By Yonghong Yi, John S. Kimball, Richard H. Chen, Mahta Moghaddam, Rolf H. Reichle, Umakant Mishra, Donatella Zona, Walter C. Oechel
An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models and can lead to large uncertainties in predicting regional ecosystem responses and climate feedbacks. In this study, we developed a spatially integrated modeling and analysis framework combining field observations, local-scale ( ∼ 50m resolution) active layer thickness (ALT) and soil moisture maps derived from low-frequency (L+P-band) airborne radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Modeled ALT results show good correspondence with in situ measurements in higher-permafrost-probability (PP ≥ 70%) areas (n = 33; R = 0.60; mean bias = 1.58cm; RMSE = 20.32cm), but with larger uncertainty in sporadic and discontinuous permafrost areas. The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32±1.18cmyr−1) and much larger increases (> 3cmyr−1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60±0.32). A spatially integrated analysis of the radar retrievals and model sensitivity simulations demonstrated that uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was the largest factor affecting modeled ALT accuracy, while soil moisture played a secondary role. Potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of active layer conditions and refinement of the modeling framework across a larger domain.
By Seyed Hamed Alemohammad, Alexandra G. Konings, Thomas Jagdhuber, Mahta Moghaddam, Dara Entekhabi
Remote Sensing of Environment
2018
Understanding the scattering mechanisms from the ground surface in the presence of different vegetation densities is necessary for the interpretation of P-band Synthetic Aperture Radar (SAR) observations and for the design of geophysical retrieval algorithms. In this study, a quantitative analysis of vegetation and soil scattering mechanisms estimated from the observations of an airborne P-band SAR instrument across nine different biomes in North America is presented. The goal is to apply a hybrid (model- and eigen-based) three component decomposition approach to separate the contributions of surface, double-bounce and vegetation volume scattering across a wide range of biome conditions. The decomposition makes no prior assumptions about vegetation structure. We characterize the dynamics of the decomposition across different North American biomes and assess their characteristic range. Impacts of vegetation coverseasonality and soil surface roughness on the contributions of each scattering mechanism are also investigated. Observations used here are part of the NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission and data have been collected between 2013 and 2015.
By Paulina Oliva, Fernando Aragón, Juan José
Journal of Environmental Economics and Management, 86
2017
This paper examines the effect of air pollution on labor supply in Lima, Peru. We focus on fine particulate matter (), an important pollutant for health according to the medical literature, and show that moderate levels of pollution reduce hours worked for working adults. Our research design takes advantage of rich household panel data in labor outcomes to address omitted variables. This research design allows us to investigate whether the response to air pollution is non-linear. We find that the effect of moderate pollution levels on hours worked is concentrated among households with susceptible dependents, i.e., small children and elderly adults; while the highest concentrations affect all households. This suggests that caregiving is likely a mechanism linking air pollution to labor supply at moderate levels. We provide further evidence of this mechanism using data on children morbidity. Finally, we find no evidence of intra-household attenuation behavior. For instance, there is no re-allocation of labor across household members, and earnings decrease with air pollution.
By Brandon H. Lee, Shon R. Hiatt, Michael Lounsburyc
The Institute for Operations Research and the Management Sciences
2017
Although existing research has demonstrated the importance of attaining legitimacy for new market categories, few scholars have considered the trade-offs associated with such actions. Using the U.S. organic food product category as a context, we explore how one standards-based certification organization—the California Certified Organic Farmers (CCOF)—sought to balance efforts to legitimate a nascent market category with retaining a shared, distinctive identity among its members. Our findings suggest that legitimacy-seeking behaviors undertaken by the standards organization diluted the initial collective identity and founding ethos of its membership. However, by shifting the meaning of “organic” from the producer to the product, CCOF was able to strengthen the categorical boundary, thereby enhancing its legitimacy. By showing how the organization managed the associated trade-offs, this study highlights the double-edged nature of legitimacy and offers important implications for the literatures on legitimacy and new market category formation.
By Paul A. Sandifer, Landon C. Knapp, Tracy K. Collier, Amanda L. Jones, Robert-Paul Juster, Christopher R. Kelble, Richard K. Kwok, John V. Miglarese, Lawrence A. Palinkas, Dwayne E. Porter, Geoffrey I. Scott, Lisa M. Smith, William C. Sullivan, and Ariana E. Sutton-Grier
Few conceptual frameworks attempt to connect disaster-associated environmental injuries to impacts on ecosystem services (the benefits humans derive from nature) and thence to both psychological and physiological human health effects. To our knowledge, this study is one of the first, if not the first, to develop a detailed conceptual model of how degraded ecosystem services affect cumulative stress impacts on the health of individual humans and communities. Our comprehensive Disaster-Pressure State-Ecosystem Services-Response-Health model demonstrates that oil spills, hurricanes, and other disasters can change key ecosystem components resulting in reductions in individual and multiple ecosystem services that support people’s livelihoods, health, and way of life. Further, the model elucidates how damage to ecosystem services produces acute, chronic, and cumulative stress in humans which increases risk of adverse psychological and physiological health outcomes. While developed and initially applied within the context of the Gulf of Mexico, it should work equally well in other geographies and for many disasters that cause impairment of ecosystem services. Use of this new tool will improve planning for responses to future disasters and help society more fully account for the costs and benefits of potential management responses. The model also can be used to help direct investments in improving response capabilities of the public health community, biomedical researchers, and environmental scientists. Finally, the model illustrates why the broad range of potential human health effects of disasters should receive equal attention to that accorded environmental damages in assessing restoration and recovery costs and time frames.
By Jangmin Kim, Saba Siddiki, William D. Leach
Public Administration Review
2017
Scholarship on collaborative governance identifies several structural and procedural factors that consistently influence governance outcomes. A promising next step for collaborative governance research is to explore how these factors interact. Focusing on two dimensions of social learning—relational and cognitive—as outcomes of collaboration, this article examines potential interacting effects of participant diversity and trust. The empirical setting entails 10 collaborative partnerships in the United States that provide advice on marine aquaculture policy. The findings indicate that diversity in beliefs among participants is positively related to relational learning, whereas diversity in participants’ affiliations is negatively related to relational learning, and high trust bolsters the positive effects of belief diversity on both relational and cognitive learning. In addition, high trust dampens the negative effects of affiliation diversity on relational learning. A more nuanced understanding of diversity in collaborative governance has practical implications for the design and facilitation of diverse stakeholder groups.
