Allometric relationships for selected macrophytes of kettle holes in northeast Germany as a basis for efficient biomass estimation using unmanned aerial systems (UAS)

Marlene Pätzig,Frenze Geiger,Daniel Rasche,Philipp Rauneker,Anette Eltner

doi:10.1016/j.aquabot.2020.103202

Abstract

Quantifying plant biomass in ecosystems is an essential basis for many ecological questions. A direct estimation of macrophyte biomass proves to be difficult for the large number of kettle holes in Pleistocene landscapes, due to their strong heterogeneities. This study compared a classical non-destructive method for biomass estimation based on allometric relationships built from a larger selection of plant trait variables with regressions only based on plant height and cover of four macrophyte species typical for kettle holes in northeast Germany (i.e. Carex riparia, Phalaris arundinacea, Persicaria amphibia, Rorippa amphibia). Their predictive power and potential applicability for remotely sensed biomass estimation using unmanned aerial systems (UAS) was evaluated. The usage of several in-situ measured plant traits of individual plants revealed best macrophyte biomass predictions (R² = 0.84 to 0.95). Yet, using only plant height and cover to predict biomass still showed a moderate to good correlation (R² = 0.52 to 0.81). Using P. arundinacea as an example, we demonstrated for one kettle hole the potential of calculating plant patch height from digital surface models (DSM) derived from UAS RGB images processed with structure-from-motion (SfM) photogrammetry. After applying a site-specific correction factor for discrepancies between reference field measurements of plant heights and DSM derived plant heights, we were able to calculate P. arundinacea biomass of the entire kettle hole based on allometric relationships using plant height and cover. Finally, we briefly discuss how further methodological development can improve UAS-derived plant height as predictor variable for biomass estimation.

Highlights

Macrophytes are a key component for biodiversity and biogeochemical processes in natural ponds (Davies et al, 2008; Onandia et al, 2018)
The regression models established based on the phenometric method explained between 84 % for C. riparia and 95 % for R. amphibia of the variation in the aboveground plant biomass (Table 1, Fig. 3)
The predicted biomass differed marginally from the actual biomass, and the maximum average deviation was an underestimation of 2.44 % (R. amphibia) followed by P. arundinacea and C. riparia with an average deviation of 2.27 or 2.25 %, respectively

Summary

Introduction

Macrophytes are a key component for biodiversity and biogeochemical processes in natural ponds (Davies et al, 2008; Onandia et al, 2018). Biomass harvest is not always possible, especially in sensitive or highly heterogeneous habitats, as it can interfere with longterm surveys, disturb existing associations in macrophyte stands and might remove or harm protected species (Gouraud et al, 2008; Wood et al, 2012). Kettle holes represent such natural ponds with pronounced wet-and-dry cycles that cause a high abiotic and biotic heterogeneity in space and time (Kuczyńska-Kippen and Nagengast, 2006; Lischeid et al, 2018; Reverey et al, 2018). Highly variable abiotic and biotic properties between and within pond ecosystems (Kalettka and Rudat, 2006) lead to a lack of research regarding the application and development of efficient survey methods for pond macrophytes and their biomass

Objectives

Methods

Results