Long-Term Community Data Reveal Ecological and Evolutionary Phenomena
TL;DR
Insight from flagship sites, monitoring networks, and global databases are integrated, highlighting statistical advances that strengthen inference despite imperfect designs and ensuring the full potential of long-term community data remains underused.
Abstract
Resolving the ecological and evolutionary processes affecting biodiversity requires long-term community data. By separating short-term variability from directional change and by revealing lags spanning years to decades, these records expose the relative roles of dispersal, environmental filtering, species interactions, and drift, as well as the relevant timescales involved. Across realms, such records show that biodiversity change will frequently concern composition rather than species richness. Across time, the records resolve dynamics such as cycles and evolutionary change invisible to short studies. Long-term records also provide rare windows into eco-evolutionary change, from climate-driven selection on phenology to trait shifts feeding back to coexistence. We integrate insights from flagship sites, monitoring networks, and global databases, highlighting statistical advances that strengthen inference despite imperfect designs. However, the full potential of long-term community data remains underused. Comparative analyses across taxa and regions, together with harmonized sampling and the initiation of new long-term monitoring, are essential to overcome existing biases.