Estimation of aboveground herbaceous biomass using visually ranked digital photographs

Methods for estimating aboveground herbaceous biomass in the field have generally involved calibrating visual estimates against clipped, dried and weighed biomass samples, requiring lengthy periods of estimation and destructive sampling in the field. Here we developed and tested a photographic estimation technique (PET) that minimises field time and provides accurate estimates of aboveground herbaceous biomass. Photographs of the biomass to be estimated taken in the field are ranked against calibration images of known biomass in the laboratory. The study was conducted in New South Wales, Australia, in grassy forest dells and grasslands at Booroolong Nature Reserve in the temperate New England Tablelands Bioregion and in semi-arid grassy shrubland on Naree Station in the arid Mulga Lands Bioregion. Photographs of quadrats containing the herbaceous biomass to be estimated were taken in successive years at both sites. Calibration and validation quadrats were also photographed, and the vegetation clipped, bagged, dried and weighed. The calibration and validation photographs were rank-ordered independently by three observers in terms of estimated dry weight, and the validation quadrats assigned a putative dry weight by reference to the known weights of the calibration images in the rank order. The accuracy of each observer’s estimates was assessed by regressing the estimated weight of each validation quadrat against the actual weight, which was withheld from the observer during the estimation procedure. Regression analysis of visually estimated weights on actual weights of validation quadrats yielded regression coefficients (R2) of 0.80–0.98 and 0.81–0.97 in the temperate-zone and arid-zone sites, respectively. PET was reliably used to visually estimate aboveground herbaceous biomass across a range of communities in two different climatic zones. The benefits of PET include reduced field time, minimisation of destructive sampling and avoidance of observer drift in estimating biomass in the field.