9 research outputs found
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Linking shorebird and marsh bird habitat use to water management in anthropogenic and natural wetlands in the Colorado River Delta
I estimated patterns of shorebird abundance and species diversity in the Colorado River Delta and Upper Gulf of California wetlands in order to determine the relative contribution of intertidal wetlands and non-tidal anthropogenic wetlands to support shorebird habitat use. Species richness varied from 15 to 26 species among sites and 29 species were detected across sites. Density during the peak migration month was higher at the anthropogenic wetland Cienega de Santa Clara (mean = 168 ind/ha, 95% C.I. 29-367), and the intertidal Golfo de Santa Clara (mean = 153 ind/ha, 95% C.I. 17-323). Anthropogenic wetlands (playa and lagoons) supported high abundance of shorebirds along with intertidal wetlands in the Colorado River Delta (mudflats). In contrast, intertidal wetlands farther south on the Sonoran Coast presented lower abundance but higher diversity of shorebird, likely as a result of the higher diversity of habitats (rocky shore, sandy beach, estuary). I modeled water management scenarios for the Cienega in order to determine the response of the dominant vegetation (southern cattail, Typha domingensis Pers.) and the area of the outflow pool below the marsh to different scenarios of water management. The model indicates that if the inflow rate is reduced below the current 4-5 m³s⁻¹ the vegetated area of the Cienega that supports habitat for marsh birds would decrease in proportion, as would the area of the outflow pool in the Santa Clara Slough identified previously as shorebird habitat. Increases in salinity will also reduce the vegetated area due to the low salt tolerance of T. domingensis. In winter about 90% of inflow water exits the Cienega into the Santa Clara Slough due to low evapotranspiration contributing to inundate areas that are used by wintering and migrating shorebirds. Lastly, I explored the feasibility of using Vegetation Indices (NDVI and EVI) to model Yuma Clapper Rail detections in the Cienega de Santa Clara as well as the effects of adding other habitat variables and the presence of fire events in the performance of linear models based on NDVI. Both NDVI and EVI were positively related to the Yuma Clapper Rail detections. The relationship was weak to moderate, but significant (P<0.001), which suggests other factors besides the vegetation condition play an important role in the bird distribution pattern. A model including all the variability among years was a better predictor of the rails detected per transect, than models for fire and non-fire years. We did not find a significant effect from adding habitat features (water % or vegetation %), and we recommend to include variables at both microhabitat level and landscape level, relevant before and during the breeding season in order to increase the explanatory power of models
Improving the efficiency and accuracy of evaluating aridland riparian habitat restoration using unmanned aerial vehicles
Unmanned Aerial Vehicles (UAVs) offer new opportunities for accurate, repeatable vegetation assessments, which are needed to adaptively manage restored habitat. We used UAVs, ground surveys, and satellite imagery to evaluate vegetation metrics for three riparian restoration sites along the Colorado River in Mexico and we compared the data accuracy and efficiency (cost and time requirements) between the three methods. We used an off-the-shelf UAV coupled with a multispectral sensor to determine Normalized Difference Vegetation Index (NDVI) and vegetation cover. We were unable to accurately classify vegetation by individual species, but by grouping riparian species of interest (cottonwood-willow, mesquite, shrubs), we achieved high overall model accuracies of 87–96% across sites (Kappa = 0.82–0.95). Producer’s and user’s accuracies were moderate to high for target vegetation classes (69–100%). UAV and ground-survey vegetation percent cover differed due to differences in methodologies (UAVs measure aerial cover; ground surveys measure foliar cover) and sources of error for each method. Correlations between UAV and ground survey vegetation cover were moderate (rs(90) = 0.24–0.58, p < 0.05). UAV NDVI (0.50–0.61) was significantly higher than Landsat NDVI (0.40–0.45) for all sites (p < 0.0001), likely due to presence of shadows with high NDVI values in UAV imagery. UAV NDVI, Landsat NDVI and UAV total vegetation cover were strongly correlated (rs(90) = 0.72–0.85, p < 0.05). UAV surveys were more labor- and cost- intensive than ground surveys in the first year, but were slightly less so in the second year. We conclude that UAVs can provide efficient, accurate assessments of riparian vegetation, which can be used in restoration site management. Due to UAV limitations to assess vegetation in a multi-layered canopy and inability to classify individual riparian species with similar spectral signals, we recommend a combined approach of UAV and ground surveys.Our Enterprise Rent-A-Car FoundationOpen access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
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Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics
Understanding the effectiveness of environmental flow deliveries along rivers requires monitoring vegetation. Monitoring data are often collected at multiple spatial scales. For riparian vegetation, optical remote sensing methods can estimate growth responses at the riparian corridor scale, and field-based measures can quantify species composition; however, the extent to which these different measures are duplicative or complementary is important to understand when planning monitoring programmes with limited resources. In this study, we analysed riparian vegetation growth in the delta of the Colorado River in response to an experimental pulse flow. Our goal was to compare ground-based measurements of vegetation structure and composition with satellite-based Landsat radiometric variables, such as the normalized difference vegetation index (NDVI). We made this comparison in 21 transects following the delivery of 131.8 million cubic meters (mcm) of water in the stream channel during the spring of 2014 as a pulse flow and 38.4 mcm as base flows. Vegetation cover increased 14% and NDVI increased 0.02 (15%) by October 2015, and both variables returned to pre-pulse flow values in October 2016. Observed changes in vegetation structure and composition did not persist after the second year. The highest increase in vegetation cover in October 2014 and October 2015 resulted from species that could respond rapidly to additional water such as reeds (Arundo donax and Phragmites australis), cattail (Typha domingensis), and herbaceous plants. Dominant shrubs, saltcedar (Tamarix spp.) and arrowweed (Pluchea sericea), both indicative of nonrestored habitats showed variable increases in cover, and native trees (Salicaceae family) presented low increases (1%). The strong NDVI-vegetation cover relationship indicates that NDVI is appropriate to detect changes at the riparian corridor scale but needs to be complemented with ground data to determine the contributions by different species to the observed trends.U.S. Geological SurveyPublic domain articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]