The power of the Bayesian model to detect the response of
different functional groups
The individual hypothesis for colonization and permanence of functional
groups using the space-state Bayesian model yielded at least three
different response patterns: i) the estimated parameters of permanence
and colonization confirm the hypothesis raised; ii) at least one of the
parameters confirm our hypothesis; or iii) no parameter fit the
hypothesis.
The Chironomidae and the Ceratopogonidae larvae are clear examples of
the first case. Their probabilities of permanence and colonization were
very close to the hypothesized probabilities. During the experiment we
found a low probability of permanence, but a high and moderate
probability of colonization for Chironomidae and Ceratopogonidae,
respectively. This indicates that these organisms invest primarily in a
rapid re-colonization of habitats, which is in line with the life cycle
of these organisms. The representatives of these families usually have
high densities and a relatively short life cycle (Trivinho-Strixino and
Strixino 1999). The life span of Ceratopogonidade and Chironomidae
females can reach 70 and 22 days, respectively (Braverman 1994), period
during which the females have two to four reproductive cycles (Corbi and
Trivinho-Strixino 2006).
Only the parameters estimated for the group composed by Coleoptera
larvae with depressed bodies (e.g., Macrelmis , Phanocerus ,Xenelmis ) did not support our hypotheses. Contrary to our
expectation, these larvae had a low permanence during the study period
accompanied by a moderate habitat colonization capacity. An explanation
for this pattern may be the mobility capacity of these larvae, and their
active search for habitats (Carvalho and Uieda 2006) that allows an
alternated occurrence of these organisms in the samples.
Our hypotheses were supported by at least one of the estimated
parameters of the remaining six groups. Many explanations may account
for these results, and we need highlight that some parameters may have
been overestimated in some hypotheses because we had limited previous
information about the biology of some groups. Despite this Hutchinsonian
shortfall, mobility of Coleoptera larvae, other uses to shelters (e.g.,
Trichoptera using the shelter to protect against possible natural
enemies, Morse 2009), rapid colonization in empty habitat (Ephemeroptera
and Plecoptera, Carvalho and Uieda 2004, 2006, Landeiro et al. 2010),
and the use of drift strategies for colonization (Megaloptera and some
Coleoptera and Trichoptera larvae, Krueger and Cook 1984, Townsend and
Hildrew 1994, Godoy et al. 2016) may explain the divergence between the
hypothesis and patterns observed in this study.
A relevant point in our study was the way we used the functional groups.
The groups were assembled according to life strategies based on
functional traits. In addition, we established testable numerical
hypotheses for predetermined parameters. Both biology of organisms and
ecological theory were included in a predictive way (Verberk et al.
2013). The elaboration of these hypotheses and our experimental design
in space-state made it possible for us to measure the permanence and
colonization responses separately. The separate estimation of the
parameters that represent these functional responses was essential to
understand how changes in flow conditions can impact the occurrence of
organisms. We also directly tested the axes of resistance and resilience
that summarize the fundamental theoretical functional traits of aquatic
insects undergoing disturbances in the environment (Lopez et al. 2016).
Separately, functional groups respond differently to changes in the flow
regimes, even for groups with similar baseline permanence and
colonization values.
Understanding the response of functional groups to different
disturbances is an important tool to elaborate theories and hypotheses
that explain temporal dynamics of aquatic communities, and to describe
the possible alternative states presented by communities depending on
environmental stress. Despite the separate estimates of probability of
permanence and colonization, the experimental design does not allow the
total separation between these two parameters and, thus, the estimated
parameters may have some level of covariance. The long-term permanence
probability may be the result of a continuous occupation of organisms,
partially affected by colonization processes. Despite this limitation,
the use of a space-state analysis reduces this covariance to acceptable
limits. To control and quantify this covariance, a similar study
limiting the habitat colonization is necessary. It is also noteworthy
that our experimental design was based on a categorical quantification
of the disturbances, leaving out a possible continuum for flow
disturbance intensity and frequency. However, this qualification is
common in studies that assess the effect of the disturbance on
biodiversity (Poff and Zimmerman 2010) and the levels we choose have
relevance to the type of environment we test our hypotheses.