Ent 207                                   Lecture 15-19                  February, 2002.

What is ecology?

KREBS definition of ecology is:

The scientific study of the interactions that determine the distribution and abundance of organisms.

In this case focused on insects, which doesn't exclude much!!!

scientific study - process of observation and experimentation leading to the rejection of all but one hypothesis: not the truth or fact but the best fitting explanation of all the observations.

interactions - include both biotic and abiotic factors.
distribution - where insects occur.
abundance - a measurement of population size.

from the point of view of agriculture, studies of populations of insects and their interactions with the environment are often restricted to a unit we call an agroecosystem.

- agroecosystems

may be extensive  "corn belt" or wheat growing areas of the Great Plains of North America or

limited - isolated orchard consisting of a few acres plantedwith widely-spaced trees or a greenhouse.

 - agroecosystems regardless of size have some common characteristics including:

(1) created and maintained by human effort.

(2) agroecosystems often lack temporal continuity.

(3) plant selection by humans

(4) in any particular system often reduced species diversity frequently a single species dominates.

(5) uniform phenology.

phenology  def'n: the study of seasonal changes which give rise to the observed periodicity of biological phenomena.

(6) addition of nutrients.

(7) frequently occurring insect, weed and disease outbreaks.

Question

      Is this an inescapable result of agriculture/agroecosystems?

Contemporary Polyculture

- Meb'engokre - Brazil.
- create forest islands - apete .
- censused ten of these islands - contained 120 species, 90 planted.
- "ecological" knowledge required is substantial.

e.g. - insects - use one species of ants to discourage a detrimental species.
- cultivate plants which have extrafloral nectars which attract predatory ants.
- bananas planted around the outside - predatory wasps nest under the leaves.

A major technological development with respect to insect pests

- WW II led to the development and introduction of many new chemical insecticides.
- massive industries which needed peacetime markets.

- seemed so effective, changed attitudes:
- ecological information had reduced importance.
- many applied entomologists talked of eradication (some still do) of insect  pests.
- some were so confident that it was suggested that preserves for some "pest" species might be needed to prevent extinction.
- detractors in the period (including entomologists) warned of deficiences of this approach ---> resistance.
- the chemical solution --produce a new chemical to overcome resistance.
- by the 1960's, the problems of resistance and secondary outbreaks.

def'n (secondary outbreaks) = the result of non-selective control procedures in which nontarget control factors {frequently unobserved predators and parasitoids} take longer to recover than the species which now becomes a pest - previously unobserved as a pest).

Some of the factors which have led to increased ecological considerations:

(1) resistance to insecticides- more than 500 species.
(2) replacement - secondary pest outbreaks = new pests.
(3) resurgence - rebound effects = worse pest than before.
(4) pollution, environmental degradation effects.
(5) led to laws, codes regulations - eliminating many pesticides.
(6) public perception/demands for "clean food".

- in order to determine whether a particular species will become a pest one may need to acquire considerable information about the population dynamics or if a known pest this information may be used to determine whether a control procedure may be necessary and if so, the best time to apply it.

- with sufficient information one may be able to anticipate a pest problem and minimize the damage/loss at the lowest cost.

- parameters one might want to measure include:

1.) density - insects per unit area.

2.) dispersion - spatial arrangement of the insects in the landscape.

      a. regular/uniform   b. random      c. clumped/aggregated

3.) dispersal - not trivial movements but immigration into an area or emigration from an area. 

long distance:

e.g. Canadian prairies - diamondback moth; don't usually complete development in our climate; recently they have been shown to overwinter here

short distance (on a more local level):

(i) nearby crops.
(ii) nearby alternate hosts - aphids woody shrubs and herbaceous plant

4.) age distribution - proportion of individuals in different age groups at any given time.  e.g. Codling moth adult flight.

univoltine - single generation in a year (many pest insect species, especially in cooler regions).

multivoltine - two or more generations in a year; the number of generations is dependent upon the developmental time requirements and adequate environmental conditions, e.g. heat. 

- whether a species is multivoltine or univoltine can depend upon genetic program  or the environment.   e. g. codling moth versus forest tent caterpillar, FTC.

- codling moth there are one to three generations per year as conditions in a given location permit; there is one generation per year regardless of conditions. 

5.) natality - birth rates.

6.) mortality - death rates - mortality is caused by numerous factors:

ABIOTIC

 - in general insects which are in their natural habitats are well adapted.
 - distribution of host plants (characteristics of an agroecosystem) may alter the natural distribution so that abiotic factors are more important - insects are found
at the limits of their range - perspective of abiotic factors.
 - will they adapt and extend range?   If they do, will they become a problem?
 - occasionally unusual weather conditions may have significant impact on insect abundance.
 - or given sufficient knowledge of abiotic factors one can perturb the system so as to reduce the survivorship of an insect.
e. g. turn over the soil for insects which overwinter as pupae in the soil.

1) temperature - outside the limits or thresholds temperature, too much or little heat can have deleterious effects.

2) moisture - moisture conditions may significantly infuence insect survival.

- grasshopper eggs require specific soil moisture conditions; if moisture conditions are suboptimal, egg survivorship decreases.
- thus if soil moisture levels remain optimal for several years grasshopper populations can increase.
- complicated by the observation that moisture levels that are optimal for grasshopper egg laying may be optimal for natural enemies as well.

3) weather - winds can transport sufficient numbers of insects to cause damage  in areas where these insects would not normally survive.

  - heavy rains can dislodge young insects from foliage and these are subsequently destroyed.

4) climate - interaction of the previous factors and others

- described insects which reach Canada but never become permanently established.
- some early attempts at biological control failed because of a failure to understand the effects of climate of insects.

e. g. difficult to establish.

a) lab and short term field results indicated that a predator had good control potential.
b) under natural conditions differential effects of the climatic conditions led to asynchrony - pest wasn't available when predator active.

BIOTIC

1) predators, 2) parasites and 3) disease (natural enemies) consider in detail when discussing biological control.

- in general, the greater the diversity and abundance of natural enemies the greater the capacity to reduce pest population densities.
- this is a feedback system and when pest numbers are low the abundance of natural enemies is frequently also low.
- under natural conditions, increases in population densities of natural enemies lag behind that of their hosts.

4) competition

i. interspecific -different species competing for the same resources.

e.g. cone moths -distort cone - kills other insects in the cone.
rarely of value for agriculture.

ii. intraspecific - as population increases competition for remaining resources increases; oviposition sites, food, overwintering sites.

e.g. . Pupation sites for overwintering codling moth

clean up debris; prepare trap sites - banding trees with cloth.

-there are many other factors which may contribute to insect mortality but these should be examined on a case by case basis.

-use information (ecological inputs) to develop management model (system where data from many sources is integrated in a control strategy).

- in some cases all this information has been plugged into computer simulation models which can be used as the basis for decision-making.

- another technique that has been used to analyze this data is to compile it into life tables.

Life tables are a convenient means of compiling information--compile information which tells us:

      1. the boundaries of insect population fluctuations.

      2. the individual factors which are involved in the "natural" regulation of

            populations.

Information can be used to evaluate the potential for manipulating these factors to satisfy our needs, i.e. to protect our crops--health, etc. or if we can't manipulate natural control factors what is the best point to apply a control strategy.

see HANDOUT  (Insect life table A and symbol key).

- error in table - used dispersion instead of dispersal.
- one of the first studies using life tables for insects. (early 1950's)
- note the sampling method - number of insects/ unit area.
- header at top of table.

i) mortality factor - starvation.
ii) sprayed with DDT anyway - minimal mortality. (Why bother spraying?)
iii) new foliage destroyed - starvation - feeding habits of larvae.

- determine point when additional controls may have most significant impact. 
- is the crical stage eggs, 1st instar,  etc. ?

see HANDOUT  (Insect life table B and C).

- natural systems tend to be more complex with respect to number and type of mortality factors.

- usually easier to evaluate agricultural systems.

- limited value with a single year of data.

- still can determine population trends - increasing,etc.

- can be plugged into simulation models - determine the effects of control procedure.

- analysis can be very complex; e. g. a chemical control procedure which may kill only 80% of the pest species at a given time but nearly 100% of a natural control agent which may exert its critical influence at a later date - possibly requiring  a further application of a pesticide at an unacceptable cost.

see HANDOUT  (commodity and costs-based tables D, E).

- another way of using life tables - a commodity with the factors causing losses tabulated. (table D).
- which in turn are converted into dollar values (table E).
- may be used to do cost/benefit analysis.

question: If cost of controlling cutworms per acre = $175.

                     would it be worth it?

see HANDOUT  winter moth

- actual case history which validated the life table approach.
- winter moth (Geometridae) introduced from Europe.

Models - use computer analysed data inputs.

e. g. Codling Moth

- pest of apples, pears, and walnuts.
- instruments (heat and moisture detectors) in the field.
- data monitored and analyzed by computer.
- predicts timing of sprays (in this case for both insects and fungal disease).

- insect - microbial (GVirus) or chemical (incorporate sterile males)
- fungus - chemical.

value of the system

(A) increased effectiveness.
(B) reduced cost.
(C) reduced pollution

(A) increased effectiveness:

      a) replaced a calendar-based system (spray according to a calender date whether there was a need or not).
      b) control procedure implimented at precisely the time when the target was most vulnerable --long term implications??

(B) reduced cost because fewer applications necessary.

(C) results in less pollution, etc., even if not a consideration of the grower!

Question:   What are data inputs to set up model?

(1)  i. life history of the pest- growth rates - generations/yr.
ii. growth requirements of the fungus (in this example).
(2) population size of the pest - e.g. codling moth - sampling.
(3) phenology.

- in the case for codling moth and apples let us start with a hypothetical orchard in isolation.
- let us further assume that we have determined the initial population size by a  sampling procedure.
How is this information useful?  What do we need to know before deciding  whether we should do anything to control the insect?
- we have a population estimate--how do we use this information, where to start?

lab studies

- determine the reproductive (biotic-text) potential - this is evaluated in the complete absence of any destructive forces;

i.e.    - no predators, parasitoids or pathogens.
- no severe weather that insects would experience in the field.
- an artificial environment.

Question:

      What information do we need to calculate the reproductive potential?

(1) length of developmental period
(2) fecundity
(3) sex ratio

(1)  LENGTH OF DEVELOPMENTAL PERIOD

- time to complete one generation.
- some examples:    (which are likely to be agricultural pests?)

i. cerambycids 1-4 years.
ii. death-watch beetle 12-15 years.
iii. Drosophila spp.- 2 weeks.
iv. Codling moth-one to three generations/yr depending upon climatic conditions.

- most agricultural pests have developmental periods of one year or less.

Question:

How does one determine the developmental period of an insect species?

Since insects are "cold-blooded" their rate of development is intimately related to the amount of heat they experience - this being measured by the temperature -increase the temperature -> growth rate increases.

in the lab

- typically insects are placed in environmentally controlled chambers using constant temperatures and then monitored for growth.
- look at increases in body weight, but the number and duration of each stadia can be monitored.
- data (for each stadium) from this series of growth studies can be plotted.

see your sketch

- from this one estimates a developmental threshold - below this temperature no development occurs(this value is variable among species).
- above the minimum and over a broad range of temperatures the relationship between development and temperature is nearly linear.
- there is a maximum above which development slows and also a temperature at which the insect has optimum development - different stages may have different optimums.
- the data has to be analyzed in order to make useful field predictions
- the most common way to make these estimates is the degree-day method;

                (DD or ^oD).

- this represents the accumulation of heat units above some minimum or threshold

      for a 24 hour period.

- in the lab the incubator temperatures are set over a range of temperatures and for each 24 hour period one performs the following calculation.

DD = INCUBATOR TEMP. - DEVELOPMENTAL THRESHOLD

      e.g.     30 - 10 = 20 degree-days

Record:

-in the field, temperatures fluctuate so the calculation is performed as follows:

DD = maximum temp. + minimum temp.  - developmental threshold

                              2

Rules:

  i) if maximum temp. for the day below the developmental threshold -> no DD accumulated.

 ii) if temperature above the threshold only part of the day set the minimum at the threshold.

                  threshold =  10 ^oC         max. = 15 ^oC           min. = 2 ^oC

            15 + 10   -  10   _{=    2.5 degree days}

                2     

iii) if maximum exceeds the optimum, set at optimum.

                  optimum = 35 ^oC           max. = 38 ^oC           min. = 25 ^oC

            35 + 25  -   10   _{=    20 degree days}      

_{- these rules are adjustments made to the degree-day model to improve the correlation of the laboratory-derived developmental rates with the actual development periods measured in the field.}

(2)  FECUNDITY- egg production by the female.

  e.g. codling moth - female: 30-40 eggs.

 (i) laboratory experiment - in some cases can optimize conditions to produce a maximum number of eggs.
 (ii) can capture pupal/adult females - dissect to determine the number of eggs in the ovaries.
(iii) could sample egg masses in the field - examine the area where eggs are laid; also determine the fertility at the same time.

 (3)  SEX RATIO

- proportion of males and females in a species often expressed as a simple ratio of males to females.
- in insects commonly 1:1.
- in one of the insects we have observed a 0:1 ratio - at least during part of the life history --aphids.

- why is this important information?  - all adults are reproductives

Consider a hypothetical example:

two insect species  (equal fecundity and developmental rates).

species A - fecundity = 100        sex ratio 1:1
species B - fecundity = 100        sex ratio 0:1

 (3 generations/year).        

species A (two individuals)

species B (two individuals)

Reproductive Potential

all these factors can be related by the following equation:

Rep. Pot.= pzⁿ

where  p = the number of individuals (set at 1 for calculation)
and     z = fecundity X sex factor
and     n = number of generations for a year or time period of interest.

e.g. length of growing season for a crop.

note - for these calculations the sex ratio is converted to the sex factor (the sex ratio expressed as the proportion of females in the total population)

Sex factor = no. of females/total population

e.g. Codling Moth-a single female under different climatic conditions.

      R.P. = (1)(40X0.5)¹--------> 20      (females)

      R.P. = (1)(40X0.5)³--------> 8000      (females)

-this calculation  -- consider as potential damage.

- might be used to evaluate the feasability of growing a particular crop in a given area.  (what are the cost of crop protection?)

e. g. Trichoplusia ni (cabbage looper)

               p = 1; z=300 X 0.5 (sex factor) n=5 (southern California)

            R.P.= (1)(300X0.5)⁵--------> 7.6 X 10¹⁰

Question:   Would you expect this number of insects to be generated even under ideal conditions?

In simplified terms, the number of individuals in a population reflects their ability to exist against all the destructive forces arrayed against them

= environmental resistance.

the abundance (A) of an insect population can be estimated by the equation:

Abundance = reproductive potential - environmental resistance