Comparing grass biomass estimation methods for management decisions in a semi‐arid landscape

Abstract

AbstractAimsEnvironmental managers require reliable and cost‐efficient monitoring methods for effective decision‐making. Understanding forage availability is important for managing wild, vertebrate herbivore populations. We developed a process for exploring the accuracy and cost efficiency of various biomass estimation techniques for a case study where semi‐arid woodland restoration is threatened by kangaroo grazing, with the aim of determining which method was most fit for purpose in a given decision context.LocationWyperfeld National Park, southeastern Australia.MethodsGrass biomass was estimated using a variety of methods, then compared to clipped biomass using linear models. Biomass estimation methods were either field‐based (i.e., rising plate meter, multispectral radiometer) or satellite‐based (i.e., Landsat satellite imagery, AussieGRASS forage production model). Sampling occurred across open and wooded semi‐arid vegetation types. We compared methods based on accuracy, the ability of each method to accurately predict a ‘forage‐switch’ threshold, cost, and the suitability for the management context.ResultsFor this case study, the multispectral radiometer was the most precise, yet most expensive, biomass estimation method over a single survey. However, satellite imagery proved to be the most cost‐efficient and fit for purpose, as it was inexpensive and most accurately estimated biomass around a forage‐switch threshold, second only to the multispectral radiometer. Accuracy of all methods was improved by including tree cover in the regression models.ConclusionsWe demonstrate a process for exploring which biomass estimation tool might be preferred for a given decision context, highlighting accuracy, consideration of tolerance to uncertainty and risk, the spatial and temporal scale of information required, and budget constraints.