Differing climatic mechanisms control transient and accumulated vegetation novelty in Europe and eastern North America.

Understanding the mechanisms of climate that produce novel ecosystems is of joint interest to conservation biologists and palaeoecologists. Here, we define and differentiate transient from accumulated novelty and evaluate four climatic mechanisms proposed to cause species to reshuffle into novel assemblages: high climatic novelty, high spatial rates of change (displacement), high variance among displacement rates for individual climate variables, and divergence among displacement vector bearings. We use climate simulations to quantify climate novelty, displacement and divergence across Europe and eastern North America from the last glacial maximum to the present, and fossil pollen records to quantify vegetation novelty.

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations.

Controlled comparison of species- and community-level models across novel climates and communities.

Species distribution models (SDMs) assume species exist in isolation and do not influence one another's distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years.