Predicting warming-induced hypoxic stress for fish in a fragmented river channel using ecosystem metabolism models

Aquatic biota often face multiple anthropogenic threats such as river fragmentation and climate change that can contribute to high rates of aquatic species imperilment world-wide. Temperature-induced hypoxia is one under-explored mechanism that can threaten aquatic species in fragmented rivers with reduced flows. We applied ecosystem metabolism models to define the effect of water temperature on net ecosystem production (NEP) of oxygen at 12 sites of a fragmented river channel that supports three fish species at risk and experiences hypoxia. We found that water temperature and precipitation events at 75% of our sites were significantly and negatively correlated to NEP estimates and explained 28% of the variation in NEP within sites. Temperature-induced reductions in NEP at these sites likely contributed to hypoxic conditions threatening the three species at risk as NEP explained 41% of the variation in dissolved oxygen near all sites. Our results have applications for understanding drivers of hypoxic stress in fragmented watercourses, integrating water temperature-NEP effects with oxygen demands of sensitive fish species, and modeling future effects of climate change on aquatic species.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Microbial Ecology of Methanotrophy in Streams Along a Gradient of CH4 Availability

Despite the recognition of streams and rivers as sources of methane (CH4) to the atmosphere, the role of CH4 oxidation (MOX) in these ecosystems remains poorly understood to date. Here, we measured the kinetics of MOX in stream sediments of 14 sites to resolve the ecophysiology of CH4 oxidizing bacteria (MOB) communities. The streams cover a gradient of land cover and associated physicochemical parameter and differed in stream- and porewater CH4 concentrations. Michealis–Menten kinetic parameter of MOX, maximum reaction velocity (Vmax), and CH4 concentration at half Vmax (KS) increased with CH4 supply. KS values in the micromolar range matched the CH4 concentrations measured in shallow stream sediments and indicate that MOX is mostly driven by low-affinity MOB. 16S rRNA gene sequencing identified MOB classified as Methylococcaceae and particularly Crenothrix. Their relative abundance correlated with pmoA gene counts and MOX rates, underscoring their pivotal role as CH4 oxidizers in stream sediments. Building on the concept of enterotypes, we identify two distinct groups of co-occurring MOB. While there was no taxonomic difference among the members of each cluster, one cluster contained abundant and common MOB, whereas the other cluster contained rare operational taxonomic units (OTUs) specific to a subset of streams. These integrated analyses of changes in MOB community structure, gene abundance, and the corresponding ecosystem process contribute to a better understanding of the distal controls on MOX in streams

Principal component analysis of experimental phytoplankton assemblages at the a) division, b) genus, and c) species level of taxonomic resolution.

<p>Genera and species were selected if their cumulative biomass over the course of each experiment was more than 1% of the total for any of the 12 enclosures. Algal densities were log₁₀(x +1)-transformed as needed, and categorical nitrogen treatments (e.g.,+or – urea) were included as passive variables. All samples were included in each PCA; however, to simplify presentation, sample ordination points are not presented and only select taxa are identified. Coloured arrows indicate cyanobacteria (blue), chlorophytes (green), cryptophytes (red), diatoms (yellow), dinoflagellates (brown), and chrysophytes (purple). Proportion of total variation explained by first (x) and second (y) principle axes are presented.</p

Least-squares regression analysis of the linear relationship between microscopic and chromatographic estimates of phytoplankton abundance.

<p>Phytoplankton biomass was measured by microscopy, while concentrations of taxonomically-diagnostic biomarker pigments were analysed by spectrophotometry (chlorophyll <i>a</i>) and high performance liquid chromatography (all other pigments). Data were log₁₀(x+1) transformed prior to analysis (<i>df</i> = 58). Algal biomass was summed according to distribution of indicator pigments prior to statistical analysis.</p

Biomass responses of important phytoplankton species to fertilisation with nitrogen in mesocosms conducted in Augusts and September.

<p>Biomass presented as mg wet mass L⁻¹. Symbols represent mean and standard errors (± SE, <i>n</i> = 3) for each of the nitrogen treatments, including addition of NH₄⁺ (shaded triangle, coarse dashed line), NO₃⁻ (shaded square, medium dashed line) and urea (shaded circle, fine dashed line), as well as unamended (control) mesocosms (solid circle, solid line).</p

Repeated-measures analysis of variance for the response of selected phytoplankton taxa to added nitrogen.

<p>Probability (<i>p</i>) values were calculated for treatment and treatment-time interaction effects. Tukey’s HSD <i>post hoc</i> results represent mean treatment values ordered from largest to smallest and significant differences (>) at α = 0.05, for urea (U), nitrate (NO), ammonium (NH), and the control (C). If a treatment falls on both sides of a “>” this indicates no significant difference from the treatments on either side. All phytoplankton biomass (mg L⁻¹) data were log₁₀(x+1??transformed prior to analysis to meet assumptions of normality. Probabilities were not corrected for number of comparisons.</p

Biomass responses of major phytoplankton groups to fertilisation with nitrogen in mesocosms conducted in August and September.

<p>Algal groups (mg wet mass L⁻¹) include; a) cyanobacteria, b) chlorophytes, c) diatoms, d) chrysophytes, e) cryptophytes and f ) dinoflagellates. Symbols represent mean and standard errors (± SE, <i>n</i> = 3) for each of the nitrogen treatments, included amendments with NH₄⁺ (shaded triangle, coarse dashed line), NO₃⁻ (shaded square, medium dashed line) and urea (shaded circle, fine dashed line), as well as unamended (control) mesocosms (solid circle, solid line).</p