High Methane Emissions from a Midlatitude Reservoir Draining an Agricultural Watershed

Reservoirs are a globally significant source of methane (CH₄), although most measurements have been made in tropical and boreal systems draining undeveloped watersheds. To assess the magnitude of CH₄ emissions from reservoirs in midlatitude agricultural regions, we measured CH₄ and carbon dioxide (CO₂) emission rates from William H. Harsha Lake (Ohio, U.S.A.), an agricultural impacted reservoir, over a 13 month period. The reservoir was a strong source of CH₄ throughout the year, emitting on average 176 ± 36 mg C m^–2 d^–1, the highest reservoir CH₄ emissions profile documented in the United States to date. Contrary to our initial hypothesis, the largest CH₄ emissions were during summer stratified conditions, not during fall turnover. The river–reservoir transition zone emitted CH₄ at rates an order of magnitude higher than the rest of the reservoir, and total carbon emissions (i.e., CH₄ + CO₂) were also greater at the transition zone, indicating that the river delta supported greater carbon mineralization rates than elsewhere. Midlatitude agricultural impacted reservoirs may be a larger source of CH₄ to the atmosphere than currently recognized, particularly if river deltas are consistent CH₄ hot spots. We estimate that CH₄ emissions from agricultural reservoirs could be a significant component of anthropogenic CH₄ emissions in the U.S.A

Macroinvertebrate variables before, during, and after treatment for control and experimental sites.

<p>Mean (± SE) back-transformed values are reported for insect richness (A) and total richness (B) based on riffle bucket samples, and Shannon diversity (C) and % dominant (D) based on biomass values for riffle bucket samples. <i>P</i>-values reflect results of ANOVA for Group*Period interaction; only significant biotic models (<i>P</i><0.05) are included (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085011#pone-0085011-t004" target="_blank">Table 4</a>).</p

Water chemistry before, during, and after treatment for control and experimental sites.

<p>Mean (± SE) back-transformed values are reported. Conductivity (A) was sampled during seasonal biotic monitoring, and calcium (B), iron (C), and sulfate (D) were sampled during monthly baseflow water quality monitoring. <i>P</i>-values reflect results of ANOVA for Group*Period interaction for the strongest models (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085011#pone-0085011-t003" target="_blank">Table 3</a>).</p

Biotic variable summary statistics and ANOVA results for Group*Period interaction.

1<p>Lambda is value for the exponential transformation.</p>2<p>**<i>P</i><0.01, *<i>P</i><0.05.</p>3<p>PIBI is the Periphyton Index of Biotic Integrity <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085011#pone.0085011-Hill1" target="_blank">[45]</a>.</p>4<p>Macroinvertebrate variables were calculated separately for multi-habitat net samples (based on abundance data) and bucket samples in riffle habitats (represented as abundance and biomass).</p>5<p>EPT represents taxa in the orders Ephemeroptera, Plecoptera, and Trichoptera (considered sensitive to disturbance).</p

Physical and chemical variable summary statistics and ANOVA results for Group*Period interaction.

<p>¹ Lambda is value for the exponential transformation.</p><p>²***<i>P</i><0.001, *<i>P</i><0.05.</p>3<p>Habitat variables (including some water quality variables) were sampled five times per year during biotic sampling events.</p>4<p>HHEI score from Ohio Environmental Protection Agency Primary Headwater Habitat Evaluation Index <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085011#pone.0085011-Ohio1" target="_blank">[40]</a>.</p>5<p>QHEI score from Rapid Bioassessment Protocols Quantitative Habitat Assessment for high gradient streams, and filamentous algae score (range 0–4) is from RBP benthic macroinvertebrate field sheet <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085011#pone.0085011-Barbour1" target="_blank">[39]</a>.</p>6<p>Water quality variables were sampled monthly during baseflow conditions.</p

Non-metric multidimensional scaling ordination for macroinvertebrate biomass from bucket samples.

<p>Assemblages were different for Control (C) vs. Experimental (E) sites (Axis 2) and comparing Before (B), During (D), and After installation of stormwater management (Axes 1, 3, and all; <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085011#pone-0085011-t005" target="_blank">Table 5</a>). The 3D solution explained 84.3% of the variation, and the final stress was 15.8.</p

Non-metric multidimensional scaling ordination for macroinvertebrate abundances from bucket samples.

<p>Assemblages were different for Control (C) and Experimental (E) sites (Axes 2 and 3) and comparing Before (B), During (D), and After (A) installation of stormwater management (all axes combined; <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085011#pone-0085011-t005" target="_blank">Table 5</a>). The 3D solution explained 86.2% of the variation, and the final stress was 16.1.</p

ANOVA results for ordination axes.

1<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085011#pone-0085011-t002" target="_blank">Table 2</a> for variable descriptions.</p>2<p>***<i>P</i><0.001, **<i>P</i><0.01, * <i>P</i><0.05. – indicates effect not tested in combined axis model.</p>3<p>Macroinvertebrate abundance and biomass were based on bucket samples in riffle habitats.</p

Shepherd Creek catchment and subcatchments in Cincinnati, Ohio (USA).

<p>Sub1 was nested within Sub2, Sub4 was nested within Sub3, and all of the subcatchments drained to the catchment outlet (Catch). Sub 5a was discontinued in 2006. Rain barrels and rain gardens were installed throughout the catchment except in Sub4 and Sub5.</p

Catchment area and land cover based on cumulative piped catchments draining to each site.

<p>¹ Forest cover is based on topographic catchment.</p><p>² Total impervious area (%) includes all impervious surfaces identified by air photos and site visits <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085011#pone.0085011-Roy2" target="_blank">[38]</a>.</p><p>³ Directly connected impervious area (DCIA) was calculated by subtracting the rooftop area draining to rain barrels installed in 2007 and 2008.</p><p>⁴ Stormwater management installations includes number of rain barrels and rain gardens installed in 2007 and overall (2007 & 2008), and the total density of barrels and gardens within each subcatchment.</p