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      Design patterns for wildlife‐related camera trap image analysis

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          Abstract

          This paper describes and explains design patterns for software that supports how analysts can efficiently inspect and classify camera trap images for wildlife‐related ecological attributes. Broadly speaking, a design pattern identifies a commonly occurring problem and a general reusable design approach to solve that problem. A developer can then use that design approach to create a specific software solution appropriate to the particular situation under consideration. In particular, design patterns for camera trap image analysis by wildlife biologists address solutions to commonly occurring problems they face while inspecting a large number of images and entering ecological data describing image attributes. We developed design patterns for image classification based on our understanding of biologists' needs that we acquired over 8 years during development and application of the freely available Timelapse image analysis system. For each design pattern presented, we describe the problem, a design approach that solves that problem, and a concrete example of how Timelapse addresses the design pattern. Our design patterns offer both general and specific solutions related to: maintaining data consistency, efficiencies in image inspection, methods for navigating between images, efficiencies in data entry including highly repetitious data entry, and sorting and filtering image into sequences, episodes, and subsets. These design patterns can inform the design of other camera trap systems and can help biologists assess how competing software products address their project‐specific needs along with determining an efficient workflow.

          Abstract

          We describe design patterns for software that supports how ecologists can efficiently inspect and classify camera trap images for wildlife‐related ecological attributes. Each design pattern addresses a problem and possible solutions to common issues faced by ecologists when inspecting and entering tagging data for a massive number of images. These design patterns inform the design of other camera trap analysis systems, and help biologists assess how competing software products address their project‐specific needs.

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          Most cited references33

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          REVIEW: Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes

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            Assessing tiger population dynamics using photographic capture-recapture sampling.

            Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, "robust design" capture-recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of gamma" = gamma' = 0.10 +/- 0.069 (values are estimated mean +/- SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 +/- 0.051, and the estimated probability that a newly caught animal was a transient was tau = 0.18 +/- 0.11. During the period when the sampled area was of constant size, the estimated population size N(t) varied from 17 +/- 1.7 to 31 +/- 2.1 tigers, with a geometric mean rate of annual population change estimated as lambda = 1.03 +/- 0.020, representing a 3% annual increase. The estimated recruitment of new animals, B(t), varied from 0 +/- 3.0 to 14 +/- 2.9 tigers. Population density estimates, D, ranged from 7.33 +/- 0.8 tigers/100 km2 to 21.73 +/- 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.
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              Scaling-up camera traps: monitoring the planet's biodiversity with networks of remote sensors

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                Author and article information

                Contributors
                saul@ucalgary.ca
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                02 December 2019
                December 2019
                : 9
                : 24 ( doiID: 10.1002/ece3.v9.24 )
                : 13706-13730
                Affiliations
                [ 1 ] Department of Computer Science University of Calgary Calgary AB Canada
                [ 2 ] Freshwater Fisheries Society of BC Research Evaluation & Development Section University of British Columbia Vancouver BC Canada
                [ 3 ] Parks Canada, Banff National Park Banff AB Canada
                Author notes
                [*] [* ] Correspondence

                Saul Greenberg, Department of Computer Science, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada.

                Email: saul@ 123456ucalgary.ca

                Author information
                https://orcid.org/0000-0003-0174-9665
                Article
                ECE35767
                10.1002/ece3.5767
                6953665
                31938476
                0fe46407-9f82-41f4-b912-eabad1845353
                © 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 June 2019
                : 15 August 2019
                : 30 August 2019
                Page count
                Figures: 19, Tables: 0, Pages: 24, Words: 16131
                Funding
                Funded by: National Science and Engineering Research Council of Canada
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                December 2019
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.4 mode:remove_FC converted:10.01.2020

                Evolutionary Biology
                camera traps,data encoding and acquisition,design patterns,experience design,human–computer interaction,image inspection,tagging,wildlife monitoring

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