Fowler on redistricting council | Trusel measures Greenland ice | Schuckman named ASPRS exec. dir.

IMAGE OF THE WEEK

West Greenland ice cap

Luke Trusel configures equipment to measure sub-surface temperatures in the West Greenland ice cap. Image: Sarah Das ©Woods Hole Oceanographic Institution.

GOOD NEWS

Monday, September 20, 4 p.m. ET, EESI Earthtalks “Examining climate-human-fire interactions and feedbacks in temperate ecosystems,” David McWethy, Montana State University. Zoom webinar: https://psu.zoom.us/s/767635597

Friday, October 1, 5 p.m. ET, deadline for undergraduate and graduate student fall academic enrichment award applications. Apply using this link: https://sites.psu.edu/geogcommunity/academic-enrichment-request-form/

Connor Chapman and Andrew Carleton’s article based on Chapman’s master’s thesis, “Soil moisture influence on warm-season convective precipitation for the U.S. Corn Belt,” was accepted for publication in the Journal of Applied Meteorology and Climatology.

Erica Smithwick was appointed to Penn State’s Carbon Emissions Reduction Task Force. https://news.psu.edu/story/668103/2021/09/03/impact/task-force-created-significantly-reduce-penn-states-carbon-emissions

Karen Schuckman was appointed as the next executive director of the American Society for Photogrammetry and Remote Sensing (ASPRS).

The fall semester Coffee Hour schedule has been announced. For speakers and dates, visit the calendar of events web page.

NEWS

Governor Wolf Creates Redistricting Advisory Council to Help Evaluate Fairness in Upcoming Congressional Redistricting Map

Christopher S. Fowler is a member of the council

Governor Tom Wolf is committed to a fair and transparent redistricting process and today signed an executive order creating the Pennsylvania Redistricting Advisory Council. The six-member council, comprised of redistricting experts, will provide guidance to the governor to assist his review of the congressional redistricting plan which will be passed by the General Assembly later this year.

Tracking Traits Podcast: Evolutionary Drivers of our Taste Preferences for Vegetables

Bronwen Powell is interviewed

Penn State undergraduate student Hannah Marchok interviews Assistant Professor of Geography, African Studies, and Anthropology Bronwen Powell about her research into factors that may drive dietary practices across different groups of people in different regions of East Africa.

A Recent Reversal Discovered in the Response of Greenland’s Ice Caps to Climate Change

Luke Trusel is a member of the research team

New collaborative research from the Woods Hole Oceanographic Institution and five partner institutions (University of Arizona, University of Washington, Pennsylvania State University, Desert Research Institute and University of Bergen), published on September 9, 2021, in Nature Geoscience, reveals that during past periods glaciers and ice caps in coastal west Greenland experienced climate conditions much different than the interior of Greenland. Over the past 2,000 years, these ice caps endured periods of warming during which they grew larger rather than shrinking.

Past fires may hold key to reducing severity of future wildfires in western US

Previous fires may hold the key to predicting and reducing the severity of future wildfires in the western United States as fire activity continues to increase, according to researchers from Penn State and the U.S. Forest Service.

RECENTLY PUBLISHED

Determinants of Smallholder Maintenance of Crop Diversity in Morocco’s High Atlas Mountains

Zachary A. Goldberg, Bronwen Powell, Abderrahim Ouarghidi
Human Ecology
https://doi.org/10.1007/s10745-021-00248-7
Smallholder farmers are important managers of global crop diversity. However, agricultural modernization is changing farming practices and raising questions about the socio-ecological factors that support crop diversity. In the context of the semi-arid High Atlas Mountains in Morocco, we explored determinants of crop diversity through a cross-sectional survey and farmer interviews in villages adopting new crops such as apples. Through a multiple linear regression analysis and farmer interviews, we found that market participation, land holdings, and water access influenced crop diversity. We highlight the importance of water access for crop diversity, especially in semi-arid regions with uneven hydrological resources.

Interpretable machine learning for analysing heterogeneous drivers of geographic events in space-time

Arif Masrur, Manzhu Yu, Prasenjit Mitra, Donna Peuquet & Alan Taylor (2021)
International Journal of Geographical Information Science
DOI: 10.1080/13658816.2021.1965608
Machine learning (ML) interpretability has become increasingly crucial for identifying accurate and relevant structural relationships between spatial events and factors that explain them. Methodologically aspatial ML algorithms with an apparent high predictive power ignore non-stationary domain relationships in spatio-temporal data (e.g. dependence, heterogeneity), leading to incorrect interpretations and poor management decisions. This study addresses this critical methodological issue of ‘interpretability’ in ML-based modeling of structural relationships using the example of heterogeneous drivers of wildfires across the United States. Specifically, we present and evaluate a spatio-temporally interpretable random forest (iST-RF) that uses spatio-temporal sampling-based training and weighted prediction. Although the ultimate scientific objective is to derive interpretation in space-time, experiments show that iST-RF can improve predictive accuracy (76%) compared to the aspatial RF approach (70%) while enhancing interpretations of the trained model’s spatio-temporal relevance for its ensemble prediction. This novel approach can help balance prediction and interpretation with fidelity in a spatial data science life cycle. However, challenges exist for predictive modeling when the dataset is very small because in such cases locally optimized sub-model’s prediction performance can be suboptimal. With that caveat, our proposed approach is an ideal choice for identifying drivers of spatio-temporal events at country- or regional-scale studies.

Land use change dynamics in Euro-mediterranean mountain regions: Driving forces and consequences for the landscape

Yolanda Jiménez-Olivencia, Álvaro Ibáñez-Jiménez, Laura Porcel-Rodríguez, Karl Zimmerer
Land Use Policy
https://doi.org/10.1016/j.landusepol.2021.105721
The marginalization of mountain regions in Mediterranean Europe since the mid-20th Century has triggered important socioeconomic and environmental changes that are putting the survival of highly regulated and environmentally adapted landscapes in jeopardy. We still have only a limited understanding of the driving forces behind these dynamics of change and their final consequences for the structure and character of the landscape. In general, the transformation of the landscape and its causes have been studied at regional and local level and various syntheses have been made for Europe or the Mediterranean as a whole, focusing above all on changes in the use of farmland. The objective of this paper is to provide a holistic view of the changes that have taken place in the landscape in the Euro-Mediterranean region, focusing in particular on the mountains because of their role as heritage reserves and as sources of environmental services. This research involves a systematic review of the evidence about the dynamics of land use change, its underlying drivers and their effects on the landscape. We analyse 53 case studies from 6 countries situated on the northern shores of the Mediterranean. These studies covered a period of around 40 years and were each performed at a local scale. The results reveal that landscape change is caused above all by the abandonment of farmland and reforestation (in over 90% of cases), and by pressure from urban development in the case of coastal and peri-urban mountain ranges. In addition, the dominant dynamics in each case vary depending on the bioclimatic area in question, to the extent that bioclimate has been shown to be an important explanatory factor behind these dynamics. The underlying boosters of change normally act together and those most commonly cited are economic, demographic and geographic. As regards the impacts on the structure and character of the landscape, the dynamics analysed are manifested first and foremost in degradation processes, in an increase in homogenization, which affects above all the most humid bioclimates, and in the fragmentation of open spaces. This analysis provides a general overview of the causes and consequences of the changes in land use in the mountain regions of Mediterranean Europe and raises questions of interest for policy-making that affects the landscape.

Drivers of fire severity shift as landscapes transition to an active fire regime, Klamath Mountains, USA

Taylor, A. H., L. B. Harris, and S. A. Drury
Ecosphere
https://esajournals.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ecs2.3734
Fire severity patterns are driven by interactions between fire, vegetation, and terrain, and they generate legacy effects that influence future fire severity. A century of fire exclusion and fuel buildup has eroded legacy effects, and contemporary fire severity patterns may diverge from historical patterns. In recent decades, area burned and area burned at high severity have increased and landscapes are transitioning back to an active fire regime where disturbance legacies will again play a strong role in determining fire severity. Understanding the drivers of fire severity is crucial for anticipating future fire severity patterns as active fire regimes are reestablished. We identified drivers of fire severity in the Klamath Mountains, a landscape with an active fire regime, using two machine learning statistical models: one model for nonreburns (n = 92) and one model for reburns (n = 61). Both models predicted low better than moderate or high-severity fire. Fire severity drivers contrasted sharply between non-reburns and reburns. Fire weather and fuels were dominant controls in non-reburns, while previous burn severity, fuel characteristics, and time since last fire were drivers for reburns. In reburns, areas initially burned at low (high) severity burned the same way again. This tendency was sufficiently strong that reburn fire severity could be predicted equally well with only severity of the previous fire in the model. Thus, reburn fire severity is more predictable than severity in non-reburns that are driven by the stochastic influences of fire weather. Reburn severity in aggregate was also higher than non-reburn severity suggesting a positive feedback effect that could contribute to an upward drift in fire severity as area burned increases. Terrain had low importance in both models. This indicates strong terrain controls in the past may not carry into the future. Low- and moderate-severity fire effects were prevalent in non-reburns under moderate fire weather and self-reinforcing behavior maintained these effects in reburns even under more extreme weather, particularly in reburns within 10 yr. Our findings suggest deliberate use of wildfire and prescribed fire under moderate conditions would increase fire resilience in landscapes transitioning to an active fire regime.

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