Copeia 2011, No. 3, 365–371 Breeding Chorus Indices Are Weakly Related to Estimated Abundance of Boreal Chorus Frogs Paul Stephen Corn1, Erin Muths2, Amanda M. Kissel2,3, and Rick D. Scherer4 Call surveys used to monitor breeding choruses of anuran amphibians generate index values that are frequently used to represent the number of male frogs present, but few studies have quantified this relationship. We compared abundance of male Boreal Chorus Frogs (Pseudacris maculata), estimated using capture–recapture methods in two populations in Colorado, to call index values derived from automated recordings. Single index values, such as might result from large monitoring efforts, were unrelated to population size. A synthetic call saturation index (CSI), the daily proportion of the maximum possible sum of index values derived from multiple recordings, was greater in larger populations, but the relationship was not highly predictive. UDITORY surveys of breeding anurans are a com- 1997; Hemesath, 1998; Burton et al., 2006; Pierce and mon tool used to verify distributions, investigate Gutzwiller, 2007) and may disagree on which species are A ecological relationships, and monitor trends of present (Genet and Sargent, 2003; Lotz and Allen, 2007; populations at various geographic and temporal scales Pierce and Gutzwiller, 2007). (Dorcas et al., 2009). Call survey data are recorded typically Most call surveys are conducted manually (i.e., by humans on an integer scale of one to three (Bishop et al., 1997; Weir who go to a field site and listen to frog choruses), and in large and Mossman, 2005), although Brodman (2009) used a five- monitoring programs a single index value would be used to point scale proposed by Karns (1986). Qualitatively, these represent the relative abundance of a species at a site. The scales indicate the number of frogs heard calling (one or two, a standard protocol of the North American Amphibian Moni- few, many). However, based on the reasonable expectation toring Program (NAAMP) specifies that survey routes should be that a larger number of frogs should generate a greater amount completed at least three times in a breeding season (Weir and of sound, there has long been a desire to treat these numbers as Mossman, 2005). However, this is intended more to capture quantitative indices to population size. Some authors have inter-specific variation in calling activity than to provide done that explicitly (Fahrig et al., 1995; Mossman et al., 1998; multiple observations for species at individual sites. To avoid Mazerolle, 2005; Eigenbrod et al., 2008; Brodman, 2009), but the problem of intra-specific seasonal variation in activity the more common approach is to treat these data conserva- (Crouch and Paton, 2002) and the statistical complications of tively as indicating whether a species was present or not repeated measures (Weir et al., 2009), analyses of call data as detected, and use occupancy analysis to estimate detection indices of abundance should be restricted to the observation probability (Weir et al., 2005; Pellet and Schmidt, 2005; obtained during a species’ maximum breeding activity. This Jackson et al., 2006; Sung et al., 2006; Brander et al., 2007). was the approach used by Mossman et al. (1998), but Early in the development of call surveys as a sampling restricting the data to a single observation likely exacerbates method, Vogt and Hine (1982) stated that for estimating problems with other sources of variation (environmental abundance, ‘‘Call indices for frogs are of limited use . ’’, influences and observer bias). One potential solution may lie and concluded, ‘‘Its value as a census technique is generally with the use of automated recording systems (ARS; Peterson limited to data on species presence.’’ Vogt and Hine and Dorcas, 1994; Dorcas et al., 2009), which can generate objected that in some species not all males in a breeding large amounts of data. The use of ARS has enormous potential congregation may call, but that other species may have to expand our understanding of anuran breeding phenology dense choruses of hundreds of calling males, making by allowing larger scale investigations and comparisons across individual calls impossible to count, and they described landscapes. However, to take advantage of ARS, the relation- biotic and abiotic factors that may influence data collected ship between the information we derive from sound record- with call surveys, all of which have been verified by ings and the information gathered from more intensive subsequent studies. These include that timing and intensity population level sampling must be quantified. We explore of calling activity varies among species and season (Bishop the use of ARS (sometimes termed ‘‘frogloggers’’) to evaluate et al., 1997; Crouch and Paton, 2002; de Solla et al., 2006; how both manual surveys and parameters derived from Saenz et al., 2006), time of day (Bridges and Dorcas, 2000; multiple recordings compare to abundance of Boreal Chorus Oseen and Wassersug, 2002), and may be dependent on the Frogs (Pseudacris maculata) estimated using capture–recapture weather, particularly temperature and precipitation (Oseen (CR) methods. and Wassersug, 2002; Kirlin et al., 2006; Saenz et al., 2006; Tupper et al., 2007; Steelman and Dorcas, 2010). Research MATERIALS AND METHODS also introduced the additional problem of observer bias, i.e., different observers often assign different index scores to a We recorded calling P. maculata at two ponds in the Rocky given chorus of frogs (Bishop et al., 1997; Shirose et al., Mountains in Larimer County, Colorado (Lily Pond [2969 m 1 U.S. Geological Survey, Northern Rocky Mountain Science Center, Aldo Leopold Wilderness Research Institute, 790 E. Beckwith Avenue, Missoula, Montana 59801; E-mail: [email protected]. Send reprint requests to this address. 2 U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Avenue, Building C, Fort Collins, Colorado 80526; E-mail: (EM) [email protected]. 3 Present address: Department of Biological Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada; E-mail: [email protected]. 4 Colorado State University, Department of Fish, Wildlife, & Conservation, Fort Collins, Colorado 80523; E-mail: [email protected]. Submitted: 8 December 2010. Accepted: 4 May 2011. Associate Editor: M. J. Lannoo. F 2011 by the American Society of Ichthyologists and Herpetologists DOI: 10.1643/CH-10-190 366 Copeia 2011, No. 3 elevation] and Matthews Pond [2803 m]), where we have observed breeding by this species annually since 1986 (Corn et al., 1989, 2000; Corn and Muths, 2002). Both ponds are shallow (,2 m deep), fishless vernal wetlands situated within a matrix of second-growth forest (Vertucci and Corn, 1996). They vary in size and depth depending on winter snow pack. Lily Pond averages about 0.5 ha and Matthews Pond about 0.07 ha during breeding, and they typically dry completely by late summer. Wood Frogs (Lithobates sylvati- cus) also breed at both ponds. We deployed ARS at Lily Pond beginning in 1994 and Matthews Pond in 1995. Through 2005, we used analog ARS constructed using a stereo cassette tape recorder controlled by a solid-state timer (Peterson and Dorcas, 1994; Corn et al., 2000; Saenz et al., 2006). One channel recorded frog calls from an external omni-directional microphone, while the other channel recorded the time from a voice clock activated at the beginning of each recording with a microphone inside the case of the ARS. Calls were recorded Fig. 1. Mean (61 SE) daily call saturation index (for eight years at Lily for 12 sec every 30 min in 1994–1995, and 18 sec every hour Pond and ten years at Matthews Pond combined) relative to the in 1996–2005. In 2006–2007, we used ARS constructed initiation of calling activity. Data from years without recordings or when around a monaural digital voice recorder (DVR, Diasonic recordings failed to determine the initiation of breeding activity were Technology Ltd., model DDR-5100, 512 megabyte capacity) not used in this figure. Arrows indicate the mean dates for the first three using an external omni-directional microphone and pow- CR occasions. ered using external D-cell batteries through the DC input. The DVR could be programmed for ten daily recordings; we made 54-sec recordings hourly from 1600 to 0100 (1-min used the closed capture–recapture model in program MARK recordings were programmed; this discrepancy appears to be (White and Burnham, 1999) to estimate population size at characteristic of the DVR). In 2008–2009, we deployed ARS each site for each year. The closed capture–recapture model designed for acoustic monitoring (Songmeter SM-1, Wildlife comprises parameters that represent capture probability (pi, Acoustics, Inc.). The Songmeter has flexible programming the probability of first capture on occasion i, and ci, the capabilities, records in stereo using two external omni- probability of recapture on occasion i)andestimated directional microphones, and stores digital files on remov- number of adult males (Nˆ ). We evaluated three of the able SD cards. We made hourly 5-min recordings at both standard models of capture probability (Otis et al., 1978): locations. As with the analog ARS, recordings with the SM-1 M0—capture probability is constant across individuals and were made 24 hr per day. sampling occasions within each year (null model); Mb— All recordings (analog and digital) were scored by a capture probability varies between individuals that have or human listener. Only the first 15 sec of the digital recordings have not been captured previously (behavior effect) but does were assessed to keep the data consistent with the earlier not vary across sampling occasions; and Mt—capture tape recordings. The listener scored recordings with calling probability varies across sampling occasions but not across according to the standard three-point NAAMP index (Weir individuals. Akaike’s Information Criterion for small sample and Mossman, 2005): 1 5 individual calls distinguishable, sizes (QAICc) was used to determine which of the models in no overlap; 2 5 individual calls distinguishable, some the set best represented the data.