Table name Description cp_lake_information lake-specific class assignments for the clusters, the ecological temporal group, and response class; unique identifiers and location information; CHL time series predictability, dynamics, and climate causality (1/0) cp_chl_climate_timeseries lake-specific annual estimates of median summer chl; and, seasonal values for the four climate predictors cp_lk_eco_context lake-specific values of ecological context variables cp_chl_glmnet lake-specific glmnet results distinguising ecological temporal classes by ecological context variables cp_chl_dynamics_modeling model results that determine whether a lake-specific CHL time series is predictable or not predictable, and whether the time series dynamics are linear-stochastic or nonlinear cp_chl_climatecausal_gr Granger modeling results for season-specific climate causality for lakes with linear-stochastic CHL time series cp_chl_climatecausal_ccm CCM modeling results for season-specific climate causality for lakes with nonlinear CHL time series cp_chl_bpanom annual breakpoints and anomalies for lake-specific CHL time series cp_climate_bpanom annual breakpoints and anomalies for lake-specific seasonal climate time series for temperature, precipitation, drought, and ENSO cp_chl_climate_monotonic_trends monotonic trends results for lake-specific CHL time series and for each seasonal climate variable time series cp_data_dictionary data dictionary providing definitions of columns in each data table along with information on data type, units, and source information cp_domain_dictionary definition of possible values of entries in the data dictionary that are factor type.

These datasets include both the raw data and the model results from a project exploring causal relationships between climate and lake productivity of a diverse set of 24,452 US lakes over 34 years (1984-2008). Climate change is expected to increase lake productivity and algal blooms and cause regime shifts, particularly in human-impacted ecosystems. First we assessed the potential for nonlinear dynamics in summer median lake chlorophyll (CHL; derived from remote sensing) to demonstrate the potential for regime shifts in these lakes; second, we modeled the causal effects of climate on lake CHL over the 34 years. Climate was causally related to CHL in 34% of lakes; of those, 71% exhibited abrupt shifts, but only 13% had the potential for regime shifts. Climate-influenced lakes had low productivity at environmental extremes and experienced some directional climate change. Our synthesis of 24,452 time series demonstrates that effects of climate on lake productivity depend on recent climate change interacting with human impact and environmental context.