Migration tendency in juvenile steelhead trout, Salmo gairdneri Richardson, injected with thyroxine and thiourea

Juvenile steelhead trout, Salmo gairdneri injected with thyroxine (T₄) near the time of seaward migration exhibited a significantly lower migration tendency than untreated controls of fish injected with saline, thiourea, or a combination of T₄ and thiourea. Fish injected with thiourea alone or in combination with T₄ prior to the time of maximum migration tendency showed enhanced migration over untreated and saline injected controls and those injected with T₄ alone. Injections of T₄ or a combination of T₄ and thiourea elevated plasma T₄ and tri-iodothyronine (T₃) concentrations, while injection of thiourea alone depressed thyroid hormone levels relative to saline-injected controls. Plasma concentrations of T₃ and T₄ returned to control levels within 10 days in all groups. We suggest that thyroid hormones are antagonistic to mechanisms underlying seaward migration of steelhead trout and that these antagonistic effects must be overcome before migration tendency is expressed.     

What kind of spatial and temporal details are required in models of heterogeneous systems?

Spatial and temporal heterogeneity can make ecological systems hard to understand and model. We propose a simple classification of the types of spatial and temporal complexity contained in ecological systems, and describe the kinds of data and models needed to account for each. We classify ecological systems by the presence of heterogeneity at the scale of study, the nature of their dynamics (linear vs non-linear), attributes of the patches that constitute the heterogeneous system, and the presence and directionality of interactions among patches. Heterogeneity in space and time are nearly equivalent in our framework. Advanced modeling skills are necessary to create appropriate mathematical representations of highly complex systems (with non-linear dynamics, patches with more than one kind of important attribute, or interactive patches). Simple models can work well when the scale of heterogeneity is much finer than the scale of observation, when low precision is sufficient, when patches interact only weakly, or when empirical approaches are used to fit functions and constants. Having a way to classify complexity in space and time in ecological systems should help ecologists to select modeling approaches consistent with their abilities and goals.