Transcript poster

Paradox of the Cichlids
T.Janzen & R.S.Etienne
Community and Conservation Ecology Group, University of Groningen
Introduction
The young age and high diversity of the cichlids in the three African rift
lakes has amazed biologists, ecologists and evolutionary researchers for
many years. Lake Tanganyika is deeper, older, and has a more complex
bathymetry than the other two lakes. Ecological and evolutionary theory
tells us that it should have the most species of the three lakes, but it has
the fewest.
Why?
Lake
Victoria
Lake
Lake
Malawi Tanganyika
Age (My)
0.25-0.75
3–5
9 – 12
# Species
~700
~700
~250
68 635
29 600
32 893
83 m
706 m
1 471 m
Area (km2)
Water height
Depth
Million years ago
Proposed lake level of Lake Tanganyika
Existing theory ignores external factors
•Lake Age Differences in age could promote diversity by
granting more time for speciation to act, but it also grants
more time for extinction to occur.
•Water level fluctuations Over the history of the three
lakes water level changes have not been rare instances,
but rather recurring phenomena. Frequent changes of
water level could promote diversificiation by changing
lake size.
•Bathymetry Lake Tanganyika is the deepest of the three
lakes and consists of three sub-basins that cause the lake
to split up when water levels are low. Interaction between
the water level and the bathymetry could therefore
promote allopatric speciation.
Research questions
•How do external factors influence biodiversity?
•How do allopatric and sympatric speciation interact during
adaptive radiation?
•What is the influence of bathymetry on the differences in
biodiversity in the rift lakes?
•Is sexual selection stronger in lake Malawi compared to lake
Tanganyika?
picture courtesy Jen Reynolds
Approach
To answer these questions we will make use of spatially explicit individual based
simulations. We will develop a general model assessing the influence of
environment size, environment shape and environment stability on
biodiversity. Using this general model we will be able to make predictions on the
african rift lake system, incorporate specifics of the african rift lakes and make
accurate predictions about current biodiversity estimates.