In the face of global biodiversity declines, predicting the fate of biological systems is a key
goal in ecology. One popular approach is the search for early warning signals (EWS s) …

Throughout the life sciences, we routinely seek to interpret measurements and observations
using parametrized mechanistic mathematical models. A fundamental and often overlooked …

Analyzing ecological data often requires modeling the autocorrelation created by spatial and
temporal processes. Many seemingly disparate statistical methods used to account for …

Foreseeing population collapse is an on-going target in ecology, and this has led to the
development of early warning signals based on expected changes in leading indicators …

Ecosystems on the verge of major reorganization—regime shift—may exhibit declining
resilience, which can be detected using a collection of generic statistical tests known as …

Many real-world systems can exhibit tipping points and multiple stable states, creating the
potential for sudden and difficult to reverse transitions into a less desirable regime. The …

Interpreting data using mechanistic mathematical models provides a foundation for
discovery and decision-making in all areas of science and engineering. Developing …

The recent description of potentially generic early warning signals is a promising
development that may help conservationists to anticipate a population's collapse prior to its …

Human land use, such as livestock grazing, can have profound yet varied effects on wildlife
interacting within common ecosystems, yet our understanding of land‐use effects is often …

Complex systems can undergo abrupt state transitions near critical points. Theory and
controlled experimental studies suggest that the approach to critical points can be …