Summary of Ecological forecasting

After many papers, chapters of Ecological Forecasting, hours spent learning about Bayesian statistics and ecological forecasting, I have completed my work on ecological forecasting. Originally, I had planned on creating my own ecological forecast but after a good amount of reading and learning about forecasts, I quickly realized that I lacked the tools and understanding to create one of my own. Unfortunately I never got to go sampling in the field during my Monroe but may still go when I get back to school.

Ecological forecasting focuses on combining real data and models. These are two very broad subjects that cover a large range of topics, from trees to fish. Forecasts can be applied to many variables and models across time and space. No forecast is the same because new data should always be incorporated and different models are used for different situations. Different forecasts can also incorporate different levels of ecology including community and population ecology.

Bayesian statistics focus on Bayes’ theorem which can be seen below:

Image result for bayes theorem(

Bayesian statistics incorporates the past circumstances into the probability of the future. It also produces a distribution of probabilities, rather than one number. This method of statistics becomes more and more accurate as the number of trails are done.

Ecological forecasts can be very useful in conservation and everyday life because it can provide information about how people and ecosystems would be effected by changes in factors. For example, NOAA produces ecological forecasts of harmful algal blooms in large bodies of water including the Chesapeake Bay and the Great Lakes. As a result of these forecasts, fishermen in the Chesapeake Bay can adjust their routes accordingly and people looking to swim in the Great Lakes know where it is safest. They also produce forecasts of sea nettles (a jellyfish) in the Chesapeake Bay which influence where people will swim and choose to boat. Besides predicting the location of where organisms will be, NOAA produces forecasts on the best places to plant sea grasses to avoid losing them to ocean currents which improves the efficiency of conservation.

While ecological forecasting can be helpful, some are skeptical to it due to the idea that ecology is a complex topic and our understanding of systems can be underdeveloped. Predicting exactly what will happen in ecology is impossible due to the fact that there are interactions and factors we do know about. There are things that humans know and know they do not know but there are also factors we have no idea are even factors, things we don’t know we don’t know and cannot include in the forecast or the accuracy of the forecast. Also forecasts can provide good predictions, but they are mere predictions and are not completely accurate, as a result the uncertainty and accuracy of a forecast should be clearly stated and worked through.

This project has been very informative and interesting. I am happy to have chosen a topic that is fairly new and still in the process of development. While this has made my research more challenging, it is cool to know that I am one of many who believes this topic is important and will prove influential in the future. Ecological forecasting can be extremely helpful with current issues and will likely prove to be even more helpful in the future when we know more about it.

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