| Summary: | As the earth's climate rapidly changes, it remains unclear how populations will respond to novel systems and anthropogenic inputs to said systems. The development of new applied conservation tools will be critical to the implementation of solutions to novel problems. My dissertation focuses on developing and implementing novel quantitative models to directly estimate demographic parameters, and inform our understanding of ecological and evolutionary processes. I use a 29-year (1986–2014) dataset on black brant geese (Branta bernicla nigricans, hereafter brant) collected on the Yukon-Kuskokwim River Delta in western Alaska. In Chapter 2 (Riecke et al., 2018), I use simulated and real data to develop a novel fully conditional robust design likelihood which we implement in a Bayesian framework. I test my novel likelihood using simulated data, demonstrating its efficacy, and then use this model structure to examine the effects of environmental conditions during growth on future lifetime fitness in brant. My results clearly indicate that more structurally developed goslings experienced increased breeding probability as an adult (β = 0.14; f = 0.94) with no effect on adult survival (β = 0.01; f = 0.62). I also provide evidence for long-term declines in apparent survival of breeding adult females (β = −0.01; f = 0.90). Thus, long-term declines in gosling growth rates (Lohman et al., 2019) may lead to reduced future reproductive potential at the population level. Further, temporal variation in gosling growth rates may lead to substantial differences in reproductive potential among cohorts. In my third chapter (Riecke et al., 2019a), I use simulated data to test the impacts of the inverse Wishart prior for the covariance matrix of a multivariate normal distribution, and propose a novel alternative distribution. My simulations and analyses demonstrate the inverse Wishart prior distribution substantially affects estimates of covariances and variances of demographic parameters, and that our proposed alternative distribution is substantially more effective than the conjugate inverse Wishart prior. My simulations also reveal that substantial long-term data is required to estimate correlations regardless of the prior distribution chosen by demographers, where many previous studies have failed to meet these minimal thresholds. I then use our novel variance-covariance parameterization to estimate the correlation between survival of adult and juvenile female brant, where shared environmental conditions lead to a strong positive correlation between these parameters (ρ = 0.563; 95% CRI 0.181–0.823). Given the potential for continued long-term habitat degradation in non- breeding areas and rapidly declining juvenile survival, our research provides strong evidence for the importance of maintaining critical migratory stopover, staging, and wintering areas. In Chapter 4, I examine the impacts of long-term habitat degradation and climatic oscillations on adult phenotype in black brant. Specifically, we examine long-term changes in tarsus length of adult female brant, where mean female tarsus of each cohort declined by 7.73 mm from 1986–2013. I then show that gosling growth rates have declined substantially (κ1 = −0.108 day) over the same time period, explaining substantial variation in adult body size (R2 = 0.209; 85% CRI = 0.043– 0.418). I also used the methods developed in Chapter 2 to examine long-term changes in the effects of body size on breeding probability and adult survival. At the beginning of the study, survival was positively correlated with adult body size (β3 = 0.066, ηβ3 = 0.982), and body size had no effect on breeding probability. Over time, the relationships between body size, survival (β9 = −0.041, ηβ9 = 0.890), and breeding propensity (α9 = −0.096, ηβ9 = 0.847) reversed, where smaller individuals now experience increased breeding and survival probability relative to large individuals. Thus, my results provide evidence that long-term changes in habitat can affect phenotype both through environmental conditions during growth, as well as changing selection pressures. Further, climatic oscillations might affect these processes. My fifth chapter combines nest monitoring data and capture-recapture data for gosling, juvenile, and adult brant and their nests to estimate temporal variation in every brant demographic parameter across the entirety of the brant life cycle. I subsequently estimate the contributions of each demographic parameter to population growth rates, as well as their covariance, to better understand the potential impacts of management actions on declining populations of adult females (βηad = −151.96, 90% CRI -170.57, -133.62) and population growth rate (βλ = −0.0040, 90% CRI -0.0055, -0.0025). There was weak evidence for long-term declines in adult survival (βφad = −0.013, ν = 0.863), nest survival (βφnest = −0.036, ν = 0.905), and clutch size (βξ = −0.007, ν = 0.836), and strong evidence for long-term declines in juvenile survival (βφjuv = −0.051, ν = 0.992). Conversely, there was strong evidence for increasing gosling survival (βφgos = 0.016, ν = 0.949) and breeding probability (βγ = 0.061, ν = 0.993). Our findings indicate that brant are experiencing declining demographic rates in both breeding and non-breeding areas, where future conservation efforts will focus on positively impacting both areas. Collectively, these chapters highlight the importance of quantitative ecological tools, and the effects of changing ecosystems and climate on life-history trade-offs, selection pressures, and population trends on a long-lived specialist herbivore.
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