Landscapes Forest and Global Change - ESA - Escola Superior ...

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E.S. Meier et al. 2010. Projections of shifts in species distributions 73 available, one may consider for each species adequate migration assumptions (i.e. “no migration” for mid to late successional species and “unlimited migration” for early successional species), and may have to investigate more intensively the influence on range shifts by smallscale processes limiting species establishment, survival and dispersal, such as biotic interactions (e.g. inter-specific competition, facilitation) or disturbances, which were so far are often ignored in analysis on large-scale species distributions. Improved predictions of potential species distributions under future climates and in novel communities may assist strategies for sustainable forest management. Especially in this domain it is important to dynamically adapt management decisions to on-going climate changes, due to the long life span of trees. Tree life cycles take multiple decades to complete, and the rate at which trees can disperse and migrate, invade and form closed forests in areas that become climatically suitable is even slower. Incorporating such local processes by combining a dynamic model approach with large-scale SDMs will be crucial for a better understanding of how tree species interact in a changing climate. This is key to produce more accurate and detailed predictions of tree responses to climate change as are required by forest-management. References Bertness, M. D. & R. Callaway (1994) Positive interactions in communities. Trends in Ecology & Evolution, 9, 191-193. Brooker, R. W., J. M. J. Travis, E. J. Clark & C. Dytham (2007) Modelling species' range shifts in a changing climate: The impacts of biotic interactions, dispersal distance and the rate of climate change. Journal of Theoretical Biology, 245, 59-65. Caplat, P., M. Anand & C. Bauch (2008) Interactions between climate change, competition, dispersal, and disturbances in a tree migration model. Theor Ecol, 209–220. Davis, M. B. & R. G. Shaw (2001) Range shifts and adaptive responses to Quaternary climate change. Science, 292, 673-679. Etterson, J. R. & R. G. Shaw (2001) Constraint to adaptive evolution in response to global warming. Science, 294, 151-154. Higgins, S. I., J. S. Clark, R. Nathan, T. Hovestadt, F. Schurr, J. M. V. Fragoso, M. R. Aguiar, E. Ribbens & S. Lavorel (2003) Forecasting plant migration rates: managing uncertainty for risk assessment. Journal of Ecology, 91, 341-347. Iverson, L. R., M. W. Schwartz & A. M. Prasad (2004) How fast and far might tree species migrate in the eastern United States due to climate change Global Ecology and Biogeography, 13, 209-219. Lischke, H., N. E. Zimmermann, J. Bolliger, S. Rickebusch & T. J. Loffler. 2004. TreeMig: A forest-landscape model for simulating spatio-temporal patterns from stand to landscape scale. In International Conference of the International-Environmental-Modelling-and- Software-Society, 409-420. Osnabruck, GERMANY: Elsevier Science Bv. MacArthur, R. H. 1972. Geographical ecology: patterns in the distribution of species. Parmesan, C. & G. Yohe (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature, 421, 37-42. Root, T. L., J. T. Price, K. R. Hall, S. H. Schneider, C. Rosenzweig & J. A. Pounds (2003) Fingerprints of global warming on wild animals and plants. Nature, 421, 57-60. Solomon, A. M. & A. P. Kirilenko (1997) Climate change and terrestrial biomass: what if trees do not migrate Global Ecology and Biogeography Letters, 6, 139-148. Thuiller, W., M. B. Araújo & S. Lavorel (2004) Do we need land-cover data to model species distributions in Europe Journal of Biogeography, 31, 353-361. Whittaker, R. J., K. J. Willis & R. Field (2001) Scale and species richness: towards a general, hierarchical theory of species diversity. Journal of Biogeography, 28, 453-470. Woodward, F. I. 1987. Climate and plant distribution. Cambridge University Press. London. Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.) 2010, Instituto Politécnico de Bragança, Bragança, Portugal.
H. Moutahir et al. 2010. Application of remote sensing to assess wildfire impact 74 Application of remote sensing to assess the wildfire impact on the natural vegetation recovery and landscape structure in the Mediterranean forest of South eastern Spain H. Moutahir 1* , J.F. Bellot 1 , A.Bonet 1 , M.J. Baeza 2 & I. Touhami 1 1 Departamento de Ecología, Universidad de Alicante, Ap. 99, 03080 Alicante, Spain 2 Fundación CEAM, Parque Tecnológico Paterna, C/Charles Darwin 14, 46980 Valencia, Spain Abstract Forest fires in the Mediterranean zone cause major disturbances in landscape structure especially in the wooded stratum, since the recovery of the initial state of the natural vegetation is a complex and very slow process. This process, depending on many factors, passes through several stages leading to changes in the landscape structure through time. In this research, several Landsat TM and ETM+ images were used to assess the impact of wild fire in the Mediterranean forests of south eastern Spain over the past 25 years. The use of the Normalized Difference Vegetation Index (NDVI) for mapping the burnt zones and indicators of landscape heterogeneity allowed us to analyze the degree of landscape change in these forests caused by the fires. In the majority of the observed zones the natural vegetation did not completely recover over this time period. The alteration in landscape structure and its floristic composition depends on the type of vegetation and its maturity before the fire, topography, microclimates, the climate general, and finally, land use and management. Keywords: Forest fire, Vegetation recovery, Landscape structure, Remote sensing, NDVI 1. Introduction Situated on the Mediterranean coast in the South East of Spain, The Valencian Community is one of the most affected areas by the wildfires. In 1994 a total of 138404 ha of wooded and non wooded area were burnt which represents a third of the burnt area in Spain. Due to their magnitude wildfires are considered one of the most important driving forces determining the current forest landscape in the Mediterranean basin (Naveh 1994) and several authors speak about a homogenization of the landscape after fires. These fires affect landscape patterns which can affect the ecological processes (Turner, 1989). The satellite images thanks to their spatial and temporal resolution allow the assessment of wildfires impact on the landscape. In this way we carry out this research using a several Landsat TM and ETM+ images of a burnt area in the South East of the Valencian Community. * Corresponding author. Tel.: +34 644474238 - Fax: +34 965909832 Email address: hassane_moutahir@yahoo.fr Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.) 2010, Instituto Politécnico de Bragança, Bragança, Portugal.
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Landscapes Forest and Global Change
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The contributions to this volume ha
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Table of contents Foreword Preface
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Fine-scale mapping of High Nature V
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Characterization of a Maculinea alc
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Urban tree inventory and socio-econ
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xiii Foreword Twenty years ago, Dr.
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Section 1 Scaling in landscape anal
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V. Cortes et al. 2010. Environmenta
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B. Bożętka 2010. Recent relations
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S.F. Chen et al. 2010. A physiotope
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T. Curt & J. Pausas 2010. Are chang
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R.A Fleming et al. 2010. Forest man
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R.A Fleming et al. 2010. Forest man
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P.C. Goebel et al. 2010. How import
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L.R. Iverson et al. 2010. Merger of
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T.-C. Lin et al. 2010. Immediate ef
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K. L. Martin & P.C. Goebel 2010. Im
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G.M. Pastur et al. 2010. Indirect e
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E.W Saragih et al. 2010. Effects of
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L.R.P. Williamson et al. 2010. Anth
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N. Zurbriggen et al. 2010. Modeling
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Section 4 Biodiversity conservation
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Akbarzadeh et al. 2010. Ecotourism
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Akbarzadeh et al. 2010. Ecotourism
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C. Carvalho-Santos 2010. Fine-scale
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I. Catalano et al. 2010. Wood macro
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R.A. Diaz-Varela et al. 2010. Exten
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R.A. Diaz-Varela et al. 2010. Asses
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P.A.E. Diogo & J. Aranha 2010. GIS
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P.A.E. Diogo & J. Aranha 2010. GIS
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V. Etemad & N. Avani 2010. Investig
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A.E. Eycott et al. 2010. The impact
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E. Fernández-Núñez et al. 2010.
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N. Fracassi & D. Somma 2010. Partic
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J. Hartter et al. 2010. Fortresses
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M.B. Horta et al. 2010. Landscape S
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Sara Marques et al. 2010. Impact of
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M.G.C. Martins & J. Aranha 2010. El
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J.-F. Mas et al. 2010. Modeling lan
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R.S. Moro & T.K. Pereira 2010. Eval
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R.S. Moro & C.H Rocha 2010. A metho
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M.C.C. Rodrigues et al. 2010. Contr
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M.C. Rodrigues et al. 2010. Charact
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Section 6 Tools of landscape assess
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J.-F. Mas et al. 2010. Assessing
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M.L Porto et al. 2010. Naturalness
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M. Rehor & V. Ondracek 2010. Applic
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J. Russell et al. 2010. Developing
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Section 7 Management and sustainabi
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M. Castro et al. 2010. Relationship
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E. Volkova 2010. The regional analy
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Section 9 Symposia
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Z.L. Urech & J.P. Sorg 2010. Taking
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Measures of landscape structure as
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Network theory to conserve and reco
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Management and conservation of Medi
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P.M. Fernandes et al. 2010. Testing
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E. Andrieu et al. 2010. When forest
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D. Geni et al. 2010. A framework fo
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A. Ouin et al. 2010. Do wooded elem
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IUFRO Unit 8.01.02 Landscape Ecolog
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