Article

Reproduction of olive tree habitat suitability for global change impact assessment

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Abstract

The olive tree is so typical of the Mediterranean climate that its presence in a territory qualifies the climate of this as Mediterranean. Many clues indicated that in the past olive cultivation limits moved northward or southward in the Northern Hemisphere according to warmer or cooler climate, respectively. This makes the olive tree cultivation area a possible biological indicator of changes in climate and the identification of the climatological parameters that limit its cultivation plays an important role for climate change impact assessment. In this work, three different approaches were compared, with the aim to compare methodologies suited to predict olive tree distribution over the Mediterranean basin: two classifiers (Random Forest, RF and an Artificial Neural Network, ANN) and a spatial model to infer climatic limiters of plant distribution (CLPD). These methodologies were applied within a framework including a geographical information system (GIS), which spatially defined olive tree cultivated area, and climatological informative layers (average temperature and cumulated rainfall, 50km×50km), which were used as predictor variables. The results indicated that RF achieved on the whole, the lowest classification error (113 misclassified cases on 1906 test cases) followed by ANN (128 cases) and CLPD (153 cases). A validation test, performed over areas out of the Mediterranean basin where olive tree is cultivated (i.e. California and Southern Australia), confirmed the goodness of the RF fitted model in predicting olive tree suitable areas. In general, climatic predictor variables of the coldest and warmest periods of the year were the most significant in determining the limits of suitable olive cultivation area for these methodologies. In particular, temperature of January and July and rainfall of October and July were the climatic predictor variables having highest significance for both RF and ANN. Temperature of January >2°C, of July >20°C and cumulated annual rainfall >240mm were the bounds found in the spatial model. The fitted RF model, coupled with the results of both Regional and General Circulation Model, was finally proposed to assess climate change impact on olive tree cultivated area in the Mediterranean basin.

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... Global warming is expected to affect the phenology dates of plants, particularly olives Bonofiglio et al., 2008;García-Mozo et al., 2010;Oteros et al., 2013). There is an overall trend of earlier occurrence of key phenological events such as flowering and a consequent shortening of the crop growth phases (Osborne et al., 2000;Giannakopoulos et al., 2009;Moriondo et al., 2008Moriondo et al., , 2010García-Mozo et al., 2010). This advance of phenological phases is more evident in arboreal than in herbaceous crops (García-Mozo et al., 2010) resulting in a shorter time for biomass accumulation and yield formation (Bindi et al., 1996;Olesen et al., 2011). ...
... They concluded that with the further temperature rise it could be necessary to introduce new varieties with lesser chilling requirements; otherwise, it would be required to move production into other areas with lower temperature. In fact, due to the changes in temperature and precipitation patterns, the area climatically suitable for olive cultivation could be enlarged northwards and to higher altitudes, thus increasing the range of areas suitable for olives into new areas of France, Italy, the Balkans and the northern Iberian Peninsula (Bindi et al., 1992;Bindi and Howden, 2004;Moriondo et al., 2008;Gutierrez et al., 2009). ...
... The areas suitable for olive cultivation in the Mediterranean region are presented in Fig. 4 for years 2000 and 2050. Results for present scenario were compared with the present suitability map elaborated by Moriondo et al. (2008). Differences were small and they were due to the fact that these authors used the mean temperature of 2 • C in January (the coldest month) as threshold for olives cultivation whereas, in the present study, this threshold was reduced to 0 • C. Results of the present study showed that the area climatically suitable for growing olives, about 39% of the total area of the region in 2000, could increase to almost 50% in 2050. ...
Article
The Mediterranean basin is the largest world area having specific climatic conditions suitable for olive cultivation, which has a great socio-economic importance in the region. However, the Mediterranean might be particularly affected by climate change, which could have extensive impacts on ecosystems and agricultural production. This work focussed on the climate change impact on olive growing in the Mediterranean region considering the possible alterations of cultivable areas, phenological dates, crop evapotranspiration and irrigation requirements. Monthly climate data, with a spatial resolution of 0.25° × 0.25° (latitude by longitude), have been derived from Regional Climate Models driven by ECHAM5 for the A1B scenario of the Special Report on Emissions Scenarios (SRES). The data used in the analysis represented two time periods: (i) present, called year 2000 (average values for the period 1991–2010), and (ii) future, called year 2050 (average values for the period 2036–2065). The areas suitable for olive cultivation were determined using the temperature requirements approach known as the Agro Ecological Zoning method. Crop evapotranspiration and irrigation requirements were estimated following the standard procedure described in the FAO Irrigation and Drainage Paper 56. Results showed that the potentially cultivable areas for olive growing are expected to extend northward and at higher altitudes and to increase by 25% in 50 years. The olive flowering is likely to be anticipated by 11 ± 3 days and crop evapotranspiration is expected to increase on average by 8% (51 ± 17 mm season−1). Net irrigation requirements are predicted to increase by 18.5% (70 ± 28 mm season−1), up to 140 mm in Southern Spain and some areas of Algeria and Morocco. Differently, effective evapotranspiration of rainfed olives could decrease in most areas due to expected reduction of precipitation and increase of evapotranspirative demand, thus making it not possible to keep rainfed olives’ production as it is at present.
... In this perspective, the use of tree crops-and especially the olive tree-as a bio-climatic indicator has been progressively consolidated in environmental studies (Moriondo et al. 2008(Moriondo et al. , 2013. Although the spatial distribution of the olive tree in Europe is associated to a relatively well-defined latitudinal gradient, empirical evidence demonstrating a recent shift towards northern regions in the geographical range of this crop have been increasingly collected (Moriondo et al. 2008;Audsley et al. 2006;Gutierrez et al. 2009;Olesen et al. 2011;Tanasijevic et al. 2014). ...
... In this perspective, the use of tree crops-and especially the olive tree-as a bio-climatic indicator has been progressively consolidated in environmental studies (Moriondo et al. 2008(Moriondo et al. , 2013. Although the spatial distribution of the olive tree in Europe is associated to a relatively well-defined latitudinal gradient, empirical evidence demonstrating a recent shift towards northern regions in the geographical range of this crop have been increasingly collected (Moriondo et al. 2008;Audsley et al. 2006;Gutierrez et al. 2009;Olesen et al. 2011;Tanasijevic et al. 2014). These results are particularly interesting since it was demonstrated how persistent climate variations-at both regional and local scale, from single cities to larger metropolitan regions-possibly associated to land mismanagement, may drive changes in the use of land impacting vegetation cover and land quality and even transforming (e.g. ...
... If Romans have had a key role in spreading cultivation of olive grove (Moriondo et al. 2008), traces of this 'holy' plant in Greece are grounded in mythology: the goddess Athena was planting the first olive tree in the Acropolis of Athens after the father Zeus has asked her to create something who could be useful for humanity (Loumou and Giourga 2003). According to Salvati et al. (2015a, b), mythology indicated Greece as the original country of olive tree, which is a sacred plant at the point that it seems that somebody, who was caught damaging or cutting this tree, was punished through exile or death. ...
Article
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Dispersed urbanization has expanded into rural land worldwide. The present work focused on the Athens’ metropolitan area, the capital of Greece, discussing the potential role of a typical rural Mediterranean landscape dominated by olive groves, in urban containment and peri-urban conservation of biodiversity and local traditions. Having a great cultural, culinary and aesthetic importance, olive groves characterize Mediterranean peri-urban landscapes in a distinctive way. This study identifies processes of urban dispersion and changes in the ‘olive landscape’ in the study area, proposing new ideas for a sustainable land management in metropolitan contexts that have recently undergone processes of territorial transformation toward urban sprawl, under the effect of socioeconomic disturbances, including economic crisis. ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- You can read the full–text view–only version of our paper by using the link below: http://rdcu.be/HtDx
... The strong relationships of olive-growing areas with Mediterranean climate, in addition to the absence of competitive interactions with other species and the role of human intervention in reducing the time lag between spatial changes in climate and crop distribution, allow for the consideration of cultivated areas of this species as a sensible indicator of temperature change for the entire Mediterranean Basin (Moriondo et al., 2008). Moreover, in the coming decades, the olive tree will face the greatest climatic change that has been recorded since its spread into the Mediterranean Basin, and as a result its cultivated area is expected to adapt to the predicted future climate. ...
... Biogeogr.) (2013) @BULLET@BULLET, @BULLET@BULLET–@BULLET@BULLET database (CLC 2000) was used to identify those areas where olive trees are cultivated (see Moriondo et al., 2008, for details). Different sources and proxies provided evidence of past olivegrowing areas. ...
... In other words, if a GCM is able to model palaeoclimates satisfactorily, it is likely to reproduce reasonably well the expected climate in a future scenario. On these premises, the change in the area of olive cultivation during the last two millennia was used as a palaeoclimate proxy because of the tight linkage between the Mediterranean climate and olive cultivation (Moriondo et al., 2008 ). These reconstructions were compared with the results obtained from coupling the outputs of the NCAR-CSM palaeo-GCM to a simple climate-based ecological model to describe the changes in olivegrowing areas across the Mediterranean Basin during the last millennium. ...
Article
Aim This paper aims to project areas of olive cultivation into future scenarios. Accordingly, we first asked the question whether global circulation models (GCMs) are able to reproduce past climatic conditions and we used historical ranges of olive cultivation as a palaeoclimate proxy. Location The Mediterranean basin. Methods We used an ecological model, calibrated and validated for modern times, to test the reliability of a general circulation model (NCAR-CSM GCM) in reproducing past ranges of olive tree cultivation inferred from the literature, archaeo-botanical investigations and fossil pollen analyses. Results The re-constructions of olive growing areas, obtained for the Medieval Climate Anomaly (MCA, 1200-1300 AD) and the Little Ice Age (LIA, 1600-1700 AD) by coupling the outputs of NCAR-CSM to the ecological model, were in agreement to those observed. Simulations of olive growing areas for future time-windows showed that a northwards expansion of the species is expected to occur by 2100. Main conclusions These results demonstrate that the NCAR-CSM can provide an accurate reconstruction of past climate with results sensitive to climate forcing factors and thus, it is more likely to give reliable projections for the future. Additionally, the warming and drying conditions expected in the coming decades may determine changes across the Mediterranean basin that is unprecedented.
... Moreover, models have resulted robust and reliable to elaborate vegetation maps on a large scale-basis, as well as to assess the response of plant species to climate change (Gottfried et al., 1999;Latimer et al., 2006;Austin, 2007). Several statistical models have been applied to map climaterelated plant suitability (Guisan and Theurillat, 2000), and amongst them, machine learning models have proved good performances (Moriondo et al., 2008;Casalegno et al., 2011;Gaál et al., 2012;Moriondo et al., 2013aMoriondo et al., , 2013b. Moreover, several authors recommended random forest (RF) machine learning model for ecological and species distribution modelling applications (Prasad et al., 2006;Araùjo and Luoto, 2007) also at large scale extents (Prentice et al., 1992;Thuiller et al., 2008;Casalegno et al., 2011) because its characteristics of bootstrap-resampling, tree averaging and randomisation of predictors on big dataset (Attorre et al., 2011). ...
... The machine learning predictive model RF (Breiman, 2001) was employed for reproducing current pasturelands suitability and for assessing future climate impacts on the distribution of natural grasslands across the Apennine chain. RF consists of a combination of a large ensemble of decision tree classifiers widely used in ecological studies (Latimer et al., 2006;Evans and Cushman, 2009;Casalegno et al., 2011) especially for predicting climate changes effects on species distribution (Moriondo et al., 2008;Attorre et al., 2011;Moriondo et al., 2013aMoriondo et al., , 2013b. In RF, each classifier is generated using a bootstrap sample, which is randomly split into two subsets, one used for training (66%) and one for internal testing (33%, out-of-bag sample, OOB). ...
Article
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This work aims at evaluating the impacts of climate change on pastoral resources located along the Apennines chain. To this end, random forest machine learning model was first calibrated for the present period and then applied to future conditions, as projected by HadCM3 general circulation model, in order to simulate possible spatial variation/shift of pastoral areas in two time slices (centred on 2050 and 2080) under A2 and B2 SRES scenarios. Pre-existent spatial database, namely Corine land cover map and WorldClim, were integrated and harmonised in a GIS environment in order to extract climate variables (mean seasonal precipitation, mean maximum temperature of the warmest month and minimum temperature of the coldest month) and response variables (presence/absence of pastures) to be used as model predictors. Random forest model resulted robust and coherent to simulate pastureland suitability under current climatology (classification accuracy error=19%). Accordingly, results indicated that increases in temperatures coupled with decreases in precipitation, as simulated by HadCM3 in the future, would have impacts of great concern on potential pasture distribution. In the specific, an overall decline of pasturelands suitability is predicted by the middle of the century in both A2 (–46%) and B2 (–41%) along the entire chain. However, despite alarming reductions in pastures suitability along the northern (–69% and –71% under A2 and B2 scenarios, respectively) and central Apennines (–90% under both scenarios) by the end of the century, expansions are predicted along the southern areas of the chain (+96% and +105% under A2 and B2 scenarios, respectively). This may be probably due to expansions in pastures dominated by xeric and thermophiles species, which will likely benefit from warmer and drier future conditions predicted in the southern zone of the chain by the HadCM3. Hence, the expected climate, coupled with an increasing abandonment of the traditional grazing practices, will likely threat grassland biodiversity as well as pastoral potential distribution currently dominating the Apennines chain.
... The olive tree is a domestic variety of the wild olive (e.g. Breton, Medail, Pinatel, & Berville, 2006;Kaniewski et al., 2012;Moriondo, Stefanini, & Bindi, 2008), an abundant fruiting tree in the original vegetation, and it has been demonstrated that small olive groves interspersed in the montado matrix can have a positive impact on several taxa, including carnivores and birds (e.g. Leal, Martins, Palmeirim, & Granadeiro, 2011;Rosalino, Rosário, & Santos-Reis, 2009). ...
... The relevant criteria were based on the present distribution of the two habitats in southern Iberia and on the literature (e.g. Aguiar, Cerdeira, Martins, & Ferreira;Duarte et al., 2008;Moriondo et al., 2008). Multi-criteria models that consider simultaneously all relevant descriptors were developed using the fuzzy MCE module in Idrisi (v.15.01 Andes, Clark University, Worcester, MA, USA). ...
Article
Agro-silvo-pastoral systems occupy much of the Mediterranean region. Promoting landscape heterogeneity in these systems is a potentially valuable management strategy to enhance woodland biodiversity. We evaluated the effects on birds of managing patches of olive groves and riparian galleries to promote heterogeneity of these systems in Portugal.For a large cork oak woodland we (i) used nesting season bird density estimates and habitat descriptors to generate suitability models for each studied species; (ii) identified areas suitable to establish new patches of riparian galleries and olive groves, and used this information to (iii) generate scenarios maps with different levels of cover of both habitats. Finally, (iv) the model of each bird species was applied over the future scenarios to estimate potential changes in its distribution and abundance.Future scenarios with greater availability of riparian vegetation resulted in major increases in projected populations of seven of the 21 studied species, but gains with increases of olive groves were predicted in just three species. Bird species predicted to increase the most with the recovery of riparian vegetation are presently among the least abundant in the region. Restoring riparian galleries would be highly beneficial for birds, whereas promoting traditional olive groves would have lower conservation implications.The methodology used proved helpful to select areas particularly appropriate for habitat management, generate simulated landscapes incorporating this management, and predict the population and spatial responses of species to these simulated scenarios, thus having a good potential to guide conservation management. Moreover, our results indicate that simple management measures should have substantial positive effects on the bird community of oak woodlands, without compromising the essential economic return of the system.
... In this scenario, the olive phenology may provide useful indications to evaluate the influence of climate change on plant growth for the whole Mediterranean region, since the geographical limits of this cultivation approximately delimit the extent of the Mediterranean climate in Eurasia and North Africa [11,12]. Since the different olive varieties are adapted to specific climatic, edaphic, and lithological conditions, the possible variations occurring in a climate change scenario would have a significant impact on the distribution of these varieties and, consequently, on their growth and productivity [13,14]. This is especially expected for some old varieties cultivated in narrow geographic niches with specific micro-climatic characteristics [15]. ...
... In this scenario, the Campania region in Italy has already experienced an increase in minimum temperatures of approximately 1.4 • C from 2005 to 2017 [43]. This situation, in agreement with research showing a dramatic global warming since the 1980s [13,44], poses concerns regarding the impact that climate change can have also on restricted geographical areas such as that of the Campania region. ...
Article
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Olea europaea L. is a crop typical of the Mediterranean area that has an important role in economy, society, and culture of this region. Climate change is expected to have significant impact on this crop, which is typically adapted to certain pedo-climatic characteristics of restricted geographic areas. In this scenario, the aim of this study was to evaluate the time-course response of pollen viability to different combinations of temperature and humidity. The study was performed comparing flowering time and pollen functionality of O. europaea from twelve cultivars growing at the same site belonging to the Campania olive collection in Italy. Pollen was incubated at 12 °C, 22 °C, and 36 °C in combination with 50% RH or 100% RH treatments for 5 days. The results highlighted that a drastic loss of pollen viability occurs when pollen is subjected to a combination of high humidity and high temperature, whereas 50% RH had less impact on pollen thermotolerance, because most cultivars preserved a high pollen viability over time. In the ongoing climate change scenario, it is critical to assess the effect of increasing temperatures on sensitive reproductive traits such as pollen viability to predict possible reduction in crop yield. Moreover, the results highlighted that the effect of temperature increase on pollen thermotolerance should be evaluated in combination with other environmental factors such as humidity conditions. The screening of olive cultivars based on pollen thermotolerance is critical in the ongoing climate change scenario, especially considering that the economic value of this species relies on successful fertilization and embryo development, and also that production cycle of Olea europaea can be longer than a hundred years.
... Leur grande connaissance dans l'écologie des espèces et de leur distribution a 11 permis de définir des critères pour formaliser des représentations de l'ECM. Olea europaea est 12 cultivé sur le bassin méditerranéen depuis six millénaires (Moriondo et al. 2008). Son aire de 13 distribution a été délimitée par Moriondo et al. (2008.) ...
... Olea europaea est 12 cultivé sur le bassin méditerranéen depuis six millénaires (Moriondo et al. 2008). Son aire de 13 distribution a été délimitée par Moriondo et al. (2008.) Notre proposition d'approche multicritère de l'enveloppe climatique méditerranéenne en 7 saisonnalité flottante permet : 8  une adaptation de la limite nord des territoires considérés comme méditerranéens par 9 l'indice de sécheresse S de Daget (1977b) ...
... Numerous studies have demonstrated that reproductive phenology is an important and useful indicator of the impact of climate change Moriondo et al., 2013). The olive flowering period is considered a good bio-indicator for global warming, mainly due to its dependence on temperature and to its geographical distribution over one of the most high-risk areas for global warming on the Earth (Moriondo et al., 2008;Orlandi et al., 2014a;Osborne et al., 2000). However, there are rarely long time series of data available that can be used to detect significant phenological changes. ...
... To our purposes, an important feature of the RF algorithm is the variable importance, which is a natural output of the procedure and measures the deterioration of the predictive ability of the model when each predictor is replaced in 5 turn by random noise. This method has been extensively used in bibliography in a variety of applications ranging from bioinformatics (Díaz-Uriarte and De Andres, 2006) to remote sensing (Pal, 2005;Gislason et al., 2006;Ghimire et al., 2010) and ecology (Cutler et al., 2007;Peters et al., 2007;Moriondo et al., 2008) just to mention an, incomplete, list of applica-10 tion fields. For what concerns mapping of landslides, this method was used by Stumpf and Kerle (2011a, b), who used the RF technique to implement an automatic landslide inventory mapping on the basis of very high resolution remote sensing imagery. ...
Article
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We present a quantitative indirect statistical modeling for predicting rainfall-induced shallow landsliding. We consider as input layers both static thematic predictors, such as geomorphological, geological, climatological information, and numerical weather model's forecast. Two different statistical techniques are used to combine together the above mentioned predictors: a Generalized Linear Model and Breiman's Random Forests. We tested these two techniques for two rainfall events that occurred in 2011 and 2013 in Tuscany region (central Italy). Model's evaluation is measured by means of sensitivity-specificity ROC analysis. In the 2011 rainfall event, the Random Forests technique performs slightly better, whereas in the 2013 rainfall event the Generalized Linear Model provides more accurate predictions. This study seeks also to establish whether the rainfall-induced shallow landsliding prediction might substantially benefit from the information provided by the numerical weather model's outputs. Using the variable importance parameter provided by the Random Forests algorithm, we asses the added value carried by numerical weather forecast, in particular in the rainfall event characterized by deep atmospheric convection and heavy precipitations.
... Given that the reproductive phenology of the olive tree in the Mediterranean area is regulated by the meteorological parameters related to the previous autumn, winter, and spring seasons, the olive can be considered as a sensitive indicator of the biological impact of future climate change. In this sense, the present study adds further support to other studies that have indicated that olive phenology is a good and useful bio-indicator of future climate change, mainly through its dependence on temperature and through its geographical distribution over one of the most high-risk warming areas on the Earth García-Mozo et al. 2008;Giorgi and Lionello 2008;Moriondo et al. 2008;Orlandi et al. 2014;Osborne et al. 2000;Vergni and Todisco 2011). ...
Article
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The aim of the present study was to develop pheno-meteorological models to explain and forecast the main olive flowering phenological phases within the Mediterranean basin, across a latitudinal and longitudinal gradient that includes Tunisia, Spain, and Italy. To analyze the aerobiological sampling points, study periods from 13 years (1999-2011) to 19 years (1993-2011) were used. The forecasting models were constructed using partial least-squares regression, considering both the flowering start and full-flowering dates as dependent variables. The percentages of variance explained by the full-flowering models (mean 84 %) were greater than those explained by the flowering start models (mean 77 %). Moreover, given the time lag from the North African areas to the central Mediterranean areas in the main olive flowering dates, the regional full-flowering predictive models are proposed as the most useful to improve the knowledge of the influence of climate on the olive tree floral phenology. The meteorological parameters related to the previous autumn and both the winter and the spring seasons, and above all the temperatures, regulate the reproductive phenology of olive trees in the Mediterranean area. The mean anticipation of flowering start and full flowering for the future period from 2081 to 2100 was estimated at 10 and 12 days, respectively. One question can be raised: Will the olive trees located in the warmest areas be northward displaced or will they be able to adapt their physiology in response to the higher temperatures? The present study can be considered as an approach to design more detailed future bioclimate research.
... Pero tienen como gran desventaja que operan como cajas negras, por lo que no se pueden examinar las relaciones causa efecto. Sí se ha aplicado a la distribución de plantas en algunos trabajos, como Harrison et al. (2006) y Moriond et al. (2008). ...
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Tesis Univ. Granada. Departamento de Botánica. Leída el 16 de octubre de 2009
... Climatic changes and agronomic tools are creating opportunities for olive growing in new areas (Bindi, Ferrini, & Miglietta, 1992;Moriondo, Stefanini, & Bindi, 2008) generating novel local markets. The majority of consumers surveyed, aware of living in a territory not traditionally associated with EVOO production, were interested in consumption of locally produced oil. ...
Article
This study investigates consumer attitude towards local virgin olive oil production and examines associations between consumer preference and sensory evaluations carried out by a trained panel. The panel evaluated four extra virgin olive oils in terms of descriptors such as bitter, pungent and fruity. Consumers demonstrated a high level of interest in locally produced oil and expected it to score low for bitterness and pungency. Participants were segmented into clusters, having first been asked to declare their liking-drivers, choosing between low- or high-fruity intensity and low- or high-bitter-pungent intensity. Having tasted the oils, consumers were requested to provide hedonic scores and to judge oil quality. Those consumers who expressed a preference for olive fruitiness did not generally score in accordance with its intensity, as assessed by the expert panel. The bitter-pungent attribute appears be a more suitable characteristic for determining consumer preference. These results may prove useful in orienting local production towards the real expectations and preferences of consumers.
... More recently, to overcome these limits, risk assessment models based on the effect of bioclimatic variables in relation to agro-habitat cultivation have become more popular (Barney and Di Tomaso, 2010). These models were also applied, to good effect, to cultivation in the Mediterranean area (Moriondo et al., 2008). Models based on bioclimatic variables were also applied to the assessment of quality loss risk in wine production Jones, 2006). ...
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Climate change is expected to have a significant impact on various economic sectors (IPCC, 2007) but an especially large one on agriculture because animal and crop growth are heavily influenced by weather conditions during their life cycles. In this paper, a multidisciplinary approach is developed that jointly uses economic and bio-climate models to evaluate the impact of climate change on viticulture in Tuscany (central Italy). Then a model is used to evaluate the likelihood of adoption of various adaptation strategies.
... Nell'ultimo ventennio si è, però, assistito a un'espansione verso nord dell'olivo -sostenuta dal favorevole regime dei prezzi dell'olio extra vergine di oliva, l'ottenimento di un prodotto di buona qualità e, forse, il cambiamento globale del clima (Moriondo et al. 2008) sin'ora frenata dal verificarsi, con cadenza pressoché ventennale, di imponenti danni da gelo che, nel passato, hanno richiesto la completa ricostituzione di molti impianti (Foto 2 e 3). ...
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The olive grove is the major portion of Mediterranean landscape mosaic. The dominance of olive cropping on agricultural space, the plant framework and the productive structure’s longevity are just a few of the features rendering the olive tree symbol of heritage and cultural identity in the Mediterranean area. High levels of environmental value in terms of animal and vegetal biodiversity are found in low input olive agro-ecosystems, as a natural ecosystems mimic. The CAP (Common Agricultural Policy) Health Check 2009 ascribes to agriculture the multifunctional attribute and the role of landscape guardian, identifying in farms the most active actors in producing no food services such as agro-ecosystem conservation and restoration, land marketing and local productions. Trades, economic policies and land planning decisions in last decades influenced and determined the evolution of most of rural lands, naturally dynamic, to abandon practices or land degradation. The need to protect landscapes, as well as farmlands has became urgent. However, some of the actual landscape management plans are regarded as conflicting with the most important goal of agriculture: the production. The olive groves landscape protection, such as of all the rural landscapes, must be reached bounding different and sometimes opposite needs, linked to the environment protection through conservation and to the structural changes in farming and in turn in landscaping driven by farmers initiative. Planning a systematic and synergic action between public, as landscape conservation, and private interest, as farmer’s goals, is imperative to support and enhance land management.
... Moreover, woodlands with wild olives are a key element of natural landscapes and were associated to high biodiversity, aesthetic beauty, and important ecosystem services such as the protection from soil erosion (Gomez et al. 2009). It was hypothesized that the northern range of the olive tree, both as cultivated and wild species, is currently shifting towards the north in the Mediterranean basin (Moriondo et al. 2008). The present study explores this phenomenon in Italy during the last twenty years by using statistical data and analysis of bibliographic sources. ...
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Decreasing rainfall, climate aridity and severe droughts have become, in the last years, global issues due to their economic, social, and ecological implications. Empirical evidence suggest that the Mediterranean basin is an hotspot for climate variations. This study discusses the use of the olive tree, a typical Mediterranean crop, as a bio-climatic indicator. The distribution of the olive tree showed a well-defined latitude gradient progressively reducing in density towards north. Due to climate variations, however, there are evidence on a shift towards north in the geographical range of this crop. The present study analyzes the spatial distribution of the olive cultivated area in Italy with a special focus on northern Italy. Results indicate that olive cultivated area increased in northern Italy especially in lowland and middle upland areas while decreasing in both central and southern Italy. The highest increase was observed during 1992-2000 after recurrent winter drought and local warming. The article discusses the implications of the illustrated range shift and a possible landscape scenario for the coming future.
... Olive (Olea europaea L.) is one of the most ancient cultivated fruit trees in the Mediterranean basin (Zohary and Spiegel Roy, 1975; Moriondo et al., 2008; Villalobos et al., 2012) where it plays a fundamental role by integrating agriculture, environment and landscape into a complex system. Although in recent years olive trees have been cultivated successfully in countries such as California, Australia, Argentina and South Africa (De Graaff and Eppink, 1999), olive is mainly grown in the Mediterranean area and dominates its rural landscape (Loumou and Giourga, 2003). ...
... Tuscany is situated between 9–12 @BULLET East longitude and 42–44 @BULLET North latitude and is administratively divided into ten provinces (Fig. 1). The region, which coincides with the Northern limit of olive tree cultivation in Italy (Moriondo et al., 2008), shows very heterogeneous morphological and land cover features and is therefore suitable to test the applicability of the proposed methodology. Its climate ranges from Mediterranean to temperate warm or cool following the altitudinal and latitudinal gradients and the distance from the sea (Rapetti and Vittorini, 1995). ...
Article
The current paper presents the development and testing of a multi-step methodology which integrates remotely sensed and ancillary data to estimate olive (Olea europaea L.) fruit yield in Tuscany (Central Italy). The processing of very high resolution (Ikonos) and high resolution (Landsat ETM+) images provides a map of olive tree canopy cover fraction for all Tuscany olive yards, which is used to extract olive tree NDVI values from MODIS imagery. The combination of these values with standard meteorological data within a modified parametric model (C-Fix) enables the prediction of daily olive tree gross primary production (GPP) for ten years (2000–2009). These GPP estimates are then joint to the respiration estimates of a bio-geochemical model (BIOME-BGC) to simulate olive tree net primary production (NPP). The NPP accumulated over proper periods of the ten growing seasons is finally converted into olive fruit yield, whose accuracy is assessed through comparison with provincial statistics. The methodology is only partly capable of capturing spatial and temporal olive fruit yield variability at province level, but can accurately reproduce inter-year yield variation over the entire region. The paper concludes with a discussion of the results achieved and with considerations on the research prospects.
... In this paper a set of widely used viticultural climatic indices were used to analyse the spatial distribution of the Hungarian wine regions. This process was performed by Random Forest, a machine learning approach, which has been demonstrated to be one of the most promising techniques for ecological classification (Cutler et al., 2007; Moriondo et al., 2008, Evans et al., 2011). This approach allowed identifying the potential shift/contraction of the wine regions according to the expected climate change. ...
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This paper aims to simulate and analyse the impact of climate change on the Hungarian wine regions using spatial layers of temperature-based bioclimatic indices. Random forest classification was used to analyse the similarities between the present and future climate of the wine regions. The model was firstly calibrated for the present period then applied for the expected future climatic conditions simulated by the RegCM3 model with A1B scenario. Results show that in the near future (2021-2050) the grapevine regions typical of the southern may expand in greater part of the country, while at the end of the century (2071-2100) only the northern part of the country shows some similarities with the present climate. Despite these results, Hungary is expected to remain amongst the regions with good quality grapevine growing conditions, but the structure of the cultivation and/or varieties should be changed.
... Currently, olive culture spreads gradually in many non-Mediterranean regions with variable altitudes (Gutierrez, Ponti, & Cossu, 2009). In addition, climate warming, low rainfall and soil salinity are becoming the principal environmental problems for the olive industry (Jemai et al., 2009) and will drive olive tree cultivation to frost-free northern and high altitude areas (Gutierrez et al., 2009;Moriondo, Stefanini, & Bindi, 2008). Although the antioxidant activity of oil olive phenolics has been under constant research for many years, the properties of table olives phenolics have not been studied to an equal extent. ...
Article
The antioxidant ability of phenolic extracts of olive fruits during maturity in Chondrolia and Amfissis cultivars grown at 10 m and 300 m altitude showed that altitude affected phenol content, antioxidant and Fe2+/Fe3+ reduction/binding ability. The hydroxyl radical, peroxyl radical and peroxynitrite-induced DNA nicking assays have been used to evaluate the anti-radical activity of the extracts. Results showed that the ability of olive extracts to prevent radical-mediated DNA damage arises from the triple synergistic action of the genotype, the altitude and the maturation stage.
... (72); FAO (Food and Agriculture Organization of the United Nations) Agro-MAPS (http://kids.fao.org/agromaps/) and GAEZ data (Global Agro-Ecological Zones; see http://gaez.fao.org/); published data and printed maps of olive distribution (e.g., 95,96,129). The M3-Crops data for yield are representative of the year 2000, and proved crucial for estimating the distribution in the southern Mediterranean Basin where Corine data for olive were not available. ...
Article
Full-text available
The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests.
... We drew our data from research on wheat (Karamanos et al., 2008) (2000), Li et al. (2000), Pleijel et al. (2000), Bindi et al. (2001), Kimball et al. (2002), Kimball et al. (2007) and Taub (2010). In the cases where the AquaCrop model was not used (vegetables, tree crops, etc.) we used earlier research results (Mortensen, 1994;Rosenzweig et al., 1996;Kimball and Idso, 2001;Olesen and Bindi, 2002;Chartzoulakis and Psarras, 2005;Kimball et al., 2007;Garnaut, 2008;Moriondo et al., 2008;Ventrella et al., 2008;Gutierrez et al., 2009;Moretti et al., 2010;Orduna et al., 2010). The results obtained for Scenarios Α1Β, Α2 and Β2 for the periods 2041-2050 and 2091-2100 compared to baseline period 1991-2000 are presented in Table 2.28. ...
... Currently , olive culture spreads gradually in many non-Mediterranean regions with variable altitudes (Gutierrez, Ponti, & Cossu, 2009). In addition, climate warming, low rainfall and soil salinity are becoming the principal environmental problems for the olive industry (Jemai et al., 2009) and will drive olive tree cultivation to frost-free northern and high altitude areas (Gutierrez et al., 2009; Moriondo, Stefanini, & Bindi, 2008 ). Although the antioxidant activity of oil olive phenolics has been under constant research for many years, the properties of table olives phenolics have not been studied to an equal extent. ...
... This region, including districts with intensive farming systems, has traditionally shown a wet, temperate alpine mixed climate, with mild and wet summers and temperate continental winters, having fog, snow and late freezing as basic characteristics of the cold season [83][84][85][86]. By hypothesizing the northern Mediterranean range of the olive tree moving progressively toward the north as a possible response to climate warming [87], our study provides empirical data contributing to delineating such a relationship in Northern Italy, a suboptimal region for olive cropping and one of the less suitable districts in Southern Europe because of the dominance of a temperate continental (non-Mediterranean) climate regime. Northern Italy-and more specifically, the area encompassing the Alps to the north and the Apennines to the south-includes seven administrative regions of the country (from west to east, Piedmont, Aosta Valley, Lombardy, Trentino Alto Adige, Veneto, Friuli Venezia Giulia and Emilia Romagna), displaying an evident (climatic) gap with the rest of Italy (Central and Southern regions), which are considered a traditional part of the geographical range of olive trees. ...
Article
Full-text available
Climate change leverages landscape transformations and exerts variable pressure on natural environments and rural systems. Earlier studies outlined how Mediterranean Europe has become a global hotspot of climate warming and land use change. The present work assumes the olive tree, a typical Mediterranean crop, as a candidate bioclimatic indicator, delineating the latent impact of climate aridity on traditional cropping systems at the northern range of the biogeographical distribution of the olive tree. Since the olive tree follows a well-defined latitude gradient with a progressive decline in both frequency and density moving toward the north, we considered Italy as an appropriate case to investigate how climate change may (directly or indirectly) influence the spatial distribution of this crop. By adopting an exploratory approach grounded in the quali-quantitative analysis of official statistics, the present study investigates long-term changes over time in the spatial distribution of the olive tree surface area in Northern Italy, a region traditionally considered outside the ecological range of the species because of unsuitable climate conditions. Olive tree cultivated areas increased in Northern Italy, especially in flat districts and upland areas, while they decreased in Central and Southern Italy under optimal climate conditions, mostly because of land abandonment. The most intense expansion of the olive tree surface area in Italy was observed in the northern region between 1992 and 2000 and corresponded with the intensification of winter droughts during the late 1980s and the early 1990s and local warming since the mid-1980s. Assuming the intrinsic role of farmers in the expansion of the olive tree into the suboptimal land of Northern Italy, the empirical results of our study suggest how climate aridity and local warming may underlie the shift toward the north in the geographical range of the olive tree in the Mediterranean Basin. We finally discussed the implications of the olive range shift as a part of a possible landscape scenario for a more arid future.
... This implies that the frequency of extreme temperatures during flowering is not expected to increase significantly. Some studies suggest a gradual northward shift of current olive cultivation areas in the coming decades (Tanasijevic et al., 2014;Moriondo et al., 2008;Moriondo et al., 2013). Expanding our analysis beyond the already cultivated areas and existing varieties requires models that take into account not only cultivar differences but also the complex response of olive photosynthesis and growth to radiation, temperature and CO 2 concentration. ...
Article
Olive orchards represent a key agricultural system with high economic and environmental prominence. Expected future climate tendencies over the Mediterranean could threaten the sustainability of such strategic tree crop. This study evaluates the productive and environmental performance of olive orchards under different climate change scenarios and management strategies across the main olive-farming regions over southern Europe using the process-based model OliveCan. Simulations were performed for low density LD (100 trees ha⁻¹), high density HD (400 trees ha⁻¹) and super high density SHD (1650 trees ha⁻¹) olive orchards over baseline period (1980-2010) and future scenarios (2041–2070 and 2071–2100 for RCP4.5 and RCP8.5). Results showed that the future increase in CO2 concentration may compensate the negative effects of higher evaporative demand and diminished water supply resulting in an enhancement of water use efficiency and carbon capture potential in olive orchards. Irrigation requirement for the maximum productivity are expected to increase by 5−27%. Moreover, rainfed low density orchards will be the most vulnerable to expected climate changes, in particular in the driest areas. In fact, a decrease in yield up to 28 % with an increase in its interannual variability of 20 % is expected over the Iberian Peninsula while yield increased up to 26 % over the centre of the Mediterranean. Deficit irrigation and intensification will improve olive orchard productivity and carbon sequestration capacity. Besides, the decrease in winter chilling is not expected to be enough to produce significant flowering anomalies or failures over the study area. Even though findings of this research showed that olive orchards may benefit from future conditions, assessment of management alternatives at local scale will be a must for a better adaptability of olive orchards.
... Moreover, the use of prototype tractors designed for olive crops and reducing the impact on the soil increases the safety levels of the operator. This study assumes the Northern Mediterranean range of the olive tree migrating progressively towards the north as a response to climate warming (Moriondo et al. 2008). We tested this hypothesis for Italy, a Southern European country with marked climate disparities between a continental regime in northern regions and a semi-arid, Mediterranean regime in southern regions, during three recent decades using statistical data and an extensive literature review and updating a preliminary report covering a shorter time interval (Colantoni et al. 2013). ...
Article
Full-text available
Southern Europe is becoming a hotspot for climate change. Appropriate mechanisation is necessary for reducing soil compacting in such contexts. The olive tree distribution – a typical Mediterranean crop – showed a well-defined latitude gradient with progressive decline moving towards the north. Climate change, however, has supposed to cause a significant shift towards the north in the geographical range of olive trees. Our study analyses the spatial distribution of the olive tree area in Italy, a region within the species' ecological range apart from the Northern region, which is now becoming progressively specialised in this crop because of local warming. Results indicate that olive cultivated area increased in Northern Italy, especially in flat districts and upland areas, while decreasing (more or less rapidly) in central and southern Italy because of land abandonment.
... We drew our data from research on wheat (Karamanos et al., 2008) (2000), Li et al. (2000), Pleijel et al. (2000), Bindi et al. (2001), Kimball et al. (2002), Kimball et al. (2007) and Taub (2010). In the cases where the AquaCrop model was not used (vegetables, tree crops, etc.) we used earlier research results (Mortensen, 1994;Rosenzweig et al., 1996;Kimball and Idso, 2001;Olesen and Bindi, 2002;Chartzoulakis and Psarras, 2005;Kimball et al., 2007;Garnaut, 2008;Moriondo et al., 2008;Ventrella et al., 2008;Gutierrez et al., 2009;Moretti et al., 2010;Orduna et al., 2010). The results obtained for Scenarios Α1Β, Α2 and Β2 for the periods 2041-2050 and 2091-2100 compared to baseline period 1991-2000 are presented in Table 2.28. ...
Chapter
Chapter 5 of the June 2011 report by Climate Change Impacts Study Committee, Bank of Greece. https://www.bankofgreece.gr/Publications/ClimateChange_FullReport_bm.pdf
... Although Valonia oak ( Q. macrolepis † ) is projected to lose more than half of its current distribution in Greece, suitable habitat will remain elsewhere in Europe (Harrison et al. , 2006 ). Archaeological and historical evidence documents the presence of olive ( Olea europeae *) cultivation in Mediterranean regions beyond this species' current geographical limits (Moriondo et al. , 2008 ). The distribution of olives is primarily limited by temperature, and contraction from southern Italy may occur due to heat stress (Gutierrez et al. , 2009 ). ...
Chapter
Introduction Pollen, in general, represents the central vector of gene flow among plant populations and is the major factor in reproductive success and fitness in, for example, forest communities (LaDeau and Clark, 2006). Allergenic pollen, in particular, and fungal spores constitute an important human health issue (Beggs, 2004; Huynen et al., 2003). Climate change-related effects have already been observed in airborne pollen concentration and pollen production, plant (Chapter 3) and pollen distribution (Chapter 4), pollen allergenicity (Chapter 5), and timing and duration of the pollen season (Chapter 6). Many factors have been discussed that may contribute not only to more frequent and severe allergic respiratory disease but also to new allergen sensitisation and increases in the development of allergic diseases (Chapters 3-9). One factor may be the observed increase in airborne quantities of allergenic pollen (Ziello et al., 2012). In the light of recent climate change, several plant characteristics such as plant biomass and pollen production are considered to change (e.g., Albertine et al., 2014; Rogers et al., 2006; Ziska et al., 2003), thus affecting atmospheric pollen concentration. However, the actual concentration of airborne pollen is altered by land use/land cover changes, abundance of invasive species or disturbance (see Chapter 3), and modified by various aerobiological processes, for example, emission, dispersion/transport, and deposition - factors which are predominantly controlled by atmospheric dynamics (Dahl et al., 2013; see also Chapter 4). Thus, annual sums of daily average airborne pollen concentrations (also called the annual pollen index, API) can differ considerably from what would be expected from effective pollen production and release (Frei and Gassner, 2008a). Nevertheless, the API obtained from pollen traps is believed to be an appropriate quantitative measure of the intensity of the airborne pollen season (Galán et al., 2008). The next two sections will provide information about the history of aerobiological networks and the results obtained from their long-term data. The effects of meteorological factors on pollen emission, dispersion/transport, and deposition are also briefly considered (see also Chapter 4). The results of experimental studies (Section 2.3.2) help to identify and disentangle the impacts of climate change on pollen production. Separate sections are dedicated to fungal spores and, finally, to research gaps which should encourage further work in the field of aeroallergen production and atmospheric concentration.
... In the Mediterranean basin, the olive tree (Olea europea L.) is cultivated on a large surface accounting for 0.98 of global olive trees cultivation (Moriondo et al., 2008). Olive agro-industrial sector produces, besides olives and olive oil, important amounts of by-products (olive cake (OC) and waste-water) (Alburquerque et al., 2006). ...
Preprint
Background The current study was carried out to evaluate the effect of olive cake and cactus cladodes incorporation on carcass characteristics and meat quality of goat kids.
... For the Mediterranean Basin, and especially for Andalusia, it is estimated that climate change will result in substantial warming and a significant decrease in precipitation in the coming decades (Dell'Aquila et al., 2012;Gualdi et al., 2013), which might cause serious ecological, economic and social changes. Because the different olive varieties are adapted to specific climatic, edaphic and lithological conditions, the variations that could occur in a context of climate change would have a significant impact on the distribution of olive varieties and, as a consequence, their growth and productivity (Moriondo et al., 2008;Ponti et al., 2014). Some olive-growing regions where traditional varieties are cultivated -yielding fruit, and thus oil, of high quality -are located in relatively-narrow geographic niches and have specific microclimatic characteristics (Rubio de Casas et al., 2002). ...
Article
World olive production is based on the cultivation of different varieties that respond differently to abiotic factors. Climate change may affect the area of land suitable for olive cultivation and change production levels, thus causing serious damage to this economically-relevant and highly-productive olive grove agroecosystem. In Mediterranean regions such as Andalusia, one of the main areas of olive production, the effect of climate change seems threatening. Thus, our main aims are: (1) to examine the abiotic factors that characterise the current cultivated locations and predict the current and potential distribution of these locations; (2) to evaluate the effect of climate change (based on regional scenarios) on the future environmental suitability of each olive variety; and (3) to analyse the expected alteration in the annual olive production. We used the seven most-productive olive varieties in Andalusia and the wild olive species to develop Species Distribution Models (SDMs), coupled with soil properties, geomorphology, water balance and (bio-)climatic predictors at a fine scale. We also derived future climate projections to assess the effect of climate change on the environmental suitability and productivity of each olive variety. We found that soil pH was the most-important factor for most distribution models, while (bio-)climatic predictors - such as continentality index, summer and autumn precipitation and winter temperature - provided important contributions. In general, projections based on regional climate change scenarios point to a decrease in the area suitable for olive crops in Andalusia, due to an increase in evapotranspiration and a decrease in precipitation. These changes in suitable area are also projected to decrease olive production for almost all the olive-growing provinces investigated. Our findings may anticipate the effects of climate change on olive crops and provide early estimates of fruit production, at local and regional scales, as well as forming the basis of adaptation strategies.
... The excess of rainfall at some given key stages of the vegetative-productive olive cycle (flowering-fruit set-ripening) generate different challenges for the development of olive trees in humid regions (Tous et al., 2005). According to the thermal requirements of the species proposed by Moriondo et al. (2008), Uruguay is an area suitable for the development of olive production. The average annual temperature is 17.7°C, varying from 19.8°C in the northwest zone to 16.6°C in the south coast. ...
Article
Full-text available
Worldwide olive industry has expanded into new climatic regions outside the Mediterranean basin due to an increase in extra virgin olive oil demand posing new challenges. This is the case of Uruguay, South America, where the olive crop area reached 10,000 hectares in the last 15 years and is intended to the production of EVOO. Uruguay has a temperate humid climate with mean precipitations above 1,100 mm per year but unequally distributed, mild winters, and warm summers, with mean annual temperatures of 17.7°C. Different agroecological conditions require local knowledge to achieve good productivity whereby the objective of this work was to show the feasibility and potential of olive oil production under our climatic conditions. For this the agronomic performance of Arbequina, Barnea, Frantoio, Leccino, Manzanilla de Sevilla, and Picual cultivars was evaluated along 10 years of full production. Phenology behavior, vegetative growth rate, productive efficiency, alternate bearing, and oil yield were determined. Sprouting and flowering processes occur in a wide window within the annual cycle between the months of August to November with great interannual variation. More than 8 t/ha fruit yield and 40% oil yields in dry weight basis were obtained in promising cultivars. However, alternate bearing arose as the main production limiting factor, with ABI values greater than 0.60 for most cultivars. We conclude that olive oil production in humid climate regions is feasible and the most promising cultivars based on productive efficiency are Arbequina and Picual.
... El cambio climático en los Pirineos: impactos, vulnerabilidades y adaptación El cambio climático en los Pirineos: impactos, vulnerabilidades y adaptación Por lo que respecta a los Pirineos y en particular para el cultivo del olivo, se estima una expansión de la superficie potencialmente idónea y aceptable (Moriondo et al., 2008;Tanasijevic et al., 2014). Sin embargo, no hay que olvidar que los eventos extremos cada vez más frecuentes como las heladas tardías, podrían revertir parte de los efectos positivos anteriormente citados, ya que incidirían sobre las plantas en un estado de desarrollo avanzado y más vulnerable a las heladas (Trnka et al., 2015). ...
... Experimental sites distribution in Tuscany region and bio-climate classification of olive tree cultivated area in Italy. The bio-climate map is a modified fromRivas-Martınez et al. (2004), olive grove distribution and the limits of olive tree cultivation were obtained from Corine Land Cover andMoriondo et al. (2008). ...
Article
This paper describes the architecture of a process-based model that simulates on a daily time step growth and development of an olive agroecosystem, including the olive tree and grass cover growth and their competition for water. The key process of the model is the simulation of daily potential biomass increase for olive tree and grass cover that may be reduced depending on water availability. The model includes a phenological sub-model simulating the sequence of olive tree vegetative and reproductive stages for determining changes in biomass allocation and the timing of possible environmental stresses (heat and water stress) that may reduce final yield. The model was calibrated and validated in Tuscany region by exploiting a data set covering heterogeneous climatic features as well as soil types and management practices existing in this region. The results pointed out that the model is able to faithfully reproduce water balance of the system, biomass accumulation and yield of olive tree and grass cover biomass. We concluded that this model is a useful prognostic tool to test the effectiveness of management practices for improving economic viability of olive tree cultivation.
... In the same table, reported data show the large diversity in the ability of olive cultivars to respond to water stress conditions. Moriondo et al. (2008) demonstrated that water availability, i.e., precipitation, had a more relevant impact than temperature in determining the suitability of olive cultivation in the Mediterranean basin. Thus, the core issue of our study on olive adaptability remains on soil water conditions and on intraspecific difference in response to water availability. ...
Article
Full-text available
Adaptation to climate change is a major challenge facing the agricultural sector worldwide. Olive (Olea europaea L.) is a global, high value crop currently cultivated in 28 countries worldwide. Global data to assess the vulnerability of the crop to climate variability are scarce, and in some notable cases, such the United Nations Food and Agriculture Organization database (FAO, 2006), qualitative assessments rather than quantitative indicators are provided. The aim of this study is to demonstrate a new approach to help overcome these constraints toward a globally applicable method to assess the adaptability of olive cultivars. The adaptability of 11 cultivars, widely used in 11 countries worldwide, was studied using a new generic approach based on the evaluation of soil hydrological regime against cultivar-specific hydrological requirements. The approach requires local data, notably on soil hydrological properties, but it is easily transferable to other countries and regions. We applied an agrohydrological model in 60 soil units to determine hydrological indicators both in a reference (1961–1990) and a future (2021–2050) climate case. We compared indicators with cultivar-specific requirements to achieve the target yield; requirements were established using experimental yield response curves. We estimated the probability of adaptation, i.e., the probability that a given cultivar attains the target yield, and we used it to evaluate the cultivar potential distribution in the study area. At the locations where soil hydrological conditions were favorable, the probabilities of adaptation of the cultivars were high in both climate cases. The results show that the area with suitable conditions for the target yield (area of adaptability) decreased under future climate for all the cultivars, with higher reduction for Frantoio and Maiatica and smaller reduction for Itrana, Nocellara, Ascolana, and Kalamata. These cultivars are currently grown in Argentina, United States (US), Australia, France, Greece, and Italy. Our results indicate also that these cultivars require higher available soil water to attain the target yield, i.e., we may expect similar vulnerability in other parts of the world. Based on these findings, we provide some specific recommendations for enrichment of global databases and for further developments of our approach, to increase its potential for global application.
... Many studies have reported an increase in crop water requirements in the Mediterranean region (Doll 2002;Topcu et al., 2008), as well as the augment of irrigation requirements (Fischer et al., 2007, Giannakopoulos et al., 2009, Villani et al., 2011. However, other studies have reported a decrease in net irrigation requirements due to a more favourable rainfall distribution (Lovelli et al., and to higher altitudes (Bindi and Howden, 2004;Moriondo et al., 2008;Tanasijevic et al., 2014). Although the olive is resistant to water shortage, it produces best with high rainfall or with irrigation (Iniesta et al., 2009;Palese et al., 2010;Martinez-Cob and Faci, 2010). ...
Article
Full-text available
This study investigated the possible impact of climate change on the olive cultivation in Montenegro in terms of growth suitability, crop phenology, water requirements and yield. The elaborations were performed in GIS through the integration of climate, soil and crop data and successive application of the agro-ecological zoning methodology and a soil-water balance model. The analysis included the baseline climate (1961-1990) and the climate data projections from the coupled regional climate model EBU-POM corresponding to the three scenarios: i) A1B (2001-2030), ii) A1B (2071-2100) and iii) A2 (2071-2100). Reference evapotranspiration was calculated using a modified Penman-Monteith approach from the air temperature data, while crop evapotranspiration and irrigation requirements were estimated following the standard FAO methodology. The results revealed that the foreseen increase of air temperature would extend the potentially cultivable areas from the present 17% of the total land surface to 30.2% in the A2 scenario. The areas suitable for olive cultivation are expected to shift northwards, and to the higher altitudes. Global warming would anticipate the flowering period of olives up to 17 days under the A2 scenario. Crop water requirements would likely increase in the future up to 3%, while the crop evapotranspiration under rainfed is foreseen to decrease from 5.5% to 21.7%. Net irrigation requirements would increase from 29.5 mm in the A1B scenario to 103.4 mm in the A2 scenario. The highest relative yield loss of 16.2±7.6% is expected under the A2 scenario which does not preclude the rainfed cultivation of olives in the future. Riassunto: In questo studio è stato valutato il possibile impatto dei cambiamenti climatici sulla coltivazione dell'olivo in Montenegro in termini di idoneità alla crescita, fenologia, fabbisogni idrici e resa. Le elaborazioni sono state eseguite in ambiente GIS integrando i dati climatici, del suolo e della coltura e successivamente sono stati applicati la metodologia di zonizzazione agro-ecologica e un modello di bilancio idrico del suolo. Le analisi hanno riguardato l'analisi dei dati di riferimento (1961-1990) e le proiezioni ottenute con il modello climatico regionale accoppiato EBU-POM corrispondente ai tre scenari: i) A1B (2001-2030), ii) A1B (2071-2100) e iii) A2 (2071-2100). L'evapotraspirazione di riferimento è stata calcolata utilizzando un approccio Penman-Monteith modificato a partire dai dati di temperatura dell'aria, mentre l'evapotraspirazione e il fabbisogno irriguo delle colture sono stati stimati in base alla metodologia standard utilizzata dalla FAO. I risultati hanno rivelato che l'aumento previsto della temperatura dell'aria potrebbe estendere le aree potenzialmente coltivabili dall'attuale 17% al 30,2% nello scenario A2. Le aree adatte alla coltivazione dell'olivo dovrebbero spostarsi verso nord e ad altitudini superiori. Il riscaldamento globale anticiperebbe il periodo di fioritura dell'olivo fino a 17 giorni con lo scenario A2. I fabbisogni idrici della coltura potrebbero aumentare fino al 3%, mentre è previsto che l'evapotraspirazione in condizioni di asciutta potrebbe passare dal 5,5% al 21,7%. I fabbisogni netti di irrigazione aumenterebbero da 29,5 mm nello scenario A1B a 103,4 mm nello scenario A2. La massima perdita in resa relativa si attesterebbe al 16,2 ± 7,6% nello scenario futuro A2 che non preclude la coltivazione in asciutta dell'olivo.
... As different olive varieties are adapted to specific climatic, edaphic and lithological conditions, variations that may occur in the context of climate change will have a significant impact on the distribution of olive varieties and their growth and productivity as a result (Moriondo et al., 2008). Therefore, these varieties are predicted to be more vulnerable to both short-term and longterm climate change than the main olive varieties (Olesen et al., 2011). ...
Article
Full-text available
Climate change, threatening the ecosystem, living things and even us, has brought people all over the world together to fight it. Each country has started to develop its own action plans. To combat climate change, we need to change our perspectives and production systems. Although all kinds of damage will be affected by climate change, olives, which have a rich history and a source of healing, will be more affected. This review will be the first study in which many holistic approaches such as the effect of climate change on the physiology of olives, the effect of CO2 emission on olives, the effect of drought on olives, climate change and new olive regions, socio-cultural dimension, new methods to reduce climate change, and the sustainability of olive groves. With this review, the interaction between climate change and olives will be revealed, and will shed light on future studies.
Chapter
Weather conditions play a fundamental role in plant growth and development, due to their direct and indirect influence on physical, chemical and biological processes. It is then crucial the analysis of possible impact due to current and future climate change and variability. With this main objective, this chapter starts with a preliminary analysis of plant responses to weather conditions and then with an evaluation of climate change and variability, deeply discussing the main impacts and stresses of climate change, considering enhanced CO2, higher temperature and available water. Then responses of different systems are discussed together with available adaptation options and conditions for their effective deployment. Different levels of adaptations were considered, from the short and long term measures, to the farm , regional and national options. The chapter concludes with a discussion of future directions in plant biometeorology and research gaps.
Chapter
Biometeorology was first officially recognised as an emerging interdisciplinary science in August 1956, when Dr. Tromp and colleagues organized the first International Symposium of Biometeorology in the UNESCO Building in Paris. The meeting led to the establishment of the international society. The first issue of the societies' journal, The International Journal of Biometeorology, was published 5 years later in 1961. This volume was initiated to mark the 50th anniversary of the establishment of the International Society of Bioclimatology and Biometeorology. In 1956, there were few interdisciplinary scientific societies and the idea of creating new disciplines at the interstices of well-established fields was not universally welcomed by established scholars and their scientific societies in meteorology and biology. One consequence of being viewed as somehow less scientific was that the emerging interdisciplinary groups tended to stress the importance of scientific rigour, sometimes at the expense of innovation and originality. This was reflected in the rapid crystallisation of biometeorology into specialised sub-fields, particularly human, plant, and animal biometeorology in the early decades. These groups attracted the interest of some applied meteorologists and climatologists, with their partners and collaborators drawn from traditional disciplines, i.e. health sciences for human biometeorology, and botanists, zoologists, agronomists, and related sciences for plant and animal biometeorology. These three sub-disciplines tended to dominate the Congresses of the International Society of Biometeorology held every 3 years, and the papers published in the journal. The Society flourished and its scientific rigour and respectability was established, although the interdisciplinary ambitions were not entirely fulfilled in the way imagined.
Article
In central Queensland, Australia, relatively little is known about where gullies occur (‘gully presence’). This is despite a general acceptance among scientists and politicians that gully erosion in the region is an ecologically important process, exacerbated by grazing pressure. We aimed to create a risk map of gully presence for a 4.86 × 106-ha area of central Queensland dominated by grazing and thought to be particularly prone to gully erosion. We achieved this by using (i) light detection and ranging (lidar) technology (vertical accuracy < 0.15 m; spatial resolution 0.5 m) to observe topography on transects at eight selected sites within the study area, (ii) object-oriented classification to derive gully presence from lidar observations and (iii) a random forest to model the relationship between gully presence and a set of readily available explanatory variables (comprising soil, topography, and vegetation information; finest spatial resolution 25 m) and (iv) extrapolating the model to unsampled locations. Cross-validation indicated that the predictive ability of the model was modest, with an average area under the receiver operating characteristic curve of 0.62 (where 1.0 is a perfect model and 0.5 is no better than chance). The greatest risk of gully presence was associated with areas of large topographic variation, and where, coincidentally, there was relatively little long-term vegetation cover. Ultimately, however, we acknowledge that the quality of the map is limited by the small area of observed lidar data relative to the study area, the relatively coarse spatial resolution of the explanatory variables and the possibility that gully presence is the result of different processes at different locations.
Data
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To better understand the roots of Holland Reference Services in two divisional libraries, the Humanities Library and the Social Sciences Library, the author has culled the Archive in honor of Pauline Lilje in order to show readers some of his favorite original documents from the '70s.
Chapter
Climatic change is expected to have important impact on different economic sectors (e.g. agriculture, forestry, energy consumptions, tourism, etc.). Among human activities, agricultural sector is likely to be particularly exposed to climate change hazard, since animal and crop growth are largely determined by the weather conditions during their life cycles. As a consequence, understanding the potential impacts of climate change on the agriculture has become increasingly important and is of a main concern especially for the sustainability of agricultural system and for policy-making purposes. Climate change is likely to affect agricultural systems very differently in various parts of the world. In the Mediterranean area particular attention should be devoted to climate change impact and adaptation assessments on typical Mediterranean crops like grapevine (Vitis vinifera L.), durum wheat (Triticum turgidum subs. durum Desf.) and olive (Olea europaea L.), since the projected global warming may seriously compromise the fragile equilibrium between climate and crops. In this study the impacts on durum wheat and grapevine yields, and olive suitable cultivation area were investigated for two time slices under A1B SRES scenario, at first. Then, some adaptation strategies to cope with these impacts were explored. The results indicated that projected higher temperatures resulted in a general advance of phenological stages with respect to the baseline and in a shorter inter-phase time for both durum wheat and grapevine. Despite the general decrease of time for biomass accumulation, durum wheat took advantage of the positive effect of higher CO2 concentration, while grapevine resulted more vulnerable to warmer and drier future climate. Adaptation options, aiming at avoiding extremely high temperatures during sensible phases and prolonging the duration of the reproductive stage, resulted as positive strategies to alleviate negative impacts or exploit possible beneficial effects of a changing climate. Finally, the rising temperature will cause a northward and eastward shift of the olive tree suitable area.
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The current study was carried out to evaluate the effect of olive cake and cactus cladodes incorporation on growth performance, carcass characteristics and meat quality of goat kids. Forty-eight male goat kids were divided into four groups. The control group received a conventional diet and the test groups received, on dry matter basis, 200 g/kg of olive cake (OC), 160 g/kg of cactus cladodes (CC), or 80 g/kg OC and 80 g/kg CC (OC+CC) 1 respectively. During the experiment, the dry matter intake (DMI) and the average daily gain (ADG) were determined. At the end of the trial, all animals were slaughtered and the carcass quality was characterized. Samples of longissimus dorsi and semimembranosus were collected to determine meat quality. The diets did not affect DMI, ADG, final body weight and carcass characteristics, except for muscle index that decreased with 200 g/kg OC, and redness and yellowness at tail outline and belly (P<0.05). The OC incorporation increased yellowness at tail and decreased redness at belly (P<0.05), while the CC inclusion decreased redness at tail outline (P<0.01), and redness (P<0.05) and yellowness at belly (P<0.01). Meat ultimate pH, color, moisture and tenderness were not affected by diets. In longissimus dorsi, higher protein (P<0.001) and lower fat and ash (P<0.05) content were observed with CC, and lower protein content with OC and OC+CC (P<0.001). In semimembranosus, a low initial pH (P<0.05) was observed with OC and high protein content (P<0.001) with CC and OC+CC. Generally, groups, ratios, and indexes of fatty acids (FA) were similar between groups, except the FA profile that was affected by diet, especially for semimembranosus. In longissimus dorsi, the OC and CC introduction decreased C16:1, and C20:3n-3 increased with CC and OC+CC (P<0.05). While in semimembranosus, OC increased C6:0, C8:0, C18:3n-3, C20:2, and C22:2, whereas CC incorporation reduced C8:0, C10:0, and C15:1, and OC+CC reduced C10:0 (P<0.05). Overall, OC and CC showed a lack of negative effects on growth performance, carcass characteristics and meat quality. Thus, they could be introduced in goat kids’ diet to reduce supplement charges. Keywords: olive cake; cactus cladode; goat kid; carcass; meat quality; fatty acid.
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Cropping activity has an importance that extends beyond farming communities, to governments, private industries, and to scientific research. We have developed a remote sensing-based method to detect arable cropping activity in central and southern Queensland, Australia, based on time series analysis of the NDVI layer of MODIS-Terra MOD13Q1 (250-m pixel) imagery. Local auto-regression was used to characterise phenological cycles in the NDVI time series. A random forest was then used to model three broad classes of agricultural vegetation (Grazing, Summer Cropping and Winter Cropping), as a function of phenological metrics and the local variance of the NDVI time series. The latter was found to be the most important distinguishing factor between the three classes. Pixel-by-pixel predictions of the random forest were obtained bi-annually for the study area over a 10-year period. Moderate agreement was seen between the predictions of the random forest and (independent) visual interpretation of Landsat imagery (Cohen's index of agreement, κc, of 0.59). We then demonstrated how the random forest's predictions can be used to define the consistency of cropping activity at the spatial scale of an individual farm property; when compared with (independent) visual interpretation of Landsat imagery the agreement was also moderate (κc = 0.68). In comparison with other crop-mapping approaches in the literature, our results have been achieved: (i) without restricting the method to annual NDVI time series; (ii) without assuming that the time series is regularly spaced and periodic; (iii) by considering only the ‘greening-up’ phase of the phenological cycles.
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Em Oeiras, no campus do INIAV, existe uma coleção de oliveiras que para além do seu interesse para a investigação agrária, tem interesse educativo. Neste artigo refe-rem-se alguns dados sobre esta espécie e a metodologia de divulgação da coleção de oliveiras. Oliveira-uma árvore típica do mediterrâneo com relevância económica A oliveira (Olea europaea L.) da Família Oleaceae tem sido amplamente cultivada atra-vés dos tempos em olivais tradicionais ou intensivos. O seu fruto-a azeitona-e o óleo que dela se extrai-o azeite-usam-se para fins alimentares, sendo parte importan-te da dieta mediterrânica. Esta fruteira lenhosa é, de uma maneira geral, tolerante ao stress hídrico e adapta-se bem a uma ampla gama de solos e de condições culturais, incluindo os solos ácidos e alcalinos. Os resultados do inquérito da União Europeia (UE) relativo à área ocupada com olivei-ras na UE 3 indicaram que esta representava cerca de 4,6 milhões de hectares em 2017. Este inquérito englobou apenas os oito Estados-Membros da UE que possuíam áreas de oliveiras superiores a 1000 hectares. A Espanha (com 55% da área total) e a Itália (com 23% da área total) tinham mais de três quartos da área total da UE com oliveiras, seguidos da Grécia (15%) e Portugal (7%). Os outros quatro Estados-Membros abrangi-dos pelo inquérito (França, Croácia, Chipre e Eslovénia) representavam em conjunto 1% da área total de oliveiras da UE. Deste modo, Portugal tem a nível da UE, a quarta maior área de plantação de oliveiras, sendo esta cultura importante para a economia nacional. A nível mundial, a zona ecológica onde existem oliveiras situa-se entre as latitudes 30 o e 45 o nos hemisférios Norte e Sul, em regiões com clima mediterrânico. A oliveira é uma árvore tão típica do clima mediterrânico que a sua presença num dado território pode qualificar, na opinião de Moriondo et al. (2008) 6 , o clima desse território como sen-do mediterrânico e daí também se afirmar que "Onde a oliveira não chega, o Mediterrâ-neo morre". Hoje em dia, centenas de variedades de oliveira são descritas e referenciadas para a produção de azeite e/ou azeitona de mesa, sendo algumas delas específicas e prove-nientes de determinadas regiões. No Catálogo Nacional de Variedades-CNVFruteiras (DGAV, 2016) 2 são referidas as variedades de Olea europaea L. com aptidão para produ-ção de frutos. CITAÇÃO Lima, M. A. A.(2022) Uma coleção de oliveiras em Oeiras, Rev. Ciência Elem., V10(01):014.
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Riedizione (integrata da due paragrafi inediti dedicati al commercio dell’olio d’oliva e agli olii diversi da quello d’oliva, e corredata di note) di un testo già apparso nel volume A. Cortonesi, G. Pasquali, G. Piccinni, Uomini e campagne nell’Italia medievale, Roma-Bari 2002, pp. 240-260.
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Algorithms are developed for contouring on spherical surfaces and in Cartesian two-space. These algorithms are used to investigate errors on small-scale climate maps caused by the common practice of interpolating - from irregularly-spaced data points to regular-lattice nodes - and contouring in Cartesian two-space. Using mean annual air temperatures drawn from 100 irregularly-spaced weather stations, the annual air-temperature field over the western half of the northern hemisphere is estimated both on the sphere (assumed to be correct) and in Cartesian two-space. When these fields are mapped and compared, error magnitudes as large as 5 degree to 10 degree C appear in the air-temperature field approximated in Cartesian two-space.
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The effects of temperature on the progamic phase, fertilization and initial fruit set in cross pollinated olives were studied to determine the reasons for poor fruit set when high temperatures occur during the bloom period. Fruit set in ‘Manzanillo’ olive was completely inhibited at 30°C constant temperature. This temperature significantly reduced pollen germination but did not prevent pollen tube growth. Ovule penetration by the pollen tube was observed in 47% of the flowers at 30°C; however, the lack of growth of both functional ovules and ovaries suggests problems in zygote formation or endosperm development. The most favourable temperature was 25°C, in which faster pollen tube growth, more and earlier fertilization, and more fruit set occurred. At 20°C pollen tube growth was slower, resulting in delayed and reduced fertilization.
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We review the 1000-year climatic and environmental history of the Earth contained in various proxy records. As indicators, the proxies duly represent local climate. Questions on the validity of locality paradigm will become sharper as climatic changes on timescales of 50-100 years or longer are being pursued. This is because the thermal and dynamical constraints imposed by local geography will become increasingly important as the air-sea-land interaction timescale increases. Because the nature of the proxy climate indicators are so different, the results cannot be combined or compared into a hemispheric or global quantitative composite. However, considered as an ensemble of individual expert opinions, the assemblage of local representations of climate establishes both the Little Ice Age and Medieval Warm Period as climatic anomalies with world-wide imprints, extending earlier results by Bryson et al. (1963), Lamb (1965), and numerous intervening research efforts. Furthermore, the individual proxies can be used to address the question of whether the 20th century is the warmest of the 2nd millennium locally. Across the world, many records reveal that the 20th century is probably not the warmest nor an uniquely extreme climatic period of the last millennium, although it is clear that human activity had impacted many microscopic realms of the climate and environment.
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The use of crop simulation models to evaluate cultivars and cropping practices has developed greatly in the last few years. These tools can provide unique advantages in several situations, for example, allowing a quick response when new needs arise or to extrapolate results of field experiments in different environmental (climate, soil) and agronomic (cultivars, cropping systems) situations. The operational utilisation of the results of models is however bounded by the problem of extrapolating then to all points on the land surface, which is not always a trivial task in topographically complex regions. The present work investigates the use of different methodologies for the extension of the outputs of a grapevine model in a rugged region of central Italy, Tuscany. In particular, 2 approaches were considered, the first based on statistical assumptions and the second on neural network reasoning. These techniques were applied using, as input parameters, topographical information layers and low-resolution satellite data related to vegetation development. The results obtained show that, in general, the neural network approach produced higher accuracy levels than the statistical approach, but the latter was more capable of merging information coming from different sources. Moreover, the estimates derived from the 2 methods show different spatial patterns and ranges, which must be taken into account when considering these approaches for possible operational uses.
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We predict current distribution and abundance for tree species present in eastern North America, and subsequently estimate potential suitable habitat for those species under a changed climate with 2×CO2. We used a series of statistical models (i. e., Regression Tree Analysis (RTA), Multivariate Adaptive Regression Splines (MARS), Bagging Trees (BT) and Random Forests (RF)) via our model, DISTRIB, for this purpose. These techniques were evaluated on several tree species, and advantages and disadvantages of each method were noted. RF provides the best prediction maps of potential suitable habitat. Overall, a combination of RTA, BT, and RF may yield the best information and most interpretable maps of suitable habitat. Using these tools, we provide statistics on potential changes in suitable habitat for 135 tree species of eastern North America.A suitable habitat does not guarantee the presence of a species, as many barriers for the species still exist before it will be able to colonize that new suitable habitat. Dispersal ability, abundance of the colonizing species, and the nature of fragmented landscapes also influence migration and are modeled with our cellular automata model, SHIFT. For each cell outside a species' current boundary, SHIFT creates an estimate of the probability that each unoccupied cell will become colonized over 100 years. By evaluating the probability of colonization within the potential “new” suitable habitat, we can estimate the proportion of new habitat that might be colonized within a century. This proportion is low (<15%) for five example species, suggesting that there is a serious lag between the potential movement of suitable habitat and the potential for the species to migrate into the new habitat. However, humans could accidentally or purposefully alter the migration rates of species by physically moving the propagules.
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Geostatistical analyses of 35 plant species from 213 packrat middens with combined records spanning the last 40,000 yr indicate that many presumed winter precipitation-dependent taxa that existed in the Sonoran Desert during the last glaciation were expelled by increasing monsoon precipitation instead of waning cool-season moisture. The statistical influence of excessive monsoon rainfall on the distributions of many species probably reflects the simultaneous increase in the magnitude and occurrence of fire. During the early Holocene, results indicate a dramatic decrease in cool-season precipitation and an increase in monsoon rainfall. Levels of temperature and precipitation continued to change linearly until they reached modern values. These conclusions are drawn from a newly developed computer model that determines which climatic factors impede species movement into an unoccupied region. Climatic “limiters,” derived from digital versions of modern plant distributions, elevation, and meteorological data, formed the basis of the reconstructions. Particularly important distribution limiters for the Sonoran Desert include maximum warm-season precipitation and low winter temperatures. The model allows for quantitative estimates of past climatic changes with relatively detailed temporal and spatial resolutions. These results can be used to refine paleoclimatic interpretations based on coarser resolution General Circulation Models.
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From Shepard's (1968) local-search method, algorithms are developed for contouring on spherical surfaces and in Cartesian two-space. These algorithms are used to investigate errors on small-scale climate maps caused by the common practice of interpolating—from irregularly-spaced data points to regular-lattice nodes—and contouring in Cartesian two-space. Using mean annual air temperatures drawn from 100 irregularly-spaced weather stations, the annual air-temperature field over the western half of the northern hemisphere is estimated both on the sphere (assumed to be correct) and in Cartesian two-space. When these fields are mapped and compared, error magnitudes as large as 5° to 10° C appear in the air-temperature field approximated in Cartesian two-space.
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Understorey vegetation is a critical component of biodiversity and an essential habitat component for many wildlife species. However, compared to overstorey, information about understorey vegetation distribution is scant, available mainly over small areas or through imprecise large area maps from tedious and time-consuming field surveys. A practical approach to classifying understorey vegetation from remote sensing data is needed for more accurate habitat analyses and biodiversity estimates. As a case study, we mapped the spatial distribution of understorey bamboo in Wolong Nature Reserve (south-western China) using remote sensing data from a leaf-on or growing season. Training on a limited set of ground data and using widely available Landsat TM data as input, a nonlinear artificial neural network achieved a classification accuracy of 80% despite the presence of co-occurring mid-storey and understorey vegetation. These results suggest that the influences of understorey vegetation on remote sensing data are available to practical approaches to classifying understorey vegetation. The success here to map bamboo distribution has important implications for giant panda conservation and provides a good foundation for developing methods to map the spatial distributions of other understorey plant species.
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A new and relatively straightforward approach to interpolating and spatially averaging air temperature from weather-station observations is introduced and evaluated using yearly station averages taken from the Jones et al. archive. All available terrestrial station records over the period from 1881 through to 1988 are examined. Called climatologically aided interpolation, or CAI, our procedure makes combined use of (i) a spatially high-resolution air-temperature climatology recently compiled by Legates and Willmott, as well as (ii) spatially interpolated yearly temperature deviations (evaluated at the stations) from the climatology. Spherically based inverse-distance-weighting and triangular-decomposition interpolation algorithms are used to interpolate yearly station temperatures and temperature deviations to the nodes of a regular, spherical lattice. Interpolation errors are estimated using a cross-validation methodology. Interpolation errors associated with CAI estimates of annual-average air temperatures over the terrestrial surface are quite low. On average, CAI errors are of the order of 0.8°C, whereas interpolations made directly (and only) from the yearly station temperatures exhibit average errors between 1.3°C and 1.9°C. Although both the high-resolution climatology and the interpolated temperature-deviation fields explain non-trivial portions of the space-time variability in terrestrial air temperature, most of CAI's accuracy can be attributed to the spatial variability captured by the high-resolution (Legates and Willmott's) climatology. Our results suggest that raw air-temperature fields as well as temperature anomaly fields can be interpolated reliably.
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Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale-dependent context.
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Despite the variety of statistical methods available for static modeling of plant distribution, few studies directly compare methods on a common data set. In this paper, the predictive power of Generalized Linear Models (GLM) versus Canonical Correspondence Analysis (CCA) models of plant distribution in the Spring Mountains of Nevada, USA, are compared. Results show that GLM models give better predictions than CCA models because a species-specific subset of explanatory variables can be selected in GLM, while in CCA, all species are modeled using the same set of composite environmental variables (axes). Although both techniques can be readily ported to a Geographical Information System (GIS), CCA models are more readily implemented for many species at once. Predictions from both techniques rank the species models in the same order of quality; i.e. a species whose distribution is well modeled by GLM is also well modeled by CCA and vice-versa. In both cases, species for which model predictions have the poorest accuracy are either disturbance or fire related, or species for which too few observations were available to calibrate and evaluate the model. Each technique has its advantages and drawbacks. In general GLM will provide better species specific-models, but CCA will provide a broader overview of multiple species, diversity, and plant communities.
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The periods from 1675–1715 (Late Maunder Minimum; LMM)and 1780–1830 (Early Instrumental Period; EIP)delineate important parts of the so-called `Little IceAge' (LIA), in which Europe experienced predominantcooling. Documentary data, assembled from a number ofsources, in the course of the EU funded researchproject ADVICE (Annual to Decadal Variability ofClimate in Europe), has been used to locate anddescribe events in the southern Balkans and easternMediterranean. The resulting data has been usedfirstly to investigate the incidence of phenomena suchas crops sterility, famine and epidemics and theirrelationships with climate, and secondly to analysethe extent of variability, particularly the occurrenceof extreme events, such as severe winters (cold, wetor snowy), long periods of drought and wet periods.During the LMM and EIP, more such extreme situationswere apparent compared with the last 50 years of thetwentieth century. From the scattered data found for1675–1715 and 1780–1830, the winter and spring climatein southern Balkans and the eastern Mediterranean,especially during the LMM, can be characterised ascooler and relatively rainier with a highervariability compared with the recent decades.
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The task of modeling the distribution of a large number of tree species under future climate scenarios presents unique challenges. First, the model must be robust enough to handle climate data outside the current range without producing unacceptable instability in the output. In addition, the technique should have automatic search mechanisms built in to select the most appropriate values for input model parameters for each species so that minimal effort is required when these parameters are fine-tuned for individual tree species. We evaluated four statistical models—Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS)—for predictive vegetation mapping under current and future climate scenarios according to the Canadian Climate Centre global circulation model. To test, we applied these techniques to four tree species common in the eastern United States: loblolly pine (Pinus taeda), sugar maple (Acer saccharum), American beech (Fagus grandifolia), and white oak (Quercus alba). When the four techniques were assessed with Kappa and fuzzy Kappa statistics, RF and BT were superior in reproducing current importance value (a measure of basal area in addition to abundance) distributions for the four tree species, as derived from approximately 100,000 USDA Forest Service’s Forest Inventory and Analysis plots. Future estimates of suitable habitat after climate change were visually more reasonable with BT and RF, with slightly better performance by RF as assessed by Kappa statistics, correlation estimates, and spatial distribution of importance values. Although RTA did not perform as well as BT and RF, it provided interpretive models for species whose distributions were captured well by our current set of predictors. MARS was adequate for predicting current distributions but unacceptable for future climate. We consider RTA, BT, and RF modeling approaches, especially when used together to take advantage of their individual strengths, to be robust for predictive mapping and recommend their inclusion in the ecological toolbox.
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The integration of Landsat TM and environmental GIS data sets using artificial intelligence rule-induction and decision-tree analysis is shown to facilitate the production of vegetation maps with both floristic and structural information. This technique is particularly suited to vegetation mapping in disturbed or hilly environments that are unsuited to either conventional remote sensing methods or GIS modeling using environmental data bases.
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Plant species’ climatic range limiters provide clues to reconstruct past climates, restore ecosystems, and manage agricultural systems. However, precise climatic limiters are unknown for many important species, and determining them typically involves long-term autecological studies. A new method presented here automatically and quantitatively infers limiters for a plant species using its documented, digitized distribution. The method uses available and accessible elevation and climate datasets from the US Geological Survey (USGS) and NOAA, along with common off-the-shelf (COTS) geographic information software technology (GIS) to determine which variables in the plant distribution climate space are actually limiting the range by restricting its movement into surrounding territory. The method utilizes precision climate interpolation allowing for independent variables in addition to latitude and longitude, via a software package developed at Australian National University (ANUSPLIN). For this first run, elevation and slope were included as independent variables for interpolating precipitation and temperature surfaces. The model defined limits for five Sonoran Desert plant species: Carnegiea gigantea, Cercidium microphyllum, Encelia farinosa, Ferocactus acanthodes, and Larrea tridentata. Results were tested against environmental factors outlined in autecological studies. Important model-derived climatic constraints to the distribution of C. gigantea include insufficient monsoon precipitation, low winter and monsoon temperatures, and excessive monsoon and fall precipitation. The distribution of C. microphyllum is constrained by cold winter and fall temperatures, excessive spring and summer precipitation and insufficient fall precipitation. E. farinosa is restricted by frigid winter temperatures and too much summer rainfall. Key factors limiting F. acanthodes are cold winter temperatures and inadequate fall and monsoon precipitation. An inordinate amount of precipitation during the summer, monsoon, and fall constrict the range of L. tridentata, along with an abnormally cool summer or monsoon. Results indicate that the method adequately resolves plant range limiters consistent with the autecological record. Future changes to the model are offered to improve results.
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The olive was one of the first fruit trees cultivated by man. It has been claimed that cultivation of the olive began in Israel during the Chalcolithic Period. Careful botanical examination of pollen grains, stones and wood remains gathered from living trees and from archaeological contexts show that it is impossible to distinguish between wild and cultivated olives. The ample remnants of olive found in archaeological contexts, together with other finds, such as pottery vessels, oil lamps, and olive oil installations, indicate that the earliest widespread use of olives in Israel was in the Early Bronze Age.
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In this paper an attempt is made to reconstruct air temperature variations in winter (December, January and February) from 2500 documentary data over the period ad 750-1300 for a region comprising the Benelux countries, eastern France, western Germany, Switzerland and northern Italy. Anomalous (warm and cold) winters were classified on the basis of proxy information on frost, freezing of water bodies, duration of snowcover and untimely activity of vegetation using semiquantitative indices. For the most severe winters during the Medieval Warm Period' (MWP) as well as for the outstanding warm and dry winter ad 1289/90, possible analogue cases from the last 300 years are considered, analysed, synoptically interpreted and compared with each other. It is concluded that severe winters were somewhat less frequent and less extreme during the MWP, ad 900-1300, than in the ninth century and from 1300 to 1900. Mean air temperatures for 30 year. periods were estimated from linear regression models including indices and instrumental measurements. From ad 1090 to 1179 winter temperatures were at the level of the Little Ice Age' (LIA). From ad 1180 to 1299 they were at that of the twentieth century. The warm and stable winter climate in the thirteenth century supported subtropical plants such as olive trees in the Po valley (northern Italy) and fig trees around Cologne (Germany). The period ad 1300-1329 which marks the transition to the LIA was 1{degrees}C colder. It is concluded that the 1961-90 level of winter temperatures in western central Europe is still within the threshold of natural variability of the last thousand years, albeit at its upper boundary.
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There is now ample evidence of the ecological impacts of recent climate change, from polar terrestrial to tropical marine environments. The responses of both flora and fauna span an array of ecosystems and organizational hierarchies, from the species to the community levels. Despite continued uncertainty as to community and ecosystem trajectories under global change, our review exposes a coherent pattern of ecological change across systems. Although we are only at an early stage in the projected trends of global warming, ecological responses to recent climate change are already clearly visible.
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Chloroplast DNA diversity in the olive ( Olea europaea L.) complex was studied using PCR-RFLP and microsatellite markers. Fifteen chlorotypes were distinguished. We constructed a cpDNA phylogenetic tree in which five clades were recognised and located in distinct geographic areas: clade A in Central and Southern Africa, clade C in Asia, clade M in North-West Africa, clade E1 in the Mediterranean Basin and Sahara, and clade E2 in West Mediterranea. Cultivated olive clustered with Mediterranean and Saharan wild forms (clades E1 and E2). Strong genetic differentiation for cpDNA markers was observed between eastern and western Mediterranean olives, suggesting that these areas have represented different glacial refugia. Humans most likely spread one eastern chlorotype, preponderant in cultivars, across the western Mediterranean Basin. Its presence in O. e. subsp. laperrinei from the Sahara suggests a possible Mediterranean olive origin in an African population, which may have overlapped in the Southern Mediterranean during the Quaternary.
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Widespread extinction is a predicted ecological consequence of global warming. Extinction risk under climate change scenarios is a function of distribution breadth. Focusing on trees and birds of the eastern United States, we used joint climate and environment models to examine fit and climate change vulnerability as a function of distribution breadth. We found that extinction vulnerability increases with decreasing distribution size. We also found that model fit decreases with decreasing distribution size, resulting in high prediction uncertainty among narrowly distributed species. High prediction uncertainty creates a conservation dilemma in that excluding these species under-predicts extinction risk and favors mistaken inaction on global warming. By contrast, including narrow endemics results in over-predicting extinction risk and promotes mistaken inaction on behalf of individual species prematurely considered doomed to extinction.
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The Australian olive industry is attaining a state of maturity viability that will lead it to become a significant force in the domestic market, but as yet only a niche player, internationally. This paper outlines the changes that have occurred in the recent decade and which have lead to this transformation and points to issues that should be addressed to maintain success. First for the drivers for the growth of the domestic industry was cultural change which occurred as result of European migration post World War II and the changes in diet and cuisine brought by the immigrants and their descendants. Secondly the rise in olive oil consumption to the point where Aus$ 160million oils and related products are imported was recognised as an opportunity. These two factors were then coupled to the suitability of southern Australia for cultivation especially for industrial scale plantations, the rise in the economy and Australian horticulture and agricultural expertise, as exemplified by the international success of the Australian wine industry. Sustained growth will depend on advances in efficiency and market development in an environment of globalisation in which Australia will produce about 1% only of world olive products. Limited expertise in sensory analysis is being overcome through international linkages and training programs but such activities need to continue to be advanced, as does education of the Australian community which presently consumes lower grade products than the high quality products that are anticipated will be the primary outputs of this 'new industry'.
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A Mapped Atmosphere-Plant-Soil System (MAPSS) has been constructed for simulating the potential biosphere impacts and biosphere-atmosphere feedbacks from climatic change. The system calculates the potential vegetation type and leaf area that could be supported at a site, within the constraints of the abiotic climate. Both woody vegetation and grass are supported and compete for light and water. The woody vegetation can be either trees or shrubs, evergreen or deciduous, and needleleaved or broadleaved. A complete site water balance is calculated and integrates the vegetation leaf area and stomatal conductance in canopy transpiration and soil hydrology. The MAPSS model accurately simulates the distributions of forests, grasslands, and deserts and reproduces observed monthly runoff. The model can be used for predictions of new vegetation distribution patterns, soil moisture, and runoff patterns in alternative climates.
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With the rise of new powerful statistical techniques and GIS tools, the development of predictive habitat distribution models has rapidly increased in ecology. Such models are static and probabilistic in nature, since they statistically relate the geographical distribution of species or communities to their present environment. A wide array of models has been developed to cover aspects as diverse as biogeography, conservation biology, climate change research, and habitat or species management. In this paper, we present a review of predictive habitat distribution modeling. The variety of statistical techniques used is growing. Ordinary multiple regression and its generalized form (GLM) are very popular and are often used for modeling species distributions. Other methods include neural networks, ordination and classification methods, Bayesian models, locally weighted approaches (e.g. GAM), environmental envelopes or even combinations of these models. The selection of an appropriate method should not depend solely on statistical considerations. Some models are better suited to reflect theoretical findings on the shape and nature of the species’ response (or realized niche). Conceptual considerations include e.g. the trade-off between optimizing accuracy versus optimizing generality. In the field of static distribution modeling, the latter is mostly related to selecting appropriate predictor variables and to designing an appropriate procedure for model selection. New methods, including threshold-independent measures (e.g. receiver operating characteristic (ROC)-plots) and resampling techniques (e.g. bootstrap, cross-validation) have been introduced in ecology for testing the accuracy of predictive models. The choice of an evaluation measure should be driven primarily by the goals of the study. This may possibly lead to the attribution of different weights to the various types of prediction errors (e.g. omission, commission or confusion). Testing the model in a wider range of situations (in space and time) will permit one to define the range of applications for which the model predictions are suitable. In turn, the qualification of the model depends primarily on the goals of the study that define the qualification criteria and on the usability of the model, rather than on statistics alone.
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Two "smart' interpolation procedures are presented and assessed with respect to their ability to estimate annual-average air temperatures at unsampled points in space from available station averages. Smart approaches exmained here improve upon commonly used procedures in that they incorporate spatially high-resolution digital elevation information, an average environmental lapse rate, and/or another higher-resolution longer-term average temperature field. Two other straightforward or commonly used interpolation methods also are presented and evaluated as benchmarks to which the smart interpolators can be compared. Smart approaches are significantly more accurate than either traditional methods or estimates spatially interpolated from a high-resolution climatology alone. A smart interpolation method that makes combined use of a digital elevation model (DEM) and traditional interpolation was nearly 24% more accurate than traditional interpolation by itself. -from Authors
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The 1000 yr climatic and environmental history of the Earth contained in various proxy records is reviewed. As indicators, the proxies duly represent local climate. Because each is of a different nature, the results from the proxy indicators cannot be combined into a hemispheric or global quantitative composite. However, considered as an ensemble of individual expert opinions, the assemblage of local representations of climate establishes both the Little Ice Age and Medieval Warm Period as climatic anomalies with worldwide imprints, extending earlier results by Bryson et al. (1963), Lamb (1965), and numerous intervening research efforts. Furthermore, the individual proxies can be used to address the question of whether the 20th century is the warmest of the 2nd millennium locally. Across the world, many records reveal that the 20th century is probably not the warmest nor a uniquely extreme climatic period of the last millennium.
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Morphometric analyses show quantitative differences in anatomical characters of wood and charcoal between wild and cultivated olive. Samples from modern olive wood in eastern Spain (Levante) provide five distinctive anatomical criteria: growth width ring, vessel surface, number of vessels per group, vessel density, and vulnerability ratio. Multivariate analysis shows that growth ring width and number of vessels per group are both significant criteria for discriminating between wild and cultivated olive. Moreover, bioclimatic environments of wild olive (thermomediterranean and mesomediterranean stages) are distinguished by vessel density. Ancient olive charcoal from archaeological sites at Valencia and Alicante implies increasing aridification from the Cardial Neolithic to the Roman Period. This pattern may reflect the onset of a Mediterranean climate and human deforestation. Charcoal from cultivated specimens of early Neolithic age shows that the olive tree is the earliest cultivated temperate fruit.
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$, S'il y a un numéro ci-après, c'est le champ Number, i.e. le vol. de la série (livres) ou le fasc. (revues): 6 London; New York
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In many fields using empirical areal data there arises a need for interpolating from irregularly-spaced data to produce a continuous surface. These irregularly-spaced locations, hence referred to as “data points,” may have diverse meanings: in meterology, weather observation stations; in geography, surveyed locations; in city and regional planning, centers of data-collection zones; in biology, observation locations. It is assumed that a unique number (such as rainfall in meteorology, or altitude in geography) is associated with each data point. In order to display these data in some type of contour map or perspective view, to compare them with data for the same region based on other data points, or to analyze them for extremes, gradients, or other purposes, it is extremely useful, if not essential, to define a continuous function fitting the given values exactly. Interpolated values over a fine grid may then be evaluated. In using such a function it is assumed that the original data are without error, or that compensation for error will be made after interpolation.
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Two artificial neural networks (ANN) and three traditional statistical classification methods are used to classify Forest Inventory and Analysis (FIA) plots into six ecological habitats in the U.S. Northeast. Four variables (overstory and understory species composition, hardwood basal area percentage, and current FIA forest type) are identified from a list of available stand variables as the most important discriminating variables for habitat classification. The error matrix and accuracy indices are used to assess the classification accuracy of the models and to test the differences between the five classifiers. The ANN models (MLP and RBF) are superior to the traditional statistical methods such as linear discriminant analysis and minimum-distance classification. The classification accuracy of the ANN models is 90% or higher for overall classification, and exceeds 92% in five of the six habitat categories. The K-Nearest Neighbor (KNN) method classifies the six ecological habitats as accurately as the two neural network models. This study shows that the ANN models and KNN method have a great potential for the classification of ecological habitats using FIA data, due to their flexibility of modeling algorithms and robustness to the problems in FIA data such as non-Gaussian distributions, nonlinear relationships, outliers and noise in the data. For. Sci. 49(4):619–631.
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This paper presents a generalization of the perception learning procedure for learning the correct sets of connections for arbitrary networks. The rule, falled the generalized delta rule, is a simple scheme for implementing a gradient descent method for finding weights that minimize the sum squared error of the sytem's performance. The major theoretical contribution of the work is the procedure called error propagation, whereby the gradient can be determined by individual units of the network based only on locally available information. The major empirical contribution of the work is to show that the problem of local minima not serious in this application of gradient descent. Keywords: Learning; networks; Perceptrons; Adaptive systems; Learning machines; and Back propagation