# Land cover changes following biogas development across different farm types: A nationwide study in France

Léa Boros, Lucie Martin, Marco Carozzi, Sabine Houot, Philippe Martin,

Florent Levavasseur

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Léa Boros, Lucie Martin, Marco Carozzi, Sabine Houot, Philippe Martin, et al.. Land cover changes following biogas development across different farm types: A nationwide study in France. Global Change Biology - Bioenergy, 2025, 17 (10), pp.e70073. 10.1111/gcbb.70073. hal-05240634

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Global Change Biology Bioenergy

BIOPRODUCTS FOR A SUSTAINABLE BIOECONOMY

RESEARCH ARTICLE

OPEN ACCESS

# Land Cover Changes Following Biogas Development Across Different Farm Types: A Nationwide Study in France

Léa Boros¹,² ID | Lucie Martin¹ | Marco Carozzi² ID | Sabine Houot¹ | Philippe Martin² ID | Florent Levavasseur¹ ID

¹Université Paris-Saclay, INRAE, AgroParisTech, UMR EcoSys, Palaiseau, France | ²Université Paris-Saclay, INRAE, AgroParisTech, UMR SADAPT, Palaiseau, France

**Correspondence:** Léa Boros (lea.boros@inrae.fr)

**Received:** 10 March 2025 | **Revised:** 10 June 2025 | **Accepted:** 21 July 2025

**Funding:** This work received funding from GRDF (Gaz Réseau Distribution France). It was also funded by the French Research Agency within the CLAND project under the "Investissements d'avenir" program with the reference ANR-16-CONV-0003, and by the metaprogram "Agriculture and forestry in the face of climate change: Adaptation and mitigation" (CLIMAE) of the French National Research Institute for Agriculture, Food, and Environment (INRAE). Partial support was also provided by the Center for Interdisciplinary Studies on Biodiversity, Agroecology, Society, and Climate (C-BASC).

**Keywords:** anaerobic digestion | biogas plant | energy cover crop | energy crop | land cover | land use | sequential crops

## ABSTRACT

Biogas production is increasingly promoted across Europe as a renewable energy source, with growing attention to minimizing land use impacts and preserving food production. In France, biogas plant development has rapidly expanded in recent years, along with the use of energy cover crops. This study examines the national land cover changes following the implementation of biogas plants and explores potential explanatory variables for these changes. Using four key databases (the French Land Parcel Identification System, the SINOE database, the Open Data Reseaux Energies database, and the 2020 French Agricultural Census), we identified farms linked to biogas plants and analyzed their land cover dynamics across various farm characteristics between 2010 and 2021. A typology of land cover changes was developed through clustering techniques. At the national level, our results showed significant land cover changes, including increases in maize and other cereal areas (e.g., rye, triticale, sorghum, among others) and decreases in rapeseed and common wheat. Regional variability emerged which suggests distinct strategies of energy crop introduction. Notably, stronger land cover changes were observed on field crop farms and on those with injection-based biogas plants, which are expected to become the dominant system in the future. Additionally, irrigation availability tended to favor summer energy cover crops over winter energy cover crops. Distinct land cover changes were also observed on organic farms, with a notable increase in "grassland and forage crop" areas (excluding silage maize). As the European biomethane market expands, concerns arise regarding the long-term land cover implications of this growth. While energy cover crops are promoted as a sustainable feedstock for biomethane production, their widespread adoption could still lead to significant land cover changes. This raises important questions about the feasibility of achieving Europe's biomethane production goals while addressing potential land use challenges.

## 1 | Introduction

European Union countries are committed to transitioning toward renewable energy sources to address pressing environmental, economic, and security challenges. The recent Russo-Ukrainian conflict has further motivated the European Commission to implement the REPowerEU plan, launched in May 2022, with aims

to reduce energy consumption, diversify energy supplies, and scale up clean energy (European Commission 2022a). This plan includes the Biomethane Action Plan, which targets an annual biogas or biomethane production of 35 billion cubic meters by 2030, with an emphasis on increasing biomethane injection into the grid rather than producing biogas for cogeneration of electricity and heat (European Commission 2022a). Biogas—and its

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2025 The Author(s). GCB Bioenergy published by John Wiley & Sons Ltd.
purified form, biomethane—is produced through the anaerobic digestion of biomass, which includes waste or residues (e.g., manure, agricultural residues, food waste, and sewage sludge) or energy crops. Energy crops encompass both dedicated energy crops that are main crops grown primarily for energy production and energy cover crops (ECC), cultivated between two main food or feed crops during the summer or winter seasons for energy purposes. The anaerobic digestion process also produces digestate, an organic fertilizer that can be used in agriculture.

The Renewable Energy Directive (RED II), which sets the European framework for renewable energy development, mandates that biogas development be sustainable by prioritizing production from waste and residues over dedicated energy crops, to minimize food or feed competition and avoid issues related to land-use change (European Parliament 2018a). Since 2016, the number of biogas plants using dedicated energy crops in Europe has declined (Cristina et al. 2022), reversing the trend observed from 2009 to 2016, when energy crops like maize dominated due to their high energy yield (Weiland 2003). In particular, Germany, which is the leading biogas producer in Europe, has significantly relied on energy crops, leading to an expansion of maize cultivation at the expense of grasslands (Csikos et al. 2019; Kyere et al. 2021; Lüker-Jans et al. 2017; Yang et al. 2021). This conversion has been linked to several environmental issues, including soil erosion, increased reactive nitrogen loss, and a reduction in soil organic carbon, as well as a rise in agricultural inputs (Arrobas et al. 2016; Graß et al. 2013; Zhang et al. 2021). Furthermore, this land-use shift is known to have negative impacts on farmland biodiversity, particularly among vertebrate species (Gevers et al. 2011; Jerrentrup et al. 2017). The economic impacts are also noteworthy: biogas production from energy crops can drive up silage maize prices and affect local, European, and global agricultural markets, including those for cereals, oilseeds, and livestock products (Bartoli et al. 2016; Britz and Delzeit 2013; Mertens et al. 2016). Given limited opportunities for expanding agricultural land in Europe, increased energy crop production for biogas may also lead to land-use changes outside Europe, as displaced food production could shift to other regions (Britz and Delzeit 2013; Styles et al. 2015).

France experienced a rapid surge in the number of biogas plants, from 440 in 2018 to 1636 in operation in 2023 (Ademe 2024). Of these, 64% use cogeneration systems while 36% employ injection systems (GRDF 2023). With one of the fastest-growing biomethane markets in Europe (Directorate General for Energy 2023), France is expected to become the second-largest biomethane producer after Germany by 2050 (Sulewski et al. 2023). The biogas development began later in France than in Germany, and the use of dedicated energy crops has been restricted to 15% of the annual feedstock gross tonnage in the digester (Ministère de l'Environnement 2016). Consequently, biogas plants initially relied mainly on manure, but there is now a growing shift toward intermediate crops for biogas production, also known as sequential crops or ECC. These crops are more energetic than manure and offer an option for biogas feedstock in regions without manure or waste. ECC are promoted as a promising option to produce biomass for energy while limiting carbon emissions (Malone et al. 2023; Nilsson et al. 2024) and reactive nitrogen losses (Malone et al. 2018, 2023). As a result, they are expected to become a major feedstock source for anaerobic digestion in Europe

by 2050 (Birman et al. 2021; Brémond et al. 2021). ECC allow farmers to produce both food or feed crops and crops for biogas on the same plot in the same year, in contrast to dedicated energy crops. However, maximizing biomass production with two crops per year (main crop and ECC) is not feasible with certain main crops, such as rapeseed or wheat, which require longer growing periods. Consequently, land use changes are expected with ECC, as observed in regions of eastern, central, and western France (Cadiou 2023; Carton et al. 2022; Garambois et al. 2022), but less extensively than changes associated with dedicated energy crops.

Previous work by Levavasseur et al. (2023), using the Land Parcel Identification System (LPIS) and the SINOE database (Ademe 2024), studied land cover changes associated with biogas development in France for plants operational between 2011 and 2018. Their results showed that two-thirds of French farms linked to anaerobic digestion exhibited minimal land cover changes, while one-third showed significant evolution of their land cover. Since 2018, the number of biogas plants has increased by approximately 40% (Ademe 2024), with expansion not only in livestock regions but also in areas traditionally dominated by field crops. This growth includes a rise in injection-based systems and increased production capacities (Garambois et al. 2022). Therefore, assessing recent land cover changes due to this new wave of biogas plants is timely and relevant.

Despite the established correlation between biogas development and land cover changes on farms in France (Levavasseur et al. 2023), significant knowledge gaps persist regarding the specific dynamics of these changes. For instance, little is known about how the land cover of farms with biogas plants evolves depending on their biogas system (injection or cogeneration), farm specialization, presence of an irrigation system, or organic certification. This study aims to address this knowledge gap while updating previous work by incorporating recent French biogas plants, which are predominantly injection system biogas plants. Specifically, we seek to: (1) describe land cover changes on French farms with biogas plants, (2) analyze how these changes vary across different explanatory variables, and (3) establish a typology of land cover changes associated with anaerobic digestion. This work aims to provide valuable insights that may guide sustainable agricultural and energy planning.

We explored several hypotheses on potential land cover changes on farms involved in biogas production. We hypothesize that land cover changes associated with biogas development in France are likely to be more pronounced on farms specialized in field crops, as these farms cannot rely on manure as feedstock. Additionally, we anticipate specific changes on livestock farms, with potential decreases in grassland areas due to reduced grazing time, or conversely, increases in grassland areas harvested as silage to supply anaerobic digestion units (Cadiou 2023; Garambois et al. 2022). Further, we hypothesize that farms equipped with irrigation systems may experience specific land cover shifts, focusing more on crop rotations involving main crops and/or ECC with high water demand such as maize (Amaducci et al. 2016). On organic farms, we expect land cover changes to be less extensive compared to non-organic farms, as integrating ECC into rotations while maintaining yields on main crops has proven to be challenging (Cadiou 2023). Finally, we hypothesize that farms with biogas injection systems are likely to experience greater
land cover changes than those with cogeneration systems, given that injection systems typically require larger volumes of feedstock due to their higher production capacities (Ademe 2024).

## 2 | Materials and Methods

Building on the methodological framework proposed by Levavasseur et al. (2023) to study land cover evolution in French farms associated with biogas plants, we improved the approach by incorporating the Agricultural Census 2020 to explore potential explanatory variables of land cover changes following the development of biogas plants. This study also updates the results and refines the analytical process. The following section provides a brief summary of the previous method, followed by details on the integration of the new database and the analytical methods employed.

### 2.1 | Quantifying Land Cover Changes Before and After Biogas Plant Implementation

To retrieve information on land cover of farms associated with a biogas plant in France, we applied the method proposed in Levavasseur et al. (2023), which was based on the combination of three databases:

1. The SINOE database, provided by the French national agency for the ecological transition (Ademe 2024), identifies the location of biogas plants in France, their start-up year, their biogas utilization method (boiler, injection, or cogeneration systems) and the type of managing entity (farmers, agro-industries, waste treatment plants, or others). This database does not identify the specific farms associated with each biogas plant. It was extracted in August 2024 and included 1743 biogas plants. Biogas plant locations from this database were verified manually thanks to high-resolution aerial photography available on the Géoportail platform (Institut National De L'information Géographique Et Forestière [IGN] 2023). Each point was overlaid on satellite imagery, and if it did not precisely match the visible biogas plant structures (e.g., digesters and tanks), it was manually adjusted to the correct location. When uncertainty remained, the biogas plant's exact address was searched online.

2. The Opendata Réseaux-Energies (ODRE) database (Réseaux-Energies 2024), which provides a list of biogas plants in France equipped with injection systems, their start-up year, their location, and the type of managing entity, allowed the addition of 17 biogas plants not present in the SINOE database. Biogas plant locations from this database were also verified with aerial photography.

3. The French Land Parcel Identification Systems (LPIS) (Agence de services et de paiement [ASP] 2024), which provides annual land cover at the parcel level for French farms that have applied for European subsidies under the Common Agricultural Policy (CAP) (Regulation (EC) No 640/2014, European Commission 2014). The French LPIS also includes farm identifiers. For this study, French LPIS data with identifiers was available for the years 2007–2022, providing 28 groups of crops.

In our study, we managed the 28 crop groups of the LPIS by combining temporary grassland, permanent grassland, and forage crops (except forage maize) into a single category called “Grassland and forage crops”. This grouping was based on feedback from field actors, including governmental agencies, who reported inconsistencies in how these categories were declared, farmers sometimes using them interchangeably. Moreover, a major administrative reclassification of temporary grassland into permanent grassland in the LPIS in 2018 led to an artificial rise in permanent grassland areas. Given these inconsistencies, we decided to merge these categories despite the potential loss of information. This approach allowed for more reliable classifications despite data inconsistencies. The “other cereals” group used in this article follows the existing categorization in the LPIS database. It includes cereal crops that are less widespread than common wheat, barley, or maize, such as rye, triticale, oats, sorghum, and durum wheat.

Farms with inconsistent farm areas across years as well as farms with less than 40 ha were excluded from the analysis; as the latter likely corresponded to fragmented administrative representations of larger farms in the LPIS dataset, making it difficult to capture coherent land cover dynamics at the farm scale.

To link each biogas plant to its associated farm, the locations of biogas plants managed by farmers from SINOE and ODRE databases were merged with the location of farm parcels from the LPIS. A plant was attributed to the farm owning the parcel on which it was located in its start-up year. If no parcel existed that year, the plant was linked to the most recent prior parcel. If no parcel was found, a nearest-neighbor approach was applied, as detailed in Levavasseur et al. (2023). Although this approach restricts the analysis to a single farm per biogas plant, overlooking the potential involvement of multiple farms in the management of a single plant, it remains the only method currently available for linking biogas plants to their associated farms in France.

The land cover of each identified farm was retrieved from the LPIS over the years, enabling a comparison of land cover before and after biogas plant implementation. To expand the study's scope and include more biogas plants, particularly those with recent start-up years, we opted for a 2-year period before and after anaerobic digestion, rather than the 3-year period used by Levavasseur et al. (2023). A sensitivity analysis confirmed that this shorter period resulted in minimal information loss, as land cover changes between the 2- and 3-year periods were highly similar, with only slightly less pronounced changes in the 2-year window (results not shown). This adjustment allowed us to analyze land cover changes for biogas plants established between 2010 and 2021. Finally, to evaluate land cover evolution, the mean crop area was calculated for each group of crop and each farm as a percentage of the total farm area for both the pre- and post-anaerobic digestion periods.

To ensure that observed changes were specific to farms with biogas plants and not due to broader trends, control zones were created based on French homogeneous agricultural regions (“régions agricoles”). These regions, which are smaller than the NUTS3 level (“département”), represent territorial divisions determined by a dominant agricultural vocation. The mean land cover change in each control area was calculated for the same periods as those of the biogas plant. For further details, please refer to Levavasseur et al. (2023).
## 2.2 | Exploring the Influence of Farm Characteristics and Regional Context on Land Cover Changes

### 2.2.1 | Farm Characteristics From the 2020 French Agricultural Census

The agricultural census is a periodic large-scale survey conducted across European countries to collect comprehensive data on agricultural structures, encompassing general information about farms and farmers, their land cover, livestock, labor force, and diversification activities (Regulation (EU) 2018/1091, European Parliament 2018b). The most recent French agricultural census was conducted between October 2020 and May 2021 (Ministère de l'Agriculture (SSP), 2021) and non-anonymized data are made available through the Secure Data Access Center (CASD), a third-party organization responsible for French secure data provision. The land cover changes analyzed in this study were linked to variables from the French Agricultural Census 2020 (AC2020) thanks to the CAP unique farm identifier, which is available in both the LPIS and AC2020 datasets. By doing so, we assumed that the information from the AC2020 was representative of the farms for which we studied the land cover in the LPIS, even for some periods not including 2020.

In order to evaluate the specific dynamics of land cover changes on farms with biogas plants, four variables from the AC2020 were used: type of farming, presence of irrigable surfaces, presence of irrigated surfaces, and presence of organic surfaces. The levels of “type of farming” variable were grouped into three categories: livestock, field crops, and crop-livestock farming. The groupings are detailed in Table S1.

### 2.2.2 | Analyzing Land Cover Evolution in Relation to Variables From French Agricultural Census

To quantify land cover evolution before and after the implementation of anaerobic digestion for all crops simultaneously, we developed the Land Cover Evolution Score (LCES), which measures the extent of land cover change at the farm level over time in %. The LCES is defined for each farm as follows:

$$LCES = \frac{\sum_{i}^{N} | evolution_{i} |}{2}$$

where N represents the total number of crops in the farm, evolution_i represents the difference in the percentage of farm area allocated to crop i after the implementation of anaerobic digestion compared to before, specifically:

$$\text{evolution}_i = \% \text{farm area allocated to crop } i \text{ after anaerobic digestion} - \% \text{farm area allocated to crop } i \text{ before anaerobic digestion}$$

To account for the fact that changes in crop proportions are counted twice (once as a decrease for one crop and once as an increase for another), the total change was divided by two, providing the share of utilized agricultural area (UAA) that effectively underwent a land cover change. This score enabled the

measurement of an overall trend of change at the farm level, which was not possible through crop-by-crop observation alone.

Using R (v 5.3.1), the LCES of farms with biogas plants was compared to that of the control zone using a Wilcoxon test. Differences in LCES across the following variables were also analyzed: type of farming, presence of irrigable surfaces, presence of irrigated surface, organic farming, biogas valorization method, and biogas plant start-up year. For variables with two levels, a Wilcoxon test was applied, while a Kruskal-Wallis test followed by a Dunn test was used for variables with more than two levels. Additionally, a regression analysis was performed to examine the effect of UAA of the farms on LCES. Finally, the same tests were applied to individual crops to investigate the evolution of each crop before and after anaerobic digestion.

### 2.2.3 | Typology of Land Cover Changes at the National Scale and Across Farm Types

To analyze the co-evolution of crops, we performed a k-means classification. Exploratory analyses including all crops showed that focusing on those with significant national-scale variations (Figures S1 and S2) and known to be affected by biogas plant implementation (Cadiou 2023; Carton et al. 2022; Garambois et al. 2022) ensured more robust and interpretable results. These selected crops were barley, grain and silage maize, grassland and forage crops, other cereals, rapeseed, and common wheat (referred to as “wheat” hereafter). Sunflower was excluded because its crop changes were too minor to impact classification. The classification method was selected by comparing silhouette scores across k-means, hierarchical clustering, and density-based spatial clustering of applications with noise, choosing the method with the lowest score. The six-cluster configuration provided the most meaningful interpretation, offering clearer insights into the data, and was close to the recommended number of clusters (5) based on the 30 indices calculated by the NbClust function (from NbClust R package version 3.0.1). Mean crop proportion of farm UAA and standard deviation were computed for each crop and cluster. Each cluster was characterized by its proportion of different farm types, biogas valorization methods, organic farming practices, mean irrigable and irrigated areas, mean UAA, and its geographical distribution within the former French regions (NUTS2 level).

## 3 | Results

### 3.1 | Description of Studied Biogas Plants and Their Associated Farms

Out of the SINOE and ODRE databases, 1257 biogas plants were managed by farmers. 328 were excluded due to start-up years before 2010 or after 2021, 18 for having a UAA of less than 40 ha, 16 due to inconsistencies in reported farm area across years, 35 for not meeting the identification criteria, and 29 due to data inconsistencies in the SINOE, the ODRE, or the RPG databases. This process resulted in a final dataset of 831 biogas plants. Three of these did not have a CAP identifier in the AC2020 database, yielding a final sample of 828 farms with biogas plants at the national scale. Figure 1 presents the geographic distribution of these biogas plants across France.
<figure><img src="image_4.png" /><figcaption>**FIGURE 1** | Number of studied biogas plants and their associated farms per French former regions (NUTS2 level).</figcaption></figure>

Among these 828 farms with biogas plants, most were identified as livestock farms (65% of the farms) and primarily used cogeneration systems to valorize biogas (71%) (Table 1). However, since 2018, we observed a growing number of biogas plants with injection systems, particularly in field crop farms, which accounted for 49% (n = 57) of new injection biogas plants in 2021 (Figure 2a,b). 8% of farms (68) cultivated organic crops, compared to 12% of farms in France in 2020. Of these 68 farms, 72% (n = 49) had all of their UAA dedicated to organic farming, while 10% (n = 7) had between 50% and 99% of their UAA dedicated to organic farming. Of these organic farms equipped with biogas plants, 62% were livestock farms, 22% specialized in field crops, and 88% valorized the biogas via cogeneration.

On average, the studied farms had a UAA of 260 ha, significantly exceeding the average size of cereal farms (96 ha) and dairy farms (106 ha) in France in 2020 (French Agricultural Census, 2021). Among the farms with biogas plants, those practicing crop-livestock farming were slightly larger than those specializing in field crops, which in turn were larger than those focusing on livestock farming. There were no differences in UAA between farms associated with biogas plants using injection systems and those with cogeneration systems (see Table S2 for details).

**3.2 | Analysis of Land Cover Changes of French Farms With Biogas Plants Based on Different Farming Systems**

The LCES of farms with a biogas plant were compared to those in the control zone. Results indicate that land cover changes were more pronounced in farms with biogas plants, with an average of 18% of the farm UAA undergoing crop changes following the

implementation of anaerobic digestion (Figure 3). In contrast, the control zone showed an average LCES of only 6%. At the national scale, land cover changes in farms with biogas plants were primarily driven by increases in grain and silage maize, as well as other cereals (e.g., rye, triticale, and sorghum), with their share of total farm area expanding by +4.1% and +1.0%, respectively, following the implementation of anaerobic digestion (Figure S1). Conversely, wheat and rapeseed areas decreased by -3.0% and -2.5%, respectively. Barley, as well as “grassland and forage crop” areas remained stable, though “grassland and forage” areas were lower in farms with biogas plants compared to those in the control zone. These changes were not observed in the control zone, except for a slight variation in other cereal areas (Figure S1).

We observed that LCES was the highest in field crop farms (22.1%), followed by crop-livestock farms (16.3%), while livestock farms experienced the lowest level of land cover changes (12.0%) (Figure 4a). In terms of biogas valorization methods, farms with injection-based biogas plants showed higher LCES (19.8%) than those with cogeneration systems (12.9%) (Figure 4b).

When analyzing the crop changes contributing to LCES (Figure S2a), we observed consistent trends across types of farms, with the extent of changes being higher on field crop farms and lower on livestock farms. These crop changes followed the same patterns observed across all farms: an increase in maize areas as well as other cereals, and a decrease in wheat and rapeseed areas. Only sunflower had distinct evolution depending on the farm type: its proportion of total farm area significantly increased of +1.1% in field crop farms, while it remained stable in livestock and crop-livestock farms. Notably, the increase in maize areas reached up to +6% of the total farm
<table><caption>**TABLE 1** | Distribution of studied farms across farm type, biogas valorization method, and organic farming, in number of farms and proportion in the total studied population.</caption><thead><tr><th rowspan="2">Type of farming and organic farming</th><th rowspan="2"></th><th colspan="4">Biogas valorization method</th></tr><tr><th>Cogeneration</th><th>Injection</th><th>Boiler</th><th>Total</th></tr></thead><tbody><tr><td rowspan="2">Livestock</td><td>Non-organic</td><td>397</td><td>90</td><td>6</td><td rowspan="2">535 (65%)</td></tr><tr><td>Organic</td><td>38</td><td>3</td><td>1</td></tr><tr><td rowspan="2">Field crops</td><td>Non-organic</td><td>63</td><td>111</td><td>0</td><td rowspan="2">189 (23%)</td></tr><tr><td>Organic</td><td>13</td><td>2</td><td>0</td></tr><tr><td rowspan="2">Crop-livestock</td><td>Non-organic</td><td>65</td><td>27</td><td>1</td><td rowspan="2">104 (12%)</td></tr><tr><td>Organic</td><td>9</td><td>2</td><td>0</td></tr><tr><td colspan="2">Total</td><td>585 (71%)</td><td>235 (28%)</td><td>8 (1%)</td><td>828 (100%)</td></tr></tbody></table>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /><figcaption>**FIGURE 2** | (a) Number of new biogas plants per year from 2010 to 2021, categorized by biogas valorization method and the type of farming of their associated farm. Boiler biogas plants were removed for readability (represents only 1% of studied biogas plants). CG, cogeneration system; IN, injection system. (b) Total number of biogas plants, classified by biogas valorization method and type of farming of their associated farm.</figcaption></figure>

area in field crop farms. No significant changes in “grassland and forage crop” areas before and after anaerobic digestion were observed in any farm type.

A similar pattern was observed when comparing crop changes across biogas valorization methods (Figure S2b). The trends remained consistent between farms with injection-based biogas
<figure><img src="image_7.png" /><figcaption>**FIGURE 3** | Distribution of the Land Cover Evolution Score (LCES) in farms with biogas plants vs. control zone.</figcaption></figure>

plants and those using cogeneration systems, except that crop changes were stronger with injection systems. Sunflower was again the only exception, showing an increase in cultivated area for farms with injection systems, while no significant changes were observed for farms with cogeneration systems.

Organic farms exhibited slightly higher LCES (17.4%) values than non-organic farms (14.6%), although the difference was not statistically significant overall (Figure 4c). However, significant differences were observed when analyzing crops individually (Figure S2c). Crop changes in organic farms were largely characterized by an increase in “grassland and forage crop” proportion (+3.12% of total farm area) and, to a lesser extent, by reductions in wheat and rapeseed proportions (−2.5% and −1.5%, respectively). Notably, maize proportion remained almost unchanged in organic farms with biogas plants (+0.17% of total farm area).

The comparison of LCES between farms with and without irrigation revealed that farms with irrigable areas exhibited slightly higher LCES values (Figure 4f). Similarly, farms with irrigated areas showed higher LCES values than non-irrigated farms (Figure 4g). However, these differences were relatively minor (LCES non-irrigable: 14.4% vs. irrigable: 16.2%; LCES non-irrigated: 14.5% vs. irrigated: 16.2%) and were smaller than those associated with the type of farming or biogas valorization methods.

Finally, the start-up year was not correlated with LCES level (Figure 4d), as well as the UAA of the farms (Figure 4e).

## 3.3 | Typology of Land Cover Changes of French Farms With Biogas Plants

The *k*-means classification identified patterns of simultaneous crop proportion changes across farms with biogas plants, explaining 41% of the variance in land cover changes. This analysis aimed to detect specific trends within clusters of farms, beyond the national trends of increased maize and other cereals and decreased wheat and rapeseed. The classification resulted in six clusters, with the associated changes shown in Figure 5.

Of the 828 studied farms with biogas plants, 44% (n = 367) did not exhibit any land cover changes (Cluster 1) following the start-up of their biogas plants, except a slight increase in “grassland and forage crop” proportions (+1.8% in average). In contrast, Cluster 2, comprising a smaller number of farms (n = 28), showed a significant average increase of farm area proportion dedicated to barley (+19.1%), accompanied by a reduction in wheat proportion (−12.5%) and, to a lesser extent, rapeseed and other cereals. Cluster 3, representing 6.4% of the studied farms (n = 53), was characterized by a rise in the proportion of land allocated to other cereals, with an average increase of +12.4%, mainly compensated by a reduction in wheat proportion. Cluster 4, which included 234 farms (28%), experienced an average increase of +8.0% in maize proportion, while “grassland and forage crop” proportion decreased by an average of −4.5%. Cluster 5, representing 12% of the farms (n = 100), showed more pronounced changes, with maize proportion rising by +14.7%, offset by reductions in wheat and rapeseed proportions (−7.1% and −11.3%, respectively). Finally, Cluster 6, accounting for 5.6% of the farms (n = 46), was marked by an average increase of +16.7% in “grassland and forage crop” proportion, balanced by reductions in wheat, rapeseed, and barley (Figure 5).

For better readability, the following names will be used for the clusters throughout the manuscript:

* Cluster 1: No land cover changes → Cluster 1_NoLCC

* Cluster 2: Barley increased; wheat decreased → Cluster 2_Bi-Wd

* Cluster 3: Other cereals increased; wheat decreased → Cluster 3_OCi-Wd

* Cluster 4: Maize increased; “grassland and forage crops” decreased → Cluster 4_Mi-GFd

* Cluster 5: Maize increased; rapeseed and wheat decreased → Cluster 5_Mi-RWd

* Cluster 6: “Grassland and forage crops” increased; wheat and rapeseed decreased → Cluster 6_GFi-WRd

Almost all farming types, biogas valorization methods, and organic certification status were represented across clusters; though some tendencies emerged (Table 2).

The two clusters with no or relatively little land cover changes (1_NoLCC and 4_Mi-GFd) had the highest proportions of livestock farms (68% and 76%, respectively) and the highest levels of cogeneration-based biogas plants (77% and 74%). While no specific location stood out for the 1_NoLCC cluster, the 4_Mi-GFd cluster was particularly represented in western France, a region known for its high prevalence of livestock farming (Figure 6).

Clusters 2_Bi-Wd, 3_OCi-Wd and 5_Mi-RWd, characterized by stronger changes in cereal proportions but stable “grassland and forage crop” proportions, had the highest proportion of field crops farms (46%, 36%, and 40%, respectively) and injection-based biogas plants (50%, 44%, and 40%). Notably, cluster 2_Bi-Wd contained no crop-livestock farms, and 5_Mi-RWd had the lowest level of livestock farms (48%). Clusters 2_Bi-Wd and 3_OCi-Wd were predominantly represented in central France
<figure><img src="image_8.png" /><figcaption>**FIGURE 4** | Land Cover Evolution Score (LCES) by (a) type of farming, (b) biogas valorization method, (c) organic certification, (d) biogas plant start-up year, (e) total utilized agricultural area, (f) presence of irrigable areas on the farm, and (g) presence of irrigated areas on the farm. Start-up year classes were created to improve readability; however, the same results were observed when the test was performed for each individual start-up year.</figcaption></figure>

regions (Ile-de-France and Centre-Val-de-Loire regions, respectively), while cluster 5_Mi-RWd was widely represented in northern France. Cluster 2_Bi-Wd and 3_OCi-Wd also stood out with the largest irrigable (and irrigated) areas, averaging 96 and 74 ha, respectively.

Finally, the cluster characterized by the strongest increase in “grassland and forage crop” areas (6_GFi-WRd) had the highest proportion of crop-livestock farms (26%) and the highest proportion of farms growing organic crops (21%). This cluster was particularly represented in Eastern France.

No significant differences in UAA were observed between clusters.

# 4 | Discussion

## 4.1 | Influence of Agricultural Practices and Biogas Systems on Land Cover Changes Associated With Biogas Development at the French National Scale

By including new biogas plants implemented in the range 2019–2021, our study confirmed and strengthened the trends of land cover changes associated with biogas development in France, previously observed in Levavasseur et al. (2023). The national average increase in the proportion of maize in UAA of farms with biogas plants rose from +3.4% to +4.1% in this study. Meanwhile, the decreases in the proportions of wheat and rapeseed intensified, shifting from initial reductions of –1.9%
<figure><img src="image_9.png" /><figcaption>**FIGURE 5** | Clusters from the *k*-means classification and the associated crop changes in proportion of farm UAA; *n* represents the number of farms per cluster, and (*x*%) indicates the proportion of farms within the total population of studied farms with biogas plants.</figcaption></figure>

and -1.8% to -3% and -2.5%, respectively. Additionally, a notable increase in the proportion of other cereals was observed. “Grassland and forage crop” proportions remained stable at the national scale. Figure 3 suggested that these land cover changes were specific to the establishment of a biogas plant and were not observed in control zones.

To integrate ECC in rotation, farmers tend to reduce the cultivation of long-cycle crops (Boros et al. 2025; Garambois et al. 2022; Launay et al. 2022; Marty et al. 2022). Thus, the observed decreases in wheat and rapeseed proportions are likely driven by their long growth periods, which hinder the double cropping required for ECC. On the other hand, the increase in maize proportions (as main crop) could be attributed to two main factors: its cultivation as a dedicated energy crop, within regulatory limits (a maximum of 15% of feedstock for biogas plants built after 2017), and its compatibility with winter ECC. Indeed, winter ECC, typically sown in autumn and harvested by mid-April to early May in France, allows for a subsequent summer main crop like grain maize. The rise in other cereal proportions might similarly reflect their use as dedicated energy crops for biogas production, or as a main

crop preceding or following summer or winter ECC (Boros et al. 2025; Garambois et al. 2022). However, the lack of specific data on ECC in the French LPIS limits precise assessment of these factors.

We validated the hypothesis that field crop farms exhibited greater land cover changes compared to other types of farming (Figure 4a; clusters 2_Bi-Wd, 3_OCi-Wd and 5_Mi-RWd in Table 2). This is likely due to their reliance on ECC and dedicated energy crops to supply the digester, given their limited access to manure. While these farms also often rely on agro-industrial waste as feedstock, competition for these resources is intensifying with the growing number of biogas plants. Consequently, some farmers are increasingly turning to ECC cultivation to secure digester feedstock (Cadiou 2023; Marty et al. 2022). This trend could further intensify land cover changes in field crop systems as biogas plant development progresses.

Contrary to what was expected, no specific land cover changes were observed among the livestock farms with biogas plants at the national scale. Their crop evolution trends were similar to
<table><caption>**TABLE 2** | Characteristics of clusters: Proportion of type of farming, biogas valorization method, and organic certification status, average UAA (Utilized Agricultural Area), irrigable and irrigated surfaces.</caption><thead><tr><th rowspan="2">Clusters</th><th colspan="3">Type of farming (number of farms + %)</th><th colspan="3">Biogas utilization (number of farms + %)</th><th colspan="3">Organic areas (no. of farms + %)</th><th rowspan="2">UAA (ha)</th><th rowspan="2">Irrigable areas (ha)</th><th rowspan="2">Irrigated areas (ha)</th></tr><tr><th>Livestock</th><th>Field crop</th><th>Crop-livestock</th><th>Cogene-ration</th><th>Injection</th><th>Boiler</th><th>Yes</th><th>No</th><th>(mean ± SD)</th><th>(mean ± SD)</th><th>(mean ± SD)</th></tr></thead><tbody><tr><td>1_No-LCC</td><td>231 (68%)</td><td>60 (18%)</td><td>48 (14%)</td><td>261 (77%)</td><td>72 (21%)</td><td>6 (2%)</td><td>31 (9%)</td><td>308 (91%)</td><td>258 ± 153</td><td>28 ± 71</td><td>14 ± 39</td></tr><tr><td>2_Bi-Wd</td><td>14 (54%)</td><td>12 (46%)</td><td>—</td><td>13 (50%)</td><td>13 (50%)</td><td>—</td><td>2 (8%)</td><td>24 (92%)</td><td>244 ± 139</td><td>96 ± 144</td><td>48 ± 78</td></tr><tr><td>3_OCi-Wd</td><td>26 (52%)</td><td>18 (36%)</td><td>6 (12%)</td><td>28 (56%)</td><td>22 (44%)</td><td>—</td><td>6 (12%)</td><td>44 (88%)</td><td>273 ± 168</td><td>74 ± 158</td><td>35 ± 83</td></tr><tr><td>4_Mi-GFd</td><td>164 (76%)</td><td>35 (16%)</td><td>18 (8%)</td><td>160 (74%)</td><td>55 (25%)</td><td>2 (1%)</td><td>13 (6%)</td><td>204 (94%)</td><td>240 ± 134</td><td>26 ± 85</td><td>19 ± 77</td></tr><tr><td>5_Mi-RWd</td><td>43 (48%)</td><td>36 (40%)</td><td>11 (12%)</td><td>51 (57%)</td><td>39 (43%)</td><td>—</td><td>3 (3%)</td><td>87 (97%)</td><td>293 ± 174</td><td>17 ± 52</td><td>10 ± 32</td></tr><tr><td>6_GFi-WRd</td><td>22 (52%)</td><td>9 (22%)</td><td>11 (26%)</td><td>29 (69%)</td><td>13 (31%)</td><td>—</td><td>9 (21%)</td><td>33 (79%)</td><td>221 ± 101</td><td>24 ± 45</td><td>12 ± 26</td></tr></tbody></table>

Note: The value with the highest share or area per column is underlined.

those of field crop and crop-livestock farms but were less pronounced (Figure S2a). Furthermore, no significant changes in “grassland and forage crop” proportion were detected although this result may partly reflect classification limitations, as temporary, permanent grasslands, and forage crops were grouped to avoid inconsistencies in declarations of the LPIS data. However, local disparities in “grassland and forage crop” areas were observed and will be explored in Section 4.2.

The hypothesis that land cover changes were more pronounced in farms with injection-system biogas plants was validated through the LCES (Figure 4b), crop-by-crop comparisons (Figure S2b), and cluster analysis (Figure 5 and Table 2). This may result from the higher biogas production levels typically associated with injection plants in France compared to cogeneration systems (Ademe 2024), potentially leading to increased ECC and dedicated energy crop productions that have high energetic value. Additionally, field crop farms, characterized by the highest land cover changes, were more prevalent in the injection group (Figure 2b), thereby increasing the average land cover changes observed in this group. However, even within each farming type, land cover changes were consistently higher for injection systems compared to cogeneration systems (data not shown). This supports the hypotheses that injection systems might be linked to amplified land cover changes following biogas plant implementation. It is worth noting that injection-system biogas plants are currently the type most rapidly expanding, given their higher energy efficiency compared to cogeneration systems (Wu et al. 2016). These systems are strongly promoted by the European Union, including France, particularly in response to the energy challenges exacerbated by the Russo-Ukrainian conflict (European Commission 2022b). Consequently, if the sector continues to develop along current trends, a sustained or even increased level of land cover changes associated with biogas expansion can be anticipated.

Currently, literature on the environmental, social, and economic effects of the observed land cover changes is limited. Most studies have focused on grassland conversion and maize expansion (Arrobas et al. 2016; Bartoli et al. 2016; Gevers et al. 2011), with less attention given to shifts in other cereal and oilseed crop areas. However, such changes are likely to affect the cereal market and potentially disrupt other agricultural sectors, as noted by Britz and Delzeit (2013) in their analysis of the German biogas sector, which relies more heavily on energy crops. In France, the impact may be more moderate, as 44% of farms showed almost no crop changes. For those that did experience changes, these involved diverse crops or diverse strategies (e.g., cluster 4_Mi-GFd vs. 6_GFi-WRd), contrasting with neighboring countries where land cover changes often translated into a uniform shift toward increased maize cultivation and grassland reduction. From an economic and environmental perspective, such diversification of strategies could contribute to risk mitigation by reducing vulnerability to market fluctuations and environmental pressures (Renard and Tilman 2019). It could limit the potential magnitude of impacts on specific crop markets or biodiversity by avoiding over-reliance on a single crop or land use. This does not mean impacts would be absent, but rather that risks would spread across different crops and systems, potentially increasing resilience. Further studies on the effects of these crop shifts on the economy and the environment are needed.
<figure><img src="image_10.png" /><figcaption>**FIGURE 6** | Geographical distribution of the *k*-means classification clusters across former French regions (NUTS2 level).</figcaption></figure>

Contrary to initial hypotheses, overall land cover changes observed in organic farms with biogas plants were slightly more pronounced than those in non-organic farms, although this difference was not statistically significant, suggesting unexpected dynamics (Figure 4c). However, when analyzing crop specific changes of organic farms (Figure S2c), cereal proportion within total farm area showed less variation compared to the non-organic group, the changes being primarily driven by an increase in the proportion of “grassland and forage crops”. This trend could be related to factors associated with biogas plant development, such as the stabilization of livestock farming enabled by biogas revenues or the expansion of grassland areas to harvest silage for feeding the digester (Auburger et al. 2017; Cadiou 2023; Marty et al. 2022). Alternatively, these changes might result from broader factors unrelated to the biogas plant, such as the transition to organic farming. Investigating the timing of organic conversion could provide further insight into the causality of observed changes and would be a valuable direction for future studies. Further research, including on-farm interviews, would also help to better understand the dynamics specific to organic farms with biogas plants. Additionally, Cadiou (2023) highlighted that organic farmers may face challenges integrating ECC into their rotations, often relying on conventional farms to supply feedstock for their digesters. It is worth noting that organic biogas farmers are a minority in our sample, with only 68 individuals, limiting their overall influence on the observed trends.

A slight increase in LCES was observed for farms with irrigable and irrigated areas, although this trend remained marginal. However, crop-level analysis revealed that the increase in maize proportion was less pronounced for farms with irrigation, contradicting our initial hypothesis (Figure S2d). This might be partly explained by the fact that irrigated farms already had a higher baseline proportion of maize before biogas development

compared to non-irrigated farms. As a result, the relative increase in maize proportion was smaller but eventually converged to similar levels across both farm types. Notably, the irrigated farms in our sample were predominantly located in southern France (data not shown), particularly in the southwest region, where maize cultivation is already well established, accounting for the higher baseline maize proportion in farms with irrigation.

Interestingly, farms with irrigation exhibited a more pronounced increase in the proportion of total farm area dedicated to other cereals (Figure S2d). These cereals generally do not require irrigation but can serve as main crops preceding a summer ECC, such as maize or sorghum, which may benefit from irrigation. Therefore, the hypothesis that irrigation availability promotes a higher proportion of summer crops, either as main crops prior to ECC or as ECC, seems partly validated at this stage; however, it would require confirmation through on-farm interviews in regions with high irrigation prevalence. Additionally, ECC declarations from farmers would also provide valuable insights into the dynamics of those land cover changes and support more robust conclusions. However, such data are currently unavailable in France.

A limitation of our approach was that we were only able to associate one farm per biogas plant, although several farms are usually involved. As a result, not all French farms engaged in biogas production were captured. An alternative approach was to use the “biogas producer” variable available in the AC2020 dataset for each French farm. However, concerns arose regarding the quality of this variable, and it did not specify the start-up year of biogas production, preventing land cover comparisons before and after biogas plant implementation. Consequently, the current method remains the best available option to date, ensuring that at least one farm is identified for each biogas plant. Improving information in future Agricultural Censuses or other
agricultural surveys would help capture all farms involved in
biogas production projects. Further details on the limitations of
the method used to associate biogas plants with farms are avail-
able in Levavasseur et al. (2023).

When analyzing French LPIS data, temporary grassland, per-
manent grassland, and forage crops were grouped to avoid cap-
turing changes that merely reflect inconsistent declarations or
administrative changes (e.g., forage plants declared as tempo-
rary grassland 1 year and as forage plants the next, as well as
the major 2018 administrative changes of temporary grassland
to permanent grassland). While this grouping inevitably results
in the loss of valuable information, particularly regarding the
conversion or creation of permanent grasslands, it remains the
most appropriate solution given the limitations of the data.

## 4.2 | Diverse Strategies of Land Cover Changes Across Regions and Agricultural and Biogas Systems

The *k*-means classification of land cover evolution revealed that all farming types and biogas valorization methods were represented in each cluster; although some were more prevalent in particular clusters.

Notably, clusters with high levels of crop changes (Cluster 2_Bi-Wd, 3_OCi-Wd and 5_Mi-RWd) were those with the highest proportion of field crop farms. Different strategies emerged within these clusters. The increase in barley and decrease in wheat proportions of Cluster 2_Bi-Wd could indicate a strategy to incorporate summer ECC into the rotation, following winter barley. Cluster 3_OCi-Wd might similarly reflect the introduction of summer ECC after a cereal crop. However, other cereals (e.g., triticale or rye) were preferred over barley. This preference may be linked to regional factors, particularly the typically lower cereal crop yield potential in areas where triticale or rye are grown (Agreste Conjoncture 2023; FranceAgriMer and Arvalis 2024). This regional variation could explain why Cluster 3_OCi-Wd is more prevalent in central France, while Cluster 2_Bi-Wd is more common in the center-north France (Ile-de-France region), where yield potentials are higher. Finally, Cluster 5_Mi-RWd was characterized by an increase in maize proportions, at the expense of wheat and rapeseed, suggesting the introduction of winter ECC before maize as the main crop. The strategy to introduce winter ECC rather than summer ECC seemed more widespread, as Cluster 5_Mi-RWd represented 12.1% of the studied farms, compared to 3.4% for Cluster 2_Bi-Wd and 6.4% for Cluster 3_OCi-Wd. These strategies to incorporate ECC in rotations were consistent with the actual agricultural practices observed on French farms with biogas plants (Boros et al. 2025; Carton et al. 2022; Garambois et al. 2022; Marty et al. 2022). Notably, Cluster 5_Mi-RWd included a large majority of recently established biogas plants, with 83% of farms with biogas plants established between 2018 and 2021, compared to 54% for Cluster 2_Bi-Wd and 74% for Cluster 3_OCi-Wd. This may reflect a strategy of new biogas plants to secure biogas feedstock supply, as winter ECC generally offer more consistent yields than summer ECC, which are more exposed to climatic variability.

Clusters 2_Bi-Wd and 3_OCi-Wd, in contrast to 5_Mi-RWd, were
associated with significantly larger irrigable areas, averaging

96 ha and 74 ha, respectively, compared to just 17 ha for Cluster 5_Mi-RWd. This disparity likely explains the preference for summer ECC strategies in Clusters 2_Bi-Wd and 3_OCi-Wd, where irrigation mitigates the risk of poor yields, while Cluster 5_Mi-RWd favors winter ECC, which are less dependent on irrigation (Boros et al. 2025; Garambois et al. 2022). It is worth noting that AC2020 variables, such as the presence of irrigation, reflect conditions specific to the year 2020 and may not fully capture the situation of farms with biogas plants established several years earlier. The longer the time gap between the commissioning date and 2020, the more likely irrigation practices may have evolved. To account for this, we considered 2018 as a reasonable threshold beyond which differences between actual practices at biogas plant start-up and those observed in 2020 may be more likely. However, only 34% of biogas farms in our sample had a start-up year before 2018, and only 27% of these are classified as “with irrigation system”, suggesting a limited impact on the overall results.

Cluster 6_GFi-WRd highlighted significant increases in “grasslands and forage crops” at the expense of cereals, particularly wheat, rapeseed, and, to a lesser extent, barley. This cluster was predominantly represented in eastern France, where Cadiou (2023) documented similar land cover changes during surveys conducted in the Grand Est region. Two key approaches emerged from Cadiou’s work. The first involved growing a winter ECC followed by temporary grasslands, to mitigate the risks associated with low-yielding summer crops following winter ECC. The second approach consisted of cultivating temporary grasslands, such as ryegrass, harvested directly for biogas production. However, the necessary grouping of permanent grassland, temporary grassland, and forage crop due to inconsistencies in LPIS data prevents a more detailed analysis of these strategies, which would in any case require dedicated on-farm investigations. The predominance of Cluster 6_GFi-WRd in eastern France also points to potential regional factors influencing these strategies, which remain to be fully understood.

Cluster 4_Mi-GFd, primarily composed of livestock farms, showed an increase in maize proportions alongside a decrease in grassland and forage crops. This pattern is close to land cover strategies observed in Germany, where grasslands have been reduced in favor of maize cultivation (Csikos et al. 2019; Kyere et al. 2021; Lüker-Jans et al. 2017). However, these results would benefit from further investigation without the grouping of temporary grasslands, permanent grasslands, and forage crops, which we applied in this study due to inconsistencies in LPIS declarations. Such disaggregation would allow for a more detailed analysis of permanent grassland trends. Nevertheless, this trend may indicate a strategy to produce maize either as a dedicated energy crop or as a crop following winter ECC. Notably, this cluster is predominantly located in western France (particularly in Brittany, Normandy, and Pays de la Loire), which aligns with qualitative feedback from the local Water Agency (personal communication) that reported an increase in declarations of expanding maize areas on farms equipped with biogas units in Western France regions. The limited presence of this cluster in Eastern France, known for its significant livestock production, suggests that regional factors, beyond the type of farming, play a role in land cover dynamics. Further investigation is needed to identify these local determinants.
Finally, Cluster 1_NoLCC, which accounted for 44% of farms with no or limited crop changes, was represented across all regions of France. Notably, this cluster had the lowest proportion of injection-based biogas plants. This raises questions about the future impact on land cover changes of the development of biomethane, as discussed in Section 4.1, given that the majority of new biogas plants are now injection-based.

## 4.3 | Comparison of Land Cover Changes Following Biogas Development in European Countries

In contrast with the situation observed in Germany a decade ago (Csikos et al. 2019; Kyere et al. 2021; Lüker-Jans et al. 2017), France did not experience widespread grassland conversion alongside an increase in maize areas at a national scale. Avoiding replication of the German model was a key objective set by French policymakers from the outset of biogas development (Cadiou 2023), which began later in France, to mitigate environmental impacts such as biodiversity loss, soil erosion, or increased reactive nitrogen loss (Arrobas et al. 2016; Gevers et al. 2011; Graß et al. 2013; Jerrentrup et al. 2017). However, a similar trend was observed in Cluster 4_Mi-GFd (28% of studied farms), but at a smaller level than in Germany, where silage maize acreage locally increased by 20% on average between 2003 and 2010 (Csikos et al. 2019). In contrast to the situation in Germany, a diversity of land cover change strategies to incorporate biogas crops was observed in France. This indicates that the development of biogas production in France should not lead to a homogenization of farming practices or landscapes. However, given the strong regional representation of certain clusters (e.g., cluster 2_Bi_Wd, 3_OCi_Wd, or 4_Mi_GFd), some homogenization of practices may nevertheless occur at regional scales.

Only a limited number of studies quantifying land cover evolution following biogas development have been published, most of which focused on the German case (Csikos et al. 2019; Kyere et al. 2021; Lüker-Jans et al. 2017; Vergara and Lakes 2019; Yang et al. 2021). Replicating this study in other countries with well-established biogas sectors, such as Denmark, the Netherlands, or Italy, would offer valuable insights into the effects of various public policies on land use changes following the establishment of biogas plants, assuming that comparable LPIS data are available, which can vary across European countries (Leonhardt et al. 2024). Notably, there is a lack of scientific studies examining the implementation of energy cover crops, also known as sequential crops, on a national scale in Europe, despite these practices being central to the future development of biogas production (Birman et al. 2021; Brémond et al. 2021). The approach developed in this study could also be used to assess land cover changes driven by other localized projects such as renewable energy development, irrigation systems, or the construction of other on-farm infrastructure for which data are available.

Future studies evaluating the environmental, economic, and social impacts of anaerobic digestion should consider the variety of land cover changes observed in this study, an aspect often overlooked in the literature, where ECC are either assumed to have no impact or their effects on land cover changes are not considered in evaluations (Esnouf et al. 2021; Malet et al. 2023; Nilsson

et al. 2024; Styles et al. 2015). However, our findings indicate that the development of biogas in France does indeed influence land cover changes. This raises concerns similar to those associated with indirect land use changes caused by dedicated energy crops (Vergara and Lakes 2019). In particular, the crops no longer produced within France due to ECC introduction could need to be grown elsewhere. If this occurs outside the EU, where environmental safeguards may be weaker, it could amplify the global environmental costs of anaerobic digestion, potentially contributing to deforestation (Britz and Delzeit 2013; Styles et al. 2015).

# 5 | Conclusion

This study examined land cover changes associated with biogas plant development in France, integrating recent installations characterized by a higher proportion of injection-based biogas plants and field crop farms. Our findings confirmed that French biogas farms experienced distinct land cover changes not observed in non-biogas farms. While over 40% of the studied farms showed no significant land cover changes, the remaining farms exhibited trends of changes consistent with previous studies but with greater intensity, suggesting an ongoing intensification of land cover changes linked to anaerobic digestion.

These changes were consistent across all farm types and biogas valorization methods, though they were particularly pronounced in field crop farms and those associated with injection-based biogas plants. Regional disparities also emerged, driven more by local dynamics than by farm or biogas plant characteristics, highlighting the need for further territorial investigations.

Notably, maize expansion and grassland conversion, which were dominant strategies in earlier European biogas development, were not the only patterns observed in France. This suggests that French national limitations on dedicated energy crops have been effective, favoring a diversification of strategies that may help mitigate land cover impacts of anaerobic digestion.

Given the rapid expansion of the biomethane market, driven by European policies promoting its development, the increasing reliance on injection-based plants raises concerns about future land cover impacts. Although ECC are promoted as a sustainable feedstock for development across European countries, their widespread adoption, as seen in France, may still result in land cover changes, raising questions about the feasibility of achieving Europe's goal to expand biomethane production while limiting land use relative issues. Future research should further explore the sustainability of biogas and biomethane development taking into account the observed land cover changes.

## Author Contributions

**Léa Boros:** data curation, formal analysis, methodology, resources, visualization, writing – original draft, writing – review and editing.

**Lucie Martin:** data curation, formal analysis, methodology, writing – review and editing. **Marco Carozzi:** supervision, writing – review and editing. **Sabine Houot:** supervision, writing – review and editing.

**Philippe Martin:** supervision, writing – review and editing. **Florent**

**Levavasseur:** conceptualization, funding acquisition, methodology, project administration, supervision, writing – review and editing.
## Acknowledgments

This work received funding from GRDF (Gaz Réseau Distribution France). It was also funded by the French Research Agency within the CLAND project under the "Investissements d'avenir" program with the reference ANR-16-CONV-0003, and by the metaprogram "Agriculture and forestry in the face of climate change: adaptation and mitigation" (CLIMAE) of the French National Research Institute for Agriculture, Food and Environment (INRAE). Partial support was also provided by the Center for Interdisciplinary Studies on Biodiversity, Agroecology, Society, and Climate (C-BASC). The authors are grateful to all funders for their support to this research.

## Conflicts of Interest

The authors declare no conflicts of interest.

## Data Availability Statement

Access to some confidential data (French LPIS database and Agricultural Census 2020), on which this work is based has been made possible within a secure environment offered by CASD—Centre d'accès sécurisé aux données (Ref. https://doi.org/10.34724/CASD). The SINOE database is openly accessible at: https://www.sinoe.org/filtres/index/thematique#table-annuaire. The ODRE database can also be accessed openly at: https://opendata.reseaux-energies.fr/explore/dataset/point s-dinjection-de-biomethane-en-france/information/?disjunctive.site&disjunctive.nom_epci&disjunctive.departement&disjunctive.region&disjunctive.type_de_reseau&disjunctive.grx_demandeur&disjunctive.region_du_pitdpitp&disjunctive.departement_pitdpitp.

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## Supporting Information

Additional supporting information can be found online in the Supporting Information section. **Appendix S1:** gcbb70073-sup-0001-AppendixS1.docx.