Methods and Lessons Learned from a Fisheries- Independent Reef Fish Sampling Program in the Florida Keys, USA Alejandro Acosta Florida Fish and Wildlife Conservation Commission Fish and Wildlife Research Institute South Florida Regional Laboratory 2796 Overseas Hwy; Suite 119; Marathon, FL 33050-2227 Saltwater Recreational Fishing License
We are here, somewhere
Fisheries Independent Surveys Fisheries-independent data are collected through scientific surveys and are a critical component of fishery stock assessments. These data, combined with fisheries-dependent data (catch & effort), provide a more accurate picture of stock status. Since the data are not influenced by specific management or socioeconomic measures they present an unbiased accounting of the stock.
FWRI Fisheries Independent Program Philosophy Holistic approach Multi-species Multi-habitat Multi-gear Targeted species Broad size range sampled Juveniles Subadults Adults Standardized procedures Fish released alive, except for: Representative samples Unidentified samples Research samples Age and growth Reproduction
FWC Fisheries Independent Program Background Began sampling in 1989 in Tampa Bay and Charlotte Harbor seasonal (spring and fall) stratified-random sampling monthly sampling at fixed stations sample design emphasized juvenile life stages Progressively expanded through the state currently sample seven estuaries and seagrass beds and coral reefs in the Florida Keys (1999-Present) Significantly modified sampling design in 1996 initiated monthly stratified-random sampling omitted fixed-station sampling incorporated gears for sampling subadult/adult fishes
FWC Fisheries Independent Sampling programs Choctawhatchee Bay & Santa Rosa Sound 1992-1997 Apalachicola 1997 Cedar Key 1996 Tampa Bay 1989 Charlotte Harbor 1989 Northeast Florida 2001 Northern Indian River Lagoon 1990 Southern Indian River Lagoon 1997 Florida Keys 1998
Fisheries Independent program objectives The primary goal of the survey is to develop estimates of juvenile abundance for commercial important reef fish species in the Florida Keys. Develop indices of recruitment for species as they enter the fishery Correlate juvenile and adult relative abundances Estimating abundances of juveniles (usually young of the year) helps evaluate the health of a stock, and allows possible forecasting of future commercial and recreational abundance. Predict future adult relative abundances Detect changes in size or age structure of fish populations
Fisheries Independent program objectives Improve existing knowledge and understanding of individual species: Life history parameters age and growth age/size at sexual maturity fecundity reproductive patterns Habitat utilization at different life stages (EFH) Assess ecological communities Provide data and technical assistance for the development of ecosystem models (e.g., ECOPATH)
The aim of this presentation will be two-fold: First: to present some of the results from our fisheries independent trawl and visual census data from 1999-2003 in the Florida Keys National Marine Sanctuary Second: to discuss the use of these results for individual stock assessments,management strategies and the present general considerations needed to establish a fisheries-independent program
METHODS
STUDY AREA Map of Fisheries-Independent Monitoring Program sampling areas, divided into 4 zones (A-D), in the Florida Keys National Marine Sanctuary (FKNMS). Seagrass areas sampled during trawl surveys are shown in green; reef areas sampled during visual surveys are shown in red.
Program sampling design Stratified-random sampling The Florida Keys are subdivided into zones Each zone is further subdivided into grids (1nm 2 ) Available habitat in each grid is identified Set number of sampling grids randomly selected from each zone each month Sampling site within each grid is randomly selected
Data Collected Data collected at each sampling site include: Location information Habitat characteristics (bottom type, shore type) Water chemistry (salinity, temperature, DO, etc.) Weather (tide, wind, cloud cover, time, etc.) Species data Number Representative sizes and identification of species Random culls for life history studies Specimens with obvious external abnormalities culled Specimens culled for analysis of mercury concentration
Sampling Gear Trawls were conducted over seagrass beds in three zones (B, C, & D) of the FKNMS, including both Atlantic and Gulf sides of the Keys, from Tavernier to Key West. Trawls samples were collected by 3-minute bottom tows using a 20 otter trawl with a 1/4 mesh cod-end liner. Visual censuses were conducted by SCUBA divers who enumerated and assigned a length estimation to certain fish within standardized areas using two sampling techniques: transects (30m x 10m) and point counts (5m radius). Visual surveys were performed over reef areas in four zones (A-D) from Key Largo to Key West.
Some results from the trawl survey
Summary of catch and effort data for Florida Keys stratified-random sampling, 1999-2003 6.1-m Trawl Visual Census Totals Zone Animals Hauls Animals Counts Animals Samples A 60,024 1,693 60,024 1,693 B 3,805 292 49,018 1,352 52,823 1,644 C 22,489 518 39,062 974 61,551 1,492 D 13,527 285 44,044 1,514 57,571 1,799 Totals 39,821 1,095 192,148 5,533 231,969 6,628
9.36 10.67 3.89 2.27 1.91 3.45 Mean density (# fish/100m 2 ) by stratum (Gulf of Mexico and Atlantic Ocean), zone (B, C, and D), and subzone (B G & O, C G & O, and D G & O ) for the seven most abundant families and all others collected in trawl samples
Mean density (# fish/100m 2 ) Comparison of mean fish density by zone and strata for the three most abundant species caught in trawls. 6.00 Haemulon plumieri White grunt 15.00 Eucinostomus spp. Mojarras 2.50 Monacanthus ciliatus Fringed filefish Monacanthus ciliatus 4.00 2.00 0.00-2.00 ] ] G ] ] ] Strata O ] 10.00 5.00 0.00-5.00-10.00 ] ] Zones B Eucinostomus C spp. D G ] Strata ] O ] 2.00 1.50 1.00 0.50 0.00 ] ] G ] ] Strata ] ] O The lowest densities of Haemulon plumieri (White grunt) were observed on the ocean side in zone B. While Eucinostomus spp. were similarly distributed among zones and strata, they were absent from zone B on the ocean side. The highest densities of Monacanathus ciliatus (Fringed filefish) were observed on the Gulf side.
Number of of fish Number of of fish Number of fish Number of of fish 1600 1400 1200 1000 800 600 400 200 1000 a. Haemulon plumieri G = 81.5mm 900 b. O = 71.5mm 800 700 600 500 400 300 200 100 Monacanthus ciliatus G = 65.9mm O = 66.2mm 0 900 800 700 600 500 400 300 200 0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 100 c. 90 d. Lagodon rhomboides G = 76.2mm O = 107.3mm 80 70 60 50 40 30 20 Lutjanus synagris G = 83.4mm O = 96.5mm 100 10 0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 Standard length (mm) 0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 220 240
Trawl Summary Results Total fish densities were lower on the ocean side than on the Gulf side in zones C and D. Overall fish densities were considerably lower in zone B than in zone C and D (p < 0.005). Variability among by-catch, bottom type, and bottom vegetation between strata was also evident, but not statistically significant. Larger fish densities were observed in seagrass beds on the Gulf and ocean sides. Fish densities were significantly lower in the spring on the ocean side. The results of the first two years sampling and three years of seasonal sampling strongly indicated that catch rates for juveniles of the species of commercial value were too low to allow the development of viable juvenile recruitment indices.
Some visual surveys Results In general for all fish collected, the two sampling methods (transects and point counts) produced similar results when density and mean total length were compared with zone, habitat type, biotic cover, and depth.
Species Recorded during Visual Surveys Lutjanus analis - Mutton Snapper Lutjanus apodus - Schoolmaster Lutjanus synagris - Lane Snapper Lutjanus griseus - Gray Snapper Lutjanus jocu - Dog Snapper Lutjanus cyanopterus - Cubera Snapper Lutjanus mahogoni - Mahogany Snapper Ocyurus chrysurus - Yellowtail Snapper Epinephelus morio - Red Grouper Epinephelus itajara - Jewfish Epinephelus striatus - Nassau Grouper Epinephelus fulvus - Coney Epinephelus cruentatus - Graysby Epinephelus adscensionis - Rock Hind Epinephelus guttatus - Red Hind Mycteroperca microlepis - Gag Grouper Mycteroperca phenax - Scamp Mycteroperca bonaci - Black Grouper Mycteroperca tigris - Tiger Grouper Haemulon parrai - Sailors Choice Haemulon aurolineatum - Tomtate Haemulon melanurum - Cottonwick Haemulon sciurus - Bluestriped Grunt Haemulon macrostomum - Spanish Grunt Haemulon plumieri - White Grunt Haemulon carbonarium - Caesar Grunt Haemulon flavolineatum - French Grunt Haemulon chrysargyreum - Smallmouth Grunt Haemulon album - Margate Anistotremus virginicus - Porkfish Anistotremus surinamensis - Black Margate Holacanthus bermudensis - Blue Angelfish Holacanthus tricolor - Rock Beauty Holacanthus ciliaris - Queen Angelfish Pomacanthus arcuatus - Gray Angelfish Pomacanthus paru - French Angelfish Cantherhines macrocerus - Whitespotted Filefish Balistes vetula - Queen Triggerfish Balistes capriscus - Gray Triggerfish Priacanthus arenatus - Bigeye Priacanthus cruentatus - Glasseye Snapper Lachnolaimus maximus - Hogfish Bodianus rufus - Spanish Hogfish Bodianus pulchellus - Spotfin Hogfish Chaetodon striatus - Banded Butterflyfish Chaetodon sedentarius - Reef Butterflyfish Chaetodon ocellatus - Spotfin Butterflyfish Chaetodon capistratus Foureye Butterflyfish
2.5 Snappers Geometric Mean Density per 100 m 2 2 1.5 1 0.5 0 Lutjanus analis Lutjanus apodus Lutjanus griseus Lutjanus synagris Ocyurus chrysurus
0.5 Geometric Mean Density per 100 m 2 0.4 Butterflyfish 0.3 0.2 0.1 0 Chaetodon capistratus Chaetodon ocellatus Chaetodon sedentarius Chaetodon striatus
Geometric Mean Density per 100 m 2 0.2 Groupers 0.15 0.1 0.05 0 Epinephelus cruentatus Epinephelus morio Mycteroperca bonaci
Some Applications of the Fishery-Independent Data Indices of relative abundance for Yellowtail snapper Habitat Associations Species distributions Life history Length frequency distributions Ecosystem modeling
While variability in density and mean total length among zones, habitat, biotic cover and depth was evident, these differences were species-specific. Ocyurus chrysurus Yellowtail snapper
Geometric mean density of O. chrysurus Geometric Mean density (fish/100m 2 8 7 6 5 4 3 2 1999 2000 2001 2002 2003 Year
number of fish Length frequency distribution Ocyurus chrysurus visual census 1999-2003 1200 1000 800 1999 2000 2001 2002 2003 600 400 200 0 > 5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 size class (cm)
Density (log (x +1 )) Densities of yellowtail snapper were not significantly different among habitats or zones surveyed. 1.2 1.1 1.0.8.6.4 1.0.9.8.7.6.5.4.3.2.2 A B C D.1 0.0 Continuous Edge Intermittent Zone Habitat Type
Systematic trends were evident for each zone, habitat and biotic cover for Haemulon plumieri (white grunt), however, no significant differences in density were observed. The results indicated a larger mean size observed in deep sites than in shallow sites. Haemulon plumieri White grunt
Geometric mean density of H. plumieri Geometric mean density (fish/100m 2 14 13 12 11 10 9 8 7 6 5 4 3 2 1999 2000 2001 2002 2003 Year
number of fish Length frequency distribution Haemulon plumieri visual census 1999-2003 4500 4000 3500 3000 2500 2000 1500 1999 2000 2001 2002 2003 1000 500 0 > 5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 size class (cm)
Density (log (x+1)) Comparison of density (fish/100m 2 ) of white grunt by biotic cover and depth (m). 3 8.0 6.0 2 4.0 1 0 2.0 0.0-2.0-1 -4.0-6.0-2 AM AU CE CM CS GM SP TH Major Biotic Cover Depth (m) CODES AM = algae: mixed, AU = algae: unknown, CE = coral: encrusting CM = coral: massive, CS = coral: soft, GM = grasses: mixed SP = sponges, TH = Thalassia
Estimation of Growth and Mortality Parameters for Yellowtail snapper Our approach of using length-frequency data to estimate growth parameters and mortality for O. chrysurus provides some limited results. Length-converted catch curve estimates of total mortality are highly dependent on the estimated growth parameters. Consequently, estimates of Z generally parallel estimates of K and L 4. Due to the ontogenetic shift occurring in this species, it is difficult to obtain an unbiased population length-distribution unless sampling is conducted in both shallow and deep water habitats.
Lessons Learned
Trawl Survey Although the sampling effort described here has provided us with valuable, and previously non-existent, baseline data on the utilization of the grassbeds of the FKNMS by small and juvenile fishes, the trawling methodology has proven largely ineffective for identifying major nursery habitats for reef fish species. With the exception of Haemulon plumieri, catches of all the commercially and recreationally important species have been very low in number, have occurred in only a small percentage of samples, and most importantly of all, have included extremely few early juveniles.
Applications of the Data For Stock assessment: Fishery-independent surveys offer the best choice for achieving a reliable index of abundance if designed well with respect to location, timing, sampling gear, and other statistical survey design considerations For Marine Reserves: The kind of approach taken in this study, combining several independent sampling methods to obtain accurate estimates of fish density by habitat, seems to be appropriate for selection and management of reserves. If these protected areas are to be effective, they must include the diversity of habitats necessary to accommodate a wide range of fish species.
OVERALL CONSIDERATIONS
The information derived from monitoring is, usually, of a general nature and intended to provide an empirical context within which to make decisions about the management of a specific issue or species. The choice of sampling methods for general monitoring should be related to methods widely used in other studies, and the documentation of their sampling characteristics is an important component in the development of fisheries independent monitoring.
The development and implementation of a fisheries independent program over such a large scale as the Florida Keys is expensive and logistically constrained. So it is critical that the sampling methods provide: Reliable data Be able to identify changes or patterns of abundance Logistically practical, so it can be implemented in many situations and most importantly Inexpensive, so the sampling can be conducted even with limited budgets
Multi-Species, Multi-Gear Approach We chose to cover as many species as logistically possible because: A fisheries independent program should take into account the status of several species The range of size frequency samples was the same for most of the species targeted Most of the reef species of commercial interest shared the same habitats sampled A multi-species approach maximized the cost of the program
Multi-Species, Multi-Gear Approach Helps ensure that your long-term monitoring program is actually long-term because it prevents the program from being tied to only one species or issue It also gives flexibility to the program, allowing changes to meet the requirements of managers Similarly, assisting multiple user groups, both inside and outside of your organization, makes the program much less expendable and more marketable when new funding opportunities arise
Quality Control and training Do as much gear testing as possible before starting program. (In our case usually a year testing and ground-truthing the habitats) Carefully consider any changes to gear types or methodology, even apparently minor changes can lead to doubts about the reality of observed trends in the data Incorporation of new gear types is sometimes unavoidable (e.g., change in programmatic needs) but must do extensive comparison of new methodology vs. old for calibration
It is extremely important to emphasize observer training to maximize the similarity in counts and size estimation, especially when the program uses many different observers. We required from our observers periodic recalibration in order to ensure that the observer biases remain consistent Inter-annual and spatial comparisons rest on the assumption that all the observers were counting and measuring with equal bias.
Major Struggles Quality control of the data collected Employee retention Maintaining funding Burn-out due to year-round monitoring Teaching field personnel to think like a fish and without bias
ACKNOWLEDGMENTS I would like to thank the current FWRI/SFRL fish group: Claudine Bartels, Karole Ferguson, Paul Barbera Matt Hoxie, Jeff Simonds and Marie Tellier for their continuing efforts in the field and in the laboratory. To Jim Colvocoresses for his guidance and advice during all the previous years and to the many hard working individuals that collected the data for this program from 1999 through 2003. Funding was provided by State of Florida Saltwater Fishing License monies and by the Department of the Interior, U.S. Fish and Wildlife Service.