Biodiversity Informatics Assessment 1

The Red Kite (Milvus milvus) is a scavenging raptor found throughout Europe and native to Britain. Red Kites were once common throughout Britain. During the last century their populations were reduced to just a handful of birds in the Welsh valleys by persecution. In 1989, after satisfying the IUCN criteria, Red Kites were reintroduced to southern England, in the Chilterns, and northern Scotland, on the Black Isle near Inverness. A total of 93 birds were translocated from Swedish and Spanish kite populations to each of the two reintroduction sites. Since this time, the southern England population has increased in size to over 300 breeding pairs. The north Scotland population, on the other hand, has grown slowly and reached only 46 breeding pairs in 2008 For reintroduction projects to be successful, it is vital that a viable population of wild individuals can be achieved and this should be accompanied by a comprehensive monitoring programme.

Red Kites are systematically monitored in a yearly census. Nests are located in March and April when breeding pairs can be found displaying and nest building. Between late March and early May eggs are laid and this is indicated by the presence of an incubating female. In late May nests are re-visited to check for young. A nest containing young will have faecal material, or ‘whitewash’ spread around the base of the nest tree. With experience the size and number of young present can be estimated using the quantity of faecal material. In July and August the nesting sites are checked for the presence of fledged young. After the visit to check for the presence of young, a further visit follows in which the nest tree is climbed. During this visit the young are fitted with BTO metal leg rings and biometric measurements are made. Along with this patagial wing tags are fitted to both wings. The colour of the left wing indicates the population from which the bird originated and the right wing tag the year in which it was born. The tags have markings such as letters or numbers so that each kite can be identified individually.

The dataset ‘kite.csv’ on the Moodle page represents biometric measurements for kite chicks in the North of Scotland and the Chilterns populations in 2014. Each record represents an individual chick and the columns show the location in which it was born along with its sex, wing length, weight and tarsus length as well as the mean productivity of its mother in previous years.

TASK

Explain how you would analyse these data to investigate differences in chick size. Use figures and results from Exploratory Data Analysis along with ecological and statistical literature to explain and justify your choice of analyses.

Use figures and results from Exploratory Data Analysis along with ecological and statistical literature to explain and justify your choice of analyses. You should include your R code as an appendix.

Your assessment submission should consist of one single file w ith y our R code provided as an appendix. This should be submitted as a document file (Word, Open/Libre Office or PDF.

Weighting = 30%

This assignment should be submitted online through Moodle before 2pm

on 09/12/21 following the university’s assessment submission guidelines.

Assessment criteria

The description of possible analysis approaches will be assessed according to the following criteria:

• You should describe analysis methods which are appropriate to investigate the question posed
• The methods described should be supported where appropriate with references to fieldwork methods, the literature and the results of your EDA
• Your work should be concise and informative

The submitted R scripts will be assessed using the following criteria:

• The code should run without error
• The code should perform appropriate analyses and graphics
• The code should be fully commented so that it
  • explains what the code does
  • explains the decision making behind the analyses
  • briefly interprets the results of the analyses

A consistent style should be adopted adhering to the following guidelines:

• File names – Should be meaningful and end in ‘.R’
• Object names – Should be meaningful and components should be separated with a ‘.’ or ‘_’. Be consistent within your code.
• Function names – Should be meaningful and use CamelCase
• Use ‘<-’ as an assignment operator
• Put spaces after all commas, around mathematical operators and after closing brackets but not between functions and their opening bracket. As an exception don’t put spaces around ‘:’.
• Opening curly braces should never go on their own line. Closing curly braces should always go on their own line.
• Indent code or add extra spaces to improve readability if required
• Use ‘#’ and a space to add comments to your code. Put long comments on their own line; short comments can be appended to lines containing code
• If your code is long and consists of several different parts use commented lines of ‘# ————-’ to break up your code