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Abstract Ecological and life-history variation and both interspecific and intraspecific brood parasitism contribute to diversity in egg phenotype within the same species. In this study, Barn Swallows (Hirundo rustica erythrogaster) laid eggs with high intraclutch repeatability in egg size, shape, and maculation. Despite this high intraclutch repeatability, last-laid eggs had consistently less of the eggshell covered in spots and fewer spots than earlier-laid eggs in the clutch. We examined sources of interclutch and intraclutch variation using both direct measurements and custom software (SpotEgg, NaturePatternMatch) that provide detailed information on egg characteristics, especially maculation measures. In addition to our main findings, maculation on different sides of the egg was highly repeatable; however, only shape, proportion of the eggshell maculated, and average spot size were repeatable between first and replacement clutches. Low intraclutch variation in maculation could allow females to recognize their clutch and this may be adaptive for colonial nesting species, such as the Barn Swallow. Characterizing intraspecific variation in egg size, shape, and maculation is the first step in understanding whether intraclutch variation is low enough—and interclutch variation high enough—such that eggs could serve as identity signals. 

Byte-addressable, non-volatile, random access memory (NVM) has the potential to dramatically accelerate the performance of storage-intensive workloads. For applications with irregular data access patterns, and applications that rely on ad-hoc data structures, the most promising model for interacting with NVM is a transactional model. However, the specifics of the model matter significantly. We introduce two models for programming persistent transactions. We show how to build concurrent persistent transactional memory from traditional software transactional memories. We then introduce general and model-specific optimizations that can substantially improve the performance of persistent transactions. Our evaluation shows a substantial improvement in the both the latency and scalability of persistent transactions. 

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.