Sometimes taking another look at apparently simple experiments, that we do all the time with students for example as demonstrations, can inspire a new look at long held assumptions about what we really think we know. Indeed, much of ecological theory about animal behaviour is based on interpretations of observations limited to discrete time intervals and seasons.
Our most recent article was inspired by a problem we encountered during a field ecology school when a group of students wished to interpret the results of a light avoidance experiment with crabs. In marine ecology, researchers have long relied on observations made in experimental containers of different types, like aquaria and raceways. Using these containers allows the ecologist to observe and record movements of individuals under different stimuli, and under near continuous conditions (at least for the duration of the experiment).
How to represent movement of organisms?
The hardest part is developing a consistent representation that is simple, yet allows the probabilities of each movement observed to be estimated. Even when movement is constrained by an experimental container, like these raceways (excerpt of Figure 1 from our article), the number of possible combinations are quite high. This is an important step to be able to interpret behaviours, such as preference for a a particular food, or light conditions.
While these types of experiments appear quite simple (hence their prevalence in basic experimental ecology courses) the analysis and interpretation of results are fraught with difficulties. An important challenge is how to decide what to compare observations with in order to interpret behaviours. In this article, we propose a quantitative "reference" state for the distribution of behaviours that can be expected which is then used as a basis of comparison for experimental results.
Abstract
"The technical difficulties of performing underwater observation implies that marine ecologists have long relied on behavioral experiments to study reactions of marine organisms. In this article, we examine the underlying complexity of assumptions made in raceway experiments and we propose a statistical inference proceduretailored to this type of experimental protocol. As an example, experiments were performed to test if light of two different intensities affects the proximal behavior (i.e. direct, local and immediate) of two species of crustaceans, the hermit crab (Pagurus bernhardus), and the green crab (Carcinus maenas). Individuals were collected in the vicinity of the Sven Loven Marine Center in Tjarnö (Sweden). Their movements in raceways were recorded and the statistical distance between the resulting experimental distribution and a simulated null distribution was used to compare their behavior in two situations : dim (when they were expected to feed) and bright light (when they were expected to shelter). Initial tests indicated no differences of behavior between dim and bright light for the two species. However, when compared to the reference state (here, a null distribution) the behavior in dim light deviates significantly from the null distribution suggesting non-random behavior. Our results suggest nonetheless that efforts should be made to understand the behaviors of the individuals of these two species to establish a comprehensive reference state as a basis for comparison. This fundamental information should be a pre-requisite before implementing experiments testing how potential disturbances affect individual organisms in behavioral ecology
Citation
Guarini, Jean-Marc, Coston-Guarini, J., Deprez, T., and Chauvaud, L. (2019) An inference procedure for behavioral studies combining numerical simulations, statistics and experimental results. J. of the Marine Biological Association of UK. 1-7. doi:10.1017/S0025315417001783