scholarly journals Estimating population parameters of broadnose sevengill sharks ( Notorynchus cepedianus ) using photo identification capture‐recapture

2020 ◽  
Vol 97 (4) ◽  
pp. 987-995
Author(s):  
Robert Lewis ◽  
Steve Dawson ◽  
William Rayment
Keyword(s):  
Population Parameters ◽  
Photo Identification ◽  
Capture Recapture

scholarly journals Abundance, survival and temporary emigration of bottlenose dolphins (Tursiops sp.) off Useless Loop in the western gulf of Shark Bay, Western Australia

2012 ◽  
Vol 63 (11) ◽  
pp. 1059 ◽  
Author(s):  
Krista Nicholson ◽  
Lars Bejder ◽  
Simon J. Allen ◽  
Michael Krützen ◽  
Kenneth H. Pollock
Keyword(s):  
Western Australia ◽  
Bottlenose Dolphins ◽  
Early Spring ◽  
Anthropogenic Activity ◽  
Apparent Survival ◽  
Photo Identification ◽  
Temporary Emigration ◽  
Shark Bay ◽  
Abundance Estimates ◽  
Capture Recapture

Capture–recapture models were used to provide estimates of abundance, apparent survival and temporary emigration of Indo-Pacific bottlenose dolphins (Tursiops sp.) in a 226-km2 study area off Useless Loop in the western gulf of Shark Bay, Western Australia. Photo-identification data were collected during boat-based surveys in Austral autumn to early spring (April–September) from 2007 to 2011. Abundance estimates varied from 115 (s.e. 5.2, 95% CI 105–126) individuals in 2008 to 208 (s.e. 17.3, 95% CI 177–245) individuals in 2010. The variability in abundance estimates is likely to be a reflection of how individuals used the study area, rather than fluctuations in true population size. The best fitting capture–recapture model suggested a random temporary emigration pattern and, when coupled with relatively high temporary emigration rates (0.33 (s.e. 0.07) – 0.66 (s.e. 0.05)) indicated that the study area did not cover the entire ranges of the photo-identified dolphins. Apparent survival rate is a product of true survival and permanent emigration and was estimated annually at 0.95 (s.e. 0.02). Since permanent emigration from the study area is unlikely, true survival was estimated to be close to 0.95. This study provides a robust baseline for future comparisons of dolphin demographics, which may be of importance should climate change or increasing anthropogenic activity affect this population.

scholarly journals Abundance and survival estimates of the southeastern Pacific humpback whale stock from 1991–2006 photo-identification surveys in Ecuador

2020 ◽  
pp. 301-307 ◽  
Author(s):  
Fernando Félix ◽  
Cristina Castro ◽  
Jeffrey L. Laake
Keyword(s):  
Annual Variation ◽  
Humpback Whales ◽  
Collaborative Effort ◽  
Transient Effect ◽  
Photo Identification ◽  
Migration Timing ◽  
Open Population ◽  
Southeastern Pacific ◽  
Capture Recapture ◽  
Wintering Areas

Southeastern Pacific humpback whales (Breeding Stock G) breed along the northwestern coast of South America and farther north up to CostaRica. Photo-identification surveys conducted aboard whalewatching vessels during the migration/breeding season from June to September between1991 and 2006 off the coast of Ecuador (2°S, 81°W) have produced a database of 1,511 individual whales. Comparisons of photographs produced190 between-year re-sightings of 155 individual whales. Closed and open capture-recapture models were used to estimate abundance and survival.The best estimate of abundance in 2006 with the Chapman modified-Petersen was 6,504 (95% CI: 4,270–9,907; CV = 0.21). Abundance estimatesfrom open population models were considerably lower due to heterogeneity in capture probability which produced a ‘transient’ effect. Our bestestimate of true survival was 0.919 (95% CI: 0.850–0.958). Heterogeneity most likely occurred from inter-annual variation in sampling and unknownstructure and variation in the migration timing and corridor. A more extensive collaborative effort including other wintering areas further north aswell as integrating breeding-feeding data will help to reduce heterogeneity and increase precision in abundance and survival estimates.

Survival of Alytes cisternasii tadpoles in stream pools: a capture-recapture study using photo-identification

2011 ◽  
Vol 32 (3) ◽  
pp. 365-374 ◽  
Author(s):  
Joana Ribeiro ◽  
Rui Rebelo
Keyword(s):  
Survival Rates ◽  
Larval Survival ◽  
Life Cycles ◽  
Life History Stage ◽  
High Survival ◽  
Amphibian Population ◽  
Photo Identification ◽  
Temporary Stream ◽  
Capture Recapture ◽  
First Time

AbstractFor amphibians with complex life cycles, the regulation of populations may occur in each life history stage and although available data stress the importance of studying amphibian population dynamics during the larval stage, most studies so far still focus only on the adult phase, due to the difficulty to estimate larval survival under field conditions. Through a two-months capture-recapture study of 646 photo-identified tadpoles of Alytes cisternasii we aimed to estimate tadpole survival in isolated temporary stream pools – their main habitat – as well as to evaluate how pool characteristics and intraspecific competition (tadpole density) affect this parameter. Photo-identification was performed with the help of the software I3S. We used the POPAN formulation of the Jolly-Seber model to estimate survival rates and population size in 9 stream pools. Tadpole density varied from ∼1 to 40 tadpoles · m–2. Tadpole weekly survival was relatively high, varying from 75 to 99% · week–1. Among-pool differences in survival were best explained by pool depth, and not by tadpole density or other pool characteristics. The lower survival estimates were obtained for the deep pools. The very high survival estimates for some pools are an indication that this type of discrete habitat may play an important role for this species. To our knowledge, this is the first time that photo-identification is used to obtain estimates for survival and density of tadpoles.

scholarly journals Recommendations for photo-identification methods used in capture-recapture models with cetaceans

2014 ◽  
Vol 31 (1) ◽  
pp. 298-321 ◽  
Author(s):  
Kim Urian ◽  
Antoinette Gorgone ◽  
Andrew Read ◽  
Brian Balmer ◽  
Randall S. Wells ◽  
...  
Keyword(s):  
Identification Methods ◽  
Photo Identification ◽  
Capture Recapture

scholarly journals Revisiting giraffe photo-identification using deep learning and network analysis

2020 ◽  
Author(s):  
Vincent Miele ◽  
Gaspard Dussert ◽  
Bruno Spataro ◽  
Simon Chamaillé-Jammes ◽  
Dominique Allainé ◽  
...  
Keyword(s):  
Metric Learning ◽  
Simple Task ◽  
Photo Identification ◽  
Software Packages ◽  
Animal Populations ◽  
In The Wild ◽  
Capture Recapture ◽  
Deep Metric Learning ◽  
Similarity Networks ◽  
Do So

AbstractAn increasing number of research programs rely on photographic capture-recapture (vs. direct marking) of individuals to study distribution and demography within animal populations. Photo-identification of individuals living in the wild is sometimes feasible using idiosyncratic coat or skin patterns, like for giraffes. When performed manually, the task is tedious and becomes almost impossible as populations grow in size. Computer vision techniques are an appealing and unavoidable help to tackle this apparently simple task in the big-data era. In this context, we propose to revisit giraffe re-identification using convolutional neural networks (CNNs).We first developed an end-to-end pipeline to retrieve a comprehensive set of re-identified giraffes from about 4, 000 raw photographs. To do so, we combined CNN-based object detection, SIFT pattern matching, and image similarity networks. We then quantified the performance of deep metric learning to retrieve the identity of known and unknown individuals. The re-identification performance of CNNs reached a top 5 accuracy of about 90%. Fully based on open-source software packages, our work paves the way for further attempts to build CNN-based pipelines for re-identification of individual animals, in giraffes but also in other species.

scholarly journals Identifying individual cougars (Puma concolor) in remote camera images – implications for population estimates

2018 ◽  
Vol 45 (3) ◽  
pp. 274 ◽  
Author(s):  
Peter D. Alexander ◽  
Eric M. Gese
Keyword(s):  
Puma Concolor ◽  
Camera Traps ◽  
Camera Trapping ◽  
Field Methods ◽  
Density Estimates ◽  
North West ◽  
Photo Identification ◽  
Matching Process ◽  
Capture Recapture ◽  
Remote Camera

Context Several studies have estimated cougar (Puma concolor) abundance using remote camera trapping in conjunction with capture–mark–recapture (CMR) type analyses. However, this methodology (photo-CMR) requires that photo-captured individuals are individually recognisable (photo identification). Photo identification is generally achieved using naturally occurring marks (e.g. stripes or spots) that are unique to each individual. Cougars, however, are uniformly pelaged, and photo identification must be based on subtler attributes such as scars, ear nicks or body morphology. There is some debate as to whether these types of features are sufficient for photo-CMR, but there is little research directly evaluating its feasibility with cougars. Aim We aimed to examine researchers’ ability to reliably identify individual cougars in photographs taken from a camera-trapping survey, in order to evaluate the appropriateness of photo-CMR for estimating cougar abundance or CMR-derived parameters. Methods We collected cougar photo detections using a grid of 55 remote camera traps in north-west Wyoming, USA. The photo detections were distributed to professional biologists working in cougar research, who independently attempted to identify individuals in a pairwise matching process. We assessed the level to which their results agreed, using simple percentage agreement and Fleiss’s kappa. We also generated and compared spatially explicit capture–recapture (SECR) density estimates using their resultant detection histories. Key results There were no cases where participants were in full agreement on a cougar’s ID. Agreement in photo identification among participants was low (n = 7; simple agreement = 46.7%; Fleiss’s kappa = 0.183). The resultant SECR density estimates ranged from 0.7 to 13.5 cougars per 100 km2 (n = 4; s.d. = 6.11). Conclusion We were unable to produce reliable estimates of cougar density using photo-CMR, due to our inability to accurately photo-tag detected individuals. Abundance estimators that do not require complete photo-tagging (i.e. mark–resight) were also infeasible, given the lack of agreement on any single cougar’s ID. Implications This research suggested that there are substantial problems with the application of photo-CMR to estimate the size of cougar populations. Although improvements in camera technology or field methods may resolve these issues, researchers attempting to use this method on cougars should be cautious.

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