DOI: 10.5061/dryad.jq2bvq8bc
title: Fire, grazers and browsers interact with grass competition to determine tree establishment in an African savanna

description: In savanna ecosystems, fire and herbivory alter the competitive
 relationship between trees and grasses. Mechanistically, grazing
 herbivores favor trees by removing grass, which reduces tree-grass
 competition and limits fire. Conversely, browsing herbivores consume trees
 and limit their recovery from fire. Herbivore feeding decisions are in
 turn shaped by risk-resource trade-offs that potentially determine the
 spatial patterns of herbivory. Identifying the dominant mechanistic
 pathways by which fire and herbivores control tree cover remains
 challenging, but is essential for understanding savanna dynamics. We used
 an experiment in the Serengeti ecosystem and a simple simulation driven by
 experimental results to address two main aims: (1) determine the
 importance of direct and indirect effects of grass, fire and herbivory on
 seedling establishment; and (2) establish whether predators determine the
 spatial pattern of successful seedling establishment via effects on
 mesoherbivore distribution. We transplanted tree seedlings into plots with
 a factorial combination of grass and herbivores (present/absent) across a
 lion kill-risk gradient in the Serengeti, burning half of the plots near
 the end of the experiment. Ungrazed grass limited tree seedling survival
 directly via competition, indirectly via fire, and by slowing seedling
 growth, which drove higher seedling mortality during fires. These effects
 restricted seedling establishment to below 18% and, in conjunction with
 browsing, resulted in seedling establishment dropping below 5%. In the
 absence of browsing and fire, grazing drove a 7.5-fold increase in
 seedling establishment. Lion predation risk had no observable impact on
 herbivore effects on seedling establishment. The severe negative effects
 of grass on seedling mortality suggests that regional patterns of tree
 cover and fire may overestimate the role of fire in limiting tree cover,
 with regular fires representing a proxy for the competitive effects of
 grass.
description: Data were collected within the Serengeti National Park (hereafter
 “Serengeti”), Tanzania, between March 2018 and December 2019. Our study
 site consisted of a subset of the ~206 camera traps comprising the
 Snapshot Serengeti (SS) grid. We used kill risk probability density
 estimates for each camera in the SS grid extracted from a kernel density
 distribution created using over 2500 historic lion kill locations of 6
 common herbivore species. We selected 80 cameras in this section of the
 grid and categorized lion kill risk as high-, medium- or low-risk based on
 kill risk probability density functions. We then used stratified random
 sampling to select 48 final cameras (16 high-risk, 16 medium-risk, 16
 low-risk) within a ~460 km2 area as our focal experimental sites. The
 grass community in the study area is dominated by <em>Themeda
 triandra, Pennisetum mezzianum, Panicum maximum, Eustachys
 paspaloides</em> and <em>Digitaria macroblephara</em>,
 and has burned approximately every 3 years since 2000.
 <em>Tree-seedling survival data</em>
 We focused on the seedling-sapling recruitment phase of tree
 demographics. We set up a fully factorial grass competition (grass vs. no
 grass) × herbivore exclusion (present vs. absent) experiment within each
 site, resulting in four 1m x 1m plots per site. In the grass competition
 treatment, grass was either completely removed or present, and in the
 herbivore exclusion treatment herbivores were either excluded using cages
 or allowed to feed freely. At the onset of the long rains, when trees
 normally recruit from seed (February 2018), we transplanted two V.
 robusta and two V. tortillis seedlings within each plot (15 cm from each
 corner), giving a total of 768 seedlings overall (2 species x 2 seedlings
 per plot x 4 plots per site × 48 sites). We had previously grown the
 seedlings under ambient light conditions and watered them to soil
 saturation every two days for 4 weeks prior to transplanting.
 To non-destructively estimate aboveground grass biomass in each
 plot, we used an indirect approach based on light attenuation through the
 grass canopy. We sampled seedling height, basal diameter and grass biomass
 of each plot using the same protocol every three months until July 2019,
 at which time half of the sites were burned. Although efforts were made to
 limit wildfires, nine sites (four high-risk, four medium-risk, one
 low-risk) burned in unplanned fires during July 2018 (before we could
 apply the fire treatment). We binned remaining sites by predation risk
 category and used a random number generator to select five high-risk, five
 medium-risk, and eight low-risk sites that were burned in October 2019.
 We resampled plots one final time in
 December 2019 after two months of consistent rainfall when surviving
 burned seedlings had had sufficient time to
 resprout. This data is avalaible in two .csv
 files: serengeti.transplant.seedling.survival.csv -
 contains raw data of all seedlings through the entire
 study fire.survival.csv - contains a subset of
 seedlings that were burned with pre and post burn survival
 recorded <em>Herbivore
 data</em> At each site we had one camera trap
 facing our experimental plots and we collected and processed all images
 over the study period. We used camera-trap occupancy data from these
 images for all mammalian herbivores
 larger than a dik-dik (Madoqua kirkii) and generated daily metabolic-adjusted herbivore
 indices (kg.d-1). We divided herbivores into mesobrowser, mesograzer,
 megagrazer and megabrowser guilds, but excluded giraffe from analysis as
 they are unlikely to feed on tree seedlings. We further split
 mesoherbivores into migratory or resident designations
 and calculated total daily metabolic-adjusted herbivore
 indices for each guild. These data are available in the .csv file
 herbivore.mmass.csv
description: All the necessary information for these data is included in the
 ReadMe file.