9780521861724htl 1..2

(Jacob Rumans) #1

Prediction 2
Assuming that a population is at equilibrium density (i.e. N/M0.75), popula-
tion biomass (B¼MN, mg dry mass or ash-free dry mass m^2 ) will increase
with body mass, such that B/M0.25(Fig.4.1). This relationship is attributed to a
lower rate of flow of energy and resources through the bodies of large versus
small organisms (indicated by time-specific P/B, see AppendixI, Fig.4.10)asa
result of lower metabolic costs (see Prediction 3, below; Brown et al., 2004).


Prediction 3
Biomass turnover rate (P/B, yr^1 ) will decrease with increasing M, because
organisms with large body sizes often have longer development times (or CPIs,
AppendixI) compared with organisms with small body sizes. The decrease in
P/B is proportional to M0.25(Fig.4.1), which is equivalent to dividing P/M^0 (see
Prediction 4, below) by B / M0.25. P/B / M0.25 is identical to the relationship of the
empirically derived mass-specific metabolic rate with M (Brownet al., 2004).


Prediction 4
Production (P¼BP/B, mg dry mass or ash-free dry mass m^2 yr^1 ) will be
independent of body size (Brownet al., 2004). This is because the product of
B/M0.25and P/B/M0.25is equivalent to P/M^0 (Fig.4.1).
Each of these predictions is subject to the assumptions that resource supply and
temperature are constant across body-size classes. These assumptions appear to
be reasonable for population and taxon-specific production statistics extracted
from withinsingleandindependentstream communities rather than for data that
are pooled across communities. This is an important distinction because most
studies of the relationship between body size and components of production are
based on the analysis of variables pooledacrossa diverse assemblage of commu-
nities and ecosystems (e.g. Banse & Mosher, 1980 ; Benke, 1993 ; Morin & Dumont
1994 ;Brownet al., 2004), yet the factors believed to constrain these variables –
such as temperature and nutrient and organic carbon supply – operatewithin
communities and ecosystems (see Cyr & Walker, 2004 ).


Study streams
We used data from four streams for our tests of these predictions – the
Ogeechee River, Georgia; Upper Ball Creek, North Carolina; and Sutton
Stream and Stony Creek, New Zealand. Each stream has perennial flow and
we assume that trophic resources limit community secondary production
rather than physical factors such as disturbance (see assumptions related to
Prediction 1). Since our data sets are based on discrete communities we are able
to assume that representatives of the different body-mass classes within each
system were subject to similar resource and temperature regimes. We chose
these streams because the production dynamics of their communities has


BIOMASS TURNOVER AND BODY SIZE 57
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