Underline all appropriate categories for your submission: Oral; Poster; Oral but will accept Poster; Student Travel Scholarship; Student Presentation Award. Asterisk (*) denotes the person(s) making the presentation. (31 July 2012)

An Airboat Based Survey for Mottled Duck Pair Density Estimation and Visibility Correction Bruce E. Davis,* School of Renewable Natural Resources, Louisiana State University, Baton

Rouge, LA, 70803, USA (bdavis@wlf.la.gov) Frank C. Rohwer, School of Renewable Natural Resources, Louisiana State University, Baton

Rouge, LA, 70803, USA (frohwer@lsu.edu) Larry Reynolds, Louisiana Department of Wildlife and Fisheries, Baton Rouge, LA, 70808,

USA (lreynolds@wlf.la.gov) Mark Otto, U. S. Fish and Wildlife Service, Patuxent Wildlife Research Center, Laurel, MD,

20708, USA (Mark_Otto@fws.gov) Extended Abstract: Mottled ducks (Anas fulvigula) are abundant breeding waterfowl in coastal marshes of Louisiana and Texas. Wetland managers need current information on pair densities of mottled ducks to assess and direct management and conservation activities, but lack unbiased estimates of mottled duck abundance in Gulf Coast marshes during spring. Population indexes could be established for the area using data from transects flown via fixed wing aircraft, but techniques to correct these counts for visibility and attain population estimates have not been attempted. Counts from simple line transects likely provide inaccurate estimates of numbers of animals present during a survey because observers miss substantial numbers of animals while conducting surveys. Helicopter counts can be used to correct visibility bias of fixed wing aircraft surveys for mottled ducks by flying an exhaustive search pattern, but helicopter surveys are costly. We evaluate airboats as a means for correction of fixed wing counts for missed ducks. The number of missed animals predictably increases with distance from the transect line, and the subsequent population estimates can be adjusted to attain unbiased estimates of

population density if the sighting distance from the transect line can be estimated. Our objectives were to 1) estimate densities of indicated breeding pairs in each marsh type using transects completed by airboat, 2) to compare the number of indicated breeding pairs estimated using PROGRAM DISTANCE on airboat transects with the number of indicated breeding pairs detected via helicopter, and 3) to establish visibility correction factors for fixed wing transects using airboat transects. Segments of fixed wing transects were selected for survey via airboat and helicopter 1-2 d after survey from the fixed wing aircraft in southwest Louisiana; portions of 10 and 9 transects were surveyed via both airboat and helicopter in 2009 and 2010, respectively. We sampled portions of these segments via straight line transects from an airboat where we could attain permission for access and water conditions permitted access. A helicopter was flown in a zigzag pattern within 200 meters of transect lines in an attempt to attain a complete count in the 400 meter wide. We used PROGRAM DISTANCE to estimate habitat specific densities of indicated breeding

pairs in each marsh type. We estimated densities of indicated breeding pairs separately for 2009 and 2010. We estimated variances of densities empirically for each habitat type sampled in 2009, but assumed a Poisson distribution of the data in 2010. Pair density estimates produced using distance sampling analysis techniques were highest in fresh marsh habitats. Estimated densities derived from the airboat were directly related to counts produced using a helicopter (Pearson correlation coefficient = 0.96; Fig. 1).

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Figure 1. Scatter plot of indicated breeding pairs derived from distance sampling from an airboat by the number of detections of indicated breeding pairs seen from transect flown in a helicopter. The fixed wing counts explained 38.6% of the variation in the airboat survey (Figure 4.7). We estimated that for each unit increase in fixed wing count data, true total count increased by a factor of 2.525 (± 0.541) and that the intercept of the VCF equation was 3.676 (± 3.152), yielding a VCF equation of: Count = (fixed wing count*2.525) + 3.676 Analysis using PROGRAM DISTANCE allows correction of bias towards increased

detection of objects nearest the transect line. Airboat transects represent a cost effective alternative to using helicopters for establishing visibility correction factors for fixed wing aircraft count data, after correction of airboat transect counts. Airboat operation is considerably cheaper than operation of helicopters. Further, many state and federal wildlife management agencies in the gulf coast region have airboats readily at their disposal, whereas, helicopters typically need to be rented to perform surveys. In our analysis, we treated the corrected airboat counts as a census and calculated a VCF using a regression equation fitted to our corrected counts. The parameter estimate for the slope of this regression had a low standard error and lower and upper 95% confidence limits of 1.42 and 3.63, respectively. The parameter estimate for the intercept of this model had a much wider confidence interval than did the parameter estimate for the slope of the regression with lower and upper 95% confidence limits of -2.74 and 10.10, respectively; error on the intercept of the model would lead to a proportionally greater impact on index values near zero than to larger values. Variation in visibility rates increases variation in VCFs and associated population estimates. Differences in visibility of pairs among different habitat types are possible in these data and may lead to bias in our VCFs, thus caution is warranted in interpretation of these results. Substantial variation in pair densities for each habitat type estimated in our study exists. Reduction of unexplained variation in VCFs among different types of marsh habitats may be possible with increased sample sizes.

Underline all appropriate categories for your submission: Oral; Poster; Oral but will accept Poster; Student Travel Scholarship; Student Presentation Award. Asterisk (*) denotes the person(s) making the presentation. (Date of submission) Distance sampling for divers: Spring and Fall monitoring of diving ducks on the lower Great Lakes Brendan T. Shirkey,* Department of Fisheries and Wildlife, Michigan State University, East

Lansing, MI, 48823 (shirkeyb@msu.edu) Dr. David R. Luukkonen, Michigan DNR Wildlife Division, Rose Lake Research Station, East

Lansing, MI, 48823 (luukkonend@michigan.gov) Dr. Scott R. Winterstein, Department of Fisheries and Wildlife, Michigan State University, East

Lansing, MI, 48823 (winterst@msu.edu)

Extended Abstract: Lake St. Clair, the lower Detroit River, and western Lake Erie have often harbored the highest concentrations of waterfowl in the Great Lakes region and consequently were listed as areas of continental significance by the North American Waterfowl Management Plan (NAWMP 2004). The area is of particular importance to diving ducks including lesser scaup and canvasbacks, which have both been identified by the Upper Mississippi River Great Lakes Region Joint Venture as species of priority (UMRGLJV 2007). The Michigan Division of Natural Resources (MDNR) has conducted multi-species aerial surveys of diving ducks on the U.S. portion of Lake St. Clair dating back to 1983. In 2010, the MDNR expanded the traditionally surveyed area to include all of Lake St. Clair (1149 km2) and portions of western Lake Erie (621 km2 ). Furthermore, with a larger survey area, the MDNR decided to test distance sampling techniques as an alternative to traditional census methods for abundance estimation. The MDNR was also able to secure funding to conduct spring migration monitoring, which could provide important abundance data for species such as lesser

scaup that may ultimately be limited by a lack of quality spring habitat (Anteau and Afton 2008). Methods: We established 26 line transects, 13 on Lake St. Clair and 13 on western Lake Erie in Fall of 2010. All flights were conducted using a DHC-2 DeHaviland Beaver on floats, and the pilots flew at a fixed altitude of 91 m and approximate speed of 150 km/h. We were able to use this target altitude and basic trigonometry to establish 5 distance categories: 0-50, 51-125, 126-225, 226-425, and >425 m respectively. When we encountered a flock of diving ducks, we recorded the appropriate distance category based on the center of the flock, estimated number of birds, and species composition. In addition, all audio recordings were associated with a GPS waypoint allowing us to conduct more detailed distributional analyses. The distance data was analyzed using the software Distance 6.0. Using Distance, we were able to estimate diving duck abundance for individual surveys, and estimate annual duck-use-days for canvasbacks, scaup, and redheads during spring and fall migrations.

Results: We completed 5 surveys during Fall 2010, Spring 2011, Fall 2011 and Spring 2012 for a total of 20 surveys. In addition to distance from line transects, detection probabilities of diving ducks were most influenced by flock size. Consequently, the half normal key function with flock size included a covariate was most consistently the top-rated model for both our individual surveys and analyses with data pooled for multiple surveys. Model fit improved significantly during later migration periods, and we hypothesize improved model fit was largely a function of using a consistent set of observers, all of whom were gaining experience with distance sampling protocols. Our peak abundance estimate for Lake St. Clair and western Lake Erie occurred on 15 November 2011 with an estimated 468,129 diving ducks. Generally, abundances were much higher in Fall (often exceeding 300,000 birds) as compared to Spring abundances. Pooled analyses suggested scaup most heavily used the study area, which is unsurprising since they were frequently seen on both lakes as opposed to canvasbacks and redheads that were mostly restricted to Lake St. Clair. Peak seasonal use by all 3 species occurred in Fall 2011 with an estimated 3 million canvasback-use-days, 6.2 million scaup-use-days, and 3 million redhead-use days. Management Implications: We believe distance sampling is a viable option for monitoring of diving ducks or other open water species and may offer an improved alternative to more traditional census or fixed width techniques, especially when the target study area is large or survey conditions are variable (i.e. varying sunlight and wind conditions). We do not believe we are in major violation of the 3 key distance sampling assumptions: 1) detection on the transect line is 1.0, 2) no responsive movement prior to detection, and 3) accurate distance

measurements, and future surveys will allow us to continually evaluate our ability to meet these 3 assumptions Fundamental to our current methodology is observer’s ability to accurately determine flock size since flock size is included as a covariate in the detection model. We recommend extensive observer training (e.g., with the wildlife software Counts; Hodges 1993) and a one year pilot study for anyone interested in adopting distance sampling techniques. Ultimately, we hope this work establishes a foundation for a long-term, consistently collected data set that can be used for UMRGLJV and MDNR conservation planning that will ensure continued harvest opportunities for diving duck enthusiasts in the lower Great Lakes. Literature Cited: Anteau, M. J. and A. D. Afton. 2004. Nutrient reserves of lesser scaup during spring migration in the Mississippi Flyway: a test of the Spring Condition Hypothesis. Auk 121:917-929. Hodges, J. L. 1993. Count- a simulation for learning to estimate wildlife numbers. The Wildlife Society Bulletin 21:96-97. NAWMP 2004. North American Waterfowl Management Plan, Plan Committee, 2004. Implementation Framework; Strengthening the Biological Foundation. Canadian Wildlife Services, U.S. Fish and Wildlife Service, Secretaria de Medio Ambiente y Recursos Naturales, Pp 106. UMRGLJV 2007. Upper Mississippi River and Great Lakes Region Joint Venture Waterfowl Habitat Conservation Strategy, U. S. Fish and Wildlife Service, Fort Snelling, Minnesota, USA.

Underline all appropriate categories for your submission: Oral; Poster; Oral but will accept Poster; Student Travel Scholarship; Student Presentation Award. Asterisk (*) denotes the person(s) making the presentation. (Date of submission) Optimizing Baited Swim-in Trap Efficiency During Pre-Season Duck Banding on Yukon Delta NWR (guideline = ~10 words)

Kyle A. Spragens,* Wildlife Biologist, USFWS, Yukon Delta NWR,

Bethel, AK, 99559 (kyle_spragens@fws.gov) Melissa L. Gabrielson, Wildlife Biologist, USFWS, Yukon Delta NWR,

Bethel, AK, 99559 (melissa_gabrielson@fws.gov)

Extended Abstract: Since 1990, Yukon Delta National Wildlife Refuge (YDNWR) has participated in a pre-season banding of northern pintail (Anas acuta) and mallard (A. platyrhynchos) that was established in collaboration with the Division of Migratory Bird Management (USFWS 1990). American green-winged teal (A. crecca carolinensis) have been considered a secondary target. The fact that little information exists on green-winged teal survival and harvest has justified the continued banding efforts (Trost, pers. comm.). Assessment of harvest distribution and derivation provide baseline data for updating waterfowl management decisions within the Pacific Flyway. Standard capture methodology uses cloverleaf, swim-in traps baited with whole kernel corn (Miller, unpubl. rept.) at 3 traditional trapping sites located in marshy areas along the northwest shoreline of Kgun Lake. Three modifications can be made to improve capture totals, including increased numbers of traps or checks per trap and trap size. However optimizing capture efforts requires

information on the rate at which ducks return to the traps and the ratio of recaptures per capture event. During the 2011 and 2012 field seasons Reconyx trail-cameras were used at each trap to identify potential trap predators and timing of predator presence to help minimize predation event impacts. Additionally, we were able to assess temporal patterns of duck use in relationship to trap-checking schedule efficiency. This presentation will provide results from the remote monitoring of our baited swim-in traps and provide modifications that have been made to the trap checking schedule.

Literature Cited: Miller, H.W. Bait traps, baits, and techniques.

Unpubl. rept. U.S. Fish & Wildl. Serv., Northern Prairie Wild. Res. Ctr., Jamestown, ND.

U.S. Fish & Wildlife Service. 1990. Preseason pintail and mallard banding in Alaska - 1990.

Memo to field stations. Regional Directorate, Refuges and Wildlife, Anchorage, AK.

20 April 1990.

Underline all appropriate categories for your submission: Oral; Poster; Oral but will accept Poster; Student Travel Scholarship; Student Presentation Award. Asterisk (*) denotes the person(s) making the presentation. (July 13, 2012) Application of Light-level Geolocation to Waterfowl Management

Luke C. Hawk,* Cooperative Wildlife Research Laboratory, Center for Ecology, Department of

Zoology, Southern Illinois University Carbondale, Carbondale, IL 62901-6504 (lchawk04@siu.edu)

Michael W. Eichholz, Cooperative Wildlife Research Laboratory, Center for Ecology,

Department of Zoology, Southern Illinois University Carbondale, Carbondale, IL 62901-6504

Joshua D. Stafford,

Assistant Unit Leader, U.S. Geological Survey, South Dakota Cooperative

Fish & Wildlife Research Unit, Department of Wildlife and Sciences, South Dakota State University, Box 2140B, Brookings, SD

Extended Abstract: As capital breeders, waterfowl use nutrient reserves stored during the non-breeding season for egg production and incubation (Krapu 1981). The acquisition and maintenance of these reserves requires that waterfowl have wetland habitats available to them as they transition from wintering to breeding sites (Anteau and Afton 2009). To ensure that habitat is allocated efficiently data must be made available that provides managers with an unbiased estimate of required duck use days for a given region, including stopover duration, distance between stopovers, and population distribution. Light-level geolocators (geolocators) are extremely small and lightweight compared to other tracking methods. While the accuracy of location estimates from a geolocator placed in a set position is relatively high, compared to other less

intrusive methods, the accuracy of estimated locations can be affected by variability in shading regimes that impede the photocells ability to give accurate photoperiod recordings. Light-level geolocation typically has a reported accuracy of ±190 km when used for oceanic foraging seabirds (Phillips et al. 2004). Geolocator use with waterfowl will subject light recordings to a greater diversity of habitat types than seabirds. Each habitat type encountered will have its own unique shading regime and effect on perceived photoperiod (Fig. 1). To evaluate geolocator precision we moved 15 mk18-h geolocators (British Antarctic Survey [BAS], Cambridge, United Kingdom) within and among habitats found in southern Illinois from 27 January – 15 May 2012. Habitats were categorized by the type of overhead cover present including no cover, grassland, and deciduous forest.

Fig. 1 – Location estimates of 3 geolocators (mk18-h, British Antarctic Survey) placed in Jackson County, Illinois during November 2011. Geolocators maintained location estimates for latitude within a range of ~400 km in a single cover type; however, movement between cover types resulted in ranges >600 km (Fig. 2). Also, precision was greatly reduced during 4 week period surrounding the equinox, 6 March – 2 April. Shading from cloud cover also had a significant effect on the precision of latitude estimates that extended to periods several weeks away from the equinox. The longitude estimates are more precise than the latitude estimates and are not affected by the equinox. When geolocators were moved between different cover types the overall range increased from 150 km to 300 km. Our results indicate geolocators will provide adequate location estimates for habitat generalists at only the largest of spatial scales (e.g., flyways and multi-state

regions). Averages from a series of locations can achieve greater accuracy, but this is dependent upon the amount of time an individual spends in an area. The greater precision of longitude estimates may allow data from geolocators to be used to estimate the number of stopovers and stopover duration for an individual; however, this would be dependent upon the shift in longitude evident from a migratory movement compared to an individual’s daily movements between habitats.

Fig. 2 – Latitudinal ranges of estimates (km) from 3 geolocators in Jackson County, Illinois. Literature Cited:

Anteau, M. J. and A. D. Afton. 2009. Lipid reserves of lesser scaup (Aythya affinis) migrating across a large landscape are consistent with the “spring condition” hypothesis. Auk 126:873-883.

Krapu, G. L. 1981. The role of nutrient reserves in mallard reproduction. Auk 98:28-38.

Phillips, R. A., J. R. D. Silk, J. P. Croxall, V.

Afanasyiv, D. R. Briggs. 2004. Accuracy of geolocation estimates for flying seabirds. Marine Ecology Progress Series 266:265-272.

An Analytical Framework for Quantifying Landscape-scale Waterfowl Food Energy and Allocating Habitat Objectives in a Dynamic System: Lessons from the Lower Mississippi Valley Joint Venture John Tirpak,* Lower Mississippi Valley Joint Venture and Gulf Coastal Plains & Ozarks

Landscape Conservation Cooperative, U.S. Fish and Wildlife Service, USGS / National Wetlands Research Center, 700 Cajundome Boulevard, Lafayette, LA 70506 (John_Tirpak@fws.gov)

Luke Naylor,* Arkansas Game and Fish Commission, 2 Natural Resources Drive, Little Rock, AR 72205 (lwnaylor@agfc.state.ar.us)

Dale James, Ducks Unlimited – Southern Region, 193 Business Park Drive, Suite E Ridgeland, MS 391572 (djames@ducks.org)

Tom Edwards, U.S. Fish and Wildlife Service – Division of Migratory Birds, 2312 Quebec Road, Tallulah, LA 71282 (Tom_Edwards@fws.gov)

Blaine Elliott, Lower Mississippi Valley Joint Venture, U.S. Fish and Wildlife Service, 2524 South Frontage Road, Vicksburg, MS 39180 (blaine_elliott@fws.gov)

Dan Fuqua, Tennessee Wildlife Resources Agency, 200 Lowell Thomas Drive Jackson, TN 38301 (Dan.Fuqua@state.tn.us)

Tim Kreher, Kentucky Department of Fish and Wildlife Resources, 10535 Ogden Landing Road, West Kentucky WMA, Kevil, KY 42053 (tim.kreher@ky.gov)

Paul Link, Louisiana Department of Wildlife and Fisheries, 2000 Quail Drive, Room 436, Baton Rouge, LA 70808 (plink@wlf.louisiana.gov)

Frank Nelson, Missouri Department of Conservation, Resource Science Division, Open Rivers/Wetlands Field Station, 3815 E. Jackson, Jackson, MO 63755 (Frank.Nelson@mdc.mo.gov)

Ed Penny, Mississippi Department of Wildlife, Fisheries, and Parks, 1505 Eastover Drive, Jackson, MS 39211 (edp@mdwfp.state.ms.us)

Gary Pogue, U.S. Fish and Wildlife Service, 309 North Church Street, Dyersburg, TN 38024 (Gary_Pogue@fws.gov)

Steve Reagan, U.S. Fish and Wildlife Service, 2970 Bluff Lake Road, Brooksville, MS 39739 (Steve_Reagan@fws.gov)

Ken Reinecke, U.S. Geological Survey, Patuxent Wildlife Research Center, 2524 S Frontage Road, Suite C, Vicksburg, MS 39180-5269 (ken_reinecke@usgs.gov)

Keith McKnight, Lower Mississippi Valley Joint Venture, U.S. Fish and Wildlife Service, 11942 FM 848, Tyler, TX 75707 (steven_mcknight@fws.gov)

Extended Abstract: Established to implement the goals and objectives of the North American Waterfowl Management Plan (NAMWP), the Lower Mississippi Valley Joint Venture (LMVJV) has identified development of landscapes capable of sustaining waterfowl at prescribed levels in the Mississippi Alluvial Valley (MAV) as a high priority. To achieve this goal, the LMVJV relies on coordinated conservation design and delivery strategies that not only reflect the shared vision of individual partners but also are grounded in science and documented in peer-reviewed and peer-refereed publications. For example, Reinecke and Loesch (1996) outlined a process for using mid-winter survey and county harvest data to step down the continental population objectives from the NAWMP to the MAV regional scale and to translate those regional goals to habitat objectives in units of duck energy-days (DEDs). While this derivation of population and habitat objectives is transparent, defensible, and replicable, the allocation of DED objectives among habitat sources is less clear. Although Reinecke et al. (1989) identified the key sources and types of habitats used by waterfowl in the MAV, they provide little guidance on either the distribution and abundance of these habitats on the landscape or the relative reliance that managers should place on each. Thus, the LMVJV relied on expert opinion to provide coarse guidelines on the amount of DEDs that managers should rely on natural flood, private managed, and public managed lands to provide. Because few of the assumptions underlying these decisions were documented, differences of opinion over the specific value and weight to be placed on each of these sources led to disagreement on the best strategies for waterfowl conservation in the MAV. Because these differences threatened to undermine the coordinated habitat delivery

necessary to achieve the NAWMP objectives, the LMVJV spent considerable effort in creating a data-driven framework that provided a transparent and replicable process for allocation of DED objectives within the MAV. In the broadest sense, waterfowl conservation in the LMVJV is driven by the philosophy that management is used to address historical losses in the capacity of the natural system to provide the resources needed by waterfowl. Although substantial capacity for DEDs still exists within the natural system, it varies widely both temporally and spatially. Indeed, in some exceptional years, habitat objectives may be achieved with minimal management intervention. Thus, the goal for managing waterfowl in a dynamic system such as the MAV needs to explicitly identify the frequency or regularity at which objectives should be achieved. Simply stating the goal as, “Achieve DED objectives” is not sufficient as it represents a risk level that is incompatible with the desires of the LMVJV Partnership. After considerable debate, the LMVJV expressed this goal as, “Achieve DED objectives in each state in 4 out of 5 years.” The implications of this approach for other systems that demonstrate high interannual variation are obvious. However, we urge the NAWMP (through its Science Support Team) to quickly provide guidelines to individual JVs on the appropriate level of risk to assume in achieving objectives. We believe this is the appropriate venue as risk tolerance is likely greater at the continental scale than the regional scale, and different levels of risk within a JV strongly affect the conservation effort and expenditures needed to achieve objectives. Furthermore, adoption of different levels of risk across JVs could threaten the coordinated delivery necessary to sustain continental waterfowl populations.

Once we identified an appropriate goal statement, we used a conceptually simple allocation model to identify the necessary contributions from different habitat sources. Recognizing that all DEDs are provided by one of three habitat sources (natural flooded, privately managed and publicly managed lands), we used basic algebra to derive Equation 1. (1) DEDPublic = DEDTotal - DEDPrivate - DED

Natural Flood This arrangement of variables is in line with the general philosophy of waterfowl conservation in the MAV as it depicts the habitat objective for public lands as the difference between the total DED objective and the DEDs provided by private managed lands and the natural system. DEDs associated with each habitat source are further defined as a function of several parameters shown in Equations 2-4. (2) DEDNatural Flood = f (extent, frequency,

duration, depth, habitat) (3) DEDPrivate = f (status, extent, reliability,

disturbance, habitat) (4) DEDPublic = f (extent, performance,

disturbance, habitat)

Those parameters common to all habitat sources include extent of water and quality of the habitat types over which that water occurred. Additional parameters important for DED derivation include the frequency, depth and duration of water on the landscape that occur from naturally flooded habitats, the conservation program status of individual parcels on private land habitats, reliability with which water is managed; the level of disturbance ducks experience on privately managed lands; the performance of managers in actually flooding areas that are considered “manageable”; and, the relative

disturbance ducks experience on publicly managed lands. Applying these equations requires accurate estimates of DEDs associated with each habitat source. Thus, novel methods were used to estimate the individual parameters in the model. We will discuss in detail several of the more critical model parameters (e.g., incorporation of disturbance, reliability, frequency, etc.) and the methodology used to estimate them as we believe these approaches also have obvious applicability to other JV’s conservation design efforts for waterfowl. Literature Cited Reinecke, K. J. and C. R. Loesch. 1996. Integrating research and management to conserve wildfowl (Anatidae) and wetlands in the Mississippi Alluvial Valley, U.S.A. Pages 927-940 in Marcel Birkan, editor. Anatidae 2000 : an international conference on the conservation, habitat management and wise use of ducks, geese and swans - une conférence internationale sur la conservation, la gestion des habitats et l'utilisation rationnelle des canards, des oies et des cygnes : Strasbourg, France, December 5-9, 1994. Gibier Faune Sauvage, Game and Wildlife 13(3). Reinecke, K. J., R. M. Kaminski, D. J. Moorehead, J. D. Hodges, and J. R. Nassar. 1989. Mississippi Alluvial Valley. Pages 203–247 in L. M. Smith, R. L. Pederson, and R. M. Kaminski, editors. Habitat management for migrating and wintering waterfowl in North America. Texas Tech University Press, Lubbock.

Underline all appropriate categories for your submission: Oral; Poster; Oral but will accept Poster; Student Travel Scholarship; Student Presentation Award. Asterisk (*) denotes the person(s) making the presentation. (Date of submission: July 15, 2012) Development of a field key for the identification of Florida mottled ducks

Ronald R. Bielefeld, Florida Fish and Wildlife Conservation Commission, Fish and Wildlife

Research Institute, 544 Jay Street, Sebastian, FL 32958, USA. (Ron.Bielefeld@MyFWC.com)

Jamie C. Feddersen,* Florida Fish and Wildlife Conservation Commission, Waterfowl Management Program, 3200 T.M. Goodwin Road, Fellsmere, FL 32948, USA. (Jamie.Feddersen@MyFWC.com)

Andrew Engilis, Jr., Department of Wildlife Fish and Conservation Biology, University of California, Davis, CA 95616, USA (aengilisjr@ucdavis.edu)

John M. Eadie, Department of Wildlife Fish and Conservation Biology, University of California, Davis, CA 95616 USA (jmeadie@ucdavis.edu)

Michael D. Tringali, Florida Fish and Wildlife Conservation Commission, Fish and Wildlife Research Institute, 100 8th Avenue SE, St. Petersburg, FL 33701, USA. (Mike.Tringali@MyFWC.com)

R. Joseph Benedict, Florida Fish and Wildlife Conservation Commission, Waterfowl Management Program, 8932 Apalachee Parkway, Tallahassee, FL 32311, USA. (Joe.Benedict@MyFWC.com)

Extended Abstract: Florida mottled ducks (Anas fulvigula fulvigula) are non-migratory and differ genetically from the Western Gulf Coast population of mottled ducks (McCracken et al. 2001). Mallards (Anas platyrhynchos) historically occurred in Florida only during fall and winter. However, releases of captive-reared mallards have established a feral population throughout much of the Florida mottled duck breeding range. These two closely related species have been interbreeding and producing fertile hybrid offspring for decades. Unless the feral mallard and hybrid populations are greatly reduced or eliminated, hybridization and genetic introgression jeopardizes the future existence of the Florida mottled duck as a distinct taxa. The first need in developing an effective management program is the ability to distinguish Florida mottled ducks from mallards and hybrids. The development of an

identification key based on plumage traits vetted by genetics will allow managers to efficiently deal with feral mallards and hybrids while protecting mottled ducks. We developed a plumage key for the identification of mottled ducks using a suite of potentially informative phenotypic and morphometric characteristics. This key should allow managers to assess the composition of the mottled duck population (excluding hybrids and mallards) in Florida without the need for expensive, time-consuming genetic procedures, and if needed, facilitate the reduction of feral mallard and hybrid populations. We measured plumage and structural traits (n=25) from museum specimens of 99 Florida mottled ducks and 45 mallards collected prior to the establishment of feral mallard populations in Florida (pre-1960). These data were analyzed using Discriminant Function Analyses to identify morphometric variables

that varied significantly between Florida mottled ducks and mallards. These traits were included in a preliminary mottled duck identification key along with phenotypic characteristics that were deemed diagnostic of mottled ducks and excluded mallards. This preliminary key was used to make a priori assignments for 80 mottled duck, 55 mallard, and 46 suspected hybrid carcasses collected from throughout the mottled duck range in Florida since 2001. A genetic sample was collected from each bird at the time the bird was assessed. For each specimen, we surveyed 94 variable microsatellite markers. Fifty-nine loci were isolated from a Florida mottled duck genomic library (Seyoum et al. 2012); the remaining 35 markers were optimized from loci isolated previously for various Anatid species (Williams et al. 2005, Hsaio et al. 2008). Programs STRUCTURE and NewHybrids were used to obtain assignment probabilities of genomic proportions (i.e., parental lineage) for each individual. Both programs provided similar results indicating the presence of pure mottled duck, mallard, and various hybrid classes in our sample. We used the Partition Platform in program JMP to recursively partition (i.e., build decision trees for) plumage traits based on population assignment (i.e., mottled duck, mallard, and hybrid). We used a 0.95 assignment probability of a bird being a pure mottled duck (as obtained from program NewHybrids) as our threshold for the partition analyses. Recursive partition analyses identified plumage characteristics for both males and females that allowed us to separate all mallards and a large proportion of hybrids (81% for males, r2 = 0.487 and 77% for females r2 = 0.482) from mottled ducks. This field identification key should allow managers to differentiate all mallards and most hybrids

from pure mottled ducks when in-hand. Some hybrid individuals (most likely mottled duck backcrosses) were too similar to pure mottled ducks to be identified using the traits we included in the analyses. We are currently testing the validity, efficacy, and teachability of the key using ducks collected throughout the breeding range and annual cycle of the Florida mottled duck. Once validated, this will provide a reliable identification key based on a few readily discernible physical traits to managers engaged in mallard reduction programs. Literature Cited: Hsiao, M.C., H. C. Liu, Y. C. Hsu, Y. H. Hu,

S. H. Li, S. R. Lee,. 2008. Isolation and characterization of microsatellite markers in Tsaiya duck. Asian-Australian Journal of Animal Science 21(5): 624-627.

Seyoum, S., M. D. Tringali, R. R. Bielefeld, J. C. Feddersen, R. J. Benedict, A. T. Fanning, B. L. Barthel, C. Curtis, C. Puchulutegui, A. C. M. Roberts, V. L. Villanova, E. C. Tucker. 2012. Fifty-nine microsatellite markers for hybrid classification studies involving endemic Florida Mottled Duck (Anas fulvigula fulvigula) and invasive Mallards (A. platyrhynchos). Conservation Genetics Resources DOI: 10.1007/s12686-012-9622-9

Williams, C.L., R. C. Brust, T. T. Fendley, G.

R. Tiller Jr, O. E. Rhodes Jr,. 2005. Comparison of hybridization between mottled duck and mallard in Florida and South Carolina using microsatellite DNA analysis. Conservation Genetics 6: 445-453.

Oral Presentation but will accept Poster

13 July 2012

A Decision Support Tool to Conserve Priority Playas for Migrating Waterfowl

Anne M. Bartuszevige*, Conservation Science Director, Playa Lakes Joint Venture, Lafayette, CO 80026 (anne.bartuszevige@pljv.org)

Extended Abstract: Playas are the primary wetland type found in the western Great Plains. They are small, ephemeral, depressional, recharge wetlands that are found at the lowest point of a closed watershed (Smith 2003). More than 75,000 playas have been identified throughout the region (PLJV unpubl data). Playas fill during intense rain events through surface run-off. Water is lost through recharge to the underlying Ogallala Aquifer and evapotranspiration (Smith 2003, Gurdak and Roe 2009). When wet, playas provide essential stopover and roosting habitat for migrating and wintering waterfowl, shorebirds, and waterbirds (Smith 2003). In addition, wetland birds are found at a higher density in regions with higher densities of playas (Cariveau and Pavlacky 2008, Webb et al. 2010).

However, the Great Plains is one of the most intensely agricultural regions in the U.S.; greater than 50% of the landscape has been converted to row crop agriculture (PLJV unpubl data). Approximately 80% of playas are found in tilled ground, which is the primary threat to wetland destruction. Increased sediment input from farming practices fills the playas causing alterations to hydrology and ability to support migrating wetland birds (Tsai et al. 2007). In addition, pitting (to drain large playas) and road construction can negatively impact playas as well.

Increasingly, the western Great Plains are being relied upon for energy production in addition to agricultural products. Traditional

(oil and gas production) and alternative energy sources (biofuels and wind energy development) are being developed in the region putting increased pressure on ecosystems.

Playa Lakes Joint Venture (PLJV) has been working to educate landowners and industry on the importance of playa ecosystems and have had profound success. The result has been increased awareness of playas and desire to direct conservation dollars to these important wetlands. However, with over 75,000 present on the landscape, the question arises, what are the priority playas? Which playas are important for development to avoid and which playas are important to direct conservation dollars towards?

To answer these questions, PLJV has developed a science-based geospatial decision support system (DSS) to identify priority playas for avoidance by development activities, and for conservation and restoration through Farm Bill programs and easements. The DSS is composed of two geospatial layers: a playa cluster layer and a priority playa layer.

To identify playa clusters, PLJV conducted an extensive literature search for articles that quantify waterfowl response to wetland density in the western Great Plains. These data were incorporated into a spatial analysis which identified clusters of playas at the scale at which waterfowl respond.

To identify priority playas, PLJV established working groups in each of the six states in

its region. Working groups were composed of biologists from various government, non-profit and industry organizations. Working groups were asked to identify and rank important factors to consider in playa conservation (e.g., landcover attributes, connectivity, size, disturbance, etc.) based on scientific literature and expert opinion. Individual playas were assigned a numerical score based on these assessments and subsequently ranked and prioritized.

Together, these two layers identify priority areas for playa conservation at two spatial scales. The clusters layer identifies areas of high densities of playas for conservation at a landscape scale. The priority playas layers further identifies individual basins for conservation action.

These two geospatial layers are combined with written guidance in the form of a user’s manual and best management practices. The user’s manual describes how the layers were developed and how to interpret them. The best management practices document describes science-based avoid, minimize and mitigate options for playa conservation.

Together these geospatial layers and written documents form the basis for strategic playa conservation throughout the western Great Plains. In addition, due to the broad stakeholder group that contributed to the development of the DSS, the tools will be incorporated into planning products from states (KS Natural Resources Planner) and federal initiatives (Ogallala Initiative).

Increasing attention is being given to the western Great Plains due to alternative energy development and declining water levels in the Ogallala Aquifer. Playas are an integral part of the Great Plains ecosystem and thus have become conservation targets. The Playa DSS is a giant step forward in strategic wetland conservation for waterfowl in the western Great Plains and the Central Flyway.

Literature Cited:

Cariveau, A. B. and D. Pavlacky, Jr. 2008. Assessment and conservation of playas in eastern Colorado. Rocky Mountain Bird Observatory, Brighton CO, USA.

Gurdak, J. J. and C. D. Roe. 2009. Recharge rates and chemistry beneath playas of the High Plains aquifer – A literature review and synthesis: U.S. Geological Survey Circular 1333.

Smith, L. M. 2003. Playas of the Great Plains. University of Texas Press, Austin, TX, USA.

Tsai J-S. L. S. Venne, S. T. McMurry, L. M. Smith. 2007. Influences of landuse and wetland characteristics on water loss rates and hydroperiods of playas in the southern High Plains, USA. Wetlands 27:683-692

Webb, E. B., L. Smith, M. P. Vrtiska, T. G. LaGrange. 2010. Effects of local and landscape variable on wetland bird habitat use during migration through the Rainwater Basin. Journal of Wildlife Management 74:109-119.

Oral, but will accept poster Using existing data to prioritize wetland conservation in Illinois. Richard D. Schultheis1* and Michael E. Eichholz2 1 Kansas Department of Wildlife, Parks, and Tourism. Emporia, KS,

66801(richard.schultheis@ksoutdoors.com) 2 Cooperative Wildlife Research Lab and Center for Ecology, Southern Illinois University.

Carbondale, IL 62901 (eichholz@siu.edu)

Extended Abstract: Efforts to quantify habitat requirements of wildlife populations are a key component to conservation planning. Using that information to focus conservation efforts in areas that will maximize benefits for wildlife is the logical next step. In this project, we used available estimates of habitat requirements for wetland dependent wildlife (Soulliere et al. 2007, for example), and general information on habitat preferences, occupancy, and density for species without available habitat requirement estimates, along with recently updated wetland availability information (Ducks Unlimited 2010), to prioritize future wetland conservation efforts within the state of Illinois. We also compared the wetland habitats we highlighted as conservation priority to those previously identified for the state, and used available data on lands currently in conservation programs to assess where conservation is occurring, and how that corresponds to what we, and others, suggest as priority. In general, most wetland habitat availability was higher to much higher than wetland dependent wildlife requirements. The one habitat type that appeared to be in defect was deep marsh, a habitat that is no longer common in Illinois. However, assumptions about habitat quality, as well with difficulties in habitat identification using aerial photography, increase the uncertainty in any

conclusions about habitat abundances and deficits.

Figure 1. Wetland conservation priority for the natural divisions of Illinois Habitat priority was based on habitat importance indices for the common wetland dependent wildlife of the state, including; waterfowl, waterbirds, shorebirds, landbirds, small mammals, and furbearers. Resulting priority areas for wetland conservation were often associated with river bottoms of the state’s large rivers, as well as The Cache River region of Southern Illinois (Figure 1). These priority areas align well with areas previously identified by other conservation groups

(Ducks Unlimited, The Nature Conservancy, National Audubon Society) (Figure 2). Wetlands currently in some form of conservation also correlate relatively well to the areas we, and others, have identified as conservation priority.

Figure 2. Wetland conservation priority areas previously identified in Illinois. Overall, further research on wetland habitat quality may be necessary to limit uncertainty of conclusions, but it appears that wetland abundance within Illinois is currently sufficient to support population objectives for wetland dependent wildlife. As money becomes more limited for wetland conservation, planning documents that focus conservation in the habitats that benefit wetland dependent wildlife most will allow conservation planners to more effectively restore and preserve appropriate wetland habitats.

Table 2.1. Number (n) and area (in ha) of wetland and deepwater habitats in Illinois. Data is summary of 2010 NWI update completed by Ducks Unlimited (2010) Habitat Type n Total area WETLANDS (W) Palustrine Forested Swamp 1,046 6,069 Bottomland Forest 55,202 305,351 Emergent Shall. marsh/wet m. 73,482 68,239 Semi-p. hemi/deep marsh 10,552 15,043 Open Water 173,695 79,076 Scrub-shrub 11,568 27,083 Lacustrine Shallow lake 456 20,709 Lake shore 280 902 Emergent lake 18 289 Riverine Perennial 1,854 978 Intermittent 31 40 TOTAL WETLAND 328,184 523,778 DEEPWATER HABITAT (D) Lacustrine 1,653 92,620 Riverine 756 81,245 TOTAL DEEPWATER 2,409 173,865 TOTAL HABITAT 330,593 697,643

Literature Cited: Soulliere, G. J., Potter, B. A., Coluccy, J. M.,

Gatti, R. C., Roy, C. L., Luukkonen, D. R., Brown, P. W., and M. W. Eichholz. 2007. Upper Mississippi River and Great Lakes Region Joint Venture Waterfowl Habitat Conservation Strategy. U.S. Fish and Wildlife Service, Fort Snelling, Minnesota, USA.

Ducks Unlimited. 2010. Updating the National Wetland Inventory (NWI) for Illinois. Final report submitted to Illinois Department of Natural Resources. DU Great Lakes Atlantic Regional Office, Ann Arbor, Michigan, USA.

Oral but will accept Poster Managing Hydrilla –Invasive Exotic Plant but Important Food for Wintering Waterfowl R. Joseph Benedict,* Florida Fish and Wildlife Conservation Commission, Tallahassee, FL

32311 (Joe.Benedict@MyFWC.com) Stephen V. Rockwood, Florida Fish and Wildlife Conservation Commission, Fellsmere, FL

32948 (Steve.Rockwood@MyFWC.com) Ed Harris, Florida Fish and Wildlife Conservation Commission, Orlando, FL 32812

(Ed.Harris@MyFWC.com) Jamie C. Feddersen, Florida Fish and Wildlife Conservation Commission, Fellsmere, FL 32948

(Jamie.Feddersen@MyFWC.com) Extended Abstract: Between 1985 and 1996, Florida lost approximately >105,000 ha of freshwater, emergent wetlands and losses continue (Dahl 2004). These wetlands are essential for resident, migrating, and wintering waterfowl in Florida. Additionally, flood control and water quality issues have resulted in established water level regulations for many Florida lakes resulting in altered natural hydrologies. These changes, coupled with proliferation of invasive exotic plants, such as Hydrilla (Hydrilla verticillata), have caused disagreement between resource managers and recreationalists on management of Hydrilla in infested lakes. When becoming established in Florida lakes, Hydrilla can displace ecologically important native submersed plants, such as pondweeds (Potamogeton spp.), eelgrass (Vallisneria americana), and coontail (Ceratophyllum demersum), by shading or simply outcompeting and eliminating native vegetation. Nonetheless, Hydrilla may replace some of the lost functions and values associated with emergent marshes, because it provides food for waterfowl in littoral and other deeper water zones. Numerous studies document the important relationship between Hydrilla and wintering waterfowl (Gasaway et al. 1979, Joyce et al. 1980, Johnson and Montalbano 1984, and Johnson and Montalbano 1987) and its importance as

food source for ducks, coots (Fulica americana), and common gallinules (Gallinula galeata) (Montalbano et al 1978, Montalbano et al. 1979, Hardin et al. 1984, O’Meara et al. 1982, and Mulholland 1983). For example, Johnson and Montalbano (1984) reported that waterfowl preferred Hydrilla over native plants, and Hydrilla also attracted a greater diversity of waterfowl species than native communities. In 2011, the Florida Fish and Wildlife Conservation Commission’s (FWC) Position Statement for Hydrilla Management, established guidance on how Hydrilla would be managed and what process would be employed to determine management prescriptions for individual waterbodies. Although the FWC prefers to manage for native aquatic plants, it recognizes that where native submersed aquatic plants are absent or limited, Hydrilla may be beneficial to fish and wildlife particularly in systems unlikely to provide other quality habitat. With input from resource management partners and local stakeholders, the FWC is developing Hydrilla management prescriptions for public waterbodies using a risk-based analysis that considers human safety issues, economic concerns, budgetary constraints, fish and wildlife values and recreational use. Use of FWC’s Position Statement and the process for development

of management prescriptions for individual waterbodies will be detailed. Literature Cited: Dahl, T.E. 2004. Florida’s wetlands – an

update on status and trends 1985-1996. U. S. Department of Interior, Fish and Wildlife Service, Washington, D.C.

Florida Fish and Wildlife Conservation

Commission. 2011. Agency Position on Hydrilla Management. Florida Fish and Wildlife Conservation Commission, Tallahassee, Florida.

Gasaway, R.D., S. Hardin, and J. Howard.

1976. Factors influencing wintering waterfowl abundance in Lake Wales, Florida. Proceedings of the Annual Conference of Southeastern Association of Fish and Wildlife Agencies 31:77-83.

Hardin, S., R. Land, M. Spelman, and G.

Morse. 1984. Food items of grass carp, American coots, and ring-necked ducks from a central Florida lake. Proceedings of the Annual Conference of Southeastern Association of Fish and Wildlife Agencies 38:313-318.

Johnson, F.A., and F. Montalbano III. 1984.

Selection of plant communities by wintering waterfowl on Lake Okeechobee, Florida. Journal of Wildlife Management 48:174-178.

Johnson, F.A., and F. Montalbano III. 1987.

Considering waterfowl habitat in hydrilla control policies. Wildlife Society Bulletin 15:466-469.

Joyce, J.C., W.T. Haller, and D. Colle.

1980. Investigation of the presence and survivability of hydrilla propagules in

waterfowl. Aquatics, Volume 2, Number 3.

Montalbano, F., III, S. Hardin, and W.M.

Hetrick. 1979. Utilization of hydrilla by ducks and coots in central Florida. Proceedings of the Annual Conference of Southeastern Association of Fish and Wildlife Agencies 33:36-42

Montalbano, F., III, W.M. Hetrick, and T.C.

Hines. 1978. Duck foods in central Florida phosphate settling ponds. Pages 247-255 in D. E. Samual, J.R. Stauffer, C.H. Hocutt, and W.T. Mason, editors. Proceedings of the symposium on surface mining and fish/wildlife needs in the eastern United States. U.S. Department of Interior, Fish and Wildlife Service OBS-78/79.

Mulholland, R. 1983. Feeding ecology of

the common moorhen and purple gallinule on Orange Lake, Florida. Thesis, University of Florida, Gainesville, Florida, USA.

O’Meara, T.E., W.R. Marion, O.B. Myers,

and W.M. Hetrick. 1982. Food habits of three bird species on phosphate-mine settling ponds and natural wetlands. Proceedings of the Annual Conference of Southeastern Association of Fish and Wildlife Agencies 36:515-526.

Underline all appropriate categories for your submission: Oral; Poster; Oral but will accept Poster; Student Travel Scholarship; Student Presentation Award. Asterisk (*) denotes the person(s) making the presentation. (Date of submission)

A Multi-Locus Evaluation of the New World Clade of the Mallard Complex

Philip Lavretsky,* Department of Environmental Sciences, Wright State University, Dayton,

Ohio, 45385 (lavretsky.2@wright.edu) Jeffrey L. Peters, Department of Environmental Sciences, Wright State University, Dayton,

Ohio, 45385 (jeffrey.peters@wright.edu) Extended Abstract: Mainland North America is host to the mallard (Anas platyrhynchos), American black duck (Anas rubripes; “black duck”), mottled duck (Anas fulvigula), and Mexican duck (Anas diazi). The mottled duck and Mexican duck are both endemic to lower latitudes of North America and are the only two non-migratory Anatini ducks within the region (Johnsgard 1978). In contrast, both mallards and black ducks are more widespread and migratory. Whereas the black duck is restricted to eastern North America, the mallard has a holarctic distribution extending across North America, Europe and Asia (Johnsgard 1978). Phylogenetic analyses based on mitochondrial DNA (mtDNA) place the North American species as each other’s closest relatives (Johnson and Sorenson 1999, McCracken et al. 2001), with divergence estimates of ~100,000 years (Kulikova et al. 2004). Due to expanding mallard populations resulting from environmental degradation, release programs, and close phylogenetic relationships, mallards are increasingly hybridizing with the endemic species (Ankney et al. 1987, McCracken et al. 2001, Perez-Arteaga et al. 2002) resulting in a risk of extinction by introgression (Rhymer and Simberloff 1996). As such, hybrid identification has been a priority in the management of these populations. However, identifying diagnostic markers has been difficult for both phylogenetic and population analyses, due to confounding effects of incomplete lineage sorting and introgression

(McCracken et al. 2001). In this study, we sequenced 16 nuclear loci across the genome to 1) better understand phylogenetic relationships of the New World taxa and 2) develop markers for the identification of pure and hybrid individuals. Results and Discussion: 50 mallards (MALL), 24 black ducks (ABDU), 50 mottled ducks (25 from Florida, MODU fl, and 25 from the gulf coast, MODUgc), and 25 Mexican ducks (MEDU) were assayed for 16 nuclear loci. Averaged across the loci, pair-wise ΦST estimates ranged from 1-5%, corroborating the close relationship of these taxa (Table 1). More specifically, we found that mallard, black ducks and Mexican ducks share a high proportion of haplotypes, while both mottled duck populations were almost as different from one another as they were from all the other taxa.

Among the 16 loci, there were no fixed differences that allow species identification; therefore, genetic identification of individuals needs to be based on frequency differences among loci. Isolating and coding 1-2 SNPs with the highest ΦST between mallards and

ABDU MALL MEDU MODUfl

ABDU – – – – MALL 0.013 – – – MEDU 0.017 0.021 – –

MODUfl 0.042 0.045 0.05 – MODUgc 0.033 0.039 0.045 0.038

Table 1. Pair-wise ΦST estimates.

each endemic species, we were able to correctly assign many individuals to each respective population with ≥ 90% confidence (Fig. 1A-C). However, there are clear differences in the ability of these markers to resolve relationships between these paired analyses. Resolving MEDU and ABDU from MALL individuals will require more samples and loci. Nevertheless, compared to other bi-parental markers that have been used (e.g., microsatellites, AFLPs), SNPs are more readily reproduced in different laboratories, and will be directly comparable among different studies, as well as among all the species within the clade. This comparability will improve and enhance the management and conservation of these species. Citations Ankney, D. C., D. G. Dennis, and R. C. Bailey.

1987. Increasing Mallards, Decreasing American Black Ducks: Coincidence or Cause and Effect? The Journal of Wildlife Management 51:523-529.

Johnsgard, P. A. 1978. Ducks, Geese, and swans. in Lincoln, Univ. Nebraska Press.

Johnson, K. P., and M. D. Sorenson. 1999. Phylogeny and biogeography of dabbling ducks (genus: Anas): A comparison of molecular and morphological evidence. Auk 116:792-805.

Kulikova, I. V., Y. N. Zhuravlev, and K. G. McCracken. 2004. Asymmetric Hybridization and Sex-Biased Gene Flow between Eastern Spot-Billed Ducks (Anas zonorhyncha) and Mallards (A. platyrhynchos) in the Russian Far East. The Auk 121:930-949.

McCracken, K. G., W. P. Johnson, and F. H. Sheldon. 2001. Molecular population genetics, phylogeography, and conservation biology of the Mottled

Duck (Anas fulvigula). Conservation Genetics 2:87-102.

Perez-Arteaga, A., K. J. Gaston, and M. Kershaw. 2002. Population trends and priority conservation sites for Mexican Duck Anas diazi. Bird Conservation International 12:35-52.

Rhymer, J. M., and D. Simberloff. 1996. Extinction by Hybridization and Introgression Annual Review of Ecology and Systematics 27:83-109.

Figures 1A-C. Pair-wise population assignment probability based on 1-2 SNPs per nuclear locus using the program Structure for mallards (MALL) with black ducks (ABDU), Mexican ducks (MEDU), and 2 mottled duck populations (MODUfl, MODUgf).

Figure 1C.

Figure 1A.

Figure 1B.