Research Paper

INTRODUCTION

The Whooping Crane (Grus americana) is the rarest crane on earth and one of the rarest birds in North America and it is listed as “Endangered” in the USA, Canada, and by the International Union for Conservation of Nature (Canadian Wildlife Service (CWS) and U.S. Fish and Wildlife Service [USFWS] 2007, French et al. 2018, BirdLife International 2020, Urbanek and Lewis 2020). The Aransas-Wood Buffalo population (AWBP) of Whooping Cranes is the last remnant wild population of the species. It winters on the Texas coast on and around Aransas National Wildlife Refuge (NWR) and breeds on and around Wood Buffalo National Park in the Northwest Territories and Alberta, Canada (French et al. 2018, Urbanek and Lewis 2020). In the winter of 2022–2023, the AWBP was estimated at 536 (95% CI = 443.5-644.1) within the primary survey area on the wintering grounds (Butler et al. 2023). While on the wintering grounds, the AWBP primarily uses saltmarsh and bay habitat during the winter months (Stevenson and Griffith 1946, Allen 1952, Stehn and Prieto 2010, Smith et al. 2018). Within these estuarine habitats, they feed on blue crabs (Callinectes sapidus), Carolina wolfberry (Lycium carolinianum), snails (various Gastropoda spp.), clams (Bivalvia spp.), fish (Osteichthyes spp.), shrimp (Crustacea spp.), and other items (Allen 1952, Hunt and Slack 1989, Chavez-Ramirez 1996, Westwood and Chavez-Ramirez 2005). In addition to the estuarine habitats, wintering AWBP Whooping Cranes use grasslands, agricultural areas, and freshwater wetlands, and in these habitats, their diet includes acorns (Quercus spp.), crayfish (Cambarus spp.), grasshoppers (Orthoptera spp.), dragonfly/damselfly larvae (Odonata spp.), corn (Zea mays), wheat (Triticum spp.), sorghum (Sorghum bicolor), and other plant materials (Stevenson and Griffith 1946, Allen 1952, Chavez-Ramirez 1996). Sufficient foraging resources represent an essential component of quality habitat, but associated food webs can vary substantially by region, demonstrating the adaptive capacity of Whooping Cranes (Chavez-Ramirez 1996, Bergeson et al. 2001, Caven et al. 2021). Given the primary reliance of the AWBP on coastal or near coastal environments, it is unsurprising that most habitat models for the wintering grounds have been limited to areas near the coast (Metzger et al. 2020, Golden et al. 2022). Although AWBP Whooping Cranes have wintered nearly exclusively on the Texas coast since the late 1930s, their historic wintering range was more expansive, with some reports from more inland areas (Stevenson and Griffith 1946, Allen 1952, Austin et al. 2018).

In the winter months, it has been widely reported that Whooping Crane family groups defend territories (Stevenson and Griffith 1946, Allen 1952, Stehn and Johnson 1987). In 2006, the average territory was reported to be 2.1 km² (Stehn and Prieto 2010). However, Butler et al. (2022b) showed that Whooping Crane core use areas and home ranges were more expansive than the previously reported territories, with a core autocorrelated kernel density estimate (AKDE) area ranging from 0.4–107.2 km² (x̅ = 11.0 ± 17.1 [SD]) and a 95% AKDE area ranging from 1.1–308.6 km² (x̅ = 30.1 ± 45.2 [SD]).

Whooping Cranes in the re-introduced Eastern Migratory Population (EMP) have started using short-stopping migration strategies, and few birds are traveling to their initial wintering grounds (Teitelbaum et al. 2016, 2018, Mendgen et al. 2023). Although the EMP originally wintered primarily in Florida, the wintering areas began shifting northward in 2007–2008 (Urbanek et al. 2014, Teitelbaum et al. 2016, 2018). In the warm short winter of 2011–2012, many EMP cranes started wintering in Indiana (Urbanek et al. 2014, Fitzpatrick et al. 2018), and fewer than 10% of the population wintered as far south as Florida by the winter of 2013–2014 (Teitelbaum et al. 2018). Some evidence shows that habitat is available for the AWBP to allow for short-stopping, although the birds in this population have rarely used this strategy (Mendgen et al. 2023).

Although short-stopping has not been widely used in the AWBP, individuals and small groups, particularly juveniles, have been documented away from the Texas Coast during the winter (Stehn and Johnson 1987, Stehn 1992, 2009, 2010, Butler et al. 2020). In the winter of 2011–2012, as many as nine Whooping Cranes used Granger Lake, Texas, and surrounding agricultural areas, and birds were also reported in Kansas and Nebraska, USA (Wright et al. 2014). Since that winter, data have shown their use of the area in 2012–2013 and 2013–2014 (Harrell and Bidwell 2013, Pearse et al. 2020a, Jung et al. 2022). Furthermore, Whooping Cranes have been documented inland within Colorado and Wharton counties, Texas (Harrell and Bidwell 2013, Butler et al. 2020, 2022a, 2023).

Here, we summarize the continued use of inland areas by wintering AWBP Whooping Cranes. Throughout this paper, we use the term inland wintering birds to refer to birds that spent at least a portion of their winter in inland areas away from coastal habitats. We focus particularly on the Granger Lake area and Colorado/Wharton counties, where inland winter use by multiple birds over several years has been reported. Additionally, our objective was to compare space use and daily movements for birds using inland areas and more traditional coastal areas.

METHODS

Study area

This study took place in coastal and central Texas, USA. The birds on the coast primarily used Aransas, Refugio, and Calhoun counties, although there was use in additional coastal counties. Much of their space use is centered on Aransas NWR. Space use on the coast occurs primarily within or near the saltmarsh community dominated by salt grass (Distichlis spicata), saltwort (Batis maritima), smooth cordgrass (Spartina alterniflora), glasswort (Salicornia sp.), and bushy seaside tansy (Borrichia frutescens) but also included use of adjacent uplands (CWS and USFWS 2007, Butler et al. 2014). Birds in the Granger Lake area used Bell, Williamson, and Milam counties but flew over and stopped at additional counties between the coast and inland areas. Many of the locations were on or near Granger Lake, a United States Army Corps of Engineers Reservoir (Jung et al. 2022). Individuals also used surrounding agricultural areas, grazed pasture, and smaller wetlands (Wright et al. 2012). Corn, hay/haylage, cotton (Gossypium hirsutum), wheat (Triticum aestivum), and sorghum are the dominant crops in Bell, Milam, and Williamson counties (U.S. Department of Agriculture 2019). Granger Lake is ca. 270 km from Aransas NWR headquarters (Fig. 1) and ca. 219 km from the nearest estuarine/marine wetland (per Euclidean distance; U.S. Fish and Wildlife Service 2018). Granger Lake is within the AWBP 50% core area migration corridor, so individuals may be familiar with this area through migration (Pearse et al. 2018). Birds in Colorado/Wharton counties used the southern portion of Colorado County and the northern portion of Wharton County near Nada, Texas. A few points were in Lavaca County. These birds flew over additional counties between the coast and inland areas. Many of the locations were in agricultural and flooded agricultural areas (Butler et al. 2020, 2022a, 2023). Rice (Oryza sativa), hay/haylage, and corn are the dominant crops by acre in Colorado County (U.S. Department of Agriculture 2019). Cotton, corn, rice, hay/haylage, and sorghum are the dominant crops in Wharton County (U.S. Department of Agriculture 2019). The city of Nada is ca. 127 km from Aransas NWR headquarters and ca. 63 km from the nearest estuarine/marine wetland (U.S. Fish and Wildlife Service 2018). Nada, Texas is within the AWBP 75% core area migration corridor, so some individuals may be familiar with this area through migration (Pearse et al. 2018).

Data

Whooping Crane locational data from 2009 to 2018 was provided by Pearse et al. (2020a). A total of 68 Whooping Cranes were fitted with platform transmitting terminals (PTT; North Star Science and Technology LLC, Baltimore, Maryland, USA), which generally provided 4–5 locations for each crane daily via the Argos satellite system (Argos, Inc., Landover, Maryland, USA; Pearse et al. 2015, 2020a). Whooping Crane locations were examined for potential errors using several indicators, including deviation from expected time sequences, displacement rates exceeding 100 km/h, or movements forming acute angles <5 degrees across distances >50 km (Douglas et al. 2012, Pearse et al. 2015, 2020a). Additionally, we used unpublished data from inland wintering Whooping Cranes from winters of 2017–2018 to 2021–2022. These data were obtained through the International Whooping Crane Tracking Partnership led by CWS, Parks Canada Agency (PCA), the USFWS, and the U.S. Geological Survey. These Whooping Cranes were fitted with Global System for Mobiles (GSM) transmitters using third and fourth generation cellular networks (Ornitela, Vilnius, Lithuania). As the temporal resolution of these two data sources varied, we exclusively used data from Pearse et al. (2020a) to examine daily movements. Data from Pearse et al. (2020a) and unpublished transmitter data were employed for home range comparisons. Finally, all data were used to describe the frequency and occurrence of inland wintering behavior and to provide clarification to previously published research on this topic.

To document Whooping Crane use of inland wintering areas, we compiled information from eBird reports (eBird 2024), iNaturalist reports (iNaturalist 2023), USFWS annual survey reports (USFWS 2012, Harrell and Bidwell 2013, Butler et al. 2020, 2022a, 2023), Whooping Crane transmitter data (Pearse et al. 2020a and unpublished data), and personal communications or observations (Michael Forsberg, Michael A. Kalisek, and International Crane Foundation staff). We also summarized the number of individual Whooping Cranes that used the Granger Lake area and Colorado/Wharton counties each winter since the winter of 2011–2012. We only included accounts from 1 December–28/29 February to avoid reports of late or early migrating birds. We report the high counts for each area and winter. Where there was uncertainty regarding the number of individuals using an area, we noted it.

To summarize the use of inland areas by marked birds, we used transmitter data from Pearse et al. (2020a) as well as more recent unpublished transmitter data on inland wintering birds. We summarized the number of periods on the coast and at inland areas, the number of days on the coast each winter, the number of days using inland areas each winter, the total number of winter days, and the proportion of winter days that birds were using inland areas. Temporal data gaps were rare and were usually 1–2 d with one instance of 6 consecutive days. For data gaps between travel days, we counted those days as remaining in the area (coast or inland) they were in when the data gap began. For data gaps around travel periods, we used the first and last data available for those gaps. For instance, if a bird was on the coast on 29 December and the next data point was in an inland area on 31 December, we treated 29 December as the last day of the period on the coast and 31 December as the first day of the period in an inland area. We treated partial days of use as one day, so if a bird left the coast on 13 November and arrived at an inland area on 13 November, then we treated 13 November as the last day for that period on the coast and the first day for the period in an inland area. Due to this, the total number of days on the coast and the total number of days inland may add up to more than the total number of winter days.

We excluded a few individuals from various results and analyses. We excluded a juvenile Whooping Crane that wintered in Kansas with Sandhill Cranes (Antigone canadensis, Butler et al. 2020) from all results. One bird used the Granger Lake area for 3.1% of the winter, with its winter home range established exclusively on the coast; we excluded data from this individual this winter from our home range analyses but included it in other results and daily movement analyses. An additional inland wintering bird was not marked until February, so we did not include it in the home range analysis, as it did not have enough points to have a home range calculated in Butler et al. (2022b). Additionally, we excluded one juvenile with fewer days of data than its marked parent with similar movement patterns from both home range and daily movements analyses. Due to their unknown family status and the fact that we did not have any using inland wintering areas, we excluded adults with unknown family status from all analyses.

Statistical analyses

The distribution of each outcome variable employed in this study was assessed via multiple approaches to determine dispersion, skewness, and outliers. We evaluated outcome variable distributions using histograms of varying bin widths with the “ggplot2” package (Wickham 2016). We also used quantile-quantile (Q-Q) plots (Das and Rahmatullah Imon 2016) and the Shapiro-Wilk normality test to evaluate data distributions (Royston 1982) using the “stats” package (R Core Team 2020). We evaluated extreme values disjunct from larger data distributions using the Grubb’s test for outliers from the “outliers” package in program R (Grubbs 1950, Komsta 2011).

We obtained age and family status from Pearse et al. (2019) and Butler et al. (2022b), and banding, recapture, and resighting notes from the International Whooping Crane Tracking Partnership. We analyzed the data using the following ages and family status: family groups (juveniles assumed or known to be with adults, and adults known to be with juveniles), subadults (second and third winter birds), and adults (adults without juveniles).

We used 95% AKDE home range data from the winters of 2009–2010 to 2017–2018 from Butler et al. (2022b). Additionally, we calculated 95% AKDE home ranges (Fleming and Calabrese 2017) for two inland wintering individuals across four crane winters (data from an individual crane within one winter) from 2017–2018 to 2021–2022 using the methods of Butler et al. (2022b). The use of AKDEs and continuous-time stochastic processes allow for comparison of this home range data to home range data with less frequent location points (Noonan et al. 2019). We compared 95% AKDE areas for Whooping Cranes detected wintering inland as well as those that wintered in coastal habitats using a two-tailed Mann-Whitney U test (Bauer 1972). Results from bivariate analyses with categorical predictors were displayed using box plots denoting interquartile ranges (IQR) in addition to whiskers representing values of up to 1.5 times the IQR using “ggplot2” (Wickham 2016).

We used the “adehabitatLT” and “move” packages (Calenge 2006, Kranstauber et al. 2018) in the statistical software program R (R Core Team 2020) to generate step lengths between successive locations. We calculated the total distance moved per day (km) by individual, which consisted of the summation of distances between the first location of each day and the first location of the subsequent day, or the next available data point in the case of missing data. To reduce bias due to missing GPS fixes, we excluded days with fewer than three locations in analyses. We defined inland locations by latitudes of at least 29.0 and longitudes of less than or equal to -95.5 (Fig. 1). We determined these by examining coastal locations and producing a threshold based off the most northern and eastern locations. Traveling days consisted of instances where an individual had locations on the coast and inland, indicating that the individual moved between the two. We report the distances moved on travel days but omitted these days from the comparison of daily movements between coastal birds and inland birds. Additionally, we dropped any cases in which 0 m of daily movement was observed across location points and cases with missing values for the dependent variable (daily distances moved). We included data from the first arrival (20 October) to the 95th percentile departure date (30 April; Pearse et al. 2020b). We censored data within 5 d of initial capture to avoid bias associated with capture effects (Lamb et al. 2020). We dropped movement data from individuals with <10 d on the wintering grounds within a winter. Finally, we omitted the two most extreme non-travel related daily movement distances as they were graphically disjunct from the broader distribution per Q-Q plots as well as histograms and were clearly outliers per respective Grubb’s tests. We scaled all numeric data to modified z-scores representing standard deviations above the minimum value for each variable in the database to improve model convergence and provide standardized coefficients using the “scale” function in the “stats” package (Bring 1994, Afifi et al. 2020, R Core Team 2020). We compared daily movements of individuals that used the coast exclusively and those that used inland wintering areas using a two-tailed Mann-Whitney U test (Bauer 1972). We used a Kruskal-Wallis H test with a Dunn post hoc test (Z) to compare differences in daily movement among coastal individuals, inland individuals while on the coast, and inland individuals while in inland areas (Kruskal and Wallis 1952, Dinno 2015, Mangiafico 2015). We employed a Benjamini-Hochberg p value correction to limit incidence of type I error across multiple comparisons (Benjamini and Hochberg 1995).

We investigated the influence of inland wintering on Whooping Cranes’ daily movement patterns considering additional demographic and temporal factors that could also affect movements using generalized linear mixed-effects models (GLMM) with the “lme4” package (Dean and Nielsen 2007, Bates et al. 2015, 2021). We fit Gamma family GLMMs with a log link function and used bound optimization by quadratic approximation (BOBYQA) to control the fitting process (Powell 2009). We used the “allFit” function in the “lme4” package to confirm the appropriateness of the BOBYQA non-linear optimizer (Nash and Varadhan 2011). All models included the daily distance traveled (km) for each crane-day as the outcome variable and a set of uncorrelated variables such as crane age and family status, winter day (linear and quadratic), and winter range (inland or coastal), telemetry location (inland or coastal) as fixed effects predictor variables (Table 1). Each model also incorporated two variables as random effects, including the calendar year and the number of satellite locations provided by PTTs for each crane-day, which allowed model intercepts to vary across these values (Table 1).

Spearman Rank and Pearson Product-Moment Correlation Coefficients were both used to check models for collinearity between fixed effects predictors using the “Hmisc” package (Zar 2005, Harrell 2021). Variables demonstrating >0.6 correlation by either metric were not included as fixed effects predictors within the same model (Dormann et al. 2013). We also conducted variance inflation tests on candidate models to ensure collinearity did not arise between more than two predictors using the “car” package; models scoring >5.0 on any parameter were dropped from the analysis (Fox and Weisberg 2019).

Model sets included each predictor variable individually with the two random effects variables (five models), a set of four a priori multivariate models, and two null models, one including random effects and one without. We ran 11 models in total and compared them using Akaike Information Criterion corrected for small sample sizes (AIC_c) using the “MuMIn” package (Burnham and Anderson 2002, Burnham et al. 2011, Barton 2020). Results were reported for all models within AIC_c delta < 2 (Burnham et al. 2011).

We used the “effects” package in R to display the predicted influence of fixed effects independent variables on Whooping Crane daily movement patterns holding all other model covariates constant (Fox and Weisberg 2018). We also transformed fixed effects predictor variable parameter estimates altered by the log-link function to percent change in the dependent variable (daily distance moved in km) per a one unit increase in the predictor variable (Benoit et al. 2011). All analyses were conducted in the statistical software program R (R Core Team 2020).

RESULTS

There have been inland wintering individuals during five of 13 winters in the Granger Lake area and 11 of 13 winters in Colorado/Wharton counties from 2011–2012 to 2023–2024. Particularly noteworthy years include at least nine birds using the Granger Lake area in 2011–2012, 10 birds using the Granger Lake area in 2012–2013, at least 11 individuals using Colorado/Wharton counties in 2022–2023, and at least 18 individuals using Colorado/Wharton counties in 2023–2024 (Table 2).

Six cranes fitted with operational transmitters spent between 3.1–99.3% of their winter at inland areas across 10 bird-winters from 2011–2012 to 2021–2022 (Table 3). This includes three individuals across five crane winters in the Granger Lake area and three individuals across five crane winters in Colorado/Wharton counties (Table 3). All cranes in this study went to the coast first or visited it at least once during the winter (Table 3).

Inland wintering individuals had mean AKDE home ranges that were 3.1 times as large as coastal individuals (W = 176, p = 0.002). The 95% AKDE of Whooping Cranes was 83.41±33.7 km² (mean ± SE, n = 8, median = 50.55) for inland wintering Whooping Cranes and 27.16±3.4 km² (n = 126, median = 14.3) for coastal birds (Fig. 2).

Cranes on average had 3.8 satellite telemetry locations per day (range = 3–6) in our cleaned data set. We identified eight travel days between inland areas and the coast in the Pearse et al. (2020a) data set that averaged 220.8±26.3 km (±SE). Daily movement distances on travel days ranged from 219.6 km to 323.5 km (n = 5) for birds traveling to or from the Granger Lake area and from 125.1 km to 151.8 km (n = 3) for birds traveling to or from Colorado/Wharton counties. After dropping travel days, daily distance movements averaged 4.12±0.04 km per day and ranged from 0.01–81.5 km (n = 12,894). Inland wintering Whooping Cranes moved an average of 7.51±0.32 km per day (median = 6.78, n = 461), which was greater than daily movements by coastal wintering cranes, which averaged 3.99±0.04 km per day (median = 2.75 km, n = 12,433 W = 1,101,169, p < 0.001). Daily distances of coastal birds, inland wintering birds while inland, and inland wintering birds while on the coast were different (Kruskal-Wallis chi-squared = 205.86, df = 2, p < 0.001). In pairwise comparisons, daily distances of coastal birds differed from both inland wintering birds while on the coast and inland wintering birds while inland (Z = -7.65 and -12.27, p < 0.001; Table 4). Whooping Cranes that wintered inland did not move more while inland than while on the coast (Z = -1.21, p = 0.223; Table 4).

All nine a priori and bivariate models outperformed the simple null model as well as the null including random effects per AIC_c rankings (Table 5). The top ranked model included a quadratic function for day of winter (integer: 1-192/193), range as inland or being exclusively coastal (Range), and age and family status (Age/family status) as fixed effects predictor variables as well as calendar year the winter began (Year) and the number of GPS locations for each crane day per satellite telemetry as random effects (GPS Loc.; Table 5). This model was the best model based on AIC_c criteria (weight = 1.0).

The top model predicted that having inland habitats within a crane’s winter range equated to a 92.0±4.2% increase in daily movement (Fig. 3, Table 6). This model also predicted that daily movement varied across the season, with larger daily movements for all cranes earlier and later in the wintering period compared with the middle of the season (Fig. 4, Table 6). The top model suggested that family groups are predicted to have a 7.0±2.1% increase in daily movements compared with adults without juveniles, whereas subadults are predicted to have a 13.1±2.2% increase in daily movements compared with adults without juveniles. However, there was significant overlap in confidence intervals across age and family status (Fig. 5, Table 6).

DISCUSSION

We provide the most complete information available on the phenomenon of inland wintering of Whooping Cranes in the AWBP, and the first comparison of home ranges and daily movements between inland wintering and traditional coastal birds. Time will tell if the individuals using these inland wintering areas represent a new colonization event, or possibly a recolonization of the historic range, that will lead to additional birds expanding from these areas, or if these movements represent aberrant behaviors that occur stochastically or only under specific environmental conditions. This population’s historical range shrunk considerably as the population numbers dropped (Allen 1952). Following the range contraction, all the known territories were on the Blackjack Peninsula on the Aransas National Wildlife Refuge, but as the population expanded, individuals established territories on Matagorda Island in 1958, San Jose Island in 1969, Lamar Peninsula in 1971, and Welder Flats in 1973 (Stehn and Prieto 2010; Fig. 1). However, it is worth highlighting that Whooping Cranes were using these areas many years prior to the respective authors classifying them as reestablished territories (Allen 1952, Stehn and Johnson 1987). Based on the available evidence, inland wintering in Colorado/Wharton counties appears to represent a potential colonization and a new wintering area more than Granger Lake given its consistent use over a 13-yr period. Moreover, the number of birds using Colorado/Wharton counties is ostensibly increasing.

Whooping Cranes that used inland areas for a portion of the winter had larger home ranges and greater daily movements. These trends could be indicative of a few different drivers. Inland wintering birds may move more due to lower quality, lower quantity, or more diffuse food resources in inland areas (Knight et al. 2019, Teitelbaum et al. 2023). Birds in inland wintering areas may also be moving more and using larger areas due to lower crane densities and fewer territorial disputes (Stehn and Johnson 1987, Stehn and Prieto 2010). However, the fact that inland wintering birds move more than traditional coastal birds both while they are inland and when they are on the coast implies the cause of these larger home ranges and daily movements is more complex and possibly as related to the birds as the habitat.

Our top model indicated that factors other than wintering inland or coastal affected daily movements. Our top model included temporal effects on daily movements with individuals moving more when they first arrived and prior to departure compared with the middle of winter. Whooping Cranes may be making exploratory movements before settling into their winter home ranges. Exploratory movements are common in the animal kingdom (Züst et al. 2023). Individuals that arrive early or depart late likely have fewer neighbors to contend with and fewer territorial disputes, allowing for more uncontested movement. Alternatively, there may be additional aggressive interactions early in the winter as individuals arrive and core use areas are established. LaFever (2006) documented that flight and other movements were greatest for Whooping Cranes in the early winter and found territorial defense flights occurred most often in November–December. Butler et al. (2022b) used variograms to filter out the large movements of Whooping Cranes arriving on the wintering grounds before calculating home ranges. Our top model also included age/family status. Age/family status influenced daily movements, with subadults moving the largest daily distances, although there was significant overlap in confidence intervals. Butler et al. (2022b) found subadult female Whooping Cranes used larger areas than subadult males or family groups.

Pearse et al. (2020b) determined the distance between stopover sites for migrating AWBP Whooping Cranes averaged 307.7 km (SD = 187.6). Some of the travel days between Granger Lake and the coast are comparable to travel distances seen during migration. The larger home ranges, daily movements, and travel days for inland wintering birds likely have winter energy expenditure implications. VonBank et al. (2021) found that Greater White-Fronted Geese (Anser albifrons frontalis) had greater energy expenditure and spent more time flying and feeding in more recently established wintering areas than in their historical wintering areas. Butler et al. (2022b) highlighted that wintering AWBP birds were using larger areas and shifting home ranges between winters more than previously reported. Inland wintering behavior may represent an escalation of recent behavioral patterns, including reduced attachment to a bounded winter range and space use flexibility.

Short-stopping is well established in the EMP, and there appears to be habitat available in the migratory corridor of the AWBP (Teitelbaum et al. 2016, Mendgen et al. 2023). In the winter of 2011–2012, possibly due to drought and warm conditions, AWBP birds were found around Granger Lake, south-central Kansas, and central Nebraska (Wright et al. 2014). That is the first year birds were reported in Colorado/Wharton counties (eBird 2024). Interestingly, the winter of 2011–2012 is also the year that a large number of EMP birds started wintering in Indiana, which was attributed to a warm short winter (Urbanek et al. 2014, Fitzpatrick et al. 2018). Whooping Cranes of the EMP are still using these northern short-stopping locations as one of their primary wintering areas (Thompson et al. 2022). However, unlike the EMP birds, the use of these inland areas by AWBP individuals does not represent short-stopping. All inland wintering birds with fitted operational transmitters in this study, used both the traditional coastal areas and inland wintering areas to some extent. Most birds visited the coast first before moving into inland areas, and many returned to the coast at times during the winter. The use of these inland areas does not shorten their total migration distance and should not be considered short-stopping (Elmberg et al. 2014).

Although the use of these inland areas does not represent short-stopping behavior, it does represent either a temporary or permanent shift or expansion in AWBP wintering areas. Metzger et al. (2020) estimated the current carrying capacity in the coastal region at 4,414 cranes based on habitat models, so the expansion into non-coastal wintering areas is probably unrelated to limited habitat area on the coast. However, habitat quality in coastal Texas is significantly moderated by hydrological conditions (Chavez-Ramirez and Wehtje 2012, Wozniak et al. 2012, Butler et al. 2022b). Texas was undergoing a significant drought in the winter of 2011–2012 (U.S. Drought Monitor 2012), and Whooping Cranes have been shown to use uplands to a greater extent and have larger home ranges during drought years (Butler et al. 2014, 2022b). This is likely due to declining food resources in the saltmarsh community during drought and high salinity years (Chavez-Ramirez and Wehtje 2012, Wozniak et al. 2012). The extreme drought, which may have led to a decline in resources, could have pushed birds into novel inland areas or into areas they were familiar with from previous migrations. Large winter movements following the occurrence of severe weather events and declining food resources have been well documented in other avian species (Gourlay-Larour et al. 2012, Knight et al. 2019, Teitelbaum et al. 2023).

The inland wintering individuals in this study are using largely agricultural areas. The area used in Colorado and Wharton counties is similar to areas used by Whooping Cranes in the Louisiana Non-Migratory Population in southwestern Louisiana, where the use of rice agriculture by cranes is common (Pickens et al. 2017, Vasseur et al. 2023). All crane species have adapted to rely on agricultural landscapes to some extent, which can provide alternatives to traditional habitats, especially as natural environments are degraded (Hemminger et al. 2022). Siberian Cranes (Leucogeranus leucogeranus) are a critically endangered wetland-dependent crane species (Archibald et al. 2020). Wintering Siberian Cranes at Poyang Lake forage predominantly on tubers of Vallisneria spiralis in shallow water and mudflat habitat. Following substantial declines of Vallisneria spiralis, individuals have been documented to switch habitats and use wet meadows and nearby agricultural areas, including lotus (Nelumbo nucifera) ponds and rice fields (Jia et al. 2013, Burnham et al. 2017, Zhi et al. 2019, Hou et al. 2020). The stronghold of the Blue Crane’s (Grus paradisea) range in South Africa has shifted to the Western Cape Province following conversion of the natural environment to cereal crops and dryland pastures (Morrison et al. 2012). Inland wintering within AWBP Whooping Cranes may reflect recent shifts observed in the Gruidae family in response to agricultural expansion and surface water exploitation.

Whooping Cranes learn a great deal from their parents in their first year through social learning (Johns et al. 2005, Stevenson and Griffith 1946, Mendgen et al. 2023). The use of inland areas in a bird’s first winter could lead to learned behaviors that carry on throughout their lives. Our data do include some birds with multiple years of inland use, however, other marked birds did not exhibit this strategy. It is possible that some birds may have returned to these inland areas later in life, as Whooping Cranes can outlive the functionality of their transmitters. Continued use of inland areas by various age classes and individuals with varying family status, particularly in Colorado/Wharton counties, does suggest learned use of this area as a potential wintering area.

Although the birds are using new wintering areas, it is also worth repeating that all the birds in this study that used inland areas also used traditional coastal areas for a portion of the winter. Butler et al. (2022b) documented split home ranges of wintering Whooping Cranes, including inland wintering individuals in this study and coastal birds. Teitelbaum et al. (2018) also documented the use of multiple wintering areas for some birds in the EMP, and on average these sites were 233±68 (SE) km apart. The back and forth between inland and coastal areas is not very well understood and warrants more research. Research suggests that some crane species are relatively flexible in their wintering range, and such winter movements may increase for Whooping Cranes as the population recovers and individual bird’s behaviors likely become more variable (Alonso et al. 2008, Krapu et al. 2011).

Continued use of inland areas has implications for how we manage, monitor, and plan for this population’s recovery. In the winter of 2022–2023, 11 birds used Colorado/Wharton counties well outside the primary and secondary USFWS survey areas, and an estimated 536 (95% CI = 443.5-644.1) were within the primary survey area during the survey period (Butler et al. 2023). Accounting for these birds will be a challenge, as many go back and forth between inland areas and the primary and secondary survey areas during winter. Additionally, these birds are using larger areas and moving greater daily distances, likely making tracking unmarked birds more difficult. Our understanding of current and future wintering habitat of the AWBP is based almost exclusively on traditional coastal habitat. For example, habitat models and carrying capacity estimates under both current conditions and future sea level rise and development scenarios include only coastal or coastal adjacent habitats (Metzger et al. 2020, Golden et al. 2022). A reevaluation of what is considered useable habitat for wintering AWBP Whooping Cranes should be considered, along with how much is available, and what threats to those habitats exist. Monitoring bird use and abundance in these inland areas over the coming years is important, particularly in Colorado/Wharton counties, where use has continued and increased. Additionally, documenting the behavior, diet, and energy expenditure of these inland wintering birds represents important applied research topics.

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