Transcript 2007 - Global Change Consulting Consortium, Inc.

3
5
B43B-1159
Predictability and detectability of biogeographic changes in plant distributions
Vincent P. Gutschick, Dept. of Biology, New Mexico State Univ., Las Cruces, NM 88003
and Global Change Consulting Consortium, Las Cruces, NM
4
Abstract:
Rapid climatic changes are envisioned as atmospheric composition is changed by
human activities. These changes have long been predicted to drive large-scale changes in
the distribution of plants and of all their associated biota. The direct effects of increasing
atmospheric CO2 on photosynthesis, transpiration, and nutrient dynamics have also
been predicted to alter the abundance and density of whole functional groups of plants,
particularly those differing in photosynthetic pathways (increases in C3 plants at the
expense of C4s, as one considerable simplification). In recent work, I have pointed out
major physiological diversity among individual plant species in their direct responses to
elevated CO2. The consequences include considerable fragmentation in migration
patterns of plant species over decades to centuries. Refining the predictions is a
daunting task largely in the areas of physiology, ecology, and evolution. Detecting the
changes for validation of predictions and for management/ response strategies is
similarly a major challenge. Many changes in plant performance and distribution driven
directly by climate and CO2 are modest to date, given the modest scale of changes in these
two drivers over decadal time scales amenable to both field studies and remote sensing.
Large-scale changes, such as in growing season, have occurred but species details
have not been resolved in observations with global, repeated coverage. Additional largescale studies, to merge with small-scale studies, are needed. I review briefly the feasibility of
remote-sensing studies for such purposes. For limited campaigns, there is the potential for
resolving species by spectral signature, using advance hyperspectral sensing coupled with
biophysical models. More general remote-sensing technologies allow detecting shifts
between functional types (e.g., grass/woodland) at ecotones, and shifts at all locations in
physiological stresses - particularly water stress in its temporal and spatial spectra - directly
or via changes in gross primary productivity.
1
2
The need for predictability, and detectablity, of changes in biogeogaphic
distributions of plants (and associated biota): some “starter” questions:
For native vegetation per se  Discerning signs of imminent loss of some
ecosystem services; improving the design of conservation areas
For agriculture (where distribution is admittedly under conscious control)
 Discerning shifts in relative fitness of weeds vs. crops
For climatology and hydrology (longer term)  Setting proper boundary
conditions for future scenarios in GCMs and related models
Developing testable hypotheses to guide research:
E.g., H: Predictability and detectability of biogeographic changes
driven by changes in P, T, and CO2 mixing ratio are currently
both low (see below),
Both will be significantly improved by
* Physiological ecology models of plant responses to T, P, and
esp. CO2 by individual species – or new “climate-change” functional
groups- with direct responses of plants to CO2 being the least
appreciated but, I propose, the most significant
* Explicit physiological ecology of plant responses to extreme events
- not to mean T, P, etc.
- not to extremes defined in meteorological drivers, but defined in
biotic terms (Gutschick and BassiriRad, New Phytologist, 2003)
* Delineation of new functional groups of plant species, based on
their evolutionary ecology: genetic variation for adaptive responses
to high CO2 disappeared long ago, from lack of selection pressure;
only correlations to adaptive responses to T and P variations remain,
and these must be sought
* Hyperspectral sensing (aircraft-based or with Hyperion) , capable of
resolving plant species or groups spectrally and by phenology
 Potential coverage is limited by small fields of view, limited
repeat coverage, and the need for extensive ground data on
optics of leaves, litter, etc.
 Use advance statistical design
- hierarchical/ nested sampling
- targeted to species most likely to change and of greatest
functional significance for ecosystem services, hydrology,
and climatology
-A focus on invasive species is one tack; changes among
indigenous wild (native) vegetation in another, as is managed
change of crop species
3
Detectability remains low or very restricted among species and geographic
First, is there much to detect yet?
Some major biomes change inherently slowly (boreal forests)
…except under extremes, such as the 2002 conifer dieoff in the US SW!
- climatically initiated, mediated by insects and disease
Predictability is currently low, for changes in biogeographic distribution and in
species abundance regarded in their being driven by changes in climate and in
direct CO2 mixing ratio
* Changes in the meteorological drivers, primarily T & P, are challenging to predict
- GCMs show significant divergence among selves, esp. in US SW, Mediterranean
- Another emergent pattern to worry about: no-analog climates (e.g., Williams
et al., PNAS, 2007 and earlier)
* Diversity in plant responses to climatic changes is pronounced
- Ex biotic interactions (Loehle and Leblanc) – there exists a huge number of
pairwise interactions among plant spp., and even more with pollinators, etc.
- Ex extremes as strong selectors; some plants are at limits currently, others aren’t FIG
We have negligible knowledge of true limits or population diversity in same
* There is similar or greater diversity in direct responses to CO2 mixing ratio
- Diversity among plant species has been demonstrated in direct effects on N
uptake, e.g
….and thus, on photosynthesis (A),
stomatal conducance (gs) consequent
transpiration (E), water-use efficiency (WUE),
N-use efficiency (PNUE), N-“sparing”
(1/N content)
 Competitive standings are set to change
markedly, even among species within a classic
functional group (C3 shrubs, C4 grasses, …)
 Can we find new functional groups, vs.
morphotype and PS pathway?
…and perhaps we should count worldwide grassland  shrubland transition
…and diseases, such as chestnut blight – one of the major transitions in
the history of biogeography (less driven by climate than by introductions)
...and changes in phenology, just coming into purview / harbingers of species
advances and declines?
…and changes in stress level (water stress, as in forests in various locales;
subject to remote sensing detection), also harbingers of change
Can we do adequate causal attribution, for estimating trajectories?
Agricultural shifts are much faster (field crops, pastures) and cover a large fraction of
land area; however, it remains a bit difficult to attribute farm choices to direct
considerations of climate and CO2
What detection methods are operable?
Ground surveys in intensively monitored areas (national parks,. …)
Optical remote sensing, by spectral (and geometric) signatures
Only locally, and with much ground optical data and calibration
Aircraft campaigns – e.g., Carnegie Airborne Observatory (Asner et al.)
A remarkable encroachment sequence ,
evaluated from aerial photos (Laliberte et al., 2003)
Instrumented transects – e.g., Gamon et al.; Nagler et al. (2005)
Pattern recognition among limited species – e.g., Laliberte et al.
5
Criteria of success – we had better have some
* Retrospective studies
We have detected many changes…but causal attribution is harder (absent?)
* Prospective studies
What is expected time scale? spatial scale? magnitude of shift ? (not a simple scalar
measure; at least a vector)  Experimental design is critical and as yet undefined
* The bottom line: we need to know what we’re looking for and its statistical AND
functional significance