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Tools for Analyzing Functioning: From Single
Species to Functional Traits
Many studies that link biodiversity with ecosystem functioning have focused on different biodiversity metrics, multiple
processes and ecological interactions (Reiss et al. 2009). The
usage of experimental data and modeling has been discussed,
since the combination of these approaches could allow the
detection of early signs of functioning shifts due to predicted
global change. In this section a set of tools for studying the
functioning of ecosystems is proposed. First, we focus on
dynamic energetic budget (DEB) for single-species analysis
due to the importance of evaluating the contribution of each
component of functional groups. Second, we illustrate the
use of ecological network analysis (ENA) to study
community- level interactions. Third, we suggest the use of
loop analysis (LA) to investigate how external inputs affect
ecosystems.
Species Level Analysis Using the Dynamic
Energy Budget (DEB) Model
The first step for studying an ecosystem is to understand the
contribution of each component since ecological processes
can be related to multiple species and at the same time one
species might be involved in multiple processes (Reiss et al.
2009). The DEB is an individual-based model proposed as a
method to analyze the role of the individual into the functioning context.
Kooijman (2010) proposes the DEB model for analyzing
energy fluxes within individuals (Fig. 2). The DEB theory is
based on the first law of thermodynamics and assumes the
conservation of energy and mass. The model focuses on
three basic energy fluxes: assimilation, dissipation and
growth. Assimilation is the inflow of energy that enters the
reserve pool proportional to the surface area of the organism.
It is represented by the feeding minus the material excreted
via feces, in the case of heterotrophs. In photoautotrophs,
assimilation refers to the acquisition of nutrients mainly by
photosynthesis (Edmunds et al. 2011). The energy reserve is
used by the organism for maintenance, growth and reproduction. Dissipation corresponds to maintenance processes that
use part of the reserve, which will result in products released
into the environment, i.e., respiration. Growth corresponds to
the increase of body size. The model also includes energy
from the reserve that is invested in reproduction.
The DEB model is ideal for integrating single-species
experimental outcomes (Edmunds et al. 2011). The model
connects data acquired from physiology and structure of the
organisms, i.e., functional traits, to provide an overview of
the species as a system. In addition, the DEB model is able
to describe the impacts of disturbance, e.g., pollutants
(Nisbet et al. 2000; van der Meer 2006). The model also
allows the assessment of the organisms from larval to adult
stage, e.g., Monaco et al. (2014) carried out experiments
with the sea-star Pisaster ochraceus under different lifestages and determined the transitions according to body size.
The empirical data was used to predict the responses (e.g.,
flow of energy from reserve, structure and gonads to biomass). However, to exploit the potential of DEB models,
more experiments considering how the traits change under
different environmental conditions (e.g., temperature) would
be necessary. The analysis of energy fluxes under future
environmental state may assist the prediction of how the species will respond to environmental shifts or even to the new
regions where they can be introduced. Knowing how species
will respond is crucial because the species may change (e.g.,
become more or less efficient in processing energy or even
disappear), resulting in biodiversity reshuffling under the
effect of global change drivers.
The software developed for the DEB model is called
DEBtool
9
for Matlab. It enables the user to analyze ecophysiological data by calculating relationships between variables and check the model predictions.
Analyzing single-species systems corresponds to finding
only one piece of the entire puzzle. Putting empirical data
together using a DEB model has good potential for single
species and population analysis but the usage for ecosystems
is still not certain (Nisbet et al. 2000). Muller et al. (2009)
used the DEB model for analyzing the flow of energy using
carbon and nitrogen as currencies of an autotroph, a heterotroph, and the symbiotic interaction between them. However,
for modeling the complex interactions of ecosystems we
suggest ENA as a better approach.
Ecological Network Analysis (ENA)
In order to connect the species embedded into a system and
their relationships with abiotic components, ENA is a useful
tool. It increases the complexity of food web analysis by
quantifying the flow of energy and including interactions
with non-living compartments that are part of the ecosystem
(Gaedke 1995; Fig. 2). Food web models depict topological
webs, i.e., binary networks where the species are the nodes
(compartments) and the connections between them are
representations of “who eats whom”. ENA analysis considers that the food webs are exchanging energy with and within
non-living compartments as well (Magri et al. 2017). The
analysis is considered weighted when it includes the infor9 The software and additional information can be found here: http://
www.bio.vu.nl/thb/deb/deblab/
F. R. Barboza et al.
Tools for Analyzing Functioning: From Single
Species to Functional Traits
Many studies that link biodiversity with ecosystem functioning have focused on different biodiversity metrics, multiple
processes and ecological interactions (Reiss et al. 2009). The
usage of experimental data and modeling has been discussed,
since the combination of these approaches could allow the
detection of early signs of functioning shifts due to predicted
global change. In this section a set of tools for studying the
functioning of ecosystems is proposed. First, we focus on
dynamic energetic budget (DEB) for single-species analysis
due to the importance of evaluating the contribution of each
component of functional groups. Second, we illustrate the
use of ecological network analysis (ENA) to study
community- level interactions. Third, we suggest the use of
loop analysis (LA) to investigate how external inputs affect
ecosystems.
Species Level Analysis Using the Dynamic
Energy Budget (DEB) Model
The first step for studying an ecosystem is to understand the
contribution of each component since ecological processes
can be related to multiple species and at the same time one
species might be involved in multiple processes (Reiss et al.
2009). The DEB is an individual-based model proposed as a
method to analyze the role of the individual into the functioning context.
Kooijman (2010) proposes the DEB model for analyzing
energy fluxes within individuals (Fig. 2). The DEB theory is
based on the first law of thermodynamics and assumes the
conservation of energy and mass. The model focuses on
three basic energy fluxes: assimilation, dissipation and
growth. Assimilation is the inflow of energy that enters the
reserve pool proportional to the surface area of the organism.
It is represented by the feeding minus the material excreted
via feces, in the case of heterotrophs. In photoautotrophs,
assimilation refers to the acquisition of nutrients mainly by
photosynthesis (Edmunds et al. 2011). The energy reserve is
used by the organism for maintenance, growth and reproduction. Dissipation corresponds to maintenance processes that
use part of the reserve, which will result in products released
into the environment, i.e., respiration. Growth corresponds to
the increase of body size. The model also includes energy
from the reserve that is invested in reproduction.
The DEB model is ideal for integrating single-species
experimental outcomes (Edmunds et al. 2011). The model
connects data acquired from physiology and structure of the
organisms, i.e., functional traits, to provide an overview of
the species as a system. In addition, the DEB model is able
to describe the impacts of disturbance, e.g., pollutants
(Nisbet et al. 2000; van der Meer 2006). The model also
allows the assessment of the organisms from larval to adult
stage, e.g., Monaco et al. (2014) carried out experiments
with the sea-star Pisaster ochraceus under different lifestages and determined the transitions according to body size.
The empirical data was used to predict the responses (e.g.,
flow of energy from reserve, structure and gonads to biomass). However, to exploit the potential of DEB models,
more experiments considering how the traits change under
different environmental conditions (e.g., temperature) would
be necessary. The analysis of energy fluxes under future
environmental state may assist the prediction of how the species will respond to environmental shifts or even to the new
regions where they can be introduced. Knowing how species
will respond is crucial because the species may change (e.g.,
become more or less efficient in processing energy or even
disappear), resulting in biodiversity reshuffling under the
effect of global change drivers.
The software developed for the DEB model is called
DEBtool
9
for Matlab. It enables the user to analyze ecophysiological data by calculating relationships between variables and check the model predictions.
Analyzing single-species systems corresponds to finding
only one piece of the entire puzzle. Putting empirical data
together using a DEB model has good potential for single
species and population analysis but the usage for ecosystems
is still not certain (Nisbet et al. 2000). Muller et al. (2009)
used the DEB model for analyzing the flow of energy using
carbon and nitrogen as currencies of an autotroph, a heterotroph, and the symbiotic interaction between them. However,
for modeling the complex interactions of ecosystems we
suggest ENA as a better approach.
Ecological Network Analysis (ENA)
In order to connect the species embedded into a system and
their relationships with abiotic components, ENA is a useful
tool. It increases the complexity of food web analysis by
quantifying the flow of energy and including interactions
with non-living compartments that are part of the ecosystem
(Gaedke 1995; Fig. 2). Food web models depict topological
webs, i.e., binary networks where the species are the nodes
(compartments) and the connections between them are
representations of “who eats whom”. ENA analysis considers that the food webs are exchanging energy with and within
non-living compartments as well (Magri et al. 2017). The
analysis is considered weighted when it includes the infor9 The software and additional information can be found here: http://
www.bio.vu.nl/thb/deb/deblab/
F. R. Barboza et al.