Millennia of metacommunity diversification and homogenization captured by sedimentary ancient DNA

Millennia of metacommunity diversification and homogenization captured by sedimentary ancient DNA | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Ecology Letters This is a preprint and has not been peer reviewed. Data may be preliminary. 3 June 2025 V1 Latest version Share on Millennia of metacommunity diversification and homogenization captured by sedimentary ancient DNA Authors : Dilli Prasad Rijal 0000-0002-6194-4414 [email protected] , Antony Brown , Nigel Yoccoz 0000-0003-2192-1039 , Peter Heintzman 0000-0002-6449-0219 , Inger Alsos , and Kari Anne Bråthen 0000-0003-0942-1074 Authors Info & Affiliations https://doi.org/10.22541/au.174895925.54844679/v1 Published Ecology Letters Version of record Peer review timeline 425 views 300 downloads Contents Abstract Introduction Materials and methods Results Discussion Acknowledgement List of figures List of figure legends References Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Biodiversity change in metacommunities, such as homogenization, is often measured using beta diversity metrics. However, other metrics can provide complementary information. Here we use spatial alpha (𝝰), beta (𝝱), gamma (𝛄) and zeta (𝛇) diversity to describe plant metacommunity development at successive time-periods over 12 millennia in a previously glaciated region, as applied to sedimentary ancient DNA data. We find that the metacommunity diversified (𝝱) and homogenized (𝛇) over millennia, concurrently with an increase in the number of taxa (𝝰 and 𝛄). The turnover of taxa between time-periods declined, with taxon appearance exceeding taxon disappearance in the communities. This suggests local co-existence of taxa increased. In contrast, the turnover of shared taxa (ζ) among communities was continuously high, suggesting the regional metacommunity homogenization was largely transient. That plant communities homogenized but remained distinctively different over millennia highlights how individual communities are essential to maintain metacommunity biodiversity. Introduction The functioning of ecological communities is linked to their biodiversity (Hooper et al. 2005; Loreau et al. 2022), including the stability of their aggregate ecosystem properties (Loreau et al. 2021). However, it is the intrinsic character of ecological communities to continuously change their biodiversity (Darwin 1859; MacArthur & Wilson 1967; Magurran et al. 2019; Vellend 2010). This implies that legacies from former compositions can have consequences for biodiversity at a later stage through priority effects or niche construction (Jackson & Blois 2015; Odling-Smee et al. 2013; Stroud et al. 2024; Svenning et al. 2015). Furthermore, ecological community biodiversity change does not occur in isolation, as changes in one community may affect the biodiversity and ecosystem functioning in a neighboring community (Leibold et al. 2004; Mori et al. 2018). Hence, documenting spatio-temporal change in the biodiversity of ecological communities is essential for predicting changes in ecosystem functioning. Biotic homogenization, a process whereby genetic, taxonomic, or functional similarities of regional biotas increase over time (Blowes et al. 2024; sensu Olden & Rooney 2006), is a biodiversity change related to the loss of biodiversity in our time (Blowes et al. 2024; Bråthen et al. 2024; Daru et al. 2021; Mori et al. 2018; Staude et al. 2022; Yang et al. 2021). However, biotic homogenization has also been found in regions where species richness has been increasing (Finderup Nielsen et al. 2019) or has not changed (Bråthen et al. 2024), and species loss has been documented in the absence of biotic homogenization (García Criado et al. 2025; Keck et al. 2025). Indeed, spatial and temporal biodiversity change among communities can take many forms (Blowes et al. 2024; McGill et al. 2015; Socolar et al. 2016). For instance, biotic homogenization in a metacommunity under increasing or decreasing levels of biodiversity can be termed additive or subtractive homogenization for either the gain of the same species or the loss of different species respectively (sensu Socolar et al. 2016). In addition, common and widespread species are likely to be gained, and rare species lost, as a result of homogenization (Blowes et al. 2024; Socolar et al. 2016). The extent to which common species appear late in the ecological succession process is further suggested as a driver of biotic homogenization, emphasizing the role of natural, as opposed to anthropogenic, causes of the biodiversity change (Staude et al. 2023). Biodiversity loss can however also happen through the process of metacommunity diversification where, for example, the species lost are those in common among the communities (Blowes et al. 2024; Socolar et al. 2016). The many forms that biodiversity change can take within a metacommunity suggest that its interpretation should be done within rigorous theoretically-based frameworks. The concepts of alpha, beta and gamma diversity are commonly applied to describe biodiversity change (Wang & Loreau 2014; Whittaker 1972). The alpha and gamma diversity metrics are, in their simplest form, merely counts of taxa at the community and metacommunity level, respectively. Beta diversity metrics provide information about the differences between communities either in time or space (Pinsky et al. 2025), and are contingent on the level of taxonomic identity attained in order to provide information about species turnover (Anderson et al. 2011; Baselga et al. 2007; Koleff et al. 2003; Magurran et al. 2018). Accordingly, spatio-temporal studies of biotic homogenization often use measures of beta diversity (Blowes et al. 2024; Daru et al. 2021; Finderup Nielsen et al. 2019; Fraser et al. 2022; Keck et al. 2025; Mori et al. 2018; Yang et al. 2021). For the partitioning of biodiversity among several localities, or communities within a metacommunity, zeta diversity has also been applied (Latombe et al. 2017; Simons et al. 2019). Zeta diversity is a metric that captures the number of shared taxa among communities and is flexible in the number of communities that can be compared (Hui & McGeoch 2014). For instance, in a metacommunity of three communities the spatial beta and zeta diversity can be complementary in providing information about the average species difference (beta) and the number of shared species (zeta), where an increase in both would suggest both diversification and homogenization (Fig. 1a and b). Hence, to disentangle more subtle changes such as additive homogenization (Fig. 1a and b), or other forms for spatio-temporal change (Fig. S1), we propose the inclusion of zeta diversity within a framework that typically consists of alpha, beta, and gamma diversity. Biodiversity change is challenging to quantify over long timescales, however. A lack of data, in particular from the past, causes a lack of biodiversity baselines towards which current, and future, biodiversity can be evaluated (Fordham et al. 2020; Magurran et al. 2010, 2019). As temporal changes in biodiversity are interlinked with spatial patterns, care should be used when substituting space for time (Damgaard 2019). Accordingly, the depiction of biodiversity change and novelty depends on both spatial and temporal baselines (Radeloff et al. 2015). Long-term adaptive monitoring that can provide such biodiversity baselines are rare (Ims & Yoccoz 2017; Lindenmayer & Likens 2009) and data that provides such baselines from the past, need to be interpreted with caution to avoid biased inferences of biodiversity change (Kapfer et al. 2017). Empirical studies that permit assessment of biodiversity change are hence very valuable, with paleoecological studies providing unprecedented ecological insights. Pollen-based paleoecological studies have provided information about shifting baselines of biodiversity (Allen & Huntley 1999; Birks & Birks 2000; Birks et al. 2016; Felde et al. 2017; Giesecke et al. 2019; Seppä et al. 2009; Willis et al. 2010). However, pollen-based studies are both limited and biased by low taxonomic resolution typically to the family or genus, long-distance dispersed pollen limiting single community assessments, swamping by high pollen-producing taxa such as trees and grasses, and low pollen production by insect-pollinated species such as herbs (Birks et al. 2016; Felde et al. 2015; Reitalu et al. 2019). In comparison, plant sedimentary ancient DNA ( sed aDNA) has a more local and spatially delimitable signature, fewer problems with swamping, an average higher taxonomic resolution often to species, and species richness values recovered from recently-deposited sediments have been found to correlate with that of modern local vegetation (Alsos et al. 2018; Sønstebø et al. 2010). When the two approaches are compared, sed aDNA better reflects the local plant community and detects more herbaceous species and more taxa overall than pollen analyses (Clarke et al. 2019; Sjögren et al. 2017; Zimmermann et al. 2017b, a). Thus, sed aDNA provides an improved basis from which we can detect spatio-temporal biodiversity changes in metacommunities of the past. In this study we explore how the set of alpha, beta, gamma, and zeta diversity metrics behave in a plant metacommunity spanning the last 16 millennia in northern Fennoscandia. This time period covers the retreat of the glacial ice that had covered nearly all of Fennoscandia to the present. We particularly focus on the metacommunity processes of diversification and homogenization (Fig. 1c), using sed aDNA data from lake sediments that have been identified using reference libraries constructed from the extant Nordic flora. Because each lake has accumulated sed aDNA from its catchment, we define a community as the species assemblage from a lake catchment and define the metacommunity as the full set of lake catchments. Since the ice-retreat, regional increases in both the number of taxa (Rijal et al. 2021) and trait diversity during the Early Holocene (Alsos et al. 2022) have already been documented. Here we ask to what extent the metacommunity biodiversity has been diversifying or homogenizing from the time of ice-retreat and primary succession towards the present-day ecosystem (Fig. 1c, Fig. S1). Because the geographical distances among the communities vary, we also ask to what extent there is distance decay in biodiversity (Hui & McGeoch 2014; McGeoch et al. 2019), comparing time and distance to the changes in biodiversity within the metacommunity. Materials and methods Study area, current vegetation, and time span of lake sediment records The study area covers northernmost Fennoscandia above the Arctic Circle (67.75-70.43 N, 19.62-30.02 E) (Fig. 2). Sediment cores from the 10 study lakes (nine in Norway and one in Finland) vary in their age range, with the oldest starting at 16.1 thousand calibrated years before present (ka), but with most covering the majority of the Holocene (starting at 11.7 ka) (Table S1). The current catchment vegetation of lake Sandfjorddalen, Eaštorjávri South, Langfjordvannet, and Jøkelvatnet are dominated by treeless heath, shrub, meadow, and mire. Gauptjern, Nesservatnet and Nordvivatnet are surrounded by birch ( Betula pubescens ) forests, but also heath, meadow, and mire. Horntjernet, Sierravannet and Kuutsjärvi are surrounded by mixed boreal forests, heath, and mire but with pine ( Pinus sylvestris ; all three lakes) and spruce ( Picea abies ; latter two lakes) also present. The 10 lake sites are located in the present-day ecotone of northern Boreal birch-conifer vegetation and the open-shrub tundra, and are defined as belonging to the ecoregion of Scandinavian Montane Birch forest and grasslands (https://ecoregions.appspot.com, Dinerstein et al. 2017). The aDNA dataset We analyzed a previously-published terrestrial plant sed aDNA dataset originating from sediment cores of the 10 lakes. Out of the 355 sed aDNA samples used in this study, 316 were published by Rijal et al. (2021) and the remaining 39 by Alsos et al. (2022). The taxonomic assignment of some sed aDNA sequences published in Rijal et al. (2021) were revised by Alsos et al. (2022) using the PhyloNorway DNA reference library for vascular plants (Alsos et al. 2020). Altogether the terrestrial plant dataset consists of 213 vascular plants and 77 bryophytes. We converted semi-quantitative PCR replicate data of the 290 terrestrial plant taxa originating from 350 distinct sediment samples (five DNA extraction duplicates were excluded) into presence/absence data to represent the plant communities analyzed in this study (Table S1). Taxon detection in sed aDNA analysis is expected to be biased towards sample age due to increased DNA degradation with time (Capo et al. 2021). Both DNA degradation and PCR biases can therefore directly affect the estimation of our diversity metrics. However, the data used here were based on eight PCR replicates to maximise taxon detection (Alsos et al. 2022; Rijal et al. 2021). We highlight that there was minimal to no age bias effect on the samples, and detection bias was minimized by applying quality control metrics to filter out poor quality samples (see Rijal et al. 2021). Finally, the entire dataset was harmonized using standardized taxonomy (Alsos et al. 2022; Rijal et al. 2021), assuring a reliable database for estimating diversity metrics within and among the lake sediment records. Calculation of biodiversity metrics The total number of unique taxa from each sediment sample was used to represent a community in a window of time. A metacommunity approach was taken by using the sediment samples from each of 8 lakes (for the Early and Middle Holocene; two records did not cover this time interval) and 10 lakes (for the Late Holocene), where the set of all lakes represented a metacommunity. To capture biodiversity change over time at the metacommunity level, the total numbers of unique taxa from each sediment sample were binned into time-intervals for the total set of lakes. Bins were made for each 500-year time interval for all analyses, except for the distance decay analysis where bins were made for each of the three climate-related Holocene sub-divisions, i.e. each 4000-year time interval from 11.7 ka to present (Walker et al. 2012). Alpha diversity was calculated as the number of taxa per sediment sample in each community (Rijal et al. 2021), and then averaged across all lakes within each time bin to have an estimate of average alpha diversity for each 500-year interval throughout the Holocene. Gamma diversity was calculated as the total number of taxa at the metacommunity level (at each 500-year interval and with one estimate per timestep only). Whitaker’s additive beta diversity was calculated for each 500-year interval following Lande (1996). Temporal beta diversity (species turnover) was calculated as Jaccard’s dissimilarity, or the species exchange ratio, between each 500-year interval within each community, with \(\beta\) dis = (S imm + S ext )/ S tot (Hillebrand et al. 2018; Koleff et al. 2003), where S imm is immigration or taxa appearing between time-consecutive samples, S ext is extinction or taxa disappearing between time-consecutive samples, and S tot is the total number of detected taxa of two time-consecutive samples. We calculated temporal beta diversity across the timestep between consecutive 500-year intervals in three ways: the average per community, the total for the entire metacommunity, and across the subset of shared taxa within the metacommunity (Fig. 1a and b). Zeta diversity was calculated as the number of taxa shared among the communities (Hui & McGeoch 2014; McGeoch et al. 2019) at each 500-year interval, comparing two, three and more catchment communities until all taxa of all communities at each interval were compared. Note that for zeta diversity estimates of the total metacommunity, i.e. with all communities compared, there was only one estimate of zeta diversity per interval possible. The number of communities compared is termed the zeta order. Because a zeta order of 1 equals the average alpha diversity among communities, it was omitted. The maximum zeta order applied increases from 7 to 8 to 9 from Early to Middle to Late Holocene, respectively. We also included an analysis of the zeta ratio, calculated as the ratio of zeta diversity of order n+1 divided by zeta diversity of order n (Hui & McGeoch 2014; McGeoch et al. 2019) at each 500-year time interval. The zeta ratio therefore provides information as to the species turnover within the subset of shared species at any time instance (Latombe et al. 2017). This is also considered as a retention rate across the metacommunity of rare to common species (McGeoch et al. 2019). Finally, we assessed distance decay, i.e. how zeta diversity was affected by the Euclidean distance among different communities, for the same set of samples over the three Holocene subdivisions, thereby excluding Late Glacial samples (>11.7 ka) that were only present at three lakes (Table S1). Statistical analysis To test whether the diversity analyses were impacted by the increasing number of communities over time, largely related to the glaciation history (Figure 2), we created subsets of data by randomly subsampling from the full dataset without replacement. However, as there were few communities during the Late Glacial time interval, we generated a set of six datasets based on resampling of 1 to 5 communities, and with resampling starting at the time-interval the metacommunity had sufficient communities for resampling (see Fig. S2 for subsampling details). The gamma, beta, and zeta diversities were calculated from each dataset using 100 subsampling iterations. The average values from these repetitions were then compared to those derived from the full dataset (Figs. S2 and S3). Similar trends of gamma and zeta diversities, and comparable temporal beta diversity trends were recovered independently of the number of communities added (Figs. S2 and S3). The final analysis was therefore based on the full data set. The temporal trend of all diversity metrics were modelled using generalized additive models (GAMs). For alpha and beta diversity (for each community), we used the number of taxa in each sediment sample as the response variable and the age of the sample as the predictor variable. For gamma diversity, zeta diversity, and the zeta ratio (all at the metacommunity level), we used the number of taxa in 500-year intervals as the response variable and the time intervals as the predictor variable. The zeta diversity estimates were rounded to the closest whole numbers prior to modelling in order to retain properties of counts (e.g. increasing variance with the mean). For GAMs of zeta diversity and the zeta ratio, the zeta order of 9 was excluded as there were too few time intervals to fit the GAM. We initially used the Poisson distribution for modeling alpha, gamma, and zeta diversities. However, due to overdispersion, we changed the distribution to either a Negative Binomial or Tweedie distribution in order to improve model fit (Fig. S4). Excluding the oldest sample and using log transformed taxonomic richness as the response variable in a linear model improved the model fit in Nesservannet. A linear model for gamma diversity and a Tweedie GAM for the mean alpha diversity improved model fit (Fig. S5). When calculating temporal beta diversity for the subset of shared taxa, we applied the list of taxa as defined by the zeta diversity of the total metacommunity per 500-year interval. Note that the maximum number of communities, or the maximum zeta order with shared taxa, could vary between consecutive 500-year intervals (see Fig. 1a for an illustration). A binomial distribution was primarily used while modeling temporal beta diversity, i.e. the proportional ratio of counts (see Douma & Weedon 2019). Removal of the most recent sample of Kuutsjärvi and application of a Gaussian distribution to both Kuutsjärvi and Nesservannet improved the model fit at catchments while analyzing the temporal beta diversity pattern through time (Fig. S6). A linear model for temporal beta diversity at the metacommunity level and for the shared taxa, as well as a log linear model for mean temporal beta diversity at 500-year intervals provided better fits than a binomial distribution (Fig. S7). A Tweedie GAM was needed to improve the model fit in one of the analyses of the temporal pattern of zeta diversity (Fig. S8) and GAMs with beta regression provided a reasonable model fit (Fig. S9) while analyzing the temporal pattern of zeta-ratio (see Douma & Weedon 2019). We performed all analyses in R (R Core Team, 2023): the GAM analyses used the mgcv package (Wood 2017), the diagnostic plots for all the regression models were generated using DHARMa (Hartig 2022), and the temporal trends of all diversity metrics were visualized using ggplot2 (Wickham 2016). Results The size of the metacommunity, in terms of the number of constituent communities, increased over time as the glacial ice retreated and the sampling sites could be colonized, although two records begin in the Late Holocene (Figure 2). Still, as also shown by Rijal et al. (2021), the different communities had different rates of alpha diversity (number of taxa) change over time independent of when their records began, with an increase in all communities except Sandfjordalen and Langfjordvatnet during the Middle Holocene and Gauptjern which stabilized in the Late Holocene towards the present (Fig. 1, Fig. 3a, Table S2). At the metacommunity level, the average alpha diversity had a steady increase throughout the Holocene (F = 76.1, edf = 4.07, p < 0.0001, Fig. 3b, Fig. S10b). The total number of taxa at the metacommunity level, the gamma diversity, also increased (F 1,31 = 547, R 2 adj = 0.94, p < 0.0001) at a rate far exceeding that of the average alpha diversity (Fig. 3b). Consequently, the additive beta diversity increased throughout the Holocene (F 1,29 = 294.8, R 2 adj = 0.91, p < 0.0001, Fig. 1a and b, Fig. S11), as the distance between the average alpha and the gamma diversity increased over time (Fig. 3b). The taxon exchange over time, the temporal beta diversity, changed both within and among the communities (Fig. 4a, Fig. S12a), with an increasing trend in the Late Glacial period in Langfjordvannet and with most communities showing a significant decline during the Holocene (Table S3). At the metacommunity level, the taxon exchange between time instances showed a clear decline throughout the Holocene (Fig. 4b, Fig. S12b), both when calculated as the average taxon exchange across communities (F 1,30 = 32.1, R 2 adj = 0.50, p < 0.0001) and at the metacommunity level (F 1,30 = 77.49, R 2 adj = 0.71, p < 0.0001). Trends in both plant taxon appearance (immigration) and disappearance (local extinction) in the metacommunity were increasing over time (Fig. S13-14), with plant taxon appearance being slightly higher than disappearance. The number of shared taxa among communities, the zeta diversity, increased with time throughout the Holocene (Fig. 5a). However, the rate of increase in zeta diversity was dependent on the average number of communities compared. The highest rate of increase was found for the average of any two communities, i.e. the zeta order of 2, whereas the rate levelled off markedly as more communities were compared, i.e. as the zeta order increased (Fig. 5a, Fig. S15a). The subtle reduction in the rate of increase in zeta diversity for higher orders was further indicated by their non-significant smoothing terms (Table S4). The rate at which the taxa shared among communities were retained at the metacommunity level, the zeta ratio, shifted with time only in the Early Holocene (inset Fig. 5b, Fig. S15b, Table S5) suggesting a shift from rare to more common taxa being shared. The retention rate in the Middle and Late Holocene was higher and did not change over time (Fig. 5b) suggesting the balance between rare and common taxa being shared among communities stabilized. Temporal beta diversity was also calculated for the subset of shared species in the metacommunity (Fig. 1). The exchange rate between time instances was high within this subset of taxa, and did not change throughout the Holocene (F 1,23 = 0.00, R 2 adj = -0.04, p > 0.05, Fig. 4b). Only a few taxa were consistently shared among the communities through time (Table S6). Zeta diversity was also related to distance between communities (Fig. 6), but this is only clear in the Late Holocene as shown by the decreasing number of taxa being shared with increasing distance among communities (Fig. 6, Fig. S16) and statistically significant smooth terms (Table S7). Discussion We applied a set of complementary diversity metrics to a unique spatio-temporal dataset of plant sed aDNA taxa, and found the complementarity provides novel insights into the extensive plant diversity changes that took place in northern Fennoscandia throughout the Holocene. First, we find that the number of taxa at the community level (average alpha), at the metacommunity level (gamma), different between communities (additive beta), and shared among the communities (zeta) all increased continuously from the time of the ice-retreat to the Late Holocene. Hence, the metacommunity both diversified and homogenized concurrently over millennia. As the metacommunity increased in taxon richness over the same time, we can specify both processes as additive. Homogenization decreased as more communities were compared (with increasing zeta order) and so we can conclude that homogenization differed within the metacommunity. However, these patterns are based on mere counts of taxa at each 500-year interval since the ice-retreat. We therefore also addressed taxon turnover between time intervals (measured as the exchange rate of taxa, or temporal dissimilarity). We find a growing proportion of the taxa was persistent over time at the community and metacommunity levels, whereas the turnover was continuously high among the subset of shared taxa in the metacommunity throughout the Holocene. Our findings thus suggest that a metacommunity can remain spatially diverse over millennia in spite of biotic homogenization taking place among its communities. Furthermore, our findings suggest that biotic homogenization at one time instance does not need to imply that homogenization is persistent over time, or that all communities are equally involved in the homogenization process. The plant diversity changes of the metacommunity are clearly linked to the development of the communities following the ice-retreat of the last glaciation (Alsos et al. 2022; Birks et al. 2012; Huntley et al. 2013), with the taxon richness at the community level (alpha diversity) starting close to zero and increasing. As the Holocene proceeded, taxon richness at the metacommunity level (gamma diversity), increased many-fold more than the average taxon richness per community. This discrepancy indicates a large increase in the number of taxa being different between the communities (additive beta diversity) and shows the metacommunity consistently diversified throughout the Holocene. This further suggests the development of the metacommunity was consistent with spatial niche separation through priority effects (Chase 2003), including niche construction (Fukami 2015; Odling-Smee et al. 2013) in which biota are directing the community change, and/or species sorting among its communities, in which environmental differences cause communities to differ (Leibold et al. 2004; Mori et al. 2018). The increase in taxon richness at both the community and metacommunity levels continued throughout the Holocene, suggesting the species pool at both the local and the regional scale may still not be saturated (Alsos et al. 2022; Rijal et al. 2021), further suggesting the diversity changes of this northern Fennoscandian metacommunity have been impacted by the addition of new taxa over millennia. The number of taxa shared among the communities (zeta) also increased continuously throughout the Holocene. Biotic homogenization during the Holocene has previously been found among assemblages of North American mammalian faunas, with two distinct phases in which the first followed the extinction of megafauna and the second the rise of human impact (Fraser et al. 2022). In contrast, the plant metacommunity homogenization observed in our study happened in a region with low human population size and growth (Brown et al. 2022). Furthermore, the number of shared taxa increased alongside metacommunity richness, and can therefore be classified as additive biotic homogenization in which the communities become more homogenous through the addition of new shared species (Socolar et al. 2016). However, less than 10 taxa were shared among all the communities in any 500-year time window, a fraction of the average taxon richness (average alpha) in the metacommunity. The biotic homogenization may thus not have caused a decrease in the multifunctionality of the metacommunity (sensu Mori et al. 2018), as the set of functions provided with the shared taxa were in addition to a growing set of unique taxa in the communities (Alsos et al. 2022). Furthermore, although the biotic homogenization was linked to primary succession, emphasizing a natural way by which homogenization can take place (Staude et al. 2023), the continued differentiation of taxa among communities within the metacommunity suggests succession was limited as a homogenization force. Importantly, we found a high exchange rate between time intervals among the shared taxa. Hence, the set of shared taxa shifted, especially among forbs, whereas shared woody taxa, that would be linked to late successional stages, showed a higher consistency over time (see Table S6). The biotic homogenization as identified by the pairwise comparison of communities, the zeta-diversity of order two, is equal to a beta-metric providing pairwise similarity of community assemblages (McGeoch et al. 2019). Hence, a beta diversity metric would suffice to capture homogenization. However, zeta diversity of higher orders provided more insight as to how the biotic homogenization was distributed among communities. For instance, there was no significant increase in biotic homogenization over time when all communities were compared, whereas the average of subsets of up to five communities did show a significant increase. This suggests that biotic homogenization was stronger among a subset of the metacommunity. The number of shared taxa (zeta) declining with distance between communities in the Late Holocene could be contributing to this spatio-temporal pattern in biotic homogenization. Indeed, distance between communities can affect patterns of movement within a metacommunity (sensu MacArthur & Wilson 1967; Storch & Okie 2019), for example through dispersal distance, low connectance, or environmental distance (Chase 2003). Spatio-temporal information provided by the retention rate (zeta-ratio) was however less obvious in our study. Clearly, taxa shared by all communities are widespread whereas those that are either unique or shared by two or a few communities are rarer (Blowes et al. 2024). This information was however already evident from the spatio-temporal pattern of zeta diversity, where it was clear that it was only a subset of the shared taxa that were shared among all communities and hence widespread. The decreasing turnover rate between successive assemblages indicates an increasing proportion of the taxa remained in the metacommunity as the Holocene developed. The finding that more taxa appeared than disappeared over time further suggests the proportion of taxa co-existing in the local communities also increased over time. Biodiversity per se can be a stabilizing force promoting species coexistence (Loreau et al. 2022) and ecosystem functioning, as argued in the insurance hypothesis (Yachi & Loreau 1999). The number of taxa do, however, not necessarily imply stability of ecosystem functioning, as this depends on the traits present (Chao & Colwell 2022; Mori et al. 2018). For the metacommunity of this study, plant trait diversity showed no change after 9 ka (Alsos et al. 2022) whereas biotic homogenization continued, hence we can speculate that homogenization did not contribute to the addition of new, shared functionality among the communities. Rather, the constant addition of new plant taxa, some of which were shared among the communities, suggest niche complementarity has been ongoing for millennia and possibly enhanced by a range of ecological interactions as the communities have diversified. Studies from more recent deglaciation events have found positive links between plant communities, abiotic conditions, and the biodiversity of other kingdoms (Ficetola et al. 2024), which underscores the importance of plants as primary producers, and so we consider the changing biodiversity documented here as being informative at the ecosystem level. Importantly in this study however, any fluctuations in biodiversity at decadal timescales are smoothed. Hence, studies examining changing biodiversity over decadal timescales from more recent deglaciation events (Cantera et al. 2024) or from changing vegetation compositions in northern Fennoscandia (Bråthen et al. 2024), are considered not directly comparable to the results of this study. Here we rather emphasize the role of complementary biodiversity metrics in capturing spatio-temporal change as an important insight. In conclusion, we gain important insights into plant biodiversity changes in northern Fennoscandia during the Holocene that are informative for biodiversity changes in our time. First, communities can remain unique for millennia. Hence, loss of habitat in one community indicates loss of biodiversity to the metacommunity, which strengthens the argument that habitat loss through human influence causes ecosystem decay and biodiversity loss (Chase et al. 2020). From a practical perspective, the fact that communities can remain unique in their assemblages of taxa through millennia highlights the risk of extrapolating information from one community to another (McGill 2019). Second, novel ecosystems can continuously develop over millennia (Burke et al. 2019), as is the case for our metacommunity as interpreted from diversification throughout the Holocene. This may reflect the inevitably non-spatially uniform nature of changes in both the natural and human impacted environment. Finally, our findings emphasize that additive homogenization and additive diversification are not mutually exclusive processes in a metacommunity, highlighting the need for complementary metrics for analyzing diversity change. Acknowledgement The study was funded by Research Council of Norway grant 250963/F20 (to IGA, NGY, KAB; supported DPR, PDH) for the ECOGEN project; The European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme grant agreement No 819192 for the IceAGenT project (IGA, AGB); and UiT, ArcEcoGen Centre (supported DPR). We thank Chloe Marquart for fieldwork assistance at Nesservatnet. The authors declare no conflict of interests. List of figures Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 List of figure legends Fig. 1 A framework for addressing biodiversity change in a metacommunity. (a) An illustration of the spatio-temporal partitioning of the biodiversity of a metacommunity at two time-instances. The spatial components of alpha (𝝰), gamma (𝛄) and zeta (𝛇) diversity are presented at each time-instance along with additive beta diversity (𝝱 add ) calculated as 𝛄-ᾱ (Lande 1996). 𝛇 is the average number of species shared among communities (Hui & McGeoch 2014; McGeoch et al. 2019). The temporal component of dissimilar beta diversity (Jaccard dissimilar index, i.e. the rate of change in species (or taxa) appearing (immigrating) and disappearing (extirpated or extinct) within communities over time (Hillebrand et al. 2018) (𝝱 d,t ) is presented between the two time-instances. 𝝱 d,t is partitioned into the turnover rate within the metacommunity (𝝱 d,t,m ), in average within all communities (𝝱 d,t,c ) (stapled line in the figure because only one community is exemplified but the values represent the average across all three communities) and within the subset of shared species of the maximum zeta order (𝝱 d,t,s ). (b) A graphical presentation of the illustrated metacommunity shows that the average community richness (ᾱ), the total species richness (𝛄), the difference in species richness between the communities (𝝱 add ) and the number of shared species in the metacommunity (𝛇) all increase over time, indicating the metacommunity both diversify (D) and homogenize (H), and that the highest temporal species turnover is found at the community level (𝝱 d,t,c ). (c) Ways by which species diversity in a metacommunity may change spatio-temporally over millennia. The set of biodiversity metrics provide information about metacommunity biodiversity diversification (D) and homogenization (H), with the colored fields representing a continuum of possible change – a diversity space. The stapled lines (and areas in between) represent hypothetical metacommunity change at timesteps from the retreat of the ice sheets (see Fig. 2) until the present. Change in 𝝰 or 𝛄 over time (left panel). Development of species diversity on average across catchment communities (ᾱ) or their metacommunity (𝛄). Note that this is not equal to the accumulated species diversity, as some taxa may disappear over time. Continuous immigration and hence new species are environmentally filtered through both abiotic conditions and ecological interactions that may cause dynamics in species diversity at both community and metacommunity level (Mittelbach & Schemske 2015). The development of average ᾱ and 𝛄 diversity can therefore take one of several trajectories. Change in spatial 𝝱 add over time (second panel) can be derived directly from the 𝛄 and the average ᾱ across the metacommunity as a measure of the difference among the communities. Change in 𝛇 over time (or temporal change in species similarity across communities) (third panel). If, for instance, a set of pioneer species were successful in dispersing to and establishing in all communities at the onset of the Holocene, 𝛇 will equal the set of pioneer species at this time but can never be larger than that of the community with the lowest 𝝰 diversity. At the other extreme, with no shared species among the communities at the onset of the Holocene, and with the species assemblages of all communities remaining unique, 𝛇 would stay at zero. Change in 𝝱 d,t over time (last panel). Trajectories in 𝝱 d,t are many. It can in principle range from a maximum (𝝱 d,t = 1) reflecting a complete turnover of the species assemblage between timesteps, to a steep decline (𝝱 d,t > 0) reflecting that all species persist alongside species immigration and a minimum (𝝱 d,t =0) reflecting no turnover. Between the extremes of 0 and 1, 𝝱 d,t decline can reflect different processes such as the increase or decrease in the proportion of species with a stable presence over time. Fig. 2. Digital elevation map of the study area (data source: European Environment Agency (EEA)) . The most credible generalized extent of the Scandinavian ice sheet (Hughes et al. 2016) at 15, 12, and 11 ka are indicated by transparent layers. Lake locations are depicted with points scaled by the total taxa found in the lake. Lakes are further depicted with their names, codes and number of samples within the parentheses, and the temporal span of each sediment core in thousands of years before present (ka). Inset shows the extent of the Scandinavian ice sheet at 15 and 10 ka. See Table S1 for lake metadata. Fig. 3 . Alpha and gamma diversity during the Holocene. (a) Taxonomic richness of terrestrial plants (alpha diversity) over time in single catchment communities, and (b) the average alpha (±1SD) and gamma diversity across the metacommunity over time. The metacommunity estimates are based on sediment samples binned at each 500-year interval and intervals older than 13 ka are represented by a single lake Shadings indicate 95% confidence intervals of the fitted models. See Fig. S10 for raw data points and Fig. 2 for lake names. Fig. 4. Temporal beta diversity during the Holocene. The terrestrial plant taxa turnover rate between successive samples over time in (a) each of 10 communities, and (b) across the metacommunity including mean temporal beta diversity across local communities and the temporal beta diversity among the subset of shared taxa in the metacommunity. The subset of shared taxa applied here are those shared among the maximum number of communities at each time interval. The metacommunity estimates are based on sediment samples each binned at 500-year intervals and intervals older than 13 ka are represented by a single lake. Shadings indicate 95% confidence intervals of the fitted models. See Fig. S11 for raw data points and Fig. 2 for lake names. Fig. 5. Zeta diversity and zeta ratio during the Holocene. (a) Zeta diversity over time for 10 communities. Each line shows the average number of shared terrestrial plant taxa among two (zeta order of 2) and up to eight (zeta order of 8) communities. (b) Zeta ratio over time for 10 communities. Each line shows the proportion of taxa that are shared between two neighboring zeta orders. The inset shows the retention rate, the relation between zeta ratio, and zeta order, at four distinct time-intervals. All estimates are based on sediment samples each binned at 500-year intervals. Shadings indicate 95% confidence intervals of the fitted generalized additive models. See Fig. S14 for raw data points. Fig. 6 . Zeta diversity with distance during the Early, Middle, and Late Holocene. 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Collection Ecology Letters Authors Affiliations Dilli Prasad Rijal 0000-0002-6194-4414 [email protected] UiT The Arctic University of Norway Museum and Academy of Fine Arts View all articles by this author Antony Brown UiT The Arctic University of Norway Museum and Academy of Fine Arts View all articles by this author Nigel Yoccoz 0000-0003-2192-1039 University of Tromsø View all articles by this author Peter Heintzman 0000-0002-6449-0219 Centre for Palaeogenetics, Svante Arrhenius väg 20C, SE-10691 Stockholm, Sweden View all articles by this author Inger Alsos Tromsø University Museum View all articles by this author Kari Anne Bråthen 0000-0003-0942-1074 Arctic University of Norway View all articles by this author Metrics & Citations Metrics Article Usage 425 views 300 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Dilli Prasad Rijal, Antony Brown, Nigel Yoccoz, et al. 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