The document discusses prey-predator relationships in insects. It describes how insects face intense survival challenges where every small trait can impact whether they become prey or avoid predation. Over millions of years, these interactions have evolved complex strategies on both sides. The summary explores functional and numerical responses of predators to changes in prey density, and models that describe oscillating population dynamics, including Lotka-Volterra, Nicholson-Bailey, and Hassell-Varley models. Understanding these complex relationships is important for biological control of agricultural pests.

3. • The intricate nature of prey and predator relationships is a interesting and fundamental aspect
of the animal kingdom.
• But today, the focus is on a smaller yet no less dramatic stage: THE WORLD OF
INSECTS.
• Insects face an intense survival game where every small movement, color, shape, chemical
secretion, and strategic action can significantly impact their survival.
• These interactions have evolved over millions of years, shaping the web of life and
influencing the survival of insects.

4. • The world of prey-predator interactions in insects.
• Explore the various tactics employed by insects to avoid becoming a meal themselves.
 Understanding the process of predation and its complex effects on species interactions
and food-web dynamics has, enhanced our ability to use invertebrate predators as
effective biological control agents.

6. Prey:
• Prey refers to an organism that is hunted and consumed by
another organism for its sustenance.
• Animals, plants, or even microorganisms.
Predator:
• A predator is an organism that actively hunts, kills, and
consumes other organisms, known as prey, as its primary
source of nutrition.

7. Prey-Predator Relationships:
• Prey-predator relationships, also known as predator-prey interactions, describe the
dynamic interactions between organisms in which one organism (the predator)
hunts, kills, and consumes another organism (the prey) for food.
• These relationships are essential components of ecosystems and play a significant
role in regulating populations and maintaining ecological balance.
• They can lead to cycles of population fluctuations, where changes in prey abundance
influence predator numbers and vice versa.

8.  Here are some basic principles of predator-prey interactions:
 Population Dynamics
 Predator-Prey Cycles
 Coevolution
 Prey Strategies
 Predator Strategies
 Predator Satiation

9. The feeding habit of predators
• Predators are omnivores, consuming not only prey but also
other predators and plant resources, and they are generalized in
their feeding habits.
• For example: Big-eyed bugs are omnivorous, they consume
aphids, lepidopteran eggs, larvae, pods, seeds, and leaves.
• Ground beetles, like Scaphinotus, selectively feed on molluscs.
• Parasites, like parasitoids, exhibit high specialization, often
feeding on a single insect life stage due to intimate associations.

10. Predator effects on prey abundance
• Predators can significantly reduce prey populations as
demonstrated by the co-occurrence of herbivorous planthoppers
(Prokelisia marginata) and wolf spider predators (Pardosa
littoralis) in North American inter-tidal marshes. Removing
spiders leads to high planthopper populations, while adding them
back suppresses them. (Dobel and Denno 1994)
• Predators can suppress prey populations, as seen with the
cottony cushion scale (Icerya purchasi) in Australia. The late
1800s introduced a ladybird beetle (Rodolia cardinalis), saving
the industry (Caltagirone and Doutt 1989). However, toxic growth
regulators in the 1990s led to its re-emergence (Grafton-Cardwell
et al. 2006).

11. Understanding the prey-predator interactions involves understanding predators
responses to changes in prey density, which can be
1)Functional
2)Numerical
depending on the growth of prey densities.
Predator responses to changes in prey density

12. • The functional response of a predator is the change in an individual’s rate of prey
consumption changes in response to prey density.
• This can estimate prey depletion rates, identify predator preferences, and predict
community dynamics.
 Holling's component analysis approach identified predator-related factors contributing to the
functional response.
Functional response

13.  His classic experiment recorded the number of disks captured in
one minute. The general disk equation describes a Type II
functional response curve, where predator’s consumption rate
increases at a decelerating rate until it levels off at an upper
plateau.

14. The general disk equation is
NA=
aTN
1+aTH
N
• NA is the number of discs picked
• N is the density of discs offered
• T is the total time available for searching
• TH is the handling time
• a is the searching efficiency or attack rate of the
predator
 This response represents a compromise between the time available for searching and
the time necessary to capture, eat, and digest each piece of prey.
 At low prey densities, predators spend most of their time searching, while at high
densities, they spend most time handling captured prey.

15.  A Type I functional response occurs when
a single predator's consumption rate is
limited by prey density.
 Thus, over a wide range of densities, the
per capita consumption and prey density
linearly related up to a threshold density.
 This response may be exclusive to filter
feeders including web-building spiders
which are able to snare many food items
simultaneously. (Jeschke et al. 2004).
Per
capita
consumption
rate
Fraction
of
available
prey
consumed

16. Type II functional response
 Most invertebrate predators (e.g., hunting
spiders, praying mantids, ladybird beetles)
and parasitoids exhibit this type of
response. (Luck 1984, Fernandez-Arhex and
Corley 2003)
 Here the fraction of prey captured decreases
with increasing prey density.
 This reduces the ability of the predators to
control prey population growth, allowing
prey to escape predation.
Per
capita
consumption
rate
Fraction
of
available
prey
consumed

17.  Many vertebrate predators and some
invertebrate predators exhibit this type.
 Here consumption rate responds slowly to
the increase in prey density.
 At higher prey densities, consumption rate
rises rapidly, and at very high prey densities,
consumption rate saturates and is limited by
time and satiation.
Per
capita
consumption
rate
Fraction
of
available
prey
consumed
Type III functional response/ sigmoidal
response.

18.  The rapid rise in consumption rate at intermediate prey densities can be due to
multiple mechanisms,
1. Learning to discover and capture prey with increased efficiency (Holling 1959a,
Tinbergen 1960),
2. They may simply increase the searching rate (Murdoch and Oaten 1975, Hassell
et al. 1977)
 This type of response contributes to prey-population regulation and may promote
stability in the prey-predator interaction.

19. Holling (1965) predicted that prey species evolve
defensive mechanisms against predators.
The functional response is humping with prey density.
Tostowaryk (1972) demonstrated this in colonial
sawflies.
The predator (pentatomid bug) attack rate initially
increases with increased density, but the prey(sawflies
larva) defensive response becomes effective at higher
densities.
When the larvae defense is removed, the humped
response becomes less evident, resulting in a classic
Type II response.
Functional response to a defended prey
Per
capita
consumption
rate
Prey
attacked
per
predator
per
32
hrs

20.  Predators often aggregate in areas where prey is
abundant, resulting in a short-term change in
predators' spatial distribution.
Numerical response
 Additionally, predator populations may build as a consequence of increased reproduction,
with the reproductive numerical response only after exhibiting a lag equal to the predator's
generation time.
 It describes change in predator density as a function of change in prey density.
 This pattern is influenced by predator aggregation and enhanced reproduction.

21.  The local density of the wolf spider Pardosa littoralis, for instance, can be
dramatically enhanced over a three-day period when prey (planthopper) are
experimentally added to its habitat (Dobel and Denno 1994).
 A significant increase in the number of ladybird beetles (e.g., Hippodamia
convergens) in response to artificially enhanced aphid densities can be detected
within as little as one day following aphid manipulation (Evans and Toler 2007).
 The number of eggs produced by ladybird beetle females has been shown to
increase with an increase in aphid abundance (Dixon and Guo 1993).

22.  The reciprocal interactions of predators and prey determine long-term population
dynamics.
 Hudson Bay Company's fur-trapping records show spectacular periodicity with peaks and
valleys of abundance Hare and Lynx.
Prey–predator dynamics

23. • An example of a coupled prey-predator population cycle in insects is a long-term
manipulative study assessing the impact of a natural-enemy complex on the dynamics of
southern pine beetle populations in southern United States(Turchin et al. 1999).
The intensity of the predation on the pine beetle population during
the outbreak can be estimated by the difference between beetles
exposed to predation to that of beetles protected from predation
The clerid beetle exhibits population oscillations
that are coupled with those of the pine beetle

24.  Alfred Lotka and Vito Volterra developed the Lotka-Volterra equations to describe the
cyclic dynamics of prey-predator interactions.
 They based their models on observations of reciprocal prey-predator cycles in nature.
 They used differential equations to model populations with overlapping generations and
continuous reproduction.
Lotka–Volterra model of prey–predator interactions
For the prey population, the rate of population
change through time (dH/dt) is represented by
the equation:
𝑑𝐻
𝑑𝑡
= 𝑟𝐻 − αHP
• H is prey density,
• 𝑟 is the rate of increase of the prey population
(birth rate),
• α is a constant that measures the prey’s
vulnerability to the predator
• P is predator density.
 Thus, exponential growth of the prey population (𝑟H) is countered by deaths due to predation
(αHP)

25.  Change in the predator population through time (
𝑑𝑝
𝑑𝑡
) is shown by:
 c is a constant, namely the rate that prey are killed and converted to predator
offspring,
 d is the rate of decrease in the predator population (death rate).
𝑑𝑝
𝑑𝑡
= cHP - dP
 The decline in the predator population (-dP) due to death is offset by the rate
that predators kill prey and convert them into offspring (cHP).

26. • The two equations provide a
periodic solution in that predator
and prey populations oscillate in
reciprocal fashion through time.
• The Lotka-Volterra equations' dynamics in two-
phase space result in a neutral limit cycle, where
both predator and prey populations perpetually
cycle in time.
Time
Abundance

27.  Gause (1934) tested the Lotka-Volterra model experimentally with the predaceous ciliate
Didinium nasutum and its prey, Paramecium caudatum.
He found that prey populations exploded without predators, but with predators,
Paramecium populations diminished.
Gause's experiments showed that only by artificially adding a single individual predator
and prey every third day could obtain a persistent prey-predator cycle.

28. Limitations of lotka voltera model
The Lotka-Volterra model oversimplifies real-world predator-prey interactions by assuming
 Making it inadequate for describing complex ecological dynamics accurately.
1
2
3
4
5
Constant parameters
Ignoring spatial complexities
Disregarding the effects of other species and environmental factors
Assumes unlimited resources and exponential growth
Does not account for evolutionary adaptations

29.  Nicholson and Bailey (1935) criticized the Lotka-Volterra equations for unrealistic expectations of
predator-prey response.
 They proposed a discrete-time model using difference equations for insect populations with
synchronous reproduction and no overlap of generations, instead of using calculus for continuous
population change.
Nicholson–Bailey model of prey–predator interactions
Predator/parasitoid search is random.
Prey/hosts are distributed uniformly in a uniform environment.
The ease with which prey can be found does not vary with the
density of the prey population.
The appetite of predators (i.e., the capacity for parasitoid oviposition)
is insatiable, independent of prey population density.
The predator/parasitoid has an “area of discovery” that is a constant.
Several simplifying
assumptions were
made:

30. The prey population has the capacity to grow exponentially (𝑟𝐻𝑡).
• The area of discovery represents the efficiency of the parasitoid in finding its prey and is
measured as the proportion of prey found in the total habitat searched by the parasitoid
during its lifetime.
• The greater the area searched (i.e., larger α) means more hosts killed, and fewer to survive
and contribute to the next generation.
• The Poisson distribution tells us that if attacks are random and independent, then e−αPt is
the probability of a host not being attacked.
• Therefore, Hte−αPt is the expected number of hosts which are not attacked and survive to
reproduce.

31. • Alternatively, the proportion of the prey population succumbing to parasitism
would be 1– e-αp
t
.
• The number of parasitoids alive in the next generation (pt+1) is described as :
𝒑𝒕 + 𝟏 = 𝒄𝑯𝒕(𝟏 − e-αpt )
 Therefore, host abundance in the next generation (Ht+1) can be modeled as a function
of current host abundance (Ht) using the equation
𝑯𝒕 + 𝟏 = 𝒓𝑯𝒕𝒆
−∝ 𝑷𝒕
• Ht is host density
• ∝ is area of discovery
• 𝑟 is the rate of increase of the host population (birth rate)
• P is parasitoid density
• t is the generation.

32. • The equations suggest a steady state in a constant environment where hosts and
parasitoids can remain at equilibrium densities, but this state is unstable, leading to
coupled oscillations until local extinction.

33. The Nicholson-Bailey model, despite its lack of realism, serves as a foundation for future
research on prey-predator interactions, incorporating ecological factors to enhance its
predictive capabilities.
 Even though Nicholson and Bailey initially assumed organisms to be evenly distributed over
a uniform area, the need for recolonization from other patches in the face of localized
extinction highlights the importance of spatial factors in understanding population behavior.

34.  Hassell and Varley (1969) modified the Nicholson-Bailey model to account for
mutual interference among parasitoids.
 They criticized the Nicholson-Bailey model for its lack of dependence of parasitoid
density on area of discovery (α).
 They found that the area of discovery is linearly related to parasitoid density,
with a decreasing with increased density in the following manner.
Mutual interference and the Hassell–Varley model
𝒍𝒐𝒈α = 𝒍𝒐𝒈𝑸 − (𝒎𝒍𝒐𝒈𝒑)
• α is the area of discovery
• p is the parasitoid density
• Q is the 'quest constant' indicating the level of efficiency of one parasite
• m is the “mutual interference constant.”

35. According to this relationship, the area of discovery (α), rather than being constant, is actually
predicted to decline with an increase in parasitoid density (p).
Thus, we can solve by taking the antilog of the expression, swap this new density dependent
term (α = 𝑸𝒑
_𝒎) for the α in the Nicholson–Bailey model, and the new “parasite quest
equations” become, by substitution:
𝑯𝒕 + 𝟏 = 𝒓𝑯𝒕𝒆
_𝑸𝑷𝒕 𝟏_𝒎
𝒑𝒕 + 𝟏 = 𝒄𝑯𝒕(𝟏 − e-Qpt 1-m )
 H is host density
 r is the rate of increase of the host population (birth rate)
 c is the rate at which consumed prey are converted into parasitoid offspring
 t is the generation.

36. Unlike the Nicholson–Bailey model, the Hassell–Varley model provides for stable dynamics
between parasitoids and hosts by incorporating density dependence into the behavior of the
parasitoid population.
 This model provides stable dynamics between
parasitoids and hosts by incorporating density
dependence into the parasitoid population behavior.
 The greater the mutual interference constant (m), the
greater the tendency for the host-parasitoid model to
stabilize.

37.  In addition to spatial processes Complex habitat structure and the refuge it
provides for prey from predation contribute to persistence in prey-predator
interactions.
 For example, the citrus-feeding spider mite Eotetranychus sexmaculatus and its
predatory mite Typhlodromus occidentalis interact in a complex-structured habitat.
Habitat complexity and refuge from predation
simple habitat: monoculture of oranges arranged on trays.
complex-structured habitat: oranges were interspersed among rubber balls and little posts.
(Huffaker, 1958)

38. Predatory mites easily dispersed throughout
the habitat, prey were driven to a threateningly
low density, and the predator went extinct.
prey dispersed and found refuges from predation,
and three complete predator–prey oscillations
resulted before the food quality of oranges
deteriorated and the system collapsed.
(Huffaker, 1958)

39. When the two populations are in equilibrium, the predator density equals the prey's
birth rate divided by the prey's death rate , and the prey's density equals the predator's
death rate divided by the predator's birth rate. This is shown graphically below.

40. Predation in complex food webs
• The presence of multiple predator and prey species in a system can alter the interaction
between a specific prey–predator pair, and complicate predictions of population
dynamics.
If this is the case, the multipredator assemblage is said to have prominent impacts on prey
They may be of :
Additive interactions.
Antagonistic interactions.
Synergistic interactions.

41. Evolutionary response of prey to predation
 Prey species have evolved a wide range of defenses in response to selection from
predation
 Such defenses can be categorized as primary, secondary or tertiary
Primary prey defenses:
 Function to prevent the initiation of a capture attempt by a predator, typically by evading
detection altogether. (i.e colourational defense)
Secondary prey defenses:
 These operate when primary defenses does not hold well. (i.e behavioural defense)
Tertiary prey defenses:
 Interrupt predation after capture and during the handling phase. (i.e structural and
chemical defense)

42. Cryptic colouration (I am not here).
 By the deceptive look, the insect gains protection.
 The insect looks like a particular object that forms a
common component of the environment or the colour of
the insect blends with the background.
These are of three types:
A. Homochromism- Colour is similar e.g,. Preying mantid.
B. Homomorphism- Form is similar e.g,. Cowbug.
C. Homotypism- Both colour and form is similar e.g,. Stick
insect.
Colourational defense:

43. Revealing colouration (I am dangerous) :
E.g,. Giant silk worm. Forewings are cryptically coloured. Hind wings are
attractively coloured.
 Once the bird locates the insect, the prey insect exposes the bright hind
wings the eye spots to startle the predator.

44. Warning coloration (I am not tasty):
 Butterflies are usually attractively coloured.
 The bright colour serves as a warning to the predator.
Larva of monarch butterfly while feeding on the milk
weed plant ingests cardiac glycosides. As a result, both
larva and adult become unpalatable.

45. Mimicry(I am some one else);
 One species of animal imitates the appearance of another better protected animal
species, there by sharing immunity against destruction.
 The former is called mimic and the latter is known as model.
There are two types of mimicry:
1. Batesian mimicry
• Mimic is restricted to palatable species.
• Mimic alone gets protection because the predators are apparently misled.
E.g; viceroy butterfly: Liminitis archippus – Mimic.
Monarch butterfly: Danaus plexippus – Model.
Hypolimnas bolina – Mimic: Euploea core – Model

46. Batesian mimicry is when a non-poisonous species has markings similar to a poisonous
species and gains protection from this similarity. Since many predators have become sick from
eating the poisonous butterfly, they will avoid any similar looking animals in the future, and
the mimic is protected
MIMIC MODEL

47. 2. Mullerian mimicry is when two poisonous
species have similar markings;
Fewer insects need to be sacrificed in order to teach
the predators not to eat these unpalatable animals.
• Tropical Queens, Monarch butterflies are two
poisonous butterflies that have similar markings.
• Another example is the poisonous Viceroy which
mimics the poisonous Monarch butterfly.
 The form of mimicry is advantages to both the
mimic and model.

48. Behavioural defense
Jumping
Reflex dropping
Thanatosis
Threatening pose
Protective constructions
• Eggs
• Nymph
• Larva
• Pupa
• Adult

49. Structural defense
Horny integument
Sclerotised cerci
Tentacles

50. Chemical defense
Defensive chemicals may be of two types viz,. Venom and oderiferous compounds
 The venom is injected into the body of the enemy. E.g, honey bee.
 Odoriferous or repugnatorial substances:
 Exogenous
 Endogenous

51. 1. Exogenous
Osmeteria: Odoriferous plant components accumulated in
thoracic pouches are expelled by the eversion of a pair coloured
protrusible structures called osmeteria releasing a disagreeable
odour in response to a disturbance.
2. Endogenous
Stink glands: In stink bugs and rice earhead bug, a stink gland is
present in metathorax which emanates a bad odour when
handled.
Poisonous setae: They are present in the body wall of certain
caterpillar. E.g; Castor slug. The setal tip breaks off issuing the
poison from poison gland cell.

52. Case study 1
Title : Temperature-Dependent Functional Response of Harmonia axyridis (Coleoptera:
Coccinellidae) on the Eggs of Spodoptera litura (Lepidoptera: Noctuidae) in Laboratory
Authors : Yasir Islam et al., 2020
Journal : Insects
MASS REARING OF H.axyridis
In January 2019, colonies of Harmonia axyridis and Acyrthosiphon pisum (Harris) (Hemiptera:
Aphididae) were established from a population of adults taken from a stock culture at Key Laboratory of
Hubei, Insect Resources Utilization and Sustainable Pest Management, located at Huazhong
Agricultural University (HZAU), Wuhan, China.
MASS REARING OF S.litura
Spodoptera litura population was established from a collection of 50 pupae obtained from, The Institute
of Plant Protection and Soil Fertility Hubei Academy of Agricultural Sciences, Wuhan, China in 2019.

54. Conclusions
•The growth stage of Harmonia axyridis and temperature significantly affect the consumption
of Spodoptera litura eggs.
•The 4th instar and adult stages of Harmonia axyridis show the highest egg consumption rates,
particularly at higher temperatures (25-35°C) .
•These findings suggest that the 4th instar and adult stages of Harmonia axyridis can be
effectively utilized as biocontrol agents to suppress Spodoptera litura populations in fields and
greenhouses, providing an eco-friendly alternative to chemical insecticides .
•Overall, the study contributes to the understanding of predator-prey dynamics and provides
valuable insights for the development of integrated pest management strategies targeting
Spodoptera litura.

55. Case study 2
Title : Predator Prey Interaction between Lepidopteran Pests and Coccinellids Insects
of Cotton in Southern Punjab Pakistan
Authors : Mujahid Niaz Akhtar and Amjad Farooq
Journal : Pakistan Journal of Zoology
Field study was carried out from 2014-2016 to investigate the predator prey relationship
between chewing insect pests of cotton like as American bollworm (ABW), pink bollworm
(PBW), spotted bollworm (SBW) and their predators including seven spotted lady beetle and
spiders

56. Variable
Adult
ABW
Lady
beetle
Adult
PBW
Adult
SBW
2014
Lady beetle 0.1165
P-Value 0.2366
Adult PBW 0.6943 0.2821
P-Value 0.0000 0.0036
Adult SBW 0.7378 -0.0387 0.8583
P-Value 0.0000 0.6952 0.0000
Spider 0.1291 0.7166 0.2957 0.0764
P-Value 0.1894 0.0000 0.0022 0.4386
2015
Lady beetle 0.0207
P-Value 0.8341
Adult PBW 0.8934 0.2672
P-Value 0.0000 0.0059
Adult SBW 0.7329 -0.1562 0.6795
P-Value 0.0000 0.1115 0.0000
Spider 0.0743 0.7441 0.2507 -0.0230
P-Value 0.4510 0.0000 0.0099 0.8155
2016
Lady beetle 0.3862
P-Value 0.0000
Adult PBW 0.7732 0.3198
P-Value 0.0000 0.0009
Adult SBW 0.8396 0.3121 0.9180
P-Value 0.0000 0.0012 0.0000
Spider 0.5217 0.7722 0.3649 0.4058
P-Value 0.0000 0.0000 0.0001 0.0000

58. CONCLUSIONS
 Lady beetle and spiders showed significant correlation for pink bollworms than
ABW and SBW during 2014 and 2015 as shown by the coefficient of correlation
between their populations.
 In 2016, the correlation coefficients were quite higher than previous years. Lady
beetles had highest correlations with ABW, followed by PBW and SBW
population. The pattern was quietly changed during this year. Spider had similar
change in correlations in order of ABW>SBW>PBW.
• Relationships between predator and prey populations are presented in the form of
correlations and prediction equations (regression).

59. Case study 3
Title : Functional response and predatory interactions in conspecific and heterospecific
combinations of two congeneric species (Coleoptera: Coccinellidae)
Authors : Kumar and Mishra, 2014
Journal : European Journal of Entomology
 Adults of Coccinella septempunctata (C7) and Coccinella transversalis (Ct) were collected from
fields around Lucknow, India and allowed to mate. Mating pairs were separated and kept as pairs.
 They were provided with an ad libitum supply of the aphid, Acyrthosiphon pisum (Ap), reared on
broad bean, Vicia faba L. (Fabaceae) in a green house
 As they are the most voracious stages, fourth instar larvae (12 h after moulting) and adult females
were used in the experiments

62. conclusions
- The study found that the predatory interactions between Coccinella septempunctata (C7) and Coccinella
transversalis (Ct) lady beetles were influenced by the abundance of prey.
- The functional response of the predators followed a decelerating (type II) pattern when prey was scarce to
optimal, and an accelerating (type III) pattern when prey was optimal to abundant.
- The predators interacted antagonistically in most combinations, except for the C7 + C7 combination with an
extremely scarce supply of prey, where they had an additive effect.
- The heterospecific combination of C7 + Ct consumed fewer aphids than the conspecific combination of C7 +
C7 when prey was scarce to optimal, but consumed a similar number when prey was abundant.
- The conversion efficiency of prey biomass into predator biomass was higher in the heterospecific combination
of C7 + Ct compared to the conspecific combinations of C7 + C7 or Ct + Ct at all prey densities.
- The growth rate of the predators was highest when provided with an abundant supply of prey, while the
conversion efficiency was highest when prey was extremely scarce.