Geology topics

Miguel L. Villarreal

Publications and source records attributed to Miguel L. Villarreal.

At least 55 records · Page 3Linked to original sources

USGS2018

Evaluating and monitoring forest fuel treatments using remote sensing applications in Arizona, U.S.A.

The practice of fire suppression across the western United States over the past century has led to dense forests, and when coupled with drought has contributed to an increase in large and destructive wildfires. Forest management efforts aimed at reducing flammable fuels through various fuel treatments can help to restore frequent fire regimes and increase forest resilience. Our research examines how different fuel treatments influenced burn severity and post-fire vegetative stand dynamics on the San Carlos Apache Reservation, in east-central Arizona, U.S.A. Our methods included the use of multitemporal remote sensing data and cloud computing to evaluate burn severity and post-fire vegetation conditions as well as statistical analyses. We investigated how forest thinning, commercial harvesting, prescribed burning, and resource benefit burning (managed wildfire) related to satellite measured burn severity (the difference Normalized Burn Ratio – dNBR) following the 2013 Creek Fire and used spectral measures of post-fire stand dynamics to track changes in land surface characteristics (i.e., brightness, greenness and wetness). We found strong negative relationships between dNBR and post-fire greenness and wetness, and a positive non-linear relationship between dNBR and brightness, with greater variability at higher severities. Fire severity and post-fire surface changes also differed by treatment type. Our results showed harvested and thinned sites that were not treated with prescribed fire had the highest severity fire. When harvesting was followed by a prescribed burn, the sites experienced lower burn severity and reduced post-fire changes in vegetation greenness and wetness. Areas that had previously experienced resource benefit burns had the lowest burn severities and the highest post-fire greenness measurements compared to all other treatments, except for where the prescribed burn had occurred. These results suggest that fire treatments may be most effective at reducing the probability of hazardous fire and increasing post-fire recovery. This research demonstrates the utility of remote sensing and spatial data t o inform forest management, and how various fuel treatments can influence burn severity and post-fire vegetation response within ponderosa pine forests across the southwestern U.S.

Arizona↗

USGS2018

Landsat time series analysis of fractional plant cover changes on abandoned energy development sites

Oil and natural gas development in the western United States has increased substantially in recent decades as technological advances like horizontal drilling and hydraulic fracturing have made extraction more commercially viable. Oil and gas pads are often developed for production, and then capped, reclaimed, and left to recover when no longer productive. Understanding the rates, controls, and degree of recovery of these reclaimed well sites to a state similar to pre-development conditions is critical for energy development and land management decision processes. Here we use a multi-decadal time series of satellite imagery (Landsat 5, 1984–2011) to assess vegetation regrowth on 365 abandoned well pads located across the Colorado Plateau in Utah, Colorado, and New Mexico. We developed high-frequency time series of the Soil-Adjusted Total Vegetation Index (SATVI) for each well pad using the Google Earth Engine cloud computing platform. BFAST time-series models were used to fit temporal trends, identifying when vegetation was cleared from the site and the magnitudes and rates of vegetation change after abandonment. The time series metrics are used to calculate the relative fractional vegetation cover (RFVC) of each pad, a measure of post-abandonment vegetation cover relative to pre-drilling condition. Mean and median RFVC were 36% (s.d. 33%) and 26%, respectively, five years after abandonment, with one third of well pads having RFVC greater than 50%. Statistical analyses suggest that much of the high vegetation cover is associated with weedy invasive annual species such as cheatgrass (Bromus tectorum) and Russian thistle (Salsola spp.). Climate conditions and the year of abandonment also play a role, with increased cover in later years associated with a wetter period. Non-linear change at many pads suggests longer recovery times than would be estimated by linear extrapolation. New techniques implemented here address a complex response of cover change to soils, management, and climate over time, and can be extended to the operational monitoring of energy development across large areas.

International Journal of Applied Earth Observation↗

USGS2018

Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands

Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.

Colorado Plateau↗

USGS2017

Evaluating land-use change scenarios for the Puget Sound Basin, Washington, within the ecosystem recovery target model-based framework

The Puget Sound Basin, Washington, has experienced rapid urban growth in recent decades, with varying impacts to local ecosystems and natural resources. To plan for future growth, land managers often use scenarios to assess how the pattern and volume of growth may affect natural resources. Using three different land-management scenarios for the years 2000–2060, we assessed various spatial patterns of urban growth relative to maps depicting a model-based characterization of the ecological integrity and recent development pressure of individual land parcels. The three scenarios depict future trajectories of land-use change under alternative management strategies—status quo, managed growth, and unconstrained growth. The resulting analysis offers a preliminary assessment of how future growth patterns in the Puget Sound Basin may impact land targeted for conservation and how short-term metrics of land-development pressure compare to longer term growth projections.

Washington↗

USGS2017

Historical analysis of riparian vegetation change in response to shifting management objectives on the Middle Rio Grande

Riparian ecosystems are valuable to the ecological and human communities that depend on them. Over the past century, they have been subject to shifting management practices to maximize human use and ecosystem services, creating a complex relationship between water policy, management, and the natural ecosystem. This has necessitated research on the spatial and temporal dynamics of riparian vegetation change. The San Acacia Reach of the Middle Rio Grande has experienced multiple management and river flow fluctuations, resulting in threats to its riparian and aquatic ecosystems. This research uses remote sensing data, GIS, a review of management decisions, and an assessment of climate to both quantify how riparian vegetation has been altered over time and provide interpretations of the relationships between riparian change and shifting climate and management objectives. This research focused on four management phases from 1935 to 2014, each highlighting different management practices and climate-driven river patterns, providing unique opportunities to observe a direct relationship between river management, climate, and riparian response. Overall, we believe that management practices coupled with reduced surface river-flows with limited overbank flooding influenced the compositional and spatial patterns of vegetation, including possibly increasing non-native vegetation coverage. However, recent restoration efforts have begun to reduce non-native vegetation coverage.

New Mexico↗

USGS2017

Climate legacy and lag effects on dryland plant communities in the southwestern U.S.

Climate change effects on vegetation will likely be strong in the southwestern U.S., which is projected to experience large increases in temperature and changes in precipitation. Plant communities in the southwestern U.S. may be particularly vulnerable to climate change as the productivity of many plant species is strongly water-limited. This study examines the relationship between climate and vegetation condition using a time-series of Landsat imagery across grassland, shrubland, and woodland communities on the Colorado Plateau, USA. We improve on poorly understood inter-annual climate-vegetation relationships by exploring how the responses of different plant communities depend on climate legacies (>12 months) and lag behind shorter-term (3–12 month) changes in water availability. Our results show a prolonged drying trend on the Colorado Plateau since the early 1990s that was punctuated in several years by intense droughts. In areas that experienced sustained dry conditions or a drying trend, vegetation greenness (a proxy for production) increased linearly when conditions were interrupted by wetting events. In contrast, in areas that experienced sustained wet conditions or a wetting trend, vegetation greenness was weakly or not related to wetting events, indicating that production may saturate if vegetation experiences sufficient water availability. Shrubland and woodland communities had stronger relationships with climate at long lags (6–12 months) and many maintained greenness under sustained water deficit, whereas grassland communities had stronger relationships at short lags (3–6 months) and lost greenness even in periods of short-term drought. The results of our study show the importance of identifying climate legacies and lags when assessing indicators of ecological drought, which can be used to improve forecasts of which plant communities will be vulnerable under future climate change.

Colorado Plateau↗

USGS2017

Disturbance automated reference toolset (DART): Assessing patterns in ecological recovery from energy development on the Colorado Plateau

A new disturbance automated reference toolset (DART) was developed to monitor human land surface impacts using soil-type and ecological context. DART identifies reference areas with similar soils, topography, and geology; and compares the disturbance condition to the reference area condition using a quantile-based approach based on a satellite vegetation index. DART was able to represent 26–55% of variation of relative differences in bare ground and 26–41% of variation in total foliar cover when comparing sites with nearby ecological reference areas using the Soil Adjusted Total Vegetation Index (SATVI). Assessment of ecological recovery at oil and gas pads on the Colorado Plateau with DART revealed that more than half of well-pads were below the 25th percentile of reference areas. Machine learning trend analysis of poorly recovering well-pads (quantile < 0.23) had out-of-bag error rates between 37 and 40% indicating moderate association with environmental and management variables hypothesized to influence recovery. Well-pads in grasslands (median quantile [MQ] = 13%), blackbrush ( Coleogyne ramosissima ) shrublands (MQ = 18%), arid canyon complexes (MQ = 18%), warmer areas with more summer-dominated precipitation, and state administered areas (MQ = 12%) had low recovery rates. Results showcase the usefulness of DART for assessing discrete surface land disturbances, and highlight the need for more targeted rehabilitation efforts at oil and gas well-pads in the arid southwest US.

Colorado Plateau↗

USGS2016

Decadal shifts in grass and woody plant cover are driven by prolonged drying and modified by topo‐edaphic properties

Woody plant encroachment and overall declines in perennial vegetation in dryland regions can alter ecosystem properties and indicate land degradation, but the causes of these shifts remain controversial. Determining how changes in the abundance and distribution of grass and woody plants are influenced by conditions that regulate water availability at a regional scale provides a baseline to compare how management actions alter the composition of these vegetation types at a more local scale and can be used to predict future shifts under climate change. Using a remote‐sensing‐based approach, we assessed the balance between grasses and woody plants and how climate and topo‐edaphic conditions affected their abundances across the northern Sonoran Desert from 1989 to 2009. Despite widespread woody plant encroachment in this region over the last 150 years, we found that leguminous trees, including mesquite ( Prosopis spp.), declined in cover in areas with prolonged drying conditions during the early 21st century. Creosote bush ( Larrea tridentata ) also had moderate decreases with prolonged drying but was buffered from changes on soils with low clay that promote infiltration and high available water capacity that allows for retention of water at depth. Perennial grasses have expanded and contracted over the last two decades in response to summer precipitation and were especially dynamic on shallow soils with high clay that have large fluctuations in water availability. Our results suggest that topo‐edaphic properties can amplify or ameliorate climate‐induced changes in woody plants and perennial grasses. Understanding these relationships has important implications for ecosystem function under climate change in the southwestern USA and can inform management efforts to regulate grass and woody plant abundances.

Arizona↗

USGS2016

Comparison of remote sensing indices for monitoring of desert cienegas

This research considers the applicability of different vegetation indices at 30 m resolution for mapping and monitoring desert wetland (cienega) health and spatial extent through time at Cienega Creek in southeastern Arizona, USA. Multiple stressors including the risk of decadal-scale drought, the effects of current and predicted global warming, and continued anthropogenic pressures threaten aquatic habitats in the southwest and cienegas are recognized as important sites for conservation and restoration efforts. However, cienegas present a challenge to satellite-imagery based analysis due to their small size and mixed surface cover of open water, exposed soils, and vegetation. We created time series of five well-known vegetation indices using annual Landsat Thematic Mapper (TM) images retrieved during the April–June dry season, from 1984 to 2011 to map landscape-level distribution of wetlands and monitor the temporal dynamics of individual sites. Indices included the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Infrared Index (NDII). One topographic index, the Topographic Wetness Index (TWI), was analyzed to examine the utility of topography in mapping distribution of cienegas. Our results indicate that the NDII, calculated using Landsat TM band 5, outperforms the other indices at differentiating cienegas from riparian and upland sites, and was the best means to analyze change. As such, it offers a critical baseline for future studies that seek to extend the analysis of cienegas to other regions and time scales, and has broader applicability to the remote sensing of wetland features in arid landscapes.

Arizona↗

USGS2016

Continuous 1985-2012 Landsat monitoring to assess fire effects on meadows in Yosemite National Park, California

To assess how montane meadow vegetation recovered after a wildfire that occurred in Yosemite National Park, CA in 1996, Google Earth Engine image processing was applied to leverage the entire Landsat Thematic Mapper archive from 1985 to 2012. Vegetation greenness (normalized difference vegetation index [NDVI]) was summarized every 16 days across the 28-year Landsat time series for 26 meadows. Disturbance event detection was hindered by the subtle influence of low-severity fire on meadow vegetation. A hard break (August 1996) was identified corresponding to the Ackerson Fire, and monthly composites were used to compare NDVI values and NDVI trends within burned and unburned meadows before, immediately after, and continuously for more than a decade following the fire date. Results indicate that NDVI values were significantly lower at 95% confidence level for burned meadows following the fire date, yet not significantly lower at 95% confidence level in the unburned meadows. Burned meadows continued to exhibit lower monthly NDVI in the dormant season through 2012. Over the entire monitoring period, the negative-trending, dormant season NDVI slopes in the burned meadows were also significantly lower than unburned meadows at 90% confidence level. Lower than average NDVI values and slopes in the dormant season compared to unburned meadows, coupled with photographic evidence, strongly suggest that evergreen vegetation was removed from the periphery of some meadows after the fire. These analyses provide insight into how satellite imagery can be used to monitor low-severity fire effects on meadow vegetation.

California↗

USGS2016

Multi-index time series monitoring of drought and fire effects on desert grasslands

The Western United States is expected to undergo both extended periods of drought and longer wildfire seasons under forecasted global climate change and it is important to understand how these disturbances will interact and affect recovery and composition of plant communities in the future. In this research paper we describe the temporal response of grassland communities to drought and fire in southern Arizona, where land managers are using repeated, prescribed fire as a habitat restoration tool. Using a 25-year atlas of fire locations, we paired sites with multiple fires to unburned control areas and compare satellite and field-based estimates of vegetation cover over time. Two hundred and fifty Landsat TM images, dating from 1985–2011, were used to derive estimates of Total Vegetation Fractional Cover (TVFC) of live and senescent grass using the Soil-Adjusted Total Vegetation Index (SATVI) and post-fire vegetation greenness using the Normalized Difference Vegetation Index (NDVI). We also implemented a Greenness to Cover Index that is the difference of time-standardized SATVI-TVFC and NDVI values at a given time and location to identify post-fire shifts in native, non-native, and annual plant cover. The results highlight anomalous greening and browning during drought periods related to amounts of annual and non-native plant cover present. Results suggest that aggressive application of prescribed fire may encourage spread of non-native perennial grasses and annual plants, particularly during droughts.

Remote Sensing of Environment↗

USGS2014

Modelling landscape-scale erosion potential related to vehicle disturbances along the U.S.-Mexico border

Decades of intensive off-road vehicle use for border security, immigration, smuggling, recreation, and military training along the USA–Mexico border have prompted concerns about long-term human impacts on sensitive desert ecosystems. To help managers identify areas susceptible to soil erosion from anthropogenic activities, we developed a series of erosion potential models based on factors from the Universal Soil Loss Equation (USLE). To better express the vulnerability of soils to human disturbances, we refined two factors whose categorical and spatial representations limit the application of the USLE for non-agricultural landscapes: the C -factor (vegetation cover) and the P -factor (support practice/management). A soil compaction index ( P -factor) was calculated as the difference in saturated hydrologic conductivity ( K s ) between disturbed and undisturbed soils, which was then scaled up to maps of vehicle disturbances digitized from aerial photography. The C -factor was improved using a satellite-based vegetation index, which was better correlated with estimated ground cover ( r 2  = 0·77) than data derived from land cover ( r 2  = 0·06). We identified 9,780 km of unauthorized off-road tracks in the 2,800-km 2 study area. Maps of these disturbances, when integrated with soil compaction data using the USLE, provided landscape-scale information on areas vulnerable to erosion from both natural processes and human activities and are detailed enough for adaptive management and restoration planning. The models revealed erosion potential hotspots adjacent to the border and within areas managed as critical habitat for the threatened flat-tailed horned lizard and endangered Sonoran pronghorn.

Land Degradation and Development↗

USGS2014

Remote sensing analysis of riparian vegetation response to desert marsh restoration in the Mexican Highlands

Desert marshes, or cienegas, are extremely biodiverse habitats imperiled by anthropogenic demands for water and changing climates. Given their widespread loss and increased recognition, remarkably little is known about restoration techniques. In this study, we examine the effects of gabions (wire baskets filled with rocks used as dams) on vegetation in the Cienega San Bernardino, in the Arizona, Sonora portion of the US-Mexico border, using a remote-sensing analysis coupled with field data. The Normalized Difference Vegetation Index (NDVI), used here as a proxy for plant biomass, is compared at gabion and control sites over a 27-year period during the driest months (May/June). Over this period, green-up occurred at most sites where there were gabions and at a few of the control sites where gabions had not been constructed. When we statistically controlled for differences among sites in source area, stream order, elevation, and interannual winter rainfall, as well as comparisons of before and after the initiation of gabion construction, vegetation increased around gabions yet did not change (or decreased) where there were no gabions. We found that NDVI does not vary with precipitation inputs prior to construction of gabions but demonstrates a strong response to precipitation after the gabions are built. Field data describing plant cover, species richness, and species composition document increases from 2000 to 2012 and corroborate reestablished biomass at gabions. Our findings validate that gabions can be used to restore riparian vegetation and potentially ameliorate drought conditions in a desert cienega.

Ecological Engineering↗

USGS2013

Influence of monsoon-related riparian phenology on yellow-billed cuckoo habitat selection in Arizona

Aim: The western yellow-billed cuckoo (Coccyzus americanus occidentalis), a Neotropical migrant bird, is facing steep population declines in its western breeding grounds owing primarily to loss of native habitat. The favoured esting habitat for the cuckoo in the south-western United States is low-elevation riparian forests and woodlands. Our aim was to explore relationships between vegetation phenology patterns captured by satellite phenometrics and the distribution of the yellow-billed cuckoo, and to use this information to map cuckoo habitat. Location: Arizona, USA. Methods: Land surface phenometrics were derived from satellite Advanced Very High-Resolution Radiometer (AVHRR), bi-weekly time-composite, ormalized difference vegetation index (NDVI) data for 1998 and 1999 at a resolution of 1 km. Fourier harmonics were used to analyse the waveform of the annual NDVI profile in each pixel. To create the models, we coupled 1998 satellite phenometrics with 1998 field survey data of cuckoo presence or absence and with point data that sampled riparian and cottonwood–willow vegetation types. Our models were verified and refined using field and satellite data collected in 1999. Results: The models reveal that cuckoos prefer areas that experience peak greenness 29 days later, are 36% more dynamic and slightly (< 1%) more productive than their average cottonwood–willow habitat. The results support a scenario in which cuckoos migrate northwards, following the greening of riparian corridors and surrounding landscapes in response to monsoon precipitation, but then select a nesting site based on optimizing the near-term foraging potential of the neighbourhood. Main conclusions: The identification of preferred phenotypes within recognized habitat can be used to refine future habitat models, inform habitat response to climate change, and suggest adaptation strategies. For example, models of phenotype preferences can guide management actions by identifying and prioritizing for conservation those landscapes that reliably exhibit highly preferred phenometrics on a consistent basis.

Arizona↗

USGS2013

Framing scenarios of binational water policy with a tool to visualize, quantify and valuate changes in ecosystem services

In the Santa Cruz Watershed, located on the Arizona-Sonora portion of the U.S.-Mexico border, an international wastewater treatment plant treats wastewater from cities on both sides of the border, before discharging it into the river in Arizona. These artificial flows often subsidize important perennial surface water ecosystems in the region. An explicit understanding of the benefits of maintaining instream flow for present and future generations requires the ability to assess and understand the important trade-offs implicit in water-resource management decisions. In this paper, we outline an approach for modeling and visualizing impacts of management decisions in terms of rare terrestrial and aquatic wildlife, vegetation, surface water, groundwater recharge, real-estate values and socio-environmental vulnerable communities. We identify and quantify ecosystem services and model the potential reduction in effluent discharge to the U.S. that is under scrutiny by binational water policy makers and of concern to stakeholders. Results of service provisioning are presented, and implications for policy makers and resource managers are discussed. This paper presents a robust ecosystem services assessment of multiple scenarios of watershed management as a means to discern eco-hydrological responses and consider their potential values for future generations living in the borderlands.

Arizona;Sonora↗

USGS2013

Historical and contemporary geographic data reveal complex spatial and temporal responses of vegetation to climate and land stewardship

Vegetation and land-cover changes are not always directional but follow complex trajectories over space and time, driven by changing anthropogenic and abiotic conditions. We present a multi-observational approach to land-change analysis that addresses the complex geographic and temporal variability of vegetation changes related to climate and land use. Using land-ownership data as a proxy for land-use practices, multitemporal land-cover maps, and repeat photography dating to the late 19th century, we examine changing spatial and temporal distributions of two vegetation types with high conservation value in the southwestern United States: grasslands and riparian vegetation. In contrast to many reported vegetation changes, notably shrub encroachment in desert grasslands, we found an overall increase in grassland area and decline of xeroriparian and riparian vegetation. These observed change patterns were neither temporally directional nor spatially uniform over the landscape. Historical data suggest that long-term vegetation changes coincide with broad climate fluctuations while fine-scale patterns are determined by land-management practices. In some cases, restoration and active management appear to weaken the effects of climate on vegetation; therefore, if land managers in this region act in accord with on-going directional changes, the current drought and associated ecological reorganization may provide an opportunity to achieve desired restoration endpoints.

Land↗

USGS2013

Biodiversity losses and conservation trade-offs: Assessing future urban growth scenarios for a North American trade corridor

The Sonoran Desert and Apache Highlands ecoregions of North America are areas of exceptionally high plant and vertebrate biodiversity. However, much of the vertebrate biodiversity is supported by only a few vegetation types with limited distributions, some of which are increasingly threatened by changing land uses. We assessed the impacts of two future urban growth scenarios on biodiversity in a binational watershed in Arizona, USA and Sonora, Mexico. We quantified and mapped terrestrial vertebrate species richness using Wildlife Habitat Relation models and validated the results with data from National Park Service biological inventories. Future urban growth, based on historical trends, was projected to the year 2050 for 1) a “Current Trends” scenario and, 2) a “Megalopolis” scenario that represented a transnational growth corridor with open-space conservation attributes. Based on Current Trends, 45% of existing riparian woodland (267 of 451species), and 34% of semi-desert grasslands (215 of 451 species) will be lost, whereas, in the Megalopolis scenario, these types would decline by 44% and 24% respectively. Outcomes of the two models suggest a trade-off at the taxonomic class level: Current Trends would reduce and fragment mammal and herpetofauna habitat, while Megalopolis would result in loss of avian-rich riparian habitat.

International Journal of Biodiversity Science, Eco↗

USGS2013

Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA

Riparian vegetation provides important wildlife habitat in the Southwestern United States, but limited distributions and spatial complexity often leads to inaccurate representation in maps used to guide conservation. We test the use of data conflation and aggregation on multiple vegetation/land-cover maps to improve the accuracy of habitat models for the threatened western yellow-billed cuckoo (Coccyzus americanus occidentalis). We used species observations (n = 479) from a state-wide survey to develop habitat models from 1) three vegetation/land-cover maps produced at different geographic scales ranging from state to national, and 2) new aggregate maps defined by the spatial agreement of cover types, which were defined as high (agreement = all data sets), moderate (agreement ≥ 2), and low (no agreement required). Model accuracies, predicted habitat locations, and total area of predicted habitat varied considerably, illustrating the effects of input data quality on habitat predictions and resulting potential impacts on conservation planning. Habitat models based on aggregated and conflated data were more accurate and had higher model sensitivity than original vegetation/land-cover, but this accuracy came at the cost of reduced geographic extent of predicted habitat. Using the highest performing models, we assessed cuckoo habitat preference and distribution in Arizona and found that major watersheds containing high-probably habitat are fragmented by a wide swath of low-probability habitat. Focus on riparian restoration in these areas could provide more breeding habitat for the threatened cuckoo, offset potential future habitat losses in adjacent watershed, and increase regional connectivity for other threatened vertebrates that also use riparian corridors.

Arizona↗