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A fuzzy logic method to assess the relationship between landscape patterns and bird richness of the Rolling Pampas
Authors
A Cerezo
A Goijman
+64 more
A Salski
A Schmida
A Soriano
AB Bennett
AC Weibull
AM Cingolani
AM Liebhold
AM Schrag
AS Giacomo Di
B Center
C Kampichler
Claudio M. Ghersa
CM Ghersa
CM Ghersa
D Dubois
D Rocchini
DFB Flynn
DG Mayer
DO Ferraro
EA Beever
ED Concepción
Federico Weyland
H Azadi
H Li
H Li
I Roschewitz
IS Zonneveld
J Bengtsson
J Dauber
J Filloy
J Wu
Jacques Baudry
JAG Jaeger
JL Dickinson
JP Guerschman
JSR Jang
K Yamada
KA With
L Fahrig
LA Zadeh
LA Zadeh
M Codesido
M Liu
MG Turner
MI Goldstein
MJ Ducey
P Batáry
P Legendre
PA Matson
Q Chen
S Kragten
SA Cushman
SA Levin
T Prato
T Tscharntke
TG Benton
TR Seastedt
VM Comparatore
VR Cueto
W Leekwijck Van
W Pedrycz
X Li
Y Lu
YA Phillis
Publication date
1 January 2012
Publisher
'Springer Science and Business Media LLC'
Doi
Abstract
The loss of biodiversity in productive ecosystems is a global concern of the last decades. The Rolling Pampas of Argentina is an intensively cropped region that underwent important land use and landscape change, with different impacts on biodiversity of both plants and animals. Land use type and habitat complexity are hypothesized to be the most important factors determining species richness in agro-ecosystems. But it is not easy to define these attributes in an unambiguous fashion, or determine their interactions at different spatial scales. A fuzzy logic approach allows overcoming some of these problems by using linguistic variables and logic rules to relate them and formulate hypothesis. We constructed fuzzy logic models to study how bird species richness in the Rolling Pampas is related to land use and habitat complexity, and how these variables interact at two spatial scales. Results showed that at the local scale, landscape complexity is the most important factor determining species numbers; trees and bodies of water are the most influential complexities. The effect of local scale landscape attributes was modified depending on the context at broader scales, so that agricultural sites were enriched when surrounded by more favorable landscapes. There was a high dispersion in the predicted/observed value relationship, indicating that landscape factors interact in more complex ways than those captured by the models we used. We suggest that the fuzzy logic approach is suitable for working with biological systems, and we discuss the advantages and disadvantages of its use. © 2012 Springer Science+Business Media B.V.Fil: Weyland, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía; ArgentinaFil: Baudry, Jacques. Institut National de la Recherche Agronomique; FranciaFil: Ghersa, Claudio Marco. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía; Argentin
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