Carbon Footprint and Economic Trade-Offs in Traditional Greek Silvopastoral Systems: An Integrated Life Cycle Assessment Approach

Abstract

Silvopastoral systems, though ecologically beneficial, remain underrepresented in the European Union’s Common Agricultural Policy and are seldom studied in Mediterranean contexts. The current study assesses both the environmental and economic aspects of five typical silvopastoral systems in central Greece, encompassing cattle, sheep, and goat farming. A Life Cycle Assessment approach was implemented to quantify greenhouse gas emissions using economic allocation, distributing impacts between milk and meat outputs. Enteric fermentation was the major emission source, accounting for up to 65.14% of total emissions in beef-based systems, while feeding and soil emissions were more prominent in mixed and small ruminant systems. Total farm-level emissions ranged from 60,609 to 273,579 kg CO₂eq per year. Economically, only beef-integrated systems achieved an average annual profitability above EUR 20,000 per farm, based on financial data averaged over the last five years (2020–2024) from selected case studies in central Greece, while the remaining systems fell below the national poverty threshold for an average household, underscoring concerns about their economic viability. The findings underline the dual challenges of economic viability and policy neglect, stressing the need for targeted support if these multifunctional systems are to add value to EU climate goals and rural sustainability.

1. Introduction

Agroforestry systems (AFSs) contribute to sustainability by providing multiple ecosystem services, reducing input requirements, and mitigating the impacts of climate change [1,2]. The intentional integration of trees with pasture and/or crops simultaneously is widely regarded as highly resilient, multifunctional systems and effective carbon dioxide sinks, sustaining rural livelihoods and safeguarding essential aspects of local cultural heritage [3]. AFSs also optimize carbon sequestration by efficiently distributing resources between trees and crops. By creating shadier, cooler, and more humid microclimates, AFSs reduce the loss of fine organic matter through erosion and enhance mycorrhizal associations, thereby improving nutrient uptake and overall soil fertility [4]. To build resilience and reduce emissions, European agriculture should adapt to climate change, with agroforestry standing out as a key strategy that harmoniously integrates both goals [5].

Within the broader agroforestry framework, silvopastoral systems specifically involve the intentional integration of livestock grazing with woody vegetation, such as forests, woodlands, or orchards. These systems leverage complex livestock–tree interactions, including enhanced forage availability and nutritional quality under tree cover, improved animal thermal comfort, and reduced evapotranspiration, which extend feed production seasons by shielding pastures from heat and drought stress. Grazing livestock also contribute positively to forest and landscape management by reducing flammable understory vegetation, thereby mitigating wildfire risk and facilitating nutrient cycling through trampling and dung deposition [3,6]. However, these interactions are dynamic and context-specific, influenced by livestock species, grazing intensity, tree density, and local climatic and management conditions [7,8].

Across the European Union and the United Kingdom, agroforestry spans an estimated 15.4 million hectares—around 3.6% of total land and 8.8% of the agricultural area in use—demonstrating its potential for sustainable land use [9]. Despite this, many national policies still overlook its value in addressing climate challenges. Notably, 16 Member States have yet to incorporate agroforestry into their official strategies or action plans, revealing a clear disconnect between its benefits and current policy priorities [10]. This is further evident in the Common Agricultural Policy (CAP), where the absence of recognition for agroforestry practices is reflected in the legislation’s inability to identify optimal land-use combinations that would enhance productivity, as well as its failure to highlight areas where agroforestry could be effectively promoted [11]. Even today, many actions that should already be established as policies remain merely recommendations. Specifically, the integration of AFSs into climate neutrality efforts to support European climate change targets, as well as the simplification of policies under Pillar I and II payments, along with the need for clear objectives and reduced administrative burdens, remains inadequately addressed [12].

Traditional AFSs could offer viable and sustainable solutions to restore landscape productivity, particularly in the Mediterranean basin, where depopulation and wildfire susceptibility pose significant threats [13]. Despite their continuous provision of ecosystem services and numerous environmental benefits [14], farmers encounter significant challenges, including knowledge and experience gaps, labor shortages, limited access to capital, and inadequate technical support, which hinder their widespread adoption and effectiveness [15,16,17]. Furthermore, the so-called “industrial” agroforestry is often associated with negative overall impacts, as it typically involves limited intercropping practices, relies on highly destructive industrialized practices, and contributes to the conversion of pristine forests into mixed plantations [18]. In this context, carbon farming presents another challenge, as carbon-trading schemes can be exploited, potentially leading to a neoliberal land grab [19], accelerating deforestation and degradation of natural forests under the guise of agroforestry expansion [18].

The latter highlights the crucial role of rational management in sustainable AFSs, reducing Greenhouse Gas (GHG) emissions and promoting nature-based solutions that foster economic, environmental, and social stability in rural areas. AFSs have a higher Carbon (C) storage capacity than conventional arable systems [20] and offer a significant advantage over traditional agriculture by enhancing Soil Organic Carbon (SOC) stocks [21,22,23]. Nonetheless, AFSs often have higher C input requirements than conventional agricultural systems due to their increased resource demands [24]. Moreover, accurately assessing biomass C stocks and soil C storage in diverse agroforestry landscapes remains challenging and, in some cases, unreliable [25]. Given the diversity of AFSs, it is essential to quantify their environmental and economic impacts using a robust methodological framework, such as Life Cycle Assessment (LCA), to ensure comprehensive and accurate evaluation across various contexts and scales.

LCA is broadly acknowledged as a robust method for evaluating the environmental impacts associated with agricultural [26] and livestock production [27]. Although LCA has been increasingly applied to AFSs in recent years, the number of publications remains limited, with most studies concentrated in tropical regions, while in Europe, the majority of studies are concentrated in Spain [28]. The potential of AFSs to improve environmental sustainability in European agriculture has shown considerable variability in environmental performance, largely shaped by factors such as the types of livestock involved, the production objectives, and the degree of integration with semi-natural grasslands [29]. The impact of AFSs on ecosystem services is generally positive, enhancing their promotion towards sustainable rural practices, but it is strongly influenced by contextual factors [30].

Within this framework, the environmental and economic framework of AFSs in Greece remains vague, with limited research available on their impacts. Greece has a rich tradition of agroforestry [31,32] and features one of the highest proportions of utilized agricultural area in Europe, comprising 31% AFSs, particularly in the central and northeastern regions of the country [9]. Regarding the silvicultural systems, mixed outcomes concerning both economic and environmental impacts were reported regarding olive trees and annual crops in Northern Greece, underscoring the need for further research [24]. Furthermore, the Greek silvopastoral systems illustrate high environmental impacts, mainly due to low efficiency figures and output levels [29], while other implications integrate higher economic and administrative burdens [33] as well as challenges related to management practices [34]. The primary objective of this study is to conduct a comprehensive economic and environmental assessment of silvopastoral systems in Central Greece within an LCA framework. Given the lack of previous studies on the GHG emissions of silvopastoral systems in Greece, this research aims to address this gap and establish an initial baseline.

Silvopastoral systems require tailored evaluation methods within LCA and Life Cycle Costing (LCC) frameworks due to their distinctive livestock–tree components. LCA should integrate livestock-related emissions, such as enteric fermentation and manure management, and carefully address allocation between meat and milk outputs [35,36]. Similarly, LCC in silvopastoral systems should capture economic dimensions unique to livestock–forest operations, including rotational grazing infrastructure (if any), animal health management, etc., elements less prevalent in crop-dominated AFS. In this context, the current study focuses on whole-farm economic and environmental performance to reflect the real-world complexity of silvopastoral systems. By analyzing complete farm operations rather than standardized units, critical trade-offs are observed that are often obscured in unit-based assessments. This system-level perspective is essential for understanding the diverse outcomes and sustainability challenges faced by mixed-production farms.

2. Materials and Methods

2.1. Study Area and Experimental Systems

The study area is in the Evritania Prefecture (38°40′–39°17′Lat. and 21°22′–21°57′Long.). Local vegetation is mostly composed of Abies borisii regis and Abies cephalonica fir forests. The area is a transitional zone between the Abies cephalonica found further south and the Abies borisii regis found further north [37]. The area has a continental Mediterranean climate, with mean annual temperature of 9.9 °C, mean minimum temperature of −1.5 °C, mean maximum temperature of 25.2 °C, and mean rainfall of 1402 mm (1973–2005 data from Agios Nikolaos meteorological station). The drought period usually lasts from mid-June to early September.

Livestock farming in Evrytania is mainly semi-extensive. The grazing period varies from 6 to 7 months in the more mountainous areas to 10 to 11 months in the more lowland areas around Lake Kremasta. During the rest of the season, the animals remain in the stables and are fed with various mixtures of cereals, hay, and straw. Cattle farming is on the rise, while sheep and goats are on the decline. In 2024, the number of cattle was about 5700, while the number of milking female sheep was 23,072, and that of goats was 13,875 (data derived from the Department of Animal and Plant Sciences of the Regional Unit of Evrytania). Cattle farming in Evrytania is exclusively for meat production. On the other hand, sheep and goat farming has a mixed purpose, with the focus on dairy production. Ewes and goats are fed more intensively during lactation, while lambs and kids available for slaughter are either raised exclusively on their mothers’ milk or on various combinations of milk, cereal, and hay or fresh grass, depending on the time of year. This study draws upon the analysis of five case studies, selected for their representativeness of the most typical forms of silvopastoral farming systems, as detailed below:

• Mixed Beef–Sheep Meat and Dairy System (GBS)
• Extensive Beef Meat and Grazing Sheep Dairy System (EBGS)
• Grazing Meat and Milk Sheep System (GS)
• Extensive Dairy Goat System (EGo)
• Extensive Meat and Dairy Goat System (EGo+)

The GBS farm is a mixed-production system representing a traditional model of beef production from suckler cows, utilizing marginal grassland areas in the Evritania region. In addition, the silvopastoral system includes extensive sheep farming for both meat and milk production. Farm management follows a semi-extensive approach, combining the use of natural pastures with supplemental feeding through corn and alfalfa fodder for the sheep and concentrates for the cows. The EBGS silvopastoral system follows similar management principles, with two main distinctions: sheep are raised exclusively for milk production, and cattle—both cows and calves—graze on pastures throughout the entire year.

This GS system is centered around sheep, which graze on designated areas for approximately six months each year, operating within a semi-extensive framework. The system produces both meat and milk, with management practices designed to optimize the use of available grazing resources. The goat systems follow similar management practices, adhering to a purely extensive framework that utilizes available pasture resources and woodland waste. The primary distinction between the two systems lies in the output products: the EGo farm produces only milk, while the EGo+ farm generates both meat and milk.

2.2. Goal and Scope Definition

LCA is a comprehensive framework, assessing and estimating the environmental impacts associated with the entire lifecycle of a product or process [38]. The flexibility of LCA through the amalgamation of environmental and socio-economic factors develops an integrated assessment tool in the form of a Life Cycle Sustainability Assessment (LCSA) [39].

The current study applies an integrated environmental–economic approach, specifically combining LCA with LCC to evaluate the environmental and economic sustainability of silvopastoral systems in Greece. Social aspects are discussed qualitatively but not modelled quantitatively due to methodological limitations and data unavailability.

The primary objective of this study is to conduct a comprehensive assessment of silvopastoral agroforestry systems located in the Evrytania region of Central Greece. The evaluation focuses on the estimation of Carbon Footprint (CF), defined as the net GHG emissions per unit of product, implementing an LCA approach. This study applies a cradle-to-gate system boundary, encompassing both on-farm emissions, such as those from livestock (e.g., enteric fermentation), soil processes, and manure management, and off-farm emissions, including those related to electricity and fuel consumption, fodder production, and water needs.

To ensure comparability and relevance, emissions are reported using two functional units: (i) per unit of main product (i.e., kg of meat or per liter of milk), and (ii) as total CF per farm. The economic evaluation is conducted in parallel, using a similar methodological framework to evaluate the financial sustainability of the selected silvopastoral systems. It should be noted that emissions and costs related to machinery, infrastructure, and veterinary pharmaceuticals are excluded from the analysis. Figure 1 illustrates the system boundaries applied in both the LCA and LCC components. It includes on-farm sources of emissions such as enteric fermentation, manure management, and soil processes, as well as off-farm inputs like feed, fuel, water, and electricity. Within this framework, the selected five illustrative case studies are systematically analyzed, allowing for a comparative assessment of their environmental impacts in terms of CO₂-equivalent emissions, as well as their economic performance within a context of increasing sustainability demands.

2.3. Inventory Analysis

Each stage of the assessment is linked to a range of products, quantified as emissions per unit, depending on the selected indicator. In accordance with the defined system boundaries, most emission factors and calculation equations implemented are derived from the Intergovernmental Panel on Climate Change (IPCC) guidelines [40]. The analysis incorporated Greece’s National Inventory Report on GHGs to comply with national reporting standards [41]. For parameters not included in the national inventory, regionally consistent values from Eastern European and Mediterranean datasets were applied, following IPCC Refinement recommendations. Emissions are reported in terms of CO₂ equivalents (CO₂–eq), using a 100-year Global Warming Potential (GWP) of 27 for methane (CH₄) and 273 for nitrous oxide (N₂O), as established by the latest (6th) IPCC Assessment Report [42]. The inventory analysis encompassing primary GHG emissions, emission factors, and associated data is presented in

Table 1. Inventory analysis for emissions.

Emission types	GHG	Emission factors	Unit	Reference
Enteric fermentation
Dairy Cattle	CH4	99	kgCO2eq/head	[41,43]
Other Cattle	CH4	58	kgCO2eq/head	[41,43]
Goats	CH4	5	kgCO2eq/head	[41,43]
Sheep	CH4	8	kgCO2eq/head	[41,43]
Manure management
Dairy Cattle	CH4	1.03	kgCO2eq/head	[41]
Other Cattle	CH4	0.2	kgCO2eq/head	[41]
Goats	CH4	12.72	kgCO2eq/head	[41]
Sheep	CH4	3.6	kgCO2eq/head	[41]
Direct N2O	N2O	0.005	kg N2O eN/kg N Solid storage system	[41,43]
Indirect N2O	N2O	0.01	kg N2O eN/volatilized	[41,43]
Soil management
N from urine and dung inputs to grazed soils in Sheep/Goat	N2O	0.01	kg N2O eN per kg N input	[41,44]
N from urine and dung inputs to grazed soils in Cow	N2O	0.02	kg N2O eN per kg N input	[41,44]
Indirect Emissions	N2O	0.01	kg N2O eN per kg % N volatilized/leaching	[41,44]
Off-farm
Concentrates Meat Cow	CO2	0.655	kg CO2eq/kg	[45]
Concentrates Dairy Sheep	CO2	0.512	kg CO2eq/kg	[45]
Concentrates Meat Sheep	CO2	0.513	kg CO2eq/kg	[45]
Concentrates Goat	CO2	0.753	kg CO2eq/kg	[45]
Fodder corn	CO2	0.296	kg CO2eq/kg	[45]
Fodder triticale	CO2	0.353	kg CO2eq/kg	[45]
Fodder barley	CO2	0.321	kg CO2eq/kg	[45]
Energy
Electricity	CO2	0.258	kg CO2eq/kWh	[46]
Fuel diesel combustion	CO2	2.664	kg CO2eq/liter-combustion	[45]
Fuel diesel upstream	CO2	0.32	kg CO2eq/liter-upstream	[45]

.

In parallel with the development of the emissions inventory, a detailed economic dataset was also compiled. This included a range of variables, such as capital costs, labor wages, product market prices, hours contributed by family members, and the proportion of the labor force that was hired. Following the LCC methodological framework, economic data were collected based on actual farm operations, covering a five-year period regarding the silvopastoral systems under study. Electricity prices were obtained from Eurostat statistical reports, calculated as the average over the most recent five-year period [47], while fuel prices were derived from the European Commission’s Weekly Oil Bulletins [48], averaged across the reporting periods of the past five years to ensure representativeness and temporal consistency. The resulting average prices, including taxes, were EUR 0.204 per kWh for electricity and EUR 1.6329 per liter for automotive diesel fuel.

2.4. Impact Assessment Calculations

A variety of methodological approaches for estimating GHG emissions and their contribution to the CF of a product or service have been developed and are well documented in the scientific literature [49]. For the environmental impact assessment, all relevant inventory data were converted into CO₂ equivalents, applying the 100-year GWP metric. The methodological protocol for calculating environmental outcomes draws upon established literature, including comparative studies of agroforestry systems in Spanish regions, conducted under comparable agro-climatic and livestock production conditions [50,51,52]. The unified CO₂ equivalent indicator (EI) is determined by the GWP over a 100-year horizon and the emission factors (EFs) representing the quantity of each pollutant j emitted per management system i as follows:

$${\mathrm{E}\mathrm{I}}_{\mathrm{i}}=\sum _{\mathrm{n}=1}^{\mathrm{i}}{\mathrm{E}\mathrm{F}}_{\mathrm{i},\mathrm{j}}\times {\mathrm{G}\mathrm{W}\mathrm{P}}_{100}$$

(1)

Apart from the environmental analysis, the economic assessment has to calculate accurate annual estimates of cash flow, investment costs, and revenues over a farm’s lifecycle, accounting for operational variability and the long-term economic span of agroforestry systems [24]. The LCC approach distributes fixed and variable costs across a farm’s annual cycle, allowing for the calculation of indicators such as Net Present Value (NPV), which captures the net difference between discounted revenues and expenditures over time. In this context, Discounted Cost (DC) is derived using a similar mathematical formulation as NPV, but accounting exclusively for cash outflow as follows [53]:

$$DC=\sum _{t=0}^n{\displaystyle \frac{O_t}{{\left(1+i\right)}^t}}$$

(2)

where O_t represents the outflows per year, i is the discount rate and t is the amount of time periods for the selected AFS. The outflows are linked to reported expenditures for labor, energy, feed, land acquisition, and veterinary treatments. The discount rate used in economic analyses for silvopastoral systems varies based on factors like project type, economic conditions, and country-specific rates. The selected discount rate of 4% was determined based on current Greek financial conditions and established European practices, incorporating the real yield of Greek government bonds together with a moderate risk premium reflecting typical uncertainties and liquidity constraints. Such an approach aligns with established methodologies in agroforestry assessments, which typically utilize a 4% real discount rate in the European region [54,55].

2.5. Allocation Method

The selection of a credible allocation procedure focusing on the ISO principles [56] should hinge on the idea that one factor directly influences or causes a change in the other. Therefore, the economic allocation method could be a key step in calculating the CF, since it is frequently applied in LCA of agri-food systems and is particularly relevant to attributional LCA approaches [57]. The importance of economic allocation, particularly when utilized in livestock systems, is further enhanced by Kytta et al. [58], Pereyra-Goday et al. [59], and Weiler et al. [60]. Moreover, economic allocation is seen as an efficient approach for distributing and categorizing environmental impacts in cases where multiple co-products are generated, as is often the case in similar agricultural systems [61].

Nevertheless, the economic allocation is not a spotless approach, integrating a degree of uncertainty due to price fluctuations, which may influence the final outcomes [62]. State interventions such as subsidies and/or quotas can further complicate the accurate assessment and comparison of environmental impacts [63]. Nevertheless, economic allocation is still considered consistent in application, particularly in cases where processes are interconnected and cannot be easily separated [64]. For the current study, emissions are allocated based on the economic value of the milk and meat produced by the silvopastoral systems, following the economic allocation approach.

3. Results

The silvopastoral systems analyzed display both common features and significant differences in terms of inputs and outputs, shaped mainly by resource availability and associated costs. Farm-level specificity is central to depiction of the results, enabling a detailed examination of the unique performance patterns within each silvopastoral system.

Table 2. Technical indicators of the selected systems.

Indicators	GBS	EGBS	GS	EGo	EGo+
Farm
System type	Mixed	Extensive beef/grazing sheep	Grazing	Extensive	Extensive
No. of reproductive sheep and/or cows (average population)	200	90	160	180	170
Lambs born per sheep	1.25	1.36	1.33	-	-
Calves born per cow	0.86	0.91	-	-	-
Kids born per goat	-	-	-	1.29	1.21
% Grazing time/year	Cows 50%/Sheep 60%	Cows 100%/Sheep 60%	60%	100%	100%
Inputs
AWUs	1	1	1	1	1
Family AWUs	0.31	0.19	0.11	0.17	0.11
Fuel (l)	2000	1200	2500	1500	1700
Electricity (kWh)	6000	1500	5000	0	0
Water (m3)	1100	800	310	0	0
Fodder bought (t)	40	3	25	4	17
Concentrates bought (t)	20	8	32	4	-
Outputs
Goat/Sheep Milk (l)	9990.00	4138.00	13,886.00	20,632.00	14,804.00
Goat/Sheep Meat (kg)	608.00	-	1484.00	-	1634.00
Beef Meat (kg)	9986.00	6970.00	-	-	-

summarizes the main production characteristics, resource requirements, and outputs for the five systems studied (GBS, EGBS, GS, EGo, and EGo+). Differences in farm structure are evident, especially in terms of livestock types, grazing practices, and input use. Although none of the farms reported employing external labor, all relied to some extent on family members to carry out farm activities, with family labor contributions ranging from 0.11 to 0.31 Annual Working Units (AWUs).

Additionally, the GBS farm recorded the highest levels of energy use and water consumption, which can be attributed to its simultaneous production of beef meat, sheep meat, and sheep milk. In contrast, the purely extensive goat systems (EGo and EGo+) showed no electricity usage, as reported by the farm owners, and highlighted significantly lower water requirements. As expected, the proportion of time animals spend grazing throughout the year greatly influences the dependence on purchased fodder and concentrates, with extensive systems requiring considerably less external feed input.

3.1. Economic Assessment

To assess the economic impact of each input and output on the final production,

Table 3. Farm-level economic metrics.

Farm ID	GBS	EGBS	GS	EGo	EGo+
Cost
Feeding (EUR)	28,100.00	15,480.00	15,240.00	7040.00	6000.00
Energy (EUR)	2423.48	1387.74	3305.80	1320.00	1496.00
Labor (EUR)	3300.00	2100.00	1200.00	1800.00	1200.00
Vet/Pharma (EUR)	3750.00	1250.00	1500.00	1500.00	1000.00
Water (EUR)	1922.91	961.45	411.58	-	-
Revenue
Milk Revenue (EUR)	12,012.00	4965.60	16,663.20	17,743.52	15,544.20
Goat/Sheep Meat Revenue (EUR)	3648.00	-	12,820.00	-	14,040.00
Beef Meat Revenue (EUR)	49,950.00	38,335.00	-	-	-
Total Revenue (EUR)	65,610.00	43,300.60	29,483.20	17,743.52	29,584.20
Economic/Area Allocation
% from Milk	18.31%	11.47%	56.52%	100.00%	52.54%
% from Meat	81.69%	88.53%	43.48%	0.00%	47.46%
Total Area (ha)	250	125	200	155	110
Revenue per ha (EUR)	262.44	346.40	147.42	114.47	268.95
Cost per ha (EUR)	157.99	169.43	108.29	75.23	88.15

was created to illustrate the costs and revenue generated by each silvopastoral system. This table provides an overview of the economic performance of the selected systems, detailing expenses for feeding, energy, labor, veterinary services, and water, alongside revenue from milk and meat production. The farms cover areas ranging from 125 to 250 hectares, which are not owned by the farmers but consist of land with woody vegetation, including forests and grasslands, where grazing is permitted.

GBS demonstrates the highest total revenue (EUR 65,610) due to its diversified production of beef, sheep meat, and milk, though it also includes the highest feeding costs (EUR 28,100), labor costs (EUR 3300), vet/pharma expenses (EUR 3750), energy expenses (EUR 2423.48), and water expenses (EUR 1922.91). In contrast, the purely extensive goat systems (EGo and EGo+) have lower input costs, especially in feed and veterinary expenses, but consequently show lower overall revenue, with EGo generating EUR 17,743.52 entirely from milk production. The GBS and EGBS systems are primarily focused on meat production, with more than 80% of their income coming from meat sales. In contrast, the GS and EGo+ systems have a more balanced revenue structure, with milk contributing slightly more to their income (56.52% and 52.54%) compared to meat (43.48% and 47.46%), respectively. Feeding costs appear to be a major economic factor, significantly impacting the total expenses. To illustrate this, Figure 2 presents the cost breakdown, showing how resources are allocated across the selected farms.

Feeding expenses represent the largest cost component across all selected systems, ranging from 58.86% in the EGo system to 71.40% in the EGBS system. Furthermore, land acquisition costs are minimal for farmers as they utilize state-provided land, resulting in the lowest cost percentages. Energy costs include expenses for fuel and electricity consumption, integrating a significant portion of expenses in the goat and sheep systems, ranging from 11.22% to 15.27%. Energy shares decrease proportionally in the GBS and EGBS systems (6.06% and 6.40%, respectively), while water consumption costs account for 4.81% and 4.43%, respectively, in these systems.

In GBS and EGBS, high feeding costs dominate the budget, reflecting input-intensive strategies, whereas in EGo and EGo+, lower feed shares are offset by higher proportions of labor and veterinary costs. Cost per hectare followed a similar pattern, with the most input-intensive systems, EGBS (EUR 169.43/ha) and GBS (EUR 157.99/ha), illustrating the highest values, and the extensive goat-based systems, EGo (EUR 75.23/ha) and EGo+ (EUR 88.15/ha), the lowest.

3.2. Environmental Assessment

Apart from the economic assessment, the current study highlights the key environmental challenges of the Greek silvopastoral systems.

Table 4. Carbon footprint of meat and milk production in livestock systems (kg CO₂eq/unit).

Emission Source	Unit	GBS	EGBS	GS	EGo	EGo+
Enteric fermentation CH4
Cows	kg CO2eq/kg meat	15.68	8.95	-	-	-
Goat/Sheep (meat)	kg CO2eq/kg meat	8.28	-	10.13	-	6.67
Goat/Sheep (milk)	kg CO2eq/L milk	1.66	2.70	1.41	1.22	0.81
Manure management
Cows	kg CO2eq/kg meat	2.18	1.26	-	-	-
Goat/Sheep (meat)	kg CO2eq/kg meat	2.83	-	3.46	-	3.29
Goat/Sheep (milk)	kg CO2eq/L milk	0.57	0.92	0.48	0.44	0.40
Soil management
N from urine and dung inputs to grazed soils (Cows)	kg CO2eq/kg meat	3.13	2.98	-	-	-
N from urine and dung inputs to grazed soils (Goat/Sheep meat)	kg CO2eq/kg meat	1.48	-	2.18	-	4.61
N from urine and dung inputs to grazed soils (Goat/Sheep milk)	kg CO2eq/L milk	0.30	0.48	0.30	0.84	0.56
Energy
Electricity (Cows)	kg CO2eq/kg meat	0.12	0.05	-	-	-
Electricity (Goat/Sheep meat)	kg CO2eq/kg meat	0.14	-	0.38	-	-
Electricity (Goat/Sheep milk)	kg CO2eq/L milk	0.03	0.01	0.05	-	-
Fuel combustion (Cows)	kg CO2eq/kg meat	0.41	0.41	-	-	-
Fuel combustion (Goat/Sheep meat)	kg CO2eq/kg meat	0.49	-	1.95	0.20	1.32
Fuel combustion (Goat/Sheep milk)	kg CO2eq/L milk	0.10	0.09	0.27	-	0.16
Fuel upstream (Cows)	kg CO2eq/kg meat	0.05	0.05	-	-	-
Fuel upstream (Goat/Sheep meat)	kg CO2eq/kg meat	0.06		0.23	0.02	0.16
Fuel upstream (Goat/Sheep milk)	kg CO2eq/L milk	0.01	0.01	0.03	-	0.02
Feeding
Concentrates for Cows	kg CO2eq/kg meat	1.03	0.59	-	-	-
Concentrates for dairy Sheep	kg CO2eq/L milk	-	-	0.85	-	-
Concentrates for meat Sheep	kg CO2eq/kg meat	-	-	6.14	-	-
Concentrates for dairy Goats	kg CO2eq/L milk	-	-	-	0.15	-
Fodder corn for meat production	kg CO2eq/kg meat	1.70	-	-	-	0.86
Fodder corn for milk production	kg CO2eq/L milk	0.34				0.11
Fodder triticale for dairy Goat/Sheep	kg CO2eq/L milk	0.68	0.26	0.36	0.07	0.06
Fodder triticale for meat Goat/Sheep	kg CO2eq/kg meat	3.38	-	2.59	-	0.51
Fodder barley for milk production	kg CO2eq/L milk	-	-	-	-	0.02
Fodder barley for meat production	kg CO2eq/kg meat	-	-	-	-	0.19
Totals
Cows	kg CO2eq/kg meat	22.59	14.28	-	-	-
Goat/Sheep (meat)	kg CO2eq/kg meat	18.36	-	27.05	-	17.60
Goat/Sheep (milk)	kg CO2eq/L milk	3.68	4.48	3.75	2.94	2.15
Total kgCO2 per year	kg CO2eq/farm	273,579.14	117,868.57	92,333.36	62,021.24	60,609.86

integrates the impact of the various emission sources in the five analyzed systems, expressed in kg CO₂ equivalents per unit of measure. Taking into account the total emissions per farm, the GBS system emerges as the highest emitter, with a total of 273,579.14 kg CO₂eq per year, primarily driven by the substantial emissions from both enteric fermentation and feeding, especially during the calf fattening stage. The EGBS system highlights significantly lower total emissions (117,868.57 kg CO₂eq per year), while the goat/sheep systems (GS, EGo, EGo+) present notably lower emissions, with GS at 92,333.36 kg CO2eq, EGo at 62,021.24 kg CO2eq, and EGo+ at 60,609.86 kg CO₂eq. Among these, the emissions per unit of milk and meat are lower for EGo and EGo+ systems, with feeding and energy consumption playing a more prominent role in GS, especially in meat production.

In systems involving cows, such as GBS and EGBS, enteric fermentation accounts for substantial CH₄ emissions, with GBS reporting the highest emissions of 15.68 kg CO₂eq per kg of meat. Furthermore, the EGBS system shows relatively high emissions from both enteric fermentation and manure management, albeit at a lower rate due to fewer numbers of reproductive animals. The EGo and EGo+ systems illustrate comparatively lower emissions in these categories. Goat and sheep meat production results in lower enteric fermentation emissions, with the highest emissions reported in GS (27.05 kg CO₂eq per kg of meat). These results highlight the total and per-product impact; the importance of the emission levels regarding the selected silvopastoral systems is depicted in Figure 3.

Enteric fermentation plays the most important role for all the analyzed systems, accounting for more than one-third of the total emissions. Farms that include beef cattle production are associated with the highest percentage of emissions due to enteric fermentation, with GBS and EGBS accounting for 65.14% and 62.31% of their GHG emissions, respectively. Manure management and soil management also have a significant impact on emissions, with the goat systems (EGo and EGo+) illustrating the largest contributions from soil management (27.12% and 26.21%, respectively) and suggesting a higher reliance on grazing. The energy/fuel impact category shows lower contributions in total, with the GBS and EGBS systems at a slightly lower level (3–4%), whereas the goat/sheep systems range between 7 and 10%. Finally, emissions related to feeding are the second most significant contributor in the GS system (32.26%), but are less significant in the other systems, with values below 10%.

3.3. Economic and Environmental Trade-Offs

The paired-bar comparison in Figure 4 contrasts the shares of total monetary cost and total GHG emissions attributable to feeding and on-farm energy for each silvopastoral system. Purchased feed is the dominant expenditure in every case (≈ 60–71% of total cost), yet its climate relevance is highly system-specific. In the cattle-based farms (GBS, EGBS), feed contributes only 4–9% of the footprint because enteric fermentation remains the overriding emission source (≥62%). Conversely, in the case of GS concentrate use, the feed’s GHG share increases to 32%, demonstrating a marked decoupling between euro and carbon burdens.

Energy and fuel represent a consistent, though secondary, driver, accounting for 6–15% of the cost and 3–10% of GHG, being highest in the goat–sheep farms (GS, EGo, EGo+) due to higher demands for diesel and electricity. By contrast, in small-ruminant systems, feed manufacture and energy account for 40–60% of emissions and a similar share of operating costs; thus, the priority is to reformulate concentrates with local legumes or agro-industrial by-products, adopt precision feeding to curb N excretion, and replace diesel or grid electricity with on-farm solar, measures that jointly lower both € ha⁻¹ and kg CO₂-eq ha⁻¹.

Scaling subsystem insights into farm totals reveals two profitable but contrasting pathways. EGBS delivers a high economic margin (~EUR 177 ha⁻¹) yet remains emission-intensive (~940 kg CO₂-eq ha⁻¹), typifying a “high-output/high-impact” model. EGo+, by restraining external feed and fuel inputs, achieves an even higher margin (~EUR 181 ha⁻¹) at a substantially lower footprint (~550 kg CO₂-eq ha⁻¹). Intermediate systems (GBS, GS, EGo) cluster around lower margins or higher footprints, underscoring that profitability and climate performance are not inherently aligned. Figure 4 highlights where economic savings and emission reductions can converge—feed sourcing in GS and energy rationalization in EGo/EGo+—providing clear priorities for targeted improvement.

4. Discussion

Under the European Climate Law, the EU has committed to reducing GHG emissions by 55% by 2030 compared to 1990 levels and achieving climate neutrality by 2050 [65]. In this context, agroforestry systems could play a pivotal role in supporting these goals [66], though agroforestry systems remain largely underrepresented and undervalued within the CAP [11]. To address the existing knowledge gap among Member States in the EU, it is essential to systematically monitor and document the potential environmental and socio-economic effects. This study represents an initial effort to quantify such impacts for typical silvopastoral systems in Greece, marking a first step in this direction. Regarding the total figures, the CF associated with beef-cow breeding operations was found to be higher than that of goat and sheep meat production, consistent with expectations and findings reported in comparable studies [67]. Escribano et al. [68] reported a CF of 639.58 kg CO₂eq per hectare in comparable systems characterized by low stocking densities and minimal labor demands, primarily met through family involvement. These results align closely with the present study’s average estimate of 690.01 kg CO₂eq per hectare.

Nevertheless, Eldesouky et al. [50] reported significantly higher emissions (425,036 kg CO₂eq) for a grazing dairy sheep farm, compared to the substantially lower figure observed in this study (92,333.36 kg CO₂eq). This discrepancy is largely attributable to the scale of the operations, as the referenced farm maintained around 600 reproductive sheep, whereas the farms examined here averaged approximately 160 animals. Regarding the shares of GHG emissions, enteric fermentation emerges as a dominant factor, with its significance varying based on animal species, herd size, and feeding practices. The results are partially consistent with previous research. Specifically, the proportion of emissions from enteric fermentation in the dairy goat and sheep farms analyzed here falls within a range comparable to earlier studies, which have reported contributions as high as 43.63% of total farm emissions [50,51]. In contrast, the same studies on meat sheep farms have reported significantly higher contributions from enteric fermentation, in some cases reaching up to 80% of total emissions. However, this pattern does not hold in the current analysis, due to the mixed-production nature of the examined systems, which generate both meat and milk rather than focusing exclusively on meat production.

Transforming degraded pastures into well-managed silvopastoral systems in beef-cow breeding operations holds potential for fostering more sustainable farming practices. This is stated by de Figueiredo et al. [69], highlighting environmental impact values between 9.4 and 18.5 kg CO₂eq per kg of meat, which are in line with the current study (ranging from 14.28 to 22.59 kg CO₂eq per kg of meat). Furthermore, the contribution of enteric fermentation to total emissions in the current research (62.31% for EGBS and 65.14% for GBS systems) also aligns with the broader literature, where reported shares vary from 51% to 87% [51,68,69]. However, in systems that include cattle, feeding does not emerge as a dominant contributor to environmental impacts (feeding shares between 4.38% and 8.60%), with their share falling well below the 30% as reported by Eldesouky et al. [50]. Instead, the results align more closely with those of Horrillo et al. [51], largely due to the reduced use of concentrate feed per animal.

One of the key limitations of agroforestry systems lies in their economic profitability [70,71], and this study reinforces this conclusion to a higher degree. While farms incorporating beef-cow meat production demonstrate relatively adequate profit figures (EUR 25,613.61 for GBS and EUR 21,621.41 for EGBS), the remaining three systems generate less than EUR 13,671, below the national poverty threshold for an average household [72], raising concerns about their financial viability. However, on a per-hectare basis, the overall figures align reasonably well with those reported in comparable studies [73]. Furthermore, potential subsidies could enhance the willpower of farmers to adopt silvopastoral practices [74], though there were no subsidies reported by the participants in the current research, further reducing their total income. This is evident from other Greek goat farms, which have demonstrated significantly higher gross margins [75]. It should be noted, however, that these farms were not operating under silvopastoral conditions and were situated in non-mountainous areas.

A significant financial challenge for farmers is the feeding costs, accounting for more than 59% of the total expenses in each of the selected silvopastoral systems. Combined with broader socio-economic pressures that have driven either intensification or abandonment of traditional practices, these high costs have contributed to the declining appeal of agroforestry systems. A distinct inverse relationship emerges between economic margin and greenhouse gas intensity across the five silvopastoral systems studied. The beef-dominated EGBS farm records a high gross margin of approximately EUR 177 ha⁻¹ but an emission intensity of roughly 940 kg CO₂-eq ha⁻¹, whereas the low-input goat–sheep system EGo⁺ attains a comparable margin (~EUR 181 ha⁻¹) at a significantly lower footprint (~550 kg CO₂-eq ha⁻¹). Conversely, GS and EGo exhibit the smallest margins alongside the lowest emissions, while GBS occupies an intermediate economic position yet displays the largest footprint (~1090 kg CO₂-eq ha⁻¹). These patterns confirm that, within the selected systems, greater profitability is generally associated with higher climate impact, underscoring a measurable economic–environmental trade-off among Mediterranean silvopastoral systems.

Cattle-based systems are dominated by enteric fermentation emissions, so the most effective lever is to restrain ruminal methanogenesis. In this context, feed additives such as 3-nitrooxypropanol could routinely lower enteric emissions by around 30% in dairy and beef trials without depressing growth performance [76]. By contrast, goat–sheep farms derive 40–60% of both costs and GHG emissions from concentrate feed and energy needs. Therefore, replacing cereal concentrates with local agro-industrial by-products can cut feed-related emissions by 15–25% while reducing ration costs [77].

Furthermore, the European trend toward environmental sustainability and circular economies develops a new scheme, altering the farm efficiency and complicating even further the decision-making process [78]. To reverse this trend, policy interventions are needed to correct the current imbalances and encourage adoption by offering targeted incentives. Policy support should target each system’s critical hot spots. In cattle farms, cost-sharing for enteric-methane inhibitors offers a cost-effective route to simultaneous economic and environmental gains [79]. For goat–sheep systems, grants should prioritize on-farm protein-crop cultivation, preservation of indigenous breeds, and the adoption of context-appropriate novel technologies [80,81]. Supporting agroforestry is crucial, given its substantial ecological and cultural value within the Greek landscape [31].

5. Conclusions

Agroforestry systems integrate nature-based approaches that support the sustainable development of rural and environmentally vulnerable regions. In this context, the current study offers an initial assessment of the environmental and economic performance of traditional silvopastoral practices in central Greece. The systems examined relied exclusively on family labor and illustrated high costs for feeding operations. Furthermore, enteric fermentation emerged as the dominant contributor, accounting for more than one-third of total GHG emissions for all the silvopastoral systems.

Focusing on sheep and goat farms, they emit considerably lower environmental impacts; however, their economic returns remain insufficient. The profit generated is considered inadequate, and government support (subsidies or targeted policy measures) is essential for their viability. Regarding social sustainability, the current study captured only basic indicators, family labor structures, absence of workplace injuries or chemical exposure, and lack of PDO/PGI certification.

Because these qualitative findings do not fully represent equity, well-being, or broader stakeholder perspectives, future studies could apply a dedicated social study based on stakeholder consultations to quantify social costs and benefits. Other studies could explore the carbon sequestration capabilities of silvopastoral systems to better understand their environmental trade-offs relative to conventional livestock farming. Furthermore, incorporating a broader range of environmental impact categories (e.g., acidification) could provide a more comprehensive evaluation of the strengths and weaknesses of Greek silvopastoral practices