Application of a Maximum Sustainable Yield Model to White Sturgeon ( Acipenser transmontanus )

1. Application of a Maximum Sustainable Yield Modelto White Sturgeon (Acipenser transmontanus) Erin M. Collins Advanced Ecology Fall 2012 INTRODUCTION White sturgeon populations have been in decline for more than a century. The decline is due to the take of mature spawning fish and not attributed to general over fishing. White sturgeon do not reach sexual maturity until they are approximately 15-25 years old and can live upwards of 100 years. Although their numbers are in decline, there is still an active fishery for white sturgeon. In order to protect the spawning population and provide a fishery for anglers, a restricted fishery has been enacted. Take is restricted to fish between 46-66 inches and one angler may keep only three fish per year, this is monitored by a report card system. Maximum sustainable yield is a management tool created in the 1930’s as a way to combat worldwide declines in global fisheries. This tool seeks to determine the maximum exploitation level a population can handle without crashing. The idea is that is a population is held at a level where it is growing at its maximum, that there will be a surplus of individuals available for harvest. OBJECTIVE The purpose of this project was to apply a maximum sustainable yield model to an artificial white sturgeon population. ABSTRACT A simple maximum sustainable yield model was applied to an artificial white sturgeon population. The model was an adaptation of the logistics growth model and the Graham-Schaefer surplus production model. The application was unsuccessful. The population crashed with the addition of the harvest. This was most likely a result of user error and artificial data used in the model. RESULTS I could not get the model to work with the parameters that I selected. I used the calculated maximum sustainable yield value of 1,563 tons but the population crashed. Then I tried to use the yield equation instead, value is 138, but this also crashed the population. When population equilibrium at maximum sustainable yield was calculated I got a negative number. Figure 3: The study subject white sturgeon Acipenser transmontanus. DISCUSSION I could not successfully model the sturgeon population using the maximum sustainable yield equations that I found. When deciding on a model I had many to choose from, which leads me to believe that there is not one single model, and that not every model will work for each type of species out there. When modeling sturgeon, the model will need to include parameters for slot limits and life stage. Data on their population growth rates and their catch ability will also need to be readily available for use in the models, they currently are not published anywhere. I believe that because I did not have access to any data and therefore had to make up the model parameters, that I ultimately caused my population to crash no matter the values that I used. Table 1. (Left) Equations used to calculate maximum sustainable yield model. METHODS The model chosen for this project was a combination of logistics growth and the Graham-Schaefer sustainable yield equation. Equations for maximum sustainable yield and equilibrium were taken from the literature. Reasonable values for the parameters were adapted from the literature as well as knowledge of the life-history of white sturgeon. Actual values could not be found in the literature. Definitions of parameters N= population size X= population biomass Y= yield r= intrinsic rate of increase q= catch ability quotient K= carrying capacity E= fishing effort Table 2: (Above) Values used in calculation of maximum sustainable yield and yield calculations. Figure 1: Graph shows how the sturgeon population biomass behaves under logistics growth alone. The population increases until its carrying capacity when population growth slows down. Figure 2: Graph shows the effect of harvest on the populations biomass. Harvesting at both maximum sustainable yield and calculated harvest levels caused a crash in biomass.