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Management and research applications of long-range surveillance radar data for birds, bats, and flying insects

There is renewed interest in using long-range surveillance radar as a biological research tool due to substantial improvements in the network of radars within the United States. Technical improvements, the digital nature of the radar data, and the availability of computing power and geographic information systems, enable a broad range of biological applications. This publication provides a summary of long-range surveillance radar technology and applications of these data to questions about movement patterns of birds and other flying wildlife. The intended audience is potential radar-data end users, including natural-resource management and regulatory agencies, conservation organizations, and industry. This summary includes a definition of long-range surveillance radar, descriptions of its strengths and weaknesses, information on applications of the data, cost, methods of calibration, and what end users need to do, and some key references and resources.

Texas↗

Distributions of host heterogeneity in susceptibility show signatures of pathogen geographic structure in an insect baculovirus

Segregated variation between populations is a fundamental evolutionary process leading to parasite specialization, yet the resulting impacts on infection heterogeneity within populations are theoretically and empirically understudied. We asked whether the distribution of host susceptibility to infection within populations carries the signatures of geographic structure from pathogen local adaptation, maladaptation, or generalism in a nuclear polyhedrosis virus that infects the Gulf Fritillary butterfly Dione vanillae . For this virus, there is genetic support for two geographically distinct groups within San Diego County, based on whole genome sequencing of 16 virus isolates. Reciprocal laboratory infections showed evidence of two contrasting viral life history strategies: a ‘generalist’ phenotype that consistently infected variable hosts and a ‘specialist’ that performed slightly better in its local host population. As predicted by our theoretical model, the more consistent infection displayed by the generalist across populations corresponded to lower heterogeneity in susceptibility within populations, modeled as gamma distribution. Furthermore, the generalist phenotype was collected over a wider geographic range despite having a tenfold-lower mean infection rate than the specialist, suggesting that a strategy of more consistent infection provides key fitness advantages across diverse host populations. Intriguingly, when there is variation in host susceptibility, interpretations of pathogen local adaptation are dose-dependent. Measuring infectivity across multiple doses enables estimation of the whole distribution of susceptibility, which provides more reliable identification of pathogen specialization to its local host. Our work demonstrates how trait distributions and not only their mean values can carry quantifiable signatures of eco-evolutionary processes in interspecific interactions.

BioRxiv↗