Quantifying spatial and temporal variability of spatially correlated disturbances

摘要: Abstract We propose three metrics to quantify the spatial and temporal structure of events within dynamical systems. Although original intention was develop separately variability or clustering, our ultimate conclusion is that it impossible completely separate space time. The observed a system depends on scale over which measurements were taken, measurements. explore two variations basic contact process lattice population model where, instead individual sites becoming empty independently, larger-scale disturbance simultaneously affect several sites; these may either be arranged contiguous block, sampled from larger region. adjust rate such in way per-site held fixed. Changing disturbances while controlling induces changes as well (depending at measured), because occur less frequently. Analytical results are obtained for particular using hypergeometric distribution, but spatiotemporal can also applied numerically observations simulations field data level variation spatially structured find intermediate scales most useful indicating success population; micro- (single sites) macro- (entire landscape) miss fundamental features system. versions go extinct widely different disturbances, have very similar critical values persistence among models.