Free Custom «Causes of Zonation on Sheltered Rocky Shores» Essay Paper

Free Custom «Causes of Zonation on Sheltered Rocky Shores» Essay Paper

Overall aim: in lectures you will learn about the influence of major environmental and biological processes on the patterns of distribution of rocky shores communities; you will learn how classical and recent experiments have been done to understand the causes of these patterns. This practical will give you a chance to look for evidence that environmental gradients and/or interspecific competition influence species zonation.  You will gain experience in the ‘scientific process’ of formulating a hypothesis, testing it empirically and writing up your findings in a scientific report.

Overview of activity. You will work in groups of ~5 students. Each group will collect data on the shore; in the laboratory groups will analyse the data and start writing the Methods and Results sections of the report. You will also do a spot test on identification and natural history (field guides can be used) based on the shore work. Following the practical, Groups will complete the Methods+Results section, and individual students will write their own Introduction and Discussion of the report. See below for full details on requirements for the Group and Individual Student reports.


Shore activities

You will sample a vertical transect of the shore. Each transect is sampled by two student groups (10 students); the two groups share the transect data. Students work in pairs or three together, sharing one 50×50 cm quadrat, a 1-meter ruler and a note book.

Within your transect, identify 3 shore zones based on the dominant algae: Pelvetia, Fucus spiralis (use F. vesiculosus if a clear F. spiralis zone is absent) and Ascophyllum zones. In the centre of each zone, each set of 10 students should do the following:

1. Quadrat observations

•  H1. Algal cover. In a minimum of five, randomly located, 0.5×0.5 m quadrats per group of 5 students, estimate the percentage cover by algae. Without moving plants, first estimate what percentage of the quadrat area is covered by canopy species (‘Total cover’ of all species); then estimate the Cover by each individual species (you may lift plants), then estimate the cover of under-storey and turf species. Note: as the seaweeds are in different layers, the ‘Sum’ of the cover of all species can exceed 100%.

•  H2. Maximum plant height. Inside each of the five quadrats, record the height of the five biggest plants (from rock to tallest tip per clump) for the dominant fucoid species per zone (i.e. Pelvetia, Fucus spiralis, F. vesiculosus, Ascophyllum, respectively). Be sure to write down the species name for each observation. DO NOT PULL OFF THE PLANTS TO MEASURE THEM, leave them attached.

2. Timed searches

•  H3. Species counts. For each shore zone, working in pairs, make a 5 minute timed search for all the species you can see. Record both the animals and the plants. Avoid removing algae or sessile animals unless strictly necessary for laboratory identification.Laboratory activities

Collect all the data for the transect (from your group + your partner group). Each group (5 students) will then spend the afternoon drafting the Methods and Results section for the report. Most likely, this task will have to be completed after the practical. All group members will use the same Methods and Results section, so make sure that each member of the group receives a copy of it. The Leader of each group must hand a copy, or email, the draft group Methods and Results to the course organiser before leaving the lab at the end of the day. You then can finalize it amongst yourself in your own time and hand in one version by the deadline.

To complete the Results the group should do the following:

Generate appropriate plots to represent your data. Plot the mean±s.e. percentage cover versus shore zone (s.e. = standard error = st.deviation/√n): plot the Total canopy cover, the cover per fucoid species (Pelvetia, Fucus spiralis, F. Vesiculosus, Ascophyllum) and one for the Sum canopy cover (sum cover of all species). Do not make plots for under-storey or turf species or sub-dominant canopy species. Example plots will be shown in the practical.

From max plant height observations

Plot the mean±s.e. maximum plant height versus shore zone. If time, you might consider doing a 1-Way ANOVA to test the effect of shore zone (shore level) on the average maximum heights of algae. See your first year ‘Key Skills’ notes for how to do this; you may have to log-transform your data to meet the ANOVA assumptions of homogeneity of variance. If significant, follow any significant ANOVA by a posthoc comparison to establish which shore levels differ in mean plant heights. Ask demonstrators if in doubt.

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From species counts

Calculate and plot the mean±s.e. no of species per shore zone for: i) algae, ii) animals, and iii) algae+animals. You can also draw curves of cumulative species numbers versus the number of timed searches you did (ask demonstrators for help).

Following the practical, each student will produce a 2 page (maximum) Introduction and Discussion to accompany the group Methods and Results section. Be sure to state the tested hypotheses in the last paragraph of your Introduction (you may re-state the hypotheses from this document). Please, make full use of the relevant literature in your Introduction and Discussion and finish your report by listing the References you cited. The References can be on an additional page and are not included in the page limit. Model the format of your report on a paper in a scientific journal.

All journals put online their ‘Instructions to Authors’ which you could choose to follow. In particular be sure to cite references appropriately in your text -  E.g. Smith et al. (2006) and Duncan (2009) found that pigs can fly; or:  Pigs can fly (Smith et al. 2006; Duncan 2009). Consult your 1st year notes on how to write a scientific report/paper, how to use references appropriately and how to construct your reference list. There are also good guides in the Deiniol Library (search the Catalogue with terms ‘writing scientific report’ or ‘report writing’). At the bottom of your cover-sheet to the report, please write your group number and the name of your group leader.

Ynys Faelog has clearly visible dominant fucoid zones. The vertical transect of the rocky shore was sampled during a mean low water neap tide. The 3 zones sampled were (Ascophyllum nodosum, Fucus spiralis and Pelvetia canaliculata).  Sampling began at the Ascophyllum zone at the beginning of the flood tide. The study was conducted in pairs using a 0.50m2 quadrat and a 1 metre ruler to ensure consistency in the sampling.

To test H1, pairs each took 3 random quadrats (total of 15 quadrats for the group of 5) at the centre of each zone; this was done to give a representative sample of each zone. The total percentage cover of algae and the percentage cover of each species were estimated using quadrats.  The percentage cover of algae inside a quadrat was estimated without moving the canopy species. To estimate the percentage cover of each species, the canopy species were lifted to see the turf species below.

To compare the competitive abilities of algal species (H2), the heights of the five tallest individual plants from each quadrat was measured in each zone. The seaweed was measured from where the holdfast is attached to the substrate to the tip of the frond. Care was taken not to pull the flora off the substrate, as species such as Ascophyllum nodosum can take 15 years to reach current length (Martin Skov, personal comment)

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To investigate the environmental conditions (H3), repeated species counts of macro- fauna and macro-flora were conducted for 5 minutes at each zone along the vertical transect. All species were left in situ with a protocol decided that removal of algae or sessile fauna would only be for lab identification.

Data from the 2 groups of 5 was collated. The mean was calculated from the percentage, height and number of species per zone for the species count in the quadrats to compare the differences at each zone.  Standard error was also calculated for the percentage cover data.




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