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The Rocky Flats National Wildlife Refuge is located west of Denver, Colorado, USA along the central Front Range of the Rocky Mountains. The wildlife refuge property includes a former U.S. Department of Energy nuclear weapons facility, hereafter \"the former Rocky Flats site.\" Owing to the storage and use of aqueous film forming foam (AFFF) at the on-site fire department, industrial areas of the former Rocky Flats site has detectable concentrations of per- and polyfluoroalkyl substances (PFAS) in groundwater (range perfluorooctanesulfonic acid [PFOS]: not detected [ND] [<0.75]-350 ng/L, perfluorooctanoic acid [PFOA]: ND [<0.55]-160 ng/L) and surface water (range PFOS: 1.9-18 ng/L, PFOA: ND [<0.55]-13 ng/L). AFFF is a known source of PFOA and PFOS contamination in the environment. PFAS are a class of thousands of human-made chemicals considered ubiquitous in the environment globally. Exposure to these chemicals can negatively impact the health of both humans and wildlife. In March 2023, we used a draft version of the U.S. Environmental Protection Agency Method 1633 to analyze liver and muscle tissues from 17 Rocky Mountain elk (Cervus canadensis nelsoni) to detect the presence of PFAS. We collected samples from 15 elk residing at the former Rocky Flats site and 2 elk at locations with no known PFAS contamination (i.e., control locations). Neither PFOA nor PFOS was detected in elk muscle tissues collected at the former Rocky Flats site or the control locations. The average method detection limits for PFOA and PFOS in muscle tissues were 0.166 ng/g and 0.154 ng/g respectively. PFOS was detected within 100% of the liver tissues harvested from elk at the former Rocky Flats site and both control locations. The average PFOS concentrations in liver tissues collected at the former Rocky Flats site and control locations were 16.23 ± 4.40 ng/g (maximum concentration 34.20 ng/g) and 8.75 ± 3.02 ng/g (maximum concentration 9.40 ng/g), respectively. To the best of our knowledge, this is the first study examining PFAS concentrations in elk. Although we were unable to draw conclusions owing to the relatively small sample size, PFOS concentrations in liver tissues collected at the former Rocky Flats site were low, consistent with those detected in other species of wildlife studied in the United States with known PFAS contamination.

Accurate assessment of abundance forms a central challenge in population ecology and wildlife management. Many statistical techniques have been developed to estimate population sizes because populations change over time and space and to correct for the bias resulting from animals that are present in a study area but not observed. The mobility of individuals makes it difficult to design sampling procedures that account for movement into and out of areas with fixed jurisdictional boundaries. Aerial surveys are the gold standard used to obtain data of large mobile species in geographic regions with harsh terrain, but these surveys can be prohibitively expensive and dangerous. Estimating abundance with ground-based census methods have practical advantages, but it can be difficult to simultaneously account for temporary emigration and observer error to avoid biased results. Contemporary research in population ecology increasingly relies on telemetry observations of the states and locations of individuals to gain insight on vital rates, animal movements, and population abundance. Analytical models that use observations of movements to improve estimates of abundance have not been developed. Here we build upon existing multi-state mark–recapture methods using a hierarchical N-mixture model with multiple sources of data, including telemetry data on locations of individuals, to improve estimates of population sizes. We used a state-space approach to model animal movements to approximate the number of marked animals present within the study area at any observation period, thereby accounting for a frequently changing number of marked individuals. We illustrate the approach using data on a population of elk (Cervus elaphus nelsoni) in Northern Colorado, USA. We demonstrate substantial improvement compared to existing abundance estimation methods and corroborate our results from the ground based surveys with estimates from aerial surveys during the same seasons. We develop a hierarchical Bayesian N-mixture model using multiple sources of data on abundance, movement and survival to estimate the population size of a mobile species that uses remote conservation areas. The model improves accuracy of inference relative to previous methods for estimating abundance of open populations.

This dissertation addresses the question of how legacy industrial regions—those that have historically relied on manufacturing (and to an extent also resource extraction and agriculture)—can regain or sustain competitiveness in a global, service-dominant, and digitally automated economy. This question is examined through the lens of a small industry that is geographically concentrated in these regions and provides services directly related to material production.The industry is called robotics systems integration. It consists of engineering consultants and service providers that design and implement robotic automation systems for manufacturers.The conceptual framework underlying this inquiry is that of evolutionary economic geography (EEG), which views economic evolution as in some ways analogous to biological evolution. From this perspective, the role of firms is similar to the role of biological organisms, because both firms and organisms scale up to form ecosystems, and these ecosystems can be studied at a regional level. Understanding how these ecosystems work can help to understand why some regions and industries stagnate and decline, and what can be done to change these trajectories of these regions. Special attention is given to the role of individual and organizational agency in transferring the information needed for regional economic ecosystems to adapt.Data was collected through a survey and interviews of robotics systems integrators. The analysis in the dissertation is organized around four main themes. They are: integrators’ geography, their role and position in the robotics supply chain, their ability to absorb and propagate a type of evolutionary information called related variety, and their human capital needs and practices.Results suggest that integrators are indeed agents for facilitating the evolutionary transfer of information within and between regional industrial ecosystems, and across multiple technologies. Key pathways for this transfer are 1) interactions with customers and suppliers, and 2) human capital practices that prioritize a “synthetic” sensibility over a codified set of skills. This synthetic sensibility is characterized by a predilection towards solving practical physical, material, and spatial problems of the kind often presented when working with industrial automation systems.These evolutionary information transfers are geographically contingent. While integrators’ customers are geographically dispersed, integrators themselves are heavily concentrated in legacy industrial regions, and this pattern does not appear to be changing any time soon. Moreover, integrators actively recruit for personnel from nearby institutions and prioritize these synthetic sensibilities that are embedded in legacy regions during recruitment.While this research cannot establish a direct causal link between robotics systems integrators and the evolutionary trajectory of their regional industrial ecosystems, it does suggest that further probing these issues by looking at similar regions and industries could be helpful in identifying productive evolutionary paths forward for peripheral regions often thought to be left out of the 21st century knowledge- and service-based economy.

Leigh and Kraft offer information on the Alabama Robotics Technology Park (RTP) which is a unique facility and public workforce development program that provides robotics training and research and development space to manufacturing firms and their employees in Alabama.. The RTP originated out of a recognition that cultivating a local robotics skill-base could fortify business attraction and retention efforts. They also discuss how the RTP differs from traditional workforce development models by focusing on an emerging technological process rather than an industry sector and address how the RTP aligns with existing statewide economic and workforce development programs and considers future implications for this model in a time of rapid technological change

Finally, this report adopts a broad conceptualization of sustainability. Often, sustainability is perceived as an envi- ronmental or \"green\" concept only. Planning for urban industry certainly fits within this framework, and this report discusses green industrial tools and strategies specifically in Chapter 4 (\"Brownfields,\" p. 38) and Chapter 5 (\"Industry and the 'Green' Economy,\" p. 50).

1. Phenological events - defined points in the life cycle of a plant or animal - have been regarded as highly plastic traits, reflecting flexible responses to various environmental cues. 2. The ability of a species to track, via shifts in phenological events, the abiotic environment through time might dictate its vulnerability to future climate change. Understanding the predictors and drivers of phenological change is therefore critical. 3. Here, we evaluated evidence for phylogenetic conservatism - the tendency for closely related species to share similar ecological and biological attributes - in phenological traits across flowering plants. We aggregated published and unpublished data on timing of first flower and first leaf, encompassing ~4000 species at 23 sites across the Northern Hemisphere. We reconstructed the phylogeny for the set of included species, first, using the software program Phylomatic, and second, from DNA data. We then quantified phylogenetic conservatism in plant phenology within and across sites. 4. We show that more closely related species tend to flower and leaf at similar times. By contrasting mean flowering times within and across sites, however, we illustrate that it is not the time of year that is conserved, but rather the phenological responses to a common set of abiotic cues. 5. Our findings suggest that species cannot be treated as statistically independent when modelling phenological responses. 6. Synthesis. Closely related species tend to resemble each other in the timing of their life-history events, a likely product of evolutionarily conserved responses to environmental cues. The search for the underlying drivers of phenology must therefore account for species' shared evolutionary histories.

Noncommunicable diseases (NCDs) are on the rise worldwide. Obesity, cardiovascular disease, and type 2 diabetes are among a long list of “lifestyle” diseases that were rare throughout human history but are now common. The evolutionary mismatch hypothesis posits that humans evolved in environments that radically differ from those we currently experience; consequently, traits that were once advantageous may now be “mismatched” and disease causing. At the genetic level, this hypothesis predicts that loci with a history of selection will exhibit “genotype by environment” (GxE) interactions, with different health effects in “ancestral” versus “modern” environments. To identify such loci, we advocate for combining genomic tools in partnership with subsistence-level groups experiencing rapid lifestyle change. In these populations, comparisons of individuals falling on opposite extremes of the “matched” to “mismatched” spectrum are uniquely possible. More broadly, the work we propose will inform our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and cultures.

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health.