Loading…

Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion

As the climate warms, the Arctic permafrost region has undergone widespread vegetation changes, exhibiting overall greening trends but with spatial heterogeneity. This study investigates an underexamined mechanism driving heterogeneous greening patterns, thermokarst lake drainage, which creates drai...

Full description

Saved in:
Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2023-09, Vol.15 (18), p.4561
Main Authors: Liu, Aobo, Chen, Yating, Cheng, Xiao
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c359t-26149be9ec95a725bc38b2bafd1338777de45edebb43403d795bbdb0b40a66c13
container_end_page
container_issue 18
container_start_page 4561
container_title Remote sensing (Basel, Switzerland)
container_volume 15
creator Liu, Aobo
Chen, Yating
Cheng, Xiao
description As the climate warms, the Arctic permafrost region has undergone widespread vegetation changes, exhibiting overall greening trends but with spatial heterogeneity. This study investigates an underexamined mechanism driving heterogeneous greening patterns, thermokarst lake drainage, which creates drained lake basins (DLBs) that represent localized greening hotspots. Focusing on the Yamal–Gydan region in Siberia, we detect 2712 lakes that have drained during the period of 2000–2020, using Landsat time-series imagery and an automated change detection algorithm. Vegetation changes in the DLBs and the entire study area were quantified through NDVI trend analysis. Additionally, a machine learning model was employed to correlate NDVI trajectories in the DLBs with environmental drivers. We find that DLBs provide ideal conditions for plant colonization, with greenness levels reaching or exceeding those of the surrounding vegetation within about five years. The greening trend in DLBs is 8.4 times the regional average, thus contributing disproportionately despite their small area share. Number of years since lake drainage, annual soil temperature, latitude, air temperature trends, and summer precipitation emerged as key factors influencing DLB greening. Our study highlights lake drainage and subsequent vegetation growth as an important fine-scale process augmenting regional greening signals. Quantifying these dynamics is critical for assessing climate impacts on regional vegetation change.
doi_str_mv 10.3390/rs15184561
format article
fullrecord <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_5ec98faaff104d2d9c33de7108904089</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A780020925</galeid><doaj_id>oai_doaj_org_article_5ec98faaff104d2d9c33de7108904089</doaj_id><sourcerecordid>A780020925</sourcerecordid><originalsourceid>FETCH-LOGICAL-c359t-26149be9ec95a725bc38b2bafd1338777de45edebb43403d795bbdb0b40a66c13</originalsourceid><addsrcrecordid>eNpNUc1uFDEMHiEqUZVeeIJI3JC25HdmcqzKslRaicu2Uk-RkzjT7E9SktlDOfEOvCFPQmARYEu29enzZ8vuujeMXgmh6ftSmWKjVD170Z1zOvCF5Jq__K9-1V3WuqXNhGCayvNutwwB3VxJDmTziOWQd1DqTNawQ_KhQEwwIcmJrLODffyKntzjhDPMsYGrgphimkhMZH5E8gAH2P_49n317CGRzTH5AmTpcsGp0V93ZwH2FS__5Ivu7uNyc_Npsf68ur25Xi-cUHpe8J5JbVGj0woGrqwTo-UWgmdCjMMweJQKPVorhaTCD1pZ6y21kkLfOyYuutuTrs-wNU8lHqA8mwzR_AZymQyUObo9GtWGjAEgBEal5147ITwOjI7tOi00rbcnraeSvxyxzmabjyW19Q0fe903pugb6-rEmqCJxhTyXMA193iILicMseHXw0gpp5qr1vDu1OBKrrVg-Lsmo-bXM82_Z4qfsTqR0g</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2869610836</pqid></control><display><type>article</type><title>Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion</title><source>Publicly Available Content Database</source><creator>Liu, Aobo ; Chen, Yating ; Cheng, Xiao</creator><creatorcontrib>Liu, Aobo ; Chen, Yating ; Cheng, Xiao</creatorcontrib><description>As the climate warms, the Arctic permafrost region has undergone widespread vegetation changes, exhibiting overall greening trends but with spatial heterogeneity. This study investigates an underexamined mechanism driving heterogeneous greening patterns, thermokarst lake drainage, which creates drained lake basins (DLBs) that represent localized greening hotspots. Focusing on the Yamal–Gydan region in Siberia, we detect 2712 lakes that have drained during the period of 2000–2020, using Landsat time-series imagery and an automated change detection algorithm. Vegetation changes in the DLBs and the entire study area were quantified through NDVI trend analysis. Additionally, a machine learning model was employed to correlate NDVI trajectories in the DLBs with environmental drivers. We find that DLBs provide ideal conditions for plant colonization, with greenness levels reaching or exceeding those of the surrounding vegetation within about five years. The greening trend in DLBs is 8.4 times the regional average, thus contributing disproportionately despite their small area share. Number of years since lake drainage, annual soil temperature, latitude, air temperature trends, and summer precipitation emerged as key factors influencing DLB greening. Our study highlights lake drainage and subsequent vegetation growth as an important fine-scale process augmenting regional greening signals. Quantifying these dynamics is critical for assessing climate impacts on regional vegetation change.</description><identifier>ISSN: 2072-4292</identifier><identifier>EISSN: 2072-4292</identifier><identifier>DOI: 10.3390/rs15184561</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Air temperature ; Algorithms ; Arctic greening ; Basins ; Carbon ; Change detection ; Climate ; Climate change ; Drainage ; Drainage basins ; drained lake basins ; Earth resources technology satellites ; Environmental assessment ; Greening ; Heterogeneity ; Hydrology ; Lake basins ; Lakes ; Land area ; Landsat ; Landsat satellites ; Machine learning ; Marginal seas ; Permafrost ; Quantitative analysis ; Regions ; Remote sensing ; Rivers ; Satellite imagery ; Sediments ; Soil erosion ; Soil temperature ; Spatial heterogeneity ; Surface water ; Sustainable living ; Taiga &amp; tundra ; Topography ; Trend analysis ; Trends ; Tundra ; Vegetation ; Vegetation changes ; Vegetation growth ; Yamal–Gydan tundra ecoregion</subject><ispartof>Remote sensing (Basel, Switzerland), 2023-09, Vol.15 (18), p.4561</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c359t-26149be9ec95a725bc38b2bafd1338777de45edebb43403d795bbdb0b40a66c13</cites><orcidid>0000-0001-8912-8729 ; 0000-0001-6910-6565</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2869610836/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2869610836?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Liu, Aobo</creatorcontrib><creatorcontrib>Chen, Yating</creatorcontrib><creatorcontrib>Cheng, Xiao</creatorcontrib><title>Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion</title><title>Remote sensing (Basel, Switzerland)</title><description>As the climate warms, the Arctic permafrost region has undergone widespread vegetation changes, exhibiting overall greening trends but with spatial heterogeneity. This study investigates an underexamined mechanism driving heterogeneous greening patterns, thermokarst lake drainage, which creates drained lake basins (DLBs) that represent localized greening hotspots. Focusing on the Yamal–Gydan region in Siberia, we detect 2712 lakes that have drained during the period of 2000–2020, using Landsat time-series imagery and an automated change detection algorithm. Vegetation changes in the DLBs and the entire study area were quantified through NDVI trend analysis. Additionally, a machine learning model was employed to correlate NDVI trajectories in the DLBs with environmental drivers. We find that DLBs provide ideal conditions for plant colonization, with greenness levels reaching or exceeding those of the surrounding vegetation within about five years. The greening trend in DLBs is 8.4 times the regional average, thus contributing disproportionately despite their small area share. Number of years since lake drainage, annual soil temperature, latitude, air temperature trends, and summer precipitation emerged as key factors influencing DLB greening. Our study highlights lake drainage and subsequent vegetation growth as an important fine-scale process augmenting regional greening signals. Quantifying these dynamics is critical for assessing climate impacts on regional vegetation change.</description><subject>Air temperature</subject><subject>Algorithms</subject><subject>Arctic greening</subject><subject>Basins</subject><subject>Carbon</subject><subject>Change detection</subject><subject>Climate</subject><subject>Climate change</subject><subject>Drainage</subject><subject>Drainage basins</subject><subject>drained lake basins</subject><subject>Earth resources technology satellites</subject><subject>Environmental assessment</subject><subject>Greening</subject><subject>Heterogeneity</subject><subject>Hydrology</subject><subject>Lake basins</subject><subject>Lakes</subject><subject>Land area</subject><subject>Landsat</subject><subject>Landsat satellites</subject><subject>Machine learning</subject><subject>Marginal seas</subject><subject>Permafrost</subject><subject>Quantitative analysis</subject><subject>Regions</subject><subject>Remote sensing</subject><subject>Rivers</subject><subject>Satellite imagery</subject><subject>Sediments</subject><subject>Soil erosion</subject><subject>Soil temperature</subject><subject>Spatial heterogeneity</subject><subject>Surface water</subject><subject>Sustainable living</subject><subject>Taiga &amp; tundra</subject><subject>Topography</subject><subject>Trend analysis</subject><subject>Trends</subject><subject>Tundra</subject><subject>Vegetation</subject><subject>Vegetation changes</subject><subject>Vegetation growth</subject><subject>Yamal–Gydan tundra ecoregion</subject><issn>2072-4292</issn><issn>2072-4292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNUc1uFDEMHiEqUZVeeIJI3JC25HdmcqzKslRaicu2Uk-RkzjT7E9SktlDOfEOvCFPQmARYEu29enzZ8vuujeMXgmh6ftSmWKjVD170Z1zOvCF5Jq__K9-1V3WuqXNhGCayvNutwwB3VxJDmTziOWQd1DqTNawQ_KhQEwwIcmJrLODffyKntzjhDPMsYGrgphimkhMZH5E8gAH2P_49n317CGRzTH5AmTpcsGp0V93ZwH2FS__5Ivu7uNyc_Npsf68ur25Xi-cUHpe8J5JbVGj0woGrqwTo-UWgmdCjMMweJQKPVorhaTCD1pZ6y21kkLfOyYuutuTrs-wNU8lHqA8mwzR_AZymQyUObo9GtWGjAEgBEal5147ITwOjI7tOi00rbcnraeSvxyxzmabjyW19Q0fe903pugb6-rEmqCJxhTyXMA193iILicMseHXw0gpp5qr1vDu1OBKrrVg-Lsmo-bXM82_Z4qfsTqR0g</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Liu, Aobo</creator><creator>Chen, Yating</creator><creator>Cheng, Xiao</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7QR</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-8912-8729</orcidid><orcidid>https://orcid.org/0000-0001-6910-6565</orcidid></search><sort><creationdate>20230901</creationdate><title>Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion</title><author>Liu, Aobo ; Chen, Yating ; Cheng, Xiao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-26149be9ec95a725bc38b2bafd1338777de45edebb43403d795bbdb0b40a66c13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Air temperature</topic><topic>Algorithms</topic><topic>Arctic greening</topic><topic>Basins</topic><topic>Carbon</topic><topic>Change detection</topic><topic>Climate</topic><topic>Climate change</topic><topic>Drainage</topic><topic>Drainage basins</topic><topic>drained lake basins</topic><topic>Earth resources technology satellites</topic><topic>Environmental assessment</topic><topic>Greening</topic><topic>Heterogeneity</topic><topic>Hydrology</topic><topic>Lake basins</topic><topic>Lakes</topic><topic>Land area</topic><topic>Landsat</topic><topic>Landsat satellites</topic><topic>Machine learning</topic><topic>Marginal seas</topic><topic>Permafrost</topic><topic>Quantitative analysis</topic><topic>Regions</topic><topic>Remote sensing</topic><topic>Rivers</topic><topic>Satellite imagery</topic><topic>Sediments</topic><topic>Soil erosion</topic><topic>Soil temperature</topic><topic>Spatial heterogeneity</topic><topic>Surface water</topic><topic>Sustainable living</topic><topic>Taiga &amp; tundra</topic><topic>Topography</topic><topic>Trend analysis</topic><topic>Trends</topic><topic>Tundra</topic><topic>Vegetation</topic><topic>Vegetation changes</topic><topic>Vegetation growth</topic><topic>Yamal–Gydan tundra ecoregion</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Aobo</creatorcontrib><creatorcontrib>Chen, Yating</creatorcontrib><creatorcontrib>Cheng, Xiao</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Engineering Database</collection><collection>ProQuest advanced technologies &amp; aerospace journals</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>Directory of Open Access Journals(OpenAccess)</collection><jtitle>Remote sensing (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Aobo</au><au>Chen, Yating</au><au>Cheng, Xiao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion</atitle><jtitle>Remote sensing (Basel, Switzerland)</jtitle><date>2023-09-01</date><risdate>2023</risdate><volume>15</volume><issue>18</issue><spage>4561</spage><pages>4561-</pages><issn>2072-4292</issn><eissn>2072-4292</eissn><abstract>As the climate warms, the Arctic permafrost region has undergone widespread vegetation changes, exhibiting overall greening trends but with spatial heterogeneity. This study investigates an underexamined mechanism driving heterogeneous greening patterns, thermokarst lake drainage, which creates drained lake basins (DLBs) that represent localized greening hotspots. Focusing on the Yamal–Gydan region in Siberia, we detect 2712 lakes that have drained during the period of 2000–2020, using Landsat time-series imagery and an automated change detection algorithm. Vegetation changes in the DLBs and the entire study area were quantified through NDVI trend analysis. Additionally, a machine learning model was employed to correlate NDVI trajectories in the DLBs with environmental drivers. We find that DLBs provide ideal conditions for plant colonization, with greenness levels reaching or exceeding those of the surrounding vegetation within about five years. The greening trend in DLBs is 8.4 times the regional average, thus contributing disproportionately despite their small area share. Number of years since lake drainage, annual soil temperature, latitude, air temperature trends, and summer precipitation emerged as key factors influencing DLB greening. Our study highlights lake drainage and subsequent vegetation growth as an important fine-scale process augmenting regional greening signals. Quantifying these dynamics is critical for assessing climate impacts on regional vegetation change.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/rs15184561</doi><orcidid>https://orcid.org/0000-0001-8912-8729</orcidid><orcidid>https://orcid.org/0000-0001-6910-6565</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2072-4292
ispartof Remote sensing (Basel, Switzerland), 2023-09, Vol.15 (18), p.4561
issn 2072-4292
2072-4292
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_5ec98faaff104d2d9c33de7108904089
source Publicly Available Content Database
subjects Air temperature
Algorithms
Arctic greening
Basins
Carbon
Change detection
Climate
Climate change
Drainage
Drainage basins
drained lake basins
Earth resources technology satellites
Environmental assessment
Greening
Heterogeneity
Hydrology
Lake basins
Lakes
Land area
Landsat
Landsat satellites
Machine learning
Marginal seas
Permafrost
Quantitative analysis
Regions
Remote sensing
Rivers
Satellite imagery
Sediments
Soil erosion
Soil temperature
Spatial heterogeneity
Surface water
Sustainable living
Taiga & tundra
Topography
Trend analysis
Trends
Tundra
Vegetation
Vegetation changes
Vegetation growth
Yamal–Gydan tundra ecoregion
title Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T06%3A49%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Effects%20of%20Thermokarst%20Lake%20Drainage%20on%20Localized%20Vegetation%20Greening%20in%20the%20Yamal%E2%80%93Gydan%20Tundra%20Ecoregion&rft.jtitle=Remote%20sensing%20(Basel,%20Switzerland)&rft.au=Liu,%20Aobo&rft.date=2023-09-01&rft.volume=15&rft.issue=18&rft.spage=4561&rft.pages=4561-&rft.issn=2072-4292&rft.eissn=2072-4292&rft_id=info:doi/10.3390/rs15184561&rft_dat=%3Cgale_doaj_%3EA780020925%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c359t-26149be9ec95a725bc38b2bafd1338777de45edebb43403d795bbdb0b40a66c13%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2869610836&rft_id=info:pmid/&rft_galeid=A780020925&rfr_iscdi=true