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  1. ; ; ; ; ; ; ; ; ; ; et al ( , Mammalian Biology)
    Parallel-laser photogrammetry is growing in popularity as a way to collect non-invasive body size data from wild mammals. Despite its many appeals, this method requires researchers to hand-measure (i) the pixel distance between the parallel laser spots (inter-laser distance) to produce a scale within the image, and (ii) the pixel distance between the study subject’s body landmarks (inter-landmark distance). This manual effort is time-consuming and introduces human error: a researcher measuring the same image twice will rarely return the same values both times (resulting in within-observer error), as is also the case when two researchers measure the same image (resulting in between-observer error). Here, we present two independent methods that automate the inter-laser distance measurement of parallel-laser photogrammetry images. One method uses machine learning and image processing techniques in Python, and the other uses image processing techniques in ImageJ. Both of these methods reduce labor and increase precision without sacrificing accuracy. We first introduce the workflow of the two methods. Then, using two parallel-laser datasets of wild mountain gorilla and wild savannah baboon images, we validate the precision of these two automated methods relative to manual measurements and to each other. We also estimate the reduction of variation in final body size estimates in centimeters when adopting these automated methods, as these methods have no human error. Finally, we highlight the strengths of each method, suggest best practices for adopting either of them, and propose future directions for the automation of parallel-laser photogrammetry data. 
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  2. ; ; ; ; ; ; ; ( , American Journal of Primatology)
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  3. ; ; ; ; ; ; ; ( , American Journal of Physical Anthropology)
    Objectives

    Ecological factors, but also tooth‐to‐tooth contact over time, have a dramatic effect on tooth wear in primates. The aim of this study is to test whether incisor tooth wear changes predictably with age and can thus be used as an age estimation method in a wild population of mountain gorillas (Gorilla beringei beringei) from Volcanoes National Park, Rwanda.

     Materials and methods

    In mountain gorillas of confidently known chronological age (N = 24), we measured the crown height of all permanent maxillary and mandibular incisors (I1, I1, I2, I2) as a proxy for incisal macrowear. Linear and quadratic regressions for each incisor were used to test whether age can be predicted by crown height. Using these models, we then predicted age at death of two individual mountain gorillas of probable identifications, based on their incisor crown height.

     Results

    Age decreased significantly with incisor height for all teeth, but the upper first incisors (I1) provided the best results, with the lowest Akaike's Information Criterion corrected for small sample size (AICc) and lowest Standard Error of the Estimate (SEE). When the best age equations for each sex were applied to gorillas with probable identifications, the predicted ages differed 1.58 and 3.33 years from the probable ages of these individuals.

     Conclusions

    Our findings corroborate that incisor crown height, a proxy for incisal wear, varies predictably with age. This relationship can be used to estimate age at death of unknown gorillas in the skeletal collection, and in some cases, to corroborate the identity of individual gorillas recovered from the forest postmortem at an advanced state of decomposition. Such identifications help fill gaps in the demographic database and support research that requires individual‐level data.

     
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  4. ; ; ; ; ; ; ; ( , American Journal of Physical Anthropology)