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Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha−1. Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.
An improved approach to predicting preferred habitat and targetting survey effort for threatened plant species is needed to aid discovery and conservation of new populations. This study employs several approaches to aid in the delineation of preferred habitat for the Leafless Tongue Orchid, Cryptostylis hunteriana Nicholls. BIOCLIM, a bioclimatic analysis and prediction system, is used initially to generate a bioclimatic habitat envelope within which the species can be expected to occur, based on all known sites in the Shoalhaven Local Government Area. Within the BIOCLIM envelope it is possible to further investigate the extent to which the species exhibits preferences for other habitat factors such as geology, soil landscapes and forest ecosystems. Multivariate techniques are used to compare floristic data from sites where Cryptostylis hunteriana is present, and sites from forest ecosystems where it has not been recorded historically. These techniques are also used to identify species which are diagnostic of each of these sets of sites. All 25 sites with Cryptostylis hunteriana populations are restricted to six forest ecosystems having a total area of 15% of the Shoalhaven Local Government Area and 47% of the BIOCLIM envelope. Within these forest ecosystems, ten plant species deemed indicative of the possible presence of the Cryptostylis hunteriana are identified.