Comparison of interpolation methods for mapping climatic and bioclimatic variables at regional scale

Attorre, Fabio; Alfó, Marco; Sanctis, Michele De; Francesconi, Fabio; Bruno, F.

doi:10.1002/joc.1495

Cited by 158 publications

(102 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Climatic indicators were calculated as long-term averages of total monthly (and annual) precipitation and (mean, minimum, and maximum) temperature. Temperature and rainfall data were uploaded to ArcGis 9.2 and then spatialized using an ordinary kriging interpolation (Goovaerts 2000;Attorre et al 2007). …”

Section: Climatementioning

confidence: 99%

Combining Environmental Factors and Agriculturalists’ Observations of Environmental Changes in the Traditional Terrace System of the Amalfi Coast (Southern Italy)

Savo

Caneva

McClatchey

et al. 2013

AMBIO

View full text Add to dashboard Cite

Terraces are traditional engineered ecosystems that affect the hydro-geological equilibrium, slope stability, and local communities. The aims of this paper are (i) identifying environmental factors that affect terrace stability in the Amalfi Coast, (ii) defining agriculturalists' observations on environmental changes within that system and (iii) exploring potentiality of these observations to better define conservation strategies. All available data on physical and ecological factors recognized to affect the terrace system were collected and analyzed. Interviews were conducted with agriculturalists to obtain long-term observations on environmental factors that interact with this system. Landslides are more frequent where rainfall is high and during winter. Fires have an uneven annual distribution, with higher frequency during summers. Agriculturalists detailed complex interactions among environmental factors, economic elements, and terraces. These observations represent a valuable resource for defining causes and effects of abandonment and for better addressing conservation strategies.

show abstract

Section: Climatementioning

confidence: 99%

Combining Environmental Factors and Agriculturalists’ Observations of Environmental Changes in the Traditional Terrace System of the Amalfi Coast (Southern Italy)

Savo

Caneva

McClatchey

et al. 2013

AMBIO

View full text Add to dashboard Cite

show abstract

“…Very high resolution (30 arc-seconds) cur rent climatic surfaces were obtained by inter polating climatic data (average of the 1961-1991 period) from 210 stations for pre cipitation and 151 for temperature through universal kriging (i.e., simple kriging with trend function defined on the basis of a set of co-variates) that has been proven to produce reliable estimates at a regional scale (Attorre et al 2007). Future projections for 2080 (midpoint of the period 2070-2099) were de rived using one general circulation model experiment (HadCM3 - Mitchell et al 2004).…”

Section: Environmental Variablesmentioning

confidence: 99%

Predicting the effect of climate change on tree species abundance and distribution at a regional scale

Attorre¹,

Francesconi²,

Scarnati³

et al. 2008

iForest

View full text Add to dashboard Cite

The elaboration of conservation strategies at regional scale, dealing with the potential effects of climate change on the abundance and distribution of tree species, should be supported by models produced at the appropriate scale. We used a bioclimatic model aimed at analysing the large-scale effects of climate change on the abundance and distribution of tree species with respect to their chorological and ecological characteristics. Abundance data for 16 species, sampled in 912 plots, distributed on a 3x3 km grid were used. A climatic model provided high resolution current climatic surfaces and a climatic scenario for 2080 was obtained using the A1FI emission scenario of HadCM3 GCM. A determ inistic Regression Tree Analysis (RTA) and Multiple Linear Regression (MLR) were applied in order to define the realised niche of the species in relation to the chosen environmental variables. The comparison between RMSE values showed that RTA always outperforms MLR, in terms of predicting species distri bution. Zonal species were better predicted than rare species (extrazonal or with specific habitat requirements). Climate change is expected to determine a general increase of the average potential altitude. Only the Mediterranean spe cies are likely to be favoured by the predicted climate change, while for the two other chorological types (Sub-Mediterranean and Eurosiberian) the re sponse seems to be species-specific, depending on the ecological characteristic of each species: the more thermophilous and xerophilous species should bene fit from the predicted drought in terms of area and mean abundance, while mesophilous species should suffer a strong reduction.Keywords: Climate change, Tree species, Central Italy, Potential distribution maps, Regional scale, Regression tree analysis cording to the following formula:where x is one of the considered species, NS is the number of stems of a plot and BA is the basal area of the plot calculated using the diameter at breast height of each one of the stems. In monotypic stands, the IV could reach a maximum of 200. We analysed sixteen species that are the most abundant in the study area: (see Tab. 2 -Pignatti 1982). In order to explain the response of the species to climate change, Ellenberg's indicator val ues (Ellenberg et al. 1992), revised for Italy by Pignatti (2005), for temperature and moisture were used. These indicator values describe the ecological optima for the spe cies along ecological gradients using an or dinal scale, i.e., temperature: 1 (cold, alpine environment) to 12 (hot, subdesertic envir onment); moisture: 1 (dry environment, arid soil) to 12 (water environment). Environmental variablesVery high resolution (30 arc-seconds) cur rent climatic surfaces were obtained by inter polating climatic data (average of the 1961-1991 period) from 210 stations for pre cipitation and 151 for temperature through universal kriging (i.e., simple kriging with trend function defined on the basis of a set of co-variates) that has been proven to produce reliable estimates at a regio...

show abstract

“…As the coordinates are used to characterize general tendencies over a study area, they are usually less applicable for small areas with strong locally determined air temperature fields KRYZA 2009, 2012). In some papers, in addition to coordinates, the index of continentality has also been used (ATTORRE et al 2007;HOGEWIND and BISSOLLI 2011;KRAHEN-MANN et al 2011).…”

Section: Introductionmentioning

confidence: 99%

“…One of the most frequently applied is slope inclination (LENNON and TURNER 1995;SZYMANOWSKI et al 2013); however, its role in physical processes determining air temperature is ambiguous. This variable probably should not stand alone but rather in conjunction with terrain aspect (AGNEW and PALU-TIKOF 2000;ATTORRE et al 2007;HIEBL et al 2009;APAYDIN et al 2011). The role of the relief, particularly associated with the disposal of cooler air from the slopes and a tendency to the accumulation of cold air in concave terrain forms, is expressed in such variables as concavity/convexity, relative height and terrain curvature (NINYEROLA et al 2007;ESTEBAN et al 2009;HIEBL et al 2009;SZYMANOWSKI et al 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Relatively rarely used explanatory variable of air temperature is solar irradiation (VICENTE-SERRANO et al 2003;ATTORRE et al 2007;BENAVIDES et al 2007;ESTEBAN et al 2009;JOLY et al 2011), even if this variable is complex, representing general geographic, atmospheric and astronomic energetic conditions, as well as local influence of terrain height and relief (slope, aspect, and hillshades).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Role of Auxiliary Variables in Deterministic and Deterministic-Stochastic Spatial Models of Air Temperature in Poland

Szymanowski

Kryza

2015

Pure Appl. Geophys.

View full text Add to dashboard Cite

Abstract-Our study examines the role of auxiliary variables in the process of spatial modelling and mapping of climatological elements, with air temperature in Poland used as an example. The multivariable algorithms are the most frequently applied for spatialization of air temperature, and their results in many studies are proved to be better in comparison to those obtained by various onedimensional techniques. In most of the previous studies, two main strategies were used to perform multidimensional spatial interpolation of air temperature. First, it was accepted that all variables significantly correlated with air temperature should be incorporated into the model. Second, it was assumed that the more spatial variation of air temperature was deterministically explained, the better was the quality of spatial interpolation. The main goal of the paper was to examine both above-mentioned assumptions. The analysis was performed using data from 250 meteorological stations and for 69 air temperature cases aggregated on different levels: from daily means to 10-year annual mean. Two cases were considered for detailed analysis. The set of potential auxiliary variables covered 11 environmental predictors of air temperature. Another purpose of the study was to compare the results of interpolation given by various multivariable methods using the same set of explanatory variables. Two regression models: multiple linear (MLR) and geographically weighted (GWR) method, as well as their extensions to the regression-kriging form, MLRK and GWRK, respectively, were examined. Stepwise regression was used to select variables for the individual models and the crossvalidation method was used to validate the results with a special attention paid to statistically significant improvement of the model using the mean absolute error (MAE) criterion. The main results of this study led to rejection of both assumptions considered. Usually, including more than two or three of the most significantly correlated auxiliary variables does not improve the quality of the spatial model. The effects of introduction of certain variables into the model were not climatologically justified and were seen on maps as unexpected and undesired artefacts. The results confirm, in accordance with previous studies, that in the case of air temperature distribution, the spatial process is non-stationary; thus, the local GWR model performs better than the global MLR if they are specified using the same set of auxiliary variables. If only GWR residuals are autocorrelated, the geographically weighted regression-kriging (GWRK) model seems to be optimal for air temperature spatial interpolation.

show abstract

Comparison of interpolation methods for mapping climatic and bioclimatic variables at regional scale

Cited by 158 publications

References 42 publications

Combining Environmental Factors and Agriculturalists’ Observations of Environmental Changes in the Traditional Terrace System of the Amalfi Coast (Southern Italy)

Combining Environmental Factors and Agriculturalists’ Observations of Environmental Changes in the Traditional Terrace System of the Amalfi Coast (Southern Italy)

Predicting the effect of climate change on tree species abundance and distribution at a regional scale

The Role of Auxiliary Variables in Deterministic and Deterministic-Stochastic Spatial Models of Air Temperature in Poland

Contact Info

Product

Resources

About