Shorebird response to spatiotemporal variability in non-tidal wetlands in the Sacramento Valley
Over 50% of Western Hemisphere shorebird species are in decline due to ongoing habitat loss and degradation. Many shorebird species require flooded habitat to rest and feed during migratory movements spanning thousands of miles between breeding and wintering grounds every spring and fall. In particular, shorebirds require shallowly flooded habitat (water depth <15cm deep)—due to their morphology (i.e., bill and tarsus length), many species are excluded from exploiting invertebrate prey resources in deeper waters. While habitat-associations for shorebirds are relatively well understood from observational studies, the distribution of suitable shorebird habitat over the broad areas used by these species during migration is not well described. In some regions of high wetland loss, shorebirds are heavily reliant on a core network of remaining human-managed wetlands and flood-irrigated agricultural fields. Refuges also provide substantial flooded habitat resources; however, these have typically been designed and managed to match the habitat needs of waterfowl, which can use much deeper water than shorebirds. Effective conservation strategies for migratory shorebirds will require improved understanding of flooded habitat suitability patterns over large migratory pathways, as well as knowledge of how species respond to habitat fluctuations over time.
We analyzed water extent dynamics across the Sacramento Valley of California, a globally important shorebird stopover site, for a 1983-2015 Landsat time series, and evaluated the effect of climate on water extent. Satellite measurements of surface water offer promise for understanding wetland habitat availability at broad spatial and temporal scales. A range of methods can detect open water from imagery, including supervised classification approaches and thresholds for spectral bands and indices. Thresholds provide a time advantage; however, there is no universally superior index, nor single best threshold for all instances. We used random forest to model the presence or absence of water from >6,200 reference pixels, and derived an optimal water probability threshold for our study area using receiver operating characteristic curves. An optimized mid-infrared (1.5–1.7 µm) threshold identified open water in the Sacramento Valley of California at 30-m resolution with an average of 90% producer’s accuracy, comparable to approaches that require more intensive user input. SLC-off Landsat 7 imagery was integrated by applying a customized interpolation that mapped water in missing data gaps with 99% user’s accuracy. On average we detected open water on ~26,000 ha (~3% of the study area) in early April at the peak of shorebird migration, while water extent increased five-fold after the migration rush. Over the last three decades, late March water extent declined by ~1,300 ha per year, primarily due to changes in the extent and timing of agricultural flood-irrigation. Water within shorebird habitats was significantly associated with an index of water availability at the peak of migration. Our approach can be used to optimize thresholds for time series analysis and near-real-time mapping in other regions, and requires only marginally more time than generating a confusion matrix.
Two dimensional representations of flooded habitat are insufficient to capture dynamic changes within the narrow water depth range that is effectively accessible to migratory shorebirds. We developed a method to quantify shallow water habitat distributions in inland non-tidal wetlands, and assessed how water management practices have affected the amount of shorebird habitat in Sacramento National Wildlife Refuge Complex (SNWRC), California. We produced water depth distributions and modeled optimal habitat (<10 cm deep) within 23 managed wetlands using high-resolution topography and fixed-point water depth records. We also demonstrated that habitat availability, specifically suitable water depth ranges, can be tracked from satellite imagery and high-resolution topography. We found that wetlands with lower topographic roughness may have a higher potential to provide shorebird habitat and that strategically reducing water levels could increase habitat extent. Over 50% of the wetlands measured provided optimal habitat across <10% of their area at the peak of migration in early April, and most provided a brief duration of shallow water habitat. Reducing water volumes could increase the proportion of optimal habitat by 1– 1,678% (mean = 294 %) compared to actual volumes measured at peak spring migration in 2016. For wetlands with a high habitat potential, beginning wetland drawdown earlier and extending drawdown time could dramatically improve habitat conditions at the peak of shorebird migration. Our approach can be adapted to track dynamic hydrologic changes at broader spatial scales as additional high-resolution topographic (e.g., lidar, drone imagery photogrammetry) and optical remote sensing data (e.g., Planet imagery, drone photography) become available.
Attempting to model the response of a community of shorebird species to flooded habitat dynamics from local to landscape scale necessitates a rich dataset including field observations of shorebird habitat use as well as information regarding regional habitat conditions over multiple time periods. Bringing together these data sources results in several challenges for classical statistical approaches, including overdispersion, fixed and random effects due to repeated measures, irregular temporal intervals, and missing data. We investigated how spring migration habitat use by 19 shorebird species at 327 wetland survey locations across SNWRC responded to flooded habitat fluctuations at multiple spatial scales from 1997-2015 using a generalized joint attribute modelling approach. In this analysis, we integrated shorebird census records and habitat conditions documented in the field with a suite of landscape-level habitat measurements derived from satellite imagery, as well as water availability, water allocation and land use information. We found that abundance by species peaked in late March and early April at SNWRC. Shorebird abundance responded positively to the amount of flooded habitat at a given wetland survey location. The total amount of water detected was the most important landscape habitat measure; shorebirds were less likely to be observed at high abundance at SNWRC wetlands when greater flooded habitat extent was present on the surrounding landscape. We found that human land and water management were influential drivers of shorebird habitat use. Water allocation information and reservoir storage resulted in better model fit (i.e., lower DIC) than including measures of surface water availability or drought conditions. Furthermore, the amount of landscape flooded habitat on agricultural land produced a better fit than considering all flooded habitat, or flooded habitat detected in wetlands. We found that the most relevant scale for measuring landscape flooded habitat was within 2-10 km of wetland survey locations; this distance could be a useful guideline for monitoring habitat conditions and targeting creation of supplemental habitat to bolster the existing wetland network in the Sacramento Valley.
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Rights for Collection: Duke Dissertations
Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info