A simplified and affordable approach to forest monitoring using single terrestrial laser scans and transect sampling.

Traditional forestry, ecology, and fuels monitoring methods can be costly and error-prone, and are often used beyond their original assumptions due to difficulty or unavailability of more appropriate methods. These traditional methods tend to be rigid and may not be useful for detecting new ecological changes or required data at modern levels of precision [1]. The integration of Terrestrial Laser Scanning (TLS) methods into forest monitoring strategies can cost effectively standardize data collection, improve efficiency, and reduce error, with datasets that can easily be analyzed to better inform management decisions. Affordable (sub-$20K) off-the-shelf TLS units-such as the Leica BLK360- have been used commercially in the built environment but have untapped potential in the natural world for monitoring. Here, we provide a methodology that successfully integrates LiDAR scanning with existing monitoring methods. This new method:•Allows for simplified and quick extraction of forestry, fuels and ecological vegetation variables from a single TLS point cloud and quick transect sampling.•Streamlines the data collection process, removes sampling bias, and produces data that can be easily processed to provide inputs for models and decision support frameworks.•Is adaptable to integrate additional or new environmental measurements.

A novel approach to fuel biomass sampling for 3D fuel characterization.

Surface fuels are the critical link between structure and function in frequently burned pine ecosystems, which are found globally (Williamson and Black, 1981; Rebertus et al., 1989; Glitzenstein et al., 1995) [[1], [2], [3]]. We bring fuels to the forefront of fire ecology through the concept of the Ecology of Fuels (Hiers et al. 2009) [4]. This concept describes a cyclic process between fuels, fire behavior, and fire effects, which ultimately affect future fuel distribution (Mitchell et al. 2009) [5]. Low-intensity surface fires are driven by the variability in fine-scale (sub-m level) fuels (Loudermilk et al. 2012) [6]. Traditional fuel measurement approaches do not capture this variability because they are over-generalized, and do not consider the fine-scale architecture of interwoven fuel types. Here, we introduce a new approach, the "3D fuels sampling protocol" that measures fuel biomass at the scale and dimensions useful for characterizing heterogeneous fuels found in low-intensity surface fire regimes. •Traditional fuel measurements are oversimplified, prone to sampling bias, and unrealistic for relating to fire behavior (Van Wagner, 1968; Hardy et al., 2008) [7,8].•We developed a novel field sampling approach to measuring 3D fuels using an adjustable rectangular prism sampling frame. This voxel sampling protocol records fuel biomass, occupied volume, and fuel types at multiple scales.•This method is scalable and versatile across ecosystems, and reduces sampling bias by eliminating the need for ocular estimations.