Broadening the Taxonomic Scope of Coral Reef Palaeoecological Studies

2 DR. MARIA DEL CARMEN GOMEZ CABRERA (Orcid ID : 0000-0001-9665-2123)

5 Article type : Original Article

8 Broadening the taxonomic scope of coral reef paleoecological studies using ancient DNA 9 10 Gomez Cabrera M d C1, Young J M2, Roff G1, Staples T1, Ortiz J C3, 1, Pandolfi John M1*, Cooper 11 A2* 12 13 1Australian Research Council Centre of Excellence for Coral Reef Studies, Centre for Marine 14 Science and School of Biological Sciences, The University of Queensland, Brisbane, QLD, 4072, 15 Australia 16 2Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, 5005, Australia 17 3Australian Institute for Marine Science, PMB No. 3, Townsville, QLD, 4810, Australia 18 19 * joint senior authors 20 21 Ancient DNA, environmental DNA, coral reef, macroalgae, marine paleoecology, metabarcoding 22 23 Running title: Ancient DNA from coral reefs Author Manuscript 24

This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/MEC.15038

This article is protected by copyright. All rights reserved 25 26 Corresponding author: 27 Maria del Carmen Gomez Cabrera. School of Biological Sciences, The University of Queensland, 28 Brisbane, QLD, 4072, Australia. email: [email protected]. Fax: +61 7 33654755 29 Abstract 30 Marine environments face acute pressures from human impacts, often resulting in substantial 31 changes in community structure. On the inshore Great Barrier Reef (GBR), paleoecological 32 studies show the collapse of the previously dominant coral Acropora from the impacts of 33 degraded water quality associated with European colonization. Even more dramatic impacts can 34 result in the replacement of corals by fleshy macroalgae on modern reefs, but their past 35 distribution is unknown because they leave no fossil record. Here we apply DNA metabarcoding 36 and High-Throughput Sequencing of the 18S rDNA gene on paleoenvironmental DNA (aeDNA) 37 derived from sediment cores at two sites on Pandora Reef (GBR), to enhance paleoecological 38 studies by incorporating key soft-bodied taxa, including macroalgae. We compared temporal 39 trends in this aeDNA record with those of coral genera derived from macrofossils. Multivariate 40 analysis of 12 eukaryotic groups from the aeDNA community showed wide variability over the 41 past 750 years. The occurrence of brown macroalgae was negatively correlated only with the 42 dominant coral at both sites. The occurrence of coralline and green macroalgae was positively 43 correlated with only the dominant coral at one of the sites, where we also observed a significant 44 association between the whole coral community and the occurrence of each of the 3 45 macroalgae groups. Our results demonstrate that reef sediments can provide a valuable archive 46 for understanding the past distribution and occurrence of important soft-bodied reef dwellers. 47 Combining information from fossils and aeDNA provides an enhanced understanding of 48 temporal changes of reefs ecosystems at decadal to millennial time-scales. 49 50 Introduction Author Manuscript 51 Coral reefs are among the most diverse marine ecosystems in the world (Leray & Knowlton 52 2016), providing resources to more than a billion people globally. Reefs also help shape the

This article is protected by copyright. All rights reserved 53 landscape, protect coastlines from erosion, and contribute to the maintenance of coastal 54 habitats, such as seagrass beds and mangrove communities (Costanza et al. 2014; Marre et al. 55 2016). These ecosystem services depend on healthy coral reefs, but these ecosystems 56 worldwide are experiencing decline due to local and global anthropogenic pressures that 57 threaten the capacity of coral reefs to recover after disturbances (Pandolfi et al. 2003; Ortiz et 58 al. 2018). 59 60 The declining ability of ecological communities to recover from human-induced disturbances is 61 now commonplace in marine ecosystems (Done 1992; Pandolfi et al. 2011). Both acute and 62 prolonged exposure to stress, including declining water quality due to intensive agriculture and 63 land clearing, overfishing, crown-of-thorns starfish predation, rising temperatures and ocean 64 acidification have resulted in increased bleaching, disease, and mortality of reef-building corals 65 (Pandolfi et al. 2003; Hughes et al. 2007; Pandolfi et al. 2011; Pandolfi 2015; Hughes et al. 66 2017). Differential mortality of many reef species results from these disturbances, changing not 67 only species composition and biodiversity but ecosystem function and the services coral reefs 68 provide (Bellwood et al. 2004, Mumby et al. 2007; Hughes et al. 2018). 69 70 Understanding the dynamics of coral reefs through time is important for understanding their 71 response to environmental change and thus predicting the future behaviour of these 72 ecosystems (Pandolfi et al. 2003; Cramer et al. 2012; Roff et al. 2013). Since reef-building 73 (scleractinian) corals leave a fossil record, paleoecological reconstructions of their past relative 74 abundances are a reliable proxy for coral community structure at centennial to millennial scales 75 (Pandolfi 1996; Cramer et al. 2012; Roff et al. 2013; Clark et al. 2014). We can also infer some 76 characteristics of these ancient environments using other reef organisms that leave a fossil 77 record, such as foraminifera and certain molluscs (Reymond et al. 2013; Cramer et al. 2015; 78 Narayan et al. 2015). Following European colonization in the late nineteenth century, coral Author Manuscript 79 dominance on inshore sites along the Great Barrier Reef (GBR) has shifted from fast-growing 80 competitive Acropora spp. to species more tolerant of turbid water such as fast-growing

This article is protected by copyright. All rights reserved 81 Pavona, and slow-growing Goniopora, and Porites, with reduced capacity for the maintenance 82 of reef complexity and ecosystem function (Roff et al. 2013; Ortiz et al. 2014; Clark et al. 2017). 83 84 Macroalgae are significant reef dwellers with important and varied interactions with reef corals. 85 Brown algae are fast-growing, rapid colonists that directly compete with corals for substrate 86 space, while crustose coralline algae facilitate the settlement of coral larvae (Heyward & Negri 87 1999; Birrell et al. 2008). Green macroalgae are composed of groups both detrimental to corals, 88 and those dependent upon corals for habitat (Jompa & McCook 2003). However, it has been 89 difficult to assess past changes in macroalgal community structure due to the absence, in most 90 groups, of calcified skeletons, resulting in limited historical or fossil data. A historical 91 perspective on community structure of macroalgae and other organisms that do not leave a 92 fossil record would vastly improve our understanding of past and present coral reef dynamics. 93 94 The study of past ecosystems has recently been enhanced by the incorporation of ancient DNA 95 signals from paleoenvironments (aeDNA) such as marine, lacustrine or terrestrial sediments, ice 96 and permafrost (Burbano et al. 2010; Rawlence et al. 2014; Willerslev et al. 2014; Cooper et al. 97 2015; Parks et al. 2015). The genetic diversity contained within these complex DNA mixtures can 98 be examined using DNA metabarcoding via High-Throughput Sequencing (HTS) (Orlando et al. 99 2015). Importantly, this molecular approach enables identification of organisms that leave a 100 poor or non-existent fossil record such as bacteria, fungi, algae, many plants, and soft-bodied 101 animals, ultimately allowing the exploration of ecological questions at a taxonomic and 102 functional scale far beyond observational/experimental data alone. 103 104 Here we use ancient paleoenvironmental DNA (hereafter aeDNA) from two reef sediment cores 105 to: 1) explore temporal trends in taxonomic composition of inshore reefs in the Great Barrier 106 Reef (GBR), Australia over centennial time scales, and 2) compare the history of macroalgal Author Manuscript 107 communities derived from aeDNA with the history of coral communities derived from fossil 108 corals. We chose to analyse two cores that showed contrasting histories of coral abundance,

This article is protected by copyright. All rights reserved 109 one where the fast-growing branching Acropora was the dominant coral, and one where the 110 dominant coral fluctuated through time, but the slower-growing, more sediment-tolerant 111 Goniopora was the most abundant coral throughout the time-series. 112 Marine sediment cores were analysed using DNA metabarcoding and HTS of the 18S rDNA gene 113 to estimate overall biodiversity from a preserved aeDNA community, and then to focus in on the 114 community structure of macroalgae communities over the past 750 years. Molecular 115 macroalgae composition data were correlated with contemporaneous coral community 116 composition data derived from macrofossils and the history of both groups was documented 117 through time. We found a large number of Operational Taxonomic Units (OTUs) derived from 118 aeDNA data, testifying to the potential for aeDNA of reef sediment cores to enhance our 119 understanding of temporal trends in biodiversity using reef sediment cores. We also found that 120 temporal patterns in the abundance of dominant corals in the fossil record were associated with 121 expected shifts in the relative abundance of macroalgal types derived from the aeDNA data. 122 123 Materials and methods 124 Study site 125 Pandora Reef is an inshore shallow platform reef of the Palm Island group located around 17 km 126 from the coast of Queensland, Australia in the central Great Barrier Reef (GBR) (Fig. 1). It is 127 influenced by sediment and contaminant-laden flood plume waters from the Burdekin River, 128 located about 130 km to the southeast and the Herbert River located about 25 km to the north 129 (Done et al. 2007; Kroon et al. 2012; Roff et al. 2015; Clark et al. 2017). The reef has been 130 described as a turbid-water patch reef since it is periodically exposed to sediment and nutrient 131 influx from these rivers (Done et al. 2007). 132 133 Sample collection 134 Modern samples Author Manuscript 135 In order to establish a suite of present day OTUs to compare with the ancient eDNA, we 136 collected modern sediment samples in the same places where we extracted reef sediment

This article is protected by copyright. All rights reserved 137 cores. The suite of OTUs that could be identified from a similar sample of modern eDNA from 138 sediment gives some understanding of the reliability of the metabarcoding method in coral reef 139 environments and places the results of the metabarcoding of the aeDNA into context. Modern 140 sediment from three locations from two sites were sampled where reef sediment cores were 141 previously collected on Pandora Reef (mPAN1-A, mPAN1-B and mPAN3, see Ancient samples for 142 coordinates). In the site associated with sediment core PAN1, surface sediment samples were 143 collected from two adjacent areas 10m apart, while in the site associated with PAN3, a single 144 sediment sample was collected. All samples were collected using sterile 50 mL Falcon tubes. 145 Each sample was centrifuged (4500 rpm for 3 mins) to settle resuspended sediment. 250 mg of 146 sediment from each of these samples was added to separate bead tubes provided in the 147 PowerLyzer DNA Isolation kit (MOBIO, Carlsbad, CA, USA) and processed following the 148 manufacturer’s protocol. 149 150 Ancient samples 151 Two reef-matrix cores (PAN1 and PAN3) were collected on the leeward side of Pandora Reef

152 (18°48’45”S 146°25’59”E) in 2007 as part of a larger project examining temporal patterns in 153 coral community structure of inshore coral reefs in the central GBR at decadal to millennial 154 scales before and after European colonization of the Queensland coastline (Roff et al. 2015; 155 (Roff et al. 2013; Clark et al. 2014). Cores were extracted from back reef locations at 5 m water 156 depth in an attempt to minimize wave energy, and thus lateral sediment mixing. We chose two 157 cores for our ‘proof-of-concept’ study based on contrasting trends in fossil coral relative 158 abundance patterns. In core PAN1, a mixed coral assemblage was replaced about 1/3 of the 159 way upcore by an Acropora-dominated coral assemblage. Acropora is a competitive, fast- 160 growing coral sensitive to turbidity. In core PAN3, coral dominance fluctuated between 161 Acropora, Goniopora, and Pavona, with slow-growing, sediment-tolerant, Goniopora as the 162 most abundant coral throughout the core. Author Manuscript 163

This article is protected by copyright. All rights reserved 164 Cores were extracted using SCUBA by inserting a 10 cm diameter, 5 m long aluminium tube in 165 the reef sediment using an open-barrel push-core technique at 5 m water depth on the reef 166 slope. 3-dimensional images of the cores were obtained using a CT scan (Lightspeed VCT, 167 General Electric Healthcare) before sectioning the cores longitudinally. One half of the core was

168 archived (covered in plastic wrap to avoid desiccation and placed in storage at 4°C) for 169 subsequent DNA analysis. Together with CT images, the fossil coral community was 170 reconstructed from coral fragments obtained at 5 cm intervals from the working half of the 171 core. Core chronologies and accretion rates were determined from U-series dating of coral 172 fragments (Roff et al. 2015). 173 174 Duplicate sediment samples (of approximately 1 g) were extracted at 20 cm intervals along the 175 length of each of the archived cores. Collection of the sediment occurred in a clean room at The 176 University of Queensland, not associated with a facility where DNA is processed. Samples were 177 collected sequentially from the bottom (oldest) to the top (youngest) of the core to prevent 178 contamination of older samples with younger DNA. After discarding the outermost 2-3 cm of 179 the core surface at individual sample points, sediment was collected from the inner part of the 180 core using a fresh sterile disposable spatula and placed in individual DNA-free sample tubes. 181 These tubes were stored at 4oC until aeDNA extractions were performed. 250 mg of sediment 182 was processed at each core interval in duplicate using the PowerLyzer DNA Isolation kit (MOBIO, 183 Carlsbad, CA, USA), following the manufacturer’s instructions. For all DNA extractions, including 184 modern surface samples, extraction blank controls (EBCs), which contained no sediment, were 185 processed in parallel with samples to monitor background DNA levels from laboratory reagents. 186 To avoid contamination with modern DNA, extractions and subsequent PCR amplification, DNA 187 libraries, and sequencing were performed in the purpose-built laboratories of the Australian 188 Centre for Ancient DNA (ACAD). 189 Author Manuscript 190 PCR amplification and library preparation

This article is protected by copyright. All rights reserved 191 All DNA extracts and environmental blank controls (containing no sample) were amplified using 192 universal eukaryote 18S rDNA primers that have been modified to include Illumina sequencing 193 adapters and a unique sample specific 12 bp Golay barcode in the reverse primer (in 194 bold):1391F_Euk forward primer, 5’- AATGATACGGCGACCACCGAGATCTACAC TATCGCCGTT CG 195 GTACACACCGCCCGTC-3’; EukBr reverse primer 3’-; 196 CAAGCAGAAGACGGCATACGAGATnnnnnnnnnnnnTCCCTTGTCTCCAGTCAGTCAGCATGATCCTTCT 197 GCAGGTTCACCTAC -5’). This primer set amplifies a ~200 bp target sequence. PCR amplifications

198 were performed in a 25 μL reaction mix containing 2.5 mM MgCl2, 0.24 mM dNTPs, 0.24 μm of 199 each primer, 0.4 mg/μL bovine serum albumin, Invitrogen Platinum HiFi Taq polymerase in 10x 200 reaction buffer (Applied Biosystems, Melbourne Australia), and 2 μL DNA extract. The PCR 201 protocol included the following parameters: 9 mins at 94oC, followed by 35 cycles of 94oC for 30 202 sec, 57oC for 20 sec, and 72oC for 30 sec, and a final extension at 72oC for 7 mins. PCR 203 amplifications were performed in triplicate and pooled to minimise PCR bias, and a no-template 204 PCR amplification control was included to monitor background DNA levels in PCR reagents. 205 Triplicate PCR products were pooled and purified using an Agencourt AMPure XP PCR 206 Purification kit (Beckman Coulter Genomics, NSW), and each was quantified using the HS dsDNA 207 Qubit Assay on a Qubit 2.0 Fluorometer (Life Technologies, Carlsbad, CA, USA). Purified PCR 208 products from all samples (n=93) were pooled to equimolar concentration, and the library was 209 diluted to 2nM and sequenced using a 300 cycle, 2x150bp Illumina MiSeq kit. 210 211 DNA sequencing data was de-multiplexed according to the unique index sequence assigned to 212 individual samples using CASAVA version 1.8.2 213 (http://support.illumina.com/sequencing/sequencing_software/casava.ilmn). As the barcode 214 indices were separated by ≥2 bp, sequences with one index mismatch were retained at this 215 step. Cutadapt v.1.1 was then used to remove sequencing adapters and discard sequences less 216 than 100 bp. Low quality sequences (less than Q20 over 90% of the sequence) were excluded Author Manuscript 217 using fastx toolkit v.0.0.14 (http://hannonlab.cshi.edu/fastx_toolkit). Remaining sequences 218 were then formatted for use with QIIME v.1.8.0 (http://genomics.azcc.arizona.edu/help.php3),

This article is protected by copyright. All rights reserved 219 where sequences with greater than 97% similarity to the SILVA v104 reference database were 220 binned into Operational Taxonomic Units (OTUs) using open reference clustering in UCLUST. A 221 set of representative sequences was generated by selecting the most abundant sequence to 222 represent that OTU. The number of sequences per sample ranged from 7220 (P3.EBC3) to 223 243,416 (P3.3B). OTUs detected in the EBCs were removed from the experimental samples to 224 ensure only OTUs native to the samples were included, and only OTUs that were classified as 225 “Eukaryotic” were included in the final OTU dataset. 226 227 The resulting dataset was split into three OTU taxonomy tables (modern, PAN1 and PAN3) and, 228 for each dataset, all samples were rarefied to an even sequencing depth before comparing 229 them. Further filtering of the dataset was carried out to include only OTUs with known 230 ecological behaviour. For example, organisms such as marine fungi, amoebas and other 231 unicellular organisms were excluded due to a lack of ecological information. Similarly, OTUs 232 classified as unknown eukaryotes could not be assigned to a particular taxonomic group and 233 were also excluded. As a result of these filtering steps, samples P1.4b.0 and P1.4b.100 (Tables 1 234 and 2) were excluded from the dataset, as these predominantly consisted of unknown 235 eukaryotic organisms or fungi. 236 237 Data analysis 238 To establish the degree to which aeDNA community composition varied through time, a 239 multivariate distance-based linear model (DistLm) was performed using a presence/absence 240 matrix extracted from the OTU matrix of 18S rDNA taxonomic groups retrieved from each core 241 as the multivariate response and time (years ago) as the explanatory variable. To visualise the 242 temporal patterns in community composition, a Principal Coordinates Ordination (PCO) plot was 243 used for each core. Contour lines were drawn around clusters of samples from time points that 244 shared at least 40% similarity. Every sample within each core was compared to every other Author Manuscript 245 sample using the Bray-Curtis similarity index. 246

This article is protected by copyright. All rights reserved 247 To evaluate if temporal differences in the coral community composition observed in the fossil 248 record are contemporaneous with differences in the relative abundance of OTUs from the 249 aeDNA, we used a Relate Test (non-parametric Mantel Test) using the Bray-Curtis similarity 250 index for both matrices. 251 252 To explore the potential association between the coral community composition (relative 253 abundance of 13 to 16 coral taxa derived from the fossil record) and the relative abundance of 254 the three macroalgae taxa that have ecologically relevant interactions with corals (Corallinales – 255 crustose coralline algae; Chlorophyta – green algae; Phaeophyceae – brown algae; derived from 256 the aeDNA data), we used another multivariate linear model using permutations to evaluate 257 significance (DistLm) for each core. The multivariate response variable was the relative 258 abundance of the fossil coral genera. The explanatory variables were the relative abundance of 259 each of the 3 algal groups described above. Coral relative abundance data was determined 260 through taxonomic dry weight of fossil skeletons (coral genus) within each 5 cm core section 261 and expressed as a proportion of total dry weight of all coral genera per 5 cm core section (Roff 262 2010). Macroalgae relative abundance was calculated as the occurrence of individual 263 macroalgae OTUs within each 5 cm core section expressed as a proportion of the total number 264 of macroalgae OTUs representing the three macroalgae groups in each sample. To evaluate any 265 association between specific coral species and the relative abundance of each of the three 266 macroalgal groups, we calculated the Pearson correlation coefficient between the relative 267 abundance of each of the three macroalgae groups and each one of the coral genera found in 268 the fossil record of the cores. 269 270 We estimated trends in the relative abundance of taxa over time using two generalized additive 271 models (GAM: mgcv package (Wood 2011)). We modeled each of the two cores separately, but 272 each model included the aeDNA relative abundance of all three algae taxa groups (Chlorophyta, Author Manuscript 273 Corallinales and Phaeophyceae) as well as the fossil coral relative abundance of the dominant 274 coral genus (Acropora and Goniopora in PAN1 and PAN3, respectively). Only the dominant coral

This article is protected by copyright. All rights reserved 275 genus was used since these were the only ones that showed significant Pearson correlation 276 coefficients with the three macroalgal groups. As our response variable, relative abundance, 277 was bound between zero and one, we fit models using beta errors and logit link function, 278 transforming relative abundances of exactly zero or one as Y = (y * (n − 1) + 0.5) / n) (Smithson & 279 Verkuilen 2006). These models contained two fixed effects. Years before present was included 280 as a continuous fixed effect, fit as sets of four cubic regression spline with knots determined by 281 generalized cross validation. Taxa was included as a four-level factor to estimate taxa-specific 282 intercepts, and separate splines were fit to each taxa. The multivariate analysis was conducted 283 using Primer, and the correlations and GAMs were conducted in R. 284 285 Results 286 Coral macrofossil trends 287 The coral macrofossil community composition was previously censused on a 5 cm scale (Roff 288 2010; Roff et al. 2013). Coral community composition from reef sediment core PAN1 was more 289 variable through time than that from PAN3. The most abundant coral genus from PAN1 was 290 Acropora, followed by Montipora, but PAN3 was dominated by the coral genus Goniopora, 291 followed by Pavona (Figs. 2 and 3). 292 293 Temporal trends in 18S rDNA derived from aeDNA 294 Among all sample locations (mPAN1-A, mPAN1-B and mPAN3), 204 OTUs were recovered from 295 the modern sediment, with an average of 128 OTUs per location. All of the sediment samples 296 taken from the two cores (PAN1 and PAN3) yielded aeDNA. We found 97 OTUs in core PAN1 297 and 122 OTUs present in PAN3. Out of the 204 taxa derived from the modern sediment data, we 298 identified a subset of twelve taxonomic groups known to occur on coral reefs or similar marine 299 environments, that also occurred in the sediment cores: Dinophycea planktonic, Dinophycea 300 benthonic, Bryozoa, Tunicata, Hexacorallia, Octocorallia, Porifera, Rizaria, Rhodophyta Author Manuscript 301 (Corallinales – coralline algae), Chlorophyta (green algae), Diatoms, and Phaeophyceae (brown 302 algae), and provide their relative abundance throughout each core (Figs. 2, 3; Tables 1, 2). Three

This article is protected by copyright. All rights reserved 303 samples from PAN1 and one sample from PAN3 were excluded from further analysis based on 304 the absence of aeDNA from any of these taxonomic groups. aeDNA from Hexacorallia (including 305 the reef-building scleractinian corals) was very low, but aeDNA was derived from three of the 306 major macroalgae groups inhabiting Pandora Reef. 307 308 Time (numbers of years ago) was not a significant predictor of the multivariate dispersion 309 observed in the aeDNA community structure in PAN1 (DistLm r2 = 0.12, p = 0.107, Fig. 4a), but 310 explained 44% of the multivariate dispersion of the aeDNA community structure of PAN3 311 (DistLm r2 = 0.442, p = 0.001, Fig. 4b). Two clusters were evident in the ordination plot (PCO) for 312 PAN3, one comprising samples 400-600 years old and closely related to the occurrence of 313 Phaeophyceae, and a second cluster comprising samples from younger ages and related to the 314 occurrence of a large group of other taxa including Hexacorallia, which aligns opposite to 315 Phaeophyceae (Fig 4b). No temporal groupings were obvious from the ordination of the PAN1 316 aeDNA communities (Fig. 4a). 317 318 Results from the Mantel Relate tests showed that temporal changes in the coral community 319 composition derived from the fossil record were highly correlated with the those observed from 320 the whole taxa relative abundances (derived from aeDNA) in PAN3 (Rho=0.294; p=0.01), but not 321 in PAN1 (Rho=-0.15; p=0.208). We used DistLm to investigate the association between the fossil 322 coral community composition and the relative abundance of each group of algae found in the 323 aeDNA community (coralline, green and brown algae). For one of the cores (PAN3) we found a 324 significant non-metric correlation between the whole coral community composition and each 325 algal type (Table 3). We calculated Pearson correlation coefficients between the relative 326 abundance of each individual coral genus obtained from fossil coral samples (Table 3) and the 327 relative abundance of each of the three macroalgae groups derived from aeDNA. For PAN1, 328 where Acropora is dominant, we found a significant negative correlation only between it and Author Manuscript 329 brown algae (Table 3). For PAN3, where Goniopora is dominant, we found a significant positive 330 correlation only between it and both coralline and green algae, but a negative correlation

This article is protected by copyright. All rights reserved 331 between this coral only and brown algae (Table 3). The temporal trends in relative abundance of 332 the dominant coral from each core (supported by the GAM model results) are consistent with 333 the Pearson correlation results, with the relative abundance of Acropora from PAN1 (Fig. 5a) 334 and Goniopora from PAN3 (Fig 5b) increasing through time as the relative abundance of brown 335 macroalgae decreases (Table S1). Similarly, the relative abundance of both the coralline and 336 green algae increase through time in both cores (Fig 5; Tables S1 and S2). 337 338 Discussion 339 Ancient environmental DNA is becoming increasingly used as a tool to understand past 340 environments (Pedersen et al. 2014; Sarkissian et al. 2017), address important ecological and 341 evolutionary questions over expanded temporal frames (Rawlence et al. 2014; Hofreiter et al. 342 2015; Orlando et al. 2015), estimate biodiversity (Willerslev et al. 2014) and detect cryptic or 343 rare (Orlando et al. 2013; Malaspinas et al. 2014) and invasive species from sediment or water 344 samples (Martin et al. 2013; Pedersen et al. 2013). Our results indicate that incorporating 345 ancient DNA in the form of paleoecological environmental DNA (aeDNA) data in traditional 346 paleoecological studies of coral reefs represents a significant development for understanding 347 the historical ecological role of coral reef organisms that do not leave a fossil record. 348 349 Assessing biodiversity using aeDNA & eDNA from coral reef sediments 350 In the modern and ancient environmental DNA, we found 12 marine taxonomic groups that 351 inhabit the reef (Tables 1 and 2). The major component of the OTUs was protist DNA (e.g. 352 dinoflagellates, foraminifera), and only a small proportion of it was multicellular eukaryote DNA 353 (e.g. tunicates, algae). Although 18S rDNA is one of the most commonly used markers in 354 biodiversity studies (Meyer et al 2010), many marine eukaryotes still lack a reference database. 355 For example, roughly half of the ~1.1 million 18S rDNA sequences in GenBank (accessed 14 356 September 2018) originate from terrestrial fungi while only about 100,000 originate from Author Manuscript 357 marine organisms, about 30% of which belong to uncultured and unidentified marine

This article is protected by copyright. All rights reserved 358 eukaryotes. This lack of reference databases limits the ability to match OTUs to specific taxa and 359 is a recurrent problem in biodiversity studies of marine environments (Stat et al. 2017). 360 361 The temporal distribution of the 12 taxonomic groups varied between the two cores. In PAN1 362 there were no trends in the presence of these taxa through time (Fig 4a). In contrast, two 363 discrete temporal groupings characterized PAN3 with the brown algae (Phaeophyceae) driving 364 community composition of samples older than 300 years and other taxa, including Hexacorallia, 365 driving community composition after this time (Fig 4b). One possible explanation for this 366 pattern is differential preservation of aeDNA among taxa. If brown algae DNA preserves better, 367 it is possible that the lack of the other taxa in the older periods for PAN3 may not be ecologically 368 relevant. However, the fact that the aeDNA community of PAN1 during the same older period is 369 diverse and encompasses taxa absent in PAN3 suggests that the observed pattern in PAN3 may 370 reflect real changes in community composition. Moreover, the decreasing trend in relative 371 abundance of brown algae through time at the same time that Hexacorallia relative abundance 372 increases (Fig 4b), corroborates results from the ordination (Fig. 5). Another explanation is the 373 expected patchy distribution of reef communities at the spatial scale of our studied cores. For 374 the fossil coral data, multiple cores from individual sites produced consistent patterns of 375 community structure through time (Roff et al. 2013). Future studies of our aeDNA communities 376 with replicate cores will help resolve the spatial scales at which reef communities varied 377 through time. Overall, the fact that at least for one of the cores (PAN3) there was a strong 378 correlation in the temporal patterns of similarity between the fossil coral and aeDNA 379 community structure, demonstrates the potential for: 1) congruence between fossil and 380 molecular approaches, and 2) aeDNA approaches to detect ecologically relevant patterns in past 381 coral reef communities. 382 383 Algae DNA was present in most samples; this is encouraging, since one of the motivations for Author Manuscript 384 this study was to find an alternative method to investigate past distributions of organisms that 385 do not leave a fossilized skeleton in the geological record, such as fleshy macroalgae that

This article is protected by copyright. All rights reserved 386 compete directly with corals for space on the reef (Figs. 2, 3). The recovery of non-coralline red 387 algae aeDNA was very poor; in both cores it was only recovered in the most recent sample (1 of 388 16 samples for PAN1, and 1 of 17 for PAN3). In contrast, aeDNA from coralline, green and brown 389 algae was recovered throughout both cores: in 7, 10 and 10 of the 16 samples, respectively, in 390 PAN1, and in 6, 10 and 6 of the 17 samples, respectively, in PAN3. The degree to which this 391 differential preservation of algal groups represents real differences in community composition 392 or is the result of amplification bias can be evaluated in future studies both experimentally, and 393 through the use of more specific primers than were used in the present study (Rawlence et al. 394 2014; Furlan et al. 2016). 395 396 One surprising result is that aeDNA from corals, which have a large and important presence in 397 coral reefs ecosystems, was not well represented in the OTUs we derived from the coral reef 398 sediment samples, especially in comparison to their robust fossil record. Although a number of 399 other taphonomic and metagenomic effects could contribute to this (see below section on 400 ‘Limitations’), it is also conceivable that the actual amount of coral tissue that is shed into the 401 environment is smaller relative to other fleshier organisms such as macroalgae or sponges 402 (Vandenhoek et al. 1978; Littler et al. 1991; Duarte & Cebrian 1996). Moreover, due to the 403 symbiotic nature of corals, a substantial proportion of this tissue is actually the dinoflagellate 404 family Symbiodiniaceae (Fitt et al. 2000; Lajeunesse et al. 2018). Cells in the coral endoderm can 405 harbour from 1 to 6 Symbiodiniaceae cells (Muscatine et al. 1998), and symbionts comprise at 406 least 15% of the cells in the coral tissue (Mieog et al. 2009). We retrieved a large proportion of 407 aeDNA from planktonic and benthonic Dinophyceae (Figs 2, 3), the group to which 408 Symbiodiniaceae belongs. Although our method did not allow for a finer breakdown of 409 Dinophyceae (see more detail in the ‘Limitations’ section below), it is clear that this group was 410 better represented by the aeDNA than were corals. Many dinoflagellates, including 411 Symbiodiniaceae, compress their DNA into a crystal structure, making it highly resistant to Author Manuscript 412 decomposition (Bouligand & Norris 2001). As such, it is not surprising that the Dinophyceae are

This article is protected by copyright. All rights reserved 413 well represented through time. Thus, the coral macrofossil record provides more information on 414 past coral community composition than coral aeDNA. 415 416 Temporal dynamics of macroalgae inferred from aeDNA and corals inferred from macrofossils 417 The detection of fleshy macroalgae (seaweed) in past reefs using aeDNA from reef sediment 418 cores provides a unique opportunity to compare their long-term community dynamics with 419 those of reef corals derived from the macrofossil record. One of the reef sediment cores (PAN3) 420 showed an overall slight but significant relationship between the relative abundance of all coral 421 genera derived from the macrofossils and the relative abundance of each of the three groups of 422 macroalgae derived from aeDNA (Table 3). This is not surprising, as all three algal groups are 423 known to have a variety of biotic interactions with reef corals on modern reefs. We further 424 explore the nature of these interactions in the context of the relationship between the relative 425 abundance of each group of algae and that of the individual reef corals. 426 427 Consistent across both of the cores was an inverse relationship between the relative abundance 428 of brown algae and the dominant coral: Acropora in PAN1 and Goniopora in PAN3 (Table 3; Fig. 429 5). None of the other coral genera showed any association with the relative abundance of any 430 of the algae, in either core. Fleshy brown algae compete heavily with corals for space on coral 431 reefs, and when disturbance results in high coral mortality, they have the ability to swiftly 432 colonize substrate left vacant (a process known as ‘regime shift’ or ‘phase shift’: Hughes 1994; 433 Ninio et al. 2000; Hughes et al. 2007). The degree to which these phase shifts have occurred in 434 the past is unknown, principally because of the lack of fleshy macro-algae preserved in the fossil 435 record. At present we are unable to ascribe the inverse relationship in relative abundance 436 between the dominant coral and brown macroalgae to a phase shift, as the relative abundances 437 of the two groups of organisms were derived from two separate data sets. Moreover, estimates 438 of total abundance could not be made with the aeDNA techniques we employed, and it is Author Manuscript 439 problematic to interpret benthic cover in past reef settings even using fossils. Regardless, our 440 detection of fleshy macro-algae in past reefs using aeDNA in the reef sediment cores provides a

This article is protected by copyright. All rights reserved 441 rare glimpse into how the relative abundance of coral genera and brown macroalgae varied 442 over time. This represents the first time that paleoecological changes in coral abundances have 443 been (negatively) associated with changes in the relative abundance of brown algae (Table 3; 444 Fig. 5). 445 In the same core where we found a statistical association between coral community structure 446 and macroalgae relative abundance (PAN3), we also found a positive correlation between both 447 coralline and green algae vs coral abundance (Table 3; Fig. 5). Reef habitats with abundant 448 coralline algae are generally associated with high coral cover, since they enhance settlement of 449 both corals and other invertebrates (Goreau 1963; Heyward & Negri 1999; McCook et al. 2001). 450 The primary productivity of these algae is also important in maintaining the structure of reefs, 451 since they make a large contribution to inorganic reef production and they help to bind the reef 452 in place, facilitating reef accretion (Chisholm 2003). In contrast, the relationship between green 453 algae and corals on living reefs is complex, with some algal species harmful to coral growth and 454 others benefiting from complexity in coral-dominated habitats (Jompa & McCook 2003). The 455 findings of associations between macroalgae and corals are encouraging, and we plan further 456 studies to specifically target ancient macroalgae DNA by employing specific primers with the 457 goal of understanding macroalgal dynamics at lower taxonomic levels. 458 459 Our analysis of trends in aeDNA provide essential temporal context for understanding the long- 460 term ecological dynamics of important components of the coral reef ecosystem that do not 461 leave behind a fossil record. Future studies will encompass a more intensive sampling regime of 462 the aeDNA (for example, matching the coral fossil sampling effort every 5 cm along the cores 463 and sampling more cores) and target specific taxa at lower taxonomic scales to reconstruct 464 historical trajectories of macroalgae and other soft-bodied organisms. This study opens a 465 previously undeveloped research avenue, and broadens our taxonomic scope to explore 466 patterns of ecological change at centennial to millennial scales on coral reefs. Author Manuscript 467 468 Limitations

This article is protected by copyright. All rights reserved 469 Many previous studies of paleoenvironmental DNA (aeDNA) have focussed on environments 470 with “ideal” conditions for the preservation and ultimate recovery of aeDNA such as high 471 latitude (frozen/cold) environments, low energy anoxic lake sediments or very stable deep sea 472 habitats (Corinaldesi et al. 2011; Pedersen et al. 2013; Danovaro et al. 2014; Rawlence et al. 473 2014). However, technical advances now allow the recovery of aeDNA from a variety of 474 microenvironments, including archaeological sites (da Fonseca et al. 2015). The high-energy 475 environments of shallow water tropical coral reefs would seem far from ideal to preserve 476 aeDNA. However, we recovered a large number of OTUs that are resident on coral reefs from at 477 least 750 years ago. This aeDNA was extracted from our sediment cores even though they were 478 collected and archived for several years prior to analysis. The aeDNA community composition 479 did not vary sequentially through time (samples from PAN3 cluster in two temporal groups, and 480 samples from PAN1 show no temporal trend) arguing against progressive aeDNA degradation 481 through time as a driver of the relative abundance of taxa derived from aeDNA in these young 482 coral reef samples (Fig. 4). 483 484 One of the biggest challenges in aeDNA research is assessing the extent to which taphonomic 485 processes (i.e. biological and physical processes that act to bias ecological information and occur 486 during the timespan from the death of the organism until aeDNA extraction) affect the recovery 487 of aeDNA differentially among taxa. Multiple studies show taxonomic bias, as the recovery of 488 aeDNA is not uniform among taxa due to a variety of post-mortem biotic and abiotic processes 489 (Corinaldesi et al. 2008; Gansauge & Meyer 2013, Birks & Birks 2016). In Quaternary floras, 490 these affect the transportation, incorporation, and preservation of aeDNA in sediments (Birks & 491 Birks 2016). For mammal bones, the propensity for tissues and environments to create closed 492 systems appears to be of greater importance than the absolute age of the aeDNA (Kistler et al. 493 2017). To date there is little knowledge of how taphonomic processes affect the preservation of 494 aeDNA from aquatic habitats, though assemblages derived from aeDNA have been shown to be Author Manuscript 495 stable over decadal timescales in lake sediments (Capo et al. 2017). 496

This article is protected by copyright. All rights reserved 497 There are several processes that occur in high-energy shallow reef settings that need to be 498 considered in assessing aeDNA content of reef sediments. Sediment reworking has the potential 499 to quickly degrade aeDNA within the sediment or lead to lateral or vertical mixing of aeDNA. 500 Sediment transported from river plumes may bring terrestrial DNA from the surrounding 501 catchment, as may occur in lake sediments (Parducci et al. 2017). In our study, sediment plumes 502 from flooded coastal rivers commonly reach the nearshore reefs of Pandora reef in the Palm 503 Islands. It is certain that these plumes bring DNA from terrestrial organisms with them and did 504 so throughout the time frame of this study. To counteract the inclusion of these organisms into 505 our analysis, we specifically excluded from the analysis any aeDNA from groups with no marine 506 representatives, since our primary interest was to describe the in situ coral reef community. 507 However, lateral mixing may still occur through local currents that transport DNA across reef 508 habitats or sites (Kelly et al. 2018). Moreover, we have presented data from just 2 sediment 509 cores as a proof-of-concept; given the different patterns exhibited by PAN1 and PAN3, more 510 replication at the level of cores should increase confidence in the strength of our approach. 511 512 Vertical migration of aeDNA can also occur within the reef sedimentary body, not only through 513 leaching, but also through vertical mixing of older deposits through post-depositional processes 514 such as storms and bioturbation. To limit these issues, we targeted study sites from back reef 515 locations with low wave energy where both lateral and vertical post-depositional mixing was 516 minimal: our cores showed no evidence of re-working, storm deposits or bioturbation. 517 Importantly, U-series radiometric age dates were sequential through the cores (no age 518 reversals), and active reef accretion was continuous throughout the time series (Roff et al. 519 2015). However, while sediment turnover does not exist on the scale of coral fragments > 4 mm 520 diameter, dissolved organic matter has the potential to diffuse through pore waters into deeper 521 sediment layers, as shown for caves by Haile et al. (2007). But it is also true that aeDNA tends to 522 adsorb to sediment particles, providing some sort of protection from aeDNA diffusion to older Author Manuscript 523 sedimentary layers (Torti et al. 2015). Given these issues and the nature of our study system, we

This article is protected by copyright. All rights reserved 524 believe that most of the aeDNA present in our samples is derived locally, and should represent 525 the composition of the local coral reef community. 526 527 Finally, limitations associated with metabarcoding analysis can also introduce bias. Limited 528 availability of aeDNA templates and differential amplification of particular DNA templates can 529 cause false positives/negatives (Leonardi et al. 2017). Because these methods require high- 530 quality databases for comparison, the lack of genetic information about the vast majority of 531 coral reef organisms (Carugati et al. 2015; Leray & Knowlton 2016) presently limits our studies 532 to well-known components of the reef, such as the macroalgae studied here. There are a 533 number of procedures that could be used in the future to enhance recovery of taxa obtained 534 from our aeDNA libraries, including selective enrichment of target DNA and shotgun 535 metagenomics (Orlando & Cooper 2014; Alberdi et al. 2018). 536 537 There are a number of approaches that can be used in the future to improve the use of aeDNA 538 in the paleoecological reconstruction of coral reefs. Future studies would benefit from more 539 intensive sampling of the aeDNA to match the coral fossil sampling effort. This will allow direct 540 comparison of the taxonomic overlap between fossil and aeDNA records, which will add an 541 extra layer of confidence and nuance to the use of aeDNA in coral reef ecosystems. Further 542 work should also target specific taxa to reconstruct historical trajectories of coral and 543 macroalgae species and other soft-bodied organisms to enhance our knowledge of ancient reef 544 ecosystems, by incorporating additional biomarkers such as COI for invertebrate metabarcoding 545 and chloroplast markers such as rbcL for algae metabarcoding. Including selective enrichment 546 (‘Baits’) of degraded or damaged DNA can also help in targeting specific aeDNA and assist with 547 the amplification of difficult taxa. 548 All Illumina MiSeq raw sequence data and the taxonomy tables for the cores as well as for the 549 modern samples are available through the UQ eSpace, URL Author Manuscript 550 https://espace.library.uq.edu.au/view/UQ:e4e2535 DOI: https://doi.org/10.14264/uql.2019.2

551

This article is protected by copyright. All rights reserved 552 Acknowledgments. We acknowledge funding from the ARC Centre of Excellence for Coral Reef 553 Studies and the National Environmental Research Program, where the ideas for this work were 554 developed. Dr Cynthia Riginos and Karin Zwiep provided helpful comments. We also 555 acknowledge the constructive comments from three anonymous reviewers.

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This article is protected by copyright. All rights reserved 768 Roff, G., Zhao, J. X., & Pandolfi, J. M. (2015). Rapid accretion of inshore reef slopes from the 769 central Great Barrier Reef during the late Holocene. Geology, 43(4), 343-346. 770 doi:10.1130/g36478.1 771 Sarkissian, Der, C., Pichereau, V., Dupont, C., Ilsøe, P. C., Perrigault, M., Butler, P., et al. (2017). 772 Ancient DNA analysis identifies marine mollusc shells as new metagenomic archives of 773 the past. Molecular Ecology Resources, 17(5), 835–853. http://doi.org/10.1111/1755- 774 0998.12679 775 Smithson M, Verkuilen J (2006). "A Better Lemon Squeezer? Maximum-Likelihood Regression 776 with Beta-Distributed Dependent Variables." Psychological Methods, 11 (1), 54–71. 777 Stat, M., M. J. Huggett, R. Bernasconi, J. D. DiBattista, T. E. Berry, S. J. Newman, E. S. Harvey and 778 M. Bunce (2017). Ecosystem biomonitoring with eDNA: metabarcoding across the tree of 779 life in a tropical marine environment. Scientific Reports, 7, 12240. 780 Torti, A., Lever, M. A., & Jorgensen, B. B. (2015). Origin, dynamics, and implications of 781 extracellular DNA pools in marine sediments. Marine Genomics, 24, 185-196. 782 doi:10.1016/j.margen.2015.08.007 783 Vandenhoek, C., Breeman, A. M., Bak, R. P. M., & Vanbuurt, G. (1978). Distribution of algae, 784 corals and gorgonians in relation to depth, light attenuation, water movement and 785 grazing pressure in fringing coral reefs of Curacao, Netherlands Antilles. Aquatic Botany, 786 5(1), 1-46. doi:10.1016/0304-3770(78)90045-1 787 Willerslev, E., Davison, J., Moora, M., Zobel, M., Coissac, E., Edwards, M. E., . . . Taberlet, P. 788 (2014). Fifty thousand years of Arctic vegetation and megafaunal diet. Nature, 789 506(7486), 47-+. doi:10.1038/nature12921 790 Wood, S.N. (2011) Fast stable restricted maximum likelihood and marginal likelihood estimation 791 of semiparametric generalized linear models. Journal of the Royal Statistical Society (B) 792 73(1), 3-36. 793 Author Manuscript

794 Table 1. Matrix of taxonomic groups in each sediment sample in PAN1. Values are the relative 795 abundances of different taxa used in the aeDNA analysis.

This article is protected by copyright. All rights reserved Dinophyc Bryo Tunic Dista eae Dinophyc zoa ata Hexacor nce plankton eae (mos (incl allia Octocor Rhizaria Bacilla Coralli from (plankton benthos s udes (include allia Porif (include riophy nales Chlorop Phaeoph core ic (benthic anim sea s stony (include era s ceae (coralli hyta yceae Sampl top dinoflage dinoflage als) squir corals) s sea (spo foramin (Diato ne (green (brown e (cm) llates) llates) ts) fans) nges) ifers) ms) algae) algae) algae) P1.4a

.140 0 35.63 0 0.57 0.57 0 0 1.44 0 1.44 49.71 10.34 0.29

P1.4a 58.6 .120 20 3.45 0 0 3.45 0 0 2 3.45 3.45 13.79 13.79 0

P1.4a 25.8 .100 40 10.48 0 3.23 0 1.61 11.29 1 8.87 0 18.55 14.52 5.65 P1.4a

.80 60 90 0 0 0 0 0 0 10 0 0 0 0

P1.4a 68.3 .60 80 14.39 0.719 5 3.6 0.72 0.72 0 0 0 10.79 0.719 0 P1.4a

.40 100 0 41.38 0 0 0 0 1.72 1.73 0 0 0 55.17 P1.4a

.20 120 71.94 0 4.35 0 2.77 0 3.95 0 0 11.07 1.98 3.95 P1.4a

.0 140 50 0 0 0 0 10 20 3.33 0 0 16.67 0

P1.4b 25.6 .140 160 51.38 0 9 0.92 0.92 0 0.92 0 0 0 8.26 11.93 P1.4b

.120 180 0 0 0 0 0 0 9.38 0 0 28.13 9.38 53.13 P1.4b

.100 200 100 0 0 0 0 0 0 0 0 0 0 0

P1.4b 14.2 .80 220 23.81 0 9 0 0 0 9.52 28.57 0 0 9.52 14.29 P1.4b

.60 240 50 0 0 0 0 0 0 3.85 3.85 0 0 42.31 P1.4b

.40 260 8.82 Author Manuscript 0 0 0 0 0 0 17.65 0 0 1.47 72.06 P1.4b

.20 280 47.06 0 0 0 0 5.88 5.88 0 0 5.88 0 35.29

.0 300 100 0 0 0 0 0 0 0 0 0 0 0 796

797

798 Table 2. Matrix of taxonomic groups in each sediment sample in PAN3. Values are the relative 799 abundances (%) of different taxa used in the aeDNA analysis.

Dist anc e Bryo fro Dinophyc zoa Tunic Hexaco Rhiza m eae Dinophyc (mo ata rallia ria cor plankton eae ss (inclu (includ Octoc (incl Bacillari Corallin e (plankton benthos ani des es orallia Porif udes ophyce ales Chloro Phaeophy top ic (benthic mals sea stony (includ era fora ae (coralli phyta ceae Sampl (cm dinoflage dinoflage ) squirt corals) es sea (spo minif (Diato ne (green (brown e ) llates) llates) s) fans) nges) ers) ms) algae) algae) algae) P3.a.

140 0 8.23 3.56 0.05 0 0.2 73.95 1.46 0.95 0.05 1.71 9.54 0.05 P3.a.

120 20 22.86 0 2.86 1.22 8.16 4.9 6.53 5.31 0 12.24 19.18 9.8 P3.a.

100 40 40 9.09 3.64 0.61 12.73 0 3.03 6.67 15.76 3.64 3.64 1.21

P3.a. 3.4188 80 60 48.72 0 0 2.56 0.85 03 0 0 1.71 0 15.38 0

P3.a. 2.2556 26.3 60 80 40.6 0 5.26 0.75 5.26 39 7.52 2 0 0 7.52 0

P3.a. 0.7987 40 100 53.83 0 0.16 3.04 9.27 22 0 6.71 12.78 0 0.64 0

P3.a. 11.6 3.5874 20 120 30.49 0 6 0 23.32 44 0.45 0 4.04 0 5.38 0

P3.a. 16.8 3.9156 16.2 0 140 24.7 0 7 0 6.02 63 1.81 7 21.69 0 0.3 2.41 Author Manuscript P3.b. 16.7 0.3731 160 160 0 0 9 4.1 11.94 34 7.09 5.6 0.37 1.12 1.49 0

P3.b. 180 10.34 0 27.5 0 27.59 0 0 0 3.49 0 0 0

This article is protected by copyright. All rights reserved Site Coral taxa Corallinales Chlorophyta Phaeophyceae 140 9 (Coralline algae) (Green algae) (Brown algae) P3.b. 10.2 Whole coral community Ps-F=0.92 p= 0.45 R2= 0.08 Ps-F=0.65 p=0.52 R2= 0.06 Ps-F=1.99 p=0.10 R2= 0.15 120 200 60.26 0 6 0 3.85 0 0 0 10.26 0 0 1.28 P3.b. Acropora r=0.41 p=0.164 r=0.34 p=0.257 r=-0.58 p=0.038

100 220 3.89 0 4.52 0.25 0.75 0 2.38 8.28 6.15 2.86 0.5 3.26 P3.b.

80 240 0 0 2.41 0 7.23 0 0 0 0 1.2 0 0 P3.b.

60 260 0 0 0 0 0 0 1.08 0 0 0 0 0 P3.b.

40 280 0 0 1.27 0 0 0 1.27 0 3.8 0 0 0 P3.b.

20 300 0 0 0 0 0 0 0 0 0 0 0 0

P3.b. 13.7 0 320 7.84 0 0 0 0 0 0 3 0 0 0 0 800

801

802

803

804 Table 3. Associations between macroalgae and coral. Statistical summary of the relationship between 805 the whole macrofossil coral community composition (from fossils) and the relative abundance of the 806 three macroalgal taxa (from aeDNA) that have ecologically relevant interactions with corals using DistLm, 807 for each individual core, PAN1 and PAN3. Also shown are Pearson correlation coefficients (and their p- 808 values) between the relative abundance of three macroalgal groups and each of the coral taxa present at 809 each site in order of their relative abundance summed across the entire core. Red represents significant 810 negative correlation, green represents significant positive correlation, and blue represents significant 811 non-metric correlation (for whole coral community analysis). Author Manuscript

This article is protected by copyright. All rights reserved Montipora r=-0.18 p=0.561 r=0.14 p=0.653 r=0.05 p=0.864 Seriatopora r=-0.02 p=0.938 r=0.12 p=0.699 r=-0.06 p=0.841 Stylophora r=0.004 p=0.990 r=-0.16 p=0.597 r=0.11 p=0.719 Pocillopora r=0.15 p=0.625 r=0.21 p=0.490 r=-0.27 p=0.369 Galaxea r=0.15 p=0.626 r=0.16 p=0.605 r=-0.24 p=0.438

Echinophyllia r=-0.31 p=0.311 r=-0.29 p=0.343 r=0.46 p=0.117

Merulina r=-0.21 p=0.483 r=-0.32 p=0.285 r=0.40 p=0.171

Fungia r=-0.26 p=0.399 r=-0.25 p=0.408 r=0.39 p=0.187 PAN1 Pavona r=-0.13 p=0.667 r=-0.25 p=0.408 r=0.29 p=0.341 Turbinaria r=-0.26 p=0.399 r=-0.23 p=0.450 r=0.38 p=0.205 Montastrea r=0.01 p=0.967 r=-0.15 p=0.639 r=0.09 p=0.768 Cycloseris r=-0.26 p=0.399 r=0.16 p=0.595 r=0.10 p=0.744 Porites r=-0.26 p=0.399 r=-0.25 p=0.408 r=0.39 p=0.187 Whole coral community Ps-F=2.25 p=0.04 R2=0.13 Ps-F=5.58 p<0.01 R2=0.29 Ps-F=5.39 p<0.01 R2=0.28 Goniopora r=0.70 p=0.003 r=0.85 p=0.000 r=-0.89 p=0.000 Pavona r=-0.21 p=0.442 r=-0.39 p=0.136 r=0.37 p=0.164 Acropora r=-0.26 p=0.333 r=-0.40 p=0.122 r=0.40 p=0.130 Seriatopora r=-0.25 p=0.346 r=-0.40 p=0.122 r=0.39 p=0.132

Millepora r=-0.21 p=0.435 r=0.14 p=0.614 r=-0.02 p=0.944

Pocillopora r=-0.16 p=0.549 r=-0.26 p=0.337 r=0.25 p=0.347

Galaxea r=-0.15 p=0.582 r=-0.22 p=0.406 r=0.22 p=0.409

Montipora r=-0.12 p=0.650 r=-0.24 p=0.383 r=0.22 p=0.414

Paulaustrea r=-0.13 p=0.647 r=-0.20 p=0.462 r=0.19 p=0.474 PAN3 Turbinaria r=-0.12 p=0.655 r=-0.16 p=0.569 r=0.16 p=0.554 Fungia r=-0.12 p=0.663 r=-0.19 p=0.486 r=0.18 p=0.497 Caulaustrea r=-0.12 p=0.663 r=-0.14 p=0.600 r=0.15 p=0.150 Stylophora r=-0.12 p=0.663 r=-0.19 p=0.486 r=0.18 p=0.497 Porites r=-0.12 0.663 r=0.42 p=0.110 r=-0.26 p=0.333 Leptoseris r=-0.12 p=0.663 r=-0.19 p=0.486 r=0.18 p=0.497 Hydnophora r=-0.12 p=0.663 r=-0.14 p=0.600 r=0.15 p=0.150 Author Manuscript 812 813

This article is protected by copyright. All rights reserved 814 Figure captions 815 Figure 1. Sediment cores were taken from two sites at Pandora Reef (PAN1 and PAN3), an 816 inshore reef of the Great Barrier Reef located adjacent to the central Queensland 817 coastline. Cores were taken as part of an extensive GBR coring campaign between 818 2007-2014; modern sediment samples were taken from 2 locations near the PAN1 819 site (mPAN1-A, mPAN1-B) and 1 location near the PAN3 site (mPAN3) in 2015. 820 821 Figure 2. Historical sequence of coral reef communities (relative abundance of different 822 organisms) from sediment core PAN1 from Pandora reef. The fossil coral 823 community is derived from macrofossil abundance data collected from 5 cm slices 824 sampled along the entire length of ½ of the core (Roff 2010). The aeDNA community 825 data is derived from molecular analysis of sediment sampled every 20 cm along the 826 entire length of the archived ½ of the same core from which the macrofossil data 827 was derived. Core depths range from the top of the core (youngest) to the bottom 828 (oldest). U-series age dates performed on individual coral fragments are shown 829 where they were obtained from the core. Also shown are extrapolated ages derived 830 from the U-series age dates. 831 832 Figure 3. Historical sequence of coral reef communities (relative abundance of different 833 organisms) from sediment core PAN3 from Pandora reef. The fossil coral 834 community is derived from macrofossil abundance data collected from 5 cm slices 835 sampled along the entire length of ½ of the core (Roff 2010). The aeDNA community 836 data is derived from molecular analysis of sediment sampled every 20 cm along the 837 entire length of the archived ½ of the same core from which the macrofossil data 838 was derived. Core depths range from the top of the core (youngest) to the bottom 839 (oldest), U-series age dates from coral fragments are shown where they were Author Manuscript 840 obtained from the core. Also shown are extrapolated ages derived from the U-series 841 age dates.

This article is protected by copyright. All rights reserved 842 843 Figure 4. Principal Coordinate analysis (PCO) of aeDNA communities from the a) PAN1 and b) 844 PAN3 sediment cores from Pandora Reef, Great Barrier Reef. Individual samples 845 were taken every 20 cm along the length of the cores, and numbers are interpolated 846 ages (years before present) of samples. Complete linkage hierarchical cluster 847 analysis resulted in two distinct clusters for core PAN3 (denoted in grey) at the 20% 848 similarity level. Vectors shown for taxa that have Pearson’s correlation coefficient > 849 0.6. 850 851 Figure 5. Trends in relative abundance over the study period for three algal taxa groups, 852 coralline (Corallinales), green (Chlorophyta), and brown (Phaeophyceae) 853 macroalgae, and the dominant coral genus in each core, Acropora in PAN1 and 854 Goniopora in PAN3. Points are relative abundance estimated from either coral 855 macrofossil occurrence (coral genera) or aeDNA (macroalgae). Shaded regions 856 behind splines are 95% confidence intervals. Author Manuscript

PandoraPandora reefreef

18˚30’ S

18˚8’”S mPAN3 Ingham PAN3 mPAN1-B

PAN1 mPAN1-A

146˚’”E 18˚’ S 1 km

QLD Coast Greater Palm Group

Australia

19˚10’ S

146˚’ E 146˚’ E 146˚’ E

Figure 1 Author Manuscript

aeDNA algae Fossil coral aeDNA community Acropora

U-series date U-series ago) (yrs Age (cm) Coredepth community community Monipora 28 ± 17 28 0 Stylophora Seriatopora Turbinaria 61 20

Fossil coral community coral Fossil Other coral Phaeophyceae 109 40 Chlorophyta 118 ± 25 Corallinales aeDNA algae Diatoms 158 60 Rhizaria Porifera Octocorallia 206 80 Hexacorallia Tunicata aeDNA community 255 100 Bryozoa Dinophyceae benthos Dinophyceae plankton 303 120

328 ± 41

346 140

382 160

418 ± 30 418 180

470 220

496 ± 35 496 240

624 260

752 280

0 50 100 0 50 100 0 50 100

Relaive aundaneAuthor Manuscript % Relaive aundane % Relaive aundane %

Fossil coral aeDNA algae aeDNA ouity Goniopora ouity U-seriesdate Age yrs ago yrs Age depth Core ouity Pavona 26 0 Millepora Acropora 41 20 Monipora

Fossil coral community coral Fossil Other coral 56 40 Phaeophyta Chlorophyta 71 ± 37 71 60 Coralliales aeDNA algae Diatoms 87 80 Rhizaria Porifera 102 100 Octocorallia Hexacorallia 114 ± 16 126 120 aeDNA community Tuicata Bryozoa 177 140 Diophyceae ethos Diophyceae plakto 227 160 253 ± 3

270 180

304 200

316 ± 5 338 220

372 240

406 ± 14 406 260

476 280

547 300

618 320

0 50Author Manuscript 100 0 50 100 0 50 100 Relaive audae % Relaive audae % Relaive audae %

60 (a) Dinophyceae benthos Phaeophyceae

500 20 600 400

Dinophyceae plankton 700 Tunicata 0 100 modern modern 400yrs 300

PCO2 (28.1% of (28.1% PCO2 total variation) 100yrs 500yrs -20 200yrs 600yrs 300yrs 700yrs 200 -40 40% similarity boundaries -60 -40 -20 0 20 40 60

PCO1 (49.3% of total variation)

600 yrs 40 (b) Dinophyceae plankton

Rhizaria Tunicata 20 Chlorophyta Phaeophyceae 100 Hexacorallia

Spermatophyta 300 0 Bryozoa Porifera modern 400 modern 400yrs 200 -20 100yrs 500yrs

PCO2 (20.1% of total variation) PCO2 (20.1% 200yrs 600yrs

500 300yrs

-40 40% similarity boundaries -40 -20 0 20 40 60 80

PCO1 (57.9% of total variation) Author Manuscript

(a) PAN1 (b) PAN3 Acropora Phaeophyceae Gonipora Phaeophyceae 1.0 ● ● ● ● 1.0 ●●● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● 0.8 ● 0.8 ● ● ● ● ● 0.6 ● ●● 0.6 ● ● 0.4 0.4 ● ● ● ● 0.2 0.2 ● ● ● ● 0.0 ● ● ● ● ●● 0.0 ● ● ● ●●●● ● ●● Corallinales Chlorophyta Corallinales Chlorophyta 1.0 ● 1.0 ● 0.8 ● 0.8 ● Relative abundance Relative abundance Relative ● 0.6 0.6 ● ● ● ● ● ●● ● ● 0.4 ● 0.4 ● ● ● ● 0.2 ● 0.2 ● ● ● ● ● ● ● ● 0.0 ● ●● ●● ● ● ● ● ● 0.0 ● ● ● ●● ●● ● ●●●● ● ● ● ●●●●● 600 400 200 0 600 400 200 0 600 400 200 0 600 400 200 0 Author Manuscript Years before present Years before present