University of Maine
  • Orono, Maine, United States
Recent publications
To prepare students to address water-related challenges, undergraduate STEM education must provide them with opportunities to learn and reason about water issues. Water in Society is an introductory-level, innovative, and interdisciplinary undergraduate course offered annually at a large midwestern university. The course focuses on both disciplinary concepts and civic engagement, and is designed around a variety of interactive, research-based practices to support students’ learning, engagement with authentic data, scientific models and modeling, and collaboration and learning among peers. This study aims to evaluate, “ how have student outcomes and perceptions changed over five years of the course?”. The results are based on data from students ( n = 326) in five consecutive years of the course, during which time the course transitioned from a face-to-face model to fully asynchronous online model due, in part, to impacts of the COVID-19 pandemic. The particularly rapid and abrupt transition between 2020 and 2021 in response to COVID-19 led to many course changes, including modes of communication between instructors and students and opportunities for collaboration. Here, multiple measures are used to evaluate students’ learning about water concepts, model-based reasoning about socio-hydrologic systems, and perceptions of the course across all five years. By the end of each iteration of the course, students improved their knowledge of hydrologic concepts, independent of the course format or other student-level variables. However, results also show that students’ performance on complex socio-hydrologic systems modeling tasks, as well as their overall satisfaction with the course, decreased in Year 5 when the course was fully online. Results provide insight into efforts to move undergraduate STEM courses online and specific evidence of the COVID-19 pandemic’s impacts on undergraduate STEM teaching and learning about water.
How cultural values differ across countries has attracted a lot of research attention. However, growing evidence suggests that cultural values vary within borders, along the lines of subcultures. This paper explores cultural value differences and similarities among subcultures in Russia, and whether the values underlying these subcultures are reflected on unique preferences for workplace rewards. Our findings from a sample of 959 employees across three subcultures in Russia highlight significant differences in work values and in preference for specific rewards, suggesting the need to further study and understand subcultures within nation states, especially in large countries with a rich and complex socio-political history.
In this study, a comparative analysis of the impacts of uncertainties induced by government economic policy and the crude oil and stock markets on the stock returns of 62 energy firms is carried out across different market states. We find that economic policy uncertainty (EPU) has a stronger influence than the two market-based uncertainties. However, the oil market uncertainty (OVX) outperforms the general stock market uncertainty (VIX) for the causality-in-mean, but the reverse holds for the causality-in-variance. Stronger causal impacts are also observed during the normal and bearish market states, in that order. Finally, more significant connection is attributed to the causality-in-mean than the causality-in-variance. Thus, uncertainties, especially the one induced by the economic policy, should not be jettisoned in modeling and forecasting stock returns. The regime-switching regression model also supports the role of uncertainties in predicting the stock returns of the energy firms, with particular emphasis on adverse impact in most regimes. The fact that causality is stronger at the middle and lower quantiles also suggests the poor risk-hedging power of the stocks at the normal and bearish market states.
Small-scale hydropower (SHP) is attracting international attention as a reliable and flexible renewable energy option. In the United States, federal agencies have recently examined new SHP sites for development and assessed existing non-powered dam infrastructure for additional generation capacity. Hydropower decisions are informed by the cost, feasibility, and performance of different project options. This review is the first to: 1) categorize different types of SHP and the variety of specific cost and performance metrics used to evaluate projects; and 2) compare the cost and performance results (annual capacity factor, project power capacity, net present value (NPV), benefit-cost ratio, and levelized cost of energy) for 13 SHP studies in multiple countries spanning four continents, using diverse generation technologies and technoeconomic assessment models. Cost estimates in different currencies and dollar years are harmonized to provide comparable data ranges and simple calculations and statistics (e.g., NPV: $-1.8 to $30 million total; -$551,382/kilowatt (kW) to $11,502/kW; $3,609/kW mean; $2,655/kW median). General trends are documented in the SHP literature (i.e., decreasing levelized cost of energy and increasing benefit-cost ratio with increasing power capacity), but there is a striking lack of consistency in reported detail, assumptions, definitions, and data inputs. Similarly, there is much variability in key input parameters (e.g., capacity factor, discount rate, project lifetime, etc.), which limit meaningful comparisons across studies and highlight a need for more publicly available, user-friendly, and free SHP cost estimation tools with site-specific default input data, user-defined flexibility, and uncertainty analysis.
Understanding the forest carbon cycle has become increasingly important as carbon dioxide (CO2) emissions contribute to the changing climate. Decomposition is a major component of the forest carbon cycle; however, aspects of wood decomposition remain poorly understood, especially for stumps. To fill this knowledge gap, we examined the change in CO2 emissions over time from Picea rubens Sarg. (red spruce) stumps using a 32-year chronosequence (i.e., 0, 2, 4, 8, 23, and 32 years since harvest) derived from detailed harvesting records in a northern conifer forest in central Maine, USA, that has experienced repeated partial harvests. We found low initial CO2 flux (3.2 μmol CO2 m⁻² s⁻¹ at year 0) followed by a rapid increase, peaking 8 years post-harvest (24.3 μmol CO2 m⁻² s⁻¹) followed in turn by a decrease to very low rates by years 23 and 32 (1.4 and 1.7 μmol CO2 m⁻² s⁻¹, respectively). We found no clear relationship between CO2 emissions and any of the environmental or stump variables tested (wood temperature, wood moisture, soil moisture, and/or stump volume), suggesting that time since harvest was the overriding influence on CO2 flux rates. The large variability in CO2 flux rates among stumps of the same time since harvest points to the need for future research that includes larger sample sizes and covers a wider range of environmental and stump variables to better capture potential sources of variation. Our results add to the growing body of research on carbon emissions from deadwood that can inform forest carbon-cycle models. In addition, forest managers, who are increasingly interested in carbon management, can use these results to assess harvesting impacts on forest carbon emissions.
Millennial-scale climate oscillations of the last ice age registered in Greenland and Antarctic ice cores did not always vary in unison. A striking example is that the strongest Antarctic warming episodes occurred during Heinrich episodes in the North Atlantic region. Although the bipolar seesaw affords a possible explanation for such anti-phasing, it does not account for the equally striking observation that climate varied in unison between the hemispheres about half the time. Such phasing differences suggest the need for an alternative hypothesis in which the polar regions at times responded in unison to common forcing, and at other times left the impression of a bipolar seesaw. We posit that this impression arose from the effect of warmer-than-usual summers on continental ice sheets adjacent to the North Atlantic Ocean during each Heinrich episode. The relatively warm Heinrich summers produced discharges of meltwater and icebergs of sufficient volume to stimulate very cold winter conditions from widespread sea ice on a freshened ocean surface. The intervals between Heinrich episodes featured relaxation of sea-ice-induced winter severity from reduced summertime influx of meltwater and icebergs, indicating relatively cooler summer conditions. It is postulated that the causative variations in freshwater fluxes were driven by a climate signal most evident in Antarctic ice cores but also recognized in other paleoclimate records in both polar hemispheres. We suggest that this widespread signal arose from changes in the latitude and strength of the austral westerlies and the resulting effect on the western Pacific tropical warm pool, a mechanism dubbed the Zealandia Switch.
Leaf traits are expressed either as area-based content (g m⁻²) or mass-based concentration (mg/g or %) and subsequently scaled to canopy level using leaf area index (LAI) and foliage biomass, respectively. Despite their wide use, it remains unclear whether the two trait expressions and scaling options (by LAI or foliage biomass) yield the same prediction accuracy using multispectral remote sensing data and additional site variables. In this study, we used LAI (m² m⁻²) and foliage biomass (kg) to upscale area-based content [leaf mass per area (LMA), equivalent water thickness (EWT), nitrogen (Narea) and potassium (Karea)] and mass-based concentration [leaf dry matter content (LDMC), leaf water content (LWC), Nmass, and Kmass)], respectively in two contrasting study sites (coastal vs inland) for an ecologically important yet distinct regional species (red spruce, Picea rubens Sarg.) in Maine, USA. We used partial least squares regression (PLSR) and random forest (RF) to examine the effect of these metrics on model performance and prediction accuracy at both leaf- and canopy-scales using Sentinel-2 satellite bands, vegetation indices, as well as several topographical variables and depth to water table (DWT). The best-performing models (based on cross-validated normalized root mean square error: nRMSE) were used to generate high-resolution canopy trait maps. Results demonstrated that prediction accuracies of area-based leaf traits were generally higher (R² = 0.41–0.65, nRMSE = 0.14–0.20) than the mass-based concentration (R² = 0.42–0.65, nRMSE = 0.15–0.25) for both sites and modelling techniques. We also observed that canopy traits upscaled by LAI yield better prediction accuracies (R² = 0.44–0.70, nRMSE = 0.17–0.20) compared to a foliage biomass upscaling approach (R² = 0.41–0.57, nRMSE = 0.19–0.24). Among site variables, DWT was a significant variable in modeling canopy traits and showed robust behavior across the contrasting study sites. Overall, our study highlights the importance of trait expression and how it affects foliar trait retrieval accuracy at both leaf- and canopy-scale using satellite multispectral data and site variables. These findings have implications on leaf trait modelling especially in the context of monitoring dynamics in forest health and productivity from space.
Sablefish (Anoplopoma fimbria) are an emerging aquaculture species native to the continental shelf of the northern Pacific Ocean. There is limited information on both innate and adaptive immunity for this species and new tools are needed to determine antibody response following vaccination or disease outbreaks. In this paper, a monoclonal antibody, UI-25A, specific to sablefish IgM was produced in mice. Western blotting confirmed UI-25A recognizes the heavy chain of IgM and does not cross react to proteins or carbohydrates in serum of four other teleost species. An ELISA was developed to measure Aeromonas salmonicida specific IgM in the plasma of sablefish from a previous experiment where fish were immunized with a proprietary A. salmonicida vaccine. UI-25A was used in Western blot analyses to identify immunogenic regions of A. salmonicida recognized by this specific IgM from vaccinated sablefish. Immunofluorescent staining also demonstrated the ability of UI-25A to recognize membrane-bound IgM and identify IgM + cells in the head kidney. These results demonstrate the usefulness of UI-25A as a tool to improve the understanding of antibody-mediated immunity in sablefish as well as to provide valuable information for vaccine development and expansion of aquaculture efforts for this fish species.
A circular economy (CE) would reduce both extraction and disposal by encouraging green design and circular business models, as well as repair, reuse, remanufacturing, and recycling. The CE started among architects and engineers, with little interest among economists. This article introduces CE concepts to economists, introduces key insights about the CE from other disciplines, and describes how economists can use these insights for a more complete economic analysis of policies that can better improve human welfare. An economic model of CE behavior can benefit from understanding the environmental gains from green designs based on engineering, transaction-cost savings from information based on blockchain technology, life cycle assessments based on industrial ecology, and behavioral science concepts of cultural barriers and social decision making that affect how producers and consumers respond to incentives. With various disciplines brought to bear on the subject, the combined analysis can exceed the sum of its parts. Expected final online publication date for the Annual Review of Resource Economics, Volume 14 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Background and Objectives There is growing interest in better understanding the sectoral reach of age-friendly community practice. Action across a wide range of actors is central to achieving age-friendly societal change according to the World Health Organization and required for governmental participation in its Global Network of Age-Friendly Cities and Communities. However, there is limited knowledge regarding the scope of sectoral reach by age-friendly communities. Research Design and Methods We used qualitative inquiry to assess sectoral efforts reported by American age-friendly communities that completed a five- year cycle of participation (n=40). We employed directed content analysis using a priori indicators by sectoral actors: public (i.e., government), private (i.e., business), and civil society including nonprofit organizations and volunteers. We classify sectoral actions by type (i.e., intersectoral, multisectoral) and by clustered domain community foci (i.e., built, social, service). Results Our study identifies the extent and types of sectoral actors and actions reported by age-friendly communities with the greatest efforts reported in the public sector, and while similarly distributed across all the domains, slightly more efforts were noted in the built environment. We also found greater intersectoral efforts (i.e., explicitly working towards shared goals) than multisectoral (i.e., not necessarily in collaboration on shared goals), particularly across government. Discussion and Implications While our study substantiates the breadth of actions towards age-friendly change, additional research is needed to examine the ways in which the public and other sectoral actions are further linked to outcomes in communities in the United States and in other countries.
Rain erosion is one of the most detrimental factors contributing to wind turbine blade (WTB) coating fatigue damage especially for utility-scale wind turbines (WTs). To prevent rain erosion induced WTB coating fatigue damage, this paper proposes a deep reinforcement learning (DRL)-based optimization method for finding the optimal rotor speed under different rain intensities and wind speeds. First, an efficient physics-based model for predicting WTB coating fatigue damage considering the comprehensive blade coating fatigue mechanism, rain intensity distribution, and wind speed distribution is presented. Then, a WT rotor speed design optimization problem is constructed to search for the optimal rotor speed under different rain intensity and wind speed conditions. To address the challenge of optimizing the efficiency, the original design optimization problem is converted into a DRL-based design optimization model. A hybrid reward is proposed to enhance the DRL agent trained by a deep deterministic policy gradient algorithm. Finally, the proposed DRL-based design optimization method is utilized to guide the optimal rotor speed scheduling of a 5-MW WT under given wind speed and rain intensity conditions. The results show that the proposed method could extend the predicted WTB blade coating fatigue life by 2.55 times with a minor reduction in the energy yield (0.027%) compared to the original rotor speed schedule that only considers maximum power capture. The computational time of the proposed method is reduced significantly compared to that of the traditional gradient and evolutional design optimization methods.
Yeast use the G-protein–coupled receptor signaling pathway to detect and track the mating pheromone. The G-protein–coupled receptor pathway is inhibited by the regulator of G-protein signaling (RGS) Sst2 which induces Gα GTPase activity and inactivation of downstream signaling. G-protein signaling activates the MAPK Fus3, which phosphorylates the RGS; however, the role of this modification is unknown. We found that pheromone-induced RGS phosphorylation peaks early; the phospho-state of RGS controls its localization and influences MAPK spatial distribution. Surprisingly, phosphorylation of the RGS promotes completion of cytokinesis before pheromone-induced growth. Completion of cytokinesis in the presence of pheromone is promoted by the kelch-repeat protein, Kel1 and antagonized by the formin Bni1. We found that RGS complexes with Kel1 and prefers the unphosphorylatable RGS mutant. We also found overexpression of unphosphorylatable RGS exacerbates cytokinetic defects, whereas they are rescued by overexpression of Kel1. These data lead us to a model where Kel1 promotes completion of cytokinesis before pheromone-induced polarity but is inhibited by unphosphorylated RGS binding.
Currently, there is a rapid demand for the development of floating offshore wind turbines (FOWTs) for deployment in sites with deep water depths. FOWTs are highly complex structures that are subjected to combined loading from wind, hydrodynamic, hydrostatic, and mooring loads, and these loads have a significant influence on their dynamic behavior. The complexity of such a multi-body system makes the dynamic analysis considerably challenging and demands an efficient model to capture the physical characteristics of the system accurately. This paper proposes a novel framework for modeling floating offshore wind turbines (FOWTs) based on the vector form intrinsic finite element (VFIFE) method. In this framework, the multi-body dynamics (MBD) is used to handle the rigid body motion, and the analysis of structural deformation and the solution of governing equation of motions (EOMs) is implemented based on the VFIFE method. The methodology considers the FOWT as two rigid bodies: (a) the tower, which is a structural assembly of platform and nacelle; and (b) the rotor that can mechanically rotate relative to the nacelle. Further, a dynamic and flexible model of the mooring system is included, and their axial extension, inertia, and hydrodynamic loads are considered. The EOMs of the FOWT and mooring system are derived by the Newton-Euler (NE) and Newton's second law, respectively and the central difference scheme is implemented to solve the EOMs. Finally, the developed model is subjected to different load cases under the combined action of wind and waves, and the responses of platform motion and the axial tension of the mooring system are calculated and verified against the FAST. After thorough verification of the VFIFE model which showed excellent agreement with FAST results, the proposed model is used (a) to highlight the variations caused by neglecting the dynamic of the mooring system where the results are compared with the quasi-static mooring model developed using the MAP++ module in FAST, and (b) reveal the coupled mechanism of the platform pitch and yaw motion when the rotor is spinning.
Megaherbivores are keystone species whose removal from landscapes can cause cascading ecosystem changes, yet the consequences of Late Quaternary megaherbivore extinctions remain uncertain. This paper tests the Megaherbivory Release Hypothesis (MRH), which posits that the decline and extinction of megaherbivores (body size >1000 kg) during the last deglaciation in eastern North America contributed to the expansion of more palatable hardwood tree taxa, the development of vegetation assemblages with no modern analogue, and increased fuel load and fire activity. Coprophilous fungal spores in lake sediment records are used as proxies for megaherbivore abundance and are essential to testing the MRH through analyses of lead/lag relationships among vegetation composition, megaherbivore abundance, fire, and climate. Although some prior analyses of coprophilous fungal spores from individual sites have supported the MRH, these interpretations have been complicated by 1) discrepancies in the timing of coprophilous spore declines versus megaherbivore extinction timing based on dated vertebrate remains, 2) reliance on a single fungal taxon (Sporormiella) rather than a full suite of coprophilous fungi taxa, and 3) uncertainties in the taphonomic processes that influence fungal spore abundances. To examine the spatiotemporal relationships among megaherbivory, vegetation, and fire, we developed five new multi-taxon coprophilous fungal spore records for comparison with existing pollen, spore, and charcoal records from 14 sites across eastern North America. The MRH was well supported in the northeast and central US, with most sites showing a coprophilous spore decline by ∼14.6 ka followed by a rise of hardwood taxa (∼14.4 ka). However, changes in fire regime varied widely among northeast and central US sites and may have preceded spore declines. The MRH was not well supported in the southeastern US, where a smaller rise in hardwood taxa (∼16.1–13.1 ka) generally preceded the decline in coprophilous spores at individual sites (∼15.8–12.7 ka). These site-level and regional differences suggest spatial variations in the strength of couplings among late-Quaternary megaherbivore extinctions, vegetation composition and structure, and fire regime. Possible explanations for the differences between the northern and southeastern US include (1) differences in landscape heterogeneity of canopy openness and palatability, (2) net primary productivity and sensitivity to top-down trophic effects, (3) megaherbivore density, and (4) climate trends and seasonality at orbital to millennial timescales.
Payment for ecosystem services (PES) is a prominent neoliberal, market-based environmental policy tool to promote conservation of biodiversity and ecosystem services (ES) that has been applied since the late 1990s in both industrialized and developing countries. Recent studies have documented how PES programs do not actually function as market-based programs, and that they are often modified on the ground by local actors. Adding to this literature, our study uses an actor-oriented approach to examine how local actors in Veracruz, Mexico respond to and make changes to payment for hydrological services (PHS) programs, a prominent PES program used to address water quality and quantity issues. Drawing on interviews with 15 institutional actors and 58 landowners, we investigate how these actors challenge and modify these programs to make them more responsive to local socioecological conditions and needs. Our argument is that situated knowledge about land uses and socioecological conditions, and norms of equity and fairness, play central roles in empowering social actors to alternately adopt, contest, and re-shape PHS programs to better meet local conditions and needs.
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Elena Korotkikh
  • Institute of Climate Change
Yong-jiang Zhang
  • School of Biology and Ecology
Ivan J Fernandez
  • School of Forest Resources and Climate Change Insitute
Renae Moran
  • School of Food and Agriculture
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