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  • 1
    Publication Date: 2022-05-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Long, M. H., Rheuban, J. E., McCorkle, D. C., Burdige, D. J., & Zimmerman, R. C. Closing the oxygen mass balance in shallow coastal ecosystems. Limnology and Oceanography, 64(6), (2019): 2694-2708, doi: 10.1002/lno.11248.
    Description: The oxygen concentration in marine ecosystems is influenced by production and consumption in the water column and fluxes across both the atmosphere–water and benthic–water boundaries. Each of these fluxes has the potential to be significant in shallow ecosystems due to high fluxes and low water volumes. This study evaluated the contributions of these three fluxes to the oxygen budget in two contrasting ecosystems, a Zostera marina (eelgrass) meadow in Virginia, U.S.A., and a coral reef in Bermuda. Benthic oxygen fluxes were evaluated by eddy covariance. Water column oxygen production and consumption were measured using an automated water incubation system. Atmosphere–water oxygen fluxes were estimated by parameterizations based on wind speed or turbulent kinetic energy dissipation rates. We observed significant contributions of both benthic fluxes and water column processes to the oxygen mass balance, despite the often‐assumed dominance of the benthic communities. Water column rates accounted for 45% and 58% of the total oxygen rate, and benthic fluxes accounted for 23% and 39% of the total oxygen rate in the shallow (~ 1.5 m) eelgrass meadow and deeper (~ 7.5 m) reef site, respectively. Atmosphere–water fluxes were a minor component at the deeper reef site (3%) but a major component at the shallow eelgrass meadow (32%), driven by diel changes in the sign and strength of atmosphere–water gradient. When summed, the measured benthic, atmosphere–water, and water column rates predicted, with 85–90% confidence, the observed time rate of change of oxygen in the water column and provided an accurate, high temporal resolution closure of the oxygen mass balance.
    Description: This work was substantially improved by comments from two anonymous reviewers. We thank Victoria Hill, David Ruble, Jeremy Bleakney, and Brian Collister for assistance in the field and the staff of the Bermuda Institute of Ocean Sciences and the Anheuser‐Busch Coastal Research Center for logistical support. This work was supported by NSF OCE grants 1657727 (to M.H.L. and D.C.M.), 1635403 (to R.C.Z. and D.J.B.), and 1633951 (to M.H.L.).
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-05-27
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jenouvrier, S., Long, M. C., Coste, C. F. D., Holland, M., Gamelon, M., Yoccoz, N., & Saether, B.-E. Detecting climate signals in populations across life histories. Global Change Biology, 28, (2022): 2236– 2258, https://doi.org/10.1111/gcb.16041.
    Description: Climate impacts are not always easily discerned in wild populations as detecting climate change signals in populations is challenged by stochastic noise associated with natural climate variability, variability in biotic and abiotic processes, and observation error in demographic rates. Detection of the impact of climate change on populations requires making a formal distinction between signals in the population associated with long-term climate trends from those generated by stochastic noise. The time of emergence (ToE) identifies when the signal of anthropogenic climate change can be quantitatively distinguished from natural climate variability. This concept has been applied extensively in the climate sciences, but has not been explored in the context of population dynamics. Here, we outline an approach to detecting climate-driven signals in populations based on an assessment of when climate change drives population dynamics beyond the envelope characteristic of stochastic variations in an unperturbed state. Specifically, we present a theoretical assessment of the time of emergence of climate-driven signals in population dynamics (ToEpop). We identify the dependence of (ToEpop)on the magnitude of both trends and variability in climate and also explore the effect of intrinsic demographic controls on (ToEpop). We demonstrate that different life histories (fast species vs. slow species), demographic processes (survival, reproduction), and the relationships between climate and demographic rates yield population dynamics that filter climate trends and variability differently. We illustrate empirically how to detect the point in time when anthropogenic signals in populations emerge from stochastic noise for a species threatened by climate change: the emperor penguin. Finally, we propose six testable hypotheses and a road map for future research.
    Description: We acknowledge the support of NASA 80NSSC20K1289 to SJ, ML, and MH; NSF OPP 1744794 to SJ and NSF OPP 2037561 to SJ and MH.
    Keywords: climate change ; emperor penguin ; life histories ; population trend ; population variability ; signal to noise ; time of emergence
    Repository Name: Woods Hole Open Access Server
    Type: Article
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