1. Sheep and Goat Extensive Production Systems: The Importance of Assessing Welfare
Extensive farming is generally perceived by society and consumers as a more sustainable and animal-friendly method of animal production. However, this remains to be validated by science. First, the welfare of animals kept, permanently or temporarily, in these systems must be scientifically and transparently studied [
6,
23]. Multiple approaches have been used to assess sheep and goat welfare in intensive systems [
24], but ways for adapting and integrating this knowledge into protocols for small ruminants in extensive systems is still open to discussion.
The first welfare assessment protocols using animal-based indicators were developed for intensive production systems, especially for dairy/beef cattle, poultry, and pigs (e.g., Welfare Quality), due to the overall high animal density per unit area associated with such systems. On the other hand, welfare assessment protocols for small ruminants, developed under the Animal Welfare Indicators (AWIN) project [
25,
26], were tested in different rearing conditions: dairy goats kept in intensive systems and sheep in extensive and semi-intensive farms [
25]. Although these protocols may be useful for the assessment of welfare in all systems, it is necessary to ensure that appropriate and evidence-based changes are inserted and integrated. For example, some original measures may not be applicable or may show a very low prevalence and should thus be withdrawn, while new indicators will undoubtedly need to be added. Additionally, the assessors may need to record variable indicators dependable on various factors (e.g., terrain, distance, access, time, and weather constraints). Recently, a study [
27] tested the feasibility and reliability of the AWIN protocol for the welfare assessment of dairy goats in semi-extensive farming conditions. It showed that some indicators from the AWIN sheep protocol could be successfully integrated into the original goat protocol, but some validation studies were nonetheless still needed.
Here, we discuss some of the main limits of these protocols when applied to fully extensive systems, as an opportunity for the use of novel technologies that are presented in the following sections.
Neither small-ruminant AWIN protocol includes males in the evaluation. Although this is not an issue for dairy cattle or pigs in intensive farms, it may be an important flaw for extensive and pasture farming systems [
28,
29,
30]. Most published studies only assess the welfare and behavior of males in relation to the use of reproductive technologies [
31] or in castration [
32]. When applying an assessment protocol, it should be remembered that behavior is inherently different between females and males and that the presence of males may influence the behavior of the females (and vice-versa); for example, ewes are usually more active and vocal than rams [
33,
34]. Consequently, the welfare of males in the flock has often been overlooked. Therefore, developing or adapting protocols to groups that include males should consider such particularities.
Some proposals have been made to adapt existing protocols to less intensive farming systems [
13,
27,
35,
36,
37] although this should be regarded as a complex and challenging task considering the settings’ diversity [
24,
36]. Small ruminants bred in extensive farming systems are more exposed to weather conditions, which implies a need for considering temperature, humidity, and even wind exposure in welfare assessments. Extreme conditions, as well as sudden variations in weather, may significantly change the expression or intensity of some indicators and, thus, the welfare of the animals. Heat stress must be considered in these evaluations as well as each breed’s capacity to adapt and cope with its environment [
15]. Breeds selected to live in extensive or pasture farming systems are usually more resilient and well adapted to the climatic conditions [
38,
39]. However, when exposed to temperatures outside their thermal comfort zone, more sturdy animals may mask poor welfare signs, making assessment very difficult [
39]. The volatility of these circumstances poses an enormous and complex challenge for welfare assessment in small ruminant species kept in harsher environmental conditions. Nevertheless, indicators related to thermal comfort should be seen as an essential component of protocols to be used in extensive farming systems. For example, weather and environment monitoring stations may be important assets as they will allow for accurate correlations between welfare indicators and weather conditions. Other ways novel technologies may help in overcoming some of these issues will be further addressed in subsequent sections.
One of the principles suggested by the AWIN protocol is good housing. Although in extensive systems actual housing is very limited or even absent, the provision of shade or shelter from wind, rain, or snow should be considered as the lack may result in very poor welfare, particularly for young animals. Providing some sort of shelter, whether for feeding or for protection from climate extremes, will result in higher welfare levels [
40,
41]. However, the extension and type of landscape in which these animals are generally kept may preclude the building of such shelters [
24]. Thus, including the presence of shade/shelter and its accessibility, should be considered as an important indicator of animal comfort.
Extensively kept small ruminants may be more prone to lameness problems due to constant exposure to wet soils and infection agents or due to the need to walk long distances along rough paths. Additionally, they are usually less frequently checked for signs of pain or discomfort and very rarely treated early, compared to animals in intensive farms [
13]. Although conducting a thorough hoof examination poses great challenges in extensive systems, lameness assessments should include traditional gait scoring but also the careful examination of hooves if the prevalence of severely lame animals is detected. Moreover, the time of the year, climate, and terrain conditions should also be considered in these protocols. Technologies such as thermography, image scanning, or weight pads may be an expeditious and reliable way of detecting lame animals going through a race.
Several other problems deserve special attention in extensively kept flocks due to potential differences in prevalence and severity when compared with intensive systems [
42]. Body condition score, diarrhea, and fleece condition are just a few examples of measures that may need substantiation and critical analysis before being approved [
36,
43]. These may vary according to weather conditions, season, and type of feeding (e.g., fresh grass), and the welfare impact of these changes must be verified. In extensive systems, in which the handling of individuals may be difficult, sorting gates and electronic weighing scales combined with e-ID may be used for the automatic collection of weight data.
Well-designed studies on the behavior of small ruminants in extensive conditions are required to ensure the validity of the many animal-based measures, including the group mental state assessment trough the Quality Behavior Assessment (QBA) used in the existing AWIN protocols [
44]. Despite the merit of on-farm welfare assessment schemes like the AWIN protocols, there is a need to introduce indicators that address positive aspects of animal welfare [
45]. In this sense, other methods, including the five-domain model, were developed [
46] and applied to sheep [
13,
47]. This model incorporates three survival-related domains (nutrition, environment, and health), a behavior-related domain, and a fifth domain that results from a comprehensive assessment of how the other domains impact the animal’s affective experience [
48,
49]. Besides, it is an ever-evolving model [
50], which also allows for new interpretations and adaptations to extensively farmed species. In this way, identifying valid, reliable, and viable animal-based indicators related to the positive aspects of animal welfare will improve the quality of life of animals and strengthen communication about animal welfare to stakeholders [
50]. Likewise, measuring human–animal interactions in extensive systems might differ from the intensive systems norm. Therefore, it is relevant to combine the knowledge acquired in intensive systems, but also to understand how the human–animal interaction is in extensive systems, and to not infer by mistake that the applicable behavioral parameters might be the same.
An equally important issue in applying protocols to extensive systems is feasibility. For example, the time needed to apply the protocol in very large settings, or the difficulties associated with the exposure to open-field constraints, all have to be considered to ensure validity and feasibility. In this context, on-farm welfare assessment feasibility can be increased by adopting a strategy supported on a few valid and reliable animal-based indicators [
13] complemented by the introduction of new technologies, such as automatic-recording devices or drones [
51].
Finally, a word on an often-demoted issue—the need for specifically trained evaluators [
27,
52] so that the repeatability and credibility of the protocols are guaranteed. Experienced and competent auditors in intensive system assessments may not be prepared for the work needed in extensive settings.
In summary, welfare assessment of extensively kept small ruminants should be seen as a very specific subject, and not just an extension or simple adaptation of the protocols validated for intensive systems. Due to particular features and limitations, full-field assessment may be too difficult to manage through traditional farm-level personal observation. This provides excellent opportunities for new sensor technologies, as will be discussed in the following sections. The main constraints to the use of new technologies in small ruminants in extensive settings, such as drones, intra-ruminal sensors or ear-tags containing accelerometers, are cost and the difficulty of getting accurate, real-time readings.