Measuring everything over a long term period with many subjects is the key to good outcomes in science. A bad example is simply using one or two pairs of Mexicans in one season with one breeding type and calling it good science or good research. You need many many test subjects using the exact same controlled variables to formulate a solid outcome or reproducible predictor or phenomenon. Switching media type year after year to run tests on only one pair is useless and doesn't provide real data that can be axtrapilated across the entire species. It's not until you have enough numbers to formulate a verifiable and reproducible outcome or trend can you then and only then claim anything.



So set them up the same next year and measure again. Repeat enough times to get solid data then change one variable and see if that variable changes your outcomes. That's when you can narrow it down to what variables actually do cause change. Changing to many variables at once will lead to confusion because you can't prove which one was the factor or if they were working in tandom.



In the Mexican example changing everything from year to year proves nothing because you can't prove what variable is the real issue that causes the outcomes to change. That's useless gibberish...



So keep doing what your doing and collect the data. The data will tell you what it means once you have enough to see a trend.



Good luck.

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