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Role of Surface Melt and Icing Events in Livestock Mortality across Mongolia’s Semi-Arid Landscape. REMOTE SENSING 2019. [DOI: 10.3390/rs11202392] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Livestock production is a socioeconomic linchpin in Mongolia and is affected by large-scale livestock die-offs. Colloquially known as dzuds, these die-offs are driven by anomalous climatic events, including extreme cold temperatures, extended snow cover duration (SCD) and drought. As average temperatures across Mongolia have increased at roughly twice the global rate, we hypothesized that increasing cold season surface melt including soil freeze/thaw (FT), snowmelt, and icing events associated with regional warming have become increasingly important drivers of dzud events as they can reduce pasture productivity and inhibit access to grazing. Here, we use daily brightness temperature (Tb) observations to identify anomalous surface melt and icing events across Mongolia from 2003–2016 and their contribution to dzuds relative to other climatic drivers, including winter temperatures, SCD, and drought. We find a positive relationship between surface melt and icing events and livestock mortality during the fall in southern Mongolia and during the spring in the central and western regions. Further, anomalous seasonal surface melt and icing events explain 17–34% of the total variance in annual livestock mortality, with cold temperatures as the leading contributor of dzuds (20–37%). Summer drought showed the greatest explanatory power (43%) but overall had less statistically significant relationships relative to winter temperatures. Our results indicate that surface melt and icing events will become an increasingly important driver of dzuds as annual temperatures and livestock populations are projected to increase in Mongolia.
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Bokhorst S, Pedersen SH, Brucker L, Anisimov O, Bjerke JW, Brown RD, Ehrich D, Essery RLH, Heilig A, Ingvander S, Johansson C, Johansson M, Jónsdóttir IS, Inga N, Luojus K, Macelloni G, Mariash H, McLennan D, Rosqvist GN, Sato A, Savela H, Schneebeli M, Sokolov A, Sokratov SA, Terzago S, Vikhamar-Schuler D, Williamson S, Qiu Y, Callaghan TV. Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts. AMBIO 2016; 45:516-37. [PMID: 26984258 PMCID: PMC4980315 DOI: 10.1007/s13280-016-0770-0] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Revised: 11/03/2015] [Accepted: 02/05/2016] [Indexed: 05/07/2023]
Abstract
Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.
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Affiliation(s)
- Stef Bokhorst
- FRAM – High North Research Centre on Climate and the Environment, Norwegian Institute for Nature Research (NINA), PO Box 6606, Langnes, 9296 Tromsø Norway
- Department of Ecological Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands
| | - Stine Højlund Pedersen
- Department of Bioscience, Arctic Research Centre, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark
| | - Ludovic Brucker
- NASA GSFC Cryospheric Sciences Laboratory, Code 615, Greenbelt, MD 20771 USA
- Goddard Earth Sciences Technology and Research Studies and Investigations, Universities Space Research Association, Columbia, MD 21044 USA
| | - Oleg Anisimov
- State Hydrological Institute of Roshydromet, 23 Second Line V.O., St.Petersburg, Russia 199053
- International Centre for Science and Education “Best”, North-East Federal University, Yakutsk, Russia
| | - Jarle W. Bjerke
- FRAM – High North Research Centre on Climate and the Environment, Norwegian Institute for Nature Research (NINA), PO Box 6606, Langnes, 9296 Tromsø Norway
| | - Ross D. Brown
- Climate Research Division, Environment Canada Ouranos, 550 Sherbrooke St. West, 19th Floor, Montreal, QC H3A 1B9 Canada
| | - Dorothee Ehrich
- Department of Arctic and Marine Biology, University of Tromsø, 9037 Tromsø, Norway
| | | | - Achim Heilig
- Institute of Environmental Physics, University of Heidelberg, Im Neuenheimer Feld 229, 69120 Heidelberg, Germany
| | - Susanne Ingvander
- Department of Physical Geography, Stockholm University, 106 91 Stockholm, Sweden
| | - Cecilia Johansson
- Department of Earth Sciences, Uppsala University, Villavägen 16, 75236 Uppsala, Sweden
| | - Margareta Johansson
- Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62 Lund, Sweden
- Royal Swedish Academy of Sciences, PO Box 50005, 104 05 Stockholm, Sweden
| | - Ingibjörg Svala Jónsdóttir
- University Centre in Svalbard, PO Box 156, 9171 Longyearbyen, Norway
- Faculty of Life- and Environmental Sciences, University of Iceland, Sturlugata 7, 101 Reykjavík, Iceland
| | - Niila Inga
- Leavas Sámi Community, Box 53, 981 21 Kiruna, Sweden
| | - Kari Luojus
- Arctic Research, Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
| | - Giovanni Macelloni
- IFAC-CNR - Institute of Applied Physics “Nello Carrara”, National Research Council, Via Madonna del Piano 10, 50019 Sesto Fiorentino, FI Italy
| | - Heather Mariash
- National Wildlife Research Centre, Environment Canada, 1125 Colonel By Drive, Ottawa, K1A 0H3 Canada
| | - Donald McLennan
- Canadian High Arctic Research Station (CHARS), 360 Albert Street, Suite 1710, Ottawa, ON K1R 7X7 Canada
| | - Gunhild Ninis Rosqvist
- Department of Physical Geography, Stockholm University, 106 91 Stockholm, Sweden
- Department of Earth Sciences, University of Bergen, 5020 Bergen, Norway
| | - Atsushi Sato
- Snow and Ice Research Center, National Research Institute for Earth Science and Disaster Prevention, 187-16 Suyoshi, Nagaoka, Niigata 940-0821 Japan
| | - Hannele Savela
- Thule Insitute, University of Oulu, PO Box 7300, 90014 Oulu, Finland
| | - Martin Schneebeli
- WSL Institute for Snow and Avalanche Research SLF, Flüelastrasse 11, 7260 Davos Dorf, Switzerland
| | - Aleksandr Sokolov
- Arctic Research Station of Institute of Plant and Animal Ecology, Ural Branch, Russian Academy of Sciences, Labytnangi, Russia 629400
- Science Center for Arctic Studies, State Organization of Yamal-Nenets Autonomous District, Salekhard, Russia
| | - Sergey A. Sokratov
- Arctic Environment Laboratory, Faculty of Geography, M.V. Lomonosov Moscow State University, Leninskie gory 1, Moscow, Russia 119991
| | - Silvia Terzago
- Institute of Atmospheric Sciences and Climate, National Research Council (ISAC-CNR), Corso Fiume 4, 10133 Turin, Italy
| | - Dagrun Vikhamar-Schuler
- Division for Model and Climate Analysis, R&D Department, The Norwegian Meteorological Institute, Postboks 43, Blindern, 0313 Oslo, Norway
| | - Scott Williamson
- Department of Biological Sciences, University of Alberta, CW 405, Biological Sciences Bldg., Edmonton, AB T6G 2E9 Canada
| | - Yubao Qiu
- Institute of Remote Sensing and Digital Earth, Chinese Academic of Science, Beijing, 100094 China
- Group on Earth Observations, Cold Regions Initiative, Geneva, Switzerland
| | - Terry V. Callaghan
- Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62 Lund, Sweden
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, S10 2TN UK
- National Research Tomsk Stated University, 36, Lenin Ave., Tomsk, Russia 634050
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Non-Invasive Assessment of the Interrelationships of Diet, Pregnancy Rate, Group Composition, and Physiological and Nutritional Stress of Barren-Ground Caribou in Late Winter. PLoS One 2015; 10:e0127586. [PMID: 26061003 PMCID: PMC4464525 DOI: 10.1371/journal.pone.0127586] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Accepted: 04/16/2015] [Indexed: 11/29/2022] Open
Abstract
The winter diet of barren-ground caribou may affect adult survival, timing of parturition, neonatal survival, and postpartum mass. We used microhistological analyses and hormone levels in feces to determine sex-specific late-winter diets, pregnancy rates, group composition, and endocrine-based measures of physiological and nutritional stress. Lichens, which are highly digestible but contain little protein, dominated the diet (> 68%) but were less prevalent in the diets of pregnant females as compared to non-pregnant females and males. The amount of lichens in the diets of pregnant females decreased at higher latitudes and as winter progressed. Pregnancy rates (82.1%, 95% CI = 76.0 – 88.1%) of adult cows were within the expected range for a declining herd, while pregnancy status was not associated with lichen abundance in the diet. Most groups (80%) were of mixed sex. Male: female ratios (62:100) were not skewed enough to affect the decline. Levels of hormones indicating nutritional stress were detected in areas of low habitat quality and at higher latitudes. Levels of hormones indicated that physiological stress was greatest for pregnant cows, which faced the increasing demands of gestation in late winter. These fecal-based measures of diet and stress provided contextual information for the potential mechanisms of the ongoing decline. Non-invasive techniques, such as monitoring diets, pregnancy rates, sex ratios and stress levels from fecal samples, will become increasingly important as monitoring tools as the industrial footprint continues to expand in the Arctic.
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