Abstract
AbstractSoil and plant responses to climate change can be quantified in controlled settings. However, the complexity of climate projections often leads researchers to evaluate ecosystem response based on general trends, rather than specific climate model outputs. Climate projections capture spatial and temporal climate extremes and variability that are lost when using mean climate trends. In addition, application of climate projections in experimental settings remains limited. Our objective was to develop a framework to incorporate statistically downscaled climate model projections into the design of temperature and precipitation treatments for ecological experiments. To demonstrate the utility of experimental treatments derived from climate projections, we used wetlands in the Great Plains as a model ecosystem for evaluating plant and soil responses. Spatial and temporal projections were selected to capture variability and intensity of projected future conditions for exemplary purposes. To illustrate climate projection application for ecological experiments, we developed temperature and precipitation treatments based on moderate‐emissions scenario climate outputs (i.e., RCP4.5–650 ppm CO2 equivalent). Our temperature treatments captured weekly trends that represented cool, average, and warm temperature predictions, and our daily precipitation treatments mimicked various seasonal precipitation trends and extreme events projected for the late 21st century. Treatments were applied to two short‐term controlled experiments evaluating (1) plant germination (temperature treatment applied in growth chamber) and (2) soil nitrogen cycling (precipitation treatment applied in greenhouse) responses to projected future conditions in the Great Plains. Our approach provides flexibility for selecting appropriate and precise climate model outputs to design experimental treatments. Using these techniques, ecologists can better incorporate variation in climate model projections for experimentally evaluating ecosystem responses to future climate conditions, reduce uncertainty in predictive ecological models, and apply predicted outcomes when making management and policy decisions.
Highlights
Ecosystems face substantial threats due to increased atmospheric greenhouse gas concentrations and, subsequently, global and regional climate change (Hughes 2000, Wuethrich 2000, Walther et al 2002)
Climate projections used to inform the IPCC Fourth and Fifth Assessment Reports are known as Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5), respectively
Downscaled climate projections from CMIP3 and CMIP5 are available for several future time periods through the end of the 21st century and may be accessed at https://gdo-dcp.ucllnl.org/downscaled_cmip_pro jections/dcpInterface.html (Reclamation 2013) or https://cida.usgs.gov/gdp/ (Blodgett et al 2011)
Summary
Ecosystems face substantial threats due to increased atmospheric greenhouse gas concentrations and, subsequently, global and regional climate change (Hughes 2000, Wuethrich 2000, Walther et al 2002). Impacts of increasing temperature, shifting precipitation patterns, and increased frequency and severity of extreme precipitation events have been documented in terrestrial, aquatic, natural, and anthropogenic ecosystems, and the consequences of climate change will likely be exacerbated in the 21st century (IPCC 2014, Melillo et al 2014). Aquatic flora and fauna have been impacted directly by atmospheric warming (Covich et al 1997, Poff et al 2002) and have experienced climate change effects associated with alterations to surrounding terrestrial ecosystems (Meyer et al 1999). Ecosystem carbon flux, based on the balance between photosynthesis and respiration, is controlled by atmospheric CO2 levels, temperature, and nutrient availability, and may respond variably to changing climate drivers (Raich and Tufekciogul 2000, Schlesinger and Andrews 2000, Ryan 2008). While trends have been observed over the past 40 yr in a changing climate, it is much more challenging to predict how plant and soil processes may be impacted in the coming decades
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