This week’s blog was written by Nathan, a 2019 Drummers alum. Nathan is a student at Penn State. He returned to field school this past summer as a member of the Academy Support Team.
Today I went with my wildlife measurements class to a local stream at Shaver’s Creek in State College. We went there around noon to do a stream survey of the different vertebrates that can be found in the stream and look at the overall detection probability of certain species.
Detection probability is the likelihood of finding an organism species given a certain amount of time. We did this by flipping over rocks near a stream and seeing what kinds of reptiles and amphibians we could find as a class in a few given survey transects. There was a goal to find about 13 species and a few species that were “bonuses”. This bonus included a special species of salamander that we only knew to be red and a box turtle.
With this in mind, we each formed groups, collected bins for collection, and went made out transects we would be looking through. My group went through 2 transects of 15m of stream habitat with about a meter inland off the shore. From our 2 transects, we discovered about 17 Northern Dusky salamanders, 1 Northern Slimy salamander, 2 Northern Two-lined salamanders, and 2 Pickerel frogs. While ours had some interesting species that we discovered, there was a definite disparity in the detection probability of these different species.
After a while of searching, all the groups came together and we discussed what we found. Besides what was already discussed, other species found were a Spring Peeper, an American Toad, and 2 Northern red-bellied snakes. There were a few other Two-lined, Slimy salamanders and Pickerel frogs, and an innumerable amount of Dusky salamanders. Based on this, we were able to find 7 of the 13 species we wanted to find and were unable to find a single Box turtle or a single Northern Red Salamander, our hidden species. This indicated a very small detection probability for these species.
Detection probability was partially measured based on “human hours” as my professor called it. We had 19 students and 1 professor and were there for 1.5 hours, so we could multiply these numbers to get 30 human hours spent looking for organisms. If we take this number and divide it by any individual species amount, we can then get a general idea of how much time it should take to likely find a certain species. This can be used to help indicate a species prevalence, as without this number we wouldn’t truly understand what a certain quantity means when it comes to species richness and density in an area. This is not as accurate as a complete species count would be for an area and has room for sampling area in many factors, yet it is more practical and gives results that are accurate enough to make an inference about a population if the sampling size is large enough. This can help give important insight into possible areas of improvement for the management of a certain species that might not have been prevalent in the stream survey that was done.
Data is the cornerstone of scientific research, and so I would highly recommend taking a class like this if you have an interest in wildlife management, as it will prepare you for many future careers.
Streamside Discoveries
Posted: October 12, 2024 by Katie Mace
This week’s blog was written by Nathan, a 2019 Drummers alum. Nathan is a student at Penn State. He returned to field school this past summer as a member of the Academy Support Team.
Today I went with my wildlife measurements class to a local stream at Shaver’s Creek in State College. We went there around noon to do a stream survey of the different vertebrates that can be found in the stream and look at the overall detection probability of certain species.
Detection probability is the likelihood of finding an organism species given a certain amount of time. We did this by flipping over rocks near a stream and seeing what kinds of reptiles and amphibians we could find as a class in a few given survey transects. There was a goal to find about 13 species and a few species that were “bonuses”. This bonus included a special species of salamander that we only knew to be red and a box turtle.
With this in mind, we each formed groups, collected bins for collection, and went made out transects we would be looking through. My group went through 2 transects of 15m of stream habitat with about a meter inland off the shore. From our 2 transects, we discovered about 17 Northern Dusky salamanders, 1 Northern Slimy salamander, 2 Northern Two-lined salamanders, and 2 Pickerel frogs. While ours had some interesting species that we discovered, there was a definite disparity in the detection probability of these different species.
After a while of searching, all the groups came together and we discussed what we found. Besides what was already discussed, other species found were a Spring Peeper, an American Toad, and 2 Northern red-bellied snakes. There were a few other Two-lined, Slimy salamanders and Pickerel frogs, and an innumerable amount of Dusky salamanders. Based on this, we were able to find 7 of the 13 species we wanted to find and were unable to find a single Box turtle or a single Northern Red Salamander, our hidden species. This indicated a very small detection probability for these species.
Detection probability was partially measured based on “human hours” as my professor called it. We had 19 students and 1 professor and were there for 1.5 hours, so we could multiply these numbers to get 30 human hours spent looking for organisms. If we take this number and divide it by any individual species amount, we can then get a general idea of how much time it should take to likely find a certain species. This can be used to help indicate a species prevalence, as without this number we wouldn’t truly understand what a certain quantity means when it comes to species richness and density in an area. This is not as accurate as a complete species count would be for an area and has room for sampling area in many factors, yet it is more practical and gives results that are accurate enough to make an inference about a population if the sampling size is large enough. This can help give important insight into possible areas of improvement for the management of a certain species that might not have been prevalent in the stream survey that was done.
Data is the cornerstone of scientific research, and so I would highly recommend taking a class like this if you have an interest in wildlife management, as it will prepare you for many future careers.
Category: Youth Blog Tags: alumni, education, featured, nature observation, stream survey