Organic Farming | 2016 | Volume 2 | Issue 1 | Pages 23–27
ISSN: 2297–6485
Research Article
Can the Adoption of Organic Farming Be Predicted by
Biogeographic Factors? A French Case Study
Marco Pautasso
*, Anja Vieweger
and A. M
arcia Barbosa
Animal and Plant Health Unit, European Food Safety Authority (EFSA), Parma, Italy
Organic Research Centre, Elm Farm, Hamstead Marshall, Newbury, UK
Centro de Investiga
ao em Biodiversidade e Recursos Gen
eticos (CIBIO), InBIO Research Network in Biodiversity and
Evolutionary Biology, University of
Evora, Portugal
* Corresponding author: E-Mail: mar[email protected]; Tel.: +39 521036775
The positions and opinions presented in this article are those of the authors alone and are not intended to represent the
views or scientific works of EFSA.
Submitted: 13 January 2016 | In revised form: 21 April 2016 | Accepted: 9 June 2016 |
Published: 29 June 2016
Organic farming adoption is on the rise in many countries, due to the increased awareness of
farmers, citizens, governments and other stakeholders of its more sustainable nature. Various studies
have investigated the socio-economic drivers (e.g., consumer demand, support measures, agricultural
policies) of organic farming adoption, but less attention has been paid to whether biogeographic factors
could also be associated with variation in rates of organically managed farms in certain regions within
countries. We investigate whether biogeographic factors are associated with variation in the proportion of
land under organic farming in French departments. The proportion of land under organic farming increased
with decreasing latitude and increasing department area. Non-significant factors were number of plant
taxa, proportion of Natura 2000 protected areas, connectivity, longitude, altitude and department population.
These results were robust to controlling for spatial autocorrelation. Larger and southern French departments
tend to have a greater adoption of organic farming, possibly because of the more extensive nature of
agriculture in such regions. Biogeographic factors have been relatively neglected in investigations of the
drivers of organic farming adoption, but may have an important explanatory value.
biodiversity; France, human population; land sharing; macroecology; organic farming; plant
species richness; protected areas; spatial autocorrelation; sustainable development
1. Introduction
Organic farming is on the rise globally [
]. Between 2001
and 2011, agricultural land under organic management
increased from nearly 16 to over 37 million hectares world-
wide [
]. This trend is also reflected in the market for organ-
ically grown produce; during the same decade, the global
organic market grew by 170%, with sales reaching nearly
63 billion US$ in 2011 [
]. In 2011, France (3.8 billion Eu-
ros) was the second largest market for organic products in
Europe (21.5 billion Euros) [4].
Organic farming aims to reconnect agriculture with na-
2016 by the authors; licensee Librello, Switzerland. This open access article was published
under a Creative Commons Attribution License (
ture and biodiversity, making use of natural systems and
cycles and reducing external inputs (for example, growing
a wider variety of crops and using natural ways to reduce
pest populations, e.g. rotations). Industrial agriculture is
currently one of the greatest threats to biodiversity [
Several studies have shown that organic farming benefits
biodiversity, because of its less intensive cultivation prac-
tices [8–14] (see also [15]).
So far, studies investigating factors driving organic farm-
ing adoption have focused on socio-economic factors (e.g.,
agricultural policies, consumer demand, support measures
and networks) [
]. However, given the connection of
organic farming with nature, it could also be expected that
the presence of organic farming co-varies with regional vari-
ation in biodiversity, as was shown at the landscape level
]. Given that large-scale variation in biodiversity is in turn
associated with biogeographic factors such as latitude, area
and human population [
], it is reasonable to expect
that also regional patterns in organic farming adoption will
tend to be associated with such biogeographic factors.
This study aims to test this hypothesis by using data
on organic farming adoption from French departments, to-
gether with some key biogeographic factors. Our main
question was: is organic farming more likely to be adopted
in regions with an already higher presence of biodiversity?
More generally, can biogeographic factors help predict pat-
terns in organic farming adoption across regions?
2. Material and Methods
Data on the proportion of agricultural land under or-
ganic farming (2008) for the 96 French metropolitan de-
partments (with exception of Paris: data not available)
were obtained from the website for sustainable develop-
ment of the French government (http://www.statistiques. From the same website,
data for each French department were obtained on land-
scape connectivity (average size of natural habitats; 2006),
the proportion of Natura 2000 protected areas (2009), the
total area and human population (2011). Altitude was
obtained from [
] as a raster map at ca. 1 km
tion, and averaged at French departments using the zonal
statistics plugin of QGIS 2.6 [
] and an administrative
map downloaded from the EDIT Geoplatform [
]. Natura
2000 data are indicators of recent efforts to achieve na-
ture protection and may not be representative of historic
or overall actions to protect nature, as the Natura 2000
reserve selection focused on regions with low presence
of already available protection (i.e. National and Regional
parks). Data on the number of vascular plant taxa (including
subspecies) recorded for each department were obtained
in 2012 from the Tela Botanica website (http://www.tela- Given the rel-
atively low number of data points, we avoided including
an excessive number of explanatory variables; further bio-
geographic factors could be considered in future analyses,
including distance from the sea and road density.
Multivariate models were run in Spatial Analysis for
Macroecology (SAM) [
]. Given that spatial autocorre-
lation can reduce the effective degrees of freedom, thus
leading to potentially misleading P-values [
], the analysis
was performed both without (Linear Regression Model) and
with controlling (Spatial Autoregression, Generalized Least
Squares, with a Gaussian Model for the residual spatial
component) for spatial autocorrelation [
]. All variables
(apart from latitude and longitude) were log-transformed
prior to analysis so as to better approach a normal distri-
bution. Non-significant variables (at p
0.05) were kept
in the models to demonstrate that they were not significant
predictors. The significance of the significant factors was
robust against model reduction. We did not observe strong
collinearity (correlation coefficient
0.70) among the ex-
planatory variables, with the only exception of connectivity
and plant biodiversity (correlation coefficient = 0.75).
3. Results
Without controlling for spatial autocorrelation, the propor-
tion of organic farming in French departments increased
significantly with decreasing latitude and increasing depart-
ment area. There was no significant association with plant
biodiversity, proportion of protected areas, connectivity, lon-
gitude, altitude and human population size (Table 1).
All these results were confirmed when controlling for spa-
tial autocorrelation, although with slightly different P-values
and parameter estimates (Table 2). On its own, latitude ex-
plains about 40% of the variation among French departments
in their proportion of organic farming (Figure 1). Department
area on its own explains about 17% of the variation in pro-
portion of organic farming, but this is largely due to a few
data points, i.e. some small departments in the Ile-de-France
area with very low proportion of organic farming.
Table 1.
Results of a General Linear Model for the proportion of agricultural land under organic farming in French
Departments (2008) as a function of plant biodiversity, landscape connectivity, proportion of Natura 2000 protected areas,
latitude, longitude, altitude, human population size and department area. The number of data points is 95, the adjusted
of the model 0.50, and the intercept 1.457 (s.e. = 2.074).
N of plant taxa Landscape connectivity % Natura 2000 Latitude Longitude Altitude Human population Area
parameter estimate 0.264 0.047 0.113 -0.084 0.003 0.038 0.056 0.327
s.e. 0.486 0.101 0.09 0.024 0.017 0.172 0.132 0.139
P-value 0.59 0.64 0.21 <0.001 0.87 0.82 0.67 0.02
Table 2.
Results of a Generalized Least Squares model controlling for spatial autocorrelation, for the proportion of agricul-
tural land under organic farming in French Departments (2008) as a function of plant biodiversity, landscape connectivity,
proportion of Natura 2000 protected areas, latitude, longitude, altitude, human population size and department area. The
number of data points is 95, the Akaike Criterion Indicator of the model 59.9, and the intercept 1.457 (s.e. = 1.972).
N of plant taxa Landscape connectivity % Natura 2000 Latitude Longitude Altitude Human population Area (km
Parameter estimate 0.264 0.047 0.113 -0.084 0.003 0.038 0.056 0.327
s.e. 0.462 0.096 0.086 0.023 0.016 0.164 0.125 0.133
P-value 0.57 0.63 0.19 <0.001 0.87 0.81 0.65 0.02
4. Discussion
Several studies have shown the essential role of agro-
ecological approaches, and particularly organic agriculture,
for sustainable development [
]. Ecological intensifi-
cation enables an improvement of productivity while at the
same time reducing adverse effects on the environment
]. Not only the adoption of organic farming practices,
but also research on organic farming has expanded consid-
erably over the last years [
]. This study provides
evidence that biogeographic factors can be associated with
patterns in organic farming adoption across regions.
There are three main results of this analysis. First, there
are no substantial differences between models of the pro-
portion of organic farming in French departments (i) taking
spatial autocorrelation into account, and (ii) not taking it
into account. The results of models taking into account
spatial correlation are more conservative and should be
trusted more than those without taking it into account, but
in this case there are only slight differences in parameter
estimates and P-values.
Second, this result does not imply that there is no spatial
autocorrelation in the examined variables. For example, the
investigated response variable (the proportion of cultivated
land under organic farming) was significantly spatially auto-
correlated at short distances, as shown by an analysis of
Moran’s I (Figure 2). This result is in agreement with previ-
ous reports of spatial aggregation and neighbouring effects
in the adoption of organic farming within countries [42–45].
To some extent, such spatial aggregation might be due to
the underlying spatial autocorrelation of biogeographic fac-
tors associated with variation in organic farming adoption.
However, there is also an important role of neighbouring
effects of e.g. social networks and farmer communities in
explaining the spatial aggregation of organic farming.
A third result of this study (which holds when controlling for
spatial autocorrelation) is the latitudinal gradient from North
to South in French adoption of organic farming. Farmers in
the South of France might have switched more easily to or-
ganic cultivation because of the larger variety of crops they
can cultivate in their climatic and environmental settings. In
addition, it could be easier to switch to organic cultivation in
viticulture (which is typical in Southern France) than for other
crops. Moreover, due to a mix of climatic, edaphic, historical
and cultural reasons, Southern French departments tend to be
located in regions of less intensive agriculture, thus facilitating
the adoption of less intensive agricultural practices [46]. This
finding is in agreement with previous analyses in England,
Germany, the USA and Sweden, which found that organic
farming was more likely to occur in marginal areas, where
the loss of production due to organic conversion is relatively
small [
] and in regions with more heterogeneous land-
scapes [
], thus likely to harbour greater plant biodiversity
]. However, we did not observe a significant association
of organic farming adoption with plant biodiversity. It is also
possible that the observed latitudinal gradient in organic farm-
ing adoption correlates with other socio-economic factors (e.g.
personal beliefs, levels of political and financial support, public
perceptions, type of crops) that were not considered here.
40 42 44 46 48 50 52
% organic agriculture
Latitude (°)
Figure 1.
Latitudinal gradient of the proportion of agri-
cultural land under organic farming (logarithmically trans-
formed) in French departments (2008; n = 95,
0.125x + 6.079, R
= 0.40, p < 0.001).
Figure 2.
Moran’s I for the proportion of agricultural land un-
der organic farming (logarithmically transformed) in French
departments (2008).
Interestingly, although there is generally little variation
among French departments in area, this was a significant
factor in our analysis, due to the few very small departments
(mainly located in the Paris area) having surprisingly low
organic farming adoption rates.
Further research should investigate whether biogeo-
graphic factors are still significant determinants of organic
farming adoption when including a large suite of socio-
economic explanatory variables. Econometric and socio-
economic models of organic farming adoption may benefit
from including data on large-scale biogeographic factors. It
would also be interesting to use a finer spatial resolution of the
data used here, to test for any scale-dependence in the rela-
tive importance of biogeographic and socio-economic factors
as explanatory variables for organic farming adoption rates.
5. Conclusions
Most research on regional patterns of organic farming
has focused on socio-economic and cultural factors,
from policy support to agglomeration effects and from
the philosophy of farmers to the development of mar-
kets for organic produce and organic seed [40,5159].
Whilst these factors are undoubtedly important, this
study builds on evidence obtained at the landscape
level on the role of environmental factors in shaping
organic farming adoption [
] and suggests that bio-
geographic variables may play a contributing role in
how widespread organic farming is becoming across
entire countries.
Many thanks to V. Chable, O. Holdenrieder, D. McKey
and S. Vos for insights and discussions, and to T.
oring, T. Matoni and anonymous reviewers for helpful
comments on a previous draft. AMB is supported by
ao para a Ci
encia e a Tecnologia through ‘FCT
Investigator contract IF/00266/2013 and exploratory
project CP1168/CT0001.
References and Notes
[1] Granatstein D, Kirby E, Willer H, et al. Organic horticulture expands
globally. Chronica Horticulturae. 2010;50(4):31–38.
Paull J. The uptake of organic agriculture: A decade of world-
wide development. Journal of Social and Development Sciences.
Willer H, Lernoud J, Home R. The world of organic agriculture 2013:
Summary. In: Willer H, Lernoud J, Kilcher L, editors. The World of Or-
ganic Agriculture. Statistics and Emerging Trends. Frick, Switzerland:
Research Institute of Organic Agriculture (FiBL) and International Fed-
eration of Organic Agriculture Movements (IFOAM); 2013. pp. 26–33.
[4] Schaack D PSWH Lernoud J. The organic market in Europe 2011—
Nine percent increase compared with 2010. In: Willer H, Lernoud J,
Kilcher L, editors. The World of Organic Agriculture. Statistics and
Emerging Trends. Frick, Switzerland: Research Institute of Organic
Agriculture (FiBL) and International Federation of Organic Agriculture
Movements (IFOAM); 2013. pp. 224–229.
[5] Donald PF, Green RE, Heath MF. Agricultural intensification and the
collapse of Europe’s farmland bird populations. Proceedings of the
Royal Society of London B: Biological Sciences. 2001;268(1462):25–
29. doi:10.1098/rspb.2000.1325.
Stoate C, B
aldi A, Beja P, Boatman ND, Herzon I, van Doorn A, et al.
Ecological impacts of early 21st century agricultural change in Europe
A review. Journal of Environmental Management. 2009;91(1):22–46.
Balmford A, Green R, Phalan B. What conservationists need to
know about farming. Proceedings of the Royal Society B: Biological
Sciences. 2012;279(1739):2714–2724. doi:10.1098/rspb.2012.0515.
Mader P. Soil fertility and biodiversity in organic farming. Science.
2002;296(5573):1694–1697. doi:10.1126/science.1071148.
Gabriel D, Tscharntke T. Insect pollinated plants benefit from organic
farming. Agriculture, Ecosystems & Environment. 2007;118(1-4):43–
48. doi:10.1016/j.agee.2006.04.005.
Holzschuh A, Steffan-Dewenter I, Tscharntke T. Agricultural land-
scapes with organic crops support higher pollinator diversity. Oikos.
2008;117(3):354–361. doi:10.1111/j.2007.0030-1299.16303.x.
Chifflot V, Rivest D, Olivier A, Cogliastro A, Khasa D. Molecu-
lar analysis of arbuscular mycorrhizal community structure and
spores distribution in tree-based intercropping and forest sys-
tems. Agriculture, Ecosystems & Environment. 2009;131(1-2):32–39.
[12] Rundl
of M, Edlund M, Smith HG. Organic farming at local and land-
scape scales benefits plant diversity. Ecography. 2009;33(3):514–522.
Tuomisto HL, Hodge ID, Riordan P, Macdonald DW. Does or-
ganic farming reduce environmental impacts? A meta-analysis
of European research. Journal of Environmental Management.
2012;112:309–320. doi:10.1016/j.jenvman.2012.08.018.
Tuck SL, Winqvist C, Mota F, Ahnstr
om J, Turnbull LA, Bengtsson
J. Land-use intensity and the effects of organic farming on biodi-
versity: a hierarchical meta-analysis. Journal of Applied Ecology.
2014;51(3):746–755. doi:10.1111/1365-2664.12219.
[15] Schneider MK, L
uscher G, Jeanneret P, Arndorfer M, Ammari Y, Bai-
ley D, et al. Gains to species diversity in organically farmed fields are
not propagated at the farm level. Nature Communications. 2014;5.
Lamine C, Bellon S. Conversion to organic farming: a multidi-
mensional research object at the crossroads of agricultural and so-
cial sciences. A review. Agronomy for Sustainable Development.
2009;29(1):97–112. doi:10.1051/agro:2008007.
Schmidtner E, Lippert C, Dabbert S. Haben Nachbarschaftseffekte
einen Einfluss auf die r
aumliche Verteilung des
Oko-Landbaus in
Deutschland? 20. Jahrestagung der
Osterreichischen Gesellschaft
ur Agrar
okonomie. In: Land-und Ern
ahrungswirtschaft 2020. Vienna,
Austria: Universit
at f
ur Bodenkultur; 2010. pp. 109–110.
Kaufmann P, Zemeckis R, Skulskis V, Kairyte E, Stagl S. The diffusion
of organic farming in Lithuania. Journal of Sustainable Agriculture.
2011;35(5):522–549. doi:10.1080/10440046.2011.579838.
Ilbery B, Kirwan J, Maye D. Explaining regional and local differ-
ences in organic farming in England and Wales: A comparison
of South West Wales and South East England. Regional Studies.
2014;50(1):110–123. doi:10.1080/00343404.2014.895805.
Gabriel D, Carver SJ, Durham H, Kunin WE, Palmer RC, Sait SM,
et al. The spatial aggregation of organic farming in England and
its underlying environmental correlates. Journal of Applied Ecology.
2009;46(2):323–333. doi:10.1111/j.1365-2664.2009.01624.x.
Bernholt H, Kehlenbeck K, Gebauer J, Buerkert A. Plant species rich-
ness and diversity in urban and peri-urban gardens of Niamey, Niger.
Agroforestry Systems. 2009;77(3):159–179. doi:10.1007/s10457-
Pecher C, Fritz SA, Marini L, Fontaneto D, Pautasso M. Scale-
dependence of the correlation between human population and the
species richness of stream macro-invertebrates. Basic and Applied
Ecology. 2010;11(3):272–280. doi:10.1016/j.baae.2009.09.005.
Freeman J. Domesticated crop richness in human subsistence cul-
tivation systems: a test of macroecological and economic deter-
minants. Global Ecology and Biogeography. 2011;21(4):428–440.
de Grenade R, Nabhan GP. Baja California peninsula oases: An
agro-biodiversity of isolation and integration. Applied Geography.
2013;41:24–35. doi:10.1016/j.apgeog.2013.03.008.
[25] Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. Very high
resolution interpolated climate surfaces for global land areas. In-
ternational Journal of Climatology. 2005;25(15):1965–1978. Data
available from: doi:10.1002/joc.1276.
QGIS Development Team. QGIS Geographic Information System;
2014. Available from:
Sastre P, Roca P, Lobo JM. A Geoplatform for improving acces-
sibility to environmental cartography. Journal of Biogeography.
2009;36(3):568–568. doi:10.1111/j.1365-2699.2008.02070.x.
Rangel TF, Diniz-Filho JAF, Bini LM. SAM: a comprehensive applica-
tion for Spatial Analysis in Macroecology. Ecography. 2010;33(1):46–
50. doi:10.1111/j.1600-0587.2009.06299.x.
Dormann CF. Effects of incorporating spatial autocorrelation into the
analysis of species distribution data. Global Ecology and Biogeogra-
phy. 2007;16(2):129–138. doi:10.1111/j.1466-8238.2006.00279.x.
Pautasso M, Zotti M. Macrofungal taxa and human population in
Italy’s regions. Biodiversity and Conservation. 2008;18(2):473–485.
[31] Cantarello E, Steck CE, Fontana P, Fontaneto D, Marini L, Pautasso
M. A multi-scale study of Orthoptera species richness and human
population size controlling for sampling effort. Naturwissenschaften.
2009;97(3):265–271. doi:10.1007/s00114-009-0636-4.
Geertsema W, Rossing WA, Landis DA, Bianchi FJ, van Rijn PC,
ee JH, et al. Actionable knowledge for ecological intensi-
fication of agriculture. Frontiers in Ecology and the Environment.
2016;14(4):209–216. doi:10.1002/fee.1258.
Gomiero T, Pimentel D, Paoletti MG. Environmental impact of dif-
ferent agricultural management practices: Conventional vs. organic
agriculture. Critical Reviews in Plant Sciences. 2011;30(1-2):95–124.
Wolf BM, H
aring AM, Heß J. Strategies towards evaluation beyond
scientific impact. Pathways not only for agricultural Research. Or-
ganic Farming. 2015;1(1). doi:10.12924/of2015.01010003.
Watson CA, Atkinson D, Gosling P, Jackson LR, Rayns FW. Managing
soil fertility in organic farming systems. Soil Use and Management.
2006;18:239–247. doi:10.1111/j.1475-2743.2002.tb00265.x.
Kassam A, Friedrich T. Nutrient management in conservation agricul-
ture: a biologically-based approach to sustainable production intensi-
fication. In: 7th Conservation Agriculture Conference. Dnipropetrovsk,
Ukraine; 2009. pp. 1–20.
Scialabba NEH, M
uller-Lindenlauf M. Organic agriculture and climate
change. Renewable Agriculture and Food Systems. 2010;25(02):158–
169. doi:10.1017/s1742170510000116.
Smith LG, Williams AG, Pearce BD. The energy efficiency of organic
agriculture: A review. Renewable Agriculture and Food Systems.
2014;30(03):280–301. doi:10.1017/s1742170513000471.
Siegmeier T, M
oller D. Mapping research at the intersection
of organic farming and bioenergy A scientometric review.
Renewable and Sustainable Energy Reviews. 2013;25:197–204.
[40] D
oring TF. A fresh start for organic farming research. 2013;1(1):1–2.
Aleixandre JL, Aleixandre-Tud
o JL, Bola
nos-Pizarro M, Aleixandre-
Benavent R. Mapping the scientific research in organic farm-
ing: a bibliometric review. Scientometrics. 2015;105(1):295–309.
Schmidtner E, Lippert C, Engler B, Haring AM, Aurbacher J, Dab-
bert S. Spatial distribution of organic farming in Germany: does
neighbourhood matter? European Review of Agricultural Economics.
2011;39(4):661–683. doi:10.1093/erae/jbr047.
Lapple D, Kelley H. Spatial dependence in the adoption of organic
drystock farming in Ireland. European Review of Agricultural Eco-
nomics. 2014;42(2):315–337. doi:10.1093/erae/jbu024.
Wollni M, Andersson C. Spatial patterns of organic agriculture adop-
tion: Evidence from Honduras. Ecological Economics. 2014;97:120–
128. doi:10.1016/j.ecolecon.2013.11.010.
Yang AL, Rounsevell MDA, Wilson RM, Haggett C. Spatial anal-
ysis of agri-environmental policy uptake and expenditure in Scot-
land. Journal of Environmental Management. 2014;133:104–115.
Teillard F, Allaire G, Cahuzac E, L
eger F, Maign
e E, Tichit M. A novel
method for mapping agricultural intensity reveals its spatial aggrega-
tion: Implications for conservation policies. Agriculture, Ecosystems
& Environment. 2012;149:135–143. doi:10.1016/j.agee.2011.12.018.
Kostandini G, Mykerezi E, Tanellari E. Viability of organic pro-
duction in rural counties: county and state-level evidence from
the United States. Journal of Agricultural and Applied Economics.
olf M, Smith HG. The effect of organic farming on butterfly
diversity depends on landscape context. Journal of Applied Ecology.
2006;43(6):1121–1127. doi:10.1111/j.1365-2664.2006.01233.x.
Norton L, Johnson P, Joys A, Stuart R, Chamberlain D, Feber R, et al.
Consequences of organic and non-organic farming practices for field,
farm and landscape complexity. Agriculture, Ecosystems & Environ-
ment. 2009;129(1-3):221–227. doi:10.1016/j.agee.2008.09.002.
Bredemeier B, R
uter S, von Haaren C, Reich M, Schaarschmidt F.
Spatial congruence between organic farming and biodiversity related
landscape features in Germany. International Journal of Biodiversity
Science, Ecosystem Services & Management. 2015;11(4):330–340.
Padel S. Conversion to organic farming: A typical example of the
diffusion of an innovation? Sociologia Ruralis. 2001;41(1):40–61.
Koesling M, Flaten O, Lien G. Factors influencing the conver-
sion to organic farming in Norway. IJARGE. 2008;7(1–2):78–95.
Geniaux G, Lambert M, Bellon S. Analyse de la diffusion spatiale de
l’agriculture biologique en r
egion Provence-Alpes-C
ote d’Azur (Paca):
construction d’une m
ethodologie d’observation et de prospective. In-
novations Agronomiques. 2009;4:417–426.
oring TF, Bocci R, Hitchings R, Howlett S, van Bueren ETL, Pautasso
M, et al. The organic seed regulations framework in Europe—Current
status and recommendations for future development. Organic Agricul-
ture. 2012;2(3-4):173–183. doi:10.1007/s13165-012-0034-7.
Allaire G, Cahuzac
E, Pom
eon T, Simioni M. Approche spa-
tiale de la conversion
a l’agriculture biologique. Les dynamiques
egionales en France.
Economie rurale. 2014;(339-340):9–31.
Latruffe L, Nauges C. Technical efficiency and conversion to or-
ganic farming: the case of France. European Review of Agricultural
Economics. 2013;41(2):227–253. doi:10.1093/erae/jbt024.
Allaire G, Pom
eon T, Maign
e E, Cahuzac E, Simioni M, Desjeux Y.
Territorial analysis of the diffusion of organic farming in France: Be-
tween heterogeneity and spatial dependence. Ecological Indicators.
2015;59:70–81. doi:10.1016/j.ecolind.2015.03.009.
Home R, Ries E, Tschanz A, Inderm
uhle A. Social factors
in the decision by Swiss farmers to convert to organic farming.
Acta Fytotechnica et Zootecnica. 2015;18(Special Issue):154–156.
Boncinelli F, Bartolini F, Brunori G, Casini L. Spatial anal-
ysis of the participation in agri-environment measures for or-
ganic farming. Renewable Agriculture and Food Systems. 2015;