Climate change will reduce North American inland wetland areas and disrupt their seasonal regimes.

Climate change can alter wetland extent and function, but such impacts are perplexing. Here, changes in wetland characteristics over North America from 25° to 53° North are projected under two climate scenarios using a state-of-the-science Earth system model. At the continental scale, annual wetland area decreases by ~10% (6%-14%) under the high emission scenario, but spatiotemporal changes vary, reaching up to ±50%.

Phenological shifts in lake stratification under climate change.

One of the most important physical characteristics driving lifecycle events in lakes is stratification. Already subtle variations in the timing of stratification onset and break-up (phenology) are known to have major ecological effects, mainly by determining the availability of light, nutrients, carbon and oxygen to organisms. Despite its ecological importance, historic and future global changes in stratification phenology are unknown.

A substantial role of soil erosion in the land carbon sink and its future changes.

Realistic representation of land carbon sink in climate models is vital for predicting carbon climate feedbacks in a changing world. Although soil erosion that removes land organic carbon has increased substantially since the onset of agriculture, it is rarely included in the current generation of climate models. Using an Earth system model (ESM) with soil erosion represented, we estimated that on average soil erosion displaces 5% of newly fixed land organic carbon downslope annually in the continental United States.

Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches.

Stresses from heat and drought are expected to increasingly suppress crop yields, but the degree to which current models can represent these effects is uncertain. Here we evaluate the algorithms that determine impacts of heat and drought stress on maize in 16 major maize models by incorporating these algorithms into a standard model, the Agricultural Production Systems sIMulator (APSIM), and running an ensemble of simulations. Although both daily mean temperature and daylight temperature are common choice of forcing heat stress algorithms, current parameterizations in most models favor the use of daylight temperature even though the algorithm was designed for daily mean temperature.