Indian Forest Service Examination Forest Inventory & Sampling Design: practice questions

Indian Forest Service Examination (IFoS) — Forestry optional · India · Union Public Service Commission

Original practice questions written to the published syllabus · not past papers

9worked here, free

18written to this exam in this subject

10syllabus units

What this subject covers

Planning and running forest inventories: kinds of enumeration, sampling designs and plot types, sample size, estimation and error, from a timber cruise to a national forest inventory.

In the exams: ICAR AICE-JRF 59 Unit 4 (forest inventory, kinds of enumeration, sampling methods, sample plots); ICAR AIEEA-PG Group 09 (forest inventory); IFoS Forestry Paper II Section A; SAF Certified Forester; Indonesia timber-cruiser certification

Objectives and kinds of enumeration: complete and partial
Simple random and systematic sampling
Stratified sampling
Cluster, multistage and multiphase sampling
Sample plots: fixed-area, variable-radius, permanent
Sample size and sampling error
Point, line and strip cruising
National forest inventories and continuous forest inventory
Inventory of non-timber resources and biodiversity
Inventory data processing and reporting

Where the 18 questions fall

How our questions for Indian Forest Service Examination spread across the units of Forest Inventory & Sampling Design. Difficulty: 4 easy, 11 medium, 3 hard.

Inventory of non-timber resources and biodiversity	3
Objectives and kinds of enumeration: complete and partial	2
Stratified sampling	2
Cluster, multistage and multiphase sampling	2
Sample size and sampling error	2
National forest inventories and continuous forest inventory	2
Inventory data processing and reporting	2
Simple random and systematic sampling	1
Sample plots: fixed-area, variable-radius, permanent	1
Point, line and strip cruising	1

9 practice questions, worked

Choose an answer, then open the working. Each explanation says why the right answer is right and why the others are not.

1 · Objectives and kinds of enumeration: complete and partial · hard

A volume equation built for trees up to 60 cm diameter is applied to an inventory where many trees exceed 90 cm. Which kind of error does this most likely add?

Sampling error only, which more plots would remove
Edge-effect error from plots crossing the boundary
Finite-population error from a large sampling fraction
Prediction or model error, and possible bias

Answer and working

D. Prediction or model error, and possible bias

Extrapolating an equation beyond its data range causes prediction error and often systematic bias. More plots reduce sampling error but not this; edge effects and the finite population correction are unrelated.

Further reading: Kershaw et al., Forest Mensuration (5th ed., 2016); Shiver & Borders, Sampling Techniques for Forest Resource Inventory (1996); de Vries, Sampling Theory for Forest Inventory (1986)

2 · Simple random and systematic sampling · medium

Why do most forest inventories use systematic grids despite their statistical weakness?

Grids always give an unbiased standard error from one sample without any assumptions regarding the forest
Grids need fewer plots than any random design for every forest and every variable
Grids avoid the need to measure plot radius because plots touch one another
Grids are easy to lay out, spread plots evenly over the forest and give a map of variation

Answer and working

D. Grids are easy to lay out, spread plots evenly over the forest and give a map of variation

Practicality and even coverage are the reasons. No unbiased error formula exists for a single systematic sample, they do not always need fewer plots, and plots on a grid are still measured individually.

Further reading: Kershaw et al., Forest Mensuration (5th ed., 2016); Shiver & Borders, Sampling Techniques for Forest Resource Inventory (1996); de Vries, Sampling Theory for Forest Inventory (1986)

3 · Stratified sampling · easy

In Neyman (optimum) allocation, the number of plots in a stratum is proportional to:

Stratum area multiplied by stratum standard deviation
Stratum area alone
Stratum mean volume alone
Number of tree species in the stratum

Answer and working

A. Stratum area multiplied by stratum standard deviation

Neyman allocation gives more plots to large and variable strata: nh ∝ Ah × sh. Area alone is proportional allocation; mean volume and species count are not the basis.

Further reading: Kershaw et al., Forest Mensuration (5th ed., 2016); Shiver & Borders, Sampling Techniques for Forest Resource Inventory (1996); de Vries, Sampling Theory for Forest Inventory (1986)

4 · Cluster, multistage and multiphase sampling · medium

In double sampling for stratification, what does each phase estimate?

Photo points estimate stratum proportions; ground plots on a subsample estimate stratum means
Ground plots estimate stratum proportions; photo points estimate tree heights in each stratum
Both phases measure only forest area; volume comes from yield tables for each stratum
Photo points estimate mortality; ground plots estimate ingrowth since the last inventory

Answer and working

A. Photo points estimate stratum proportions; ground plots on a subsample estimate stratum means

The large photo sample classifies points into strata to estimate their proportions; the ground subsample gives stratum means. This was the classic design of many national inventories.

Further reading: Kershaw et al., Forest Mensuration (5th ed., 2016); Shiver & Borders, Sampling Techniques for Forest Resource Inventory (1996); de Vries, Sampling Theory for Forest Inventory (1986)

5 · Sample size and sampling error · hard

Two independent strata totals have standard errors of 30,000 m³ and 40,000 m³. What is the standard error of the forest total?

70,000 m³
50,000 m³
35,000 m³
10,000 m³

Answer and working

B. 50,000 m³

Independent variances add: √(30,000² + 40,000²) = 50,000 m³. Adding the SEs (70,000) overstates; averaging (35,000) or subtracting (10,000) are wrong.

Further reading: Kershaw et al., Forest Mensuration (5th ed., 2016); Shiver & Borders, Sampling Techniques for Forest Resource Inventory (1996); de Vries, Sampling Theory for Forest Inventory (1986)

6 · Point, line and strip cruising · medium

Which is an advantage of line-plot cruising over strip cruising?

It needs no compass or measurement of distances between plots along the lines
Fewer borderline trees and clearly defined sample units for calculating error
It measures every tree in the forest and so has no sampling error at all
It works only in plantations and cannot be used in natural mixed forest

Answer and working

B. Fewer borderline trees and clearly defined sample units for calculating error

Plots have shorter perimeters than long strips and each plot is a unit for statistics. Line-plot cruising still needs compass and distance, is a sample, and works in natural forest.

Further reading: Kershaw et al., Forest Mensuration (5th ed., 2016); Shiver & Borders, Sampling Techniques for Forest Resource Inventory (1996); de Vries, Sampling Theory for Forest Inventory (1986)

7 · Inventory of non-timber resources and biodiversity · medium

In phytosociological studies the importance value index (IVI) of a species is:

Density × frequency × dominance, summing to 100 over all species in the stand
Relative density alone, expressed per hectare and summing to the total stocking of the stand
Relative density + relative frequency + relative dominance, summing to 300 over all species
Basal area divided by tree height, averaged over all the quadrats in the study

Answer and working

C. Relative density + relative frequency + relative dominance, summing to 300 over all species

IVI adds three relative measures in per cent, so all species together total 300. Multiplication, density alone and basal area ÷ height are not the IVI.

Further reading: Kershaw et al., Forest Mensuration (5th ed., 2016); Shiver & Borders, Sampling Techniques for Forest Resource Inventory (1996); de Vries, Sampling Theory for Forest Inventory (1986)

8 · Inventory of non-timber resources and biodiversity · medium

Which carbon pools are recognised in IPCC guidance for forest land?

Only timber volume, bark and branches in the merchantable stem of trees above the stump height
Leaves, flowers and fruits only, because they are renewed every year
Above-ground biomass, below-ground biomass, deadwood, litter and soil organic carbon
Atmospheric carbon dioxide, methane and nitrous oxide above the canopy

Answer and working

C. Above-ground biomass, below-ground biomass, deadwood, litter and soil organic carbon

IPCC defines five forest carbon pools: above-ground biomass, below-ground biomass, deadwood, litter and soil organic matter. The other lists are incomplete or not pools.

Further reading: Kershaw et al., Forest Mensuration (5th ed., 2016); Shiver & Borders, Sampling Techniques for Forest Resource Inventory (1996); de Vries, Sampling Theory for Forest Inventory (1986)

9 · Inventory data processing and reporting · medium

Before analysis, field data are screened mainly for:

Missing values, impossible values, wrong species codes and duplicated plots
The handwriting style of each crew member on the original field sheets
Plots with volumes above the mean, which are removed as outliers automatically
Plots measured on rainy days, which are always discarded from the analysis

Answer and working

A. Missing values, impossible values, wrong species codes and duplicated plots

Checks target errors in the data. Removing all above-average plots or rainy-day plots would bias the results; handwriting is irrelevant if values are correct.

Further reading: Kershaw et al., Forest Mensuration (5th ed., 2016); Shiver & Borders, Sampling Techniques for Forest Resource Inventory (1996); de Vries, Sampling Theory for Forest Inventory (1986)

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