harvest rates with information from harvested individuals to further increase their ability to effectively manage deer populations under selective harvest programs.     

A holistic approach for evaluating ecological water allocation in the Yellow River basin of China

The characteristics and sustainable management of water resources on a basin scale require that they should be managed using a holistic approach. In this study, a holistic methodology called the holistic approach in a basin scale (HABS) is proposed to determine the ecological water requirements of a whole basin. There are three principles in HABS. First, ecological water requirements in a basin scale indicate not only the coupling of hydrological and ecological systems, but also the exchange of matter and energy between each ecological type through all kinds of physical geography processes. Second, ecological water requirements can be divided into different types according to their functions, and water requirements of different types are compatible. Third, ecological water requirements are related to a multiple system including water quality, water quantity, and time and space, which interact with each other. The holistic approach in a basin scale was then used in the Yellow River Basin and it suggested that 265.0 × 10⁸ m³ of water, 45% of the total surface water resources, should be allocated to ecological systems, such as rivers, lakes, wetlands and cities, to sustain its function and health. The ecological water requirements of inside river systems and outside river systems were respectively 261.0 × 10⁸ and 3.65 × 10⁸ m³.     

A system dynamics model for evaluating collaborative forest management: a case study in Indonesia

This article presents a system dynamics (SD) method to examine the problem of forest degradation. The model developed takes a system-oriented view of forest management, embracing both social and biophysical factors affecting deforestation. Social factors examined are socio-economic variables or elements that influence behaviour and decision-making choices at the household level. Biophysical factors are four sub-components that are considered major land uses namely, the paddy field component, rattan plantations, coffee plantations and forest stands. The model was applied in a case study located in Pasir District of East Kalimantan, Indonesia. The site covers an area that includes a protected forest and a privately allocated timber license concession. Three village communities are examined in the case study. The SD model developed was applied to the case study focusing on three management policies or scenarios, which are based on access rights to the forest resources within the study area. Specifically, the property arrangements examined in each scenario are: Policy 1 – status quo (i.e. continue present property rights arrangements); Policy 2 – local communities manage the forest exclusively; and Policy 3 – collaborative management involving both local communities and a private company. Results from the model show that the third policy is the most viable option, and also lead to a win–win solution.     

The effect of deer management on the abundance of Ixodes ricinus in Scotland

The management of wildlife hosts for controlling parasites and disease has a history of mixed success. Deer can be important hosts for ticks, such as Ixodes ricinus, which is the primary vector of disease-causing zoonotic pathogens in Europe. Deer are generally managed by culling and fencing for forestry protection, habitat conservation, and commercial hunting, and in this study we test whether these deer management methods can be useful for controlling ticks, with implications for tick-borne pathogens. At different spatial scales and habitats we tested the hypotheses that tick abundance is reduced by (1) culling deer and (2) deer exclusion using fencing. We compared abundance indices of hosts and questing I. ricinus nymphs using a combination of small-scale fencing experiments on moorland, a large-scale natural experiment of fenced and unfenced pairs of forests, and cross-sectional surveys of forest and moorland areas with varying deer densities. As predicted, areas with fewer deer had fewer ticks, and fenced exclosures had dramatically fewer ticks in both large-scale forest and small-scale moorland plots. Fencing and reducing deer density were also associated with higher ground vegetation. The implications of these results on other hosts, pathogen prevalence, and disease risk are discussed. This study provides evidence of how traditional management methods of a keystone species can reduce a generalist parasite, with implications for disease risk mitigation.     

A combined ecosystem and value chain modeling approach for evaluating societal cost and benefit of fishing

We describe a combined ecological and economic approach aimed at giving more equal emphasis to both disciplines, while being integrated so that design, analysis, data entry and storage, and result capabilities are developed with emphasis on deriving a user-friendly, easily accessible tool. We have thus developed the approach as an integrated module of the freely available Ecopath with Ecosim scientific software; the world's most widely applied ecological modeling tool. We link the trophic ecosystem model to a value-chain approach where we explicitly and in considerable detail keep track of the flow (amounts, revenue, and costs) of fish products from sea through to the end consumer. We also describe the social aspects of the fish production and trade, by evaluating employment and income diagnostics. This is done with emphasis on distribution income while accounting for social aspects of the fishing sector. From a management perspective, one of the interesting aspects of the approach we introduce here, is that it opens for direct evaluation of what impact management interventions, e.g., quota settings, effort regulation, or area closures, may have on the ecosystem, the economy and the social setting, as well as on food availability for the consumer.     

A geostatistical approach for mapping thematic classification accuracy and evaluating the impact of inaccurate spatial data on ecological model predictions

Spatial information in the form of geographical information system coverages and remotely sensed imagery is increasingly used in ecological modeling. Examples include maps of land cover type from which ecologically relevant properties, such as biomass or leaf area index, are derived. Spatial information, however, is not error-free: acquisition and processing errors, as well as the complexity of the physical processes involved, make remotely sensed data imperfect measurements of ecological attributes. It is therefore important to first assess the accuracy of the spatial information being used and then evaluate the impact of such inaccurate information on ecological model predictions. In this paper, the role of geostatistics for mapping thematic classification accuracy through integration of abundant image-derived (soft) and sparse higher accuracy (hard) class labels is presented. Such assessment leads to local indices of map quality, which can be used for guiding additional ground surveys. Stochastic simulation is proposed for generating multiple alternative realizations (maps) of the spatial distribution of the higher accuracy class labels over the study area. All simulated realizations are consistent with the available pieces of information (hard and soft labels) up to their validated level of accuracy. The simulated alternative class label representations can be used for assessing joint spatial accuracy, i.e., classification accuracy regarding entire spatial features read from the thematic map. Such realizations can also serve as input parameters to spatially explicit ecological models; the resulting distribution of ecological responses provides a model of uncertainty regarding the ecological model prediction. A case study illustrates the generation of alternative land cover maps for a Landsat Thematic Mapper (TM) subscene, and the subsequent construction of local map quality indices. Simulated land cover maps are then input into a biogeochemical model for assessing uncertainty regarding net primary production (NPP).     

我国自然保护区有效管理评价指标研究

本文根据我国自然保护区建设速度较快但管理水平较低的现状，在多年调查研究的基础上，提出制定自然保护区有效管理评价标准的必要性，并详细阐述了在保护区管理条件、管理措施、科研基础和管理成效等四个方面的评价内容，提出１３项评价指标，进而作了详细的评分等级划分，提出一套评价全国自然保护区管理质量的指标体系，为全国自然保护区管理的监督检查提供了一套简便适用、易于操作的评判标准。     

A density projection approach for non-trivial information dynamics: Adaptive management of stochastic natural resources

We demonstrate a density projection approximation method for solving resource management problems with imperfect state information. The method expands the set of partially-observed Markov decision process (POMDP) problems that can be solved with standard dynamic programming tools by addressing dimensionality problems in the decision maker's belief state. Density projection is suitable for uncertainty over both physical states (e.g. resource stock) and process structure (e.g. biophysical parameters). We apply the method to an adaptive management problem under structural uncertainty in which a fishery manager's harvest policy affects both the stock of fish and the belief state about the process governing reproduction. We solve for the optimal endogenous learning policy—the active adaptive management approach—and compare it to passive learning and non-learning strategies. We demonstrate how learning improves efficiency but typically follows a period of costly short-run investment.     

A co-operative approach to risk management in an active lead/zinc smelter community

Trail, Canada has been the site of a large lead/zinc smelting facility since 1916. In mid 1990, the Trail Community Lead Task Force was established and given responsibility for developing a strategy to reduce children's blood lead levels. With funding from the provincial government, the smelting company and the municipal government, the Task Force has carried out blood lead screening, case management, community education, exposure pathways modelling and remediation trials. The decline in children's blood lead levels appeared to accelerate following the implementation of these programmes. The average blood lead in Trail children aged 6–72 months fell 14% from the autumn of 1991 to autumn of 1992, whereas for the previous 16 years, the average annual decline had been about 4%. In subsequent years, blood lead levels have appeared to plateau. Throughout the 5-year history of the Task Force, its members have demonstrated a strong sense of common purpose and have worked co-operatively to reach consensus on most issues.     

Non-thermal plasmas for disease control and abiotic stress management in plants

Environmental Chemistry Letters - Climate change is predicted to cause severe loss in agricultural production by increasing disease epidemics and intensifying abiotic stresses. Therefore,...     

A state-dependent model for the optimal management of an invasive metapopulation.

Management of invasive species involves choosing between different management strategy options, but often the best strategy for a particular scenario is not obvious. We illustrate the use of optimization methods to determine the most efficient management strategy using one of the most devastating invasive forest pests in North America, the gypsy moth (Lymantria dispar), as a case study. The optimization approach involves the application of stochastic dynamic programming (SDP) to a metapopulation framework with different infestation patch sizes, with the goal of minimizing infestation spread. We use a novel "moving window" approach as a way to address a spatially explicit problem without being explicitly spatial. We examine results for two cases in order to develop general rules of thumb for management. We explore a model with limited parameter information and then assess how strategies change with specific parameterization for the gypsy moth. The model results in a complex but stable, state-dependent management strategy for a multiyear management program that is robust even under situations of uncertainty. The general rule of thumb for the basic model consists of three strategies: eradicating medium-density infestations, reducing large-density infestations, and reducing the colonization rate from the main infestation, depending on the state of the system. With specific gypsy moth parameterization, reducing colonization decreases in importance relative to the other two strategies. The application of this model to gypsy moth management emphasizes the importance of managing based on the state of the system, and if applied to a specific geographic area, has the potential to substantially improve the efficiency and cost-effectiveness of current gypsy moth eradication programs, helping to slow the spread of this pest. Additionally, the approach used for this particular invasive species can be extended to the optimization of management programs for the spread of other invasive and problem species exhibiting metapopulation dynamics.     

A trait-based approach for downscaling complexity in plankton ecosystem models

Although predator–prey cycles can be easily predicted with mathematical models it is only since recently that oscillations observed in a chemostat predator–prey (rotifer–algal) experiment offer an interesting workbench for testing model soundness. These new observations have highlighted the limitations of the conventional modelling approach in correctly reproducing some unexpected characteristics of the cycles. Simulations are improved when changes in algal community structure, resulting from natural selection operating on an assemblage of algal clones differing in competitive ability and defence against rotifer predation, is considered in multi-prey models. This approach, however, leads to extra complexity in terms of state variables and parameters. We show here that multi-prey models with one predator can be effectively approximated with a simpler (only a few differential equations) model derived in the context of adaptive dynamics and obtained with a moment-based approximation. The moment-based approximation has been already discussed in the literature but mostly in a theoretical context, therefore we focus on the strength of this approach in downscaling model complexity by relating it to the chemostat predator–prey experiment. Being based on mechanistic concepts, our modelling framework can be applied to any community of competing species for which a trade-off between competitive ability and resistance to predators can be appropriately defined. We suggest that this approach can be of great benefit for reducing complexity in biogeochemical modelling studies at the basin or global ocean scale.     

A study of the Kazdagi (Mt. Ida) National Park: an ecological approach to the management of tourism

In the field of tourism, where environmental resources are the primary attraction, ecotourism is one of the sustainable approaches now considered as an alternative when considering today's increasing environmental problems. Indeed, according to the World Tourism Organisation, ecotourism is the fastest growing market within the tourist industry. The purpose of this study is to determine tourism activities sensitive to the environment, to help tourism in Turkey and neighbouring countries, and to help spread ecotourism by protecting biological species. The Kazdagi (Mt. Ida) area in Turkey is used as an example and case study.     

A fractal approach for detecting spatial hierarchy and structure on mussel beds

Within beds of blue mussel (Mytilus edulis L.), individuals are aggregated into small patches, which in turn are incorporated into bigger patches, revealing a complex hierarchy of spatial structure. The present study was done to find the different scales of variation in the distribution of mussel biomass, and to describe the spatial heterogeneity on these scales. The three approaches compared for this purpose were fractal analysis, spatial autocorrelation and hierarchical (or nested) analysis of variances (ANOVA). The complexity (i.e. patchiness) of mussel aggregations was described with fractal dimension, calculated with the semivariogram method. Three intertidal mussel beds were studied on the west coast of Sweden. The distribution of wet biomass was studied along transects up to 128 m. The average biomasses of blue mussels on the three mussel beds were 1825낚, 179ᆩ and 576ᇖ g per0.1 m², respectively, and the fractal dimensions of the mussel distribution were 1.726ǂ.010, 1.842ǂ.014 and 1.939ǂ.029 on transects 1-3, respectively. Distributions of mussels revealed multiscaling behaviour. The fractal dimension significantly changed twice on different scales on the first bed (thus showing three scaling regions), the second and third beds revealed two and three scaling regions, respectively. High fractal dimension was followed by significant spatial autocorrelation on smaller scales. The fractal analysis detects the multiple scaling regions of spatial variance even when the spatial structure may not be distinguished significantly by conventional statistical inference. The study shows that the fractal analysis, the spatial autocorrelation analysis and the hierarchical ANOVA give complementary information about the spatial variability in mussel populations.