ASU Scholarship Showcase

In this synthesis, we hope to accomplish two things: 1) reflect on how the analysis of the new archaeological cases presented in this special feature adds to previous case studies by revisiting a set of propositions reported in a 2006 special feature, and 2) reflect on four main ideas that are more specific to the archaeological cases: i) societal choices are influenced by robustness–vulnerability trade-offs, ii) there is interplay between robustness–vulnerability trade-offs and robustness–performance trade-offs, iii) societies often get locked in to particular strategies, and iv) multiple positive feedbacks escalate the perceived cost of societal change. We then discuss whether these lock-in traps can be prevented or whether the risks associated with them can be mitigated. We conclude by highlighting how these long-term historical studies can help us to understand current society, societal practices, and the nexus between ecology and society.

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations.

We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO₂ and CH₄ fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data.

Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO₂ proxy measurements such as radiocarbon in CO₂ and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.

Errors in the specification or utilization of fossil fuel CO₂ emissions within carbon budget or atmospheric CO₂ inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO₂ concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Regridding of fossil fuel CO₂ emissions (FFCO₂) from fine to coarse grids to enable atmospheric transport simulations can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. For example, emissions originally emanating from the land are emitted from a grid cell for which the vertical mixing reflects the roughness and/or surface energy exchange of an ocean surface. We test this potential "dynamical inconsistency" by examining simulated global atmospheric CO₂ concentration driven by two different approaches to regridding fossil fuel CO₂ emissions. The two approaches are as follows: (1) a commonly used method that allocates emissions to grid cells with no attempt to ensure dynamical consistency with atmospheric transport and (2) an improved method that reallocates emissions to grid cells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO₂ concentration when comparing these two approaches. The emissions difference ranges from −30.3 TgC grid cell^-1 yr^-1 (−3.39 kgC m^-2 yr^-1) to +30.0 TgC grid cell^-1 yr^-1 (+2.6 kgC m^-2 yr^-1) along coastal margins. Maximum simulated annual mean CO₂ concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO₂ monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO₂ concentration, such as atmospheric CO₂ inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.

As part of an international collaboration to compare large-scale commons, we used the Social-Ecological Systems Meta-Analysis Database (SESMAD) to systematically map out attributes of and changes in the Great Barrier Reef Marine Park (GBRMP) in Australia. We focus on eight design principles from common-pool resource (CPR) theory and other key social-ecological systems governance variables, and explore to what extent they help explain the social and ecological outcomes of park management through time. Our analysis showed that commercial fisheries management and the re-zoning of the GBRMP in 2004 led to improvements in ecological condition of the reef, particularly fisheries. These boundary and rights changes were supported by effective monitoring, sanctioning and conflict resolution. Moderate biophysical connectivity was also important for improved outcomes. However, our analysis also highlighted that continued challenges to improved ecological health in terms of coral cover and biodiversity can be explained by fuzzy boundaries between land and sea, and the significance of external drivers to even large-scale social-ecological systems (SES). While ecological and institutional fit in the marine SES was high, this was not the case when considering the coastal SES. Nested governance arrangements become even more important at this larger scale. To our knowledge, our paper provides the first analysis linking the re-zoning of the GBRMP to CPR and SES theory. We discuss important challenges to coding large-scale systems for meta-analysis.

The Montreal Protocol is generally credited as a successful example of international cooperation in response to a global environmental problem. As a result, the production and consumption of ozone-depleting substances has declined rapidly, and it is expected that atmospheric ozone concentrations will return to their normal ranges toward the end of this century. This paper applies the social-ecological system framework and common-pool resource theory to explore the congruence between successful resolution of small-scale appropriation problems and ozone regulation, a large-scale pollution problem. The results of our analysis correspond closely to past studies of the Protocol that highlight the importance of attributes such as a limited number of major industrial producers, advances in scientific knowledge, and the availability of technological substitutes. However, in contrast to previous theoretical accounts that focus on one or a few variables, our analysis suggests that its success may have been the result of interactions between a wider range of SES attributes, many of which are associated with successful small-scale environmental governance. Although carefully noting the limitations of drawing conclusions from the analysis of a single case, our analysis reveals the potential for fruitful interplay between common-pool resource theory and large-scale pollution problems.

The purpose of the United Nations-guided process to establish Sustainable Development Goals is to galvanize governments and civil society to rise to the interlinked environmental, societal, and economic challenges we face in the Anthropocene. We argue that the process of setting Sustainable Development Goals should take three key aspects into consideration. First, it should embrace an integrated social-ecological system perspective and acknowledge the key dynamics that such systems entail, including the role of ecosystems in sustaining human wellbeing, multiple cross-scale interactions, and uncertain thresholds. Second, the process needs to address trade-offs between the ambition of goals and the feasibility in reaching them, recognizing biophysical, social, and political constraints. Third, the goal-setting exercise and the management of goal implementation need to be guided by existing knowledge about the principles, dynamics, and constraints of social change processes at all scales, from the individual to the global. Combining these three aspects will increase the chances of establishing and achieving effective Sustainable Development Goals.

Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment. This large variability is washed out in bulk assays, and there is a need of techniques that can quantify interactions of bacteria with ligands at the single bacterium level. In this work, we present a label-free and real-time plasmonic imaging technique to measure the binding kinetics of ligand interactions with single bacteria, and perform statistical analysis of the heterogeneity. Using the technique, we have studied interactions of antibodies with single Escherichia coli O157:H7 cells and demonstrated a capability of determining the binding kinetic constants of single live bacteria with ligands, and quantify heterogeneity in a microbial population.

High-resolution, global quantification of fossil fuel CO[subscript 2] emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high-resolution fossil fuel CO[subscript 2] emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long-term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long-term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter-term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO[subscript 2] emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO[subscript 2] emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set.

Background: Most excess deaths that occur during extreme hot weather events do not have natural heat recorded as an underlying or contributing cause. This study aims to identify the specific individuals who died because of hot weather using only secondary data. A novel approach was developed in which the expected number of deaths was repeatedly sampled from all deaths that occurred during a hot weather event, and compared with deaths during a control period. The deaths were compared with respect to five factors known to be associated with hot weather mortality. Individuals were ranked by their presence in significant models over 100 trials of 10,000 repetitions. Those with the highest rankings were identified as probable excess deaths. Sensitivity analyses were performed on a range of model combinations. These methods were applied to a 2009 hot weather event in greater Vancouver, Canada.

Results: The excess deaths identified were sensitive to differences in model combinations, particularly between univariate and multivariate approaches. One multivariate and one univariate combination were chosen as the best models for further analyses. The individuals identified by multiple combinations suggest that marginalized populations in greater Vancouver are at higher risk of death during hot weather.

Conclusions: This study proposes novel methods for classifying specific deaths as expected or excess during a hot weather event. Further work is needed to evaluate performance of the methods in simulation studies and against clinically identified cases. If confirmed, these methods could be applied to a wide range of populations and events of interest.

Background:
Ketogenic diets are high fat and low carbohydrate or very low carbohydrate diets, which render high production of ketones upon consumption known as nutritional ketosis (NK). Ketosis is also produced during fasting periods, which is known as fasting ketosis (FK). Recently, the combinations of NK and FK, as well as NK alone, have been used as resources for weight loss management and treatment of epilepsy.

Methods:
A crossover study design was applied to 11 healthy individuals, who maintained moderately sedentary lifestyle, and consumed three types of diet randomly assigned over a three-week period. All participants completed the diets in a randomized and counterbalanced fashion. Each weekly diet protocol included three phases: Phase 1 - A mixed diet with ratio of fat: (carbohydrate + protein) by mass of 0.18 or the equivalence of 29% energy from fat from Day 1 to Day 5. Phase 2- A mixed or a high-fat diet with ratio of fat: (carbohydrate + protein) by mass of approximately 0.18, 1.63, or 3.80 on Day 6 or the equivalence of 29%, 79%, or 90% energy from fat, respectively. Phase 3 - A fasting diet with no calorie intake on Day 7. Caloric intake from diets on Day 1 to Day 6 was equal to each individual’s energy expenditure. On Day 7, ketone buildup from FK was measured.

Results:
A statistically significant effect of Phase 2 (Day 6) diet was found on FK of Day 7, as indicated by repeated analysis of variance (ANOVA), F(2,20) = 6.73, p < 0.0058. Using a Fisher LDS pair-wise comparison, higher significant levels of acetone buildup were found for diets with 79% fat content and 90% fat content vs. 29% fat content (with p = 0.00159**, and 0.04435**, respectively), with no significant difference between diets with 79% fat content and 90% fat content. In addition, independent of the diet, a significantly higher ketone buildup capability of subjects with higher resting energy expenditure (R[superscript 2] = 0.92), and lower body mass index (R[superscript 2] = 0.71) was observed during FK.