Department of Geography

Book Review

Margins are central rather then peripheral to defining political identities. Italian national identity, though often seen as a fragile construct, is by no means unique in this regard. National identities must be constantly in question in order to thrive. Three geopolitical moments or forces are identified as having contributed at different times and in distinctive ways to the spatial construction of Italian identity: the border question, the immigrant/emigrant experience, and the North-South regional division.

Since the collapse of the postwar Italian party system in 1992-3, Italian politics has been dominated by the figure of Silvio Berlusconi, undoubtedly the major politician on the political center-right and elected as prime minister successively in 1994, 2001, and 2008. The image of Berlusconi as Italy’s political leader is often seen by commentators as much more positive at home than it has been abroad. Some well known foreign media, for example, have been much more consistently negative about Berlusconi’s dual role as media baron and political leader than have domestic media (and considerable public opinion) in Italy. If so, then Berlusconi’s exit from a central position in Italian politics may create external relief that he is gone and improved regard for Italy as a whole but at the expense of a huge “hole” that his absence may create domestically. On close analysis, however, The presumed gap between views of Berlusconi at “home” and “abroad” looks smaller, however, than conventional wisdom would suggest. At least over the recent course of his political career, he has stimulated a similar range of increasingly attitudinal negative responses both in Italy and elsewhere, although with variations over time everywhere and from place to place outside of Italy. These responses are increasingly negative, both at home and abroad. Berlusconi’s reputation is very much related to popular perceptions of his practical successes and failures as a leader and to what sort of leader he has actually been. It is not simply the result of a “battle” of media images without substantive content. This is encouraging news for those looking towards a future in which Italian politics will be less dominated by popular media such as television and its presumed manipulation of a totally pliant electorate. The exit of the “big seducer” will leave a troubling legacy of unresolved problems while also creating openings for a political future in which Italians may be more collectively invested.

"Sovranismo" has become the “go-to” word to use in contrasting those advocating “take back control” and nationalism against the “globalists” who are the bête noire of populism. This paper discusses the recent provenance of the word and the impluses that underlie it. It then considers the various arguments for sovranismo more broadly. The final section discusses the actual history of state sovereignty and suggests that current usage lacks much understanding of its complexities.

Summer temperature extremes can have large impacts on humans and the biosphere, and an increase in heat extremes is one of the most visible symptoms of climate change. Multiple mechanisms have been proposed that would predict faster warming of heat extremes than typical summer days, but it is unclear whether this is occurring. Here, we show that, in both observations and historical climate model simulations, the hottest summer days have warmed at the same pace as the median globally, in each hemisphere, and in the tropics from 1959 to 2023. In contrast, the coldest summer days have warmed more slowly than the median in the global average, a signal that is not simulated in any of 262 simulations across 28 CMIP6 models. The observed stretching of the cold tail indicates that observed summertime temperatures have become more variable despite the lack of hot day amplification. The interannual variability and trend in the warming of both hot and cold extremes compared to the median can be explained from a surface energy balance perspective based on changes in net surface radiation and evaporative fraction. Tropical hot day amplification is projected to emerge in the future (2024-2099, SSP3-7.0 scenario), while Northern Hemisphere heat extremes are expected to continue to follow the median.

Observation of glacier surface characteristics through remotely sensed time-series data is essential for understanding glacier seasonality, mass balance, and long-term trends. Yet, the reliability of these observations depends significantly on the quality of the time-series data. This study presents a meticulous preprocessing scheme to improve the quality of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Snow Index (NDSI) time-series data for glacier monitoring. We propose a three-step algorithm specifically crafted to overcome the challenges associated with cloud contamination reduction, outlier removal and data gap handling. This innovative approach iteratively compares the median values of automatically adjusted asymmetrical moving windows to achieve convergence, removing outliers using minimal window size to keep the temporal resolution as high as possible. The methodology’s effectiveness is demonstrated through its application to two glaciers from the United States Geological Survey (USGS) Benchmark Project, showcasing significant improvements in the quality of smoothed MODIS NDSI time series. These results affirm the efficacy of the proposed scheme in rendering a more reliable evaluation of glacier surface condition and seasonal fluctuations. Consequently, this study contributes significant methodological advancements to the fields of remote sensing and glaciology, enhancing the accuracy of glacier monitoring techniques.

Abstract: Antarctic sea ice, a key component in the complex Antarctic climate system, is an important driver and indicator of the global climate. In the relatively short satellite‐observed period from 1979 to 2022 the sea ice extent has continuously increased (contrasting a major decrease in Arctic sea ice) up to a dramatic decrease between 2014 and 2017. Recent years have seen record sea ice lows in February 2022–February 2023. We use a statistical ensemble reconstruction of Antarctic sea ice to put the observed changes into the historical context of the entire 20th century. We propose a seasonal Vector Auto‐Regressive Moving Average (VARMA) model fit in a Bayesian framework using regularized horseshoe priors on the regression coefficients to create a stochastic ensemble reconstruction of monthly Antarctic Sea ice extent from 1900 to 1979. This novel model produces a set of 2,500 plausible sea ice extent reconstructions for the sea ice by sector that incorporate the autocorrelation structure of sea ice over time as well as the dependence of sea ice between the sectors. These fully observed reconstructions exhibit plausible month‐to‐month changes in reconstructed sea ice as well as plausible interactions between the sectors and the total. We reconstruct an overall higher sea ice extent earlier in the 20th century with a relatively sharp decline in the 1970s. These trends agree well with previous reconstructions of Antarctic sea ice based on ice core data, whaling locations, and climatological data, as well as early satellite observations in the reconstruction period.

Abstract: Forests are a large carbon sink and could serve as natural climate solutions that help moderate future warming. Thus, establishing forest carbon baselines is essential for tracking climate‐mitigation targets. Western US forests are natural climate solution hotspots but are profoundly threatened by drought and altered disturbance regimes. How these factors shape spatial patterns of carbon storage and carbon change over time is poorly resolved. Here, we estimate live and dead forest carbon density in 19 forested western US ecoregions with national inventory data (2005–2019) to determine: (a) current carbon distributions, (b) underpinning drivers, and (c) recent trends. Potential drivers of current carbon included harvest, wildfire, insect and disease, topography, and climate. Using random forests, we evaluated driver importance and relationships with current live and dead carbon within ecoregions. We assessed trends using linear models. Pacific Northwest (PNW) and Southwest (SW) ecoregions were most and least carbon dense, respectively. Climate was an important carbon driver in the SW and Lower Rockies. Fire reduced live and increased dead carbon, and was most important in the Upper Rockies and California. No ecoregion was unaffected by fire. Harvest and private ownership reduced carbon, particularly in the PNW. Since 2005, live carbon declined across much of the western US, likely from drought and fire. Carbon has increased in PNW ecoregions, likely recovering from past harvest, but recent record fire years may alter trajectories. Our results provide insight into western US forest carbon function and future vulnerabilities, which is vital for effective climate change mitigation strategies.

Spatiotemporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant water uptake and evapotranspiration. The PWS is studied using 21,455 wooded locations containing U.S. Forest Service Forest Inventory and Analysis plots across the western United States, where species cover is known and where a single species is locally dominant. Using a species-specific mean PWS value explains 23% of observed PWS variability. By contrast, a random forest driven by mean vegetation density, mean climate, soil properties, and topographic descriptors explains 43% of observed PWS variability. Thus, the dominant species explains only 53% (23% compared to 43%) of explainable variations in PWS. Mean climate and mean NDVI also exert significant influence on PWS. Our results suggest that studies of differences between species should explicitly consider the environments (climate, soil, topography) in which observations for each species are made, and whether those environments are representative of the entire species range.

Abstract: The cool season (November–March) of 2022–2023 was exceptional in the western United States (US), with the highest precipitation totals in ≥128 years in some areas. Recent precipitation extremes and expectations based on thermodynamics motivate us to evaluate the evidence for an anthropogenic intensification of western US cool‐season precipitation to date. Over cool seasons 1951–2023, trends in precipitation totals on the wettest cool‐season days were neutral or negative across the western US, and significantly negative in northern California and parts of the Pacific Northwest, counter to the expected net intensification effect from anthropogenic forcing. Multiple reanalysis data sets indicate a corresponding lack of increase in moisture transports into the western US, suggesting that atmospheric circulation trends over the North Pacific have counteracted the increases in atmospheric moisture expected from warming alone. The lack of precipitation intensification to date is generally consistent with climate model simulations. A large ensemble of 648 simulations from 35 climate models suggests it is too soon to detect anthropogenic intensification of precipitation across much of the western US. In California, the 35‐model median time of emergence for intensification of the wettest days is 2080 under a mid‐level emissions scenario. On the other hand, observed reductions of precipitation extremes in California and the Pacific Northwest are near the lower edge of the large ensemble of simulated trends, calling into question model representation of western US precipitation variability.