-
___________________________________________________________________________________
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
223
GEOGRAPHIC CLINES IN GENETIC VARIATION
Gerald Rehfeldt(presented by Albert R. Stage)
USDA Forest ServiceRocky Mountain Research Station
In risk mapping, the primary considerations are the presence of
the host tree species, somemeasure of its density, and the
distribution of the pest agent. High-density or overstockedstands
are often considered to be of higher risk then stands with lower
stocking levels; alsoimportant is the climatic stress on the
population. This presentation shows how the predic-tions from a
climate model can be converted to variables that may indicate the
status of thestress of conifer species and their populations in the
western USA and southwestern Canada.Forty-eight monthlies were
derived from the basic temperature and precipitation data and fitto
geographic surfaces with thin plate splines. These monthlies were
then used to describe theclines of genetic variation that exist
within species for growth characteristics. The mapping ofclinal
variation is useful in delineating seed zones and deriving seed
transfer guidelines. Thereverse image of such maps should indicate
where the species would be under stress due toclimatic conditions.
For this reason, it is recommended that the monthlies and the
climaticlimits could be useful in risk mapping.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
224
1. Genetic variation is displayed along geographic gradients but
interpretationis invariably in terms of climate. Out of the files
is a geographic cline, Dou-glas-fir vs. elevation. Geographic
variation is acting as a surrogate for cli-mate, which is more
difficult to measure. Armed with a climate model wethen ready to
assess plant-climate relationships. With climate models
thatprovided point predictions we cannot replace the
surrogates.
In this slide, genetic variation in growth potential measured in
a provenancetest of populations of Douglas-fir is related to the
elevation of the stand inwhich the seeds were collected.
INTRODUCTION
Genetics research during the last 75 year or so has demonstrated
that species of forest trees arecomposed of populations, each of
which is adapted (i.e., physiologically attuned) to only aportion
of the environmental gradient inhabited by the species. For most of
the widespreadspecies, models exist that describe the clinal
variation in genetic responses of populationswithin species. These
models are invariably driven by geographic predictors. But, now
that aclimate model is available that makes point predictions on
the landscape, researchers can di-rectly relate and eventually map
genetic responses to climate.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
225
climate variables derived from temperature and precipitation
monthlies
• Degree-days > 5 °C
• Degree-days < 0 °C
• Frost-free period
• Last spring frost
• First fall frost
• Growing season degree-days > 5 °C
• Summer-winter temperature differential
• Date degree-days > 5 °C reaches 100
• Mean annual temperature• Mean annual precipitation• Growing
season precipitation• Mean cold month temperature• Minimum cold
month
temperature• Mean warm month
temperature• Maximum warm month
temperature• Annual moisture index• Summer moisture index
2. There are 48 surfaces form normalized monthlies – weather
variables basedon temperature and precipitation.
3. All of these variables are of demonstrated importance in
plant geography.The model can then be used to predict the climate
across the landscape.
climate surfaces
• 3006 weather stations• Hutchinson’s thin plate splines•
Temperature and precipitation surfaces• Algorithms for derived
variables• Splines for derived variables• Predict for DEM grids (1
km)• Map with GIS
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
2264. This is a map of degree-days>5C. There are nearly 6
million terrestrial pixels
in the map, and predicted values of degree days range from 0 to
6700.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
2275. In this map, we’re zooming in from the previous slide on
Lewiston, Idaho,
Idaho’s only seaport. This looks like a map of DEMs, but it’s
not. This is amap of degree-days that clearly shows the major
drainages (Snake, Salmon,Clearwater), the Lewiston-Clarkston
valley, and the high mountains. De-gree-days range from 2700 to 0
for the pixels in this map.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
2286. This is the same map of Lewiston that allows some of the
topography to
show through. Now, these maps are based on a 1 k grid which can
be seen inthe slides. It’s important to know that the climate model
itself makes pointpredictions that are not necessarily tied to the
DEMs.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
2297. Frost-free periods vary from 0 to 365.
8. Negetative degree-days show how severe the winters are.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
2309. Then using output from the General Circulation Models and
refitting the
splines, one can map climates predicted for the future. This map
is for de-gree-days>5 and uses the greenhouse gas scenario (1%
increase per year) ofthe Hadley and Canadian GCMs. Upper left is
contemporary climate, upperright is that for the decade beginning
in 2030, lower left for the decade be-ginning in 2060, and lower
right for the decade beginning in 2090.
Range in contemporary values 0 to 6700. Range in 2090 will be 0
to 8344.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
23110. This is the same sequence of illustrations that was used
in the previous slide.
It shows the effects of global warming on negative degree-days.
Notice theeffects are expected to be much greater on winter
temperatures than on sum-mer temperatures.
Degree-days < 0 Contemporary ranges is 0 to 2250, 2090 range
would be 0to 1052.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
23211. FFP (frost-free period) current on left, 2090 on
right..
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
23312. To me, this one is scary. Global warming, of course, is
portrayed as a tem-
perature effect. Yet, the response of plants will be determined
by the inter-action of temperature with precipitation. This slide
compares the contem-porary annual moisture index (DD5/MAP) for the
contemporary climate(left) with that projected for 2090
(right).
AMI (annual moisture index): left is for 2000, right is 2090.
dd5/map.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
23413. Now, armed with the climate model, we’re ready to
consider biological
effects. This slide compares our ability to predict genetic
responses of popu-lations with geographic predictors (left) and
climate predictors (right).
Pinus sylvestris lattitude is a good surrogate for the climate
variables.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
235
GOALS
assess population differentiation in relation to climate
Pinus sylvestris and Larix sibirica
Picea engelmannii
compare effects of climate change
Siberia vs. western USA
14. This is a similar comparison for Engelmann spruce. Engelmann
spruce–elevation is a poor surrogate for the climate effects; in
fact, it leads to thewrong interpretation.
15. Studies of genetic responses to climate included researchers
from RMRSand the Sukachev Institute of Forest in Krasnoyarsk,
Russia. We had theseobjectives. Only those dealing with USA will be
considered here.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
236
GOALS
assess population differentiation in relation to climate
Pinus sylvestris and Larix sibirica
Picea engelmannii
compare effects of climate change
Siberia vs. western USA
genecology of Engelmann spruce
• 295 populations sampling natural distribution
• 18 blue spruce populations
• 20 white spruce
• common garden studies in Idaho
16. Definitions.
17. The USA example involves Engelmann spruce.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
23718. This photo was taken in the provenance test conducted at
low elevation at
the Priest River Experimental Forest. The populations are
planted in 10-tree row plots. This means that any differences that
are apparent betweenrows is due to genetic differences between the
populations. At this mildsite, differences are obvious.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
23819. This is the high elevation planting site. Growth is less
at high elevation, and
differences were more difficult to detect.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
23920. Yet, in studies of genetic variation of western conifers,
the best variables for
assessing genetic differentiation invariably come from
greenhouse-shadehouse tests of shoot elongation where precise
measurements can bemade while controlling extraneous environmental
effects (e.g., mosquitoeshave a definite effect on the quality of
the data).
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
240
Engelmann results
• genetic differences are obvious
• genetic differences most pronounced for patterns of shoot
elongation
• winter temperatures drive population differentiation
22. The tests showed these results. They can be displayed by
clines in relationto the climate where the seeds were
collected.
21. This slide shows different patterns of shoot elongation for
spruce popula-tions.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
24123. The cline is steepest for the warmest climate and
flattens out in the coldest
climates. One can then describe clines like this on with
regression models.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
242
regression models
0.73winter temperatures, summer maximum temperatures
amount
0.62winter temperatures, summer max temperatures, freezing
dates
rate
0.83winter temperature, summer maximum temperature
duration
0.81winter temperatures, summer maximum temperatures
cessation
0.54winter temperatures, summer precipitation
start
R2predictorsshoot elongation variable
24. Notice that the best predictors for spruce involve winter
temperatures – thevariables that are expected to change the most
with global warming. Thesemodels, of course, are suited to
predicting responses. But to map responses,we need to know the
climate at point locations on a map grid. The splineclimate model,
as shown previously, can be use to estimate the climate ofeach of
the 6 million pixels for all of the climate variables that are
importantin predicting genetic responses in spruce. Then for each
pixel, one can esti-mate the genetic response for a population
growing there as if it had beentested in a common garden. This is
what we get:
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
24325. This map says that the duration of shoot elongation for
populations from
throughout western USA varies from 12 to 400 days. It’s
nonsense. And,the reason it doesn’t make sense is that Engelmann
spruce does not grow inall of these pixels. Before we can make
sense out of this, we need an estimateof which pixels are
climatically suited for the species.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
244
27. This slide shows the results from four different attempts to
map the Engel-mann distribution. They’re pretty good, but all have
problems.
mapping distribution of Engelmann spruce
• 17 climate variables
• Climatic limits of 295 populations
• Canonical discriminant analysis of 9 species (1500
observations)
26. First map now a second approximation.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
24528. This map is the consensus of the four on the previous
slide. 11% of the 7
million pixels show suitable climate–Black Hills error, Colorado
hole, Si-erra Nevada and so on; remember, this is a climate unite.
This map willsuffice for this presentation, but one should be aware
that we’ve now devel-oped statistical approaches that do a much
better job. So, we now have arough species map which gives us a
basis for predicting genetic responses toclimate. Still, one must
remember:
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
246
30. This map is more like it. Continuous variation across
landscape, durationfrom 21 to 9 – clines steepest for mildest
climates but for the results to beuseful to forest managers we need
to classify the variation into seed zonesor clime types.
29. Climate might be right but other things are limiting.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
247
Climatypesbreadth: ± standard error of the mean for t0.2for
duration of shoot elongation:
interval (days)zone
73-859
63-738
55-637
47-556
41-475
36-414
31-363
27-31 2
below 27 1
31. Climatype classifications.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
24832. Geographic Zones for Duration of Shoot Elongation: all
populations occu-
pying pixels of the same color are expected to have a similar
duration ofshoot elongation when grown in a common garden. Zones
are smaller inmild climates and broader in more severe. However,
these zones are foronly 1 variable. For describing genetic
variation in this species, we have 5variables and all need to be
taken into consideration.
.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
249
Engelmann spruce climatypes
3rate of elongation
5start of elongation
8cessation of elongation
7amount of elongation
9duration of elongation
zonesvariable
33. All possible combinations of these zones would give 3600!!
But, we’re lucky.For western USA, there’s only 286.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
250 34. Here they are. This may not be 3600, but it’s still a
huge number that wouldbe impractical to administer by management.
So, when we think about howwe got to this point, we realize that
there were many sources of error alongthe way.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
251
Sources of errorPopulation effects
sampling errorsexperimental errors
Climate datanormalizationfitting splines
Genecologyregression models: population effects on climate
MappingDEMsClimate predictions per DEMRaster calculator
35. There were sampling errors, experimental errors, errors in
climate estimates,errors in the splines, errors in the DEMs, and
errors of prediction – all, wehope, are tiny. But, there are many
sources of error such that the errors ofestimation in delineating
seed zones or climatypes can’t be quantified. Forthis reason, one
can not assume that the boundaries between these zonesare fixed. In
fact, 286 climatypes mapped for Englemann spruce are domi-nated by
a few large climatypes.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
252
36. Keep in mind that 100 pixels is approximately equivalent to
1 township or36 square miles. It’s the few large climatypes on
which management shouldconcentrate. We can see the large ones as we
zoom in:
climatypesummary statistics
• total climatypes: 268
• climatypes with pixels99: 168
• area of 20 largest climatypes: 66%
37. There are 65 climatypes shown here for Idaho and Montana,
but 20 accountfor about 75% of the distribution of spruce.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
25338. So, let’s look at global warming:
Global Warming
AmountSiberia:
+6 to +8 °Cup to +20% (100 mm) ppt
western USA:+4 to +5 °Cup to +17% (130 mm) ppt
EffectSiberia: bonanzawestern USA: disaster
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
25439. This slide shows a map of the distribution of spruce
predicted for the cli-
mates of today (upper left), decade of 2030 (upper right),
decade of 2060(lower left), and decade of 2090 (lower right).
Obviously, the climates fa-vorable for this species move upwards
off the top of the mountains andnorthward off the top of the
map.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
25540. Here’s a gallery of some of the contemporary sites that
are expected to have
a climate suitable for spruce at the end of the century. It’s
hard to imagine aorderly migration into such places.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
25641. This is complicated, but this slide illustrates how
populations and, there-
fore, species will respond to a change in climate. Each of these
figures showsgenetic response functions for two populations, for
lodgepole pine on theleft and Scots pine on the right. These
results come from provenance tests.They show that populations have
a climatic optimium within which growth(and survival is optimum).
This is the point at the peak of the respectivecurves. However,
populations differ in growth potential, as shown by thedifferent
heights of the curves. They also differ in cold hardiness, and this
isillustrated by the differences in thex-axis coordinate of the
optimum. And,there is a negative relationship between growth
potential of populationsand cold hardiness. Together, these
characteristics mean that most popula-tions are competitively
excluded from their climatic optima. In fact, onlyone population,
the one with the highest sit index growing in the mildestclimates,
actually occupies its optima. Other populations are relegated
tosuboptimal conditions and the degree of suboptimality increases
as the cli-mate becomes more and more severe. It’s the degree of
suboptimality thatwill determine initial responses to global
warming. For populations occu-pying their optima, any warming will
be deleterious to growth and sur-vival. But, for populations
occupying sites that are colder than their optima,a warming climate
will be advantageous. Consequently, for western USA,global warming
has disastrous consequences in both the short and long terms.But in
Siberia, global warming should be a stimulant to growth and
pro-ductivity.
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
25742. When we think about global warming, one tends to
concentrate on the
amount of warming. But, in historical perspective, the amount of
changeisn’t very much: temperatures fluctuated by about 7C during
the Pleistocene.Plants can adjust to this amount of change. The
scary part about globalwarming from the viewpoint of plants is the
speed.
the time factor• Interspecific effects
– Immigration is slow; extirpation can be fast
– Result is a temporarily impoverished flora
• Intraspecific effects– Accommodating global warming requires
more change
per generation than genetic systems can provide
– Result is a lag in response to change
• Adjusting to global warming may require natural systems up to
1000 years
• Scariest part of global warming is the speed not the amount of
change
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
25843. Concluding points about global warming. How does mankind
participate?
By assisting migration of genotypes to the novel location of
their optimalclimates. By planting more trees.
finale
• when converted to variables with physiological importance,
4-5°C increase has huge impact
-- alter species distributions
-- wholesale redistribution of genotypes within species
• to mitigate the impact, mankind can participate in the
evolutionary processes
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
25944. Maps like this one can provide assistance to the manager.
The blue shows
the distribution of a climatypes in the contemporary climate.
The orangeshows the 2030 projected distribution of the climate
inhabited by theclimatypes, the yellow the 2060 distribution, and
the pink the 2090 distri-bution. For mankind to be participating in
the evolutionary process, seedstoday could be collected in the blue
zone and planted in the orange zone inanticipation of the change in
climate.
-
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
Rehfeldt
_____________________________________________________________________________________
26045. Because the cause of the problem is not being addressed,
what we can ac-
complish as individuals is almost nothing compared to the scope
of the prob-lem. My suggestion is to buy now while permafrost is
still cheap and watchnatural history unfold.
opinion page
• yes, it’s happening• no, the GCM’s don’t quite have it right•
yes, there is something we can do to
mitigate the effects• but, it’s the cause not the effect
that
needs attention• buy now Siberian or Yukonian estates,
sit back, and watch the show
-
_____________________________________________________ Geographic
Clines in Genetic Variation
Workshop Proceedings: Quantitative Techniques for Deriving
National Scale Data
261
REFERENCES
Rehfeldt, G.E., C.C. Ying, D.L. Spittlehouse, and D.L. Hamilton.
1999. Genetic responses toclimate in Pinus contorta: niche breadth,
climate change, and reforestation. Ecological Mono-graphs 69:
375-407.
Rehfeldt, G.E., C.C. Ying, and W.R. Wykoff. 2001. Physiologic
Plasticity, Evolution, and Impacts of a Changing climate on Pinus
contorta. Climatic Change 50: 55-376.
Rehfeldt, G.E., Ying CC, Spittlehouse DL, Hamilton DL (1999)
Genetic responses to climate inPinus contorta: niche breadth,
climate change, and reforestation. Ecological Monographs
69:375-407.
Rehfeldt, G.E., N.M. Tchebakova, Y.I. Parfenova, W.R. Wykoff,
N.A. Kouzmina, and L.I.Milyutin. 2002. Intraspecific responses to
climate in Pinus sylvestris. Global Change Biology 8:1-18.
Rehfeldt, G.E. 2004, Inter- and intra-specific variation in
Picea engelmannii and its congenericcohorts: biosystematics,
genecology and climate-change. Gen. Tech. Rep. RMRS-GTR-134.Ft
Collins, CO: U.S. Department of Agriculture, Forest Service, Rock
Mountain ResearchStation.
Rehfeldt, G.E., N.M. Tchebakova, and E. Parfenova. 2004. Genetic
responses to climate andclimate change in conifers of the temperate
and boreal forests. Recent Advances in Geneticsand Breeding 1:
113-130.
Rehfeldt, G.E. 2005. A spline climate model for western United
States. Gen. Tech. Rep. RMRS-GTR. Ft Collins, CO: U.S. Department
of Agriculture, Forest Service, Rock MountainResearch Station. In
Press.