IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0270140.html
   My bibliography  Save this article

Stem girth changes in response to soil water potential in lowland dipterocarp forest in Borneo: An individualistic time-series analysis

Author

Listed:
  • David M Newbery
  • Marcus Lingenfelder

Abstract

Time-series data offer a way of investigating the causes driving ecological processes as phenomena. To test for possible differences in water relations between species of different forest structural guilds at Danum (Sabah, NE Borneo), daily stem girth increments (gthi), of 18 trees across six species were regressed individually on soil moisture potential (SMP) and temperature (TEMP), accounting for temporal autocorrelation (in GLS-arima models), and compared between a wet and a dry period. The best-fitting significant variables were SMP the day before and TEMP the same day. The first resulted in a mix of positive and negative coefficients, the second largely positive ones. An adjustment for dry-period showers was applied. Interactions were stronger in dry than wet period. Negative relationships for overstorey trees can be interpreted in a reversed causal sense: fast transporting stems depleted soil water and lowered SMP. Positive relationships for understorey trees meant they took up most water at high SMP. The unexpected negative relationships for these small trees may have been due to their roots accessing deeper water supplies (if SMP was inversely related to that of the surface layer), and this was influenced by competition with larger neighbour trees. A tree-soil flux dynamics manifold may have been operating. Patterns of mean diurnal girth variation were more consistent among species, and time-series coefficients were negatively related to their maxima. Expected differences in response to SMP in the wet and dry periods did not clearly support a previous hypothesis differentiating drought and non-drought tolerant understorey guilds. Trees within species showed highly individual responses when tree size was standardized. Data on individual root systems and SMP at several depths are needed to get closer to the mechanisms that underlie the tree-soil water phenomena in these tropical forests. Neighborhood stochasticity importantly creates varying local environments experienced by individual trees.

Suggested Citation

  • David M Newbery & Marcus Lingenfelder, 2022. "Stem girth changes in response to soil water potential in lowland dipterocarp forest in Borneo: An individualistic time-series analysis," PLOS ONE, Public Library of Science, vol. 17(6), pages 1-43, June.
    • Handle: RePEc:plo:pone00:0270140
    DOI: 10.1371/journal.pone.0270140
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0270140
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0270140&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0270140?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Cartwright,Nancy, 2007. "Hunting Causes and Using Them," Cambridge Books, Cambridge University Press, number 9780521860819, June.
    2. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    3. Steppe, Kathy & De Pauw, Dirk J.W. & Lemeur, Raoul, 2008. "Validation of a dynamic stem diameter variation model and the resulting seasonal changes in calibrated parameter values," Ecological Modelling, Elsevier, vol. 218(3), pages 247-259.
    4. Zeileis, Achim & Grothendieck, Gabor, 2005. "zoo: S3 Infrastructure for Regular and Irregular Time Series," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i06).
    5. Cartwright,Nancy, 2007. "Hunting Causes and Using Them," Cambridge Books, Cambridge University Press, number 9780521677981, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andrew Gelman & Guido Imbens, 2013. "Why ask Why? Forward Causal Inference and Reverse Causal Questions," NBER Working Papers 19614, National Bureau of Economic Research, Inc.
    2. Courgeau, Daniel, 2012. "Probability and social science : methodologial relationships between the two approaches ?," MPRA Paper 43102, University Library of Munich, Germany.
    3. Massimo Albanese, 2022. "Community Enterprises: Snapshots from Italy," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 8, ejes_v8_i.
    4. Adrian Pabst & Roberto Scazzieri, 2012. "The political economy of civil society," Constitutional Political Economy, Springer, vol. 23(4), pages 337-356, December.
    5. Michael Margolis, 2017. "Graphs as a Tool for the Close Reading of Econometrics (Settler Mortality is not a Valid Instrument for Institutions)," Economic Thought, World Economics Association, vol. 6(1), pages 56-82, March.
    6. Mouchart, Michel & Russo, Federica & Wunsch, Guillaume, 2011. "Inferring causal relations by modelling structures : Article de recherche," LIDAM Discussion Papers ISBA 2011007, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Galbács Peter, 2021. "What did it take for Lucas to set up ‘useful’ analogue systems in monetary business cycle theory?," Economics and Business Review, Sciendo, vol. 7(3), pages 61-82, September.
    8. Emily Chamlee-Wright, 2010. "Qualitative methods and the pursuit of economic understanding," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 23(4), pages 321-331, December.
    9. Pearl Judea, 2018. "Does Obesity Shorten Life? Or is it the Soda? On Non-manipulable Causes," Journal of Causal Inference, De Gruyter, vol. 6(2), pages 1-7, September.
    10. Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.
    11. Padró, R. & Marco, I. & Font, C. & Tello, E., 2019. "Beyond Chayanov: A sustainable agroecological farm reproductive analysis of peasant domestic units and rural communities (Sentmenat; Catalonia, 1860)," Ecological Economics, Elsevier, vol. 160(C), pages 227-239.
    12. Priscilla Álamos-Concha & Valérie Pattyn & Benoît Rihoux & Benjamin Schalembier & Derek Beach & Bart Cambré, 2022. "Conservative solutions for progress: on solution types when combining QCA with in-depth Process-Tracing," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 1965-1997, August.
    13. Georgia Papacharalampous & Hristos Tyralis & Demetris Koutsoyiannis, 2018. "Univariate Time Series Forecasting of Temperature and Precipitation with a Focus on Machine Learning Algorithms: a Multiple-Case Study from Greece," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 5207-5239, December.
    14. Paul Shaffer, 2018. "Causal pluralism and mixed methods in the analysis of poverty dynamics," WIDER Working Paper Series 115, World Institute for Development Economic Research (UNU-WIDER).
    15. John Kay, 2014. "El mapa no es el territorio: un ensayo sobre el estado de la economía," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 16(30), pages 13-24, January-J.
    16. LeRoy, Stephen F, 2024. "Reconsidering Causation," University of California at Santa Barbara, Economics Working Paper Series qt12q3t2vd, Department of Economics, UC Santa Barbara.
    17. Deirdre Nansen McCloskey, 2013. "Why Economics cannot Explain the Modern World," The Economic Record, The Economic Society of Australia, vol. 89, pages 8-22, June.
    18. Hünermund Paul & Louw Beyers & Caspi Itamar, 2023. "Double machine learning and automated confounder selection: A cautionary tale," Journal of Causal Inference, De Gruyter, vol. 11(1), pages 1-12, January.
    19. Magdalena Małecka, 2017. "Posner versus Kelsen: the challenges for scientific analysis of law," European Journal of Law and Economics, Springer, vol. 43(3), pages 495-516, June.
    20. Magdalena Osinska, 2011. "On the Interpretation of Causality in Granger’s Sense," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 129-140.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0270140. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.