Introduction In this lab, we will be examining the effects of Sea Star Wasting D

Introduction
In this lab, we will be examining the effects of Sea Star Wasting Disease (SSWD) on the common sea star Pisaster ochraceus. P. ochraceus (Echinodermata: Asteroidea) was described as the very first keystone species, where it has a tremendous impact on the rocky intertidal community despite being present in relatively low abundance (Paine, 1966; MacDonald, 2016). Basically sea stars are eating machines and can remove the dominant competitor mussels (Mollusca: Bivalvia we will get here in Week 5!) allowing many other invertebrates to live in the rocky intertidal zone. Therefore, removal of this sea star leads to a decrease in the number of invertebrates you find in an ecosystem as this single species remarkably controls which organisms can survive.
In 2014, many asteroids were affected by SSWD and started to die. As the disease progresses sea stars start to lose their grip, get twisted arms with lesions forming eventually leading to arms falling off and death of the animal. Death of this animal can then have cascading effects on the rest of the community of animals.
Questions, hypotheses and predictions
Wildlife managers and scientists work together using data to make informed decisions about how to ensure that species do not go extinct. Here, I want you to assume the role of a scientist working at the Oregon Department of Fisheries and Wildlife to determine if P. ochraceus is endangered. Your boss also wants answers to the following questions and your working group has come up with 3 hypotheses that could be tested. In this lab I want you to address 1 of these 3 questions and hypotheses using the dataset found in Canvas.
Question 1) Has SSWD significantly decreased the abundance of P. ochraceus along the Oregon Coast?
Hypothesis 1) P. ochraceus is susceptible to SSWD, because other sea stars are susceptible and there is no adaptive immune system in echinoderms
Question 2) Are seastars differentially affected at different “sites” along the Oregon Coast (i.e. where should conservation efforts be concentrated)?
Hypothesis 2) P. ochraceus will be differentially affected at different “sites”, because the pathogen likely travels via water currents and some “sites” may be more protected than others.
Question 3) Are seastars differentially affected at different “capes” along the Oregon Coast?
Hypothesis 3) P. ochraceus will be decreased more in Southern “capes”, because Southern “capes” should have warmer water making the animals there more susceptible.
Experimental design
As part of PISCO observations, sea star abundance has been measured several times a year dating back ~25 years. Your working group has been collecting and collating data on P. ochraceus abundance from 2012-2015. SSWD was first spotted in July of 2013 along the West coast starting in both California and Washington.
Fig 1. To the left is a map of the Oregon Coast showing the “sites” sampled. The Oregon/California border is South (warmer waters) and is depicted on the Map. The Washington/Oregon state border is the Columbia River (North: Colder waters). There were three sampled “capes” (multiple “sites” are present in each “cape”): Cape Blanco (Southernmost cape), Cape Perpetua and Cape foulweather (Northernmost cape).
I highly recommend you watch the videos associated with this lab (Dr. Sarah Gravem interviews 2 and 3 associated with lab 3) to see how these data are collected!
In brief, several times a year seastar abundance “Total SeaStars” were counted along a belt transect as detailed in the videos. Each belt transect was 20 m2 in total area, so we can calculate density (“density_stars/m2”) as the total number of P. ochraceus found divided by 20 m2. At each site, the belt transects were laid out multiple times to create replicates (“rep”).
Instead of repeating all the details in the videos, I will just highlight what the variables in the data set represent.
“Cape”: the cape it was sampled from.
“site”: is the sampling location within the larger geographical “capes”
“Year”, “Month”, “date”: When the samples were taken
“annual sample no.”: How many times in a given year a site was sampled.
“rep”: the replicate number. At each site, on any given date, multiple belt transects were done to count sea stars. Each separate belt transect was a replicate (“rep”)
“species”: Although Dr. Gravem’s team examined lots of species, for simplicity we will look at only P. ochraceus.
“Total SeaStars”: The total number of P. ochraceus found along the belt transect
“Area_m2”: the total area searched in a single belt transect. Should by 20 m2 for all in this dataset.
Lab 3: Sea Star Wasting Disease along the Oregon Coast (5 pts)
Lab 3: Sea Star Wasting Disease along the Oregon Coast (5 pts)
“density_stars/m2”: “Total SeaStars” divided by “Area_m2” or “Total SeaStars” /“Area_m2”
Statistical tests (analyzing the data!)
Please refer back to lab 2 for how to do common statistical tests. Please let me know if you have any questions!
Questions:
1a) Which hypothesis are you testing (1,2 or 3)? _________
b) Please write your prediction (If the hypothesis is correct, then… (2 pts)
2) There are lots of ways you could design your experiment to test your predictions. Likely you can see if your prediction is supported or rejected by using a t-test. Please analyze the data as you see fit and report back if there was a significant effect of SSWD on seastars.
For a t-test, a good way to report your data is using the formulaic sentence below.
“There was/was not a significant difference between __________ and ________ (t=###, df=##, p=##).”
(2 pts).
3) Was hypothesis your team’s hypothesis supported? Why or why not (1 pt)?
Please write answers to this assignment in a separate file and submit to Canvas Sun Week 3 by 11:59 pm.
MacDonald, 2016: https://daily.jstor.org/how-the-keystone-species-c…
Paine, R.T, 1966. “Food web complexity and species diversity”. The American Naturalist. Vol. 100 (910): 65-75.