DataSheet1_The legacy of intensive agricultural history on the soil health of (sub)tropical landscapes.pdf

Soil health conceptualized as a measurable ecosystem property provides a powerful tool for monitoring progress in restoration projects or implementation of best management practices to improve degraded lands and promote sustainable agroecosystems. We surveyed soils collected from a range of land uses (i.e., protected native and non-native forest, managed pasture, unmanaged previously intensive agricultural lands, organic cropland, and conventional cropland) across a range of soil orders (Oxisol, Mollisol, Andisol, Inceptisol, and Vertisol) on three Hawaiian Islands. Forty-six soil health indicators encompassing biological, chemical, and physical properties were measured. In this multivariate survey, the most distinct group was the unmanaged, previously intensive agriculture lands, which was significantly different from all other land uses even when considering differences in mineralogy. Importantly, the soil health indicators of well-managed pastures in Hawaiʻi were not different from protected forests, suggesting that well-managed grazing lands may be as healthy and resilient as protected forests. A suite of 11 readily measured indicators emerged out of a first-principle approach to determining a holistic indication of soil health across a range of soils and systems in Hawaiʻi encompassing much of the diversity in the tropics and subtropics. Every land use may improve its soil health status within a reasonable range of expectations for a soil’s land use history, current land use, and mineralogy. Key drivers of inherent differences in the soil health indicators, including intensive land use history, current land use practices, and mineralogy, must be interwoven into the soil health index, which should set minimum and maximum benchmarks and weight indicators according to equitable standards.</p

A Large‐Scale Analysis of Pockets of Open Cells and Their Radiative Impact

Pockets of open cells sometimes form within closed‐cell stratocumulus cloud decks but little is known about their statistical properties or prevalence. A convolutional neural network was used to detect occurrences of pockets of open cells (POCs). Trained on a small hand‐logged dataset and applied to 13 years of satellite imagery the neural network is able to classify 8,491 POCs. This extensive database allows the first robust analysis of the spatial and temporal prevalence of these phenomena, as well as a detailed analysis of their micro‐physical properties. We find a large (30%) increase in cloud effective radius inside POCs as compared to their surroundings and similarly large (20%) decrease in cloud fraction. This also allows their global radiative effect to be determined. Using simple radiative approximations we find that the instantaneous global annual mean top‐of‐atmosphere perturbation by all POCs is only 0.01 W/m2

The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples From Terra and Aqua

International audienc