Reviews and syntheses: Spatial and temporal patterns in seagrass metabolic fluxes

Seagrass meadow metabolism has been measured for decades to gain insight into ecosystem energy, biomass production, food web dynamics, and, more recently, to inform its potential in ameliorating ocean acidification (OA). This extensive body of literature can be used to infer trends and drivers of seagrass meadow metabolism. Here, we synthesize the results from 56 studies reporting in situ rates of seagrass gross primary productivity, respiration, and/or net community productivity to highlight spatial and temporal variability in oxygen (O2) fluxes. We illustrate that daytime net community production (NCP) is positive overall and similar across seasons and geographies. Full-day NCP rates, which illustrate the potential cumulative effect of seagrass beds on seawater biogeochemistry integrated over day and night, were also positive overall but were higher in summer months in both tropical and temperate ecosystems. Although our analyses suggest seagrass meadows are generally autotrophic, the effects on seawater oxygen are relatively small in magnitude. We also find positive correlations between gross primary production and temperature, although this effect may vary between temperate and tropical geographies and may change under future climate scenarios if seagrasses approach thermal tolerance thresholds. In addition, we illustrate that periods when full-day NCP is highest could be associated with lower nighttime O2 and increased diurnal variability in seawater O2. These results can serve as first-order estimates of when and where OA amelioration by seagrasses may be likely. However, improved understanding of variations in NCPdic:NCPO2 ratios and increased work directly measuring metabolically driven alterations in seawater pH will further inform the potential for seagrass meadows to serve in this context

A review of the opportunities and challenges for using remote sensing for management of surface-canopy forming kelps

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cavanaugh, K. C., Bell, T., Costa, M., Eddy, N. E., Gendall, L., Gleason, M. G., Hessing-Lewis, M., Martone, R., McPherson, M., Pontier, O., Reshitnyk, L., Beas-Luna, R., Carr, M., Caselle, J. E., Cavanaugh, K. C., Miller, R. F., Hamilton, S., Heady, W. N., Hirsh, H. K., Hohman R., Lee L. C., Lorda J., Ray J., Reed D. C., Saccomanno V. R., Schroeder, S. B. A review of the opportunities and challenges for using remote sensing for management of surface-canopy forming kelps. Frontiers in Marine Science, 8, (2021): 753531, https://doi.org/10.3389/fmars.2021.753531.Surface-canopy forming kelps provide the foundation for ecosystems that are ecologically, culturally, and economically important. However, these kelp forests are naturally dynamic systems that are also threatened by a range of global and local pressures. As a result, there is a need for tools that enable managers to reliably track changes in their distribution, abundance, and health in a timely manner. Remote sensing data availability has increased dramatically in recent years and this data represents a valuable tool for monitoring surface-canopy forming kelps. However, the choice of remote sensing data and analytic approach must be properly matched to management objectives and tailored to the physical and biological characteristics of the region of interest. This review identifies remote sensing datasets and analyses best suited to address different management needs and environmental settings using case studies from the west coast of North America. We highlight the importance of integrating different datasets and approaches to facilitate comparisons across regions and promote coordination of management strategies.Funding was provided by the Nature Conservancy (Grant No. 02042019-5719), the U.S. National Science Foundation (Grant No. OCE 1831937), and the U.S. Department of Energy ARPA-E (Grant No. DE-AR0000922)

Predicting Coral Reef Carbonate Chemistry Through Statistical Modeling: Constraining Nearshore Residence Time Around Guam

To accurately predict the impacts of ocean acidification on shallow-water ecosystems, we must account for the biogeochemical impact of local benthic communities, as well as the connectivity between offshore and onshore water masses. Estimation of residence time can help quantify this connectivity and determine the degree to which the benthos can influence the chemistry of the overlying water column. We present estimates of nearshore residence time for Guam and utilize these estimates to model the effects of benthic ecosystem metabolism on the coral reef carbonate system. Control volume and particle tracking approaches were used to estimate nearshore residence time. These estimates were paired with observed patterns in the reef carbonate system around Guam using water samples collected by NOAA's National Coral Reef Monitoring Program. Model performance results suggest that when considering the effects of benthic metabolism on the carbonate system, it is paramount to represent the contact time of the water volume with the benthos. Even coarse estimates of residence time significantly increase model skill. We observed the highest predictive skill in models including control volume derived estimates of residence time, but only when those estimates were included as an interaction with benthic composition. This work shows that not only is residence time critically important to better predict biogeochemical variability in coral reef environments, but that even coarse hydrodynamic models can provide useful residence time estimates at management relevant, whole-ecosystem scales

Measurements of the Total and Differential Higgs Boson Production Cross Sections Combining the H??????? and H???ZZ*???4??? Decay Channels at s\sqrt{s}=8??????TeV with the ATLAS Detector

Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3~fb$^{-1}$ of $pp$ collisions produced by the Large Hadron Collider at a center-of-mass energy of $\sqrt{s} = 8$ TeV and recorded by the ATLAS detector. Cross sections are obtained from measured $H \rightarrow \gamma \gamma$ and $H \rightarrow ZZ ^{*}\rightarrow 4\ell$ event yields, which are combined accounting for detector efficiencies, fiducial acceptances and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be $\sigma_{pp \to H} = 33.0 \pm 5.3 \, ({\rm stat}) \pm 1.6 \, ({\rm sys}) \mathrm{pb}$. The measurements are compared to state-of-the-art predictions.Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3  fb-1 of pp collisions produced by the Large Hadron Collider at a center-of-mass energy of s=8  TeV and recorded by the ATLAS detector. Cross sections are obtained from measured H→γγ and H→ZZ*→4ℓ event yields, which are combined accounting for detector efficiencies, fiducial acceptances, and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be σpp→H=33.0±5.3 (stat)±1.6 (syst)  pb. The measurements are compared to state-of-the-art predictions.Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3 fb$^{-1}$ of $pp$ collisions produced by the Large Hadron Collider at a center-of-mass energy of $\sqrt{s} = 8$ TeV and recorded by the ATLAS detector. Cross sections are obtained from measured $H \rightarrow \gamma \gamma$ and $H \rightarrow ZZ ^{*}\rightarrow 4\ell$ event yields, which are combined accounting for detector efficiencies, fiducial acceptances and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be $\sigma_{pp \to H} = 33.0 \pm 5.3 \, ({\rm stat}) \pm 1.6 \, ({\rm sys}) \mathrm{pb}$. The measurements are compared to state-of-the-art predictions