Partitioning of the GoM based on a multi-locus assessment of the
zooplankton community
Both the results of the multivariate regression and the PCA suggest a
clear spatial and temporal segregation of zooplankton that was mainly
explained by oxygen, temperature, and longitude gradients. The
importance of longitude in the model suggests that additional unexplored
predictors related to this variable may also play key roles in shaping
the composition of the zooplankton community. In this sense, we did not
consider the longitudinal spatial gradient as a source of ecological
patterns per se but as a proxy of still unrevealed environmental
predictors that may explain a portion of the variability in the
zooplankton community
(Gluchowska
et al., 2017; Hawkins & Diniz-filho, 2004). Our results suggest that
the physical characteristics of the water column may support the
occurrence of at least three heterogeneous ecoregions within the studied
area. Such ecoregions comprise the north, south, and an eastern area
around the Yucatan peninsula. Furthermore, the characteristics of the
water profiles of each region may determine the distribution of at least
some zooplankton species, resulting in the aforementioned structural
segregation. Accordingly, the main empiric boundaries inferred in this
study may be located around 86 °W and 22 °N, which coincide with the
presence of the LC (eastern boundary) and with the southern edge of
quasi-permanent cyclonic and anticyclonic eddies (north-south boundary),
respectively.
So far, few efforts have described the pelagic communities across the
entire GoM; however, our proposed partitioning strongly supports earlier
insights based on both chlorophyll concentrations and water mass
dynamics. In this context, Damien et al. (2018) proposed the first
partitioning of the GoM along 22 °N based on chlorophyll concentrations,
while Sheinbaum et al. (2016) estimated that among 60–80% of the
horizontal variance of the Yucatan Channel is directly and/or indirectly
related with the LC. The proposed GoM partitioning was clearly evident
during the summer expeditions (cruises XIXIMI-04 and XIXIMI -06),
whereas an alternative oxygen-temperature partitioning was observed and
related with seasonal water dynamics during XIXIMI-05. The water
analysis of this cruise revealed the occurrence of two anticyclonic
eddies that crossed 22 °N, creating a north-south boundary and willing
the GoM into a diagonal south-west/north-east thermal configuration
(Fig. 6). As this boundary was detected once, we cannot state if this
water organization may be considered a usual season-specific
configuration or an anomaly, and more research is needed to resolve this
issue.
Finally, the zooplankton in the GoM seems to form a more stable
community in the southern region (south of 22 °N) compared to that of
the northern region. Indeed, stations from sampling Lines F, G, H, and J
showed low structural variability over the 3 years of observations. This
is likely explained by the higher productivity observed in this section
of the GoM compared to that of the southern region. Indeed, the northern
region is under the influence of a quasi-permanent cyclonic gyre, which
has been associated with higher nutrient concentrations, fluorescence,
and productivity compared to that of the southern region (Färber Lorda,
Athié, Camacho Ibar, Daessle, & Molina, 2019; Linacre et al., 2015;
Pérez-Brunius, García-Carrillo, Dubranna, Sheinbaum, & Candela, 2013).
The northern region is also influenced by upwelled waters from the Bank
of Campeche (Salmerón-García et al., 2011).
Temporal zooplankton variability may be also related with oxygen,
temperature, and longitude gradients. Although low environmental
variability was observed during the study, the abundance of the same
taxa, such as Mysidae, Hormathiidae, Euphausiidae, and Calanidae, likely
varied according to the co-occurrence of certain environmental
conditions. An analysis of the distributions of single taxa was not
directly addressed in this paper since our goal was to study the
temporal effects of abiotic factors on the entire zooplankton community.
However, the integration of single taxa into the analysis is essential
to fully understand the functioning of the GoM ecosystem. Their
representation in the model is critical and requires a set of
taxon-specific DNA libraries that were not available when this study was
conducted; however, the development a finer taxonomic scale is currently
underway.
Detecting the spatio-temporal variability in the zooplankton community
in this study relied on the information of a multi-locus metabarcoding
approach. Notably, despite the aforementioned observed taxonomic
discrepancies among the two loci employed in this study, similar
zooplankton distributions were obtained for both 18S and COI. This
suggests that the results obtained strongly reflect the natural
variability of the zooplankton community, and methodological bias (e.g.,
implemented molecular markers) is likely to have only marginally
affected the results. It is probable that the main limitation associated
with using the combined information of COI or 18S rRNA markers lies in
the incompleteness of reference databases and that not all zooplankton
species have reference sequences deposited for either the COI or 18S
rRNA markers
(Larke
et al., 2017; Stefanni et al., 2018). However, in contrast to previous
studies that recommended 18S rRNA as the most suitable marker for
surveying zooplankton communities
(Zhan,
Bailey, Heath, & Macisaac, 2014), our insights suggests that COI
provide similar taxa coverage of zooplankton phyla with higher taxonomic
resolution, as suggested by Machida et al. (2017). Finally, our results
support that COI may provide better taxa classifications for lower
taxonomic levels compared to those of 18S rRNA
(Larke
et al., 2017; Stefanni et al., 2018). In this study, we observed that
18S rRNA presented a relatively high affinity to Calanoida and
Euphausiacea while COI provided relatively uniform taxonomic coverage
(L. J. Clarke, Soubrier, Weyrich, & Cooper, 2014; Deagle, Jarman,
Coissac, Pompanon, & Taberlet, 2014). Due to the taxonomic
complementarity of those loci, we suggest that most comprehensive
assessments of zooplankton biodiversity may be conducted using a
synergistic multi-locus approach.