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Soil stores three times more carbon than the atmosphere, making small changes in its storage and release crucial for carbon cycling and climate models. This study examined the impact of the 2020 California Silverado Fire on pyrogenic carbon (PyC) deposits using nitrogen and carbon isotopes as proxies. While the results showed significant variability in δ¹⁵N, δ¹³C, total carbon, and total nitrogen across sites, they did not support the hypothesis that wildfire increases δ¹⁵N while keeping δ¹³C constant, emphasizing the need for location-based controls when using δ¹⁵N to track PyC.

Understanding the relationships between temperature, MEI, SPI, and CO2 concentration is important as they measure the major influencers of California’s regional climate: temperature, ENSO, precipitation, and atmospheric CO2. In this article, the authors analyzed temperature, Multivariate El Niño-Southern Oscillation Index (MEI), and Standard Precipitation Index (SPI) data from the San Francisco Bay Area from 1971 to 2016. They also analyzed CO2 records from Mauna Loa, HI for the same time period, along with the annual temperature anomalies for the Bay Area.

The authors looked at how soil temperature changes with fire to develop a sensor system that could aid in earlier detection of fires.

The authors looked at beach nourishment (a way to combat erosion on coasts) and resulting grain size distribution. Their work is important to understand the dynamics of erosion and it's relation to wave action and the implications this has for efforts to mitigate coastal erosion.

Growing climate concerns have intensified research into zero-emission transportation fuels, notably hydrogen. Hydrogen is considered a clean fuel because its only major by-product is water. This project analyzes how hydrogen compares to kerosene as a commercial aircraft fuel with respect to cost, CO2 emissions, and flight range.

Current horticulture practices often rely on pesticides, causing environmental harm. To address this, authors explore the use of ultrasonic sound emissions to detect plant stress at an individual level.

Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.

The authors test symbiotic relationships among cyanobacteria species to generate more robust cultures for potential biofuel production.

The authors looked at the impact of different harvest and feeding treatments on Heterandria formosa over three generations as a model for changes in marine ecosystems.

The authors compare rates of renewable energy adoption between states that historically vote for democrats versus republicans in presidential elections.