Spatiotemporal analysis of olive flowering using geostatistical techniques

Rojo, Jesús; Pérez-Badía, Rosa

doi:10.1016/j.scitotenv.2014.10.022

Cited by 51 publications

(14 citation statements)

References 43 publications

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“…Spatial analyses in aerobiology mainly involve the following: the comparison between two or more different localizations (Stach et al 2008; Puc and Kasprzyk 2013; Sauliene et al 2014); the description of spatial variation of pollen season properties or pollen concentrations (Emberlin et al 2002; Rieux et al 2008; Myszkowska et al 2010; Nowosad et al 2015); or the investigation of pollen transportation using back trajectories (Skjoth et al2008, 2009; Veriankaite et al2009; Rojo and Pérez-Badia 2015). There have been only a few studies in which spatial models of Betula pollen count were built.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula

Nowosad

2015

Int J Biometeorol

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Corylus, Alnus, and Betula trees are among the most important sources of allergic pollen in the temperate zone of the Northern Hemisphere and have a large impact on the quality of life and productivity of allergy sufferers. Therefore, it is important to predict high pollen concentrations, both in time and space. The aim of this study was to create and evaluate spatiotemporal models for predicting high Corylus, Alnus, and Betula pollen concentration levels, based on gridded meteorological data. Aerobiological monitoring was carried out in 11 cities in Poland and gathered, depending on the site, between 2 and 16 years of measurements. According to the first allergy symptoms during exposure, a high pollen count level was established for each taxon. An optimizing probability threshold technique was used for mitigation of the problem of imbalance in the pollen concentration levels. For each taxon, the model was built using a random forest method. The study revealed the possibility of moderately reliable prediction of Corylus and highly reliable prediction of Alnus and Betula high pollen concentration levels, using preprocessed gridded meteorological data. Cumulative growing degree days and potential evaporation proved to be two of the most important predictor variables in the models. The final models predicted not only for single locations but also for continuous areas. Furthermore, the proposed modeling framework could be used to predict high pollen concentrations of Corylus, Alnus, Betula, and other taxa, and in other countries.

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Section: Introductionmentioning

confidence: 99%

Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula

Nowosad

2015

Int J Biometeorol

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“…This reanalysis dataset comprised four parameters from NCEP Parameter Code Table , as well as 93 parameters from NCEP Parameter Code Table 2 (http://rda.ucar.edu/datasets/ds090.0/#metadata/grib.html?_do=y). The meteorological data have a spatial resolution of 1°× 1° (approximately 100 km × 100 km) in latitude and longitude, as used in several studies (Hernández‐Ceballos et al ., , ; Rojo & Pérez‐Badia, ).…”

Section: Methodsmentioning

confidence: 99%

The first record of subtropical insects (Thysanoptera) in central Europe: long‐distance transport of airborne thrips, applying three‐dimensional backward trajectories

Makra

Bodnár

Fülöp

et al. 2017

Agri and Forest Entomology

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1 The present study reports the first occurrence and flight period of three species, namely Scolothrips tenuipennis zur Strassen 1965, Frankliniella schultzei Trybom, 1910 and Zurstrassenia figuratus zur Strassen, 1968, in Hungary. A fourth, undescribed species belonging to the genus Caliothrips was also captured. 2 The distribution area of these species is North Africa and it is hypothesized that they are transported to Hungary via long-distance air currents. 3 Data for a suction trap are examined in South-East Hungary, in the 3-year period 2002-2004 from May to September. A three-dimensional back-trajectory analysis based on the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) transport and dispersion model was performed for the observation days to determine the origin and path of air masses and evaluate of the possibility of long-distance transport of thrips species. 4 Surprisingly, the analysis showed that only a few percent of the back trajectories originated or passed over North Africa. The results suggest that the captured thrips species could survive long-distance transport at low-level trajectories and establish new populations in Western Europe, the eastern part of Europe and Northern Central Europe, which together serve as source areas for the long-range transport of thrips to the target station.

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“…Numerous studies have pointed out the importance of olive yield forecasting of airborne pollen amounts and weather conditions during the months following olive pollination [4,6,7]. However, pollen monitoring of olive groves has other valuable purposes from an agronomic point of view besides predicting olive yield as it allows to study the olive reproductive cycle on large areas of olive orchards as well [8].…”

Section: Introductionmentioning

confidence: 99%

Impact of Climate Change on Olive Crop Production in Italy

et al. 2020

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The effects of climate change on agricultural systems raise important uncertainties about the future productivity and suitability of crops, especially in areas suffering from intense environmental changes. Olive groves occupy Mediterranean areas characterized by seasonal temporary droughts, which cause this cultivation to be highly dependent on local microclimatic conditions. Olive crop production can be reliably estimated using pollen intensity metrics together with post-pollination environmental conditions. In this study, we applied this kind of statistics-based models to identify the most relevant meteorological variables during the post-pollination periods for olive fruit production. Olive pollen time-series for the period of 1999–2012 was analyzed in 16 Italian provinces. Minimum and maximum temperature during spring and summer (March–August) showed a negative relationship with olive production, while precipitation always showed a positive correlation. The increase in aridity conditions observed in areas of Italy during the summer represents an important risk of decreasing olive crop production. The effect of climate change on the olive production trend is not clear because of the interactions between human and environmental factors, although some areas might show an increase in productivity in the near future under different climate change scenarios. However, as more drastic changes in temperature or precipitation take place, the risk to olive production will be considerably greater.

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Spatiotemporal analysis of olive flowering using geostatistical techniques

Cited by 51 publications

References 43 publications

Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula

Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula

The first record of subtropical insects (Thysanoptera) in central Europe: long‐distance transport of airborne thrips, applying three‐dimensional backward trajectories

Impact of Climate Change on Olive Crop Production in Italy

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