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Percival M. Marshall

Publications and source records attributed to Percival M. Marshall.

2 recordsLinked to original sources

Risk of invasive waterfowl interaction with poultry production: Understanding potential for avian pathogen transmission via species distribution models

Recent outbreaks of highly pathogenic avian influenza have devastated poultry production across the United States, with more than 77 million birds culled in 2022–2024 alone. Wild waterfowl, including various invasive species, host numerous pathogens, including highly pathogenic avian influenza virus (HPAIV), and have been implicated as catalysts of disease outbreaks among native fauna and domestic birds. In major poultry-producing states like Arkansas, USA, where the poultry sector is responsible for significant economic activity (>$4 billion USD in 2022), understanding the risk of invasive waterfowl interactions with domestic poultry is critical. Here, we assessed the risk of invasive waterfowl-poultry interaction in Arkansas by comparing the density of poultry production sites (chicken houses) to areas of high habitat suitability for two invasive waterfowl species, (Egyptian Goose [ Alopochen aegyptiaca ] and Mute Swan [ Cygnus olor ]), known to host significant pathogens, including avian influenza viruses. The percentage of urban land cover was the most important habitat characteristic for both invasive waterfowl species. At the 95% confidence interval, chicken house densities in areas highly suitable for both species (Egyptian Goose = 0.91 ± 0.11 chicken houses/km 2 ; Mute Swan = 0.61 ± 0.03 chicken houses/km 2 ) were three to five times higher than chicken house densities across the state (0.17 ± 0.01 chicken houses/km 2 ). We show that northwestern and western Arkansas, both areas of high importance for poultry production, are also at high risk of invasive waterfowl presence. Our results suggest that targeted monitoring efforts for waterfowl-poultry contact in these areas could help mitigate the risk of avian pathogen exposure in Arkansas and similar regions with high poultry production.

Biological Invasions

Scenario planning and multispecies occupancy models reveal positive avian responses to restoration of afforested woodlands

Scenario planning is a powerful approach for assessing restoration outcomes under alternative futures. However, developing plausible scenarios remains daunting in complex systems like ecological communities. Here, we used Bayesian multispecies occupancy modeling to develop scenarios to assess woodland restoration outcomes in afforested communities in seven wildlife management areas in Arkansas, U.S.A. Our objectives were (1) to define plausible woodland restoration and afforestation scenarios by quantifying historic ranges of variation in mean tree cover and tree cover heterogeneity from 1986 to 2021 and (2) to predict changes in bird species richness and occupancy patterns for six species of greatest conservation need under two future scenarios: complete afforestation (100% tree cover) and woodland restoration (based on remotely sensed historic tree cover). Using 35 years of remotely sensed tree cover data and 6 years of bird monitoring data, we developed multispecies occupancy models to predict future bird species richness and occupancy under the complete afforestation and woodland restoration scenarios. Between 1986 and 2021, tree cover increased in all study areas—with one increasing 70%. Under the woodland restoration scenario, avian species richness increased up to 20%, and four of six species of greatest conservation need exhibited gains in occupancy probability. The complete afforestation scenario had negligible effects on richness and occupancy. Overall, we found decreasing tree cover to historic levels prior to widespread afforestation would provide community-level benefits and would do little harm even to forest-dependent species of conservation concern. Applying multispecies occupancy modeling within a scenario planning framework allows for comparing multiscale trade-offs between plausible futures.

Restoration Ecology