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Determining Relative Abundance and Distribution Patterns of Insect Pests
Chapter · April 2019
DOI: 10.1007/978-981-13-2652-3_4
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Chapter Title Determining Relative Abundance and Distribution Patterns of Insect Pests Copyright Year 2019
Copyright Holder Springer Nature Singapore Pte Ltd.
Corresponding Author Family Name Prabhulinga Particle
Given Name T.
Suffix
Division Division of Entomology
Organization Central Institute for Cotton Research (CICR) Address Nagpur, India
Author Family Name Kumar
Particle
Given Name A. D. N. T.
Suffix
Division Crop Protection Division
Organization Coconut Research Institute Sri Lanka Address Lunuwila, Sri Lanka
Abstract Abundance of pests on a crop is an important criterion for timing the screening of germplasms. Screening should be aimed against more than one key pest.
This will facilitate developing resistant/tolerant variety against multiple species. Determining relative abundance also indicates the distribution patterns of the target insect species on the plant. Relative abundance also aids in developing sampling plans for the key pests.
Keywords
(separated by ‘-’)
Relative abundance - Sampling - Distribution patterns - Timing of screening
Determining Relative Abundance
1and Distribution Patterns of Insect Pests
23
T. Prabhulinga and A. D. N. T. Kumar
4
Abstract Abundance of pests on a crop is an important criterion for timing the
5
screening of germplasms. Screening should be aimed against more than one key pest. This will facilitate developing resistant/tolerant variety against multiple spe- 6
cies. Determining relative abundance also indicates the distribution patterns of the 7
target insect species on the plant. Relative abundance also aids in developing 8 9
sampling plans for the key pests.
10
Keywords Relative abundance · Sampling · Distribution patterns · Timing of
11
screening
1 Introduction
1213
The relative number of a species in a habitat is an important factor in ecology
14
especially in the applied sense. Measures of abundance, which are estimated by counting the number of individuals in a specified area, are used to reflect population 15
level and well-being. Thus, abundance of insects has a pivotal role to play in many 16
ecological contexts, including the limitation of species ranges and geographical 17
distribution patterns of species. Relative species abundances are measured for a 18 19
trophic level. Species occupying the same trophic level will potentially or actually
20
compete for the same resources.
21
A sample of the relative abundance of pod borers offield bean (Lablab niger) is
22
enumerated below.
T. Prabhulinga (*)
Division of Entomology, Central Institute for Cotton Research (CICR), Nagpur, India A. D. N. T. Kumar
Crop Protection Division, Coconut Research Institute Sri Lanka, Lunuwila, Sri Lanka
©Springer Nature Singapore Pte Ltd. 2019
A. Kumar Chakravarthy, V. Selvanarayanan (eds.),Experimental Techniques in Host-Plant Resistance,https://doi.org/10.1007/978-981-13-2652-3_4
27
23 • Lablab nigerplants of erect (L. nigervar.lignosus) and creeping (L. nigervar.
24 typicus) types were used to determine the relative abundance and distribution
25 patterns of the lab lab pod borer,Adisura atkinsoniMoore, the dominant species.
26 • Numbers of life stages of pod borers were made to estimate their relative
27 abundance.
28 • The pattern of oviposition at weekly or 10-day intervals was also analysed.
29 • ‘Local’(erect type) and ‘EC- 36417’(creeping type, trailed on 2.5 m bamboo
30 poles), ofLablab nigerthat are highly preferred for oviposition (Chakravarthy
31 1978, 1983), cultivars were chosen to study the pattern of oviposition by
32 A. atkinsonimoths along the plant vertical axis.
33 • The plants’heights at which the borer moths laid eggs were recorded.
34 • The vertical distribution ofA. atkinsonieggs was also observed under laboratory
35 conditions in Bengaluru.
36 • Field collected blooms of‘local’cultivar inserted inflasks (500 ml) containing
37 water were placed in oviposition cages (1 m3).
38 • Four pairs ofA. atkinsonimoths were introduced intofive cages (1 m3) made of
39 wood and wire mesh.
40 • Fresh blooms and 10% honey solution were changed every day for 9 days in
41 the cage.
42 • FiveL. nigerfields in the study area were visited to record the spatial distribution
43 ofA. atkinsonieggs and larvae.
44 • Fields were divided into a varying number of quadrats of 1m2 each, and the
45 recorded numbers of eggs per 100 blooms in each quadrat were maintained.
46 • Spatial distribution pattern of less than 10-day-old pods was simultaneously
47 recorded in two (B and C)fields to see if egg distribution ofA. atkinsoniclosely
48 followed the distribution of such pods on the plants.
49 • Pods ofLablab niger var.‘EC-36417’and‘local’that were collected from 100
50 blooms per quadrat from the twofields were split open to record the number and
51 stage of larvae present inside the pods.
52 • All spatial distribution patterns were based on the sample mean and the variance.
53 A test for departure from randomness based on the variance (S2) to mean (X) ratio
54 was calculated as follows:
IS2X¼
XiX2
Xðη1Þ
55 where Xiis the number of eggs of larvae in the ith units in a sample. Values of
56 Igreater or smaller than one indicated over- and under-dispersion, respectively. The
57 exponent K of the negative binomial distribution was estimated from samples
58 following Southwood (1978).
59 • As per the method, a value ofK >8 indicated that the distribution is approaching a
60 Poisson distribution; and the smaller the value of K, the greater the extent of
61 aggregation. Mean size of the clump (A.) was calculated using Arbous and
28 T. Prabhulinga and A. D. N. T. Kumar
Kerrich’s (1951) formula, by which ifA.¼<2, the aggregation would seem to be 62 63
due to environmental impact.
• If in the majority of the samplesK is smaller than X, the statisticU could be 64 65
arrived at following Anscombe (1950).
U¼S2X 1þX K
• A positive value ofU indicated that the distribution is skewed more than the 66 67
negative binomial distribution and a negative value less skewed than the negative
68
binomial distribution.
2 Distribution Patterns, Sample Size and Sampling
69The above three parameters determine the success and accuracy of experiment on 70
population. Before conducting an experiment, the distribution pattern of insect pest 71
needs to be determined. We have to standardize the sample size too. The selection of 72 73
reliable sampling method is also crucial.
74
As an example, three varieties of cotton belonging toGossypium arboreumand
75
G. hirsutumgroup were raised in the field following randomized complete block
76
design using recommended package of practices of the University of Agricultural
77
Sciences, Bengaluru. Distribution pattern of the spotted pod borer, Earias spp.,
78
could be studied as under.
3 The Steps Are as Follows
79• Spatial distribution of eggs of the borer was determined by counting in a linear 80
fashion, eggs on top two-thirds of the plant infive rows. 81
• Distribution pattern of egg was based on the mean toS2ratio, andX2test was used 82
to confirm the distribution. 83
• Larval spatial patterns were realized by visual counts, both in damaged fruiting 84 85
parts and those that remain undamaged.
• Larvae were counted in thefive rows selected (ten plants per row per variety per 86 87
sowing date) one after another.
• Vertical distribution was determined by dividing plant canopy vertically into 88 89
three levels, viz. top (0–20 cm), mid (21–40 cm) and bottom (41–50 cm), and
90
countingEariaseggs and larvae at each level.
• Data was subjected to one-way analysis of variance to get variations in mean 91 92
between levels of plant height along vertical axis.
Determining Relative Abundance and Distribution Patterns of Insect Pests 29
93 • To determine whether insects’ preference for a particular height is density-
94 dependent, the insect counts were pooled and their relative distribution among
95 the levels and density classes found.
96
4 Sample Size
97 • Sample unit sizes of 5, 6, 7, 8, 9 and 10 cotton plants of each variety were
98 compared with a unit size of 25 plants for samplingEariasspp. larvae. So, a
99 sample unit size of 25 plants (about 5% of the plant population) was treated as
100 ‘large sample’.
101 • Each sample size is tabulated exhibiting number of units (plants), mean (X),
102 standard deviation (SD) and standard error (SE) of a number ofEariaslarvae per
103 plant.
104 • Precision of a sample size was based on SE ofx.Sample size having the least SE
105 relative to‘large sample’was chosen as the most precise sample and is derived as:
n¼ t/2S CX
106 wheret/2 is the standard deviate corresponding to the desired probability level a,Cis
107 constant proportion of thexbased on half width of the (1α) confidence interval
108 andSis the standard deviation.
109 The standard deviation (S) is given by:x2i
SD¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi X2i 1=n P
Xi
ð Þ2 n1 s
110 wherenis the number of units in the sample, standard error (SE) is given by (S/n)
111 andSis standard deviation.
112
5 Number of Larvae in Damaged Fruiting Structures
113 • The reproductive parts, viz. buds, squares, flowers and bolls, are randomly
114 harvested from plants tofind extent of borer infestation.
115 • Infested fruiting structures are debracted and dissected to count the number of
116 Eariaslarvae.
117 • Correlation analyses run between percentage borer infestation and larval counts
118 tofind if damaged fruiting structures sampled provided an estimate of the larval
119 population of theEariasspp. (Table1and Fig.1).
30 T. Prabhulinga and A. D. N. T. Kumar
K¼ X 120
S2X
, λ¼ X
2K V, where V is a function with a X2 (chi square)
121
distribution with 2 K df as per Arbous and Kerrich (1951), and whenK¼8, the
122
distribution is Poisson. Whenλ¼2, the distribution is due to environmental effect and not due to the inherent property of the insect population (Southwood1978). 123
124 Acknowledgement The authors were thankful to the authorities of the Central Institute for Cotton
125 Research (CICR), Nagpur, and Coconut Research Institute, Sri Lanka, Lunuwila, Sri Lanka, for the
126 encouragement.
t1:1 Table 1 Spatial distribution ofEariasspp.eggs and larvae on four cotton varieties
Variety Sowing date
Mean per plant
Variance Distribution Dispersion index
X2 (Chi Square) Uniform Clump
Note: Mean of 50 plants per variety per sowing date. +¼mean>S2,–¼Mean<S2.Values greater or smaller than 1 indicate over- and under-dispersion, respectively
7 13 20 21 25 7 15 31 18 28 5 19 1 14 15
305 100 90 80 70 60 50 40 30 20 10 0
1976 NOV 1976 NOV 1976 NOV 1976 NOV 1976 NOV 1977 NOV
DEC DEC FEB JUL SEP SEP OCT NOV OCT
100 90 80 70 60 50 40 30 20 10 0
LARVAL NUMBER / 50 BLOOMS % LARVAL
Total number of larvae
% Adisura larvae
% Larave of other borer spp
Fig. 1 Relative abundance of pod borers onLablab niger. (Source: Chakravarthy A.K1983) Determining Relative Abundance and Distribution Patterns of Insect Pests 31
127
References
128 Anscombe, F. J. (1950). Sampling theory of the negative binomial and logarithmic series distribu- 129 tions.Biometrika Journal, 37, 358–382.
130 Arbous, A. G., & Kerrich, J. E. (1951). Accident statistics and the concept of accident-proneness.
131 Biometrics Journal, 7, 340–432.
132 Chakravarthy, A. K. (1978). Pod borer resistance in field beans, Lablab niger Medick with 133 particular reference to the pod borerAdisura atkinsoniMoore (p. 180). M. Sc. Thesis submitted 134 to University of Agril. Sciences, Bangalore.
135 Chakravarthy, A. K. (1983). Relative abundance offield bean (Lablab nigerMedick) pod-borers 136 and distribution patterns of the borer,Adisura atkinsonimoore.Insect Science and Application, 137 4(4), 401–406.
138 Southwood, T. R. E. (1978).Ecological methods(p. 391). London: Methuen.
139
Further Reading
140 Mihm, J. A. (1982). Techniques for efficient mass rearing and infestations in screening for host 141 plant resistance to Corn ear worm,Heliothis zea. In:Proceedings of the International Work- 142 shops on Heliothismanagement(pp. 255–261), 15–20 November 1981, ICRISAT Centre, 143 Pathancheru, India. Eds: Reed, W. & Kumble, V., ICRISAT.
144 Sharma, H. C. (2005).Heliothis/Helicoverpa management: Emerging trends and strategies for 145 future research(p. 469). New Delhi: Oxoford and IBH Publishing Company, Pvt. Ltd.
146 Strong, D. R., Lawton John, H., & Southwood Sir, R. (1984). Insects on plants. Community 147 patterns and mechanisms(p. 314). Oxford: Blackwell Scientific Publications.
32 T. Prabhulinga and A. D. N. T. Kumar
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