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Detection Probability (detection + probability)
Selected AbstractsSite Occupancy Models with Heterogeneous Detection ProbabilitiesBIOMETRICS, Issue 1 2006J. Andrew Royle Summary Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these "site occupancy" models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link (2003, Biometrics59, 1123,1130) demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs. [source] On the importance of estimating detection probabilities from at-sea surveys of flying seabirdsJOURNAL OF AVIAN BIOLOGY, Issue 6 2009Christophe Barbraud The primary and accepted method used to estimate seabird densities at sea from ships is the strip transect method, designed to correct for the effect of random directional bird movement relative to that of the ship. However, this method relies on the critical assumption that all of the birds within the survey strip are detected. We used the distance sampling method from line-transects to estimate detection probability of a number of species of flying seabirds, and to test whether distance from the ship and bird body size affected detectability. Detection probability decreased from 0.987 (SE=0.029) to 0.269 (SE=0.035) with increasing strip half-width from 100 to 1400,m. Detection probability also varied between size-groups of species with strip half-width. For all size-groups, this probability was close to 1 for strip half-width of 100,m, but was 0.869 (SE=0.115), 0.725 (SE=0.096) and 0.693 (SE=0.091) for strip half-width of 300,m, a typical strip width used in seabird surveys, for respectively large, medium and small size flying seabirds. For larger strip half-width, detection probability was higher for large sized species, intermediate for medium sized species and lower for smaller sized species. For strip half-width larger than 100,m we suggest that more attention should be paid to testing the assumption of perfect detectability, because abundance estimates may be underestimated when this assumption is violated. Finally, the effect of the speed of travel of flying seabird on the detection probability was estimated in a simulation study, which suggests that detection probability was underestimated with increasing flying speed. [source] A spatial model of bird abundance as adjusted for detection probabilityECOGRAPHY, Issue 2 2009P. Marcos Gorresen Modeling the spatial distribution of animals can be complicated by spatial and temporal effects (i.e. spatial autocorrelation and trends in abundance over time) and other factors such as imperfect detection probabilities and observation-related nuisance variables. Recent advances in modeling have demonstrated various approaches that handle most of these factors but which require a degree of sampling effort (e.g. replication) not available to many field studies. We present a two-step approach that addresses these challenges to spatially model species abundance. Habitat, spatial and temporal variables were handled with a Bayesian approach which facilitated modeling hierarchically structured data. Predicted abundance was subsequently adjusted to account for imperfect detection and the area effectively sampled for each species. We provide examples of our modeling approach for two endemic Hawaiian nectarivorous honeycreepers: ,i,iwi Vestiaria coccinea and ,apapane Himatione sanguinea. [source] Multi-scale occupancy estimation and modelling using multiple detection methodsJOURNAL OF APPLIED ECOLOGY, Issue 5 2008James D. Nichols Summary 1Occupancy estimation and modelling based on detection,nondetection data provide an effective way of exploring change in a species' distribution across time and space in cases where the species is not always detected with certainty. Today, many monitoring programmes target multiple species, or life stages within a species, requiring the use of multiple detection methods. When multiple methods or devices are used at the same sample sites, animals can be detected by more than one method. 2We develop occupancy models for multiple detection methods that permit simultaneous use of data from all methods for inference about method-specific detection probabilities. Moreover, the approach permits estimation of occupancy at two spatial scales: the larger scale corresponds to species' use of a sample unit, whereas the smaller scale corresponds to presence of the species at the local sample station or site. 3We apply the models to data collected on two different vertebrate species: striped skunks Mephitis mephitis and red salamanders Pseudotriton ruber. For striped skunks, large-scale occupancy estimates were consistent between two sampling seasons. Small-scale occupancy probabilities were slightly lower in the late winter/spring when skunks tend to conserve energy, and movements are limited to males in search of females for breeding. There was strong evidence of method-specific detection probabilities for skunks. As anticipated, large- and small-scale occupancy areas completely overlapped for red salamanders. The analyses provided weak evidence of method-specific detection probabilities for this species. 4Synthesis and applications. Increasingly, many studies are utilizing multiple detection methods at sampling locations. The modelling approach presented here makes efficient use of detections from multiple methods to estimate occupancy probabilities at two spatial scales and to compare detection probabilities associated with different detection methods. The models can be viewed as another variation of Pollock's robust design and may be applicable to a wide variety of scenarios where species occur in an area but are not always near the sampled locations. The estimation approach is likely to be especially useful in multispecies conservation programmes by providing efficient estimates using multiple detection devices and by providing device-specific detection probability estimates for use in survey design. [source] On the importance of estimating detection probabilities from at-sea surveys of flying seabirdsJOURNAL OF AVIAN BIOLOGY, Issue 6 2009Christophe Barbraud The primary and accepted method used to estimate seabird densities at sea from ships is the strip transect method, designed to correct for the effect of random directional bird movement relative to that of the ship. However, this method relies on the critical assumption that all of the birds within the survey strip are detected. We used the distance sampling method from line-transects to estimate detection probability of a number of species of flying seabirds, and to test whether distance from the ship and bird body size affected detectability. Detection probability decreased from 0.987 (SE=0.029) to 0.269 (SE=0.035) with increasing strip half-width from 100 to 1400,m. Detection probability also varied between size-groups of species with strip half-width. For all size-groups, this probability was close to 1 for strip half-width of 100,m, but was 0.869 (SE=0.115), 0.725 (SE=0.096) and 0.693 (SE=0.091) for strip half-width of 300,m, a typical strip width used in seabird surveys, for respectively large, medium and small size flying seabirds. For larger strip half-width, detection probability was higher for large sized species, intermediate for medium sized species and lower for smaller sized species. For strip half-width larger than 100,m we suggest that more attention should be paid to testing the assumption of perfect detectability, because abundance estimates may be underestimated when this assumption is violated. Finally, the effect of the speed of travel of flying seabird on the detection probability was estimated in a simulation study, which suggests that detection probability was underestimated with increasing flying speed. [source] Comparative dynamics of avian communities across edges and interiors of North American ecoregionsJOURNAL OF BIOGEOGRAPHY, Issue 4 2006Krithi K. Karanth Abstract Aim, Based on a priori hypotheses, we developed predictions about how avian communities might differ at the edges vs. interiors of ecoregions. Specifically, we predicted lower species richness and greater local turnover and extinction probabilities for regional edges. We tested these predictions using North American Breeding Bird Survey (BBS) data across nine ecoregions over a 20-year time period. Location, Data from 2238 BBS routes within nine ecoregions of the United States were used. Methods, The estimation methods used accounted for species detection probabilities < 1. Parameter estimates for species richness, local turnover and extinction probabilities were obtained using the program COMDYN. We examined the difference in community-level parameters estimated from within exterior edges (the habitat interface between ecoregions), interior edges (the habitat interface between two bird conservation regions within the same ecoregion) and interior (habitat excluding interfaces). General linear models were constructed to examine sources of variation in community parameters for five ecoregions (containing all three habitat types) and all nine ecoregions (containing two habitat types). Results, Analyses provided evidence that interior habitats and interior edges had on average higher bird species richness than exterior edges, providing some evidence of reduced species richness near habitat edges. Lower average extinction probabilities and turnover rates in interior habitats (five-region analysis) provided some support for our predictions about these quantities. However, analyses directed at all three response variables, i.e. species richness, local turnover, and local extinction probability, provided evidence of an interaction between habitat and region, indicating that the relationships did not hold in all regions. Main conclusions, The overall predictions of lower species richness, higher local turnover and extinction probabilities in regional edge habitats, as opposed to interior habitats, were generally supported. However, these predicted tendencies did not hold in all regions. [source] Detection, survival rates and dynamics of a cryptic plant, Asclepias meadii: applications of mark-recapture models to long-term monitoring studiesJOURNAL OF ECOLOGY, Issue 2 2009Helen M. Alexander Summary 1Analysis of population trajectories is central to assessing risk in populations of conservation concern. In animal studies, researchers realize that probabilities of detection of individuals are often less than one. Plants can also escape detection due to dormancy, herbivory, or observer error, but such information is rarely incorporated into population studies. 2We monitored a population of Asclepias meadii, a rare long-lived prairie perennial. Despite standardized methods, numbers of observed plants fluctuated greatly from 1992 to 2006. Individual plants often had periods of 1,5 years between initial and final sighting when no stems were found. To determine the actual population trajectories, we estimated rates of survival and population growth using mark-recapture models. We also estimated initial and resighting probabilities of detection. In 2007, we repeated surveys to identify reasons for low detection probabilities. 3We estimated 95% annual survival and a population growth rate of 1.023. Probabilities of initial detection were low (typically from 0.120 to 0.311 depending on prairie burn treatment), whereas average probability of detection for marked plants was 0.728. 4Comparisons of survival estimates from 15- and 8-year data sets revealed that survival estimates decline in the final years of a multi-year period, probably due to heterogeneity in encounter histories. 5By conducting three different surveys in 2007, we found that both herbivory over a multiple-week period and observer error contributed substantially to gaps in detection. 6Synthesis. Probabilities of detection that are less than one complicate interpretation of population dynamics, whether of mobile animals or inconspicuous plants. Our work illustrates three general points that could apply to many plant population studies: (i) mark-recapture models may provide insights on vital rates and population trajectories despite the extreme variability in count data that can arise because of low detectability, (ii) probabilities of initial detection can be quantified and can be considerably less than probabilities of resighting, and (iii) repeated surveys can help researchers determine the degree to which dormancy, herbivory, or observer error contribute to low probabilities of detection. Consideration of these points can improve the design and analysis of monitoring programs. [source] Cuscore Statistics to Monitor a Non-stationary SystemQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 3 2007Harriet Black Nembhard Abstract We investigate the monitoring of a process subject to minimum mean-squared error feedback control using cumulative score (Cuscore) charts. Specifically, we design Cuscore statistics to discover spike, step, bump, and ramp signals hidden in non-stationary disturbance for feedback-controlled processes. We develop the adjustment and monitoring policies for combinations of process dynamics, disturbance, and signal that are practical in industry. We also address issues of detection probabilities and distributions using simulation. A manufacturing case study is used to illustrate the utility of the Cuscore approach. Copyright © 2006 John Wiley & Sons, Ltd. [source] Double-Observer Line Transect Methods: Levels of IndependenceBIOMETRICS, Issue 1 2010Stephen T. Buckland Summary Double-observer line transect methods are becoming increasingly widespread, especially for the estimation of marine mammal abundance from aerial and shipboard surveys when detection of animals on the line is uncertain. The resulting data supplement conventional distance sampling data with two-sample mark,recapture data. Like conventional mark,recapture data, these have inherent problems for estimating abundance in the presence of heterogeneity. Unlike conventional mark,recapture methods, line transect methods use knowledge of the distribution of a covariate, which affects detection probability (namely, distance from the transect line) in inference. This knowledge can be used to diagnose unmodeled heterogeneity in the mark,recapture component of the data. By modeling the covariance in detection probabilities with distance, we show how the estimation problem can be formulated in terms of different levels of independence. At one extreme, full independence is assumed, as in the Petersen estimator (which does not use distance data); at the other extreme, independence only occurs in the limit as detection probability tends to one. Between the two extremes, there is a range of models, including those currently in common use, which have intermediate levels of independence. We show how this framework can be used to provide more reliable analysis of double-observer line transect data. We test the methods by simulation, and by analysis of a dataset for which true abundance is known. We illustrate the approach through analysis of minke whale sightings data from the North Sea and adjacent waters. [source] Site Occupancy Models with Heterogeneous Detection ProbabilitiesBIOMETRICS, Issue 1 2006J. Andrew Royle Summary Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these "site occupancy" models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link (2003, Biometrics59, 1123,1130) demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs. [source] Differential Use of Trails by Forest Mammals and the Implications for Camera-Trap Studies: A Case Study from BelizeBIOTROPICA, Issue 1 2010Bart J. Harmsen ABSTRACT Relative abundance indices are often used to compare species abundance between sites. The indices assume that species have similar detection probabilities, or that differences between detection probabilities are known and can be corrected for. Indices often consist of encounter frequencies of footprints, burrows, markings or photo captures along trails or transect lines, but the assumption of equal detection probabilities is rarely validated. This study analyzes detection probabilities of a range of Neotropical mammals on trails in dense secondary forests, using camera-trap and track data. Photo captures of the two large cats, jaguars (Panthera onca) and pumas (Puma concolor), were correlated solely with trail variables, while photo captures of their potential prey species had no correlation or negative correlation with trail variables. The Neotropical mammals varied greatly in their tendency to follow or cross trails based on footprints surveys. This indicates that camera locations on trails will have varying detection probability for these Neotropical mammals. Even the two similar-sized jaguars and pumas, occupying relatively similar niches, differed subtly in their use of trails. Pumas followed trails more completely while jaguars were more likely to deviate from trails. The ecological significance of these findings is that jaguars seem to be more willing to use the forest matrix away from trails than do pumas. We conclude that trail-based indices, such as photographic captures or tracks along trails, are not appropriate for comparison between Neotropical species, and not even between relatively similar species like jaguars and pumas. [source] A spatial model of bird abundance as adjusted for detection probabilityECOGRAPHY, Issue 2 2009P. Marcos Gorresen Modeling the spatial distribution of animals can be complicated by spatial and temporal effects (i.e. spatial autocorrelation and trends in abundance over time) and other factors such as imperfect detection probabilities and observation-related nuisance variables. Recent advances in modeling have demonstrated various approaches that handle most of these factors but which require a degree of sampling effort (e.g. replication) not available to many field studies. We present a two-step approach that addresses these challenges to spatially model species abundance. Habitat, spatial and temporal variables were handled with a Bayesian approach which facilitated modeling hierarchically structured data. Predicted abundance was subsequently adjusted to account for imperfect detection and the area effectively sampled for each species. We provide examples of our modeling approach for two endemic Hawaiian nectarivorous honeycreepers: ,i,iwi Vestiaria coccinea and ,apapane Himatione sanguinea. [source] On the estimation of species richness based on the accumulation of previously unrecorded speciesECOGRAPHY, Issue 1 2002Emmanuelle Cam Estimation of species richness of local communities has become an important topic in community ecology and monitoring. Investigators can seldom enumerate all the species present in the area of interest during sampling sessions. If the location of interest is sampled repeatedly within a short time period, the number of new species recorded is typically largest in the initial sample and decreases as sampling proceeds, but new species may be detected if sampling sessions are added. The question is how to estimate the total number of species. The data collected by sampling the area of interest repeatedly can be used to build species accumulation curves: the cumulative number of species recorded as a function of the number of sampling sessions (which we refer to as "species accumulation data"). A classic approach used to compute total species richness is to fit curves to the data on species accumulation with sampling effort. This approach does not rest on direct estimation of the probability of detecting species during sampling sessions and has no underlying basis regarding the sampling process that gave rise to the data. Here we recommend a probabilistic, nonparametric estimator for species richness for use with species accumulation data. We use estimators of population size that were developed for capture-recapture data, but that can be used to estimate the size of species assemblages using species accumulation data. Models of detection probability account for the underlying sampling process. They permit variation in detection probability among species. We illustrate this approach using data from the North American Breeding Bird Survey (BBS). We describe other situations where species accumulation data are collected under different designs (e.g., over longer periods of time, or over spatial replicates) and that lend themselves to of use capture-recapture models for estimating the size of the community of interest. We discuss the assumptions and interpretations corresponding to each situation. [source] Large scale wildlife monitoring studies: statistical methods for design and analysisENVIRONMETRICS, Issue 2 2002Kenneth H. Pollock Abstract Techniques for estimation of absolute abundance of wildlife populations have received a lot of attention in recent years. The statistical research has been focused on intensive small-scale studies. Recently, however, wildlife biologists have desired to study populations of animals at very large scales for monitoring purposes. Population indices are widely used in these extensive monitoring programs because they are inexpensive compared to estimates of absolute abundance. A crucial underlying assumption is that the population index (C) is directly proportional to the population density (D). The proportionality constant, ,, is simply the probability of ,detection' for animals in the survey. As spatial and temporal comparisons of indices are crucial, it is necessary to also assume that the probability of detection is constant over space and time. Biologists intuitively recognize this when they design rigid protocols for the studies where the indices are collected. Unfortunately, however, in many field studies the assumption is clearly invalid. We believe that the estimation of detection probability should be built into the monitoring design through a double sampling approach. A large sample of points provides an abundance index, and a smaller sub-sample of the same points is used to estimate detection probability. There is an important need for statistical research on the design and analysis of these complex studies. Some basic concepts based on actual avian, amphibian, and fish monitoring studies are presented in this article. Copyright © 2002 John Wiley & Sons, Ltd. [source] On the importance of estimating detection probabilities from at-sea surveys of flying seabirdsJOURNAL OF AVIAN BIOLOGY, Issue 6 2009Christophe Barbraud The primary and accepted method used to estimate seabird densities at sea from ships is the strip transect method, designed to correct for the effect of random directional bird movement relative to that of the ship. However, this method relies on the critical assumption that all of the birds within the survey strip are detected. We used the distance sampling method from line-transects to estimate detection probability of a number of species of flying seabirds, and to test whether distance from the ship and bird body size affected detectability. Detection probability decreased from 0.987 (SE=0.029) to 0.269 (SE=0.035) with increasing strip half-width from 100 to 1400,m. Detection probability also varied between size-groups of species with strip half-width. For all size-groups, this probability was close to 1 for strip half-width of 100,m, but was 0.869 (SE=0.115), 0.725 (SE=0.096) and 0.693 (SE=0.091) for strip half-width of 300,m, a typical strip width used in seabird surveys, for respectively large, medium and small size flying seabirds. For larger strip half-width, detection probability was higher for large sized species, intermediate for medium sized species and lower for smaller sized species. For strip half-width larger than 100,m we suggest that more attention should be paid to testing the assumption of perfect detectability, because abundance estimates may be underestimated when this assumption is violated. Finally, the effect of the speed of travel of flying seabird on the detection probability was estimated in a simulation study, which suggests that detection probability was underestimated with increasing flying speed. [source] How biased are estimates of extinction probability in revisitation studies?JOURNAL OF ECOLOGY, Issue 5 2006MARC KÉRY Summary 1Extinction is a fundamental topic for population ecology and especially for conservation and metapopulation biology. Most empirical studies on extinction resurvey historically occupied sites and estimate extinction probability as the proportion of sites where a species is no longer detected. Possible non-detection of surviving populations is usually not accounted for, which may result in extinction probabilities that are overestimated. 2As part of a large revisitation study in north-east Switzerland, 376 sites with historically known occurrences of a total of 11 plant species 80,100 years ago were visited by two independent observers. Based on typical population size, ramet size and plant architecture, we judged six species as easy to find and five species as hard to find. Using capture,recapture methods to separate non-detection from true extinction, we gauged the bias of extinction probability estimates that do not account for non-detection. 3When non-detection was not accounted for, a single visit resulted in an average estimate of population extinction probability of 0.49 (range 0.27,0.67). However, the mean detection probability of a surviving population during a single visit had an estimated average of only 0.81 (range 0.57,1). Consequently, accounting for non-detection resulted in extinction probability estimates ranging between 0.09 and 0.61 (mean 0.36). Based on a single survey, our revisitation study would have overestimated the extinction rate on average by 11 percentage points (range 5,22%) or by 59% (range 0,250%) relative to the estimated true value. 4A simple binomial argument enables the calculation of the minimum required number of visits to detect a surviving population with high probability (e.g. 95%). For the easy to find species, approximately two visits would be required to find most of the surviving populations, whereas up to four visits would be required for the hard to find species. 5In revisitation studies, only repeated revisits allow the separation of extinction from simple non-detection. Unless corrected for possible non-detection, extinction probability may be strongly overestimated, and hence some control for non-detection is desirable at least in a subset of species/sites in revisitation studies. These issues are also relevant to the estimation of extinction in metapopulation studies and to the collection of quality data for habitat and distribution models. [source] Estimating species' absence, colonization and local extinction in patchy landscapes: an application of occupancy models with rodentsJOURNAL OF ZOOLOGY, Issue 3 2007A. Mortelliti Abstract Making an inference on the absence of a species in a site is often problematic, due to detection probability being, in most cases, <1. Inference is more complicated if detection probability, together with distribution patterns, vary during the year, since the possibility of inferring a species absence, at reasonable costs, may be possible only in certain periods. Our aim here is to show how such challenging situations can be by tackled by applying some recently developed occupancy models combined with sample size (number of repeated surveys) estimation. We thus analysed the distribution of two rodents Myodes glareolus and Mus musculus domesticus in a fragmented landscape in central Italy pointing out how it is possible to identify true absences, non-detections, extinctions/colonizations and determine seasonal values of detection probability. [source] A trend filtering algorithm for wide-field variability surveysMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 2 2005Géza Kovács ABSTRACT We show that various systematics related to certain instrumental effects and data reduction anomalies in wide-field variability surveys can be efficiently corrected by a trend filtering algorithm (TFA) applied to the photometric time-series produced by standard data pipelines. Statistical tests, performed on the data base of the HAT Network project, show that by the application of this filtering method the cumulative detection probability of periodic transits increases by up to 0.4 for variables brighter than 11 mag, with a trend of increasing efficiency toward brighter magnitudes. We also show that the TFA can be used for the reconstruction of periodic signals by iteratively filtering out systematic distortions. [source] Discrete search allocation game with false contactsNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 1 2007Ryusuke Hohzaki Abstract This paper deals with a two-person zero-sum game called a search allocation game, where a searcher and a target participate, taking account of false contacts. The searcher distributes his search effort in a search space in order to detect the target. On the other hand, the target moves to avoid the searcher. As a payoff of the game, we take the cumulative amount of search effort weighted by the target distribution, which can be derived as an approximation of the detection probability of the target. The searcher's strategy is a plan of distributing search effort and the target's is a movement represented by a path or transition probability across the search space. In the search, there are false contacts caused by environmental noises, signal processing noises, or real objects resembling true targets. If they happen, the searcher must take some time for their investigation, which interrupts the search for a while. There have been few researches dealing with search games with false contacts. In this paper, we formulate the game into a mathematical programming problem to obtain its equilibrium point. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007 [source] Hiding role assignment in mission-critical collaborative systemsQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 3 2002Xinwen Fu Abstract In a mission critical collaboration system, a group of roles are assigned to computer nodes connected by a communication network. Role assignment is mission-critical information and needs to be protected. In this paper, we develop methods to effectively and efficiently protect the information of role assignment from traffic analysis, a passive attack. To measure the system security, we introduce a metric of detection probability, defined as the probability that a role assignment can be discovered. A heuristic greedy algorithm is given to minimize the resource consumption while guaranteeing a low detection-probability level. Our performance evaluation shows that the algorithm proposed in this paper performs well in terms of execution time and resource usage compared to an exhaustive search algorithm. We also propose to use additional means (e.g. additional nodes) to further increase the security level of a system at the cost of a mild resource consumption increase. Copyright © 2002 John Wiley & Sons, Ltd. [source] Multimodal signaling in wild Lemur catta: Economic design and territorial function of urine markingAMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY, Issue 2 2009Elisabetta Palagi Abstract Urine marking has been neglected in prosimian primates. Captive studies showed that the Malagasy prosimian Lemur catta scent marks with urine, as well as via specialized depositions. L. catta urine mark, a multimodal signal, differs from simple urination in terms of different design features, including tail configuration: the tail is held up during marking (UT-up) and down during urination (UT-down). We explore economy and function of UT-up in the female dominant L. catta. We collected 240 h of observations on one group at Berenty (south Madagascar) during the nonmating period via all occurrences sampling. We gathered behavioral bouts/contexts (marking, traveling, feeding, resting, and fights) and recorded 191 UT-ups and 79 UT-downs. Via Global Positioning System we established the location of the places frequented i) by extragroup individuals and ii) by group members, in this case recording also behavioral context and time spent in each place. We found that L. catta UT-up is not an artifact of captivity. Moreover, UT-up in the nonmating period plays a role in territorial defense, which is mostly performed by females in L. catta society. Female UT-ups were the most investigated and UT-ups were performed/investigated more by females. Finally, signal use is parsimonious, in that urine is economically placed where and when detection probability by competitors is higher. UT-ups were performed in places most frequented by extragroup individuals and in presence of extragroup competitors (nonrandom topography and timing). In conclusion, we suggest that UT-up is an economical signal with a primarily territorial function. Am J Phys Anthropol, 2009. © 2008 Wiley-Liss, Inc. [source] Estimates of population size of white-chinned petrels and grey petrels at Kerguelen Islands and sensitivity to fisheriesANIMAL CONSERVATION, Issue 3 2009C. Barbraud Abstract White-chinned petrels Procellaria aequinoctialis and grey petrels Procellaria cinerea are among the most frequently killed seabird species by accidental bycatch, and both species have received strong conservation concern. Data on population size are required to evaluate the impact of bycatch and to establish management plans. We estimated the population size of both species at Kerguelen, Southern Indian Ocean, from 2004 to 2006 by explicitly taking into account detection probability of burrows using distance sampling and burrow occupancy. A total of 31 line-transects were distributed across the eastern part of Kerguelen, representing a total length of 566 km. Detectability was low (from 0.19 to 0.54 for white-chinned petrels, 0.58 for grey petrels). Burrow densities varied from 1.37±0.67 to 25.77±5.23 burrows ha,1 for white-chinned petrels and was 2.78±0.79 burrows ha,1 for grey petrels. For white-chinned petrels, these densities were extrapolated to the entire surface area of vegetation and there were 234 000 (186 000,297 000) active burrows on Kerguelen. For grey petrels, the number of active burrows for the eastern part of Kerguelen was 3400 (1900,5600). Based on these estimates, the potential biological removal method suggests that the additional mortality on birds caused by the fisheries operating around Kerguelen can be considered a serious threat for the species at least at the regional scale of the Southern Indian Ocean, especially for grey petrels. [source] Few beetle species can be detected with 95% confidence using pitfall trapsAUSTRAL ECOLOGY, Issue 1 2010DON A. DRISCOLL Abstract False absences in wildlife surveys make it difficult to identify metapopulation processes, increase uncertainty of management decisions and bias parameter estimates in habitat models. Despite these risks, the number of species that can be detected with a certain probability in a community survey has rarely been examined. I sampled beetles over 5 months using pitfall trap grids at three rainforest locations in Tasmania, Australia. I compared detection probability for dispersed and clustered sampling schemes using a zero-inflated binomial model and a simpler occurrence method to calculate the probability of detection. After excluding extremely rare species, I analysed 12 of 121 species. Only three to six species could be detected with 95% probability using a sampling effort that is frequently applied in ecological studies. A majority of common species had a mid summer peak in detection probability meaning that survey effort could be reduced from 5 to 2 months with only a small reduction in data quality. Most species occurred at only a proportion of sample points within locations. Despite the implied spatial structuring, three small grids within a location detected 10 of 12 species as effectively as large, dispersed grids. This study warns that as little as 5% of the beetle fauna may have a 95% probability of detection using the frequently applied pitfall trap method, highlighting a substantial limitation in our ability to accurately map the distributions of ground invertebrates. Whether very large sample sizes can overcome this limitation remains to be examined. [source] Double-Observer Line Transect Methods: Levels of IndependenceBIOMETRICS, Issue 1 2010Stephen T. Buckland Summary Double-observer line transect methods are becoming increasingly widespread, especially for the estimation of marine mammal abundance from aerial and shipboard surveys when detection of animals on the line is uncertain. The resulting data supplement conventional distance sampling data with two-sample mark,recapture data. Like conventional mark,recapture data, these have inherent problems for estimating abundance in the presence of heterogeneity. Unlike conventional mark,recapture methods, line transect methods use knowledge of the distribution of a covariate, which affects detection probability (namely, distance from the transect line) in inference. This knowledge can be used to diagnose unmodeled heterogeneity in the mark,recapture component of the data. By modeling the covariance in detection probabilities with distance, we show how the estimation problem can be formulated in terms of different levels of independence. At one extreme, full independence is assumed, as in the Petersen estimator (which does not use distance data); at the other extreme, independence only occurs in the limit as detection probability tends to one. Between the two extremes, there is a range of models, including those currently in common use, which have intermediate levels of independence. We show how this framework can be used to provide more reliable analysis of double-observer line transect data. We test the methods by simulation, and by analysis of a dataset for which true abundance is known. We illustrate the approach through analysis of minke whale sightings data from the North Sea and adjacent waters. [source] Analysis of Capture,Recapture Models with Individual Covariates Using Data AugmentationBIOMETRICS, Issue 1 2009J. Andrew Royle Summary I consider the analysis of capture,recapture models with individual covariates that influence detection probability. Bayesian analysis of the joint likelihood is carried out using a flexible data augmentation scheme that facilitates analysis by Markov chain Monte Carlo methods, and a simple and straightforward implementation in freely available software. This approach is applied to a study of meadow voles (Microtus pennsylvanicus) in which auxiliary data on a continuous covariate (body mass) are recorded, and it is thought that detection probability is related to body mass. In a second example, the model is applied to an aerial waterfowl survey in which a double-observer protocol is used. The fundamental unit of observation is the cluster of individual birds, and the size of the cluster (a discrete covariate) is used as a covariate on detection probability. [source] Site Occupancy Models with Heterogeneous Detection ProbabilitiesBIOMETRICS, Issue 1 2006J. Andrew Royle Summary Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these "site occupancy" models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link (2003, Biometrics59, 1123,1130) demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs. [source] Differential Use of Trails by Forest Mammals and the Implications for Camera-Trap Studies: A Case Study from BelizeBIOTROPICA, Issue 1 2010Bart J. Harmsen ABSTRACT Relative abundance indices are often used to compare species abundance between sites. The indices assume that species have similar detection probabilities, or that differences between detection probabilities are known and can be corrected for. Indices often consist of encounter frequencies of footprints, burrows, markings or photo captures along trails or transect lines, but the assumption of equal detection probabilities is rarely validated. This study analyzes detection probabilities of a range of Neotropical mammals on trails in dense secondary forests, using camera-trap and track data. Photo captures of the two large cats, jaguars (Panthera onca) and pumas (Puma concolor), were correlated solely with trail variables, while photo captures of their potential prey species had no correlation or negative correlation with trail variables. The Neotropical mammals varied greatly in their tendency to follow or cross trails based on footprints surveys. This indicates that camera locations on trails will have varying detection probability for these Neotropical mammals. Even the two similar-sized jaguars and pumas, occupying relatively similar niches, differed subtly in their use of trails. Pumas followed trails more completely while jaguars were more likely to deviate from trails. The ecological significance of these findings is that jaguars seem to be more willing to use the forest matrix away from trails than do pumas. We conclude that trail-based indices, such as photographic captures or tracks along trails, are not appropriate for comparison between Neotropical species, and not even between relatively similar species like jaguars and pumas. [source] | ||||||||||||||||