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Physiological idiosyncrasies and extreme events
- two gaps in models of vegetation change
several
Vincent P. Gutschick
Global Change Consulting Consortium, Inc.
Hormoz BassiriRad
Biological Sciences, University of Illinois, Chicago
Session B21C. Adaptation of Vegetation to Changes in Environmental Forcing II
Tuesday, 15 Dec. 2009
Scope of discussion:
● Terrestrial
● Plants (other kingdoms where intrinsically linked to plants)
Principal ideas:
Models of biogeographic change are mandated for planning mitigation and
societal adaptation
DGVMs get current and paleo biomes fairly well, yet…
How much ex tuning?
Species level weak; community assembly
rules are also weak.
Current changes greater in # and rate
Positing biogeographic primarily on the abiotic environment
(temperature, precipitation - including seasonality of these –
and biogeochemistry) misses major effects in ecology, physiology,
and evolution
Empirical studies of biogeography have emphasized the abiotic environment,
while theoretical studies have emphasized the biotic (gene flow, local
adaptation, dispersal, etc.) (Roy et al., 2009)
What is missed?
• Ecological processes are important
• Only weakly correlated with abiotic environment
• Direct effects of CO2 vary dramatically among species
• Genetic adaptation:
• Occurs diffferentially among species
• Restructures ecological processes, thus, also the niches
• Has at least 5 underappreciated characteristics
• Extreme events may be more important than means for realized niche.
Their nature differs markedly from what is captured in even
advanced statistics of weather sequences
Ecological processes – dispersal dynamics, plus…
• Competition
• In some DGVMs
• Yet, competitive rankings are multi-dimensional
• E.g., resource acquisition, resource use – for multiple
resources … and GCC-induced changes are not in
parallel in the different dimensions
• May also be non-transitive  require individual-based
models
• Converse exists: nurse-plant effect
• Disease, disease hosting and vectoring, pests (esp. herbivores)
• Currently map approximately to climate / remain only
implicit in DGVMs
• Have changed ranges – e.g., bird malaria in Hawaii
• Accidental introductions remap ranges / are highly
unpredictable in effect
• Changes of D & P ranges not necessarily parallel to
changes in host climatic-range changes
• Pollinator and disperser activity
• Offsets from flowering & fruiting already observed
Direct effects of elevated CO2 other than on
photosynthesis alone
• Are numerous
gs ↓ (Ball-Berry-Leuning-Dewar) Tleaf ↑, WUE
fN ↓ (functional balance)
(physics)
A ↑, PNUE ↑ (Farquhar et al.)
• Yet vary dramatically among species, even within functional
groups
• Humidity response of gs
• N uptake
• Shift competitive performance (fitness, more generally)
Accounting for shifts and their diversity in models requires
significant complexity in algorithms
Genetic adaptation contributes to biogeographic shifts
• Importance varies according to (CO2 rise time)/(generation time)
• Genetic variation must be high or supplied at high rates to avoid
extinction (e.g., Bell and Collins, 2008)
• Frequency of adverse change more important than severity (ibid.)
• Adaptive variation for performance at high CO2 has been largely
lost
• Selection is not simple, nor simply predicted based on current
correlations of traits with environment
• Genetic constraints (linkages, esp.) on evolution can be severe
- adaptive complexes differ between environments
• Will selection be directional, relaxed, or diversifying? (Aviolo,
2008)
• Meiotic drive can favor allele segregation
• DNA methylation alters gene expression, hence, selection 
maternal effects, e.g.
• Local adaptation can be a trap as biogeographic zones move
Extreme events may be more important than
means for realized niche
• Their nature differs markedly from what is captured in
even advanced statistics of weather sequences
• Specific to organism and genotype
• Primarily arise from exceeding phenotypic acclimation
bounds
• Temporal sequences are critical
• Cross-correlations in environmental variables matter, as
shown in 2001-4 bark beetle outbreaks
• Biotic overlays occur, as with 2001-4 bark beetle outbreak
• Recovery phase may embody most of fitness effects
• The spectrum of biological extreme events is complex
• May not correlate with mean climate
• Spectrum is changing as climate changes
What is being done?
• Physics of climate regimes being done well
• Also, some physiology, but far from enough
• Very little full ecology, esp. of disease and pests
What can be done?
• Realign theory and experiment
• E.g., resolve discrepancy - complex patterns of good genetic
correlations with abiotic factors such as temperature but
poor correlations of metabolomes with abiotic factors (Kunin et al. ,2009)
• Consider managed ecosystems? Now dominate! / also affect realized
niches of wild plants
• Make realistic plans for combined post-hoc analyses and
predictive capabilities
Make realistic plans
• Past attempts at predictions + testing: how many? what quality?
• Can we handle the complexity? Even as a computing grand challenge?
• Even more than power, need the data!
 Pin down the main sources of variance, vs. trying to make
a comprehensive model
• Winnow all the complexities outlined here
Expectations:
• Need big research investment – NEON++
• Expect low skill in short-term predictions, more in long term
Grow in skill as did weather prediction – too late for some changes, but
in time for others
• Task: respond, more than predict, for next few decades