This sequential limiting of resources means that the addition of a single resource would not push the system into highly unstable dynamics, reducing the probability that the ‘‘paradox of
Trang 1Ecologists are beginning to understand how stoichiometry
and nutritional balance affect population and food web
dy-namics Nevertheless, it is extremely likely that herbivore
growth is often less than maximal solely because their
en-vironment does not provide sufficient quantities of all key
nutritional requisites In fact, the greatest disparity in
bio-chemical, elemental, and stoichiometric composition in the
entire food web occurs at the link where herbivores convert
plant material into animal tissue The implication is clear:
Even in a world full of green energy, many or most herbivores
cannot obtain enough requisite resources to grow, survive, or
reproduce at high rates Nutritional shortages regulate
herbi-vore numbers and often limit their effects on plant biomass
Recent theoretical studies of the role of food quality in terms
of edibility and nutrient content show that low food quality can
greatly influence consumer–resource interactions This has
two important consequences First, low food quality reduces
the growth rate of the consumer, making that interaction
more stable Second, in systems in which multiple resources
could be limiting, the addition of large amounts of a single
resource (such as nitrogen or phosphate) may increase that
resource to a level at which it is no longer limiting; however, a
second resource would become limiting and so on This
sequential limiting of resources means that the addition of a
single resource would not push the system into highly
unstable dynamics, reducing the probability that the ‘‘paradox
of enrichment’’ occurs Rosenzweig introduced the concept of
the paradox of enrichment to explain the addition of a resource
leading to the collapse of a consumer–resource interaction This
happens because the addition of the resource drives the
population of the consumer to a higher level that results in
overcompensation by the consumer (predator) driving the
re-source (prey) extinct However, most systems have several
po-tentially limiting resources For example, Leibold’s study of
ponds found that nitrogen additions do not lead to strong
trophic cascades or the paradox of enrichment because light
becomes limiting with relatively modest nitrogen additions
Interaction Strength
One goal of functional webs is the quantification of
inter-action strengths within food webs Various definitions have
been used for ‘‘interaction strengths.’’ In Lotka–Volterra
mod-els, interaction strengths are due solely to the direct
inter-actions between species pairs and are measured on a per capita
basis Estimations of the strength of these direct interactions
are fraught with difficulties Measurements in artificial systems
may not allow for behavioral responses For example, Sih has
shown that prey species have different escape mechanisms or
routes depending on the species of predator Thus, when in
the presence of two predators, the response of a prey may
result in its increased susceptibility to one or the other
predator due to a behavior that is not evidenced when only
the one predator is present
Measurements in natural systems are also problematic
be-cause they may not account for indirect interactions Many
studies have elucidated the interaction strength among pairs of
species However, indirect effects may play a strong role in
determining the realized interaction strength Thus, Paine has
argued that interaction strengths should always be measured
in the field with the full complement of natural species present and that these measurements should incorporate all indirect effects The realized interaction strength accounts for all direct and indirect interactions For example, predator–prey inter-actions are functionally negative due to the direct effect However, the indirect effect of a predator may reduce the number of competitors of the prey species, thus resulting in an overall positive interaction strength (direct þ indirect effects) Therefore, potentially strong indirect effects can make mech-anistic interpretation of experimental results among species difficult
Path analysis, a new statistical method, has been used to evaluate causal hypotheses concerning the strengths of inter-actions in many systems Path analysis is essentially a multiple regression on each species in which specific causal relation-ships (e.g., alternative food web configurations), specific ex-perimental treatments, and other interactions are diagrammed
in a community interaction web The community interaction
is essentially a food web to which nonconsumptive inter-actions, such as pollination, competition, and mutualisms are added Hypotheses for the causal relationships between pairs
of species not directly linked can become quite complicated However, path analysis can test different hypothesized com-munity web structures by accounting for both direct and in-direct relationships Then, experimental manipulations (e.g., species removals or additions) can test predictions of the path analysis
Can Energetic Webs Provide Insight into Population and Community Dynamics?
A problem in food web studies is how to connect the great amount of quantitative information in energetic webs to population and community dynamics described by functional webs Much progress would occur if we could determine the dynamical importance of a particular species or feeding link from an inspection of the magnitude of energy transfer or diet composition Unfortunately, no clear answer is forthcoming
In fact, it appears that even highly quantified information such
as the number of calories passed along a certain pathway or the frequency of prey in the diet of a consumer conveys little information about the dynamics of interacting populations because these descriptive parameters do not correlate with interaction strength
There is no clear rationale to argue that food web dynamics and energetics are necessarily correlated; indeed, logic and evidence suggest that dynamics often cannot be predicted from data on diet or energy flow The degree of resource suppression is not a function of energy transfer Consumer regulation of populations need involve little energy transfer and few feeding interactions For example, removing predatory rats from New Zealand islands increased lizard abundance 3–30 times although lizards formed o3% of rat’s diet Key regulatory factors may produce much less overall mortality than other factors Brief, intense predation episodes may net little energy for the predator but may be central to prey dy-namics The consumption of young stages (seeds, eggs, and larvae) may provide trivial energy to a consumer but can
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