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CGRFA/WG-AnGR-7/12/Inf.6 E September 2012 ...

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Surveying and monitoring of animal genetic resources (FAO, 2011b) suggests the establishment of a strategy working group for surveying and monitoring of animal genetic resources, which might directly conduct data collection or might coordinate and oversee subcontractors carrying surveys. The National Coordinator for Management of Animal Genetic Resources should be part of these entities or collaborate closely with them. In many cases, information and expertise on breeds will be scattered in many places, including officially and unofficially recognized breed associations, NGOs, elite breeders, breed experts, research centres and universities. Potential sources of information should be mapped thoroughly and a wide range of stakeholders should be involved in planning and implementing data-collection activities.

Action 3. Gather information about each breed population Adequate planning of data collection is important in ensuring the success of surveys and the quality of results (FAO, 2011b). Planning should include accurate definition of the parameters to be collected and the methodology of collection, identification of sources of reliable information, identification of collaborators and obtaining financial support. As information different breeds may be obtained from many different sources, it is advisable, as a first step, to define clearly a common set of parameters that need to be collected in order to estimate risk status. This will help to ensure that the risk-status estimates of different breeds are comparable.

The base set of parameters required in order to compute risk status following FAO risk categories are:

total population size or total number of breeding females (registered and not registered, if possible);

total number of breeding males (registered and not registered, if possible);

percentage of females bred to males of the same breed, as females used for crossing do not contribute to renewal of the population;

trend of population size, classified as stable, decreasing, increasing, or, whenever possible, measured by an estimate of growth rate during recent years (see Box 8);

presence of conservation programmes, and/or of populations maintained by commercial companies or research institutions, under strict control;

and whenever relevant and possible:

distribution, measured as: (a) length (km) of the maximum radius of the area within which approximately 75 percent of the population lies, (b) number of herds and trends in these figures;

degree of introgression through the use of cross-bred animals as breeding stock.

The collection of additional parameters will improve understanding of the factors driving breed dynamics and improve risk-status estimates (see Task 2, Action 2). These additional parameters include the following:

number of registered breeding females: registered females constitute the part of the population that can be monitored in terms of age structure, reproduction capacity, accumulated inbreeding, mating structure, gene introgression from other breeds and can actively participate in selection programmes;

number of females registered each year: the annual number of registered female replacements has been suggested as a more accurate measure of population dynamics, CGRFA/WG-AnGR-7/12/Inf.6 mainly because it reflects the current interest of breeders in keeping the breed (Sponenberg and Christman, 1995;

Alderson, 2009);

number of males used in AI: when AI is practised, the contribution of males to the next generation can be highly heterogeneous, accelerating the F in future generations (see Section 6);

presence of selection and the type of selection practised (mass selection, index selection based on best linear unbiased prediction (BLUP), optimum contribution selection, etc.):

selection will usually accelerate inbreeding rate if methods to control inbreeding are not implemented effectively (see Section 6 and 7);

presence of past bottlenecks (severe restrictions in the number of males or females in a past generation): bottlenecks usually result in depletion of genetic variability, thus affecting the genetic variation currently present in the population;

presence of active breeders associations (this is expected to increase the resilience of the breed);

average age of farmers keeping the breed, as an indication of generational transfer of herds and an early indicator of future breed dynamics;

cultural attachment of farmers to their breed (a high level of attachment is expected to increase the resilience of the breed);

economic competitiveness of the breed relative to other breeds and/or economic activities in the area (population decline has been often associated with a lack of economic competitiveness);

national and regional trends in animal production;

national gross domestic product and the proportional contribution of agricultural products;

economic and political stability of the country/region;

risk of catastrophes, such as epidemics, drought, floods, and contingency plans for dealing with them;

and presence and status of other populations of the same breed in other countries.

In general, the base set of parameters required for calculating risk status according to FAO categories are single data points per population per year. The exception is the trend in population size, which involves calculations if a numerical estimate of growth rate is desired (i.e. rather than simple categorization of trend as increasing, stable or decreasing) or if trend is to be determined by using more than two observations of yearly population size (see Box 8). For the additional parameters listed above, a common methodology within the country should be put in place for all breeds, thus allowing across-breed comparisons. Several of the parameters are not quantitative in nature and, therefore, the use of a classification system is recommended. For example, presence of selection or recent bottlenecks could be categorized as yes or no. The cultural attachment of livestock keepers to their breeds could be classified as high, medium or low. In addition, the systems used should be harmonized as much as possible across countries that may be collaborating in conservation activities.

In this respect, communication and collaboration among national advisory committees from neighbouring countries is advisable.

Finally, collecting the data required to determine risk status is a costly and time-consuming exercise. It is therefore important that the provision of adequate human and financial resources is thoroughly addressed during the planning phases (FAO, 2011b).

Action 4. Analyse and interpret data Once data have been collected, they must be analysed and interpreted in order to estimate as accurately as possible breeds degree of risk and identify and understanding the factors influencing the degree of risk.

CGRFA/WG-AnGR-7/12/Inf.6 Box Estimation of population growth rate The estimation of population growth rate (r) requires at least two censuses at a time interval of at least several years or about one generation interval for the respective species. The parameter of particular importance is the number of breeding females, although the same equation can be applied to other parameters, such as total populations size.

Rate of growth per year (r) is estimated by means of the following equation:

r = anti-log[ (log N 2 log N 1 )/t ], where N 1 and N 2 are, respectively, the number of breeding females from first and the second census and t is the time interval in years between the two censuses. If more than two sets of census data are available, regression analysis can be used to obtain predicted values of N 1 and N 2 based on the trend across the multiple data points.

Example Data: Year 1 = 2 000 and N 1 = 1 000 breeding females;

Year 2 = 2008 and N 2 = 800 breeding females;

t = 8 years.

Note that time is measured in years in this example, rather than in a genetic unit, such as number of generations. For horses the time period between the two censuses encompasses about one generation interval, while for poultry it encompasses about eight generation intervals, although this does not change the value of r.

Calculation: r = anti-log[(log 800 log 1 000) / 8] = 0.988.

The growth rate r is <1, and the population size, measured as number of breeding females, has been decreasing.

Following the method described in Box 6, the population size that can be expected after another years (in 2028) if the growth rate does not change can be calculated as follows: N 20 = (0.98820) = 628.

As underlined in Box 6 this prediction assumes that the growth rate will remain constant in the coming years. In situations characterized by uncertainty (a high level of economic and political instability, high risk of catastrophes, low rates of generational transfer of herds, weak cultural attachment to breeds, etc.), the population size and growth rate should be monitored continuously over the years.

Data analysis should be preceded by accurate editing of the information collected. This should be done as soon as possible after data collection. Providers of data may be asked to provide accompanying notes that facilitate the interpretation of the data. The estimates for certain parameters can be verified by comparing them to information from other sources. For example, the number of breeding males in a population where natural insemination is used should correspond logically to the number of herds and the number of females;

population trends should be compared to previous estimates;

the total number of females registered each year should be compatible with the number of breeding females registered. Data analysis may indicate the need to collect additional information that can contribute to a better understanding of breed dynamics and risk status. Data collection and analysis are discussed in detail in Surveying and monitoring of animal genetic resources (FAO, 2011b). Conservation of animal genetic resources involves many different disciplines, ranging from conservation biology to sociology and economics. Discussion with experts in these disciplines may provide useful insights into the data and the consequences of the trends observed. Box 9 provides an example of how various data can be interpreted.

CGRFA/WG-AnGR-7/12/Inf.6 Box Analysis of population data: an example The following hypothetical example shows how statistical analysis can provide an understanding of trends of breed populations and insights into the factors affecting population dynamics.

Data on a hypothetical breed distributed across eight herds Herd size Farmers age Herd code Reproduction (no. of breeding females) (years) A 8 natural B 10 artificial C 60 artificial D 15 natural E 175 artificial F 70 artificial G 12 natural H 310 artificial The following statistics can be calculated from the raw data:

Herd size: mean = 82.5;

standard deviation = 107.8;

range 8 to 310.

Herd size distribution: <50 females/herd (50 percent), 50100 (25 percent), >100 (25 percent).

Farmers age: mean = 57.6;

standard deviation = 13.8;

range = 40 to 73.

Correlation between herd size and farmers age = -0.76.

Frequency of AI = 62.5 percent.

Frequency of AI as a proportion of herd size = <50 females/herd, 25 percent;

50/herd, 100 percent.

The analysis shows that mean herd size provides limited information because the number of breeding females varies widely across the herds (standard deviation > mean). There is a clear correlation between the age of the farmer and the herd size;

the greater the age, the smaller the herd;

this might be explained by the fact that older farmers invest less in farming activities. AI is used more frequently in large herds than in small herds. The prospects for the survival of small herds (50 percent of herds have fewer than 15 females and their owners are all more than 65 years old) should raise some concern.

Task 2. Identify breeds eligible for conservation activities Action 1. Assign breeds to categories according to risk status From a conservation point of view, one of the most important outcomes of a breed survey is the categorization of breeds according to their risk status. This facilitates the monitoring of livestock biodiversity at national level, helps in the planning of conservation actions and contributes to reporting and analysis at international level (e.g. FAO, 2011a). A limited number of parameters are sufficient for obtaining an indication of risk, but the collection of additional information can refine the analysis by detecting underlying trends and causes.

The risk categorization system proposed in these guidelines combines, in terms of criteria and thresholds, the previous system used by FAO (FAO, 2007b) with more recent proposals (Gandini et al., 2005;

Alderson, 2009;

Alderson, 2010).

The categorization is primarily based on three major parameters:

1. numerical scarcity (number of breeding females);

2. inbreeding rate (F);

and 3. presence of active conservation programmes.

Numerical scarcity is most accurately measured based on the number of females in the breeding population, and preferably also the proportion of females mated to males of the same breed (i.e. not cross-bred). When these data are not available, the total population size can be used as a proxy.

CGRFA/WG-AnGR-7/12/Inf.6 When possible, the rate of population growth/decline should be estimated or at least the general trend should be identified.

The F is estimated based on the numbers of breeding males and females, following the approach described in Box 7. The scarcer gender, usually males in livestock populations, is the factor that primarily influences N e.

Conservation programmes, both in vivo and in vitro, are implemented for the purpose of increasing a breeds chances of survival (i.e. decreasing the risk of extinction). The categorization system recognizes this fact by including subcategories for breeds that are included in conservation programmes. These subcategories are particularly important for the purpose of reporting to DAD-IS and for monitoring the diversity of animal genetic resources at global level.

The three parameters listed above are used to assign breeds into the following five categories (and two subcategories), listed in descending order of risk:

extinct, critical (including the subcategory critical-maintained), endangered (including the subcategory endangered-maintained), vulnerable, and not at risk.

In addition, a sixth category, unknown, is used to describe breeds for which precise information on their population size is lacking. Breeds that are categorized as critical, endangered or vulnerable are grouped together in the broader category, at-risk.

Assignment to risk-status categories is based on the least favourable parameter, i.e. breeds are allocated to the highest-risk category for which they qualify. For example, if the number of females in a breed is small enough to indicate that it should be assigned to the critical category, then it is assigned to this category even if the number of males is large enough to suggest that it should be classified as endangered. A breed cannot be assigned to two different categories.

Species differ greatly in their reproductive capacities, measured as the expected number of breeding females produced by each female during her life. Even if the census size is equal, populations belonging to species with low reproductive capacity, such as the horse, are at relatively greater risk than populations belonging to species with high reproductive capacity, such as the pig. This is because in species with lower reproductive capacity, recovery from a population decline will take more time and more generations of breeding. For example, because female pigs can produce ten or more offspring per litter and multiple litters per year, a pig population may easily double its census size within a single year, whereas the same process would require many years for a horse population.

For the sake of simplicity, when assigning breeds to risk status categories FAO has previously not used different thresholds for different species (FAO 1998, 2007b). In these guidelines a refinement of this type is introduced, but in a simplified form. Species are assigned to two groups, the first group comprises species that have high reproductive capacity, such as pigs, rabbits, guinea pigs and avian species, and the second comprises species that have low reproductive capacity, i.e. those belonging to the taxonomical families Bovidae, Equidae, Camelidae and Cervidae. For the reasons described above, the species in the low reproductive capacity group have thresholds for the number of breeding females and for overall population size that are three times greater than those used in the high reproductive capacity group (this applies to all risk-status categories) (Alderson, 2010). Thresholds for the number of males (i.e. for F) are the same for all species, as the reproductive capacity of a species is primarily determined by the reproduction capacity of the females. Table 2 shows the reproductive capacity classification for all species recorded in DAD-IS.

CGRFA/WG-AnGR-7/12/Inf.6 Table 2. Reproductive capacity of livestock species recorded in DAD-IS.

High reproductive capacity Low reproductive capacity Cassowary Chicken Alpaca Ass Chilean tinamou Dog Bactrian camel Buffalo Duck Emu Cattle Deer Goose Guinea fowl Dromedary Goat Guinea pig andu Guanaco Horse Ostrich Partridge Llama Sheep Peacock Pheasant Vicua Yak Pig Pigeon Quail Rabbit Swallow Turkey Risk status classification Extinct: A breed is categorized as extinct when there are no breeding males or breeding females remaining. The categorization refers to live animals. Even if genetic material that would allow recreation of a breed has been cryoconserved, the breed will nonetheless be classified as extinct. If countries have breeds that have no live animals but have genetic material stored in a gene bank, they are encouraged to indicate in DAD-IS that a cryoconservation programme is active. Such breeds can then be reported as cryoconserved by FAO. However, the interpretation of these data may be difficult, as the ability to reconstitute an extinct breed depends on the amount of and type of stored material.

From a practical point of view, extinction may occur well before the loss of the last animal or genetic material, because a small number of living animals or small quantity of stored germplasm represents a very small amount of genetic information, which may be insufficient to keep the breed viable in the long term.

Critical: A breed is categorized as critical if:

the total number of breeding females is less than or equal to 100 (300 for species with low reproductive capacity);

or the overall population size is less than or equal to 80 (240) and the population trend is increasing and the proportion of females being bred to males of the same breed is greater than 80 percent (i.e. cross-breeding is equal to or less than 20 percent);

the overall population size is less than or equal to 120 (360) and either the population trend is stable or decreasing, or the percentage of females being bred to males of the same breed is equal to or less than 80 percent (i.e. cross-breeding is greater than 20 percent);

or the total number of breeding males is less than or equal to five (i.e. F is 3 percent or greater).

If the population trend is unknown, then it is assumed to be decreasing. Likewise, if the proportion of females bred to males of the same breed is unknown, it is assumed to be less than 80 percent.

Breeds for which demographic characteristics suggest a critical risk of extinction, but that have active conservation programmes (including cryoconservation) in place, or populations that are maintained by commercial companies or research institutions are considered to be critical-maintained for reporting purposes.

Endangered: A breed is categorized as endangered if:

the total number of breeding females is greater than 100 (300 for species with low reproductive capacity) and less than or equal to 1 000 (3 000);

or the overall population size is greater than 80 (240) and less than 800 (2 400) and increasing in size and the percentage of females being bred to males of the same breed is above 80 percent;

or the overall population size is greater than 120 (360) and less than or equal to 1 200 (3 600) and either the trend is stable or decreasing or the percentage of females being bred to males of the same breed is equal to or less than 80 percent;

or the total number of breeding males is less than or equal to 20 and greater than five (i.e. F is between 1 and 3 percent);

CGRFA/WG-AnGR-7/12/Inf.6 Once again, if the population trend is unknown, then it is assumed to be decreasing. Likewise, if the proportion of females bred to males of the same breed is unknown, it is assumed to be less than 80 percent.

Endangered breeds will be assigned to the subcategory endangered-maintained if active conservation programmes are in place or if their populations are maintained by commercial companies or research institutions.

Vulnerable: A breed is categorized as vulnerable if:

the total number of breeding females is between 1 000 and 2 000 (3 000 and 6 000 for species with low reproductive capacity);

or the overall population size is greater than 800 (2 400) and less than or equal to 1 600 (4 800) and increasing and the percentage of females being bred to males of the same breed is greater than 80 percent;

the overall population size is greater than 1 200 (3 600) and less than or equal to 2 (7 200) but decreasing and the percentage of females being bred to males of the same breed is equal to or below 80 percent;

or the total number of breeding males is between 20 and 35 (i.e. the F is between 0.5 and percent).

Unknown population trends and proportions of females bred pure are assumed to be decreasing and less than 80 percent, respectively.

Not at risk: A breed is categorized as not at risk if the population status is known and the breed does not fall in the critical or endangered categories (including the respective subcategories) or the vulnerable category. In addition, a breed can be considered not at risk even if the precise population size is not known, as long as existing knowledge is sufficient to provide certainty that the population size exceeds the respective thresholds for the vulnerable category. Nevertheless, for such breeds the implementation of a survey to obtain a more precise estimate of population size is strongly recommended (FAO, 2011b).

Unknown: This category is self-explanatory and calls for urgent action. A population survey is needed;

the breed could be critical, endangered or vulnerable!

Table 3. Risk categories according to numbers of breeding females, numbers of males and species reproductive capacity* Breeding females (n) Reproductive Males 100 101 - 300 301 - 1 000 1 001 - 2 000 2 001 - 3 000 3 001 - 6 000 >6 capacity (n) High* 6 - 21 - > Low** 6 - 21 - < = critical, = endangered, = vulnerable and = not at risk.

* High reproductive capacity species = pigs, rabbits, guinea pigs, dogs and all poultry species.

**Low reproduction capacity species = horses, donkeys, cattle, yaks, buffaloes, deer, sheep, goats and camelids.

Table 3 shows the risk classification system graphically, as a function of numbers of breeding-age females, numbers of males and the reproductive capacity of the species. Note that in each case, a low value for the least favourable parameter is sufficient to result in the breed being allocated to the higher risk-status category. For example, if the population includes only five males, the breed is allocated to the critical category even if the number of breeding females exceeds 6 000.

CGRFA/WG-AnGR-7/12/Inf.6 Tables 4 and 5 are similar to Table 3, but they show the risk categories when the size of the entire population is used rather than the number of breeding females, along with the population trend and the proportion of females mated to males of the same breed. Table 4 presents results for populations with high reproductive capacity and Table 5 presents results for species with low reproductive capacity.

Table 4. Risk categories for species with high reproductive capacity*, according to total population size and trend, numbers of males and proportion of pure-breeding Population size (n) Population trend and pure-breeding Males 80 81 - 20 121 - 800 801 - 1 200 1201 - 1 600 1601 - 2 400 >2 proportion** (n) Increasing trend and >80% pure- 6 - breeding 21 - > Decreasing trend or 80% pure- 6 - breeding 21 - > = critical, = endangered, = vulnerable and = not at risk.

*High reproductive capacity species = pigs, rabbits, guinea pigs, dogs and all poultry species.

** When trend and proportion of pure-breeding are unknown, trend is assumed to be decreasing and pure-breeding is assumed to be <80 Percent.

Table 5. Risk categories for species with low reproductive capacity*, according to total population size and trend, numbers of males and proportion of pure-breeding Population trend Population size (n) and pure-breeding Males 240 241 - 360 361 - 2 400 2 401 - 3 600 3 601 - 4 800 4 801 - 7 200 >7 proportion** (n) Increasing trend and >80% pure- 6 - breeding 21 - > Decreasing trend or 80% pure- 6 - breeding 21 - > = critical, = endangered, = vulnerable and = not at risk.

* Low reproduction capacity species = horses, donkeys, cattle, yaks, buffaloes, deer, sheep, goats and camelids.

** When trend and proportion of pure-breeding are unknown, trend is assumed to be decreasing and pure-breeding is assumed to be <80 percent.

Action 2. Refine the categorization of risk The thresholds presented in Tables 3 to 5 for assignment of breeds to risk categories in DAD-IS were developed for general application on a global level. They should be used judiciously at national level.

They provide a basis for ranking breeds within a country according to degree of risk. They should prompt the need for additional data collection and breed monitoring. Studying similarities among breeds in the same categories may also help to identify factors acting upon the degree of risk for local animal genetic resources, now and in the future. They should not be applied uncritically, however.

For example, simply to assume that all populations with more than 1 000 females (>3 000 for species with low reproductive capacity) and 15 males are not endangered may be risky. Historical bottlenecks or inappropriate mating and selection systems may have resulted in an average relationship and F in the population that are much greater than expected based on numbers of breeding males and females.

In such cases, the need for action is as urgent as in the case of breeds assigned to higher risk-status CGRFA/WG-AnGR-7/12/Inf.6 categories. One option for addressing this issue is to calculate F by using a more sophisticated approach (see Section 6) and reclassify the breed according to the F thresholds provided rather than according to the DAD-IS criteria based on numbers of males.

Potential factors to be considered in refining the DAD-IS risk categories:

Population trend is not considered in the assignment of DAD-IS risk status when the number of breeding females is used as the population size parameter. For breed management at national level, a more informative approach is to estimate population growth and assign risk status based on the projected population size ten years into the future.

Concentration of a major part of the population in a restricted geographical area or in a few herds will usually place the breed at greater risk from the consequences of catastrophic events (i.e. events that occur rarely but that greatly reduce the size of the livestock population in the affected area) such as disease outbreaks, natural disasters and political upheavals. When the occurrence of such events is considered possible, breeds with a concentrated distribution should be upgraded to the next (higher) risk-status category (e.g.

from vulnerable to endangered). Such an approach has been developed for the United Kingdom (Alderson, 2009). The thresholds in this case are based on the maximum radius of a circle in which 75 percent of the population of a breed is found: if the radius is less than 12.5 km, then the breed is assigned to the critical category;

and if the radius is between 12.5 km and 25 km the breed is assigned to the endangered category.

Although the DAD-IS risk classification does not consider proportion of pure-breeding females when the number of breeding females is used as the population size criterion, countries should calculate the proportion of cross-breeding that occurs. Females used for cross-breeding do not contribute to population renewal. In addition, it is important to monitor the degree of introgression from other breeds in both the females and the males of the population (i.e. if cross-bred animals are used for mating, rather than simply marketed in a terminal crossing system see Section 7). Continual cross-breeding and introgression of genetics from other breeds will erode the original genetic variation of the population. Levels of 12.5, 7.5 and 2.5 percent introgression per generation have been suggested as thresholds for considering a population critical, endangered and vulnerable, respectively (Alderson, 2010). For the sake of simplicity, this factor has not been taken into account as a risk criterion in these guidelines.

However, it should be considered when taking action at national level.

In the above discussion of the genetic aspects of risk (i.e. F) the generation is used as the unit of time. Genetic changes in a population occur at the transmission of genes from parents to progeny. The F should be low enough to avoid expression of deleterious alleles (i.e. genetic defects and inbreeding depression Meuwissen and Woolliams, 1994) and their accumulation in the long term. However, in planning a conservation programme, it is necessary to consider actions and consequences in terms of years. To account for this, we can convert F per generation to a yearly rate by dividing F by the average generation interval (in years).

Generation interval varies according to the species and the breeding system. Average generation intervals in major livestock species are approximately as follows:

at least one year for avian species;

o 1 to 2 years for pigs;

o 4 years for sheep and goats;

o 6 years for cattle, buffalo, llamas and alpacas;

and o 8 years for horses, asses and camels.

o The differences in generation intervals imply that populations exposed to similar F per generation but belonging to different species will accumulate different amounts of inbreeding in a given time period. For example, a pig population (generation interval of two years) with F of 1 percent will accumulate 15 percent inbreeding in 30 years, while in the same time period a cattle population (generation interval of six years) will accumulate percent inbreeding. Although generation interval will not affect risk status at any single moment in time, this factor should be kept in mind in making plans for the future, especially in situations when is not possible to increase the population size rapidly to above the critical or endangered threshold (such limited animal housing facilities in an in vivo ex situ CGRFA/WG-AnGR-7/12/Inf.6 programme). Breeding approaches to avoid inbreeding (see Section 6) will be particularly important in such cases.

When more information is available, and in particular when a breed is on the borderline between risk categories, additional analysis should be undertaken in order to refine the state of knowledge about the breeds degree of risk, reasons for this degree of risk, and how to conserve the breed. For example, the demographic and inbreeding aspects of risk can be more precisely evaluated by considering the numbers (and year-to-year trends) of registered females, number of males used in AI, number of herds, and the trends. Pedigree data and information about historical bottlenecks will yield information about genetic variability.

As described above, populations should be assigned to risk categories according to the least favourable parameter, i.e. if one parameter indicates a high degree of risk the breed should be assigned to a high-risk category even if other parameters correspond to a lower degree of risk. For example, populations consisting of several hundred females and a very limited number of males are not uncommon. For example, consider a breed population consisting of 3 400 cows, which is stable in size and in which five bulls are used for AI. This population should be categorized as critical, based on the low number of males, even though the number of females would qualify the breed as vulnerable. In such cases, it is important to underline the fact that the breed is in a high risk category because of suboptimal management. By simply increasing the number of males from 4 to 25, the breed could be moved up into the vulnerable category.

Action 3. Interpret results of the risk classification and contemplate the consequences for each breed The genetic and demographic consequences associated with the different risk categories are shown in Table 6: the higher the risk category, the more unfavourable the genetic and demographic consequences and the more urgent the need for action (see Section 3). If the risk category is high, the breed suffers greater loss of diversity due to inbreeding depression and loss of alleles and faces greater risk of extinction due to random events, such as disease outbreaks, natural disasters and even low fertility rates or unequal sex ratios among the offspring.

Table 6. Genetic and demographic consequences associated with risk categories Genetic consequences Demographic consequence Risk category Loss of diversity Genetic defects Susceptibility to random events Critical ++++ ++++ +++ Endangered +++ ++ + Vulnerable ++ + Not at Risk + + Note: the number of + signs corresponds to the severity of the negative consequence.

Note that even populations that are classified as not at risk are subject to loss of genetic diversity and expression of deleterious alleles. However, this occurs with less intensity than in breeds in the at-risk categories.

Alternative systems of risk categorization As described above, various procedures have been proposed and are used for estimating degrees of risk and for categorizing breeds according to their risk status (for reviews see Gandini et al., 2005;

Alderson, 2009;

Alderson 2010;

Boettcher et al., 2010). Some methods emphasize population demography (e.g. EC Commission Regulation 445/2002 7), others, such as that proposed by the European Federation of Animal Science (EAAP), emphasize genetic erosion based on estimates of N e (e.g. EFABIS http://efabis.net). When countries have more information available than is needed for categorizing breeds according to the worldwide FAO system, they may wish to develop national criteria and thresholds for risk categories. If countries develop their own approaches, it is strongly recommended that they base them on the general demographic and genetic principles presented above http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:32002R0445:EN:NOT CGRFA/WG-AnGR-7/12/Inf.6 and seek, as far as possible, to use criteria similar to those used elsewhere, as this will facilitate comparisons of risk status on an international scale.

Specific risk criteria can also be developed at regional level, taking into account the levels of data availability common to the countries of the region. Such criteria are, for example, used to classify European transboundary breeds recorded in EFABIS. In the case of breeds that are kept in more than one country, degree of risk should be calculated first at national level;

then, in collaboration with the other countries in which the breed is present, it should be calculated at regional or global level. DAD IS offers users the possibility to visualize simultaneously the risk status of national populations of transboundary breeds and also calculates risk status on an international level. When exchange of animals or germplasm (semen and/or embryos) among country populations is large enough, these populations can be considered subgroups of a single large population. In such cases, if national populations are at risk due to their small sizes, it is essential that countries collaborate and manage their national populations as a large single population. Programmes for common management of country populations should be implemented in particular for breeds in the critical and endangered categories, with the aim of controlling or reducing their risk status.

Population sizes and breed utilization The categorization systems described above are based on population numbers required to reduce genetic erosion and decrease the risk of extinction. Larger population sizes may be necessary for practical reasons, such as to guarantee the fulfilment of breed roles such as provision of cultural, environmental or social services, or to develop niche products (see Section 8). In addition, larger breed populations have more scope for combining increased selection with the maintenance of genetic diversity (see Section 7).

Because the categorization system used by FAO is designed specifically for use in assessing genetic erosion and risk of extinction rather than for assessing breeds contributions to a wider range of national and regional needs and objectives, the system is not recommended as a basis for breed subsidy programmes.

Action 4. Disseminate information about risk to stakeholders The degree of risk provides an indication of the time that is available to evaluate options and to act to save the breed before it becomes extinct. Therefore, once a breeds risk status has been established, it is important to communicate this outcome to all relevant stakeholders as soon as possible. Ideally, the information will stimulate the stakeholders to act. Surveying and Monitoring of Animal Genetic Resources (FAO, 2011a) provides detailed information on how report and communicate the results of surveys and indicates the importance of providing stakeholder groups with information that is tailored to their needs. It also provides advice on how identify appropriate messages and communication methods.

Effective dissemination of information on breeds risk status can also raise awareness among policy makers and the general public. This may facilitate the raising of funds to support breed conservation activities. One approach that can be adopted at national level is to develop and publish a Red List of breeds at risk of extinction.

Although dissemination of information at national level is of primary significance, exchange of information about breeds at risk is also important at international level. National Coordinators should ensure that all relevant breed population data available at national level is entered into DAD-IS or (for European countries) EFABIS. It is also important to communicate to both national authorities and international collaborators the difficulties encountered in population monitoring and information dissemination so that they can be taken into account in the planning of subsequent investigations.

Task 3. Design and implement interventions according to the risk category Different risk categories require different conservation measures. With the exception of implementing a formal selection programme (which is not recommended for small populations), the actions should be similar for all categories, but the stress and urgency put on each will vary from one risk category to another. The interventions must also consider the countrys livestock development objectives, available resources and technical capacity, as well as the needs and wishes of stakeholders, particularly the livestock keepers.

Action 1. Identify the most appropriate interventions, based on risk status CGRFA/WG-AnGR-7/12/Inf.6 Table 7 outlines the relative emphasis that should be given to four different types of intervention enlarging the population, managing diversity, selection for productivity and cryoconservation;

according to risk category.

Table 7. Relative importance of different animal genetic resources management objectives for populations in different risk-status category Risk category Enlarging the Managing Selection for Cryoconservation population diversity productivity Critical +++ ++ +++ Endangered ++ +++ ++ Vulnerable + + +++ + Not at risk +++ Populations categorized as critical will have already lost a major part of their original genetic variation and require urgent attention. Two basic requirements are 1) to determine the genetic status of the populations (e.g. accumulated inbreeding and/or amount of introgression from other breeds) and 2) to assess the likelihood of the breed recovering from the critical status. If recovery is deemed possible, efforts should be directed primarily towards increasing the real population size of the breed while controlling inbreeding through judicious mating. In such populations, enlargement of real population size is the first objective. This means that if possible, all animals should remain in the active breeding population even if they are closely related to other animals in the population. The use of advanced reproductive technologies such as superovulation and embryo transfer may also be justified.

Increasing the census size will help increase the N e. If possible, semen and/or embryos should be cryoconserved to help insure against breed loss in the short term and to improve management of genetic variation in the long term.

For populations categorized as endangered, the objective of interventions should be to prevent them from falling into the critical category and ideally to raise them to vulnerable status. Emphasis should be placed on increasing the N e as well as the census size. Relative to critical breeds, endangered breeds offer more opportunity for managing genetic diversity, such as by targeting specific animals in population expansion activities (i.e. targeting individual animals that are less related to the general population than others see Section 6). Cryoconservation to complement in vivo conservation is recommended.

Vulnerable populations should be managed so as to prevent them from falling into the endangered category, and thus selection for production is paramount, although it should be optimized with maintenance of genetic diversity (see Section 7). The dynamics of vulnerable populations should be continuously monitored so as to understand the factors threatening the breeds viability. Programmes to increase the breeds economic competitiveness should be implemented if possible (Section 8).

Preventing vulnerable breeds from reaching the higher risk categories is preferable to applying remedial actions. Vulnerable populations should be subject to genetic improvement measures, but measures to maintain a sufficiently large N e (i.e. at least 50) should also be implemented along with actions designed to increase the census size. Although the need for cryoconservation will not be as great as in critical and endangered breeds, banking of genetic material from vulnerable breeds is recommended, especially if it can be simply implemented as part of a conventional artificial programme.

The absence of a + sign in a cell in Table 7 does not mean that the corresponding activity is irrelevant.

For example, increasing the population census size is always desirable, even for not-at-risk breeds.

However this will not be a priority in management plans for such breeds. Some selection for production to help improve profitability may be desirable for any breed, but is very unlikely to be feasible for critical and endangered populations without compromising genetic variability. Cryoconservation can always be beneficial, but its benefits exceed its costs by a greater margin when extinction risk is higher.

Although not shown in Table 7, populations categorized as unknown should not to be ignored.

These breeds need urgent analysis to determine their risk status. Breed surveys should be undertaken as soon as possible.

CGRFA/WG-AnGR-7/12/Inf.6 Action 2. Implement the interventions Whichever interventions are proposed, they should be undertaken in a timely and efficient manner.

Details about implementing specific interventions are presented in Sections 4 to 8.

Task 4. Update risk status.

Livestock production systems in many areas of the world are being transformed rapidly. These changes may affect demographic trends and the genetic status of breeds within short periods of time. It is therefore advisable to establish within each country a methodology for regularly updating the risk status of breeds, as well as early warning and information systems capable of monitoring changes in the nature and intensity of the major factors affecting negatively breed risk. For example, cross breeding activities should be strictly monitored, as should the number of males and their use, especially in populations where AI is widely practised. Efficient monitoring and analysis of population data is a prerequisite for the timely implementation of conservation measures.

The methods used for surveying the status of animal genetic resources and the threats facing them may change over time as new techniques become available and production systems change. In such cases, the change from one method to another needs to be carefully analysed before the adoption of the new method in order to ensure consistency between older and newer data. For further advice on this and other aspects of planning a national monitoring strategy for animal genetic resources, see FAO (2011b).

References Alderson, L. 2009. Breeds at risk: Definition and measurement of the factors which determine endangerment. Livestock Science, 123: 23-27.

Alderson, L. 2010. Report from the seminar "Native breeds at risk, criteria and classification", London 2010.

CBD. 1992. Convention on Biological Diversity. Montreal (available at http://www.cbd.int/convention).

FAO. 1998. Secondary guidelines: management of small populations at risk. Rome (available at http://www.fao.org/ag/againfo/programmes/es/lead/toolbox/Indust/sml-popn.pdf).

FAO. 2007a. Global Plan of Action for Animal Genetic Resources and the Interlaken Declaration.

Rome (available at ftp://ftp.fao.org/docrep/fao/010/a1404e/a1404e00.pdf).

FAO. 2007b. The State of the Worlds Animal Genetic Resources for Food and Agriculture, edited by B.

Rischkowsky & D. Pilling. Rome (available at www.fao.org/docrep/010/a1250e/a1250e00.htm).

FAO. 2011a. Status and trends of animal genetic resources 2010. Rome (available at http://www.fao.org/docrep/meeting/021/am131e.pdf).

FAO. 2011b. Surveying and monitoring of animal genetic resources. FAO Animal Production and Health Guidelines. No. 7. Rome (available at www.fao.org/docrep/014/ba0055e/ba0055e00.pdf).

Gandini, G., Ollivier, L., Danell, B., Distl, O., Georgudis, A., Groeneveld, E., Martiniuk, E., van Arendonk, J. & Woolliams, J. 2005. Criteria to assess the degree of endangerment of livestock breeds in Europe. 2005. Livestock Production Science, 91: 173182.

Santiago, E. & Caballero, A. 1995. Effective size of populations under selection. Genetics, 139:


Sponenberg, D.P. & Christman, C.J. 1995. A conservation breeding handbook. Pittsboro, USA, The American Livestock Breeds Conservancy.

CGRFA/WG-AnGR-7/12/Inf.6 III. DETERMINING THE CONSERVATION VALUE OF A BREED Upon completion of the activities described in Section 2, a country will have a measure of the risk status of each of its breeds. All breeds in at-risk categories can be considered candidates for conservation activities. Ideally, a conservation programme would be developed for all at-risk breeds.

In most countries, however, the costs required to conserve all breeds at risk will be greater than the resources available for conservation. Depending on the goal of the conservation programme, the conservation of all breeds may anyway not be justifiable. Some breeds may be judged to have no particularly unique or valuable characteristics worth conserving, either for the immediate or the longer term, and have little historical or cultural significance. In other cases, breeds may be very similar to each other genetically, meaning that a large proportion of the genetic diversity of the total population can be captured by conserving only a subset of breeds, or in some cases by making a composite population by combining multiple closely related breeds. Countries will need to decide how the resources available for conservation should be utilized and which breeds should be conserved.

A wide range of approaches for prioritizing breeds for inclusion in conservation programmes is available. These approaches vary considerably in the types of information and data used and in their complexity and precision. This section is therefore broken into two subsections that differ in terms of complexity. Specifically, the second subsection describes methods that use genetic markers for evaluating genetic variability, whereas the first subsection involves techniques that do not require genetic markers. The approaches described generally increase in complexity and in the amount of information required as one reads further into each subsection.

Before choosing a prioritization method, countries should consider the level of precision they require and the state of capacity to implement various options. In some cases, the National Advisory Committee will need to collaborate with local researchers and other experts to implement the prioritization methods. The more complex approaches described below will not be feasible for some countries because of a lack of molecular genetic data or technical capacity. If this is the case, the simple approaches outlined in the following subsection are perfectly acceptable. However, both phenotypic and molecular genetic characterization should receive due consideration in a countrys national strategy and action plan for animal genetic resources to help ensure that prioritization can be as accurate as possible.

Accounting for factors other than risk status in prioritizing breeds for conservation Rationale Risk status is generally considered the most important criterion for determining whether a breed should be subject to conservation activities. As a simple approach, breeds can be ranked according to their risk status, and those at the greatest risk given the greatest priority for conservation. However, other factors may influence a breeds conservation value, and countries may wish to consider these as well. Among the factors that may influence the conservation priority of a breed are the following (Ruane, 2000).

Species In general, breeds belonging to species that are more economically or culturally important to a country will merit a greater priority in conservation strategies. In addition, species should be given high conservation priority in the countries where they were originally domesticated, especially if the species are not common in other parts of the world. For example, in Peru, the alpaca has a high conservation value for all the above reasons.

Practical considerations may also influence conservation priorities among species. In vivo conservation programmes for small animals, such as poultry, rabbits and even small ruminants, are likely to be less costly than programmes for larger species such as cattle or horses. Thus, if all other factors (e.g. economic, cultural, etc.) are equal, the smaller species may merit greater priority because more breeds can be conserved per unit of resources spent on conservation. On the other hand, larger animals may have more value per animal unit.

CGRFA/WG-AnGR-7/12/Inf.6 Most formal, objective procedures for prioritization of breeds for conservation (see below) are applicable for use within species rather than across species.

Genetic diversity of the breed As described above, genetic diversity is critical to the conservation of animal genetic resources.

Two aspects of genetic diversity can be considered in conservation decisions:

Genetic uniqueness of the breed. Maintaining breeds that are genetically distinct is often a high priority for national conservation programmes. At-risk breeds that are distinct from each other and from the breeds in the not-at-risk category are particularly valuable from a genetic point of view, as they may be more likely to have unique alleles and gene combinations (see Box 10). Understanding the genetic history of a particular breed will assist in determining its uniqueness.

Genetic variation within the breed. Genetic variation gives an animal genetic resource the capacity to adapt and allows for genetic response to selection. Conserving the most genetically diverse breeds is the most efficient way to conserve the diversity of a given species.

Box Unique alleles allow the Araucana chicken of Chile to produce natural Easter eggs The Easter egg hunt is a traditional holiday event in many predominantly Christian countries. Children search in parks and gardens for painted eggs that were supposedly hidden by a mythical rabbit.

However, breed of chicken is able to provide coloured eggs year-round, by a totally natural process.

The Araucana hen is an endangered chicken breed from Chile. It is recognized for its particular phenotypic characteristics, the presence of earrings (straight feathers coming from the neck, right down their ears, like earrings) and blue-shelled eggs. These features occur because of the existence of the gen Et and gen O alleles in the breeds genome, which are unique in the species. The Araucana hen is also well-known in its local area for its high rusticity. It is capable of withstanding extreme temperatures and tolerating locally present diseases. The eggs and laying hens can command very high prices, which may even be twice as high as those of commercial breeds. The breed is associated with the Mapuche, an indigenous Chilean community, who uses it in traditional ceremonies and raise it in extensive systems. Today, the Chilean Government and other stakeholders are developing research programmes involving the conservation of Araucana genetic material and its use by the indigenous community.

Provided by Ignacio Garca Len and Pascalle Renee Ziomi Smith.

Phenotypic characteristics of the breed Traits of economic importance. Clearly, if a breed has exceptional economic productivity this is likely to be due in part to superior genetics. Thus, action should be taken to ensure these genes are available for breeding programmes. Both the current and potential future importance of particular characteristics should be considered. Of course, breeds whose economic value is currently high are less likely to be currently at risk.

Agricultural economists have proposed a system with which to describe the values for animal genetic resources that mirrors approaches used to describe other types of resource (see Box 10).

The system facilitates the comparison of attributes that can be immediately marketed (such as milk or meat) with those that cannot (such as genetic variation).

Unique traits. Breeds with special behavioural, physiological or morphological traits should be given high priority for conservation, as these traits are likely to have a genetic basis and be associated with unique alleles (see Box 11).

CGRFA/WG-AnGR-7/12/Inf.6 Box Botfly resistance in the Blanco Orejinegro cattle of Colombia The Blanco Orejinegro is a Colombian Creole cattle breed distinguished by its white coat and black ears. The breed descends from the cattle introduced by the Spanish conquistadores in the fifteenth century and was developed in the central foothills of the Andes, the region of the country known for its coffee production. Also endemic to this region is the botfly (Dermatobia hominis, or "nuche" in Spanish), a parasite of cattle skin. Botfly infections cause huge economic losses, not only because of the damage caused to hides by the movement of the botfly larvae under the cattles skin, but also because of the weight loss that occurs because of discomfort and secondary infections caused by lesions produced when the larvae penetrate the skin at the start and the end of their lifecycles. At El Nus Research Station, located in Antioquia, Colombia, many studies on cattlebotfly interactions have been carried out since 1948. Studies have shown that the progeny of animals that were not parasitized (i.e. that showed resistance) were also resistant. This led researchers to conclude that this resistance has a genetic origin, most likely controlled by one or a few genes acting in a non-additive (dominant) manner. The presence of these genes makes the Blanco Orejinegro a valued genetic resource for livestock production in this area of Colombia, and possibly in other countries where the botfly is endemic.

Provided by German Martinez Correal.

Adaptation to a specific environment. The adaptation of breeds to specific environments is likely to be under some genetic control. Thus conservation of breeds showing such adaptations may be important. Environmental adaptations will be especially important if the conditions to which the breed is adapted are likely to become more common in the future (e.g. warmer conditions under predicted climate change scenarios).

Cultural or historical value Breeds were developed in part by human intervention and thus can be regarded as part of the cultural or historical heritage of a give region or population that has been passed down the generations and thus should be passed on to future generations (Ruane, 2000). Therefore, breeds with greater cultural importance should receive greater conservation priority. In many areas of the world, traditional grazing over many centuries has contributed to the creation and maintenance of agro-ecosystems of high biodiversity value. Similarly, many landscapes have been shaped over time by traditional farming systems. The results of co-evolutionary processes among locally adapted breeds, traditional framing systems and the natural environment retain their character and richness as long as the breed and production system are maintained. For example, grazing livestock maintain the distinctive features of alpine meadows. A breeds role in maintaining a unique ecosystem may be a reason for giving it a high priority for inclusion in a conservation programme. Methods for estimating the cultural value of a breed are available (Gandini and Villa, 2003;

Simianer et al., 2003).

Probability of success in conserving the breed The main reason for prioritizing among breeds is to ensure that available resources are invested as wisely as possible. The future sustainability of a conserved breed must therefore be considered during the prioritization. Factors such as the existence of a breeders association, organized record keeping, the existence of a stock of semen from males of previous generations, or evidence of interest and cooperation among breeders often indicate a greater chance that the breed will be able survive with only a relatively small amount of formal assistance from outside.

On the other hand, breeds in a critical state of risk whose population has declined to only a few animals (and that has no other resources such as cryopreserved semen or embryos) may never regain a large and diverse gene pool, regardless of the interventions undertaken.

CGRFA/WG-AnGR-7/12/Inf.6 Status of a breed at regional level When only local breeds are considered for a national conservation programme, prioritization is simplified because only the factors listed above need be considered. The situation is more complex when transboundary breeds are candidates for conservation. Such breeds can be at-risk in one country and not at risk in another country or not at risk on a regional basis if all national populations are considered. DAD-IS assigns a global risk status to transboundary breeds, but this should be regarded simply as an estimate. The relevant countries should collaborate to establish a more definitive risk status for each transboundary breed.

An individual country may give a transboundary breed low conservation priority under the assumption that another country will conserve it. This creates the risk that some breeds will end up being conserved by no country. The best solution is discussion, prioritization and planning for conservation of such breeds at regional level. A similar approach could be applied at the global level, for international transboundary breeds at risk.

Objective: To determine the conservation value for each breed based on non-demographic factors.


1. List of breeds at risk;

and 2. Sources of information (including stakeholders) about factors influencing conservation value.


Information about factors affecting the conservation value of each breed;

and Ranking of breeds on the basis of conservation value.

Task 1. Assess the conservation priority of breeds according to non-demographic factors Action 1. Assign responsibilities for prioritization of breeds An entity with the responsibility for determining the conservation value of breeds must be established so that a clear and unambiguous decision can be made. This responsible entity may be the National Advisory Committee on animal genetic resources (see Section 1), a special conservation task force, a specialized NGO that works with keepers of breeds at risk, or even a single individual with sufficient knowledge of the animal genetic resources within the country. For simplicity, the discussion in this section will always refer to the National Advisory Committee as the entity responsible for prioritizing breeds for conservation. Whatever entity is given this task, participatory approaches to prioritization should be used and representatives of all major stakeholders should be consulted.

Action 2. Determine the factors upon which the calculation of conservation value will be based, according to the desired conservation strategy The first activity of the responsible entity will be to evaluate the conservation objectives for each species (see Section 1) and, based upon these objectives, agree upon the factors to be considered in determining the conservation value of the breeds, as well as their relative importance.

The thought process required in order to obtain a list of specific factors for use in assessing conservation value based on a general conservation objective may be facilitated by considering the overall strategy for conservation of animal genetic resources in a country. Bennewitz et al. (2007) outlined three strategies to consider.

1. Maximum risk strategy. This strategy considers only the degree of endangerment, and can be justified if the main objective of the country is primarily to prevent the near-term loss (within ~10 years) of breeds at high risk of extinction.

2. Maximum diversity strategy. This strategy considers only the genetic diversity of a breed relative to the amount of diversity of other breeds that at are risk and as a complement to the diversity of the breeds that are not at risk. This strategy may be optimal where a fixed amount of financial support is available for conservation activities and the goal is to capture as much genetic diversity as possible for the funds available.

CGRFA/WG-AnGR-7/12/Inf.6 3. Maximum utility strategy. This strategy considers factors beyond risk of endangerment and genetic variability. Although this strategy may be applicable in many situations, it should particularly be used if conservation programmes are expected to be partially or fully economically self-sustainable.

The choice of the strategy, the factors influencing priority and the relative importance of each factor are decisions that merit serious thought and discussion. The choice of breeds to be targeted may vary greatly depending on the strategy and factors chosen, especially when there are many breeds at risk and few resources for their conservation. Some factors that may influence conservation priority are antagonistic, and breeds that excel for one may rank poorly for another. For example, breeds at the greatest risk of extinction (and thus deserving of the highest priority with the maximum risk strategy) will often be low in genetic diversity (maximum diversity strategy) and/or genetic value for economic or special traits (maximum utility strategy). Also, the probability of success of the conservation programme is often lowest for the breeds at the greatest risk of extinction.

In some cases, two or more factors may be closely related. For example, the cultural importance of a breed may be tied to its genetic uniqueness or presence of a special trait. In such cases, consideration of all these factors may result in their over-emphasis in determining conservation priority.

If quantitative methods are going to be used to rank breeds (see below in this section), the National Advisory Committee should agree on numerical weights for the factors used to determine conservation value that are proportional to their relative importance. Various approaches have been proposed to aid in the process of assigning weights. A simple participatory and visual approach is called participatory piling, whereby members of the group charged with assigning weights are each given a certain number of small objects (stones, marbles, beans, etc.) and asked to distribute them across the various factors based on their perceived importance. The results are then averaged across the participants to obtain overall weights.

In a more objective but more complicated approach, economists have suggested assigning the values of breeds to different classes and estimating values in monetary terms. Box 12 describes an approach for classifying values that may be applied to breeds or other animal genetic resources.

Box Values of animal genetic resources From a formal economic perspective, animal genetic resources can have various different types of values for conservation. These values can be categorized as follows (Drucker et al., 2001;

FAO 2007):

Direct use value results from benefits obtained from the utilization of animal genetic resources, such as the production of milk or meat;

Indirect use value results from the provision of support or protection to other activities that produce benefits, such as through the provision of regulating and supporting ecosystem services;

Option value results from the potential benefits of having a given resource available for the future;

for example, having genetic variability available that can be used to respond to market and environmental changes;

Bequest value results from benefits that might be obtained from the knowledge that others may derive benefits from the animal genetic resource in the future;

Existence value derived only from the satisfaction of knowing that a given animal genetic resource exists, even if no other type of value can be derived from it.

In most instances, indirect use and option values will be the most important for at-risk animal genetic resources, as these are values in which locally adapted breeds are likely to excel over other breeds. Increasing, the direct use value will contribute to economic sustainability of a breed and therefore, the potential success of conservation activities (see Sections 7 and 8). Bequest and existence values are likely to apply only in particular situations.

CGRFA/WG-AnGR-7/12/Inf.6 A method known as choice modelling can be used to obtain quantitative data for the values listed in Box 12. In brief, choice modelling uses a survey or questionnaire to evaluate the preference of respondents (e.g. farmers or other stakeholders) for a set of alternative outcomes (i.e. profiles describing breeds or types of animals). Each of the alternative outcomes is defined by a set of attributes with different levels (i.e. traits of breeds). Then, a statistical model is used to determine the importance of a given value based on the frequency with which the profiles excelling in that value were chosen by the respondents. Some examples of the application of choice models to animal genetic resources are presented in Box 13. Clearly, the success of choice modelling will depend greatly on the appropriateness of the design of the survey and the statistical analysis. Therefore, applying such an approach will generally require consultation with a statistician or other scientist with experience in choice modelling.

Box Using choice models to value and rank breeds for conservation Choice models can be used in order to understand the full range of values livestock can have for people and to express these as a Total Economic Value. The Total Economic Value includes a whole range of values held by breeds, ranging from the value of the goods they produce (use values) to landscape/recreational, adaptive, cultural or simply existence values. Non-use values cannot be assessed from market transactions and are often undervalued if not assessed properly. In choice models, people are asked to state their preferences for hypothetical animal profiles that describe the traits of breeds. People choose their preferred profile, which allows calculation of how much they might be willing to pay for particular traits. Analysis of choice data reveal the values of traits relative to each other and allows ranking of the traits. Choice models have been used widely for valuing livestock breeds in developing countries, mostly in Africa and mostly applied to cattle breeds (e.g. Zander and Drucker, 2008), but also to breeds of small ruminants (e.g. Omondi et al., 2008), chickens (e.g. Faustin et al., 2010) and pigs (e.g. Scarpa et al., 2003). The evaluation can often be used to identify farmers who prefer the traits of traditional breeds and may therefore be willing to conserve them with minimal external incentive payments.

Recently, choice model studies have been carried out on European endangered cattle breeds in order to understand synergies between the use of the animals and conservation management (Fadlaoui et al., 2006). Results showed that the European public would be willing to pay substantial amounts simply to ensure the existence of some breeds for their own sake, but the public also appreciated the role of some at-risk locally adapted breeds as components in traditional landscapes, in cultural events and as sources of premium food products.

Results from choice modelling can be combined with measures of genetic distinctiveness and the costs of conservation, allowing conservation programmes to be ranked according to their efficiency (Weitzman, 1998;

Zander et al., 2009). In countries where farmers already get paid to keep at-risk breeds, choice model results can help maximize the efficiency of such breed conservation programmes, by matching conservation payments to the value of each breed to the public.

Provided by Kerstin Zander.

Action 3. Gather the information necessary to determine the conservation priority Once a decision has been made with regard to the factors influencing conservation priority, research should be undertaken, if necessary, to determine the status of each breed with respect to each factor.

For example, if the phenotypic characteristics of each breed are going to be considered, then this information should be obtained for all or a representative sample of animals. For traits of economic importance, breed averages should be obtained. The presence of unique traits or of adaptation to a particular environment should be noted if these qualities are recognized as important for prioritization.

Pedigrees or genetic markers can provide insight into genetic variation (this topic is discussed in more detail in Section 5). Any historical or cultural significance of the breed should be noted.

Ideally, countries will have already characterized their breeds phenotypically and genetically prior to undertaking decision making on conservation (see Phenotypic characterization of animal genetic resources FAO, 2012 and Molecular genetic characterization of animal genetic resources FAO, CGRFA/WG-AnGR-7/12/Inf.6 2011). If breeds have been characterized, then most, if not all, of the information required will have been gathered through that process. If characterization has not been undertaken, then the most efficient approach would be to combine characterization and gathering of data for conservation decision making. If this is not possible, then the members of the National Advisory Committee or other persons responsible for collecting and organizing the information required may need to consult a number of sources. Ideally, the persons chosen to collect the information will have some existing familiarity with the breeds. Data for phenotypic traits may be available in local or international scientific literature or in local grey literature, such as technical reports. Various stakeholders (e.g. farmers and breeders, local historians) can be consulted to obtain information about other factors such as unique traits and breeding history in order to obtain insight into the uniqueness and cultural significance of the breeds.

Information about genetic diversity can be obtained from a variety of sources, which may differ in terms of their accuracy. For standardized breeds with recorded histories and pedigrees, determining the origin of the breed and the extent to which it has been influenced in the past by other breeds (introgression) likely to be more straightforward than for non-standardized breeds. Pedigree data can be used to estimate the level of inbreeding and its trend over time (F) and therefore N e. As discussed in more detail in the next subsection, genetic markers can be used to evaluate genetic diversity within breeds and genetic relationships among breeds. In the absence of such sources of information, consultation with stakeholders that have knowledge of the history of breeds can yield valuable data.

Past population bottlenecks (severe reduction in population numbers) will have led to lower variation in the current population. Past cross-breeding can be expected to have decreased the uniqueness and distinctiveness of a breed. Widespread use of AI will likely have decreased N e, by increasing the imbalance in the ratio of male versus female parents.

Action 4. Discuss and evaluate the advantages and disadvantages of the breeds Section 1 describes the use of a SWOT analysis to describe the roles, functions and dynamics of livestock species and assist in establishing conservation objectives. The information from the SWOT analysis, along with the information gathered under Action 3 can serve as the basis for a discussion on the values of each breed and its contributions to the various conservation objectives. Ideally, this discussion should be undertaken by the members of the National Advisory Committee. The merits and disadvantages of each breed should be noted. The results of the discussion and evaluation should be summarized in written form, so that the committee can, if requested to do so, easily explain their decisions to policy makers.

Action 5. Rank breeds for conservation priority Based on the group discussion and analysis, breeds should be ranked for conservation priority. Either subjective or quantitative approaches can be used.

At the close of the discussion undertaken in Action 4, it may be possible for committee members simply to arrive at a clear consensus on a priority order for the breeds at risk. If a consensus cannot be reached, a vote can be taken to obtain a final decision. Alternatively, all committee members may be asked to rank the breeds in priority order and then the rankings can be averaged to yield a final order.

If the responsible entity is a single person, a subjective ranking may be used. However, in such cases, the person should document the logic he or she followed in the decision-making process in order to inform policy makers and other stakeholders.

For a quantitative approach, the attributes for each breed for each factor influencing conservation priority must be expressed numerically. Statistics, such as breed averages for economically important traits will automatically be expressed in numerical terms, but not this is necessarily the case for factors such as presence and absence of special traits or cultural importance. For presence and absence of unique or adaptive traits, presence can be scored as 1 and absence as 0. When multiple special traits are considered, then results can be summed for each breed. For more heterogeneous characteristics, such as historical and cultural significance, two options may be considered:

1. Breeds can be ranked for the characteristic of interest, and then assigned scores corresponding to their ranking. For example, for cultural significance among a group of three breeds, the breed with the most importance can be assigned a score of 3, the second a score of 2 and the third a score of 1.

CGRFA/WG-AnGR-7/12/Inf.6 2. Breeds can be rated for the characteristic of interest in a process similar to that described above for overall conservation priority. For example, members of the conservation committee can each be asked to rate every breed for its cultural importance on a 1 to scale, with 10 being very important and 1 being not important. The committee members ratings can then be averaged for each breed.

Even when the maximum diversity and maximum value strategies are used, risk status will usually be an important consideration and the breeds at the greatest risk of extinction should generally receive the highest priority. Therefore, decisions should be made separately within each risk category. When there is only a single non-demographic factor upon which to base conservation priority, the decision is straightforward. Breeds can simply be prioritized (within risk category) based on their ranking for the single factor.

When multiple factors influence conservation priority, then a simple multifactor index can be used to prioritize breeds. The following formula can be used to establish priority according to conservation values:

CV i = w F1 (F1 i 1 )/ F1 + wF 2 (F2 i F2 )/ F2 +... + w Fn (Fn i Fn )/ Fn, (Equation 1) where, CV i = is the conservation value of Breed i, w F1 = is the weight (i.e. relative importance) of Factor 1 (e.g. genetic uniqueness), F1 i = is the value for Factor 1 for Breed i, F1 = is the average of all breeds for Factor 1, F1 = is the standard deviation of all breeds for Factor 1, and so forth for the rest of the factors to be considered. Box 14 presents an example of a situation in which three hypothetical breeds must be prioritized for conservation.

Box Use of a simple index to prioritize three breeds for conservation This example shows how a simple index based on four factors can be used to prioritize breeds for conservation. The table shows the values assigned to three hypothetical dairy cattle breeds for each of the four factors, along with the relative weights assigned to each factor.

Breed values, population averages and weights for four factors to be considered in conservation prioritization Effective Genetic Milk yield Cultural population size uniqueness (kg/year) importance Breed 1 60 2 1 000 Breed 2 100 3 700 Breed 3 50 1 500 Overall mean 70 2 733.33 0. Standard deviation 26.46 1 251.66 0. Weight in index 3 1 2 In this example, the four factors under consideration are effective population size (N e ), genetic uniqueness, annual milk yield per female and cultural importance. It is an example the use of the maximum value strategy for evaluating breeds. Two of the factors, N e and genetic uniqueness, are both measures of genetic diversity. The National Advisory Committee for Animal Genetic Resources has decided that N e is the most important factor, and it is therefore given the greatest weight (w = 3). N e and milk yield are estimated and measured quantitative factors, respectively, whereas genetic uniqueness and cultural importance are based on ratings.

Each of the three breeds is superior to the others in one of the four factors: Breed 1 has the greatest CGRFA/WG-AnGR-7/12/Inf.6 milk yield;

Breed 2 has the most genetic diversity (for both measures);

and Breed 3 is the only breed considered to have any particular cultural importance.

The table below shows intermediate calculations and final results for the conservation value index for each breed. Standardized values are the factor values minus overall mean, divided by standard deviation. Weighted values are standardized values times weights. Conservation values are the sums of weighted values for each breed.

Standardized and weighted values and overall conservation value and rank for three breeds.

Breed 1 Breed 2 Breed Standardized values Effective population size -0.38 1.13 -0. Genetic uniqueness 0 1 - Milk yield 1.06 -0.13 -0. Cultural importance -0.58 -0.58 1. Weighted values Effective population size -1.13 3.40 -2. Genetic uniqueness 0 1 - Milk yield 2.12 -0.26 -1. Cultural importance -0.58 -0.58 1. Conservation value 0.41 3.56 -3. Rank 2 1 According to the conservation value index, Breed 2 merits the greatest priority for conservation, mostly because of its superiority in genetic diversity, the most important factor. Breed 3 ranks last despite its high cultural importance, because this factor is not considered as important as genetic variability or milk yield, for which this breed is inferior.

Note that the choice of factors used in this case is intended as an example rather than as a recommendation. Each country should determine its own criteria, based on local objectives.

Although milk yield was considered in this example, alternative factors such as functional traits or a more complex measure of milk productivity that also considers the cost of production may be preferable. Also, this example has four factors, but a country may consider more or fewer factors.

The weights assigned to the various factors are also for example purposes only. Each country should establish its own weights for prioritization.

Task 2. Disseminate information to stakeholders Stakeholders involved in implementing or financially supporting conservation programmes must be informed about both the results of the breed prioritization and the logic used in the prioritization.

Action 1. Prepare a report on breed prioritization The results of the breed prioritization should be summarized in a written report that is distributed to stakeholders. The report should also include an explanation of the procedures used and a summary of the information used to support the analyses.

Action 2. Hold meetings with stakeholders to explain the results of the prioritization Stakeholders should be given an opportunity to discuss the results of the prioritization activities and to voice any concerns they may have about the final ranking of breeds. Concerns should be taken seriously and addressed thoroughly, because the efforts made in prioritization will be wasted if stakeholders refuse to accept them and implement programmes according to the recommendations.

CGRFA/WG-AnGR-7/12/Inf.6 Use of information from genetic markers to account formally for genetic diversity in conservation prioritization Rationale The importance of maintaining diversity and genetic variation in animal genetic resources is described in the preceding sections. Genetic variability allows for adaptation and genetic improvement and protects against the detrimental effects of inbreeding, such as increased occurrence of genetic defects and decreases in fecundity and viability. Genetic diversity and variation should thus be considered in the planning of conservation programmes and in the prioritization of breeds for conservation activities.

The previous section described approaches to prioritization that consider genetic diversity on the basis of measures of N e based on pedigree or population structure and/or knowledge of genetic uniqueness.

This section describes the use of genetic markers based on DNA to estimate diversity both within and across breeds and the use of these estimates in prioritizing breeds and making conservation decisions.

When breeds have been subject to genetic characterization and molecular genetic data are therefore available, formal methods can be used to account objectively for genetic variability within and among breeds along with other factors when assigning priority to breeds for conservation.

Objective: To evaluate the genetic diversity of breeds by using genetic markers and account for this diversity in decision-making regarding which breeds to include in conservation activities.


1. Information on the general conservation objectives to be addressed;

2. List of breeds to be considered for inclusion in conservation programmes;

3. For each breed, information on the factors that affect conservation value;

and 4. The molecular genetic information needed to evaluate breed diversity.


Quantified analysis of the genetic diversity of breeds in each species under consideration;

and List of breeds prioritized for conservation.

Task 1. Gather the data needed to apply objective methods of breed prioritization Action 1. Obtain molecular genetic data on breeds Genetic characterization is a recommended step in the evaluation of breeds for improvement of their management and for development of programmes for sustainable use and conservation. Genetic characterization includes the collection and analysis of DNA from a sample of animals from each breed of interest, in order to evaluate genetic variability at molecular level and determine relationships among breeds (Box 15). Guidelines on molecular characterization (FAO, 2011) are available to assist countries in this activity.

For reliable results, DNA should be collected from at least 40 animals, including at least 10 of each sex. Animals should represent the geographical and genetic distribution of the breed, which generally means that very close relatives should be avoided. Animals should be genotyped by using the most informative system of genetic markers available given the financial constraints. Current recommendations are to use the panels of 30 species-specific microsatellite markers compiled by the ISAG-FAO Advisory Group and listed in the FAO guidelines Molecular genetic characterization of animal genetic resources (FAO, 2011), but newer genotyping platforms such as SNP chips may be considered, based on costs and overall objectives. Ideally, genetic characterization data should be obtained not only for the breeds at risk, but also for the not-at-risk local and transboundary breeds in the country. High genetic similarity to not-at-risk breeds indicates low distinctiveness and thus diminishes a breeds conservation priority. Box 16 gives an example of how genetic markers were used to make inferences about populations of pigs and chickens in Southern Africa.

CGRFA/WG-AnGR-7/12/Inf.6 Box Genetic markers Molecular genetic markers are sites of variability in the sequence of DNA that have a statistical association with a characteristic of different cells, individuals or populations. Various types of markers exist. They differ in the types of variation evaluated and the laboratory procedures used.

Markers can be neutral or affected by the process of selection. Neutral markers are recommended for measuring genetic diversity and population genetic statistics. Selective markers are associated with phenotypic traits. In the last two decades, molecular markers have been widely used to investigate the genetic diversity of livestock populations. In the late 1980s to early 1990s the use of short tandem-repeat DNA sequences, known as microsatellites, became popular because of their high polymorphism, high information content, speed of assay, low cost and suitability for analysis in automatic sequencers. They have also been used extensively for investigating the evolutionary history and diversity of livestock species.

As a result of whole genome sequencing and HapMap projects, millions of single nucleotide polymorphisms (SNP) have recently been identified in several livestock species. From these, panels including tens of thousands of validated SNPs are already available to the scientific community (e.g.

in cattle, sheep, chickens and pigs) or will likely be available in the near future (e.g. in goats, horses), permitting genome-wide scans at a very low cost per data point. SNP panels open new perspectives in livestock genetics, in particular for the investigation of genome diversity within and among individuals and populations, population structure and inbreeding, and for the identification of signatures left by selection. This last application provides an attractive prospect for the identification of genomic regions influencing traits that are very difficult to record and are directly associated with conservation value of an animal genetic resource.

With the continual rapid advancement in DNA sequencing technology, whole genome data are a realistic target for population and conservation studies in the very near future. Technology provides new methods of assaying adaptive variation in the genome of threatened populations, enabling prioritization protocols to use unique adaptive variants as well as neutral, demographically mediated variation, and even to test the association of this variation with environmental variables and thereby identify geographic regions of priority (e.g. Bonin et al., 2007;

Joost et al., 2007). By examining all regions of the genome and through genome-specific coalescent analysis, the effects of mutation, drift, selection and admixture can be distinguished at a fine scale. Therefore, for example, locally adapted variants can be distinguished from ancestral polymorphisms and long-term selection can be distinguished from admixture.

Provided by Alessandra Stella.

Action 2. Agree upon specific genetic objectives for maintenance of genetic diversity The general objective of conserving genetic diversity may have a more specific goal and this goal will affect the definition of molecular genetic diversity to be used to prioritize breeds. The appropriate approach to the assessment of genetic diversity depends on the specific type of genetic diversity to be conserved. For example, the specific goal may be to maintain the maximum amount of diversity across breeds. Alternatively, conservation of genetically distinct breeds may be the primary objective. In other cases, ensuring the maintenance of specific alleles or gene combinations may be important. In most cases, a balance between conserving specific breeds and across-breed diversity will be the most logical objective.

If relationships among breeds are not considered important, then a simple quantitative measure of diversity such as heterozygosity or marker-based N e (see Box 17), can be calculated. This measure of diversity can simply be inserted into the Conservation Value (CV) equation described under Task 1, Action 5 of the preceding subsection. However, ignoring relationships among breeds is not optimal, and thus using a more complex objective approach, as described Actions 3 to 7 below is preferable.

CGRFA/WG-AnGR-7/12/Inf.6 Box Use of genetic markers to study the diversity of chickens in Southern Africa Southern Africa is the home of a number of local chicken populations. The importance of these animal genetic resources has been recognized, and specialized institutional flocks have been developed for their conservation. There has always been some uncertainty, however, about whether these populations are distinct breeds or just ecotypes within the same breed and whether the genetics of the local chickens are well-represented in the conservation flocks. A research project was therefore undertaken to answer these and other questions regarding the chicken populations in Southern Africa.

DNA was sampled from three village chicken populations, as well as from four conservation flocks and several reference populations. The countries with chicken genetic resources represented in the analysis were Malawi, Mozambique, Namibia, South Africa and Zimbabwe. The project followed FAO guidelines for characterizing animal genetic resources (FAO, 2011 and FAO, 2012), whereby the production environment was first described via questionnaires and surveys, followed by genetic analyses of the populations using both microsatellite DNA markers and mitochondrial DNA.

The analyses yielded several conclusions. First, from a genetic perspective, the three populations of village in chickens from across the subregion were all part of a single large population. However, slightly different ecotypes had been developed through breeding within isolated geographic regions The differences among ecotypes were primarily observable at the phenotypic level (e.g. plumage or coat colour and in some cases production performance). In addition, cluster analyses indicated that the village populations were genetically distinct from the conservation lines, even in the case of the village populations that were reportedly used to form particular lines. The village populations were found to be more genetically diverse than the conserved lines, based on the numbers of alleles for the genetic markers. Inbreeding within the conservation lines was less than within the village populations. Mitochondrial DNA revealed multiple maternal lineages;

South African chicken populations shared three major haplotypes, which were presumed to have originated from China, Southeast Asia and the Indian subcontinent.

The overall findings increased awareness of the importance of genetic management and utilization of the local chicken genetic resources of Southern Africa. In addition, the study provided a baseline dataset to support the decision-making process for the design of conservation strategies. Among the main conclusions of the study were that the conserved lines were being managed well, inbreeding was being kept low, but the initial sampling may have been too small and failed sufficiently to represent the genetic variability of the village populations. Resampling to capture this diversity was therefore suggested.

Provided by Kennedy Dzama. For further information, see Mtileni et al. (2011a, 2011b).

Action 3. Choose the objective method to be applied based on the genetic objectives and the definition of molecular diversity The application of objective approaches to account for molecular genetic diversity in the prioritization of breeds for conservation has been reviewed by Boettcher et al. (2010). Various options exist. The choice of which to apply will vary according to the definition of genetic diversity that is being used.

The Weitzman (1992) approach measures genetic diversity according to genetic distances among breeds (Box 18) and therefore considers exclusively the genetic differences among breeds while ignoring the genetic variation within breeds. This approach should be applied when only uniqueness of breeds is considered important and crossing of breeds is not expected to be undertaken in the future.

The prioritization procedures of Caballero and Toro (2002) and Eding et al. (2002) define diversity according to kinship (Box 19) and are suitable when within-breed diversity is of primary importance.

This approach will capture the most genetic information across a selection of breeds and is ideal for maintaining the maximum species-wide diversity. Such an approach is justified if the individual breeds are not considered important and crossing of conserved breeds is expected to be common in the future. In most situations, future activities will emphasize the maintenance of distinct breeds, with some cross-breeding. In such cases, the definitions of diversity used in the prioritization methods of Piyasatian and Kinghorn (2003) and Bennewitz and Meuwissen (2005a), which consider an intermediate balance of within- and across-breed diversity, will be the best option (Meuwissen, 2009).

CGRFA/WG-AnGR-7/12/Inf.6 Box Estimating within-breed molecular genetic diversity The simplest measure of within-breed genetic diversity is heterozygosity. Increased heterozygosity is associated with greater genetic diversity. An animal is heterozygous at a given locus if its two alleles differ. Two measures of heterozygosity exist: observed and expected heterozygosity.

Observed heterozygosity (H o ) at a given locus is calculated simply by observing the genotype of each animal sampled, counting the number of heterozygous animals and dividing by the total number of animals. Expected heterozygosity (H e ) at a given locus is calculated by determining the frequency of each allele present and then applying the following formula:

n (1 p ) (Equation 2) He = i i= where n is the number of loci and p i is the frequency of allele i. Heterozygosity measures should be calculated for each locus and averaged across loci. Most computer software for molecular genetic analysis will compute both H e and H o. All breeds should be evaluated using the same loci.

For prioritization of breeds, H e is preferable, as it indicates the amount of genetic diversity available assuming random mating. In fact, H e is also known as gene diversity. H o may differ significantly from the H e if some type of non-random mating has occurred in the previous generation. Inbreeding or mating of similar animals decreases (assortative mating) H o, whereas mating of non-similar animals (disassortative mating) increases H o.

Molecular markers may also be used to estimate N e. Various approaches to doing this have been proposed, several of which are described by Cervantes et al. (2011). Many of the approaches require multistage sampling of animals, which may not always be feasible. For a single sample of genotyped animals, N e can be estimated based on linkage disquelibrium. Various software for computing molecular N e exist:

NeEstimator (Ovenden et al., 2007) is based on theoretical expectations (Hill, 1981;

Waples, 1991) of differences between observed and expected gametic frequencies. It can be downloaded free of charge from http://www.dpi.qld.gov.au/28_6908.htm. Registration is required.

ONeSAMP (Tallmon et al., 2008) applies an approximate Bayesian formulation to obtain an estimator similar to theoretical expectations that is expected to increase precision relative to the NeEstimator software. Calculation is performed online at http://genomics.jun.alaska.edu. The user inserts values for various parameters (numbers of individuals and loci) and provides the path to the input file. Results are sent by e-mail.

Box The use of genetic markers for estimating genetic distances among breeds Genetic distance is a quantitative measure of genetic divergence between two sequences, individuals, breeds or species. For a pair of livestock breeds, genetic distance provides a relative estimate of the time that has passed since the two breeds existed as part of a single, panmictic population. Divergence between the two breeds over time is measured through changes that have occurred through allelic substitution, resulting in different allelic frequencies among breeds.

Many methods for estimating genetic distance exist. One that is considered particularly appropriate to account for short-term genetic differences, such as those that arise during breed formation, is that proposed by Reynolds et al. (1983).

(p p yk ) xk Reynolds genetic distance = k (Equation 3) 1 p xkp yk j k where, for j different loci and different alleles for each locus and two breeds x and y, p xk and p yk are the frequencies of allele k in breeds x and y. Various software are available free of charge for estimating genetic distances from genetic-marker data, including TFPGA (http://www.marksgeneticsoftware.net/tfpga.htm Miller, 1997) and PHYLIP (http://phylip.com Felsenstein, 2005).

CGRFA/WG-AnGR-7/12/Inf.6 Box The use of genetic markers for calculating kinships among breeds The kinship or the coefficient of kinship (also known as coancestry) between two individuals is defined as the probability that single alleles drawn from the same locus of each of the two individuals are identical by descent from a common ancestor. Kinship is used as a measure of genetic diversity, and increased kinship indicates decreased genetic diversity. Kinships can be estimated by using pedigrees if the data are sufficiently complete to trace pedigrees back to common ancestors. However, such detailed pedigree data are not available for many breeds, and pedigree data for estimating of kinships across breeds are almost universally absent. Genetic markers can be used, however, to obtain estimates of kinship between individuals and average kinships both within and across breeds.

For a single locus with K different alleles, a simple measure of kinship between two breeds can be calculated using the following equation:

p p yk (Equation 4) Simple kinship = xk k where p xk and p yk are the frequencies of allele k in breeds x and y, respectively. To obtain a full kinship matrix M, this kinship should be calculated for each locus for all combinations of breeds (including for the case in which breeds x and y are the same) and averaged across loci. The following example is based on three breeds:

m11 m12 m M = m 21 m 22 m 23 (Equation 5) m31 m32 m33 m 11 is the average simple kinship across all loci for breed 1 and itself, m 12 is the average simple kinship between breeds 1 and 2, and so forth.

Note that this method for estimating of kinship is simple and based on some genetic assumptions that will generally not be true in livestock populations. Eding and Meuwissen (2001 and 2003) described methods to account for this additional complexity in estimating kinships. The software Molkin (http://www.ucm.es/info/prodanim/html/JP_Web.htm) can be used to compute average kinships of groups of breeds (Gutierrez et al., 2005).

Action 4: Estimate extinction risk As noted above, extinction risk is usually the most important factor in the prioritization of breeds for conservation. The prioritization approaches discussed above account for this implicitly by recommending that breeds are prioritized within each risk category and that breeds within the higher risk category be given greatest priority. The objective methods of prioritization with molecular genetic information imply the use of a numerical estimate of extinction risk.

There are several ways to approach quantitative measurement of extinction risk:

First, if the National Advisory Committee is satisfied with the assumption that risk is equal within each risk category and does not wish to consider prioritization across categories (i.e., so that all breeds within a given risk category are assumed to have greater conservation value than all breeds from categories of lower risk, regardless of non-risk factors), the objective approach can simply be applied within risk category, and all breeds can be assigned an equal risk of extinction (0.25, for example), regardless of risk category.

Second, if the committee is willing to assume extinction probability is equal within risk category, but would like to allow for prioritization across risk categories, then reasonable estimates of the probability of extinction can be established for each category, and breeds within the same category can be assigned the same risk value. For example, extinction probabilities of 0.50, 0.25, and 0.10 may be reasonable for Critical, Endangered and Vulnerable categories, respectively.

Third, a specific extinction probability can be estimated for each breed (i.e. and risk category will not be directly considered). Three general approaches can be used to estimate extinction CGRFA/WG-AnGR-7/12/Inf.6 probability. The first approach is to identify factors assumed to affect breed extinction and use them as parameters to define endangerment categories to which breeds are assigned (Reist-Marti et al., 2003 see Box 20). The second approach is to predict the trend in extinction probability over time through mathematical modelling of population dynamics (Bennewitz and Meuwissen, 2005b). The third approach is to use loss of genetic variation through time as a proxy for extinction (Simon and Buchenauer, 1993). In general, the second and third approaches require historical census and pedigree data, respectively, which may limit or preclude their application in many countries.

Action 5: Determine non-genetic factors to include in prioritization As explained earlier in this section, many factors in addition to genetic variability and extinction risk may influence the conservation priority of a breed. Many of the objective methods allow for the consideration of such factors in prioritization. The information collected in Actions 3 and 4 in the preceding subsection should be incorporated into objective approaches for prioritization. However, given that genetic markers will account for diversity, genetic factors such as N e and distinctiveness should not be included.

Action 6: Prioritize breeds for conservation Methods have been developed for combining data on molecular genotypes, phenotypic characteristics, risk of extinction, and cultural and social factors to yield a single value for each breed that can serve as a final criterion for prioritization. Examples of such a comprehensive approach to objective prioritization of breeds for conservation have been presented by various authors (e.g. Reist-Marti et al., 2003;

Tapio et al., 2006;

Gizaw et al., 2008). These procedures involve a reasonably high level of arithmetic and computational complexity and thus require appropriate expertise in genetics and matrix algebra. Expert assistance may be necessary. An adapted version of the approach of Reist-Marti et al.

(2003) and Gizaw et al. (2008) is summarized step-by-step in Box 20.

Task 2. Disseminate information to stakeholders Regardless of the prioritization procedure, the stakeholders of conservation programmes must be informed about the priority assigned to breeds. Actions equivalent to those described in Task 2 of the preceding subsection are thus required.

Box A step-by-step example of an objective method prioritizing breeds Step 1: Estimate extinction risk. Following the framework of Reist-Marti et al. (2003), extinction risk can be estimated by assigning values to each breed for various criteria related to breed survival.

The following example is based on five factors:

1. population size 2. change in population size 3. geographic distribution 4. presence of formal breeding programmes 5. farmer satisfaction Other criteria can be chosen, and the method can also be applied based on more or fewer than five factors. Potential additional or alternative criteria include the amount of cross-breeding, the ratio of breeding males to females, the presence or absence of marketing programmes and the level of civil unrest within the country or region.

For each criterion, a set of ordered categories should be established, with each successive category being associated with greater risk. A fractional value (i.e. <1.0) should be assigned to each category, with the value increasing in magnitude as risk increases. The size of the maximum value should correspond to the importance of the criterion. The sum of all maximum values should be <1.0.

Adopting this approach, the following system could be used:

p is a parameter relating to estimated population size, as follows:

p = 0.0 if population size is 10 000 breeding females CGRFA/WG-AnGR-7/12/Inf.6 p = 0.1 if population size is between 2 001 and 10 p = 0.2 if population size is between 1 001 and 2 p = 0.3 if population size is between 100 and 1 p = 0.4 if population size is < c is a parameter relating to recent change in population size (e.g. previous 10 years), as follows:

c = 0.0 if population is relatively stable or increasing c = 0.1 if population has decreased by 10 to 20 percent c = 0.2 if population has decreased by >20 percent g is a parameter relating to geographical distribution, as follows:

g = 0.0 if the breed is found in locations across the country g = 0.1 if animals tend to be found one specific area of the country b is a parameter relating to maintenance of pure-bred animals through formal programmes such as a breeding association or government nucleus, as follows:

b = 0.0 if a programme exists b = 0.1 if no programme exists f is a parameter relating to livestock keepers opinions towards the economic or productive performance of their breed;

it is based on a survey and scores are assigned on a 4-point scale where 1 = poor and 4 = excellent:

f = 0.0 if average farmer opinion f = 0.1 if average farmer opinion < For breed i, extinction risk is equal to the sum of the values for the five parameters:

risk i = p i + c i + g i + b i + f i + 0.05 (Equation 6).

The sum of all maximum values is 0.90 (0.3 + 0.2 + 0.1 + 0.1 + 0.1), whereas the minimum is zero, so the addition of 0.05 in Equation 6 above is to ensure a result between 0.05 and 0.95.

Step 2: Assign conservation values independent of genetic diversity.

The conservation value (CV) index procedure shown in Equation 1 and demonstrated in Box should be applied to all breeds, except that factors associated with the genetic diversity of the breeds should be removed from the calculation, because these factors will be accounted for by the genetic markers. In order to use the approach of Gizaw et al. (2008) the CV resulting from Equation should be standardized to fall within a range between 0.1 and 0.9.

To obtain standardized conservation values (SCV) from non-standardized (CV), the following procedure should be used:

The breed with the greatest CV (CV max ) should be assigned an SCV of 0.9.

The breed with the smallest CV (CV min ) should be assigned an SCV of 0.1.

For a given breed i with CV between CV min and CV max, SCV can be determined by applying the following equation:

SCV i = 0.1 + [0.8 * (CV i - CV min ) / (CV max - CV min )] (Equation 7) Application of this equation will result in a set of SCV that range between 0.1 and 0.9.

Step 3: Account for the genetic diversity of breeds on the basis of marker data.

To determine the relative importance of each breed with regard to its genetic diversity, the recommended strategy is to apply the approach of Bennewitz and Meuwissen (2005a) to determine the contribution of each breed to a core set of breeds that will capture the optimal amount of genetic diversity. The assistance of a statistician or mathematician will likely be necessary for this analysis.

CGRFA/WG-AnGR-7/12/Inf.6 The first step in the procedure is to calculate a matrix (M) of genetic relationships (marker-based kinships) according to alleles shared among the animals genotyped from each breed (see Box 17).

Then a vector (c) of contributions of each breed to a core set of breeds that maximize genetic variability can be obtained by calculating the following matrix calculation:

1 1 1'N M1F 4 M F M 1N (Equation 8) c= 1'N M11N 4 where M-1 is the inverse of the kinship matrix among breeds, F is the diagonal of M (i.e. a vector of within-breed kinships) and 1 N is a vector of ones of length equal to the number of breeds.

This calculation will yield for each breed a contribution parameter between 0.0 and 1.0. This parameter can be denoted D i for a given breed i. Some breeds will likely contribute little diversity or distinctiveness and will have a contribution of zero.

Solving the above equation will require the use of software that performs linear and/or matrix algebra.

Multifunctional mathematic and statistical packages can be used for matrix computations, such as the commercial MATLAB, Mathematica and IML module of SAS and the freely available R package (http://www.r-project.org). Free and low-cost matrix algebra software are also available on the internet (see http://www.scicomp.uni-erlangen.de/archives/SW/linalg.html). Some web sites, such as http://people.hofstra.edu/Stefan_Waner/RealWorld/matrixalgebra/fancymatrixalg2.html and http://www.picalc.com/matrix-calculator.html perform calculations on line, although solving the above equation with these tools will require performing a series of successive single- or two-matrix operations.

Simple matrix computations can be also performed in Microsoft Excel.

Step 4. Calculate total utility, which will be the basis for prioritization.

The breeds can then be prioritized based on total utility (U i ) according to the following formula:

U i = 4 (risk i D i ) + SCV i (Equation 9) Where:

U i is the total utility for breed i;

4 is a constant value that determines the weight placed on the combination of risk and diversity (D) relative to conservation value (SCV) and can be changed according to national priorities;

countries may consider comparing results using different values of this constant;

risk i is the risk of extinction for breed i, as calculated in Step 1;

D i is the contribution of breed i to the overall genetic diversity of the collection of breeds, as determined in Step 3;

and SCV i is the standardized conservation value of breed i, from Step 2.

The breeds should then be ordered according to total utility (U) and the breed with the greatest total utility should be considered to have the greatest priority for conservation, the second greatest should be considered the second most important for conservation, etc.

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CGRFA/WG-AnGR-7/12/Inf.6 IV. CHOOSING THE APPROPRIATE CONSERVATION METHOD FOR EACH BREED Once the breeds at risk have been identified and they have been prioritized for conservation, the next questions raised are: which conservation method should be used? Is ex situ the appropriate method or is in situ conservation the method of choice? Or is a combination of approaches the best solution?

Rationale As is explained in Section 1, in situ, ex situ in vivo and cryoconservation have different advantages and disadvantages.

The advantages of in situ conservation are that it:

allows the breed to continue to develop in the context of changes in production conditions and offers greater opportunities for research;

facilitates breed evolution and adaptation to the environment and gives insight into breed characteristics;

helps maintain the indigenous knowledge of livestock keepers;

creates possibilities for sustainable utilization in rural areas;

allows the breed to maintain its cultural role and its contribution to nature management;

and can be financially self-sustainable.

The disadvantages of in situ conservation are that it:

exposes the breed to risks associated with catastrophic disasters and disease outbreaks;

and does not protect (founder) alleles from genetic drift when the population is small (alleles with a low frequency in the population can easily disappear because of low numbers of breeding animals).

The advantages of ex situ in vivo conservation are that it:

offers insurance against changes in production conditions and offers opportunities for research (but these advantages are much less marked than in the case of in situ conservation);

allows for strict control of selection and mating decisions;

and offers an opportunity to regenerate a breed quickly from the limited number of females available (with ex situ conserved semen) without applying a cross-breeding strategy.

The disadvantages of ex situ in vivo conservation are that it:

inhibits breed evolution and adaptation to the contemporary production environment;

contributes only minimally to objectives related to the sustainable utilization of rural areas;

does not safeguard the breed against disasters and diseases;

does not protect (founder) alleles from genetic drift;

and can be costly in the long term, especially if the breeds productivity is low.

The advantages of cryoconservation (FAO, 2012) are that it:

safeguards the flexibility of the genetic system;

protects the genetic information of a breed against catastrophic events such as disasters and disease outbreaks;

protects (founder) alleles from genetic drift (founder animals that are no longer in the recent generations of the pedigrees of living animals can be re-used for breeding);

and requires relatively little cost for the maintenance of stored germplasm.

The disadvantages of cryoconservation are that it:

inhibits breed evolution and adaptation to the environment;

does not contribute to objectives related to sustainable utilization of rural areas;

and implementation requires particular technical skills and the costs of establishing a cryoconservation programme can be high.

CGRFA/WG-AnGR-7/12/Inf.6 Objective: To choose the appropriate conservation strategy.


1. awareness of the advantages and disadvantages of the various conservation options available for the species and breeds to be conserved;

and 2. national resources available for use in management of animal genetic resources, including infrastructure, facilities, financing, technical capacity and stakeholders.


decisions on the conservation methods to be applied for the different species and breeds.

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