NOAA Coral Reef Conservation Grant- Final Report Project title...Indo-Pacific lionfish (Pterois...

NOAA Coral Reef Conservation Grant- Final Report

Project title: Setting and evaluating ecological targets for invasive lionfish control Principal investigators: Dr. Stephanie Green Oregon State University Corvallis, Oregon, USA Mr. Lad Akins Reef Environmental Education Foundation Key Largo, Florida, USA NOAA Coral Reef Conservation Program priority areas: This project addresses the following Coral Reef Conservation Program and Jurisdictional Coral Reef Management Priorities:

• 2012 CRCP Domestic Coral Reef Conservation Grant priority 4.2: Reducing invasive species impacts to coral reef ecosystems, including projects that address the proliferation of lionfish (Pterois volitans) in Florida and the U.S. Caribbean

• US Virgin Islands Jurisdictional Coral Reef Management Priority Goal 8 Control/manage invasive species

• Florida Jurisdictional Coral Reef Management Priority A3 Improve coordinated emergency response to disturbance events and restoration of reef injuries (e.g. invasive species

Table of Contents:

i. Executive summary ii. Project rationale iii. Project objectives iv. Methods v. Results vi. Discussion vii. Next steps Appendix I. Project partners Appendix II. Model structure and parameters

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i. Executive summary Indo-Pacific lionfish (Pterois volitans and P. miles) pose a serious threat to the integrity of invaded Western Atlantic coral reef ecosystems. Over the past five years, lionfish have rapidly colonized US coral reef, mangrove and seagrass habitats off South Florida, in the Gulf of Mexico and around the US Caribbean territories of Puerto Rico and the Virgin Islands, where they consume an array of native species. Although the vast geographic extent of the invasion makes complete eradication of lionfish from the Atlantic unlikely, local control—in the form of manual removal by divers—is emerging as the primary strategy for preventing ecological impacts within priority marine areas, such as MPAs. Managers across the region are now designing and implementing local lionfish control programs. To make efficient use of limited management resources, information on the extent to which lionfish populations must be suppressed to prevent impacts and the management resources needed to effect control are urgently needed.

To contribute to coral reef conservation in US jurisdictions and beyond faced with the lionfish invasion, we 1) developed and validated a predictive model—the Lionfish Removal Target Model (LRT Model)—for use as a management tool to set location-specific lionfish control targets which prevent impacts to invaded fish communities and 2) estimated the management effort required to achieve and maintain lionfish removal targets over time. To achieve these objectives, we conducted a lionfish removal experiment on 42 invaded coral reefs within two protected zones off South Florida (Florida Keys National Marine Sanctuary and Biscayne National Park) to determine 1) the performance of LRT Model targets under a variety of habitat and environmental conditions, 2) the quantity and quality of monitoring data needed to produce location-specific LRT Model targets, and 3) the removal effort (i.e., catch per unit effort, personnel and logistics) and frequency required to achieve and maintain local lionfish populations below target levels over time, in partnership with Florida Fish and Wildlife Conservation Commission, US National Park Service, NOAA National Marine Sanctuaries Program, Oregon State University, NOVA Southeastern University, NOAA CCFHR, and local dive operators and volunteer organizations.

Applying local fish community monitoring data within the LRT modelling framework, we generate ecological thresholds at which invasive lionfish begin to deplete their prey resources for 42 coral reefs sites in FKNMS and Biscayne National Park, and experimentally show that sustained local removal by divers and snorkeler is successful in suppressing lionfish below levels predicted to elicit negative ecological impacts. Lionfish density exceeded target thresholds at 64% of South Florida sites at the outset of the project, with densities varying between 0 -1000 lionfish ha-1. The extent of lionfish density reduction required varied between 0 and 96%, depending on lionfish density and native fish biomass. Sites with high lionfish recolonization rates and depauperate native fish communities were at highest risk of impact. While bi-monthly removal events were sufficient to suppress lionfish densities below target levels at all sites, crucially the ease of capturing lionfish remaining at the removal sites decreased over time, resulting in 3x more effort (i.e. time) per individual and overall reduced capture success by the end of the study period, possibly due to shifts in lionfish behaviour following unsuccessful capture. Given that lionfish recolonization is ongoing, our study shows that expending effort to

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achieve complete removal from reefs is often not the optimal strategy, and in fact provides diminishing returns in terms of catch per effort over time. Instead, we propose that removal effort is best spent suppressing lionfish to low levels, using LRT model targets as a guide, and diverting extra effort to achieve suppression at a broader range of sites.

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ii. Project rationale

The lionfish invasion Indo-Pacific lionfish (Pterois volitans and P. miles) have swiftly invaded the western Atlantic, Caribbean and Gulf of Mexico, where they now occupy virtually all marine habitat types from shoreline to at least 1,000 feet deep [1, 2]. Well-defended from predation by venomous spines, lionfish consume a wide array of native marine species [3, 4]. Dense lionfish populations have rapidly depleted native fish biomass at several invaded coral reef sites [4-6], and exponential increases in abundance continue across the region [7]. Over the past two years lionfish have rapidly colonized US coral reef, mangrove and seagrass habitats off South Florida, in the Gulf of Mexico and around the US Caribbean territories of Puerto Rico and the Virgin Islands. Their abundance is now increasing rap idly across all locations [7, 8]. Without prompt management action, widespread impacts from lionfish pose a serious threat to the integrity of US coral reef ecosystems, and the coastal human populations which depend on them [9,10]. Management action To mitigate the effects of lionfish, managers across the region are currently designing and implementing control programs [11]. To be effective, these programs must make efficient use limited management resources, necessitating a pragmatic approach to lionfish control. The vast geographic extent of the invasion makes complete eradication of lionfish from the Atlantic unlikely [12, 13]. However, local control—in the form of manual removal by divers, snorkelers and fishers— is proving effective in reducing lionfish densities at many locations [11]. Local control is now emerging as the primary strategy for preventing ecological impacts within priority marine areas invaded by lionfish, such as MPAs (i.e., national parks, marine sanctuaries and special protected areas). Information needs Three major questions emerge when designing lionfish control plans: 1) Where should removal efforts be targeted? 2) How many lionfish should be removed? 3) How much effort is required to effect sufficient removal? Priority locations for control can be identified by considering ecological and socioeconomic value, logistic constraints and legal mandates within specific jurisdictions. However, an effective method for setting quantitative lionfish removal targets within these priority areas, and estimates of the resources required to achieve removal, are urgently needed to guide management action.

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iii. Project objectives

The project seeks to provide managers with critical information needed to protect coral reef ecosystems from the impacts of invasive lionfish. This work focuses on two objectives, comprised of two goals each: Objective 1: Develop a predictive management tool for setting location-specific lionfish control targets (LRT Model) An empirical model recently developed by Green et al. [14] provides the basis for a broadly-applicable method for estimating location-specific targets for lionfish removal. The Lionfish Removal Target Model (from here on referred to as the ‘LRT Model’) quantitatively links the density of local lionfish populations to the severity of their impact on native marine fish communities by estimating two essential rates: prey consumption by invasive lionfish and biomass production by native fish prey. Targets for control are estimated as the threshold densities at which lionfish over-consume native fishes, causing declines in their biomass. Maintaining local lionfish densities at or below the target ‘threshold’ density can thus prevent predation-induced declines in native fish biomass. Prey consumption rates for lionfish are estimated from field observations of predation behaviour and account for the effects of varying lionfish body size and water temperatures on invaded coral reefs [15-17]. Production rates for native fish prey are estimated by converting standing fish biomass to annual production rates, using known scaling constants between fish body size, water temperature and net rate of biomass production (i.e. somatic growth plus reproduction, minus natural mortality) [18,19]. The LRT Model uses location-specific data on native prey fish, lionfish and water temperature gathered through monitoring programs. As a result, control targets (expressed as lionfish per unit area) are relevant to the local scale at which both impacts and removals occur. While the approach has been applied and validated for coral patch reefs in the Bahamas, the general structure of the LRT Model may be applicable across habitat types and environmental conditions. This project will determine whether the LRT can be adapted into a general tool for use by managers in any location to set local-targets for lionfish removal. Objective 1 will be achieved through three sub-components:

a) Assess the performance of the LRT Model under a variety of habitat and environmental conditions

b) Determine how data quality and quantity effect LRT Model output c) Develop LRT modelling tool software and user guide

This grant supported the achievement of Objectives 1a and b.

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Objective 2: Determine the management effort required to meet and maintain lionfish removal targets After managers have identified priority areas for lionfish removal and established targets for control, they must next determine the resources (i.e., personnel and logistics) required to conduct removals. Information on catch per unit effort (CPUE) of lionfish required to meet removal targets is currently unavailable, but will greatly aid managers in estimating resource needs within their jurisdiction. We propose to quantify the effort (i.e., in terms of cost, time and personnel) required to meet and maintain LRT model targets. Information on CPUE by habitat type, initial lionfish densities and gear-type (i.e., spear versus hand net) will be distributed to managers, so that they can better estimate resource requirements based on conditions within their local jurisdiction. Objective 2 will be achieved through two subcomponents:

a) Assess the effort required to achieve lionfish removal target b) Assess the frequency of removal required to maintain lionfish removal targets

iv. Methods

a. Study design

This project addresses Objectives 1a/ b and 2a/b by developing and testing targets for lionfish control on invaded coral reef sites off south Florida via a removal experiment. We have secured funding to continue the experiment through December 2015 with continued support from NOAA CRCP and our other project partners, with aim of starting to evaluate the long term effects and management of lionfish on coral reef communities in future. Here we report on the findings of this study conducted during the award period (February 2013-March 2013). In February 2013, we selected 42 locations in three coral reef sites representing continuous and patch reef habitats within three zones off South Florida; 20 study sites within the 'no-spearing zone' off Key Largo within the Florida Keys National Marine Sanctuary (FKNMS), 6 sites within Tennessee and Conch Reef ROAs within FKNMS, and 16 sites within Biscayne National Park (BNP) as locations for this study (Figure 1). Of these sites, half are patch reef habitats at ~3-5m depth, located on the eastern edge of Hawk Channel, which runs north-south along the Atlantic coast of the Florida Keys approximately 1 mile from shore. The other half of sites are located on continuous reef habitats at ~20m depth located approximately 3 miles from shore. The study sites span 140km stretch of reef from Elliott Key south to Matecumbe Key (Figure 1). Both targeted removal and reference sites are visited on a bi-monthly basis to gather time series

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data on lionfish density, size distribution and colonization rates in relation to habitat factors and removal effort (Table 1). To delineate survey areas on continuous reefs, we ran two- 50 x 20m transects parallel from the reef crest each site (at depths of ~20 and 15m), starting at an installed rebar marker at a depth of ~20m. Patch reef sites were all selected to be <50m in diameter, and were clearly distinct habitats separated by sand and seagrass on all sites from adjacent reef. Figure 1. Study reefs off the upper Florida Keys and Biscayne Bay. Shading indicates regulatory boundaries: yellow (FKNMS) and white (BNP). Dot color indicates experimental treatment: red (lionfish monitoring and removal on a bi-monthly basis) and white (no lionfish removal; monitoring only). Yellow dots indicate study sites within 'Research Only Areas' of the FKNMS: 1 (Conch Reef) and 2 (Tennessee Reef). Both ROA zones contain a total of 6 lionfish removal sites.

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Table 1. Study design and data collection schedule for the targeted lionfish removal experiment in South Florida. *Indicates similar sites that are not prioritized for removal and thus will serve as ‘no removal’ controls for the experiment

Location Treatment

Number of sites per habitat

Bi-monthly lionfish removal

Bi-annual monitoring

Total days Patch

reefs Continuous reefs

Days per event

Total events

Days per event

Total events

BNP

Targeted removal 4 4 2 7 4 3 26

Reference* 4 4 2 7 4 3 26

FKNMS

Targeted removal 6 7 4 7 7 3 49

Reference* 6 7 4 7 7 3 49

b. Modelling targets for lionfish control The LRT Model uses site-specific data on native prey fish biomass, lionfish body sizes and water temperature to estimate local rates of prey fish production and lionfish prey consumption. Details of the model structure and required parameters are available in Appendix II. Targets are set from the LRT Model as the density below which lionfish will not over-consume their prey, causing declines in biomass. The necessary data sets must contain information on the density and size of all small-bodied fishes (i.e., <15 cm total length [TL], the maximum size deemed potential prey for lionfish). These data are collected most reliably using replicated belt transect surveys at each site, in which detailed searches for all fishes (including juveniles and cryptic species) are conducted [21]. Site-specific data on lionfish body sizes and densities are most reliably obtained from replicated lionfish-only belt transects surveys at each site. Some of the required native fish, lionfish and water temperature data are currently collected at several of the study locations during on-going research and monitoring projects by regional and local partners (Table 1).

In February 2013, we gathered data on native prey fish biomass and lionfish body sizes to parametrize the LRT Model for the 42 study reefs using standard methodologies developed for monitoring lionfish and their prey on continuous and patch reef habitat types (Green 2012 in `Monitoring for Ecological Impacts' in JA Morris Ed. 'Invasive lionfish: A guide to control and management'; described in detail below in section ‘c’ and ‘d’ below). We then used our site-specific field data on native prey fish biomass and lionfish body sizes, along with annual local water temperature data from the NOAA National Buoy Center

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(http://www.ndbc.noaa.gov/buoy), to generate probabilistic site-specific predictions for the density at which lionfish would begin to over-consume the prey base at each site (Appendix II; Figure 2).

c. Testing control targets through lionfish removal and monitoring

Over the project period, we conducted bi-monthly dives at each reef site to survey for invasive lionfish, and also carried out removals at half of the sites which were designated as the 'removal' treatment. Our protocol for monitoring lionfish followed the standard methodologies developed for monitoring on continuous and patch reef habitat types (Green 2012 in `Monitoring for Ecological Impacts' in JA Morris Ed. 'Invasive lionfish: A guide to control and management'). During each site visit, two buddy teams of divers (4 divers total) made a systematic search for lionfish and native predator species (potential competitors with lionfish) within 1- 50x 20m transect area on continuous sites, or along 1/2 of each side for patch reefs, taking ~30-40mins for the search. At the removal sites, any lionfish sighted were removed by spear or net by one of the buddy team members. The second buddy recorded data on lionfish location, size, behaviour, and search/removal effort, including the time spent locating each lionfish, number of attempts at capture, whether the fish was caught successfully, and the type of gear used for collection. Information recorded by each dive buddy pair was used to calculate catch per unit effort over time and across sites (Objective 2a). All collected specimens were measured, dissected and archived in each location (FKNMS specimens are archived at REEF and Biscayne specimens are archived by Biscayne National Park). We then compared the density of lionfish at removal and non-removal sites over the course of the experiment to evaluate the ability of diver removal to suppress lionfish below target control levels and the amount of effort required to achieve control.

d. Monitoring native fish community response to lionfish control

Every six months during the project period, we collected data on native reef fish communities at all study sites in FKNMS and Biscayne National Park (February 2013, Sept 2013 and March 2013). Methods for native reef fishes followed the standard methodologies developed for monitoring on continuous and patch reef habitat types (Green 2012 in `Monitoring for Ecological Impacts' in JA Morris Ed. 'Invasive lionfish: A guide to control and management' ). At continuous sites, we again conducted 4 replicated belt transects surveys of 20 x 2m length, on which we counted and estimated total length (to the nearest 1cm) of all native fishes. Transects followed the survey lines deployed to delineate the site, and ran parallel to the reef crest. During a first pass of the transects (~4min duration) we recorded the identity, size and abundance of all fish species greater than 15cm total length, and on a second pass (~20min duration) we recorded the identity, size (total length [TL] to the nearest cm) and abundance of all reef fishes less than 15cm total length. At patch reef sites, we conducted 4 replicated belt transect surveys of 20 x

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2m, on which we counted and estimated total length (to the nearest 1cm) of all native fishes. Transects were stratified across the reef area in north-south orientation. To survey lionfish on patch reefs, we bisected the habitat by running a transect line along the middle of the patch. In a buddy pair, we then conducted separate roving diver surveys on each half of the patch, recoding the location, size (TL to the nearest 1cm) and behavior of lionfish only following the same search method of Green et al. 2012. At all sites, we also conducted 30min REEF roving diver surveys and stationary visual census (SVC) surveys. Native fish community and lionfish population data from these methods were used to compare the utility of each, in comparison to transect data, in generating targets for lionfish removal, as well as tracking changes in native fish community composition over the course of the experiment.

v. Results

a. Targets for lionfish control

Lionfish were present at 31 of the 42 reefs at the outset of this study, with in situ densities ranging from 0-1,000 lionfish ha-1 across the sites (164 ± 231 lionfish ha-1; mean ± SD; Figure 2). At the start of the study, lionfish density was much greater at sites within FKNMS (217 ± 273 lionfish ha-1; mean ± SD) compared with Biscayne National Park (82 ± 106 lionfish ha-1; mean ± SD). In FKNMS, lionfish densities were greater on shallow patch reefs within Hawk Channel (403 ± 296 lionfish ha-1; mean ± SD), compared with deeper continuous reefs (71 ± 135 lionfish ha-1; mean ± SD). However, we found the opposite pattern in Biscayne; lionfish densities on deeper continuous sites (120 ± 136 lionfish ha-1; mean ± SD) greatly exceeding those on shallow patch reefs (45 ± 45 lionfish ha-1; mean ± SD).

We found little relationship between the intensity of invasion (i.e. lionfish biomass) and the amount of prey biomass available at the study reefs at the start of our study (Figure 3). Predictions generated from the LRT Model using site-specific fish community data reveal the study reefs within FKNMS and BNP could tolerate lionfish densities ranging between an average of 14 and 201 lionfish ha-1 across the sites, before lionfish would begin to over-consume local reef fish prey (Figure 2). Target ‘threshold’ density varied greatly across the study reefs owing to the large variation in the standing biomass of reef fish prey (Figure 2; Appendix II). Lionfish densities exceeded predicted threshold targets at 27 of the 42 study reefs (64%) at the outset of the experiment. Lionfish density reductions ranging between 6 to 97%, depending on the site, were required in order to prevent further lionfish predation effects to resident prey fishes at reefs where densities exceeded these threshold values (Figure 3).

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Figure 2. Comparison of the actual density of invasive lionfish (blue bars) and the predicted ‘sustainable’ densities of lionfish (red bars) at each of the 42 coral reef study sites off South Florida. The difference between the two bars at each site is the extent to which lionfish densities must be reduced in order to prevent predation-induced declines to native prey fishes.

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Figure 3. Relationship between the standing biomass of lionfish and prey-sized (i.e. <12cm TL) native fishes on the South Florida study reefs at the outset of the removal experiment. Blue circles represent continuous reefs (N = 22 sites) and orange triangles represent patch reefs (N = 20 sites) There was no significant correlation between the amount of lionfish and prey biomass for either reef type (P > 0.4, R2 <0.06 for both tests).

b. Removal success and recolonization in relation to control targets

Following baseline data collection in February 2013, we conducted over 300 dives across the study sites in both FKNMS and Biscayne National Park between May 2013 and March 2014 to survey fish communities and remove invasive lionfish. Data collection at each site involved a minimum of 4 personnel (for bi-monthly lionfish monitoring and removal) or 6 personnel (for bi-annual native fish monitoring) from Appendix I to complete all tasks. In some cases, two consecutive dives were required to collect all data components at a site.

Over the project period, a total of 620 lionfish observations were made at the 26 study reefs in FKNMS. Of these, 454 were at reference (i.e. 'non-removal' sites), while 166 were at removal sites. Divers successfully removed 134 lionfish from the 13 removal sites in FKNMS (an average 81% capture success over the period). Over this same period, 167 lionfish observations were made at the 16 study reefs in Biscayne National Park, where 69 were at reference (i.e. 'non-

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removal' sites), while 98 were at removal sites. Divers successfully removed 75 lionfish from the 8 removal sites in FKNMS (an average 76% capture success over the period).

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Figure 4. Lionfish density (mean ± 95% CI) at the 42 study reefs off South Florida over the course of the removal experiment. The red lines represent the mean target ‘threshold’ lionfish density for the corresponding group of sites, bounded by 95% confidence intervals (red shaded area).

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Lionfish recolonization rates following removal events ranged from 0 to 150 lionfish ha-1 month-1 across the study, depending on the site (Figure 4). In general, re-colonization was much lower on study reefs in Biscayne National Park compared with those in FKNMS, with lionfish completely absent from the majority of both continuous and patch reef sites in BNP by March 2014, regardless of treatment (Figure 4a and b). By contrast, lionfish consistently recolonized both continuous and patch reef sites within FKNMS following depletion during bi-monthly removal visits (rate: 15 ± 25 lionfish ha-1 month-1; mean ± SD; Figure 4c and d).

Regardless of treatment (i.e. removal or non-removal), the size of lionfish increased significantly on deep continuous reefs sites in both BNP and FKNMS over the course of the study (Figure 5a and b). By contrast, average lionfish size decreased on shallow patch reefs where removal took place, but remained constant on reference patch reefs where culling did not occur for this study (Figure 5c and d).

Figure 5. Body size (mean ± 95% CI) of lionfish at the 42 study reefs off South Florida over the course of the removal experiment.

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c. Quantifying removal efficiency and effort

At the outset of the study, surveyors removed an average of 90% of lionfish encountered on removal reefs (Figure 6), with each dive pair spending an average of 1.04 min fish-1 to collect and secure each individual lionfish. As a result, during the first round of removals at the study sites, divers were successfully able to collect all lionfish sighted (i.e. achieve a density of 0 lionfish ha-

1) from 75% of the study reefs, leaving a single or few individuals uncaptured at 25% of sites. Over the course of the study, divers were able to maintain lionfish densities below 10 lionfish h-1 across the removal sites. However, the amount of effort expended by teams to achieve suppression steadily increased over time, rising to 3.6 min fish-1 by the end of the year; more than 3x the amount of time expended per fish compared with the start of the study (Figure 6b). Although culling efforts outstripped the rate at which lionfish recolonized between site visits (Figure 4) resulting in continued suppression of lionfish below target ‘threshold’ densities, divers had decreasing success in culling the few lionfish present at the removal sites over time, which capture success steadily decreasing to 67% by the end of the year (Figure 6a). Figure 6 A. The proportion (mean ± 95% CI) of invasive lionfish encountered at the 21 removal reefs that were successfully captured over the course of the experiment. B. The amount of time (in mins; mean ± 95% CI) spent pursuing each lionfish encountered across the 21 removal reefs in South Florida.

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i. Discussion This study utilized basic monitoring data on native fish community biomass and size structure, and water temperature within the LRT modelling framework to estimate ecological thresholds at which invasive lionfish begin to deplete their prey resources for 42 coral reefs sites in FKNMS and Biscayne National Park, and shows that sustained local removal by divers and snorkeler is successful in suppressing lionfish below levels predicted to elicit negative ecological impacts. Our analyses indicate that the level of invasion that reefs can tolerate before negative effects are likely to occur varies greatly across sites, owing to large natural variation in the standing biomass of native reef fish prey at a reef. Variable densities of lionfish across the sites at the outset of the experiment meant that the extent to which lionfish needed to be culled in order to achieve adequate suppression varied greatly across the 42 South Florida reefs.

Our year-long removal experiment revealed that bi-monthly removal visits were sufficient to continually suppress local lionfish densities below critical threshold densities across all sites. Recolonization rates were highly variable across sites. Given that bi-monthly removal was sufficient to maintain lionfish below critical levels at the most rapidly recolonized sites, it is likely that less frequent visitation may be sufficient to achieve adequate control at sites across many of the reefs. However, our estimates of recolonization are based on a single year of data; it will be essential to understand how annual variation in environmental conditions affect recolonization, and thus the efficacy of control, over a longer time period. We are currently working with Oregon State University PhD candidate Alex Davis to tease out environmental correlates of patchy lionfish distribution and recolonization rates across the study system.

Preliminary analyses of native fish community data from the study reefs shows a small decline in the biomass of the smallest size classes of lionfish prey at reference (i.e. non-removal reefs), but no evidence of decline or recovery for larger size classes between treatments. This is not wholly unexpected given the short duration of the project (one year); other studies of lionfish control have only observed significant changes in native fish biomass following 18 months of lionfish culling, owing to a lag in the effects of predation by lionfish on the size structure of native fish communities [14]. By continuing this removal study long-term, our intent is to gather fish community data over a period sufficient to evaluate the extent to which native fish communities respond to continued lionfish population suppression in the study region.

Crucially, we found that the amount of effort required to capture lionfish increased substantially over the course of the study, and that divers successfully captured a smaller proportion of lionfish that remained at reefs over time. Although lionfish densities remained suppressed below target levels at the study sites, the amount of time spent capturing individual lionfish increased more than 3 times over the course of the study and capture success decreased. These effects may occur if removers are selecting for the most ‘bold’ lionfish first, leaving wary individuals for subsequent visits that are difficult to capture or lionfish may exhibit learned avoidance of divers following capture attempts. We are currently examining behavioural data collected during lionfish surveys to determine the extent to which such behavioural shifts are occurring, and what their effect may be on overall removal success and effort.

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ii. Next steps Develop the LRT model software tool and user guide The LRT modelling framework is a field-validated approach for developing ecologically meaningful targets for lionfish suppression across invaded habitats. Our study shows that sustained removal efforts can be successful in suppressing lionfish populations. However, the next key step in setting and applying targets for control is to identify priority locations for removal effort. Priorities will be based on a number of factors, including ecological, economic and social components. Our aim is to support managers in identifying priority locations by understanding the risk posed by lionfish to ecological resources in a variety of near shore marine habitats by developing the LRT model in to a freely and widely available software tool that managers across the region can use to identify locations at most risk from the lionfish invasion (Objective 1c- not part of this award). Evaluate the effects of environmental variation on lionfish recolonization and prey response Understanding the effect of inter-annual environmental variation and on-going regional actions to control lionfish on local invasion dynamics is key or informing on going control efforts. To this end, we have secured funding to continue the lionfish removal study through December 2015 and aim to seek additional support to maintain the project long term. We will continue to incorporate lionfish and native fish community as part of an on-going long term study of the ecological and management of lionfish on South Florida reefs. Data from this research will also contribute to a comparative project assessing the relative cost and effectiveness of three lionfish removal techniques (derbies, trapping and sustained diver removal [this project]), funded by Florida Sea Grant. Additional field, travel and staff funding continue to be provided as match for this project through the Elizabeth Ordway Dunn Foundation, the Mote Protect Our Reefs Fund and David H. Smith Conservation Research Fellowship.

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References 1. Morris, J.A.J., and Whitfield, P.E. (2009). Biology, Ecology, Control and Management of the Invasive Indo-Pacific Lionfish: An Updated Integrated Assessment. NOAA Technical Memorandum NOS NCCOS 99. 2. Betancur-R. et al. (2011). Reconstructing the lionfish invasion: insights into Greater Caribbean biogeography. Journal of Biogeography 38: 1281-1293 3. Morris, J.A.J., and Akins, J.L. (2009). Feeding ecology of invasive lionfish (Pterois volitans) in the Bahamian Archipelago. Environmental Biology of Fishes 86, 389-398. 4. Green, S. et al. (2012). Invasive lionfish drive Atlantic coral reef fish declines. PLOS ONE. 5. Albins, M.A., and Hixon, M.A. Personal communication 6. Albins, M.A., and Hixon, M.A. (2011). Worst Case scenario: potential long-term effects of invasive predatory lionfish (Pterois volitans) on Atlantic and Caribbean coral-reef communities. Environmental Biology of Fishes 7. REEF (2011) Reef Environmental Education Foundation Volunteer Fish Survey Project. www.reef.org. 8. USGS (2011) USGS Non-Indigenous Aquatic Species Database. 9. Sutherland, W.J. et al. (2010). A horizon scan of global conservation issues for 2010. Trends in Ecology & Evolution 25, 1-7. 10. Albins, M.A. and Hixon, M.A. (2008). Invasive Indo-Pacific lionfish Pterois volitans reduce recruitment of Atlantic coral-reef fishes. Marine Ecology Progress Series. 367:233-238 11. Akins, J.L. (2011). Methods for control. In Best practicies and stragtegies for lionfish control, J. Morris, ed. (NOAA ICRI joint publication). 12. Morris, J. et al. (2011). A stage-based matrix population model of invasive lionfish with implications for control. Biological Invasions 13, 7-12. 13. Barbour, A.B. et al. (2011). Evaluating the potential efficacy of invasive lionfish (Pterois volitans) removals. PLoS ONE 6, e19666. 14. Green, S.J., N.K. Dulvy, A.B. Cooper, I.M. Côté. (2014) Linking removal targets to the

ecological effects of invaders: A predictive model and field test. Ecological Applications. 24: 1311-1322.

15. Green, S.J. et al. (2011). Foraging behaviour and prey consumption in the Indo-Pacific lionfish on Bahamian coral reefs. Marine Ecology Progress Series. 433: 159-167. 16. Côté, I.M., and Maljkovic, A. (2010). Predation rates of Indo-Pacific lionfish on Bahamian coral reefs. Marine Ecology Progress Series. 404: 210-255. 17. Côté, I.M., and Green, S.J. (2012). Potential effects of climate change on a marine invasion: the importance of current context. Current Zoology. 18. Brown, J.H. et al. (2004). Towards a metabolic theory of ecology. Ecology. 85(7): 1771- 1789.

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19. Lorenzen, K. (1996). The relationship between body weight and natural mortality in juvenile and adult fish: comparison of natural ecosystems and aquaculture. Journal of Fish Biology. 49: 627-647. 20. Ault, T.R. and Johnson, C.R. (1998). Spatially and temporally predictable fish communities on coral reefs. Ecological Monographs. 68: 25-50. 21. Green, S.J. (2012) Ecological monitoring methods. In Invasive lionfish: A guide to control and management, JA Morris Jr., ed. (GCFI Special Pubilcation publication). 22. Bohnsack, J.A., and Bannerot, S.P. (1986). A stationary visual census technique for quantitatively assessing community structure of coral reef fishes. NOAA Technical Report NMFS 41. 23. Schmitt, E.F., and Sulllivan, K.M. (1996). Analysis of a volunteer method for collecting fish presence and abundance data in the Florida Keys. Bulletin of Marine Science. 59(2): 404- 416.

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Appendix I. Project partners that have assisted with lionfish surveys and removals at the 42 coral reef study sites off South Florida. Sector Agency Description Key personnel

Biscayne National Park

BNP staff has conducted bi-monthly lionfish surveys and removals at the 16 BNP sites.

Dr. Vanessa McDonough, Shelby Moneysmith

John Pennekamp State Park

Pennekamp Park staff has assisted with bi-monthly lionfish surveys and removals at the 20 sites in FKNMS.

Steve Schalk, Trudy Ferraro

University

NOVA Southeastern University

We are conducting lionfish surveys and removals at the 6 sites within Conch and Tennessee Reef ROAs, in conjunction with an MSc project research at NOVA Southeastern University (lionfish movement through external tagging and tracking of lionfish between removal and adjacent non-removal sites).

Dr. David Kersetter, Adam Nardelli, Ben Barker

University of Miami

University of Miami MSc program students are employed as lionfish interns with Biscayne National Park and have assisted with bi-monthly lionfish surveys and removals at the 16 BNP sites.

Kristian Rogers

Non-government

Coral Restoration Foundation

CRF has generously donated staff time for bi-monthly lionfish surveys and removals at the FKNMS 20 sites.

Jessica Levy, Kayla Ripple

REEF

REEF interns and staff have participated in the bulk of data collection, monitoring and lionfish removals to date.

Elizabeth Underwood

Keys Marine Lab

Marine Lab staff have generously donated time for bi-monthly lionfish surveys and removals at the FKNMS 26 sites.

Keri Kenning, Ellie Splain

Audubon Society

Audubon Society staff have generously donated time for bi- Elissa Connolly-Randazzo

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monthly lionfish surveys and removals at the FKNMS 26 sites.

volunteers

A number of local volunteers donated time and logistic expenses to conduct data collection, monitoring and lionfish removal in both FKNMS and BNP.

Carlos and Allison Estape, Roger and Patricia Grimes, Joe Thomas, Liz Becker, Ed Martin, Lindsay Sweet

Dive industry

Quiescence Dive Services

Quiescence Dive Services has provided discounted logistic support and donated staff time to the bi-monthly lionfish removals in FKNMS.

Rob Bleser, Steve Campbell, Harry Sutherland, Ryan Trueblood, Cait Kelliher

Divers Direct Divers Direct currently provides discounted logistic support for field activities and will continue to do so.

Kevin Sennecal, Kathy Smith

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Appendix II: Model structure and parameters LRT model description and parameter table modified from Green et al. 2014 [14]: The LRT Model predation focuses on estimates of two annual, assemblage-specific (i.e., site-specific) rates: biomass production by lionfish prey (𝑃𝑃�; g ha-1 yr-1), and the rate of prey consumption by lionfish (𝐶𝐶̅; g ha-1 yr-1) per site. The difference between the two is the net rate of biomass production (𝑁𝑁𝑝𝑝��) by the prey fish assemblage at a site: 𝑁𝑁𝑝𝑝�� = 𝑃𝑃� − 𝐶𝐶̅ (1)

Our model and analyses are based on the hypothesis that the biomass of prey fishes residing on a reef will decline if lionfish consume prey at a rate that exceeds the rate of prey production (i.e., 𝑁𝑁𝑝𝑝��< 0).

Rates of prey fish production (𝑃𝑃�). We estimated the rate of annual prey fish production

(𝑃𝑃�) by converting the body mass of fish prey to rates of annual biomass production using known metabolic relationships (Brown et al. 2004). This approach considers the intrinsic relationship between a fish's size and the rate at which it produces new biomass (Allen 1971; Banse and Mosher 1980; Jennings 2005). This simple approach assumes that variation in the rate of natural mortality from native predators is not a substantial influence on prey production at each reef site. However, there is evidence that lionfish can exert mortality on their prey that far exceeds that from native predators, resulting in local extirpation of reef fishes (Pusack et al. 2013; Albins 2012), supporting our approach of singling out lionfish predation as a main driver of prey biomass dynamics. In addition, variation in reef fish biomass, owing to recruitment variation, could affect our estimates of fish standing biomass, and thus productivity. However, the magnitude of variation in fish biomass is often far greater between reefs than within-reefs over time (Cassele and Warner 1996; Hamilton et al. 2006; Hixon et al. 2012) and, for broadcast spawning fishes, recruitment and mortality in the first year of life has been shown to contribute little to overall population growth rate (Heppell et al. 1999) . Our method captures spatial variation in fish biomass by generating reef-specific models, and we approximated within-reef variation in fish biomass by conducting multiple spatially-segregated surveys of fish biomass time, and incorporating variance among surveys into estimates of site-specific production.

𝑃𝑃� was calculated as:

𝑃𝑃� =1𝑧𝑧��𝑃𝑃𝑣𝑣,𝑖𝑖,𝑧𝑧

∀𝑣𝑣∀𝑖𝑖∀𝑧𝑧

(2) where v is a single individual of fish species i observed on visual transect survey z per site. For simplicity, we will refer to 𝑃𝑃𝑣𝑣,𝑖𝑖,𝑧𝑧 as 𝑃𝑃, which is calculated as:

𝑃𝑃 = 𝑍𝑍𝑍𝑍 (3)

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Z and 𝑍𝑍are the total mortality rate (i.e. the probability of dying) and body mass, respectively, for each individual fish. The mortality rate 𝑍𝑍 scales as an allometric function of body mass (𝑍𝑍) with constants j and q, which approximates the ratio of production rate in g ha-1 yr-1 to standing biomass in g ha-1 (i.e., P/B of (Polovina 1984), such that:

𝑍𝑍 ≈ 𝑃𝑃𝑍𝑍

= 𝑗𝑗𝑍𝑍𝑞𝑞

𝑒𝑒𝐸𝐸/𝑘𝑘𝑘𝑘

(4) The scaling exponent (q) of the relationship between P/B and body mass has been theoretically explored, and empirically validated (Brown et al. 2004), as -0.25. However, j varies with taxonomic group and ecosystem-specific species interactions (Brown et al. 2004). Analyses of juvenile and adult marine tropical fish taxa suggest a j value of 3.08 (Lorenzen 1996). The equation 𝑒𝑒𝐸𝐸/𝑘𝑘𝑘𝑘 describes the effect of environmental temperature on prey fish production rates, where E is the activation energy, k Boltzmann’s constant and T is ambient water temperature, expressed in degrees Kelvin (Table A1). Prey fish body mass 𝑍𝑍 was estimated using the allometric function:

𝑍𝑍 = 𝑎𝑎𝑖𝑖𝐿𝐿𝑏𝑏𝑖𝑖 (5) where 𝐿𝐿 is the total length of individual fish, converted to weight using allometric length-weight scaling constants 𝑎𝑎𝑖𝑖and 𝑏𝑏𝑖𝑖 which are species-specific and derived from the literature (Fish Base; http://www.fishbase.org). Rates of lionfish prey consumption (𝐶𝐶̅).We estimated annual reef-specific prey consumption by lionfish at a site (𝐶𝐶̅) from four key reef-specific parameters: lionfish population density, size structure, diet composition and predation rates. Thus, 𝐶𝐶̅ = �̅�𝑑𝑊𝑊� �̅�𝑝(0.006𝑒𝑒0.16𝑘𝑘𝑊𝑊𝑙𝑙��

ℎ)𝑦𝑦 (6) where �̅�𝑑 is the density of lionfish per hectare of habitat, calculated as the average number of lionfish observed on transects at the site (individuals ha-1). 𝑊𝑊� is the mean body mass (in g) of lionfish, calculated as: 𝑊𝑊� = 1

𝑚𝑚∑ (𝑎𝑎𝑙𝑙𝐿𝐿𝑚𝑚𝑏𝑏𝑙𝑙)∀𝑚𝑚

(7) where 𝐿𝐿𝑚𝑚 is the total length of each of m lionfish (in cm) observed at the site, and 𝑎𝑎𝑙𝑙and 𝑏𝑏𝑙𝑙 are lionfish-specific allometric length–weight scaling constants. In Equation 6, the parameter �̅�𝑝 estimates the mean proportion of fish in the total diet of lionfish, which can take a value between 0 and 1. The function 0.006e0.16T describes the scaling

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relationship between lionfish mass-specific prey consumption rate (g prey-1 g lionfish-1 day-1) and body weight (g) derived by Côté and Green (2012) from two field studies of lionfish prey consumption at different water temperatures (Côté and Maljković 2010, Green et al. 2011; Table A1). The scaling constant h has a value of -0.29 for lionfish (Côté and Green 2012). Finally, we extrapolated average daily consumption rates by lionfish to annual rates by multiplying by the constant y, which is 365.4 days/year. Our approach to estimating consumption assumes that prey density has little effect on lionfish consumption rates because. Field and experimental observations of invasive lionfish reveal that they achieve high rates of prey capture (Green et al. 2011) and cause prey mortality rates near 1 (Pusack 2013) across prey densities. Our model of net prey fish production (𝑁𝑁�), with all terms made explicit, is given by:

𝑁𝑁𝑝𝑝�� =1𝑧𝑧

��𝑗𝑗(𝑎𝑎𝑖𝑖𝐿𝐿𝑣𝑣,𝑖𝑖,𝑧𝑧

𝑏𝑏𝑖𝑖)𝑞𝑞

𝑒𝑒𝐸𝐸𝑘𝑘𝑘𝑘

�𝑎𝑎𝑖𝑖𝐿𝐿𝑣𝑣,𝑖𝑖,𝑧𝑧𝑏𝑏𝑖𝑖

∀𝑣𝑣∀𝑖𝑖∀𝑧𝑧

− �̅�𝑑1𝑚𝑚�(𝑎𝑎𝑙𝑙𝐿𝐿𝑚𝑚𝑏𝑏𝑙𝑙)∀𝑚𝑚

�̅�𝑝 �0.006𝑒𝑒0.16𝑇𝑇1𝑚𝑚�(𝑎𝑎𝑙𝑙𝐿𝐿𝑚𝑚𝑏𝑏𝑙𝑙)𝑚𝑚

ℎ

�𝑦𝑦

(8) Target lionfish density (�̅�𝑑). The density 'threshold' at which lionfish begin to deplete resident fish prey on an invaded reef is modelled as the density at which prey consumption by lionfish (𝐶𝐶̅) equals the rate of prey fish biomass production (𝑃𝑃�) (𝑁𝑁𝑝𝑝�� = 0 in Equation 1). Thus, by setting 𝑁𝑁𝑝𝑝�� =0 and solving for �̅�𝑑 in Equation 8, this target density is given as:

�̅�𝑑 =

1𝑧𝑧 ∑ ∑ ∑ �

𝑗𝑗(𝑎𝑎𝑖𝑖𝐿𝐿𝑣𝑣,𝑖𝑖,𝑧𝑧𝑏𝑏𝑖𝑖)𝑞𝑞

𝑒𝑒𝐸𝐸𝑘𝑘𝑘𝑘

�𝑎𝑎𝑖𝑖𝐿𝐿𝑣𝑣,𝑖𝑖,𝑧𝑧𝑏𝑏𝑖𝑖∀𝑣𝑣∀𝑖𝑖∀𝑧𝑧

1𝑚𝑚∑ (𝑎𝑎𝑙𝑙𝐿𝐿𝑚𝑚𝑏𝑏𝑙𝑙)∀𝑚𝑚 �̅�𝑝�0.006𝑒𝑒0.16𝑘𝑘 1

𝑚𝑚∑ (𝑎𝑎𝑙𝑙𝐿𝐿𝑚𝑚𝑏𝑏𝑙𝑙)𝑚𝑚

ℎ�𝜋𝜋𝜋𝜋2 (9)

In equation 9, we scale �̅�𝑑 by the area over which lionfish forage, which for patch reefs was estimated as 𝜋𝜋𝜋𝜋2; a circular area where the radius r is half the diameter of the patch reef (in m), plus a 10m buffer which accounts for observations of lionfish foraging in seagrass patches adjacent to reefs on which they are resident (Green et al. 2010; Table A1).

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Table A1. Parameters for the LRT model (Green et al. 2014 [14]) used to model the density at which lionfish begin to over-consume their fish prey on invaded South Florida coral reefs. Note: v is a single individual of fish species i observed on visual transect survey z per site. * Indicates parameters for which error was propagated through the calculations using Monte Carlo simulation.

Model component Parameter Meaning Value Source

Prey fish production (𝑃𝑃�)

Lv,i,z *prey fish length 1 -13cm (individual-specific) Site-specific

j, q *metabolic biomass-production scaling constants q =0.25; j =3.08 Brown et al. 2004,

Lorenzen 1996

ai, bi species-specific length-weight scaling constants Species-specific www.fishbase.org

E activation energy 0.65eV Brown et al. 2004 k Boltzmann's constant 8.06 x 10-5 T *water temperature 299.25 ± 3 oK (26 ± 3°C) NOAA 2013

Lionfish prey consumption (𝐶𝐶̅)

al, bl lionfish-specific length-weight scaling constants al = 0.00497;bl = 3.291 Green et al. 2012

Lm *lionfish length 6-390mm (individual-specific) Site-specific h *prey consumption scaling constant 0.29 Côté and Green 2012 x scales daily rate to annual rate 365.4 days year-1 p *proportion of diet composed of fish 0.7± 0.07 Green et al. 2012 T *water temperature 299.25 ± 3 oK (26 ± 3°C) NOAA 2013

r *radial distance of the area over which lionfish forage

Radius of reef area + 10m into sand/seagrass (Green et al. 2011)

Site-specific

y constant scaling daily to annual consumption 365.4 days/year

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NOAA Coral Reef Conservation Grant- Final Report Project title...Indo-Pacific lionfish (Pterois...

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