Red Snapper distribution on natural habitats and artificial structures in the northern Gulf of Mexico

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Red Snapper distribution on natural habitats and artificial structures in the northern Gulf of Mexico SEFSC Mandy Karnauskas and John Walter, NMFS SEFSC Miami Matthew Campbell and Adam Pollack, NMFS SEFSC Pascagoula J. Marcus Drymon and Sean Powers, University of South Alabama GSMFC 67th Annual Spring Meeting March 16, 2017

Motivation: Where are red snapper? Spatial planning Survey design Basis for other studies SEAMAP survey stations U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 2

Motivation: Where are red snapper? Gallaway et al 2009. Rev in Fish Sci U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 3

There are a lot of artificial structures in the Gulf of Mexico U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 4

and they re full of red snapper http://www.brownsvilleherald.com/ http://www.reefmaker.com/photos/underwater-pictures How do we create a comprehensive map? U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 5

Basic study schematic Sampling and study domain Northern Gulf of Mexico, depths 7-140 m (min/max depth for RS) Data Intensive longline, handline sampling in 2011 (CSSP), targeted sampling of platforms and reefs in other surveys, usseabed habitat data Statistical modeling merge different data sources and account for survey artifacts (e.g. sampling different areas at different times of the day) Predictive mapping Predict distribution by age, area, depth and habitat type on 10-km 2 grid U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 6

Sampling programs 1. 2011 Congressional supplemental sampling Longline stratified random Handline stratified random Handline targeted natural reefs 2. Handline on platforms (SEAMAP) 3. Handline on artificial reefs (Powers, Drymon et al.) U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 7

Domains of inference Longline and randomized handline: everywhere but natural reefs, platforms and known artificial structures Targeted handline: natural reefs, platforms, or artificial reefs - area of influence assumed to be 100 m radius Reynolds, 2007 U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 8

Methods: Choose your own adventure Quick and dirty (skip to slide 11) Statistical labyrinth (go to next slide) Audience participation! U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 9

Methods flowchart U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 10

Methods simplified Area of habitat Catch rate on habitat X = Relative abundance on habitat Sum across all habitats, plot for each grid cell Relative abundance U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 11

Methods replicated with raw data Area of habitat Catch rate on habitat X = Relative abundance on habitat 80.00% raw data % area * catch rate raw data statistical habitat type % area of GoM catch rate results (relative derived abundance) from raw % of total model mud 60.00% 78.71% 1.00 data calculation 0.79 11.37% 14.12% natural reefs 21.14% 24.87 results output from full 5.26 75.97% 71.58% artificial 40.00% reefs 0.13% 598.37 statistical process 0.75 10.82% 12.47% oil platforms 0.02% 519.53 0.13 1.84% 1.83% 20.00% SUM 6.92 100% 100% 0.00% mud & sand rock & gravel artificial reefs oil platforms U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 12

Statistical model predicts across entire GoM, by age 25 20 platforms : natural habitats artificial reefs : natural habitats 15 10 5 0 ages 1-2 age 3 age 4 age 5+ ages 1-2 age 3 age 4 age 5+ platforms : natural habitats 22.4 4.1 0.4 0.2 artificial reefs : natural habitats 19.9 9.0 16.9 18.2 U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 13

Contribution of artificial structures: relative number Number (%) Biomass (%) Fecundity (%) All natural habitats 86.7 92.2 93.6 All artificial structures 13.3 7.8 6.4 Platforms 2.3 0.4 0.1 Artificial reefs 11 7.4 6.2 U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 14

Contribution of artificial structures: relative biomass Number (%) Biomass (%) Fecundity (%) All natural habitats 86.7 92.2 93.6 All artificial structures 13.3 7.8 6.4 Platforms 2.3 0.4 0.1 Artificial reefs 11 7.4 6.2 U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 15

Contribution of artificial structures: relative fecundity Number (%) Biomass (%) Fecundity (%) All natural habitats 86.7 92.2 93.6 All artificial structures 13.3 7.8 6.4 Platforms 2.3 0.4 0.1 Artificial reefs 11 7.4 6.2 U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 16

Locally, artificial structures are extremely important U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 17

Caveats/assumptions Handline gear assumed to have same catchability among habitats Relies upon databases of known artificial reefs and platforms (underestimate of structures by half would be ~ two-fold contribution) Area of influence assumed to be constant across surrounding area and same for all artificial structures Snapshot of 2011 distribution platform survey in different year (2007) Artificial reef sampling limited to relatively small area Only relative abundance map Statistical model does not capture small-scale variability Maps would not work for identifying fishing locations U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 18

Conclusions Artificial structures can harbor the majority of Red snapper present in certain hotspots that are locally important for fishing opportunities But calculated across the entire Gulf, artificial structures comprise a small fraction of the total seafloor (~0.15%) and harbor a small fraction of the population (~13%). U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 19

Conclusions Because artificial structures harbor smaller, younger Red snapper than are found on natural reefs, their contribution to the overall stock is low in terms of biomass (8% of total) and spawning potential (6% of total). U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 20

Does this study answer whether artificial habitats increase the production of Red snapper in the Gulf of Mexico? No, though it does indicate that the relative impact of artificial reefs on red snapper production would be small due to the amount of this habitat relative to natural habitat U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 21

How does this study change the stock assessment? It doesn t. However, the study does help to scale the impact of potential differences in populations on artificial structures versus natural reefs. Current assessment models essentially average the rates of growth, mortality, and spawning across natural habitats and artificial reefs. Given the relatively small relative abundance on artificial structures, any differences would probably have a minimal effect on the stock assessment. If information on habitat-specific growth, maturity, fecundity, etc. becomes available, the results from this study would allow inclusion of this on the stock assessment. U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 22

What are the implications of this study for management? Artificial structures have important local fishery impacts that should be considered when interpreting fishery-independent data The detailed spatial map of red snapper abundance could be used to inform spatial management, survey design, or to further explore the potential implications of shifting biomass from natural reef to artificial reef areas Implications on stock status and catch advice are likely to be minor since catches from both natural and artificial reefs are already included in the assessment, and the proportion of red snapper that occupy artificial structures is small relative to the total population U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 23

Future directions What are the implications of shifting 8% of the biomass to locations it wouldn t normally be? U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 24

Future directions What effect has increasing artificial habitats had on stocks and the Gulf of Mexico ecosystem? 2017 Update coming next week! Gulf of Mexico Ecosystem Status Report - Suite of physical, biological, economic, and social indicators for understanding status and trends in the ecosystem U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 25

Acknowledgements Numerous data providers, analysts and contributors to the SEDAR 31 Red Snapper stock assessment and the 2014 update assessment. Robert Allman and the NMFS Panama City aging team provided much of the age data. Funding for the major survey data used in this work comes from a Congressional Supplemental Sampling Program. Funding for the artificial reef sampling was provided by NMFS SEAMAP via a subcontract from the Alabama Department of Conservation and Natural Resources, Marine Resources Division. Nate Bacheler, Xinsheng Zhang, Gary Fitzhugh, Clay Porch, Alex Chester and several anonymous reviewers gave many helpful comments. George Bosarge provided assistance with the artificial reef structure estimation. U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 26

U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 27

Model performance GLM explains about onefourth of variability in data - sampling variability - gear selectivity - large-scale spatial variability d.f. Deviance Residual d.f. Residual deviance Dev. explained (%) Logistic model (response: probability of presence) age class 5 230.3 18612 7993.4 2.80 gear 2 766.0 18610 7227.4 9.58 depth 6 229.1 18604 6998.3 3.17 longitude 7 310.4 18597 6687.9 4.44 month 6 59.3 18591 6628.6 0.89 hour 3 14.3 18588 6614.3 0.22 age class:gear 10 193.7 18578 6420.6 2.93 age class:depth 30 117.3 18548 6303.3 1.83 depth:longitude 42 235.5 18506 6067.8 3.74 Poisson model (response: abundance-when-present) age class 5 32.48 1077 1437.4 2.21 gear 2 0.22 1075 1437.2 0.02 depth 6 28.42 1069 1408.7 1.98 longitude 7 35.61 1062 1373.1 2.53 month 6 48.10 1056 1325 3.50 hour 3 1.91 1053 1323.1 0.14 age class:gear 10 59.54 1043 1263.6 4.50 age class:depth 30 91.54 1013 1172 7.24 depth:longitude 42 63.23 971 1108.8 5.40 U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 28