# The Role of Organic Farming in Landscape Conservation

Emilien Veron, Raja Chakir

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# The Role of Organic Farming in Landscape Conservation

Emilien Veron¹* Raja Chakir¹

November 7, 2025

¹University of Paris-Saclay, INRAE, AgroParisTech, Paris Saclay Applied Economics, Palaiseau, France.
Corresponding author: emilien.veron@inrae.fr

## Abstract

Hedgerows support biodiversity, soil protection, and ecosystem resilience, yet their density in France has declined sharply in recent decades. This study investigates whether organic farming promotes hedgerow conservation, using georeferenced farm data from 2015 to 2022 and detailed hedgerow inventories. We estimate cross-sectional and TWFE models to identify the causal effect of organic conversion on hedgerow density. Relative to farms that remained conventional, those that converted to organic farming increased hedgerow density by approximately 0.95 meters per hectare. Moreover, converting farms rapidly converged on the hedgerow level of farms that were organic throughout the period, suggesting early adoption of conservation-oriented practices during transition. The positive effect of organic conversion is concentrated in cereal farms, while no significant changes are observed in vineyards or orchards, probably reflecting differences in yield penalties and reliance on ecosystem services across crop types. Policy simulations indicate that targeting hedgerow subsidies on organic and converting farms could more than double the impact per euro spent, reducing the budget needed to meet national restoration goals by up to 60 percent.

**Keywords:** Organic Farming, Hedgerow Conservation, Sustainable Agriculture, Landscape policy

**JEL Codes:** Q15, Q18, Q57, C23
# Contents

<table><tr><td>1</td><td>Introduction</td><td>3</td></tr><tr><td>2</td><td>Background on hedgerows and organic farming in France</td><td>5</td></tr><tr><td>2.1</td><td>Historical evolution of hedgerows</td><td>5</td></tr><tr><td>2.2</td><td>Organic farming in France</td><td>6</td></tr><tr><td>3</td><td>Data and summary statistics</td><td>7</td></tr><tr><td>3.1</td><td>Data sources</td><td>7</td></tr><tr><td>3.1.1</td><td>BD Haie</td><td>7</td></tr><tr><td>3.1.2</td><td>LPIS</td><td>8</td></tr><tr><td>3.2</td><td>Summary statistics</td><td>8</td></tr><tr><td>4</td><td>Empirical Strategy</td><td>11</td></tr><tr><td>4.1</td><td>Cross-Sectional Specification</td><td>12</td></tr><tr><td>4.2</td><td>Panel data models</td><td>12</td></tr><tr><td>5</td><td>Results</td><td>14</td></tr><tr><td>5.1</td><td>Cross section results: Initial hedgerow density</td><td>14</td></tr><tr><td>5.2</td><td>TWFE results: evolution of hedgerow density</td><td>15</td></tr><tr><td>6</td><td>Heterogeneity</td><td>19</td></tr><tr><td>6.1</td><td>Crop Specialization and Hedgerow Dynamics</td><td>19</td></tr><tr><td>7</td><td>Robustness check</td><td>22</td></tr><tr><td>7.1</td><td>Change variable: sum of hedgerows</td><td>22</td></tr><tr><td>7.2</td><td>Farmers' decisions: qualitative census</td><td>23</td></tr><tr><td>7.3</td><td>Other database: Small Woody Features</td><td>24</td></tr><tr><td>8</td><td>Simulating Policy Efficiency Gains from Targeted Hedgerow Support</td><td>26</td></tr><tr><td>9</td><td>Conclusion</td><td>27</td></tr><tr><td>A</td><td>Appendix</td><td>32</td></tr><tr><td>A.1</td><td>Summary statistics: Nuts-2 hedgerow distribution</td><td>32</td></tr><tr><td>A.2</td><td>Robustness check: impact of conversion on length of hedgerows in meters</td><td>32</td></tr><tr><td>A.3</td><td>TWFE result: impact of conversion on hedgerow density depending on crop heterogeneity</td><td>34</td></tr><tr><td>A.4</td><td>Robustness Check with a Simple DID Model</td><td>37</td></tr><tr><td>A.5</td><td>Pacte en faveur de la haie policy: table of hedge planting and maintenance costs</td><td>40</td></tr></table>
# 1 Introduction

Hedgerows are integral to agricultural landscapes, offering key ecosystem services such as carbon sequestration, erosion control, biodiversity support, and habitats for pollinators and natural pest predators (Montgomery et al., 2020). Yet despite their recognized benefits, hedgerow density has sharply declined in recent decades; France alone lost nearly half of its hedgerows between 1975 and 2004 (Pointereau and Coulon, 2006). While the Common Agricultural Policy (CAP) has introduced measures—such as Ecological Focus Areas (EFAs) and Agri-Environmental Schemes (AES)—to address this decline, these efforts have been largely ineffective (Jereb et al., 2017). Financial, administrative, and opportunity cost constraints continue to limit farmers’ participation in conservation programs (AFAC agroforesteries, 2015). In parallel, organic farming has emerged as a promising model for promoting biodiversity and reducing chemical inputs (Tuck et al., 2014; Reganold and Wachter, 2016; Sidemo-Holm et al., 2024). However, recent policy shifts may slow its expansion. In France, the removal of maintenance subsidies has discouraged new conversions to organic farming, potentially weakening its role in biodiversity and landscape management (Cour des comptes, 2022). This policy change raises concerns not only for organic production but also for its positive spillovers, particularly its role in supporting hedgerow conservation.

This paper investigates whether organic farming contributes to the conservation of hedgerows. We test the hypothesis that organic farmers, who rely more on natural pest control and ecological processes, have stronger incentives to maintain hedgerows as functional landscape infrastructure. We argue that better alignment between hedgerow conservation programs and organic farming policy could generate dual benefits: strengthening ecosystem services while promoting sustainable agriculture.

Our analysis combines geospatial data from the BD Haie database, which maps hedgerow networks, with plot-level farming information from the Land Parcel Identification System (LPIS). Using data from 2015 and 2022, we assess the relationship between organic farming and hedgerow density through two complementary approaches: a cross-sectional model that captures differences between farms, and a first-difference model that exploits within-farm changes over time. This empirical strategy allows us to isolate the effect of adopting organic practices while addressing potential biases from time-invariant unobservables and staggered treatment timing. The study has three key strengths: it relies on a nationally representative dataset covering over 220,000 farms; it uses panel data to better identify the causal effect of organic conversion on hedgerow presence; and it distinguishes between certified organic farms and those in transition, revealing that conservation efforts are especially pronounced during the conversion phase.

The connection between organic farming and hedgerow conservation is related to broader themes in the economics of land use, biodiversity, and ecosystem services. While hedgerows remain understudied in economics, a growing literature highlights the environmental value of landscape complexity, particularly under organic systems. Recent studies suggest that organic farming supports hedgerows and biodiversity more broadly. For instance, Couthouis et al. (2023) and Eriksson and Lindgren (2023) link organic practices with greater ecological performance through enhanced landscape features. Other work shows that complex landscapes improve organic farms’ resilience and
productivity by bolstering pest predator populations (Klinnert et al., 2024; Schrama et al., 2018). However, the causal effect of organic farming on hedgerow dynamics remains largely unexplored.

Hedgerows provide habitats for beneficial species like beetles, bats, and spiders, strengthening natural pest control (Montgomery et al., 2020). This ecological function is recognized in European Regulation (EU) 2018/848, which emphasizes organic farming's dependence on biological pest management. Empirical studies show that landscape composition shapes pest control outcomes (Bianchi et al., 2006; Albrecht et al., 2020), and that organic systems benefit from landscape complexity through higher yields and reduced pest pressure (Klinnert et al., 2024). While hedgerows can reduce yields locally near their base, they often improve net productivity across parcels (Pollard et al., 1974; Lenka et al., 2012). Advisory guidelines for organic farmers now explicitly recommend hedgerow planting to offset the absence of chemical pesticides and promote beneficial insect habitats (Chambres d'agriculture de Bretagne, Normandie et Pays de la Loire, 2025). Both the quality and density of hedgerows are important for service delivery (Baudry, 2004).

Theoretically, hedgerows can act as natural insurance against production risks. In the framework developed by Quaas and Baumgärtner (2008), ecosystem services provide risk buffering that can substitute for financial insurance. However, the presence of financial insurance can create moral hazard, encouraging input intensification to raise expected indemnities. Empirical studies show that insured farmers often adopt more intensive practices, such as increased pesticide use or land expansion (Chakir and Hardelin, 2014; Wu, 1999; Yu et al., 2018).

We contribute to several strands of the literature. First, we provide new evidence on the role of organic farming in landscape conservation. While Guderjan et al. (2023) show that hedgerows buffer biodiversity losses on organic farms near conventional plots, we demonstrate that organic practices actively promote hedgerow expansion. This finding complements research on the positive externalities of organic farming (Sautereau and Benoit, 2016), showing that organic area growth can drive landscape-level change. A key strength of our analysis is its scale: we cover 98.7% of French agricultural plots across two periods, allowing fine-grained tracking of hedgerow dynamics.

Second, we build on the literature linking organic farming to ecosystem-based pest control (Klinnert et al., 2024; Larsen et al., 2024; Muneret et al., 2018; Schrama et al., 2018). For example, Muneret et al. (2018) find that organic practices enhance pest regulation while reducing pathogen pressure, despite higher weed levels. Larsen et al. (2024) show that organic area shares influence pesticide use, with spillover effects on neighboring conventional fields. Our study adds a new dimension by linking organic farming to the landscape structures—specifically hedgerows—that underpin natural pest control. By showing that organic conversion leads to greater hedgerow density, we highlight a mechanism through which organic agriculture may contribute to pest regulation and sustainability not only through farm management practices, but also through its impact on landscape structures.

Finally, our results have direct policy implications. We propose a framework that integrates landscape conservation with organic support programs. Our findings suggest that hedgerow conservation efforts should prioritize organic farms, which show higher levels of hedgerow plantation and growth. By demonstrating a strong link between farm-level decisions and landscape-scale outcomes, we argue for better coordination between AES, EFAs, and organic farming incentives. Rather than
treating hedgerow protection as a standalone goal, our approach sees organic agriculture as both a beneficiary and a driver of biodiversity-friendly landscapes. This is especially relevant in the context of the European Green Deal and the Farm to Fork Strategy, which call for coherent policies to reduce inputs, protect habitats, and support farmers (European Environment Agency, 2024). Our results provide actionable insights for designing spatially targeted, cost-effective policies that strengthen ecological resilience in agricultural systems.

The remainder of the paper is organized as follows. Section 2 outlines the policy context. Section 3 describes the data and presents summary statistics. Section 4 presents the empirical strategy. Section 5 presents the main findings on hedgerow dynamics. Section 6 examines heterogeneity by conversion status and specialization. Section 7 reports robustness checks. Section 8 presents a policy simulation. Section 9 concludes.

# 2 Background on hedgerows and organic farming in France

## 2.1 Historical evolution of hedgerows

Historically, hedgerows were established for both practical and agronomic purposes, playing a key role in structuring rural landscapes. Their historical density varies significantly across regions, shaped by two main factors: the initial level of forest cover (since many hedgerows originated from the clearance of dense woodlands for agricultural use) and the type of farming systems in place (Baudry et al., 2000). Livestock-oriented areas, in particular, saw widespread adoption of hedgerows due to their multiple functions: serving as barriers to livestock, acting as windbreaks, providing shade, and contributing to microclimate regulation. This trend was especially pronounced from the Middle Ages onward, with substantial development in Normandy and Brittany, where the conversion of arable land into pasture coincided with the growth of dairy and meat markets. The decline of hedgerows began with the advent of barbed wire and farm mechanization, and it accelerated between the 1950s and 1970s due to land consolidation policies (Baudry, 2004). Since 1950, it is estimated that around 70% of France's hedgerow network has disappeared (Pointereau and Coulon (2006), CGAAER (2023)). This trend is not unique to France: Belgium lost approximately 30% of its hedgerows over 41 years (Van Den Berge et al., 2019); Catalonia experienced a 46% decline between 1957 and 1987 (Pointereau and Coulon (2006)); and the United Kingdom lost roughly 27%, with a sharp increase in removals during the 1960s (Dover, 2019).

In response to this decline, a policy shift occurred in the 1970s with the promotion of so-called "functional" hedgerows, those better suited to modern agricultural practices and mechanization. These hedgerows were pruned to facilitate tractor movement and minimize ground coverage, while still retaining certain ecological functions, such as acting as windbreaks. This was accompanied by a slowdown in hedgerow removal between 1982 and 1994 (Pointereau and Coulon, 2006). Although this trend continued with support from CAP measures, the overall trajectory has not been reversed: between 2017 and 2021, France still experienced a net annual loss of 23,500 km of hedgerows (CGAAER, 2023).
Today, the decision to retain or remove a hedgerow is primarily based on a cost-benefit analysis performed by the farmer. Indeed Cocco et al. (2025) find that although farmers probably benefited from subsidized hedgerow clearance, the societal costs, primarily due to carbon emissions, outweighed the private gains, suggesting that the public economic balance of hedgerow removal is negative. When hedgerows offer tangible benefits such as erosion control, crop protection, microclimate regulation, or wood production, they are more likely to be preserved. Conversely, their maintenance becomes less viable when they are seen as obstacles to productivity or mechanized operations. This economic and functional rationale thus repositions hedgerows not merely as residual landscape features, but increasingly as agricultural infrastructure, whose survival depends on their integration into modern production systems.

**Hedgerow policies** The Common Agricultural Policy (CAP) employs various tools to promote hedgerow conservation and expansion, but their effectiveness has been limited. Under Pillar 1, CAP Green Payments subsidies require farmers to allocate Ecological Focus Areas (EFAs) on their land, which may include hedgerows alongside other environmentally beneficial features such as catch crops. By prioritizing productive EFAs, this policy aims to incentivize hedgerow maintenance and expansion while meeting broader environmental objectives (Jereb et al., 2017). Pillar 2 includes Agri-Environmental Schemes (AES), which offer contracts for the maintenance of hedgerows. However, participation in these schemes is constrained by financial and practical barriers. Maintenance costs, coupled with the opportunity cost of land allocation for hedgerows, often exceed the subsidies provided. Furthermore, restrictions on future hedge removal discourage farmer engagement, highlighting the need for policy reforms to make AES contracts more viable and financially flexible.

Despite these initiatives, CAP policies have largely failed to stop hedgerow decline or encourage the adoption of maintenance practices. Several factors contribute to this ineffectiveness, including productivity losses due to reduced cultivable land, high maintenance costs, and historical policies that incentivized hedgerow removal (Cocco et al., 2025). For instance, the "Hedgerow Maintenance" AES program is rarely adopted, covering only 0.6% of all hedgerows in France. Administrative burdens and additional costs are significant obstacles; according to AFAC agroforesteries (2015), farmers often incur losses of approximately €1 per contracted meter due to inadequate subsidy levels. Current policies also fail to account for the ecosystem services provided by hedgerows, such as biodiversity conservation, carbon sequestration, and natural pest control, emphasizing the need for more comprehensive and economically balanced policy frameworks (Bateman et al., 2013).

## 2.2 Organic farming in France

Organic farming (OF) is often presented as a production system that is more environmentally friendly, particularly because it supports the provision of ecosystem services. By eliminating the use of synthetic inputs, it generates positive externalities such as improved biodiversity, soil fertility, and water quality, thereby contributing to a reconfiguration of agricultural landscapes (Gomiero et al., 2011). However, the abandonment of synthetic pesticides represents one of the main constraints for farmers converting to organic systems, as it creates challenges in pest management, as highlighted by Home et al. (2019). To address this constraint, several stakeholders, including
Chambers of Agriculture, recommend the use of agroecological infrastructure features, particularly hedgerows, which provide habitats for beneficial organisms and help limit weeds. Thus, the expansion of OF could go hand in hand with a broader adoption of hedgerows, thereby strengthening the sustainability of agroecosystems.

Nevertheless, this dynamic faces structural obstacles. Despite strong political commitment since the first Ambition Bio plan, the conversion to OF has slowed considerably: after steady growth between 2007 and 2020, the area undergoing conversion declined by 4% between 2022 and 2024, jeopardizing the achievement of the European Green Deal targets (Agence Bio, 2025). Several reports emphasize a lack of coherence in public policies, marked by the gradual phase-out of maintenance support, high administrative complexity, and policy instability, which undermine the long-term adoption of organic practices (Cour des comptes, 2022).

Thus, while OF represents a central lever for the agroecological transition, its development remains highly dependent on stable and coherent public policies (Brunelle et al., 2024). One of the aims of this article is precisely to demonstrate how public policy could not only reinvigorate the conversion dynamics towards OF but also promote the restoration of a dense hedgerow network in France, to maximize the synergies between organic farming and agroecological infrastructure.

# 3 Data and summary statistics

## 3.1 Data sources

To analyze the relationship between organic farming and hedgerow conservation this study uses two primary datasets: the French reference layer of the linear hedges (BD haie) database, which maps vegetation structures across France, and the Land Parcel Identification System (LPIS), which details farming practices at the plot level. By combining these datasets for 2015 and 2022, we capture changes in hedgerow structures and link them to specific agricultural practices, enabling a robust spatial analysis.

### 3.1.1 BD Haie

In 2017, the French Biodiversity Agency (Office Français de la Biodiversité, OFB) and the National Institute of Geographic and Forest Information (Institut National de l'Information Géographique et Forestière, IGN) launched an initiative to produce a comprehensive map of linear hedgerows across metropolitan France. To date, two datasets have been released. The first, *BD Haie V1*, published in 2020, is constructed from two primary data sources. The first source comprises hedgerows and small woods identified in IGN's *BD TOPO* database, which were extracted through automated segmentation and photo interpretation of aerial imagery from 2004 to 2015. The second source consists of tree-lined hedgerows, lines of trees, and non-agricultural small woods from the *French Land Parcel Identification System* (LPIS), a cadastral land-use registry. The second dataset, *BD Haie V2*, released in 2024, incorporates non-agricultural RPG data from 2020 to 2022 alongside aerial imagery from the same period. The availability of these two datasets enables
an assessment of changes in hedgerow coverage over time, distinguishing patterns before 2015 and
after 2022.

3.1.2 LPIS

The French LPIS produced by the French *Agence de services et de paiement*<fnref n="1" />, contains annual listings of all agricultural land units receiving CAP aid. This second database allows us to observe nearly the entire French agricultural sector at the plot level, covering approximately 85% of farmers and 98.7% of the utilized agricultural area. This spatial data provides annual information on each plot, including practices, crops, and farmer IDs.

For each agricultural plot, we assign hedgerows located within the plot and within a 10-meter buffer. This assignment is conducted separately for the [2004–2015] and [2020–2022] datasets. For example, in Figure 1, the top left and top right show, respectively, the hedges existing in 2015 and 2022 in a random area. The bottom figure compares these two states, allowing us to identify different hedgerow dynamics over time: hedgerows that remained in place throughout the period (shown in blue), newly established hedgerows appearing only between 2020 and 2022 (shown in green), and hedgerows that were present before 2015 but were removed by 2022 (shown in red).

**3.2 Summary statistics**

Between 2015 and 2022, the length of hedgerows surrounding agricultural areas decreased from 1,551,976 km to 1,463,694 km, representing a net loss of 88,282 km. This corresponds to an average decline of 11,035 km per year, highlighting a persistent and significant reduction of hedgerow cover in rural landscapes over the period. The maps in figure 2, show the average density of hedges around fields in France between 2015 and 2022. There is spatial heterogeneity between *départements*, with sparsely wooded areas (less than 10m per ha) mainly around the Paris region and Corsica and areas with six to eight times more wooded areas (over 80m per ha) in the north-west of France. Between 2015 and 2022, there were no significant changes within *départements*. However, several *départements* are now shown in a lighter color, reflecting a reduction in density of hedgerows in those *départements*. When we look at the distribution of farm hedgerow density at the Nuts-2 level, on figure 6 (in Appendix A.1), we see a strong heterogeneity between farmers in the same region. Indeed, for the majority of regions the distribution ranges from 0m per ha to 100m per ha, and even close to 150m per ha for the Normandy and Brittany regions. The analysis of individual behavior in hedgerow development strategies therefore appears relevant.

Table 1 presents summary statistics on farm size and hedgerow density by farm group. We focus our analysis on farmers observed at the beginning and end of the period. These groups are based on farmers’ practices in 2015 and 2022. The group *Conventional-Conventional*, corresponds to farmers practicing conventional agriculture who continued to do so throughout the period. Organic farms exhibit significantly higher hedgerow density than conventional farms. Indeed, the group that remained organic had around 42m of hedges per hectare compared with 34.7m for the group that

<footnote n="1">¹French public body responsible, in particular, for the administrative and financial management of the CAP in France</footnote>
<figure><img src="image_2.png" /><figcaption>Figure 1: Distribution and changes in hedgerows based on *BD Haie* and LPIS</figcaption></figure>

Note: The maps are based on the simultaneous projection of LPIS and BD Haie data, allowing for the identification of hedgerow presence and changes over time between 2015 and 2022. Maps a) and b) show the hedgerows and farming plots according to the type of practice (conventional in cream and organic in green). Map c) illustrates the changes between 2015 and 2022: hedgerows removed are shown in red, newly planted ones in green, and those that remained throughout the 2015-2022 period in blue.

remained conventional, a difference of around 8 metres per ha. Additionally, organic farms tend to be smaller in total size, with a mean area of 71.5 hectares compared to 89.9 hectares for conventional farms (in 2022). Hedgerow density per hectare is systematically higher over the *Organic-Organic* group (42 m/ha in 2015 and 42.21 m/ha in 2022) than *Conventional-Conventional* group (34.72 m/ha in 2015 and 34.34 m/ha in 2022), reinforcing the pattern that organic farms tend to preserve more hedgerows. The group that remained organic increased its hedgerow density by an average of 0.21m per ha, whereas this density decreased in the conventional group (-0.38m per ha).

In the group of farms that converted to organic during the period (group *Conventional-Organic*), we can see two things. First, this group was more similar to the group of conventional farmers than to the group of farmers who were already organic. In fact, the group of farmers undergoing conversion had farms 20 ha larger than the group of farmers already in organic farming. Second, this group of farmers had slightly lower hedgerow density than their conventional counterparts in 2015 (32.77m per ha vs 34.72m per ha). But, we can see that the trend in relation to hedgerows among this group of farmers converting to organic is positive. On average, among the farmers who
<figure><img src="image_3.png" /><figcaption>Figure 2: Distribution of hedgerows around farm plots in m per ha</figcaption></figure>

Source: BD Haies V1 (2020) V2 (2024), IGN, LPIS 2015/2022

converted, hedgerow density increased by 0.15m per ha between 2015 and 2022. This last result seems to indicate a growing awareness of the importance of hedgerows following this change in farming practice.

The fourth group includes farmers who have converted from organic to conventional farming. It should be noted that these farmers are marginal (around 0.5%), and seem to be experiencing difficulties in their practices, as indicated by their decrease in farm size by 5 ha, whereas all the other groups increased their size on average over the same period.

Referring to Table 2, significant differences can be observed in both the level of subsidies received and the uptake of climate insurance across farming systems. Conventional farmers receive, on average, between €2,485 and €3,759 more in Pillar 1 payments than their organic counterparts, a gap largely explained by the larger average size of conventional holdings. In contrast, Pillar 2 support is more favorable to organic farmers, primarily due to the inclusion of subsidies dedicated to organic conversion and maintenance within this pillar. With respect to agri-environmental measures, organic farmers are proportionally more engaged in the “hedgerow maintenance” scheme (1% compared to 0.6% for conventional farmers in 2022). Moreover, they receive higher average payments (approximately €300 more), reflecting the greater length of hedgerows contracted under these agreements. Finally, the overall uptake of climate insurance remains relatively limited, with
<table><caption>Table 1: Descriptive statistics by type of farm practice transition (2015–2022)</caption><thead><tr><th>Farm practice in 2015</th><th>Conventional</th><th>Organic</th><th>Conventional</th><th>Organic</th></tr><tr><th>Farm practice in 2022</th><th>Conventional</th><th>Organic</th><th>Conventional</th><th>Organic</th></tr></thead><tbody><tr><td><i>FarmSize</i><sub>2015</sub></td><td>85.64<br>(105.69)</td><td>67.39<br>(75.17)</td><td>88.60<br>(84.07)</td><td>81.66<br>(89.53)</td></tr><tr><td><i>FarmSize</i><sub>2022</sub></td><td>89.87<br>(110.94)</td><td>71.49<br>(79.37)</td><td>94.79<br>(89.02)</td><td>77.03<br>(91.22)</td></tr><tr><td><i>Hedge</i><sub>2015</sub> (in m)</td><td>2289.51<br>(2626.10)</td><td>2171.22<br>(2317.48)</td><td>2422.71<br>(2394.47)</td><td>2187.21<br>(2301.12)</td></tr><tr><td><i>Hedge</i><sub>2022</sub> (in m)</td><td>2217.19<br>(2380.24)</td><td>2339.37<br>(2549.57)</td><td>2632.44<br>(2658.19)</td><td>2023.00<br>(2392.91)</td></tr><tr><td><i>Hedge</i><sub>2015</sub> (in m/ha)</td><td>34.72<br>(30.15)</td><td>42.00<br>(55.61)</td><td>32.77<br>(22.58)</td><td>35.48<br>(28.93)</td></tr><tr><td><i>Hedge</i><sub>2022</sub> (in m/ha)</td><td>34.34<br>(29.70)</td><td>42.21<br>(35.55)</td><td>32.92<br>(23.49)</td><td>36.99<br>(34.40)</td></tr><tr><td>N</td><td>202698</td><td>12848</td><td>11755</td><td>1306</td></tr></tbody></table>

*Note:* This table reports summary statistics by farm type, categorized by agricultural practice in 2015 and 2022. Groups include farms that remained conventional, farms that converted to organic, and farms that remained organic. Variables include farm size (in hectares) and total hedgerow length (in meters and meters per hectare). Standard deviations are in parentheses.

<table><caption>Table 2: Descriptive statistics on CAP per farmer in France</caption><thead><tr><th rowspan="3"></th><th colspan="4">2015</th><th colspan="4">2022</th></tr><tr><th colspan="2">Conventional</th><th colspan="2">Organic</th><th colspan="2">Conventional</th><th colspan="2">Organic</th></tr><tr><th>% receiving</th><th>Mean (sd)</th><th>% receiving</th><th>Mean (sd)</th><th>% receiving</th><th>Mean (sd)</th><th>% receiving</th><th>Mean (sd)</th></tr></thead><tbody><tr><td>P1 (in €)</td><td>93.5</td><td>21431.38<br>(21882.31)</td><td>87.1</td><td>17672.42<br>(20961.96)</td><td>94.9</td><td>22904.72<br>(22019.8)</td><td>88.1</td><td>20419.82<br>(21654.15)</td></tr><tr><td>P2 (in €)</td><td>40.2</td><td>7925.89<br>(8478.16)</td><td>46.7</td><td>10049.34<br>(9885.71)</td><td>87.8</td><td>10981.11<br>(12038.25)</td><td>84.4</td><td>13079.87<br>(14244.67)</td></tr><tr><td>Crop insurance (in €)</td><td>16.6</td><td>705.48<br>(2076.14)</td><td>10.3</td><td>270.86<br>(1844.72)</td><td>17.4</td><td>1355.52<br>(3432.58)</td><td>13</td><td>682.82<br>(2947.12)</td></tr><tr><td>AES Hedgerows (in €)</td><td>0.3</td><td>1578.21<br>(2105.15)</td><td>0.9</td><td>1724.32<br>(2120.18)</td><td>0.6</td><td>1723.31<br>(1859.37)</td><td>1</td><td>2019.43<br>(1959.58)</td></tr></tbody></table>

*Notes:* This table reports descriptive statistics on Common Agricultural Policy (CAP) payments per farmer in France for 2015 and 2022, by farm type (conventional vs. organic). Reported measures include the share of farmers receiving each type of support (%) and the mean amount received in euros. Standard deviations are shown in parentheses.

only about 16% of farmers participating. Nonetheless, conventional farmers appear more likely to subscribe and do so for significantly larger areas—approximately twice that covered by their organic counterparts—resulting in higher average compensation (€1,355 compared to €682 for organic farmers).

## 4 Empirical Strategy

We examine the relationship between organic farming and hedgerow density using two complementary approaches: a cross-sectional model that exploits variation across farms, and First Difference (FD) models that capture within-farm changes over time. Both specifications leverage detailed information on farm practices, policy participation, and landscape characteristics observed in 2015 and 2022.
## 4.1 Cross-Sectional Specification

We begin by estimating a cross-sectional model to document static differences in hedgerow density between organic and conventional farms:

$$Hedges_i = \gamma_0 + \beta_1 \cdot Organic_i + \beta_2 \cdot X_i + \delta_{D(i)} + \varepsilon_i, \quad (1)$$

where $Hedges_i$ denotes hedgerow density, measured in meters per hectare, on farm $i$ in 2015 or 2022. The variable $Organic_i$ is an indicator equal to one if the farm has at least one plot certified as organic, and zero otherwise. The vector $X_i$ also includes control variables derived from individual Common Agricultural Policy (CAP) payments, both in aggregated form and disaggregated by type, including agri-environmental schemes (AES) and multi-risk climate insurance support. The specification includes *département* fixed effects, $\delta_{D(i)}$, to control for spatial heterogeneity in landscape and agro-climatic conditions. The error term $\varepsilon_i$ captures unobserved determinants of hedgerow density.

To investigate the relationship between conversion to organic farming and changes in hedgerow density, we estimate a series of first-difference (FD) models. This approach leverages our panel dataset covering two time periods (2015 and 2022), and focuses on within-farm changes in hedgerow density, thereby eliminating all time-invariant unobserved heterogeneity.

## 4.2 Panel data models

We estimate a set of models using a two-way fixed effects (TWFE) framework to evaluate the causal impact of organic conversion on hedgerow density. Our panel covers two time periods (2015 and 2022) and allows us to exploit variation in both the timing of adoption and farm-level exposure to treatment. Specifically, we estimate the following specification:

$$Hedges_{it} = \alpha_i + \lambda_t + \delta \cdot Converted_i + \theta \cdot X_{it} + \varepsilon_{it}, \quad (2)$$

where $Hedges_{it}$ denotes hedgerow density (in meters per hectare) for farm $i$ in year $t$. The term $\alpha_i$ captures farm fixed effects to control for time-invariant unobserved heterogeneity, while $\lambda_t$ represents year fixed effects. The variable $Converted_i$ is a binary indicator equal to one if farm $i$ converted to organic farming between 2015 and 2022, and zero otherwise. Importantly, farms for which $Converted_i = 0$ may belong to three different groups depending on the specification: (i) conventional farms that never converted, (ii) farms that were already certified organic in 2015 and remained so throughout the study period, or (iii) the pooled group that combines both categories. The definition of the benchmark group, therefore, conditions the interpretation of $\delta$: it measures the average change in hedgerow density for converters relative to the chosen benchmark group. As in equation 1 for the cross-sectional specification, we add the control vector $X_i$, linked to CAP payments, in order to assess how both the variation in payment amounts and the receipt (or non-receipt) of support may affect farmers' landscape decisions.
**Cohort-Specific Effects.** To account for potential heterogeneity in treatment effects, we further estimate a cohort-specific TWFE model that allows the effect of conversion to vary by the year of adoption:

$$ \text{Hedges}_{it} = \alpha_i + \lambda_t + \sum_{c \in \{2018,2019,2020,2021\}} \delta_c \cdot D_i^{(c)} + \mathbf{X}_{it}\theta + \varepsilon_{it}, \quad (3) $$

where $D_i^{(c)}$ is a binary variable equal to one if farm $i$ converted to organic farming in year $c$, and zero otherwise. The omitted category depends on the benchmark group definition described below. The coefficients $\delta_c$ estimate the effect of conversion separately for each adoption cohort, relative to the corresponding benchmark, and allow us to examine whether hedgerow dynamics differ depending on how long farms have been under organic management.

**Alternative benchmark Groups.** We estimate both specifications under three alternative definitions of the benchmark group to assess robustness and facilitate interpretation:

* **TWFE Model 1 (Conventional benchmark Group):** Here, $\text{Converted}_i = 0$ includes only farms that remained conventional in both 2015 and 2022. The treatment effect, therefore, compares converters directly with farms that never adopted organic farming.

* **TWFE Model 2 (Organic benchmark Group):** Here, $\text{Converted}_i = 0$ includes only farms that were already organic in 2015 and remained so until 2022. This comparison tests whether recently converted farms reach the same level of hedgerow density as long-established organic farms.

* **TWFE Model 3 (Pooled benchmark Group):** Here, $\text{Converted}_i = 0$ includes both conventional farms and those already organic in 2015. Pooling these groups maximizes the number of observations in the control sample and provides a broad benchmark across all non-treated units.

**Justification.** The TWFE framework is well-suited to our two-period panel and staggered treatment design. Farm fixed effects control for unobserved, time-invariant heterogeneity that may jointly influence hedgerow density and the decision to convert, while year fixed effects capture common shocks that affect all farms equally. Observing the exact year of conversion allows us to assign farms to treatment cohorts and avoid misclassification bias. Finally, estimating the models under alternative benchmark groups is essential in our setting: it highlights whether our findings depend on comparisons with conventional farms or with already-organic farms, and provides a robustness check in the absence of longer pretreatment series (Roth et al., 2023).
# 5 Results

## 5.1 Cross section results: Initial hedgerow density

Table 3 presents cross-sectional regression estimates examining the association between farming practices and hedgerow density at the farm level in 2015 and in 2022. The dependent variable, *Hedgerows/ha*, represents the total length of hedgerows per hectare on each farm. The analysis compares organic farms (at least one organic certified plot) with conventional farms serving as the reference category. Given the cross-sectional nature of the model, results should be interpreted as correlations rather than causal effects, as omitted variable bias and unobserved heterogeneity may influence the estimates.

Across all specifications, organic farms exhibit significantly higher hedgerow density than conventional farms. In 2015 (Column 1), organic farms have on average 5.3 meters more hedgerows per hectare compared to conventional farms. This positive and highly significant association remains robust when we add *département* fixed effects (Column 2-3), with slightly lower estimates at 4.3 meters per hectare. This gap increases over time, as we can see that in 2022, organic farms have 5 meters more per hectare than conventional farms. This is mainly due to a drop in the density of hedges on conventional farms from 38.62 m per hectare in 2015 (Column 1) to 34.2 m in 2022 (Column 4). Finally, at farm level, organic farmers have on average 10% more hedgerows per hectare. These results suggest that organic farms are more likely to maintain higher levels of hedgerow density, possibly due to stronger environmental commitments, agroecological practices, or compliance with organic certification requirements that encourage biodiversity conservation.

Table 3 reports the correlation between CAP subsidies and hedgerow density. Columns (2) and (4) reveal a negative association between both Pillar 1 and Pillar 2 payments and hedgerow presence. Specifically, an additional €1,000 of Pillar 1 subsidies—largely determined by farm size—correlates with a reduction of 0.38 meters of hedgerow per hectare. This pattern is consistent with the notion that larger farms, which receive more Pillar 1 support, tend to have lower hedgerow densities.

Similarly, Pillar 2 payments are also negatively associated with hedgerow density, although the magnitude is smaller: an additional €1,000 of Pillar 2 support is associated with a decrease of 0.13 meters of hedgerow per hectare. This muted effect probably reflects the heterogeneous objectives of Pillar 2, which combines instruments aimed at natural resource management, rural development, and agricultural competitiveness. These objectives may exert offsetting forces on hedgerow density.

Disaggregating Pillar 2 into its main components sheds further light on this result. While AES (Agri-Environmental Scheme) payments explicitly targeting hedgerow maintenance are positively associated with hedgerow density, subsidies linked to climate risk insurance adoption are negatively associated with it. This pattern suggests a degree of substitutability between formal insurance mechanisms and natural risk mitigation via hedgerows.

Given the cross-sectional nature of this analysis, the results should not be interpreted as causal. Omitted variable bias and unobserved heterogeneity may influence the estimated relationships, as farms with greater environmental awareness or policy incentives may be more likely to adopt organic practices and simultaneously maintain higher hedgerow density. Additionally, reverse causality
<table><caption>Table 3: Cross-sectional analysis on the hedgerow density (in m per ha) at the farm level</caption><thead><tr><th></th><th colspan="8">Dependent variable: Hedgerows in m /ha</th></tr><tr><th></th><th>2015<br>(1)</th><th>2015<br>(2)</th><th>2015<br>(3)</th><th>2022<br>(4)</th><th>2022<br>(5)</th><th>2022<br>(6)</th><th>Pooled<br>(7)</th><th>2015-2022<br>(8)</th></tr></thead><tbody><tr><td>Farming practice</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Organic</td><td>5.32***<br>(0.45)</td><td>4.31***<br>(0.46)</td><td>4.01***<br>(0.44)</td><td>5.8***<br>(0.16)</td><td>4.94***<br>(0.15)</td><td>4.94***<br>(0.15)</td><td>3.85***<br>(0.22)</td><td>3.74***<br>(0.21)</td></tr><tr><td>CAP (in 1000€)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Pillar 1</td><td></td><td>-0.38***<br>(0.01)</td><td></td><td></td><td>-0.26***<br>(0.00)</td><td></td><td>-0.33***<br>(0.00)</td><td></td></tr><tr><td>Pillar 2</td><td></td><td>-0.13***<br>(0.02)</td><td></td><td></td><td>-0.05***<br>(0.01)</td><td></td><td>-0.07***<br>(0.01)</td><td></td></tr><tr><td>Multi-risk climate insurance</td><td></td><td></td><td>-1.64***<br>(0.08)</td><td></td><td></td><td>-0.93***<br>(0.02)</td><td></td><td>-1.17***<br>(0.03)</td></tr><tr><td>AES Hedgerows</td><td></td><td></td><td>1.74**<br>(0.65)</td><td></td><td></td><td>2.42***<br>(0.23)</td><td></td><td>2.03***<br>(0.32)</td></tr><tr><td>(Intercept)</td><td>38.62***<br>(0.11)</td><td>44.53***<br>(1.12)</td><td>37.22***<br>(1.12)</td><td>34.16***<br>(0.06)</td><td>39.46***<br>(0.54)</td><td>34.10***<br>(0.55)</td><td>42.35***<br>(0.66)</td><td>35.90***<br>(0.66)</td></tr><tr><td>Dept</td><td>F</td><td>T</td><td>T</td><td>F</td><td>T</td><td>T</td><td>T</td><td>T</td></tr><tr><td>R<sup>2</sup></td><td>0.01</td><td>0.07</td><td>0.06</td><td>0.01</td><td>0.25</td><td>0.22</td><td>0.10</td><td>0.09</td></tr><tr><td>Adj. R<sup>2</sup></td><td>0.01</td><td>0.07</td><td>0.06</td><td>0.01</td><td>0.25</td><td>0.22</td><td>0.10</td><td>0.09</td></tr><tr><td>Num. obs.</td><td>357174</td><td>357174</td><td>311274</td><td>357174</td><td>311274</td><td>311274</td><td>668448</td><td>668448</td></tr></tbody></table>

Note: OLS regressions based on Equation (1). The dependent variable is hedgerow density (m/ha). Organic is a binary indicator for farms with at least one organic plot. CAP variables include Pillar 1 and 2 payments (in €1,000), with Pillar 2 measures targeting hedgerow maintenance and crop insurance. Department fixed effects included in all but columns (1) and (4). Standard errors in parentheses. Statistical significance levels: ***p < 0.001; **p < 0.01; *p < 0.05.

cannot be ruled out: farms with already high hedgerow density may be more inclined to transition to organic farming due to environmental considerations.

Despite these limitations, the results provide important insights into the relationship between farming practices and landscape conservation. The strong positive association between organic farming and hedgerow density suggests that policies promoting organic agriculture may contribute to maintaining or increasing landscape biodiversity. However, the negative correlation observed for farms undergoing conversion highlights potential challenges in the transition phase, suggesting that additional support may be needed to encourage hedgerow conservation among farms in the process of converting to organic practices.

## 5.2 TWFE results: evolution of hedgerow density

To mitigate these previous concerns, we complement this analysis with TWFE models, which control for time-invariant unobserved heterogeneity by analyzing changes in hedgerow density over time at the farm level.

To isolate the marginal effect of conversion to organic farming on hedgerow density, it is essential to control for other farms. However, this group is heterogeneous, comprising both farmers who remained conventional and those who remained organic throughout the period. As shown earlier, these two subgroups exhibit distinct hedgerow dynamics. Organic farms tend to maintain or expand
hedgerows, while conventional farms tend to lose them. It is therefore important to verify whether the estimated effects of conversion are sensitive to the composition of the benchmark group.

Figure 3, based on specifications 4-5 and 7-8 from table 4, illustrates how the effect of organic conversion varies depending on the benchmark group. When comparing converted farms to those that remained conventional, the main result holds: converted farms increase hedgerow density by approximately 1 meter per hectare more than conventional farms over the period. Disaggregating the effects by the year of conversion reveals heterogeneity in the intensity of hedgerow expansion. The effect strengthens with the time elapsed since conversion, with the largest gains observed among farms that began conversion in 2018. In contrast, more recently converted farms (those who transitioned in 2020 or 2021) exhibit no significant difference in hedgerow variation relative to conventional farmers (table 4 specification 2).

In contrast, when converted farms are compared to those that remained organic, no statisti- cally significant difference in hedgerow dynamics is detected. This result suggests two important patterns. First, organic farmers continue to maintain and expand hedgerows even after the initial conversion period. Second, converting farmers appear to adopt hedgerow-preserving practices early in the transition process. However, recently converted farmers, particularly those who converted in 2021, exhibit lower hedgerow growth than farms that were organic throughout the period (col- umn 8 on table 4). This finding suggests that the newly converted farmers have not had time to undertake conservation work and hedge planting, indicating that this is a practice not immediately implemented after conversion.

Specifications 3-6-9 investigate the role of CAP Pillar 2 measures, focusing on two instruments: (i) partial reimbursement of climate risk insurance premiums and (ii) AES aimed at hedgerow maintenance. The CAP instruments are expressed as the amount received by each farmer (in thousands of euros). The interaction between participation in AES and organic conversion re- veals strong complementarities. Farms that engage in both organic practices and AES contracts exhibit hedgerow expansion of nearly 1.1 meters per hectare for every additional €1,000 in AES subsidies received. These findings indicate that the combination of organic farming and targeted environmental measures delivers the most significant conservation outcomes.

Finally, Hedgerow density decreases by roughly 0.09 meters per hectare for each €1,000 of com- pensation received through the multi-risk climate insurance subsidy, indicating that farmers tend to reduce hedgerows as they increase the share of their land covered by such insurance (specifica- tion 3-6-9 on table 4). This result confirms a substitution between financial insurance and natural insurance. Insured farmers reduce the number of hedgerows in order to maximize their yields, whereas uninsured farmers tend to increase natural elements on their land to enhance the provision of ecosystem services, thereby securing natural protection against climate risks.

Overall, these findings emphasize that organic conversion and AES participation are effective levers for promoting hedgerow conservation, especially when implemented jointly. However, insur- ance subsidies may inadvertently weaken farmers’ incentives to maintain natural landscape features.
<figure><img src="image_4.png" /><figcaption>Figure 3: Impact of conversion to organic farming on hedgerow density, depending on the benchmark group.</figcaption></figure>

*Note:* The left side uses farms that remain conventional during the study period as the benchmark group, based on specifications 1 and 2 from Table 4. The right side uses farms that remain organic during the study period as the benchmark group, based on specifications 5 and 6. Each point represents a coefficient estimate from a TWFE model including individual and *département* × year fixed effects. Error bars indicate 95% confidence intervals.
<table><caption>Table 4: FD impact on conversion in organic and CAP measures on hedgerows density (in m per ha).</caption><thead><tr><th rowspan="3"></th><th colspan="9">Dependent variable: Hedgerows in meters per ha</th></tr><tr><th colspan="3">Benchmark: Pooled</th><th colspan="3">Benchmark: Conventional</th><th colspan="3">Benchmark: Organic</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th></tr></thead><tbody><tr><td>Conversion to organic</td><td>0.96***<br>(0.14)</td><td>0.93***<br>(0.14)</td><td>1.00***<br>(0.12)</td><td>0.97***<br>(0.12)</td><td>-0.09<br>(0.46)</td><td>-0.09<br>(0.46)</td><td></td><td></td><td></td></tr><tr><td>Conversion in 2018</td><td></td><td>0.85***<br>(0.25)</td><td></td><td>1.52***<br>(0.27)</td><td></td><td></td><td>-0.57<br>(0.44)</td><td></td><td></td></tr><tr><td>Conversion in 2019</td><td></td><td>0.53*<br>(0.26)</td><td></td><td>0.78**<br>(0.29)</td><td></td><td></td><td>-0.76<br>(0.48)</td><td></td><td></td></tr><tr><td>Conversion in 2020</td><td></td><td>0.33<br>(0.25)</td><td></td><td>0.50*<br>(0.24)</td><td></td><td></td><td>-0.91<br>(0.53)</td><td></td><td></td></tr><tr><td>Conversion in 2021</td><td></td><td>-0.07<br>(0.25)</td><td></td><td>0.20<br>(0.22)</td><td></td><td></td><td>-1.27*<br>(0.54)</td><td></td><td></td></tr><tr><td>AES Hedgerows (in thousand €)</td><td></td><td></td><td>0.13<br>(0.07)</td><td></td><td>0.10<br>(0.07)</td><td></td><td></td><td>0.54<br>(0.28)</td><td></td></tr><tr><td>AES Hedgerows × Conversion</td><td></td><td></td><td>1.09**<br>(0.41)</td><td></td><td>1.14**<br>(0.41)</td><td></td><td></td><td>0.38<br>(0.40)</td><td></td></tr><tr><td>Multi-risk climate Ins. (in thousand €)</td><td></td><td></td><td>-0.09***<br>(0.01)</td><td></td><td>-0.09***<br>(0.01)</td><td></td><td></td><td>-0.10***<br>(0.03)</td><td></td></tr><tr><td>Num. obs.</td><td colspan="3">668,766</td><td colspan="3">429,107</td><td colspan="3">49,233</td></tr><tr><td>Num. farms</td><td colspan="3">439,841</td><td colspan="3">214,453</td><td colspan="3">24,603</td></tr><tr><td>Dept × LT Adj. R<sup>2</sup></td><td colspan="3">0.92</td><td colspan="3">0.84</td><td colspan="3">0.53</td></tr><tr><td>Within R<sup>2</sup></td><td colspan="3">0.01</td><td colspan="3">0.02</td><td colspan="3">0.00</td></tr></tbody></table>

Note: This table presents the results from FD regressions based on Eq.2 and Eq.3, where the dependent variable is hedgerow density (in meters per hectare) at the farm level. The control group consists of rest of non conversion farmer in columns (1)-(3), always-conventional farms in columns (4)-(6), and always-organic farms in columns (7)-(9). The binary variable Conversion to organic equals one if the farm converted to organic farming at any point between 2015 and 2022. In columns (2)-(5)-(8), the Conversion to organic variable is disaggregated into a set of binary indicators, each representing the first year in which a farm initiated its conversion to organic farming. CAP-related payments include AES targeting hedgerow maintenance and crop insurance support. All specifications include farm fixed effects and department-specific linear time trends. Statistical significance levels: ***p < 0.001; **p < 0.01; *p < 0.05.
# 6 Heterogeneity

In this section, we assess whether the previous results are robust across crop types.

## 6.1 Crop Specialization and Hedgerow Dynamics

We next explore whether hedgerow dynamics vary with crop specialization, as the ecological and agronomic benefits of hedgerows are likely to be crop-dependent. For each farm, we construct crop composition measures based on the share of land allocated to six major crop categories: cereals, oilseed crops, grassland and fodder, permanent crops (excluding vineyards), vineyards, and vegetables.

Table 5 highlights systematic differences in land use between conventional and organic farms. On average, organic and transitioning farms allocate a smaller proportion of their land to cereals (18%) compared to conventional farms (32%). Conversely, organic farms dedicate a larger share of their land to permanent crops and vineyards—choices that probably reflect both agronomic strategies and market orientation. Turning to further descriptive statistics, Table 10 (see Appendix A.3) explores the relationship between crop types and hedgerow density in 2015 and 2022. Cereal plots, used as the reference category, have an average hedgerow density of 29.84 meters per hectare (as indicated by the intercept in specification 1). In contrast, grasslands and permanent crops show significantly higher densities, with 21 meters more per hectare, bringing their total to roughly 50 meters per hectare. Moreover, when controlling for crop type, hedgerow density is consistently higher on organically managed plots. Notably, organic vegetable and fruit plots feature 63 additional meters of hedgerows per hectare compared to their conventional equivalents, while oilseed crops under organic management show a difference of 25 meters per hectare.

$$ \text{Hedges/ha}_{i,t} = \beta_1 \cdot \text{Conversion}_{i,t} + \sum_{k=1}^{5} \theta_k \cdot \text{CropShare}_{i,k,t} \\ + \sum_{k=1}^{5} \lambda_k \cdot (\text{CropShare}_{i,k,t} \cdot \text{Conv}_{i,t}) + \gamma_i + \delta_{D(i)}t + \varepsilon_{i,t}, \quad (4) $$

Equation (4) extends the panel data specification (Eq. (2)) to account for heterogeneity in land use by including the shares of five crop types, expressed as proportions of the farm's total utilized agricultural area. Cereals are omitted and serve as the reference category.

The binary variable Conversion$_{i,t}$ equals one if farm i has converted to organic farming during the period 2015–2022, and zero otherwise. The interaction terms between crop shares and Conversion$_{i,t}$ allow the effect of conversion on hedgerow density to vary depending on the farm's crop structure. The coefficients $\theta_k$ capture baseline differences in hedgerow density across crop types relative to cereal-based farms (for non-converting farms), while the interaction coefficients $\lambda_k$ measure how the effect of conversion varies by crop type. As before, the model includes farm fixed effects $\gamma_i$ to account for unobserved time-invariant heterogeneity, and incorporates départe-
ment-specific time trends via $\delta_{D(i)}t$ to capture differential evolution in hedgerow dynamics across administrative regions.

Figure 4 presents the results of the TWFE model (see Table A.3), illustrating hedgerow dynamics by crop type. For each sub-figure, on the left side, converting farms are compared to farms that remained conventional throughout the period; on the right side, they are compared to farms that were always organic. The first bin in each panel shows the average effect for all farms that converted to organic farming compared to the benchmark group. The subsequent bins represent subgroups of converting farmers, distinguished by the year in which they first adopted organic practices.

The results reveal three key patterns. First, conversion to organic farming leads to a positive change in hedgerow density relative to conventional farms for most crop types, including cereals, oilseeds, and grassland. The estimated effects range from +1.01 meters per hectare for cereals to approximately +0.01 meters for grassland. Second, no significant differences emerge between the group converting to organic during the study period and farms that remained organic throughout the period, suggesting that organic practices supporting hedgerow conservation are adopted early in the transition period. Third, the positive effect of conversion is most pronounced among cereal farmers who converted early in the period (2018), indicating that hedgerow planting is a gradual adjustment that strengthens over time.

These results underscore the heterogeneity of hedgerow dynamics across crop types and farming systems. The agronomic benefits of hedgerows are closely linked to the need to mitigate yield reductions under organic management. For instance, hedgerows can play a critical role in enhancing natural pest control and stabilizing yields for organic cereal producers. In contrast, conventional cereal farmers may view hedgerows primarily as a cost, given their impact on usable land area and on mechanized farming practices.

<table><caption>Table 5: Average share of UAA by crop type and farm practices</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Conventional</th><th rowspan="2">Organic</th><th colspan="4">Conversion in :</th></tr><tr><th>2018</th><th>2019</th><th>2020</th><th>2021</th></tr></thead><tbody><tr><td>Cereals</td><td>0.316<br>(0.301)</td><td>0.154<br>(0.217)</td><td>0.220<br>(0.240)</td><td>0.201<br>(0.231)</td><td>0.186<br>(0.222)</td><td>0.180<br>(0.226)</td></tr><tr><td>Oilseeds</td><td>0.070<br>(0.134)</td><td>0.056<br>(0.131)</td><td>0.101<br>(0.179)</td><td>0.085<br>(0.158)</td><td>0.086<br>(0.162)</td><td>0.078<br>(0.153)</td></tr><tr><td>Grassland & Fodder</td><td>0.498<br>(0.390)</td><td>0.449<br>(0.377)</td><td>0.438<br>(0.363)</td><td>0.442<br>(0.366)</td><td>0.416<br>(0.362)</td><td>0.421<br>(0.367)</td></tr><tr><td>Permanent crops (excluded wine)</td><td>0.016<br>(0.102)</td><td>0.063<br>(0.188)</td><td>0.072<br>(0.215)</td><td>0.076<br>(0.220)</td><td>0.069<br>(0.209)</td><td>0.058<br>(0.190)</td></tr><tr><td>Wine</td><td>0.061<br>(0.222)</td><td>0.220<br>(0.382)</td><td>0.109<br>(0.290)</td><td>0.134<br>(0.314)</td><td>0.190<br>(0.362)</td><td>0.215<br>(0.379)</td></tr><tr><td>Fruits & Vegetables</td><td>0.032<br>(0.110)</td><td>0.050<br>(0.150)</td><td>0.053<br>(0.162)</td><td>0.054<br>(0.162)</td><td>0.047<br>(0.150)</td><td>0.042<br>(0.143)</td></tr><tr><td>Nb of farms</td><td>287821</td><td>3158</td><td>4585</td><td>4977</td><td>5375</td><td>5358</td></tr></tbody></table>

Note: This table reports the average share of Utilised Agricultural Area (UAA) allocated to different crop types across farms, by farming system. The first two columns show the average crop shares for always-conventional and always-organic farms, respectively. Columns (3) to (6) display the crop composition for farms that converted to organic farming in 2018, 2019, 2020, and 2021, respectively. Standard deviations are shown in parentheses. The last row indicates the number of farms in each category.
<figure><img src="image_5.png" /><figcaption>Figure 4: Impact of conversion on hedgerow density (m per ha) depending on crop type and benchmark group.</figcaption></figure>

Note: In each subfigure, the left-hand part reports coefficient estimates from a TWFE model using the "always conventional" group as the benchmark (specifications 1 and 2 in Table 11). The right-hand part refers to estimates using the "always organic" group as the benchmark (specifications 3 and 4). In subfigure (a), the model estimates the effect of organic conversion on the number of hedgerows for a cereal farm. All estimates include individual fixed effects and *département* × year fixed effects. Error bars represent 95% confidence intervals.
# 7 Robustness check

## 7.1 Change variable: sum of hedgerows

To test the robustness of our outcome variable, hedgerow density measured in meters per hectare, we alternatively consider the total length of hedgerows per farm (in meters). This is motivated by the fact that the ratio $\frac{\text{Hedgerows}}{\text{UAA}}$ can change even without any modification to hedgerow length, solely due to fluctuations in the farm's UAA.

The coefficient plot in Figure 5 and the results in Appendix A.2 confirm our previous findings. Farmers who convert to organic farming, compared to those who remain conventional, increase their total hedgerow length by an average of 119 meters. Once again, the timing of the conversion decision plays a key role in explaining these changes. Farmers who began the conversion process in 2018 or 2019 increased their hedgerow length significantly more than those who converted in 2021.

Figure 5: Impact of conversion to organic on hedgerow length (in m), depending on the benchmark group.

<figure><img src="image_6.png" /></figure>

*Note:* The left-hand side uses farms that remained conventional as the benchmark group, based on specifications 1 and 2 from Table 9. The right-hand side uses farms that remained organic as the benchmark group, based on specifications 5 and 6. Each point represents a coefficient estimate from a TWFE model including individual and *département* × year fixed effects. Error bars indicate 95% confidence intervals.
## 7.2 Farmers’ decisions: qualitative census

In the 2010 Agricultural Census, farmers were surveyed about their farming practices and landscape management. This section analyzes the qualitative responses related to hedgerows and lines of trees to complement our previous findings.

Farmers were categorized into two groups: (1) **Certified organic farmers**, having at least one product certified as "organic"<fnref n="2" />; and (2) **Conventional farmers**, who responded "no" to this question.

The sample includes 18,050 certified organic farmers and 498,102 conventional farmers. All respondents were asked whether they had planted or maintained hedgerows and lines of trees over the past three years. Responses were binary ("yes" or "no"), providing qualitative insights into their landscape management behavior.

We estimate the probability that farmer *i* chooses to plant or maintain lines of trees and hedgerows using a probit model:

$$ \Pr(Y_i = 1 | X_i) = \Phi(\beta_0 + \beta_1 \text{Organic}_i) \quad (5) $$

In this model, $Y_i = 1$ if the farmer chooses to plant or maintain trees and hedgerows, and $Y_i = 0$ otherwise. The function $\Phi(\cdot)$ denotes the cumulative distribution function of the standard normal distribution, consistent with the probit specification. The variable $\text{Organic}_i$ is a binary variable equal to 1 for farmers who are fully certified organic, equal to 0 if the farmer follows conventional agricultural practices.

The results reported in Table 6, based on equation 5, indicate that farmers already certified as organic are significantly more likely than conventional farmers to plant and maintain hedgerows and lines of trees (columns (1) to (4)). The magnitude and significance of these effects highlight clear behavioral differences between organic and conventional farmers regarding the shaping and maintenance of the landscape. Since the agricultural census questionnaire did not include the item on hedgerow management and planting in the 2020 survey wave, this analysis can only be conducted for a single period.

<footnote n="2">²Affirmative response to the question: “Do you have an ‘organic farming’ certification for any of the products from your farm (including wine)?”</footnote>
<table><caption>Table 6: Probit Models of Tree and Hedgerow Management by Farming System</caption><thead><tr><th rowspan="2"></th><th colspan="2">Hedgerows</th><th colspan="2">Trees alignments</th></tr><tr><th>Plant<br>(1)</th><th>Maintenance<br>(2)</th><th>Plant<br>(3)</th><th>Maintenance<br>(4)</th></tr></thead><tbody><tr><td>Farming practice<br>(ref: Conventional)</td><td></td><td></td><td></td><td></td></tr><tr><td>Organic</td><td>0.550***<br>(0.013)</td><td>0.247***<br>(0.010)</td><td>0.394***<br>(0.015)</td><td>0.205***<br>(0.010)</td></tr><tr><td>(Intercept)</td><td>-1.746***<br>(0.003)</td><td>0.094***<br>(0.002)</td><td>-1.927***<br>(0.004)</td><td>-0.617***<br>(0.002)</td></tr><tr><td>Num. farms</td><td>516152</td><td>516152</td><td>516152</td><td>516152</td></tr><tr><td>AIC</td><td>181587</td><td>711473</td><td>132072</td><td>602821</td></tr><tr><td>LL</td><td>-90791</td><td>-355734</td><td>-66034</td><td>-301397</td></tr></tbody></table>

*Note:* This table reports the results of probit models (Eq. 5) estimating the probability that a farmer chooses to plant or maintain hedgerows or tree alignments, depending on their farming system. The dependent variable $Y_i$ equals 1 if the farmer engages in the respective practice, and 0 otherwise. Explanatory variables include farmer systems: *Conventional* for farmers using conventional agricultural practices and *Organic* for fully certified organic farmers. Coefficients should be interpreted relative to this reference group. Standard errors are reported in parentheses. Significance levels are indicated as follows: \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001.

## 7.3 Other database: Small Woody Features

To verify the robustness of our results, we employ an alternative vegetation dataset: *Small Woody Features 2018 (SWF)* (Copernicus, 2023). This approach enables us to validate our findings using data from a different year (2018) and to include not just linear vegetation structures, such as hedgerows, but also patchy features, including groups of trees, isolated trees, and scrub.

The SWF data were derived from very high resolution satellite imagery provided by Copernicus Contributing Missions. In SWF, two types of vegetation are considered. First, linear structures including hedgerows, lines of trees, or patches of scrub located along field margins, roads, or riparian areas, with a minimum length of 30 meters. Second, patchy structures consisting of scattered groups of trees or patches of scrub, as well as isolated trees or shrubs, with sizes ranging from 200 $m^2$ to 5000 $m^2$.

Table 7, based on a sample of 329,803 farms, including 9,610 fully organic, 16,924 undergoing conversion, and 4,509 mixed farms, provides key insights. Column (1) shows that fully organic farms have twice the density of small woody elements<fnref n="3" /> (hedgerows, lines of trees, groups of trees, or shrubs) per hectare compared to fully conventional farms (24.2 elements per hectare for organic vs. 11.8 for conventional). Additionally, farms undergoing conversion to organic also display slightly higher vegetation density compared to conventional farms. This result aligns with table 3, which highlights the fact that farms undergoing conversion had similar hedgerow densities to conventional farms in 2015 but showed higher hedgerow densities than conventional farms by 2022.

<footnote n="3">³A small woody element is defined as a 25 $m^2$ area covered by vegetation (based on a 5x5 meter raster), which may be formed by linear structures or scattered elements.</footnote>
<table><caption>Table 7: Farm level, small woody element /ha,</caption><thead><tr><th></th><th colspan="2" style="text-align: center;">Small woody element /ha</th></tr><tr><th></th><th colspan="2" style="text-align: center;">2018</th></tr><tr><th></th><th style="text-align: center;">(1)</th><th style="text-align: center;">(2)</th></tr></thead><tbody><tr><td>Farming practice (ref: Fully conventional)</td><td></td><td></td></tr><tr><td>Fully organic</td><td style="text-align: center;">12.481<sup>***</sup><br>(0.237)</td><td style="text-align: center;">10.872<sup>***</sup><br>(0.232)</td></tr><tr><td>Under conversion</td><td style="text-align: center;">4.181<sup>***</sup><br>(0.181)</td><td style="text-align: center;">2.821<sup>***</sup><br>(0.177)</td></tr><tr><td>Mix</td><td style="text-align: center;">7.902<sup>***</sup><br>(0.343)</td><td style="text-align: center;">5.633<sup>***</sup><br>(0.336)</td></tr><tr><td>Constant</td><td style="text-align: center;">11.777<sup>***</sup><br>(0.042)</td><td style="text-align: center;">10.812<sup>***</sup><br>(0.426)</td></tr><tr><td>Dept</td><td style="text-align: center;">F</td><td style="text-align: center;">T</td></tr><tr><td>Nb Obs</td><td style="text-align: center;">329,803</td><td style="text-align: center;">329,803</td></tr><tr><td>Adjusted R<sup>2</sup></td><td style="text-align: center;">0.011</td><td style="text-align: center;">0.064</td></tr></tbody></table>

Note: This table reports OLS estimates of the relationship between farming practices and the density of small woody elements (in meters per hectare) at the farm level in 2018. The dependent variable is the number of small woody elements, defined as a 25 m² area covered by vegetation (based on a 5x5 meter raster), which may consist of linear or scattered features. The key independent variable is farming practice, treated as a categorical variable with "fully conventional" as the reference category. "Under conversion" refers to farms undergoing the organic conversion process, and *Mix* farms are those combining organic and conventional plots. Column (1) includes no additional controls; Column (2) includes *département* fixed effects. Robust standard errors are in parentheses. ***p < 0.001.
# 8 Simulating Policy Efficiency Gains from Targeted Hedgerow Support

This section combines estimated treatment effects with program cost data to assess how targeting hedgerow subsidies to organic and converting farmers can improve policy efficiency under a fixed budget.

The French government's *Pacte en faveur de la haie* (pact benefiting hedgerows) is a multi-year initiative launched to restore the country's hedgerow network. Initially funded at €110 million annually over the period 2024-2030, the program aimed to support the planting of 50,000 kilometers of hedgerow by 2030. A 2025 budget revision reduced annual funding to €45 million. In the absence of further adjustments, this implies a reduction in the program's total budget from €770 million to €380 million. The program provides direct payments to farmers for each meter of hedgerow planted. Under current rules, all farmers are eligible to receive this subsidy, which ranges from €14.20 to €23.30 per meter (calculation detail in Appendix A.5) depending on the technical specifications of the installation (DRAAF Grand Est, 2024).

Estimates from Table 4 indicate that farmers either certified organic or in the process of organic conversion respond strongly to hedgerow-related public support. On average, these farmers plant 1.14 additional meters of hedgerow per hectare in response to a €1,000 subsidy. Given an average farm size of 94.79 hectares, this corresponds to roughly 108 meters per farm, implying an effective cost of €9.25 to €12.27 per meter. This value represents the estimated willingness to accept (WTA) for hedgerow planting among organic and converting farmers and falls well below the observed range of subsidy costs under the general program.

To evaluate the policy's efficiency under alternative targeting strategies, we simulate hedgerow planting outcomes under two scenarios: (i) a *universal subsidy* available to all farmers, and (ii) a *targeted subsidy* restricted to organic and converting farmers. In both cases, we assume a constant annual budget of €45 million.

<table><caption>Table 8: Simulated hedgerow planting and required budget under alternative targeting scenarios</caption><thead><tr><th></th><th>All farmers</th><th>Organic/Under conversion</th></tr></thead><tbody><tr><td>Policy subsidy (€/m)</td><td>[14.2, 23.3]</td><td>—</td></tr><tr><td>WTA (€/m)</td><td>—</td><td>[9.25, 12.27]</td></tr><tr><td>Hedgerows per €1,000 (m)</td><td>[42.9, 70.4]</td><td>[85.5,108]</td></tr><tr><td>Hedgerows for €45M (km)</td><td>[1931, 3169]</td><td>[3667,4865]</td></tr><tr><td>Required budget to reach 50000 km by 2030 (€M)</td><td>[711, 1165]</td><td>[462, 614]</td></tr></tbody></table>

Table 8 reports the simulated outcomes. When the program is available to all farmers, the total length of hedgerows planted annually varies between 1,931 and 3,169 kilometers, depending on the implementation cost. This corresponds to between 42.9 and 70.4 meters per €1,000 of spending. In contrast, when support is directed exclusively to organic and converting farmers, the estimated annual planting reaches approximately 3,667 to 4,865 kilometers. These gains stem from a substantially lower WTA among the targeted group, which allows for more hedgerow coverage at a given budget level.
Overall, the results suggest that targeting support toward farmers with a stronger predisposition to plant hedgerows, such as those involved in organic systems, can more than double the policy's impact and yield up to 2.5 times more hedgerows per euro spent. To meet the program's goal of planting 50,000 kilometers of hedgerows by 2030, the required budget would range from €711 million to €1.165 billion under the universal scheme, depending on the per meter cost, but would fall to just €462 to €614 million if subsidies are restricted to organic and converting farmers.

Given the program's initial overall budget of €770 million, the objectives could likely have been achieved by targeting only certified organic farmers and those undergoing conversion. With the revised total budget of €380 million, however, the target now appears unattainable, particularly in the absence of targeting beneficiaries based on agricultural practice.

# 9 Conclusion

This paper provides new evidence on the relationship between organic farming and hedgerow conservation. Our results consistently show that organic farms are associated with higher hedgerow density than conventional farms, both in levels and in changes over time. In 2015, organic farms exhibited approximately 10% higher hedgerow density than conventional farms. Between 2015 and 2022, this divergence widened as conventional farms experienced a decline in hedgerow density (-0.4 meters per hectare), while organic farms increased hedgerow density (+0.2 meters per hectare).

To identify the causal effect of organic farming, we focus on farms that converted between 2015 and 2022. A TWFE specification reveals that conversion leads to a significant increase in hedgerow density. Specifically, relative to farms that remained conventional, converted farms increased hedgerow density by approximately 0.95 meters per hectare. Interestingly, we find that the hedgerow dynamics of converting farms quickly converge to those of farms that were organic throughout the period, suggesting early adoption of conservation-oriented practices during the transition.

The timing of conversion plays an important role. Early adopters, who converted four or more years ago, exhibit the largest increases in hedgerow density (+0.85 meters per hectare), indicating that hedgerow planting is a gradual adjustment. The process begins with the conservation of existing hedgerows and progressively shifts towards active planting. Robustness checks using the SWF dataset confirm that organic farms are not only characterized by higher linear hedgerow density but also by greater vegetation diversity, including patchy woody features such as tree clusters and scrubland. This pattern suggests that organic farmers adopt more diversified and adaptive vegetation management strategies, contributing to ecological resilience.

Beyond farming practices, our results highlight significant heterogeneity across crop types. We show that orchards and grassland systematically exhibit higher hedgerow densities, regardless of management system. However, the positive effect of organic conversion on hedgerow dynamics is primarily concentrated in cereal production. For vineyards and orchards, conversion does not significantly affect hedgerow density. This heterogeneity is consistent with agronomic mechanisms. Cereal yields typically suffer larger organic-conventional yield gaps (approximately 30% according to Seufert et al. (2012)), making farmers more reliant on ecosystem services provided by hedgerows.
In contrast, perennial crops such as vineyards and orchards face smaller yield penalties and derive fewer marginal benefits from hedgerows (Klinnert et al., 2024).

From a policy perspective, these findings raise concerns about the effectiveness of existing CAP instruments. Despite their ecological importance, hedgerows remain insufficiently protected. The uptake of hedgerow maintenance agri-environmental schemes is extremely limited, covering only 0.6% of France's hedgerow network. Administrative burdens and insufficient financial incentives are probably key barriers, as maintenance contracts often impose net costs on farmers (AFAC agroforesteries, 2015). Moreover, the CAP budget allocated to encouraging farmers to purchase climate risk insurance harms hedgerow development. Policymakers need to consider farmers' trade-off behavior between financial and natural insurance when designing support schemes for insurance. More broadly, current CAP measures appear insufficient to reverse the ongoing decline in hedgerows.

Policy simulations suggest that targeting hedgerow subsidies to organic and converting farmers could more than double the impact per euro spent. The initially planned budget of €770 million would have been sufficient to reach the 50,000 km target if it had been exclusively allocated to organic and converting farmers. This underlines the potential efficiency gains from aligning agri-environmental support with farmers already engaged in conservation practices.

These results underscore the potential for designing more effective conservation incentives by aligning hedgerow conservation programs with organic farming support. Recognizing the complementarities between organic practices and landscape conservation could help improve both ecological and economic outcomes. Future research could investigate heterogeneous effects by farming specialization, regional policy design, and land-use history. In addition, quantifying the long-term environmental and productivity impacts of hedgerows would provide valuable insights for the design of agri-environmental policies aimed at fostering resilient and sustainable agricultural landscapes.

## Financial disclosure statement

This work was supported by the French Research Agency within the CLAND project [ANR-16-CONV-0003] and the European Union's Horizon Europe Research and Innovation program within the LAMASUS project [101060423].

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# A Appendix

## A.1 Summary statistics: Nuts-2 hedgerow distribution

<figure><img src="image_7.png" /><figcaption>Figure 6: Farm hedgerow density (in m per ha), at the NUTS-2 level in France (period 2015-2022)</figcaption></figure>

## A.2 Robustness check: impact of conversion on length of hedgerows in meters

In the main analysis, we examine hedgerow density, measured as the total length of hedgerows divided by the farm area. However, changes in hedgerow density do not necessarily reflect changes in the length of hedgerows; they may also result from variations in farm size. To verify that organic conversion is indeed the driver of an increase in hedgerow length at the farm level, we estimate the TWFE model in equation 2 using the dependent variable *hedgerows in meters*, i.e. the total length of hedgerows on the farm.

Table 9 confirms that, over the 2015–2022 period, conversion to organic farming increases hedgerow length by 113 to 119 meters compared to farms that remained conventional, depending on the specification (columns 1, 3, and 4). Once again, we observe a stronger effect depending on the timing of conversion, with the largest effect found for early converters (column 2).
<table><caption>Table 9: TWFE impact on conversion in organic and CAP measures on hedgerows density (in m).</caption><thead><tr><th rowspan="3">Benchmark:</th><th colspan="12">Dependent variable: Hedgerows in meters</th></tr><tr><th colspan="4">Conventional</th><th colspan="4">Organic</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th></tr></thead><tbody><tr><td>Conversion to organic</td><td>119.04***<br>(8.13)</td><td></td><td>116.24***<br>(8.13)</td><td>113.52***<br>(8.15)</td><td>6.46<br>(10.97)</td><td></td><td>6.56<br>(10.94)</td><td>11.88<br>(12.13)</td></tr><tr><td>Conversion in 2018</td><td></td><td>124.76***<br>(20.24)</td><td></td><td></td><td></td><td>60.86**<br>(19.10)</td><td></td><td></td></tr><tr><td>Conversion in 2019</td><td></td><td>139.83***<br>(22.02)</td><td></td><td></td><td></td><td>82.92***<br>(20.61)</td><td></td><td></td></tr><tr><td>Conversion in 2020</td><td></td><td>104.46***<br>(18.48)</td><td></td><td></td><td></td><td>54.00**<br>(18.29)</td><td></td><td></td></tr><tr><td>Conversion in 2021</td><td></td><td>72.45***<br>(18.87)</td><td></td><td></td><td></td><td>56.86**<br>(21.02)</td><td></td><td></td></tr><tr><td>AES Hedgerows</td><td></td><td></td><td>48.27***<br>(13.35)</td><td>92.90***<br>(27.16)</td><td></td><td></td><td>94.68***<br>(28.50)</td><td>82.09<br>(59.70)</td></tr><tr><td>AES × Conversion</td><td></td><td></td><td>105.13<br>(64.59)</td><td>320.36**<br>(99.72)</td><td></td><td></td><td>44.97<br>(63.47)</td><td>242.35*<br>(112.31)</td></tr><tr><td>Multi-risk climatic insurrance</td><td></td><td></td><td>-15.13***<br>(1.46)</td><td>-21.31***<br>(3.65)</td><td></td><td></td><td>-14.73***<br>(3.52)</td><td>-16.87<br>(11.83)</td></tr><tr><td>UAA</td><td>21.88***<br>(0.29)</td><td>21.88***<br>(0.29)</td><td>22.01***<br>(0.29)</td><td>21.88***<br>(0.29)</td><td>21.74***<br>(1.02)</td><td>21.63***<br>(1.02)</td><td>21.85***<br>(1.03)</td><td>21.73***<br>(1.02)</td></tr><tr><td>Num. observations</td><td colspan="2">429,107</td><td colspan="2">429,107</td><td colspan="2">49,233</td><td colspan="2">49,233</td></tr><tr><td>Num. farms</td><td colspan="2">214,453</td><td colspan="2">214,453</td><td colspan="2">24,603</td><td colspan="2">24,603</td></tr><tr><td>Dept × LT fixed effects</td><td colspan="2">T</td><td colspan="2">T</td><td colspan="2">T</td><td colspan="2">T</td></tr><tr><td>Adj. R<sup>2</sup></td><td colspan="2">0.96</td><td colspan="2">0.96</td><td colspan="2">0.94</td><td colspan="2">0.94</td></tr><tr><td>Within R<sup>2</sup></td><td colspan="2">0.46</td><td colspan="2">0.46</td><td colspan="2">0.45</td><td colspan="2">0.45</td></tr></tbody></table>

Note: This table presents the results from TWFE regressions based on Equation (2), where the dependent variable is length of hedgerows (in meters) at the farm level. The control group consists of always-conventional farms in columns (1)–(4), and always-organic farms in columns (5)–(8). The binary variable *Conversion to organic* equals one if the farm converted to organic farming at any point between 2015 and 2022. In columns (2) and (6), the *Conversion to organic* variable is disaggregated into a set of binary indicators, each representing the first year in which a farm initiated its conversion to organic farming. In columns (3) and (7), CAP-related payments (AES targeting hedgerow maintenance and multi-risk climate insurance) are expressed in thousands of euros, while in columns (4) and (8), they correspond to a binary variable indicating whether the farmer received the payment (1) or not (0). The variable *UAA* refers to the farm’s utilised agricultural area, included to account for changes in hedgerow length driven by changes in farm size. All specifications include farm fixed effects and department-specific linear time trends. Statistical significance levels: ***p < 0.001; **p < 0.01; *p < 0.05.
### A.3 TWFE result: impact of conversion on hedgerow density depending on crop heterogeneity

#### Cross section regression

$$ \text{Hedges/ha}_i = \gamma_0 + \beta_1 \cdot \text{Organic}_i + \sum_{k=1}^{5} \theta_k \cdot \text{CropShare}_{ik} + \sum_{k=1}^{5} \lambda_k \cdot (\text{CropShare}_{ik} \cdot \text{Organic}_i) + \delta_{D(i)} + \varepsilon_i, \quad (6) $$

Equation (6) extends the baseline OLS model (Eq. (1)) by breaking down farm-level land use into six categories of crop types, expressed as shares of the farm's total utilized agricultural area. These crop shares are entered into the regression as continuous variables, and we include interaction terms between each crop share and the binary organic farming indicator to capture heterogeneous effects of organic practices depending on the farm's land-use structure.

We exclude cereals from the set of crop share variables, so it serves as the reference category. The coefficients $\theta_k$ measure the difference in hedgerow density between farms with a given crop type $k$ and farms mainly growing cereals, for non-organic farms. The interaction terms $\lambda_k$ estimate how these differences vary for organic farms relative to conventional ones.
<table><caption>Table 10: Cross-sectional analysis of the influence of crop types on hedgerow density</caption><thead><tr><th></th><th colspan="6">Dependent variable: Hedgerows in m /ha</th></tr><tr><th></th><th colspan="2">2015</th><th colspan="2">2022</th><th colspan="2">Pooled</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>(Intercept)</td><td>29.84***<br>(2.59)</td><td>30.48***<br>(2.60)</td><td>27.05***<br>(2.89)</td><td>28.05***<br>(2.88)</td><td>28.86***<br>(2.69)</td><td>29.65***<br>(2.69)</td></tr><tr><td>Organic</td><td>0.13<br>(2.00)</td><td>0.58<br>(1.94)</td><td>-0.88<br>(1.80)</td><td>-0.33<br>(1.72)</td><td>-1.32<br>(1.72)</td><td>-0.58<br>(1.64)</td></tr><tr><td>% by crops (ref: cereals)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>% oilseeds crops</td><td>-22.49***<br>(6.74)</td><td>-21.76***<br>(6.54)</td><td>-15.96*<br>(6.32)</td><td>-15.00*<br>(6.03)</td><td>-20.26**<br>(6.48)</td><td>-19.35**<br>(6.23)</td></tr><tr><td>Organic X % oilseeds crops</td><td>25.59***<br>(5.53)</td><td>24.50***<br>(5.52)</td><td>13.74**<br>(4.46)</td><td>12.47**<br>(4.31)</td><td>19.07***<br>(4.75)</td><td>17.88***<br>(4.67)</td></tr><tr><td>% Grassland & fodder</td><td>21.12***<br>(3.04)</td><td>20.46***<br>(3.04)</td><td>17.65***<br>(3.02)</td><td>16.58***<br>(3.00)</td><td>19.18***<br>(2.95)</td><td>18.36***<br>(2.94)</td></tr><tr><td>Organic X % Grassland & fodder</td><td>-8.01**<br>(2.91)</td><td>-8.52**<br>(2.87)</td><td>0.08<br>(2.35)</td><td>-0.55<br>(2.26)</td><td>-3.12<br>(2.21)</td><td>-3.94<br>(2.14)</td></tr><tr><td>% Perm corps (exlud: wine)</td><td>21.12***<br>(6.08)</td><td>21.12***<br>(6.09)</td><td>10.17*<br>(4.41)</td><td>9.26*<br>(4.41)</td><td>17.15**<br>(5.51)</td><td>16.71**<br>(5.52)</td></tr><tr><td>Organic X %Perm corps (exlud: wine)</td><td>4.71<br>(7.54)</td><td>4.41<br>(7.45)</td><td>12.75**<br>(4.04)</td><td>12.21**<br>(4.01)</td><td>6.85<br>(4.59)</td><td>6.05<br>(4.54)</td></tr><tr><td>% Wine</td><td>-0.23<br>(3.81)</td><td>0.77<br>(3.55)</td><td>-2.93<br>(3.83)</td><td>-1.64<br>(3.57)</td><td>-1.92<br>(3.79)</td><td>-0.70<br>(3.54)</td></tr><tr><td>Organic X % Wine</td><td>4.07<br>(2.41)</td><td>2.99<br>(2.30)</td><td>3.14<br>(2.10)</td><td>2.21<br>(2.00)</td><td>3.22<br>(2.06)</td><td>2.29<br>(1.96)</td></tr><tr><td>Legumes & Vegetables</td><td>4.15<br>(9.00)</td><td>4.25<br>(8.98)</td><td>-11.12<br>(6.13)</td><td>-11.21<br>(6.05)</td><td>-3.67<br>(7.58)</td><td>-3.55<br>(7.54)</td></tr><tr><td>Organic X % Legumes & Vegetables</td><td>63.42***<br>(9.27)</td><td>62.37***<br>(9.29)</td><td>69.75***<br>(7.36)</td><td>68.37***<br>(7.29)</td><td>66.08***<br>(8.11)</td><td>64.54***<br>(8.08)</td></tr><tr><td>Multi-risk climatic insurrance</td><td></td><td>-1.53***<br>(0.29)</td><td></td><td>-0.99***<br>(0.19)</td><td></td><td>-1.20***<br>(0.22)</td></tr><tr><td>AES Hedgerows</td><td></td><td>-0.42<br>(0.60)</td><td></td><td>1.65<br>(0.87)</td><td></td><td>0.72<br>(0.59)</td></tr><tr><td>Cluster (Dept)</td><td>T</td><td>T</td><td>T</td><td>T</td><td>T</td><td>T</td></tr><tr><td>Num. obs.</td><td>357174</td><td>357174</td><td>311274</td><td>311274</td><td>668448</td><td>668448</td></tr><tr><td>Adj. R<sup>2</sup></td><td>0.03</td><td>0.03</td><td>0.09</td><td>0.09</td><td>0.04</td><td>0.04</td></tr></tbody></table>

<footnote>Note: This table reports OLS estimates based on Equation (6), where the dependent variable is hedgerow density (in meters per hectare) at the farm level. Crop shares refer to the proportion of a farm's UAA dedicated to each crop type. The specification also includes interaction terms between each crop share and the organic farming indicator to capture heterogeneous effects by land use structure. The reference category for crop type is cereals. Models in columns (2), (4), and (6) control for CAP Pillar 2 measures: insurance subsidies and agri-environmental schemes (AES) targeting hedgerows. All models include department fixed effects and standard errors clustered at the department level. ***p < 0.001; **p < 0.01; *p < 0.05.</footnote>
<table><caption>Table 11: TWFE regression: interaction between crop type shares and organic conversion on hedgerow density</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Benchmark:</th><th colspan="4">Dependent variable: Hedgerows in m / ha</th></tr><tr><th>Conventional<br>(1)<br>1.05<sup>***</sup><br>(0.21)</th><th>(2)</th><th>(3)</th><th>Organic<br>(4)</th></tr></thead><tbody><tr><td>ref % cereals</td><td></td><td></td><td>-0.15<br>(0.46)</td><td></td><td></td></tr><tr><td>Year conversion: 2018 X % cereals</td><td></td><td>1.83<sup>***</sup><br>(0.51)</td><td></td><td></td><td>-0.41<br>(0.61)</td></tr><tr><td>Year conversion: 2019 X % cereals</td><td></td><td>0.55<br>(0.56)</td><td></td><td></td><td>-0.85<br>(0.58)</td></tr><tr><td>Year conversion: 2020 X % cereals</td><td></td><td>0.50<br>(0.46)</td><td></td><td></td><td>-1.26<br>(0.67)</td></tr><tr><td>Year conversion: 2021 X % cereals</td><td></td><td>0.16<br>(0.43)</td><td></td><td></td><td>-1.87<sup>**</sup><br>(0.61)</td></tr><tr><td>% oilseeds</td><td></td><td>-0.04<sup>***</sup><br>(0.00)</td><td>-0.04<sup>***</sup><br>(0.00)</td><td>-0.03<sup>***</sup><br>(0.00)</td><td>-0.03<sup>***</sup><br>(0.00)</td></tr><tr><td>All conversion X % oilseeds</td><td></td><td>0.01<sup>*</sup><br>(0.00)</td><td></td><td>0.00<br>(0.00)</td><td></td></tr><tr><td>Year conversion: 2018 X % oilseeds</td><td></td><td></td><td>0.00<br>(0.01)</td><td></td><td>0.01<br>(0.01)</td></tr><tr><td>Year conversion: 2019 X % oilseeds</td><td></td><td></td><td>0.01<br>(0.01)</td><td></td><td>-0.00<br>(0.01)</td></tr><tr><td>Year conversion: 2020 X % oilseeds</td><td></td><td></td><td>0.01<sup>*</sup><br>(0.01)</td><td></td><td>0.00<br>(0.01)</td></tr><tr><td>Year conversion: 2021 X % oilseeds</td><td></td><td></td><td>0.02<sup>**</sup><br>(0.01)</td><td></td><td>0.02<sup>*</sup><br>(0.01)</td></tr><tr><td>% Grassland & Fodder</td><td></td><td>-0.06<sup>***</sup><br>(0.00)</td><td>-0.05<sup>***</sup><br>(0.00)</td><td>-0.04<sup>***</sup><br>(0.00)</td><td>-0.04<sup>***</sup><br>(0.00)</td></tr><tr><td>All conversion X % Grassland & Fodder</td><td></td><td>0.01<sup>***</sup><br>(0.00)</td><td></td><td>0.00<br>(0.00)</td><td></td></tr><tr><td>Year conversion: 2018 X % Grassland & Fodder</td><td></td><td></td><td>0.01<br>(0.00)</td><td></td><td>0.01<sup>*</sup><br>(0.00)</td></tr><tr><td>Year conversion: 2019 X % Grassland & Fodder</td><td></td><td></td><td>0.01<sup>**</sup><br>(0.00)</td><td></td><td>0.01<br>(0.00)</td></tr><tr><td>Year conversion: 2020 X % Grassland & Fodder</td><td></td><td></td><td>0.01<sup>**</sup><br>(0.00)</td><td></td><td>0.01<sup>**</sup><br>(0.00)</td></tr><tr><td>Year conversion: 2021 X % Grassland & Fodder</td><td></td><td></td><td>0.01<sup>**</sup><br>(0.00)</td><td></td><td>0.01<sup>**</sup><br>(0.00)</td></tr><tr><td>% permanent crops (excluded wine)</td><td></td><td>-0.07<sup>***</sup><br>(0.02)</td><td>-0.07<sup>***</sup><br>(0.02)</td><td>-0.20<sup>*</sup><br>(0.10)</td><td>-0.21<br>(0.11)</td></tr><tr><td>All conversion X % permanent crops (excluded wine)</td><td></td><td>0.03<sup>*</sup><br>(0.01)</td><td></td><td>0.08<sup>*</sup><br>(0.04)</td><td></td></tr><tr><td>Year conversion: 2018 X % permanent crops (excluded wine)</td><td></td><td></td><td>0.01<br>(0.03)</td><td></td><td>0.02<br>(0.04)</td></tr><tr><td>Year conversion: 2019 X % permanent crops (excluded wine)</td><td></td><td></td><td>0.04<br>(0.02)</td><td></td><td>0.08<br>(0.04)</td></tr><tr><td>Year conversion: 2020 X % permanent crops (excluded wine)</td><td></td><td></td><td>0.02<br>(0.02)</td><td></td><td>0.07<sup>*</sup><br>(0.03)</td></tr><tr><td>Year conversion: 2021 X % permanent crops (excluded wine)</td><td></td><td></td><td>0.04<sup>*</sup><br>(0.02)</td><td></td><td>0.11<br>(0.07)</td></tr><tr><td>% wine</td><td></td><td>-0.07<sup>***</sup><br>(0.01)</td><td>-0.07<sup>***</sup><br>(0.01)</td><td>-0.06<sup>***</sup><br>(0.02)</td><td>-0.07<sup>***</sup><br>(0.02)</td></tr><tr><td>All conversion X % wine</td><td></td><td>-0.01<sup>*</sup><br>(0.01)</td><td></td><td>0.01<br>(0.02)</td><td></td></tr><tr><td>Year conversion: 2018 X % wine</td><td></td><td></td><td>-0.01<br>(0.02)</td><td></td><td>0.00<br>(0.01)</td></tr><tr><td>Year conversion: 2019 X % wine</td><td></td><td></td><td>0.00<br>(0.02)</td><td></td><td>0.02<br>(0.03)</td></tr><tr><td>Year conversion: 2020 X % wine</td><td></td><td></td><td>-0.01<br>(0.01)</td><td></td><td>0.03<br>(0.02)</td></tr><tr><td>Year conversion: 2021 X % wine</td><td></td><td></td><td>-0.01<br>(0.01)</td><td></td><td>0.02<br>(0.02)</td></tr><tr><td>% Fruits & Vegetables</td><td></td><td>-0.03<sup>***</sup><br>(0.00)</td><td>-0.03<sup>***</sup><br>(0.00)</td><td>-0.02<sup>*</sup><br>(0.01)</td><td>-0.01<br>(0.01)</td></tr><tr><td>All conversion X % Fruits & Vegetables</td><td></td><td>0.01<br>(0.01)</td><td></td><td>-0.00<br>(0.01)</td><td></td></tr><tr><td>Year conversion: 2018 X % Fruits & Vegetables</td><td></td><td></td><td>-0.01<br>(0.01)</td><td></td><td>-0.06<sup>***</sup><br>(0.02)</td></tr><tr><td>Year conversion: 2019 X % Fruits & Vegetables</td><td></td><td></td><td>0.02<sup>*</sup><br>(0.01)</td><td></td><td>-0.02<br>(0.01)</td></tr><tr><td>Year conversion: 2020 X % Fruits & Vegetables</td><td></td><td></td><td>0.03<sup>*</sup><br>(0.01)</td><td></td><td>0.01<br>(0.01)</td></tr><tr><td>Year conversion: 2021 X % Fruits & Vegetables</td><td></td><td></td><td>0.00<br>(0.01)</td><td></td><td>-0.01<br>(0.02)</td></tr><tr><td>DEPT X LT</td><td>T</td><td></td><td>T</td><td></td><td>T</td></tr><tr><td>Num. obs.</td><td>429107</td><td>429107</td><td>49233</td><td></td><td>49233</td></tr><tr><td>Num. farms</td><td>214453</td><td>214453</td><td>24603</td><td></td><td>24603</td></tr><tr><td>Adj. R<sup>2</sup></td><td>0.84</td><td>0.84</td><td>0.53</td><td></td><td>0.53</td></tr><tr><td>Within Adj. R<sup>2</sup></td><td>0.02</td><td>0.02</td><td>0.00</td><td></td><td>0.00</td></tr></tbody></table>

Note: This table reports estimates from a TWFE model (Equation (4)) assessing how the share of different crop types interacts with organic conversion status in influencing hedgerow density (measured in meters per hectare). All models include farm fixed effects ($\gamma_i$) and department-year fixed effects ($\delta_{D(i)t}$). The variable *Conversion* is interacted with crop shares to capture differential effects by crop type. Columns (2) and (4) disaggregate these effects based on the year of conversion, by interacting crop shares with year-specific conversion dummies. Robust standard errors are reported in parentheses. ***$p < 0.001$; **$p < 0.01$; *$p < 0.05$
## A.4 Robustness Check with a Simple DID Model

In this section, we simply check whether our results are robust using a basic DID model without fixed effects, as described in the following equation:

$$Hedges_{it} = \alpha + \delta (Converted_{i} \times Year2022_{t}) + \varepsilon_{it} \quad (7)$$

where $Hedges_{it}$ is the hedgerow density per hectare for farmer $i$ at time $t$, Converted$_i$ is a treatment group indicator that equals 1 if farmer $i$ converted during the period, Year2022$_t$ is a post-treatment time indicator, and $\delta$ captures the difference-in-differences estimate.

Tables 12 and 13 confirm the results obtained in the main analysis with fixed effects. In these tables, which report estimates from a simple Difference-in-Differences model without fixed effects, we again find that farms that converted to organic farming increased their hedge density by about 4.30 m/ha compared to non-converting farms.

Moreover, Table 13 shows that the magnitude of this increase depends on the length of time since conversion. Farms that converted in 2018 exhibit a significantly larger increase in hedge density than those that converted in 2020 or 2021.
<table><thead><tr><th></th><th colspan="3" style="text-align: center;">Dependent variable: Hedgerows in m</th></tr><tr><th>Benchmark:</th><th>Pooled</th><th>Conventional</th><th>Organic</th></tr></thead><tbody><tr><td>(Intercept)</td><td>39.16***<br>(0.09)</td><td>34.72***<br>(0.07)</td><td>41.99***<br>(0.33)</td></tr><tr><td>Yr: 2022</td><td>-4.15***<br>(0.13)</td><td>-0.38***<br>(0.09)</td><td>0.21<br>(0.47)</td></tr><tr><td>Farmer before conversion</td><td>-6.40***<br>(0.48)</td><td>-1.97***<br>(0.28)</td><td>-9.23***<br>(0.48)</td></tr><tr><td>Farmer after conversion</td><td>4.30***<br>(0.68)</td><td>0.54<br>(0.40)</td><td>-0.06<br>(0.67)</td></tr><tr><td>R<sup>2</sup></td><td>0.00</td><td>0.00</td><td>0.02</td></tr><tr><td>Adj. R<sup>2</sup></td><td>0.00</td><td>0.00</td><td>0.02</td></tr><tr><td>Num. obs.</td><td>668766</td><td>429107</td><td>49233</td></tr></tbody></table>

<caption>Table 12: Simple Difference-in-Differences Estimates of Hedgerow Density</caption>

*Notes:* The estimates are based on the simple DID model without fixed effects described in Eq. 7. The coefficient "Farmer after conversion" corresponds to the difference-in-differences estimate. We rely on three benchmark groups for comparison with the converted farmers: in column (1), the benchmark includes all other farmers; in column (2), only conventional farmers; and in column (3), only organic farmers. Robust standard errors are reported in parentheses.
***p < 0.001; **p < 0.01; *p < 0.05.

<footnote>***p < 0.001; **p < 0.01; *p < 0.05</footnote>
<table><thead><tr><th></th><th>Dependent variable: Hedgerows in m<br>Benchmark: Conventional</th></tr></thead><tbody><tr><td>(Intercept)</td><td>35.14***</td></tr><tr><td>Yr: 2022</td><td>-0.21*<br>(0.07)</td></tr><tr><td colspan="2"><em>Farmer group in 2015:</em></td></tr><tr><td>Always Organic</td><td>-0.84<br>(0.83)</td></tr><tr><td>Conversion in 2018</td><td>-2.27***<br>(0.61)</td></tr><tr><td>Conversion in 2019</td><td>-1.36*<br>(0.59)</td></tr><tr><td>Conversion in 2020</td><td>-2.35***<br>(0.58)</td></tr><tr><td>Conversion in 2021</td><td>-2.17***<br>(0.59)<br>(0.09)</td></tr><tr><td colspan="2"><em>Farmer group in 2022:</em></td></tr><tr><td>Always Organic</td><td>3.11**<br>(1.00)</td></tr><tr><td>Conversion in 2018</td><td>2.60***<br>(0.76)</td></tr><tr><td>Conversion in 2019</td><td>2.47***<br>(0.74)</td></tr><tr><td>Conversion in 2020</td><td>1.37<br>(0.72)</td></tr><tr><td>Conversion in 2021</td><td>0.74<br>(0.73)</td></tr><tr><td>R<sup>2</sup></td><td>0.00</td></tr><tr><td>Adj. R<sup>2</sup></td><td>0.00</td></tr><tr><td>Num. obs.</td><td>540136</td></tr></tbody></table>

Notes: The estimates are obtained from the simple DID model without fixed effects presented in Eq. 7, adapted to the cohort specification in Eq. 3. The coefficient "Farmer after conversion" captures the difference-in-differences estimate. In this table, the benchmark group for comparison with converted farmers consists solely of conventional farmers (column 1). Robust standard errors are reported in parentheses. ***p < 0.001; **p < 0.01; *p < 0.05.

<caption>Table 13: Simple Difference-in-Differences Estimates of Hedgerow Density by Conversion Year</caption>

<footnote>***p < 0.001; **p < 0.01; *p < 0.05</footnote>
## A.5 *Pacte en faveur de la haie* policy: table of hedge planting and maintenance costs

The main instrument of the *Pacte en faveur de la haie* (pact benefiting hedgerows) policy is a partial reimbursement (90%) of the expenses incurred by farmers for hedgerow planting projects. More specifically, to calculate the amount of subsidy they are eligible for, farmers must estimate their project costs based on the planting and maintenance cost scale provided in Appendix 6 of the report DRAAF Grand Est (2024) (an extract of the scale is presented in Table 14). If the funding application is approved, the subsidy will cover 90% of the eligible expenses.

In our simulations (section 8), we consider two cost scenarios for establishing a single-row hedge. The first, referred to as the *mandatory cost*, corresponds to the minimum required investment of 15.82€ per meter, covering essential planting and maintenance operations. The second scenario, termed the *full cost*, includes additional optional expenses such as the installation of a grass strip, fixed fencing, and protection against large wild animals, bringing the total to 25.85€ per meter (Table 14). Since the policy covers 90% of planting and maintenance expenses, we apply a subsidized cost of 14.2€ and 23.3€ per meter, respectively, for the two scenarios.

<table><caption>Table 14: Hedgerow planting cost, extracted from Annex 6 DRAAF Grand Est (2024)</caption><thead><tr><th>Description</th><th>Single-row hedge (€/m)</th><th>Double-row hedge (€/m)</th></tr></thead><tbody><tr><td><strong>Mandatory cost:</strong></td><td></td><td></td></tr><tr><td>Soil preparation before planting and installation of plants</td><td>4.14</td><td>5.51</td></tr><tr><td>Purchase of local plant species</td><td>3.06</td><td>4.07</td></tr><tr><td>Supply and installation of mulch</td><td>4.32</td><td>5.75</td></tr><tr><td>Maintenance over 3 years: Clearing of young plants from the herbaceous layer and replacement of dead plants + pruning in year N+3</td><td>4.30</td><td>5.72</td></tr><tr><td><strong>Total for mandatory cost</strong></td><td><strong>15.82</strong></td><td><strong>21.05</strong></td></tr><tr><td><strong>Optional cost:</strong></td><td></td><td></td></tr><tr><td>Installation of a grass strip 3 m wide (1 row) or 4 m wide (2 rows)</td><td>0.70</td><td>0.93</td></tr><tr><td>Installation of a fixed fence</td><td>4.50</td><td>4.50</td></tr><tr><td>Purchase and installation of protection against large wild animals (Mandatory if high hedge)</td><td>4.83</td><td>6.42</td></tr><tr><td><strong>Total for full cost</strong></td><td><strong>25.85</strong></td><td><strong>32.90</strong></td></tr></tbody></table>