Case Studies on Impacts of Climate Change on Smallholder Livestock Production in Egypt and Spain

Abstract

Climate change is one of the hot topics of this decade and seriously affects all economic production sectors including the livestock farming sector. In many scenarios, the Mediterranean region is expected to experience unconventional and severe climate change that necessitates adopting effective strategies to improve the resilience of the livestock farming sector, particularly for smallholders. Here, we performed a cross-sectional survey of 277 smallholder livestock farmers in Egypt and 223 in Spain in order to (1) assess smallholder livestock farmers’ awareness of climate change and its potential impacts on animal performance, (2) identify climate change factors affecting animal productivity, and (3) identify the resilience of small-scale livestock farms in the region to the effects of climate change on animal productivity and existing and future needed adaptive measures. The results showed that just over 90% of respondents were aware of climate change and its potential effects on animal productivity, and just over 60% of smallholders in Spain obtained relevant knowledge through their own direct observation, while most smallholders in Egypt obtained knowledge through communication with other farmers and from the media. The role of extension advisors has diminished in the two countries, recording 0.36% in Egypt and 1.35% in Spain. The survey responses suggest that heat waves, humidity, and drought are the major climatic changes affecting smallholding animal production, representing 68.65, 16.34, and 15.01%, respectively. Climatic change appears to have affected primarily milk yield, wool production, and reproductive performance on the smallholding farms in our survey, while affecting meat production, mortality rate, and egg production to a smaller extent. As measures to buffer the effects of climate change, 25% of respondents in Egypt indicated that they have adopted nutritional strategies, 36% indicated that they manage housing conditions, and 6% indicated that they use genetically improved animal breeds. The corresponding percentages among respondents in Spain were 15%, 28%, and 4%, respectively. In conclusion, awareness about climate change as well as adaptation measures are the major axes to sustaining the growing demand for livestock products. Furthermore, mitigation strategies are keys to limiting the upcoming extent of climate change, and there are several adaptation strategies.

1. Introduction

Agricultural and livestock production needs to expand to 3–4 times the current levels by the year 2050 in order to meet the needs of the world’s expected 9.7 billion inhabitants. Achieving this increase in the face of climate change remains one of the most daunting challenges for society. Already, 82% of natural disasters during 1998–2017 were climate-related [1], and heat waves, drought, storms, and floods are expected to become more frequent as global temperatures continue to increase. Climate change has lowered world agricultural productivity by 1–5% every decade since the 1970s and has become a great threat for the sustainability of livestock farming systems at different levels. Climate change is also expected to severely impact livestock productivity, although its effects on livestock farming systems have been neglected in the literature, particularly on farms in developing countries [2].

The Mediterranean Basin has experienced, and will likely continue to experience, a reduction in annual rainfall and widespread warming over most of its areas, especially during the summer season. These might lead to critical water shortages, especially in the southern Mediterranean [3,4]. Egypt is extremely vulnerable to the threats of climate change [5,6]; it is predicted that the average annual temperature in Egypt will increase by 1.07–1.27 °C by 2030, with a 10th percentile of 0.37–0.61 °C and a 90th percentile of 1.78–2.11 °C [7]. In Spain, average temperatures have risen by 1.5 °C since 1965, and while there were 10–12 heat waves per decade between 1980 and 2000, there were 24 per decade between 2010 and 2020. Heat waves in the country are also expected to last longer, with at least 41 days of extreme heat per year by 2050 [8]. Consequently, climate change has already harmed animal productivity, health, and welfare, and these trends are predicted to worsen in the future [9,10,11].

Globally, 1.3 billion people are employed in the production of livestock and poultry; more than 600 million smallholders from developing countries depend on livestock for food and financial security, yet they are more vulnerable than larger farming operations to food insecurity due to climate change [12]. The majority of smallholder livestock farms, particularly in developing countries, are frequently characterized by low productivity, low feed availability, and poor quality of feed resources [13], and are more vulnerable to negative impacts of climate change. In Egypt, most livestock breeders are smallholders [8], who produce around 25% of the country’s poultry, 28% of the country’s eggs, and a considerable amount of milk for commercial and domestic use (available at: https://www.fao.org/in-action/asl2050/countries/egy/en/ accessed on 17 August 2023). The extreme vulnerability of smallholders to climate shocks makes it even more important for them to be aware of the threats and implement mitigation measures, which may include access to appropriate consulting and advisory services and the use of smart technologies to follow climate trends to continuously monitor their impact on animal productivity [14].

As mentioned above, forecast studies for climate change in the Mediterranean Basin supposed different scenarios for the future change in the area’s climate. Accordingly, different perceptions from smallholder livestock farmers are expected according to the geographic distribution and the related climate change as well as their experience. Moreover, the type and severity of climate change can differently affect animal health and productivity, feed availability, and existing breeding systems. All of these factors can shape adaptation strategies required for the two countries selected to represent the Mediterranean Basin in this case study. Thus, understanding livestock farmers’ perceptions of climate-related hazards is pivotal since it can realize their vulnerable nature and adaption behavior [14]. This assumption can be underpinned by the findings of previous studies assessing the smallholder livestock farmers’ perception of climate change and the impacts of climate change on animal performance [15,16]. For example, a vulnerability assessment study by Jamshidi et al. [17] indicated that the majority of smallholder livestock farmers were relatively vulnerable to climate change, and there were 13 factors that highly contributed to vulnerability, including education, income, access to infrastructure, credit, and land size. Another study in Iran indicated that most smallholder livestock farmers were relatively vulnerable to climate change, and it identified several factors contributing to that vulnerability, including inadequate education, income, access to infrastructure, credit, and land size [17]. A study in India identified inadequate information about climate change and a lack of infrastructure as the most pressing obstacles to the resilience of smallholders to climate change [18].

Based on the literature and to deepen our limited understanding of the awareness of climate change and the implementation of mitigation strategies among smallholder livestock farmers in the Mediterranean, we performed a cross-sectional survey of a relatively large sample of farmers in Egypt and Spain, considering three hypotheses to guide our study:

Hypothesis 1.

Data are needed on the awareness and perceptions of climate change and its impacts on animal performance among smallholder livestock farmers in order to increase their resilience to climate change.

Hypothesis 2.

Climate change factors affecting animal productivity and the resilience of small-scale livestock farms in the Mediterranean Basin differ from region to region.

Hypothesis 3.

Greater support to smallholder livestock farmers as well as deeper and broader implementation of mitigation measures are needed to strengthen the resilience and sustainability of this sector in the face of climate change.

2. Materials and Methods

2.1. Questionnaire Design

A questionnaire was developed specifically for this study. The introductory section of the questionnaire described the aims and importance of the study and indicated that respondents were eligible to participate only if they were livestock smallholders and at least 18 years old.

The first section on data collection asked about respondent demographics, including sex, age, educational level, province or city of residence, years working as a smallholder livestock farmer, main purpose for raising animals, farming system (livestock only or crops and livestock), size of agricultural tenure, number of animals, type of livestock (large ruminants, small ruminants, monogastric animals), and main breeding system (indoor, outdoor, mixed).

The second and third sections collected data about respondents’ perception and awareness of the potential effects of climate change on livestock smallholding, the impact of climate change that respondents have observed so far on the food productivity of their animals, and the measures that they have applied to mitigate this impact.

The questionnaire included 19 closed-ended questions and two open-ended questions (size of agricultural tenure, number of animals). To respond to closed-ended questions, participants had to select one answer from several options, multiple answers from several options, or one rating on a 3-point Likert scale. Items with a Likert scale asked whether something had increased (response of “1”), decreased (“2”) or remained unchanged (“3”). The questionnaire was composed originally in English, and then translated into Arabic and Spanish to match the native languages of the study participants. The translated questionnaires were piloted on 15 experts in this field who were not part of the final sample in order to confirm the clarity of the items.

2.2. Participants, Zones of the Study, and Data Collection

Data were collected from 542 smallholder livestock farmers through semi-structured interviews conducted on their farms by trained investigators or local extension officers between January and May 2023. A total of 500 responses (n = 227 and 223 for Egypt and Spain, respectively) were considered valid after revising the responses, eliminating uncompleted responses, and confirming respondents’ agricultural tenure and number of owned animals to ensure they are smallholders. The mean agricultural tenure was 11.391 and 22.86 Hectare and the mean numbers of animals were 12.74, 52.45, 48.93, and 0 for large animals, small ruminants, monogastric animals, and pigs in Egypt, while the same corresponding values were 54.92, 147.65, 368.53, and 1962.33, respectively, in Spain. The farmers responded to the questionnaire of this study were from Al-Sharkia Province, Egypt, and Zaragoza Province, Community of Aragon, Spain (Figure 1). The meteorological variables of both provinces were obtained from regional and national agencies (available at: https://weatherspark.com accessed on 17 August 2023). In Al-Sharkia, the hot season lasts for 4.3 months, from 19 May to 30 September, with an average daily high temperature above 32.78 °C. Meanwhile, the cold season lasts for 3.1 months, from 3 December to 7 March, with an average daily high temperature below 22.78 °C. In Zaragoza, the hot season lasts for 3.0 months, from 10 June to 10 September, with an average daily high temperature above 28.33 °C. Meanwhile, the cold season lasts for 3.6 months, from 15 November to 2 March, with an average daily high temperature below 15.00 °C.

2.3. Data Analysis

Data from valid questionnaires were downloaded into Microsoft Excel and assessed using the Kaiser–Meyer–Olkin measurement of sampling adequacy and the Bartlett test of sphericity. Differences in non-parametric data were assessed for significance using the chi-squared test. Differences associated with p < 0.05 were considered significant. Logistic regression was used to determine the degree of awareness about the effects of climatic change on animal productivity. Such regression was also used to identify factors associated with reduced animal productivity from among the following independent variables: education level, age, sex, experience as a smallholder livestock farmer, goals of animal raising, farming system, types of livestock, and breeding system. Relative risk was assessed in terms of odds ratios (ORs) and associated 95% confidence intervals (CIs).

The statistical model was incorporated as follows:

Log (Π AWARE/(1 − Π AWARE)) = β0 + β1ED + β2 AGE + β3SEX+ β4 YEAR + β5GOAL + β6APP+ β7TYPE+ β8BREED

where Π AWARE is the probability of awareness, ED is the education level, EXP is the experience in livestock, YEAR is the years working as livestock farmer, GOAL is the goals of animal rising, APP is the applied farming system, TYPE is the types of livestock, and BREED is the breeding system. Responses on the 3-point Likert scale were log-transformed and used with a class length of 0.600 to extract factors that were associated with climate change and were negatively affecting livestock farming. Factors were extracted and ranked using principal component analysis. The eigenvalue remained greater than 1 after varimax rotation. Figures were prepared using GraphPad Prism 9.0.1. USA.

3. Results

Demographic characteristics of survey respondents are shown in

Table 1. Demographic characteristics of survey respondents.

Characteristic and Category *	Egypt (n = 277)	Spain (n = 223)	Total (n = 500)
Education level (X2 = 49.791, p < 0.001)
Pre-university	91 (32.85)	83 (37.22)	174 (34.80)
Bachelor’s degree	85 (30.69)	68 (30.49)	153 (30.60)
No formal education	96 (34.66)	35 (15.70)	131 (26.20)
No response	5 (1.80)	37 (16.59)	42 (8.40)
Age, yr (X2 = 0.326, p = 0.849)
18–30	72 (25.99)	61 (27.36)	133 (26.6)
31–50	115 (41.52)	87 (39.01)	202 (40.4)
>51	90 (32.49)	75 (33.63)	165 (33)
Sex (X2 = 0.266, p = 0.606)
Male	251 (90.61)	205 (91.93)	456 (91.2)
Female	26 (9.39)	18 (8.07)	44 (8.8)
Years working as livestock farmer (X2 = 45.409, p < 0.001)
1–10	46 (16.61)	26 (11.66)	72 (14.4)
11–20	49 (17.69)	4 (1.79)	53 (10.6)
21–30	60 (21.66)	39 (17.49)	99 (19.8)
31–40	59 (21.30)	75 (33.63)	134 (26.8)
41+	63 (22.74)	79 (35.43)	142 (28.4)
Primary goal in raising animals (X2 = 29.181, p < 0.001)
Sales as main income source	128 (46.21)	152 (68.16)	280 (56.0)
Sales as a partial income source	82 (29.60)	51 (22.87)	133 (26.6)
Domestic consumption	67 (24.19)	20 (8.97)	87 (17.4)
Applied farming system (X2 = 12.169, p = 0.001)
Livestock only	107 (38.63)	121 (54.26)	228 (45.6)
Livestock and crops	170 (61.37)	102 (45.74)	272 (54.4)
Types of livestock (X2 = 25.377, p < 0.001)
Large animals	117 (42.24)	71 (31.84)	188 (37.6)
Small ruminants	88 (31.77)	46 (20.63)	134 (26.8)
Monogastric animals	72 (25.99)	106 (47.53)	178 (35.6)
Breeding system (X2 = 4.608, p = 0.099)
Indoor	127 (45.85)	116 (52.01)	243 (48.6)
Outdoor	60 (21.66)	54 (24.22)	114 (22.8)
Mixed	90 (32.49)	53 (23.77)	143 (28.6)

* Values are the number of responses and corresponding percentages (%) unless otherwise noted, and X² is the chi-squared value.

. Nearly all respondents in both countries were male, and approximately 40% were 31–50 years old, while a quarter were younger. Just over a quarter of respondents from each country had 31–40 years of experience as smallholder livestock farmers, while another quarter had more than 41 years of experience. Two thirds of respondents from both countries raised their animals for sale to generate their primary income, and another quarter raised them for sale to generate supplementary income. Just over half of respondents cultivated crops while also managing their livestock, while the remainder only managed livestock. The proportion of farmers who bred large animals was slightly larger than the proportions that bred small ruminants or monogastric animals. Just under half of respondents bred their animals indoors, while nearly equal proportions of the remainder bred their animals indoors or in a mixed system.

3.1. Awareness of Climate Change

Nearly 90% of Egyptian respondents and nearly all of Spanish respondents indicated that they were aware of climate change (Figure 2). More than 60% of Spanish respondents indicated that their awareness came from personal observation, whereas a similar proportion of Egyptian respondents attributed their awareness to communication with other farmers and to the media. Only a handful of respondents in both countries identified extension advisors as a source of their awareness.

A logistic regression analysis of different demographic characteristics associated with participants’ awareness about climatic change is shown in

Table 2. Logistic regression to identify characteristics of respondents associated with climate change.

Variables *	Regression Coefficient, β		Odds Ratio	95% Confidence Interval	p-Value
	β	Std. Error
Educational level:
Pre-university education			Ref.
University education (Bachelor)	1.152	0.809	3.16	1.226–5.392	0.017
No education	−1.727	0.445	0.178	0.074–0.425	0.001
Do not wish to answer	−2.369	0.510	0.094	0.034–0.254	<0.001
Age:
18 to 30 years			Ref.
31 to 50 years	0.814	0.330	2.259	0.972–4.118	0.050
>51 years	−0.320	0.111	0.726	0.358–1.474	0.375
Sex:
Male			Ref.
Female	−3.398	0.379	0.033	0.016–0.070	<0.001
Experience in livestock:
1–10 years			Ref.
11–20 years	−0.172	0.026	0.841	0.444–1.662	0.705
21–30 years	0.790	0.263	2.203	1.002–3.335	0.049
31–40 years	1.385	0.494	4.00	2.516–6.892	0.005
41 years and above	1.446	0.504	4.249	2.622–7.015	0.002
Goals of animal raising:
Sales as main income source			Ref.
Sales as a partial income source	−1.487	0.376	0.226	0.108–0.472	<0.001
House consumption	−1.367	0.421	0.255	0.112–0.582	0.001
Applied farming system:
Livestock farming system only			Ref.
Mixed crop livestock farming system	−0.331	0.114	0.718	0.338–1.330	0.293
Types of livestock:
Large animals			Ref.
Small ruminants	−1.716	0.338	0.180	0.075–0.432	0.001
Monogastric	−1.041	0.461	0.353	0.143–0.648	0.024
Breeding system:
Indoor breeding system			Ref.
Outdoor breeding system	1.061	0.392	0.346	0.160–0.747	0.007
Mixed system	−0.935	0.380	0.393	0.186–0.625	0.014

* Based on combined data from Egyptian and Spanish respondents.

. Participants with a university education had 3.16 times higher odds of being aware about climatic change compared to their counterparts with pre-university education. In the same context, the odds of awareness decreased by 82.2 (OR = 0.178) and 9.6% (OR = 0.094) for uneducated participants and those who did not want to answer, respectively. The age of participants was another factor that affected the degree of awareness; the odds value of awareness was 2.259 times higher for participants in the age category from 31 to 50 years, while it decreased by 27.4% (OR = 0.726) for those in advanced ages (>51 years) compared to those in the age category between 18 and 30 years. Also, the probability of awareness decreased in females by 96.7% (OR = 0.033) compared to males. Another variable significantly associated with the degree of awareness was the years of the participants’ experience in the livestock industry; there was a significant increase in the probability of awareness for participants with a longer time of experience in livestock farming compared to those with a shorter time of experience in livestock farming. Moreover, participants who breed animals for sale as a partial income source and house consumption were less likely to be aware about climatic change (OR = 0.226 and 0.255, respectively) compared to those who aimed to raise animals for sale as the main income source. With respect to the type of livestock, the odds of awareness decreased by 82% (OR = 0.180) and 64.7% (OR = 0.353) for small ruminant and mono-gastric breeders, respectively, compared to large animal breeders. Participants who follow the outdoor breeding system and mixed system were less likely to be aware of climatic change compared to their counterparts who follow the indoor breeding system; the odds ratio decreased by 65.4 (OR = 0.346) and 60.7% (OR = 0.393), respectively. To summarize, logistic regression identified significantly greater awareness of climate change with higher education level, age between 31 and 50, longer experience in livestock farming, and livestock farming as a primary income source rather than for supplementary income or domestic consumption.

3.2. Climate Change and Potentially Related Negative Effects on Livestock Farming

The major effect of climate change that Spanish respondents reported was drought, while Egyptian respondents indicated heat weaves and increased humidity (

Table 3. Major climate changes and potentially associated effects on livestock farming as observed by participants.

Variable *	Egypt (n = 236)	Spain (n = 217)	Total (n = 453)
Major climate changes (X2 = 89.970, p < 0.001)
Heat waves	184 (77.97) a	127 (57.53) b	311 (68.65)
Snow	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)
Rain	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)
Sunshine	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)
Storm	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)
Evaporation	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)
Humidity	52 (22.03) a	22 (10.14) b	74 (16.34)
Drought	0.00 (0.00)	68 (31.34)	68 (15.01)
Flood	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)
Major problems negatively affecting livestock farming
Spread of diseases (X2 = 3.004, p = 0.222)	$\overline{\mathrm{x}}$ = 1.775	$\overline{\mathrm{x}}$ = 1.756	$\overline{\mathrm{x}}$ = 1.766
Increase (1)	135 (57.20)	121 (55.76)	256 (56.51)
Decrease (2)	19 (8.05)	28 (12.90)	47 (10.38)
No change (3)	82 (34.75)	68 (31.34)	150 (33.11)
Appearance of new diseases (X2 = 40.966, p < 0.001)	$\overline{\mathrm{x}}$ = 1.356	$\overline{\mathrm{x}}$ = 1.839	$\overline{\mathrm{x}}$ = 1.587
Increase (1)	181 (76.69) a	118 (54.38) b	299 (66.01)
Decrease (2)	26 (11.02)	16 (7.37)	42 (9.27)
No change (3)	29 (12.29) b	83 (38.25) a	112 (24.72)
Use of medications (X2 = 31.386, p < 0.001)	$\overline{\mathrm{x}}$ = 1.606	$\overline{\mathrm{x}}$ = 2.069	$\overline{\mathrm{x}}$ = 1.828
Increase (1)	147 (62.29) a	89 (41.01) b	236 (52.10)
Decrease (2)	35 (14.83)	24 (11.06)	59 (13.02)
No change (3)	54 (22.88) b	104 (47.93) a	158 (34.88)
Availability of feed resources: (X2 = 77.144, p < 0.001)	$\overline{\mathrm{x}}$ = 2.123	$\overline{\mathrm{x}}$ = 2.433	$\overline{\mathrm{x}}$ = 2.229
Increase (1)	26 (11.02)	34 (15.67)	60 (13.24)
Decrease (2)	155 (65.68) a	55 (25.35) b	210 (46.36)
No change (3)	55 (23.31) b	128 (58.99) a	183 (40.40)
Water shortage (X2 = 221.076, p < 0.001)	$\overline{\mathrm{x}}$ = 2.877	$\overline{\mathrm{x}}$ = 2.184	$\overline{\mathrm{x}}$ = 2.545
Increase (1)	10.00 (4.24) b	56 (25.81) a	66 (14.57)
Decrease (2)	9.00 (3.81) b	65 (29.95) a	74 (16.34)
No change (3)	217 (91.95) a	96 (44.24) b	313 (69.09)

* Values are the number of responses and their corresponding percentages (%) unless otherwise noted, X² is the chi-squared value, p is the probability, $\overline{\mathrm{x}}$ is mean response on the Likert scale, and ^a,b superscripts indicate a significant difference between means within a row at p < 0.05.

). Respondents from the two countries differed in what they identified as major problems negatively affecting livestock farming, with more respondents from Egypt reporting the appearance of new diseases and the use of medications or feed additives, and more respondents from Spain reporting the availability of feed resources or fodder.

Principal component analysis indicated that the spread of diseases, the appearance of new diseases, and the use of medications and feed additives were the three negative effects of climate change most strongly affecting the respondents’ livestock farms (Figure 3 and Table S1). Less strong determinants were water shortage and the availability of feed resources or fodder.

3.3. Effects of Climate Change on Animal Performance

Most participants in both countries indicated that they monitored animal performance through personal observation alone or together with written documentation, and participants in both countries reported that the production of milk, meat, and wool had decreased together with reproductive performance (

Table 4. Participant responses about the effects of climate change on animal performance.

Variable *	Egypt (n = 236)	Spain (n = 217)	Total (n = 453)
Monitoring of animal performance: (X2 = 15.439, p = 0.004)
Personal observation only	129 (54.66)	156 (71.89)	285 (62.91)
Personal observation with recording	54 (22.88)	36 (16.59)	90 (19.87)
No monitoring	53 (22.46) a	25 (11.52) b	78 (17.22)
Trends in animal performance
Milk yield: (X2 = 3.156, p = 0.206)	$\overline{\mathrm{x}}$ = 2.093	$\overline{\mathrm{x}}$ = 2.142	$\overline{\mathrm{x}}$ = 2.108
Increase	38 (16.10)	24 (11.06)	62 (13.69)
Decrease	138 (58.47)	142 (65.44)	280 (61.81)
No change	60 (25.42)	51 (23.50)	111 (24.50)
Meat production (X2 = 5.622, p = 0.060)	$\overline{\mathrm{x}}$ = 2.216	$\overline{\mathrm{x}}$ = 2.147	$\overline{\mathrm{x}}$ = 2.183
Increase	58 (24.58)	70 (32.26)	128 (28.25)
Decrease	69 (29.24)	45 (20.74)	114 (25.17)
No change	109 (46.19)	102 (47.00)	211 (46.58)
Egg production (X2 = 2.752, p = 0.252)	$\overline{\mathrm{x}}$ = 2.538	$\overline{\mathrm{x}}$ = 2.645	$\overline{\mathrm{x}}$ = 2.440
Increase	40 (16.95)	25 (11.52)	65 (14.35)
Decrease	29 (12.29)	27 (12.44)	56 (12.36)
No change	167 (70.76)	165 (76.04)	332 (73.29)
Wool production (X2 = 18.863, p < 0.001)	$\overline{\mathrm{x}}$ = 2.136	$\overline{\mathrm{x}}$ = 2.037	$\overline{\mathrm{x}}$ = 2.088
Increase	37 (15.68)	24 (11.06)	61 (13.47)
Decrease	130 (55.08)	161 (74.19)	291 (64.23)
No change	69 (29.24) a	32 (14.75) b	101 (22.30)
Reproductive efficiency (X2 = 5.396, p = 0.068)	$\overline{\mathrm{x}}$ = 2.038	$\overline{\mathrm{x}}$ = 2.134	$\overline{\mathrm{x}}$ = 2.084
Increase	43 (18.22)	39 (17.97)	82 (18.10)
Decrease	141 (59.75)	110 (50.69)	251 (55.41)
No change	52 (22.03)	68 (31.34)	120 (26.49)
Mortality (X2 = 21.989, p < 0.001)	$\overline{\mathrm{x}}$ = 2.000	$\overline{\mathrm{x}}$ = 1.627	$\overline{\mathrm{x}}$ = 1.821
Increase	101 (42.80)	129 (59.45)	230 (50.77)
Decrease	34 (14.41)	40 (18.43)	74 (16.34)
No change	101 (42.80) a	48 (22.12) b	149 (32.89)
Effect of climate change on the resilience of the farm: (X2 = 5.952, p = 0.071)
Turning from a main income source to a partial source	73 (30.93)	46 (21.20)	119 (26.26)
Completely shifting to another income source	25 (10.59)	22 (10.14)	47 (10.38)
No effect	138 (58.47)	149 (68.66)	287 (63.36)

* Values are the number of responses and their corresponding percentages (%) unless otherwise noted, X² is the chi-squared value, p is the probability, $\overline{\mathrm{x}}$ is mean response on the Likert scale, and ^a,b superscripts indicate a significant difference between means within a row at p < 0.05.

). Egg production, in contrast, remained stable. A range of 40–60% of the participants in both countries indicated that mortality rate increased; however, Egyptian participants reported higher significant responses for no change in mortality rate than Spanish participants. Few respondents in both countries indicated that climate change had caused them to shift their reliance on their livestock farm from a primary to secondary income, or to switch entirely to another source of income.

3.4. Ranks of Different Animal Production Sectors as Affected by the Climate Changes

In this study, principal component analysis (PCA) and the computed Eigenvalues had a substantial role in identifying and understanding the associations of different animal production sectors with climate change (Figure 4 and Table S2). The varimax method was carried out to perform the rotation of the PCA; loading greater than 0.60 is statistically significant. The factor analysis included four factors that described 76.71% of total data variability. The first dominant factor accounted for 32.91% of the total variance with an Eigenvalue of 1.97. This factor indicated that the milk yield, wool production, and reproductive performance were the major three factors affected by climatic change. The second factor (23.21% of the total variance with Eigenvalue = 1.39) revealed that both meat production and mortality rate were the second two sectors affected by climatic change. Meanwhile, egg production was the third sector affected by climatic change (12.91% of the total variance with Eigenvalue = 0.775; Figure 4).

3.5. Relationships between Changes in Climate and in Animal Performance as Perceived by Respondents

We detected significant associations between heat waves, humidity, or drought with lower milk yield, and heat waves with lower wool production and reproductive efficiency as well as higher mortality (

Table 5. Relationships between changes in climate and in animal performance as perceived by respondents *.

Variable *	Heat Waves (n = 311)	Humidity (n = 74)	Drought (n = 68)
Milk yield: (X2 = 32.967, p < 0.001)	$\overline{\mathrm{x}}$ = 2.109	$\overline{\mathrm{x}}$ = 2.027	$\overline{\mathrm{x}}$ = 2.191
Increase (1)	30 (6.62)	17 (3.75)	15 (3.31)
Decrease (2)	217 (47.90) a	38 (8.39) b	25 (5.52) b
No change (3)	64 (14.13) a	19 (4.19) b	28 (6.18) b
Meat production: (X2 = 72.520, p < 0.001)	$\overline{\mathrm{x}}$ = 2.376	$\overline{\mathrm{x}}$ = 1.878	$\overline{\mathrm{x}}$ = 1.632
Increase (1)	51 (11.26)	35 (7.73)	42 (9.27)
Decrease (2)	92 (20.31) a	13 (2.87) b	9 (1.99) b
No change (3)	168 (37.09) a	26 (5.74) b	17 (3.75) b
Egg production: (X2 = 76.702, p < 0.001)	$\overline{\mathrm{x}}$ = 2.772	$\overline{\mathrm{x}}$ = 1.973	$\overline{\mathrm{x}}$ = 2.426
Increase (1)	19 (4.19)	31 (6.84)	15 (3.31)
Decrease (2)	33 (7.28)	14 (3.09)	9 (1.99)
No change (3)	259 (57.17) a	29 (6.40) b	44 (9.71) b
Wool production: (X2 = 63.044, p < 0.001)	$\overline{\mathrm{x}}$ = 2.129	$\overline{\mathrm{x}}$ = 1.959	$\overline{\mathrm{x}}$ = 2.044
Increase (1)	21 (4.64)	27 (5.96)	13 (2.87)
Decrease (2)	229 (50.55) a	23 (5.08) b	39 (8.61) b
No change (3)	61 (13.47) a	24 (5.30) b	16 (3.53) b
Animal reproductive efficiency: (X2 = 97.262, p < 0.001)	$\overline{\mathrm{x}}$ = 2.128	$\overline{\mathrm{x}}$ = 1.946	$\overline{\mathrm{x}}$ = 2.029
Increase (1)	28 (6.18)	34 (7.51)	20 (4.42)
Decrease (2)	215 (47.46) a	10 (2.21) b	26 (5.74) b
No change (3)	68 (15.01) a	30 (6.62) b	22 (4.86) b
Mortality rate: (X2 = 29.710, p < 0.001)	$\overline{\mathrm{x}}$ = 1.682	$\overline{\mathrm{x}}$ = 2.000	$\overline{\mathrm{x}}$ = 2.265
Increase (1)	178 (39.29) a	33 (7.28) b	19 (4.19) b
Decrease (2)	54 (11.92) a	8 (1.77) b	12 (2.65) b
No change (3)	79 (17.44) a	33 (7.28) b	37 (8.17) b

* Based on combined data from Egyptian and Spanish respondents, values are the number of responses and their corresponding percentages (%) unless otherwise noted, X² is the chi-squared value, p is the probability, $\overline{\mathrm{x}}$ is mean response on the Likert scale, and ^a,b superscripts indicate a significant difference between means within a row at p < 0.05.

). Both egg production and meat production were less associated with climate change and remain unchanged by climate factors (heat waves, humidity, and drought).

3.6. Strategies to Mitigate Effects of Climate Change Applied by Respondents

The proportions of smallholder livestock farmers who reported controlling housing conditions or adopting genetically improved animal breeds did not differ significantly between Egypt and Spain, while the proportion of farmers using nutritional strategies was significantly higher in Egypt (

Table 6. Strategies and types of support consider necessary to improve resilience of smallholder livestock farmers to climate changes.

Variable *		Egypt (n = 236)	Spain (n = 217)	Total (n = 453)
Use of strategies to alleviate the negative effects of climate change on the respondent’s farm (X2 = 9.099, p = 0.028)
Nutritional strategies		58 (24.58) a	33 (15.21) b	91 (20.09)
Controlling housing conditions		84 (35.59)	61 (28.11)	145 (32.01)
Adopting genetically improved animal breeds		13 (5.51)	9 (4.15)	22 (4.86)
No strategy applied		81 (34.32)	95 (43.78)	176 (38.85)
Some other strategy applied		0.00	19 (8.76)	19 (4.19)
Types of help needed to mitigate negative effects of climate change on the respondent’s farm (X2 = 6.371, p = 0.173)
Extension/veterinary services	63 (26.70)		46(21.18)	109 (24.06)
Improved infrastructure	35 (14.83)		50 (23.04)	85 (18.76)
Access to affordable adaptive animal breeds	37 (15.68)		31 (14.29)	68 (15.01)
Access to affordable water and alternative feed	34 (14.41)		28 (12.90)	62 (13.69)
Insurance and financial compensation	45 (19.07)		29 (13.36)	74 (16.34)
Other	22 (9.32)		33 (15.21)	55 (12.14)
Animal species most adaptable to climate change (X2 = 3.948, p = 0.138)
Large animals (cattle and buffalo)	101 (42.80)		90 (41.47)	191 (42.16)
Small ruminants (sheep and goats)	105 (44.49)		85 (39.17)	190 (41.94)
Monogastric animals (poultry, pigs, rabbits)	30 (12.71)		42 (19.35)	72 (15.90)

* Values are the number of responses and their corresponding percentages (%) unless otherwise noted, X² is the chi-squared value, and p is the probability, and ^a,b superscripts indicate a significant difference between means within a row at p < 0.05.

).

Farmers in the two countries also did not differ significantly in the types of services that they considered necessary to mitigate the negative effects of climate change, or in the animal species that they considered most adaptable to climate change (Table 6).

4. Discussion

4.1. Awareness of Climate Change

Our cross-sectional survey of smallholder livestock farmers in Egypt and Spain suggests that the two communities are quite aware of climate change and the dangers that it poses to their livelihood.

The high awareness of climate change and its negative effects on smallholder livestock farming in our sample echoes findings from a study of livestock farmers in Sierra Leone [18], which concluded that the farmers there are quite concerned about climate risks and closely follow climate change and its expected impacts on their farming systems. These results in several countries suggest that policymakers can rechannel their efforts away from trying to convince smallholder livestock farmers about climate change and its potential impacts toward implementing suitable measures to support farmers in mitigating those impacts. Nevertheless, our survey suggests that certain types of smallholder livestock farmers may benefit from awareness-building around climate change: those with no, primary, or secondary education; women; those who breed animals primarily for domestic consumption; and those who apply outdoor or mixed breeding systems.

Extension and advisory services could be a strong resource in increasing the awareness of climate change and its negative impacts [19,20,21], yet our survey found that very few farmers obtained relevant information from these sources. Instead, they obtained their information through personal experience, conversations with colleagues, or the media. Thus, our analysis highlights the need for greater contact between advisors and smallholder livestock farmers around the issue of climate change.

4.2. Major Climate Changes and Their Impact on Livestock Production, as Perceived by Smallholder Livestock Farmers

The changes in climate that most livestock farmers in both countries in our study observed were heat waves and humidity, with many Spanish farmers also mentioning drought. The Mediterranean basin is warming 20% faster than the global average, and an increase of 2–4 °C may reduce precipitation by up to 30% in southern Europe. Water temperature is expected to rise by between 1.8 °C and 3.5 °C by 2100 with hotspots in Spain and the eastern Mediterranean including Egypt. Droughts and the desertification of rivers has been reported in many European countries [22,23]. In this way, our survey suggests that smallholder livestock farmers in the Mediterranean align with what the United Nations and other expert groups are saying.

Our survey further suggests that farmers’ perceptions of the potential negative impacts of climate change on their livestock align with the available evidence. Our respondents reported that the spread of disease, the emergence of new disease, the intensive use of medication, and shortages of feed and water were major problems associated with climate change, and indeed, all of these have been linked to climate change. High temperature and humidity help spread disease and lead to the emergence of new disease. For example, a temperature rise of 5 °C in northern Europe would create suitable conditions for the bluetongue virus to spread to new areas by 2050 [24], and temperature increases may help aflatoxin B1 spread to new wheat and maize crops in Europe [25,26]. This may increase animal exposure to aflatoxin B1 in contaminated feed, affecting their own safety as well as that of the humans who consume their milk or meat. The spread of disease in animals can easily lead to greater use of antibiotics and other medicines, especially in Egypt, where few restrictions on antibiotic availability are enforced. In this and other ways, rises in temperature, humidity, and drought can promote the emergence of antimicrobial resistance [27,28]. Rising temperatures, humidity, and drought can cause shortages of water and feed [29,30], to which smallholder livestock farmers are particularly vulnerable [16], in part because their land tends to lie in arid and semi-arid regions [31].

Our survey participants reported significant decreases in milk yield, wool production, and reproductive performance as well as increased mortality, which our analysis attributed to heat waves, which is consistent with the known effects of heat waves on crop production, feed quality, animal productivity in general and wool production in particular [27], reproductive performance [32,33], and livestock immunity [34,35]. Also consistent with our results is a study suggesting that elevated temperatures during the century will reduce animal productivity by 25% [6].

Our respondents considered dairy animals and their milk production to be the most vulnerable to the effects of climate change, mainly heat stress (heat waves). This reflects the high metabolic rate of dairy animals and the fact that heat stress reduces their feed intake. Dairy cows in the Mediterranean produce less milk with rising temperature [36,37]. Large ruminants account for more than 96% of global milk production [38], and cattle and buffaloes are the main milk-producing animals in Egypt, with 85% of these animals owned by smallholder farmers. Larger animals are more vulnerable than smaller animals to heat stress [6].

Our respondents indicated that heat stress was less likely to affect egg production and growth performance. This may reflect short production cycles under controlled conditions, which mitigates the effects of climate change; one such example is poultry breeding for egg production [34,39].

More studies are needed to identify the livestock breeding systems and animal types that can better tolerate the harsh conditions of climate change.

4.3. Measures of Adaptation and Support to Mitigate Negative Effects of Climate Change on Smallholder Livestock Farming

The success of the dissemination of climate change adaptation strategies depends on whether farmers fully realize what climate change is and are therefore able to identify the adaptive measures necessary [15,40]. In our survey, 60% of participants indicated that they control housing conditions and apply nutritional strategies in order to adapt to climate change. In contrast, fewer respondents reported using genetically improved livestock breeds, and around 39% indicated that they required support for implementing this strategy. Genetic selection to improve livestock tolerance to heat stress, drought, and other challenges of climate change is actually one of the most important strategies for long-term adaptation, especially as the effects of climate change on animals intensify [41]. This strategy can also be effective even with outdoor and mixed breeding systems, which do not allow for the control of housing conditions.

Even though nearly all respondents in our survey indicated that they were aware of the potential negative effects of climate change on animal productivity and health, fully 30% reported not using any adaptive or mitigating measures, mainly due to the lack of advisory or extension/veterinary services. Studies in Bangladesh and Zambia have shown that farmers who have access to agricultural extension services are more likely to be aware of climate change and its risks to agriculture and are more likely to apply different effective adaptive strategies [42,43].

Our respondents also indicated the need for improving infrastructure and obtaining financial insurance. Many smallholder livestock farmers live in rural areas, which often lack infrastructure to ensure access to adequate feed, water, and energy in the face of climate change [18]. Especially for this reason, farmers should be introduced to drought-tolerant plant feed and shrubs common in the Mediterranean basin as a way to compensate for feed shortages, especially for smallholders with mixed breeding systems or pastures. Farmers should also be educated about techniques for storing feed, such as silage production, the use of mixed crops, and agricultural byproduct management.

Like the respondents in our survey, smallholder livestock farmers in Sierra Leone have also identified a lack of cash, poor infrastructure, and poor knowledge of management as barriers to the mitigation of the effects of climate change [18]. Another study in Indonesia, focusing on coffee and livestock integration as a climate-smart agriculture implementation for smallholders, highlighted the importance of establishing strategic partnerships with non-financial service providers and providing technical assistance towards optimal credit use to complement financial support for coffee–livestock integration [44].

4.4. Limitations and Recommendations

To our knowledge, this is the first study to assess the perceptions of smallholder livestock farmers in the Mediterranean Basin about major climate change, its negative effects on livestock performance, and the obstacles and adaptive strategies required to mitigate those effects. While respondents from Egypt and Spain overlapped extensively in their perceptions, there were some regional differences, such as the predominance of drought in Spain and the heat waves and high humidity in Egypt. Regional differences in climate, animal breeding systems, and goals of livestock production among smallholders mean that more countries than only Egypt and Spain should be analyzed in order to gain a complete picture of the resilience of Mediterranean farmers to climate change. In addition, future work should examine specific types of livestock farms individually (e.g., dairy farms, fattening farms, poultry farms) rather than in aggregate as in the present study.

5. Conclusions

In this case study, heat waves, humidity, and drought are the major changes in climate that negatively impact livestock production by smallholders. These climate change factors are associated with decreases in the availability of feed/fodder for the animals and increases in heat stress, as well as infectious diseases leading to the decrease in animal production and reproductive performance. According to the information collected through this survey, adaptation strategies such as improving animals’ tolerance to heat stress and drought through identifying local breeds most adapted to local climatic changes, adopting nutritional strategies, and controlling housing conditions might be the best options to relieve the negative effects of climate change in livestock. Similarly, forecasting systems and early warning systems should be developed for livestock disease control. All these strategies should also be linked with certain extension services in order to ensure their feasibility and applicability when applied by smallholder livestock farmers under Mediterranean conditions.