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Abstract As camera trapping has become a standard practice in wildlife ecology, developing techniques to extract additional information from images will increase the utility of generated data. Despite rapid advancements in camera trapping practices, methods for estimating animal size or distance from the camera using captured images have not been standardized. Deriving animal sizes directly from images creates opportunities to collect wildlife metrics such as growth rates or changes in body condition. Distances to animals may be used to quantify important aspects of sampling design such as the effective area sampled or distribution of animals in the camera's field‐of‐view.We present a method of using pixel measurements in an image to estimate animal size or distance from the camera using a conceptual model in photogrammetry known as the ‘pinhole camera model’. We evaluated the performance of this approach both using stationary three‐dimensional animal targets and in a field setting using live captive reindeerRangifer tarandusranging in size and distance from the camera.We found total mean relative error of estimated animal sizes or distances from the cameras in our simulation was −3.0% and 3.3% and in our field setting was −8.6% and 10.5%, respectively. In our simulation, mean relative error of size or distance estimates were not statistically different between image settings within camera models, between camera models or between the measured dimension used in calculations.We provide recommendations for applying the pinhole camera model in a wildlife camera trapping context. Our approach of using the pinhole camera model to estimate animal size or distance from the camera produced robust estimates using a single image while remaining easy to implement and generalizable to different camera trap models and installations, thus enhancing its utility for a variety of camera trap applications and expanding opportunities to use camera trap images in novel ways.
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Calibration of 2‐D soil zymography for correct analysis of enzyme distribution
Soil zymography is a new technique developed to visualize two‐dimensional distributions of enzyme activities. The method consists of incubating a membrane saturated with an enzyme‐specific fluorogenic substrate on a surface of the soil sample, followed by recording the membrane image generated by a fluorescent product (e.g. MUF: methylumbelliferone) in ultraviolet light. Despite its relative ease of use, performing zymography involves multiple user‐made decisions that might affect the accuracy of enzyme activity estimates. Therefore, unification of the zymography methodology is required for correct estimations and comparisons of various studies. We evaluated the following methodological aspects of the implementation of zymography: (a) camera settings and image processing, (b) effects of evaporation and (c) calibration procedures. Camera settings (shutter speeds or exposure time) affected the intensity of background fluorescence and signal‐to‐noise ratios (SNR). However, because their combined effects varied depending on MUF concentrations, light and camera setting need to be optimized for the expected range of MUF concentrations prior to zymography. Evaporation of MUF solution from the membrane had no effect on fluorescence. Relations between MUF concentration and intensity of fluorescence during calibrations demonstrated a saturated pattern and were strongly affected by image noise outside the optimal range (e.g. 8–14 μmMUF pixel−1). We developed a new calibration approach that is based on a piecewise linear regression. The new approach accounted for specific ranges of MUF concentration and uses nonuniformly saturated membranes, reflecting the real distribution of enzyme activities in soil. The new calibration algorithm eliminated biases of the standard calibration and resulted in greater accuracy in predicting MUF concentrations. HighlightsWe developed a new approach to calibration for 2‐D soil zymography.The approach accounted for spatial nonuniformity of soil zymograms.Standard calibration resulted in systematic underestimation of enzyme activity.Soil zymography requires pixel‐based calibration with nonuniformly saturated membranes.
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- PAR ID:
- 10459964
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- European Journal of Soil Science
- Volume:
- 70
- Issue:
- 4
- ISSN:
- 1351-0754
- Format(s):
- Medium: X Size: p. 715-726
- Size(s):
- p. 715-726
- Sponsoring Org:
- National Science Foundation
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