Exploring Pattern Analysis with Sycamore Aphids

Many students enjoy biology as a qualitative science but struggle with its quantitative aspects. Yet the detection of patterns and testing hypotheses about their causes is a central aim of biological inquiry. That is the goal of the laboratory analysis described in this article. This exercise involves the students right away in collecting data from living organisms, calculation of some basic statistics, and the formal test of a hypothesis. This fall will be the 10th year I've used this exercise at the college freshman level, but I believe this lab could be used on almost any campus and adapted to any class size. The equipment requirements are minimal and the protocol is simple to follow. The real value lies in empowering students to work with their own data and to see that patterns in biology can be approached quantitatively (requiring only algebra), all critical tools for inquiry-based learning. The aphid of study, likely to be found on practically any sycamore tree in North America, is Drepanosiphum platanoides (Schrank), a relatively large "pale or dark green or reddish yellow species with the wing veins slightly dusky" (Essig, 1958, p.234). A few other aphids may be found on sycamore leaves (Drepanaphis spp., Periphyllus spp.) and may be used instead. The point is to illustrate how individuals in a population may be distributed and to test a null hypothesis of randomness that, if rejected, suggests a host of possible biotic or abiotic causes. To activate student interest in the project, solicit their own ideas for causes, after a brief discussion of aphid biology. What follows is the handout I give to the students on the first day; they have a week to complete the lab. After the handout discussion is a section for the instructor on implementation of the techniques used and some possible extensions. Purpose In this lab you will practice important aspects of biological inquiry: observation, data collection, data analysis, and scientific writing. You will work in pairs and do the lab on your own time. The objectives of this laboratory are: 1. to become familiar with how to calculate a sample mean and variance 2. to become familiar with population sampling and data analysis 3. to collect your own data from live organisms and puzzle over a real biological pattern. Ecology has been defined as the study of the distribution and abundance of organisms (Andrewartha & Burch, 1954). This is because patterns we see may reflect and reveal unseen ecological relationships. Thus the analysis of spatial pattern can lead to a better understanding of the biotic and abiotic forces that affect organisms. Our null hypothesis may be that individuals of a species are distributed at random, implying no particular interactions with each other or the environment. For example, when cottonwood seeds drift down onto a newly-formed Platte River sandbar, they may land randomly (that is, any chosen square meter of sandbar has an equal probability of receiving a seed). Later, the emerging seedlings may not show a random pattern. Pattern analysis might reveal a population of organisms to be aggregated (clumped) or evenly-distributed (regular). Both terms refer to a deviation from randomness that can be quantified. One must use care in selecting a technique for sampling organisms that will not bias one's results. Also, different techniques and scales will have different powers of detection. For example, consider that a newspaper photo represents an image at a distance but only dots of various sizes on very close inspection. What we choose to measure, count, etc. has a great influence on the pattern we detect. In some cases, sampling units (SUs) present themselves naturally (i.e., leaves on a plant). In other cases we may choose the size, shape, and location of the SUs. Over a century ago, two University of Nebraska graduate students (Roscoe Pound & Frederick Clements, 1898) championed the use of the quadrat in plant community analysis. …