Overview of the biology of extreme events Vincent P Gutschick

1. Overview of the biology of extreme events Vincent P Gutschick Global Change Consulting Consortium Las Cruces, NM vince.gutschick@gmail.com) Hormoz BassiriRad Biological Sciences, University of Illinois Chicago, IL hormoz@uic.edu 2008 Fall Meeting American Geophysical Union San Francisco, CA 15-19 December 2008 PowerPoints available at: http://gcconsortium.com/agu08.ppt and ../agu08long.ppt

2. KH Raffa et al., BioScience 58(2008): 501-517 Extreme events are… 1) … rare, and impactful … attention-getting 2003 heat wave in Europe (weeks among decades) - for humans - for atmospheric fluxes Hurricane Katrina (days among decades) Conifer dieoff across Western North America (years among many decades) Rise of atmospheric CO2 (century or so among megayears) Snowball Earth (My among Gy) …and many more ….appearing (but not really) categorically different from (more) normal events  extremity is a distribution

3. Extreme events are… 1) … rare, and impactful … attention-getting 2) Inordinately weighted in the physiology, ecology, and evolution of organisms Hence, also, in biogeochemical cycles Katrina: 0.1 Pg C reinjection expected from tree death Conifer dieoff: 0.3 Pg C reinjection 2003 heat wave in Europe (-NPP, -Rd, -WUE, -APAR; drought) Snowball Earth: end of CH4 atmosphere, major greenhouse Yet, mostly anecdotal to date – no comprehensive framework

4. GF Gravatt, Unasylva 3(1949):3-7) Extreme events are… 1) … rare, and impactful … attention-getting 2) Inordinately weighted in the physiology, ecology, and evolution of organisms 3) Of diverse origins: ● meteorological – heat wave, hurricane ● biotic - evolutionary – Snowball Earth - anthropogenic – land-use change; deforestation  ΔT, ΔP (incl. monsoons) - introduction of exotics (chestnut blight, Dutch elm, Oz rabbits…) ● orbital – ice ages ● tectonic- Toba eruption, 70 kya

5. Extreme events are… 1) … rare, and impactful … attention-getting 2) Inordinately weighted in the physiology, ecology, and evolution of organisms 3) Of diverse origins: meteorological, biotic, orbital, tectonic 4) Occurring/recurrent, over wide scales - of time Mega-years: Snowball Earth, C4 plant evolution (occurring, not recurrent, we trust) Years: Darwin's finches, evolution of beak size Hours or days: flower drop in extreme T events - of space (same examples)

6. JR Ehleringer, Oecologia 95(1993): 340-346 Extreme events are… ……. 5) For biological EEs…and for much of consequent effects on climate, hydrology, etc.: A) Defined by organismal effects, not drivers Chihuahuan desert: heat, drought effects  native vs. introduced B) Physiological in effect – Leaf damage from heat, frost And cascading to the ecological – Cheatgrass and fire regime; pollinator timing And to the evolutionary Toba eruption signature on human genome 20th-year extreme drought: Ci/Ca selected in Encelia farinosa; Other examples (see expanded presentation)

7. Extreme events are… ……. 5) For biological EEs…and for much of consequent effects on climate, hydrology, etc.: A) Defined organismally B) Physiological, ecological, evolutionary C) Likely more important than mean values of conditions Recent manipulative experiments Natural conditions: frosts structuring ecosystems Fitness effects likely concentrated in EEs D) Likely: fitness effects concentrated in the recovery phase Drought recovery: resource acquisition restarts in recovery, not event

8. PM Brown & R Wu, Ecology 86(2005): 3030-3038 Extreme events are… 1) … rare, and impactful … attention-getting 2) Inordinately weighted in the physiology, ecology, and evolution of organisms 3) Of diverse origins: meteorological, biotic, orbital, tectonic 4) Occurring/recurrent, over wide scales of time and space 5) For biological EEs: A) Defined organismally; B) Physiological, ecological, evolutionary; C) More important than “normal” conditions; D) Often more evident in recovery phase 6) Positive as well as negative: e.g., pluvial events for forest reestablishment after fire

9. Aust. J. Plant Physiol. 25(1998): 27-37 Extreme events are… …… 6) Positive as well as negative: e.g., pluvial events for forest reestablishment after fire 7) Generally defined by sequences, not points in time; Order and rate of driver events matters High T's in spring vs. winter; Cold-weather leaf drop in Larrea tridentata of warm deserts High-T flower drop in Opuntia cacti in spring (see earlier slide) Hardening to low T in Eucalyptus pauciflora B) Thus, they are defined as events, not trends Trends admittedly can increase/ decrease probability of pointwise extremes in driving variables, such as T Example of events, with trend overlay: Eucalyptus pauciflora in pastures Time scales important – rise of CO2: trend  event in evolutionary time

10. Extreme events are… …… 5) For biological EEs: A) Defined organismally; B) Physiological, ecological, evolutionary; C) More important than “normal” conditions; D) Often more evident in recovery phase 6) Positive as well as negative: e.g., pluvial events for forest reestablishment after fire (Brown & Wu 05) 7) Generally defined by sequences, not points in time; 8) Often defined by multiple variables (e.g., drought and T, in conifer dieback of 2000 ff.) 9) And by cascades, which may involve other organisms Drought, high T  beetle outbreaks  conifer death Reduced CH status Other examples (see expanded presentation)

11. Extreme events are… …… 7) Generally defined by sequences, not points in time; 8) Often defined by multiple variables (e.g., drought and T, in conifer dieback of 2000 ff.) 9) And by cascades 10 Because of sequence-dependence, multiple correlated drivers, and cascades: challenging to describe statistically -even if only observationally, much less, predictively For defined sequences: ARIMAs, etc. But: who knows the important sequences, as for frost damage? Statistical surprises in observations: now finding heavy tails in floods – other surprises waiting?

12. Science 289(2000): 2068-2074 Extreme events are… …… 7) Generally defined by sequences, not points in time; 8) Often defined by multiple variables (e.g., drought and T, in conifer dieback of 2000 ff.) 9) And by cascades 10) Because of sequence-dependence, multiple correlated drivers, and cascades: hard to do statistics upon 11) Changing in spectrum A) Drivers themselves, as shifts in PDFs – e.g., extremes in precipitation Annual amounts, or heavy events B) Crossing thresholds – recasting of even the form of PDFs Non-analog climates Thermohaline circulation shutdown in past, and perhaps in future  New “normals” can constitute extremes for extant genotypes

13. SJ Crafts-Brandner & ME Salvucci, Plant Physiol. 129(2002): 1773-1780 Extreme events are… …… 8, 9, 10) Often defined by multiple variables, cascades  challenging statistics 11) Changing in spectrum 12) Thus, challenging to predict for effects E.g, “March of the trees” with rising CO2 & climate change: - Potential effects on radiative balance and biogeochemical fluxes Responses arein physiological time, of the individual organism: Physiological & ecological responses to EEs: poorly known Acclimation is response - may reach limits in rates (Rubisco activase in maize) or amounts  dysacclimation as a definable extreme) Direct responses to CO2 :poorly known, and extremely variable  potential biogeographic chaos (VP Gutschick, Ecol. Mod. 200(2007): 433–451)

14. Extreme events are… … 12) Thus, challenging to predict for effects A, B) radiative balance, biogeochemical fluxes; physiological time C) Response in evolutionary time – nuanced, at the very least: Responses are constrained by population genetic structure Who says responses are adaptive? (the organisms’ “toolkits” are limited) Most genetic variation is neutral, nonadaptive (Kimura, 1983 ff.) Adaptive responses to high CO2 – almost all lost in 20 My – N dynamics D) How good are our predictive capacities fordrivers of EEs? Point events – observations (return times) – good Correlated multiple variabales – in development GCMs’ abilities to capture spectrum (PDF) of point events – fair GCMs’ abilities to capture sequences that define EEs – unknown Biotic effects, such as disease prevalence- !! Annual mean precip. JP Iorio et al., Climate Dyn. 23(2004): 243-258

15. Recap: lots of specifics to account for, lots of conceptual • and mathematical challenges • (Blue = needed for a conceptual framework) • * Inordinately weighted in physiology / ecology / evolution / biogeochem cycles • * Diverse in origins * Diverse in scales of time & space • * Defined by organismal response, not drivers • * Likely more important than mean values * Can be positive, too • * Defined by sequences, not points; multiple variables; cascades • * Challenging for statistics * Changing in spectrum • * Challenging in knowing organismal responses, even for adaptiveness • * Challenging to capture proper statistics in their (meteorological…) drivers

16. We need observational tools, and, more so, a comprehensive framework, with * biology: physiology, ecology, evolution * meteorology and climatology * statistics Who's going to plan it? OR will we default and live with greater uncertainty than we need to for prevention and amelioration? PowerPoints available at: http://gcconsortium.com/agu08.ppt and ../agu08long.ppt