scholarly journals A Bayesian approach to inferring dispersal kernels with incomplete mark-recapture data

2019 ◽  
Author(s):  
Akira Terui
Keyword(s):  
Food Webs ◽  
Bayesian Approach ◽  
Bayesian Model ◽  
Coupled Model ◽  
Ecological Process ◽  
Mark Recapture ◽  
In The Wild ◽  
Biased Estimates ◽  
Dispersal Kernels ◽  
Extract Information

AbstractDispersal is a fundamental ecological process that links populations, communities and food webs in space. However, dispersal is tremendously difficult to study in the wild because we must track individuals dispersing in a landscape. One conventional method to measure animal dispersal is a mark-recapture technique. Despite its usefulness, this approach has been recurrently criticized because it is virtually impossible to survey all possible ranges of dispersal in nature. Here, I propose a novel Bayesian model to better estimate dispersal parameters from incomplete mark-recapture data. The dispersal-observation coupled model, DOCM, can extract information from both recaptured and unrecaptured individuals, providing less biased estimates of dispersal parameters. Simulations demonstrated the usefulness of DOCM under various sampling designs. I also suggest extensions of the DOCM to accommodate more realistic scenarios. Application of the DOCM may, therefore, provide valuable insights into how individuals disperse in the wild.

scholarly journals Challenges and opportunities for monitoring wild Nile crocodiles with scute mark-recapture photography

Koedoe ◽  
2018 ◽  
Vol 60 (1) ◽  
Author(s):  
Bernard W.T. Coetzee ◽  
Sam M. Ferreira ◽  
Kristine Maciejewski
Keyword(s):  
Conservation Status ◽  
Field Conditions ◽  
High Turnover ◽  
Mark Recapture ◽  
Non Invasive ◽  
Open Population ◽  
Challenges And Opportunities ◽  
In Captivity ◽  
In The Wild

The global conservation status of Nile crocodiles (Crocodylus niloticus) was last assessed in 1996. The species presents particular difficulty in monitoring because it can be cryptic, require expertise to handle, and caudal tail tags and transmitters are often lost. Some studies advocate mark-recapture techniques based on photograph identification of the unique scute markings of crocodile tails as a non-invasive means of monitoring their populations. Researchers developed this method with crocodiles in captivity. In this study, we test the technique under field conditions by monitoring crocodiles from 2015 to 2017 in the Sunset Dam in the Kruger National Park. Using a Cormack-Jolly-Seber open population model, we found that the dam may host 15–30 individuals, but that there is a high turnover of individuals and much uncertainty in model outputs. The dam’s population thus has high rates of immigration and emigration. The method proved challenging under field conditions, as there was bias in identifying scute markings consistently. The efficient use of the method requires an exceptional quality of photographic equipment. Animal crypsis, however, remains an issue. In this study, we discuss how to improve the mark-recapture photography methodology, especially to adapt the technique for citizen science initiatives.Conservation implications: Using scute mark-recapture photography presents challenges under field conditions. These challenges require innovative, practical and analytical solutions to successfully use the technique before monitoring programmes, aimed at ensuring the persistence of crocodiles in the wild, can be implemented.

A Bayesian mark–recapture model for multiple-recapture data in a catch-and-release fishery

2009 ◽  
Vol 66 (9) ◽  
pp. 1554-1568 ◽  
Author(s):  
Rebecca Whitlock ◽  
Murdoch McAllister
Keyword(s):  
Model Evaluation ◽  
Bayesian Model ◽  
Evaluation Criteria ◽  
Strong Support ◽  
Fishing Effort ◽  
Length Class ◽  
Fraser River ◽  
Mark Recapture ◽  
Movement Rates ◽  
Seasonal Movement

This paper extends a state–space Bayesian mark–recapture framework to multiple-recapture data to estimate fishery-specific capture and mortality rates and seasonal movement rates for fish in different length classes. The methodology is applied to tag recapture data for white sturgeon ( Acipenser transmontanus ) collected in the recreational fishery and the Canadian Department of Fisheries and Ocean’s test fishery at Albion in the lower Fraser River. Significant differences were found between some estimated movement rates by season and length class, supporting the notion of there being marked differences in seasonal movement patterns between different life history stages of A. transmontanus in the lower Fraser River. Uncertainty in the tag reporting rate parameter, quantified using a recreational creel sampling program, is summarized by a prior distribution. The utility of recreational fishing effort as a model covariate in accounting for seasonal and spatial variation in recapture rates is addressed using Bayesian model evaluation criteria. The data provide strong support in favour of models that include fishing effort as a covariate. The appropriate level of stratification for the recreational catchability parameter q is assessed using Bayesian model evaluation criteria; models in which q is estimated by season and length class have the highest posterior probabilities.

scholarly journals A hierarchical Bayesian approach to multi-state mark-recapture: simulations and applications

2009 ◽  
Vol 46 (3) ◽  
pp. 610-620 ◽  
Author(s):  
Anna M. Calvert ◽  
Simon J. Bonner ◽  
Ian D. Jonsen ◽  
Joanna Mills Flemming ◽  
Sandra J. Walde ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Hierarchical Bayesian ◽  
Mark Recapture

Bayesian approach to incremental batch learning on forest cover sensor data for multiclass classification

2021 ◽  
pp. 1063293X2110584
Author(s):  
Venkata Vara Prasad D ◽  
Lokeswari Y Venkataramana ◽  
Saraswathi S ◽  
Sarah Mathew ◽  
Snigdha V
Keyword(s):  
Bayesian Approach ◽  
Incremental Learning ◽  
Bayesian Model ◽  
Forest Cover ◽  
Bayesian Framework ◽  
Training Data ◽  
Sensor Data ◽  
Learning Approaches ◽  
New Class ◽  
Multiple Levels

Deep neural networks can be used to perform nonlinear operations at multiple levels, such as a neural network that is composed of many hidden layers. Although deep learning approaches show good results, they have a drawback called catastrophic forgetting, which is a reduction in performance when a new class is added. Incremental learning is a learning method where existing knowledge should be retained even when new data is acquired. It involves learning with multiple batches of training data and the newer learning sessions do not require the data used in the previous iterations. The Bayesian approach to incremental learning uses the concept of the probability distribution of weights. The key idea of Bayes theorem is to find an updated distribution of weights and biases. In the Bayesian framework, the beliefs can be updated iteratively as the new data comes in. Bayesian framework allows to update the beliefs iteratively in real-time as data comes in. The Bayesian model for incremental learning showed an accuracy of 82%. The execution time for the Bayesian model was lesser on GPU (670 s) when compared to CPU (1165 s).

A Bayesian approach to finding groups in a food web

2013 ◽  
Vol 59 (1) ◽  
pp. 37-41
Author(s):  
Andrew R. Solow ◽  
Andrew R. Solow
Keyword(s):  
Food Web ◽  
Food Webs ◽  
Bayesian Approach ◽  
High Density ◽  
Low Density ◽  
Prior Distributions ◽  
New Approach ◽  
Coachella Valley

A food web describes the feeding links between species in a community. The species in many food webs are organized into groups of highly linked species that are weakly linked to species in other groups. A Bayesian approach to identifying such groups in an observed food web is described. This approach extends a previous non-Bayesian one that does not exploit information about the relatively high density of links within groups and relatively low density between groups. Under the new approach, this information is encoded through prior distributions for within- and between-group link densities. The approach is shown to work well on simulated food webs. Results are presented of the application of the method to the Coachella Valley desert food web.

On the Estimation of Dispersal Kernels from Individual Mark-Recapture Data

2006 ◽  
Vol 13 (2) ◽  
pp. 183-197 ◽  
Author(s):  
Masami Fujiwara ◽  
Kurt E. Anderson ◽  
Michael G. Neubert ◽  
Hal Caswell
Keyword(s):  
Mark Recapture ◽  
Dispersal Kernels

Bias and Loss of Precision Due to Tag Loss in Jolly–Seber Estimates for Mark–Recapture Experiments

1981 ◽  
Vol 38 (9) ◽  
pp. 1077-1095 ◽  
Author(s):  
A. N. Arnason ◽  
K. H. Mills
Keyword(s):  
Loss Rate ◽  
Full Model ◽  
Coregonus Clupeaformis ◽  
Lake Whitefish ◽  
Mark Recapture ◽  
Tag Retention ◽  
Tag Loss ◽  
Capture Recapture ◽  
Biased Estimates ◽  
Theoretical Analyses

A crucial, though often ignored, assumption of mark–recapture experiments is that animals do not lose their marks (tags). We present results of theoretical analyses of the effects of tag loss on estimates of population size ([Formula: see text]), survival ([Formula: see text]), births or new entries ([Formula: see text]), and on their standard errors (SE()), for the Jolly–Seber (full) model allowing birth and death. We show that[Formula: see text], SE([Formula: see text]) and SE([Formula: see text]) are not biased by tag loss, while [Formula: see text], [Formula: see text], and SE([Formula: see text]) are biased. A similar analysis for the Jolly–Seber (death-only) model where births are known not to occur shows that [Formula: see text], [Formula: see text], and SE([Formula: see text]) are strongly biased by tag loss while only SE([Formula: see text]) is unbiased. Moreover, for both models, tag loss causes a loss in precision in all estimates (i.e. an increase in the standard error of the estimate, leading to wider confidence intervals). Throughout the paper, we assume that tag loss is homogeneous among animals; that is, it is the same for all marked animals regardless of age, sex, or tag-retention time, although the rate per unit time may change over time (e.g. over years or seasons within years).We develop analytic formulae for both models that allow calculation of the expected bias and SE in an estimate at given tag loss rates in a population of given size, subject to specified sampling, survival, and birth rates. The analytic formulae are large sample approximations, but are shown, by simulations, to be adequate provided marked captures (mi) and subsequent recoveries (ri) are no lower than around 5.We discuss how these calculations can be used in practical situations to plan experiments that will yield adequately precise estimates and to determine whether corrections to compensate for tag loss are necessary. In general, corrections are unnecessary if bias is slight or precision is poor. Otherwise, they should be corrected. The biased estimates from the full model ([Formula: see text], SE([Formula: see text]), and [Formula: see text]) are correctable only if an estimate of tag-loss rate is available. The death-only model estimates can all be corrected to eliminate bias due to tag loss both with and without knowledge of the tag-loss, rate. Knowledge of the tag-loss rate will usually give higher precision of the corrected estimates over those corrected without knowing the tag-loss rate.The Robson–Regier method of estimating tag loss can be used in experiments with double tagging where one tag is a permanent batch mark and where all recaptured animals are removed. We extend this method to allow for the multiple mark–recapture case where recaptures may be returned to the population. An example of the methods of estimating tag loss and then correcting the death-only model estimates is presented for some lake whitefish (Coregonus clupeaformis) data. Without the corrections, the estimates for these data would have been in serious error. The example provides some evidence that the correction may work even when the tag loss is not homogeneous across all animals.Recommendations are presented for planning mark–recapture experiments to minimize the problems created by tag loss.Key words: marking methods, tag loss, bias of estimates, capture–recapture, Jolly–Seber estimates, population estimates, survival, mortality, lake whitefish

scholarly journals Three tick species parasitizing a rock python in Sri Lanka

2012 ◽  
Vol 4 (1) ◽  
pp. 54-56
Author(s):  
T.S.P. Fernando ◽  
H.K.A.V.A. Kulasena Fernando
Keyword(s):  
Immune Response ◽  
Population Dynamics ◽  
Sri Lanka ◽  
Food Webs ◽  
Tick Species ◽  
Ecosystem Health ◽  
Driving Forces ◽  
Host Parasite Interactions ◽  
In The Wild ◽  
Host Parasite

Parasitism is a relationship where one of the parties (the parasite) either harms its host or lives at the expense of it. Host parasite interactions are important driving forces in population dynamics and even extinction. These interactions are also indicators of ecosystem health and they are important in stabilizing food webs. A parasite may cause mechanical injury, stimulate a damaging inflammatory or immune response, or simply rob the host of nutrition. However in the wild most parasites must live in harmony with their hosts. If the parasites kill the host, they themselves would ultimately die without shelter and nutrition. Reptiles become hosts to a number of parasitic organisms ranging from protozoans to arthropods. Among these, ticks (hard and soft) are the most common arthropod group that parasitizes reptiles.

Fecundity, pouch young survivorship and breeding season of the northern bettong (Bettongia tropica) in the wild.

2001 ◽  
Vol 23 (2) ◽  
pp. 95 ◽  
Author(s):  
K Vernes ◽  
LC Pope
Keyword(s):  
Breeding Season ◽  
Wild Population ◽  
Reproductive Potential ◽  
Limited Data ◽  
Mark Recapture ◽  
Adult Females ◽  
In The Wild ◽  
Growth Equations

Reproduction in a wild population of northern bettongs (Bettongia tropica) was studied at Davies Creek in northeastern Queensland between November 1994 and February 1997. Using mark-recapture, we recorded 88 individual pouch young (PY) during the study (34 male, 45 female, 9 unknown sex). Using captive-derived growth equations we estimated that 90 % of PY survived to permanent emergence from the pouch (PEP). Birth of a new PY coincided with PEP of the previous young 78 % of the time; 12 % of births occurred within 2 - 8 weeks of PEP while the remaining 10 % probably died before PEP. 96 % of adult females carried PY at the time of capture. B. tropica bred continuously, with no significant differences in numbers of births recorded in different months. Few young that were marked in the pouch were captured as sub-adults, and none were captured as adults. Limited data on longevity indicated that B. tropica can live to at least 5 years. Our data suggest that B. tropica has a high reproductive potential; however, the fate of PY after PEP remains poorly known; and this may represent the period of greatest bettong mortality.

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