Geography

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Author: search.filters.author.Sahajpal, Ritvik

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    Potential Vegetation and Carbon Redistribution in Northern North America from Climate Change
    (MDPI, 2016-01-06) Flanagan, Steven A.; Hurtt, George C.; Fisk, Justin P.; Sahajpal, Ritvik; Hansen, Matthew C.; Dolan, Katelyn A.; Sullivan, Joe H.; Zhao, Maosheng
    There are strong relationships between climate and ecosystems. With the prospect of anthropogenic forcing accelerating climate change, there is a need to understand how terrestrial vegetation responds to this change as it influences the carbon balance. Previous studies have primarily addressed this question using empirically based models relating the observed pattern of vegetation and climate, together with scenarios of potential future climate change, to predict how vegetation may redistribute. Unlike previous studies, here we use an advanced mechanistic, individually based, ecosystem model to predict the terrestrial vegetation response from future climate change. The use of such a model opens up opportunities to test with remote sensing data, and the possibility of simulating the transient response to climate change over large domains. The model was first run with a current climatology at half-degree resolution and compared to remote sensing data on dominant plant functional types for northern North America for validation. Future climate data were then used as inputs to predict the equilibrium response of vegetation in terms of dominant plant functional type and carbon redistribution. At the domain scale, total forest cover changed by ~2% and total carbon storage increased by ~8% in response to climate change. These domain level changes were the result of much larger gross changes within the domain. Evergreen forest cover decreased 48% and deciduous forest cover increased 77%. The dominant plant functional type changed on 58% of the sites, while total carbon in deciduous vegetation increased 107% and evergreen vegetation decreased 31%. The percent of terrestrial carbon from deciduous and evergreen plant functional types changed from 27%/73% under current climate conditions, to 54%/46% under future climate conditions. These large predicted changes in vegetation and carbon in response to future climate change are comparable to previous empirically based estimates, and motivate the need for future development with this mechanistic model to estimate the transient response to future climate changes.
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    Potential Transient Response of Terrestrial Vegetation and Carbon in Northern North America from Climate Change
    (MDPI, 2019-09-18) Flanagan, Steven A.; Hurtt, George C.; Fisk, Justin P.; Sahajpal, Ritvik; Zhao, Maosheng; Dubayah, Ralph; Hansen, Matthew C.; Sullivan, Joe H.; Collatz, G. James
    Terrestrial ecosystems and their vegetation are linked to climate. With the potential of accelerated climate change from anthropogenic forcing, there is a need to further evaluate the transient response of ecosystems, their vegetation, and their influence on the carbon balance, to this change. The equilibrium response of ecosystems to climate change has been estimated in previous studies in global domains. However, research on the transient response of terrestrial vegetation to climate change is often limited to domains at the sub-continent scale. Estimation of the transient response of vegetation requires the use of mechanistic models to predict the consequences of competition, dispersal, landscape heterogeneity, disturbance, and other factors, where it becomes computationally prohibitive at scales larger than sub-continental. Here, we used a pseudo-spatial ecosystem model with a vegetation migration sub-model that reduced computational intensity and predicted the transient response of vegetation and carbon to climate change in northern North America. The ecosystem model was first run with a current climatology at half-degree resolution for 1000 years to establish current vegetation and carbon distribution. From that distribution, climate was changed to a future climatology and the ecosystem model run for an additional 2000 simulation years. A model experimental design with different combinations of vegetation dispersal rates, dispersal modes, and disturbance rates produced 18 potential change scenarios. Results indicated that potential redistribution of terrestrial vegetation from climate change was strongly impacted by dispersal rates, moderately affected by disturbance rates, and marginally impacted by dispersal mode. For carbon, the sensitivities were opposite. A potential transient net carbon sink greater than that predicted by the equilibrium response was estimated on time scales of decades–centuries, but diminished over longer time scales. Continued research should further explore the interactions between competition, dispersal, and disturbance, particularly in regards to vegetation redistribution.
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    Evaluating the Impact of the 2020 Iowa Derecho on Corn and Soybean Fields Using Synthetic Aperture Radar
    (MDPI, 2020-11-26) Hosseini, Mehdi; Kerner, Hannah R.; Sahajpal, Ritvik; Puricelli, Estefania; Lu, Yu-Hsiang; Lawal, Afolarin Fahd; Humber, Michael L.; Mitkish, Mary; Meyer, Seth; Becker-Reshef, Inbal
    On 10 August 2020, a series of intense and fast-moving windstorms known as a derecho caused widespread damage across Iowa’s (the top US corn-producing state) agricultural regions. This severe weather event bent and flattened crops over approximately one-third of the state. Immediate evaluation of the disaster’s impact on agricultural lands, including maps of crop damage, was critical to enabling a rapid response by government agencies, insurance companies, and the agricultural supply chain. Given the very large area impacted by the disaster, satellite imagery stands out as the most efficient means of estimating the disaster impact. In this study, we used time-series of Sentinel-1 data to detect the impacted fields. We developed an in-season crop type map using Harmonized Landsat and Sentinel-2 data to assess the impact on important commodity crops. We intersected a SAR-based damage map with an in-season crop type map to create damaged area maps for corn and soybean fields. In total, we identified 2.59 million acres as damaged by the derecho, consisting of 1.99 million acres of corn and 0.6 million acres of soybean fields. Also, we categorized the impacted fields to three classes of mild impacts, medium impacts and high impacts. In total, 1.087 million acres of corn and 0.206 million acres of soybean were categorized as high impacted fields.
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    Disturbance Distance: quantifying forests’ vulnerability to disturbance under current and future conditions
    (IOP Publishing, 2017-11-02) Dolan, Katelyn A; Hurtt, George C; Flanagan, Steve A; Fisk, Justin P; Sahajpal, Ritvik; Huang, Chengquan; Page, Yannik Le; Dubayah, Ralph; Masek, Jeffrey G
    Disturbances, both natural and anthropogenic, are critical determinants of forest structure, function, and distribution. The vulnerability of forests to potential changes in disturbance rates remains largely unknown. Here, we developed a framework for quantifying and mapping the vulnerability of forests to changes in disturbance rates. By comparing recent estimates of observed forest disturbance rates over a sample of contiguous US forests to modeled rates of disturbance resulting in forest loss, a novel index of vulnerability, Disturbance Distance, was produced. Sample results indicate that 20% of current US forestland could be lost if disturbance rates were to double, with southwestern forests showing highest vulnerability. Under a future climate scenario, the majority of US forests showed capabilities of withstanding higher rates of disturbance then under the current climate scenario, which may buffer some impacts of intensified forest disturbance.
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    Assessing Cellulosic Biofuel Feedstock Production Across a Gradient of Agricultural Management Systems in the U.S. Midwest
    (2014) Sahajpal, Ritvik; Hurtt, George C; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    While biofuels are widely considered to be a part of the solution to high oil prices, a comprehensive assessment of the environmental sustainability of existing and future biofuel systems is needed to assess their utility in meeting U.S. energy and food needs without exacerbating environmental harm. The following questions guide this research: 1. What is the spatial extent and composition of agricultural management systems that exist in the U.S. Midwest? 2. How does sub-grid scale edaphic variation impact our estimation of poplar biomass productivity across a gradient of spatial scales in the U.S. Midwest? 3. How do location and management interactions impact yield gap analysis of cellulosic ethanol production in U.S. Midwest? In the first chapter, I developed an algorithm to identify representative crop rotations in the U.S. Midwest, using remotely sensed data; and used this information to detect pronounced shifts from grassland to monoculture cultivation in the U.S. Midwest. In the second chapter, a new algorithm is developed to reduce the computational burden of high resolution ecosystem modeling of poplar plantations in U.S. Midwest, with the results from the high resolution modeling being used to estimate the impact of averaging and discretization of soil properties on poplar yield estimates. In the third chapter, a novel yield gap analysis of cellulosic feedstocks on marginal lands in the U.S. Midwest is conducted to determine the management inputs needed to reach their yield potential in a sustainable manner. The significance of this research lies in providing a spatially explicit regional scale analysis of the tradeoffs between food and fuel production and providing an understanding of which biofuel crops should be grown where to maximize production while mitigating environmental damage.