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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Earth Sci.</journal-id>
<journal-title>Frontiers in Earth Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Earth Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-6463</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">892524</article-id>
<article-id pub-id-type="doi">10.3389/feart.2022.892524</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Earth Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Distributive Features of Dissolved Organic Carbon in Aquatic Systems in the Source Area of the Yellow River on the Northeastern Qinghai&#x2013;Tibet Plateau, China</article-title>
<alt-title alt-title-type="left-running-head">Ma et al.</alt-title>
<alt-title alt-title-type="right-running-head">DOC in SAYR</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Ma</surname>
<given-names>Qiang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1612478/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Jin</surname>
<given-names>Huijun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/961570/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wu</surname>
<given-names>Qingbai</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1196414/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yang</surname>
<given-names>Yuzhong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1016274/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Qingfeng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1621498/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Luo</surname>
<given-names>Dongliang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/967821/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Huang</surname>
<given-names>Yadong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1837148/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Yan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1375644/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Xiaoying</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1333324/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Serban</surname>
<given-names>Raul D.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1665063/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liang</surname>
<given-names>Sihai</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1836520/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Gao</surname>
<given-names>Shuhui</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Marchenko</surname>
<given-names>Sergey S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1372959/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>State Key Laboratory of Frozen Soil Engineering</institution>, <institution>Northwest Institute of Eco-Environment and Resources</institution>, <institution>Chinese Academy of Sciences</institution>, <addr-line>Lanzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>School of Civil Engineering</institution>, <institution>Ministry of Education Observational and Research Station of Permafrost Geo-Environment in Northeast China</institution>, <institution>Institute of Cold-Regions Science and Engineering</institution>, <institution>Northeast Forestry University</institution>, <addr-line>Harbin</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education</institution>, <institution>School of Forestry</institution>, <institution>Northeast Forestry University</institution>, <addr-line>Harbin</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Institute for Alpine Environment</institution>, <institution>Eurac Research</institution>, <addr-line>Bolzano</addr-line>, <country>Italy</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>School of Water Resources and Environment</institution>, <institution>China University of Geosciences</institution>, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>School of Civil Engineering</institution>, <institution>Lanzhou Jiaotong University</institution>, <addr-line>Lanzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Geophysical Institute</institution>, <institution>University of Alaska Fairbanks</institution>, <addr-line>Fairbanks</addr-line>, <addr-line>AK</addr-line>, <country>United States</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/296579/overview">Tommaso Tesi</ext-link>, National Research Council (CNR), Italy</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1568048/overview">Chunlin Song</ext-link>, Sichuan University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/648447/overview">Xiaofan Yang</ext-link>, Beijing Normal University, China</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Huijun Jin, <email>hjjin@lzb.ac.cn</email>; Qingbai Wu, <email>qbwu@lzb.ac.cn</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Cryospheric Sciences, a section of the journal Frontiers in Earth Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>08</day>
<month>06</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>10</volume>
<elocation-id>892524</elocation-id>
<history>
<date date-type="received">
<day>09</day>
<month>03</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>19</day>
<month>04</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Ma, Jin, Wu, Yang, Wang, Luo, Huang, Li, Li, Serban, Liang, Gao and Marchenko.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Ma, Jin, Wu, Yang, Wang, Luo, Huang, Li, Li, Serban, Liang, Gao and Marchenko</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Dissolved organic carbon (DOC) is the main participant in carbon cycles through water pathways. Recent studies have highlighted the roles of aquatic systems in landscape and watershed carbon budgets. This study is based on 261 samples collected between 2016 and 2017, from individual water types (e.g., river/stream, lake/pond, icing/spring, snow/rain, groundwater/ice, and others) in the source area of the Yellow River (SAYR). These samples were analyzed for examining the distributive features of DOC in aquatic systems, especially in relation to environmental factors. It shows that: 1) DOC concentrations in permafrost-related waters (7.2&#x2013;234.4&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) were often the highest among all aquatic DOC sources (lakes/ponds: 21.3 &#xb1; 34.1&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>, rivers/streams: 4.3 &#xb1; 3.7&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>, and groundwater: 1.8 &#xb1; 1.4&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>); 2) the seasonality of riverine DOC showed declining features in 2016 and high in summer/autumn, followed by a spring freshet in 2017, and a close association with intra-annual precipitation modes; 3) the main controls of aquatic DOC are permafrost presence, precipitation, and NDVI, and they contribute to 38% of variances of environmental variables in affecting variations in aquatic DOC in the SAYR; and 4) a literature review on biodegradable DOC (BDOC) of varied aquatic DOC pools indicates the highest DOC concentrations (48&#x2013;1,548&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and BDOC (23&#x2013;71%) of ground-ice meltwater. Thus, we suggest that in the SAYR, permafrost dynamics dominate aquatic DOC distribution, and permafrost thaw may alter aquatic DOC budgets, eventually becoming an additional source for atmospheric carbon emissions.</p>
</abstract>
<kwd-group>
<kwd>alpine permafrost</kwd>
<kwd>source area of the Yellow River</kwd>
<kwd>dissolved organic carbon</kwd>
<kwd>DOC distribution</kwd>
<kwd>aquatic systems</kwd>
</kwd-group>
<contract-num rid="cn001">XDA20100103</contract-num>
<contract-sponsor id="cn001">Northeast Forestry University<named-content content-type="fundref-id">10.13039/501100002965</named-content>
</contract-sponsor>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<p>Soils in permafrost regions store &#x223c;60% organic carbon all over the globe, despite the limited areal extents of permafrost occupying less than 15% of currently exposed global land area (<xref ref-type="bibr" rid="B19">Hugelius et al., 2014</xref>; <xref ref-type="bibr" rid="B50">Schuur et al., 2015</xref>). Permafrost regions are globally important organic carbon reservoirs and play a key role in global carbon cycling (<xref ref-type="bibr" rid="B49">Schuur et al., 2008</xref>; <xref ref-type="bibr" rid="B55">Strauss et al., 2017</xref>; <xref ref-type="bibr" rid="B22">Jin and Ma, 2021</xref>). The Qinghai&#x2013;Tibet Plateau (QTP) is underlain by the most extensive alpine and plateau permafrost (1.15 &#xd7; 10<sup>6</sup>&#xa0;km<sup>2</sup>) in the world, and the warm and thin high-elevational permafrost is very sensitive to climate change (<xref ref-type="bibr" rid="B46">Ran et al., 2020</xref>).</p>
<p>Aquatic ecosystems are important pathways of carbon cycling in permafrost regions (<xref ref-type="bibr" rid="B14">Frey and McClelland, 2009</xref>). Dissolved organic carbon (DOC) is the major organic carbon pool in aquatic ecosystems and an active participant in freshwater ecology, biogeochemistry, and carbon cycles in permafrost regions through lateral pathways (<xref ref-type="bibr" rid="B18">Hope et al., 1994</xref>; <xref ref-type="bibr" rid="B10">Eimers et al., 2008</xref>). Under a warming climate, DOC dynamics in aquatic systems (e.g., rivers/streams, lakes/ponds, groundwater, among many others) have been substantially shifted and have been frequently reported in permafrost regions (<xref ref-type="bibr" rid="B48">Schindler et al., 1997</xref>; <xref ref-type="bibr" rid="B59">Vonk et al., 2015a</xref>; <xref ref-type="bibr" rid="B56">Tank et al., 2016</xref>; <xref ref-type="bibr" rid="B32">Ma, 2020</xref>). A multi-decadal observation (1972&#x2013;2012) of in-stream DOC dynamics in the Mackenzie River basin reported a general increasing trend of DOC flux (&#x2b;39.9%) at the outlet and suggests the important roles of permafrost thaw in DOC fluxes according to seasonal and sub-catchment trends (<xref ref-type="bibr" rid="B56">Tank et al., 2016</xref>). Climate change, droughts, and forest fires have already caused a 15&#x2013;20% decrease in DOC concentrations in boreal lakes, northeastern Ontario (<xref ref-type="bibr" rid="B48">Schindler et al., 1997</xref>). Thermokarst lakes formed by the thawing of ice-rich permafrost are generally characterized by high DOC concentrations (<xref ref-type="bibr" rid="B53">Shirokova et al., 2013</xref>; <xref ref-type="bibr" rid="B34">Matheus Carnevali et al., 2015</xref>; <xref ref-type="bibr" rid="B35">Matveev et al., 2016</xref>; <xref ref-type="bibr" rid="B37">Mu et al., 2016</xref>). Groundwater is projected to become an increasing source of freshwater and DOC to the Arctic Basin as permafrost thaws (<xref ref-type="bibr" rid="B7">Connolly et al., 2020</xref>). However, the distributive features of DOC in aquatic systems and individual water types (rivers/streams, lakes/ponds, groundwater, and others) are less investigated in permafrost regions, especially on the QTP.</p>
<p>Aquatic organic carbon pools are also sources of atmospheric carbon emissions (<xref ref-type="bibr" rid="B6">Cole et al., 2007</xref>; <xref ref-type="bibr" rid="B51">Serikova et al., 2018</xref>; <xref ref-type="bibr" rid="B9">Dean et al., 2020</xref>; <xref ref-type="bibr" rid="B68">Zhang et al., 2020</xref>; <xref ref-type="bibr" rid="B47">Rosentreter et al., 2021</xref>). Half of the global methane emissions originate from aquatic ecosystems, such as those in lakes/ponds, reservoirs, rivers/streams, wetlands, coastal regions, and oceans, among many others (<xref ref-type="bibr" rid="B47">Rosentreter et al., 2021</xref>). The Arctic, on average with a 16% areal extent of water bodies in all landscapes (<xref ref-type="bibr" rid="B59">Vonk et al., 2015a</xref>), may become a region of net carbon emission under a warming climate (<xref ref-type="bibr" rid="B51">Serikova et al., 2018</xref>). The QTP is also a water-abundant domain, originating from 13 major rivers in Eastern and Southern Asia (e.g., Yellow, Yangtze, and Mekong rivers), annually discharging about 6.56 trillion m<sup>3</sup> (6,560&#xa0;km<sup>3</sup>) of water, or 13% of global total annual discharge (<xref ref-type="bibr" rid="B62">Wang et al., 2021</xref>). In-stream average methane emission rates from the eastern QTP were also reported as high as 11.9&#xa0;mmol CH<sub>4</sub>&#xb7;m<sup>&#x2212;2</sup>&#xb7;d<sup>&#x2212;1</sup>, six times higher than the concurrent global average (<xref ref-type="bibr" rid="B68">Zhang et al., 2020</xref>). Therefore, aquatic DOC pools are potentially important sources for atmospheric carbon emissions.</p>
<p>Extensively (34% of the areal extent of the catchment) underlain by permafrost, the source area of the Yellow River (SAYR) above the Tanag hydrological station on northeastern QTP presents various water types, such as rivers/streams, tectonic and thermokarst lakes, wetlands, icings, and springs. Aquatic systems are crucial pathways for regional carbon budgets, while distributive features of aquatic DOC and its regulators have been seldomly systematically explored. In this study, a total of 261 water samples from various waters across the SAYR were collected and analyzed for investigating the distribution of DOC concentrations in aquatic systems. Then, by employing principal component analysis (PCA), influencing environmental factors of DOC concentrations in individual water types are examined. In the end, by synthesizing globally published data on biodegradable DOC in varied water types, the release potentials of aquatic DOC to the atmosphere are briefly discussed.</p>
</sec>
<sec id="s2">
<title>2 Study Area and Methods</title>
<sec id="s2-1">
<title>2.1 Study Area</title>
<p>The SAYR (32.2&#xb0;&#x2013;36.1&#xb0;N, 95.9&#xb0;&#x2013;103.4&#xb0;E; 2,629&#x2013;6,235&#xa0;m a. s.&#xa0;l.) is the up-reach catchment of the Yellow River basin above the Tanag hydrological station (35.5&#x2da;N, 100.2&#x2da;E; 2,629&#xa0;m a. s.&#xa0;l.), on the northeastern QTP, China (<xref ref-type="fig" rid="F1">Figure 1</xref>), covering an area of 1.212 &#xd7; 10<sup>5</sup>&#xa0;km<sup>2</sup>. The climate in the SAYR is characterized by long winters (November&#x2013;April) and short summers (June&#x2013;August). Mean annual air temperature (MAAT) and annual precipitation in the SAYR are 0.2&#xb0;C and 507.7&#xa0;mm (1960&#x2013;2012), respectively (<xref ref-type="bibr" rid="B28">Lan et al., 2013</xref>). The climate in the up-reach SAYR above the Huanghe&#x2019;yan hydrological station (34.9&#xb0;N, 98.2&#xb0;E; 4,215&#xa0;m a. s.&#xa0;l.) is characterized by a dry&#x2013;cold climate with a MAAT less than &#x2212;3.5&#xb0;C and annual precipitation of 300&#x2013;400&#xa0;mm (<xref ref-type="bibr" rid="B24">Jin et al., 2010</xref>). The growing season varies with elevation but mainly concentrates from May to September. With an areal extent of permafrost at 34% in the SAYR, permafrost occurs extensively (86%) in the up-reach SAYR, with rich manifestations in periglacial landforms and MAAT (1961&#x2013;2019) varying from &#x2212;3.5 to about 0&#xb0;C. Alpine permafrost can be as thick as up to about 360&#xa0;m on very high mountain tops on the peak of Mt. Maq&#xea;n Gangri (6,235&#xa0;m a. s.&#xa0;l.) in the Anye Maq&#xea;n Mountains (<xref ref-type="bibr" rid="B61">Wang and French, 1995</xref>; <xref ref-type="bibr" rid="B20">Jin et al., 2009</xref>, <xref ref-type="bibr" rid="B23">2020</xref>; <xref ref-type="bibr" rid="B29">Luo et al., 2020</xref>; <xref ref-type="bibr" rid="B52">Sheng et al., 2020</xref>). The lower reaches/basins of the SAYR between Huanghe&#x2019;yan and Tanag hydrological stations are dominated by a relatively warm&#x2013;wet climate, particularly in the southeastern SAYR (mainly on the Zo&#xee;g&#xe9; Peat Plateau), where MAAT is at about 7.5&#xb0;C and annual precipitation, about 654&#xa0;mm (<xref ref-type="bibr" rid="B67">Yu et al., 2017</xref>). The snow-melt season generally extends from April to October in the lower reaches/basins of the SAYR. Glaciers are minimally presented in the SAYR (mainly in the Anye Maq&#xea;n Mountains) (126.7&#xa0;km<sup>2</sup>), or 2% of the SAYR in the areal extent (<xref ref-type="bibr" rid="B3">Blue et al., 2013</xref>; <xref ref-type="bibr" rid="B21">Jin et al., 2019</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Map of sampling locations in the source area of the Yellow River (SAYR) on the northeastern Qinghai&#x2013;Tibet Plateau, SW China. Notes: Sub-panel SOC shows the spatial distribution of soil organic carbon (SOC) content; sub-panel PP shows the distribution of permafrost presence; sub-panel PREP is the distribution of daily precipitation on 12 August 2016; and sub-panel NDVI is the normalized difference vegetation index on 12 August 2016.</p>
</caption>
<graphic xlink:href="feart-10-892524-g001.tif"/>
</fig>
<p>The SAYR is characterized by a high-mountain surrounded by flat valleys and plains. The baseflow accounts for a large portion of annual streamflow (&#x223c;50% or more) (<xref ref-type="bibr" rid="B30">Ma et al., 2019a</xref>). Numerous meandering rivers in the valleys on the Zo&#xee;g&#xe9; Peat Plateau, which are conducive to water conservancy, in addition to rich precipitation, have facilitated the accumulation of thick peat layers (0.5&#x223c;10.5&#xa0;m) in the Holocene (mainly since 11.7&#xa0;ka B.P.), particularly in the Megathermal period in the mid-Holocene at 8.5&#x2013;4.0&#xa0;ka B. P. (<xref ref-type="bibr" rid="B67">Yu et al., 2017</xref>; <xref ref-type="bibr" rid="B21">Jin et al., 2019</xref>, <xref ref-type="bibr" rid="B23">2020</xref>). Alpine steppes and alpine meadows dominate alpine vegetation in the up-reach SAYR and the lower reaches/basins of SAYR; The SAYR is sporadically dotted with shrubs and forests at lower elevations. In alpine wetlands on the Zo&#xee;g&#xe9; Peat Plateau, aquatic vegetation (e.g., <italic>Kobresia pygmaea</italic> and <italic>K. tibetica</italic>) is extensively observed (<xref ref-type="bibr" rid="B4">Brierley et al., 2016</xref>).</p>
</sec>
<sec id="s2-2">
<title>2.2 Methods</title>
<sec id="s2-2-1">
<title>2.2.1 Sample Collection and Laboratory Analyses</title>
<p>The field data were collected from April 2016 to December 2017 in rivers/streams, lakes/ponds, commercial wells, precipitation, aufeis, and springs in the SAYR (<xref ref-type="fig" rid="F1">Figure 1</xref>). A total of 261 water samples were collected during the sampling periods. The river/stream samples were mainly collected in the up-reach SAYR, such as the mainstream Yellow River and its tributaries (Kari Qu, Duo Qu, Lena Qu, Ze Qu, You&#x2019;er Qu, and Hei&#x2019;he and Bai&#x2019;he rivers on the Zo&#xee;g&#xe9; Peat Plateau) in the snow-melt season (April&#x2013;May), summer&#x2013;autumn season (July&#x2013;October), and the freezing season (November&#x2013;next March). The water samples of lakes/ponds were collected from thermokarst lakes, large-size tectonic lakes (e.g., Gyaring and Ngoring lakes), and lakes on the Zo&#xee;g&#xe9; Plateau, among many others. Groundwater samples were collected from multiple commercial wells in villages and towns across the SAYR. A borehole was drilled on the northern shore of the Wanlong Worma Lake to the south of Ng&#xf6;ring Lake in the up-reach SAYR and the samples of supra- and sub-permafrost waters were collected during the field-work season of 29 April to 2&#xa0;May 2017. In the lower reaches/basins of SAYR, a 25-m-deep borehole was drilled on 22 October 2017 near Maqu County, and the water samples were collected and labeled as phreatic groundwater. Precipitation samples were collected in both solid precipitation (snow/hail) and rain. Aufeis/icings were mainly collected in the up-reach SAYR in the winter of 2016 and 2017 (<xref ref-type="fig" rid="F2">Figure 2</xref>). Detailed information on water sampling is provided in <xref ref-type="sec" rid="s12">Table S1</xref>.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Dissolved organic carbon concentrations (mg C&#xb7;L<sup>&#x2212;1</sup>) in aquatic systems in the source area of the Yellow River (SAYR) above the Tanag hydrological station in Qinghai Province, SW China. Notes: &#x201c;<bold>
<italic>n</italic>
</bold>&#x201d; indicates the number of field samples. <bold>(A)</bold> DOC concentrations in individual water type (hail/snow/rain, groundwater, lakes/ponds, river/stream, and icing/spring); <bold>(B)</bold> permafrost-related aquatic DOC concentrations; <bold>(C)</bold> seasonal variations of in-stream DOC concentrations in 2016; <bold>(D)</bold> seasonal variations of in-stream DOC concentrations in 2017.</p>
</caption>
<graphic xlink:href="feart-10-892524-g002.tif"/>
</fig>
<p>The water samples were taken to the State Key Laboratory of Frozen Soils Engineering, Lanzhou, China, after collection and kept at 4&#xb0;C before laboratory pre-processing and analyses. The water samples were first filtered through the mixed cellulose ester (MCE) filters (0.45&#xa0;&#xb5;m pore size), and the content of DOC was determined using a total organic carbon analyzer (TOC analyzer, I. O. Corporation; precision: &#xb1; 0.5&#x2030;).</p>
</sec>
<sec id="s2-2-2">
<title>2.2.2 Statistical Analyses</title>
<p>To evaluate the environmental controllers for aquatic DOC concentrations, we employed the principal component analysis (PCA) (<xref ref-type="bibr" rid="B27">Kotz and Nadarajah, 2004</xref>). The presence of permafrost, SOC content, normalized difference vegetation index (NDVI), and precipitation were taken as the environmental controllers for aquatic DOC concentrations (<xref ref-type="fig" rid="F1">Figure 1</xref>). Data information and sources are presented in <xref ref-type="table" rid="T1">Table 1</xref>.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>List of environmental controllers for aquatic DOC concentrations in the source area of the Yellow River (SAYR) above the Tanag hydrological station in Qinghai Province, Southwest China.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Data type</th>
<th align="center">Abbreviation</th>
<th align="center">Temporal span</th>
<th align="center">Temporal resolution (d)</th>
<th align="center">Data source</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Precipitation</td>
<td align="left">PREP</td>
<td align="center">2016&#x2013;2017</td>
<td align="center">1</td>
<td align="left">National Meteorological Information Center (<ext-link ext-link-type="uri" xlink:href="http://data.cma.cn">http://data.cma.cn</ext-link>)</td>
</tr>
<tr>
<td align="left">Permafrost presence</td>
<td align="left">PP</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="left">
<xref ref-type="bibr" rid="B45">Ran et al. (2022)</xref>
</td>
</tr>
<tr>
<td align="left">Normalized difference vegetation index</td>
<td align="left">NDVI</td>
<td align="center">2016&#x2013;2017</td>
<td align="center">16</td>
<td align="left">National Earth System Science Data Center (<ext-link ext-link-type="uri" xlink:href="http://www.geodata.cn">http://www.geodata.cn</ext-link>)</td>
</tr>
<tr>
<td align="left">Soil organic carbon content</td>
<td align="left">OC</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="left">
<xref ref-type="bibr" rid="B64">Wieder et al. (2014)</xref>
</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Daily precipitation data were measured using the Chinese standard precipitation gauge without discriminating between liquid and solid precipitation forms. An error validation (wetting and evaporation losses, trace precipitation, and wind) was implemented for liquid and solid precipitation forms, respectively, by employing daily air temperature and wind speed data (<xref ref-type="bibr" rid="B66">Ye et al., 2004</xref>; <xref ref-type="bibr" rid="B65">Yang et al., 2005</xref>). The validated daily precipitation was then interpolated using the empirical Bayesian kriging method to obtain the spatial distribution of daily precipitation in the SAYR. Winter precipitation was calculated by accumulating daily solid precipitation in winter. Spring precipitation was calculated by accumulating winter snowfall, due to spring freshet was mainly impacted by melting accumulated snow in winter (<xref ref-type="bibr" rid="B30">Ma et al., 2019a</xref>). The site-specific data of the environmental variables were extracted from spatial data at the sampling sites (<xref ref-type="fig" rid="F1">Figure 1</xref>). PCA was used to summarize the rescaled variables (PREP, PP, SOC, and NDVI) by reducing the dimensionality of the data while retaining most of the variability in the dataset to determine impacting environmental variables at aquatic DOC sampling sites and to find linear relationships between environmental variables. All statistical analyses were implemented in the Origin Pro 2021b.</p>
</sec>
<sec id="s2-2-3">
<title>2.2.3 Literature Synthesis</title>
<p>A meta-analysis of results of both seasonally in-stream dynamics and concentrations of DOC in various water types was implemented to compare DOC concentrations in various water types in the SAYR with those in other alpine/high-plateau and northern/Arctic permafrost regions to have a comprehensive understanding of aquatic DOC distributions. A synthesis of published data on biodegradable DOC in various water types in northern permafrost regions, in combination with the distribution of aquatic DOC concentrations, was analyzed to determine the releasing potentials of aquatic DOC to atmospheric carbon emissions. DOC concentrations and BDOC data were gathered by synthesizing relevant studies on the ISI Web of Science<sup>TM</sup>, as well as previous compilations on DOC in permafrost regions and the biodegradability of aquatic DOC (such as <xref ref-type="bibr" rid="B60">Vonk et al., 2015b</xref>; <xref ref-type="bibr" rid="B31">Ma et al., 2019b</xref>). A total of 19 studies on DOC concentrations and aquatic BDOC with experimental data were referred (<xref ref-type="bibr" rid="B13">Finlay et al., 2006</xref>, <xref ref-type="bibr" rid="B12">2009</xref>; <xref ref-type="bibr" rid="B15">Guo and Macdonald, 2006</xref>; <xref ref-type="bibr" rid="B42">Petrone et al., 2006</xref>; <xref ref-type="bibr" rid="B17">Holmes et al., 2008</xref>; <xref ref-type="bibr" rid="B2">Balcarczyk et al., 2009</xref>; <xref ref-type="bibr" rid="B38">O&#x2019;Donnell et al., 2012</xref>; <xref ref-type="bibr" rid="B63">Wickland et al., 2012</xref>; <xref ref-type="bibr" rid="B39">Olefeldt and Roulet, 2014</xref>; <xref ref-type="bibr" rid="B1">Abbott et al., 2014</xref>; <xref ref-type="bibr" rid="B58">Vonk et al., 2013</xref>; <xref ref-type="bibr" rid="B11">Ewing et al., 2015</xref>; <xref ref-type="bibr" rid="B33">Mann et al., 2015</xref>; <xref ref-type="bibr" rid="B37">Mu et al., 2016</xref>; <xref ref-type="bibr" rid="B40">Selvam et al., 2017</xref>; <xref ref-type="bibr" rid="B57">Textor et al., 2019</xref>; <xref ref-type="bibr" rid="B7">Connolly et al., 2020</xref>; <xref ref-type="bibr" rid="B41">Payandi-Rolland et al., 2020</xref>; <xref ref-type="bibr" rid="B5">Chen et al., 2021</xref>; <xref ref-type="bibr" rid="B54">Stolpmann et al., 2021</xref>). Among these results, we collect DOC concentrations and BDOC in literature works by following the criteria, as: 1) located in the alpine (e.g., QTP) or Arctic permafrost regions, 2) ranges of DOC concentrations and BDOC were adopted, and 3) using incubation experiments or chemical proxies to access BDOC.</p>
</sec>
</sec>
</sec>
<sec sec-type="results|discussion" id="s3">
<title>3 Results and Discussions</title>
<sec id="s3-1">
<title>3.1 Patterned DOC Concentrations in Aquatic Systems in the SAYR</title>
<p>DOC concentrations in aquatic systems show strong variations among individual water types in the SAYR (<xref ref-type="fig" rid="F2">Figure 2A</xref>). The highest DOC concentration was found in thermokarst lakes with an average of 38.4 &#xb1; 48.5&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup> (<italic>n</italic> &#x3d; 171 samples; data are expressed as average &#xb1; one standard deviation) and a maximum of 234.4&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>. Permafrost-related water types showed similarly high DOC concentrations (ground-ice meltwater: 32.94&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>, supra-permafrost water: 20.54 &#xb1; 3.6&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>, and sub-permafrost water: 16.8 &#xb1; 1.2&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) (<xref ref-type="fig" rid="F2">Figure 2B</xref>). Thermokarst lakes/ponds (21.3 &#xb1; 34.1&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) were characterized by almost five times higher average DOC concentrations than those of rivers/streams (4.3 &#xb1; 3.7&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and with a wide DOC range of &#x223c;0.5&#x2013;234.4&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>. Other water types (hail/snow/rain, springs/icings, and groundwater) had low average DOC concentrations between 0.8 &#xb1; 1.0 and 1.8 &#xb1; 1.4&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>, and their ranges were much narrower than those lakes/ponds and rivers/streams (<xref ref-type="table" rid="T2">Table 2</xref>). There are marked seasonal variations in in-stream DOC concentrations in the SAYR. The SAYR-average of DOC concentrations in winter is generally lower than those in spring (snow-melt season), summer, and autumn. In 2016, the greatest in-stream DOC concentration (4.5 &#xb1; 2.2&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) occurred during the spring snow-melt season, and decreased into summer&#x2013;autumn (2.4 &#xb1; 3.7&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>), and winter (0.8 &#xb1; 0.6&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) (<xref ref-type="fig" rid="F2">Figure 2C</xref>). In 2017, DOC concentrations were the greatest in summer&#x2013;autumn (7.0 &#xb1; 4.8&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>), with a range of 0.5&#x2013;13.4&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>, followed by those of the snow-melt season (3.6 &#xb1; 6.0&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and the winter season (1.1 &#xb1; 0.5&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) (<xref ref-type="fig" rid="F2">Figure 2D</xref>).</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>List of minimum, average, median, and maximum values of dissolved organic carbon (DOC) concentrations in each water type in the source area of the Yellow River (SAYR) above the Tanag hydrological station in Qinghai Province, China.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">Water type</th>
<th rowspan="2" align="center">Region</th>
<th colspan="4" align="center">DOC (mg C&#xb7;L<sup>&#x2212;1</sup>)</th>
<th rowspan="2" align="center">Reference</th>
</tr>
<tr>
<th align="center">Minimum</th>
<th align="center">Average &#xb1; SD</th>
<th align="center">Median</th>
<th align="center">Maximum</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="3" align="left">Streams/rivers</td>
<td align="left">SAYR</td>
<td align="center">0.7</td>
<td align="center">4.2 &#xb1; 3.7</td>
<td align="center">3.1</td>
<td align="center">21.0</td>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">Permafrost regions</td>
<td align="center">1.0</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="center">32.0</td>
<td align="left">
<xref ref-type="bibr" rid="B31">Ma et al. (2019b)</xref>
</td>
</tr>
<tr>
<td align="left">QTP</td>
<td align="center">0.4</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="center">30.8</td>
<td align="left">
<xref ref-type="bibr" rid="B5">Chen et al. (2021)</xref>
</td>
</tr>
<tr>
<td rowspan="2" align="left">Spring streamflows</td>
<td align="left">SAYR</td>
<td align="center">0.1</td>
<td align="center">4.3 &#xb1; 3.1</td>
<td align="center">3.8</td>
<td align="center">25.4</td>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">Upper Yukon</td>
<td align="center">&#x2014;</td>
<td align="center">36.12</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="left">
<xref ref-type="bibr" rid="B15">Guo and Macdonald (2006)</xref>
</td>
</tr>
<tr>
<td rowspan="2" align="left">Summer&#x2013;autumn streamflows</td>
<td align="left">SAYR</td>
<td align="center">0.5</td>
<td align="center">4.5 &#xb1; 4.8</td>
<td align="center">2.1</td>
<td align="center">21.0</td>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">Upper Yukon</td>
<td align="center">&#x2014;</td>
<td align="center">7.3</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="left">
<xref ref-type="bibr" rid="B15">Guo and Macdonald (2006)</xref>
</td>
</tr>
<tr>
<td rowspan="3" align="left">Winter streamflows</td>
<td align="left">SAYR</td>
<td align="center">0.5</td>
<td align="center">0.9 &#xb1; 0.6</td>
<td align="center">0.8</td>
<td align="center">1.5</td>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">Yukon Basin</td>
<td align="center">1.0</td>
<td align="center">3.9 &#xb1; 0.5</td>
<td align="center">&#x2014;</td>
<td align="center">20.0</td>
<td align="left">
<xref ref-type="bibr" rid="B38">O&#x27;Donnell et al. (2012)</xref>
</td>
</tr>
<tr>
<td align="left">YZR</td>
<td align="center">&#x2014;</td>
<td align="center">0.5 &#xb1; 0.2</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="left">
<xref ref-type="bibr" rid="B5">Chen et al. (2021)</xref>
</td>
</tr>
<tr>
<td rowspan="2" align="left">Lakes/ponds</td>
<td align="left">SAYR</td>
<td align="center">0.5</td>
<td align="center">21.3 &#xb1; 34.1</td>
<td align="center">9.4</td>
<td align="center">234.4</td>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">Permafrost regions</td>
<td align="center">0.0</td>
<td align="center">&#x2014;</td>
<td align="center">10.8</td>
<td align="center">1,130.0</td>
<td align="left">
<xref ref-type="bibr" rid="B54">Stolpmann et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Springs/icings</td>
<td align="left">SAYR</td>
<td align="center">0.2</td>
<td align="center">0.6 &#xb1; 0.5</td>
<td align="center">0.5</td>
<td align="center">1.7</td>
<td align="left">This study</td>
</tr>
<tr>
<td rowspan="2" align="left">Precipitation (rain, snow, and others)</td>
<td align="left">SAYR</td>
<td align="center">0.4</td>
<td align="center">0.8 &#xb1; 1.0</td>
<td align="center">0.4</td>
<td align="center">1.8</td>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">Permafrost regions</td>
<td align="center">1.0</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="center">2.4</td>
<td align="left">
<xref ref-type="bibr" rid="B31">Ma et al. (2019b)</xref>
</td>
</tr>
<tr>
<td rowspan="2" align="left">Groundwater</td>
<td align="left">SAYR</td>
<td align="center">0.6</td>
<td align="center">1.8 &#xb1; 1.4</td>
<td align="center">1.4</td>
<td align="center">5.3</td>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">Permafrost regions</td>
<td align="center">&#x2014;</td>
<td align="center">&#x223c;0.7</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="left">
<xref ref-type="bibr" rid="B31">Ma et al. (2019b)</xref>
</td>
</tr>
<tr>
<td rowspan="2" align="left">Supra-permafrost water</td>
<td align="left">SAYR</td>
<td align="center">17.9</td>
<td align="center">20.5 &#xb1; 3.6</td>
<td align="center">&#x2014;</td>
<td align="center">23.1</td>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">Alaskan Arctic NE coast</td>
<td align="center">&#x2014;</td>
<td align="center">33 &#xb1; 2</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="left">
<xref ref-type="bibr" rid="B7">Connolly et al. (2020)</xref>
</td>
</tr>
<tr>
<td align="left">Sub-permafrost water</td>
<td align="left">SAYR</td>
<td align="center">15.9</td>
<td align="center">16.8 &#xb1; 1.2</td>
<td align="center">&#x2014;</td>
<td align="center">17.6</td>
<td align="left">This study</td>
</tr>
<tr>
<td rowspan="2" align="left">Ground-ice meltwater</td>
<td align="left">SAYR</td>
<td align="center">&#x2014;</td>
<td align="center">32.94</td>
<td align="center">&#x2014;</td>
<td align="left"/>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">Interior Alaska</td>
<td align="center">48</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="center">1,548</td>
<td align="left">
<xref ref-type="bibr" rid="B11">Ewing et al. (2015)</xref>
</td>
</tr>
<tr>
<td rowspan="2" align="left">Thermokarst lakes/ponds</td>
<td align="left">SAYR</td>
<td align="center">7.2</td>
<td align="center">38.5 &#xb1; 48.5</td>
<td align="center">27.1</td>
<td align="center">234.4</td>
<td align="left">This study</td>
</tr>
<tr>
<td align="left">QTP</td>
<td align="center">1.2</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="center">49.6</td>
<td align="left">
<xref ref-type="bibr" rid="B37">Mu et al. (2016)</xref>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: YZR stands for the Yarlung Zangbo River in the southern Tibet Autonomous Region, Southwest China.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>In the SAYR, in-stream DOC concentrations are averaged at 4.2 &#xb1; 3.7&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>, with a range of 0.7&#x2013;21.0&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>, comparable to DOC ranges in northern permafrost regions (1&#x2013;32&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and some other catchments on the QTP (0.4&#x2013;30.8&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>). In the SAYR, in-stream DOC concentrations were characterized by the greatest values (4.5 &#xb1; 2.2&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) during the spring snow-melt season, and decreased in summer&#x2013;autumn (2.4 &#xb1; 3.7&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and declined further in winter (0.8 &#xb1; 0.6&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) in 2016 (<xref ref-type="fig" rid="F2">Figure 2C</xref>). In 2017, DOC concentrations were the greatest in summer&#x2013;autumn (7.0 &#xb1; 4.8&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>), followed by those in the snow-melt season (3.6 &#xb1; 6.0&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and winter season (1.1 &#xb1; 0.5&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) (<xref ref-type="fig" rid="F2">Figure 2D</xref>). In northern permafrost regions, such as the upper Yukon River Basin, seasonal DOC concentrations are characterized by the greatest average in-stream DOC (36.12&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) in the snow-melt season and decreased to that in summer&#x2013;autumn (7.3&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) (<xref ref-type="bibr" rid="B15">Guo and Macdonald, 2006</xref>; <xref ref-type="bibr" rid="B16">Guo et al., 2018</xref>). It is generally proven that in-stream DOC concentrations are positively related with discharge. In the upper Yukon River, the yearly peak flow occurs in spring freshet and the discharge declines in the following seasons (<xref ref-type="bibr" rid="B15">Guo and Macdonald, 2006</xref>; <xref ref-type="bibr" rid="B16">Guo et al., 2018</xref>).</p>
<p>The Yellow River flow in the SAYR is dominated by the monsoonal climate and mainly recharged by summer precipitation from July to September. In 2017, the summer peak flow induced high in-stream DOC concentrations from July to September. However, in 2016, the SAYR underwent a dryer summer, and no peak flow was observed from July to September. Therefore, accumulated snowfall in winter merely induced a small spring freshet and relatively high snow-melt DOC concentrations. In winter, in-stream DOC concentrations in the SAYR were smaller than those in the summer&#x2013;autumn and snow-melt season in both 2016 and 2017. They are consistent with those existing observations in northern permafrost regions. However, winter in-stream DOC concentrations in the SAYR (0.9 &#xb1; 0.6&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>), comparable with those of the upper Yarlung Zangbo River (0.5 &#xb1; 0.2&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) on the southern Tibet Plateau, are smaller than those in northern permafrost regions (e.g., Yukon: 3.9 &#xb1; 0.5&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>). Lacustrine DOC concentrations (0.5&#x2013;234.4&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) in the SAYR are generally lower than those in northern permafrost regions (0&#x2013;1,130&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>), while comparable to those on the QTP (21.3 &#xb1; 34.1&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>). DOC concentrations in the supra-permafrost water (20.5 &#xb1; 3.6&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) are higher than those in the sub-permafrost water (16.8 &#xb1; 1.2&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) (<italic>n</italic> &#x3d; 4; north bank of the Wanlong Worma Lake in the Wanlong Worma River Basin of the Duo Qu River in the south-central SAYR). Along the Alaska Arctic coast, DOC concentrations of supra-permafrost water are reported as 33 &#xb1; 2&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup> (<xref ref-type="bibr" rid="B7">Connolly et al., 2020</xref>), which is higher than those observed in the SAYR. DOC concentrations in ground-ice melt-water in the up-reach SAYR are much lower than those in northern permafrost regions, which may be resulted from the limited dataset. DOC concentrations in springs/icings waters, precipitation, and groundwater are generally low (&#x223c;1&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>), with DOC in groundwater a bit higher than the other two water types.</p>
</sec>
<sec id="s3-2">
<title>3.2 Environmental Controllers for Aquatic DOC Concentrations in the SAYR</title>
<p>The site-specific data of environmental elements (PREP, NDVI, SOC, and PP) were extracted and the principle environmental controllers for aquatic DOC concentrations were examined by employing the standard PCA method. Data were binned into in-stream water samples collected in the snow-melt season, summer/autumn and winter, groundwater samples, lacustrine samples, and altogether binning of various aquatic samples for the PCAs (<xref ref-type="table" rid="T3">Table 3</xref>; <xref ref-type="fig" rid="F3">Figure 3</xref>). In different water types, the sources and formations of DOC may differ, such as seasonally hydrological processes bringing in different DOC sources into streams/rivers. By binning environmental variables and DOC concentrations in different water types, the key environmental controllers can be determined for each water type.</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Correlations between multi-environmental variables and aquatic DOC concentrations for each principal component in a PCA analysis.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left"/>
<th colspan="3" align="center">Snow-melt season</th>
<th rowspan="2" align="left"/>
<th colspan="3" align="center">Summer/autumn</th>
<th rowspan="2" align="left"/>
<th colspan="3" align="center">Winter</th>
</tr>
<tr>
<th align="center">1</th>
<th align="center">2</th>
<th align="center">3</th>
<th align="center">1</th>
<th align="center">2</th>
<th align="center">3</th>
<th align="center">1</th>
<th align="center">2</th>
<th align="center">3</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">PP</td>
<td align="char" char=".">
<bold>0.59</bold>
</td>
<td align="char" char=".">0.04</td>
<td align="char" char=".">0.09</td>
<td align="left">PP</td>
<td align="char" char=".">
<bold>0.65</bold>
</td>
<td align="char" char=".">0.10</td>
<td align="char" char=".">&#x2212;0.06</td>
<td align="left">PP</td>
<td align="char" char=".">0.46</td>
<td align="char" char=".">
<bold>0.51</bold>
</td>
<td align="char" char=".">0.07</td>
</tr>
<tr>
<td align="left">PREP</td>
<td align="char" char=".">
<bold>0.61</bold>
</td>
<td align="char" char=".">&#x2212;0.01</td>
<td align="char" char=".">&#x2212;0.07</td>
<td align="left">PREP</td>
<td align="char" char=".">&#x2212;0.27</td>
<td align="char" char=".">0.46</td>
<td align="char" char=".">
<bold>0.80</bold>
</td>
<td align="left">PREP</td>
<td align="char" char=".">&#x2212;0.07</td>
<td align="char" char=".">
<bold>0.77</bold>
</td>
<td align="char" char=".">0.28</td>
</tr>
<tr>
<td align="left">SOC</td>
<td align="char" char=".">0.09</td>
<td align="char" char=".">&#x2212;<bold>0.69</bold>
</td>
<td align="char" char=".">
<bold>0.71</bold>
</td>
<td align="left">SOC</td>
<td align="char" char=".">0.40</td>
<td align="char" char=".">&#x2212;0.46</td>
<td align="char" char=".">
<bold>0.55</bold>
</td>
<td align="left">SOC</td>
<td align="char" char=".">
<bold>0.57</bold>
</td>
<td align="char" char=".">&#x2212;0.27</td>
<td align="char" char=".">&#x2212;0.04</td>
</tr>
<tr>
<td align="left">NDVI</td>
<td align="char" char=".">&#x2212;0.42</td>
<td align="char" char=".">0.37</td>
<td align="char" char=".">
<bold>0.52</bold>
</td>
<td align="left">NDVI</td>
<td align="char" char=".">&#x2212;<bold>0.57</bold>
</td>
<td align="char" char=".">&#x2212;0.27</td>
<td align="char" char=".">&#x2212;0.11</td>
<td align="left">NDVI</td>
<td align="char" char=".">0.49</td>
<td align="char" char=".">0.16</td>
<td align="char" char=".">&#x2212;<bold>0.65</bold>
</td>
</tr>
<tr>
<td align="left">DOC</td>
<td align="char" char=".">0.32</td>
<td align="char" char=".">
<bold>0.63</bold>
</td>
<td align="char" char=".">0.46</td>
<td align="left">DOC</td>
<td align="char" char=".">0.13</td>
<td align="char" char=".">
<bold>0.71</bold>
</td>
<td align="char" char=".">&#x2212;0.19</td>
<td align="left">DOC</td>
<td align="char" char=".">0.47</td>
<td align="char" char=".">0.23</td>
<td align="char" char=".">
<bold>0.70</bold>
</td>
</tr>
<tr>
<td align="left">Variance explained</td>
<td align="char" char=".">41</td>
<td align="char" char=".">22</td>
<td align="char" char=".">18</td>
<td align="left">Variance explained</td>
<td align="char" char=".">33</td>
<td align="char" char=".">27</td>
<td align="char" char=".">17</td>
<td align="left">Variance explained</td>
<td align="char" char=".">42</td>
<td align="char" char=".">28</td>
<td align="char" char=".">14</td>
</tr>
</tbody>
</table>
<table>
<thead>
<tr>
<td rowspan="2" align="left"/>
<td colspan="3" align="center">Groundwater</td>
<td rowspan="2" align="left"/>
<td colspan="3" align="center">Lakes/ponds</td>
<td rowspan="2" align="left"/>
<td colspan="3" align="center">Aquatic systems</td>
</tr>
<tr>
<td align="center">1</td>
<td align="center">2</td>
<td align="left"/>
<td align="center">1</td>
<td align="center">2</td>
<td align="center">3</td>
<td align="center">1</td>
<td align="center">2</td>
<td align="center">3</td>
</tr>
</thead>
<tbody>
<tr>
<td align="left">PP</td>
<td align="char" char=".">
<bold>0.56</bold>
</td>
<td align="char" char=".">0.22</td>
<td align="center">&#x2014;</td>
<td align="left">PP</td>
<td align="char" char=".">0.43</td>
<td align="char" char=".">0.44</td>
<td align="char" char=".">&#x2212;0.12</td>
<td align="left">PP</td>
<td align="char" char=".">
<bold>0.52</bold>
</td>
<td align="char" char=".">0.22</td>
<td align="char" char=".">0.17</td>
</tr>
<tr>
<td align="left">PREP</td>
<td align="char" char=".">0.13</td>
<td align="char" char=".">&#x2212;<bold>0.66</bold>
</td>
<td align="center">&#x2014;</td>
<td align="left">PREP</td>
<td align="char" char=".">
<bold>0.63</bold>
</td>
<td align="char" char=".">&#x2212;0.06</td>
<td align="char" char=".">&#x2212;0.16</td>
<td align="left">PREP</td>
<td align="char" char=".">
<bold>0.59</bold>
</td>
<td align="char" char=".">&#x2212;0.06</td>
<td align="char" char=".">&#x2212;0.11</td>
</tr>
<tr>
<td align="left">SOC</td>
<td align="char" char=".">0.39</td>
<td align="char" char=".">0.46</td>
<td align="center">&#x2014;</td>
<td align="left">SOC</td>
<td align="char" char=".">&#x2212;0.16</td>
<td align="char" char=".">
<bold>0.60</bold>
</td>
<td align="char" char=".">&#x2212;<bold>0.68</bold>
</td>
<td align="left">SOC</td>
<td align="char" char=".">0.03</td>
<td align="char" char=".">
<bold>0.82</bold>
</td>
<td align="char" char=".">0.46</td>
</tr>
<tr>
<td align="left">NDVI</td>
<td align="char" char=".">&#x2212;0.33</td>
<td align="char" char=".">
<bold>0.55</bold>
</td>
<td align="center">&#x2014;</td>
<td align="left">NDVI</td>
<td align="char" char=".">&#x2212;0.40</td>
<td align="char" char=".">
<bold>0.57</bold>
</td>
<td align="char" char=".">
<bold>0.50</bold>
</td>
<td align="left">NDVI</td>
<td align="char" char=".">&#x2212;<bold>0.52</bold>
</td>
<td align="char" char=".">&#x2212;0.10</td>
<td align="char" char=".">0.49</td>
</tr>
<tr>
<td align="left">DOC</td>
<td align="char" char=".">
<bold>0.64</bold>
</td>
<td align="char" char=".">&#x2212;0.06</td>
<td align="center">&#x2014;</td>
<td align="left">DOC</td>
<td align="char" char=".">0.49</td>
<td align="char" char=".">0.34</td>
<td align="char" char=".">
<bold>0.50</bold>
</td>
<td align="left">DOC</td>
<td align="char" char=".">0.31</td>
<td align="char" char=".">&#x2212;<bold>0.52</bold>
</td>
<td align="char" char=".">
<bold>0.71</bold>
</td>
</tr>
<tr>
<td align="left">Variance explained</td>
<td align="char" char=".">42</td>
<td align="char" char=".">33</td>
<td align="center">&#x2014;</td>
<td align="left">Variance explained</td>
<td align="char" char=".">36</td>
<td align="char" char=".">23</td>
<td align="char" char=".">19</td>
<td align="left">Variance explained</td>
<td align="char" char=".">38</td>
<td align="char" char=".">22</td>
<td align="char" char=".">18</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Notes: According to the practice of <xref ref-type="bibr" rid="B60">Vonk et al. (2015b)</xref>, the correlation coefficients of above 0.7 are considered strong, and those at 0.5&#x2013;0.7, moderate.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Biplot of the PCA of various water types in the source area of the Yellow River (SAYR) and variable correlation plot (blue arrow).</p>
</caption>
<graphic xlink:href="feart-10-892524-g003.tif"/>
</fig>
<p>PC1, PC2, and PC3 together explained 81% of the variance among all environmental factors in the snow-melt season (<xref ref-type="table" rid="T3">Table 3</xref>). PC1 was moderately correlated with PREP (<italic>r</italic> &#x3d; 0.61) and PP (<italic>r</italic> &#x3d; 0.59), PC2 was moderately correlated with DOC (<italic>r</italic> &#x3d; 0.63) and SOC (<italic>r</italic> &#x3d; &#x2212;0.69), and PC3 was strongly correlated with SOC (<italic>r</italic> &#x3d; 0.71) and moderately with NDVI (<italic>r</italic> &#x3d; 0.52) (<xref ref-type="table" rid="T3">Table 3</xref>). Due to the fact that we took accumulated solid precipitation in winter as precipitation in the snow-melt season, the positive correlation between PP and PREP illustrates higher accumulated snow in winter in permafrost regions than that in areas of seasonal frost or talik. In-stream DOC concentrations were negatively correlated with the SOC content, obviously inconsistent with those previous observations (<xref ref-type="bibr" rid="B44">Prokushkin et al., 2009</xref>; <xref ref-type="bibr" rid="B26">Kindler et al., 2011</xref>; <xref ref-type="bibr" rid="B25">Kicklighter et al., 2013</xref>). When the ground surface starts to thaw in the snow-melt season, SOC and litterfalls dominate the in-stream DOC (<xref ref-type="bibr" rid="B43">Prokushkin et al., 2010</xref>; <xref ref-type="bibr" rid="B16">Guo et al., 2018</xref>), possibly due to representativeness of sampling locations. Three components (PC1, PC2, and PC3) together (<xref ref-type="table" rid="T3">Table 3</xref>) explained 77% variance of all environmental factors in summer&#x2013;autumn. PC1 was moderately correlated with PP (<italic>r</italic> &#x3d; 0.65) and negatively correlated with NDVI (<italic>r</italic> &#x3d; &#x2212;0.57); PC2 was strongly correlated with DOC (<italic>r</italic> &#x3d; 0.71); and PC3 was strongly correlated with PREP (<italic>r</italic> &#x3d; 0.80) and moderately with SOC (<italic>r</italic> &#x3d; 0.55). PP was negatively correlated with NDVI, possibly due to warmer climate and higher NDVI in the downstream SAYR compared to alpine steppes and meadows in upstream SAYR extensively underlain by alpine permafrost. PC1, PC2, and PC3 explained 84% of the variance of environmental factors in winter (<xref ref-type="table" rid="T3">Table 3</xref>). PC1 was moderately correlated with SOC (<italic>r</italic> &#x3d; 0.57). PC2 was closely correlated with PREP (<italic>r</italic> &#x3d; 0.77) and moderately with PP (<italic>r</italic> &#x3d; 0.51). PC3 was closely correlated with DOC (<italic>r</italic> &#x3d; 0.70) and moderately with NDVI (<italic>r</italic> &#x3d; &#x2212;0.65). The negative correlation of winter DOC with NDVI demonstrates relatively higher NDVI in downstream SAYR characterized by lower winter in-stream DOC concentrations.</p>
<p>Two principal components explained 75% of the variance in environmental factors in groundwater sampling sites (<xref ref-type="table" rid="T3">Table 3</xref>). PC1 was moderately correlated with DOC (<italic>r</italic> &#x3d; 0.64) and negatively with PP (<italic>r</italic> &#x3d; 0.56). PC2 was moderately correlated with PREP (<italic>r</italic> &#x3d; &#x2212;0.66) and NDVI (<italic>r</italic> &#x3d; 0.55). The correlation of groundwater DOC with PP proves that groundwater has become an increasing source of DOC upon permafrost thaw (<xref ref-type="bibr" rid="B36">Moore, 2010</xref>). The negative correlation of PREP with NDVI disagrees with the environmental characteristics in the SAYR, likely due to specific sampling locations. PC1, PC2, and PC3 together explained 78% variations of environmental factors in lacustrine sampling sites (<xref ref-type="table" rid="T3">Table 3</xref>). PC1 was moderately correlated with PREP (<italic>r</italic> &#x3d; 0.63), PC2 was moderately correlated with SOC (r &#x3d; 0.60) and NDVI (r &#x3d; 0.57), and PC3 was negatively correlated with SOC (r &#x3d; -0.68) and moderately with NDVI (<italic>r</italic> &#x3d; 0.50) and DOC (<italic>r</italic> &#x3d; 0.50). Correlations between SOC and NDVI illustrate that a higher NDVI can accumulate more SOC. The correlation of NDVI and lacustrine DOC indicates that sampling plots with higher NDVI are likely to have higher DOC concentrations in lakes/ponds, similar to that reported in earlier studies (<xref ref-type="bibr" rid="B48">Schindler et al., 1997</xref>). However, the fact that they were negatively correlated with SOC contradicted those previous observations (<xref ref-type="bibr" rid="B8">De March et al., 1975</xref>; <xref ref-type="bibr" rid="B48">Schindler et al., 1997</xref>). This might have resulted from samples mostly collected in the up-reach SAYR and lower reaches of SAYR around the Zo&#xee;g&#xe9; wetlands, where SOC was negatively correlated with PP and lacustrine DOC. PC1 explained 38% of the variation of all aquatic samples, with important contributions of PP (<italic>r</italic> &#x3d; 0.52), PREP (<italic>r</italic> &#x3d; 0.59), and NDVI (<italic>r</italic> &#x3d; &#x2212;0.52) (<xref ref-type="table" rid="T3">Table 3</xref>). The PC2 explained 22% of the variations, correlated with SOC (<italic>r</italic> &#x3d; 0.82) and DOC (<italic>r</italic> &#x3d; &#x2212;0.52) (<xref ref-type="table" rid="T3">Table 3</xref>). SOC appeared to be grouped with PP, whereas NDVI was on the opposite side of the plot (<xref ref-type="fig" rid="F3">Figure 3</xref>), implying the positive and negative correlations between SOC and NDVI, respectively, with PP. DOC and PREP were grouped together in the down-right quadrant of the plot, indicating the positive correlation between DOC and PREP among all aquatic types. Groundwater and summer streams/rivers were clustered on the left side of the plot, while other water types showed no clear separation.</p>
</sec>
<sec id="s3-3">
<title>3.3 Potentials of DOC Decomposition in Aquatic Systems</title>
<p>Aquatic organic carbon is also an important atmospheric carbon source. A meta-analysis of results for decomposability of DOC in varied aquatic systems (e.g., rivers/streams, groundwater, lakes/ponds, and soil solutions) and seasonal rivers/streams was performed for identifying the potentials of transformation from aquatic DOC into atmospheric carbon. Combined with results of DOC concentrations of varied water types and seasonal rivers/streams in northern and other permafrost regions through the method of literature synthesis, hotspots of atmospheric carbon emission from aquatic systems were preliminarily explored (<xref ref-type="fig" rid="F4">Figure 4</xref>).</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>DOC concentrations and biodegradable DOC (BDOC) in aquatic systems in permafrost domains.<bold> (A)</bold> Seasonal distribution of in-stream DOC and BDOC (<xref ref-type="bibr" rid="B13">Finlay et al., 2006</xref>, <xref ref-type="bibr" rid="B12">2009</xref>; <xref ref-type="bibr" rid="B42">Petrone et al., 2006</xref>; <xref ref-type="bibr" rid="B17">Holmes et al., 2008</xref>; <xref ref-type="bibr" rid="B38">O&#x2019;donnell et al., 2012</xref>; <xref ref-type="bibr" rid="B63">Wickland et al., 2012</xref>; <xref ref-type="bibr" rid="B39">Olefeldt and Roulet, 2014</xref>; <xref ref-type="bibr" rid="B1">Abbott et al., 2014</xref>), and <bold>(B)</bold> DOC and BDOC in varied water types (<xref ref-type="bibr" rid="B58">Vonk et al., 2013</xref>, <xref ref-type="bibr" rid="B60">2015b</xref>; <xref ref-type="bibr" rid="B1">Abbott et al., 2014</xref>; <xref ref-type="bibr" rid="B33">Mann et al., 2015</xref>; <xref ref-type="bibr" rid="B40">Selvam et al., 2017</xref>; <xref ref-type="bibr" rid="B57">Textor et al., 2019</xref>; <xref ref-type="bibr" rid="B41">Payandi-Rolland et al., 2020</xref>); Notes: BDOC can be calculated by either incubation experiment (7&#x2013;40&#xa0;d) (<xref ref-type="bibr" rid="B17">Holmes et al., 2008</xref>; <xref ref-type="bibr" rid="B58">Vonk et al., 2013</xref>; <xref ref-type="bibr" rid="B1">Abbott et al., 2014</xref>; <xref ref-type="bibr" rid="B40">Selvam et al., 2017</xref>; <xref ref-type="bibr" rid="B57">Textor et al., 2019</xref>) or proxies of chemical compositions, for example, hydrophilic compounds as a labile fraction of DOC mineralization (<xref ref-type="bibr" rid="B38">O&#x27;Donnell et al., 2012</xref>) and tyrosine- and tryptophan-like fluorophores (<xref ref-type="bibr" rid="B13">Finlay et al., 2006</xref>; <xref ref-type="bibr" rid="B15">Guo and Macdonald, 2006</xref>; <xref ref-type="bibr" rid="B42">Petrone et al., 2006</xref>; <xref ref-type="bibr" rid="B2">Balcarczyk et al., 2009</xref>).</p>
</caption>
<graphic xlink:href="feart-10-892524-g004.tif"/>
</fig>
<p>The ranges of in-stream DOC concentrations are similar in the snow-melt season (2.4&#x2013;33.6&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and summer&#x2013;autumn (6&#x2013;44.0&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) across 10 sampling sites, in the Yukon River Basin and northeastern Siberia (<xref ref-type="bibr" rid="B13">Finlay et al., 2006</xref>, <xref ref-type="bibr" rid="B12">2009</xref>; <xref ref-type="bibr" rid="B15">Guo and Macdonald, 2006</xref>; <xref ref-type="bibr" rid="B42">Petrone et al., 2006</xref>; <xref ref-type="bibr" rid="B39">Olefeldt and Roulet, 2014</xref>) (<xref ref-type="fig" rid="F4">Figure 4A</xref>). In the SAYR, ranges of in-stream DOC concentrations in the snow-melt season (0.1&#x2013;25.4&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and summer/autumn (0.5&#x2013;21.0&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) fell in the existing ranges. In-stream biodegradable DOC (BDOC) in the snow-melt season is 20&#x2013;40% (<xref ref-type="bibr" rid="B1">Abbott et al., 2014</xref>), yet in-stream BDOC in summer&#x2013;autumn is much smaller ranging from 1 to 10% (<xref ref-type="bibr" rid="B63">Wickland et al., 2012</xref>) (<xref ref-type="fig" rid="F4">Figure 4A</xref>). In-stream DOC concentrations in winter range from 1 to 20&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>, relatively lower than those in both the snow-melt seasons and summer&#x2013;autumn (<xref ref-type="bibr" rid="B38">O&#x2019;Donnell et al., 2012</xref>) (<xref ref-type="fig" rid="F4">Figure 4A</xref>). Winter in-stream DOC concentrations in the SAYR ranged from 0.5 to 1.5&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup> were also smaller than those in other seasons. In the winter season, in-stream BDOC reported across the Yukon River Basin ranges from 10 to 53%, higher than in-stream BDOC in other seasons (<xref ref-type="bibr" rid="B38">O&#x27;Donnell et al., 2012</xref>; <xref ref-type="bibr" rid="B63">Wickland et al., 2012</xref>) (<xref ref-type="fig" rid="F4">Figure 4A</xref>). Thus, in-stream BDOC in the spring snow-melt season and winter with relatively higher DOC concentrations or BDOC are potentially important sources of atmospheric carbon emissions from aquatic systems. DOC concentrations in different water types have shown featured distributions. The ranges of DOC concentrations are the lowest in groundwater (0.5&#x2013;3.9&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>), and the highest in ground-ice melt-water (48&#x2013;1,548&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) (<xref ref-type="bibr" rid="B31">Ma et al., 2019b</xref>) (<xref ref-type="fig" rid="F4">Figure 4B</xref>). DOC ranges in lakes/ponds (0.5&#x2013;49&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) are generally higher than those in rivers/streams (1&#x2013;32&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and soil solutions (2&#x2013;30&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) (<xref ref-type="bibr" rid="B1">Abbott et al., 2014</xref>; <xref ref-type="bibr" rid="B31">Ma et al., 2019b</xref>). The distributive features of aquatic DOC in the SAYR are consistent with existing and latest research results. Correspondingly, the BDOC of ground-ice meltwater is the highest among all water types (23&#x2013;71%), followed by lakes/ponds (1&#x2013;71%), rivers/streams (1&#x2013;40%), and soil solutions (0&#x2013;10%) (<xref ref-type="bibr" rid="B33">Mann et al., 2015</xref>; <xref ref-type="bibr" rid="B41">Payandi-Rolland et al., 2020</xref>; <xref ref-type="bibr" rid="B40">Selvam et al., 2017</xref>; <xref ref-type="bibr" rid="B57">Textor et al., 2019</xref>; <xref ref-type="bibr" rid="B58">Vonk et al., 2013</xref>, <xref ref-type="bibr" rid="B60">2015b</xref>) (<xref ref-type="fig" rid="F4">Figure 4B</xref>). Therefore, DOC associated with ground-ice melt-water, lakes/ponds, and rivers/streams are relatively labile and potentially a major atmospheric carbon source among other aquatic water types in permafrost regions.</p>
</sec>
</sec>
<sec id="s4">
<title>4 Conclusion</title>
<p>In permafrost regions, aquatic systems are important pathways of carbon cycling, and potentially acted as major atmospheric carbon sources. DOC concentrations in aquatic systems show strong variations among individual water types in the SAYR. Permafrost-related water types show higher DOC concentrations (ground-ice meltwater, 32.94&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>; supra-permafrost water, 20.54 &#xb1; 3.6&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>; and sub-permafrost water, 16.8 &#xb1; 1.2&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) than other water types (lakes/ponds, 21.3 &#xb1; 34.1&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>; rivers/streams, 4.3 &#xb1; 3.7&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>; and groundwater, 1.8 &#xb1; 1.4&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>). Seasonal features of in-stream DOC concentrations were characterized by declining features in 2016 (snow-melt season: 4.5 &#xb1; 2.2&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup> &#x3e; summer&#x2013;autumn: 2.4 &#xb1; 3.7&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup> &#x3e; winter: 0.8 &#xb1; 0.6&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and the greatest in-stream DOC concentrations (7.0 &#xb1; 4.8&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) in summer&#x2013;autumn, and they decreased in the spring snow-melt season (3.6 &#xb1; 6.0&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) and winter (1.1 &#xb1; 0.5&#xa0;mg&#xa0;C&#xb7;L<sup>&#x2212;1</sup>) in 2017, and they were associated with intra-annual variations in precipitation modes. Aquatic DOC concentrations and their ranges in the SAYR are consistent with those observed in northern permafrost regions and other QTP sub-basins. PP, PREP, and NDVI explained 38% variance of environmental variables in aquatic DOC distribution in the SAYR, and the PCA analysis reveals that the presence of permafrost is correlated with groundwater DOC, which suggests that groundwater is becoming an additional source of DOC with progressive permafrost thaw in the SAYR. Relatively higher in-stream DOC concentrations in the snow-melt season and winter in combination with higher BDOC and higher DOC concentrations in ground-ice meltwater, lakes/ponds, and rivers/streams are potentially major sources of atmospheric carbon emission from aquatic systems in the SAYR.</p>
</sec>
</body>
<back>
<sec id="s5">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s6">
<title>Author Contributions</title>
<p>Conceptualization, QM and HJ; methodology, QM; software, RS and SM; validation, YY and SL; formal analysis, QM; investigation, DL, YH, XL, and SG; resources, HJ and QW; data curation, QM; writing&#x2014;original draft preparation, QM; writing&#x2014;review and editing, HJ; visualization, QM; supervision, project funding, and administration, HJ and QW. All authors have read and agreed to the published version of the manuscript.</p>
</sec>
<sec id="s7">
<title>Funding</title>
<p>This work was funded by the Chinese Academy of Sciences (CAS) Strategic Priority Research Program (Grant No. XDA20100103) and Consulting Project of Ministry of Natural Resources &#x201c;Impacts of shrinking glaciers and degrading permafrost on ecosystems, Yellow River discharge and carbon sources and sinks in the Source Area of Yellow River on northeastern Qinghai&#x2013;Tibet Plateau, China.&#x201d; The article processing charges (APC) are funded by the CAS Strategic Priority Research Program (Grant No. XDA20100103).</p>
</sec>
<sec sec-type="COI-statement" id="s8">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s9">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<ack>
<p>The authors would like to express the sincere gratitude to the five unidentified reviewers for their kind comments and generous efforts in reviewing and improving the manuscript.</p>
</ack>
<sec id="s12">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/feart.2022.892524/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/feart.2022.892524/full&#x23;supplementary-material</ext-link>.</p>
<supplementary-material xlink:href="Table1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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