TY - JOUR
T1 - Net energy intake rate as a common currency to explain swan spatial distribution in a shallow lake
AU - Gyimesi, A.
AU - Varghese, S.
AU - De Leeuw, J.
AU - Nolet, B.A.
N1 - Reporting year: 2012
Metis note: 5133; WAG; AnE
PY - 2012
Y1 - 2012
N2 - Animal distribution is usually predicted from the
spatial variation in food biomass, whereas foraging theory
commonly uses net energy intake rate as the currency to be
maximized. We tested whether net energy intake rate better
predicted the distribution and abundance of tundra swans
than food biomass. In a shallow lake, we mapped the density
of sago pondweed tubers during 2 years, and calculated the
foraging benefits and costs to tundra swans. Swan residence
was expressed in bird-days, i.e. the sum of daily counts. We
used four measures of increasing complexity to predict
bird-days per inlet: total food biomass (B), total food
biomass above giving-up density (B+), total accessible food
biomass above giving-up density (aB+), and total achievable
net energy intake rate above giving-up energy intake
rate (NEI+). Considering both years, observed bird-days of
inlets correlated only with NEI+, and not with B, B+, or aB+.
In both years, our predictions of bird-days based on the
NEI+model better matched observed relationships than the
predictions of the other three models. Our case study suggests
that in heterogeneous wetlands, correcting for givingup
density, food accessibility and foraging costs may be
necessary in order to predict bird distribution and
abundance.
AB - Animal distribution is usually predicted from the
spatial variation in food biomass, whereas foraging theory
commonly uses net energy intake rate as the currency to be
maximized. We tested whether net energy intake rate better
predicted the distribution and abundance of tundra swans
than food biomass. In a shallow lake, we mapped the density
of sago pondweed tubers during 2 years, and calculated the
foraging benefits and costs to tundra swans. Swan residence
was expressed in bird-days, i.e. the sum of daily counts. We
used four measures of increasing complexity to predict
bird-days per inlet: total food biomass (B), total food
biomass above giving-up density (B+), total accessible food
biomass above giving-up density (aB+), and total achievable
net energy intake rate above giving-up energy intake
rate (NEI+). Considering both years, observed bird-days of
inlets correlated only with NEI+, and not with B, B+, or aB+.
In both years, our predictions of bird-days based on the
NEI+model better matched observed relationships than the
predictions of the other three models. Our case study suggests
that in heterogeneous wetlands, correcting for givingup
density, food accessibility and foraging costs may be
necessary in order to predict bird distribution and
abundance.
KW - national
U2 - 10.1007/s13157-011-0256-6
DO - 10.1007/s13157-011-0256-6
M3 - Article
SN - 0277-5212
VL - 32
SP - 119
EP - 127
JO - Wetlands
JF - Wetlands
IS - 1
ER -