Piecewise Structural Equation Model (SEM) Disentangles the Environmental Conditions Favoring Diatom Diazotroph Associations (DDAs) in the Western Tropical North Atlantic (WTNA)

Abstract

Diatom diazotroph associations (DDAs) are important components in the world’s oceans, especially in the western tropical north Atlantic (WTNA), where blooms have a significant impact on carbon and nitrogen cycling. However, drivers of their abundances and distribution patterns remain unknown. Here, we examined abundance and distribution patterns for two DDA populations in relation to the Amazon River (AR) plume in the WTNA. Quantitative PCR assays, targeting two DDAs (het-1 and het-2) by their symbiont’s nifH gene, served as input in a piecewise structural equation model (SEM). Collections were made during high (spring 2010) and low (fall 2011) flow discharges of the AR. The distributions of dissolved nutrients, chlorophyll-a, and DDAs showed coherent patterns indicative of areas influenced by the AR. A symbiotic Hemiaulus hauckii-Richelia (het-2) bloom (>106 cells L-1) occurred during higher discharge of the AR and was coincident with mesohaline to oceanic (30–35) sea surface salinities (SSS), and regions devoid of dissolved inorganic nitrogen (DIN), low concentrations of both DIP (>0.1 μmol L-1) and Si (>1.0 μmol L-1). The Richelia (het-1) associated with Rhizosolenia was only present in 2010 and at lower densities (10-1.76 × 105 nifH copies L-1) than het-2 and limited to regions of oceanic SSS (>36). The het-2 symbiont detected in 2011 was associated with H. membranaceus (>103 nifH copies L-1) and were restricted to regions with mesohaline SSS (31.8–34.3), immeasurable DIN, moderate DIP (0.1–0.60 μmol L-1) and higher Si (4.19–22.1 μmol L-1). The piecewise SEM identified a profound direct negative effect of turbidity on the het-2 abundance in spring 2010, while DIP and water turbidity had a more positive influence in fall 2011, corroborating our observations of DDAs at subsurface maximas. We also found a striking difference in the influence of salinity on DDA symbionts suggesting a niche differentiation and preferences in oceanic and mesohaline salinities by het-1 and het-2, respectively. The use of the piecewise SEM to disentangle the complex and concomitant hydrography of the WTNA acting on two biogeochemically relevant populations was novel and underscores its use to predict conditions favoring abundance and distributions of microbial populations.

Direct and indirect effects of flood regime on macroinvertebrate assemblages in a floodplain riverscape

“…Because of the repeated-measure structure of our dataset, we used site ID as a random effect in all models to account for unmeasured site-specific effects, and the season of each sampling event was included as fixed factor in each model to correct for seasonal effects. (Shipley, 2009;Shipley, 2013;Stenegren et al, 2017). The final model was the one with the lowest AIC and the most variables (Stenegren et al, 2017).…”

“…(Shipley, 2009;Shipley, 2013;Stenegren et al, 2017). The final model was the one with the lowest AIC and the most variables (Stenegren et al, 2017). The original model was developed to be associated with our initial hypotheses with a summary of rationale or justification presented in test H 4 , we assumed that FD and community evenness would be negatively correlated to biofilm biomass.…”

“…We then optimized this model using a stepwise backward selection procedure on the basis of the AICc for each separate generalized linear mixed model (Pasanen‐Mortensen et al, ; Theodorou et al, ). Based on the d‐separation test implemented in the PiecewiseSEM package, we incrementally incorporated significant missing pathways that further improved the AICc of the overall model (Shipley, ; Shipley, ; Stenegren et al, ). The final model was the one with the lowest AIC and the most variables (Stenegren et al, ).…”

“…Based on the d‐separation test implemented in the PiecewiseSEM package, we incrementally incorporated significant missing pathways that further improved the AICc of the overall model (Shipley, ; Shipley, ; Stenegren et al, ). The final model was the one with the lowest AIC and the most variables (Stenegren et al, ).…”

Structural Equation Modelling Reveals That Nutrients and Physicochemistry Act Additively on the Dynamics of a Microcosm-Based Biotic Community

“…Given the importance and complexity of phytoplankton dynamics, SEM has become an increasingly popular tool to study these phenomena. For example, in recent years, SEM has been successfully used to determine the drivers of diatom diazotroph associations in western tropical north Atlantic blooms [12], test hypotheses regarding the impact of climate factors on algal assemblages in a shallow temperate estuary [13], and explore the biotic and abiotic variables that contributed to the establishment of Ceratium furcoides in a shallow eutrophic reservoir [14].…”