RESEARCH
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 worldwide. PNAS. | 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 have shown 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. In forests, we have found that 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. (2023). Mixotrophic microbes create carbon tipping points under warming. Funct. Ecol., Cover Story. | Media links: Duke Today; Oceanographic; Grist; AGU Eos; Nature Climate Change
Wieczynski, D. J., et al. (2023). Viral infections mediate microbial controls on ecosystem responses to global warming. FEMS Microbiology Ecology, Editor's Choice. | Media links: DOE Office of Science
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.
Ecology and evolution in fluctuating environments
Environmental fluctuations are a major black box in ecology, but will likely have greater eco-evolutionary consequences with global change than environmental averages. We have used theory, experimental evolution, and field mesocosms to show that environmental fluctuations can have profound and unexpected effects on ecological and evolutionary processes by controlling i) intraspecific competition and diversity, ii) population extinction risk, iii) the evolution of novel traits, and iv) competitive dominance and invasion by non-native species. Importantly, these outcomes depend on how traits, their inherent tradeoffs, and the frequency of environmental fluctuations affect long-term performance (fitness) of genotypes and species.
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.
Harnessing the ecological data revolution
Linking theory with real-world ecological patterns has always been a difficult challenge, but the rapid increase in large ecological datasets provides extensive information that's quickly outpacing theory. I take advantage of this data revolution by developing data science techniques to test theory against dense observational and experimental datasets, leveraging cutting-edge data-producing tools like high-throughput fluid imaging and flow cytometry in the lab and airborne remote sensing, integrated field sampling networks, and climate raster grids at landscape-to-global scales in the field. This data-heavy approach has helped discern which mechanisms of environmental responses are robust to the complexity of the real world, informing more refined predictions of ecosystem responses to rapid global change.
Wieczynski, D. J., et al. (2019). Climate shapes and shifts functional biodiversity in forests worldwide. PNAS. | 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 2024