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Modern forest management seeks to balance multiple social, economic, and ecological goals. Different management approaches create different types of disturbances in a forest ecosystem and thus also differ in their impacts on plants, animals, and insects. Understanding these impacts is important for conservation of forest ecosystem function, but challenging due to the large spatial and temporal scale over which management occurs. Most past research has focused on relatively small areas, short time scales, and/or a small number of species. To address this, we examined the effects of two common silvicultural systems (even and uneven aged) on abundance and richness of three vertebrate taxa (birds, small mammals, and herpetofauna) over a two-decade period in a temperate hardwood forest in Missouri, USA. The two systems removed a similar amount of biomass overall, but differed in the intensity, number, and configuration of harvests applied. We found that vertebrate population responses varied by taxa, occurred at multiple spatial scales, and were concentrated in the period following the first harvest entry. Birds generally had the largest changes in relative abundance, both positive and negative, following management. Small mammals and reptiles had smaller, but generally positive, responses; amphibians were mixed. Bird species tended to respond in the same way to both silvicultural systems, while small mammals and herpetofauna did not respond consistently. Thus, for birds, the total amount of harvest disturbance across the landscape drives population responses, while for others the size and configuration of individual harvests is likely more important. Synthesizing results across the vertebrate community at large spatial and temporal scales allows managers to better understand trade-offs when making decisions that will affect wildlife in contrasting ways., (© 2019 by the Ecological Society of America.)

We present predictor variables and R and Stan code for simulating and analyzing counts of Missouri Ozark herpetofauna in response to three forest management strategies. Our code performs four primary purposes: import predictor variables from spreadsheets; simulate synthetic response variables based on imported predictor variables and user-supplied values for data-generating parameters; format synthetic data for export to Stan; and analyze synthetic data.