R. Hijmans, S. Cameron, J. Parra, P. Jones, and A. Jarvis, Very high resolution interpolated climate surfaces for global land areas, International Journal of Climatology, vol.18, issue.15, pp.1965-1978, 2005.
DOI : 10.1002/joc.1276

E. Mcintire and A. Fajardo, Beyond description: the active and effective way to infer processes from spatial patterns, Ecology, vol.63, issue.1, pp.46-56, 2009.
DOI : 10.1111/j.0030-1299.2004.12497.x

J. Franklin and J. Miller, Mapping species distributions: spatial inference and prediction. Cambridge, 2009.
DOI : 10.1017/CBO9780511810602

S. Hay, S. Randolph, and D. Rogers, Remote Sensing and Geographical Information Systems in Epidemiology, 2000.

R. Haining, Spatial data analysis in the social and environmental sciences, Cambridge England, vol.409, 1990.
DOI : 10.1017/CBO9780511623356

C. Gaucherel, S. Alleaume, and C. Hely, The Comparison Map Profile Method: A Strategy for Multiscale Comparison of Quantitative and Qualitative Images, IEEE Transactions on Geoscience and Remote Sensing, vol.46, issue.9, pp.2708-2719, 2008.
DOI : 10.1109/TGRS.2008.919379

N. Raes and H. Ter-steege, A null-model for significance testing of presence-only species distribution models, Ecography, vol.11, issue.5, pp.727-736, 2007.
DOI : 10.1111/j.2007.0906-7590.05041.x

S. Roxburgh and M. Matsuki, The Statistical Validation of Null Models Used in Spatial Association Analyses, Oikos, vol.85, issue.1, pp.68-78, 1999.
DOI : 10.2307/3546792

W. Tobler, A Computer Movie Simulating Urban Growth in the Detroit Region, Supplement: Proceedings. International Geographical Union. Commission on Quantitative Methods, pp.234-240, 1970.
DOI : 10.2307/143141

S. Hurlbert, Pseudoreplication and the Design of Ecological Field Experiments, Ecological Monographs, vol.54, issue.2, pp.187-211, 1984.
DOI : 10.2307/1942661

J. Miller, J. Franklin, and R. Aspinall, Incorporating spatial dependence in predictive vegetation models, Ecological Modelling, vol.202, issue.3-4, pp.225-242, 2007.
DOI : 10.1016/j.ecolmodel.2006.12.012

J. Lennon, Red-shifts and red herrings in geographical ecology, Ecography, vol.335, issue.1, pp.101-113, 2000.
DOI : 10.1111/j.1600-0587.2000.tb00265.x

R. Bivand, A Monte Carlo study of correlation coefficient estimation with spatially autocorrelated observations, Quaestiones Geographicae, vol.6, pp.5-10, 1980.

C. Dormann, J. Mcpherson, M. Araujo, R. Bivand, and J. Bolliger, Response to Comment on ???Methods to account for spatial autocorrelation in the analysis of species distributional data: a review???, Ecography, vol.4, issue.3, pp.609-628, 2007.
DOI : 10.1111/j.1600-0587.2009.05907.x

M. Fadili and E. Bullmore, Wavelet-Generalized Least Squares: A New BLU Estimator of Linear Regression Models with 1/f Errors, NeuroImage, vol.15, issue.1, pp.217-232, 2002.
DOI : 10.1006/nimg.2001.0955

G. Carl, C. Dormann, and I. Kühn, A wavelet-based method to remove spatial autocorrelation in the analysis of species distributional data, Web Ecology, vol.8, issue.1, pp.22-29, 2008.
DOI : 10.5194/we-8-22-2008-supplement

N. Barbier, P. Couteron, O. Planchon, and A. Diouf, Multiscale comparison of spatial patterns using two-dimensional cross-spectral analysis: application to a semi-arid (gapped) landscape, Landscape Ecology, vol.20, issue.6, pp.889-902, 2010.
DOI : 10.1007/s10980-010-9466-1

URL : https://hal.archives-ouvertes.fr/halsde-00564564

M. Detto, A. Molini, G. Katul, P. Stoy, and S. Palmroth, Causality and Persistence in Ecological Systems: A Nonparametric Spectral Granger Causality Approach, The American Naturalist, vol.179, issue.4, pp.524-535, 2012.
DOI : 10.1086/664628

T. Keitt and D. Urban, SCALE-SPECIFIC INFERENCE USING WAVELETS, Ecology, vol.86, issue.9, pp.2497-2504, 2005.
DOI : 10.1890/02-0738

URL : http://dx.doi.org/10.6084/M9.FIGSHARE.C.3298760

N. Kingsbury, A dual-tree complex wavelet transform with improved orthogonality and symmetry properties, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), pp.375-378, 2000.
DOI : 10.1109/ICIP.2000.899397

N. Kingsbury, The dual-tree complex wavelet transform: a new technique for shift invariance and directional filters, 1998.

B. Manly, Randomization, bootstrap, and Monte Carlo methods in biology, Boca Raton, vol.455, 2007.

T. Schreiber and A. Schmitz, Surrogate time series, Physica D: Nonlinear Phenomena, vol.142, issue.3-4, pp.346-382, 2000.
DOI : 10.1016/S0167-2789(00)00043-9

N. Gotelli and G. Graves, Null models in ecology, 1996.

H. Lotwick and B. Silverman, Methods for Analysing Spatial Processes of Several Types of Points, Journal of the Royal Statistical Society Series B (Methodological), vol.44, pp.406-413, 1982.

M. Palmer and E. Van-der-maarel, Variance in Species Richness, Species Association, and Niche Limitation, Oikos, vol.73, issue.2, pp.203-213, 1995.
DOI : 10.2307/3545909

T. Keitt, Spectral representation of neutral landscapes, Landscape Ecology, vol.15, issue.5, pp.479-493, 2000.
DOI : 10.1023/A:1008193015770

I. Rodríguez-iturbe and R. A. , Fractal river basins : chance and selforganization . Cambridge, 1997.

B. Rabus, M. Eineder, A. Roth, and R. Bamler, The shuttle radar topography mission???a new class of digital elevation models acquired by spaceborne radar, ISPRS Journal of Photogrammetry and Remote Sensing, vol.57, issue.4, pp.241-262, 2003.
DOI : 10.1016/S0924-2716(02)00124-7

S. Prince and S. Goward, Global Primary Production: A Remote Sensing Approach, Journal of Biogeography, vol.22, issue.4/5, pp.815-835, 1995.
DOI : 10.2307/2845983

A. Cerioli, Modified Tests of Independence in 2 x 2 Tables with Spatial Data, Biometrics, vol.53, issue.2, pp.619-628, 1997.
DOI : 10.2307/2533962

A. Cerioli, Testing Mutual Independence Between Two Discrete-Valued Spatial Processes: A Correction to Pearson Chi-Squared, Biometrics, vol.89, issue.4, pp.888-897, 2002.
DOI : 10.1111/j.0006-341X.2002.00888.x

C. Liu, M. White, and G. Newell, Measuring and comparing the accuracy of species distribution models with presence-absence data, Ecography, vol.19, issue.2, pp.232-243, 2011.
DOI : 10.1111/j.1600-0587.2010.06354.x

M. Araújo, R. Pearson, W. Thuiller, and E. M. , Validation of species-climate impact models under climate change, Global Change Biology, vol.430, issue.9, pp.1504-1513, 2005.
DOI : 10.1111/j.0906-7590.2004.03673.x

B. Merckx, M. Steyaert, A. Vanreusel, M. Vincx, and J. Vanaverbeke, Null models reveal preferential sampling, spatial autocorrelation and overfitting in habitat suitability modelling, Ecological Modelling, vol.222, issue.3, pp.588-597, 2011.
DOI : 10.1016/j.ecolmodel.2010.11.016

I. Parmentier, R. Harrigan, W. Buermann, E. Mitchard, and S. Saatchi, Predicting alpha diversity of African rain forests: models based on climate and satellite-derived data do not perform better than a purely spatial model, Journal of Biogeography, vol.130, issue.6, pp.1164-1176, 2011.
DOI : 10.1111/j.1365-2699.2010.02467.x

R. Anderson, M. Gomez-laverde, and A. Peterson, Geographical distributions of spiny pocket mice in South America: insights from predictive models, Global Ecology and Biogeography, vol.4, issue.2, pp.131-141, 2002.
DOI : 10.1080/136588199241391

S. Dolédec, D. Chessel, and C. Gimaret-carpentier, NICHE SEPARATION IN COMMUNITY ANALYSIS: A NEW METHOD, Ecology, vol.81, issue.10, pp.2914-2927, 2000.
DOI : 10.1086/282837

R. Pearson, C. Raxworthy, M. Nakamura, and A. Peterson, ORIGINAL ARTICLE: Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar, Journal of Biogeography, vol.157, issue.1, pp.102-117, 2007.
DOI : 10.1111/j.1365-2699.2006.01594.x

A. Lobo, K. Moloney, O. Chic, and N. Chiariello, Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data, Landscape Ecology, vol.13, issue.2, pp.111-131, 1998.
DOI : 10.1023/A:1007938526886

E. Pardo-igúzquiza and M. Chica-olmo, The Fourier Integral Method: An efficient spectral method for simulation of random fields, Mathematical Geology, vol.25, issue.2, pp.177-217, 1993.
DOI : 10.1007/BF00893272

J. Rayner, An introduction to spectral analysis. London: Pion, 1971.

T. Schreiber and A. Schmitz, Improved Surrogate Data for Nonlinearity Tests, Physical Review Letters, vol.77, issue.4, pp.635-638, 1996.
DOI : 10.1103/PhysRevLett.77.635

C. Keylock, A wavelet-based method for surrogate data generation, Physica D: Nonlinear Phenomena, vol.225, issue.2, pp.219-228, 2007.
DOI : 10.1016/j.physd.2006.10.012

M. Palu?, Bootstrapping Multifractals: Surrogate Data from Random Cascades on Wavelet Dyadic Trees, Physical Review Letters, vol.101, issue.13, 2008.
DOI : 10.1103/PhysRevLett.101.134101

M. Breakspear, M. Brammer, and P. Robinson, Construction of multivariate surrogate sets from nonlinear data using the wavelet transform, Physica D: Nonlinear Phenomena, vol.182, issue.1-2, pp.1-22, 2003.
DOI : 10.1016/S0167-2789(03)00136-2

I. Selesnick, R. Baraniuk, and N. Kingsbury, The dual-tree complex wavelet transform, IEEE Signal Processing Magazine, vol.22, issue.6, pp.123-151, 2005.
DOI : 10.1109/MSP.2005.1550194

P. De-rivaz, Complex wavelet based image analysis and synthesis. Cambridge: University of Cambridge, 2000.

N. Kingsbury, Complex Wavelets for Shift Invariant Analysis and Filtering of Signals, Applied and Computational Harmonic Analysis, vol.10, issue.3, pp.234-253, 2001.
DOI : 10.1006/acha.2000.0343

B. Mandelbrot, V. Ness, and J. , Fractional Brownian Motions, Fractional Noises and Applications, SIAM Review, vol.10, issue.4, pp.422-437, 1968.
DOI : 10.1137/1010093

D. Saupe, Random Fractals in Image Synthesis, Fractals and chaos, pp.89-118, 1991.
DOI : 10.1007/978-1-4612-3034-2_6

L. Kaplan and C. Kuo, An improved method for 2-D self-similar image synthesis, IEEE Transactions on Image Processing, vol.5, issue.5, pp.754-761, 1996.
DOI : 10.1109/83.495958

S. Hoefer, H. Hannachi, M. Pandit, and R. Kumaresan, Isotropic twodimensional Fractional Brownian Motion and its application in Ultrasonic analysis, 14th Annual International Conference of the IEEE, pp.1267-1269, 1992.