Temporal analysis of sweet chestnut decline in northeastern Portugal using geostatistical tools

The rising demand for sweet chestnut (Castanea sativa) in Portugal and elsewhere in Europe has led to more intensive management practices to increase nut production. This intensification has potentially increased the widespread of ink and chestnut blight diseases, causing decline in sweet chestnut orchards health and production and limiting the establishment of new planted areas. In this study we estimated chestnut decline along the last twenty years (1986 to 2006) in the northern part of Portugal using 1986, 1995 and 2006 aerial photography to quantify the damage at the tree level within fixed sample plots according to a categorical scale. Mean damage and damage variance in each date, however, were not significantly different. Geostatistical analyses indicated, however, changes in the spatial distribution of damaged and undamaged areas over time. The spread of decline in the region of study was estimated using Kriging based on the spherical model. During the examined period we observed spread of chestnut decline and increasing damage levels in regions where damage is systematically high. The chestnut productive surface in the region has increased in the last twenty years because new plantations exceeded mortality areas. The spatial analyses applied here have made clearer the relations between the spread of chestnut decline and geographical variables.

[1]  D. Krige.  A statistical approach to some basic mine valuation problems on the Witwatersrand, by D.G. Krige, published in the Journal, December 1951 : introduction by the author , 1951 .

[2]  C. Marques,et al.  Assessment of the spread of chestnut ink disease using remote sensing and geostatistical methods , 2007, European Journal of Plant Pathology.

[3]  G. Zentmyer.  Phytophthora cinnamomi and the diseases it causes. , 1980 .

[4]  T. Fonseca,et al.  Soil compaction and chestnut ink disease , 2004 .

[5]  P. Diggle,et al.  Overview of statistical methods for disease mapping and its relationship to cluster detection , 2001 .

[7]  Carlos Marques,et al.  Assessment of the spread of chestnut ink disease from 1995 to 2005 using aerial photography and geostatistical methods , 2009 .

[8]  Ester Portela,et al.  Assessment and Description of Magnesium Deficiencies in Chestnut Groves , 2003 .

[9]  U. Heiniger,et al.  Aerial photographs reveal chestnut-blight foci , 1994 .

[10]  A. W. Warrick,et al.  13 – Spatial Variability of Soil Physical Properties in the Field , 1980 .

[11]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[12]  Claudio Belli,et al.  MONITORING INK DISEASE OF CHESTNUT WITH THE AIRBORNE MULTISPECTRAL SYSTEM A.S.P.I.S. , 2005 .

[13]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[14]  L. M. Martins,et al.  SOILS AND CLIMATIC CHARACTERISTIC OF CHESTNUT STANDS THAT DIFFER ON THE PRESENCE OF THE INK DISEASE , 1999 .

[15]  A. Konopka,et al.  FIELD-SCALE VARIABILITY OF SOIL PROPERTIES IN CENTRAL IOWA SOILS , 1994 .

[16]  Carlos Marques,et al.  Small format aerial photography to assess chestnut ink disease , 2001 .

[17]  Michael Edward Hohn,et al.  An Introduction to Applied Geostatistics: by Edward H. Isaaks and R. Mohan Srivastava, 1989, Oxford University Press, New York, 561 p., ISBN 0-19-505012-6, ISBN 0-19-505013-4 (paperback), $55.00 cloth, $35.00 paper (US) , 1991 .