Joan A. Browder
The FIAN is designed to support the four broad objectives of MAP: (1) to establish a pre-CERP reference state, including variability, for each of the performance measures; (2) to determine the status and trends in the performance measures; (3) to detect unexpected responses of the ecosystem to changes in stressors resulting from CERP activities; and (4) to support scientific investigations designed to increase ecosystem understanding, cause-and-effect, and interpretation of unanticipated results.
FIAN is a regional scale monitoring program of seagrass-associated fish and invertebrate (penaeid and caridean shrimp and crabs) communities present in shallow waters of South Florida; the pink shrimp, Farfantepenaeus duorarum, as a restoration indicator, is a species of special interest. FIAN provides input to the pink shrimp performance measure. The pink shrimp emerged as an ecosystem attribute to be monitored from the Florida and Biscayne Bay conceptual ecological models.
A 1-m2 throw-trap is the basic gear used to sample fauna in FIAN. Associated with each throw-trap animal sample are measurements of seagrass/algae habitat, water depth, sediment depth and surface temperature, salinity and turbidity. Twice annually, a randomly located throw-trap sample is collected in each cell of a 30-cell grid at each of the 19 monitoring locations at the end of the dry season (April/May) and the wet season (September/October).
The data developed in FIAN will be used to evaluate the success of CERP by contributing to the assessment of the estuarine response to restoration-related modifications to upstream hydrology in the freshwater Everglades. At present, FIAN provides input to the pink shrimp performance measure. The pink shrimp emerged as an ecosystem attribute to be monitored from the Florida and Biscayne Bay conceptual ecological models. More generally these data will be used to relate seagrass-associated faunal communities to habitat and environmental conditions in subtropical seagrass communities.
The close coupling of FIAN with seagrass monitoring recognizes the importance of shallow seagrass systems to the function of coastal waters and their vulnerability to anthropogenic change. Estuaries downstream from CERP projects will be affected by changes in the quantity, timing, and distribution of freshwater inflows; associated changes in estuarine salinity regimes and subsequent, long-term, changes in benthic vegetation are anticipated.
40001 State Road 9336
Transl. rev and ed. by C. D. Fuller and H. S. Conrad
The full text is available online.
Durako, M. J.; Hall, M. O.; Hefty, L. N.
Ellerberg, H.
DiDomenico, W. J.; King, L. E.
Littler, M. M.; Bucher, K. E.; Norris, J. N.
Camp, D. K.; Angel, M. V.; Bousfield, E. L.; Brunel, P.; Brusca, R. C.; Cadien, D.; Cohen, A. C.; Conlan, K.; Eldredge, L. G.; Felder, D. L.; Goy, J. W,; Haney, T.; Hann, B.; Heard, R. W.; Hendrycks, E. A.; Hobbs III, H. H.; Holsinger, J. R.; Kensley, B.; Laubitz, D. R.; LeCroy, S. E.; Lemaitre, R.; Maddocks, R. F.; Martin, J. W.; Mikkelsen, P.; Nelson, E.; Newman, W. A.; Overstreet, R. M.; Poly, W. J.; Price, W. W.; Reid, J. W.; Robertson, A.; Rogers, D. C.; Ross, A.; Scotte, M.; Schram, F. R. Shih, C-T; Watling, L.; Wilson, G. D. F.; Turgeon, D. D.
Crossmen, E. J.; Espinosa-Perez, H.; Findley, L. T.; Gilbert, C. R.; Lea, R. N.; Williams, J. D.
Brown, J. A.
Jacobson, L. D.; Squire, J. L.
The full article is available via journal subscription or single article purchase. The abstract may be viewed on the website below
2. The number on Braun-Blanquet replicates from a throw-trap sampling site was increased from 3 to 6 effective with the Spring 2007 collections (collect_num 5).
3. Effective with the Spring07 collection 3 variables were added to the Braun-Blanquet sampling method: GRASStotal, ALGAEtotal and VEGtotal.
Spatial data (i.e. sample positions) are plotted in ArcGIS vs the initial sample location (from random sample station table) and compared. Visual discrepancies are evaluated and corrected in each case.
Location data (latitude and longitude) recorded in the field are entered into ArcGis and visually compared with the initial, randomly generated, sample locations. Discrepancies are evaluated on a case by case basis. In the case where no explanation for differences is apparent the initial sampling point is assigned. In FIAN to date the point sampled has differed from the specified random sampling point by about 15 m on average.
A single randomly located 1-m2 throw-trap sample is collected from within each cell of each monitoring location’s 30-cell grid. Thirty samples from each of the 19 locations within the network constitute a collection, 570 samples in total. This sampling design results in samples being doubly randomized (grid is randomly fitted and sample is randomly located) and quasi-evenly distributed across the gradients of habitat and environmental conditions present at the monitoring location.
Each monitoring location is sampled twice each year during April/May (end of dry season) and September/October (end of wet season).
Field methods
The 1-m square throw-trap is used to collect discrete, quantitative samples of organisms that are associated with benthic vegetation or that seek shelter in benthic vegetation when disturbed (Robblee et al 1991). The throw-trap, as used in FIAN, is an open ended 1-m square aluminum box, 45-cm deep, with panels of weighted nylon netting (0.16-mm stretch mesh DELTA netting) attached on parallel edges at the top of the trap. Each panel of netting is large enough to cover the top of the throw-trap. Random sampling locations in each cell were determined using ArcGIS 9 (v 9.2). Once the anchored boat has settled into the wind the throw-trap is thrown into undisturbed water off the rear of the boat where it drops to the bottom and is immediately covered if in water deeper than 45cm. The throw-trap is covered between each pass of the sweep net when under water. Once the trap is in place, it is cleared of animals with separate passes with a 1-m-wide framed sweep net of mesh size similar to the panels. SCUBA equipment (surface-supplied hookah) is used to sample the throw-trap in water deeper than about 0.75 m. Preliminary sampling established that 5 passes of the sweep net would remove about 95% of the fish, caridean shrimp and pink shrimp in the throw-trap and would constitute a sample. Crabs were sampled less efficiently (approx. 60%). The material collected in each pass is washed over a 1-mm sieve in the boat, labeled and secured in a net bag with mesh size similar to the panels, and held on ice until preserved in 10% formalin at the dock. For the Spring-2005 collection, material from separate passes of the sweep net through the throw-trap were combined as a single sample and washed over a 1-mm sieve in the boat. Beginning with the Fall-2005 collection, material from each pass was processed separately; therefore, the data from one throw-trap sample consists of a series of 5 consecutive removal counts for the species collected in the trap.
Five random sampling points (latitude, longitude) in each cell were determined using ArcGIS 9 (v 9.2) in preparation for each seasonal collection. The first point of the five points in each cell was sampled unless the boat could not reach that point or seagrass and/or benthic algae were not found in the vicinity. Each of the five sample points were visited in order and the first point of the five was sampled when benthic vegetation was present and the boat could reach it. The fifth sampling point was sampled regardless of the presence of benthic vegetation or in the event that the boat was unable to reach the point, a sample was collected as near to the fifth specified sampling point as possible. The actual latitude/longitude where each sample was collected was recorded.
Associated with each throw-trap sample are date, time and location, surface and bottom salinity and temperature, turbidity, water depth, and sediment depth are estimated at each sample station.
Seagrass and algae present at a throw-trap sampling site are quantified using two methods: visually with a modified Braun-Blanquet cover-abundance method (Braun-Blanquet 1932; Mueller-Dombois and Ellenberg 1974; Fourqurean et al. 2001) and with a harvest-density method (Robblee et al 1991). Both methods provide estimates of seagrass/algae canopy height and species composition. The Braun-Blanquet method also includes a qualitative estimate of sediment texture. The harvest-density sampling was stopped after the Fall 2007 collection.
The Braun-Blanquet method involves visually quantifying the cover and abundance of seagrass and algae observed in a 0.25-m2 quadrat. This method is used in MAP seagrass monitoring in FHAP-SF. In FIAN six replicates are collected with each throw-trap sample; five are located in a semi-circle around the throw-trap (from the right to the left side of the boat, approx. 5-m radius); the sixth quadrat is located outside and immediately adjacent to one side of the throw-trap. Habitat in the throw-trap can not be directly sampled because doing so prior to removing animals from the trap might allow animals to escape while the habitat is altered following the removal of animals. This semi-quantitative method requires relatively little time per quadrat (10-15 minutes for 6 replicates). For a particular sample quadrat, the investigator first lists all the species or plant groupings that are observed. The cover-abundance rating is then assigned for each taxa using the following ordinal scale:
0.1 = individual, 0.5 = sparse, 1 = 0-5%, 2 = 5-25%, 3 = 25-50%, 4 = 50-75%, and 5 = 75-100%.
The upper four scale values (2, 3, 4 and 5) refer only to cover while the lower three scale values are essentially estimates of abundance, i.e. number of individuals per species. At present the raw data are converted to estimates of frequency of occurrence and averageor median cover. Averaging ordinal scale data provides an estimate of cover at the sample station but averages or medians cannot be back-converted to Braun-Blanquet scores.. In addition to cover-abundance estimates, maximum canopy height is measured and a qualitative estimate of sediment texture based on feel is made within each quadrat; M = mud, SM = sand/mud, MS = mud/sand, S = sand, CS = coarse shell, R = rubble, HH = halimeda hash, combinations of these, etc. Initially, three replicate quadrats were used to characterize habitat at a sample station. Replication was increased to six quadrats beginning with the Spring-2007 collection. Further, estimates of cover-abundance for 3 plant groupings, all-vegetation, all-seagrass, and all-algae were added with the Spring-2007 collection. Since Braun-Blanquet cover-abundance estimates are not additive, these broad plant groupings provide an estimate of overall habitat and are comparable to the aggregated estimates of seagrass standing crop and algal biomass.
The harvest method involves dropping a single 10-cm square wire quadrat adjacent to one outside corner of the throw-trap. The vegetation within the quadrat is removed, washed free of sediment, and separated to species and litter (dead seagrass material). Seagrass short shoots and blades are counted and enumerated by species. Randomly, up to five short shoots, blades intact, are selected from each seagrass species present, from which blade length is estimated; blade width is only measured for Thalassia. Seagrass standing crop is measured by drying all blades, flowers, and seeds for 24 hrs at 100 deg C after acid washing to remove calcareous epiphytes. Algal biomass (not acid washed) is also determined by drying for 24 hrs at 100 degC; rhizoidal mass often associated with calcareous algae is removed. For the Spring-2007 collection the 10-cm square quadrat was placed within the Braun-Blanquet quadrat located adjacent to the throw-trap facilitating a direct comparison of methods. Harvest samples were discontinued following the Fall-2007 collection.
Laboratory methods
Processing begins with the sample being separated from the 10% formalin by decanting over a 1-mm sieve; sample material is washed free of residual formalin with freshwater. Waste 10% formalin solution is reused until diluted and than disposed of as required by law as a non-hazardous material. All fish, caridean and penaeid shrimp, and crabs are removed from each sample manually in the laboratory. Where possible animals are identified to species and then counted and measured as appropriate. Fish, crabs and the penaeid shrimp are sized, standard length (SL), carapace width (CW), and carapace length (CL), respectively. The gender of each pink shrimp is determined as male, female, unknown. Caridean shrimp are not sized but the number, by species, with eggs (gravid) is recorded. A voucher collection of all species identified is maintained in the laboratory for reference at Nova Southeastern University/Oceanographic Center.
Instrumentation
Surface and bottom salinity and temperature are measured in the field using a hand-held WTW 330i Conductivity Field Meter (or equivalent, 315i). Salinity is measured (automatic temperature corrected) from 0 to 70 psu and temperature is measured from -5 to 99.9 deg C. An ATAGO automatic temperature (10-30 deg C) compensating refractometer, model ATC S. Mill-E, with a salinity range of 1 to 100 psu (1-psu resolution) is used as a field backup to the conductivity meter to measure salinity. A hand held thermometer (1-deg C increments) is used as a field backup to measure temperature. Turbidity is estimated from a sample collected from undisturbed water between the surface and approximately 10-cm depth. Samples are held on ice in the field and cooled in a refrigerator in the laboratory until turbidity is measured. An HF Scientific DRT-15CE portable turbidimeter measuring NTU over three selectable ranges, 0-10, 0-100, 0-1000 NTU, is used to measure turbidity. Laboratory analysis occurs within 24 hrs of sample collection. Water depth at the time of collection is estimated to the nearest centimeter using a 3-m PVC pole with 1-cm gradations. Sediment depth at the throw-trap site is measured by probing with a 1.2-cm (½ inch) diameter 3-m long rod graded in 1-cm increments. A Garmin GPSMAP492 GPS is used to estimate the location of the throw-trap sample.
QA/QC Methods
a. Field/laboratory - In the field each sweep (n=5) from each sample (n=30) collected at each monitoring location (n=19) is maintained separately in mesh bags; material is placed over ice initially and then preserved in 10% formalin at the dock. Storing on ice lessens the shock to the organism, especially for shrimp and crabs, of entering formalin. Fewer detached appendages result but is still a problen. Legs are important for identification purposes especially the identification of crabs.
All field data collected from each cell of the 30 cells constituting a monitoring location (environmental data, location, and Braun-Blanquet habitat data) are recorded on data sheets in the field. Each sheet is checked for accuracy and completeness by a second person. In the laboratory field sheets are gathered into notebooks by cell for each monitoring location. Subsequent lab sheets enumerating harvest data (species, seagrass blade lengths and widths, etc) animals collected (species, sizes, gender, etc, as appropriate), are included in the notebook as completed by cell and monitoring location.
Prior to processing in the laboratory sample material and 10% formalin are separated by decanting over a 1-mm sieve; sample material is washed free of residual formalin with freshwater. Waste 10% formalin solution is recycled and then disposed of as required by law as a non-hazardous material.
All fish, caridean and penaeid shrimps and crabs are removed from each washed sweep sample manually in the laboratory. To provide a check on our sorting an approximate 10% subsample of sorted material is sorted by a second individual. If necessary the sample is sorted again. Where possible animals are identified to species and then counted and measured as appropriate. A voucher collection of all species identified from the project is maintained in the laboratory for reference. New species to this collection as appropriate and they are confirmed by a subject area expert. After samples are processed, the animals are placed in 70% alcohol and stored, by collection, at the Dan Beard Center at Everglades National Park.
b. Instrumentation - Conductivity/salinity instruments are calibrated before each field day. In the field the probe is washed with freshwater before each use. In the field turbidity samples are collected and stored on ice. Each evening the days samples are processed; the turbidimeter is calibrated prior to processing samples and turbidities are determined in comparison to sealed standards.
Data synthesis
All data sheets are scanned and data transcribed into Excel data files. Six Excel files, containing multiple sheets as appropriate, contain cumulative project data starting with the Spring 2005 collection and to date through the Fall 2007 collection. Multiple sheets include raw data (by replicate or by sweep) and summary statistic (by cell). The latter includes total for fish and invertebrate data; average, median or frequency for Braun-Blanquet data and average blade length, width, etc for seagrass metric data.
Data files include: Braun-Blanquet cover/abundance data, FIAN_BB_Data s05_f09.xls; seagrass metric data, FIAN_Blade_Data s05_f07.xls; invertebrate data, FIAN_Crustacean_Data s05_f09.xls; fish data, FIAN_Fish_Data s05_f09.xls; animal size data, FIAN_Size_Data s05_s09.xls; seagrass harvest data, FIAN_Standing_Crop_Data s05_s07.xls; and field data, FIAN_Station_Data s05_f09.xls.
All data entered are verified by a second individual. Location data (latitude and longitude) recorded in the field are entered into ArcGis and visually compared with the initial, randomly generated, sample locations. Discrepancies are evaluated on a case by case basis. In the case where no explanation for differences is apparent the initial sampling point is assigned. In FIAN to date the point sampled has differed from the specified random sampling point by about 15 m on average.
Analysis methods
Raw fish and invertebrate data (#’s/sweep, 5 sweeps) are summarized as total/throw-trap by species. Raw Braun-Blanquet data (as many as 6 quads) are summarized as average and frequency of occurrence. Raw seagrass harvest data,prior to drying and weighing, are summarized as average blade length, width, etc by species and leaf area (length x width).
Statistical analyses were conducted using SPSS 15.0 and/or SigmaStat 3.5. Geographical Information Systems analyses and mapping were conducted using ArcGIS 9.2. Primer 6.1.6 was used for conducting community analyses including hierarchical cluster analysis and ANSIM. SigmaPlot 10 was used for graphics.
Throw-Trap Efficiency: In the throw-trap sampling protocol, the number of passes of the sweep net initially was set at five to establish a capture efficiency of about 95% (based on preliminary sampling in April-May 2005 across 19 monitoring locations in FIAN. Meeting this standard helps to ensure comparability between sample sites, collections and studies. The number of passes with the sweep net was determined graphically using a cumulative catch curve and was set at the number of passes required to remove 95% of individuals of 4 taxa, fish, caridean shrimp, pink shrimp, and crabs from the throw-trap.
To evaluate throw-trap efficiency across the FIAN sampling network, removal counts for 5 taxa (fish, penaeid shrimp, caridean shrimp, crabs and the pink shrimp) were totaled by pass (total of pass 1, pass 2, through pass 5) for the 30 throw-trap samples from each sampling location for five collections (from April-May 2005) combined. The resultant removal series were modeled as multinomial distributions to estimate a "true" abundance based on the capture sequence alone (Zippen 1956). Throw-trap efficiency with 95% CI for each taxon was calculated as the percentage of this estimated "true" abundance collected at the sampling location.
Change Detection: Estimates of minimal detectable change in FIAN (smallest percent difference detectable at a = 0.05) were made following Zar (1999) in lieu of power analysis since the sample size was fixed at 30 (df = 29) in order to facilitate linkage with MAP seagrass monitoring (FHAP-SF). A priori a level was set at 0.05 (2-tailed) and power set at 80% (1-ß = 0.20, 1-tailed). The standard error of the mean for each group at each sampling location was used as an estimate of sample variance in the analysis.
Cluster Analysis: Hierarchical cluster analysis was used to identify natural groupings of the 19 FIAN monitoring locations based on the similarities of their respective fish, shrimp and crab assemblages. The species composition on which cluster analyses were based included both fish and crustacean taxa. Initially, abundance data for all taxa were transformed by the fourth root transformation (y0.25; where y = abundance) in order to counteract the weight of the dominant species without extremely reducing their importance. Transformed abundance data for all taxa were than averaged for each monitoring location (n=30) within each collection. Separate cluster analyses were conducted using the Bray-Curtis similarity measure and complete linkage to construct dendrograms for each of the five collections. Clusters separated at about the 50% level were identified for further analysis.
An ANOSIM test (analysis of similarity), a non-parametric permutation procedure, approximates a univariate ANOVA (analysis of variance). ANOSIM analyses were used to determine whether pair-wise site-similarity levels of species composition within defined classes of region were significantly higher than similar levels between classes. The regions were Biscayne Bay, Florida Bay, and southwest coast.
A series of approaches were variously employed to characterize differences in the epibenthic fish and crustacean assemblage among clusters. The rank abundance of species within targeted taxa, fish, shrimp and crabs, was determined. The total number of species and the number of species accounting for 90% of individuals in each cluster was determined. Oneway ANOVA was used to test for differences among clusters in the abundance of four taxa (fish, caridean shrimp, crabs, and the pink shrimp) and in several habitat and environment measures: water depth, total standing crop, maximum canopy height, sediment depth. When these ANOVAs indicated that differences among clusters were present, Tukey’s HSD Test was used to indicate which clusters differed.
Delta-Approach: Surveys often produce data that are highly skewed and contain many zeros. Throw-trap based data is no exception. The proportion of zeros and skewness in the data reflect the density of the target organism or taxa, its underlying distribution (homogeneous to heterogeneous), and possibly other factors (e.g. variable catch ability) and ultimately affects the precision of abundance estimates based on means. Separating zero values from non-zero values in a collection often allows a relatively simple distribution to be fitted to the non-zero data and in some situations leads to more efficient estimators of variance. The case where non-zero values are log-normally distributed is referred to as the delta-distribution (Aitchison and Brown 1957), hence "the delta approach".
The delta approach involves generating two data sets from the original catch data: the proportion of throw-trap samples positive for the target species, referred to as "occurrence", and, the mean abundance of sample positives for the target species, referred to as "concentration". The product of occurrence and concentration is the "delta-density". When the concentration data are appropriately transformed, delta-density is considered to be more representative of the data than a mean density estimate calculated with zero values included (Seber 1982). Separate analysis of the two components, occurrence and concentration, not only results in a more robust estimation and better understanding of the variance associated with each component but also typically reduces variance around the delta-density value (Lo et al. 1992). The two constituents, occurrence and concentration, each alone provide useful ecological insights into faunal variance and are easily compared with baseline conditions in a monitoring context.
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40001 State Road 9336
Braun-Blanquet cover/abundance data, FIAN_BB_Data s05_f09.xls; seagrass metric data, FIAN_Blade_Data s05_f07.xls; invertebrate data, FIAN_Crustacean_Data s05_f09.xls; fish data, FIAN_Fish_Data s05_f09.xls; animal size data, FIAN_Size_Data s05_s09.xls; seagrass harvest data, FIAN_Standing_Crop_Data s05_s07.xls; and field data, FIAN_Station_Data s05_f09.xls.
40001 State Road 9336
The project PI has declined to provide a comprehensive review of the final version of this metadata record. Any questions should be directed to Michael Robblee at mike_robblee@usgs.gov
U.S. Department of the Interior, U.S. Geological Survey
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