From Ecological States to Trajectories: Revealing Ecological Dynamics Through Environmental Nucleic Acids

Abstract

Environmental nucleic acids (eNA) are transforming ecological biomonitoring by enabling sensitive, scalable, and minimally invasive observations across multiple dimensions of ecological systems. Here, we examine how eNA can extend biomonitoring from ecological state assessment toward the inference of ecological trajectories. We first synthesize how biological production and release, molecular identity and physical state, environmental transport and retention, and analytical recovery shape the temporal characteristics of eNA observations. We then show how ecologically validated eNA signals can characterize taxonomic, demographic, physiological, and functional dimensions of an ecological state. Repeated and complementary observations can resolve key trajectory properties, including direction and magnitude, rate and timing, intermediate pathways, and patterns of progression, stabilization, and recovery. Inferring the processes that generate these trajectories is more demanding because similar molecular patterns may arise from alternative ecological and molecular mechanisms, requiring complementary observations, mechanistic or state‐space models, and explicit treatment of identifiability and uncertainty. Trajectory‐oriented monitoring can further support adaptive management by linking observed ecological change to intervention, reassessment, and recovery decisions. Future progress depends on matching molecular targets and sampling designs to ecological timescales, incorporating dynamic reference regimes and management thresholds, and advancing eNA biomonitoring toward forecasting ecological dynamics and supporting more timely, evidence‐based environmental management decisions.