Perception of the Relevance of Soil Compaction and Application of Measures to Prevent It among German Farmers

Sandra Ledermüller; Johanna Fick; Anna Jacobs

doi:10.3390/agronomy11050969

Ledermüller, Sandra;Fick, Johanna;Jacobs, Anna

2021-05-13 00:00:00

agronomy Article Perception of the Relevance of Soil Compaction and Application of Measures to Prevent It among German Farmers 1 , 2 1 Sandra Ledermüller *, Johanna Fick and Anna Jacobs Coordination Unit Soil, Thünen Institute, Bundesallee 49, 38116 Braunschweig, Germany; Anna.Jacobs@thuenen.de Thünen Institute of Rural Studies, Bundesallee 63, 38116 Braunschweig, Germany; Johann.Fick@thuenen.de * Correspondence: Sandra.Ledermueller@thuenen.de Abstract: Intensive ﬁeld trafﬁc and high axle loads can lead to soil compaction, with ecological and economic consequences. However, the relevance of this issue among practitioners is largely unknown. Therefore, the aim of this study was to determine the relevance of this issue for farmers in Germany, whether and which mitigation measures are applied to avoid it, and what a (non-) application might depend on. We conducted an online survey among farmers in Germany in winter 2017/2018. For the majority of the respondents, soil compaction is a relevant issue on their own farm, and even at higher share rates, this issue is important for Germany as a whole. To prevent or avoid soil compaction, 85% of the participants apply agronomic, 78% tyre/chassis, and 59% planning/management measures. The farm size, tractor power, working in full- or part-time, estimated relevance of soil compaction for Germany, and the estimated yield loss were positively associated with the application of management measures. The insights gained suggested that more effort is needed to encourage farmers’ perceptions regarding soil compaction in order to generate demand-oriented and practice-oriented recommendations for action for various target groups and Citation: Ledermüller, S.; Fick, J.; Jacobs, A. Perception of the Relevance thus promote the application of soil-conserving measures on a broad scale. of Soil Compaction and Application of Measures to Prevent It among Keywords: soil management; farmers’ attitudes; yield loss; risk perception; advisory service; German Farmers. Agronomy 2021, 11, formal learning 969. https://doi.org/10.3390/ agronomy11050969 Academic Editors: E. A. C. Costantini 1. Introduction and Simone Priori Background Received: 23 April 2021 Soil compaction of arable soils is caused by intensive ﬁeld trafﬁc on wet soils due to Accepted: 11 May 2021 under unfavourable weather conditions [1–4]. Soil compaction leads to decreased porosity Published: 13 May 2021 and changed pore size distribution and disturbs the water and gas regime of soils [5,6]. It also reduces hydraulic conductivity and increases bulk density, which can cause ﬂoods [7], Publisher’s Note: MDPI stays neutral disturbs biological processes in the soil, and promotes nitrous oxide emissions (N O) [8–11] with regard to jurisdictional claims in or reduces crop growth [12,13]. Soil degradation caused by compaction is receiving increas- published maps and institutional afﬁl- ing attention from policymakers as it is considered as a major soil threat in Europe [14]. iations. Among suggestions for efﬁcient soil management, preventing soil compaction is one of the key objectives for the future Common Agricultural Policy (CAP) [15] and is seen as one lever to achieve the goals of the European Green Deal [16]. Copyright: © 2021 by the authors. Measures to Prevent or Mitigate Soil Compaction Licensee MDPI, Basel, Switzerland. In Germany, crops such as silage maize and sugar beet are especially associated with This article is an open access article high machinery loads during harvest in late summer/autumn, when the weather is rainy distributed under the terms and and soils have a high moisture content and are therefore susceptible to compaction [17]. The conditions of the Creative Commons area under silage maize and sugar beet regionally accounts for up to 20–34% and 14–24% of Attribution (CC BY) license (https:// arable land in individual districts, respectively [18]. Additionally, a large amount of liquid creativecommons.org/licenses/by/ manure is applied to the ﬁelds in spring, when soils can be even wetter than in autumn. 4.0/). Agronomy 2021, 11, 969. https://doi.org/10.3390/agronomy11050969 https://www.mdpi.com/journal/agronomy Agronomy 2021, 11, 969 2 of 24 With climate change, drier summers and wetter winters are expected for Germany [19]. This also brings drier soils in the summer, but the regional expression of this is associated with considerable uncertainties [20]. Dry conditions in summer could be beneﬁcial for wetter regions in terms of the number of trafﬁcable days [21]. However, this has not been demonstrated for Germany so far. To prevent or mitigate soil compaction, farmers can choose between a variety of mitigation measures, including agronomic, technical, or man- agement measures [22]. Agronomic measures include, for example, the cultivation of cover crops, direct seeding, or no or no-turn tillage without ploughing. These measures have a rather indirect effect on the prevention of soil compaction by stimulating soil biota, thereby improving aggregate stability and thus the resilience of soils [2,23–25]. As a further side effect, the number of machine passes is reduced and the generation of a so-called “plough sole” is avoided. They are referred to as indirect measures for the purposes of this paper because they are not primarily applied to prevent soil compaction. The technical measures include tyre variations and conﬁgurations as wide tyres, twin tyres, or technical options to adopt the tyre inﬂation pressure and chassis options as rubber tracks or crab steering. These measures increase the contact area or decrease the number of wheelings and thus the associated soil pressure [26]. Information on the functionality, advantages, and disad- vantages of these measures in the form of manufacturers’ recommendations, practitioner reports, or articles in agricultural journals is widely available (e.g., [27–32]). Separating street and ﬁeld transport during harvest and manure spreading or the adaption of the machine utilisation scope to the trafﬁcable period of the soil are among the management measures. When separating street and ﬁeld transport, the tyre pressures of the transport vehicles on the ﬁeld are adjusted to the respective requirements (low tyre pressure for soil protection). For this measure, an additional transport vehicle is needed, which causes additional operational costs. When adapting the machine utilisation scope, it is generally not expected with 100%. The 100% utilisation scope of a beet harvester, for example, would be 1000 ha per year and 10 years of utilisation. This way, the highest machine efﬁciency and thus the lowest machine costs per ha are achieved. If it is now planned with a utilisation scope of 70%, farmers can react ﬂexibly to weather conditions and are not under pressure to use the machine under any conditions. In this case, the machine costs per ha will increase. There is much less information available on these measures and it is provided rather by ofﬁcial bodies (e.g., [33,34]). (Pro-) Soil Conservation Behaviour and Decision Making of Farmers Thorsøe et al. [35] described subsoil compaction as a “wicked” problem. Contrary to tame problems, wicked problems are “ill-deﬁned, ambiguous and associated with strong moral, political and professional issues. Since they are strongly stakeholder dependent, there is often little consensus about what the problem is, let alone how to deal with it. [ . . . ] they are sets of complex, interacting issues evolving in a dynamic social context” [36]. In the context of soil compaction, pragmatic trade-offs, technological barriers, knowledge deﬁcit, and responsibility outsourcing are to be mentioned [35]. Furthermore, yield effects and thus the direct economic consequences largely depend on the soil type and soil conditions at the time of wheeling and type of machinery [37]. For decisions on sustainable soil management as made by local actors, knowledge of the local soil properties and management is necessary. Moreover, each player acts in an individual socioeconomic environment, which also needs consideration [38,39]. In the past, exploring what farmers in industrialised countries know about soil com- paction, how they perceive it, and what measures they implement to avoid or mitigate it were issues that received little attention from a scientiﬁc perspective. However, there are quite a number of studies on different aspects of sustainable land management in developing countries (e.g., [40–44]) but only a few in industrialised regions such as Central Europe. For Central European conditions, Reichardt and Jürgens [45] studied the adoption of precision farming in Germany and found technical challenges (e.g., data handling and interpretation, incompatibility between machines) to be the main barrier for a broad adop- Agronomy 2021, 11, 969 3 of 24 tion. Caffaro and Cavallo [46] found perceived, not further speciﬁed, economic barriers to have a negative effect on the application of smart farming technologies in Italy. Farm size, in contrast, had a positive effect on the implementation. Tamirat et al. [47] showed for Germany and Denmark that farm size, age, and information/demonstration events signiﬁcantly inﬂuence the decision of farmers to adopt precision agriculture. Regarding the acceptance of conservation measures in Germany, Sattler and Nagel [48] observed that associated risk, effectiveness, and the efforts needed to implement a certain measure are equally or even more important than economic considerations. For a change in land management practices in order to avoid soil erosion in UK, Boardman et al. [49] pointed out the importance of ﬁnancial incentives as a motivator, in addition to socioeconomic inﬂuences. According to Barnes et al. [50], farm size and income had an inﬂuence on the adoption of precision agriculture technologies, but so did expectations of economic beneﬁts from adoption and personal attitudes towards information and innovation. In the review of Bartkowski and Bartke [51] on decision making concerning soil management, economic considerations and pro-environmental attitude were found to be studied most often, and studies that reported a signiﬁcant inﬂuence of these variables on decision making predomi- nate. Concerning the effect of information and advisory service, Klerkx and Jansen [52] and Baumgart-Getz et al. [53] pointed out the important role of advisory service in terms of capacity and awareness building for sustainable farming and management among farm- ers. Within the stakeholder groups from practice and policy design and implementation, Prager et al. [54] identiﬁed advisory services as impotant players for the promotion of conservation measures. Especially for the case of sustainable soil management, Ingram and Mills [55] suggest for Europe that not all needs of farmers and advisors are met to push forward sustainable soil management. Aim of This Study In order to promote measures against soil compaction, e.g., by policy interventions or by information and education, it is of high importance to know how widespread such measures are and on which factors application depends. With this knowledge, certain measures can be promoted in a targeted manner and the promotion can be designed in a target-group-oriented way. Moreover, knowledge on the perceived relevance of the issue by farmers, as the main decision makers, is of strong importance. From this, conclusions may be drawn about the type of interventions that can promote adoption. If the relevance is assessed as being high but adoption is low, suitable measures are probably lacking or are unknown. If the relevance is assessed as being low, it is possible that the relevance is actually low or that the sensitivity to the issue needs sharpening. To the best of our knowledge, no scientiﬁcally based information is available on the perception of soil compaction as a relevant problem in Germany. The same applies to the adoption of measures to avoid it in Germany because the technical and management measures described above are not included in any agri-environmental program or agricultural surveys. Thus, the aim of this study was to explore the perception and knowledge of soil compaction, to ﬁnd out how widespread mitigation measures to avoid soil compaction are, but also to identify possible variables that may determine the adoption of measures preventing soil compaction among German farmers. 2. Materials and Methods Due to the lack of a complete and accessible contact list of farmers in Germany, we contacted as many farmers as possible to obtain a broad sample. We did this by distributing the invitation to the online survey through numerous channels, including articles in agricultural magazines, press releases of ofﬁcial institutions, interest groups, and magazines and announcements published by farmers’ associations. In particular, by contacting agricultural magazines/media and farmers’ associations in all Federal States of Germany, we aimed to obtain a regionally balanced sample (see Appendix A, Table A1 for complete list). In addition, we offered non-cash rewards to increase motivation for Agronomy 2021, 11, x FOR PEER REVIEW 4 of 25 Agronomy 2021, 11, 969 4 of 24 we aimed to obtain a regionally balanced sample (see Appendix A, Table A1 for complete participation. The survey was active from February to April 2017. To conduct the survey, we list). In addition, we offered non-cash rewards to increase motivation for participation. used Thethe surv softwar ey was eac LimeSurvey tive from Fe.br The uary questionnair to April 2017. e consisted To conduct t ofh5 e survey, w sections which e used the addressed variables softwarer Li ecognised meSurvey.fr The qu om the esti literatur onnaire c eoto nsisted o inﬂuence f 5 section pro-envir s whonmental ich addressed var behaviour ia- in a bles recognised from the literature to influence pro-environmental behaviour in a broader broader sense: 1. general information on the farm, 2. crop rotation and soil tillage, sense: 1. general information on the farm, 2. crop rotation and soil tillage, 3. perception of 3. perception of and measures applied to prevent soil compaction, 4. technical equipment and measures applied to prevent soil compaction, 4. technical equipment and process or- and process organisation, and 5. use of consulting and information offers. We used ﬁve ganisation, and 5. use of consulting and information offers. We used five different ques- different question types. Single-choice questions were chosen for categories which were tion types. Single-choice questions were chosen for categories which were mutually ex- mutually exclusive. Multiple-choice questions were asked when a selection of expected clusive. Multiple-choice questions were asked when a selection of expected answers was answers was known but not mutually exclusive. Open-text/numeric questions were asked known but not mutually exclusive. Open-text/numeric questions were asked when the when the answers were unperceivable or when a number was required. For personal answers were unperceivable or when a number was required. For personal assessments, assessments, a ﬁve-point rating scale was chosen. When a speciﬁcation of categories was a five-point rating scale was chosen. When a specification of categories was desired, the desired, the multiple- and single-choice questions were combined with open-text questions. multiple- and single-choice questions were combined with open-text questions. In total, In total, the survey was accessed 285 times, of which 124 respondents dropped out before the survey was accessed 285 times, of which 124 respondents dropped out before the ques- the tions o questions f intereof st ( inter Sectiest on 3 (Section ). Of the rem 3). Of aining the 1 r6 emaining 1 observations, 161 observations, only those which only report those ed which practicing arable farming were included in the evaluation presented here. The remaining reported practicing arable farming were included in the evaluation presented here. The 154 observations were included in the further analyses. Not all of them were complete, remaining 154 observations were included in the further analyses. Not all of them were and, therefore, the number of observations considered for each question varies and is in- complete, and, therefore, the number of observations considered for each question varies dicated accordingly. To evaluate variables influencing the application of measures, we and is indicated accordingly. To evaluate variables inﬂuencing the application of measures, adopted the scheme of Bartkowski and Bartke [51] and allocated the variables queried to we adopted the scheme of Bartkowski and Bartke [51] and allocated the variables queried the respective groups (Figure 1). to the respective groups (Figure 1). Figure 1. Theoretical framework for the evaluation of variables affecting the application of measures. Modiﬁed according to Figure 1. Theoretical framework for the evaluation of variables affecting the application of measures. Modified according Bartkowski and Bartke [51]. to Bartkowski and Bartke [51]. In group (1), we included the variables education, function, age, and full-/part- In group (1), we included the variables education, function, age, and full-/part-time occupation. For group (2), we captured the variables problem perception and organic/con- time occupation. For group (2), we captured the variables problem perception and or- ventional management as an indicator of environmental attitude. For group (3), we cap- ganic/conventional management as an indicator of environmental attitude. For group (3), tured the variables farm size, share of rented land, machinery, crop rotation, and soil char- we captured the variables farm size, share of rented land, machinery, crop rotation, and acteristics. For group (4), we recorded the variables use of advisory service, and for group soil characteristics. For group (4), we recorded the variables use of advisory service, and for group (5), the variables estimated yield loss by soil compaction and farm diversiﬁ- cation. It should be noted that the allocation of variables to the respective groups was partly subjective. For example, the variable full-/part-time occupation was allocated to “characteristics of the farmer” because it can inﬂuence focus and prioritisation in terms of how much time and money a farmer invests. Another scientist could assign this variable to Agronomy 2021, 11, 969 5 of 24 the “economic conditions” (see Appendix B, Table A2 for questions, question type, and unit). We distinguished the applied measures, which we asked as multiple-choice ques- tions, into three groups. The ﬁrst differentiation was made according to the effects on soil compaction into direct and indirect effects. The second differentiation was made according to the type of measure. This resulted in the ﬁrst group of “agronomic” measures with a more indirect effect in terms of soil compaction. The second group consists of measures with a direct effect on soil compaction of the type “tyre/chassis”, which are associated with a low planning effort (adjusting the internal tyre pressure), are well known (wide tyres), or are partly standard from the manufacturer (rubber tracks). The third group also consists of measures with a direct effect, but of the type “planning/management”, which are associated with a much greater long-term planning effort (adapt machine utilisation scope) or a short-term crop and operation speciﬁc management with additional machine capacity requirement (separation of ﬁeld and street transport) (Table 1). Table 1. Asked measures and corresponding grouping. Asked Measure Effect on Soil Compaction Type of Measure direct seeding indirect agronomic cultivation of cover crops indirect agronomic no-turn tillage indirect agronomic adjusting the internal tyre pressure (with tyre inﬂation system or quick direct tyre/chassis exhaust valves for manual pressure control) soil protecting tyres (e.g., twin tyres, rubber track, wide tyres), direct tyre/chassis crab steering direct tyre/chassis adoption of the machine utilisation scope to trafﬁcable period direct planning/management separation of ﬁeld and street transport in manure spreading direct planning/management separation of ﬁeld and street transport at harvest direct planning/management For a deeper evaluation of the variables inﬂuencing the application of measures, we focused on the direct measures of the group “planning/management”. We did so because these measures are less promoted and more complex than those of the group “tyre/chassis” and have a kind of innovative character and are therefore subject to special consideration within this analysis. Statistical data from the survey year (2017) were used to contextualise our dataset, but for some characteristics, the most recent data were taken from the Farm Structure Survey in 2016 (FSS 2016). We used descriptive statistics; additionally, the chi-square test at p 0.05 for categorical data was used to evaluate signiﬁcant differences between observed and expected distributions between the groups “measure applied” and “no measure applied” among the tested variables. For numerical data, the t-test was used to assess whether the dif- ferences in the expression of the variables between the group applying direct measures and the group not applying direct measures of type “planning/management” were assumed to be signiﬁcant at p 0.05. The exact p values are provided at the appropriate places. 3. Results and Discussion 3.1. General Description of the Dataset Out of the 154 observations, the largest proportion of respondents were from Lower Saxony (32%), followed by Bavaria (16%), Baden-Würtemberg (8%), and Northrhine- Westphalia (7%) (Table 2). The remaining federal states were represented with 1–5% of the respondents, except the city states Berlin, Hamburg, Bremen and Saarland, and Rhineland- Palatinate, with no respondents. The location was not speciﬁed by 20%. A comparison of the distribution of farms with the real distribution of arable farms in Germany as captured by FSS 2016 indicated that our dataset overrepresented Lower Saxony and underrepre- sented Bavaria [56]. The remaining federal states were quite well represented. Agronomy 2021, 11, 969 6 of 24 Table 2. Distribution of participating farmers in our dataset (n = 154) (Germany-wide survey: “Technical soil protection” 2017) and of arable farms captured by the Farm Structural Survey (FSS) 2016 [56] across the federal states of Germany. Federal State Our Dataset Statistics (FSS 2016) Lower Saxony 32% 15% Bavaria 16% 35% Baden-Würtemberg 8% 13% Northrhine-Westphalia 7% 13% Hesse 5% 6% Schleswig Holstein 3% 4% Thuringia 3% 1% Saxony 3% 2% Mecklenburg Western 1% 2% Pomerania Brandenburg 1% 2% Saxony-Anhalt 1% 2% With 86%, the majority of the participants were the farm managers, 7% were family member employees, 1% non-family member employees, and 5% had another function or did not respond to this question. While the ofﬁcial statistics for Germany showed an employment rate of 48% full-time and 52% part-time (FSS 2016, [57]), the majority in our dataset were running the farm full-time (76%) and the smaller share part-time (22%). A small share gave no answer (2%) (Table 3). Thus, the group of full-time farmers was overrepresented in our dataset. Table 3. Distribution of participating farmers in our dataset (n = 154) (Germany-wide survey: “Technical soil protection” 2017) and ofﬁcial statistics (FSS 2016 [57] and 2017 [58]) according to different features for our dataset. Feature Our Dataset Statistics Year of Statistics full-time 76% 48% 2016 (FSS) part-time 22% 52% 2016 (FSS) organic 13% 11% 2017 conventional 85% 89% 2017 university degree 35% 9% 2016 (FSS) The smaller share of participants practiced organic farming, with 13%, and the larger share of 85% practiced conventional farming; 2% gave no information on this. For the year 2017, the ofﬁcial statistics reported that 11% of the farms in Germany practiced organic farming [58], which was quite well-represented in our dataset (Table 3). With 35% of the farm managers having a university degree in our dataset, this group was overrepresented compared to the ofﬁcial statistics for arable farms in Germany, with 9% (FSS 2016, [58]) (Table 3). The majority (68%) of the corresponding farms in our dataset had a total area of arable land between 50 and <500 ha, whereas our dataset slightly underrepresented the farm groups below <50 ha and overrepresented the farms 50 ha (Table 4). Agronomy 2021, 11, x FOR PEER REVIEW 7 of 25 Agronomy 2021, 11, 969 7 of 24 arable land between 50 and <500 ha, whereas our dataset slightly underrepresented the farm groups below <50 ha and overrepresented the farms ≥50 ha (Table 4). Table 4. Distribution of participating farmers in our dataset (Germany-wide survey: “Technical soil protection” 2017) and ofﬁcial statistics [58] according to arable land. Table 4. Distribution of participating farmers in our dataset (Germany-wide survey: “Technical soil protection” 2017) and official statistics [58] according to arable land. Arable Land Our Dataset Statistics 2017 Arable Land Our Dataset Statistics 2017 under 5 3% 3% under 5 3% 3% 5–<10 1% 12% 5–<10 1% 12% 10–<20 5% 19% 10–< 20–<5020 5% 16% 19% 27% 50–<100 29% 21% 20–<50 16% 27% 100–<500 39% 16% 50–<100 29% 21% 500 9% 2% 100–<500 39% 16% ≥500 9% 2% The mean area of cultivated arable land was 314 ha (standard derivation SD = 193 ha) The mean area of cultivated arable land was 314 ha (standard derivation SD = 193 ha) and 45 ha of grassland (SD = 7 ha), the most powerful tractor had a mean power of 182 hp and 45 ha of grassland (SD = 7 ha), the most powerful tractor had a mean power of 182 hp (SD = 76 hp), and the share of rented land was 50% (SD = 30%). (SD = 76 hp), and the share of rented land was 50% (SD = 30%). 3.2. Perception of Soil Compaction 3.2. Perception of Soil Compaction To investigate the perception of soil compaction, we asked the farmers about the To investigate the perception of soil compaction, we asked the farmers about the rel- relevance of soil compaction for their own farm (n = 152) and for Germany (n = 153). For evance of soil compaction for their own farm (n = 152) and for Germany (n = 153). For Germany, six participants answered “can not judge”; for their own farms, none did so. Germany, six participants answered “can not judge”; for their own farms, none did so. In In general, from “not relevant at all” to “very relevant” on a ﬁve-point rating scale, the general, from “not relevant at all” to “very relevant” on a five-point rating scale, the num- number of answers increased more strongly for Germany than for participants’ own farms ber of answers increased more strongly for Germany than for participants’ own farms (Figur (Fige ure 2). 2). FigureFigure 2. 2. Perception Percepof tion of soil co soil compaction mpaction for p for participants’ articipants’ ow own n fa farms rms (n = 15 (n = 152) 2) and for Ger and for Germany many (n = 153). (Germany-wid (n = 153). (Germany-wide e survey: “Technical soil protection” 2017). survey: “Technical soil protection” 2017). Whereas 76% of the 152 participants who answered this question perceived soil com- Whereas 76% of the 152 participants who answered this question perceived soil paction as “relevant” or “very relevant” (point 4 and 5 on the rating scale) for Germany, compaction as “relevant” or “very relevant” (point 4 and 5 on the rating scale) for Germany, just 57% did so for their own farm. On the contrary, 8% perceived soil compaction as “not just 57% did so for their own farm. On the contrary, 8% perceived soil compaction as “not relevant” or “not relevant at all” (point 1 and 2 on the rating scale) for Germany and 27% relevant” or “not relevant at all” (point 1 and 2 on the rating scale) for Germany and 27% for their own farm. We cannot exclude the possibility that the stated high relevance and for their own farm. We cannot exclude the possibility that the stated high relevance and sensitivity to soil compaction issues is a result of the recruiting procedure. Therefore, we sensitivity to soil compaction issues is a result of the recruiting procedure. Therefore, we assume that “innovators” and “early adaptors” are somewhat overrepresented. Around assume that “innovators” and “early adaptors” are somewhat overrepresented. Around 60% rated the relevance higher for Germany than for their own farm and around 40% the 60% rated the relevance higher for Germany than for their own farm and around 40% the other way around (Figure 3). other way around (Figure 3). Agronomy 2021, 11, 969 8 of 24 Agronomy 2021, 11, x FOR PEER REVIEW 8 of 25 Figure 3. Number of estimates of the relevance of soil compaction per scale unit (1–5 rating scale) for participants’ own Figure 3. Number of estimates of the relevance of soil compaction per scale unit (1–5 rating scale) for participants’ own farms and for Germany, dark grey = same relevance estimated for participants’ own farms and for Germany; light grey = farms and for Germany, dark grey = same relevance estimated for participants’ own farms and for Germany; light grey = higher relevance estimated for Germany than for participants’ own farm; n = 145. (Germany-wide survey: “Technical soil protection” 2017). higher relevance estimated for Germany than for participants’ own farm; n = 145. (Germany-wide survey: “Technical soil protection” 2017). In their study, Thorsøe et al. [35] detected similar patterns for Denmark, as 77% of the respondents regarded soil compaction as a “high” or “considerable” risk for Danish In their study, Thorsøe et al. [35] detected similar patterns for Denmark, as 77% of farming, and 39% for their own farm. There seems to be a gap between the individual and the respondents regarded soil compaction as a “high” or “considerable” risk for Danish the overarching, collective concern. Since soil compaction is a difficult topic with complex farming, under and lyin39% g processe for s (“w theiricked problem own farm.” The as descr re seems ibed by Thorsø to be e a et al. gap[35]), between one expla the - individual nation could be that individuals underestimate their exposure as a kind of moral exclu- and the overarching, collective concern. Since soil compaction is a difﬁcult topic with sion. Opotow et al. [59] described moral exclusion as a way to avoid the complexity and complex underlying processes (“wicked problem” as described by Thorsøe et al. [35]), ambiguity of environmental problems. This moral exclusion leads to an underestimation one explanation could be that individuals underestimate their exposure as a kind of of environmental threats to one’s own land [60,61]. However, the results of our survey moral exclusion. Opotow et al. [59] described moral exclusion as a way to avoid the may have further explanations. Using the argumentation of Dessart et al. [61], perception is influenced by what others do or say—in other words, by the social system. Conse- complexity and ambiguity of environmental problems. This moral exclusion leads to quently, the increased perception of soil compaction as a problem for Germany compared an underestimation of environmental threats to one’s own land [60,61]. However, the to participants’ own farms can be seen as a result of social norms and expectations. This results of our survey may have further explanations. Using the argumentation of Dessart may in turn be reinforced by the increased media coverage of the issue of soil compaction et al. [61], perception is inﬂuenced by what others do or say—in other words, by the in agriculture. social system. As a second Consequently indicator f,othe r the percepti increased on of per soil ception compacof tion, we soil compaction asked about the esti- as a problem for mated yield loss due to and the area affected by soil compaction. This question was only Germany compared to participants’ own farms can be seen as a result of social norms and posed to participants who rated the relevance of soil compaction for their own farm as 3 expectations. This may in turn be reinforced by the increased media coverage of the issue or higher (n = 106). The mean area affected was estimated to be 17% (median 10%) and the of soil compaction in agriculture. correspondent yield loss (n = 105) on the affected area to be 22% (median 20%) (Figure 4). As a second indicator for the perception of soil compaction, we asked about the estimated yield loss due to and the area affected by soil compaction. This question was only posed to participants who rated the relevance of soil compaction for their own farm Agronomy 2021, 11, x FOR PEER REVIEW 9 of 25 as 3 or higher (n = 106). The mean area affected was estimated to be 17% (median 10%) and the correspondent yield loss (n = 105) on the affected area to be 22% (median 20%) (Figure 4). Figure 4. Estimated area affected by, and yield loss due to, soil compaction in percent (Box: 25– Figure 4. Estimated area affected by, and yield loss due to, soil compaction in percent (Box: 25–75% 75% quantile; line in box: median (50% quantile), cross: mean, lower whisker: Q1–1.5 * inter-quar- quantile; line in box: median (50% quantile), cross: mean, lower whisker: Q1–1.5 * inter-quartile tile range (IQR), upper whisker: Q3 + 1.5 * IQR, points: outlier). (Germany-wide survey: “Technical soil protect range (IQR), ion” 2017). upper whisker: Q3 + 1.5 * IQR, points: outlier). (Germany-wide survey: “Technical soil protection” 2017). Above the 75% quantile, the mean area affected was 44%, with a higher mean esti- mated yield loss than the total mean of 26%. Below the 25% quantile, values were 1% and 17%, respectively. When multiplying the share of affected compacted area with the corre- sponding yield loss, the mean estimated “effective” yield loss was 3% (max. = 36%; min. = 0%). The results are in line with findings from Schleswig-Holstein, where farmers esti- mated 10% of their land to be affected by soil compaction, but the estimated yield loss was higher, ranging from 5 to 9% [62]. Scientific research to estimate yield effects of soil com- paction is diverse in terms of investigated soils, crops, weather conditions, and machine configurations and varies on a wide range along these factors. Keller et al. [7] and Chamen et al. [37] gave an overview of numerous individual studies in their reviews and reported yield effects due to soil compaction between −2.5 and −27% (mean = −11%, number of studies cited = 15) and between +12 and −47% (mean = −16%, number of studies cited = 35), respectively. To gain an insight into how farmers perceive soil compaction, we asked how they recognised that their fields may be affected. Out of 154 participants, 94 perceived soil com- paction based on different indicators, which they were asked to name in a free-text ques- tion; multiple answers were possible. Of these, 50 participants named one indicator, 35 mentioned two, eight mentioned three, and one mentioned four indicators. Visual com- paction phenomena were most often referred to (44 times) (Figure 5). The major state- ments in this indicator category were waterlogging on the field and visible traffic lanes in the field. Plant physiological indicators such as growth depressions or restricted root growth were mentioned 42 times, followed by other indicators which could not be clearly assigned to one of the other categories, such as plough sole or compaction with 31 mentions. Economic indicators such as yield decrease or yield loss were mentioned 25 times. In the category pests and diseases, with two mentions, increased abundance of field horsetail and fungal infection were specified. For soil biological indicators, with also two mentions, improvement of the soil life and less earthworms were mentioned. Agronomy 2021, 11, 969 9 of 24 Above the 75% quantile, the mean area affected was 44%, with a higher mean esti- mated yield loss than the total mean of 26%. Below the 25% quantile, values were 1% and 17%, respectively. When multiplying the share of affected compacted area with the corresponding yield loss, the mean estimated “effective” yield loss was 3% (max. = 36%; min. = 0%). The results are in line with ﬁndings from Schleswig-Holstein, where farmers estimated 10% of their land to be affected by soil compaction, but the estimated yield loss was higher, ranging from 5 to 9% [62]. Scientiﬁc research to estimate yield effects of soil compaction is diverse in terms of investigated soils, crops, weather conditions, and machine conﬁgurations and varies on a wide range along these factors. Keller et al. [7] and Chamen et al. [37] gave an overview of numerous individual studies in their reviews and reported yield effects due to soil compaction between 2.5 and 27% (mean = 11%, number of studies cited = 15) and between +12 and 47% (mean = 16%, number of studies cited = 35), respectively. To gain an insight into how farmers perceive soil compaction, we asked how they recognised that their ﬁelds may be affected. Out of 154 participants, 94 perceived soil compaction based on different indicators, which they were asked to name in a free-text question; multiple answers were possible. Of these, 50 participants named one indicator, 35 mentioned two, eight mentioned three, and one mentioned four indicators. Visual compaction phenomena were most often referred to (44 times) (Figure 5). The major statements in this indicator category were waterlogging on the ﬁeld and visible trafﬁc lanes in the ﬁeld. Plant physiological indicators such as growth depressions or restricted root growth were mentioned 42 times, followed by other indicators which could not be clearly assigned to one of the other categories, such as plough sole or compaction with 31 mentions. Economic indicators such as yield decrease or yield loss were mentioned 25 times. In the category pests and diseases, with two mentions, increased abundance of ﬁeld horsetail and fungal infection were speciﬁed. For soil biological indicators, with also two mentions, improvement of the soil Agronomy 2021, 11, x FOR PEER REVIEW 10 of 25 life and less earthworms were mentioned. Figure 5. Percentage of perceived indicators for soil compaction, summarised in categories (n = 154). (Germany-wide sur- Figure 5. Percentage of perceived indicators for soil compaction, summarised in categories (n = 154). (Germany-wide vey: “Technical soil protection” 2017). survey: “Technical soil protection” 2017). Indicators can be distinguished into primary ones, which indicate directly the com- Indicators can be distinguished into primary ones, which indicate directly the com- paction itself, and secondary ones, which rather indicate the indirect effects. The indica- paction itself, and secondary ones, which rather indicate the indirect effects. The indicators tors listed up to this point, except the category others, describe the possible secondary listed up to this point, except the category others, describe the possible secondary effects effects of soil compaction. Generally, secondary effects are easier to detect and more visi- of soil compaction. Generally, secondary effects are easier to detect and more visible than ble than primary effects [63,64]. The soil physical indicators such as water storage or for- primary effects [63,64]. The soil physical indicators such as water storage or formation of clods, mation of clods, with two mentions, and in situ measurements such as spade, penetrologger, with two mentions, and in situ measurements such as spade, penetrologger, or soil penetrometer or soil penetrometer diagnosis, with six mentions, describe the primary effects of soil com- diagnosis, with six mentions, describe the primary effects of soil compaction (with hatching paction (with hatching in Figure 5). Such in situ measurements can detect changes in bulk in Figur densit ey5 , so ). il s Such truct in ure, and soil situ measur stements rength as a can didetect rect reschanges ult of the pro in bulk cess o density f soil co,mpaction soil structure, and [6soil 3,65,6 str 6]. W ength hile t as hese a dir ind ect icatr oesult rs are c of lea the rly mea process surabof le and sc soil compaction ientifically base [63d, ,65 th ,66 e pre- ]. While viously mentioned indicators of secondary effects are based more on perception and ex- these indicators are clearly measurable and scientiﬁcally based, the previously mentioned perience. Since this was a free-text question, the assignment of the answers to the respec- indicators of secondary effects are based more on perception and experience. Since this tive categories, especially for the secondary effects, is subjective. Nevertheless, these indi- was a free-text question, the assignment of the answers to the respective categories, espe- cators were observed clearly more frequently than those of the primary effects. We con- cially for the secondary effects, is subjective. Nevertheless, these indicators were observed clude that farmers either rely more on their perceptions and experience to identify soil clearly more frequently than those of the primary effects. We conclude that farmers either compaction, or that easily applicable and comprehensible methods to verify these percep- rely more on their perceptions and experience to identify soil compaction, or that easily tions are lacking in practice or not known. 3.3. Applied Measures The participants were asked what kind of measures they apply to prevent soil com- paction. Multiple answers were possible and 154 participants answered the question. As for the indirect, “agronomic” measures, 85% reported using at least one of them. In total, 94% of the farmers applied at least one direct measure to prevent soil compaction, 78% applied at least one measure of the group “tyre/chassis”, and 59% applied at least one measure of the group “planning/management” (Figure 6; for grouping, see Table 1). Agronomy 2021, 11, 969 10 of 24 applicable and comprehensible methods to verify these perceptions are lacking in practice or not known. 3.3. Applied Measures The participants were asked what kind of measures they apply to prevent soil com- paction. Multiple answers were possible and 154 participants answered the question. As for the indirect, “agronomic” measures, 85% reported using at least one of them. In total, 94% of the farmers applied at least one direct measure to prevent soil compaction, 78% Agronomy 2021, 11, x FOR PEER REVIEW 11 of 25 applied at least one measure of the group “tyre/chassis”, and 59% applied at least one measure of the group “planning/management” (Figure 6; for grouping, see Table 1). Figure 6. Applied measures, grouped by “tyre/chassis”, “planning/management”, and “agronomic measures” (n = 154). Figure 6. Applied measures, grouped by “tyre/chassis”, “planning/management”, and “agronomic measures” (n = 154). (Germany-wide survey: “Technical soil protection” 2017). (Germany-wide survey: “Technical soil protection” 2017). Cultivation of cover crops was most frequently mentioned within the group of “ag- Cultivation of cover crops was most frequently mentioned within the group of “agro- ronomic” measures (75%). Within “tyre/chassis” measures, soil-protecting tyres were nomic” measures (75%). Within “tyre/chassis” measures, soil-protecting tyres were most most often named (78%). Adjustment of internal tyre pressure (pressure adjustment with often named (78%). Adjustment of internal tyre pressure (pressure adjustment with tyre tyre inflation system or quick exhaust valves for manual pressure control) was stated to inﬂation system or quick exhaust valves for manual pressure control) was stated to be be applied by 56% of the participants. As the only available approximate estimate, Volk applied by 56% of the participants. As the only available approximate estimate, Volk [30] [30] estimated the number of users of tyre inflation systems at 10,000 in 2018 for Germany. estimated the number of users of tyre inﬂation systems at 10,000 in 2018 for Germany. With With 275,392 arable farms in 2016 (FSS [58]), this corresponds to a share of 4%. The adop- 275,392 arable farms in 2016 (FSS [58]), this corresponds to a share of 4%. The adoption tion rate of quick exhaust valves, which we asked in the same answer option, is probably rate of quick exhaust valves, which we asked in the same answer option, is probably a lot a lot higher, as they are easier to upgrade on the tyre and cheaper. However, no infor- higher, as they are easier to upgrade on the tyre and cheaper. However, no information on mation on this is available. Therefore, we cannot make a statement regarding the repre- this is available. Therefore, we cannot make a statement regarding the representativeness sentativeness of our sample in this respect. Within “planning/management” measures, adaption of machine utilisation scope was most often mentioned (32%), followed by sep- of our sample in this respect. Within “planning/management” measures, adaption of aration of street and field transport during manure application (27%) and during harvest machine utilisation scope was most often mentioned (32%), followed by separation of street (22%). The last mentioned measures of the “planning/management” group are addressed and ﬁeld transport during manure application (27%) and during harvest (22%). The last when talking about measures in the following chapters of this paper. In the evaluations, mentioned measures of the “planning/management” group are addressed when talking we focused on the comparison between the group that has applied these “planning/man- about measures in the following chapters of this paper. In the evaluations, we focused agement” measures (“measures applied”, 59%) and the group that has not applied them on the comparison between the group that has applied these “planning/management” (“no measure applied”, 41%). measures (“measures applied”, 59%) and the group that has not applied them (“no measure applied”, 41%). 3.4. Factors Influencing the Application of Measures 3.4.1. Objective Characteristics of the Farm 3.4. Factors Inﬂuencing the Application of Measures Within the objective characteristics of the farm, we considered the variables total ar- 3.4.1. Objective Characteristics of the Farm able land, the power of the most powerful tractor, the share of rented land, the share of Within the objective characteristics of the farm, we considered the variables total arable different crop-groups within the crop rotation, the area share of different soil textures land, the power of the most powerful tractor, the share of rented land, the share of different (light soils = predominantly sandy substrate; medium soils = predominantly silty/loamy substrate; heavy soils = predominantly clayey substrate), and the number of operations outsourced to contractors. The group of farmers “measure applied” cultivated 233 ha of arable land and the most powerful tractor had a mean power of 204 hp (Figure 7a,b). In the group of farmers named “no measure applied”, these were 134 ha and 158 hp, respec- tively. The differences between the two groups of farmers were significant for these two variables (ha arable land p = 0.02; hp most powerful tractor p = 0.0001). In the literature, Agronomy 2021, 11, 969 11 of 24 crop-groups within the crop rotation, the area share of different soil textures (light soils = predominantly sandy substrate; medium soils = predominantly silty/loamy substrate; heavy soils = predominantly clayey substrate), and the number of operations outsourced to contractors. The group of farmers “measure applied” cultivated 233 ha of arable land and the most powerful tractor had a mean power of 204 hp (Figure 7a,b). In the group of farmers named “no measure applied”, these were 134 ha and 158 hp, respectively. The differences Agronomy 2021, 11, x FOR PEER REVIEW 12 of 25 between the two groups of farmers were signiﬁcant for these two variables (ha arable land p = 0.02; hp most powerful tractor p = 0.0001). In the literature, the inﬂuence of farm size, here indicated by the area of arable land, on farmers’ participation in environmental the influence of farm size, here indicated by the area of arable land, on farmers’ participa- measures was reported to be contradictory [67]. Wuepper et al. [68], for example, concluded tion in environmental measures was reported to be contradictory [67]. Wuepper et al. [68], that small family farms are not principally more sustainably oriented. Van Vliet et al. [69] for example, concluded that small family farms are not principally more sustainably ori- stated that environmentally sustainable practices cannot be associated directly with farm ented. Van Vliet et al. [69] stated that environmentally sustainable practices cannot be as- size, and Novelli [70] supposed that farm size plays an important role in the decision sociated directly with farm size, and Novelli [70] supposed that farm size plays an im- making of farmers because it affects the emerging opportunity costs of a certain measure. It portant role in the decision making of farmers because it affects the emerging opportunity can be argued that larger farms have greater capacity in terms of machines and manpower costs of a certain measure. It can be argued that larger farms have greater capacity in terms to implement complex “planning/management” measures. of machines and manpower to implement complex “planning/management” measures. FigureFigure 7 7. Inﬂuence . Influeof nce the of the variables variables (a)(a arable ) arable lan land, d, ( (b b)) tra tractor ctor power, and ( power, andc()c share o ) sharef re ofnted rented land land per group “measure per group “measure applied” and “no measure applied” (Box: 25–75% quantile; line in box: median (50% quantile), cross: mean, lower whisker: applied” and “no measure applied” (Box: 25–75% quantile; line in box: median (50% quantile), cross: mean, lower whisker: Q1–1.5 * IQR, upper whisker: Q3 + 1.5 * IQR, points: outlier); different letters indicate statistically significant differences Q1–1.5 * IQR, upper whisker: Q3 + 1.5 * IQR, points: outlier); different letters indicate statistically signiﬁcant differences (t-test, p ≤ 0.05). (Germany-wide survey: “Technical soil protection” 2017). (t-test, p 0.05). (Germany-wide survey: “Technical soil protection” 2017). The share of rented land in percent was slightly, but not significantly (p = 0.12), higher The share of rented land in percent was slightly, but not signiﬁcantly (p = 0.12), higher for the group “measure applied” (Figure 7c). Caswell et al. [71] argued that farmers who for the group “measure applied” (Figure 7c). Caswell et al. [71] argued that farmers lease fields for long periods feel responsible to the landlord or are afraid of being held who lease ﬁelds for long periods feel responsible to the landlord or are afraid of being responsible for possible damages. Therefore, renters act the same as or similarly to land- held responsible for possible damages. Therefore, renters act the same as or similarly to owners with regard to soil protection. A similar conclusion was drawn by Leonhardt et landowners al. [72] for with Austri regar a, where d to t soil enure pr i otection. s seen as A a long similar -term choice conclusion and therefo was drawn re the land by Leonhar is dt treated equally in terms of soil protection. et al. [72] for Austria, where tenure is seen as a long-term choice and therefore the land is For the variables area share of soil textures and share of crops, the difference between treated equally in terms of soil protection. the groups of farmers “measure applied” and “no measure applied” was small and not For the variables area share of soil textures and share of crops, the difference between significant, except for the share of forage grass (area share of soil textures p = 0.47 (light the groups of farmers “measure applied” and “no measure applied” was small and not soils), 0.26 (medium soils), 0.19 (heavy soils); share of crops p = 0.36 (root crops), 0.25 signiﬁcant, except for the share of forage grass (area share of soil textures p = 0.47 (light (grains), 0.29 (maize), 0.05 (forage grass)), between 0 and 4% for soils and 0 and 5% for soils), 0.26 (medium soils), 0.19 (heavy soils); share of crops p = 0.36 (root crops), 0.25 crops (Figure 8a,b). (grains), 0.29 (maize), 0.05 (forage grass)), between 0 and 4% for soils and 0 and 5% for crops (Figure 8a,b). Agronomy 2021, 11, x FOR PEER REVIEW 13 of 25 Agronomy 2021, 11, 969 12 of 24 a a b a a apply not apply not apply apply n = 89 n = 61 n = 62 n = 91 (b) (a) Figure 8. Inﬂuence of the variables (a) area share of soil texture (light soils = predominantly sandy substrate; medium soils Figure 8. Influence of the variables (a) area share of soil texture (light soils = predominantly sandy substrate; medium soils = predominantly silty/loamy substrate; heavy soils = predominantly clayey substrate) and (b) share of crops per group = predominantly silty/loamy substrate; heavy soils = predominantly clayey substrate) and (b) share of crops per group “measure applied” and “no measure applied” (Box: 25–75% quantile; line in box: median (50% quantile), cross: mean, “measure applied” and “no measure applied” (Box: 25–75% quantile; line in box: median (50% quantile), cross: mean, lower lower whisker: Q1–1.5 * IQR, upper whisker: Q3 + 1.5 * IQR, points: outlier); different letters indicate statistically significant whisker: Q1–1.5 * IQR, upper whisker: Q3 + 1.5 * IQR, points: outlier); different letters indicate statistically signiﬁcant differences (t-test, p ≤ 0.05). (Germany-wide survey: “Technical soil protection” 2017). differences (t-test, p 0.05). (Germany-wide survey: “Technical soil protection” 2017). As soil texture is one of the most relevant factors (besides soil moisture at the time of As soil texture is one of the most relevant factors (besides soil moisture at the time of wheeling and loads applied) influencing the risk of soil compaction [73–77], we expected wheeling and loads applied) inﬂuencing the risk of soil compaction [73–77], we expected differentiation in the application of measures according to the area share of light, medium, differentiation in the application of measures according to the area share of light, medium, and heavy soil textures. However, we cannot confirm an effect of the dominant soil struc- and heavy soil textures. However, we cannot conﬁrm an effect of the dominant soil ture. In particular, root crops (sugar beet or potato) and (silage) maize harvests involve structure. In particular, root crops (sugar beet or potato) and (silage) maize harvests involve heavy machinery with harvest dates in late summer/fall. In Germany, considerable rain- fall often occurs at this time of year, making the soils susceptible to compaction. Therefore, heavy machinery with harvest dates in late summer/fall. In Germany, considerable rainfall we expected an impact on the grown crops but could not confirm any association. often occurs at this time of year, making the soils susceptible to compaction. Therefore, we In total, 130 participants answered the question regarding whether they engage ag- expected an impact on the grown crops but could not conﬁrm any association. ricultural contractors and 80% of them do so. For specifications of operations outsourced, In total, 130 participants answered the question regarding whether they engage multiple answers were possible. Among those who engage agricultural contractors, most agricultural contractors and 80% of them do so. For speciﬁcations of operations outsourced, often, harvest was mentioned to be outsourced (73%), followed by the application of liq- multiple answers were possible. Among those who engage agricultural contractors, most uid manure (56%), seeding (21%), others (18%, e.g., mulching or application of solid ma- often, harvest was mentioned to be outsourced (73%), followed by the application of liquid nure), tilling (10%), pest control (6%), and mineral fertilisation (4%). There was no influ- manure (56%), seeding (21%), others (18%, e.g., mulching or application of solid manure), ence of the number of outsourced operations on the application of measures to prevent tilling (10%), pest control (6%), and mineral fertilisation (4%). There was no inﬂuence soil compaction. The outsourcing of operations is a crucial factor for soil compaction risk of the number of outsourced operations on the application of measures to prevent soil on arable land, since “farmers partly lost control” [35,78] concerning the timing of field- compaction. The outsourcing of operations is a crucial factor for soil compaction risk on work and the machine used and its configuration (e.g., internal tyre pressure). Von Buttlar arable et al. [62] rep land, since orted that “farmers 91% of the partly farm lost ers p contr artol” icip[ at 35 in ,78 g in ] a concerning survey used the agtiming ricultura of l con ﬁeldwork - tractors or machinery cooperations, of which 43% state that soil-protecting technology is and the machine used and its conﬁguration (e.g., internal tyre pressure). Von Buttlar “used” or “mostly used”; in 25% of the cases, it is “partly used”, and in 33%, no such et al. [62] reported that 91% of the farmers participating in a survey used agricultural technology is used or it is not known. Besides this study, no information is available on contractors or machinery cooperations, of which 43% state that soil-protecting technology the use of soil-protecting technologies among agricultural contractors. Since agricultural is “used” or “mostly used”; in 25% of the cases, it is “partly used”, and in 33%, no such contractors play such a substantial role in minimising soil compaction on arable land, we technology is used or it is not known. Besides this study, no information is available on suggest investigating in more detail how the topic is integrated in these companies in or- the use of soil-protecting technologies among agricultural contractors. Since agricultural der to engage these stakeholders in soil conservation as well. contractors play such a substantial role in minimising soil compaction on arable land, we suggest investigating in more detail how the topic is integrated in these companies in order to engage these stakeholders in soil conservation as well. 3.4.2. Objective Characteristics of the Farmers To capture the objective characteristics of the farmers, we queried the highest level of agrarian education, age, their own function on the farm, and whether they run the farm full- or part-time. Within the group “measures applied” (n = 77), 44% were agricultural Agronomy 2021, 11, x FOR PEER REVIEW 14 of 25 Agronomy 2021, 11, 969 3.4.2. Objective Characteristics of the Farmers 13 of 24 To capture the objective characteristics of the farmers, we queried the highest level of agrarian education, age, their own function on the farm, and whether they run the farm full- or part-time. Within the group “measures applied” (n = 77), 44% were agricultural engineers/Master ’s degree holders, and within the group “no measures applied” (n = 55), engineers/Master’s degree holders, and within the group “no measures applied” (n = 55), this ﬁgure was 27% (Figure 9). this figure was 27% (Figure 9). Figure 9. Percentage of agrarian education type by the groups “measure applied” and “no measure applied” (n = 77) Figure 9. Percentage of agrarian education type by the groups “measure applied” and “no measure applied” (n = 77) and and “no measure applied” (n = 55). (Germany-wide survey: “Technical soil protection” 2017). “no measure applied” (n = 55). (Germany-wide survey: “Technical soil protection” 2017). The share of master training (in German, “Meisterabschluss”) of all education types The share of master training (in German, “Meisterabschluss”) of all education types was 30 and 33% for the groups “measures applied” and “no measures applied”, respec- was 30 and 33% for the groups “measures applied” and “no measures applied”, respectively. tively. The share of farmers who were state-certified technicians was 9 and 4% and the The share of farmers who were state-certiﬁed technicians was 9 and 4% and the share who share who had formal agricultural training was 8 and 16% in the group “measures ap- had plied formal ” and in agricultural the other group, respect training was i8 vely. The ch and 16% in i-sq the uare t group est in “measur dicated no essig applied” nificanceand in the(p other = 0.08) group, for the distribut respectively ion of the deg . The chi-squar reese , even w test indicated hen aggno regating univer signiﬁcancesity (p degrees = 0.08) for the and non-university degrees before statistical evaluation. However, other studies found distribution of the degrees, even when aggregating university degrees and non-university the level of education to be a critical variable influencing pro-environmental behaviour degrees before statistical evaluation. However, other studies found the level of education to among farmers [79–81] and scientists are calling for more education, especially in the field be a critical variable inﬂuencing pro-environmental behaviour among farmers [79–81] and of soil protection [82,83]. We suggest that our results do not follow this general recom- scientists are calling for more education, especially in the ﬁeld of soil protection [82,83]. We mendation since an agricultural degree can be obtained in different ways in Germany: suggest that our results do not follow this general recommendation since an agricultural there is the possibility of studying agriculture at university, where (presumably) rather degree can be obtained in different ways in Germany: there is the possibility of studying theoretical expertise is taught, or the option to follow a formal vocational training, which agriculture at university, where (presumably) rather theoretical expertise is taught, or the is more focused on practical knowledge. Moreover, informal education in the sense of option to follow a formal vocational training, which is more focused on practical knowledge. social learning has been reported to play a significant role in strengthening sustainable Moreover, informal education in the sense of social learning has been reported to play a agriculture [84,85], as sharing information and learning in a group of peers can shift social signiﬁcant norms [60]. To date, ther role in strengthening e are no sustainable studies on ho agricultur w the topi e c of [84 soi ,85], l compa as sharing ction is informati included on and learning in the cin urra icula of different group of peers types o can shift f stud social y and t norms raining[ in 60 G ].eT rm o an date, y. We ther cons e ar ider e t no hat studies this on open question needs illumination first in order to strengthen formal education in terms of how the topic of soil compaction is included in the curricula of different types of study and soil compaction. training in Germany. We consider that this open question needs illumination ﬁrst in order We asked the age by ranges (n = 133), with the result that the shares of the respond- to strengthen formal education in terms of soil compaction. ents within the respective ranges were only slightly shifted between the group “measures We asked the age by ranges (n = 133), with the result that the shares of the respondents applied” and “no measures applied”. No significant (p = 0.82) difference was found for within the respective ranges were only slightly shifted between the group “measures this characteristic, although younger people displayed a higher level of environmental applied” and “no measures applied”. No signiﬁcant (p = 0.82) difference was found for awareness [86]. On the other hand, it could be argued that older farmers apply more soil- this characteristic, although younger people displayed a higher level of environmental conserving measures due to the experience and knowledge gained in their working life awareness [86]. On the other hand, it could be argued that older farmers apply more [87]. While Knowler and Bradshaw [88] explored in the wider field of conservation agri- soil-conserving measures due to the experience and knowledge gained in their working culture both positive and insignificant correlations between adoption and experience, we life [87]. While Knowler and Bradshaw [88] explored in the wider ﬁeld of conservation found no significant connection here, assuming that age equals experience. agricultur Furt eher, bothwe com positive pared andth insigniﬁcant e groups “mcorr easuelations re applieb d” and etween “no m adoption easure ap andp experience, lied” among different the functions (manager, not the farm manager) of those running the farm. we found no signiﬁcant connection here, assuming that age equals experience. Further, we compared the groups “measure applied” and “no measure applied” among different the functions (manager, not the farm manager) of those running the farm. The largest share in our dataset (88%) were the farm manager. Among the farm managers, a larger proportion applied measures than not. Non-farm managers showed the reverse trend, without signiﬁcance (p = 0.16) for this variable (Table 5). Agronomy 2021, 11, 969 14 of 24 Table 5. Distribution between the groups “measure applied” and “no measure applied” according to participants’ own functions within the farm (n = 151) and whether the farm is run full-time or part-time (n = 151). Apply Not Apply a a not the farm manager (n = 18) 44% (8) 56% (10) a a farm manager (n = 133) 62% (82) 38% (51) a b farm run in full-time (n = 117) 65% (76) 35% (41) a b farm run in part-time (n = 34) 41% (14) 59% (20) Different letters indicate statistically signiﬁcant differences (chi-square test, p 0.05); absolute values given in brackets. (Germany-wide survey: “Technical soil protection” 2017). A signiﬁcant (p = 0.01) association between the groups “measure applied” and “no measure applied” and whether the farm is run full- or part-time was found (Table 5). Those who run the farm full-time were more likely to apply measures than those running the farm part-time. Of the 151 participants who answered the two previous questions, around half (48%) were farm managers who run the farm full-time. Murphy et al. [89] found that the more working time farmers spend on the farm, the more likely they are to participate in the Rural Environment Protection Program. 3.4.3. Behavioural Characteristics Behavioural characteristics describe, among others, the inﬂuence of the perceptions and attitudes of a farmer on decision making [61]. As an indicator for perception, we referred to the estimated relevance of soil compaction in Germany and in the participants’ own farms (Figure 2). Those participants who estimated soil compaction as not relevant for Germany (point 1 and 2 on the rating scale) all belonged to the group “measure applied” (Table 6). Of those respondents who rated soil compaction for Germany as relevant (point 4 and 5 on the rating scale), around half applied the measures. The chi-square test suggested a signiﬁcant (p = 0.001) association between the estimated relevance of soil compaction for Germany and the application of measures. Since the subsample not relevant for Germany was relatively small, this result should not be overinterpreted. Table 6. Distribution between the groups “measure applied” and “no measure applied” according to the perception of soil compaction (sc) for participants’ own farms, for Germany, and according to management. Apply Not Apply a b sc for Germany not relevant (n = 12) 100% (12) 0% (0) a b sc for Germany relevant (n = 116) 52% (60) 48% (56) a a sc for own farm not relevant (n = 42) 67% (28) 33% (14) a a sc for own farm relevant (n = 87) 59% (51) 41% (36) a a conventional (n = 131) 63% (82) 37% (49) a a organic (n = 20) 40% (8) 60% (12) Different letters indicate statistically signiﬁcant differences (chi-square test, p 0.05); absolute values given in brackets. (Germany-wide survey: “Technical soil protection” 2017). In both groups for which soil compaction for participants’ own farms is estimated as relevant or not relevant, the majority of participants applied measures (59 and 67%), and the difference was not signiﬁcant (p = 0.38). Even if the perception of environmental risks can inﬂuence the application of measures to prevent them [61], there was no unambiguous direction in our evaluation. Moreover, those participants who rated soil compaction to be not relevant did rather apply measures to prevent it than the others. There are studies reporting positive effects of individual risk perception on the pro-environmental behaviour of farmers (e.g., [90,91]), no signiﬁcant effect [92], and even a mismatch between risk perception and risk management strategies [93]. The expression of a perception Agronomy 2021, 11, x FOR PEER REVIEW 16 of 25 Agronomy 2021, 11, 969 15 of 24 not relevant did rather apply measures to prevent it than the others. There are studies involves a prominent psychological component and other studies already described similar reporting positive effects of individual risk perception on the pro-environmental behav- iour discr ofepancies farmers (e. between g., [90,91per ]), no ception signific and ant eaction ffect [92], [94and ] as even we found a mismatch here. between risk perception an As an indicator d risk man for agethe ment strateg environmentally ies [93]. The e friendly xpression attitude, of a perception we referred involves to whether the a prominent psychological component and other studies already described similar dis- farm is managed conventionally or organically, assuming that organic farmers are more crepancies between perception and action [94] as we found here. environmentally aware. However, among the conventional farmers, more participants As an indicator for the environmentally friendly attitude, we referred to whether the applied measures (63%), and among the organic farmers, who were clearly a smaller farm is managed conventionally or organically, assuming that organic farmers are more subsample here, the majority of participants did not apply measures (60%), but this ﬁgure environmentally aware. However, among the conventional farmers, more participants ap- was not signiﬁcant (p = 0.06) (Table 6). This is in line with the study of McCan et al. [94], plied measures (63%), and among the organic farmers, who were clearly a smaller sub- who found no clear indication that organic farmers have a higher environmental awareness, sample here, the majority of participants did not apply measures (60%), but this figure as they previously hypothesised. Michel-Guillou and Moser [95] concluded that social was not significant (p = 0.06) (Table 6). This is in line with the study of McCan et al. [94], variables had a greater inﬂuence on pro-environmental behaviour than environmental who found no clear indication that organic farmers have a higher environmental aware- awareness. In fact, it is difﬁcult to imply that organic farmers are less environmentally ness, as they previously hypothesised. Michel-Guillou and Moser [95] concluded that so- friendly based on the results that they apply fewer of the measures considered. As McCann cial variables had a greater influence on pro-environmental behaviour than environmen- ta et l aw al. arene [94]snoted s. In fact in , it their is difstudy ficult t,oor im ganic ply thfarmers at organic achieve farmers a higher re less envi sustainability ronmentally through a friendly based on the results that they apply fewer of the measures considered. As variety of measures in the areas of fertilisation, winter cover crops, and diversity of crop McCann et al. [94] noted in their study, organic farmers achieve higher sustainability rotations. through a variety of measures in the areas of fertilisation, winter cover crops, and diver- sity of crop rotations. 3.4.4. Social–Institutional Characteristics Around 35% (n = 54) of the participants claimed to use advisory services, 51% (n = 79) 3.4.4. Social–Institutional Characteristics did not, and 14% (n = 21) did not answer this question. In the group “measure applied”, Around 35% (n = 54) of the participants claimed to use advisory services, 51% (n = more participants use advisory services; in the group “no measure applied”, it is the other 79) did not, and 14% (n = 21) did not answer this question. In the group “measure applied”, way around (Table 7). The differences in the distributions are not signiﬁcant (p = 0.18). more participants use advisory services; in the group “no measure applied”, it is the other way around (Table 7). The differences in the distributions are not significant (p = 0.18). Table 7. Number of participants who use or do not use advisory services in general and corresponding Table 7. numbers Number of parti within the gr coups ipants who use “measur or e applied” do not usand e advi “no sory s measur ervices in general e applied”. and corre- sponding numbers within the groups “measure applied” and “no measure applied”. Apply Not Apply Apply Not Apply a a Use of advisory services (n = 54) 65% (35) 35% (19) a a Use of advisory services (n = 54) 65% (35) 35% (19) a a No use of advisory services (n = 79) 53% (42) 47% (37) a a No use of advisory services (n = 79) 53% (42) 47% (37) Different letters indicate statistically signiﬁcant differences (chi-square test, p 0.05); absolute values given in Different letters indicate statistically significant differences (chi-square test, p ≤ 0.05); absolute val- brackets. (Germany-wide survey: “Technical soil protection” 2017). ues given in brackets. (Germany-wide survey: “Technical soil protection” 2017). The type of advisory service used was also asked and multiple answers were possible. The type of advisory service used was also asked and multiple answers were possi- bPr le. P ofessional rofessional associations associations were were mentioned mentioned 37 times (Figure 37 times (Figur 10). e 10). Figure 10. Use of advisory service by type of service (n = 54). (Germany-wide survey: “Technical Figure 10. Use of advisory service by type of service (n = 54). (Germany-wide survey: “Technical soil soil protection” 2017). protection” 2017). Germany-speciﬁc professional associations such as GKB e. V. (society for conservation tillage), Bioland e.V. (association for organic farming in Germany), or DLG (German Agri- cultural Society) were mentioned most often, namely 37 times. This is followed by private advisory services, with 20 mentions; the chamber of agriculture, with 19 mentions; public Agronomy 2021, 11, 969 16 of 24 authorities (“Ofﬁzialberatung” in German), with 18 mentions, and others, with 10 men- tions. Within the category “others”, the Swiss online tool Terranimo [96] was mentioned, as well as agricultural magazines. Marx and Jacobs [97] concluded in their overview of ofﬁcial recommendations for action and advisory material concerning soil compaction in Germany that some of the existing recommendations on national and federal state level are partly difﬁcult to access or out of date. Therefore, they advocated for easier access to recommendations and advisory tools and for more target-group-orientated presentation and modern design. In our study, the professional associations were mentioned twice as often as the ofﬁcial state institutions. An alternative explanation is that organisations with an agricultural background are more likely to be seen as a reliable peer group and are therefore used more often [60]. However, it should also be noted that the advisory structure in Germany varies from region to region. In Southern Germany, advice is mainly provided by ofﬁcial state institutions; in the north-west, it is mainly by chambers of agriculture; and in the east, private advisory services dominate [98]. 3.4.5. Economic Conditions In our survey, economic conditions were captured by estimated yield loss and farm diversiﬁcation. In total, 106 and 105 participants estimated the affected area by and yield loss due to soil compaction (see Section 3.2). For comparison purposes, the surveyed yield loss and the affected area were multiplied because, otherwise, for example, an estimated yield loss of 50% on a corresponding area of 1% could not be compared to the same yield loss on an estimated area of 20%. There was a signiﬁcant difference in the estimated “effective” yield loss (estimated yield loss multiplied by the estimated share of affected compacted area) between the group “measures applied” and the group “no measures applied”, with a mean of 3% and 6% yield loss, respectively. Therefore, we assume that the greater the estimated yield loss—hence, the level of one’s own risk—the more likely farmers are to apply complex “planning/management” measures. The prerequisite for an appropriate reaction on a perceived risk is understanding and knowledge about possible interventions. In order to characterise the diversity of the farms, we asked if there was any other farm activity besides arable farming. Business diversiﬁcation can broaden the income base and enhance the viability of a business [99]. Income dependency on arable products can be reduced, highlighting the compelling need to maintain a productive soil through soil conservation measures. In all four groups of farming sectors, a higher percentage applied measures than did not, and there was no signiﬁcant (p = 0.39) link between farm diversiﬁcation and the application of measures (Table 8). Table 8. Number of participants within each farming sector and corresponding numbers within the groups “measure applied” and “no measure applied” (n = 154). Apply Not Apply a a sector arable (n = 67) 57% (38) 43% (29) a a sector arable + livestock (n = 20) 75% (15) 25% (5) a a sector arable + grassland (n = 17) 65% (11) 35% (6) a a sector arable + grassland + livestock (n = 50) 54% (27) 46% (23) Different letters indicate statistically signiﬁcant differences (chi-square test, p 0.05); absolute values given in brackets. (Germany-wide survey: “Technical soil protection” 2017). Farm size is also an economic constraint. An increased farm size, where we observed a higher rate of the application of management measures (Figure 7a), may increase the farm income and also the capability of risk management [100]. Higher income, greater machinery, and human resources on larger farms allow ﬁnancial and organisational ﬂexibilities that are needed for the “planning/management” measures under consideration. They also require a certain amount of strategic thinking, as they are more organisational in nature and less based on technical solutions that are already more established (e.g., wide tyres). Agronomy 2021, 11, 969 17 of 24 An increasing farm size can foster innovation, whereas running the farm part-time, where we observed a lower rate of application of management measures (Table 5), can hold back innovations [101]. 3.5. Recommendations and Options for Action From our results, we derived various options for action that will support and promote soil conservation. They are: (1) an objective assessment of the relevance of soil compaction for farmers, (2) research and development activities to identify soil damage using non- invasive methods, and (3) recommendations for soil protection in agricultural practice. Measures in these three areas support different objectives, address different target groups, and can thus be used in the sense of a modular system. (1) We recommend the development of methods that allow farmers to conduct a “soil compaction” survey for their soils using low-threshold offers. Regional soil characteristics and crops grown, but also the use of already existing data, e.g., from ﬁeld documentation, need to be considered. There are already some methods in place, such as the “Simple soil structure assessment for the farmer” [102] or the “BASIS TERRA BOX” [103] with materials and a method manual for the analysis and evaluation of soil conditions. These are to be reﬁned and communicated more effectively (3, iii). The overall aim is to achieve a better self-assessment of the risk of soil compaction by farmers and thereby to promote the need of application of soil protection measures (3). (2) Activities to identify soil damage with non-invasive methods are currently in early research stage using close-range remote sensing via drones and remote sensing with satellite data. While close-up sensing allows short-term and event-related interventions, the analyses with remote sensing data are rather an evaluation of time series and images taken cannot be inﬂuenced by the researcher. Once these methods are applicable on a large scale, they can support the proposed actions (3), e.g., by identifying areas that are particularly threatened by or vulnerable to soil compaction and therefore deserve support. (3) In soil protection, three types of support can be distinguished: (i) investment support for technical measures, such as tyre pressure control systems, (ii) area-related support in the context of agri-environmental measures for the application of soil conserva- tion practices, and (iii) expansion of knowledge transfer to prevent soil compaction and disseminate soil conservation measures. (i) Investment support for the establishment of technical measures aims to increase equipment for the application of technical soil conser- vation measures by the farmer or the contractor. Advantageously, such funding is easy to administer. Disadvantages are the risk that investment supports may be taken up even though investments in soil conservation measures would also take place without it and the limited possibility to control application of technical measures. (ii) In the context of agri- environmental measures, the application of speciﬁc measures can be made more attractive through area-related support. The aim is to promote the use of soil-conserving measures speciﬁcally for critical works such as manure spreading in spring or sugar beet harvest. (iii) The expansion of knowledge transfer on soil conservation is aimed at professional farmers and contractors as well as those in training or education. In addition to traditional knowledge transfer activities, peer-to-peer formats should also be promoted. Particularly for education and training, it is important to examine how soil protection is currently addressed and which improvements are conceivable. The expansion of knowledge transfer can in turn promote the appropriate application of soil condition assessment methods by farmers (1) and the acceptance and uptake of possible funding options (i, ii). Regarding possible target groups, we see a need for action in addressing contractors, farmers in training and further education, as well as part-time farmers. For these target groups, it is necessary to create suitable information opportunities that address the speciﬁc needs (e.g., little timeframe for new impulses, narrow time windows for crop management). Agronomy 2021, 11, 969 18 of 24 4. Conclusions Our study is the ﬁrst record of the adoption of mitigation measures to avoid or reduce soil compaction in Germany, although we assume that a follow-up study with a larger and more representative sample size is needed. Farmers sometimes need to take contradictory requirements into account within their decisions (economics, market demands, delivery dates, arable restrictions), of which the avoidance of soil compaction is only one aspect [35]. Thus, the application of mitigation measures to prevent soil compaction seems rather to be seen as an add-on within the management when the farm is large enough to give economic ﬂexibilities for voluntary measures. We found few signiﬁcant differences between the group of farmers who apply measures and those who do not. However, it is important to keep in mind that a correlation is not a causality and that no single factor can be used to explain the application or non-application of soil conservation measures alone and that there might be socio-psychological components in addition to what a quantitative survey can cover [81,104]. Thus, we suggest qualitative follow-up in-depth surveys and interviews on variables which drive farmers during decisions pro or contra a measure. Against the background of supporting a transition of agricultural practices towards soil conservation, more educational work is needed. This concerns formal education as well as informal and advisory service since they shape the socio-psychological background of farmers. Author Contributions: Conceptualisation, S.L. and J.F.; Formal analysis, S.L.; Investigation, S.L. and J.F.; Project administration, A.J.; Writing—original draft, S.L.; Writing—review and editing, S.L., J.F. and A.J. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Federal Ministry of Education and Research—BMBF of Germany, grant number 031A563A (ﬁrst phase) and 031B0684A (second phase). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Detailed primary data and the full questionnaire in German and English are stored and published in the BonaRes Repository and are available online at: https: //doi.org/10.20387/bonares-k85p-tr5n (Ledermueller, S. & Fick, J. 2020). Acknowledgments: We thank all the farmers participating in our survey and the associations and professional magazines that made our survey public. Furthermore, we would like to thank Nele Gnutzmann, Kirstin Marx and Bernhard Osterburg for the preliminary work in the project and the review of the questionnaire. Additionally, we thank Norbert Röder for the consultation in the evaluation of the results. Conﬂicts of Interest: The authors declare no conﬂict of interest. Agronomy 2021, 11, 969 19 of 24 Appendix A Table A1. Overview of the used information channels to distribute the invitation to participate in the online survey. (Germany-wide survey: “Technical soil protection” 2017). Institutional Type Institution Information Channel farmers’ association of all 16 Federal States direct approach by phone and/or (e-)mail Chamber of agriculture of Lower Saxony direct approach by phone and/or (e-)mail Bioland regional associations press release/newsletter farmers’ association Naturland press release/newsletter Arbeitsgemeinschaft bäuerliche press release/newsletter Landwirtschaft e. V. Bauernbund press release/newsletter AgrarEurope press release Agrarheute.com press release Agrartechnik press release Agrarticker press release Agrartotal press release Agrarzeitung press release Bauernblatt Schleswig-Holstein press release Bauernzeitung press release BW Agrar press release/newsletter DG Verlag (Newsletter Volks- und editorial ofﬁces of professional newsletter media channels Raiffeisenbanken) DLG-Agrarticker press release Dlz Agrarmagazin press release Hessenbauer press release Land+Forst press release and journal article LZ Rheinland press release Proplanta.de press release Rheinische Bauernzeitung press release Sparkassenmagazin Agrar press release Top agrar press release Wochenblatt Landwirtschaft & Landleben press release Stiftung Ökologie und Landbau press release/newsletter Gesellschaft für konservierende press release/newsletter associations/communities of Bodenbearbeitung interest Rationalisierungs-Kuratorium press release/newsletter eilbote short article bonnerblogs.de press release/newsletter Thünen Institute press release, website, twitter scientiﬁc institutions or Project team SOILAssist website groups BONARES-Centre website Agronomy 2021, 11, 969 20 of 24 Appendix B Table A2. Overview of the analysed groups, underlying variables, applied questions, and question (translated in English from the original questionnaire) types to investigate technical soil protection. For original version of the questionnaire, see “Data Availability Statement”. (Germany-wide survey: “Technical soil protection” 2017). Group Variable Question Question Type How much arable land (in ha) is currently farmed? Farm size Open numeric Total? How much arable land (in ha) is currently farmed? Of Share of rented land Open numeric which rented? Please indicate which tractors you use for ﬁeld work Machinery on your farm (excluding contractors)—tractor 1: Open numeric power (in PS) Objective How many crop rotations are cultivated on your farm? Open numeric characteristics of Crop rotation Please indicate the crop rotation members (max. six farm Single-choice members each rotation) What percentage of arable land do you cultivate with Open numeric each crop rotation? Please state the predominant soil types in percent: Soil Characteristics light soil (sand), medium soil (silty/loamy), heavy Open numeric soil (clay) Education What is your highest agricultural qualiﬁcation? Single-choice Objective Function In which function are you active on the farm? Single-choice characteristics of Age Please indicate your age Single-choice farmer Occupation How is your occupation? Full-time or part-time? Single-choice In your opinion, is the topic of soil compaction relevant for Germany? Problem perception 5 point rating scale Behavioural Do you consider the topic of soil compaction to be characteristics relevant for your business? Farming system How is the farm managed? Single-choice Social– institutional Use of advisory service Which advisory services do you use? Multiple-choice environment How high do you estimate the proportion of compacted arable land on your farm (in%)? How high Yield loss Open numeric do you estimate the average yield loss on compacted Economic land on your farm (in%)? constraints Which branches of business are there on your farm? Farm diversiﬁcation Multiple-choice Arable farming, grassland, livestock Application of measures to Low-threshold, complex Which of the following measures do you apply? Multiple-choice prevent soil compaction References 1. Défossez, P.; Richard, G.; Boizard, H.; O’Sullivan, M.F. Modeling change in soil compaction due to agricultural trafﬁc as function of soil water content. Geoderma 2003, 116, 89–105. [CrossRef] 2. Pöhlitz, J.; Rücknagel, J.; Schlüter, S.; Vogel, H.-J.; Christen, O. Estimation of critical stress ranges to preserve soil functions for differently textured soils. Soil Tillage Res. 2020, 200, 104637. [CrossRef] 3. de Lima, R.P.; da Silva, A.P.; Giarola, N.F.B.; da Silva, A.R.; Rolim, M.M. Changes in soil compaction indicators in response to agricultural ﬁeld trafﬁc. Biosyst. Eng. 2017, 162, 1–10. [CrossRef] 4. Lamandé, M.; Schjønning, P. Soil mechanical stresses in high wheel load agricultural ﬁeld trafﬁc: A case study. Soil Res. 2018, 56, 129–135. [CrossRef] 5. Fu, Y.; Tian, Z.; Amoozegar, A.; Heitman, J. Measuring dynamic changes of soil porosity during compaction. Soil Tillage Res. 2019, 193, 114–121. [CrossRef] Agronomy 2021, 11, 969 21 of 24 6. Berisso, F.E.; Schjønning, P.; Keller, T.; Lamandé, M.; Etana, A.; de Jonge, L.W.; Iversen, B.V.; Arvidsson, J.; Forkman, J. Persistent effects of subsoil compaction on pore size distribution and gas transport in a loamy soil. Soil Tillage Res. 2012, 122, 42–51. [CrossRef] 7. Keller, T.; Sandin, M.; Colombi, T.; Horn, R.; Or, D. Historical increase in agricultural machinery weights enhanced soil stress levels and adversely affected soil functioning. Soil Tillage Res. 2019, 194, 104293. [CrossRef] 8. Liu, Q.; Liu, B.; Zhang, Y.; Lin, Z.; Zhu, T.; Sun, R.; Wang, X.; Ma, J.; Bei, Q.; Liu, G.; et al. Can biochar alleviate soil compaction stress on wheat growth and mitigate soil N O emissions? Soil Biol. Biochem. 2017, 104, 8–17. [CrossRef] 9. Beylich, A.; Oberholzer, H.-R.; Schrader, S.; Höper, H.; Wilke, B.-M. Evaluation of soil compaction effects on soil biota and soil biological processes in soils. Soil Tillage Res. 2010, 109, 133–143. [CrossRef] 10. Sitaula, B.K.; Hansen, S.; Sitaula, J.I.B.; Bakken, L.R. Effects of soil compaction on N O emission in agricultural soil. Chemosphere Glob. Chang. Sci. 2000, 2, 367–371. [CrossRef] 11. Antille, D.L.; Chamen, W.C.T.; Tullberg, J.N.; Lal, R. The potential of controlled trafﬁc farming to mitigate greenhouse gas emissions and enhance carbon sequestration in arable land: A critical review. Trans. ASABE 2015, 58, 707–731. 12. Arvidsson, J. Subsoil compaction caused by heavy sugarbeet harvesters in southern Sweden: I. Soil physical properties and crop yield in six ﬁeld experiments. Soil Tillage Res. 2001, 60, 67–78. [CrossRef] 13. Colombi, T.; Keller, T. Developing strategies to recover crop productivity after soil compaction—A plant eco-physiological perspective. Soil Tillage Res. 2019, 191, 156–161. [CrossRef] 14. EEA. The European Environment—State and Outlook 2020: Knowledge and Transition to a Sustainable Europe; European Environment Agenc: Luxembourg, 2019; ISBN 9789294800909. [CrossRef] 15. EC. Key Policy Objectives of the Future CAP: CAP Speciﬁc Objective: Efﬁcient Soil Management. Available online: https://ec. europa.eu/info/sites/info/ﬁles/food-farming-ﬁsheries/key_policies/documents/cap-speciﬁc-objectives-brief-5-soil_en.pdf (accessed on 16 September 2020). 16. Montanarella, L.; Panagos, P. The relevance of sustainable soil management within the European Green Deal. Land Use Policy 2021, 100, 104950. [CrossRef] 17. Arvidsson, J.; Sjöberg, E.; van den Akker, J.J. Subsoil compaction by heavy sugarbeet harvesters in southern Sweden: III. Risk assessment using a soil water model. Soil Tillage Res. 2003, 73, 77–87. [CrossRef] 18. Gocht, A.; Röder, N. Thünen Atlas: Landwirtschaftliche Nutzung Version 2014: Konsistent: Kreisdaten zur Landwirtschaft. Available online: https://www.thuenen.de/de/infrastruktur/thuenen-atlas-und-geoinformation/thuenen-atlas/konsistent- kreisdaten-zur-landwirtschaft/ (accessed on 5 February 2021). 19. MacDonald, A.M.; Matthews, K.B.; Paterson, E.; Aspinall, R.J. The impact of climate change on the soil/moisture regime of Scottish mineral soils. Environ. Pollut. 1994, 83, 245–250. [CrossRef] 20. van der Linden, E.C.; Haarsma, R.J.; van der Schrier, G. Impact of climate model resolution on soil moisture projections in central-western Europe. Hydrol. Earth Syst. Sci. 2019, 23, 191–206. [CrossRef] 21. Bormann, H. Analysis of possible impacts of climate change on the hydrological regimes of different regions in Germany. Adv. Geosci. 2009, 21, 3–11. [CrossRef] 22. Brunotte, J.; Brandhuber, R.; Vorderbrügge, T.; Schrader, S. Vorsorge gegen Bodenverdichtung. Gute Fachliche Praxis— Bodenbewirtschaftung und Bodenschutz 2015, 2, 21–73. 23. Harasim, E.; Antonkiewicz, J.; Kwiatkowski, C.A. The Effects of Catch Crops and Tillage Systems on Selected Physical Properties and Enzymatic Activity of Loess Soil in a Spring Wheat Monoculture. Agronomy 2020, 10, 334. [CrossRef] 24. Lal, R. Restoring Soil Quality to Mitigate Soil Degradation. Sustainability 2015, 7, 5875–5895. [CrossRef] 25. Wanic, M.; Zuk-Golaszewska, K.; Orzech, K. Catch crops and the soil environment—A review of the literature. J. Elem. 2018, 24. [CrossRef] 26. ten Damme, L.; Stettler, M.; Pinet, F.; Vervaet, P.; Keller, T.; Munkholm, L.J.; Lamandé, M. The contribution of tyre evolution to the reduction of soil compaction risks. Soil Tillage Res. 2019, 194, 104283. [CrossRef] 27. Gerdes, J.T. Erträge Steigern, Kosten Senken: Reifendruck und Regelanlagen als Erfolgsfaktoren im Landwirtschaftlichen Betrieb. Available online: https://ﬁrstclaasrental.claas.com/de/blog/ertrage-steigern-kosten-senken-reifendruck-und-regelanlagen- als-erfolgsfaktoren-im-landwirtschaftlichen-betrieb/ (accessed on 4 January 2021). 28. Deter, A. Alles Rund um Agrarreifen/Landwirtschaftsreifen. Available online: https://www.topagrar.com/technik/news/ technik-technikwissen-alles-rund-um-reifen-9376481.html?test=direktbuchung (accessed on 4 January 2021). 29. Deter, A. Bodenschonung Durch Neues Fliegl Hundegang-Güllefass. Available online: https://www.topagrar.com/technik/ news/extreme-bodenschonung-durch-neuste-ﬂiegl-hundegangtechnik-11932567.html (accessed on 4 January 2021). 30. Volk, L. Reifendruckanlagen mit Drehdurchführungen (DD) und Fahrer-Assistenz: Variabler Reifenfülldruck Ist Eine Richtige Entwicklung zu Mehr Bodenschutz, Bessere Dieselefﬁzienz, Mehr Fahrkomfort, Mehr Klimaschutz und Mehr Verkehrssicherheit. Available online: https://www4.fh-swf.de/media/downloads/fbaw_1/reifenregler/pdfs/RDAEntwicklungMaerz2018.pdf (accessed on 4 January 2021). 31. Blunk. Hier gibt es ’was auf die Ohren: Bodenschonung und Reifendruck. Available online: https://www.blunk-gmbh.de/ technik/bodenschonung-reifendruck/ (accessed on 4 January 2021). 32. Uppenkamp, N. Reifenwahl—Was Bringen Moderne Reifenkonzepte? Available online: https://www.landwirtschaftskammer. de/landwirtschaft/technik/aussenwirtschaft/reifen.htm (accessed on 4 January 2021). Agronomy 2021, 11, 969 22 of 24 33. Brandhuber, R.; Demmel, M.; Koch, H.-J.; Brunotte, J. Bodenschonender Einsatz von Landmaschinen: Empfehlungen für die Praxis. DLG-Merkblatt 344, Frankfurt am Main. 2008. Available online: https://www.lﬂ.bayern.de/mam/cms07/iab/dateien/ boden_dlg_merkblatt.pdf (accessed on 4 January 2021). 34. UBA. Verdichtung. Available online: https://www.umweltbundesamt.de/themen/boden-landwirtschaft/bodenbelastungen/ verdichtung#bodenverdichtung-ein-problem (accessed on 4 January 2021). 35. Thorsøe, M.H.; Noe, E.B.; Lamandé, M.; Frelih-Larsen, A.; Kjeldsen, C.; Zandersen, M.; Schjønning, P. Sustainable soil management—Farmers’ perspectives on subsoil compaction and the opportunities and barriers for intervention. Land Use Policy 2019, 86, 427–437. [CrossRef] 36. Ritchey, T. Wicked Problems: Modelling Social Messes with Morphological Analysis. Acta Morphologica Generalis 2013, 2. 37. Chamen, T.W.C.; Moxey, A.P.; Towers, W.; Balana, B.; Hallett, P.D. Mitigating arable soil compaction—A review and analysis of available cost and beneﬁt data. Soil Tillage Res. 2015, 146, 10–25. [CrossRef] 38. Huynh, H.T.N.; Lobry de Bruyn, L.A.; Wilson, B.R.; Knox, O.G.G. Insights, implications and challenges of studying local soil knowledge for sustainable land use: A critical review. Soil Res. 2020, 58, 219. [CrossRef] 39. Montanarella, L.; Pennock, D.J.; McKenzie, N.; Badraoui, M.; Chude, V.; Baptista, I.; Mamo, T.; Yemefack, M.; Singh Aulakh, M.; Yagi, K.; et al. World’s soils are under threat. SOIL 2016, 2, 79–82. [CrossRef] 40. Odendo, M.; Obare, G.; Salasya, B. Farmers’ perceptions and knowledge of soil fertility degradation in two contrasting sites in western Kenya. Land Degrad. Dev. 2010, 21, 557–564. [CrossRef] 41. Yusuf, M.B.; Mustafa, F.B.; Salleh, K.O. Farmer perception of soil erosion and investment in soil conservation measures: Emerging evidence from northern Taraba State, Nigeria. Soil Use Manag. 2017, 33, 163–173. [CrossRef] 42. Tesfahunegn, G.B. Farmers’ perception on land degradation in northern Ethiopia: Implication for developing sustainable land management. Soc. Sci. J. 2019, 56, 268–287. [CrossRef] 43. Faridi, A.A.; Kavoosi-Kalashami, M.; Bilali, H.E. Attitude components affecting adoption of soil and water conservation measures by paddy farmers in Rasht County, Northern Iran. Land Use Policy 2020, 99, 104885. [CrossRef] 44. Sileshi, M.; Kadigi, R.; Mutabazi, K.; Sieber, S. Determinants for adoption of physical soil and water conservation measures by smallholder farmers in Ethiopia. Int. Soil Water Conserv. Res. 2019, 7, 354–361. [CrossRef] 45. Reichardt, M.; Jürgens, C. Adoption and future perspective of precision farming in Germany: Results of several surveys among different agricultural target groups. Precis. Agric. 2009, 10, 73–94. [CrossRef] 46. Caffaro, F.; Cavallo, E. The Effects of Individual Variables, Farming System Characteristics and Perceived Barriers on Actual Use of Smart Farming Technologies: Evidence from the Piedmont Region, Northwestern Italy. Agriculture 2019, 9, 111. [CrossRef] 47. Tamirat, T.W.; Pedersen, S.M.; Lind, K.M. Farm and operator characteristics affecting adoption of precision agriculture in Denmark and Germany. Acta Agric. Scand. Sect. B Soil Plant Sci. 2018, 68, 349–357. [CrossRef] 48. Sattler, C.; Nagel, U.J. Factors affecting farmers’ acceptance of conservation measures—A case study from north-eastern Germany. Land Use Policy 2010, 27, 70–77. [CrossRef] 49. Boardman, J.; Bateman, S.; Seymour, S. Understanding the inﬂuence of farmer motivations on changes to soil erosion risk on sites of former serious erosion in the South Downs National Park, UK. Land Use Policy 2017, 60, 298–312. [CrossRef] 50. Barnes, A.P.; Soto, I.; Eory, V.; Beck, B.; Balafoutis, A.; Sánchez, B.; Vangeyte, J.; Fountas, S.; van der Wal, T.; Gómez-Barbero, M. Exploring the adoption of precision agricultural technologies: A cross regional study of EU farmers. Land Use Policy 2019, 80, 163–174. [CrossRef] 51. Bartkowski, B.; Bartke, S. Leverage Points for Governing Agricultural Soils: A Review of Empirical Studies of European Farmers’ Decision-Making. Sustainability 2018, 10, 3179. [CrossRef] 52. Klerkx, L.; Jansen, J. Building knowledge systems for sustainable agriculture: Supporting private advisors to adequately address sustainable farm management in regular service contacts. Int. J. Agric. Sustain. 2010, 8, 148–163. [CrossRef] 53. Baumgart-Getz, A.; Prokopy, L.S.; Floress, K. Why farmers adopt best management practice in the United States: A meta-analysis of the adoption literature. J. Environ. Manag. 2012, 96, 17–25. [CrossRef] 54. Prager, K.; Schuler, J.; Helming, K.; Zander, P.; Ratinger, T.; Hagedorn, K. Soil degradation, farming practices, institutions and policy responses: An analytical framework. Land Degrad. Dev. 2011, 22, 32–46. [CrossRef] 55. Ingram, J.; Mills, J. Are advisory services “ﬁt for purpose” to support sustainable soil management? An assessment of advice in Europe. Soil Use Manag. 2019, 35, 21–31. [CrossRef] 56. 5DESTATIS. Landwirtschaftliche Betriebe, Fläche: Bundesländer, Jahre, Bodennutzungsarten: Landwirtschaftszählung: Haupter- hebung 2016. 2021. Available online: https://www-genesis.destatis.de/genesis//online?operation=table&code=41141-0016 &bypass=true&levelindex=1&levelid=1614328105781#abreadcrumb (accessed on 25 February 2021). 57. DESTATIS. Landwirtschaftliche Betriebe: Deutschland, Jahre, Größenklassen des Standardoutputs, Rechtsformen, Betrieb- swirtschaftliche Ausrichtung: Landwirtschaftszählung: Haupterhebung 2016. 2021. Available online: https://www- genesis.destatis.de/genesis//online?operation=table&code=41141-0014&bypass=true&levelindex=1&levelid=1614236837782# abreadcrumb (accessed on 25 February 2021). 58. BMEL. Statistisches Jahrbuch Über Ernährung, Landwirtschaft und Forsten der Bundesrepublik Deutschland 2018. 2019. Available online: https://www.bmel-statistik.de/ﬁleadmin/SITE_MASTER/content/Jahrbuch/Agrarstatistisches-Jahrbuch-2018.pdf (accessed on 11 December 2020). Agronomy 2021, 11, 969 23 of 24 59. Opotow, S.; Weiss, L. New Ways of Thinking about Environmentalism: Denial and the Process of Moral Exclusion in Environmen- tal Conﬂict. J. Soc. Issues 2000, 56, 475–490. [CrossRef] 60. Mills, J.; Gaskell, P.; Ingram, J.; Dwyer, J.; Reed, M.; Short, C. Engaging farmers in environmental management through a better understanding of behaviour. Agric. Hum. Values 2017, 34, 283–299. [CrossRef] 61. Dessart, F.J.; Barreiro-Hurlé, J.; van Bavel, R. Behavioural factors affecting the adoption of sustainable farming practices: A policy-oriented review. Eur. Rev. Agric. Econ. 2019, 46, 417–471. [CrossRef] 62. von Buttlar, C.; Müller-Thomsen, U.; Schlüter, H. Erweiterte Befragung von Beratern, Lohnunternehmern und Praktikern zur Betroffen- heit landwirtschaftlich genutzter Flächen von Bodenverdichtungen unter Berücksichtigung regionaler Schwerpunkte und Problemlagen; Ingenieurgesellschaft für Landwirtschaft und Umwelt: Göttingen, Germany, 2017. 63. Batey, T.; McKenzie, D.C. Soil compaction: Identiﬁcation directly in the ﬁeld. Soil Use Manag. 2006, 22, 123–131. [CrossRef] 64. Wolkowski, R.; Lowery, B. Soil Compaction: Causes, Concerns, and Cures; Cooperative Extension Publishing (A3367); University of Wisconsin: Madison, WI, USA, 2008. 65. Håkansson, I.; Lipiec, J. A review of the usefulness of relative bulk density values in studies of soil structure and compaction. Soil Tillage Res. 2000, 53, 71–85. [CrossRef] 66. Alaoui, A.; Diserens, E. Mapping soil compaction—A review. Curr. Opin. Environ. Sci. Health 2018, 5, 60–66. [CrossRef] 67. Defrancesco, E.; Gatto, P.; Runge, F.; Trestini, S. Factors Affecting Farmers’ Participation in Agri-environmental Measures: A Northern Italian Perspective. J. Agric. Econ. 2008, 59, 114–131. [CrossRef] 68. Wuepper, D.; Wimmer, S.; Sauer, J. Is small family farming more environmentally sustainable? Evidence from a spatial regression discontinuity design in Germany. Land Use Policy 2019, 90, 104360. [CrossRef] 69. van Vliet, J.A.; Schut, A.G.T.; Reidsma, P.; Descheemaeker, K.; Slingerland, M.; van de Ven, G.W.J.; Giller, K.E. De-mystifying family farming: Features, diversity and trends across the globe. Glob. Food Secur. 2015, 5, 11–18. [CrossRef] 70. Novelli, S. Determinants of environmentally-friendly farming. Qual. Access Success 2018, 19, 340–346. 71. Caswell, M.; Fuglie, K.; Ingram, C.; Jans, S.; Kascak, C. Adoption of Agricultural Production Practices: Lessons Learned from the U.S. Department of Agriculture Area Studies Project; U.S. Department of Agriculture: Washington, DC, USA, 2001. 72. Leonhardt, H.; Penker, M.; Salhofer, K. Do farmers care about rented land? A multi-method study on land tenure and soil conservation. Land Use Policy 2019, 82, 228–239. [CrossRef] 73. Imhoff, S.; Da Silva, A.P.; Fallow, D. Susceptibility to compaction, load support capacity, and soil compressibility of Hapludox. Soil Sci. Soc. Am. J. 2004, 68, 17–24. [CrossRef] 74. Ledermüller, S.; Brunotte, J.; Lorenz, M.; Osterburg, B. Arbeitsbericht: Verbesserung des physikalischen Bodenschutzes bei der Wirtschafts- düngerausbringung im Frühjahr—Herausforderungen und Lösungsansätze; BonaRes Series: Halle, Germany, 2020. [CrossRef] 75. Lorenz, M.; Brunotte, J.; Vorderbrügge, T.; Brandhuber, R.; Koch, H.-J.; Senger, M.; Fröba, N.; Löpmeier, F.-J. Anpassung der Lasteinträge landwirtschaftlicher Maschinen an die Verdichtungsempﬁndlichkeit des Bodens—Grundlagen für ein bodenscho- nendes Befahren von Ackerland. Landbauforschung 2016, 66, 101–144. [CrossRef] 76. Safﬁh-Hdadi, K.; Défossez, P.; Richard, G.; Cui, Y.J.; Tang, A.M.; Chaplain, V. A method for predicting soil susceptibility to the compaction of surface layers as a function of water content and bulk density. Soil Tillage Res. 2009, 105, 96–103. [CrossRef] 77. Jones, R.J.A.; Spoor, G.; Thomasson, A.J. Vulnerability of subsoils in Europe to compaction: A preliminary analysis. Soil Tillage Res. 2003, 73, 131–143. [CrossRef] 78. Schjønning, P.; Lamandé, M.; Thorsøe, M.H.; Frelih-Larsen, A. Policy Brief: Subsoil Compaction—A Threat to Sustainable Food Production and Soil Ecosystem Services. Available online: https://www.ecologic.eu/sites/ﬁles/publication/2018/2730_recare_ subsoil-compaction_web.pdf (accessed on 5 January 2021). 79. Rezaei-Moghaddam, K.; Vatankhah, N.; Ajili, A. Adoption of pro-environmental behaviors among farmers: Application of Value–Belief–Norm theory. Chem. Biol. Technol. Agric. 2020, 7. [CrossRef] 80. Hilimire, K.; Greenberg, K. Water conservation behaviors among beginning farmers in the western United States. J. Soil Water Conserv. 2019, 74, 138–144. [CrossRef] 81. Delaroche, M. Adoption of conservation practices: What have we learned from two decades of social-psychological approaches? Curr. Opin. Environ. Sustain. 2020, 45, 25–35. [CrossRef] 82. Salhi, A.; Benabdelouahab, T.; Martin-Vide, J.; Okacha, A.; El Hasnaoui, Y.; El Mousaoui, M.; El Morabit, A.; Himi, M.; Benabdelouahab, S.; Lebrini, Y.; et al. Bridging the gap of perception is the only way to align soil protection actions. Sci. Total Environ. 2020, 718, 137421. [CrossRef] [PubMed] 83. Bampa, F.; O’Sullivan, L.; Madena, K.; Sandén, T.; Spiegel, H.; Henriksen, C.B.; Ghaley, B.B.; Jones, A.; Staes, J.; Sturel, S.; et al. Harvesting European knowledge on soil functions and land management using multi-criteria decision analysis. Soil Use Manag. 2019, 35, 6–20. [CrossRef] 84. Schneider, F.; Ledermann, T.; Fry, P.; Rist, S. Soil conservation in Swiss agriculture—Approaching abstract and symbolic meanings in farmers’ life-worlds. Land Use Policy 2010, 27, 332–339. [CrossRef] 85. Schneider, F.; Fry, P.; Ledermann, T.; Rist, S. Social Learning Processes in Swiss Soil Protection—The ‘From Farmer—To Farmer ’ Project. Hum. Ecol. 2009, 37, 475–489. [CrossRef] 86. Diamantopoulos, A.; Schlegelmilch, B.B.; Sinkovics, R.R.; Bohlen, G.M. Can socio-demographics still play a role in proﬁling green consumers? A review of the evidence and an empirical investigation. J. Bus. Res. 2003, 56, 465–480. [CrossRef] Agronomy 2021, 11, 969 24 of 24 87. Ahnström, J.; Höckert, J.; Bergeå, H.L.; Francis, C.A.; Skelton, P.; Hallgren, L. Farmers and nature conservation: What is known about attitudes, context factors and actions affecting conservation? Renew. Agric. Food Syst. 2009, 24, 38–47. [CrossRef] 88. Knowler, D.; Bradshaw, B. Farmers’ adoption of conservation agriculture: A review and synthesis of recent research. Food Policy 2007, 32, 25–48. [CrossRef] 89. Murphy, G.; Hynes, S.; Murphy, E.; O’Donoghue, C. An investigation into the type of farmer who chose to participate in Rural Environment Protection Scheme (REPS) and the role of institutional change in inﬂuencing scheme effectiveness. Land Use Policy 2014, 39, 199–210. [CrossRef] 90. Toma, L.; Mathijs, E. Environmental risk perception, environmental concern and propensity to participate in organic farming programmes. J. Environ. Manag. 2007, 83, 145–157. [CrossRef] 91. Zhou, Z.; Liu, J.; Zeng, H.; Zhang, T.; Chen, X. How does soil pollution risk perception affect farmers’ pro-environmental behavior? The role of income level. J. Environ. Manag. 2020, 270, 110806. [CrossRef] [PubMed] 92. van Winsen, F.; de Mey, Y.; Lauwers, L.; van Passel, S.; Vancauteren, M.; Wauters, E. Determinants of risk behaviour: Effects of perceived risks and risk attitude on farmer ’s adoption of risk management strategies. J. Risk Res. 2016, 19, 56–78. [CrossRef] 93. Duong, T.T.; Brewer, T.; Luck, J.; Zander, K. A Global Review of Farmers’ Perceptions of Agricultural Risks and Risk Management Strategies. Agriculture 2019, 9, 10. [CrossRef] 94. McCann, E.; Sullivan, S.; Erickson, D.; de Young, R. Environmental Awareness, Economic Orientation, and Farming Practices: A Comparison of Organic and Conventional Farmers. Environ. Manag. 1997, 21, 747–758. [CrossRef] 95. Michel-Guillou, E.; Moser, G. Commitment of farmers to environmental protection: From social pressure to environmental conscience. J. Environ. Psychol. 2006, 26, 227–235. [CrossRef] 96. Stettler, M.; LKeller, T.; Weisskopf, P.; Lamandé, M.; Lassen, P.; Schjønning, P. Terranimo —ein webbasiertes Modell zur Abschätzung des Bodenverdichtungsrisikos. Landtechnik 2014, 69, 132–138. 97. Marx, K.; Jacobs, A. SOILAssist-Teilprojekt ‚Akzeptanz und Implementierung‘: Analyse behördlicher Handlungsempfehlungen zur Vermeidung von Bodenverdichtung auf Ackerböden, 160th ed.; Braunschweig/Germany. 2020. Available online: https: //www.thuenen.de/media/publikationen/thuenen-workingpaper/ThuenenWorkingPaper_160.pdf (accessed on 27 January 2021). 98. Thomas, A. Landwirtschaftliche Beratung in der Bundesrepublik Deutschland—eine Übersicht. 2007. Available online: http:// www2.komm-agrar.de/cms/sites/komm-agrar.de/ﬁles/bub_2007_02_thomas_lw_beratung_in_dtl.pdf (accessed on 26 February 2021). 99. Turner, M.; Whitehead, I.; Millard, N. The Effects of Public Funding on Farmers’ Attitudes to Farm Diversiﬁcation; Centre for Rural Research, University of Exeter: Yasit, UK, 2006; ISBN 1870558936. 100. Poon, K.; Weersink, A. Factors affecting variability in farm and off-farm income. Agric. Financ. Rev. 2011, 71, 379–397. [CrossRef] 101. Läpple, D.; Renwick, A.; Thorne, F. Measuring and understanding the drivers of agricultural innovation: Evidence from Ireland. Food Policy 2015, 51, 1–8. [CrossRef] 102. Simple Soil Structure Assessment for the Farmer, 3rd ed.; Thünen-Institut, Gesellschaft für konservierende Bodenbearbeitung e.V. (GKB): Neuenhagen, Germany, 2012. 103. Bodenzustandserfassung Landwirtschaftlich Genutzter Böden. Available online: https://www.schleswig-holstein.de/DE/ Fachinhalte/B/boden/landwGenutzteBoeden.html#docbe206fff-4ccf-4934-a29c-24fcfe303ca3bodyText2 (accessed on 1 January 2021). 104. Burton, R.J.F. The inﬂuence of farmer demographic characteristics on environmental behaviour: A review. J. Environ. Manag. 2014, 135, 19–26. [CrossRef]

http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Agronomy Multidisciplinary Digital Publishing Institute

http://www.deepdyve.com/lp/multidisciplinary-digital-publishing-institute/perception-of-the-relevance-of-soil-compaction-and-application-of-1VKl1LPMuv

Perception of the Relevance of Soil Compaction and Application of Measures to Prevent It among German Farmers

Loading next page...

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher: Multidisciplinary Digital Publishing Institute
Copyright: © 1996-2021 MDPI (Basel, Switzerland) unless otherwise stated Disclaimer The statements, opinions and data contained in the journals are solely those of the individual authors and contributors and not of the publisher and the editor(s). MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Terms and Conditions Privacy Policy
ISSN: 2073-4395
DOI: 10.3390/agronomy11050969
Publisher site: See Article on Publisher Site

Abstract

Journal

Agronomy – Multidisciplinary Digital Publishing Institute

Published: May 13, 2021

Keywords: soil management; farmers’ attitudes; yield loss; risk perception; advisory service; formal learning

Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Perception of the Relevance of Soil Compaction and Application of Measures to Prevent It among German Farmers

Perception of the Relevance of Soil Compaction and Application of Measures to Prevent It among German Farmers

Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Perception of the Relevance of Soil Compaction and Application of Measures to Prevent It among German Farmers

Perception of the Relevance of Soil Compaction and Application of Measures to Prevent It among German Farmers

References

Abstract

Journal

Recommended Articles

There are no references for this article.

Our policy towards the use of cookies