Universidade de Trás-os-Montes e Alto Douro

The Asinina de Miranda donkey breed (Equus asinus):

demographic analysis and

characterization of the reproductive cycles

PhD Thesis in Veterinary Sciences – Clinics

Miguel Nuno Pinheiro Quaresma

Supervisor: Professora Doutora Rita Maria Payan Carreira

Vila Real, 2015

This work was partially sponsored by the Portuguese Science and Technology Foundation (FCT) under the Project PEst- OE/AGR/UI0772/2011 and 2014.

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I declare that the contents of this thesis are my own work and that they have not been presented to any University other than the University of Trás-os-Montes and Alto Douro.

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Abstract

Donkeys play a very important role in the ecological maintenance of rural areas. The interest in their conservation and characterization has increased over the last years. The main purpose of this work was to augment the knowledge on the demographic and reproductive characteristics of the Asinina de Miranda breed, giving scientific support to implement more effective conservation and breeding strategies. These objectives were accomplished through different approaches. For the purpose of demographic analysis, the Foal and Studbooks were analysed, along with a survey to donkey owners. To predict the progression of the breed under the current management system and to identify variables vital for the breed survival, a population viability analysis (PVA) program was applied, showing that the breed is currently at risk of extinction. The pedigree and herd records of this donkey breed were also analysed to identify genealogical and human factors that may affect the breed genetic diversity in the future. The most critical factor for breed survival was the percentage of females breeding per year but the actual percentage needed was dependent of the carrying capacity of the breed. Reducing female mortality, age at first offspring production, assuring the register on the Studbook and tracking of the foals will also significantly foster the breed recovery and maintenance. The overall neonatal mortality for the first month of life was 8.92%, being lower in females (6.51%) than in males (12.0%). The foal neonatal mortality was unevenly distributed throughout the year and lowers when females were 5 to 15 years old (8.06%), compared to younger than 4 years or older than 16 years at foaling (respectively 10.3% and 14.1%). The main identified factors for inbreeding risk were the low breeding rates, the low number of males and their unequal contribution to the genetic pool, the unequal contribution of the herds to genetic pool and the advanced age of herd owners.

For the purpose of the reproductive cycle characterization of the jennies a group was followed, both during the breeding and non-breeding seasons, by ultrasonography and serum progesterone determinations for two years. The changes of body condition score (BCS) were regularly checked to test its putative effect on the ovarian activity. To access BCS, different methods were compared to find the one more sensitive to the changes in body adiposity. BCS was evaluated both by visual and palpation appraisal and by real time ultrasonography (RTU) of subcutaneous fat and thoracic wall tissue depths. A significant correlation was established between BCS and all RTU measurements. The study also showed that RTU measurements

- vii - have a logarithmic relationship with BCS and that RTU, combined with image analysis, permits accurate fat and tissue depths measurements to monitor fat reserves in jennies.

During the breeding season, the interovulatory interval was 23.8 ± 0.551 days, with diestrus and estrus lasting 17.9 ± 0.462 and 6.65 ± 0.298 days, respectively. Age and BCS affected the length of the interovulatory intervals in the breeding season; BCS also influenced the diestrus length and the time in heat after ovulation. The incidence of single, double and triple ovulations was 57.58%, 36.36% and 6.06%, respectively. Multiple ovulations extended the interval from beginning of estrus to ovulation, but had no effects on the other periods. When combined with age, higher BCS also affected the ovulation rate. Divergence of the dominant follicle occurred around day -8.7 (day 0 = ovulation), independently of the ovulation rate. The dominant follicle was larger at divergence in single ovulators than in multiple ovulators (19.18 ± 0.968 mm vs. 18.05 ± 1.16 mm). Similarly, the maximum follicular diameter before ovulation was larger in single ovulatory cycles than in multple ovulatory cycles (40.2 ± 1.41 mm vs. 37.2 ± 0.825 mm, respectively). The daily growth rate of dominant follicles was independent of the ovulation rate for the period preceding heat or during heat.

The study of the reproductive patterns in the non-breeding season relied on the surveillance of the jennies reproductive cycles from September to May. It was found that 75% (9:12) of the females presented disruption of the normal pattern of ovarian activity during this period. Loss of the normal cyclicity included anestrus (41.7%), silent ovulatory estrus (25%), or persistency of corpus luteum (8.3%). Only 25% (3:12) of the females retained regular cyclicity during this season. The study also showed that disrupted ovarian cycles might be triggered in jennies if BCS decreases below a given threshold between autumn equinox and winter solstice, suggesting that BCS modulates the seasonal influences on ovarian cyclicity in jennies.

Keywords: Donkey, Population Viability Analysis, Pedigree, Reproductive cycles, Seasonality, Body Condition Score.

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Resumo

Os asininos desempenham um papel fundamental no equilíbrio ecológico das zonas rurais. O interesse na sua conservação e caracterização aumentou nos últimos anos. O principal objetivo deste trabalho foi o de aumentar o nível de conhecimento da demografia e reprodução da população da raça Asinina de Miranda, fornecendo suporte científico à implementação de estratégias de conservação e maneio. Estes objetivos foram alcançados através de uma aproximação multidisciplinar. Para a análise e caracterização demográficas, analisaram-se os Livros Genealógico e de Nascimentos, complementando-se a informação obtida com um inquérito aos proprietários dos animais. No sentido de prever a progressão da raça sob as atuais condições de maneio e de identificar as variáveis vitais à sua sobrevivência, utilizou-se um programa informático de análise de viabilidade de população, que mostrou que a raça está atualmente em risco de extinção. Os registos genealógicos e dos criadores foram igualmente analisados para identificar fatores humanos e genealógicos que possam vir a afetar a diversidade genética da raça. O principal fator limitante para a sobrevivência da raça foi a percentagem anual de fêmeas em reprodução, estando esta percentagem dependente da população existente. Outros fatores importantes para a recuperação e manutenção da raça foram a redução da mortalidade das fêmeas, idade ao primeiro parto, registo no Livro Genealógico e rastreabilidade dos animais. A taxa de mortalidade dos burrancos no primeiro mês de vida foi de 8,92%, mais baixa nas fêmeas (6,51%) que nos machos (12%). A mortalidade neonatal esteve distribuída de forma não uniforme ao longo do ano, sendo igualmente menor em fêmeas com idades ao parto compreendidas entre os 5 e 15 anos (8,06%), em comparação com as fêmeas de idade inferior a 4 anos ou superior a 16 anos (10,3% e 14,1%, respetivamente). Os principais fatores de risco para o aumento da consanguinidade foram as baixas taxas de reprodução, o reduzido número de machos e a sua desigual contribuição para a genética populacional, a contribuição desigual dos diferentes criadores para a genética da população e a idade avançada dos proprietários.

No que concerne à atividade reprodutiva das fêmeas, um grupo foi seguido durante as estações reprodutiva e não-reprodutiva, por ecografia e medições da progesterona sérica durante dois anos. Foram regularmente monitorizadas as variações na condição corporal para estimar os seus eventuais efeitos na atividade ovárica, com um estudo comparativo de diferentes métodos de avaliação da condição corporal. Esta foi avaliada por métodos de observação visual com palpação e por mensuração da espessura da gordura subcutânea e da

- ix - profundidade dos tecidos subcutâneos da parede torácica, com recurso à ecografia. Encontrou-se uma correlação significativa entre a condição corporal e todas as medições ecográficas. As medições ecográficas de profundidade dos tecidos subcutâneos têm uma relação logarítmica com a avaliação da condição corporal tradicional. A ecografia combinada com a análise de imagem permite uma medição fidedigna da profundidade dos tecidos e gordura subcutâneos para a monitorização das reservas de gordura nas burras.

Na estação reprodutiva, o intervalo inter-ovulatório foi de 23,8 ± 0,551 dias; o diestro e o estro apresentaram uma duração de 17,9 ± 0,462 e 6,65 ± 0,298 dias, respetivamente. Durante este período a duração dos intervalos inter-ovulatórios foi influenciada pela idade e condição corporal; esta última influenciou ainda a duração do diestro e o tempo em cio após ovulação. A incidência de ovulações simples, duplas ou triplas foi de 57,58%, 36,36% e 6,06%, respetivamente. As ovulações múltiplas aumentaram a duração do intervalo entre o início do estro e a última ovulação do ciclo, mas não interferiram com a duração das outras fases do ciclo. Quando combinada com a idade, uma condição corporal mais elevada afetou igualmente a taxa de ovulação. A divergência do folículo dominante ocorreu cerca 8,7 antes da ovulação, independentemente da taxa de ovulação. O folículo dominante era maior à divergência em ovulações simples do que em ovulações múltiplas (19,18 ± 0,968 mm vs. 18,05 ± 1,16 mm). De igual modo, o tamanho folicular máximo antes da ovulação era maior nas ovulações múltiplas que nas simples (40,2 ± 1,41 mm vs. 37,2 ± 0,825 mm). A taxa de crescimento dos folículos dominantes foi independente da taxa de ovulação, tanto no período antes do cio como após o seu início.

Para o estudo dos padrões reprodutivos na estação não-reprodutiva, as fêmeas foram seguidas de setembro a maio. Verificou-se que 75% (9/12) destas fêmeas apresentaram alterações do padrão normal de atividade ovárica durante este período. A perda da ciclicidade normal apresentou-se como anestro (41,7%), estro silencioso com ovulação (25%) ou persistência do corpo lúteo (8,3%). Somente 25% (3/12) das fêmeas mantiveram ciclicidade regular. Este estudo revelou ainda que a interrupção dos ciclos ováricos pode ser desencadeada se a condição corporal descer abaixo de um determinado limiar entre o equinócio do outono e o solstício de inverno, sugerindo que a condição corporal modula as influências sazonais da ciclicidade ovárica em burras.

Palavras-chave: Asininos, Análise de Viabilidade de População, Genealogia, Reprodução, Sazonalidade, Condição Corporal.

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Para os meus pais

Para os meus filhos

Para a Lina

“Crescemos sacrificando o que somos hoje pelo que podemos ser amanhã”

Anónimo

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Agradecimentos / Acknowledgments

Começo por agradecer à Universidade de Trás-os-Montes, na pessoa do seu Magnifico Reitor, a cedência dos meios que me permitiram realizar este trabalho, assim como ao Departamento de Zootecnia por ter acolhido os animais e os ter mantido durante o estudo.

O meu principal agradecimento vai para a Professora Doutora Rita Payan Carreira pela dedicação que colocou neste trabalho e pela preciosa orientação.

Ao Professor Doutor Severiano Silva agradeço, além da sua simpatia, toda a disponibilidade, assim como a oportunidade de colaboração que permitiu diversificar, estender e enriquecer os horizontes deste trabalho.

Ao Professor Doutor Jorge Colaço pela inestimável ajuda com estatística e com sábios conselhos na investigação.

À Professora Doutora Ângela Martins, pela sua valiosa colaboração na elaboração dos capítulos dedicados à análise demográfica. A sua simpatia e disponibilidade foram um incentivo enorme.

Ao Professor Doutor João Brandão, pela amizade, pela partilha de ideias e pelo entusiasmo contagiante no nosso esforço de investigação em torno dos asininos.

Ao Dr. Celso Santos pelo auxílio laboratorial na medição da progesterona.

Ao Professor Doutor Luis Ferreira pela preciosa e desinteressada ajuda na elaboração das figuras.

À Cristina por todo o carinho e ajuda no meu trabalho prático na UTAD e em Miranda. Sem a tua ajuda não sei se o teria feito. Este trabalho é também teu.

Ao Dr. Miguel Nóvoa da AEPGA, pela inestimável ajuda com os animais, proprietários e com os dados do Livro Genealógico.

À Associação para o Estudo e Proteção do Gado Asinino (AEPGA), pela colaboração na realização do trabalho de campo e pelas fêmeas cedidas para o estudo.

À Drª. Sara Mora, Drª Raquel Paiva, Dr. Jesus Buil Garcia e Drª Tamara pela ajuda de campo na “nossa” Miranda do Douro.

- xiii - À Claudia Costa, à Joana Braga, ao Manuel Campião, ao Nuno Martins, à Teresa Nóvoa, à Ana Ramalho pela ajuda no campo em Miranda e por partilharem comigo o amor a estes animais.

A todos os alunos do MIMV que me ajudaram nas ecografias e tratamento das burras, com uma palavra especial para a Ana Margarida, o Rafael Correia, a Catarina Pereira e outros, que me ajudaram nas ecografias e tratamento das burras, nas noites gélidas e dias de calor infernal de Vila Real. Uma palavra especial ainda para a minha amiga Sara Ramalheira Martins pelo Template da dissertação, e, principalmente, por cada um dos seus sorrisos.

A todos os colegas da Área Hospitalar de Animais de Produção e Equinos do Hospital Veterinário que partilharam comigo estes anos de duro trabalho profissional, com uma palavra especial, que os outros perdoaram porque sabem também o que sinto por eles, à minha querida amiga Joana Elias e ao Alexandre Triguinho.

Ao pessoal do CEGA que prestou uma necessária ajuda nos cuidados das burras, com um agradecimento especial para o Eng. Paulo Fontes.

A todos os Amigos que fizeram parte da jornada até agora e que tenho a certeza que continuarão a fazer.

A todos e a cada um dos criadores e proprietários de burros, o meu mais profundo agradecimento, não só pela disponibilidade sempre presente que me permitiu observar um tão grande número de animais durante o trabalho de campo, mas principalmente porque são eles os principais responsáveis pela preservação de um património tão único. Obrigado pela forma como sempre me receberam em cada casa e em cada aldeia, obrigado por cada história partilhada, razões que fazem com que cada dia no Planalto valha a pena.

Ao meu pai por ser o meu herói e o ombro que eu sempre sei estar ali.

À minha mãe, pela força que me dá e pelo que tenho dela.

À minha querida irmã por ser uma das luzes e exemplo da minha vida.

Para os meus filhos, meus heróis e meu orgulho.

Para toda a minha família, um agradecimento tão especial, por me terem sempre apoiado tanto em todas as minhas decisões e em todos os meus sonhos.

Para a Lina, por tudo o que somos há mais de 20 anos. Uma caminhada em que ela sempre esteve para mim.

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Uma palavra especial e saudosa ao meu avô José Inácio Quaresma, um homem superior com uma vida que me serve de exemplo nos princípios e valores da vida e à minha querida avó Ana, uma heroína que criou sozinha 9 filhos e que permitiu também a cada um deles e dos seus netos serem o que são hoje.

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Index of figures

Figure 1. Neighbour-joining tree for seven Iberian donkey breeds, based on nucleotide divergence between populations (Adapted from Aranguran-Mendez et al., 2004). ______6

Figure 2. Total of Asinina de Miranda foals born each month during a ten years period, from 2002 to 2012.______38

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Contents

1. Background ______1 1.1. The Donkey ______3 1.1.1. The origin of the donkey species ______3 1.1.2. Donkeys situation worldwide ______4 1.1.3. The Asinina de Miranda breed and donkeys situation in Portugal ______5 1.2. Demographic analysis ______7 1.2.1 Population viability analysis ______9 1.2.2 Pedigree analysis ______10 1.3. The reproductive physiology of female donkeys ______11 1.3.1. Donkey sexual behaviour ______16 1.3.2. Reproductive efficiency in equids ______17 1.3.3. Body Condition Score ______18 2. Aims of the thesis ______21 3. Material and Methods ______25 3.1. Demographic analysis (paper I-II) ______27 3.2. Animals, Handling and Housing (papers III-V) ______28 3.3. Assessment of BCS (paper III) ______29 3.4. Characterization of the reproductive activity (papers IV and V) ______29 3.4.1. Serum progesterone determination ______30 3.4.2. Ultrasound survey of the ovarian pattern ______30 3.4.3. Descriptors definition ______31 3.5. Statistical analysis in non-population studies (papers III-V) ______32 4. Main results ______35 4.1. Demographic analysis (papers I-II) ______37 4.1.2. Population viability analyses (paper I) ______38 4.1.2. Pedigree analysis (paper II) ______39 4.2. Establishment of a sensitive method for BCS analysis (paper III) ______40 4.3. Characterization of the ovarian pattern in the breeding season (paper IV) ___ 40 4.4. Characterization of the ovarian pattern in the non-breeding season (paper V) 42 5. General discussion ______43 6. Main conclusions ______51

- xix - 7. Future research ______57 8. References ______61 Appendices

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Appendices

Papers I-V

The present thesis is based on the following papers, which will be referred to in the text by their Roman numerals:

I. Quaresma M, Martins, AMF, Rodrigues JB, Colaço J, Payan-Carreira R (2014) Viability analyses of a donkey breed endangered of extinction: the case of the Asinina de Miranda (Equus asinus). Animal Production Science, http://dx.doi.org/10.1071/AN13307.

II. Quaresma M., Martins AMF, Rodrigues JB, Colaço J, Payan-Carreira R (2013) Pedigree and herd characterization of a donkey breed vulnerable to extinction. Animal 8, 354-359.

III. Quaresma M, Payan-Carreira R, Silva S. (2013) Relationship between ultrasound measurements of body fat reserves and body condition score in female donkeys. The Veterinary Journal 197, 329-334.

IV. Quaresma M, Payan-Carreira R (2015). Characterization of the estrous cycle of Asinina de Miranda jennies (Equus asinus). Theriogenology 83, 616-624.

V. Quaresma M.; Payan-Carreira, R; Silva, S. (2013). Effects of body condition on ovarian activity patterns in the winter season in Asinina de Miranda donkeys (Submitted).

Papers I to III are reproduced under the Publishers´ policies for copyright and self-archiving.

Other works have been produced during my PhD studies, either in the forms of full paper, short communications or communications in scientific events. They might be used in the thesis, during the introduction or the discussion of results, but were only listed in my Curriculum vitae.

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Abbreviations

%TF Percentage of males from outside the farm AEPGA Associação para o Estudo e Proteção do Gado Asinino AGE Average age of parents at all offspring birth ANOVA Analysis of variance BCS Body condition score BW Body weight CV Coefficient of variation DR Dispersal regions FAO Food and Agriculture Organization of the United Nations FCT Portuguese Science and Technology Foundation FSH Follicle-stimulating hormone GCI Genetic conservation index HR Home region INE Instituto Nacional de Estatística INT Average age of breeder parents at descendants’ birth LH Luteinizing hormone MHz MegaHertz mtDNA Mitochondrial deoxyribonucleic acid No. Number NH Number of herds OFIC Ovulation fossa inclusion cyst P4 Progesterone PVA Population viability analysis R Pairwise correlation coefficient r2 Determination coefficient RAM Asinina de Miranda breed rsd Residual standard deviation RTU Real time ultrasonography SD Standard deviation SE Standard error SEM Standard error of the mean SF Subcutaneous fat

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SFR Subcutaneous fat at rump SFW Subcutaneous fat at withers SFT Subcutaneous fat at tail head SFTh Subcutaneous fat at thorax TD Thoracic wall tissue depth TDBrib6 Thoracic wall tissue depth between the 6th and 7th ribs TDBrib13 Thoracic wall tissue depth between the 12th and 13th ribs TDOrib6 Thoracic wall tissue depth over the 6th rib TDOrib13 Thoracic wall tissue depth over the 13th rib UTF Use of bought stallions UTP Use of in-born stallions

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1. Background

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Background

1. Background

1.1. The Donkey

1.1.2. The origin of the donkey species

The close symbiotic relationship of Homo sapiens and domestic animals over millennia is changing. Accompanied by domestic animals, mankind thrived worldwide over the last 12 000 years, increasing domestic animal biodiversity via adaptation to many environmental challenges, resulting in about 6 000 breeds within only a small number of species. However, during the last 50 years of the 20th century, about one fifth of these livestock breeds have become extinct. This lost in diversity is sometimes presented as a choice of no deep consequence, even though we are in the process of losing valuable genetic resources and our historic heritage (Hodges, 2006). The domestic donkey (Equus asinus) is one of the two domestic species of the genus Equus, along with the horse (Equus caballus). According to mtDNA analysis, differences between the donkey and the horse suggest that the evolutionary separation of the two species occurred 9 million years ago (Xu et al., 1996), distinctly earlier than the 3 to 5 million years that paleontological data pointed before (Lindsay et al., 1980).

Domestication of the donkey might have responded to the needs of pastoralists and other societies in the North-eastern region of Africa due to the desertification of the Sahara (Beja- Pereira et al., 2004). The domestication of the donkey marked a major cultural shift, allowing extensive movement and trade to the early sedentary societies, transforming ancient transport systems in Africa and Eurasia (Clutton-Brock, 1999). The donkeys’ ability to carry heavy loads trough arid lands enabled pastoralists to move farther and more frequently (Rossel et al., 2008).

Archaeological evidences suggest that donkeys were domesticated around 6 000 years ago, in a non-linear and prolonged process with multiple locations (Beja-Pereira et al., 2004; Rossel et al., 2008, Kimura et al., 2011). It is now widely accepted that the wild origins of the domestic donkeys were the African wild asses, the Equus africanus africanus (Nubian wild ass) and the Equus africanus somaliensis (Somali wild ass) (Epstein, 1984; Camac, 1989). These subspecies were estimated to have diverged 0.303 to 0.910 million years ago into two wild populations geographically separated (Beja-Pereira et al., 2004). Asiatic wild asses were excluded as ancestors of the domestic donkey by genetic testing (Lei et al., 2007), despite the earlier proposed theory for a Near-East domestication of donkeys (Clutton –Brock, 1999).

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Genetic studies of modern donkeys worldwide showed the existence of two distinct mitochondrial halogroups, termed Clades 1 and 2, that are distinct in the two recognised ancestor lines: Nubian wild asses present Clade 1 halogroup, while Clade 2 halogroup, initially attributed to the Somali wild ass, remains nowadays of unascertained origin (Kimura et al., 2011).

The Nubian ass (Equus asinus africanus) is at the origin of the North African breeds, as well as of the Andaluza (from South of the Iberian Peninsula) and Majorera (from the Canary Islands) breeds, both of grey-brown coat (García Dory et al., 1990; Yanes, 1999; Jordana and Avellanet, 2002). On the other side, the Somalian ass (Equus africanus somaliensis) have been proposed to originate the Southwest Asia donkeys and probably also the majority of European breeds, including the Catalonian, Mallorquina, Encartaciones and Zamorano- Leones, the four black coated breeds from north of the Iberian Peninsula (Epstein, 1984; Aranguren-Mendez et al., 2001, 2002, 2004).

1.1.2. Donkeys situation worldwide

Among the domestic animals, the donkey still plays an important role in the development of human society (Chen et al., 2010). In 1996, there was an estimated donkey population of 44 million animals worldwide, most of them maintained for work. In 2007, FAO reported a decrease of this number to 41 millions. However, not all countries maintain accurate estimates of donkey populations, because donkey ownership is seldom registered. The decline in the Southern Europe donkey population, namely in Mediterranean region, was more pronounced than in other regions of the world. This issued from the development of modern, highly mechanized agriculture practises that reduced the donkeys’ importance for work. Although donkeys can be milked, this is not common; also, only few countries prize donkeys’ meat. Consequently, food-based donkey products are of limited interest and, in most industrialized countries, donkeys are kept specifically for recreation, breeding, showing or companionship. Some farmers keep donkeys for guarding sheep (Starkey and Starkey, 1996).

Donkeys may be found in almost all world regions but, as other lower numbered species, present a less uniform distribution pattern compared to cattle, sheep or chickens (FAO, 2013). Donkey populations have declined dramatically in most industrialized countries of Europe (Ivankovic et al., 2002; Barbosa, 2003) and North America (Starkey and Starkey, 1996) prompting the assumption that donkey populations will also decline rapidly in the emerging

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industrialized nations, following its rapid urbanization; yet, such countries also have large rural populations of low incomes, which may continue to benefit from donkeys for local transport (Fielding, 1991; Starkey and Starkey, 1996; Lei et al., 2007; Zhang et al., 2010). Animal traction is increasing in importance in parts of Africa; thereby the species decline in draught is far from universal. Donkeys continue to serve as pack animals even in parts of Europe and the Caucasus. Moreover, grazing donkeys can play a role in landscape management and fire prevention (FAO, 2007). Even in countries where they have a major economic importance to the large rural population, like Mexico, the donkeys have traditionally been ignored (Lopez-Lopez et al., 2005). There is a justification to contribute to an objective assessment of the donkey as a low cost effective source of renewable power. One aspect of this assessment will, of necessity, include the need to have a more complete knowledge of the reproductive characteristics of the donkey, particularly of the female (Fielding, 1988).

1.1.3. The Asinina de Miranda breed and donkeys situation in Portugal

In Europe, asinine populations went from 3 million in 1944 to less than 1 million in 1994. As a consequence, many autochthonous donkey breeds face extinction (Starkey and Starkey, 1996). Although in 1925 there were accounted 243 702 donkeys in Portugal (Sttau-Monteiro, 1933), its number decreased to less than 15 000 in 2009 (INE, 2011). Conversely, with the evolution of the rural Portuguese agriculture and socio-economic conditions, donkeys re- assume a new, renewed utility (Barbosa et al., 2003). Socio-economic reasons preserved the Asinina de Miranda breed in the Northeast Portugal; some of the agricultural work in this mountain region can only be done with the help of these animals (Barbosa et al., 2003).

The Asinina de Miranda donkey type was first recognised by Samões (2000), who characterized the population of donkeys on the Douro International Natural Park. In 2002, the breed was officially recognized by the national authorities that created the breed Studbook, to be maintained by the Associação para o Estudo e Proteção do Gado Asinino (AEPGA), in Miranda do Douro (Quaresma et al., 2005). Considering the studies by Aranguren-Mendez et al. (2001, 2002 and 2004), and the close phenotypic and geographic relation between the Portuguese Asinina de Miranda and the Spanish Zamorano-Leonês breeds, the neighbour joining tree for the Iberian donkey breeds would place the Asinina da Miranda as described on Figure 1.

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Figure 1. Neighbour-joining tree for seven Iberian donkey breeds, based on nucleotide divergence between populations (Adapted from Aranguran-Mendez et al., 2004).

In 2003, a preservation plan was initiated for the Asinina de Miranda, analogous to the one done for the Catalonian breed (Jordana and Folch, 1998), with different measures occurring simultaneously: 1) general description of the population; 2) census and individual registry of the animals; 3) morphologic and genetic characterization of the animals, with pedigree analysis; 4) health and welfare characterization of the population; 5) in situ conservation program, incrementing the population size, maximizing the influence of all founders, keeping the maximum genetic diversity. Several steps had commenced then, such as the points 2, 3, 4 and 5; others have been postponed in time. Some recent studies provided the necessary scientific support to this proposal (Barros, 2013; Couto, 2013; Quaresma et al., 2013b; Rodrigues, 2013) and tried to address more specific topics.

For a breed recovery and maintenance, a high reproductive efficiency must be attained. When the breed is endangered, the production of more individuals is needed and, after recovery, the equilibrium between produced and harvested animals is necessary to maintain a viable population. This efficiency depends on genetic factors, as inbreeding depression and the species or breed limitations for offspring production (Al-Atiyat, 2009; Colli et al., 2012). It is also dependent of natural factors as the dual effect of body condition score and nutrition or seasonality (Ferreira-Dias et al., 2005; Aurich, 2011). At last, the success of any breed is highly dependent on its capacity to make the stockholders produce and maintain the animals

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for economic or cultural reasons (Gandini and Villa, 2003; Reist-Marti et al., 2006; Hoffmann, 2010; Colli et al., 2012).

1.2. Demographic analysis

In order to secure population viability, management strategies must be sensitive to local ecological, social and economic conditions. Understanding the basic population dynamics is fundamental to a successful conservation program (Armbruster and Lande, 1993; Duchev and Groeneveld, 2006). Also, to create an effective conservation program there is the need to know where a breed stands in terms of population viability and genetic diversity, which success strongly depends on the regular evaluation of parameters characterizing the target population (FAO, 2007). This allows a better access to the critical level of endangerment of a breed, being useful to evaluate the success of carried out conservation strategies and to suggest new ones to be implemented in the future (Pinheiro et al., 2013).

One of the first stages of any conservation program is the evaluation of genetic diversity within a breed (Ciampolini et al., 2007), since long term survival of a population depends on the maintenance of sufficient genetic variation for individual fitness, population adaptability and fertility (Falconer, 1989; Meuwissen and Woolliams, 1994; Lacy et al., 1995; Falconer and Mackay, 1996; Fernandez et al., 2000; Valera et al., 2000; Frankham et al., 2004). Breeds that suffered substantial decline in population size may present high levels of inbreeding, resulting in inbreeding depression and aggravated risk of extinction, since the loss of heterozygosity is usually inversely proportional to population size (Ghafouri-Kesbi, 2010).

Development of selection and mating criteria for controlling inbreeding are based on relationships obtained from pedigrees, on the principle of reducing the average coancestry among selected individuals for mating (Fernandez et al., 2000). In a small population as the Asinina de Miranda it will be hard to maintain a long time mating process using only unrelated animals in mating decisions. To minimize the negative impact of an increase of overall inbreeding, reduction of effective population size and, consequently, loss of genetic variability, a mating policy must be implemented pursuing the equal contribution of the maximum number of animals from both genders to the next generation (Falconer and MacKay, 1996; Folch and Jordana, 1998).

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Inbreeding depression is a major concern in populations that are small, isolated or have low intrinsic population growth rate (Allendorf and Ryman, 2002); it corresponds to a reduction of a population genetic fitness as a consequence of crossing closely related individuals. To avoid inbreeding depression and foster sufficient genetic diversity for adaptive change to occur, it is necessary a minimum number of animals. The effective number may vary with the author, and have to be adapted to each situation. Waples (2002) defend an effective population size (Ne) of at least 100 individuals to census population sizes of about 500 to 1000 animals, while Lande (1988) suggest that an effective population size of 550 individuals is necessary to maintain the typical levels of genetic variability for quantitative traits in a population. Rasch and Herrendorfer (1990; in FAO, 1992) recommended a Ne of 200 for maintaining a genetically constant population over 50 generations. Contrasting, Brem et al. (1990; in FAO, 1992) defend that a population is not threatened when the effective population size is over 50, for a minimum of 10 males. Still, for effective selection, a Ne of at least 100 is necessary (FAO, 1992), or as defended by Meuwissen and Woolliams (1994), the critical size for Ne is between 50 and 100.

Within the framework of breed conservation, the combination of genetic diversity and kinship information provides important baseline data for future breed conservation efforts, especially for critically endangered breeds (Gomez et al., 2012). In human managed populations, selection is the main factor responsible for the loss in genetic diversity (Hedrick, 2000; Ghafouri-Kesbi, 2010). Where only a few phenotypically superior animals are allowed to contribute to the gene pool of the next generation, a genetic bottleneck is imposed on the population (Allendorf, 1986). In such situations, breeding management measures are essential to assure that the effective population size does not go under acceptable levels (Foose et al., 1986).

The studies on genetic diversity of donkey breeds using molecular markers showed an underestimation of the inbreeding coefficient by pedigree analysis alone, probably due to the lack of genealogical records. Several studies have been performed on the demographic and genealogical structure of donkey breeds in Spain (Folch and Jordana, 1998; Jordana et al., 1999; Jordana et al., 2001; Aranguren-Mendez et al., 2002; Guttiérez et al., 2005), Italy (Cecchi et al., 2006; Ciampolini et al., 2007), and in other countries of the Mediterranean area (Ivankovic et al., 2002; Vranova et al., 2011).

- 8 - Background

1.2.1 Population viability analysis

Population viability analysis has become a commonly used tool in endangered populations’ management. However, one must be aware that it should be treated as a model and that models are simplifications of the real world (Reed et al., 2002); therefore, predictions are only probabilistic (Shaffer, 1990). Despite these caveats and limitations, PVA remains an important tool for conservation biologists in effecting positive management actions (Reed et al., 2002). These analyses uses stochastic models with fluctuating population size and varying demographic parameters to predict population size and the probability of persistence for a defined period, under specific conditions (Soulé, 1987). PVA is mostly appropriate for comparing the relative effects of potential management actions on population growth or persistence (Marmontel et al., 1997; Reed et al., 2002). For most endangered species, an extinction risk of less than 5% in 100 years is taken as an acceptable goal for preservation from extinction (Marmontel et al., 1997). A desired population level is one that is unlikely to fall into an extinction process (Lacy, 1993).

There is no single mathematical process that constitutes PVA, but all approaches have in common an assessment of a population’s risk of extinction or its projected growth, either under current conditions or expected from proposed management. Results should be presented to express the range of possible results and the uncertainty associated within this range, rather than as a single value, such as mean time to extinction (Reed et al., 2002). In PVA, the mean is typically larger than the median, so the median time to extinction might be more appropriate for reporting population persistence (Mills et al., 1996).

Sensitivity analysis can complement the predictions that arise from PVA by providing insights into factors that most affect population growth or extinction probability and can also benefit researchers by identifying factors whose estimation is most critical for population- level studies (Reed, 2002). Because the insights provided by sensitivity analysis can change with variations in a population’s carrying capacity (Beissinger and Westphal, 1998; Reed, 2002), a small measured sensitivity does not necessarily mean that a parameter has always such an effect on population growth (Reed et al., 2002). For example, age-structure, age- specific mortality, and age-specific reproduction are usually key factors determining the ability of a population to persist (Marmontel et al., 1997).

Vortex 9.99c is a software program often used for PVA that uses a Monte Carlo simulation of the effects of both deterministic and stochastic events (demographic, environmental and

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genetic) on populations (Lacy et al., 1993, 2009). Demographic stochasticity includes random variation in demographic parameters, whereas environmental stochasticity refers to variation in the environment external to a population (Simberlof, 1988). Nevertheless, this distinction is somewhat arbitrary: the first affects only very small populations whereas the latter may be significant to larger populations (Goodman, 1987).

1.2.2 Pedigree analysis

The concept of pedigree analysis goes back to the work of Wright and McPhee (1925). Later on, James (1972) described a procedure on how to compute genetic contributions of individuals to later generations from pedigrees. The pedigree analysis allows population managers to assess the genetic structure of a population and to plan appropriate breeding strategies targeting a balance between genetic response and the loss of genetic diversity (Ghafouri-Kesbi, 2010). It is considered a useful tool to describe genetic variability within populations and its evolution across generations (Boichard et al., 1997). Pedigree analysis has been applied to study the genetic variability and population structure in many equine breeds, exploiting the application of different software to analyse genealogical data (Sabbioni et al., 2007).

The theory of population genetics, developed for ideal populations, can be extended to real populations by computing effective population size (Ne), which adjusts the actual number of active breeding animals to a gender ratio of 1:1 (Wright, 1931). The calculation of Ne is considerably sensitive to the quality of pedigree information and accurate estimates of Ne are central to developing suitable conservation strategies, when making the estimation of parameters based on identity-by-descent of genes (Ghafouri-Kesbi, 2010; Gomez et al., 2012). Consequently, another approach can be recommended to assess genetic diversity - the analysis of the probabilities of gene origin, first introduced by Dickson and Lush (1933) and further developed by Lacy (1989). An important advantage of parameters obtained by this approach is to be less sensitive to pedigree completeness in comparison to parameters based on identity-by-descent of genes (Boichard et al., 1997).

The effective number of founders (fe) concept was defined by Lacy (1989), who also introduced the concept of founder genome equivalents (Lacy, 1989, 1995). Alderson (1991) proposed computing the gene origin probabilities or each potential candidate for breeding with reference to the founders, and then selecting animals with the highest effective number

- 10 - Background

of founders as a way of equalizing founder contributions. Caballero and Toro (2000, 2002) found that effective population size, effective number of founders and founder genome equivalents are interrelated in terms of coancestry and variance of contributions from ancestors to descendants, and proposed a new parameter - the effective number of non- founder genomes - to describe the relationship between the effective number of founders and founder genome equivalents.

Studbooks with accurate records are vital so that information on the genetic size of a population can be obtained by analysing pedigree information. However, the creation and closing of a Studbook can originate bottlenecks on the genetic diversity of a population; that´s why Studbooks should be continuously surveyed to prevent further losses of genetic diversity (Schurink et al., 2012).

Compared to other farm animals, equids present a higher generation interval. Within small populations that primarily target breed conservation; long generation intervals are advantageous in order to minimize the increase of inbreeding per unit of time (Vostry et al., 2011). On the other hand, the time span is longer before an increase in inbreeding rate is detected due to the low numbers of stallions and breeding mares used (Hamann and Distl, 2008; Vostry et al., 2011).

Pedigree analysis for the evaluation of genetic variability and diversity was already done in Portuguese horse breeds as the Sorraia (Luís et al., 2007; Pinheiro et al., 2013), Garrano (Morais et al., 2005) and Lusitano (Vicente et al., 2012), as well as for other European horse breeds (Sabbione et al., 2007; Hamann and Distl, 2012; Schurink et al., 2012; Siderits et al., 2013), but such information for the Asinina de Miranda breed is still lacking.

1.3. The reproductive physiology of female donkeys

Of the two domestics equid species, horses are by far the most studied in terms of the reproductive cycle. It is therefore natural that a lot of the studies in donkey arose by comparison. While many similarities in reproductive physiology exist between donkeys and horses, there are important differences (Blanchard and Taylor, 2005). It is generally accepted that the diestrus is longer in jennies than in mares (Vandeplassche, 1981; Meira et al., 1995; Ginther et al., 1995), while the estrus is similar in length between these species (Vandeplassche, 1981; Henry et al., 1987; Carluccio et al., 2005); consequently, donkeys

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present longer interestrous intervals (Ginther et al., 1987; Fielding, 1988; Blanchard et al., 1999; Taberner et al., 2008). One of the main reasons endorsing the increased understanding of the jennies estrous cycles is the interest to manipulate the cycle for optimization of fertility (Carluccio et al., 2006).

During the breeding season, in horses, cycle length is about 22 days, with 5–7 days of estrus (Aurich, 2011). The first report on the length of donkey estrous cycle, by Nishikawa and Yamazaki (1949b), describe similar characteristics for standard jennies in Japan: an interestrous interval of 22.8 ± 0.109 days (ranging 13-31 days) with an estrus length of 6.02 ± 0.677 days (ranging 3-14 days). In this first report, the resemblances between donkeys and horses on respect to seasonality, duration of estrus and estrous cycle were also established. Since then, several other studies were performed on different donkey breeds, such as Catalan (Taberner et al., 2008), the Anatolian (Kalender et al., 2012), the Brazilian Pêga (Meira et al., 1995) and Marchador (Conceição et al., 2009), the Mammoth (Blanchard et al., 1999), the Martina Franca (Contri et al., 2014) and the Baudet de Poitou (Trimeche et al., 1995).

Equids are seasonal polyestrous species, presenting the onset of the breeding season in spring, triggered by an increase in daylight, temperature and food availability (Naggy et al., 2000). In horses, seasonal reproductive activity is stimulated by long days and short nights (Palmer and Guillaume, 1992; Fitzgerald and McManus, 2000; Nagy et al., 2000; Ferreira-Dias et al., 2005). In the northern hemisphere, the natural breeding season occurs from April to September in most horses, while in less domesticated horse breeds it may occur between May and October. In the mare, the non-reproductive season can be differentiated into an autumn transitional phase from cyclic activity to anestrus, a mid-anovulatory period at winter and a second transitional phase to cyclic activity in spring (Ginther, 1992; Aurich, 2011). Among riding and racing breeds, about 30% of mares show ovulatory cycles throughout the winter season (Aurich, 2011), while in most other breeds, 85 to 95% of mares cease ovarian cyclicity around the autumn equinox (Ginther, 1992). As in the rest of the northern hemisphere, in Portugal the reproductive season lasts from April to September, although some females start cycling as early as January (Ferreira-Dias et al., 2005; Atayde and Rocha, 2011; Fradinho et al., 2014).

One of the first studies characterizing the reproductive activity in Japanese jennies showed a breeding season lasting from April to September and an anestrus season between December and January, while the transition stages into and from the breeding season occurred from

- 12 - Background

February to March and from October to November, respectively (Nishikawa and Yamazaki, 1949b). It is generally accepted that the reproductive function is less affected by season in donkeys than in horses (Ginther el al., 1987; Henry et al., 1987; Lemma et al., 2006), though the genetic of the breed may influence seasonal determinism. Mammoth donkeys seem to be less affected by season than the reported in other standard donkeys, displaying estrous cycle and estrus of similar length (respectively, 23.3 ± 2.6 days and 5.9 ± 2.1 days among the four seasons of the year (Blanchard et al., 1999).

The seasonal reproductive pattern results from an endogenous circannual rhythm determined by external environmental factors such as photoperiod and temperature, which are considered as main determinants of seasonality (Fitzgerald and McManus, 2000; Naggy et al., 2000; Aurich, 2011). However, other external cues may also influence the strength exerted by seasonality on the suppression of ovarian activity in the non-breeding season – determining the anestrus depth. Among these factors, age, nutrition and body condition may act as secondary modulator factors for the reproductive activity (Henneke et al., 1983; Fitzgerald and McManus, 2000; Godoi et al., 2002; Gentry et al., 2002; Salazar-Ortiz et al., 2011, Fradinho et al., 2014; Morley et al., 2014). Therefore, in many horse populations a proportion of mares might cycle continuously throughout the year, usually those with high body condition (Waller et al., 2006).

Not all reports agree on the differences in the estrous cycle length or the duration of each cycle stage in mares passing into anestrus (Ginther, 1992; Blanchard et al., 2003; King et al., 1993; Nequin et al., 1990), which may result from year differences, the location of the study, the breed or type, age or nutrition level (Ginther et al., 2004). In the autumn transition, ovulation failure is followed by a phase of variable follicular activity anticipating the reduction in the follicular growth characteristic of deep anestrus. Even in mares that keep cycling year-round, small differences in the length of the estrous stages have been reported during the breeding and the non-breeding seasons. Dowsett et al. (1993) reported the shortening of estrus during winter season, compared to spring or summer, together with the elongation of the estrous cycle, while King et al. (1993) described a non-significant decrease in the luteal stage in mares during winter.

In mares, the follicular growth during winter is usually minimal and corresponds to successive waves of small follicles development, with a diameter of no more than 15 mm. Low circulating concentrations of luteinizing hormone (LH) contribute to the reduction in

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follicular growth (van Niekerk and van Niekerk, 1997b). However, follicle-stimulating hormone (FSH) surges are maintained and follicular waves can be distinguished throughout the anovulatory season. The spring transitional period is variable in length, ranging from 30 to 90 days. It begins with the resuming of follicular deviation, with development of a dominant follicle reaching a size between 20 mm and 30 mm in diameter. In addition, it also encompasses the development of an increasing number of follicles with a diameter greater than 15 mm. Subsequently, usually one to three anovulatory follicular waves develop before ovulation occurs (Ginther, 1992; Donadeu and Watson, 2007). The length of the anovulatory period varies among mares (Dowsett et al., 1993).

Galisteo and Perez-Marin (2010) identified the photoperiod as the most important factor for synchronizing seasonal reproductive activity in jennies. However, other factors may modify the intensity of the depression over the reproductive activity, alike the coupled effect of nutrition, energy balance and BCS, as reported by Lemma et al. (2006) for jennies in latitudes with small photoperiodic variation.

With regard to pre-ovulatory follicular development and ovulation, equids differ from other farm animal species. The pre-ovulatory follicle is larger and ruptures at a specific region of the ovary – the ovulation fossa. From deviation onwards, that occurs when dominant follicle attains a size around 22.5 mm and 7 days before ovulation (Ginther et al., 2006; Donadeu and Watson, 2007), the pre-ovulatory follicle grows at an average rate of 3 mm per day to a diameter of approximately 35 mm, four days before ovulation. Continued growth occurs up to 2 days before ovulation, when follicular size reaches a plateau at approximately 40 mm (Ginther et al., 2008). Mares ovulate consistently from similar pre-ovulatory diameters in consecutive cycles (Cuervo-Arango and Newcombe, 2008).

Nishikawa and Yamasaki (1949a) reported that the diameter of the largest follicle at the beginning of estrus was 10 to 30 mm in diameter for standard Japanese jennies. Ovulation occurs in jennies at a maximum follicle size of 30 to 45 mm (Nishikawa and Yamasaki, 1949a; Dadarwal et al., 2004), an average of 6.6 days after the estrus onset (Nishikawa and Yamasaki, 1949a). In jennies, estrus average follicular growth rates range from 2.4 and 3.7 mm/day (Ginther, 1992; Dadarwal et al., 2004; Taberner et al., 2008; Conceição et al., 2009), considering different donkey breeds.

In mares, the follicle size at ovulation, as well as the rate of dominant follicle growth, differs according to the ovulation rate, in particular during the 2.5 days prior to ovulation; this results

- 14 - Background

in a lower preovulatory follicle diameter in double ovulators compared to single ovulators mares (Aurich, 2011). The reduced follicular growth might be related to lower FSH concentrations, most probably due to higher estradiol concentrations from the two preovulatory follicles (Ginther et al., 2008). In mares, multiple ovulations vary between 7% and 25%. Genetic influences on twining are not clear, but incidence of multiple ovulations varies with the breed (Bresinska et al., 2004; Wolc et al., 2005), with larger breeds having a higher incidence than smaller breeds of horses or ponies. In addition, it may also vary with the reproductive status and age, or in consequence to the administration of hCG or its analogues in the schemes of estrous cycle manipulation (Aurich, 2011).

Multiple ovulations are more prevalent in donkeys than in horses. The rate of multiple ovulations in this species varies with the reports, ranging from 5.3% to almost 70% (Nishikawa and Yamasaki, 1949a; Vandeplassche et al., 1981; Henry et al., 1991; Meira et al., 1995; Ginther et al., 1987; Taberner et al., 2008). The incidence of multiple ovulations in a herd of Mammoth jennies was found to be higher (61%) than that reported for other jennies. Moreover, it was found that jennies displaying multiple ovulations tend to repeat it in several estrous cycles (Blanchard et al., 1999; Taberner et al., 2008), suggesting the existence of a genetic influence. Also, Ginther (1992) refers the repeatability of multiple ovulations in individual mares, considering it a heritable trait. So, the higher incidence of multiple ovulations reported in the herd of Mammoth jennies (Blanchard et al., 1999) may reflect the selection of certain family lines. No season effects were detected on the incidence of multiple ovulations in jennies (Ginther et al., 1987) but, in the mare, the prevalence of multiple ovulations is positively affected by the female BCS (Guillaume et al., 2006).

Multiple ovulations may occur in a synchronous event, if ovulations occur at intervals shorter than 24 hours, or asynchronously, if the interval between ovulations lasts for more than 24 hours (Ginther et al., 1987; Taberner et al., 2008; Meira et al., 1995). In jennies, most of the multiple ovulators remain in estrus until after the final ovulation (Ginther et al., 1987; Blanchard et al., 1999), as it was also reported for the mare (Blanchard et al., 2003).

In the mare, circulating concentrations of progesterone immediately increase at the time of ovulation (Roberto da Costa et al., 2005). Maximal concentrations of progesterone are reached on day 8 after ovulation and then slowly decrease until the onset of luteolysis that begins at approximately day 14. Functional luteolysis occurs around day 15 and is initiated by endometrial secretion of prostaglandin F2α (PGF2α) (Aurich, 2011). Also, individual variations

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are expected either on the onset of progesterone peak and on progesterone values in mares with similar length of estrous cycles (Squires et al., 1974; Satué and Gardon, 2013); such variations were associated with differences in the secretory capacity of the corpus luteum and the hormonal catabolic rate and the existence of multiple ovulations (Satué and Gardon, 2013). In jennies, the progesterone patterns resemble those described in mares. Progesterone levels usually remain below 1ng/ml during estrus, rising rapidly after ovulation to reach peak levels above 10 ng/ml five days after ovulation and dropping sharply two to three days prior to the onset of estrus (Henry et al, 1987 Carluccio et al., 2008; Meira et al., 1995; Contri et al., 2014).

Pregnancy length in jennies is described as quite variable (Fielding; 1988). There are values reported from 353.4 ± 13 days (Crisci et al., 2014) to 355-365 days (Galisteo and Perez- Marin, 2010), longer in average than pregnancy in mares (Ginther, 1992). In jennies, no significant differences were observed between the breeds. Breeding season has a significant effect on gestation length, with longer gestation lengths when jennies were covered during the early period of breeding season. Breed, age of jenny, year of birth, foal gender, month of breeding, and type of gestation do not have a significant effect on gestation length (Galisteo and Perez-Marin, 2010).

1.3.1 Donkey sexual behaviour

Sexual behaviour of donkeys is characterized by a series of attitudes during sexual interactions. Jennies display a variety of estrus behaviors that include: a) mounting; b) herding/chasing other jennies, teasing of other jennies, and Flehmen response; c) mouth clapping; d) winking; e) raising the tail; f) urination; g) posturing (i.e., abducted rear legs, arched tail, tipped pelvis, and lowered perineal area); h) standing to be mounted. Interestingly, in estrus, mouth clapping begins almost one day before onset of other positive signs and lasts almost one day more (Clayton et al., 1981; Vandeplassche, 1981; Henry et al., 1998; McDonnell, 1998). A conspicuous characteristic of donkeys mating is the usually longer time for mating and the fact that jacks will continue to pursue and attempt mounting even if kicked (Clayton et al., 1981; McDonnell, 1998). Several periods of sexual interactions separated by periods of male withdrawal from the female are needed before breeding is achieved. In comparison to mares, jennies play a more active role in the mating process (Vandeplassche, 1981; Henry et al., 1991, Henry et al., 1998). Breeding potential of this species is high;

- 16 - Background

human interference in the pattern of sexual interaction does not seem to change attitudes displayed during courtship but may alter breeding efficiency of the jacks (Henry et al., 1998).

1.3.2 Reproductive efficiency in equids

The reproductive efficiency is a major determinant of profitable equids breeding and conservation programs, in case of endangered species or breeds. For these programs, the knowledge of the reproductive capability, manifested by the production of viable offspring (Ginther, 1992), and the identification of the main determining effects on the reproductive success is of major importance (Morel et al., 2010). However, one major limitation might be the difficulties in obtaining accurate fertility data (Kuisma et al., 2006).

Compared to other domestic species, horses have been considered as presenting relatively low reproductive efficiency, particularly when under traditional, low technique, breeding systems (Morris e Allen, 2002; Ricketts and Troedsson, 2007). The reproductive efficiency for the species depends on both genomic and non-genomic effects. Among the genomic effects, besides the particularities of the breed, are major determinants of the reproductive success the number of available reproducers and breed inbreeding (already reviewed in this document), as most often fertility is negatively correlated with homozygosity (van Eldik et al., 2006). Breeds with small populations have increased susceptibility to infertility and lower pregnancy rates, thereby presenting decreased reproductive success (Collins et al., 2012). This may be due to compromised reproductive physiology (Collins et al., 2012) or to a decrease in the breed fitness to environmental changes (Sommer, 2005).

From the non-genomic effects, main determining issues are the factors associated with the animal, such as age and parity for females (Carnevale and Ginther, 1992), and the environmental effects, that include the photoperiod, the nutritional status and its reflection on BCS (Aurich, 2011), and the management factors, including managerial arbitrary decisions (Ricketts and Troedsson, 2007). The photoperiod extent may influence the length of the breeding season, the differences being more pronounced between animals living near the poles and those in living tropical areas. The longer the length of the breeding season, higher will be the season pregnancy or the foaling rates (Osborne, 1975; Satué and Gardon, 2013). For animals living in temperate regions, nutrition and the energetic metabolism may be the major drive force in the regularity of the yearly oestrous cycles (Fitzgerald and McManus, 2000).

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1.3.3. Body Condition Score (BCS)

Inadequate nutrition and reduced body fat are associated with impaired reproductive efficiency in mares (Henneke et al., 1983, 1984; Hines et al., 1987; Waller et al., 2006). It is commonly accepted that most mares with high BCS (7.5 to 8.5) continue to cycle throughout the non-breeding season. On the other side, low BCS in mares were associated with a consistent seasonal anovulatory state.

Although low BCS and leptin concentrations were associated with inactive ovaries during winter and early spring, mares with low BCS eventually ovulated in April and May while leptin concentrations remained low (Gentry et al., 2002b), suggesting that although important modulators, BCS or the serum metabolites are not major determinants of regular ovarian activity during a positive photoperiod. Fitzgerald and MacManus (2003) reported an increase in the length of diestrus and interovulatory interval in fat mares (BCS ≥ 7) under controlled management compared to mares in moderate BCS. In free ranging tropical jennies, variations in BCS can also affect the ovarian activity (Lemma et al., 2006).

Both obesity and emaciation are, paradoxically, common problems in donkeys, the first in rich (Pearson and Ouassat, 2000) and the second in poor countries (Pritchard et al., 2005). Good management involves ensuring that animals eat the daily requirements for maintenance and satisfaction of the work and production needs (Eley and French, 1994; Pearson and Ouassat, 2000; Vall et al., 2003), but overfeeding and obesity are risky. Hyperlipaemia is a severe condition that can affect overweight donkeys. It has a high mortality rate and several predisposing factors are recognized in donkey breeds, such as obesity, female gender, pregnancy, lactation, older age, intercurrent disease and anorexia (Reid and Mohammed, 1996; Durham, 2006).

The body condition score has often been used as an index of nutritive status of livestock (Russel et al., 1969; Lowman et al., 1976; Edmonson et al., 1989; Santucci et al., 1991; Frutos et al., 2012). In horses and donkeys it uses visual appraisal and palpation of some anatomical landmarks (Henneke et al., 1983; Pearson and Ouassat, 2000; Vall et al., 2003; Carter et al., 2009), but these methods are affected by a certain level of subjectivity (Vecchi et al., 2010), and small BCS changes cannot be realistically detected even by trained observers (Ferguson, 1996; Mottet et al., 2009). Although there are reports of BCS systems in donkeys (Pearson and Ouassat, 2000; Vall et al., 2003), more accurate methods have never been tested. BCS must be considered a subjective technique to a certain degree (Ferguson, 1996; Mottet et al.,

- 18 - Background

2009; Vecchi et al., 2010; Frutos et al., 2012). On the other side, Real Time Ultrasound (RTU) can be used in the field to routinely predict body fat reserves with a higher degree of accuracy (Schröder and Staufenbiel, 2006; Dugdale et al., 2010), giving even better results if used in conjunction with BCS traditional assessment (Dugdale et al., 2011a). RTU measurements has been proved to be accurate in predicting body fat in different species (Westervelt et al., 1976; Gee et al., 2003; Silva and Cadavez, 2012), but not all points for the collection of images equally reflect body fat reserve changes (Gentry et al., 2004; Argo et al., 2012).

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2. Aims of the thesis

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Aims of the thesis

2. Aims of the Thesis

Limited knowledge exists on donkey reproductive activity, in particular on that of the Asinina de Miranda breed. The identification of the most important internal and external factors modulating their reproductive traits is vital, when designing a breeding program. Moreover, previous work (Quaresma et al., 20111) suggested that some of the detected reproductive abnormalities might have a genetic background, possibly associated to increased consanguinity or to a high ovulation rate per cycle. Thus, the overall aims of this thesis were to assess and characterise the reproductive activity in Asinina de Miranda jennies and to identify the most important factors limiting the reproductive efficiency in this breed.

Taking into consideration the perception that the Asinina de Miranda breed was endangered of extinction, and that endogamy is often present in such populations and might be a strong determinant of the breed fertility, studies on the breed demography and on its reproductive function were envisaged. The acquisition of evidence-based scientific knowledge on the breed demography and female reproduction is of paramount importance on the recovery and maintenance of the Asinina de Miranda breed. It also may be useful supporting recovery programs of other breeds in similar conditions.

Specific aims for the present thesis were:

. To determine the putative influences of several genetic factors on the Asinina de Miranda reproduction, in particular:

- To estimate the viability of the Asinina de Miranda breed on the present scenario, identifying the variables that are determinant to the breed conservation and suggest new management strategies, if perceived as needed;

- To analyse some fertility traits (such as foal rate, neonatal survival, conception rates, twin index, foaling intervals), age pyramid and mortality rates in Asinina de Miranda population;

- To analyse the pedigree records and typify some of the socioeconomic features of herds and owners of the Asinina de Miranda breed, identifying the environmental and management factors that may affect the breed genetic variability in the future;

1 Quaresma M, Payan-Carreira R, Pires MA, Edwards JF. 2011. Bilateral ovulation fossa inclusion cysts in Miranda jennets. J Comp Pathol. Nov;145(4):367-72

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. From data gathered in those studies, to discuss suitable strategies to minimize the loss of genetic diversity, based on identified variables, acting early in the beginning of the breed recovery project;

. To investigate the relationship between BCS and the subcutaneous fat and thoracic wall tissue depths assessed by RTU in donkeys, and to determine the most sensible test to estimate female adiposity;

. To characterize the estrous cycle of Asinina de Miranda jennies during the breeding season, including: the lengths of the interovulatory intervals and of the estrus and diestrus stages; the ovulation rate and the prevalence of multiple ovulations; the follicular size at different moments of the follicular wave, whether single or multiple ovulations are considered, and the pattern of follicular growth and; the moment of ovulation from the onset of heat behaviour, as well as to estimate the putative influences of endogenous or exogenous factors, such as age and BCS, on those parameters.

. To analyse the ovarian activity pattern in Asinina de Miranda jennies during the winter period, in comparison to the other seasons’ patterns, and to estimate the modulatory role of BCS in the autumn transition on the triggering of anestrus during the winter season.

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3. Material and Methods

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Material and Methods

3. Material and Methods

Overall issues regarding the research methods used in the present thesis (papers I-V) are outlined in this section. For further detailed descriptions, the reader is referred to each individual paper.

The components of the work consisted of two years studies developed in live animals maintained at UTAD facilities, and two additional period of 6 months, one to select the females for these studies (including a gynaecological exam to discard ovarian and uterine pathologies), and the other to analyse the breed records and extract the information needed to the population analysis. The females were selected from AEPGA animals and covered different age groups, similar to those put on reproduction in the region. The overall design of the experiments was to follow the natural cycles during the different reproductive seasons, starting on September. After a period of 3 to 4 regular cycles in the breeding season, females were allowed to breed. Pregnancy diagnosis was performed between post-ovulatory days 14 and 16, and the number of embryos recorded. If necessary, embryo reduction was performed until day 18 post ovulation, to guarantee the progress of only singleton pregnancies. The initial pregnancy was surveyed and jennies were returned to AEPGA after pregnancy day 90.

The use of animal as research objects in Papers III-V was conducted under the guidelines of the European Council Directive 2010/63/EU for the protection of animals used for experimental and other scientific purposes. No ethical approval was necessary for Papers I-II, as the data were obtained from the official Studbook and Foal book datasets, hold by AEPGA.

3.1. Demographic analysis (papers I-II)

The population analysis was parameterized with data from Asinina de Miranda breed Studbook and Foalbook, comprising data for the entire purebred population, as well as for herds and owners, from 2002 (opening of the Studbook) until the end of 2012 (one year after closing of the Studbook). Further data concerning reproductive practices and mortality was collected through a survey to the donkey owners during the year of 2012.

For population viability analysis, the program used was Vortex 9.99c (Lacy et al., 2009), a Monte Carlo stochastic simulation, individual-based software developed for long-lived animals often used to assess the risk of extinction for breeds or species with long life cycles. After the PVA program running, additional results were calculated from the demographic data

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available, on parameters related to the most sensitive variables on population viability, but not directly included on the PVA input. These included age at parturition, parity and foaling intervals of the jennies and foal mortality rates in the first month of life and its relation to mothers’ age and month of birth.

The pedigree analysis was performed using ENDOG v4.8 (Gutiérrez and Goyache, 2005). To characterize the depth of the pedigree, the average complete generation, the maximum of fully traced generations and the number of equivalent generations was calculated. The assessment of the genetic variability was done calculating the individual inbreeding coefficient (F) and average relatedness coefficients (AR) and the parameters characterizing the concentration of gene origin, such as the effective number of founders (fe), and the effective number of ancestors (fa), as well as the effective population size (Ne). Moreover, the genetic conservation index (GCI) for each animal was calculated according to Alderson (1992) and generations intervals were calculated for the four pathways parent-offspring for sires and dams of all foals and for the mean age of sires of sons, sires of daughters, dams of sons and dams of daughters (Gutiérrez and Goyache, 2005).

3.2. Animals, Handling and Housing (papers III-V)

In the study of the female reproductive physiology, 16 adult animals were housed at Vila Real, Portugal (41º17’ N, 7º44’ W, 431 m above sea level) and were kept year-round under natural photoperiod, with a 9 hours daylight in winter solstice and 15 hours in summer solstice. The study was developed over two consecutive years, with two groups of different animals equal in number each year. Climate conditions were similar for both years in temperature, humidity, rainfall and daylight. The jennies were maintained under the same basic management conditions for both years in a 2500 m2 paddock with a 50 m2 shelter offering protection from rain, sun and wind. Animals were fed according to accepted protocols (Smith and Wood, 2008), which consisted of 5–7 kg of hay and straw and 200 to 400 g of concentrate per jenny, twice daily, equating to a dry matter intake between 1.5% and 2% of BW. Clean fresh water was available ad libitum.

Jennies were teased daily with a male that displayed good libido, taken to a paddock adjacent to the jennies, separated only by a wire fence. Afterwards, the male was removed to an indoor box, in a facility 400 m away. Female behaviour was observed during 30 minutes and classified according to McDonnell (1998).

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All the females used were adult, non-pregnant, non-lactating and clinically healthy jennies from the Portuguese Asinina de Miranda breed, presenting regular estrous cycles at the onset of the study. Due to some unpredictable occurrences, some animals were not followed throughout the entire defined period, and the number of females used changed between experiments. The age of the females ranged from 3 to 18 years old.

3.3. Assessment of BCS (paper III)

BCS evaluation by visual appraisal and palpation was obtained independently by two technicians according to Pearson and Ouassat (2000). After BCS evaluation, ultrasound examinations were performed in six measurement points: at the backbone at withers, over the 13th thoracic vertebrae, along the mid-portion of the rump, 4 cm laterally and parallel to the midline, on the flat area anterior to the tail-head parallel to the midline, at the thoracic cage perpendicular to the ribs, directly behind the elbow over the 6th and 7th ribs and at middle of thoracic cage over the 12th and 13th ribs, midway from the dorsal and ventral midlines.

An Aloka SSD 500 V real time scanner equipped with a linear probe of 7.5 MHz (UST- 5512U-7.5, 38 mm) was used, the scanner connected to a video camera (DCRHC96E, Sony). From the recorded video, a satisfactory image was selected and the frame extracted as a 724 - 580 TIFF image file; measurements were performed with aid of the ImageJ software, (http://imagej.nih.gov/ij/index.html) to determine the subcutaneous fat depths.

3.4. Characterization of the reproductive activity (papers IV and V)

To characterize the pattern of ovarian activity during the breeding season, information from progesterone serum levels were combined with data extracted from the films of ultrasound examinations. The luteal stages of the cycle were mainly delimited from serum progesterone concentrations. Heat behaviour in the presence of basal progesterone levels served to delimit the follicular stage. Ultrasound images were used to obtain data concerning follicular development.

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3.4.1. Serum progesterone determination (papers IV-V)

Serum progesterone (P4) measurements were used to survey the luteal activity, for which blood samples were collected by venipuncture of the jugular into serum-gel tubes (S- Monovette®, Sarstedt, Nümbrecht, Germany), preceding every ultrasound session. After samples centrifugation at 2500 rpm for 10 min, the serum was stored at - 20ºC until assayed.

Serum progesterone concentrations were determined by chemiluminescent immunoassay system (IMMULITE 1000®; Siemen’s Medical Solutions Diagnostics, Los Angeles, CA, USA), using a commercial progesterone kit (Siemens Immulite® Progesterone Kit) and commercially available reagents (all from Siemens Healthcare Diagnostics, Amadora, Portugal). Interassay coefficient of variance for the controls (Multivalent Control Module, Siemens, respectively CON4, CON5 and CON6 for low, intermediate and high controls) ranged from 1.3 and 1.5% for the lower and intermediate controls, to 4.6% for the high control.

To validate the progesterone kit for donkeys, serial dilutions in buffer of a blood sample obtained from a 40 days pregnant jenny were done. The coefficients of regression obtained were 96%.

3.4.2. Ultrasound survey of the ovarian pattern (papers IV-V)

Ovarian activity was evaluated by transrectal palpation and ultrasonography, following the procedures described by Ginther (1992), at every 48 hours during diestrus or anestrus and every 12 hours during estrus. A linear-array scanner (Shnezhen Veterinary US scanner) coupled to a 5 MHz linear probe was used connected to a video camera (DCRHC96E, Sony) and all scans were recorded for posterior analysis. The diameters of the ovarian follicles were obtained retrospectively from the average of the narrowest and widest dimensions on selected US scan images. One single operator established follicular size measurements, using the ImageJ software on fixed frame images.

The following parameters were used as descriptors in paper IV: the duration of the interovulatory interval and of the estrus and diestrus stages of the cycle; the ovulation rate (number of ovulation per estrus) and the prevalence of multiple ovulations; the maximum follicular size prior to ovulation; the pattern of the final follicular growth, from divergence to

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estrus onset and from there to ovulation; the laterality of ovulation and; the time in heat after ovulation.

The ovarian activity during the non-breeding season (paper V) was classified as following: cyclic when females presented a luteal phase following an estrus-associated ovulation; silent estrus if regular follicular development with ovulation existed in the absence of signs of standing estrus; anestrus, corresponding to the persistence of progesterone levels below 1 ng/mL for more than two consecutive weeks in the absence of a large follicle and of estrous behaviour and; anovulation, where it was observed the development of a dominant follicle (size > 30 mm) persisting for several days without achieving ovulation, while exhibiting estrus behaviour.

Furthermore, for the same work (paper V), the descriptors used included the lengths of the interovulatory interval of each individual stage (follicular and luteal stages), the size and number of follicles, the presence of corpus luteum (CL) and its lifespan, as well as the maximum follicular diameter before ovulation or regression.

Moreover, for the breeding season (paper IV), the fertility rate, the pregnancy length and pregnancy losses for Asinina de Miranda jennies were also calculated. The pregnancy rate (%) was estimated as the number of pregnant females divided by the number of ovulating jennies in the observed cycle×100 (Shirazi et al., 2004). Pregnancy diagnosis was established between days 14 and 16 post-ovulation. The pregnancy was followed by periodic ultrasound exams until days 90 to 120 after conception, when the study was concluded, to detect pregnancy losses. Also, pregnancy losses after the end of the study were recorded based on reports of foetal expelling prior to term. Pregnancy length was estimated as the period between ovulation (detected by ultrasonography) and spontaneous parturition.

3.4.3. Descriptors definition (papers IV-V)

The interovulatory interval (IOI) was defined as the interval (in days) between estrus- associated ovulation in successive cycles, or as the period between the last ovulations of each cycle in the case of multiple ovulations. Sequential US records were used to establish the moment of ovulation as the mid-time between two US scans when a dominant follicle ceased to be observed during estrus.

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The onset of estrus was set at the moment when the female first showed signs of receptivity to the male, with serum progesterone levels below 1 ng/ml, while the end of estrus was considered as the moment when the jenny refused the jack. Diestrus corresponded to the period when serum progesterone levels remained above 1 ng/ml and the female refused the jack (Contri et al., 2014).

A dominant follicle was defined as the one deviated from the cohort of growing follicles, becoming the largest in the ovary, whether or not it ovulated (Ginther et al., 2004). The dominant follicle, or follicles in case of multiple ovulations, was considered ovulatory if reached ovulation.

3.5. Statistical analysis in non-population studies (papers III-V)

In paper III, all statistical analyses were performed with the JMP software (version 5.0.1.2. SAS Institute). The SF and TD measurements were analysed by ANOVA using Tukey test for comparison of group means, with the anatomical site as effect. The relationship between BCS and RTU measurements was assessed by correlation and regression analysis. To perform regression analysis both the untransformed and Log transformed values were used for the independent and dependent variables. The accuracy of the estimates was based on determination coefficient (r2), and residual standard deviation (rsd) (MacNeil, 1983).

In papers IV and V, concerning the ovarian activity in the breeding and the non-breeding seasons, statistical analysis was carried out using SPSS® (version 20 for Windows). The traits analysed, presented as mean ± standard error (SE), were the lengths of the interovulatory interval and of diestrus and estrus, the size of dominant follicles, the time (in hours) in estrus after ovulation and the final follicular growth rate, and both the BCS and the thickness of fat deposits at two targeted sites. The interovulatory interval, estrus and diestrus were assigned to the month when they started.

Other than descriptive statistics and the frequency distribution for the above-mentioned parameters, the differences between groups were tested by one-way ANOVA, with post-hoc Bonferroni test for mean comparisons. The relation between follicular growth rate and pre- ovulatory maximum size was determined by linear regression. A general linear model for univariate analysis of variance was used to estimate the effects of BCS on the changes of ovarian cyclicity, and the covariance analysis having age as covariable and BCS as main

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effect was used to test for factors´ influences on the jennies ovarian cyclicity. All statistical tests were performed setting the significance level at 0.05.

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4. Main results

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Main results

4. Main results

A summary of results of the studies included in this thesis is presented below; more detailed information is contained on the annexed copies of the manuscripts and articles.

4.1. Demographic analysis (papers I-II)

The Asinina de Miranda Studbook, started in 2002, comprises a total of 760 animals, from which 725 animals, born between 1982 and December 2012, are still alive. The potentially reproductive population at the end of 2012 comprised 589 individuals, 545 females and 72 males, alive and younger than 20 years old. The Foalbook presented 542 birth records, from which 308 were females and 234 male foals, on the analysed 10 years period. About one third of the animals registered on the Foalbook were thereafter transferred to the Studbook (35.8%; n = 542), with an unequal gender proportion of harvesting: 51.0% (n = 308) for females and 81.6% (n = 234) for males. Only 54.1% (314:580) of the adult females registered on the Studbook ever foaled. From those 314 jennies, 62.7% (n = 197) foaled once, 20.4% (n = 64) twice and just 16.9% (n = 53) foaled three or more times. The average number of foaling per jenny, in the Asinina de Miranda breed for the 10 years period analysed, was 1.05.

The average foaling interval for the breed, calculated from 191 records obtained from 117 multiparous animals, was 24.3 ± 0.978 months. More than half of the multiparous females presented a foaling interval shorter than 24 months (65.4%), though only 24.6% foaled at yearly intervals. Longer foaling intervals were observed in the remainder females: 24.1% for the 25 to 36 months foaling intervals and 10.5% for foaling intervals above 3 years.

Foaling was unevenly distributed through the year. A high number of foaling was recorded between February and June (52.9%), with an average of 56.8 ± 3.57 offspring per month, while the lowest occurrences were recorded from July to January (47.1%), with an average of 36.1 ± 1.79 offspring per month (Figure 2).

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Figure 2. Total of Asinina de Miranda foals born each month during a ten years period, from 2002 to 2012.

The overall neonatal mortality for the first month of life in Asinina de Miranda breed was 8.92% (48:538). When separated by gender, neonatal mortality was significantly lower in females (6.51%; 20:307) than in males (12.0%; 28:234) (P = 0.028). Alike foaling distribution, the neonatal mortality was unevenly distributed throughout the year. However, the month of foaling did not exert a significant influence over the neonatal mortality (X2 = 15.691; Fisher = 17.785; P = 0.061). Neonatal mortality was also independent of the jenny´s age (X2 = 12.652; Fisher=20.266; P = 0.522) or parity (X2 = 3.053; Fisher = 3.255; P = 0.591). The neonatal foal mortality rate was lower in females aged between 5 to 15 years (8.06%) compared to the recorded in animals younger than 4 years old or older than 16 years at foaling (10.3% and 14.1%, respectively). The percentage of twin foaling at gestation term was 2.85%, with a foal neonatal mortality rate of 40%.

4.1.2. Population viability analyses (paper I)

Considering the maintenance of actual management and reproductive rates, Vortex 9.99c output indicates that Asinina de Miranda has a high risk of facing extinction, with a population of less than 100 individuals in less than 30 years. The sensitivity test identified the following parameters as those with greater impact on the breed survival, by order of sensitivity: 1) percentage of adult females breeding per year; 2) female mortality till the end of breeding age; 3) the age at first offspring for females and; 4) the number of females being

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harvested. Keeping unchanged all other variables, more than 50% of the adult females will need to foal annually in order to conserve the breed. Increasing the carrying capacity from 600 to 1000 animals would be compatible with the need for just around 35% of the females foaling annually, if all other variables were kept on current levels.

Alternatively, the best-suited scenario consists on the cumulative change of several parameters, keeping the remainder at the current level: 1) an increase in the percentages of females breeding per year, from 20% to over 35%; 2) a decrease in female mortality from around 20% to 15% for the first year of life and to 2% on the subsequent years till 20 years of age; 3) the reduction of harvesting to 5 female per year; 4) and a reduction of the age at first offspring in females to 4 years old. With this approach, the percentage of jennies foaling annually may decrease to around 25% if the breed carrying capacity stabilizes around 1000 individuals, instead of the current 600.

4.1.3. Pedigree analysis (paper II)

The reference population (individuals with both parents identified) was 160, corresponding to only 21.05% of the Asinina de Miranda population, which lead to an effective population size (Ne) of 360.63. The mean average maximum generations were 0.33 and the number of complete traced generations was 0.22. The estimated number of ancestors and founders contributing to the reference population was 121 and 128, respectively. The number of ancestors explaining 50% of the genetic variability was 117. Of the 760 animals registered, only 33 males and 120 females produced registered offspring. Each stallion has been on service for an average of 3.33 ± 0.18 years and produced 1 ± 0.008 male and 3.94 ± 0.030 female offspring. The contribution of each male to the breed genetic pool was unequal with over half of the offspring (88:160) originating from 6 males, 3 of them related, a father and 2 of his sons.

There were 353 registered Asinina de Miranda donkey owners but only 70 herds (19.83%) have registered foals on the Studbook. The mean age of the herd owners was 65.50 ± 0.884 years, with a negative association among the herd size and owners’ age (P < 0.001). In contrast, the size of the herd and the ownership of a male were both positively associated (P < 0.001) with the herd number of in-born foals. Both the owners’ age and the herd location (home region vs. dispersal regions) were negatively associated with the foaling number (P < 0.001). Herds’ distribution by size showed a prevalence of the traditionally small-sized

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herds with one or two females. The type of herds significantly differed between Asinina de Miranda home region and the dispersal regions (P < 0.001), with a prevalence of traditional use for work on the home region, contrasting with the new uses of production and leisure on the dispersal regions.

4.2. Establishment of a sensitive method for BCS analysis (paper III)

The jennies on this study presented a four-point range of variation in BCS. A large variation was observed for subcutaneous fat RTU measurement sites along the thoracolumbar axis (CV between 27% and 41%) during the study. The RTU measurements at other sites showed less variation (CV between 16% and 22%). A significant correlation was found between BCS and all RTU measurements (0.65 < r < 0.86; P < 0.01). A significant correlation was also observed between all measures of RTU (0.47 < r < 0.84; P < 0.01). When the correlations between the SF RTU measurements were considered, it was observed that correlations between SFT and SFW on one side and, SFT and SFR on the other side showed the highest values (r = 0.75 and r = 0.67; P < 0.01, respectively). Among the different SF measurements, the SFR showed the highest correlation coefficient with the TD measurements (r = 0.768; P < 0.01). All equations with variables transformed into a logarithmic scale gave better coefficients of determination. Actually, the r2 increased from 3.3 to 12.1 percentage points, which represents an increase of 7–23% in this coefficient.

This result suggests that both SF and TD measurements have a logarithmic relationship with BCS. The coefficient of determination for SF estimations with raw variables and with log transformed variables ranged from 0.52 to 0.67 and 0.57 to 0.74, respectively. For TD measurements, the equations with raw variables explain 39 – 66% of the variation, whereas the equations with log transformed variables explain 42 – 75% of the variation of those measurements. All equations with log transformed variables gave better coefficients of determination. The best fitting simple regression models for SF and TD predictions were, respectively: eSFW = -0.74 + e2.06.BCS and eTDBrib13 = 0.52 + e0.96.BCS

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4.3. Characterization of the ovarian pattern in the breeding season (paper IV)

During the breeding season the length of the interovulatory interval in the Asinina de Miranda was 23.8 ± 0.551 days, ranging from 17.6 to 34.7 days. The lengths of diestrus and estrus were, respectively, 17.9 ± 0.462 days (11.6 to 27 days) and 6.65 ± 0.298 days (3.15 to 9.71 days). Higher BCS were positively associated with longer interovulatory intervals (P = 0.022) and diestrus (P = 0.003) but did not influence the length of estrus (P = 0.944). The estrus length was shorter in case of single ovulations (5.2 ± 0.403 days) than in double (6.8 ± 0.270 days) or triple ovulations (7.9 ± 1.9 days).

In general, ovulation occurred less than 15 hours before the end of estrus, but jennies maintained estrous behaviour for a variable period after ovulation. Of the 33 cycles analysed, 57.58% (n = 19) were associated with single ovulations and 42.42% (n = 14) with multiple ovulations, from which 36.36% (n = 12) were double ovulations and 6.06% (n = 2) were triple ovulations. The incidence of multiple ovulations was significantly higher (P = 0.02) in some jennies. A higher number of ovulations occurred during daytime (63.3%; n = 31) than during the night (36.7%; n = 18).

In single ovulators, follicular divergence occurred 8.72 ± 0.403 days prior to ovulation, for a follicle diameter of 19.18 ± 0.968 mm, while in multiple ovulators it occurred at day 8.92 ± 0.234 before the ovulation of the follicle, regardless of the order of follicle ovulation, for a follicle diameter of 18.05 ± 1.16 mm. The average size of the dominant follicle at the onset of estrus was 25 ± 0.951 mm, being different (P < 0.001) in case of single and double ovulations (respectively 29.2 ± 1.41 mm and 22.2 ± 0.811 mm). No differences were found on the average size of the dominant follicle at the onset of estrus between triple (23.3 ± 4.24 mm) and double (22.2 ± 0.811 mm) (P = 0.130) or single (29.2 ± 1.41 mm) (P = 0.456) ovulations. The overall maximum follicular diameter prior to ovulation was 38.4 ± 0.68 mm; it was smaller in multiple ovulatory cycles than in single ovulatory cycles (P = 0.03).

The ovulation rate did not affect the daily growth rate of the dominant follicle. The daily follicular growth rate during the estrus was significantly higher than in the period from divergence to onset of estrus in single (P < 0.001), double (P < 0.001) and triple ovulations (P = 0.004). Higher follicular size at the onset of estrus and higher daily growth rates of the dominant follicle during estrus were associated with ovulation of larger follicles (respectively, P = 0.001 and P = 0.027).

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The pregnancy rate observed at day 30 post ovulation was 85.71%, despite that the conception rate was 100% at the first mating cycle. The pregnancies arose from either single ovulatory cycles (7:14) or double ovulatory cycles (7:14). In pregnancies issuing from double ovulation cycles, four females (57%) carried twin pregnancies while three females (43%) carried singletons. In diagnosed twin pregnancies (n = 4), manual elimination of one embryonic vesicle was performed around day 18; pregnancy was lost in one case but evolved uneventfully with one embryo in the other 3. Pregnancy was carried to term in 10 jennies (71.43%). Pregnancy losses (n = 4; 28.57%) occurred at different periods of pregnancy: 2 occurred prior to day 30 (including the one following embryo crushing) and were classified as embryonic mortality, while 2 other were reported after the end of the study, at 5 and 8 months of pregnancy, on the oldest females aged 17 and 18 years old, and were classified as fetal loss or abortion. The causes of the embryonic and fetal losses were not explored in the present study. The mean pregnancy length for this group of Asinina de Miranda donkeys (n=10) was 370 ± 9.4 days (349-392 days).

4.4. Characterization of the ovarian pattern in the non-breeding season (paper V)

Of the twelve females studied, nine jennies (75%) showed disruption of the normal pattern of ovarian activity during the non-breeding season; only 3 females (25%) maintained the regular ovarian pattern in the same period. Loss of the normal cyclicity included anestrus (n=5; GrA), silent ovulatory estrus (n=3; GrSE), and persistency of corpus luteum (n=1; GrPCL). Anestrus started between the 3rd November and 12th December. The mean duration of anestrus was 147 ± 28 days, with the first ovulation occurring at 17th March. In this group, resumption of regular estrous cycles with ovulation occurred after an elongated estrus (11.9 ± 7.8 days) in comparison to those recorded in the reproductive season (5.5 ± 1.8 days) (P = 0.027). It was also detected an increase in the average pre-ovulatory follicle size in the first ovulation of the year.

BCS affected the ability to maintain regular ovarian activity during the non-breeding season (P < 0.001), with animals in poor body condition showing disturbed regular ovarian activity. Age was positively associated with BCS (P < 0.001). These factors presented synergic effects on the loss of regular ovarian cycles: younger jennies that also showed the lower BCS scoring were more likely to undergo anestrus (P < 0.001).

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5. General discussion

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General discussion

5. General discussion

The overall number of Asinina de Miranda animals places the breed in the vulnerable to extinction category (FAO, 2007). Based on the data available and under the current management, the Asinina de Miranda breed will face eminent extinction with a population of less than 100 individuals in less than 30 years, mainly due to a low percentage of females breeding yearly. However, it is important to keep in mind that PVA is a simulation and reality is always more complex than what any model could predict (Burgman and Possingham, 2000). Because of the declining numbers in the population and the breeding rates, there is also an increased risk of inbreeding. The number of animals in reproductive age still allows for the implementation of an effective conservation program. However, the low foaling rates demand for urgent action (papers I-II).

The identification of the number of females breeding each year as the major limiting factor for equine breeds survival was already reported by Thirstrup et al. (2009). To preclude the ongoing reduction of the population, a larger number of foals must be born each year. The owners ought to be convinced to breed as soon as possible (foal heat), at the weaning of the foal (two foals in three years) or at least every two years, to keep the breeding rate at required levels. Jennies should be breed for the first time at 3 years old. Foals born from March to May, July, and from October to November tend to have better chances of survival than those born in other months. For a carrying capacity between 600 and 1000 animals, 35 to 50% of the females in reproductive age must foal each year for Asinina de Miranda breed survival on the long term (paper I). Developing new purposes for the breed, such as milk production or its use in leisure and as companion animal, will strength the policies for rescuing the breed and support the conservation and breeding programs.

Despite the pedigree shallowness, an important loss of founder genetic diversity was noticeable by the low effective number of founders and ancestors of the reference population in comparison with the registered number of founders and ancestors. The rates between these indices revealed that for each founder or ancestor contributing to the reference population, the genetic information for more than two other founders or ancestors was lost. It would be desirable to broaden the use of different males in the same reproductive season, and to use them throughout several seasons; this strategy preserves better allele variability than the system where one stallion stays in the herd alone throughout several reproductive seasons

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(Luís et al., 2007). Prolonging the generation intervals by keeping the animals for longer periods in reproduction may be a suitable strategy to increase the number of Asinina de Miranda jacks and jennies breeding, thereby increasing the effective population size and reducing the inbreeding (Meuwissen, 1999; Caballero and Toro, 2002). For most of the herds, only one or two animals are kept and the number of foaling reported by the few bigger herds is disproportionally higher. This might favour a genetic bottleneck, with few herds and their animals being genetically overrepresented in the future (paper II).

The classification and use of the genetic conservation index and the average relatedness of the animals should be considered and made available to owners in breeding decisions, selecting the ones with the highest value on the first and the lowest in the second (Dunner et al., 1998; Valera et al., 2005). Breeding management should be conveyed by both the increase in the number of official tested jacks and by reducing the inbreeding rate at mating, particularly in bigger, more isolated herds, away from the breed home region, as it has been suggested in other donkey breeds (Bordonaro et al., 2012) (paper II).

The most cost effective measures are those involving breeders directly, sharing with them the responsibility on the recovery programs while promoting the breed (Reist-Marti et al., 2006). Conservation of farm animal resources should be designed with a long-term perspective, using a planning horizon of at least 50 years. Training courses for breeders and marketing activities for promotion of the breed and its products should be a priority, to avoid erroneous breeding decisions and promote socio-economic interest on the breed (Simianer, 2005). The development of new applications for the breed may increase the interest on its maintenance, as recently observed with Asinina de Miranda breed introduction into donkey milk production, touristic activities, as pets and in asinotherapy, involving younger people (papers I-II).

The findings reported in paper III are in accordance with previous studies that showed high variations in subcutaneous fat RTU measurement along the thoracolumbar axis. This was a predictable finding since fat is the most variable body tissue in this corporal region (Gee et al., 2003). The variations observed in SF RTU measurements with body weight variations were higher at the tail-head site (P < 0.05) than at the withers, loin or rump, results that are in agreement with the work of Gentry et al. (2004) and Silva et al. (2012), in horses. The exponential relationship found between BCS and RTU measurements could also make it difficult to accurately score jennies in a moderate to obese condition by visual appraisal and

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manual palpation alone. However, lack of available animals with BCS lower than 3/9 and higher than 7/9 in the present sample did not allow us to corroborate that RTU is equally useful for obese and emaciated donkeys. Nevertheless, the results obtained in females of moderate body condition also showed that not all the points used for collection of information on body condition have the same sensitivity when estimating the effects of body condition on the reproductive activity; the most suitable points to assess donkey fat deposits were the subcutaneous fat at withers and the thoracic wall tissue depth between the 6th and 7th ribs (paper III).

During the breeding season, donkeys are described as presenting longer estrus cycles than horses, but similar in length to pony mares (Vandeplassche et al., 1981; Taberner et al., 2008) and this also applies to Asinina de Miranda jennies. Mean estrus length for Asinina de Miranda (6.56 ± 0.55 days) was similar to the reported for other European breeds, such as the Martina Franca, the Zamorano-Leones and the Catalan (Taberner et al., 2008; Galisteo and Perez-Marin, 2010; Contri et al., 2014), but shorter than in the Baudet de Poitou or Brazilian standard jennies (Henry et al., 1978; Trimeche et al., 1995). Mean diestrus length for the Asinina de Miranda was similar to the reported for Mammoth and Martina Franca jennies (Blanchard et al., 1999; Contri et al., 2014), but it was slightly shorter than in the Catalan (Taberner et al., 2008), or standard American jennies (Vandeplassche et al., 1981) (paper IV). Age did not influenced the lengths of estrus and diestrus in Asinina de Miranda jennies. Nevertheless, older jennies showed longer interovulatory intervals, as observed in mares (Blanchard et al., 2003). However, the interovulatory interval and the duration of diestrus were affected by BCS: higher body condition scores lengthened the interovulatory intervals and diestrus in Asinina de Miranda females (paper IV).

The prevalence of multiple ovulations in Asinina de Miranda jennies reached 42.42%, from which 36.36% were double ovulations and 6.06% triple. This data is supported by other studies in Spanish donkeys – the Catalan (Taberner et al., 2008; Galisteo and Perez-Marin, 2010), the Andalusian and the Zamorano-Leonês (Galisteo and Perez-Marin, 2010), but lower than for Mammoth donkeys (Blanchard et al., 1999). As previously described by Ginther (1992) in mares and by Taberner et al. (2008) in jennies, multiple ovulations were highly repetitive in individual females. The existence of multiple ovulations did not affect the interovulatory interval in Asinina de Miranda jennies, although it enlarged the estrus length as well as the interval from the beginning of the estrus until ovulation. Our results are supported

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by comparable descriptions in Spanish donkey breeds (Galisteo and Perez-Marin, 2010). In the present study, prevalence of multiple ovulations was positively affected by the female BCS, as it has also been reported in mares (Guillaume et al., 2006) (paper IV).

In Asinina de Miranda jennies with multiple ovulations at estrus, a similar proportion of synchronous and asynchronous ovulations was observed. The dimensions of the dominant follicle at the onset of estrus and around ovulation, as well as the dominant follicle daily growth rate, were similar in Asinina de Miranda to those described in other breeds sharing similar estrous cycle features. Dominant follicles were first detected in the ovary as the fastest growing follicle at about 13 days prior to ovulation, which is in accordance to the findings of Conceição et al. (2009). Onset of estrus happened 6 to 5 days before ovulation in Asinina de Miranda jennies. Comparison of the dominant follicle dimensions at different moments of the follicular wave in Asinina the Miranda and data available for other donkey breeds is detailed in paper IV. Expectably, the daily follicular growth was higher during estrus than in the period between divergence and onset of estrus, as it is also acknowledged in mares (Blanchard et al., 2003) (paper IV).

Follicular size was independent of BCS in the present study, as it was the dominant follicle growth pattern. This seems to be in contrast to the work of Gastal et al. (2004), which showed that, in mares, the body condition was positively associated with maximum diameter of pre- ovulatory follicle for the first ovulations in the breeding season. Also, Lemma et al. (2006) found that BCS was positively correlated to the diameter of the pre-ovulatory dominant follicle in Ethiopian jennies. However, the relatively constant moderate body condition evidenced by the females in the present study might explain the differences between our results and those referred above (paper IV).

Overall, the cyclic changes of serum progesterone levels in Asinina de Miranda resemble those referred for other donkey breeds (Carluccio et al., 2008; Meira et al., 1995; Contri et al., 2014), as well as for mares (Ginther et al., 2008a). Twenty-four hours after ovulation (ovulation = day 0), serum progesterone levels were within basal values; the plateau lasted from day 6 to day 15 post-ovulation with the progesterone levels maintained in high values. Two to three days prior to begin of estrous behaviour, progesterone levels dropped sharply. Cumulative progesterone values were influenced by number of ovulations in our study, which agrees with data presented by Meira et al. (1995) in Pêga jennies (paper IV).

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It is currently accepted that female donkeys reared on temperate zones are subjected to seasonal effects on reproductive function. However, a clear division of the year into anestrus and ovulatory season is unusual (Ginther, 1987). It has also been shown that a relatively high number of jennies have regular estrous cycles throughout the year (Blanchard et al., 1999); still, in some studies, seasonal anestrus and irregularities in the ovarian cycles have been described in standard jennies in winter (Ginther et al, 1987; Henry et al., 1987). The variation in BCS has been proven to affect the ovarian activity in free ranging tropical jennies (Lemma et al., 2006), as it happens with mares. Mares with high BCS can usually keep cycling throughout the winter (Waller et al., 2006).

Excluding the group of females in anestrus, paper V failed to evidence differences in the interovulatory interval between the non-breeding season and the breeding or the transitional seasons. However, an average decrease in 2 days in the estrus length at fall was found in animals entering acyclicity, when compared to those retaining cyclicity in the non-breeding season. Likewise, females displaying silent estrus during the non-breeding season tended to present shorter estrus than those remaining cyclic, but in this case the differences were non- significant (paper V).

In mares (King et al., 1993), entrance in anestrus may occur after three different conditions: following the resolution of a spontaneous CL by normal luteolysis, resolution of a prolonged CL unaccompanied by follicular growth or an anovulatory estrus in association with follicular atresia. In the case of Asinina de Miranda females, anestrus followed either a shortened diestrus with spontaneous luteolysis or an anovulatory estrus. The sole case of extended luteal function was followed by resumption of ovarian cyclicity, not of anestrus (paper V).

Although changes in photoperiod are considered the most important factor for synchronizing seasonal reproductive activity in equids, authors also agree that additional factors may modify the intensity of the reproductive activity depression, such as the binomial effect of nutrition and BCS (van Niekerk and van Niekerk, 1997a; Fitzgerald and McManus, 2000; Ferreira- Dias et al., 2005; Galisteo et al., 2010). In Asinina de Miranda donkeys, BCS affected the pattern of ovarian activity during the non-breeding season, suggesting that body fat adiposity may be an important modulator of reproductive activity in winter for this breed. The majority of jennies (75%) in this study presented a disturbed pattern of ovarian activity during the non- breeding season. Females with the lowest BCS between the autumnal equinox and the winter solstice entered anestrus, while those maintaining their BCS around 5 points showed silent

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ovulations and females cycling regularly throughout the year were able to keep their BCS continually above 5 points. This suggests that jennies will maintain regular ovarian cycles if they maintain or increase their body condition to above 5 points around autumn equinox. A decrease of BCS to values below 5 points will predispose the jennies to enter a period of irregular ovarian activity, which will be characterized by anestrus if BCS is kept below 4 points (paper V).

We could hypothesize that the severity of the body condition losses in jennies close to the winter solstice will depress pituitary ability to respond to GnRH stimulation with regular FSH pattern and adequate LH surge, aggravating the inhibition exerted by the photoperiod cues on GnRH-pathways. In females with unchanging body adiposity, residual influences of adiposity on the hypothalamic-pituitary-ovarian dynamics will exist, and they would allow the maintenance of regular ovarian activity. Females that evidenced small changes in adiposity would represent an intermediate situation: although not sufficient to compromise ovulation, disturbed sex steroid production by ovarian structures might interfere with estrus behaviour exhibition, thus favouring the occurrence of silent estrus (paper V).

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6. Main conclusions

- 51 -

Main conclusions

6. Main conclusions The results obtained in this work added further and new insights to the demography and reproductive physiology of the donkey. Based on the results presented in this Thesis the following main conclusions were drawn:

. The Asinina de Miranda donkeys are at high risk of extinction on the next 50 years, according to the population viability analysis simulation. The most critical factor identified for breed survival was the percentage of females breeding per year, which was dependent of the carrying capacity of the breed. If the number of animals on the breed increases, a lower percentage of females breeding is enough for population maintenance.

. Reducing female mortality, age at first offspring production, assuring the register on the Studbook and tracking the foals will also significantly foster the breed recovery and maintenance, allowing for a reduced breeding burden to the females used.

. The breeding rate for the Asinina de Miranda for the past ten years was very low. Thought the potentially reproductive population is close to 600 individuals, less than 50% of the purebred registered females ever foaled, and from those almost 63% only foaled once. Moreover, the ratio of foaling/live animals is low (0.23) and this is not enough for breed maintenance.

. The overall neonatal mortality for the first month of life was lower in females than in males, suggesting that more attention is given to that gender segment. The neonatal mortality was unevenly distributed throughout the year, and higher in foals of females under 4 or over 15 years old. The identification of the major risk factors will allow the development of specific measures to reduce the mortality rates.

. The estimated number of founders and ancestors contributing to the reference population was not too low, but these numbers might be biased and overestimated by the short period elapsed since the creation of the Asinina de Miranda Studbook. Most likely, some of the founders might be related and the real inbreeding is higher than pedigree analysis can determine. This may predispose to a dangerous genetic bottleneck on the nearby future, urging for a more balanced contribution of the different farms to the genetic pool.

. The farmers’ age and the location within the home region, along with the small size of the farm, are the main factors that may determine a negative outcome of future breeding programs. Contrasting, the size of the herd and the ownership of a male were identified as

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potentially positive factors fostering foaling numbers. This raises awareness to the necessity of raising the interest on the breed by younger owners, while still supporting the older owners on their contributions to the future of the breed.

. The main identified risk factors for inbreeding were: low breeding rates, low number of males and their unequal contribution to the genetic pool, as well as the unequal contribution of the herds to genetic pool and the advanced age of herd owners. It urges to increase the number of animals used into reproduction. A higher number of males should be introduced into reproduction seeking for an equal contribution of their genetic to the breed, especially of those less represented. The same applies for females in reproductive age.

. Since the economic sustainability is a prerequisite for the preservation of the breed, additional incentives to breed must be created. New strategies for the sustainable use of Asinina de Miranda, such as tourism, asinotherapy, as pets or sustainable milk production must be fomented to combat the negative change in agricultural practices that left the traditional herds with no incentive to breed.

. In animals presenting moderate body condition scores (4 to 7 points), RTU assessment of fat adipose reserves is more sensitive to changes than the classical BCS evaluation based on visual and tactile appraisal.

. The duration of the interovulatory interval and of estrus and diestrus stages was established for the Asinina de Miranda donkey. Age and BCS affected the length of the interovulatory intervals, with BCS also influencing the diestrus length and the time in heat after ovulation. This knowledge will be helpful on designing more effective breeding programs.

. The prevalence of single, double and triple ovulations was 57.58%, 36.36% and 6.06%, respectively, for the surveyed period. Multiple ovulations did not affect the length of the interovulatory interval, nor the individual cycle stages, but lengthened the interval from beginning of estrus to last ovulation. The ovulation rate was affected by BCS combined with age. This highlights the importance of an early gestation diagnosis, in order to avoid twin gestation and its related high foal mortality.

. Divergence of the dominant follicle occurred around day -8.7 (day 0 = ovulation) independently of the type of ovulation considered. In single ovulators’ cycles, the

- 54 - Main conclusions

dominant follicles were larger at divergence and at ovulation in Asinina de Miranda breed. The daily growth rate of dominant follicles was independent of the ovulation rate; the dominant follicle size and the follicle growth rate were independent from BCS. The better prediction of ovulation in Asinina de Miranda jennies, allowed by this knowledge, will aid a more rational use of jacks in the breeding season.

. Pregnancy rate at day 30 was 85.7%, with a rate of 25% twin pregnancies. The foaling rate was 71.4%. The mean pregnancy length found in this group of jennies was 370 ± 9.4 days.

. A large sub-population of jennies showed disturbed ovarian activity during the winter season. Disturbed regular cyclicity was associated with anestrus, silent estrus and, in one case, to persistency of corpus luteum. BCS was more important than age when triggering these changes. This finding drives attention to the importance of monitoring the female BCS around the autumn transition and to the maintenance of a minimum threshold of BCS, in order to promote the regularity of major follicular waves or to guarantee an early onset of regular ovarian cycles and ovulation on spring.

In conclusion, this work highlighted the need of urgent actions to establish new breeding policies to increase the number of offspring produced by year, in order to avoid the foreseen breed extinction. The identification of the most important physiological and environmental constraints to the reproductive efficiency for the Asinina de Miranda donkey, where the arbitrary decisions of donkey owners play an important role, was done. It is now time to address the main actions to incorporate within new conservation and breeding programs, taking into consideration that the Studbook was closed by the end of 2012, impairing the register of new individuals of unknown ascendants.

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7. Future research

- 57 -

Future research

7. Future research

The work developed in this Thesis, unveiling new insights in to demography and reproduction of donkeys, also raise questions to be answer in future research. The questions perceived as the ones to be explored were:

. The need to enroll new studies on the genetic diversity of the breed using molecular markers to establish unambiguous information on the level of heterozygosity for the breed.

. Studies on the socio-economic variables and the development of new interests for donkey breeds should be endorsed to found sustainable uses for the donkeys, fostering the conservation strategies essential to rescue the breed from extinction.

. Enlarging the research on BCS to include larger BCS categories and BCS variations, and a wider age range of animals to consolidate these observations and to precise the threshold for body condition to guarantee an early onset of regular ovarian cycles and ovulation. Try to identify metabolic markers that could support the reproductive management.

. A wither study of reproductive physiology of donkey females, emphasising the influence of aging on fertility and also on pharmacological manipulation of reproduction, incorporated in assisted reproduction techniques.

- 59 -

8. References

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8. References

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Appendices Papers I-V

Paper I

Animal Production Science http://dx.doi.org/10.1071/AN13307

Published online: 30 September 2014

Viability analyses of an endangered donkey breed: the case of the Asinina de Miranda (Equus asinus)

M. QuaresmaA,B,C†, A.M.F. MartinsB, J.B. RodriguesD, J. ColaçoB and R. Payan-CarreiraB

A Hospital Veterinário da UTAD, Escola de Ciências Agrárias e Veterinárias - Universidade de Trás-os-Montes e Alto Douro, PO Box 1013, 5000-801 Vila Real, Portugal

B Centro de Estudos em Ciências Agrárias e Veterinárias - Universidade de Trás-os-Montes e Alto Douro, PO Box 1013, 5000-801 Vila Real, Portugal C

C Associação Para o Estudo e Proteção do Gado Asinino (AEPGA), Largo da Igreja, 5225 - 011 Atenor, Portuga

D Departamento de Ciências Veterinárias - Universidade de Trás-os-Montes e Alto Douro, PO Box 1013, 5000-801 Vila Real, Portugal

Keywords: Conservation, management decisions, reproduction, mortality rate, population dynamics, PVA.

Paper II

Animal (2014) 8, 354–359

Pedigree and herd characterization of a donkey breed vulnerable to extinction.

M. Quaresma1,2, A.M.F. Martins2, J.B. Rodrigues3, J. Colaço2 and R. Payan-Carreira2

1Hospital Veterinário da UTAD, Escola Ciências Agrárias e Veterinárias (ECAV) - Universidade de Trás-os-Montes e Alto Douro, PO Box 1013, 5000-801 Vila Real, Portugal

2Centro de Estudos Ciências Agrárias e Veterinárias (CECAV)- Universidade de Trás-os- Montes e Alto Douro, PO Box 1013, 5000-801 Vila Real, Portugal

3Departamento de Ciências Veterinárias - Universidade de Trás-os-Montes e Alto Douro, PO Box 1013, 5000-801 Vila Real, Portugal

Keywords: conservation, donkey, herds, inbreeding, pedigree analysis.

Paper III

The Veterinary Journal (2013) 197, 329-334

Relationship between ultrasound measurements of body fat reserves and body condition score in female donkeys

M. Quaresma a,b,*, R. Payan-Carreira b,c, S. R. Silva b,c a ECAV, UTAD, Veterinary Teaching Hospital, PO Box 1013, 5000-801 Vila Real, Portugal b CECAV-Universidade de Trás-os-Montes e Alto Douro, PO Box 1013, 5000-801 Vila Real, Portugal c ECAV, UTAD, Department of Zootechnics, PO Box 1013, 5000-801 Vila Real, Portugal

Keywords: Donkey, Body condition score, Ultrasound, Subcutaneous fat.

Paper IV

Theriogenology (2015) 83, 616-624.

Estrous cycle characterization for Asinina de Miranda jennies (Equus asinus)

M. Quaresma a,b,c*, R. Payan-Carreira c a Veterinary Teaching Hospital, Universidade de Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal b Associação Para o Estudo e Proteção do Gado Asinino (AEPGA), Largo da Igreja, 5225 - 011 Atenor, Portugal c Centro de Estudos Ciências Agrárias e Veterinárias (CECAV) - Universidade de Trás-os- Montes e Alto Douro, Quinta de Prados, 5000-801 Vila Real, Portugal

Keywords: donkey, reproduction, body condition score, ovulation, follicle.

Paper V

Submitted

Patterns of ovarian activity during the non-breeding season in Asinina de Miranda jennies.

M. Quaresma a,b,c*,S. R. Silva b, R. Payan-Carreira b

a Hospital Veterinário, Escola de Ciências Agrárias e Veterinárias, Universidade de Trás-os- Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal b Centro de Ciência Animal e Veterinária - Universidade de Trás-os-Montes e Alto Douro, Quinta de Prados, 5000-801 Vila Real, Portugal c Associação Para o Estudo e Proteção do Gado Asinino (AEPGA), Largo da Igreja, 5225 - 011 Atenor, Portugal

Keywords: seasonality; body condition score; donkey reproduction.