A Markov random field spatio-temporal analysis of ocean temperature

The National Oceanic Data Center (NODC) contains historical records from approximately 144,000 hydrographic stations in the North Atlantic. This data has been used by oceanographers to construct maps of point estimates of pressure, temperature, salinity and oxygen in the North Atlantic (Levitus (1994); Lozier et al. (1995)). Because data from any particular year are scarce, the previous maps have been for time-averaged values only. In addition, the maps have been reported without uncertainty estimates. This paper presents a Markov random field (MRF) analysis that can generate maps for specific time periods along with associated uncertainties. To estimate changes in oceanic properties over time previous oceanographic work has focused on differences between a few time periods each having many observations. Due to data scarcity this poses a severe restriction for both spatial and temporal coverage of climatic change. The MRF analysis provides a means for temporal modeling that does not require high data density at each time period. To demonstrate the usefulness of a MRF analysis of oceanic data we investigate the temporal variability along 24.5°N in the North Atlantic. Our results are compared to an earlier analysis (Parrilla et al. (1994)) where data from only three time periods was used. We obtain a more thorough understanding of the temperature change found by this previous study.     

空管威胁、差错与意外状态的贝叶斯模型分析研究

为准确理解民航空中交通管理中各类人为差错数据的可靠性和相关性,为安全决策提供量化依据,对空管威胁、差错和意外状态数据进行贝叶斯模型分析。该方法在先验概率基础上,通过研究空中意外状态发生条件下威胁与差错各自发生的后验概率,获得上述3类安全信息的相关性大小排序。针对收集到的625起数据样本进行了研究,结果表明:与空中意外状态的发生相关性最大的3类差错依次为:管制员对机组的通讯差错、信息差错以及管制员对管制员的通讯差错;与空中意外状态的发生相关性最大的3类威胁依次为:程序威胁、相邻单位威胁和空中交通威胁。空管运行单位的安全管控应重点关注管制员/机组间的通讯差错,并针对各种可能出现的威胁预先制定应对程序。     

Bayesian Decision‐Network Modeling of Multiple Stakeholders for Reef Ecosystem Restoration in the Coral Triangle

Proposals for marine conservation measures have proliferated in the last 2 decades due to increased reports of fishery declines and interest in conservation. Fishers and fisheries managers have often disagreed strongly when discussing controls on fisheries. In such situations, ecosystem‐based models and fisheries‐stock assessment models can help resolve disagreements by highlighting the trade‐offs that would be made under alternative management scenarios. We extended the analytical framework for modeling such trade‐offs by including additional stakeholders whose livelihoods and the value they place on conservation depend on the condition of the marine ecosystem. To do so, we used Bayesian decision‐network models (BDNs) in a case study of an Indonesian coral reef fishery. Our model included interests of the fishers and fishery managers; individuals in the tourism industry; conservation interests of the state, nongovernmental organizations, and the local public; and uncertainties in ecosystem status, projections of fisheries revenues, tourism growth, and levels of interest in conservation. We calculated the total utility (i.e., value) of a range of restoration scenarios. Restricting net fisheries and live‐fish fisheries appeared to be the best compromise solutions under several combinations of settings of modeled variables. Results of our case study highlight the implications of alternate formulations for coral reef stakeholder utility functions and discount rates for the calculation of the net benefits of alternative fisheries management options. This case study may also serve as a useful example for other decision analyses with multiple stakeholders. Modelo de Red de Decisión Bayesiana de Múltiples Actores Interesados en la Restauración de Ecosistemas de Arrecife en el Triángulo de Coral     

Accelerating Adaptation of Natural Resource Management to Address Climate Change

Natural resource managers are seeking tools to help them address current and future effects of climate change. We present a model for collaborative planning aimed at identifying ways to adapt management actions to address the effects of climate change in landscapes that cross public and private jurisdictional boundaries. The Southwest Climate Change Initiative (SWCCI) piloted the Adaptation for Conservation Targets (ACT) planning approach at workshops in 4 southwestern U.S. landscapes. This planning approach successfully increased participants’ self‐reported capacity to address climate change by providing them with a better understanding of potential effects and guiding the identification of solutions. The workshops fostered cross‐jurisdictional and multidisciplinary dialogue on climate change through active participation of scientists and managers in assessing climate change effects, discussing the implications of those effects for determining management goals and activities, and cultivating opportunities for regional coordination on adaptation of management plans. Facilitated application of the ACT framework advanced group discussions beyond assessing effects to devising options to mitigate the effects of climate change on specific species, ecological functions, and ecosystems. Participants addressed uncertainty about future conditions by considering more than one climate‐change scenario. They outlined opportunities and identified next steps for implementing several actions, and local partnerships have begun implementing actions and conducting additional planning. Continued investment in adaptation of management plans and actions to address the effects of climate change in the southwestern United States and extension of the approaches used in this project to additional landscapes are needed if biological diversity and ecosystem services are to be maintained in a rapidly changing world. Acelerando la Adaptación del Manejo de Recursos Naturales para Atender el Cambio Climático     

Bayesian sample size determination for inspection of general corrosion of process components

A Bayesian approach-based method is proposed for calculating the minimum size of a sample to assess, with a specified precision, the integrity of process components suffering from general corrosion. The proposed method ensures that the error in the posterior estimate of the mean does not exceed a pre-defined acceptable margin of error at a specified confidence level. An analytical formula to estimate the sample size is introduced. The sample size obtained using the proposed method is smaller than a sample size obtained using the classical method with same confidence level. This reduces sampling inspection cost without affecting the precision of the estimate.     

Effects of Multiple Levels of Social Organization on Survival and Abundance

Abstract: Identifying how social organization shapes individual behavior, survival, and fecundity of animals that live in groups can inform conservation efforts and improve forecasts of population abundance, even when the mechanism responsible for group‐level differences is unknown. We constructed a hierarchical Bayesian model to quantify the relative variability in survival rates among different levels of social organization (matrilines and pods) of an endangered population of killer whales (Orcinus orca). Individual killer whales often participate in group activities such as prey sharing and cooperative hunting. The estimated age‐specific survival probabilities and survivorship curves differed considerably among pods and to a lesser extent among matrilines (within pods). Across all pods, males had lower life expectancy than females. Differences in survival between pods may be caused by a combination of factors that vary across the population's range, including reduced prey availability, contaminants in prey, and human activity. Our modeling approach could be applied to demographic rates for other species and for parameters other than survival, including reproduction, prey selection, movement, and detection probabilities.     

On Valuing Information in Adaptive‐Management Models

Abstract: Active adaptive management looks at the benefit of using strategies that may be suboptimal in the near term but may provide additional information that will facilitate better management in the future. In many adaptive‐management problems that have been studied, the optimal active and passive policies (accounting for learning when designing policies and designing policy on the basis of current best information, respectively) are very similar. This seems paradoxical; when faced with uncertainty about the best course of action, managers should spend very little effort on actively designing programs to learn about the system they are managing. We considered two possible reasons why active and passive adaptive solutions are often similar. First, the benefits of learning are often confined to the particular case study in the modeled scenario, whereas in reality information gained from local studies is often applied more broadly. Second, management objectives that incorporate the variance of an estimate may place greater emphasis on learning than more commonly used objectives that aim to maximize an expected value. We explored these issues in a case study of Merri Creek, Melbourne, Australia, in which the aim was to choose between two options for revegetation. We explicitly incorporated monitoring costs in the model. The value of the terminal rewards and the choice of objective both influenced the difference between active and passive adaptive solutions. Explicitly considering the cost of monitoring provided a different perspective on how the terminal reward and management objective affected learning. The states for which it was optimal to monitor did not always coincide with the states in which active and passive adaptive management differed. Our results emphasize that spending resources on monitoring is only optimal when the expected benefits of the options being considered are similar and when the pay‐off for learning about their benefits is large.     

Effects of Land‐Use Change on Community Composition of Tropical Amphibians and Reptiles in Sulawesi,Indonesia

Abstract: Little is known about the effects of anthropogenic land‐use change on the amphibians and reptiles of the biodiverse tropical forests of Southeast Asia. We studied a land‐use modification gradient stretching from primary forest, secondary forest, natural‐shade cacao agroforest, planted‐shade cacao agroforest to open areas in central Sulawesi, Indonesia. We determined species richness, abundance, turnover, and community composition in all habitat types and related these to environmental correlates, such as canopy heterogeneity and thickness of leaf litter. Amphibian species richness decreased systematically along the land‐use modification gradient, but reptile richness and abundance peaked in natural‐shade cacao agroforests. Species richness and abundance patterns across the disturbance gradient were best explained by canopy cover and leaf‐litter thickness in amphibians and by canopy heterogeneity and cover in reptiles. Amphibians were more severely affected by forest disturbance in Sulawesi than reptiles. Heterogeneous canopy cover and thick leaf litter should be maintained in cacao plantations to facilitate the conservation value for both groups. For long‐term and sustainable use of plantations, pruned shade trees should be permanently kept to allow rejuvenation of cacao and, thus, to prevent repeated forest encroachment.     

直升机电力作业非线性动态安全评价模型

为有效提高直升机电力作业安全评价能力,落实通用航空作业标准化和规范化管理,本文以直升机电力作业中人员因素、直升机设备因素、电力作业设备因素、自然环境因素、机场环境因素、组织因素、规章管理因素7个模块为一级指标建立安全评价指标体系。结合多位专家给出的概率语义值,基于模糊集与改进的证据融合理论量化各指标风险程度,同时采用三角模糊数法确定中间节点条件概率,最后利用贝叶斯网络模型灵活推理能力,提出直升机电力作业非线性动态安全评价模型。通过对某通用航空公司直升机电力作业安全状况评价分析可知,企业组织因素、电力作业设备因素以及人员因素为主要薄弱环节,需加强管理,可通过提高从业人员的安全防范意识、提高设备可靠性以及加强人员培训等措施对风险进行预防。     

Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.