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

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J.L. Hernández-Stefanoni et al. 2010. Effects of landscape structure and stand age on species richness and biomass 646 structure and spatial dependence had a comparable or even stronger effect on species diversity than stand age. These results are consistent with recent findings in tropical forests showing that long-term monitoring data follow chronosequence patterns for basal area, but not for species density, indicating that stand age largely determines basal area –and biomass, whereas species density seems to be strongly affected by other factors operating at the local and landscape level (Chazdon et al. 2007). Our results also show that, for juveniles, pure spatial dependence appears to be the most important predictor of both species density and biomass. This result could either imply strong dispersal/recruitment limitation, or be due to an environmental component that was not considered, such as topographic or soil variables (Jones et al, 2008). PCNM submodels allowed us to link the spatial distribution of species density and biomass to stand age and landscape structure at different spatial scales. At the very broad scale, stand age contributed most to biomass, and landscape structure to species density. At the broad scale, stand age contributed most to both species density and biomass. Finally, we found a strong negative association between species density and PD and SHAPE_AM, as well as a positive association between species density and edge density (ED). These results may suggest that moderate levels of disturbance may enhance species richness in a forest-dominated landscape. However, high levels of disturbance resulting in a high degree of fragmentation can have a strong negative impact on species richness (Hill and Curran, 2003). References Bellier, E., Monestiez, P., Durbec, J.P. and Candau, J.N. 2007. Identifying spatial relationships at multiple scales: principal coordinate of neighbour matrices (PCNM) and geostatistical approches. Ecography, 30: 385-399. Borcard D, Legendre P, Avois-Jacquet C, Tuomisto H. 2004. Dissecting the spatial structure of ecological data at multiple scales. Ecology 85:1826–1832 Cairns, M.A., Olmsted, I., Granados, J., Argaez, J., 2003. Composition and aboveground tree biomass of a dry semi-evergreen forest on Mexico’s Yucatan Peninsula. Forest. Ecology and Management . 186, 125–132. Campbell, J.B. 1987. Introduction to remote sensing. The Guilford Press. New York. Chazdon, R.L., Letcher, S.G., Breugel, M. van,Martínez-Ramos, M. Bongers, F. and Finegan, B. 2007. Rates of change in tree communities of secondary Neotropical forests following major disturbances. Phil. Trans. R. Soc. B 362: 273-289. Cushman SA, McGarigal K (2004) Patterns in the speciesenvironment relationship depend on both scale and choice of response variables. Oikos 105:117–124. Flores, J.and Espejel, I. 1994. Tipos de vegetación de la Península de Yucatán. Etnoflora Yucatanense, Fascículo 3. México 135 p. Hill J.L., Curran P.J. 2003. Area, shape and isolation of tropical forest fragments: effects on tree species diversity and implications for conservation. Journal of Biogeography 30: 1391- 1403. Hughes, R.F., J.B. Kauffman and V.J. Jaramillo-Luque. 1999. Biomass, carbon, and nutrient dynamics of secondary forests in a humid tropical region of México. Ecology 80:1892- 1907. Jones, MM., Tuomisto, H., Borcard, D, Legendre, P., Clark, DB., and Olivas, PC. 2008. Explaining variation in tropical plant community composition: inXuence of environmental and spatial data quality. Oecologia 155:593–604. Mazerolle M.J., Villard M.A. 1999. Patch characteristics and landscape context as predictor of species presence and abundance: A review. Ecoscience 6(1): 177-124. McGarigal K., Cushman S.A., Neel M.C., Ene E. 2002. FRAGSTATS: spatial pattern analysis for categorical maps. University of Massachusetts. Portillo-Quintero, C.A., Sánchez-Azofeifa, G.A. 2010. Extent and conservation of tropical dry forests in the Americas. Biological Conservation 143 (2010) 144–155. 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.
E. Uuemaa et al. 2010. Spatial gradients of landscape metrics as an indicator of human influence on landscape 647 Spatial gradients of landscape metrics as an indicator of human influence on landscape Evelyn Uuemaa * , Ramon Reimets, Tõnu Oja, Arno Kanal & Ülo Mander Department of Geography, Institute of Ecology and Earth Sciences, University of Tartu, Estonia Abstract Landscape metrics have been widely used for mapping of land cover/use change and analysing relationships between landscape pattern and processes. Natural factors and human activity diversify and homogenize landscape simultaneously. The aim of our study was to analyze the extent and magnitude of human influence on landscape along landscape gradients near main roads. We calculated several landscape metrics for gradients along main roads of Tartu and Tallinn on Estonian Basic Map (1:10 000) from different years (1997/1998 and 2004/2005). We compared the gradients of landscape metrics to determine how the anthropogenic areas have expanded in 10 years and whether the housing and infrastructure tend to expand more quickly on fertile soils. The results showed that the housing has mostly expanded on fields eliminating the possibility to use fertile soils for agriculture or foresting. The pressure on forest areas was not as intense as on agricultural areas. The gradients enable to compare the changes in landscape structure in time and space at the same time. Keywords: spatial gradients, landscape metrics, settlement structure 1. Introduction Changes in landscape are caused by natural and anthropogenic factors. Natural changes occur during a long time, mostly due to climate change. The anthropogenic impact on landscapes is expressed by changes in land use related primarily to changes in the settlement structure. Natural factors and human activity diversify and homogenize landscape simultaneously. Landscape metrics that means all parameters that quantify the spatial pattern of landscape from topographic measures (Vivoni et al. 2005) to proportions of land use/cover, shape and area metrics (Palmer 2004) have been suggested for measuring landscape diversity. These metrics enable to evaluate habitat suitability for animals and birds (Weiers et al. 2004), nutrient fluxes and losses (Uuemaa et al. 2005). Attempts to relate landscape metrics to human perception of a landscape have been made as well (Antrop and Van Eetvelde 2000). Both human activities and those of other biota in landscape may be generalised as landscape consumption (Oja, Prede 2004). Different software has been developed to calculate landscape metrics like FRAGSTATS (McGarigal and Marks 1995) but there are no unambiguously interpretable indicators and there can be found numerous researches on the issue of the use/interpretation of landscape metrics (Wu 2004, Uuemaa et al. 2005, Oja et al. 2005, Uuemaa et al. 2007). * Corresponding author. Tel.: +372 52 27 830 - Fax: +372 7375 825 Email address: evelyn.uuemaa@ut.ee 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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D. S. de Ron et al. 2010. Habitat s
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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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V.D. de Campos & S M. Carvalho 2010
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N.S. Evseeva & Z.N. Kvasnikova 2010
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N.S. Evseeva & Z.N. Kvasnikova 2010
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S. Frank et al. 2010. A regionally
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M. García et al. 2010. The effect
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M. García et al. 2010. The effect
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S. Gholami et al. 2010. Spatial pat
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P. González-Moreno et al. 2010. Th
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T. Höbinger et al. 2010. Impact of
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P. Matos et al. 2010. Can lichen fu
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E.S. Meier et al. 2010. Projections
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E.S. Meier et al. 2010. Projections
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H. Moutahir et al. 2010. Applicatio
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H. Moutahir et al. 2010. Applicatio
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C. Palaghianu 2010. The use of Voro
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F. Peña-Cortés et al. 2010. Spati
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F.M. Rabenilalana et al. 2010. Mult
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A. Ruskule et al. 2010. Patterns of
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E. Sayad 2010. Nitrogen retrancloca
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E. Sayad 2010. Nitrogen retrancloca
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G. Zhelezov 2010. Evaluation of the
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Section 3 Disturbances in changing
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A. Altamirano et al. 2010. Human-ca
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A. Altamirano et al. 2010. Human-ca
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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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J.O. López-Martínez et al. 2010.
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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. Tsibulnikova 2010. Economic esti
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M. Akbarzadeh & E. Kouhgardi 2010.
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J. Beldade & T. Panagopoulos 2010.
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M.L. Leite & J.S.V. Filho2010. Anal
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M.C. Rodrigues et al. 2010. Charact
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S.M. Scheffer & E. Schimanski 2010.
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M. Deconchat et al. 2010. Identific
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J. Gaspar et al. 2010. Visibility a
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K. Koschke et al. 2010. Using a mul
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J.-F. Mas et al. 2010. Assessing
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A. Matos et al. 2010. Economic valu
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A. Migliozzi et al. 2010. Land-use
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M.L Porto et al. 2010. Naturalness
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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. Kouhgardi et al. 2010. Values of
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E. Kouhgardi et al. 2010. Values of
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E. Schimanski 2010. The importance
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L.A.M. da Silva & E. Shimanki 2010.
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Management and conservation of Medi
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D. Geni et al. 2010. A framework fo
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J.M. Rey Benayas 2010. Restoration
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IUFRO Unit 8.01.02 Landscape Ecolog
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