NESCent
Project: 2007-2010
COMPARATIVE
SOCIOBIOLOGY AND BEHAVIORAL ECOLOGY: A SYNTHETIC
REVIEW
©
Clara B. Jones, Ph.D.
National
Evolutionary Synthesis Center (NESCent), Duke University
Revised:
2 February 2008
Introduction,
Background, and Hypotheses: The
purpose of this project is to conduct a
synthetic,
comparative analysis of the determinants of social evolution within
and across several
animal
taxa, in particular, insects, fish, birds, and mammals. Social
evolution, a density-dependent
effect,
has been characterized in two related ways in the literature, one
emphasizing an
individual’s
benefits
to a conspecific’s lifetime
reproductive success or “inclusive fitness”
(cooperation,
altruism: e.g., West, 1967), the other defining sociality as all
interindividual
interactions
among conspecifics and classifying it broadly as selfishness,
cooperation, altruism, or
spite
(e.g., Trivers, 1985), depending upon differential costs and benefits
to actor
and
recipient.
To
my knowledge, a quantitative, empirical, synthetic approach has not
been undertaken on this
topic
within and between families and classes, although several narrative
and qualitative
assessments
exist (e.g., Wilson, 1971, 1975; Vehrencamp, 1979; Helms Cahan et
al., 2002).
Sociality
occurs inconsistently though widely in nature, and several authors
(e.g., Maynard Smith
&
Szathmary, 2002; also see Taborsky, 2007) have pointed out that the
evolution of social
behavior
and social organization is a seminal biological transition, an
insight that has been
underestimated
in the scientific literature. Significantly, much debate exists not
only about the
potential
to derive general principles of social evolution but also about the
particular parameters
of
such general statements should they exist (see Crespi & Choe,
1997; Reeve, 2001; Frank,
2006;
Reeve & Hölldobler, 2007; Crespi, 2007). A comparative and
synthetic analysis of social
evolution
has the potential to reveal patterns and processes—both conserved
and taxon specific—
permitting
tests of competing hypotheses for the evolution of sociality
(especially Helms Cahan
et
al., 2002; also see Vehrencamp, 1979; Reeve, 2001; Nowak, 2006;
Frank, 2006; Reeve &
Hölldobler,
2007) as well as the identification of complementary and opposing
models within and
between
taxonomic groups (e.g., invertebrates and vertebrates; birds and
mammals; terrestrial and
aquatic
forms; arboreal and terrestrial species). These works lead to the
following tests:
Patterns
and processes in the dataset will reveal a “series” or
“trajectory” of events
about
dispersal, breeding, and alloparental care (after Helms-Cahan et al.,
2002).
This
approach permits the construction of a decision tree for each unit
within and
between
taxa and the quantitative analysis of alternative “trajectories”
including
benefits
and constraints once a database based upon empirical results for
these factors
has
been assembled. Helms Cahan et al. (2002, Table 1, p. 210) provide a
preliminary,
qualitative schema based upon data for ≈50 species; however, the
proposed
database would expand this treatment to the broadest possible range
of taxa
among
insects, fish, birds, and mammals based upon empirical reports, both
published
and unpublished. The
primary hypothesis derived from the schema of
Helms-Cahan
et al. is: Social evolution is a function of differential benefits
and
constraints
from dispersal, breeding, and alloparental care.
Recent
attempts to formulate synthetic statements of social evolution (e.g.,
Vehrencamp,
2000; Reeve, 2001; Crespi, 2005; Faulkes et al., 1997; Reeve &
Hölldobler,
2007) have advanced somewhat different suites of characteristics than
those
of Helms Cahan et al. (2002). As a result, the proposed database will
include,
as
well, measures of costs of reproduction, “reduced reproduction”,
tradeoffs between
helping
and offspring production, the presence or absence of castes,
coefficients of
within-group
relatedness, intragroup competition, and intergroup competition,
expanding
the hypothesis above by several factors.
The
proposed database would, also, permit quantitative tests of
Vehrencamp’s (1979)
narrative
schema of “evolutionary routes to sociality”. Specifically, this
author
proposes
“familial” (solitary, subsocial, intermediate subsocial, and
eusocial) and
“parasocial”
(solitary, communal, quasisocial, semisocial, and eusocial) routes as
trajectories
differentiating classes of social organisms. In addition to providing
a
quantitative
treatment of these ideas, the proposed review would evaluate these
“routes”
across a broad range of taxa.
Nowak
(2006) has recently proposed five “rules for the evolution of
cooperation”:
kin
selection, direct reciprocity, indirect reciprocity, network
reciprocity, and group
selection.
This author provides theoretical treatments for each strategy
(“rule”), and
the
realism of his results can be evaluated by the proposed analysis.
The
proposed review will also permit tests of Frank’s (2006)
theoretical formulations
concerning
the differential effects for social evolution of kin selection and
“repression
of competition” (Frank, 1995, 1998, 2006) in addition to other work
on
the
topic of “policing” (Ratnieks & Wenseleers, 2005). Combined
with the questions
based
upon the analysis of Helms Cahan et al. (2002), the new project may
yield
insights
into the necessary and/or sufficient factors favoring social
evolution.
Previous
work has sometimes viewed social effects and sexual/reproductive
effects as
effectively
the same (West, 1967; also see Taborsky, 1994; Reeve, 2001; Reeve &
Hölldobler,
2007). Importantly, however, recent treatments demonstrate the value
of
treating
Mating Systems and Social Systems from a coevolutionary perspective
(Crespi,
2007, Figure 20.1). The present project will follow Crespi’s (2007)
paradigm
in its specification, delineation, and analysis of character
traits/states, both
those
advanced in the previous literature and those deemed particularly
significant by
this
author and her future collaborators (e.g., quantified local effects
as they might
influence
density-dependence (see West et al., 2002). Paucity of available
datasets
may
require collaboration with one or more theoreticians and analyses of
data will
require
consultation with biometricians and, possibly, specialists in
bioinformatics.
Related
to the above, several authors have emphasized the importance of
polymorphisms
and polyphenisms for behavioral expression (e.g., West-Eberhard,
2003;
Jones, 2005a, b), and it has been noted that development involves
“the
ontogeny
of all aspects of the phenotype, at all levels of organization, and
in all
organisms”
(West-Eberhard, 2003, p. vii). Hypothetically, the current conceptual
framework
might be conducted at any or all levels of biological/organismal
analysis
from
the molecular to the community, tasks that appear at this point in
time to be
daunting.
Clearly, judgment calls will need to be made concerning the
parameters
and
logistics of the present project, decisions to be made in accord with
collaborators
and
advisors.
As
discussed in Jones (2005a, c; also see Jarvis, 1978; Lovegrove &
Wissel, 1988; Heinze &
Keller,
2000; Jones & Agoramoorthy, 2003; Russell et al., 2003;
Whitfield, 2006; Toth et al.,
2007),
the literature on social evolution provides many indicators that
energetic factors, in
particular,
energy savings, may provide fundamental explanations for its rise
(e.g., Leontideus
rosalia:
Kleiman, 1977; Kierulff & Rylands, 2003). I am particularly
interested in the potential
for
pathways sensitive to energy-maximization and/or energy-savings to be
implicated across taxa
in
the evolution of complex sociality (see, especially, Schoener, 1971;
Toth et al., 2007 and
references).
Ultimately, it is likely that mathematical expressions of the
fundamental energetic
aetiology
of sociality can be expressed as a function of body mass (m) derived
from the
3
fundamental
relation, E= mc2.
This treatment requires that the database envisioned herein include
information
on environmental regimes (e.g., food dispersion and quality) that can
be treated
quantitatively
with the factors advanced by Helms Cahan et al. (2002). Other
measures of
possible
significance (e.g., resource patchiness and/or environmental
stochasticity; see Emlen,
1973;
Roughgarden, 1979) can, also, be added to the analysis and to the
factors included in our
main
hypothesis stated above, decisions that will be refined as the
program progresses.
Figure
1 (see http://www.nescent.org/dir/sabbatical_fellow.php?id=00005:
© Clara B. Jones)
displays
suggested
directions of potential conflict(s) (differential optima) where one
class
or
category of individuals imposes costs in inclusive fitness upon
another class or
category
of individuals (closed arrows) to which the latter may respond
adaptively
(broken arrows). Each of these potential conflicts among interacting
individuals
or groups from different age-sex categories (or from the category of
interaction
between food and females) may be analyzed in the context of
generalized
“conflict
theory” (e.g. Rice, 2000; Gavrilets, 2000; Burt & Trivers,
2006), including
mechanisms
of coevolution resulting from evolutionary “arms races” (Van
Valen, 1973).
Across
taxa, the evolution of social behavior (interindividual interactions
among
conspecifics)
is likely to reveal the significance of causes, mechanisms,
functions, and
consequences
of patterns of conflict for complex sociality--the repression of
competition
by
selfish, cooperative, altruistic, or spiteful behavior."
Search
Strategy for the Analysis: In
addition to the solicitation of unpublished data,
conventional
search strategies will be employed, including searching databases
(e.g., Biosis,
PubMed)
and secondary sources (e.g., Wilson, 1971, 1975). Other approaches
will be evaluated
with
one or more collaborators as the project proceeds, with data quality
issues always in mind.
Sample
“Call for Data”: An
Excel file detailing all variables will be provided to potential
contributors
for input of data with 6 month timeframe for submission of data and
≈2 year
timeframe
for assembly of database.
Potential
Confounding Variables/Data Quality Issues: Judgment
calls will need to be made by
the
author and her future collaborator(s) concerning, in particular:
assessing error, including
treatment
of empty cells (if appropriate to the quantitative analyses,
confidence intervals will be
assigned);
related to the prior issue: it is unlikely that the shapes of the
populations of sampling
distributions
can be assessed; uneven quality of data, in particular, unpublished
data;
inconsistencies
between data for the same species; definitions of factors (e.g.,
primary vs.
secondary
dispersal; varieties of co-breeding); architecture of dataset
relative to methods of
quantitative
analysis (How to analyze large comparative datasets?), etc. Since
much of the theory
upon
which the present project is based is relatively recent, a major
problem will be to assemble
complete
datasets for a sufficient sample size. This challenge presents yet
another quality issue:
using
several sources to assemble complete sets of information for the same
species. With
patience
and diligence and with input from a variety of colleagues, these and
remaining quality
issues
are likely to be minimized for a first approximation of the outlined
objectives and
conceptual
framework using multivariate and/or regression treatments as well as
comparative
analysis.
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