Applying Multi-Sensor Satellite Data to Identify Key Natural Factors in Annual Livestock Change and Winter Livestock Disaster (<i>Dzud</i>) in Mongolian Nomadic Pasturelands

In the present study, we tested the applicability of multi-sensor satellite data to account for key natural factors of annual livestock number changes in county-level <i>soum</i> districts of Mongolia. A schematic model of nomadic landscapes was developed and used to select potential dri...

Full description

Saved in:
Bibliographic Details
Main Authors: Sinkyu Kang, Nanghyun Cho, Amartuvshin Narantsetseg, Bolor-Erdene Lkhamsuren, Otgon Khongorzul, Tumendemberel Tegshdelger, Bumsuk Seo, Keunchang Jang
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Land
Subjects:
Online Access:https://www.mdpi.com/2073-445X/13/3/391
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850225449114796032
author Sinkyu Kang
Nanghyun Cho
Amartuvshin Narantsetseg
Bolor-Erdene Lkhamsuren
Otgon Khongorzul
Tumendemberel Tegshdelger
Bumsuk Seo
Keunchang Jang
author_facet Sinkyu Kang
Nanghyun Cho
Amartuvshin Narantsetseg
Bolor-Erdene Lkhamsuren
Otgon Khongorzul
Tumendemberel Tegshdelger
Bumsuk Seo
Keunchang Jang
author_sort Sinkyu Kang
collection DOAJ
description In the present study, we tested the applicability of multi-sensor satellite data to account for key natural factors of annual livestock number changes in county-level <i>soum</i> districts of Mongolia. A schematic model of nomadic landscapes was developed and used to select potential drivers retrievable from multi-sensor satellite data. Three alternative methods (principal component analysis, PCA; stepwise multiple regression, SMR; and random forest machine learning model, RF) were used to determine the key drivers for livestock changes and <i>Dzud</i> outbreaks. The countrywide <i>Dzud</i> in 2010 was well-characterized by the PCA as cold with a snowy winter and low summer foraging biomass. The RF estimated the annual livestock change with high accuracy (R<sup>2</sup> > 0.9 in most <i>soums</i>). The SMR was less accurate but provided better intuitive insights on the regionality of the key factors and its relationships with local climate and <i>Dzud</i> characteristics. Summer and winter variables appeared to be almost equally important in both models. The primary factors of livestock change and <i>Dzud</i> showed regional patterns: dryness in the south, temperature in the north, and foraging resource in the central and western regions. This study demonstrates a synergistic potential of models and satellite data to understand climate–vegetation–livestock interactions in Mongolian nomadic pastures.
format Article
id doaj-art-a149d82bd2f14cbda213bfcb88e621b9
institution OA Journals
issn 2073-445X
language English
publishDate 2024-03-01
publisher MDPI AG
record_format Article
series Land
spelling doaj-art-a149d82bd2f14cbda213bfcb88e621b92025-08-20T02:05:21ZengMDPI AGLand2073-445X2024-03-0113339110.3390/land13030391Applying Multi-Sensor Satellite Data to Identify Key Natural Factors in Annual Livestock Change and Winter Livestock Disaster (<i>Dzud</i>) in Mongolian Nomadic PasturelandsSinkyu Kang0Nanghyun Cho1Amartuvshin Narantsetseg2Bolor-Erdene Lkhamsuren3Otgon Khongorzul4Tumendemberel Tegshdelger5Bumsuk Seo6Keunchang Jang7Department of Environmental Science, Kangwon National University, Chuncheon 24341, Republic of KoreaDepartment of Environmental Science, Kangwon National University, Chuncheon 24341, Republic of KoreaBotanic Garden and Research Institute, Mongolian Academy of Sciences, Ulaanbaatar 13330, MongoliaDepartment of Environmental Science, Kangwon National University, Chuncheon 24341, Republic of KoreaDepartment of Environmental Science, Kangwon National University, Chuncheon 24341, Republic of KoreaDepartment of Environmental Science, Kangwon National University, Chuncheon 24341, Republic of KoreaDepartment of Environmental Science, Kangwon National University, Chuncheon 24341, Republic of KoreaForest Environment and Conservation Department, National Institute of Forest Science, Seoul 02455, Republic of KoreaIn the present study, we tested the applicability of multi-sensor satellite data to account for key natural factors of annual livestock number changes in county-level <i>soum</i> districts of Mongolia. A schematic model of nomadic landscapes was developed and used to select potential drivers retrievable from multi-sensor satellite data. Three alternative methods (principal component analysis, PCA; stepwise multiple regression, SMR; and random forest machine learning model, RF) were used to determine the key drivers for livestock changes and <i>Dzud</i> outbreaks. The countrywide <i>Dzud</i> in 2010 was well-characterized by the PCA as cold with a snowy winter and low summer foraging biomass. The RF estimated the annual livestock change with high accuracy (R<sup>2</sup> > 0.9 in most <i>soums</i>). The SMR was less accurate but provided better intuitive insights on the regionality of the key factors and its relationships with local climate and <i>Dzud</i> characteristics. Summer and winter variables appeared to be almost equally important in both models. The primary factors of livestock change and <i>Dzud</i> showed regional patterns: dryness in the south, temperature in the north, and foraging resource in the central and western regions. This study demonstrates a synergistic potential of models and satellite data to understand climate–vegetation–livestock interactions in Mongolian nomadic pastures.https://www.mdpi.com/2073-445X/13/3/391livestock changenatural factormulti-sensor satellite datamultivariate analysismachine learning
spellingShingle Sinkyu Kang
Nanghyun Cho
Amartuvshin Narantsetseg
Bolor-Erdene Lkhamsuren
Otgon Khongorzul
Tumendemberel Tegshdelger
Bumsuk Seo
Keunchang Jang
Applying Multi-Sensor Satellite Data to Identify Key Natural Factors in Annual Livestock Change and Winter Livestock Disaster (<i>Dzud</i>) in Mongolian Nomadic Pasturelands
Land
livestock change
natural factor
multi-sensor satellite data
multivariate analysis
machine learning
title Applying Multi-Sensor Satellite Data to Identify Key Natural Factors in Annual Livestock Change and Winter Livestock Disaster (<i>Dzud</i>) in Mongolian Nomadic Pasturelands
title_full Applying Multi-Sensor Satellite Data to Identify Key Natural Factors in Annual Livestock Change and Winter Livestock Disaster (<i>Dzud</i>) in Mongolian Nomadic Pasturelands
title_fullStr Applying Multi-Sensor Satellite Data to Identify Key Natural Factors in Annual Livestock Change and Winter Livestock Disaster (<i>Dzud</i>) in Mongolian Nomadic Pasturelands
title_full_unstemmed Applying Multi-Sensor Satellite Data to Identify Key Natural Factors in Annual Livestock Change and Winter Livestock Disaster (<i>Dzud</i>) in Mongolian Nomadic Pasturelands
title_short Applying Multi-Sensor Satellite Data to Identify Key Natural Factors in Annual Livestock Change and Winter Livestock Disaster (<i>Dzud</i>) in Mongolian Nomadic Pasturelands
title_sort applying multi sensor satellite data to identify key natural factors in annual livestock change and winter livestock disaster i dzud i in mongolian nomadic pasturelands
topic livestock change
natural factor
multi-sensor satellite data
multivariate analysis
machine learning
url https://www.mdpi.com/2073-445X/13/3/391
work_keys_str_mv AT sinkyukang applyingmultisensorsatellitedatatoidentifykeynaturalfactorsinannuallivestockchangeandwinterlivestockdisasteridzudiinmongoliannomadicpasturelands
AT nanghyuncho applyingmultisensorsatellitedatatoidentifykeynaturalfactorsinannuallivestockchangeandwinterlivestockdisasteridzudiinmongoliannomadicpasturelands
AT amartuvshinnarantsetseg applyingmultisensorsatellitedatatoidentifykeynaturalfactorsinannuallivestockchangeandwinterlivestockdisasteridzudiinmongoliannomadicpasturelands
AT bolorerdenelkhamsuren applyingmultisensorsatellitedatatoidentifykeynaturalfactorsinannuallivestockchangeandwinterlivestockdisasteridzudiinmongoliannomadicpasturelands
AT otgonkhongorzul applyingmultisensorsatellitedatatoidentifykeynaturalfactorsinannuallivestockchangeandwinterlivestockdisasteridzudiinmongoliannomadicpasturelands
AT tumendembereltegshdelger applyingmultisensorsatellitedatatoidentifykeynaturalfactorsinannuallivestockchangeandwinterlivestockdisasteridzudiinmongoliannomadicpasturelands
AT bumsukseo applyingmultisensorsatellitedatatoidentifykeynaturalfactorsinannuallivestockchangeandwinterlivestockdisasteridzudiinmongoliannomadicpasturelands
AT keunchangjang applyingmultisensorsatellitedatatoidentifykeynaturalfactorsinannuallivestockchangeandwinterlivestockdisasteridzudiinmongoliannomadicpasturelands