ZooST: Zooplankton over Space and Time
Conference Year
January 2021
Abstract
Climate change is rapidly altering the magnitude and phenology of ecological processes and communities. Single observation “snapshots” from multi-lake surveys over a wide geographic range are typically used to evaluate plankton dynamics and their responses to environmental change. The environmental gradients resulting from the differing conditions of the multiple lakes are assumed to be reliable proxies for time (Space-for-Time-substitutions (SFTS)), useful due to the lack of detailed temporal datasets. SFTS surveys, however, have been critiqued for their assumption that spatial and temporal scales can be coupled. In SFTS lake studies, zooplankton are commonly used as indicators of ecosystem change by modeling how community structure is influenced by environmental conditions (e.g., temperature, nutrients, pH, chlorophyll-a), or by using processed-based models (e.g., secondary production estimates). However, the ability of large-scale snapshots to represent time-integrated patterns in zooplankton community structure and function remains untested. I am compiling long-term time series of zooplankton and associated lake data in order to simulate “snapshot” sampling. I propose to empirically re-sample the data sets under different SFTS permutations and compare results among those permutations using a suite of typical analyses (e.g., diversity indices, production models based on production:biomass ratios). I hypothesize that results will not be reproducible across different SFTS survey permutations and will not capture long-term changes and patterns in the lake data due to the confounding effect of temporal variation within each lake.
Primary Faculty Mentor Name
Jason Stockwell
Secondary Mentor Name
Ariana Chiapella
Graduate Student Mentors
Ariana Chiapella
Faculty/Staff Collaborators
Jason Stockwell (Faculty advisor) and Ariana Chiapella (Graduate Student Mentor)
Status
Undergraduate
Student College
Rubenstein School of Environmental and Natural Resources
Program/Major
Environmental Sciences
Primary Research Category
Food & Environment Studies
ZooST: Zooplankton over Space and Time
Climate change is rapidly altering the magnitude and phenology of ecological processes and communities. Single observation “snapshots” from multi-lake surveys over a wide geographic range are typically used to evaluate plankton dynamics and their responses to environmental change. The environmental gradients resulting from the differing conditions of the multiple lakes are assumed to be reliable proxies for time (Space-for-Time-substitutions (SFTS)), useful due to the lack of detailed temporal datasets. SFTS surveys, however, have been critiqued for their assumption that spatial and temporal scales can be coupled. In SFTS lake studies, zooplankton are commonly used as indicators of ecosystem change by modeling how community structure is influenced by environmental conditions (e.g., temperature, nutrients, pH, chlorophyll-a), or by using processed-based models (e.g., secondary production estimates). However, the ability of large-scale snapshots to represent time-integrated patterns in zooplankton community structure and function remains untested. I am compiling long-term time series of zooplankton and associated lake data in order to simulate “snapshot” sampling. I propose to empirically re-sample the data sets under different SFTS permutations and compare results among those permutations using a suite of typical analyses (e.g., diversity indices, production models based on production:biomass ratios). I hypothesize that results will not be reproducible across different SFTS survey permutations and will not capture long-term changes and patterns in the lake data due to the confounding effect of temporal variation within each lake.