Prolificacy–survival trade-off in Morada Nova sheep under Brazilian semiarid conditions

Prolificacy–survival trade-off in Morada Nova sheep under Brazilian semiarid conditions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prolificacy–survival trade-off in Morada Nova sheep under Brazilian semiarid conditions Robson Mateus Freitas Silveira, Aysllan Pereira, Mirela Balistrieri, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8123627/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Domesticated breeds living in resource-limited environments offer an opportunity to investigate life-history trade-offs between offspring number, offspring survival, and seasonal variability in resources. We used long-term data from 13 Morada Nova sheep flocks monitored between 1999 and 2015 in the Brazilian semi-arid region to evaluate how prolificacy and seasonality shape maternal reproductive output and progeny survival. For each ewe lambing event, we quantified total progeny weight at birth (PWB) and weaning (PWW), as well as survival rates at birth (PSRB) and weaning (PSRW), and classified births as occurring in the dry or rainy season. Ewes with single births showed lower PWB and PWW, but higher PSRB and PSRW, than ewes with multiple births (P < 0.0001). When the number of progeny at birth was included as a covariate, each additional lamb was associated with an increase of 0.93 kg in PWB and 2.49 kg in PWW (P < 0.0001), but also with a reduction of 6 percentage points in PSRB and 17 percentage points in PSRW, revealing a strong trade-off between litter size and offspring survival. Ewes with multiple births were more productive in terms of total kilograms of lamb weaned, despite lower survival rates per offspring. We also found that Morada Nova ewes tended to wean more lambs during the dry season than during the rainy season, suggesting that reproductive output is synchronized with local patterns of resource availability and management. Together, these results highlight how life-history trade-offs and environmental seasonality interact to shape reproductive strategies in a locally adapted sheep breed under semi-arid conditions. productive efficiency reproductive efficiency local breeds prolificacy Figures Figure 1 INTRODUCTION The Morada Nova breed, developed in the northeastern region of Brazil—particularly in the municipality of Morada Nova, Ceará—is characterized by its small size, predominantly polled phenotype, and high prolificacy (Facó, 2008; Façanha et al., 2021 ). These animals produce high-quality meat and leather even under stressful environmental conditions, such as elevated temperatures and prolonged droughts (Silveira et al., 2023 ). As such, this breed represents a crucial genetic resource for sheep production in semiarid regions, where harsh climatic conditions can severely impact reproductive performance. Improving productivity is one of the primary strategies for increasing profitability in commercial sheep farming. Systems that achieve better production indicators are generally more profitable and sustainable (Silveira et al., 2021 ). In this context, adapting livestock production systems to environmental constraints poses a major challenge to farmers and professionals in the field. One of the main difficulties in sheep production is the need to produce lambs earlier and at lower cost. Productive efficiency refers to the performance of ewes within the production system, reflecting their potential under specific nutritional and health management conditions (Ungerfeld, Rodriguez, and Perez-Clariget, 2020). Seasonal variation in reproductive behavior among sheep breeds is influenced by evolutionary adaptations to their native environments. For instance, Soay ewes may experience only one to three estrous cycles per year (Grubb and Jewell, 1973 ), while many hair sheep breeds show only minor seasonal variation in reproductive activity (Wildeus, 1997 ). Thus, regional environmental conditions play a critical role in shaping reproductive management strategies across different breeds. Key traits such as lamb weight at weaning significantly impact the economic viability of sheep production, as they are closely tied to the system’s capacity to meet consumer demand (Silveira et al., 2023 ). Maternal traits, including prolificacy and maternal ability, are essential. While high prolificacy increases the number of lambs per parturition, it does not necessarily ensure their survival, which also depends on maternal behavior and milk yield (Wilson et al., 2025 ). Therefore, it is crucial that ewes not only produce multiple offspring but are also capable of raising them successfully until weaning, thereby enhancing their overall productive efficiency. Although several studies have addressed the impact of prolificacy, lamb weight, and survival in breeds such as Merino (Paganoni et al., 2022 ; Haslin et al., 2023 ; Lockwood et al., 2023 ), Dorset, Hampshire, and Suffolk (Osorio-Avalos et al., 2012 ), there is a scarcity of data on these aspects in Morada Nova sheep. Despite their adaptation to the harsh conditions of northeastern Brazil, Morada Nova ewes remain underrepresented in the scientific literature. This study aimed to evaluate the effect of prolificacy and seasonality on the performance of Morada Nova ewes by analyzing the total weight of offspring per ewe at birth and weaning, as well as lamb survival during these stages, and whether lambs are heavier when born in the dry or rainy season. MATERIAL AND METHODS Herd Information Thirteen Morada Nova sheep herds located in different municipalities in CE, assessed between 1999 and 2015 were evaluated (2278 records – Table 1 ). The information regarding the herds was managed and stored in the Herd Management System – SGR (Lôbo, 2013 ). The ewes were raised in an extensive system, primarily grazing on native Caatinga pasture, with supplementation feed provided in some herds during periods of greater pasture scarcity. Table 1 Distribution of parturitions by type and year in Morada Nova ewes used in the study Factors Variables n Type of parturition Simple 1252 Double 921 Triple 105 Total 2278 Years 1999 38 2000 44 2001 47 2002 82 2003 39 2004 34 2005 114 2006 150 2007 223 2008 263 2009 323 2010 338 2011 197 2012 225 2013 151 2014 5 2015 5 Total 2278 The progenies were raised with the dams until weaning, initially fed on milk, and later transitioned to native pasture. The region where these herds are located is characterized by annual precipitation ranging from 150 mm to 1300 mm, with an average of approximately 700 mm. It has an average temperature of 28º C (ranging from 18º C and 40º C) and an average relative humidity of 60%. Sanitary management included monitoring newborn lambs, ensuring colostrum ingestion, and checking navel healing. Vermifugation was performed after the rainy season and as needed, following the recommendations for each animal category. During the final third of the gestation and at 15 days of age for the lambs, vaccinations against rabies and to control clostridiosis were performed. Parasite control was managed using the FAMACHA© method (Bath et al., 1996 ; Van Wyk et l., 2002), with treatments every 15 days during the rainy season (October to March) and every 30 days in the dry season (April to September). Additional sanitary control included monitoring for eimeriosis (coccidiosis), which was treated with sulfa according to the manufacturer's guidelines. After childbirth, the lambs’ navel was treated and, if necessary, cut after drying. The lambs were weighed at birth and at weaning. Lambs were weaned at 60 days of age. Characteristics Studied The characteristics associated with the productive efficiency of the females included total weight of lambs born and weaned per female per parturition (PWB and PWW, respectively), and the survival rate of the progenies at birth (PSRB) and at weaning (PSRW). Lambs were weighed at birth and weaning using a calibrated electronic scale to ensure measurement accuracy. The PWB was calculated by summing the weight of lambs born from the same birth per ewe, adjusted for each season or year of birth. The PWW was determined by totaling the weights of the lambs immediately after the suckling period for each ewe per parturition. The PSRB was obtained by dividing the number of alive and viable progenies at birth by the total number of progenies born per ewe per parturition. Similarly, PSRW was determined by dividing the number of progenies weaned by the total number of progenies born per ewes per parturition. The absence of data at birth and weaning was considered indicative of lamb mortality, and a value of zero was assigned to the total weight of lambs born (PWB) and weaned (PWW) for the respective ewe. Descriptive statistics for the evaluated characteristics are presented in Table 2 . Table 2 Mean and standard deviation for total weight of progenies at birth (PWB) and weaning (PWW), and survival rate at birth (PSRB) and weaning (PSRW) in ewes of the Morada Nova breed Traits Average Standard deviation PWB (kg) 2.66 1.33 PWW (kg) 14.04 5.75 PSRB (%) 0.85 0.34 PSRW (%) 0.89 0.24 Statistical Analysis The model used for PWB and PWW considered the effects of herd (13 classes), year of birth (1999 to 2015), month of weighing (12 months), progeny management (9 classes), order of birth of the mother (1 to 8, females with parity order above 8 were grouped in the latter), sex of the progeny (male or female) and class of progeny group in the same parity or interaction of the sex of the progenies with the type of parity (for single parries, being one male or one female; for twin births, two males, two females or one male and one female; and finally triplets or more regardless of sex) and the weight of the ewe was also used as a covariate. The same effects were considered for the adjustment of the weaning weight of progenies, including the effect of progeny age at weaning. With the adjusted individual weight values of the progenies, the total weights of the progenies at birth (PWB) and at weaning (PWW) were calculated. To assess the effect of prolificacy on the PWB, PWW, PSRB, and PSRW characteristics, two types of analyses were performed: I) least squares means analysis, using type of parturition (single, double, and triple) as a class variable to compare means by class; II) regression analysis, with type of parturition as a covariate to estimate the effect of each additional progeny on the studied characteristics. Both analyses adjusted for herd (13 levels), parity order (1 to 8; with orders greater than 8 grouped together), year (1999 to 2015) and month of parturition (12 months), and covariate weight of mother at parturition. When significant differences were found, means were compared using the Tukey-Kramer test with a 5% significance ( p ≤ 0.05). Canonical discriminant analysis (CDA) was performed to discriminate the main variables that differentiate the type of parturition and which variables have discriminatory power. The general CDA model is described in Eq. (1) \(\:{Z}_{n}=\:\propto\:+\:{\beta\:}_{1}{X}_{1}+{\beta\:}_{2}{X}_{2}+\:\cdots\:+\:{\beta\:}_{n}{X}_{n}\) [1] Where: \(\:{Z}_{n}\) is the dependent variable (databases), \(\:\propto\:\) is the intercept, \(\:{X}_{i}\) are the explanatory variables, \(\:{\beta\:}_{i}\) are the discriminant coefficients for each explanatory variable. For this, a stepwise method was used, which is indicated when there are a large number of variables to include in the function. The discriminant power was evaluated by % of variance, Wilks' Lambda statistic, and standardized coefficients. Finally, with the aim of analyzing whether there was an association between the type of lambing of the ewe (single - S, multiple - M) and its type of progeny - statistical techniques such as the Chi-Square test and Fisher's exact test were used to verify a possible association of prolificacy between the type of lambing of the mother and her offspring by seasonality [Dry season – Jan to Jul and Rainy season– Aug to Dec)]. Statistical analyses were performed using SAS and SPSS software RESULTS AND DISCUSSION Significant differences (P < 0.0001) were found between the means for all studied characteristics concerning the type of parturition (Table 3 ). The PWB values observed for single parturitions were similar to those reported by Shiotsuki et al. ( 2014 ), however they were greater for twin parturitions. It is noteworthy that these authors used data from the same herds in the present study, with the only differences being the years evaluated (the current study includes more recent data). In a literature review by Facó et al. ( 2008 ), the average survival rates for this breed were 82.2% from birth to weaning and 66.4% from birth to one year old. In contrast, Rosati et al. ( 2002 ) reported lower survival rates from birth to weaning (72%) when considering several sheep breeds. Table 3 Least squares means for total progeny weight at birth (PWB) and weaning (PWW), and survival rates at birth (PSRB) and weaning (PSRW) by type of parturition in Morada Nova ewes Type of parturition PWB (kg) PWW (kg) PSRB (%) PSRW (%) Simple 2.22 c 15.68 b 88.0 a 100.0 a Double 3.54 a 19.00 a 85.0 b 81.0 b Triple 2.91 b 18.30 a 64.0 c 78.0 b Means followed by different letters in the column differ statistically by the Tukey - Kramer test ( p < 0.0001). Regarding prolificacy, ewes with single births showed lower PWB and PWW values but higher PSRB and PSRW values (Table 3 ), which aligns with the findings of Aguirre et al. ( 2017 ) and Duguma et al. ( 2002 ), who also observed that increasing the number of lambs per birth reduces survival rates but increases total lamb weight at weaning. This is expected, as the weight of a lamb from a single birth does not exceed the total weight of lambs from twin births, meaning that PWB and PWW are lower in single births. On the other hand, single ewe lambs offer a better chance of progeny survival at birth and weaning, due to factors such as increased maternal care and greater milk availability. This is evidenced by higher progeny survival rates from single births compared to multiple births. Aguirre et al. ( 2017 ) reported survival rates of 69.2, 47.6, and 38.4% for lambs from single, double, and triple births respectively, further demonstrating that PSRW decreases as the number of lambs per birth increases. Conversely, twin births, when resulting in live births, provide a greater total weight of lambs at birth and weaning. Duguma et al. ( 2002 ), in their study of Merino ewes, also observed greater PWB and PWW values for ewes with multiple births. However, it is crucial to consider the economic efficiency, as raising twin lambs incurs additional costs. While selecting ewes thinking in multiple births may increase productivity in sheep farming, it may not necessarily improve the economic viability of the operation. An economic analysis would be needed to assess this impact. The lamb's weight directly affects its survival rate at birth and weaning as it reflects factors such as nutrition, development, maternal ability, and the health of both the lamb and its mother. Thus, low birth weight is one of the main causes of mortality at this stage (Nóbrega Junior et al., 2005 ). Therefore, effective nutritional and health management of ewes and lambs postpartum is important to reducing mortality and, consequently, increasing the number of lambs at weaning. The total weight of lambs per ewe at weaning is a key productivity indicator, influenced by factors such as fertility, prolificity, survival rate, and maternal ability (Amarilho-Silveira et al., 2017 ). Among these traits, maternal ability is important because it is widely used to evaluate the productive and reproductive performance of ewes. It serves as a valuable criterion for selecting superior ewes (Duguma et al., 2002 ; Wilson et al., 2025 ) and for evaluating the overall efficiency of the production system (Moreno et al., 2010 ). While selecting ewes for multiple births may increase overall productivity (PWW), it is essential to consider the additional costs of managing and feeding multiple lambs. Studies such as Mokhtari et al. ( 2010 ) suggest that the economic benefit of multiple births is only realized when survival rates are sufficiently high to offset the increased costs. Therefore, a cost-benefit analysis is crucial before making decisions based solely on prolificacy. The low survival rates of lambs, especially when the number of lambs per birth increases, can be attributed to deficiencies in the rearing system. The primary contributors to lamb mortality in the first weeks of life are nutritional factors (such as starvation and/or hypoglycemia), environmental factors (such as hypothermia, predators, or crushing), and health issues (such as deformities, infections, or traumas; Nóbrega Junior et al., 2005 ). Lambs born from twin births have lower individual weights due to nutrient competition, which begins in utero and continues until weaning, making them more vulnerable. These challenges, combined with potentially inadequate management by the farmers, lead to greater mortality rates in the herd (Pires et al., 2011 , Nóbrega Junior et al., 2005 ). The results of the canonical discriminant analysis highlight the importance of birth weight as the primary factor distinguishing birth types. The fact that lambs from twin and triple births have similar weights, but differ from those born as singles, suggests that prolificacy directly impacts weight and, consequently, survival. This variation could have significant implications for selecting breeding animals in semi-arid production systems. The use of the number of progenies at calving as a covariate revealed that each additional progeny per calving results in an increase of 0.93 kg in lamb's weight at birth and 2.49 kg at weaning. However, this also corresponds to a 6% reduction in the birth survival rate and a 17% reduction in the weaning survival rate of the lambs (Table 4 ). The regression analysis provided a detailed view of the effect of prolificacy on the evaluated characteristics. Understanding the economic values of these characteristics allows for a more accurate assessment of the benefits of multiple births in the production system. Therefore, prolificity should be evaluated alongside survival rates to better gauge female overall productivity, rather than considering prolificacy alone. Table 4 – Regression analysis of the number of progenies per lamb on total weight of progenies at birth (PWB) and weaning (PWW), and survival rates at birth (PSRB) and weaning (PSRW) in Morada Nova ewes Traits Regression Coefficient (b) Standard error of b p -value PWB (kg) 0.93 0.03 < 0.0001 PWW (kg) 2.49 0.19 < 0.0001 PSRB (%) -6.00 1.00 < 0.0001 PSRW (%) -17.00 1.00 < 0.0001 The summary of the canonical discriminant analysis considering the productive indexes is presented in Table 5 . The first two canonical functions discriminated 100% of the data variation, but only the first function discriminated 99.9% of the data and was the only significant function (P < 0.001). The weight of the progeny at birth was the only variable that was able to differentiate the birth types. The biplot of the two canonical functions and the classification rates shows this dynamic of birth weight as a function of the birth type, in which it is observed that the animals born from twin or triple births have similar weights (close centroids), but divergent from the single births (Fig. 1 ). Only 13.2% of the animals born from triple births were correctly classified in their group of origin, while the single birth animals presented a rate of 93.2%. Table 5 Summary of canonical discriminant analysis for productive indices of Morada Nova sheep in the Brazilian semiarid region Eigenvalues Function Eigenvalues % of variance % cumulative Canonical correlation 1 1.239 a 100.0 100.0 0.744 2 0.000 a 0.0 100.0 0.010 Wilks’ Lambda Test of functions Wilks’ Lambda Qui-square df p -value 1 0.446 1905.003 4 0.000 2 1.000 0.237 1 0.627 1 2 PWB 0.98 -0.29 PWW 0.1 1.01 Classification results Predict group association Simple Double Triple Count Simple 932 78 0 Double 188 931 33 Triple 6 171 27 % Simple 92.3 7.7 0.0 Double 16.3 80.8 2.9 Triple 2.9 83.8 13.2 Note: Total weights of progenies at birth (PWB) and weaning (PWW) The association tests between the type of birth of the ewe and its progeny were not significant in the dry and rainy seasons [Chi-square test: p = 0.55 and p = 0.11, respectively). However, a statistically significant difference ( p = 0.014) was observed between the number of lambs weaned during the dry and rainy periods. The average number of lambs weaned during the dry period was 1.65 ± 0.657, which was slightly greater compared to 1.60 ± 0.616 during the rainy period. This difference may be related to the reproductive seasonality of the ewes. Ewes giving birth in the dry season are likely conceived during the rainy season when better forage availability improves their body condition. This enhanced nutrition positively influences the hypothalamic-pituitary-gonadal axis, promoting greater follicular development and codominance, leading to more lambs born and weaned. IMPLICATIONS The results of this study, although consistent with previous findings, bring important implications that advance current knowledge on the performance of hair sheep in semiarid environments. Classical studies have already indicated the existence of an optimal prolificacy level that maximizes the number of weaned lambs without excessively increasing neonatal losses (Owen et al., 1986 ). For example, in Cambridge sheep with high prolificacy, increasing litter size beyond a certain threshold resulted in higher lamb mortality and nonlinear gains in the number of weaned lambs, with a maximum reached at intermediate prolificacy levels. Similarly, Holmøy et al. ( 2014 ) reported in Norwegian sheep that the risk of neonatal loss grows drastically in higher-order multiple births (triplets), especially in young ewes, suggesting biological limitations in maternal care and the ability to sustain large litters. These findings are corroborated under Brazilian semiarid conditions, while we demonstrate for the first time such effects in a locally adapted breed, reaffirming the generality of the trade-off between prolificacy and progeny survival across different environments. The novelty of this work lies in the use of a large dataset covering 13 Morada Nova herds in Brazil over a long longitudinal period. To our knowledge, no previous studies of comparable scale and scope have focused on this breed under real field conditions in semiarid systems. This evidence clearly shows that locally adapted breeds can sustain high reproductive performance in nutritionally and thermally challenging environments. Indeed, the use of locally adapted sheep breeds has been increasing in northeastern Brazil, as producers seek productive animals under climatic and nutritional stress (Landim et al., 2021; Silveira et al., 2023 ). Hair sheep adapted to semiarid regions, such as the Morada Nova, present high rusticity, heat tolerance, and parasite resistance (Façanha et al., 2021 ) — traits crucial for maintaining productivity in low-fertility soils and irregular climates with low rainfall. Morada Nova sheep, in particular, are notable for their early sexual maturity, high fertility, prolificacy, and strong maternal ability, combined with a small adult body size that favors efficiency in low-input systems (Pereira et al., 2023 ; Façanha et al., 2021 ). These characteristics explain why local breeds such as Morada Nova are considered essential genetic resources for conservation: not only can they survive where exotic breeds would struggle, but they also sustain lamb production in both quantity and quality compatible with regional realities. This aspect is especially relevant in the context of future climate change. As reported by Silveira et al. ( 2026 ), the conservation of locally adapted genetic resources will be essential to preserve biodiversity, strengthen ecosystem resilience, and meet the challenges of food security under climate pressure. Findings from other contexts reinforce this perspective. Molotsi et al. ( 2017 ), for example, in a literature review, reported that the indigenous Namaqua Afrikaner breed outperformed commercially selected breeds such as Dorper in the number of lambs weaned under adverse conditions, highlighting the adaptive advantage of native breeds in terms of survival and reproduction. These parallels underscore the strategic value of conserving and using local breeds such as Morada Nova in semiarid systems, not only from a cultural and biodiversity perspective but also as a pathway to improved sustainable productivity. Our findings deepen the understanding of the balance between prolificacy and survival in restrictive environments. We observed that high prolificacy increases total lamb production but also imposes greater mortality risks, particularly in triplets and in young ewes. Conversely, moderate prolificacy (one to two lambs per birth) tends to maximize the number of lambs weaned, consistent with the optimal balance concept described by Wilson et al. ( 2025 ). This pattern also aligns with Dwyer et al. ( 2005 ), who reported a reduction of approximately 1 kg in birth weight for each additional lamb in the litter, compromising lamb viability. From a practical perspective, our results support strategies in both management and breeding that aim to balance productivity and survival. In management, this includes nutritional support during late gestation, peripartum assistance, and differentiated monitoring of primiparous and multiple-bearing ewes. In genetic improvement, progeny survival should be included as a criterion, alongside reproductive indices, emphasizing indicators such as the number of lambs weaned per mated ewe. This approach is more consistent with biological efficiency and system sustainability, as it values genotypes capable of producing a higher proportion of viable offspring. In summary, although we confirm trends already described in other breeds and regions, this study advances knowledge by demonstrating these relationships in a locally adapted breed in the Brazilian semiarid, based on original field data. The insights presented here provide technical support for specific management and breeding recommendations, reinforce the importance of conserving the Morada Nova breed, and contribute to the development of more balanced, resilient, and sustainable sheep production systems under environmental constraints. CONCLUSION In Morada Nova ewes, multiple births increased productivity but reduced progeny survival, highlighting a clear trade-off between prolificacy and lamb viability. Moderate prolificacy proved to be more efficient for optimizing production under semiarid conditions, balancing total weaned lamb weight and survival rates. Furthermore, Morada Nova ewes tended to wean more lambs during the dry season than in the rainy season, reinforcing the influence of environmental seasonality on the breed’s productive and reproductive performance. Declarations Funding None Conflicts of interest The authors declare that they have no conflicts of interest. Ethics approval All the procedures performed in the study followed the ethical principles of the Declaration of Helsinki Consent to participate No applicable. Consent for publication No applicable. Availability of data and material No applicable. Code availability No applicable. Authors’ contributions Robson Mateus Freitas Silveira: data analysis, text editing and final review Aysllan Harlley Rodrigues Pereira: Conceptualization, methodology, data curation, data analysis, text editing and final review Mirela Balistrieri: text editing and final review Paula Renata Cortat: text editing and final review Kleibe de Moraes Silva: text editing and final review Eula Regina Carrara: text editing and final review Concepta Mcmanus: text editing and final review Aline Vieira Landim: Conceptualization, methodology, data curation, data analysis, text editing and final review Declaration of generative AI and AI-assisted technologies During the preparation of this work, the authors utilized ChatGPT to improve readability in specific sections of the manuscript. After using this tool, the authors carefully reviewed and edited the content as needed and take full responsibility for the publication's content. References Aguirre EL, Mattos EC, Eler JP, et al. 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Small Rumin Res. 2002;43(1):65–74. Shiotsuki L, Oliveira DP, Lôbo RNB, et al. Genetic parameters for growth and reproductive traits of Morada Nova sheep kept by smallholder in semi-arid Brazil. Small Rumin Res. 2014;58:73–82. Silveira RMF, Façanha DAE, Vasconcelos AM, Leite SCB, Leite JHGM, Saraiva EP, et al. Physiological adaptability of livestock to climate change: A global model-based assessment for the 21st century. Environ Impact Assess Rev. 2026;116:108061. Silveira RMF, Lima DF, Camelo BV, McManus C, Silva VJ, Ferreira J, et al. Machine learning applied to understand perceptions, habits and preferences of lamb meat consumers in the Brazilian semi-arid region. Small Rumin Res. 2023;227:107088. https://doi.org/10.1016/j.smallrumres.2023.107088 Silveira RMF, McManus CM, Carrara ER, De Vecchi LB, Carvalho JRS, Costa HHA, et al. Adaptive, morphometric and productive responses of Brazilian hair lambs: crossing between indigenous breeds—A machine learning approach. Small Rumin Res. 2024;232:107208. Silveira RMF, Vasconcelos AM, Silva VJ, Ortiz Vega WH, Toro-Mujica P, Ferreira J. Typification, characterization, and differentiation of sheep production systems in the Brazilian semiarid region. NJAS: Wageningen J Life Sci. 2021;93(1):48–73. https://doi.org/10.1080/27685241.2021.1956220 Ungerfeld R, Rodriguez MGK, Perez-Clariget R. Reproductive response of postpartum spring-lambing ewes: Effects of weaning on follicular growth and postpartum interval on response to ram placement with ewes (‘ram effect’). Anim Reprod Sci. 2022;223:106642. https://doi.org/10.1016/j.anireprosci.2020.106642 van Wyk JA, Bath GF. The FAMACHA system for managing haemonchosis in sheep and goats by clinically identifying individual animals for treatment. Vet Res. 2002;33(5):509–29. https://doi.org/10.1051/vetres:2002036 Wildeus S. Hair sheep genetic resources and their contribution to diversified small ruminant production in the United States. J Anim Sci. 1997;75:630–40. https://doi.org/10.2527/1997.753630x Wilson CS, Cherry NL, Taylor JB. Lamb survivability: a new approach to an old problem. Front Anim Sci. 2025;6:1497380. https://doi.org/10.3389/fanim.2025.1497380 Supplementary Files floatimage1.png Graphical Abstract Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 20 Nov, 2025 Reviewers invited by journal 20 Nov, 2025 Editor assigned by journal 17 Nov, 2025 First submitted to journal 15 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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08:32:46","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":108399,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8123627/v1/e3848d5176ddc40c1249915f.html"},{"id":96975934,"identity":"3509a4fd-1d97-40ec-9ed9-f39de33109eb","added_by":"auto","created_at":"2025-11-28 08:32:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":165299,"visible":true,"origin":"","legend":"\u003cp\u003eBiplot of canonical discriminant analysis for the productive indexes of Morada Nova sheep in the Brazilian semiarid region\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8123627/v1/e517dc845f0f628daf178337.png"},{"id":97144702,"identity":"f37a5020-601a-43c4-8a53-c3cf0406511e","added_by":"auto","created_at":"2025-12-01 10:11:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":841114,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8123627/v1/f1ea6e48-0dcd-4f3f-bcb6-4aca6eea68ff.pdf"},{"id":96975940,"identity":"20adea03-901f-4f2f-8856-1fe5cebe3eb0","added_by":"auto","created_at":"2025-11-28 08:32:46","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":541358,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical Abstract\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8123627/v1/179c66c80e22815dd9dd51d6.png"}],"financialInterests":"","formattedTitle":"Prolificacy–survival trade-off in Morada Nova sheep under Brazilian semiarid conditions","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe Morada Nova breed, developed in the northeastern region of Brazil\u0026mdash;particularly in the municipality of Morada Nova, Cear\u0026aacute;\u0026mdash;is characterized by its small size, predominantly polled phenotype, and high prolificacy (Fac\u0026oacute;, 2008; Fa\u0026ccedil;anha et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These animals produce high-quality meat and leather even under stressful environmental conditions, such as elevated temperatures and prolonged droughts (Silveira et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As such, this breed represents a crucial genetic resource for sheep production in semiarid regions, where harsh climatic conditions can severely impact reproductive performance.\u003c/p\u003e\u003cp\u003eImproving productivity is one of the primary strategies for increasing profitability in commercial sheep farming. Systems that achieve better production indicators are generally more profitable and sustainable (Silveira et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this context, adapting livestock production systems to environmental constraints poses a major challenge to farmers and professionals in the field. One of the main difficulties in sheep production is the need to produce lambs earlier and at lower cost.\u003c/p\u003e\u003cp\u003eProductive efficiency refers to the performance of ewes within the production system, reflecting their potential under specific nutritional and health management conditions (Ungerfeld, Rodriguez, and Perez-Clariget, 2020). Seasonal variation in reproductive behavior among sheep breeds is influenced by evolutionary adaptations to their native environments. For instance, Soay ewes may experience only one to three estrous cycles per year (Grubb and Jewell, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1973\u003c/span\u003e), while many hair sheep breeds show only minor seasonal variation in reproductive activity (Wildeus, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Thus, regional environmental conditions play a critical role in shaping reproductive management strategies across different breeds.\u003c/p\u003e\u003cp\u003eKey traits such as lamb weight at weaning significantly impact the economic viability of sheep production, as they are closely tied to the system\u0026rsquo;s capacity to meet consumer demand (Silveira et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Maternal traits, including prolificacy and maternal ability, are essential. While high prolificacy increases the number of lambs per parturition, it does not necessarily ensure their survival, which also depends on maternal behavior and milk yield (Wilson et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Therefore, it is crucial that ewes not only produce multiple offspring but are also capable of raising them successfully until weaning, thereby enhancing their overall productive efficiency.\u003c/p\u003e\u003cp\u003eAlthough several studies have addressed the impact of prolificacy, lamb weight, and survival in breeds such as Merino (Paganoni et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Haslin et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lockwood et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Dorset, Hampshire, and Suffolk (Osorio-Avalos et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), there is a scarcity of data on these aspects in Morada Nova sheep. Despite their adaptation to the harsh conditions of northeastern Brazil, Morada Nova ewes remain underrepresented in the scientific literature.\u003c/p\u003e\u003cp\u003eThis study aimed to evaluate the effect of prolificacy and seasonality on the performance of Morada Nova ewes by analyzing the total weight of offspring per ewe at birth and weaning, as well as lamb survival during these stages, and whether lambs are heavier when born in the dry or rainy season.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eHerd Information\u003c/h2\u003e\u003cp\u003eThirteen Morada Nova sheep herds located in different municipalities in CE, assessed between 1999 and 2015 were evaluated (2278 records \u0026ndash; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The information regarding the herds was managed and stored in the Herd Management System \u0026ndash; SGR (L\u0026ocirc;bo, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The ewes were raised in an extensive system, primarily grazing on native \u003cem\u003eCaatinga\u003c/em\u003e pasture, with supplementation feed provided in some herds during periods of greater pasture scarcity.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of parturitions by type and year in Morada Nova ewes used in the study\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFactors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eType of parturition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSimple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1252\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDouble\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e921\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTriple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e105\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2278\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"17\" rowspan=\"18\"\u003e\u003cp\u003eYears\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e114\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e223\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e263\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e323\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e338\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e197\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e225\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e151\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2278\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe progenies were raised with the dams until weaning, initially fed on milk, and later transitioned to native pasture. The region where these herds are located is characterized by annual precipitation ranging from 150 mm to 1300 mm, with an average of approximately 700 mm. It has an average temperature of 28\u0026ordm; C (ranging from 18\u0026ordm; C and 40\u0026ordm; C) and an average relative humidity of 60%.\u003c/p\u003e\u003cp\u003eSanitary management included monitoring newborn lambs, ensuring colostrum ingestion, and checking navel healing. Vermifugation was performed after the rainy season and as needed, following the recommendations for each animal category. During the final third of the gestation and at 15 days of age for the lambs, vaccinations against rabies and to control clostridiosis were performed. Parasite control was managed using the FAMACHA\u0026copy; method (Bath et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Van Wyk et l., 2002), with treatments every 15 days during the rainy season (October to March) and every 30 days in the dry season (April to September). Additional sanitary control included monitoring for eimeriosis (coccidiosis), which was treated with sulfa according to the manufacturer's guidelines. After childbirth, the lambs\u0026rsquo; navel was treated and, if necessary, cut after drying. The lambs were weighed at birth and at weaning. Lambs were weaned at 60 days of age.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCharacteristics Studied\u003c/h3\u003e\n\u003cp\u003eThe characteristics associated with the productive efficiency of the females included total weight of lambs born and weaned per female per parturition (PWB and PWW, respectively), and the survival rate of the progenies at birth (PSRB) and at weaning (PSRW). Lambs were weighed at birth and weaning using a calibrated electronic scale to ensure measurement accuracy. The PWB was calculated by summing the weight of lambs born from the same birth per ewe, adjusted for each season or year of birth. The PWW was determined by totaling the weights of the lambs immediately after the suckling period for each ewe per parturition. The PSRB was obtained by dividing the number of alive and viable progenies at birth by the total number of progenies born per ewe per parturition. Similarly, PSRW was determined by dividing the number of progenies weaned by the total number of progenies born per ewes per parturition. The absence of data at birth and weaning was considered indicative of lamb mortality, and a value of zero was assigned to the total weight of lambs born (PWB) and weaned (PWW) for the respective ewe. Descriptive statistics for the evaluated characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMean and standard deviation for total weight of progenies at birth (PWB) and weaning (PWW), and survival rate at birth (PSRB) and weaning (PSRW) in ewes of the Morada Nova breed\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTraits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAverage\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStandard deviation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePWB (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePWW (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSRB (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSRW (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe model used for PWB and PWW considered the effects of herd (13 classes), year of birth (1999 to 2015), month of weighing (12 months), progeny management (9 classes), order of birth of the mother (1 to 8, females with parity order above 8 were grouped in the latter), sex of the progeny (male or female) and class of progeny group in the same parity or interaction of the sex of the progenies with the type of parity (for single parries, being one male or one female; for twin births, two males, two females or one male and one female; and finally triplets or more regardless of sex) and the weight of the ewe was also used as a covariate. The same effects were considered for the adjustment of the weaning weight of progenies, including the effect of progeny age at weaning. With the adjusted individual weight values of the progenies, the total weights of the progenies at birth (PWB) and at weaning (PWW) were calculated.\u003c/p\u003e\u003cp\u003eTo assess the effect of prolificacy on the PWB, PWW, PSRB, and PSRW characteristics, two types of analyses were performed: I) least squares means analysis, using type of parturition (single, double, and triple) as a class variable to compare means by class; II) regression analysis, with type of parturition as a covariate to estimate the effect of each additional progeny on the studied characteristics. Both analyses adjusted for herd (13 levels), parity order (1 to 8; with orders greater than 8 grouped together), year (1999 to 2015) and month of parturition (12 months), and covariate weight of mother at parturition. When significant differences were found, means were compared using the Tukey-Kramer test with a 5% significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eCanonical discriminant analysis (CDA) was performed to discriminate the main variables that differentiate the type of parturition and which variables have discriminatory power. The general CDA model is described in Eq.\u0026nbsp;(1)\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Z}_{n}=\\:\\propto\\:+\\:{\\beta\\:}_{1}{X}_{1}+{\\beta\\:}_{2}{X}_{2}+\\:\\cdots\\:+\\:{\\beta\\:}_{n}{X}_{n}\\)\u003c/span\u003e\u003c/span\u003e[1]\u003c/p\u003e\u003cp\u003eWhere:\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Z}_{n}\\)\u003c/span\u003e\u003c/span\u003e is the dependent variable (databases),\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\propto\\:\\)\u003c/span\u003e\u003c/span\u003e is the intercept,\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{i}\\)\u003c/span\u003e\u003c/span\u003e are the explanatory variables,\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{i}\\)\u003c/span\u003e\u003c/span\u003e are the discriminant coefficients for each explanatory variable.\u003c/p\u003e\u003cp\u003eFor this, a stepwise method was used, which is indicated when there are a large number of variables to include in the function. The discriminant power was evaluated by % of variance, Wilks' Lambda statistic, and standardized coefficients.\u003c/p\u003e\u003cp\u003eFinally, with the aim of analyzing whether there was an association between the type of lambing of the ewe (single - S, multiple - M) and its type of progeny - statistical techniques such as the Chi-Square test and Fisher's exact test were used to verify a possible association of prolificacy between the type of lambing of the mother and her offspring by seasonality [Dry season \u0026ndash; Jan to Jul and Rainy season\u0026ndash; Aug to Dec)]. Statistical analyses were performed using SAS and SPSS software\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cp\u003eSignificant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) were found between the means for all studied characteristics concerning the type of parturition (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The PWB values observed for single parturitions were similar to those reported by Shiotsuki et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), however they were greater for twin parturitions. It is noteworthy that these authors used data from the same herds in the present study, with the only differences being the years evaluated (the current study includes more recent data). In a literature review by Fac\u0026oacute; et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), the average survival rates for this breed were 82.2% from birth to weaning and 66.4% from birth to one year old. In contrast, Rosati et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) reported lower survival rates from birth to weaning (72%) when considering several sheep breeds.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLeast squares means for total progeny weight at birth (PWB) and weaning (PWW), and survival rates at birth (PSRB) and weaning (PSRW) by type of parturition in Morada Nova ewes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of parturition\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePWB (kg)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePWW (kg)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePSRB (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePSRW (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSimple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.22\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.68\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDouble\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.54\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.91\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.30\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eMeans followed by different letters in the column differ statistically by the Tukey - Kramer test (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRegarding prolificacy, ewes with single births showed lower PWB and PWW values but higher PSRB and PSRW values (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), which aligns with the findings of Aguirre et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Duguma et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), who also observed that increasing the number of lambs per birth reduces survival rates but increases total lamb weight at weaning. This is expected, as the weight of a lamb from a single birth does not exceed the total weight of lambs from twin births, meaning that PWB and PWW are lower in single births. On the other hand, single ewe lambs offer a better chance of progeny survival at birth and weaning, due to factors such as increased maternal care and greater milk availability. This is evidenced by higher progeny survival rates from single births compared to multiple births. Aguirre et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) reported survival rates of 69.2, 47.6, and 38.4% for lambs from single, double, and triple births respectively, further demonstrating that PSRW decreases as the number of lambs per birth increases. Conversely, twin births, when resulting in live births, provide a greater total weight of lambs at birth and weaning. Duguma et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), in their study of Merino ewes, also observed greater PWB and PWW values for ewes with multiple births. However, it is crucial to consider the economic efficiency, as raising twin lambs incurs additional costs. While selecting ewes thinking in multiple births may increase productivity in sheep farming, it may not necessarily improve the economic viability of the operation. An economic analysis would be needed to assess this impact.\u003c/p\u003e\u003cp\u003eThe lamb's weight directly affects its survival rate at birth and weaning as it reflects factors such as nutrition, development, maternal ability, and the health of both the lamb and its mother. Thus, low birth weight is one of the main causes of mortality at this stage (N\u0026oacute;brega Junior et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Therefore, effective nutritional and health management of ewes and lambs postpartum is important to reducing mortality and, consequently, increasing the number of lambs at weaning. The total weight of lambs per ewe at weaning is a key productivity indicator, influenced by factors such as fertility, prolificity, survival rate, and maternal ability (Amarilho-Silveira et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Among these traits, maternal ability is important because it is widely used to evaluate the productive and reproductive performance of ewes. It serves as a valuable criterion for selecting superior ewes (Duguma et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Wilson et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and for evaluating the overall efficiency of the production system (Moreno et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhile selecting ewes for multiple births may increase overall productivity (PWW), it is essential to consider the additional costs of managing and feeding multiple lambs. Studies such as Mokhtari et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) suggest that the economic benefit of multiple births is only realized when survival rates are sufficiently high to offset the increased costs. Therefore, a cost-benefit analysis is crucial before making decisions based solely on prolificacy.\u003c/p\u003e\u003cp\u003eThe low survival rates of lambs, especially when the number of lambs per birth increases, can be attributed to deficiencies in the rearing system. The primary contributors to lamb mortality in the first weeks of life are nutritional factors (such as starvation and/or hypoglycemia), environmental factors (such as hypothermia, predators, or crushing), and health issues (such as deformities, infections, or traumas; N\u0026oacute;brega Junior et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Lambs born from twin births have lower individual weights due to nutrient competition, which begins in utero and continues until weaning, making them more vulnerable. These challenges, combined with potentially inadequate management by the farmers, lead to greater mortality rates in the herd (Pires et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, N\u0026oacute;brega Junior et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results of the canonical discriminant analysis highlight the importance of birth weight as the primary factor distinguishing birth types. The fact that lambs from twin and triple births have similar weights, but differ from those born as singles, suggests that prolificacy directly impacts weight and, consequently, survival. This variation could have significant implications for selecting breeding animals in semi-arid production systems.\u003c/p\u003e\u003cp\u003eThe use of the number of progenies at calving as a covariate revealed that each additional progeny per calving results in an increase of 0.93 kg in lamb's weight at birth and 2.49 kg at weaning. However, this also corresponds to a 6% reduction in the birth survival rate and a 17% reduction in the weaning survival rate of the lambs (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The regression analysis provided a detailed view of the effect of prolificacy on the evaluated characteristics. Understanding the economic values of these characteristics allows for a more accurate assessment of the benefits of multiple births in the production system. Therefore, prolificity should be evaluated alongside survival rates to better gauge female overall productivity, rather than considering prolificacy alone.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u0026ndash; Regression analysis of the number of progenies per lamb on total weight of progenies at birth (PWB) and weaning (PWW), and survival rates at birth (PSRB) and weaning (PSRW) in Morada Nova ewes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTraits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRegression Coefficient (b)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStandard error of b\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePWB (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePWW (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSRB (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-6.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSRW (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-17.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe summary of the canonical discriminant analysis considering the productive indexes is presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The first two canonical functions discriminated 100% of the data variation, but only the first function discriminated 99.9% of the data and was the only significant function (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The weight of the progeny at birth was the only variable that was able to differentiate the birth types. The biplot of the two canonical functions and the classification rates shows this dynamic of birth weight as a function of the birth type, in which it is observed that the animals born from twin or triple births have similar weights (close centroids), but divergent from the single births (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Only 13.2% of the animals born from triple births were correctly classified in their group of origin, while the single birth animals presented a rate of 93.2%.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of canonical discriminant analysis for productive indices of Morada Nova sheep in the Brazilian semiarid region\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eEigenvalues\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFunction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEigenvalues\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% of variance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e% cumulative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCanonical correlation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.239\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.744\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.000\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWilks\u0026rsquo; Lambda\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTest of functions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWilks\u0026rsquo; Lambda\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQui-square\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1905.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.237\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.627\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePWB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e-0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePWW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eClassification results\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003ePredict group association\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSimple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDouble\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTriple\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eCount\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSimple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDouble\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e931\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTriple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSimple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e92.3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDouble\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e80.8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTriple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e13.2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote:\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eTotal weights of progenies at birth (PWB) and weaning (PWW)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe association tests between the type of birth of the ewe and its progeny were not significant in the dry and rainy seasons [Chi-square test: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.55 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.11, respectively). However, a statistically significant difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014) was observed between the number of lambs weaned during the dry and rainy periods. The average number of lambs weaned during the dry period was 1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.657, which was slightly greater compared to 1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.616 during the rainy period. This difference may be related to the reproductive seasonality of the ewes. Ewes giving birth in the dry season are likely conceived during the rainy season when better forage availability improves their body condition. This enhanced nutrition positively influences the hypothalamic-pituitary-gonadal axis, promoting greater follicular development and codominance, leading to more lambs born and weaned.\u003c/p\u003e\n\u003ch3\u003eIMPLICATIONS\u003c/h3\u003e\n\u003cp\u003eThe results of this study, although consistent with previous findings, bring important implications that advance current knowledge on the performance of hair sheep in semiarid environments. Classical studies have already indicated the existence of an optimal prolificacy level that maximizes the number of weaned lambs without excessively increasing neonatal losses (Owen et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). For example, in Cambridge sheep with high prolificacy, increasing litter size beyond a certain threshold resulted in higher lamb mortality and nonlinear gains in the number of weaned lambs, with a maximum reached at intermediate prolificacy levels. Similarly, Holm\u0026oslash;y et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) reported in Norwegian sheep that the risk of neonatal loss grows drastically in higher-order multiple births (triplets), especially in young ewes, suggesting biological limitations in maternal care and the ability to sustain large litters. These findings are corroborated under Brazilian semiarid conditions, while we demonstrate for the first time such effects in a locally adapted breed, reaffirming the generality of the trade-off between prolificacy and progeny survival across different environments.\u003c/p\u003e\u003cp\u003eThe novelty of this work lies in the use of a large dataset covering 13 Morada Nova herds in Brazil over a long longitudinal period. To our knowledge, no previous studies of comparable scale and scope have focused on this breed under real field conditions in semiarid systems. This evidence clearly shows that locally adapted breeds can sustain high reproductive performance in nutritionally and thermally challenging environments. Indeed, the use of locally adapted sheep breeds has been increasing in northeastern Brazil, as producers seek productive animals under climatic and nutritional stress (Landim et al., 2021; Silveira et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Hair sheep adapted to semiarid regions, such as the Morada Nova, present high rusticity, heat tolerance, and parasite resistance (Fa\u0026ccedil;anha et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) \u0026mdash; traits crucial for maintaining productivity in low-fertility soils and irregular climates with low rainfall.\u003c/p\u003e\u003cp\u003eMorada Nova sheep, in particular, are notable for their early sexual maturity, high fertility, prolificacy, and strong maternal ability, combined with a small adult body size that favors efficiency in low-input systems (Pereira et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Fa\u0026ccedil;anha et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These characteristics explain why local breeds such as Morada Nova are considered essential genetic resources for conservation: not only can they survive where exotic breeds would struggle, but they also sustain lamb production in both quantity and quality compatible with regional realities. This aspect is especially relevant in the context of future climate change. As reported by Silveira et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2026\u003c/span\u003e), the conservation of locally adapted genetic resources will be essential to preserve biodiversity, strengthen ecosystem resilience, and meet the challenges of food security under climate pressure.\u003c/p\u003e\u003cp\u003eFindings from other contexts reinforce this perspective. Molotsi et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), for example, in a literature review, reported that the indigenous Namaqua Afrikaner breed outperformed commercially selected breeds such as Dorper in the number of lambs weaned under adverse conditions, highlighting the adaptive advantage of native breeds in terms of survival and reproduction. These parallels underscore the strategic value of conserving and using local breeds such as Morada Nova in semiarid systems, not only from a cultural and biodiversity perspective but also as a pathway to improved sustainable productivity.\u003c/p\u003e\u003cp\u003eOur findings deepen the understanding of the balance between prolificacy and survival in restrictive environments. We observed that high prolificacy increases total lamb production but also imposes greater mortality risks, particularly in triplets and in young ewes. Conversely, moderate prolificacy (one to two lambs per birth) tends to maximize the number of lambs weaned, consistent with the optimal balance concept described by Wilson et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This pattern also aligns with Dwyer et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), who reported a reduction of approximately 1 kg in birth weight for each additional lamb in the litter, compromising lamb viability.\u003c/p\u003e\u003cp\u003eFrom a practical perspective, our results support strategies in both management and breeding that aim to balance productivity and survival. In management, this includes nutritional support during late gestation, peripartum assistance, and differentiated monitoring of primiparous and multiple-bearing ewes. In genetic improvement, progeny survival should be included as a criterion, alongside reproductive indices, emphasizing indicators such as the number of lambs weaned per mated ewe. This approach is more consistent with biological efficiency and system sustainability, as it values genotypes capable of producing a higher proportion of viable offspring.\u003c/p\u003e\u003cp\u003e In summary, although we confirm trends already described in other breeds and regions, this study advances knowledge by demonstrating these relationships in a locally adapted breed in the Brazilian semiarid, based on original field data. The insights presented here provide technical support for specific management and breeding recommendations, reinforce the importance of conserving the Morada Nova breed, and contribute to the development of more balanced, resilient, and sustainable sheep production systems under environmental constraints.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn Morada Nova ewes, multiple births increased productivity but reduced progeny survival, highlighting a clear trade-off between prolificacy and lamb viability. Moderate prolificacy proved to be more efficient for optimizing production under semiarid conditions, balancing total weaned lamb weight and survival rates. Furthermore, Morada Nova ewes tended to wean more lambs during the dry season than in the rainy season, reinforcing the influence of environmental seasonality on the breed\u0026rsquo;s productive and reproductive performance.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the procedures performed in the study followed the ethical principles of the Declaration of Helsinki\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRobson Mateus Freitas Silveira: data analysis, text editing and final review\u003c/p\u003e\n\u003cp\u003eAysllan Harlley Rodrigues Pereira: Conceptualization, methodology, data curation, data analysis, text editing and final review\u003c/p\u003e\n\u003cp\u003eMirela Balistrieri: text editing and final review\u003c/p\u003e\n\u003cp\u003ePaula Renata Cortat: text editing and final review\u003c/p\u003e\n\u003cp\u003eKleibe de Moraes Silva: text editing and final review\u003c/p\u003e\n\u003cp\u003eEula Regina Carrara: text editing and final review\u003c/p\u003e\n\u003cp\u003eConcepta Mcmanus: text editing and final review\u003c/p\u003e\n\u003cp\u003eAline Vieira Landim: Conceptualization, methodology, data curation, data analysis, text editing and final review\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work, the authors utilized ChatGPT to improve readability in specific sections of the manuscript. After using this tool, the authors carefully reviewed and edited the content as needed and take full responsibility for the publication\u0026apos;s content.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAguirre EL, Mattos EC, Eler JP, et al. Genetic parameters and genetic trends for reproductive traits of Santa In\u0026ecirc;s sheep kept in extensive environments in Brazil. J Anim Sci Livest Prod. 2017;1.\u003c/li\u003e\n\u003cli\u003eAmarilho-Silveira F, Dionello NJL, Mendon\u0026ccedil;a G, et al. Par\u0026acirc;metros gen\u0026eacute;ticos do peso total de cordeiros nascidos por ovelha em ovinos Texel. Rev Cient Rural. 2017;19.\u003c/li\u003e\n\u003cli\u003eBath GF, Malan FS, van Wyk JA. The \u0026apos;FAMACHA\u0026apos; ovine anaemia guide to assist with the control of haemonchosis. In: Proc 7th Annu Congr Livestock Health Prod Group, South African Vet Assoc, Port Elizabeth, South Africa; 1996.\u003c/li\u003e\n\u003cli\u003eDuguma G, Shoeman SJ, Cloete SWP, et al. Genetic and environmental parameters for ewe productivity in Merinos. S Afr J Anim Sci. 2002;32:154\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eDwyer C, Calvert S, Farish M, Donbavand J, Pickup H. Breed, litter and parity effects on placental weight and placentome number, and consequences for the neonatal behavior of the lamb. Theriogenology. 2005;63:1092\u0026ndash;1110. https://doi.org/10.1016/j.theriogenology.2004.06.003\u003c/li\u003e\n\u003cli\u003eFa\u0026ccedil;anha DAE, Ferreira J, Silveira RMF, Morais FX, Medeiros CC, Fac\u0026oacute; O, et al. Thermoregulatory responses, and acid\u0026ndash;base and electrolytic balance of indigenous ewes of different coat colour in an equatorial semiarid region. Anim Prod Sci. 2021;62(2):121\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eFac\u0026oacute; OF, Paiva SR, Alves LDRN, L\u0026ocirc;bo RNB, et al. Ra\u0026ccedil;a Morada Nova: origem, caracter\u0026iacute;sticas e perspectivas. Embrapa Caprinos e Ovinos. 2008;Documentos 75.\u003c/li\u003e\n\u003cli\u003eGrubb P, Jewell PA. The rut and the occurrence of oestrus in the Soay sheep on St Kilda. J Reprod Fertil. 1973;19:491\u0026ndash;502.\u003c/li\u003e\n\u003cli\u003eHaslin E, Allington T, Blumer SE, Boshoff J, Clarke BE, Hancock SN, et al. Management of body condition score between pregnancy scanning and lamb marking impacts the survival of triplet-bearing ewes and their lambs. Animals. 2023;13:2057. https://doi.org/10.3390/ani13132057\u003c/li\u003e\n\u003cli\u003eHolm\u0026oslash;y IH, Waage S, Gr\u0026ouml;hn YT. Ewe characteristics associated with neonatal loss in Norwegian sheep. Prev Vet Med. 2014;114(3-4):267\u0026ndash;75. https://doi.org/10.1016/j.prevetmed.2014.02.007\u003c/li\u003e\n\u003cli\u003eLockwood A, Allington T, Blumer SE, Boshoff J, Clarke BE, Hancock SN, et al. Decreasing mob size at lambing increases the survival of triplet lambs born on farms across southern Australia. Animals. 2023;13:1936. https://doi.org/10.3390/ani13121936\u003c/li\u003e\n\u003cli\u003eLandim, A.V., Peres, M.C.R., Costa, H.H.A. \u003cem\u003eet al.\u003c/em\u003e Feeding restriction in the pre and postpartum period of hair ewes raised in the semi-arid region: implications on performance and carcass traits of the progeny. \u003cem\u003eTrop Anim Health Prod\u003c/em\u003e \u003cstrong\u003e54\u003c/strong\u003e, 303 (2022). https://doi.org/10.1007/s11250-022-03279-4 \u003c/li\u003e\n\u003cli\u003eL\u0026ocirc;bo, R.N.B. 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Front Anim Sci. 2025;6:1497380. https://doi.org/10.3389/fanim.2025.1497380\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"productive efficiency, reproductive efficiency, local breeds, prolificacy","lastPublishedDoi":"10.21203/rs.3.rs-8123627/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8123627/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDomesticated breeds living in resource-limited environments offer an opportunity to investigate life-history trade-offs between offspring number, offspring survival, and seasonal variability in resources. We used long-term data from 13 Morada Nova sheep flocks monitored between 1999 and 2015 in the Brazilian semi-arid region to evaluate how prolificacy and seasonality shape maternal reproductive output and progeny survival. For each ewe lambing event, we quantified total progeny weight at birth (PWB) and weaning (PWW), as well as survival rates at birth (PSRB) and weaning (PSRW), and classified births as occurring in the dry or rainy season. Ewes with single births showed lower PWB and PWW, but higher PSRB and PSRW, than ewes with multiple births (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). When the number of progeny at birth was included as a covariate, each additional lamb was associated with an increase of 0.93 kg in PWB and 2.49 kg in PWW (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), but also with a reduction of 6 percentage points in PSRB and 17 percentage points in PSRW, revealing a strong trade-off between litter size and offspring survival. Ewes with multiple births were more productive in terms of total kilograms of lamb weaned, despite lower survival rates per offspring. We also found that Morada Nova ewes tended to wean more lambs during the dry season than during the rainy season, suggesting that reproductive output is synchronized with local patterns of resource availability and management. Together, these results highlight how life-history trade-offs and environmental seasonality interact to shape reproductive strategies in a locally adapted sheep breed under semi-arid conditions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e","manuscriptTitle":"Prolificacy–survival trade-off in Morada Nova sheep under Brazilian semiarid conditions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-28 08:32:41","doi":"10.21203/rs.3.rs-8123627/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-11-20T21:28:33+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-20T18:05:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-18T04:10:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Animal Health and Production","date":"2025-11-15T12:48:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f92c7f45-8bde-488f-ab06-b06e643a964e","owner":[],"postedDate":"November 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T14:22:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-28 08:32:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8123627","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8123627","identity":"rs-8123627","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}