DOI: 10.5061/dryad.tx95x6b5r
title: Ecosystem-wide responses to fire and large mammal herbivores in an African savanna

description: Fire and large mammal herbivores (LMH) are the principal top-down forces
 maintaining savanna structure.  Nonetheless, experiments designed
 to investigate interactions between fire and LMH are rare in savannas, and
 relationships between environmental variation and biodiversity in the
 context of fire and LMH are poorly understood.  This study
 addresses these gaps by manipulating the presence of LMH and early and
 late dry season fires in a tropical African savanna.  In
 addition, this work simultaneously explores environmental variables
 including soil and foliar quality, vegetation cover, and nearby water
 sources to more holistically describe factors affecting savanna
 functioning and biodiversity.  After one year of experimental
 treatments, changes in vegetation were already apparent.  Shrub
 abundance and richness and grass richness were higher in the absence of
 LMH, while grass biomass increased three-fold in burned plots as compared
 to unburned plots.  Foliar nutrients tended to increase in open
 plots, while phenolics decreased.  Amphibian abundance decreased
 with early burns and was higher with LMH.  In contrast, small
 mammal abundance and richness increased without LMH and with time since
 fire.  Richness and foraging of LMH were highest after late
 burns. These results demonstrate ecosystem-wide effects of LMH,
 illustrating the importance of considering multiple taxa when designing
 fire management programs. For example, burning negatively affected
 amphibians and small mammals and changed vegetation at the same time it
 increased LMH foraging.  In the long-term, this experiment will
 shed light on interacting effects of fire and LMH on savanna biodiversity
 and function.  
description: <strong>Study site</strong> The
 Gorongosa Savanna Ecology Experiment is in a Rift Valley Lowland Woodland
 landscape (Lötter et al., 2021) in Gorongosa National Park (GNP),
 Mozambique (-18°58', 34°20', ~25 m a.s.l.).  The experimental
 area covers ~197-ha.  Woody plant communities include a mixed broadleaf
 savanna dominated by <em>Combretum adenogonium</em>
 (Combretaceae) which transitions to a more open savanna co-dominated by
 <em>Acacia (Vachellia) robusta</em> and <em>Acacia
 (Senegalia) nigrescens </em>(Fabaceae).  The most common shrub is
 <em>Capparis erythrocarpos </em>var. <em>rosea
 </em>(Capparaceae), and common grasses include <em>Megathyrsus
 maximus,</em> <em>P. infestum, P. coloratum, Urochloa
 mosambicensis, </em>and <em>Digitaria eriantha.</em> 
 Soils are silty clay loams.  The average annual temperature is 24.1° C,
 and average annual precipitation is 1053 mm.  The area is a mesic savanna
 with a dry season extending from April to November; 86% of rain falls
 between November and March.  Between 2001 and the start of the experiment
 in 2020, the study area burned every 2-3 years, and the last fire recorded
 before the experiment was in 2016 (Table S2).  The biomass of large mammal
 herbivores derived from full aerial counts of 129,393 hectares of savanna
 habitat in Gorongosa in 2020 and 2022 averaged 5,938
 kg/km<sup>2</sup>.  This biomass figure is moderate to high in
 comparison to areas with similar mean annual precipitation (East 1984,
 Hempson et al. 2015b). <strong>Study
 design</strong> In December 2020, three 30 x 30 m
 exclosure (fenced) plots were established in ten replicate blocks; fences
 were 2 m tall, and the top wires were electrified to prevent elephant
 damage.  Each block consisted of three exclosure plots and three open
 plots and averaged 1.15 ha in size.  Blocks were randomly located within
 the study area, maintaining a minimum distance of 100 m between them. 
 Plots within the blocks were a minimum of 20 m apart.  They were located
 to avoid large termite mounds and to contain at least one tree.  Treatment
 levels were randomly assigned to the plots.  One pair of open and closed
 plots was subject to a cold burn (beginning of the dry season) on 18-20
 May 2021, and another pair of plots was subject to a hot burn (middle of
 the dry season) on 15-16 September 2021.  The first rain after the cold
 burn was 19 mm on 22-23 May 2021.  After the hot burn, the first rain was
 5.3 mm on 19 September 2021.  Two control burn plots, one fenced and one
 open, burned due to escaped embers during the hot burn, so they were
 treated as hot burn plots in analyses.
 <strong>Soil and vegetation
 measurements</strong> Soil samples were taken
 before the experiment and one year after the first cold burns for C and N
 analyses.  In March 2021, before the exclosures began to take effect and
 before any experimental burns, three soil samples were collected from 2-15
 cm depth at random locations within three randomly selected plots per
 block.  In May 2022, three soil samples were collected from all plots. 
 Samples were mixed at the plot level, dried in an oven at 50 °C, sieved,
 and sent to the Central Analytical Facilities at the University of
 Stellenbosch for C and N analyses following standard protocols using Vario
 EL Cube (Elementar Analysensysteme GmbH, Germany) elemental
 analysis. Shrub richness and abundance were measured in
 February-March of 2021, just after the exclosures were installed, and
 again in February-May 2022.  Woody species classified as shrubs were
 perennial plants that consistently flower below 1.3 m and often do not
 have a clearly dominant stem.  Abundant species in our dataset were
 <em>Capparis erythrocarpos</em>, species of <em>Grewia,
 Salvadora persica</em>, and <em>Dichrostachys
 cinerea</em>.  Shrubs were measured in four 5 x 5 m subplots located
 5 m from the edge of each corner of the plots.  Diameter at breast height
 (DBH) of all trees in the plots was measured in December 2020, before the
 exclosures were installed, and in December 2021, one year after the
 exclosures were installed.  Data were used to calculate the size corrected
 relative growth rate (RGR) and the change in basal diameter.  RGR was
 calculated by subtracting initial diameters from final diameters and
 dividing the response by the initial diameter.  Basal area measurements
 included all individuals present in 2020 and 2021 (including new recruits
 in 2021).  Basal area was summed at the plot level for analyses, and the
 average RGR per plot was used in analyses.  The area of all
 <em>Capparis erythrocarpos</em> var.
 <em>rosea</em> individuals in the plots was estimated by
 measuring the length and width of the plants at the same time DBH
 measurements were made. Grass biomass and percent cover
 of grasses and herbaceous plants (forbs) were measured in February-March
 2021.  These data were used for all pre-burn values through May 2021. 
 Biomass data were collected again in June, July, September, October, and
 December 2021, and between February and April 2022 (each plot was measured
 once in this last period).  Grass and herbaceous plant cover were measured
 again in June, August, September, October, and December 2021 and again
 between February and April 2022 (each plot was measured once in this
 period).  Biomass data from July represented July and August in analyses
 of fauna (see below).  Percent cover data from August were also used for
 both July and August.  Grass biomass, grass cover, and forb cover data
 representing November in analyses of fauna were measured in October (see
 below).  To measure grass biomass, grass height was measured with a disc
 pasture meter every 4 m along seven parallel transects spaced 4 m apart
 for a total of 56 points per plot.  The average height per plot was
 calculated and converted to dry weight of grass biomass based on a
 calibration curve developed with samples collected in the experimental
 area (Trollope and Potgieter, 1986).  Grass and forb cover were measured
 in 16 1 m<sup>2</sup> sub-subplots within each plot.  A
 sub-subplot was located in each corner of the 5 x 5 m subplots in which
 shrubs were measured (Appendix 1: Figure S1).  Cover was measured by
 visually estimating the percent of the quadrat occupied by grass or
 forbs.  One to two weeks after each fire, the area burned was measured in
 the same sub-subplots as grass cover.  The height of the burn scars on all
 trees was also measured. Leaf samples were collected
 for elemental analysis (C, N, Ca, K, Mg, P, Si, and Na) and for analysis
 of total phenolics.  Five focal species representing the most abundant
 grasses and woody species were selected for analyses,
 <em>Megathyrsus maximus </em>(Poaceae), <em>Urochloa
 mosambicensis</em> (Poaceae), <em>Capparis
 erythrocarpos</em> var. <em>rosea</em> (Capparaceae),
 <em>Acacia nigrescens</em> (Fabaceae), and <em>Acacia
 robusta</em> (Fabaceae).  Undamaged leaves were randomly collected
 from all plots in which the plants were present in February 2022.  Samples
 from trees were collected from the lowest branches.  Samples were dried at
 40 ̊C.  Leaf samples were ground to a fine powder in coffee grinders and
 were sent to the Central Analytical Facilities at the University of
 Stellenbosch for analyses.  Percent C and N were quantified using a Vario
 EL Cube Elemental Analyzer (Elementar Analysensysteme GmbH, Germany).  The
 concentrations (mg/kg) of other elements were measured with inductively
 coupled plasma mass spectroscopy using an Agilent 7900 inductively coupled
 plasma mass spectrometer (Agilent Technologies, Inc, USA) following the
 lab’s standard procedures.  Total phenolics were quantified using the
 Prussian blue assay (Price and Butler, 1977).  Extractions followed Hattas
 et al. (2005), and absorbance was determined using a spectrophotometer set
 at a wavelength of 720 nm (Shimadzu UV-1800).  Concentrations of total
 phenolics were determined using a calibration curve based on Gallic acid
 (Hattas and Julkunen-Tiitto 2012). <strong>Insect
 sampling</strong> Crickets (Gryllidae: 
 Orthoptera) were the focal insect group in this study because they are
 reliable indicators of habitat quality (Andersen et al., 2001) and are
 omnivorous and polyphagous, and are therefore less affected by the local
 plant assemblage in a given plot (Capinera, 2020).  In addition, crickets
 are relatively easy to sample with standardized, passive methods (Clayton,
 2002).  Gryllidae is species-rich and widely distributed across Africa
 (Robillard et al., 2014; Jaiswara et al., 2018), with 1083 species
 described from the continent (Cigliano et al., 2023). 
 Ground-dwelling crickets were collected during the dry season
 from April to November 2021 (with the exception of July) and after the
 rains began in January 2022.  Crickets were collected in nine pitfall
 traps per plot separated from each other by 5 m along two diagonal lines
 across the plots.  Traps consisted of 8 cm diameter cups inserted 13 cm
 into the soil and filled with water and detergent.  Two collections (April
 and May) were conducted before the cold burn.  The first post-cold burn
 collection was done one week after the fires (the last week of May). 
 Three weeks after the cold burn, another collection was done, and
 collections continued monthly until the hot burn in September.  Insects
 were collected two weeks after the hot burn, and collections continued
 monthly through November.  The pre-cold burn collections were each two
 days, and all subsequent collections were seven days.  The abundance and
 richness of insects in analyses was therefore corrected by the number of
 trapping days.  All insects were identified to morphospecies and are
 stored in the E.O. Wilson Biodiversity Laboratory in GNP.
 <strong>Herpetofauna sampling</strong>
 Amphibians and reptiles were assessed with visual searches and
 pitfall traps monthly.  Visual searches were performed nine times for
 amphibians, in March, May, June, July, August, September, October, and
 November 2021 and in February 2022.  Reptile data were collected in the
 same months with the exception of March 2021.  The same pitfall traps used
 in cricket sampling (described above) were used for herpetofauna
 sampling.  Visual searches consisted of searching each plot for 20
 minutes.  All potential microhabitats (e.g., trees, leaves, shrubs, leaf
 litter, dead tree trunks, holes in the soil, seasonal pans) were
 searched.  All frogs, lizards, and snakes were recorded and photographed
 when possible.  Searches took place in the morning from 7:00 to 11:00 and
 in the afternoon from 15:00 to 18:00.  Five plots were searched each day,
 three in the morning and two in the afternoon; each plot was searched once
 in the morning and once in the afternoon every month. 
 Habitat characteristics that may influence the presence of
 amphibians and reptiles were also measured.  In the same sub-subplots
 where grass and forb cover were measured, leaf-litter cover and litter
 depth were measured.  All downed tree trunks in the plots were counted,
 and their diameters were measured 1.3 m from the base.  Pans (seasonal
 ponds that serve as potential amphibian breeding sites) within 200 m of
 the center of each plot were counted using QGIS v. 3.20, based on GNP’s
 map of water sources.  <strong>Small mammal
 sampling</strong> Small mammals were sampled
 between May and October 2021 using Sherman traps (23 x 9 x 8 cm) baited
 with rice and sesame seeds mixed with peanut butter.  Six traps were
 spaced 9 m apart along two 28 m transects separated by 9 m in each plot
 (three traps per transect).  The traps were left open for three
 consecutive nights in each sampling period.  During the first sampling
 period, traps were set in all the plots.  One week after the cold burn,
 traps were set in the burned and control burn (no fire) plots.  One week
 after the hot burn, only the plots subject to the late season fire and the
 control burn plots were sampled.  All small mammals captured were
 identified, marked with a permanent marker, and released 100 m from the
 point of capture. <strong>Large mammal
 sampling</strong> Large mammal herbivores were
 surveyed using camera traps with a manufacturer-reported detection
 distance of 25 m and a maximum sampling radius of 120 m (Vikeri E2 Trail
 Camera, USA) in the unfenced plots.  Cameras were mounted at a height of
 1.5 m in the NE corner of each plot, facing SE and angled slightly
 downward.  When triggered, the cameras took three photos, with a minimum
 30 s interval between trigger events.  The cameras were active for three
 sampling periods: 19 March - 24 April 2021 (before the cold burn), 8 June
 - 8 September 2021 (after the cold burn), and 29 September 2021 - 30
 January 2022 (after the hot burn).  Large herbivore species richness was
 determined for each sampling period (including warthog, bushpig, red
 duiker, oribi, impala, bushbuck, nyala, waterbuck, sable, kudu,
 wildebeest, buffalo, and elephant).  For the four most abundant species
 (warthog, impala, nyala, and kudu), a measurement of foraging intensity
 was calculated based on the number of individual animals photographed in a
 foraging posture during the sampling period (animals were counted once per
 detection event but counted multiple times if they appeared in sequential
 detections and were still foraging).
description: •           Summary of experimental efforts underlying this dataset The
 datasets included here are from the Gorongosa Savanna Ecology Experiment,
 a factorial experiment exploring interactions between fire (cold and hot
 burns and plots without fire) and large mammals (exclosure vs. open
 plots).  All methods are described in the uploaded methods and in the
 article, Ecosystem-wide responses to fire and large mammal herbivores in
 an African savanna, in Biotropica. •           Description of file
 structure and contents Files are Excel files.  One worksheet contains the
 data, organized and ready for analyses, and the second worksheet (titled
 ‘explanation’) describes the variables in each column of the data
 worksheets. •           Definitions of all variables, abbreviations,
 missing data codes, and units All descriptions are in the ‘explanation’
 worksheets of the Excel files.  The only exception is the phenolics
 dataset in which the column names are self-explanatory.  Cells with “NA”
 lacked data. •           Links to other publicly accessible locations of
 the data N/A •           Other sources, if any, that the data was derived
 from N/A •           Any other details that may influence reuse or
 replication efforts Please see the methods to understand how the data were
 generated.