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Adaptability of Mediterranean Agricultural Systems to Climate Change. The Example
of the Sierra M
agina Olive-Growing Region (Andalusia, Spain). Part I: Past and Present
MARIANNE COHEN,* JOSYANE RONCHAIL,
1
MARI
´AALONSO-ROLDA
´N,
#
CE
´LINE MORCEL,
@
STE
´PHANE ANGLES,* EDUARDO ARAQUE-JIMENEZ,
&
AND DAVID LABAT**
* University of Paris Diderot, Sorbonne Paris Cit
e, UMR Ladyss, Paris France
1
University of Paris Diderot, Sorbonne Paris Cit
e, UMR Locean (Sorbonne Universit
es-UPMC, CNRS, IRD, MNHN), Paris, France
#
Pasos, Participaci
on y Sostenibilidad,
Orgiva, Granada, Spain
@
University of Paris Diderot, Sorbonne Paris Cit
e, Paris, France
&
Territorio y Polı´tica Regional, Facultad de Geografı´a, Universidad de Ja
en, Ja
en, Spain
** G
eosciences Environnement Toulouse, Universit
e de Toulouse (CNRS, IRD, OMP), Toulouse, France
(Manuscript received 31 July 2012, in final form 7 March 2014)
ABSTRACT
This research focuses on the adaptability of olive-growing systems to climate change in the Sierra M
agina
region of Andalusia. The authors combined a retrospective and prospective analysis, an interdisciplinary
approach, collaboration among climatologists, geographers, and sociologists, and the participation of local
farmers and stakeholders, all contributing their own knowledge.
This paper assesses the adaptability of olive-growing systems to climate irregularities over the past 50 yr.
First, a climatic study shows that rainfall decreased by 18% during the period 1955–2009. Water resource
availability has declined 2 or 3 times more than rainfall, in part because of the expansion of irrigation, which
ameliorated the effects of droughts and increased profitability. Second, relationships between rainfall and
both irrigated and rainfed olive yields are assessed. These show that the cumulative rainfall of the 2 yr pre-
ceding the crop explains 41% of the variability of irrigated olive tree yields and 46% of rainfed yields; this
result was unexpected for irrigated yields. Third, this study examines the perceptions of climate variability of
15 farmers, the views of 16 local stakeholders [developers, olive oil professionals, local authorities, a con-
servationist, and a representative of a local nongovernmental organization (NGO)]. The perceptions of the
farmers are interpreted with respect to their socioeconomic status. All farmer and stakeholder interviewees
know to a certain extent the climatic influence on olive yields, and most of them acknowledge the recent
climatic changes. These findings will be valuable for future assessments of the adaptability of the agricultural
and social systems to climate change.
1. Introduction
a. A retrospective–prospective analysis of the
adaptability of Mediterranean agriculture to
climate change
In Mediterranean regions, the most common climate
change scenarios foresee an increase in temperatures and
adecreaseinrainfall(Christensen et al. 2007;Stocker
et al. 2014;Giorgi and Lionello 2008;Magnan et al. 2009;
Gualdi et al. 2013), and an increase in extreme episodes
(Hertig et al. 2013), with potential consequences for
agricultural yields (FAO 2008) and natural resources.
In this context, we must look beyond the question
of sustainable development and risk and incorporate
the concepts of vulnerability, adaptation, and the
resilience of socioeconomic systems facing environ-
mental change. Generally, climate scientists use the
concept of adaptation (Christensen et al. 2007;Stocker
et al. 2014;Simonet 2009). We decided to employ the
concept of adaptability (Walker et al. 2004), since it
takes into account the flexibility and heterogeneity of
societies’ responses to environmental changes. Indeed,
interactions between society and nature depend on
natural resources, such as groundwater, that are to
a certain extent integrated into the economy and are
sensitive to environmental changes, particularly to
climate change (Latiri et al. 2009).
Corresponding author address: Marianne Cohen, Univ. Paris
Diderot, Sorbonne Paris Cit
e, UMR Ladyss, 5 rue Thomas Mann,
Case courrier 7001, 75205 Paris CEDEX 13, France.
E-mail: cohen@univ-paris-diderot.fr
380 WEATHER, CLIMATE, AND SOCIETY VOLUME 6
DOI: 10.1175/WCAS-D-12-00043.1
Ó2014 American Meteorological Society
Vulnerable drought-prone agricultural systems are
relevant examples to examine adaptability to climate
change, since these systems are local models of global
ecological issues. Adaptability to climate change de-
pends on local societies’ choices, agricultural models
promoted by public policies, international markets
(CCAFS 2009;O’Brien et al. 2011;World Bank 2010),
and community-level organization (Heltberg et al.
2009). Drought experience may also ‘‘solidify people’s
perception about certainty of [future climatic] change’’
[Diggs 1991, p. 129; this result is also found by Australian
Bureau of Statistics (2009) and Seres (2010)].
Because of the long life duration of the olive trees,
olive growing provides a useful example to investigate
the adaptability to climate change. While Sofo et al.
(2008) consider the olive tree as a paradigm for drought
tolerance in Mediterranean climate, Moriana et al.
(2003) show a negative relation between olive yield and
evapotranspiration, suggesting that olive yields are
sensitive to rainfall irregularity and that irrigation
should improve it. According to Gal
an et al. (2008),
spring (flowering season) and summer (fruiting season)
rainfall and both maximum and minimum temperatures
in summer and autumn (harvest) are the major weather-
related parameters affecting fruit production. Garc
ıa-
Mozo et al. (2010),Avolio et al. (2012), and Orlandi
et al. (2012) show how temperature influences the phe-
nological phases of the olive tree. Besides, the yield of
the olive tree is alternatively high and low (vecer
ıa; bi-
ennial bearing). The vegetative growth produces nodes
every 2 yr that will bear potential floral buds the fol-
lowing year (Lavee 1996;Angles 1997). Other features
should influence olive yields, including the interspecific
competition from weeds and the intraspecific competi-
tion due to olive tree planting density.
Moreover, olive growing is an increasingly interesting
alternative for the local development of Mediterranean
sloping lands [higher profits than cereal or cattle breed-
ing, increased demand (Moriana et al. 2003), increased
yield due to irrigation]. This trend is acute in countries
such as Spain that have benefited from guaranteed prices
and subsidies after joining the European Union (EU) in
1986 (Milli and Gatti 2005;Araque Jimenez 2008), al-
though, it is noteworthy that these benefits have been
decreasing since the 2000s. Simultaneously, rainfall as
well as water resources have decreased in southern Spain
during the twentieth century (Duran et al. 2006;Lorenzo-
Lacruz et al. 2012). The water resource decline has been
exacerbated by inefficient water management (Liggins
2008;G
omez-Lim
on et al. 2012).
Despite the importance of this issue, the adaptability
of olive-growing regions to climate change has not been
taken into account in previous studies (Stroosnijder
et al. 2008). Within the scope of the French Scientific
Interest Group (GIS) Climate, Environment, and Soci-
ety Program, we have attempted to link three aspects of
the adaptability to climate change: the climate vari-
ability, the agriculture adaptability, and the perception
and strategies of stakeholders and farmers in a highly
specialized and market-dependent olive-growing re-
gion, Sierra M
agina (Andaluc
ıa, Spain). To achieve this
objective, we have combined climatological and geo-
graphical quantitative analyses and a sociological quali-
tative study. We linked retrospective and prospective
analyses to assess how the society–nature systems have
developed adaptability to past and present climate ir-
regularities (Beck et al. 2006;Enfors and Gordon 2007;
Mengistu 2011) and how useful the stakeholders’ expe-
riences and perceptions are for the future. Our method
attempts to contribute to the improvement of adaptability
assessment of rural areas to climate change (Lynch et al.
2008) and to be responsive to stakeholders’ concerns.
Nevertheless, our study is not thoroughly conclusive due
to the smallsize of our sociological sampleand due to the
complex interactions that might impact future trends.
Our study is published in two companion papers (Parts I
and II, retrospective and prospective analyses, respec-
tively). Part I is dedicated to the past and present. In sec-
tion 2, we present our method, and in section 3, we present
our results; in section 3a, we analyze the evolution of cli-
mate and water resources since 1955. In section 3b,we
carry out a study on the relationships between climate and
olive yield. In section 3c, we combine these results with the
farming and climate variability knowledge of farmers and
stakeholders. Finally, we draw conclusions in section 4.
In a companion paper, about the future, we carry out
research on the future local climate change, its conse-
quences on olive yield and water resources, and on
farmers and stakeholders’ points of view on these issues
(Ronchail et al. 2014).
b. Presentation of the case study
The rural region of Sierra M
agina (776 km
2
; 56 675
inhabitants; INE 2010) is located in Andalusia, Ja
en
Province, in the upper reaches of the Guadalquivir ba-
sin, on the Mediterranean-facing range of the Betic
Mountains (Fig. 1). It has a typical Mediterranean cli-
mate, modulated by altitude as Sierra M
agina peaks at
2167 m (section 3a). Agrarian surface covers 48.5% of
the total surface (Fig. 2;MAGRAMA 2006). Olive grow-
ing has become a monoculture, particularly after Spain
joined the EU in 1986 (section 1a). In Sierra M
agina, olive
groves represented 66% of cultivated land—55 000 ha—in
1986 and 85% in 2006—66 000 ha (Sanchez-Martinez
and Gallego-Simon 2009;Sanchez-Martinez et al. 2011).
In Ja
en Province, the area extent of olive groves
JULY 2014 C O H E N E T A L . 381
increased from 330 000 ha in 1945 to 455 000 ha in 1986
and to 570 000 ha (approximately) since 2002 [Ministerio
de Agricultura, Alimentaci
on y Medio Ambiente
(MAGRAMA)]. Sierra M
agina is a good example of the
intensification of agriculture and water resources extrac-
tion and of their negative environmental consequences
in the Ja
en Province (Araque Jimenez 2008;Ballais et al.
2013). In Sierra M
agina, the proportion of irrigated
olive groves increased significantly from 27% in 1986
(15 000 ha) to 51% in 2006 (34 000 ha) (Sanchez-Martinez
and Gallego-Simon 2009). In Ja
en Province, this pro-
portion remained less than 10% during the period
1945–79, grew slowly until the drought of the mid-1990s
(1995, 14%), and grew dramatically afterward, varying
FIG. 1. Location map of the Guadalquivir basin drainage, of the Sierra M
agina region, and of
the grid points of the climatic simulations within the Ensemble-Based Predictions of Climate
Changes and their Impacts (ENSEMBLES) project (http://ensemblesrt3.dmi.dk).
FIG. 2. Land use in the study area. [Sources are MAGRAMA (2006),CHG (2010), the
ENSEMBLES project, and www.juntadeandalucia.es].
382 WEATHER, CLIMATE, AND SOCIETY VOLUME 6
between 30% and 33% since 2004 (MAGRAMA). Nu-
merous reservoirs have been built by the irrigation com-
munities to store water for periods of low flow (Fig. 2),
and today water resources are largely devoted to irriga-
tion and are overexploited in some areas (section 3a).
Moreover, the weed control, especially below the trees
(ruedo), restrains the interspecific competition; it is op-
erated by tilling, or by the use of chemical means that are
encouraged by the Common Agricultural Policy since the
2000s, in order to restrain erosion (Ballais et al. 2013).
Jointly with economic factors (section 1a) and other
technical improvement in groves management (e.g.,
harvesting techniques), these changes allowed a dra-
matic increase in olive yields (section 3b) and generated
prosperity in the olive sector during the period 1986–
2005 with a positive societal outcome, stopping the ex-
odus of the rural population observed from 1950 to 1990
(INE 2010;IEA 2010).
As in other sloping lands in Mediterranean Europe
(Stroosnijder et al. 2008), various types of olive-growing
systems are observed in the Sierra M
agina region, varying
according to the use of irrigation and mechanization, the
density of olive trees, and the use of chemical herbicides.
Mechanization and irrigation are the main factors of the
farms’ viability (Sanchez-Martinez et al. 2011). The in-
crease of planting density is recommended since the 2000s
to improve the viability (Porras Piedra et al. 1997). High-
density olive groves (.200 trees ha
21
) reached 18% in
Andaluc
ıa in 2012 (MAGRAMA-SGT 2013). The im-
plementation of high-density groves is more difficult in
Ja
en Province, due to the lower capacity of small farm
owners to invest, with 70% of the holdings covering less
than 5 ha (INE 2010;Sanchez-Martinez et al. 2011). Dur-
ing the same period, the decrease of olive oil price (since
2005; www.internationaloliveoil.org/) and of government
subsidy (since 1999) are making the local economy vul-
nerable. Because of these characteristics, Sierra M
agina is
a representative example of olive-growing diversity, con-
straints, and potentials in Mediterranean Europe.
2. Data and methods
a. Sharing knowledge between disciplines and with
local stakeholders
A Sierra M
agina local action group (Asociaci
on para
el Desarrollo Rural) requested that our team investigate
the future of olive growing in Sierra M
agina in the
context of climate change. Our collaboration with
stakeholders and farmers developed to the extent that
we incorporated their ‘‘lay science’’ with our scientific
and modeling process (Corburn 2007). This process,
called ‘‘post-normal science’’ by other scientists, is
suitable for research incorporating complex issues and
significant level of uncertainty, which is the case for
olive-growing adaptability to climate change (Saloranta
2001;Lynch et al. 2008).
This process followed several steps: First, we analyzed
projections of climate in Sierra M
agina, focusing on the
parameters that stakeholders considered as limiting ol-
ive growth, in order to benefit from their knowledge and
promote their buy in of our projections. Second, we
observed during the interviews that farmers expressed
doubt about climate change since they are used to
dealing with interannual climate variability. Conse-
quently, we verified and mapped which parameters of
climate and water resources had changed over the last
decades and to what extent. Third, when we presented
the results of the climatic study to local stakeholders,
they responded that the uncertainties in our scenarios
were making their decision making difficult. They asked
us to determine the impacts of climate change specifi-
cally on olive production. Fourth, while modeling the
relations between climate and olive yield, we used the
local knowledge and additional agronomical information
to better understand the discrepancies between observed
and simulated yield values.
Moreover, the members of each discipline sought to
communicate their results in simple terms in order to
disseminate their findings. The results of the interviews,
presented in a table, played the role of a common pool of
knowledge; each discipline used it to assess its hypoth-
eses, improve its methods, and finally to compare its
results with the local knowledge.
In this bottom-up research, the process of exchanging
knowledge between disciplines and with stakeholders
and farmers led to the innovation and improvement
of our scientific approach and of its results. This process
required open-mindedness on the part of each researcher.
b. Data
1) CLIMATIC DATA
The analyses of the local climate
1
and its evolution are
based on local daily rainfall and temperatures from the
Spanish Meteorological State Agency database [Agen-
cia Estatal de Meteorolog
ıa (AEMET)] (Fig. 3; see the
appendix;Table A1). The description of the current
climate is based on 29 rainfall gauges and 12 tem-
perature stations (Fig. 3), with datasets that cover
a rather short time period (1988–2008; H. Garcin 2010,
1
In what follows we refer to both climate change on time scales
of decades and climate indices or variables such as precipitation
and temperature averaged over months or years. We use the word
climate alone to refer to either one of these when the context
is clear.
JULY 2014 C O H E N E T A L . 383
unpublished manuscript). The analysis of climate vari-
ability has been carried out using a smaller number of
stations (Fig. 3 and Fig. 4), but with longer time series
(from 1955 to 2009 for 15 rainfall gauge stations and
from 1974 to 2009 for 7 and 8 stations measuring maxi-
mum and minimum temperature, respectively). All the
stations are geolocated and integrated in a GIS system,
using Arcgis 10.0 software (Table 1).
2) YIELD,WATER RESOURCES,AND LAND USE
DATA
From 1999 to 2009, areal extent, olive production, and
yield data of rainfed and irrigated olive groves are
available for the province of Ja
en, at the annual time
scale, on the Agriculture, Food, and Environment De-
partment website (MAGRAMA; http://www.magrama.
gob.es). We copied older data (period 1955–99) from
MAGRAMA’s provincial registers in Ja
en. Olive har-
vesting runs from November (year Y21) to January–
February (year Y), and the MAGRAMA database
attributes the corresponding yield to year Y.
The MAGRAMA data Sistema de Informaci
on
Geogr
afica de Parcelas Agr
ıcolas (SIGPAC) (common
agricultural policy GIS; MAGRAMA 2006) provide
information about land use, and the Guadalquivir
Basin Authority data (CHG 2010)provideinfor-
mation about irrigation. An aerial photography of
the region is available online (www.juntadeandalucia.
es/medioambiente/site/rediam) for 2004. Water re-
sources data are available on the Confederaci
on
Hidrogr
af
ıca del Guadalquivir (CHG) website (and at
www.conocetusfuentes.com). We integrated these data
in a GIS (Table 1;Fig. 5). The Centro de Estudios
y Experimentaci
on de Obras P
ublicas (Center for Studies
and Experimentation of Civil Works; CEDEX) website
(http://hercules.cedex.es/anuarioaforos/default.asp)pro-
vides data on river discharge in several stations (Fig. 5b;
Table 2).
3) FARMERS AND STAKEHOLDERS
We conducted semistructured interviews of 31
people—stakeholders and farmers—in November
2009, March 2010, and May 2012. We selected the 16
stakeholders in order to collect a diversity of opinions on
climate change: 4 developers, 7 olive oil professionals, 3
local authorities, 1 conservationist, and 1 representative
FIG. 3. AEMET stations and study villages. [Sources are www.juntadeandalucia.es, the
ENSEMBLES project, AEMET, and CHG (2010)].
FIG. 4. Annual Rainfall Regional Index for 15 stations during the
period 1955–2009. The 1979 break is indicated as well as changes in
mean rainfall during the periods 1955–1979 and 1980–2009 re-
spectively (mean rainfall during the period 1955–2009: 615mm).
Source: AEMET
384 WEATHER, CLIMATE, AND SOCIETY VOLUME 6
from a local nongovernmental organization (NGO). For
the same reason, we selected 15 farmers according to
the size of their property (6 small-scale farmers and 9
medium- and large-scale farmers). The size of holding is
not usually a sampling criterion of olive system studies
(Stroosnijder et al. 2008) or of climate change studies
(Seres 2010;Merot et al. 2012). Its influence on the
perception of climate change has not been thoroughly
established (Diggs 1991;Australian Bureau of Statistics
2009). Nevertheless, we assume in our case study that
the farm size, which determines the importance of ag-
riculture in household income, may influence farmers’
concerns about climate change.
We chose to investigate farmers’ perceptions of cli-
mate change in two villages of Sierra M
agina, with dif-
ferent farming and climatic systems, in order to test the
influence of these variables (Diggs 1991;Australian
Bureau of Statistics 2009;Seres 2010;Merot et al. 2012).
The first one, Bedmar, is a medium-size village (3127
inhabitants; IEA 2010) located in the northeastern part
of the region (Fig. 3). It receives from 469 to 568 mm of
rain yr
21
according to the different Bedmar stations
(AEMET). The olive grove system is traditional (,200
trees ha
21
;MAGRAMA-SGT 2013), and the groves
are largely drip irrigated (83.6%; INE 2010). The sec-
ond, Larva, is the smallest village of the region with 478
inhabitants (IEA 2010). It receives 402 mm of rain yr
21
(in Cabra del Santo Cristo; see the appendix;Table
A1). Over the last decade, after a decrease in rainfall,
farmers have replaced the rainfed cereal crops with
drip-irrigated olive groves thanks to the diversion of
the Guadiana Menor River (not mapped in Fig. 2).
Some of these new groves are intensive (.200 trees ha
21
).
Larva’s farmers have thereby showed their adaptability
to recent climate changes within a market-dependent
context. The 15 farmers were selected among the members
of the cooperative of Bedmar ‘‘S. C. A. Bedmarense’’ and
the irrigation community ‘‘Llanos de Larva.’’
c. Methods
We use statistical and cartographic methods—for cli-
mate, water resource, and yield data—and qualitative
methods—for sociological data—and we combine and
compare their respective results.
1) STATISTICAL AND CARTOGRAPHIC METHODS
Principal component analysis (PCA) was performed
on annual climate series in order to summarize the
variability of climate in the Sierra M
agina region and to
assess whether the sets of rainfall and temperatures
stations exhibit uniform time–space variations or not.
We computed the Bravais–Pearson coefficient of
correlation (r) between time and climate indices in order
to detect trends in the series, as well as between climate
TABLE 1. Multisource data integrated in the GIS database Sierra M
agina.
Themes Shapefile Spatial unit Source Information selected
Climate Designed by authors from
georeferenced data
Climatic station (point) AEMET Temperature and rainfall
Designed by authors IPCC grid ENSEMBLES Half-degree grid
Topography Junta de Andalusia Pixel Junta de Andalusia website
(www.juntadeandalucia.es)
Digital terrain model (DTM)
Land division SIGPAC Local authority shape MAGRAMA (2006) Shape of Sierra M
agina district
Land use Aerial photography Plot of land (polygons) Junta de Andalusia website
(www.juntadeandalucia.es)
Land use high-density groves
Irrigation Designed by authors
from CHG (2010)
Area of irrigated land
(polygons)
CHG (2010) Origin of water resource used
for irrigation, regulation
Pools Junta de Andalusia Pools (polygons) Junta de Andalusia website
(www.juntadeandalucia.es)
Pools used to store water
for irrigation
Rivers CHG website Segments of
rivers (lines)
CHG (2010) Name of rivers, presence of dams
Berbel (2008) Situation of rivers in 2015
Designed by authors
from CEDEX map
Discharge stations
(points)
CEDEX website Evolution of discharge since 1955
Groundwater CHG website Aquifers (polygons) CHG (2010) Name, exploitation rate in %
IGME (1997) and
Gonz
alez-Hernando and
Gonz
alez-Ram
on (2002)
Evolution of some aquifers
Springs Designed from
georeferenced data
by J. Salam
e (2010,
unpublished
manuscript)
Springs (points) Conoce Tu Fuentes
Initiative Website (www.
conocetusfuentes.com)
Name, use (irrigation), minimal
and maximal stream in m
3
s
21
JULY 2014 C O H E N E T A L . 385
indices and yield data to measure their relationship.
Generally, ris considered significant when the pvalue is
lower than 0.05.
Linear regression is used to relate yields to time.
Detrended yields values (independent from the trend)
are obtained by subtracting the regression estimates
from the observed values. Moreover, wavelet analysis
allows removing the variability due to the biennial
bearing (section 1a) from detrended yields series. The
multiresolution analysis is used to provide an orthogonal
dyadic decomposition of the signal (Labat et al. 2000).
Then, it is possible to isolate a given frequency or period
and to filter it from the signal by simply removing it from
the multiresolution analysis and then to sum up again all
the other components. This method proves its efficiency
compared to Fourier filtering when the signal is not
stationary. The resulting yield values, detrended and
without the biennial bearing, are called residual
yields.
Linear regression is also used for modeling the re-
lationships between climatic indices and detrended
yields (Figs. 6,7,8). The statistical significance of these
models is assessed using F tests to confirm the goodness
of fit of the model and by ttests of individual parameters
to verify the significance of the estimated parameters
(see the appendix;Table A2). Finally, we use break tests
TABLE 2. Discharge of the main rivers during the periods 1955–79 and 1980–2009.
Code Name River Regime
Measure
period Mean
1955 1979
(m
3
s
21
)
Missing
years
Mean 1980–
2009
(m
3
s
21
)
Missing
years
Evolution
in %Begins Ends
5002 Guadalquivir Guadalquivir Altered 1912 1994 12.92 12 6.11 15 252.75
5003 Pedro Marin Guadalquivir Altered 1911 2009 26.84 13.5 11.39 14 257.55
5004 Mengibar Guadalquivir Altered 1912 2009 47.09 6 23.88 10 249.29
5023 Guadiana
menor
Guadiana
menor
Altered 1911 1990 16.78 7 3.59 28 278.60
5024 Horno del vidrio Jandulilla Natural 1932 2009 0.18 24 0.46 7 1150.57
5029 Mengibar Guadalbullon Natural 1912 2009 5.43 2 2.22 5 259.10
5044 Cacin Cacin Natural 1930 1969 1.44 10 —
5061 Guadalquivir Guadalquivir Altered 1949 1995 26.49 4 12.21 14 253.91
5062 Mengibar Guadalquivir Altered 1949 1995 50.38 2 20.15 14 260.00
5083 Puente Nuevo Guadalbullon Natural 1970 2009 5.06 15 1.44 4 271.55
5084 Puente Jontoya Quiebrajano Natural 1974 2009 1.82 21 0.95 1.5 248.13
FIG. 5. Origin of the water used for irrigation. (a) Groundwater and (b) surface water. [Sources are CHG (2010), http://hercules.cedex.es,
ENSEMBLES project, www.juntadeandalucia.es, and www.conocetusfuentes.com.]
386 WEATHER, CLIMATE, AND SOCIETY VOLUME 6
to identify break points in time series (Pettitt 1979;
Mann 1945).
We select by photo interpretation and compute with
a GIS (Arcgis 10.0) the percentage of high-density olive
groves surface in 2004 in a sample area (northwest grid
cell; Fig. 1). In this region, the increase in planting
density is supposed to be the most probable. Indeed, the
size of olive groves is rather large [mean of 0.75 ha;
standard deviatin (SD) of 2.45], and the area is located in
the Guadalquivir valley, where irrigation is very easy. In
comparison, the average size of groves is 0.6 ha in Ja
en
Province (SD of 2.55). In this cell, where 20.71% of the
olive groves of our study area are located, high-density
groves represent 5.76% of the olive groves surface
(MAGRAMA 2006). We also built water resources
maps, overlaying thematic information (Fig. 5). We
compared the evolution of river flow and regional
rainfall during two periods: 1955–79 and 1980–2009.
2) SOCIOLOGICAL APPROACH
(i) Overview of the sociological method
A detailed analysis of rural reality leads us to un-
derstand its complexity (Weber 1978). With this pur-
pose, we first built a typology according to Weber’s
‘‘ideal types’’ method (Weber 1949), within the frame-
work of interpretative sociology. Then, we compiled
perceptions, decisions, and personal trajectories of both
farmers and stakeholders to establish a relation between
their profile and their views on climate change.
(ii) Semistructured interviews on the strategies and
climate perceptions of farmers and stakeholders
In November 2009, we interviewed nine institutional
representatives, here referred to collectively as stake-
holders. We asked them about the farming system, the
key climatic parameters for olive growth, and their views
on climate change and the natural resources. We ana-
lyzed these semistructured interviews qualitatively.
In March 2010, we interviewed 15 farmers on the
following main topics: the farmer and the farm, decision-
making process, opinion about climate change (present
and future), decision according to climatic projections,
and other information. We arranged the collected
FIG. 6. Evolution of irrigated (black line) and rainfed (gray line)
yields during the period 1954–2009. Linear trends (black thin lines)
are represented as well as the coefficients of determination (r
2
)
between yields values and time. Source is MAGRAMA.
FIG. 7. Biennial regional rainfall in 15 stations without the JJA totals (bars) and annual residual
(without trend and biennial bearing) irrigated (gray line) and rainfed (black line) yields.1980 rainfall
value is the sum of 1978 and 1979 rainfall (without JJA rainfall). The 1980 yield values corresponds
to the November 1979 to January–February 1980 crop. Sources are MAGRAMA and AEMET.
JULY 2014 C O H E N E T A L . 387
information in a table in order to facilitate the sharing of
information with other scientists and cross analyzed the
interviewees and their opinions about the main topics.
Then, we analyzed the information qualitatively and
built a cognitive scheme (Fig. 9) in order to display the
logical relations established by farmers between pro-
cesses, their causes, and their consequences (Cohen
et al. 2009).
(iii) Interviews on local knowledge about the
relationship yield–climate
In May 2012, we conducted semistructured interviews
to compile the experience of six olive oil professionals
and one representative NGO on the relationship be-
tween climate and olive yield and their views about the
discrepancies of our yield–climate model. We also
compiled agronomic data to confirm the consistency of
their views (Table 4;Fig. 10).
3. Main results
a. Climate and water resources evolutions
1) THE CLIMATE IN THE SIERRA MA
´GINA AND ITS
EVOLUTION SINCE THE 1950S
(i) Mean climate
Mean monthly rainfall and temperature data (1988–
2008; see the appendix;Table A1) show that in the
Sierra M
agina, as in many Mediterranean regions,
annual-mean daily maximum temperatures are high
(between 208and 238C, up to 258C in Guadalquivir
valley), summers are dry and very hot (up to 408in the
valley), and maximum rainfall is observed in October–
January (winter) and April–May (spring). Annual
rainfall varies from 450 to 900 mm yr
21
on the western
side of Sierra M
agina, exposed to the westerlies, and
from 400 to 600 mm yr
21
on the lee side of the mountain,
FIG. 8. Observed (black line) and simulated (gray line) residual yields, that is, detrended and without the biennial bearing, during the
period 1980–2009, for (a) irrigated yield and (b) rainfed yield. Estimated yields are function of the biennial rainfall without the summer
rainfall (JJA) in 15 stations. Sources are MAGRAMA and AEMET.
FIG. 9. Farmers’ opinions and perception on changes in climate.
388 WEATHER, CLIMATE, AND SOCIETY VOLUME 6
as shown by Gimenez Martinez (1982). We took this
spatial rainfall variability into account when we selected
the sample villages where we conducted the farmer’s
interviews (section 2b).
(ii) Rainfall evolution since 1955
The first PCA (PC1) on annual rainfall (15 stations,
during the period 1955–2009) summarizes 80% of the
total rainfall variance and reveals an important spatial
consistency of rainfall variability in the Sierra M
agina
region. The presence of this feature allowed us to con-
struct an annual regional rainfall index by averaging the
rainfall of the 15 stations (Fig. 4). This regional rainfall
index is strongly correlated with the time series of PC1
(r50.99, p,0.000 01).
Figure 4 shows a strong interannual variability of
rainfall with, for instance, a regional rainfall index as low
as 400 mm in the mid-1990s and as high as 1000 mm in
1996 and 1997. This irregularity is a characteristic of
Mediterranean climate (Gimenez-Martinez 1982).
During the period 1955–2009, the annual regional
rainfall index is correlated negatively and significantly
(r520.31, p50.05) with time, indicating a negative
rainfall trend. Moreover, different break tests applied to
the regional rainfall index highlight a break point (p5
0.05) in 1979 (Fig. 4). Rainfall decreased by 18% be-
tween the first period (1955–79: 731 mm yr
21
) and the
second one (1980–2009: 598 mm yr
21
). Considering
seasonal rainfall time series at individual stations, the
drop varied from 10% to 30%, principally in winter.
The rainfall decrease in the region of the Sierra
M
agina is consistent with the pattern reported by
Rodrigo et al. (2000) and Rodrigo (2010) for the entire
Andalusian autonomous region and with the findings of
Rodrigo and Trigo (2007) and Gonz
alez-Hidalgo et al.
(2010), who described a decrease of rainfall intensity in
Spain along with a shortening of the wet season. The
long-term variability is probably due to a long-term phase
change of the North Atlantic Oscillation (Rodr
ıguez-
Puebla et al. 1998,2001;Trigo et al. 2004).
Most of the farmers and stakeholders interviewed
reported the rainfall decrease (section 3c).
(iii) Temperature evolution since the 1970s
PCA analysis on annual minimum and maximum tem-
perature time series (7 and 8 stations, respectively, during
the period 1974–2009) shows that the time–space variations
in temperatures is less uniform than the variation in rain-
fall. PC1 captures 58% and 55% of the total variance of
maximum and minimum temperatures, respectively, and
highlights some spatial differences in the timing tempera-
ture changes. The correlation between time and the mini-
mum temperature PC1 time series is significant and positive
(r510.79, p,0.000 01), indicating a trend of increasing
nighttime temperatures. Trend analysis on seasonal values
in individual stations shows that the strongest increases
in minimum temperature occur in spring and summer,
consistent with Del R
ıo et al. (2011). Break tests on
individual series show breaks in four stations out of
seven at the end of the 1970s and at the beginning of the
1990s.
In contrast, the maximum temperature PC1 time se-
ries is not significantly correlated with time; two stations
out of eight exhibit a positive trend, one shows a nega-
tive trend, and the others show no change. This result is
not consistent with findings of increase in both maxi-
mum and minimum temperatures by many authors,
among them Brunet et al. (2007), or perceptions of
stakeholders and farmers (section 3c).
The number of frost days diminished consistently, as
observed in the Iberian Peninsula by Fernandez-Montes
and Rodrigo (2011), while the number of very hot days,
with a maximum temperature over 408C, remained un-
changed in the Sierra M
agina region (408C is a critical
temperature for olive trees; Loussert and Brousse 1978).
2) USE AND SITUATION OF WATER RESOURCES IN
SIERRA MA
´GINA
Water resources are a key factor for the olive-growing
sustainability within the context of climate change. Drip
irrigation for olive groves does not require much water;
in 2010, CHG recommends to use 1290 m
3
ha
21
yr
21
,
equivalent to a third of the lowest annual rainfall value
(400 mm); according to some interviewees, 500 to
800 m
3
ha
21
yr
21
—50 to 80 mm—are sufficient. How-
ever, the average water consumption for drip irrigation
in olive grove is currently higher in the Guadalquivir
FIG. 10. Damages of P. oleae in 1996–2009. Source are Memorias
Atrias and DPO (denominaci
on de origen protegida) Sierra
M
agina, (2012 unpublished data).
JULY 2014 C O H E N E T A L . 389
basin (1837 m
3
ha
21
yr
21
; 183.7 mm; Arg€
uelles 2010).
This difference may partly be due to the existence of
illegal wells or pools. Nevertheless, we must have in
mind that in 1995 the water allocation for olive trees
irrigation was up to 3000 m
3
ha
21
yr
21
(300 mm) and that
the amount has been reduced by the basin authority
(CHG) (Berbel 2008) in order to mitigate the agrarian
water deficit in the upper basin (225 to 230%; CHG
2010). Water used for olive groves’ drip irrigation is
currently extracted either from surface or/and ground-
water bodies (CHG 2010;Fig. 4).
(i) Groundwater resources
Sierra M
agina is a karstic mountain with numerous
groundwater bodies, most of them with high perme-
ability and productivity. Despite the groundwater con-
trol policy, half of the aquifers are overexploited (Fig.
4a). Water storage has decreased in four aquifers. Gen-
erally, the decline happened after the severe drought
of the mid-1990s (Fig. 10;IGME 1997;Gonz
alez-
Hernando and Gonz
alez-Ram
on 2002;CHG 2010). For
this reason, drip irrigation, mainly based on surface
water resources, replaced the ancient irrigation system,
based on the utilization of springs, canals (acequias), and
ditches. Nevertheless, because of the high water de-
mand, groundwater is also increasingly exploited (10%
of the total amount of water in 1992, 21% in 2007, and
726 hm
3
in the Guadalquivir basin), mostly for agricul-
ture (84%; CHG 2010) by individual farmers (64% of
the users; Corominas-Masip 2002). Most of the springs
used for agriculture have a low flow, particularly those
from overexploited aquifers (Fig. 4a; J. Salam
e 2010,
unpublished manuscript). Local people confirmed these
observations (section 3c).
Drip irrigation increase and winter rainfall decrease
are the main reasons for groundwater decline (e.g.,
Ubeda aquifer; Corominas-Masip 2002). The growing
demand for freshwater may also have had a negative
influence on aquifers located around cities [e.g., Mancha
Real–Pegalajar (Gonz
alez-Ramon 2008) and Bedmar–
J
odar aquifers].
(ii) Surface water resources
The main water resource used for olive groves drip
irrigation is surface water. Almost the entire river
network is used for irrigation. A band 10 to 15 km wide
along the Guadalquivir River is irrigated by pumping
water from the river (points 2–4 and 61–62, Fig. 5b). The
same thing happens in Larva, where farmers use a di-
version (not mapped) of the Guadiana Menor River
(point 23, Fig. 5b). The Guadalbull
on River (points 83
and 84, Fig. 5b) supplies water for irrigated olive groves,
replacing the dried springs from the Mancha Real–
Pegalajar aquifer (Fig. 5a;Gonz
alez-Ram
on 2008). The
most important rivers of the region, the Guadalquivir,
Guadiana Menor, and Quiebrajano (near point 153,
Fig. 5b), are highly regulated. Surface water is generally
used by the irrigation communities, which comprise
69% of the users (Corominas-Masip 2002). Surface
water is highly exploited, exceeding the rate of 60% in
most of the small rivers (Bedmar, Torres, and Jandulla
Rivers, which flow from Sierra M
agina to the Gua-
dalquivir River) and also in large parts of the large ones
(e.g., Guadalbullon, Guadiana Menor, and Guadalqui-
vir; CHG 2010).
When comparing two periods, 1955–79 and 1980–
2009, during which rainfall decreased by 18%, we ob-
serve that the streamflow decrease has been double or
even triple (Table 2) the rainfall decrease. The stream-
flow decrease may be due to dams (Lorenzo Lacruz et al.
2012). In our case study, the most important dam was
built during the first period of our study (Table 3). We
assume that, besides and because of the rainfall de-
crease, the intense extraction of water for olive grove
irrigation has contributed to the discharge decrease
since the 1980s. These results are consistent with other
studies on the effects of rainfall decrease and of land use
change on water resources degradation (Duran et al.
2006;Perez and Andreo 2006;Rodr
ıguez-D
ıaz et al.
2007;Lorenzo-Lacruz et al. 2012).
b. Olive oil yield variability since the 1950s and its
relationship with climate
1) HISTORICAL,ECONOMIC,PHYSIOLOGICAL,
AND TECHNICAL COMPONENTS OF YIELD
VARIABILITY
Olive yields increased significantly since the 1950s in
Ja
en Province, from 1000 to 3000 kg ha
21
and from 2000
to 4000 kg ha
21
, for rainfed and irrigated yields, re-
spectively (Fig. 6). This trend is due to multiple factors
TABLE 3. Inflow and outflow of the main dams in the study area.
River dam Built Full capacity In (m
3
s
21
) Out (m
3
s
21
)
Pedro Marin–Guadalquivir 1969 1975–76 14.5 14.5
Quiebrajano 1976 0.3 0
Alto Guadiana Menor 2000 3.4 3.4
390 WEATHER, CLIMATE, AND SOCIETY VOLUME 6
explained in section 1b. The Bravais–Pearson coefficients
of correlation between yield and time are positive and
significant (r50.73 and p,0.000 01 for irrigated yield
and r50.57 and p50.000 01 for rainfed yield). A high-
frequency variability of both rainfed and irrigated olive
groves, due to the biennial bearing (section 1a), is also
clearly noticeable in Fig. 5.
2) RELATIONSHIP BETWEEN YIELD AND CLIMATE
INDICES
We subtracted both the historical trend (section 1b)
and the biennial bearing (section 1a) from the observed
yield values and obtained residual yields values that can
be considered as mainly related to climate (Fig. 6). The
influence of planting density on residual yield is con-
sidered low; indeed high-density groves cover only
5.76% of olive groves surface, in large plots of land
(mean 6.04 ha), in our sample area located in Ja
en
Province in 2004. Because of the mechanical or chemical
weed control, the role of interspecific competition on
yield is also considered as insignificant as explained
above (section 1b). Since rainfall is not stationary and
shows a break in 1979, we examined the relationship
between rainfall and residual yields during the period
1980–2009.
(i) Dependence of yield on rainfall
Bravais–Pearson coefficients of correlation are cal-
culated between residual yields and regional rainfall
indices computed on various periods of time in order to
find the best relationship between rainfall and yields.
The best result is observed between the residual yields
of year Y(corresponding to the harvest occurring from
November year Y21 to January–February year Y)and
the accumulated biennial rainfall [without the summer
values, June, July, and August (JJA)] of the two pre-
vious years (years Y22 and year Y21; Fig. 6). The
result that the rainfall during the previous 2 yr is im-
portant was expected because of the biennial bearing
(section 1a). But, the fact that summer rainfall does
not contribute much to the explanation of the yields
variability is partly inconsistent with Gal
an et al.
(2008), who found that the spring and summer period
rainfall is correlated with fruit production, and with
Doupis et al. (2013), who show that the lack of irriga-
tion in summer favors stomata closure and the limita-
tion of photosynthesis.
The coefficients of correlation between yields values
and rainfall are 0.64 (p50.0001) and 0.68 (p,0.0001)
for irrigated and rainfed yields, respectively. This means
that drip irrigation does not mitigate the lack of rainfall
as much as might be expected (Loussert and Brousse
1978;Moriana et al. 2003).
Simulated residual yields, dependent on rainfall, are
computed using linear regression models. The equations
of the models are as follows:
SRRY 51:6054 RR 21817:38, (1)
SRIY 51:2266 RR 21393:25. (2)
SRRY is the simulated residual rainfed yield, SRIY is
the simulated irrigated yield, and RR is the biennial
rainfall without summer values. The goodness of fit of
the models and the significance of the estimated pa-
rameters are assessed by F tests and ttests. Their results
are presented in Table A2 and confirm the quality of the
models.
These results mean that residual yield increases by
160 kg ha
21
each time biennial rainfall (without sum-
mer) values increase by 100 mm for rainfed crops and by
120 kg ha
21
for irrigated crops.
Some discrepancies between observed and simulated
residual series are highlighted in Fig. 8, with overestimated
values during the dry period of the mid-1990s (especially for
rainfed values) and after some rainy years, at the end of
the 1990s. Also, underestimated values characterize the
beginning of the twenty-first century. Agronomic informa-
tion gathered by semistructured interviews with farmers
and stakeholders helps understanding of the differences
between observed and simulated yields (section 3c).
Finally, a wavelet analysis on rainfall and yields series
presented in Fig. 8 reveals a 6-yr pattern since the 1990s
(not shown); this is consistent with the 7–9-yr rainfall
variability observed in the Iberian Peninsula and related
to the North Atlantic Oscillation variability (Rodr
ıguez-
Puebla et al. 1998,2001;Rodrigo et al. 2000).
(ii) Dependence of yield on temperature
We do not assess the relationship between tempera-
tures and yields because it is difficult to obtain a reliable
index of regional temperature. Indeed, temperature
data lack homogeneity as seen in section 3a. This is
a limitation of our work as temperature has an influence
on olive yield (Gal
an et al. 2008).
c. Understanding the farming system and the
perception of climate variability
We constructed a typology of the different farmers
and farming systems of Sierra M
agina, characterized by
the role that farming income plays within the household
economy. This role can be the main income source, a
complement to the main income source, or capital
investments (M. Alonso-Rold
an 2010, unpublished
manuscript). This typology is helpful in understand-
ing farmers’ interpretations about climate change and
variability.
JULY 2014 C O H E N E T A L . 391
1) TYPOLOGY OF SIERRA MA
´GINA’S FARMERS
The typology covers three target groups (small-,
medium-, and large-scale farmers), using different olive
production systems among those described by Stroosnijder
et al. (2008).
(i) Type 1: Small-scale farmers
In small farms (less than 5 to 10 ha, depending on the
production and on the market), the income from olive
groves is an additional (secondary) income. Farmers
cultivate their own olive groves in their spare time, and
they usually invest in small equipment and drip irriga-
tion systems. They harvest the olives with the help of
the family and then mill the olives in a local cooper-
ative, so they obtain olive oil for self-consumption and
extra revenues. All farming systems are present in this
group: from traditional olive groves (,200 trees ha
21
;
MAGRAMA-SGT 2013) to one intensive olive grove
(.400 t rees ha
21
, in the same place), rainfed or irrigated,
in high or low slope areas. Olive groves are partially
mechanized (pruning, fertilization, or weed control are
done manually, especially in rainfed olive groves).
(ii) Type 2: Medium-scale farmers
In this group, the farmers are professional, and they
make a living from the revenues that their holding
generates. They follow a strategy based on competitive
investments to increase the farm size and the farm ma-
chinery. However, as with small-scale farmers, they
depend on market prices. The farming system consists of
traditional or intensive olive groves, with drip irrigation
systems located in low slope areas. Harvesting, pruning,
pest control, fertilizing, irrigation, mechanical, or
chemical weed controls are carried out with farming
machinery.
(iii) Type 3: Large-scale farmers
The property is big enough (more than 50 ha, ac-
cording to the interviewees) to have wage earner(s) full
time. Their farm is a capital investment, and they rely on
other professional farmers to manage it. The farming
systems within this group may be traditional or intensive
olive grove, all of them with drip irrigation, located in
low slope areas and completely machine operated.
2) LOCAL PERCEPTIONS OF CLIMATE AND WATER
RESOURCES
The survey responses from our interviews show dif-
ferent opinions on the climate. While all institutional
stakeholders acknowledge the existence of climate
change, and consider it a future threat, the farmers’
views are more varied.
(i) Institutional stakeholders’ perception about
climate
The stakeholders interviewed in November 2009
considered climate change a true phenomenon, a recent
and a drastic process, and they are aware of the dangerous
effects associated with it. They reported observed
changes in climate, that is, rainfall decrease, particularly
during winter and spring, more frequent extreme events
(storms), higher temperatures in winter and in summer,
as well as drastic seasonal changes. Our study has partly
confirmed their statements (section 3a). Their opinions
are based on their own experience or on elders’ or
farmers’ testimonies. However, only one person men-
tioned the relationship between higher temperature and
CO
2
concentration. Stakeholders regret that farmers
have little awareness of climate change, despite the in-
creasing importance given to this phenomenon in the
mass media.
(ii) Farmers’ perceptions of climate
Most of the farmers (9/15) considered that climate has
changed during the past years, while some others (3/15)
interpreted these changes as a demonstration of the
usual climate irregularity of Sierra M
agina (Fig. 9). A
larger proportion of medium- and large-scale farmers
(6/9) than small-scale farmers (3/6) acknowledged
changes in climate during the last 10 to 20 yr. Nearly half
of the farmers (7/15) have noticed a rainfall decrease.
Three out of seven farmers described a period of re-
duced rainfall that is consistent with our results. Four of
them also mentioned an increase in temperature, which
our data partially confirm. Most of the farmers who
mentioned a change in climate did not give an expla-
nation (6/9). Surprisingly, these perceptions do not de-
pend on the village or on the olive-growing system,
although the Larva farmers changed their crop system
partly because of the drought.
(iii) Farmers, and stakeholders, perceptions of water
resources
Despite the dramatic decrease during the last decades
(section 3a), a water resources decline was mentioned in
the same proportion as a water resources improvement
(4/15). In addition, the groundwater issue was debated
locally. Some farmers considered that the capacity of
groundwater bodies is sufficient for drip irrigation. One
local NGO [Asociaci
on vecinal ‘‘Fuente de la Reja’’ de
Pegalajar (Ja
en) 2002] considered that Pegalajar spring
is a collective and cultural legacy to be preserved,
while hydrogeologist Gonz
alez-Ram
on (2008) found
that the corresponding aquifer is not overexploited.
This spring dried up in 1988 and flowed again after
392 WEATHER, CLIMATE, AND SOCIETY VOLUME 6
heavy rains in 2010 and 2013, filling occasionally the
ancient basin (charca) used for the gravity irrigation of
orchards. Other stakeholders were aware of the water
resource scarcity, but they thought that technical im-
provements and better water management were ap-
propriate solutions.
3) LOCAL KNOWLEDGE ABOUT THE
RELATIONSHIP BETWEEN CLIMATE AND YIELD
Farmers and stakeholders interviewed in November
2009 and March 2010 mentioned the same climatic pa-
rameters favoring olive growth: sufficient rainfall for
branch development and mild, maximum temperatures
the following year to avoid flowers falling in spring; and
sufficient rainfall for olive growth and mild maximum
temperatures to avoid olive fall in autumn. Those state-
ments are, to some extent, similar to previous literature
(Loussert and Brousse 1978;Lavee 1996;Moriana et al.
2003;Gal
an et al. 2008) and to our findings on the re-
lationships between climate and yields (section 3b).
Most farmers related good harvests to temperatures
(12/15) and to rainfall (11/15), six of them, regardless of
the use of irrigation. Considering longer time periods,
almost half of them (7/15) explained the olive yield
increase with the use of irrigation, but the same pro-
portion attributed the increase to other factors (e.g.,
technical practices; only one person refers to climate).
These latter statements are rather close to our results on
the relationships between irrigated yields and rainfall
(section 3b).
The stakeholders we interviewed in May 2012 about
the models between rainfall and yields were quite sur-
prised by the relatively poor efficiency of irrigation
shown by our model. They agreed with our results that
show concomitant decreases in rainfall and in yields
during the years 1993–95 and 2005 (Fig. 7). Some of
them explained lower than expected yields observed in
1998 and 1999 (after 1996 and 1997 rainy years) by high
temperatures, others by the impact of parasites or by the
saturation of olive roots in the deep and clayish soils
near Guadalquivir River. Indeed, data supplied by the
Denomination of Protected Origin Office technicians
(Memorias Atrias, 1995–2009, unpublished data) dem-
onstrate that the damages of the most virulent olive
groves parasite, Prays oleae, were significant in 1997 and
1998 (Fig. 10). Local data (Table 4) suggest that the
farmers do adjust irrigation practices based on rainfall.
In such cases, soil saturation occurring during rainy
years might not be due to overirrigation. Last, stake-
holders attributed higher than expected yields during
the period 1999–2005 (Fig. 8) to the maturity of the olive
trees, which were planted from the mid-1980s to the end
of the 1990s, when farmers received European subsidies
for these new plantations.
4. Discussion and conclusions
The study of the past and present conditions of olive
groves and climate in Sierra M
agina has contributed to
our knowledge of this Mediterranean agrarian region. In
this section, we summarize our main results and discuss
a key point: does past experience provide a basis for
adaptation to climate change?
a. Main results on climate, water resources, and yield
Our study documents the different changes in rainfall,
water resources, and olive yields in the mountainous
region of Sierra M
agina (Andaluc
ıa, Spain) since the
1950s and points out the relationships between yields
and rainfall since 1980. In this region, the record of
rainfall is highly variable and exhibits a step function
decrease of 18% after a break point in 1979. Notably,
available water resources also decreased, dropping 2 or
3 times more than rainfall since 1955. Meanwhile, in the
Ja
en Province that includes Sierra M
agina, olive yields
increased considerably since the middle of the twentieth
century, from 1000 to 3000 kg ha
21
and from 2000 to
4000 kg ha
21
for rainfed and irrigated yields, respectively.
The yield increase can be related to economic, social, and
technical factors, and the increased proportion of irri-
gated groves is considered an adaptation to the decreasing
rainfall and an effort to increase profits (Adams et al.
1998;Adger 2000).
Nevertheless, we have proved that yield still depends
on rainfall regardless of irrigation. Indeed, the rainfall
of the 2 yr (without summer totals) preceding the crop
explains 41% of the variability of residual (without
trend and biennial bearing) irrigated olive tree yields
and 46% of residual rainfed yields. This is an unexpected
result compared to previous studies (Loussert and Brousse
1978;Moriana et al. 2003).
TABLE 4. Annual regional rainfall and water consumption of the irrigation community Santa Potenciana (1000 ha of olive groves in
Villanueva de la Reina, in the course of the Guadalquivir River). Period 2002–11. Source is V. Gallego (xxxx, unpublished data).
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Rainfall (mm) 570 654 541 377 525 522 735 826 1111 No data
Water use (m
3
ha
21
) 1090 1100 835 1580 900 900 600 850 275 430
JULY 2014 C O H E N E T A L . 393
We confirm the increase in minimum temperature
found by Brunet et al. (2007),Del R
ıo et al. (2011), and
Fernandez-Montes and Rodrigo (2011) but, due to the
lack of reliable data, we could not confirm the negative
influence of maximum temperature on olive yield, as
shown by Gal
an et al. (2008).
b. Consistency between our results and local
knowledge and perception
The knowledge of local stakeholders and farmers is
partly consistent with our results on the evolution of
climate and water resources during the last decades and
on the relationships between climate and yields. The
awareness about climate issues varies according to the
two groups of interviewees. For the stakeholders, recent
changes in climate are warning signs of future climate
change. They are unanimous on that matter, while
farmers’ opinions vary according to the importance of
farm income relative to the total household income. The
large- and medium-scale farmers are the most aware of
climate change. Indeed, most of them (five out of nine)
are relying exclusively on their farming activity, while
in small farms, olive growing is a secondary activity
for five out of six farmers. Our typology is different
from Stroosnijder et al. (2008),whichisbasedon
the type of olive-growing systems; nevertheless, it
seems relevant to understand differences in farmers’
perceptions and strategies related to climate change.
TABLE A1. Codes, names, locations, availability period of rainfall or temperature, and mean annual rainfall (in mm) and temperatures
(in 8C) in the stations used in this work. The mean annual rainfall, minimal temperature (Tmin), and maximal temperature (Tmax) are
computed on the data availability period. Different sets of stations are used to analyze first the local climate (1988–2008) and second the
rainfall evolution and its relation with yields (1955–2009).
AEMET code Name
Longitude
(W)
Latitude
(N) Altitude Beginning End
Climatic
variables
Mean annual
Rainfall Tmin Tmax
5032 Iznatoraf 0380200200 3880902000 1039 1944 2009 P(mm) 400
5039 La Iruela 0285903700 3785501000 933 1955 2009 P(mm) 496
5089 Pozo Alcon 0285500700 3784603000 1020 1911 2009 P(mm) 568
5138 Cabra de Santo Cristo 0381701700 3784201000 938 1985 2009 P(mm)/T(8C) 402 9.7 22.2
5149 Belmez de la Moraleda 0382204700 3784303000 887 1985 2009 P(mm) 543
5163 Jimena 0382803700 3785003000 590 1950 2009 P(mm)/T(8C) 516 12 19.8
5165 Torres 0382905700 3784602000 1030 1985 2009 P(mm) 587
5169 Jaen Los Racioneros 0383701700 3785605000 260 1945 2009 P(mm) 496
5220 Canena 0382805200 3880205000 546 1955 2009 P(mm)/T(8C) 540 12 22.7
5252 Linares, Torrubia 0383904700 3880101500 290 1945 2009 P(mm)/T(8C) 544 10 24.3
5255 Campillo de Arenas
(B. Monasterio)
0383805700 3783505000 1160 1985 2009 P(mm) 672
5263 Pegalajar 0383805500 3784401700 827 1985 2009 P(mm) 509
5266 La Guardia de Jaen 0384102700 3784403000 645 1985 2009 P(mm) 403
5271 Torre del Campo 0385305200 3784601800 640 1954 2009 P(mm) 642
5272 Torre del Campo
(el termino)
0385102700 3784901000 460 1956 2009 P(mm) 494
5334 Higuera de Arjona 0385902700 3785802000 380 1985 2009 P(mm) 485
5349 Arjona ‘‘Santo Tomas’’ 0480901700 3785800000 340 1955 2009 P(mm) 544
5418 Valdepenas de Jaen 0384900200 3783501500 927 1944 2009 P(mm) 764
7045 Pontones C. H. Segura 0284001100 3880701300 1350 1934 2009 P(mm)/T(8C) 900 3.5 17.5
7054 Salto de Miller 0282703500 3881301800 750 1961 2009 P(mm)/T(8C) 597 7.3 20.6
7056 Santiago de la Espada 0283301000 3880604400 1340 1934 2009 P(mm) 757
5166A Torres 0383003200 3784701000 885 1978 2009 P(mm) 568
5166i Baeza (las Escuelas) 0383004200 3785202000 535 1989 1993 T(8C) 11 22.8
5171A Villatorres-Villargordo 0384303700 3785603500 345 1974 2009 P(mm)/T(8C) 428 11 24.7
5180E Beas de Segura (Las
Perales)
0285202700 3881702000 345 1974 2009 T(8C) 8.6 20.8
5250O Lupion 0383205000 3785905300 503 1983 2009 P(mm) 459
5262B Pegalajar
(la Cerradura)
0383801700 3784103200 560 1977 2009 P(mm) 451
5269A Los Villares 0384805600 3784101700 640 1950 2009 P(mm) 547
5270A Jaen (CHG) 0384701700 3784600000 570 1985 2009 P(mm)/T(8C) 497 11 22.8
5279U Linares ‘‘Vor’’ 0383705700 3880902500 520 1974 2009 T(8C) 11 22.8
5330A Torredonjimeno 0385702500 3784505400 591 1956 2009 P(mm)/T(8C) 612 abs 21.7
5334B Higuera de Aarjona 0385903400 3785803700 360 1985 2009 P(mm) 460
394 WEATHER, CLIMATE, AND SOCIETY VOLUME 6
Differences in local climate and agricultural systems do
not seem to explain the farmer’s views, contrary to the
findings of other authors (Diggs 1991;Australian Bureau
of Statistics 2009;Seres 2010;Merot et al. 2012). A larger
survey would be useful to confirm this result.
c. Is past experience useful for adaptability to future
climate change?
In our study, the experience of declining rainfall
(after 1979) and of drought (mid-1990s, 2005) does not
always ‘‘solidify people’s perception about certainty of
[future climatic] change,’’ as found by Diggs (1991,
p. 129). The farmers base their interpretations of
the recent climatic changes on their own experience
and on the limited information they have. This could be
the reason for their low degree of awareness—or even
skepticism—about future climate change, particularly
among the small-scale farmers who represent the largest
group overall. Most stakeholders also refer to their own
experience of climate change, but their awareness may be
explained by a better access to information.
Stakeholders and some of the farmers view drip irri-
gation as the technique that ‘‘saved’’ the olive yields
after the long-lasting drought in the mid-1990s. Indeed,
the relatively high yields of irrigated olive groves during
the period 1993–95 is seen as convincing evidence of the
usefulness of irrigation. Two decades later, as shown by
our results and other authors’ (G
omez-Lim
on et al.
2012;Lopez-Gunn et al. 2012), drip irrigation is not as
effective at increasing yields as expected. Some farmers
have always known about the dependence of irrigated
groves on rainfall, but other farmers and all the stake-
holders still believe in irrigation. Those farmers interviewed
appeared to be less aware than stakeholders about the
decline of water resources.
According to Heltberg et al. (2009) ‘‘climate change
will cause some climatic variables to deviate from their
historical range [...]. Traditional approaches to decision
making in risky climates based on communities’ historic
experience could lose value’’ in the future.
This seems to be the case in Sierra M
agina. Past expe-
rience is not a valuable asset in formulating future adap-
tation strategies. During the 1990s, after the decline of
groundwater resources, irrigation benefited from the pos-
sibility of exploiting surface water; now all the water re-
sources, from the ground and from the rivers, are already
divided between users. In addition the European subsidies,
a substantial support in past times, are decreasing. More-
over, if local farmers are connecting olive growing to the
climate influence on yields, their perception of past climate
still depends on personal interpretations, which obviously
remains diverse. Our companion paper (Part II) discusses
the paradoxical relationships between climate predictions,
their consequences for water resources, and olive yields
and farmers’ doubts about climate change.
Acknowledgments. We thank the French Scientific
Interest Group (GIS) Climate, Environment, and Soci-
ety (CNRS, CEA, UVSQ, UPMC, Ecole Polytechnique,
and ADEME) for the financial support it brought to
the Regyna (regionalization of rainfall and hydrological
and agronomical impacts) program. Benjamin Sultan
TABLE A2. Significance of statistical tests.
(a) Irrigated yield vs rainfall
Value Standard error T statistics P
b21393.245 84 319.659 457 24.358 531 58 0.000 159 63
a 1.226 638 97 0.279 371 57 4.390 707 97 0.000 146 27
Variance analysis
Degree of freedom Sum of squares F P
Regression 1 2 383 596.05 19.278 316 5 0.000 146 27
Residuals 28 3461 956.31
Total 29 5845 552.36
(b) Rainfed yields vs rainfall
Value Standard error T statistics P
b21817.384 87 373.625 051 24.864 194 37 4.0204 310
25
a 1.605 405 09 0.326 535 68 4.916 476 86 3.4849 310
25
Variance analysis
Degree of freedom Sum of squares F P
Regression 1 4 082 896.89 24.171 744 7 3.4849 310
25
Residuals 28 4729 535.01
Total 29 8812 431.9
JULY 2014 C O H E N E T A L . 395
(French Institute for Research and Development, IRD,
and the Laboratory of Oceanography and Climate,
Locean) coordinated this program and incentivized our
participation. The UMR Ladyss and the University
Paris Diderot (Erasmus Program) have also provided
financial support.
We would also like to thank the DPO Sierra M
agina,
Larva and Bedmar’s city hall, AEMET, MAGRAMA,
and the Agriculture Secretary of Ja
en for the data pro-
vision and the farmers’ generous contribution. Thanks
also to the researchers, Alia Gana, Philippe Boudes,
Catherine Darrot (UMR Ladyss), Benjamin Sultan
(UMR Locean), Vincente Jos
e Gallego-Simon (Uni-
versidad Internacional de Andaluc
ıa), Jos
eDomingo
Sanchez-Martinez (Universidad de Ja
en), and Pascal
Oettli (Locean), and the master students who con-
tributed to this work: Joelle Salam
e (University of
Paris Diderot, 2010) and Imanol Sinde (Agro-
ParisTech, 2012). Thanks to Milena Palibrk and the
P^
ole Image for the technical support and to Corinne
Blostin, Arnaud Apoteker, and colleagues for their
help for the English language. Finally, we are very
grateful to the reviewers who helped us to improve and
to edit the manuscript.
APPENDIX
Station Data and Significance Tables
Codes, names, locations, availability period of rain-
fall or temperature, and mean annual rainfall (in mm)
and temperatures (in 8C) in the stations used in this
work (Table A1) and the significance of statistical tests
(Table A2).
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