Effects of drought on the abundance and distribution of non-breeding shorebirds in central California, USA

Barbaree, Blake A.; Reiter, Matthew E.; Hickey, Catherine M.; Strum, Khara M.; Isola, Jennifer E.; Jennings, Scott; Tarjan, L. Max; Strong, Cheryl; Stenzel, Lynne E.; Shuford, W. David

doi:10.1371/journal.pone.0240931

Cited by 6 publications

(13 citation statements)

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“…Surrounding these core habitat needs, our study identified a large time frame over which additional habitat may be needed, particularly in drier years, ranging from early January through early May. Our finding of reduced habitat availability for migratory shorebirds in the Central Valley in recent years is noteworthy because it is consistent with what was predicted to result from ongoing climatic warming (Barbaree et al, 2020; Matchett & Fleskes, 2017). From 1895 to 2017, the highest annual mean air temperatures ever recorded in California occurred in the last four years (coincident with our study), with 2014 being the warmest on record, followed by 2015, 2017, and 2016 (WRCC, 2018).…”

Section: Discussionsupporting

confidence: 77%

Shorebird food energy shortfalls and the effectiveness of habitat incentive programs in record wet, dry, and warm years

Golet

Dybala

Reiter

et al. 2022

Ecological Monographs

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Programs that incentivize private landowners to create habitats that offset losses due to conversion and climate change are increasingly being used to bolster sensitive wildlife populations. In the Central Valley of California, shorebird habitat incentive programs pay landowners to create additional habitat during the non-breeding season by flooding their fields. However, it remains unclear how successful these programs have been in supporting baseline shorebird population needs or meeting established population goals, particularly in the face of changing environmental conditions. To address these questions, we used bioenergetics modeling to estimate shorebird food energy needs over four consecutive years that had the highest annual mean air temperatures ever recorded in California, and included years of extreme drought, as well as the second wettest winter on record. Our objectives were to (1) characterize annual variability in the timing and magnitude of shorebird food energy shortfalls, (2) estimate the contributions that incentive programs made to meeting these needs, and (3) develop recommendations for implementation of future habitat programs to advance shorebird conservation in the region. Overall, we found a high level of consistency in the timing and magnitude of habitat shortfalls, especially in fall, despite large differences in annual rainfall, a result that was unexpected, but that emphasizes how highly managed the hydrological system is in the Central Valley. We also found that the magnitude of both fall and spring energy shortfalls increased, relative to recent (2007-2014) estimates, perhaps due to aberrantly warm conditions. Incentive programs implemented to provide supplemental habitat were somewhat effective in reducing shortfalls for the assumed baseline population, but there were consistent unmet habitat needs when there were not enough shallow open water foraging areas available. Strategies to offset these remaining food energy deficits include scaling up habitat investments, adjusting the timing of habitat programs to better match the migration patterns of the birds, and adapting

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Section: Discussionsupporting

confidence: 77%

Shorebird food energy shortfalls and the effectiveness of habitat incentive programs in record wet, dry, and warm years

Golet

Dybala

Reiter

et al. 2022

Ecological Monographs

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“…Consistent with our results that show the best performing models used a combination of both real‐time and long‐term data, some taxa, such as whales, may respond to both historical and contemporaneous environmental conditions (Abrahms et al, 2019 ). Previous studies have demonstrated that shorebirds typically shift their distributions as a function of dynamic within‐year water availability, both in the Central Valley (Barbaree et al, 2018 , 2020 ) and elsewhere (Maclean et al, 2008 ; Steen et al, 2018 ). The tendency to visit the same site every year may simply be a function of available habitat.…”

Section: Discussionmentioning

confidence: 99%

“…We combined multiple data sets on the occurrence of five species of shorebirds (treating long‐ and short‐billed dowitchers as a single taxa), including structured data sets and complete checklists in the opportunistically collected eBird reference data set (ERD) through 2016 (Sullivan et al, 2009 ). The structured data sets (Barbaree et al, 2020 ; Golet et al, 2018 ; Reiter et al, 2011 ; Sesser et al, 2016 , 2018 ; Shuford et al, 2019 ; Strum et al, 2013 ) were largely conducted during times of year and in rice and other agricultural habitats where, given flooding, shorebirds were expected. To supplement the spatial and temporal extent of the structured data, we included eBird observations that used sampling protocols that closely matched the structured data: namely, observations collected during daylight hours and by stationary observers.…”

Section: Methodsmentioning

confidence: 99%

“…Although the structured data sets were taken by different observers for different experimental questions (Barbaree et al, 2020 , Golet et al, 2018 , Reiter et al, 2011 , Sesser et al, 2016 , 2018 , Shuford et al, 2019 , Strum et al, 2013 ), they all employed similar search and data collection protocols. Stationary observers identified all shorebirds to species and counted all individuals within a 160–200‐m fixed radius or until the intersection of levees or natural barriers, whichever was closer.…”

Section: Methodsmentioning

confidence: 99%

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Both real‐time and long‐term environmental data perform well in predicting shorebird distributions in managed habitat

Conlisk

Golet

Reynolds

et al. 2022

Ecological Applications

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Highly mobile species, such as migratory birds, respond to seasonal and interannual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species‐distribution models typically rely on long‐term average habitat conditions, mostly because large‐extent, temporally resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real‐time environmental data increases the predictive ability of distribution models, relative to using long‐term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16 days), and 17‐year long‐term average surface water data. Using abundance‐weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. Although modeling with both real‐time and long‐term average data provided good fit to withheld validation data (the area under the receiver operating characteristic curve, or AUC, averaged between 0.79 and 0.89 for all taxa), there were small differences in model performance. The best models incorporated long‐term average conditions and spatial pattern information for real‐time flooding (e.g., perimeter‐area ratio of real‐time water bodies). There was not a substantial difference in the performance of real‐time and long‐term average data models within time periods when real‐time surface water differed substantially from the long‐term average (specifically during drought years 2013–2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real‐time data may ultimately be best for guiding dynamic, adaptive conservation actions, whereas models based on long‐term averages may be more helpful for guiding permanent wetland protection and restoration.

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“…This Research Topic highlights that rainfall impacts birds in diverse ways, and Rosamond et al show that Dickcissel (Spiza americana) populations decline with increasing amounts of summer rainfall. However, drought also influences the distribution of breeding birds (Barbaree et al, 2020;Campos-Cerqueira and Aide, 2021) and particularly so in arid regions (Herremans, 2004). Bourne et al advance our understanding of adaptive responses to drought by showing that Southern Pied Babblers (Turdoides bicolor) in the Kalahari Desert in South Africa significantly reduce their reproductive effort during breeding seasons characterised by drought but subsequently increase their reproductive effort during the breeding seasons immediately following droughts.…”

Section: Impact Of Weather On Birds During Nest Building and Incubationmentioning

confidence: 99%

Editorial: The Impact of Weather on the Behavior and Ecology of Birds

2021

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Effects of drought on the abundance and distribution of non-breeding shorebirds in central California, USA

Cited by 6 publications

References 54 publications

Shorebird food energy shortfalls and the effectiveness of habitat incentive programs in record wet, dry, and warm years

Shorebird food energy shortfalls and the effectiveness of habitat incentive programs in record wet, dry, and warm years

Both real‐time and long‐term environmental data perform well in predicting shorebird distributions in managed habitat

Editorial: The Impact of Weather on the Behavior and Ecology of Birds

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