A tipping point is a critical transition point where a system is
impending to collapse under a slight disturbance. Based on sequential
time-series data, such transition can be captured by early warning
signals like critical slowing down. However, sequential time-series data
is limited for most macro-ecosystems, which brings the challenge for
practical application. Here we report that density fluctuation, a purely
spatial metric, robustly indicates the tipping point of Ising-type
ecosystems. Ricker model and an agroecosystem, both of which have been
proved to fall in Ising universality class, are used as prototypes to
illustrate how density fluctuation captures the tipping point from
instantaneous spatial configurations. The agroecosystem demonstrates
experimental evidence that the existence of an Ising-type tipping point
depends on the dynamics properties of the system. In addition to
detecting tipping points, early warning signals were able to infer
ecological processes from spatial patterns of the agroecosystem. As
spatially high-resolution data are becoming increasingly available,
density fluctuation offers a novel perspective on anticipating tipping
points and identifying ecological processes from spatial patterns.