Multi-scale Modeling of Animal Movement and General Behavior Data Using Hidden Markov Models with Hierarchical Structures

Hidden Markov models (HMMs) are commonly used to model animal movement data and infer aspects of animal behavior. An HMM assumes that each data point from a time series of observations stems from one of N possible states. The states are loosely connected to behavioral modes that manifest themselves at the temporal resolution at which observations are made. Due to advances in tag technology and tracking with digital video recordings, data can be collected at increasingly fine temporal resolutions. Yet, inferences at time scales cruder than those at which data are collected and, which correspond to larger-scale behavioral processes, are not yet answered via HMMs. We include additional hierarchical structures to the basic HMM framework, incorporating multiple Markov chains at various time scales. The hierarchically structured HMMs allow for behavioral inferences at multiple time scales and can also serve as a means to avoid coarsening data. Our proposed framework is one of the first that models animal behavior simultaneously at multiple time scales, opening new possibilities in the area of animal movement and behavior modeling. We illustrate the application of hierarchically structured HMMs in two real-data examples: (i) vertical movements of harbor porpoises observed in the field, and (ii) garter snake movement data collected as part of an experimental design. Supplementary materials accompanying this paper appear online.     

A set of nonlinear regression models for animal movement in response to a single landscape feature

The study of individual animal movement in relation to objects in a landscape is important in many areas of ecology and conservation biology. Yet, many of the models used by ecologists do not account for landscape features and thus may not be conducive to analysis of animal movement data. This article develops a set of nonlinear regression models for both move angles and move distances in relation to a single object in the landscape. Our models incorporate the concept of perceptual range from theories of animal movement behavior. We describe numerical methods for obtaining the maximum likelihood estimates of the model parameters. For illustration, we show results from both computer simulated data and real movement data collected for a red diamond rattlesnake (Crotalus ruber) via radio telemetry field techniques.     

Imputation Approaches for Animal Movement Modeling

The analysis of telemetry data is common in animal ecological studies. While the collection of telemetry data for individual animals has improved dramatically, the methods to properly account for inherent uncertainties (e.g., measurement error, dependence, barriers to movement) have lagged behind. Still, many new statistical approaches have been developed to infer unknown quantities affecting animal movement or predict movement based on telemetry data. Hierarchical statistical models are useful to account for some of the aforementioned uncertainties, as well as provide population-level inference, but they often come with an increased computational burden. For certain types of statistical models, it is straightforward to provide inference if the latent true animal trajectory is known, but challenging otherwise. In these cases, approaches related to multiple imputation have been employed to account for the uncertainty associated with our knowledge of the latent trajectory. Despite the increasing use of imputation approaches for modeling animal movement, the general sensitivity and accuracy of these methods have not been explored in detail. We provide an introduction to animal movement modeling and describe how imputation approaches may be helpful for certain types of models. We also assess the performance of imputation approaches in two simulation studies. Our simulation studies suggests that inference for model parameters directly related to the location of an individual may be more accurate than inference for parameters associated with higher-order processes such as velocity or acceleration. Finally, we apply these methods to analyze a telemetry data set involving northern fur seals (Callorhinus ursinus) in the Bering Sea. Supplementary materials accompanying this paper appear online.     

Soil survey data needs when studying modern land use problems

Abstract. Modern land use problems in the Netherlands are now focused on striking a balance between agricultural production, environmental protection, and nature and landscape conservation by means of new laws on soil protection. Quantitative expressions for crucial land qualities for different land management scenarios are needed to obtain adequate input for the decision making process emphasizing not only actual, but particularly potential conditions. Computer simulation techniques are being applied in this context. Three case studies are reviewed, covering: (i) adsorption of excess phosphate from animal manure; (ii) effects of lowering of water deficits for crops, and (iii) effects of soil tillage and compaction on crucial land qualities for agricultural production. Lack of representative basic data for simulation models inhibits their widespread practical application. Derivation of such basic data from existing soil-survey databases is therefore being discussed in terms of using various types of transfer functions, which allow more effective use of available data. In addition, geographical information systems are needed to allow rapid output for areas of land as represented on soil maps.     

Reflected Stochastic Differential Equation Models for Constrained Animal Movement

Movement for many animal species is constrained in space by barriers such as rivers, shorelines, or impassable cliffs. We develop an approach for modeling animal movement constrained in space by considering a class of constrained stochastic processes, reflected stochastic differential equations. Our approach generalizes existing methods for modeling unconstrained animal movement. We present methods for simulation and inference based on augmenting the constrained movement path with a latent unconstrained path and illustrate this augmentation with a simulation example and an analysis of telemetry data from a Steller sea lion (Eumatopias jubatus) in southeast Alaska.     

Difference in spatiotemporal patterns of wildlife road-crossings and wildlife-vehicle collisions

Human–wildlife conflicts like wildlife–vehicle collisions pose major challenges for the management and conservation of mobile wildlife in human-dominated landscapes, particularly when large species are involved. Mitigation measures to reduce risk of collisions may be based on information given by wildlife movement and collision data. To test whether movement and collision data indicate different spatiotemporal risk zones, we predicted year-around probabilities of road-crossings of GPS-marked female moose (Alces alces) (n = 102), and compared them with spatiotemporal patterns of police recorded moose-vehicle collisions (n = 1158). Probability of moose road-crossings peaked in May, June, and between mid November and the beginning of January, i.e. during moose migration. Moose-vehicle collisions were more likely during autumn and winter. Comparing environmental attributes of crossing and collision sites showed significant differences. The likelihood of collisions increased with the abundance of human-modified areas and higher allowed speed, and was lower on forest roads. We found that animal movement data alone are insufficient to predict collision risk zones, while analyses of collision data alone overestimate the collision risk in certain habitats. Our findings suggest that higher collision risk is largely due to low light and poor road surface conditions rather than to more animal road-crossings. This suggests that efforts to reduce wildlife collisions should focus on driver attitudes and road conditions rather than animal movement, and any efforts to model the collision risk will require actual collision data, and not just movement data.     

畜禽养殖业产污系数和排污系数计算方法

畜禽养殖业产污系数与排污系数是畜牧环境研究和粪便处理工程设计的基础指标,但由于中国畜牧业环境工作起步晚,还没有根据中国畜牧业生产特性确定的产污系数和排污系数。该文根据中国畜禽养殖业的特点,提出了畜禽养殖业产污系数和排污系数的定义、计算方法,并结合典型猪场进行了案例分析。对于北京市某养猪场进行分析,结果表明：该猪场保育、育肥和妊娠母猪3个阶段的COD产污系数分别为每头252.8、479.6、493.4 g/d,全氮分别为每头20.4、33.2、43.7 g/d,全磷分别为每头3.48、6.06、9.93 g/d,在该猪场废弃物处理系统的运行情况下,计算得出了该场保育、育肥和妊娠母猪3个阶段的COD排污系数分别为每头44.9、64.1、22.5 g/d,全氮分别为每头14.1、20.9、36.3 g/d和全磷分别为每头1.0、1.8、0.4 g/d。研究结果为畜禽养殖业污染源普查、废弃物处理工程运行和畜禽养殖业环境影响评价提供了参考。     

Bayesian Inference for Animal Space Use and Other Movement Metrics

The analysis of animal movement and resource use has become a standard tool in the study of animal ecology. Telemetry devices have become quite sophisticated in terms of overall size and data collecting capacity. Statistical methods to analyze movement have responded, becoming ever more complex, often relying on state-space modeling. Estimation of movement metrics such as utilization distributions have not followed suit, relying primarily on kernel density estimation. Here we consider a method for making inference about space use that is free of all of the major problems associated with kernel density estimation of utilization distributions such as autocorrelation, irregular time gaps, and error in observed locations. Our proposed method is based on a data augmentation approach that defines use as a summary of the complete path of the animal which is only partially observed. We use a sample from the posterior distribution of the complete path to construct a posterior sample for the metric of interest. Three basic importance sampling based methods for sampling from the posterior distribution of the path are proposed and compared. We demonstrate the augmentation approach by estimating a spatial map of diving intensity for female northern fur seals in the Pribilof Islands, Alaska.     

以粪污水热资源化为核心的高效种养结合系统分析与展望

种养结合系统是实现养殖业和种植业可持续发展的重要途径。水热技术可以转化畜禽粪污生产生物原油、生物炭、水相产物和气体产物,分别具有燃料、土壤改良、农用杀菌剂和温室气体肥料应用潜力,以粪污水热资源化为核心构建的高效种养结合系统有助于提高土地对畜禽粪污的消纳能力、构建生态可持续的绿色循环农业,实现畜禽粪污资源化利用、种植业和养殖的协同高效发展。该研究基于国内外近十余年的研究,系统综述了粪污水热资源化产物在种养结合生态循环农业模式中的作用和应用潜力,论述了畜禽粪污水热转化生物原油在农业内燃机中作为燃料的研究现状,阐述了水相产物作为潜在的农用杀菌剂在作物病害防控中的作用,梳理了畜禽粪污来源水热炭在转化机理、理化特性和还田应用中的研究进展,分析了气相产物中的组分和用于温室种植的潜力。在此基础上总结了以粪污水热资源化为核心的高效种养结合系统面临的主要挑战,并对水热资源化产物农业循环应用的研究方向进行展望。研究为畜禽粪污水热资源化产物的高值利用和高效种养结合系统研究提供理论参考。     

Modeling Collective Animal Movement Through Interactions in Behavioral States

Animal movement often exhibits changing behavior because animals often alternate between exploring, resting, feeding, or other potential states. Changes in these behavioral states are often driven by environmental conditions or the behavior of nearby individuals. We propose a model for dependence among individuals’ behavioral states. We couple this state switching with complex discrete-time animal movement models to analyze a large variety of animal movement types. To demonstrate this method of capturing dependence, we study the movements of ants in a nest. The behavioral interaction structure is combined with a spatially varying stochastic differential equation model to allow for spatially and temporally heterogeneous collective movement of all ants within the nest. Our results reveal behavioral tendencies that are related to nearby individuals, particularly the queen, and to different locations in the nest.     

泛种养结合视角下北京市养殖业土地承载力评估

种养结合是中国未来农业绿色发展的重要方向。其中,对畜禽粪污的土地承载力的准确估算是关键。针对北京市畜禽粪污消纳的土地没有充分利用及其氮磷需求取值不够准确的问题,该研究根据畜禽养殖数据计算了2018年北京畜禽养殖粪污产生量和氮磷养分资源量,以粮地、菜地、园地、部分林地、草地及未利用土地6种地类作为畜禽粪污的消纳场所,利用统计年鉴和ArcGIS估算了6种类型的土地资源量,根据文献综合分析了各地类单位面积的氮磷养分需求量,进而计算了北京市域内畜禽养殖业的土地承载力。结果表明：2018年北京市畜禽养殖总量为453万头猪当量,畜禽粪污产生总量为380.1万t,氮磷养分资源量分别为2.61万及0.53万t。在有机肥全部替代化肥的情况下,仅以耕地（粮地、菜地）作为畜禽粪污的消纳场所,则全市种植业土地能够承载的最大养殖量为675万头猪当量;若以6种土地类型作为畜禽粪污的消纳场所,则为1 089万头猪当量,是仅以耕地作为消纳场所的1.61倍。若有机肥50%替代化肥,仅以耕地为畜禽粪污消纳场所,土地承载力为337.6万头猪当量,则2018年的养殖规模已经超过耕地承载力。若以6种土地作为消纳场所,其土地承载力为544.5万头猪当量,与现养殖规模相比还有20.1%的养殖潜力。因此,在环境保护的前提下促进养殖业的发展,一是要扩大有机肥对化肥的替代比例,二是要将更多的可作为畜禽粪污消纳的土地类型加以充分利用。     

A simple method for assessing leaching risk of bacteria through soils

Abstract. Bacterial contamination of water is a problem worldwide and is often acute in developing countries where human and animal waste is disposed of on land for use as fertilizer or because of poorly developed sanitation systems. Studying leaching risk through soils is difficult when no suitable microbiological laboratory is available. A method using the movement of ZnO particles through soils as a surrogate for studying bacteria directly was tested. ZnO particles with a similar size to bacteria can readily be detected by chemical analysis. For a range of nine different soil textures, leaching rates of ZnO particles under near saturated conditions were significantly correlated with leaching rates of Escherichia coli cells ( P =0.013). For both ZnO and E. coli , leaching was generally greatest through fine textured soils.     

基于Geo-WebServices的农田环境动态监测与评价分析系统

为实现农田环境质量数据的在线共享、查询统计与评价分析服务,该文结合地统计学及农田环境质量监测相关专业知识建立采样点布设优选评价模型,并基于GIS、GNSS、角色访问控制等技术,设计开发了农田环境动态监测与评价分析系统。应用证明,系统采用Geo-WebServices技术能够实现分布式存储的极高分辨率遥感影像和大比例尺基础地理数据等数据服务的实时在线集成与共享,提高了数据分析精度,也解决了高精度基础空间数据的共享安全性及数据版权的问题;能依据角色分配用户权限,使得系统安全可靠;能灵活定制与管理农田环境监测评价与预警分析等模型,并实现从采样布设优选评价、采样点数据预处理、环境质量评价与预警分析及结果多方式直观的可视化等全流程的动态监测分析功能,系统能有效应用于农田环境质量监测与管理。     

Estimation of animal location from radio telemetry data with temporal dependencies

We evaluate the performance of several estimators of animal location when data arise from radio telemetry studies. We assume that error-prone bearings are taken at regular time intervals from known locations, that observations may be frequent enough to introduce temporal dependencies, and that animals remain within well-defined home ranges. We simulated data to examine several factors including home range shape, dependency between successive locations, sample size and strategy, and bearing error. Simulated data, supplemented by data based on actual paths for Rocky Mountain elk (Cervus elaphus nelsoni), were used to evaluate alternative location estimators: Lenth’s maximum likelihood estimator (MLE) that assumes independence; Pace’s moving average version of the MLE that introduces a post hoc dependence in the data; and three estimators from state-space models that explicitly model animal movement and dependencies. The state-space models differed in the assumed model of animal movement and included a simple normal random walk, a variation of the random walk that includes a centralizing parameter, and a discretetime version of the Ornstein-Uhlenbeck model for movement within an elliptical home range. Estimates were evaluated in terms of location error and estimator precision. The independent MLE had the poorest performance under most scenarios, particularly when actual locations were dependent. The centrally biased random walk estimator generally had smallest location errors and best precision, whether or not data displayed dependencies. Rather than assuming independence or discarding observations to achieve independence, estimation of location would be served better by accounting for potential dependencies. Methods based on simple models of animal movement may vastly improve estimates, and models that recognize an animal’s sense of home territory are preferred.     

山西省农牧生产体系磷流动空间变异特征

为揭示山西省农牧生产体系磷流动空间分布特征,进一步为养分资源综合管理提供科学建议,本研究使用食物链养分流动模型(NUFER)与Arc GIS相结合,以2011年山西省11个地市农牧生产体系为研究对象,计算了农牧生产体系中的磷流动、损失及账户平衡,并对各个生产体系的磷利用效率(PUE)、有机废弃物中磷的循环利用效率、磷的损失途径等重要指标进行了综合评价,描述了2011年山西省各地市农牧生产体系与区域尺度的磷流动变化特征。研究结果表明,山西省各地市农牧体系磷的投入和损失差异较大,农田生产体系投入范围在22.5~83.0 kg·hm~(-2),而整个农牧生产体系损失区间在2.7~8.8 kg·hm~(-2);磷的投入和损失均总体呈现东南部高、西北部低的空间分布格局;各地市农田磷素均有盈余但程度不均,为9.4~48.4 kg·hm~(-2)。农田生产系统的磷素利用效率(PUEc)高于全国平均水平;农牧生产体系的磷利用效率(PUEc+a)较低,全省平均水平仅为30.3%,主要是由于农牧分离较为严重;有机废弃物的循环利用效率较低(60%)。省域东南部存在潜在环境风险,晋城、晋中等地市有大量的粪尿磷未得到回收利用,可作为周边农业主产区的农田养分资源。因此通过提高农牧生产体系的养分管理水平和区域间养分资源协同管理,能够大幅提高磷的利用效率,同时有效降低环境风险,实现山西农业可持续发展。     

Agronomic and public aspects of soil nitrogen research

Abstract. Public perceptions of agriculture as a contributor to environmental stress are resulting in changes within agricultural production systems. Increasingly, these systems will need to be economically viable, environmentally sound, socially and politically acceptable, and conserving of natural resources-the characteristics that describe a sustainable agriculture. Improving and maintaining agricultural production systems with these characteristics must continue to be the objectives of agricultural research. Nitrogen research has contributed markedly to meeting the production and economic goals of agriculture, but it has not yet focused enough on answering socially and politically sensitive questions. Questions are posed about the environmental effects of various nitrogen management practices and the research needed to answer them is outlined. Emphasis is put on immobilization-mineralization as affected by use of nitrification inhibitors and split-application, release of nitrogen from animal manures, legumes, and other crop residues, and establishing acceptable yield goals.     

动物农家肥的应用与环境化学研究进展

Animal manure consists of predominantly urine and feces,but also may contain bedding materials,dropped feed,scurf,and other farming wastes.Manure is typically applied to soils as fertilizer for agricultural production.The estimated amount of manure produced in 12 major livestock-producing countries is 9 × 10~9 Mg of manure annually.Manure is rich in plant nutrients.However,manure is also considered as an environmental pollutant when it is over-applied to cropland or following runoff into surface water.Manure can also in?uence global climate change via emissions of methane(CH_4) and nitrous oxide(N_2O).Thus,increased and updated knowledge of applied and environmental chemistry of animal manure is needed to shed light on the research and development of animal manure utilization and minimization of its adverse environmental concerns.The advances in basic and applied studies of manure major components,organic matter,phosphorus,and nitrogen,primarily related to US livestock production are summarized in this review.Detailed focus was placed on three notable challenges for future manure research:1) soil application of animal manure,2)manure phytate phosphorus,and 3) manure nitrogen availability.This review may contribute to the global effort in sustainable and environmentally sound agriculture by stimulating new ideas and directions in animal manure research,and promoting application of knowledge and insight derived from manure research into improved manure management strategies.     

Nutrient management in low input grazing-based systems of meat production

Abstract. Low input grazing-based meat production is often practised on land where alternative land use is restricted and where high biodiversity warrants specific environmental payments. Although these systems are characterized by low external nutrient inputs, significant nutrient losses may occur per unit of produce, even though losses per unit area are low. If the aim is to have animal production without further eutrophication of watercourses, these losses should be minimized,. However, if nutrient-poor grasslands characterized by high biodiversity are the aim, some losses must be accepted to balance nutrient inputs by atmospheric deposition. The impact of grazing animals on nutrient dynamics in grasslands is reviewed in this paper, and options to further improve nutrient management are discussed. It is concluded that nutrient management should largely be addressed indirectly through management of animal behaviour in relation to grazing and supplemental feeding, as well as through optimization of the seasonal distribution of livestock size. A case study indicated that N losses from a cattle farm could be reduced considerably by these means, while animal production could actually be improved. Sustainability issues and trends in legislative and social pressures on low input grazing-based systems of animal production are discussed in relation to nutrient management and practical recommendations.     

Nutrient management in low input grazing–based systems of meat production

Abstract. Low input grazing-based meat production is often practised on land where alternative land use is restricted and where high biodiversity warrants specific environmental payments. Although these systems are characterized by low external nutrient inputs, significant nutrient losses may occur per unit of produce, even though losses per unit area are low. If the aim is to have animal production without further eutrophication of watercourses, these losses should be minimized,. However, if nutrient-poor grasslands characterized by high biodiversity are the aim, some losses must be accepted to balance nutrient inputs by atmospheric deposition. The impact of grazing animals on nutrient dynamics in grasslands is reviewed in this paper, and options to further improve nutrient management are discussed. It is concluded that nutrient management should largely be addressed indirectly through management of animal behaviour in relation to grazing and supplemental feeding, as well as through optimization of the seasonal distribution of livestock size. A case study indicated that N losses from a cattle farm could be reduced considerably by these means, while animal production could actually be improved. Sustainability issues and trends in legislative and social pressures on low input grazing-based systems of animal production are discussed in relation to nutrient management and practical recommendations.     

Limited-Information Modeling of Loggerhead Turtle Population Size

We attempt to estimate the size of a population of female loggerhead turtles. In traditional capture-recapture experiments to estimate the size of an animal population, individual animals are tagged and the information about which individuals are captured repeatedly is crucial. For these loggerhead turtle data, information about individual turtles is not available. Rather, we observe only the counts of successful and failed nestings at a location over a series of days (in our case, three). We view the turtles’ nesting behavior as an alternating renewal process, model it using parametric distributions, and then derive probability distributions that describe the behavior of the turtles during the three days via a 3-way contingency table. We adopt a Bayesian approach, formulating our model in terms of parameters about which strong prior information is available. We use a Gibbs sampling algorithm to sample from the posterior distribution of our random quantities, the most crucial of which is the number of turtles remaining offshore during the entire sampling period. We illustrate the method using data sets from loggerhead turtle sites along the South Carolina coast. We provide a simulation study which illustrates the quality and robustness of the method and investigates sensitivity to prior parameter specification.