Physical connectivity processes: examples relevant for fisheries management. Villy Kourafalou. University of Miami/RSMAS

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1 Physical connectivity processes: examples relevant for fisheries management Villy Kourafalou University of Miami/RSMAS

2 OUTLINE What is physical connectivity? Do fisheries managers need to consider physical oceanography processes? Currents connecting coastal ecosystems (local vs. regional connectivity) Land-sea, coastal to offshore and air-sea interactions Interdisciplinary, high resolution regional/coastal modeling

3 What is oceanographic connectivity? The circulation patterns controlling the flow and exchange of materials (nutrients, organisms, sediments, pollutants, ) Application: to support biogeochemical connectivity processes (genetic or evolutionary connectivity, demographic connectivity ) Related processes Land-sea interactions (eg. rivers, along-shelf and cross-shelf transport) Coastal to offshore interactions (eg. cross-marginal transport, shelf break processes, boundary currents) Air-sea interactions (eg. wind-driven circulation, upwelling)

4 Science to advance these activities is supported by the GODAE OceanView Coastal Ocean and Shelf Seas Task Team which: fosters international collaboration to advance science and applications in support of coastal ocean forecasting focuses on coastal and shelf dynamics, open ocean processes that control shelf break exchanges, as well as land-sea interactions through estuaries and inlets aims to help achieve a seamless transition framework from the global to the coastal scales These activities are further promoted by the GODAE OceanView Marine Ecosystem Analysis & Prediction Task Team

5 Some examples (focus on MPAs: Marine Protected Areas)

6 GULF OF MEXICO Many MPAs Distant connectivity (remote ecosystems) possible GoM bathymetry (m). Arrows: LC stages, with an anticyclonic ring (red). Magenta: MPAs (FGBNMS: Flower Garden Banks, MS: Madison Swanson, PR: Pulley Ridge, BSAG: Banco de San Antonio and Guanahacabibes, SK: Sian Ka an, BC: Banco Chinchorro)

7 Hydrodynamic modeling 1/50 0 Gulf of Mexico HYCOM 1/100 0 FKEYS - HYCOM FKEYS ~2 km resolution, data assimilation Nested in global HYCOM (1/12) Realistic river forcing, NAVGEM atm. ~900 m resolution, free running Nested in NRL GoM (1/25 ) NAVGEM atm. forcing Univ. of Miami/RSMAS/Coastal and Shelf Modeling Group Main products: near real-time 7-day forecasts of circulation, Sea Surface Height and SST high-resolution model archives

8 Hydrodynamic modeling Sea Surface Height, GoM-HYCOM 1/ Deepwater Horizon oil spill period 2010 Variable connectivity pathways, depending on Gulf Stream evolution

9 Bluefin tuna migration / passage through Deepwater Horizon site, 2010 Provided by Barbara Block, Stanford Univ. Location of cyclonic eddy intensification (Le Hénaff et al., 2012) favored for longer tuna stay

10 Hydrodynamic modeling Cyclonic frontal eddies along the Florida Current, impacting South Florida MPAs Sea Surface Height and Currents (FKEYS-HYCOM 1/100 0 ) Kourafalou and Kang, 2012

11 Ocean currents influencing larval transport Drifter trajectories Aug.-Oct (NOAA-AOML data) Sea Surface Height (FKEYS-HYCOM 1/100 0 ) and drifter tracks Drifters entrained in cyclonic eddies around the Dry Tortugas MPA spawning grounds

12 Larval transport modeling: connectivity among MPAs Virtual larvae are released and tracked within the fine resolution (FKEYS-HYCOM 1/100 0 ) hydrodynamic model until their settlement. Probabilistic simulations indicate mesophotic-shallow connections, during sporadic settlement pulses. 3D view of the settlement habitat of the Connectivity Modeling System, composed of three depth strata Vaz et al., 2016

13 Larval transport modeling: connectivity among MPAs Connectivity controlled by offshore eddy Connectivity controlled by shelf currents Probability Density Function (PDF) of larval trajectories calculated over 12 days before the end of the pelagic larval duration. Circulation (Lagrangian Coherent Structures) Vaz et al., 2016

14 Larval transport modeling Individual Based Model (IBM): particles that represent marine species larvae Derive connectivity estimates (sources/sinks, amplitude etc.) SPAWNING Paris et al., DAYS CONNECTIVITY MATRIX (between spawning and settlement sites) Cowen et al., 2006

15 Nutrient transport and ecosystem modeling A) HYCOM-COSINE model and B) MODIS- AQUA satellite chl-a concentration for October 2009 (monthly mean). GoM-HYCOM 1/ COSINE Coupling high-resolution regional circulation model with the Carbon, Silicate, Nitrogen Ecosystem model Ecopath-with-Ecosim (EwE) ecosystem model model (using outputs of the coupled biophysical model): suitable for ecosystem management scenarios, to estimate biomass spatiotemporal evolution

16 Application on specific processes: Land-sea and coastal-offshore interactions Mississippi River waters carry nutrients, sediments and pollutants They have been observed and modeled to affect both neighboring and remote coastal ecosystems (hundreds of km s away) This connectivity is controlled by the mesoscale circulation (oceanic currents and eddies) High resolution basin-wide and nested models help elucidate the related processes and advance prediction tools that can be used for ecosystem management

17 Influence of Mississippi waters on coastal water quality Physical model: ROMS v3.0 Biological model: BIO_FENNEL with OXYGEN and CARBON options Resolution: 1-20 km in horizontal, 30 vertical layers Forcing: 3-hourly NCEP NARR winds; climatological surface heat and freshwater fluxes River inputs: daily measurements of FW input by U.S. Army Corps of Engineers; monthly estimates of nutrient and particulate matter loads from USGS Oxygen Model realistically simulates bottom water hypoxia (low oxygen) and eutrophication-driven acidification (low ph) Combined stressors affecting the ecosystem ph Laurent, Fennel et al., GRL (subm.) Provided by. K. Fennel

18 ph Oxygen Climate projections Present Future (2100) bottom waters in mid August June-September Laurent, Fennel et al., in prep. Future projections show expansion of hypoxic area (primarily due to increased density stratification) and dramatic drop in ph (due to the combination of atmospheric CO2 levels and nutrient inputs) Provided by. K. Fennel

19 1 st example: 2004 Mississippi River water export impacting remote MPAs Sea Surface Height and Currents Univ. of Miami/RSMAS NGoM-HYCOM 1/50 0 model nested in NRL GoM-HYCOM 1/25 0 model Ocean Color obs. In situ obs. Schiller and Kourafalou, 2014

20 2 nd example: 2014 Mississippi River water export impacting remote MPAs SSS, Aug SSS, Aug PR DT R/V Walton Smith on-board Sea Surface Salinity, August 13-28, 2014 Vertical salinity sections close to PR and DT, Aug. 22, 23 and 25, Large and sudden salinity drop on Aug. 18, which affected 3 MPAs m thick layer of very low salinity: large quantities of fresh waters 2014: below average Miss. River (MR) discharge MR discharge in 2014 (red), 2011 (dashed); clim. in black Le Hénaff and Kourafalou, 2016

21 2014 Mississippi River (MR) water export : hydrodynamic modeling August: Main branch extends along the edge of the WFS LC reattaches, entrains MR waters Late August: MR waters reach the FL Straits MR waters keep extending eastward in Delta area (winds)

22 Management needs: Flower Gardens Bank MPA mortality event (summer 2016) 06/ / / /22-28 Late July 2016: patches of high mortality observed on one site Concurrent with offshore transport of coastal, high Chl-a and/or turbid waters during June-July Weekly anomalies in Chl-a in summer of Red: positive anomalies, blue: negative anomalies. The 2 black dots are FGBNMS reefs. Complex of local river runoff (rivers other than the Mississippi), wind-driven upwelling and mesoscale circulation processes High resolution physical/biogeochemical/ecosystem modeling needed to address scientific and management questions

23 Concluding remarks Physical processes influence the transport of nutrients, larvae and pollutants Physical connectivity plays a significant role in the management needs of Marine Protected Areas Interdisciplinary high resolution modeling systems, in tandem with targeted observations, are a significant tool toward understanding the connectivity processes GODAE OceanView supports the required research and development to advance such systems, through the Coastal Ocean and Shelf Seas Task Team and the Marine Ecosystem Analysis and Prediction Task Team