1. A2A2 H1H1 H2H2 The food web Primary producers Primary consumers D Detritus and associated Microflora (bacteria/fungi) P Death and sedimentation herbivore detritivore A1A1 inedible Secondary Productivity: Primary production supports a web of consumers—a simple example Productivity Biomass

2. Defining some productivity terms Birth (production) term Death (loss) term B bB/t mB/t

3. The productivity is a combination of the birth of new organisms and the growth of the organisms already present Similarly, the death process is a combination of death of organisms and weight loss by existing organisms. If the productivity (birth term) exceeds the death term the biomass is increasing, and if the death term is larger, the biomass is decreasing Time (t) Biomass of a consumer

4. Time (t) Rotifer Biomass So if we measure and B at any point in time and we can estimate the specific birth rate, we can then obtain the specific death rate by subtraction.

5. For a tiny consumer like a rotifer the birth rate is easy to estimate since the adult females carry their eggs around until they hatch When they hatch they come out as full sized rotifers. If we know the fraction of adults carrying egs and the average time it takes for eggs to hatch, we can calculate the birth rate. Since the rotifers are born more or less full size, so there is no need to model or measure the growth of individuals. A tiny organism like a rotifer is born at full size, so productivity amounts to measuring the rate at which new animals are born Rotifers carrying eggs

6. Time (t) Rotifer Biomass

7. For a large organism like a fish, biomass production occurs mostly from individual growth. New born fish are so tiny that birth of individuals makes a negligible contribution to biomass production Year classes The W t represent the Weights of each year class We can calculate the growth rate of biomass individual fish by weighing fish and determining their age and then seeing how much weight they gain each year. The productivity of each age class is the Specific growth rate (SGR) of that age class times the total biomass of that age class in the population.

8. This approach assumes that the size vs age relationship is relatively constant. The W t represent the Weights of each year class

9. By this method the average SGR for the whole population can be calculated as the weighted average over all age classes However there is a problem with this approach…???

10. However there is a problem with this approach. By considering only the gain in weight across age classes, this method ignores weight gained and lost within the same year, eg Gonad tissue Adult fish usually convert a considerable portion of their body mass to gonads and release it during spawning every year. Thus it does not add to next year’s weight and would not be recorded as growth We can quite easily correct for this by factoring in gonad production (add GSI) We would of course only make this GSI correction on adult age classes.

11. Scales of a chum salmon 2+ 3+ 4+ Measure distances from scale center to each annulus along a chosen axis How can we tell how old a fish is?

13. LALA Age yr Convert the growth curve based on length to weights using a length-weight plot for the species This allows us to construct a growth curve based on length and age.

14. Many types of bony structures are commonly used to determine age of fish Scale Otolith Opercular bone These three structures are all from the same 3+ year old 30 cm cutthroat trout

15. The specific death rates can also be estimated from the population structure. This time we assume that the age structure of the population is constant, and that the numbers of individuals of each age within a sample reflects the proportion of that age group in the population. Assume we have a sample of 215 pike from a population. The N t /  N t represent the proportion of the population in each year class

16. Age 135 0 * * * * 110 30 55 20 # 0 50 100 The survivorship curve assuming stable age structure for the population looks like this m 1 =0.69 150 m 3 =0.41 m 2 =0.61

17. Productivity termloss term Summary