|Document Type:||Journal Article|
|Title:||Quantifying aggregation and association in three dimensional landscapes|
|Author:||M. D. Scheuerell|
Interactions among organisms depend on their spatial distributions. In particular, meaningful interpretations of the role of these interactions in structuring population, community, and ecosystem dynamics depend on the scale of analysis. Here, I develop two statistical methods for analyzing patterns in the aggregation and association of organisms inhabiting pelagic ecosystems that are inherently three dimensional. The first method only utilizes data on the nearest neighbors of individuals and works well for multiple comparisons over species or time, but it is not designed to test for departures from a Poisson random distribution toward uniformity. The second approach, however, takes advantage of the measured distances among all of the sampled individuals in the population and can test for departures toward uniformity. I also develop an edge correction to account for the biases associated with sampling by hydroacoustics, an effective means for measuring the three–dimensional positions of organisms in pelagic ecosystems. I used empirical data on the locations of predatory and prey fishes obtained with hydroacoustics in Lake Washington to illustrate how three–dimensional patterns of aggregation and association of predators and their prey can be assessed with these metrics. I found that prey fish were aggregated only during the day and at spatial scales of 1 m or less. Their potential predators, on the other hand, were aggregated at all spatial scales up to 5 m during the day, but only at scales <3 m at night. Predators and their prey were positively associated with one another at scales of 0.5–1 m during the day, but not at all during the night, reflecting the visual foraging nature of the predators and their high mobility relative to their prey. Furthermore, predators and prey were negatively associated during the night and at scales >2 m during the day, which may reflect predator avoidance. These results highlight how high–resolution, three–dimensional data on the spatial positions of aquatic organisms can improve understanding of the spatial scaling of interactions among organisms in pelagic ecosystems.