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Donahue K, Kimball JS, Du J, Bunt F, Colliander A, Moghaddam M, Johnson J, Kim Y, Rawlins MA. Deep learning estimation of northern hemisphere soil freeze-thaw dynamics using satellite multi-frequency microwave brightness temperature observations. Front Big Data 2023; 6:1243559. [PMID: 38045095 PMCID: PMC10690831 DOI: 10.3389/fdata.2023.1243559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 10/31/2023] [Indexed: 12/05/2023] Open
Abstract
Satellite microwave sensors are well suited for monitoring landscape freeze-thaw (FT) transitions owing to the strong brightness temperature (TB) or backscatter response to changes in liquid water abundance between predominantly frozen and thawed conditions. The FT retrieval is also a sensitive climate indicator with strong biophysical importance. However, retrieval algorithms can have difficulty distinguishing the FT status of soils from that of overlying features such as snow and vegetation, while variable land conditions can also degrade performance. Here, we applied a deep learning model using a multilayer convolutional neural network driven by AMSR2 and SMAP TB records, and trained on surface (~0-5 cm depth) soil temperature FT observations. Soil FT states were classified for the local morning (6 a.m.) and evening (6 p.m.) conditions corresponding to SMAP descending and ascending orbital overpasses, mapped to a 9 km polar grid spanning a five-year (2016-2020) record and Northern Hemisphere domain. Continuous variable estimates of the probability of frozen or thawed conditions were derived using a model cost function optimized against FT observational training data. Model results derived using combined multi-frequency (1.4, 18.7, 36.5 GHz) TBs produced the highest soil FT accuracy over other models derived using only single sensor or single frequency TB inputs. Moreover, SMAP L-band (1.4 GHz) TBs provided enhanced soil FT information and performance gain over model results derived using only AMSR2 TB inputs. The resulting soil FT classification showed favorable and consistent performance against soil FT observations from ERA5 reanalysis (mean percent accuracy, MPA: 92.7%) and in situ weather stations (MPA: 91.0%). The soil FT accuracy was generally consistent between morning and afternoon predictions and across different land covers and seasons. The model also showed better FT accuracy than ERA5 against regional weather station measurements (91.0% vs. 86.1% MPA). However, model confidence was lower in complex terrain where FT spatial heterogeneity was likely beneath the effective model grain size. Our results provide a high level of precision in mapping soil FT dynamics to improve understanding of complex seasonal transitions and their influence on ecological processes and climate feedbacks, with the potential to inform Earth system model predictions.
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Affiliation(s)
- Kellen Donahue
- Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, United States
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - John S. Kimball
- Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, United States
| | - Jinyang Du
- Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, United States
| | - Fredrick Bunt
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - Andreas Colliander
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
| | - Mahta Moghaddam
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States
| | - Jesse Johnson
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - Youngwook Kim
- Department of Biology, College of Science, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Michael A. Rawlins
- Department of Earth, Geographic, and Climate Sciences, University of Massachusetts, Amherst, MA, United States
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2
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Watts JD, Farina M, Kimball JS, Schiferl LD, Liu Z, Arndt KA, Zona D, Ballantyne A, Euskirchen ES, Parmentier FJW, Helbig M, Sonnentag O, Tagesson T, Rinne J, Ikawa H, Ueyama M, Kobayashi H, Sachs T, Nadeau DF, Kochendorfer J, Jackowicz-Korczynski M, Virkkala A, Aurela M, Commane R, Byrne B, Birch L, Johnson MS, Madani N, Rogers B, Du J, Endsley A, Savage K, Poulter B, Zhang Z, Bruhwiler LM, Miller CE, Goetz S, Oechel WC. Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget. Glob Chang Biol 2023; 29:1870-1889. [PMID: 36647630 DOI: 10.1111/gcb.16553] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 11/29/2022] [Accepted: 11/30/2022] [Indexed: 05/28/2023]
Abstract
Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003-2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco ), net ecosystem CO2 exchange (NEE; Reco - GPP), and terrestrial methane (CH4 ) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of -850 Tg CO2 -C year-1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4 ) were estimated at 35 Tg CH4 -C year-1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.
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Affiliation(s)
| | - Mary Farina
- Woodwell Climate Research Center, Falmouth, Massachusetts, USA
- Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, Montana, USA
| | - John S Kimball
- Numerical Terradynamic Simulation Group (NTSG), ISB 415, University of Montana, Missoula, Montana, USA
| | - Luke D Schiferl
- Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
| | - Zhihua Liu
- Numerical Terradynamic Simulation Group (NTSG), ISB 415, University of Montana, Missoula, Montana, USA
| | - Kyle A Arndt
- Woodwell Climate Research Center, Falmouth, Massachusetts, USA
- Earth Systems Research Center, University of New Hampshire, Durham, New Hampshire, USA
| | - Donatella Zona
- Global Change Research Group, Department of Biology, Physical Sciences 240, San Diego State University, San Diego, California, USA
| | - Ashley Ballantyne
- Global Climate and Ecology Laboratory, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, Montana, USA
| | | | - Frans-Jan W Parmentier
- Department of Geosciences, Center for Biogeochemistry in the Anthropocene, University of Oslo, Oslo, Norway
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - Manuel Helbig
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada
| | | | - Torbern Tagesson
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - Janne Rinne
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
- Natural Resources Institute Finland, Helsinki, Finland
| | - Hiroki Ikawa
- Hokkaido Agricultural Research Center, NARO, Sapporo, Japan
| | | | - Hideki Kobayashi
- JAMSTEC-Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
| | - Torsten Sachs
- GFZ German Research Centre for Geoscience, Potsdam, Germany
| | - Daniel F Nadeau
- Department of Civil and Water Engineering, Université Laval, Quebec City, Quebec, Canada
| | - John Kochendorfer
- NOAA Air Resources Laboratory, Atmospheric and Turbulent Diffusion Division, Oak Ridge, Tennessee, USA
| | - Marcin Jackowicz-Korczynski
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
- Department of Ecoscience, Aarhus University, Roskilde, Denmark
| | - Anna Virkkala
- Woodwell Climate Research Center, Falmouth, Massachusetts, USA
| | - Mika Aurela
- Finnish Meteorological Institute, Helsinki, Finland
| | - Roisin Commane
- Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, USA
| | - Brendan Byrne
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Leah Birch
- Woodwell Climate Research Center, Falmouth, Massachusetts, USA
| | - Matthew S Johnson
- Biospheric Science Branch, NASA Ames Research Center, Moffett Field, California, USA
| | - Nima Madani
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Brendan Rogers
- Woodwell Climate Research Center, Falmouth, Massachusetts, USA
| | - Jinyang Du
- Numerical Terradynamic Simulation Group (NTSG), ISB 415, University of Montana, Missoula, Montana, USA
| | - Arthur Endsley
- Numerical Terradynamic Simulation Group (NTSG), ISB 415, University of Montana, Missoula, Montana, USA
| | - Kathleen Savage
- Woodwell Climate Research Center, Falmouth, Massachusetts, USA
| | - Ben Poulter
- NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Zhen Zhang
- Department of Geographical Sciences, University of Maryland, College Park, Maryland, USA
| | - Lori M Bruhwiler
- NOAA Earth System Research Laboratory, Global Monitoring Division, Boulder, Colorado, USA
| | - Charles E Miller
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Scott Goetz
- School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, USA
| | - Walter C Oechel
- Global Change Research Group, Department of Biology, Physical Sciences 240, San Diego State University, San Diego, California, USA
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3
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Zona D, Lafleur PM, Hufkens K, Gioli B, Bailey B, Burba G, Euskirchen ES, Watts JD, Arndt KA, Farina M, Kimball JS, Heimann M, Göckede M, Pallandt M, Christensen TR, Mastepanov M, López‐Blanco E, Dolman AJ, Commane R, Miller CE, Hashemi J, Kutzbach L, Holl D, Boike J, Wille C, Sachs T, Kalhori A, Humphreys ER, Sonnentag O, Meyer G, Gosselin GH, Marsh P, Oechel WC. Pan-Arctic soil moisture control on tundra carbon sequestration and plant productivity. Glob Chang Biol 2023; 29:1267-1281. [PMID: 36353841 PMCID: PMC10099953 DOI: 10.1111/gcb.16487] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/16/2022] [Accepted: 10/05/2022] [Indexed: 05/26/2023]
Abstract
Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.
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Affiliation(s)
- Donatella Zona
- Department BiologySan Diego State UniversitySan DiegoCaliforniaUSA
- School of BiosciencesUniversity of SheffieldSheffieldUK
| | - Peter M. Lafleur
- School of the EnvironmentTrent UniversityPeterboroughOntarioCanada
| | | | - Beniamino Gioli
- National Research Council (CNR)Institute of BioEconomy (IBE)FlorenceItaly
| | - Barbara Bailey
- Department of Mathematics and Statistics, San Diego State UniversitySan DiegoCaliforniaUSA
| | - George Burba
- LI‐COR BiosciencesLincolnNebraskaUSA
- The Robert B. Daugherty Water for Food Global Institute and School of Natural ResourcesUniversity of NebraskaLincolnNebraskaUSA
| | | | - Jennifer D. Watts
- Woodwell Climate Research CenterFalmouthMassachusettsUSA
- W.A. Franke College of Forestry & ConservationThe University of MontanaMissoulaMontanaUSA
| | - Kyle A. Arndt
- Woodwell Climate Research CenterFalmouthMassachusettsUSA
| | - Mary Farina
- Woodwell Climate Research CenterFalmouthMassachusettsUSA
| | - John S. Kimball
- W.A. Franke College of Forestry & ConservationThe University of MontanaMissoulaMontanaUSA
| | - Martin Heimann
- Max Planck Institute for BiogeochemistryJenaGermany
- Faculty of Science, Institute for Atmospheric and Earth System Research (INAR) / Physics, University of HelsinkiHelsinkiFinland
| | | | | | - Torben R. Christensen
- Department of Ecoscience, Arctic Research CentreAarhus UniversityRoskildeDenmark
- Oulanka Research StationOulu UniversityKuusamoFinland
| | - Mikhail Mastepanov
- Department of Ecoscience, Arctic Research CentreAarhus UniversityRoskildeDenmark
- Oulanka Research StationOulu UniversityKuusamoFinland
| | - Efrén López‐Blanco
- Department of Ecoscience, Arctic Research CentreAarhus UniversityRoskildeDenmark
- Department of Environment and Minerals, Greenland Institute of Natural ResourcesNuukGreenland
| | | | - Roisin Commane
- Department of Earth and Environmental Sciences, Lamont‐Doherty Earth ObservatoryColumbia UniversityPalisadesNew YorkUSA
| | - Charles E. Miller
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCaliforniaUSA
| | - Josh Hashemi
- Department BiologySan Diego State UniversitySan DiegoCaliforniaUSA
- Environmental Meteorology, Institute of Earth and Environmental SciencesUniversity of FreiburgFreiburgGermany
| | - Lars Kutzbach
- Institute of Soil Science, Center for Earth System Research and Sustainability (CEN)Universität HamburgHamburgGermany
| | - David Holl
- Institute of Soil Science, Center for Earth System Research and Sustainability (CEN)Universität HamburgHamburgGermany
| | - Julia Boike
- Geography DepartmentHumboldt‐Universität zu BerlinBerlinGermany
- Alfred Wegener Institute Helmholtz Centre for Polar and Marine ResearchPotsdamGermany
| | | | - Torsten Sachs
- GFZ German Research Centre for GeosciencesPotsdamGermany
| | - Aram Kalhori
- GFZ German Research Centre for GeosciencesPotsdamGermany
| | - Elyn R. Humphreys
- Department of Geography & Environmental StudiesCarleton UniversityOttawaOntarioCanada
| | - Oliver Sonnentag
- Département de GéographieUniversité de MontréalMontréalQuebecCanada
| | - Gesa Meyer
- Département de GéographieUniversité de MontréalMontréalQuebecCanada
| | | | - Philip Marsh
- Department of Geography and Environmental Studies, Wilfrid Laurier UniversityWaterlooOntarioCanada
| | - Walter C. Oechel
- Department BiologySan Diego State UniversitySan DiegoCaliforniaUSA
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4
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Liu Z, Kimball JS, Ballantyne AP, Parazoo NC, Wang WJ, Bastos A, Madani N, Natali SM, Watts JD, Rogers BM, Ciais P, Yu K, Virkkala AM, Chevallier F, Peters W, Patra PK, Chandra N. Respiratory loss during late-growing season determines the net carbon dioxide sink in northern permafrost regions. Nat Commun 2022; 13:5626. [PMID: 36163194 PMCID: PMC9512808 DOI: 10.1038/s41467-022-33293-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 09/12/2022] [Indexed: 11/20/2022] Open
Abstract
Warming of northern high latitude regions (NHL, > 50 °N) has increased both photosynthesis and respiration which results in considerable uncertainty regarding the net carbon dioxide (CO2) balance of NHL ecosystems. Using estimates constrained from atmospheric observations from 1980 to 2017, we find that the increasing trends of net CO2 uptake in the early-growing season are of similar magnitude across the tree cover gradient in the NHL. However, the trend of respiratory CO2 loss during late-growing season increases significantly with increasing tree cover, offsetting a larger fraction of photosynthetic CO2 uptake, and thus resulting in a slower rate of increasing annual net CO2 uptake in areas with higher tree cover, especially in central and southern boreal forest regions. The magnitude of this seasonal compensation effect explains the difference in net CO2 uptake trends along the NHL vegetation- permafrost gradient. Such seasonal compensation dynamics are not captured by dynamic global vegetation models, which simulate weaker respiration control on carbon exchange during the late-growing season, and thus calls into question projections of increasing net CO2 uptake as high latitude ecosystems respond to warming climate conditions. The northern high latitude permafrost region has been an important contributor to the carbon sink since the 1980s. A new study finds that as tree cover increases, respiratory CO2 loss during late-growing season offsets photosynthetic CO2 uptake and leads to a slower rate of increasing annual net CO2 uptake.
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Affiliation(s)
- Zhihua Liu
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA. .,CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, Liaoning, China.
| | - John S Kimball
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA. .,Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT, USA.
| | - Ashley P Ballantyne
- Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT, USA. .,Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France.
| | - Nicholas C Parazoo
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Wen J Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, Changchun, Jilin, China.
| | - Ana Bastos
- Max Planck Institute for Biogeochemistry, Department of Biogeochemical Integration, Jena, Germany
| | - Nima Madani
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | | | | | | | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Kailiang Yu
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | | | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Wouter Peters
- Meteorology and Air Quality Group, Wageningen University and Research, Wageningen, the Netherlands.,University, Centre for Isotope Research, Groningen, the Netherlands
| | - Prabir K Patra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
| | - Naveen Chandra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
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5
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Dannenberg MP, Yan D, Barnes ML, Smith WK, Johnston MR, Scott RL, Biederman JA, Knowles JF, Wang X, Duman T, Litvak ME, Kimball JS, Williams AP, Zhang Y. Exceptional heat and atmospheric dryness amplified losses of primary production during the 2020 U.S. Southwest hot drought. Glob Chang Biol 2022; 28:4794-4806. [PMID: 35452156 PMCID: PMC9545136 DOI: 10.1111/gcb.16214] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 03/23/2022] [Indexed: 05/28/2023]
Abstract
Earth's ecosystems are increasingly threatened by "hot drought," which occurs when hot air temperatures coincide with precipitation deficits, intensifying the hydrological, physiological, and ecological effects of drought by enhancing evaporative losses of soil moisture (SM) and increasing plant stress due to higher vapor pressure deficit (VPD). Drought-induced reductions in gross primary production (GPP) exert a major influence on the terrestrial carbon sink, but the extent to which hotter and atmospherically drier conditions will amplify the effects of precipitation deficits on Earth's carbon cycle remains largely unknown. During summer and autumn 2020, the U.S. Southwest experienced one of the most intense hot droughts on record, with record-low precipitation and record-high air temperature and VPD across the region. Here, we use this natural experiment to evaluate the effects of hot drought on GPP and further decompose those negative GPP anomalies into their constituent meteorological and hydrological drivers. We found a 122 Tg C (>25%) reduction in GPP below the 2015-2019 mean, by far the lowest regional GPP over the Soil Moisture Active Passive satellite record. Roughly half of the estimated GPP loss was attributable to low SM (likely a combination of record-low precipitation and warming-enhanced evaporative depletion), but record-breaking VPD amplified the reduction of GPP, contributing roughly 40% of the GPP anomaly. Both air temperature and VPD are very likely to continue increasing over the next century, likely leading to more frequent and intense hot droughts and substantially enhancing drought-induced GPP reductions.
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Affiliation(s)
- Matthew P. Dannenberg
- Department of Geographical and Sustainability SciencesUniversity of IowaIowa CityIowaUSA
| | - Dong Yan
- Information and Data CenterChina Renewable Energy Engineering InstituteBeijingChina
- School of Natural Resources and the EnvironmentUniversity of ArizonaTucsonArizonaUSA
| | - Mallory L. Barnes
- O'Neill School of Public and Environmental AffairsIndiana UniversityBloomingtonIndianaUSA
| | - William K. Smith
- School of Natural Resources and the EnvironmentUniversity of ArizonaTucsonArizonaUSA
| | - Miriam R. Johnston
- Department of Geographical and Sustainability SciencesUniversity of IowaIowa CityIowaUSA
| | - Russell L. Scott
- Southwest Watershed Research Center, Agricultural Research ServiceU.S. Department of AgricultureTucsonArizonaUSA
| | - Joel A. Biederman
- Southwest Watershed Research Center, Agricultural Research ServiceU.S. Department of AgricultureTucsonArizonaUSA
| | - John F. Knowles
- Department of Earth and Environmental SciencesCalifornia State UniversityChicoCaliforniaUSA
| | - Xian Wang
- School of Natural Resources and the EnvironmentUniversity of ArizonaTucsonArizonaUSA
| | - Tomer Duman
- Department of BiologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Marcy E. Litvak
- Department of BiologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - John S. Kimball
- Numerical Terradynamic Simulation GroupUniversity of MontanaMissoulaMontanaUSA
| | - A. Park Williams
- Department of GeographyUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Yao Zhang
- Sino‐French Institute for Earth System Science, College of Urban and Environmental SciencesPeking UniversityBeijingChina
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6
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Liu Y, Wu H, Wang S, Chen X, Kimball JS, Zhang C, Gao H, Guo P. Evaluation of trophic state for inland waters through combining Forel-Ule Index and inherent optical properties. Sci Total Environ 2022; 820:153316. [PMID: 35066030 DOI: 10.1016/j.scitotenv.2022.153316] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 01/17/2022] [Accepted: 01/17/2022] [Indexed: 06/14/2023]
Abstract
Eutrophication is a severe environmental pollution problem for inland waters and poses significant threats to the water safety. Monitoring trophic state of inland waters using optical remote sensing generally requires the inversion of water quality parameters, such as chlorophyll-a, secchi depth, etc. However, the accurate inversion of these individual indicators remains challenging, while the associated retrieval errors can propagate and degrade the evaluation of trophic state. Hence, we proposed a novel monitoring method by developing a Trophic State Index (TSI) based on optical remote-sensing parameters, i.e., Forel-Ule index (FUI) and non-water absorption coefficient at 674 nm (referred to as at-w(674)) retrieved from Sentinel-3 Ocean and Land Color Instrument (OLCI) imagery. The estimated TSI showed favorable correspondence with observed water quality data, including coefficient of determination (r2 = 0.91), root mean squared error (RMSE = 5.54), and mean absolute percentage error (MAPE = 10.69%). Using the Sentinel-3 OLCI data, the proposed method also had very good performance in the field spectrum (MAPE = 5.25 % , RMSE = 3.36). The monthly trophic state evaluation also showed congruence (MAPE = 12.51 % , RMSE = 6.41) with surface water quality monthly report (SWQMR) from the Ministry of Environment and Ecology of the People's Republic of China. The monthly TSI showed favorable agreement for 23 ungauged lakes (RMSE = 7.26, MAPE = 12.78%), indicating potential utility for regional lake water quality monitoring. The proposed method was then applied to 47 other large (>50 km2) water bodies in the Middle-and-Lower watershed of Yangtze River and the Huaihe watershed to evaluate the spatial and temporal variation of trophic state from 2016 to 2020. The TSI results revealed several lakes, such as Lake Honghu and Lake Luoma, with rapidly deteriorating water quality during the study period, while other lakes show relative improvement (e.g., Xiashan Reservoir), indicating unbalanced environmental pressure over the region. Overall, this study showed promising performance and potential for satellite-based monitoring of regional aquatic environments.
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Affiliation(s)
- Yongxin Liu
- School of Earth and Space Sciences, Peking University, Beijing 100871, China; Engineering Research Center of Earth Observation and Navigation (CEON), Ministry of Education of the PRC, No. 5 Yiheyuan Road, Haidian District, Beijing 100871, China
| | - Huan Wu
- Southern Marine Science and Engineering Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Guangdong, China; Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangdong, China; Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
| | - Shenglei Wang
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Xiuwan Chen
- School of Earth and Space Sciences, Peking University, Beijing 100871, China; Engineering Research Center of Earth Observation and Navigation (CEON), Ministry of Education of the PRC, No. 5 Yiheyuan Road, Haidian District, Beijing 100871, China
| | - John S Kimball
- Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT 59801, USA
| | - Chenlu Zhang
- School of Earth and Space Sciences, Peking University, Beijing 100871, China; Engineering Research Center of Earth Observation and Navigation (CEON), Ministry of Education of the PRC, No. 5 Yiheyuan Road, Haidian District, Beijing 100871, China
| | - Han Gao
- School of Earth and Space Sciences, Peking University, Beijing 100871, China; Engineering Research Center of Earth Observation and Navigation (CEON), Ministry of Education of the PRC, No. 5 Yiheyuan Road, Haidian District, Beijing 100871, China
| | - Peng Guo
- School of Earth and Space Sciences, Peking University, Beijing 100871, China; Engineering Research Center of Earth Observation and Navigation (CEON), Ministry of Education of the PRC, No. 5 Yiheyuan Road, Haidian District, Beijing 100871, China
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7
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van Rees CB, Hand BK, Carter SC, Bargeron C, Cline TJ, Daniel W, Ferrante JA, Gaddis K, Hunter ME, Jarnevich CS, McGeoch MA, Morisette JT, Neilson ME, Roy HE, Rozance MA, Sepulveda A, Wallace RD, Whited D, Wilcox T, Kimball JS, Luikart G. A framework to integrate innovations in invasion science for proactive management. Biol Rev Camb Philos Soc 2022; 97:1712-1735. [PMID: 35451197 DOI: 10.1111/brv.12859] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 03/29/2022] [Accepted: 03/30/2022] [Indexed: 11/26/2022]
Abstract
Invasive alien species (IAS) are a rising threat to biodiversity, national security, and regional economies, with impacts in the hundreds of billions of U.S. dollars annually. Proactive or predictive approaches guided by scientific knowledge are essential to keeping pace with growing impacts of invasions under climate change. Although the rapid development of diverse technologies and approaches has produced tools with the potential to greatly accelerate invasion research and management, innovation has far outpaced implementation and coordination. Technological and methodological syntheses are urgently needed to close the growing implementation gap and facilitate interdisciplinary collaboration and synergy among evolving disciplines. A broad review is necessary to demonstrate the utility and relevance of work in diverse fields to generate actionable science for the ongoing invasion crisis. Here, we review such advances in relevant fields including remote sensing, epidemiology, big data analytics, environmental DNA (eDNA) sampling, genomics, and others, and present a generalized framework for distilling existing and emerging data into products for proactive IAS research and management. This integrated workflow provides a pathway for scientists and practitioners in diverse disciplines to contribute to applied invasion biology in a coordinated, synergistic, and scalable manner.
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Affiliation(s)
- Charles B van Rees
- Flathead Lake Biological Station, University of Montana, 32125 Bio Station Lane, Polson, MT, 59860, U.S.A
| | - Brian K Hand
- Flathead Lake Biological Station, University of Montana, 32125 Bio Station Lane, Polson, MT, 59860, U.S.A
| | - Sean C Carter
- Numerical Terradynamic Simulation Group, University of Montana, ISB 415, Missoula, MT, 59812, U.S.A
| | - Chuck Bargeron
- Center for Invasive Species and Ecosystem Health, University of Georgia, 4601 Research Way, Tifton, GA, 31793, U.S.A
| | - Timothy J Cline
- U.S. Geological Survey, Northern Rocky Mountain Science Center, 2327 University Way STE 2, Bozeman MT 59717 & 320 Grinnel Drive, West Glacier, MT, 59936, U.S.A
| | - Wesley Daniel
- U.S. Geological Survey, Wetland and Aquatic Research Center, 7920 NW 71st Street, Gainesville, FL, 32653, U.S.A
| | - Jason A Ferrante
- U.S. Geological Survey, Wetland and Aquatic Research Center, 7920 NW 71st Street, Gainesville, FL, 32653, U.S.A
| | - Keith Gaddis
- NASA Biological Diversity and Ecological Forecasting Programs, 300 E St. SW, Washington, DC, 20546, U.S.A
| | - Margaret E Hunter
- U.S. Geological Survey, Wetland and Aquatic Research Center, 7920 NW 71st Street, Gainesville, FL, 32653, U.S.A
| | - Catherine S Jarnevich
- U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Avenue Bldg C, Fort Collins, CO, 80526, U.S.A
| | - Melodie A McGeoch
- Department of Environment and Genetics, La Trobe University, Plenty Road & Kingsbury Drive, Bundoora, Victoria, 3086, Australia
| | - Jeffrey T Morisette
- U.S. Forest Service Rocky Mountain Research Station, 26 Fort Missoula Road, Missoula, 59804, MT, U.S.A
| | - Matthew E Neilson
- U.S. Geological Survey, Wetland and Aquatic Research Center, 7920 NW 71st Street, Gainesville, FL, 32653, U.S.A
| | - Helen E Roy
- UK Centre for Ecology & Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, OX10 8BB, U.K
| | - Mary Ann Rozance
- Northwest Climate Adaptation Science Center, University of Washington, Box 355674, Seattle, WA, 98195, U.S.A
| | - Adam Sepulveda
- U.S. Forest Service Rocky Mountain Research Station, 26 Fort Missoula Road, Missoula, 59804, MT, U.S.A
| | - Rebekah D Wallace
- Center for Invasive Species and Ecosystem Health, University of Georgia, 4601 Research Way, Tifton, GA, 31793, U.S.A
| | - Diane Whited
- Flathead Lake Biological Station, University of Montana, 32125 Bio Station Lane, Polson, MT, 59860, U.S.A
| | - Taylor Wilcox
- U.S. Forest Service Rocky Mountain Research Station, 26 Fort Missoula Road, Missoula, 59804, MT, U.S.A
| | - John S Kimball
- Numerical Terradynamic Simulation Group, University of Montana, ISB 415, Missoula, MT, 59812, U.S.A
| | - Gordon Luikart
- Flathead Lake Biological Station, University of Montana, 32125 Bio Station Lane, Polson, MT, 59860, U.S.A
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8
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Brust C, Kimball JS, Maneta MP, Jencso K, Reichle RH. DroughtCast: A Machine Learning Forecast of the United States Drought Monitor. Front Big Data 2022; 4:773478. [PMID: 34993467 PMCID: PMC8725730 DOI: 10.3389/fdata.2021.773478] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 11/22/2021] [Indexed: 12/04/2022] Open
Abstract
Drought is one of the most ecologically and economically devastating natural phenomena affecting the United States, causing the U.S. economy billions of dollars in damage, and driving widespread degradation of ecosystem health. Many drought indices are implemented to monitor the current extent and status of drought so stakeholders such as farmers and local governments can appropriately respond. Methods to forecast drought conditions weeks to months in advance are less common but would provide a more effective early warning system to enhance drought response, mitigation, and adaptation planning. To resolve this issue, we introduce DroughtCast, a machine learning framework for forecasting the United States Drought Monitor (USDM). DroughtCast operates on the knowledge that recent anomalies in hydrology and meteorology drive future changes in drought conditions. We use simulated meteorology and satellite observed soil moisture as inputs into a recurrent neural network to accurately forecast the USDM between 1 and 12 weeks into the future. Our analysis shows that precipitation, soil moisture, and temperature are the most important input variables when forecasting future drought conditions. Additionally, a case study of the 2017 Northern Plains Flash Drought shows that DroughtCast was able to forecast a very extreme drought event up to 12 weeks before its onset. Given the favorable forecasting skill of the model, DroughtCast may provide a promising tool for land managers and local governments in preparing for and mitigating the effects of drought.
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Affiliation(s)
- Colin Brust
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, United States
| | - John S Kimball
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, United States
| | - Marco P Maneta
- Regional Hydrology Lab, Geosciences Department, University of Montana, Missoula, MT, United States.,Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, United States
| | - Kelsey Jencso
- Montana Climate Office, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, United States
| | - Rolf H Reichle
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, United States
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9
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Carter S, van Rees CB, Hand BK, Muhlfeld CC, Luikart G, Kimball JS. Testing a Generalizable Machine Learning Workflow for Aquatic Invasive Species on Rainbow Trout ( Oncorhynchus mykiss) in Northwest Montana. Front Big Data 2021; 4:734990. [PMID: 34734177 PMCID: PMC8558495 DOI: 10.3389/fdata.2021.734990] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 09/17/2021] [Indexed: 11/13/2022] Open
Abstract
Biological invasions are accelerating worldwide, causing major ecological and economic impacts in aquatic ecosystems. The urgent decision-making needs of invasive species managers can be better met by the integration of biodiversity big data with large-domain models and data-driven products. Remotely sensed data products can be combined with existing invasive species occurrence data via machine learning models to provide the proactive spatial risk analysis necessary for implementing coordinated and agile management paradigms across large scales. We present a workflow that generates rapid spatial risk assessments on aquatic invasive species using occurrence data, spatially explicit environmental data, and an ensemble approach to species distribution modeling using five machine learning algorithms. For proof of concept and validation, we tested this workflow using extensive spatial and temporal hybridization and occurrence data from a well-studied, ongoing, and climate-driven species invasion in the upper Flathead River system in northwestern Montana, USA. Rainbow Trout (RBT; Oncorhynchus mykiss), an introduced species in the Flathead River basin, compete and readily hybridize with native Westslope Cutthroat Trout (WCT; O. clarkii lewisii), and the spread of RBT individuals and their alleles has been tracked for decades. We used remotely sensed and other geospatial data as key environmental predictors for projecting resultant habitat suitability to geographic space. The ensemble modeling technique yielded high accuracy predictions relative to 30-fold cross-validated datasets (87% 30-fold cross-validated accuracy score). Both top predictors and model performance relative to these predictors matched current understanding of the drivers of RBT invasion and habitat suitability, indicating that temperature is a major factor influencing the spread of invasive RBT and hybridization with native WCT. The congruence between more time-consuming modeling approaches and our rapid machine-learning approach suggest that this workflow could be applied more broadly to provide data-driven management information for early detection of potential invaders.
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Affiliation(s)
- S Carter
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, United States
| | - C B van Rees
- Flathead Lake Biological Station, Division of Biological Sciences, University of Montana, Polson, MT, United States
| | - B K Hand
- Flathead Lake Biological Station, Division of Biological Sciences, University of Montana, Polson, MT, United States
| | - C C Muhlfeld
- Flathead Lake Biological Station, Division of Biological Sciences, University of Montana, Polson, MT, United States.,U.S. Geological Survey, Northern Rocky Mountain Science Center, Glacier National Park, West Glacier, MT, United States.,Department of Ecosystem and Conservation Sciences, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, United States
| | - G Luikart
- Flathead Lake Biological Station, Division of Biological Sciences, University of Montana, Polson, MT, United States
| | - J S Kimball
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, United States.,Department of Ecosystem and Conservation Sciences, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, United States
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10
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Du J, Kimball JS, Sheffield J, Pan M, Fisher CK, Beck HE, Wood EF. Satellite Flood Inundation Assessment and Forecast Using SMAP and Landsat. IEEE J Sel Top Appl Earth Obs Remote Sens 2021; 14:6707-6715. [PMID: 34316323 PMCID: PMC8312582 DOI: 10.1109/jstars.2021.3092340] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The capability and synergistic use of multisource satellite observations for flood monitoring and forecasts is crucial for improving disaster preparedness and mitigation. Here, surface fractional water cover (FW) retrievals derived from Soil Moisture Active Passive (SMAP) L-band (1.4 GHz) brightness temperatures were used for flood assessment over southeast Africa during the Cyclone Idai event. We then focused on five subcatchments of the Pungwe basin and developed a machine learning based approach with the support of Google Earth Engine for daily (24-h) forecasting of FW and 30-m inundation downscaling and mapping. The Classification and Regression Trees model was selected and trained using retrievals derived from SMAP and Landsat coupled with rainfall forecasts from the NOAA Global Forecast System. Independent validation showed that FW predictions over randomly selected dates are highly correlated (R = 0.87) with the Landsat observations. The forecast results captured the flood temporal dynamics from the Idai event; and the associated 30-m downscaling results showed inundation spatial patterns consistent with independent satellite synthetic aperture radar observations. The data-driven approach provides new capacity for flood monitoring and forecasts leveraging synergistic satellite observations and big data analysis, which is particularly valuable for data sparse regions.
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Affiliation(s)
- Jinyang Du
- Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT 59801 USA
| | - John S Kimball
- Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT 59801 USA
| | - Justin Sheffield
- School of Geography and Environmental Sciences, University of Southampton, Southampton SO17 1BJ, U.K
| | - Ming Pan
- Civil and Environmental Engineering, Princeton University, Princeton, NJ 08542 USA, and also with the Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA 92093 USA
| | | | - Hylke E Beck
- Civil and Environmental Engineering, Princeton University, Princeton, NJ 08542 USA, and also with the European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy
| | - Eric F Wood
- Civil and Environmental Engineering, Princeton University, Princeton, NJ 08542 USA
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11
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Wurster PM, Maneta M, Kimball JS, Endsley KA, Beguería S. Monitoring Crop Status in the Continental United States Using the SMAP Level-4 Carbon Product. Front Big Data 2021; 3:597720. [PMID: 33693422 PMCID: PMC7931861 DOI: 10.3389/fdata.2020.597720] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 11/19/2020] [Indexed: 12/02/2022] Open
Abstract
Accurate monitoring of crop condition is critical to detect anomalies that may threaten the economic viability of agriculture and to understand how crops respond to climatic variability. Retrievals of soil moisture and vegetation information from satellite-based remote-sensing products offer an opportunity for continuous and affordable crop condition monitoring. This study compared weekly anomalies in accumulated gross primary production (GPP) from the SMAP Level-4 Carbon (L4C) product to anomalies calculated from a state-scale weekly crop condition index (CCI) and also to crop yield anomalies calculated from county-level yield data reported at the end of the season. We focused on barley, spring wheat, corn, and soybeans cultivated in the continental United States from 2000 to 2018. We found that consistencies between SMAP L4C GPP anomalies and both crop condition and yield anomalies increased as crops developed from the emergence stage (r: 0.4–0.7) and matured (r: 0.6–0.9) and that the agreement was better in drier regions (r: 0.4–0.9) than in wetter regions (r: −0.8–0.4). The L4C provides weekly GPP estimates at a 1-km scale, permitting the evaluation and tracking of anomalies in crop status at higher spatial detail than metrics based on the state-level CCI or county-level crop yields. We demonstrate that the L4C GPP product can be used operationally to monitor crop condition with the potential to become an important tool to inform decision-making and research.
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Affiliation(s)
- Patrick M Wurster
- Regional Hydrology Lab, Geosciences Department, University of Montana, Missoula, MT, United States
| | - Marco Maneta
- Regional Hydrology Lab, Geosciences Department, University of Montana, Missoula, MT, United States.,Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, United States
| | - John S Kimball
- Numerical Terradynamic Simulation Group, University of Montana, W.A. Franke College of Forestry and Conservation, Missoula, MT, United States
| | - K Arthur Endsley
- Numerical Terradynamic Simulation Group, University of Montana, W.A. Franke College of Forestry and Conservation, Missoula, MT, United States
| | - Santiago Beguería
- Estación Experimental de Aula Dei, Consejo Superior de Investigaciones Científicas (EEAD-CSIC), Zaragoza, Spain
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12
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Wu G, Guan K, Li Y, Novick KA, Feng X, McDowell NG, Konings AG, Thompson SE, Kimball JS, De Kauwe MG, Ainsworth EA, Jiang C. Interannual variability of ecosystem iso/anisohydry is regulated by environmental dryness. New Phytol 2021; 229:2562-2575. [PMID: 33118166 DOI: 10.1111/nph.17040] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 10/16/2020] [Indexed: 06/11/2023]
Abstract
●Plants are characterized by the iso/anisohydry continuum depending on how they regulate leaf water potential (ΨL ). However, how iso/anisohydry changes over time in response to year-to-year variations in environmental dryness and how such responses vary across different regions remains poorly characterized. ●We investigated how dryness, represented by aridity index, affects the interannual variability of ecosystem iso/anisohydry at the regional scale, estimated using satellite microwave vegetation optical depth (VOD) observations. This ecosystem-level analysis was further complemented with published field observations of species-level ΨL . ●We found different behaviors in the directionality and sensitivity of isohydricity (σ) with respect to the interannual variation of dryness in different ecosystems. These behaviors can largely be differentiated by the average dryness of the ecosystem itself: in mesic ecosystems, σ decreases in drier years with a higher sensitivity to dryness; in xeric ecosystems, σ increases in drier years with a lower sensitivity to dryness. These results were supported by the species-level synthesis. ●Our study suggests that how plants adjust their water use across years - as revealed by their interannual variability in isohydricity - depends on the dryness of plants' living environment. This finding advances our understanding of plant responses to drought at regional scales.
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Affiliation(s)
- Genghong Wu
- College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Kaiyu Guan
- College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana Champaign, Champaign, IL, 61820, USA
| | - Yan Li
- State Key Laboratory of Earth Surface Processes and Resources Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Kimberly A Novick
- O'Neill School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington, IN, 47405, USA
| | - Xue Feng
- Department of Civil, Environmental, and Geo-Engineering, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Nate G McDowell
- Earth Systems Science Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Alexandra G Konings
- Department of Earth System Science, Stanford University, Stanford, CA, 94305, USA
| | - Sally E Thompson
- Department of Civil and Environmental Engineering, University of California Berkeley, Berkeley, CA, 94720, USA
- Department of Civil, Environmental and Mining Engineering, University of Western Australia, Crawley, WA, 6009, Australia
| | - John S Kimball
- Numerical Terra dynamic Simulation Group, College of Forestry & Conservation, University of Montana, Missoula, MT, 59812, USA
| | - Martin G De Kauwe
- ARC Australia Centre of Excellence for Climate Extremes, Sydney, NSW, 2052, Australia
- Climate Change Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
- Evolution and Ecology Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Elizabeth A Ainsworth
- Department of Plant Biology, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
- USDA ARS Global Change and Photosynthesis Research Unit, Urbana, IL, 61801, USA
| | - Chongya Jiang
- College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
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13
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Park H, Watanabe E, Kim Y, Polyakov I, Oshima K, Zhang X, Kimball JS, Yang D. Increasing riverine heat influx triggers Arctic sea ice decline and oceanic and atmospheric warming. Sci Adv 2020; 6:6/45/eabc4699. [PMID: 33158866 PMCID: PMC7673719 DOI: 10.1126/sciadv.abc4699] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 09/15/2020] [Indexed: 06/11/2023]
Abstract
Arctic river discharge increased over the last several decades, conveying heat and freshwater into the Arctic Ocean and likely affecting regional sea ice and the ocean heat budget. However, until now, there have been only limited assessments of riverine heat impacts. Here, we adopted a synthesis of a pan-Arctic sea ice-ocean model and a land surface model to quantify impacts of river heat on the Arctic sea ice and ocean heat budget. We show that river heat contributed up to 10% of the regional sea ice reduction over the Arctic shelves from 1980 to 2015. Particularly notable, this effect occurs as earlier sea ice breakup in late spring and early summer. The increasing ice-free area in the shelf seas results in a warmer ocean in summer, enhancing ocean-atmosphere energy exchange and atmospheric warming. Our findings suggest that a positive river heat-sea ice feedback nearly doubles the river heat effect.
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Affiliation(s)
- Hotaek Park
- Institute of Arctic Climate and Environmental Research, JAMSTEC, Yokosuka, Japan.
- Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Japan
| | - Eiji Watanabe
- Institute of Arctic Climate and Environmental Research, JAMSTEC, Yokosuka, Japan
| | - Youngwook Kim
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, The University of Montana, Missoula, MT 59812, USA
- Department of Biology, College of Science United Arab Emirates University P.O. Box 15551, Al Ain, United Arab Emirates
| | - Igor Polyakov
- International Arctic Research Center and College of Natural Science and Mathematics, University of Alaska Fairbanks, 930 Koyukuk Drive, Fairbanks, AK, 99775, USA
- Finnish Meteorological Institute, Erik Palménin aukio 1, Helsinki, Finland
| | - Kazuhiro Oshima
- Faculty of Software and Information Technology, Aomori University, Aomori, Japan
| | - Xiangdong Zhang
- International Arctic Research Center and Department of Atmospheric Sciences, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
| | - John S Kimball
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, The University of Montana, Missoula, MT 59812, USA
| | - Daqing Yang
- Environment and Climate Change Canada, Victoria, Canada
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14
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Liu Z, Kimball JS, Parazoo NC, Ballantyne AP, Wang WJ, Madani N, Pan CG, Watts JD, Reichle RH, Sonnentag O, Marsh P, Hurkuck M, Helbig M, Quinton WL, Zona D, Ueyama M, Kobayashi H, Euskirchen ES. Increased high-latitude photosynthetic carbon gain offset by respiration carbon loss during an anomalous warm winter to spring transition. Glob Chang Biol 2020; 26:682-696. [PMID: 31596019 DOI: 10.1111/gcb.14863] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 07/21/2019] [Indexed: 06/10/2023]
Abstract
Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2 ) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010-2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon-climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes.
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Affiliation(s)
- Zhihua Liu
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
| | - John S Kimball
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
- Department of Ecosystem and Conservation Sciences, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
| | - Nicholas C Parazoo
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Ashley P Ballantyne
- Department of Ecosystem and Conservation Sciences, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
| | - Wen J Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Nima Madani
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Caleb G Pan
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
| | | | | | - Oliver Sonnentag
- Département de géographie and Centre d'études nordiques, Université de Montréal, Montreal, QC, Canada
| | - Philip Marsh
- Cold Regions Research Centre, Wilfrid Laurier University, Waterloo, ON, Canada
| | - Miriam Hurkuck
- Département de géographie and Centre d'études nordiques, Université de Montréal, Montreal, QC, Canada
| | - Manuel Helbig
- School of Geography and Earth Sciences, McMaster University, Hamilton, ON, Canada
| | - William L Quinton
- Cold Regions Research Centre, Wilfrid Laurier University, Waterloo, ON, Canada
| | - Donatella Zona
- Global Change Research Group, Department of Biology, San Diego State University, San Diego, CA, USA
| | - Masahito Ueyama
- Graduate School of Life and Environmental Sciences, Osaka Prefecture University, Sakai, Japan
| | - Hideki Kobayashi
- Institute of Arctic Climate and Environment Research, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
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15
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DU J, Kimball JS, Galantowicz J, Kim SB, Chan SK, Reichle R, Jones LA, Watts JD. Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat. Remote Sens Environ 2018; 213:1-17. [PMID: 30050230 PMCID: PMC6055934 DOI: 10.1016/j.rse.2018.04.054] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
A method to assess global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fwLBand ) retrievals were derived using SMAP H-polarization brightness temperature (Tb ) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency Tb observations from AMSR2. The resulting fwLBand global record has high temporal sampling (1-3 days) and 36-km spatial resolution. The fwLBand annual averages corresponded favourably (R=0.85, p-value<0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly fwLBand averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable fwLBand performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) fwLBand results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m fwLBand retrievals showed favourable spatial accuracy for water (commission error 31.46%, omission error 30.20%) and land (commission error 0.87%, omission error 0.96%) classifications and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new fwLBand algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics and potential flood risk.
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Affiliation(s)
- Jinyang DU
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, The University of Montana, Missoula, MT 59812, United States
| | - John S Kimball
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, The University of Montana, Missoula, MT 59812, United States
| | - John Galantowicz
- Atmospheric and Environmental Research, Lexington, MA 02421, United States
| | - Seung-Bum Kim
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, United States
| | - Steven K Chan
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, United States
| | - Rolf Reichle
- NASA Goddard Space Flight Center, Greenbelt, MD, 20771, United States
| | - Lucas A Jones
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, The University of Montana, Missoula, MT 59812, United States
| | - Jennifer D Watts
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, The University of Montana, Missoula, MT 59812, United States
- Woods Hole Research Center, Falmouth, MA, 02540, United States
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Du J, Kimball JS, Reichle RH, Jones LA, Watts JD, Kim Y. Global Satellite Retrievals of the Near-Surface Atmospheric Vapor Pressure Deficit from AMSR-E and AMSR2. Remote Sens (Basel) 2018; 10:1175. [PMID: 30505569 PMCID: PMC6258077 DOI: 10.3390/rs10081175] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Near-surface atmospheric Vapor Pressure Deficit (VPD) is a key environmental variable affecting vegetation water stress, evapotranspiration, and atmospheric moisture demand. Although VPD is readily derived from in situ standard weather station measurements, more spatially continuous global observations for regional monitoring of VPD are lacking. Here, we document a new method to estimate daily (both a.m. and p.m.) global land surface VPD at a 25-km resolution using a satellite passive microwave remotely sensed Land Parameter Data Record (LPDR) derived from the Advanced Microwave Scanning Radiometer (AMSR) sensors. The AMSR-derived VPD record shows strong correspondence (correlation coefficient ≥ 0.80, p-value < 0.001) and overall good performance (0.48 kPa ≤ Root Mean Square Error ≤ 0.69 kPa) against independent VPD observations from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data. The estimated AMSR VPD retrieval uncertainties vary with land cover type, satellite observation time, and underlying LPDR data quality. These results provide new satellite capabilities for global mapping and monitoring of land surface VPD dynamics from ongoing AMSR2 operations. Overall good accuracy and similar observations from both AMSR2 and AMSR-E allow for the development of climate data records documenting recent (from 2002) VPD trends and potential impacts on vegetation, land surface evaporation, and energy budgets.
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Affiliation(s)
- Jinyang Du
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry and Conservation, The University of Montana, Missoula, MT 59812, USA
| | - John S. Kimball
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry and Conservation, The University of Montana, Missoula, MT 59812, USA
| | | | - Lucas A. Jones
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry and Conservation, The University of Montana, Missoula, MT 59812, USA
| | - Jennifer D. Watts
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry and Conservation, The University of Montana, Missoula, MT 59812, USA
- Woods Hole Research Center, Falmouth, MA 02540, USA
| | - Youngwook Kim
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry and Conservation, The University of Montana, Missoula, MT 59812, USA
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Madani N, Kimball JS, Ballantyne AP, Affleck DLR, van Bodegom PM, Reich PB, Kattge J, Sala A, Nazeri M, Jones MO, Zhao M, Running SW. Future global productivity will be affected by plant trait response to climate. Sci Rep 2018; 8:2870. [PMID: 29434266 PMCID: PMC5809371 DOI: 10.1038/s41598-018-21172-9] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Accepted: 01/31/2018] [Indexed: 11/24/2022] Open
Abstract
Plant traits are both responsive to local climate and strong predictors of primary productivity. We hypothesized that future climate change might promote a shift in global plant traits resulting in changes in Gross Primary Productivity (GPP). We characterized the relationship between key plant traits, namely Specific Leaf Area (SLA), height, and seed mass, and local climate and primary productivity. We found that by 2070, tropical and arid ecosystems will be more suitable for plants with relatively lower canopy height, SLA and seed mass, while far northern latitudes will favor woody and taller plants than at present. Using a network of tower eddy covariance CO2 flux measurements and the extrapolated plant trait maps, we estimated the global distribution of annual GPP under current and projected future plant community distribution. We predict that annual GPP in northern biomes (≥45 °N) will increase by 31% (+8.1 ± 0.5 Pg C), but this will be offset by a 17.9% GPP decline in the tropics (-11.8 ± 0.84 Pg C). These findings suggest that regional climate changes will affect plant trait distributions, which may in turn affect global productivity patterns.
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Affiliation(s)
- Nima Madani
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, MT, 59812, USA.
- Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, Montana, 59812, USA.
| | - John S Kimball
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, MT, 59812, USA
- Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, Montana, 59812, USA
| | - Ashley P Ballantyne
- Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, Montana, 59812, USA
| | - David L R Affleck
- Department of Forest Management, W.A. Franke College of Forestry & Conservation, University of Montana, 32 Campus Drive, Missoula, MT, 59812, USA
| | - Peter M van Bodegom
- Institute of Environmental Sciences (CML), University Leiden, 2333CC, Leiden, The Netherlands
| | - Peter B Reich
- Department of Forest Resources, University of Minnesota, 1530 Cleveland Avenue North, St. Paul, Minnesota, 55108, USA
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, 2753 NSW, Australia
| | - Jens Kattge
- Max-Planck-Institute for Biogeochemistry, 07745, Jena, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103, Leipzig, Germany
| | - Anna Sala
- Division of Biological Sciences, University of Montana, Missoula, MT, 59812, USA
| | - Mona Nazeri
- Department of Wildlife, Fisheries and Aquaculture, Mississippi State University, MS, 39762, USA
| | - Matthew O Jones
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, MT, 59812, USA
| | - Maosheng Zhao
- Department of Geographical Sciences, University of Maryland, College Park, Maryland, 20742, USA
| | - Steven W Running
- Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, MT, 59812, USA
- Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, Montana, 59812, USA
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Yi Y, Kimball JS, Chen RH, Moghaddam M, Reichle RH, Mishra U, Zona D, Oechel WC. Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska. Cryosphere 2018; 12:145-161. [PMID: 32577170 PMCID: PMC7309651 DOI: 10.5194/tc-12-145-2018] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models and can lead to large uncertainties in predicting regional ecosystem responses and climate feedbacks. In this study, we developed a spatially integrated modelling and analysis framework combining field observations, local scale (~ 50 m resolution) active layer thickness (ALT) and soil moisture maps derived from airborne low frequency (L+P-band) radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Modelled ALT results show good correspondence with in situ measurements in higher permafrost probability (PP ≥ 70%) areas (n = 33, R = 0.60, mean bias = 1.58 cm, RMSE = 20.32 cm), but with larger uncertainty in sporadic and discontinuous permafrost areas. The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32 ± 1.18 cm yr-1) and much larger increases (> 3 cm yr-1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). A spatially integrated analysis of the radar retrievals and model sensitivity simulations demonstrated that uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was the largest factor affecting modeled ALT accuracy, while soil moisture played a secondary role. Potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of active layer conditions and refinement of the modelling framework across a larger domain.
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Affiliation(s)
- Yonghong Yi
- Numerical Terradynamic Simulation Group, The University of Montana, Missoula MT, USA
| | - John S. Kimball
- Numerical Terradynamic Simulation Group, The University of Montana, Missoula MT, USA
| | - Richard H. Chen
- Department of Electrical Engineering, University of Southern California, CA, USA
| | - Mahta Moghaddam
- Department of Electrical Engineering, University of Southern California, CA, USA
| | - Rolf H. Reichle
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Umakant Mishra
- Environmental Science Division, Argonne National Laboratory, Argonne, IL, USA
| | - Donatella Zona
- Department of Biology, San Diego State University, San Diego, CA, USA
| | - Walter C. Oechel
- Department of Biology, San Diego State University, San Diego, CA, USA
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Reichle RH, De Lannoy GJM, Liu Q, Koster RD, Kimball JS, Crow WT, Ardizzone JV, Chakraborty P, Collins DW, Conaty AL, Girotto M, Jones LA, Kolassa J, Lievens H, Lucchesi RA, Smith EB. Global Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using Assimilation Diagnostics. J Hydrometeorol 2017; 18:3217-3237. [PMID: 30364509 DOI: 10.1175/jhm-d-17-0063.1] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with ~2.5day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of ~0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under ~3 K), the soil moisture increments (under ~0.01 m3 m-3), and the surface soil temperature increments (under ~1 K). Typical instantaneous values are ~6 K for O-F residuals, ~0.01 (~0.003) m3 m-3 for surface (root-zone) soil moisture increments, and ~0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.
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Affiliation(s)
- Rolf H Reichle
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | | | - Qing Liu
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Randal D Koster
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | | | - Wade T Crow
- USDA ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD, USA
| | - Joseph V Ardizzone
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Purnendu Chakraborty
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Douglas W Collins
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Austin L Conaty
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Manuela Girotto
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- GESTAR, Universities Space Research Association, Columbia, MD, USA
| | | | - Jana Kolassa
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- GESTAR, Universities Space Research Association, Columbia, MD, USA
| | - Hans Lievens
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium
| | - Robert A Lucchesi
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Edmond B Smith
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
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20
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Reichle RH, De Lannoy GJM, Liu Q, Koster RD, Kimball JS, Crow WT, Ardizzone JV, Chakraborty P, Collins DW, Conaty AL, Girotto M, Jones LA, Kolassa J, Lievens H, Lucchesi RA, Smith EB. Global Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using Assimilation Diagnostics. J Hydrometeorol 2017; 18:3217-3237. [PMID: 30364509 PMCID: PMC6196324 DOI: 10.1175/jhm-d-17-0130.1] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with ~2.5day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of ~0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under ~3 K), the soil moisture increments (under ~0.01 m3 m-3), and the surface soil temperature increments (under ~1 K). Typical instantaneous values are ~6 K for O-F residuals, ~0.01 (~0.003) m3 m-3 for surface (root-zone) soil moisture increments, and ~0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.
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Affiliation(s)
- Rolf H. Reichle
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | | | - Qing Liu
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Randal D. Koster
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | | | - Wade T. Crow
- USDA ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD, USA
| | - Joseph V. Ardizzone
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Purnendu Chakraborty
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Douglas W. Collins
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Austin L. Conaty
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Manuela Girotto
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- GESTAR, Universities Space Research Association, Columbia, MD, USA
| | | | - Jana Kolassa
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- GESTAR, Universities Space Research Association, Columbia, MD, USA
| | - Hans Lievens
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium
| | - Robert A. Lucchesi
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
| | - Edmond B. Smith
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
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Hand BK, Muhlfeld CC, Wade AA, Kovach RP, Whited DC, Narum SR, Matala AP, Ackerman MW, Garner BA, Kimball JS, Stanford JA, Luikart G. Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics. Mol Ecol 2016; 25:689-705. [PMID: 26677031 DOI: 10.1111/mec.13517] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2014] [Revised: 11/25/2015] [Accepted: 12/09/2015] [Indexed: 01/06/2023]
Abstract
Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST ) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.
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Affiliation(s)
- Brian K Hand
- Flathead Lake Biological Station, University of Montana, Polson, MT, 59860, USA
| | - Clint C Muhlfeld
- Flathead Lake Biological Station, University of Montana, Polson, MT, 59860, USA.,U.S. Geological Survey, Northern Rocky Mountain Science Center, Glacier National Park, West Glacier, MT, 59936, USA
| | - Alisa A Wade
- Flathead Lake Biological Station, University of Montana, Polson, MT, 59860, USA
| | - Ryan P Kovach
- U.S. Geological Survey, Northern Rocky Mountain Science Center, Glacier National Park, West Glacier, MT, 59936, USA
| | - Diane C Whited
- Flathead Lake Biological Station, University of Montana, Polson, MT, 59860, USA
| | - Shawn R Narum
- Columbia River Inter-Tribal Fish Commission, Hagerman Fish Culture Experiment Station, 3059-F National Fish Hatchery Road, Hagerman, ID, 83332, USA
| | - Andrew P Matala
- Columbia River Inter-Tribal Fish Commission, Hagerman Fish Culture Experiment Station, 3059-F National Fish Hatchery Road, Hagerman, ID, 83332, USA
| | - Michael W Ackerman
- Pacific States Marine Fisheries Commission, IDFG Eagle Fish Genetic Laboratory, 1800 Trout Road, Eagle, ID, 83616, USA
| | - Brittany A Garner
- Flathead Lake Biological Station, University of Montana, Polson, MT, 59860, USA
| | - John S Kimball
- College of Forestry & Conservation, The University of Montana, Missoula, MT, 59812, USA
| | - Jack A Stanford
- Flathead Lake Biological Station, University of Montana, Polson, MT, 59860, USA.,Division of Biological Sciences, The University of Montana, Missoula, MT, 59812, USA
| | - Gordon Luikart
- Flathead Lake Biological Station, University of Montana, Polson, MT, 59860, USA.,Division of Biological Sciences, The University of Montana, Missoula, MT, 59812, USA
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22
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Madani N, Kimball JS, Nazeri M, Kumar L, Affleck DLR. Remote Sensing Derived Fire Frequency, Soil Moisture and Ecosystem Productivity Explain Regional Movements in Emu over Australia. PLoS One 2016; 11:e0147285. [PMID: 26799732 PMCID: PMC4723036 DOI: 10.1371/journal.pone.0147285] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2015] [Accepted: 01/01/2016] [Indexed: 11/18/2022] Open
Abstract
Species distribution modeling has been widely used in studying habitat relationships and for conservation purposes. However, neglecting ecological knowledge about species, e.g. their seasonal movements, and ignoring the proper environmental factors that can explain key elements for species survival (shelter, food and water) increase model uncertainty. This study exemplifies how these ecological gaps in species distribution modeling can be addressed by modeling the distribution of the emu (Dromaius novaehollandiae) in Australia. Emus cover a large area during the austral winter. However, their habitat shrinks during the summer months. We show evidence of emu summer habitat shrinkage due to higher fire frequency, and low water and food availability in northern regions. Our findings indicate that emus prefer areas with higher vegetation productivity and low fire recurrence, while their distribution is linked to an optimal intermediate (~0.12 m3 m(-3)) soil moisture range. We propose that the application of three geospatial data products derived from satellite remote sensing, namely fire frequency, ecosystem productivity, and soil water content, provides an effective representation of emu general habitat requirements, and substantially improves species distribution modeling and representation of the species' ecological habitat niche across Australia.
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Affiliation(s)
- Nima Madani
- Numerical Terradynamic Simulation Group, College of Forestry & Conservation, University of Montana, 32 Campus Drive Missoula, MT, 59812, United States of America
| | - John S. Kimball
- Numerical Terradynamic Simulation Group, College of Forestry & Conservation, University of Montana, 32 Campus Drive Missoula, MT, 59812, United States of America
| | - Mona Nazeri
- School of Journalism, Department of Environmental Journalism, University of Montana, 32 Campus Drive, Missoula, MT, 59812, United States of America
| | - Lalit Kumar
- Ecosystem Management, School of Environmental and Rural Science, University of New England, Ring Road, Armidale, New South Wales, 2351, Australia
| | - David L. R. Affleck
- College of Forestry and Conservation, University of Montana, 32 Campus Drive, Missoula, MT, 59812, United States of America
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Zhang K, Kimball JS, Nemani RR, Running SW, Hong Y, Gourley JJ, Yu Z. Vegetation Greening and Climate Change Promote Multidecadal Rises of Global Land Evapotranspiration. Sci Rep 2015; 5:15956. [PMID: 26514110 PMCID: PMC4626800 DOI: 10.1038/srep15956] [Citation(s) in RCA: 198] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2015] [Accepted: 10/06/2015] [Indexed: 11/17/2022] Open
Abstract
Recent studies showed that anomalous dry conditions and limited moisture supply roughly between 1998 and 2008, especially in the Southern Hemisphere, led to reduced vegetation productivity and ceased growth in land evapotranspiration (ET). However, natural variability of Earth’s climate system can degrade capabilities for identifying climate trends. Here we produced a long-term (1982–2013) remote sensing based land ET record and investigated multidecadal changes in global ET and underlying causes. The ET record shows a significant upward global trend of 0.88 mm yr−2 (P < 0.001) over the 32-year period, mainly driven by vegetation greening (0.018% per year; P < 0.001) and rising atmosphere moisture demand (0.75 mm yr−2; P = 0.016). Our results indicate that reduced ET growth between 1998 and 2008 was an episodic phenomenon, with subsequent recovery of the ET growth rate after 2008. Terrestrial precipitation also shows a positive trend of 0.66 mm yr−2 (P = 0.08) over the same period consistent with expected water cycle intensification, but this trend is lower than coincident increases in evaporative demand and ET, implying a possibility of cumulative water supply constraint to ET. Continuation of these trends will likely exacerbate regional drought-induced disturbances, especially during regional dry climate phases associated with strong El Niño events.
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Affiliation(s)
- Ke Zhang
- Cooperative Institute for Mesosacle Meteorological Studies, The University of Oklahoma, 120 David L. Boren Blvd., Norman, OK 73072, USA.,Hydrometeorology &Remote Sensing (HyDROS) Laboratory and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK.,State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, 1 Xikang Road, Nanjing, Jiangsu Province, 210098, China
| | - John S Kimball
- Numerical Terradynamic Simulation Group, The University of Montana, 32 Campus Drive #1224, Missoula, MT 59812-1224, USA
| | | | - Steven W Running
- Numerical Terradynamic Simulation Group, The University of Montana, 32 Campus Drive #1224, Missoula, MT 59812-1224, USA
| | - Yang Hong
- Hydrometeorology &Remote Sensing (HyDROS) Laboratory and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK.,Department of Hydraulic Engineering, Tsinghua University, Beijing, China
| | | | - Zhongbo Yu
- State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, 1 Xikang Road, Nanjing, Jiangsu Province, 210098, China
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Jones MO, Kimball JS, Small EE, Larson KM. Comparing land surface phenology derived from satellite and GPS network microwave remote sensing. Int J Biometeorol 2014; 58:1305-1315. [PMID: 24005849 DOI: 10.1007/s00484-013-0726-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2013] [Revised: 08/12/2013] [Accepted: 08/22/2013] [Indexed: 06/02/2023]
Abstract
The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.
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Affiliation(s)
- Matthew O Jones
- Flathead Lake Biological Station (FLBS), Numerical Terradynamic Simulation Group (NTSG), University of Montana, Davidson Honors College Room 021, NTSG Annex, 32 Campus Dr., Missoula, MT, 59812, USA,
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Jones MO, Kimball JS, Jones LA. Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada. Glob Chang Biol 2013; 19:3111-3122. [PMID: 23749682 DOI: 10.1111/gcb.12288] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2013] [Revised: 05/17/2013] [Accepted: 05/25/2013] [Indexed: 06/02/2023]
Abstract
The rate of vegetation recovery from boreal wildfire influences terrestrial carbon cycle processes and climate feedbacks by affecting the surface energy budget and land-atmosphere carbon exchange. Previous forest recovery assessments using satellite optical-infrared normalized difference vegetation index (NDVI) and tower CO(2) eddy covariance techniques indicate rapid vegetation recovery within 5-10 years, but these techniques are not directly sensitive to changes in vegetation biomass. Alternatively, the vegetation optical depth (VOD) parameter from satellite passive microwave remote sensing can detect changes in canopy biomass structure and may provide a useful metric of post-fire vegetation response to inform regional recovery assessments. We analyzed a multi-year (2003-2010) satellite VOD record from the NASA AMSR-E (Advanced Microwave Scanning Radiometer for EOS) sensor to estimate forest recovery trajectories for 14 large boreal fires from 2004 in Alaska and Canada. The VOD record indicated initial post-fire canopy biomass recovery within 3-7 years, lagging NDVI recovery by 1-5 years. The VOD lag was attributed to slower non-photosynthetic (woody) and photosynthetic (foliar) canopy biomass recovery, relative to the faster canopy greenness response indicated from the NDVI. The duration of VOD recovery to pre-burn conditions was also directly proportional (P < 0.01) to satellite (moderate resolution imaging spectroradiometer) estimated tree cover loss used as a metric of fire severity. Our results indicate that vegetation biomass recovery from boreal fire disturbance is generally slower than reported from previous assessments based solely on satellite optical-infrared remote sensing, while the VOD parameter enables more comprehensive assessments of boreal forest recovery.
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Affiliation(s)
- Matthew O Jones
- The University of Montana Flathead Lake Biological Station, Polson, MT, 59860, USA; Numerical Terradynamic Simulation Group, The University of Montana, Missoula, MT, 59812, USA
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Wade AA, Beechie TJ, Fleishman E, Mantua NJ, Wu H, Kimball JS, Stoms DM, Stanford JA. Steelhead vulnerability to climate change in the
P
acific
N
orthwest. J Appl Ecol 2013. [DOI: 10.1111/1365-2664.12137] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Alisa A. Wade
- National Center for Ecological Analysis and Synthesis 735 State Street, Suite 300 Santa Barbara CA 93101 USA
| | - Timothy J. Beechie
- NOAA Fisheries Northwest Fisheries Science Center 2725 Montlake Boulevard East Seattle WA 98112 USA
| | - Erica Fleishman
- John Muir Institute of the Environment One Shields Avenue University of California Davis CA 95616 USA
| | - Nathan J. Mantua
- NOAA Fisheries Southwest Fisheries Science Center Fisheries Ecology Division, 110 Shaffer Road Santa Cruz CA 95060 USA
| | - Huan Wu
- Flathead Lake Biological Station The University of Montana 32125 Bio Station Lane Polson MT 59860 USA
| | - John S. Kimball
- Flathead Lake Biological Station The University of Montana 32125 Bio Station Lane Polson MT 59860 USA
| | - David M. Stoms
- California Energy Commission 1516 Ninth Street Sacramento CA 95814 USA
| | - Jack A. Stanford
- Flathead Lake Biological Station The University of Montana 32125 Bio Station Lane Polson MT 59860 USA
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Chuang TW, Henebry GM, Kimball JS, VanRoekel-Patton DL, Hildreth MB, Wimberly MC. Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics. Remote Sens Environ 2012; 125:147-156. [PMID: 23049143 PMCID: PMC3463408 DOI: 10.1016/j.rse.2012.07.018] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Environmental variability has important influences on mosquito life cycles and understanding the spatial and temporal patterns of mosquito populations is critical for mosquito control and vector-borne disease prevention. Meteorological data used for model-based predictions of mosquito abundance and life cycle dynamics are typically acquired from ground-based weather stations; however, data availability and completeness are often limited by sparse networks and resource availability. In contrast, environmental measurements from satellite remote sensing are more spatially continuous and can be retrieved automatically. This study compared environmental measurements from the NASA Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and in situ weather station data to examine their ability to predict the abundance of two important mosquito species (Aedes vexans and Culex tarsalis) in Sioux Falls, South Dakota, USA from 2005 to 2010. The AMSR-E land parameters included daily surface water inundation fraction, surface air temperature, soil moisture, and microwave vegetation opacity. The AMSR-E derived models had better fits and higher forecasting accuracy than models based on weather station data despite the relatively coarse (25-km) spatial resolution of the satellite data. In the AMSR-E models, air temperature and surface water fraction were the best predictors of Aedes vexans, whereas air temperature and vegetation opacity were the best predictors of Cx. tarsalis abundance. The models were used to extrapolate spatial, seasonal, and interannual patterns of climatic suitability for mosquitoes across eastern South Dakota. Our findings demonstrate that environmental metrics derived from satellite passive microwave radiometry are suitable for predicting mosquito population dynamics and can potentially improve the effectiveness of mosquito-borne disease early warning systems.
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Affiliation(s)
- Ting-Wu Chuang
- Geographic Information Science Center of Excellence, South Dakota State University, Brookings, SD 57007, United States
| | - Geoffrey M. Henebry
- Geographic Information Science Center of Excellence, South Dakota State University, Brookings, SD 57007, United States
| | - John S. Kimball
- Flathead Lake Biological Station, Division of Biological Sciences, The University of Montana, Polson, MT 59860, United States
| | | | - Michael B. Hildreth
- Department of Biology and Microbiology, South Dakota State University, Brookings, SD 57007, United States
- Department of Veterinary & Biomedical Science, South Dakota State University, Brookings, SD 57007, United States
| | - Michael C. Wimberly
- Geographic Information Science Center of Excellence, South Dakota State University, Brookings, SD 57007, United States
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Zhang K, Kimball JS, Hogg EH, Zhao M, Oechel WC, Cassano JJ, Running SW. Satellite-based model detection of recent climate-driven changes in northern high-latitude vegetation productivity. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2007jg000621] [Citation(s) in RCA: 88] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Abstract
Floodplains are among the world's most threatened ecosystems due to the pervasiveness of dams, levee systems, and other modifications to rivers. Few unaltered floodplains remain where we may examine their dynamics over decadal time scales. Our study provides a detailed examination of landscape change over a 60-year period (1945-2004) on the Nyack floodplain of the Middle Fork of the Flathead River, a free-flowing, gravel-bed river in northwest Montana, USA. We used historical aerial photographs and airborne and satellite imagery to delineate habitats (i.e., mature forest, regenerative forest, water, cobble) within the floodplain. We related changes in the distribution and size of these habitats to hydrologic disturbance and regional climate. Results show a relationship between changes in floodplain habitats and annual flood magnitude, as well as between hydrology and the cooling and warming phases of the Pacific Decadal Oscillation (PDO). Large magnitude floods and greater frequency of moderate floods were associated with the cooling phases of the PDO, resulting in a floodplain environment dominated by extensive restructuring and regeneration of floodplain habitats. Conversely, warming phases of the PDO corresponded with decreases in magnitude, duration, and frequency of critical flows, creating a floodplain environment dominated by late successional vegetation and low levels of physical restructuring. Over the 60-year time series, habitat change was widespread throughout the floodplain, though the relative abundances of the habitats did not change greatly. We conclude that the long- and short-term interactions of climate, floods, and plant succession produce a shifting habitat mosaic that is a fundamental attribute of natural floodplain ecosystems.
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Affiliation(s)
- Diane C Whited
- Flathead Lake Biological Station, Division of Biological Sciences, The University of Montana, 311 Bio Station Lane, Polson, Montana 59860-9659, USA.
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31
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Zhang K, Kimball JS, Zhao M, Oechel WC, Cassano J, Running SW. Sensitivity of pan-Arctic terrestrial net primary productivity simulations to daily surface meteorology from NCEP-NCAR and ERA-40 reanalyses. ACTA ACUST UNITED AC 2007. [DOI: 10.1029/2006jg000249] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Kang S, Kimball JS, Running SW. Simulating effects of fire disturbance and climate change on boreal forest productivity and evapotranspiration. Sci Total Environ 2006; 362:85-102. [PMID: 16364407 DOI: 10.1016/j.scitotenv.2005.11.014] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2005] [Revised: 10/28/2005] [Accepted: 11/01/2005] [Indexed: 05/05/2023]
Abstract
We used a terrestrial ecosystem process model, BIOME-BGC, to investigate historical climate change and fire disturbance effects on regional carbon and water budgets within a 357,500 km(2) portion of the Canadian boreal forest. Historical patterns of increasing atmospheric CO2, climate change, and regional fire activity were used as model drivers to evaluate the relative effects of these impacts to spatial patterns and temporal trends in forest net primary production (NPP) and evapotranspiration (ET). Historical trends of increasing atmospheric CO2 resulted in overall 13% and 5% increases in annual NPP and ET from 1994 to 1996, respectively. NPP was found to be relatively sensitive to changes in air temperature (T(a)), while ET was more sensitive to precipitation (P) change within the ranges of observed climate variability (e.g., +/-2 degrees C for T(a) and +/-20% for P). In addition, the potential effect of climate change related warming on NPP is exacerbated or offset depending on whether these changes are accompanied by respective decreases or increases in precipitation. Historical fire activity generally resulted in reductions of both NPP and ET, which consumed an average of approximately 6% of annual NPP from 1959 to 1996. Areas currently occupied by dry conifer forests were found to be subject to more frequent fire activity, which consumed approximately 8% of annual NPP. The results of this study show that the North American boreal ecosystem is sensitive to historical patterns of increasing atmospheric CO2, climate change and regional fire activity. The relative impacts of these disturbances on NPP and ET interact in complex ways and are spatially variable depending on regional land cover and climate gradients.
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Affiliation(s)
- Sinkyu Kang
- Department of Environmental Science, Kangwon National University, Chunchon, Kangwon-do 200-701, South Korea.
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Potter CS, Wang S, Nikolov NT, McGuire AD, Liu J, King AW, Kimball JS, Grant RF, Frolking SE, Clein JS, Chen JM, Amthor JS. Comparison of boreal ecosystem model sensitivity to variability in climate and forest site parameters. ACTA ACUST UNITED AC 2001. [DOI: 10.1029/2000jd000224] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Keyser AR, Kimball JS, Nemani RR, Running SW. Simulating the effects of climate change on the carbon balance of North American high-latitude forests. Glob Chang Biol 2000; 6:185-195. [PMID: 35026932 DOI: 10.1046/j.1365-2486.2000.06020.x] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The large magnitude of predicted warming at high latitudes and the potential feedback of ecosystems to atmospheric CO2 concentrations make it important to quantify both warming and its effects on high-latitude carbon balance. We analysed long-term, daily surface meteorological records for 13 sites in Alaska and north-western Canada and an 82-y record of river ice breakup date for the Tanana River in interior Alaska. We found increases in winter and spring temperature extrema for all sites, with the greatest increases in spring minimum temperature, average 0.47 °C per 10 y, and a 0.7-day per 10 y advance in ice breakup on the Tanana River. We used the climate records to drive an ecosystem process model, BIOME_BGC, to simulate the effects of climate change on the carbon and water balances of boreal forest ecosystems. The growing season has lengthened by an average of 2.6 days per 10 y with an advance in average leaf onset date of 1.10 days per 10 y. This advance in the start of the active growing season correlates positively with progressively earlier ice breakup on the Tanana River in interior Alaska. The advance in the start of the growing season resulted in a 20% increase in net primary production for both aspen (Populus tremuloides) and white spruce (Picea glauca) stands. Aspen had a greater mean increase in maintenance respiration than spruce, whereas spruce had a greater mean increase in evapotranspiration. Average decomposition rates also increased for both species. Both net primary production and decomposition are enhanced in our simulations, suggesting that productive forest types may not experience a significant shift in net carbon flux as a result of climate warming.
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Affiliation(s)
- A R Keyser
- Numerical Terradynamic Simulation Group, School of Forestry, University of Montana, Missoula, MT 59812, USA
| | - J S Kimball
- Numerical Terradynamic Simulation Group, School of Forestry, University of Montana, Missoula, MT 59812, USA
| | - R R Nemani
- Numerical Terradynamic Simulation Group, School of Forestry, University of Montana, Missoula, MT 59812, USA
| | - S W Running
- Numerical Terradynamic Simulation Group, School of Forestry, University of Montana, Missoula, MT 59812, USA
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Kimball JS, Thornton PE, White MA, Running SW. Simulating forest productivity and surface-atmosphere carbon exchange in the BOREAS study region. Tree Physiol 1997; 17:589-599. [PMID: 14759832 DOI: 10.1093/treephys/17.8-9.589] [Citation(s) in RCA: 48] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
A process-based, general ecosystem model (BIOME-BGC) was used to simulate daily gross primary production, maintenance and heterotrophic respiration, net primary production and net ecosystem carbon exchange of boreal aspen, jack pine and black spruce stands. Model simulations of daily net carbon exchange of the ecosystem (NEE) explained 51.7% (SE = 1.32 g C m(-2) day(-1)) of the variance in daily NEE derived from stand eddy flux measurements of CO(2) during 1994. Differences between measured and simulated results were attributed to several factors including difficulties associated with measuring nighttime CO(2) fluxes and model assumptions of site homogeneity. However, comparisons between simulations and field data improved markedly at coarser time-scales. Model simulations explained 66.1% (SE = 0.97 g C m(-2) day(-1)) of the variance in measured NEE when 5-day means of daily results were compared. Annual simulations of aboveground net primary production ranged from 0.6-2.4 Mg C ha(-1) year(-1) and were concurrent with results derived from tree increment core measurements and allometric equations. Model simulations showed that all of the sites were net sinks (0.1-4.1 Mg C ha(-1) year(-1)) of atmospheric carbon for 1994. Older conifer stands showed narrow margins between uptake of carbon by net photosynthesis and carbon release through respiration. Younger stands were more productive than older stands, primarily because of lower maintenance respiration costs. However, all sites appeared to be less productive than temperate forests. Productivity simulations were strongly linked to stand morphology and site conditions. Old jack pine and aspen stands showed decreased productivity in response to simulated low soil water contents near the end of the 1994 growing season. Compared with the aspen stand, the jack pine stand appeared better adapted to conserve soil water through lower daily evapotranspiration losses but also exhibited a narrower margin between daily net photosynthesis and respiration. Stands subjected to water stress during the growing season may exist on the edge between being annual sources or sinks for atmospheric carbon.
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Affiliation(s)
- John S. Kimball
- School of Forestry/NTSG, University of Montana, Missoula, MT 59812, USA
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