Skip to main content
SpringerLink
Log in

Attributing interannual variability of net ecosystem exchange to modeled ecological processes in forested wetlands of contrasting stand age

  • Research Article
  • Published:
Landscape Ecology Aims and scope Submit manuscript

Abstract

The drivers of interannual variability (IAV) of net ecosystem exchange (NEE) in forested wetlands are poorly understood, making it difficult to predict changes in atmospheric fluxes in response to land use and climate change. Similarly, these ecosystems demonstrate dynamic physiological and phenological responses to climate over time yet are typically modeled using static parameters that represent unchanging ecological conditions. Though static first-order ecosystem models are informative, they fundamentally lack the ability to represent dynamic annual changes in ecological processes that may drive IAV of NEE through time. We aimed to improve understanding of how forested wetlands dynamically respond to climate and which key ecological processes may contribute to IAV of NEE. Simultaneously, we aimed to develop tools to evaluate dynamically parameterized process based first-order ecosystem models. To achieve these objectives, long-term ecological data were fused with the Total Ecosystem (TECO) model in three loblolly pine plantations and a bottomland hardwood forest of contrasting stand age in wetland areas of the lower coastal plain of North Carolina. Variance decomposition was used to assess changes in large-scale ecosystem drivers. To investigate individual processes, both static and dynamic data-assimilation were conducted to simulate time–invariant and time–varying ecological response. Anomalies in dynamic ecosystem process response were correlated with NEE anomalies to attribute IAV of NEE to underlying process-based mechanisms that may drive annual changes in NEE across stand age and sites. Assessment of large-scale drivers of IAV of NEE across sites demonstrated that maximum carbon uptake (MCU) dominated IAV of NEE in the mature pine plantation. These large-scale NEE signals were further parsed into ecological processes in the TECO model, where process anomaly correlation showed that slight variations in root maintenance respiration and woody biomass turnover rates may be underlying drivers of IAV of MCU and subsequently NEE. However, in the young pine plantations and bottomland hardwood forest IAV of NEE was not dominated by MCU. In contrast, IAV of NEE in young plantations was influenced most by annual changes in maximum carbon release (MCR) and carbon uptake period (CUP), while IAV of NEE in the bottomland hardwood forest was dominated by CUP. These results demonstrate that dynamic data assimilation (DA), variance decomposition, and process anomaly correlation are investigative and diagnostic tools for process-based models, though maximum GPP was systematically underestimated by models across sites. Despite problems with peak GPP representation, anomaly correlation between ecological processes and IAV of NEE allowed investigation of the specific ecological drivers of annual variability in ecosystem-level carbon exchange. As ecosystems show dynamic physiological and phenological properties through time, it may be important to allow models to have dynamic/time–varying ecological responses, especially if the root causes of IAV of NEE are to be attributed to ecological processes in process-based models.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Aguilos M, Mitra B, Noormets A, Minick K, Prajapati P, Gavazzi M, Sun G, McNulty S, Li X, Domec J-C, Miao G, King J (2020) Long-term carbon flux and balance in managed and natural coastal forested wetlands of the Southeastern USA. Agric For Meteorol 288:108022

    Article  Google Scholar 

  • Aguilos M, Sun G, Noormets A, Domec JC, McNulty S, Gavazzi M, Minick K, Mitra B, Prajapati P, Yang Y, King J (2021) Effects of land-use change and drought on decadal evapotranspiration and water balance of natural and managed forested wetlands along the southeastern US lower coastal plain. Agric for Meteorol 303:108381

    Article  Google Scholar 

  • Ahlström A, Raupach MR, Schurgers G, Smith B, Arneth A, Jung M, Reichstein M, Canadell JG, Friedlingstein P, Jain AK, Kato E, Poulter B, Sitch S, Stocker BD, Viovy N, Wang YP, Wiltshire A, Zaehle S, Zeng N (2015) The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink. Science 348(6237):895–899

    Article  PubMed  Google Scholar 

  • Ball JT, Woodrow IE, Berry JA (1987) A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions. In: Biggins J (ed) Progress in Photosynthesis Research, vol 4. Proceedings of the VIIth International Congress on Photosynthesis ProvidenceRhode Island. USA, Springer, Netherlands, pp 221–224

    Chapter  Google Scholar 

  • Chmura GL, Anisfeld SC, Cahoon DR, Lynch JC (2003) Global carbon sequestration in tidal. Glob Biogeochem Cycles https://doi.org/10.1029/2002GB001917

    Article  Google Scholar 

  • Churkina G, Schimel D, Braswell BH, Xiao X (2005) Spatial analysis of growing season length control over net ecosystem exchange. Glob Change Biol 11(10):1777–1787

    Article  Google Scholar 

  • Day JW, Christian RR, Boesch DM, Yáñez-Arancibia A, Morris J, Twilley RR, Naylor L, Schaffner L, Stevenson C (2008) Consequences of climate change on the ecogeomorphology of Coastal Wetlands. Estuaries Coasts 31(3):477–491

    Article  Google Scholar 

  • Domec JC, King JS, Ward E, Christopher Oishi A, Palmroth S, Radecki A, Bell DM, Miao G, Gavazzi M, Johnson DM, McNulty SG, Sun G, Noormets A (2015) Conversion of natural forests to managed forest plantations decreases tree resistance to prolonged droughts. For Ecol Manag 355:58–71

    Article  Google Scholar 

  • Dragoni D, Schmid HP, Wayson CA, Potter H, Grimmond CSB, Randolph JC (2011) Evidence of increased net ecosystem productivity associated with a longer vegetated season in a deciduous forest in south-central Indiana, USA. Glob Change Biol 17:886–897

    Article  Google Scholar 

  • Farquhar GD, von Caemmerer S, Berry JA (1980) A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149(1):78–90

    Article  CAS  PubMed  Google Scholar 

  • Fu Z, Dong J, Zhou Y, Stoy PC, Niu S (2017) Long term trend and interannual variability of land carbon uptake-the attribution and processes. Environ Res Lett 12(1):014018

    Article  Google Scholar 

  • Fu Z, Stoy PC, Poulter B, Gerken T, Zhang Z, Wakbulcho G, Niu S (2019) Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange. Glob Change Biol 25(10):3381–3394

    Article  Google Scholar 

  • Ichii K, Hashimoto H, Nemani R, White M (2005) Modeling the interannual variability and trends in gross and net primary productivity of tropical forests from 1982 to 1999. Glob Planet Change 48(4):274–286

    Article  Google Scholar 

  • Jung M, Reichstein M, Schwalm CR, Huntingford C, Sitch S, Ahlstrom A, Arneth A, Camps-Valls G, Ciais P, Friedlingstein P, Gans F, Ichii K, Ain AKJ, Kato E, Papale D, Poulter B, Raduly B, Rodenbeck C, Tramontana G, Zeng N (2017) Compensatory water effects link yearly global land CO2 sink changes to temperature. Nature 541(7638):516–520

    Article  CAS  PubMed  Google Scholar 

  • King JS, Albaugh TJ, Allen HL, Kress LW (1999) Stand-level allometry in Pinus taeda as affected by irrigation and fertilization. Tree Physiol 19(12):769–778

    Article  CAS  PubMed  Google Scholar 

  • Le Quéré C, Andrew RM, Friedlingstein P, Sitch S, Pongratz J, Manning AC, Korsbakken JI, Peters GP, Canadell JG, Jackson RB, Boden TA, Tans PP, Andrews OD, Arora VK, Bakker DCE, Barbero L, Becker M, Betts RA, Bopp L, Zhu D (2018) Global Carbon Budget 2017. Earth Syst Sci Data 10(1):405–448

    Article  Google Scholar 

  • Luo Y, Schuur EAG (2020) Model parameterization to represent processes at unresolved scales and changing properties of evolving systems. Glob Change Biol 26(3):1109–1117

    Article  Google Scholar 

  • Magnani F, Mencuccini M, Borghetti M, Berbigier P, Berninger F, Delzon S, Grelle A, Hari P, Jarvis PG, Kolari P, Kowalski AS, Lankreijer H, Law BE, Lindroth A, Loustau D, Manca G, Moncrieff JB, Rayment M, Tedeschi V, Grace J (2007) The human footprint in the carbon cycle of temperate and boreal forests. Nature 447(7146):849–851

    Article  CAS  Google Scholar 

  • Miao G, Noormets A, Domec JC, Fuentes M, Trettin CC, Sun G, McNulty SG, King JS (2017) Hydrology and microtopography control carbon dynamics in wetlands: implications in partitioning ecosystem respiration in a coastal plain forested wetland. Agric for Meteorol 247:343–355

    Article  Google Scholar 

  • Mkhabela MS, Amiro BD, Barr AG, Black TA, Hawthorne I, Kidston J, McCaughey JH, Orchansky AL, Nesic Z, Sass A, Shashkov A, Zha T (2009) Comparison of carbon dynamics and water use efficiency following fire and harvesting in canadian boreal forests. Agric for Meteorol 149(5):783–794

    Article  Google Scholar 

  • Moreno-Mateos D, Power ME, Comín FA, Yockteng R (2012) Structural and functional loss in restored Wetland Ecosystems. PLoS Biol 10(1):e1001247

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Noormets A, Chen J, Crow TR (2007) Age-dependent changes in ecosystem carbon fluxes in managed forests in Northern Wisconsin. USA Ecosyst 10(2):187–203

    Article  CAS  Google Scholar 

  • Noormets A, Gavazzi MJ, McNulty SG, Domec JC, Sun GE, King JS, Chen J (2010) Response of carbon fluxes to drought in a coastal plain loblolly pine forest. Glob Change Biol 16(1):272–287

    Article  Google Scholar 

  • Noormets A, McNulty SG, Domec J-C, Gavazzi M, Sun G, King JS (2012) The role of harvest residue in rotation cycle carbon balance in loblolly pine plantations. Glob Change Biol 18(10):3186

    Article  Google Scholar 

  • Poulter B, Frank D, Ciais P, Myneni RB, Andela N, Bi J, Broquet G, Canadell JG, Chevallier F, Liu YY, Running SW, Sitch S, van der Werf GR (2014) Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature 509(7502):600–603

    Article  CAS  PubMed  Google Scholar 

  • Pregitzer KS, Euskirchen ES (2004) Carbon cycling and storage in world forests: biome patterns related to forest age. Glob Change Biol 10(12):2052–2077

    Article  Google Scholar 

  • Schwalm CR, Black TA, Morgenstern KAI, Humphreys ER (2007) A method for deriving net primary productivity and component respiratory fluxes from tower-based eddy covariance data: a case study using a 17-year data record from a Douglas-fir chronosequence. Glob Change Biol 13(2):370–385

    Article  Google Scholar 

  • Shao J, Zhou X, Luo Y, Li B, Aurela M, Billesbach D, Blanken PD, Bracho R, Chen J, Fischer M, Fu Y, Gu L, Han S, He Y, Kolb T, Li Y, Nagy Z, Niu S, Oechel WC, Zhang J (2015) Biotic and climatic controls on interannual variability in carbon fluxes across terrestrial ecosystems. Agric for Meteorol 205:11–22

    Article  Google Scholar 

  • Wang YP, Leuning R (1998) A two-leaf model for canopy conductance, photosynthesis and partitioning of available energy I: model description and comparison with a multi-layered model. Agric for Meteorol 91(1):89–111

    Article  Google Scholar 

  • Wang X, Piao S, Ciais P, Friedlingstein P, Myneni RB, Cox P, Heimann M, Miller J, Peng S, Wang T, Yang H, Chen A (2014) A two-fold increase of carbon cycle sensitivity to tropical temperature variations. Nature 506(7487):212–215

    Article  CAS  PubMed  Google Scholar 

  • Weng E, Luo Y (2008) Soil hydrological properties regulate grassland ecosystem responses to multifactor global change: a modeling analysis  J Geophysical Res. https://doi.org/10.1029/2007JG000539

    Article  Google Scholar 

  • White E, Kaplan D (2017) Restore or retreat? Saltwater intrusion and water management in coastal wetlands. Ecosyst Health Sustain 3(1):e01258

    Article  Google Scholar 

  • Wutzler T, Lucas-Moffat A, Migliavacca M, Knauer J, Sickel K, Šigut L, Menzer O, Reichstein M (2018) Basic and extensible post-processing of eddy covariance flux data with REddyProc. Biogeosciences 15:5015

    Article  CAS  Google Scholar 

  • Xia J, Niu S, Ciais P, Janssens IA, Chen J, Ammann C, Arain A, Blanken PD, Cescatti A, Bonal D, Buchmann N, Curtis PS, Chen S, Dong J, Flanagan LB, Frankenberg C, Georgiadis T, Gough CM, Hui D, Luo Y (2015) Joint control of terrestrial gross primary productivity by plant phenology and physiology. Proceedings Natl Acad Sci United States of America 112:2788

    Article  CAS  Google Scholar 

  • Zhou S, Zhang Y, Caylor KK, Luo Y, Xiao X, Ciais P, Huang Y, Wang G (2016) Explaining inter-annual variability of gross primary productivity from plant phenology and physiology. Agric For Meteorology 226:246–256

    Article  Google Scholar 

  • Zhou S, Zhang Y, Ciais P, Xiao X, Luo Y, Caylor KK, Huang Y, Wang G (2017) Dominant role of plant physiology in trend and variability of gross primary productivity in North America. Sci Rep 7(1):41366

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zscheischler J, Fatichi S, Wolf S, Blanken PD, Bohrer G, Clark K, Desai AR, Hollinger D, Keenan T, Novick KA, Seneviratne SI (2016) Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes. J Geophys Res 121(8):2186–2198

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank the many funding agencies that have provided long-term support for field-based measurements and further model-based investigation of these sites. We also acknowledge the many researchers who were instrumental in long-term support of ecological sites and measurements over the last two decades.

Funding

Modeling work supported by US National Science Foundation (DEB 1655499, DEB 2017884). Primary support for field research was provided by USDA NIFA (Multi-agency A.5 Carbon Cycle Science Program) award 2014-67003-22068. Additional support was provided by DOE NICCR award 08-SC-NICCR-1072, the USDA Forest Service award 13-JV-11330110-081, and DOE LBNL award M1900080. 

Author information

Authors and Affiliations

  1. Center for Ecosystem Sciences and Society, Northern Arizona University, Flagstaff, AZ, USA

    Jon M. Wells, Xin Huang & Yuan Gao

  2. Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, USA

    Maricar Aguilos & John King

  3. School of informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA

    Xin Huang

  4. Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China

    Enqing Hou

  5. Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA

    Wenjuan Huang

  6. Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China

    Cuijuan Liao & Lin Lin

  7. College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China

    Ruiying Zhao

  8. Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA

    Han Qiu

  9. Department of Ecosystem Science and Management, Texas A&M University, College Station, TX, USA

    Asko Noormets

  10. Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA

    Lifen Jiang & Yiqi Luo

  11. School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA

    Keanan Allen, Lifen Jiang & Yiqi Luo

Authors
  1. Jon M. Wells
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maricar Aguilos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xin Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuan Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Enqing Hou
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wenjuan Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Cuijuan Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Lin Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ruiying Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Han Qiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Keanan Allen
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. John King
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Asko Noormets
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Lifen Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Yiqi Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

JW: Conceptualization, Methodology, Software, Validation, Formal analysis, Writing—Original draft, visualization MMA: Conceptualization, methodology, data curation, Writing—Review & Editing XH: Conceptualization, Methodology, Software, Writing—Review & Editing. YG: Conceptualization, Methodology, Software, Writing—Review & Editing EH: Conceptualization, Methodology, Software, Writing—Review & Editing WH: Conceptualization, Methodology, Writing—Review & Editing CL: Conceptualization, Methodology, Writing—Review & Editing LL: Conceptualization, Methodology, Writing—Review & Editing RZ: Conceptualization, Methodology, Writing—Review & Editing. HQ: Conceptualization, Methodology, Writing—Review & Editing KA: Conceptualization, Methodology, Writing—Review & Editing JSK: Conceptualization, Resources, Funding Acquisition, Writing—Review & Editing AN: Conceptualization, Resources, Funding Acquisition, Writing—Review & Editing LJ: Conceptualization, Methodology, Resources, Supervision, Project administration, Funding Acquisition, Writing—Review & Editing YL: Conceptualization, Methodology, Resources, Supervision, Project administration, Funding Acquisition, Writing—Review & Editing.

Corresponding author

Correspondence to Jon M. Wells.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 17.6 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wells, J.M., Aguilos, M., Huang, X. et al. Attributing interannual variability of net ecosystem exchange to modeled ecological processes in forested wetlands of contrasting stand age. Landsc Ecol 38, 3985–3998 (2023). https://doi.org/10.1007/s10980-023-01768-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10980-023-01768-x

Keywords

Search

Navigation