The following is the established format for referencing this article:Navarre, K. L., J. M. Warren, and D. N. Koons. 2022. Hydrology management influences nest survival but not clutch size in Lesser Scaup. Avian Conservation and Ecology 17(2):29.
ABSTRACTComponents of reproductive success such as clutch size and nest survival may greatly affect avian population growth rates. Understanding how environmental conditions influence temporal variation in these demographic parameters could thus provide valuable insight into best management practices for species of concern. One such species that could benefit from a better understanding of such processes is Lesser Scaup (Aythya affinis), whose overall abundance in North America has declined since the early 1980s. We used a long-term study (2005–2019) of Lesser Scaup demography at Red Rock Lakes National Wildlife Refuge in southwestern Montana, USA, to examine how the management of wetland conditions influenced within- and across-year temporal variation in clutch size and nest survival. Predicted clutch size varied more across nest initiation dates (6.18–10.05 eggs) within years than it did across years (7.51–8.38 eggs), and none of the covariates we examined were significantly related to clutch size across years. Nest daily survival rates varied substantially across days within breeding seasons (e.g., 2018: 0.38–0.985), and annual mean nest survival varied greatly across years (0.27–0.58). Furthermore, seasonal chronology of managed wetland water levels influenced nest survival such that years when water levels gradually rose to a maximum late in the breeding season, relative to mean nest initiation date, resulted in the highest nest survival. These findings collectively suggest that when flows can be manipulated with water control structures, efforts to manage the chronology of water levels at watershed and local wetland scales could improve nest survival, whereas such management efforts will not likely affect clutch sizes.
A goal in wildlife management and conservation is to determine which demographic parameters have the greatest influence on population dynamics to identify where in the annual life cycle management actions might have their greatest impact. For long- and medium-lived species, adult survival probabilities are often found to have the greatest potential to affect population growth rates (Sæther and Bakke 2000). However, adult survival is often buffered against environmental variation and, because it is less variable among years compared to other demographic parameters (Pfister 1998, Morris and Doak 2004), it often has little influence on realized population growth rates (Gaillard et al. 1998). The vital rates that compose reproductive success, however, often fluctuate greatly among years and, in turn, may have a great impact on realized population growth rates (Koons et al. 2014, 2017). Determining factors governing temporal variation in reproduction could provide insights into how to influence key vital rates and positively affect populations in a feasible and efficient manner.
Nesting ecology is the most broadly researched topic in avian ecology and encompasses several important vital rates such as clutch size and nest survival. Together, clutch size and nest survival are major contributors to avian reproductive success, individual fitness, and variation in population growth rates (Martin 1995, Sæther and Bakke 2000). Temporal variation in environmental conditions may also influence food availability, specifically, invertebrate resources, which provide protein and minerals that are vital for clutch formation (Drobney 1991, Robertson 1995). Variation in clutch size at a given locale and time of year is driven by resource availability and energetic constraints (Lack 1947), as well as individual heterogeneity in the ability to acquire resources and allocate energy to the clutch (van Noordwijk and de Jong 1986). For example, limited food resources later in the nesting season often result in lower maternal body condition and, consequently, smaller clutch size (Krapu 1981, Devries et al. 2008). Given that older, more experienced individuals tend to be best at optimizing energy acquisition and timing of nest initiation with available resources, there is often a positive relationship between age or experience and clutch size (Hamann and Cooke 1987, Decker et al. 2012). Variability in resource availability across years could also influence mean annual clutch sizes via the same mechanisms.
Like clutch size, nest survival in waterfowl can vary greatly within and across years and across habitats (Klett and Johnson 1982, Wilson et al. 2007). Predation is the leading determinant of nest survival that often dictates observed spatiotemporal patterns, but research on waterfowl has focused primarily on spatial variation across habitats (Clark and Shutler 1999, Stephens et al. 2005, but see Walker et al. 2013). Whereas previous studies have found that nest-site selection influences nest survival in many dabbling ducks (Guyn and Clark 1997, Clark and Shutler 1999), studies of diving ducks have found no relationship between nest-site selection and nest survival (Krasowski and Nudds 1986, Maxson and Riggs 1996, O’Neil et al. 2014). Predation intensity can also vary temporally within a breeding season (Wilson et al. 2007, Colwell et al. 2011). In wetland systems, water levels during the breeding season can influence the ability of various mammalian predators to access nests (Maxson and Riggs 1996, Albrecht et al. 2006), or ample availability of alternative prey may result in prey-switching among predators and hence lower levels of nest predation (Ackerman 2002, Brook et al. 2005, 2008). Nest survival may also be driven by variation in environmental conditions across years, which can influence resource availability and female body condition, induce numerical effects on predator populations, drive alternative prey resources for predators, and, in turn, collectively influence temporal variation in nest survival rates (Blums et al. 1997, Drever and Clark 2007, Devries et al. 2008). Fluctuations in wet and dry periods, wetland density, and current-year primary productivity were found to influence nest survival in the prairie pothole region (Walker et al. 2013, Ringelman et al. 2018). Thus, when studying nesting ecology, it is important to consider many drivers of clutch size and nest survival to understand what influences reproductive success and population dynamics, especially for informing the management of declining populations.
Lesser Scaup (Aythya affinis) is a diving duck that could benefit from a deeper understanding of the processes influencing temporal variation in clutch size and nest survival because its population has declined since the early 1980s while other North American waterfowl are thriving. The most recent estimate of scaup abundance (3.6 ± 0.2 million) remains below objectives of the North American Waterfowl Management Plan of 4.9 million (note that estimates of scaup abundance represent a combination of Greater Scaup [Aythya marila] and Lesser Scaup because these two species cannot be differentiated in aerial surveys, but comprises ~90% Lesser Scaup; Lesser Scaup hereafter scaup; U.S. Fish and Wildlife Service 2019, Anteau et al. 2020). Recent analyses of demographic data have found no long-term declines in survival and concluded that recruitment has been the likely driver of decline (Arnold et al. 2016, 2018, Koons et al. 2017).
Although nesting ecology has been widely studied in scaup, few studies have been conducted consecutively over long periods of time at one location (Koons et al. 2006, but see Dawson and Clark 1996, 2000, Rotella et al. 2003). We studied a population of scaup at Red Rock Lakes National Wildlife Refuge (hereafter RRL), Montana, which is an important breeding location for scaup in the Intermountain West, from 2006–2015 and 2017–2018 (see Methods: Study site). Previous studies at RRL have examined how variation in female pre-breeding body condition influences clutch size and how reproductive success (including nest survival) can lead to carry-over effects in subsequent seasons (Warren et al. 2013, Warren 2018). Because habitat features have little influence on nest-site selection at RRL (O’Neil et al. 2014) and because the vast majority of scaup nests in sedge vegetation, where the degree of inundation by water is determined by the water level of RRL, associations between nest survival and different vegetation habitats were not of focal interest. Rather, our primary objectives were to build on previous studies and identify manageable environmental variables that (1) are related to temporal variation in scaup clutch size and nest survival at the study area, and (2) correspond to similar environmental processes that may affect scaup populations at other locales. Specifically, we predicted that years with lower water levels would serve as a proxy for decreased aquatic invertebrate abundances and, simultaneously, reduced protection of nests from predators, thereby resulting in lower clutch size (because of limited food availability) and nest survival (because of predation; Drever et al. 2012, Austin et al. 2014, McLean et al. 2016). Water levels can be manipulated at RRL by managing a dam at the out-flow of Lower Red Rock Lake, which is somewhat emblematic of fluvial wetlands within the western boreal forest ecosystem that are influenced by large hydroelectric dams such as in the Peace-Athabasca Delta and Saskatchewan River Delta (> 3000 and 10,000 km², respectively; Townsend 1966).
Our study was conducted on Lower Red Rock Lake (LRRL) at RRL in southwest Montana, USA (Fig. 1). LRRL is a 2330-ha, high elevation (2014 m above mean sea level) montane wetland complex within the Centennial Valley that supports a high density of breeding scaup (> 7.7 breeding pairs/km² [J. Warren, personal observaton], which is a high nesting density throughout the scaup range). This wetland system is characterized by large areas of open water with hardstem bulrush (Schoenoplectus acutus) islands and surrounded by vast stands of seasonally flooded Northwest Territory sedge (Carex utriculata). Interspersed in the sedge stands are small (< 2 ha) open water ponds, which offer nesting habitat (i.e., to nest near open water and escape from predators). Water levels in LRRL do not exceed 1.5 m during the nesting season. Average annual precipitation and temperature are 49.5 cm and 1.7°C, respectively. This site is similar to the core breeding range of scaup in the northwest boreal forest of Canada and Alaska, as it has similar growing season length, shallow waters, fluvial hydrology, and large expanses of flooded Northwest Territory sedge (U.S. Fish and Wildlife Service 2009, Wells et al. 2010, Gurney et al. 2011, 2017). These properties contrast prairie wetlands that are fed by snow runoff and groundwater (Hayashi et al. 2016), and the prairie pothole region, where many previous studies of scaup have been conducted (Austin and Fredrickson 1986, Rotella et al. 2003).
To study determinants of temporal variation in scaup clutch size and nest survival at our study area, we conducted nest searching efforts through June and July beginning in 2006 and continued nest searching efforts each summer through 2018, except for 2016 due to lack of funding. The study area was divided into 16 survey blocks, each containing one to four 750 × 750 m cells (blocks with predominately open water had one cell, whereas blocks that were predominately vegetation had four cells). Investigators systematically searched these survey blocks on foot, including on the bulrush islands located in LRRL and the surrounding nearshore and upland habitats, because scaup are both overwater and upland nesters. Scaup hens were flushed from nests by disturbing vegetation with a willow switch or a trained dog. When a nest was located, we determined clutch size and incubation stage and estimated nest initiation date by candling eggs (Weller 1956). Nest locations were recorded in Universal Transverse Mercator coordinates using a global positioning system, and a willow switch with flagging tape was placed 4 m to the north of the nest to assist in locating for future visits. We continued to visit nests every 7–10 days until its fate was determined (i.e., successful, destroyed, abandoned). Any nests abandoned due to investigator disturbance (abandoned immediately after they found) were removed from analyses; however, nests naturally abandoned were included in analyses.
We quantified wetland conditions at the study site using a capacitance probe water level and temperature data logger (model WT-HR 1500; TruTrac, Christchurch, New Zealand). In April of each year, we deployed the probe at the outflow of LRRL to record hourly water levels and temperature throughout the breeding season. We also made visual observations of a staff gauge at the same location in case of capacitance probe malfunctions. Averaged hourly water level and temperature readings were used to calculate mean annual pre-breeding and breeding season values described below. In the case of capacitance probe malfunction, the visual observation value was used as the daily value of water level (see Appendix 1, Environmental Conditions for further details).
To address our objective of evaluating environmental drivers of clutch size, we estimated within and across-year temporal variation in clutch size using generalized linear mixed-effect models with Poisson distribution and a log-link. Models were fitted using maximum likelihood estimation in the lme4 package (Bates et al. 2012) in R (R Core Team 2020). The nest initiation date (INIT) of each nest was included as a fixed effect because previous studies have found that nests initiated earlier in the breeding season have larger clutch sizes compared to nests initiated later in the season, largely because of the mechanisms discussed earlier (Batt et al. 1992, Esler et al. 2001) and because this effect has previously been detected for scaup at our study site (Warren et al. 2013). We also considered fixed effects for both the mean pre-breeding season water level (PRELVL, 01 May–15 June) and water temperature (PRETEMP, 01 May–15 June) because both variables can influence primary productivity and available invertebrate food resources (Vannote and Sweeney 1980, Cayrou and Céréghino 2005), which scaup are known to acquire once arriving on the breeding grounds before clutch formation (Cutting et al. 2011). As an alternative, we also considered mean breeding season water level (LVL, 01 May–31 August) because females must continue to forage throughout the egg laying period to supply nutrients for egg production (Arnold and Rohwer 1991). We also considered an index of nesting phenology (PHENIND) relative to water level by subtracting the annual mean nest initiation date (INIT) from the ordinal date of maximum water level each year. A large positive PHENIND indicates that water levels peaked late in the breeding season relative to mean nest initiation date and is likely indicative of gradually rising levels during nesting, whereas a large negative PHENIND indicates that water levels peaked early in the breeding season before mean nest initiation (such conditions result from low snowpack or very warm spring temperatures, or both). Chronology of peak water level may influence invertebrate resource pulses that align or misalign (Winder and Schindler 2004, Thackeray et al. 2010) with scaup nutritional needs during egg production. All explanatory hydrological variables were standardized (mean = 0 and standard deviation [SD] = 1) using the scale() function in R. We similarly standardized nest initiation dates within each year relative to the respective annual mean to account for within-year variation among nests that could be attributable to unmeasured individual heterogeneity in female reproductive investment (Aubry et al. 2009).
Our suite of considered models included univariate fixed effects of each covariate, bivariate additive effects between nest initiation date and each hydrological covariate that varied among years, as well as relevant interactions (see Appendix 1, Table A1.1). We also included a random intercept for nest year (YEARRAN) to estimate temporal variation among years not explained by the fixed effects. Conditional Akaike’s Information Criterion (cAIC) was used for model selection because it appropriately accounts for the dimension of the random effect in the penalty term (Saefken et al. 2014). We considered parameters to be imprecise and uninformative if their 95% confidence interval (CI) overlapped zero and if addition of such parameters to a nested simplification increased the cAIC value of a model, as opposed to decreasing it. The addition of parameters with explanatory power should decrease the information criterion of a model (Arnold 2010).
To address our objective of identifying environmental drivers of temporal variation in nest survival, we estimated daily survival rates (DSR) of nests using the “nest survival model” in the RMark package for R (Laake 2013, R Core Team 2020), which calls program MARK (White and Burnham 1999). This model allowed us to examine environmental covariates for temporal variation in DSR of nests on the logit scale (Dinsmore et al. 2002, Rotella et al. 2004, Rotella 2007).
Previous work with nesting birds has found that DSR can increase as the nesting season progresses because of decreased rates of nest predation as alternative prey become available to predators (Wilson et al. 2007, Colwell et al. 2011). DSR may also decrease throughout the breeding season due to declines in female body condition and corresponding reduction in incubation constancy (Brook et al. 2005, Devries et al. 2008). Across waterfowl studies, most have found a negative relationship between nest initiation date and nest survival (Flint and Grand 1996, Arnold et al. 2007, Grant and Shaffer 2012, Raquel et al. 2015), although some have found a positive (Grand 1995, Greenwood et al. 1995, Garrettson and Rohwer 2001) or quadratic relationship (Pieron and Rohwer 2010), and one interesting study documented an interaction with inter-nest distance (Ringelman et al. 2018). Therefore, we considered models with a linear (TIME, measured in days) or quadratic (TIME + TIME²) seasonal time trend. We also considered a univariate model for the effect of nest age, defined as the number of days since nest initiation for each nest (NAGE), because DSR is known to increase with nest age as females increase incubation constancy and because of detection bias (Klett and Johnson 1982, Forbes et al. 1994).
We next considered the same covariates describing variation in wetland conditions across years that were used in the clutch size analysis, which allowed us to explore how they might simultaneously influence nest survival. For example, water levels during the pre-breeding period (PRELVL) could influence food availability and body condition in females (Warren et al. 2013), possibly affecting nest survival via incubation constancy (Yerkes 1998). Nesting females in poor body condition require more frequent incubation breaks to forage, increasing the risk of nest exposure to predators (Blums et al. 1997). Pre-breeding season water temperatures (PRETEMP) could also affect nest survival because water temperatures influence invertebrate hatches (Ward and Stanford 1982) when females are acquiring nutrients for incubation and could affect nest survival via the same mechanisms as pre-breeding water levels. Average water levels during the nesting season (LVL) could influence nest survival by restricting predator access to nests. Nest predators such as coyote (Canis latrans), red fox (Vulpes vulpes), and striped skunk (Mephitis mephitis; but not racoon, Procyon lotor, which do not occur at RRL) are less likely to wade or swim through large expanses of flooded sedge during high water years, whereas during low water years, such predators may easily walk to nests in the favored sedge habitat (Jobin and Picman 1997). The phenological index (PHENIND: ordinal date of maximum water level minus mean nest initiation date) may reveal a match or mismatch between nesting females’ nutritional needs and food resources, which may influence female body condition, incubation constancy, and, therefore, nest survival, or it could provide more acute insight into how the timing of rising (or dropping) water levels might affect both protection from predators and the chances of nests becoming flooded (Winder and Schindler 2004, Thackeray et al. 2010). For example, a large positive PHENIND could be indicative of a year with substantial snowpack but slow runoff, leading to gradually rising water levels during a nesting season (offering protection from predators), but peaking after nesting concludes (limiting potential for flooding of nests; Van Dellen and Sedinger 2021).
We took a tiered approach to model selection because we were primarily interested in temporal drivers of nest survival across years while accounting for within-year variation in DSR of nests and wanted to avoid data dredging associated with consideration of all possible combinations of covariates (Franklin et al. 2000). First, we built a set of models with explanatory variables describing temporal variation in wetland conditions among years that included univariate effects of each wetland covariate, and a null model with CONSTANT DSR. Bivariate additive effects of the wetland covariates were also considered (though additive effects of PRETEMP and PHENIND were not considered due to multicollinearity). As with the clutch size analysis, if additional parameters did not decrease information criterion values, we considered the effects uninformative (Arnold 2010). We then retained the top model(s) from the first step and considered additional effects of covariates serving as proxies for biological mechanisms that could affect within-year variation in nest mortality, including TIME, TIME + TIME², and NAGE. We used Akaike’s information criterion adjusted for small sample sizes (AICc) for model selection in both steps of the DSR analysis (Akaike 1998, Burnham and Anderson 2002). After determining the top model with fixed-effect covariates describing within- and among-year variation in nest survival, we implemented a model with year (YEAR) as a fixed effect plus the supported parameterization for covariates describing within-year temporal variation. To determine the explanatory power of the focal covariates describing temporal variation in nest survival across years in our top models, we conducted an analysis of deviance (ANODEV) to measure the proportion of deviance (eq. 1) explained by covariates in a model compared to full year effects (i.e., YEAR as a fixed effect; Skalski 1996).
where WITHIN refers to the most supported parameterization of covariates for temporal variation within years, and ACROSS for covariates describing temporal variation across years. Finally, we used the fitted DSR estimates from the top model and the delta method (Powell 2007) to estimate a nest survival probability for each year (using a 34-day period of laying and incubation; Warren 2018).
Annual measurements for environmental conditions at LRRL and the covariates described above are summarized in Appendix 1 (Fig. A1.1 and Environmental Conditions).
Clutch size estimates
Over 12 years, we monitored a total of 825 nests. For the clutch size analyses, we removed any nest with clutch size < 4 because these were not considered full clutches (i.e., likely a result of partial egg predation, accidental ejection of eggs by the female, or both; Batt and Prince 1979, Anteau et al. 2020), which left 711 nests for analysis. The mean clutch size across years was 7.93 eggs (± 1.67 SD; Appendix 1, Fig. A1.2), and annual means ranged from 7.07 (in 2006) to 8.96 (in 2012) eggs (Fig. 2). Mean nest initiation date for the study period was day 172.21 ± 9.42 (21 June), with the earliest mean nest initiation date occurring in 2007 (day 166, 15 June) and the latest in 2011 (day 187, 06 July; Appendix 1, Fig. A1.3). Across the study period, nest initiation dates ranged from ordinal day 142 to 202 (22 May–21 July), with a median of day 172 (20 June).
The univariate model with nest-specific initiation date within a year (INIT) was the top model among our candidate set designed to explain within- and across-year variation in scaup clutch size at the study area (Appendix 1, Table A1.1). Several other models were within two cAIC points of our top model; however, they were all additive or interaction models that included the top model as a nested simplification, deeming the more complex models as uninformative, and the estimated coefficients associated with the additional parameters were imprecise (i.e., 95% CI widely overlapped 0). In our top-ranking model, nests that were initiated later in the season had significantly smaller clutch sizes (log-scale intercept: 2.06 ± 0.02, 95% CI: 2.02 to 2.10, INIT: −0.11 ± 0.01, 95% CI: −0.14 to −0.09; Fig. 3). After controlling for relative nest initiation dates within each year, the variance for the year random effect (0.002 ± 0.047 on the log scale) indicated that clutch size varied little between years (Fig. 2).
Daily survival rate and nest survival estimates
We monitored a total of 783 nests until their fate was determined, of which 537 were successful (68.6% apparent nest survival). In our first tier of model selection, only three models outperformed a null model, and the top model included a univariate effect of PHENIND that carried 51% of the model weight (logit-scale intercept: 3.87 ± 0.07, 95% CI: 3.74 to 4.00, PHENIND: 0.18 ± 0.07, 95% CI: 0.05 to 0.30; see Appendix 1, Table A1.2 for model selection table). The second and third models included additional but uninformative parameters, and therefore, we retained only PHENIND in the second tier of model selection, in which we added explanatory variables for within-year variation in DSR.
In the next tier of model comparison, the data indicated greatest support for additive effects of PHENIND and the quadratic model of TIME + TIME² across days within a season, which carried nearly 100% of the model weight (logit-scale intercept: −0.45 ± 0.62, 95% CI: −1.66 to 0.76, PHENID: 0.19 ± 0.07, 95% CI: 0.06 to 0.32, TIME: 0.15 ± 0.03, 95% CI: 0.10 to 0.20, TIME²: −1.20 × 10−3 ± 2.91 × 10−4, 95% CI: −1.75 × 10−3 to 6.12 × 10−4; see Appendix 1, Table A1.3 for model selection table). DSR was lower at the beginning of each nesting season, increased and peaked in the middle of the season, and generally plateaued after the peak (Fig. 4). The positive effect of PHENIND indicated that DSR was generally higher in years when the ordinal date of maximum water level was much later than the mean nest initiation date (Fig. 5). For example, 2014 had the highest PHENIND, when the date of maximum water level was on day 243 (31 August), the mean nest initiation date was on day 171 (20 June), the last nest hatched on day 225 (13 August), and DSR peaked at 0.990 ± 0.002 (95% CI: 0.986 to 0.993) in this season. The years with the lowest PHENIND were 2009 and 2010, with a date of maximum water level of day 121 (01 May) and a mean nest initiation date of day 174 (23 June). The maximum DSRs during these seasons were 0.983 ± 0.003 (95% CI: 0.978 to 0.987) and 0.982 ± 0.003 (95% CI: 0.784 to 0.984) for 2009 and 2010, respectively. Results from the ANODEV indicated that PHENIND (in the PHENIND + TIME + TIME² model) explained 34% of the variation in DSR across years compared to the YEAR + TIME + TIME² model with full year effects (i.e., independent estimates for every year).
We used predicted DSRs from our top-ranked model (PHENIND + TIME + TIME²) to calculate annual nest survival estimates beginning on the mean nest initiation date of each year, using the 34-day egg laying and incubation period starting from this date, using the delta method. Nest survival at LRRL averaged 0.43 (± 0.02, 95% CI: 0.38 to 0.48) among all years. Annual nest survival was highest in 2011 (0.58 ± 0.03, 95% CI: 0.52 to 0.64) and lowest in 2007 (0.28 ± 0.04, 95% CI: 0.21 to 0.35; Fig. 6).
For the first time, we found that the annual chronology of when wetland water levels peaked, relative to mean nest initiation dates, explained significant amounts of temporal variation in scaup nest survival across years. After controlling for notable variation in nest daily survival rates across days of exposure within nesting seasons, years in which water levels peaked later in or after the nesting season corresponded to higher nest daily survival rates and overall nest survival. Peak water levels late in the breeding season are likely indicative of gradually rising water levels due to snow melt that inhibit accessibility of nests to predators but do not flood nests like a peak in the middle of the nesting season could do (Van Dellen and Sedinger 2021). Despite examining a large suite of relationships for seasonal water level and temperature relationships with mean annual clutch size across years, none were statistically significant, perhaps because clutch size was nearly constant across 12 years of study. Below, we discuss our findings relative to the presiding literature and outline inferences for guiding management applications at wetland to watershed scales.
As is common in avian populations, clutch size declined seasonally at the study area (Rowe et al. 1994, Decker et al. 2012) but exhibited little variation across years and did not respond to annual fluctuations in the water variables we considered. The small temporal variability of clutch size across years at the study site (process variance = 0.0023) was similar to that at other sites in the northern boreal, prairie parklands, and prairie pothole regions (Corcoran et al. 2007, Gurney et al. 2011). It is hypothesized that within-year variation in clutch size is due to individual heterogeneity in specific females, such as age and innate ablility to improve body condition just prior to breeding (Lindberg et al. 2013, Warren et al. 2013). Re-nesting attempts could have also influenced the observed variation in clutch size given that females are known to lay fewer eggs in re-nesting attempts (Batt and Prince 1979); however, we were unable to accurately differentiate re-nests from initial nests in our study.
In general, nests are initiated later at RRL compared to many other study sites throughout the species’ range. For example, the mean nest initiation date across all years was day 172.21 ± 9.42, which is later than sites at similar latitudes (Missouri Coteau, North Dakota: 166.1 ± 10.1; St. Denis National Wildlife Area, Saskatchewan 166.8 ± 10.9). It is similar to more northerly sites (Cardinal Lake, Northwest Territories: 173.8 ± 8.1; Yellowknife, Northwest Territories: 170.0 ± 9.4), but also similar to Erickson, Manitoba (170.2 ± 9.8), which is at a slightly higher latitude but lower elevation (Gurney et al. 2011). This pattern is likely due to the high elevation of the southern RRL location. In addition, Raquel et al. (2016) found that scaup initiated nests over a span of 11 days (interquartile range of 25–27%) at St. Denis National Wildlife Area and Redberry Lake, in Saskatchewan, whereas scaup at RLL initiated nests over a 14-day period (interquartile range of 25–75%), suggesting that although scaup at RRL initiate nests later, the span of nest initiation may be similar to other locations. We did not specifically explore drivers for nest initiation dates, but others have found weak correlations with growing season length (Gurney et al. 2011) and no effect of spring pond counts (Raquel et al. 2016), suggesting that scaup tend to initiate nests at similar times each year, regardless of environmental conditions.
Furthermore, mean clutch size at the study site (7.9 ± 1.7) was slightly lower than at other nesting locations at similar latitudes (e.g., Missouri Coteau, North Dakota: 9.6 ± 1.8; Erickson, Manitoba: 9.8 ± 1.6), likely due to the high elevation. Similar to high latitude (e.g., Yukon Flats National Wildlife Refuge, Alaska: 8.2 ± 1.5; Cardinal Lake, Northwest Territories: 8.3 ± 1.6), high elevation is generally associated with smaller clutch sizes in most waterfowl species (Gurney et al. 2011). Gurney et al. (2011) also found that regardless of latitude and the length of the growing season at a study area, scaup clutch sizes varied little across years. In addition, studies have found that scaup rely heavily on endogenous nutrients obtained at stopover locations prior to arriving on the breeding grounds (Afton and Ankney 1991, Esler et al. 2001), which could explain why environmental variables at the site explained little of the variation in clutch size across years. However, Cutting et al. (2011) found that scaup at LRRL rely heavily on endogenous nutrients when local conditions are poor and exogenous nutrients when local resources are readily available, suggesting that scaup might readily adapt their energetic acquisition and allocation strategy for clutch formation. The small process variance in clutch size and the lack of response to measured environmental variables at the study site further suggest that these plastic energetic strategies help scaup buffer their clutch size against annual fluctuations in environmental conditions on the breeding grounds.
Contrary to clutch size, nest survival varied substantially across years and was positively correlated with the index of annual water level chronology relative to mean nest initiation date, indicating that nest survival was highest in years when water reached peak levels after the nesting season had already concluded. Inconsistent with the concept of a resource–consumer phenology mismatch, this result more so suggests that rising wetland levels to a late-season peak may have provided protection against mammalian predators and nest flooding. Maintaining flooded sedge habitats likely protected nesting females from mammalian predators such as coyotes, foxes, and skunks, which are not inclined to wade through flooded sedge habitats to search for overwater nests (Jobin and Picman 1997). However, nests were still susceptible to predation from American mink (Neovison vison) and avian predators such as common ravens (Corvus corx) and gulls (Laridae spp.). High water levels late in the breeding season also allow females to swim off their nests discretely when taking incubation breaks. In contrast, low water periods force females to fly off their nests, revealing the nest location to predators, especially avian ones, resulting in increased rates of nest failure. More conspicuous incubation behavior resulted in higher rates of predation in shorebirds, which is also likely the case in waterfowl given that they are exposed to similar nest predators (Smith et al. 2012, Ellis et al. 2020). Finally, maximizing water levels extremely late in the breeding season compared to mean nest initiation date may have also led to decreased rates of nest flooding given that many nests would have already hatched prior to peak water levels, whereas a peak water level in the middle of the nesting season could flood a substantial number of nests. Nest flooding is a known cause of nest failure at LRRL (Warren et al. 2013), was the second leading cause of nest failure in the boreal forest (Walker and Lindberg 2005), and is often a cause of nest failure in other diving duck species (Bouffard et al. 1987, McAuley and Longcore 1989).
Historically (1950s–1990s), scaup nest survival varied among years and locations, with average rates in the prairie grasslands, prairie parklands, and northern boreal of 37.3%, 29.5%, and 57.2%, respectively (Anteau et al. 2020). More recent studies in these locations found nest survival rates of 14% in the northern boreal (Brook 2002) and 12% in the prairie parklands (Koons and Rotella 2003), with rates ranging from 11–27% in the Alaskan boreal forest (Walker et al. 2005, Corcoran et al. 2007, Martin et al. 2009). With a mean rate of 43% at LRRL, nest survival is higher than many of the recent estimates at other locations but lower than historic estimates in the northern boreal. The water control structure at LRRL can maintain relatively high water levels, acting as a buffer against drought cycles, and is likely contributing to the elevated nest survival rates via protection from some mammalian predators.
Broadly, some studies have found scaup nest survival to vary by habitat type, year, and cover type (Emery et al. 2005). Walker et al. (2005) found that nest survival varied with year, date of discovery, and habitat type in the Alaskan boreal forest; specifically, nest survival was highest in upland habitats followed by islands, floating vegetation, and meadows. Ultimately, they concluded that nest survival was driven by variation in predator risk, because it was the largest cause of nest failure, and water fluctuations, because they found evidence of nest flooding. Likewise, Corcoran et al. (2007) found nest survival to be driven by habitat type, and nests located on wooded creeks had the highest probability of survival followed by nests located on small and large wetlands. They hypothesized that this result was due to predators being less inclined to search for nests among the dense vegetation of wooded creeks. In contrast, Koons and Rotella (2003) found that none of their measured covariates (habitat type, observer effect, year, or nesting period) influenced nest survival in Canadian parklands. These studies not only highlight the need to understand how habitats do or do not influence nest survival in scaup, but also demonstrate that habitat influences may be site specific. Furthermore, these studies did not explore how water levels or water level chronology could influence nest survival, which our results suggest should be explored at other breeding locations.
Water levels can be managed in some aquatic ecosystems using water control structures (e.g., stoplog structures, small dams, large dams). However, given the lack of response to variation in water levels and temperature across years, managers have little potential to influence clutch size in scaup at the local population level via manipulations of water conditions at LRRL and perhaps elsewhere (although see Warren et al. 2013 for potential to favor certain individual strategies). Nevertheless, we did find that water levels could be managed to increase slowly throughout the breeding season to improve nest survival. In years with ample snowpack and slow runoff, water levels could be manipulated via a water control structure on LRRL. Managers historically increased water levels early in the breeding season to provide ample nesting habitat for Trumpeter Swans (Cygnus buccinator), which nest earlier than scaup, then drew down water levels throughout the breeding season, and finally increased water levels again to maximize recreational opportunities such as waterfowl hunting in the autumn. Altering wetland management practices to slowly increase and then maintain water levels throughout the breeding season would maximize the extent of flooded sedge habitats, benefiting scaup nesting performance and population growth (Koons and Rotella 2003). Maximizing the extent of flooded sedge habitats throughout the breeding season, but without flooding nests, may also benefit scaup in other locations because they prefer to nest in wetland margins with sedge throughout their range, and many systems can be manipulated via water control structures (e.g., stoplog structures, small dams, large dams).
At local wetland scales, water control structures could be used to fine-tune the chronology of wetland hydrology for improving scaup nesting habitat (e.g., national wildlife refuges, state and provincial management areas, etc.). Although such actions have limited spatial potential and are not likely to mitigate continental declines in abundance for a species with such a vast breeding range, local actions can have important effects on local ecosystem services (e.g., wildlife viewing, hunting opportunities, and trophic cycling of nutrients). Although the majority of scaup breeds in the western boreal forest, a vast region that is largely uninhabited by people, there are large wetland complexes that attract large numbers of scaup and are influenced by large hydroelectric dams, including the Saskatchewan River Delta, the Peace-Athabasca Delta, among others. The primary management of these dams will be directed at electricity generation, but our results indicate that it would be beneficial for waterfowl managers to consider seeking a seat at provincial hydroelectric stakeholder tables to voice needs for nesting scaup and other waterfowl. Such representation in the water management decision-making process could tip the scales in ways that could meaningfully affect scaup reproductive success at larger scales than LRRL alone.
When possible, given the presence of water control structures (of any size), our findings provide a tool for managers to consider that may have previously been overlooked for scaup. Managers must nevertheless be mindful of the other disturbances that may be affecting the suitability of scaup breeding habitat, including the footprints of the oil and gas, mineral mining, and timber industries in the boreal forest (Wells et al. 2010, Prairie Habitat Joint Venture 2014), as well as agricultural expansion and intensification in the prairie pothole region and elsewhere (Rashford et al. 2011). Across southern latitudes, wetland consolidation for agriculture has decreased the abundance and quality of wetlands for scaup (Anteau and Afton 2008, Anteau et al. 2011), in addition to potential changes in agricultural crops, which may be less conducive to waterfowl nesting (Rashford et al. 2016). Furthermore, climate change is predicted to alter precipitation regimes, and much of the scaup breeding range will become hotter and drier and may also experience increased variability in extremes of wet and dry cycles (Drever et al. 2012, Anteau et al. 2016). Informed hydrology management at scaup breeding areas that attempts to maximize scaup nest survival by safeguarding against predators and minimizing nest failures from flooding, may benefit scaup at RRL, at other similar wetlands, and even at some large watersheds within the important western boreal forest.
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K.L.N. collected and compiled field data, performed the statistical analysis, and wrote the manuscript. J.M.W. collected field data, developed and designed field protocols, and assisted with editing the manuscript. D.N.K. assisted with analysis design and manuscript editing.
We sincerely thank all the staff at Red Rock Lakes National Wildlife Refuge, Ducks Unlimited Montana, and the countless technicians and volunteers who assisted with trapping and banding efforts, notably: K. Bas, A. Greenawalt, Dr. T. Riecke, E. Sawa, C. Vennum, T. Walker, and S. Walden. We also thank Y. Kanno and C. Aldridge for constructive comments.
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