Seasonal survival of adult female mottled ducks

Abstract

The mottled duck (Anas fulgivula) is a non-migratory duck dependent on coastal habitats to meet all of its life cycle requirements in the Western Gulf Coast (WGC) of Texas and Louisiana, USA. This population of mottled ducks has experienced a moderate decline during the past 2 decades. Adult survival has been identified as an important factor influencing population demography. Previous work based on band-recovery data has provided only annual estimates of survival. We assessed seasonal patterns of female mottled duck survival from 2009 to 2012 using individuals marked with satellite platform transmitter terminals (PTTs). We used temperature and movement sensors within each PTT to indicate potential mortality events. We estimated cumulative weekly survival and ranked factors influential in patterns of mortality using known-fate modeling in Program MARK. Models included 4 predictors: week; hunting and non-hunting periods; biological periods defined as breeding, brooding, molt, and pairing; and mass at time of capture. Models containing hunt periods, during and outside the mottled duck season, comprised essentially 100% of model weights where both legal and illegal harvest had a negative influence on mottled duck survival. Survival rates were low during 2009-2011 (12-38% annual rate of survival), when compared with the long-term banding average of 53% annual survival. During 2011, survival of female mottled ducks was the lowest annual rate (12%) ever documented and coincided with extreme drought. Management actions maximizing the availability of wetlands and associated upland habitats during hunting seasons and drought conditions may increase adult female mottled duck survival. Ó

Distribution of contaminants in the environment and wildlife habitat use: a case study with lead and waterfowl on the Upper Texas Coast

“…We recorded locations and space use data from female mottled ducks from 2006-2012. Locations were collected via very-high-frequency (VHF) radio telemetry during 2006(Rigby and Haukos 2015 and via satellite telemetry during 2009-2012 (Moon et al 2017). For VHF location data collection, trapping and handling were conducted based on guidelines contained in permits from the Texas Tech University Institutional Animal Care and Use Committee (06026-06) and USFWS.…”

“…For satellite location data collection, female mottled ducks were captured via airboat by nightlighting and fitted with Platform Transmitter Terminal (PTT; 22-g Model 100, Microwave Telemetry Inc., Columbia, MD) telemetry units during August 2009-2011 under Bird Banding Laboratory permit #09072 and USFWS Animal Care and Use guidelines. This unit constituted <3% of body mass, which did not have a negative effect on survival (Moon et al 2017). Data collection began 72 h after radio-tagged birds were released and continued with locations recorded ≥2 times per week until mortality, transmitter malfunction/failure, or study termination.…”

Filling in the gaps in survival analysis: using field data to infer plant responses to environmental stressors

“…Long census intervals can obscure the importance of individual, acute events (e.g., frost exposure), as well as interactions between environmental conditions in driving mortality (Ferguson et al 2017). Many ecologists have approached this particular issue by developing methods to select variables with the most predictive power, for example, by using model selection (e.g., AIC) approaches to test how a variety of aggregate windows or lags in environmental conditions explain observed survival (Altwegg and Anderson 2009, Ehrl en et al 2016, Ferguson et al 2017, Moon et al 2017. However, disentangling the relevant relative contributions of past stress and current conditions within a model is still not straightforward (Teller et al 2016).…”

“…At the population level, survival determines species ranges (Gaston 2009), and at larger scales can influence ecosystem processes that provide vital services to humans (Anderegg et al 2015). Rates of survival depend strongly on environmental conditions (Balducci et al 2015, Moon et al 2017), yet the specific environmental drivers and relevant timescales are rarely known a priori. For most organisms, the ultimate causes of mortality at any given time are a result of both environmental conditions they experienced immediately prior to death (acute stressors) and the accumulated or lagged effects of past environmental conditions (chronic stressors; Guinet et al 1998, Thompson and Ollason 2001, Betini et al 2014).…”

“…However, disentangling the relevant relative contributions of past stress and current conditions within a model is still not straightforward (Teller et al 2016). Many ecologists have approached this particular issue by developing methods to select variables with the most predictive power, for example, by using model selection (e.g., AIC) approaches to test how a variety of aggregate windows or lags in environmental conditions explain observed survival (Altwegg and Anderson 2009, Ehrl en et al 2016, Ferguson et al 2017, Moon et al 2017. However, these approaches introduce further challenges.…”