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Hindawi Publishing Corporation International Journal of Zoology Volume 2012, Article ID 475071, 5 pages doi:10.1155/2012/475071 Research Article 1 2 1 3 1 Marco Ferretti, Marco Foi, Gisella Paci, Walter Tosi, and Marco Bagliacca Department of Animal Production, University of Pisa, Viale delle Piagge 2, 56100 Pisa, Italy Department of the Earth Science, University of Milan, Via Mangiagalli 34, 20133 Milan, Italy Geographic Information System Oﬃce, Province of Pistoia, Corso Gramsci 110, 51100 Pistoia, Italy Correspondence should be addressed to Marco Ferretti, firstname.lastname@example.org Received 1 October 2012; Revised 5 December 2012; Accepted 6 December 2012 Academic Editor: Hynek Burda Copyright © 2012 Marco Ferretti et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The aim of the study was to test Appennino, a tool used to evaluate the habitats of animals through compositional analysis. This free tool calculates an animal’s habitat use within the GIS platform for ArcGIS and saves and exports the results of the comparative land uses to other statistical software. Visual Basic for Application programming language was employed to prepare the ESRI ArcGIS 9.x utility. The tool was tested on a dataset of 546 pheasant positions obtained from a study carried out in Tuscany (Italy). The tool automatically gave the same results as the results obtained by calculating the surfaces in ESRI ArcGIS, exporting the data from the ArcGIS, then using a commercial spreadsheet and/or statistical software to calculate the animal’s habitat use with a considerable reduction in time. 1. Introduction and transpose hundreds to thousands of positions (ﬁxes) for each animal onto digital maps. Managing this dataset Wildlife management studies identify the resources (e.g., manually is complex and susceptible to errors by the use of food items or habitats) used by animals and document their simple spreadsheets; therefore, we produced a freely available availability. Resource availability is deﬁned as the quantity tool, Appennino, that is completely operable within the accessible to the animal or populations of animals and GIS suite (ArcGIS) to calculate the animal’s preferences by is distinguished from abundance, which is deﬁned as the using compositional analysis. We decided to make the tool resources in the environment . Resource usage is the for “ArcGIS” since most game managers use this particular “quantity” taken by an animal or population of animals. program for GIS management. However, it should be Resources may be consumed, in the case of food items, or stressed that we do not have any direct ﬁnancial relationship simply visited, in the case of habitats . A wide variety with ESRI, the producers of ArcGIS. of methods are available to study animal resource selection . One such method is compositional analysis, which is 2. Materials and Methods often used to analyze habitat preference [4, 5]. It studies the animal’s preference both in terms of “home range” and Thetoolwas ﬁrst codedinVisualBasic forApplication “ﬁx” (single positions within the home range). At present, (VBA) directly using the facilities provided by the ESRI positions and surfaces calculated in GIS programs must ArcGIS environment [9, 10]. Thetoolwas basedoncompo- be exported to other free or commercial software such as sitional analysis [3, 11, 12]. spreadsheets (LibreOﬃceCalc, OpenOﬃce, Microsoft-Excel, Appennino can be downloaded, free of charge, from and so on), general statistical programs (R Project for http://biblio.unipi.it/content/servizio-bibliotecario/risorse- Statistical Computing, JMP, SPSS, and so on), or speciﬁc web or http://www.marcoferretti.altervista.org/index ﬁle/ programs (Compos Analysis v.6.3-Smith ecology, Biotas- Page419.htm or http://bagliacca.altervista.org/GIStool.html. Ecological Software Solutions LCC). The tool needs at least four “shapes”: the land use polygon The development of VHF- and GPS-radio collars to layer, the home range polygon shape of every individual track animal movements [6–8] led to the need to store animal, the land use circular random plots, and the ﬁx layer 2 International Journal of Zoology Forms where user chooses the TOC layer for the analysis Creation of temporary directories with the copy of the original layers Study areas layer Home ranges layer Land use layer for for analysis for analysis analysis purposes purposes purposes Intersect between the home ranges and the land use Intersect between the study area and the use of the land + dissolve for the identiﬁcation of the animal + dissolve for the land use typology + splite for the identiﬁcation of the animal Land use layer only A layer for each for the individual animal study area Join between the individual table of each animal and the table of land use. Updating of the tables of each animal Creation of the empty matrix layer Append of individual tables to the matrix. Calculation of the various matrix ﬁelds Forms where we ask the user to choose whether to continue the analysis in ARC GIS environment and to make one-way ANOVA or to export the matrix in txt or dbf format ﬁle Figure 1: Flow chart of the ﬁrst step of the tool. of the animals. The tool works both on home range and ﬁx o , o , ..., o ,where o is the estimated proportion of the u1 u2 uD ui analyses. i type resource used by the individual. The proportions sum The tool works as follows. It assumes there are D types to one. Similarly, the analysis sets the available proportions of resource units available, and that the individual animal’s for the same animals as π , π , ..., π . The analysis a1 a2 aD proportional resource usage is described by the composition cannot be applied when resources units are described by International Journal of Zoology 3 Production of a new table The tool transforms the matrix into table with a land use code values in each ﬁeld Populate a two-dimensional array Perform the one-way ANOVA analysis Table with mean and Analysis of variance standard deviation Box-plot graph table values Figure 2: Flow chart of the second step of the tool. continuous variables, unless they are expressed as discrete and 2009 on a group of pheasants (Phasianus colchicus) classes. The log-ratio transformation y = log (o /o ) released in a protected area (PA) near Florence (Tuscany, i ui uj is calculated for any component o .The diﬀerences i = Italy, Figure 3)[6, 16] at the end of the two steps. log (o /o ) − log (π /π ) are then calculated for the ith ui uj ai aj The Appennino tool is completely operable within the e e animal to represent the diﬀerence between the relative use ArcGIS suite to evaluate animal preferences by compositional and availability of resources i and j. Problems related to the analysis. This enables it to be maintained within the GIS sampling level [13–15] are avoided, since the animal is used software and avoids having to export the database to any as the unit of observation, so that data independence and external statistical software, while producing the same results multivariate normality are ensured. With no selection, the as other statistical software. mean value of d is expected to be zero for all i. Generally speaking, in software applications when there are zero values, 4. Conclusions land use cannot be calculated and an error message is generated. Our tool avoids the problem by replacing zero We have presented Appennino as a tool that automatically values with a value corresponding to 1% of the smallest gives the complete matrix of the compositional analysis, value observed, although the substitution of zero values with which can then be exported in other statistical software pack- arbitrary constants has led to some criticism of the method ages for further statistical analysis. Our tool thus prevents . The tool works through a two-step process. In the ﬁrst calculation errors with high quantities of data and is also easy step, the deﬁnition of the analysis matrix is derived from to use. In addition, Appennino performs basic statistics of primary data (this data array can be exported in “.txt” or the data set, is free of charge, and can be downloaded with “.dbf” ﬁle format to be used in other statistical software). the VBA source code for further improvements. In the second step, an ANOVA test can be run directly on the newly created matrix, without leaving the ArcGIS environment. Acknowledgments Figures 1 and 2 show how the program works. The authors would like to thank Daniel S. Soper, PhD. Assistant Professor Department of Information Systems and 3. Results and Discussion Decision Sciences Mihaylo College of Business and Eco- nomics California State University Fullerton and Provincia Figures 4 and 5 show the ﬁnal output of the tool when it was applied to data from a study carried out between 2008 di Pistoia and Ambito Territoriale di Caccia Firenze 5 for 4 International Journal of Zoology N N ( (met mete ers rs) ) 0 0 250 250 500 500 1000 1000 Availability plots Olive orchards Home ranges Spring crops-for-game Land use Fall crops-for-game Mediterranean wood Grasses and pastures Shrub land Urban areas Fallow land Rivers and ponds Vineyards Figure 3: Land use polygon layer with the home range polygon shape of each individual animal and the land use circular plots generated with the Hawth tool (http://www.spatialecology.com/htools/), from the ArcGIS table of contents. Note: the land use layer, performed for clarity, is not required by the tool. With this set of data, 50 random circular plots of the average home range size of the birds in the case study (110 m) were chosen across the study area. Figure 4: Analysis of variance table. Figure 5: Box-plot graph of the land uses. Note: with this data set, the land uses which give maximum values of occurrence are “Spring crops-for-game” and “Fall crops-for-game.” The land uses which give the least uses are the “Rivers and ponds” and “Urban areas” (P< 0.05). International Journal of Zoology 5 their cooperation. The authors of the paper do not have any ﬁnancial association with ESRI, the producers of the program mentioned in the paper. References  J.R.Alldredge,D.L.Thomas, andL.L.Mcdonald, “Survey and comparison of methods for study of resource selection,” Journal of Agricultural, Biological, and Environmental Statistics, vol. 3, no. 3, pp. 237–253, 1998.  B. F. J. Manly, “Comments on design and analysis of multiple- choice feeding-preference experiments,” Oecologia, vol. 93, no. 1, pp. 149–152, 1993.  B.F.J.Manly,L.L.McDonald, D. L. Thomas,T.L.McDonald, andW.P.Erickson, Resource Selection By Animals: Statistical Design and Analysis For Field Studies,KluwerAcademic Publishers, Boston, Mass, USA, 2nd edition, 2002.  T.M.Fearer andD.F.Stauﬀer, “Relationship of ruﬀed grouse Bonasa umbellus to landscape characteristics in southwest Virginia, USA,” Wildlife Biology, vol. 10, no. 2, pp. 81–89, 2004.  M. Ferretti, G. Paci, S. Porrini, L. Galardi, and M. Bagliacca, “Habitat use and home range traits of resident and relocated hares [Lepus europaeus, Pallas),” Italian Journal of Animal Science, vol. 9, no. 3, pp. 278–284, 2010.  M. Ferretti, F. Falcini, G. Paci, and M. Bagliacca, “Captive rearing technologies and survival of pheasants (Phasianus colchicus L.),” Italian Journal of Animal Science, vol. 11, no. e2, pp. 160–164, 2012.  B. 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Published: Dec 25, 2012
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