Modelling the effects of environmental and individual variability when measuring the costs of first reproduction

How do animals balance their investment in young against their own chances to survive and reproduce in the future? This life–history trade–off, referred to as the cost of reproduction (Williams, 1966), holds a central place in life–history theory (Roff, 1992; Stearns, 1992; McNamara & Houston, 1996). Because individuals can only acquire a limited amount of energy, reproduction and survival as well as current and future reproduction are considered as functions competing for the same resources. In this framework, individuals may optimise life–history decisions. If the reproductive effort in one year leads to a loss in future reproductive output through decreased adult survival or reduced fecundity, then the optimal effort in the current season is less than the effort that would maximize the number of offspring produced in that season (Charnov & Krebs, 1974). There are at least two kinds of factors likely to confound the measurement of the costs of reproduction in the wild. First, there could be differences in the amount of energy individuals acquire and allocate to various functions. This phenotypic heterogeneity can mask or exacerbate individual allocation patterns when trends are averaged across a population (Vaupel & Yashin, 1985; McDonald et al., 1996; Cam & Monnat, 2000). Second, there could be variations in resource availability affecting energy acquisition and allocation. Theoretical models examining the optimal phenotypic balance between reproduction and survival under variable breeding conditions have investigated the influence of environmental stochasticity on the cost of reproduction in birds (Erikstad et al., 1998; Orzack & Tuljapurkar, 2001). However, there is little empirical evidence supporting these theoretical models. Here, we present analysis of the influence of experience, but also of the differential effects of environmental and individual variation on survival and future breeding probability. We address the question of the costs of reproduction using data from a 17–year study of individually marked blue petrels (Halobaena caerulea), a small (190 g) long–lived seabird breeding on sub–Antarctic islands. Data were analysed using multistate capture–recapture models (Brownie et al., 1993; Schwarz et al., 1993; Nichols et al., 1994). The most general model we started with was the conditional Arnason–Schwarz model (Schwarz et al., 1993). We used the following notation for states: 1. Nonbreeder that never previously bred; 2. First–time breeder; 3. Experienced breeder; and 4. Nonbreeder that previously bred. This general model was constrained since some parameters were not defined, given our definition of individual states. Using matrix notation, the parameters defined above can be summarized in matrices of survival, transition and capture probabilities: We examined the effect of two covariates that were suspected to affect survival and breeding probabilities: sea surface height representing oceanographic conditions at a regional scale, and body mass of birds during breeding. Covariates were tested through ultrastructural models in which survival probability is a function of sea surface height and/or body mass, following a linear–logistic function: where is the intercept parameter, and is a slope parameters. Our selection of models for estimation was based on model goodness–of–fit (GOF) tests and a modified Akaike’s Information Criterion that takes into account sample sizes (AICc; see Akaike, 1973; Lebreton et al., 1992; Burnham & Anderson, 2002). We used program U–CARE (Choquet et al., 2003a) for GOF testing, and M–SURGE (Choquet et al., 2003b) for model selection and parameter estimation. The GOF test of our general model indicated a lack of fit and we used a variance inflation factor ( = 1.336) in the remaining analysis. Recapture probabilities varied with state. Recapture probability for breeders was extremely close to one. Experienced nonbreeders had higher recapture probabilities (0.528 ± 0.033) than inexperienced breeders (0.364 ± 0.019). First–time breeders had the lowest mean survival probabilities (0.775 ± 0.035), and experienced breeders had the highest mean survival probabilities (0.882 ± 0.035). Inexperienced and experienced nonbreeders had intermediate mean survival probabilities, indicating a cost of first reproduction for first time breeders. First–time breeders had a lower probability of breeding in the following year than experienced breeders, and nonbreeders had a lower probability of breeding in the following year than breeders. Among nonbreeders, inexperienced nonbreeders had a lower probability of breeding in the following year than experienced nonbreeders. A model where state survival probabilities were a function of sea surface height had the lowest QAICc. Survival of inexperienced individuals (both breeders and nonbreeders) was negatively affected by poor oceanographic conditions, whereas experienced birds seem to be only weakly affected by similar conditions. The costs of reproduction for first–time breeders were particularly marked during harsh climatic conditions. Body condition of experienced breeders was higher than the body condition of first–time and nonbreeders. Body condition of individuals seen only once was lower than body condition of those seen at least twice. At the individual level, there was no clear evidence for an increase in body condition across years. These results can be interpreted in the light of the selection hypothesis (Curio, 1983; Forslund & Pärt, 1995). The inferiority of inexperienced breeders may be linked to a higher proportion of lower–quality individuals in younger age classes. First reproduction may act as a filter selecting individuals of higher quality/body mass. The improvement of performance within individuals may contribute marginally to the observed patterns at the population level. Environmental stochasticity, and more particularly the variation in sea surface height reflecting resource availability is probably a major factor of selection.We examined the effect of two covariates that ere suspected to affect survival and breeding probabilities: sea surface height representing oceanographic conditions at a regional scale, and body mass of birds during breeding. Covariates were tested through ultrastructural models in which survival probability is a function of sea surface height and/or body mass, following a linear–logistic function: where is the intercept parameter, and is a slope parameters. Our selection of models for estimation was based on model goodness–of–fit (GOF) tests and a modified Akaike’s Information Criterion that takes into account sample sizes (AICc; see Akaike, 1973; Lebreton et al., 1992; Burnham & Anderson, 2002). We used program U–CARE (Choquet et al., 2003a) for GOF testing, and M–SURGE (Choquet et al., 2003b) for model selection and parameter estimation. The GOF test of our general model indicated a lack of fit and we used a variance inflation factor ( = 1.336) in the remaining analysis. Recapture probabilities varied with state. Recapture probability for breeders was extremely close to one. Experienced nonbreeders had higher recapture probabilities (0.528 ± 0.033) than inexperienced breeders (0.364 ± 0.019). First–time breeders had the lowest mean survival probabilities (0.775 ± 0.035), and experienced breeders had the highest mean survival probabilities (0.882 ± 0.035). Inexperienced and experienced nonbreeders had intermediate mean survival probabilities, indicating a cost of first reproduction for first time breeders. First–time breeders had a lower probability of breeding in the following year than experienced breeders, and nonbreeders had a lower probability of breeding in the following year than breeders. Among nonbreeders, inexperienced nonbreeders had a lower probability of breeding in the following year than experienced nonbreeders. A model where state survival probabilities were a function of sea surface height had the lowest QAICc. Survival of inexperienced individuals (both breeders and nonbreeders) was negatively affected by poor oceanographic conditions, whereas experienced birds seem to be only weakly affected by similar conditions. The costs of reproduction for first–time breeders were particularly marked during harsh climatic conditions. Body condition of experienced breeders was higher than the body condition of first–time and nonbreeders. Body condition of individuals seen only once was lower than body condition of those seen at least twice. At the individual level, there was no clear evidence for an increase in body condition across years. These results can be interpreted in the light of the selection hypothesis (Curio, 1983; Forslund & Pärt, 1995). The inferiority of inexperienced breeders may be linked to a higher proportion of lower–quality individuals in younger age classes. First reproduction may act as a filter selecting individuals of higher quality/body mass. The improvement of performance within individuals may contribute marginally to the observed patterns at the population level. Environmental stochasticity, and more particularly the variation in sea surface height reflecting resource availability is probably a major factor of selection. We examined the effect of two covariates that were suspected to affect survival and breeding probabilities: sea surface height representing oceanographic conditions at a regional scale, and body mass of birds during breeding. Covariates were tested through ultrastructural models in which survival probability is a function of sea surface height and/or body mass, following a linear–logistic function: where is the intercept parameter, and is a slope parameters. Our selection of models for estimation was based on model goodness–of–fit (GOF) tests and a modified Akaike’s Information Criterion that takes into account sample sizes (AICc; see Akaike, 1973; Lebreton et al., 1992; Burnham & Anderson, 2002). We used program U–CARE (Choquet et al., 2003a) for GOF testing, and M–SURGE (Choquet et al., 2003b) for model selection and parameter estimation. The GOF test of our general model indicated a lack of fit and we used a variance inflation factor ( = 1.336) in the remaining analysis. Recapture probabilities varied with state. Recapture probability for breeders was extremely close to one. Experienced nonbreeders had higher recapture probabilities (0.528 ± 0.033) than inexperienced breeders (0.364 ± 0.019). First–time breeders had the lowest mean survival probabilities (0.775 ± 0.035), and experienced breeders had the highest mean survival probabilities (0.882 ± 0.035). Inexperienced and experienced nonbreeders had intermediate mean survival probabilities, indicating a cost of first reproduction for first time breeders. First–time breeders had a lower probability of breeding in the following year than experienced breeders, and nonbreeders had a lower probability of breeding in the following year than breeders. Among nonbreeders, inexperienced nonbreeders had a lower probability of breeding in the following year than experienced nonbreeders. A model where state survival probabilities were a function of sea surface height had the lowest QAICc. Survival of inexperienced individuals (both breeders and nonbreeders) was negatively affected by poor oceanographic conditions, whereas experienced birds seem to be only weakly affected by similar conditions. The costs of reproduction for first–time breeders were particularly marked during harsh climatic conditions. Body condition of experienced breeders was higher than the body condition of first–time and nonbreeders. Body condition of individuals seen only once was lower than body condition of those seen at least twice. At the individual level, there was no clear evidence for an increase in body condition across years. These results can be interpreted in the light of the selection hypothesis (Curio, 1983; Forslund & Pärt, 1995). The inferiority of inexperienced breeders may be linked to a higher proportion of lower–quality individuals in younger age classes. First reproduction may act as a filter selecting individuals of higher quality/body mass. The improvement of performance within individuals may contribute marginally to the observed patterns at the population level. Environmental stochasticity, and more particularly the variation in sea surface height reflecting resource availability is probably a major factor of selection

Semiparametric Regression in Capture-Recapture Modelling

Capture-recapture models were developed to estimate survival using data arising from marking and monitoring wild animals over time. Variation in the survival process may be explained by incorporating relevant covariates. We develop nonparametric and semiparametric regression models for estimating survival in capture-recapture models. A fully Bayesian approach using MCMC simulations was employed to estimate the model parameters. The work is illustrated by a study of Snow petrels, in which survival probabilities are expressed as nonlinear functions of a climate covariate, using data from a 40-year study on marked individuals, nesting at Petrels Island, Terre Adelie

¿Afecta la calidad del hábitat alimentario a la capacidad reproductiva de la garceta común, Egretta garzetta?

In order to understand the role of foraging habitat quality on fecundity parameters we measured habitat use, breeding parameters, and body condition of chicks in six colonies of Little Egrets in southern France. The foraging habitat available differed between colonies; it was mainly natural marshes around the Carrelet colony, agricultural lands (rice fields and dry crops) around the Agon colony, a mix of agricultural and natural lands around the Redon and Fiélouse colonies, a mix of natural and urbanised/industrial lands around the Palissade colony, and mainly cultivated and urbanised lands around the Chaumont colony. The habitat attractiveness to adult Little Egret breeding was higher for natural marshes than for other habitat types. Agricultural marshes (rice fields) came next. Other human–made habitats came last. Clutch size and body condition index of chicks did not differ between colonies. Brood size was influenced by both the association of the proportion of natural marshes in the foraging area and clutch size, and the association of clutch size and the total number of heron pairs in the colony. The effect of the proportion of natural marshes could not be distinguished from the effects of the colony size. The potential influence of other parameters not taken into account in this study is discussed.Con la finalidad de conocer el papel que ejerce la calidad del hábitat alimentario sobre los parámetros de fecundidad, se evaluaron el uso del hábitat, los parámetros reproductivos y las condiciones físicas de los polluelos de seis colonias de garceta común en el sur de Francia. El hábitat alimentario disponible variaba de unas colonias a otras, siendo principalmente marismas naturales en el entorno de la colonia de Carrelet, terrenos agrícolas (campos de arroz y cultivos de secano) alrededor de la colonia de Agon, una combinación de terrenos agrícolas y naturales alrededor de las colonias de Redon y Fiélouse, una combinación de terrenos naturales y urbanizados/industriales alrededor de la colonia de Palissade, y principalmente terrenos cultivados y urbanizados alrededor de la colonia de Chaumont. En la época de reproducción, los adultos de garceta común se sienten atraídos principalmente por las marismas naturales, en detrimento de otros tipos de hábitat. Las tierras agrícolas anegadas (campos de arroz) siguen en orden de preferencia, mientras los hábitats construidos por el hombre ocupan el último lugar. El tamaño de la puesta y el índice de estado físico de los polluelos no mostraron diferencias entre las colonias. El tamaño de la nidada estuvo influenciado tanto por la asociación de la proporción de marismas naturales en el hábitat alimentario y el tamaño de la puesta, como por la asociación del tamaño de la puesta y el número total de parejas de garzas de la colonia. El efecto de la proporción de marismas naturales no se puede diferenciar del ejercido por el tamaño de la colonia. Se discute también la influencia potencial de otros parámetros que no se han tenido en cuenta en este estudio

Using self-organizing maps to investigate environmental factors regulating colony size and breeding success of the White Stork (Ciconia ciconia)

We studied variations in the size of breeding colonies and in breeding performance of White Storks Ciconia ciconia in 2006–2008 in north-east Algeria. Each colony site was characterized using 12 environmental variables describing the physical environment, land-cover categories, and human activities, and by three demographic parameters: the number of breeding pairs, the number of pairs with chicks, and the number of fledged chicks per pair. Generalized linear mixed models and the self-organizing map algorithm (SOM, neural network) were used to investigate effects of biotic, abiotic, and anthropogenic factors on demographic parameters and on their relationships. Numbers of breeding pairs and of pairs with chicks were affected by the same environmental factors, mainly anthropogenic, which differed from those affecting the number of fledged chicks per pair. Numbers of fledged chicks per pair was not affected by colony size or by the number of nests with chicks. The categorization of the environmental variables into natural and anthropogenic, in connection with demographic parameters, was relevant to detect factors explaining variation in colony size and breeding parameters. The SOM proved a relevant tool to help determine actual dynamics in White Stork colonies, and thus to support effective conservation decisions at a regional scale

Sexual Size Dimorphism and Body Condition in the Australasian Gannet

Funding: The research was financially supported by the Holsworth Wildlife Research Endowment. Acknowledgments We thank the Victorian Marine Science Consortium, Sea All Dolphin Swim, Parks Victoria, and the Point Danger Management Committee for logistical support. We are grateful for the assistance of the many field volunteers involved in the study.Peer reviewedPublisher PD