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The aim of this study was to examine the effects of elevated carbon dioxide [CO2] and ozone [O3] and their interaction on wood chemistry and anatomy of five clones of 3-year-old trembling aspen (Populus tremuloides Michx.). Wood chemistry was studied also on paper birch (Betula papyrifera Marsh.) and sugar maple (Acer saccharum Marsh.) seedling-origin saplings of the same age. Material for the study was collected from the Aspen Free-Air CO2 Enrichment (FACE) experiment in Rhinelander, WI, USA, where the saplings had been exposed to four treatments: control (C; ambient CO2, ambient O3), elevated CO2 (560ppm during daylight hours), elevated O3 (1.5 × ambient during daylight hours) and their combination (CO2 + O3) for three growing seasons (1998–2000). Wood chemistry responses to the elevated CO2 and O3 treatments differed between species. Aspen was most responsive, while maple was the least responsive of the three tree species. Aspen genotype affected the responses of wood chemistry and, to some extent, wood structure to the treatments. The lignin concentration increased under elevated O3 in four clones of aspen and in birch. However, elevated CO2 ameliorated the effect. In two aspen clones, nitrogen in wood samples decreased under combined exposure to CO2 and O2. Soluble sugar concentration in one aspen clone and starch concentration in two clones were increased by elevated CO2. In aspen wood, α-cellulose concentration changed under elevated CO2, decreasing under ambient 03 and slightly increasing under elevated O3. Hemicellulose concentration in birch was decreased by elevated CO2 and increased by elevated O3. In aspen, elevated O3 induced statistically significant reductions in distance from the pith to the bark and vessel lumen diameter, as well as increased wall thickness and wall percentage, and in one clone, decreased fibre lumen diameter. Our results show that juvenile wood properties of broadleaves, depending on species and genotype, were altered by atmospheric gas concentrations predicted for the year 2050 and that CO2 ameliorates some adverse effects of elevated O3 on wood chemistry. [ABSTRACT FROM AUTHOR]

While the majority of adults across the United States report that they believe that global warming is happening, far fewer report discussing global warming (Howe et al., 2015, https://doi.org/10.1038/nclimate2583; Marlon et al., 2022, https://climatecommunication.yale.edu/visualizations‐data/ycom‐us/). One way to inspire further climate action and engagement is to increase individuals' capacity to confidently and effectively discuss climate change. Climate communication science highlights that such communication is most effective when it is anecdotal, narrative, tailored to the audience, and place‐based. To generate climate conversations and inspire action in a variety of communities, partners at the University of Minnesota Extension piloted a program to train community members from across the state of Minnesota in effective climate communication through a series of instructional workshops, coaching, and participant‐led communication activities. Following the training portion of the program, participants identified and hosted their own climate‐related communication activities in their communities. These "climate conversations" took place across Minnesota and included community events, dialogue with elected leaders, and conversations stimulated through literature, among other activities. In their communities, program participants sparked conversations, initiated long‐term climate action efforts, and improved their sense of efficacy in response to climate change. Participants also reported that they improved their climate conversation skills, increased their local climate knowledge, established a support network with fellow participants, had reduced anxiety around communicating, and increased their confidence in being able to communicate about climate change in their communities. This pilot program provides a framework for future cohort‐ and community‐based climate communication programs in the state and beyond. Plain Language Summary: More frequent, effective climate conversations initiated by a diversity of trusted voices can help to increase climate concern and desire for action at the community level. However, in the United States, there is a disconnect between the level of concern individuals have about climate change and the extent to which individuals talk about the issue. To help bridge this gap, the University of Minnesota Climate Adaptation Partnership developed a training program aimed at inspiring and equipping local community members across Greater Minnesota with the skills and confidence to have effective conversations about climate change in their communities. This paper summarizes the programmatic activities we used to support our goals, and some reflections on the program's results. This pilot program provides a framework for future efforts that can be facilitated by Extension programs, community‐based organizations, universities, and others to inspire and accelerate similar community‐centered climate conversations. Key Points: We piloted a training program to teach Minnesotans to effectively communicate about climate change and its impacts on their communitiesParticipants improved behavioral and conversation skills to communicate about climate change more effectivelyThis program provides a framework for future programs aimed at increasing the diversity of people engaging in local climate conversations [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Economics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A mass‐conserving method to downscale precipitation from global climate models (GCMs) using sub‐grid‐scale topography and modeled 700‐mb wind direction is presented. Runoff is simulated using a stand‐alone hydrological model, with this and several other methods as inputs, and compared to runoff simulated using historical observations over the western contiguous United States. Results suggest the mitigation of grid‐scale biases is more critical than downscaling for some regions with large wet biases (e.g., the Great Basin and Upper Colorado). In other regions (e.g., the Pacific Northwest) the new method produces more realistic sub‐grid‐scale variability in runoff compared to unadjusted GCM output and a simpler downscaling method. The presented method also brings the runoff centroid timing closer to that simulated with observations for all subregions examined. Plain Language Summary: Due to limitations in computing power which necessitates coarse spatial resolution, climate models do not include many details on mountains and their impact on precipitation. For this reason, it is difficult to estimate the impact of climate change on the availability of water for human consumption in places like the western United States, where mountain snowpack is an important source of water. This paper presents a way to adjust precipitation estimates from climate models by using some simple statistics about nearby mountains and valleys. The adjusted precipitation is then used in a hydrologic model to calculate the runoff that is simulated with different precipitation inputs. Results show that in most cases, the precipitation adjustment improves estimates of the resultant runoff relative to simulations with observed precipitation. The main exceptions are in very dry areas where the climate model produces far too much precipitation. With further work, the proposed adjustment may be integrated into the climate model itself to make it easier for those managing water resources (e.g., controlling reservoir levels) to use the model output to plan and adapt to climate change. Key Points: A mass‐conserving method for downscaling orographic precipitation improves modeled runoff from the CESM2Considering upwind topography further improves modeled runoff compared to simpler adjustmentsNot tuning to individual model grid points makes this method more generalizable than many existing statistical downscaling methods [ABSTRACT FROM AUTHOR]

Copyright of Review of Policy Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Solomon Hsiang's study, which was recently published in Science, has caused extensive discussion by indicating that future climate change may exert influences on the agricultural yield, labor supply, and energy demand, among others of the United States. Based on the above study, we use an optimized input‐output model to evaluate the economic ripple effect (ERE) of the United States on the world due to climate change under Representative Concentration Pathway 4.5 with different increases in the annual mean temperature (AMT; 1, 1.5, and 2°C) between 2020 and 2100. The results show that if a loss of gross domestic product of 0.88% occurs with a 1°C AMT increase in the United States, the ERE of approximately 0.12% will be generated onto the global gross domestic product; with a 2°C increase, the ERE will triple. The time variation trend of the ERE conforms to the future variations in AMT. The degree of this effect on other regions of the world is closely related to the trade links between the United States and economic aggregates. Among these regions, Canada shows the greatest impact, followed by China. The ERE that China suffers may increase by 4.5 times as the AMT in the United States increases from 1 to 2°C. In cold regions, the benefit from global warming will decrease due to the ERE from other regions, which will inhibit their economic development. This paper aims to provide new perspectives and data‐based support for regions around the world to cope with climate change and to develop policies by studying the ERE behind international trade. [ABSTRACT FROM AUTHOR]

Drawing from theory on the "co-production" of science and society, this paper provides an account of trajectories in US climatology, roughly from the 1850s to 1920, the period during which climatology emerged as an organized branch of meteorology and government administration. The historical narrative traces the development of climatology both as a professional/institutional project and as a component of a larger governmental logic. Historical analysis of climatologists' scientific texts, maps, and social organization within government provides a sociological explanation for the emergent "stabilization" of climate as a geographic-statistical category. Climatic stability, defined by the view that climate is unchanging, was advanced over this period in a way that linked the interests and practices of climatologists to actors invested in facilitating and administrating commercial agriculture and trade. I position the logic of climatology and the discourse of climatic stability historically, with reference to prior concern with climate change and, in recent decades, efforts to govern global warming through geoengineering climatic stability. [ABSTRACT FROM AUTHOR]

Copyright of Policy Studies Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper traces the development of energy policy in the mainline churches beginning with Margaret Mead and René Dubos's 1974 commission to prepare a report to the National Council of Churches on the use of plutonium as a commercial fuel. The report stirred a controversy and a broader examination of energy ethics that culminated in the adoption in 1979 of a National Council of Churches of Christ in the U.S.A. policy paper and encouraged constituent denominations to make their own studies of energy policy. The development and implementation of these policies is followed from 1980 to the present, using the Presbyterian Church ( U.S.A.) as a representative mainline denomination. This turn to ethical reasoning to support change in U.S. energy policy is a hopeful development, given the stalemate in such discussion when framed in scientific or political terms. [ABSTRACT FROM AUTHOR]

Catchments are complex systems containing channel networks and hillslopes. Channel networks interact with hillslopes and are pathways for transporting water, sediment, and nutrients. Understanding the branching and flux transport patterns of channel networks is critical for predicting the response of catchments to external forcing such as climate and tectonics. However, factors creating complexities in catchments are not fully understood. Here, we propose a new framework based on multiscale entropy approach to evaluate complexity of catchments using two different representations of channel networks. First, we investigate the structural complexity using the width‐function, which characterizes the spatial arrangement of channels. Second, we utilize the incremental area‐function along the main channel to study the functional complexity that captures the patterns of transport of fluxes. Our analysis reveals stronger controls of topological connectivity on the functional complexity than on structural complexity, indicating unchannelized surface (hillslope) contribution to the increase of heterogeneity in transport processes. Plain Language Summary: Catchments are complex natural landscape systems that contain hillslopes and channel networks. Understanding and quantifying features and processes that result in catchment complexity is important for predicting their response to changing human and climatic conditions. In this paper, we use an entropy‐based approach to explore the role of channel network and hillslope toward the contribution to catchment's complexity. Based on 40 natural catchments with minimum human impact across the United States in different climatic and geologic conditions, our results show that hillslopes add significant complexity to the catchments and suggest the amount of hillslope information one needs to account for in accurate predictive modeling of hydrologic processes at the catchment scale. Key Points: Topology controls structural and functional complexityFunctional complexity is higher than structural complexity due to contribution from hillslope processesScale of peak difference between the impact of topology on functional and structural complexity indicates the average hillslope length scale [ABSTRACT FROM AUTHOR]

Precipitation extremes are increasing globally due to anthropogenic climate change. However, there remains uncertainty regarding impacts upon flood occurrence and subsequent population exposure. Here, we quantify changes in population exposure to flood hazard across the contiguous United States. We combine simulations from a climate model large ensemble and a high‐resolution hydrodynamic flood model—allowing us to directly assess changes across a wide range of extreme precipitation magnitudes and accumulation timescales. We report a mean increase in the 100‐year precipitation event of ~20% (magnitude) and >200% (frequency) in a high warming scenario, yielding a ~30–127% increase in population exposure. We further find a nonlinear increase for the most intense precipitation events—suggesting accelerating societal impacts from historically rare or unprecedented precipitation events in the 21st century. Plain Language Summary: Heavy rainfall is increasing globally due to human‐caused global warming. However, it is still unclear how these increases in heavy rainfall might affect flood risk. In this paper, we investigate how global warming and population changes together may be affecting the number of people at risk from floods in the United States. We combine simulations from a climate model and flood model—allowing us to consider a wide range of heavy rainfall events. We report a ~20% increase in the size and a >200% increase in the frequency of very heavy and rare rainfall events, which leads to a ~30–127% increase in the number of people at risk from floods. Finally, we find that the heaviest rainfall events increase by the widest margin—suggesting the possibility of major increases in damage and disruption caused by severe floods in the 21st century. Key Points: Population exposure to flood hazard is increasing due to both climate‐driven increases in extreme rainfall as well as demographic shiftsThere is a wide range of plausible increases in population exposed to flood hazard, depending strongly on climate and growth scenarioWe find a nonlinear increase for most extreme events, suggesting accelerating societal impacts from historically unprecedented rainfall [ABSTRACT FROM AUTHOR]

The article presents a commentary on bioenergy in a global environment. The author mentions some papers focusing on biofuels and the effects of the industry on economic stability, global food prices, and climate change. The author comments on the papers and renders perspectives on the U.S. bioenergy sector and its policies.

To study trends in extreme precipitation across the United States over the years 1951–2017, we analyze 10 climate indexes that represent extreme precipitation, such as annual maximum of daily precipitation and annual maximum of consecutive five‐day average precipitation. We consider the gridded data produced by the CLIMDEX project (http://www.climdex.org/gewocs.html), constructed using daily precipitation data. These indexes exhibit spatial and mutual dependence. In this paper, we propose a multivariate spatial skew‐t process for joint modeling of extreme precipitation indexes and discuss its theoretical properties. The model framework allows Bayesian inference while maintaining a computational time that is competitive with common multivariate geostatistical approaches. In a numerical study, we find that the proposed model outperforms several simpler alternatives in terms of various model selection criteria. We apply the proposed model to estimate the average decadal change in the extreme precipitation indexes throughout the United States and find several significant local changes. [ABSTRACT FROM AUTHOR]

In an average year (1979–2016), the United States experiences nearly 1,100 tornadoes, which cause a total of 68 fatalities. Annual fatality rates have decreased since the peak in the 1920s, but there is a concern that they could start to rise again with increases in vulnerable populations and the impacts of climate change. It is possible to assess the risk of tornado fatalities using the historical record. However, the rarity of tornadoes and the short period of record may not capture the true risk. One way around this problem is to simulate thousands of years' worth of tornadoes to obtain a broader picture of risk. Previous tornado risk models have distributed tornadoes randomly or used climatology to generate realistic tornado patterns on an annual (or longer) time scale. From an operational standpoint, it would be useful to have a model that distributes tornadoes on a daily time step to enable the forecasting of potential tornado impacts on a given day. The present study introduces one such model that distributes tornadoes using information about the favourability of the atmospheric environment for tornado development: The Tornado Daily Impacts Simulator (TorDIS). The paper demonstrates model utility through 1,000 year simulations over several metropolitan areas and with a comparison between modelled and observed impacts for several high‐impact tornado days. Forecasting potential tornado impacts on a daily time step could allow emergency managers to plan ahead for high‐risk days to prioritize their resources and save lives. [ABSTRACT FROM AUTHOR]

As climate change unfolds, formal planning for climate adaptation is emerging at all levels of governments. This paper examines the factors that lead U.S. state governments to develop comprehensive adaptation plans. Using an event history analysis, we find that a state is more likely to engage in adaptation planning we find that a state is more likely to engage in adaptation planning when it experienced more extreme weather events recently, has more economic activities in coastal regions, or when it has high levels of incomes and civic engagement. We also show that political ideology plays a critical role in subnational adaptation decision making. A state is less likely to pursue adaptation planning when it has a Republican governor or has a lack of preference for environmental legislations. In addition to the internal characteristics, our study further provides evidence of the external influence from other nearby adapting states through spatial policy diffusion. These findings shed light on the motivation for and obstacles to a state's adoption of adaptation policy and also provide implications for environmental federalism. [ABSTRACT FROM AUTHOR]

This paper explores questions concerning knowledge coproduction as applied to the extractive sector through an ex‐post evaluation of an environmental impact assessment (EIA) process for a proposed copper and gold mine in Panama. Theoretical underpinnings of knowledge are highlighted, and barriers or enablers to knowledge coproduction are explored, including syntactic, semantic, and pragmatic boundaries and trust building. Reflection is based on the authors' participation as EIA practitioners on the project. Knowledge sharing between the EIA project team and stakeholders are placed in the context of knowledge coproduction theory and application. Different types of knowledge—fast and slow, tacit and explicit, and traditional and expert—are integrated into an adapted version of Nonaka's knowledge spiral model, illustrating the progression of knowledge coproduction through various activities and actors in EIA. Findings support the contention that explicitly designing and implementing knowledge coproduction into EIA practice can help improve environmental governance in the extractive sector. [ABSTRACT FROM AUTHOR]

Drought has affected much of the western United States since about the year 2000, including the Upper Colorado River Basin (UCRB). Using a time series of UCRB streamflow derived from a tree‐ring based reconstruction of UCRB streamflow for the years 1 CE through 1905 CE, together with naturalized UCRB streamflow values for 1906 CE through 2021 CE, we identify 51 drought events, including the 2000–2021 drought. Although the recent 2000–2021 drought has been relatively severe, it is not the most severe of the UCRB drought events we identified. Results also indicate that natural variability combined with projected climate warming can result in UCRB drought events that are more severe than any drought since 1 CE. Plain Language Summary: A long and severe drought has affected much of the western United States since about the year 2000 CE, including the Upper Colorado River Basin (UCRB). Comparing this drought to past UCRB droughts (during 1 CE through 2021 CE), we find that the 2000–2021 drought is not the most severe UCRB drought. The results also suggest that natural variability combined with projected climate warming could result in UCRB drought events that are more severe than any drought since 1 CE. Key Points: We identify 51 drought events for the years 1 CE through 2021 CE for the Upper Colorado River Basin (UCRB)Twelve of the 51 UCRB droughts we identify were more severe than the 2000–2021 droughtNatural variability and/or a 1°C temperature increase can trigger UCRB droughts that are more severe than the 2000–2021 drought [ABSTRACT FROM AUTHOR]

Much of the attention surrounding local climate protection in the United States is associated with two networks: ICLEI Local Governments for Sustainability's Cities for Climate Protection and the U. S. Conference of Mayors' Climate Protection Agreement ( MCPA). However, the impact of these networks on member-city actions has not been clearly established. This paper examines whether, and to what extent, participation in climate networks leads to the implementation of greenhouse gas ( GHG)-reducing policies, above and beyond what would have been done in their absence. To account for the possibility that cities which join climate networks are systematically different from those that do not and control for self-selection induced bias, three statistical techniques-propensity score matching, Heckman full information maximum likelihood, and instrumental variables-are employed to estimate the 'treatment effect' of participation. Results suggest that impact is network specific: ICLEI membership causes small to moderate increases in cities' GHG-relevant activity, whereas the MCPA has no such effect. The characteristics of each network are evaluated in light of these findings. [ABSTRACT FROM AUTHOR]

International labour migration is a multidimensional process and primarily a family mechanism intended to reduce vulnerabilities associated with underlying inequalities. However, for immigrants, the break-up of physical contact with family members is an enduring feature of vulnerability in their communication with origins (often in developing countries). On the whole, family relationships are transformed: the absence of physical contact is traded-off with remittances sent home to family members. Remittances create potential for resilience by increasing human development of children, while reducing extreme poverty at the local level. Remittance flows are also an important source of foreign exchange for countries of origin. However, labour markets' polarization, backlash, and economic downturns at destinations (often in developed countries), and governments' moral hazard, currency revaluation, and production inertia at origins recreate vulnerabilities and disrupt the potential build-up of resilience. In fact, the re-creation of vulnerabilities largely outweighs the generation of resilience threads. The paper develops a typology that highlights the dynamic interaction between vulnerabilities and resilience, revealing the multiple aspects of people and remittances flows, the potential for mainstreaming migration policies into economic development, and the scale of the policy task to reduce vulnerabilities associated to international labour migration. [ABSTRACT FROM AUTHOR]

This article focuses on connected factors that contribute to United States (US) media reporting on anthropogenic climate change science. It analyses US newspapers and television news from 1995 to 2006 as well as semi-structured interviews with climate scientists and environmental journalists. Through analyses of power and scale, the paper brings together issues of framing in journalism to questions of certainty/uncertainty in climate science. The paper examines how and why US media have represented conflict and contentions, despite an emergent consensus view regarding anthropogenic climate science. [ABSTRACT FROM AUTHOR]

In March 2001, President G.W. Bush announced that the United States had abandoned the ratification of the Kyoto Protocol. This paper describes the historical background as well as the political reasons and mechanisms behind the Bush administration's decision. Moreover, it deals with two alternative policy proposals, which have emerged at the US federal and the state level since then. The paper then highlights some important differences between EU and US climate change policies. The most important difference is that the EU wants global warming mitigation and the US, if necessary at all, is emphasizing the need to adapt to climate change. The paper concludes by suggesting that if a post-Kyoto treaty wants to bring the US back on board it will need to address this difference. Copyright © 2003 John Wiley & Sons, Ltd and ERP Environment. [ABSTRACT FROM AUTHOR]

To better understand the regional changes in summertime temperatures across the conterminous United States (CONUS), we adopt a recently developed machine learning framework that can be used to reveal the timing of emergence of forced climate signals from the noise of internal climate variability. Specifically, we train an artificial neural network (ANN) on seasonally averaged temperatures across the CONUS and then task the ANN to output the year associated with an individual map. In order to correctly identify the year, the ANN must therefore learn time‐evolving patterns of climate change amidst the noise of internal climate variability. The ANNs are first trained and tested on data from large ensembles and then evaluated using observations from a station‐based data set. To understand how the ANN is making its predictions, we leverage a collection of ad hoc feature attribution methods from explainable artificial intelligence (XAI). We find that anthropogenic signals in seasonal mean minimum temperature have emerged by the early 2000s for the CONUS, which occurred earliest in the Eastern United States. While our observational timing of emergence estimates are not as sensitive to the spatial resolution of the training data, we find a notable improvement in ANN skill using a higher resolution climate model, especially for its early twentieth century predictions. Composites of XAI maps reveal that this improvement is linked to temperatures around higher topography. We find that increases in spatial resolution of the ANN training data may yield benefits for machine learning applications in climate science. Plain Language Summary: While temperatures around the world continue to warm due to human‐caused climate change, some areas have observed smaller temperature trends than others. Understanding this regional variability in the rate of warming is important when assessing future projections. One location that has observed less warming is across the United States during their summer season. To evaluate temperature variability in this region using real‐world observations and climate model simulations, we use a statistical method from artificial intelligence called neural networks. The goal of the neural network setup is to learn temperature patterns across the United States and then identify whether climate change effects have exceeded the range of natural variability that has occurred in the past. This is called the timing of emergence (ToE), which is the first year that the effect has clearly appeared. We find that the average United States minimum temperature increase has already emerged in historical records. However, we find no ToE for the average maximum temperature, other than in the Western United States. Another important finding of this study is that by using higher resolution climate model data (i.e., more latitude and longitude points), we find better accuracy in the neural network predictions. Key Points: Forced temperature changes have emerged in observations during summer in the United States as detected by an artificial neural networkIncreasing spatial resolution improves neural network skill for predicting the year of a given summer temperature mapWestern United States land surface climate properties contribute to earlier timing of emergence predictions for the SPEAR climate model [ABSTRACT FROM AUTHOR]

There is growing urgency for improved public and commercial services to support a resilient, secure, and thriving United States (US) in the face of mounting decision‐support needs for environmental stewardship and hazard response, as well as for climate change adaptation and mitigation. Sustained space‐based Earth observations are critical infrastructure to support the delivery of science and decision‐support information with local, national, and global utility. This is reflected in part through the United States' sustained support of a suite of weather and land‐imaging satellites. However, outside of these two areas, the US lacks an overarching, systematic plan or framework to identify, prioritize, fund, and implement sustained space‐based Earth observations to meet the Nation's full range of needs for science, government policy, and societal support. To aid and accelerate the discussion on our nation's needs, challenges and opportunities associated with sustained critical space‐based Earth observations, the Keck Institute for Space Studies (KISS) sponsored a multi‐week think‐tank study to offer ways forward. Based on this study, the KISS study team suggests the establishment of a robust coordination framework to help address US needs for sustained Earth observations. This coordination framework could account for: (a) approaches to identify and prioritize satellite observations needed to meet US needs for science and services, (b) the rapidly evolving landscape of space‐based Earth viewing architecture options and technology improvements with increasing opportunities and lower cost access to space, and (c) the technical and programmatic underpinnings required for proper and comprehensive data stewardship to support a wide range of research and public services. Plain Language Summary: The Keck Institute of Space Studies has carried out a think tank study to codify best practices, articulate successes, and identify challenges and opportunities in the prioritization, acquisition, curation, and stewardship of sustained space‐based Earth observations. The goal of the study is to accelerate discussion and plans for a greater and more impactful US contribution to the global satellite observing system that will support decision‐making regarding climate change, environmental hazards, and national security. Based on this study, the KISS study team suggests the establishment of a nimble and responsive coordination framework to help guide and shepherd US concerns regarding sustained Earth observations. This coordination framework should account for: (a) approaches to identify and prioritize satellite observations needed to meet US needs for science and services, (b) the rapidly evolving landscape of space‐based Earth viewing architecture options and technology improvements with increasing opportunities and lower cost access to space and (c) the technical and programmatic underpinnings required for proper and comprehensive data stewardship with a broad science and services user base in mind. Key Points: There is growing urgency for improved public and commercial services to support a resilient, secure, and thriving USSpace‐based Earth observations represent an essential component of the infrastructure needed to support the delivery of needed informationThe US would benefit from an overarching plan for sustained Earth observations to support our science, policy, and resilience goals [ABSTRACT FROM AUTHOR]

Electricity and water systems in the Western US (WUS) are closely connected, with hydropower comprising 20% of total annual WUS generation, and electricity related to water comprising about 7% of total WUS electricity use. Because of these interdependencies, the threat of climate change to WUS resources will likely have compounding electricity impacts on the Western Interconnect grid. This study describes a WUS‐wide water system model with a particular emphasis on estimating climate impacts on hydropower generation and water‐related electricity use, which can be linked with a grid expansion model to support climate‐resilient electricity planning. The water system model combines climatically‐driven physical hydrology and management of both water supply and demand allocation, and is applied to an ensemble of 15 climate scenarios out to 2050. Model results show decreasing streamflow in key basins of the WUS under most scenarios. Annual water‐related electricity use increases up to 4%, and by up to 6% during the summer months, driven by growing agricultural demands met increasingly through a shift toward energy‐intensive groundwater to replace declining surface water. Total annual hydropower generation changes by +5% to −20% by mid‐century but declines in most scenarios, with decreases in summer generation by up to nearly −30%. Water‐related electricity use increases tend to coincide with hydropower generation declines, annually and seasonally, demonstrating the importance of concurrently evaluating the climate signal on both water‐for‐energy and energy‐for‐water to inform planning for grid reliability and decarbonization goals. Plain Language Summary: Electricity and water systems in the Western United States (WUS) have a strong dependency. Water fuels hydropower generation and electricity is used to pump, transport, treat, heat, and dispose of water. Climate change poses a serious threat to water availability in the WUS and is likely to also affect hydropower generation and electricity use related to water. This study develops a WUS water system model to evaluate the impact of a set of climate change scenarios on the dynamic interplay between water availability and demand and hydropower generation and electricity use by the water sector by 2050. We find that in many key basins, streamflow decreases under the climate scenarios. At the same time, reliance on groundwater increases to meet growing agricultural water demand. Hydropower generation shows decreases in most cases while energy use related to water increases. Because these hydropower generation declines tend to occur during periods when electricity demand for water grows, electricity grid planners in the Western Interconnect will benefit from this type of study by informing future grid buildouts that maintain reliability and decarbonization goals. Key Points: Interactions among hydro‐climate, hydropower, and water's energy use are critical for evaluating Western US (WUS) water‐energy climate risksUnder climate change, our WUS water model finds declining streamflows, growing agricultural demands, and increased groundwater useWith warming and drying, water‐related energy use grows while hydropower generation decreases under most climate scenarios by mid‐century [ABSTRACT FROM AUTHOR]

Accurate assessment of changes in water availability with changing climate is vital for effective mitigation and adaptation. In this research, we employ a parsimonious Budyko curve method to evaluate changes in water availability under low‐ (SSP126) and high‐emission (SSP585) scenarios for 331 river basins in the contiguous United States. We also assess the relative role of changes in precipitation (∆P) and potential evapotranspiration (∆PET) with changing climate on the increase in water availability vulnerability. Results highlight that around 43% (28%) of basins are projected to experience increased vulnerability to changing climate in high‐emission (low‐emission) scenarios. Sub‐humid basins are most often impacted, while arid and semi‐arid basins exhibit lower sensitivity to changes. Intriguingly, ∆PET emerges as the dominant control on vulnerability, surpassing ∆P, particularly under SSP585 scenario. The analysis prompts water managers to focus on long‐term mitigation planning and scientists to further constraint climate and water budget forecasts in affected basins. Plain Language Summary: Assessment of changes in water availability because of the changing climate is useful for mitigation and adaptation planning. In this study, water availability change in river basins in the contiguous United States is assessed. Which basins will become more vulnerable in terms of reduced water availability in the future climate and how the vulnerability changes within different aridity zones is studied. The study presents a novel methodology to assess and quantify whether the changes in potential evapotranspiration or precipitation are the main driver of future water vulnerability. We find that vulnerability increase due to an increase in potential evapotranspiration to be large. From the different aridity zones, sub‐humid basins are projected to most often experience an increase in vulnerability. Key Points: Changes in water availability under climate change scenarios are evaluatedSub‐humid basins are most often impactedVulnerability increase is large due to increase in Potential Evapotranspiration [ABSTRACT FROM AUTHOR]

Probabilistic Seismic Hazard Analysis (PSHA) is a methodology that estimates the likelihood that various levels of earthquake-caused ground motions will be exceeded at a given location in a given future time period. Due to large uncertainties in all of the geosciences data and in their modeling, multiple model interpretations are often possible. This leads to disagreements among the experts, which in the past has led to disagreement on the selection of a ground motion for design at a given site. This paper reports on a project, co-sponsored by the U.S. Nuclear Regulatory Commission, the U.S. Department of Energy,and the Electric Power Research Institute, that was undertaken to review the state-of-the-art and improve on the overall stability of thePSHA process, by providing methodological guidance on how to performa PSHA. The project reviewed past studies and examined ways to improve on the present state-of-the-art. In analyzing past PSHA studies, the most important conclusion is that differences in PSHA results are commonly due to process rather than technical differences. Thus, the project concentrated heavily on developing process recommendations, especially on the use of multiple experts, and this paper reports on those process recommendations. The problem of facilitating and integrating the judgments of a diverse group of experts is analyzed in detail. The authors believe that the concepts and process principles applyjust as well to non-earthquake fields such as volcanic hazard, floodrisk, nuclear-plant safety, and climate change. [ABSTRACT FROM AUTHOR]

It is often held that the UK has been something of a leader in its response to climate change, and that the USA has been more of a laggard. Whilst much of this debate relates to government policy, in this paper we consider whether this is true when it comes to corporate action on climate change. We use the retail sector to explore this question. This sector is important because of its own greenhouse gas (GHG) emissions and because of the emissions it influences through its supply chains and value chains. On the basis of extensive reviews of corporate reports and other publically available data, we find that companies in the UK are some way ahead of their US counterparts in terms of the actions they are taking (in particular in relation to their willingness to focus on their supply-chain-related emissions), the ambition of the emission reduction targets that they are setting for themselves, and (while acknowledging the difficulties in making direct performance comparisons) the rates of improvement in their energy consumption and GHG emissions. We therefore conclude that at least some of the wider claims about the relative performance of the UK and the USA on climate change are mirrored in the manner in which corporations are responding to climate change. Copyright © 2014 John Wiley & Sons, Ltd and ERP Environment [ABSTRACT FROM AUTHOR]

Climate change will have potentially significant effects on freshwater quality due to increases in river and lake temperatures, changes in the magnitude and seasonality of river runoff, and more frequent and severe extreme events. These physical impacts will in turn have economic consequences through effects on riparian development, river and reservoir recreation, water treatment, harmful aquatic blooms, and a range of other sectors. In this paper, we analyze the physical and economic effects of changes in freshwater quality across the contiguous U.S. in futures with and without global-scale greenhouse gas mitigation. Using a water allocation and quality model of 2119 river basins, we estimate the impacts of various projected emissions outcomes on several key water quality indicators, and monetize these impacts with a water quality index approach. Under mitigation, we find that water temperatures decrease considerably and that dissolved oxygen levels rise in response. We find that the annual economic impacts on water quality of a high emissions scenario rise from $1.4 billion in 2050 to $4 billion in 2100, leading to present value mitigation benefits, discounted at 3%, of approximately $17.5 billion over the 2015-2100 period. [ABSTRACT FROM AUTHOR]

This study empirically estimates the effects of climate on land‐use change across the conterminous United States and uses the empirical model to simulate the effects of a range of future climate change scenarios on the allocation of land to forestry, agriculture, and development. Ricardian estimation linking climate with the net returns to land production is integrated with a discrete‐choice estimation of plot‐level land‐use change. Comparing projected land‐use changes across scenarios, we find that drier and warmer climate scenarios favor forest land, wetter and cooler climate scenarios favor developed land, and wetter and warmer climate scenarios favor crop lands. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Botanical careers are more important than ever, given that environmental challenges such as climate change and deforestation threaten plants daily and because plants contribute to solutions to these problems. Plants act as our sources of food, medicine, textiles, and oxygen, which means finding ways to mitigate these environmental challenges is crucial. Despite this, little is known about what career opportunities exist for botanists outside of academia and how well academia is training graduate students for these careers. This study centers on the current state of academic botanical careers and how well students completing post‐baccalaureate degrees (herein referred to as graduate students) are being prepared to fill careers within the botanical workforce. Summary: Plant science plays a crucial role in our society and in ongoing efforts to address many global challenges, including food insecurity and climate change. Despite a predicted increase in botanical career opportunities, little is known about how well academia is training graduate students for careers outside of academia.To further our understanding of the current state of academic training for botanical careers, we surveyed 85 faculty and 40 graduate students working in academia in the plant sciences in the United States.We found that the top challenges to university professors in academia are lack of support staff and funding, whereas students completing their post‐baccalaureate degrees cited finances and lack of supportive mentoring as their top challenges. Despite the fact that most graduate students surveyed wanted a career at a research‐intensive university, many botanists in academia are retiring without being replaced by more botanists. Faculty expertise is also misaligned with needs from industry and government employers, causing challenges to training graduate students for these careers outside of academia. Although our data point to a lack of career opportunities within academia, we also note that current graduate student education still emphasizes such careers and is not properly preparing graduate students for the careers they are more likely to obtain within the private and government sectors.We discuss the implications of these findings and present several recommendations for preparing future generations of plant scientists for more realistic career trajectories. [ABSTRACT FROM AUTHOR]

Background Occupational heat-related mortality is not well studied and risk factors remain largely unknown. This paper describes the epidemiological characteristics of heat-related deaths among workers in the US 2000-2010. Methods Fatality data were obtained at the Bureau of Labor Statistics from the confidential on-site Census of Fatal Occupational Injuries database. Fatality rates and risk ratios with 95% confidence intervals were calculated by year, sex, age group, ethnicity, race, state, and industry. Results Between 2000 and 2010, 359 occupational heat-related deaths were identified in the U.S., for a yearly average fatality rate of 0.22 per 1 million workers. Highest rates were found among Hispanics, men, the agriculture and construction industries, the state of Mississippi, and very small establishments. Conclusions This study provides the first comprehensive national profile of heat-related deaths in the U.S. workplace. Prevention efforts should be directed at small businesses and at industries and individuals with the highest risk. Am. J. Ind. Med. 58:203-211, 2015. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

As the United States struggles with national solutions to address climate change, state and local governments have become leaders in both mitigation and adaptation policy. Although a significant and growing body of research targets these policies, most studies have assumed common factors motivating both adaptation and mitigation policy adoption. There remains a need for more research on cities of all sizes, their adoption of specific local policies, the factors motivating those choices, and whether the influences for mitigation differ from those that motivate adaptation. The paper uses data from a new survey of over 200 local governments in eleven states of the Great Plains region, including measures distinguishing between mitigation and adaptation policies. These data are employed to test the relative influence of factors from three areas: the policy environment, the attitudes of governmental actors, and community atmosphere, in explaining observed variation in the adoption of climate change policies. [ABSTRACT FROM AUTHOR]

Cumulative research has demonstrated both the reality and potential impacts of global climate change. In this paper, we focus on the nature of climate-related policy development at a subnational level by considering actions undertaken by municipal governments in the United States. Specifically, our research objective is to provide an initial descriptive assessment of how local governments utilize what we term research-based knowledge (RBK) to inform their planning and action strategies around climate change mitigation and adaptation. Doing so is important because local governments in the United States represent a key source of policy innovation on climate change issues and because there is relatively little existing research on exactly how RBK might be utilized in this domain. Our comparative case descriptions from four locations suggest that city officials use RBK in both strategic and political manners. That is, while using existing information and policy networks and generally relying on outside experts for rational comprehensive evaluation, climate-related RBK often both justifies the existing position of local officials (strategic use) and legitimizes previous policy choices (political use). The implications of this initial assessment can assist in testing future theoretic arguments on the exact nature of RBK acquisition and use surrounding climate change policymaking. [ABSTRACT FROM AUTHOR]

Small island developing States ( SIDS) have narrow resource bases and are usually extremely reliant on fossil fuel based energy for transport and electricity generation. These island economies are thus particularly vulnerable to the impacts of peak oil and also to climate change, impacts which are likely to not only hamper economic development but also adversely affect the quality of life of local inhabitants. In order to reduce the vulnerability of SIDS to peak oil, an urgent transition to renewable sources of energy is necessary. This paper propounds that the reform of power sector that took place in Caribbean and Pacific SIDS (particularly between 1970 and 2000) should have been viewed as an opportunity to re-orient power producers away from the proclivity to utilise conventional fossil fuel uses. Reasons why reform measures did not result in a substantive transition are put forward. Moreover, recommendations towards facilitating a transition to renewable energy in the power sector through future reforms are proposed. [ABSTRACT FROM AUTHOR]

The promulgation of the Mandatory Reporting of Greenhouse Gases Rule stands as the first step to developing a comprehensive national approach to climate change. However, what role, if any, did interest groups play in the development of this rule? This paper applies Kingdon's multiple streams model as a descriptive framework to analyze interview data for this rule to better understand interest group involvement across all the stages of the rule-making process (rule development, notice and comment phase, and rule finalization). Our research suggests that interest groups were indeed influential throughout the process, but those involved during rule development were clearly at an advantage. [ABSTRACT FROM AUTHOR]

Climate change and food security have become critical issues in the agricultural policy agenda. Although global warming is expected to increase both the frequency and severity of heat stress on dairy cattle, there are very few economic studies focusing on this issue. This paper contributes to the literature by integrating the frontier methodology, commonly used in applied production economics, with heat stress indexes used by animal scientists but largely ignored by economists. Our econometric models are useful to quantify gross benefits expected from adaptation to climatic conditions represented by the Temperature Humidity Index (THI) and alternatively by the Equivalent Temperature Index (ETI). Stochastic production frontier analysis is used to measure technical efficiency for an unbalanced panel of 103 dairy farms located in Florida and Georgia. Five alternative model specifications are evaluated. The results reveal that both THI and ETI have a significant nonlinear negative effect on milk production. The climatic indexes when incorporated in the frontier specification absorb some of the output shortfall that otherwise would be attributable to inefficiency. The results indicate that using fans combined with sprinklers is an effective adaptation to offset output losses stemming from heat stress conditions. [ABSTRACT FROM AUTHOR]

Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency. Plain Language Summary: Winter storms can have devastating socioeconomic impacts across the United States. Climate models are used to understand and predict these winter storms and how they might change in the future, therefore helping to inform climate policy and emergency services. It is essential that we evaluate these climate models so that their performance and accuracy can be optimized. One way of evaluating climate models is to assess their ability in reproducing the large‐scale atmospheric conditions which occur during extreme events. Here we apply a cyclone tracking algorithm and self‐organizing maps, a machine‐learning approach, to automate the process of identifying key patterns associated with historical winter storm activity. We then use this approach to assess if CMIP6 climate models are able to reproduce the same patterns including the winter storm frequency and intensity. Our results show that, regardless of resolution, most CMIP6 models struggle to simulate the more extreme patterns and tend to favor weaker patterns that are not as conducive to cyclone formation. As a result, most models simulate too few winter storms, however, the error in storm intensity is more varied, with some models producing stronger storms and others producing weaker storms on average. Key Points: Despite resolution, CMIP6 models struggle to reproduce amplified synoptic patterns over the US, with a robust bias toward zonal patternsMost CMIP6 models produce too few cyclones over the northeastern US, while model errors are more varied when considering cyclone intensityIncreased resolution increases the number and intensity of simulated extratropical cyclones but does not improve model representation of synoptic patterns [ABSTRACT FROM AUTHOR]

Mortality due to extreme temperatures is one of the most worrying impacts of climate change. In this analysis, we use historic mortality and temperature data from 106 cities in the United States to develop a model that predicts deaths attributable to temperature. With this model and projections of future temperature from climate models, we estimate temperature‐related deaths in the United States due to climate change, changing demographics, and adaptation. We find that temperature‐related deaths increase rapidly as the climate warms, but this is mainly due to an expanding and aging population. For global average warming below 3°C above pre‐industrial levels, we find that climate change slightly reduces temperature‐related mortality in the U.S. because the reduction of cold‐related mortality exceeds the increase in heat‐related deaths. Above 3°C warming, whether the increase in heat‐related deaths exceeds the decrease in cold‐related deaths depends on the level of adaptation. Southern U.S. cities are already well adapted to hot temperatures and the reduction of cold‐related mortality drives overall lower mortality. Cities in the Northern U.S. are not well adapted to high temperatures, so the increase in heat‐related mortality exceeds the reduction in cold‐related mortality. Thus, while the total number of climate‐related mortality may not change much, climate change will shift mortality in the U.S. to higher latitudes. Plain Language Summary: Deaths due to extreme temperatures is one of the most important impacts of climate change. Here we estimate future temperature related deaths in the US using climate projection, population projection, and adaptation assumptions. We find that in 3°C of global warming level, temperature‐related deaths will increase by a factor of five, mostly due to aging and increasing population. Below 3°C warming, impact of climate change slightly decreases temperature‐related deaths, because the decrease in cold‐related deaths exceeds the increase in heat‐related deaths. Above 3°C warming, impact of climate change depends on the level of adaptation. Furthermore, we find that temperature‐related mortality shifts Northward. This is due to increase of heat‐related deaths in Northern cities, which are currently poorly adapted to heat. Key Points: Temperature‐related deaths in the U.S. will increase by a factor of 5 with 3°C of warming, mostly due to aging and increasing populationImpact of climate change is not significant until 3°C of global warming, and it depends on the level of adaptation beyond that pointTemperature‐related deaths will shift Northward, due to increasing heat‐related deaths in poorly heat‐adapted Northern cities [ABSTRACT FROM AUTHOR]

Forests are critical to the planetary operational system and evolved without human management for millions of years in North America. Actively managing forests to help them adapt to a changing climate and disturbance regime has become a major focus in the United States. Aside from a subset of forests wherein wood production, human safety, and experimental research are primary goals, we argue that expensive management interventions are often unnecessary, have uncertain benefits, or are detrimental to many forest attributes such as resilience, carbon accumulation, structural complexity, and genetic and biological diversity. Natural forests (i.e., those protected and largely free from human management) tend to develop greater complexity, carbon storage, and tree diversity over time than forests that are actively managed; and natural forests often become less susceptible to future insect attacks and fire following these disturbances. Natural forest stewardship is therefore a critical and cost effective strategy in forest climate adaptation. [ABSTRACT FROM AUTHOR]

Changes in land use and land cover alter the local energy balance and contribute to distinct urban climates. This paper presents a local-scale above-canopy study of intra-urban land cover mixes in two cities to analyse the relative effects of surface morphology and local climate on the surface energy balance (SEB). The study is conducted for urban areas in Phoenix, Arizona, and Portland, Oregon, cities with distinct climates but similarly warm and dry summers. A Local-Scale Urban Meteorological Parameterization Scheme (LUMPS) is used to analyse the relative contributions of local weather extremes and land cover variations on the urban energy balance. The partitioning of net all-wave radiation into turbulent sensible and latent heat fluxes as well as heat storage is investigated for a typical dry summer month and two extreme weather scenarios in the two cities. Results of sensitivity analyses show that incoming solar radiation is an important driver of the SEB in LUMPS and should be considered in the generation of climate scenarios. The relationship between individual land cover fractions and SEB fluxes is not clear because of interrelated effects of surface characteristics in the land cover mix. Daytime Bowen ratios vary inversely with vegetation fraction between and within cities for all weather scenarios. Impervious surface cover is positively correlated to the available energy that is partitioned into sensible heat. Cumulative evapotranspiration (ET) is similar for average weather conditions across medium wet sites in Phoenix and Portland but varies more in Portland than in Phoenix under extreme weather conditions. Results suggest that land cover manipulation could offset influences of weather extremes on ET in Portland to a certain degree but not in Phoenix. These findings highlight the importance of spatial and climatic context in the urban design process to mitigate the effects of urbanization. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT The multi-dimensional nature of the current global crisis requires a holistic approach in addressing economic, social and ecological problems. Following the crisis, several organizations started to publish reports on a concept called Green New Deal (GND) with reference to the New Deal policies of the 1930s in the USA. Since then, the concept has gained increasing popularity among the public. On the other hand, it fuelled a heated discussion between its supporters and ecosocialists. The aim of this paper is to highlight the points at which GND supporters and ecosocialists converge and diverge, and discuss critically the transformative capacity of different GND proposals. We conclude that GND policies can help to set the stage for the transformation long sought by the ecosocialist agenda, and hence from this perspective, these two approaches can be seen as complementary rather than substitutes. Copyright © 2012 John Wiley & Sons, Ltd and ERP Environment. [ABSTRACT FROM AUTHOR]

Multilevel governance poses several challenges for the politics of climate change. On the one hand, the unequal distribution of power and interests can serve as a barrier to implementing coherent policy at a federal level. On the other, these features also enable policy leadership among sub-federal units. In the context of wide variation in climate policy at both national and sub-federal levels in Canada and in the United States, this paper utilizes an original data set to examine public attitudes and perceptions toward climate science and climate change policy in two federal systems. Drawing on national and provincial/state level data from telephone surveys administered in the United States and in Canada, the paper provides insight into where the public stands on the climate change issue in two of the most carbon-intensive federal systems in the world. The paper includes the first directly comparable public opinion data on how Canadians and Americans form their opinions regarding climate matters and provides insight into the preferences of these two populations regarding climate policies at both the national and sub-federal levels. Key findings are examined in the context of growing policy experiments at the sub-federal level in both countries and limited national level progress in the adoption of climate change legislation. [ABSTRACT FROM AUTHOR]

Assisted colonization could help prevent the extinction of threatened and endangered species by intentionally moving a species to a region where it has not occurred in the recent past, but should survive under future climate scenarios. Where species are naturally localized and confined to patchy habitats, assisted colonization might be the only means for population dispersal across human landscape barriers such as urban and agriculture areas. The major risk associated with assisted colonization is introducing ecologically harmful species. Previous policy papers have described management options for deciding when to move a species to mitigate for climate change. We build on this previous work by examining management options and policy solutions for assisted colonization under the U.S. Endangered Species Act (ESA). On its surface, the ESA statutory language appears to provide the legal framework for allowing assisted colonization, as the U.S. Congress gave the U.S. Fish and Wildlife Service (USFWS) broad discretion to manage populations of endangered species. However, current USFWS regulations are an impediment to assisted colonization for many endangered animal species, whereas regulations do not necessarily restrict assisted colonization of endangered plants. Because of this discrepancy, we recommend a review of the regulatory language governing movements of endangered species. [ABSTRACT FROM AUTHOR]

Some expected changes in climate resulting from human greenhouse gas emissions are clear and well documented, but others may be harder to predict because they involve extreme weather events or heretofore unusual combinations of weather patterns. One recent example of unusual weather that may become more frequent with climate change occurred in early spring 2007 when a large Arctic air mass moved into the eastern United States following a very warm late winter. In this paper, we document effects of this freeze event on Walker Branch, a well-studied stream ecosystem in eastern Tennessee. The 2007 spring freeze killed newly grown leaf tissues in the forest canopy, dramatically increasing the amount of light reaching the stream. Light levels at the stream surface were sustained at levels considerably above those normal for the late spring and summer months due to the incomplete recovery of canopy leaf area. Increased light levels caused a cascade of ecological effects in the stream beginning with considerably higher (two–three times) rates of gross primary production (GPP) during the late spring and summer months when normally low light levels severely limit stream GPP. Higher rates of stream GPP in turn resulted in higher rates of nitrate (NO3−) uptake by the autotrophic community and lower NO3− concentrations in stream water. Higher rates of stream GPP in summer also resulted in higher growth rates of a dominant herbivore, the snail Elimia clavaeformis. Typically, during summer months net NO3− uptake and snail growth rates are zero to negative; however, in 2007 uptake and growth were maintained at moderate levels. These results show how changes in forest vegetation phenology can have dramatic effects on stream productivity at multiple trophic levels and on nutrient cycling as a result of tight coupling of forest and stream ecosystems. Thus, climate change-induced changes in canopy structure and phenology may lead to large effects on stream ecosystems in the future. [ABSTRACT FROM AUTHOR]

The Endangered Species Act of 1973 is one of the nation's most significant and most controversial environmental laws. Over three-and-a-half decades, it has profoundly influenced both private and federal agency behavior. As the scope of that influence has come to be recognized, a law that is ostensibly to be guided by science has inevitably become entangled in politics. The generality of many of the law's key provisions has produced continuing uncertainty and conflict over some basic issues. Among these are what species or other taxa are potentially subject to the Act's protections, what the extent of those protections is, and whether the Act's ultimate goal of recovery is one that is being effectively achieved. New challenges face the administrators of this law, including that of incorporating climate change considerations into the decisions made under the Act, and responding to the information made available by recent advances in genetics. This paper provides a brief overview of the Endangered Species Act's history and its key provisions, and a more in-depth look at some of the current and recurrent controversies that have attended its implementation. [ABSTRACT FROM AUTHOR]

The detection and mapping of canopy disturbance caused by natural events such as cyclones in tropical rainforests is important for monitoring and understanding rainforest dynamics and recovery. In February 1999 tropical cyclone Rona crossed the coastline of Far North Queensland, Australia, causing significant damage to the rainforest canopy in some areas. This paper examines the application of multitemporal canopy digital elevation models (DEMs) generated by a NASA-operated airborne radar mapping system called TOPSAR in 1996 and 2000, for detection of canopy disturbance caused by cyclone damage. Canopy damage was mapped here by identifying areas with a significant decrease in canopy height estimated from the difference of the 1996 and 2000 TOPSAR DEMs. Conventional aerial photographs, flown shortly after the cyclone (March 1999), were used to validate the resulting map of cyclone damaged rainforest canopy. The results showed that the DEM-derived canopy damage map performed reasonably well when comparing the spatial distribution and size of damaged areas, while taking into account the time difference between cyclone damage and the second radar acquisition. Some errors were encountered on the steeper slopes which were related to terrain distortions inherent in radar images of steep terrain. The height accuracy of the DEM was close to the depth of some of the gaps being mapped, which also contributed to errors. Even so, the results demonstrate there may be potential for weather-independent, regional-scale mapping of forest canopy change from imaging radar that is not always possible from traditional optical means of measuring canopy elevation, for example, airborne laser data and stereo aerial photography. This may be possible in relatively flat areas, provided the second radar acquisition occurs within months of the damaging event. Further algorithm refinement is required to improve its robustness and the range of topographies where this approach can provide reliable estimates of the extent of canopy disturbance. [ABSTRACT FROM AUTHOR]

Atmospheric measurements and land-based inventories imply that terrestrial ecosystems in the northern hemisphere are taking up significant amounts of anthropogenic cabon dioxide (CO2) emissions; however, there is considerable disagreement about the causes of this uptake, and its expected future trajectory. In this paper, we use the ecosystem demography (ED) model to quantify the contributions of disturbance history, CO2 fertilization and climate variability to the past, current, and future terrestrial carbon fluxes in the Eastern United States. The simulations indicate that forest regrowth following agricultural abandonment accounts for uptake of 0.11 Pg C yr−1 in the 1980s and 0.15 Pg C yr−1 in the 1990s, and regrowth following forest harvesting accounts for an additional 0.1 Pg C yr−1 of uptake during both these decades. The addition of CO2 fertilization into the model simulations increases carbon uptake rates to 0.38 Pg C yr−1 in the 1980s and 0.47 Pg C yr−1 in the 1990s. Comparisons of predicted aboveground carbon uptake to regional-scale forest inventory measurements indicate that the model's predictions in the absence of CO2 fertilization are 14% lower than observed, while in the presence of CO2 fertilization, predicted uptake rates are 28% larger than observed. Comparable results are obtained from comparisons of predicted total Net Ecosystem Productivity to the carbon fluxes observed at the Harvard Forest flux tower site and in model simulations free-air CO2 enrichment (FACE) experiments. These results imply that disturbance history is the principal mechanism responsible for current carbon uptake in the Eastern United States, and that conventional biogeochemical formulations of plant growth overestimate the response of plants to rising CO2 levels. Model projections out to 2100 imply that the carbon uptake arising from forest regrowth will increasingly be dominated by forest regrowth following harvesting. Consequently, actual carbon storage declines to near zero by the end of the 21st century as the forest regrowth that has occurred since agricultural abandonment comes into equilibrium with the landscape's new disturbance regime. Incorporating interannual climate variability into the model simulations gives rise to large interannual variation in regional carbon fluxes, indicating that long-term measurements are necessary to detect the signature of processes that give rise to long-term uptake and storage. [ABSTRACT FROM AUTHOR]

Aim Climate change has the potential to have an impact on the distribution of ticks and tick-borne diseases. This paper identifies the changes in climate suitability for the tick Rhipicephalus (Boophilus) microplus in the Americas by analysing climate data for the period 1950–99. Location The model was applied to the American continent. Methods A model based on Environmental Niche Modelling was used on a gridded (0.5°) long-term (1950–99) climate data set. A map of the core range of the species was constructed, and areas where habitat suitability (HS) changes suddenly over short time periods were identified as regions of high sensitivity. Tendency of climate in the continent was evaluated and scenarios constructed for 2025 and 2050. Results Regions of high sensitivity included the southern USA, Mexico and western and central Argentina. Analysis of climate variables in these regions identified water vapour pressure deficit and evaporation as underlying the high sensitivity of habitat suitability in the USA and Mexico, and showed that episodes of high variability are linked to the El Niño Southern Oscillation. Projections of the tendency of HS as observed for the 1950–99 period point to an increase in this value in parts of the southern USA and in central Argentina, a finding that can be attributed to the progressive increase in minimum and yearly averaged temperatures. Conclusions Short-term changes in climate may drive the system into unstable situations with sudden changes in habitat suitability for the target tick in specific zones of the Americas. Results suggest an increased abiotic (climate) suitability for R. microplus in areas whose habitat is currently unsuitable for this species. [ABSTRACT FROM AUTHOR]