Sedimentary ancient DNA reveals past ecosystem and biodiversity changes on the Tibetan Plateau: Overview and prospects

Jia, Weihan; Anslan, Sten; Chen, Fahu; Cao, Xianyong; Dong, Hailiang; Dulias, Katharina; Gu, Zhengquan; Heinecke, Liv; Jiang, Hongchen; Kruse, Stefan; Kang, Wengang; Li, Kai; Liu, Sisi; Liu, Xingqi; Liu, Ying; Ni, Jian; Schwalb, Antje; Stoof‐Leichsenring, Kathleen R.; Shen, Wei; Tian, Fang; Wang, Jing; Wang, Yongbo; Wang, Yucheng; Xu, Hai; Yang, Xiaoyan; Zhang, Dongju; Herzschuh, Ulrike

doi:10.1016/j.quascirev.2022.107703

Cited by 23 publications

(6 citation statements)

References 186 publications

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“…R. Soc. B 379: 20230017 the Tibetan Plateau [34,48] that generally cover long time spans (up to about 50 kyr), and many shorter records from the British Isles [49,50] (figure 2, electronic supplementary material, table S1). By using quality measures and standardization [41], the dataset may be combined into even larger datasets.…”

Section: The Advantage Of Sedadna Datamentioning

confidence: 99%

“…The largest lake sediment metabarcoding study is one of 10 northern Fennoscandian lakes (387/355 samples x 8 PCR replicates, [ 15 , 41 ]), and a study of 705 samples from 14 lakes in the European Alps will soon be available ( figure 2 ; electronic supplementary material, table S1). There is also an increasing number of lakes analysed from Siberia and the Tibetan Plateau [ 34 , 48 ] that generally cover long time spans (up to about 50 kyr), and many shorter records from the British Isles [ 49 , 50 ] ( figure 2 , electronic supplementary material, table S1). By using quality measures and standardization [ 41 ], the dataset may be combined into even larger datasets.…”

Section: The Advantage Of Sed Adna Datamentioning

confidence: 99%

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Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change

Alsos,

Boussange,

Rijal

et al. 2024

Phil. Trans. R. Soc. B

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Ecosystem response to climate change is complex. In order to forecast ecosystem dynamics, we need high-quality data on changes in past species abundance that can inform process-based models. Sedimentary ancient DNA ( sed aDNA) has revolutionised our ability to document past ecosystems' dynamics. It provides time series of increased taxonomic resolution compared to microfossils (pollen, spores), and can often give species-level information, especially for past vascular plant and mammal abundances. Time series are much richer in information than contemporary spatial distribution information, which have been traditionally used to train models for predicting biodiversity and ecosystem responses to climate change. Here, we outline the potential contribution of sed aDNA to forecast ecosystem changes. We showcase how species-level time series may allow quantification of the effect of biotic interactions in ecosystem dynamics, and be used to estimate dispersal rates when a dense network of sites is available. By combining palaeo-time series, process-based models, and inverse modelling, we can recover the biotic and abiotic processes underlying ecosystem dynamics, which are traditionally very challenging to characterise. Dynamic models informed by sed aDNA can further be used to extrapolate beyond current dynamics and provide robust forecasts of ecosystem responses to future climate change. This article is part of the theme issue ‘Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere’.

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Section: The Advantage Of Sedadna Datamentioning

confidence: 99%

Section: The Advantage Of Sed Adna Datamentioning

confidence: 99%

Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change

Alsos,

Boussange,

Rijal

et al. 2024

Phil. Trans. R. Soc. B

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show abstract

“…There is also an increasing number of lakes analysed from Siberia and the Tibetan Plateau [34,47] that generally cover long time spans (up to about 50 ka), and many shorter records from the British Isles [48,49] (Figure 2, Supplementary Table 1). By using quality measures and standardisation [41], the dataset may be combined into even larger datasets.…”

Section: In Prep)mentioning

confidence: 99%

Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change

Alsos,

Boussange,

Rijal

et al. 2023

Preprint

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Ecosystem response to climate change is complex. In order to forecast ecosystem dynamics, we need high-quality data on changes in past species abundance that can inform process-based models. Ancient DNA has revolutionised our ability to document past ecosystems' dynamics. It provides time-series of increased taxonomic resolution compared to microfossils (pollen, spores), and can often give species-level information, especially for past vascular plant and mammal abundances. Time series are much richer in information than contemporary spatial distribution information, which have been traditionally used to train models for predicting biodiversity and ecosystem responses to climate change. Here, we outline the potential contribution of sedimentary ancient DNA (sedaDNA) to forecast ecosystem changes. We showcase how species-level time-series may allow quantification of the effect of biotic interactions in ecosystem dynamics, and be used to estimate dispersal rates when a dense network of sites is available. By combining palaeo-time series, process-based models, and inverse modelling, we can recover the biotic and abiotic processes underlying ecosystem dynamics, which are traditionally very challenging to characterise. Dynamic models informed by sedaDNA can further be used to extrapolate beyond current dynamics and provide robust forecasts of ecosystem responses to future climate change.

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“…Lake sediments are the most suitable archives for tracking temporal species-environment relationships ( 46 ). Compared to the traditional proxies (e.g., pollen and diatoms), sedimentary ancient DNA (sedaDNA) extracted from lake sediments has become a powerful tool for retrieving more detailed assemblages of past plants, animals, and microbes within lakes and their catchments ( 47 ). SedaDNA metagenomics (shotgun sequencing) has been increasingly used for ecosystem-level investigations and shows reliable taxonomic classification down to the genus level due to advancements in bioinformatic analysis and reference databases ( 48 , 49 ).…”

Section: Introductionmentioning

confidence: 99%

Tibetan terrestrial and aquatic ecosystems collapsed with cryosphere loss inferred from sedimentary ancient metagenomics

Liu,

Stoof-Leichsenring,

Harms

et al. 2024

Sci. Adv.

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Glacier and permafrost shrinkage and land-use intensification threaten mountain wildlife and affect nature conservation strategies. Here, we present paleometagenomic records of terrestrial and aquatic taxa from the southeastern Tibetan Plateau covering the last 18,000 years to help understand the complex alpine ecosystem dynamics. We infer that steppe-meadow became woodland at 14 ka (cal BP) controlled by cryosphere loss, further driving a herbivore change from wild yak to deer. These findings weaken the hypothesis of top-down control by large herbivores in the terrestrial ecosystem. We find a turnover in the aquatic communities at 14 ka, transitioning from glacier-related (blue-green) algae to abundant nonglacier-preferring picocyanobacteria, macrophytes, fish, and otters. There is no evidence for substantial effects of livestock herding in either ecosystem. Using network analysis, we assess the stress-gradient hypothesis and reveal that root hemiparasitic and cushion plants are keystone taxa. With ongoing cryosphere loss, the protection of their habitats is likely to be of conservation benefit on the Tibetan Plateau.

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Sedimentary ancient DNA reveals past ecosystem and biodiversity changes on the Tibetan Plateau: Overview and prospects

Cited by 23 publications

References 186 publications

Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change

Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change

Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change

Tibetan terrestrial and aquatic ecosystems collapsed with cryosphere loss inferred from sedimentary ancient metagenomics

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