A spatially explicit approach to estimating species occupancy and spatial correlation.

摘要: 1. Understanding and predicting the form of species distributions, or occupancy patterns, is fundamental to macroecology dependent on identification scaling relationships that underlie patterns observed. 2. Occupancy-abundance models based negative binomial distribution Taylor's power law are spatially implicit, rather than explicit, as they include no information relative positions individuals. Here we present a explicit model, spatial (SSO) estimate correlation, join-count statistics, pair approximation, approach. This model provides description range size aspects structure. 3. Occupancy data from Drosophilidae inhabiting decaying fruit mesocosm were used test SSO model. Predictions implicit largely equally accurate. The thus more efficient it less demanding, informative an estimation correlation. 4. results also showed differ when examined with vs. approaches; relationship between local density identifies focal grain for studying scale-dependent nature ecological relationships; longer length sample edge, higher observed under conditions aggregation. 5. presents step towards general occupancy, demonstrates inclusion in macroecological warrants further attention.