Qualitative Methods to Surveying Kelp Forest Species Distributions at Hopkins Marine Lab
In the field of ecology, understanding the abundance and distribution of species is essential to determining relationships(Brown 1989). This information is obtained by a number of techniques falling within either experimental studies or observational surveys. These two techniques each have their advantages and drawbacks, which include likelihood of error, necessary time and monetary investment, and ethics(Black 1996). Within the category of surveys, the investigators may take either a qualitative or quantitative approach to collecting their data. This survey of kelp forest species at Hopkins Marine Labfocused primarily on determining the distribution of algal, invertebrate and fish species that were sampled. By taking this survey qualitatively, the aim was to gain an understanding of the abundance of each species. Qualitative assessments can be effective in determining social interactions between organisms, but often have drawbacks in determining all of the underlying factors influencing them(Pope 1995). The species targeted were chosen because knowing their distributions gives insight to the species interactions in the kelp forest ecosystem at the Hopkins site. With a general knowledge of the feeding hierarchy of this species list, these insights may include foraging habits for fish and invertebrate species. Another insight may be of the affects on algal density and biodiversity on the densities and biodiversities of higher trophic levels.
Questions we hope to answer with this survey include: What is the effectiveness of qualitative sampling between different taxonomic groups? Do certain characteristics of individual species have a significant effect as well? Do divers have differing data? What factors influencing their data collection techniques could cause this? How strong is the variance with respect to depth and distance along the meter tape? Are there any other factors that could be causing variances in the data collected?
The survey was done with a 30 meter transect done in both the on and offshore directions from the cable by each buddy pair. Each 30m transect was composed of two data sets. Each buddy took abundance data for the 28 species during both outward and inward kicking portions of the transects while reeling or unreeling the transect tape. The buddy pairs were spaced every 5 meters along the cable from the 80m - 145m marks. Species abundances were recorded on the data sheets for each 10m section of each 30m transect. The abundances were recorded as numbers 1-5, representing an absence, rarity, presence, commonality, or abundance for each species.
Survey data was taken at Hopkins Marine Lab kelp forest, a subtidal, low disturbance dive site in Monterey, CA. It is primarily composed of granite rocky substrate although there are patches of sandy bottom. The cable that transects were run off of runs close to the contour line, parallel to shore.
After collection, the data was then analyzed via comparisons between buddy pairs, the deep vs. shallow transects, and distances along each transect tape. The percent variances of all the data between these factors was calculated and graphed in figure 1. Additionally, each taxonomic groups data was compared by these factors and graphed(figure 2). The mean abundance data for each species individually was calculated and displayed in figure 3. Then, to see difference in data recorded by buddies for each species, percent difference graphs were created for both 1-5 abundance rating(figure 4) and for presence vs. absence(figure 5). Finally, a relative difference percentage graph(figure 6) was created for the buddy pairs with regard to mean abundance of all the species together.
The data in the variance component analysis graph[jf1](figure 1) shows that the distance along the meter mark had the greatest percent variance in data at 41% and an almost equally high value between buddy pair data at 38%. The third computed value, variance by depth, or transect direction, was a much lower 23%, but still a significant variance in data.
The variance components by taxa graphsagain, don’t refer to the graph in this way. Make your statement and follow with a figure reference (fig 2) seen in figure 2 display the same comparisons, but divided into taxonomic groups. This new look at the data shows that for the algal observations, the most variance was again seen between buddy pairs and meter distance. For the fish data however, buddy variances were significantly lower, at less than 20% while the meter distance component increased to nearly 60%. In the final graph we see that for the invertebrates, the only variance components were between buddies and transect depths, each composing 50% of the total variance. Be concise! These last sentences can be a single short sentence and say the same thing.
The results of our mean abundance calculations show relatively low abundances for all the fish species with none above “rare”. For the algae, we see distinct distributions, with Macrocystis and Cystosiera being characterized as “common”, and all the other species besides Polysiphonia as “rare”. Polysiphonia seemed to be “absent” most often. The distribution of invertebrates is much less organized (????). The most abundant species is clearly [jf2]Patiria miniata, or the bat star, which is ranked between “common” and “abundant”, with the next most common species, Pisaster giganteus,or the great spined star, reaching only just above “present”. Species seemingly [jf3]absent were Urticina lofotensis(white spotted anemone), Haliotis rufescens(red abalone), and Strongylocentrotus fransiscanus(red urchin).
Figure 4 displays graphs of the relative difference between buddies for each of the species. The fish species all showed a similar percentage besides Sebastes chrysomelas, the black and yellow rockfish, which was only around 10%. Most other species surveyed abundances differed by 25-40%. The algal species were also fairly even in their relative differences around 20-30% besides Dictyoneurum reticulatum and Dictyoneurum californicum, which were both characterized differently by 50% between buddies. The invertebrates showed much more variation in their relative difference. Five species(Balanophyllia elegans, Calliostoma ligatum, Pachycerianthus fimbriatus, Pisaster giganteus, Tethya aurantia) hadrelativedifferences of 50% or higher, whilethree species (Urticina lofotensis, Haliotis rufescens and Strongylocentrotus fransiscanus) were 10% or less. The remaining five species ranged between 10-50%.
The graphs in figure 5 display the percent disagreement between buddies when the data was simplified to just a presence or absence of each species. This data give very similar results to that of the original data except in the cases of Cystoseira, which showed a much lower percent difference, and Macrocystis and Patiria miniataw, which showed a 0% difference.
The display of percent difference between buddies by mean abundance of species in figure 6 shows that species that were more rarely seen were more likely to have different abundance values recorded by their observers.
Qualitative surveying has been found to be very useful in learning the distributions and abundances of certain species and lead to findings about their ecological interactions(Hallacher 1985). The results of the mean abundance observation for this survey (Figure 3) show a distribution that is composed primarily of invertebrates and algae with fish species being the more rare organisms in the ecosystem. The dominant species within these two groups are Cystoseira, Macrocystisand Patiria miniata(figure 3). These three species have also been sampled the most accurately with respect to relative difference between buddies’ data in both the abundance rating and the present/absent comparisons (figures 4 and 5). The rarest organisms found in each category had the next lowest relative difference values (figures 3, 4 and 5) besides Polysiphonia (we didn’t sample polysiphonia. ?????), which has a very high difference percentage for unknown reasons. The group with the most difference in data between buddies falls on the intermediately distributed species. This could likely be attributed to divers being less knowledgeable in this range of species. This could also be the result of divers under the pressure of remembering a distribution of 28 different species, found it easier to notice and recall a vast “abundance” in few species and occasional“rare” or “absent”species, than distinguish between the “common” and “present” categories for the species that fall within.
Species that seem to have very distinct characteristics, such as coloration or size seem to be more accurate as well in a presence vs. absence percent difference comparison(figure 5). Examples include Macrocystis which would be difficult to miss for its sheer size, and Sebastes chrysomelas which when seen, is very distinguishable with its bright yellow and black patterning.
The final, and most likely reason for the widespread difference in buddy observations is found in the knowledge that each diver has a different opinion of what each of the abundance characterizations means in terms of species numbers and density. Many of these opinions depend on what the diver’s history is and whether or not they consider these abundances to be relative to only the species listed, or relative to their past interaction with such species and environments.
The variance in the data due to meter distance is slightly more substantial overall than that due to buddy comparisons and significantly more so for the alga and fish taxons. Although the reason for the nonexistence of variance in the invertebrate data due to meter distance is not known, reasons for the very high values in the other two groups are numerous. For the area where sampling was done, the substrate type varies from rocky reef to sandy bottom equally in both depths. Because each buddy pairs data was divided into only these two depths vs. the six divisions of 10 meter distances along the two transects, the chance of variability of substrate change with respect to 10m sections of tape is much higher. This higher likelihood of substrate variability correlates with the higher variance in the data found for meter distance.
There were a variety of factors that make much of this data too variable for use in a deeper ??? ecological sense. All of this data does however provide use with lessons on survey techniques and the role that taxon and species level characteristics play in collecting qualitative data.
Black N. 1996. Why we need observational studies to evaluate the effectiveness of health care.BMJ 312: 1215-1218.
Brown, J.H and B.A. Maurer. 1989. Macroecology: The division of food and space among species on continents.Science243: 1145-1150
Hallacher, L.E. and Roberts, D.A. 1985. Differential utilization of space and food by the inshore rockfishes (Scorpaenidae: Sebastes) of Carmel Bay, CA.Environmental Biology of Fishes12, 91-110
PopeC and N.Mays.1995.Qualitative research: reaching the parts other methods cannot reach: an introduction to qualitative methods in health and health services research.BMJ311:42–45
Variance Components by Taxa
__0__/4 Figure legends Accurate
__0__/4 Figure Legends well composed (complete and concise)
__4__/5 Results organized according to questions
__4__/4 Graphs presented in a logical order, case made for the order
__4__/4 Grammar, sentence structure and spelling
__2__/4 Clarity and conciseness of writing
____/9 How well did they answer the questions they present in the Intro?
1)_3___/3 Discuss the results from the specific to the general.
2)__3__/3 Do these results surprise you? In other words, is the qualitative method more or less reliable than you thought it would be, and do you think that degree of reliability (which can be assessed based on relative difference between buddies) implies anything about accuracy?
3)__3__/3 Do you think the qualitative sampling approach is appropriate for describing trends of species abundances through time? Explain your answer
__2__/3 Grammar and Spelling
__2__/2 General Thoughtfulness
__2__/3 Clarity and conciseness
__4__/5 Organization of discussion
__3__/3 Context and Bigger Picture
General Notes: Figures always require legends. This gives the reader the ability to interpret the graphs without referring to the text. You hit on a lot of good points, but your discussion can be better organized. Be concise!
The discussion is a good place to talk about the larger application of the research.
[jf1]Very wordy, just make a statement of the results.
[jf2]Avoid these modifiers, they are wordy and don’t add to your satement