Development and testing of a genetic marker‐based pedigree reconstruction system ‘PR‐genie’ incorporating size‐class data

For wildlife populations, it is often difficult to determine biological parameters that indicate breeding patterns and population mixing, but knowledge of these parameters is essential for effective management. A pedigree encodes the relationship between individuals and can provide insight into the dynamics of a population over its recent history. Here, we present a method for the reconstruction of pedigrees for wild populations of animals that live long enough to breed multiple times over their lifetime and that have complex or unknown generational structures. Reconstruction was based on microsatellite genotype data along with ancillary biological information: sex and observed body size class as an indicator of relative age of individuals within the population. Using body size‐class data to infer relative age has not been considered previously in wildlife genealogy and provides a marked improvement in accuracy of pedigree reconstruction. Body size‐class data are particularly useful for wild populations because it is much easier to collect noninvasively than absolute age data. This new pedigree reconstruction system, PR‐genie, performs reconstruction using maximum likelihood with optimization driven by the cross‐entropy method. We demonstrated pedigree reconstruction performance on simulated populations (comparing reconstructed pedigrees to known true pedigrees) over a wide range of population parameters and under assortative and intergenerational mating schema. Reconstruction accuracy increased with the presence of size‐class data and as the amount and quality of genetic data increased. We provide recommendations as to the amount and quality of data necessary to provide insight into detailed familial relationships in a wildlife population using this pedigree reconstruction technique.     

Wildlife hazard assessment for Phoenix Sky Harbor International Airport

We examined wildlife abundance, distribution, and movement patterns at Phoenix Sky Harbor International Airport (PHX) and within an 8-km radius to assess current air-strike hazards, and to provide baseline information for projecting changes in air-strike hazards as land-use patterns around PHX change. We found that water sources at or near PHX especially induced wildlife movement patterns that put air traffic at risk. This was particularly true of the Salt River bed adjacent to the airport, which also is a natural flight corridor for birds. Compounding the problem, air traffic at PHX was the heaviest when bird abundance and activity was the greatest during migration and breeding. We feel that air strike hazards at PHX are likely to increase substantially as the Salt River bed is reclaimed to produce additional lakes and high quality riparian habitat. We offer recommendations to reduce the hazard levels currently found at PHX and to reduce additional hazards as the habitat around PHX is converted and produces more attractive wildlife habitat.     

Overlapping landscapes: A persistent,but misdirected concern when collecting and analyzing ecological data

A primary focus of wildlife ecology is studying how the arrangement, quality, and distribution of habitat influence wildlife populations at multiple spatial scales. A practical limitation of conducting wildlife–habitat investigations in the field, however, is that sampling points tend to be close to one another, resulting in spatial clustering. Consequently, when ecologists seek to quantify the effects of environmental predictors surrounding their sampling points, they encounter the issue of using landscapes that are partially or completely overlapping. A presumed problem of overlapping landscapes is that data generated from these landscapes, when used as predictors in statistical modeling, might violate the assumption of independence. However, the independence of error is the critical assumption, not the independence of predictor variables. Nonetheless, many researchers strive to avoid such overlaps through sampling design or alternative analytical procedures and specialized software programs have been created to assist with this. We present theoretical arguments and empirical evidence showing that changing the amount of overlap does not alter the degree of spatial autocorrelation. Using data derived from 2 broad-scaled avian monitoring programs, we quantified the relationship between forest cover and bird abundance and occurrence at multiple landscapes ranging from 100 m to 24 km across. We found no clear evidence that increasing overlap of landscapes increased spatial autocorrelation in model residuals. Our results demonstrate that the concern of overlapping landscapes as a potential cause of violation of spatial independency among sampling units is misdirected and represents an oversimplification of the statistical and ecological issues surrounding spatial autocorrelation. Overlapping landscapes and spatial autocorrelation are separate issues in the modeling of wildlife populations and their habitats; non-overlapping landscapes do not ensure spatial independency and overlapping landscapes do not necessarily lead to greater spatial autocorrelation in model errors. © 2011 The Wildlife Society.     

Wildlife tracking data management: a new vision

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioural data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals'' environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.     

Use of information on disease diagnoses from databases for animal health economic,welfare and food safety purposes: strengths and limitations of recordings

Many animal health, welfare and food safety databases include data on clinical and test-based disease diagnoses. However, the circumstances and constraints for establishing the diagnoses vary considerably among databases. Therefore results based on different databases are difficult to compare and compilation of data in order to perform meta-analysis is almost impossible. Nevertheless, diagnostic information collected either routinely or in research projects is valuable in cross comparisons between databases, but there is a need for improved transparency and documentation of the data and the performance characteristics of tests used to establish diagnoses. The objective of this paper is to outline the circumstances and constraints for recording of disease diagnoses in different types of databases, and to discuss these in the context of disease diagnoses when using them for additional purposes, including research. Finally some limitations and recommendations for use of data and for recording of diagnostic information in the future are given. It is concluded that many research questions have such a specific objective that investigators need to collect their own data. However, there are also examples, where a minimal amount of extra information or continued validation could make sufficient improvement of secondary data to be used for other purposes. Regardless, researchers should always carefully evaluate the opportunities and constraints when they decide to use secondary data. If the data in the existing databases are not sufficiently valid, researchers may have to collect their own data, but improved recording of diagnostic data may improve the usefulness of secondary diagnostic data in the future.     

Camera traps and guard observations as an alternative to researcher observation for studying anthropogenic foraging

Foraging by wildlife on anthropogenic foods can have negative impacts on both humans and wildlife. Addressing this issue requires reliable data on the patterns of anthropogenic foraging by wild animals, but while direct observation by researchers can be highly accurate, this method is also costly and labor‐intensive, making it impractical in the long‐term or over large spatial areas. Camera traps and observations by guards employed to deter animals from fields could be efficient alternative methods of data collection for understanding patterns of foraging by wildlife in crop fields. Here, we investigated how data on crop‐foraging by chacma baboons and vervet monkeys collected by camera traps and crop guards predicted data collected by researchers, on a commercial farm in South Africa. We found that data from camera traps and field guard observations predicted crop loss and the frequency of crop‐foraging events from researcher observations for crop‐foraging by baboons and to a lesser extent for vervets. The effectiveness of cameras at capturing crop‐foraging events was dependent on their position on the field edge. We believe that these alternatives to direct observation by researchers represent an efficient and low‐cost method for long‐term and large‐scale monitoring of foraging by wildlife on crops.     

Private Lands Programs and Lessons Learned in Illinois

ABSTRACT State wildlife agencies commonly offer private landowners cost-share and technical assistance to improve habitat, but the cost-effectiveness and long-term outcomes of these efforts are rarely evaluated. In 1998, we began a 3-part, statewide evaluation of the Illinois Department of Natural Resources’ (IDNR; USA) Private Land Wildlife Habitat Management Program (hereafter the program) as it functioned from 1986 to 1996. We sent a mail-back questionnaire to IDNR biologists to collect information on their perceptions of the program. We sent a separate mail-back questionnaire to private landholders who participated in the program to ascertain their demographic profile, motivations for participation, and attitudes regarding the program. We also conducted on-site evaluations of private properties that were managed under the guidance of the program. We conducted our study to 1) assess if the program effectively assisted participants in establishing and maintaining wildlife habitat, and 2) determine factors associated with optimal management of wildlife habitat on private lands to refine the program and improve effectiveness. We found significant differences between participants in their land use priorities and motivations for managing wildlife and in the resources available to participants to establish and maintain habitat. Our results indicate that although financial incentives may increase participation in private lands initiatives, improving technical and material assistance to landholders is essential for maintaining quality wildlife habitat over the long-term.     

Biological ontologies in rice databases. An introduction to the activities in Gramene and Oryzabase

An enormous amount of information and materials in the field of biology has been accumulating, such as nucleotide and amino acid sequences, gene and protein functions, mutants and their phenotypes, and literature references, produced by the rapid development in this field. Effective use of the information may strongly promote biological studies, and may lead to many important findings. It is, however, time-consuming and laborious for individual researchers to collect information from individual original sites and to rearrange it for their own purpose. A concept, ontology, has been introduced in biology to support and encourage researchers to share and reuse information among biological databases. Ontology has a glossary, named dynamic controlled vocabulary, in which relationships between terms are defined. Since each term is strictly defined and identified with an ID number, a set of data represented in biological ontology is easily accessible to automated information processing, even if the data sets are across several databases and/or different organisms. In this mini-review, we introduce activities in Gramene and Oryzabase, which provide biological ontologies for Oryza sativa (rice).     

Development of multi-species indicators for the Nevada Wildlife Action Plan

Wildlife managers, conservationists, and policy-makers are interested in indicators that aggregate population status and/or trend information for multiple species. Several multi-species indicators have been proposed, which either report species status ranks or rank changes (using either the International Union for the Conservation of Nature or NatureServe ranking systems), or which report the average direction or tendency of time series from multiple populations or species. We explore the utility of these indicators within the context of the Nevada Wildlife Action Plan, one of 56 state or territorial wildlife conservation plans that have recently been developed and published by state wildlife agencies in the USA. The Nevada Wildlife Action Plan identifies 186 “species of greatest conservation need,” including birds, mammals, reptiles, amphibians, fish, and mollusks. Significant deficiencies in the existing monitoring data for these taxa limit the applicability of nearly all of the multi-species indicators that have been described to date. However, we were able to populate a simple multi-species status indicator with data for all 186 species. We also describe a simple graphical indicator that summarizes information about the direction of population trends for suites of multiple species, and discuss how this tool could be populated with data in future revisions of the Nevada Wildlife Action Plan.     

IP traceback with sparsely-tagged fragment marking scheme under massively multiple attack paths

IP traceback is known to be one of the most effective measures to deter Internet attacks. Various techniques for IP traceback have been suggested. Among them, we focus on Probabilistic Packet Marking scheme (PPM) with tagging. We believe PPM is more advantageous than others because it does not generate additional network traffic and requires minimal protocol change. However, three parameters need to be optimized to make PPM practical under massively multiple attack paths: the number of packets to collect, the number of fragment combinations to recover the IP addresses, and the false positive error rate. Tagging is an effective way to reduce the number of combinations but it increases the false positive error rates when the number of routers in the attack paths grows. Other PPM-related techniques suggested in the past have similar problems. They improve one or two parameters at the expense of others, or they require additional data structures such as an upstream router map. In this paper, we propose a method that optimizes the three parameters at the same time and recovers original IPs quickly and correctly even in the presence of massive multiple attack paths. Our method does not need either a combinatorial process to recover IPs or additional information such as an upstream router map. Our result shows that our method recovers 95% of the original IPs correctly with no fragment combinations and with zero false positives. It needs to collect only 8N packets per router where N is the number of routers involved in the attack paths.     

中国野生动物调查存在的问题与改进建议

一百余年前,人类就开始了相对系统的野生动物调查。目前已经建立了成熟的方法体系,并制定了相应的调查规范。最近几十年来,我国科研人员进行了大量的野生动物调查。但是,当前我国的野外调查规范还不够细致,调查者在调查时缺乏必要的约束,导致调查数据不规范、不可靠,很多重要信息缺失。突出问题有：样线信息不全,只有起点和终点的经纬度,没有自动记录的详细样线信息（如每秒记录一次的连续点位信息,含经纬度和时间）;动物位点信息缺乏可信度指标（如距观测者的距离）;调查时间不合理;调查地点的空间取样不均衡;记录的标准化不够（如每个观测点的观测时长不确定）等等。对此,我们参考国际通用的调查规范,提出了一些简单易行的调查要点,以便提高野外调查数据的质量。另外,我们提倡野外记录的无纸化,充分利用现有的手机应用软件（APP）和模型工具提高野外记录以及后期数据处理的效率。最后,我们提议建立固定的中国生物多样性监测样线体系,以便消除每年调查时空间取样的不确定性,更好地量化野生动物的时间动态,为野生动物的保护和管理提供依据。     

From Wiens to Robel: A Review of Grassland-Bird Habitat Selection

ABSTRACT Efforts to stabilize or increase grassland bird populations require identification of suitable habitat as a first step. Although the number of studies examining grassland-bird habitat selection has increased substantially in recent years, much uncertainty exists regarding local-scale habitat variables that researchers should consider. We reviewed 57 studies and identified important vegetation features correlated with grassland bird abundance, density, occurrence, and nest and territory selection. Our objectives were to 1) guide future studies of grassland-bird habitat use by providing a reduced set of relevant vegetation characteristics, 2) challenge researchers to critically think about what variables to consider, and 3) highlight the need to include consistent definitions of terms used to describe grassland bird habitat. We identified 9 variables that were important predictors of habitat use by grassland birds: coverage of bare ground (important in 50% of the instances where it was included), grass (34% of instances), dead vegetation (33% of instances), forbs (31% of instances), and litter (29% of instances), along with an index of vegetation density (39% of instances) and volume (39% of instances), litter depth (36% of instances), and vegetation height (41% of instances). Only 25% of studies provided information on effects sizes and measures of variance. Furthermore, definitions of measured habitat variables were not consistent among studies. We provide definitions of the 9 important variables and implore authors to report effect size and measures of variance. Standardization of terms and reporting of meaningful results will facilitate replication of wildlife research and enhance our ability to recognize general patterns that emerge from observational studies of habitat use.     

Noniterative adjustment to regression estimators with population-based auxiliary information for semiparametric models

Disease registries, surveillance data, and other datasets with extremely large sample sizes become increasingly available in providing population-based information on disease incidence, survival probability, or other important public health characteristics. Such information can be leveraged in studies that collect detailed measurements but with smaller sample sizes. In contrast to recent proposals that formulate additional information as constraints in optimization problems, we develop a general framework to construct simple estimators that update the usual regression estimators with some functionals of data that incorporate the additional information. We consider general settings that incorporate nuisance parameters in the auxiliary information, non-i.i.d. data such as those from case-control studies, and semiparametric models with infinite-dimensional parameters common in survival analysis. Details of several important data and sampling settings are provided with numerical examples.     

Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management

Barbed and woven wire fences, common structures across western North America, act as impediments to wildlife movements. In particular, fencing influences pronghorn (Antilocapra americana) daily and seasonal movements, as well as modifying habitat selection. Because of fencing''s impacts to pronghorn and other wildlife, it is a potentially important factor in both wildlife movement and habitat selection models. At this time, no geospatial fencing data is available at regional scales. Consequently, we constructed a regional fence model using a series of land tenure assumptions for the Hi-Line region of northern Montana – an area consisting of 13 counties over 103,400 km². Randomized 3.2 km long transects (n = 738) on both paved and unpaved roads were driven to collect information on habitat, fence densities and fence type. Using GIS, we constructed a fence location and a density model incorporating ownership, size, neighboring parcels, township boundaries and roads. Local knowledge of land ownership and land use assisted in improving the final models. We predict there is greater than 263,300 km of fencing in the Hi-Line region, with a maximum density of 6.8 km of fencing per km² and mean density of 2.4 km of fencing per km². Using field data to assess model accuracy, Cohen''s Kappa was measured at 0.40. On-the-ground fence modification or removal could be prioritized by identifying high fence densities in critical wildlife areas such as pronghorn migratory pathways or sage grouse lekking habitat. Such novel fence data can assist wildlife and land managers to assess effects of anthropogenic features to wildlife at various scales; which in turn may help conserve declining grassland species and overall ecological functionality.     

Human vs. machine: Detecting wildlife in camera trap images

As the capacity to collect and store large amounts of data expands, identifying and evaluating strategies to efficiently convert raw data into meaningful information is increasingly necessary. Across disciplines, this data processing task has become a significant challenge, delaying progress and actionable insights. In ecology, the growing use of camera traps (i.e., remotely triggered cameras) to collect information on wildlife has led to an enormous volume of raw data (i.e., images) in need of review and annotation. To expedite camera trap image processing, many have turned to the field of artificial intelligence (AI) and use machine learning models to automate tasks such as detecting and classifying wildlife in images. To contribute understanding of the utility of AI tools for processing wildlife camera trap images, we evaluated the performance of a state-of-the-art computer vision model developed by Microsoft AI for Earth named MegaDetector using data from an ongoing camera trap study in Arctic Alaska, USA. Compared to image labels determined by manual human review, we found MegaDetector reliably determined the presence or absence of wildlife in images generated by motion detection camera settings (≥94.6% accuracy), however, performance was substantially poorer for images collected with time-lapse camera settings (≤61.6% accuracy). By examining time-lapse images where MegaDetector failed to detect wildlife, we gained practical insights into animal size and distance detection limits and discuss how those may impact the performance of MegaDetector in other systems. We anticipate our findings will stimulate critical thinking about the tradeoffs of using automated AI tools or manual human review to process camera trap images and help to inform effective implementation of study designs.     

红外相机技术在物种监测中的应用及数据挖掘

由于濒危物种数量稀少以及大多数野生动物对人类活动敏感, 增加了传统调查的难度。众所周知,红外相机在野生动物调查研究中具有天然优势; 然而随着红外相机技术的广泛推广应用及数据采集量的不断加大, 科研人员也面临了一系列关于红外相机监测及后续数据处理中出现的问题。本文详细阐述了红外相机数据管理和利用方面存在的3个关键问题: 数据管理缺乏规范化、数据网络缺乏一体化、数据获取缺乏标准化。同时以秦岭、卧龙等地的一些研究为主体, 列举分析了红外相机照片后续数据挖掘中8个方面的内容, 即兽类的个体识别、物种时间活动格局、物种空间活动格局、偶见物种信息利用、物种行为活动、繁殖信息、疾病情况、人为干扰。这些信息的有效利用可为野生动物及生物多样性的保护、管理提供一定科学支撑。     

SILIC: A cross database framework for automatically extracting robust biodiversity information from soundscape recordings based on object detection and a tiny training dataset

• 1.Passive acoustic monitoring (PAM) offers many advantages comparing with other survey methods and gains an increasing use in terrestrial ecology, but the massive effort needed to extract species information from a large number of recordings limits its application. The convolutional neural network (CNN) has been demonstrated with its high performance and effectiveness in identifying sound sources automatically. However, requiring a large amount of training data still constitutes a challenge.
• 2.Object detection is used to detect multiple objects in photos or videos and is effective at detecting small objects in a complex context, such as animal sounds in a spectrogram and shows the opportunity to build a good performance model with a small training dataset. Therefore, we developed the Sound Identification and Labeling Intelligence for Creatures (SILIC), which integrates online animal sound databases, PAM databases and an object detection-based model, for extracting information on the sounds of multiple species from complex soundscape recordings.
• 3.We used the sounds of six owl species in Taiwan to demonstrate the effectiveness, efficiency and application potential of the SILIC framework. Using only 786 sound labels in 133 recordings, our model successfully identified the species' sounds from the recordings collected at five PAM stations, with a macro-average AUC of 0.89 and a mAP of 0.83. The model also provided the time and frequency information, such as the duration and bandwidth, of the sounds.
• 4.To our best knowledge, this is the first time that the object detection algorithm has been used to identify sounds of multiple wildlife species. With an online sound-labeling platform embedded and a novel data preprocessing approach (i.e., rainbow mapping) applied, the SILIC shows its good performance and high efficiency in identifying wildlife sounds and extracting robust species, time and frequency information from a massive amount of soundscape recordings based on a tiny training dataset acquired from existing animal sound databases. The SILIC can help expand the application of PAM as a tool to evaluate the state of and detect the change in biodiversity by, for example, providing high temporal resolution and continuous information on species presence across a monitoring network.

     

What You Should Know About Land-Cover Data

ABSTRACT Wildlife biologists are using land-characteristics data sets for a variety of applications. Many kinds of landscape variables have been characterized and the resultant data sets or maps are readily accessible. Often, too little consideration is given to the accuracy or traits of these data sets, most likely because biologists do not know how such data are compiled and rendered, or the potential pitfalls that can be encountered when applying these data. To increase understanding of the nature of land-characteristics data sets, I introduce aspects of source information and data-handling methodology that include the following: ambiguity of land characteristics; temporal considerations and the dynamic nature of the landscape; type of source data versus landscape features of interest; data resolution, scale, and geographic extent; data entry and positional problems; rare landscape features; and interpreter variation. I also include guidance for determining the quality of land-characteristics data sets through metadata or published documentation, visual clues, and independent information. The quality or suitability of the data sets for wildlife applications may be improved with thematic or spatial generalization, avoidance of transitional areas on maps, and merging of multiple data sources. Knowledge of the underlying challenges in compiling such data sets will help wildlife biologists to better assess the strengths and limitations and determine how best to use these data.     

The need for standardization in wildlife science: home range estimators as an example

Individual studies in wildlife science are indicative rather than conclusive. Although multiple studies can be meta-analyzed in such a way that scientific hypotheses can be tested, robust meta-analyses are often difficult or impossible if variables of interest are not measured in a uniform manner. We hypothesized that measurements, even of basic and unequivocal variables, are rarely standardized in wildlife sciences. We tested this assumption by reviewing randomly selected papers that describe the home range of mammals (n?=?25) and birds (n?=?25). In these papers, home ranges were calculated using 11 methods and 8 computer programs. The number of radiolocations used to calculate home ranges varied from 9 to >2,000. By estimating home ranges for two radiotelemetry data sets, we demonstrate that home ranges are not comparable if different methods are used and that estimates of home range are not standardized. We assume that measurements of other biological variables are even less consistent across studies. In order to advance wildlife sciences, we believe that standardization initiatives are required at an international level.     

Comparing data of different survey methods for sustainable wildlife management in hunting areas: the case of Tarangire–Manyara ecosystem,northern Tanzania

Cost–benefit considerations of wildlife monitoring are essential, particularly, in areas outside national park boundaries, where resources for conducting wildlife censuses are scarce, but that, at the same time, are subject to high pressure for wildlife utilization, such as hunting. Large mammal survey data from various sources were collated and analyzed to investigate which methods are best suited for monitoring purposes at low cost in the Tarangire–Manyara ecosystem, northern Tanzania. Our results indicate that primary data (from aerial and road transects counts) that involve direct species observations, although sometimes very expensive, are required for establishing the status of the target species in terms of density or population size. Concomitantly, secondary data from various sources, such as interviews, hunting quota, and damage reports, obtained over wide areas and over longer periods of time, can provide important information on presence/absence and distribution of species within an area. In addition, the study revealed that hunting quotas set did not correlate with species abundance/numbers from the primary data surveys for most of the large mammals hunted within the ecosystem. For a better conservation and management of wildlife, in particular with respect to the forthcoming formation of Wildlife Management Areas, we propose an integrated approach to wildlife monitoring using primary and secondary data sources through the involvement of local people’s knowledge.