Effect of environmental predictors on zooplankton diversity
As previously observed for the northern GoM, environmental conditions in
the southern GoM “were comparable among years, but more variable in
space” (Elliott, Pierson, & Roman, 2012). Indeed, similar patterns of
zooplankton spatial aggregations over-time allowed us to combine the
genetic information of each field expedition in order to explore the
spatio-temporal variability in the zooplankton community as a whole in a
comprehensive analysis.
Our findings suggest that all tested environmental predictors may
promote changes in the structure of the zooplankton community, even with
low contribution percentages. The simplest explanation for such a poor
relationship is that other factors, which were not taken into
consideration (e.g., nutrient variation and irradiance, among others),
could also be involved in shaping the structure of the zooplankton
community of the study area. Moreover, biotic interactions within a
zooplankton community, such as predation or symbiotic associations, may
also shape the structure of the community (Gasca, Suárez-Morales, &
Haddock, 2007; Hereu et al., 2020; Jennifer E. & Mary N., 2001).
However, alternative and/or complementary possibilities may be also
proposed. In this regard, it has been previously reported that
environmental predictors generally show patchiness
(Espinasse,
Carlotti, Zhou, & Devenon, 2014; Gluchowska et al., 2017; Trudnowska,
Gluchowska, Beszczynska-Möller, Blachowiak-Samolyk, & Kwasniewski,
2016; Usov et al.,
2019), which
hampers pattern assessments over a continuous space
(Helenius,
Leskinen, Lehtonen, & Nurminen, 2017; Usov et al.,
2019). This may
become particularly relevant in studies that consider large-scale
geographic areas or the open ocean, in which environmental gradients
usually show three-dimensional reorganizations
(Usov et al.,
2019).
Thus, multiple factors like winds, currents, and water mass movements,
among others, may disrupt the linearity of hydrological boundaries
(Espinasse et
al., 2014; Usov et al.,
2019).
In our study, the discontinuity of hydrological patterns mainly
challenged the cluster organization of the sampling stations. Indeed,
even stations that were geographically close to one another presented
dissimilarities in environmental profiles that ranged from small to
large. These divergences mostly concerned stations located in the
central portion of the sampling area (Lines C, D, and E), suggesting
that this area may be considered a transitional region separating the
northern and southern ecoregions.
Finally, the low strength of the correlations between abiotic and biotic
factors may be also explained by considering the experimental design.
One of the aims of this study was to relate the environmental variables
with the structural patterns of the zooplankton community. Accordingly,
the environmental data were evaluated in the context of the zooplankton
community, which may have hidden taxa-specific ecological niche
partitioning. For example, the abundance of a given taxon may increase
in response to a specific combination of environmental conditions, but
simultaneously, the same conditions may provoke a decrease in the
abundance of other taxa (Elliott et al., 2012). Hence, the observed low
environmental contribution percentages may have been the result from
opposing taxa-specific responses to the same environmental cues. If
validated, this supposition may be used to re-evaluate the implications
of the observed correlations. In this context, we posit that the
inclusion of additional predictors into the model may not necessarily
result in a strengthening of the correlations between biotic and abiotic
variables, as some taxa will likely respond positively to a new
predictor while others may respond negatively. Nonetheless, additional
research is needed to support or reject this hypothesis.