119 research outputs found
mara-freilich/mixed-layer-subduction: v1.0
No full text<p>Codes and data for </p>
<p>Freilich, M., & Mahadevan, A. (2021). Coherent pathways for subduction from the surface mixed layer at ocean fronts. <em>Journal of Geophysical Research: Oceans</em>, <em>126</em>(5), e2020JC017042.</p>
mara-freilich/network_analysis: Network analysis for Arboleda-Baena et al., submitted 2021
No full textCodes to analyze the properties of ecological association networks on environmental gradient
Reconstructing ecological networks with noisy dynamics
No full textEcosystems functioning is based on an intricate web of interactions among living entities. Most of these interactions are difficult to observe, especially when the diversity of interacting entities is large and they are of small size and abundance. To sidestep this limitation, it has become common to infer the network structure of ecosystems from time series of species abundance, but it is not clear how well can networks be reconstructed, especially in the presence of stochasticity that propagates through ecological networks. We evaluate the effects of intrinsic noise and network topology on the performance of different methods of inferring network structure from time-series data. Analysis of seven different four-species motifs using a stochastic model demonstrates that star-shaped motifs are differentially detected by these methods while rings are differentially constructed. The ability to reconstruct the network is unaffected by the magnitude of stochasticity in the population dynamics. Instead, interaction between the stochastic and deterministic parts of the system determines the path that the whole system takes to equilibrium and shapes the species covariance. We highlight the effects of long transients on the path to equilibrium and suggest a path forward for developing more ecologically sound statistical techniques
Species co-occurrence networks: Can they reveal trophic and non-trophic interactions in ecological communities?
No full textCo‐occurrence methods are increasingly utilized in ecology to infer networks of species interactions where detailed knowledge based on empirical studies is difficult to obtain. Their use is particularly common, but not restricted to, microbial networks constructed from metagenomic analyses. In this study, we test the efficacy of this procedure by comparing an inferred network constructed using spatially intensive co‐occurrence data from the rocky intertidal zone in central Chile to a well‐resolved, empirically based, species interaction network from the same region. We evaluated the overlap in the information provided by each network and the extent to which there is a bias for co‐occurrence data to better detect known trophic or non‐trophic, positive or negative interactions. We found a poor correspondence between the co‐occurrence network and the known species interactions with overall sensitivity (probability of true link detection) equal to 0.469, and specificity (true non‐interaction) equal to 0.527. The ability to detect interactions varied with interaction type. Positive non‐trophic interactions such as commensalism and facilitation were detected at the highest rates. These results demonstrate that co‐occurrence networks do not represent classical ecological networks in which interactions are defined by direct observations or experimental manipulations. Co‐occurrence networks provide information about the joint spatial effects of environmental conditions, recruitment, and, to some extent, biotic interactions, and among the latter, they tend to better detect niche‐expanding positive non‐trophic interactions. Detection of links (sensitivity or specificity) was not higher for well‐known intertidal keystone species than for the rest of consumers in the community. Thus, as observed in previous empirical and theoretical studies, patterns of interactions in co‐occurrence networks must be interpreted with caution, especially when extending interaction‐based ecological theory to interpret network variability and stability. Co‐occurrence networks may be particularly valuable for analysis of community dynamics that blends interactions and environment, rather than pairwise interactions alone
Coherent Pathways for Subduction From the Surface Mixed Layer at Ocean Fronts
No full textAuthor Posting. © American Geophysical Union, 2021. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 126(5), (2021): e2020JC017042, https://doi.org/10.1029/2020JC017042.In frontal zones, water masses that are tens of kilometers in extent with origins in the mixed layer can be identified in the pycnocline for days to months. Here, we explore the pathways and mechanisms of subduction, the process by which water from the surface mixed layer makes its way into the pycnocline, using a submesoscale-resolving numerical model of a mesoscale front. By identifying Lagrangian trajectories of water parcels that exit the mixed layer, we study the evolution of dynamical properties from a statistical standpoint. Velocity- and buoyancy-gradients increase as water parcels experience both mesoscale (geostrophic) and submesoscale (ageostrophic) frontogenesis and subduct beneath the mixed layer into the stratified pycnocline along isopycnals that outcrop in the mixed layer. Subduction is transient and occurs in coherent regions along the front, the spatial and temporal scales of which influence the scales of the subducted water masses in the pycnocline. An examination of specific subduction events reveals a range of submesoscale features that support subduction. Contrary to the forced submesoscale processes that sequester low potential vorticity (PV) anomalies in the interior, we find that PV can be elevated in subducting water masses. The rate of subduction is of similar magnitude to previous studies (∼100 m/year), but the Lagrangian evolution of properties on water parcels and pathways that are unraveled in this study emphasize the role of submesoscale dynamics coupled with mesoscale frontogenesis.This research was funded by the ONR CALYPSO DRI grant N00014-16-1-3130. MAF was partially funded by a Martin Fellowship from MIT
Decomposition of vertical velocity for nutrient transport in the upper ocean
No full textAuthor Posting. © American Meteorological Society, 2019. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 49(6), (2019): 1561-1575, doi:10.1175/JPO-D-19-0002.1.Within the pycnocline, where diapycnal mixing is suppressed, both the vertical movement (uplift) of isopycnal surfaces and upward motion along sloping isopycnals supply nutrients to the euphotic layer, but the relative importance of each of these mechanisms is unknown. We present a method for decomposing vertical velocity w into two components in a Lagrangian frame: vertical velocity along sloping isopycnal surfaces and the adiabatic vertical velocity of isopycnal surfaces . We show that , where is the isopycnal slope and is the geometric aspect ratio of the flow, and that accounts for 10%–25% of the total vertical velocity w for isopycnal slopes representative of the midlatitude pycnocline. We perform the decomposition of w in a process study model of a midlatitude eddying flow field generated with a range of isopycnal slopes. A spectral decomposition of the velocity components shows that while is the largest contributor to vertical velocity, is of comparable magnitude at horizontal scales less than about 10 km, that is, at submesoscales. Increasing the horizontal grid resolution of models is known to increase vertical velocity; this increase is disproportionately due to better resolution of , as is shown here by comparing 1- and 4-km resolution model runs. Along-isopycnal vertical transport can be an important contributor to the vertical flux of tracers, including oxygen, nutrients, and chlorophyll, although we find weak covariance between vertical velocity and nutrient anomaly in our model.MAF was supported by a National Defense Science and Engineering Graduate Fellowship and AM by NSF OCE-I434788. The authors thank Glenn Flierl and Ruth Curry for helpful conversations, and three anonymous reviewers for comments that improved the manuscript.2020-06-1
Vertical fluxes in the upper ocean
No full textSubmitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2021.Oceanic fronts at the mesoscale and submesoscale are associated with enhanced vertical motion, which strengthens their role in global biogeochemical cycling as hotspots of primary production and subduction of carbon from the surface to the interior. Using process study models, theory, and field observations of biogeochemical tracers, this thesis improves understanding of submesoscale vertical tracer fluxes and their influence on carbon cycling. Unlike buoyancy, vertical transport of biogeochemical tracers can occur both due to the movement of isopycnals and due to motion along sloping isopycnals. We decompose the vertical velocity below the mixed layer into two components in a Lagrangian frame: vertical velocity along sloping isopycnal surfaces and the adiabatic vertical velocity of isopycnal surfaces and demonstrate that vertical motion along isopycnal surfaces is particularly important at submesoscales (1-10 km). The vertical flux of nutrient, and consequently the new production
of phytoplankton depends not just on the vertical velocity but on the relative time scales of vertical transport and nutrient uptake. Vertical nutrient flux is maximum when the biological timescale of phytoplankton growth matches the vertical velocity frequency.
Export of organic matter from the surface and the interior requires water parcels to cross the mixed layer base. Using Lagrangian analysis, we study the dynamics of this process and demonstrate that geostrophic and ageostrophic frontogenesis drive subduction along density surfaces across the mixed layer base. Along-front variability is an important factor in subduction. Both the physical and biological modeling studies described above are used to interpret observations from three research cruises in the Western Mediterranean. We sample intrusions of high chlorophyll and particulate organic carbon below the euphotic zone that
are advected downward by 100 meters on timescales of days to weeks. We characterize the community composition in these subsurface intrusions at a lateral resolution of 1–10 km. We observe systematic changes in community composition due to the changing light environment and differential decay of the phytoplankton communities in low-light environments, along with mixing. We conclude that advective fluxes could make a contribution to carbon export in subtropical gyres that is equal to the sinking flux.The work in this dissertation was funded by a NDSEG fellowship, Martin Fellowship, Grassle fellowship, Montrym grant, WHOI Academic Programs Office, and Office of Naval Research CALYPSO DRI grant N00014-16-1-3130
Calypso hydrographic data
No full text<p>Data for "3D-intrusions transport active surface microbial assemblages to the dark ocean"</p>
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