Potential plant extinctions with the loss of the Pleistocene mammoth steppe

Domain: earth_science
Published: 2025-01-14
Editorial outcome: major_revision

Abstract
During the Pleistocene-Holocene transition, the dominant mammoth steppe ecosystem across northern Eurasia vanished, in parallel with megafauna extinctions. However, plant extinction patterns are rarely detected due to lack of identifiable fossil records. Here, we introduce a method for detection of plant taxa loss at regional (extirpation) to potentially global scale (extinction) and their causes, as determined from ancient plant DNA metabarcoding in sediment cores (sedaDNA) from lakes in Siberia and Alaska over the past 28,000 years. Overall, potential plant extinctions track changes in temperature, in vegetation, and in megafauna extinctions at the Pleistocene-Holocene transition. Estimated potential plant extinction rates were 1.7–5.9 extinctions per million species years (E/MSY), above background extinction rates but below modern estimates. Major potential plant extinction events were detected around 17,000 and 9000 years ago which lag maximum vegetation turnover. Our results indicate that herbaceous taxa and taxa contributing less to beta diversity are more vulnerable to extinction. While the robustness of the estimates will increase as DNA reference libraries and ancient sedaDNA data expand, the available data support that plants are more resilient to environmental changes than mammals.

Introduction
Human-induced climate change and habitat fragmentation are causing widespread damage to ecosystems, triggering species extinctions at a global scale 1–4. Estimated extinction rates over the past 500 years range between 150 and 260 per million species years (E/MSY), significantly exceeding the 0.1–1 E/MSY background extinction rates 3. The impact of species extinctions extends across all taxonomic groups of Eukaryotes, with varying degrees of vulnerability observed 5. Since 1900, mammals have faced the greatest extinction pressure, with 243 E/MSY 3, of course, influenced by taxonomic biases arising from different research efforts across species groups 3,6–9. Emerging evidence highlights the underappreciated susceptibility of certain taxonomic groups to increased extinction risks 3,10,11. Among the less investigated taxa, plant species are more prevalent 12–14. Notably, 20% of plant species are currently classified as threatened (IUCN), a proportion similar to that of threatened mammal species 15,16. Extinction rates of plants range from 18 to 26 E/MSY, up to 500 times the background rate 17. However, uncertainties are particularly high for plants because, among others, their potential dormancy in the seed bank.

Extinctions are more common in regions with high species diversity 5,18. They occur globally, but only 1–2 plant extinctions are known from boreal-arctic regions 17. Low arctic diversity may to some extent originate from recurrent extinction waves related to severe glacial-interglacial climate and environmental change, providing a suitable testbed to examine species extinctions in the context of natural climate variability. This applies in particular to the transition from the last glacial to the Holocene between 19 and 9 ka BP for which intense investigations revealed severe extinctions among megafauna 19–23. In parallel to the megafaunal loss, the well-established mammoth steppe ecosystem disappeared with no modern analogue but some relics in the Central Asian mountain ranges 24–31. This ecosystem was characterised by a rich mosaic of woodlands and grassland covering much of the unglaciated northern hemisphere that has persisted through several glacial and interglacial stages 31,32. Despite the supposed role of Pleistocene megafauna as keystone species, interacting extensively and shaping their environment, only one plant taxon, a Picea (spruce) species present in North America, has been reported extinct in the area during the late Pleistocene 33 while further extinctions were reported for tree species in northern Europe during the Quaternary 34. The surprising lack of any plant-mammalia co-extinction may point to our misconception of the role of large mammal herbivores in maintaining grassy ecosystems as proposed for eastern Beringia 35 and Tibet 36 or derives from our poor understanding of the eco-evolutionary traits that support plant taxa survival, or it simply originates from our methodologic limitations to record extinct plant taxa.

Connecting specific traits to extinction remains elusive, emphasising the necessity for recent investigations to clarify these relationships. Recent observations indicate that plant taxa inhabiting the periphery of their native ranges, regionally rare species and habitat specialists face heightened extinction risks, while broader-ranging clades exhibit greater resilience to climatic shifts 37. However, the realisation that rarity does not consistently heighten extinction risk, and that introductions and speciation may intersect with extinction, further complicates our understanding 38,39. Additionally, factors like plant size and seed production dynamics play crucial roles in determining extinction probabilities 40. Despite these insights, discerning a clear phylogenetic pattern in plant extinctions remains challenging 40,41. This maybe attributed to the ‘shotgun extinction’ principle, where extinctions occur predominantly at the species level across various phyla, necessitating species-level detection to infer extinction events accurately 42. Plant macrofossils are scarce 43, and microfossils rarely possess sufficient diagnostic characters to allow for species description 44, unlike mammals, where even full carcasses have been found allowing detailed descriptions of extinct species (i.e. ref. 45). Plant taxonomy heavily relies on floral characteristics, which are rarely well preserved, traditionally limiting the study of past plant extinctions making direct comparisons of plant extinction at genus of family level especially during mass extinction events, distinct from the Pleistocene/Holocene transition 46.

The investigation of plant extinction (the global disappearance) or extirpation (spatially restricted disappearance) requires a methodologically consistent assessment of taxa occurrences across space and time, ideally at the species level 3,47. Currently, there are no multi-site time-series datasets available which cover the loss of the mammoth steppe at a subcontinental scale with the required taxonomic precision. Synthesised spatiotemporal pollen datasets, for instance, typically only identify plant taxa to the family or genus level (e.g. ref. 44). Plant macrofossils, although often allowing identification to species level, are rare due to degradation in the absence of optimal preservation conditions 48. Metabarcoding, utilising the chloroplast trnL (UAA) intron as a marker to analyse sedimentary ancient DNA (sedaDNA), can provide the required taxonomic resolution for assessing changes in species richness 27,49,50 and the plant species pool 51. However, like all genetic methods, metabarcoding relies on taxonomic assignments against DNA reference databases, which often have limited representation of rare taxa, and with few exceptions 52, do not contain sequences of extinct taxa 53,54. To improve the detection of extinct and rare taxa absent from databases, new concepts are needed, as current plant metabarcoding analyses mostly only consider the 100% assigned amplicon sequence variants (ASVs), limiting the detection of mismatches and taxa not represented in DNA databases 55. Therefore, allowing mismatches is essential for investigating both extirpated and potentially extinct taxa. In addition, ecological principles, including the dynamic nature of species distribution ranges influenced by biotic and abiotic factors 56, offer valuable insights. Distinct communities, shaped by significant species interactions, can be identified across space and time 57, potentially including species that have become extinct at specific points of change in community composition among sites. Beta diversity can be used to describe changes in community composition through time and estimate the turnover component of community dissimilarity change representing the contribution of replacement between distinct species, phylogenetic lineages or functional attributes. Therefore, applying a community-based approach on DNA sequences absent from modern DNA samples but evident in past communities may provide clues to potential extinctions.

This study aims to address critical gaps in understanding plant extinctions during the Pleistocene–Holocene transition by analysing ancient DNA metabarcoding data from sediment cores spanning the last 28,000 years, collected from lakes in Siberia and Alaska (Beringia). By integrating established methods with a novel approach for identifying unknown taxa and tracing potential extinction signals, we estimate both local extirpation rates and potential global extinction rates. Our findings reveal that plant extinctions are closely associated with shifts in temperature, vegetation dynamics and megafauna extinctions during this period of environmental upheaval. We estimate extinction rates of 1.7–5.9 extinctions per million species years (E/MSY), higher than background levels but lower than modern estimates. Major extinction events are detected around 17,000 and 9000 years ago, lagging behind peaks in vegetation turnover. Herbaceous taxa and species contributing less to beta diversity are more vulnerable to extinction. While expanding DNA reference libraries and sedaDNA datasets will further refine these estimates, our results suggest that plants demonstrate greater resilience to past environmental changes compared to mammals.

Results
Rates of potential plant extinctions
We analysed metabarcoding data from 504 samples from eight lake sediment cores representing seven lakes from northeastern Siberia and Alaska, each covering at least the last 28,000 years (Table 1). To allow for a reliable taxonomic assignment, we set up a customised database, named SibAla_2023, for Siberia and Alaska (55–90°N, 50–150°E and 40–90°N, 150°E–140°W) including all vascular plant species from Embryophyta clades Tracheophyta, Bryophyta, Marchantiophyta and Anthocerotophyta which have >10 regional occurrences in the Global Biodiversity Information Facility database (GBIF 58) and which have available trnL P6 loop sequences from public databases (arctborbryo 59–61); EMBL 14362; PhyloNorway 51). SibAla_2023 includes 3398 species (representing a 70% GBIF database coverage) and a total of 2371 unique sequence types.

The metabarcoding analyses yielded a total of 128,619,625 reads, which were assigned to 23,005 ASVs. To ensure reliable and real taxa detection, we applied a quality filter in the metabarcoding sequencing results, checking polymerase chain reaction (PCR) replicates’ replicability. Assignment was allowed if a sequence showed 90–100% similarity to the referencedatabase to allow for the detection of potential extinct taxa. Counting only the ASVs with a minimum of 100 reads, 332 were assigned with 100% similarity to the reference database and a further 5089 were ASVs with 90–99% similarity (Supplementary Data 1). To exclude sequences that can originate from PCR or sequencing errors, we developed a quality approach accounting for co-occurrence patterns, and statistically detected 10 communities comprising at least five ASVs within the built network (Supplementary Data 2). By collapsing all ASVs which are part of similar communities and with similar taxonomic names, we transferred the ASVs signal into a taxa signal (Supplementary Note 2). The effectiveness of the community approach to identify real taxa was indicated by the fact that for 14 of 16 taxa represented by more than one unique ASV, ASVs assigned to similar taxa are part of the same community (see Supplementary Data 4).

To allow investigation of appearance and disappearance of taxa through time, 2000-year time-slices covering the last 28,000 years were set. A 1000 iteration resampling of number of cores, number of samples and reads was performed to ensure proper comparison between time-slices. After resampling, the final dataset includes 359 taxa (Fig. 1). Among them 216 are db taxa i.e. taxa derived from ASVs with similar co-occurrence patterns and 100% match to the SibAla_2023 database. A total of 143 taxa are non-db taxa, i.e. taxa derived from ASVs with similar co-occurrence patterns but only 90–99% match to SibAla_2023 (Supplementary Data 3 for the median abundance).

Of the 359 taxa, 127 are lost (i.e. absent from the modern time-slice (0–2000 years time bin); Fig. 2a). Among them, 67 are lost db taxa (53%) which are absent from the sites in the modern time-slice but still present in the study region as they match 100% with a reference in the SibAla_2023 database. Thus, based on the db taxa only, the loss of db taxa at these seven sites is 31%. Furthermore, there are 60 lost non-db taxa (47%), i.e. they are absent from the modern time-slice and are not covered by the SibAla_2023 database. In our dataset, the 60 lost non-db taxa represents the maximum number of potentially extinct taxa (Fig. 2c). The loss of non-db taxa is 42%, and thus by 11% higher than the lost db taxa.

We set up a synthetic dataset to test whether the observed portion of 67/60 of db taxa/non-db taxa missing in the modern time-slice can plausibly only originate from the fraction of GBIF plant species covered/not covered by the SibAla_2023 (Supplementary Note 2). The synthetic dataset mimics our palaeorecord by resampling GBIF according to the observed taxa gains and losses between consecutive time-slices. For taxa present in the modern time-slice the simulated dataset has a median proportion of 70/30% db taxa/non-db taxa reflecting the 70% database coverage of GBIF taxa (Fig. 2b). Within error bars, this is in intriguing agreement with the observed proportion of 64/36% db taxa/non-db taxa observed by our sedaDNA dataset in the modern time-slice. In contrast, the simulated proportion of 67/33% for db/non-db taxa absent in the modern time-slice differ from the observed proportion of 53/47% db/non-db taxa absent in the modern sedaDNA time-slice. Thus, the fraction of non-db taxa missing in the modern sedaDNA time-slices is higher than expected based on database cover. From this result, we conclude that of the 60 lost non-db taxa, 42 could be expected from the database coverage and therefore, a minimum of 18 taxa are likely extirpated from the study region or even potentially globally extinct.

The distribution of rare to common taxa is similar between the GBIF fractions covered and not covered by the SibAla_2023 database (Supplementary Fig. 2). Therefore, we consider it unlikely that an unequal representation of rare taxa might have artificially created the extinction signal.

We further assessed whether the lost non-db taxa are more likely extirpated from the region of Siberia and Alaska or even potentially extinct. We found that 88% (54/60) of the lost non-db taxa have no match with other global databases and are therefore potentially extinct globally (Supplementary Note 2.4). For the six taxa that show a 100% match with other databases, we assessed the likelihood that they have modern refugia outside the study region of Siberia and Alaska by assessing the species overlap between regions where the taxa are found and the region of Siberia and Alaska at family level. Our analyses yielded a rather low likelihood for outside refugia of <5% for two taxa and <30% for four taxa (Supplementary Note 2.4) with an average of 18.2% of the detected taxa, representing one taxon which likely has an outside refugium and is, therefore, extirpated and not extinct. From this analysis, we conclude that 59 of 60 lost non-db taxa are potentially extinct. Taking the results of all analyses together, we conclude that 17 to 59 lost non-db taxa are potentially globally extinct. Thus, the potential extinction rate ranges between 1.7 and 5.9 E/MSY over the last 28,000 years in the study area.

Temporal pattern of potential taxa extinction and correlation to potential drivers
In our dataset, taxa disappeared and/or appeared frequently over past time-slices. We estimated the potential extinction rate with confidence intervals by accounting for the likelihood of a taxa to reappear given the remaining time-slices until present time (Fig. 3a, see Supplementary Note 3 and Supplementary Figs. 5–7).

Potential plant extinctions mainly occurred in two waves around 17,000–15,000 cal. yrs BP (10.6% above the expected rate, with a confidence of 100–96%) and 9000 cal. yrs BP (19.4% above the expected rate and 97% confidence). For comparison, loss of db taxa occurred mainly between 19,000 and 9000 cal. yrs BP and with a peak at 13,000 cal. yrs BP which is 26.7% higher than the expected rate and has a confidence of 99.5% (Supplementary Note 3).

A synthetic dataset was created using the SibAla_2023 database to simulate random ASV loss and the corresponding progression of species loss. This allowed to confirm that the taxonomic resolution of the analysed taxa (assessed through a community approach and not always assigned to the species level) likely did not influence the results and that the non-db taxa loss approach accurately reflects the actual pattern of species loss (Supplementary Note 2.5).

Our data indicate a compositional change in vegetation during the Pleistocene–Holocene transition, from predominantly forbs and graminoids (67–78% of the taxa detected) before 15 ka to an increased number of shrubs and trees (22–33%, Supplementary Fig. 3). The assessment of the driver of potential plant extinction rates using a generalised linear mixed effect model (Intercept; Chi2=456.9; p=0.001) highlights vegetation turnover (Fig. 3b) ‘shifted by one time-slice’ is most important (Chi2=30.3; p<0.001), followed by the megafauna extinction using extinction frames reported in refs. 63,64 (Fig. 3d) (Chi2=16; p<0.001), and July temperature changes (Fig. 3c, Chi2=6.8; p=0.009; see Supplementary Note 4 and Supplementary Table 7).

Characteristics of the potentially extinct taxa
In this study, 48% db taxa are assigned to species level, 38% to genus and 15% to family level. Herbaceous taxa are the dominant functional group with 267 assigned taxa (29 graminoids and 238 forbs), followed by shrubs with 66 taxa and trees with 26. Asteraceae, Ericaceae, Rosaceae, Ranunculaceae and Polygonaceae are the most represented families of the 37 detected plant families.

Herbaceous taxa have a higher proportion of lost non-db taxa than woody taxa (shrubs and trees, Fig. 4d). On average, 23.3% of the forbs are lost, which is more than the relative proportion of the lost graminoids (21.6%), lost shrubs (14.1%) and lost trees (10.3%). All differences are significant (t-test, p value <0.001).

The lost non-db taxa are more likely specialists than the other taxa (Fig. 4a). Lost non-db taxa are part of communities with a mean size of 39.85 taxa, which is significantly lower than the community size of other taxa, meaning all taxa that are not lost non-db taxa (41.37 taxa; wilcox.test, two-sided, p value <0.001). Lost non-db taxa have a low species contribution to beta diversity (SCBD) score (6.4e-5), that is, they contribute significantly less to the beta diversity than the other taxa (Fig. 4b; 2.4e-3; wilcox.test, two-sided, p value <0.001). The lost non-db taxa are slightly more phylogenetically close to each other (average cophenetic distance of 241.9.39) than to the other taxa (253 for average cophenetic distance between the lost non-db taxa and the other taxa; Fig. 4c).

Lost non-db taxa are most abundant in the family Boraginaceae (average lost non-db taxa in the family relative to the total number of taxa, 55.9%; Fig. 4e). The proportion of lost non-db taxa decreases from Asparagaceae (49.4%, t-test, two-sided, p value <0.001), through Papaveraceae (49%, t-test, two-sided, p value = 1), Fabaceae (29.5%, t-test, two-sided, p value <0.001), Polygonaceae (25.4%, t-test, two-sided, p value <0.001), Rosaceae (24.1%, t-test, two-sided, p value = 0.3), Poaceae (23.3%, t-test, two-sided, p value = 1), Juncaceae (20%), Asteraceae (19%, t-test, two-sided, p value = 0.9), Cyperaceae (18.8%, t-test, two-sided, p value = 1), Brassicaceae (15.3%, t-test, two-sided, p value <0.001), Orobanchaceae (15.1%, t-test, two-sided, p value = 1), Ericaceae (12.5%, t-test, two-sided, p value <0.001), Salicaceae (11.4%, t-test, two-sided, p value = 0.3), Ranunculaceae (6%, t-test, two-sided, p value <0.001), Betulaceae (4.8%, t-test, two-sided, p value = 0.1), and Saxifragaceae (3.6%, t-test, two-sided, p value = 0.03) to Pinaceae (1.3%, t-test, two-sided, p value <0.001).

Methods
Site description and timeframe
We used eight lake sediment cores from seven sites spanning the Pleistocene to Holocene transition. The sites are distributed across Siberia and Alaska covering the Beringia and allowing investigation of vegetation changes over an area previously covered by the Pleistocene mammoth steppe (Fig. 1).

Lake Bilyakh (65°17′N, 126°47′E; 340 m above sea level (a.s.l.)) is situated in the western part of the Verkhoyansk Mountains, about 140 km south of the Arctic Circle. The lake covers an area of ~23 km2, has an average water depth of 8 m, and a maximum measured depth of about 25 m. It is fed by direct precipitation as well as several small creeks and streams. The climate is characterised by mean January temperatures around −40°C, mean July temperatures about 15–19°C, and annual precipitation of 300–400 mm. Today the plant is dominated by open mountain deciduous forests and woodlands with Larix.

Lake Bolshoe Toko (56°05′N, 130°90′E, 903 m a.s.l.) is located in a depression of tectonic and glacial origin, on the northern flank of the eastern Stanovoy Mountain range, it is bordered by moraines of three glacials at its northeastern margins. It is 15.4 km long and 7.4 km wide, with a maximum water depth of about 80 m and surface area of 82.6 km2. Mean annual air temperature in the study region is 11.2°C, ranging from −65°C in January to +34°C in July. Annual precipitation varies from 276 to 579 mm. Soil cover is thin and contains large amounts of gravel. Northern taiga dominate the study area, forests consist of Larix, Picea and Pinus.

Lake E5 (68.641667°N, 149.457706°W, 795 m a.s.l.) is situated in the northern foothills of the Brooks Range, northern Alaska, it is located on an older glacial landscape (>125 ka BP), referred to as the Sagavanirktok, and did not glaciated during the LGM. It is a small lake, with ~650 m long × 310 m wide at its widest point, and surface area 0.1 km2. The Sagavanirktok River moraine in the Lake E5 basin is almost entirely vegetated with tussock tundra, but along the ridge top southwest of the lake, a few large erratic boulders protrude 1–2 m above the vegetated surface.

Lake Emanda (65°17′N, 135°45′E, 671 m a.s.l.) is situated in the Yana Highlands east of the Verkhoyansk Mountains in Siberia. The lake is 7.5 km long, 6.5 km wide, has a surface area of 33.1 km2 and a maximum water depth of 15 m. The climate is categorised as continental subarctic, with large seasonal temperature gradients and a mean annual precipitation of 233 mm. The present-day winter climate is predominantly controlled by the intensity of the Siberian High-Pressure system, which causes very cold and long winter periods with thin snow cover and mean January air temperatures of −44.7°C. The summer climate is mainly controlled by the Asiatic Thermal Low-Pressure system and a high-pressure system over the North Pacific, resulting in short but relatively warm summer periods with mean July temperatures of 13.0°C and higher precipitation of 40–50 mm per month between June and August. The soil around the lake is pervaded by permafrost. The modern vegetation is represented by sparse mountain larch (Larix cajanderi) forests of lichen (Flavocetraria cucullata, Cladina arbuscula) type with Betula exilis and Pinus pumila and of Vaccinium-moss and lichen type (V. vitis-idaea, V. uliginosum, Aulacomnium turgidum, Sphagnum spp., Flavocetraria cucullata).

Lake Ilirney (67°21′N, 168°19′E, 1790 m a.s.l.) is situated in the region of Chukotka, far east Russia. The lake is bounded by the Anadyr Mountains to the north. The basin itself is 12 km in length and 3.6 km across at its widest point and oriented northeast to southwest along a large structural feature. The basin can be split into two sub-basins: a larger depocenter in the southwest and a smaller basin in the northeast divided by a roughly north-south oriented bathymetric high. The maximum water depth in the southwestern basin and in the northeastern basin is 44 and 25 m, respectively. The catchment area is 1214 km2. A strongly continental climate characterises Ilirney with a mean annual temperature of −13.5°C and average January and July temperatures of −33.4°C and 12.1°C, respectively. Regional snowfall is equivalent to 110 mm of water and June–September precipitation totals 70 mm. The lake zone is covered by continuous permafrost and located at the latitudinal tundra-taiga ecotone boundary. The direct vicinity is dominated by open mountain Larix forests.

Age models for the sediment records were adopted from previous studies listed in Table 1. The cores cover the last 62,000 years for the oldest core and the last 28,000 years for the most recent one. Therefore, we investigated the last 28,000 years only and split the records into 14 time-slices of 2000 years.

Sampling and sediment DNA lab work
For each of the lake sediment cores, the opening and subsampling were performed in the climate chamber of the Helmholtz Centre Potsdam—German Research Centre for Geosciences (GFZ) at 4°C, physically remote from any molecular genetic labs preventing contamination with modern DNA. Precautions for clean subsampling were applied during sediment core subsampling. All surfaces in the climate chamber at GFZ (Potsdam, Germany) were cleaned with DNA Exitus PlusTM (VWR, Germany) and demineralised water before working on the core. The sampling tools such as knives, scalpels and their holders were cleaned before the taking of each sample (as recommended in ref. 99). About 3 mm of each sample slice that was in touch with the plastic tube or the thin foil that covered the half-core was removed using a sterile scalpel as these parts cannot be considered sterile 100.

Collected sediment samples were stored in 8 mL sterile tubes (Sarstedt) at −20°C.

Molecular genetic analyses of the sediment samples were conducted in the palaeogenetic laboratories of the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI) in Potsdam, Germany (as described in ref. 30). This laboratory is dedicated to ancient DNA isolation and PCR setup and is located in a building devoid of any molecular genetic work. It is cleaned frequently and subjected to nightly UV-irradiation. All laboratory work was performed in a UVC/T-M-AR DNA/RNA cleaner-box (BIOSAN, Latvia). DNA isolations and PCR setups were performed on different days using dedicated sets of pipettes and equipment. Further precautions to reduce contamination included UV-irradiation of 10× buffer, BSA, MgSO4 and DEPC-treated water for 10 min in a UV crosslinker in thin-walled PCR reaction tubes (recommendations of ref. 99). Each laboratory step including subsampling, extraction, PCR amplification, purification and pooling, as well as next generation sequencing was done for each core separately. The same laboratory protocols for DNA isolation and PCR were followed for all cores. DNA isolations were performed, each with nine samples and one control (blank). Total DNA was isolated from ~3–5 g of sample material using the PowerMax® Soil DNA Isolation Kit (Qiagen, Germany, cat# 12988-10) added to 1.2 mL of C1 buffer, 0.4 mL of 2 mg/mL Proteinase K (protK, Karl Roth, Germany, cat# 7528.1) and 0.5 mL of 1 M dithiothreitol (DTT, Omnilab, Germany, cat# 1198463). This mixture was homogenised for 10 min on a vibratory mixer (Vortex Genie 2, MoBio Laboratories, USA) and incubated overnight at 56°C while rotating. All subsequent steps were performed according to the instructions of the manufacturer Qiagen, except for the final elution volume which varied between 1.6 and 2.0 mL. For most core samples, 800 μL of elution buffer (C6 buffer) was applied to the filter membrane, incubated for 10 min at room temperature and then centrifuged for 3 min at 2500×g. This step was performed twice ending up with a final volume of 1.6 mL. One exception was for the Lake Ilirney (EN18208) core where 2 mL of elution buffer (C6 buffer) was directly added to the filter membrane. For all core sediment samples, except for samples from Lake Bolshoe Toko, 1 mL of the DNA extracts were concentrated using the GeneJET PCR Purification Kit (Thermo Fisher Scientific, cat# K0692) using 100–50 μL elution buffer. The concentrated DNA was measured using the ds-DNA BR Assay Kits (Invitrogen, USA, cat# Q32853) and the Qubit® 2.0 fluorometer Qubit 2.0 fluorometer (Invitrogen, cat# Q32866). Then, the DNA solution was diluted to 3 ng/µL for the PCR reactions.

The PCR reactions were performed using the trnL g and h primers 68. Both primers were modified on the 5′ end by unique 8 bp tags which varied from each other in at least five base pairs to distinguish samples after sequencing and were additionally elongated by NNN tagging to improve cluster detection on the sequencing platform. The PCR reactions contained 1.25 U Platinum® Taq High Fidelity DNA Polymerase (Invitrogen, USA, cat# 10675783), 1× HiFi buffer (cat# 10675783), 2 mM MgSO4 (cat# 10675783), 0.25 mM mixed dNTPs (Life Technology, cat# R1121), 0.8 mg Bovine Serum Albumin (VWR, Germany, cat# 11761797), 0.2 mM of each primer (IDT) and 3 μL DNA in a final volume of 25 μL. PCRs were carried out in a Professional Basic Thermocycler (Biometra, Germany) with initial denaturation at 94°C for 5 min, followed by 50 cycles of 94°C for 30 s, 50°C for 30 s, 68°C for 30 s and a final extension at 72°C for 10 min. The extraction blank and one no template control (NTC) were included in each PCR to identify possible contamination during extraction and PCR set-up. For each extraction sample, three PCR replicates with differently tagged primers were performed. Except for the Bolshoe Toko core, replicates were amplified with the same tag combination. PCR success was checked with gel-electrophoresis on 2% agarose gels (Carl Roth GmbH & Co. KG, Germany). The PCR products were purified using the MinElute PCR Purification Kit (Qiagen, Germany, cat# 28006), following the manufacturer’s recommendations, and finally eluted in 20 μL of elution buffer. The DNA concentrations were quantified with the dsDNA BR Assay (Invitrogen, USA, cat# Q32853) using the Qubit 2.0 fluorometer (Invitrogen, cat# Q32866). To avoid bias based on differences in DNA concentration between samples, all replicates were pooled in equimolar concentrations for each core. For each core, all extraction blanks and NTCs were included in the sequencing run, even though they were negative in the PCRs. Each sequencing run was performed by Fasteris SA sequencing service (Switzerland) with the paired-end sequencing on a HiSeq or NextSeq Illumina platform (Supplementary Table 1).

Data analysis
Each core metabarcoding dataset was analysed individually using OBITOOLS (version 3 101). Overlapping paired reads were merged using the command obi align paired end. The unmerged reads were removed with obi grep -a mode: alignment. The command obi ngs filter assigned each sequence to its corresponding sample according to the tag combination. Reads were de replicated with the command obi uniq --merge sample and cleaned from PCR and sequencing errors using obi clean -s MERGED_sample -r 0.05 -H, which keeps head sequences (-H) that lack variants with a count greater than 5% of their own count (-r 0.05). Taxonomic assignments of the ASVs were performed using obi ecotag with the use of the customised SibAla_2023 database.

The customised database SibAla_2023 has been compiled using different R packages with the following steps. 1. Taxa selection from a given region (55–90°N, 50–150°E and 40–90°N, 150°E–140°W) and taxa occurrences (>10) using the Global Biodiversity Information Facility (GBIF accessed the 16.03.2023 58) resulting in 233 families, 1059 genera and 4849 species. 2. Alignment between selected taxa and available P6 loop sequences from public databases (arctborbryo 59–61); EMBL 14362; PhyloNorway 51). 3. Quality filtering of selected P6 loop sequences. 4. Preparation for usage with obi ecotag. The SibAla_2023 database compared with given occurrences in GBIF amounts to 95.7% (family level), 89.4% (genus level) and 70.1% (species level) of taxonomic coverage. Finally, the SibAla_2023 database includes a total of 4939 entries, comprising 3398 species, 947 genera and 223 families that collapse into 2371 unique P6 loop sequence types. The entries of the database are encoded with a unique identifier.

Data quality was assessed by investigating the replicability of the PCR replicates and their compositional patterns by non-metric multidimensional scaling analyses. The analysis was done core-wise and only ASVs that have a 100% identity match to the reference database were used. The ASVs compositional data were Hellinger transformed with decostand() and ordination was performed with metaMDS() in the R package vegan (version 2.6-2 102). If replicates of the same sample did not form a cluster but show that one replicate is distant from the others (indicating a different compositional signal), we checked read count and composition of the replicate. If the total read count of the affected replicate was below 100 counts and/or the sample was composed of fewer (less than three) and different plant sequence types as compared to the remaining replicates of the sample, replicates were excluded from the dataset. After replicate evaluation, the replicate removal was done on the raw data (Obitools 3 output). The remaining high-quality replicates were merged into samples by summarising the replicate read counts.

The single-core data was filtered for ASVs that have at least a 90% similarity with reference sequences SibAla_2023. Finally, the eight single-core datasets were merged into one dataset by keeping only ASVs appearing in at least ten samples with a minimum read count of 100 reads per ASV. From this final dataset, we grouped ASVs with 100% similarity into database ASVs (dbASVs) and the remaining ASVs (with 99–90% similarity) into non-dbASVs.

Given the strong connection between the occurrence of species within plant communities over time and space, we utilised co-occurrence patterns to group ASVs into these communities. This helps enhance our confidence in the taxonomic signals. First, we ran a correlation analysis using the corr.test function in R (Spearman method and the Holm adjustment for non-normally distributed data). We retained only results with a positive correlation score above 0.4 and constructed a network using the graph_from_data_frame function. Next, we used the cluster Louvain function from the igraph R package to detect community structures and optimise modularity scores. Within these identified plant communities containing at least five ASVs, we differentiated between database ASVs (dbASVs) and non-database ASVs (non-dbASVs), assigning them to unique taxa accordingly. To minimise potential errors, we collapsed non-dbASVs to dbASVs within communities if their taxonomic assignments matched. For example, if within the same community, non-dbASVs that are assigned to the same family as dbASVs will be collapsed with the name of the dbASVs under a single db taxon. This step helps mitigate the risk of chimeric sequences and other PCR/sequencing artefacts.

We split the lake sediment records into 14 time-slices of 2000 years. The mean age is used: the oldest time-slice covering 28,000–26,000 cal. yrs BP and the most recent and modern time-slice covering 2000–0 cal. yrs BP. For setting up our reads per taxon per time-slice dataset, we performed a three-step resampling script to balance the number of reads, number of samples and number of sites (see Supplementary Note 1 and Supplementary Table 2 and Supplementary Fig. 1). The resampling was performed 1000 times. The results presented are based on the median values obtained from analysing the 1000 resampled datasets. We assessed the occurrence of each db taxon and non-db taxon in each time-slice. We defined the lost db taxa and lost non-db taxa as those absent from the modern time-slice.

To test whether the observed portion of lost db taxa/non-db taxa can plausibly only originate from the fraction of GBIF plant species covered/not covered by the SibAla_2023, we created a synthetic dataset to mimic our palaeorecord by resampling GBIF according to the observed taxa gains and losses between consecutive time-slices. For example, if eight and six db taxa and non-db taxa, respectively were lost between time-slice 27,000 and 25,000, and three db taxa and five non-database taxa were gained over the same time period, we randomly removed eight and added three taxa that were in the reference database whereas we removed six and added three taxa that were lacking in the reference database. We then compared the observed db taxa/non-db taxa ratios to the simulated values. In addition, we compared the distribution of rare taxa in both GBIF and our dataset to check whether an unequal representation of rare taxa might artificially create an extinction signal.

Finally, to assess the potential presence of lost non-db taxa beyond the region used to build the SibAla_2023 database, we conducted a MegaBLAST 103 against the global, NCBI nt database 104 using Geneious Prime 2023.2.1. This resulted in the assignment of seven ASVs to species level with 100% confidence. For each species assigned, we obtained its occurrence region using GBIF, encompassing all occurrences of the species. Subsequently, we identified the families to which the assigned species belong and compared all species within these families in the study area to those in the region of Siberia and Alaska belonging to the same family. If the number of species exceeded 100, a random selection of 100 species was made from each region for comparison; if fewer than 100 species were present, all were used. This analysis helped determine the overlap of species between the two regions.

We consider the number of all non-db taxa absent from modern time-slice and are not covered by the SibAla_2023 database as the maximum number of potentially globally extinct taxa. The minimum number of potentially globally extinct taxa was retrieved taking into account the analyses of GBIF plant species coverage of SibAla_2023 and considering lost taxa presence outside the study region of Siberia and Alaska. Accordingly, we estimated the minimum and maximum rate of potential taxa extinctions presented in units of the number of extinctions per million species years (E/MSY; as described in ref. 105).

Disappearance of taxa in the dataset happens at every time-slice in parallel to the reappearance of taxa. There can be several time-slices between a taxon’s disappearance and its reappearance in the dataset. Therefore, potential extinction rates would increase towards the recent time-slices as fewer time-slices are left for a disappeared taxon to reappear in the dataset. For this reason, reappearance rates are the key to identifying potential extinction events.

To establish an expected extirpation rate for each taxon disappearing from a time-slice, we report the number of time-slices it took to reappear in the dataset. Measured from each of the 1000 resampling iterations, a maximum of nine time-slices can be considered for a taxon to reappear once it disappeared. Therefore, we measured the expected extirpation rate using the time-slices ~25,000, ~23,000 and ~21,000 yrs BP, as this leaves nine time-slices for a taxon to reappear later in the dataset once they disappeared from a time-slice. At every resampling iteration, we estimated the number of time-slices needed for lost taxa to reappear for each time-slice they disappeared from. We used this distribution and the median number of time-slices needed for taxa to reappear as the expected reappearance rate for each time-slice. We compared this expected reappearance rate to the observed rate at each time-slice for each of the 1000 iteration steps of our resampling. We could then infer a likelihood of extirpation (lost db taxa) and potential extinction (lost non-db taxa) based on the proportion that the observed reappearance rate is lower than expected for each time-slice (see Supplementary Note 3 and Supplementary Fig. 5). In addition, we could infer the net proportion of taxa loss as the difference between the percentage of observed taxa lost and the expected loss at each time-slice.

To examine whether ASV loss and species loss share the same patterns, we analysed data from the SibAla_2023 database, which contains corresponding information for ASVs and species. Each ASV may be linked to multiple species, and vice versa, a single species may correspond to multiple ASVs. We simulated ASV loss progress by setting the same ASV loss and reappearance numbers obtained from sedimentary ancient DNA results. Leveraging the ASV species correlation from the SibAla_2023 database, we simulated species loss progress by matching observed ASV losses in each artificial time-slice. For each time-slice, we determined the species loss and reappearance numbers. Subsequently, using the same methodology applied to calculate past taxa losses, we calculated the proportion of lost species relative to the expected values. Our results aligned with sedimentary DNA estimates, revealing a consistent pattern. Specifically, periods characterised by substantial taxa loss also exhibited significant species loss.

Generalised linear models (GLM) were built to identify potential correlations between the observed plant loss (extirpation and potential extinction) rate for each of the 1000 iteration steps and biotic and abiotic factors. Only positive plant taxa-loss values were used, and the negative values were set to 0 in order to build a binomial GLM with positive values of plant taxa-loss rate as success (observed plant taxa loss) and negative values as non-success (non-observed plant taxa loss). After fitting with a step for the best likelihood ratio test, the parameters explaining the most variance of the plant extinction were selected (see Supplementary Note 4 and Supplementary Table 7). The factor representing beta-diversity changes that explain the most variance is the replacement rate (vegetation turnover) with a 2000 yrs shift (i.e. an increase in replacement rate occurs one time-slice before the plant taxa loss). The factor that explain the most plant taxa-loss variance for climate change is the pollen-based reconstructed changes in median temperature anomalies using the modern analogue technique 44,106. For the beta-diversity estimate, the temperature changes and the megafauna extinction timeframes (estimated from refs. 63,64), a pairwise GLM with binomial distribution was performed against the plant extirpation and potential extinction rates.

To characterise the lost non-db taxa, we compared their characteristics with other taxa (and to the taxa present in the modern time-slice; Supplementary Note 5). For each db taxon and non db taxon, we estimated whether they are more specialist or generalist based on the number of taxa present in their detected communities. We assumed that taxa present in communities with fewer total taxa are more specialist than taxa present in communities with more total taxa. We compared the number of taxa per community for the lost non-db taxa and the modern taxa with a Wilcoxon statistic test. Before going extinct, a taxon is likely to become rare and functionally extinct. To estimate the contribution of the taxa to the functionality of the system, we assessed their SCBD scores with the beta.div function from the adespatial R package (version 0.3-14 107) on square-root relative abundance data. We compared the SCBD score of the lost non-db taxa to the modern db taxa with a Wilcoxon statistic test. Phylogeny of the assigned taxa was retrieved using the ‘V.Phylomaker.2’ R package that implements mega-trees of vascular plants (GBOTB.extended.TPL, version 0.1.0 108). Cophenetic distances between taxa were measured with the cophenetic.phylo() function from the ape R package (version 5.6-2 109). The average distances between the lost non-db taxa, and the other taxa were compared with a Wilcoxon statistic test. To investigate vegetation composition changes, the db taxa and non db taxa were categorised within four functional plant types based on their best taxonomic assignment: grasses, rushes and grass-like sedges (Poaceae, Juncaceae and Cyperaceae) as graminoids; forbs, which are other herbs; shrubs; and trees (Supplementary Data 3). We compared the proportion of the lost non-db taxa relative to the total taxa per functional plant type. Significant differences between groups were tested by pairwise comparison with Bonferroni correction. The same methods were used to compare families. Based on the taxonomic name, taxa were grouped into different plant families. Only families with a minimum of five non-db taxa were investigated.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This paper uses a spatially expansive selection of sediment cores distributed across eastern Siberia and Alaska to assess potential vegetation extirpations or extinctions using sediment aDNA. By pooling multiple DNA datasets, the authors had improved taxon assignments, and identified ~60 potential sequences that had no modern match. Their aim was to understand the potential role of megafaunal extinctions and abrupt climate change on vegetation turnover and/or taxon extirpations or extinctions during a period of widespread global change.\nWhile I find the study's premise exciting and the broader topic is of high relevance, this paper is undermined by several flaws in the framing and the approach. These could perhaps be ameliorated, but there will still be some limits that need better qualification and transparency. The paper could be better organized, and it often feels as though the megafauna story is tacked on as an afterthought. There are also a number of key references missing (even understanding the brevity necessary for a paper of this type). As a result, the overall scholarship fails to position the paper within broader dialogues about drivers of plant diversity, extinction, and megaherbivore ecology. This in turn undermines the arguments, as some statements (noted throughout below) are either incorrect or are more nuanced or complex than is being represented here (for example, our understanding of the underpinnings of extinction risk is much more nuanced and dynamic than is represented here).\nAs an example, the authors state that “we identified potential plant taxa loss events that happened in parallel to both the Plesistocene mammoth-steppe loss (vegetation turnover) and the megafauna extinction showing the importance of of past trophic interactions and potential co-extinction events in parallel to the loss of past biota,\" but this argument is not well-scaffolded throughout-- the setup and supporting literature are missing, and the discussion focuses more on the approach, at the expense of the ecological questions this paper is attempted to grapple with. This is a fixable problem, but it's going to take a lot of engagement with the literature and some reframing of the text.\nPerhaps more critically, though, I have two major concerns about the experimental design. While I'm enthusiastic about these questions and the promise of the methods in addressing them, it just may not be possible to do what you're trying to do, and at a minimum, this text needs a lot of qualifying statements. My first concern is that the taphonomy of sedaDNA does not allow for us to say anything about extinction or even extirpation at this coarse spatial resolution. We can certainly say that some sequences were locally extirpated, but this requires a more up-front framing of what \"local\" means in a sedaDNA record (i.e., within the catchment area of the lake, within the proxy's representation, etc., which is not large for sedaDNA). In terms of spatial grain, eight lakes spanning a broad geographic range is not sufficient to capture biodiversity loss, especially when the source area of sedaDNA is so small compared with, e.g., pollen (which has too coarse a taxonomic resolution).\nSecondly, I am not convinced that an incomplete ASV match means that the taxon has been lost, and while the authors do identify some caveats, many are missing. There could be some within-species variation in sequences due to local adaptation, and we know that many reference datasets have taxonomic errors (i.e., the assignments are not accurate because the species was incorrectly identified). But more importantly, there are gaps in our reference datasets, particularly within the region of this analysis. While it may be the case that the 60 taxa identified as \"missing\" have actually disappeared (though see my previous point about spatial grain), it's just as likely that you have an incomplete library problem. I may have missed it, but this appears not to have been discussed at all, even in the caveats section.\nHere's why this gets tricky: the authors identify an extinction window of 19,000 to 9,000 BP, but the problem is, this corresponds with the period of highest climate-driven taxonomic turnover due to climate-driven range shifts.\nAs far as calculating extinction rates, this is not even typically done for the entire Quaternary, let alone a particular time slice within it. The reason the denominator for extinction rates is a million years is because there is variability at shorter timescales. Elevated rates above background are just hard to quantify at timescales this small.\nUltimately, while I’m really excited by the questions this paper asks, and I am really supportive of the authors using some interesting and novel approaches to gain traction, I’m just not convinced that this study isn't just showing what we already know, but in a more taxonomically detailed way: that megafaunal losses are associated with the collapse of the mammoth steppe and widespread vegetation turnover. Without confidence that these are actual extirpations, rather than range shifts or contractions, it’s not clear what we’ve gained by adding the higher taxonomic resolution of sedaDNA. I would suggest reframing this story as being about sequence losses, because loss of genetic diversity is, at a minimum, locally important and a precursor to extinction.\nAs a final note, using pollen-based temperature reconstructions to explain aDNA-inferred taxon losses is circular, because both proxies come from the same place (plants). While I deeply sympathize with the lack of regional resolution independent paleoclimate records, some do exist (including from some of the sites used in this study), so I’m curious why the authors chose not to include those records? Or why not use paleoclimate simulations? And rather than MAT, I would recommend using bioclimatic variables that have been shown to be the most important for limiting plant ranges, such as mean temperature of the coldest month and precipitation (both means and seasonality). This has the potential to be far more informative. While I deeply appreciate that such data are limited for the paleorecord, we can definitely do better than the circularity of pollen-derived MATs. At a minimum, I’d like to see some alternatives used here.\nSome line-by-line comments follow:\n90-94 It’s not entirely clear what’s meant by this paragraph – do you mean that aDNA sequences can be used as a proxy to reconstruct community and range dynamics? That seems straightforward, but this should be clarified, and also include some discussion about how relative abundance cannot (yet, at least) be inferred from sedaDNA records.\nFig. 2 It seems weird to include carnivores (Homotherium, Panthera) in this figure. I would explain the justification or focus just on herbivores.\n359 “It” has an unclear antecedent here.\n365-368 This is bordering on tautology – there was more turnover because there was more turnover.\n369-371 This final sentence feels vague and underdeveloped – it’s not entirely clear what the conclusion is meant to be.", "reviewer_2": "In their paper 'Potential plant extinctions with the loss of the Pleistocene mammoth-steppe' Courtin et al. use metabarcoding to investigate loss of plant species in arctic Russia and Alaska during the transition from the Pleistocene to the Holocene. They do so by characterizing ASVs according to their similarity to their reference database, and, in cases where ASVs appears distinct from both modern time slices and the reference database, they characterize that ASV as potentially extinct.\nI like the overall angle of the manuscript, and I agree with the authors that plant extinctions are terribly understudied. However, my main concern with this manuscript also relates to the focus on extinctions in the paper. I am not convinced that what the author quantify is actually extinctions. Could it not simply be range shifts, in combination with incomplete databases? I think the paper could benefit from a slight rewriting, with less emphasis on extinctions and more focus on community changes and perhaps loss of diversity.\nFurthermore, it might be beyond the scope of this paper, but the conclusions here could be strengthened by including more data. I know that the paper ‘Fifty thousand years of Arctic vegetation and megafaunal diet’ has a large trnL-gh dataset from the same area. Perhaps this dataset could be merged with the dataset at hand?\nThat being said, I think that this is an important paper with a novel approach to analysyse these increasingly large and complicated metabarcoding datasets, and I think that it is a good fit for Nature communications.\nMinor comments:\nFig 1:\nI think that the map from figure 4 should be moved to this figure.\nFurthermore, I would recommend splitting figure 1c into two panels, one for candidate taxa and one for dbtaxa. This would make it easier for the reader to appreciate subtle differences between the two. It is also currently a bit confusing that the same colours are repeated twice.\nLine 140: This assumption is almost certainly incorrect. If you sampled more in the modern time slice, you might find many of these ‘extirpated’ taxa.\nLine 146: ‘the proportion of candidate taxa present in a time-slice decreases through time’ I don’t think that this is supported by the data in Fic 1c.\nFig 2:\nIt is not clear how the confidence threshold of 80% was chosen.\nFurthermore, it would be interesting to also have the Greenland ice core data to compare with (perhaps overlaid on fig 2d).\nFig 4:\nThis figure gives a good overview of the analystical approach. Perhaps it should be moved, so that this becomes the new figure 1.", "reviewer_3": "The authors have provided an important new contribution to our understanding of plant extinction and extirpation in the former “Mammoth Steppe” landscapes of the northern high latitudes. The geographic range of their study makes the work particularly valuable for scholars focusing on the Late Quaternary Extinctions and the patterns and processes driving that episode in Earth history. The dynamics of plant communities during and following the LQE are still not well understood. The authors have added new depth to this particular field by taking an expansive view across multiple Siberian/Alaskan biomes as they exist today. Their analysis of sedimentary DNA taken from lake cores drawn from multiple sites reveals significant patterns of plant losses correlating with known waves of large herbivore extinctions leading to the disappearance of the Mammoth Steppe. They find that rates of plant losses may have reached 120 times the background rates of extinction. Their results show these episodes correlate with rapid environmental shifts of the Late Pleistocene. Such instability becomes most pronounced in the high latitudes. From this, the authors make a good case for the relevance of their analysis of paleoecological proxy data, given that climate and environmental change in these regions is proceeding considerably more rapidly today. This report is building on a growing body of work in this area that is well-referenced here.\nMy comments below are minor but mainly focus on the clarity of the writing so as to make it more accessible to a wider body of readers.\nFrom the Abstract and in the Introduction and other sections, plant losses are characterized as “extirpations”, and “potential extinctions”, but these terms should be clearly defined and explained as they apply to the findings presented here. I am sure the authors have precise meanings for each of these terms, and I assume neither means actual extinction. It would be most helpful to the reader if these terms were explained early on in the Introduction. For the Abstract, I would suggest wording that briefly draws out the meaning of each, rather than introducing both terms parenthetically (line 19). Since the main thrust of the subsequent data interpretation hinges on these two concepts, it is important to have them made clear at the outset.\nBeta diversity is another term that although used in certain areas of community ecology, is not commonly used in paleoecological studies. It would be helpful to the reader if the authors explained this concept early on in the Introduction, as it also is pivotal to their data interpretation.\nIn the Discussion section, (line 262 and following) in referring to the two waves of megafaunal extinction, the first during the Late Glacial Maximum; and the second peaking between 15,000 and 10,000 years bp., we learn that “estimated plant extirpation” peaking around 13,000 bp, (in the middle of this time interval) does not correlate with megafaunal losses. Nevertheless, “potential plant extinction” does correlate with this second wave. At first, this seems paradoxical. No doubt this is an instance of the particular uses of the terms as outlined above in 1).\nIt would be useful to have at least a brief description of the geographic setting of each of the sites where the cores were taken. As it is, the map in Figure 4 and Table 1 appear to be the only places where the reader can find this information, yet this would involve following each of the references listed in the far right column of Table 1."}, "author_response": "Point-by-Point response Reviewer1:\nReviewer1 major comment: This paper uses a spatially expansive selection of sediment cores\ndistributed across eastern Siberia and Alaska to assess potential vegetation extirpations or\nextinctions using sediment aDNA. By pooling multiple DNA datasets, the authors had\nimproved taxon assignments, and identified ~60 potential sequences that had no modern match.\nTheir aim was to understand the potential role of megafaunal extinctions and abrupt climate\nchange on vegetation turnover and/or taxon extirpations or extinctions during a period of\nwidespread global change.\nWhile I find the study's premise exciting and the broader topic is of high relevance, this paper\nis undermined by several flaws in the framing and the approach. These could perhaps be\nameliorated, but there will still be some limits that need better qualification and transparency.\nThe paper could be better organized, and it often feels as though the megafauna story is tacked\non as an afterthought. There are also a number of key references missing (even understanding\nthe brevity necessary for a paper of this type). As a result, the overall scholarship fails to\nposition the paper within broader dialogues about drivers of plant diversity, extinction, and\nmegaherbivore ecology. This in turn undermines the arguments, as some statements (noted\nthroughout below) are either incorrect or are more nuanced or complex than is being\nrepresented here (for example, our understanding of the underpinnings of extinction risk is\nmuch more nuanced and dynamic than is represented here).\nAs an example, the authors state that “we identified potential plant taxa loss events that\nhappened in parallel to both the Plesistocene mammoth-steppe loss (vegetation turnover) and\nthe megafauna extinction showing the importance of of past trophic interactions and potential\nco-extinction events in parallel to the loss of past biota,\" but this argument is not well-\nscaffolded throughout-- the setup and supporting literature are missing, and the discussion\nfocuses more on the approach, at the expense of the ecological questions this paper is attempted\nto grapple with. This is a fixable problem, but it's going to take a lot of engagement with the\nliterature and some reframing of the text.\nOur response: Thank you for your comment. We believe the strength of this manuscript lies\nin its novel systematic approach to handling sedaDNA data. Following your advice, we have\nadded additional citations to enhance the ecological discussion. The first paragraphs of the\ndiscussion now emphasize the robustness of our results while addressing caveats and potential\nlimitations. Additionally, we have revised the rest of the discussion to focus more on the\necological implications rather than the methodological approach.\nNew text: line 305 to 385 for the discussion of limitations and robustness.\nReviewer1 major comment: Perhaps more critically, though, I have two major concerns about\nthe experimental design. While I'm enthusiastic about these questions and the promise of the\nmethods in addressing them, it just may not be possible to do what you're trying to do, and at\na minimum, this text needs a lot of qualifying statements. My first concern is that the\ntaphonomy of sedaDNA does not allow for us to say anything about extinction or even\nextirpation at this coarse spatial resolution. We can certainly say that some sequences were\nlocally extirpated, but this requires a more up-front framing of what \"local\" means in a\nsedaDNA record (i.e., within the catchment area of the lake, within the proxy's representation,\netc., which is not large for sedaDNA). In terms of spatial grain, eight lakes spanning a broad\ngeographic range is not sufficient to capture biodiversity loss, especially when the source area\nof sedaDNA is so small compared with, e.g., pollen (which has too coarse a taxonomic\nresolution).\nOur response: Thank you for your comment. We conducted new tests and made additional\nefforts to highlight the robustness of our approach in demonstrating past plant extinctions. We\nnow provide a minimum and maximum extinction rate while remaining conservative in our\nestimates. The main text now includes results showing that the lost non-dbtaxa are not only a\nfraction missing from the SibAla_2023 reference database. Furthermore, we tested whether the\nsmall fraction of lost non-dbtaxa matching to other databases correspond to related species that\nmight have survived in refugia. Additionally, we have added new paragraphs in the discussion\nthat extensively presents the potential limitations of our approach and the taphonomy of\nsedaDNA. We used all available cores that covered the Pleistocene to Holocene transition with\ngood sample resolution, ensuring samples from each 2000-yrs time slice over the last 28,000\nyears. While more sites should be investigated to allow a more robust estimate, our study of\nseven sites does confirm the general assumption that Pleistocene plant extinction rates are far\nlower than those for mammals. We hope that our study can be used as a baseline with an\nestablished methods on how extinction events can be explored using sedaDNA datasets for\nfuture studies that will incorporate more sites and better reference databases and encourage the\ncommunity to work in that direction.\nNew text: line 182 to 224 for the description of further analysis to improve the robustness of\nour approach and the new estimated range of potentially extinct fraction.\nReviewer1 major comment: Secondly, I am not convinced that an incomplete ASV match\nmeans that the taxon has been lost, and while the authors do identify some caveats, many are\nmissing. There could be some within-species variation in sequences due to local adaptation,\nand we know that many reference datasets have taxonomic errors (i.e., the assignments are not\naccurate because the species was incorrectly identified). But more importantly, there are gaps\nin our reference datasets, particularly within the region of this analysis. While it may be the\ncase that the 60 taxa identified as \"missing\" have actually disappeared (though see my previous\npoint about spatial grain), it's just as likely that you have an incomplete library problem. I may\nhave missed it, but this appears not to have been discussed at all, even in the caveats section.\nOur response: Thank you for your comment. Taking this into account, we performed extensive\ntests to highlight the robustness of our results, such as checking the database coverage and the\nhypothesis of refugia. We now provide a range of potential extinction from 1.7 to 5.9 E/MSY\nwhich are above background extinction but below modern estimates. Additionally, we\nrestructured all sections of the manuscript to better emphasize the strengths and caveats of our\nstudy. In the introduction, we provide further information on the limitations of existing methods\nand how our approach addresses these issues. In the discussion, the first paragraphs now focus\non highlighting our main results and placing them in the context of known biases and caveats\nwithout diminishing their significance.\nNew text: line 87 to 11 for the introduction of limits of current methods. Line 305 to 385 for\nthe discussion of limitations and robustness of our approach.\nReviewer1 major comment: Here's why this gets tricky: the authors identify an extinction\nwindow of 19,000 to 9,000 BP, but the problem is, this corresponds with the period of highest\nclimate-driven taxonomic turnover due to climate-driven range shifts.\nOur response: Thank you for your comment. This is true, and indeed it may be hard to\ndistinguish turnover from extinction, as both are likely to take place at the same time. If all loss\nof non-dbtaxa was solely due to range shift and thus represent extirpation, we would expect the\nproportion of loss to be equal for dbtaxa and non-dbtaxa. The somewhat higher loss of non-\ndbtaxa may be ascribed that they in general are more rare and thus difficult to detect.\nAlternatively, they may represent global extinction, as suggested by the fact that most are\nmissing from modern global databases. We have now made this point clearer in the discussion.\nFurther, species turnover implies species replacement and loss in the study area that can be due\nto climate change and range shifts. With ongoing climate-driven changes, we observe that plant\nspecies are both changing range and going extinct during modern times. Therefore, we\nhypothesize that a fraction of past plant species facing similar stresses and constraints could\nalso have gone extinct in parallel to others shifting range. Additionally, we have included\nanother test to highlight the robustness of our approach and for example while checking among\nthe lost non-dbtaxa, we estimate that only a small fraction of these species matches other\ndatabases and could have survived in refugia (6 taxa) and therefore lower our estimate for\npotential plant extinction now ranging from 17 to 59 taxa.\nNew text: Line 333 to 340 for the clarification in the discussion. Line 211 to 221 for the\npotential refugia check.\nReviewer1 major comment: As far as calculating extinction rates, this is not even typically\ndone for the entire Quaternary, let alone a particular time slice within it. The reason the\ndenominator for extinction rates is a million years is because there is variability at shorter\ntimescales. Elevated rates above background are just hard to quantify at timescales this small.\nOur response: Thank you for your comment. The extinction rates we calculated are also used\non ongoing extinctions as highlighted in Cowie et al., 2022. In this case, the rates are derived\nfrom short-term observations (taxonomic identification has only existed for a few centuries),\nand not all taxa have been described, so there is only an estimate of the total number of taxa.\nWe assume that both modern data and past sedaDNA-based data face similar limitations.\nTherefore, we used these rates to provide a basis for comparison between extinction rates that\noccurred during the transition between the Pleistocene and the Holocene and modern rates.\nReviewer1 major comment: Ultimately, while I’m really excited by the questions this paper\nasks, and I am really supportive of the authors using some interesting and novel approaches to\ngain traction, I’m just not convinced that this study isn't just showing what we already know,\nbut in a more taxonomically detailed way: that megafaunal losses are associated with the\ncollapse of the mammoth steppe and widespread vegetation turnover. Without confidence that\nthese are actual extirpations, rather than range shifts or contractions, it’s not clear what we’ve\ngained by adding the higher taxonomic resolution of sedaDNA. I would suggest reframing this\nstory as being about sequence losses, because loss of genetic diversity is, at a minimum,\nlocally important and a precursor to extinction.\nOur response: Thank you for your comment and interest in our study. The method we applied\nwas specifically designed to identify patterns of appearance and disappearance of plant taxa\nover time, using a community approach rather than relying solely on the best assigned\ntaxonomic name. We decided to focus on estimating potential extinction rates and conducted\nfurther tests to underscore the robustness of our results. We hope these additions convince you\nthat we could identify potential plant extinctions during this period, as indicated by the loss of\nDNA sequence signals absent from modern DNA databases. Additionally, the marker used in\nour study is effective for identifying plant taxa using small (ancient) DNA fragments but is\nlimited when investigating population genetics. For such investigations, other approaches, such\nas metagenomics with hybridization capture or shotgun sequencing, would be recommended.\nWe understand and agree that the framing of the study needed improvement. To address this,\nwe have completely restructured the introduction, adding more literature to emphasize previous\nwork in the field of paleoecology and highlighting nuances and unresolved questions.\nAdditionally, we have worked to provide more ecological context to the study, thereby\nenhancing its framework. Similar restructuring has been performed in the discussion section to\nbetter scaffold our arguments. This section has been revised with new paragraphs to highlight\nsome limitations while still pinpointing the main results this study can offer within the\nconstraints of sedaDNA datasets.\nNew text: line 182 to 224 for the new results presented to improve the robustness of our results\nand refine the potentially extinct taxa rates to a range. Line 58 to 62, 71 to 73 and 76 to 81 for\nadded literature in the introduction.\nReviewer1 major comment: As a final note, using pollen-based temperature reconstructions\nto explain aDNA-inferred taxon losses is circular, because both proxies come from the same\nplace (plants). While I deeply sympathize with the lack of regional resolution independent\npaleoclimate records, some do exist (including from some of the sites used in this study), so\nI’m curious why the authors chose not to include those records? Or why not use paleoclimate\nsimulations? And rather than MAT, I would recommend using bioclimatic variables that have\nbeen shown to be the most important for limiting plant ranges, such as mean temperature of the\ncoldest month and precipitation (both means and seasonality). This has the potential to be far\nmore informative. While I deeply appreciate that such data are limited for the paleorecord, we\ncan definitely do better than the circularity of pollen-derived MATs. At a minimum, I’d like to\nsee some alternatives used here.\nOur response: Thank you for your comment. Regarding the use of pollen-based temperature\nreconstruction, we tested several proxies for past climate changes, including simulated\ntemperature and precipitation estimates from records covering the study area (Dallmeyer et al.,\n2022, 10.1038/s41467-022-33646-6) and temperature and precipitation estimates from pollen-\nbased reconstruction (both MAT and WA-PLS, Herzschuh et al. 2022, 10.5194/essd-14-3213-\n2022). After concluding that both simulated and pollen-based reconstructions yielded similar\nresults (i.e., correlation to plant taxa loss), we chose to use the pollen-based data. This decision\nwas based on known evidence that pollen-based reconstructions generally align better with\nexpected regional changes than simulated data. This is further detailed in the supplementary\nnote 6.\nSome line-by-line comments follow:\nReviewer1 minor comment: 31 While patterns of extinction remain poorly constrained (due\nin part because of poor biodiversity estimates) I don’t think it’s accurate to say that the drivers\nof extinction remain unknown. There’s a broad literature about the causes of extinction that\nthis statement glosses over.\nOur response: Thank you for your comment. We agree that our point was not clear and may\nhave been misleading. To address this, we have completely rewritten the introduction to\nimprove the overall framework of the study and clarify our approach.\nReviewer1 minor comment: 35 This is a misrepresentation of the literature. The paper cited\n(4) does not argue that estimates are unreliable, but rather points out a discrepancy between\npredictions and reality. There are a number of potential mechanisms beyond data quality that\nare explored in the paper and elsewhere, and this statement and its citations aren’t doing that\nliterature justice.\nOur response: Thank you for your comment. As previously mentioned, we agree that the first\nversion of the introduction did not adequately highlight previous work in the field. We have\ncompletely reworked and restructured the introduction to address this issue.\nReviewer1 minor comment: 36 This statement is a bit misleading, and is missing a number\nof key references on the impacts of climate change on extinction. The paper cited doesn’t\nactually refer to debates, but rather points out that climate change is seldom included in the\nassessment of extinction risk in IUCN Red list criteria. There have been numerous studies,\nboth for individual species and broadly across clades, that seek to forecast extinction risk due to\nclimate change. Those paper should be cited at a minimum.\nOur response: Thank you for your comment. We believe that we have addressed this concern\nand clarified our introduction in its revised version by adding further literature.\nReviewer1 minor comment: 38 This would be a great place to cite the conservation\npaleobiology literature.\nReviewer1 minor comment: 46 But see also: Winter et al., 2009, PNAS\n(https://doi.org/10.1073/pnas.0907088106), Purvis 2008, Annual Rev. of Ecology and\nSystematics (https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-063008-\n102010), Davies et al., 2011\n(https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1000620)...and others\nwhich contradict this statement.\nOur response: Thank you. With your general comments in mind, we now implemented further\ncitations to better highlight previous conservation paleobiology literature and nuanced our\noriginal introduction.\nNew text: Added literature as recommended line 58 to 62 and 71 to 81 for example.\nReviewer1 minor comment: 54 The question of whether there were plant extinctions driven\nby megafaunal extinctions is intriguing, but needs more development here. Most ecosystems\nthat lost megaherbivores did retain some examples, and we don’t see the disappearance of\nbiomes per se.\nOur response: Thank you for your comment. Considering that the mammoth steppe biome\nlacks a modern analogue, except for potential relicts in the Altai mountain range, and given the\nsimultaneous occurrence of megafaunal extinction during the transition between the\nPleistocene and the Holocene, we believe this context scaffolds well the hypothesis of potential\nplant extinction.\nNew text: line 48 to 66.\nReviewer1 minor comment: 56 I don’t typically see a hyphen between “mammoth” and\n“steppe” and would suggest removing it.\nOur response: Thank you for your comment. We removed the hyphen throughout the\nmanuscript.\nReviewer1 minor comment: 57 This is unclear. If the species range shifts are plant species\nrange shifts, that’s a mechanism to avoid extinction during climate change, no?\nOur response: Thank you for your comment. It is well established that species possess specific\ngeographic ranges, and they may attempt to track environmental changes if their niche changes\nwith climate change. However, certain species may be unable to shift their ranges at a pace\ncommensurate with the rapidity of environmental shifts. Consequently, they face the risk of\nrange contraction, extinction, or complete habitat loss (Parmesan et al., 2005, 10.1175/1520-\n0477(2000)081 ; Urban, 2015, 10.1126/science.aaa4984).\nReviewer1 minor comment: 58 This paper explores forecasted extinction risks, but there are\na number of studies on the impacts of Quaternary climates and megafaunal extinctions on plant\nranges and extinctions, and the framing in the next sentence “this tremendous climate and\necosystem change” implies that this reference [20] is relevant to that.\nOur response: Thank you for your comment. We reworked the introduction and therefore this\nsentence do not exist anymore. This reference is now cited as 13.\nNew text: line 41 to 42 for new citation of this reference.\nReviewer1 minor comment: 60 I would cite Botkin et al., 2007, BioScience\n(https://doi.org/10.1641/B570306), which refers to a “Quaternary conundrum.” There is also\ndeeper-time literature that discusses the resilience of plants in the extinction record that would\nbe worth citing in this intro, too, such as McElwain & Punyasena 2007, TREE\n(https://doi.org/10.1016/j.tree.2007.09.003) and Scott Wing’s chapter on plants and mass\nextinctions in Extinctions in the History of Life. I would also make it clear that it's not an\nabsence of study driving the few documented plant extinctions at the Pleistocene-Holocene\ntransition. This has been a widely recognized phenomenon. It’s not that people haven’t looked.\nOur response: Thank you for your comment. We acknowledge that previous studies were not\nadequately highlighted in the initial version of the manuscript. To address this, we have\nenhanced the introduction by conducting additional literature review and including an\nexpanded bibliography including some papers you recommended.\nNew text: line 58 to 62, 76 to 78 and 81 to 84 are examples where we added the recommended\nliterature.\nReviewer1 minor comment: 65 Do we have the ability to say that this transition resulted in a\nloss of diversity per se? This is a great place to point out the taxonomic coarseness of pollen\ndata, and how aDNA can improve diversity estimates.\nOur response: Thank you for your comment. We refer to two studies conducted in areas that\nexhibited a decline in plant richness during the transition between the Pleistocene and the\nHolocene (Courtin et al., 2021, 10.3389/fevo.2021.625096; Huang et al.,\n2021,10.3389/fevo.2021.763747 ).\nNew text: line 55 to 57.\nReviewer1 minor comment: 69 P. critchfieldii wasn’t necessarily common – the plant\nmacrofossils were found in the southeastern United States, and it was likely already in low\nabundance based on the available evidence (though this could reflect a paucity of sites).\nOur response: Thank you for your comment. We agree with your observation and have made\nthe necessary modifications. Nonetheless, the confirmed extinction of only one plant species\nin the study area at the transition is of significant interest to us. This finding highlights the\noccurrence of plant extinction, a factor often underestimated in other studies, primarily due to\nthe inadequate preservation of plant fossils that would enable species-level identification and\npotentially reveal extinct plant species. We believe that using this example serves as a solid\nfoundation for formulating hypotheses regarding the potential extinction of other plant species\nduring the critical transition from the last glacial period to the Holocene.\nNew text: line 58 to 60.\nReviewer1 minor comment: 70 Large physical size or range size? Both?\nOur response: Thank you for your comment. We have rewritten this entire section, paying\ncloser attention to clearly specify whether we are referring to large mammals or expansive\ngeographic regions.\nReviewer1 minor comment: 72 This is confusing in the context of the paleorecord. When\ntalking about pollen, plant macrofossils, and DNA, size has little bearing on proxy-based\nreconstructions of species?\nOur response: Thank you for your comment. Once again, we have completely revised this\nsection to enhance clarity. Your feedback has been invaluable in helping us recognize the need\nfor this rewrite.\nReviewer1 minor comment: 72 This has been extensively researched in modern systems,\nthough. It’s also unclear what this statement means in the context of this paragraph – if you’re\nreferring to paleo extinctions, those apparently have not occurred, so this isn’t a knowledge\ngap. If you’re referring to modern extinctions, that’s a subject of active research, and this point\nalso doesn’t’ follow from the preceding sentences. It feels like this section contains several\ndifferent ideas and it’s unclear how they are connected, especially as you weave in modern and\npaleo phenomena and data sets.\nOur response: Thank you for your comment. You are entirely correct. It was never our\nintention to disregard previous work; rather, we aimed to emphasize the use of sedaDNA in\ninvestigating paleoextinction. In revising the introduction, we have tried to better highlight\nprevious research on ongoing extinction. While considerable research has been conducted on\npast plant extinctions during mass extinction events, the extinctions that occurred at the\ntransition between the last Glacial and Holocene did not reach such magnitude, whether in the\nmammoth steppe or other continents, especially for well-studied groups like megafauna.\nSimilarly, the extent of potential plant extinction identified in our study does not approach the\nscale of mass extinction events. Therefore, we deemed it unnecessary to extensively introduce\npast research on mass extinctions.\nReviewer1 minor comment: 77 There have been several studies recently that use aDNA to\nassess plant diversity changes within the mammoth steppe at the local scale, which is “sub-\ncontinental,” so I would clarify the spatial extent you’re referring to here.\nOur response: Thank you for your comment. You are correct. We have now emphasized that\nthis study utilizes multiple sites, providing a sub-continental scale perspective. Unlike other\nstudies with multiple sites, our approach ensures sample resolution across all time series for all\nsites. For example, Wang et al. 2021 (10.1038/s41586-021-04016-x) lacked the necessary\nresolution to investigate taxa appearance and disappearance through time due to missing\nsamples from recent times. This limitation prevented us from applying our method to their\ndataset, as we were unable to clearly identify Amplicon Sequence Variants and taxa absent\nfrom the modern time.\nNew text: line 87 to 89.\nReviewer1 minor comment: 79 It appears that the majority of the pollen types in this dataset\nare at the genus level, not family level?\nOur response: Thank you for your comment. This has been modified and clarified.\nNew text: line 89 to 90.\nReviewer1 minor comment: 90-94 It’s not entirely clear what’s meant by this paragraph – do\nyou mean that aDNA sequences can be used as a proxy to reconstruct community and range\ndynamics? That seems straightforward, but this should be clarified, and also include some\ndiscussion about how relative abundance cannot (yet, at least) be inferred from sedaDNA\nrecords.\nOur response: Thank you for your comment. As previously mentioned, the introduction has\nbeen completely reworked in an effort to reframe the study and clarify our approach.\nNew text: line 109 to 111\nReviewer1 minor comment: 94 How can you distinguish between plants that are missing in\nreference libraries and plants that have gone extinct prior to the establishment of those libraries?\nAre there particular bioinformatic approaches?\nOur response: Thank you for your comment. We realized that this aspect was not clear in the\nfirst version of the paper. Therefore, we have made a concerted effort to enhance the\nexplanation of our new systematic method for identifying unknown taxa, particularly those\nabsent from reference libraries, and detecting potential extinction signals. As detailed in the\nmain text, this involves taxonomic identification using similarities ranging from 90% to 100%,\nwhich permits mismatches with the reference libraries. Subsequently, to mitigate potential PCR\nor sequence errors, we have introduced a novel co-occurrence-based approach and community\ndetection method to filter out Amplicon Sequence Variants (ASVs) assigned with 90-99%\nconfidence (non-dbASVs) that exhibit similar patterns to 100% assigned ASVs (dbASVs) and\nshare comparable taxonomic names. While this approach is highly conservative, it enables us\nto retain only those candidate taxonomic names with distinctive co-occurrence patterns.\nNew text: line 596 to 609 and 619 to 629.\nReviewer1 minor comment: 104 No hyphen needed between “lake” and “sediment.”\nOur response: Thank you for your comment. We removed the hyphen.\nReviewer1 minor comment: 128 I would like to see the actual proportions listed across these\ntime bins (i.e., quantify the increase).\nOur response: This section is not present anymore in the main text. You can find some extra\ninformation about the compositional changes in the supplementary note 4.3: In the samples\nfrom the Pleistocene (~27,000 to ~17,000 cal. yrs BP), 78.3% of the taxa were either forbs or\ngraminoids, with more than 42% of the overall reads assigned. After the LGM, between\n~15,000 and ~9,000 cal. yrs BP, there was a shift towards more shrub and tree taxa in the study\narea. Between ~7,000 and ~1,000 cal. yrs BP, 29.5% of all taxa are assigned to shrubs or trees\nwith more than 91% of the overall reads assigned. For the dbtaxa we see a small decrease in\nforbs (73.5% of all dbtaxa before 15,000 cal. yrs BP and 71% after 9,000 cal. yrs BP) and\ngraminoids (11.6% to 8.1%) between the Pleistocene and the Holocene. The non-dbtaxa are\ngenerally more impacted with a decrease from 5.5% to 3.1% for graminoids and especially\nfrom 61.4% to 42.4% for forbs between before 15,000 cal. yrs BP and after 9,000 cal. yrs BP.\nReviewer1 minor comment: 140 I interpret “modern time slice” to mean sediments from core\ntops, but if that’s not the case, this needs to be more clear. Readers will not have read the\nmethods at this point in the paper, so clarity here is especially important.\nOur response: Thank you for your comment. You interpreted correctly the term modern time\nslice. It corresponds to the samples from sediments dated between 0 to 2000 cal yrs BP.\nNew text: line 174\nReviewer1 minor comment: Fig. 2 It seems weird to include carnivores (Homotherium,\nPanthera) in this figure. I would explain the justification or focus just on herbivores.\nOur response: Thank you for your comment. The extinct mammals in question were predators\nof megaherbivores. We believe this underscores the occurrence of co-extinction events within\nthe mammoth steppe ecosystem, closely linked with the extinction of megafauna. This aspect\naligns well with the main theme of our study, which focuses on highlighting further instances\nof co-extinction, this time within the Viridiplantae kingdom.\nReviewer1 minor comment: 289 Possibly, though there are plenty of counter-examples of\nrare taxa that have survived as rare taxa for a very long time, and many abundant plant taxa\nwent extinct in Europe (see: Svenning and Skov’s work on European tree extinctions).\nOur response: Thank you for your comment. We now better nuance this and highlight that\ncounter examples exist.\nNew text: line 472 to 474.\nReviewer1 minor comment: 293 The use of present tense here and in preceding sentences\nmuddies the waters a bit. I would suggest past tense for results, which will make it more clear\nthat you are talking about your results and not generalisms.\nOur response: Thank you for your comment. We restructured and rewrote the entire section\nto improve the clarity.\nNew text: line 458 to 494\nReviewer1 minor comment: 303 This is potentially significant, and so I would like to see\nsome discussion about why that is. Is it a rarefaction artifact (i.e., there were more forb and\ngraminoids, so they are statistically likelier to go extinct)?\nOur response: Thank you, this is a valuable comment. We changed the figure 4 and it now\nhighlights the proportion of missing taxa per functional group relative to the total number of\ntaxa. However, in supplementary figure 10, you can see the same figure but relative to the\nnumber of non-dbtaxa for each functional group. You can see that ~70% of non-dbtaxa that are\ngrasses and ~55% that are forbs are likely to be absent from modern times. This is much higher\nthan the non-dbtaxa shrubs and trees.\nReviewer1 minor comment: 315 This is a crucial point that should be highlighted sooner in\nthe text, but it also needs some qualification, because the databases themselves are incomplete,\nwhich is a point that is glossed over in this text.\nOur response: Thank you for your comment. We now introduce it better in the introduction\nand highlight the limitations and robustness of our approach in the first paragraph of the\ndiscussion to not leave ambiguities regarding the significance of our main results discussed.\nNew text: Line 95 to 98 and line 341 to 349.\nReviewer1 minor comment: 342 Or from Asparagaceace that just haven’t been added yet.\nOur response: Thank you for your comment. This possibility has been addressed and tested\nby examining taxa present in the Global Biodiversity Information Facility database (GBIF).\nThis assessment aims to determine whether the lost non-dbtaxa represent only a fraction of taxa\nnot covered by the reference database or if they signal potentially extinct taxa. To provide a\ncomprehensive view, we now present both a minimum and maximum extinction rate, both of\nwhich exceed background rates. Additionally, in the first paragraph of the discussion section,\nwe emphasize that the discovery of one of the taxa labelled as potentially extinct in fossil\nrecords or modern databases does not invalidate our conclusion regarding the percentage of\nextinct taxa. This is because new data may reveal additional taxa that could also be extinct.\nNew text: Figure1, line 182 to 196 and line 313 to 320.\nunderpinnings of ecological stability (or resistance and resilience) have been extensively\nstudied (though questions still remain), and diverse ecosystems are often more stable even in\nthe face of abiotic instability. And on longer timescales, environmental variability can be a\nspeciation pump that drives diversification. We don’t even know whether the tropics have more\ndiversity because they are stable (museum) or because they drive diversification (cradle).\nOur response: Thank you for your comment. As the text has been entirely restructured and\nrewritten. Still, we tried to be more nuanced as before the sentence was: “Abiotic stability is\nimportant for biotic stability” while we now say that our results provide an argument for this\nhypothesis, and not that it is universally known.\nNew text: line 442 to 444\nReviewer1 minor comment: 359 “It” has an unclear antecedent here.\nOur response: This text has been entirely revised.\nReviewer1 minor comment: 362 Be careful about words like dramatic, which are normative.\nAlso, how does this interpretation stand up to the fact that there have been multiple glacial\ncycles in the Quaternary? Shouldn’t these be taxa that have already adapted to some degree to\nhigh amounts of environmental variability at high latitudes (both seasonally and on glacial-interglacial cycles)?\nOur response: Thank you for your comment. We acknowledge that the Last Glacial to\nHolocene transition differs from previous glacial cycles of the Quaternary. While the mammoth\nsteppe and megafauna managed to survive previous glacial cycles, they did not endure the\ntransition to the Holocene. Further research is required to investigate past glacial and\ninterglacial transitions and understand why megafauna and the mammoth steppe were able to\nwithstand previous transitions but not the last one. Identifying similar mechanisms at play in\nthese transitions could provide valuable insights.\nReviewer1 minor comment: 365-368 This is bordering on tautology – there was more\nturnover because there was more turnover.\nOur response: Thank you for your comment. To avoid tautology, we reformulated.\nNew text: line 517 to 521\nReviewer1 minor comment: 369-371 This final sentence feels vague and underdeveloped –\nit’s not entirely clear what the conclusion is meant to be.\nOur response: Thank you. The final paragraph of the conclusion has been modified to clarify\nit.\nNew text: line 522 to 528\nReviewer1 minor comment: 375 Should be “Bering land bridge.” How do you differentiate\nbetween Beringia, Siberia, and Alaska (if Beringia is inclusive of both)?\nOur response: Thank you. We refer to Beringia as covering Siberia and Alaska. We modified\nthe text accordingly.\nNew text: line 532 to 533\nReviewer1 minor comment: 387 Some of these cores have been published previously – this\nstatement implies that these are new cores. Is that the case, or was previously existing sediment\nused? If the latter, this needs qualifying.\nOur response: Thank you for your comment. A site description is now provided in the\nsupplementary note 1. Further, Table 1 points to references for the cores which previous work\nhave been performed on (age models and sedaDNA).\nReviewer #2 (Remarks to the Author):\nIn their paper 'Potential plant extinctions with the loss of the Pleistocene mammoth-steppe'\nCourtin et al. use metabarcoding to investigate loss of plant species in arctic Russia and Alaska\nduring the transition from the Pleistocene to the Holocene. They do so by characterizing ASVs\naccording to their similarity to their reference database, and, in cases where ASVs appears\ndistinct from both modern time slices and the reference database, they characterize that ASV\nas potentially extinct.\nReviewer2 major comment: I like the overall angle of the manuscript, and I agree with the\nauthors that plant extinctions are terribly understudied. However, my main concern with this\nmanuscript also relates to the focus on extinctions in the paper. I am not convinced that what\nthe author quantify is actually extinctions. Could it not simply be range shifts, in combination\nwith incomplete databases? I think the paper could benefit from a slight rewriting, with less\nemphasis on extinctions and more focus on community changes and perhaps loss of diversity.\nOur response: Thank you for your comments. To improve the clarity of the study and\nunderscore the robustness of our main finding regarding potential plant extinction, we have\nimplemented additional tests to support our conclusion. We completely restructured and\nrewrote the text to ensure clarity. Moreover, we have standardized the vocabulary used to\nclearly convey that our study examines extinction rather than just extirpation. We conducted\ntests to verify that the fraction of lost non-dbtaxa did not solely result from missing taxa in the\nSibAla_2023 database. Additionally, we examined whether only a small fraction of the lost\nnon-dbtaxa matched with other databases and, among the taxa matching, assessed the\nlikelihood of their presence in refugia. In order to provide a more nuanced understanding, we\nnow present both minimum and maximum extinction rates, both of which exceed background\nextinction rates. Still, as some limitations such as the limited number of sites and potential\nrange shifts are present, we now highlight them in the first paragraph of the discussion, and\ndiscuss why our main conclusion, that plant extinction rate was low, is robust to those\nlimitations.\nNew text: line 182 to 224 for the new tests to check robustness of our results. Line 305 to 385\nfor discussion of limitations.\nReviewer2 major comment: Furthermore, it might be beyond the scope of this paper, but the\nconclusions here could be strengthened by including more data. I know that the paper ‘Fifty\nthousand years of Arctic vegetation and megafaunal diet’ has a large trnL-gh dataset from the\nsame area. Perhaps this dataset could be merged with the dataset at hand?\nThat being said, I think that this is an important paper with a novel approach to analysyse these\nincreasingly large and complicated metabarcoding datasets, and I think that it is a good fit for\nNature communications.\nOur response: Thank you for your comment. We appreciate your advice, and we agree that\nincorporating additional sites would enhance the robustness of our results. Consequently, we\nexplored the possibility of merging our dataset with others from studies such as Wang et al.\n2021, 10.1038/s41586-021-04016-x. However, none of the available datasets met the sample\nresolution required to apply our method effectively. For instance, the dataset provided by Wang\net al. lacked samples that adequately covered our modern timeslice, and the sample resolution\nwas insufficient to bin them into 2000-year intervals for investigating appearance and\ndisappearance rates. We believe that the additional work prompted by the reviewers' comments\nsignificantly strengthens our conclusions.\nReviewer2 minor comment: Fig 1: I think that the map from figure 4 should be moved to this\nfigure.\nOur response: Thank you for your comment. As you may have noticed, the figures have been\nrevised. Figure 1 now introduces the map and the methods applied, along with presenting the\nmain results and tests conducted to highlight their robustness.\nReviewer2 minor comment: Furthermore, I would recommend splitting figure 1c into two\npanels, one for candidate taxa and one for dbtaxa. This would make it easier for the reader to\nappreciate subtle differences between the two. It is also currently a bit confusing that the same\ncolours are repeated twice.\nOur response: Thank you for your comment. This figure is now in the supplementary material\nas supplementary figure 3.\nReviewer2 minor comment: Line 140: This assumption is almost certainly incorrect. If you\nsampled more in the modern time slice, you might find many of these ‘extirpated’ taxa.\nOur response: Thank you for your comment. We agree with this statement, although it applies\nto every taxon considered extinct. It is worth noting that some extinct taxa may reappear,\ndespite our efforts to mitigate this possibility. We ensured uniform sampling across all time\nslices, and it is notable that most lost non-dbtaxa disappear from the dataset at 17,000- and\n9,000-years BP. This makes it unlikely for these taxa to reappear. To address this, we developed\nan expected rate based on appearance and disappearance rates, considering that a taxon recently\nlost is more likely to reappear than one lost for multiple time slices. Furthermore, we conducted\ntests to verify that the fraction of missing non-dbtaxa from the modern time slice is not solely\ndue to missing taxa from the reference database, by creating a synthetic dataset from taxa\noccurring in the Global Biodiversity Information Facility database (GBIF).\nReviewer2 minor comment: Line 146: ‘the proportion of candidate taxa present in a time-\nslice decreases through time’ I don’t think that this is supported by the data in Fic 1c.\nOur response: Thank you for your comment. This figure is now presented in the\nsupplementary note 4.3. Further, in the samples from the Pleistocene (~27,000 to ~17,000 cal.\nyrs BP), 78.3% of the taxa were either forbs or graminoids, with more than 42% of the overall\nreads assigned. After the LGM, between ~15,000 and ~9,000 cal. yrs BP, there was a shift\ntowards more shrub and tree taxa in the study area. Between ~7,000 and ~1,000 cal. yrs BP,\n29.5% of all taxa are assigned to shrubs or trees with more than 91% of the overall reads\nassigned. For the dbtaxa we see a small decrease in forbs (73.5% of all dbtaxa before 15,000\ncal. yrs BP and 71% after 9,000 cal. yrs BP) and graminoids (11.6% to 8.1%) between the\nPleistocene and the Holocene. The non-dbtaxa are generally more impacted with a decrease\nfrom 5.5% to 3.1% for graminoids and especially from 61.4% to 42.4% for forbs between\nbefore 15,000 cal. yrs BP and after 9,000 cal. yrs BP. This confirms that over time, non-dbtaxa\nare more often lost in comparison to dbtaxa.\nReviewer2 minor comment: Fig 2: It is not clear how the confidence threshold of 80% was\nchosen.\nOur response: Thank you for your comment. We choose the 80th percentile of the distribution\nto show the variation but also to optimise visual aspects of the figure.\nReviewer2 minor comment: Furthermore, it would be interesting to also have the Greenland\nice core data to compare with (perhaps overlaid on fig 2d).\nOur response: Thank you for your comment. We tested several climate reconstruction\nmethods, which are elaborated on in the supplementary note 6. These included simulated\ntemperature and precipitation estimates from records covering the study area (Dallmeyer et al.,\n2022, 10.1038/s41467-022-33646-6), as well as temperature and precipitation estimates from\npollen-based reconstructions (both MAT and WA-PLS, Herzshuh et al., 2022, 10.5194/essd-\n14-3213-2022). Our analysis indicated that both simulated and pollen-based reconstructions\nyielded similar results in terms of correlation to plant taxa loss. However, based on our\nexperience and the fit of the data to expected changes in the region, we opted for pollen-based\ndata over simulated data.\nReviewer2 minor comment: Fig 4: This figure gives a good overview of the analystical\napproach. Perhaps it should be moved, so that this becomes the new figure 1.\nOur response: Thank you for your comment. This figure has been entirely reworked and is\nnow placed as figure 1 following your recommendation.\nReviewer #3 (Remarks to the Author):\nThe authors have provided an important new contribution to our understanding of plant\nextinction and extirpation in the former “Mammoth Steppe” landscapes of the northern high\nlatitudes. The geographic range of their study makes the work particularly valuable for scholars\nfocusing on the Late Quaternary Extinctions and the patterns and processes driving that episode\nin Earth history. The dynamics of plant communities during and following the LQE are still\nnot well understood. The authors have added new depth to this particular field by taking an\nexpansive view across multiple Siberian/Alaskan biomes as they exist today. Their analysis of\nsedimentary DNA taken from lake cores drawn from multiple sites reveals significant patterns\nof plant losses correlating with known waves of large herbivore extinctions leading to the\ndisappearance of the Mammoth Steppe. They find that rates of plant losses may have reached\n120 times the background rates of extinction. Their results show these episodes correlate with\nrapid environmental shifts of the Late Pleistocene. Such instability becomes most pronounced\nin the high latitudes. From this, the authors make a good case for the relevance of their analysis\nof paleoecological proxy data, given that climate and environmental change in these regions is\nproceeding considerably more rapidly today. This report is building on a growing body of work\nin this area that is well-referenced here.\nReviewer3 minor comment: My comments below are minor but mainly focus on the clarity\nof the writing so as to make it more accessible to a wider body of readers. From the Abstract\nand in the Introduction and other sections, plant losses are characterized as “extirpations”, and\n“potential extinctions”, but these terms should be clearly defined and explained as they apply\nto the findings presented here. I am sure the authors have precise meanings for each of these\nterms, and I assume neither means actual extinction. It would be most helpful to the reader if\nthese terms were explained early on in the Introduction. For the Abstract, I would suggest\nwording that briefly draws out the meaning of each, rather than introducing both terms\nparenthetically (line 19). Since the main thrust of the subsequent data interpretation hinges on\nthese two concepts, it is important to have them made clear at the outset.\nOur response: Thank you for your comment. We have made significant efforts to completely\nrestructure and rewrite the introduction, results, and discussion sections of the main manuscript\nin order to reframe the study and enhance clarity for readers. Moreover, we believe that our\nstudy not only demonstrates extirpation but also potential extinction. We have conducted\nadditional work to bolster the robustness of this main finding. Specifically, we have conducted\nnew investigations to test whether the fraction of lost non-dbtaxa originated solely from\nmissing taxa in the SibAla_2023 database. Furthermore, we have examined whether only a\nsmall fraction of the lost non-dbtaxa matched with other databases and, among the taxa\nmatching, assessed their likelihood of presence in refugia. To add nuance to our study, we now\nprovide both minimum and maximum extinction rates, both of which exceed background\nextinction rates. It's important to note that we maintain a conservative approach in detecting\nnon-db and potentially extinct taxa.\nNew text: line 182 to 224 for the new analysis to test the robustness of our results and refine\nthe potential extinction rates.\nReviewer3 minor comment: Beta diversity is another term that although used in certain areas\nof community ecology, is not commonly used in paleoecological studies. It would be helpful\nto the reader if the authors explained this concept early on in the Introduction, as it also is\npivotal to their data interpretation.\nOur response: Thank you for your comment. We now quickly introduce the concept in the\nintroduction. Beta diversity is used to describe changes between community. It can be\ndecomposed into several components to identify turnover between samples and contribution to\ncommunities.\nNew text: line 106 to 109\nReviewer3 minor comment: In the Discussion section, (line 262 and following) in referring\nto the two waves of megafaunal extinction, the first during the Late Glacial Maximum; and the\nsecond peaking between 15,000 and 10,000 years bp., we learn that “estimated plant\nextirpation” peaking around 13,000 bp, (in the middle of this time interval) does not correlate\nwith megafaunal losses. Nevertheless, “potential plant extinction” does correlate with this\nsecond wave. At first, this seems paradoxical. No doubt this is an instance of the particular uses\nof the terms as outlined above in 1).\nOur response: Thank you for your comment. In order to avoid any confusion, we have shifted\nour focus to emphasize the potential extinction signal which we consider the main finding of\nthis study and have reduced the emphasis on the concept of extirpation. Additionally, we have\nhighlighted the distinction between these two concepts in the introduction.\nNew text: line 85 to 87 for the introduction of both extinction and extirpation concepts.\nReviewer3 minor comment: It would be useful to have at least a brief description of the\ngeographic setting of each of the sites where the cores were taken. As it is, the map in Figure\n4 and Table 1 appear to be the only places where the reader can find this information, yet this\nwould involve following each of the references listed in the far right column of Table 1.\nOur response: Thank you for your comments. A description of the sites is now present in\nsupplementary note 1 to complement Table 1."}, {"round": 2, "reviewer_comments": {"reviewer_2": "In their resubmitted article Courtin et al have used the GBIF database to estimate the expected number of absent species in their SibAla_2023 database. Using simulations based on this fraction the authors are able to estimate how large a proportion of the ‘lost’ taxa that are probably due to incomplete databases. Based on this, the authors estimate that 17 out of 60 species are potentially extinct. I like their approach of using simulations to account for the incomplete reference libraries, and, as such my main concern about the paper have been addressed.\nI still have a couple of comments:\nMaybe I have misunderstood how this simulation works, but the simulation suggests that 42/60 species are due to incomplete databases. What is the error margin on this estimate? Because if the error margin is, say +/- 20, there is no evidence for extinctions at all.\nGiven that the main conclusion of the paper has been changed dramatically (i.e. from “extinction rate was up to 120X above bg” to “extinction rate were below modern estimates”), I think the title should be updated to reflect this. Perhaps the title could start with “Low extinction rates during the loss […]” or “Plant resilience during the […]”\nAnd speaking of the significant change in conclusion, I would like to flag that I am still not 100% convinced of the results. It is a very difficult task the authors have set themselves, estimating species loss. Having worked with metabarcoding data myself, I have sometimes found that seemingly small changes in the filtering stage (for example changing the cutoff from 100 read to 10 reads) can have dramatic effects on downstream analysis. But I guess only time will tell if these conclusions stand in the future.\nMinor comments:\nMy last comment on what is now Supplementary fig 3 still stands. To me it does not make sense to show the non-db and db data stacked in this way, as it veils all patterns for the top category (‘db taxa’ in this case).\nKind regards,\nFrederik Seersholm, University of Copenhagen\n(Remarks on code availability)\nCode was not available for review as the github depositories are not publicly available (yet). It should be noted that according to the authors \"they can be provided upon request\" during the review process.", "reviewer_3": "The authors have addressed each one of my comments and concerns. They have reworked the text accordingly.\nReviewer 1’s comments are incisive and thorough, highlighting some fundamental weaknesses in the structure of the author’s overall argument and how the results have been brought to bear in support of that argument. Reviewer 1 nevertheless expresses enthusiasm for the ambitious aims and innovative approach to a complex problem. In this, I agree; I find the revised manuscript better positioned to begin tackling that problem.\nRegarding the major comments, I find the authors have addressed each one appropriately, restructuring their argument and engaging a broader body of the literature. Importantly they have incorporated the called for caveats and qualifications. The limitations of using existing reference databases and their way of addressing this are discussed in the paragraph following line 350.\nThe problem of the plant extinction window of 19,000 to 9,000 BP coinciding with the highest rate of climate-driven range shifts is addressed in 511ff where the authors identify a significant time lag before potential extinctions happen.\nNoting the comment on the circularity of pollen-based temperature reconstructions to explain taxon losses derived from ancient DNA, I find the authors have made a good case for retaining this temperature reconstruction. While it is true that both proxies derive from plants, it is not the same array of plants. As observed by Jorgensen, et al. 2012, pollen, macrofossil, and sedaDNA data are complementary rather than overlapping.\nAmong the line-by-line remarks, I agree that mammoth steppe should not be hyphenated. Dale Guthrie coined the term and did not use a hyphen (although the title of Murchie, et al.\n2021 uses a hyphen in Nature Communications).\nI find the revised manuscript to be suitable for Nature Communications."}, "author_response": "Answer to reviewer: Thank you for your positive feedback and for endorsing our\nmanuscript for publication. We appreciate your thoughtful comments, which helped us\nimprove the clarity and overall quality of the paper. We are now glad the revisions have\naddressed your concerns, and we are grateful for your time and effort in reviewing our\nwork.\nI still have a couple of comments:\nMaybe I have misunderstood how this simulation works, but the simulation suggests that\n42/60 species are due to incomplete databases. What is the error margin on this estimate?\nBecause if the error margin is, say +/- 20, there is no evidence for extinctions at all.\nAnswer to reviewer: Thank you for your comment. In the last revision round we\nincluded safeguards check to assess the likelihood of our results. This resulted in an\nestimation of the proportion of 60 taxa missing from the modern timeslice that are due\nto technicalities such as incomplete databases. You are correct that this resulted in an\nestimation that up to 42/60 taxa can be due to incomplete databases. 42 reflect the upper\nmargin of our estimate.\nGiven that the main conclusion of the paper has been changed dramatically (i.e. from\n“extinction rate was up to 120X above bg” to “extinction rate were below modern\nestimates”), I think the title should be updated to reflect this. Perhaps the title could\nstart with “Low extinction rates during the loss […]” or “Plant resilience during the […]”\nAnswer to reviewer: Thank you for your comment. We understand your perspective,\nhowever we believe that one of the key novelties of our study is demonstrating that,\nalthough plants were more resilient to extinction during the last glacial-interglacial\ntransition compared to megafauna, our findings suggest that a fraction of plant taxa\npotentially have still undergone extinction. By highlighting this aspect in the title, we\nhope to spark further interest in the scientific community and encourage future research\nto explore this question in more depth. We also believe this study offers a novel method\n(among potentially many) to address the challenge of investigating past plant extinctions\nin the absence of macrofossils.\nAnd speaking of the significant change in conclusion, I would like to flag that I am still\nnot 100% convinced of the results. It is a very difficult task the authors have set\nthemselves, estimating species loss. Having worked with metabarcoding data myself, I\nhave sometimes found that seemingly small changes in the filtering stage (for example\nchanging the cutoff from 100 read to 10 reads) can have dramatic effects on downstream\nanalysis. But I guess only time will tell if these conclusions stand in the future.\nAnswer to reviewer: Thank you for your comment. We agree that only time will tell if\nthe conclusions presented in this study stand in the future. As mentioned before, we hope\nthat this study can lead to future research efforts that will further test our original findings\nand hypotheses.\nMinor comments:\nMy last comment on what is now Supplementary fig 3 still stands. To me it does not\nmake sense to show the non-db and db data stacked in this way, as it veils all patterns\nfor the top category (‘db taxa’ in this case).\nKind regards,\nFrederik Seersholm, University of Copenhagen\nAnswer to reviewer: Thank you for your comment. For us, this figure highlights that\nover time the fraction of non-db taxa decreases (bold line). However, we agree that the\nstack was not ideal to highlight pattern changes for the dbtaxa category and we changed\nthe supplementary figure 3 following your recommendations.\nReviewer #2 (Remarks on code availability):\nCode was not available for review as the github depositories are not publicly available\n(yet). It should be noted that according to the authors \"they can be provided upon request\"\nduring the review process.\nAnswer to reviewer: Thank you for your comment. The scripts were not yet made\npublicly available on Github but were provided for the revision process as 2 “Related\nManuscript File Supplementary Dataset” folders as Script pack 1 and Script pack 2. They\nare now made available to the public for the publication of the manuscript deposited\nunder accession: https://doi.org/10.5281/zenodo.14033298 and\nhttps://doi.org/10.5281/zenodo.14033305.\nReviewer #3 (Remarks to the Author):\nThe authors have addressed each one of my comments and concerns. They have\nreworked the text accordingly.\nReviewer 1’s comments are incisive and thorough, highlighting some fundamental\nweaknesses in the structure of the author’s overall argument and how the results have\nbeen brought to bear in support of that argument. Reviewer 1 nevertheless expresses\nenthusiasm for the ambitious aims and innovative approach to a complex problem. In\nthis, I agree; I find the revised manuscript better positioned to begin tackling that\nproblem.\nRegarding the major comments, I find the authors have addressed each one\nappropriately, restructuring their argument and engaging a broader body of the literature.\nImportantly they have incorporated the called for caveats and qualifications. The\nlimitations of using existing reference databases and their way of addressing this are\ndiscussed in the paragraph following line 350.\nThe problem of the plant extinction window of 19,000 to 9,000 BP coinciding with the\nhighest rate of climate-driven range shifts is addressed in 511ff where the authors\nidentify a significant time lag before potential extinctions happen.\nNoting the comment on the circularity of pollen-based temperature reconstructions to\nexplain taxon losses derived from ancient DNA, I find the authors have made a good\ncase for retaining this temperature reconstruction. While it is true that both proxies derive\nfrom plants, it is not the same array of plants. As observed by Jorgensen, et al. 2012,\npollen, macrofossil, and sedaDNA data are complementary rather than overlapping.\nAmong the line-by-line remarks, I agree that mammoth steppe should not be hyphenated.\nDale Guthrie coined the term and did not use a hyphen (although the title of Murchie, et\nal. 2021 uses a hyphen in Nature Communications).\nI find the revised manuscript to be suitable for Nature Communications.\nAnswer to reviewer: Thank you very much for your thoughtful and constructive\nfeedback. We greatly appreciate the time and effort you dedicated to reviewing our\nmanuscript, as your insights have been invaluable in enhancing both the clarity and\nquality of our work. The comments provided have not only highlighted areas for\nimprovement but have also guided us in refining the manuscript to better convey our\nfindings. We are confident that these revisions have strengthened the overall contribution\nof our study, and we are sincerely grateful for your input throughout this process."}]

Decision letter