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This three-essay dissertation examines how local governments manage sustainability policies/practices and how these actions are shaped by their organizational, social, and institutional environment. The first essay uses a 2015 Local Government Sustainability Practices Survey to investigate how social media shapes government sustainability plan and how its impact differs from other

This three-essay dissertation examines how local governments manage sustainability policies/practices and how these actions are shaped by their organizational, social, and institutional environment. The first essay uses a 2015 Local Government Sustainability Practices Survey to investigate how social media shapes government sustainability plan and how its impact differs from other participatory mechanisms such as public hearings and advisory committees. Drawing from a theoretical framework of individualism-collectivism, the second essay uses data on local governments in the U.S. and Japan to conduct a cross-national comparative analysis. The study finds that governments embedded in a more individualism-oriented culture are more likely to adopt environmental management practices when facing growing external pressures. The final essay uses contingency theory to provide a dynamic view of how sustainability policies might be effectively integrated into the government’s working routines. It finds that the ways through which responsibility delegation affects policy implementation are contingent upon the government’s structural and cultural arrangement. Taken together, the dissertation coincides with the growing interest among public managers and researchers in enhancing government sustainability performance and outcomes. It provides an integrated and comprehensive investigation of the organizational, social, and institutional factors that shape the development and execution of sustainability policies and practices.
ContributorsChen, Yifan (Author) / Bretschneider, Stuart (Thesis advisor) / Darnall, Nicole (Committee member) / Mossberger, Karen (Committee member) / Stritch, Justin (Committee member) / Arizona State University (Publisher)
Created2022
Description

Agassiz’s desert tortoise (Gopherus agassizii) is a long-lived species native to the Mojave Desert and is listed as threatened under the US Endangered Species Act. To aid conservation efforts for preserving the genetic diversity of this species, we generated a whole genome reference sequence with an annotation based on dee

Agassiz’s desert tortoise (Gopherus agassizii) is a long-lived species native to the Mojave Desert and is listed as threatened under the US Endangered Species Act. To aid conservation efforts for preserving the genetic diversity of this species, we generated a whole genome reference sequence with an annotation based on deep transcriptome sequences of adult skeletal muscle, lung, brain, and blood. The draft genome assembly for G. agassizii has a scaffold N50 length of 252 kbp and a total length of 2.4 Gbp. Genome annotation reveals 20,172 protein-coding genes in the G. agassizii assembly, and that gene structure is more similar to chicken than other turtles. We provide a series of comparative analyses demonstrating (1) that turtles are among the slowest-evolving genome-enabled reptiles, (2) amino acid changes in genes controlling desert tortoise traits such as shell development, longevity and osmoregulation, and (3) fixed variants across the Gopherus species complex in genes related to desert adaptations, including circadian rhythm and innate immune response. This G. agassizii genome reference and annotation is the first such resource for any tortoise, and will serve as a foundation for future analysis of the genetic basis of adaptations to the desert environment, allow for investigation into genomic factors affecting tortoise health, disease and longevity, and serve as a valuable resource for additional studies in this species complex.

Data Availability: All genomic and transcriptomic sequence files are available from the NIH-NCBI BioProject database (accession numbers PRJNA352725, PRJNA352726, and PRJNA281763). All genome assembly, transcriptome assembly, predicted protein, transcript, genome annotation, repeatmasker, phylogenetic trees, .vcf and GO enrichment files are available on Harvard Dataverse (doi:10.7910/DVN/EH2S9K).

ContributorsTollis, Marc (Author) / DeNardo, Dale F (Author) / Cornelius, John A (Author) / Dolby, Greer A (Author) / Edwards, Taylor (Author) / Henen, Brian T. (Author) / Karl, Alice E. (Author) / Murphy, Robert W. (Author) / Kusumi, Kenro (Author)
Created2017-05-31