217
15 Biogeochemical Indicators of Nutrient Enrichments in Wetlands …
eutrophication. An optimal resource allocation model can
then be very useful to assess the effects of wetland nutrient
enrichment on the microbial communities through enzyme
activities comparing with reference (unenriched) wetland
sites.
The microbial allocation of resources among community indicator enzymes (MARCIE) model was originally
developed by Sinsabaugh and Moorhead (1994) and subsequently evaluated (Sinsabaugh and Findlay 1995; Sinsabaugh et al. 1997; Sinsabaugh et al. 2002). It describes the
enzymatic activity of microbial communities in relation to
microbial production through a first order model that includes specific C, N and P allocation factors. It is based on
the premise that (i) ectoenzymatic hydrolysis of complex
molecules is the rate-limiting step in microbial activity; (ii)
that ectoenzyme synthesis is controlled at the level of transcription by induction and repression-derepression mechanisms that are linked to environmental nutrient availabilities
(Chróst 1991) and (iii) that to community level these regulatory processes appear as an optimal resource allocation
strategy (Sinsabaugh et al. 1997). In this model, extracellular enzymes are grouped into three main categories: those
involved in carbon acquisition (E C ), those involved in nitrogen acquisition (E N ), and those involved in phosphorus
acquisition (E P ). Enzyme activities serve as indicators of the
relative availability of C, N, and P. Because of their common regulatory action, it is assumed that the activities of the
many enzymes in each group are sufficiently correlated such
that the activity of one, or preferably a few, enzymes in each
group can act as an indicator for the whole group. The basic
form of this model for microbial production is:
P = k C E C
where P is the production rate and k C is a first-order rate
constant (production per unit E C activity). The expression of C-acquiring enzymes is constrained by the need
to enzymatically acquire N and P; thus E C can also be expressed as a fraction of total extracellular enzyme production (E T = Σ(E C, E N ,E P )) whose value is dependent on N and
P availability:
P = k C E T /(1 + E N /E C + E P /E C )
The model can be evaluated by the fact that (i) the microbial
production rates are proportional to total enzyme activity E T ,
and (ii) the microbial productivity is a function of specific
nutrient acquiring enzymes E T /(1 + E N /E C + E P /E C ), therefore exhibiting specific resource allocation versus generic
resource allocation. Two ratios of interest can then be formulated: E C /E N and E C /E P or the ratios between the amounts of
enzyme activity associated with C acquisition to the enzymes
involved in N and P acquisition. In addition these ratios become indices of relative N and P limitation. Pearson’s correlation coefficients between E T and E T /(1 + E N /E C + E P /E C )
can be used to assess the preferential resource allocation: a
strong positive coefficient approaching 1 indicates no difference in resource allocation (i.e., relative quantities of enzyme production), whilst weak to no significant correlations
indicate the prevalence of one or more enzymes (Corstanje
et al. 2007). Log plots of E C /E N vs E C /E P are used to assess
the relative P availability (E C /E P ) versus the relative N availability (E C /E N ) (Fig. 15.8).
Since the lumping of cellulases with polyphenol oxidative
enzymes in an E C term is problematic because both enzyme
classes are differentially regulated in relation to N, Sinsabaugh et al. (2002) recommend separate E C into two terms,
one for enzymes involved in the breakdown of holocellulose,
E Cel , and one for enzymes involved in the oxidation of lignin
and other polyphenols, E ox .
Microbial responses may vary based on litter quality
(lignin to cellulose content), the type of electron acceptors
present (oxidases vs. hydrolases) and the actual microbial
community composition (fungal phytases vs. bacterial and
plant phosphatases). Thus, the ideal situation is to include
in the assessment more than one enzyme representative of
the C, N, and P cycles each. E terms are calculated on a relative basis because of the different scalar ranges of the assays
and because assay methodology varies widely. The activity
of each enzyme is standardized to a 0–1 scale by dividing
each value by the maximum value for that enzyme in the data
set. For an E term that includes multiple enzymes activities,
the standardized values of each constituent enzyme are averaged. Usually E P included the standardized activity of acid
or alkaline phosphatase; E N the mean standardized activity
of proteases, aminopeptidases or glucosaminidases; E C the
mean standardized activity of β-glucosidase, cellobiohydrolase, endoglucanase, phenol oxidase, or peroxidase (E cel
includes the mean standardized activity of β-glucosidase,
cellobiohidrolase, endoglucanase while E ox considers the
standardized activity of phenol oxidase or peroxidase).
Significant higher levels of E C /E P and E C /E N ratios have
been found at wetland nutrient-enriched sites compared with
reference (pristine) areas (Fig. 15.8; Table 15.2; Corstanje
et al. 2007; Penton and Newman 2007). Greater E C /E P values
reflect a decrease in apparent P control on C mineralization
as a consequence of lower C:P ratios derived from P influx.
Higher E C /E N at nutrient-enriched sites has been cited owing
to elevated β-glucosidase associated with microbial production (Penton and Newman 2007). The protein content of the
organic matter source modifies the E C /E N ratio; the higher
protein percentage of algae compared with macrophyte tends
to decrease the E C /E N values (Penton and Newman 2007).
This approach helped clarify how nutrient enrichments
induce shifts on microbial allocation of resources. In the Everglades, in terms of enzyme activity the nutrient impacted
15 Biogeochemical Indicators of Nutrient Enrichments in Wetlands …
eutrophication. An optimal resource allocation model can
then be very useful to assess the effects of wetland nutrient
enrichment on the microbial communities through enzyme
activities comparing with reference (unenriched) wetland
sites.
The microbial allocation of resources among community indicator enzymes (MARCIE) model was originally
developed by Sinsabaugh and Moorhead (1994) and subsequently evaluated (Sinsabaugh and Findlay 1995; Sinsabaugh et al. 1997; Sinsabaugh et al. 2002). It describes the
enzymatic activity of microbial communities in relation to
microbial production through a first order model that includes specific C, N and P allocation factors. It is based on
the premise that (i) ectoenzymatic hydrolysis of complex
molecules is the rate-limiting step in microbial activity; (ii)
that ectoenzyme synthesis is controlled at the level of transcription by induction and repression-derepression mechanisms that are linked to environmental nutrient availabilities
(Chróst 1991) and (iii) that to community level these regulatory processes appear as an optimal resource allocation
strategy (Sinsabaugh et al. 1997). In this model, extracellular enzymes are grouped into three main categories: those
involved in carbon acquisition (E C ), those involved in nitrogen acquisition (E N ), and those involved in phosphorus
acquisition (E P ). Enzyme activities serve as indicators of the
relative availability of C, N, and P. Because of their common regulatory action, it is assumed that the activities of the
many enzymes in each group are sufficiently correlated such
that the activity of one, or preferably a few, enzymes in each
group can act as an indicator for the whole group. The basic
form of this model for microbial production is:
P = k C E C
where P is the production rate and k C is a first-order rate
constant (production per unit E C activity). The expression of C-acquiring enzymes is constrained by the need
to enzymatically acquire N and P; thus E C can also be expressed as a fraction of total extracellular enzyme production (E T = Σ(E C, E N ,E P )) whose value is dependent on N and
P availability:
P = k C E T /(1 + E N /E C + E P /E C )
The model can be evaluated by the fact that (i) the microbial
production rates are proportional to total enzyme activity E T ,
and (ii) the microbial productivity is a function of specific
nutrient acquiring enzymes E T /(1 + E N /E C + E P /E C ), therefore exhibiting specific resource allocation versus generic
resource allocation. Two ratios of interest can then be formulated: E C /E N and E C /E P or the ratios between the amounts of
enzyme activity associated with C acquisition to the enzymes
involved in N and P acquisition. In addition these ratios become indices of relative N and P limitation. Pearson’s correlation coefficients between E T and E T /(1 + E N /E C + E P /E C )
can be used to assess the preferential resource allocation: a
strong positive coefficient approaching 1 indicates no difference in resource allocation (i.e., relative quantities of enzyme production), whilst weak to no significant correlations
indicate the prevalence of one or more enzymes (Corstanje
et al. 2007). Log plots of E C /E N vs E C /E P are used to assess
the relative P availability (E C /E P ) versus the relative N availability (E C /E N ) (Fig. 15.8).
Since the lumping of cellulases with polyphenol oxidative
enzymes in an E C term is problematic because both enzyme
classes are differentially regulated in relation to N, Sinsabaugh et al. (2002) recommend separate E C into two terms,
one for enzymes involved in the breakdown of holocellulose,
E Cel , and one for enzymes involved in the oxidation of lignin
and other polyphenols, E ox .
Microbial responses may vary based on litter quality
(lignin to cellulose content), the type of electron acceptors
present (oxidases vs. hydrolases) and the actual microbial
community composition (fungal phytases vs. bacterial and
plant phosphatases). Thus, the ideal situation is to include
in the assessment more than one enzyme representative of
the C, N, and P cycles each. E terms are calculated on a relative basis because of the different scalar ranges of the assays
and because assay methodology varies widely. The activity
of each enzyme is standardized to a 0–1 scale by dividing
each value by the maximum value for that enzyme in the data
set. For an E term that includes multiple enzymes activities,
the standardized values of each constituent enzyme are averaged. Usually E P included the standardized activity of acid
or alkaline phosphatase; E N the mean standardized activity
of proteases, aminopeptidases or glucosaminidases; E C the
mean standardized activity of β-glucosidase, cellobiohydrolase, endoglucanase, phenol oxidase, or peroxidase (E cel
includes the mean standardized activity of β-glucosidase,
cellobiohidrolase, endoglucanase while E ox considers the
standardized activity of phenol oxidase or peroxidase).
Significant higher levels of E C /E P and E C /E N ratios have
been found at wetland nutrient-enriched sites compared with
reference (pristine) areas (Fig. 15.8; Table 15.2; Corstanje
et al. 2007; Penton and Newman 2007). Greater E C /E P values
reflect a decrease in apparent P control on C mineralization
as a consequence of lower C:P ratios derived from P influx.
Higher E C /E N at nutrient-enriched sites has been cited owing
to elevated β-glucosidase associated with microbial production (Penton and Newman 2007). The protein content of the
organic matter source modifies the E C /E N ratio; the higher
protein percentage of algae compared with macrophyte tends
to decrease the E C /E N values (Penton and Newman 2007).
This approach helped clarify how nutrient enrichments
induce shifts on microbial allocation of resources. In the Everglades, in terms of enzyme activity the nutrient impacted