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A habitat-based approach to determining the effects of drought on aridland bird communities

A habitat-based approach to determining the effects of drought on aridland bird communities Abstract Aridland breeding bird communities of the United States are among the most vulnerable to drought, with many species showing significant population declines associated with decreasing precipitation and increasing temperature. Individual breeding bird species have varied responses to drought which suggests complex responses to changes in water availability. Here, we evaluated the influence of water deficit, an integrative metric of drought stress, on breeding bird communities within 3 distinct aridland habitat types: riparian, pinyon-juniper, and sagebrush shrubland. We used 12 years of breeding bird survey data from 11 national parks and monuments in the Northern Colorado Plateau Inventory and Monitoring Network (NCPN). We used a multivariate community-level approach to test for the effect of annual water deficit on the bird communities in the 3 habitats. We found that bird communities responded to water deficit in all 3 habitat types, and 70% of the 30 species–habitat combinations show significant relationships between density and variation in water deficit. Our analyses revealed that the direction and magnitude of species responses to water deficit were habitat-dependent. The habitat-specific responses we observed suggest that the adaptive capacity of some species depends on the habitat in which they occur, a pattern only elucidated with our habitat-based approach. The direction and magnitude of the relationships between predicted densities and annual water deficit can be used to predict the relative sensitivity of species within habitat climate changes. These results provide the first attempt to determine how the indirect effect of changes in water availability might affect aridland breeding birds in distinct habitat types. Linking breeding bird density to annual water deficit may be valuable for predicting changes in species persistence and distribution in response to climate change. RESUMEN Las comunidades de aves reproductivas de tierras áridas de Estados Unidos están entre las más vulnerables a la sequía, con muchas especies mostrando declives poblacionales significativos asociados con disminuciones en la precipitación y aumentos en la temperatura. Las especies individuales de aves reproductivas tienen respuestas variadas a la sequía, lo que sugiere respuestas complejas a los cambios en la disponibilidad de agua. En este estudio, evaluamos la influencia del déficit de agua, una métrica integradora del estrés por sequía, sobre las comunidades de aves reproductivas dentro de tres tipos de hábitats áridos distintos: ribereño, piñón-enebro y matorral de artemisa. Usamos 12 años de datos de censos de aves reproductivas provenientes de 11 parques y monumentos nacionales de la Red de Monitoreo e Inventario de la Meseta del Norte de Colorado. Usamos un enfoque multivariado a nivel de comunidad para evaluar el efecto del déficit anual de agua sobre las comunidades de aves en los tres hábitats. Encontramos que las comunidades de aves respondieron al déficit de agua en todos los tres tipos de hábitat, y 70% de las 30 combinaciones de especies y hábitats mostraron relaciones significativas entre densidad y variación en el déficit de agua. Nuestros análisis revelaron que la dirección y magnitud de las respuestas de las especies al déficit de agua fue dependiente del hábitat. Las respuestas específicas al hábitat que observamos sugieren que la capacidad adaptativa de algunas especies depende del hábitat en el que están presentes, un patrón solo dilucidado con nuestro enfoque basado en el hábitat. La dirección y magnitud de las relaciones entre las densidades predichas y el déficit anual de agua puede ser usada para predecir la sensibilidad relativa de las especies al cambio climático dentro de cada hábitat. Estos resultados representan el primer intento para determinar cómo el efecto indirecto de los cambios en la disponibilidad de agua podría afectar a las aves reproductivas de las tierras áridas en distintos tipos de hábitats. Vincular la densidad de las aves reproductivas al déficit anual de agua puede ser importante para predecir los cambios en la persistencia y distribución de las especies en respuesta al cambio climático. Lay Summary Birds of the desert Southwest, a climate change hotspot, are among the most vulnerable groups in the United States and the risk of population declines increases with increasing drought frequency and intensity. Using 12 years of bird monitoring data, we determined how bird communities in 3 distinct habitats (riparian, pinyon-juniper, and sagebrush shrubland) responded to water deficit (a measure of drought stress) in 11 national parks and monuments in the Northern Colorado Plateau. We found that the aridland breeding bird community responses to annual water deficit depended on habitat type. Through the identification of the sensitivity of species to drought stress in specific habitats, land managers can further focus conservation efforts on the habitat in which a species is most vulnerable and prioritize habitat obligate species that show vulnerability to projected climate changes within essential habitat. Introduction The southwestern United States is a climate change hotspot where increasing aridity is projected across many scenarios (Seager et al. 2007, Diffenbaugh et al. 2008). Aridland songbird communities have been identified as one of the most vulnerable avian groups in the United States (Sauer et al. 2017, Rosenberg et al. 2019) and are particularly susceptible to drought as they already exist near physiological limits resulting from the combination of dry environmental conditions, high metabolic demands, and extreme rates of water loss. Even slight increases in ambient temperatures, which can lead to increased water requirements, can reduce foraging activity patterns (Albright et al. 2017), disrupt reproductive timing (Visser et al. 2009, McCreedy and van Riper 2015), and increase mortality rates (McKechnie and Wolf 2010). For aridland birds, temperature changes can result in abundance shifts (George et al. 1992, Albright et al. 2010a, Cruz-McDonnell and Wolf 2016, Roberts et al. 2019), lowered species richness (Albright et al. 2010b), lowered site occupancy (Riddell et al. 2019), and may result in broad-scale range shifts in the coming decades (Albright et al. 2017). Increases in drought stress in the Southwest will heighten the vulnerability of aridland bird species to projected increases in aridity for the region (Ault et al. 2014). Aridland birds are experiencing some of the largest population declines of any group in North America (Sauer et al. 2017), and Rosenberg et al. (2016) estimated that 28% of aridland birds are in steep decline. Sagebrush habitat dependent species are among the rapidly declining aridland species in the Southwest with Sage Thrasher (Oreoscoptes montanus) and Brewer’s Sparrow (Spizella breweri), showing significant population declines (44% and 35%, respectively, from 1970 to 2014) and sensitivity to warming temperatures and increased aridity (Rosenberg et al. 2016). The combined effects of extreme temperatures and reduced precipitation directly affect species across the contiguous United States but are greatest in the Southwest (Albright et al. 2010b). The Mojave Desert bird community is thought to be experiencing a community collapse in response to increased water stress caused by long-term declines in precipitation (Iknayan and Beissinger 2018). Shifts in small-bodied bird population abundance are already occurring in arid landscapes (Albright et al. 2010a, 2010b) while extreme temperature events under projected climate change scenarios render portions of species’ ranges uninhabitable (Albright et al. 2017). Therefore, the required range shifts necessary for some species to persist may prove difficult or impossible because of limitations of extrinsic biotic and abiotic environmental factors (Hargrove and Rotenberry 2011), which will increase local extirpations and shift aridland bird community structure. While temperature and precipitation are important drivers of bird response to climate change, water deficit is a more integrative metric that incorporates a suite of site-specific variables (Stephenson 1998, Lutz et al. 2010). Water deficit is the atmospheric demand for water that is unmet by soil moisture supply. It accounts for the imbalance between water supplied by precipitation and the atmospheric demand of dry air. Deficit accounts for changes caused by both precipitation and temperature. This is one reason why deficit is a more integrative measure of water availability. Importantly, deficit is more locally relevant because it accounts for modification of temperature and precipitation effects due to site characteristics, such as elevation, slope, and aspect. Previously, drought was characterized as below-average precipitation, however, increasing temperature increases evaporative demand non-linearly (Lutz et al. 2010, supplemental 2, equations 9 and 10). Thus, with warming, above-average temperature simultaneously occurring with below-average precipitation can result in extreme water stress (Allen et al. 2015). As a single variable, water deficit simplifies understanding drought stress caused by below-average precipitation, above-average temperature, or any combination thereof. Temperature and precipitation provide direct mechanisms for explaining changes to breeding bird distribution and abundance, while water deficit can aid in the determination of indirect effects of how changes to vegetation condition can, in turn, affect changes in breeding bird communities. The process of seasonal wetting and drying that is modified by site characteristics is strongly correlated with vegetation conditions on the Colorado Plateau (Thoma et al. 2019). Thoma et al. (2019) found that vegetation responded strongly to water deficit, but the magnitude of effect varied by vegetation type due to site factors including soil water holding capacity, texture, and depth. Sagebrush habitats with deeper and finer soil textures had twice the water holding capacity (115 mm) as pinyon-juniper habitats (56 mm), which are often on rockier soils (Thoma et al. 2019). For a given climate, soils with lower water holding capacity will result in higher water deficits because they retain less water and dry more rapidly. Local climate conditions reflected in water deficit calculations make water deficit a more nuanced, and perhaps a more meaningful metric in the study of the indirect effects of drought stress and climate change on bird populations. Given the strong association with vegetation condition and water deficit in earlier studies of vegetation condition in these parks, here we evaluate relationships between bird density and water deficit that could be mediated through effects of water deficit on vegetation condition. Using 12 years of breeding bird monitoring data, we determined how habitat-specific bird communities were related to water deficit in 11 national parks and monuments in the Northern Colorado Plateau Inventory and Monitoring Network (NCPN). National parks are protected from most anthropogenic disturbances and provide important wildlife habitat in the face of increasing threats outside park boundaries (Rodhouse et al. 2016). However, despite their protected status, National Park Service lands remain vulnerable to human-induced climate change, making them ideal settings for research on the indirect effects of a changing climate using observational experiments and long-term monitoring data. Our study area has been in a drought condition for much of the past 20 years (Cook et al. 2010, Vicente-Serrano et al. 2013). Compared to the historic range of variability from 1901 to 2012, national parks of the desert Southwest were in the 95th percentile of mean annual temperature and 25–75th percentile of annual precipitation in the preceding 10- (2003–2012), 20- (1993–2012), and 30-year (1983–2012) periods (Monahan and Fisichelli 2014). Among national parks nationwide, those of the desert southwest are projected to have the highest rates of warming, greatest reduction in precipitation, and high rates of climate-induced biome shifts (Hansen et al. 2014). The magnitude and direction of the aridland bird community response to changes in vegetation caused by water deficit are currently unknown. Water deficit integrates temperature, precipitation, evapotranspiration, elevation, slope, aspect, and soil properties making it a valuable predictor for the potential indirect effects of these climate drivers on future aridland bird distributions and community structure. Because water deficit is an effective predictor of vegetation distribution (Stephenson 1998, Lutz et al. 2010), mortality (van Mantgem et al. 2009), seed production (Wion et al. 2019), and overall condition (Notaro et al. 2010, Robinson et al. 2013), and given the known relationships among breeding bird communities and vegetation structure (Cody 1981, James and Wamer 1982, Chandler et al. 2009, Culbert et al. 2013), vegetation composition (Fleishman et al. 2003, Seavy and Alexander 2011), and vegetation condition (Seavy and Alexander 2011, Glisson et al. 2015), we hypothesized that the bird communities dependent on vegetation for nest sites and food production to successfully produce young would respond to the spatial and temporal variation in water deficit. Our research focused on determining the breeding bird community response to variation in water deficit derived from an annual water balance model (hereafter “water deficit”; Lutz et al. 2010, Dilts et al. 2015, Thoma et al. 2019) in 3 habitats (riparian, pinyon-juniper, and sagebrush shrubland) with the goal of building predictive models to elucidate the adaptive capacity of these aridland species to climate shifts. METHODS Study Design and Habitat Descriptions We used 12 years (2005–2015 and 2017) of breeding bird survey data to estimate bird densities in 3 habitat types (riparian, pinyon-juniper, and sagebrush shrubland) in 11 national parks and monuments of the National Park Service’s Northern Colorado Plateau Inventory and Monitoring Network (Figure 1). We identified pinyon-juniper and sagebrush shrubland habitat types on land-cover maps from the Southwest Regional Gap Analysis Project (Lowry et al. 2005) or using vegetation-association maps (Daw et al. 2017). Riparian habitat occurs along perennial streams as narrow strips of habitat, surrounded by dry uplands, and contains multiple layers of canopy, which may experience different degrees of dryness depending on groundwater levels and rooting depths. The riparian habitat is dominated by willow (Salix spp.), Tamarisk (Tamarix ramosissima), and isolated stands of Fremont cottonwood (Populus fremontii) and boxelder (Acer negundo). Pinyon-juniper habitat is dominated by two-needle pinyon (Pinus edulis) and junipers (Juniperus spp.), which varied in relative abundance. The shrub layer in pinyon-juniper habitat varies throughout the NCPN, but is often dominated by sagebrush (Artemisia spp.), mountain mahogany (Cercocarpus spp.), jointfir (Ephedra spp.), and cliffrose (Purshia spp.). Sagebrush shrubland habitat is dominated by sagebrush, primarily big sagebrush (Artemisia tridentata) and prairie sagewort (A. frigida), with rabbitbrush (Chrysothamnus spp.), greasewood (Sarcobatus spp.), and other shrub species interspersed. Riparian transects ranged in elevation from 1,283 m to 1,901 m, pinyon-juniper transects ranged in elevation from 1,393 m to 2,402 m, and sagebrush shrubland transects ranged in elevation from 1,666 m to 2,447 m. Transects within each habitat type were established across a large latitudinal gradient to allow for habitat comparisons and to guard against variation that occurs across broad geographic gradients (Figure 1). Figure 1. Open in new tabDownload slide Map of the 11 national parks and monuments where point-count surveys were conducted from 2005 to 2015 and 2017. Figure 1. Open in new tabDownload slide Map of the 11 national parks and monuments where point-count surveys were conducted from 2005 to 2015 and 2017. Water Deficit Estimates Water deficit is a measure of drought stress and is the amount of additional water vegetation would use if it was available (Stephenson 1998). The use of water-year, defined as October 1–September 30 of the following year, in the estimation of water deficit is routine in studies of vegetative responses to climate in the desert southwest, as it helps account for precipitation legacies that influence plants during the growing season (Reichmann et al. 2013, Bunting et al. 2017, Thoma et al. 2019). We used a monthly water balance model to estimate water-year water deficit using temperature and precipitation at the center of 45 bird survey transects (see below) following the methods of Lutz et al. (2010). Precipitation was partitioned into soil moisture, the quantity of water stored in the top meter of soil at the end of each month, and runoff which included overland flow plus infiltration below the rooting zone. Runoff is the proportion of water that is not available for plant growth. Maximum storage in the top meter of soil was defined by water holding capacity obtained from soil surveys (Soil Survey Staff 2019). Potential evapotranspiration (PET, mm) was the amount of water that could be evaporated or transpired with available energy if soil moisture was unlimited. Actual evapotranspiration (AET, mm) was the estimated monthly loss of water from soil via evaporation and transpiration, limited by the availability of soil moisture. Water deficit (mm) was calculated as the difference between PET and AET (Stephenson 1998). We used Daymet daily temperature and precipitation data at a 1-km grain as the climatic input to the model (Thornton et al. 2016). These data were co-located with bird point-count transects and thus represent the local elevation and latitude effects on precipitation and temperature at 1-km resolution. Within each 1-km grid cell of a temperature and precipitation time series, the water balance model calculated heat load due to slope and aspect obtained from 30-m digital elevation model at the center of each transect (U.S. Geological Survey, 2017). Heat load was calculated as a scaling factor used to adjust PET up on south aspects or down on north aspects, thus accounting for slope and aspect interactions (Lutz et al. 2010 after McCune and Keon 2002). Breeding Bird Community We sampled the breeding bird community at 675 unique sampling locations on 45 transects during the breeding season (May 1 through July 15), the timing of which varied by transect location. The elevation and latitudinal position of each transect was considered during the scheduling of each field season such that all transects were surveyed within their peak breeding season and after the passage of migratory birds. Transect orientation in pinyon-juniper and sagebrush shrubland habitats were randomly determined following protocol procedures outlined in Daw et al. (2017), the riparian transects surveyed in this study consisted of narrow strips of habitat, requiring transect placement to be centered along the length of the habitat and to follow the natural orientation of the riparian zone. All riparian habitat was narrow enough that the entire width of the riparian zone was included in the point radius of each survey (see below) and that dry upland habitat was also included in surveys of riparian habitat at some locations. Each transect consisted of 15 point-count locations, with points spaced 250 m apart. Observers visited 1 transect per day, initiated sampling within 30 min before sunrise, and completed the survey within 5 hr after sunrise. Observers walked the transect, navigated to each point using a GPS unit, and completed a 5-min point-count survey. We did not conduct surveys if winds exceeded a four on the Beaufort Scale (13–18 mph) or precipitation was more than a drizzle. During each point count, observers recoded the species and distance (m) to all individuals detected. Observers estimated the distance to each bird or cluster of birds using a laser rangefinder (Simmons LRF 600; Simmons Outdoor Products, Overland Park, KS, USA). From 2005 to 2013, field teams surveyed each transect twice annually. Starting in 2014, survey effort was reduced to one visit per year because a sufficient number of detections to estimate density had been obtained for most bird species detected and to reduce costs. The number of completed surveys varied by year, but >75% of possible surveys were completed annually. For more detailed information about survey protocols, refer to Daw et al. (2017). We first estimated transect-level detection-adjusted densities for each bird species using the Distance package (Miller et al. 2019) in program R (3.6.1, http://www.r-project.org). To avoid including double-counted individuals in our analyses, we only included detections within 125 m from the point center in our analyses. The total area covered by each transect was 73.6 ha (i.e. 15, 125-m radius points per transect). Next, we used the detection-adjusted density estimates in a multivariate analysis to determine the bird community response to changes in water deficit using the manyglm function in the R package mvabund (Wang et al. 2012). The mvabund package provides a novel set of hypothesis testing tools that is a flexible and powerful framework for analyzing multivariate abundance data (Wang et al. 2012). We used the manyglm function to simultaneously fit general linear models to each species using water deficit as the common predictor variable (Wang et al. 2012). This model-based approach alleviates the mean–variance relationship problem associated with distance-based community-level metrics (Warton et al. 2012). To meet the data structure requirements of mvabund, we sought to maximize the number of transect-level density estimates available using Distance by constraining our analyses to only include the 10 species within each habitat type with the greatest number of transect-level density estimates available (Table 1). Species with the greatest number of detections allow for the greatest number of transect-level density estimate; therefore, the species included in each habitat are not the species with the highest densities, rather the species with the greatest number of detections. For species-transect-year combinations where detections were too few to estimate density, we summed the unadjusted counts and divided by the average detection probability for that species-year. This was done for 6% of the density estimates to satisfy the need for a response variable for all species-transect-year combinations. Table 1. Aridland breeding bird community composition and mean density (±SE) for each species, estimating from 2005 to 2015 and 2017 in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Common name . Scientific name . Mean density (birds km–2) . Riparian Mourning Dove a Zenaida macroura 14.0 ± 2.1 White-throated Swift Aeronautes saxatalis 15.6 ± 2.7 Ash-throated Flycatcher b Myiarchus cinerascens 23.9 ± 1.6 Violet-green Swallow Tachycineta thalassina 50.8 ± 5.1 Blue-gray Gnatcatcher b Polioptila caerulea 120.5 ± 8.8 Rock Wren b Salpinctes obsoletus 7.9 ± 0.8 House Finch b Haemorhous mexicanus 29.5 ± 2.9 Spotted Towhee a Pipilo maculatus 88.4 ± 5.5 Yellow Warbler Setophaga petechial 92.2 ± 11.8 Lazuli Bunting Passerina amoena 53.9 ± 8.6 Pinyon-juniper Mourning Dove a 21.8 ± 4.5 Gray Flycatcher Empidonax wrightii 34.0 ± 3.1 Ash-throated Flycatcher b 15.8 ± 1.9 Gray Vireo Vireo vicinior 16.4 ± 2.8 Juniper Titmouse Baeolophus ridgwayi 40.2 ± 4.7 Blue-gray Gnatcatcher b 131.4 ± 8.9 Bewick’s Wren Thryomanes bewickii 15.0 ± 2.0 House Finch b 22.3 ± 2.2 Spotted Towhee a 24.3 ± 3.2 Black-throated Gray Warbler Setophaga nigrescens 82.5 ± 6.8 Sagebrush shrubland Mourning Dove a 6.8 ± 1.8 Dusky Flycatcher Empidonax oberholseri 10.0 ± 1.8 Rock Wren b 5.5 ± 0.7 Sage Thrasher Oreoscoptes montanus 4.7 ± 0.8 Spotted Towhee a 9.8 ± 1.3 Green-tailed Towhee Pipilo chlorurus 47.8 ± 5.5 Brewer’s Sparrow Spizella breweri 90.2 ± 6.8 Vesper Sparrow Pooecetes gramineus 45.7 ± 3.9 Lark Sparrow Chondestes grammacus 12.4 ± 2.2 Western Meadowlark Sturnella neglecta 7.5 ± 1.0 Habitat . Common name . Scientific name . Mean density (birds km–2) . Riparian Mourning Dove a Zenaida macroura 14.0 ± 2.1 White-throated Swift Aeronautes saxatalis 15.6 ± 2.7 Ash-throated Flycatcher b Myiarchus cinerascens 23.9 ± 1.6 Violet-green Swallow Tachycineta thalassina 50.8 ± 5.1 Blue-gray Gnatcatcher b Polioptila caerulea 120.5 ± 8.8 Rock Wren b Salpinctes obsoletus 7.9 ± 0.8 House Finch b Haemorhous mexicanus 29.5 ± 2.9 Spotted Towhee a Pipilo maculatus 88.4 ± 5.5 Yellow Warbler Setophaga petechial 92.2 ± 11.8 Lazuli Bunting Passerina amoena 53.9 ± 8.6 Pinyon-juniper Mourning Dove a 21.8 ± 4.5 Gray Flycatcher Empidonax wrightii 34.0 ± 3.1 Ash-throated Flycatcher b 15.8 ± 1.9 Gray Vireo Vireo vicinior 16.4 ± 2.8 Juniper Titmouse Baeolophus ridgwayi 40.2 ± 4.7 Blue-gray Gnatcatcher b 131.4 ± 8.9 Bewick’s Wren Thryomanes bewickii 15.0 ± 2.0 House Finch b 22.3 ± 2.2 Spotted Towhee a 24.3 ± 3.2 Black-throated Gray Warbler Setophaga nigrescens 82.5 ± 6.8 Sagebrush shrubland Mourning Dove a 6.8 ± 1.8 Dusky Flycatcher Empidonax oberholseri 10.0 ± 1.8 Rock Wren b 5.5 ± 0.7 Sage Thrasher Oreoscoptes montanus 4.7 ± 0.8 Spotted Towhee a 9.8 ± 1.3 Green-tailed Towhee Pipilo chlorurus 47.8 ± 5.5 Brewer’s Sparrow Spizella breweri 90.2 ± 6.8 Vesper Sparrow Pooecetes gramineus 45.7 ± 3.9 Lark Sparrow Chondestes grammacus 12.4 ± 2.2 Western Meadowlark Sturnella neglecta 7.5 ± 1.0 a Species analyzed in 3 habitats. b Species analyzed in 2 habitats. Open in new tab Table 1. Aridland breeding bird community composition and mean density (±SE) for each species, estimating from 2005 to 2015 and 2017 in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Common name . Scientific name . Mean density (birds km–2) . Riparian Mourning Dove a Zenaida macroura 14.0 ± 2.1 White-throated Swift Aeronautes saxatalis 15.6 ± 2.7 Ash-throated Flycatcher b Myiarchus cinerascens 23.9 ± 1.6 Violet-green Swallow Tachycineta thalassina 50.8 ± 5.1 Blue-gray Gnatcatcher b Polioptila caerulea 120.5 ± 8.8 Rock Wren b Salpinctes obsoletus 7.9 ± 0.8 House Finch b Haemorhous mexicanus 29.5 ± 2.9 Spotted Towhee a Pipilo maculatus 88.4 ± 5.5 Yellow Warbler Setophaga petechial 92.2 ± 11.8 Lazuli Bunting Passerina amoena 53.9 ± 8.6 Pinyon-juniper Mourning Dove a 21.8 ± 4.5 Gray Flycatcher Empidonax wrightii 34.0 ± 3.1 Ash-throated Flycatcher b 15.8 ± 1.9 Gray Vireo Vireo vicinior 16.4 ± 2.8 Juniper Titmouse Baeolophus ridgwayi 40.2 ± 4.7 Blue-gray Gnatcatcher b 131.4 ± 8.9 Bewick’s Wren Thryomanes bewickii 15.0 ± 2.0 House Finch b 22.3 ± 2.2 Spotted Towhee a 24.3 ± 3.2 Black-throated Gray Warbler Setophaga nigrescens 82.5 ± 6.8 Sagebrush shrubland Mourning Dove a 6.8 ± 1.8 Dusky Flycatcher Empidonax oberholseri 10.0 ± 1.8 Rock Wren b 5.5 ± 0.7 Sage Thrasher Oreoscoptes montanus 4.7 ± 0.8 Spotted Towhee a 9.8 ± 1.3 Green-tailed Towhee Pipilo chlorurus 47.8 ± 5.5 Brewer’s Sparrow Spizella breweri 90.2 ± 6.8 Vesper Sparrow Pooecetes gramineus 45.7 ± 3.9 Lark Sparrow Chondestes grammacus 12.4 ± 2.2 Western Meadowlark Sturnella neglecta 7.5 ± 1.0 Habitat . Common name . Scientific name . Mean density (birds km–2) . Riparian Mourning Dove a Zenaida macroura 14.0 ± 2.1 White-throated Swift Aeronautes saxatalis 15.6 ± 2.7 Ash-throated Flycatcher b Myiarchus cinerascens 23.9 ± 1.6 Violet-green Swallow Tachycineta thalassina 50.8 ± 5.1 Blue-gray Gnatcatcher b Polioptila caerulea 120.5 ± 8.8 Rock Wren b Salpinctes obsoletus 7.9 ± 0.8 House Finch b Haemorhous mexicanus 29.5 ± 2.9 Spotted Towhee a Pipilo maculatus 88.4 ± 5.5 Yellow Warbler Setophaga petechial 92.2 ± 11.8 Lazuli Bunting Passerina amoena 53.9 ± 8.6 Pinyon-juniper Mourning Dove a 21.8 ± 4.5 Gray Flycatcher Empidonax wrightii 34.0 ± 3.1 Ash-throated Flycatcher b 15.8 ± 1.9 Gray Vireo Vireo vicinior 16.4 ± 2.8 Juniper Titmouse Baeolophus ridgwayi 40.2 ± 4.7 Blue-gray Gnatcatcher b 131.4 ± 8.9 Bewick’s Wren Thryomanes bewickii 15.0 ± 2.0 House Finch b 22.3 ± 2.2 Spotted Towhee a 24.3 ± 3.2 Black-throated Gray Warbler Setophaga nigrescens 82.5 ± 6.8 Sagebrush shrubland Mourning Dove a 6.8 ± 1.8 Dusky Flycatcher Empidonax oberholseri 10.0 ± 1.8 Rock Wren b 5.5 ± 0.7 Sage Thrasher Oreoscoptes montanus 4.7 ± 0.8 Spotted Towhee a 9.8 ± 1.3 Green-tailed Towhee Pipilo chlorurus 47.8 ± 5.5 Brewer’s Sparrow Spizella breweri 90.2 ± 6.8 Vesper Sparrow Pooecetes gramineus 45.7 ± 3.9 Lark Sparrow Chondestes grammacus 12.4 ± 2.2 Western Meadowlark Sturnella neglecta 7.5 ± 1.0 a Species analyzed in 3 habitats. b Species analyzed in 2 habitats. Open in new tab Because there is likely a time lag in the bird community response to water deficit-driven changes in vegetation, we compared 2 time-lag models (a 1-year lag and a 2-year lag effect of annual water deficit) against a null model within each habitat and selected the model with the lowest Akaike information criterion (AICc, Burnham and Anderson 2002). We did not explore other lags because vegetation response to legacy effects of precipitation shortfalls revert to average condition within 2 years in semiarid grasslands (Thoma et al. 2016). Once we determined the most appropriate time lag within each habitat type, we then tested for community-wide responses to annual water deficit within each habitat using analysis of variance (ANOVA) on the manyglm object and assessed the resulting likelihood ratio tests (LRT; Warton 2011) and resampled P-values (Wang et al. 2012). If we detected a significant community-level response to water deficit within a habitat type, we then used p.uni = “adjusted” argument to determine the effect size and direction of the response for each species. Finally, we predicted the relationships between species’ densities and annual water deficit using the “predict” function on the best model within each habitat type. RESULTS From 2005 to 2015 and 2017, we conducted 12,974 point counts at 675 unique sampling locations on 45 transects during the breeding season in 11 NCPN parks and monuments, with annual averages of 349 points in riparian habitat, 356 points in pinyon-juniper habitat, and 376 points in sagebrush shrubland habitat. Annual water deficit was lowest in sagebrush and greatest in riparian habitats (Table 2). Table 2. Annual mean (±95% CI) and range of variation of climate and water deficit conditions among and within transects from 2004 to 2016 for riparian and pinyon-juniper habitats (used for analysis with a 1-year lag) and from 2003 to 2015 for sagebrush shrubland habitat (used for analysis with a 2-year lag) in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Precipitation . Temperature . Water deficit . Minimum and maximum annual water deficit across transects . Minimum range in annual water deficit within a transect . Maximum range in annual water deficit within a transect . . (mm) . (°C) . (mm) . (mm) . (mm) . (mm) . Riparian 275.4 ± 15.1 12.0 ± 0.3 536.4 ± 17.8 215.2–810.1 172.2 319.5 Pinyon-juniper 328.7 ± 15.8 10.0 ± 0.3 360.9 ± 19.8 76.9–717.2 124.6 455.8 Sagebrush shrubland 333.6 ± 15.5 6.4 ± 0.2 204.3 ± 15.1 33.6–559.8 59.3 293.8 Habitat . Precipitation . Temperature . Water deficit . Minimum and maximum annual water deficit across transects . Minimum range in annual water deficit within a transect . Maximum range in annual water deficit within a transect . . (mm) . (°C) . (mm) . (mm) . (mm) . (mm) . Riparian 275.4 ± 15.1 12.0 ± 0.3 536.4 ± 17.8 215.2–810.1 172.2 319.5 Pinyon-juniper 328.7 ± 15.8 10.0 ± 0.3 360.9 ± 19.8 76.9–717.2 124.6 455.8 Sagebrush shrubland 333.6 ± 15.5 6.4 ± 0.2 204.3 ± 15.1 33.6–559.8 59.3 293.8 Open in new tab Table 2. Annual mean (±95% CI) and range of variation of climate and water deficit conditions among and within transects from 2004 to 2016 for riparian and pinyon-juniper habitats (used for analysis with a 1-year lag) and from 2003 to 2015 for sagebrush shrubland habitat (used for analysis with a 2-year lag) in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Precipitation . Temperature . Water deficit . Minimum and maximum annual water deficit across transects . Minimum range in annual water deficit within a transect . Maximum range in annual water deficit within a transect . . (mm) . (°C) . (mm) . (mm) . (mm) . (mm) . Riparian 275.4 ± 15.1 12.0 ± 0.3 536.4 ± 17.8 215.2–810.1 172.2 319.5 Pinyon-juniper 328.7 ± 15.8 10.0 ± 0.3 360.9 ± 19.8 76.9–717.2 124.6 455.8 Sagebrush shrubland 333.6 ± 15.5 6.4 ± 0.2 204.3 ± 15.1 33.6–559.8 59.3 293.8 Habitat . Precipitation . Temperature . Water deficit . Minimum and maximum annual water deficit across transects . Minimum range in annual water deficit within a transect . Maximum range in annual water deficit within a transect . . (mm) . (°C) . (mm) . (mm) . (mm) . (mm) . Riparian 275.4 ± 15.1 12.0 ± 0.3 536.4 ± 17.8 215.2–810.1 172.2 319.5 Pinyon-juniper 328.7 ± 15.8 10.0 ± 0.3 360.9 ± 19.8 76.9–717.2 124.6 455.8 Sagebrush shrubland 333.6 ± 15.5 6.4 ± 0.2 204.3 ± 15.1 33.6–559.8 59.3 293.8 Open in new tab Models with a 1-year time-lag effect of annual water deficit on bird density performed best in riparian (ΔAIC = 15.5) and pinyon-juniper (ΔAIC = 18.7) habitats, while the 2-year lag effect was the best model in sagebrush shrubland (ΔAIC = 33.4) habitat. Annual water deficit had a significant effect on bird density at the community level within each habitat (riparian: LRT = 126, P < 0.001; pinyon-juniper: LRT = 140, P < 0.001; sagebrush shrubland: LRT = 226, P < 0.001). Individual species varied in both the direction and magnitude of their relationship to annual water deficit within each habitat type (Figure 2). Of the 30 species–habitat combinations included in this analysis, we found 27% (n = 8) were negatively related, 43% (n = 13) were positively related, and 30% (n = 9) were not related to annual water deficit (Figure 2). Figure 2. Open in new tabDownload slide Species beta coefficients (±95% CI) from the multivariate analysis of the effect of annual water deficit on bird density within each of the surveyed habitats in 11 national parks and monuments in the Northern Colorado Plateau Network from 2005 to 2015 and 2017. Figure 2. Open in new tabDownload slide Species beta coefficients (±95% CI) from the multivariate analysis of the effect of annual water deficit on bird density within each of the surveyed habitats in 11 national parks and monuments in the Northern Colorado Plateau Network from 2005 to 2015 and 2017. In riparian habitat, 4 species (Mourning Dove [Zenaida macroura], Ash-throated Flycatcher [Myiarchus cinerascens], House Finch [Haemorhous mexicanus], and Violet-green Swallow [Tachycineta thalassina]) were positively and 3 species (Spotted Towhee [Pipilo maculatus], Lazuli Bunting [Passerina amoena], and Yellow Warbler [Setophaga petechial]) were negatively related to water deficit (Table 3, Figure 2). In pinyon-juniper habitat, 5 species (Gray Vireo [Vireo vicinior], House Finch, Bewick’s Wren [Thryomanes bewickii], Juniper Titmouse [Baeolophus ridgwayi], and Ash-throated Flycatcher) were positively and 2 species (Gray Flycatcher [Empidonax wrightii] and Spotted Towhee) were negatively related to water deficit (Table 3, Figure 2). In sagebrush shrubland, 4 species (Lark Sparrow [Chondestes grammacus], Mourning Dove, Spotted Towhee, and Western Meadowlark [Sturnella neglecta]) were positively and 3 species (Sage Thrasher, Green-tailed Towhee [Pipilo chlorurus], and Dusky Flycatcher [Empidonax oberholseri]) were negatively related to water deficit (Table 3, Figure 2). Table 3. Beta (β) coefficients (± 95% CI) and likelihood ratio test (LRT) scores from a multivariate analysis for species with a significant (P ≤ 0.05) response to water deficit within each habitat type from 2005 to 2015 and 2017 in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Species . β ± 95% CI . LRT . Riparian Mourning Dove 2.52e-03 ± 1.27e-03 14.60 Ash-throated Flycatcher 1.86e-03 ± 7.40e-04 24.97 House Finch 1.39e-03 ± 7.38e-04 13.91 Violet-green Swallow 1.21e-03 ± 6.80e-04 12.46 Spotted Towhee –1.10e-03 ± 5.77e-04 13.85 Lazuli Bunting –2.07e-03 ± 1.28e-03 10.80 Yellow Warbler –2.88e-03 ± 9.31e-04 32.24 Pinyon-juniper Gray Vireo 2.61e-03 ± 7.79e-04 39.08 House Finch 2.01e-03 ± 6.77e-04 33.95 Bewick’s Wren 1.88e-03 ± 1.02e-03 11.37 Juniper Titmouse 1.33e-03 ± 6.27e-04 17.34 Ash-throated Flycatcher 1.17e-03 ± 7.16e-04 10.17 Gray Flycatcher –1.18e-03 ± 6.35e-04 13.48 Spotted Towhee –2.22e-03 ± 1.35e-03 11.95 Sagebrush shrubland Lark Sparrow 1.03e-02 ± 1.74e-03 81.97 Mourning Dove 3.63e-03 ± 1.56e-03 18.01 Spotted Towhee 2.61e-03 ± 1.75e-03 8.19 Western Meadowlark 2.36e-03 ± 1.55e-03 8.54 Sage Thrasher –4.20e-03 ± 2.89e-03 6.82 Green-tailed Towhee –5.51e-03 ± 1.31e-03 74.03 Dusky Flycatcher –8.40e-03 ± 3.52e-03 19.29 Habitat . Species . β ± 95% CI . LRT . Riparian Mourning Dove 2.52e-03 ± 1.27e-03 14.60 Ash-throated Flycatcher 1.86e-03 ± 7.40e-04 24.97 House Finch 1.39e-03 ± 7.38e-04 13.91 Violet-green Swallow 1.21e-03 ± 6.80e-04 12.46 Spotted Towhee –1.10e-03 ± 5.77e-04 13.85 Lazuli Bunting –2.07e-03 ± 1.28e-03 10.80 Yellow Warbler –2.88e-03 ± 9.31e-04 32.24 Pinyon-juniper Gray Vireo 2.61e-03 ± 7.79e-04 39.08 House Finch 2.01e-03 ± 6.77e-04 33.95 Bewick’s Wren 1.88e-03 ± 1.02e-03 11.37 Juniper Titmouse 1.33e-03 ± 6.27e-04 17.34 Ash-throated Flycatcher 1.17e-03 ± 7.16e-04 10.17 Gray Flycatcher –1.18e-03 ± 6.35e-04 13.48 Spotted Towhee –2.22e-03 ± 1.35e-03 11.95 Sagebrush shrubland Lark Sparrow 1.03e-02 ± 1.74e-03 81.97 Mourning Dove 3.63e-03 ± 1.56e-03 18.01 Spotted Towhee 2.61e-03 ± 1.75e-03 8.19 Western Meadowlark 2.36e-03 ± 1.55e-03 8.54 Sage Thrasher –4.20e-03 ± 2.89e-03 6.82 Green-tailed Towhee –5.51e-03 ± 1.31e-03 74.03 Dusky Flycatcher –8.40e-03 ± 3.52e-03 19.29 Open in new tab Table 3. Beta (β) coefficients (± 95% CI) and likelihood ratio test (LRT) scores from a multivariate analysis for species with a significant (P ≤ 0.05) response to water deficit within each habitat type from 2005 to 2015 and 2017 in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Species . β ± 95% CI . LRT . Riparian Mourning Dove 2.52e-03 ± 1.27e-03 14.60 Ash-throated Flycatcher 1.86e-03 ± 7.40e-04 24.97 House Finch 1.39e-03 ± 7.38e-04 13.91 Violet-green Swallow 1.21e-03 ± 6.80e-04 12.46 Spotted Towhee –1.10e-03 ± 5.77e-04 13.85 Lazuli Bunting –2.07e-03 ± 1.28e-03 10.80 Yellow Warbler –2.88e-03 ± 9.31e-04 32.24 Pinyon-juniper Gray Vireo 2.61e-03 ± 7.79e-04 39.08 House Finch 2.01e-03 ± 6.77e-04 33.95 Bewick’s Wren 1.88e-03 ± 1.02e-03 11.37 Juniper Titmouse 1.33e-03 ± 6.27e-04 17.34 Ash-throated Flycatcher 1.17e-03 ± 7.16e-04 10.17 Gray Flycatcher –1.18e-03 ± 6.35e-04 13.48 Spotted Towhee –2.22e-03 ± 1.35e-03 11.95 Sagebrush shrubland Lark Sparrow 1.03e-02 ± 1.74e-03 81.97 Mourning Dove 3.63e-03 ± 1.56e-03 18.01 Spotted Towhee 2.61e-03 ± 1.75e-03 8.19 Western Meadowlark 2.36e-03 ± 1.55e-03 8.54 Sage Thrasher –4.20e-03 ± 2.89e-03 6.82 Green-tailed Towhee –5.51e-03 ± 1.31e-03 74.03 Dusky Flycatcher –8.40e-03 ± 3.52e-03 19.29 Habitat . Species . β ± 95% CI . LRT . Riparian Mourning Dove 2.52e-03 ± 1.27e-03 14.60 Ash-throated Flycatcher 1.86e-03 ± 7.40e-04 24.97 House Finch 1.39e-03 ± 7.38e-04 13.91 Violet-green Swallow 1.21e-03 ± 6.80e-04 12.46 Spotted Towhee –1.10e-03 ± 5.77e-04 13.85 Lazuli Bunting –2.07e-03 ± 1.28e-03 10.80 Yellow Warbler –2.88e-03 ± 9.31e-04 32.24 Pinyon-juniper Gray Vireo 2.61e-03 ± 7.79e-04 39.08 House Finch 2.01e-03 ± 6.77e-04 33.95 Bewick’s Wren 1.88e-03 ± 1.02e-03 11.37 Juniper Titmouse 1.33e-03 ± 6.27e-04 17.34 Ash-throated Flycatcher 1.17e-03 ± 7.16e-04 10.17 Gray Flycatcher –1.18e-03 ± 6.35e-04 13.48 Spotted Towhee –2.22e-03 ± 1.35e-03 11.95 Sagebrush shrubland Lark Sparrow 1.03e-02 ± 1.74e-03 81.97 Mourning Dove 3.63e-03 ± 1.56e-03 18.01 Spotted Towhee 2.61e-03 ± 1.75e-03 8.19 Western Meadowlark 2.36e-03 ± 1.55e-03 8.54 Sage Thrasher –4.20e-03 ± 2.89e-03 6.82 Green-tailed Towhee –5.51e-03 ± 1.31e-03 74.03 Dusky Flycatcher –8.40e-03 ± 3.52e-03 19.29 Open in new tab The relationship between density and water deficit also varied in direction and magnitude of response for the same species in different habitats. Spotted Towhee occurred in all 3 habitats and was negatively associated with water deficit in riparian and pinyon-juniper and positively associated with water deficit in sagebrush shrubland (Figure 2). Mourning Dove also occurred in all 3 habitats and was positively associated with water deficit in riparian and sagebrush shrubland, but had no association with water deficit in pinyon-juniper (Figure 2). House Finch, Ash-throated Flycatcher, and Blue-gray Gnatcatcher (Polioptila caerulea) occurred in both riparian and pinyon-juniper habitats. House Finch and Ash-throated Flycatcher showed positive associations with increases in water deficit, while Blue-gray Gnatcatcher showed no association with water deficit in either habitat (Figure 2). Rock Wren (Salpinctes obsoletus) occurred in riparian and sagebrush shrubland habitat and had no association with water deficit in either habitat (Figure 2). Model-predicted relationships between bird density and annual water deficit varied by species and habitat type (Figure 3). For example, Dusky Flycatcher and Green-tailed Towhee densities in sagebrush shrubland habitat had strong negative associations with annual water deficit, showing a high sensitivity between 250 and 400 mm of annual water deficit (Figure 3). Conversely, Lark Sparrow density in sagebrush shrubland habitat was positively related to annual water deficit (Figure 3). Spotted Towhee density was negatively associated with annual water deficit in riparian (P < 0.001) and pinyon-juniper (P < 0.001) habitats and positively associated with water deficit in sagebrush shrubland habitat (P = 0.006; Figure 3). Figure 3. Open in new tabDownload slide Predicted species density responses (±95% CI) to water deficit in the 3 surveyed habitats 11 national parks and monuments in the Northern Colorado Plateau Network. Vertical dashed lines indicate the mean water deficit value across years (2004–2016 in riparian and pinyon-juniper; 2003–2015 in sagebrush shrubland) and transects within each habitat. Plots with black points and dashed lines indicate species–habitat combinations that had significant responses to annual water deficit values. Figure 3. Open in new tabDownload slide Predicted species density responses (±95% CI) to water deficit in the 3 surveyed habitats 11 national parks and monuments in the Northern Colorado Plateau Network. Vertical dashed lines indicate the mean water deficit value across years (2004–2016 in riparian and pinyon-juniper; 2003–2015 in sagebrush shrubland) and transects within each habitat. Plots with black points and dashed lines indicate species–habitat combinations that had significant responses to annual water deficit values. Discussion The 3 aridland breeding bird communities in this study showed strong associations with variation in annual water deficit, with 70% of the species showing significant though varying responses. Local water deficit differences result from site-level interactions among climate, topography, soil properties, and vegetation traits that respond differently to a given level of drought stress (Thoma et al. 2019). The spatial scale of our analyses captures variation in abiotic factors such as elevation, slope, aspect, and soil properties that influence the vegetation and, therefore, the relevant decisions associated with breeding bird habitat selection. Our habitat-based approach revealed that within each habitat type there were positive, negative, and neutral responses of bird species’ densities to water deficit and, for a few species, we detected different responses among habitats. While previous studies in the desert Southwest have found effects of precipitation, temperature, or both on bird populations across habitat types (Albright et al. 2010a, 2010b, Cruz-McDonnell and Wolf 2016, Iknayan and Beissinger 2018), to our knowledge ours is the first to use water deficit estimates within habitat types, highlighting the importance of locally mediated modifications of regional climate on bird populations at a fine geographic scale. A more regional approach (Albright et al. 2010a, 2010b, 2017, Iknayan and Beissinger 2018, Riddell et al. 2019), is informative for broad patterns in species responses to climate but the potential to detect varied species responses within different habitats is only possible with a habitat-based approach. Our results suggest that optimal habitat requirements can be met at varying annual water deficit values, and that the effect is habitat-dependent. Particular species responses may be explained by a host of indirect effects, but it is reasonable to hypothesize that the negative response of birds, such as Yellow Warblers in riparian habitat, is in part due to the close association of this species to vegetation with high water requirements that are affected by annual water deficit (Lowther et al. 2020). The mixed responses of species in the same habitat indicate that increased drought stress is not inherently negative or positive for all species, suggesting that bird species’ responses to increased water stress are likely driven by a complex suite of underlying factors. Puig-Gironès et al. (2017) also found mixed responses of species to water deficit, with both negative and neutral responses to water deficit for warbler species in northeastern Spain. The strength of response in bird density as a measure of sensitivity to changes in water deficit can be used to identify species potentially vulnerable to climate change in the Southwest. For example, under likely scenarios of increased temperatures and decreased precipitation, which will increase in water deficit, the relative adaptive capacity for Yellow Warbler in riparian habitats, where their response to water deficit was negative, is low and, therefore, their vulnerability would be high (Hunter et al. 1987, Lowther et al. 2020). We also identified species that seemed especially sensitive to water deficit, including Lazuli Bunting, in riparian habitat, Spotted Towhee in pinyon-juniper habitat, and Dusky Flycatcher and Green-tailed Towhee in sagebrush shrubland habitat. Seasonal variation in foliage height density influenced the risk of nest predation for Dusky Flycatcher in Northern California (Borgmann et al. 2013), indicating the indirect and negative effect of drought on fecundity for this species. Alternatively, species, such as Lark Sparrow in sagebrush shrubland habitat, Ash-throated Flycatcher in riparian habitat, House Finch in pinyon-juniper, and Gray Vireo in pinyon-juniper indicated positive responses to annual water deficit, and are therefore less vulnerable to projected increases in annual water deficit. Wysner et al. (2019) did not observe changes in Ash-throated Flycatcher breeding ecology related to spring temperatures in New Mexico, and Schlossberg (2006) found that elevation, not vegetation characteristics, was the best determinant of Gray Vireo abundance in the Colorado Plateau. Species responses in riparian habitat could be influenced by water sources outside of the study site, but the significant responses indicate that these species responded strongly to locally estimated deficit regardless of in-stream conditions that may be affected by groundwater inputs or accumulation of water from upslope. This suggests that nearby upland conditions that experience drought may affect species in riparian habitats. Species capable of breeding in multiple habitat types may have greater adaptive capacity to variation in water deficit. Spotted Towhee, a known shrubland habitat generalist (James 1971, Berry and Bock 1998), occurred in all 3 habitats and their response to annual water deficit was habitat dependent. Spotted Towhee breeding densities in riparian and pinyon-juniper habitats showed a negative response to water deficit, while those breeding in sagebrush shrubland habitat showed a positive response. In sagebrush shrublands, above-average precipitation can cause die-off in vegetation, specifically big sagebrush (Artemisia tridentata; Renne et al. 2019). As that habitat dries, conditions can improve for the vegetative community in sagebrush shubland, while the water deficit increases, which could explain a positive relationship between water deficit and bird density. While the biological drivers of these varying responses are unclear, Spotted Towhees are an example of a species that could shift from breeding in riparian and pinyon-juniper habitats to sagebrush shrubland habitat as annual water deficit increases. Drought stress is an important factor influencing bird populations and community structure (Tischler et al. 2013, McCreedy and van Riper 2015, Seymour et al. 2015, Theimer et al. 2018), and our results indicate that the response of bird densities to annual water deficit was likely due to a legacy of indirect effects such as primary production, plant fecundity (i.e. seed production; Bunting et al. 2017), or invertebrate food resource availability. Our analysis suggests there may be a water deficit value beyond which a species density declines, but increased temperature or decreased precipitation may also have more immediate and direct effects (Riddell et al. 2019, 2021). Additionally, compounding effects of prior year water deficit effects mediated through vegetation condition may interact with current year temperature and precipitation to cause precipitous declines greater than expected via either mechanism (direct or indirect). Understanding species’ exposure and sensitivity to climate change in specific habitat types over longer time frames, as in this study, can provide necessary information to manage lands based on the magnitude and timing of species vulnerability. In the vulnerability assessment phase of climate adaptation planning, quantitative and place-based knowledge of a species sensitivity to climate is critically important in determining when changes in specific habitats will affect specific species (Siegel et al. 2014). Site-level information can aid in crafting management strategies that reduce species vulnerability by identifying appropriately timed and habitat-specific management actions based on individual species’ needs. Plant communities and bird species vary in their ability to tolerate drought stress, leading to the differing responses we observed within and between habitat types (Noy-Meir 1973, Puig-Gironès et al. 2017). Our models provide quantitative information on the relative sensitivity of expected change in the density of a species with changing climate at management-relevant scales. The National Park Service is developing climate adaptation plans to alleviate the undesirable consequences of climate change. This is particularly timely for the National Parks of the desert Southwest, which are among the most impacted by climate change in the National Park system (Hansen et al. 2014, Monahan and Fisichelli 2014) and remain potential refugia for birds and other wildlife (Wu et al. 2018). An important component of the planning process (Stein et al. 2014) is identifying species-specific vulnerability to climate change and this research is a valuable step in that process Acknowledgments We thank the National Park Service staff that assisted in the collection of these data, H. Thomas for assistance with data management, A. Wight for assistance with our GIS needs, and all field technicians involved in the bird monitoring of the NCPN. Funding statement: Funding for this research was provided by The Northern Colorado Plateau Inventory and Monitoring Network of the National Park Service. Ethics statement: We used passive, noninvasive sampling methods (point counts). Author contributions: S.G.R., D.P.T, D.W.P., and W.G.S. conceived the idea and design; S.G.R. and E.L.T. collected field data; S.G.R., D.P.T, D.W.P., E.L.T., Z.S.L., and W.G.S. wrote the paper; S.G.R., D.P.T, D.W.P., Z.S.L., and W.G.S. developed methods; and S.G.R., D.P.T., and Z.S.L analyzed the data. Data depository: With the exception of the water balance model used to estimate annual water deficit, which is in preparation for publication, the analyses reported in this article can be reproduced using the data and R code provided by Roberts et al. (2021). LITERATURE CITED Albright , T. P. , A. M. Pidgeon, C. D. Rittenhouse, M. K. Clayton, C. 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Google Scholar Crossref Search ADS PubMed WorldCat Copyright © American Ornithological Society 2021. All rights reserved. For permissions, e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Ornithology Oxford University Press

A habitat-based approach to determining the effects of drought on aridland bird communities

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Abstract

Abstract Aridland breeding bird communities of the United States are among the most vulnerable to drought, with many species showing significant population declines associated with decreasing precipitation and increasing temperature. Individual breeding bird species have varied responses to drought which suggests complex responses to changes in water availability. Here, we evaluated the influence of water deficit, an integrative metric of drought stress, on breeding bird communities within 3 distinct aridland habitat types: riparian, pinyon-juniper, and sagebrush shrubland. We used 12 years of breeding bird survey data from 11 national parks and monuments in the Northern Colorado Plateau Inventory and Monitoring Network (NCPN). We used a multivariate community-level approach to test for the effect of annual water deficit on the bird communities in the 3 habitats. We found that bird communities responded to water deficit in all 3 habitat types, and 70% of the 30 species–habitat combinations show significant relationships between density and variation in water deficit. Our analyses revealed that the direction and magnitude of species responses to water deficit were habitat-dependent. The habitat-specific responses we observed suggest that the adaptive capacity of some species depends on the habitat in which they occur, a pattern only elucidated with our habitat-based approach. The direction and magnitude of the relationships between predicted densities and annual water deficit can be used to predict the relative sensitivity of species within habitat climate changes. These results provide the first attempt to determine how the indirect effect of changes in water availability might affect aridland breeding birds in distinct habitat types. Linking breeding bird density to annual water deficit may be valuable for predicting changes in species persistence and distribution in response to climate change. RESUMEN Las comunidades de aves reproductivas de tierras áridas de Estados Unidos están entre las más vulnerables a la sequía, con muchas especies mostrando declives poblacionales significativos asociados con disminuciones en la precipitación y aumentos en la temperatura. Las especies individuales de aves reproductivas tienen respuestas variadas a la sequía, lo que sugiere respuestas complejas a los cambios en la disponibilidad de agua. En este estudio, evaluamos la influencia del déficit de agua, una métrica integradora del estrés por sequía, sobre las comunidades de aves reproductivas dentro de tres tipos de hábitats áridos distintos: ribereño, piñón-enebro y matorral de artemisa. Usamos 12 años de datos de censos de aves reproductivas provenientes de 11 parques y monumentos nacionales de la Red de Monitoreo e Inventario de la Meseta del Norte de Colorado. Usamos un enfoque multivariado a nivel de comunidad para evaluar el efecto del déficit anual de agua sobre las comunidades de aves en los tres hábitats. Encontramos que las comunidades de aves respondieron al déficit de agua en todos los tres tipos de hábitat, y 70% de las 30 combinaciones de especies y hábitats mostraron relaciones significativas entre densidad y variación en el déficit de agua. Nuestros análisis revelaron que la dirección y magnitud de las respuestas de las especies al déficit de agua fue dependiente del hábitat. Las respuestas específicas al hábitat que observamos sugieren que la capacidad adaptativa de algunas especies depende del hábitat en el que están presentes, un patrón solo dilucidado con nuestro enfoque basado en el hábitat. La dirección y magnitud de las relaciones entre las densidades predichas y el déficit anual de agua puede ser usada para predecir la sensibilidad relativa de las especies al cambio climático dentro de cada hábitat. Estos resultados representan el primer intento para determinar cómo el efecto indirecto de los cambios en la disponibilidad de agua podría afectar a las aves reproductivas de las tierras áridas en distintos tipos de hábitats. Vincular la densidad de las aves reproductivas al déficit anual de agua puede ser importante para predecir los cambios en la persistencia y distribución de las especies en respuesta al cambio climático. Lay Summary Birds of the desert Southwest, a climate change hotspot, are among the most vulnerable groups in the United States and the risk of population declines increases with increasing drought frequency and intensity. Using 12 years of bird monitoring data, we determined how bird communities in 3 distinct habitats (riparian, pinyon-juniper, and sagebrush shrubland) responded to water deficit (a measure of drought stress) in 11 national parks and monuments in the Northern Colorado Plateau. We found that the aridland breeding bird community responses to annual water deficit depended on habitat type. Through the identification of the sensitivity of species to drought stress in specific habitats, land managers can further focus conservation efforts on the habitat in which a species is most vulnerable and prioritize habitat obligate species that show vulnerability to projected climate changes within essential habitat. Introduction The southwestern United States is a climate change hotspot where increasing aridity is projected across many scenarios (Seager et al. 2007, Diffenbaugh et al. 2008). Aridland songbird communities have been identified as one of the most vulnerable avian groups in the United States (Sauer et al. 2017, Rosenberg et al. 2019) and are particularly susceptible to drought as they already exist near physiological limits resulting from the combination of dry environmental conditions, high metabolic demands, and extreme rates of water loss. Even slight increases in ambient temperatures, which can lead to increased water requirements, can reduce foraging activity patterns (Albright et al. 2017), disrupt reproductive timing (Visser et al. 2009, McCreedy and van Riper 2015), and increase mortality rates (McKechnie and Wolf 2010). For aridland birds, temperature changes can result in abundance shifts (George et al. 1992, Albright et al. 2010a, Cruz-McDonnell and Wolf 2016, Roberts et al. 2019), lowered species richness (Albright et al. 2010b), lowered site occupancy (Riddell et al. 2019), and may result in broad-scale range shifts in the coming decades (Albright et al. 2017). Increases in drought stress in the Southwest will heighten the vulnerability of aridland bird species to projected increases in aridity for the region (Ault et al. 2014). Aridland birds are experiencing some of the largest population declines of any group in North America (Sauer et al. 2017), and Rosenberg et al. (2016) estimated that 28% of aridland birds are in steep decline. Sagebrush habitat dependent species are among the rapidly declining aridland species in the Southwest with Sage Thrasher (Oreoscoptes montanus) and Brewer’s Sparrow (Spizella breweri), showing significant population declines (44% and 35%, respectively, from 1970 to 2014) and sensitivity to warming temperatures and increased aridity (Rosenberg et al. 2016). The combined effects of extreme temperatures and reduced precipitation directly affect species across the contiguous United States but are greatest in the Southwest (Albright et al. 2010b). The Mojave Desert bird community is thought to be experiencing a community collapse in response to increased water stress caused by long-term declines in precipitation (Iknayan and Beissinger 2018). Shifts in small-bodied bird population abundance are already occurring in arid landscapes (Albright et al. 2010a, 2010b) while extreme temperature events under projected climate change scenarios render portions of species’ ranges uninhabitable (Albright et al. 2017). Therefore, the required range shifts necessary for some species to persist may prove difficult or impossible because of limitations of extrinsic biotic and abiotic environmental factors (Hargrove and Rotenberry 2011), which will increase local extirpations and shift aridland bird community structure. While temperature and precipitation are important drivers of bird response to climate change, water deficit is a more integrative metric that incorporates a suite of site-specific variables (Stephenson 1998, Lutz et al. 2010). Water deficit is the atmospheric demand for water that is unmet by soil moisture supply. It accounts for the imbalance between water supplied by precipitation and the atmospheric demand of dry air. Deficit accounts for changes caused by both precipitation and temperature. This is one reason why deficit is a more integrative measure of water availability. Importantly, deficit is more locally relevant because it accounts for modification of temperature and precipitation effects due to site characteristics, such as elevation, slope, and aspect. Previously, drought was characterized as below-average precipitation, however, increasing temperature increases evaporative demand non-linearly (Lutz et al. 2010, supplemental 2, equations 9 and 10). Thus, with warming, above-average temperature simultaneously occurring with below-average precipitation can result in extreme water stress (Allen et al. 2015). As a single variable, water deficit simplifies understanding drought stress caused by below-average precipitation, above-average temperature, or any combination thereof. Temperature and precipitation provide direct mechanisms for explaining changes to breeding bird distribution and abundance, while water deficit can aid in the determination of indirect effects of how changes to vegetation condition can, in turn, affect changes in breeding bird communities. The process of seasonal wetting and drying that is modified by site characteristics is strongly correlated with vegetation conditions on the Colorado Plateau (Thoma et al. 2019). Thoma et al. (2019) found that vegetation responded strongly to water deficit, but the magnitude of effect varied by vegetation type due to site factors including soil water holding capacity, texture, and depth. Sagebrush habitats with deeper and finer soil textures had twice the water holding capacity (115 mm) as pinyon-juniper habitats (56 mm), which are often on rockier soils (Thoma et al. 2019). For a given climate, soils with lower water holding capacity will result in higher water deficits because they retain less water and dry more rapidly. Local climate conditions reflected in water deficit calculations make water deficit a more nuanced, and perhaps a more meaningful metric in the study of the indirect effects of drought stress and climate change on bird populations. Given the strong association with vegetation condition and water deficit in earlier studies of vegetation condition in these parks, here we evaluate relationships between bird density and water deficit that could be mediated through effects of water deficit on vegetation condition. Using 12 years of breeding bird monitoring data, we determined how habitat-specific bird communities were related to water deficit in 11 national parks and monuments in the Northern Colorado Plateau Inventory and Monitoring Network (NCPN). National parks are protected from most anthropogenic disturbances and provide important wildlife habitat in the face of increasing threats outside park boundaries (Rodhouse et al. 2016). However, despite their protected status, National Park Service lands remain vulnerable to human-induced climate change, making them ideal settings for research on the indirect effects of a changing climate using observational experiments and long-term monitoring data. Our study area has been in a drought condition for much of the past 20 years (Cook et al. 2010, Vicente-Serrano et al. 2013). Compared to the historic range of variability from 1901 to 2012, national parks of the desert Southwest were in the 95th percentile of mean annual temperature and 25–75th percentile of annual precipitation in the preceding 10- (2003–2012), 20- (1993–2012), and 30-year (1983–2012) periods (Monahan and Fisichelli 2014). Among national parks nationwide, those of the desert southwest are projected to have the highest rates of warming, greatest reduction in precipitation, and high rates of climate-induced biome shifts (Hansen et al. 2014). The magnitude and direction of the aridland bird community response to changes in vegetation caused by water deficit are currently unknown. Water deficit integrates temperature, precipitation, evapotranspiration, elevation, slope, aspect, and soil properties making it a valuable predictor for the potential indirect effects of these climate drivers on future aridland bird distributions and community structure. Because water deficit is an effective predictor of vegetation distribution (Stephenson 1998, Lutz et al. 2010), mortality (van Mantgem et al. 2009), seed production (Wion et al. 2019), and overall condition (Notaro et al. 2010, Robinson et al. 2013), and given the known relationships among breeding bird communities and vegetation structure (Cody 1981, James and Wamer 1982, Chandler et al. 2009, Culbert et al. 2013), vegetation composition (Fleishman et al. 2003, Seavy and Alexander 2011), and vegetation condition (Seavy and Alexander 2011, Glisson et al. 2015), we hypothesized that the bird communities dependent on vegetation for nest sites and food production to successfully produce young would respond to the spatial and temporal variation in water deficit. Our research focused on determining the breeding bird community response to variation in water deficit derived from an annual water balance model (hereafter “water deficit”; Lutz et al. 2010, Dilts et al. 2015, Thoma et al. 2019) in 3 habitats (riparian, pinyon-juniper, and sagebrush shrubland) with the goal of building predictive models to elucidate the adaptive capacity of these aridland species to climate shifts. METHODS Study Design and Habitat Descriptions We used 12 years (2005–2015 and 2017) of breeding bird survey data to estimate bird densities in 3 habitat types (riparian, pinyon-juniper, and sagebrush shrubland) in 11 national parks and monuments of the National Park Service’s Northern Colorado Plateau Inventory and Monitoring Network (Figure 1). We identified pinyon-juniper and sagebrush shrubland habitat types on land-cover maps from the Southwest Regional Gap Analysis Project (Lowry et al. 2005) or using vegetation-association maps (Daw et al. 2017). Riparian habitat occurs along perennial streams as narrow strips of habitat, surrounded by dry uplands, and contains multiple layers of canopy, which may experience different degrees of dryness depending on groundwater levels and rooting depths. The riparian habitat is dominated by willow (Salix spp.), Tamarisk (Tamarix ramosissima), and isolated stands of Fremont cottonwood (Populus fremontii) and boxelder (Acer negundo). Pinyon-juniper habitat is dominated by two-needle pinyon (Pinus edulis) and junipers (Juniperus spp.), which varied in relative abundance. The shrub layer in pinyon-juniper habitat varies throughout the NCPN, but is often dominated by sagebrush (Artemisia spp.), mountain mahogany (Cercocarpus spp.), jointfir (Ephedra spp.), and cliffrose (Purshia spp.). Sagebrush shrubland habitat is dominated by sagebrush, primarily big sagebrush (Artemisia tridentata) and prairie sagewort (A. frigida), with rabbitbrush (Chrysothamnus spp.), greasewood (Sarcobatus spp.), and other shrub species interspersed. Riparian transects ranged in elevation from 1,283 m to 1,901 m, pinyon-juniper transects ranged in elevation from 1,393 m to 2,402 m, and sagebrush shrubland transects ranged in elevation from 1,666 m to 2,447 m. Transects within each habitat type were established across a large latitudinal gradient to allow for habitat comparisons and to guard against variation that occurs across broad geographic gradients (Figure 1). Figure 1. Open in new tabDownload slide Map of the 11 national parks and monuments where point-count surveys were conducted from 2005 to 2015 and 2017. Figure 1. Open in new tabDownload slide Map of the 11 national parks and monuments where point-count surveys were conducted from 2005 to 2015 and 2017. Water Deficit Estimates Water deficit is a measure of drought stress and is the amount of additional water vegetation would use if it was available (Stephenson 1998). The use of water-year, defined as October 1–September 30 of the following year, in the estimation of water deficit is routine in studies of vegetative responses to climate in the desert southwest, as it helps account for precipitation legacies that influence plants during the growing season (Reichmann et al. 2013, Bunting et al. 2017, Thoma et al. 2019). We used a monthly water balance model to estimate water-year water deficit using temperature and precipitation at the center of 45 bird survey transects (see below) following the methods of Lutz et al. (2010). Precipitation was partitioned into soil moisture, the quantity of water stored in the top meter of soil at the end of each month, and runoff which included overland flow plus infiltration below the rooting zone. Runoff is the proportion of water that is not available for plant growth. Maximum storage in the top meter of soil was defined by water holding capacity obtained from soil surveys (Soil Survey Staff 2019). Potential evapotranspiration (PET, mm) was the amount of water that could be evaporated or transpired with available energy if soil moisture was unlimited. Actual evapotranspiration (AET, mm) was the estimated monthly loss of water from soil via evaporation and transpiration, limited by the availability of soil moisture. Water deficit (mm) was calculated as the difference between PET and AET (Stephenson 1998). We used Daymet daily temperature and precipitation data at a 1-km grain as the climatic input to the model (Thornton et al. 2016). These data were co-located with bird point-count transects and thus represent the local elevation and latitude effects on precipitation and temperature at 1-km resolution. Within each 1-km grid cell of a temperature and precipitation time series, the water balance model calculated heat load due to slope and aspect obtained from 30-m digital elevation model at the center of each transect (U.S. Geological Survey, 2017). Heat load was calculated as a scaling factor used to adjust PET up on south aspects or down on north aspects, thus accounting for slope and aspect interactions (Lutz et al. 2010 after McCune and Keon 2002). Breeding Bird Community We sampled the breeding bird community at 675 unique sampling locations on 45 transects during the breeding season (May 1 through July 15), the timing of which varied by transect location. The elevation and latitudinal position of each transect was considered during the scheduling of each field season such that all transects were surveyed within their peak breeding season and after the passage of migratory birds. Transect orientation in pinyon-juniper and sagebrush shrubland habitats were randomly determined following protocol procedures outlined in Daw et al. (2017), the riparian transects surveyed in this study consisted of narrow strips of habitat, requiring transect placement to be centered along the length of the habitat and to follow the natural orientation of the riparian zone. All riparian habitat was narrow enough that the entire width of the riparian zone was included in the point radius of each survey (see below) and that dry upland habitat was also included in surveys of riparian habitat at some locations. Each transect consisted of 15 point-count locations, with points spaced 250 m apart. Observers visited 1 transect per day, initiated sampling within 30 min before sunrise, and completed the survey within 5 hr after sunrise. Observers walked the transect, navigated to each point using a GPS unit, and completed a 5-min point-count survey. We did not conduct surveys if winds exceeded a four on the Beaufort Scale (13–18 mph) or precipitation was more than a drizzle. During each point count, observers recoded the species and distance (m) to all individuals detected. Observers estimated the distance to each bird or cluster of birds using a laser rangefinder (Simmons LRF 600; Simmons Outdoor Products, Overland Park, KS, USA). From 2005 to 2013, field teams surveyed each transect twice annually. Starting in 2014, survey effort was reduced to one visit per year because a sufficient number of detections to estimate density had been obtained for most bird species detected and to reduce costs. The number of completed surveys varied by year, but >75% of possible surveys were completed annually. For more detailed information about survey protocols, refer to Daw et al. (2017). We first estimated transect-level detection-adjusted densities for each bird species using the Distance package (Miller et al. 2019) in program R (3.6.1, http://www.r-project.org). To avoid including double-counted individuals in our analyses, we only included detections within 125 m from the point center in our analyses. The total area covered by each transect was 73.6 ha (i.e. 15, 125-m radius points per transect). Next, we used the detection-adjusted density estimates in a multivariate analysis to determine the bird community response to changes in water deficit using the manyglm function in the R package mvabund (Wang et al. 2012). The mvabund package provides a novel set of hypothesis testing tools that is a flexible and powerful framework for analyzing multivariate abundance data (Wang et al. 2012). We used the manyglm function to simultaneously fit general linear models to each species using water deficit as the common predictor variable (Wang et al. 2012). This model-based approach alleviates the mean–variance relationship problem associated with distance-based community-level metrics (Warton et al. 2012). To meet the data structure requirements of mvabund, we sought to maximize the number of transect-level density estimates available using Distance by constraining our analyses to only include the 10 species within each habitat type with the greatest number of transect-level density estimates available (Table 1). Species with the greatest number of detections allow for the greatest number of transect-level density estimate; therefore, the species included in each habitat are not the species with the highest densities, rather the species with the greatest number of detections. For species-transect-year combinations where detections were too few to estimate density, we summed the unadjusted counts and divided by the average detection probability for that species-year. This was done for 6% of the density estimates to satisfy the need for a response variable for all species-transect-year combinations. Table 1. Aridland breeding bird community composition and mean density (±SE) for each species, estimating from 2005 to 2015 and 2017 in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Common name . Scientific name . Mean density (birds km–2) . Riparian Mourning Dove a Zenaida macroura 14.0 ± 2.1 White-throated Swift Aeronautes saxatalis 15.6 ± 2.7 Ash-throated Flycatcher b Myiarchus cinerascens 23.9 ± 1.6 Violet-green Swallow Tachycineta thalassina 50.8 ± 5.1 Blue-gray Gnatcatcher b Polioptila caerulea 120.5 ± 8.8 Rock Wren b Salpinctes obsoletus 7.9 ± 0.8 House Finch b Haemorhous mexicanus 29.5 ± 2.9 Spotted Towhee a Pipilo maculatus 88.4 ± 5.5 Yellow Warbler Setophaga petechial 92.2 ± 11.8 Lazuli Bunting Passerina amoena 53.9 ± 8.6 Pinyon-juniper Mourning Dove a 21.8 ± 4.5 Gray Flycatcher Empidonax wrightii 34.0 ± 3.1 Ash-throated Flycatcher b 15.8 ± 1.9 Gray Vireo Vireo vicinior 16.4 ± 2.8 Juniper Titmouse Baeolophus ridgwayi 40.2 ± 4.7 Blue-gray Gnatcatcher b 131.4 ± 8.9 Bewick’s Wren Thryomanes bewickii 15.0 ± 2.0 House Finch b 22.3 ± 2.2 Spotted Towhee a 24.3 ± 3.2 Black-throated Gray Warbler Setophaga nigrescens 82.5 ± 6.8 Sagebrush shrubland Mourning Dove a 6.8 ± 1.8 Dusky Flycatcher Empidonax oberholseri 10.0 ± 1.8 Rock Wren b 5.5 ± 0.7 Sage Thrasher Oreoscoptes montanus 4.7 ± 0.8 Spotted Towhee a 9.8 ± 1.3 Green-tailed Towhee Pipilo chlorurus 47.8 ± 5.5 Brewer’s Sparrow Spizella breweri 90.2 ± 6.8 Vesper Sparrow Pooecetes gramineus 45.7 ± 3.9 Lark Sparrow Chondestes grammacus 12.4 ± 2.2 Western Meadowlark Sturnella neglecta 7.5 ± 1.0 Habitat . Common name . Scientific name . Mean density (birds km–2) . Riparian Mourning Dove a Zenaida macroura 14.0 ± 2.1 White-throated Swift Aeronautes saxatalis 15.6 ± 2.7 Ash-throated Flycatcher b Myiarchus cinerascens 23.9 ± 1.6 Violet-green Swallow Tachycineta thalassina 50.8 ± 5.1 Blue-gray Gnatcatcher b Polioptila caerulea 120.5 ± 8.8 Rock Wren b Salpinctes obsoletus 7.9 ± 0.8 House Finch b Haemorhous mexicanus 29.5 ± 2.9 Spotted Towhee a Pipilo maculatus 88.4 ± 5.5 Yellow Warbler Setophaga petechial 92.2 ± 11.8 Lazuli Bunting Passerina amoena 53.9 ± 8.6 Pinyon-juniper Mourning Dove a 21.8 ± 4.5 Gray Flycatcher Empidonax wrightii 34.0 ± 3.1 Ash-throated Flycatcher b 15.8 ± 1.9 Gray Vireo Vireo vicinior 16.4 ± 2.8 Juniper Titmouse Baeolophus ridgwayi 40.2 ± 4.7 Blue-gray Gnatcatcher b 131.4 ± 8.9 Bewick’s Wren Thryomanes bewickii 15.0 ± 2.0 House Finch b 22.3 ± 2.2 Spotted Towhee a 24.3 ± 3.2 Black-throated Gray Warbler Setophaga nigrescens 82.5 ± 6.8 Sagebrush shrubland Mourning Dove a 6.8 ± 1.8 Dusky Flycatcher Empidonax oberholseri 10.0 ± 1.8 Rock Wren b 5.5 ± 0.7 Sage Thrasher Oreoscoptes montanus 4.7 ± 0.8 Spotted Towhee a 9.8 ± 1.3 Green-tailed Towhee Pipilo chlorurus 47.8 ± 5.5 Brewer’s Sparrow Spizella breweri 90.2 ± 6.8 Vesper Sparrow Pooecetes gramineus 45.7 ± 3.9 Lark Sparrow Chondestes grammacus 12.4 ± 2.2 Western Meadowlark Sturnella neglecta 7.5 ± 1.0 a Species analyzed in 3 habitats. b Species analyzed in 2 habitats. Open in new tab Table 1. Aridland breeding bird community composition and mean density (±SE) for each species, estimating from 2005 to 2015 and 2017 in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Common name . Scientific name . Mean density (birds km–2) . Riparian Mourning Dove a Zenaida macroura 14.0 ± 2.1 White-throated Swift Aeronautes saxatalis 15.6 ± 2.7 Ash-throated Flycatcher b Myiarchus cinerascens 23.9 ± 1.6 Violet-green Swallow Tachycineta thalassina 50.8 ± 5.1 Blue-gray Gnatcatcher b Polioptila caerulea 120.5 ± 8.8 Rock Wren b Salpinctes obsoletus 7.9 ± 0.8 House Finch b Haemorhous mexicanus 29.5 ± 2.9 Spotted Towhee a Pipilo maculatus 88.4 ± 5.5 Yellow Warbler Setophaga petechial 92.2 ± 11.8 Lazuli Bunting Passerina amoena 53.9 ± 8.6 Pinyon-juniper Mourning Dove a 21.8 ± 4.5 Gray Flycatcher Empidonax wrightii 34.0 ± 3.1 Ash-throated Flycatcher b 15.8 ± 1.9 Gray Vireo Vireo vicinior 16.4 ± 2.8 Juniper Titmouse Baeolophus ridgwayi 40.2 ± 4.7 Blue-gray Gnatcatcher b 131.4 ± 8.9 Bewick’s Wren Thryomanes bewickii 15.0 ± 2.0 House Finch b 22.3 ± 2.2 Spotted Towhee a 24.3 ± 3.2 Black-throated Gray Warbler Setophaga nigrescens 82.5 ± 6.8 Sagebrush shrubland Mourning Dove a 6.8 ± 1.8 Dusky Flycatcher Empidonax oberholseri 10.0 ± 1.8 Rock Wren b 5.5 ± 0.7 Sage Thrasher Oreoscoptes montanus 4.7 ± 0.8 Spotted Towhee a 9.8 ± 1.3 Green-tailed Towhee Pipilo chlorurus 47.8 ± 5.5 Brewer’s Sparrow Spizella breweri 90.2 ± 6.8 Vesper Sparrow Pooecetes gramineus 45.7 ± 3.9 Lark Sparrow Chondestes grammacus 12.4 ± 2.2 Western Meadowlark Sturnella neglecta 7.5 ± 1.0 Habitat . Common name . Scientific name . Mean density (birds km–2) . Riparian Mourning Dove a Zenaida macroura 14.0 ± 2.1 White-throated Swift Aeronautes saxatalis 15.6 ± 2.7 Ash-throated Flycatcher b Myiarchus cinerascens 23.9 ± 1.6 Violet-green Swallow Tachycineta thalassina 50.8 ± 5.1 Blue-gray Gnatcatcher b Polioptila caerulea 120.5 ± 8.8 Rock Wren b Salpinctes obsoletus 7.9 ± 0.8 House Finch b Haemorhous mexicanus 29.5 ± 2.9 Spotted Towhee a Pipilo maculatus 88.4 ± 5.5 Yellow Warbler Setophaga petechial 92.2 ± 11.8 Lazuli Bunting Passerina amoena 53.9 ± 8.6 Pinyon-juniper Mourning Dove a 21.8 ± 4.5 Gray Flycatcher Empidonax wrightii 34.0 ± 3.1 Ash-throated Flycatcher b 15.8 ± 1.9 Gray Vireo Vireo vicinior 16.4 ± 2.8 Juniper Titmouse Baeolophus ridgwayi 40.2 ± 4.7 Blue-gray Gnatcatcher b 131.4 ± 8.9 Bewick’s Wren Thryomanes bewickii 15.0 ± 2.0 House Finch b 22.3 ± 2.2 Spotted Towhee a 24.3 ± 3.2 Black-throated Gray Warbler Setophaga nigrescens 82.5 ± 6.8 Sagebrush shrubland Mourning Dove a 6.8 ± 1.8 Dusky Flycatcher Empidonax oberholseri 10.0 ± 1.8 Rock Wren b 5.5 ± 0.7 Sage Thrasher Oreoscoptes montanus 4.7 ± 0.8 Spotted Towhee a 9.8 ± 1.3 Green-tailed Towhee Pipilo chlorurus 47.8 ± 5.5 Brewer’s Sparrow Spizella breweri 90.2 ± 6.8 Vesper Sparrow Pooecetes gramineus 45.7 ± 3.9 Lark Sparrow Chondestes grammacus 12.4 ± 2.2 Western Meadowlark Sturnella neglecta 7.5 ± 1.0 a Species analyzed in 3 habitats. b Species analyzed in 2 habitats. Open in new tab Because there is likely a time lag in the bird community response to water deficit-driven changes in vegetation, we compared 2 time-lag models (a 1-year lag and a 2-year lag effect of annual water deficit) against a null model within each habitat and selected the model with the lowest Akaike information criterion (AICc, Burnham and Anderson 2002). We did not explore other lags because vegetation response to legacy effects of precipitation shortfalls revert to average condition within 2 years in semiarid grasslands (Thoma et al. 2016). Once we determined the most appropriate time lag within each habitat type, we then tested for community-wide responses to annual water deficit within each habitat using analysis of variance (ANOVA) on the manyglm object and assessed the resulting likelihood ratio tests (LRT; Warton 2011) and resampled P-values (Wang et al. 2012). If we detected a significant community-level response to water deficit within a habitat type, we then used p.uni = “adjusted” argument to determine the effect size and direction of the response for each species. Finally, we predicted the relationships between species’ densities and annual water deficit using the “predict” function on the best model within each habitat type. RESULTS From 2005 to 2015 and 2017, we conducted 12,974 point counts at 675 unique sampling locations on 45 transects during the breeding season in 11 NCPN parks and monuments, with annual averages of 349 points in riparian habitat, 356 points in pinyon-juniper habitat, and 376 points in sagebrush shrubland habitat. Annual water deficit was lowest in sagebrush and greatest in riparian habitats (Table 2). Table 2. Annual mean (±95% CI) and range of variation of climate and water deficit conditions among and within transects from 2004 to 2016 for riparian and pinyon-juniper habitats (used for analysis with a 1-year lag) and from 2003 to 2015 for sagebrush shrubland habitat (used for analysis with a 2-year lag) in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Precipitation . Temperature . Water deficit . Minimum and maximum annual water deficit across transects . Minimum range in annual water deficit within a transect . Maximum range in annual water deficit within a transect . . (mm) . (°C) . (mm) . (mm) . (mm) . (mm) . Riparian 275.4 ± 15.1 12.0 ± 0.3 536.4 ± 17.8 215.2–810.1 172.2 319.5 Pinyon-juniper 328.7 ± 15.8 10.0 ± 0.3 360.9 ± 19.8 76.9–717.2 124.6 455.8 Sagebrush shrubland 333.6 ± 15.5 6.4 ± 0.2 204.3 ± 15.1 33.6–559.8 59.3 293.8 Habitat . Precipitation . Temperature . Water deficit . Minimum and maximum annual water deficit across transects . Minimum range in annual water deficit within a transect . Maximum range in annual water deficit within a transect . . (mm) . (°C) . (mm) . (mm) . (mm) . (mm) . Riparian 275.4 ± 15.1 12.0 ± 0.3 536.4 ± 17.8 215.2–810.1 172.2 319.5 Pinyon-juniper 328.7 ± 15.8 10.0 ± 0.3 360.9 ± 19.8 76.9–717.2 124.6 455.8 Sagebrush shrubland 333.6 ± 15.5 6.4 ± 0.2 204.3 ± 15.1 33.6–559.8 59.3 293.8 Open in new tab Table 2. Annual mean (±95% CI) and range of variation of climate and water deficit conditions among and within transects from 2004 to 2016 for riparian and pinyon-juniper habitats (used for analysis with a 1-year lag) and from 2003 to 2015 for sagebrush shrubland habitat (used for analysis with a 2-year lag) in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Precipitation . Temperature . Water deficit . Minimum and maximum annual water deficit across transects . Minimum range in annual water deficit within a transect . Maximum range in annual water deficit within a transect . . (mm) . (°C) . (mm) . (mm) . (mm) . (mm) . Riparian 275.4 ± 15.1 12.0 ± 0.3 536.4 ± 17.8 215.2–810.1 172.2 319.5 Pinyon-juniper 328.7 ± 15.8 10.0 ± 0.3 360.9 ± 19.8 76.9–717.2 124.6 455.8 Sagebrush shrubland 333.6 ± 15.5 6.4 ± 0.2 204.3 ± 15.1 33.6–559.8 59.3 293.8 Habitat . Precipitation . Temperature . Water deficit . Minimum and maximum annual water deficit across transects . Minimum range in annual water deficit within a transect . Maximum range in annual water deficit within a transect . . (mm) . (°C) . (mm) . (mm) . (mm) . (mm) . Riparian 275.4 ± 15.1 12.0 ± 0.3 536.4 ± 17.8 215.2–810.1 172.2 319.5 Pinyon-juniper 328.7 ± 15.8 10.0 ± 0.3 360.9 ± 19.8 76.9–717.2 124.6 455.8 Sagebrush shrubland 333.6 ± 15.5 6.4 ± 0.2 204.3 ± 15.1 33.6–559.8 59.3 293.8 Open in new tab Models with a 1-year time-lag effect of annual water deficit on bird density performed best in riparian (ΔAIC = 15.5) and pinyon-juniper (ΔAIC = 18.7) habitats, while the 2-year lag effect was the best model in sagebrush shrubland (ΔAIC = 33.4) habitat. Annual water deficit had a significant effect on bird density at the community level within each habitat (riparian: LRT = 126, P < 0.001; pinyon-juniper: LRT = 140, P < 0.001; sagebrush shrubland: LRT = 226, P < 0.001). Individual species varied in both the direction and magnitude of their relationship to annual water deficit within each habitat type (Figure 2). Of the 30 species–habitat combinations included in this analysis, we found 27% (n = 8) were negatively related, 43% (n = 13) were positively related, and 30% (n = 9) were not related to annual water deficit (Figure 2). Figure 2. Open in new tabDownload slide Species beta coefficients (±95% CI) from the multivariate analysis of the effect of annual water deficit on bird density within each of the surveyed habitats in 11 national parks and monuments in the Northern Colorado Plateau Network from 2005 to 2015 and 2017. Figure 2. Open in new tabDownload slide Species beta coefficients (±95% CI) from the multivariate analysis of the effect of annual water deficit on bird density within each of the surveyed habitats in 11 national parks and monuments in the Northern Colorado Plateau Network from 2005 to 2015 and 2017. In riparian habitat, 4 species (Mourning Dove [Zenaida macroura], Ash-throated Flycatcher [Myiarchus cinerascens], House Finch [Haemorhous mexicanus], and Violet-green Swallow [Tachycineta thalassina]) were positively and 3 species (Spotted Towhee [Pipilo maculatus], Lazuli Bunting [Passerina amoena], and Yellow Warbler [Setophaga petechial]) were negatively related to water deficit (Table 3, Figure 2). In pinyon-juniper habitat, 5 species (Gray Vireo [Vireo vicinior], House Finch, Bewick’s Wren [Thryomanes bewickii], Juniper Titmouse [Baeolophus ridgwayi], and Ash-throated Flycatcher) were positively and 2 species (Gray Flycatcher [Empidonax wrightii] and Spotted Towhee) were negatively related to water deficit (Table 3, Figure 2). In sagebrush shrubland, 4 species (Lark Sparrow [Chondestes grammacus], Mourning Dove, Spotted Towhee, and Western Meadowlark [Sturnella neglecta]) were positively and 3 species (Sage Thrasher, Green-tailed Towhee [Pipilo chlorurus], and Dusky Flycatcher [Empidonax oberholseri]) were negatively related to water deficit (Table 3, Figure 2). Table 3. Beta (β) coefficients (± 95% CI) and likelihood ratio test (LRT) scores from a multivariate analysis for species with a significant (P ≤ 0.05) response to water deficit within each habitat type from 2005 to 2015 and 2017 in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Species . β ± 95% CI . LRT . Riparian Mourning Dove 2.52e-03 ± 1.27e-03 14.60 Ash-throated Flycatcher 1.86e-03 ± 7.40e-04 24.97 House Finch 1.39e-03 ± 7.38e-04 13.91 Violet-green Swallow 1.21e-03 ± 6.80e-04 12.46 Spotted Towhee –1.10e-03 ± 5.77e-04 13.85 Lazuli Bunting –2.07e-03 ± 1.28e-03 10.80 Yellow Warbler –2.88e-03 ± 9.31e-04 32.24 Pinyon-juniper Gray Vireo 2.61e-03 ± 7.79e-04 39.08 House Finch 2.01e-03 ± 6.77e-04 33.95 Bewick’s Wren 1.88e-03 ± 1.02e-03 11.37 Juniper Titmouse 1.33e-03 ± 6.27e-04 17.34 Ash-throated Flycatcher 1.17e-03 ± 7.16e-04 10.17 Gray Flycatcher –1.18e-03 ± 6.35e-04 13.48 Spotted Towhee –2.22e-03 ± 1.35e-03 11.95 Sagebrush shrubland Lark Sparrow 1.03e-02 ± 1.74e-03 81.97 Mourning Dove 3.63e-03 ± 1.56e-03 18.01 Spotted Towhee 2.61e-03 ± 1.75e-03 8.19 Western Meadowlark 2.36e-03 ± 1.55e-03 8.54 Sage Thrasher –4.20e-03 ± 2.89e-03 6.82 Green-tailed Towhee –5.51e-03 ± 1.31e-03 74.03 Dusky Flycatcher –8.40e-03 ± 3.52e-03 19.29 Habitat . Species . β ± 95% CI . LRT . Riparian Mourning Dove 2.52e-03 ± 1.27e-03 14.60 Ash-throated Flycatcher 1.86e-03 ± 7.40e-04 24.97 House Finch 1.39e-03 ± 7.38e-04 13.91 Violet-green Swallow 1.21e-03 ± 6.80e-04 12.46 Spotted Towhee –1.10e-03 ± 5.77e-04 13.85 Lazuli Bunting –2.07e-03 ± 1.28e-03 10.80 Yellow Warbler –2.88e-03 ± 9.31e-04 32.24 Pinyon-juniper Gray Vireo 2.61e-03 ± 7.79e-04 39.08 House Finch 2.01e-03 ± 6.77e-04 33.95 Bewick’s Wren 1.88e-03 ± 1.02e-03 11.37 Juniper Titmouse 1.33e-03 ± 6.27e-04 17.34 Ash-throated Flycatcher 1.17e-03 ± 7.16e-04 10.17 Gray Flycatcher –1.18e-03 ± 6.35e-04 13.48 Spotted Towhee –2.22e-03 ± 1.35e-03 11.95 Sagebrush shrubland Lark Sparrow 1.03e-02 ± 1.74e-03 81.97 Mourning Dove 3.63e-03 ± 1.56e-03 18.01 Spotted Towhee 2.61e-03 ± 1.75e-03 8.19 Western Meadowlark 2.36e-03 ± 1.55e-03 8.54 Sage Thrasher –4.20e-03 ± 2.89e-03 6.82 Green-tailed Towhee –5.51e-03 ± 1.31e-03 74.03 Dusky Flycatcher –8.40e-03 ± 3.52e-03 19.29 Open in new tab Table 3. Beta (β) coefficients (± 95% CI) and likelihood ratio test (LRT) scores from a multivariate analysis for species with a significant (P ≤ 0.05) response to water deficit within each habitat type from 2005 to 2015 and 2017 in 11 national parks and monuments in the Northern Colorado Plateau Network. Habitat . Species . β ± 95% CI . LRT . Riparian Mourning Dove 2.52e-03 ± 1.27e-03 14.60 Ash-throated Flycatcher 1.86e-03 ± 7.40e-04 24.97 House Finch 1.39e-03 ± 7.38e-04 13.91 Violet-green Swallow 1.21e-03 ± 6.80e-04 12.46 Spotted Towhee –1.10e-03 ± 5.77e-04 13.85 Lazuli Bunting –2.07e-03 ± 1.28e-03 10.80 Yellow Warbler –2.88e-03 ± 9.31e-04 32.24 Pinyon-juniper Gray Vireo 2.61e-03 ± 7.79e-04 39.08 House Finch 2.01e-03 ± 6.77e-04 33.95 Bewick’s Wren 1.88e-03 ± 1.02e-03 11.37 Juniper Titmouse 1.33e-03 ± 6.27e-04 17.34 Ash-throated Flycatcher 1.17e-03 ± 7.16e-04 10.17 Gray Flycatcher –1.18e-03 ± 6.35e-04 13.48 Spotted Towhee –2.22e-03 ± 1.35e-03 11.95 Sagebrush shrubland Lark Sparrow 1.03e-02 ± 1.74e-03 81.97 Mourning Dove 3.63e-03 ± 1.56e-03 18.01 Spotted Towhee 2.61e-03 ± 1.75e-03 8.19 Western Meadowlark 2.36e-03 ± 1.55e-03 8.54 Sage Thrasher –4.20e-03 ± 2.89e-03 6.82 Green-tailed Towhee –5.51e-03 ± 1.31e-03 74.03 Dusky Flycatcher –8.40e-03 ± 3.52e-03 19.29 Habitat . Species . β ± 95% CI . LRT . Riparian Mourning Dove 2.52e-03 ± 1.27e-03 14.60 Ash-throated Flycatcher 1.86e-03 ± 7.40e-04 24.97 House Finch 1.39e-03 ± 7.38e-04 13.91 Violet-green Swallow 1.21e-03 ± 6.80e-04 12.46 Spotted Towhee –1.10e-03 ± 5.77e-04 13.85 Lazuli Bunting –2.07e-03 ± 1.28e-03 10.80 Yellow Warbler –2.88e-03 ± 9.31e-04 32.24 Pinyon-juniper Gray Vireo 2.61e-03 ± 7.79e-04 39.08 House Finch 2.01e-03 ± 6.77e-04 33.95 Bewick’s Wren 1.88e-03 ± 1.02e-03 11.37 Juniper Titmouse 1.33e-03 ± 6.27e-04 17.34 Ash-throated Flycatcher 1.17e-03 ± 7.16e-04 10.17 Gray Flycatcher –1.18e-03 ± 6.35e-04 13.48 Spotted Towhee –2.22e-03 ± 1.35e-03 11.95 Sagebrush shrubland Lark Sparrow 1.03e-02 ± 1.74e-03 81.97 Mourning Dove 3.63e-03 ± 1.56e-03 18.01 Spotted Towhee 2.61e-03 ± 1.75e-03 8.19 Western Meadowlark 2.36e-03 ± 1.55e-03 8.54 Sage Thrasher –4.20e-03 ± 2.89e-03 6.82 Green-tailed Towhee –5.51e-03 ± 1.31e-03 74.03 Dusky Flycatcher –8.40e-03 ± 3.52e-03 19.29 Open in new tab The relationship between density and water deficit also varied in direction and magnitude of response for the same species in different habitats. Spotted Towhee occurred in all 3 habitats and was negatively associated with water deficit in riparian and pinyon-juniper and positively associated with water deficit in sagebrush shrubland (Figure 2). Mourning Dove also occurred in all 3 habitats and was positively associated with water deficit in riparian and sagebrush shrubland, but had no association with water deficit in pinyon-juniper (Figure 2). House Finch, Ash-throated Flycatcher, and Blue-gray Gnatcatcher (Polioptila caerulea) occurred in both riparian and pinyon-juniper habitats. House Finch and Ash-throated Flycatcher showed positive associations with increases in water deficit, while Blue-gray Gnatcatcher showed no association with water deficit in either habitat (Figure 2). Rock Wren (Salpinctes obsoletus) occurred in riparian and sagebrush shrubland habitat and had no association with water deficit in either habitat (Figure 2). Model-predicted relationships between bird density and annual water deficit varied by species and habitat type (Figure 3). For example, Dusky Flycatcher and Green-tailed Towhee densities in sagebrush shrubland habitat had strong negative associations with annual water deficit, showing a high sensitivity between 250 and 400 mm of annual water deficit (Figure 3). Conversely, Lark Sparrow density in sagebrush shrubland habitat was positively related to annual water deficit (Figure 3). Spotted Towhee density was negatively associated with annual water deficit in riparian (P < 0.001) and pinyon-juniper (P < 0.001) habitats and positively associated with water deficit in sagebrush shrubland habitat (P = 0.006; Figure 3). Figure 3. Open in new tabDownload slide Predicted species density responses (±95% CI) to water deficit in the 3 surveyed habitats 11 national parks and monuments in the Northern Colorado Plateau Network. Vertical dashed lines indicate the mean water deficit value across years (2004–2016 in riparian and pinyon-juniper; 2003–2015 in sagebrush shrubland) and transects within each habitat. Plots with black points and dashed lines indicate species–habitat combinations that had significant responses to annual water deficit values. Figure 3. Open in new tabDownload slide Predicted species density responses (±95% CI) to water deficit in the 3 surveyed habitats 11 national parks and monuments in the Northern Colorado Plateau Network. Vertical dashed lines indicate the mean water deficit value across years (2004–2016 in riparian and pinyon-juniper; 2003–2015 in sagebrush shrubland) and transects within each habitat. Plots with black points and dashed lines indicate species–habitat combinations that had significant responses to annual water deficit values. Discussion The 3 aridland breeding bird communities in this study showed strong associations with variation in annual water deficit, with 70% of the species showing significant though varying responses. Local water deficit differences result from site-level interactions among climate, topography, soil properties, and vegetation traits that respond differently to a given level of drought stress (Thoma et al. 2019). The spatial scale of our analyses captures variation in abiotic factors such as elevation, slope, aspect, and soil properties that influence the vegetation and, therefore, the relevant decisions associated with breeding bird habitat selection. Our habitat-based approach revealed that within each habitat type there were positive, negative, and neutral responses of bird species’ densities to water deficit and, for a few species, we detected different responses among habitats. While previous studies in the desert Southwest have found effects of precipitation, temperature, or both on bird populations across habitat types (Albright et al. 2010a, 2010b, Cruz-McDonnell and Wolf 2016, Iknayan and Beissinger 2018), to our knowledge ours is the first to use water deficit estimates within habitat types, highlighting the importance of locally mediated modifications of regional climate on bird populations at a fine geographic scale. A more regional approach (Albright et al. 2010a, 2010b, 2017, Iknayan and Beissinger 2018, Riddell et al. 2019), is informative for broad patterns in species responses to climate but the potential to detect varied species responses within different habitats is only possible with a habitat-based approach. Our results suggest that optimal habitat requirements can be met at varying annual water deficit values, and that the effect is habitat-dependent. Particular species responses may be explained by a host of indirect effects, but it is reasonable to hypothesize that the negative response of birds, such as Yellow Warblers in riparian habitat, is in part due to the close association of this species to vegetation with high water requirements that are affected by annual water deficit (Lowther et al. 2020). The mixed responses of species in the same habitat indicate that increased drought stress is not inherently negative or positive for all species, suggesting that bird species’ responses to increased water stress are likely driven by a complex suite of underlying factors. Puig-Gironès et al. (2017) also found mixed responses of species to water deficit, with both negative and neutral responses to water deficit for warbler species in northeastern Spain. The strength of response in bird density as a measure of sensitivity to changes in water deficit can be used to identify species potentially vulnerable to climate change in the Southwest. For example, under likely scenarios of increased temperatures and decreased precipitation, which will increase in water deficit, the relative adaptive capacity for Yellow Warbler in riparian habitats, where their response to water deficit was negative, is low and, therefore, their vulnerability would be high (Hunter et al. 1987, Lowther et al. 2020). We also identified species that seemed especially sensitive to water deficit, including Lazuli Bunting, in riparian habitat, Spotted Towhee in pinyon-juniper habitat, and Dusky Flycatcher and Green-tailed Towhee in sagebrush shrubland habitat. Seasonal variation in foliage height density influenced the risk of nest predation for Dusky Flycatcher in Northern California (Borgmann et al. 2013), indicating the indirect and negative effect of drought on fecundity for this species. Alternatively, species, such as Lark Sparrow in sagebrush shrubland habitat, Ash-throated Flycatcher in riparian habitat, House Finch in pinyon-juniper, and Gray Vireo in pinyon-juniper indicated positive responses to annual water deficit, and are therefore less vulnerable to projected increases in annual water deficit. Wysner et al. (2019) did not observe changes in Ash-throated Flycatcher breeding ecology related to spring temperatures in New Mexico, and Schlossberg (2006) found that elevation, not vegetation characteristics, was the best determinant of Gray Vireo abundance in the Colorado Plateau. Species responses in riparian habitat could be influenced by water sources outside of the study site, but the significant responses indicate that these species responded strongly to locally estimated deficit regardless of in-stream conditions that may be affected by groundwater inputs or accumulation of water from upslope. This suggests that nearby upland conditions that experience drought may affect species in riparian habitats. Species capable of breeding in multiple habitat types may have greater adaptive capacity to variation in water deficit. Spotted Towhee, a known shrubland habitat generalist (James 1971, Berry and Bock 1998), occurred in all 3 habitats and their response to annual water deficit was habitat dependent. Spotted Towhee breeding densities in riparian and pinyon-juniper habitats showed a negative response to water deficit, while those breeding in sagebrush shrubland habitat showed a positive response. In sagebrush shrublands, above-average precipitation can cause die-off in vegetation, specifically big sagebrush (Artemisia tridentata; Renne et al. 2019). As that habitat dries, conditions can improve for the vegetative community in sagebrush shubland, while the water deficit increases, which could explain a positive relationship between water deficit and bird density. While the biological drivers of these varying responses are unclear, Spotted Towhees are an example of a species that could shift from breeding in riparian and pinyon-juniper habitats to sagebrush shrubland habitat as annual water deficit increases. Drought stress is an important factor influencing bird populations and community structure (Tischler et al. 2013, McCreedy and van Riper 2015, Seymour et al. 2015, Theimer et al. 2018), and our results indicate that the response of bird densities to annual water deficit was likely due to a legacy of indirect effects such as primary production, plant fecundity (i.e. seed production; Bunting et al. 2017), or invertebrate food resource availability. Our analysis suggests there may be a water deficit value beyond which a species density declines, but increased temperature or decreased precipitation may also have more immediate and direct effects (Riddell et al. 2019, 2021). Additionally, compounding effects of prior year water deficit effects mediated through vegetation condition may interact with current year temperature and precipitation to cause precipitous declines greater than expected via either mechanism (direct or indirect). Understanding species’ exposure and sensitivity to climate change in specific habitat types over longer time frames, as in this study, can provide necessary information to manage lands based on the magnitude and timing of species vulnerability. In the vulnerability assessment phase of climate adaptation planning, quantitative and place-based knowledge of a species sensitivity to climate is critically important in determining when changes in specific habitats will affect specific species (Siegel et al. 2014). Site-level information can aid in crafting management strategies that reduce species vulnerability by identifying appropriately timed and habitat-specific management actions based on individual species’ needs. Plant communities and bird species vary in their ability to tolerate drought stress, leading to the differing responses we observed within and between habitat types (Noy-Meir 1973, Puig-Gironès et al. 2017). Our models provide quantitative information on the relative sensitivity of expected change in the density of a species with changing climate at management-relevant scales. The National Park Service is developing climate adaptation plans to alleviate the undesirable consequences of climate change. This is particularly timely for the National Parks of the desert Southwest, which are among the most impacted by climate change in the National Park system (Hansen et al. 2014, Monahan and Fisichelli 2014) and remain potential refugia for birds and other wildlife (Wu et al. 2018). An important component of the planning process (Stein et al. 2014) is identifying species-specific vulnerability to climate change and this research is a valuable step in that process Acknowledgments We thank the National Park Service staff that assisted in the collection of these data, H. Thomas for assistance with data management, A. Wight for assistance with our GIS needs, and all field technicians involved in the bird monitoring of the NCPN. Funding statement: Funding for this research was provided by The Northern Colorado Plateau Inventory and Monitoring Network of the National Park Service. Ethics statement: We used passive, noninvasive sampling methods (point counts). Author contributions: S.G.R., D.P.T, D.W.P., and W.G.S. conceived the idea and design; S.G.R. and E.L.T. collected field data; S.G.R., D.P.T, D.W.P., E.L.T., Z.S.L., and W.G.S. wrote the paper; S.G.R., D.P.T, D.W.P., Z.S.L., and W.G.S. developed methods; and S.G.R., D.P.T., and Z.S.L analyzed the data. Data depository: With the exception of the water balance model used to estimate annual water deficit, which is in preparation for publication, the analyses reported in this article can be reproduced using the data and R code provided by Roberts et al. (2021). LITERATURE CITED Albright , T. P. , A. M. Pidgeon, C. D. Rittenhouse, M. K. Clayton, C. 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Google Scholar Crossref Search ADS PubMed WorldCat Copyright © American Ornithological Society 2021. All rights reserved. For permissions, e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

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OrnithologyOxford University Press

Published: May 8, 2021

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