Daniel J Wieczynski

Department of Biology | Duke University

RESEARCH

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Scaling up from organisms to ecosystems using traits

Traits determine individual performance in a given environment, creating a fundamental link between environmental variation and population, community, and ecosystem processes. By merging trait-based theory, microcosm experiments, and analysis of global climate and forest data, we have shown how environmental impacts scale up from the individual level to drive variation in things like population growth rate, species interactions, functional biodiversity, and net primary production and respiration. This work highlights how traits are fundamental for understanding and anticipating the complex impacts of climate across organizational, spatial, and temporal scales.

Wieczynski, D. J., et al. (2021). Linking species traits and demography to explain complex temperature responses across levels of organization. PNAS. |  Media links: CBS17, Duke Today, ESA Theory Section  

Wieczynski, D. J., et al. (2019). Climate shapes and shifts functional biodiversity in forests worldwidePNAS. | Media links: PNAS "In This Issue", Nature Plants, Science Sessions Podcast

Metabolism, carbon cycling, and climate change

 

Organisms are linked to the global carbon cycle through metabolic processes like photosynthesis (carbon uptake) and respiration (carbon release) that are expected to change with global warming. We found that warming can shift the balance of carbon uptake and release in microbial food webs, leading to abrupt transitions from carbon sink states to carbon source states. Additionally, in forests, increasing temperatures drive shifts in whole-community trait composition that, in turn, systematically alter net primary production. These studies reveal how climate-driven metabolic changes redirect material fluxes within ecosystems, providing a strong, functional foundation for understanding the mechanics of imminent carbon flux shifts—and potential ecosystem-climate feedbacks—with future global change.

Wieczynski, D. J., et al. (In revision). Mixotrophs generate carbon tipping points under warming

Wieczynski, D. J., et al. (In review). Viral infections mediate microbial controls on ecosystem responses to global warming.

Wieczynski, D. J., et al. (2022). Improving landscape-scale productivity estimates by integrating trait-based models and remotely-sensed foliar-trait and canopy-structural data. Ecography.

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Ecology and evolution in fluctuating environments

 

Environmental fluctuations are a major black box in ecology, but may have stronger impacts on populations than environmental averages. We have used theory, experimental evolution, and field mesocosms to show that environmental fluctuations can have profound and unexpected effects on population ecology and evolution by i) increasing intraspecific diversity and population persistence, ii) determining whether novel traits can evolve, and iii) reversing competitive dominance to facilitate invasions by non-native species. Importantly, these outcomes depend on how traits, their tradeoffs, and the frequency of environmental fluctuations affect long-term performance (fitness).

Wieczynski, D. J., et al. (2016). Environmental fluctuations promote intraspecific diversity and population persistence via inflationary effects. Oikos.

Wieczynski, D. J., et al. (2018). Temporally Autocorrelated Environmental Fluctuations Inhibit the Evolution of Stress Tolerance. Am Nat.

Fey, S. B., & Wieczynski, D. J. (2017). The temporal structure of the environment may influence range expansions during climate warming. Glob Change Biol.

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Harnessing the ecological data revolution

 

Connecting theory to real-world patterns is a major challenge, but the rapid increase in large ecological datasets provides extensive information that may soon outpace theory development. I take advantage of this data revolution in my work by integrating theory with cutting-edge tools and techniques like fluid imaging and flow cytometry in the lab as well as landscape-to-global-scale field data sources like remote sensing data, integrated ground sampling networks, and climate raster grids. This integrative approach creates many exciting opportunities to test theoretical predictions and address issues of global change in real systems.

Wieczynski, D. J., et al. (2019). Climate shapes and shifts functional biodiversity in forests worldwidePNAS. | Media links: PNAS "In This Issue", Nature Plants, Science Sessions Podcast

Wieczynski, D. J., et al. (2021). Linking species traits and demography to explain complex temperature responses across levels of organization. PNAS. |  Media links: CBS17, Duke Today, ESA Theory Section  

Wieczynski, D. J., et al. (2022). Improving landscape-scale productivity estimates by integrating trait-based models and remotely-sensed foliar-trait and canopy-structural data. Ecography.

© Daniel J Wieczynski 2022