Description

Fieldwork Statistics and Experimental Design

Description - summary of the module content

Module description

Fieldwork Statistics and Experimental Design is a core module in any MSc; it has a transversal character and is the main basis for a rigorous approach to biotic (faunistic and floristic) and abiotic (geographic, climatic, lithology, soils, etc.) data collection and statistical (univariate and multivariate) description and analysis. For this reason, the module sits at the very beginning of the MSc and is delivered as part of a fieldwork approach in a small, nearby islet of the Channel islands (Sark, Herm and/or Alderney), where you can obtain your own data and are subjected to different analytical procedures.

Module aims - intentions of the module

The module aims to teach you to carry out fieldwork experiments, sampling and inventories strategies of plant and animal population and communities, including the fundamentals of the scientific method, the basis of the experimental design, floristic, vegetation and faunistic data collection procedures and the statistical description and analysis of the data obtained.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. Formulate detailed hypotheses that can explain the observations and experiment where the postulated hypothesis explaining the observations can be falsified
• 2. Plan rigorously field-based data collection and execute field data collection, either through sampling or inventories (censuses) procedures

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 3. Apply statistical and modelling skills to understand and interpret quantitative analyses using the more important statistical computational tools and packages
• 4. Analyse scientific results and determine their strength and validity

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 5. Communicate effectively through oral presentations, written reports, posters and scientific publication
• 6. Demonstrate management skills, such as decision-making, problem definition, project design and evaluation, risk management, teamwork and coordination, and manage resources and time

Syllabus plan

Syllabus plan

Whilst the module’s precise content may vary from year to year, it is envisaged that the syllabus will cover some or all of the following topics:

• Experiments in Ecology

o Hypotheses
o Experimental design (sampling, replication, control)
o Presentation of results

• Field work: Preparation of datasheet, tools, safety measures
• Data presentation (graphic and tables)

o Graphical representation of central and dispersion data
o Tables

• Parametric tests

o F-Snedecor
o Matched and unmatched t-test
o ANOVA (one and more than one factors)

• Non-Parametric tests

o Chi2 (contingency tables)
o U Mann Whitney
o Kolmogorov-Smirnov
o Kruskal-Wallis

• Correlation and regression

o Correlation and regression
o Multiple regression

• Classification vs. ordination

o Classification
o Ordination

• Diversity indexes
• The preparation of manuscript
• Introduction to advanced statistic and modeling tools

Learning and teaching

Learning activities and teaching methods (given in hours of study time)

Details of learning activities and teaching methods

Assessment

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

Re-assessment

Details of re-assessment (where required by referral or deferral)

Re-assessment notes

One assessment is required for this module. In all cases re-assessment will be the same as the original assessment. Where you have been referred/deferred for any form of assessment detailed above you will have the opportunity to retake within the period specified above from the date that feedback was provided.

If you pass re-assessments taken as a result of deferral, your re-assessment will be treated as it would be if it were your first attempt at the assessment and the overall module mark will not be capped.

If you pass re-assessments taken as a result of referral (i.e. following initial failure in the assessment), the overall module mark will be capped at 50%.

Resources

Indicative learning resources - Basic reading

Pre-readings:

• Chalmers and Parker (1989) The OU project guide. The Open University (Field studies council).
• Legendre and Legendre (1998) Numerical Ecology. Elsevier (Chapter 1: Complex Ecological data sets)
• Gauch Jr (1995) Multivariate analysis in community ecology. Cambridge Studies in Ecology (Chapter 4: Ordination).

Key texts:

• Arévalo, J.R., Álvarez, P., Narvaez, N. & Walker, K. 2009. The effects of fire in the regeneration of a Quercus douglasii stand in Quail Ridge Reserve, Berryessa Valley (California). Journal of Forest Research 14: 81-87.
• Arévalo, J.R. & Fernández-Palacios, J.M. 2005. Gradient analysis of exotic Pinus radiata plantations and potential restoration of natural vegetation in Tenerife, Canary Islands (Spain). Acta Oecologica 27: 1-8.
• Arévalo, J.R., Delgado, J.D., Otto, R., Naranjo, A., Salas, M. & Fernández-Palacios, J.M. 2005. Distribution of alien vs. native plant species in roadside communities along an altitudinal gradient in Tenerife and Gran Canaria (Canary Islands). Perspectives in Plant Ecology, Evolution and Systematics 7: 185-202.
• Arévalo, J.R., de Nascimiento, L., Fernández-Lugo, S., Méndez, J., González-Delgado, G., Balguerías, E., Pereira-Cabral, E., Fernández-Palacios, J.M. 2018. Regeneration dynamics in the laurel forest: changes in species richness and composition. iForest 11: 308-314

Module has an active ELE page

Key words search

Statistics, design, islands, biodiversity, conservation, biotic, abiotic, data, collection