Validating the use of temperature data loggers to measure survival of songbird nests

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1 J. Field Ornithol. 77(4): , 2006 DOI: /j x Validating the use of temperature data loggers to measure survival of songbird nests Karel Weidinger 1 Laboratory of Ornithology, Palacky University, Tr Svobody 26, Olomouc, Czech Republic Received 9 November 2005; accepted 10 June 2006 ABSTRACT. Accurate determination of nest fates and nest predators is possible through continuous video monitoring, but such monitoring is relatively expensive and labor intensive. If documenting of the timing of nest termination events is sufficient, then data loggers (DL) may allow more extensive sampling and may represent a viable alternative. I validated temperature DL records of nest survival time by simultaneous videotaping and compared results derived from DL records with those obtained by regular nest visits by an observer. I estimated the fate of 937 nests of nine species of open cup-nesting songbirds, including 673 nests monitored using DL, 165 monitored using video cameras, 33 validation nests monitored simultaneously using both DL and video cameras, and 132 control nests monitored only by observer visits. Deployment of DL did not negatively influence nest survival rate. DL reliably recorded survival time and allowed classification of nest fates based on the potential fledging age, regardless of the frequency of nest visits by an observer. The true fate of nests that survived beyond the potential fledging age can not be safely determined from time of failure, except for nocturnal events that suggest partial predation. Video revealed frequent partial or complete predation on nests with old nestlings that would have been categorized as successful by other methods. I conclude that temperature DL are efficient, reliable, and relatively inexpensive tools for recording exact nest survival times and classification of nest fates, with implications for nest survival modeling and discriminating between diurnal and nocturnal predation. SINOPSIS. Validando el uso de bitácoras electrónicas de temperatura para medir la sobrevivencia en nidos de aves canoras Es posible determinar con precisión la sobrevicencia en nidos y la depredación en estos mediante el uso de videos contínuos. Pero dicho monitoreo es relativamente costoso y requiere mucho trabajo. Si el documentar el momento en que se termina el anidamiento es suficiente para obtener la información, previamente mencionada, el uso de bitácoras electrónicas de temperatura (loggers) pudieran permitir el tomar muestras más amplias y por ende, representar una alternativa viable. Validé la toma de temperaturas con bitácoras electrónicas para determinar la sobrevivencia en nidos con la toma simultánea de videos y comparé los resultados obtenidos (con la bitácora) con los datos tomados por un observador que visitó regularmente los nidos. El estudio se hizo con 937 nidos de nueve especies de aves canoras cuyo nido es en forma de copa. De estos 673 se monitorearon utilizando bitácoras electrónicas de temperatura, 165 con cámaras de video, 33 con monitoreo simultáneo de bitacora y video y 132, como control, monitoreados mediante observación directa. El uso de las bitácoras no influyó negativamente en la tasa de sobrevivencia. La bitácora grabó el tiempo de sobrervivencia y permitió la clasificación de los nidos (exitoso o no exitoso) basado en el tiempo potencial de la edad de dejar el nido, sin importar la frecuencia de visita a los nidos por parte de observadores. La verdadera finalidad de los nidos que sobreviven, más alla de la edad potencial de dejar el nido los pichones, no puede ser determinado con exactitud, excepto en eventos nocturnos que surgieren depredación. El uso de videos permitió determinar la depredación parcial o completa en nidos, particularmente de pichones que se tardaron más que el tiempo promedio en dejar el nido y que en estudios se asume que sobrevivieron. Puedo concluir que las bitácoras electrónicas de temperatura son eficientes, confiables, de bajo costo y permiten determinar con precisión la sobrevivencia en nidos y la clasificación de estos entre exitosos y no exitosos, con implicaciones para construir modelos de sobrevivencia y discriminar entre depredores diurnos y nocturnos. Key words: data logger, nest predation, nest survival, predators, video Nest survival has been documented for many bird species in many habitats, and predation is recognized as the main cause of nest failure in most open-nesting songbirds. Determining nest fate is contingent on correct identification of important local nest predators, but such data are 1 Corresponding author. weiding@prfnw. upol.cz usually lacking (Thompson and Burhans 2003). Predators have been identified at artificial (i.e., inactive) nests using plasticine eggs (Major and Kendal 1996, Remeš 2005) and automatic setcameras (Cutler and Swann 1999). However, experiments with artificial nests may not represent natural (i.e., active) nests (Major and Kendal 1996, Thompson and Burhans 2004). Furthermore, applicability of set-cameras to active nests C 2006 The Author(s). Journal compilation C 2006 Association of Field Ornithologists 357

2 358 K. Weidinger J. Field Ornithol. Fall 2006 remains limited (Liebezeit and George 2003). Continuous video monitoring of bird nests has recently become popular among researchers (e.g., Pietz and Granfors 2000, Williams and Wood 2002, Renfrew and Ribic 2003, Stake and Cimprich 2003, Thompson and Burhans 2003, 2004, Schaefer 2004), but this method is relatively expensive and labor intensive. Investigators studying nest predation often strive to identify factors associated with the risk of predation for individual nests or habitats. Because different predators use different sensory cues to locate nests (Santisteban et al. 2002), traits such as nest concealment, coloration of eggs, and parental activity or scent at the nest are only relevant to particular predators (Pietz and Granfors 2000). In some cases, it may be sufficient to distinguish between diurnal (visual) and nocturnal (scent-oriented) predators. Knowledge of nest failure times is also essential for analyzing spatiotemporal patterns of nest predation (Larivière and Messier 2001). Another topic of recent concern is the methodology of nest survival estimation and modeling. Application of the recently developed methods (Aebischer 1999, Manolis et al. 2000, Rotella et al. 2004, Nur et al. 2004) would benefitfrom knowledge of exact nest survival times. The method of recording failure times was first implemented using artificial nests (Ball et al. 1994, Larivière and Messier 2001). However, temperature data loggers (DL) are inexpensive and readily available, and may be useful for measuring more exact survival periods for active nests because a sudden and permanent fall in nest temperature indicates the end of nest activity. Although temperature DL have been used to monitor nest microclimate (e.g., Wiebe 2001) and incubation behavior (e.g., Heer 1999, Joyce et al. 2001), their use to record nest failure is uncommon (Heer 1999, Jackson and Green 2000, Bellebaum and Boschert 2003). If proven reliable, this method would permit efficient and relatively inexpensive collection of data. My objectives were to evaluate applicability of temperature DL for (1) recording nest survival times, (2) classifying nest fates, and (3) identifying types of nest predators. METHODS Study area and nest searching. I conducted this study in Czech Republic (49 54 N, E, m asl) from 2001 to 2005 as a part of a long-term study of open-nesting songbirds (Weidinger 2001). The study area is characterized by a mosaic of arable land, with villages and remnants (woodlots and riparian strips) of deciduous forest. I collected data each year on 7 16 plots (2 10 ha) located in distinct forest patches; the median distance to the nearest neighboring plot was 1350 m. I located the nests by systematically searching in shrubs and herbaceous vegetation with approximately constant effort from mid-april to mid-july. Nests found most frequently were those of Blackcaps (Sylvia atricapilla), Song Thrushes (Turdus philomelos), Blackbirds (T. merula), Yellowhammers (Emberiza citrinella), Chaffinches (Fringilla coelebs), Chiffchaffs (Phylloscopus collybita), Garden Warblers (S. borin), Icterine Warblers (Hippolais icterina), and Dunnocks (Prunella modularis). Nests were inspected every 1 5 d (see below) to determine nest fates. I did not use nest markers and made no attempt to mask human scent. Cues potentially useful for determination of nest fate (nest appearance, behavior of parents, and presence of fledglings near nests) and nest site characteristics were recorded on the last visit to a nest. Data loggers. I used HOBO H8 Temp/ External DL (Onset Computer Corp., Pocasset, MA) with external probes (1.8 m cable). The DL were placed in weatherproof, camouflaged plastic boxes (6 3 cm). The cables were dyed dull green or brown and used based on the prevailing color of the substrate around individual nests. The steel-covered probes (4 cm long tip of the cable) were camouflaged with brown fabric tape that resembled the color and structure of the nest cup bottom. The probe was passed through the nest wall so it was horizontal at the bottom of the nest cup and partly embedded in the nest lining. The cable outside of the nest was fixed to the vegetation supporting the nest by a wire. The box with the DL was either buried in litter or hidden in dense foliage. DL were set to record temperature at 1-min intervals and recorded continuously for about 5.5 d. I tried to deploy DL immediately after nest discovery, but postponed deployment until the next visit for species sensitive to disturbance during laying and early incubation (Yellowhammer and Song Thrush). I avoided placing DL at nests with nestlings old enough to leave the nest because of my presence. Deployment took up to 5 min.

3 Vol. 77, No. 4 Measuring Nest Survival 359 All nests with DL were visited at 5-d intervals (daily during the periods of simultaneous video recording; see below) to check nest contents and exchange full DL for empty ones. To keep time spent at nests short, I offloaded the data after leaving the nest vicinity. DL remained at each nest until the nest failed or nestlings fledged. Data were collected in (50 sets each year) from mid-april to July. The mean (range) daily temperatures in the study area during May, June, and July (years pooled) were 13.6( C (range 4 20), 16.3( C (range 10 23), and 16.9( C (range 12 22), respectively. Video monitoring. I used video camera systems consisting of a video camera with 12 infrared-emitting diodes (diameter 5.3 cm, length 8.5 cm), a 24-h time-lapse VCR (Mitsubishi HS-7424EDC; 5.6 frames s 1 ), and a 12 V/40 65Ah deep cycle battery. The VCR was housed in a weatherproof plastic box cm) and connected to the camera by a 10-m cable. All system components were camouflaged by brown-green spotted painting. I used a handheld LCD monitor to adjust camera position and check system function in the field. The camera was mounted on vegetation 1 3 m from the nest and masked by natural material. The box with the VCR and battery was either buried in litter or hidden in herbaceous vegetation. I adopted the same precautions to minimize the risk of nest abandonment as with DL. When cameras and DL were placed at the same nest, video cameras were not deployed on the same day as DL to minimize time at the nest. Deployment took about 20 min, with the most time spent camouflaging the system. Because one goal of video monitoring was to record incubation and feeding behavior from as many nests as possible, each nest was typically videotaped for only 2 5 consecutive days during both the incubation and nestling stages. I visited videotaped nests daily in the afternoon or evening to change the tape (180 min VHS) and battery. Nest contents were checked only if a bird was not sitting on the nest. Videotaping started in 2002 (two sets) and continued to 2005 (eight sets). Data analysis. For nest survival estimation, Idefined potential fledging age as the age when the oldest nestling could fledge successfully (10 d for Chiffchaff and Icterine Warbler and 8 d for the other species), regardless of the actual age at fledging. Species in my study reached potential fledging age about 3 4 d before mean fledging age. I refer to that part of the nesting cycle (time from laying to fledging) after the potential fledging age as the potential fledging period. I first interpreted nest survival or failure by observation during nest visits without considering nest status derived from DL or video cameras. Nest fate was classified as survived, failed, or uncertain based on the survival to potential fledging age. Loss of individual eggs or nestlings from nests that survived to potential fledging age was not considered. A failed nest was considered predated when at least one egg or nestling disappeared from the nest; failed nests with intact clutches were considered deserted. Daily survival rate (DSR) was estimated using the Mayfield method; the exposure time (Manolis et al. 2000) was terminated on the midpoint of the last nestvisit interval (failed nests), on the last active visit before the potential fledging age (uncertain fate), or on the potential fledging age (survived nests). For DL records, I inspected the graph of temperature against time and recorded the time of a permanent decline in nest temperature as the end of nest activity. Nest fate was then classified as survived or failed according to nest survival to the potential fledging age. In contrast to nest visit data, no nest fates (given the definition above) had to be categorized as uncertain because exact survival time was known. DSR was then estimated from the exact exposure time for failed nests (i.e., without the Mayfield midpoint assumption); exposure time for survived nests was terminated on the potential fledging age. Fate of nests that survived beyond the potential fledging age was tentatively inferred from the timing of the event (probability of successful fledging was assumed to increase with nestling age and to be higher during daylight hours than during night) and appearance of the nest (e.g., disturbed or trampled). However, I made no attempt to estimate DSR for the potential fledging period. Finally, I viewed video tapes to record survival to the potential fledging date, as with DL and observer visit data. Apart from this, video records allowed me to record true nest fate (i.e., fledging, predation, or partial predation, with partial predation defined as the loss of individual eggs or nestlings from nests that fledged at least one nestling), the species of nest predator, and the exact timing of predation or fledging events. I then used these data to validate DL records from the same nests.

4 360 K. Weidinger J. Field Ornithol. Fall 2006 Table 1. Decline in nest temperature recorded by data loggers during nest termination events. Ambient Nest temperature Nest fate N temperature Initial Final Decline a Predation ± ± ± ± 4.4 Partial b ± ± ± ± 3.6 Fledging ± ± ± ± 3.6 Total ± ± ± ± 4.3 Fates of these validation nests were determined by simultaneous monitoring with video cameras (see Table 2). Values are mean temperatures ( C) ± 1 SD. a Difference between the initial and final nest temperature. b Partial predation/fledging (forced fledging). To evaluate the potential effect of DL deployment on nest survival, I also monitored a set of control nests without DL in Control nests were distributed among study plots and throughout the breeding season in approximate proportion to the distribution of DL nests. Control nests were checked using the same protocol as for DL nests. For comparison with control nests, the DSR for DL nests was estimated by considering only the information about status of the nest obtained during observer visits. For this comparison, I only used DL nests with the DL deployed on the day of nest discovery. I designed this study to evaluate the general applicability of DL for monitoring open songbird nests. Distribution of DL among species was roughly proportional to the number of nests found, and videotaping effort was distributed evenly among species. I tried to distribute DL and video cameras with respect to date and nest age as equally as possible, given the number of nests available at a particular time. Apart from this, potential confounding effect of nest and time-related covariates were controlled by the paired design of the comparisons the different nest monitoring methods were applied simultaneously to the same nests. RESULTS I estimated the fate of 937 nests, including 673 nests monitored using DL, 165 nests monitored using video cameras, 33 validation nests monitored using both DL and video cameras, and 132 control nests monitored only by observer visits. Timing of events determined from temperature records matched the time recorded on videotape in 32 of 33 nests. The one unclear case was caused by two Garden Warbler nestlings that moved around their flattened nest and were only temporarily in contact with the temperature probe during the hour before fledging. The drop in nest temperature was more distinct (t = 2.33, P = 0.027) during nest loss events (N = 24) than during fledging (N = 9; Table 1), and when ambient temperatures were lower (r = -0.42, P = 0.014; N = 33). Video records from validation nests revealed that all nests that become inactive before the potential fledging age were correctly classified as failed (Table 2). Survival to the potential fledging age could not be assessed solely by the nest status on subsequent nest visits for 12% (82 of 673) of the nests and their fates were classified as uncertain (Table 3). In contrast, data-logger records permitted classification of the fate of all nests. Of the above uncertain cases, 52% (43 of 82) nests could be unequivocally classified as failed (Table 3). All videotaped cases (N = 45) of natural fledging occurred between sunrise and sunset. Table 2. Fates of validation nests documented by video and independently classified based on survival time recorded by data loggers. Nest fate from Nest fate from video record data logger Predation Partial a Fledging Total Failed 20 b b 20 Survived c Total Data from all years and species were pooled. a Partial predation/fledging (forced fledging). b Combination of nest fates impossible, by definition. c Defined as survival to the potential fledging age.

5 Vol. 77, No. 4 Measuring Nest Survival 361 Table 3. Nest fates independently classified based either on nest visits by an observer or on survival time recorded by a data logger. Nest fate based Nest fate based on nest visits on data logger Failed Survived a Uncertain Total Failed 454 b Survived a b Total a Defined as survival to the potential fledging age. b Combination of nest fates impossible, by definition. Hence, the nocturnal events recorded by the DL during the potential fledging period, combined with the appearance of empty nests, suggest that complete or partial predation (forced fledging) occurred at 22% (39 of 176) of the nests that survived beyond the potential fledging age and were classified as successful. Video records from validation nests showed that (partial) predation occurred at 31% (4 of 13) of such nests (Table 2). Both the total number of exposure days and the number of known nest fates that could be used in estimating DSR increased with the use of DL (Table 4). Nevertheless, the DSR estimated from DL records was close to estimates based on nest visit data for all species analyzed separately, as well as for pooled data (Table 4). Daily survival rates (DSR, 95% CI, N ) were similar between DL nests and control nests in 2003 (Blackcap: 0.924, , 125 vs , , 22; Blackbird: 0.927, , 35 vs , , 28; Song Thrush: 0.914, , 20 vs , , 54; all species: 0.921, , 231 vs , , 132). The proportion of nocturnal predation events was 39% (194 of 497) and 35% (43 of 122) based on DL and video records, respectively. Videotaping showed that mammals were responsible for all nocturnal predation events (N = 43) and for 33% (26 of 79) of diurnal predation events. Moreover, no relationship was found between predator category and appearance of the predated nest. Hence, discrimination of bird and mammal predators from DL records and nest appearance was not possible. DISCUSSION Temperature DL reliably recorded nest survival times for nine species of open-nesting songbirds. The end of nest activity was best detected at nests with stable temperatures nests with older (more endothermic) nestlings and those continuously attended by females during the night. Drops in nest temperature were generally more distinct and easier to interpret for nest loss events than for fledging because trampling by nestlings may have caused probes to be buried at the bottom of nests near the time of fledging. Temperature DL cannot detect partial nest losses when the remaining nestlings or nest-attending parents warm the nest, and are not applicable during the egg-laying stage when adults are on nests less frequently. My ability to interpret temperature records was influenced by the effects Table 4. Daily survival rate (DSR) of the same nests estimated from either nest visits by an observer (V) or survival time recorded by a data logger (DL). Total Failed Exposure nests a nests days DSR 95% CI Species V DL V DL V DL V DL V DL Blackcap Blackbird Song Thrush Yellowhammer Total b Years pooled. a Lower number of nests was used to estimate DSR from nest visits than from data logger records because nests of uncertain fate observed over just one interval contributed no exposure days to estimation of DSR from nest visits; data loggers recorded exposure time also for these nests. b Also included in the total sample are species with too few nests to permit separate analyses.

6 362 K. Weidinger J. Field Ornithol. Fall 2006 of nest shading and the position of probes in the nests. Ideal positioning of probes presents a trade-off with the level of damage to nest structure and the time spent in deployment. One possible improvement in future studies would be application of multichannel DL measuring the ambient temperature at each particular nest. Use of DL in open habitats where nests are exposed to sun or in warm climate needs further evaluation. In my study, knowledge of exact survival times permitted more accurate classification of nest fate, based on the potential fledging age (or any other predefined time threshold) regardless of the frequency of nest visits by an observer. However, the true fate of nests that survived beyond the potential fledging age could not safely be determined (Heer 1999), except for the nocturnal events that suggest partial predation. The most accurate method to reliably determine nest fate after the potential fledging age is videotaping. Video records revealed frequent partial or complete predation on nests with older nestlings (see also Thompson et al. 1999, Liebezeit and George 2002, Williams and Wood 2002, Small 2005) that would have been categorized as successful based on survival to the potential fledging age or cues (e.g., nest appearance) recorded by observer visits during the potential fledging period. This has serious implications for estimating nest success (Weidinger, in press). One possible solution is to truncate exposure time on the potential fledging age or on the nest visit preceding it ( early termination sensu Manolis et al. 2000) and to restrict inferences about nest survival to the part of the nesting cycle before the truncation point. My data support the view that both the nest visit and DL records from the potential fledging period should be excluded from the estimation of nest survival rate (Stanley 2004). Knowledge of the time of failure is useful not only for classification of individual nest fates, but also for modeling of nest survival rates (Weidinger, in press). Specifically, recently developed methods that model nest survival over intervals of variable length (Rotella et al. 2004) can be simplified to a special case where survival is modeled for individual nest days or other time units (Aebischer 1999, Shaffer 2004). This should be especially useful when the effect of time-specific covariates on nest survival rate is to be evaluated (Grant et al. 2005) because it allows investigators to use covariate values for individual time units instead of averages for entire nest visit intervals. Finally, the exact nest survival time can be treated as a continuous dependent variable, making it possible to apply the methods of survival time analysis (Nur et al. 2004). Nest survival rates estimated using traditional nest visits and the DL were similar. This has two implications. First, it shows that the midpoint assumption inherent in the Mayfield method accurately approximates the actual nest failure times in the present data set. Second, because DL provided comparable estimates, more extensive sampling is possible because the effort required to monitor nests is reduced. This may be useful both logistically (simultaneous nest monitoring on several distant plots) and ethically (minimizing investigator disturbance). Video records showed that mammalian predators were active both day and night. Hence, predation by birds and mammals in my study could not be reliably distinguished by the timing of predation recorded by DL, except for the nocturnal predation that could be attributed to mammals. I was unable to reliably classify predation events by species or category (mammalian or avian) based on either visual nest disturbance or estimated failure times. This supports conclusions of previous video camera studies (Liebezeit and George 2002, Williams and Wood 2002). Nevertheless, more accurate documentation of times when nests fail may increase our understanding of predation impacts when predator activities or behaviors are well documented in a given study system (Ball et al. 1994, Jackson and Green 2000, Bellebaum and Boschert 2003). When detailed records of bird behavior, exact knowledge of individual nest fates, or predator identities are needed, there is no substitute for videotaping. The cost of each video system used in my study was about $1000 (given the local prices and exchange rate), including batteries and charger. The cost of each DL set (DL, external probe and box) was about $85, plus an additional $180 for data shuttle and software. About 5% of DL recordings in my study were defective because of bad contact between the DL and the external probe, but I used a low-price DL intended for indoor use only. Deployment of a DL takes about one-third the time needed for deployment of a video system and nests can

7 Vol. 77, No. 4 Measuring Nest Survival 363 be visited less frequently (limited by the logger capacity). If documenting the timing of nest termination events is sufficient, then DL may allow more extensive sampling and represent a viable alternative to video cameras. Because video systems are still relatively conspicuous and expensive, their applicability in areas frequently visited by people may be limited, whereas DL are more easily hidden. Of the 50 DL used over two breeding seasons in my study, two were destroyed by forester s machinery, one was removed and damaged by a large carnivore (it was recovered after 8 mo and data could still be recovered), and two cables were chewed by rodents. Based on my study, about 10 times more nests can be monitored with DL than by video cameras for the same cost and with much less effort. ACKNOWLEDGMENTS This work was supported by the Grant Agency of the Czech Republic (GAČR 206/01/P028 and GAČR 206/04/1081) and by the Ministry of Education of the Czech Republic (MSM ). I thank M. Krist, V. Pavel, V. Remeš, and the referees for constructive comments on the manuscript. LITERATURE CITED AEBISCHER, N. J Multi-way comparisons and generalized linear models of nest success: extensions of the Mayfield method. Bird Study 46: BALL, I. J., R. J. GAZDA, AND D. B. MCINTOSH A simple device for measuring survival time of artificial nests. Journal of Wildlife Management 58: BELLEBAUM, J., AND M. BOSCHERT Determining predators at nests of meadow birds. Vogelwelt 124: CUTLER, T. L., AND D. E. SWANN Using remote photography in wildlife ecology: a review. Wildlife Society Bulletin 27: GRANT, T. A., T. L. SHAFFER, E.M.MADDEN, AND P. J. PIETZ Time-specific variation in passerine nest survival: new insights into old questions. Auk 122: HEER, L Use of artificial eggs measuring temperature as a tool for the assessment of breeding parameters. Ornithologische Beobachter 96: JACKSON, D. B., AND R. E. GREEN The importance of the introduced hedgehog (Erinaceus europaeus)as a predator of the eggs of waders (Charadrii) on Machair in South Uist, Scotland. Biological Conservation 93: JOYCE, E. M., T. S. SILLETT, AND R. T. HOLMES An inexpensive method for quantifying incubation patterns of open-cup nesting birds, with data for Blackthroated Blue Warblers. Journal of Field Ornithology 72: LARIVIÈRE, S., AND F. MESSIER Temporal patterns of predation of duck nests in the Canadian prairies. American Midland Naturalist 146: LIEBEZEIT, J. R., AND T. L. GEORGE Nest predators, nest-site selection, and nesting success of the Dusky Flycatcher in a managed ponderosa pine forest. Condor 104: , AND Comparison of mechanically egg-triggered cameras and time-lapse video cameras in identifying predators at Dusky Flycatcher nests. Journal of Field Ornithology 74: MAJOR, R. E., AND C. E. KENDAL The contribution of artificial nest experiments to understanding avian reproductive success: a review of methods and conclusions. Ibis 138: MANOLIS, J. C., D. E. ANDERSEN, AND F. J. CUTHBERT Uncertain nest fates in songbird studies and variation in Mayfield estimation. Auk 117: NUR, N., A. L. HOLMES, AND G. R. GEUPEL Use of survival time analysis to analyze nesting success in birds: an example using Loggerhead Shrikes. Condor 106: PIETZ, P. J., AND D. A. GRANFORS Identifying predators and fates of grassland passerine nests using miniature video cameras. Journal of Wildlife Management 64: REMEŠ, V Birds and rodents destroy different nests: a study of Blackcap Sylvia atricapilla using the removal of nest concealment. Ibis 147: RENFREW, R. B., AND C. A. RIBIC Grassland passerine nest predators near pasture edges identified on videotape. Auk 120: ROTELLA, J. J., S. J. DINSMORE, AND T. L. SHAFFER Modelling nest survival data: a comparison of recently developed methods that can be implemented in MARK and SAS. Animal Biodiversity and Conservation 27: SANTISTEBAN, L., K. E. SIEVING, AND M. L. AVERY Use of sensory cues by Fish Crows Corvus ossifragus preying on artificial bird nests. Journal of Avian Biology 33: SCHAEFER, T Video monitoring of shrub-nests reveals nest predators. Bird Study 51: SHAFFER, T. L A unified approach to analyzing nest success. Auk 121: SMALL, S. L Mortality factors and predators of Spotted Towhee nests in the Sacramento Valley, California. Journal of Field Ornithology 76: STAKE, M. M., AND D. A. CIMPRICH Using video to monitor predation at Black-capped Vireo nests. Condor 105: STANLEY, T. R When should Mayfield model data be discarded? Wilson Bulletin 116: THOMPSON, F.R.,AND D. E. BURHANS Predation of songbird nests differs by predator and between field and forest habitats. Journal of Wildlife Management 67: , AND Differences in predators of artificial and real songbird nests: evidence of bias in

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