Environmental Engineering Reference
In-Depth Information
is controlled by and can be predicted from supply rates of a few key resources
(e.g., nitrogen, phosphorus water, and light). In contrast, little has been written about the
controls and prediction of secondary production. In part, this is because primary produc-
tion has often been viewed as an aggregate measurement that encompasses all primary
producers in an ecosystem (e.g., see Table 2.1 in Chapter 2), whereas secondary produc-
tion has been viewed at the level of individual populations, or at most guilds of consu-
mers. As we will see, secondary production is least predictable at the level of individual
populations. Here, I will address the problems of predicting and understanding the con-
trols on secondary production at three distinct levels: the production of an individual
species of consumer, the production of a guild of consumers, and the production of the
entire community of consumers. Perhaps surprisingly, predictions of secondary produc-
tion become simpler and more precise as we move from individual populations to entire
communities of consumers.
PRODUCTION OF AN INDIVIDUAL SPECIES
OF CONSUMER
Several papers (
Plante and Downing 1989; Morin and Bourassa 1992; Benke 1993;
Tumbiolo and Downing 1994; Cusson and Bourget 2005
) have considered the problem of
predicting the production of an individual species of consumer. All of these papers were
based on empirical analyses of published data, were restricted to aquatic invertebrates,
and reached similar conclusions (
Figure 3.4
):
Secondary production is readily predictable, but with a confidence interval of about
five-fold (in each direction around the mean, for a total width of 25-fold), from the
average annual biomass of the population, the body size of the animal, and the
temperature of the habitat.
Biomass is by far the best single predictor of production; adding body size and
temperature to the models adds little predictive power.
Model coefficients suggest that production depends linearly on biomass (i.e.,
B
1.0
),
inversely on the fourth-root of body mass (
M
2
0.25
), and on temperature with a Q
10
of
2 to 2.5. Production thus parallels the mass-dependence of many metabolic processes on
M
2
0.25
(
Peters 1983
).
Tumbiolo and Downing (1994)
additionally found that production of marine inverte-
brates was correlated with water depth and habitat type (i.e., seagrass beds vs. unvege-
tated habitats). They interpreted these findings as evidence that production was affected
by food quality, with higher production rates in places with high food quality. Tumbiolo
and Downing's result is interesting because it suggests that
P/B
(as opposed to
B
)is
increased in shallow waters and seagrass beds, which implies an increase in mortality as
well as growth in these food-rich environments. Thus, the whole pace of life may be
increased by the high-quality food in plant beds, just as it apparently is reduced in food-
poor ground waters (
Figure 3.2
).
Although these empirical models show that production of animal populations can read-
ily be predicted (albeit with considerable error), all of them rely chiefly on an estimate of
