Quantifying ecological memory in plant and ecosystem processes

Kiona Ogle, Jarrett J. Barber, Greg A. Barron-Gafford, Lisa Patrick Bentley, Jessica M. Young, Travis E. Huxman, Michael E. Loik, David T. Tissue

Research output: Contribution to journalArticle

106 Citations (Scopus)

Abstract

The role of time in ecology has a long history of investigation, but ecologists have largely restricted their attention to the influence of concurrent abiotic conditions on rates and magnitudes of important ecological processes. Recently, however, ecologists have improved their understanding of ecological processes by explicitly considering the effects of antecedent conditions. To broadly help in studying the role of time, we evaluate the length, temporal pattern, and strength of memory with respect to the influence of antecedent conditions on current ecological dynamics. We developed the stochastic antecedent modelling (SAM) framework as a flexible analytic approach for evaluating exogenous and endogenous process components of memory in a system of interest. We designed SAM to be useful in revealing novel insights promoting further study, illustrated in four examples with different degrees of complexity and varying time scales: stomatal conductance, soil respiration, ecosystem productivity, and tree growth. Models with antecedent effects explained an additional 18-28% of response variation compared to models without antecedent effects. Moreover, SAM also enabled identification of potential mechanisms that underlie components of memory, thus revealing temporal properties that are not apparent from traditional treatments of ecological time-series data and facilitating new hypothesis generation and additional research.

Original languageEnglish (US)
Pages (from-to)221-235
Number of pages15
JournalEcology Letters
Volume18
Issue number3
DOIs
StatePublished - Mar 1 2015

Fingerprint

antecedent conditions
ecosystems
ecosystem
modeling
ecologists
soil respiration
stomatal conductance
time series
ecology
timescale
productivity
tree growth
history
time series analysis
effect
rate

Keywords

  • Antecedent conditions
  • Hierarchical Bayesian model
  • Lag effects
  • Legacy effects
  • Net primary production
  • Soil respiration
  • Stomatal conductance
  • Time-series
  • Tree growth
  • Tree rings

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics

Cite this

Ogle, K., Barber, J. J., Barron-Gafford, G. A., Bentley, L. P., Young, J. M., Huxman, T. E., ... Tissue, D. T. (2015). Quantifying ecological memory in plant and ecosystem processes. Ecology Letters, 18(3), 221-235. https://doi.org/10.1111/ele.12399

Quantifying ecological memory in plant and ecosystem processes. / Ogle, Kiona; Barber, Jarrett J.; Barron-Gafford, Greg A.; Bentley, Lisa Patrick; Young, Jessica M.; Huxman, Travis E.; Loik, Michael E.; Tissue, David T.

In: Ecology Letters, Vol. 18, No. 3, 01.03.2015, p. 221-235.

Research output: Contribution to journalArticle

Ogle, K, Barber, JJ, Barron-Gafford, GA, Bentley, LP, Young, JM, Huxman, TE, Loik, ME & Tissue, DT 2015, 'Quantifying ecological memory in plant and ecosystem processes', Ecology Letters, vol. 18, no. 3, pp. 221-235. https://doi.org/10.1111/ele.12399
Ogle K, Barber JJ, Barron-Gafford GA, Bentley LP, Young JM, Huxman TE et al. Quantifying ecological memory in plant and ecosystem processes. Ecology Letters. 2015 Mar 1;18(3):221-235. https://doi.org/10.1111/ele.12399
Ogle, Kiona ; Barber, Jarrett J. ; Barron-Gafford, Greg A. ; Bentley, Lisa Patrick ; Young, Jessica M. ; Huxman, Travis E. ; Loik, Michael E. ; Tissue, David T. / Quantifying ecological memory in plant and ecosystem processes. In: Ecology Letters. 2015 ; Vol. 18, No. 3. pp. 221-235.
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