{"paper_id":"1a8c4a0c-ac02-435b-825d-0ade29aec0b8","body_text":"Farmer Perceptions and Adaptations to Nitrogen Regulations in Germany: A Q-Methodology Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Farmer Perceptions and Adaptations to Nitrogen Regulations in Germany: A Q-Methodology Analysis Marius Michels, Malte Behrens, Hendrik Wever, Oliver Mußhoff This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7574476/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examines farmers' perceptions and adaptation strategies in response to fertilizer use restrictions due to nitrogen pollution in designated “red areas” under § 13a of the German Fertilizer Ordinance (DüV). Using Q-methodology and qualitative interviews with 24 German farm managers conducted between December 2024 and January 2025, we identified two distinct farmer perspectives: those primarily concerned with bureaucratic burden and perceived ineffectiveness of measures, and those focused on economic burden for farmers and reduced planning certainty. Despite these differences, farmers generally oppose the regulations as they question their effectiveness. Farmer adaptations include investments in (precision) application technology, shifting to more extensive cereal varieties, increased legume cultivation, and storage capacity expansion for organic fertilizers. A few farmers even report yield reductions in winter wheat and decreased protein content in red areas. Our findings suggest that allowing farm-specific flexibility could improve acceptance while maintaining environmental effectiveness. This research demonstrates that successful groundwater protection depends more on stakeholder inclusion and acceptance than additional restrictions. Agricultural Economics & Policy Groundwater protection Nitrogen management Q-methodology German farmers Fertilizer regulations Figures Figure 1 Figure 2 1 Introduction Nitrogen fertilizers are essential for modern agricultural production (Liu et al., 2024 ), contributing to global yield increases and food security (Smil, 2002 ). However, crops typically absorb only about half of applied nitrogen (Galloway et al., 2008 ; Lassaletta et al., 2014 ), with the remainder lost to the environment, causing eutrophication, groundwater contamination, and climate change acceleration (Galloway et al., 2008 ; Liu et al., 2024 ). Poor nitrogen management hinders achievement of UN sustainability goals (Sachs et al., 2021 ) and addressing nitrogen pollution is crucial for tackling climate change (Kanter, 2018 ). In response to mounting environmental concerns associated with nitrogen surpluses, various policy measures have been developed to regulate agricultural nitrogen use (Kanter et al., 2020a , b ). The European Union's (EU) 1991 Nitrates Directive (91/676/EEC) requires Member States to designate Nitrate Vulnerable Zones (NVZs) where groundwater nitrate concentrations exceed 50 mg/l (European Commission, n.d.). Some Member States, such as Ireland and Denmark, have designated almost their entire national territory as an NVZ (Dalgaard et al., 2014 ; Ortmeyer et al., 2023 ), thereby applying uniform restrictions across all agricultural land. However, Denmark has, since 2016, complemented this uniform designation with so-called targeted regulations which introduce spatially differentiated measures in particularly vulnerable areas while allowing more flexibility elsewhere. By contrast, countries such as Scotland or France have only designated specific areas as NVZ (Ortmeyer et al., 2023 ; Barnes et al., 2009 ). Germany employs a spatially differentiated approach, with 22% of groundwater bodies exceeding the threshold (Umweltbundesamt, 2024 ). Similar to Denmark, Germany has also designated its entire territory as an NVZ. However, Germany employs an additional two-tier system: within the nationwide NVZ designation, specific “red areas” ( rote Gebiete ) under § 13a of the German Fertilizer Ordinance (Düngeverordnung, DüV)[1] (Bundesministerium der Justiz und für Verbraucherschutz, n.d.) are subject to stricter rules, such as a mandatory 20% reduction in nitrogen fertilization relative to crop requirements[2] (Bundesinformationszentrum Landwirtschaft, 2025 ). Federal states may also adopt additional measures. This differs from Denmark’s outcome-based targeted regulation approach, as Germany relies on a binary distinction between red and non-red areas. However, Germany’s § 13a DüV framework is more prescriptive and administratively demanding than typical NVZ regimes, potentially creating economic disparities between farms inside and outside the red areas (Barnes et al., 2009 ; Schröer et al., 2022 ), raising questions about environmental effectiveness (Barnes et al., 2009 ; Deutscher Bauernverband, 2020 ; Franklin et al., 2021 ), and generating social tensions (Barnes et al., 2009 ; Landvolk Niedersachsen, 2023 ). This interplay of technical stringency, spatial differentiation, and socio-political implications provides a unique context for examining farmer responses to nitrogen regulations. Effective (environmental) regulation depends on both technical design and implementation (Porter and van der Linde, 1995), clear objectives anchored in practical realities (Blanc, 2018 ; Stuhr et al., 2020), and feasible integration of measures into farming systems by farmers(e.g. Moreddu, 2007 ). Regulatory approaches may achieve only transient change without creating cultural shifts (Mills et al., 2017 ; Stuhr et al., 2020), and often rely on oversimplified understanding of farmers' motivations (Feindt et al., 2019 ). Porter and van der Linde (1995) contend that such regulations should have clear goals, flexible approaches, and incentives for innovation – characteristics that may be variably present in Germany's red area designations under § 13a DüV. Understanding farmers' perceptions and adaptations is therefore essential to evaluate and potentially refine regulations to achieve not only short-term compliance but lasting environmental improvements. Previous studies provide valuable insights into farmer attitudes and responses to nitrate regulations, yet they highlight persistent tensions between regulatory intent and on-farm realities. Scottish farmers frequently expressed limited perceived responsibility for water pollution, being unfairly penalized by the restrictions, distrust in regulations, and dissatisfaction with the costs and administrative burdens of NVZ regulations (MacGregor and Warren, 2006 ; Barnes et al., 2009 ). Likewise, Welsh dairy farmers display distrust in the scientific basis for the regulation (Franklin et al., 2021 ). While environmental concern can encourage mitigation, profit-maximizing attitudes may reduce compliance (Toma et al., 2008 ). Nevertheless, a 2016 follow-up study interviewing the same farmers as in 2006 shows that NVZ has made farmers more aware of environmental issues, and they now pose fewer objections to the requirements than before, suggesting both attitudinal and behavioral change over time (McGregor and Warren, 2016). In spite of such potential, in other studies most farmers made only minimal adjustments in practices, such as record-keeping, without substantial investment in measures such as manure storage (Barnes et al., 2009 ). Franklin et al. ( 2021 ) showed that investment in manure storage was needed but often not economically feasible for smaller dairy farmers, as also reported by MacGregor and Warren ( 2016 ) for Scottish farmers. Franklin et al. ( 2021 ) further identified unintended consequences of rigid regulatory frameworks, noting that inflexible closed periods can paradoxically increase environmental risks when farmers apply manure immediately after restriction periods end, regardless of field conditions. This represents a shift toward \"farming for regulations\" rather than responding adaptively to environmental and weather conditions. Regarding farming for (or against) regulations, Barnes et al. ( 2011 ) developed a typology of farmers in NVZ contexts, identifying three distinct groups: \"multi-functionalists\" who embrace environmental and social values; \"resistors\" who prioritize resource maximization and oppose regulation; and \"apathists\" who remain largely disengaged from the regulatory discourse. More recently, Iversen et al. ( 2024 ) revealed important disconnects between scientific and practitioner perspectives in Denmark. While scientists advocate ecosystem-based approaches, farmers strongly prefer flexible, locally-adapted measures. A particularly notable divergence concerns precision agriculture technologies. Danish farmers view these as effective NVZ management tools (Iversen et al., 2024 ), a perspective supported by Basso et al. ( 2016 ), yet Danish scientists attribute only minimal environmental benefits to precision fertilization techniques (Iversen et al., 2024 ). While these studies provide valuable insights into farmer responses to NVZ regulations in various contexts, three gaps remain in our understanding of how farmers respond to particularly stringent nitrogen regulations like Germany's red areas. First, previous research has primarily examined regulatory frameworks that are less prescriptive than Germany's approach. Second, there remains limited understanding of how farmers' viewpoints on nitrogen regulations integrate environmental, economic, and social considerations under these particularly stringent conditions. Third, existing research has primarily focused on documenting farmer responses to established regulatory frameworks rather than exploring farmer perspectives on alternative approaches that might better balance environmental protection with agricultural viability. Against this background, this study aims to examine farmers' perceptions and adaptation strategies in response to stringent nitrogen regulations in designated red areas in Germany under § 13a DüV. Specifically, we seek to: (1) identify distinct viewpoints among farmers regarding the regulatory framework and its impacts along ecological, economic and social dimensions; (2) document the technical, operational, and economic adaptations implemented by farmers in response to these regulations; and (3) explore farmers' perspectives on potential alternative regulatory approaches that might achieve environmental objectives while better accommodating farm-specific conditions. We conducted a mixed-methods study combining Q-methodology with qualitative interviews of 24 conventional farm managers in Lower Saxony, Germany (December 2024-January 2025). Lower Saxony provides an ideal study region as it contains one of the highest percentages of designated red areas among German federal states (30% of agricultural land), has diverse agricultural systems including both intensive livestock and crop production, and has implemented additional state-specific nitrogen management measures beyond the federal requirements. Q-methodology offers unique advantages for this research context by enabling the systematic identification of shared viewpoints while preserving individual perspectives, unlike traditional survey methods that may average out important distinctions in farmer attitudes. By supplementing the Q-methodology with qualitative interviews, we gain deeper insights into farmers' adaptation strategies and their reasoning behind specific responses to regulations. Participants were strategically selected with the sole criterion that they manage agricultural land within designated red areas under § 13a DüV. The study framework incorporated the three sustainability pillars (ecological, economic, and social) to examine nitrogen regulations' impacts, recognizing that regulatory success requires balance across these dimensions. This study makes several novel contributions to the literature on effective agricultural nitrogen policy. First, it provides empirical evidence of farmer responses to one of Europe's most stringent implementations of the EU Nitrates Directive, revealing how increasingly prescriptive regulations affect farmer perceptions and behaviors. Second, we identify how ecological, economic, and social considerations are integrated in farmer perspectives under stringent regulatory conditions, demonstrating that concerns transcend simple economic impacts to include broader issues of planning security, professional identity, and regulatory trust. Third, we document how farmers' adaptation strategies under strict regulatory constraints reveal both innovative responses and potential unintended consequences of current policy approaches, including shifts in crop selection and quality parameters. Fourth, we address the knowledge gap regarding regulatory alternatives by analyzing farmer-generated policy proposals that could enhance both environmental outcomes and agricultural sustainability, offering concrete pathways for policy reform based on practitioner insights. Our findings extend beyond Lower Saxony, offering valuable insights for regions considering similar regulatory approaches to address nitrate pollution concerns. This makes our case study an important reference point for policymakers, advisors, and other stakeholders working to improve nitrogen management and policies while maintaining agricultural viability. 2 Material and Methods 2.1 Survey and Data Collection This study surveyed 24 farm managers from Lower Saxony, Germany, using a strategic sampling approach as recommended by Watts and Stenner (2005) to capture diverse perspectives. The primary selection criterion required participants to manage agricultural land within red areas designated under § 13a DüV. We ensured diversity by including livestock operations in addition to arable farms. Participant recruitment followed a dual approach: direct contact through existing networks and referrals from advisors. Personal face-to-face expert interviews were conducted between December 11, 2024, and January 15, 2025. The survey received ethical approval from the German Association for Experimental Economic Research. Prior to data collection, all participants received a brief introduction to the research and its objectives. They were informed about participation conditions and data protection provisions, which required their active consent. Figure 1 shows the red areas in Lower Saxony and distribution of participants across the federal state. Red areas constitute 30% of agricultural land and 16.7% of the federal state. The Q-methodology implementation required the development of a Q-sample comprising statements representing diverse viewpoints on the topic (Table A2 , Appendix). We derived the Q-sample through comprehensive analysis of both scientific and gray literature related to the research topic. Statement selection focused on identifying challenges and opportunities presented by nitrogen regulation for agricultural operations. To maintain methodological balance, we included an equal distribution of statements across the three sustainability dimensions – ecological, economic, and social – within the Q-sample. Two farmers pre-tested all statements to ensure comprehensibility and relevance prior to implementation. The interview protocol consisted of three parts: (1) a questionnaire capturing farm and operator characteristics; (2) the Q-sorting exercise requiring participants to arrange statements on a quasi-normal distribution grid ranging from − 4 (strongly disagree) to + 4 (strongly agree) (Fig. 2); and (3) follow-up questions addressing extreme rankings, adaptations to regulations, and perspectives on mandatory versus voluntary measures. This approach facilitated both quantitative analysis of sorting patterns and qualitative understanding of participants' underlying rationales and experiences with regulations in red areas under § 13a DüV. The questionnaire can be found in the Appendix. 2.2 Data Analysis The analysis of the second part was conducted using the qmethod package in R (Zabala, 2014 ), following established Q-methodology procedures. We performed principal component analysis (PCA) with varimax rotation to identify distinct participant perspectives. The initial factor extraction began with seven factors, which was subsequently refined based on multiple criteria. Factors with eigenvalues above 1.0 (Watts and Stenner, 2005) were retained and evaluated using parallel analysis. The final factor selection was based on several criteria, including explained variance, standard errors, and factor loadings. Particular attention was paid to achieving sufficient variance explanation (> 50%) while maintaining interpretability. In the final analysis, consensus statements (similar z-scores across all factors) and distinguishing statements (statistically significantly different z-scores between factors) were identified. Data and code can be found in: https://osf.io/6xq2v/ . The interviews were recorded and initially transcribed. The resulting text was subsequently reviewed and corrected twice. For further analysis, the finalized transcripts were imported into f4 analysis software and evaluated. 3 Results and Discussion 3.1 P-Sample Characteristics The P-Sample consists of 24 farmers of which 91% are male with an average age of 39 years (Min. 23; Max. 63), 37.5% completed a two-year vocational school, 29.2% held a Master’s degree, 16.7% a Bachelor’s degree, 8.3% a Diploma, 4.2% a Ph.D., and 4.2% a Master craftsman certificate. On average, the farmers assessed themselves as risk-seeking (7.0), innovative (7.4) and relatively successful compared to other farmers (7.2) – all measured on an 11-point scale from 0 to 10. Regarding their knowledge of the current German fertilizer regulation, they rated themselves with an average 3.4 on a 5-point scale from 1 to 5. Regarding their farm, average precipitation is 682 mm/year and average soil quality is 43 (Min. 22; Max. 85) on a scale from 0 to 100. Many, 58.4%, of the farmers have an opportunity to irrigate their fields. They cultivate on average 196.8 hectares of arable land (Min. 62.5; Max. 570) and 15.6 hectares of grassland (Min. 0; Max. 115). On average, 23.6% of the farmers’ cultivated area is located in water protection areas and 76.0% in red areas. Just over half, 58.3%, have livestock on their farm besides arable farming and 8.3% have special crops (e.g. vegetables). Regarding machinery for fertilizer application, 95.8% have a fertilizer spreader or field sprayer. In addition, 45.8% apply organic fertilizers. All farms are managed conventionally. Detailed results are shown in the Table A3, Appendix. 3.2 Factor Extraction and Selection Our initial factor analysis extracted multiple factors, with eigenvalues suggesting potential extraction of up to seven factors. While parallel analysis suggested a single-factor solution (Figure A1, Appendix) explaining 52.8% of variance, this would obscure important distinctions in farmer perspectives. The 2-factor solution we selected explains 59.4% of total variance (Factor 1: 31.5%, Factor 2: 27.9%) and demonstrates high composite reliability scores (both 0.98) with low standard errors (0.16 and 0.14). While a 3-factor solution was also considered, it only increased explained variance by a marginal 5.79% (resulting in a total of 65.2% explained variance), while introducing a factor with a substantially higher standard error (0.33 for Factor 3 compared to 0.16 and 0.15 for Factors 1 and 2). Hence, the 2-factor solution was chosen. This solution achieves strong representation of respondent viewpoints with 22 of 24 participants (91.7%) distinctly loading on one of the two factors. Table 1 shows the distribution of participants among the two factors. Furthermore, the factor correlation of 0.75 indicates that while these perspectives share some common ground, they maintain distinct viewpoints on key issues, as evidenced by the 14 distinguishing statements between factors (Table 3). The 2-factor solution therefore provides the optimal balance between methodological robustness and the ability to capture meaningful distinctions in farmers' perspectives on nitrogen regulations. Table 1 Factor loadings by respondent Factor Loading respondents Total 1 Res_1, Res_4, Res_5, Res_10, Res_11, Res_15, Res_19, Res_20, Res_21, Res_23 10 2 Res_2, Res_6, Res_8, Res_9, Res_12, Res_13, Res_14, Res_16, Res_17, Res_18, Res_22, Res_24 12 No load Res_3, Res_7 2 Res = Respondent Our analysis revealed several consensus statements that were similarly ranked across both identified factors, indicating areas of shared perspective among farmers regardless of their overall viewpoint on nitrogen regulations. These consensus statements provide important insights into common ground in farmers' perceptions (Table 2). The results of Table 2 are shown graphically via z-scores in Figure A2, Appendix. Table A4 in the Appendix shows the factor loadings. Both groups agree on the administrative burden associated with complex regulations and documentation requirements (Statement (S) 17, + 4 and + 3), highlighting universal concern about bureaucratic demands. Similarly, farmers across both perspectives concurred that fertilizer regulations are excessively strict and fail to account for crop-specific needs and soil conditions (S5, + 3 and + 2), reflecting shared skepticism about regulatory appropriateness. Economic concerns also formed an area of consensus, with both groups acknowledging that restrictions in red areas create economic disadvantages through negative impacts on yields and efficiency (S9, + 2 for both factors). Additionally, farmers across both perspectives expressed feelings of exclusion from decision-making processes, contributing to a sense of powerlessness (S25, + 2 for both factors). Both groups demonstrated similar rejection of statements that suggest positive environmental outcomes from the regulations. They disagreed with claims that the regulations protect general public interests while ensuring environmental health and agricultural sustainability (S2, -4 and − 3). Likewise, both groups rejected assertions that regulations promote biological product adoption for environmental protection purposes (S6, -2 for both factors). Notably, both groups maintained neutral positions regarding the effectiveness of official advisory services (S18, scored 0 for both factors), indicating shared ambivalence about support systems for regulatory compliance. Descriptive statistics of the factors which determined the two groups are shown in Table A3, Appendix. Table 2 Factor scores for statements on the ecological, economic and social dimension on cultivation in red areas under 13a DüV Statement Factor 1 Factor 2 Ecological Dimension (Environmental and Sustainability Aspects) 1 -3 -1 2 C -4 -3 3 C 0 -1 4 -3 0 5 C 3 2 6 C -2 -2 7 1 4 8 -1 -2 Economic Dimension 9 C 2 2 10 1 3 11 -1 -4 12 -1 0 13 0 1 14 0 0 15 C 1 0 16 0 -2 Social Dimension (Psychological-Social and Administrative/Regulatory Aspects) 17 C 4 3 18 C 0 0 19 3 1 20 -2 1 21 -1 -3 22 C 2 1 23 C -2 -1 24 1 -1 25 C 2 2 Characteristics Percentage of variance explained 31.50% 27.92% Number of loading Q-Sorts 10 12 Eigenvalues 7.56 6.70 Composite reliability 0.98 0.98 Standard error of factor scores 0.16 0.14 Note: Scores range from + 4 (highest agreement) to -4 (lowest agreement). Statements marked (C) represent consensus viewpoints with similar rankings across all three factors. Statements without a mark are distinguishing statements between factors at p < 0.05. 3.3 Factor Analysis Results Factor 1 (Environmental Effectiveness Skepticism and Administrative Burden Perspective) Factor 1 explains 31.5% of the total study variance, with 10 farm managers loading on this perspective. This viewpoint is characterized by strong skepticism regarding the environmental effectiveness of nitrogen regulations coupled with substantial concerns about administrative requirements. The defining feature of this perspective is the categorical rejection of claims about environmental benefits from regulations in red areas. Farmers aligned with Factor 1 strongly disagree that regulations protect public interests by ensuring a healthy environment while making agricultural practices sustainable (S2, -4), protect groundwater (S1, -3), or improve water quality in adjacent surface waters (S4, -3). This skepticism is reinforced by participants' observations that nitrate levels \"were already decreasing before and were at a very low level\" (Int_10) and criticism that regulations are \"simply too generalized\" (Res_11). A distinctive characteristic of Factor 1 respondents is their belief that agriculture is disproportionately targeted while other pollution sources receive insufficient attention. Fifty percent of these farmers suggested focusing water protection efforts on public sewage systems and treatment plants. One farmer stated that \"agriculture is being targeted because it's the easiest area to implement changes\" (Res_21). Administrative burden emerges as the most substantial concern for this group, with strong agreement that complex regulations and documentation requirements represent a high administrative burden (S17, + 4). One farmer expressed frustration about the time investment: \"Because it's just insanely time-intensive [...]\" (Res_1). Another suggested that \"[…] part of the solution would be to make the entire regulatory framework leaner and not incorporate new changes annually\" (Res_19). Factor 1 respondents strongly agree that constant adjustments and complexity lead to stress and uncertainty among farmers (S19, + 3). The psychological impact of regulatory pressure is substantial, with one participant observing that \"the stress effects and effects of perceived pressure now almost overshadow the economic consequences for many farmers\" (Res_19), indicating that emotional burden weighs more heavily than economic effects for this group. These farmers perceive a fundamental shift away from agronomic principles toward compliance-focused farming: \"You do not focus on how to better supply the plants to improve things, but only on what regulations you have and how to comply with them\" (Res_15). The constant regulatory changes have led to a sense of futility among some farmers, as illustrated by one participant describing a colleague who said: \"I do not care anymore, I'll continue fertilizing as before, it's too much back and forth for me\" (Res_11). In addition to acknowledging economic disadvantages from the regulations (S9, + 2), Factor 1 respondents also feel excluded from decision-making processes (S25, + 2) and agree that constant adaptation to new regulations causes stress and decreases identification with the farming profession (S22, + 2). They perceive the regulations as too strict and failing to consider crop-specific needs and soil conditions (S5, + 3), emphasizing a disconnect between regulatory approaches and agricultural realities. This perspective represents a fundamental challenge to current regulatory approaches, questioning their environmental necessity and effectiveness while highlighting administrative, psychological, and professional identity costs for farmers operating in red areas. Factor 2 (Economic Planning and Farm-Specific Flexibility Perspective) Factor 2 explains 27.9% of the total study variance, with 12 farmers loading on this perspective. This viewpoint emphasizes economic planning challenges and the need for farm-specific flexibility in regulatory approaches. The most distinctive feature of this perspective is the strong emphasis on the generalized nature of regulations that fail to account for individual farm conditions. Farmers aligned with Factor 2 showed the highest agreement with the statement that regulations are too generalized and do not consider the specific conditions of individual farms, leading to inefficient resource use (S7, + 4). One participant highlighted how current regulations neglect important soil science factors: \"I find these professional aspects, such as the C/N ratio and the soil's ability to store nutrients through clay minerals, are completely inadequately addressed\" (Res_13). Others noted how the blanket regulations fail to accommodate different farming systems, particularly forage production, and that in general \"fertilization must always match yield potential\" (Res_17). Factor 2 respondents strongly rejected the notion that their production programs have changed substantially due to red area regulations (S11, -4), the statement ranked most negatively by this group. This response appears influenced by both farm characteristics and cropping choices. On average, these farms have less land in red areas (68% compared to 85% for the Factor 1 group) and often grow crops that are less sensitive to fertilizer restrictions. As two farmers explained: \"Because we have this diverse crop rotation, we have fewer problems\" (Res_13) and \"For us it hasn't changed because potatoes are simply our number one crop\" (Res_6). Winter cereals and winter rapeseed reportedly suffer greater yield losses from reduced fertilization (Res_1) than spring crops, particularly root crops like sugar beets and potatoes (Res_8). Planning security emerges as a crucial concern for this perspective, with strong agreement that regulations reduce planning security and do not contribute to long-term cultivation and operational strategies (S10, + 3). One participant described this frustration: \"This lack of planning security is simply annoying. Sometimes you're in [the red areas][3], sometimes you're out\" (Res_6). Notably, 75% of Factor 2 respondents spontaneously mentioned changes to red area boundaries during interviews, compared to only 20% of Factor 1 respondents. This suggests these farmers particularly value stable planning conditions for operational strategy. Factor 2 respondents strongly disagreed with the statement that community projects and cooperations in red areas strengthen social cohesion and promote exchange of best practices (S21, -3), indicating skepticism about collaborative approaches. This aligns with their general preference for individual farm-specific solutions rather than standardized or community-based initiatives. Some Factor 2 respondents from regions with historically low livestock density expressed surprise at being affected by the regulations, with one noting that farms in their area \"have long used purely mineral fertilizer products and have already followed recommendations \" (Res_12). This viewpoint represents a pragmatic challenge to the current regulatory framework, accepting the necessity of nitrogen management while advocating for more flexible, farm-specific approaches that better account for diverse cropping systems, soil conditions, and farm characteristics while providing the planning security needed for operational stability. 3.4 Results from the Interviews 3.4.1 Adaptation Strategies to Red Area Regulations The most important adaptation was investment in new technology, with 54% of farms investing in agricultural machinery through the \"Agricultural Investment Program\" administered by the German Landwirtschaftliche Rentenbank and introduced by the Federal Ministry of Agriculture (BMEL, 2024). These investments primarily focused on precision application technology (59%) and fertilizer distribution equipment (40%) to enable more efficient nutrient utilization. One-quarter of participating farms planned to implement application maps to target \"the right amounts on specific areas\" (Res_10). Livestock operations faced particular challenges with manure management due to autumn fertilization restrictions and the 170 kg N/ha organic fertilizer limit. Four farms, primarily pig producers, invested €200,000-250,000 each in additional storage capacity for organic fertilizer, while farms in high livestock density regions reported increased transport costs for organic fertilizers, reaching €10 per cubic meter (Res_17). Two key trends emerged in cropping system adaptations: (1) increased cultivation of spring crops, particularly sugar beet and maize while reducing winter rapeseed, and (2) modified cereal production intensity, with some wheat producers shifting to premium quality wheat to justify higher nitrogen rates while others transitioned toward more extensive production using feed wheat and winter barley. Additionally, 38% of farms incorporated more legumes in cover crop mixtures despite higher seed costs (€60–70/ha), while one-third expressed concerns about long-term soil fertility, noting that reduced organic fertilization could deplete topsoil and decrease humus content over time (Res_6). A few farmers reported yield reductions of 10–15% in winter wheat and quality impacts, particularly 0.5% lower protein content resulting in revenue losses of €20–35 per ton when quality requirements were not met. Individual farmers also reported reduced protein content in grass silage, lower starch content in starch potatoes, and quality issues in malting barley. 3.4.2 Fertilization Approaches under Nitrogen Restrictions Two distinct fertilization strategies emerged in response to the mandatory 20% reduction in nitrogen application. Most farms (67%) implemented uniform reductions across all crops, with four eliminating the ear fertilization stage in cereals. These farms focused on improving nutrient efficiency through stabilized nitrogen fertilizers (8%), nitrification inhibitors (17%), increased processing of organic material in biogas plants (17%), and direct incorporation technologies (17%). The remaining farms (33%) reallocated nitrogen to high-value crops such as potatoes or cereals to maintain quality parameters where economically beneficial. 3.4.3 Farmer Attitude towards Regulatory Flexibility Our interviews explored farmers' attitudes toward a hypothetical policy scenario allowing farms to select from a catalog of measures while maintaining core regulatory requirements. Nearly all respondents (23 of 24) expressed positive attitudes toward increased regulatory choice, with only one participant fundamentally rejecting this approach. Seven participants, while generally supportive, expressed skepticism about practical implementation, noting that acceptance would depend on which measures remained mandatory versus optional. When asked about selection criteria for measures, economic considerations dominated (71% of respondents), with others citing site-specific conditions, agronomic factors, and operational workflows. Two-thirds of respondents (67%) believed a more flexible approach would positively affect groundwater protection by enabling farm-specific solutions tailored to different farm structures, weather conditions, soil properties, and available equipment. One farmer highlighted the motivational aspect: \"The acceptance of measures would be somewhat higher [...] and as a result, one approaches the work with more diligence and effort\" (Res_13), suggesting increased ownership through choice might enhance implementation quality. The remaining one-third of participants either doubted any effect on groundwater quality or declined to assess effectiveness. Concerns about red area boundary designation emerged as a noteworthy theme, with half of farms reporting substantial boundary changes over time that undermined acceptance of both the designation process and its political justification. One participant characterized the designation process as a \"lottery\" (Res_16), highlighting perceived arbitrariness. 3.4.4 Farmer-Generated Alternative Approaches When identifying measures with the greatest financial impact, arable farms (64%) cited the autumn fertilization ban with mandatory cover crop cultivation, followed by the 20% nitrogen reduction requirement. Livestock operations equally identified these measures along with organic fertilizer limits as burdensome. Despite these concerns, several current measures received support, with 63% of farm managers specifically endorsing mandatory cover crop cultivation as an effective water protection measure. Participants suggested several alternative approaches to nitrogen management in red areas (Table A1, Appendix). A widely supported proposal (endorsed by seven participants) was allowing needs-based fertilization of cover crops to improve soil humus development and erosion protection. Participants noted that improved cover crop establishment would help \"the soil conserve more nutrients\" (Res_8) and enhance environmental benefits. The most frequently suggested administrative reform (supported by eight participants) involved shifting from field-specific documentation to a farm-level nitrogen quota system based on cultivated crops. As one farmer explained: \"Perhaps the farm could be given a total nitrogen amount that can be distributed according to its own needs in certain areas\" (Res_13). Some participants reported already shifting nitrogen between crops to maintain quality and yield while adhering to the overall 20% reduction requirement. Four participants advocated for greater flexibility in application timing based on weather and soil conditions rather than fixed calendar dates, arguing that \"nature should be considered\" (Res_17) to improve nutrient use efficiency. Riparian buffer strips were suggested by four participants as an effective water protection measure, though they acknowledged the economic trade-offs. Participants reported reducing buffer strips following relaxed set-aside requirements due to administrative burden and lack of premiums for areas under 0.1 hectare, suggesting that streamlined administration and appropriate financial incentives could increase adoption. 3.5 Discussion 3.5.1 Farmer Perspectives on Nitrogen Regulations Our Q-methodology identified two distinct farmer perspectives that offer a more nuanced understanding of responses to nitrogen regulations than previous typologies. This finding complements Barnes et al.'s (2011) typology by revealing how environmental, economic, and social considerations integrate across both perspectives - with Factor 1 respondents prioritizing concerns about regulatory effectiveness and administrative requirements, and Factor 2 respondents emphasizing economic planning challenges and farm-specific approaches. Both groups showed considerable consensus on administrative burden, excessive stringency, economic disadvantages, and exclusion from decision-making, highlighting fundamental implementation challenges in Germany's approach that transcend individual farmer differences. Similar to Iversen et al.'s (2024) findings, our results suggest farmer perspectives are shaped by practical concerns about implementation rather than environmental values alone, challenging simplistic characterizations and supporting Feindt et al.'s (2019) argument that agricultural policies often rely on oversimplified understandings of farmer motivations. 3.5.2 Skepticism about Environmental Effectiveness A key finding is the widespread skepticism about environmental effectiveness and perceived fairness of regulations, mirroring findings from MacGregor and Warren (2006) and Barnes et al. (2009). Our participants questioned the causal relationship between their specific practices and groundwater contamination, particularly given the spatial designation of red areas some viewed as arbitrary. Some farmers suggested that water protection efforts should focus on public sewage systems and treatment plants rather than agriculture, indicating a deflection of responsibility. This skepticism about the scientific basis for regulations parallels Franklin et al.'s (2021) observations and appears reinforced by frequent boundary changes reported by respondents. Similarly, Elnagheeb et al. (1995) found that most U.S. farmers did not believe reducing fertilizer application on their farms would reduce water pollution. In contrast to Barnes et al. (2009), where the improvement in public perception due to better water quality is highlighted as a positive consequence of the NVZ measures, the farmers in our study do not emphasize this effect. 3.5.3 Adaptation Strategies and Innovation Under Regulatory Pressure Unlike Barnes et al.'s (2009) finding that Scottish farmers made minimal adjustments, our study reveals substantial technical and operational adaptations among German farmers, likely reflecting the more prescriptive nature of Germany's regulations. These adaptations include investments in (precision) application technology, manure storage capacity, fertilization strategies, and crop pattern modifications, though such investments are not equally feasible for all sizes of operations (Franklin et al., 2021; MacGregor and Warren, 2016). The adoption of precision farming technology aligns with Danish farmers' perspectives on its effectiveness (Iversen et al., 2024; Basso et al., 2016). This adoption pattern likely reflects economic considerations, as farmers tend to implement technologies that offer clear profitability benefits (Wang et al., 2023). This pragmatic approach helps explain why precision agriculture technology is preferred by farmers in our study despite scientific skepticism about its environmental benefits (Iversen et al., 2024). However, these adaptations represent both technical innovation and economic rationalization, challenging the notion that environmental regulations necessarily stifle innovation (Porter and van der Linde, 1995). 3.5.4 Preference for Farm-Specific Flexibility Our findings reveal a strong preference for farm-specific approaches over standardized measures, with 23 of 24 participants expressing positive attitudes toward increased implementation flexibility. This aligns with findings from multiple studies (Iversen et al., 2024; Stuhr et al., 2020; Franklin et al., 2021). More crucially, Franklin et al. (2021) found that fixed dates in Welsh NVZ regimes led farmers to prioritize regulatory compliance over responsive management based on weather and soil conditions, potentially increasing rather than decreasing environmental risks. This suggests a fundamental tension in nitrogen policy design between standardization (which aids monitoring and enforcement) and farm-specific adaptation (which may improve implementation and effectiveness). These findings challenge assumptions that standardized approaches necessarily produce optimal outcomes, suggesting instead that regulations allowing farm-specific implementation within clear parameters might achieve better results by harnessing farmers' knowledge while maintaining accountability, consistent with Porter and van der Linde's (1995) argument for outcome-based rather than technology-based regulations. 3.5.5 Unintended Consequences of Nitrogen Regulations Our study identified concerns about unintended consequences of nitrogen regulations. While the benefits of cover crops for reducing nitrate leaching are well-established (e.g. Abdalla et al., 2019), our participants reported that restrictions on organic fertilization and cover crop fertilization in autumn could undermine their effectiveness by reducing biomass production, and consequently, both nitrogen capture and carbon sequestration. These concerns highlight how regulations that narrowly focus on nitrogen leaching might affect other environmental goals. The shift toward more extensive cereal varieties affects protein content and product quality, with implications for farm profitability (Kage et al., 2022; Schröer et al., 2022). 3.5.6 Farmer-Generated Alternatives Farmers reported cultivating wheat varieties with higher nitrogen requirements to be able to use more nitrogen on the farm. In line with this, some farm managers also reported that nitrogen is shifted between crops anyway in order to ensure quality and yield. This means that the 20% reduction is complied with at farm level or on land in red areas, but nitrogen is used more flexibly. This also corresponds to the widely supported proposal for farm-level nitrogen quotas rather than field-specific documentation requirements, which aligns with Barnes et al.'s (2009), Stuhr et al.'s (2020) as well as MacGregor and Warren's (2006) observations about administrative burden by offering specific alternatives that maintain environmental accountability while reducing paperwork requirements. 3.6 Implications Our findings have important implications for both theory and practice in environmental regulation. Theoretically, they support Porter and van der Linde's (1995) contention that well-designed environmental regulations can stimulate innovation, while suggesting that poorly designed implementation approaches may create unnecessary costs and resistance. The observed disconnect between regulatory structure and on-farm realities reinforces Blanc's (2018) argument that effective regulation requires implementation systems that are anchored in practical realities. Regulatory approaches must balance environmental objectives with economic and agricultural realities. Improving transparency in measuring and communicating nitrate reduction outcomes could enhance acceptance among farmers that are skeptical about environmental effectiveness. Meanwhile, more flexible implementation frameworks that account for farm-specific conditions and provide greater planning certainty would likely improve compliance while maintaining environmental goals. This balance recognizes that effective regulations must address both environmental protection and agricultural viability as complementary rather than competing objectives. Streamlining documentation and reporting requirements represents a promising direction for policy improvement that does not compromise environmental objectives. A farm-level nitrogen quota system based on cultivated crops instead of field-specific documentation would maintain accountability while reducing the paperwork burden. This approach could redirect farmers' attention from compliance documentation to improved nitrogen management practices. Combining mandatory baseline requirements with voluntary enhanced measures could improve both compliance and effectiveness. Offering choices within a clear regulatory framework would increase ownership and likely enhance implementation quality. This approach could include mandatory core measures addressing the most critical nitrogen pathways, supplemented by a menu of optional measures from which farmers could select based on their specific farm conditions and economic considerations. Such flexibility within a structured framework strikes a balance between the need for consistent environmental protection and the diversity of agricultural systems. Improving the stability of regulations would enhance farmers' ability to adapt their operations effectively and make appropriate investments. Long-term regulatory frameworks with clear trajectories would support investment planning and strategic adaptation. Reducing frequent boundary changes and shifting requirements would provide the consistency needed for farmers to develop and implement comprehensive adaptation strategies. This stability is particularly important given the substantial investments required for some adaptations, such as increased storage capacity or precision application technology. 3.7 Limitations This study has several important considerations that should be kept in mind when interpreting our findings. First, our strategically selected, but non-random sample of 24 farmers provided insights into distinct subjective viewpoints regarding farming in red areas. In accordance with Q methodology, we were able to reveal the structure of perspectives within our purposively selected respondents. The perspectives identified represent meaningful viewpoint configurations that occur among these farmers, though additional viewpoints might exist beyond those captured in our analysis. This is especially relevant, as the high correlation reveals a large common ground in farmers perceptions across factors. Second, our reliance on self-reported impacts (such as yield reductions) without independent verification means these findings should be interpreted as farmers' perceptions rather than objectively measured outcomes. Finally, while we documented various adaptation strategies, we did not comprehensively assess their effectiveness in reducing nitrate leaching or their long-term economic viability, which would require longitudinal data and environmental measurements beyond the scope of this study. 4 Concluding Remarks This study examined farmers' perceptions and adaptations to stringent nitrogen regulations in Germany's red areas, revealing two distinct perspectives: one centered on environmental effectiveness skepticism and administrative burden, and another focusing on economic planning challenges and farm-specific flexibility needs. Despite these differences, both perspectives question the current regulatory approach's efficacy and implementation. Farmers have responded with substantive adaptations, including technology investments, crop selection adjustments, and fertilization strategy modifications. Our findings suggest that sustainable nitrogen management requires collaborative approaches that leverage farmers' practical knowledge while maintaining environmental accountability. Balancing mandatory core requirements with farm-specific flexibility could enhance regulatory acceptance and implementation effectiveness, potentially yielding better environmental outcomes than increased stringency alone. Declarations The authors report there are no competing interests to declare. References Abdalla, M., Hastings, A., Cheng, K., Yue, Q., Chadwick, D., Espenberg, M., ... & Smith, P. (2019). A critical review of the impacts of cover crops on nitrogen leaching, net greenhouse gas balance and crop productivity. Global change biology , 25 (8), 2530-2543. https://doi.org/10.1111/gcb.14644 Barnes, A. P., Willock, J., Hall, C., & Toma, L. (2009). Farmer perspectives and practices regarding water pollution control programmes in Scotland. 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(2014): qmethod: A Package to Explore Human Perspectives Using Q Methodology. The R Journal, 6 (2), 163–173. DOI: 10.32614/rj-2014-032. Footnotes For an overview of the general DüV see Kuhn et al. ( 2020 ). A full overview is given in Table A1 , Appendix. Note: Added by the authors to clarify the quote. Additional Declarations The authors declare no competing interests. Supplementary Files Appendix.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-7574476\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":512557336,\"identity\":\"527dfe63-7837-49bc-b7a4-f862178cae78\",\"order_by\":0,\"name\":\"Marius Michels\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"https://orcid.org/0000-0002-4391-4457\",\"institution\":\"Georg-August-Universität Göttingen\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Marius\",\"middleName\":\"\",\"lastName\":\"Michels\",\"suffix\":\"\"},{\"id\":512557337,\"identity\":\"b90246cf-7950-4208-8c04-9a4aeca1fc30\",\"order_by\":1,\"name\":\"Malte Behrens\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Georg-August-Universität Göttingen\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Malte\",\"middleName\":\"\",\"lastName\":\"Behrens\",\"suffix\":\"\"},{\"id\":512557338,\"identity\":\"0347f4df-7bef-46a5-a7db-d7b8ed09d15c\",\"order_by\":2,\"name\":\"Hendrik Wever\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Georg-August-University of Goetting\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Hendrik\",\"middleName\":\"\",\"lastName\":\"Wever\",\"suffix\":\"\"},{\"id\":512557339,\"identity\":\"9cc4fb80-0b6c-4da6-8cef-1f86913d9b68\",\"order_by\":3,\"name\":\"Oliver Mußhoff\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Georg-August-Universität Göttingen\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Oliver\",\"middleName\":\"\",\"lastName\":\"Mußhoff\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-09-09 13:46:55\",\"currentVersionCode\":1,\"declarations\":{\"humanSubjects\":true,\"vertebrateSubjects\":false,\"conflictsOfInterestStatement\":false,\"humanSubjectEthicalGuidelines\":true,\"humanSubjectConsent\":true,\"humanSubjectClinicalTrial\":false,\"humanSubjectCaseReport\":false,\"vertebrateSubjectEthicalGuidelines\":false},\"doi\":\"10.21203/rs.3.rs-7574476/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-7574476/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":90981599,\"identity\":\"2dc55531-1c66-4df4-8889-457ca3efbf22\",\"added_by\":\"auto\",\"created_at\":\"2025-09-10 09:24:56\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":2128090,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eRed areas in Lower Saxony and distribution of participants. The gray areas show the districts in Lower Saxony, while the red shaded parts show the red areas under §13a DüV.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7574476/v1/4c2a19e10f0e06dec7fdd52f.png\"},{\"id\":90981598,\"identity\":\"a340b706-c3aa-4ac5-a07b-b1d14e4c17e4\",\"added_by\":\"auto\",\"created_at\":\"2025-09-10 09:24:56\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":24961,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eQ-Sort grid\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7574476/v1/faf0c8b5398c32a1c97a89c9.png\"},{\"id\":90984251,\"identity\":\"4fca7d10-78ba-4d68-88e4-2de94129329c\",\"added_by\":\"auto\",\"created_at\":\"2025-09-10 09:40:58\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":4114259,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7574476/v1/4a480079-392f-4f1a-baa8-75ae9f5ac8c7.pdf\"},{\"id\":90981604,\"identity\":\"361741c6-dc5e-44ed-9b0a-1cdab319cc7c\",\"added_by\":\"auto\",\"created_at\":\"2025-09-10 09:24:57\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":2875120,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Appendix.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7574476/v1/28f797f17e94a54391873f47.docx\"}],\"financialInterests\":\"The authors declare no competing interests.\",\"formattedTitle\":\"\\u003cp\\u003e\\u003cstrong\\u003eFarmer Perceptions and Adaptations to Nitrogen Regulations in Germany: A Q-Methodology Analysis\\u003c/strong\\u003e\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"1 Introduction\",\"content\":\"\\u003cp\\u003eNitrogen fertilizers are essential for modern agricultural production (Liu et al., \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e), contributing to global yield increases and food security (Smil, \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e2002\\u003c/span\\u003e). However, crops typically absorb only about half of applied nitrogen (Galloway et al., \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e; Lassaletta et al., \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e), with the remainder lost to the environment, causing eutrophication, groundwater contamination, and climate change acceleration (Galloway et al., \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e; Liu et al., \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Poor nitrogen management hinders achievement of UN sustainability goals (Sachs et al., \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e) and addressing nitrogen pollution is crucial for tackling climate change (Kanter, \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eIn response to mounting environmental concerns associated with nitrogen surpluses, various policy measures have been developed to regulate agricultural nitrogen use (Kanter et al., \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2020a\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003eb\\u003c/span\\u003e). The European Union's (EU) 1991 Nitrates Directive (91/676/EEC) requires Member States to designate Nitrate Vulnerable Zones (NVZs) where groundwater nitrate concentrations exceed 50 mg/l (European Commission, n.d.). Some Member States, such as Ireland and Denmark, have designated almost their entire national territory as an NVZ (Dalgaard et al., \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e; Ortmeyer et al., \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), thereby applying uniform restrictions across all agricultural land. However, Denmark has, since 2016, complemented this uniform designation with so-called \\u003cem\\u003etargeted regulations\\u003c/em\\u003e which introduce spatially differentiated measures in particularly vulnerable areas while allowing more flexibility elsewhere. By contrast, countries such as Scotland or France have only designated specific areas as NVZ (Ortmeyer et al., \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e; Barnes et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eGermany employs a spatially differentiated approach, with 22% of groundwater bodies exceeding the threshold (Umweltbundesamt, \\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Similar to Denmark, Germany has also designated its entire territory as an NVZ. However, Germany employs an additional two-tier system: within the nationwide NVZ designation, specific \\u0026ldquo;red areas\\u0026rdquo; (\\u003cem\\u003erote Gebiete\\u003c/em\\u003e) under \\u0026sect;\\u0026nbsp;13a of the German Fertilizer Ordinance (D\\u0026uuml;ngeverordnung, D\\u0026uuml;V)[1]\\u003ca class=\\\"FNLink\\\" href=\\\"#Fn1\\\" id=\\\"#FNLinkFn1\\\"\\u003e\\u003c/a\\u003e (Bundesministerium der Justiz und f\\u0026uuml;r Verbraucherschutz, n.d.) are subject to stricter rules, such as a mandatory 20% reduction in nitrogen fertilization relative to crop requirements[2]\\u003ca class=\\\"FNLink\\\" href=\\\"#Fn2\\\" id=\\\"#FNLinkFn2\\\"\\u003e\\u003c/a\\u003e (Bundesinformationszentrum Landwirtschaft, \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2025\\u003c/span\\u003e). Federal states may also adopt additional measures. This differs from Denmark\\u0026rsquo;s outcome-based targeted regulation approach, as Germany relies on a binary distinction between red and non-red areas.\\u003c/p\\u003e\\u003cp\\u003eHowever, Germany\\u0026rsquo;s \\u0026sect;\\u0026nbsp;13a D\\u0026uuml;V framework is more prescriptive and administratively demanding than typical NVZ regimes, potentially creating economic disparities between farms inside and outside the red areas (Barnes et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e; Schr\\u0026ouml;er et al., \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), raising questions about environmental effectiveness (Barnes et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e; Deutscher Bauernverband, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Franklin et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e), and generating social tensions (Barnes et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e; Landvolk Niedersachsen, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). This interplay of technical stringency, spatial differentiation, and socio-political implications provides a unique context for examining farmer responses to nitrogen regulations.\\u003c/p\\u003e\\u003cp\\u003eEffective (environmental) regulation depends on both technical design and implementation (Porter and van der Linde, 1995), clear objectives anchored in practical realities (Blanc, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e; Stuhr et al., 2020), and feasible integration of measures into farming systems by farmers(e.g. Moreddu, \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e). Regulatory approaches may achieve only transient change without creating cultural shifts (Mills et al., \\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e; Stuhr et al., 2020), and often rely on oversimplified understanding of farmers' motivations (Feindt et al., \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). Porter and van der Linde (1995) contend that such regulations should have clear goals, flexible approaches, and incentives for innovation \\u0026ndash; characteristics that may be variably present in Germany's red area designations under \\u0026sect;\\u0026nbsp;13a D\\u0026uuml;V. Understanding farmers' perceptions and adaptations is therefore essential to evaluate and potentially refine regulations to achieve not only short-term compliance but lasting environmental improvements.\\u003c/p\\u003e\\u003cp\\u003ePrevious studies provide valuable insights into farmer attitudes and responses to nitrate regulations, yet they highlight persistent tensions between regulatory intent and on-farm realities. Scottish farmers frequently expressed limited perceived responsibility for water pollution, being unfairly penalized by the restrictions, distrust in regulations, and dissatisfaction with the costs and administrative burdens of NVZ regulations (MacGregor and Warren, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e2006\\u003c/span\\u003e; Barnes et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e). Likewise, Welsh dairy farmers display distrust in the scientific basis for the regulation (Franklin et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). While environmental concern can encourage mitigation, profit-maximizing attitudes may reduce compliance (Toma et al., \\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e). Nevertheless, a 2016 follow-up study interviewing the same farmers as in 2006 shows that NVZ has made farmers more aware of environmental issues, and they now pose fewer objections to the requirements than before, suggesting both attitudinal and behavioral change over time (McGregor and Warren, 2016). In spite of such potential, in other studies most farmers made only minimal adjustments in practices, such as record-keeping, without substantial investment in measures such as manure storage (Barnes et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e). Franklin et al. (\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e) showed that investment in manure storage was needed but often not economically feasible for smaller dairy farmers, as also reported by MacGregor and Warren (\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e) for Scottish farmers.\\u003c/p\\u003e\\u003cp\\u003eFranklin et al. (\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e) further identified unintended consequences of rigid regulatory frameworks, noting that inflexible closed periods can paradoxically increase environmental risks when farmers apply manure immediately after restriction periods end, regardless of field conditions. This represents a shift toward \\\"farming for regulations\\\" rather than responding adaptively to environmental and weather conditions. Regarding farming for (or against) regulations, Barnes et al. (\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e) developed a typology of farmers in NVZ contexts, identifying three distinct groups: \\\"multi-functionalists\\\" who embrace environmental and social values; \\\"resistors\\\" who prioritize resource maximization and oppose regulation; and \\\"apathists\\\" who remain largely disengaged from the regulatory discourse. More recently, Iversen et al. (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e) revealed important disconnects between scientific and practitioner perspectives in Denmark. While scientists advocate ecosystem-based approaches, farmers strongly prefer flexible, locally-adapted measures. A particularly notable divergence concerns precision agriculture technologies. Danish farmers view these as effective NVZ management tools (Iversen et al., \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e), a perspective supported by Basso et al. (\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e), yet Danish scientists attribute only minimal environmental benefits to precision fertilization techniques (Iversen et al., \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eWhile these studies provide valuable insights into farmer responses to NVZ regulations in various contexts, three gaps remain in our understanding of how farmers respond to particularly stringent nitrogen regulations like Germany's red areas. First, previous research has primarily examined regulatory frameworks that are less prescriptive than Germany's approach. Second, there remains limited understanding of how farmers' viewpoints on nitrogen regulations integrate environmental, economic, and social considerations under these particularly stringent conditions. Third, existing research has primarily focused on documenting farmer responses to established regulatory frameworks rather than exploring farmer perspectives on alternative approaches that might better balance environmental protection with agricultural viability.\\u003c/p\\u003e\\u003cp\\u003eAgainst this background, this study aims to examine farmers' perceptions and adaptation strategies in response to stringent nitrogen regulations in designated red areas in Germany under \\u0026sect;\\u0026nbsp;13a D\\u0026uuml;V. Specifically, we seek to: (1) identify distinct viewpoints among farmers regarding the regulatory framework and its impacts along ecological, economic and social dimensions; (2) document the technical, operational, and economic adaptations implemented by farmers in response to these regulations; and (3) explore farmers' perspectives on potential alternative regulatory approaches that might achieve environmental objectives while better accommodating farm-specific conditions.\\u003c/p\\u003e\\u003cp\\u003eWe conducted a mixed-methods study combining Q-methodology with qualitative interviews of 24 conventional farm managers in Lower Saxony, Germany (December 2024-January 2025). Lower Saxony provides an ideal study region as it contains one of the highest percentages of designated red areas among German federal states (30% of agricultural land), has diverse agricultural systems including both intensive livestock and crop production, and has implemented additional state-specific nitrogen management measures beyond the federal requirements. Q-methodology offers unique advantages for this research context by enabling the systematic identification of shared viewpoints while preserving individual perspectives, unlike traditional survey methods that may average out important distinctions in farmer attitudes. By supplementing the Q-methodology with qualitative interviews, we gain deeper insights into farmers' adaptation strategies and their reasoning behind specific responses to regulations. Participants were strategically selected with the sole criterion that they manage agricultural land within designated red areas under \\u0026sect;\\u0026nbsp;13a D\\u0026uuml;V. The study framework incorporated the three sustainability pillars (ecological, economic, and social) to examine nitrogen regulations' impacts, recognizing that regulatory success requires balance across these dimensions.\\u003c/p\\u003e\\u003cp\\u003eThis study makes several novel contributions to the literature on effective agricultural nitrogen policy. First, it provides empirical evidence of farmer responses to one of Europe's most stringent implementations of the EU Nitrates Directive, revealing how increasingly prescriptive regulations affect farmer perceptions and behaviors. Second, we identify how ecological, economic, and social considerations are integrated in farmer perspectives under stringent regulatory conditions, demonstrating that concerns transcend simple economic impacts to include broader issues of planning security, professional identity, and regulatory trust. Third, we document how farmers' adaptation strategies under strict regulatory constraints reveal both innovative responses and potential unintended consequences of current policy approaches, including shifts in crop selection and quality parameters. Fourth, we address the knowledge gap regarding regulatory alternatives by analyzing farmer-generated policy proposals that could enhance both environmental outcomes and agricultural sustainability, offering concrete pathways for policy reform based on practitioner insights. Our findings extend beyond Lower Saxony, offering valuable insights for regions considering similar regulatory approaches to address nitrate pollution concerns. This makes our case study an important reference point for policymakers, advisors, and other stakeholders working to improve nitrogen management and policies while maintaining agricultural viability.\\u003c/p\\u003e\"},{\"header\":\"2 Material and Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e2.1 Survey and Data Collection\\u003c/h2\\u003e\\n \\u003cp\\u003eThis study surveyed 24 farm managers from Lower Saxony, Germany, using a strategic sampling approach as recommended by Watts and Stenner (2005) to capture diverse perspectives. The primary selection criterion required participants to manage agricultural land within red areas designated under \\u0026sect;\\u0026nbsp;13a D\\u0026uuml;V. We ensured diversity by including livestock operations in addition to arable farms. Participant recruitment followed a dual approach: direct contact through existing networks and referrals from advisors. Personal face-to-face expert interviews were conducted between December 11, 2024, and January 15, 2025. The survey received ethical approval from the German Association for Experimental Economic Research. Prior to data collection, all participants received a brief introduction to the research and its objectives. They were informed about participation conditions and data protection provisions, which required their active consent. Figure\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e shows the red areas in Lower Saxony and distribution of participants across the federal state. Red areas constitute 30% of agricultural land and 16.7% of the federal state.\\u003c/p\\u003e\\n \\u003cp\\u003eThe Q-methodology implementation required the development of a Q-sample comprising statements representing diverse viewpoints on the topic (Table \\u003cspan class=\\\"InternalRef\\\"\\u003eA2\\u003c/span\\u003e, Appendix). We derived the Q-sample through comprehensive analysis of both scientific and gray literature related to the research topic. Statement selection focused on identifying challenges and opportunities presented by nitrogen regulation for agricultural operations. To maintain methodological balance, we included an equal distribution of statements across the three sustainability dimensions \\u0026ndash; ecological, economic, and social \\u0026ndash; within the Q-sample. Two farmers pre-tested all statements to ensure comprehensibility and relevance prior to implementation.\\u003c/p\\u003e\\n \\u003cp\\u003eThe interview protocol consisted of three parts: (1) a questionnaire capturing farm and operator characteristics; (2) the Q-sorting exercise requiring participants to arrange statements on a quasi-normal distribution grid ranging from \\u0026minus;\\u0026thinsp;4 (strongly disagree) to +\\u0026thinsp;4 (strongly agree) (Fig. 2); and (3) follow-up questions addressing extreme rankings, adaptations to regulations, and perspectives on mandatory versus voluntary measures. This approach facilitated both quantitative analysis of sorting patterns and qualitative understanding of participants\\u0026apos; underlying rationales and experiences with regulations in red areas under \\u0026sect; 13a D\\u0026uuml;V. The questionnaire can be found in the Appendix.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e2.2 Data Analysis\\u003c/h2\\u003e\\n \\u003cp\\u003eThe analysis of the second part was conducted using the \\u003cem\\u003eqmethod\\u003c/em\\u003e package in \\u003cem\\u003eR\\u003c/em\\u003e (Zabala, \\u003cspan class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e), following established Q-methodology procedures. We performed principal component analysis (PCA) with varimax rotation to identify distinct participant perspectives. The initial factor extraction began with seven factors, which was subsequently refined based on multiple criteria. Factors with eigenvalues above 1.0 (Watts and Stenner, 2005) were retained and evaluated using parallel analysis. The final factor selection was based on several criteria, including explained variance, standard errors, and factor loadings. Particular attention was paid to achieving sufficient variance explanation (\\u0026gt;\\u0026thinsp;50%) while maintaining interpretability. In the final analysis, consensus statements (similar z-scores across all factors) and distinguishing statements (statistically significantly different z-scores between factors) were identified. Data and code can be found in: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://osf.io/6xq2v/\\u003c/span\\u003e\\u003c/span\\u003e. The interviews were recorded and initially transcribed. The resulting text was subsequently reviewed and corrected twice. For further analysis, the finalized transcripts were imported into \\u003cem\\u003ef4 analysis\\u003c/em\\u003e software and evaluated.\\u003c/p\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"3 Results and Discussion\",\"content\":\"\\u003cdiv id=\\\"Sec6\\\"\\u003e\\n \\u003ch2\\u003e3.1 P-Sample Characteristics\\u003c/h2\\u003e\\n \\u003cp\\u003eThe P-Sample consists of 24 farmers of which 91% are male with an average age of 39 years (Min. 23; Max. 63), 37.5% completed a two-year vocational school, 29.2% held a Master’s degree, 16.7% a Bachelor’s degree, 8.3% a Diploma, 4.2% a Ph.D., and 4.2% a Master craftsman certificate. On average, the farmers assessed themselves as risk-seeking (7.0), innovative (7.4) and relatively successful compared to other farmers (7.2) – all measured on an 11-point scale from 0 to 10. Regarding their knowledge of the current German fertilizer regulation, they rated themselves with an average 3.4 on a 5-point scale from 1 to 5. Regarding their farm, average precipitation is 682 mm/year and average soil quality is 43 (Min. 22; Max. 85) on a scale from 0 to 100. Many, 58.4%, of the farmers have an opportunity to irrigate their fields. They cultivate on average 196.8 hectares of arable land (Min. 62.5; Max. 570) and 15.6 hectares of grassland (Min. 0; Max. 115). On average, 23.6% of the farmers’ cultivated area is located in water protection areas and 76.0% in red areas. Just over half, 58.3%, have livestock on their farm besides arable farming and 8.3% have special crops (e.g. vegetables). Regarding machinery for fertilizer application, 95.8% have a fertilizer spreader or field sprayer. In addition, 45.8% apply organic fertilizers. All farms are managed conventionally. Detailed results are shown in the Table A3, Appendix.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec7\\\"\\u003e\\n \\u003ch2\\u003e3.2 Factor Extraction and Selection\\u003c/h2\\u003e\\n \\u003cp\\u003eOur initial factor analysis extracted multiple factors, with eigenvalues suggesting potential extraction of up to seven factors. While parallel analysis suggested a single-factor solution (Figure A1, Appendix) explaining 52.8% of variance, this would obscure important distinctions in farmer perspectives. The 2-factor solution we selected explains 59.4% of total variance (Factor 1: 31.5%, Factor 2: 27.9%) and demonstrates high composite reliability scores (both 0.98) with low standard errors (0.16 and 0.14). While a 3-factor solution was also considered, it only increased explained variance by a marginal 5.79% (resulting in a total of 65.2% explained variance), while introducing a factor with a substantially higher standard error (0.33 for Factor 3 compared to 0.16 and 0.15 for Factors 1 and 2). Hence, the 2-factor solution was chosen. This solution achieves strong representation of respondent viewpoints with 22 of 24 participants (91.7%) distinctly loading on one of the two factors. Table\\u0026nbsp;1 shows the distribution of participants among the two factors. Furthermore, the factor correlation of 0.75 indicates that while these perspectives share some common ground, they maintain distinct viewpoints on key issues, as evidenced by the 14 distinguishing statements between factors (Table 3). The 2-factor solution therefore provides the optimal balance between methodological robustness and the ability to capture meaningful distinctions in farmers' perspectives on nitrogen regulations.\\u003c/p\\u003e\\n \\u003cdiv\\u003e\\n \\u003ctable id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv\\u003eTable 1\\u003c/div\\u003e\\n \\u003cdiv\\u003e\\n \\u003cp\\u003eFactor loadings by respondent\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFactor\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLoading respondents\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTotal\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRes_1, Res_4, Res_5, Res_10, Res_11, Res_15, Res_19, Res_20, Res_21, Res_23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRes_2, Res_6, Res_8, Res_9, Res_12, Res_13, Res_14, Res_16, Res_17, Res_18, Res_22, Res_24\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNo load\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRes_3, Res_7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"3\\\"\\u003eRes = Respondent\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cp\\u003eOur analysis revealed several consensus statements that were similarly ranked across both identified factors, indicating areas of shared perspective among farmers regardless of their overall viewpoint on nitrogen regulations. These consensus statements provide important insights into common ground in farmers' perceptions (Table\\u0026nbsp;2). The results of Table\\u0026nbsp;2 are shown graphically via z-scores in Figure A2, Appendix. Table A4 in the Appendix shows the factor loadings.\\u003c/p\\u003e\\n \\u003cp\\u003eBoth groups agree on the administrative burden associated with complex regulations and documentation requirements (Statement (S) 17, + 4 and + 3), highlighting universal concern about bureaucratic demands. Similarly, farmers across both perspectives concurred that fertilizer regulations are excessively strict and fail to account for crop-specific needs and soil conditions (S5, + 3 and + 2), reflecting shared skepticism about regulatory appropriateness. Economic concerns also formed an area of consensus, with both groups acknowledging that restrictions in red areas create economic disadvantages through negative impacts on yields and efficiency (S9, + 2 for both factors). Additionally, farmers across both perspectives expressed feelings of exclusion from decision-making processes, contributing to a sense of powerlessness (S25, + 2 for both factors). Both groups demonstrated similar rejection of statements that suggest positive environmental outcomes from the regulations. They disagreed with claims that the regulations protect general public interests while ensuring environmental health and agricultural sustainability (S2, -4 and − 3). Likewise, both groups rejected assertions that regulations promote biological product adoption for environmental protection purposes (S6, -2 for both factors). Notably, both groups maintained neutral positions regarding the effectiveness of official advisory services (S18, scored 0 for both factors), indicating shared ambivalence about support systems for regulatory compliance. Descriptive statistics of the factors which determined the two groups are shown in Table A3, Appendix.\\u003c/p\\u003e\\n \\u003cdiv\\u003e\\n \\u003ctable id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv\\u003eTable 2\\u003c/div\\u003e\\n \\u003cdiv\\u003e\\n \\u003cp\\u003eFactor scores for statements on the ecological, economic and social dimension on cultivation in red areas under 13a DüV\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eStatement\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFactor 1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFactor 2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colspan=\\\"3\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eEcological Dimension (Environmental and Sustainability Aspects)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colspan=\\\"3\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eEconomic Dimension\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e9 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e16\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colspan=\\\"3\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eSocial Dimension (Psychological-Social and Administrative/Regulatory Aspects)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e17 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e18 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e19\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e20\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e22 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e23 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e24\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25 C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCharacteristics\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePercentage of variance explained\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e31.50%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e27.92%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNumber of loading Q-Sorts\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEigenvalues\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.70\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eComposite reliability\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.98\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.98\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eStandard error of factor scores\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.16\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"3\\\"\\u003eNote: Scores range from + 4 (highest agreement) to -4 (lowest agreement). Statements marked (C) represent consensus viewpoints with similar rankings across all three factors. Statements without a mark are distinguishing statements between factors at p \\u0026lt; 0.05.\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\n \\u003cdiv\\u003e3.3 Factor Analysis Results\\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec8\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eFactor 1 (Environmental Effectiveness Skepticism and\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eAdministrative Burden Perspective)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003eFactor 1 explains 31.5% of the total study variance, with 10 farm managers loading on this perspective. This viewpoint is characterized by strong skepticism regarding the environmental effectiveness of nitrogen regulations coupled with substantial concerns about administrative requirements.\\u003c/p\\u003e\\n \\u003cp\\u003eThe defining feature of this perspective is the categorical rejection of claims about environmental benefits from regulations in red areas. Farmers aligned with Factor 1 strongly disagree that regulations protect public interests by ensuring a healthy environment while making agricultural practices sustainable (S2, -4), protect groundwater (S1, -3), or improve water quality in adjacent surface waters (S4, -3). This skepticism is reinforced by participants' observations that nitrate levels \\\"were already decreasing before and were at a very low level\\\" (Int_10) and criticism that regulations are \\\"simply too generalized\\\" (Res_11).\\u003c/p\\u003e\\n \\u003cp\\u003eA distinctive characteristic of Factor 1 respondents is their belief that agriculture is disproportionately targeted while other pollution sources receive insufficient attention. Fifty percent of these farmers suggested focusing water protection efforts on public sewage systems and treatment plants. One farmer stated that \\\"agriculture is being targeted because it's the easiest area to implement changes\\\" (Res_21).\\u003c/p\\u003e\\n \\u003cp\\u003eAdministrative burden emerges as the most substantial concern for this group, with strong agreement that complex regulations and documentation requirements represent a high administrative burden (S17, + 4). One farmer expressed frustration about the time investment: \\\"Because it's just insanely time-intensive [...]\\\" (Res_1). Another suggested that \\\"[…] part of the solution would be to make the entire regulatory framework leaner and not incorporate new changes annually\\\" (Res_19).\\u003c/p\\u003e\\n \\u003cp\\u003eFactor 1 respondents strongly agree that constant adjustments and complexity lead to stress and uncertainty among farmers (S19, + 3). The psychological impact of regulatory pressure is substantial, with one participant observing that \\\"the stress effects and effects of perceived pressure now almost overshadow the economic consequences for many farmers\\\" (Res_19), indicating that emotional burden weighs more heavily than economic effects for this group.\\u003c/p\\u003e\\n \\u003cp\\u003eThese farmers perceive a fundamental shift away from agronomic principles toward compliance-focused farming: \\\"You do not focus on how to better supply the plants to improve things, but only on what regulations you have and how to comply with them\\\" (Res_15). The constant regulatory changes have led to a sense of futility among some farmers, as illustrated by one participant describing a colleague who said: \\\"I do not care anymore, I'll continue fertilizing as before, it's too much back and forth for me\\\" (Res_11).\\u003c/p\\u003e\\n \\u003cp\\u003eIn addition to acknowledging economic disadvantages from the regulations (S9, + 2), Factor 1 respondents also feel excluded from decision-making processes (S25, + 2) and agree that constant adaptation to new regulations causes stress and decreases identification with the farming profession (S22, + 2). They perceive the regulations as too strict and failing to consider crop-specific needs and soil conditions (S5, + 3), emphasizing a disconnect between regulatory approaches and agricultural realities.\\u003c/p\\u003e\\n \\u003cp\\u003eThis perspective represents a fundamental challenge to current regulatory approaches, questioning their environmental necessity and effectiveness while highlighting administrative, psychological, and professional identity costs for farmers operating in red areas.\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eFactor 2 (Economic Planning and Farm-Specific Flexibility Perspective)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003eFactor 2 explains 27.9% of the total study variance, with 12 farmers loading on this perspective. This viewpoint emphasizes economic planning challenges and the need for farm-specific flexibility in regulatory approaches.\\u003c/p\\u003e\\n \\u003cp\\u003eThe most distinctive feature of this perspective is the strong emphasis on the generalized nature of regulations that fail to account for individual farm conditions. Farmers aligned with Factor 2 showed the highest agreement with the statement that regulations are too generalized and do not consider the specific conditions of individual farms, leading to inefficient resource use (S7, + 4). One participant highlighted how current regulations neglect important soil science factors: \\\"I find these professional aspects, such as the C/N ratio and the soil's ability to store nutrients through clay minerals, are completely inadequately addressed\\\" (Res_13). Others noted how the blanket regulations fail to accommodate different farming systems, particularly forage production, and that in general \\\"fertilization must always match yield potential\\\" (Res_17).\\u003c/p\\u003e\\n \\u003cp\\u003eFactor 2 respondents strongly rejected the notion that their production programs have changed substantially due to red area regulations (S11, -4), the statement ranked most negatively by this group. This response appears influenced by both farm characteristics and cropping choices. On average, these farms have less land in red areas (68% compared to 85% for the Factor 1 group) and often grow crops that are less sensitive to fertilizer restrictions. As two farmers explained: \\\"Because we have this diverse crop rotation, we have fewer problems\\\" (Res_13) and \\\"For us it hasn't changed because potatoes are simply our number one crop\\\" (Res_6). Winter cereals and winter rapeseed reportedly suffer greater yield losses from reduced fertilization (Res_1) than spring crops, particularly root crops like sugar beets and potatoes (Res_8).\\u003c/p\\u003e\\n \\u003cp\\u003ePlanning security emerges as a crucial concern for this perspective, with strong agreement that regulations reduce planning security and do not contribute to long-term cultivation and operational strategies (S10, + 3). One participant described this frustration: \\\"This lack of planning security is simply annoying. Sometimes you're in [the red areas][3], sometimes you're out\\\" (Res_6). Notably, 75% of Factor 2 respondents spontaneously mentioned changes to red area boundaries during interviews, compared to only 20% of Factor 1 respondents. This suggests these farmers particularly value stable planning conditions for operational strategy.\\u003c/p\\u003e\\n \\u003cp\\u003eFactor 2 respondents strongly disagreed with the statement that community projects and cooperations in red areas strengthen social cohesion and promote exchange of best practices (S21, -3), indicating skepticism about collaborative approaches. This aligns with their general preference for individual farm-specific solutions rather than standardized or community-based initiatives. Some Factor 2 respondents from regions with historically low livestock density expressed surprise at being affected by the regulations, with one noting that farms in their area \\\"have long used purely mineral fertilizer products and have already followed recommendations \\\" (Res_12).\\u003c/p\\u003e\\n \\u003cp\\u003eThis viewpoint represents a pragmatic challenge to the current regulatory framework, accepting the necessity of nitrogen management while advocating for more flexible, farm-specific approaches that better account for diverse cropping systems, soil conditions, and farm characteristics while providing the planning security needed for operational stability.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec9\\\"\\u003e\\n \\u003ch2\\u003e3.4 Results from the Interviews\\u003c/h2\\u003e\\n \\u003cdiv id=\\\"Sec10\\\"\\u003e\\n \\u003ch2\\u003e3.4.1 Adaptation Strategies to Red Area Regulations\\u003c/h2\\u003e\\n \\u003cp\\u003eThe most important adaptation was investment in new technology, with 54% of farms investing in agricultural machinery through the \\\"Agricultural Investment Program\\\" administered by the German \\u003cem\\u003eLandwirtschaftliche Rentenbank\\u003c/em\\u003e and introduced by the Federal Ministry of Agriculture (BMEL, 2024). These investments primarily focused on precision application technology (59%) and fertilizer distribution equipment (40%) to enable more efficient nutrient utilization. One-quarter of participating farms planned to implement application maps to target \\\"the right amounts on specific areas\\\" (Res_10).\\u003c/p\\u003e\\n \\u003cp\\u003eLivestock operations faced particular challenges with manure management due to autumn fertilization restrictions and the 170 kg N/ha organic fertilizer limit. Four farms, primarily pig producers, invested €200,000-250,000 each in additional storage capacity for organic fertilizer, while farms in high livestock density regions reported increased transport costs for organic fertilizers, reaching €10 per cubic meter (Res_17).\\u003c/p\\u003e\\n \\u003cp\\u003eTwo key trends emerged in cropping system adaptations: (1) increased cultivation of spring crops, particularly sugar beet and maize while reducing winter rapeseed, and (2) modified cereal production intensity, with some wheat producers shifting to premium quality wheat to justify higher nitrogen rates while others transitioned toward more extensive production using feed wheat and winter barley. Additionally, 38% of farms incorporated more legumes in cover crop mixtures despite higher seed costs (€60–70/ha), while one-third expressed concerns about long-term soil fertility, noting that reduced organic fertilization could deplete topsoil and decrease humus content over time (Res_6).\\u003c/p\\u003e\\n \\u003cp\\u003eA few farmers reported yield reductions of 10–15% in winter wheat and quality impacts, particularly 0.5% lower protein content resulting in revenue losses of €20–35 per ton when quality requirements were not met. Individual farmers also reported reduced protein content in grass silage, lower starch content in starch potatoes, and quality issues in malting barley.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec11\\\"\\u003e\\n \\u003ch2\\u003e3.4.2 Fertilization Approaches under Nitrogen Restrictions\\u003c/h2\\u003e\\n \\u003cp\\u003eTwo distinct fertilization strategies emerged in response to the mandatory 20% reduction in nitrogen application. Most farms (67%) implemented uniform reductions across all crops, with four eliminating the ear fertilization stage in cereals. These farms focused on improving nutrient efficiency through stabilized nitrogen fertilizers (8%), nitrification inhibitors (17%), increased processing of organic material in biogas plants (17%), and direct incorporation technologies (17%). The remaining farms (33%) reallocated nitrogen to high-value crops such as potatoes or cereals to maintain quality parameters where economically beneficial.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec12\\\"\\u003e\\n \\u003ch2\\u003e3.4.3 Farmer Attitude towards Regulatory Flexibility\\u003c/h2\\u003e\\n \\u003cp\\u003eOur interviews explored farmers' attitudes toward a hypothetical policy scenario allowing farms to select from a catalog of measures while maintaining core regulatory requirements. Nearly all respondents (23 of 24) expressed positive attitudes toward increased regulatory choice, with only one participant fundamentally rejecting this approach. Seven participants, while generally supportive, expressed skepticism about practical implementation, noting that acceptance would depend on which measures remained mandatory versus optional. When asked about selection criteria for measures, economic considerations dominated (71% of respondents), with others citing site-specific conditions, agronomic factors, and operational workflows.\\u003c/p\\u003e\\n \\u003cp\\u003eTwo-thirds of respondents (67%) believed a more flexible approach would positively affect groundwater protection by enabling farm-specific solutions tailored to different farm structures, weather conditions, soil properties, and available equipment. One farmer highlighted the motivational aspect: \\\"The acceptance of measures would be somewhat higher [...] and as a result, one approaches the work with more diligence and effort\\\" (Res_13), suggesting increased ownership through choice might enhance implementation quality.\\u003c/p\\u003e\\n \\u003cp\\u003eThe remaining one-third of participants either doubted any effect on groundwater quality or declined to assess effectiveness. Concerns about red area boundary designation emerged as a noteworthy theme, with half of farms reporting substantial boundary changes over time that undermined acceptance of both the designation process and its political justification. One participant characterized the designation process as a \\\"lottery\\\" (Res_16), highlighting perceived arbitrariness.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec13\\\"\\u003e\\n \\u003ch2\\u003e3.4.4 Farmer-Generated Alternative Approaches\\u003c/h2\\u003e\\n \\u003cp\\u003eWhen identifying measures with the greatest financial impact, arable farms (64%) cited the autumn fertilization ban with mandatory cover crop cultivation, followed by the 20% nitrogen reduction requirement. Livestock operations equally identified these measures along with organic fertilizer limits as burdensome. Despite these concerns, several current measures received support, with 63% of farm managers specifically endorsing mandatory cover crop cultivation as an effective water protection measure.\\u003c/p\\u003e\\n \\u003cp\\u003eParticipants suggested several alternative approaches to nitrogen management in red areas (Table A1, Appendix). A widely supported proposal (endorsed by seven participants) was allowing needs-based fertilization of cover crops to improve soil humus development and erosion protection. Participants noted that improved cover crop establishment would help \\\"the soil conserve more nutrients\\\" (Res_8) and enhance environmental benefits.\\u003c/p\\u003e\\n \\u003cp\\u003eThe most frequently suggested administrative reform (supported by eight participants) involved shifting from field-specific documentation to a farm-level nitrogen quota system based on cultivated crops. As one farmer explained: \\\"Perhaps the farm could be given a total nitrogen amount that can be distributed according to its own needs in certain areas\\\" (Res_13). Some participants reported already shifting nitrogen between crops to maintain quality and yield while adhering to the overall 20% reduction requirement.\\u003c/p\\u003e\\n \\u003cp\\u003eFour participants advocated for greater flexibility in application timing based on weather and soil conditions rather than fixed calendar dates, arguing that \\\"nature should be considered\\\" (Res_17) to improve nutrient use efficiency. Riparian buffer strips were suggested by four participants as an effective water protection measure, though they acknowledged the economic trade-offs. Participants reported reducing buffer strips following relaxed set-aside requirements due to administrative burden and lack of premiums for areas under 0.1 hectare, suggesting that streamlined administration and appropriate financial incentives could increase adoption.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec14\\\"\\u003e\\n \\u003ch2\\u003e3.5 Discussion\\u003c/h2\\u003e\\n \\u003cdiv id=\\\"Sec15\\\"\\u003e\\n \\u003ch2\\u003e3.5.1 Farmer Perspectives on Nitrogen Regulations\\u003c/h2\\u003e\\n \\u003cp\\u003eOur Q-methodology identified two distinct farmer perspectives that offer a more nuanced understanding of responses to nitrogen regulations than previous typologies. This finding complements Barnes et al.'s (2011) typology by revealing how environmental, economic, and social considerations integrate across both perspectives - with Factor 1 respondents prioritizing concerns about regulatory effectiveness and administrative requirements, and Factor 2 respondents emphasizing economic planning challenges and farm-specific approaches. Both groups showed considerable consensus on administrative burden, excessive stringency, economic disadvantages, and exclusion from decision-making, highlighting fundamental implementation challenges in Germany's approach that transcend individual farmer differences. Similar to Iversen et al.'s (2024) findings, our results suggest farmer perspectives are shaped by practical concerns about implementation rather than environmental values alone, challenging simplistic characterizations and supporting Feindt et al.'s (2019) argument that agricultural policies often rely on oversimplified understandings of farmer motivations.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec16\\\"\\u003e\\n \\u003ch2\\u003e3.5.2 Skepticism about Environmental Effectiveness\\u003c/h2\\u003e\\n \\u003cp\\u003eA key finding is the widespread skepticism about environmental effectiveness and perceived fairness of regulations, mirroring findings from MacGregor and Warren (2006) and Barnes et al. (2009). Our participants questioned the causal relationship between their specific practices and groundwater contamination, particularly given the spatial designation of red areas some viewed as arbitrary. Some farmers suggested that water protection efforts should focus on public sewage systems and treatment plants rather than agriculture, indicating a deflection of responsibility. This skepticism about the scientific basis for regulations parallels Franklin et al.'s (2021) observations and appears reinforced by frequent boundary changes reported by respondents. Similarly, Elnagheeb et al. (1995) found that most U.S. farmers did not believe reducing fertilizer application on their farms would reduce water pollution. In contrast to Barnes et al. (2009), where the improvement in public perception due to better water quality is highlighted as a positive consequence of the NVZ measures, the farmers in our study do not emphasize this effect.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec17\\\"\\u003e\\n \\u003ch2\\u003e3.5.3 Adaptation Strategies and Innovation Under Regulatory Pressure\\u003c/h2\\u003e\\n \\u003cp\\u003eUnlike Barnes et al.'s (2009) finding that Scottish farmers made minimal adjustments, our study reveals substantial technical and operational adaptations among German farmers, likely reflecting the more prescriptive nature of Germany's regulations. These adaptations include investments in (precision) application technology, manure storage capacity, fertilization strategies, and crop pattern modifications, though such investments are not equally feasible for all sizes of operations (Franklin et al., 2021; MacGregor and Warren, 2016). The adoption of precision farming technology aligns with Danish farmers' perspectives on its effectiveness (Iversen et al., 2024; Basso et al., 2016). This adoption pattern likely reflects economic considerations, as farmers tend to implement technologies that offer clear profitability benefits (Wang et al., 2023). This pragmatic approach helps explain why precision agriculture technology is preferred by farmers in our study despite scientific skepticism about its environmental benefits (Iversen et al., 2024). However, these adaptations represent both technical innovation and economic rationalization, challenging the notion that environmental regulations necessarily stifle innovation (Porter and van der Linde, 1995).\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec18\\\"\\u003e\\n \\u003ch2\\u003e3.5.4 Preference for Farm-Specific Flexibility\\u003c/h2\\u003e\\n \\u003cp\\u003eOur findings reveal a strong preference for farm-specific approaches over standardized measures, with 23 of 24 participants expressing positive attitudes toward increased implementation flexibility. This aligns with findings from multiple studies (Iversen et al., 2024; Stuhr et al., 2020; Franklin et al., 2021). More crucially, Franklin et al. (2021) found that fixed dates in Welsh NVZ regimes led farmers to prioritize regulatory compliance over responsive management based on weather and soil conditions, potentially increasing rather than decreasing environmental risks. This suggests a fundamental tension in nitrogen policy design between standardization (which aids monitoring and enforcement) and farm-specific adaptation (which may improve implementation and effectiveness). These findings challenge assumptions that standardized approaches necessarily produce optimal outcomes, suggesting instead that regulations allowing farm-specific implementation within clear parameters might achieve better results by harnessing farmers' knowledge while maintaining accountability, consistent with Porter and van der Linde's (1995) argument for outcome-based rather than technology-based regulations.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec19\\\"\\u003e\\n \\u003ch2\\u003e3.5.5 Unintended Consequences of Nitrogen Regulations\\u003c/h2\\u003e\\n \\u003cp\\u003eOur study identified concerns about unintended consequences of nitrogen regulations. While the benefits of cover crops for reducing nitrate leaching are well-established (e.g. Abdalla et al., 2019), our participants reported that restrictions on organic fertilization and cover crop fertilization in autumn could undermine their effectiveness by reducing biomass production, and consequently, both nitrogen capture and carbon sequestration. These concerns highlight how regulations that narrowly focus on nitrogen leaching might affect other environmental goals. The shift toward more extensive cereal varieties affects protein content and product quality, with implications for farm profitability (Kage et al., 2022; Schröer et al., 2022).\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec20\\\"\\u003e\\n \\u003ch2\\u003e3.5.6 Farmer-Generated Alternatives\\u003c/h2\\u003e\\n \\u003cp\\u003eFarmers reported cultivating wheat varieties with higher nitrogen requirements to be able to use more nitrogen on the farm. In line with this, some farm managers also reported that nitrogen is shifted between crops anyway in order to ensure quality and yield. This means that the 20% reduction is complied with at farm level or on land in red areas, but nitrogen is used more flexibly. This also corresponds to the widely supported proposal for farm-level nitrogen quotas rather than field-specific documentation requirements, which aligns with Barnes et al.'s (2009), Stuhr et al.'s (2020) as well as MacGregor and Warren's (2006) observations about administrative burden by offering specific alternatives that maintain environmental accountability while reducing paperwork requirements.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec21\\\"\\u003e\\n \\u003ch2\\u003e3.6 Implications\\u003c/h2\\u003e\\n \\u003cp\\u003eOur findings have important implications for both theory and practice in environmental regulation. Theoretically, they support Porter and van der Linde's (1995) contention that well-designed environmental regulations can stimulate innovation, while suggesting that poorly designed implementation approaches may create unnecessary costs and resistance. The observed disconnect between regulatory structure and on-farm realities reinforces Blanc's (2018) argument that effective regulation requires implementation systems that are anchored in practical realities.\\u003c/p\\u003e\\n \\u003cp\\u003eRegulatory approaches must balance environmental objectives with economic and agricultural realities. Improving transparency in measuring and communicating nitrate reduction outcomes could enhance acceptance among farmers that are skeptical about environmental effectiveness. Meanwhile, more flexible implementation frameworks that account for farm-specific conditions and provide greater planning certainty would likely improve compliance while maintaining environmental goals. This balance recognizes that effective regulations must address both environmental protection and agricultural viability as complementary rather than competing objectives.\\u003c/p\\u003e\\n \\u003cp\\u003eStreamlining documentation and reporting requirements represents a promising direction for policy improvement that does not compromise environmental objectives. A farm-level nitrogen quota system based on cultivated crops instead of field-specific documentation would maintain accountability while reducing the paperwork burden. This approach could redirect farmers' attention from compliance documentation to improved nitrogen management practices.\\u003c/p\\u003e\\n \\u003cp\\u003eCombining mandatory baseline requirements with voluntary enhanced measures could improve both compliance and effectiveness. Offering choices within a clear regulatory framework would increase ownership and likely enhance implementation quality. This approach could include mandatory core measures addressing the most critical nitrogen pathways, supplemented by a menu of optional measures from which farmers could select based on their specific farm conditions and economic considerations. Such flexibility within a structured framework strikes a balance between the need for consistent environmental protection and the diversity of agricultural systems.\\u003c/p\\u003e\\n \\u003cp\\u003eImproving the stability of regulations would enhance farmers' ability to adapt their operations effectively and make appropriate investments. Long-term regulatory frameworks with clear trajectories would support investment planning and strategic adaptation. Reducing frequent boundary changes and shifting requirements would provide the consistency needed for farmers to develop and implement comprehensive adaptation strategies. This stability is particularly important given the substantial investments required for some adaptations, such as increased storage capacity or precision application technology.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec22\\\"\\u003e\\n \\u003ch2\\u003e3.7 Limitations\\u003c/h2\\u003e\\n \\u003cp\\u003eThis study has several important considerations that should be kept in mind when interpreting our findings. First, our strategically selected, but non-random sample of 24 farmers provided insights into distinct subjective viewpoints regarding farming in red areas. In accordance with Q methodology, we were able to reveal the structure of perspectives within our purposively selected respondents. The perspectives identified represent meaningful viewpoint configurations that occur among these farmers, though additional viewpoints might exist beyond those captured in our analysis. This is especially relevant, as the high correlation reveals a large common ground in farmers perceptions across factors. Second, our reliance on self-reported impacts (such as yield reductions) without independent verification means these findings should be interpreted as farmers' perceptions rather than objectively measured outcomes. Finally, while we documented various adaptation strategies, we did not comprehensively assess their effectiveness in reducing nitrate leaching or their long-term economic viability, which would require longitudinal data and environmental measurements beyond the scope of this study.\\u003c/p\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"4 Concluding Remarks\",\"content\":\"\\u003cp\\u003eThis study examined farmers' perceptions and adaptations to stringent nitrogen regulations in Germany's red areas, revealing two distinct perspectives: one centered on environmental effectiveness skepticism and administrative burden, and another focusing on economic planning challenges and farm-specific flexibility needs. Despite these differences, both perspectives question the current regulatory approach's efficacy and implementation. Farmers have responded with substantive adaptations, including technology investments, crop selection adjustments, and fertilization strategy modifications. Our findings suggest that sustainable nitrogen management requires collaborative approaches that leverage farmers' practical knowledge while maintaining environmental accountability. Balancing mandatory core requirements with farm-specific flexibility could enhance regulatory acceptance and implementation effectiveness, potentially yielding better environmental outcomes than increased stringency alone.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eThe authors report there are no competing interests to declare.\\u003c/strong\\u003e\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eAbdalla, M., Hastings, A., Cheng, K., Yue, Q., Chadwick, D., Espenberg, M., ... \\u0026amp; Smith, P. (2019). A critical review of the impacts of cover crops on nitrogen leaching, net greenhouse gas balance and crop productivity. \\u003cem\\u003eGlobal change biology\\u003c/em\\u003e, \\u003cem\\u003e25\\u003c/em\\u003e(8), 2530-2543. https://doi.org/10.1111/gcb.14644\\u003c/li\\u003e\\n\\u003cli\\u003eBarnes, A. P., Willock, J., Hall, C., \\u0026amp; Toma, L. (2009). Farmer perspectives and practices regarding water pollution control programmes in Scotland. \\u003cem\\u003eAgricultural water management\\u003c/em\\u003e, \\u003cem\\u003e96\\u003c/em\\u003e(12), 1715-1722. https://doi.org/10.1016/j.agwat.2009.07.002\\u003c/li\\u003e\\n\\u003cli\\u003eBarnes, A. P., Willock, J., Toma, L., \\u0026amp; Hall, C. (2011). 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Do farmers overuse nitrogen fertilizer to the detriment of the environment?. \\u003cem\\u003eEnvironmental and resource economics\\u003c/em\\u003e, \\u003cem\\u003e9\\u003c/em\\u003e(3), 323-340. https://doi.org/10.1007/BF02441403\\u003c/li\\u003e\\n\\u003cli\\u003eZinnbauer, M. (2023). \\u0026bdquo;Umsetzung der AllgemeinenVerwaltungsvorschrift zur Ausweisung von mitNitrat belasteten und eutrophierten Gebieten (AVV Gebietsausweisung \\u0026ndash; AVV GeA)\\u0026ldquo;Anh\\u0026ouml;rung im Ausschuss f\\u0026uuml;r Klima, Landwirtschaft und Umwelt am3. Mai 2023 im Landtag Mecklenburg-Vorpommerns. Johann Heinricht von Th\\u0026uuml;nen-Institut. Online available at: https://literatur.thuenen.de/digbib_extern/dn067168.pdf\\u003c/li\\u003e\\n\\u003cli\\u003eZabala, A. (2014): qmethod: A Package to Explore Human Perspectives Using Q Methodology. \\u003cem\\u003eThe R Journal,\\u003c/em\\u003e \\u003cem\\u003e6\\u003c/em\\u003e(2), 163\\u0026ndash;173. DOI: 10.32614/rj-2014-032.\\u003cbr\\u003e \\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Footnotes\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003e For an overview of the general D\\u0026uuml;V see Kuhn et al. (\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003e A full overview is given in Table \\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003eA1\\u003c/span\\u003e, Appendix.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003e Note: Added by the authors to clarify the quote.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Groundwater protection, Nitrogen management, Q-methodology, German farmers, Fertilizer regulations\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7574476/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7574476/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eThis study examines farmers' perceptions and adaptation strategies in response to fertilizer use restrictions due to nitrogen pollution in designated \\u0026ldquo;red areas\\u0026rdquo; under \\u0026sect;\\u0026nbsp;13a of the German Fertilizer Ordinance (D\\u0026uuml;V). Using Q-methodology and qualitative interviews with 24 German farm managers conducted between December 2024 and January 2025, we identified two distinct farmer perspectives: those primarily concerned with bureaucratic burden and perceived ineffectiveness of measures, and those focused on economic burden for farmers and reduced planning certainty. Despite these differences, farmers generally oppose the regulations as they question their effectiveness. Farmer adaptations include investments in (precision) application technology, shifting to more extensive cereal varieties, increased legume cultivation, and storage capacity expansion for organic fertilizers. A few farmers even report yield reductions in winter wheat and decreased protein content in red areas. Our findings suggest that allowing farm-specific flexibility could improve acceptance while maintaining environmental effectiveness. This research demonstrates that successful groundwater protection depends more on stakeholder inclusion and acceptance than additional restrictions.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Farmer Perceptions and Adaptations to Nitrogen Regulations in Germany: A Q-Methodology Analysis\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-09-10 09:24:52\",\"doi\":\"10.21203/rs.3.rs-7574476/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"4df35fa5-9c0c-406f-b491-e1db362fba24\",\"owner\":[],\"postedDate\":\"September 10th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":54444447,\"name\":\"Agricultural Economics \\u0026 Policy\"}],\"tags\":[],\"updatedAt\":\"2025-09-10T09:24:52+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-09-10 09:24:52\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7574476\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7574476\",\"identity\":\"rs-7574476\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}