3D imaging as a method of measuring serotiny

Abstract

BackgroundSerotiny, or pyriscence, refers to delayed seed dissemination within plants and plays an important role in the population dynamics of species following fire. Accurately understanding the variation in serotiny is crucial to predicting ecosystem responses to changing fire regimes. Three-dimensional (3D) cone surface area is one critical trait that can be used to characterize responses in serotinous species following fire, yet approaches to accurately measure cone surface area are limited. Cone surface area in regards to this paper is the total area of all surfaces of the cone. Past studies have relied on visual estimation to determine the openness of cones or to identify when cones become open. Subjective assessments of cone opening may be insufficient to adequately characterize cone responses to fire. In this study, I demonstrate the effectiveness of 3D modeling using a readily available phone camera and applications (Polycam, Blender) to quantify differences in 3D surface area of cones before and after heating treatments by comparing two serotinous conifer species, Monterey cypress (Hesperocyparis macrocarpa) and bishop pine (Pinus muricata).ResultsBishop pine had an average cone surface area increase of 175.7% while Monterey cypress had an average cone surface area increase of 43.5%. Paired t-tests showed that cone surface area significantly increased following heating for both species.ConclusionsBishop pine showed a much greater cone surface area change relative to Monterey cypress. 3D imaging with the phone application, Polycam, proved to be a successful method of quantifying cone opening, creating a mesh that could be measured with the post-image processing software, Blender. A mesh can be defined as a digital 3D representation of an object made up of connected vertices that create edges and faces. Using a readily available phone camera, one can create an accurate 3D model to measure changes in the surface area of cones before and after fire. Simple methods for quantifying serotiny, such as demonstrated here, allow for improved understanding and predictions of how species respond to fire and other environmental triggers but require further investigation including, but not limited to, comparisons between serotinous species, facultative serotinous species, and non-serotinous species.