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Some Wildlife Census Techniques

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Presentation on theme: "Some Wildlife Census Techniques"— Presentation transcript:

1 Some Wildlife Census Techniques
John MacKinnon GEF MSL Programme, China

2 Four reasons to count wildlife
Inventory – taking account of the biological contents of a given area (assessment, prioritization and management planning) Census – an inventory for a single species (monitoring conservation status) Monitoring population trends Monitoring or assessing changes or differences in species richness

3 Ability to identify

4 Special indicators - dragonflies!

5 Precision versus accuracy
Trend data is more important than total accuracy Knowing if a population is stable, increasing or declining is of more relevance to the manager than knowing if total is 24,000 or 19,000 A precise (low variance) index of relative abundance (a) is better than a less precise but more accurate census method (b)

6 Sampling and bias Try to minimize bias by:
Replicate conditions of method, sample sites, season, weather conditions, time of day, observer ability Use robust methodology Select commoner species to achieve large sample size Standardise search effort Use appropriate statistics

7 Economise by smart sampling
Impossible to count and monitor everything, so be smart in selecting indicators and sampling methods

8 Two main sampling methods, systematic (regular) or random

9 Practical application

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11 Stratified sampling

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13 Splitting samples

14 Line transects Proceed along line transect (or existing trail) for measured length. Slow walking, from vehicle or airplane. Can be one side, both sides or predetermined strip width. Note all animals of target species sighted with estimate of perpendicular distance from transect line at moment of discovery (animal may have detected observer first and moved away from transect line before observer sees it)

15 Line transects 2

16 Calculating density and populations
Density = number of individuals observed (sightings x mean group size)/(length of transect x effective strip width x how many sides surveyed) Population estimate for given habitat = density x area of habitat type available (this calculation assumes the sampled area is typical of the entire habitat)

17 Use of indirect signs The line transect method can be used to count indirect signs of the animal in question, e.g. dung piles, nests, footprint trails. The resulting density of indirect signs can be converted into an estimate of animal density by the formula (density animals = density of signs / (mean number of signs left by animal per day x mean number of days that the sign remains recognisable)

18 Footprints

19 Use of traps Many types of traps, nets can be used as sampling device to give abundance index for different species Important to relate results to ‘effort’ e.g. trap nights Note animals may become trap shy or trap happy! Index can only be converted into density estimate if calibrated in a population of known density

20 Mark, release, recapture
Trapped animals can be marked and then released The proportion of marked animals noticed in subsequent samples or observations indicates what proportion of the local population was marked and can therefore be used to estimate that total population Accuracy assumes the marks do not fall off, almost zero mortality between samples and released animals as likely to be resampled or observed as un marked animals

21 Camera traps Recognise individual animals Estimate range size
Estimate density Record breeding success but Much bias in camera wariness of species and individuals and very variable in how well sites are selected

22 Area discovery curves As one increases a search area one discovers more species but the rate of ‘new’ discovery decreases towards zero when all species present have been found. In practice one rarely has time to find everything but the rate of discovery can give a mathematical estimate of what the final number will be

23 MacKinnon Curves! In stead of counting species over increasing area, this method counts species over time but uses success of search to give greater robustness and smooth out discovery across differing conditions of weather visibility time of day etc. Make bird list of 20 species seen, then start again and make a new list. Plot total species found against lists collected

24 Steepness of curve indicates site richness

25 Calculating the zero class
Plot the number of species recorded on 1,2,3,4 lists etc. This should resemble a Poisson distribution. You can calculate the zero class graphically or using a statistical formula

26 Diversity and dominance

27 Interpreting results

28 Some real data!

29 Mapping and monitoring habitat

30 Miracle of Google!!

31 Gains and losses!

32 Habitats do change!


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