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Trophic rewilding revives biotic resistance to shrub invasion

Citation

Guyton, Jennifer et al. (2020), Trophic rewilding revives biotic resistance to shrub invasion, Dryad, Dataset, https://doi.org/10.5061/dryad.sxksn02zc

Abstract

Trophic rewilding seeks to rehabilitate degraded ecosystems by repopulating them with large animals, thereby reestablishing strong top-down interactions. Yet there are vanishingly few tests of whether such initiatives can restore ecosystem structure and functions, and on what timescales. Here we show that war-induced collapse of large-mammal populations in Mozambique’s Gorongosa National Park exacerbated woody encroachment by the invasive shrub Mimosa pigra—one of the world’s ‘100 worst’ invasive species—and that one decade of concerted trophic rewilding restored this invasion to pre-war baseline levels. Mimosa occurrence increased between 1972 and 2015, a period encompassing the near-extirpation of large herbivores during the Mozambican Civil War. From 2015–2019, mimosa abundance declined as ungulate biomass recovered. DNA metabarcoding revealed that ruminant herbivores fed heavily on mimosa, and experimental exclosures confirmed the causal role of mammalian herbivory in containing shrub encroachment. Our results provide mechanistic evidence that trophic rewilding has rapidly revived biotic resistance to a notorious woody invader, underscoring the potential for restoring ecosystem structure and functions in degraded African protected areas.

Methods

This study was conducted in Gorongosa National Park, Mozambique.

Post-war field data on Mimosa pigra were obtained from plant surveys (2011-2019) and exclosure experiments (2015-2018) conducted in the Urema Lake floodplain. Pre-war data were extracted from Tinley (1977) "Framework of the Gorongosa ecosystem, Mozambique"

Raw diet data from 2013 to 2018 have been obtained by fecal DNA metabarcoding and high-throughput sequencing. The P6 loop of the chloroplast trnL (UAA) intron was amplified using the universal primers “g” (5’-GGGCAATCCTGAGCCAA-3’) and “h” (5’-CCATTGAGTCTCTGCACCTATC-3’) (Taberlet et al. 2007). Amplicons were sequences on Illumina HiSeq 2500 platform (170 bp single-end sequencing in 2013 and 2 x 150 bp paired-end sequencing in 2015-1018). Initial processing steps were performed using the OBITOOLS software (http://metabarcoding.org/obitools) as follows: (i) Direct and reverse reads corresponding to the same sequence were aligned and merged thanks to the ‘illuminapairedend’ program. Only merged sequences with a high alignment quality score were retained (>=40). (ii) Each merged sequence was assigned to its original sample using the tags information previously added to primers using the ‘ngsfilter’ program. Only sequences containing both primers (with a maximum of 2 mismatches per primer) and exact tag sequences were selected. (iii) Strictly identical sequences were merged together while keeping information about the origin of sequences.

Users of the raw dietary data are requested to coordinate with the corresponding author (rpringle@princeton.edu) to help ensure accurate interpretation and avoid duplication with other research in progress.

Usage Notes

Raw diet data 2013

This fasta file contains unfiltered sequencing data (i.e. merged paired-end reads assigned to their original sample) from fecal samples collected in 2013.

Diet_GNP13_trnL_raw_data.fasta.gz

README_Diet_GNP13_trnL_raw_data.txt

Metadata fecal samples 2013

This file contains metadata associated to fecal samples collected in 2013.

Metadata_fecal_samples_GNP13.csv

README_Metadata_fecal_samples_GNP13.txt

Raw diet data 2015

This fasta file contains unfiltered sequencing data (i.e. merged paired-end reads assigned to their original sample) from fecal samples collected in 2015.

Diet_GNP15_trnL_raw_data.fasta.gz

README_Diet_GNP15_trnL_raw_data.txt

Metadata fecal samples 2015

This file contains metadata associated to fecal samples collected in 2015.

Metadata_fecal_samples_GNP15.csv

README_Metadata_fecal_samples_GNP15.txt

Raw diet data 2017 (early and late dry seasons)

This fasta file contains unfiltered sequencing data (i.e. merged paired-end reads assigned to their original sample) from fecal samples collected during early (June-August) and late (October-November) dry seasons 2017.

Diet_GNP17_trnL_raw_data.fasta.gz

README_Diet_GNP17_trnL_raw_data.txt

Metadata fecal samples 2017

This file contains metadata associated to fecal samples collected in 2017 (both early and dry seasons).

Metadata_fecal_samples_GNP17.csv

README_Metadata_fecal_samples_GNP17.txt

Raw diet data early dry season 2018

This fasta file contains unfiltered sequencing data (i.e. merged paired-end reads assigned to their original sample) from fecal samples collected in the early dry season (June-August) 2018.

Diet_GNP18_EarlyDrySeason_trnL_raw_data.fasta.gz

README_Diet_GNP18_EarlyDrySeason_trnL_raw_data.txt

Metadata fecal samples early dry season 2018

This file contains metadata associated to fecal samples collected in the early dry season 2018.

Metadata_fecal_samples_GNP18_EarlyDrySeason.csv

README_Metadata_fecal_samples_GNP18_EarlyDrySeason.txt

Raw diet data late dry season 2018

This fasta file contains unfiltered sequencing data (i.e. merged paired-end reads assigned to their original sample) from fecal samples collected in the late dry season (October-November) 2018.

Diet_GNP18_LateDrySeason_trnL_raw_data.fasta.gz

README_Diet_GNP18_LateDrySeason_trnL_raw_data.txt

Metadata fecal samples late dry season 2018

This file contains metadata associated to fecal samples collected in the late dry season 2018.

Metadata_fecal_samples_GNP18_LateDrySeason.csv

README_Metadata_fecal_samples_GNP18_LateDrySeason.txt

Mimosa consumption data

This table presents the mean relative read abundance and the frequency of occurrence of Mimosa pigra in the diet of the six dominant floodplain large herbivores between 2013 and 2018. These data correspond to Fig. 3 and Extended Data 2.

Mimosa_RRA_FOO.csv

README_Mimosa_RRA_FOO.txt

Most abundant plant items in large herbivores diet

These tables present the 10 most abundant mOTUs identified in the diet of the six dominant floodplain large herbivoresspecies for each sampling season (from 2013 to 2018). One sheet per sampling season (2013, 2015, 2016, 2017 early dry season, 2017 late dry season, 2017 early dry season and 2018 late dry season). These data correspond to Extended Data 1.

Most_Abundant_mOTUs_per _species.xlsx

README_ Most_Abundant_mOTUs_per_species.txt

Field data

This file contains the following field data (corresponding to Supplementary data 1-8, one sheet per dataset):

(i) Biomass density of large herbivores in Gorongosa's Urema Floodplain between 1969 and 2018. These data correspond to Fig. 2a.

(ii) Mimosa occurrence in 18 long-term floodplain monitoring plots between 1972 and 2017. These data correspond to Fig. 2b.

(iii) Rainfall measured at Gorongosa’s Chitengo camp between 1957 and 2019. These data correspond to Fig. 2c,d.

(iv) Mimosa density in four 200-m2 floodplain plots between 2011 and 2019. These data correspond to Fig. 2d.

(v) Size, survival, and reproduction of tagged mimosa plants in experimental plots over six surveys between 2015 and 2018. These data correspond to Fig. 4a-d, f and Extended Data 3.

(vi) Recruitment of mimosa seedlings and saplings in experimental plots in September 2017. These data correspond to Fig. 4e.

(vii) Total survey of mimosa abundance and biomass in experimental plots in August 2018. These data correspond to Fig. 5.

(viii) Estimation of mimosa aboveground dry biomass from canopy dimensions. These data correspond to Extended Data 4.

Supplementary_Field_Data.xlsx

README_Supplementary_Field_Data.txt

Funding

National Science Foundation, Award: IOS-1656527

National Geographic, Award: Young Explorers Grant 9459-14

National Science Foundation, Award: Graduate Research Fellowships

Randall and Mary Hack '69 Award

Princeton University's institutes for African Studies and International and Regional Studies

Carr Foundation

Sherwood Foundation

Cameron Schreir Foundation

Princeton's Innovation Fund for new ideas in the natural sciences

Princeton Environmental Institute, Princeton University, Award: Grand Challenges Program