DOI: 10.5061/dryad.h9w0vt4rd
title: Data from: Hyperspectral imaging predicts differences in carbon and nitrogen status among representative biocrust functional groups of the Colorado Plateau

description: Biological soil crusts (biocrusts) are widespread soil photosynthetic
 communities covering about 12% of Earth’s land surface and play crucial
 roles in terrestrial carbon (C) and nitrogen (N) cycles, yet scalable
 quantifications of biocrusts and their biogeochemical contributions are
 notably lacking. While remote sensing has enormous potential to assess,
 scale, and contextualize biocrusts and their functions, the applicability
 of hyperspectral data in predicting C- and N-related biocrust traits
 remains largely unexplored. We address this issue by evaluating the
 potential of in situ hyperspectral data to predict C and N across a range
 of biocrust species and different environmental conditions. We found that
 in situ hyperspectral reflectance measurements can be used to predict
 biocrust tissue C/N ratios and N concentrations with relatively high
 accuracy but to a lesser extent for potential biocrust N2 fixation rates.
 Critical wavelength domains included the visible region of the spectrum
 from roughly 490 to 600 nm, which most effectively
 captured variations in biocrust tissue C, and the shortwave infrared
 region from 1150 to 1350 nm and 1550 to 1650 nm, which most effectively
 captured biocrust tissue N and N2 fixation potential. Finally, we
 provide evidence that multi- and hyperspectral missions with targeted band
 placement, such as the proposed 26-band Landsat Next, could be effective
 in predicting biocrust traits. This work provides a critical step in
 understanding how to apply data from new and upcoming satellite missions
 to the monitoring of biocrusts.
description: <strong>Biocrust sample collection</strong>
 A total of 14 species were chosen for their variation in C and N
 cycling and their abundance in the Southwest United States and globally,
 with 10 replicate samples for each of the 14 target species. Biocrusts
 were collected from the Sand Flats Recreation Area near Moab, Utah
 (38.5781°N, 109.4472°W). Biocrusts were identified based on known field
 appearance characteristics such as color and morphology. Descriptions of
 the sampling site in detail are available in (Torres-Cruz et al., 2018).
 Two cyanolichens (<em>C. tenax</em>, <em>C.
 coccophorum</em>) and one darkly-pigmented cyanobacterium (likely
 <em>Scytonema</em> sp.)<em> </em>were selected as
 known N<sub>2</sub>-fixers (N<sub>2</sub>-fixers
 hereafter) and other species were chosen due to their high abundance at
 the Moab site and in drylands worldwide. Samples were collected by first
 wetting with deionized water and a spray bottle, then using a 1-inch (2.54
 cm) clear plastic tube to core the target species. We included only the
 minimum amount of below-crust mineral soil required to maintain sample
 integrity. We attempted to collect species in isolation, but this proved
 impossible for some species due to their propensity to grow interspersed
 with other species rather than in a monoculture even at the 1-inch scale.
 The amount of non-target species in a sample was minimized to the extent
 possible. Samples were then allowed to dry fully in the lab before photos
 were taken. Species were sorted into the following groups based on common
 functional, morphological, and taxonomic categorizations: 1)
 N<sub>2</sub>-fixers; 2) Squamulose, which includes
 chlorolichens with a squamulose morphology and the Myrmecia photobiont; 3)
 Crustose/foliose, which includes chlorolichens with a crustose or foliose
 morphology and the Trebouxia or Asterochloris
 photobiont<em> </em>and 4) Mosses.
 <strong>Biocrust traits
 measurement</strong> Functional traits associated
 with biocrust C and N cycling were assessed from tissue and trace-gas
 exchange. The biocrust samples were placed in a greenhouse where their
 moisture was maintained by gently spraying with deionized water for
 several days before being air dried. Following the final watering event, a
 set of photographs was taken while the samples were still wet. Tissue C
 and N samples were collected from air-dried biocrusts and were oven-dried
 at 60ºC. A subsample of the ground tissue was analyzed for total C and N
 on a Vario Micro Cube elemental analyzer (Elementar, Langesbold, Germany).
 Samples were assessed on a per mass (e.g., for tissue C and N) or per area
 (e.g., for potential N<sub>2</sub> fixation) basis. It should
 be noted that area-based measurements do not take into account surface
 relief and the area of the target species was measured using the ImageJ
 software based on photographs (Abràmoff et al., 2004). The area-based
 measurements are intended to represent overhead views, as would be
 obtained during typical field surveys of biocrust community cover and
 composition. For the potential
 N<sub>2</sub> fixation rate (NF<sub>pot</sub>)
 trait assessment, there are two incubation methods commonly used; the
 Acetylene Reduction Assay (ARA) (Hardy et al., 1968), which takes
 advantage of a lack of substrate specificity when measuring the reduction
 of acetylene (C<sub>2</sub>H<sub>2</sub>) into
 ethylene (C<sub>2</sub>H<sub>4</sub>) by
 nitrogenase, and second, the addition of an enriched
 <sup>15</sup>N<sub>2</sub> headspace and the
 subsequent measurement of <sup>15</sup>N in
 N<sub>2</sub>-fixer tissue. There are drawbacks to both
 methods. ARA is not a true measurement of
 N<sub>2</sub> fixation, but rather an assessment of
 nitrogenase activity. In turn, the <sup>15</sup>N technique is
 challenging for assessments of whole communities, which biocrusts are
 (i.e., multiple N<sub>2</sub>-fixing species living together
 across extremely small scales). N<sub>2</sub>-fixer tissue
 cannot be isolated from other tissues or soil (e.g., heterotrophic
 N<sub>2</sub>-fixers in soil) and thus whole samples must be
 used, which are often too diluted for observing the
 <sup>15</sup>N signal. To minimize the drawbacks of both
 methods, we assessed a subset of samples using both ARA and
 <sup>15</sup>N<sub>2</sub>, while the remaining
 samples were assessed using only ARA. Samples were given a 10% headspace
 of either acetylene or
 <sup>15</sup>N<sub>2</sub> before being incubated
 for eight hours in the greenhouse with ambient daylight and temperature.
 Following the incubation, a 4 ml headspace sample was collected from the
 ARA samples and analyzed for ethylene on a Shimadzu GC-14A with a flame
 ionization detector (FID) (Shimadzu, Kyoto, Japan). All the samples were
 then uncapped and the
 <sup>15</sup>N<sub>2</sub> samples were
 homogenized by ball mill before subsamples were wrapped in tin capsules
 and sent to the Central Appalachian Stable Isotope Facility for
 δ<sup>15</sup>N analysis. The ANOVA analysis followed by
 Tukey's Honestly Significant Difference (HSD) test was performed for
 each of the four traits to determine if there is a significant difference
 between each of two the four biocrust groups.
 <strong>Hyperspectral reflectance
 measurement</strong> In this study, <em>in
 situ</em> spectral measurement refers to measuring the reflectance
 of biocrust samples in a laboratory environment with a portable
 spectroradiometer. Specifically, hyperspectral reflectance within the
 wavelength range of 350-2500nm was measured at a 1 nm spectral resolution
 for all biocrust samples using an ASD FieldSpec 3 spectroradiometer
 (Analytical Spectral Devices, Boulder, CO, USA). The reflectance
 measurements were made in a non-destructive manner using a plant probe
 assembly consisting of a leaf clip and a contact probe (see Figure S1 in
 supporting information S1) (Udelhoven et al., 2003). The contact probe,
 with a diameter of approximately 25mm, has an internal light source of a
 halogen bulb with a color temperature of 2900K. The leaf clip has a white
 reference panel and a black background panel, which are used when checking
 white reference and during the actual reflectance measurement,
 respectively. We strictly followed the procedures used
 in previous studies when operating the spectroradiometer, including
 turning on the spectroradiometer at least 30 minutes before collecting any
 spectra optimizing the spectroradiometer, and checking the white reference
 using the ASD ViewSpec Pro software (Malvern Panalytical, 2014) every five
 minutes or whenever spectra exhibited abrupt discontinuities (Young and
 Reed, 2017). Each sample was held against the contact probe using the leaf
 clip’s dark background panel. We collected five spectra from each sample
 when the samples were wet. The biocrust samples were then air-dried before
 we collected another five spectra for each sample. We also collected
 spectra of dry mineral soil from a sampling site with similar
 characteristics to quantify the main differences between spectra of
 biocrusts and mineral soil (Phillips et al., 2022). The collected spectra
 were saved as binary files, which were imported into R (R Core Team, 2022)
 using the ‘asdreader’ package (Roudier and Lalibert, 2017). We excluded
 the reflectance within 350-400 nm and 2450-2500 nm from the following
 analyses due to the noises within these wavelength ranges as reported in
 previous studies (Barnes et al., 2017; Loozen et al., 2019).
description: # Data from: Hyperspectral imaging predicts differences in carbon and
 nitrogen status among representative biocrust functional groups of the
 Colorado Plateau
 [https://doi.org/10.5061/dryad.h9w0vt4rd](https://doi.org/10.5061/dryad.h9w0vt4rd) 1. The spectral reflectance of samples for 14 biocrust species was measured using an ASD FieldSpec 3 spectroradiometer under both wet and dry conditions. 2. Spectral reflectance of three mineral soil samples measured using an ASD FieldSpec 3 spectroradiometer 3. Biocrust functional traits data ## Description of the data and file structure 1. The biocrust spectral reflectance folder contains 1377 binary files (.asd files), each of which represents the spectra (350-2500nm) measured using an ASD FieldSpec 3 spectroradiometer. 2. The mineral soil spectral reflectance folder contains 3 binary files (.asd files), each of which represents the spectra (350-2500nm) measured using an ASD FieldSpec 3 spectroradiometer. 3. For the Excel file with the biocrust traits data: 1\) Any values that are 0 were below detection limits of the instruments used 2\)Any cells that have an x were not measured for that value (in the nmol C2H4/hr column this is because they were used as controls) ## Sharing/Access information NA ## Code/Software 1. The ASD files for spectral reflectance can be opened into R using using the ‘asdreader’ package, which can be downloaded at [https://cran.r-project.org/web/packages/asdreader/](https://cran.r-project.org/web/packages/asdreader/)  2. The biocrust traits data can be imported into R directly.