Odekon M. Encyclopedia of paleoclimatology and ancient environments

Подождите немного. Документ загружается.

with prognostic biogeography may be fully incorporated within

the land surface scheme of a GCM. This is the most compu-

tationally expensive method of making paleovegetation simula-

tions and has been applied much less often than the other

methods. The vegetation model is coded directly into the land

surface scheme of the GCM, and vegetation dynamics are

typically updated on an annual time-step. This configuration is

particularly useful for studying rapid climate changes where

changes in land surface conditions are suspected to have had a

strong physical or biogeochemical feedback to the climate sys-

tem. Such situations are frequent in the paleorecord, but uncer-

tainties about the external forcing that drives the rapid climate

change event have limited the application of such coupled mod-

els. Moreover, the biogeography component of a coupled atmo-

sphere-vegetation GCM is usually a very small part of the

total computational demand of the model; coupled atmosphere-

vegetation models could be applied more widely.

Except in the case of fully coupled vegetation atmosphere

models, paleovegetation simulation typically involves the pre-

paration of an anomaly climatology, where the GCM paleocli-

mate simulation is subtracted from a control run simulation

for the GCM. These anomalies are then applied to a gridded

dataset of present-day observed climatology. The anomaly

technique is used to avoid biases inherent in the GCM ’s control

climatology, which is often in disagreement with observed cli-

matology over large regions. The anomaly technique also

offers a degree of standardization among GCM climatologies

when it is desired to analyze the differences in the major fea-

tures of the climate simulated by different GCMs.

Vegetation history

Most late Quaternary and Holocene vegetation modeling has

focused on two key times in the past: the Last Glacial Maxi-

mum (LGM, ca, 21 ka) and the mid-Holocene (ca 6 ka;

Figure L15). These two periods have been a major focus for

paleoclimate simulations (e.g., Joussaume and Taylor, 1995;

Joussaume and Taylor, 2000; Kohfeld and Harrison, 2000)

because they represent two extremes in climate forcing. At

the LGM, the Earth’s orbital configuration was fairly similar

to today but greenhouse gas concentrations were low (Raynaud

et al., 1993), Northern Hemisphere ice sheets were expanded

(Denton and Hughes, 1981), and sea level was therefore lower

(Fairbanks, 1989). In addition to the large changes in terrestrial

geography, the ocean surface was significantly colder and the

distribution of sea ice was expanded (CLIMAP, 1981). The

configuration of the Earth’s orbit around the Sun was, however,

substantially different to that of today (and the LGM) during

the early to mid-Holocene. The phasing of the precession

(23 kyr) and obliquity (41 kyr) cycles of the orbit were such

that the high latitudes of the Northern Hemisphere received a

maximum in insolation (incoming solar radiation), both during

boreal summer and annually, at ca. 11,000 calendar y

BP. This

anomaly decayed gradually towards the present. As a direct

result of the changes in orbital forcing, many regions of the

Arctic experienced summer temperatures considerably higher

than at present during the early Holocene (see e.g., Ritchie

et al., 1983; Bradley, 2000; MacDonald et al., 2000; Elias,

2001). Increased heating of the northern continents also influ-

enced tropical climates; paleodata indicate that much wetter

conditions existed in the Sahara and in south Asia in the early

to mid-Holocene as compared to the present. However, at the

time of the Northern Hemisphere insolation maximum, the

Laurentide Ice Sheet, although substantially reduced from

the LGM, was still sufficiently large to have a major downwind

cooling effect (Mitchell et al., 1988; Harrison et al., 1992).

Northern Europe and eastern North America therefore experi-

enced a thermal maximum several thousand years after the

insolation maximum (Wright et al., 1993). For this reason,

investigations of the impact of insolation changes on climate

have conventionally focused on 6,000 y

BP, when the difference

in orbital configuration was still large but the impact of the

residual Laurentide Ice Sheet was small and essentially local.

Figure L14 Types of atmosphere model (AGCM)-vegetation model coupling.

LATE QUATERNARY-HOLOCENE VEGETATION MODELING 509

The Last Glacial Maximum

A wide range of vegetation modeling has been performed for

the LGM. This research has been motivated by the desire to

understand the effect of the radically different climate on the

Earth’s surface at present. Major climate-driven changes in

the Earth’s vegetation have implications for climate feedbacks,

the distribution of animals and humans, and for the behavior

of the biogeochemical Earth system. Studies in LGM vegeta-

tion modeling qualitatively describe changes in biogeography,

the physiological effects of climate and low CO

levels on

Figure L15 Paleovegetation simulations for the late Quaternary and Holocene. Offline simulation of the biomes of the Northern Hemisphere

north of 55



N simulated by BIOME4: for the LGM using AGCM output from the (a) MRI2 and (b) LMDH models; for 6 ka using AOGCM

output from (c) IPSL-CM1 and (d) HADCM2 models; and (e) for the present-day potential natural state using observed, gridded climatology;

(f) legend for all panels. For a further explanation of these experiments see Kaplan et al. (2003).

510 LATE QUATERNARY-HOLOCENE VEGETATION MODELING

vegetation structure and composition, implications of carbon

storage on the global carbon cycle, and sources of radiatively

active aerosols and trace gases. While most studies used simple

one-way vegetation simulations based on a GCM climatology,

a few studies have used asynchronous or fully interactive cou-

pling between vegetation and atmosphere to investigate the role

of vegetation in shaping the glacial climate. Finally, one study

uses a vegetation model in “inverse” mode to estimate changes

in climate variables using observed paleovegetation. This

method allows accounting for the effect of CO

concentration

on the observed vegetation.

Biogeography. LGM vegetation was dominated by grasses

and shrubland in the tropics, tundra, and deserts in higher lati-

tudes. The area of forest biomes was reduced as compared to

present levels on all continents. Low CO

concentrations contrib-

uted to the expansion of C

grasses. The vegetation models simu-

late large, continuous areas of rainforest in the Amazon

lowlands and on the exposed Sunda shelf, but do not display a

high degree of fragmentation in rainforest biomes as has been

suggested by some interpretations of the paleodata. Despite using

an anomaly-based technique for developing the paleoclimate, the

models are still somewhat sensitive to the GCM-simulated paleo-

climate. No analog biomes – notably graminoid and forb tundra

in the Arctic – are widespread, and the potential for more to

appear is possible especially if they were defined in the models

(Prentice et al., 1993; Kaplan et al., 2003).

Biogeography / plant physiology. Model simulations of

LGM vegetation have been used to illustrate the effect of low

concentrations on vegetation structure and plant physiol-

ogy. Jolly and Haxeltine (1997) showed that LAI and vegetation

productivity in the mountains of tropical Africa result in the

simulation of shrub and grassland and biomes in areas that might

otherwise climatically support forests. These results indicate that

attempts to use observed paleovegetation assemblages to recon-

struct climate may be wrong if the direct effect of changes in

atmospheric CO

concentrations on the vegetation was not taken

into account. Furthermore, the low CO

concentrations may be

responsible for thinner forests, such as the observed forest-park-

lands of North America that were abundant at the LGM but have

no modern analog (Cowling, 1999).

Carbon storage / carbon cycle. A great deal of vegetation

modeling has been done to estimate the role of the terrestrial

biosphere in long-term oscillations in the global carbon cycle

(Friedlingstein et al., 1992; Friedlingstein et al., 1995; François

et al., 1999; François et al., 2000; Kaplan et al., 2002; Otto

et al., 2002). All modeling studies indicate that the land bio-

sphere stored considerably less carbon at the LGM as com-

pared to the present; models predict a reduction in carbon

storage from 200 to 1,000 Pg C. The general reduction in forest

area, expansion of tundra and desert, and the effect of low

atmospheric CO

concentrations on ecosystems were the main

reasons for the reduction in carbon storage. In any reconcilia-

tion of the global glacial carbon budget, the low LGM terres-

trial carbon storage must be accounted for with increases in

carbon stored in the oceans.

Dust sources. Ice core measurements indicate that atmo-

spheric dust concentrations at the LGM were up to 20 times

greater than at present. These dramatic increases may be due

to changes in climate and land surface conditions. A modeling

study (Harrison et al., 2001) found that dust sources are highly

sensitive to land surface conditions, where potential as a dust

source increases exponentially as vegetation cover becomes

sparser. Under LGM conditions, the vegetation model indicates

that large areas of the land surface were covered by very sparse

vegetation or were completely barren, conditions ideal for dust

deflation. The effect of the cold climate and low CO

concen-

trations on terrestrial vegetation may have increased global

atmospheric dust loading significantly, with further feedbacks

to the climate system through direct radiative effects and the

export of nutrients to the ocean.

Methane. In contrast to the pattern shown in the dust

record, atmospheric methane concentrations were less than half

of those measured in the late Holocene, before strong anthropo-

genic influence. Earlier studies hypothesized that the reduction

in atmospheric methane concentrations could be due to a reduc-

tion in global wetland area and productivity (Chappellaz et al.,

1993). However, a detailed vegetation model study (Kaplan,

2002) demonstrated that wetland area did not change signifi-

cantly between the LGM and the pre-industrial period, and

therefore the reduction in methane source from wetlands was

probably not responsible for the majority of the observed

reduction in atmospheric methane concentrations. Lower vege-

tation productivity was responsible for a ca. 20% reduction in

the wetland methane source. This conclusion remains robust

even when the vegetation / wetland-methane model is driven

by a number of different GCMs, each of which exhibited a

wide range of change in global and regional climates in the

LGM paleoclimate simulation (Pinot et al., 1999).

Asynchronous coupled modeling. Initial evaluation of

vegetation model output from one-way coupling experiments

regarding a GCM paleoclimate simulation indicated that in

some areas, simulated vegetation could not be corroborated

by paleovegetation observations. This was particularly true

for the mid-latitude zone of unglaciated Eurasia, where vegeta-

tion models overpredicted the amount of forest. Asynchronous

coupling of a vegetation model to an atmosphere model

(Kubatzki and Claussen, 1998) improved on the result of the

vegetation simulation, particularly in Siberia where the inclu-

sion of vegetation-snow-albedo interaction proved to be the

key in reducing forest area in the model results. The study also

showed that vegetation-atmosphere interactions through albedo

effects were important in other areas: a “bright” parameteriza-

tion for the initial albedo of deserts resulted in the simulation

of extensive subtropical deserts worldwide, whereas a “darker”

model for desert albedo led to extensive colonization of the gla-

cial western Sahara by plants and an intensification of the mon-

soon over India.

Interactive coupled modeling. A fully coupled atmosphere-

vegetation model study of the LGM resulted in similar con-

clusions, most notably that the biophysical effect of changing

vegetation cover resulted in grasslands and tundra largely repla-

cing forests in Eurasia (Levis et al., 1999). This coupled model

study had the benefit of being able to investigate the effect of

the change in CO

concentrations on leaf stomatal conductance.

Physiological studies have shown that plants at low ambient

concentrations and under well-watered conditions will lose

more water for a given unit carbon gain; over large scales this

could have an effect on atmospheric humidity and regional

hydrology. Further sensitivity studies established that the effect

of low CO

concentrations manifest themselves in the climate

system much more strongly through direct changes in vegetation

cover and density rather than through this potential enhancement

in vegetation transpiration.

Inverse modeling. Guiot et al. (1999) used the novel tech-

nique of applying a vegetation model in inverse mode to inves-

tigate the changes in two climate variables (temperature of the

LATE QUATERNARY-HOLOCENE VEGETATION MODELING 511

coldest month and total annual precipitation) given an observed

vegetation distribution. By using a process-based vegetation

model instead of the traditional response surface or regression

methods for determining climate variables from observed veg-

etation, the authors were able to account for the changes in

vegetation structure due to low CO

concentrations that have

no modern analog. Applied to the Mediterranean basin and

Eurasia, the technique showed that many GCMs might under-

estimate the extent of cooling and drying in the LGM climate.

The mid-Holocene

While climate change between the mid-Holocene and present

was considerably smaller than the LGM-present difference, a

decade of paleoclimate simulation work indicates that capturing

these subtle changes in a climate model probably requires inter-

active simulation of the atmosphere with the land surface.

Vegetation modeling efforts for the mid-Holocene have focused

on land surface changes in the Sahara and the circumpolar

north, where the expansion of vegetation as indicated by paleo-

data was greatest. Both of these regions have been shown to

have important biophysical feedbacks to the climate system

and the observed extent of vegetation change cannot usually

be reproduced without some form of interactive coupling

between the land surface and the atmosphere. In the case of

the Sahara, even the most sophisticated coupled models still

fail to reproduce the observed extent of vegetation change. Glo-

bal vegetation response to mid-Holocene climate also has

implications for the carbon cycle and the global budgets of

radiatively active trace gases.

Biogeography. Initial simulations of mid-Holocene vegeta-

tion were performed in an offline experiment with paleoclimate

simulation from the CCM1 GCM using prescribed present-day

sea surface temperatures and preindustrial CO

concentrations

(Prentice et al., 1998). These vegetation simulations were eval-

uated for Europe, where a dense network of paleodata allowed

detailed model-data intercomparisons. Results indicated that

the model could capture only few of the major vegetation

changes observed in the data. The simulation did agree with

data in that forest cover extended further north and to higher

elevations as compared to the present, and excluded boreal con-

ifers from central and eastern Europe. But the model simulation

generally disagreed with observations, importantly in not simu-

lating the observed extent of vegetation change in southern

Europe and the extent of temperate forest types in the Fennos-

candia, and by simulating a greatly expanded area of steppe in

southeastern Europe that is not observed in the paleoecological

record. In a series of similar offline experiments, Harrison et al.

(1998) further demonstrated an ensemble of vegetation model

simulations for the mid-Holocene driven by ten different GCMs

showed quantatively similar vegetation changes in the intertropi-

cal zone and the northern and southern extratropics, with drier

equatorial forests and an increase in vegetation cover in the sub-

tropical desert regions, and an expansion of forests to the north.

An underestimate, relative to paleodata observations, of the mag-

nitude of subtropical vegetation change was also a feature com-

mon to all models. The small differences among models were

related to the simulation of features in the regional climate.

Another recent study used a coupled atmosphere-ocean GCM

with an offline vegetation model that focused specifically on

vegetation change in northern latitudes of the Northern Hemi-

sphere (Kaplan et al., 2003). This study found that both simu-

lated and observed changes at the northern forest limit were

small, but that significant changes probably occurred in the type

of tundra covering the area north of the forest boundary. While

most vegetation models treat tundra as a single vegetation class

with uniform physical properties, this study emphasized that

the height, density, and phenology of tundra vegetation may be

as important as the forest-tundra boundary itself as a biophysical

feedback to the atmosphere. All of these uncoupled offline

experiments emphasized the need for interactive coupling, both

between the atmosphere and oceans and the atmosphere and land

surface, to reproduce realistically the climate and vegetation of

the mid-Holocene.

Biogeography/ carbon storage. Another offline vegetation

modeling study (Foley, 1994) attempted to estimate the change

in global terrestrial carbon storage at the mid-Holocene com-

pared with the present, taking into account the changes in vege-

tation distribution under a simulated mid-Holocene climate.

Though significant changes in global biogeography were simu-

lated in this experiment, including the northward expansion of

the northern limit of forests and the expansion of grasslands

area in the Sahara desert, the patterns were not in particularly

good agreement with the paleobotanical record. Regionally,

NPP and vegetation carbon storage increased significantly (up

to 15%), but global carbon storage did not change significantly

between the simulated present and mid-Holocene conditions.

Asynchronous coupling. In an effort to better capture the cli-

mate and biogeography of the mid-Holocene, a series of experi-

ments used the asynchronous coupling technique (Kutzbach

et al., 1996a; Kutzbach et al., 1996b; Texier et al., 1997;de

Noblet-Ducoudré et al., 2000). All of these studies focused on

the areas of greatest climate and vegetation change since the

mid-Holocene, i.e., the Sahara region and the northern forest-tun-

dra boundary. Texier et al. (1997) found that after the fourth itera-

tion of an asynchronous coupling, global tundra area was reduced

by 25% and the savanna-desert boundaryin west Africashifted 2.5

degrees north, as compared to the present. Finally, de Noblet-

Ducoudré et al. (2000) concluded that vegetation conditions in

the Sahara were dependent on both sea surface temperature and

the simulation of atmospheric circulation, and that the observed

changes in vegetation distribution could not be explained by

including vegetation feedback alone. While no asynchronous cou-

pling experiment was fully successful in reproducing the observed

conditions of vegetation at the mid-Holocene, these experiments

did show that interaction between the land surface and the atmo-

sphere had an important influence on mid-Holocene climate.

Interactive coupling. Two recent studies used fully coupled

atmosphere-vegetation models to study the mid-Holocene cli-

mate and biogeography (Ganopolski et al., 1998; Doherty et al.,

2000). Doherty et al. (2000) showed that vegetation-atmosphere

feedbacks had the effect of not only modifying the climate over

the Sahara in general, but also the seasonal pattern of rainfall in

North Africa, particularly by extending the length of the rainy

season. This had the effect of producing an increase in vegeta-

tion over the Sahara region, but was still not consistent with

the vegetation change observed in the data. A limitation of this

study was that it used a GCM with fixed, present-day sea surface

temperatures. Ganopolski et al. (1998) used an Earth system

model of intermediate complexity (EMIC) to perform a study

of mid-Holocene climate and vegetation that included fully

coupled atmosphere, ocean, sea ice, and vegetation components

at coarse spatial resolution. While analysis was possible only

over large regions, the results indicated that ocean circulation,

sea ice, and vegetation feedbacks were important controls on

high latitude vegetation at the mid-Holocene. Alternatively, the

response of North African climate was dominated by the land

512 LATE QUATERNARY-HOLOCENE VEGETATION MODELING

surface feedback alone. Both studies showed importantly that

only with the complex interaction of atmosphere and land

surface can we begin to approach a realistic simulation of

mid-Holocene climate and vegetation.

Conclusions

Late Quaternary and Holocene vegetation modeling experiments

have, for the first time, allowed a complete picture of the Earth’s

land surface in the past to be presented in a systematic way. These

experiments have also provided an important evaluation of climate

model output, through the ability to make quantitative comparison

of simulated to observed vegetation from proxy data. These

model-data intercomparisons have highlighted deficiencies in

both climate and vegetation models and led to improvements in

modeling technique and a general trend towards full integration

of vegetation models within GCMs. As both GCMs and vegeta-

tion models improve, we may expect to see more realistic paleocli-

mate simulations, and a clearer picture of the face of the Earth.

These vegetation simulations will also see a wide range of new

application to problems in archaeology and anthropology, biogeo-

chemistry, and climate change research, all of which will present a

clearer picture of the behavior of the earth system and help

researchers reach a better understanding of the potential for future

climate change.

Jed O. Kaplan

Bibliography

Bradley, R.S., 2000. Past global changes and their significance for the

future. Quaternary Sci. Rev., 19, 391–402.

Chappellaz, J.A., Fung, I.Y., and Thompson, A.M., 1993. The atmospheric

increase since the Last Glacial Maximum (1). Source estimates.

Tellus., B 45, 228–241.

CLIMAP, 1981. Seasonal Reconstructions of the Earth’s Surface at the

Glacial Maximum. Boulder, CO: Geological Society of America.

Cowling, S.A., 1999. Simulated effects of low atmospheric CO

on struc-

ture and composition of North American vegetation at the Last Glacial

Maximum. Glob. Ecol. Biogeogr., 8,81–93.

Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A., and Totterdell, I.J., 2000.

Acceleration of global warming due to carbon-cycle feedbacks in a

coupled climate model. Nature, 408, 184–187.

de Noblet-Ducoudré, N., Claussen, R., and Prentice, C., 2000. Mid-

Holocene greening of the Sahara: First results of the GAIM 6000 year

BP Experiment with two asynchronously coupled atmosphere /biome

models. Clim. Dyn., 16, 643–659.

Denton, G.H., and Hughes, T.J., 1981. The Last Great Ice Sheets. New

York: Wiley.

Doherty, R., Kutzbach, J., Foley, J., and Pollard, D., 2000. Fully coupled

climate/ dynamical vegetation model simulations over northern Africa

during the mid-Holocene. Clim. Dyn., 16, 561–573.

Elias, S.A., 2001. Mutual climatic range reconstructions of seasonal

temperatures based on Late Pleistocene fossil beetle assemblages in

Eastern Beringia. Quaternary Sci. Rev., 20,77–91.

Fairbanks, R.G., 1989. A 17,000-year glacio-eustatic sea level record:

Influence of glacial melting rates on the younger dryas event and

deep-ocean circulation. Nature, 342, 637–642.

Foley, J.A., 1994. The sensitivity of the terrestrial biosphere to climatic

change: A simulation of the middle Holocene. Global Biogeochem. Cycles,

8,505–525.

François, L., Kaplan, J., Otto, D., Roelandt, C., Harrison, S.P., Prentice,

I.C., Warnant, P., and Ramstein, G., 2000. Comparison of vegetation

distributions and terrestrial carbon budgets reconstructed for the Last

Glacial Maximum with several biosphere models. In Braconnot, P.

(ed.), Paleoclimate Modeling Intercomparison Project (PMIP). Canada:

La Huardière, WMO/ WCRP, WCRP-111, pp. 141–145.

François, L.M., Goddéris, Y., Warnant, P., Ramstein, G., de Noblet, N., and

Lorenz, S., 1999. Carbon stocks and isotopic budgets of the terrestrial

biosphere at mid-Holocene and Last Glacial Maximum times.

Chem. Geol., 159, 163–189.

Friedlingstein, P., Delire, C., Muller, J.F. and Gerard, J.C., 1992. The

climate induced variation of the continental biosphere - a model simula-

tion of the Last Glacial Maximum. Geophys. Res. Lett., 19, 897–900.

Friedlingstein, P., Prentice, K.C., Fung, I.Y., John, J.G., and Brasseur, G.P.,

1995. Carbon-biosphere-climate interactions in the last glacial maxi-

mum climate. J. Geophys. Res-Atmos., 100, 7203–7221.

Ganopolski, A., Kubatzki, C., Claussen, M., Brovkin, V., and Petoukhov, V.,

1998. The influence of vegetation-atmosphere-ocean interaction on

climate during the mid-Holocene. Science, 280,1916–1919.

Guiot, J., Torre, F., Cheddadi, R., Peyron, O., Tarasov, P., Jolly, D., and

Kaplan, J.O., 1999. The climate of the Mediterranean basin and of Eur-

asia of the Last Glacial Maximum as reconstructed by inverse vegeta-

tion modelling and pollen data. Ecologia mediterranea, 25, 193–204.

Harrison, S.P., Kutzbach, J.E., and Behling, P., 1992. General circulation

models, paleoclimatic data and last interglacial climates. Quaternary

Int., 10–12, 231–242.

Harrison, S.P., Jolly, D., Laarif, F., Abe-Ouchi, A., Dong, B., Herterich, K.,

Hewitt, C., Joussaume, S., Kutzbach, J.E., Mitchell, J., de Noblet, N.,

and Valdes, P., 1998. Intercomparison of simulated global vegetation

distributions in response to 6 ky

BP orbital forcing. J. Clim., 11,

2721–2742.

Harrison, S.P., Kohfeld, K.E., Roelandt, C., and Claquin, T., 2001. The role

of dust in climate changes today, at the Last Glacial Maximum and in

the future. Earth-Sci. Rev., 54,43–80.

Jolly, D. and Haxeltine, A., 1997. Effect of low glacial atmospheric CO

tropical African montane vegetation. Science, 276, 786–788.

Joussaume, S., and Taylor, K.E., 1995. Status of the Paleoclimate Modeling

Intercomparison Project (PMIP). In Gates, W.L. (ed.), Proceedings of

the First International AMIP Scientific Conference, May 15–19, 1995.

Monterey, CA: WMO/ WCRP, WCRP 92, WMO/ TD-No. 732,

pp. 425–430.

Joussaume, S., and Taylor, K.E., 2000. The paleoclimate modeling inter-

comparison project. In Braconnot, P. (ed.), Paleoclimate Modeling

Intercomparison Project (PMIP). La Huardière, Canada: WMO/

WCRP, WCRP-111, WMO/ TD-No. 1007, pp. 9–24.

Kaplan, J.O., 2001. Geophysical Applications of Vegetation Modeling,

Ph.D. Thesis. Lund: Lund University, 132pp.

Kaplan, J.O., 2002. Wetlands at the Last Glacial Maximum: Distribution

and methane emissions. Geophys. Res. Lett., 29, 3.1–3.4.

Kaplan, J.O., Prentice, I.C., Knorr, W., and Valdes, P.J., 2002. Modeling the

dynamics of terrestrial carbon storage since the Last Glacial Maximum.

Geophys. Res. Lett., 29, 31.1–31.4.

Kaplan, J.O., Bigelow, N.H., Bartlein, P.J., Christensen, T.R., Cramer, W.,

Harrison, S.P., Matveyeva, N.V., McGuire, A.D., Murray, D.F.,

Prentice, I.C., Razzhivin, V.Y., Smith, B., Walker, D.A., Anderson, P.M.,

Andreev, A.A., Brubaker, L.B., Edwards, M.E., and Lozhkin, A.V.,

2003. Climate change and Arctic ecosystems: 2. Modeling, paleodata-

model comparisons, and future projections. J. Geophys. Res-Atmos., 108,

(D19), 8171, doi:10.1029 /2002JD002559.

Kohfeld, K.E., and Harrison, S.P., 2000. How well can we simulate past cli-

mates? Evaluating the models using global palaeoenvironmental data-

sets. Quaternary Sci. Rev., 19, 321–346.

Kubatzki, C., and Claussen, M., 1998. Simulation of the global biogeophysi-

cal interactions during the last glacial maximum. Clim. Dyn., 14,461–471.

Kutzbach, J., Bonan, G., Foley, J., and Harrison, S.P., 1996a. Vegetation

and soil feedbacks on the response of the African monsoon to orbital

forcing in the early to middle Holocene. Nature, 384, 623–626.

Kutzbach, J.E., Bartlein, P.J., Foley, J.A., Harrison, S.P., Hostetler, S.W.,

Liu, Z., Prentice, I.C., and Webb III, T., 1996b. Potential role of vegeta-

tion feedback in the climate sensitivity of high-latitude regions: A case

study at 6000 years

BP. Global Biogeochem. Cycles, 10, 727–736.

Levis, S., Foley, J.A., and Pollard, D., 1999. Potential high-latitude vegeta-

tion feedbacks on CO

-induced climate change. Geophys. Res. Lett., 26,

747–750.

MacDonald, G.M., Velichko, A.A., Kremenetski, C.V., Borisova, O.K.,

Goleva, A.A., Andreev, A.A., Cwynar, L.C., Riding, R.T., Forman,

S.L., Edwards, T.W.D., Aravena, R., Hammarlund, D., Szeicz, J.M.,

and Gattaulin, V.N., 2000. Holocene treeline history and climate change

across northern Eurasia. Quaternary Res., 53, 302–311.

Mitchell, J.F.B., Grahame, N.S., and Needham, K.J., 1988. Climate simu-

lations for 9000 years before present: seasonal variations and effect of

the Laurentide ice sheet. J. Geophys. Res-Atmos., 93, 8283–8303.

LATE QUATERNARY-HOLOCENE VEGETATION MODELING 513

Otto, D., Rasse, D., Kaplan, J., Warnant, P., and Francois, L., 2002.

Biospheric carbon stocks reconstructed at the Last Glacial Maximum:

comparison between general circulation models using prescribed and

computed sea surface temperatures. Glob. Planet. Change, 33,117–138.

Pinot, S., Ramstein, G., Harrison, S.P., Prentice, I.C., Guiot, J., Stute, M.,

Joussaume, S., and PMIP participating groups, 1999. Tropical paleocli-

mates at the Last Glacial Maximum: comparison of Paleoclimate Mod-

eling Intercomparison Project (PMIP) simulations and paleodata. Clim.

Dyn., 15, 857–874.

Prentice, I.C., Cramer, W., Harrison, S.P., Leemans, R., Monserud, R.A.,

and Solomon, A.M., 1992. A global biome model based on plant phy-

siology and dominance, soil properties and climate. J. Biogeogr., 19,

117–134.

Prentice, I.C.,Sykes, M.T., Lautenschlager, M., Harrison, S.P., Denissenko, O.,

and Bartlein, P.J., 1993. Modelling global vegetation patterns and terrestrial

carbon storage at the last glacial maximum. Glob. Ecol. Biogeogr., 3,

67–76.

Prentice, I.C., Harrison, S.P., Jolly, D., and Guiot, J., 1998. The climate and

biomes of Europe at 6000 yr

BP: Comparison of model simulations

and pollen-based reconstructions. Quaternary Sci. Rev., 17, 659–668.

Raynaud, D., Jouzel, J., Barnola, J.M., Chappellaz, J., Delmas, R.J., and

Lorius, C., 1993. The ice record of greenhouse gases. Science, 259, 926–934.

Ritchie, J.C., Cwynar, L.C., and Spear, R.W., 1983. Evidence from

northwest Canada for an early Holocene Milankovitch thermal

maximum. Nature, 305, 126–128.

Sitch, S., Smith, B., Prentice, I.C., Arneth, A., Bondeau, A., Cramer, W.,

Kaplan, J.O., Levis, S., Lucht, W., Sykes, M.T., Thonicke, K., and

Venevsky, S., 2003. Evaluation of ecosystem dynamics, plant geogra-

phy and terrestrial carbon cycling in the LPJ dynamic global vegetation

model. Glob. Change Biol., 9, 161–185.

Texier, D., de Noblet, N., Harrison, S.P., Haxeltine, A., Jolly, D.,

Joussaume, S., Laarif, F., Prentice, I.C., and Tarasov, P., 1997. Quanti-

fying the role of biosphere-atmosphere feedbacks in climate change:

coupled model simulations for 6000 years

BP and comparison with palaeo-

data for northern Eurasia and northern Africa. Clim. Dyn., 13,865–882.

Wright, H.E. Jr., Kutzbach, J.E., Webb, T., III, Ruddiman, W.F., Street-

Perrott, F.A., and Bartlein, P.J., 1993. Global Climates since the Last

Glacial Maximum. Minneapolis, MN: University of Minnesota Press,

569pp.

Cross-references

Holocene Climates

Hypsithermal

Last Glacial Maximum

Paleoclimate Modeling, Quaternary

Pleistocene Climates

Quaternary Vegetation Distribution

LATERITE

Laterite is an iron-rich, sub-aerial, weathering product, commonly

believed to evolve as a result of intense, in situ substrate alteration

under tropical or sub-tropical climatic conditions. It comprises

an important subset of a wider range of ferruginous and related

aluminous (i.e., bauxitic) weathering products, which include

ferricretes and various iron-rich paleosols. Laterite weathering

profiles often develop an indurated surface layer of resistant duri-

crust, forming laterally extensive sheets ca. 1–20 m in thickness

(Figure L16). These lateritized surfaces are both chemically and

physically resistant and may extend over areas of a few, to hun-

dreds, or even thousands, of square kilometers.

Historical background and definitions

The term laterite (literally “brick r ock”)wasfirstusedby

Buchanan (1807) to describe a naturally occurring material from

Angadipuram (10



N, 76



E), Kerala state, south-western

India. Once cut and allowed to harden, laterite was used as build-

ing material (Figure L17). Since this first description, the term has

had a long history of geological and geomorphological usage.

However, the unfortunate early adoption of Buchanan’scasual

field description as a type definition has since caused consider-

able confusion. A more comprehensive and geologically rigorous

description was provided by Newbold (1844) from studies of

laterite-capped plateaux near Bidar, India (17



N, 77



E).

He was the first to suggest that laterite developed in situ (in this

instance upon Deccan flood basalt lavas), by segregation and sub-

sequent rearrangement of minerals and elements that originally

comprised the parent rock (Newbold, 1846). Despite this attempt

to better define laterite and the lateritization process, the term

“laterite” (sensu lato) was used throughout the nineteenth and

twentieth centuries to describe a wide range of iron-rich, terrige-

nous weathering products and duricrusts. Unfortunately, many

of these materials were often products of fundamentally differ-

ent element enrichment and depletion processes (Schellmann,

1986; Ollier and Galloway, 1990;BourmanandOllier,2002;

Schellmann, 2003).

Modern field studies make evident that the majority of exa-

mples of iron-rich duricrust typically occur as two genetically

Figure L16 Laterite profile (ca. 40 m) exposed at the edge of a mesa

(i.e., table-land) at Panchgani (17



N, 73



E), Maharashtra, India.

Mechanically resistant upper layers of the laterite profile typically form

a protective capping overlying less altered materials below, producing

a characteristic cliff-like morphology.

514 LATERITE

distinct types. Aleva ( 1994) distinguishes between laterites,

which attain elevated iron contents entirely through autochtho-

nous residual enrichment within the weathering profile (i.e., no

net input of iron), and ferricretes, in which an absolute iron

enrichment occurs (i.e., alteration profiles that receive an

allochthonous net input of iron). This division represents a use-

ful process-based distinction, but the practicality of determin-

ing allochthony or autochthony of the iron component is

often problematic (e.g., Thomas, 1994). In practice, many

lateritic weathering profiles are modified by the introduction

of allochthonous materials. For instance, many elements

(e.g., Fe, Al and some trace metals) can be introduced either

in solution or as chelates by groundwaters passing through the

evolving weathering profile These elements can then be re-

deposited at specific levels within the profile by redox reactions

associated with variations in groundwater chemistry and water

table fluctuation. Alternatively, allochthonous material (e.g.,

eolian dust) may also be introduced by mechanical accumulation

through the exposed surface of the profile (e.g., Chadwick et al.,

1990;Brimhall etal.,1991). Nevertheless, the distinction

between dominantly autochthonous or allochthonous weathering

profiles remains important because it places constraints upon

processes operating during duricrust evolution, and upon con-

temporaneous paleoclimatic and geomorphological conditions.

Chara cterist ic prope rties

Laterites (sensu stricto) are, primarily, residual materials for-

med directly by in situ rock breakdown, and should not contain

any significant allochthonous component. They owe their chief

compositional characteristics to the relative enrichment of iron

(and often aluminum), and the other less mobile parent rock

(i.e., protolith) constituents. This enrichment occurs under

aggressive weathering conditions as a consequence of the

greater mobility, and hence loss, of constituent silica, alkalis,

and alkaline earths from the protolith ( Table L3). Since proto-

lith materials nearer the surface are more subject to weathering,

the degree of alteration will diminish with depth, thereby

producing a weathering profile ( Figure L18 ). Where such

profiles are exposed, they typically consist of an uninterrupted

progression from unaltered bedrock, through increasingly

Figure L17 Laterite quarrying at Bidar, India, showing recently cut

sections (with 1 meter scale rule) where material from the upper parts

of the profile (Zone IV) has been extracted for laterite bricks. Bidar

localities were used by Newbold (1846) to argue for laterite as an “in

situ” (i.e., autochthonous) weathering product.

Table L3 Geochemical analysis of the Bidar weathering profile

illustrated in Figure L18

Sample BB1 BB3 BB5 BB8 BB9

Major elements (wt%)

SiO

48.90 38.59 30.61 31.35 9.59

TiO

2.16 5.11 5.76 2.33 2.03

13.72 31.54 25.83 27.22 9.85

13.40 24.10 36.95 38.37 77.53

MnO 0.19 0.11 0.06 0.07 0.23

MgO 6.93 0.40 0.23 0.10 0.16

CaO 10.99 0.19 0.07 0.00 0.04

O 2.46 0.00 0.00 0.00 0.00

O 0.16 0.02 0.02 0.07 0.03

0.16 0.18 0.08 0.08 0.12

Total 99.07 100.25 99.61 99.59 99.58

(LOI) 0.60 11.74 11.11 11.13 7.31

Trace elements (ppm)

Ba 52.9 54.9 13.3 17.3 161.8

Ce 21.9 20.8 6.5 21.8 53.1

Cr 148.3 201.3 249.6 736.5 691.8

Cs 0.0 0.1 0.0 0.4 0.1

Cu 177.4 394.1 451.5 182.5 581.1

La 8.9 26.1 2.7 9.7 6.5

Nb 10.0 19.5 23.4 17.2 14.8

Nd 15.8 62.8 6.2 6.6 5.8

Ni 97.9 287.3 72.4 106.1 40.3

Pb 1.0 2.4 9.7 19.7 36.7

Rb 1.1 1.0 0.1 3.6 1.3

Sc 37.7 70.0 14.9 24.4 190.1

Sr 210.4 13.4 3.5 7.1 9.7

Th 1.0 1.9 1.4 6.0 6.9

U 0.2 1.0 2.1 1.8 1.6

V 371.3 687.0 1,846.0 967.3 2,985.7

Y 30.6 692.8 2.6 4.4 4.2

Zn 106.4 119.9 62.1 70.3 35.2

Zr 128.1 245.5 281.6 211.2 283.3

Chemical variations show an up-profile increase in the degree of alteration

from basaltic bedrock (BB1) to indurated laterite cap (BB9). Note the

enrichment of Fe and Al oxides, also metals like Cr, Cu, and V toward

the surface, with concomitant depletion of silica, alkalis and alkali earths.

(Establishment of a water table or fluvial and eolian inputs may modify

these patterns).

LATERITE 515

altered and iron enriched zones, to culminate in laterite at the

top. Lateritic duricrusts typically form the uppermost layers

of in situ weathering profiles, and crop out at the surface as a

massive, interlocking fretwork of iron (and aluminum) oxides

and hydroxides (i.e., sesquioxides, Figure L19).

Condit ions of formation

The conditions under which lateritic profiles form include:

(i) Favorable geomorphological environments characterized

by limited runoff and lack of aggressive erosion. Ingress

of rainfall and / or establishment of a water table serve to

promote evacuation of the more mobile constituents.

(ii) Favorable climatic conditions typified by seasonal, high

annual rainfall (e.g., a monsoon-type climate). High

humidity and high mean annual temperatures further pro-

mote alteration.

(iii) Regions of relative tectonic stability, characterized by

minimal uplift, crustal deformation, or erosion.

The chemical and mechanical durability of laterite confers a

prominent role in tropical and sub-tropical landscape evolution.

Studies of occurrences in India, Africa, and Australia have

proved crucial in advancing tropical geomorphology (e.g.,

McFarlane, 19 76 ;Summerfield, 19 91 ;Thomas,1994;Widdow-

son, 1997a, b). However, d isturbance, by uplift , c limate change,

or both, is likely to terminate the lateritization process and lead

to rapid erosion and stripping of the lateritic weathering profile

(Borger and Widdowson, 2001). Consequently, laterite forma-

tion and preservation has been episodic throughout the geologi-

cal record (Bardossy, 1981; McFarlane, 1983) with, for

instance, acmes occurring within cratonic regions during the

late Cretaceous “greenhouse climate, ” and during the Tertiary

thermal maxima.

Wider import ance

Recently, ferricrete and laterite duricrusts, together with Fe-rich

paleosols, have acquired renewed importance as paleoclimatic

indicators because preservation of these materials records the

occurrence of wet, tropical conditions during the geological

past (e.g., Tsekhovskii et al., 1995, Tardy and Roquin, 1998).

Such information is crucial in documenting changing regional

and global climates (e.g., Bardossy, 1981; Thomas, 1994)

and, together with other key climate proxies, aids in identifying

periods of climatic perturbation arising either rapidly through

volcanic and impact events or due to longer-term climate con-

trols (i.e., Mikankovich-Croll cycles). Importantly, the presence

of lateritic profiles in the geological record also confers wider

Figure L18 Generalized vertical section through the autochthonous

Bidar laterite weathering profile (17



N, 77



E), illustrating the

compositional (Table L3 ) and textural progression from unaltered basalt

protolith to indurated laterite (after Borger and Widdowson, 2001).

(I) unaltered basalt progressing up-profile to material displaying limited

alteration of primary minerals; (II) altered basalt containing “unaltered”

corestones within a soft saprolitic matrix, progressing upward into

(III), a saprolitic to weakly-lateritized zone with residual lithological

characteristics, increasingly obscured up-profile with increasing Fe-

mottling and segregations; (IV) moderately lateritized zone comprising

iron segregations and vermiform textures, and becoming increasingly

indurated up-profile; (V) strongly lateritized, indurated laterite with

vermiform textures, becoming highly ferruginous in the uppermost

levels of the profile. (N.B. A similar alteration progression is commonly

observed on other protolith substrates).

Figure L19 Close-up of the uppermost, indurated layer (Zone V) of a

lateritic duricrust revealing the massive, interlocking fretwork of iron

and aluminum oxides and hydroxides (i.e., sesquioxides), and their

associated ‘vermiform’ texture.

516 LATERITE

paleoenvironmental information, such as that concerning paleo-

geographic setting and the nature of paleolandscapes. For

instance, laterite formation is likely to have always been

restricted to humid tropical regions (or their climatic equiva-

lents), and to those areas characterized by low runoff, ingress

of precipitation, and the long-term establishment of a stable

water table. Reconstruction of ancient lateritized paleosurfaces

can also provide a useful tool for quantifying the degree of

neotectonic deformation, since post-lateritization uplift can

lead to the distortion of originally low-lying peneplains, and

measurable increases in surface elevation (Widdowson and

Cox, 1996).

Furthermore, appropriate mineralogical, geochemical, and

isotopic studies on laterites are also beginning to reveal detailed

information regarding past climatic and atmospheric conditions.

Carbon, oxygen, uranium-thorium, and, most recently, lithium

isotope systematics of weathering products offer the opportunity

to investigate paleoatmospheric, paleoclimatic, and paleo-

weathering conditions throughout the geological record (e.g.,

Bird and Chivas, 1989, 1993; DeQuincey et al., 2002;Pistiner

and Henderson, 2003; Kisakurek et al., 2004). For instance, geo-

chemical and isotopic analyses of Proterozoic laterites from

South Africa (Gutzmer and Beukes, 1998), suggest not only

an ancient oxidizing atmosphere, but also a hot and humid cli-

mate at ca. 2 Ga. Moreover, carbon isotope signatures preserved

within these laterites may actually indicate the presence of early,

terrestrially-based, photosynthesizing organisms. Finally , other

isotopic systems, such as samarium–neodymium (Sm–Nd), have

been successfully employed to identify and quantify allochtonous

dust input into ancient weathering profiles, and as a proxy for

monitoring the long-term chemical and isotopic balance

between the evolving weathering profile and its associated

hydrological characteristics (Viers and Wasserburg, 2004).

Mike Widdowson

Bibliography

Aleva, G.J.J., (compiler) 1994. Laterites. Concepts, Geology, Morphology

and Chemistry. Wageningen: ISRIC.

Bardossy, G., 1981. Palaeoenvironments of laterites and lateritic bauxites -

effect of global tectonism on bauxite formation. In Proceedings of the

International Seminar on Lateritisation Processes, Trivandrum, India

11–14 December, 1979. Rotterdam: Balkema, pp. 287–294.

Bird, M.I., and Chivas, A.R., 1989. Stable isotope geochronology of the

Australian regolith. Geochim. Cosmochim. Acta, 53, 3239–3256.

Bird, M.I., and Chivas, A.R., 1993. Geomorphic and palaeoclimatic

implications of an oxygen-isotope chronology for Australian deeply

weathered profiles, regolith. Aust. J. Earth Sci., 40, 345–348.

Borger, H., and Widdowson, M., 2001. Indian laterites, and lateritious

residues of southern Germany: A petrographic, mineralogical, and

geochemical comparison. Z. Geomorph. N.F., 45, 177–200.

Bourman, R.P., and Ollier, C.D., 2002. A critique of the Schellmann

definition and classification of “laterite.” Catena, 47,117–131.

Brimhall, G.H., Lewis, C.J., Ague, J.J., Dietrich, W.E., Hampel, J., Teague, T.,

and Rix, P., 1991. Metal enrichment by deposition of chemically-mature

aeolin dust. Nature, 333,819–824.

Buchanan, F., 1807. A journey from Madras through the Countries

of Mysore, Kanara, and Malabar, vol. 2. pp. 436–461; vol. 3. pp. 66,

89, 251, 258, 378. London: East India Co.

Chadwick, O.A., Brimhall, G.H., and Hendricks, D.M., 1990. From a

black to a gray box – mass balance interpretation during pedogenesis.

Geomorphology, 3, 369–390.

DeQuincey, O., Chabaux, F., Clauer, N., Sigmarsson, O., Liewig, N., and

Leprun, J-C., 2002. Chemical mobilizations in laterites: Evidence

from trace elements and

238

U-

234

U-

230

Th disequilibria. Geochim.

Cosmochim. Acta, 66, 1197–1210.

Gutzmer, J., and Beukes N.J., 1998. Earliest laterites and possible evidence

for terrestrial vegetation in the Early Proterozoic. Geology, 26, 263–266.

Kisakurek, B., Widdowson, M., and James, R.H., 2004. Behaviour of

Li isotopes during continental weathering: The Bidar laterite profile,

India. Chem. Geol., 212,27–44.

McFarlane, M.J., 1976. Laterite and Landscape. London: Academic Press,

151pp.

McFarlane, M.J., 1983. The temporal distribution of bauxitisation and

its genetic implications. In Melfi, A.J., and Carvalho, A. (eds.), Pro-

ceedings of the II International Seminar on Lateritisation Processes,

Brazil, 4–12 July, 1982. Balkema, Rotterdam: Sao Paulo, pp. 287–294.

Newbold, T.J., 1844. Notes chiefly geological, across the Peninsula from

Masultipatam to Goa, comprising remarks on the origin of regur and

laterite: Occurrence of manganese veins in the latter and on certain

traces of aqueous denudation on the surface of southern India. J. Asiat.

Soc. Beng., 15, 204–213, 224–231, 380–396.

Newbold, T.J., 1846. Summary of the geology of Southern India, Part VI:

Laterite. R. Asiat. Soc., 227–240.

Ollier, C.D., and Galloway, R.W., 1990. The laterite profile, ferricrete and

unconformity. Catena, 17,97–109.

Pistiner, J.S., and Henderson, G.M., 2003. Lithium-isotope fractionation

during continental weathering processes. Earth Planet. Sci. Lett., 214,

327–339.

Schellmann, W., 1986. A new definition of laterite. Geol. Surv. India, Mem.

120,1–7.

Schellmann, W., 2003. Discussion of “A critique of the Schellmann defini-

tion and classification of laterite.” Catena, 52,77–79.

Summerfield, M.A., 1991. Global Geomorphology. Harlow: Longman,

537pp.

Tardy, Y., and Roquin C., 1998. Dérive des continents, Paléoclimats et

Altérations Tropicales, Editions BRGM Orléans France, 473pp.

Thomas, M.F., 1994.

Geomorphology in the Tropics. Chichester, UK:

Wiley, 460pp.

Tsekhovskii, Yu. G., Shchipakina, I.G., and Khramtsov, I.N., 1995. Lateri-

tic eluvium and its redeposition products as indicators of Aptian-

Turonian climate. Stratigr. Geol. Correl., 3(3), 285–294.

Viers, J., and Wasserburg, G.J., 2004. Behavior of Sm and Nd in a lateritic

profile. Geochimica and Cosmochimica Acta, 68(9), 2043–2054.

Widdowson, M. (ed.), 1997a. Palaeosurfaces: Recognition, reconstruction,

and paleoenvironmental interpretation. Geological Society of London

Special Publication, 120, 330pp.

Widdowson, M., 1997b. Tertiary palaeosurfaces of the SW Deccan, Western

India: Implications for passive margin uplift. In Widdowson, M. (ed)

Palaeosurfaces: Recognition, Reconstruction and Palaeoenvironmental

Interpretation. Geological Society of London Special Publication, 120,

pp. 221–248.

Widdowson, M., and Cox, K.G., 1996. Uplift and erosional history of

the Deccan traps, India: Evidence from laterites and drainage patterns of

the Western Ghats and Konkan Coast. Earth Planet. Sci. Lett., 137,57–69.

Cross-references

Duricrusts

Paleosols, Pre-Quaternary

Paleosols–Quaternary

Sedimentary Iindicators of Climate Change

Weathering and Climate

LAURENTIDE ICE SHEET

The Laurentide Ice Sheet is that part of the North American ice

sheet complex that was centered on the Canadian (Laurentian)

Shield during Quaternary glaciations. Its configuration and

history are fairly well known only for the Wisconsinan (last)

Glaciation, and are known in outline only for preceding

glaciations.

The late Wisconsinan (25–10 ka

BP [ka = thousands of radio-

carbon years]) North American ice sheet complex consisted of

LAURENTIDE ICE SHEET 517

three major ice sheets: the Laurentide Ice Sheet, which was

centered on the Canadian Shield but also expanded across the

Interior Plains to the west and south; the Cordilleran Ice Sheet,

which inundated the western mountain belt between the north-

ernmost coterminous United States and Beringia (unglaciated

Yukon Territory and Alaska); and the Innuitian Ice Sheet,

which covered most of the Canadian Arctic Archipelago north

of about 75



N latitude ( Figure L20 ). The ice cover over New-

foundland and the Maritime Provinces of Canada during this

interval is usually referred to as the Appalachian Ice Complex,

because ice flowed out from local centers within the region

rather than from the Canadian Shield. All of the peripheral

ice sheets were broadly confluent with the Laurentide Ice Sheet

at the Last Glacial Maximum (LGM), and the Greenland Ice

Sheet was confluent with the Innuitian Ice Sheet. The term

Laurentide Ice Sheet is sometimes applied to this contiguous

North American ice mass, though rarely in glacial geology.

The North American ice sheet complex was by far the largest

of former late Pleistocene ice sheets, with an area of about

15 million square kilometers (17.4 million, including Green-

land ice). Its growth and decay thus accounts for more than

half, possibly as much as three quarters, of global sea-level

change during the last glacial cycle. Its presence profoundly

affected the global climate system and the isostatic deformation

of the planet.

The nucleus of this complex, the Laurentide, comprised

three major sectors, the Labrador Sector, the Keewatin Sector,

and the Baffin Sector. These sectors are named for areas of

ice sheet inception and probable areas of outflow at the

LGM. They were located respectively east, west, and north of

Hudson Bay. Continental scale syntheses of ice recession

following the LGM are given by Prest (1969), Bryson et al.

(1969), Denton and Hughes (1981), Dyke and Prest (1987),

and Dyke et al. (2003).

Wisconsinan history

Because the Laurentide Ice Sheet accounts for such a large pro-

portion of global sea-level change, the oceanic record of global

ice volume is a good proxy of its history for the period beyond

the range of reliable radiocarbon dating (>30,000 y

BP). On this

basis, the ice sheet started to nucleate about 120,000 years ago,

following marine isotopic stage 5e, and attained sequentially

greater maxima at about 115,000, 70,000, and 20,000 years

ago. It is generally agreed, though poorly demonstrated, that

ice sheet nucleation resulted from snowline lowering to the

point where snow persisted through the summers on the large

plateau areas of the Canadian Arctic Archipelago, Quebec-

Labrador, and the Arctic mainland west of Hudson Bay, for-

merly known as Keewatin. In the far north and possibly in

Hudson Bay, formation and thickening of perennial sea ice

may have assisted the process of englaciation by eliminating

iceberg calving when the ice caps advanced to shorelines.

The outlines of early Wisconsinan ice sheets are poorly known

because no moraines are now securely assigned to the maxima

at 115 ka and 70 ka (Dyke et al., 2002). If interpretations of

putative glaciolacustrine sediments (Scarborough Formation)

and till in Sunnybrook Drift at Toronto and the ages of tills

below and above the St. Pierre nonglacial sediments in the

St. Lawrence River are accepted, ice sheets reached southern-

most central Canada at these times but may not have extended

into the United States. Similarly, the extent of ice at the middle

Wisconsinan minimum (stage 3) is poorly known and has been

variously portrayed. During the ice volume minimum at about

30 ka

BP, ice cover approximately coincided with the Canadian

Shield, leaving ice cover similar to present in the Cordillera

and in the Canadian Arctic Archipelago (Dyke et al., 2002).

Late Wisconsinan glacial history is better known because it is

based on well-mapped surface glacial features, such as end

Figure L20 Isochrone map of deglaciation of North America, derived from Dyke et al. (2003).

518 LAURENTIDE ICE SHEET