How Big Is It Really? Assessing the Efficacy of Indirect Estimates of Body Size in Asian Elephants

PLoS One. 2016 Mar 3;11(3):e0150533. doi: 10.1371/journal.pone.0150533. eCollection 2016.

Abstract

Information on an organism's body size is pivotal in understanding its life history and fitness, as well as helping inform conservation measures. However, for many species, particularly large-bodied wild animals, taking accurate body size measurements can be a challenge. Various means to estimate body size have been employed, from more direct methods such as using photogrammetry to obtain height or length measurements, to indirect prediction of weight using other body morphometrics or even the size of dung boli. It is often unclear how accurate these measures are because they cannot be compared to objective measures. Here, we investigate how well existing estimation equations predict the actual body weight of Asian elephants Elephas maximus, using body measurements (height, chest girth, length, foot circumference and neck circumference) taken directly from a large population of semi-captive animals in Myanmar (n = 404). We then define new and better fitting formulas to predict body weight in Myanmar elephants from these readily available measures. We also investigate whether the important parameters height and chest girth can be estimated from photographs (n = 151). Our results show considerable variation in the ability of existing estimation equations to predict weight, and that the equations proposed in this paper predict weight better in almost all circumstances. We also find that measurements from standardised photographs reflect body height and chest girth after applying minor adjustments. Our results have implications for size estimation of large wild animals in the field, as well as for management in captive settings.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Body Size*
  • Body Weight*
  • Elephants / anatomy & histology*
  • Elephants / physiology
  • Female
  • Male
  • Myanmar
  • Photography / statistics & numerical data
  • Regression Analysis

Grants and funding

VL received funding from the European Research Council and Leverhulme Trust for this study. HSM received a Natural Environmental Research Council PhD studentship, and post-doctoral funding from the Leverhulme Trust, Society in Science—Branco Weiss Fellowship and a Drapers' Company Junior Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.