
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39251699
71216
10.1038/s41598-024-71216-6
Article
Sod farms drive habitat selection of a migratory grassland shorebird during a critical stopover period
Rodkey Tara Lafabrêgue tara.lafabregue@gmail.com

1
Ballard Bart M. 1
Tibbitts T. Lee 2
Lanctot Richard B. 3
1 https://ror.org/05abs3w97 grid.264760.1 Caesar Kleberg Wildlife Research Institute, Texas A&M University – Kingsville, Kingsville, TX 78363 USA
2 https://ror.org/05ehhzx21 Alaska Science Center, U.S. Geological Survey, Anchorage, AK 99508 USA
3 Migratory Birds Management, U.S. Fish and Wildlife Service, Anchorage, AK 99503 USA
9 9 2024
9 9 2024
2024
14 2097326 3 2024
26 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Migratory shorebirds are one of the fastest declining groups of North American avifauna. Yet, relatively little is known about how these species select habitat during migration. We explored the habitat selection of Buff-breasted Sandpipers (Calidris subruficollis) during spring and fall migration through the Texas Coastal Plain, a major stopover region for this species. Using tracking data from 118 birds compiled over 4 years, we found Buff-breasted Sandpipers selected intensively managed crops such as sod and short-stature crop fields, but generally avoided rangeland and areas near trees and shrubs. This work supports prior studies that also indicate the importance of short-stature vegetation for this species. Use of sod and corn varied by season, with birds preferring sod in spring, and avoiding corn when it is tall, but selecting for corn in fall after harvest. This dependence on cropland in the Texas Coastal Plain is contrary to habitat use observed in other parts of their non-breeding range, where rangelands are used extensively. The species' almost complete reliance on a highly specialized crop, sod, at this critical stopover site raises concerns about potential exposure to contaminants as well as questions about whether current management practices are providing suitable conditions for migratory grassland birds.

Keywords

Shorebirds
Migration ecology
Agriculture
Habitat selection
Grasslands
Subject terms

Ecology
Animal migration
Conservation biology
http://dx.doi.org/10.13039/100006004 Rob and Bessie Welder Wildlife Foundation issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

The expansion and intensification of agriculture are among the most important drivers of species declines across the globe1–3. In North America, there are few places where this is more apparent than in the midcontinent, where native grasslands have largely been replaced by cropland, rangeland, and more recently, urbanization4–7. Grassland degradation is also exacerbated by the expansion of woody plants and non-native grasses, which has been driven by changes in disturbance regimes, notably, fire suppression, incompatible grazing, water canalization or drainage, as well as, to a lesser extent, climate change8–10. Wildlife dependent on grasslands in the midcontinent region have faced correspondingly steep declines3,11,12. However, the relationship between wildlife and agriculture can be complex, especially in rangelands, which can support rich communities of native fauna13,14. Thus, understanding the habitat requirements of species using agricultural landscapes may inform conservation actions that can integrate these economically productive systems with efforts to preserve biological diversity.

The Western Gulf Coastal Plain of Texas (hereafter Texas Coastal Plain) contains some of the most fragmented grasslands in the Americas15. Urban sprawl from two of the state’s largest cities, Houston and Brownsville, is rapidly encroaching on remaining parcels of grassland as well as the extensive croplands that have recently replaced grasslands7,16–18. This trend, combined with an accompanying shift in land-ownership to smaller landholdings19, is exacerbating fragmentation and overall grassland loss in the region15,20. Despite these changes, the Texas Coastal Plain remains a biodiversity hotspot21, and its location has made it a region of international importance for migratory birds in the midcontinent22,23. Migratory shorebirds, for example, depend on the Texas Coastal Plain as a stopover area during spring and fall migration, yet the habitat requirements of these species in this region are still poorly known24,25. Habitat availability during migration is of utmost importance to migratory birds, as it directly influences their ability to replenish energy stores, which may affect their survival and subsequent breeding success26–28. The conditions encountered by individual birds during migration can either exacerbate or alleviate impacts of unfavorable conditions during breeding and wintering periods. For example, favorable conditions during migration can mitigate negative effects of climate change on Arctic-breeding species26.

The Buff-breasted Sandpiper (Calidris subruficollis) is a migratory shorebird that stops in the Texas Coastal Plain as it travels between its wintering areas in the Pampas of South America and its breeding areas in the Arctic of North America and Russia29. Due to persistent threats across this species’ migratory pathway and its small and declining population, the Buff-breasted Sandpiper is considered a species of global conservation concern30 and is designated as a species of high-conservation concern in the United States. and Canada30, listed by the IUCN Red List as Near Threatened31, and classified as threatened or vulnerable in the four countries that encompass its winter range (Argentina, Brazil, Paraguay and Uruguay)30.

One of the principal factors limiting the growth of the Buff-breasted Sandpiper population is thought to be habitat loss in both wintering and migratory regions30. Several studies suggest that the Texas Coastal Plain in particular, is an area of critical importance for this species22,24,25,30,32. Indeed, this is the only region along their migratory pathway where birds are regularly observed in high numbers during both spring and fall migration33. Habitat availability in the Texas Coastal Plain may thus be an important driver of the declining population trend in this species30.

Nearly all knowledge on habitat associations of the Buff-breasted Sandpiper in the Texas Coastal Plain is from eBird records33 and road-based surveys22,24,25, which indicate that the species is primarily observed on croplands, particularly sod farms and early-growth rice fields. However, these data come with spatial and temporal biases. For example, they are often biased towards areas where people live34,35 and towards environments where a species can be most readily detected. The latter bias may be especially pertinent to Buff-breasted Sandpipers, whose cryptic coloration and quiet vocalizations may skew detections to visually high contrast environments such as green, mowed sod farms. The prevalence of privately-owned land in the Texas Coastal Plain also means most data are collected on smaller tracts of land with easier public access, limiting inference to inaccessible areas such as the many large privately-owned ranches in the region. Finally, the few structured surveys that have occurred were all in spring22,24,25 and eBird records are also biased towards spring36.

These biases and lack of information have important implications in our understanding of what constitutes suitable migratory habitat for Buff-breasted Sandpipers in the Texas Coastal Plain. Data from other parts of its range indicate that the species is a grassland obligate with a preference for short-stature rangeland. During non-breeding in South America, for example, it is found almost exclusively in short-stature (2–6 cm) rangeland maintained by a combination of flooding and high grazing pressure14,37–40. During migration in Kansas and Nebraska, it is found in recently burned rangeland and pastureland and early growth row crops or recently harvested hay fields, with all of these having in common a very short vegetation structure41–43. Yet in the Texas Coastal Plain, few records exist of this species in rangeland, despite the prevalence of this landcover type in the region44. It is unclear whether the paucity of observations in rangelands is an artifact of the observer-biases described above, or whether important rangelands have yet to be identified.

Additionally, the species apparent dependence on short vegetation suggests Buff-breasted Sandpipers may use cropland differently during spring migration than in fall migration due to changes in crop height associated with plant maturation. There is also evidence that Buff-breasted Sandpipers are likely to avoid areas near trees14, which may harbor avian predators, as well as generally avoid roads45,46, which may introduce noise disturbance or heightened mortality risk. Roads in North America are also often flanked by powerlines, another vertical structure which can harbor avian predators47. Finally, it is unknown if the characteristics of nighttime sites differ from daytime sites. Other shorebird species have been shown to select more protected environments at night to reduce predation risk, so we may expect Buff-breasted Sandpipers to do the same48.

To address these gaps in our understanding of habitat selection patterns by Buff-breasted Sandpipers we used data from two studies that tracked birds within and across Texas spanning four years during the species’ spring and fall migration through the Texas Coastal Plain. We predicted (a) the species would occur more in rangeland than other habitat types, based on land use observations from other parts of its range; (b) sod would be used less than eBird and road-based surveys indicated due to visual biases in these surveys; (c) selection of cropland would vary seasonally, corresponding to when crop growth or harvest stage created a suitably short-stature environment; (d) birds would select areas farther from woody cover and roads; and (e) nighttime site selection would be driven by different environmental characteristics than daytime sites, with greater avoidance of woody cover during the nighttime. A more complete understanding of the habitat preferences of the Buff-breasted Sandpiper in the Texas Coastal Plain, including whether habitat selection patterns differ between migration seasons as well as between day and night, is essential for developing effective conservation strategies for this species.

Methods

Study area

The Texas Coastal Plain (Fig. 1), approximately 59,770 km2 in size, is located along the coast of the Gulf of Mexico, and is characterized by a shallow elevational gradient from sandy shoreline through coastal dunes and into prairies and brushland49. The region’s flat topography and the historic dominance of grassland and savanna ecosystems lent itself easily to European settlement and accordingly the landscape is now dominated by rangeland for cattle ranching and cropland14,19,42,45 such as cotton, rice, sorghum and corn15,21,44,49. Although some isolated patches of remnant native prairie and restored grasslands do exist, most inland grassy habitats now exist in the form of rangeland dominated by warm-season perennial introduced grasses50,51. Rangelands in the region are managed largely at private landowners’ discretion and there is great variability in how they are managed52–54. Many ranchers strive to optimize forage for cattle production, creating homogenous mid-stature pastures of native or non-native forage grasses, while others use continuous grazing with high stocking rates, creating short pastures with extensive bare earth8,53,55. Grassy habitats also occur to a lesser extent as hay fields and sod farms, the latter of which is most common in the mid-coast region of the Texas Coastal Plain.Fig. 1 Map of the Texas Coastal Plain study area, with the GPS locations of tracked Buff-breasted Sandpipers from both the Texas and range-wide studies (the latter split into locations from individuals caught within and outside the study area). Sod farms are indicated by white circles on the main map, with numbers representing the number of sod farms in the immediate area if greater than one. The inset illustrates one area of sod farms and the associated trapping locations and GPS locations of tracked birds as an example. Map was generated with QGIS 3.32 (https://www.qgis.org/)118.

Animal capture and device attachment

Tracking data from two distinct studies were used in our analyses. One study involved trapping birds only in Texas from 2021 to 2022 with the principal objective of refining understanding of habitat selection patterns at a fine temporal and spatial scale within the Texas Coastal Plain. This effort will henceforth be referred to as the “Texas study”. This work took place after an initial “range-wide study” of the species, which involved trapping and tracking birds across their annual cycle between 2016 and 201856. These studies are presented out of chronological order to give emphasis to the data from the Texas study, which forms the basis of analyses.

For the Texas study, Buff-breasted Sandpipers were captured using whoosh-nets on five private sod farms located in three Texas counties (Matagorda, Wharton and Victoria) from 4 April to 10 May and 7 August to 25 August. Once captured, we collected biometric data including diagonal tarsus (mm), head-plus-bill length (mm), culmen (mm), flattened diagonal wing chord (mm) and mass (g). These data were used to determine sex using a discriminate function analysis57; age was determined by examination of spotting pattern on the ventral side of the 10th primary30. All birds were marked with a uniquely numbered U.S. Geological Survey (USGS) band attached to the tibia of the right leg. Birds were then equipped with a GPS satellite tracking device (3.5 g Pinpoint GPS Argos, Lotek Wireless Inc., Newmarket, Ontario, Canada) epoxied to a 1-mm thin patch of pigskin leather, which was then attached to a bird’s synsacrum with cyanoacrylate glue after feathers were clipped from the area. This approach allowed the devices to fall off when the bird molted its body feathers. Devices were only placed on birds if the device weight was less than 5% of their body weight.

For the range-wide study, Buff-breasted Sandpipers were captured in December–February on the non-breeding grounds in Uruguay, Argentina and Brazil; during April–May and July–August on migration in Texas; and in June during breeding in the Alaskan Arctic. A variety of capture methods were used including cannon nets32 (Argentina), wilsternets58 (Uruguay), night lighting59 (Brazil), whoosh-nets or cannon nets (Texas), and by observers swooping or dropping mist nets on birds (Alaska)60. Similar methods to the Texas study were used to mark and measure the birds, and the same GPS transmitters were attached, but with a leg-loop harness composed of either 0.7- or 1.0-mm diameter stretchable polymer cord52.

Location acquisition

In the Texas study, tracking devices were programmed to collect 1–3 locations across four time periods (GMT -6): morning (07:15–10:45), midday (11:45–15:15), afternoon (16:15–19:45), and nighttime (01:00–01:15). The nighttime period was smaller because we were interested in determining if this was a roosting location by taking two locations 15 min apart. Exact acquisition times varied between devices to reduce sampling bias. In the first three seasons of data collection, devices were programmed to collect three locations 15 min apart in each time period in an attempt to differentiate locations where the bird was flying rather than on the ground (see Supplementary text). However, these repeated location cycles shortened the battery life of the devices and in exploratory analyses we found that identification and removal of flying locations did not impact results. Therefore, we programmed devices to collect only one location during each time period in the fourth season of data. In the range-wide study, location acquisition was at a coarser temporal grain of one location every 48 h, recorded at approximately 15:00 UTC which corresponds to the ‘morning’ time period in the Texas study. Tracking data from both studies were filtered to retain only those GPS locations that passed the Lotek cyclic redundancy check (Lotek Wireless Inc., Newmarket, Ontario, Canada) and fell within the Texas Coastal Plain.

Quantifying individual stopover area

All analyses and visualizations were carried out in program R (v.4.2.2)61 within RStudio (v.2023.6.1)62. For the Texas study, each individual’s area of use was estimated using dynamic Brownian bridge movement models, a statistical technique that estimates animal occurrence distributions (or confidence areas) by fitting a continuous-time stochastic process to movement data63. We chose this approach to identify use areas instead of minimum convex polygons and kernel density estimators because it can better account for spatial autocorrelation and irregular sampling intervals63. By considering the order and time spent at locations, these models are also able to estimate the animal’s movement capacity (i.e., maximum movement possible in given amount of time) and detect changes in this capacity based on movement patterns. Because we were interested in capturing changes in movement capacity on a daily basis, we selected a window size that represents approximately one day of data collection (i.e., 11 relocations)63. For margin size, we selected five relocations, which corresponded to about four to five hours63. This relatively large margin was chosen to be less sensitive to frequent changes in movement patterns as we assumed changes occurring over longer time periods would better represent the area truly available to the individual (e.g., the difference between frequent short flights while foraging and long-distance relocations)63. To transform the raster output of these models into a two-dimensional area, we extracted the extent of the 95% confidence interval from all occurrence distributions to define individual stopover area in subsequent analyses. Occurrence distributions were produced with the move package (v.4.1.12)64.

The coarser temporal resolution of the data from the range-wide study, and the resulting paucity of locations, did not allow the estimation of use areas via dynamic Brownian bridge movement models. So to define these we instead drew minimum convex polygons around each individuals’ locations. Minimum convex polygons are the smallest area polygon possible to be drawn which will include all locations (in this case, of a given individual). Often, an individual bird would relocate to another area within the Texas Coastal Plain during the same season, traveling up to ca. 300 km before resettling. A minimum convex polygon drawn around these long-distance relocations would have yielded an overestimation of the area of use. To account for this, we split an individual’s locations into clusters of locations when movements exceeded 21 km; these clusters were then used to draw minimum convex polygons. The 21-km threshold was determined by calculating the mean maximum daily distance traveled for each bird tracked in the Texas study, and then taking the maximum across all birds (20.98 km ≈ 21 km). Then these were buffered by the median of the maximum daily distances (14.03 km ≈ 14 km), in order to conservatively capture the area available to each individual bird in the 48 h between locations. A map of the areas of use from both studies is available in the supplementary information (Supplementary Fig. 1).

The sample sizes required for quantifying areas of use in this way by necessity filtered out any individuals tracked in the study region for less than 2 days in the Texas study (< 20 relocations) and less than 5 days in the range-wide study (< 3 relocations). This was because the dynamic Brownian Bridge movement models needed greater than two window sizes’ worth of data (2 days in the Texas study) and the minimum convex polygons need at least three locations (5 days in the range-wide study). Finally, one additional filtering step was applied to the data from the Texas study. To standardize between all seasons of data collection in the Texas study and to reduce autocorrelation we retained only one location per time period per day, closest to the “middle” of the defined time period.

Habitat selection analysis

To investigate habitat selection by the tracked Buff-breasted Sandpipers, we used a static point-based exponential habitat selection function (also known as resource selection function)65 at the population level within a used versus available context66. This method provides a statistical framework for describing the relationship between environmental characteristics and the relative probability of use by the study species65. We defined availability by generating random points across the extent of each individual’s area of use (availability), and then compared these available locations to their actual locations (use). Use and availability were thus defined at an individual level. To make population-level inference and account for the nested structure of the data, we used generalized linear mixed effects models with a logit link on the tracking data from the Texas and range-wide study dataset separately and allowed slope and intercept to vary by individual, according to the recommendations of Muff et al. (2020)67. This process loosely approximated third order selection (selection of patches within a home range, in this case the individual’s stopover area of use)68. Models were fit using the glmmTMB package (v.1.1.7)69.

For the data from the Texas study, we determined availability by generating 100 random points for each “used” location within an individual’s area of use. To confirm that we had adequately sampled availability, we started with a 1:10 used to available ratio, then increased the number of available points by 10-point increments until we reached a 1:100 ratio. In each analysis, we fit single variable models for all model covariates to visually examine the stability of the coefficients (i.e., that after a certain ratio the coefficient values remained relatively similar, within 0.002 with each random sampling of availability, see Supplementary Fig. 2)70. Additionally, available locations were given an arbitrarily high weight of 1000 in the model, allowing further stabilization of beta coefficients67,71.

To characterize availability in the range-wide study, we generated 200 random points for each “used” GPS location within a unique stopover area. Twice the number of random points was generated per used point than in the analysis on the Texas study to compensate for the smaller number of used points and to ensure availability was still being sampled adequately.

Model covariates

Explanatory variables in habitat selection models included temporal variables, landcover variables, and anthropogenic features. Temporal variables were study season and time of day (daytime vs. nighttime); each variable was included in models as an interaction term with other covariates. Landcover variables were sod, cotton/soybean, corn/sorghum, rice, grassy cover, and woody cover. All landcover variables were tested for correlation using Pearson’s correlation coefficient, and if determined to be strongly correlated (|r|> 0.5)72, were not used in same model. To reduce collinearity between interaction terms and landcover variables, as well as improve model stability, all continuous covariates were centered and scaled.

For all landcover types except sod, we used the 30-m resolution Refined Cropland Data Layer73, which has improved accuracy and sharper boundaries of cultivated land cover than the original United States Department of Agriculture (USDA) Cropland Data Layer73. Crops in this dataset are defined by the growing season for the given year. Therefore, in spring many of these croplands would be in early planting or growth stages, while in fall many would be approaching harvest or post-harvest. For the sod landcover type, we produced a custom sod farm layer by cross-referencing the Refined Cropland Data Layer with the most current high resolution satellite imagery in Google Earth Engine74,75 and identifying boundaries of sod farms via visual inspection. We chose to make a custom sod farm layer because the accuracy of the Refined Cropland Data Layer is known to be much lower for minor, more specialty crops, like sod76. Anthropogenic features included roads, defined by the TIGER: US Census Roads 2016 dataset77. To create the landcover variables, we created individual raster layers of five classes of aggregated landcover categories from the Refined Cropland Data Layer for each year: cotton/soybean, corn/sorghum, grassy cover, rice/aquaculture, and woody cover (Table 1). To capture the overall vegetative structure present on crop fields, rather than investigate plant-specific differences, cotton and soybean were combined, as well as corn and sorghum. These crops share similar growth patterns and planting times, as well as a tendency to be rotated with one another (cotton/soybean with corn/sorghum). Grassy cover was made up primarily of the landcover class “Grass/Pasture”, but also included hay crops such as rye and alfalfa. Rice was combined with some more general aquaculture classes present in much lower quantities and will hereafter be referred to only as “rice” and finally, woody cover included any tree or shrub category (Table 1). For the woody cover and road layers, we transformed these from categorical to continuous variables by calculating the Euclidean distance of each pixel to the center of the nearest pixel of woody cover or to the closest road vector, respectively. Distance was used for these two variables to capture their predicted negative influence on Buff-breasted Sandpiper presence. Alternatively, we expected the proportion of these landcover types in the surrounding area to influence selection. Therefore, to capture this effect, we transformed these categorical layers into continuous raster layers by calculating the percent cover of each class within a circular buffer of a given radius (see next section, “Characterization of spatial scale”). For the distance variables, values were transformed to exponential decays following Neilsen et al. 200978, so that their effect would become irrelevant at large distances (~ 1500 m). The resulting decay variables were then subtracted from 1 to maintain consistency in coefficient interpretation. Table 1 Reclassification scheme for landcover covariates derived from the Refined Cropland Data Layer73 used to investigate habitat selection of Buff-breasted Sandpipers in the Texas Coastal Plain.

Reclassified landcover group	Original refined cropland data layer classes	
Corn/Sorghum	Corn, sweet corn, sorghum	
Cotton/Soybean	Cotton, soybean	
Grassy Cover	Grass/pasture, alfalfa, other hay/non-alfalfa, rye	
Rice	Rice, aquaculture	
Woody cover	Deciduous forest, evergreen forest, mixed forest, shrubland, woody wetlands	

Characterization of spatial scale

Because species may respond to habitat features at multiple scales, and a user-defined scale can produce weak or misleading results even when based on biologically relevant criteria79, we conducted a scale-optimization procedure on the percent cover variables to identify their scale of effect (i.e., the scale at which a landcover variable most strongly correlated with bird presence)80. To do this, we calculated the percent of each of the landcover covariates within circular buffers of seven different radii, namely 100, 150, 200, 250, 500, 750, 1000 m, for each pixel. The scale of effect for each covariate was identified using a pseudo-optimization procedure81 in which we ran single-variable models at each scale and for each covariate retained the scale with the lowest ∆AICc score. If a covariate had more than one scale with ∆AICc scores less than or equal to six82,83, we prioritized keeping as many covariates at the same scale as possible (e.g. if covariate A performed equally at 500 m and 750 m and covariate B performed best at 750 m, covariate A was retained at 750 m). This procedure was only performed on data from the Texas study because more bird locations were available with which to make inference on scale, and we could then apply these model covariates with confidence to the coarser range-wide dataset (Table 2). Table 2 Summary of landcover covariates included in the final models investigating Buff-breasted Sandpiper habitat selection in the Texas Coastal Plain.

Covariate	Unit	Scale of effect	Derived from	
Percent sod	%	250 m	Custom layer	
Percent grassy cover	%	250 m	Refined cropland data layer	
Percent cotton/soybean	%	500 m	Refined cropland data layer	
Percent corn/sorghum	%	250 m	Refined cropland data layer	
Percent rice	%	1000 m	Refined cropland data layer	
Distance to woody	m	NA	Refined cropland data layer	
Distance to Road	m	NA	TIGER: US Census Roads 201677	
The “scale of effect” is the radius at which percentage cover in a circular buffer around locations best predicted presence of Buff-breasted Sandpiper. Custom sod layer by authors. See Table 1 for Refined Cropland Data Layer explanation.

Model specification

We investigated how landcover variables (Table 2), combined in 10 candidate models, were related to Buff-breasted Sandpiper presence using data from the Texas study and the range-wide study. The fixed effects included in these models and their representative hypotheses can be found in Table 3. The top models were selected using ∆AICc scores less than or equal to six82,83. Then four more models were created by interacting temporal variables with the landcover variables in the top model(s). Proportion of variance explained by the fixed effects (i.e., marginal R2) and by both fixed and random effects (i.e., conditional R2) was calculated for all candidate models for both datasets84. Table 3 The fixed effects and associated hypotheses of all candidate models for explaining habitat selection variation of Buff-breasted Sandpipers in the Texas Coastal Plain in both the Texas and range-wide studies.

Model	Fixed effects	Hypothesis	
1	Sod% + Grassy% + cotton/soybean% + corn/sorghum% + rice% + distance to road + distance to woody	Global model—All selected variables were combined to best predict habitat selection	
2	Grassy% + distance to woody	Only woody and grassy—“Natural” cover types drive selection rather than cropland	
3	Sod% + distance to woody	Only sod and woody—presence driven by selection for sod and avoidance of woody cover	
4	Sod%	Only sod—sod plays an exclusive role in selection	
5	Sod% + cotton/soybean% + corn/sorghum% + rice%	Only cropland types– play exclusive role in selection	
6	Sod% + grassy% + cotton/soybean% + corn/sorghum% + rice% + distance to woody	No road—grassland species in agricultural landscapes may be accustomed to farmland roads	
7	Sod% + grassy% + cotton/soybean% + corn/sorghum% + distance to road + distance to woody	No rice—flooded cropland not important for upland species	
8	Sod% + grassy% + cotton/soybean% + rice% + distance to road + distance to woody	No corn—all variables important in selection except early-seeded crops like corn	
9	Sod% + cotton/soybean% + corn/sorghum% + distance to woody	No rice, road or grassy cover—non-flooded cropland and avoidance of woody cover drive selection	
10	Sod% + cotton/soybean% + rice% + distance to woody	No corn, road or grassy cover—late-seeded crops like cotton and avoidance of woody cover drive selection	

For the Texas study, the temporal variables were season and time of day. The same analytical framework as conducted on the Texas dataset was repeated on the range-wide dataset, except there was no time-of-day covariate since all locations were acquired during daytime, and we added a two-factor “origin” variable. This origin variable was included to differentiate birds caught on sod farms in Texas from those caught outside the region. Because birds from the Texas dataset were all caught on just 5 sod farms in the central region of the Texas Coastal Plain, any analysis of habitat selection may have been biased towards this landcover type, either by virtue of tracking birds in a landscape where this landcover type was more abundant, or by tracking individuals who preferred sod. Therefore, the origin variable was modeled as an interaction with the landcover variables to test whether the effect of landcover varied as a consequence of capture location. Thus, in addition to the ten landcover only candidate models, we built models with season and origin as interactions with the landcover variables.

Functional response curves

To understand how individual birds responded to different environmental conditions within their defined area of use (see above), we created functional response curves using the multiplicative approach recommended by Holbrook et al. 201985. This approach plots the log mean use of a landcover type against the log of the mean availability of that landcover type for each tracked bird. Because individual birds from the range-wide study had so few locations within the Texas Coastal Plain, response curves were only created for birds from the Texas study.

Approval for animal use

All birds were captured and handled according to relevant animal care guidelines and regulations. The Texas study was permitted by Texas Parks and Wildlife Department Scientific Research Permit (SPR-0721-090) and Texas A&M University-Kingsville Institutional Animal Care and Use Committee (#2021-04-13). The range-wide study was permitted by a USGS bird banding permit (#23,269), Institutional Animal Care and Use Committee reviews (USGS #2016-02, United States Fish and Wildlife Service #2017-007); Alaska Department of Fish and Game (#17-134 and #18–161), Texas Parks and Wildlife Department (SPR-0316-084); Argentina’s National Parks Administration (#104/16); Brazilian Ministry of the Environment (SISBIO 42,418 and SNA #3839); and Uruguay’s Environment Ministry and National System of Protected Areas.

Results

Tracking data

In total, we included 118 Buff-breasted Sandpipers in our analyses (Table 4). In both studies, almost all birds were after-hatch year (one bird in the range-wide study was a hatch year) and more birds were tracked in fall than in spring and most tracked individuals were male (Table 4). Collectively, birds were tracked in the region for an average of 12 days in spring (range 7–17 days), and an average of 18 days in fall (range 7–39 days) (Table 4). Although birds from the range-wide study were tracked for an average of 4 days longer in spring and 8 days longer in fall, the time period when birds were tracked remained approximately the same in each study: April 4 to May 10 in spring 2016, August 12 to August 29 in fall 2016, April 21 to May 9 in spring 2018; and August 1 to September 14 in fall 2018 (Supplementary Fig. 3). Table 4 Summary of Texas and range-wide tracking data used in habitat selection analyses of male (M) and female (F) Buff-breasted Sandpipers in the Texas Coastal Plain. Data summarized by temporal (season, year) and capture variables (origin).

	Texas study	Range-wide study	
Total number of tracked birds	66

(55 M, 11 F)

	52

(44 M, 8 F)

	
By season	Spring	Fall	Spring	Fall	
Number of birds tracked	22

(21 M, 1 F)

	44

(34 M, 10 F)

	10

(9 M, 1 F)

	42

(35 M, 7 F)

	
Median locations per individual	25.5	34	9	7	
Tracking period	April 26–May 21	August 7–September 6	April 4–May 10	August 1–September 14	
By year	2021	2022	2016	2018	
Number of birds tracked	42

(37 M, 5 F)

	24

(18 M, 6 F)

	12

(11 M, 1 F)

	40

(33 M, 7 F)

	
By origin	_	_	Inside Texas	Outside Texas	
Number of birds tracked	_	_	38

(32 M, 6 F)

	14

(12 M, 2 F)

	

According to our optimization procedure, the scale of effect that best predicted species presence in the single-variable models were percent sod at 250 m; percent grassy cover at 250 m; percent cotton/soybean at 500 m; percent corn/sorghum at 200 m; and percent rice at 1000 m (Table 2). In the Texas study, locations used by Buff-breasted Sandpipers included mostly sod, cotton/soybean, and corn/sorghum. Surprisingly, less than 10% of used locations were in grassy cover (grass/pasture, rye, and other hay/non-alfalfa) or rice in either season (Fig. 2). Similar to the Texas study, most locations used by Buff-breasted Sandpipers in the range-wide study included sod, cotton/soybean, and corn/sorghum. Also like the Texas study, very few locations were within grassy cover (Fig. 2). Tracked birds in both datasets occurred more often in corn/sorghum in fall than in spring, and conversely, more often in cotton/soybean in spring than in fall. Use data between night and day in the Texas study approximated each other, with a slightly greater use of sod at night in both spring and fall (Supplementary Fig. 4).Fig. 2 Buff-breasted Sandpiper use (% of GPS locations) of each landcover class (summarized by reclassified landcover group, see Table 1, 2) during spring (left) and fall (right) migratory seasons based on birds tracked during the Texas study (top panels) and the range-wide study (bottom panels).

Habitat selection analysis: Texas study

Once temporal variables were added as interactions, the model that included the interaction between time of day and all the landcover variables was selected as the top-performing model (ΔAICc ≤ 6) (Table 5). All candidate models showed significant selection for sod by Buff-breasted Sandpipers and the top-performing model showed significant selection for cotton/soybean and significant selection against corn/sorghum, roads and woody cover (birds selecting locations farther from the two latter landcover types) (Fig. 3). The odds ratios from the top model indicated that at a population level, tracked birds were ~ 4.7 times more likely to use a location with one standard deviation increase in coverage of sod (P = 5.2 × 10–21), when all other covariates were held at their average. It also indicated a significant selection for cotton/soybean; tracked birds ~ 1.5 times more likely to use a location with every one standard deviation increase in coverage of cotton (P = 0.025). All interactions in this model were significant with exception of percent rice cover and distance to roads (Fig. 3). When comparing diurnal and nocturnal locations, models indicated birds selected against grassy cover during the day, but this effect was greater and statistically significant at night (P = 0.00057)(Fig. 3). The same relationship was observed for woody cover (P = 1.69 × 10–10)(Fig. 3). Cotton/soybean (P = 0.00022) and corn/sorghum (P = 0.000022) were also selected significantly less at night than in the day (Fig. 3). Even sod was selected for significantly less in the night than in the day (P = 0.0070), however this difference in effect size was very small (Fig. 3). To make a side-by-side comparison with the range-wide model results, we also visualize the estimates from the Texas model interacting season with all landcover types (Fig. 4), despite it being the third best ranked model (Table 5). Table 5 Model selection results for all the candidate models to explain variation in habitat selection for Buff-breasted Sandpipers in the Texas Coastal Plain using only data from the Texas study.

Interactions terms	Landcover covariates	ΔAICc	R2m	R2c	
Time of day	All landcover types	0	0.226	0.849	
None	All landcover types	69	0.223	0.849	
Season	All landcover types	70	0.224	0.842	
None	All covariates but road	395	0.214	0.851	
None	All covariates but rice	410	0.249	0.817	
None	All covariates but corn	486	0.242	0.810	
None	All covariates but rice, distance to road, and grassy cover	1056	0.268	0.767	
None	All covariates but corn, distance to road, and grassy cover	1118	0.242	0.762	
None	Only cropland	1350	0.247	0.776	
None	Only sod and woody cover	2114	0.255	0.662	
None	Only sod	2913	0.232	0.606	
None	Only woody and grassy cover	4230	0.266	0.525	
Model results indicate the interaction between time of day with all landcover variables best predicted Buff-breasted Sandpiper presence in the Texas Coastal Plain.

Fig. 3 Beta coefficient estimates from the top-ranking model describing habitat selection by Buff-breasted Sandpipers in the Texas Coastal Plain, using data from the Texas study. The top model included proportion of landcover types and distance to woody cover and roads and their interactions with the temporal variable time of day, with daytime as the reference level. Significant coefficients are indicated by a star and colors are representative of landcover type (see Fig. 2).

Habitat selection analysis: range-wide study

From the range-wide study, the model with season interacting with all landcover types was selected as the top-performing model (Table 6). The top model from the range-wide study generally agreed with the Texas model of same configuration (season*all landcover types), both indicating probability of presence increased with increasing proportion of sod and increasing distance to woody cover (Fig. 4). However, unlike the Texas model, percent sod had a significant interaction with season in the range-wide study (P = 0.014) (Fig. 4). Here, sod was selected for significantly more in spring compared to fall, although birds continued to select it preferentially overall (Fig. 4). Also, in contrast to the Texas study’s season model, the range-wide study’s top model indicated significant avoidance of grassy cover in spring (P = 0.00063), although the directions of the effect in both seasons approximate each other across the models (Fig. 4). One covariate, corn/sorghum, in the range-wide model showed an opposite pattern to the Texas top model’s estimates (Fig. 4). Corn/sorghum was selected for in fall (opposite to avoidance in the Texas top model), but avoided in spring. This is in contrast to the Texas model’s estimate, which did not find any significant difference between seasons (Fig. 4). Rice was significantly selected for in the top range-wide model (P = 0.0014), an effect not captured in the top Texas model (Fig. 4). Finally, the range-wide model did not find a statistically significant effect of distance to roads, whereas the Texas season model did (P = 0.031). Fig. 4 Beta coefficient estimates from models describing habitat selection by Buff-breasted Sandpipers in the Texas Coastal Plain using data from the Texas study (left) and the range-wide study (right). The estimates from each are derived from the models including all landcover variables and their interaction with season, which was the top-performing model from the range-wide study. Fall is the reference level for the interaction. Significant coefficients are indicated by a star and colors are representative of landcover types (see Fig. 2).

Table 6 Model selection results for all the candidate models to explain variation in habitat selection of Buff-breasted Sandpipers in the Texas Coastal Plain using data from the range-wide study.

Interactions terms	Landcover covariates	ΔAICc	R2m	R2c	
Season	All landcover types	0	0.500	0.607	
None	All landcover types	65	0.292	0.564	
Origin	All landcover types	67	0.325	0.560	
None	All covariates but rice	76	0.281	0.591	
None	All covariates but road	110	0.298	0.522	
None	All covariates but rice, distance to road, and grassy cover	171	0.212	0.437	
None	Only cropland	207	0.234	0.385	
None	All covariates but corn	351	0.331	0.469	
None	All covariates but corn, distance to road, and grassy cover	490	0.187	0.279	
None	Only sod and woody cover	535	0.202	0.232	
None	Only sod	799	0.051	0.119	
None	Only woody and grassy cover	1334	0.315	0.389	
Results indicate the model with season interacted with all landcover types is the best performing model at predicting Buff-breasted Sandpiper presence in the Texas Coastal Plain.

In the range-wide model where origin interacted with landcover types, origin only had one significant interaction, grassy cover being selected for significantly more by birds caught outside of Texas compared to birds caught in Texas (Fig. 5). Despite the differences between the Texas and range-wide analyses, in the model with ‘origin’ as an interaction term, origin was insignificant, indicating, importantly, that the effect of landcover did not vary as a consequence of whether birds were caught in Texas or outside of Texas.Fig. 5 Estimates of beta coefficients from the model describing habitat selection by Buff-breasted Sandpipers in Texas, using location data from the range-wide study. Model included all proportion and distance landcover covariates and interactions with the temporal variable origin. From Texas is the reference level for the interaction. Significant coefficients are indicated by a star and colors are representative of landcover.

Functional response curves

While the habitat selection analyses described population-level effects of landcover on Buff-breasted Sandpiper presence, the functional response curves provide an insight into how the species responds to a landcover type across a gradient of its availability (Fig. 6). The functional response curve for sod suggested birds were making a trade-off in fall; when sod was rare, birds selected it less than it was available, whereas when sod was common, birds selected it more. It appears that this tradeoff occurred once the mean proportion of sod within a 250 m buffer exceeded 0.3 (i.e., 30%) when back transforming from the log of availability (Fig. 6). In contrast, in spring all birds used sod greater than its availability. The functional response curves indicated cotton/soybean was selected against at average levels of availability for birds in fall, while spring migrants selected for cotton/soybean at most levels. Meanwhile, corn/sorghum is usually selected for less than available, with most individuals falling below the line indicating proportional selection, but some fall birds selecting for corn/sorghum when it was more available. Functional response curves indicated rice was generally avoided; in fall it was always avoided and in spring it was mostly avoided except at very high levels of availability. Selection of grassy cover was the most individually variable, but almost all individuals selected against this landcover type in both seasons. Birds appeared to select areas farther from woody cover when the average distance to woody cover in their stopover area of use was closer, but their avoidance decreased as average distance to woody cover increased. Finally, roads seemed to be selected for in proportion to their availability on a population level with a lot of individual variability (Fig. 6).Fig. 6 Multiplicative functional response curves for each landcover covariate by season explaining use (log of mean) versus availability (log of mean) in habitat types by Buff-breasted Sandpipers using data from Texas dataset. Log of the mean use by individual plotted against the log of the mean availability within their stopover area. Panels show how selection for a landcover varies by function of its availability for individual Buff-breasted Sandpipers tracked in the Texas Coastal Plain.

Discussion

Our study documents a clear selection by a migratory grassland shorebird for a rare, intensively managed crop (i.e., sod) within an agricultural landcover matrix. Contrary to our predictions, we found a general avoidance of grassy cover (hay and rangeland), with a strong selection for sod, as well to a lesser extent, other crops such as corn/sorghum and cotton/soybean. We also observed differences between nighttime and daytime habitat selection. Finally, consistent with our predictions, we observed seasonal variation in landcover types selected by Buff-breasted Sandpipers, corresponding to when these crops were at cultivation stages with short structure (i.e., recently seeded, germinating, harvested, or mowed). This supports existing literature evidencing the species’ dependence on short-stature environments from migration in the midcontinental United States41,43,86, Bolivia, Colombia40 and the nonbreeding grounds38,87. Altogether this suggests that although this species is quite specialized to environments with short vegetation (i.e., sod) or a predominance of bare earth (i.e., tilled row crops), it seems to be able to exploit a diversity of landcover types that have short-stature vegetation and bare ground.

A significant effect of rice landcover on Buff-breasted Sandpiper habitat selection was found only in the range-wide model; this covariate also had the largest scale of effect of any of the proportion landcover covariates (1000 m). This suggests our models are capturing more of an indirect effect by rice on habitat selection by the species. Although Buff-breasted Sandpipers did use rice fields occasionally (Fig. 2), as was found in a prior study in Louisiana22, it appears the species may be selecting for rice-growing areas, but only seldomly using rice fields themselves. Rice-growing areas in the study region likely represent majority cropland areas with dependable irrigation sources and moisture-retaining soils88. This is somewhat in contrast with how rice is used by Buff-breasted Sandpiper and other grassland shorebirds during the non-breeding period, where they are observed in dry paddies or paddies in the process of being flooded89,90. However, these studies were only accounts of use, not of selection in terms of the relative availability of rice to individuals.

Cotton/soybean landcover was also significantly selected for in the Texas top model, although with a much smaller effect size than sod. And although the season models from both Texas and range-wide studies suggest higher selection for cotton/soybean in spring, neither found a statistically significant seasonal difference. This was contrary to our initial prediction, in which we expected this row crop to be favored in spring, when fields were in early germination or growth stages, as opposed to fall when they would be avoided due to plants being leafed out and much taller. One explanation for this is early harvest and tilling of cotton and soybean may create short-stature bare fields in fall, in addition to it being suitable habitat in spring when it is just germinating. The functional response curve lends some support to this conclusion, with overall more positive selection for cotton in spring and much more individual variation in fall. Similar seasonal differences in selection were captured in both Texas and range-wide models, even though these were not statistically significant.

In contrast to cotton/soybean, corn/sorghum landcover was consistently selected against in the Texas models, but the range-wide top model captured a seasonal effect, where birds actually selected this crop in fall (Fig. 4). Corn and sorghum are often sown before cotton and soybean and thus would have taller seedlings than that of cotton and soybean52. These differences may explain the opposite selection pattern by Buff-breasted Sandpiper for these crops, and further underscores the importance of even small differences in vegetation height to the species14. Interpretation of this crop type’s effect, however, is complicated by the range-wide model’s indication of a seasonal effect, with positive selection in fall and negative selection in spring. This could be attributed to different harvest times across the much broader south-north gradient of land where range-wide tracked birds stopped relative to bird tracked from the Texas study, which were caught exclusively in the mid-coast52. More southern locales can begin harvesting up to a month earlier than central locales (~ June–July compared to July–August)52. Perhaps earlier harvest and tilling of corn/sorghum in these areas provided bare fields for Buff-breasted Sandpiper to exploit in fall52.

We also predicted that Buff-breasted Sandpipers would consistently select locations farther from woody cover (i.e., trees or shrubs) to minimize the risk of predation, and indeed, distance to woody cover was a highly significant landcover variable in all models. Roads were also avoided, although this effect was smaller than the avoidance of woody cover and was not significant in the range-wide model.

Our analyses also supported our prediction that site selection would be different during the day than at night. Sod was positively selected for during the day and night (Fig. 3). In contrast, corn/sorghum and woody cover, which were avoided overall, were avoided even more so at night, as was grassy cover. These selection patterns suggest that particular landcover types may pose a greater predation risk at night. This may be because the homogenous short-stature vegetation and paler background of sod fields offers birds a better view of approaching predators than the darker, taller and more heterogeneously structured grassy landcover types91. Overall, these results highlight that regardless of time of day, sod is important in explaining species presence.

The importance of sod to Buff-breasted Sandpipers was one of the most surprising findings of our study. Indeed, sod was the most salient effect in all models (both Texas and range-wide), was selected for at a very local level (ca 250 m) and was strongly selected for when it was highly available in an individual’s area of use. This finding was contrary to our assumption that observation of the species (via eBird and structured survey records) in sod farms was an artefact of high detectability and observer bias in this landcover type. We hypothesized less biased tracking data would indicate a preference for the plentiful rangeland and natural grasslands in the region, but grassy cover was generally avoided.

There were two possible limitations to our study that may have influenced these results. Firstly, our delineation of grassy cover using satellite-derived landcover products may have missed important distinctions within this landcover type across the Texas Coastal Plain. Unfortunately, it is still not feasible to identify grass heights at large spatial scales using remotely sensed data (see also Lanctot et al. 2004)92. This means our analyses would not have been able to capture evidence of short grass selection given all grass heights would have been combined, whether short or tall. This might explain the high variability and lack of significance of grassy cover in our top models. Regardless, grassy cover was very seldomly used by tracked birds in both the Texas and the range-wide study (< 10% and < 5% of used locations in this landcover type, respectively) (Fig. 2). The second limitation of the Texas study in particular was that all tracked birds were captured on just 5 sod farms in the mid-coast of the Texas Coastal Plain. This fact might make any findings from our analysis subject to a capture location effect. However, our analysis investigating the effect of a bird’s origin failed to find statistical evidence that birds captured within Texas or outside of Texas selected habitats differently. This provides confidence in the results of our analyses, and overall, we believe these limitations provide nuance rather than undermine our interpretations.

The demonstrated preference of sod and other cropland over more natural grassy cover in Texas contrasts with the regular use of rangelands during non-breeding and migration in South America14,30,40,87. We suspect there may be several reasons for these differences. In South America, grasslands used by Buff-breasted Sandpipers are characterized by seasonal flooding, and are often intensively grazed because ranchers know that they will lose the forage in these lowlands once they are submerged during the rainy season or when lagoons flood with marine waters. These disturbance regimes (flooding and grazing) work in concert to create large lawns of short-stature grasses during the birds’ stay in those regions14,40,87, in many ways mimicking or maintaining historical disturbance regimes. Indeed, sod farms share a semblance to these South American rangelands. In Texas, by contrast, historical grazing, fire, and flooding regimes have been drastically altered through contemporary and historic grazing practices, canalization of waterways, groundwater extraction, introduced exotic forage grasses, and fire suppression. These differences may offer some explanations for Buff-breasted Sandpiper avoidance of rangeland in our study.

Our analyses indirectly support previous literature indicating that this species is highly sensitive to vegetation height and structure14,86, almost exclusively using areas either dominated by bare ground or by vegetation < 6 cm in height. We also show a strong negative effect of woody cover on the species, in accordance with other studies on grassland shorebirds14,93,94. A legacy of overgrazing, and a convention for stocking rates that seek to evenly distribute grazing and thus prevent under- or over-utilization of forage by cattle have contributed to woody cover encroachment and homogenization of grasslands in the Texas Coastal Plain8,95,96. The suppression of fire, particularly high-intensity fires, has further favored this homogenization and facilitated colonization of woody plants into historically grass-dominated landscapes96–98. Large expanses of short-stature grasslands free of shrubs and trees may therefore be limited during Buff-breasted Sandpiper migration through the region.

Surface water availability is another possible explanation for why Buff-breasted Sandpipers may prefer croplands and sod over natural grassy cover in this region. We often observed Buff-breasted Sandpipers congregating in fields that had been recently irrigated and this seemed especially true during the hottest periods of the day. Sod, cotton and corn are all crops that require substantial irrigation, and the availability of surface water on farms may play a part in Buff-breasted Sandpiper’s selection of these landcover types. Water scarcity, driven by growing industrial, residential and agricultural demands in the region, and exacerbated by increased drought frequency due to climate change, has severely restricted the availability of ephemeral surface water outside of these intensively managed lands. The availability of water may thus explain Buff-breasted Sandpiper selection of these landcover types over less intensively managed rangeland. Surface water and soil moisture on these fields may benefit birds through direct and indirect effects, including thermal regulation and increased abundance of invertebrate prey.

Further, grasslands in Texas suffer from increasing abundances of non-native introduced grasses such as King Ranch (Bothriochloa ischaemum var. songarica) and Kleberg (Dichanthium annulatum) bluestems, which have been associated with lower insect diversity, richness and abundance than native species assemblages99–102. Indeed, a recent study evidenced a direct link between invertebrate declines and declines in vertebrate consumers103. In contrast, many insects classified as agricultural pests are actually increasing in abundance104. Red imported fire ants (Solenopsis invicta) have also been proposed to negatively affect invertebrate communities, although the literature is inconclusive on their overall effect105–108. Regular irrigation and fertilizer inputs may support higher abundances of invertebrate prey in cropland than in grasslands compromised by altered hydrology and non-native invasions. We highlight the importance of further study explicitly considering the role insect abundance, soil moisture, and Buff-breasted Sandpiper diet plays in habitat selection by this species.

Such high selection for sod and other cropland landcover by Buff-breasted Sandpipers is concerning, as these crops are often associated with frequent application of pesticides, such as neonicotinoid insecticides. Declines in bird populations, particularly grassland birds and insectivorous birds, have been linked with the prevalence of neonicotinoids in the environment109–111. Additionally, a study on contaminant exposure in shorebirds found direct evidence of exposure to cholinesterase-inhibiting pesticides in Buff-breasted Sandpipers sampled on early growth rice fields in South America112. So, while information on the effects of pesticides specifically on migrating shorebirds is generally lacking, the species almost exclusive use of highly managed landcover types suggests there could be negative population-level consequences. Additional study on the risk to and impacts of contaminant exposure on Buff-breasted Sandpipers and other migratory species could address these potential consequences.

In this light, we describe possible alternatives to cropland that may offer suitable migratory habitat for Buff-breasted Sandpipers with less risk of pesticide exposure. During the course of fieldwork for the Texas study, we observed the species using several key non-cropland landcover types, including a recently (< 1 month) summer-burned field of Gulf cordgrass (Spartina spartinae); a heavily grazed pasture; and moist-soil management waterfowl impoundments in the process of being flooded (see Supplementary Photos 1,2). Burns, heterogeneous grazing and moist-soil managed wetlands have been shown to provide shorebird habitat in other parts of the mid-continent96,113,114, and while anecdotal, our observations of Buff-breasted Sandpipers in areas under these management regimes adds to a body of literature supporting their potential for creation of shorebird habitat. Altogether, with the selection of early-stage or harvested crop fields, these observations also indicate the species is highly opportunistic and able to find and exploit ephemerally suitable conditions. Moreover, restoration of such ecological processes (fire and heterogeneous grazing) has been shown to support greater diversity of grassland bird communities at the landscape scale115,116, and we suggest that restoration of ephemeral water may also be important.

Shorebirds and grassland obligate species such as the Buff-breasted Sandpiper have undergone drastic declines in the past 50 years11, and these declines may be accelerating even faster than previously thought117. Despite these widespread declines, there is a relative paucity of studies on the occurrence and resource selection of many shorebird species outside of the breeding season, especially midcontinent migrants. Understanding habitat needs and potential threats faced by migratory grassland shorebirds such as the Buff-breasted Sandpiper is the first step in reversing their declines. Our finding that birds preferentially use intensively managed cropland over more natural grassy environments highlights a potential vulnerability of this species and emphasizes the importance of connecting rural working landscapes into the mosaic of conservation efforts across the midcontinent.

Conclusion

This study provides critical insights into factors driving habitat selection of Buff-breasted Sandpipers in an agricultural landscape on the Texas Coastal Plain. We found that sod was the most important landcover driving habitat selection, with birds being more likely to use locations with higher sod coverage, especially in spring. This finding was contrary to our predictions that grassy cover would be the main driver of habitat selection and that the species would select a greater diversity of landcover types than had been recorded during observer-based surveys. The preference of sod by Buff-breasted Sandpipers raises concern about the threat of pesticide exposure during this phase of its migration. It also raises questions about the management of grassland and rangeland for migratory grassland birds, stressing the need to create appropriate areas so that species like the Buff-breasted Sandpiper, which rely on short-stature environments, have habitat available to them during their migration through the region. Altogether, our findings also suggest the potential effects of surface water, contaminants and prey availability, and future studies on these topics may yield important insights into the species’ ecology. Further characterization of habitat requirements and resulting potential threats could greatly inform steps that may halt or reverse the declines of shorebird and grassland bird populations in North America observed over the past 50 years11,117.

Supplementary Information

Supplementary Information.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-71216-6.

Acknowledgements

We thank the many field technicians and volunteers who assisted with Buff-breasted Sandpiper captures. For the Texas study, we especially thank Jason Loghry, Ashley Garcia, Andres Rosales and Michael Kalisek. We enthusiastically thank the many generous landowners and managers who granted us access to their properties. We thank Texas Parks and Wildlife Mad Island Wildlife Management Area for providing us housing, and The Nature Conservancy for granting access to their property. We also want to extend additional thanks to the many collaborators who contributed to the capture efforts of the published range-wide dataset. The following organizations (and individual site managers) provided key logistical support: Texas Parks and Wildlife Department, Justin Hurst Wildlife Management Area, and Mad Island Wildlife Management Area, (David Butler, Trey Barron, Cliff Shackleford, and Lang Alford); The Nature Conservancy (Steven Goertz); Trinity National Wildlife Refuge (Laure Gonzales and Stuart Marcus); many anonymous turf farmers and managers; Texas Mid-Coast National Wildlife Refuge Complex (Jennifer Sanchez); Environmental Coordinators at B.P. Exploration Inc.; Entities at Argentina; Uruguay: Sistema Nacional de Areas Protegidas, Ministerio del Ambiente and PROBIDES, Brazil. The following individuals provided skilled field assistance: (United States): Bart Ballard, Stephanie Bilodeau, Charlie Brower, Lindsay Brown, Peter Detweiler, Bob Friedrichs, Loren Gallo, Danielle Gerik, Susan Heath, Jason Loghry, Peter Melde, David Newstead, Devon Short, Kristin Vale, Jennifer Wilson, and Woody Woodrow; (Argentina): David Balderrama, Daniel Blanco, Alex Fletcher; (Uruguay): Leandro Bergamino, Virginia Sanz, Sasha Hackembruck, Hugo Inda, Graciela Amorín; (Brasil): Fernando Faria, Gabriel Canani Sampaio, and Nicholas Winterle Daudt.

Author contributions

T.L.T. and R.B.L. originally formulated the idea and secured funding for the range-wide study. R.B.L. and B.M.B. originally formulated the idea and secured funding for the follow-up Texas study; T.L.R. further developed the methodology; T.L.T. and R.B.L. conducted fieldwork and collected data for the range-wide study; R.B.L., B.M.B., and T.L.R. conducted fieldwork and collected data for the Texas study; T.L.R. performed statistical analyses; T.L.R. led authorship of the manuscript and all authors contributed to data interpretation and drafts, and read and approved the final manuscript.

Funding

The Texas study was funded by the Caesar Kleberg Wildlife Research Institute at Texas A&M University-Kingsville, U.S. Fish and Wildlife Service Alaska Region, Asociación Calidris, National Fish and Wildlife Foundation, Neotropical Migratory Bird Conservation Program, Knobloch Family Foundation, and Manomet Incorporated. This study was also made possible through a graduate research fellowship with the Rob & Bessie Welder Wildlife Foundation. This manuscript is Welder Contribution Number 742 and Caesar Kleberg Wildlife Research Institute Manuscript Number 24-108. The range-wide study was funded by the U.S. Geological Survey/U.S. Fish and Wildlife Service Science Support Program, National Fish and Wildlife Foundation, and Neotropical Migratory Bird Conservation Program, with additional support from B.P. Exploration (Alaska), Wildlife Conservation Society, Max Planck Institute for Ornithology (Bart Kempenaers), Environment and Climate Change Canada (Jennie Rausch, Marc-Andre Cyr), U.S. Geological Survey Alaska Science Center, and U.S. Fish and Wildlife Service Migratory Bird Management. Argentina funders: Organismo Provincial para el Desarrollo Sostenible, Buenos Aires; Brazil funders: SAVE Brasil, Manomet, Inc., Instituto Neoenergia; Uruguay funders: Centro Universitario Regional del Este, Universidad de la República, Uruguay, Aves Uruguay and Fundación Lagunas Costeras, Wildlife Conservation Society funders. Funding organizations did not have input into the content of the manuscript. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the United States Government or the National Fish and Wildlife Foundation.

Data availability

The range-wide study dataset is available at Tibbitts et al. (2023). The Texas study dataset along with the custom sod layer and the R code for all analyses are available on Zenodo: 10.5281/zenodo.12821771.

Competing interests.

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. Askins RA Conservation of grassland birds in North America: Understanding ecological processes in different regions: Report of the AOU Committee on Conservation Ornithol. Monogr. 2007 iii–viii 1 46
Askins, R. A. et al. Conservation of grassland birds in North America: Understanding ecological processes in different regions: Report of the AOU Committee on Conservation. Ornithol. Monogr. iii–viii, 1–46 (2007).
2. Hill JM Egan JF Stauffer GE Diefenbach DR Habitat availability is a more plausible explanation than insecticide acute toxicity for U.S. grassland bird species declines PLoS ONE 2014 9 e98064 10.1371/journal.pone.0098064 24846309
Hill, J. M., Egan, J. F., Stauffer, G. E. & Diefenbach, D. R. Habitat availability is a more plausible explanation than insecticide acute toxicity for U.S. grassland bird species declines. PLoS ONE 9, e98064 (2014).24846309 10.1371/journal.pone.0098064
3. Stanton RL Morrissey CA Clark RG Analysis of trends and agricultural drivers of farmland bird declines in North America: A review Agric. Ecosyst. Environ. 2018 254 244 254 10.1016/j.agee.2017.11.028
Stanton, R. L., Morrissey, C. A. & Clark, R. G. Analysis of trends and agricultural drivers of farmland bird declines in North America: A review. Agric. Ecosyst. Environ. 254, 244–254 (2018).10.1016/j.agee.2017.11.028
4. Samson F Knopf F Prairie conservation in North America BioScience 1994 44 418 421 10.2307/1312365
Samson, F. & Knopf, F. Prairie conservation in North America. BioScience 44, 418–421 (1994).10.2307/1312365
5. Karl JW Hoth J North American Grassland priority conservation areas Comm. Environ. Coop. Nat. Conserv. 2005 1 152 10.13140/RG.2.2.18161.92008
Karl, J. W. & Hoth, J. North American Grassland priority conservation areas. Comm. Environ. Coop. Nat. Conserv. 1, 152. 10.13140/RG.2.2.18161.92008 (2005).10.13140/RG.2.2.18161.92008
6. With KA King AW Jensen WE Remaining large grasslands may not be sufficient to prevent grassland bird declines Biol. Conserv. 2008 141 3152 3167 10.1016/j.biocon.2008.09.025
With, K. A., King, A. W. & Jensen, W. E. Remaining large grasslands may not be sufficient to prevent grassland bird declines. Biol. Conserv. 141, 3152–3167 (2008).10.1016/j.biocon.2008.09.025
7. van Vliet J Direct and indirect loss of natural area from urban expansion Nat. Sustain. 2019 2 755 763 10.1038/s41893-019-0340-0
van Vliet, J. Direct and indirect loss of natural area from urban expansion. Nat. Sustain. 2, 755–763 (2019).10.1038/s41893-019-0340-0
8. Fuhlendorf SD Engle DM Elmore RD Limb RF Bidwell TG Conservation of pattern and process: Developing an alternativeparadigm of rangeland management Rangel. Ecol. Manag. 2012 65 579 589 10.2111/REM-D-11-00109.1
Fuhlendorf, S. D., Engle, D. M., Elmore, R. D., Limb, R. F. & Bidwell, T. G. Conservation of pattern and process: Developing an alternativeparadigm of rangeland management. Rangel. Ecol. Manag. 65, 579–589 (2012).10.2111/REM-D-11-00109.1
9. Briggs JM An ecosystem in transition: Causes and consequences of the conversion of mesic grassland to shrubland BioScience 2005 55 243 254 10.1641/0006-3568(2005)055[0243:AEITCA]2.0.CO;2
Briggs, J. M. et al. An ecosystem in transition: Causes and consequences of the conversion of mesic grassland to shrubland. BioScience 55, 243–254 (2005).10.1641/0006-3568(2005)055[0243:AEITCA]2.0.CO;2
10. Bestelmeyer BT The grassland-shrubland regime shift in the southwestern United States: Misconceptions and their implications for management BioScience 2018 68 678 690 10.1093/biosci/biy065
Bestelmeyer, B. T. et al. The grassland-shrubland regime shift in the southwestern United States: Misconceptions and their implications for management. BioScience 68, 678–690 (2018).10.1093/biosci/biy065
11. Rosenberg KV Decline of the North American avifauna Science 2019 366 120 124 10.1126/science.aaw1313 31604313
Rosenberg, K. V. et al. Decline of the North American avifauna. Science 366, 120–124 (2019).31604313 10.1126/science.aaw1313
12. Douglas D Jansen R A global review identifies agriculture as the main threat to declining grassland birds Ibis 2023 165 1107 1128 10.1111/ibi.13223
Douglas, D. & Jansen, R. A global review identifies agriculture as the main threat to declining grassland birds. Ibis 165, 1107–1128 (2023).10.1111/ibi.13223
13. Fahrig L Functional landscape heterogeneity and animal biodiversity in agricultural landscapes Ecol. Lett. 2011 14 101 112 10.1111/j.1461-0248.2010.01559.x 21087380
Fahrig, L. et al. Functional landscape heterogeneity and animal biodiversity in agricultural landscapes. Ecol. Lett. 14, 101–112 (2011).21087380 10.1111/j.1461-0248.2010.01559.x
14. Aldabe J Lanctot RB Blanco D Rocca P Inchausti P Managing grasslands to maximize migratory shorebird use and livestock production Rangel. Ecol. Manag. 2019 72 150 159 10.1016/j.rama.2018.08.001
Aldabe, J., Lanctot, R. B., Blanco, D., Rocca, P. & Inchausti, P. Managing grasslands to maximize migratory shorebird use and livestock production. Rangel. Ecol. Manag. 72, 150–159 (2019).10.1016/j.rama.2018.08.001
15. Scholtz R Twidwell D The last continuous grasslands on Earth: Identification and conservation importance Conserv. Sci. Pract. 2022 4 e626 10.1111/csp2.626
Scholtz, R. & Twidwell, D. The last continuous grasslands on Earth: Identification and conservation importance. Conserv. Sci. Pract. 4, e626 (2022).10.1111/csp2.626
16. Wear, D. N. & Greis, J. G. The Southern Forest Futures Project: Technical Report. (U.S. Department of Agriculture, Forest Service, Southern Research Station, 2013). 10.2737/srs-gtr-178.
17. Leslie Jr., D. M. An International Borderland of Concern: Conservation of Biodiversity in the Lower Rio Grande Valley. 136 http://pubs.er.usgs.gov/publication/sir20165078 (2016).
18. Hakkenberg CR Dannenberg MP Song C Ensor KB Characterizing multi-decadal, annual land cover change dynamics in Houston, TX based on automated classification of Landsat imagery Int. J. Remote Sens. 2019 40 693 718 10.1080/01431161.2018.1516318
Hakkenberg, C. R., Dannenberg, M. P., Song, C. & Ensor, K. B. Characterizing multi-decadal, annual land cover change dynamics in Houston, TX based on automated classification of Landsat imagery. Int. J. Remote Sens. 40, 693–718 (2019).10.1080/01431161.2018.1516318
19. Sorice MG Kreuter UP Wilcox BP Fox WE Classifying land-ownership motivations in central, Texas, USA: A first step in understanding drivers of large-scale land cover change J. Arid Environ. 2012 80 56 64 10.1016/j.jaridenv.2012.01.004
Sorice, M. G., Kreuter, U. P., Wilcox, B. P. & Fox, W. E. Classifying land-ownership motivations in central, Texas, USA: A first step in understanding drivers of large-scale land cover change. J. Arid Environ. 80, 56–64 (2012).10.1016/j.jaridenv.2012.01.004
20. Brennan LA Kuvlesky WP Jr North American grassland birds: An unfolding conservation crisis? J. Wildl. Manag. 2005 69 1 13 10.2193/0022-541X(2005)069<0001:NAGBAU>2.0.CO;2
Brennan, L. A. & Kuvlesky, W. P. Jr. North American grassland birds: An unfolding conservation crisis?. J. Wildl. Manag. 69, 1–13 (2005).10.2193/0022-541X(2005)069<0001:NAGBAU>2.0.CO;2
21. Noss RF How global biodiversity hotspots may go unrecognized: lessons from the North American Coastal Plain Divers. Distrib. 2015 21 236 244 10.1111/ddi.12278
Noss, R. F. et al. How global biodiversity hotspots may go unrecognized: lessons from the North American Coastal Plain. Divers. Distrib. 21, 236–244 (2015).10.1111/ddi.12278
22. Norling W Jeske CW Thigpen TF Chadwick PC Estimating shorebird populations during spring stopover in rice fields of the Louisiana and Texas gulf coastal plain Waterbirds 2012 35 361 370 10.1675/063.035.0301
Norling, W., Jeske, C. W., Thigpen, T. F. & Chadwick, P. C. Estimating shorebird populations during spring stopover in rice fields of the Louisiana and Texas gulf coastal plain. Waterbirds 35, 361–370 (2012).10.1675/063.035.0301
23. Johnsgard, P. Wings over the great plains: Bird migrations in the Central Flyway. Zea E-Books Collect. (2012).
24. Skagen SK Knopf FL Samson FB Stopover ecology of transitory populations: The case of migrant shorebirds Ecology and Conservation of Great Plains Vertebrates 1997 New York Springer 244 269
Skagen, S. K. Stopover ecology of transitory populations: The case of migrant shorebirds. In Ecology and Conservation of Great Plains Vertebrates Vol. 125 (eds Knopf, F. L. & Samson, F. B.) 244–269 (Springer, New York, 1997).
25. Skagen, S. K., Sharpe, P. B., Waltermire, R. G. & Dillon, M. B. Biogeographical profiles of shorebird migration in midcontinental North America. 46 (1999).
26. Rakhimberdiev, E. et al. Fuelling conditions at staging sites can mitigate Arctic warming effects in a migratory bird. Nat. Commun. 9, 4263 (2018).
27. Mehlman DW Conserving stopover sites for forest-dwelling migratory landbirds The Auk 2005 122 1281 1290 10.1093/auk/122.4.1281
Mehlman, D. W. et al. Conserving stopover sites for forest-dwelling migratory landbirds. The Auk 122, 1281–1290 (2005).10.1093/auk/122.4.1281
28. Hewson CM Thorup K Pearce-Higgins JW Atkinson PW Population decline is linked to migration route in the Common Cuckoo Nat. Commun. 2016 7 1 8 10.1038/ncomms12296
Hewson, C. M., Thorup, K., Pearce-Higgins, J. W. & Atkinson, P. W. Population decline is linked to migration route in the Common Cuckoo. Nat. Commun. 7, 1–8 (2016).10.1038/ncomms12296
29. McCarty JP Wolfenbarger LL Laredo CD Pyle P Lanctot RB Billerman SM Keeney BK Rodewald PG Schulenberg TS Buff-breasted Sandpiper (Calidris subruficollis) Birds of the World 2020 Ithaca Cornell Lab of Ornithology
McCarty, J. P., Wolfenbarger, L. L., Laredo, C. D., Pyle, P. & Lanctot, R. B. Buff-breasted Sandpiper (Calidris subruficollis). In Birds of the World (eds Billerman, S. M. et al.) (Cornell Lab of Ornithology, Ithaca, 2020).
30. Lanctot, R. B. et al. Conservation Plan for the Buff-Breasted Sandpiper (Tryngites Subruficollis). Version 1.0. (2009).
31. BirdLife International. Calidris subruficollis (amended version of 2016 assessment). The IUCN Red List of Threatened Species (2017).
32. Lanctot RB Light-level geolocation reveals migration patterns of the Buff-breasted Sandpiper Wader Study 2016 123 29 43 10.18194/ws.00032
Lanctot, R. B. et al. Light-level geolocation reveals migration patterns of the Buff-breasted Sandpiper. Wader Study 123, 29–43 (2016).10.18194/ws.00032
33. Sullivan BL eBird: A citizen-based bird observation network in the biological sciences Biol. Conserv. 2009 142 2282 2292 10.1016/j.biocon.2009.05.006
Sullivan, B. L. et al. eBird: A citizen-based bird observation network in the biological sciences. Biol. Conserv. 142, 2282–2292 (2009).10.1016/j.biocon.2009.05.006
34. Mair L Ruete A Explaining spatial variation in the recording effort of citizen science data across multiple taxa PLOS ONE 2016 11 e0147796 10.1371/journal.pone.0147796 26820846
Mair, L. & Ruete, A. Explaining spatial variation in the recording effort of citizen science data across multiple taxa. PLOS ONE 11, e0147796 (2016).26820846 10.1371/journal.pone.0147796
35. Tiago P Ceia-Hasse A Marques TA Capinha C Pereira HM Spatial distribution of citizen science casuistic observations for different taxonomic groups Sci. Rep. 2017 7 12832 10.1038/s41598-017-13130-8 29038469
Tiago, P., Ceia-Hasse, A., Marques, T. A., Capinha, C. & Pereira, H. M. Spatial distribution of citizen science casuistic observations for different taxonomic groups. Sci. Rep. 7, 12832 (2017).29038469 10.1038/s41598-017-13130-8
36. Zhang G Spatial and temporal patterns in volunteer data contribution activities: A case study of eBird ISPRS Int. J. Geo-Inf. 2020 9 597 10.3390/ijgi9100597
Zhang, G. Spatial and temporal patterns in volunteer data contribution activities: A case study of eBird. ISPRS Int. J. Geo-Inf. 9, 597 (2020).10.3390/ijgi9100597
37. Lanctot RB Conservation status of the Buff-breasted Sandpiper: Historic and contemporary distribution and abundance in South America Wilson Bull. 2002 114 44 72 10.1676/0043-5643(2002)114[0044:CSOTBB]2.0.CO;2
Lanctot, R. B. et al. Conservation status of the Buff-breasted Sandpiper: Historic and contemporary distribution and abundance in South America. Wilson Bull. 114, 44–72 (2002).10.1676/0043-5643(2002)114[0044:CSOTBB]2.0.CO;2
38. Blanco DE Pastizales templados del sur de américa del sur como hábitat de aves playeras migratorias Ornitol Neotropical 2004 15 159 167
Blanco, D. E. et al. Pastizales templados del sur de américa del sur como hábitat de aves playeras migratorias Ornitol. Neotropical 15, 159–167 (2004).
39. Isacch JP Cardoni DA Different grazing strategies are necessary to conserve endangered grassland birds in short and tall salty grasslands of the flooding pampas The Condor 2011 113 724 734 10.1525/cond.2011.100123
Isacch, J. P. & Cardoni, D. A. Different grazing strategies are necessary to conserve endangered grassland birds in short and tall salty grasslands of the flooding pampas. The Condor 113, 724–734 (2011).10.1525/cond.2011.100123
40. Ruiz-Guerra C Eusse-González D Arango C Miranda L Beltrán YA Spring status of buff-breasted sandpipers in Colombia Wader Study Group Bull. 2013 120 202 205
Ruiz-Guerra, C., Eusse-González, D., Arango, C., Miranda, L. & Beltrán, Y. A. Spring status of buff-breasted sandpipers in Colombia. Wader Study Group Bull. 120, 202–205 (2013).
41. Jorgensen JG McCarty JP Wolfenbarger LLR Buff-breasted sandpiper density and numbers during migratory stopover in the rainwater basin Nebraska Condor 2008 110 63 69 10.1525/cond.2008.110.1.63
Jorgensen, J. G., McCarty, J. P. & Wolfenbarger, L. L. R. Buff-breasted sandpiper density and numbers during migratory stopover in the rainwater basin Nebraska. Condor 110, 63–69 (2008).10.1525/cond.2008.110.1.63
42. McCarty JP Jorgensen JG Wolfenbarger LL Behavior of Buff-breasted Sandpipers (Tryngites subruficollis) during migratory stopover in agricultural fields PLoS ONE 2009 4 e8000 10.1371/journal.pone.0008000 19956768
McCarty, J. P., Jorgensen, J. G. & Wolfenbarger, L. L. Behavior of Buff-breasted Sandpipers (Tryngites subruficollis) during migratory stopover in agricultural fields. PLoS ONE 4, e8000 (2009).19956768 10.1371/journal.pone.0008000
43. Penner RL Andres BA Lyons JE Young EA Spring surveys (2011–2014) for American Golden-Plovers (Pluvialis dominica), Upland Sandpipers (Bartramia longicauda), and Buff-breasted Sandpipers (Calidris subruficollis) in the Flint Hills Kans. Ornithol. Soc. Bull. 2015 66 37 52
Penner, R. L., Andres, B. A., Lyons, J. E. & Young, E. A. Spring surveys (2011–2014) for American Golden-Plovers (Pluvialis dominica), Upland Sandpipers (Bartramia longicauda), and Buff-breasted Sandpipers (Calidris subruficollis) in the Flint Hills. Kans. Ornithol. Soc. Bull. 66, 37–52 (2015).
44. 2017 U.S. Census of Agriculture. https://www.nass.usda.gov/Publications/AgCensus/2017/Full_Report/Volume_1,_Chapter_1_US/usv1.txt (2019).
45. McClure CJW Ware HE Carlisle J Kaltenecker G Barber JR An experimental investigation into the effects of traffic noise on distributions of birds: avoiding the phantom road Proc. R. Soc. B Biol. Sci. 2013 280 20132290 10.1098/rspb.2013.2290
McClure, C. J. W., Ware, H. E., Carlisle, J., Kaltenecker, G. & Barber, J. R. An experimental investigation into the effects of traffic noise on distributions of birds: avoiding the phantom road. Proc. R. Soc. B Biol. Sci. 280, 20132290 (2013).10.1098/rspb.2013.2290
46. Benítez-López A Alkemade R Verweij PA The impacts of roads and other infrastructure on mammal and bird populations: A meta-analysis Biol. Conserv. 2010 143 1307 1316 10.1016/j.biocon.2010.02.009
Benítez-López, A., Alkemade, R. & Verweij, P. A. The impacts of roads and other infrastructure on mammal and bird populations: A meta-analysis. Biol. Conserv. 143, 1307–1316 (2010).10.1016/j.biocon.2010.02.009
47. Pearlstine EV Mazzotti FJ Kelly MH Relative distribution and abundance of wintering raptors in agricultural and wetland landscapes of South Florida J. Raptor Res. 2006 40 81 85 10.3356/0892-1016(2006)40[81:RDAAOW]2.0.CO;2
Pearlstine, E. V., Mazzotti, F. J. & Kelly, M. H. Relative distribution and abundance of wintering raptors in agricultural and wetland landscapes of South Florida. J. Raptor Res. 40, 81–85 (2006).10.3356/0892-1016(2006)40[81:RDAAOW]2.0.CO;2
48. Johnston-González R Abril E Predation risk and resource availability explain roost locations of Whimbrel Numenius phaeopus in a tropical mangrove delta Ibis 2019 161 839 853 10.1111/ibi.12678
Johnston-González, R. & Abril, E. Predation risk and resource availability explain roost locations of Whimbrel Numenius phaeopus in a tropical mangrove delta. Ibis 161, 839–853 (2019).10.1111/ibi.12678
49. Griffith, G., Bryce, S., Omernik, J. & Rogers A., Ecoregions of Texas. Texas Commission on Environmental Quality. 125 (2007).
50. Ball, C. S. H. & G. D. L. D. M. Southern Forages: Modern Concepts for Forage Crop Management. (IPNI, 2007).
51. Wied JP Perotto-Baldivieso HL Conkey AAT Brennan LA Mata JM Invasive grasses in South Texas rangelands: Historical perspectives and future directions Invasive Plant Sci. Manag. 2020 13 41 58 10.1017/inp.2020.11
Wied, J. P., Perotto-Baldivieso, H. L., Conkey, A. A. T., Brennan, L. A. & Mata, J. M. Invasive grasses in South Texas rangelands: Historical perspectives and future directions. Invasive Plant Sci. Manag. 13, 41–58 (2020).10.1017/inp.2020.11
52. USDA-NASS. Texas Crop Progress and Condition. https://www.nass.usda.gov/Statistics_by_State/Texas/Publications/Crop_Progress_&_Condition/prevCW/index.php (2024).
53. Fuhlendorf SD Engle DM Restoring heterogeneity on rangelands: ecosystem management based on evolutionary grazing patterns: we propose a paradigm that enhances heterogeneity instead of homogeneity to promote biological diversity and wildlife habitat on rangelands grazed by livestock BioScience 2001 51 625 632 10.1641/0006-3568(2001)051[0625:RHOREM]2.0.CO;2
Fuhlendorf, S. D. & Engle, D. M. Restoring heterogeneity on rangelands: ecosystem management based on evolutionary grazing patterns: we propose a paradigm that enhances heterogeneity instead of homogeneity to promote biological diversity and wildlife habitat on rangelands grazed by livestock. BioScience 51, 625–632 (2001).10.1641/0006-3568(2001)051[0625:RHOREM]2.0.CO;2
54. Pitman, W. D. Pastures of the US Western Gulf Coast Region. in Pastures: Dynamics, Economics and Management (ed. Prochazka, N. T.) 85–107 (Nova Science Publishers, Hauppauge, New York, USA, 2011).
55. Baker DL Guthery FS Effects of continuous grazing on habitat and density of ground-foraging birds in south Texas Rangel. Ecol. Manag. Range Manag. Arch. 1990 43 2 5
Baker, D. L. & Guthery, F. S. Effects of continuous grazing on habitat and density of ground-foraging birds in south Texas. Rangel. Ecol. Manag. Range Manag. Arch. 43, 2–5 (1990).
56. Tibbitts, L., Lanctot, R. B. & Douglas, D. C. Tracking Data for Buff-breasted Sandpipers (Calidris subruficollis) (ver. 1.0, October 2023): U.S. Geological Survey Data Release 10.5066/P9TYMUID (2023).
57. Almeida JB After-hatch and hatch year Buff-breasted Sandpipers Calidris subruficollis can be sexed accurately using morphometric measures Wader Study 2020 127 1 9 10.18194/ws.00189
Almeida, J. B. et al. After-hatch and hatch year Buff-breasted Sandpipers Calidris subruficollis can be sexed accurately using morphometric measures. Wader Study 127, 1–9 (2020).10.18194/ws.00189
58. Koopman K Hulscher JB Catching waders with a ‘wilsternet’ Wader Study Group Bull. 1979 26 10 12
Koopman, K. & Hulscher, J. B. Catching waders with a ‘wilsternet’. Wader Study Group Bull. 26, 10–12 (1979).
59. Almeida JB Wintering ecology of Buff-breasted Sandpipers (Tryngites subruficollis) in southern Brazil 2009 Reno University of Nevada
Almeida, J. B. Wintering ecology of Buff-breasted Sandpipers (Tryngites subruficollis) in southern Brazil (University of Nevada, Reno, 2009).
60. Lanctot RB Weatherhead PJ Kempenaers B Scribner KT Male traits, mating tactics and reproductive success in the buff-breasted sandpiper Tryngites subruficollis Anim. Behav. 1998 56 419 432 10.1006/anbe.1998.0841 9787033
Lanctot, R. B., Weatherhead, P. J., Kempenaers, B. & Scribner, K. T. Male traits, mating tactics and reproductive success in the buff-breasted sandpiper Tryngites subruficollis. Anim. Behav. 56, 419–432 (1998).9787033 10.1006/anbe.1998.0841
61. R Core Team R: A Language and Environment for Statistical Computing 2024 Vienna R Foundation for Statistical Computing
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2024).
62. Posit team. RStudio: Integrated Development Environment for R. (Posit Software, PBC, Boston, MA, 2024). http://www.posit.co/
63. Kranstauber B Kays R Lapoint SD Wikelski M Safi K A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement J. Anim. Ecol. 2012 81 738 746 10.1111/j.1365-2656.2012.01955.x 22348740
Kranstauber, B., Kays, R., Lapoint, S. D., Wikelski, M. & Safi, K. A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement. J. Anim. Ecol. 81, 738–746 (2012).22348740 10.1111/j.1365-2656.2012.01955.x
64. Kranstauber, B., Smolla, M. & Scharf, A. K. move: Visualizing and Analyzing Animal Track Data. (2023). R package version 3.1.0.
65. Manly BF McDonald L Thomas DL McDonald TL Erickson WP Resource Selection by Animals: Statistical Design and Analysis for Field Studies 2007 Belrin Springer
Manly, B. F., McDonald, L., Thomas, D. L., McDonald, T. L. & Erickson, W. P. Resource Selection by Animals: Statistical Design and Analysis for Field Studies (Springer, Belrin, 2007).
66. Johnson CJ Nielsen SE Merrill EH McDonald TL Boyce MS Resource selection functions based on use-availability data: theoretical motivation and evaluation methods J. Wildl. Manag. 2006 70 347 357 10.2193/0022-541X(2006)70[347:RSFBOU]2.0.CO;2
Johnson, C. J., Nielsen, S. E., Merrill, E. H., McDonald, T. L. & Boyce, M. S. Resource selection functions based on use-availability data: theoretical motivation and evaluation methods. J. Wildl. Manag. 70, 347–357 (2006).10.2193/0022-541X(2006)70[347:RSFBOU]2.0.CO;2
67. Muff S Signer J Fieberg J Accounting for individual-specific variation in habitat-selection studies: efficient estimation of mixed-effects models using Bayesian or frequentist computation J. Anim. Ecol. 2020 89 80 92 10.1111/1365-2656.13087 31454066
Muff, S., Signer, J. & Fieberg, J. Accounting for individual-specific variation in habitat-selection studies: efficient estimation of mixed-effects models using Bayesian or frequentist computation. J. Anim. Ecol. 89, 80–92 (2020).31454066 10.1111/1365-2656.13087
68. Johnson DH The comparison of usage and availability measurements for evaluating resource preference Ecology 1980 61 65 71 10.2307/1937156
Johnson, D. H. The comparison of usage and availability measurements for evaluating resource preference. Ecology 61, 65–71 (1980).10.2307/1937156
69. Brooks ME glmmTMB Balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling R J. 2017 9 378 400 10.32614/RJ-2017-066
Brooks, M. E. et al. glmmTMB Balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9, 378–400 (2017).10.32614/RJ-2017-066
70. Ventura F Matthiopoulos J Jeglinski JWE Minimal overlap between areas of high conservation priority for endangered Galapagos pinnipeds and the conservation zone of the Galapagos Marine Reserve Aquat. Conserv. Mar. Freshw. Ecosyst. 2019 29 115 126 10.1002/aqc.2943
Ventura, F., Matthiopoulos, J. & Jeglinski, J. W. E. Minimal overlap between areas of high conservation priority for endangered Galapagos pinnipeds and the conservation zone of the Galapagos Marine Reserve. Aquat. Conserv. Mar. Freshw. Ecosyst. 29, 115–126 (2019).10.1002/aqc.2943
71. Fieberg J Signer J Smith B Avgar T A ‘How to’ guide for interpreting parameters in habitat-selection analyses J. Anim. Ecol. 2021 90 1027 1043 10.1111/1365-2656.13441 33583036
Fieberg, J., Signer, J., Smith, B. & Avgar, T. A ‘How to’ guide for interpreting parameters in habitat-selection analyses. J. Anim. Ecol. 90, 1027–1043 (2021).33583036 10.1111/1365-2656.13441
72. Nettleton D Nettleton D Chapter 6 - Selection of variables and factor derivation Commercial Data Mining, pp 79–104 2014 Boston Morgan Kaufmann
Nettleton, D. Chapter 6 - Selection of variables and factor derivation. In Commercial Data Mining, pp 79–104 (ed. Nettleton, D.) (Morgan Kaufmann, Boston, 2014). 10.1016/B978-0-12-416602-8.00006-6.
73. Lin L Validation and refinement of cropland data layer using a spatial-temporal decision tree algorithm Sci. Data 2022 9 63 10.1038/s41597-022-01169-w 35236869
Lin, L. et al. Validation and refinement of cropland data layer using a spatial-temporal decision tree algorithm. Sci. Data 9, 63 (2022).35236869 10.1038/s41597-022-01169-w
74. Gorelick N Google Earth Engine: Planetary-scale geospatial analysis for everyone Remote Sens. Environ. 2017 10.1016/j.rse.2017.06.031
Gorelick, N. et al. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ.10.1016/j.rse.2017.06.031 (2017).10.1016/j.rse.2017.06.031
75. Google. Map Data 2023. Imagery 2023 Airbus, Maxar Technologies, Landsat / Copernicus, CNES / Airbus.
76. Lark TJ Schelly IH Gibbs HK Accuracy, bias, and improvements in mapping crops and cropland across the United States using the USDA Cropland Data Layer Remote Sens. 2021 13 968 10.3390/rs13050968
Lark, T. J., Schelly, I. H. & Gibbs, H. K. Accuracy, bias, and improvements in mapping crops and cropland across the United States using the USDA Cropland Data Layer. Remote Sens. 13, 968 (2021).10.3390/rs13050968
77. U.S. Census Bureau. 2016 TIGER/Line Shapefiles (machine-readable data files). (2016).
78. Nielsen S Cranston J Stenhouse G Identification of priority areas for grizzly bear conservation and recovery in Alberta Canada. J. Conserv. Plan. 2009 5 38 60
Nielsen, S., Cranston, J. & Stenhouse, G. Identification of priority areas for grizzly bear conservation and recovery in Alberta. Canada. J. Conserv. Plan. 5, 38–60 (2009).
79. Mertes K Jarzyna MA Jetz W Hierarchical multi-grain models improve descriptions of species’ environmental associations, distribution, and abundance Ecol. Appl. 2020 30 e02117 10.1002/eap.2117 32154624
Mertes, K., Jarzyna, M. A. & Jetz, W. Hierarchical multi-grain models improve descriptions of species’ environmental associations, distribution, and abundance. Ecol. Appl. 30, e02117 (2020).32154624 10.1002/eap.2117
80. Holland JD Bert DG Fahrig L Determining the spatial scale of species’ response to habitat BioScience 2004 54 227 233 10.1641/0006-3568(2004)054[0227:DTSSOS]2.0.CO;2
Holland, J. D., Bert, D. G. & Fahrig, L. Determining the spatial scale of species’ response to habitat. BioScience 54, 227–233 (2004).10.1641/0006-3568(2004)054[0227:DTSSOS]2.0.CO;2
81. McGarigal K Wan HY Zeller KA Timm BC Cushman SA Multi-scale habitat selection modeling: A review and outlook Landsc. Ecol. 2016 31 1161 1175 10.1007/s10980-016-0374-x
McGarigal, K., Wan, H. Y., Zeller, K. A., Timm, B. C. & Cushman, S. A. Multi-scale habitat selection modeling: A review and outlook. Landsc. Ecol. 31, 1161–1175 (2016).10.1007/s10980-016-0374-x
82. Johnson JB Omland KS Model selection in ecology and evolution Trends Ecol. Evol. 2004 19 101 108 10.1016/j.tree.2003.10.013 16701236
Johnson, J. B. & Omland, K. S. Model selection in ecology and evolution. Trends Ecol. Evol. 19, 101–108 (2004).16701236 10.1016/j.tree.2003.10.013
83. Burnham KP Anderson DR Multimodel inference: Understanding AIC and BIC in model selection Sociol. Methods Res. 2004 33 261 304 10.1177/0049124104268644
Burnham, K. P. & Anderson, D. R. Multimodel inference: Understanding AIC and BIC in model selection. Sociol. Methods Res. 33, 261–304 (2004).10.1177/0049124104268644
84. Nakagawa S Schielzeth H A general and simple method for obtaining R2 from generalized linear mixed-effects models Methods Ecol. Evol. 2013 4 133 142 10.1111/j.2041-210x.2012.00261.x
Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).10.1111/j.2041-210x.2012.00261.x
85. Holbrook JD Functional responses in habitat selection: clarifying hypotheses and interpretations Ecol. Appl. 2019 29 e01852 10.1002/eap.1852 30653797
Holbrook, J. D. et al. Functional responses in habitat selection: clarifying hypotheses and interpretations. Ecol. Appl. 29, e01852 (2019).30653797 10.1002/eap.1852
86. Jorgensen JG Mccarty JP Wolfenbarger LL Landscape and habitat variables affecting Buff-breasted Sandpiper Tryngites subruficollis distribution during migratory stopover in the Rainwater Basin, Nebraska, USA Wader Study Group Bull. 2007 112 45 51
Jorgensen, J. G., Mccarty, J. P. & Wolfenbarger, L. L. Landscape and habitat variables affecting Buff-breasted Sandpiper Tryngites subruficollis distribution during migratory stopover in the Rainwater Basin, Nebraska, USA. Wader Study Group Bull. 112, 45–51 (2007).
87. Faria FA Trends and population estimate of the threatened Buff-breasted Sandpiper Calidris subruficollis wintering in coastal grasslands of southern Brazil Bird Conserv. Int. 2023 33 e61 10.1017/S0959270923000138
Faria, F. A. et al. Trends and population estimate of the threatened Buff-breasted Sandpiper Calidris subruficollis wintering in coastal grasslands of southern Brazil. Bird Conserv. Int. 33, e61 (2023).10.1017/S0959270923000138
88. Hobaugh WC Stutzenbaker CD Flickinger EL Smith LM Pederson RL Kaminski RM The Rice Prairies Habitat Management for Migrating and Wintering Waterfowl in North America 1989 Lubbock Texas Tech University Press 367 384
Hobaugh, W. C., Stutzenbaker, C. D. & Flickinger, E. L. The Rice Prairies. In Habitat Management for Migrating and Wintering Waterfowl in North America (eds Smith, L. M. et al.) 367–384 (Texas Tech University Press, Lubbock, 1989).
89. Dias RA Blanco DE Goijman AP Zaccagnini ME Density, habitat use, and opportunities for conservation of shorebirds in rice fields in southeastern South America The Condor 2014 116 384 393 10.1650/CONDOR-13-160.1
Dias, R. A., Blanco, D. E., Goijman, A. P. & Zaccagnini, M. E. Density, habitat use, and opportunities for conservation of shorebirds in rice fields in southeastern South America. The Condor 116, 384–393 (2014).10.1650/CONDOR-13-160.1
90. Blanco, D. E. & Dias, R. A. Uso de Arroceras Por Chorlos y Playeros Migratorios En El Sur de América Del Sur Use of Rice Fields by Migratory Shorebirds in Southern South America Implications for Conservation and Management Uso de Arroceras Por Chorlos y Playeros Migratorios En El Su (2006).
91. Rogers DI Battley PF Piersma T Van Gils JA Rogers KG High-tide habitat choice: insights from modelling roost selection by shorebirds around a tropical bay Anim. Behav. 2006 72 563 575 10.1016/j.anbehav.2005.10.029
Rogers, D. I., Battley, P. F., Piersma, T., Van Gils, J. A. & Rogers, K. G. High-tide habitat choice: insights from modelling roost selection by shorebirds around a tropical bay. Anim. Behav. 72, 563–575 (2006).10.1016/j.anbehav.2005.10.029
92. Lanctot RB Assessing habitat availability and use by Buff- breasted Sandpipers (Tryngites subruficollis) wintering in South America Ornitol. Neotropical 2004 15 367 376
Lanctot, R. B. et al. Assessing habitat availability and use by Buff- breasted Sandpipers (Tryngites subruficollis) wintering in South America. Ornitol. Neotropical 15, 367–376 (2004).
93. Douglas DJT Pearce-Higgins JW Relative importance of prey abundance and habitat structure as drivers of shorebird breeding success and abundance Anim. Conserv. 2014 17 535 543 10.1111/acv.12119
Douglas, D. J. T. & Pearce-Higgins, J. W. Relative importance of prey abundance and habitat structure as drivers of shorebird breeding success and abundance. Anim. Conserv. 17, 535–543 (2014).10.1111/acv.12119
94. Wilson JD Modelling edge effects of mature forest plantations on peatland waders informs landscape-scale conservation J. Appl. Ecol. 2014 51 204 213 10.1111/1365-2664.12173
Wilson, J. D. et al. Modelling edge effects of mature forest plantations on peatland waders informs landscape-scale conservation. J. Appl. Ecol. 51, 204–213 (2014).10.1111/1365-2664.12173
95. Scasta JD Constraints to restoring fire and grazing ecological processes to optimize grassland vegetation structural diversity Ecol. Eng. 2016 95 865 875 10.1016/j.ecoleng.2016.06.096
Scasta, J. D. et al. Constraints to restoring fire and grazing ecological processes to optimize grassland vegetation structural diversity. Ecol. Eng. 95, 865–875 (2016).10.1016/j.ecoleng.2016.06.096
96. Hovick TJ Restoring fire to grasslands is critical for migrating shorebird populations Ecol. Soc. Am. 2017 27 1805 1814
Hovick, T. J. et al. Restoring fire to grasslands is critical for migrating shorebird populations. Ecol. Soc. Am. 27, 1805–1814 (2017).
97. Archer SR Briske DD Woody plant encroachment: Causes and consequences Rangeland Systems: Processes, Management and Challenges 2017 Cham Springer 25 84
Archer, S. R. et al. Woody plant encroachment: Causes and consequences. In Rangeland Systems: Processes, Management and Challenges (ed. Briske, D. D.) 25–84 (Springer, Cham, 2017). 10.1007/978-3-319-46709-2_2.
98. Scholtz R High-intensity fire experiments to manage shrub encroachment: lessons learned in South Africa and the United States Afr. J. Range Forage Sci. 2022 39 148 159 10.2989/10220119.2021.2008004
Scholtz, R. et al. High-intensity fire experiments to manage shrub encroachment: lessons learned in South Africa and the United States. Afr. J. Range Forage Sci. 39, 148–159 (2022).10.2989/10220119.2021.2008004
99. Hickman KR Farley GH Channell R Steier JE Effects of old world bluestem (Bothriochloa ischaemum) on food availability and avian community composition within the mixed-grass prairie Southwest. Nat. 2006 51 524 530 10.1894/0038-4909(2006)51[524:EOOWBB]2.0.CO;2
Hickman, K. R., Farley, G. H., Channell, R. & Steier, J. E. Effects of old world bluestem (Bothriochloa ischaemum) on food availability and avian community composition within the mixed-grass prairie. Southwest. Nat. 51, 524–530 (2006).10.1894/0038-4909(2006)51[524:EOOWBB]2.0.CO;2
100. Andersen EM Cambrelin MN Steidl RJ Responses of grassland arthropods to an invasion by nonnative grasses Biol. Invasions 2019 21 405 416 10.1007/s10530-018-1831-z
Andersen, E. M., Cambrelin, M. N. & Steidl, R. J. Responses of grassland arthropods to an invasion by nonnative grasses. Biol. Invasions 21, 405–416 (2019).10.1007/s10530-018-1831-z
101. Burghardt KT Tallamy DW Philips C Shropshire KJ Non-native plants reduce abundance, richness, and host specialization in lepidopteran communities Ecosphere 2010 1 art11 10.1890/ES10-00032.1
Burghardt, K. T., Tallamy, D. W., Philips, C. & Shropshire, K. J. Non-native plants reduce abundance, richness, and host specialization in lepidopteran communities. Ecosphere 1, art11 (2010).10.1890/ES10-00032.1
102. Litt AR Cord EE Fulbright TE Schuster GL Effects of invasive plants on arthropods Conserv. Biol. 2014 28 1532 1549 10.1111/cobi.12350 25065640
Litt, A. R., Cord, E. E., Fulbright, T. E. & Schuster, G. L. Effects of invasive plants on arthropods. Conserv. Biol. 28, 1532–1549 (2014).25065640 10.1111/cobi.12350
103. Narango DL Tallamy DW Marra PP Nonnative plants reduce population growth of an insectivorous bird Proc. Natl. Acad. Sci. 2018 115 11549 11554 10.1073/pnas.1809259115 30348792
Narango, D. L., Tallamy, D. W. & Marra, P. P. Nonnative plants reduce population growth of an insectivorous bird. Proc. Natl. Acad. Sci. 115, 11549–11554 (2018).30348792 10.1073/pnas.1809259115
104. Sánchez-Bayo F Wyckhuys KAG Worldwide decline of the entomofauna: A review of its drivers Biol. Conserv. 2019 232 8 27 10.1016/j.biocon.2019.01.020
Sánchez-Bayo, F. & Wyckhuys, K. A. G. Worldwide decline of the entomofauna: A review of its drivers. Biol. Conserv. 232, 8–27 (2019).10.1016/j.biocon.2019.01.020
105. Epperson DM Allen CR Red imported fire ant impacts on upland arthropods in Southern Mississippi Am. Midl. Nat. 2010 163 54 63 10.1674/0003-0031-163.1.54
Epperson, D. M. & Allen, C. R. Red imported fire ant impacts on upland arthropods in Southern Mississippi. Am. Midl. Nat. 163, 54–63 (2010).10.1674/0003-0031-163.1.54
106. Helms KR Vinson SB Coexistence of native ants with the red imported fire ant Solenopsis invicta Southwest. Nat. 2001 46 396 400 10.2307/3672443
Helms, K. R. & Vinson, S. B. Coexistence of native ants with the red imported fire ant Solenopsis invicta. Southwest. Nat. 46, 396–400 (2001).10.2307/3672443
107. Hudman KL Stevenson M Contreras K Scott A Kopachena JG Experimental suppression of red imported fire ants (Solenopsis invicta) has little impact on the survival of eggs to third instar of spring-generation monarch butterflies (Danaus plexippus) due to buffering effects of host-plant arthropods Diversity 2023 15 331 10.3390/d15030331
Hudman, K. L., Stevenson, M., Contreras, K., Scott, A. & Kopachena, J. G. Experimental suppression of red imported fire ants (Solenopsis invicta) has little impact on the survival of eggs to third instar of spring-generation monarch butterflies (Danaus plexippus) due to buffering effects of host-plant arthropods. Diversity 15, 331 (2023).10.3390/d15030331
108. Morrison LW Long-term impacts of an arthropod-community invasion by the imported fire ant, Solenopsis invicta Ecology 2002 83 2337 2345 10.1890/0012-9658(2002)083[2337:LTIOAA]2.0.CO;2
Morrison, L. W. Long-term impacts of an arthropod-community invasion by the imported fire ant, Solenopsis invicta. Ecology 83, 2337–2345 (2002).10.1890/0012-9658(2002)083[2337:LTIOAA]2.0.CO;2
109. Rigal S Farmland practices are driving bird population decline across Europe Proc. Natl. Acad. Sci. 2023 120 e2216573120 10.1073/pnas.2216573120 37186854
Rigal, S. et al. Farmland practices are driving bird population decline across Europe. Proc. Natl. Acad. Sci. 120, e2216573120 (2023).37186854 10.1073/pnas.2216573120
110. Hallmann CA Foppen RPB van Turnhout CAM de Kroon H Jongejans E Declines in insectivorous birds are associated with high neonicotinoid concentrations Nature 2014 511 341 343 10.1038/nature13531 25030173
Hallmann, C. A., Foppen, R. P. B., van Turnhout, C. A. M., de Kroon, H. & Jongejans, E. Declines in insectivorous birds are associated with high neonicotinoid concentrations. Nature 511, 341–343 (2014).25030173 10.1038/nature13531
111. Li Y Miao R Khanna M Neonicotinoids and decline in bird biodiversity in the United States Nat. Sustain. 2020 3 1027 1035 10.1038/s41893-020-0582-x
Li, Y., Miao, R. & Khanna, M. Neonicotinoids and decline in bird biodiversity in the United States. Nat. Sustain. 3, 1027–1035 (2020).10.1038/s41893-020-0582-x
112. Strum KM Exposure of nonbreeding migratory shorebirds to cholinesterase-inhibiting contaminants in the western hemisphere Condor 2010 112 15 28 10.1525/cond.2010.090026
Strum, K. M. et al. Exposure of nonbreeding migratory shorebirds to cholinesterase-inhibiting contaminants in the western hemisphere. Condor 112, 15–28 (2010).10.1525/cond.2010.090026
113. Anderson JT Smith LM Invertebrate response to moist-soil management of playa wetlands Ecol. Appl. 2000 10 550 558 10.1890/1051-0761(2000)010[0550:IRTMSM]2.0.CO;2
Anderson, J. T. & Smith, L. M. Invertebrate response to moist-soil management of playa wetlands. Ecol. Appl. 10, 550–558 (2000).10.1890/1051-0761(2000)010[0550:IRTMSM]2.0.CO;2
114. Hands HM Ryan MR Smith JW Migrant shorebird use of marsh, moist-soil, and flooded agricultural habitats Wildl. Soc. Bull. 1991 1973–2006 19 457 464
Hands, H. M., Ryan, M. R. & Smith, J. W. Migrant shorebird use of marsh, moist-soil, and flooded agricultural habitats. Wildl. Soc. Bull. 1973–2006(19), 457–464 (1991).
115. Hovick TJ Elmore RD Fuhlendorf SD Structural heterogeneity increases diversity of non-breeding grassland birds Ecosphere 2014 5 art62 10.1890/ES14-00062.1
Hovick, T. J., Elmore, R. D. & Fuhlendorf, S. D. Structural heterogeneity increases diversity of non-breeding grassland birds. Ecosphere 5, art62 (2014).10.1890/ES14-00062.1
116. Hovick TJ Elmore RD Fuhlendorf SD Engle DM Hamilton RG Spatial heterogeneity increases diversity and stability in grassland bird communities Ecol. Appl. 2015 25 662 672 10.1890/14-1067.1 26214912
Hovick, T. J., Elmore, R. D., Fuhlendorf, S. D., Engle, D. M. & Hamilton, R. G. Spatial heterogeneity increases diversity and stability in grassland bird communities. Ecol. Appl. 25, 662–672 (2015).26214912 10.1890/14-1067.1
117. Smith PA Accelerating declines of North America’s shorebirds signal the need for urgent conservation action Appl. Ornithol. 2023 10.1093/ornithapp/duad003
Smith, P. A. et al. Accelerating declines of North America’s shorebirds signal the need for urgent conservation action. Appl. Ornithol.10.1093/ornithapp/duad003 (2023).10.1093/ornithapp/duad003
118. QGIS Development Team. QGIS Geographic Information System. QGIS Association (2024).
