Maternal Effects in Relation to Helper Presence in the Cooperatively Breeding Sociable Weaver

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Study Justification:
– The study aims to investigate how the presence of helpers in cooperatively breeding species affects maternal allocation and offspring phenotypes.
– Previous studies have shown that females assisted by helpers produce smaller eggs, but it is unclear how common this effect is.
– It is also unknown whether females change egg composition when assisted by helpers, which is predicted by current maternal allocation theory but has not been previously investigated.
Study Highlights:
– The study was conducted on sociable weavers, a colonial passerine species endemic to southern Africa.
– The researchers collected data on egg mass, yolk carotenoid and hormonal contents, and fledgling mass.
– They found that egg mass decreased with group size, suggesting that helpers may compensate for the reduced investment in eggs.
– Females assisted by helpers produced eggs with lower hormonal content, specifically testosterone, androstenedione, and corticosterone levels.
– These results suggest that the environment created by helpers can influence maternal allocation and potentially offspring phenotypes.
Recommendations for Lay Reader:
– The presence of helpers in cooperatively breeding species can affect the size and composition of eggs.
– Females assisted by helpers produce smaller eggs, but the additional food brought by helpers compensates for this reduction.
– Females assisted by helpers also produce eggs with lower hormonal content.
– These findings suggest that the environment created by helpers can influence maternal allocation and offspring phenotypes.
Recommendations for Policy Maker:
– Consider the impact of helper presence on maternal allocation and offspring phenotypes in cooperatively breeding species.
– Support further research to understand the mechanisms behind the effects of helpers on egg size and composition.
– Explore the potential benefits and drawbacks of helper presence in conservation and management strategies for cooperatively breeding species.
Key Role Players:
– Researchers and scientists specializing in avian ecology and reproductive biology.
– Conservation organizations and wildlife management agencies.
– Policy makers and government officials responsible for biodiversity conservation.
Cost Items for Planning Recommendations:
– Research funding for fieldwork, data collection, and analysis.
– Equipment and supplies for capturing and marking birds, collecting and analyzing eggs, and conducting observations.
– Personnel costs for researchers, field assistants, and data analysts.
– Travel and accommodation expenses for fieldwork.
– Publication and dissemination costs for sharing research findings with the scientific community and the public.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is fairly strong, but there are some areas for improvement. The study was conducted with the permission of Northern Cape Nature Conservation and approved by the Ethics Committee of the University of Cape Town, which adds credibility to the research. The study also provides detailed methods and statistical analyses. However, the sample size is relatively small, which may limit the statistical power of the results. To improve the evidence, the researchers could consider increasing the sample size to strengthen the statistical analyses and provide more robust conclusions.

In egg laying species, breeding females may adjust the allocation of nutrients or other substances into eggs in order to maximise offspring or maternal fitness. Cooperatively breeding species offer a particularly interesting context in which to study maternal allocation because helpers create predictably improved conditions during offspring development. Some recent studies on cooperative species showed that females assisted by helpers produced smaller eggs, as the additional food brought by the helpers appeared to compensate for this reduction in egg size. However, it remains unclear how common this effect might be. Also currently unknown is whether females change egg composition when assisted by helpers. This effect is predicted by current maternal allocation theory, but has not been previously investigated. We studied egg mass and contents in sociable weavers (Philetairus socius). We found that egg mass decreased with group size, while fledgling mass did not vary, suggesting that helpers may compensate for the reduced investment in eggs. We found no differences in eggs’ carotenoid contents, but females assisted by helpers produced eggs with lower hormonal content, specifically testosterone, androstenedione (A4) and corticosterone levels. Taken together, these results suggest that the environment created by helpers can influence maternal allocation and potentially offspring phenotypes. © 2013 Paquet et al.

The work was conducted between September 2010 and February 2011 at Benfontein Nature Reserve in the Northern Cape province of South Africa (28°52′ S, 24°50′E) with the permission of Northern Cape Nature Conservation. The Ethics Committee of the University of Cape Town specifically approved this study (permit number: 5869-2009). De Beers Consolidated Mines provided access to Benfontein Game Reserve. The sociable weaver is a colonial passerine endemic to the semi-arid acacia savannahs of southern Africa [62], [63]. Sociable weavers build massive communal nests containing several independent nest chambers that are used for breeding and roosting. They are facultative cooperative breeders, breeding in pairs or with up to five helpers (mean group size 3.15 birds for this study, however the proportion of birds breeding in groups varies from ca. 30–80% between years [60]). Helpers are mainly offspring of one or both breeders (93%), although a small number of unrelated birds can also help [60]. Both sexes help, but in a previous study helpers older than one year were found to be only males [64]. [60]. Before the breeding season 503 individuals roosting in 14 colonies were captured and marked with a unique colour ring combination (see [65] for more details on the captures). Then to determine the onset of reproduction, all nest chambers in these study colonies (i.e. approximately 460) were inspected every 3 days. These chambers were marked with a numbered plastic tag. As soon as the first eggs were found, colonies were inspected every day in order to mark every new egg laid (with a soft blunt pencil) and thereby know the laying sequence (one egg is laid per day). Sociable weavers usually lay 3–4 eggs (average clutch size is 3.3 [54]). Two days after the first egg in a given nest was laid we weighed all eggs in that clutch to the nearest 0.001 g with a digital Pesola balance (n = 252 eggs from 84 clutches). On this occasion, we collected the first egg laid in that clutch, which was kept frozen until further analyses (n = 84). Only the first egg was collected in order to allow the breeding activity to continue and hence to determine the breeding group size and identity of the individuals feeding at the nest from which we collected an egg. Nest chambers were checked the following day to weigh a possible fourth egg. To associate every chick with its egg we individually marked 74 hatchlings of 38 clutches (from which we previously collected the first egg) by removing specific down feathers from the neck and/or wings. These marks were still visible 9 days after hatching when the chicks were ringed with a uniquely numbered metal ring. Due to high nest predation by snakes the number of clutches used in this study decreased from the initial 84 to 28 that actually fledged young. We weighed these chicks at 17 days old (46 chicks from 28 clutches). To identify the individuals feeding at a given chamber and hence the breeding group size, we conducted 1 or 2 hours of daily observations for at least 3 consecutive days (min = 3, max = 10, average = 6.6 days). These observations started when the nestlings were around 6 days old since before the feeding activity is slower. Group size was established when no new birds were seen feeding after on average 5.5 consecutive sessions of observations. Observers were situated in a hide placed at 3–5 m from the colony. We identified 34 breeding groups from chambers where we collected the first egg (18 groups with helpers and 16 without). Rainfall closely influences food availability and the duration and success of the breeding season in sociable weavers [54], [66], [67]. We therefore monitored rainfall at the study site using a rain gauge. Detailed methods of yolk content’s analyses are available in protocol S1. Briefly, fresh yolk carotenoids concentrations were determined by colorimetry [68], [69]. Yolk concentrations of testosterone, A4 and corticosterone were determined by radio-immunoassay [70]. Correlations between first egg mass and the different contents analysed are given in Table 1. As often found in the literature [71], testosterone and A4 concentrations were positively correlated. More surprisingly yolk mass and A4 were negatively correlated (Table 1). The aim of our analyses was to study the effect of breeding group size or type (with/without helpers) on egg mass, yolk carotenoids and hormonal contents. In addition, we analysed the effect of breeding group on fledging mass taking into account the egg mass. For all these analyses we conducted linear mixed models using the package nlme in R (R Development Core Team, 2011). The final models were obtained by sequentially eliminating explanatory variables with P values >0.1 using a backwards stepwise approach. The minimal model provided the P values of significant terms whereas P values for non-significant terms were obtained by reintroducing each non-significant variable into the minimal model [72]. For each of the following analyses we built two types of models. One using breeding group size as a dependant variable (studying linear and quadratic relationships) and one using breeding group type (i.e. with/without helpers) as the effect of helper presence may be significant but not additive (i.e. regardless of helpers’ number). We present the results based on both group size and group type but as this represents multiple testing we adjusted the P values for false recovery rates [73]. Since, the relatively small sample sizes in this study do not provide strong statistical power, we also discuss the results when they were significant before false recovery rates corrections. To study the effect of helpers on egg mass we fitted the random factor ‘nest chamber’ in order to take into account the non-independence of eggs from a same clutch. The ‘nest chamber’ factor was nested in a ‘colony’ random factor as we had several nests from each colony. We fitted group size (from 2 to 6 individuals) or group type as a dependant variable and investigated both linear and quadratic relationships for group size. We also added the following co-variables that may affect egg mass in this species [74] and others [7], [8]: laying order (1 to 4); clutch size (2–4); colony size (10–128 individuals); the number of previous breeding attempts in the season (22 eggs were collected during the first breeding attempt and 12 during the second) and rainfall over the 18 days before laying (13.9–94.5 mm). The total rainfall over this period significantly correlated with the number of active clutches (i.e. clutches with eggs or chicks), the number of clutches laid per day and clutch size (Spearman rank correlations, respectively ρ = 0.876; ρ = 0.409; ρ = 0.476 all P<1.2 10−4). For the analyses of yolk mass and contents (i.e. carotenoids and hormones) we included the same terms as above, except ‘nest chamber’ and ‘laying order’ (since we collected only the first egg of each clutch). In addition, we included ‘egg mass of the first egg’ as a fixed term for the analyses of the yolk mass in order to know if the relative investment in yolk differed depending on the presence/number of helpers. As egg and yolk mass of the first eggs collected were not significantly correlated and as both are different indicators of female investment and offspring quality that may be influenced by the mother’s circulating hormones, even independently [75], we included both egg and yolk mass as fixed terms in the analyses of yolk contents. However, as the absolute allocation in yolk mass and contents may be more relevant for offspring fitness, we also present the results without taking into account egg and yolk mass when significant. In order to investigate the effect of breeding group size and type on fledging mass we used ‘nest chamber’ nested in ‘colony’ as random factors and egg mass, the number of hatchlings, hatching order, colony size, the number of breeding attempts and the rain during the 18 days before laying as fixed factors.

Based on the provided information, it is not clear what specific innovations or recommendations can be made to improve access to maternal health. The information provided is focused on a study conducted on sociable weavers and their breeding patterns. To make recommendations for improving access to maternal health, it would be necessary to have information related to maternal health challenges and potential solutions.
AI Innovations Description
The provided description does not directly relate to improving access to maternal health. However, based on the information provided, it seems that the study focuses on understanding the effects of helper presence on maternal allocation and offspring phenotypes in sociable weavers. The study found that females assisted by helpers produced smaller eggs, but the additional food brought by the helpers compensated for this reduction in egg size. The study also found that females assisted by helpers produced eggs with lower hormonal content. These findings suggest that the environment created by helpers can influence maternal allocation and potentially offspring phenotypes.

To develop this into an innovation to improve access to maternal health, one possible recommendation could be to explore the role of social support in improving maternal health outcomes. This could involve developing interventions or programs that provide support to pregnant women and new mothers, such as through the provision of resources, education, and emotional support. By addressing the social and environmental factors that influence maternal health, it may be possible to improve access to quality maternal healthcare and ultimately improve maternal and child health outcomes.
AI Innovations Methodology
To improve access to maternal health, here are some potential recommendations:

1. Telemedicine: Implementing telemedicine services can provide remote access to healthcare professionals for prenatal and postnatal care. This can be especially beneficial for women in rural or underserved areas who may have limited access to healthcare facilities.

2. Mobile clinics: Setting up mobile clinics that travel to remote areas can help bring maternal healthcare services closer to women who may not have transportation or live far away from healthcare facilities.

3. Community health workers: Training and deploying community health workers who can provide basic maternal healthcare services, education, and support within their communities can help improve access to care.

4. Maternal health vouchers: Introducing voucher programs that provide financial assistance for maternal healthcare services can help reduce financial barriers and increase access to quality care.

5. Maternal health education programs: Implementing educational programs that focus on maternal health and prenatal care can help empower women with knowledge and resources to take care of their health during pregnancy.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the target population: Identify the specific population that will be affected by the recommendations, such as women in rural areas or low-income communities.

2. Collect baseline data: Gather data on the current state of maternal health access in the target population, including factors such as distance to healthcare facilities, availability of healthcare providers, and utilization of maternal healthcare services.

3. Model the impact of recommendations: Use statistical modeling or simulation techniques to estimate the potential impact of each recommendation on improving access to maternal health. This could involve analyzing factors such as the number of women reached, reduction in travel distance, increase in healthcare utilization, and cost-effectiveness.

4. Validate the model: Validate the model by comparing the simulated results with real-world data or conducting pilot studies to measure the actual impact of implementing the recommendations.

5. Refine and iterate: Based on the validation results, refine the model and make adjustments as necessary. Repeat the simulation process to assess the impact of any modifications or additional recommendations.

6. Evaluate cost-effectiveness: Assess the cost-effectiveness of implementing the recommendations by comparing the estimated costs of implementation with the projected benefits in terms of improved access to maternal health.

By following these steps, policymakers and healthcare providers can gain insights into the potential impact of different recommendations and make informed decisions on how to improve access to maternal health.

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