The population dynamics of migratory birds are shaped by environmental processes occurring throughout their annual cycle (Sillett et al. 2000). In particular, weather patterns have been linked to variation in adult survival in birds at every stage of the annual cycle (Newton 1998). Although severe episodic weather can directly kill adult birds (Roberts 1907a, b, Smith and Webster 1955, Newton 2007), the effects of weather on adult survival are thought to be largely mediated through changes in food availability and foraging opportunities (Smith 1982, Newton 1998) that operate throughout the year in different locations. For example, annual apparent survival of adult Sedge Warblers (Acrocephalus schoenobaenus) is strongly influenced by drought conditions on the African nonbreeding grounds; during droughts, seasonal wetland habitat acreage diminishes, competition for food supplies intensifies, and adult apparent survival declines (Peach et al. 1991, Baillie and Peach 1992). Similarly, winter precipitation is thought to be an important driver of Nearctic-Neotropical migratory bird populations, with relatively dry winters associated with lower apparent survival, delayed spring migration, and subsequently reduced breeding output (Ryel 1981, Sillett et al. 2000, Studds and Marra 2011, Rockwell et al. 2012).
In much of the tropical and subtropical regions of the Western Hemisphere, storm frequency and rainfall patterns (especially during the Caribbean winter dry season) are strongly influenced by El Niño-Southern Oscillation (ENSO) via changes in ocean temperatures and wind intensity and direction (Curtis and Adler 2000, Giannini et al. 2000, 2001, Bell and Chelliah 2006). Relatively wet ENSO periods are associated with substantial increases in arthropods (e.g., aerial insects and spiders), primary productivity, and rates of flowering and fruiting in plant communities (Polis 1997, Polis et al. 1998, Holmgren et al. 2001). These wet periods are also associated with improved overall body condition and survival in Nearctic-Neotropical migrants that overwinter in the Caribbean (Sillett et al. 2000, Strong and Sherry 2000). The apparent survival (and fecundity) of Black-throated Blue Warblers (Setophaga caerulescens), for example, is lower following relatively dry winters in Jamaica (Sillett et al. 2000). Insect prey biomass also broadly declines over the winter in the Caribbean, so that spring migrants are food limited and in relatively poorer condition than at the start of the winter (Marra and Holberton 1998, Strong and Sherry 2000), which could increase mortality during migration (Owen and Black 1989, Morrison et al. 2007).
Similarly, the normalized difference vegetation index (NDVI) is often investigated as a measure of annual variation in winter habitat quality. The NDVI is a remotely sensed indicator of vegetation “greenness” and density that has a well-established relationship to net primary productivity (Pettorelli et al. 2005). Favorable environmental conditions and increased abundance, survival, and body condition in migratory bird species have been positively correlated with NDVI values from the nonbreeding grounds (Møller 1989, Szép 1995, Peach et al. 2001, Saino et al. 2004). For these bird species, NDVI is likely a predictor of food availability because insect species richness and abundance are often positively correlated with NDVI (Gordo 2007, Lassau and Hochuli 2008, Jepsen et al. 2009).
Bicknell’s Thrush (Catharus bicknelli) is a rare, range-restricted songbird, breeding only in high-elevation fir (Abies balsamea) forests of the northeastern United States and southeastern Canada and wintering predominantly in wet, broadleaf primary forests of the Dominican Republic (Townsend et al. 2015). With a recent global population estimate of < 120,000, Bicknell’s Thrush likely have one of the smallest population sizes of any regularly occurring migratory songbird species within the contiguous U.S. and Canada (Hill and Lloyd 2017), and is considered one of the Nearctic-Neotropical migrants at greatest risk of extinction and thus of highest continental conservation concern (Rich et al. 2004, Wells 2007, Townsend et al. 2015). In the northeastern U.S., 95% of the breeding population is found above 805 m elevation in naturally fragmented “sky islands” of montane fir forest (Hill and Lloyd 2017). Similarly, on the nonbreeding grounds in the Dominican Republic, most of the occupied habitat is remote, montane forest that is naturally and anthropogenically fragmented (McFarland et al. 2013, 2018).
Recognized as a distinct species from the Gray-cheeked Thrush (Catharus minimus) only since 1995 (Monroe et al. 1995), no long-term demographic studies of Bicknell’s Thrush have yet been conducted. However, the reproductive output of Bicknell’s Thrush is known to vary with the cone cycle of balsam fir: the dominant tree species within Bicknell’s Thrush breeding habitat (McFarland and Rimmer 2002, Townsend et al. 2015). Balsam firs generally produce cones every other year, and this resource pulse appears to drive changes in populations of red squirrel (Tamiasciurus hudsonicus), a key predator on the nests of Bicknell’s Thrush and other montane bird species (Gurnell 1983, McFarland and Rimmer 2002, Strong et al. 2004). In mast years, balsam fir cones form in late spring and mature in August and early September (Frank 1990). Red squirrels move upslope into fir forests during mast years and store mature cones in middens during autumn, and the size of these middens is directly related to overwinter squirrel survival (Smith 1968, Rusch and Reeder 1978, McFarland and Rimmer 2002). The presence of this cached food source enables squirrels to persist within the fir forests into the following spring, which leads to substantially elevated rates of nest predation on Bicknell’s Thrush (McFarland and Rimmer 2002, Townsend et al. 2015). In contrast, when mature fir cones are not present during the autumn and subsequent spring, red squirrels likely emigrate downslope to mixed hardwood stands and may be entirely absent from fir forests during the breeding period of Bicknell’s Thrush in June and July (McFarland and Rimmer 2002, Townsend et al. 2015). It is conceivable that the altitudinal migration of red squirrels, and subsequent changes to the predation risk of nests and adults, directly influences the interannual site fidelity and true survival of Bicknell’s Thrush (Jason M. Hill and Kent P. McFarland, personal observations).
A better understanding of long-term trends in vital rates is key to ongoing efforts to craft a conservation strategy given current and forecasted threats to the species, which include loss of habitat and altered interspecific interactions due to climate change, deforestation on the wintering grounds, and incompatible forestry practices (e.g., precommercial thinning) on the breeding grounds (Lloyd and McFarland 2017). Analyses that describe patterns of change in demography will yield insight into the factors that may limit population growth in the species, in turn allowing for a more effective targeting of conservation actions. The Conservation Action Plan for Bicknell’s Thrush (Lloyd and McFarland 2017) identifies numerous actions on the breeding and wintering grounds that may help stem population declines and promote recovery of the species, yet at present the empirical data needed to prioritize among these actions are lacking. As a consequence, it remains unclear whether, for example, limited resources are best invested in reducing deforestation on the wintering grounds or increasing the amount of suitable breeding habitat. Delivering effective and efficient conservation depends on knowing when, where, and by which factors populations are limited (Marra et al. 2015).
We take advantage of a long-term demographic monitoring project of one breeding population of Bicknell’s Thrush in Vermont to test a series of hypotheses about the factors that limit survival and thus potentially influence rates of population growth (Fig. 1). We focused on putatively important factors operating on the breeding and wintering grounds, including the cyclical population dynamics of a nest predator (red squirrel, Sciurus vulgaris), and weather effects on food abundance on the breeding and wintering grounds (Table 1). Each of these factors has been proposed as potentially limiting population size of migratory songbirds in general, or Bicknell’s Thrush in particular.
Mt. Mansfield (44˚32′38.21″ N, 72˚48′51.52″ W, 1338 m) is the tallest peak in Vermont and has been a site for investigation into montane forest bird ecology for > 30 years. Vegetation is dominated by balsam fir, with interspersed red spruce (Picea rubra), heart-leafed paper birch (Betula cordifolia) and mountain ash (Sorbus spp.). Like other montane forests throughout the range of Bicknell’s Thrush, the dense vegetation is stunted by chronic exposure to high winds and heavy winter ice loads (Richardson et al. 2004; McFarland, Lambert, Rimmer, et al., unpublished data).
Adult thrush were passively captured in an array of static mist nets (44˚31′42.53″ N, 72˚48′56.39″ W, ~1170 m) below the summit of Mt. Mansfield in an area of ~25 ha; net locations did not change between years. We strived to open nets a minimum of 1-2 days every week in June and July from 2001 through 2015 (i.e., 14 annual survival periods, and 15 primary capture-mark-recapture periods); annual differences in field crew size and net closures because of rain and high winds resulted in substantial variation in net hours (one 12-m net open for one hour) across years (range = 158.4 to 1541.0 net hours). We outfitted each thrush with a uniquely numbered USGS aluminum leg band and sexed adult thrushes according to Pyle (1997).
We fit Cormack-Jolly-Seber (CJS) models within program MARK to estimate the probabilities of apparent annual survival (Φ, probability of remaining alive and remaining within the study area) and recapture (ρ) from our live-encounter banding records; as is standard for CJS models, adult thrushes newly captured in 2015 (the last primary period) were not included in our modeling effort (Cormack 1964, Jolly 1965, Seber 1965, White and Burnham 1999). Goodness-of-fit tests, including for overdispersion, conducted with the R package R2ucare (Gimenez et al. 2018, R Core Team 2019), suggested that our data were appropriate for CJS models (Pradel et al. 2005). We considered total net hours (a measure of netting effort) across June and July (2002-2015) as our only covariate modeling recapture probability. The remaining covariates represented processes, during the breeding and wintering periods that we hypothesized to affect Bicknell’s Thrush apparent survival (Table 1). Although mortality during migration likely has important effects on survival (Newton 2006), we lack important pieces of information about Bicknell’s Thrush migration (e.g., location of key stopover areas) that would allow us to include covariates (e.g., severity of weather during migration) describing this part of the species’ life cycle in our models. We measured Pearson’s correlation between all nonbinary covariates prior to our model selection procedure; all correlation coefficients were less than an absolute value of 0.52.
We predicted higher male apparent survival because male Bicknell’s Thrush tend to be physically larger and have longer lifespans than females (Townsend et al. 2015). A previous examination of Bicknell’s Thrush banding data noted relatively low site fidelity for adults initially captured in their second year (i.e., SY birds; McFarland, unpublished data). However, we did not have estimates of age (or individual covariates describing bird condition) for all thrushes in our dataset. We predicted, therefore, that site fidelity (a component of apparent survival) would be lowest for birds following their initial capture.
The balsam fir cone cycle is highly synchronous among mountains in the Northeast and is best described by a boom and bust pattern: in “mast years” > 75% of firs typically produce cones whereas < 1% of firs produce cones in nonmast years (McFarland and Rimmer 2002). Since 1994, we have annually collected fir mast data within our study area on Mt. Mansfield using visual surveys conducted June-September (McFarland and Rimmer 2002; McFarland, unpublished data). Mature cones in autumn of yeart predict relatively low reproductive success at that location in the breeding season of yeart+1 (McFarland and Rimmer 2002). It is conceivable, therefore, that Bicknell’s Thrush use the presence of mature cones during August and September (prior to autumn migration in early October) to gauge the probability of breeding success at that location in the following year (sensu Danchin et al. 2004, Thomson et al. 2006, Townsend et al. 2015). Alternatively, nesting failures in yeart may increase survival rate by reducing parental investment costs (Santos and Nakagawa 2012).
We examined the effects of weather on apparent survival of Bicknell’s Thrush in multiple ways. We estimated mean monthly temperature (˚C) for the winter (December-March) between primary periods on Mt. Mansfield because relatively warm winters in Vermont may be associated with increased availability and abundance of invertebrate prey (Bowles et al. 2002) when thrush return in May (Townsend et al. 2015). Birds returning to areas of relatively low food density may be more likely to permanently emigrate away from their former breeding sites (Tye 1992). We acquired global summary of the month (GSOM) climate data from the Mt. Mansfield National Oceanic and Atmospheric Administration (NOAA) Station (station ID: GHCND:USC00435416; 44˚31′29.31″ N, 72˚48′55.42″ W, 1204 m; https://www.ncdc.noaa.gov/cdo-web/datasets).
To model the effect of ENSO on avian apparent survival, we used the ENSO precipitation index (ESPI): a remotely-sensed measurement of atmospheric circulation and precipitation patterns. Positive ESPI values are associated with the El Niño (warm) phase of the ENSO cycle and generally indicate above-normal winter temperatures and precipitation for the northern Caribbean (Giannini et al. 2000, 2001, National Weather Service 2018). We calculated mean monthly ESPI values for the winter (December-March) between primary periods.
We obtained NDVI data from within the Google Earth Engine and accessed MOD13Q1 NDVI data, which is calculated every 16 days at 250-meter resolution (Carroll et al. 2017). The NDVI ranges from -1 to 1, and typical vegetation values range from 0 (sparse and relatively brown vegetation) to 1 (dense and relatively green vegetation); negative values are typically associated with water features (Carroll et al. 2017). We calculated mean monthly NDVI values from December through March across the predicted Bicknell’s Thrush range within the Dominican Republic (McFarland et al. 2013).
We also directly estimated winter precipitation within the winter range of Bicknell’s Thrush in the Dominican Republic (McFarland et al. 2013). We used CHIRPS (Climate Hazards Group InfraRed Precipitation) daily precipitation data from the Climate Hazards Group within ArcGIS (ESRI 2018). Climate Hazards Group InfraRed Precipitation is a global rainfall dataset, from 1981 to present, which combines satellite imagery with weather station data to predict daily rainfall at 0.05˚ x 0.05˚ spatial resolution (Funk et al. 2014, 2015). We calculated the mean monthly rainfall from December through March between each primary period; this four-month period corresponds with the driest period of the year for much of the Caribbean (Faaborg et al. 1984, Studds and Marra 2011). We included covariates for both ESPI and CHIRPS in our candidate models because they were weakly and nonsignificantly correlated (r = 0.35, P = 0.23) and assessed climate at different scales.
We used a hierarchical modeling approach to identify the parsimonious structure and covariates of Φ and ρ using Akaike’s information criterion corrected for small sample size (AICc; Sugiura 1978, Burnham and Anderson 2002, Hill and Diefenbach 2013, 2014). We started with a general model in which apparent survival and recapture probabilities varied by sex and time (i.e., Φ(sex + time), ρ(sex + time)). We selected the parsimonious recapture structure from four candidate models (constant, time-varying, constant by sex, and time-varying by sex). We then added the net hours covariates to the parsimonious p structure and retained it if it improved (i.e., lowered the AICc of) the model. We then identified the parsimonious survival structure from four candidate models (constant, time-varying, constant by capture cohort, and constant by sex). The resulting model was used to assess the explanatory power of the remaining apparent survival covariates.
We assessed the relative importance of our five environmental covariates on apparent survival by calculating the R2_Dev statistic (Skalski 1996, Grosbois et al. 2008). The R2_Dev statistic measures the proportion of variation in survival explained by the addition of a covariate compared to models with constant and year-varying survival. The recapture structure was kept the same among the models used to calculate the R2_Dev statistic (Santisteban et al. 2012). From the parsimonious model without apparent survival covariates, we added a single environmental covariate. We considered each covariate biologically informative if it explained > 20% of the temporal variation in apparent survival (Grosbois et al. 2008). We calculated model-averaged estimates ± unconditional SE (Powell 2007) from the parsimonious model without covariates and any model with a biologically informative covariate.
From 2001 through 2014, we captured 178 (50 female and 128 male) adult Bicknell’s Thrush on Mt. Mansfield, Vermont; the mean recapture rate was 0.69 between 2002 and 2015, and 59% of adult thrush (n = 105) were never recaptured. The number of net hours (median = 601.00 net hours, interquartile range or IQR = 415.38-1191.81) increased substantially over the years, and recapture probability (ρ = 0.52, SE = 0.05, 95% CI: 0.42, 0.61) increased with the number of net hours (β = 0.38, SE = 0.20, 95% CI: -0.00, 0.76). Recapture probability was lowest in 2004 (ρ = 0.40), the year with fewest net hours (158.38), and it was highest in 2014 (ρ = 0.67), the year with the greatest netting effort (1541.00 net hours). Models including sex-specific or time-variant probabilities of apparent survival and recapture were not well supported (Table 2).
Contrary to our expectations, NDVI, winter rainfall, and Vermont winter temperatures were not biologically informative predictors of Bicknell’s Thrush annual apparent survival (Table 3; Φ = 0.61 ± 0.03, 95% CI: 0.54, 0.68). Our model selection process indicated that fir mast status and the ENSO precipitation index (ESPI) both explained 29% of the temporal variation in apparent survival. Contrary to our hypothesis, however, apparent survival was greater (β = 0.86 ± 0.39, 95% CI: 0.10, 1.63) following mast years (Φ = 0.67 ± 0.06, 95% CI: 0.55, 0.79) compared to after nonmast years (Φ = 0.56 ± 0.06, 95% CI: 0.43, 0.68). Annual apparent survival was also higher when conditions were relatively wet on the nonbreeding grounds, but only as measured via ESPI (β = 0.55 ± 0.26, 95% CI: 0.04, 1.05) and not local rainfall (CHIRPS, β = 0.03 ± 0.02, 95% CI: -0.004, 0.07) or NDVI (β = -0.002 ± 0.002, 95% CI: -0.007, 0.001). Annual variation in NDVI within predicted habitat for Bicknell’s Thrush was muted, ranging from a low of 0.71 in 2000 to a high of 0.78 in 2014 and 2015 (median = 0.77, IQR = 0.77-0.78; Fig. 2). In our dataset, Vermont winter temperatures (β = 0.27 ± 0.16, 95% CI: -0.04, 0.58) was not strongly or significantly correlated with the El Niño-Southern Oscillation precipitation index (r = -0.20, P = 0.50).
Our research provides the most comprehensive examination of the effects of weather and other potentially limiting factors on Bicknell’s Thrush demographics to date, and our analysis yielded insight into the factors driving variation in annual apparent survival of this species. Bicknell’s Thrush apparent survival was relatively stable (median Φ = 0.61, IQR: 0.56-0.66) over our 15-year study, which mirrors the stable population trends of this species in Vermont (Hill and Lloyd 2017). These apparent survival estimates were remarkably similar to mean apparent survival estimates (0.56-0.75) reported for five other North American thrush (Turdidae species) species (Powell et al. 2000, Gardali et al. 2003, DeSante and Saracco 2009, Evans et al. 2011). In our study, Bicknell’s Thrush’ apparent survival was parsimoniously predicted by variation in seasonal resource pulses, namely masting by balsam fir.
Resource pulses, such as periodic mast production, are a common feature of many terrestrial ecosystems. In temperate and boreal forests, mast may play a keystone role in structuring community dynamics through interactions across trophic levels (Ostfeld and Keesing 2000). There is a predictable link between mast abundance and apparent survival in birds when mast is directly consumed by the birds. For example, spring temperature is negatively associated with serotinous Rocky Mountain lodgepole pine (Pinus contorta var. latifolia) cone availability in the Rocky Mountains; as spring temperatures have increased, the resulting decline in cone production has likely driven declines in adult survival and a 60% decline in the population of South Hills Crossbills (Loxia curvirostra complex) over a five-year period (Santisteban et al. 2012). However, pulsed resources often initiate far-reaching cascades of direct and indirect effects that permeate through food webs and exert pronounced population effects as well; these effects have been documented among songbird and rodent populations in a variety of forest communities including temperate deciduous forests dominated by oak (Quercus spp.; McShea 2000, Schmidt and Ostfeld 2003, Clotfelter et al. 2007), southern beech (Nothofagaus spp.; King 1983, White and King 2006), sugar maple (Acer saccharum; Fiola et al. 2017), European hornbeam (Carpinus betulus; Jędrzejewska and Jędrzejewska 1999), and boreal and montane fir forests (Messaoud et al. 2007, Townsend et al. 2015).
Masting, a primary resource pulse, is often followed by a secondary pulse that emerges as mast-consuming small mammal populations increase in response to abundant seeds. Tertiary resource pulses may subsequently result as predators respond to increases in their rodent or avian prey base (Dunn 1977, Jędrzejewska and Jędrzejewska 1999, McShea 2000, Fiola et al. 2017) as is likely the case for Bicknell’s Thrush (McFarland and Rimmer 2002, this study). Cascading secondary and tertiary resource pulses can substantially affect songbird populations through decreased productivity (McFarland and Rimmer 2002, Schmidt and Ostfeld 2003, Fiola et al. 2017) and reduced juvenile and adult survivorship (Schmidt 2003).
In our study, fir mast indirectly influenced adult Bicknell’s Thrush apparent survival (likely site fidelity, specifically), which was ~11% higher following mast years than nonmast years. These results do not support our hypothesis that the presence of mature cones in the autumn of mast years influences site fidelity in Bicknell’s Thrush. Given our results, adult Bicknell’s Thrush site fidelity may be more strongly influenced by prior nesting success as opposed to future predation risk. Indeed, prior nesting success is a reliable predictor of site fidelity for many species, including Prothonotary Warbler (Protonotaria citrea), Bobolink (Dolichonyx oryzivorus), Brown Thrasher (Toxostoma rufum), and American Robin (Turdus migratorius; Blancher and Robertson 1985, Bollinger and Gavin 1989, Haas 1998, Hoover 2003). Following mast years, red squirrel relative abundance is typically high throughout the fir zone, because > 75% of fir trees produce mast during mast years; this allows red squirrels to build large middens, resulting in higher overwinter survival and a subsequent decrease in songbird reproductive success in the following spring (Smith 1968, Rusch and Reeder 1978, McFarland and Rimmer 2002; Mountain Birdwatch 2.0 https://knb.ecoinformatics.org/view/doi:10.5063/F1XW4H49). Therefore, Bicknell’s Thrush may simply be unable to mitigate the risk of nest predation by red squirrels by emigrating elsewhere.
Vegetation greenness (NDVI) within predicted winter habitat in the Dominican Republic, which we expected would reflect increased food availability (Wilson et al. 2011), was not an important covariate of apparent survival in Bicknell’s Thrush. This lack of a relationship is likely in part a consequence of the low interannual variability of NDVI estimates within Bicknell’s Thrush winter habitat. In addition, the positive relationship between NDVI and rainfall, presumably the mechanism linking NDVI to increased food availability and increased survival of birds, disappears when annual precipitation exceeds ~1200 mm (Nicholson et al. 1990). Above this level, additional rainfall produces only minimal gains in NDVI. Nearly all of the areas considered potential winter habitat for Bicknell’s Thrush in the Dominican Republic receive > 1300 mm of precipitation annually (Izzo et al. 2010), suggesting that NDVI is likely a poor indicator of interannual variation in weather conditions that might influence the survival of Bicknell’s Thrush by regulating food availability.
Indeed, when examining variation in rainfall via a more direct index, EPSI, we found that Bicknell’s Thrush apparent survival increased during relatively wet winters on the wintering grounds. Thus our results are in keeping with other research that has demonstrated a positive relationship between rainfall and apparent survival of migratory birds (Peach et al. 1991, Sillett et al. 2000, Rockwell et al. 2017). The presumed mechanism underlying this relationship is that food availability is lower for migrants during dry years, leaving them in poorer condition and at greater risk of mortality during the nonbreeding season or spring migration (Strong and Sherry 2000, Marra and Holmes 2001, Smith et al. 2010). For Bicknell’s Thrush, this would imply a positive relationship between precipitation and the availability of either fruit or insects (Townsend et al. 2012).
Although rainfall clearly plays a key role in seasonal patterns of abundance for many species (Wolda 1978) and contributes to spatial variation in insect abundance and diversity (Janzen and Schoener 1968), correlations between interannual variation in precipitation and insect abundance are rarely documented (but see Hawkins and Holyoak 1998). Indeed, most of the evidence for moisture as a driver of food availability for migrant birds comes from comparisons among habitats (e.g., Smith et al. 2010) or within seasons (e.g., Strong and Sherry 2000). Similarly, long-term patterns in fruit production by tropical trees and shrubs are poorly known, but are not consistently linked to variation in rainfall (Polansky and Boesch 2013). Thus, although our results demonstrate a positive effect of winter rainfall on Bicknell’s Thrush apparent survival, we suggest that the underlying mechanism is uncertain. Future work might profitably focus on quantifying the influence of interannual variation in rainfall on fruit production and insect abundance within the winter range of Bicknell’s Thrush.
Our understanding of Bicknell’s Thrush population dynamics would likely be improved by measuring the factors (e.g., food availability and habitat quality) that directly affect Bicknell’s Thrush survival and site fidelity, especially during the nonbreeding period. Improved knowledge of migratory connectivity patterns and local habitat use outside of the breeding grounds would also potentially allow researchers to use covariates of finer spatial resolutions than the regional (e.g., CHIRPS rainfall data) and global (e.g., ESPI) covariates used in our study. With the majority of Bicknell’s Thrush overwintering in the Dominican Republic, it will be critically important to understand how this species is affected by the conversion of forest to agricultural field, likely the primary driver of forest loss within the nonbreeding range of Bicknell’s Thrush (McFarland et al. 2013, Curtis et al. 2018). Between 2000 and 2016, cloud forest and moist broadleaf forest in the Dominican Republic, likely the two most important types of forest on the wintering grounds for Bicknell’s Thrush (McFarland et al. 2013), declined by 5.9% and 8.9%, respectively (Lloyd and Leon, unpublished data). Deforestation on the nonbreeding grounds has been linked to declines of Wood Thrush (Hylocichla mustelina) in Central America (Taylor and Stutchbury 2016) and Golden-winged Warblers (Vermivora chrysoptera) in northern South America (Kramer et al. 2018), but our annual apparent survival estimates are likely too imprecise to detect any comparable trend in apparent survival. With Haiti’s primary forests now almost completely vanished (Hedges et al. 2018), conservation of remaining broadleaf forests in the Dominican Republic take on additional significance for Bicknell’s Thrush.
We extend sincere thanks to the many banders and net checkers who assisted us on Mt. Mansfield over the decades. Stowe Mountain Resort provided invaluable logistical support. We thank the ESRI Conservation GIS Program for software and support. We are grateful to funders of this work, including the Thomas Marshall Foundation, the USDA Forest Service Northeast Research Station, the U.S. Fish and Wildlife Service, the Forest Ecosystem Monitoring Cooperative, and trustees and friends of the Vermont Center for Ecostudies and the Vermont Institute of Natural Science. Anonymous reviewers improved the quality and content of our manuscript, thank you.
Baillie, S. R., and W. J. Peach. 1992. Population limitation in Palaearctic-African migrant passerines. Ibis 134:120-132. https://doi.org/10.1111/j.1474-919X.1992.tb04742.x
Bell, G. D., and M. Chelliah. 2006. Leading tropical modes associated with interannual and multidecadal fluctuations in North Atlantic hurricane activity. Journal of Climate 19:590-612. https://doi.org/10.1175/JCLI3659.1
Blancher, P. J., and R. J. Robertson. 1985. Site consistency in Kingbird breeding performance: implications for site fidelity. Journal of Animal Ecology 54:1017-1027. https://doi.org/10.2307/4394
Bollinger, E. K., and T. A. Gavin. 1989. The effects of site-quality on breeding site fidelity in Bobolinks. Auk 106:584-594.
Bowles, D. J., P. J. Lillford, D. A. Rees, I. A. Shanks, and J. S. Bale. 2002. Insects and low temperatures: from molecular biology to distributions and abundance. Philosophical Transactions of the Royal Society of London B: Biological Sciences 357:849-862. https://doi.org/10.1098/rstb.2002.1074
Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Springer, New York, New York, USA.
Carroll, M. L., C. M. DiMiceli, R. A. Sohlberg, and J. R. G. Townsend. 2017. 250m MODIS Normalized Difference Vegetation Index. Data coverage: 2001-2014, 250ndvi28920033435, Collection 4. University of Maryland, College Park, Maryland, USA.
Clotfelter, E. D., A. B. Pedersen, J. A. Cranford, N. Ram, E. A. Snajdr, V. Nolan, Jr., and E. D. Ketterson. 2007. Acorn mast drives long-term dynamics of rodent and songbird populations. Oecologia 154:493-503. https://doi.org/10.1007/s00442-007-0859-z
Cormack, R. M. 1964. Estimates of survival from the sighting of marked animals. Biometrika 51:429-438. https://doi.org/10.1093/biomet/51.3-4.429
Curtis, P. G., C. M. Slay, N. L. Harris, A. Tyukavina, and M. C. Hansen. 2018. Classifying drivers of global forest loss. Science 361:1108-1111. https://doi.org/10.1126/science.aau3445
Curtis, S., and R. Adler. 2000. ENSO indices based on patterns of satellite-derived precipitation. Journal of Climate 13:2786-2793. https://doi.org/10.1175/1520-0442(2000)013<2786:EIBOPO>2.0.CO;2
Danchin, É., L.-A. Giraldeau, T. J. Valone, and R. H. Wagner. 2004. Public information: from nosy neighbors to cultural evolution. Science 305:487-491. https://doi.org/10.1126/science.1098254
DeSante, D. F., and J. F. Saracco. 2009. Power of the MAPS program to detect differences and trends in survival and a vision for program expansion. Bird Populations 9:42-75. [online] URL: https://pdfs.semanticscholar.org/5501/763df4f23b986f5467d15e28f3a9eb694576.pdf?_ga=2.97585631.1329872288.1572022409-1996130432.1572022409
Dunn, E. 1977. Predation by weasels (Mustela nivalis) on breeding tits (Parus spp.) in relation to the density of tits and rodents. Journal of Animal Ecology 46:633-652. https://doi.org/10.2307/3835
Environmental Systems Research Institute (ESRI). 2018. ArcGIS desktop release 10.6.1. Environmental Systems Research Institute, Redlands, California, USA.
Evans, M., E. Gow, R. R. Roth, M. S. Johnson, and T. J. Underwood. 2011. Wood Thrush (Hylocichla mustelina), version 2.0. In A.F. Poole, editor. The birds of North America. Cornell Lab of Ornithology, Ithaca, New York, USA. https://doi.org/10.2173/bna.246
Faaborg, J., W. J. Arendt, and M. S. Kaiser. 1984. Rainfall correlates of bird population fluctuations in a Puerto Rican dry forest: a nine year study. Wilson Bulletin 96:575-593. [online] URL: https://sora.unm.edu/sites/default/files/journals/wilson/v096n04/p0575-p0593.pdf
Fiola, M.-L., A. Vernouillet, and M.-A. Villard. 2017. Linking songbird nest predation to seedling density: sugar maple masting as a resource pulse in a forest food web. Ecology and Evolution 7:10733-10742. https://doi.org/10.1002/ece3.3581
Frank, R. M. 1990. Abies balsamea (L.) Mill. Page 877 in R. M. Burns, editor. Silvics of North America: 1. Conifers, Agriculture Handbook 654. U.S. Department of Agriculture, Forest Service., Washington, D.C., USA. [online] URL: https://www.srs.fs.usda.gov/pubs/misc/ag_654/volume_1/silvics_vol1.pdf
Funk, C. C., P. J. Peterson, M. F. Landsfeld, D. H. Pedreros, J. P. Verdin, J. D. Rowland, B. E. Romero, G. J. Husak, J. C. Michaelsen, and A. P. Verdin. 2014. A quasi-global precipitation time series for drought monitoring. U.S. Geological Survey Data Series 832. U.S. Geological Survey, Reston, Virginia, USA. https://dx.doi.org/10.3133/ds832
Funk, C., P. Peterson, M. Landsfeld, D. Pedreros, J. Verdin, S. Shukla, G. Husak, J. Rowland, L. Harrison, A. Hoell, and J. Michaelsen. 2015. The climate hazards infrared precipitation with stations-a new environmental record for monitoring extremes. Scientific Data 2:150066. https://doi.org/10.1038/sdata.2015.66
Gardali, T., D. C. Barton, J. D. White, and G. R. Geupel. 2003. Juvenile and adult survival of Swainson’s Thrush (Catharus ustulatus) in coastal California: annual estimates using capture-recapture analyses. Auk 120:1188-1194.
Giannini, A., M. A. Cane, and Y. Kushnir. 2001. Interdecadal changes in the ENSO teleconnection to the Caribbean region and the North Atlantic Oscillation. American Meteorological Society 14:2867-2879. https://doi.org/10.1175/1520-0442(2001)014<2867:icitet>2.0.co;2
Giannini, A., Y. Kushnir, and M. A. Cane. 2000. Interannual variability of Caribbean rainfall, ENSO, and the Atlantic Ocean. Journal of Climate 13:297-311. https://doi.org/10.1175/1520-0442(2000)013<0297:IVOCRE>2.0.CO;2
Gimenez, O., J.-D. Lebreton, R. Choquet, and R. Pradel. 2018. R2ucare: an R package to perform goodness-of-fit tests for capture-recapture models. Methods in Ecology and Evolution 9:1749-1754. https://doi.org/10.1111/2041-210X.13014
Gordo, O. 2007. Why are bird migration dates shifting? A review of weather and climate effects on avian migratory phenology. Climate Research 35:37-58. https://doi.org/10.3354/cr00713
Grosbois, V., O. Gimenez, J.-M. Gaillard, R. Pradel, C. Barbraud, J. Clobert, A. P. Møller, and H. Weimerskirch. 2008. Assessing the impact of climate variation on survival in vertebrate populations. Biological Reviews 83:357-399. https://doi.org/10.1111/j.1469-185X.2008.00047.x
Gurnell, J. 1983. Squirrel numbers and the abundance of tree seeds. Mammal Review 13:133-148. https://doi.org/10.1111/j.1365-2907.1983.tb00274.x
Haas, C. A. 1998. Effects of prior nesting success on site fidelity and breeding dispersal: an experimental approach. Auk 115:929-936. https://doi.org/10.2307/4089511
Hawkins, B. A., and M. Holyoak. 1998. Transcontinental crashes of insect populations? American Naturalist 152:480-484. https://doi.org/10.2307/2463478
Hedges, S. B., W. B. Cohen, J. Timyan, and Z. Yang. 2018. Haiti’s biodiversity threatened by nearly complete loss of primary forest. Proceedings of the National Academy of Sciences 115:11850-11855. https://doi.org/10.1073/pnas.1809753115
Hill, J. M., and D. R. Diefenbach. 2013. Experimental removal of woody vegetation does not increase nesting success or fledgling production in two grassland sparrows (Ammodramus) in Pennsylvania. Auk 130:764-773. https://doi.org/10.1525/auk.2013.12240
Hill, J. M., and D. R. Diefenbach. 2014. Occupancy patterns of regionally declining grassland sparrow populations in a forested Pennsylvania landscape. Conservation Biology 28:735-744. https://doi.org/10.1111/cobi.12210
Hill, J. M., and J. D. Lloyd. 2017. A fine-scale U.S. population estimate of a montane spruce-fir bird species of conservation concern. Ecosphere 8:e01921. https://doi.org/10.1002/ecs2.1921
Holmgren, M., M. Scheffer, E. Ezcurra, J. R. Gutiérrez, and G. M. J. Mohren. 2001. El Niño effects on the dynamics of terrestrial ecosystems. Trends in Ecology and Evolution 16:89-94. https://doi.org/10.1016/S0169-5347(00)02052-8
Hoover, J. P. 2003. Decision rules for site fidelity in a migratory bird, the prothonotary warbler. Ecology 84:416-430. https://doi.org/10.1890/0012-9658(2003)084[0416:DRFSFI]2.0.CO;2
Izzo, M., C. M. Rosskopf, P. P. C. Aucelli, A. Maratea, R. Méndez, C. Pérez, and H. Segura. 2010. A new climatic map of the Dominican Republic based on the Thornthwaite classification. Physical Geography 31:455-472. https://doi.org/10.2747/0272-36126.96.36.1995
Janzen, D. H., and T. W. Schoener. 1968. Differences in insect abundance and diversity between wetter and drier sites during a tropical dry season. Ecology 49:96-110. https://doi.org/10.2307/1933565
Jędrzejewska, B., and W. Jędrzejewska. 1999. Predation in vertebrate communities: the Białowieża Primeval Forest as a case study. Ecological Studies series, 135. Springer, Berlin, Germany. [online] URL: https://link.springer.com/content/pdf/bfm%3A978-3-662-35364-6%2F1.pdf
Jepsen, J. U., S. B. Hagen, K. A. Høgda, R. A. Ims, S. R. Karlsen, H. Tømmervik, and N. G. Yoccoz. 2009. Monitoring the spatio-temporal dynamics of geometrid moth outbreaks in birch forest using MODIS-NDVI data. Remote Sensing of Environment 113:1939-1947. https://doi.org/10.1016/j.rse.2009.05.006
Jolly, G. M. 1965. Explicit estimates from capture-recapture data with both death and immigration-stochastic model. Biometrika 52:225-248. https://doi.org/10.1093/biomet/52.1-2.225
King, C. M. 1983. The relationships between beech (Nothofagus spp.) seedfall and populations of mice (Mus musculus), and the demographic and dietary responses of stoats (Mustela erminea), in three New Zealand forests. Journal of Animal Ecology 52:141-166. https://doi.org/10.2307/4593
Kramer, G. R., D. E. Andersen, D. A. Buehler, P. B. Wood, S. M. Peterson, J. A. Lehman, K. R. Aldinger, L. P. Bulluck, S. Harding, J. A. Jones, J. P. Loegering, C. Smalling, R. Vallender, and H. M. Streby. 2018. Population trends in Vermivora warblers are linked to strong migratory connectivity. Proceedings of the National Academy of Sciences 115:E3192-E3200. https://doi.org/10.1073/pnas.1718985115
Lassau, S. A., and D. F. Hochuli. 2008. Testing predictions of beetle community patterns derived empirically using remote sensing. Diversity and Distributions 14:138-147. https://doi.org/10.1111/j.1472-4642.2007.00438.x
Lloyd, J. D., and K. P. McFarland. 2017. A conservation action plan for Bicknell’s Thrush (Catharus bicknelli). International Bicknell’s Thrush Conservation Group (IBTCG), Woodstock, Vermont, USA. [online] URL: http://bicknellsthrush.org/conservation-action-plan/conservation-action-plan-for-bicknells-thrush
Marra, P. P., E. B. Cohen, S. R. Loss, J. E. Rutter, and C. M. Tonra. 2015. A call for full annual cycle research in animal ecology. Biology Letters 11:20150552. https://doi.org/10.1098/rsbl.2015.0552
Marra, P. P., and R. L. Holberton. 1998. Corticosterone levels as indicators of habitat quality: effects of habitat segregation in a migratory bird during the non-breeding season. Oecologia 116:284-292. https://doi.org/10.1007/s004420050590
Marra, P. P., and R. T. Holmes. 2001. Consequences of dominance-mediated habitat segregation in American Redstarts during the nonbreeding season. Auk 118:92-104. https://doi.org/10.1093/auk/118.1.92
McFarland, K. P., J. D. Lloyd, S. J. K. Frey, P. L. Johnson, R. B. Chandler, and C. C. Rimmer. 2018. Modeling spatial variation in winter abundance to direct conservation actions for a vulnerable migratory songbird, the Bicknell’s Thrush (Catharus bicknelli). Condor 120:517-529. https://doi.org/10.1650/CONDOR-17-234.1
McFarland, K. P., and C. C. Rimmer. 2002. The relationship between cone mast, red squirrel populations and migratory songbird demographics in montane fir forests. 2001 Report to the Vermont Monitoring Cooperative.Vermont Institute of Natural Science, Woodstock, Vermont, USA. [online] URL: https://www.uvm.edu/femc/attachments/project/999/reports/2001_Bird_Demographics_SquirrelCones_AnnualReport.pdf
McFarland, K. P., C. C. Rimmer, J. E. Goetz, Y. Aubry, J. M. Wunderle, Jr., A. Sutton, J. M. Townsend, A. L. Sosa, and A. Kirkconnell. 2013. A winter distribution model for Bicknell’s Thrush (Catharus bicknelli), a conservation tool for a threatened migratory songbird. PloS One 8:e53986. https://doi.org/10.1371/journal.pone.0053986
McShea, W. J. 2000. The influence of acorn crops on annual variation in rodent and bird populations. Ecology 81:228-238. https://doi.org/10.1890/0012-9658(2000)081[0228:TIOACO]2.0.CO;2
Messaoud, Y., Y. Bergeron, and H. Asselin. 2007. Reproductive potential of balsam fir (Abies balsamea), white spruce (Picea glauca), and black spruce (P. mariana) at the ecotone between mixedwood and coniferous forests in the boreal zone of western Quebec. American Journal of Botany 94:746-754. https://doi.org/10.3732/ajb.94.5.746
Møller, A. P. 1989. Population dynamics of a declining swallow Hirundo rustica L. population. Journal of Animal Ecology 58:1051-1063. https://doi.org/10.2307/5141
Monroe, Jr., B. L., R. C. Banks, J. W. Fitzpatrick, T. R. Howell, N. K. Johnson, H. Ouellet, J. V. Remsen, and R. W. Storer. 1995. Fortieth supplement to the American Ornithologists’ Union check-List of North American birds. Auk 112:819-830. [online] URL: https://sora.unm.edu/sites/default/files/journals/auk/v112n03/p0819-p0830.pdf
Morrison, R. I. G., N. C. Davidson, and J. R. Wilson. 2007. Survival of the fattest: body stores on migration and survival in Red Knots Calidris canutus islandica. Journal of Avian Biology 38:479-487. https://doi.org/10.1111/j.0908-8857.2007.03934.x
National Weather Service. 2018. ENSO effects across the northeastern Caribbean. National Weather Service, San Juan, Puerto Rico. [online] URL: https://www.weather.gov/sju/climo_enso
Newton, I. 1998. Population limitation in birds. Academic, Orlando, Florida, USA. https://doi.org/10.1016/B978-0-12-517365-0.X5000-5
Newton, I. 2006. Can conditions experienced during migration limit the population levels of birds? Journal of Ornithology 147:146-166. https://doi.org/10.1007/s10336-006-0058-4
Newton, I. 2007. Weather-related mass-mortality events in migrants. Ibis 149:453-467. https://doi.org/10.1111/j.1474-919X.2007.00704.x
Nicholson, S. E., M. L. Davenport, and A. R. Malo. 1990. A comparison of the vegetation response to rainfall in the Sahel and East Africa, using normalized difference vegetation index from NOAA AVHRR. Climatic Change 17:209-241. https://doi.org/10.1007/BF00138369
Ostfeld, R. S., and F. Keesing. 2000. Biodiversity series: the function of biodiversity in the ecology of vector-borne zoonotic diseases. Canadian Journal of Zoology 78:2061-2078. https://doi.org/10.1139/z00-172
Owen, M., and J. M. Black. 1989. Factors affecting the survival of Barnacle Geese on migration from the breeding grounds. Journal of Animal Ecology 58:603-617. https://doi.org/10.2307/4851
Peach, W., S. Baillie, and L. Underhill. 1991. Survival of British Sedge Warblers Acrocephalus schoenobaenus in relation to west African rainfall. Ibis 133:300-305. https://doi.org/10.1111/j.1474-919X.1991.tb04573.x
Peach, W. J., L. J. Lovett, S. R. Wotton, and C. Jeffs. 2001. Countryside stewardship delivers Cirl Buntings (Emberiza cirlus) in Devon, UK. Biological Conservation 101:361-373. https://doi.org/10.1016/S0006-3207(01)00083-0
Pettorelli, N., J. O. Vik, A. Mysterud, J.-M. Gaillard, C. J. Tucker, and N. C. Stenseth. 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution 20:503-510. https://doi.org/10.1016/j.tree.2005.05.011
Polansky, L., and C. Boesch. 2013. Long-term changes in fruit phenology in a west African lowland tropical rain forest are not explained by rainfall. Biotropica 45:434-440. https://doi.org/10.1111/btp.12033
Polis, G. A. 1997. El Niño effects on the dynamics and control of an island ecosystem in the Gulf of California. Ecology 78:1884-1897. https://doi.org/10.2307/2266109
Polis, G. A., S. D. Hurd, C. T. Jackson, and F. Sanchez-Piñero. 1998. Multifactor population limitation: variable spatial and temporal control of spiders on Gulf of California Island. Ecology 79:490-502. https://doi.org/10.1890/0012-9658(1998)079[0490:MPLVSA]2.0.CO;2
Powell, L. A. 2007. Approximating variance of demographic parameters using the delta method: a reference for avian biologists. Condor 109:949-954. https://doi.org/10.1093/condor/109.4.949
Powell, L. A., J. D. Lang, M. J. Conroy, and D. G. Krementz. 2000. Effects of forest management on density, survival, and population growth of Wood Thrushes. Journal of Wildlife Management 64:11-23. https://doi.org/10.2307/3802970
Pradel, R., O. Gimenez, and J.-D. Lebreton. 2005. Principles and interest of GOF tests for multistate capture-recapture models. Animal Biodiversity and Conservation 28.2:189-204. [online] URL: https://www.raco.cat/index.php/ABC/article/viewFile/56772/66542??
Pyle, P. 1997. Identification guide to North American birds, part I. Slate Creek, Bolinas, California, USA.
R Core Team. 2019. R: a language and environment for statistical computing. Version 3.6.1. R Foundation for Statistical Computing, Vienna, Austria. [online] URL: https://www.r-project.org/
Rich, T. D., C. J. Beardmore, H. Berlanga, P. J. Blancher, S. W. Bradstreet, G. S. Butcher, D. W. Demarest, E. H. Dunn, W. C. Hunter, E. E. Iñigo-Elias, J. A. Kennedy, A. M. Martell, A. O. Panjabi, D. N. Pashley, K. V. Rosenberg, C. M. Rustay, J. S. Wendt, and T. C. Will. 2004. Partners in Flight North American landbird conservation plan. Version: March 2005. Cornell Lab of Ornithology, Ithaca, New York, USA.
Richardson, A. D., X. Lee, and A. J. Friedland. 2004. Microclimatology of treeline spruce-fir forests in mountains of the northeastern United States. Agricultural and Forest Meteorology 125:53-66. https://doi.org/10.1016/j.agrformet.2004.03.006
Roberts, T. S. 1907a. A Lapland Longspur tragedy. Auk 24:369-377. [online] URL: https://sora.unm.edu/sites/default/files/journals/auk/v024n04/p0369-p0377.pdf
Roberts, T. S. 1907b. Supplemental note to “A Lapland Longspur tragedy.” Auk 24:449-450. [online] URL: https://sora.unm.edu/sites/default/files/journals/auk/v024n04/p0449-p0450.pdf
Rockwell, S. M., C. I. Bocetti, and P. P. Marra. 2012. Carry-over effects of winter climate on spring arrival date and reproductive success in an endangered migratory bird, Kirtland’s Warbler (Setophaga kirtlandii). Auk 129:744-752. https://doi.org/10.1525/auk.2012.12003
Rockwell, S. M., J. M. Wunderle, Jr., T. S. Sillett, C. I. Bocetti, D. N. Ewert, D. Currie, J. D. White, and P. P. Marra. 2017. Seasonal survival estimation for a long-distance migratory bird and the influence of winter precipitation. Oecologia 183:715-726. https://doi.org/10.1007/s00442-016-3788-x
Rusch, D. A., and W. A. Reeder. 1978. Population ecology of Alberta red squirrels. Ecology 59:400-420. https://doi.org/10.2307/1936382
Ryel, L. A. 1981. Population change in the Kirtland’s Warbler. Jack-Pine Warbler 59:76-91.
Saino, N., T. Szep, R. Ambrosini, M. Romano, and A. P. Møller. 2004. Ecological conditions during winter affect sexual selection and breeding in a migratory bird. Proceedings of the Royal Society of London B: Biological Sciences 271:681-686. https://doi.org/10.1098/rspb.2003.2656
Santisteban, L., C. W. Benkman, T. Fetz, and J. W. Smith. 2012. Survival and population size of a resident bird species are declining as temperature increases. Journal of Animal Ecology 81:352-363. https://doi.org/10.1111/j.1365-2656.2011.01918.x
Santos, E. S. A., and S. Nakagawa. 2012. The costs of parental care: a meta-analysis of the trade-off between parental effort and survival in birds. Journal of Evolutionary Biology 25:1911-1917. https://doi.org/10.1111/j.1420-9101.2012.02569.x
Schmidt, K. A. 2003. Linking frequencies of acorn masting in temperate forests to long-term population growth rates in a songbird: the Veery (Catharus fuscescens). Oikos 103:548-558. https://doi.org/10.1034/j.1600-0706.2003.12462.x
Schmidt, K. A., and R. S. Ostfeld. 2003. Songbird populations in fluctuating environments: predator responses to pulsed resources. Ecology 84:406-415. https://doi.org/10.1890/0012-9658(2003)084[0406:SPIFEP]2.0.CO;2
Seber, G. A. F. 1965. A note on the multiple-recapture census. Biometrika 52:249-259. https://doi.org/10.1093/biomet/52.1-2.249
Sillett, T. S., R. T. Holmes, and T. W. Sherry. 2000. Impacts of a global climate cycle on population dynamics of a migratory songbird. Science 288:2040-2042. https://doi.org/10.1126/science.288.5473.2040
Skalski, J. R. 1996. Regression of abundance estimates from mark-recapture surveys against environmental covariates. Canadian Journal of Fisheries and Aquatic Sciences 53:196-204. https://doi.org/10.1139/f95-169
Smith, A. G., and H. R. Webster. 1955. Effects of hail storms on waterfowl populations in Alberta, Canada: 1953. Journal of Wildlife Management 19:368-374. https://doi.org/10.2307/3797388
Smith, C. C. 1968. The adaptive nature of social organization in the genus of three squirrels Tamiasciurus. Ecological Monographs 38:31-64. https://doi.org/10.2307/1948536
Smith, J. A. M., L. R. Reitsma, and P. P. Marra. 2010. Moisture as a determinant of habitat quality for a nonbreeding Neotropical migratory songbird. Ecology 91:2874-2882. https://doi.org/10.1890/09-2212.1
Smith, K. G. 1982. Drought-induced changes in avian community structure along a montane sere. Ecology 63:952-961. http://doi.org/10.2307/1937235
Strong, A. M., C. C. Rimmer, and K. P. McFarland. 2004. Effect of prey biomass on reproductive success and mating strategy of Bicknell’s Thrush (Catharus bicknelli), a polygynandrous songbird. Auk 121:446-451.
Strong, A. M., and T. W. Sherry. 2000. Habitat-specific effects of food abundance on the condition of ovenbirds wintering in Jamaica. Journal of Animal Ecology 69:883-895. https://doi.org/10.1046/j.1365-2656.2000.00447.x
Studds, C. E., and P. P. Marra. 2011. Rainfall-induced changes in food availability modify the spring departure programme of a migratory bird. Proceedings of the Royal Society of London B: Biological Sciences 278:3437-3443. https://doi.org/10.1098/rspb.2011.0332
Sugiura, N. 1978. Further analysts of the data by Akaike’s information criterion and the finite corrections. Communications in Statistics - Theory and Methods 7:13-26. https://doi.org/10.1080/03610927808827599
Szép, T. 1995. Relationship between West African rainfall and the survival of Central European Sand Martins Riparia riparia. Ibis 137:162-168. https://doi.org/10.1111/j.1474-919X.1995.tb03235.x
Taylor, C. M., and B. J. M. Stutchbury. 2016. Effects of breeding versus winter habitat loss and fragmentation on the population dynamics of a migratory songbird. Ecological Applications 26:424-437. https://doi.org/10.1890/14-1410
Thomson, R. L., J. T. Forsman, F. Sardà-Palomera, and M. Mönkkönen. 2006. Fear factor: prey habitat selection and its consequences in a predation risk landscape. Ecography 29:507-514. https://doi.org/10.1111/j.0906-7590.2006.04568.x
Townsend, J. M., K. P. McFarland, C. C. Rimmer, W. G. Ellison, and J. E. Goetz. 2015. Bicknell’s Thrush (Catharus bicknelli). In A. J. Poole, editor. Birds of North America. Cornell Lab of Ornithology, Ithaca, New York, USA. https://birdsna.org/Species-Account/bna/species/bicthr/introduction
Townsend, J. M., C. C. Rimmer, K. P. Mcfarland, and J. E. Goetz. 2012. Site-specific variation in food resources, sex ratios, and body condition of an overwintering migrant songbird. Auk 129:683-690. https://doi.org/10.1525/auk.2012.12043
Tye, A. 1992. Assessment of territory quality and its effects on breeding success in a migrant passerine, the Wheatear Oenanthe oenanthe. Ibis 134:273-285. https://doi.org/10.1111/j.1474-919X.1992.tb03810.x
Wells, J. V. 2007. Birder’s conservation handbook: 100 North American birds at risk. Princeton University Press, Princeton, New Jersey, USA. https://doi.org/10.1515/9781400831517
White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46:S120-S139. https://doi.org/10.1080/00063659909477239
White, P. C. L., and C. M. King. 2006. Predation on native birds in New Zealand beech forests: the role of functional relationships between stoats Mustela erminea and rodents. Ibis 148:765-771. https://doi.org/10.1111/j.1474-919X.2006.00579.x
Wilson, S., S. L. LaDeau, A. P. Tøttrup, and P. P. Marra. 2011. Range-wide effects of breeding- and nonbreeding-season climate on the abundance of a Neotropical migrant songbird. Ecology 92:1789-1798. https://doi.org/10.1890/10-1757.1
Wolda, H. 1978. Seasonal fluctuations in rainfall, food and abundance of tropical insects. Journal of Animal Ecology 47:369-381. https://doi.org/10.2307/3789