In the last post, I discussed scaling in fisheries habitat science. I finished by talking about limiting factors, or the variable that is not allowing a fish population to grow. Often, determining what is actually limiting a population's growth is incredibly difficult and can be different for fishes of different ages, species, and locations. In that case, how do fisheries biologists determine what actions to take to try to help struggling populations and grow their populations? Well, we start with conceptual models. Unlike some models that provide specific, quantitative predictions and are often used at the expense of real, on-the-ground data collection, conceptual models just provide a hypothesis. Conceptual models are basically a set of qualitative ideas about how fish populations respond to different variables. For example, a simple qualitative model might predict that land uses such as grazing, farming, and urbanization will impact water quality metrics such as sediment and temperature which will in turn affect the parameters of population growth (see Fig. 1). It does not make specific predictions about how much sediment input will be changed by grazing or how a food supply will be impacted. It simply suggests there might be an impact.
Once a conceptual model like this is created (and it can simply be an idea not a drawn out diagram),
biologists can decide what parameters of each section are having the greatest impact on the next section (i.e. that grazing is causing increases in temperature that is causing higher juvenile mortality). This provides a starting point for a biologist to make an alteration in a system and watch the response of the population. If the population does not respond as predicted, the biologist will need to rethink the conceptual model or determine if a different parameter is responsible.
Conceptual models can be especially useful at large scales where climate, hydrology, and geology all impact streams in different ways and have impacts on large and small scale parameters.