Maternal antibodies in a wild altricial bird: effects on offspring immunity, growth and survival


Marjo Pihlaja, University of Jyväskylä, Department of Biological and Environmental Science, PO Box 35, FI-40014 Jyväskylä, Finland. E-mail:


  • 1In many animals immunity is not fully developed until adulthood but the young still need protection against various sets of pathogens. Thus, bird nestlings are highly dependent on antibodies received from their mother (in the eggs) during their rapid early growth period. The relationship between maternal immunity and the development of neonates’ own immunity has been poorly studied.
  • 2It has been suggested that immune function plays an important part in mediating resource competition between different life-history traits, e.g. growth and reproduction. Maternal investment of antibodies has potentially permanent effects on offspring phenotype. Thus, the trade-offs between the immune function and other important life-history traits in the offspring will also affect the fitness of the mother.
  • 3Our supplemental feeding experiment in the magpie Pica pica indicates that the immunoglobulin levels of offspring at hatching are dependent on a mother's nutritional condition. In addition, the amount of maternal immunoglobulins transferred to offspring increases along the laying order within a nest.
  • 4We also found that at the age of 8–10 days the immunoglobulin production of the offspring has already begun. Furthermore, the maternal immunoglobulin levels of the offspring at hatching were positively related to their immunoglobulin levels on day 10.
  • 5Maternal immunoglobulins did not significantly affect offspring growth, but there was a negative relationship between self-produced immunoglobulins and growth over the first 10 days, indicating a trade-off between these traits. Nestlings’ weight, however, had a positive relationship with immunoglobulin production suggesting that the observed trade-off between growth and immunoglobulin production is due to catch-up growth of nestlings with a low hatching weight. We found that within nests nestlings with higher maternal antibody levels had higher survival rate until day 20, but between nests there was an opposite relationship.
  • 6Evidently, there is a trade-off, in magpies, between maternal resources, immune function and growth, shaping the evolution of maternal investment in offspring immunity.


Animal immune systems continually adapt to changing pathogen challenges and several studies suggest that immune function plays a major part in life-history trade-offs (Sheldon & Verhulst 1996; Lochmiller & Deerenberg 2000; Norris & Evans 2000; Soler et al. 2003; Brommer 2004). In birds, innate immunity (macrophage–phagocyte system) and lymphocyte-mediated acquired immunity comprise the main immunological system (Klasing & Leshchinsky 1998). Energetic and nutritional costs associated with innate immunity are more substantial than the costs of the adaptive (B-cell-mediated acquired) immunity, at least after the adaptive immunity is fully developed (Klasing & Leshchinsky 1998; Råberg et al. 2002). However, the establishment of adaptive immunity is a slow, resource demanding process; it can take from several weeks to months during ontogeny (development until adulthood) for adaptive immunity to mature fully (Apanius 1998; Klasing & Leshchinsky 1998). Newly hatched young are dependent on innate immunity and maternal immunoglobulins (Klasing & Leshchinsky 1998; see also Tella, Scheuerlein & Ricklefs 2002). Mothers are able to transfer immunoglobulins to their young via the egg yolk (Deeming 2002; for a recent review, see Grindstaff, Brodie & Kettersson 2003). These maternal immunoglobulins protect the offspring against pathogens their mothers have encountered in their environment (Klasing & Leshchinsky 1998; Rollier et al. 2000; Gasparini et al. 2001).

Resource allocation to eggs can be nutritionally and energetically costly to the mother (Nager, Rüegger & van Noordwijk 1997; Nager, Monaghan & Houston 2000; Royle, Surai & Hartley 2003; Williams 2005). A mother has to find a balance between the amount of resources transferred to her offspring and the amount kept for herself. Immunoglobulin transfer may involve costs as well. However, on captive Japanese quail Coturnix japonica the amount of dietary proteins affected egg number and size but not egg yolk immunoglobulin levels (Grindstaff, Demas & Ketterson 2005).

Because offspring of the same mother can have different values for her future reproductive success (Viñuela 1997; Lindström 1999; Petrie et al. 2001; Saino et al. 2002, 2003; Blanco et al. 2003), it might be beneficial to the mother to vary resource allocation within clutch. For example, Buechler et al. (2002) found increasing immunoglobulin G (IgG) concentrations along the laying order in clutches of great tits Parus major where the mothers had been experimentally exposed to parasites. On the other hand, both Blount et al. (2002) and Müller et al. (2004) found a trend of decreasing maternal IgG levels with the laying order in the eggs of black-backed gulls Larus fuscus and black-headed gulls Larus ridibundus, respectively, whereas in Japanese quail egg immunoglobulin levels were equal through the laying order (Grindstaff et al. 2005).

There are benefits and costs (e.g. protection against oxygen radicals by antioxidants and production of radicals by testosterone metabolism) from the different resources deposited into the egg. Thus, there might be trade-offs or interactions between immunoglobulin levels and the other parameters of egg quality, which can also vary within laying order (Chew 1996; Haq, Bailey & Chinnah 1996; Gore & Qureshi 1997; Apanius 1998; von Schantz et al. 1999; Blount et al. 2002; Saino et al. 2002; Koutsos et al. 2003; Royle et al. 2003; Williams et al. 2005).

In nestling birds, there is a trade-off between the nutrients required for, e.g. growth and those needed to mount an immune response (Sheldon & Verhulst 1996; Klasing & Leshchinsky 1998; Lochmiller & Deerenberg 2000). High levels of maternal antibodies may therefore conserve more resources for rapid growth during the immediate post-hatching period (Klasing & Leshchinsky 1998; Buechler et al. 2002). This can be important especially in altricial species, in which the young hatch at an early stage of their ontogeny (Klasing & Leshchinsky 1998). However, maternal antibodies may partly prevent the stimulation of a neonate's own immune mechanisms (Apanius 1998; Klasing & Leshchinsky 1998; Grindstaff et al. 2003). On the other hand, there is some evidence that maternal antibodies may improve the strength of the offspring's immune response and that, in the absence of maternal immunoglobulins, the offspring's immune responsiveness is depressed (Malanchere, Huetz & Coutinho 1997; Yasuda et al. 1998). Hence, there should be a balance between the protection provided by maternal immunoglobulins and the stimulus needed for the development of a neonate's own immune system.

We investigated maternal immunoglobulin transfer and the development of adaptive immunity in a natural population of the magpie Pica pica. Magpie is a medium-sized passerine bird with an altricial developmental mode, asynchronous hatching, and sexual size dimorphism (males are about 10% larger) (Birkhead 1991). We used a food supplementation experiment to investigate whether resource limitation before and during egg laying affects the levels of maternal IgG in nestlings. Furthermore, we investigated whether unmanipulated levels of maternal and self-produced antibodies are related to nestlings’ growth and survival rates and whether there is any relationship between the post-hatching levels of maternal antibodies and the levels of offspring's own antibody production.

Materials and methods

study area and field work

This study was made in the surroundings of Jyväskylä in central Finland (62° N 25° E). A supplemental feeding experiment was conducted in spring 2002. Data for studying immunity, growth and survival were collected in 2003 and 2004. Breeding habitat was classified either as urban (Jyväskylä city centre and/or immediate presence of highway) or rural (country side and suburban with only small roads, fields and forest present).

Egg laying started in the first half of April. The nests included in this study were visited every second day during the egg laying period in all 3 years (laying interval is on average 24 h). Thus, it was possible to observe the egg laying order (for most of the eggs the precise order and for some eggs in laying intervals between two successive eggs). Newly laid eggs were individually marked with a nontoxic text marker, weighed (accuracy 0·05 g), and their length and width was measured with a ruler (accuracy 0·01 mm). Clutch size varied from six to 11 eggs.

Hatching started c.15–17 days after the last egg was laid. When the hatching began, nests were visited every day, so that one was able to note the hatching order as precisely as possible, and verify from which egg each nestling originated. If any nestlings were preparing to hatch during the nest visit, food dye was gently injected through the crack in the egg shell to the beak of the nestling to mark the given chick with given colour. Marking allowed us to identify the marked nestlings and the numbered eggs, especially if several nestlings had hatched between the visits. In 2002 (supplementary feeding experiment) all hatchlings were assigned to their eggs (mean number of hatched eggs 6·1, varying from 3 to 8). However, in 2003 the assignment of the hatchlings was not equally successful due to the more synchronous and faster hatching rate of the majority of the nests. Hatching ranks instead could be determined very well in each year, even if we had to allow many ties (typically of two chicks). However, the exactness is more than sufficient for statistically effective analyses, as on average we had 3·9 distinct rank categories for 2002. There were eight and nine cases in 2002 and 2003, respectively, when more than two nestlings hatched at the same time and got the same hatching rank. For the data from year 2003 hatching order is a categorical 0–1 variable, where one (12 nests with only three to four nestlings, and one with five nestlings) or two (24 nests) last hatched nestlings are represented with number 1. All the other siblings are represented with number 0 (one nest had three last hatched nestlings in category 1; one nest with only two hatchlings had both of them in category 0, and one nest with only one hatchling was assigned to category 1 since the hatchling originated from last laid eggs). The year 2004 is not used in the analyses where hatching rank is needed. When more than one nestling had hatched between the visits, the hatching order could be estimated in most cases by looking at the appearance of the nestlings: they were very reddish right after hatching and had remains of the blood vessels and yolk sac membranes left in their belly. If the nestlings were already heavier than their egg weight, one could say that they were already more than a few hours old. Hatching of the whole nest took on average 3 days (varied from 1 to 5 days).

supplementary feeding experiment in 2002

In year 2002, extra food [five raw chicken eggs for each pair on every second day, corresponding to 70% of daily energy needs (calculated from Högstedt 1981), placed in dummy bird nests covered with hay] was given to 15 magpie pairs in their territories close (1–3 m) to their nest. Another 15 pairs without food supplementation served as controls. Both experimental and control nest were disturbed equally as control nests were also visited every second day to observe the phase of nest building and egg laying. Nests were randomly selected from our study population, and assigned to treatments (supplementation or control) equally through the season and the breeding habitat. Supplemental food was given before and during the whole egg laying period for an average of 19 days (range 16–23 days) from late March to late April 2002. The consumption of the chicken eggs was monitored during the nest visits and only the nests where parents used the supplemental food were included as experimental nests (at hatching we had 10 experimental and nine control nests, and at fledging seven and six, respectively). The range for clutch size was five to eight eggs for the supplemented group. Supplemental feeding started on average 10·1 (± SD 3·4) days before the first egg was laid. During egg laying, nests were visited, laying order recorded and eggs marked as described above. After incubation, hatching order was recorded as described in the previous paragraph. For the chick blood sampling and other methods, see a section below. This part of the experiment was conducted with permission from the Animal Care Committee of the University of Jyväskylä (permit no. 18/23·4·2002).

A set of nests was allocated to another experiment, in which all the eggs were removed and laboratory analyses conducted before incubation. These results indicated differences between the supplemented and control nests in several egg parameters (e.g. immunoglobulins and carotenoid levels), but not in clutch size or initiation of egg laying (Heli Siitari, Marjo Pihlaja, Rauno Alatalo, Jenny Hämäläinen, Ton Groothuis, Jonathan Blount and Peter Surai unpublished data 2006). Thus, we can be confident that egg quality was affected by supplementary feeding.

maternal immunoglobulins and development of offspring immunity

In 2003, 40 nests were followed in our study population. In addition, there are data from 49 nests in 2004. These two data sets have been analysed separately, since in 2004 nestlings were challenged at the age of 6 days with phytohaemagglutinin to measure their cell-mediated immune response (data not shown here). It might have also affected circulating antibody levels (on day 10) of the nestlings. However, when analysing the relationship between immunoglobulins after hatching and the survival, years 2003 and 2004 are combined (effect of year was not quite significant for survival: P = 0·073; in any case there was no effect on significances of other variables if year is included in the model). The data from year 2002 are not used with data from 2003 or 2004. In 2003 also the first and the last egg were taken for other study purposes from 17 of 40 nests. In this case, clutch size manipulation did not affect any of the nestling parameters we used in this study compared with unmanipulated nests (Jonna Timonen, Marjo Pihlaja and Heli Siitari unpublished data 2006), so the data from the artificially reduced clutches were pooled with the data from the unmanipulated clutches.

blood sampling, growth of nestlings after hatching, and sex determination

Blood samples were taken twice during the nestling period in the years 2002 and 2003, and three times in 2004. First blood sample (maximum 2 × 15 µL) was drawn from brachial vein at hatching (mostly within 0–24 h, only in eight cases in 2003 and three cases in 2004 later). There was no change in immunoglobulins during the days of the first sampling (hierarchical linear regression P = 0·563). Second blood sample was taken when the oldest nestling within the nest was 10 days old (maximum 2 × 75 µL haematocrit capillaries from the brachial vein). In 2004, the third blood sample was taken just before fledging (on day 20) (maximum 2 × 75 µL haematocrit capillaries). Plasma was separated in the laboratory by centrifuging (13 684 g, 5 min), and stored at −20 °C for the immunoglobulin analysis (see below).

The nestlings were weighed with a Pesola spring balance (accuracy 0·1 g) for five times during their nestling period in all 3 years. They were first weighed at hatching (usually within 24 h), then consequently when the oldest nestling of the nest was 6, 10, 16 and 20 days old. During each visit the survival of each nestling was recorded. Only a few nests became predated during the nestling period (five nests in 2003 and four nests in 2004). Predated nests were not included in the survival analysis. Fledging age of the magpie nestlings is approximately 27 days (Birkhead 1991), but in this study population it has varied from 20 to 28 days. This part of the study was conducted with permission from the Animal Care Committee of the University of Jyväskylä (permits no. 1/28·1·2003 and 6/26·1·2004) and the Finnish Ministry of Agriculture and Forestry (permit no. 1604/722/2003).

Sex of the nestlings was determined using a method described in Griffiths et al. (1998). A small drop of blood was used for the Chelex® resin-based DNA extraction (Walsh, Metzger & Higuchi 1991). Two microlitres of the resulting DNA solution was used in a polymerase chain reaction (PCR) to amplify a part of the CHD-W gene in females and the CHD-Z gene in both sexes (for details see Griffiths et al. 1998).

immunoglobulin analyses

Antibodies in the blood of 1-day-old nestlings are considered to be of maternal origin (e.g. Apanius 1998; Klasing & Leshchinsky 1998). The most important type of maternally transmitted immunoglobulin in birds is immunoglobulin Y (IgY), often referred to as IgG. IgY is an ancient form of IgG, which is the main form in mammals. In this paper we will use the term ‘IgG’ instead of ‘IgY’, as it has become common practice in avian studies. In the avian egg, maternal IgG is located in the yolk (Klasing & Leshchinsky 1998). First, when the nestlings start to produce immunoglobulins, they are producing immunoglobulin type M (Frank 2002). IgM is a naïve antibody, which is then transformed to a more specific antibody IgG (Frank 2002). We can be sure that the antibodies we are measuring from the nestling's plasma after hatching is only maternal origin as there was practically no IgM present (see below).

Immunoglobulin concentrations in the plasma of each hatchling (day 0 and day 10 for all the years, additionally day 20 for the year 2004) were determined with the ELISA method. Briefly, 96-well microplates (Immuno Plate Maxisorp, Nunc Co., Nunc A/S, Roskilde, Denmark) were first coated overnight at +4° with commercial antichicken IgG antibody (10 µg mL−1, C-6409, Sigma Chemical Co., St. Louis, MO, USA). After emptying, the wells were saturated for 1 h with 1% bovine serum albumin (BSA, Roche Diagnostics GmbH, Manheim, Germany) prepared in phosphate-buffered saline (PBS, pH 7·4), and then washed three times with PBS-Tween 20 (0·25%). Samples were diluted with 1% BSA/PBS and each sample incubated in duplicates (50 µL per well) for 3 h at room temperature. Day 0 samples had dilution of 1 : 1000, day 10 samples was diluted 1 : 10 000 and day 20 samples 1 : 20 000 and 1 : 40 000. Pooled plasma samples from nestlings sampled on day 10 in 2002 and 2003, in respective assays, served as calibrators. Pooled plasma sample from 2003 was used as standard for 2004 analyses. Serial dilution of pooled samples was prepared for generating the standard curve, and immunoglobulin levels of samples are presented relative to this standard; arbitrary value of 10 equals the mean level of individuals used for the pooled sample. After washing, alkaline phosphatase conjugated antichicken IgG antibody (A-9171, Sigma Chemical Co.) was added and the plates were incubated overnight at +4 °C (dilution of 1 : 20 000). Finally after last washing, p-nitrophenyl phosphate (1 mg mL−1, Sigma 104 Phosphatase Substrate) in a diethanol amine buffer (1 mol L−1, pH 9·8) was applied. The optical density was read at 405 nm with a plate reader (Multiskan Ascent, Therma Oy, Finland).

A subset of plasma samples (sampled at hatching and on days 10 and 20) was used to test commercial antichicken IgG antibody binding properties for our species. Western blotting and immunostaining with the antibody showed that commercial antichicken IgG antibody recognized both the IgG and IgM isotypes of magpie plasma (Ilmari Jokinen and Heli Siitari, unpublished data). Immunoglobulins in magpie plasma at hatching consisted of the IgG isotype, and no measurable amount of IgM isotype was found. This was the case also for a subsample of sampled unincubated egg yolks; no measurable amount of IgM was found (Ilmari Jokinen and Heli Siitari, unpublished data). However, plasma collected on days 10 and 20 contained both types IgG and IgM. Owing to the specific characteristics of anti-immunoglobulin antibodies, determining relative concentrations of different isotypes was not possible, and therefore the results are presented as total immunoglobulin concentration.

data analysis

Data from different years (2002–04) have been analysed separately (except nestling survival analysis for effects of maternal immunoglobulins from 2003 and 2004), because of the different nature of data sets (experimental, unmanipulated and phytohaemagglutinin-challenged nests). Offspring body mass and immunoglobulin data were normalized with ln transformations. Because all measurements were made according to the age of the oldest nestling (except the first measurements after hatching, on day 0), the data were corrected with the true age of each nestling. The correction was made with the help of standardized residuals from linear regression against the true age for each of the sampling times (e.g. sampling time ‘day 10’ true age may vary between 6 and 10 days depending on the level of the hatching asynchrony).

Relative growth (change in mass relative to growth rate in the given population) until the middle of the nestling period (day 10) and until fledging (day 20) was calculated as a difference between the residuals from weight data at hatching and residuals from weight data of days 10 and 20, respectively. In other words, because of the hatching asynchrony growing time was different for individuals depending on hatching rank. Thus, relative growth until day 10 is the weight on day 10 (corrected with true age of the nestling) minus weight at hatching (day 0, corrected with true age). Consequently, relative growth until day 20 is the weight on day 20 (corrected with true age) minus weight at hatching (day 0, corrected with true age). Thus, positive values in growth rate indicate faster-than-average growth among the nestlings, whereas negative values indicate relatively slow growth.

The changes in immunoglobulin values at the population level from (maternal) levels at hatching to levels at day 20 were analysed with linear and quadratic regression for nest means. These analyses were conducted with SPSS program (version 11·5). All the other analyses were made with a hierarchical multivariate linear and binary logistic regression models (Goldstein 2003) with program mlwin 1·10, because our data have two levels: within the nest (between siblings) and between nests levels. The hierarchical level in the analyses (and tables) is within, between or within and between nests (the category ‘level’ in tables). In addition, if there were significant differences between breeding habitats, it was included as a random factor (the third level in hierarchy).

Our interest was particularly in the within-nest effects, because the nest is the environment where nestlings are competing with their siblings before fledging, and between-nest values are highly variable. Within-nest effects and between-nest effects were analysed separately if the effect was opposite between these two levels (e.g. positive relation between nests and negative within nest). In that case both levels had to be included in the model even if the effect was not significant on the other level. If the covariance of the intercept and slope between nests for a particular term was significant, the covariance was included in the model. The covariance between intercept and slope can increase variance component ostensibly. Thus, comparison of variance between null model and final model cannot be fully done in those cases. In the MLwiN, program the RIGLS option was used in estimation, because it is suited to small data sets. Five different models were constructed. In the first two models the effect of food supplementation on maternal and self-produced immunoglobulin values was analysed. Hatching order was used instead of laying order, because hatching order was also used in the other models. Correlation between the laying and hatching order is highly significant (Spearman r = 0·703, n = 98, P < 0·001). In the third model, the amount of maternal IgG (on day 0) was used as a dependent factor. In the fourth model, the amount of self-produced immunoglobulins (day 10) was used as a dependent factor. All independent terms are presented in Tables 1–3. The fifth model was a binary logistic model for the survival until day 20 with two hierarchical levels. Univariate analyses were first made for all terms. The terms that were significant (P < 0·05) in the univariate models were then included in the final multivariate model and P-values were calculated from the full model. In addition, multivariate models with other close-to-significant terms were computed, but none of these increased the model accuracy significantly. Null model and final model deviances, chi-distribution, P-values and estimates for all analysed terms are represented in Tables 1–3.

Table 1.  Feeding experiment (year 2002): immunoglobulin G at hatching. Hierarchical linear regression model of the effects of the feeding experiment (1 = fed, 0 = control) and hatching order on maternal IgG values as measured in the plasma of the chicks after hatching. Values of the rejected parameters are from univariate models. The final model includes the terms that were significant in univariate analysis. The analyses were undertaken within nests (within), between nests (between) and both within and between nests
 Deviance/χ2d.f.PVariance/estimate (error)Level
  1. N(nests) = 13, N(chicks) = 55.

Null model −3·64155   
 Between nests σ2    0·020 (0·012) 
 Within nests σ2    0·044 (0·010) 
Final model−19·91252   
 Between nests σ2    0·003 (0·005) 
 Within nests σ2    0·040 (0·009) 
Constant   10·472 (0·111) 
Experiment 14·8141< 0·001 0·247 (0·064)Between
Hatching order  5·33310·021 0·040 (0·017)Within, between
Rejected terms
 Hatching order × experiment  0·39310·530−0·023 (0·037)Within, between
 Egg weight  1·06710·302 0·046 (0·045)Within, between
 Sex (female = 1, male = 0)  0·19610·658−0·027 (0·060)Within, between
 Weight after hatching (ln)  0·25810·612 0·110 (0·216)Within, between
 Mean weight after hatching  0·18710·665 0·169 (0·392)Between
Table 2.  Immunoglobulin G at hatching (year 2003). Hierarchical linear regression model of the relationship of position (1 = last chicks, 0 = others) and the weight after hatching with maternal IgG values as measured in the plasma of the chicks after hatching. Values of the rejected parameters are from univariate models. Those terms that were significant in univariate models were included in the final model. In this final model breeding habitat is the third level in the hierarchy in addition to nest and nestling levels
 Deviance/χ2d.f.PVariance/estimate (error)Level
  1. N(nests) = 40, N(chicks) = 171.

Null model53·745171   
 Between breeding habitats σ2    0·014 (0·017) 
 Between nests σ2    0·029 (0·010) 
 Within nests σ2    0·061 (0·008) 
Final model49·230169   
 Between breeding habitats σ2    0·014 (0·017) 
 Between nests σ2    0·028 (0·010) 
 Within nests σ2    0·060 (0·007) 
Constant   −0·478 (0·093) 
Position4·56410·033 0·088 (0·041)Within, between
 Rejected terms
 Weight after hatching  (age corrected residuals)0·45310·501−0·091 (0·136)Within
 Mean weight after hatching0·26310·608 0·155 (0·301)Between
 Clutch size (no of eggs)0·18310·669 0·013 (0·030)Between
 Sex (female = 1, male = 0)1·32210·250 0·048 (0·042)Within, between
 Mean hatching date0·78510·376 0·005 (0·006)Between
 Growth until day 101·23510·266 0·038 (0·034)Within
 Mean growth until day 102·10010·147−0·075 (0·049)Between
Table 3.  Immunoglobulin levels on day 10 (year 2003). Hierarchical linear regression model of the effect of maternal IgG (in chick plasma after hatching), sex (female = 1, male = 0) and growth (in weight) (from hatching until day 10) on immunoglobulin values in the chicks’ plasma on day 10. Values of the rejected parameters are from univariate models. The final model includes the terms that were significant in univariate analysis. Growth in the final model was standardized against weight on day 10, because these terms were not independent of each other. Growth (in weight) until day 20 was not included in the final model, because the number of cases was highly reduced due to mortality at that point compared with day 10
 Deviance/χ2d.f.PVariance/estimate (error)Level
  1. N(nests) = 36, N(chicks) = 112.

Null model266·013112   
 Between nests σ2   0·186 (0·081) 
 Within nests σ2   0·464 (0·070) 
Final model239·457108   
 Between nests σ2   0·177 (0·075) 
 Within nests σ2   0·376 (0·060) 
Constant   0·246 (0·138) 
Maternal IgG (ln transformed)13·9941< 0·0010·808 (0·216)Within, between
Weight on day 10 4·81610·0280·181 (0·082)Within, between
Mass independent growth until day 1011·98410·001−0·265 (0·077)Within, between
Significant, but not in the final model
Growth until day 207·21310·007−0·168 (0·062)Within, between
Rejected terms
 Sex (female = 1, male = 0)2·27610·1310·209 (0·138)Within, between
 Hatching order1·46510·2260·182 (0·151)Within, between
 (last = 1, others = 0)
 Mean hatching date0·89110·3450·016 (0·017)Between
 Mean maternal IgG (ln)0·21210·6450·246 (0·533)Between
 Weight after hatching (ln)3·24710·0700·552 (0·305)Within, between
 Sex × weight day 101·26410·2610·187 (0·166)Within, between
 Sex × growth until day 101·99710·158−0·174 (0·123)Within, between
 Sex × growth until day 200·69510·404−0·088 (0·106)Within, between
 Survived until day 20  (1 = alive, 0 = did not survive)0·72810·3940·189 (0·222)Within, between
 Hatching order × survived until day 200·16310·6860·172 (0·427)Within, between


supplementary feeding experiment

The mean clutch size (± SD) for the supplemented group was 7·40 (0·97) eggs, and for controls 7·56 (0·88) eggs. Feeding treatment did not affect the clutch size (Mann–Whitney U-test: N(fed) = 10, N(control) = 9, U = 43·5, P = 0·905) or initiation of egg laying [in April days; fed (mean (± SD): 20·20 (3·80), control: 19·50 (4·65), Mann–Whitney U-test: N(fed) = 9, N(control) = 7, U = 44·5, P = 0·687]. Neither was the egg weight [mean (± SD); fed: 10·75 (1·04) g, control: 9·99 (1·08) g, independent samples t-test, t = 1·56, N(fed)= 10, N(control) = 9, P = 0·136] nor number of hatched young [mean (± SD); fed: 5·2 (2·5), control: 5·0 (2·9), independent samples t-test, t = 0·163, N(fed) = 10, N(control)= 9, P = 0·873] affected by the feeding treatment.

Nestlings of supplementary fed mothers had significantly higher plasma immunoglobulin levels at hatching than the nestlings of the control treatment (Table 1, Fig. 1). There was a significant increase in maternal IgG (day 0) values with the hatching order in both treatments (Table 1, Fig. 1). However, there was no effect of treatment or hatching order on immunoglobulin levels after first 10 days (P-values were 0·783–0·950).

Figure 1.

Effects of supplementary feeding of mothers and hatching order on immunoglobulin G levels in chick plasma at hatching (year 2002). Open symbols (grey line) refer to the offspring of supplementary fed parents and black symbols (black line) to the controls. Immunoglobulin values are presented relative to the plasma pool of 10-day-old magpie nestlings (2002).

development of adaptive immunity

The increase in immunoglobulin levels over the nestling period was described by quadratic regression (d.f. = 1113, F = 1482·44, R2 = 96·3%, P < 0·001, for linear regression R2 = 88·9%). At the age of 8–10 days (true age), immunoglobulin levels were on average 30 times higher than at hatching (Fig. 2).

Figure 2.

Immunoglobulin levels during the nestling period in 2004. Immunoglobulin values are presented relative to the standard (see methods), and the scale is logarithmic. The grey line represents linear regression and the black line quadratic regression. Circles show the values for nest means.

maternal immunoglobulins

There was a significant relationship between hatching rank and maternal immunoglobulins measured from nestling's plasma at hatching (Table 2). The later hatched nestlings had higher immunoglobulin levels compared with older siblings.

Nestlings with higher levels of maternal immunoglobulins survived better until day 20 in the within-nest comparison (estimate = 2·755, error = 0·987, χ2 = 7·783, d.f. = 1, P = 0·005). However, between nests it was the opposite: nests with higher levels of maternal immunoglobulins had lower survival compared with nests with lower maternal immunoglobulin levels (estimate =−2·586, error = 1·217, χ2 = 4·520, d.f. = 1, P = 0·033). Effects of hatching weight (positive effect: P < 0·001) and hatching order (negative effect: P < 0·001) on survival were controlled in the model (whole model: χ2 = 39·841, d.f. = 4, P < 0·001).

No relationship between clutch sizes, nestling sex, hatching weight, hatching date or growth with IgG values after hatching was detected.

immunoglobulins on day 10 after hatching

There was a significant, positive relationship between the maternal (day 0) immunoglobulins and nestlings’ own production (day 10) at the within-nest level, but no significant relationship for the means of the nests (Table 3, Fig. 3). There was a significant, negative relationship between growth until day 10 and immunoglobulin levels measured on day 10 (Table 3). Growth until day 20 also had a significant, negative relationship with immunoglobulin production both between and within nests (Table 3). However, weight on day 10 had a significant, positive relationship with immunoglobulin levels on day 10.

Figure 3.

Relationship between immunoglobulin levels at hatching and on day 10 (2003). For the scale, see Fig. 2. Day 10 immunoglobulin levels are age corrected standardized residuals (true age is 6–10 days) from ln transformed immunoglobulin concentrations (U mL−1).

There was no significant effect of habitat, hatching order, age difference, hatching date or other factors shown in Table 3, on nestling immunoglobulin levels on day 10. Neither was there any difference between nestlings that survived until day 20 and those that died before day 20 in terms of IgG values on day 10 (Table 3).


Our aim was to investigate whether resource limitation before and during egg laying affects the levels of maternal IgG in nestlings, whether unmanipulated levels of maternal and self-produced antibodies have an effect on nestlings’ growth and survival rates and whether there is any relationship between the post-hatching levels of maternal antibodies and the levels of offspring's own antibody production. In our supplementary feeding experiment immunoglobulin levels of offspring at hatching were dependent on a mother's nutritional condition. Immunoglobulin levels of the offspring at hatching were positively related to their immunoglobulin levels on day 10. We found a negative relationship between self-produced immunoglobulins and growth over the first 10 days, but a positive relationship between weight on day 10 and self-produced immunoglobulin. We found that within nests nestlings with higher maternal antibody levels had higher survival rate until day 20, but between nests there was an opposite relationship.

Our experiment indicated that a mother's condition, as affected by supplementary food during the egg laying, significantly affected the amount of maternal immunoglobulins transferred to her offspring. The result is in contrast to what Blount et al. (2002) found in lesser black-backed gulls Larus fuscus: carotenoid-fed females produced eggs with lower immunoglobulin concentrations compared with controls. Additionally, Grindstaff et al. (2005) found that in Japanese quail manipulation of diet protein levels did not affect the amount of immunoglobulins in mothers nor in her eggs. The quail were fed ad libidum and only protein intake was manipulated. However, our studies are not completely comparable as, we fed parents with raw chicken eggs containing also other resources than carotenoids and proteins.

There was an increase in IgG levels with the hatching order in both the experimental and the control treatments at hatching. These facts indicate that there are two factors affecting the amount of IgG received from the mother: first, the mother's condition and, secondly, the mother's differential investment accords to the offspring's position within the clutch. Nestlings hatched from last laid eggs are possibly more dependent on maternal IgG, because of the sibling competition. Increased levels of testosterone in last laid eggs in magpies (Heli Siitari, Marjo Pihlaja, Rauno Alatalo, Jenny Hämäläinen, Ton Groothuis, Jonathan Blount and Peter Surai unpublished data 2006) may depress T-cell-mediated immunity (von Schantz et al. 1999) and the maternal IgG might compensate for the reduced cell-mediated immunity of the offspring, thus increasing their probability of survival.

In our study, magpie nestlings started to produce immunoglobulins relatively early in their nestling period. At the age of 10 days immunoglobulin levels in the plasma are c.30 times higher than at hatching, and just before fledging immunoglobulin levels are approximately 80-fold. However, the development of adaptive immunity in altricial passerines is poorly studied so far, and early initiation of nestling antibody production might not be very rare phenomenon among passerines. We were not able to distinguish between immunoglobulin subtypes G and M. IgG is more efficient in binding specific antigens than IgM, which on the other hand binds wider repertoire of antigens (Frank 2002). IgG is formed from IgM (naïve antibody) and it is possible that a large amount of the immunoglobulins measured on day 10 were still naïve antibodies.

In contrast to studies that suggest that maternal antibody transmission in large amounts might hamper the development of the offspring's own immunity (see, e.g. review of Grindstaff et al. 2003), we found that the more antibodies nestlings receive from their mother, the more immunoglobulins they will have after they have started their own antibody production. Thus, in this natural population there seems to be no need for downward regulation of maternal antibody transmission to avoid harmful suppression of the development of the offspring's adaptive immunity. However, we measured total antibody levels and we did not analyse how many different idiotypes there are in relation to total antibody levels. Thus we cannot say if a large amount of specific antibody idiotype would have the same relationship. Our result is in line with studies suggesting that reduced maternal antibody transmission leads to reduced offspring immune responsiveness (chicken: Yasuda et al. 1998; mouse: Malanchere et al. 1997). In mice maternally inherited antibodies may influence an offspring's antibody production throughout their lifetime (Lemke, Hansen & Lange 2003) and it may even include trans-generation effects (Lemke & Lange 1999; in rats: Lundin et al. 1999). As the pathogen populations may vary spatially and temporarily, there might be differences between local breeding areas in the amount and quality of pathogens that breeding pairs and their nestlings are exposed to. Thus, it is reasonable that a mother prepares her nestlings for the current pathogen environment and the nestlings will response to that when their own antibody production starts. As we found that immunoglobulin production is resource limited, both mothers and nestlings should respond to possible pathogen challenges only with the effort that is optimal in a given time. As we did not sample the eggs (they were let to be incubated), or the mothers, we cannot compare levels of immunoglobulin between mothers, eggs and offspring. However, in the study by Grindstaff et al. (2005), immunoglobulin levels in the females and in their eggs were positively correlated. Additionally, the adults in our population were very sensitive for trapping and the disturbance of the parents at the time of breeding was very risky, causing desertion of nests.

Within broods maternal IgG levels were positively related to survival after the effects of hatching weight and hatching order were controlled. Thus, the mother may influence her nestlings’ survival probability by differential deposition of antibodies within her clutch. The opposite relationship between nests may be explained for example by differential infection rates between nests (e.g. local epidemics, which might lower the survival of the whole nests).

Nestlings that were heavier on day 10 after hatching produced relatively more immunoglobulins than lighter nestlings. On the other hand, our study also indicates that immunoglobulin production is costly: there was a trade-off between growth until day 10 and immunoglobulin production. A similar trade-off had previously been noted in magpie nestlings between experimentally enhanced T-cell-mediated immunity and growth by Soler et al. (2003) and in a study in blue tits Parus caeruleus (Brommer 2004).

It is not necessarily costly to grow larger in size, but to do so quickly (catch-up growth) might be (Metcalfe & Monaghan 2001, 2003). Nestlings that had a low hatching weight, but grew larger than expected by their original rank after hatching, could produce less immunoglobulins than the average by the middle of the nestling period. Kilpimaa, Alatalo & Siitari (2004) suggested that the trade-off between sexual advertisement and immune responsiveness might be working in both directions. Likewise, the situation is complex between the growth and development of the adaptive immunity during the nestling period, depending on the current needs – to grow or to defend? When high responsiveness is needed, nestlings must give up or reduce investment in growth. On the other hand, if they have to catch up in size, e.g. with their older siblings, to survive, they may have to give up investment in immunity.

In conclusion, our study suggests that maternal antibodies transferred to the eggs can have substantial effects on offspring immunity and affect their survival during the nestling period. In addition, the levels of maternal antibodies received by the nestlings were dependent on both food quantity during egg laying and the differential investment of the mother within the clutch. Moreover, the antibody production of the offspring can compete with the resources needed for growth.


We thank Jenny Hämäläinen, Laura Häsä, Christophe Lebigre, Sanna Leppänen, Eeli Mykkänen, Tuomo Pihlaja and Jonna Timonen for help in the field. We are also grateful to Dr Ilmari Jokinen for his expertise and guidance in immunology and Msc Elina Virtanen, Jenny Hämäläinen, Sanna Leppänen and two trainees for their help in the laboratory. We are very grateful to Dr Antero Malin from the Institute of Educational Research for his help with the MLwiN. We thank also Maxine Iversen, Carita Lindstedt, Johanna Mappes, Tuula Oksanen, Jarkko Routtu and anonymous reviewers who gave valuable comments on this work. We were funded by the Academy of Finland (project 202841 to R.V.A. and project 201963 and 106408 to H.S.) and Jenny and Wihuri Foundation (to M.P.).