Understanding and anticipating biological responses to climate change is both a critical applied need and a fascinating opportunity to test ecological and evolutionary principles. We are motivated by shifts in organismal traits, population demography, species distributions, and community dynamics in response to climate change that are inconsistent with current, largely correlative models. Many predictive techniques omit variation in organismal traits and how they interact with spatial and temporal variation.
We believe we can do better by moving beyond simple correlations to describe the mechanisms by which organisms respond to their environment. Mechanisms are likely to be particularly important in the context of climate and other environmental changes that force models to be extrapolated into conditions novel across the evolutionary history of organisms. Thresholds and non-linearities in biological processes warrant consideration. We recognize the importance of environmental variability and extremes and seek ways to temporally aggregate environmental responses as organisms do. We view models as a powerful integrative tool, but welcome exclusively empirical colleagues.
We acknowledge mechanistic models are often complex and data hungry. We seek a middle ground whereby models capture enough of the biology to describe key processes by which organisms respond to climate change and no more. We take a null model approach whereby we focus on well understood thermal responses across levels of biological organization while keeping in mind other constraints such as water and energy balances and community interactions.
We look to natural history collections and field and lab resurveys to test our models. We turn to ecoinformatics and biologically-informed data science approaches to test generality. We’ve found some ways to generalize thermal constraints, but admittedly our models have grown in complexity over time as we identify important, omitted mechanisms. We seek to scale across levels of organization. We’ve mostly scaled from phenotypes to fitness but are increasingly accounting for genomic and physiological mechanisms. Overall, we aim to improve predictions of ecological and evolutionary response to climate change by focusing on how organisms experience climate change.