DOI: 10.5061/dryad.jdfn2z3gr
title: Slow soil enzyme recovery following invasive tree removal through gradual changes in bacterial and fungal communities

description: Biological invasions of plants have profound effects on ecosystem
 functioning by directly and indirectly altering soil microbiota,
 especially when invasive plants co-invade with their associated
 microbiomes. Ecosystem functions may recover slowly following invader
 removal, with implications for restoration. We investigated the recovery
 of soil ecosystem function (measured as soil enzymes) following the
 removal, at different densities and times, of invasive Pinus spp. in New
 Zealand, and how different enzymatic activities responded to pine
 legacies. Enzymatic activities were driven by pine legacies via both
 abiotic (soil nutrients) and biotic (fungi and bacteria) soil properties,
 with different enzymes showing distinct patterns. The activity of the
 enzymes cellobiohydrolase (cellulose degrading),
 β-glucosidase (cellulose degrading), N-acetyl-glucosaminidase
 (chitin degrading), laccase (lignin oxidising) and acid phosphatase
 (organic phosphate hydrolysing) were influenced by time since pine removal
 and by pine density at removal via effects on biotic communities. In
 comparison, Mn-peroxidase (lignin oxidising) was positively correlated
 with density of pines at removal and was negatively correlated with time
 since removal and was only influenced by fungal communities. Synthesis.
 The recovery of soil enzymatic function following invasive species removal
 is slow, and dependent on pine legacies through the gradual changes in
 fungal and bacterial communities. The cascading effects of these changes
 suggest potential implications for the success of future plant
 establishment and restoration of co-invaded ecosystems.
description: At each site (22 sites in
 total), 5 soil samples were collected. From each sample, DNA was extracted
 for amplicon sequencing of fungal and bacterial communities. Soil nutrient
 concentrations and enzyme activities were also measured. Specific
 methodology is described below and in the manuscript.
 <em>DNA extraction</em>
 DNA was extracted from all
 soil samples using a DNeasyPowerSoil Pro Kit (Qiagen, Hilden, Germany) as
 per the manufacturer’s protocol. The fungal amplicon library was prepared
 in a one-step PCR using fungal specific primers fITS7 (5’-GTG ART CAT CGA
 ATC TTT G -3’) and ITS4 (5’-TCC TCC GCT TAT TGA TAT GC-3’) which amplify
 the ITS2 region (universal
 genetic barcode for fungi; Ihrmark et al. 2012). The ITS4 reverse primer included both Illumina
 adapted and index sequences (for identification of sequenced amplicons)
 and the fITS7 primer included Illumina adaptor sequences. The bacterial
 amplicon library was prepared in a one-step PCR using bacterial specific
 primers 515F (5’- GTG YCA GCM GCC GCG GTA A-3’) and 806R (5’-GGA CTA CNV
 GGG TWT CTA AT-3’) which amplify the 16S V4 region (Thompson et al. 2017). The 806R reverse primer included both Illumina
 adapted and index sequences (for identification of sequenced amplicons)
 and the 515F included Illumina adaptor sequences.
 PCR products were visualised
 on 1% agarose gels and concentrations normalised using SequelPrep
 (Thermofisher). Uniquely indexed libraries (n = 110 for fungi, n = 110 for
 bacteria), along with positive and negative controls, were pooled for each
 sequencing run which were performed on an Illumina MiSeq using 2 x 250
 paired end V2 chemistry following the manufacturer’s
 recommendations. <em>Bioinformatics
 analysis</em> Paired-end reads were merged using USEARCH v11
 (Edgar
 2010) with a minimum
 overlap length of 50 bp with no gaps allowed in the merged alignments.
 Sequence deconvolution such as quality control and clustering was carried
 out using VSEARCH (https://github.com/torognes/vsearch.wiki.git).
 Specifically, sequences less than 200 bp and low mean quality (&lt;20)
 were removed. Sequences that passed quality control were clustered into
 operational taxonomic units (OTUs). Fungal OTUs were identified by
 searching against the public database provided by UNITE
 (UNITE Community 2017,
 Nilsson et al. 2018).
 Bacteria OTUs were identified by searching against the public database
 provided by SILVA (Quast
 et al. 2012). Ecological
 information of each fungal OTU was based primarily on FUNGuild
 (https://github.com/UMNFuN/FUNGuild), following the user’s manual where
 assignments were made on ranks of ‘probable’ and ‘highly probable’
 (Nguyen et al.
 2016).
 <em>Abiotic soil
 properties</em> Soils were
 air dried and sieved at 2 mm in preparation for analysis. All tests were
 conducted at R J Hill Laboratories Limited (Hamilton, 3240, New
 Zealand).  <em>Soil enzyme
 assay</em> The enzyme activity of six enzymes were
 measured: cellobiohydrolase (cellulose degrading), β-glucosidase
 (cellulose degrading), N-acetyl-glucosaminidase (NAG; chitin degrading),
 acid phosphatase (organic
 phosphate hydrolysing),
 laccase (lignin oxidising) and Mn-peroxidase (lignin oxidising). These
 enzymes were chosen to encompass carbon, nitrogen and phosphorus cycling
 based on recent literature (German et al. 2011, Kyaschenko et al. 2017a,
 Sterkenburg et al. 2018).
 Cellobiohydrolase was assessed via the hydrolysis of 4-methylumbelliferyl
 β-D-cellobioside. β-glucosidase was assessed via the hydrolysis of
 4-methylumbelliferyl β-D-glucopyranoside. NAG was assessed via the
 hydrolysis of 4-methylumbelliferyl N-acetyl-β-D-glucosaminide. Acid
 phosphatase was assessed via the hydrolysis of
 4-methylumbelliferyl-phosphate. Soil samples were added to sodium acetate
 buffer (50 mM, pH 5) in the proportion of 1 g soil to 125 mL of buffer and
 the suspension was mixed for 1 min. For each enzyme, a 200 μL sample
 aliquot (pipetted during continuous stirring) was added to 50 μL of
 fluorogenic substrate. After incubation, 10 μL 1 M NaOH was added to stop
 the reaction and, after an additional 10 min, fluorescence was measured
 (excitation wavelength 365 nm, excitation slit 2.5, emission wavelength
 450 nm and emission slit 2.5) and related to 4-methylumbelliferone
 standards. Laccase activity was assessed by adding 100 μL
 of extract to 100 μL of reaction solution containing 50 mM
 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS) in
 sodium acetate buffer. Peroxidase activity was assessed via the oxidative
 coupling of 3-(dimethylamino)benzoic acid (DMAB) and
 3-methyl-2-benzothiazolinone hydrazine (MBTH) in the presence of Mn2+ and
 H2O2 (following protocols
 of Kyaschenko et al. 2017a). A 50 μL aliquot of extract was added to 150 μL
 of reaction solution (50 mM DMAB, 1 mM MBTH, 1 mM MnSO4, 100 mM sodium
 lactate, 100 mM sodium succinate, 67 μL H2O2, pH 5). Enzyme activities
 were estimated by regression of absorbance (laccase at 420 nm and
 Mn-peroxidase at 590 nm) against time. Boiled aliquots served as negative
 controls for all enzyme measurements.
description: All analyses were conducted in R version 4.1.0
 (R Core Team 2021) as
 described in the manuscript.