DOI: 10.5061/dryad.pg4f4qrr5
title: Limited increases in savanna carbon stocks over decades of fire suppression

description: Savannas cover a fifth of the land surface and contribute a third of
 terrestrial net primary production, accounting for three quarters of
 global area burned and over half of global fire-driven carbon emissions.
 Fire suppression and afforestation have been proposed as tools to increase
 carbon sequestration in these ecosystems. A robust quantification of
 whole-ecosystem carbon storage in savannas is lacking, however, especially
 under altered fire regimes. Here, we provide the first direct estimates of
 whole-ecosystem carbon response to over 60 years of fire exclusion in a
 mesic African savanna. We found that fire suppression increased
 whole-ecosystem carbon storage by only 35.4 ± 12% (mean ± standard error),
 even though tree cover increased by 78.9 ± 29.3%, corresponding to total
 gains of 23.0 ± 6.1 Mg C ha-1 at an average ~0.35 ± 0.09 Mg C ha-1 yr-1,
 more than an order of magnitude lower than previously assumed. Frequently
 burned savannas had substantial belowground carbon, especially in biomass
 and deep soils. These belowground reservoirs are not fully considered in
 afforestation or fire suppression schemes but may mean that the decadal
 sequestration potential of savannas is negligible, especially weighed
 against concomitant losses of biodiversity and function.
description: <strong>Study site</strong>: Kruger National Park
 (latitude: 22°20ʹ - 25°30ʹS; longitude: 31°10ʹ - 32°00ʹE) in South
 Africa <b>Experimental design: </b>Kruger
 maintains one of a handful of long-term burning experiments in tropical
 savannas. The experimental burning plots (EBPs) were initiated in 1954,
 making them the longest-running fire ecology research project in African
 savannas. The EBPs are distributed across four different landscapes of
 Kruger (<i>i.e.,</i> Mopani, Satara, Skukuza, Pretoriuskop)
 with different dominant tree species, parent materials, and rainfall. Each
 landscape can be considered as an independent factorial design with four
 replicates (hereafter, strings). Within each string, there are 12
 treatments with the fire return interval of each treatment representing a
 different combination of frequency and season.  For this study, we
 selected the Pretoriuskop landscape receiving ~700 m rainfall, which
 broadly represents African savannas that have the potential to reach full
 tree cover. Among these 12 treatments, we selected plots burned every year
 in August (hereafter, annual) to represent an extreme fire regime; plots
 burned every three years in August (hereafter, triennial) to represent the
 near-natural fire return interval of African savannas; and plots that have
 not burned since 1954 (hereafter, unburned) to represent savannas with
 fire-suppressed status. <strong>Light detection
 and ranging (LiDAR) data collection</strong>: Woody biomass was
 estimated using LiDAR. We used Riegl VUX-1LR LiDAR unit integrated onto a
 DJI Matrice 600 PRO unoccupied aerial system (UAS) to collect
 high-resolution airborne LiDAR data. We carried out the LiDAR survey
 during the middle of the wet season (<i>i.e.,</i> January) of
 2020 when vegetation was at full leaf-on stage. The flight altitude was
 100 m above ground level, flight speed was 8 m s<sup>-1</sup>,
 and the LiDAR scan rate was 78.1 lines/second (see Supplementary Table 4
 for other parameter settings). The UAS maintained consistent elevation
 above the ground by using 30 m × 30 m elevational data from the shuttle
 radar topography mission (SRTM) to adjust flight altitude in real time
 during the survey. All treatments within each string were surveyed with
 transects of identical heading to decrease the probability of introducing
 confounding variables and remote sensing artifacts created by differing
 survey methodologies or LiDAR scan directions.
 <strong>Ground penetrating radar data
 collection</strong>: Coarse lateral root biomass from woody plants
 was estimated using the ground penetrating radar (GPR). GPR profiles were
 acquired using the Subsurface Interface Radar (SIR) System-4000 with 1.6
 GHz shielded antenna and odometer wheels for position recording
 (Geophysical Survey Systems Inc., NH, USA). Prior to the survey, the grass
 layer was carefully removed to avoid any interference in the transmission
 of electromagnetic energy from antenna to soils. The survey was conducted
 during the dry season (September to November) of 2018 with soil water
 content less than 5%. At each 10 m × 10 m plot, GPR profiles were
 collected on a 20-cm grid. If a tree was present on a scanning line, the
 rest of the GPR profile was obtained from the opposite direction. The
 topography across all plots was relatively flat with minimal surface
 relief (&lt; 5 cm). Extra care was taken to ensure the accurate
 position of each GPR profile with a guide rope and the difference in the
 length of GPR profile was less than 1% (<i>i.e.,</i> 10 cm) of
 the supposed distance (<i>i.e.,</i> 10 m).
description: This data is comprised of two components: (1) data and code
 for light detection and ranging (LiDAR) processing; (2) data and code for
 ground penetrating radar (GPR) processing. Please refer to the paper for
 more details on data analysis.