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

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M.B. Horta & E. Keizer 2010. Assessment of human and physical factors influencing distribution of vegetation degradation 572 8 FIS 2 1 2 -19.634 2 9 FIS 1 3 2 -19.053 2 10 FIS 2 3 2 0.049 3 11 FAS 3 3 2 20.553 3 12 FAS 3 3 2 32.007 3 13 FAS 1 2 1 -47.215 2 14 FAS 1 1 2 -37.944 2 15 FAS 1 3 1 -30.508 2 16 FAS 1 3 2 -15.294 2 17 FAS 2 3 2 8.456 3 18 FAS 1 3 2 -7.658 2 19 FAS 2 3 2 3.085 3 20 FAS 1 3 2 -3.057 2 21 S 4 0 3 51.892 4 22 S 4 0 3 58.792 4 23 S 4 0 3 58.792 4 24 S 3 0 4 37.400 4 25 S 3 0 4 41.219 4 26 S 4 0 4 64.910 4 27 S 4 0 4 61.092 4 28 S 4 0 4 61.092 4 Table 2: Categorization of sample plots of the savannah and rocky shrublands according to vegetation degradation indicators (Ia – Invasive Species Cover; Id – Bare Soil Cover; Ie – Dead Shrubs Percentage ) Sample Vegetation Degradation Vegetation Degradation Type Ia Id Ie Plots Scores Classes 1 SA 3 2 2 70.965 3 2 SA 3 1 1 62.608 2 3 SA 0 0 3 1.425 1 4 SA 3 0 1 48.332 2 5 SA 2 1 0 30.965 1 6 SA 1 1 2 20.719 2 7 SA 0 2 2 22.127 2 8 SA 2 1 1 34.830 2 9 SA 1 1 1 0.570 1 10 SA 0 1 0 3.640 1 11 SA 0 0 0 0.000 0 12 RS 1 0 1 3.815 1 13 RS 0 0 2 1.083 1 14 RS 0 0 3 1.824 1 15 RS 0 0 0 0.000 0 16 RS 1 2 2 29.471 2 17 RS 1 2 2 36.360 2 18 RS 2 4 2 100.823 4 19 RS 2 4 4 93.542 4 Table 3: Correlation coefficients among human and physical factors and vegetation degradation scores in forest areas (bold entry indicate result significant at ∞ = 0.05) Distance to village/city/ settlement Human Factors Distance to the roads Independent Variables Distance to mining sites Slope % Physical Factors Geology Classes Distances to drainage -0.086 -0.001 -0.021 -0.223 0.072 0.100 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.
M.B. Horta & E. Keizer 2010. Assessment of human and physical factors influencing distribution of vegetation degradation 573 Table 4: Correlation coefficients among human and physical factors and vegetation degradation scores in savannah and rocky shrublands (bold entry indicate result significant at ∞ = 0.05) Independent Variables Distance to agricultural areas 4. Discussion Human Factors Distance to the roads Distance to mining sites Distance to tourist sites Slope % Physical Factors Geology Classes Distances to drainage -0.069 -0.137 -0.056 -0.250 -0.181 -0.061 -0.001 The results of categorization of vegetation in degradation classes showed that the majority of sampled sites were found degraded. The findings have certainly relation with the large amount of damaging activities signs found in the sampled areas. Different authors refer to the contribution of activities such as grazing, cutting and fire to processes of vegetation degradation (Kakembo 2001; Hofstad 1997; De Pietri 1995; Kumar and Bhandari 1992; De Pietri 1992; Talbot 1986). Regarding the fencing system Kumar & Bhandari (1992) found inside a protection site, higher degradation due to free grazing in unfenced areas in relation to the fenced ones. The forest areas presented higher levels of degradation while undisturbed and low degraded situations were found only in the savannah and rocky shrublands. The large availability of resources, especially wood for fuelwood and building materials in the forest areas (Michael Arnold & Dewees 1997), can be a source of major attraction for damaging activities in those areas. In the savannah areas of the EPA the trees are short and occur in low proportion, sparsely distributed through the grass layer, and consequently they do not have the potential for cutting and charcoal production activities, characterized as the highest important disturbance pressure in most of the savannah areas in Brazil (Mistry 2000). Disturbances caused by fire, although can occur in savannah areas in cases of accidental or criminal intensive burning, are not a major problem when that factor is kept in periodical lower frequencies (Coutinho 1990). Since fire is an old component of savannah ecosystems the vegetation has developed resistance and dependency on this factor (Mistry 2000; Coutinho 1990; Rizzini 1979). Perhaps grazing can contribute more to degradation processes in the savannah of the EPA, and the highest level of degradation was found in one plot with presence of grazing marks and livestock. The rocky shrublands are attractive especially for mining activities, but the impacts, although large, are restricted to the mining location. Similarly, the impacts of tourist activity on the rocky shrublands are limited to those areas close to waterfalls and cities. Grazing activities, although evidenced might be limited by the presence of large rock blocks, escarpments and deep holes (Verweij 1995). The results of correlation analysis for the forest areas showed that slope is a significant physical factor influencing the vegetation degradation distribution in the EPA Cachoeira das Andorinhas. The negative association of this factor with forest degradation agrees with Mather (1990). This author argues that slope is a proximate factor that can increase accessibility of humans to forest areas. Verweij (1995) argued that cattle also tend to choose relatively easy walking routes to meet their goals. In the study area, activities of cutting and grazing might be hindered by the slope steepness, with presence of higher degradation levels in the areas with lower slopes. 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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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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V. Núñez et al. 2010. Landscape i
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M. Redon & S. Luque 2010. Tengmalm
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M.C.C. Rodrigues et al. 2010. Contr
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M.C. Silva et al. 2010. Using Busin
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T.N. Terra & R.F dos Santos 2010. L
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E. Tetetla-Rangel et al. 2010. Rela
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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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J.S.V. Filho & M.L. Leite 2010. Sim
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F.J. Gómez et al. 2010. Land use c
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M.L. Leite & J.S.V. Filho2010. Anal
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M.L.Leite & J.S.V. Filho 2010. Iden
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M. Ortega et al. 2010. Monitoring v
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G. Puddu et al. 2010. Landscape tra
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H.R. Ratsimba et al. 2010. Multi-sc
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M.C. Rodrigues et al. 2010. Charact
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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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H. Viana & J. Aranha 2010. Assessin
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H. Viana & J. Aranha 2010. Mapping
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Section 6 Tools of landscape assess
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N. Avani et al. 2010. Investigation
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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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A.M. Geraldes 2010. Landscape runof
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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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I. Silva et al. 2010. Lisbon’s pu
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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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S. Decout et al. 2010. Connectivity
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B. Terrones et al. 2010. Detecting
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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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J.M. Rey Benayas 2010. Restoration
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IUFRO Unit 8.01.02 Landscape Ecolog
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