[Population Modeling] Introduction

[Amiyaal Ilany]

Hi, I am Amiyaal Ilany. Here is a description of my work (feel free to cut
it if it's too long):

I am a behavioral ecologist interested in broad aspects of social behavior.
I incorporate theories and approaches from several disciplines, including
mathematics, statistics, and sociology, and use empirical and theoretical
methods to better understand behavioral phenomena. Much of my research
focuses on the study of social networks and on principles of animal
communication.

*The causes and consequences of social networks*

Social network analysis is a powerful framework that provides metrics to
quantify social structure at different levels of organization. I have
adopted this approach to utilize the extensive dataset of social
interactions in a wild rock hyrax population monitored for the last 15
years by Dr. Eli Geffen’s group (Tel Aviv University). I integrate concepts
and analytical tools coming from the fields of biology, sociology and
network science that aid in understanding the causes and consequences of
social relationships. One such example is the theory of structural balance,
suggesting that humans tend to close triads in their social networks
(following ‘the friend of my friend is my friend’ rule), resulting in
clustered networks, in which individuals form cohesive social groups. I was
the first to apply this theory to a non-human animal, and found that its
predictions were fulfilled in the rock hyrax population I study, suggesting
that clustering has a role in the evolution of social structures. The
stability of hyrax networks was found to depend on the interplay between
the stabilizing forces of clustering, and the instability introduced mainly
by incoming individuals, i.e. new individuals that have not yet found their
social niche and embedded into the social network.

An important aspect of social networks that is poorly understood both
theoretically and empirically is their temporal dynamics. The current
static approach being used by most studies, that ignores temporal dynamics,
is unable to disentangle the different factors influencing social
structure. A focus of my postdoctoral research has been developing and
testing new theory that uses simple rules of cooperation to elucidate
social network dynamics. I developed a general agent-based model that
demonstrates how social stability is achieved when cooperation is practiced
in cohesive clusters of individuals. I found the tendency to form clusters
to explain the formation of stable social groups and also the mechanism
behind fission-fusion societies, with no need for more complex mechanisms
such as kin selection, reciprocity and policing, and in the face of
cheating. Nevertheless, my model predicts individuals to form groups with
their kin, and with individuals that share similar traits.

With Dr. Kay Holekamp (Michigan State University), I am studying the causes
and consequences of social network dynamics in a wild population of
individually identified spotted hyenas in Kenya. I use data collected over
25 years to identify the factors influencing long term network dynamics. I
employed stochastic agent-based models, borrowed from statistical
sociology, that allow me to estimate the contribution of multiple factors
to long-term network changes. I classify these factors into four groups: 1)
external environmental conditions, such as rainfall and prey abundance; 2)
a tendency to associate according to individual traits, such as sex and
social rank; 3) dyadic factors, such as genetic relatedness; and 4)
structural network effects, such as triadic closure. My analysis of social
network dynamics found that multiple factors determine network dynamics,
with the tendency towards clustering being the most consistent factor, as
predicted by my theoretical model. My results imply that cooperation is a
result of a complex set of causes, and emphasize the significance of
structural properties of the network in affecting individuals’ social
choices.

Identifying the factors determining social structure is the first step in
understanding the effect of sociality on life history and fitness, in terms
of longevity, mating and reproductive success. In the rock hyrax, I have
found that individuals survived longer if they were members of
socially-homogenous groups, in which social associations were more evenly
spread. No direct correlation was found between individuals’ centrality
within their social networks and longevity, suggesting that stress in
groups suffering higher social inequality may negatively affect longevity
in all individuals belonging to these groups. Investigating another role of
social structure, I employed a novel network approach to analyze the mating
patterns of the promiscuous rock hyrax. Surprisingly, I have found that
males that had high-ranked rivals were more likely to mate a female in any
specific mating interaction. Thus, my network approach revealed subtle
patterns of sexual selection that were masked when using a traditional
population level regression approach.

Links to relevant papers:

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0022375

http://www.tau.ac.il/lifesci/departments/zoology/members/geffen/documents/aoi93.pdf

http://www.nature.com/srep/2014/140326/srep04472/full/srep04472.html?WT.ec_id=SREP-631-20140401

All the best,
Amiyaal Ilany


-- 
Dr. Amiyaal Ilany
Postdoctoral Fellow
Department of Biology
University of Pennsylvania
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