Search for: All records

Over the past several decades, forests worldwide have experienced increases in biotic disturbances caused by insects and plant pathogens – a trend that is expected to continue with climate warming. Whereas the causes and effects of individual biotic disturbances are well studied, spatiotemporal interactions among multiple biotic disturbances are less so, despite their importance to ecosystem function and resilience. Here, we highlight an emerging phenomenon of “hotspots” of biotic disturbances (that is, two or more biotic disturbances that overlap in space and time), documenting trends in recent decades in temperate conifer forests of the western US. We also explore potential mechanisms behind and effects of biotic disturbance hotspots, with particular focus on how altered post‐disturbance recovery (successional pathways) can have profound consequences for ecosystem resilience and biodiversity conservation. Finally, we propose research directions that can elucidate drivers of biotic disturbance hotspots and their ecological effects at various spatial scales, and provide insight into this new knowledge frontier.

 

Variable temperature electron paramagnetic resonance (VT-EPR) was used to investigate the role of the environment and oxidation states of several coordinated Eu compounds. We find that while Eu(III) chelating complexes are diamagnetic, simple chemical reduction results in the formation of paramagnetic species. In agreement with the distorted D3h symmetry of Eu molecular complexes investigated in this study, the EPR spectrum of reduced complexes showed axially symmetric signals (g⊥ = 2.001 and g∥ = 1.994) that were successfully simulated with two Eu isotopes with nuclear spin 5/2 (151Eu and 153Eu with 48% and 52% natural abundance, respectively) and nuclear g-factors 151Eu/153Eu = 2.27. Illumination of water-soluble complex Eu(dipic)3 at 4 K led to the ligand-to-metal charge transfer (LMCT) that resulted in the formation of Eu(II) in a rhombic environment (gx = 2.006, gy = 1.995, gz = 1.988). The existence of LMCT affects the luminescence of Eu(dipic)3, and pre-reduction of the complex to Eu(II)(dipic)3 reversibly reduces red luminescence with the appearance of a weak CT blue luminescence. Furthermore, encapsulation of a large portion of the dipic ligand with Cucurbit[7]uril, a pumpkin-shaped macrocycle, inhibited ligand-to-metal charge transfer, preventing the formation of Eu(II) upon illumination. 

Atmospheric gravity waves (GWs) span a broad range of length scales. As a result, the un‐resolved and under‐resolved GWs have to be represented using a sub‐grid scale (SGS) parameterization in general circulation models (GCMs). In recent years, machine learning (ML) techniques have emerged as novel methods for SGS modeling of climate processes. In the widely used approach of supervised (offline) learning, the true representation of the SGS terms have to be properly extracted from high‐fidelity data (e.g., GW‐resolving simulations). However, this is a non‐trivial task, and the quality of the ML‐based parameterization significantly hinges on the quality of these SGS terms. Here, we compare three methods to extract 3D GW fluxes and the resulting drag (Gravity Wave Drag [GWD]) from high‐resolution simulations: Helmholtz decomposition, and spatial filtering to compute the Reynolds stress and the full SGS stress. In addition to previous studies that focused only on vertical fluxes by GWs, we also quantify the SGS GWD due to lateral momentum fluxes. We build and utilize a library of tropical high‐resolution (Δx = 3 km) simulations using weather research and forecasting model. Results show that the SGS lateral momentum fluxes could have a significant contribution to the total GWD. Moreover, when estimating GWD due to lateral effects, interactions between the SGS and the resolved large‐scale flow need to be considered. The sensitivity of the results to different filter type and length scale (dependent on GCM resolution) is also explored to inform the scale‐awareness in the development of data‐driven parameterizations.

 

Oxirene was prepared and stabilized in matrices through resonant energy transfer prior to identification in the gas phase.