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Journal of Cleaner Production 227 (2019) 1054e1067

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Review

Rebound effects in agricultural land and soil management: Review andanalytical framework

Carsten Paul a, *, Anja-Kristina Techen a, James Scott Robinson a, Katharina Helming a, b

a Leibniz Centre for Agricultural Landscape Research (ZALF), Eberswalder Str. 84, 15374, Muencheberg, Germanyb Faculty of Landscape Management and Nature Conservation, University for Sustainable Development (HNEE), Schickler Straße 5, 16225, Eberswalde,Germany

a r t i c l e i n f o

Article history:Received 18 October 2018Received in revised form8 March 2019Accepted 10 April 2019Available online 17 April 2019

Keywords:AgricultureEfficiencyJevons paradoxImpact assessmentLand sparingIrrigation

* Corresponding author.E-mail addresses: Carsten.Paul@zalf.de (C. Paul), A

https://doi.org/10.1016/j.jclepro.2019.04.1150959-6526/© 2019 The Authors. Published by Elsevie

a b s t r a c t

Increasing the efficiency of production is the basis for decoupling economic growth from resourceconsumption. In agriculture, more efficient use of natural resources is at the heart of sustainableintensification. However, technical improvements do not directly translate into resource savings becauseproducers and consumers adapt their behaviour to such improvements, often resulting in a reboundeffect, where part or all of the potential resource savings are offset. In extreme cases, increases in effi-ciency may even result in higher, instead of lower, resource consumption (the Jevons paradox).

Rebound effects are particularly complex in agricultural land and soil management, where multipleresources are used simultaneously and efficiency gains aim to lower the need for farmland, water, energy,nutrients, pesticides, and greenhouse gas emissions. In this context, quantification of rebound effects is aprerequisite for generating realistic scenarios of global food provision and for advancing the debate onland sparing versus land sharing. However, studies that provide an overview of rebound effects related tothe resources used in agriculture or guidelines for assessing potential rebound effects from future in-novations are lacking. This paper contributes to closing this gap by reviewing the current state ofknowledge and developing a framework for a structured appraisal of rebound effects. As a test case, theproposed framework is applied to emerging technologies and practices in agricultural soil managementin Germany.

The literature review revealed substantial evidence of rebound effects or even Jevons’ paradox withregard to efficiency increases in land productivity and irrigation water use. By contrast, there were fewstudies addressing rebound effects from efficiency increases in fertilizer use, pesticide application,agricultural energy use, and greenhouse gas emissions. While rebound effects are by definition caused bybehavioural adaptations of humans, in agriculture also natural adaptations occur, such as resistance ofpests to certain pesticides. Future studies should consider extending the definition of rebound effects tosuch natural adaptations. The test case revealed the potential for direct and indirect economic reboundeffects of a number of emerging technologies and practices, such as improved irrigation technologies,which increase water productivity and may thereby contribute to increases in irrigated areas and totalwater use.

The results of this study indicated that rebound effects must be assessed to achieve realistic estimatesof resource savings from efficiency improvements and to enable informed policy choices. The frameworkdeveloped in this paper is the first to facilitate such assessments.© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license

(http://creativecommons.org/licenses/by/4.0/).

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10552. Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1056

2.1. Rebound effects and Jevons’ paradox . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10562.2. Literature research & framework development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1056

nja.Techen@zalf.de (A.-K. Techen), James.S.Robinson9@gmail.com (J.S. Robinson), Helming@zalf.de (K. Helming).

r Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

C. Paul et al. / Journal of Cleaner Production 227 (2019) 1054e1067 1055

2.3. Application of the framework for the assessment of emerging technologies and practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10573. Results & discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1057

3.1. Rebound effect framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10573.1.1. Direct rebound effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10573.1.2. Indirect rebound effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10583.1.3. Economy-wide rebound effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1058

3.2. Rebound effects in agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10583.2.1. Resource: land . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10603.2.2. Resource: water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10613.2.3. Resource: nutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10623.2.4. Resource: pesticides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10623.2.5. Resource: energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10633.2.6. Resource: greenhouse gas emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1063

4. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1065Declarations of interests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1065Funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1065Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1065References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1065

1. Introduction

Improvements in resource-use efficiency are central to decou-pling economic growth from natural resource consumption. Foragriculture, this decoupling is essential, given that global driverssuch as dietary shifts toward a higher share of animal based pro-teins and population growth indicate an increasing demand foragricultural goods over the next three decades (Alexandratos andBruinsma, 2012; Tilman et al., 2011; Valin et al., 2014). Expansionof global agricultural area or intensification of production throughmuch higher use of inputs is unsuited to balance this increase, sincethe agricultural sector already significantly contributes to theexceeding of planetary boundaries for biodiversity loss andbiogeochemical flows of nitrogen and phosphorus (Steffen et al.,2015). However, increasing the resource-use efficiency in agricul-ture could create a win-win situation by enhancing economicperformance and alleviating pressures on the environment (O'Brienet al., 2014).

Efficiency targets have therefore been formulated across globaland national policy levels. At the global level, target 2 of SustainableDevelopment Goal 12 “Sustainable Consumption and Production”seeks to achieve sustainable management and efficient use ofnatural resources by 2030 (UN General Assembly, 2015). At theEuropean level, the Roadmap to a Resource Efficient Europe sets a20% reduction of resource inputs within the food chain as a mile-stone for 2020 (European Commission, 2011), while in the EU RuralDevelopment Act, increasing the efficiency of agricultural produc-tion is a priority, and water use efficiency, energy efficiency andgreenhouse gas emissions are explicitly referred to (EuropeanUnion, 2013a; Spicka, 2015). One example at the national level isthe German Policy Strategy on Bioeconomy, which seeks to achievesustainable intensification of agricultural production by increasingproductivity while protecting natural resources and minimisinggreenhouse gas emissions (German Federal Ministry of Food andAgriculture, 2014).

While efficiency increases are often considered a silver bullet,associated resource savings usually turn out to be smaller thanwhat the improvements in technical efficiency under ceteris paribusassumptions would suggest (Kolstad et al., 2014). Increasing theefficiency of a production process affects the producer-consumersystem and can trigger adaptive behaviour that offsets part or allof the initial resource savings. In extreme cases, these so-calledrebound effects can even result in a net increase in resource

consumption. “Rebound effects” is a collective term that encom-passes several economic as well as social-psychological adaptationmechanisms which occur in the wake of increases in resource-useefficiency and which affect the total consumption of that resource.It is important to note that only behavioural changes caused byefficiency improvement are considered rebound effects, whereasother changes, such as changes due to general economic growth,may also increase resource use but are not rebound effects.

The concept of rebound effects was originally developed in thecontext of energy efficiency (Greening et al., 2000; Jevons, 1865)but has since been expanded to resource-use efficiency in general(Lambin and Meyfroidt, 2011; Maxwell et al., 2011; Pfeiffer and Lin,2014). The first description of rebound effects dates back to themid-1800s and the British economist W.S. Jevons, who postulatedthat higher fuel efficiencies would always result in higher, insteadof lower resource exploitation (Alcott, 2005; Jevons, 1865). Thistheory was reiterated in the 1980s by economists Khazzoom andBrookes and termed the KhazzoomeBrookes postulate (Saunders,1992). While current research indicates that in most cases,rebound effects are not large enough to result in a net increase inresource use (Gillingham et al., 2013, 2016), even partial offsettingof savings has implications for resource-use planning and theassessment of potential benefits from innovations, such as noveltechnologies and practices in agricultural management.

Ex-ante impact assessment is a means to analyse positive andnegative as well as intended and unintended impacts of decisionoptions, such as implementing more efficient technologies andpractices, against targeted benchmarks (Helming et al., 2011). Animpressive wealth of tools and methods for ex-ante impactassessment has been developed over the last decade, particularly inthe field of agriculture (Podhora et al., 2013). However, despite theincreasing sophistication of such tools for agricultural practice (deOlde et al., 2016) and policy (Reidsma et al., 2018), considerationof rebound effects is still rare due to a lack of information on causalrelationships determining their occurrence and size. By describingand assessing these relationships, this paper facilitates theconsideration of rebound effects in future assessments, which willin turn contribute to developing sustainability policies that pro-mote technology development while mitigating its adverse effects.

This paper focuses on rebound effects in agricultural land andsoil management. This term denotes arable and grassland man-agement but excludes livestock management. A distinction is madebetween land and soil, to account for two different concepts in the

C. Paul et al. / Journal of Cleaner Production 227 (2019) 1054e10671056

debate on resource-use efficiency. Land represents the terrestrialsolid part of the earth that is not permanently under water. Moreefficient land use could reduce the expansion of agricultural areasinto natural habitats or even spare land for conservation andbiodiversity purposes (Lamb et al., 2016). Understanding reboundeffects in land management is therefore central to advancing thedebate on land sparing vs. land sharing (Mertz and Mertens, 2017;Phalan et al., 2011), where the latter represents a concept ofmultifunctional land use that is less intense but supports natureconservation purposes alongside agricultural production(Wiggering et al., 2006).

Soil, on the other hand, is the uppermost zone of the land sur-face, inwhichmineral particles, organicmatter, water, air and livingorganisms interact. In soils, biogeochemical turnover processesenable biomass growth (Soil Survey Staff, 2014), and it is the

Rebound Effect½%� ¼ Resource Savings ceteris paribus � Resource Savings actual

Resource Savings ceteris paribus

!*100 (1)

optimisation of these natural processes that is targeted byefficiency-improving innovations under the paradigms of sustain-able intensification (Garnett et al., 2013) and ecological intensifi-cation (Tittonell, 2014). Rebound effects influence how soilmanagement alternatives or novel crop varieties may reduce en-ergy consumption and result in reduced fertilizer and pesticideapplication or lower greenhouse gas emissions.With regard to bothland and soil management, rebound effects are highly relevant forevaluating the role that yield improvements may play in satisfyinga growing global demand for agricultural commodities. Althoughthe number of publications analysing rebound effects in agricul-tural land and soil management is growing, most of them arelimited to single resources and specific rebound mechanisms. Toour knowledge, there are no studies yet providing an overview ofrebound effects across the main resources used in agriculture orproviding guidelines for assessing potential rebound effects fromagricultural innovations. This paper contributes to closing this gapby:

� Reviewing the state of knowledge on rebound effects connectedto efficiency improvements in the use of the main resources ofagricultural land and soil management.

� Developing a framework that facilitates the assessment ofrebound effects from agricultural management innovations.

� Testing the framework's application by assessing emerginginnovations in agricultural land and soil management forpotential economic rebound effects.

In the following section, we describe how the literature reviewwas conducted, how the framework for assessing rebound effectswas created and provide information on the test case. In section 3,we present the framework and discuss the findings from theliterature review and from the assessment of our test case. In sec-tion 4, we draw final conclusions.

2. Materials and methods

2.1. Rebound effects and Jevons’ paradox

Rebound effects occur where producers and/or consumersadapt their behaviour to efficiency improvements in a way thatoffsets part or all of the resource savings achieved by theimprovement. They are defined as the share of resource savingsthat does not materialize because of these adaptations. Reboundeffects can be calculated from the difference between resourcesavings due to technical improvements that could be achieved in aceteris paribus situation and the actual observed resource savings(Equation (1)). Where adaptive behaviour results in a net increasein resource use, Resource Savings actual becomes negative, and therebound effect is greater than 100%, which is the definition ofJevons’ paradox or backfire.

Resource Savings ceteris paribus: Difference in resource use calcu-lated from the difference between efficiencies before and afterthe innovation, assuming no change in behaviour by producersand consumers.Resource Savings actual: Observed difference in resource usebefore and after the innovation.

Distinguishing between rebound effects and changes inresource use caused by other factors, such as increases in GDP orchanges in societal preferences is challenging (de Haan et al., 2015;Gillingham et al., 2016). Especially in the analysis of long time seriesor complex policy measures, quantifying rebound effects requiresan assessment of the various rebound mechanisms discussed insection 3.1 of this article, and assumptions on how resource usewould have developed in the absence of efficiency improvements.

Because the concept of rebound effects is resource specific, ef-ficiency increases in the use of one resource that result in increasedconsumption of another resource are not considered rebound ef-fects.While these spill-over effects are highly relevant for efficiencyimprovements in agriculture, their analysis is beyond the scope ofthis paper.

2.2. Literature research & framework development

The main physical resources used in agricultural land and soilmanagement are land and soil, water, nutrients, pesticides, andenergy. Additionally, international goals for efficiency improve-ments in agriculture include aspects of greenhouse gas emission(European Union, 2013a). These emissions can be treated likeanother resource category (the assimilatory capacity of the atmo-sphere), especially since the goals of the Paris Agreement (UNFCCC,2015) constrain the total amount of greenhouse gases that shouldbe emitted into the atmosphere. To assess the state of knowledgeon rebound effects connected to these resources, publications werereviewed using a keyword-based search in the Web of Science(Core Collection) and Scopus. The search terms rebound effect* orJevon* were combined with each of the terms: agricultur*, farm*,land, soil, irrigation, phosphorus, nitrogen, fertilizer and pesticide

C. Paul et al. / Journal of Cleaner Production 227 (2019) 1054e1067 1057

within the title, abstract or keywords. Excluding non-Englishpublications, we identified 33 articles relevant to the objectives ofthis study. An overview of the results and the resources addressedby the individual papers is provided in section 3.

To facilitate a structured analysis, we created a framework ofeconomic and social-psychological rebound effects. This frame-work builds on the commonly used classification of rebound effecttypes into direct, indirect and economy wide effects (Greeninget al., 2000; Kolstad et al., 2014), the differentiation between eco-nomic and social-psychological causes (Maxwell et al., 2011) andthe idea to combine rebound effect types and causes into a matrixlike structure (de Haan et al., 2015). In our framework, we furtherdistinguish between producer and consumer related direct andindirect rebound effects, and we list factors that influence effectsizes of the different rebound mechanisms. While the frameworkwas used to structure the findings of the literature review, infor-mation from the review was, on the other hand, used to verify andrefine the framework's list of factors influencing effect sizes.

Because the reviewed literature focusses mainly on economicrebound effects and provides little information on social-psychological mechanisms, which are consumer based and there-fore predominately food related, we additionally searched forpublications that used the term food in combination with eitherrebound effect* or Jevon* in title, abstract or keywords. In total, weconsidered 7 publications that highlight the consumer perspectiveand socio-economic causes of rebound effects (Buhl and Acosta,2016; Chitnis et al., 2014; Druckman et al., 2011; Salemdeeb et al.,2017; Benedetto et al., 2014; Grabs, 2015; Lin and Xie, 2015).

The framework presented in this article is a tool to aid theassessment of potential rebound effects. While it was createdwithin the context of innovations in agricultural land and soilmanagement, it can easily be transferred to other fields, due to itsgeneric nature.

2.3. Application of the framework for the assessment of emergingtechnologies and practices

As a test case, we assess innovations in soil management forpotential rebound effects. We draw on data from a foresight studyfocussing on future soil management in Germany, as an example forcountries with a temperate climate, industrialized agriculture andlow yield gaps. The study is based on a literature review (Techenand Helming, 2017) and expert interviews (Techen and Helming,2018), and it groups emerging technologies and practices intosoil-related management categories. In the test case, we addressthose categories for which there is sufficient evidence to evaluateefficiency improvements. The assessment of the test case isrestricted to economic rebound effects, since most consumers areunaware of the individual technologies and practices involved insoil management. Innovations in this area are therefore unlikely toaffect consumers’ perceptions of end products, which is a prereq-uisite of social-psychological rebound effects. Despite the restric-tion to economic rebound effects, the strength of the test case studyis that it covers the whole range of innovative cropping activitiesand allows the identification of multiple areas of potential reboundeffects.

3. Results & discussion

3.1. Rebound effect framework

Causes of rebound effects can be categorized as economic orsocial-psychological. From an economic point of view, more effi-cient resource use contributes to lower production costs and affectsthe price of goods and services. Under the neoclassical assumption

of rational economic agents, this leads to increased consumptionand production, thereby offsetting a portion of the initial resourcesavings (Kolstad et al., 2014). On a macroeconomic level, efficiencyincreases may promote overall economic growth associated withan increase in resource consumption, either through price effects orby enabling technological innovations (Gillingham et al., 2016).

de Haan et al. (2015) also highlight the relevance of social-psychological rebound effects and note that purely economic,rational behaviour is not a valid assumption for private consumers.For this group in particular, social-psychological factors can eithercreate rebound effects or lead to additional resource savings(Santarius and Soland, 2018). Policies aimed at increasing resource-use efficiency can affect economic boundary conditions and influ-ence social-psychological factors. Therefore, they have the potentialto promote or limit rebound effects in multiple ways (Gomez andPerez-Blanco, 2014; Sparovek et al., 2018).

Rebound effect types can be divided into direct effects, indirecteffects and economy-wide effects (Dumont et al., 2013;Gillingham et al., 2013; Maxwell et al., 2011). Rebound effect causesand types constitute the building blocks of our rebound effectframework (Fig. 1).

Starting from an improvement of efficiency that reduces thedemand for a specific resource, the adaptations of producers andconsumers can create additional demand for that resource. Eco-nomic and social-psychological causes are distinguished anddifferentiated based on rebound mechanisms. While rebound ef-fects will occur in most cases, they may be too small to be ofrelevance for a specific assessment. What effect sizes are consid-ered relevant must be determined by the user of the framework.

Within the framework, the relevance of different reboundmechanisms for a specific case is assessed by answering a set ofquestions. Analogous to a flow chart, arrows with “yes” and “no”point to likely consequences. Where a rebound mechanism isconsidered relevant, the arrow marked “yes” points to externalfactors that, together with the degree to which consumers’perception or production cost is affected, determine the size of therespective rebound effect. For example, an efficiency increase maylower production costs and motivate producers to expand. Thedegree to which such an expansion is likely is determined by thedegree of the cost reduction, by the degree of market saturation,and by the degree to which producers have access to additionalproduction factors (e.g., additional land, money, water).

3.1.1. Direct rebound effectsFrom an economic point of view, direct rebound effects

comprise income effects and substitution effects. Under the incomeeffect, higher efficiencies mean lower production costs, which maymotivate producers to expand if additional factors of production areavailable (e.g., land, labour, capital goods). For example, if theintroduction of more efficient irrigation technologies makes irri-gated agriculture more profitable, farmers may opt to expand theirarea of irrigated farmland. To do so, however, they require access toland that is allowed to be irrigated, additional labour tomanage thisland and the financial means to pay for the investment. Wherelower costs result in lower prices, consumers are likely to react withincreased consumption of the more efficient product, depending onown-price demand elasticity (Gillingham et al., 2016). Additionally,producers and consumers may opt to use the more efficient pro-duction process to substitute for other types of production. Thedegree to which this occurs depends on the elasticity of substitu-tion (Maxwell et al., 2011).

From a social-psychological point of view, services produced byprocesses that consume fewer resources are perceived as morepositive than those produced conventionally. This is especially trueif those services are labelled as socially or environmentally friendly

Fig. 1. Efficiency improvement and occurrence of rebound effects. Rebound effects will not occur unless the efficiency improvement affects economic performance or consumers'perception of final products. Blue boxes list factors that strongly influence the size of the rebound effect. (For interpretation of the references to colour in this figure legend, thereader is referred to the Web version of this article.)

C. Paul et al. / Journal of Cleaner Production 227 (2019) 1054e10671058

(e.g., energy from renewable sources). Where consumers restricttheir consumption due to awareness of resource-use implications,they may become less hesitant to consume services from moreefficient processes, thereby creating additional demand (de Haanet al., 2015; Santarius and Soland, 2018).

3.1.2. Indirect rebound effectsIndirect rebound effects occur if efficiency increases in a process

result in an increasing demand for other processes that consumethe same resource. Where higher efficiency translates into financialgains for producers and/or consumers, part or all of this gain isusually spent on additional consumption of goods and services,which may also cause additional consumption of the resource thatis saved. It is clear that direct and indirect rebound effects arenegatively correlated: the more financial resources are spent on theoriginal, more efficient process, the less can be spent on otherprocesses.

Chitnis et al. (2014) noted that indirect rebound effects are notonly caused by improvements in the efficiency of production butcan also be caused by voluntary reductions in the consumption ofspecific goods (sufficiency measures), if the monetary savings arespent elsewhere.

From a social-psychological point of view, many consumersimplicitly evaluate their own behaviour and apply a budget to theirresource consumption. Being more environmentally friendly in onerespect may therefore lead to less self-restraint in other areas (deHaan et al., 2015; Santarius and Soland, 2018). Kaklamanou et al.(2015) investigated this in an online survey in which participantswere required to agree or disagree with statements claiming thatengaging in specific sustainable practices could compensate forunsustainable behaviour in another areas. They found only a lowrate of agreement, ranging from 4%e16%, but caution that thisfigure is a conservative estimate, as concerns over the socialdesirability of answers may have led some respondents to rejectstatements.

3.1.3. Economy-wide rebound effectsEconomy-wide rebound effects occur if an entire economy is

affected through changes in societal values, increases in wealth,production or consumption, or the introduction of technologicalinnovations made possible by more efficient processes (Greeninget al., 2000; Kolstad et al., 2014). For example, the introduction ofchemical fertilizer dramatically increased the efficiency of agricul-tural production in terms of yield per hectare and reduced the needfor agricultural land. Furthermore, it has affected economies bylowering food prices and freeing up consumers’ resources to bespent on other goods and services. The resulting economic growthand increased wealth have affected dietary preferences and led toan increase in the consumption of animal-based proteins. Becausethese diets require more land per nutritional value than plant-based diets, a rebound effect has occurred that has offset part ofthe original resource savings.

From a social-psychological point of view, technological prog-ress towards more efficient processes may give consumers a senseof optimism that problems are being taken care of by experts,thereby reducing their perceived responsibility for sustainableconsumption. However, the opposite is also possible, and sustain-able development may create a new paradigm of more sustainablebehaviour (Santarius and Soland, 2018). Negative rebound effectssuch as this are referred to by Wei (2010) as super-conservation.

3.2. Rebound effects in agriculture

The keyword-based literature search identified 33 journal arti-cles addressing rebound effects connected to resource use in agri-culture. Table 1 lists the publications and the resources that theyaddress. All but two studies (Qi and Roe, 2017; van der Werf andSalou, 2015) focused on economic rebound effects. In total, 12 ar-ticles addressed rebound effects related to the resource land; 14examined the use of irrigation water; three addressed energy use;and four addressed greenhouse gas emissions. One study eachaddressed fertilizer use and pesticide application. Ten of the articles(30%) were published in the year inwhich this studywas conducted(2018), while 28 (84%) were published within the last 5 years. Theresults show that rebound effects in agriculture are a new andrapidly growing research topic. This is not to say that rebound

Table 1Resources analysed in publications addressing rebound effects in agriculture. Results of a literature search in theWeb of Science (Core Collection) and Scopus conducted on 17.& 18.07.2018, using the search terms “rebound effect*” or “Jevon*” in combination with any of the terms “agricultur*”, ”farm*”,”land”, “soil”, “irrigation”, “phosphorus”,“nitrogen”, “fertilizer” and “pesticide”within the title, abstract or keywords. Publications in langues other than English and articles that were not relevant to the objectives ofthis study were excluded.*GHG: Greenhouse gas emissions.

Reference Land Irrigation Water GHG* Energy Pesticides Fertilizer Others

Bedoya-Perales et al. (2018) xCeddia et al. (2013) xCeddia & Zepharovich (2017) xCeddia et al. (2015) xCeddia et al. (2014) xDesquilbet et al. (2017) x BiodiversityHuesemann & Huesemann (2008) x x xLatawiec et al. (2014) x xMeyfroidt (2018) xPellegrini & Fern�andez (2018) x xSparovek et al. (2018) xVarkkey et al. (2018) xVilloria et al. (2014) x

Alarcon et al. (2016) xBerbel & Mateos (2014) xBerbel et al. (2015) xBerbel et al. (2018) xDumont et al. (2013) xGomez & Perez-Blanco (2014) xKuil et al. (2018) xLoch & Adamson (2015) xMehmeti et al. (2016) xPfeiffer & Lin (2014) xSears et al. (2018) xSong et al. (2018) xSun et al. (2016) xWu et al. (2018) x

Tukker et al. (2011) xValin et al. (2013) xvan der Werf & Salou (2015) x

Rotolo et al. (2015) xScholz & Wellmer (2015) xQi & Roe (2017) Consumer behaviour

Fig. 2. Main resources in agricultural soil and land management and categories of emerging technologies and practices identified in a foresight study (Techen and Helming, 2017,2018) for which efficiency gains and economic rebound effects are expected. Greenhouse gas emissions are indirectly affected by efficiency changes in the use of land, nutrients,pesticides and energy.

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effects have not been reported in earlier studies, but rather, thatresearchers have only started very recently to address pertinentfindings as rebound effects and used the term in the title, abstractor keywords. Even among the identified studies, the terminology isnot used consistently. Some authors investigate the occurrence ofJevons’ paradox without referencing the term “rebound effect”,

while others treat the two terms as synonyms.We present and discuss the findings of the literature review,

ordered by resource category, together with results from our testcase. The latter includes expected efficiency improvements fromemerging technologies and practices (Fig. 2), and potential eco-nomic rebound effects identified through the use of our framework

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(Fig. 1). To demonstrate the application of the framework, we applyall steps in detail for the resource land, while for the other re-sources, we only note the most relevant effects to avoidredundancy.

3.2.1. Resource: landThe question of how far improvements in productivity (i.e.,

higher yields per hectare) result in reduced total land use (knownas land sparing) is the subject of a longstanding scientific debate. Atone extreme of the argument, the so-called Borlaug hypothesisstates that productivity gains are the key to limiting the expansionof agricultural land into natural ecosystems (Borlaug, 2007). At theother extreme, proponents of Jevons' paradox assert that produc-tivity gains instead motivate and promote agricultural expansion(Pellegrini and Fern�andez, 2018). The two effects seem to exist inparallel, with local circumstances determining the prevalence ofone or the other. Relevant factors promoting land sparing includethe quality of environmental governance (Ceddia et al., 2014;Varkkey et al., 2018) as well as formal recognition of indigenouspeoples' and local communities' rights to forests (Ceddia et al.,2015). However, in a test case in Argentina, Ceddia andZepharovich (2017) found that the introduction of a forest protec-tion law and land titling to indigenous peoples instead promotedthe occurrence of Jevons' paradox from agricultural intensification.As possible reasons for this result, the authors named a lack ofeffectiveness of the law and deforestation undertaken to preventland from being titled to indigenous peoples. Factors considered tocontribute to the occurrence of Jevons’ paradox are a high quality ofgovernance, as measured by World Bank indicators for corruptioncontrol, rule of law, and voice and accountability (Ceddia et al.,2013) as well as low yield levels and potential availability of newfarmland (Varkkey et al., 2018; Villoria et al., 2014).

Barbier and Burgess (1997) found a negative correlation be-tween agricultural yields and the deforestation rate in tropicalcountries between 1980 and 1985. However, Ewers et al. (2009)showed in a global study on yields and land use between 1979and 1999 that land sparing occurred only in some cases. Fordeveloped countries, they found no evidence that increases inagricultural productivity resulted in lower per capita cropland de-mand. In a meta-study, Villoria et al. (2014) showed that at theglobal level, most modelling results indicate a land-sparing effect,while Jevons’ paradox may occur regionally.

Green at al. (2005) analysed the question of land sparing vs. landsharing with a focus on biodiversity preservation and presented amodel for investigating the effects of agricultural production in-tensity. Assuming a fixed demand or production target, they foundthat if the relationship between yields and population densities isbest described by a concave function, as implied by empirical datafrom developing countries, the optimal strategy for species con-servation lies in intensive production in some places and no pro-duction in other places (land sparing). However, these authorsindicated that the assumption of a fixed demandwas a limitation oftheir study and that increased productivity could lead to higherproduction targets. This point was taken up by Desquilbet et al.(2017), who investigated the same data assuming market equilib-rium instead of exogenous production levels. They found thatintensive farming results in increased demand and that due torebound effects, extensive farming (land sharing) is more beneficialto biodiversity conservation, unless the degree of convexity be-tween biodiversity and yield is high.

Lambin and Meyfroidt (2011) discussed the implications ofdirect rebound effects from raising agricultural productivity inmore detail. They pointed to the income effect, i.e., that moreefficient production is likely to be more profitable and couldtherefore motivate expansion. This expansion would depend in the

short term on the price elasticity of demand. Although demand forstaple crops is considered mostly inelastic, lower prices could in-crease the demand for biofuels, meat and other luxury crops (in-come effect, substitution effect). Non-staple crops are considered tobe price and income elastic, and direct economic rebound effectsare therefore to be expected (Meyfroidt, 2018) where expansion ispossible through available production factors such as labour, capital(Varkkey et al., 2018) and land (Pellegrini and Fern�andez, 2018).Bedoya-Perales et al. (2018) reported rebound effects related to theexpansion of quinoa cultivation in Ecuador, where increased pro-ductivity was found to result in an increase, rather than a decreaseof cultivated land. Latawiec et al. (2014) discussed the potential ofintensification of pasture-based agriculture in Brazil to reducedeforestation and achieve land sparing. While intensification couldmeet targets for production increases with a lower land demand,they stated that higher productivity could also motivate agricul-tural expansion and that more profitable agriculture would makenature conservation more expensive, due to higher opportunitycosts. To mitigate rebound effects, these authors see a need foreconomic incentives for farmers, either through policies such astaxes, subsidies or enforcement of existing regulations, or viamarket-side initiatives, such as labelling products according totheir environmental footprint. Meyfroidt (2018) named land zoningand value chain interventions such as certification schemes asoptions for mitigating rebound effects that would otherwise lead toan increase in the use of land for agriculture through farmlandexpansion.

Regarding our test case of emerging technologies and practicesof soil management for Germany (Techen and Helming, 2017, 2018),we expect future increases in land-use efficiency from innovationsin the following categories of practices and technologies:

e Improved crop varieties: crop breeding is an on-going process,and improvements in productivity and stress tolerance are ex-pected (Rubiales et al., 2015; Gilliham et al., 2017).

e Intercroppingmay be practiced on a relevant share of croplandonce better-suited technologies become available. Meta-studiesshow that intercropping can increase yields in terms of landequivalent ratios, i.e., achieving higher yields than if all cropshad been grown as single crops on an area of land equivalent totheir share in the intercrop mix (Pelzer et al., 2014; Yu et al.,2015). Intercropping also improves productivity by increasingyield stability (Raseduzzaman and Jensen, 2017).

e An increase in the irrigated agricultural area is expected,partly motivated by concerns about climate change (Gutzleret al., 2015), which will increase the yield per hectare.

e Agroforestrymay be practicedmore in the future, mainly due toan increasing demand for lignocellulosic material for industry.Similar to intercropping, themixture of different species inwell-designed agroforestry systems can increase land equivalent ra-tios under temperate conditions (Nerlich et al., 2013; Torralbaet al., 2016).

To assess potential economic rebound effects, we apply theright-hand side of the framework presented in Fig. 1., focussing oneffects at the national scale. The first-level question “Does effi-ciency improvement lower production costs by a relevant de-gree?” can be affirmed for all listed practices except agroforestry. Inthat case, high investment costs with long payback periods arelikely to offset cost reductions, and no relevant economic reboundeffects are therefore expected. For the remaining practices, thefollowing appraisal has been made:

1) “Direct producer effect: Is production likely to beexpanded?” Due to a growing global demand for agricultural

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products (see Section 1), we assume that yield increases will befully offset by higher production and not result in an abandon-ment of agricultural area in Germany. This constitutes a reboundeffect of 100% at the national level. If profitability is stronglyincreased by the innovation, even Jevons' paradox is possible ifareas under pasture are converted into additional cropland.Such an effect has been observed in Germany in connectionwithan intensification of milk production, which motivated farmersto expand the area used for fodder maize (Laggner et al., 2014).However, regulations at the German and European levelscurrently restrict options for such conversion (especiallyEuropean Union, 2013b), thereby limiting expansion throughregulating the availability of land as an additional productionfactor.

2) “Direct consumer effect: Are product prices for consumerssignificantly reduced?” In Germany, price development foragricultural commodities depends on multiple factors, amongwhich land productivity is only one (see European Commission,2015; OECD/FAO, 2017 for projections on the basis of currenttrends). Because of this, we do not expect the identified in-novations to result in a drop in prices for German consumersand consequently do not expect them to increase consumerdemand.

3) “Direct effect: Can the more efficient process be used tosubstitute other processes?” Substitution options for agricul-tural commodities are limited and commodity specific. For foodcrops, the options for substitution are much more limited thanfor animal feed and non-food crops. In the latter category,biomass is expected to increasingly substitute fossil resources inproducts such as plastics (Morrison and Golden, 2015; Scarlatet al., 2015). Depending on the development of markets foragricultural resources for material use, increased productivitycould become a driver of this substitution, which wouldconstitute a rebound effect. Generally, this novel demand foragricultural products illustrates how an increase in availableland due to improved land-use efficiency could rapidly be uti-lized for alternative types of production.

4) “Indirect effect: Are cost savings likely to be spent elsewhere/re-invested?” In the near future, input prices are expected torise more strongly than product prices (European Commission,2015), which is likely to offset part or all of the achieved costsavings. We therefore expect only very moderate indirectrebound effects.

5) “Economy-wide effect: Will economic growth at the nationalscale be affected?” Within the test case, we consider relativelysmall changes within an economic sector (agriculture, forestryand fisheries) that generates only 0.7% of German GDP (GermanFederal Statistical Office, 2018). Therefore, we assume thateconomic growth at the national scale will not be affected to arelevant degree.

In conclusion, several potential innovations in agricultural soilmanagement were identified that would increase land-use effi-ciency and would likely cause economic rebound effects. Theseinnovations are improved crop varieties, intercropping and an in-crease in the irrigated agricultural area. Using the framework,rebound effects at national scale were found to be most likely tooccur in the form of direct producer effects through expansion and,potentially, substitution. Although effect sizes close to 100% areexpected for the resource land at the German national scale, oc-currences of Jevons’ paradox are expected to be rare due to theinstitutional setting in Germany.

3.2.2. Resource: waterFor the resource irrigation water, particularly where surface

water is used, it is necessary to distinguish between water use andwater consumption. Only a portion of the water used in irrigationsystems is taken up and consumed by plants, while the remainderis considered to be wasted. However, water wasted by inefficientirrigation systems may become re-available by seeping into aqui-fers or re-entering rivers in the form of return-flow downstreamfrom the point of abstraction (Berbel and Mateos, 2014; Dumontet al., 2013). More efficient irrigation systems reduce the share ofwater that is wasted butmay also increase the amount of water thatis available to plants, resulting in higher consumption. This canresult in a hydrological paradox, where water use declines due tohigher efficiencies, but water consumption increases, exacerbatingwater shortages (Gomez and Perez-Blanco, 2014; Grafton et al.,2018).

Additionally, rebound effects appear to be common, withseveral studies reporting cases in which rebound effects weregreater than 100%, and efficiency improvements resulted in higher,instead of lower, water consumption (Jevons’ paradox) (e.g., Perryet al., 2017; Pfeiffer and Lin, 2014; Sun et al., 2016). More efficientirrigation systems are likely to induce direct rebound effectsbecause increased water productivity constitutes an economicincentive for farmers to expand their area of irrigated land and tosubstitute non-irrigated crops for irrigated crops, which result inhigher revenues (Kuil et al., 2018; Sears et al., 2018;Wu et al., 2018).This substitution effect may even be exacerbated by the need tocover investment costs for the improved irrigation systems(Alarcon et al., 2016). While numerous studies have investigatedwhether efficiency improvements result in a reduction or increasein total water use, very few studies have attempted to quantifyeffect sizes. One exception is an article by Song et al. (2018), whoinvestigated the agricultural water rebound effect in China. Usingmacro-scale economic indicators and a statistical model to separateincreases inwater use due to technical progress from those inducedby increases in other inputs, these authors calculated an averagedirect rebound effect of 61.5% at the national level in China between1998 and 2014. They also identified rebound effect sizes greaterthan 100% at the national level for individual years. At the regionallevel, they found an average rebound effect greater than 100% insome provinces across the entire time frame.

Without accompanying policy measures, efficiency improve-ments in agricultural irrigation are likely to lead to large reboundeffects and possibly Jevons’ paradox. Accordingly, the FAO reviewreported by Perry et al. (2017) concluded that “introducing hi-techirrigation in the absence of controls on water allocations will usu-allymake the situationworse: consumption per unit area increases,the area irrigated increases, and farmers will tend to pump morewater from ever-deeper sources.” Effect sizes, however, depend onpreconditions that can be influenced by policy making. Expansiongenerally requires the availability of additional production factors,and where additional land to be irrigated is unavailable due to legalrestrictions, this type of rebound effect will not occur. Accordingly,using a microeconomic model where neither an increase in irri-gated area nor a shift to crops with a higher water demand ispossible, Berbel et al. (2018) found that efficiency improvementsresult in lower water use and negligible increases in water con-sumption when irrigation prior to the improvement already ach-ieved the full yield potential. Where deficit irrigationwas practicedbefore, water use is reduced, but water consumption is increased.

To reduce rebound effects, policy measures limiting the totalsize of irrigated area, reducing the total amount of water rights afterefficiency improvement and reassigning a portion of the achievedwater savings towards environmental goals have been suggested(Berbel et al., 2015; Grafton et al., 2018). However, Loch andAdamson (2015) discuss rebound effects and problems associatedwith such reassignment for an Australian case in which 50% of the

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achieved water savings are required to be used for environmentalgoals. In their “Blueprint to Safeguard Europe's Water Resources”the European Commission (2012) recommends adequate waterpricing as a means to avoid possible rebound effects from efficiencyimprovements in the water sector. Likewise, Song et al. (2018)suggest the need for water prices in China to reflect the realcosts. However, for agriculture, Berbel et al. (2015) considerincreasing water prices to avoid rebound effects to have only a verylimited effect. This assessment is partly shared by Dumont et al.(2013) who state that agricultural water use is price inelasticwhere surface water is used, but price elastic where groundwater isused (Dumont et al., 2013; Sears et al., 2018).

Considering the test case, novel irrigation technologies are ex-pected to yield higher water use efficiencies. Research onwater useefficiency has increased exponentially in recent years, with 20published articles in 1988, 121 in 2003 and 618 in 2016 (Velasco-Mu~noz et al., 2018). Areas of technological improvement includecombining remote sensing and soil sensors with modelling ap-proaches for better demand-specific irrigation (Barker et al., 2018;Singh et al., 2018). While rebound effects from improving theexisting irrigation infrastructure in Germany are not expected to bestrong, due to the low extent of irrigation at the national level (2,7%in 2016) (German Federal Statistical Office, 2017a), technologicalprogress may reduce the cost of irrigation and increase associatedwater productivity. Both factors are likely to promote uptake ofirrigation and increase the use of irrigation water in Germany,which would constitute a rebound effect.

3.2.3. Resource: nutrientsFor rebound effects connected to nutrient management, we

found only one study on phosphorus (Scholz and Wellmer, 2015).However, the authors addressed rebound effects only in very gen-eral terms and did not provide information on rebound mecha-nisms or effect sizes.

Based on our framework and the particularities of nutrientmanagement in agriculture, we consider direct rebound effects(expansion) from improved nutrient efficiencies to be likelybecause farmers seek to apply the amount of fertilizer that, withinthe bounds of rules and regulations, achieves the highest contri-butionmargin. Due to the law of diminishing returns from inputs toproduction, this amount is generally lower than the amount thatwould achieve the highest yields. When the nutrient-use efficiencyis increased, such as through a new crop variety that is able toachieve the same yield with a lower fertilizer input, the economicoptimum shifts and farmers adapt their nutrient managementaccordingly. This is likely to result in a situation where fertilizerinputs are reduced, but a portion of the potential resource savingsare offset to achieve higher yields. However, farmers may deviatefrom this theoretical approach due to behavioural norms (e.g., Vatn,2005) or due to imperfect knowledge, i.e. “bounded rationality”(Rubinstein, 1998). Additionally, “safety thinking” (Eckert et al.,2000) can lead to fertilizer inputs that are higher than the eco-nomic optimum.

For emerging technologies and practices in Germany (Techenand Helming, 2017, 2018), we expect increases in nutrient-use ef-ficiency from the following categories of technologies andpractices:

e Cereal-legume intercrops decrease the need for nitrogenfertilization in relation to yield, due to improved use of soil andatmospheric nitrogen (Pelzer et al., 2014). Some studies alsoshow more efficient use of phosphorus and micronutrients byintercrops (Brooker et al., 2015; Duchene et al., 2017).

e On-going developments in precision farming and decisionsupport systems, including improved sensors, data fusion

algorithms and translation into decision support, are likely toincrease the efficiency of nutrient use. This is because evencurrent precision technologies can often achieve high efficiencygains (Colaço and Bramley, 2018), and because technology inthis field is rapidly developing (Chlingaryan et al., 2018).

e Similar to intercropping, diversifications in the sequence ofcrops, such as more diverse crop rotations involving morelegumes and/or cover crops, can increase nutrient use effi-ciency (e.g. Constantin et al., 2011). Such diversifications mayemerge as a reaction to, for example, pesticide resistance ordiversified consumer demand (Techen and Helming, 2017).

e New fertilizers from recycled nutrients may increase nutrient-use efficiency in the future at the national scale and possiblyalso at the farm level (Techen and Helming, 2017).

Since significant reductions in fertilization and/or increases inyield to fertilizer ratios can be achieved with cereal-legume in-tercrops (Pelzer et al., 2014) as well as through improved precisionfarming and decision support systems (Colaço and Bramley, 2018),we expect lower production costs and potential economic reboundeffects for these innovations. In the case of more diverse crop ro-tations, economic benefits are unlikely because this practice entailsthe inclusion of less profitable crops into rotations. This assessmentwould change if a future diversification of demandwere to improvethe profitability of alternative crops, such as an increasing demandfor perennial, lignocellulosic crops for material uses in the bio-industry (Hassan et al., 2019). In the case of new fertilizers, weassume that due to more costly production processes, their pricewill be higher than that of conventional alternatives.

Regarding rebound effect sizes, the following appraisals can bemade: For intercropping with leguminous crops, direct producer-side rebound effects that would result in higher total nitrogen in-puts are not expected. The particularities of the underlying bio-logical processes limit options for farmers in this regard becausehigh external nitrogen inputs reduce the effectiveness of legumenitrogen fixation and do not result in higher overall yields in termsof the total land equivalent ratio (Pelzer et al., 2014).

For precision farming, strong direct producer-side rebound ef-fects in the form of higher total fertilizer inputs are possible. Ingeneral, an important component of precision farming is calcu-lating the spatially differentiated nutrient demand of plants. Incases of relatively low fertilizer intensities before the imple-mentation of the technology, a higher production potential in someareas of a field with corresponding higher nutrient needs canovercompensate for the reduced fertilizer application in areas witha lower production potential (Flessa et al., 2012). Accordingly,Jevons’ paradox has been observed in some earlier cases of preci-sion farming (Flessa et al., 2012). Although this possibility cannot beruled out for future cases, overall improvements in the precision offertilization (Chlingaryan et al., 2018) could compensate forpartially higher nutrient demands calculated through improvedfertilization planning.

3.2.4. Resource: pesticidesAs for nutrient management, the literature search identified

only one study addressing rebound effects connected to pesticideapplication. Rotolo et al. (2015) describe how the cultivation ofgenetically modified, pest-resistant crops, originally intended toreduce external pesticide application, has resulted in the emer-gence of resistant pest species and consequently in a need forincreased pesticide use. While these authors consider this to be anexample of Jevons’ paradox, the offsetting of the technical effi-ciency gain is caused by the adaptive capability of nature (the pestspecies in this case) and not by behavioural changes in humanactors. It would, therefore, not fall under the definition of rebound

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effects used in this paper. However, this example highlights thatagriculture operates at the interface between human and naturalsystems and that both human and non-human, natural actors willadapt to efficiency improvements. With regard to agriculture, itmay therefore be advantageous to expand the concept of reboundeffects in the future to also include natural adaptations.

For our test case, we may see improvements in pesticide useefficiency within the following categories (Techen and Helming,2017, 2018):

e Improved crop varieties are expected to increase pest resis-tance, reducing the need for pesticides (Rubiales et al., 2015).

e Well-designed intercropping systems and more diverse croprotations reduce the need for pesticide application (Brookeret al., 2015; Duchene et al., 2017).

e Improved precision farming and decision support systems arelikely to increase pesticide efficiency (Dyrmann et al., 2018).

e Biotic inoculation (i.e., inoculating seeds and soil with antag-onists of pests) can reduce the need for pesticide application(Kergunteuil et al., 2016). This new technology may becomemore economically viable with future developments(Kergunteuil et al., 2016).

By increasing pest resistance, improved crop varieties andintercropping can generally lower production costs in terms ofpesticide use, even though the overall effect on profitability is un-certain. In contrast, site-specific pesticide application, as acomponent of precision farming, is likely to largely reduce the totalinput of pesticides with the development of future technology, suchas technology that identifies single plants and treats each plantindividually with pesticides or mechanical measures (e.g.,Gonzalez-de-Santos et al., 2017; Owen et al., 2017; Philipp et al.,2017). Efficiency gains from improved crop varieties, intercrop-ping and precision farming/decision support systems could comewith direct rebound effects (substitution) if they motivate farmersto reduce tillage and substitute mechanical weed control withpesticide application. Finally, biotic inoculation is more expensivethan the use of chemical pesticides (Kergunteuil et al., 2016) andthere is no indication that this will change in the future. Bioticinoculation may rather become a complementary plant protectionstrategy in cases of pesticide resistance.

3.2.5. Resource: energyPellegrini and Fern�andez (2018) investigated the relationship

between agricultural energy use and energy efficiency during thespread of the green revolution. Based on time series from 1961 until2014, they concluded that at the global level, higher energy effi-ciencies have not resulted in lower energy use, and that theirfindings fit the definition of Jevons' paradox. Lin and Xie (2015)investigated factor substitution and rebound effects in China'sfood industry from the perspective of energy conservation. Theyfound a direct energy rebound effect of 34% and evidence of sub-stitution relationships between energy and other input factors,among which labour was the largest factor.

For fuel and electricity consumption in general, Gillingham et al.(2016, 2013) considered the sum of microeconomic and macro-economic rebound effects to not exceed 60%.

In our test case, we saw potential for increases in energy useefficiency through reduced tillage practices. While it is uncertainwhether the share of cropland under reduced tillagewill increase inGermany (41% in 2010 and 43% in 2016; German Federal StatisticalOffice, 2010, 2017b), practices that are relatively new in Germanysuch as strip-till and controlled-traffic farming may provide newincentives for farmers (Techen and Helming, 2017). Reduced tillagemethods require less fuel, to a degree that is relevant for farmers’

decision-making (Ingram, 2010; Sattler and Nagel, 2010), becausethese methods require less drag force to move soil (KTBL, 2008;�Sarauskis et al., 2017). Since there is no benefit in more frequenttillage when using improved methods, we only expect indirectrebound effects as a result of re-spending the money saved throughinnovative management. The effect size will largely depend on theenergy intensity of the goods and services upon which the savingsare re-spent.

3.2.6. Resource: greenhouse gas emissionsIn a global study using the partial equilibrium model GLOBIOM,

Valin et al. (2013) analysed scenarios that could satisfy projectedfood demand for the year 2050. For a technology pathway whereadditional production is achieved through higher productivity,these authors found strong demand-side rebound effects thatreduced potential greenhouse gas savings by 50%. Benedetto et al.(2014) presented an analytical framework for rebound effects inthe wine industry. Assuming a theoretical novel product with alower carbon footprint, they illustrated how total greenhouse gasemissions may either increase or decrease depending on pricechanges and choices made by producers and consumers. Theirexample highlighted the complex interactions of market partici-pants and the difficulty inherent in anticipating their reaction toefficiency improvements.

Demand for agricultural commodities and the associatedresource consumption is also affected by the (currently high) pro-portion of food waste. Food-saving consumer behaviour, improvedtechnical processes or novel crop varieties developed to increaseproduct shelf-lives could lower this share in the future. For theeffects of consumer-based reductions of food waste on greenhousegas savings, rebound effects of 51% (Druckman et al., 2011), rangingfrom 23% to 59% (Salemdeeb et al., 2017) and ranging from 66% to106% (Chitnis et al., 2014) have been reported. The high effect sizeswere a result of indirect rebound effects, with consumers re-spending money originally used for food which causes relativelylow greenhouse gas emissions, in favour of greenhouse gas-intensive items such as fuels in transport or energy in housing.

In a meta-analysis of life-cycle assessment studies, Clark andTilman (2017) showed that shifting from diets containing highamounts of ruminant meat to diets based on fish, pork, poultry orvegetables could provide the same nutrition with much lowerresource consumption. The impact categories they consideredincluded land, greenhouse gas emissions and energy. However,these authors stated that these alternative diets would probably becheaper and that the re-spending of the money thus saved couldresult in additional resource consumption. This would constitute anindirect rebound effect. To mitigate such effects, van der Werf andSalou (2015) proposed food labels based on greenhouse gas emis-sions per monetary unit. With this system, products of higherquality that are more expensive would be considered more posi-tively than cheaper alternatives because they reduce the amount ofmoney spent elsewhere and therefore also reduce the associatedgreenhouse gas emissions. However, in a life cycle study on theecological benefits of dietary shifts in Europe, Tukker et al. (2011)found only negligible indirect rebound effects from the slightlylower costs of alternative diets. On the other hand, they consideredeconomy-wide rebound effects to be likely, such as increased meatexports compensating for reduced domestic demand.

In our test case, innovations for reducing greenhouse gasemissions are not investigated explicitly. However, where in-novations result in land sparing or in a reduction in the use ofmineral fertilizers, pesticides or fossil fuels (see above), they alsoreduce greenhouse gas emissions. Nevertheless, an assessment oftotal effects requires that additional emissions caused by the in-novations themselves be taken into account. In the case of precision

Fig. 3. Application of the rebound effect framework to identify potential for economic rebound effects from innovations in agricultural soil management in Germany. Results refer torebound effects at the national scale.

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farming and decision support systems, an increased demand forelectricity, especially for storing data (Carolan, 2017; Fagas et al.,2017), may partly or fully offset greenhouse gas savings fromreduced fertilizer application through emissions associated withelectricity production.

Fig. 3 gives an overview of the test case's application and majorfindings.

3.2.6.1. Open challenges. Rebound effects in agriculture are anemerging research topic with a small, but rapidly growing evidencebase. However, this novelty constitutes a challenge for systematicreviews, as older publications may not refer to relevant findings interms of rebound effects or Jevons’ paradox. Where we identifiedsuch studies through cross references, we used them to comple-ment the findings of our review. Additional research is desirable forsuch studies, especially regarding effects from more efficient fer-tilizer or pesticide use where evidence is lacking. Likewise, moreresearch on social-psychological rebound effects is required, asthese effects may play an important role with regard to consumerbehaviour, and the knowledge base is still very limited (Maxwellet al., 2011; Santarius and Soland, 2018).

Quantification of rebound effects is another challenge, due tothe interplay of multiple processes and variables, especially in ex-ante assessments. Even for energy efficiency, upon which mostresearch on rebound effects has been focussed so far, publishedeffect sizes differ strongly, with some studies indicating little or noeffect, while others identify very high rates or even Jevons' paradox(see Huesemann and Huesemann, 2008 and Kolstad et al., 2014 forlists of studies from both groups). However, the majority of reportsin this field seem to agree that Jevons’ paradox constitutes anextreme case and that increases in efficiency generally result in areduction of resource consumption (Gillingham et al., 2013, 2016).Likewise, direct rebound effects from increased energy efficiency

are considered to be relatively small (Huesemann and Huesemann,2008). In a meta-study, Gillingham et al. (2016) found valuesranging from 5% to 40% for direct rebound effects from more effi-cient fuel and electricity use in developed countries, with mostvalues falling between 5 and 25%.

One reason for the divergence in published values for reboundeffect sizes lies in the exclusive focus of many studies on selectedrebound mechanisms. The framework presented in this paper canbe used to highlight which rebound mechanisms are assessed andwhich are omitted in individual studies, thereby facilitating theinterpretation of results. Additional reasons are the use of differenttime frames, which may lead to different rates of adaptation, andfinally, the technical difficulties involved in assessing economy-wide effects. According to de Haan et al. (2015), process-based,bottom-up studies generally underestimate rebound sizesbecause they are unable to fully account for economy-wide effects.On the other hand, studies based on top-down evaluations of timeseries tend to overestimate effects, due to the difficulties of sepa-rating increased resource consumption caused by efficiency gainsfrom increased consumption caused by overall economic growthand corresponding increases in consumer wealth (de Haan et al.,2015). Accordingly, Gillingham et al. (2016) noted that whilethere are plenty of examples of how both resource-use efficiencyand total resource consumption have increased since the industrialrevolution, this co-occurrence is not proof of causality and there-fore does not necessarily represent a rebound effect. Irrespective ofthe difficulties and uncertainties involved in determining reboundeffect sizes, Maxwell et al. (2011) emphasise that the implicitassumption of zero rebound effects made in some studies andpolicies is not supported by scientific evidence.

Several studies have found that consumer-based rebound ef-fects are higher for low-income groups (Buhl and Acosta, 2016;Chitnis et al., 2014). One reason for this finding could be that low

C. Paul et al. / Journal of Cleaner Production 227 (2019) 1054e1067 1065

income is associated with a higher degree of unsatisfied demand.For energy use, Grabs (2015) attributed a higher rebound effectobserved in lower income groups to the tendency to re-spend thesaved expenditure on relatively energy-intensive expenditure cat-egories. These findings also illustrate a social aspect of reboundeffects: while such effects reduce resource savings, they are basedon an increase in production and consumption and contribute tosatisfying human demand, thereby potentially improving livingconditions. This point needs to be considered in efforts to mitigaterebound effects, especially with regard to low-income countries,where efficiency gains and high rebound effects may contribute tomeeting basic human needs.

4. Conclusions

Our literature review revealed that rebound effects in thecontext of agricultural land and soil management are still a noveltopic and that there is a dearth of studies on rebound effectsassociated with efficiency improvements in several resource cate-gories. More research is particularly desirable with regard to effectsizes at different geographical scales and for social-psychologicalrebound effects. Nevertheless, we found evidence of the occur-rence of strong rebound effects or even Jevons' paradox, particu-larly for increases in productivity and for more efficient use ofirrigation water. Such effects must be considered to provide real-istic estimates of resource savings that can be achieved throughefficiency increases and sustainable intensification. The reboundeffect framework presented in this article is designed to facilitatethe required assessments. In our test case, we demonstrated how itcan be used to scan future innovations in agriculture for potentialeconomic rebound effects at the national scale. While such a broadscan over multiple innovations identifies areas where rebound ef-fects are likely, an application of the framework to single in-novations will allow a more detailed assessment of effect sizes.Where rebound effects are likely, policies that promote efficiencyincreases should aim to include measures for mitigating them andfor safeguarding against Jevons’ paradox.

Finally, this manuscript exclusively focussed on rebound effectsand consequently ignored spill-over effects, where improvementsin the use of one resource result in increased consumption of otherresources. These effects must be included in comprehensive as-sessments of novel technologies and practices.

Declarations of interests

None.

Funding

This research was funded by the German Federal Ministry ofEducation and Research (BMBF) under the framework of thefunding measure “Soil as a Sustainable Resource for the Bio-economy e BonaRes”, project “BonaRes (Module B): BonaResCentre for Soil Research, subproject A, B” (grant 031A608A,B).

Acknowledgments

The authors would like to thank Dr. B. Bartkowski and Dr. J.Luckmann for their helpful advice during the preparation of themanuscript, and four anonymous reviewers for their comments onan earlier version of this work. Additionally, the first author isindebted to Dr. J. Gonz�alez, who first introduced him to the conceptof Jevons' paradox several years ago.

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