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In their global assessment which estimated declines in oyster habitat at 85%, Beck et al. (2011) noted the need for more mapping efforts to facilitate management, and lamented the fact that "In many places the distribution of oyster habitat was better documented 100 y ago than it is today..." Florida's State Wildlife Action Plan describes the oyster reefs in Florida as in poor condition and declining but recognizes that spatial data are lacking for most of the state's oyster reefs. The Apalachicola Bay Oyster Situation Report noted: "The total current area of oyster bar in Apalachicola Bay that is not open to fishing is unknown..." (Havens et al. 2013, p. 5). A similar conclusion can be drawn for the oyster resources in general in the bay because the last comprehensive mapping of the subtidal reefs occurred in 2005 to 2006, and that effort did not include quantitative ground-truthing (sampling) of the reefs (Twichell et al. 2007). Moreover, the ongoing comprehensive studies described in Havens et al. (2013) do not include a mapping component. Although these studies are providing valuable new information on the ecology and health of oysters in the bay, and include sampling sites in several geographic areas, many of the reefs in the bay have not been sampled for a decade or more.

Oyster reefs in Apalachicola Bay occur in both tidal zones, but most attention has been paid to subtidal reefs because they provide most of the commercial harvest. Historically, oyster harvest from the bay accounted for up to 90% of the state's total harvest and 10% of the U.S. total (Camp et al. 2015). In recent years, the harvest has declined to less than 50% of these totals, and the declines have been attributed to a variety of issues including decreased freshwater river flows, drought conditions, and over-harvest of oysters (Camp et al. 2015, Pine et al. 2015, Fisch & Pine 2016, Kimbro et al. 2017). In 2012, there was a collapse of the bay's oyster fishery that resulted in substantial hardship to the regional community, and allocation of federal funds to the industry and local community, as well as subsequent studies of the fishery and its recovery (Havens et al. 2013, Camp et al. 2015). To address the need for more spatial information on the bay's oyster resources, a pilot project was conducted in 2015 to compile existing maps of subtidal reefs and provide new mapping of intertidal reefs to show the potential spatial extent of oyster reefs in Apalachicola Bay (Grizzle et al. 2015). This study emphasized the substantial uncertainty in the resulting maps for two reasons: all areas of the bay had not been recently mapped, and very little ground-truthing had been conducted on any of the reefs. The present study was conducted to provide updated maps of the extent and condition of intertidal reefs.

Mapping of intertidal oyster reefs has been conducted using a variety of methods and imagery sources, but mainly has relied on low-altitude aerials and visual interpretation of the imagery (Grizzle 1990, Grizzle et al. 2002, Wall et al. 2005, Seavey et al. 2011, Garvis et al. 2015). In the past decade or so, high-resolution (most recently <1 m) satellite imagery has begun to replace low-altitude aerials for some coastal habitats (Palandro et al. 2003, NOAA 2010). This is due at least in part to substantial differences in cost for acquiring aerial versus satellite imagery, but relatively little difference in quality. Although Grizzle et al. (2015) demonstrated the potential utility of satellite imagery for mapping the intertidal oyster reefs in Apalachicola Bay, they did not include ground-truthing or assessment of how much information on reef condition can be extracted from such imagery.

The present study was designed to build on Grizzle et al. (2015) by addressing three major objectives: (1) construct new maps showing the location and size of the intertidal oyster reefs in the bay, (2) conduct quantitative sampling on selected reefs to characterize their condition, and (3) assess the potential for using online high-resolution satellite imagery in routine mapping and monitoring.


Study Area, Design, and Field Methods

Apalachicola Bay is a large (~45,000 ha) shallow (~2.0 m mean water depth) estuary in northwestern Florida (Fig. 1; Edmiston 2008). Overall, it includes St. Vincent Sound to the west and St. George Sound to the east and receives the discharge from the Apalachicola River, the largest in Florida in terms of flow volume, which has its origins in the southern Appalachian Mountains. The resulting estuarine system is one of the most productive in North America and was designated a National Estuarine Research Reserve in 1979 (Edmiston 2008, Livingston 2015). The Bay is in a transition zone between diurnal tides to the west and semidiurnal to the southeast, resulting in a "mixed" regime ranging from one to five tides daily (Huang et al. 2002, Huang 2010). Tides can be strongly affected by winds but do not typically exceed 1 m in range. Water currents are tidally driven but are also strongly affected by river discharge and winds, and do not typically exceed 1 m/sec except in passes and tidal cuts. The result is generally well-mixed waters with little vertical stratification. Water temperature reflects meteorological trends, typically ranging from 5[degrees]C to 32[degrees]C. Salinity varies widely spatially and temporally, and can vary from less than 1 to 33 in a typical year.

As discussed in the Introduction, oysters are a major component of the ecology of the bay and the economy of the region, and they occur subtidally and intertidally, as in other estuaries in the northern Gulf of Mexico (Kennedy & Sanford 1999). The oyster mapping pilot project mentioned previously (Grizzle et al. 2015) yielded only "preliminary" maps because no field sampling (ground-truthing) was conducted; the present project provided quantitative sampling of these preliminarily mapped intertidal reefs, so the draft maps could be revised. ArcGIS software was used to create the maps which were based on Google Earth imagery obtained in December 2013 and October 2015. The overall dataset of preliminarily mapped reefs consisted of a total of 1,017 individual polygons. The aim for the present study was to inspect 100 (-10%) of the mapped reefs (Congalton & Green 1999, Finkbeiner et al. 2001), focusing on the larger reefs (>2,000 [m.sup.2]) but including the full range of reef sizes. The 100 "target" reefs were randomly selected for initial inspection using the Random Sampling function in Excel (Fig. 1). Final selections, however, were adjusted in the field to insure adequate sampling of the full range of reef sizes and condition in the three major geographic areas of the Bay.

Each reef visited was sampled by excavating three haphazardly located 0.1 [m.sup.2] quadrats, and measurements were made for total weight of live and dead oysters, number of live oysters, and shell height (to nearest millimeter) of a minimum of 30 haphazardly chosen live oysters. The position of each quadrat was determined using a Garmin 77cs GPS unit with advertised 3-m positional accuracy. Overall, the study design included ground-truthing and revision of the preliminary maps resulting from the pilot study (Grizzle et al. 2015) and an assessment of the use of high-resolution satellite imagery for routine monitoring of intertidal oyster reefs.

Data Analysis

Thematic accuracy of the preliminary maps was determined by computing the percent of inspected polygons (of the total visited) that actually were oyster reefs and expressed as "% correct" (= "overall accuracy" in Congalton 1991). In addition, notes were made in the field on reef features (e.g., color and shape) that might be important in revising the criteria used in identifying oyster reefs and potentially assessing reef condition from satellite imagery. The resulting data were used to revise the preliminary maps by deleting incorrectly identified ("non-reef) polygons. In a few cases, new polygons that had not been initially mapped as oyster reefs were added based on field notes, photographs, or other information.

Reef condition was expressed in terms of live oyster density (#/[m.sup.2]), size (shell height) distribution, and total shell (live and dead) weight (kg/[m.sup.2]) based on the quadrat sampling. One-way ANOVA was used to test for significant (P < 0.05) differences in the oyster metrics among the means stratified into three geographic regions in the Bay. This simple spatial analysis also allowed a comparison of oyster data from the present study with oyster metrics and environmental measurements available from other studies.

Assessment of Satellite Imagery

As noted in the Introduction, the present study was designed to "ground-truth" the preliminary maps described in Grizzle et al. (2015), thereby providing field data for refining the maps and characterizing reef condition. Grizzle et al. (2015) used manual interpretation and polygon construction methods based on the "signature" criteria used to identify intertidal reefs in other areas (Grizzle et al. 2002, Garvis et al. 2015). The present study focused on assessment of the potential for using satellite imagery for routine monitoring of intertidal oyster reefs by comparing the oyster field data (quadrat samples) with visually discernable features in the satellite imagery. The reef area in each satellite image at the location of each excavated quadrat was assigned to one of three classes: Class 1: white or off-white; Class 2: light brown-to-olive; and Class 3: dark brown-to-olive. Two oyster metrics (live oyster density and total shell wet weight) from each quadrat sample were then analyzed by class (one-way ANOVA), followed by Tukey Mests when appropriate.


Intertidal Oyster Reef Distribution and Condition

All field work was conducted on November 12-17, 2016. Of the 100 "target" polygons that had been identified as oyster reefs and were visited (Fig. 1), only three were found to be "non-oyster" features; one was a sparse seagrass bed and the other two were areas covered with what appeared to be worm mounds or crab holes. Although these data indicated 97% overall thematic accuracy, the preliminary maps were thoroughly reinspected and compared with other information gathered in the field that might indicate errors in the preliminary maps. This assessment resulted in adjusting the overall thematic accuracy to 77% (see details in Revised Maps section below).

Field sampling revealed one important difference among the reefs visited that potentially has important management implications, and another that likely affects the potential for using satellite imagery as a routine monitoring tool. The field observation with management implications was the occurrence of "dead margins" on reefs in several areas, possibly indicating the effects of boat wakes (Fig. 2A, B). The field observation that likely affects the potential for satellite imagery as a monitoring tool was the occurrence of recently dead oysters in some areas. These reefs largely consisted of intact clusters of dead oysters with articulated valves ("box" oysters) and minimal gape. These reefs also retained the dark brown-to-olive color of live reefs so they closely resembled live oyster clusters. Thus, they could only be differentiated from live oysters by close inspection and would not have been detectable by satellite imagery (see further discussion in the following text).

Each metric for reef condition was assessed on an overall (bay-wide) basis, and by the three geographic regions (Fig. 1). The overall (bay-wide; all quadrat samples combined) mean for live oyster density on the intertidal reefs was 40.6 individuals/0.1 [m.sup.2] (= 406/[m.sup.2]) with a mean shell height of 23.6 mm (Table 1), and the largest oyster collected was 84 mm. The "box" oysters on most reefs in the western bay included spat and adult oysters, indicating a recent massive mortality event, and perhaps more importantly, that there had been only minimal recruitment after the die-off. Mean live oyster metrics reflected this finding and showed a significant (ANOVA, P < 0.001) west-to-east increasing trend in density, but no significant differences in mean shell height or shell wet weights (Table 1). Paired t-tests (following the ANOVA) indicated that each of the three mean oyster density values differed significantly (P < 0.05) from the others.

Although there were differences in size-frequency patterns in oyster size (shell height) among the three geographical regions, the overall dataset (Fig. 3A) and plots by individual region (Fig. 3B-D) suggested two major recruitment periods each year and 2 y classes in the overall dataset--assuming previously reported growth rates and recruitment patterns (Berrigan 1988, Livingston et al. 2000) are still accurate. There are typically two major oyster reproduction periods in Apalachicola Bay: May-June and August-September (Edmiston 2008), which are similar to the pattern in other Florida estuaries (Parker et al. 2013). Because the sampling occurred in November, it was assumed that the first size peak (at 10-20 mm) represented 3-mo-old oysters. Berrigan (1988) reported a mean oyster size (mainly from subtidal reefs) of ~40 mm at 6 mo, ~60 mm at 12 mo, 75 mm (harvest size) after 16 mo, and 75-85 mm in 18-20 mo; these size/age intervals are shown on the size-frequency histogram in Figure 3A. Overall, the size-frequency data suggest two successful recruitment events in 2016 onto intertidal reefs throughout the Bay. As noted previously, the observations of many recently dead (box) oysters in the western portions of the bay suggested a recent massive die-off in that region of all size classes. The size-frequency data also indicate a recent (within two or so years) die-off. mainly because no large/older live oysters were collected although their empty shells ("boxes") were noted.

Revised Maps and Assessment of Satellite Imagery

Figure 4 consists of revised versions of the initial mapping effort separated into three major geographic regions showing the locations of the 782 mapped intertidal oyster reefs, which ranged in size from ~3 [m.sup.2] to 3.9 ha (9.7 ac) and covered a total of 94 ha (233 ac) of bottom area. Intertidal reefs were distributed widely throughout the bay, but there were substantial differences in the number of reefs and areal coverage in the three major geographic regions: 433 reefs covering a total of 56 ha (139 ac) in the western area (St. Vincent Sound); 113 reefs covering 8 ha (19 ac) in the central area; and 236 reefs covering 30 ha (75 ac) in the eastern area (St. George Sound).

The field sampling data from only the 100 visited reefs indicated an overall thematic accuracy of 97%. When the imagery was reinspected, however, it was found that many seagrass beds clustered in a few areas were misidentified in the original mapping effort (Grizzle et al. 2015) as oyster reefs and were deleted. In addition, a few small oyster reefs observed during the ground-truthing had not been mapped originally, and these were added to the dataset. The overall result was a reduction in the mapped oyster reefs from the original 1,017 (Grizzle et al. 2015) to 782, indicating 77% thematic accuracy. Although much remains to be determined with respect to its utility as a routine monitoring tool, perhaps the more relevant question is how much information can easily be extracted from satellite imagery based on existing imagery and methods used in the present study?

As discussed in the Materials and Methods section, three distinct colors (classes) could be discerned in most images of the mapped reefs, and as illustrated in Figure 5. The three classes represent different combinations of reflectance, light wavelengths reflected, and surface roughness or patchiness of the reef surface. All three are to some extent dependent on the properties of the meteorological conditions when the imagery was recorded, the sensor(s) used, and processing of the imagery. All three are also potentially affected by oyster metrics. Thus, the different classes potentially represent measures of reef "condition." The aim here was to determine the relationship between image properties and measured oyster metrics that might be useful in assessing reef condition.

There was no apparent relationship between oyster metrics determined from quadrat samples and the three reef imagery classes when data from all three geographic areas were combined. This was expected because most of the reefs in the western area of the bay consisted largely of dead "box" oysters that appeared very similar in color and other features to reefs with high-density live oysters, as discussed previously. Therefore, only quadrat data from the central and eastern sections of the bay (Fig. 1) were used in the analysis, which showed the same overall trend for live oyster density and total shell wet weight: substantially and significantly greater live oyster density and shell weight in Class 3 (dark brown-to-olive) compared with Class 1 (white or off-white) (Fig. 6).


Oyster Reef Spatial Patterns in Apalaehieola Bay

Oysters are a major component of the ecology of Apalachicola Bay--perhaps covering nearly 10% of the total bay bottom area (see following text)--and the economy of the region. Some of the recent research in the bay has included intertidal reefs, but most has been on subtidal reefs because they are the source of most of the commercial harvest (Edmiston 2008, Havens et al. 2013, Camp et al. 2015, Pine et al. 2015, Kimbro et al. 2017). The present study focused on the intertidal oyster reefs and provided new data on their distribution and condition. Although a detailed comparative assessment cannot be made because of the lack of recent data on the areal extent of subtidal reefs, some useful comparisons can be made. Extensive sampling of the subtidal reefs throughout the bay in 2016 by Florida Fish and Wildlife Conservation Commission indicated that live oysters only occurred at 66 of the 161 total stations sampled, and the overall average live oyster density at those stations was only 17 oysters/[m.sup.2] (Melanie Parker, personal communication), compared with an overall mean of ~400 oysters/[m.sup.2] on the intertidal reefs sampled in the present study (Table 1). Although these data indicate substantial disparity in live oyster density of subtidal and intertidal reefs at present, there is much greater bottom area coverage by subtidal reefs. A total of 94 ha (233 ac) of intertidal reefs were mapped compared with ~1,600 to ~4,000 ha (4,000-10,000 ac) of subtidal "oyster bottom" mapped or estimated in previous efforts (Livingston 1984, Twichell et al. 2007, FDACS 2015). This comparison should not, however, be taken to indicate that the intertidal reefs are not ecologically or otherwise important, but only that their relative areal coverage is much smaller than that of the subtidal reefs. To our knowledge, there are no studies on how the bay's intertidal and subtidal oyster populations might be interconnected with respect to larval recruitment, disease transmission, or other processes.

The previous bay-wide data, however, can be compared with studies in other areas. Referring to the previous data, intertidal reefs covered less than 1 % of the bay's total bottom area (~45,000 ha) compared with the subtidal reefs occupying from 3.5% to 8.9%. Bahr and Lanier (1981) reviewed some of the early work in the southeastern United States and found that intertidal reefs have been reported to cover from less than 1 % to 9% of the entire bottom area of the estuary. Grizzle (1990) reported similar findings [intertidal reefs covered 5.6% of the open water (= not covered by mangroves) areas] in the Mosquito Lagoon on Florida's east coast, and further reported that tidal range was strongly positively correlated with bottom areal coverage. Recent studies by Byers et al. (2015) on the geographic (from North Carolina to northeastern Florida) variations in a variety of oyster reef characteristics documented the importance of tidal prism (tidal range X surface area), thereby explaining some of the underlying causal mechanisms for how tidal range affects oyster reef ecology and spatial patterns in an estuary. Ridge et al. (2015) further identified an "optimal growth zone" for their study reefs in North Carolina that was determined by aerial exposure time, and interpreted their data in the context of sea level rise and landward migration of the intertidal zone. The present study provides extensive data for assessing future changes in intertidal oyster reef spatial patterns and condition.

Considering individual reef condition metrics, the overall (Bay-wide; all quadrat samples combined) mean for live oyster density (~400/[m.sup.2]) and mean shell height of 23.6 mm in the present study compare well with recent studies in the bay by Kimbro (2013), and the density data compare well with some historical data from the subtidal reefs (Berrigan 1988). Mean size of oysters on the bay's intertidal reefs in 2016, however, was substantially less than historical data for the subtidal reefs; Berrigan (1988) reported mean shell heights ranged from 26.7 to 65.5 mm, reflecting the fact that there were substantial numbers of large (>75 mm) oysters at that time (1984 to 1986). The data on density and size, however, compare well with studies on intertidal oyster reefs in other areas in Florida (Grizzle 1990, Tolley & Volety 2005, Grizzle et al. 2006, Volety et al. 2008, Parker et al. 2013, Milbrandt et al. 2015). Thus, the intertidal reefs in Apalachicola Bay may typically differ in size structure from presentday subtidal reefs. In any case, much more research would be needed to determine how the intertidal oyster populations compare with the subtidal populations with respect to the overall ecology of the bay as well as how they might be related ecologically to the subtidal reefs.

The present study found wide differences in intertidal oyster densities in different regions of the bay (Table 1), which has been reported in previous research on the bay's subtidal oysters (Berrigan 1988, Livingston et al. 2000, Edmiston 2008), including recent studies before and after the 2012 fishery collapse. For example, Livingston et al. (2000) produced maps of oyster mortality that illustrated how river flow and salinity variations were related to mortality patterns across the bay during 1985 and 1986. Under moderate river flows, oyster mortality was reduced throughout the central portions of the bay. Under low-flow conditions, the overall area of low mortality in the central bay decreased. This was hypothesized to result from predators moving further into the bay with the more saline waters from both ends and the two barrier island inlets in the central bay. Wang et al. (2008) used a coupled modeling approach and focused on oyster growth instead of oyster mortality. Their field validation sampling of oyster beds only included four sites and did not include the extreme western or eastern portions of the bay. Although their findings were consistent with previous studies indicating that salinity has a major effect on oyster growth, Wang et al., provide brief cautionary discussion (pp. 85-86) of the complex relationship between oyster growth and salinity. The converse situation--high river flows such as during a hurricane--can result in essentially the opposite result with respect to mortality spatial patterns if salinities are depressed below tolerance levels of the oyster (Shumway 1996, Edmiston et al. 2008). The impacts of storms are, however, more complicated because storm-related factors other than salinity can cause high oyster mortality. For example, a hurricane in 1985 produced extreme tides, strong winds, heavy rainfall, and high river discharges that in combination resulted in substantial oyster mortalities (Berrigan 1988, 1990). Oyster production in most areas of the bay, except the eastern end, dropped by ~90% resulting in closures to harvest, but rebounds in growth and recruitment quickly followed in some areas of the Bay. Edmiston et al. (2008) reviewed the literature on the impacts of subsequent storms on oysters in the bay, emphasizing that the effects of sporadic events such as hurricanes can vary widely in the bay and involve multiple mortality factors, and their effects are not easy to predict. In summary, it seems reasonable to expect wide spatial variations in both intertidal and subtidal oyster reef metrics.

More recently and after the 2012 fishery collapse, Allen et al. (2013) described preliminary results from spatial models that included a range of water and oyster management options on oyster production and harvest. Camp et al. (2015) and Pine et al. (2015) explored the relationship between ecological and social issues involved in the recent collapse of the fishery. Their findings overall underscored the complex nature of causal factors in the dynamics of a heavily harvested species such as the oyster, and the uncertainties involved in its future. Fisch and Pine (2016) assessed the role that river discharges potentially play in long-term dynamics of oyster harvest from the Bay, confirming the importance of freshwater discharges to the ecology, production, and human harvest of oysters but also underscoring the complex nature of the relationship. Kimbro et al. (2017) demonstrated the potential importance of predation as related to freshwater discharges to the Bay in oyster population dynamics. In summary, recent research has provided new perspectives on the temporal and spatial dynamics of oyster populations in the bay, but a quantitative and predictive understanding is still lacking. The present study provides a quantitative dataset on the intertidal reefs that can be used to assess future changes, and potentially how the intertidal populations might be related to oysters in subtidal waters.

Management Implications

The first monitoring recommendation in Havens et al. (2013, p. 4) stated: "The fisheries independent monitoring program needs to be expanded in its spatial extent to include all of the bay where oyster bars occur, including areas that are closed to fishing, because these may represent important sources of oyster spat." To our knowledge, the data herein represent the first attempt at determining the spatial extent and condition of the bay's intertidal reefs. Perhaps the most important management-related conclusion to be drawn from the data on reef condition is that the intertidal reefs showed the same spatial pattern in condition as recent previous research on the subtidal reefs which found most oysters were dead in the western bay (St. Vincent Sound area), and live oyster densities and size frequencies in other areas of the bay were typical of healthy intertidal reefs in other estuaries in Florida (Kimbro 2013, Grizzle et al. 2017, FWC unpublished data). In summary, these data suggest that a widespread die-off involving all size classes and both intertidal and subtidal reefs occurred within the past few years. Thus, the intertidal data point to the lack of knowledge overall for the bay's oyster populations, and the next steps needed, particularly in the context of the 2012 fishery collapse (Havens et al. 2013, Camp et al. 2015, Pine et al. 2015, Fisch & Pine 2016, Kimbro et al. 2017).

As discussed in detail previously, the maps produced by the present study indicate that areal coverage by intertidal reefs in the bay is probably only a small portion of the areal coverage by subtidal reefs. The subtidal reefs, however, have not been comprehensively mapped since the mid-2000s (Twichell et al. 2007). Moreover, an extensive sampling effort by FWC in 2016 indicated that only 66 of 161 sampling stations on the mapped subtidal reefs had oysters present. Most of the "non-oyster" stations consisted of mud or sand sediments, suggesting that perhaps most of the previously mapped subtidal reefs are now dead and even lacking in oyster shell. The FWC data are still being analyzed, but overall their data show that live oyster densities on the subtidal reefs averaged only 17 oysters/[m.sup.2], less than a fourth of the average density on the intertidal reefs in the central and eastern regions of the bay (Table 1). These comparative data strongly suggest that the intertidal reefs may be in a better condition than the subtidal reefs, at least in most areas of the bay. But many of the reefs in the bay regardless of tidal elevation are not in a good condition, and understanding the factors involved in the recent die-offs is far from complete. As already discussed, the relationship between oysters and environmental conditions in the Apalachicola Bay is complicated and has been assessed from a variety of ecological, historical, and management perspectives. The ongoing studies described in Havens et al. (2013) are yielding new information relevant to future management actions but do not include a comprehensive mapping of the bay's subtidal reefs. Better knowledge of the spatial extent and condition of the subtidal oyster reefs in the bay is badly needed [Allen et al. 2013 (p. 19), Pine et al. 2015], and could be combined with the new information provided by the present study to yield comprehensive information on the spatial extent and condition of the bay's oyster resources.

The present study found reefs in several areas with "dead margins," which are accumulations of dead shells typically mounded up along one margin (Fig. 2). In extreme cases where only mounds of dead shells occur, these formations are called shell "rakes" which are a common feature along shorelines exposed to wind-generated waves and boat wakes (Grizzle et al. 2002, Wall et al. 2005, Coen & Grizzle 2007, Garvis et al. 2015). To our knowledge, the occurrence of rakes or dead margins has not been reported in the Apalachicola Bay. Although the present study did not quantify the dead margins, their extent in some areas (e.g., see Fig. 2) suggests that additional studies aimed at determining their distribution and potential causes are warranted.

Another mapping-related topic that is relevant to an important ongoing management issue is the siting of restoration (shelling) efforts. How should the locations of restoration sites be determined? The current restoration efforts coordinated by the Department of Agriculture and Consumer Services in the Apalachicola Bay focus on adding new hard substrate (mainly fossil oyster shell) to areas that have historically been productive oyster bottoms (FDACS 2015). This process has been demonstrated in many areas, including the Apalachicola Bay (Berrigan 1988, 1990), to be an effective method for increasing oyster abundance because it increases the amount of hard substrate available for settlement of oyster larvae from wild adult oysters in the system. But there can be widely variable results in restoration success, suggesting that reefs that were productive historically might not be today. The ongoing FWC research on shelling rates at three experimental sites is providing important information on the volumes of shell per unit bottom area that result in best reef development, but the initial findings indicated wide variability (regardless of shelling rate) in recruitment and reef development at the three study sites (Grizzle et al. 2017). Thus, site location can be critical in determining restoration success. Recent research in New Hampshire involving three reefs and 2 y of sampling showed that recruitment rates were negligible at distances greater than 500 m from each study reef (which consisted of moderate densities of live adult oysters), suggesting that restoration sites should be located as close as possible to a healthy population of adult oysters (Eckert 2016). Much more research is needed to better understand what these findings mean for restoration practices in other areas, but they do suggest that the spatial scales involved may be much smaller than previously thought. In light of the wide spatial variability in various oyster metrics on both subtidal and intertidal reefs indicated by essentially all recent research in the Apalachicola Bay, it is suggested that the next steps for the bay should include more extensive and hypothesis-driven research on spatial patterns. For example, data from the FWC 2016 baywide sampling project could be supplemented with additional sampling involving NRDA sites designed to assess restoration success with respect to location and distance from healthy natural reefs. Such knowledge might be used to assess restoration success of recent efforts in the bay with the aim of improving the process for choosing future restoration sites.

Present research and the history (~100 y) of oyster dynamics in the Apalachicola Bay might also be viewed through the lens of much longer-term geological processes that are sometimes not explicitly considered in management actions. The studies by Twichell et al. (2010) indicate that the present-day oyster reefs (mainly the subtidal reefs) in the bay began to develop on the crests of broad, flat sand bars ~2,400 BP, most of which were oriented perpendicular to the long axis of the Bay. The subtidal reefs today reflect changes in the original spatial patterns resulting from more than two millennia of responses to changes in sea level, water quality conditions, sediment inputs from both freshwater and marine sources, and more recently by human harvest practices. In brief, their core and seismic profile data indicated that oyster reefs were more extensive historically and have decreased at their edges due to fine sediment inputs from the Apalachicola River. The early reefs grew vertically and migrated westward, suggesting a net westward transport of sediments in the bay. This simple model of reef development might be incorporated into future management efforts aimed at ameliorating the long-term effects of climate change and sea level rise. For example, if it is assumed that reef development and expansion is more likely along the western margins of most reefs, then restoration efforts could be focused in these areas on each restored reef when designing restoration projects on historical (but currently degraded) oyster reefs. In any case, assessment of this long-term spatial component should be considered in future research.

Finally, very little research has dealt with the substantial ecosystem services the bay's oyster reefs (intertidal and subtidal) provide (Coen & Grizzle 2007, Grabowski & Peterson 2007). In addition to oyster landings, the 2012 fishery collapse in the bay also resulted in a loss of some portion of the ecosystem services oyster reefs provided. The collapse thus had ecological as well as economic and social effects. For example, in their assessment of long-term changes in water filtration by oyster reefs in 13 estuaries in North America, zu Ermgassen et al. (2013) found that only Apalachicola Bay showed an increase. But their assessment was based on 1990 to 2010 data when live oyster densities were much higher than post-2012 (see Table I in zu Ermgassen et al. 2012). It seems reasonable to assume that other ecosystem services provided by the bay's oyster reefs also have been diminished since 2012.

Assessment of Satellite Imagery for Routine Monitoring

The final objective of the present study was to assess the potential of high-resolution satellite imagery for routine mapping and monitoring of intertidal oyster reefs. In this respect, the present study complements the ongoing Oyster Integrated Mapping and Monitoring Program of the Florida Fish and Wildlife Conservation Commission that seeks to foster state-wide communication and other goals among practitioners involved in oyster reef (and other coastal habitats) mapping ( The management needs of a variety of stakeholders interested in the oyster resources of the Apalachicola Bay and the region center around better knowledge of the spatial dimensions and condition of oyster reefs, and better methods for monitoring these reefs. Thus, although the present study focused on Apalachicola Bay, the results are relevant to other state and regional management efforts.

The present study achieved 77% overall thematic accuracy in mapping the intertidal reefs in the bay based on 2013 and 2015 imagery and 2016 field sampling (ground-truthing) data, thus demonstrating that high-resolution (<1 m) satellite imagery can be used to accurately identify (using manual interpretation) and map intertidal oyster reefs. In addition, the comparison of quadrat data on live oyster density and shell weight with three classes of reef color in the imagery demonstrated that important reef condition metrics can be discerned directly from the imagery (Figs. 5 and 6). These findings warrant discussion in several respects relevant to assessing how effective satellite imagery might be for general use in reef monitoring.

Perhaps foremost, the availability and cost of appropriate imagery needs to be considered. Submeter resolution imagery is now widely available from various providers (e.g., Harris Geospatial Solutions, Landinfo) including freely available online sources such as ArcGIS Online, Google Earth, Bing Maps, and others (Green et al. 2017). Each provider offers a variety of imagery types covering a range of wavelengths and tools for working with the imagery. The major point here is that digital satellite imagery is now comparable in many ways to low-altitude aerial imagery, and its availability is widespread and economical. Perhaps the most important limitation today is the temporal resolution of satellite imagery; users have no control over when the imagery becomes available, how frequently imagery is obtained, nor the conditions (e.g., tide stage) under which it is obtained. Nonetheless, commercial suppliers can greatly facilitate the task of finding acceptable imagery.

Another consideration is image interpretation methods. The polygons around the reefs were manually drawn and the imagery visually interpreted, as discussed in the Materials and Methods section and by Grizzle et al. (2015). Although manual interpretation is probably the most-used method for aerial and satellite imagery in general, a variety of automated and semiautomated approaches have been developed; Green et al. (2017) provide a comprehensive and recent general review. The relevant literature on intertidal oyster reefs, however, is limited (Schill et al. 2006, Le Bris et al. 2016). In sum, this research has demonstrated limited success for automated image processing methods, but this may simply be the result of limited research for oyster reefs.

A final topic to consider here concerns how much information on reef condition can be inferred from satellite imagery. Can we count oysters from space? The short answer is yes, but the accuracy of the counts may not be acceptable--at least for now. The present study demonstrated a kind of "low-medium-high" level of accuracy based on field density measurements (quadrat counts). Although the imagery with respect to additional characteristics was not fully assessed, differences in texture and subtle differences in color were easily discerned visually. This indicates that much finer assessments than the present study achieved are possible. The pace at which the quality and spatial resolution of satellite imagery has been improving is remarkable, and it will likely continue to get better (Green et al. 2017). It is suggested that the most immediate need is more research on inferring reef condition directly from the imagery. This research should include assessments of different kinds of imagery and different geographic areas under different environmental conditions (e.g., tide stage and water clarity), and should involve GPS units with submeter spatial accuracy for describing the locations of reference sampling of the reefs. High-resolution satellite imagery is a powerful tool that has yet to be explored for routine monitoring and assessment of intertidal oyster reefs.


This study was funded by the Florida State Wildlife Grants program. Jenna Harper and Rebecca Bernard with the Apalachicola National Estuarine Research Reserve (ANERR) assisted in planning and implementation of the project. Support was also received from the University of New Hampshire and The Nature Conservancy. We thank Josh Hobson with the St. George Island State Park for facilitating our work in the Park. Finally, Ethan Borque with ANERR graciously ferried us from reef to reef by boat, assisted in the field work, and provided us with helpful information and references on previous research in the bay. We are very grateful for his help.


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(1) Jackson Estuarine Laboratory, University of New Hampshire, 85 Adams Point Road, Durham, NH 03824; (2) The Nature Conservancy, 2500 Maitland Center Parkway, Ste. 311, Maitland, FL 32751

(*) Corresponding author. E-mail:

DOI: 10.2983/035.037.0514
TABLE 1. Summary of means for univariate metrics on reef
characteristics derived from field sampling.

Area       Live oyster                           Live oyster
(W, C, E)  density (#/0.1 [m.sup.2])  SE     n   shell height (mm)

W           3.4                        1.09  48  26.5
C          42.9                        7.39  12  22.4
E          99.3                       13.22  30  21.6

Area                 All shell weight
(W, C, E)  SE    n   (kg/0.1 [m.sup.2])  SE    n

W          3.50  22  1.7                 0.12  34
C          2.55  12  1.4                 0.21  12
E          1.18  26  1.6                 0.20  24

See Figure 1 for three geographic areas (W = west, C = central, E =
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Author:Grizzle, Raymond; Ward, Krystin; Geselbracht, Laura; Birch, Anne
Publication:Journal of Shellfish Research
Article Type:Report
Geographic Code:1U5FL
Date:Dec 1, 2018

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