Dale E. Gawlik Fred H. Sklar Unknown model This project is a component of the ATLSS program http://sofia.usgs.gov/projects/atlss/wading_birds/ The conceptual model for this study is based on the idea that hydroperiod is a long-term process that primarily influences the abundance, body size, and species composition of the prey community whereas water depth has immediate effects on individual birds by influencing their ability to capture prey. This study seeks to determine through field experiments, the proximate effects of water depth, prey density, prey size, and prey species on wading bird foraging parameters. The species of wading birds examined in this study are those in the ATLSS wading bird model: the Wood Stork, White Ibis, Great Egret, and Great Blue Heron. The recovery of wading bird populations has been identified as a key component of successful Everglades restoration. Proposed causes for the decline in wading bird numbers have in common the notion that current hydropatterns have altered the availability of prey. Indeed, food availability may be the single most important factor limiting populations of wading birds in the Everglades. In the face of conflicting management scenarios, knowing the relative importance of each component of food availability is a precursor to understanding the effects of specific water management regimes on wading birds. Ongoing modeling efforts in south Florida such as the ATLSS program, integrate such information and provide predictive power for future management decisions. Currently, the biggest information gap limiting the wading bird model of ATLSS is foraging success as a function of prey availability. The South Florida Water Management District (SFWMD) is currently conducting a series of experiments aimed at determining the effects of water management on the use of foraging sites by wading birds. Site-use data are available immediately after each experiment and thus allow for quick analyses and write-up. However, also as part of those experiments, we recorded on film, foraging behavior of wading birds at feeding sites with known prey availabilities. This project was completed in 2003 199812 20030802 Observed Complete None planned ponds adjacent to and NW of Arthur R. Marshall Loxahatchee National Wildlife Refuge, Palm Beach County, FL -80.625 -80.125 26.875 26.3 none wading birds ATLSS fish hydrology biology ISO 19115 Topic Category biota environment inlandWaters 002 007 012 Department of Commerce, 1995, Countries, Dependencies, Areas of Special Sovereignty, and Their Principal Administrative Divisions, Federal Information Processing Standard (FIPS) 10-4, Washington, D.C., National Institute of Standards and Technology US United States U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST Florida FL Department of Commerce, 1990, Counties and Equivalent Entities of the United States, Its Possessions, and Associated Areas, FIPS 6-3, Washington, DC, National Institute of Standards and Technology Palm Beach County USGS Geographic Names Information System Loxahatchee National Wildlife Refuge none Greater Lake Okeechobee none multiple species U.S. Department of Agriculture - Agricultural Research Service (ARS) U.S. Department of Agriculture - Natural Resources Conservation Service (NRCS) Department of the Interior - U.S. Geological Survey Department of Commerce - National Oceanic and Atmospheric Administration (NOAA) Environmental Protection Agency (EPA) Smithsonian Institution - National Museum of Natural History (NMNH) 2000 Database Retrieved from the Integrated Taxonomic Information System on-line database, http://www.itis.gov. http://www.itis.gov Ponds were initially stocked with known fish. Wading bird feeding flocks were filmed for 5-45 minutes from a vehicle with a Hi-8 video camera and 8-120 mm zoom lens. Specific species studied are Wood Stork, White Ibis, Great Egret, and Great Blue Heron. unknown All fish an birds are identified to the species level Kingdom Animalia animals Phylum Chordata chordates Subphylum Vertebrata vertebrates Class Aves birds Order Ciconiiformes storks herons ibises American vultures Family Ciconiidae storks Genus Mycteria wood storks Species Mycteria americana Family Ardeidae bitterns egrets herons Genus Casmerodius great egrets Species Ardea alba great egret Genus Ardea great herons Species Ardea herodias great blue heron Family Threskiornithidae ibises spoonbills Genus Eudocimus white ibises scarlet ibises Species Eudocimus albus white ibis Superclass Osteichthyes bony fishes Class Actinopterygii ray-finned fishes spiny rayed fishes Subclass Neopterygii Infraclass Teleostei Superorder Ostariophysi Order Cypriniformes minnows suckers Family Cyprinidae carps minnows Genus Notemigonus golden shiners Species Notemigonus crysoleucas golden shiner Superorder Acanthopterygii Order Perciformes perch-like fishes Suborder Percoidei Family Centrarchidae sunfishes Genus Lepomis common sunfishes eared sunfishes Species Lepomis macrochirus bluegill none These data are subject to change and are not citeable until reviewed and approved for official publication. Dale Gawlik Florida Atlantic University mailing address

Dept. Of Biological Sciences 777 Glades Road

Boca Raton FL 33431-0991 USA 561 297-3333 561 297-2749 dgawlik@fau.edu not applicable not available Field experiments were conducted in a set of 15 0.2-ha ponds directly adjacent to, and NW of, Arthur R. Marshall Loxahatchee National Wildlife Refuge in Palm Beach County, Florida. Three experiments (water depth and fish density, water depth and fish size, water depth and fish species) were conducted between March, 1996 and March 1997 (contact Gawlik for detailed methods for the water depth and fish density experiment). Each experiment began when ponds were stocked with fish and ended when bird-use nearly ceased (a period of approximately 2 weeks). The maximum number of birds present in a day (all ponds pooled) was approximately 280. For the fish density experiment, 2 treatments were assigned randomly among 12 ponds using a 3x2x2 factorial arrangement (water depth: 10 cm, 19 cm, 28 cm; fish density: 3 fish/m2, 10 fish/m2; replicates: 2). For the fish size experiment, 2 treatments were assigned randomly among 12 ponds using a 3x2x2 factorial arrangement (water depth: 19 cm, 28 cm, 37 cm; fish size: 3 cm, 8 cm; replicates: 2). All ponds were stocked at a density of 8 fish/m2. For the fish species experiment, 3 treatments (water depth: 10 cm, 28 cm; fish density: 4 fish/m2, 16 fish/m2; fish species: bluegill, golden shiner; replicates: 2) were assigned randomly among 12 ponds. This 2x2x2x2 arrangement was more complex because the treatment of high fish density and low water was eliminated from the design. For all experiments, ponds were initially stocked at known fish densities; however, those densities decreased quickly as a result of bird predation. Thus, we treated fish density as a continuous variable, which we monitored regularly. We determined fish densities during at least 4 sampling periods based on 1-m2 throw-trap samples (Kushlan 1974). Sampling ceased in individual ponds if no stocked fish were captured in any of the throw-trap samples. Throw-trap samples were distributed evenly within a pond by dividing each pond into 16 10x8 m plots and conducting one throw-trap sample in each plot during each sampling period. A test of sampling efficiency indicated the numbers of fish captured in throw traps represents an average of 55% of the actual fish density in the experimental ponds. All fish density values reported are the number of fish captured in throw traps uncorrected for sampling efficiency. A linear regression model was fitted to the data from each pond such that the response was the number of fish/m2 transformed as y(ln +1). The predicted values were back-transformed to get estimated densities of fish for each pond each day of the experiment with the constraint that no predicted value could be less than zero. The estimated values were used in subsequent analyses of bird foraging success. To measure wading bird foraging responses, we filmed feeding flocksfor 5-45 minutes from a vehicle with a Hi-8 mm video camera and 8-120 mm zoom lens. A pilot study indicated that filming from a parked vehicle with cloth-covered windows disturbed birds less than a portable blind. Selection of a flock to film was based on where the largest group of birds were foraging and whether data were lacking for a given treatment combination. Flocks were allowed several minutes to re-settle and resume feeding before filming was initiated. Filming was concluded if flock size changed by more than 25%. Our aim was to get 15 min of film on each bird (with a minimum time limit of 5 min) and a maximum of 15 birds per species per film session. If too few individuals in a film session met that criterion then the minimum time limit was reduced to 2 min. During feeding activities, birds would sometimes travel to the edge of a pond or leave the pond momentarily. Because of the sloped edge of the pond, water depths in those areas were less than treatment levels. Thus, we excluded from time-activity budgets any period where a bird was at the edge or outside of a pond. This criterion resulted in a further shortening of some time-activity budgets. 200001 Following the field portion of the study, time-activity budgets of focal birds (Altmann 1974) were constructed from videotapes. Tapes were viewed using a Hi-8 VCR connected to a high-resolution video monitor. Data were entered into an Oracle database through a personal computer connected to an interoffice-network. To eliminate the possibility of constructing time-activity budgets on the same individual more than once in a session, we did not use as focal birds, individuals of the focal species that appeared in view after the first focal bird left the screen. However, before a focal bird left the field of view, any new birds that appeared could have been used as focal birds. A foraging bout ended when a focal bird left the field of view, became obscured in a flock, or the film session ended (usually about 15 minutes). Capture rates were calculated as the number of prey consumed divided by the length of time (min) of the time-activity budget. Birds that never consumed a prey item were excluded from the analysis. From each time-activity budget, we calculated mean prey-intake rate as the response variable. Descriptive statistics such as the mean and standard deviation are presented for each bird species at different treatment levels. This is the format most useful for incorporating parameter values into the ATLSS wading bird model (W. Wolff, Univ. of Miami, pers. commun.). For species of which we had adequate data to conduct statistical analyses, we determined the relative effects of the treatment variables on the response variables. Tests were conducted using PROC GLM in SAS version 6.12 for Windowsâ with water depth, fish size, and fish species as class variables and fish density as a continuous variable. We specified an initial full model containing main effects and interactions. Non-significant (p > 0.05) interactions indicated that a model was over-specified and contained more terms than necessary (Littel et al. 1991, Freund and Wilson 1993). In that case, we constructed a subsequent set of reduced models containing the main effects and significant interactions only. 2001 Thus far, only the water depth and fish density experiment has been completely analyzed. The results from the water depth and fish size experiment are nearing completion. Key results include the development and refinement of a conceptual model of wading bird foraging behavior. This model provided the rules for quantifying time-activity budgets for all species, including tactile and visual foragers, under the circumstance encountered during the experiments. We calculated prey-intake rates and their associated variability for 2 prey densities and 3 water depths. These numbers can be used to refine parameter estimates currently in the ATLSS wading bird model. We reported foraging costs (giving-up densities of fish) and their associated variability for each species at 3 depths. Note that fish density estimates and giving-up densities were not corrected for sampling efficiency thus resulting in an underestimate of true density. The adjusted numbers can be used in the ATLSS model because it reflects the lower threshold of fish abundance where wading birds will no longer use the site. 2000 As part of the third experiment, the District (SFWMD) filmed foraging behaviors of wading birds at feeding sites with known fish species, water depths, and fish densities. Current funding levels at the District dictate that the foraging data, which require thousands of hours to extract from the films, will not be available soon enough to be used in the ATLSS wading bird model. This third experiment proposes to examine the effect of fish species, fish density, and water depth. The species of wading birds examined in this study are those in the ATLSS wading bird model: Wood Stork (Mycteria americana), White Ibis (Eudocimus albus), Great Egret (Casmerodius albus) and Great Blue Heron (Ardea herodias). The species of fish being compared are the Bluegill and Golden Shiner, both of which are native to the Everglades. The experimental hypotheses being tested are that fish species, fish density, and water depth, affect wading bird prey-intake rates and capture success. 2002 Dale Gawlik Florida Atlantic University mailing address

Dept. Of Biological Sciences 777 Glades Road

Boca Raton FL 33431-0991 USA 561 297-3333 561 297-2749 dgawlik@fau.edu ponds NW and adjacent to Loxahatchee NWR Dale Gawlik Florida Atlantic University mailing address

Dept. Of Biological Sciences 777 Glades Road

Boca Raton FL 33431-0991 USA 561 297-3333 561 297-2749 dgawlik@fau.edu wading bird foraging parameters No warrantees are implied or explicit for the data Contact Dale Gawlik for information and data from this project. none 20070124 Heather Henkel U.S. Geological Survey mailing and physical address

600 Fourth Street South

St. Petersburg FL 33701 USA 727 803-8747 ext 3028 727 803-2030 sofia-metadata@usgs.gov Content Standard for Digital Geospatial Metadata Part 1: Biological Data Profile FGDC-STD-001.1-1999