GC13G-1230
Can we Detect Ecosystem Critical Transitions and Early Warning Signals of Catastrophic Shifts from Palaeo-Ecological Records?

Monday, 14 December 2015
Poster Hall (Moscone South)
Marie-Eloide Perga1, Zofia Ecaterina Taranu2, Irene Gregory-Eaves3, Victor Frossard1, Zoe Thomas4, Pierre Legendre2, N John Anderson5, Peter Leavitt6 and Peter Gell7, (1)Inst Nat Recherche Agronomique, CARRTEL, Université de Savoie, Thonon-les-bains, France, (2)University of Montreal, Biological Sciences, Montreal, QC, Canada, (3)McGill University, Department of Biology, Montreal, QC, Canada, (4)University of New South Wales, Sydney, Australia, (5)University College, London, United Kingdom, (6)University of Regina, Regina, Canada, (7)Federation University Australia, Water Research Network, Ballarat, Australia
Abstract:
The observation that managed ecosystems often fail to respond smoothly to changing external pressures has shed some light on their complex non-linear dynamics. The concept of critical transitions (i.e., ecosystem regime shifts), thresholds and alternative stable states has since spread to the ecological and environmental management literature. Most recently, however, reviews have raised some skepticism about whether these catastrophic transitions are the exceptions rather than the rule. Overall, a better understanding of the occurrence and processes of such critical transitions requires more empirical testing and evidence on the mechanistic links between pressures and consequent ecological change. Many of the changes observed, or modeled, by ecologists extend beyond the monitoring record. Palaeo-ecological records thus represent a unique opportunity to extend our temporal perspective to the relevancy of critical transitions. Yet, paleo-ecological records have their own biases and shortcomings, such as sediment focusing, irregular temporal integration and often studied in a semi-quantitative way. As such, palaeo-ecological time series are not strictly analogous to instrumental datasets. In this work, we aimed to test, using both modeled and actual records, how different properties that are common in palaeo-ecological records affect our ability to detect past non-linear dynamics, such as early-warning signals of catastrophic shifts.