Nasonia vitripennis, the jewel wasp

by Dr. Bethia H. King

GOAL: Provide information and exercises to allow teachers to use the jewel wasp to illustrate biology concepts while meeting the Illinois Learning Goals. This page grew from a presentation at New Ideas in Science conference for middle and high school teachers 7 April 2000, NIU.



I. Why use the jewel wasp?  (see also Dr. Jack Werren's web site)
A. Easy to work with living jewel wasps
    1.  does NOT sting or bite
    2.  commercially available
    2. amazingly easy to maintain and handle
    3. 2 week generation time
  suited to independent/class research projects
B. Iinformation available
    1.  on a wide diversity of topics:  evolution, molecular, genetics, ecology, etc.
    2.  abstracts about available on the web
    3.  both basic and applied research has been done

II. Wasps

A.  Large, social wasps including paper wasps, hornets, yellow jackets are best known by the public.
B.  But many wasps are small, live alone
C.  Parasitic wasps, which the jewel wasp is, parasitize other invertebrates, usually other insects.
      There are more than 100,000 species of parasitic wasps.
       Some species are used in control of pest insects, e.g., the jewel wasp is sold commercially to control pest flies.
       Usually small, often hidden in another insect much of their life (photo of Muscidifurax, of Spalangia cameroni next to a dime, exploring a host, drilling into a host to lay an egg)

III. Taxonomy, classification of the jewel wasp

A. Domain Eucarya = species with eukaryotic cells (DNA in membrane-bound nucleus)
     Kingdom Animalia      (along with humans)
        Phylum Arthropoda    (along with spiders, centipedes, shrimp)
            Class Insecta           (6 legs, 2 pairs wings in adult usually)
                Order Hymenoptera       (= wasps, bees, and ants)
                    Family Pteromalidae    (family names often end with "idae")
                       Genus Nasonia         (must be capitalized and underlined or in italics)
                           Species Nasonia vitripennis        (unique binomial (2 part)  name, not just vitripennis)
B. Insects
    1.  = 70-75% of all animal species, more than 1 million species
    2.  generally less studied per species than vertebrates (fish, amphibians, reptiles, birds, mammals)




papers per species per year

















































From May, 1988: Nature 241:1441-1449.

    3.  why do research on insects instead of closer relatives
        a.  ethical and practical advantages
        b.  economic impact:
             damage to health, food, belongings
             control agents of other pests

C. Less than half of all existing species or organisms have yet been discovered, even in U.S.
    e.g., N. vitripennis was the only known species of Nasonia until the mid 1980's.
    Then 2 new species were discovered,  in bird nests.
    1.  Like most insects, they have no common names, only their scientific names.
    2.  Nasonia longicornis and Nasonia giraulti:
    3.  Whereas  N. vitripennis males have short, nonflying wings,
         Nasonia giraulti males have wings that are 2.4 times that size.
         This difference is known to result from  a few genes, which cause bigger cells, not more cells

IV. Biology of the Jewel Wasp

A. jewel wasp � 2 mm long
    1. female = winged, can fly, usually larger than males
    2. males = brachypterous = short wings, no flight
    3. a parasitic wasp (= parasitoid wasp)

B. host = fly pupa = soft white pupa inside hard dark "shell"
    host = Sarcophaga bullata, Calliphora vomitoria, etc.
    dies when parasitized

C. Natural habitat = carrion, nests, dumpsters
    1. dead animal is colonized [succession]
        via smell, attracts female Nv, carrion beetles, blow flies, also bacteria, fungi, mites
    2. blow fly maggots move to drier parts to pupate
        a. fly egg -> fly larva = maggot -> fly pupa -> winged adult fly = complete metamorphosis
        b. Wings, legs, antennae, hairs pop out during pupation, which occurs inside a "shell."
            (shell = puparium = hardened "skin" of last larval stage)
        c. The adult escapes from the "shell" by using a pulsating bulging soft-spot on it's head.
            (really cool to watch).  The bulging cracks open the "shell".

D. Jewel Wasp Life Cycle
    (diagram shows female laying eggs next to black dot = where she injected venom into the host,
      then wasp larvae in host shell, then wasp pupae in host shell, then adult wasps emerging from host shell,
      note some bit of fly remains)
    1. female Nv parasitizes a fly pupa
         a. She walks over it, feeling and tasting it with her antennae, then later with the tip of her abdomen.
         b. Then she unsheaths her ovipositor (egg layer), and uses it to drill through the dark fly pupa "shell."
         c. She stings into the soft white fly pupa, injecting venom.  She does NOT sting people.
         d. She then squeezes eggs (about 15) out through her ovipositor and onto the white fly pupa inside the shell.
             Or she may stab repeatedly into the fly pupa, and create a feeding tube that brings host fluids out onto
             the "shell," where she laps them up.
     2. Inside the host "shell"
         a. white egg -> wormlike larva -> white pupa -> dark winged adult
         b. sometimes some larvae go into a dormancy called diapause
            (1) diapause = a period of delayed development and reduced metabolism that is broken by cold-dark
            (2) To break diapause of  the larvae, 3 or more months in the refrigerator, followed by exposure to 15-25oC.
            (3) Nv survive the winter by
                  (a) diapause
                  (b) fly shell -> can go 2-3X lower temp
                  (c) get glycerol (antifreeze) from fly host
        c. Adult wasps chew a hole out of the fly "shell."
    3. males develop quicker, come out first, wait for the females to mate.

E. Haplodiploidy: Wasps, ants, and bees are haplodiploid.
    1. female stores sperm in a spermatheca
        (photo shows bands=sperm in oval structure=spermatheca and bend in the duct leading away)
    2. A duct connects the spermatheca to the oviduct (egg passageway).
        If female bends duct to hold back sperm -> unfertilized egg -> son, 1N
        (1N = 1 set of chromosomes)
        If female unbends duct, release sperm -> fertilized egg -> daughter, 2N
       (2N = chromosomes matched in pairs based on size, shape;
                 for each pair, one chromosome comes from the mother, the other from the father.)

F. Other ways organisms might control offspring sex, e.g., humans
     XY sex determination -> 50% X sperm -> 50% daughters
    But can still potentially change sex ratio by:
    1. Differential fertilization by X versus Y sperm X versus Y respond differently to pH, stress hormone levels.
        The timing of insemination relative to the female's reproductive cycle (period cycle) affects her chance of a female,
        perhaps via pH changes.
    2. Natural or unnatural abortion/infanticide of 1 sex.


I. Experimental Design: Have students "block" treatments:
    do treatment one and treatment two always in pairs, matching within each such pair as many variables as possible
     -- age of wasps, day and time tested (and hence temperature, humidity, noise, wind, etc.).
    This teaches the concept of control and is easier than trying to control every single individual wasp in an experiment.

II.  Hypotheses about Locomotor Activity Levels

A. How?
     Record proportion of time spent locomoting in a 10 minute period in a terrarium or a petri dish.
B. What to compare?
    1. female exposed to good host versus female exposed to dead host
        a. 1 host for about 3 hour or maybe 10 hosts for a day
        b. dead hosts: freeze-killed, then stored at room temp
        c. students generate hypotheses:
           (1) Predict female that had poor host will be more active than female that had good host --
                (a) this makes her more likely to find good hosts.
                (b) she needs to rest to recuperate from drilling effort
          (2) Predict female that had good host will be more active than female that had poor host --
                because she has energy from feeding on the host
    2. virgin versus mated females
        a. Obtain virgins by separating males from females in wasps' pupal stage.
        b. students generate hypotheses:
            Predict mated will be active as mechanism to find hosts
            Predict virgin inactive as mechanism to get mated since males can't fly.
        c. Data from King, Grimm, and Reno article (to get, click here and then click on October on left and scroll down)
   3. If female's activity differs on novel versus familiar background
       -> a simple way to see what appears different to them
      a. Put each of 40 females in petri dish with background under dish:
          20 females on blue, 20 on yellow for 1 day  (or pick how long by convenience, e.g, for 1 hour, 3 hour...)
      b. Then move female to new dish on same color background or different color background
          Record proportion of 10 min active.
      c. Result: females on new color more active.
      d.  Try different colors or patterns.
           If difference, conclude females can distinguish pattern/color.
           No difference, conclude females don't distinguish.

II. Adaptive Hypotheses (models) about Offspring Sex Ratio = % offspring that are female

A. Testing the local mate competition (LMC) model
     1. assumes: mating @ natal site, then female dispersal to new sites (e.g., carrion) to oviposit
     2. predicts female-bias sex ratio in a population
        Nv normally produces 80-90% female offspring,
     3. Sex ratio is a genetic trait and hence subject to selection:
        Artifical selection against female bias -> 50-55% females in 14 generations
        (Parker ED Jr., Orzack SH. 1985. Genetics 110:93-105.)
     4. predicts each mother will produce decreased % daughters as more mothers
         r = proportion of female offspring, m = # of ovipositing mothers
         r = (n-1)(2n-1)/(n(4n-1)). Plot r versus m to visualize.
         a. Lone female will produce only enough sons to inseminate local females.
             Otherwise, competition among brothers -> waste resources which could have been used for additional daughters.
             Additional daughters provide mates for her sons.
         b. When multiple mothers are ovipositing,
             (1) additional sons increase a mother's chance that one of her sons rather than another female's son will
                  inseminate locally available females.
             (2) the advantage of additional daughters decreases:
                  they provide mates not just for her own sons, but also for the sons of other mothers.
         c. Reality: data fits model reasonably well
             Greater sex ratio with more mothers in 12 of 14 parasitic wasp species examined,
             the 12 species coming from 4 families.

B. Conclusion
      1. The model is supported. BUT we need to make sure other model(s) do not make the same prediction.
      2. Crowding Model also predicts increasing proportion of sons with increasing number of ovipositing mothers:
          More mothers -> more crowding in host -> offspring smaller.
          May be better to oviposit sons when offspring will be small:
          males are smaller than females so perhaps being large is less important for a female's ability to mate
          than for a female's egg production.
     3. Differential mortality is another possibility: perhaps more daughters than sons die from crowding
     4. So which model is right?
         Answer: look for predictions that differ between the 2 models, but also realize both models could be right.

C. Interspecific Test of the LMC model
     1. N. vitripennis males have short wings, can't fly
         N. giraulti males are fully-winged, can fly
     2. predict N. giraulti does more mating away from the natal site
         so predict N. giraulti less female-biased sex ratio than N. vitripennis
     3. reality: the opposite
         Did the experiment fail?
                Answer: no, failure to support hypothesis not = failed experiment
         Do we throw out the model?
               Answer: not from just 1 instance of lack of support but yes if repeatedly not supported
     4. Solution to puzzle of not supporting our prediction:
         Our assumption that flight reduced local mating was wrong:
         despite their longer wings, female N. giraulti turn out to do more local mating, inside the host, than N. vitripennis.

III. Adaption in general
A.  models in general = use of math equations and graphs to predict what
      trait will become most prevalent by natural selection
       adaptation = genetic trait that causes its carrier to produce more offspring than other genetic traits do
       e.g., adult Nv play dead when disturbed which probably results in less predation, so more offspring

B. Exercise to model natural selection, e.g., on playing dead.
     Give students 2 colors of same type candy
     2 colors represent 2 genotypes; death by student eating candy
     (candy evolution handout: also shows 3 other major mechanisms of evolution:
      mutation, chance= random genetic drift, and gene flow = migration)

C. Does adaptive, "smart" behavior require thought?
    1. Do wasps have to mathematically figure out what behavior is most adaptive in order to behave adaptively?
        Answer: no, easiest to see with a plant e.g.,
        e.g., venus fly trap: contact -> venus fly trap close ->digests Nitrogen from insect -> better survival,
                important to carnivorous plants because in N poor soil
    2.  Generally: intelligent behavior from 1 or more of the following:
        a. Conscious reasoning = logic
            no nerves for in plants; not yet found in insects
        b. Associative learning:
           if behavior -> punishment -> stop behavior
           if behavior -> reward, continue behavior
          No nerves for in plants; has been found in insects, including Nv
       c.  "unthinking intelligence" = natural selection: "survival of the fittest"
       d. simple rules of thumb can -> smart behavior in a predictable environment
           e.g., bumble bees start at bottom of inflorescence where most nectar.
                  rule not = start with best flower; rule = start at bottom and go up
          e.g., play dead by seizure when disturbed versus by pretending


I.  Nv is Used in Applied Research (applicable to human problems)
     A. biocontrol = control pests with predators, parasites
          1. Nv sometimes parasitizes pest flies (e.g., house fly)
          2. Nv sold on internet
             easy to rear but other wasp species probably better for biocontrol
          3. adv: nontoxic to humans, wildlife, fairly specific hosts
    B.  Biocontrol can mess up "ecological balance" just as chemical control can
         e.g., Cane Toad (hilarious video) in Australia to control sugar cane beetle but doesn't and toad population exploded
    C.  Biocontrol may reduce resistance problems
         1.  Flies and other pests become resistant to insecticides
         2.  Use of biocontrol agents may select for resistant flies too (it does in lab)
         3.  BUT wasps can evolve ability to overcome fly resistance versus chemicals can't,
              though we can switch chemicals
        4. not always economical compared to chemical control

II.  Nv is Used  in Basic Research (basic knowledge)

B. Why understanding locomotor activity is of interest:
     1. To understand evolution, behavior
         Be more or less active may be a "simple rule of thumb" for finding good hosts, ensuring mating.
     2. May be useful for biocontrol:
         Release active wasps if need them to disperse to locate hosts.
         Release inactive wasps if need them to stay at release site.
C. Why understanding sex ratios is of interest:
     1. To understand evolution, behavior
     2. In biocontrol, female-biased sex ratios may be useful.
         One female can mate with many females, and it is the females which kill the pest hosts.


I. Wasp N. vitripennis
    A. Obtain from Carolina Biological Supply Co. (They send instructions.) or Ward’s:
         Can crack off top about 1/6th of host pupa length at pointy (head) end to check on wasp development.
    B. Maintaining adults:
         1. Keep in petri dishes or in test tubes plugged with cotton.
             Minimize static with glass versus plastic container and humidity.
         2. Feed adults a wasp-size drop of honey.
             Wet honey with water drop every 2-3 days or keep in humid container.
         3. Adults live about 2 weeks
    C. Pick up adults with soft forceps/paintbrush or with test tubes
         Wasps walk up tube. Slap tube to tap them out onto a table. Then place test tube over top.
    D. Generating more wasps
         1. Put a mated female with 2 Sarcophaga bullata or 5 Calliphora vomitoria for a day.
            (or just leave 1 or 2 females with hosts until they die.)
         2.  Any female that has been in a tube with wasps that emerged from host(s) is probably mated.
              Or you can assure mating by putting together in a test tube,
              a male and female that were isolated as pupae and hence are virgin.
         3. Development time:  Egg to adult takes about 2 weeks at 27oC.
             males emerge out of host before females by a day or 2.
    E.  Refrigerate to slow down, warm to speed up development.

II. Fly Hosts:
     A. Obtain
          Sarcophaga bullata = blow fly, come as pupae or larvae from Carolina Biological Supply Co.
          Calliphora vomitoria = 2nd fly host species, come as larvae,
          from Grubco, Inc, OH 1-800-222-3562, $5.50 + delivery for 500
          check your local bait shop.
     B. Maintaining hosts:
          1. If you order larvae, open package immediately. Dump into steep sided plastic container, like a shoebox,
              with sheet of newspaper on bottom.
              Can put under light -> they crawl under newpaper to pupate.
              Will be parasitizable in 2-3 days. ("Shell" becomes easy to crack with white pupa inside).
          2. Store pupae in cup covered with paper towel+ rubber band, in refrigerator for months.
          3. Can crack off a cap that is 1/6 of host pupa length at pointy (head) end to check on.
              Should find a white, puffed out fly pupa.  As gets deflated looking or dark, time to get new hosts.
          4. Wasps can also develop on just-thawed frozen pupae, but fewer wasps will develop per host.

III. Disposal:  freeze-kill extras wasps and flies.


LOCOMOTOR ACTIVITY: Mean � SE (range = minimum - maximum) seconds active and number of hops, short flights and long flights. Hops were less than about 2 cm, short flights about 2 - 6 cm, and long flights about 6 cm.
Data from King, Bethia H., Grimm, Katie and Reno, Hilary. 2000. Effects of mating on female locomotor activity in the parasitoid wasp Nasonia vitripennis (Hymenoptera: Pteromalidae).(to get, click here and then click on October on left and scroll down)

                                                          Short       Long
Treatment    n   Time Active Hops       Flights     Flights

   Virgin     22    238 � 28       0             0.091      0.045
                        (51 - 533)      (0 - 0)     (0 - 1)     (0 - 1)

Mated       22    406 � 25       2.23         1.46        3.36
                        (128 - 572)    (0 -29)     (0 - 8)     (0 - 14)

                        t = 4.50
                        df = 42
                        P < 0.001

OFFSPRING SEX RATIOS OF 2 NASONIA SPECIES: Mean � s.d.. sex ratio (proportion sons) and number of emerging sons and daughters per female with different numbers of females ovipositing on four hosts. Sample size is the number of vials. The H values below the data are the results of analyses by Kruskal-Wallis one-way ANOVA.
Data from King, B. H. and S. W. Skinner. 1991. Sex ratio in a new species of Nasonia with fully-winged males. Evolution 45:225-228.   Plot of data versus predicted LMC curve.

Number of          Sons              Daughters       Sex Ratio          Sample
Mothers                                                                                Size
per Vial
Nasonia vitripennis
 1                       10.0 �  5.5      54.6 � 15.4      0.16 � 0.06      10
 2                       24.6 � 11.3     34.1 � 15.8      0.43 � 0.16        9
 4                       30.3 �  7.7      22.6 �  6.7       0.57 � 0.11       8
 8                       31.3 �  9.6        8.4 �  3.7       0.78 � 0.10       8
16                      18.7 �  3.9        4.6 �  1.2       0.80 � 0.07       8
                          H = 22.97       H = 34.92        H = 34.27
                          P < 0.001        P < 0.001        P  < 0.001

Nasonia giraulti
 1                        2.9 �  0.4      49.4 � 15.5      0.06 � 0.02       7
 2                        3.1 � 2.5       25.7 � 11.9      0.10 � 0.06       8
 4                        3.2 � 2.1       17.8 � 10.0      0.15 � 0.08     11
 8                        4.5 � 2.7       18.6 � 8.6        0.19 � 0.07      9
16                       4.6 � 1.3       16.4 � 2.2        0.22 � 0.04     10
                           H = 9.08       H = 20.23        H = 22.67
                           P = 0.06        P < 0.001        P < 0.001

LOCOMOTOR ACTIVITY OF Nasonia vitripennis: Raw Data
variable/column 1: 1 = virgin, 2 = mated female
variable 2: # of hops
variable 3: # of short flights
variable 4: # of long flights
variable 5: duration of testing, minutes
variable 6: duration of testing, seconds
variable 7: time active, minutes
variable 8: time active, seconds
1 0 0 0 10 00.64 05 30.76
2 1 0 0 10 00.75 08 17.97
1 0 0 0 10 00.41 01 36.50
2 0 0 0 10 00.37 06 15.94
1 0 0 0 10 00.54 03 04.71
2 0 0 4 10 00.69 07 40.26
1 0 0 0 10 00.47 04 50.67
2 1 2 1 10 00.43 09 20.95
1 0 0 0 10 00.00 01 54.00
2 29 1 4 10 00.53 05 43.30
1 0 1 0 10 00.75 05 23.50
2 0 0 0 10 00.62 07 31.06
1 0 0 0 10 00.34 05 20.39
2 0 0 1 10 01.53 05 40.40
1 0 0 0 10 01.47 03 01.37
2 0 0 4 10 01.40 07 07.02
1 0 0 0 10 00.41 08 52.95
2 0 0 0 10 01.13 03 50.96
1 0 0 0 10 00.00 02 59.33
2 0 0 0 10 00.00 09 17.32
1 0 0 0 10 00.30 02 27.60
2 0 1 0 10 00.22 08 30.98
1 0 1 1 10 01.52 01 53.01
2 0 4 6 10 00.19 07 20.94
1 0 0 0 10 00.00 05 39.17
2 0 1 8 10 00.85 07 51.94
1 0 0 0 10 02.02 05 23.00
2 0 0 0 10 00.52 09 32.93
1 0 0 0 10 01.31 02 56.74
2 0 0 0 10 00.47 02 08.20
1 0 0 0 10 00.33 05 52.48
2 0 1 7 10 00.57 05 15.96
1 0 0 0 10 00.37 01 08.55
2 0 0 0 10 00.66 09 03.98
1 0 0 0 10 00.00 08 13.00
2 1 6 9 10 00.65 06 58.35
1 0 0 0 10 00.00 00 50.52
2 1 8 14 10 00.00 05 57.33
1 0 0 0 10 00.00 03 25.28
2 8 3 1 10 20.19 05 08.74
1 0 0 0 10 00.53 01 48.74
2 0 4 9 10 00.78 05 40.35
1 0 0 0 10 00.53 05 07.95
2 8 1 6 10 00.00 05 01.30


Statistics: 1) Ignore and have students just look at means (averages). or 2) Have students rely on the statistical values provided, following the statistical rule: If P < 0.05, conclude the treatments differ from each other. If P > 0.05, conclude the treatments do not differ from each other statistically. or 3) have students do statistics, by hand or by computer.

When asking a question such as, "Does the sex ratio depend on the number of mothers?," we attempt to answer by looking at a sample (e.g., a sample of wasps). If all of the single mothers produce a greater proportion of daughters than all of the paired mothers and if we have looked at lots of wasps, we feel confident that proportion of daughters depends on the number of mothers. However, outcomes often are not that clear cut. Also, because we are looking at a sample and not every single wasp that exists, there is the possibility of sampling error. Sampling error occurs when the sample you are looking at is not representative of the population from which it came. We need criteria by which to decide whether observed differences reflect real differences or are due to sampling error. Statistics provide that criteria.

It is conventional to use 0.05 as the significance level in statistical tests. If a statistical test indicates that there is a difference among treatments, and we have used 0.05 (or less) as the significance level, then there is a 5% or less chance that the difference we observed is just due to sampling error.

COMPARING TWO MEANS BY A T-TEST (e.g., time active for mated versus virgin mothers):

A t-test tests whether there is a difference between two means (averages). It assumes that the values in each of the two groups being compared are normally distributed. (I.e., if you plotted the range of observed values on the x-axis and the frequency of those values on the y-axis, then for each group the line would be bell-shaped.) The t-test also assumes that the two groups have the same variance (exhibit the same amount of variation). Luckily, the t-test is robust to these assumptions (i.e., it will give reliable results even if the assumptions are off somewhat). If you do your analyses on a computer, you can do statistical tests to check the assumptions, and switch to a nonparametric test (a Mann-Whitney U test) if the assumptions are not met.


1. t = (mean of treatment 1 - mean of treatment 2) � square root of the pooled variance

2. n1 = # of values in treatment 1
    n2 = # of values in treatment 2

mean for treatment1 = sum of all the values in that treatment � n1
pooled variance = (n1 - 1)(variance1) + (n2 - 1)(variance2)
                                           (n1 + n2 - 2)

variance1 = S (each value in treatment 1 - mean1)2
                                   (n1 - 1)

df = degrees of freedom = n1 + n2 - 2

3. In a table of Critical values for the t-test at alpha = 0.05, find your df and the t that is in the table for that df.
    If your calculated t is bigger than the tabular t, conclude that the two groups were different.
    If the calculated t is less than the tabular t, conclude that the two groups were not statistically different.
    (For the Nasonia data set presented here, table t = 2.0)

COMPARING OBSERVED VERSUS EXPECTED FREQUENCIES BY CHI-SQUARE ANALYSIS: (e.g., number of sons and daughters observed versus expected by LMC model:

One way to have students analyze the sex ratio data is by chi-square, which compares observed frequencies to expected frequencies.

1. For each number of mothers in a vial, to generate the observed frequencies,
    multiply the number of sons and the number of daughters each by the sample size.
2. For each number of mothers in a vial, to generate the expected frequencies
    of sons: multiply the total number of observed offspring (sons +
    daughters) by the sex ratio calculated from LMC theory, m = number of
    mothers, proportion sons = (m-1)(2m-1)/(m(4m-1)).
3. To generate the expected frequencies of daughters, subtract the expected
     frequency of sons from the total number of observed offspring.

1. chi-square = S { (observed - expected)2/expected}
    That is for each combination of sex and number of mothers in a vial, you would compute
     (observed - expected)2/expected. Then you would sum those values up. Sum 10 values in this case.
2. Calculate what is called the degrees of freedom for the test:  df = number of categories compared - 1
    df = 10 -1 in this case.
3. In a table of Critical values for the chi-square at alpha = 0.05, find your df and its corresponding table chi-square.
    Compare the table chi-square to the chi-square that you computed.
    a. If your calculated chi-square is bigger than the table chi-square,
        conclude that the observed frequencies were different from the expected.
        To see the logic of this, look at the chi-square equation in #1 above:
         note that the bigger the difference between observed and expected, the bigger the Chi-Square,
         and the more likely that your observed values differ from the values that you would expect if there
         was no difference among treatments.
    b. If your calculated chi-square is less than the table chi-square,
        conclude that the observed frequencies were not statistically different from the expected.
    c. You should be able to figure out which of these two outcomes allows you to conclude that the wasps responded
        differently than the LMC model predicted.)

RESOURCES ����������

WEB SITES:    search on "parasitoid wasp" or "jewel wasp" or "sex ratio" Use the quotes.
���� ���������������������Teaching lab on inheritance of eye color in jewel wasps:
������������������������� Exploring the Lotka-Volterra Competition Model using Two Species of Parasitoid Wasps:
Competition Within and Between Species of Parasitoid Wasps:
������������������������� High school class working with jewel wasps:

������������������������� Mating isolation due to a bacterial infection in jewel wasps

BOOKS       Brown L, Downhower JF. 1988. Analyses in Behavioral Ecology.
                     Behavioral labs with a wide range of species, not just insects; designed for college age, but might provide
                     ideas for middle or high school science projects and has short explanations of statistics to analyze the data
                     they collect.

Charnov EL. 1982. The Theory of Sex Allocation. Princeton University Press, Princeton, NJ.

Wrensch DL, Ebbert, M, eds. 1993. Evolution and Diversity of Sex Ratio in Insects and Mites. Chapman and Hall, New York.

Godfray HCJ. 1994. Parasitoids. Princeton University Press, Princeton, NJ.

Waage JK, Greathead D, eds. 1986. Insect Parasitoids. Academic Press, London.


Review Articles:
Werren JH. 1987. Labile sex ratios in wasps and bees. Bioscience 37:498-506.
King BH. 1987. Offspring sex ratios in parasitoid wasps. Quarterly Review of Biology 62:367-396.
Reviews, for parasitic wasps, all the different things that affect what sex offspring a mother produces.
King BH. 1993. Sex ratio manipulation by parasitoid wasps. pp. 418-441. In: Wrensch DL, Ebbert, M (eds). Evolution and Diversity of Sex Ratio in Insects and Mites. Chapman and Hall, New York.
Summarizes sex ratio manipulation by parasitoid wasps in relation to 2 sets of adaptation models.

Primary Literature = original descriptions of experiment and data
King BH. 1993. Flight activity in the parasitoid wasp Nasonia vitripennis (Hymenoptera: Pteromalidae). Journal of Insect Behavior 6:313-321.
Measured how long females from different treatments flew when tethered.
King BH, Skinner SW. 1991. Proximal mechanisms of the sex ratio and clutch size responses of the parasitoid wasp Nasonia vitripennis to parasitized hosts. Animal Behaviour 42:23-32.
females produce a greater proportion of sons not only when they are with other females versus alone but also when they encounter an already parasitized host versus an unparasitized host. This paper examines how they tell whether or not a host has already been parasitized.
King BH. 1992. Sex ratios of the wasp Nasonia vitripennis from self- versus conspecifically-parasitized hosts: local mate competition versus host quality models. Journal of Evolutionary Biology 5:445-455.
Examines whether a female can distinguish between a host that she herself parasitized versus one that another female parasitized. The theory and experiments are complicated.
King BH. 1993. Sequence of offspring sex production in the parasitoid wasp Nasonia vitripennis in response to unparasitized versus parasitized hosts. Animal Behaviour 45:1236-1238.
Moderately complex. Shows that females tend to start laying sons first in parasitized hosts and daughters first in unparasitized hosts.

Dr. Bethia H. King,, Department of Biological Sciences, Northern Illinois University, DeKalb, IL 60115,

� Bethia King 2000, 2005, 2007