Anthropogenically-mediated density dependence in a declining farmland bird

Land management intrinsically influences the distribution of animals and can consequently alter the potential for density-dependent processes to act within populations. For declining species, high densities of breeding territories are typically considered to represent productive populations. However, as density-dependent effects of food limitation or predator pressure may occur (especially when species are dependent upon separate nesting and foraging habitats), high territory density may limit per-capita productivity. Here, we use a declining but widespread European farmland bird, the yellowhammer Emberiza citrinella L., as a model system to test whether higher territory densities result in lower fledging success, parental provisioning rates or nestling growth rates compared to lower densities. Organic landscapes held higher territory densities, but nests on organic farms fledged fewer nestlings, translating to a 5 times higher rate of population shrinkage on organic farms compared to conventional. In addition, when parental provisioning behaviour was not restricted by predation risk (i.e. at times of low corvid activity), nestling provisioning rates were higher at lower territory densities, resulting in a much greater increase in nestling mass in low density areas, suggesting that food limitation occurred at high densities. These findings in turn suggest an ecological trap, whereby preferred nesting habitat does not provide sufficient food for rearing nestlings at high population density, creating a population sink. Habitat management for farmland birds should focus not simply on creating a high nesting density, but also on ensuring heterogeneous habitats to provide food resources in close proximity to nesting birds, even if this occurs through potentially restricting overall nest density but increasing population-level breeding success

'A learned man and a patriot': the reception Of Cicero in the early imperial period

This thesis is a literary study of how the life and works of Marcus Tullius Cicero were received in the century that followed his death. There are two ways of understanding the importance of such a study: the first is to think of it as a vital first step in assessing Cicero's impact on European thought and literature; the second is to see it as a study of how the people of early imperial Rome interacted with their Republican past. In order to provide a broad overview of this subject, I have chosen to focus on three separate areas of imperial literature which together provide a representative snapshot of Roman literary activity in this period. The period in question is essentially an extended Augustan age: beginning with Cicero's death ending in the reign of Tiberius. The first area of imperial literature under consideration is historiography. This section begins with a consideration of Sallust's decision to downplay Cicero's role in defeating the Catilinarian Conspiracy, ultimately concluding that this is authorial posturing on Sallust's part, a reflection of Cicero's importance in the years immediately following his death. This is followed by a chapter on the presence of Ciceronian allusions in Livy, arguing that they were a key means by which he enriched his narrative of the Hannibalic war. It concludes with two chapters on historiographical descriptions of Cicero's death, noting that these treatments become markedly more hagiographic the further one progresses into Tiberius' Principate. The second area under consideration is rhetoric, specifically focussing on the prominence of the declamation hall in this era. The three chapters in this section study the testimony of Valerius Maximus and Seneca the Elder, both of whom bear witness to Cicero's fundamental importance to this institution. The section concludes that the world of declamation was the prime motor for the hagiographic treatments of Cicero that was noted in the later historical accounts of his death. The third and final section considers the poetry of the Augustan era, demonstrating that a process of declining sophistication is not the whole story in Cicero's reception. By looking at Virgil and Ovid's intertextual relationships with Cicero, this section demonstrates that he was a rich source of inspiration for some of the ancient world's most erudite authors.</p

Appendix B. Simulation results: log-linear trend data analyzed with the Markov and generalized Markov models.

Simulation results: log-linear trend data analyzed with the Markov and generalized Markov models

Appendix A. Simulation results: log-linear trend data and log-linear trend model.

Simulation results: log-linear trend data and log-linear trend model

Appendix C. Simulation results for parameters associated with abundance and detection from Markov data analyzed with the Markov and log-linear trend models.

Simulation results for parameters associated with abundance and detection from Markov data analyzed with the Markov and log-linear trend models

Avifauna of a Chaco Locality in Bolivia

Volume: 105Start Page: 114End Page: 14

Supplement 1. Data, R code and JAGS model description to repeat simulation study investigating power to detect population trends with correlated abundances between years, using the Markov and the log-linear trend model.

<h2>File List</h2><div> <p><a href="data.100m.R">data.100m.R</a>: (MD5: 25cca5e0b23be3915b197a50bcd1fb18) R data object containing data used in the hierarchical distance sampling analysis of island scrub-jay abundance by Sillett et al. (2012); loads the following objects</p> <blockquote> <p>covs: data frame with survey point covariates <br> Xall.100m: matrix with detections from fall survey, survey site by 100-m distance band<br> Xall.spring.100m: matrix with detections from spring survey, survey site by 100-m distance band</p> </blockquote> <p><a href="Sollmann_et_al_R_script_Markovian_model.txt">Sollmann_et_al_R_script_Markovian_model.txt</a>: (MD5: ) R script file with code to simulate, analyze, and summarize data under a Markovian abundance model where <i>N</i> at time <i>t</i> depends on <i>N</i> at time <i>t</i>-1, using the open-population hierarchical distance sampling model.</p> <p><a href="Sollmann_et_al_Markovian_model_JAGS_code.txt">Sollmann_et_al_Markovian_model_JAGS_code.txt</a>: (MD5: ) JAGS model description of the open-population hierarchical distance sampling model used in the R script above.</p> <p><a href="Sollmann_et_al_R_script_Markovian_data_log-linear_trend_model.txt">Sollmann_et_al_R_script_Markovian_data_log-linear_trend_model.txt</a>: (MD5: ) R script file with code to simulate data under a Markovian abundance model (see above), and analyze and summarize it under a hierarchical distance sampling model with a log-linear time effect on abundance.</p> <p><a href="Sollmann_et_al_Independent_years_model_JAGS_code.txt">Sollmann_et_al_Independent_years_model_JAGS_code.txt</a>: (MD5: ) JAGS model description of the hierarchical distance sampling model with linear time effect used in the R script above.</p> </div><h2>Description</h2><div> <p>Data files and code are set up to repeat the simulation study investigating power to detect population trends with independent and correlated abundances between years, as presented in the Simulation section in the manuscript.</p> </div

Supplement 1. R code, data, and grid covariates used in the analyses.

<h2>File List</h2><blockquote> <p><a href="R_Code.R">R_Code.R</a></p> <p><a href="data_100m.R">data_100m.R</a></p> <p><a href="grid_covariates.R">grid_covariates.R</a></p> </blockquote><h2>Description</h2><blockquote> <p>R_Code.R contains annotated R code used to run the analyses in this paper; data_100m.R contains the count data and habitat covariates for the 307 survey plots; grid_covariates.R contains the standardized habitat covariate values used to computer population size for the entire island.</p> </blockquote