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Abstract Restoring ecosystems in a changing climate requires understanding how management interventions interact with climate conditions. In tallgrass prairies, disturbance through fire, mowing, or grazing is a critical force in maintaining herbaceous plant diversity. However, unlike historical fire regimes that occurred throughout the growing season, management actions like prescribed fire and mowing are commonly limited to the spring or fall seasons. Warming winters are resulting in less snow, causing overwintering plants to experience reduced insulation from snow and these more extreme winter conditions may be exacerbated or ameliorated depending on the timing of management actions. Understanding this novel interaction between the timing of management actions and snow depth is critical for managing and restoring grassland ecosystems. Here, we applied experimental management treatments (spring and fall burn and fall mow) in combination with snow depth manipulations to test whether the type and timing of commonly implemented disturbances interact with snow depth to affect restored prairie plant diversity and composition. Overall, snow manipulations and management actions influenced soil temperature while only management actions influenced spring thaw timing. Burning in the fall, which removes litter prior to winter resulted in colder soils and earlier spring thaw timing. However, plant communities were mostly resistant to these effects. Instead, plants responded to management actions such that burning and mowing, regardless of timing, increased plant diversity and spring burning increased flowering structure cover while reducing weedy cool season grass cover. Together these results suggest that grassland plant communities are resistant to winter climate change over the short term and that burning or mowing is critical to promoting plant diversity in tallgrass prairies.
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Contrasting seasonal effects of climate change influence density in a cold‐adapted species
Abstract Many ecological processes are profoundly influenced by abiotic factors, such as temperature and snow. However, despite strong evidence linking shifts in these ecological processes to corresponding shifts in abiotic factors driven by climate change, the mechanisms connecting population size to season‐specific climate drivers are little understood. Using a 21‐year dataset and a Bayesian state space model, we identified biologically informed seasonal climate covariates that influenced densities of snowshoe hares (Lepus americanus), a cold‐adapted boreal herbivore. We found that snow and temperature had strong but conflicting season‐dependent effects. Reduced snow duration in spring and fall and warmer summers were associated with lowered hare density, whereas warmer winters were associated with increased density. When modeled simultaneously and under two climate change scenarios, the negative effects of reduced fall and spring snow duration and warmer summers overwhelm the positive effect of warmer winters, producing projected population declines. Ultimately, the contrasting population‐level impacts of climate change across seasons emphasize the critical need to examine the entire annual climate cycle to understand potential long‐term population consequences of climate change.
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- Award ID(s):
- 1736249
- PAR ID:
- 10372938
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Global Change Biology
- Volume:
- 28
- Issue:
- 21
- ISSN:
- 1354-1013
- Format(s):
- Medium: X Size: p. 6228-6238
- Size(s):
- p. 6228-6238
- Sponsoring Org:
- National Science Foundation
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