Livestock systems and land use: which diversity for which sustainability?
M. Durua,b,*, O. Theronda,b
a
INRA, UMR 1248 AGIR, F-31326 Castanet Tolosan, France
b
Université Toulouse, INPT, UMR AGIR, F-31029 Toulouse, France
* corresponding author
ABSTRACT: Changes in agriculture during the twentieth century led to high levels of food
production based on increasing inputs and specialization of farms and agricultural regions. To
address negative externalities of these changes, two forms of ecological modernization (EM) of
agriculture are promoted: “weak-EM”, based on increasing input efficiency through crop and animal
monitoring and nutrient recycling, and “strong-EM”, based on increasing agrobiodiversity at
different space and time scales to develop ecosystem services and in turn reduce inputs. We analyze
whether within- or among-farm diversity (in species or farming practices) is an asset for the
sustainability of livestock systems. First, we propose a multi-scale (field to territory) and multidomain (environmental, economic, social) analytical framework for defining local livestock systems
at stake in our analysis, then we describe its forms of EM (weak vs. strong). Second, we assess both
systems, considering sustainability as a state described by state variables and as a process assessed
according to ecological (e.g. diversity) and socio-economic principles (e.g. economy of scale or
scope, agricultural innovation system type). We analyze their resilience in the face of a changing
environment. Third, we apply our framework to assess a variety of livestock system case studies
(dairy, organic, integrated crop-livestock).
Keywords: agri-food, agro-ecosystem, dairy farm, ecological principle, innovation, profitability,
resilience, security, social
INTRODUCTION
The model of productivist agriculture expanded greatly after the Second World War in
Western countries. It is based on use of large amounts of synthetic inputs and natural resources and
genetic improvement of plants and animals to minimize the effects of limiting production factors and
environmental heterogeneity. It has been accompanied by simplification and standardization of
production modes, decreased diversity of crops and livestock breeds, and the creation of uniform
landscapes. It has often led to geographical separation of cropping systems and livestock systems
(LS) and development of LS with little or no connection to local agricultural land. This model of
agriculture allowed a massive increase in agricultural production due to a sharp increase in
productivity of farm labor and land. In a context of economy of scale and expression of comparative
advantages (e.g. soil fertility, climate, knowledge, labor costs, infrastructure, regulations), it has led
to the specialization of farms and regions within countries (e.g. dairy farms in Brittany for France) or
between countries (e.g. Europe imports South American soybeans as animal feed). The objectives of
increasing the health safety of agricultural production and standardizing it has strengthened the
specialization processes (Horlings and Marsden, 2011; Lamine, 2011).
In the 1980s, emerged awareness of negative effects of productivist agriculture on biodiversity
and ecosystem functioning, climate change, but also on product quality, human health, and depletion
of fossil and water resources, influencing resource scarcity. It was argued that the productivist model
could be developed since negative externalities are not included in production costs. More
specifically, livestock have been blamed for their effects on nutrient surpluses, water pollution,
fossil-energy use, competition for food, and emission of greenhouse gases (GHG) (FAO, 2006;
Janzen 2011).
At the same time, the development of concepts and political concerns about sustainability and
multifunctionality has redefined the objectives assigned to agriculture via agricultural policies. Good
agricultural practices reducing negative impacts of agriculture, development of planned biological
diversity, and conservation of high-value natural systems and areas have become key targets of these
policies. Regarding geographical specialization, the conservation and even the development of LS in
crop-oriented zones is becoming a challenge in Western Europe and the USA. Even though livestock
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can both stress and benefit land, the consensus now seems that agriculture including livestock
production produces a number of ecosystem services that benefit human well-being (MEA, 2005;
Janzen, 2011). Provisioning services, such as supply of animal products, depend on supporting and
regulating services, also called input services (Lamarque et al., 2011), such as soil fertility, soil
moisture, soil stability, pest control, and pollination. Land use and management help produce nonmarket services such as carbon (C) sequestration and recreational landscapes (Zhang et al., 2007; van
Oudenhoven et al., 2012). In turn, agriculture also produces a number of ecosystem disservices such
as GHG (nitrous oxide, methane (CH4)), especially ruminant production (Power, 2010). As
underlined by Gliessman (2006), the problem lies not so much with the animals themselves but
rather with how they are integrated into agroecosystems and food systems.
Two main forms of “ecological modernization” (EM) of crop and livestock systems aim to
respond to sustainability regulations and policies (Horlings and Mardsen, 2011). One, continuing the
productivist model, is “weak” EM of LS (“weak-EMLS”). It aims primarily to reduce major negative
impacts by optimizing input use and, accordingly, energy and matter flows. It is based on increasing
resource-use efficiency by recycling waste (Kuisma et al., 2012) and implementing good agricultural
practices (Ingram, 2008) or technology, such as precision agriculture (Rains et al., 2011). It may also
be based on the use of new technologies such as biofertilizers (Singh et al., 2011) and genetically
modified organisms. It does not call into question the specialization of farms and territories or the
drastic reduction in the number of cultivated species or breeds.
The other form, breaking with the productivist model, corresponds to “strong-EMLS”. In
addition to the principles of resource recycling and flow optimization, it aims to promote diversified
farming systems (Kremen et al., 20012) that enhance biodiversity in agroecosystems at different
organizational levels to provide supporting services (i.e. those necessary for delivery of other
services, such as nutrient cycling), regulating services (e.g. climate regulation), and cultural services
(i.e. non-material benefits such as aesthetic and recreational enjoyment). These services depend on
practices implemented at the plot and farm scales, but also, importantly, at the landscape scale.
Unlike weak-EMLS, it introduces a paradigm shift in the way of thinking about the link between
environment and production.
While weak-EMLS and the associated industrial agriculture model are based mainly on onesize-fits-all technologies and/or agricultural practices rendering agroecosystems (including animals)
artificial, the challenge of strong-EMLS is implementing agricultural practices that take advantage of
complementarities between ecosystem services provided by biodiversity at different organizational
levels. Of course, the two forms of EMLS correspond to two ideals. Both forms can coexist in the
same geographical area; however, weak-EMLS corresponds to the current mainstream in developed
countries. Continuing the productivist model, weak-EMLS can be considered the dominant
sociotechnical regime, i.e. a relatively stable configuration of institutions, techniques, regulations,
standards, production norms, practices, and actor networks. This form is dominant because of its
ability to create technological, organizational, and institutional “lock-in” that ensure its persistence
(Vanloqueren and Baret, 2009). In contrast, strong-EMLS, based on diversified and integrated croplivestock systems, can be considered as production niches, i.e. unstable configurations of formal and
informal networks of actors in which radical innovations emerge (Geels, 2002). Depending upon
biogeographical, economic (agri-food chains), and political contexts, most LS follow either weak- or
strong-EMLS, from grassland-based and mixed crop-livestock systems to confinement systems. The
form of EM followed strongly determines the nature and degree of the connectedness of LS to local
grassland and cropping systems. Each form of EM has strengths and weaknesses at farm and localto-global levels. Accordingly, concerns about their sustainability are a subject of debate.
Sustainability can be defined as the ability to maintain a state at a certain level. For
agriculture, sustainability has been used to express the state in which agricultural yields are
maintained within the capacity of the ecosystem supporting it. In that sense, sustainability means
sustainability of the ecosystem’s function to provide food and other products and services (Kajikawa,
2008). Used in this way, it converges with the WCED’s (1987) definition of sustainable development
as “development that meets the needs of the present without compromising the ability of future
generations to meet their own needs”. Most often, existing approaches to assess sustainability of a
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“snapshot” state of agricultural systems use sustainability indicators covering the three pillars of
sustainable development.
Resilience thinking offers a vision of sustainability as a process for examining how to
maintain system functioning in the face of perturbations (Folke et al., 2002). Persistence is born out
of both resistance to change and maintenance of current states, as well as adaptive renewal leading to
new states when new characteristics of the context (e.g. episodic shocks) redirect the system (Walker
et al., 2004). Resilience is not driven by the identity of the elements of a system, but rather by the
functions those elements provide. Assessing resilience answers two key questions: resilience of what
(which system and which properties) and resilience to what (which perturbations). Most studies of
resilience of agricultural systems assess whether they are able to maintain their essential attributes
and functions within and across levels despite changes in specific components or activities. In
contrast, Jackson et al. (2011) speak about “sustainagility” rather than resilience, focusing on actors’
capacities to adapt to meet their needs in new ways instead of remaining in current trajectories. For
LS, dynamic assessment of resilience is explored less often than assessment of the state of
sustainability, but it is the only one that examines their adaptive capacity and trade-offs among
services (Turner, 2010).
Furthermore, as for every system, analyzing sustainability of a LS requires clearly defining
which components lie inside and which lie outside of its boundaries. For this, a LS can be regarded
as a domain of activity within a farm that uses resources, produces services (e.g. food, fiber,
biodiversity, landscape), and emits waste and pollutants or as a system embedded in larger and more
complex socio-economic systems including farms (e.g. agri-food chains).
The objective of this paper is to provide an integrated analysis of LS in countries where
specialization and intensification of agriculture has led to negative environmental impacts and that
are now seeking forms of EM to reduce these impacts while maintaining or increasing agricultural
production. It focuses on the diversity of ruminant LS. Throughout the paper, strong and weak forms
of EMLS are used as two ends of a continuum. We first define LS at the local level and the two
corresponding forms of EM. For this, we rely on the multi-domain and multi-level (local vs. global)
grid of Darnhoffer et al. (2010). We then assess LS sustainability according to the two forms of EM,
both as a state, using sustainability indicators of LS, and as a process, using ecological and
socioeconomic properties of the “social-ecological” system in which LS are embedded. Finally, we
illustrate the application of our analytical approach to a French dairy livestock case study and a
variety of other LS.
CHARACTERIZING THE DIVERSITY OF LIVESTOCK SYSTEMS
Livestock systems are embedded in multi-level and multi-domain agricultural systems
LS, like agricultural systems in general, can be represented as a complex hierarchical nested
system in which the hierarchical levels are composed of multiple subsystems in different domains:
ecological and biological, economic and social (Darnhoffer et al., 2009; Ewert et al., 2011; ten Napel
et al., 2011). Interactions between these subsystems occur between levels and domains (Fig. 1).
In the bottom agricultural level, interacting farms and farmer networks (the farm community)
are the key subsystems (Fig. 1, bottom line). They shape the agroecosystem, including crops and
animals (left column), which is managed to produce food for society and income for farm families
(middle column). The agroecosystem provides goods and non-market services according to local and
global biophysical characteristics and farmer management practices. As for other economic actors,
farmers’ behavior depends on their social, technical, economic, and political networks and
environment. More precisely, their behavior may depend on the ecological context, agri-food
chain(s), and social and political contexts in which their agricultural activities are embedded. All of
these shape farmers’ individual lifestyles (values, preferences, representation of the farming system
state and functioning, objectives and associated strategies, third column), which direct farmers
towards one of the two forms of EM (weak or strong).
Interactions between subsystems occur between subsystems at the same level (e.g. farm-level),
between subsystems at different levels, and between domains via biophysical and socio-economic
processes (e.g. nutrient flows, management practices, social interaction, economic organization)
(Darnhoffer et al., 2010; Jackson et al., 2010; Ewert et al., 2011). For example, global warming
depends on aggregated effects of land use and management practices and in return, it affects the
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length of growing periods, the crops grown, and vegetation dynamics at the farm level. Interactions
across domains occur at the farm level through agricultural practices that depend on biophysical
conditions from field (soil and climate), farmland, and landscape levels (e.g. bioregulation).
Interactions occur also across time scales at the field level (e.g. cumulative effect of soil management
techniques on soil biota and structure) and at higher levels (e.g. nitrogen cascade).
Figure 1. Livestock systems in their local, regional and national/global contexts: interactions
between hierarchically nested levels (levels n1, 2, 3 in lines) within and between ecological,
economic and social domains (columns) and main features of systems by domain and level of
organization. Gray cells correspond to the local level, containing communities, farms and
agroecosystems (crop, animal, habitat diversity), the level on which this paper focuses. Adapted from
Darnhoffer et al. (2010).
This conceptual representation of agricultural systems enables us to define boundaries of LS
investigated in this paper. We focus our analysis on the local level, where farmers, farmer
communities and, potentially, local market organization determine land use and land cover and
accordingly their diversity and sustainability. This definition or focus is more restrictive than the one
of Cabell and Oelofse (2012), who define agricultural systems as complex entities aiming to
produce, distribute, and consume food, fuel, and fiber, and for which public policies intend to
decrease environmental impacts of management practices (e.g. C sequestration). In our approach, the
levels above the local level are the (external) environment of the LS. Of course the LS is an open
system that exchanges energy, material, and information (resources) with its environment. LS
involved in weak- or strong-EM differ greatly in the nature and intensity of biophysical and socioeconomic processes and interactions with their environment.
Weak-EMLS, in continuity with the productivist model, is primarily underpinned by economic
reasoning still based on the economy of scale, searching for the least expensive inputs from the
world market (e.g. Argentine or Brazilian soybeans for European livestock farms) and marketing raw
agricultural products or even biochemical components (i.e. likely to be traded on the world market).
At the farm level, this led to simplification and standardization of cropping systems, animal breeds
and feeding systems, and strong mechanization. A general decrease in agricultural market prices (and
thus in profit per unit) over the past few decades, especially for animal products, and amortization of
large farm investments has pushed farmers to increase farm sizes. Farms tend to be similar and
compete to survive, including for land. Locally, they interact little and are mainly interconnected
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through regional- to world-scale markets. At the regional-market level, the objective of decreasing
costs of supplying raw materials (e.g. concentrate feed) and collecting products (e.g. milk)
encourages the geographical concentration of the same type of farms and thus the specialization of
farms and regions. Accordingly, farm and regional specialization are strongly linked. LS following
weak-EM are strongly integrated at higher levels via their great dependence on international trade
agreements and commodity prices: “economic sustainability is the foremost concern for the
businesses involved, with progress on other dimensions of sustainability being developed from
positions of economic viability” (Leat et al., 2011).
Strong-EMLS is underpinned by diversification of crop and sometimes animal species within
farms and accordingly within landscapes. This form of agriculture, based on functional
complementarities between species, can also be based on taking advantage of complementarities
between farms at the local level. Hence, livestock farms may buy some of the diversified production
of local crop farms (e.g. protein crops) rather than raw materials from national or world markets (e.g.
soybeans from other continents). Strong-EMLS offers the opportunity to organize an economy of
scope (vs. of scale) at farm and local levels to build a traceable market and take advantage of
production potentials (natural and social capital) of farms at the local level. This diversified local
market may support development of more sovereign farms than weak-EMLS, insofar as they depend
less on the global context for inputs (self-production or local exchange) and product processing and
marketing (Altieri et al., 2011). Being based on agrobiodiversity, strong-EMLS are economically and
environmentally sustainable, but more adaptive management is needed if they are to succeed. This
requires coping with uncertainty (Williams, 2011) and renewing systems of agricultural innovation
(Klerxk et al., 2012).
In conclusion, weak-EMLS is more connected than strong-EMLS to levels of organization that
include farms because networks of people, resources, infrastructure, markets, and institutions that are
dedicated to transporting resources to farms and animal products to retailers are potentially much
larger.
Diversity of livestock systems at the local level
Weak-EMLS is based on continually improving crop and animal performances (quantity and
quality) while reducing undesirable emissions (Fig. 2) and sometimes sensitivity to adverse
environmental conditions (e.g. drought, pests). Its main EM rationale is that of industrial ecology,
aiming to organize interactions between subsystems of the entire production system to improve
resource-use efficiency and waste recycling (Figuière and Metereau, 2012). Technology-based,
precision-livestock farming is one pathway for increasing resource-use efficiency. In dairy
production, for example, radio-frequency identification tags can identify cattle in computercontrolled self-feeders to adjust concentrated feed to individual daily potential milk production,
while milking robots, which can estimate this potential milk production, allow cows to schedule their
own milking (Gebbers and Adamchuk, 2010). Some innovations based on remote sensing for
operational crop monitoring need to be organized at a regional level to process and disseminate
information at low costs. One of the main objectives of weak-EMLS is to improve the “degree of
circularity”, i.e. the proportion of material and energy resources recycled, which directly reflects the
level of resource-use efficiency. An increase in the degree of circularity would be for example to
shift from using manure directly as fertilizer to using biogas slurry as fertilizer. Some innovations
consist of organizing recycling at the landscape level, for example by collecting complementary
types of waste for biogas production.
Strong-EMLS, based on integrating agroecosystem components and increasing
agrobiodiversity to supply multiple ecosystem services to agriculture, thereby reducing the need for
off-farm inputs, represents a paradigm shift from conventional systems (Koohafkan et al., 2011). The
supply of ecosystem services crucially depends on maintaining biodiversity, from soil microbes to
flora and fauna and their interactions (Altieri and Nicolls, 2004, Hooper et al., 2005). For example,
manure applications increase diversity of microbial and invertebrate communities in soils, which in
turn promotes nutrient cycling (Reganold et al., 2010). Practices implemented at the field scale can
impact, by cascading effects, larger ecological scales, such as landscapes, watersheds (nitrates), and
the Earth (GHG emissions) (Galloway et al., 2008; Walker, 2004). The necessary coordination of
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land use within a territory is important to best express biological regulations and, if necessary,
exchange raw materials (e.g. forage, straw, manure).
Across spatial scales, agrobiodiversity can occur within fields (crop mixture), around field
boundary (e.g. hedgerows, grass strips), across neighboring fields (mosaics of crop types and landuse practices), and at the landscape scale (e.g. landscape matrix, woodlots, semi-natural areas).
Across temporal scales, asynchronous tilling, planting, harvesting, cover cropping, and crop rotations
contribute to the maintenance of landscape-scale heterogeneity (Shennan, 2008), while no-till,
permanent grasslands, or landscape infrastructures allow the natural processes of ecological
succession to enhance agrobiodiversity dynamically. Regarding ruminants, diversity can be
promoted raising different breeds of the same species or different species. Mixed-species stocking
offers advantages for animal health (e.g. more effective parasite management) and crops (more
uniform use of plants) and can spread cash flow over more than a single market (Anderson et al.,
2012).
Figure
2. Two forms of ecological modernization of livestock systems (EMLS), shifting from conventional
agriculture to weak- and strong-EMLS, focusing on land use. Weak-EMLS is the current
mainstream. Local and regional landscapes are represented by light gray and dark gray trapezoids,
respectively. The figure at the top left represents a farm composed of one or more activities
symbolized by slightly (weak-EMLS) or greatly (strong-EMLS) overlapping circles representing
(C)rops in blue, (G)rasslands in green, and (A)nimals in orange. Mixture of species: checkered color
circles; exchange of raw material: arrows within light and dark gray trapezoid for weak- and strongEMLS, respectively; disservices and inputs: pink arrows; ecosystem services: green arrows.
In strong-EMLS, “integrated crop-livestock systems” offer opportunities to increase
ecosystem services via spatial and temporal interactions between animals, crops, and grassland (Fig.
2): grazing crop residues; sacrifice grazing (Sanderson et al., 2013). Crops and livestocks can be
integrated at the farm level but also at the local level, through networks to optimize resource
allocation or create local diversified marketing channels adapted to the territory, i.e. to select crops
or animals that are best suited to a given characteristic, such as soil conditions (Moraine et al., 2013).
Synergistically, increasing crop-livestock integration can increase the degree of circularity of
nutrients, for example transitioning from growing cover-crops in cropping systems to provide
6
ecosystem services to grazing or harvesting them to feed animals so as to produce biogas from
manure (Fig. 3) (Martens et al., 2011).
Figure 3. An example of management practices for enhancing recycling (arrows 3 and 4) and
ecosystem services (arrows 1 and 2) while increasing fodder for ruminants (arrows 2 and 4) and
energy (e.g. methanization). Management practices 1, 2 and 4 are specific to strong ecological
modernization of livestock systems.
SUSTAINABILITY OF LIVESTOCK SYSTEMS: ASSESSMENT, PRINCIPLES,
PROCESSES
Sustainability assessment of livestock system state
We use well-identified sustainability indicators for LS (e.g. Lebacq et al., 2012) to assess
those resulting from the two forms of EM (Table 1). For environmental criteria, strong-EMLS by
definition performed better for biodiversity, soil quality, and C sequestration, due mainly to
characteristics such as greater proportion of grasslands on the farm and/or crop rotation with
grasslands. For nitrate losses, indoor cow feeding (weak-EMLS), where waste can be wellcontrolled, can perform better than grazing (strong-EMLS) in some situations (e.g. sandy soil
coupled with rainy weather and low temperatures). For CH4 emissions, detailed description of
practices is needed to compare forms of EM. For example, feeding cows with silage maize and
concentrated feeds tends to have lower CH4 emissions than grass-based feeding systems, especially if
linseed is added (Doreau et al., 2011).
Table 1 Qualitative assessment of sustainability of livestock systems when shifting from
conventional to weak- and strong-ecological modernization (EMLS) over the current context
(adapted from Lebacq et al., 2013)
Domain
Criteria
Weak-EMLS
Strong-EMLS
=/++
Environment Biodiversity
Economy
Social
GHG (chemical inputs,
energy consumption)
Soil quality
Methane
C sequestration
Profitability
Autonomy
Risk
Transmissibility
Internal (working condition;
quality of life)
External (multi-functionality
of agriculture)
Quality of products
Sovereignty
+
++
=/+
=
+
- (market)
+ (dependency
+/-
+
+
+
+
+ (local governance)
- (due to diversity)
+/=
+/-
=/+
?
-
+
?
+
+; =;-: improving, maintaining or deteriorating the sustainability criterion considered
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Both forms of EM can be economically profitable. Even though strong-EMLS may have lower
outputs, its inputs are also lower (e.g. fewer antibiotics and fertilizers), so that profit per output unit
can increase (Lebacq et al., 2012). On the other hand, autonomy (for external financing or inputs) is
by definition high for strong-EMLS systems. Risk of income variability may be lower for strongEMLS systems because they are based on an economy of scope (i.e. diversified production).
However, for weak-EMLS systems, this depends on their connectivity to the agri-food chain. Farm
transmissibility is also generally easier for weak-EMLS systems due to smaller farm size, but capital
for machinery can be similar.
For social criteria, working conditions and quality of life may differ, but each form of EM may
be satisfactory because the assessment depends greatly on farmer preferences and/or lifestyles
(Vanclay, 2004). However, as underlined by Tripp (2008), agroecological management is much
more complex and accordingly requires advanced and continuous learning because management
practices are context-dependent. External criteria are related to the multifunctionality of agriculture,
which is undoubtedly greater for strong-EMLS. Product quality is not simple to compare from a
human health point of view. On one hand, it can be better controlled in specialized and simplified
food-chain production (weak-EMLS), but in some cases, catastrophes can occur due to strong links
between components of the agri-food chain (e.g. prion crisis). Strong-EMLS, being more
autonomous, has lower risk of such catastrophes. Strong-EMLS performs better from the
organoleptic point of view, especially if animals are fed from natural grasslands (e.g. Coulon et al.
(2004) for cheeses). For technology, strong-EMLS has higher sovereignty. For energy, however,
both forms of EM can have slightly negative or even positive energetic balance due to internal
energy production (e.g. biogas production or solar-energy capture).
Resilience of livestock systems: a social-ecological point of view
To focus on LS sustainability as a process, we rely on the comprehensive review of Biggs et
al. (2012), who present three key properties of (agro)ecological systems to manage and four
properties of the governance system required to ensure resilience of ecosystem services. Cabell and
Oelofse (2012) propose a similar approach, while Schouten et al. (2012) propose a resilience-based
framework to assess public policy regarding rural social- and economic-ecological systems. All of
these authors highlight the challenge of developing adapted and fully consistent social-ecological
systems, which we adapt for LS (Fig. 4). In these studies, as for Darnhoffer et al. (2010), the main
issues are the agroecosystem properties to have to provide ecosystem services and the governance
structures and management strategies of agroecosystems. We present below some of these key
ecological and socioeconomic properties and how they are taken into account in the two forms of
EM.
Figure 4. The livestock system as a social-ecological system. Farmers and their communities are at
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the interface of ecological and socioeconomic systems; by their practices they generate services, and
emissions, and their practices are shaped by the socioeconomic system and climate and global
changes. Key components are plants, animals, and the landscape matrix for ecological systems and
retailers, consumers, and politics for socioeconomic systems. Italics indicate the main properties of
these systems for enhancing development and resilience of ecosystem services. Black arrows
indicate input ecosystem services, while white arrows indicate other ecosystem services. Adapted
from Biggs et al. (2012) and Schouten et al. (2012).
Properties of the (agro)ecological system to be managed
The agroecological system is composed mainly of planned diversity (domestic plants and
animals), the landscape matrix, and associated biological diversity and infrastructures (e.g. for water
retention, anaerobic digestion) that determine nutrient cycling and agricultural production (Fig. 4,
left side). Based on the five ecological principles proposed by Altieri (1999) for developing
agroecological cropping systems (i.e. based on ecosystem services), Dumont et al. (2012) developed
equivalent ones for LS:
Decreasing the inputs needed for production
Decreasing pollution by optimizing the metabolic functioning (nutrient cycling) of farming
systems
Adopting livestock management practices that aim to improve animal (and human) health
Increasing biodiversity within LS to strengthen their resilience
Preserving biodiversity by adapting cropping and livestock management practices
The two first principles aim to increase input efficiency through relevant management, but
they depend on the form of EM. For weak-EMLS, the first principle is related essentially to genetic
advances, while the second one depends mainly on technology-based increases in input-use
efficiency and waste recycling. For example, ammonia emissions can be reduced by storing manure
in sealed tanks and then covering it after application to fields. For both EM forms, plants or
industrial by-products with high water contents can be promoted for feeding animals if the places of
production and use are not too far. Producing energy from waste and by-products can be done in
both forms of EM. The third principle is taken into account in both types of EM but according to two
different rationales. Strong-EMLS aims to render animals more resilient and less sensitive to pests to
a greater extent than weak-EMLS. Productive and health viewpoints are closely interconnected and
considered jointly to explain multi-factorial diseases in terms of risk factors. Improving animal
health reduces emissions of pharmaceutical residues into the environment. To achieve a human-diet
profile balanced in fatty acids, weak-EMLS may add linseed to the diets of ruminants fed maize and
soybean (Glasser et al., 2008), whereas strong-EMLS may feed ruminants by grazing (Dewhust et
al., 2006). The last two principles are core principles of strong-EMLS. They are explicitly related to
agronomic practices or landscape-management strategies that intentionally incorporate functional
biodiversity at multiple organizational levels and temporal scales of crop, grassland, and livestock
diversity (Ostergard et al., 2010; Kremen et al., 2012; Kremen and Miles, 2012). By considering
agrobiodiversity as both a resource and an output of LS, the last three principles put food and
agroecosystem integrity at the core of EMLS (Dumont et al., 2012). Furthermore, they provide dualbenefit solutions by stimulating natural processes to reduce inputs and increase income.
Properties of social systems that impact (agro)ecological systems directly or indirectly
We selected a set of key principles for governance of social-economic systems and
management of (agro)ecological systems that determine the local form of LS. Here, governance
means the social and political processes that shape the management of agroecosystems and farms.
Applied to agricultural systems, some of these principles are related to the economy of agri-food
chains and others to agricultural innovation systems for facilitating their adaptation in a changing
world (Fig. 4, right side). We examine below how some of these principles sustain only strongEMLS, while others support development of both forms of EM, but according to two different
rationales.
Farm profitability is needed for modern agriculture to persist, and the need for security
depends upon farmers’ adversity to risk (Sander and van Ittersum, 2007). The economy of scale and
9
labor productivity remain strong driving factors for increasing farm profitability in weak-EMLS. LS
involved in weak-EM are usually strongly coupled to upstream and downstream segments of agrifood chains, for which profitability depends on farm input and output markets. Due to their high
specialization, they are sensitive to price volatility. Thus, reducing the number of “tightly coupled”
systems, in which accidents inevitably become catastrophes, is required to prevent risks
(Kirschenmann, 2010). In contrast, LS involved in strong-EM are less sensitive to exogenous
influences due to their high autonomy. They can spread economic and production risks over several
different enterprises, thereby taking advantage of a variety of agricultural markets (Hendrickson,
2008; Darnhoffer et al., 2010). This development of economy of scale may be amplified through
high cooperation between individuals at the local level (e.g. by sharing expensive equipment such as
direct seeding machines). In addition, local farmers’ markets and food cooperatives can enhance
these properties by developing the exchange of protein and forage products between crop and
livestock farms (Hendrickson et al., 2008).
In weak-EM, knowledge production and dissemination emphasize spreading one-size-fits-all
technologies such as precision agriculture. Stakeholders are organized into large networks,
institutions, and lobbies that defend the merits of weak-EM and claim the need to concentrate money
and effort into large companies to develop technologies (pharmaceuticals, genetics) that consume
human and monetary resources. Farms are usually managed through a planned process in which
necessary knowledge about the specific production situation is usually low or acquired through
automatic and dedicated technologies (e.g. chlorophyll fluorescence sensors). In these systems,
innovation is a top-down process in which public and private research and development provide
farmers with technologies (inputs and materials) to be used in a standardized manner.
In contrast, managers following strong-EM have to cope with uncertainty about biological and
ecological processes that generate ecosystem services and partial control (observational uncertainty)
over the effects of practices on these processes, especially input services. Furthermore, most research
about ecosystem services stresses that agricultural practices aiming to increase their supply should be
site-specific. Farmers have to consider the local expression of the processes involved, for example
plant-animal interactions during grazing (Hodgson, 1985), soil-animal interactions to manage
parasites during grazing (Dumont et al., 2012), and plant-soil interactions for nutrients (Eviner, 2008;
Tomich et al., 2010). Most often, farmers incorporate traditional cultivation techniques with modern
knowledge (Doré et al., 2011). They practice strong adaptive management, which consists of active
monitoring of and feedback from the effects and outcomes of decisions. In this way, farmers learn
that consequential actions are always necessarily specific (Jiggins and Röling, 2000). Furthermore,
farmers are organized into grassroots networks and institutions for reflexive analysis and sharing of
learning. The on-farm innovation implemented in strong-EMLS is usually collaborative (sharing
information through field visits). It is based on developing coordination between actors to coproduce knowledge and technology, possibly supported by participatory and interdisciplinary
research (Knickel et al., 2009). This so called “agricultural innovation system” supports social
involvement i.e. engaging in social exchange.
From ecological and social properties to the resilience of sustainable livestock systems
Walker et al. (2004) define resilience of a social-ecological system as its “capacity to absorb
disturbance, undergo change and retain the same essential functions, structure, identity and
feedbacks”. Disturbance can result from slow processes (e.g. climate change, change in consumer
behavior) or fast changes (e.g. price volatility, strong drought, animal health crises, certain
regulations and norms).
For slow changes in the environment of LS, incremental adaptations for both forms of EMLS
may be sufficient to maintain farm profitability. However, beyond a certain threshold of disturbance,
a specialized farm based on weak-EM may be endangered because incremental technological
innovations may no longer maintain profitability or meet environmental standards (e.g. Belgian
blue cattle system in Schiere et al., 2012). In contrast, strong-EMLS may resist strong perturbations
such as recurrent droughts due to complementarities between diversified organisms (e.g. equilibrium
among species with differing drought sensitivities in crop and grassland mixtures), increased
biophysical capacities (e.g. soil water-holding capacity in conservation agriculture), or breeding of
native livestock breeds. Less diversified farms need to reduce their sensitivity to profit margins,
10
especially when no government subsidies exist to compensate for losses. Ways to do so include
irrigating forage crops (if possible) or buying insurance to anticipate abnormal weather years. In the
same vein LS involved in weak-EM can decrease their sensitivity to price volatility of inputs (e.g.
soybean) and outputs (e.g. meat) by signing contracts with pre-defined prices with companies for
supplying and with retailers for selling.
In general, strengths and weaknesses of the two forms of EM will depend on trade-offs
between economic and social/policy drivers at national or global levels (n3 in Fig. 1). At these levels,
the more negative externalities are addressed with norms, regulations, or taxes and the more scarce
resources become, the more the context will be favorable for strong-EM. At the local level, synergies
between farmers and consumers that promote local markets, possibly supported by local or national
policies via subsidies or advertising, can favor the emergence of niches that are based on strong-EM
principles (Geels, 2005).
Adapting LS to improve their resilience can lead to managing trade-offs and synergies among
ecosystem services. For example, assessments of French LS (based mainly on weak-EM) show,
especially for dairy farms, a reduction in GHG emissions of 15-25% from 1990-2010, while milk
production per cow increased (Dollé et al., 2013). However, there was great variability among
systems (up to 30%), meaning that many livestock farms can achieve greater reductions. Thus,
synergies requiring greater agrobiodiversity may need to be sought to decrease impacts. To reduce
trade-offs between animal production and GHG emissions, relevant management practices must also
provide an economic benefit for farmers (Sanderson et al., 2013). However, diversifying land use by
increasing bioenergy production may create trade-offs in land use at local and regional levels
(Sanderson et al., 2013).
Adaptations of LS also raise the issue of their adaptive capacities linked to their path
dependency, i.e. how their past development largely determines their future path (Cabell and
Oelofse, 2012). Farms involved in weak-EMLS may have great difficulty adopting the principles that
sustain strong-EMLS due to technical, organizational and “lock-ins”. For example, increasing dairyfarm profitability by increasing farm size and mechanization (e.g. milking robots) can decrease cow
grazing, and thus benefits associated with grazed grass.
ANALYSIS OF EMERGENT AND CONVENTIONAL LIVESTOCK SYSTEMS
Comparison of conventional dairy farms to those involved in sustainable farm networks in
Brittany
Most farming systems in Brittany are dairy farms (17,000 out of 37,000 farms). Since the
1950s, concentration of livestock has induced strong economic and social development, but also
public concern about human health hazards, food security, and environmental problems (AcostaAlba et al., 2012). Governments have set targets for decreasing environmental impacts based on
scientific recommendations and conclusions at national (e.g. the French “Grenelle Environnement”),
European (e.g. EU Water Framework Directive), and global scales (e.g. Kyoto Protocol); so, there
are specific regulations and high pressure to adapt current dairy systems into more sustainable ones.
Two main pathways corresponding to weak and strong-EMLS processes are observed.
The main and more developed path, supported by the dominant agricultural political
movement, encourages farmers to optimize their systems by providing relevant tools such as
planning and monitoring to manage grazing and farm-gate nutrient budgets to manage nitrogen. In
France, an alternative option is supported by farm networks called CIVAM that promote sustainable
agriculture by implementing innovative ways to develop agriculture and rural activities as a part of
sustainable territorial development. They promote and develop strategies to enhance the technical
and decisional sovereignty of farmers and exchanges with local communities. They attempt to
answer local questions from a global perspective about the functions and place of agriculture in
society (RAD, 2013). Farmers in these networks are more familiar with self-organization, reflexive
analysis, and sharing experiences than most farmers involved in conventional dairy systems. Based
on their personal experiences and histories, farmers can identify their sustainability priorities so as to
improve their environment, solidarity, product quality, economic efficiency, and quality of life. Each
farmer has a personal vision of the progress that he or she can accomplish. The agricultural
innovation system that sustains these farmer networks is based fully upon the social principles
mentioned above. The goal of farmer networks is to move forward together, exchanging experiences
11
and viewpoints. For this, farmer networks organize local exchanges and training during economic
and technical field trips. As for economic principles, farmers aim to be globally self-sufficient and
locally interdependent. However, since farm size is small, most CIVAM farmers specialize in dairy
production. In addition to these principles, they contract for specifications, including 75% of forage
resources coming from grasslands, < 50 kg/ha of synthetic N fertilizer applied to grasslands, no bare
soil in winter, rotation length > 3 years, only a small area in silage maize, and no plastic film used to
grow maize. However, some ecosystem services requiring specific crop spatial arrangements cannot
be implemented because farmers involved in these farm networks are spreading in the landscape.
Table 2. Comparison of conventional dairy farms and “sustainable dary farm network” in Brittany
Domain
Criteria
Civam
Conventional
Structure
Agricultural land (ha)
64
71
Animal unit (dairy cows)
75 (49)
96 (48)
Land use and Stocking rate (number of animal 1.28
1.61
management
units per ha)
Land use in ha
45/8/12
40/15/15
(grassland/maize/crops)
Maize for silage (%SFP)
12
37
Hedge (ml/ha)
>150 linear No obligation
meter/ha
Economy
Inputs (euros/ha)
100
240
Milk / cow (kg)
5749
6636
Food cost (euros/1000l)
78
120
Mechanization cost (euros/ha)
400
500
Farm incomes (euros)
134718
157309
Gross operating profit (euros)
53365
42291
Environment
Pesticide treatment frequency for
0.83-1.24
1.66
maize **
GHG emissions (CH4, CO2, N2O 1100
1100
(kg eq CO2/1000l) *
Net GHG emissions kg eq 874
1018
CO2/1000l)
*Less CH4 emissions for conventional farms; More C sequestered for Civam farms due to
grasslands and hedges
** number of applications with standard approved dosages
Comparing land use and management and criteria for economic and environmental
sustainability for conventional farms in weak-EM and CIVAM farms in strong-EM, crops and
grasslands are more diversified in CIVAM farms (Table 2). Milk production per cow for CIVAM
farms is lower, but economic results are higher due to lower costs of mechanization and chemical
inputs; however, land required per cow, and even more so per kg of milk produced, is higher. Clear
differences are found for pesticide applications number, but differences in GHG emissions are small.
Clear advantages for environment appear for CIVAM farms only when assuming C sequestration by
their large areas of semi-permanent grasslands (Le Rohellec and Mouchet, 2008; Le Rohellec et al.,
2011).
Recognized types of sustainable livestock systems
Organic agriculture: the example of beef farms
Organic farming, which excludes the use of synthetic fertilizers, pesticides (herbicides,
insecticides, and fungicides), livestock antibiotics, food additives, and genetically modified
organisms, is considered as one form of sustainable agriculture (Francis, 2009). Some ecological
principles on which organic farming is based correspond to those we defined above for strong-EMLS
(e.g. crop diversity, soil management, animal health). Moreover, many organic farmers are organized
in networks for sharing information (Francis, 2009). In a recent review, Gomiero et al. (2013) found
12
that energy consumption and GHG emissions were lowest for organic vs. conventional dairy farms in
Europe, regardless of the functional unit of measure (per ha or per l of milk). These authors pointed
out that multicriteria analysis based on key indicators is essential, because some systems may have
an advantage for one criterion (e.g. CH4 emissions) but a disadvantage for another (e.g.
eutrophication). However, being based on contractual obligations for inputs but not results, organic
farming does not explore all the possibilities offered by agroecological principles. To bridge the
productivity gap between organic and conventional agricultures, experts involved in organic
agriculture recently suggested promoting “ecofunctional intensification”, defined as stimulating
more knowledge and achieving a high degree of organization per land unit (Niggli et al., 2008), both
of which are similar to the principles described above for strong-EM.
Comparison of productive, environmental, and economic performances of organic vs.
conventional specialized suckler cattle farms in France showed the former to have lower meat
production (by -18 to -37% per ha) but also lower GHG emissions per ha (and per kg of animal
liveweight depending on system intensification) when taking C sequestration into account (Veysset
et al., 2011). Operational costs of organic beef farms decreased due to a decrease in inputs (-9 to 52%), while farm income decreased an average of approximately 20% (Veysset et al., 2011). In
these, LS based on natural permanent grasslands, combining improved grass species with biological
fertilizers on a small portion of the grazing area, could be one mechanism for turning cows out to
pasture earlier, thereby reducing the length of the indoor feeding period.
In the USA, alternative beef-production systems (e.g. organic, grass-fed) offer consumers
and producers alternatives to conventional beef production, but their production costs are usually
higher (Mathews and Johnson, 2013). Beef produced from these systems has different properties
(e.g. resource and other input use, GHG emissions, animal welfare, processing and food
safety/security concerns) that may appeal to various consumers. In their analysis, Mathews and
Johnson (2013) emphasized that the trade-offs associated with each system can influence their
attractiveness to consumers. For example, grass-based systems can produce a better fatty-acid profile
for meat and accordingly human health properties, while incentives for LS in marginal lands can
increase GHG emissions.
What about integrated crop-livestock systems?
The number of mixed crop-livestock farming systems, in which some of the crops are sold,
has greatly declined in Europe and North America since the Second World War. However,
integration of crops and livestock at the farm level, as already mentioned, is expected to provide
many advantages (Wilkins, 2008). Currently, mixed-farming systems are concentrated in less
favorable areas where soil heterogeneity offers opportunities to grow crops for forage and for sale
(Ryschawy et al., 2012). In this context, the environmental and economic performances of such
systems are usually greater than those of specialized farms. However, in specialized crop or livestock
regions, many authors claim that, given the economic context, area-wide integration can be more
successful than only farm-level integration (Entz and Thiessen-Martens, 2009). Area-wide
integration of crops and livestock can be an option to deal with a range of environmental and
economic issues (e.g. nutrient surplus, water shortage, low forage self-sufficiency of livestock farms)
or challenges (e.g. decreasing chemical inputs of crop farms). It is based on exchanges of forage,
grain, by-products, and manure between specialized crop and livestock farms and can be
implemented through weak- or strong-EMLS. For the former form, it may consist of common
facilities for producing energy from crop residues as well as manure, straw, or grain exchanges. It
requires the proximity of crop and livestock operations unless products are dehydrated (Bell and
Moore, 2012). For the latter form, it can occur by introducing legumes in rotations of specialized
cash crop farms to be sold as hay or dehydrated product. This increases fertility and biological
regulations, decreasing chemical inputs to crop farms while providing fodder for livestock farms
(Sanderson et al., 2013). More broadly, crop and livestock integration at different spatial and
temporal scales can constitute an ultimate form of strong-EMLS when designed to enhance a large
set of ecosystem services (Lovell et al., 2010; Francis and Porter, 2011; Moraine et al., 2013).
CONCLUDING REMARKS
Focusing on LS at the local level and their land-use dimensions, we described and assessed
13
sustainability of two ideal forms of EM of these systems: weak- and strong-EM, representing two
extremes of a continuum. They are based partly upon similar ecological and socioeconomic
principles but are implemented differently. For weak-EMLS, reducing negative impacts of LS on the
environment is achieved by increasing input-use efficiency and waste recycling, while for strongEMLS, in addition to these practices, it comes from promoting ecosystem services based on
biodiversity. Reducing climate and economic risks occurs via insurance and contract for weakEMLS but via diversified farming and agrobiodiversity for strong-EMLS. Organic agriculture can
contribute to strong-EMLS; however, since the former is based on contractual obligations for inputs
but not results, it can fail to fully exploit ecological and socioeconomic principles that ground strongEMLS. Crop and livestock integration can constitute an ultimate form of strong-EMLS when
designed to enhance a large set of ecosystems and based on area-wide integration. In developed
countries, weak-EMLS is the dominant sociotechnical regime, and organic and integrated croplivestock farms are at the niche state. Strong-EMLS is only now emerging.
In agreement with Baccon et al. (2012), we illustrated that development of EMLS forms
depends on institutional contexts. Strong-EMLS may be favored by institutional environments that
specifically promote diversified farming systems, limit synthetic inputs and natural resources use,
and enhance the social benefits of sustainable agriculture. In contrast, weak-EMLS is driven mostly
by the economic dimension of sustainability. More pronounced forms of weak-EMLS have strong
path-dependency in the face of change, which may limit their ability to deal with radically new
environmental norms and market conditions (Sutherland et al., 2012).
Assessing sustainability of the many existing and developing LS in different geographical
areas within a country can help politicians adapt their policies to meet their objectives. For example,
in Europe, it can help in choosing a balance between direct payments to farmers for conditional
observance of environmentally friendly practices and return payments that compensate additional
costs and income losses when implementing agroecological practices that go beyond standard good
farming practices. It can also help evaluate the advantages and disadvantages of conservation
easements (i.e. for long-term ecosystem services) or market credits (e.g. for C sequestration).
Acknowledgements
This paper has benefited of discussions that occurred in two projects: O2LA (Locally Adapted
Organisms and Organizations; ANR-09-STRA-08) funded by the French Agency for Research and
CANTOGETHER (Crops and ANimals TOGETHER) funded by the European Commission’s
Seventh Framework Programme (Food, Agriculture and Fisheries, Biotechnology).
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