Embedded Files
Environmental conditions
Environmental conditions
During the sampling period, the temperature values indicated the presence of cold waters during the seasonal upwelling period or dry season (January – April) (mean = 23.3°C; s.d. = 2.9). On the other hand, the water temperature during the wet season or the non-upwelling season (May – December) showed warm waters (mean = 28.2°C; s.d. = 0.7) (Figure 8). The maximum temperature value recorded during this study was 29.4°C and the minimum value 17.4°C. This value ranges match previous data from studies made in the Bay of Panama, which indicates that during the upwelling season the sea temperature decreases below 20°C and during the rainy season it can reach temperatures around 29°C.
Salinity presented higher values (35.1 ‰; s.d. = 1.3) during upwelling compared to the non-upwelling season (33.2 ‰; s.d. = 1.3) (Figure 8). Our data remain within the salinity ranges obtained from previous studies where it is mentioned that the salinity during the rainy season is generally less than 30 ppt. due to the increase in rainfall and meanwhile during the upwelling the salinity increases. As shown in our data, in coastal upwelling systems, temperature is inversely related to salinity, as was obtained in our study, where the highest values of temperature coincided with the lowest values of salinity.
The dissolved oxygen values we obtained (Figure 8) are related to other studies that described that one of the characteristics in coastal seasonal upwelling systems is that by increasing nutrients, dissolved oxygen in seawater decreases their concentrations. In our study, the organisms presented a higher abundance in non-upwelling conditions, where dissolved oxygen is higher.
Figure 11. Environmental conditions in relation with the depth of the sites and the two different seasons.
Density and diversity of the pelagic gastropods
Density and diversity of the pelagic gastropods
The project had a total duration of 11 months, starting in April 2019 and ending in March 2020. A total of 390 zooplankton samples were collected at the three sampling sites, 246 samples corresponding to the non-upwelling period and 96 samples during seasonal upwelling.
Pelagic gastropods were identified by their morphological characteristics within the taxa Pteropoda and Pterotracheoidea, up to the most specific taxon, in this case genus or suborder. We found ten taxa from the order Pteropoda: Cavolinia, Creseis, Gymnosomata, Clio, Peracle, Desmopterus, Diacavolinia, Diacria, Hyalocylis and Limacina (Figure 9). On Pterotracheoidea we collected three genera: Atlanta, Firoloida and Pterotrachea (Figure 9). The genera that displayed a higher density throughout the sampling period between the three sample sites were Creseis, Hyalocylis, Atlanta and Gymnosomata (Figure 9). The remain genera had a very low representation between the upwelling and non-upwelling seasons. The genera Cavolinia, Desmopterus, Firoloida and Pterotrachea were only recorded during the upwelling period, while the genus Diacria was only reported during non-outcrop (Figure 9).
Figure 12. Holoplanktonic gastropods registered on this study. A) Diacavolinia, B) Cavolinia, C) Diacria, D) Clio, E) Hyalocylis, F) Creseis, G) Limacina, H) Paraclione, I) Desmopterus, J) Atlanta, K) Pterotrachea, L) Firoloida.
Community composition
Community composition
The correlation show:
CCA1 has:
Positive correlation with pH (0.47) and water temperature (0.34)
Negative correlation with salinity (-0.41)
CCA2 shows very weak correlations with all variables
The CCA biplot shows:
Environmental vectors (red arrows):
pH and water temperature point in similar directions, indicating they are positively correlated
Salinity points in roughly the opposite direction, showing negative correlation with temperature and pH
Dissolved oxygen shows a different pattern, suggesting some independence from other variables
Species distributions:
Some species (like Creseis) show strong associations with certain environmental conditions
Other species show more neutral positions, suggesting less environmental specificity
The spread of species points indicates different environmental preferences among species
Figure 13. CCA Biplot of the three sites (Bay of Panama, Las Perlas and Taboguilla).
Figure 14. CCA Biplot of the Bay of Panama
The CCA analysis shows that the environmental variables in the Bay of Panama explain about 14% of the total variation in species data (constrained inertia ≈ 0.1728 of the total 1.2297). Even though the overall explained variation is moderate, the first canonical axis (CCA1) captures around 54.5% of that constrained variation. This indicates a dominant environmental gradient influencing species distribution at this site.
The envfit results reveal that all four environmental variables are highly significant (p = 0.001). Noteworthy details include:
Water Temperature: Has a strong positive contribution to CCA1 and CCA2, suggesting higher values strongly influence the species patterns.
pH: Also shows a solid contribution, reinforcing its importance.
Dissolved Oxygen and Salinity: Both are significant, with salinity having a notably strong negative vector along CCA1.
This outcome confirms that multiple environmental gradients are at play, with temperature and salinity being particularly influential.
The overall constrained analysis of the Las Perlas site shows that the environmental variables together explain about 16.4% of the total variation in the species data. A closer look at the constrained eigenvalues indicates that the first canonical axis (CCA1) captures roughly 86.6% of the constrained variation, whereas the remaining axes contribute much less. This suggests that a single dominant environmental gradient—driven by the measured variables—is largely responsible for structuring the species assemblages at this site.
The envfit analysis indicates:
pH (ph_mean.1m): Shows strong significance (p = 0.001) with a high vector magnitude (0.95660 on CCA1), suggesting a robust influence on species distribution.
Salinity (salinity_ppt_mean.1m): Also highly significant (p = 0.001) and with a strong negative contribution along CCA1, indicating that salinity gradients are critical.
Water Temperature (water.temperature_C_mean.1m): Moderately significant (p = 0.039), while
Dissolved Oxygen (dissolved.oxygen_mg/L_mean.1m): Is similarly significant at p = 0.040.
Thus, while all environmental variables contribute to the species patterns, pH and salinity are particularly influential at Las Perlas.
Figure 15. CCA Biplot of Las Perlas.
Figure 16. CCA Biplot of Taboguilla.
The overall CCA model shows that only about 3.1% of the variation in the pteropod community data is constrained by the measured environmental variables. However, when looking at the constrained eigenvalues, the first axis (CCA1) alone explains about 58.15% of the constrained variation, while CCA2 accounts for about 19.34%. In other words, although the overall constrained variation is relatively small compared to the total inertia, the environmental gradient revealed by CCA1 is dominant at Taboguilla.
The envfit results indicate:
pH (ph_mean.1m) is highly significant (p = 0.001) with a strong vector correlation (0.98638 on CCA1).
Water Temperature (water.temperature_C_mean.1m) is also significant (p = 0.015) with a moderately strong influence.
Dissolved oxygen and salinity do not show significant relationships in this site, as their p-values suggest a lack of strong association.
This tells us that at Taboguilla the environmental gradient most strongly associated with species distribution is pH, with water temperature playing a secondary role.
For seasonal effects in Taboguilla indicates a highly significant difference between seasons (p = 0.001) with an R² of about 0.067. This suggests that, although only about 6.7% of the overall variation in species composition can be explained by the season, the seasonal differences are statistically significant. Thus, seasonality plays an important role in structuring the pteropod community at this site.
Environmental variables on density of species
Environmental variables on density of species
The Linear Discriminant Analysis (LDA) plot (Figure 14) shows the separation of environmental variables among the three sites: Bay of Panama (red), Las Perlas (green), and Taboguilla (blue). The ellipses represent the 95% confidence intervals for each site. There is noticeable overlap among the groups, indicating that the environmental conditions across the sites are somewhat similar. However, Taboguilla shows a broader distribution along the first linear discriminant axis, suggesting greater environmental variability compared to the other sites. Las Perlas displays the most compact clustering, implying more homogeneous environmental conditions. Although there is some differentiation, especially between Taboguilla and the other sites, the overlapping ellipses suggest that environmental variables alone do not completely discriminate among these locations.
Figure 17. LDA of environmental variables.
Figure 18. PCA of environmental variables and species.
The PCA biplot (Figure 15) illustrates the relationship between environmental variables, species densities, and sampling sites (Bay of Panama, Las Perlas, and Taboguilla). The first two principal components explain 23.8% (Dim1) and 13.2% (Dim2) of the variation. Arrows indicate the influence of environmental variables, with dissolved oxygen and water temperature positively correlated along Dim1, while salinity is negatively correlated. Species such as Gymnosomata, Atlanta, and Hyalocylis are associated with higher dissolved oxygen and temperature, whereas Cresesis is linked to lower salinity. Sites show considerable overlap, though Taboguilla displays a wider spread, indicating greater environmental variability. The clustering suggests some environmental differentiation, but species composition overlaps among the sites.
From the Figure 16, a PCA Biplot, we can observe that water temperature, pH, and dissolved oxygen (in orange) are strongly correlated and point in a similar direction, suggesting that these factors collectively influence pteropod distributions. Salinity, on the other hand, is pointing in a different direction, indicating that it has a different, possibly opposing, effect on species distribution compared to temperature-related variables. The species names, shown in green and blue, are positioned based on their associations with these environmental factors. For example, species such as Cavolinia and Pterotrachea are positioned along the same axis as salinity, suggesting a stronger association with saline environments. In contrast, species like Hyalocylis and Creseis are more aligned with high temperature and low oxygen conditions, indicating that they thrive in warmer, less oxygenated waters.
Overall, this PCA biplot highlights how environmental factors shape the distribution of pteropod species, with temperature, pH, and oxygen playing a major role in defining community structure. The clustering of species suggests that different groups have distinct environmental preferences, which could have important ecological implications for understanding how pteropods respond to changing ocean conditions.
Figure 19. PCA of Pteropods.
Conclusions
Conclusions
The results of this study highlight the significant impact of seasonal variability on the abundance and distribution of pteropod species. The analysis of species abundance reveals a significant seasonal variation, with all three species—Creseis, Hyalocylis, and Atlanta—showing higher numbers during the wet season compared to the dry season. Creseis emerges as the most dominant species in both seasons, with an 11-fold increase in the wet season (11,167 individuals) compared to the dry season (1,011 individuals). Hyalocylis exhibits the most pronounced relative increase, with a 17-fold rise from 104 individuals in the dry season to 1,807 individuals in the wet season. Similarly, Atlanta follows the same trend, increasing fourfold from 144 individuals to 543 individuals. The consistency in relative abundance across seasons (Creseis > Hyalocylis > Atlanta) suggests a stable ecological structure, with Creseis maintaining its dominance despite seasonal fluctuations. These patterns indicate that the wet season offers more favorable conditions for pteropod proliferation, likely due to increased water temperature, dissolved oxygen levels, and nutrient availability.
The pronounced seasonal differences in species abundance align with environmental shifts that distinguish the wet and dry seasons. The wet season, characterized by higher temperatures, pH, and dissolved oxygen, creates conditions that support greater pteropod densities, while the dry season’s higher salinity may impose physiological stress on these species. The exceptionally high increase in Hyalocylis during the wet season suggests that this species is particularly sensitive to these environmental changes, while Creseis shows a more resilient yet substantial response. These findings, supported by multivariate analyses such as PCA and NMDS, emphasize the role of environmental parameters in shaping community composition. The observed fluctuations in pteropod abundance and diversity could have cascading effects on marine food webs and ecosystem functioning, particularly in response to climate change and shifting ocean conditions. Continued monitoring of these species and their environmental drivers is essential for understanding long-term ecological trends and the potential impacts of environmental disturbances on marine ecosystems.
Page updated
Report abuse