3. Modelo de optimizaci´ on
3.3. Caso 3: Despacho econ´ omico por orden de m´ eritos, considerando flujos de
ungulate ^ rodent ° reptile • primate ^ pinneped * human ^ elasmotxanch fish ■ cetaean ° cam!V ore ^ bony fish ^ bird
8
Figure 1.1 D ata taken from Q uirling (1950). Logio-transformed brain w eight in grams plotted against Logio-transform ed body w eight in grams for species from a variety o f vertebrate orders.
Table 1.1 O rder-specific least squares regressions calculated from brain w eight
O rder n Intercept Slope SE r: P
ungulate 24 0.141 0.458 0.145 0.836 0.000 bird 52 -0.685 0.500 0.173 0.869 0.000 bony fish 40 -1.484 0.511 0.204 0.833 0.000 reptile 19 -1.914 0.570 0.182 0.937 0.000 carnivore 35 -0.557 0.579 0.149 0.917 0.000 rodent 14 -1.056 0.686 0.179 0.939 0.000 primate^ 10 -0.884 0.748 0.149 0.942 0.000 primate^ 11 -1.121 0.820 0.180 0.935 0.000
Based on values from Q uirling (1950). W eights in grams. Cetaceans and Elasm obranch fish are excluded due to inadequate sam ple sizes for regression analysis, r^ = regression coefficient. SE = standard error, n = num ber o f species represented, P = probability based on bivariate correlation w ith tw o-tailed significance o f 95%. Primate^ = prim ates excluding hum an, primate^ = prim ates including human.
1.5) H um an encephalisation relative to other prim ates
H ow ever, as noted, a predictive equation is largely a function o f the species included
in the sample. In a larger database o f prim ate brain and body w eights, com piled by
Stephan et al. (1985), hum an brain w eight and body w eight can be assessed relative to
26 other anthropoid (haplorhine) prim ates, including hum ans, and 17 prosim ian
(strepsirhine) prim ates. It should be noted that in this database, a species is often
represented by m ultiple individuals and no reference to sex is given. Tarsius syrichta
is excluded from this analysis as it is debatable w hether or not its taxonom ic affinity
lies w ith the haplorhines or strepsirhines (D ene et al. 1976, Stephan 1984, Joffe and
D unbar 1998).
Figure 1.2 is a scatterplot o f logio-transform ed brain w eight plotted against body
w eight in prim ates and shows that there is a clear grade-shift betw een these tw o infra
orders in term s o f their relationship betw een brain and body w eight, as docum ented by
other w orkers (M artin and H arvey 1985, M artin 1989a,b). A lthough haplorhine and
strepsirhine slopes are very sim ilar, the intercepts for those slopes differ, w ith the
strepsirhine intercept below that o f the haplorhines (see equations 3 and 4). The two
slopes differ significantly. These grade-shifts have clear im plications for the
calculation o f residuals. W hen fitting a haplorhine-speciflc and strepsirhine-speciflc
regression to the prim ates in the Stephan et al. (1985) database, it is possible to
calculate brain size residuals from the infra-order-speciflc regression line. Table 1.2
lists the infra-order specific residuals calculated from these data. H um an relative
brain size is assessed relative to haplorhine prim ates alone as our species clearly falls
m ost closely w ithin this grade.
Figure 1.3 shows logio-transform ed brain w eights plotted against body w eights for the
haplorhine prim ates m easured by Stephan et al (1985). H um ans and a num ber o f
other species are labeled. The least squares linear regression equations (including and
excluding hum ans) are also given (see equations 5 and 6).
There is som e debate as to w hich regression technique should be applied to data for
reduced m ajor axis regression be used, w hile M artin (1983) recom m ends the m ajor
axis regression. Falk et al. (1999) on the other hand, used least squares linear
regression to describe the relationship betw een brain size and body w eight, and
Trinkaus and H ilton (1996) argue for its use w hen predicting one variable from
another. Follow ing D ean et al. (1999) and Trinkaus and H ilton (1996), least squares
linear regression is used here.
A ccording to Sokal and R o h lf (1997) least squares regression allows for the
calculation o f residuals from a m ean regression line, w here the sum o f the squared
deviations (calculated as a vertical line from the data point to the line) is as sm all as
possible, and w here m easurem ent error associated w ith the independent variable is
relatively low. In contrast, the m ajor axis model assum es that m easurem ent error is
greater on the x-axis, w hile the reduced m ajor axis m odel assum es that the error is
even on both axes, and o f a very low order (Ricker 1973, R ayner 1985).
Figure 1.3 shows that hum ans have a m arkedly positive residual (+0.39) relative to the
other anthropoid prim ates in the sample. Table 1.2 lists the species-specific residuals
calculated from strepsirhine and haplorhine regressions, and shows that M iopithecus
talapoin, Saim iri sciurus, Cebus sp. and Lagothrix lagothricha are also notably
encephalised for prim ates o f their body size. C orresponding EQ values based on the
m am m alian regression given by M artin (1983) are also listed. R esulting
encephalisation values differ depending on the regression used.
In this regression analysis, the chim panzee is not encephalised relative to the other
anthropoids in the sample. Rather, its brain w eight lies on the regression line. This
contradicts other studies (Jerison 1973, M artin 1983) and is likely an artifact o f the
individual used in the Stephan et al. (1985) sample rather than the species as a w hole.
The above regressions show that there is variation in relative brain size am ong both
haplorhine prim ates (sd = 0.13, n = 26) and strepsirhine prim ates (sd = 0.12, n = 17) .
A num ber o f w orkers have attributed this variation in relative brain size to adaptations
arising from variation in social dem ands (Byrne and W hiten 1988, D unbar 1992,
ecological/foraging dem ands (M ilton 1979, 1988; Parker and G ibson 1979, Clutton-
B rock and H arvey 1980, G ibson 1986, M acN ab and Eisenberg 1989, Barton and
Purvis 1994, Barton 1996, Barton and D unbar 1997). These authors argue that
varying levels o f social com plexity and/or foraging com plexity have placed
differential selection pressures on species for encephalisation. R eader and Laland
(2002), in contrast argue that increased brain size has evolved in response to
innovation, social intelligence and tool use.
For exam ple, D unbar (1992) argued that neocortex size and group size are correlated
in prim ates, w ith highly social prim ates having relatively large neocortices - the part
o f the brain associated w ith abstract thought, foreplanning and association formation.
H e suggested that the com plex nature o f prim ate social interactions w as the selection
pressure for increased neocortex size, largely in response to the cognitive dem ands o f
m aintaining social cohesion in large groups in w hich individuals m ust m onitor
com plex triadic relationships.
K evem e et al. (1996) found that the neocortex is under the control o f the m aternal
genom e and the authors suggested that increased neocortex size, therefore, evolved in
m atrilinial prim ate societies, associated w ith com plex hierarchical relationships.
In contrast, Clutton-Brock and H arvey (1980) show ed that brain w eight is correlated
w ith diet and hom e range in prim ates. The authors argued that increased relative brain
w eight in frugivores, over folivores, is associated w ith increased cognitive dem ands o f
m onitoring a w idely dispersed and ephem eral food resources (i.e. fruit). Barton
(1996) showed sim ilar findings in assessing the relationship betw een neocortex size
and behavioral ecology in prim ates.
Parker and G ibson (1977) and G ibson (1986) have argued that ecological selection
pressures, particularly the cognitively com plex task o f extractive foraging o f
em bedded food resources, has been the driving force behind increased brain w eight in
R eader and Laland (2002), rather than arguing for a social versus ecological
intelligence model, have suggested that these social and ecological cognitive
processes are not m utually exclusive but interact to produce innovative behaviors, the
basis for increased brain size selection in prim ates, w ith both social and ecological
benefits. The authors cite tool use as an outcome o f these cognitive processes.
M uch o f the w ork on the social intelligence hypothesis and the ecological intelligence
hypothesis, how ever, is based on cross-sectional data and indirect m easures o f social
and ecological intelligence. M oreover, there is disagreem ent as to the functional
correlates o f relative brain size. For example. D eacon (1997) has argued that in non
hum an prim ates, encephalisation does not reflect increased brain size, but rather
reduced body size (dwarfism) over evolutionary time.
In summary, encephalisation is a m easure o f brain size relative to body size. There
m ay be som e disagreem ent as to w hether encephalisation in non-hum an prim ates has
evolved in réponse to increased brain size or decreased body size, but m ost authors
agree that a com bination o f social and ecological selection pressures have favored
4.0'
■2
3.0
O c i m isimians
" prosimians